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](22) [FullText HTML](5) [PDF 4113KB](3)
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](499) [FullText HTML](369) [PDF 3771KB](3)
Abstract:
Experiments on dense phase pneumatic conveying of pulverized coal were carried out in the self-built pneumatic conveying facility with a Industrial pipe diameter of 50 mm. The gas-solid two-phase flow characteristics through the bend were studied. Firstly, With the help of Enick and Klinzing model, the entrance length of gas-solid two-phase flow in a bend outlet is calculated. It is found that electrical capacitance tomography (ECT) is in the underdeveloped area, where the flow is affected by the bend. The flow patterns of the outlet section of the bend were analyzed in the means of ECT, and it was found that the flow pattern changed from the packed bed flow to the unstable/stable plug flow with the increase of the superficial gas velocity. Due to the influence of inertial force and centrifugal force, there was an obvious radial distribution in the concentration of the pipe section when the pulverized coal flowed through the bend, while the coal concentration on lateral wall surface was relatively high. Next, regression analysis of experimental data is carried out by using pressure drop model and dimensional analysis method, a pressure drop model of pulverized coal dense phase pneumatic conveying bend was established by providing errors most smaller than ±10%. Finally, based on micro element analysis and pressure drop distribution along the bend, the distribution characteristics of pulverized coal concentration along the bend were obtained. The research in this work can provide important guiding significance in reducing the wear of bend.
Abstract:
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](23) [FullText HTML](14) [PDF 0KB](3)
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](64) [FullText HTML](30) [PDF 0KB](5)
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](73) [FullText HTML](23) [PDF 0KB](5)
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](57) [FullText HTML](38) [PDF 0KB](5)
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](46) [FullText HTML](32) [PDF 0KB](2)
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](65) [FullText HTML](35) [PDF 0KB](38)
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](43) [FullText HTML](23) [PDF 0KB](11)
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](90) [FullText HTML](42) [PDF 0KB](15)
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](347) [FullText HTML](192) [PDF 0KB](12)
Abstract:
With the development of target detection algorithms, the intrusion detection based on surveillance video has attracted more and more attentions. Due to the complexity of the traditional target detection algorithm and the difficulty in detecting in real time in the scene of limited computing power and storage space, this paper proposes a lightweight intrusion detection algorithm. Firstly, the preliminary screening target is extracted through the adaptive update rate of the mixed Gaussian foreground extraction algorithm. And then, the preliminary screening target is identified based on the improved residual squeeze network (R-SqueezeNet) classification. It is shown via experimental results that, without reducing the detection accuracy, the proposed algorithm can increase the detection speed by an average of 30 times compared with the traditional algorithm, and the model size is reduced to 1/40 of YOLOv3-tiny.
[Abstract](66) [FullText HTML](31) [PDF 0KB](6)
Abstract:
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](63) [FullText HTML](24) [PDF 0KB](12)
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](46) [FullText HTML](44) [PDF 1286KB](7)
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](42) [FullText HTML](24) [PDF 873KB](4)
Abstract:
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](40) [FullText HTML](28) [PDF 1494KB](2)
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](82) [FullText HTML](41) [PDF 1132KB](8)
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](49) [FullText HTML](40) [PDF 1004KB](2)
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](35) [FullText HTML](20) [PDF 1744KB](2)
Abstract:
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](38) [FullText HTML](27) [PDF 733KB](3)
Abstract:
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](88) [FullText HTML](35) [PDF 5572KB](14)
Abstract:
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](78) [FullText HTML](33) [PDF 2249KB](12)
Abstract:
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](50) [FullText HTML](24) [PDF 1449KB](1)
Abstract:
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](53) [FullText HTML](37) [PDF 1304KB](1)
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[Abstract](53) [FullText HTML](37) [PDF 1768KB](0)
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The contact mechanical properties and fatigue life of plug sampling valve are studied in this paper. The mechanical analysis of the installation and sampling process of the plug sampling valve is carried out by applying the relevant mechanical theories. A theoretical model is established for the contact stress calculation of the contact surface in the installation process. A calculation model is established for the radial contact stress of the plug in the working process of the plug sampling valve. A calculation model is established for calculating the contact stress distribution of three typical cross sections of the plug surface. The contact stress distribution of the plug during sampling is verified by finite element method. And then, with a specific example, the variation and distribution of contact stress at each point on the plug surface during the sampling process are numerically calculated and studied. Based on the basic theory of fatigue life, the influences of pipeline working pressure and the amount of pressing in the process of plug installation on the fatigue life of plug are studied.
[Abstract](49) [FullText HTML](19) [PDF 1481KB](5)
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Bubbling contact scrubbing is an important method for the separation and purification of gas-solid wet scrubbing. Dust-containing bubbles are the unit dust collectors of bubbling contact scrubbing, in-depth research on the operating characteristics of dust-containing bubbles will provide important theoretical support for the efficient removal of fine particles and the optimal design of bubbling scrubbers. Based on the volume of fluid-discrete phase model (VOF-DPM) method, the rising process of the dust-containing single bubble and the parallel dust-containing double bubble in the initial static liquid and the effect on the particle removal rate are studied. Results show that smaller bubbles have complex deformations and irregular oscillations, with higher deformation strength; when the bubble size is greater than 12 mm, the shape change is suppressed, the rising bubble deformation has an enhanced effect on the removal of solid particles, small size bubbles have a high particle removal rate due to complex morphological changes. The removal rate of different size particles in different size bubbles is significantly different, and there is a suitable bubble size range for efficient removal. When the initial distance between parallel dust-bearing double bubbles is constant, their ascending process in the initial still liquid presents a "close-separate-close" cycle. The effect of the interaction in the process on particle removal is different within different size parallel double bubbles, the bubble interaction can enhance the particle removal within a certain size range. The 8 mm-10 mm double bubble interaction strengthens the removal of 1 μm particles, while the 12 mm-14 mm double bubble interaction weakens the removal of 1 μm particles.
[Abstract](57) [FullText HTML](41) [PDF 772KB](5)
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The paper generated a modified AAV serotype, named AAVc1, by inserting an oligopeptide PGPSPAD after N573 of the AAV5 capsid, which exhibited better muscle tropism than AAV5, 8 and 9 both in vitro and in vivo. The number of green fluorescence protein (GFP) positive C2C12 myoblast cells in AAVc1 group was 25% higher than AAV9 group, almost twice the AAV8 group and three times of the AAV5 group. The percentage of both type I and type II skeletal muscle fibers infected by AAVc1 was also 20-30% higher than those infected by AAV9, implicating better transduction efficiency of AAVc1 in murine muscles. Furthermore, we found that the neutralizing antibodies (Nabs) present in rhesus monkey sera against AAVc1 were less than those against AAV9, indicating less immune response against AAVc1 than AAV9. Altogether, these observations illuminate potential advantages of AAVc1 over wild type AAV serotypes for gene therapy.
[Abstract](67) [FullText HTML](45) [PDF 1372KB](3)
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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](68) [FullText HTML](38) [PDF 842KB](8)
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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](55) [FullText HTML](29) [PDF 1115KB](4)
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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](46) [FullText HTML](18) [PDF 808KB](3)
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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](48) [FullText HTML](29) [PDF 1023KB](2)
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Introducing inorganic materials, such as boron nitride (BN), with good thermal conductivity and insulation properties into polymer materials can significantly enhance the thermal conductivity of composites. For thermoplastic composites, controlling the orderly distribution and connection of thermal conductivity fillers in the matrix during machining is the key to improving thermal conductivity. In this study, the BN/Nano-Al2O3/Micro-Al2O3/PA6/PP composite with high thermal conductivity was prepared by introducing BN sheet and two sizes of alumina balls (Nano-Al2O3 and Micro-Al2O3) into nylon 6/polypropylene (PA6/PP) alloy by two-step method. By means of the shear force during the processing and the volume repulsion of PP phase, it is found that BN sheets and Al2O3 spheres are uniformly dispersed, oriented and connected in the PA6 phase. Nano-Al2O3 of small size inserts into the gaps between BN sheets, while Micro-Al2O3 of large size inserts and changes the orientation of BN sheets. Nano-Al2O3 and Micro-Al2O3 common auxiliary BN to form the three-dimensional heat transfer filler network, reducing the anisotropy of thermal conductivity. When the mass ratio of Nano-Al2O3∶Micro-Al2O3 is 7.5∶7.5, the thermal conductivity of BN-25/Nano-Al2O3-7.5/Micro-Al2O3-7.5/PA6/PP composite reaches the maximum, the in-plane thermal conductivity is 1.46 Wm−1·K−1, the through-plane thermal conductivity is 1.39 Wm−1·K−1. Meanwhile, the introduction of the two kinds of Al2O3 greatly increases the tensile modulus of the composite. In addition, in the application of heat dissipation experiment, the composite reduces the temperature rise range of LED under working conditions, which has a good applicability.
[Abstract](67) [FullText HTML](30) [PDF 1093KB](8)
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Resveratrol, a secondary metabolite of stilbene, is synthesized by the L-Phenylalanine pathway in plants. Under external conditions, various plants are used to produce resveratrol. However, the most commonly used plant cell cultures for the production of stilbene are still from grapes. In this paper, an optimal technology for the production of resveratrol from suspension cell of Vitis vinifera L. was established. In response to cell growth and resveratrol biosynthesis, the effects of different carbon sources, nitrogen sources, precursors, inducers and hormones on resveratrol synthesis in the grape cells were studied by single factor test, Plackett-Burman test and response surface methodology. The results showed that the optimal nutrient conditions of suspension cells were as follows: B5 medium 5 g/L, sucrose 37.5 g/L, yeast extract 800 mg/L, phenylalanine 100 mg/L, methyl jasmonate 80 μmol/L, 2, 4-chlorophenoxyacetic acid 4.1 mg/L, 6-benzylaminopurine 0.2 mg/L, polyvinylpyrrolidone 1g/L. Under this condition, the highest expression of resveratrol was 3026.64 ± 56 μg/g in cell suspension culture at 26 °C for 7 days, which was 51.13 times higher than that before optimization, the optimal nutrient conditions can significantly promote the synthesis of resveratrol. In this study, the nutrient composition of suspension cells of Vitis vinifera was studied in detail, and the optimal culture conditions for the growth and resveratrol synthesis of the suspension cells were determined, on the one hand, it provides a basis for analyzing the function of grape suspension cells, and on the other hand, it lays a good foundation for enlarging the production of resveratrol and other substances.
[Abstract](43) [FullText HTML](35) [PDF 938KB](7)
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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](46) [FullText HTML](36) [PDF 731KB](2)
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Give a graph $G$, let $E\left(G\right)$ denoted the set of edges and ${d}_{G}\left(v\right)$ the degree of the vertex $v$, respectively. For an edge $e=uv$, the general sum-connectivity index ${\chi }_{\alpha }\left(e\right)={({d}_{G}\left(u\right)+{d}_{G}(v\left)\right)}^{\alpha }$, in which $\alpha$ is any real number. Before taking the product of two simple connected graphs $G$ and $H$, we first perform ${\rm{S}},{\rm{R}},{\rm{Q}},{\rm{T}}$ operations on the graph $H$, denoted as $F\left(H\right)$, in which $F\in \{S, R, Q, T\}$, then take the lexicographical product of graphs $G$ and $F\left(H\right)$, we give the sharp bounds on general sum-connectivity index of graphs for operations based on lexicographic product, and these bounds are sharp.
[Abstract](38) [FullText HTML](46) [PDF 965KB](2)
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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](32) [FullText HTML](36) [PDF 1275KB](0)
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Using the VUMAT subroutine embedding method, the stress-strain relationship in the elastic deformation stage of the polyimide polymer material is described, and the effect of the cutting process parameters on the cutting force and cutting force of the polyimide milling process is analyzed through the three-dimensional thermal-mechanical coupling finite element model. The influence law of temperature and chip morphology, the result is that as the feed rate increases, the simulated cutting force and cutting temperature will increase, and the degree of banding of chips will become serious. Subsequently, the cutting experiment was used, and the difference between the simulation and the experiment cutting force was up to 18%, and the difference in cutting temperature was up to 23%. When the feed rate increases, the degree of chip curling increases and the surface texture becomes deeper, and when the feed rate is 0.15 mm/r and 0.45 mm/r, the chip edge tears. Defects such as adhesion, drawing, and layup of tiny chips on the machined surface of the workpiece cause the material microporous flow channel to be blocked. This constitutive model has certain universality to polymer materials. The validity and accuracy of the simulation model have been verified, and the optimal milling process parameters for polyimide have been obtained: milling depth ap = 1 mm, milling speed v = 75 (m/min), and feed amount f = 0.2 ~0.3 (mm/r).
[Abstract](37) [FullText HTML](27) [PDF 909KB](1)
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This paper aims to explore the efficiency and function of pH sensitive polymer micelles in targeted delivery and release of Shiga toxin 1 subunit A to HeLa cells. Recombinantly expressed the Shiga toxin 1 A subunit Stx1A and the attenuated variant A subunit Mu-Stx1A in Escherichia coli, and used pH-sensitive polymer micelles PEG8-PDPA100-PEG8 to carry them to the cervical cancer cells Hela. In vitro activity test showed that the recombinant protein Stx1A could significantly inhibit protein synthesis, but the attenuated mutant Mu-Stx1A did not. Stx1A and Mu-Stx1A were successfully transported into HeLa cells by polymeric micelles, and the transfection efficiency increased with the increase of protein concentration. After Stx1A micelle entered the cells, it successfully released the active subunit Stx1A, leading to cytopathy and apoptosis, which became more evident with the concentration of Stx1A. Experiments have proved the polymer micelles can successfully encapsulate, transport and stably release complete Stx1A molecules into tumor cells, exerting toxic functions to induce programmed cell death. Polymer micelles can play an effective role in protein transport, which provides a theoretical basis for the subsequent research and application of Shiga toxin 1 subunit A in tumor therapy.
[Abstract](48) [FullText HTML](38) [PDF 1592KB](3)
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Physical Unclonable Function (PUF) circuits show good resistance to intrusive physical attacks. However, with the continuous improvement of chip integration and IoT (Internet of Things) technology, model attacks and limited energy budgets not only seriously threaten the security of PUF circuits, but also limit the energy efficiency of PUF circuits. In this paper, a delayed PUF structure based on dynamic subthreshold logic is proposed. First, the structure utilizes a sub-threshold voltage control circuit to form the nonlinear part of the output function. Then the initial value of the output voltage is modified by charge sharing effect, hence the nonlinear output function varies with the challenge input. Finally, the PUF response is outputted by a dynamic subthreshold arbiter. The proposed PUF is designed in TSMC 65 nm CMOS Technology and verified by HSPICE tool. Experimental results show that it can effectively resist model attacks and has an energy consumption of 0.23pJ/bit which is 23.3% lower than similar circuits.
[Abstract](74) [FullText HTML](38) [PDF 1049KB](9)
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[Abstract](42) [FullText HTML](29) [PDF 721KB](2)
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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 is 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 has been a research hotspot in this field at home and abroad. In order to reduce the sintering temperature of BaTiO3 ceramics, many methods have 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 have been investigated. The results show that co-doping of CuO, B2O3 and Li2O can 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 2h 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 growth rapidly. The low eutectic phase and solid solution reaction during 0.7wt%CuO-1.5wt%B2O3-0.3wt%Li2O (BCL) co-doping were the main reasons for decreasing sintering temperature.
[Abstract](60) [FullText HTML](30) [PDF 995KB](9)
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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. Among them, Music Emotion Recognition (MER) is an important research direction, which has great research value for video soundtracks, but there are relatively few researches on music emotion recognition. Some researchers combine Mel Frequency Cepstral coefficient (MFCC) and Residual Phase (RP) to extract music emotional features and improve classification accuracy. However, training models in traditional deep learning takes time longer. In order to improve the efficiency of feature mining of music emotional features, this paper uses the combination of MFCC and RP weighting to extract features. At the same time, in order to shorten the training time of the model, this article combines the Long Short-Term Memory (LSTM) and the Broad Learning System (BLS) together to build a new wide and deep learning network, named LSTM-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, 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, and the advantages of the two are combined to obtain the LSTM-BLS network model for the task of music emotion classification. The experimental results on the Emotion dataset show that the algorithm in this paper has achieved higher recognition accuracy than other complex networks and improved training efficiency, achieved great experimental results, and provided new feasible ideas for the development of music emotion recognition.
[Abstract](55) [FullText HTML](41) [PDF 881KB](2)
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The beak of Dosidicus gigas is a feeding organ, which is completely composed of organic matter. The rostrum of the beak has a strong hardness and mechanical strength. The mechanical strength gradually decreases from the rostrum to the wing and. There is a significant gradient change. And the degree of pigmentation is gradually becoming shallower. Inspired by the gradient of the mechanical properties of stalk squid, the paper used chitosan, dopa, sodium periodate and other organic materials to simulate a material similar to the mechanical properties of keratin. The material can eliminate the interface, and its mechanical properties are spatially variable. And this material feature can be applied to the industry in the future.
[Abstract](40) [FullText HTML](46) [PDF 1442KB](11)
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Breast cancer (BRCA) is the most frequently diagnosed cancer in females worldwide. HER2-positive (HER2+) breast cancer accounts for 15%-20% of total breast cancer, which related to HER2 overexpression and rapid deteriorations of cancer. Lapatinib is a dual EGFR/HER2 inhibitor for HER2+ breast cancer therapy, while the drug resistance is main reason for treatment failure. As a critical component of the translational machinery, eukaryotic translation elongation factor 1 alpha 2 (EEF1A2) was significantly upregulated to promote the cancer progression in various tumors like breast tumor. This study explored the potential relation of EEF1A2 and HER2 in breast cancer. The EEF1A2 mRNA expressions in human breast cancer tissues were analyzed by TCGA online data. The differences of EEF1A2 mRNA levels and its impacts to prognosis between HER2-positive breast cancer tissues and HER2-negative ones were further detected. The EEF1A2-knockdown plasmid was constructed via shRNA for the further transfection. Subsequently, we explored the proliferation, metastasis and apoptosis of SKBR3 and MDA-MB-453, the HER2-positive breast cancer cells, treated with EEF1A2-knockdown and lapatinib via MTT, colony formation, Transwell assay and apoptosis assay, respectively. Results of TCGA analysis showed EEF1A2 mRNA overexpressed in breast cancer tissues. Most importantly, EEF1A2 mRNA levels in HER2-positive breast cancer tissues were significantly higher than that in HER2-negative subtype. The higher level of EEF1A2 mRNA correlated with the lower overall survival in HER2-positive breast cancer. While the EEF1A2-knockdown enhanced the lapatinib’s impacts on proliferation, migration, invasion and apoptosis of SKBR3 and MDA-MB-453 in vitro. Western blot showed the EEF1A2-knockdown augmented the inhibition on HER2/AKT pathway induced by lapatinib in cells. Thus, we suggested that EEF1A2 could be a potential target to improve the therapy of HER2-positive breast cancer treated with lapatinib.
[Abstract](69) [FullText HTML](46) [PDF 939KB](7)
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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](52) [FullText HTML](35) [PDF 886KB](2)
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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](64) [FullText HTML](40) [PDF 706KB](4)
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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 re-duce 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](52) [FullText HTML](46) [PDF 960KB](3)
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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](1033) [FullText HTML](286) [PDF 1117KB](166)
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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.
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[Abstract](278) [FullText HTML](190) [PDF 3738KB](7)
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In this paper, the process models of the shale gas chemical looping reforming to methanol combined with the solid oxide fuel cell for power generation is established by the means of the system decomposition, unit modeling, and process simulation. The technical analysis of the new process is carried out through technical indexes, which consists of four aspects of raw material consumption, product output, process energy consumption, and exergy efficiency. In this paper, the efficient utilization of the shale gas resource is realized through the chemical looping reforming for simultaneously producing the syngas-hydrogen and then syngas used for methanol synthesis. After adjusting the composition of the syngas for methanol production, the remaining hydrogen is fueled to solid oxide fuel cell unit and the purge gas of the methanol synthesis is fueled to chemical looping combustion unit for power generation, by which the self-sufficiency as well as surplus of the electric energy can be achieved. Through the mass and energy integration between chemical looping reforming, chemical looping combustion, methanol synthesis, and solid oxide fuel cell, the technical and environmental performance of the shale gas chemical looping reforming to methanol combined with solid oxide fuel cell process can be significantly improved. This paper also discusses the influence of different methane conversion rates on the technical performance of the new process. In a word, the exergy efficiency of the process with 60.0%-methane conversion rate is only 57%, while the exergy efficiency of the process with 80.0%—99.3% methane conversion rate can be as high as 71%—74%.
[Abstract](316) [FullText HTML](226) [PDF 4905KB](3)
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Noise is an important problem which need to be resolved in people's life. The modeling accuracy and control result in active noise control are affected by the nonlinear factors. Secondary path identification is optimized according to the active noise control (ANC) principle, to improve the accuracy and effect of noise control. The finite impulse response (FIR) model used to identify is replaced by the back propagation (BP) neural network, which performs better on the nonlinear factors. Based on least mean square (LMS) algorithm, the ANC algorithm under the secondary path model of neural network is deduced, and the iteration formula of coefficients is derived. The active noise control platform in a duct is built with the TMS320VC5509A as the core processor and the duct as the noise environment. The platform includes input, output and processing modules. The neural network model is trained with input and output signals as training samples. The signals of secondary path are generated by the addictive white noise. The neural network improves the accuracy of secondary path identification model as shown in the training results, which means that the nonlinear factors of secondary path can be described by the neural network. The coefficients computed offline are loaded into the DSP and taken as the filtering parameters of the input signals. Under 500 Hz and 500+800 Hz noise source, the noise control experiment of FIR secondary path model and traditional ANC algorithm is compared with neural network model and optimized ANC algorithm. The results show that the algorithm is effective with good performance under the low-frequency noise of single and two-mixed frequency.
[Abstract](857) [FullText HTML](420) [PDF 4180KB](9)
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When the cyber-physical system (Cyber-Physical System, CPS) performs remote state estimation, it is easy for an attacker to attack the system by tampering with wirelessly transmitted measurement data, etc., thereby causing loss of system performance. In order to defend against attacks, we need to fully understand the attacker's attack strategy. According to the attacker's understanding of the system knowledge, we divide the research into two situations: one is that the attacker has limited ability and cannot directly obtain the transmission data, but can use additional sensors to get a measurement; the other one is that the attacker has a good understanding of the system, and can either directly obtain the transmission data or use its own additional sensors to measure the data. We analyze estimation performance of the attacker's optimal linear deception attack strategy under the KL divergence detector for these two situations, and transform the optimal attack problem into a convex optimization problem. Finally, we give a closed-form expression of the optimal linear deception attack in a one dimensional situation. We compare the estimation error covariance caused by the optimal attack in the two cases, and conclude that the more the attacker understands the system knowledge and the greater the impact of the attack on system performance. At the same time, it is also compared with the existing literature in terms of estimation performance and optimal attack, and use numerical simulation to verify the effectiveness of the proposed results.
[Abstract](528) [FullText HTML](348) [PDF 3809KB](6)
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Silver nanoparticles (AgNPs) are widely used in flexible electronic products for their superior physical and chemical properties. However, the thin films formed by sintering single-sized silver nanoparticles undergo many challenges due to their defects. The films formed by single small-sized AgNPs have high porosity, small grain size and many defects, while the ones formed by single large-sized AgNPs have larger grain size and less defects, but its sintering temperature and porosity are high. In this context, the mechanical properties of the films mixed with 10 nm and 50 nm AgNPs were investigated by finite element simulation to enhance the mechanical stabilities, service reliabilities and electrical conductivities of the sintered structure of AgNPs, in which the 10 nm AgNPs serve as the “filler” to increase the initial stacking density and weld the large AgNPs together, while the 50 nm AgNPs play as the framework to decrease the initial crystallographic defects and stabilize the sintered structures. In the simulation, the filling spacing between large nanoparticles is selected as a parameter to characterize the mixing ratio of large and small nanoparticles. Simulation results showed that when the spacing was short, the small particles were subjected to uneven stress in the filling area, and cracks were easy to occur. When the spacing was too long, the film strength decreased due to the increased number of pores. The results showed that the mechanical properties were superior when the spacing was 50 nm in mixed mode.
[Abstract](1182) [FullText HTML](626) [PDF 4853KB](18)
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As the core technology of the robot controller, the motion control algorithm has important influence on the robot motion performance including stability, reliability, and rapidity. However, the application of motion control algorithms usually faces the problems of poor generality, complex embedded algorithm, and long design cycles. Aiming at these problems, this study combines the complex flexible S-shaped acceleration/deceleration (ACC/DEC) motion control algorithm and proposes a model-based hardware-software collaboration design method, which can greatly shorten the design cycle of the robot motion control system and improve the development efficiency. By modeling the flexible motion control algorithm and establishing a set of interface parameter list easily calculated, the proposed algorithm can adaptively change the motion speed planning according to the parameters in the list such that the flexibility of application can be improved. The model design and simulation test for flexible motion control algorithms are completed in Simulink platform. The Math Works toolbox is utilized to automatically generate the embedded C code and programmable logic IP cores for the software and hardware models. Finally, the proposed algorithm function is realized in the motion controller based on zynq-7000. It is verified via the simulation results that the designed model can achieve the effect of the S-shaped ACC/DEC algorithm and the speed profile has great flexible characteristics. Moreover, the ACC/DEC algorithm deployed on the Zynq-7000 is in agreement with the simulation results. Hence, the model-based software and hardware co-design method has important application value in the field of personalized robots.
[Abstract](938) [FullText HTML](760) [PDF 3807KB](14)
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Modified activated carbon was prepared by stepwise composite modification in the presence of oxidant and nucleophilic addition reagent. The specific surface area and pore structure of the activated carbon were measured by N2 adsorption-desorption (BET). Formaldehyde was used as a model pollutant to test the purification performance of the modified activated carbon. The results showed that the stepwise composite modification, first with the oxidant, and then the nucleophilic addition reagent, could significantly improved the fast purification efficiency of activated carbon for formaldehyde. In contrast, the stepwise composite modification, first with the nucleophilic addition reagent, and then with the oxidant, showed an excellent long-term purification effect. After the activated carbon was impregnated first with 2-imidazolidinone followed by treatment with sodium hypochlorite in a stepwise manner, the long-term purification efficiency of formaldehyde with coconut shell and coal-based activated carbon reached 94.2% and 96.2%, respectively.
[Abstract](311) [FullText HTML](250) [PDF 4066KB](9)
Abstract:
A computational fluid dynamics model for simulating gas-liquid two-phase flow in a shake flask was proposed, named the centrifugal acceleration model. The model was successfully applied to investigate effects of baffles, rotation speed and filling volume on the mass transfer and shearing environment in the shake flask flow field. The results show the presence of the baffle increases the gas-liquid oxygen transfer capacity inside the flask and provids a larger shearing environment than the unbaffled flask; Higher rotation speed is favorable for the gas-liquid mass transfer ability, and the optimal liquid volume exists for a specific rotation speed that provides the best gas-liquid oxygen mass transfer capacity. Finally, the flow field simulation results were analyzed for interpreting the better result for clavulanic acid seed and fermentation process in baffled flask. The method formed in this paper can be extended to the fermentation analysis of other products.
[Abstract](481) [FullText HTML](336) [PDF 3834KB](1)
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In the process of using reverse osmosis membrane method to treat wastewater, the surface of membrane is easily scaled, which needs adding the corresponding membrane antiscalant, the quality of membrane antiscalant directly affects the effectiveness and efficiency of wastewater treatment. Nano-sized spherical polyelectrolyte brush with a core-shell structure synthesized by emulsion polymerization. Under the influence of static electricity and Donnan effect, it has the characteristics of selectively adsorbing counter ions and inhibiting the crystallization of inorganic salts. Therefore, nano-sized spherical polyelectrolyte brush can be used in wastewater treatment process as antiscalant. The scale inhibition performance of nano-sized spherical polyelectrolyte brush on CaCO3, CaSO4, Al3+ was evaluated through dynamic evaluation experiments. The experimental results show that compared with the imported scale inhibitor ASD-200, the scale inhibition performance of nano-sized spherical polyelectrolyte brush on CaCO3 and CaSO4 is improved by 100% and 30%, respectively. Besides, it has excellent resistance performance on Al3+.
[Abstract](623) [FullText HTML](373) [PDF 4096KB](20)
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The pesticide reducing has been a key issue in pesticides area in recent years. The use of nano-carrier technology to incorporate pesticides into nanoparticle provides new route for solving the problem. Different from most nano-carrier technologies which are based on thermodynamic equilibrium self-assembly, the emerging Flash Nanoprecipitation (FNP) method is based on kinetic control, preparing nanoparticles through turbulent mixing of chemical engineering fluids. It has advantages like high drug loading efficiency, short preparation time (milliseconds), easy to scale-up and continuously production, etc. Moreover, it can also systematically control the microstructures of nanoparticle, such as morphology, internal structure and surface structure, which can provide help for further improving the efficiency and low-toxic utilization of pesticide nanoparticle.
[Abstract](854) [FullText HTML](680) [PDF 3809KB](10)
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The development of water-soluble fluorescent probes has become a topical research area for environmental and biological applications. Water solubility is desired for fluorescent probes to function in aqueous media. The introduction of water-soluble groups to conventional organic fluorophores is challenging in terms of preparation and purification. In this paper, fluorescent probes 3 , 6 and 9 based on spirobilfuorene skeleton were designed and synthesized, featuring naphthalene anhydride functionality. These compounds were prepared by hydrolysis of corresponding molecules bearing naphthalenedimide, which is a common electron acceptor often used in fluorophores. The anhydride group not only allows these compounds to be separated and purified in common organic solvents, such as chloroform and tetrahydrofuran, but also imparts enough water solubility. The anhydride group undergoes hydrolysis upon exposing to alkaline conditions in aqueous media, evidenced by a hypochromic-shift in UV-vis absorption spectra with increasing pH. For example, the ratio of absorption at 365 nm over absorption at 472 nm of compound 3 in water, elevated from 2.5 at pH = 2 continuously to 3.4 at pH = 11. The conversion from charge neutral anhydride form to negatively charged carboxylate form switches the solubility of such probes to more polar media. These probes displayed fluorescence emission in the visible range, at 519, 440, and 404 nm, respectively. After incubation Hela cells with these probes at 10 μmol/L for 30 min, confocal microscopy displays clear cell contours with minimal noise, demonstrating efficiency of our strategy.
[Abstract](686) [FullText HTML](463) [PDF 4630KB](12)
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Aero-engine is a complex system with interdisciplinary and multi-component coupling, and its working conditions are complex. It can have catastrophic consequence once the failure of aero-engine occurs. Therefore, the failure analysis of aero-engine system can provide important reference for its design, maintenance and safe operation. In this work, co-word analysis method is adopted, and three multivariate analysis methods of factor analysis, cluster analysis and multidimensional scale analysis are used to classify the keywords in the field of aero-engine system failure, and the main failure forms are summarized and the results are visualized. It is found that clustering analysis with autocorrelation is better. Generally, compared with traditional statistical analysis or theoretical analysis, the analysis results of typical failure forms are basically consistent, but co-word analysis is more specific, detailed and accurate for the study of different failure mechanisms. The results of traditional statistical analysis only stay at the level of general quantitative analysis, and can only indicate the general failure direction for practical engineering application. Multi-dimensional scale analysis realizes visual similarity visualization of failure keywords. The closer to the origin of coordinates, the more core the failure forms are, the higher the frequency of occurrence is. For these common faults in the service process, combining cluster analysis results and multidimensional scale analysis charts, it is convenient for technicians to find out the failure reasons of faulty equipment more quickly, grasp the key points of work more accurately, and determine the protection scheme more effectively, effectively avoiding the recurrence of similar events and prolonging the service life of the engine.
[Abstract](561) [FullText HTML](343) [PDF 3452KB](6)
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Based on the screening of tumor cytotoxicity, fractions and compounds from the South China Sea sponge Pseduoceratina sp. were isolated and purified by silica gel column and HPLC. The structure were identified by ESI-MS and NMR spectroscopy. The anti-proliferation of fractions and compounds against A549, HepG2 and HeLa cell lines had been investigated by SRB method. The targets in the cell were calculated and predicted by Chemmapper Server. The results showed that two bromotyrosine alkaloids were obtained and identified as hemifistularin-3( 1 ) and 11, 19- dideoxyfistularin 3( 2 ). Their IC50 values were higher than 91.76 μmol/L against three tumor cells. While the combination of the two compounds at a certain ratio showed good cytotoxicity, the IC50 value against A549 cells was as low as 8.71 μmol/L. It was indicated that they had significant synergistic effect on three tested tumor cells. Their targets might focus on Hsf1 protein and Vanilloid Receptor 1 and the synergistic effect might be associated with multi-target of compounds.
[Abstract](281) [FullText HTML](151) [PDF 3500KB](15)
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A key problem in speaker verification task is the condition mismatch between the training data and the testing data, which may significantly affect the verification performance. In most of the speaker recognition application scenarios, it is usually impossible to obtain enough samples to retrain the speaker recognition model. At the same time, the samples that is used to train the original model usually may be quite different from those obtained in real applications due to the variability caused by the intrinsic factors (e.g., the changes in emotion, language, vocal effect, speaking style, and aging, etc. or extrinsic ones (e.g., background noise, transmission channel, microphone, room acoustics, and distance from the microphone, etc.). In this paper, an adversarial domain adaptation strategy is designed and applied to the X-Vector-based speaker verification scheme for enhancing its domain adaptation ability. First, the X-Vector scheme is trained on the source dataset (AISHELL1). Then, the domain adaptation strategy is applied to the obtained X-Vector scheme for enabling it adapt to the target dataset (VoxCeleb1 or CN-Celeb). Finally, the performances of the X-Vector schemes obtained before and after adaptation are compared via the target dataset, from which it is demonstrated that the proposed adaptation strategy achieves 21.46% and 19.24% Equal Error Rate (EER) reduction on VoxCeleb1 and CN-Celeb dataset, respectively.
[Abstract](477) [FullText HTML](215) [PDF 3808KB](32)
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Object detection has been a research hotspot in the field of computer vision in recent years. Due to the extensive application of deep learning, the target detection technology combined with deep learning has been developing and making continuous breakthroughs. In the field of target detection, it is difficult to solve the problem of target detection with few sample categories, and detect small targets with high accuracy via the training with few sample categories. By means of the model-agnostic meta-learning (MAML) algorithm in meta learning, this paper improves the information transmission form of the backbone network in YOLOv3 to make Darknet-53 achieve two stages of parameter internal update and external update in gradient descent. By multi-step gradient adjustment on the initial parameters, the trained weights can focus more on the feature information of the target. Even only via a small number of sample categories, it can also maintain the sensitivity to the target in the new task. It is shown via the experiment results that the mean average precision(mAP) value of YOLOv3 model attains 74.81%, and the mAP value of YOLOv3 model based on MAML algorithm can reach 80.05%, which improves the accuracy by about 5%. The network structure and training mechanism of the modified YOLOv3 via MAML can improve the accuracy of detection in training and prediction, and the trained weights can make the model have high detection accuracy and high generalization.
[Abstract](301) [FullText HTML](219) [PDF 3962KB](4)
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A variable-length particle swarm optimization (VLPSO) shows good performance for feature selection on large data sets. However, its completely random particle initialization will result in certain blindness in the initial stage. Meanwhile, the single updating mechanism of VLPSO and the information isolation among subpopulations also affect the classification performance. In order to cope with the defect of VLPSO, this paper proposes a co-evolutionary feature selection method based on variable-length particle and multi-behavior interaction(M-CVLPSO). Firstly, to improve the blindness caused by random initialization, the multidirectional initialization strategy in continuous space is adopted to shorten the distance between the initial solution and the optimal solution from the perspective of expectation. Secondly, particles are divided into leaders, followers, and weeders according to fitness, and then, multiple updating strategies are adopted in the process of iteration to balance the diversity and convergence of dynamic algorithms. At the same time, the dimension reduction index is integrated into the fitness function to further enhance the performance of the algorithm on some datasets. The convergence of the proposed algorithm is proved theoretically. Finally, the experimental analysis is carried out on the classification accuracy, dimension reduction and calculation time based on 11 large-scale feature selection data sets, which show that the proposed model has better comprehensive performance than the four comparison algorithms.
[Abstract](212) [FullText HTML](167) [PDF 3660KB](3)
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It is of great significance to study the flow shop scheduling problem with no-idle constrains, since No-idle production Scheduling exists widely in modern industry. This paper proposes a multi-objective discrete sine optimization algorithm (MDSOA) to solve the mixed no-idle permutation flow shop scheduling problem (MNPFSP), whose goal is to minimize the makespan and the maximum tardiness. Firstly, an external archive set (AS) is established to store Pareto front and update after each iteration. Secondly, based on the basic sine optimization algorithm, the destruction reconstruction mechanism of the iterative greedy (IG) algorithm is introduced to redefine a location update strategy, whose key feature is suitable for discrete scheduling problems. Besides, both the fast non-dominate sorting method and the crowding distance are utilized to screen the population for retaining the elite solutions and ensuring the diversity and distribution of solutions. Finally, simulation experiments are made via 11 instances with different scales in Taillard Benchmark, which, together with the comparisons with NSGA-II and NSGA-III, demonstrate the effectiveness of the proposed MDSOA algorithm for solving MNPFSP.
[Abstract](713) [FullText HTML](489) [PDF 3701KB](24)
Abstract:
The music source separation is to separate a piece of music into its individual sounds. As a specific case, the Singing Voice Separation (SVS) separates the music into vocals and accompaniment. Due to its potential applications in music melody extraction, music genre classification, singing voice detection, and singer identification, etc, SVS has been becoming a hot topic in the music information retrieval field in recent years. It is recently reported that a variety of convolutional neural network architectures based on U-Net has been successfully employed for the SVS task and the better performance can be achieved. Besides, Wave-U-Net is proposed to achieve the end-to-end SVS by analyzing the music waveform directly. However, the performance of the SVS approaches in the time-domain relies heavily on the quality of the feature extraction procedure. In this paper, the conventional Wave-U-Net based SVS scheme is modified for enhancing its performance. Firstly, at the encoding and decoding blocks, a residual unit is designed and adopted to replace the plain neural unit to solve the degradation problem to some extent. Secondly, at the skip connection, an attention gate mechanism is introduced to reduce the semantic gap between the output of the previous layer in the decoding block and the one of the corresponding layer in the encoding block. To verify the effectiveness of the proposed scheme, termed as RA-WaveUNet, in the SVS task, its performances are compared with those of state-of-the-art schemes on the maximum open dataset MUSDB18. It is demonstrated from experimental results that the proposed scheme can achieve better performances than Wave-U-Net based ones and other SVS schemes. Moreover, both the above modifications contribute to the performance enhancement.
[Abstract](815) [FullText HTML](418) [PDF 3820KB](6)
Abstract:
Aiming at the complexity and variety of production modes in the actual production system, this paper investigates the hybrid flowshop lot-streaming scheduling problem with batch processing. A variable batching method is proposed by considering the capacity of batch machine and the processing ability of unrelated machines. A scheduling model is established to minimize the completion time via dynamic continuous processing strategy. At the same time, a discrete water wave optimization (DWWO) is proposed to solve the scheduling model. According to the characteristic of batching and optimization objectives, four decoding methods are designed to optimize the machine selection and processing sequence of jobs. By the block optimal insertion, cross operation, and multi neighborhood search, the operation operators is improved for enhancing the local search ability. Moreover, an operation of replacing inferior solution is proposed to improve the convergence ability of the proposed algorithm. Finally, the experimental design method is used to calibrate the parameters of DWWO, and different scale examples are designed to evaluate the performance of DWWO. It is shown via the experimental results that the proposed DWWO algorithm can effectively deal with the hybrid flowshop lot-streaming scheduling problem with batch processing.
[Abstract](1058) [FullText HTML](606) [PDF 3673KB](10)
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Ranpirnase is a multi-functional protein drug widely studied by researchers all over the world. It was first isolated from the oocytes and early embryos of the Northern Leopard Frog, and belonged to the ribonuclease A (RNase A) superfamily. Ranpirnase not only inhibits protein biosynthetic pathway, but independently induces tumor cell apoptosis. It also has antiviral activity. In this study, in order to improve the expression level of ranpirnase in E. coli. , a Plackett-Burman (PB) experimental design was applied to examine the effect of various factors on ranpirnase expression in recombinant E. coli . We also optimized the recombinant E. coli fermentation medium and inducing conditions. On the basis of these results, the ranpirnase expression in recombinant E. coli was carried out in a 7 L fermentor with the combined exponential and pH-Stat feeding strategy. With the optimized fermentation medium, the protein expression at the flask level was increased from 9% to 36%, and the OD600 value increased from 4.8 to 5.47. The expression level of ranpirnase at the 7 L fermentor level reached 55%, and the OD600 value was increased to 35 after the optimization. The use of the optimized medium for high-density fermentation of ranpirnase leads to a lowered production cost, facilitating its commercialization.
[Abstract](745) [FullText HTML](439) [PDF 4436KB](19)
Abstract:
In order to improve the performance of multi-phase motor torque control strategy, the symmetrical six-phase permanent magnet synchronous motor was taken as the research object. On the basis of its structure and winding distribution characteristics, a mathematical model in natural coordinate system was established. In view of the complexity of calculation under multiphase electromagnetic coupling, the vector transformation model under the rotating coordinate system was derived. In consideration of the large starting torque fluctuation of multiphase motors, a new direct torque control (DTC) strategy based on SVPWM technology was proposed. In the MATLAB/Simulink environment, the mathematical model under the vector decoupling transformation of the motor was simulated. The results showed that the proposed control algorithm presented better anti-disturbance and regulation performance on the motor electromagnetic torque, flux linkage and other parameters than the traditional direct torque control. The study demonstrates verify the effectiveness and feasibility of the developed control algorithm.
[Abstract](509) [FullText HTML](389) [PDF 3890KB](8)
Abstract:
Two kinds of Kex2 protease mutants Kex2-K291L and Kex2-K291H were successfully expressed in Pichia. pastoris, which were induced by methanol, and purified with anion exchange chromatography (Q-FF). Finally, the enzymatic characteristics of these Kex2 proteases were characterized. It was showed that compared with the wild-type Kex2, the degradation of the two mutants Kex2-K291H and Kex2-K291L was significantly improved. The wild-type Kex2 protease was degraded during the purification, and a non-single band appeared, while the mutants were not degraded during the purification, and it was still a single band. The optimum pH and temperature of these two mutants were the same as those of the wild-type Kex2. Their optimal pH and temperature were pH 9.0 and 37 ℃, respectively. Compared with the wild-type Kex2 protease, the pH stability range of the mutant Kex2-K291H was expanded, from the range of pH 5.0 to 6.0 to the range of pH 5.0 to 7.0; compared with the wild-type Kex2, Kex2-K291H was more stable at the temperature range of 4 ℃ to 37 ℃. Enzymatic reaction kinetics studies showed that the Kcat/Km values of mutant Kex2-K291H and Kex2-K291L were 1.8 and 2.0 fold higher than that of the wild-type Kex2 protease, respectively.
[Abstract](579) [FullText HTML](411) [PDF 4016KB](11)
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Smart nano-pesticides have been prepared to efficiently deliver a sufficient amount of active ingredients in response to different stimuli, employing targeted and controlled release mechanisms. In this paper, an enzyme-responsive carrier for controlled release of lambda-cyhalothrin (LC) was prepared through loading LC into aminated hollow mesoporous silica (HMSN) nanoparticles by physical adsorption, and then carboxymethyl-β-cyclodextrin (CM-β-CD) was coated onto the surface of HMSN using amidation reaction as the blocking molecule. A series of physicochemical characterization showed the successful construction of the CM-β-CD/LC/HMSN material. An in vitro release test showed that the LC release amount from CM-β-CD /LC/HMSN reached up to 55% in the presence of α-amylase, while only about 20% could be released in the absence of the enzyme, suggesting that the pesticide release was dependent on enzymatic activity. Biological tests showed that the pesticide formulation had good insecticidal effect on Mythimna separate larvae. Based on the results obtained by different experimental methods, we believe that the nanoparticles would be useful for releasing LC after degradation of cyclodextrin enzymatically in vivo , suppressing the survival of Mythimna separate larvae.
[Abstract](981) [FullText HTML](793) [PDF 6302KB](25)
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A nanopesticide has been increasingly favored due to its small particle size, high biological efficacy, and good dispersibility. However, a nanopesticide typically has a high price because of its costly production, which limits its applications in many cost-sensitive agricultural areas. Aligned with the national policy of the dosage reduction and efficacy enhancement of agrochemicals, a nanopesticide has very promising and demanded applications. This review introduces a new technology, capable of highly effective production of an aqueous nanodispersion with an ultra-high load of a pesticide, the flash nanoformation (FNF) technology, which is expected to be able to realize massive production of nanopesticides in a fast and economical way.
[Abstract](760) [FullText HTML](378) [PDF 3858KB](24)
Abstract:
Great progress has been made in the fundamental theories and applications of chemical engineering. With the advancement of modern sciences, there emerges an interdisciplinary field termed agrochemical engineering that incorporates the knowledge and techniques of both chemical engineering and agricultural science. In this review, the conceptual advancement of agrochemical engineering and the recent progress in the preparation and application of nano-agrochemicals are described. In particular, the newly emerged preparation methods for nano-pesticides such as the flash nano-precipitation technology, the development of smart pesticides for controlled drug release, the migration trend of nano-pesticides, and the extension of new fertilizers and pesticides to the integral control of water and agrochemicals are discussed in details. Finally, a perspective is given in regard to the future development of agrochemical engineering.
[Abstract](241) [FullText HTML](166) [PDF 9265KB](7)
Abstract:
To screen out the potential targets and molecular mechanisms of Epigallocatechin gallate (EGCG) in the treatment of triple negative breast cancer (MDA-MB-231). Databases was used to explore the potential targets between EGCG and MDA-MB-231. The “target-pathway” networks of common targets were constructed using Cytoscape 3.8.0 software, while the String database was used to draw and analyze the PPI network. Subsequently, the core genes were submitted to the Metascape database for GO and KEGG enrichment analyses; Finally, the prediction results were verified through in vitro experiment. A total of 537 EGCG targets and 181 disaster targets were obtained, 30 key targets were retained by further screening from 88 common potential targets. The results of the enrichment analyses showed that the active targets were involved in 20 core GO biological processes and 17 KEGG signaling pathways, such as cancer signaling pathways, toxic tolerance pathways, pancreatic cancer pathways, rectal cancer pathways, small cell lung cancer pathways. Molecular docking illuminated that EGCG could interact with β-catenin in a non-covalent manner. The in vitro experiment revealed that HGF could induce the expression of β-catenin, and EGCG could repress the HGF-induced over-expression of β-catenin. EGCG inhibited cell viability through multiple targets and multiple pathways, among them, it has been basically confirmed that EGCG can affect the HGF / β-catenin pathway, providing a theoretical and practical basis for further mechanism exploration.
[Abstract](918) [FullText HTML](451) [PDF 0KB](28)
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At present, neural networks have been widely used, and have achieved some success in many fields. However, there is not much theoretical analysis about neural networks. This paper analyzed the convergence of the back-propagation algorithm with momentum for the three-layer feed-forward neural networks. In our model, the learning rate is set to be a constant, and the momentum coefficient is set as an adaptive variable to accelerate and stabilize the training procedure of network parameters. The corresponding convergence results and detailed proofs are given. Compared with the existing results, our results are more general.
[Abstract](237) [FullText HTML](237) [PDF 0KB](9)
Abstract:
Acoustic scene classification (ASC) is one of the most challenging tasks in the field of computational auditory scene analysis (CASA). Most of the traditional ASC models are based on the combination of the linear frequency analysis-based handcrafted feature and the deep learning-based classification model method. However, the linear frequency analysis-based feature extraction method cannot mimic the nonlinear frequency selectivity of the human basilar membrane, which results in lower feature resolution. On the other hand, the existing classification model cannot solve the low classification accuracy caused by complex sound sources and highly overlapping of sound events. To deal with these problems, this paper proposes an ASC model based on cochleagram multi-instance analysis. The equivalent rectangular bandwidth cosine filter bank is adopted to analyze the signal spectrum and simulate the acoustic perception property of human beings. Meanwhile, multi-instance learning strategy is introduced to characterize the entire data structure of acoustic scenes for improving classification accuracy. In addition, in order to enhance the robustness to frequency shift of sound events, the average pooling method is adopted in the classification prediction integrator of the multi-instance learning classification model. Finally, it is shown via the experimental results on the DCASE 2018 and DCASE 2019 Challenge Task1a dataset that the proposed model in this work can achieve higher classification accuracy than the baseline model provided by the DCASE 2018 Challenge and the traditional model based on Log Mel spectrogram and multi-instance learning. Moreover, it is also verified that the average pooling is better than the maximum pooling.
[Abstract](221) [FullText HTML](159) [PDF 0KB](1)
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With the explosive growth of video data, video intelligent analysis has been becoming the academic and industrial research hotspot. The objective of video action detection is to obtain the location and time information of actions based on action recognition. By combining the single shot multi-box detector (SSD) with the RGB space flow and optical flow, this paper proposes a region spatiotemporal two-in-one action detection network. To improve the nonlocal spatiotemporal module in the network, a pixel filter is proposed in optical flow to extract the information of key motion regions, and then, the correlation calculation is performed only on the selected key motion regions in the spatial flow. The proposed module can get long-range dependence of actions effectively and reduce the computational cost of the nonlocal module and the interference of video background noise. Finally, the proposed network is tested on the benchmark dataset UCF101-24, and attain better detection performance.
[Abstract](260) [FullText HTML](197) [PDF 0KB](6)
Abstract:
Compared with the traditional machine learning algorithms, deploying deep neural networks in embedded systems can significantly improve the performance of robot system object recognition. However, its performance is limited by the computing resources and memory capacity of the embedded platform. Hence, it is quite necessary to simplify the network structure and improve the system efficiency through model pruning and parameter quantification. Meanwhile, it is also necessary to prevent overfitting through dropout regularization and improve the accuracy of system recognition. In order to further improve the object recognition performance of the deep neural network algorithm in the embedded robot system, this paper proposes a deep neural network dropout regularization method based on constant false alarm detection (CFAR-Dropout). Firstly, by quantizing the weights, the weights and activations are reduced from floating point numbers to binary values. Secondly, a constant false alarm detector (CFAR) is designed to maintain a certain false alarm rate, adaptively delete some neuron nodes, and optimize the neuron nodes involved in the calculation. Finally, on the embedded platform PYNQ-Z2, an VGG16-based optimization model is used to experimentally verify the object recognition performance of the proposed algorithm. It is shown via experimental results that compared with the classic dropout regularization method, the CFAR-Dropout regularization method can reduce the error rate by 2%, and effectively prevent the overfitting. Moreover, compared with the original network structure, the proposed algorithm can reduce the amount of the occupied memory by about 8%, and effectively prevent over-parameterization.
[Abstract](51) [FullText HTML](49) [PDF 0KB](8)
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Two-dimensional (2D) graphene oxide (GO) exhibits superlative properties for biomedical applications such as drug delivery, biosensing and bioimaging. There are questions, however, about their biocompatibility on organs including liver, which is frequently targeted by therapeutic nanomaterials or secondary spread from other uptake sites. In this study, we systemically explored the biological impact of GO on three major liver cell types: Kupffer cells, liver sinusoidal endothelial cells (LSEC), and hepatocytes. Pristine (pGO) and reduced (rGO) oxidation states of GO flakes with large (510 nm) and small sizes (110 nm) were synthesized. These samples show differences in cellular response, depending on oxidation state as well as lateral size. While pGO induced plasma membrane damage and necrosis (large > small flakes) in Kupffer cells, minimal cytotoxicity was observed in LSEC and hepatocytes. In contrast, rGO induced apoptosis in Kupffer cells (large > small flakes) and LSEC, with negligible effects in hepatocytes. While pGO attached to the Kupffer cell membrane and induced lipid peroxidation and cytoskeleton disruption, rGO was mostly taken up in Kupffer cells. Moreover, while pGO and rGO were taken up in roughly similar amounts by LSEC, little uptake for hepatocytes. Further study of intracellular effects of the GO species at the level of lysosomes and functionally linked NLRP3 inflammasomes demonstrated that lysosomal damage by rGO in Kupffer and LSEC induced IL-1β production. Similar effects were not seen in hepatocytes or with pGO. Collectively, this study reveals that surface oxidation state and lateral size of GO differentially impact liver cells based on interactions with cell membranes, cellular uptake, and damage to lysosomes.
[Abstract](37) [FullText HTML](20) [PDF 0KB](0)
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The min-max \begin{document}$k$\end{document}-traveling salesmen problem on a tree (Min-Max k-TSPT) is an extension of multiple traveling salesmen problem in tree structure. In this paper, Min-Max k-TSPT, multi-depot Min-Max k-TSPT and min-max \begin{document}$k$\end{document}-path cover problem on a tree (Min-Max k-PCPT) were studied. We present pseudo-polynomial exact algorithms for them by bottom-up dynamic programming. Besides, based on the algorithm of multi-depot Min-Max k-TSPT, we devise pseudo-polynomial exact algorithms solving multi-depot Min-Max k-PCPT and multi-depot min-max \begin{document}$k$\end{document}-Chinese postmen problem on a tree (multi-depot Min-Max k-CPPT) for the first time.
[Abstract](242) [FullText HTML](139) [PDF 1227KB](10)
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The effects of nozzle screw structure on liquid jet breakup were investigated with a high-speed camera. Five nozzles with different diameters (4.00, 4.80, 7.50, 8.75 and 10.80 mm) were used in the experiment. The thread depth range was 0.40—1.25 mm, the liquid jet Reynolds number was within the scope of 500—22 600, and the Weber number was within the scope of 0.000 3~1.2. The experimental results show the screw structure has a strong disturbance to the jet and promotes the breakup of jet. By comparing the jet breakup length under different exprerimental conditions, it can be obtained that increasing Reynolds number leads to the decrease of breakup length when the Reynolds number is less than 1 600. The structure of nozzle screw has little influence on the fracture length of liquid jet. The breakup length of liquid jet increases first and then decreases with the Reynolds numbers raised. In this condition, the influence of screw structure of nozzle is significant, the breakup length is shorter than the smooth one. When the Reynolds number is in the 7 000 range above, the breakup length of liquid jet rises with the increase of Reynolds number and the screw structure of nozzle continues to promote the decrease of the fracture length of liquid jet. The experimental results show that the influence of nozzle screw structure on small diameter nozzle (diameter less than 5 mm) is more significant than the larger nozzle. By using dimensionless thread depth, Reynolds number and Weber number, the relationship for predicting the rupture length of liquid jet was established.
[Abstract](449) [FullText HTML](360) [PDF 1037KB](16)
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The Claus process is one of the technologies for efficient acid gas processing and sulfur recovering. In industry, it is necessary to add combustion-supporting gas for combustion to ensure flame stability when processing low concentration acid gas, which leads to problems such as increased production of harmful substances like polycyclic aromatic hydrocarbons and organic sulfur. The use of pure oxygen for combustion can not only increase the temperature of the furnace and the removal rate of hydrocarbon impurities, but also avoid the problems caused by the addition of combustion-supporting gas. In this paper, a full Claus process model was built in the Aspen Plus and was validated by industrial data. The influence of the inlet acid gas composition, oxygen concentration, oxygen preheating temperature, furnace pressure, oxygen gas intake and the temperature of the second catalytic stage reactor on the Clause process were studied. The optimization tool in Aspen Plus was used to calculate the best operating parameters. The optimized results showed that the sulfur recovery efficiency increased from 98.31% — 99.08% and the emission of SO2, the main pollutant in the tail gas, reduced from 0.350 kmol/h to 0.278 kmol/h, reduction rate at 20.6%. Moreover, it saved 9133.38 kJ/kmol(acid gas) heat required for the preheating of the acid gas and air.
[Abstract](471) [FullText HTML](373) [PDF 1313KB](6)
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The evolution characteristics of the reduction process of single iron concentrate particles under high temperature and CO atmospheres were studied in the in-situ experiment of a high temperature stage microscope. The high-temperature reduction process of single iron concentrate was recorded via in-situ experiment, and the reduced product (elemental iron) was verified by using Raman spectrometer. The results showed that the initial formation time of the elemental iron on the particle surface was mainly affected by temperature, and this influence from the gas flowrate was smaller. The initial formation time decreased 75% when the reducing temperature reduced from 1 100 ℃ to 1 300 ℃. But a unchanged result of this formation time was found in the temperature range from 1 300 ℃ to 1 400 ℃. Nodular structures were found on the surface of iron concentrate particles during the reduction process between 1 100 ℃ and 1 350 ℃, and their sizes increased with the rising reduction temperature. A characteristic number l, which was self-defined as the mean value of the length and width, increased from 6 μm at 1 100 ℃ to 15 μm at 1 350 ℃. When the reduction temperature was above 1 400 ℃, layered melting products were observed for the iron concentrate particle: the product on the core is reduced iron, the second layer was the root-shaped metal iron with reduced molten ferrous oxide, and the outer layer was the iron slag containing Al, Ca, Si, and other elements.
[Abstract](51) [FullText HTML](25) [PDF 819KB](5)
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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](44) [FullText HTML](34) [PDF 713KB](0)
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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](474) [FullText HTML](290) [PDF 1032KB](9)
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By using the feature extraction strategy of local extraction and global integration, this paper propose a multi-block convolutional variational information bottleneck (MBCVIB) for the fault diagnosis of multivariate dynamic processes. Firstly, according to the process mechanism, all variables are divided into sub-blocks and the variables in the same operation unit will be put into the same block. Secondly, one-dimension convolutional neural network (1-D CNN) is used to extract the local dynamic features of each operating unit in the process, which considers the temporal correlation between samples. Besides, a global feature representation is constructed by concatenating the local dynamic features of all operating units. On the basis of global features, the most relevant fault information is further extracted according to the variational information bottleneck principle. Finally, the proposed model is validated via Continuous Stirred Tank Reactor (CSTR) and Tennessee Eastman Process (TEP), which achieves an average fault diagnosis accuracy of 0.983 on CSTR and 0.955 on TEP.
[Abstract](616) [FullText HTML](453) [PDF 1171KB](14)
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In order to solve the multimodal multi-objective optimization problem and find all solutions equivalent to the Pareto optimal solution, this paper proposes a novel group search optimization algorithm (MMO_LTSGSO) based on spatial learning mechanism and emotion tracking behavior by introducing social behavior into the basic group search algorithm. Firstly, a spatial learning mechanism is established and the decision of the population distribution state (discrete state and concentrated state) is made according to the real-time information of the learned individual's own position and the best individual position. When the population is in a discrete state, the following and wandering way is adopted to enhance the space exploration ability of the algorithm. With the optimization process, individuals interact with each other, and the spatial distance gradually decreases. At this time, the population gradually aggregates, the dynamic step search strategy is used to update the individual position, which can explore the solution around the optimal solution in real time and accelerate the convergence speed of the algorithm. Secondly, in order to prevent the algorithm from falling into stagnation and improve the accuracy of the algorithm, the emotion factor is introduced to make certain individuals track their moving behavior along their preferred direction. Then, special congestion distance calculation and guided evolution strategy are used to ensure the diversity of the algorithm in decision space and target space. Finally, the convergence of the algorithm is proved theoretically, and its performance is verified via 15 multimodal multi-objective optimization test benchmark functions, and is also compared with several existing multimodal multi-objective optimization algorithms. It is shown via the experiments results that the proposed algorithm can effectively solve multimodal multi-objective optimization problems.
[Abstract](430) [FullText HTML](329) [PDF 1206KB](3)
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In the ultrasonic imaging of polyethylene (PE) pipe joints, the detection of characteristic line, resistance wire and echo of pipe inner wall is the key technology to realize automatic identification of welding defects. Aiming at the characteristics of obvious longitudinal stratification and more global interference in ultrasonic image, an adaptive ultrasonic signal line detection algorithm for polyethylene pipeline is proposed. Firstly, the grayscale image is adaptively blurred and projected in the horizontal direction for identifying the hierarchical area. Secondly, based on the target feature and spatial information, an improved adaptive threshold segmentation algorithm is proposed to detect feature lines. Thirdly, the Otsu-CRF algorithm is proposed to detect the signal line of the resistance wires. Finally, the detection of pipeline inner wall echo is fulfilled by color space conversion and threshold segmentation. It is shown via experimental results that the proposed adaptive algorithm can completely detect three signal lines and enhances the detection effect and efficiency than the existing algorithms. It also verifies the feasibility of applying the algorithm to the automatic detection of ultrasonic signal line of polyethylene pipe electrofusion welding joint.
[Abstract](544) [FullText HTML](396) [PDF 1186KB](15)
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In recent years, with the continuous breakthrough in the field of algorithms, the current target detection algorithms has higher and higher computational complexity. In the forward inference stage, many practical applications often face low latency and strict power consumption restrictions. How to realize a low-power, low-cost, and high-performance target detection platform has gradually attracted more attentions. As a high-performance, reconfigurable and low-cost embedded platform, Field Programmable Gate Array (FPGA) is becoming the key technology of algorithm application. In view of the above requirements, this paper proposes a low-power target detection accelerator architecture based on FPGA+SOC (System On Chip) heterogeneous platform by adopting various hardware acceleration methods such as coarse and fine granularity optimization, parameter fixed-point and reordering. Aiming at the design limitation of existing researches on Zynq 7000 series FPGA, this paper proposes a new multi-dimensional hardware acceleration of YOLOv2 (You Only Look Once) algorithm, and deeply analyzes and models the accelerator performance and resource consumption to verify the rationality of the architecture. In order to make full use of the on-chip hardware resources to optimize the design of each module, the accelerator data access mechanism is improved to effectively reduce the transmission delay of the system and improve the actual utilization rate of bus bandwidth. The fixed-point processing of floating-point numbers can reduce the processing load of FPGA and further accelerate the processing speed. It is shown via experiments that the architecture achieves 26.98 GOPs performance on PYNQ-Z2 platform, which is about 38.71% higher than the existing FPGA-based target detection platform, and the power consumption is only 2.96W. Moreover, it has far-reaching significance for the application of target detection algorithm.
[Abstract](390) [FullText HTML](136) [PDF 757KB](10)
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Ice nucleation proteins (INPs), which exist widely in nature, can induce water molecules to arrange regularly at micro scale resulting in elevated freezing point, but their tertiary structures have not been determined by experiments. The latest research shows that INPs may interact with water molecules to promote the formation of ice nuclei through TXT template of central repeat region, which shares identical structural feature of antifreeze proteins but with larger template area and opposite functionalities. INPs also have tyrosine (TYR) ladders to form new β−helix dimer along dimerization interface, thus increasing the active surface area of protein ice. At the same time, in a series of control experiments, it was found that polyglycerol at a certain concentration obviously combined with the INP of ice nucleation bacteria Pseudomonas syringae and inhibited its ice nucleation activity. In this work, molecular simulation software AutoDock was used to study the binding interaction of ice nucleation protein model of Pseudomonas borealis with glycerol and triglycerol molecules, in order to discover the corresponding inhibition mechanism on ice nucleation proteins and its universality with other INPs. The binding information shows that the ligand molecules express different binding abilities to TXT template and tyrosine ladder, and other residues of ice nucleation protein may participate in the binding with TXT freezing template.
[Abstract](114) [FullText HTML](81) [PDF 1203KB](4)
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[Abstract](69) [FullText HTML](65) [PDF 824KB](4)
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The rarely used spare parts’ demand usually changes sharply, and the demand interval is long and uncertain, which results in inaccurate prediction of spare part demand and the difficulty to make a reasonable inventory decision. A novel method is proposed for demand forecasting and inventory optimization. In the proposed method, the Gaussian process regression is used to forecast the demand interval, and then combined to an augmented sample statistical method called by Bootstrap, to predict the probability distribution of spare parts demand. Based on the demand probability statistics, the stochastic inventory model on the total inventory cost can be established. The particle swarm algorithm is used to solve the problem of minimizing the total cost for inventory decision. The experimental results from two sets of real data show that the proposed method has higher prediction accuracy. Besides, the inventory decision achieves the goal of minimum inventory cost subject to service level of spare parts, which shows the practicality of the proposed method.
[Abstract](66) [FullText HTML](58) [PDF 1503KB](5)
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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 OCs with different Fe2O3 content and CO were compared to verify. The experimental results showed that the specific surface area and pore volume of CaSO4/Ben OCs increase with the addition of Fe2O3, which improved the reduction reaction rate and maintained the high CO2 concentration in the system. Fe2O3 can inhibit CaSO4 reaction to generate CaO and sulfur-containing gases, and improve the stability of CaSO4/Ben OC circulation reaction. w=15% Fe2O3 addition was the best choice. The addition of w=15% 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](416) [FullText HTML](129) [PDF 775KB](3)
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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](431) [FullText HTML](131) [PDF 1387KB](2)
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In the process of pressurized feeding, the powders will be compacted under gas pressurization, which will cause the cohesive arching and flow blockage. The main reason for these problems is that the mechanism of consolidation of powders under gas pressurization and the effective regulation method have not been mastered yet. In this work, the consolidation characteristics of powders under gas pressurization and mechanical pressurization were investigated, providing a reference for optimizing pressurized powder feeding. The density distribution of the powder bed under different consolidation states was characterized by using the forces on an intruder immersed in the powder bed, and the influence mechanism of gas pressurization on the consolidation characteristics of powders was analyzed. The results show that a smaller increase in the compressive stress under gas pressurization can make the compaction density increase significantly, but the gas will penetrate into the bed, weakening the mechanical force generated by the pressurized gas on the bed, so the consolidation characteristics under gas pressurization and mechanical pressurization are markedly different: the compressive stress on the powder bed under gas pressurization increases linearly with the pressurization rate, and the critical value of compaction density under gas pressurization is only 85% of that of mechanical pressurization, thus it is relatively easier to compact the powder bed under mechanical pressurization. And the final pressure of gas pressurization hardly affects the compaction density of the powder bed. The research on the mechanical properties of the powder bed shows that the density distribution under gas pressurization is more uniform than that under mechanical pressurization. The dimensionless resistance force Fb/Fb,0 is used to characterize the consolidation characteristics of the powder bed, which increases linearly with applied normal stress and exponentially with the compaction density.
[Abstract](487) [FullText HTML](145) [PDF 926KB](6)
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Sophorolipids (SLs) is one of the most promising biosurfactants, which has been widely used in cosmetics, petroleum, pharmaceutical and other industrial fields. In this study, n-hexadecane was used as hydrophobic substrate to investigate the effect of different oxygen supply levels on SLs synthesis. Through the integrated analyses of metabolic flux distribution and key enzyme activities during the fermentation process, it was found that the oxygen supply level significantly affected the syntheses of fatty acids and hydroxyl fatty acids, and simultaneously caused significant changes in the utilization of glucose and alkanes.The on-line physiological parameter respiratory auotient (RQ) could well represent the changes of intracellular metabolic flux, so as to be expected to act as a key process parameter to regulate the cell metabolism in the further. Finally, by providing the appropriate oxygen supply level during the synthesis period of SLs, it can not only enhance the utilization rate of relatively expensive substrate alkane, but also significantly reduce the power input, thus improving the production economy. The results of this study would be easily extended to other hydrophobic substrates such as rapeseed oil and oleic acid for SLs fermentation, and would provide a solid theoretical basis for the development and application of industrial-scale SLs fermentation process control strategies.
[Abstract](310) [FullText HTML](317) [PDF 620KB](1)
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Gender identiﬁcation is a relevant task in speaker verification. It can also be used as an auxiliary tool in Automatic Speech Recognition(ASR) to improve model performance. To improve the accuracy of gender identification, some researchers have proposed some scheme based on deep learning. However, compared to the acoustic conditioned data in training, speech data in application scenarios is usually masked by the background noise, such as music, environmental noise, or background chatter, etc. Thus the performance of gender identification model is seriously degraded due to the data difference between training and actual use. In order to solve this problem, we propose a domain adaptive model combining Generative Adversarial Network(GAN) and GhostVLAD layer. The introduction of GhostVLAD can effectively reduce the interference of noise and irrelevant information in speech. Besides, the domain adaptation with GANs can realize the adaptation of the model to the target domain data. Furthermore, to maintain the network’s ability of gender discrimination, we use an auxiliary loss during the adversarial training. Voxceleb1 is chosen as the source domain data, while Audioset and Movie as the target domain data. The experimental results show that the proposed model achieves a relative improvement of 5.13% and 7.72% over the baseline in target domain data.
[Abstract](329) [FullText HTML](337) [PDF 1127KB](8)
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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](278) [FullText HTML](281) [PDF 1817KB](4)
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Tobermorite (TOB) was major phase of calcium silicate board and autoclaved aerated concrete, which were widely used refractory materials and thermal insulation materials in the building engineering field. However, these materials were easy to wear so that large quantities of solid wastes have been produced. The problem of functionalized utilization of TOB needed to be resolved urgently. In the present paper, TOB samples with good crystal morphology were prepared by hydrothermal synthesis and were calcined at different temperature (H-TOB). Then the porous SiO2 material (300AH-TOB) was successfully prepared by acid treatment of H-TOB, and the porous SiO2 material was characterized by XRD, N2 adsorption-desorption, SEM, TEM and other testing methods to investigated the formation mechanism. The BET and pore size distribution test analysis showed that the specific surface area of 300AH-TOB after thermal activation at 300 ℃ and hydrochloric acid modification was 570.25 m2/g, and the total pore volume was 0.747 m3/g. After heat treatment and hydrochloric acid treatment, the calcium ions in TOB were selectively dissolved, and the main component of the acid-insoluble material was silica. Therefore, it was inferred that the silicon oxide exhibits an eight-membered ring double-chain deformation structure composed of a silicon-oxygen tetrahedron, resulting in an increase in mesopores and micropores. The adsorption performance of TOB, 300H-TOB and 300AH-TOB on two organic dyes, Safranine T and crystal violet, was investigated by static adsorption experiments. The adsorption rates were 56.35% and 47.69% for TOB; 25.57% and 42.69% for 300H-TOB; and 91.46% and 88.86% for 300AH-TOB, respectively, with the addition amount of 0.4 g. The porous material prepared from TOB had favorable adsorption of organic dyes, indicating its promising potential in adsorption application.
[Abstract](271) [FullText HTML](289) [PDF 923KB](5)
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According to the periodic dynamic characteristics of traffic flow, a traffic flow probability combination model method based on similarity clustering is proposed. It fully mines and exploits the potential similarity of traffic flow data. First, use adaptive k-means++ clustering method to classify the historical traffic flow data with time-period similarity and build a combined model for each sub-dataset with different characteristics correspondingly. Second, for the newly input traffic flow state data, analyze the similarity between the input data and the classified datasets to calculate the probability weight of each combined model. Finally, the predicted output is obtained through the probability fusion of the combined models. The effectiveness and accuracy of the proposed prediction model are verified by carrying out the simulation experiments.
[Abstract](712) [FullText HTML](304) [PDF 1086KB](4)
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The electroluminescence(EL) performance of the blue light phosphorescent white organic light emitting diode(WOLED) incorporating Au NPs, Ag NPs and their mixed NPs beneath the PEDOT: PSS hole injection layer(HIL) has been investigated, and the surface plasmon-enhanced EL efficiency has been demonstrated. The EL properties of OLED sample with either Ag or Au NPs has been improved compared to the samples without Metal Nanoparticles(MNPs). The OLED with mixed NPs of volume ratio of 3: 1(Au NPs: Ag NPs) shows best EL properties: External Quantum Efficiency(EQE) of 15.19% and Power Efficiency(PE) of 15.03 lm/W, which are improved by 29.06% and 23.00% respectively compared to the samples without MNPs. The influence of localized surface plasmon resonance(LSPR) from MNPs in the various EML on the EL and spectra properties is discussed in details. The improvement of OLED with mixed MNPs is due to the sufficient coupling between the LSPR of mixed MNPs and the excitons in the emission layer without significant exciton quenching from the MNPs.
[Abstract](135) [FullText HTML](108) [PDF 1210KB](1)
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CuFe catalyst is an important catalyst for higher alcohols formation from syngas. In order to gain insight to the reaction mechanism, spin-polarized density functional theory calculations were performed to investigate the growth mechanism of carbon chains on CuFe (100) and (110) surfaces. The calculated results show that Cu atoms prefer to aggregate rather than homogeneously distribute on the Fe(100) and (110) surfaces. With the increase of Cu atoms, the surface energy decreases gradually, indicating that the surface is more stable. The dominant activation mechanism of CO on CuFe(100) surfaces is that H-assisted CO dissociation via CHO intermediate, then the intermediate CHO is progressively hydrogenated to form CH2O and CH3O. and CH3O is dominantly hydrogenated to CH3OH.The pathway of carbon chain growth is CHO rather than CO insertion. The activation mechanism of CO on CuFe(110) surface is the same as CuFe(100) surface. The pathway of CH3O formation is that CO+3H→CHO+2H→CH2O+H→CH3O. On the contrary of CuFe (100) surface, CH3 formation is more favorable thermodynamically than CH3OH formation, which leads to more CH3 available for CO insertion to form C2+ higher alcohols. It provides an idea for improving the production of higher alcohols on CuFe catalyst. If an ingenious structure, such as the step surface, can be designed to have the two advantages of CH3O on CuFe(110) surface being more inclined to generate CH3 and the low CHO insertion reaction energy barrier on CuFe(100) surface, the higher alcohols selectivity of CuFe catalyst will be greatly improved.
[Abstract](219) [FullText HTML](149) [PDF 850KB](2)
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Zinc ingots are the main raw material for the production of galvanized sheets. The consumption of zinc ingots fluctuates greatly due to the impact of contract orders and product structure, resulting in fluctuating demand. Material demand often presents the characteristics of small sample size and large variation range. Its non-stationarity and non-linearity make the problem of demand forecasting more difficult. 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, accurate material demand forecasting has important practical significance for the optimization of raw material procurement and production management adjustments of iron and steel enterprises. In order to improve the prediction accuracy of zinc ingot demand, 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, firstly, the chaotic Tent mapping strategy is adopted 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; Finally, the differential evolution is integrated in the location update process to reduce the possibility of the algorithm misconvergence. For the improved gray wolf algorithm, a simulation experiment is carried out with a typical benchmark test function, and the result shows that its comprehensive performance is superior. Based on the production performance data of a certain unit of a steel plant, the zinc ingot consumption was modeled and predicted, and the SVR was optimized using the IGWO algorithm. The experimental results showed that IGWO-SVR has higher prediction accuracy, better stability and better generalization ability.
[Abstract](339) [FullText HTML](162) [PDF 1450KB](1)
Abstract:
Taking the linear ball bearing subjected to transverse load as the research object, the relationship between the contact force and deformation of the balls is established based on the mechanical analysis. Combined with the Hertz Theory and deformation coordination relation, an accurate mechanical model for calculating the contact force and deformation of each ball in linear bearing is constructed, which considers the dimensional error of the balls and the clearance of the bearing. Using MATLAB software to form the algorithm and taking the LM8UU linear bearing as an example, the factors affecting the contact force of balls such as the size and position of lateral load, the dimensional error and clearance between balls and raceways are deeply studied. Finally, a series of regular relationship curves are obtained. The result shows that the contact force of each ball increases with the increase of transverse load. As the transverse load moves from the middle to the edge, the distribution of force on the balls starts to become uneven, with more circular columns bearing the force, but less balls bearing in each column. Clearance makes the contact force decrease among most of the balls, while a small part of the balls bear more with the increase of clearance. The negative dimensional error of one ball reduces its contact force and the positive one increases its contact force. When all balls have dimensional error, the contact force exerted on each ball will be significantly different from that without considering dimensional error. These conclusions provide a theoretical basis for further accurate calculation of the stress distribution, deformation and fatigue life of linear bearings.
[Abstract](430) [FullText HTML](238) [PDF 902KB](6)
Abstract:
Aiming at the localization problem of illegal whistle vehicles, a fast moving sound source location system based on distributed microphone array is proposed. The system uses GNSS clock to realize the time synchronization between microphones, and transmits the synchronously collected sound information to the cloud database. The cloud computing technology is applied to realize the sound source localization algorithm. Compared with the centralized microphone array, the system can greatly reduce the number of microphones and computing resources, and has the advantages of cost-effective and flexible deployment. The system adopts a fast location algorithm based on time difference of arrival and frequency of arrival, which makes full use of the difference information of arrival frequency between distributed microphones caused by Doppler effect to overcome the bottleneck that the time of arrival method is difficult to adapt to moving sound source. This method avoids 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 The advantages of. The results of system simulation and field experiment show that the system can achieve fast and accurate positioning of high-speed moving sound source, and can be well applied to the scene of car whistle positioning.
[Abstract](184) [FullText HTML](126) [PDF 956KB](4)
Abstract:
BiOI is considered as one of most promising visible light photocatalyst because of its narrow band gap and layered structure. BiOI photocatalyst was synthesized by hydro-solvo-thermal process using bismuth nitrate and potassium iodide as raw materials, and a mixed solution of water and 2- methoxyethanol as a solvent. The crystal structure, micro-morphology, light absorption performance and specific surface area of the samples were characterized by XRD, SEM, UV-Vis-DRS and BET respectively. The photocatalytic activities of BiOI samples under visible-light irradiation were evaluated by the degradation of methyl orange. The results showed that the volume ratio of 2-methoxyethanol in the mixture solvent had a significant influence on the morphology and performance of the BiOI. The morphology of the BiOI photocatalyst prepared at 50% volume ratio of 2-methoxyethanol of the mixture solvent is a flower microsphere. The BiOI microspheres were fabricated by nanosheets with the characteristics of mesoporous structure. Because of adding of 2-methoxyethanol, the crystal growth of BiOI was strongly restrained, and the dominant growth along (110) plane was very obvious. The photocatalytic activity of BiOI has been significantly improved because of the larger specific surface area and the flower spherical structure. After 150 minutes of visible light irradiation, 77.9% methyl orange were degraded, and the degradation rate was 14 times that of the nanosheet BiOI photocatalyst. The photocatalytic mechanism of BiOI under visible light was proposed. The photoinduced holes(h+) and ∙O2 are the active species in the MO photocatalytic degradation process. Furthermore, the photo-generated holes (h+) were the most important photocatalytic active species.
[Abstract](247) [FullText HTML](153) [PDF 683KB](1)
Abstract:
The essential factor to consistently improve the teaching quality of college education relies on the quality of curriculum, which is the basis to realize the reform idea of all higher education. Colleges and universities have accumulated a large amount of curriculum data in long-term teaching activities. How to use data to evaluate the course and provide decision support for improving the quality of course teaching has become an important research field. This paper designs a curriculum evaluation system based on association rules and cluster analysis, then analyzes the functional requirements of the curriculum evaluation and preprocesses the course evaluation data. The FP-growth algorithm is used to analyze the association rules of the score of student course and K-means++ algorithm is used for cluster analysis, which improves the analysis accuracy of course data, realizes the automation of course evaluation, and improves the efficiency and objectivity of evaluation.
[Abstract](333) [FullText HTML](338) [PDF 1084KB](3)
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High energy and cost consumption of wastewater treatment has always been a huge problem to chemical industries, especially coal chemical industry since it generates a large amount of high-concentration organic wastewater. Fixed-bed Lurgi gasifier wastewater is employed as example to perform the research of wastewater treatment to value added chemicals for cost reduction. The process design of coupling the coal gasification wastewater treatment and the solid oxide cells (SOCs) system with renewable energy is proposed to synthesize dimethyl ether (DME) by comparison of one-step and two-step scenarios. Afterwards, process simulation, integration, tech-economic and carbon emission are all performed to analyze the coupling system. The economy analysis and carbon dioxide emission show that although the carbon emission reduction of unit productivity for one-step scenario is better than that of two-step case, the carbon sequestration rate of the latter is much higher than that of the former and the two step scenario is superior in unit production cost with only 2.32% more CO2 emission. Besides, two-step method for DME production under wind power is better in economy and carbon emission reduction. Investment breakdown reveals that the cost of renewable energy is the main contributor of the annual production cost and therefore looking for cheap alternative energy is an effective way to reduce the production cost and improve economic performance. In summary, it is economically and environmentally feasible to deepen and efficiently use wastewater as resources by coupling the energy efficient SOCs system and producing value added chemicals.
[Abstract](290) [FullText HTML](174) [PDF 1395KB](12)
Abstract:
With the vigorous development and application of distributed energy, major challenges have been raised to the planning and operation of traditional power grids. The intermittent influence of distributed energy such as wind power and photovoltaic power generation on energy dispatch and the impact of uncertainty on the power grid are issues that need to be solved urgently. In view of the intermittency and uncertainty of distributed power generation, the wind-solar energy-storage joint optimization model is established with the goal of minimizing wind-solar forecast power generation error and energy storage output, and a method of real-time online optimization of wind-solar complementary power generation and energy storage is proposed. Improved PSO (Particle Swarm Optimization) algorithm is used to optimize the model in real time. Based on the establishment of the wind-solar-storage complementary model, the co-generation of wind-solar storage is regarded as an equivalent node to construct an optimal power flow model with the optimal output of diesel generators as the objective function. GA (Genetic Algorithm) is used to solve the optimal power flow model. Finally, the IEEE30-node system is taken as an example to verify the correctness and effectiveness of the strategy.
[Abstract](277) [FullText HTML](204) [PDF 1182KB](10)
Abstract:
Cholinium-amino acid based ionic liquids, CHAAILs, which were shown to be “practically harmless” and considered as truly green chemicals, have drawn much attention recently. The high viscosity of pure ionic liquid limits its application. Solutions containing ionic liquids are more frequently used in various fields. The mixtures of CHAAILs and water has already been used in biomass processing and extraction. However, there are few studies on the physicochemical properties of aqueous solutions of CHAAILs, especially for the migration properties like viscosities (η) and electrical conductivities (к), which are important physical and chemical data for the industrialization of ionic liquids and are crucial for mass transfer rate. Herein, we synthesized two CHAAILs, cholinium glycinate[Ch][Gly] and cholinium analinate [Ch][Ala]. The viscosities and the electrical conductivities of water + [Ch][Gly] and water + [Ch][Ala] systems were determined at different temperatures from 288.15K to 323.15K. The change of both the viscosities and electrical conductivities with temperature can be well described by Arrhenius equation and VFT equation, respectively. The viscosites of the water + CHAAILs mixtures decreased with the increasing temperature while the electrical conductivites increased with temperature. The excess viscosities (Δη) were also calculated and correlated by Redlich-Kister equation, which showed obvious negative deviation and the deviation increased with decreasing temperature and the increasing of alkyl chain length of amino acid anion. The relationship between molar electrical conductivities and viscosities of water + CHAAILs mixtures were correlated by Walden rule. The results show that the binary system of water +[Ch][Ala] has a good ionicity.
[Abstract](757) [FullText HTML](427) [PDF 2518KB](7)
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