Abstract:
Polyethylene glycol (PEG) is a low toxicity, stable water-soluble polymer compound, is widely used as auxiliary materials, solvents, additives and modifiers, although its behavior in aqueous solution has been studied through spectroscopy, chromatograph, molecular simmlation and many other experiments, but the study of structures and interactions in PEG/alcohol/water solution is scarce, which has important sigficance for the application of PEG. In this paper, the properties of a series of PEG/2-butoxyethanol (2BE)/water solutions have been studied by measuring dynamic light scattering,resonance light scattering, density and heat capacity. The particle size distribution and resonance light scattering intensity of 2BE/H2O and PEG/2BE/H2O solutions determined by light scattering experiments showed that 2BE content affected the aggregation structures and interactions in solutions, and the addition of PEG molecules destroied and recombined the 2BE/H2O association aggregates and the 2BE self-association aggregates, which increased the sizes of the aggregates. The apparent molar volume of infinite dilution $V_{\varPhi ,PEG}^0$, the interaction parameter SV and the apparent molar heat capacity CΦ,PEG for PEG chain in 2BE/H2O mixed solvents were deduced from density and heat capacity data at 25℃. It was found that $V_{\varPhi ,PEG}^0$ reached the minimum value at the molar fraction of 2BE x2BE=0.0242; SV increased first, then decreased and finally increased again with the increase of x2BE, and changed from the negative to the positive at x2BE =0.0167, and had a positive maximum at x2BE=0.0242; CΦ,PEG decreased with the increase of x2BE, but the decrease became not obvious when x2BE>0.0167. The above characteristic changes of macroscopic thermodynamic variables were consistent with the structuers and interactions in the solutions.
[Abstract](29) [FullText HTML](13) [PDF 4357KB](15)
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To realize automatic leakage detection for infrared gas imaging, we propose an instance segmentation method for gas plumes, which can simultaneously offer leakage detection, plume segmentation, and multi-source detection. To model the anisotropy of plumes in embedding space, different from the existing instance segmentation methods, we employ a new clustering loss function based on the similarity of the probability of two-dimensional Gaussians. The loss function pulls the pixels of the instance together and jointly maximizes the segmentation mask of each plume by learning a bandwidth that is with a slanted elliptical shape. Moreover, to obtain more infrared gas imaging data and avoid the difficulty of manually labeling plume contours, we generate a large synthetic infrared gas imaging data set and train our model on synthetic data. Experimental results show that our method can successfully perform automatic leakage detection on real infrared videos after training on synthetic data. Compared with the state-of-the-art methods, our method can perform plume instance segmentation at a higher speed while maintaining a high accuracy, which is suitable for real-time detection.
[Abstract](116) [FullText HTML](25) [PDF 3508KB](52)
Abstract:
The bromine ion content in the deposit brine of potash production from Indochina Peninsula rock salt mine reaches 2000~3000 mg/L, which is a valuable raw material for bromine production. Effective use of bromine resources associated with rock salt mines is significant to improving the comprehensive utilization of rock salt mines and alleviating the pressure caused by shortage of bromine resources in China, and thus is of great significance to the economy, society and environment. In this paper, a capillary microchannel set-up is built to carry out the research on the separation of bromine from the simulated deposit brine. First, by combining quantum chemical calculations and extraction experiments, n-dodecane was selected as the extractant for bromine due to decent extraction ratio and relatively low bromine loss ratio. Orthogonal experimental design was used to determine the optimal process conditions for the microextraction. And it was found at conditions of temperature 25 ºC, oil-water phase ratio 1, T-type mixer inner through hole diameter 0.25 mm, capillary microchannel inner diameter 0.5 mm, total flow rate 0.1 mL/min, and residence time 70 s, 78.70% of bromine extraction ratio can be achieved.
[Abstract](136) [FullText HTML](38) [PDF 4033KB](37)
Abstract:
Focusing on the accuracy of action recognition task, a model combining both adaptive graph convolution and long short term memory (AAGC-LSTM) is proposed. The model aims to capture the spatial-temporal co-occurrence features of human skeleton motion. It breaks the constraint of using the natural human skeleton as the inherent adjacency matrix in graph convolution and uses combination of adaptive graph convolution and LSTM for the extraction of spatial-temporal co-occurrence-features. In order to capture key nodes’ information of the action recognition task, an attention module is embedded in the model to combine the human skeleton information in a dynamic way. Meanwhile, the primary motion information of skeleton joints and secondary motion information of skeleton edges can be fed to the AAGC-LSTM model separately to form the two branches. The two classification results can be fused to improve the accuracy of recognition. Experiments show that this model achieves 90.1% and 95.6% accuracy on the NTU RGB+D dataset under the Cross Subject and Cross View metric, and achieves 93.6% accuracy on the North Western dataset, which verifies that the model is superior in extracting skeleton motion spatial-temporal features and action recognition task.
[Abstract](67) [FullText HTML](45) [PDF 5811KB](23)
Abstract:
Based on computational particle fluid dynamics (CPFD), an industrial grade polyethylene fluidized bed model in cold state was established to simulate the gas-solid properties of fluidized bed, and the image processing function of MATLAB was used to calculate the bubble size in the fluidized bed by matching the image pixels with the simulated grid. The effects of gas velocity and initial material quantity on the gas-solid flow characteristics of industrial grade polyethylene fluidized bed were studied from the perspectives of fluidized bed flow structure , particles and bubble. The results show that compared with the equipment in pilot and experimental stages, the side-wall effect in the industrial fluidized bed is obviously weak, and the dense-phase zone presents a more uniform particle distribution. The gas velocity has a great influence on the gas-solid flow in the fluidized bed. Under the operating condition of 0.46m/s gas velocity, the particle distribution in the dense-phase zone is the most uniform, and the bulk flow becomes steady. The initial bed height mainly affects the height of the dense phase zone after fluidization, but has little effect on the bed expansion rate.
[Abstract](67) [FullText HTML](20) [PDF 3430KB](14)
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A metal-free catalytic “one-pot” strategy for the facile synthesis of biologically relevant molecular architectures pyrrolo[1,2-a] (iso)quinolines has been developed. Based on our previous studies on the synthesis of indolizines and imidazopyridines, the process is promoted by amine and N-heterocyclic carbene (NHC) relay catalysis via Michael addition-[3+2] cycloaddition of azaarenes and α,β-unsaturated aldehydes. The reactions between azaarenes (1 equiv) and α,β-unsaturated aldehydes (2 equiv) are catalyzed by the amine catalyst (20 mol%) and NHC catalyst (20 mol%) relay catalysis in the presence of 4-dimethylaminopyridine (DMAP) as base (3 equiv) and (diacetoxyiodo)benzene (PIDA) as oxidant (4 equiv) in toluene at room temperature. The first Michael addition step is catalyzed by amine catalyst for 24 h at room temperature to give the Michael addition product. Without any further work-up, then NHC catalyst, DMAP and PIDA are added into the solution for additional 18 h at room temperature. In this step, the cycloaddition and aromatization happen to give pyrrolo[1,2-a] quinoline products. The “one-pot” reactions perform smoothly for various substituted and more conjugated quinolines, including tethered neutral, electron-withdrawing and electron-donating groups at 4, 6, 7-position of quinolines. Ethyl 2-(benzo[f]quinolin-3-yl)acetate also works well to give the quinoline product in 75% yield. The alternation of the α,β-unsaturated aldehyde structures with electron-donating and -withdrawing groups on the phenyl ring work well to give the corresponding quinoline products in moderate to good yields. Moreover, isoquinoline can be tolerated in this reaction to give the corresponding isoquinoline product in good yield (72%). And hetero quinoline-ethyl 2-(quinoxalin-2-yl)acetate works well to afford ethyl 1-formyl-2-phenylpyrrolo[1,2-a]quinoxaline-3-carboxylate in 56% yield.
[Abstract](93) [FullText HTML](34) [PDF 0KB](35)
Abstract:
In the process of zero discharge of high-salt wastewater from coal chemical industry, a small amount of concentrated residual liquid will be produced, the salt content is as high as 20% ~ 30%, and it contains a certain amount of heavy metal ions represented by zinc ions. It is hazardous waste and has high treatment costs. This research carried out the simulation calculation of the occurrence state of zinc ions in the high-salt system, obtained the variation trend of the proportion of various forms of Zn with the pH value, temperature, and NaCl salt concentration, and carried out the actual high-salt organic wastewater system with Na2S as the precipitant. In-depth exploration of removal, optimization of the stirring speed, initial pH value, sodium sulfide dosage and other process conditions, provide theoretical guidance and technical support for the removal of zinc ions in coal chemical high-salt wastewater.
[Abstract](83) [FullText HTML](69) [PDF 0KB](21)
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Filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) is one of the candidate schemes for 5g multicarrier communication system, As with orthogonal frequency division multiplexing (OFDM) and other multicarrier schemes, there is a problem of high peak-to-average power ratio (PAPR), This will affect the efficiency of high power amplifier (HPA). Aiming at the problem that the high PAPR of FBMC/OQAM system, a method based on real valued neural network is proposed. In this method, two real valued neural networks are established at the transmitter and the receiver to reduce PAPR and bit error ratio (BER) respectively. Simulation results show that it is better than dispersive selected mapping (DSLM), clipping , coding and PRnet in PAPR and BER.
[Abstract](213) [FullText HTML](96) [PDF 0KB](71)
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LSTM network can effectively deal with time series and is widely used to analyze stock prices and future trends. However, the important parameters in the LSTM network are usually determined by experience and are highly subjective, or the optimal value cannot be determined due to the influence of calculation cost, which leads to the decrease of the fitting ability of the model. To solve this problem, an improved particle swarm optimization algorithm is proposed to optimize the key parameters of LSTM network, reduce the influence of human factors, and optimize the forecasting process, so as to build a stock price forecasting model with higher forecasting accuracy. In this model, a dynamic multi-swarm particle swarm optimizer is built to improve the performance of PSO algorithm and avoid local optimization. At the same time, aiming at the problem that the high dimension, high noise and data redundancy of stock market data lead to the increase of model training cost and the decrease of prediction performance, the feature selection model was constructed based on a variety of feature selection algorithms to complete the filtering and screening of index features, and a perfect prediction index system was constructed. Experimental results show that the proposed model has higher prediction accuracy and universal applicability in stock price prediction.
[Abstract](63) [FullText HTML](21) [PDF 0KB](12)
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Dipropargyl ether of bisphenols and dichlorosilane were polymerized by Grignard process to obtain silicon-containing propargyl ether of bisphenol A resin (PSPE-A) and silicon-containing propargyl ether of diphenyl ether resin (PSPE-O). The silicon-containing propargyl ether of bisphenol resins (PSPE) were further end capped with diethynyl benzene to obtain the ethynylphenyl-terminated PSPE-A resin (DPSPE-A) and PSPE-O resin (DPSPE-O). The four resins were characterized by proton nuclear magnetic resonance and size exclusion chromatograph. The cure reactions, thermal stability and mechanical properties of the resins were studied as well as the mechanical properties of the quartz fiber cloth (QF) and carbon fiber cloth (T300CF) reinforced resin composites. The results show that synthesized PSPE resins present the high curing temperature. The curing temperature and apparent activation energy of the PSPE resins can be distinctly declined by introducing diethynyl benzene as end capping agent. The viscosity at 110 ℃ of PSPE-A and PSPE-O are stable and lower than 300 mPa s. The viscosity at 110 ℃ of PSPE-O is much lower than that of PSPE-A. The temperature of 5% weight loss (Td5) and residual yield at 800 ℃ (Yr800℃) in N2 of the cured ethynylphenyl-terminated PSPE resin can increase to 486 ℃ and 75%. The glass transition temperature (Tg) of the cured DPSPE is higher than 400 ℃. However, the flexural strength and impact strength of the cured PSPE resin decrease to 28 MPa and 3.27 kJ/m2 after end capped with ethynylphenyl groups. The flexural strength and interlaminar shear strength (ILSS) of the QF/PSPE-A and T300CF/PSPE-A composites are 461 MPa and 35 MPa, 655 MPa and 39 MPa, respectively.
[Abstract](99) [FullText HTML](38) [PDF 4155KB](14)
Abstract:
Certain amounts of sulfide are present in gas field produced water and it brings negative effects on environment and human health, therefore, it is essential to remove sulfide first. Since the electrochemical oxidation method has the advantages of high efficiency without secondary pollution, here we introduced it into the sulfide removal process under the conditions of high salinity and hardness. Based on the cyclic voltammetry characteristics, sulfide removal efficiency, and economic analysis, Ti/RuO2-SnO2-IrO2 was selected as the anode. The removal of sulfide by two-dimensional electrochemical oxidation follows zero-order kinetics, that is, in all reaction stages, residual sulfide concentration in solution has a linear relationship with time. Sulfide exists in the form of HS in the solution. When HS is oxidized, H+ will be released. Therefore, it is necessary to select a suitable initial pH and control the reaction time. The sulfide removal ratio and corresponding energy consumption of simulated gas field produced water with 300 mg/L sulfide and 2.5% NaCl were >99.2% and 55.2 kWh/kg S2−, respectively, with the electrode distance of 5 cm, current density of 200 A/m2, aeration rate of 1 L/min, the initial pH of 9-10, and running time of 35 min. Moreover, reversing cathode and anode was found to effectively solve the problem of scaling on cathode caused by high Ca2+ and Mg2+ concentration.
[Abstract](96) [FullText HTML](39) [PDF 4223KB](17)
Abstract:
Electrospray technology can solve the problems of long membrane formation period, thicker membrane layer and low flux of traditional chitosan nanofiltration membranes. In this study, the NH2-UIO-66(Zr)/chitosan positively charged nanofiltration membrane was successfully prepared by combining the direct membrane-forming properties of chitosan with electrospray technology and introducing metal-organic frameworks (MOFs). This membrane has achieved efficient separation and enrichment of Ni2+. The morphology, structure and properties of membrane were investigated by SEM, EDS, Zeta potential, water contact angle measurements, etc. Studies have shown that compared with the traditional coating process, the permeability of the chitosan composite membrane prepared by the electrospray method is increased by 634% and the membrane can still maintain a good rejection. However, pure chitosan matrix membranes are usually affected by trade-off effect, and it is difficult to further improve the separation performance. The introduction of NH2-UIO-66 (Zr) as a filler can effectively alleviate the trade-off effect. Hybridization improves the hydrophilicity of the separation layer and forms a special membrane surface structure, thereby increasing permeability of composite membrane. Experiments show that the limit of NH2-UiO-66(Zr) loading is 5 wt% (the ratio of MOFs to chitosan). The optimized NH2-UIO-66(Zr)/chitosan membrane has a higher flux than pristine chitosan membrane (increased by 38%). The prepared membrane exhibited a high NiCl2 rejection of 92% and a water permeability of 4.7×10-5 L·m-2·h-1·Pa-1 (test pressure: 4×105 Pa; feed concentration: 0.5 g/L). In addition, the hybrid membrane exhibits excellent mechanical strength and has the potential to separate a single solution of MgCl2, ZnCl2 and Pb(NO3)2.
[Abstract](150) [FullText HTML](68) [PDF 4113KB](20)
Abstract:
Based on the reaction of synthetic ammonia, a three-dimensional multi-component reaction-diffusion model of catalyst particles was established and verified by COMSOL software. The results of model verification show that there is little difference between the multi-component diffusion model and the one-component diffusion model. The inner surface utilization of ammonia catalysts with different shapes was close to each other. In industrial reactors, the calculation of internal diffusion efficiency factor of ammonia synthesis catalyst could be carried out according to the uniform surface area of spheres. Based on the different positions of the reactor, the simulation results of the synthesis ammonia A301 catalyst show that: Temperature, particle size and reaction process are important factors affecting the efficiency of diffusion of catalyst. The diffusion effects of different reaction stages are quite different. At the initial stage of reaction, when the reacting rate and the internal diffusion retardation is large, the efficiency factor of internal diffusion can be improved obviously by reducing the particle size of catalyst. The results show that the efficiency factor is almost linearly negatively correlated to the particle size of catalyst. In the middle and late stage, when the reaction is close to equilibrium, the utilization rate of the inner surface of the catalyst can remain above 0.9, and the internal diffusion is not sensitive to the changes of temperature and particle size at this time. In this case, the catalyst with appropriate large particle size can be selected in reactor in order to reduce the pressure drop of the catalyst bed.
[Abstract](129) [FullText HTML](138) [PDF 0KB](30)
Abstract:
Hydrophobic coatings were prepared in xylene or xylene/ethyl acetate solvent by using 10% and 30% (mass fraction) fluorosilicate modified epoxy resin as the matrix. The influence of fluorosilicon content and solvent type on hydrophobicity as well as micromorphology of the coatings were investigated. The results show that with the increase of fluorosilicon content, the contact angle of the coating enhances. When only using xylene as the solvent, the surface of the coating is relatively smooth, and the maximum contact angle is 105.0°. In xylene/ethyl acetate system, 5~15 µm micropores are formed attributing to the difference of solvent volatilization rate. Meanwhile, 0.1~0.6 µm bumps are generated in those micropores along with phase separation of fluorosilicon and epoxy segments according to nucleation-growth mechanism. The surface energy of coatings reduces with the spontaneous migration of F and Si to the outer surface in the process of film formation. When the content of fluorosilicon segments increases to 30%, much more air could be trapped in the micropores and protrusions. The highest contact angle of the coating rises to 115.5° and the hydrophobicity is improved obviously. The coating also exhibits high adhesion of 5B and hardness of 6H, suggesting its excellent application performance.
[Abstract](155) [FullText HTML](75) [PDF 0KB](6)
Abstract:
Based on the capacity expansion and revamping of a 1.8 million t/a Davy methanol production project of an energy and chemical company, the model was established and analyzed. A multilayer cross one-dimensional quasi-homogeneous mathematical model was established for the adiabatic heat transfer of methanol radial reactor. It is used in Aspen Plus to simulate the series-parallel coupling process of dual radial reactor. It is found that increasing the area of the central pipe hole can effectively reduce the pressure drop of the perforation at large flow rate, and lowering the inlet temperature is effective for reducing the hot spot temperature, but it will increase the circulating gas flow rate. Changing the ratio of feed gas actually changes the connection mode of the reactor and increases the methanol production of the 2# reactor. The optimum production conditions were obtained when the fresh gas ratio was 0.8 and the entry temperature was 235℃, and the production capacity reached 130% of the original process.
[Abstract](237) [FullText HTML](94) [PDF 0KB](20)
Abstract:
At present, in the field of production scheduling, affected by many factors such as production technology, each production process often requires multiple machines to participate in processing at the same time. At the same time, the number of workpieces to be processed is large, and each type of workpiece needs to be processed in batches to shorten the production cycle. Therefore, in a job shop environment, this paper adopts a variable batching scheme according to the load of the machines involved in each processing process, and proposes a non-mixed multi-processor combined production batch scheduling model, and combines the brainstorming algorithm to find the shortest Processing time. An improved brainstorming algorithm is proposed, which introduces greedy thinking and dynamic discussion mechanism. The number of discussions changes adaptively with the iteration of the algorithm. The global search and local search are combined to strengthen the search ability of the algorithm. The test results show that the improved brainstorming algorithm is more efficient and convergent than the basic brainstorming algorithm.
[Abstract](147) [FullText HTML](90) [PDF 0KB](11)
Abstract:
Hemophilia is an X chromosome-linked bleeding disorder disease caused by a lack of coagulation factor. Hemophilia patients suffer from spontaneous bleedings that may occur in different organs and tissues. Hemophilic arthropathy (HA) is the primary etiology leading to disability in hemophilia patients which is caused by the recurrent bleeding in the joints. Over expression of pro-inflammatory cytokines has been putatively recognized as one of the mechanism. In the progression of HA, proinflammatory cytokines serve as signaling mediators, among which TNFα is one of the most important. As a receptor of TNFα, sTNFR (soluble tumor necrosis factor receptor) specifically bind to TNFαand antagonize its proinflammtory effect. To investigate the therapeutic effect of local long-term TNFα expression on HA, hemophilia B mice were intraarticularly injected with rAAV5-TNFR:Fc. In the present study, plasmid pAAV-TNFR:Fc was constructed and used for the package of rAAV5-TNFR:Fc. Transgene expression mediated by infection in vitro and in vivo were confirmed by western blot. Then hemophilia B mice divided into prophylaxis group and treatment group were intraarticularly injected with rAAV5-TNFR:Fc, and 6 weeks after HA was induced, joints tissues were collected for RNA extract to measure the mRNA expression level of TNFα、IL-1β、IL-6 and IL-10. The pathology changes of joints were also graded by histology and the scorings of synovitis arthritis, macrophage infiltration and neovascularization were obtained. The results suggested that, 6 weeks after joints hemarthrosis induction, sTNFR expression in joints persisted. The pathological sequela in two groups were reduced in different degrees after rAAV5-TNFR:Fc local delivery and delivery as a prophylaxis showed better outcome than as a treatment. It was concluded that recombinant adeno-associated virus mediated soluble tumor necrosis factor receptor can be a therapeutic approach for HA treatment.
[Abstract](196) [FullText HTML](108) [PDF 0KB](14)
Abstract:
Since convergence and diversity are taken into consideration cooperatively in the whole iteration process, the traditional multi-objective optimization algorithms will generate a large number of dominated solutions in the early stage of search which will result in the waste of computing resources or non-convergence of the algorithms. To aim at this limitation, the proposed algorithm is divided into three steps in this paper, namely the optimal value exploration for each objective, rough search for Pareto front, local optimization stage with group division. Different tasks are assigned to promote convergence and diversity for each stage. The solutions are divided into different groups according to the value of the objective function, and then the statistical feedback information (SFI) from each group is then applied to guide the parent-selection process. Thus, the distribution and convergence of the solutions could be controlled more precisely. We proposed a stepwise multi-objective evolutionary algorithm based on statistical feedback information(SFI-SMOEA), the proposed algorithm is shown to perform comparably or better than the state-of-the-art on a variety of scalable benchmark problems.
[Abstract](226) [FullText HTML](306) [PDF 0KB](73)
Abstract:
A two-stage multi-objective optimization algorithm based on Pareto dominance is proposed for 2-dimensional and 3-dimensional multi-objective problems. In the global search stage, the population is sorted according to the Pareto dominance relation, and the corresponding selection strategy is carried out according to the ranking level of the critical layer subset. In the local adjustment stage, the individuals in the population are fine tuned, and the new individuals are compared with the nearest individuals in terms of dominance, distribution and convergence, so as to replace the poor individuals. The influence of the two stages on the performance of the algorithm is analyzed, and the population with local adjustment is compared, the results show that the local adjustment strategy can effectively enhance the performance of the algorithm. By solving the standard test function and comparing with other classical multi-objective algorithms, this algorithm has some advantages in convergence and distribution.
[Abstract](212) [FullText HTML](144) [PDF 0KB](33)
Abstract:
With the rapid progress of seawater desalination technology, concentrated brine has not been effectively used due to the lack of mature development and treatment process. Direct emissions of concentrated brine are seriously harmful to the ecological environment. At the same time, massive emissions of carbon dioxide have exacerbated the greenhouse effect. Aiming at the resource utilization of concentrated brine and carbon dioxide, combined with the previous research basis of using calcium hydroxide as the precipitant to prepare magnesium hydroxide, this paper proposes a carbonization technical process to prepare magnesium bicarbonate using magnesium hydroxide as the precursor from low magnesium systems. The research focuses on the carbonization process of magnesium hydroxide, investigating the influence of liquid-solid ratio, temperature, carbon dioxide gas velocity, stirring speed, and raw material difference on the carbonization process, and monitoring the change of calcium and magnesium ion concentration and pH value during the carbonization process. It was found that under room temperature and atmospheric pressure, the carbonization effect is the best when the liquid-solid ratio is 40, the carbon dioxide gas velocity is 400 mL/min, and the stirring speed is 300 r/min, the concentration of Mg2+ in the carbonization solution from analytical purity magnesium hydroxide is 0.315 mol/L and there exists no Ca2+, the concentration of Mg2+ in the carbonization solution from self-made magnesium hydroxide is 0.203 mol/L, the concentration of Ca2+ is 3.2×10−4 mol/L, calcium impurities are basically separated. The particle size and dispersion of magnesium hydroxide have significant impact on the carbonization effect: smaller particle size and better dispersion promote the carbonization process. The shrinking core model of magnesium hydroxide is briefly discussed at the same time, the fits of the carbonization process at different slurry temperatures show good linearity.
[Abstract](406) [FullText HTML](157) [PDF 0KB](71)
Abstract:
In order to improve the detection accuracy of Android malware, a static detection method of Android malware based on LSTM-SVM (long short-term memory network-support vector machine) model is proposed. Firstly, the APK (Android Package) file of Android software is decompiled, and three types of information, including permission, component and intent, are extracted from the AndroidManifest.xml file to form the XML features. Then, the API (Application Programming Interface) called situation is analyzed according to the smali files to form the API features. Secondly, considering the timing and feature dimension of malware operation, LSTM anomaly detection model is constructed based on XML feature, and SVM anomaly detection model is constructed based on API feature. Finally, the parallel mode is adopted for two models, and the final detection result is obtained based on probability difference fusion algorithm. The experimental results on CICAndMal2017 data set show that the detection accuracy of this method can reach more than 98%.
[Abstract](170) [FullText HTML](82) [PDF 0KB](28)
Abstract:
In this paper, the cyclone fluidized bed with single tangential inlet and double tangential inlet is modeled and its internal flow field is analyzed respectively. The Euler multiphase flow model was used to analyze the distribution state and velocity distribution of particles, and the axial climbing characteristics and dead zone distribution of the two structures were compared and observed. The results show that the double-swirl structure has better fluidization degree and more uniform and stable particle distribution. In the cyclone fluidized bed particle collisions and rotation must not ignore, limited by eulerian two-fluid model, this paper uses the EDEM discrete element analysis of the two kinds of structure of particle movement characteristics, as well as the law of the velocity changes over time. Comparing the different import structure of fluidized beds, it is found that the particles in the bed of the axial alternating motion acceleration and deceleration, double tangential inlet structure of fluidization performance is better, which can faster to make particles reach the stable state. In this paper, the characteristics of the flow field and particle movement of the fluidized bed with different structures are analyzed by two kinds of simulation methods to explore the improvement of the adsorption performance of the swirl fluidized bed.
[Abstract](205) [FullText HTML](126) [PDF 1286KB](22)
Abstract:
A three-dimensional model for a random packed bed filter was established by coupling computational fluid dynamics (CFD) and discrete element method (DEM). To ensure more accurate simulation results can be obtained, the interactions of liquid-solid, particle-granule and particle-particle were taken into consideration. The filtration performance including filtration efficiency, pressure drop and impurity holding capacity were carefully analyzed, and particle deposition distribution and morphology were also numerically investigated. The simulation results of filtration efficiency have a good agreement with the experimental results. The deviation of the pressure drop is within the allowable error range of the Ergun equation. The impurity holding capacity is represented by the deposition uniformity obtained by simulation results, which increases with the superficial velocity. Correlation of deposition uniformity for granular bed filters is presented and it has good prediction accuracy. The results show that cascade filtration has both a high filtration efficiency and a low pressure drop by combining deep bed filtration and surface filtration. The quality factor of the cascade filter is greater than that of a single-layer filter. The simulation analysis of particle deposition morphology and distribution shows that particles mainly deposit on the surface of single-layer filter packed with fine granules, resulting in its small holding capacity. As for the cascade filter, the fine granular layer ensures high filtration efficiency while coarse granular layer provides large impurity holding capacity.
[Abstract](163) [FullText HTML](101) [PDF 1494KB](7)
Abstract:
Hierarchical ZSM-5 and β zeolites were synthesized by solvent evaporation induced self-assembly and oriented attachment growth methods, respectively, and their catalytic properties in n-heptane cracking were assessed to determine the impact of hierarchical structure over catalysis. The catalytic cracking of n-heptane to generate light olefins was evaluated and the results demonstrated that high yields of light olefins could be attained on hierarchical zeolites, despite of lower conversions due to the reduction of acid site number. The hierarchical ZSM-5 and β can increase the yield of light olefins by 16.78% and 21.63%. Hierarchical β zeolite outperformed hierarchical ZSM-5 under identical operation conditions. Under optimized 680 ℃ and space velocity of 10.0 h−1·g-N-Heptane·g-Cat.−1, the yield of ligiht olefins by hierarchical β-HTS reached 50.29%, and simultaneously the highest propylene selectivity of 32.68% was achieved. The superior catalytic performance was attributed to a combined effect of reduced acid site density and enhanced diffusion property. The higher propylene selectivity was attributed to the unique large micropore size, better mesopore connectivity and decreased acid site density of hierarchical β.
[Abstract](212) [FullText HTML](87) [PDF 1132KB](22)
Abstract:
The core component (EG-Paraffin) was obtained by impregnation of Paraffin in expanded graphite (EG), and the shell component (EP-Paraffin@SiO2) was obtained by filling the obtained Paraffin@SiO2 microcapsules into epoxy resin. The EG-Paraffin/EP-Paraffin@SiO2 phase change composite with macroscopic core-shell structure was prepared by simple molding. The experimental results show that the macroscopic core-shell structure gave the phase change composite excellent leak-proof performance and shape stability. The microcapsules in the shell component maintained a high enthalpy (greater than 144 J/g) of the phase change composite. On the one hand, EG in the core component can encapsulate the paraffin effectively, and on the other hand, the heat transfer rate of the phase change composites can be greatly improved. The excellent comprehensive performance of this phase change composite has great application potential in the field of thermal energy storage and thermal management.
[Abstract](166) [FullText HTML](121) [PDF 1004KB](12)
Abstract:
In this study, a heterogeneous photocatalyst TPPF20-TPA based on 5, 10, 15, 20-tetrakis (pentafluorophenyl) porphyrin (TPPF20) was synthesized, which can be used in photo-induced electron/energy transfer-reversible addition-fragmentation chain transfer (PET-RAFT) polymerization under the radiation of blue light (λmax = 425 nm). A series of polymers with defined molecular weights and low dispersion can be obtained through the PET-RAFT polymerization process. It was confirmed by 1H-NMR and GPC that the conversion rate of monomer methyl methacrylate (MMA) and molecular weight of the polymer can be controlled by changing the polymerization time, and the reaction process can also be controlled by switching the light source. In addition, the experimental results showed that different monomers can be handled by the PET-RAFT polymerization. Chain extension experiments show that the polymer chain ends have high fidelity. Based on the insolubility of TPPF20-TPA in different organic solvents (e.g ethanol, dichloromethane, dimethyl sulfoxide), it can be easily purified and reused. The results show that it is recycled for 3 independent PET-RAFT polymerization reactions. The polymerization efficiency is not significantly reduced, showing the great potential of the catalyst in the RAFT polymerization system.
[Abstract](197) [FullText HTML](124) [PDF 1744KB](15)
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The aqueous medium reaction method is currently mainly used in biomedicine field, and there are few reports in the research field of functional polymer materials. In this article, we studied the synthesis of multifunctional benzoxazole resins in aqueous medium. Polybenzoxazole are currently mainly used in the form of fibers. We designed and synthesized four new monomers (DAR-C, DAR-N, LAR-C and LAR-N) containing benzoxazole structure, and a series of thermosetting benzoxazole resins were obtained through curing process. Their structure and chemical composition were characterized by EI-MS and FT-IR. Their curing characteristics were studied by DSC, heat resistance and dielectric properties were characterized by TGA and broadband dielectric spectrometer. The results show that: cracking the benzoxazole structure and increasing their free volume can effectively improve the solubility of the resin. In addition, cyanide resins with higher nitrogen content have better solubility. The introduction of the benzoxazole structure effectively improves the heat resistance of the resin. Among them, the Td5 of PLAR-N and PDAR-N in the air are 612 °C and 600 °C, respectively, which is 150 °C higher than that of traditional thermosetting resins. Biphenyl forms a more complete cross-linking system and has higher curing reactivity than single benzene. Therefore, the heat resistance of PLAR-N is better than that of PDAR-N. In addition, with the improvement of the cross-linking system, the dielectric properties of the resin have also been greatly improved. Below 1k Hz, the dielectric constant is as low as 2.24. The dielectric loss is as low as 0.008. There will be good development prospects in the field of heat resistance and low dielectric.
[Abstract](133) [FullText HTML](92) [PDF 733KB](10)
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Porcine epidemic diarrhea virus can infect pigs of different ages and cause porcine epidemic diarrhea, causing heavy economic losses to the pig industry around the world. There is currently no effective treatment for porcine epidemic diarrhea, and vaccination is its key preventive measure. In order to develop an effective porcine epidemic diarrhea virus subunit vaccine, a tandem epitope subunit (EC) was assembled from the COE region (E1), S1D region (E2), and C-terminal region (E3) of spike protein, and the M3 region (E4) of membrane protein, and a baculovirus expression system was constructed for the production of subunit vaccine EC. The reported candidate subunits COE and S1 were used as positive controls. Three target proteins of EC, COE and S1 were produced by baculovirus expression vector systems in insect cell line Sf9, and purified with a nickel affinity chromatography column, respectively. The immunogenicity of different subunit vaccines was evaluated on BALB/c mouse. The results showed that the EC, COE and S1 gene sequences were successfully inserted into the baculovirus genome. All of three proteins could be expressed and secreted into culture supernatant. Compared with the subunit vaccines of COE and S1, subunit vaccine EC could stimulate mouse to produce larger amount of specific immunoglobulin G, interferon-γ and tumor necrosis factor-α than controls. The above results indicate that each subunit vaccine can stimulate the humoral and cellular immunity of mouse, and the immunogenicity of subunit vaccine EC is much stronger.
[Abstract](226) [FullText HTML](131) [PDF 5572KB](30)
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Molten alkali carbonate are widely concerned as potential thermal storage and transfer materials in solar power utilization. As an effective method in molten salt research, computer simulations have been widely used and researchers have been working hard to enhance the accurate of this method. In this paper, local structure and some physical properties of K2CO3 and Na2CO3 at different temperature were calculated by a complex simulation method including First-principle molecular dynamics, Machine learning and Classical molecular dynamics. In this method, First-principle molecular dynamics offered accuracy structure information, Machine learning was used to create deep potential from structure information to describe potential energy of system, and classical molecular dynamics simulation was used to performed large scale simulation. This complex method can reduce calculation errors caused by potential functions and empirical parameters. The calculation results show that energy and force learning test errors of K2CO3 were 8.62×10-4eV/atom and 4.67×10-2eV/10-10m, respectively, test errors of Na2CO3 were 1.19×10-3eV/atom and 5.31×10-2eV/10-10m. In all simulation process, the carbonate ion was a standard equilateral triangle structure in the system, and carbonate clusters were slightly loosened with the increase of temperature; the distance between anions and cations gradually increases with the increase of temperature. Comparing calculated data of the property with experimental value, the result shows that calculated data is in good agreement with the experimental value. The deviations of density, specific heat capacity and thermal conductivity of K2CO3 are 5.0%, 3.3% and 8.0%. The deviations of density, specific heat capacity and thermal conductivity of Na2CO3 are 5.6%, 6.5% and 3.5%.
[Abstract](333) [FullText HTML](224) [PDF 2249KB](44)
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Speech emotion recognition is widely used in various fields such as vehicle driving systems, service industries, education, and medical care. In order to allow computers to more accurately recognize the emotions of the speaker, a multi-task learning 3D convolution neural network and bidirectional long-short term memory Network with attention mechanism for speech emotion recognition is proposed. Based on the multi-spectral feature fusion group, the three-dimensional convolutional neural network was used to extract deep speech emotion features, and the multi-task learning mechanism of gender classification was combined to improve the accuracy of speech emotion recognition. Experimental results show that the model has a high accuracy on CASIA Chinese emotional corpus.
[Abstract](173) [FullText HTML](71) [PDF 1449KB](8)
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Pervaporation (PV) process is a membrane-based separation technology that provides low-cost, environmentally friendly, and efficient characteristics in the separation of azeotropic mixtures. In this research work, we provided a preparation method of a composite membrane based on molybdenum disulfide (MoS2) two-dimensional material and used to dehydrate isopropanol aqueous solution. A ceramic hollow fiber (CHF) membrane was used as a substrate to prepare the MoS2 composite membrane. In order to reduce the macropores on the surface of the CHF membrane, a TiO2 intermediate layer was introduced on the outer surface of the CHF substrate. Polyvinyl alcohol (PVA) was used as a binder in the preparation of the MoS2/PVA separation layer. MoS2/PVA separation layer was constructed on the surface of the TiO2-CHF membrane by vacuum filtration and then crosslinked with glutaraldehyde solution to reduce the swelling degree of the MoS2/PVA separation layer in the aqueous solution. We studied the morphology and physi-co-chemical properties of the obtained membranes by field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), atomic force microscopy (AFM), energy-dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), and water contact angle (WCA) measurements. MoS2/PVA composite membrane showed 486 (g/(m2·h)) of permeation flux and 445 of separation factor in a 90% IPA aqueous solution at 50 ℃. Our research work provides a comprehensive understanding of the preparation of MoS2 composite membranes on CHF membranes to effectively dehydrate isopropanol through the pervaporation process.
[Abstract](174) [FullText HTML](103) [PDF 1304KB](5)
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[Abstract](213) [FullText HTML](161) [PDF 1372KB](12)
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In this work, a simple in-situ reduction strategy was developed to synthesize silicon-based polystyrene-b-polyacrylic acid (PS-b-PAA) micelles loaded with copper nanoclusters (Cu-POMs). Firstly, the structure of PS-b-PAA micelles were fixed by MPTMS to obtain a sulfhydryl-modified organosilica micelles (POMs). Considering copper ions possess a remarkable coordination ability with thiol groups, subsequently, Cu-POMs were successfully prepared. Significantly, the Cu+ on the surface of the nanoparticles could dissociate in response to tumor microenvironment (TME) acidity. Then the released Cu+ will effectively degrade the excessive H2O2 in tumor cells to produce highly toxic •OH. In addition, GSH could reduce Cu2+ into Cu+, as a result of its reductive ability, realizing a self-circulation for promoting the sustained generation of reactive oxygen species (ROS) and consumption of GSH simultaneously. The morphology and hydrodynamic size of Cu-POMs were detected by means of transmission electron microscopy (TEM) and dynamic light scattering (DLS), respectively. Raman spectroscopy was used to detect the functional groups of Cu-POMs. And then the valence of Cu in Cu-POMs was analyzed by X-ray photoelectron spectroscopy (XPS). The stability of Cu-POMs was investigated in simulating physiological conditions. Besides, the ability to generate hydroxyl radical (•OH) through Fenton-like reaction of Cu-POMs was verified by methylene blue (MB) degradation experiments. At the same time, cytotoxicity tests were used to evaluate biosafety and killing effect on tumor cells of Cu-POMs. The results showed that the synthesized Cu-POMs has pH responsiveness, which can take full advantage of the slightly acidic environment in TME while avoiding the leakage of copper ions in normal tissues, ensuring its biosafety. In addition, Cu-POMs owns GSH depletion properties, which can effectively catalyze H2O2 in TME to generate highly cytotoxic •OH for specific tumor treatment.
[Abstract](239) [FullText HTML](130) [PDF 842KB](33)
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The electrofusion welding status of the polyethylene (PE) gas pipeline can be obtained through the ultrasonic pictures taken by the phased array system. However, whether there are welding defects is currently judged by professionals. And the feature line, resistance wire, and bottom in each picture are manually checked for defect-related information. Then the defect categories and levels are determined. The disadvantage of this method is that it is time-consuming and labor-intensive, and is prone to missed detections and false detections. Aiming at the identification of electrofusion welding defects in PE pipelines, this paper proposes an automatic identification method of welding defects based on image processing technology. This method judges the categories and levels of defects in ultrasound images. The method consists of four steps: 1) expanding the number of existing pictures through data enhancement technology to build a data set; 2) training the image semantic segmentation model to perform semantic segmentation on the image; 3) using mathematical morphology to remove the noise of the segmentation result, and obtaining defect-related information through connected domain analysis; 4) identifying defect categories and levels based on welding standards and defect-related information. The experimental results show that the defect recognition method proposed in this paper meets the requirements of industrial applications in terms of accuracy, recall and running time.
[Abstract](215) [FullText HTML](98) [PDF 1115KB](15)
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CsPbX3 perovskite semiconductor has received extensive research attention in the past decade due to its high light absorption coefficient, adjustable fluorescence emission in the visible light range, long carrier diffusion length and relatively good defect tolerance. It can be used as high-efficiency phosphors in electroluminescence quantum yield light-emitting devices. In order to obtain a wider range of fluorescence emission, the element composition and crystal arrangement of the perovskite nanocrystals can be adjusted by ion exchange or the introduction of guest transition metal ions into the host nanocrystals, which leads to the changes of the optical, electronic and magnetic properties of the host nanocrystal. Using ligand-assisted reprecipitation method, nickel chloride was added to the precursor solution of manganese-doped perovskite (CsPbxMn1-x(Cl/Br)3) nanocrystals (NC). It was found that compared with the manganese-doped perovskite NCs, the Mn2+ fluorescence intensity of the nickel-manganese co-doped perovskite NCs increased by about 100%, and the morphology changed from approximate cubic block (side length~14 nm) to nanowire (width 2~3 nm). This can be attributed to the fact that the addition of nickel ions reduces the (100) surface energy, and the fully dissolved precursor gets more crystal nuclei and induces the growth of perovskite nanowires. Subsequently, nanowires were used as phosphors and commercially available UV chips to construct a simple light-emitting diode device. Its strong and broad orange fluorescence emission confirmed the potential performance of the prepared Cs(PbxMnyNi1-x-y)(Cl/Br)3 nanowires in light-emitting applications. Finally, nickel chloride was added to the manganese-doped zero-dimensional networked perovskite (Cs4PbxMn1-x(Cl/Br)6), and the nickel-manganese co-doped zero-dimensional networked perovskite nanowires verified the growth mechanism of the perovskite nanowires. All the results provide a reference for the synthesis of novel doped perovskite nanowires.
[Abstract](132) [FullText HTML](110) [PDF 938KB](17)
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In order to quickly and efficiently screen out A. oryzae strains with high-yield Rhizomucor miehei lipase(RML). Firstly, this study optimized the double indicator method for high throughput measurement of RML enzyme activity. The preheating time was controlled to 5 min to ensure a stable reaction temperature. The blank difference of the plate was eliminated, and the R2 of the standard curve was increased from 0.988 to 0.992, which ensured the measurement accuracy. Using commercial RML to draw a standard curve, so that the measurement results more reflect the actual situation.Secondly, a high throughput culture system of A. oryzae was established. The 24-well microplate was used as the carrier for high throughput culture, and the conditions of the microplate culture were optimized. It was found that when the liquid volume was 2 mL and the pH was natural, adding two glass beads was the most suitable for the growth and metabolism of A. oryzae, and its physiological state was most similar to that of shaking flask culture, so it could be applied to high throughput primary screening culture.Finally, after A. oryzae spores were mutagenated by ARTP, 36000-48000 mutagenated spores were screened by means of mixed culture. The mixed spores whose yield was more than 20% higher than that of the control group were selected for the coating plate. After the spores were obtained, the strains with enzyme activity higher than 20% of the control group were selected for the preliminary re-screening in shaking flask. Four high-yield mutant strains were obtained, And verified by shake flask, mutant strains Ⅰ7-D6-7, Ⅱ4-4B-5, Ⅲ3-5C-1, Ⅴ7-6C-3 lipase activity were reached 265.98 U/mL, 240.90 U/mL, 253.52 U/mL, 293.50 U/mL, higher than the control group (176.52 U/mL)were 50.68%, 36.47%, 43.61%, 66.27%.
[Abstract](168) [FullText HTML](92) [PDF 939KB](11)
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The purpose of feature point matching is to generate a corresponding relationship between the input images. It is a basic and important module in visual odometry and has a wide range of applications in many computer vision fields. Random Sample Consensus (RANSAC) is a widely used image matching algorithm, but it has the disadvantages of low recall rate and long time-consuming. Based on the grid motion statistics method and the sequence selection strategy, this paper proposes an improved RANSAC algorithm. First, the quality of the initial feature matching is sorted. On this basis, the input image is divided into a certain number of grids, and the grid the grid is performed according to the motion smoothness theory. Then select the grids with higher scores to estimate the local homography matrix respectively. Finally, the local homography matrices are aggregated to further eliminate the influence of noise and obtain the optimal model. In addition, the sequential selection strategy is used to obtain the homography matrix, which further improves the efficiency of the algorithm. The simulation results show that the image matching algorithm based on grid acceleration and sequential selection strategy has obvious advantages.
[Abstract](154) [FullText HTML](127) [PDF 886KB](8)
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At present, collaborative filtering algorithm is widely used in the recommendation system. Due to the data sparsity problem, there is the drawback of low recommendation accuracy in traditional collaborative filtering algorithm.This paper introduces the social trust network of users to mine the trust information of users to alleviate the accuracy. In addition, this paper also considers the penalty weight of popular items in the calculation of scoring similarity and the influence of the common proportion of user scoring items in the traditional calculation formula of scoring similarity. On this basis, this paper proposes a hybrid recommendation model (TPRA) that integrates commodity popularity and trust. The experimental results on Epinions data set show that the proposed algorithm achieves better results than the control algorithm on all the evaluation indexes used in this paper. Compared with the control algorithm, the proposed algorithm can reduce MAE and RMSE by at least 3%.
[Abstract](143) [FullText HTML](146) [PDF 960KB](9)
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With the rapid development of information and communication technology, microwave dielectric materials have also developed correspondingly. Al2O3 ceramics are widely used in resonators, ceramic substrates, and satellite communication devices due to their excellent microwave dielectric properties. However, the sintering temperature of Al2O3 ceramics is relatively high. Considering environmental protection, energy saving and emission reduction, low-temperature sintering of Al2O3 ceramics is also an important aspect which people pay attention to. Doping additives is a method that has been studied more and has a significant effect on reducing the sintering temperature of Al2O3 ceramics. Recently, CuO-TiO2-Nb2O5 doping has attracted the attention of people because of its outstanding cooling effect. Although some reports show that it can effectively reduce the sintering temperature, Q×f value is low. The sintering behavior, microstructure and microwave dielectric properties of Al2O3 ceramics doped with 0.4%CuO−0.5%TiO2−0.1%Nb2O5 have been investigated. The results show that 0.4%CuO+0.5%TiO2+0.1%Nb2O5 which (mass fraction 1%) reduces the sintering temperature of Al2O3 ceramics effectively. Samples with relative densities of ≥96% and uniform microstructure could be obtained when sintered at 1150 ℃. Higher temperature could further increase the density of the sample, but it inevitably led to abnormal grain growth. Meanwhile, the investigation results show that the low-firing Al2O3 ceramics have good microwave dielectric properties especially high Q×f value. A high Q×f value of 64632 GHz could be obtained for the 1150 ℃ sintered sample. The reason for the low temperature densification, abnormal grain growth behavior and the changing trend of the microwave dielectric properties are discussed in the paper.
[Abstract](1068) [FullText HTML](286) [PDF 1117KB](167)
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Cobalt selenide is considered to be an ideal anode material for lithium-ion batteries because of its good lithium-ion insertion/extraction capability. However, due to large volumetric expansion upon cycling and insulating nature, the performance of cobalt selenide is limited. In this study, we obtained CoSe2-C/C-PAN by coating CoSe2-C polyhedrons with polyacrylonitrile (PAN) in N2 atmosphere. The CoSe2-C polyhedrons were successfully synthesized using Co-based zeolitic imidazolate framework (ZIF-67) as precursor through a two-step method, including carbonization of ZIF-67 and subsequent selenization. The resultant CoSe2-C/C-PAN presents high specific capacity and excellent cycling stability with an initial discharge capacity of 1 440 mAh/g at 0.2 A/g and a reversible capacity of 653 mAh/g at 1 A/g after 200 cycles as anode material of Li-ion battery. The excellent battery performance of CoSe2-C/C-PAN should be attributed to the synergistic effect of nanostructured CoSe2 and carbon materials, in which the nanostructured CoSe2 possesses high reactivity towards lithium-ions and the carbon can provide a continuous conductive matrix to facilitate the charge transfer and an effective buffering to mitigate the structure variation of CoSe2 during cycling. And such significantly enhanced electrochemical performance should be ascribed to the improved electrical conductivity and structure stability of C-PAN.
Articles in press have been peer-reviewed and accepted, which are not yet assigned to volumes/issues, but are citable by Digital Object Identifier (DOI).
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[Abstract](218) [FullText HTML](156) [PDF 3704KB](15)
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The main characteristic of rarely used spare parts include the sharp change of demand, and long and uncertain demand interval, which will result in the inaccurate prediction on the spare part demand such that it is difficult to make a reasonable inventory decision. Aiming at the above issues, this work proposes a novel demand forecasting and inventory optimization method to improve the accuracy of decision-making. In the proposed method, the Gaussian process regression is used to forecast the demand interval, and then, the Bootstrap augmented sample statistical method is combined to predict the probability distribution of spare parts demand. Based on the obtained demand probability statistics results, the stochastic inventory model on the total inventory cost is established and the particle swarm algorithm is further utilized to search the optimal inventory decision variable. Finally, the experimental results from two sets of practical industrial spare parts show that the proposed method has the higher prediction accuracy. Meanwhile, the obtained inventory decision can achieve lower total inventory cost on the premise of satisfying service level, which illustrates the practicality of the proposed prediction and optimization method of infrequent spare partsmethod.
[Abstract](441) [FullText HTML](273) [PDF 3962KB](6)
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Zinc ingots are the main raw material for the production of galvanized sheets and its consumption may fluctuate greatly due to the contract orders and product structure, which further results in fluctuating demand. Material demand often reflects the characteristics of small sample size and large variation range, whose non-stationarity and non-linearity make the demand forecasting more difficult. Meanwhile, the inaccuracy of demand forecasting will be gradually amplified in the information transmission of the supply chain, which will inevitably affect the material procurement plan and inventory management. Therefore, the accurate material demand forecasting has important practical significance for the optimization of raw material procurement and the production management scheduling of iron and steel enterprises. In order to improve the prediction accuracy of zinc ingot demand for galvanized sheet production, this paper proposes a zinc consumption prediction modeling method based on Support Vector Regression (SVR) optimized by Improved Grey Wolf Optimization (IGWO). Aiming at the shortcomings of fast convergence and premature maturity of traditional gray wolf algorithm, the chaotic Tent mapping strategy is firstly adopted to initialize the population so as to enhance the diversity and distribution uniformity of the initial population. Secondly, an adaptive adjustment strategy of control parameters is introduced to balance the search ability and development ability of the algorithm. Finally, the differential evolution is integrated in the location update process to reduce the possibility of false convergence of the algorithm. For the improved gray wolf algorithm, a simulation experiment is made via a typical benchmark test function, whose result verify the superiority of the improved algorithm in comprehensive performance. Furthermore, based on the actual production data of a unit in a steel plant, the zinc ingot consumption is modeled and predicted, and the parameters of SVR is optimized via the IGWO algorithm. The experimental results show that IGWO-SVR has higher prediction accuracy, better stability and better generalization ability.
[Abstract](147) [FullText HTML](122) [PDF 4742KB](14)
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Multiple cycles of experiments and reaction performance tests respectively were conducted using a batch fluidized bed reactor and a thermogravimetric analyzer. The catalytic effect of Fe2O3 on CaSO4/Ben oxygen carriers (OCs) during chemical looping combustion (CLC) was analyzed and the reaction activation energy of CaSO4/Ben OCs with different Fe2O3 contents and CO were compared to verify. The experimental results showed that the specific surface area and pore volume of CaSO4/Ben OCs increased with the addition of Fe2O3, which improved the reduction reaction rate and maintained the high CO2 concentration in the system. Fe2O3 could inhibit CaSO4 reaction to generate CaO and sulfur-containing gases, and improve the stability of CaSO4/Ben OCs circulation reaction. w=15.0% Fe2O3 addition was the best choice. The addition of w=15.0% Fe2O3 reduced the activation energy of CaSO4/Ben OCs reacting with CO from 88.72 kJ/ mol to 43.08 kJ/mol, and the reactivity of CaSO4/Ben OCs were significantly improved.
[Abstract](584) [FullText HTML](347) [PDF 3813KB](17)
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Aiming at the localization problem of illegal whistle vehicles, a fast location system of moving sound source based on distributed microphone array is proposed. GNSS clock is used to realize the time synchronization between microphones, and the sound information collected synchronously is transmitted to the cloud database. Meanwhile, cloud computing technology is applied to realize the sound source localization algorithm. Compared with the centralized microphone array, it can greatly reduce the number of microphones and computing resources, and has the advantages of cost economy and flexible deployment. Besides, the proposed system adopts a fast location algorithm based on the arrival time difference and arrival frequency, which can make full use of the arrival frequency difference information between distributed microphones caused by Doppler effect to overcome the bottleneck of the arrival time difference method that is difficult to adapt to moving sound source. This proposed method can avoid the process of eliminating Doppler effect with complex calculation and large amount of calculation, and has low computational complexity and can adapt to high-speed moving sound source. Finally, the system simulation and field experiment results show that the proposed system can realize the fast and accurate positioning of high-speed moving sound source, and can be better applied to the scene of car whistle positioning.
[Abstract](442) [FullText HTML](383) [PDF 4145KB](15)
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In view of the periodic dynamic characteristics of traffic flow, a probabilistic combination model of traffic flow based on similarity clustering is proposed, which fully excavates the similarity characteristics of different periods of traffic flow. Firstly, the adaptive K-means + + clustering method is used to cluster the historical traffic flow data, and the traffic flow data with time similarity is classified. Then, the combination model is constructed for different sequence feature data sets. Furthermore, according to the new traffic flow state data, the similarity between the new traffic flow state data and the classified data is analyzed, and the probability weight of the combined model is calculated. And then, the prediction output is obtained by fusing the probability weight of the combined model results. Finally, the simulation experiment verifies the validity and accuracy of the proposed prediction model.
[Abstract](197) [FullText HTML](101) [PDF 4449KB](21)
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[Abstract](464) [FullText HTML](434) [PDF 3520KB](12)
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Gender identiﬁcation is a quite important task in speaker verification and can also be used as an auxiliary tool in automatic speech recognition (ASR) to improve model performance. In order to increase the accuracy of gender identification, some schemes based on deep learning have been recently reported. However, compared with the acoustic conditioned data in training, speech data in the actual application scenarios is usually masked by the background noise, such as music, environmental noise, background chatter, etc. Thus, the performance of gender identification model based on audio is seriously degraded due to the great difference between the actual speech data and the model training data. In order to solve this problem, we propose a domain adaptive model via combining generative adversarial network(GAN) and Ghost VLAD layer. The introduction of GhostVLAD can effectively reduce the interference of noise and irrelevant information in speech and the training method based on GaN can realize the adaptation of the model to the target domain data. During the confrontation training, auxiliary loss is introduced to maintain the representation ability of gender characteristics. Finally, by voxceleb1 data set as the source domain, audioset and movie data set as the target domain, the performance of the domain adaptive model is tested, from which it is shown that compared with the gender recognition model based on convolution neural network, this model can improve the accuracy of gender recognition by 5.13% and 7.72% , respectively.
[Abstract](20) [FullText HTML](5) [PDF 4414KB](4)
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Serum amyloid A (SAA) is an acute-phase protein mainly produced by the liver in response to proinflammatory cytokines. SAA genes and proteins are significantly activated during the acute phase response, which comprises a number of phenomena that occur in the presence of inflammation and infection, increased temperature and hormonal and metabolic alterations. Therefore SAA is a sensitive indicator of inflammation in the early stage of infectious diseases, which is important for diagnosis, evaluation, monitoring and treatment of inflammation. Fluorescent immunochromatography is one of the most popular strategies for point-of-care testing (POCT), which is capable of rapid screening for disease detection. Fluorescent microspheres QM-OH@PS-COOH were obtained from aggregation-induced emission (AIE) quinoline-malononitrile (QM) derivatives QM-OH. The morphology and structure of these QM fluorescent microspheres were characterized by scanning electron microscopy et al. Finally, these fluorescent microspheres were utilized to detect for SAA concertation in clinical samples via fluorescent immunochromatography. The results showed that QM-OH@PS-COOH has uniform sizes with regular shapes. Compared with commercial fluorescent microspheres, these AIE microspheres had similar density, solid content and carboxyl content. The QM-OH@PS-COOH system exhibited the detection of SAA with high sensitivity in clinical samples via fluorescent immunochromatography. Thus, this new type of QM fluorescent microspheres could be employed as an important tool for clinical diagnosis, enabling quantitatively analyze and monitor the concentration of SAA during the inflammation process. Therefore, we believe that these detection platforms based on QM-OH@PS-COOH can serve as a screening platform for early disease detection, especially self-testing in POCT.
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In this paper, Panax notoginseng (P. notoginseng) suspension cells were used for the production of chlorogenic acids (CGAs), of which bioactivities were evaluated. Firstly, CGAs in P. notoginseng suspension cells were identified by liquid chromatography-tandem mass spectrometry. Secondly, the suspension culture system and elicitation mode were optimized. At last, the antioxidant and α-glucosidase inhibitory activity of CGAs from P. notoginseng cells were determined. The main results were as follows: 1) Four CGAs were inferred in P. notoginseng cells. 2) The optimal condition was obtained (B5 + 4.0 mg/L NAA + 0.2 mg/L 6-BA + 40 g/L sucrose + 2 g/L PVP, pH 7.5 and 15% inoculation size). 3) By co-culture with 30 μmol/L methyl jasmonate for 3 days, the CGAs yield could reach up to 684.07 mg/L, which was 1.44 times that of control. 4) CGAs from P. notoginseng cells showed an excellent antioxidant capacity in radical-scavenging test and, moreover, certain inhibition on α-glucosidase activity. Thus, our results indicated that the production of CGAs by P. notoginseng cells have potential applications in healthy food and daily cosmetics.
[Abstract](200) [FullText HTML](75) [PDF 4241KB](8)
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Positive definite linear systems arise in many areas of scientific computing and engineering applications, such as solid mechanics, dynamics, nonlinear programming and partial differential equations. It is very meaningful to explore how to efficiently solve the large scale sparse saddle point problem. This paper proposes an extrapolated positive definite and skew-Hermitian (EPSS) iterative method for solving large sparse positive definite linear systems. The new method first splits the coefficient matrix into positive definite matrix and skew-Hermitian matrix, next constructs a new non-symmetric two-step iterative scheme. The new method can not only solve non-Hermitian positive definite linear equations, but also be used for solving Hermitian positive definite linear equations, which greatly accelerates the convergence speed of the iterative method. Then theoretical analysis shows that the new method is convergent. And the necessary and sufficient conditions for the convergence of the new method are given.Moreover the spectral radius of the iterative matrix of the new method is smaller than that of the iterative matrix of the positive definite and skew-Hermitian (PSS) iterative method when selecting appropriate variables. After that numerical experiments are given to show that the new method is efficient and more competitive than PSS iteration method and the extrapolated Hermitian and skew-Hermitian (EHSS) iterative method. Finally, numerical experiments analyze the sensitivity of the parameters in the EPSS iterative method and find the approximate optimal parameters.
[Abstract](117) [FullText HTML](176) [PDF 3897KB](8)
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In this article, a new three-parameter asymmetric generalized error distribution and its extension are introduced. This includes as special case the symmetric Normal distribution. One skewness parameter and two tail parameters are introduced into the generalized error distribution to control the asymmetric and the left tail as well as the right tail respectively. Basic properties of the distribution are studied in details, including the cumulative distribution function, the quantile function, the origin moment of each order and so no, and the sampling method of the random variable is given. Different approaches to the estimation of parameters, such as moments, maximum likelihood and Bayesian methods are discussed. Finally, two applications are made to two real data sets modeling example.
[Abstract](144) [FullText HTML](83) [PDF 4502KB](9)
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Multilayer capacitors with BaTiO3 as the core dielectric material was known as the most widely used and classic perovskite ferroelectrics. Due to the high sintering temperature of BaTiO3 based ceramics, only noble metal materials could be used as internal electrodes. Therefore, it was of great practical significance to reduce the sintering temperature of BaTiO3 based ceramics to match with the base metal electrode materials with lower melting point, so as to reduce the cost, which had been a research hotspot in this field at home and abroad. In order to reduce the sintering temperature of BaTiO3 ceramics, many methods had been used, among which the simplest and most effective method was to add appropriate sintering additives. In this work, BaTiO3 ceramics were sintered at low temperatures via co-doping with CuO, B2O3 and Li2O. The phase composition, density and microstructure of the ceramics at different sintering temperatures had been investigated. The results showed that co-doping of CuO, B2O3 and Li2O could effectively reduce the sintering temperature of BaTiO3 ceramics. Single tetragonal phase BaTiO3 ceramics with high density of 5.75 g/cm3 could be obtained after sintering at 950 ℃ for 2 h and the relative density was 95.6%, while higher sintering temperature led to the decrease of the density of the ceramics. The density of sample sintered at 1100 ℃ was only 5.23 g/cm3 and the relative density was 86.9%. Meanwhile, the microstructure of BaTiO3 ceramics changed obviously with the increase of sintering temperature, and the grains grew rapidly. The low eutectic phase and solid solution reaction during 0.7%CuO-1.5%B2O3-0.3%Li2O (BCL) co-doping were the main reasons for decreasing sintering temperature.
[Abstract](206) [FullText HTML](111) [PDF 3793KB](7)
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Give a graph \begin{document}$G$\end{document}, let \begin{document}$E\left(G\right)$\end{document} denoted the set of edges and \begin{document}${d}_{G}\left(v\right)$\end{document} the degree of the vertex \begin{document}$v$\end{document}, respectively. For an edge \begin{document}$e=uv$\end{document}, the general sum-connectivity index \begin{document}${\chi }_{\alpha }\left(e\right)={({d}_{G}\left(u\right)+{d}_{G}(v\left)\right)}^{\alpha }$\end{document}, in which \begin{document}$\alpha$\end{document} is any real number. Before taking the product of two simple connected graphs \begin{document}$G$\end{document} and \begin{document}$H$\end{document}, we first perform \begin{document}${S},{R},{Q},{T}$\end{document} operations on the graph \begin{document}$H$\end{document}, denoted as \begin{document}$F\left(H\right)$\end{document}, in which \begin{document}$F\in \{S, R, Q, T\}$\end{document}, then take the lexicographical product of graphs \begin{document}$G$\end{document} and \begin{document}$F\left(H\right)$\end{document}, we give the sharp bounds on general sum-connectivity index of graphs for operations based on lexicographic product, and these bounds are sharp.
Abstract:
The low voltage ride through performance of doubly fed fan depends not only on the control strategy, but also on the selection of control parameters.Because the control parameter optimization algorithm takes too long to achieve the corresponding effect in real-time control, a method based on off-line parameter optimization, model training and on-line fault identification is proposed in this paper.Firstly, a large number of different types of fault data are obtained through the established DFIG grid connection model, and the control parameters are optimized offline according to the fault type to form the corresponding low-voltage ride through mode, and then the different fault data are classified to form the training samples of neural network.At the moment of power grid fault, the fault data can be directly used to quickly judge the fault type through the trained distributed deep neural network, and select the appropriate control strategy according to the fault type.The feasibility of this method and its advantages in control effect and speed are verified by the fault identification and parameter optimization method of doubly fed fan model.
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The chlorination of sucrose-6-acetates (S-6-A) to produce sucralose-6-acetate (TGS-6-A) is a key step in the synthesis of sucralose. In this work, the thermodynamic calculation of the chlorination reaction was carried out using the group contribution method. The results show that the reaction is exothermic and irreversible in the temperature range of 372 K to 389 K. The thermodynamic calculations were performed on the hydrolysis reaction of TGS-6-A and the equilibrium constants at different temperatures were obtained, which agree well with the experimental value, confirming the reliability of the calculation methods used in this work. Then the effect of temperature on reaction rate was studied by batch experiments and a chain reaction kinetic model of chlorination reaction was established. The activation energy of the main reactions was calculated as 103.87 kJ·mol−1 and 153.87 kJ·mol−1, respectively, and the activation energy of the side reaction was 87.09 kJ·mol−1. The kinetic experiment results show that the main reaction is more affected by reaction temperature, increasing the temperature and controlling the reaction time can effectively increase the yield of the target product TGS-6-A.
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Saccharomyces cerevisiae is one of the cell factories in biomanufacturing because of numerous advantages towards industrial fermentations, which include robust growth in low pH, lower temperatures, high tolerance to shear stress, lack of phage contamination, and ease of separation. However, the Crabtree effect of S. cerevisiae made ethanol and glycerol be accumulated due to carbon overflow. For the production of intermediate derivatives of the TCA cycle, such as itaconic acid, the Crabtree effect must be overcome by using a suitable strategy. In this paper, the role of NOX and AOX1 on the Crabtree effect in batch fermentation of S. cerevisiae was investigated by expressing the NADH oxidase NOX and the alternative oxidase AOX1 with plasmids having different copy numbers. It was revealed that both strains expressing NOX and AOX1 in high copy vectors caused significant metabolic changes. The high copy expressing nox strains were able to oxidize cytoplasmic NADH, glycerol secretion in the medium was reduced by 43.94%, and IA concentration was not changed. In contrast, strains with high copy expression of aox1 had cytoplasmic residual AOX1, which oxidized cytoplasmic NADH and reduced glycerol accumulation. Further location of AOX1 to the mitochondria of S. cerevisiae with the mitochondrial location signals AAC2 and BCS1p reduced the effect of AOX1 on glycerol synthesis, and IA production was enhanced to 116.98 mg/L. However, none of the strains expressing AOX1, AAC2-AOX1 and BCS1p-AOX1 significantly alleviated the accumulation of ethanol in batch fermentation. This study helps to improve the production of TCA cycle derivatives from glucose by engineered S. cerevisiae, provides a reference for the production of TCA cycle derivatives from S. cerevisiae in the batch culture at high original glucose concentrations.
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Due to inherent factors such as infrastructure construction, wireless sensor networks must consider the problem of limited network resources and uneven resource consumption. In this paper, based on swarm intelligence fuzzy control, fuzzy control is introduced into swarm intelligence artificial bee swarm routing protocol to solve the optimization problem of multipath routing planning in software-defined sensor networks. Based on the SDN-WISE software defined network architecture and swarm intelligence algorithm, and the optimal link was searched by generating artificial bees to simulate the process of honey gathering. Artificial bees adjust different data transmission links, judge regional state through fuzzy logic, and evaluate the data link with the highest value by generating fitness function, generating an optimized routing solution. The experimental results show that, compared with the classical routing algorithms is adopted in this method to optimize the routing problem solving process in the framework of loosely coupled software-defined network by integrating the agent adaptive ability of artificial bees and the fault-tolerant logic of fuzzy control. The experimental results show that, It has obvious advantages in residual energy management, network utilization, transmission delay and packet delivery rate.
Abstract:
This paper considers a hybrid fuzzy neural networks (FNN) for time-series prediction based on error distribution analysis. Firstly, a new hybrid FNN (HFNN) structure is established, where the last two layers is replaced by a combination of a full connection layer and nonlinear activation function. Thus, more parameters can be updated in training process to guarantee the prediction accuracy. Secondly, a novel attention loss function is proposed to make a sample with a certain error distribution get more gains in training process. Based on rule analysis with probability density function, it is seen that the proposed method can provide a more uniform and stable predicted output. The prediction errors of HFNN converge to a compact set. Finally, two benchmark problems are applied to demonstrate the hybrid model performance on time series prediction. The comparisons with other prediction models have verified the efficiency and accuracy of the proposed HFNN model.
Abstract:
Heat integration across different units is an effective measure to improve energy utilization in chemical plants. In order to obtain the actual energy-saving potential across the units and improve the fluctuation resistance of the retrofitting schemes, a retrofitting method based on the actual cold and heat composite curves is put forward. Based on the industrial data of benzene production and C8 units in a petrochemical enterprise, the heat exchanger networks of the two units are simulated in Aspen HYSYS and the pinch analysis is done with Aspen Energy Analyzer. Considering the unreasonable heat transfer of benzene production unit and the safety constraints, retrofitting schemes for the heat exchanger network of benzene production unit are proposed to reduce the steam consumption. Since the energy-saving potential of the C8 unit is limited and the unreasonable heat transfer is distributed in different heat exchangers, it is not cost-effective to retrofit the heat exchanger network of the C8 unit. The energy-saving potential of heat integration between the two units is analyzed by constructing the actual cold and hot composite curves. The advantage of using the actual cold and hot composite curves to guide the heat integration across the two units is that it uses the actual residual energy, which is more practical than the theoretical situation such as the grand composite curve. Besides, limitations and complexity of implementation are also considered to make retrofitting schemes. As a result, two heat integration retrofit schemes across the two units are proposed, compared, and discussed. The results show that the scheme with more energy saving needs more investment costs and has a slightly longer payback period, but has more economic benefits in the long term.
Abstract:
The order of the stability and binding constant of curcumin encapsulated by three Tween aggregates is: Tween-85 vesicles > Tween-60 vesicles > Tween-80 micelles. By UV and fluorescence measurements, it is found that curcumin is encapsulated in the hydrophobic region of the alkyl chains of Tween aggregates with the hydrophobic interaction as the main driving force. The 1H NMR data confirm that the encapsulation position and force of curcumin are closely related to the alkyl chain structure of Tween surfactants. Compared with Tween-60 vesicles with a particle size of ~92 nm, the micelles formed by Tween-80 containing double bonds in the alkyl chain have loosely arranged hydrophobic region. Therefore, curcumin encapsulated by Tween-80 micelles exhibits lower stability, binding constant, and UV absorption and fluorescence emission intensities. Tween-85 with three unsaturated alkyl chains can generate vesicles with a particle size of ~150 nm, and its bilayer has the highest hydrophobicity which has the best encapsulation effect on curcumin.
Abstract:
Heat exchanger network, HEN, is one of the most important parts in chemical production process. HEN optimization become an effective tool to save energy and keep sustainable development. There are many methods to optimize HEN. In principle, mathematical programming seems a comprehensive solution, while the pinch point method is still a handy tool, due to its simplicity and clear physical meaning. Special arrangement is required when phase change is considered in the system. The aim of this paper is to investigate six streams distributed in adjacent sections in an ethylene cracking process from systematic perspective, as no heat recovery is involved, and only utility is matched to meet their temperature requirement in process. Problem table is used to determine the pinch point for the design of HEN. Due to the complex phase change of the mixture in the heat exchange system, the phase change section is converted into one or more streams with constant heat capacity flow rate according to its thermal load and material characteristics, so as to determine the temperature interval. In traditional pinch point method, △Tmin is found as 11℃, and it is determined to be 9℃ with the consideration of carbon emission. The pinch point is determined by problem table at 88.3℃ for the hot stream and 79.3℃ for the cold stream. Under this condition, the minimum thermal utility required by the heat exchanger network is 12727.27 kW, and the required minimum cold utility is 38719.59kW. The total annual cost is reduced by 2620585.49 USD/a, and the carbon emission is reduced by 61453.50t/a. According to the design principles of pinch technology and stream matching criteria, the energy-efficient heat exchanger network structure has been obtained.
[Abstract](183) [FullText HTML](200) [PDF 3929KB](34)
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1,2,3,4-Tetrahydro-isoquinolines are a significant class of building blocks used in the pharmaceutical and agrochemical industries, and existed widely in a variety of chiral amine drugs. Among them, (S)-1-Phenyl-1,2,3,4-tetrahydro-isoquinoline ((S)-1-Ph-THIQ) is the key precursor for the synthesis of Solifenacin, a drug for the treatment of overactive bladder. Imine reductase (IRED)-catalyzed asymmetric reduction of 1-phenyl-3,4-dihydroisoquinoline (1-Ph-DHIQ) is a green and promising route towards chiral 1-Ph-THIQ. However, currently there is only a limited number of reported IREDs that could catalyze the synthesis of chiral 1-Ph-THIQ from 1-Ph-DHIQ, and they may suffer from issues including low activity, poor stereoselectivity, and substrate inhibition. In this study, we first discovered an IRED AdIR1 with considerable properties by screening a panel of IREDs and identified key residues which may affect the activity via homo-modelling and structure comparison. Protein engineering was performed to generate mutant F172Y with elevated catalytic efficiency, which was then characterized in terms of kinetic parameters and thermostability. Finally, preparative synthesis of (S)-1-Ph-THIQ on gram-scale was achieved employing mutant F172Y, demonstrating the considerable applicability of this biocatalytic route in the synthesis of (S)-1-Ph-THIQ.
[Abstract](183) [FullText HTML](112) [PDF 4895KB](15)
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High temperature and high dielectric constant polymer nanocomposites have attracted widespread attention in pulse power system. such as mobile electronics, electric vehicles and electronic equipment ,which due to their processing flexibility, light weight, and low cost. Herein, a new type of thermosetting benzoxazole high-temperature resistant resin NPBO was synthesized by chemical methods. The chemical structure and thermal curing behavior of NPBO were studied by H-NMR , EI-MS spectra and DSC, it proved excellent thermal properties. At the same time, the stepwise reaction and chemical grafting were used to prepare polyurethane-coated barium titanate core-shell hybrid nanoparticles (PU@BT), and then the PU @BT and NPBO resins were compounded according to different components to prepare PU@BT/NPBO nanocomposites. Use scanning electron microscope (SEM) and transmission electron microscope (TEM) to observe the morphology of PU@BT. and particles are evenly coated and showed a good dispersion performance. Finally, the dielectric properties of the composite materials are measured by a broadband dielectric spectrometer. It is found that as the volume fraction of PU@BT increases from 0 to 10%, the dielectric constant of the composite material increases significantly. At 1 kHz, the dielectric constant of NPBO is 3.3, and when 10% PU@BT is added, the dielectric constant of the composite is 7.3, which is an increase of 1.21 times. The composite material provides a theoretical basis for its application in the field of dielectrics.
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PBT polyether polyurethanes with different active hydrogen components were prepared by a two-step method using 3, 3-diazymoxy-tetrahydrofuran copolymer (PBT) as the soft segment of polyether polyurethanes, toluene diisocyanate (TDI) as the curing agent, diethylene glycol (DEG) as the chain extender and trimethylol propane (TMP) as the crosslinking agent. The curing reaction kinetics and mechanical properties of PBT/TDI, PBT/TDI/DEG, PBT/TDI/TMP and PBT/TDI/DEG/TMP systems were studied by Fourier Transform infrared spectroscopy (FT-IR), differential scanning calorimeter (DSC), electronic universal testing machine and swelling ratio test. The results show that the curing reactions of PBT / TDI, PBT / TDI / DEG, PBT / TDI / TMP / and PBT / TDI / DEG / TMP systems are second-order reactions, and the activation energies of these systems are 135.98, 165.57, 164.93 and 164.29 kJ / mol respectively. The addition of DEG can significantly increase the elongation at break of the adhesive matrix, but the tensile strength decreases; The addition of TMP can improve the tensile strength of the adhesive matrix and reduce the elongation at break; when DEG and TMP exist simultaneously, the tensile strength of the adhesive matrix increased and the elongation at break decreased. DEG and TMP can both improve the crosslinking density of the curing systems.
[Abstract](96) [FullText HTML](28) [PDF 3858KB](6)
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Coupled process of CaCl2 waste mineralization by reaction extraction crystallization has the function of waste recycling and mineralization of CO2, which has a broad application prospect. The key to low cost operation of reaction extraction crystallization coupling mineralization process is the effective regeneration of organic amine extractant. Solid acid catalyst was used to strengthen the pyrolysis regeneration process to realize the regeneration of organic amine.At the same time, the coupled process also producedvaluable HCl gas,, which improved the economyof the process. The effect of heating temperature, carrier gas flow, stirring speed, diluent amount and catalyst amount on the thermal dissociation of trioctylamine hydrochloride by 5A molecular sieve were investigated. The results showed that the pyrolysis of trioctylamine hydrochloride catalyzed by 5A molecular sieve conformed to the first-order kinetic model. The thermal dissociation reaction rate was accelerated and the conversion rate was increased with the increase of thermal dissociation temperature, carrier gas flow, the increase of diluent naphthalene and catalyst amount, and the effect of rotational speed on the thermal dissociation reaction was not obvious. Considering the conversion rate and energy consumption, the optimized pyrolysis conditions were as follws: reaction temperature 180 ℃, carrier gas flow 300 mL/min, rotating speed 150 rpm, mass ratio of triactylamine hydrochloride to naphthalene 1:4, mass ratio to 5A molecular sieve 10:1, 4-hour conversion rate is 95%, and 8-hour conversion rate is 99%. The 5 cycles experiments showed that 5A zeolite still had good catalytic activity.
Abstract:
The electrochemical method has been proved to be an effective method to remove ammonia, but the research on the energy consumption control has been neglected. This research uses artificial intelligence and back propagation neural network to establish the ammonia removal rate prediction model and intelligent control strategy. The model consists of a prediction module and a control module with a back propagation neural network (BPNN) algorithm model. First, 4 hidden layers (per 60 neurons) and a negative feedback adjustment mechanism are used to develop the BPNN algorithm to optimize the model and predict the ammonia removal rate. Through parameter analysis and comparison of response surface models, the BPNN model proposed in this paper has better coefficient of determination and lower mean square error. According to the water quality changes and the determined target of ammonia removal rate, the current control strategy in the electrochemical can be obtained through the BPNN model. Finally, the proposed intelligent control strategy is applied to the electrochemical system for ammonia removal, reducing the negative impact of water quality changes, and can also reduce energy consumption by 38% compared with the original strategy. This work proves the application potential of artificial intelligence and back propagation neural network in the electrochemical of ammonia removal, and provides the possibility to automate the water treatment process.
[Abstract](11) [FullText HTML](10) [PDF 3798KB](1)
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Antifungal effects of 7 different active components from plant essential oils (including cinnamaldehyde, citral, carvacrol, linalool, thymol, menthol, perillyl alcohol) against Fusarium graminearum (F.g.) were compared by the method of inhibiting mycelial growth in vitro. Citral, carvacrol, and thymol were selected due to their lower EC50 values and formed a compound with each other, respectively. The compound composed of carvacrol and thymol was considered the most excellent paring with the best inhibitory effect against F.g. in vitro. Additionally, the mass ratio of carvacrol and thymol in the compound was optimized and finalized the formulation of natural compound fungicide. Results showed that when the mass ratio of carvacrol and thymol was 1∶2, the fungicide had the best antifungal effect against F.g. and the synergistic index (S.I.) is 1.45, which showed a synergistic effect. The possible antifungal mechanisms of carvacrol and thymol compound were also analyzed. The prepared natural compound fungicide could change the permeability of F.g.’s cell membrane, reflected by the change in conductivity. Furthermore, the effects of the prepared natural compounded fungicide on wheat coleoptiles against F.g. were studied. It could significantly inhibit the growth of lesions on wheat coleoptiles. When fungicide, which concentration was 200 μg·mL−1, was administered to wheat coleoptiles infected by F.g., the control rate of the protective group and the curative group were 79.08 % and 84.54 %, respectively. This research provided theoretical guidance for developing natural compound fungicides with precise efficacy. The possibility of further application of active components of plant essential oils has also been discussed.
[Abstract](263) [FullText HTML](129) [PDF 3915KB](40)
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With the development of the artificial intelligence and digital audio technology, music information retrieval (MIR) has gradually become a research hotspot. Meanwhile, music emotion recognition (MER) is becoming an important research direction, due to its great research value for video soundtracks. However, there have been relatively few researching results on music emotion recognition. Although some researchers combine Mel Frequency Cepstral coefficient (MFCC) and Residual Phase (RP) to extract music emotional features and improve classification accuracy, the training models in traditional deep learning takes longer time. In order to improve the efficiency of feature mining of music emotional features, Mel frequency cepstral coefficient (MFCC) and residual phase (RP) are weighted and combined in this work to extract music emotion features so that the mining efficiency of music emotion features can be effectively improved. At the same time, in order to improve the classification accuracy of music emotion and shorten the training time of the model, by integrating the Long Short-Term Memory (LSTM) and the Broad Learning System (BLS), a new wide and deep learning network (LSTM-BLS) is further built to train music emotion recognition and classification by using LSTM as the feature mapping node of BLS. The network structure of this model makes full use of the ability of BLS to quickly process complex data. Its advantages are simple structure and short model training time, thereby improving recognition efficiency, and LSTM has excellent performance in extracting time series features from time series data. The time sequence relationship of music can be extracted so that the emotional characteristics of the music can be preserved to the greatest extent. Finally, the experimental results on the emotion dataset show that the proposed algorithm can achieve higher recognition accuracy than other complex networks and provide new feasible ideas for the music emotion recognition.
[Abstract](15) [FullText HTML](14) [PDF 7189KB](3)
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An improved attention algorithm based on the MaskRCNN network to improve the effect of the semantic segmentation of the test paper, because separating the printed and handwritten regions is a key step to achieve the semantic segmentation of the test paper. The algorithm embeds the Subspace Multiscale Feature Fusion (SMFF) module into the feature pyramid structure of the MaskRCNN network, which calculates attention features based on the subspace, and reduces the spatial and channel redundancy in the feature map. Fusion can effectively extract features of text regions of different sizes and enhance the correlation between features. The experimental results show that the average accuracy of the MaskRCNN network model based on the SMFF module is 15.8% and 10.2% higher than that of the original MaskRCNN network model in the target detection and semantic segmentation tasks of the test paper image dataset, which has a large performance improvement than the MaskRCNN based on the commonly used attention module.
[Abstract](13) [FullText HTML](10) [PDF 4452KB](0)
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Due to multi-path effect and electromagnetic interference, RSS-based indoor positioning systems show poor accuracy. In this paper, an indoor positioning scheme of a heterogeneous wireless sensor network (WSN) based on the RSS and inertial measurement is proposed, which uses the distributed consensus cubature information filters with credibility evaluation to estimate target positions collaboratively. An event triggering mechanism is introduced, where the sensor nodes are awaken to serve only if their RSS constraints are satisfied. The simulation and experiment results of a mobile car show that the positioning accuracy and robustness of the proposed method improve significantly. Moreover, the distributed positioning sheme and event-triggering mechanism help to reduce network energy consumption effectively.
[Abstract](15) [FullText HTML](16) [PDF 5506KB](2)
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Traditional linear multivariate Granger causality test introduces conditional variables to determine whether the causal relationships exist between every two variables or not. However, the traditional way of selecting conditional variables is manual, which lacks of reasonable rules. To deal with the problem, an improved nonlinear multivariate Granger causality test method with selecting conditional variables is proposed in this paper. The proposed method in this paper combines traditional Granger test and multivariable Granger test. This method uses nonlinear Granger causality test to construct a preliminary structure by analyzing the potential relationships between variables to determine which variables are suitable as conditional variables, then nonlinear multivariable Granger causality test can be further used on these preprocessed conditional variables; Two kinds of topological structures are introduced to avoid the repeated inspection of some real relationships that do not produce pseudo causality problems. In our method, support vector regression is used as the way to cope with the nonlinearity. The experimental results on numerical simulation and wastewater treatment benchmark simulation model show that the influence of irrelevant variables is reduced by the proposed method in this paper via selecting condition variables and the causal relationship between variables could be analyzed more accurately. Moreover, the proposed method can adapt to nonlinear conditions and has better performance in terms of computational intensity.
[Abstract](172) [FullText HTML](96) [PDF 8842KB](16)
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Supersonic impinging jets are widely occurred in aeronautics, especially in vertically takeoff and landing of aircrafts. In this paper, large eddy simulation of a supersonic jet impinging on a large plate is presented. The nozzle-to-plate space is 2.08 times of nozzle exit diameter, and the nozzle-pressure ratio is equal to 4.03. Unit ring vortex forcing method for the inflow is used in LES to trigger the turbulence. Results indicate that the position and strength of shock wave are periodical. As the Mach disc oscillates in the axial direction, the underexpanded gas has more sufficient space for expansion, so it can reach a higher speed. In the wall jet zone, the large-scale annular vortical structures are continuous. Along the radial direction, the large-scale vortices break up and generate smaller vortices. Sound wave propagation to the upstream from the wall is observed. After reflection from the lip of the nozzle, it propagates to the downstream near the shear layer, thus a feedback loop is formed. It dominates the generation of monotone. Fast Fourier transform is applied to the pressure fluctuation. The results verify that the feedback loop has the same frequency as the tone. Proper orthogonal decomposition is employed to analyze the velocity fluctuation. The modes and their energy contribution rates are calculated. The jet boundary, Mach disc and the oblique shock wave, the recirculation area and the wall jet all have strong correlation. The generation and evolution of large scale turbulence structures in turbulent field are presented and analyzed.
[Abstract](23) [FullText HTML](7) [PDF 4704KB](2)
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MiRNA is a single-stranded and small non-coding RNA, which is closely related to human diseases. Predicting miRNA-disease associations can help understand the pathogenesis of diseases at the molecular level, so as to provide basis for studying the prognosis, diagnosis, evaluation and treatment of diseases. In miRNA-disease association prediction, most methods used miRNA functional similarity and disease semantic similarity as input, they ignored the miRNA sequence similarity, disease functional similarity and hamming similarity. And in the feature extraction process, they not considered the information complementarity between the linear features and nonlinear features, which would affect the quality of feature extraction of miRNA and disease. Therefore, we propose a novel miRNA-disease association prediction model GCNMSF. First, we introduce the miRNA sequence similarity, disease semantic similarity and hamming similarity, and use similarity kernel fusion method to integrate multi-source similarities of miRNA and disease respectively. Then, we use the graph convolutional network to learn nonlinear features. And the convolutional attention block is embedded into GCN to optimize feature distribution. At the same time, the non-negative matrix factorization method is introduced to learn linear features of miRNA and disease to enrich the feature space which can improve the ability of predicting miRNA-disease associations. Finally, we fused the linear and nonlinear features of miRNA and disease to predict miRNA-disease associations. We use five-fold cross validation to evaluate GCNMSF and the experimental results show that our model is better than the existing methods. In addition, we conduct ablation experiment and case studies to evaluate the effectiveness and applicability of the model. The results of ablation experiment verify the fusion of multi-source similarity information and the combination of linear and nonlinear features are helpful for miRNA-disease association prediction. The case studies of lung and breast cancers further confirmed that GCNMSF can not only predict the potential miRNA-disease associations, but also discover the miRNA-disease associations of unknown diseases.
[Abstract](15) [FullText HTML](10) [PDF 4111KB](3)
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One of the important way of 3D model making is 3D reconstruction. At present, 3D scene reconstruction with moving object interference is a research hotspot. To solve this problem, this paper proposes a 3D reconstruction framework named ORBTSDF-SCNet. This framework combines SLAM (Simultaneous Localization And Mapping), TSDF(Truncated Signed Distance Function) and SCNet(Sample Consistency Networks) technology to complete 3D scene reconstruction with moving object interference. In this framework, firstly, aiming at the fact that SLAM system can only output point cloud and can not directly generate 3D model, this paper proposes a 3D reconstruction method ORBTSDF.In this method, depth camera or binocular camera obtains RGBD image of the moving objects and scene, the tracking thread of ORB_SLAM2 is applied to obtains pose information in real time, the surface reconstruction algorithm TSDF is adopted to realize 3D model reconstruction combined with depth image.At the same time, in order to eliminate the interference of moving objects in 3D scene reconstruction, such as image smear, low accuracy or reconstruction failure etc., a deep learning instance segmentation network SCNet is used to detect and segment moving objects. By combining with some optimization strategies, the error of detection and instance segmentation , the alignment error of depth map and RGB map are reduced. When the instance of the moving object is removed, the RGBD image is transmitted back to the part of ORBTSDF to form a 3D scene reconstruction without moving objects. Comparative experiments on ICL-NUM and TUM datasets shows the effectiveness of the proposed method.
Abstract:
In order to study the variation of the crack growth behavior of oxygen-sensitive materials under the interaction of creep-oxidation, the physical mechanism of dynamic embrittlement was used to establish a mathematical model of creep coupled oxidation damage. The creep-oxidation crack growth of nickel-based alloy was analyzed by Abaqus and Voronoi diagram techniques. Meanwhile, the effects of load level, Grain boundary direction at initial crack, oxygen diffusion rate and creep properties on crack growth were analyzed. Results show that when the load is small, the oxidation promotion effect is significant when the crack propagates; creep gradually tends to dominate when the load increases. Since oxygen is easier to diffuse, the crack initiation time of straight grain boundary cracks is shorter than that of oblique grain boundary cracks. As the oxygen diffusion rate increases, the crack initiation time decreases, and the increase of load will cause the crack initiation time of the straight grain boundary cracks to stabilize. Creep constitutive parameters have almost no effect on the law of crack initiation time with load. The better the creep property of the materials or service conditions, the more obvious the effect of oxidation.
Abstract:
In order to ensure the safe and stable operation of the production process and avoid losses due to failures, timely detection of abnormal conditions and accurate diagnosis of abnormal conditions are of very important research significance. Aiming at the complexity of the chemical process, this paper proposes a parallel long and short-term memory network and convolutional neural network (PLSTM-CNN) model for fault detection in the chemical production process. This model effectively combines the LSTM's ability to extract global features from time series data and the CNN model's ability to extract local features, reducing the loss of feature information and achieving a higher fault detection rate. The one-dimensional dense convolutional neural network is used as the main body of CNN, combined with the LSTM network's sensitivity to sequence information changes, to avoid model overfitting while building a deeper network. The maximum mutual information coefficient (MMIC) data preprocessing method is adopted to improve the local correlation of the data and improve the efficiency of the PLSTM-CNN model in detecting faults under different initial conditions. Taking the Eastman Process of Tennessee (TE) process in Tennessee as the research object, the PLSTM-CNN model is significantly better than the traditional recurrent neural network in indicators such as the average failure detection rate and the false negative rate.
[Abstract](11) [FullText HTML](7) [PDF 4582KB](1)
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Aimed at solving the problems of complex background and variable lighting in laboratory scene understanding, based on the complementary characteristics of RGB image information and depth image information in scene understanding, a perceptual attention and lightweight spatial fusion network model is proposed. In the perceptual attention module of this model, the RGB image and the depth image in the network are used to implement the multi-level assistance to the RGB information by the depth information in a weighted mode. In the lightweight spatial pyramid pooling module, increasing the level of the joint atrous space convolution not only effectively aggregates multi-scale features, but also reduces the parameter amount of the traditional spatial pyramid pooling module by around 89%, enabling the RGB image information and depth image information to fuse more adequately. The model performs better on the two public datasets of indoor scenes than among the classic algorithm. The analysis of each module through ablation experiments verifies that the mean intersections over union of the algorithm proposed in this paper increase by 4.3% and 3.5% respectively. Finally, a test based on the dataset of biological laboratory on the more complex scenes is carried out, which shows that the model can effectively realize the scene understanding of biological laboratory.
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Abstract:
Optical chemical structure recognition from scientific publications is an essential part of rediscovering a chemical structure. Rule-based approaches and emerging deep learning methods both face certain problems, such as a low recognition rate. In this paper, we propose DeepOCSR, a deep learning method for optical chemical structure recognition. Based on the encoder–decoder architecture, this method introduces Transformer and ResNeSt models for converting chemical structure images from publications into SMILES sequences. To train and verify our method, two novel chemical structure datasets were constructed, one of which contained common substituents in the chemical literature. Our proposed method has been extensively tested against existing publicly available deep-learning approaches. The experimental results show that our method outperforms the compared approaches in several pivotal evaluation metrics, including similarity and validity, proving the effectiveness of our method.
[Abstract](10) [FullText HTML](11) [PDF 3836KB](1)
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In the process of the slurry breakup, the throat of the liquid bridge keeps shrinking. When the minimum characteristic diameter of the liquid bridge is close to the size of the solid particle, the slurry will exhibit the complex variation characteristics in the process of time, which is significantly different from pure liquid. Therefore, the study of the micro breakup characteristics of the slurry is helpful to reveal the atomization mechanism and improve the simulation model of slurry. Here Shenhua coal and Huadian coal are used as the raw materials to prepare coal water slurry with a mass concentration range of 58% -62 %(mass fraction). The influence of the physical and chemical parameters of coal water slurry on its microscopic breakup process has been studied by the rotary rheometer, the static surface tension meter, the dynamic surface tension meter, the high-speed camera, the image processing software, and so on. Coal water slurry is a shear thinning non-Newtonian fluid. So in this paper the Herschel-Bulkley model is used to establish the rheological relationship of coal water slurry. Unlike the static surface tension, the dynamic surface tension of coal water slurry decreases with the increase of the characteristic bubble time. After increasing, the minimum surface tension appears around between 100 ms and 200 ms. Finally based on the rheological properties and the dynamic surface tension of coal water slurry, the relationship between the change of the characteristic diameter of coal water slurry micro-breakup and the time of breakup is obtained.
[Abstract](11) [FullText HTML](7) [PDF 4036KB](2)
Abstract:
Pitch-based spherical activated carbon (PSAC) is widely used in medical treatment, environmental protection and other fields because of its advantages of high specific surface area, high mechanical strength, high packing intensity and low fluid resistance. A series of SnOx-CeOx/PSAC catalysts were prepared by impregnation method using PSAC prepared from high softening point petroleum pitch as support. And their catalytic performance were evaluated by the low-temperature selective catalytic reduction (SCR) of NO with NH3. The obtained samples were mainly characterized by nitrogen adsorption/desorption, X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). The results show that SnOx-CeOx/PSAC catalyst exhibits higher SCR activity in comparison with CeOx/PSAC catalyst, and the trend of NO conversion firstly increases and then decreases with the increasing of metal loading. The Sn(5%)Ce(13%)/PSAC catalyst exhibits the highest NO removal activity, where the highest NO conversion can reach about 98% in the temperature range of 100~300 oC. The reason is mainly attributed to the improved dispersion of cerium oxide on the surface of PSAC by addition of SnOx, and the formation of solid solution between SnOx and CeOx with the fluorite-type structure, which may be caused by the incorporation of Sn4+ into the crystal lattice of CeO2. Furthermore, there are a certain amount of Ce3+, and higher percentage of surface chemisorbed oxygen on the catalyst surface because of the synergistic effect between tin and cerium oxides. These factors result in the excellent NH3-SCR performance of the Sn(5%)Ce(13%)/PSAC catalyst. Compared with CeOx/PSAC catalyst, SnOx-CeOx/PSAC catalyst exhibits a higher resistance to SO2 poisoning. NO conversion of Sn(5%)Ce(13%)/PSAC catalyst is still about 80% at 260 oC after the introduction of SO2 in the feed gas for 420 min.
[Abstract](17) [FullText HTML](10) [PDF 4233KB](1)
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Solid dispersions (SDs) is one of the main technologies to improve the dissolution of poorly soluble drugs in drug research and development. However, supersaturated high-energy amorphous state drug in SDs are often associated with a tendency to recrystallized during long term storage. The carrier of SDs plays a key role in maintaining the amorphous state of the drug. Traditionally, the screening of the carrier in the development process is a time-consuming process. The effect of polymer carriers on the long-term physical stability of the amorphous state of Erlotinib (ERL) in SDs were studied. ERL SDs were prepared with different ratios of HPMC, HPMCAS, PVP, PVP/VA, Eudragit, and Soluplus by solvent evaporation method. Through the Flory-Huggins interaction parameter χ and anti-solvent microscopic observations, the compatibility of the polymer with ERL and polymer's influence on the crystallization of ERL were predicted. Focused Beam Reflectance Measurement (FBRM) system was used to analyzed morphologically the regulating effect of the polymer on the crystallization process. Then the amorphous state formed by different proportions of SDs were characterized by Powder X-Ray Diffraction (PXRD), Differential Scanning Calorimetry (DSC) and Fourier Transform Infrared Spectroscopy(FT-IR). The physical stability of amorphous state of SDs in accelerated test condition were determined by PXRD. The results showed that HPMC is a suitable carrier for the preparation of ERL amorphous SDs. The combination of the interaction parameter χ, anti-solvent microscopic observation and FBRM analysis is an effective way to select suitable carrier for amorphous SDs. A full understanding of the impact of polymers on amorphous SDs is of positive significance for the rapid development of poorly soluble drugs.
Abstract:
Anionic surfactant-sodium dodecyl benzene sulfonate (SDBS), sodium lauryl sulfate (SLS), sodium N-lauroyl sarcosinate (NLSS), sodium dodecyl sulfonate (SDS), zwitterionic surfactant-cocoamide propylene betaine (CAB), and non-ionic surfactant-fatty alcohol polyoxyethylene ether (AEO), Tween 20(T20) have been used for combination experiment in binary surfactant systems. Foamability which defined by the ratio of foam volume and initial liquid volume has been characterized as well as the relevant surface activity parameters such as .interaction parameter(βm), the mole fraction in micelle and surface(Xa), and the Gibbs free energy(ΔGm0). Further exploration was performed to evaluate the effect of the interaction of the binary surfactant mixture on the foamability. The results show that during the combination process of anionic and zwitterionic surfactants, coagulation occurs when the molar concentration ratio closes to 1:1. When the surfactant with linear hydrophobic group and the nonionic surface with larger hydrophilic group are mixed, competitive adsorption occurs, which weakens the foamability of the surfactant. Synergistic effects can be produced when anionic surfactants with similar structures are compounded. The mixture of sodium dodecylbenzene sulfonate (SDBS) and sodium lauroyl sarcosinate (NLSS) has the best foaming performance when the molar concentration ratio is 3:7, which has the best foam quality(Q=12.9). The interaction parameter is βm=-9.83 (XSDBSm=0.4) calculated by the theory of synergy, which has a strong Synergistic effect. The Gibbs free energy is ΔGm0=-13.6kJ/mol, proving that the formation of micelles is a spontaneous process.
Abstract:
Based on the method of Grand Canonical Monte Carlo and molecular dynamic simulation, the adsorption, diffusion and permeation behavior of H2O in PBT polyether polyurethane (PUPBT) elastomer were simulated. The results show that the heat of adsorption of H2O on PUPBT at 298, 318, 338 and 358k is 41.15, 40.23, 36.84 and 34.16 kJ/mol respectively in the fugacity range of 0~1000 kPa. The adsorption equilibrium has been reached when the temperature is 298 K. With the increase of temperature, the adsorption capacity of PUPBT toward H2O is declined. The adsorption of H2O on PUPBT is not a uniform adsorption, H2O molecules Adsorbed to the lower potential energy region near the center of the holes in the polymer. The results of diffusion simulation show that under the environmental conditions of 298, 318, 338 and 358 K when the pressure is 101 kPa, the free volume fraction of H2O/PUPBT was 14.37%, 15.55%, 17.00% and 17.85%, respectively, when the diffusion coefficients of H2O into PUPBT are 1.488×10−6、1.999×10−6、3.086×10−6 and 3.462×10-6 cm2/s. And the diffusion of H2O into PUPBT is not a uniform diffusion, but a jump-motion diffusion in free volumes. The solubility coefficient of H2O molecules in PUPBT is the major factor that affects the permeability coefficient of the system. With the increase of temperature, the permeability coefficient of H2O into PUPBT decreases gradually.
Abstract:
A gas-liquid-solid three-phase ebullated-bed reactor with an inner diameter of 286 mm and a height of 7.2 m was used to conduct intermittent liquid phase and continuous gas phase operations. The three-phase system was composed of water, air, and Al2O3 spherical particles. The macroscopic liquid circulation velocity was measured at a solid holdup of 12% ~ 30% and the superficial gas velocity of 0.086 ~ 0.216 m/s. In this study, the tracer method was used to determine the concentration curves of multiple tracers at the inlet and outlet of the reactor. The axial dispersion coefficient of the liquid phase was solved by MATLAB software. Substituting it into the definition of Einstein's diffusion coefficient to get the liquid circulation velocity. The experimental results show that at a certain solid holdup, as the superficial gas velocity increases, small bubbles gradually gather into large bubbles. The rising velocity of the bubbles continues to increase, and the liquid circulation velocity also increases accordingly. Increasing the superficial gas velocity can significantly increase the liquid circulation velocity. At a constant superficial gas velocity, as the solid holdup increases, the large bubble holdup increases, and the bubble rise velocity also increases. As a result, the liquid circulation velocity also increases. However, because the increase of solid holdup will hinder the circulation of liquid to a certain extent, as the solid holdup increases, the increase of the liquid circulation velocity continues to decrease. It shows that there may be an optimal value for the solid holdup.
[Abstract](5) [FullText HTML](11) [PDF 3821KB](3)
Abstract:
The aim of this study was to quantify the effects of multiple factors on fermentation broth rheology. Industrial fed-batch fermentations of Acremonium chrysogenum were conducted, and rheology properties of samples were adequately described by power law model. Nonlinear modeling taking only fungal morphology and cell concentration into consideration led to poor correlation and little prediction function. One of the reasons probably was that the model was oversimplified and some inconspicuous but significant factors were omitted. Consequently, extra elements such as substrate concentration, feed mode, media composition were taken into account, following tremendously increased sample library and existence of variables multicollinearity. Two major morphologies of A. chrysogenum were observed in fermentation broth, i.e.freely dispersed arthrospores and filamentous mycelium. It was found that the number of arthrospores was the major factor contributing to rheology properties, based on the standard partial regression coefficients. Using the partial least squares regression (PLSR) model, good prediction of flow index(n) and consistency index(K) can be made from linear recombination of variables, with R2=0.94, R2=0.91 respectively.
Abstract:
Changes in the choroid are closely related to many ophthalmic diseases. Doctors often need to manually split the choroid layer in the optical tomography image (OCT) during diagnosis, and then quantify the health of the choroid, but manual segmentation is time-consuming and laborious. The difficulty of automatic segmentation of choroid lies in the blurred boundary of the OCT images, for it is difficult to capture the context information, and secondly, the choroidal structure is similar to the retina structure, which is easy to confuse. In order to solve this difficulty, the residual codec model of fusion coordinate parallel attention module and dense atrous convolution module is proposed. A bridge structure is designed, which combines attention mechanism and atrous convolution to suppress shallow noise while increasing the model's receptive fields. In order to make the model pay attention to the choroidal structure information, a hybrid loss function with structural similarity is introduced. The experimental results show that the model can effectively improve the segmentation accuracy of the choroid, and the Dice coefficient and Jaccard similarity reached 97.63 percent and 95.28 percent on the OCT images data set.
Abstract:
Process monitoring is a crucial part of ensuring the safety and quality of industrial production. A sparse D-vine Copula-based (SDVC) process monitoring method is proposed for the problem of nonlinearity and non-Gaussian properties of high-dimensional data in industrial processes. Firstly, considering that the traditional Vine Copula structure optimization method tends to cause estimation errors to accumulate in the Vine structure and the computational burden grows sharply with the increase of data dimensionality. The prior probability of bivariate Copula is modified so that the bivariate Copula in high-level structure tree is more inclined to be optimized to independent states, and the sparse optimization of the high-level tree structure is achieved. Secondly, the vine structure node order determination method is improved. It is expanded sequentially according to the sum of correlations among nodes, making it more applicable to D-vine modeling of horizontal structure. Finally, the high density region (HDR) and density quantile theory are introduced to determine the control boundary and construct generalized local probability (GLP) index to realize real-time monitoring of industrial processes. The superior performance of the proposed method was verified through the Tennessee-Eastman (TE) and acetic acid dehydration industrial processes.
[Abstract](12) [FullText HTML](6) [PDF 3742KB](0)
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Cyber-physical systems (CPS) are tight integration of embedded computers and physical devices, which has a wide of applications in many areas such as process industry, smart energy, medical care, and national defense. However, it is a challenging task to design CPS software that meets both functional and performance requirements, since various physical devices and software in CSPs are interconnected and complex in structures and behaviors. The CPS that controls the operation of physical devices is usually running in dynamical environment. The environmental parameters will affect the structures and behaviors of CPS. This paper proposes a data-based adaptive software structure model design method. In this method, the software architecture model of CPS is constructed by the hierarchical combination of unit modules. The multi-level formal models for CPS software are based on formalisms of Petri net and temporal logic, in order to precisely specify CPS software architecture model, properties, and refine the relation between different levels. The adaptive evolution of CPS is realized by taking advantage of formal semantics, aspect-oriented method, and data analysis algorithms, which abstracts the function of environmental factors into aspect model and obtains a comprehensive CPS model and basic model. The formal method based on Petri nets and temporal logic provides mathematical expression and analysis means for CPS model. Theoretical analysis and experiments show that the designed method is feasible and efficient.
[Abstract](17) [FullText HTML](10) [PDF 3835KB](3)
Abstract:
Electroencephalogram (EEG) functional connectivity microstates represent quasi-stable global neuronal activity and are considered the building blocks of brain dynamics. Therefore, microstate sequence analysis is a promising method to understand the brain dynamics behind various emotional states. Recent studies have shown that the sequence of EEG microstates is non-Markov and non-stationary, which also explains the importance of temporal dynamics between different emotional states. However, the microstate features based on probability statistics can not well represent the dynamic characteristics of EEG signals. These findings inspire us to use recurrence analysis to model time series of microstates to capture non-obvious correlations in time series. In conclusion, we propose an emotion decoding model based on recurrence analysis of EEG functional connectivity microstate sequences. Firstly, the functional connection microstate pattern of each frame signal is established by using the correlation of time-domain signals between each channel, and the typical microstate patterns are obtained by clustering. Then, the original EEG signals were mapped to microstate time series according to typical microstate patterns, and the time series were analyzed recursively to construct recurrence plots to characterize the EEG dynamic characteristics. Finally, Convolutional Neural Networks (CNNs) are used to predict the regression of emotions based on the valence or arousal value. On open dataset DEAP, the regression effect of the Mean Square Error (MSE) of the model in the two dimensions of valence and arousal is 3.45±1.42 and 2.79±1.48, respectively, which is better than the MSE of 3.87±1.67 and 3.25±1.71 based on the traditional statistical characteristics of microstate features.
[Abstract](11) [FullText HTML](13) [PDF 3745KB](3)
Abstract:
An adaptive weighted concept drift detection method based on McDiarmid boundary (WMDDM) is proposed to solve the problems of high detection delay, missed detection and false alarm in the active detection method of concept drift. WMDDM algorithm has a weight adjustment mechanism. The adaptive attenuation algorithm is introduced as a weight function to give the old data lower weights and dynamically adjust according to the changes in the data stream in order to adapt to the concept drift faster. The warning level and drift level of the weighted classification accuracy are obtained by McDiarmid's inequality. When it is detected that the weighted classification accuracy rate drops outside the drift level, the detection result is fed back to the classifier. When it is detected that the weighted classification accuracy rate drops beyond the warning level, the detector adapts to the change of the data flow through the triggered weight adjustment mechanism. The experiment uses 4 artificial data sets (two mutation drift data sets, two gradual drift data sets) and 1 real data set, which are mainly compared with Fast Hoeffding Drift Detection Method (FHDDM), Drift Detection Method based on the Hoeffding’s inequality (HDDM) and other algorithms. Experimental results show that the WMDDM algorithm has the lowest false alarm rate and missed detection rate, and the average detection delay and accuracy rate rank the top 2 among the six algorithms. Finally, WMDDM algorithm is used to classify real data sets and compared with FHDDM algorithm. The results show that WMDDM algorithm has a higher classification accuracy rate than FHDDM. Therefore, the WMDDM algorithm is suitable for abrupt and gradual conceptual drift, and has strong robustness.
Abstract:
Optimization of heat exchanger network is an effective way of energy recovery. However, the model with large optimization space of heat exchanger network is often a complex mixed-integer nonlinear programming (MINLP) model with nonlinear and non-convexity constraints, and difficult to get a feasible solution. In this paper, based on the stage-wise superstructure, a new type of heat exchanger network contains flow split, reflux and non-isothermal mixing was built, and while increasing the optimization space of heat exchange network, linear constraints were set to greatly improve the solvability of MINLP model. Two cases in literature were used to verify the contribution of flow split, reflux, isothermal mixing and non-isothermal mixing to the optimization of heat exchanger network, and the effectiveness and applicability of the model.
Abstract:
With the development of the logistics industry, cold chain logistics have been studied by more and more scholarsas an important branch of the logistics industry. Because the waste of resources in cold chain logistics and distribution is a problem that cannot be underestimated, we use the optimization algorithm to solve the multi-objective optimization model to provide an effective distribution plan for solving the problem of resource waste in this paper. We establish a multi-objective cold chain logistics optimization model with minimizing distribution costs and maximizing customer satisfaction as the objective function in this paper. Customer satisfaction is reflected by the relationship between the delivery vehicle’s arrival time at the customer’s point and the customer’s specific time window; delivery costs are composed of transportation costs, cargo damage costs, cooling costs, and time penalty costs. We adopt the improved five-elements cycle optimization (FECO), which is the five-elements cycle optimization algorithm of dual-mode updating individuals (FECO-DMUI) for multi-objective cold chain logistics optimization model in this paper. The chain logistics optimization model is solved by FECO-DMUI algorithm and compared with FECO algorithm, NSGA-II, whale optimization algorithm and gray wolf optimization algorithm. The effectiveness of the model and algorithm is verified through specific examples, and the FECO-DMUI algorithm can be used to obtain the optimal solution set for path optimization more efficiently in the multi-objective cold chain distribution problem.
[Abstract](12) [FullText HTML](7) [PDF 4962KB](2)
Abstract:
In multivariate time series prediction, it is difficult to capture short-term mutation during long time series, which leads to significant prediction errors. A short-term information enhancement model called clockwork triggered long short term memory (CWTLSTM) neural network is proposed in this paper. The new model groups neurons in the network and assigns different activation frequencies to each group. The neurons in each group can be activated only when the time step is equal to an integer multiple of their specified period. According to the number of the group period, the network is divided into backbone network chain and short-term input enhancement chain. When the short-term input enhancement chain is activated on the time step close to the output position, the input information at that point will be transmitted to the backbone network chain uniaxially, and the weight of short-term input data will be enhanced. So the model can quickly respond to the data fluctuation caused by short-term mutation information, on the basis of storing long-term information. The prediction performance of CWTLSTM was verified by air pollution data set and cement cooler data set, compared with LSTM, XGboost and CWRNN models. The results show that the proposed model has good performance in reducing forecasting error and forecasting future trend. In the experiment, the parameter sensitivity of the model to the periodic allocation strategy is also analyzed, which verifies the role of CWTLSTM in short-term information enhancement to a certain extent.
[Abstract](12) [FullText HTML](7) [PDF 3567KB](1)
Abstract:
Knowledge graphs are useful for many artificial intelligence (AI) tasks. However, knowledge graphs often lack of complete facts. In this paper, we study the problem of predicting missing links by learning embeddings of entities and relations in graph knowledge. We introduce a mirror space translation method to learning the symmetric/antisymmetric patterns. Relations are still modelled as translations in our new space, while entities are modelled as points that have mirror points. Within this space, translation-based models gain the ability to model symmetry/antisymmetry relations. Our proposed model MTransE applies the concept of mirrored space to TransE, with experiments on four well-known datasets, shows the performance over other baseline models.
Abstract:
Over recent years, immunotherapy has developed rapidly, which has changed the way of cancer treatment. However, most patients cannot benefit from immunotherapy, which may be due to insufficient reprogramming of the immunosuppressive tumor microenvironment (TME) and thus limited reinvigoration of antitumor immunity. In TME, adenosine, a metabolite of ATP, is an effective immunoregulatory factor. Extracellular 5'-nucleotidase (CD73) is the rate-limiting molecule in the process of adenosine production. Overexpression of CD73 on tumor cells and immune cells leads to a higher concentration of adenosine in the TME. The high concentration of adenosine suppresses the anti-tumor immune response, promotes tumor cells proliferate, metastasis and angiogenesis. Therefore, anti-CD73 therapy is expected to become a promising strategy for cancer immunotherapy.Several anti-CD73 mAbs (MEDI9447, BMS986179, SRF373/NZV930, CPI-006/CPX-006, IPH5301, TJ004309) and small molecule CD73 inhibitors ((LY3475070, AB680, CB-708) are being investigated in early phase clinical trials. But so far, there is no CD73 targeted product for the treatment of cancer on the market. In this study, firstly we performed the screening of our compound library containing 876 listed drugs to identify candidate inhibitors targeting CD73. Preliminary experimental results showed that Cisatracurium besylate (51w89) could inhibit the enzyme activity of recombinant CD73 with an IC50 value of 13.30 μmol/L. To verify the interactions between 51w89 and CD73 and evaluate their binding affinities, we performed surface plasmon resonance (SPR) experiments using a Biacore T200 (GE Healthcare). The binding affinity (KD value) of 51w89 binding to CD73 was 20.45 μmol/L. Encouraged by these results at the molecular level, we next evaluated the inhibitory effect of 51w89 against CD73 in MDA-MB-231 cells. The results show that the IC50 of 51w89 against CD73 in MDA-MB-231 cells was 17.70 μmol/L, which was close to the IC50 value at the molecular level. Subsequently, we proved the role of CD73 in the migration of MDA-MB-231 cells through scratch tests, transwell tests and siRNA tests, and found that 51w89 could inhibit the migration of MDA-MB-231 cells. Moreover, we found that 51w89 could limit the inhibitory effect of AMP on CD8+ T cells. Taken together, we speculated that 51w89 could be used as a potent small-molecule inhibitor of CD73 for subsequent antitumor research.
[Abstract](33) [FullText HTML](23) [PDF 4224KB](10)
Abstract:
The paper establishes the function of time between the change of water temperature of the gas water heater through the establishment of heat transfer model. In addition, the function of water temperature of hot water pipe is calculated and the importance of intelligent water pump system for water saving is analyzed. In particular, the integration of non-elementary functions by curve fitting is worth reference to engineering technicians. Finally, several practical methods to shorten the waiting time of hot water are given: 1. Improve the outlet temperature of gas water heater; 2. Install hot water storage device in the bathroom; 3. Install gas water heater near the bathroom; 4. Hot water pipe add insulation material and hot water circulation pump; 5. Accelerate the pumping speed of hot water circulation pump; 6. Fully realize zero hot water waiting need to open the gas water heater and circulation pump, keep the hot water pipe without water.
[Abstract](12) [FullText HTML](6) [PDF 3815KB](3)
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Single-walled carbon nanotubes (SWCNTs) can combine with proteins in organisms, creating potential biosafety risks. In this paper, SWCNTs and two separated single-chiral single-walled carbon nanotubes ((6,5)-SWCNT, (8,3)-SWCNT) were combined with Bovine hemoglobin (BHb) respectively, and SWCNTs interaction with BHb were analyzed by fluorescence spectroscopy. The results showed that the fluorescence quenching of BHb by SWCNTs was resulted from the combination of dynamic quenching and static quenching. The fluorescence quenching of BHb by single chiral (6,5)-SWCNT and (8,3)-SWCNT was static quenching. The order of the binding constants of BHb and different SWCNTs was as follows: SWCNTs>(6,5)-SWCNT>(8,3)-SWCNT. Van der Waals force, hydrogen bond and hydrophobic interaction were the main forces in the interaction. The result of this article will assist the revealing of the potential biosafety risks of SWCNTs.
Abstract:
The service life of metalworking fluids can be shortened by existence of microorganism, and it is necessary to explore the composition of microbial communities in metalworking fluids. Three different methods were measured to determine the best one to separate microorganisms from metal working fluids. The concentration of microorganisms can be increased by the mikrocount combi method which has the optimal separation result. Under the help of Illumina MiSeq high-throughput sequencing, the composition of the microbial diversity of metalworking fluid samples at the 6 levels of phylum, class, order, family, genus, and species were completed respectively. Moreover, bacteria were detected in six groups of samples, while fungus were discovered in only two groups. Meanwhile, it was easier for bacteria to thrive in metalworking fluids than fungi, and fungi was only existed in samples with high bacterial contamination. A total of 2 phyla, 2 classes, 5 orders, 6 families, 10 genera and 14 species of bacteria were detected in all samples, while 4 phyla, 8 classes, 10 orders, 14 families, 15 genera and 17 species of fungi were also detected, which means that the fungal diversity is more abundant. Citrobacter_freundii_g_Citrobacter, unclassified_g_Citrobacter, unclassified_f_Enterobacteriaceae were identified as the dominant bacteria, and most of bacteria detected were Gram-negative. The composition of the metalworking fluid will affect the type of bacteria. All detected bacteria can destroy the stability of the metal working fluid through different ways, which shorten its service life. The dominant fungi were unclassified_k_Fungi and Fusarium_petroliphilum. The health of operators will be harmed by metalworking fluids with microbial contamination.

Abstract:
Clostridium histolyticum collagenase H (ColH) recognizes the Y-Gly of collagen and hydrolyzes it into small peptides. The high molecular weight ColH(116 kDa) secreting strain was successfully constructed by fusing colH gene with signal peptide sequence of outer membrane protein A. In this study, we found that the secretion of ColH was effected by the position of the signal peptide at the N-terminal, and the presence of excess amino acid fragments at the N-terminal significantly reduced the secretion function of the signal peptide-guided collagenase. Orthogonal experiment and single factor experiment were used to optimize the induction conditions and medium additives to improve the secretory expression. Under the conditions of inducing temperature of 25 ℃, the cell density(OD600) of 0.9, IPTG concentration of 0.1 mmol/L, liquid volume of 20%, magnesium ion concentration of 10 mmol/L, and 2% glycine added at 2.5 h after induction, the highest extracellular collagenase activity was 0.68 U/mL after induction for 20 h, which was 38.1 times of that before optimization, and the secretory expression level was greatly increased. Glycine added into the culture medium is a common strategy to promote the secretion of recombinant protein. Experimental results showed that the amount and time of glycine added after induction had the greatest influence on the secretion of collagenase. The addition of calcium and magnesium ions in the medium can promote the growth of E.coli, the results also showed that but only the addition of magnesium ion can promote the secretion of ColH.
[Abstract](14) [FullText HTML](19) [PDF 4594KB](0)
Abstract:
Gasification temperature is the most important operating parameter of entrained flow gasifier. However, the coal gasifier unit lacks long-term and reliable gasification temperature measurement. In order to monitor the operation state of entrained flow gasifier in real time and ensure the safe and stable operation of gasification system, measurable data such as gasifier cooling system and reaction system are collected. The outlet temperature of gasifier was predicted by using theoretical calculation model and BP neural based on genetic algorithm model(GABP). The results of prediction were compared with industrial measurement data. The results show that the outlet temperature of gasifier can be obtained by theoretical calculation of quench system, but the accuracy and stability of prediction results are poor due to low sensitivity of measurement parameters. GABP neural network model can greatly improve the prediction performance. Base on the gasification chamber parameters, the prediction error is large due to the fluctuation of coal water slurry flow rate and the lack of coal property data. Taking quench system parameters as the input of GABP neural network can greatly improve the prediction accuracy, and the absolute value of the prediction error is less than 15 K. Both of the train set and verification set have excellent prediction results, the average absolute errors of GABP model with quench system parameters as input are about 5 K. GABP model has good performances in the face of complex working conditions. Carry out predictions under different conditions, the results under steady and variable coal load have good prediction precision and stability, meet the demand of online monitoring of gasifier temperature.
[Abstract](12) [FullText HTML](13) [PDF 3672KB](1)
Abstract:
In the task of Chinese named entity recognition, word information fusion vocabulary information can enrich text features, but a word may correspond to multiple candidate words, which is prone to vocabulary conflict. The fusion of irrelevant vocabulary information will affect the recognition effect of the model. In this paper, a Chinese named entity recognition method based on hierarchical adjustment of dictionary information is proposed. All potential words are layered according to the word length, and the weight of low-level words is adjusted through high-level word feedback to retain more useful information, so as to alleviate the problem of semantic deviation and reduce the impact of word conflict. Then, the word information is spliced into the word information to enhance the text feature representation. Experiments are carried out on resume and Weibo data sets. The experimental results show that this method has better effect than the traditional method.
[Abstract](10) [FullText HTML](21) [PDF 3526KB](1)
Abstract:
Recently, the method of combining BERT(Bidirectional Encoder Representations from Transformers) and neural network model has been widely used in the field of Chinese medical named entity recognition. However, BERT was segmented at the granularity of characters in Chinese, and Chinese word segmentation was not considered. And neural network models were often locally unstable, and even small disturbances may mislead them, resulting in poor model robustness. In order to solve these two problems, a Chinese medical named entity recognition model based on RoBERTa(A Robustly Optimized BERT Pre-training Approach) and adversarial training, namely AT-RBC (Adversarial Training with RoBERTa-wwm-ext-large+BiLSTM+CRF), was proposed. Firstly, use RoBERTa-wwm-ext-large(A Robustly Optimized BERT Pre-training Approach-whole word masking-extended data-large) pre-trained model to obtain initial vector representation of input text. Secondly, some perturbations were added to the initial vector representation to generate adversarial samples. Finally, the initial vector representation and adversarial samples were sequentially inputted to bidirectional long short-term memory network and conditional random field to obtain the final prediction. Experiments on the CCKS 2019 data set show that the F1 score of the improved model reaches 88.96%, achieving good results. Experiments were also conducted on the Resume data set, and the F1 value reaches 97.14%, which proved the effectiveness of the improved model.
Abstract:
Microservice architecture builds applications as independent components and runs each application process as a service. The decoupling and independent development of microservices make the flexibility and speed of software update possible. Meanwhile, it also brings many problems, such as service decomposition, transmission delay, and reliability. This paper uses PrT net (Predicated Petri net) to model the microservice composition by event bus to establish the dependency among microservices, transmission latency, and reliability of microservice composition. The event listening mechanism is a delegated event handling mechanism. When a specified event occurs in the event source, it will notify the specified event listener to perform the corresponding operation. For event-based communication, when the event occurs, the microservice will publish the event. Then, we propose a BP (primary and backup) replication allocation strategy meeting the sub-deadline through microservice instances of the primary and backup replica to improve the overall reliability of microservice composition. In this paper, the PB replica deployment strategy is analyzed from two cases: single task and multi task PB replica. By deploying the primary and backup replica of the task in different containers or host resources, the goal of improving the reliability of cloud applications has been achieved. The related properties of constructed models are established by using the related theories of PrT net. Through semantic and syntax analysis, the correctness of the PrT net modeling is analyzed. Finally, several experiments are carried out to verify the effectiveness of the modeling and analysis method. Experimental results show that the proposed microservice reliability strategy is effective by taking the guarantee ratio as the reliability parameter.
Abstract:
Exhaled breath condensate (EBC) is a kind of respiratory lining fluid, which is easy to collect and non-invasive. EBC was considered to be the ideal sample for the study of pulmonary diseases. Proteomics is one of the novel methods to develop disease biomarkers, and the proteomics of EBC is widely studied due to its tremendous biological potential. It can reflect different disease status by analyzing the components of EBC protein, explore potential biomarkers, and improve the diagnostic ability of lung cancer and other diseases. In this study, an EBC proteomics method based on data independent acquisition (DIA) was established to overcome the disadvantage of low protein concentration of EBC, and 2052 proteins were identified. On this basis, the weighted gene co-expression network analysis (WGCNA) was carried out. WGCNA is a novel bioinformatic analysis technology, which allows multiple analysis of different omics information. A total of 61 hub proteins were screened by cluster analysis, and the hub proteins were analyzed by gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interactions (PPIs) analysis. The results showed that the hub proteins mainly existed in the nucleus and cytoplasm, and participated in the metabolic pathways related to human diseases, which indicated that the hub proteins could reflect the disease status and hold the potential to be biomarkers. In conclusion, the DIA-based EBC proteomics combined with WGCNA analysis, could effectively explore the potential biological functions of EBC, which could be applied to a large-scale clinical research and contribute to the exploration of biomarkers in the future.
Abstract:
The hydrodynamics and the suspension state of the Mg(OH)2 particles was studied by multiple reference frame (MRF) and the standard k – ε model in Fluent software. The effects on impeller height and stirring speed were discussed. The simulated results showed that the appropriate increase of impeller installation height was benefit for the settling and discharge of the coarse particles. which mainly attributed to the decrease of flow velocity in the bottom zone of the crystallizer. However, when the installation height was too high, the flow velocity in the baffle cylinder was increased, which caused the nonuniformity of the flow velocity. The low stirring speed was disadvantageous for the suspension of Mg(OH)2 particles. With the increasing stirring speed, the nonuniformity of the flow velocity in the settling zone was significantly improved and the particles in the crystallizer were more uniform in suspension state. The optimal installation height of impeller and stirring rate were determined to be 3.3m and 70rpm, respectively. The related results provided theoretical support for the structure and operation optimization of DTB type crystallizer for the project of 130,000 t per year magnesium hydroxide production.
[Abstract](11) [FullText HTML](28) [PDF 3954KB](1)
Abstract:
Organic molecules with fluorine usually possess unique physical, chemical, and biological properties, thus playing an important role in material science and pharmaceutical chemistry. Meanwhile, functionalization of organic molecules via C−H activation has drawn extremely broad attention in recent years. Therefore, C−H fluorination for the synthesis of fluorine-containing molecules is a very important and challenging project in organic synthesis. Directing groups such as pyridine and amide have been utilized to facilitate C−H fluorinations, however, most of the directing groups are usually installed into the substrates before the fluorination and uninstalled after the fluorination, thus reducing the step economy of the reaction. Carboxylic group is ubiquitous in organic molecules and it can dramatically increase the step economy if it is employed as native directing group. Indeed, it has been utilized as directing group in C−H activations such as arylation, olefination, acetoxylation. While carboxylic group directed C−H fluorination remains a challenge. In this research, by using the carboxylic group as a directing group, after optimization of the reaction conditions including additive, solvent, fluorination reagent and ligand, we realized the Pd-catalyzed ortho-C(sp2)-H fluorination of benzoic acid, which affords the ortho-mono-fluorinated product in up to 13% isolated yield. A pyridone ligand with a nitro group at the C-5 position and an amide group at the C-3 position was found to be able to promote this transformation. We believe these results will benefit future development of carboxylic group directed C−H fluorination.
[Abstract](194) [FullText HTML](47) [PDF 4078KB](31)
Abstract:
This paper investigates the periodic event-triggered sliding mode control (SMC) of the permanent magnet synchronous motor (PMSM). The periodic event-triggered mechanism is introduced to decide whether to send the system state to the controller through the network for saving communication resources. Firstly, the sliding mode controller is synthesized based on the traditional event-triggered mechanism. By designing the event-triggered conditions, sufficient criteria for the existence of the actual sliding mode are provided, and the robust actual stability of the controlled system is guaranteed. And then, the SMC problem is considered for the periodic event-triggered scheme. Considering the characteristics of the periodic event-triggered mechanism, the upper bound of the error between two adjacent sampling times is estimated. Selection criteria of the sampling period and the control gain are provided for ensuring the robust actual stability of the controlled system and the existence of the practical sliding mode. Finally, simulation results illustrate the effectiveness of the proposed controller.
[Abstract](152) [FullText HTML](127) [PDF 819KB](13)
Abstract:
The effects of temperature, pressure and feed ratio on the methane reformer were studied based on a kinetic model. The conversion rates of CH4, H2O and CO2 all increase with the increase of temperature at p=3.2 MPa. Compared with the steam reforming of methane, the reaction temperature required for the conversion of CH4 and CO2 is higher and the conversion of CO2 begins at 650 ℃.The effect of temperature on the reaction rate of dry reforming of methane is more significant at relatively high reaction temperature and pressure. With the increase of pressure, the conversion rates of CH4, H2O and CO2 decrease rapidly. When the pressure reaches 3.5 MPa, the conversion rates of CH4, H2O and CO2 are all less than 40%. However, the influence of pressure on n(H2)/n(CO) is not obvious. The increase of CO2 in the reaction system is beneficial to improve the conversion rate of CH4, but significantly reduces the conversion rate of H2O at p=3.2 MPa.CO2 conversion increases rapidly at first and then keeps stable with the increase of n(CO2)/n(CH4). CH4 and H2O conversion both increase with the increase of n(H2O)/n(CH4). The analysis of feed ratio and reaction temperature showed that n(H2)/n(CO) can be adjusted by adjusting the temperature and the relative concentration of H2O and CO2 in the feed gas to carry out the subsequent industrial production.
[Abstract](130) [FullText HTML](122) [PDF 713KB](3)
Abstract:
Power-gating-aware design has been an active area of research in the last decade, aiming at reducing power dissipation while meeting a desired system throughput. In this study, an algorithm integrating both scheduling and binding processes is developed with the fine-grained functional unit (FU) power-gating technique, to achieve maximum leakage energy reduction. Firstly, the break-even points of FUs are analyzed, and the leakage energy reduction problem is formulated as an idle interval partition problem. Secondly, the idle interval length of each possible scheduling result is estimated. Finally, operations are scheduled to the control steps with maximization of the leakage energy saving. The experimental results show that our proposed algorithms can significantly reduce leakage energy while maintaining the system performance and circuit area, and therefore, provides a suit-able design solution for the circuits used in satellites.
[Abstract](531) [FullText HTML](222) [PDF 775KB](7)
Abstract:
Cucurbiturils (CB[n]s) is a hollow macrocyclic molecule formed by the condensation of glycoluril and formaldehyde under acidic conditions. The glycoluril units are linked together by methylene bridges, and cucurbiturils have hydrophobic cavity and polar carbonyl groups on both portals. Cucurbituril has strong inclusion ability for positively charged guest molecules such as protonated organic amines, pyridinium, and viologen. The study of the inclusion behaviors of aryl substituted viologen with cucurbit[8]uril urea (CB[8]) is of great significance for the further construction of related supramolecular polymers and even stimulus responsive materials. In this work, asymmetric 1-ethyl-1'-benzyl-4,4'-bipyridine bromide (EBV) was used to investigate its inclusion behaviors with CB[8] in aqueous solution by means of 1H-NMR spectroscopy, isothermal titration calorimetry (ITC) and high resolution electrospray ionization mass spectrometry (ESI-HRMS). The results show that the benzyl unit of EBV will firstly enter into the cavity of CB[8] to form a 1∶1 inclusion complex, and a 1∶2 supramolecular system where one CB[8] molecule encircles two benzyl groups will ultimately form. The constant of the first 1∶1 inclusion process is 1.65(±1.22)×107 M−1, the corresponding ΔH and −TΔS are −26.2(±1.26) kJ/mol and 14.6 kJ/mol, respectively. and the apparent inclusion constant of the whole process is 1.34(±0.193)×1013 M−2, the corresponding ΔH and −TΔS are −64.4(±3.19) kJ/mol and −9.43 kJ/mol, respectively, indicating that the host-guest complexation is driven by both enthalpy and entropy.
[Abstract](517) [FullText HTML](442) [PDF 1127KB](18)
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The effects of reaction conditions on hydrogen production from methanol steam reforming were discussed. The experimental results showed that the optimum temperature of the reaction was about 240 ℃. The high temperature would make the CO selectivity higher, and the low temperature would make the conversion of CH3OH lower.When H2O/CH3OH molar ratio increases, the conversion of CH3OH increases and the selectivity of CO decreases. However, if H2O/CH3OH molar ratio is too high, more energy will be consumed.Under the premise of ensuring the conversion rate of CH3OH, the reaction efficiency can be improved by appropriately increasing the liquid hourly space velocity of feed liquid.The Langmuir-Hinshelwood two-rate dynamics model equation was used to fit the experimental data of intrinsic dynamics. The calculated values of molar flow rates of CO and CO2 in the gas products at the reactor outlet were in good agreement with the experimental values, and the two-rate model could be applied.The deactivation of CuO/ZnO/Al2O3 modified catalysts at 200 ℃ and 300 ℃ was investigated. The catalysts were characterized by BET, XRF, XRD and CO-TPD, the results showed that the main reasons for the deactivation of the catalysts were besides hot sintering. The reduction of specific surface area, the reduction of mesoporous ratio, CuO loss and the increase of CuO grain size are also the specific reasons for catalyst deactivation. The high content of CO produced in the high temperature has no obvious effect on catalyst deactivation.
[Abstract](930) [FullText HTML](499) [PDF 2518KB](14)
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