ALBERT

Description: The influence of size effect on the hydromechanical behavior of rock mass has long been recognized. As a result, analysis of the rock mass size effect has been developed. However, when conducting size effect studies, the representativeness of the sample is less considered. Therefore, combining the existing statistical methods and sampling methods, a comprehensive representative sampling method for rock mass is present. In this method, a large number of sample statistics of different sizes are provided in the progressive coverage method; then, the plane density of the track length is defined as the value of stratification to perform stratified sampling for representative samples. Furthermore, it is applied to a joint network model generated in accordance with the actual situation and compared with those of other methods. The sampling results show that the proposed method can provide a certain reference value for studying the scale-dependent behavior of rock mass mechanical parameters.

Description: The Linxing area is located in the north of the eastern margin of the Ordos Basin, which has great resource potential for tight gas. In this paper, fluid inclusion analysis and basin modeling are the main means to clarify the gas accumulation mechanism of the Upper Paleozoic in the Linxing area. Petrographic analysis shows that fluid inclusions can be classified into 5 types: aqueous inclusions, hydrocarbon-bearing aqueous inclusions, hydrocarbon inclusions, crystal-bearing aqueous inclusions, and aqueous-carbonic inclusions. According to the statistical analysis of homogenization temperature and salinity of fluid inclusions, combined with the burial-thermal evolution, the study area was divided into 3 areas: the inner-magma baking area, the middle-anomal thermal area, and the outer-normal thermal area. The gas accumulation characteristics are differences among the 3 areas, the closer to Zijinshan magmatic pluton, the earlier gas accumulation period; and the vertical gas accumulation in the inner-magma baking area and the middle-anomal thermal area was not a slow and gradual process from bottom to top. The period from the Middle Jurassic to the Early Cretaceous is the key period for rapid pressure accumulation in the Upper Paleozoic reservoirs, which is consistent with the period of natural gas accumulation. The area near the Zijinshan magmatic pluton was the high fluid potential area during the gas accumulation period, which indicates that natural gas and other fluids migrated from Zijinshan magmatic pluton to the surrounding area. It is concluded that in the Linxing area, the Zijinshan magmatic pluton had a significant impact on natural gas accumulation, and the natural gas accumulation model under the control of magmatic thermal-tectonic effect was proposed.

Description: The seepage of gas-liquid two-phase flow in fracture is a commonly found phenomenon in nature. To reveal the underlying mechanism and the critical condition of the chaos occurrence, a stochastic gas-liquid two-phase flow seepage model is established, and then investigated through a numerical simulation and a horizontal Hele-Shaw experiment. The numerical simulation and laboratory experiment results show that the seepage chaos of gas-liquid two-phase flow takes place when the relative saturation is in the range of gas relative saturation 44%-70%, and the occurrence probability can be expressed in polynomials. The chaos probability exceeds 80% when the relative saturation of gas is 47%-65%, and the chaos probability is 100% when the relative gas saturation is 57%-60%. It is found that the stochastic variation of gas connection cluster and the compressibility of gas lead to a remarkable change of pressure gradient of the gas-liquid flow both in magnitude and direction. Therefore, the turbulent flow is formed, the kinetic energy of fluid transport decreases gradually, and the flow is stopped at last.

Description: An effective porosity is defined as the ratio of volume of interconnected pore space to total volume of a porous sample. It controls the magnitude of fluid flow and is a key parameter in the assessment of recoverable resources. However, its accurate measurement in tight formations is challenging, due to their complex pore structure and lithofacies heterogeneity. In this study, porosities of sixteen lacustrine shale samples from the second Member of the Kongdian Formation (Ek2) in the Cangdong Sag, Bohai Bay Basin were measured and compared using multiple methods and sample sizes to compare and contrast the effective porosity results. The methods included helium pycnometry (HP; cubes of 1 cm3 and grains at 500-841 μm), water immersion porosimetry (WIP; cubes), mercury intrusion porosimetry (MIP; cubes), and nuclear magnetic resonance (NMR; cubes). Finally, samples were completely sealed using paraffin for bulk density measurements to evaluate the extent of potential clay swelling in shale samples involving probing fluids. Results from the HP, WIP, and MIP methods for skeletal density, bulk density, and effective porosity with cubic samples were compared. While very similar skeletal densities were found for all three methods, a lower bulk density, and therefore lower porosity, from the MIP approach can be attributed to the experimental conditions (e.g., vacuum efficiency, applied pressure, wettability of water/helium vs. mercury) and the probable presence of pores with diameters larger than 50 μm not measurable by MIP. Furthermore, the HP porosity of granular samples with 500-841 μm grain sizes can be regarded as approaching the total porosity. The complicated relationship between WIP and NMR porosities may result from the heat-induced volatilization of moisture in pores during NMR tests, and countercurrent imbibition of water replacing the residual hydrocarbons during the saturation process for sample preparation in both tests. The swelling behavior of the lacustrine Ek2 shale with water is not significant because of the low content of expansive clay minerals. In summary, the WIP and HP methods are recommended for effective porosity measurement, whereas the NMR and MIP methods are invaluable for the measurement of pore-size distribution, with additional information on the effective porosity.

Description: The lower Silurian Longmaxi Formation hosts a highly productive shale gas play in the Zhaotong region of southern China. According to core observation, X-ray diffraction analyses, and scanning electron microscopy (SEM) observations, the shale comprises primarily quartz, carbonate minerals, and clay minerals, with minor amounts of plagioclase, K-feldspar, and pyrite. The clay mineral content ranges from 15.0% to 46.1%, with an average of 29.3% in the Zhaotong region. Organic geochemical analyses show that the Longmaxi Formation has good potential for shale gas resources by calculating total organic carbon, vitrinite reflectance, and gas content. Scanning electron microscope images demonstrate that reservoir pore types in the Longmaxi shale include organic pores, interparticle pores, intercrystalline pores, intraparticle pores, and fractures. Reservoir distribution is controlled by lithofacies, mineral composition, and geochemical factors. In addition, we investigated the relationships between reservoir parameters and production from 15 individual wells in the Zhaotong region by correlation coefficients. As a result, the brittleness index, total organic carbon (TOC), porosity, and gas content were used to define high-quality reservoirs in the Longmaxi shale. Based on these criteria, we mapped the thickness and distribution of high-quality reservoirs in the Longmaxi Formation and selected highlighted several key sites for future exploration and development.

Description: Controlling and maintaining the orientation of the balloon-borne gondola for high-altitude flight is a prerequisite for ensuring the pointing control of observation instruments. When the balloon-borne gondola is flying in the stratosphere of the atmosphere, the existing external interferences will be converted into the coupling moment to the azimuth control system. Meanwhile, those uncertain factors and the frictional nonlinearity of the control system will also cause a certain magnitude of coupling moment. The existence of such coupling moment largely impacts on the accuracy and stability of the orientation control for the angular momentum exchange devices of the balloon-borne gondola. To address such an issue, this paper proposes and implements a novel type of integrated decoupler device. With this decoupler adopted, the aziDmuth control system could sense the existence of coupling torque and azimuth fluctuations quickly and suppress the influences of external interference, uncertain factors, and system structure nonlinearity on the azimuth control effectively, thereby improving the control accuracy of the azimuth control system. Both simulations and experiments are conducted to verify the effectiveness of the proposed device. The results show that the integration of the decoupler and the controller of the azimuth control system provide the azimuth control of the balloon-borne gondola with high accuracy and stability. Such a decoupler device design has a broad potential and could not only be used for balloon-borne gondola control but also could be applied onto other control systems using angular momentum exchange devices as actuators.

Description: When mine water inrush accidents occur, timely and accurately identifying the water inrush source plays an important role in determining the cause of water inrush and making a solution to a disaster. According to the differences of water chemical composition in each water sources of mine, eight kinds of indicators of water chemical composition were selected as sample variables for water inrush source identification. On this basis, an identification model of water inrush source was established by using principal component analysis (PCA) and Fisher discriminant analysis (FDA) combined. The model was used to identify the water inrush source of 14 groups of training samples and 12 groups of samples to be judged in different water sources of the Xiandewang coal mine, and it was compared with the results of the conventional identification model which used the FDA method. Results of this study showed that having processed data by using the PCA method can effectively eliminate the effects of information superposition between sample indicators, and the identification accuracy of mine water inrush source was significantly increased. Related study in this paper can provide some basis and reference for the study of mine water inrush source identification technology.

Description: The abundance of organic matter in shales, which has a direct effect on the hydrocarbon generation potential of shales, is an important organic geochemical parameter for evaluating shale gas reservoirs. The total organic carbon content (TOC content) in shale is controlled by the abundance of original sedimentary organic matter. Therefore, it is very important to study the mechanism of organic matter enrichment in shale. In this paper, the Lower Cambrian marine shales from the Lower Yangtze region are selected as the research subject, most of which originate from a typical area well called Well JXY1. The degree of pyritization (DOP) is used to characterize the redox environment of the water body, while the P/Al ratio is used to analyze the biological productivity of paleoseawater. The paleosalinity of seawater is calculated via carbon and oxygen isotope analysis. In addition, the early Cambrian hydrothermal activities were studied by using core description; Si, Al, Fe, and Mn elemental analysis; and oxygen isotope calculations. The results show that during the early Cambrian Wangyinpu sedimentary period, the seawater was an anaerobic water body with H2S, and the oxygen concentration was approximately 0 mL/L. In the middle stages of the Wangyinpu sedimentary period, the water body had the strongest reducibility and the highest biological productivity. Moreover, the paleoocean in this period between the Yangtze plate and the Cathaysian plate was greatly affected by hydrothermal activities, with temperatures ranging from 90°C to 120°C. Active hydrothermal activities promoted high biological productivity and an anaerobic environment, both of which were conducive to the preservation and enrichment of organic matter, resulting in extremely high TOC content in the Wangyinpu shales (from 6.5% to approximately 16%).

Description: Gates are important operating facilities and resources in civil airports. It is a core task in the airport operation management to select reasonable gates for inbound and outbound flights. We present a continuous time formulation with second-order cone programming (SOCP) for the gate assignment problem which allocates flights to available gates to optimize both the transfer time of passengers and the robustness of the airport operations schedules. The problem is formulated as a mixed integer nonlinear program, and then, the quadratic objective that minimizes the walking distance of transferring passengers is linearized, and the objective that minimizes the variance of idle time at the gates is transformed to a second-order cone constraint with a linear objective function. Then, a Lagrangian relaxation algorithm is developed by exploiting the problem structure. Computational tests are carried out to illustrate the efficiency of the model and the algorithms. It is shown that the continuous time formulation is more efficient than the existing model, and the Lagrangian relaxation algorithm can obtain better solutions faster than a commercial solver.

Description: Generating relations involving the special functions have already proved their important role in mathematics and other fields of sciences. In this paper, we aim to provide some presumably new generating relations in connection with the generalized multi-index Bessel–Maitland function Jνjm,qλjm,γ.. The main results presented here, being very general, can yield a number of particular or equivalent identities, some of which are explicitly demonstrated.

Description: High heterogeneity and nonuniformly distributed multiscale pore systems are two characteristics of the unconventional reservoirs, which lead to very complex transport mechanisms. Limited by inadequate computational capability and imaging field of view, flow simulation cannot be directly performed on complex pore structures. The traditional methods usually coarsen the grid to reduce the computational load but will lead to the missing microstructure information and inaccurate simulation results. To develop a better understanding of flow properties in unconventional reservoirs, this study proposed a new upscaling method integrated gray lattice Boltzmann method (GLBM) and pore network model (PNM), accounting for the fluid flow in heterogeneous porous media. This method can reasonably reduce the computational loads while preserving certain micropore characteristics. Verifications are conducted by comparing the simulation and experimental results on tight sandstones, and good agreements are achieved. The proposed method is proven to be capable of estimating bulk properties in highly heterogenous unconventional reservoirs. This method could contribute to the development of multiscale pore structure characterizations and enhance the understandings of fluid flow mechanisms in unconventional reservoirs.

Description: Natural polyphenols contained in olive mill wastewaters (OMW) have been usually associated with great bioactive properties as “antioxidants”. In this work, we recovered the polyphenols after adsorption onto natural clay “ghassoul” by different solvents: water, ethyl acetate, and methanol (PPW, PPA, and PPM, respectively) to avoid environmental pollution. Also, we tested the antioxidant activity of the extracted polyphenols by two methods: 1,1-diphenyl-2-picrylhydrazyl (DPPH) and total antioxidant capacity (TAC). Then, we analyzed antimicrobial activity by the microdilution technique to determine at the minimum inhibitory concentration (MIC) and the minimum bactericidal concentration (MBC). The OMW of the Fez-Meknes region has a very acidic pH, considerable amounts of mineral matter, and a high concentration of polyphenols and organic content. The results of the test from DPPH showed good antiradical potential for polyphenols extracted with water, but the TAC showed an important capacity for all extracts unless PPA. The antibacterial activity is not the same on the four bacteria studied (Escherichia coli, Salmonella sp, Staphylococcus aureus, and Enterococcus faecalis), and all extracts inhibit most tested germs that do not have the same MIC and the same sensitivity. Only the PPW showed the minimum bactericidal concentration (MBC) that is equal to 0.290 mg/mL for Salmonella sp and Staphylococcus aureus, which confirms that the extraction by water of the adsorbed polyphenols is an original solution to recover the polyphenols and also to obtain a natural phenolic antioxidant which can be used in the pharmaceutical, nourishment, and cosmetic industry.

Description: With the rapid development of e-commerce, logistic enterprises must better predict customer demand to improve distribution efficiency, so as to deliver goods in advance, which makes logistics stochastic and dynamic. In order to deal with this challenge and respond to the concept of “green logistics,” an electric vehicle routing problem with stochastic demands (EVRPSD) and proactive remedial measures is investigated, and an EVRPSD model with probability constraints is established. At the same time, a hybrid heuristic algorithm, combining a saving method and an improved Tabu search algorithm, is proposed to solve the model. Moreover, two insertion strategies with the greedy algorithm for charging stations and dynamic nodes are introduced. Finally, a large number of experimental data show that the heuristic algorithm proposed in this paper is feasible and effective.

Description: Low-permeability reservoirs have tiny pores with winding and complicated pore throats. The oil recovery efficiency of low-permeability reservoirs can be enhanced through the displacement of reservoir oil through imbibition. In the present study, experiments were conducted to investigate variations in the imbibition height of hydrophilic and weakly-hydrophilic rock samples under different interfacial tensions. An imbibition model considering imbibition resistance and bending of pore throats was established based on fractal theory. According to the experimental results, variations in the imbibition height of low-permeability rock samples with time can be divided into three stages. In the first stage, the capillary force plays a dominant role, while the viscous force and gravity have very slight effects. The imbibition height first increases rapidly and then levels off to a constant rate. With the increase in interfacial tension, the imbibition rate in the first stage increases, the ultimate imbibition height increases initially and then decreases, and the contribution of the imbibition height in the first stage to the ultimate imbibition height becomes greater. There is an optimal interfacial tension that causes the ultimate imbibition height to reach its maximum. The calculated results obtained from the proposed imbibition model are consistent with the experimental results, indicating that the model can accurately reflect the change in the imbibition height in low-permeability reservoirs in the first stage.

Description: The Otago Schist in the South Island of New Zealand represents an exhumed Mesozoic accretionary prism. Two coastal areas (Akatore Creek and Bruce Rocks) south of Dunedin preserve structural and geochemical evidence for the development of postmetamorphic hydrothermal systems that involved widespread fluid-rock reaction at shallow crustal depths. The Jurassic to Triassic pumpellyite-actinolite (Akatore Creek) to upper greenschist facies (Bruce Rocks) metamorphic fabrics were crosscut by sets of regionally extensive Cretaceous exhumation joints. Many of the joints were subsequently reactivated to form networks of small-displacement (

Description: Widely distributed in North China, Ordovician karst is characterized by having high thickness, nonuniform aquosity, and significant water pressure-bearing properties. Deep mining in North China is threatened by associated water hazards; hence, research on the hydrogeological characteristics of deep Ordovician karst is needed. In this study, the Weibei coalfield in Shaanxi Province, China, was selected as the study area, especially mines in the Hancheng and Chenghe mining areas. In situ experiments, including water pumping, water drainage, water injecting and water pressure, and laboratory experiments, were conducted to study the hydrogeological characteristics of the Ordovician karst top in the study area. A comprehensive analysis was conducted on controlling factors for the development of the Ordovician karst top in the study area, and a method for evaluating the water inrush risk in coal mining areas based on karst hydrogeological characteristics was proposed. The research results indicated that the Ordovician karst top in the study area was characterized by heterogeneity, vertical zonation, and partially filled properties, which were mainly controlled by two factors: sedimentation and tectonism. The hydrogeological conditions of the Ordovician karst could be divided into three types: nonfilled and nonsignificant tectonism, filled and nonsignificant tectonism, and significant tectonism. Among them, the filled and nonsignificant tectonism type Ordovician karst top type had a filling thickness of 20 m. Based on karst hydrogeological characteristics, the methods were proposed to evaluate the water inrush risk in the coal mining floor. The practical tests verified the methods.

Description: Hyperspectral remote sensing technology has a strong capability for ground object detection due to the low spatial resolution of hyperspectral imaging spectrometers. A single pixel that leads to a hyperspectral remote sensing image usually contains more than one feature coverage type, resulting in a mixed pixel. The existence of a mixed pixel affects the accuracy of the ground object identification and classification and hinders the application and development of hyperspectral technology. For the problem of unmixing of mixed pixels in hyperspectral images (HSIs), the linear mixing model can model the mixed pixels well. Through the collation of nearly five years of the literature, this paper introduces the development status and problems of linear unmixing models from four aspects: geometric method, nonnegative matrix factorization (NMF), Bayesian method, and sparse unmixing.

Description: It is critical to select an optimized sand control method for an interbedded sandstone and mudstone reservoir (ISMR) due to its serious sand production hazards. However, currently, most general sand control methods cannot meet the requirements of sand control in interbedded sandstone and mudstone reservoirs (e.g., Bohai Bay oil and gas fields from China). Ensuring efficiency of sand control and increasing the oil and gas production rate in this interbedded sandstone and mudstone become more and more important. In this paper, a “multilayer rotatable sand control experimental device” for the interbedded sandstone and mudstone reservoir was developed. A series of sand control experimental studies were conducted by using the proposed device. The net-to-gross ratio (NTG) and well inclinations are two major factors considered in the experimental analysis. In addition, a sensitivity analysis regarding formation particle size distribution (PSD), clay content, and mineral compositions is performed in the experiment under a moderate sand control mode. With systematic experimental test results in this work, combined with numerous existing sand control models, a set of optimum sand control design and the associated optimization template for ISMR were developed, which have been successfully applied in Bohai Bay. Field application results show that NTG and well inclination are two critical parameters in the design of sand control in ISMR. The optimal indexes of a sand control mode are determined as NTG of 0.4 and well inclination of 45°. The introduction of these two key factors in sand control design broadens the application range of moderate sand production.

Description: Object tracking based on low-rank sparse learning usually makes the drift phenomenon occur when the target faces severe occlusion and fast motion. In this paper, we propose a novel tracking algorithm via reverse low-rank sparse learning and fractional-order variation regularization. Firstly, we utilize convex low-rank constraint to force the appearance similarity of the candidate particles, so as to prune the irrelevant particles. Secondly, fractional-order variation is introduced to constrain the sparse coefficient difference in the bounded variation space, which allows the difference between consecutive frames to exist, so as to adapt object fast motion. Meanwhile, fractional-order regularization can restrain severe occlusion by considering more adjacent frames information. Thirdly, we employ an inverse sparse representation method to model the relationship between target candidates and target template, which can reduce the computation complexity for online tracking. Finally, an online updating scheme based on alternating iteration is proposed for tracking computation. Experiments on benchmark sequences show that our algorithm outperforms several state-of-the-art methods, especially exhibiting better adaptability for fast motion and severe occlusion.

Description: The scale dependence of surface roughness is critical in characterising the hydromechanical properties of field-scale rock joints but is still not well understood, particularly when different orders of roughness are considered. We experimentally reveal the scale dependence of two-order roughness, i.e., waviness and unevenness through fractal parameters using the triangular prism surface area method (TPM). The surfaces of three natural joints of granite with the same dimension of 1000 mm×1000 mm are digitised using a 3D laser scanner at three different measurement resolutions. Waviness and unevenness are quantitatively separated by considering the area variation of joint surface as grid size changes. The corresponding fractal dimensions of waviness and unevenness in sampling window sizes ranging from 100 mm×100 mm to 1000 mm×1000 mm at an interval of 100 mm×100 mm are determined. We find that both the fractal dimensions of waviness and unevenness vary as the window size increases. No obvious stationarity threshold has been found for the three rock joint samples, indicating the surface roughness of natural rock joints should be quantified at the scale of the rock mass in the field.

Description: The article addresses the extended Graetz–Nusselt problem in finite-length microchannels for prescribed wall heat flux boundary conditions, including the effects of rarefaction, streamwise conduction, and viscous dissipation. The analytical solution proposed, valid for low-intermediate Peclet values, takes into account the presence of the thermal development region. The influence of all transport parameters (Peclet Pe, Knudsen Kn, and Brinkman Br) and geometrical parameters (entry length and microchannel aspect ratio) is investigated. Performances of different wall heat flux functions have been analyzed in terms of the averaged Nusselt number. In the absence of viscous dissipation Br=0, the best heating protocol is a decreasing wall heat flux function. In the presence of dissipation Br〉0, the best heating protocol is a uniform wall heat flux.

Description: Many people use traditional methods such as quasi-Newton method and Gauss–Newton-based BFGS to solve nonlinear equations. In this paper, we present an improved particle swarm optimization algorithm to solve nonlinear equations. The novel algorithm introduces the historical and local optimum information of particles to update a particle’s velocity. Five sets of typical nonlinear equations are employed to test the quality and reliability of the novel algorithm search comparing with the PSO algorithm. Numerical results show that the proposed method is effective for the given test problems. The new algorithm can be used as a new tool to solve nonlinear equations, continuous function optimization, etc., and the combinatorial optimization problem. The global convergence of the given method is established.

Description: At present, there are two main standards, ISO 23828 : 2013 and SAE J 2572–2014, which prescribe the hydrogen consumption test using the pressure method, gravimetric method, and flow method. However, these methods do not meet the test requirements for electric energy consumption and the range of plug-in hybrid fuel cell vehicles (FCVs) which are the main technical considerations in China and Europe. In this paper, a new test method for the hydrogen consumption, electric energy consumption, and range of FCVs is proposed without the use of additional hydrogen supply, measurement instruments, or energy consumption correction, which can improve the operability of the test and avoid the conversion between electric energy and hydrogen. One plug-in hybrid FCV and one nonplug-in hybrid FCV were tested using the proposed method. The results show that the new method meets the requirements of fuel economy test for FCVs with hydrogen consumption rate, electric energy consumption rate, the range for plug-in hybrid FCVs, hydrogen consumption rate, and the range for nonplug-in FCVs.

Description: Karst collapse pillars (KCPs) frequently cause severe groundwater inrush disasters in coal mining above a confined aquifer. An accurate understanding of the damage and fracture evolution, permeability enhancement, and seepage changes in KCPs under the combined action of mining-induced stress and confined hydraulic pressure is of great significance for the early prediction and prevention of groundwater inrush from KCPs in coal seam floors. In this study, a micromechanics-based coupled stress-seepage-damage (SSD) modeling approach, in which the macroscopic mechanical and hydraulic properties of the rock are explicitly related to the microcrack kinetics, is proposed to simulate the fracture evolution and the associated groundwater flow in KCPs. An in situ high-precision microseismic monitoring technology is used to verify the micromechanical modeling results, which indicate that the numerical model successfully reproduces the damage and fracture evolution in a coal seam floor with a KCP during the mining process. The presented model also provides a visual representation of the complex process of KCP activation and groundwater inrush channel formation. A numerical study shows that the damage and activation of a KCP start from the edge of the KCP, gradually develop toward the interior of the KCP, and eventually connect with the damage fracture zone of the floor, forming a primary water-conducting channel in the KCP, causing the confined groundwater to flow into the working face. Groundwater inrush from a KCP is a gradual process instead of a mutation process. A reduction in the distance between the working face and a KCP and increases in the confined hydraulic pressure and the initial water-conducting height of the KCP can significantly increase the risk of groundwater inrush from the KCP.

Description: According to the waste type identification requirement in waste classification, a waste type identification method based on a bird flock neural network (BFNN) was proposed. The problem of obtaining the feature dataset of waste images was considered, and color histogram and texture feature extraction techniques were used. The local optimum problem of a typical backpropagation neural network (BPNN) was considered, and a bird flock optimization (BFO) algorithm was proposed. The accuracy problem of the typical BPNN was considered, and a new online weight adjustment method of neurons was proposed. The number of hidden layer neurons (nodes) of the typical BPNN was considered, and an online adjustment method was proposed. The experimental results show that the recyclables (paper, plastic, glass, and cloth) and nonrecyclables can effectively be identified by the waste type identification method based on the BFNN, and the recognition accuracy is 81% which meets actual needs.

Description: A GPU-based Multigroup Genetic Algorithm was proposed, which parallelized the traditional genetic algorithm with a coarse-grained architecture island model. The original population is divided into several subpopulations to simulate different living environments, thus increasing species richness. For each subpopulation, different mutation rates were adopted, and the crossover results were optimized by combining the crossover method based on distance. The adaptive mutation strategy based on the number of generations was adopted to prevent the algorithm from falling into the local optimal solution. An elite strategy was adopted for outstanding individuals to retain their superior genes. The algorithm was implemented with CUDA/C, combined with the powerful parallel computing capabilities of GPUs, which greatly improved the computing efficiency. It provided a new solution to the TSP problem.

Description: Okanin is a major flavonoid found in Coreopsis tinctoria Nutt., arousing huge interest recently for its considerable biological characteristics including antioxidant, antineurotoxic, and antidiabetic activities. An ultrahigh performance liquid chromatography triple-quadrupole tandem mass spectrometry (UPLC-MS) was successfully used to determine okanin in rat plasma after oral administration of okanin. Bavachalcone acted as an internal standard (IS). By gradient elution, IS and analyte were separated on a C18 column for 7 min at a flow rate of 0.25 mL/min with acetonitrile-0.1% acetic acid mobile phase. The stability, matrix effect, extraction recovery, accuracy, precision, linearity, and selectivity of the method were firstly demonstrated. The major pharmacokinetic parameters of okanin in rat plasma were then measured using the developed UPLC-MS method. An UPLC-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) was finally established to obtain the specific and accurate mass of okanin in rat plasma after oral administration, and its proposed fragmentation was further elaborated.

Description: A common challenge faced by liner operators in practice is to effectively allocate empty containers now in a way that minimizes the expectation of costs and reduces inefficiencies in the future with uncertainty. To incorporate uncertainties in the operational model, we formulate a two-stage stochastic programming model for the stochastic empty container repositioning (ECR) problem. This paper proposes a separable piecewise linear learning algorithm (SPELL) to approximate the expected cost function. The core of SPELL involves learning steps that provide information for updating the expected cost function adaptively through a sequence of piecewise linear separable approximations. Moreover, SPELL can utilize the network structure of the ECR problem and does not require any information about the distribution of the uncertain parameters. For the two-stage stochastic programs, we prove the convergence of SPELL. Computational results show that SPELL performs well in terms of operating costs. When the scale of the problem is very large and the dimensionality of the problem is increased, SPELL continues to provide consistent performance very efficiently and exhibits excellent convergence performance.

Description: The unstoppable quest for low-cost reinforcing agent gingered the enthusiasm towards developing and utilising the agro-based waste product as reinforcement since they are promptly accessible, sustainable, and inexpensive to purchase. In this study, AA6061/rice husk ash matrix composites were produced through metallurgical stir casting techniques. Different weight percentages of reinforcement in the range of 2%, 4%, 6%, and 8% were used to fabricate the composites. The reinforced composites were characterized by SEM/EDS for microstructural study. The mechanical behaviour was examined for all the produced samples. SEM/EDS analysis revealed the presence of silica, a major constituent of rice husk ash in the produced composites. The results of the mechanical behaviour show that upgrading the weight percentage of reinforcing agent increases the mechanical properties. AA6061/8% rice hush ash generated a consistent rise with filler concentration in comparison with the aluminium alloy in all operating functions.

Description: In this paper, we propose a finite-time sliding mode trajectory tracking control methodology for the vertical takeoff and landing unmanned aerial vehicle (VTOL UAV). Firstly, a system error model of trajectory tracking task is established based on Rodrigues parameters by considering both external and internal uncertainties. According to the cascade property, the system model is divided into translational and rotational subsystems, and a hierarchical control structure is hence proposed. Then, a finite-time generalized nonlinear disturbance observer (NDOB) is proposed, based on which the finite-time convergence result of equivalent disturbance estimation can be acquired. Finally, by introducing a tan-type compensator into the traditional terminal sliding mode control (SMC), the finite-time convergence result of the closed-loop control system is acquired based on Lyapunov stability analysis. Simulation results show the effectiveness of the proposed methodology.

Description: Compared with single consensus, the multiconsensus of multiagent systems with nonlinear dynamics can reflect some real-world cases. This paper proposes a novel distributed law based only on intermittent relative information to achieve the multiconsensus. By constructing an appropriate Lyapunov function, sufficient conditions on control parameters are derived to undertake the reliability of closed-loop dynamics. Ultimately, the availability of results is completely validated by these numerical examples.

Description: Collaborative navigation is the key technology for multimobile robot system. In order to improve the performance of collaborative navigation system, the collaborative navigation algorithms based on odometer/vision multisource information fusion are presented in this paper. Firstly, the multisource information fusion collaborative navigation system model is established, including mobile robot model, odometry measurement model, lidar relative measurement model, UWB relative measurement model, and the SLAM model based on lidar measurement. Secondly, the frameworks of centralized and decentralized collaborative navigation based on odometer/vision fusion are given, and the SLAM algorithms based on vision are presented. Then, the centralized and decentralized odometer/vision collaborative navigation algorithms are derived, including the time update, single node measurement update, relative measurement update between nodes, and covariance cross filtering algorithm. Finally, different simulation experiments are designed to verify the effectiveness of the algorithms. Two kinds of multirobot collaborative navigation experimental scenes, which are relative measurement aided odometer and odometer/SLAM fusion, are designed, respectively. The advantages and disadvantages of centralized versus decentralized collaborative navigation algorithms in different experimental scenes are analyzed.

Description: Spring linkage can be applied to in-pipe robots for connecting different modules together and can make it pass through elbows more easily. However, its stiffness cannot be set to be too hard or too soft. This paper tries to make a balance between the compressive stiffness and the bending stiffness of the spring. After a brief introduction to the construction mechanism and some assumptions, the mathematical representation of the spring bending stiffness was deduced based on the Kirchhoff theory which describes the spatial curve with displacement rather than time. Then, some simulations aiming at verifying the correctness of the deduced bending stiffness expression were carried out. Finally, the relationship between the two rigidities was found out, which helps to find a way to decrease the bending stiffness of spring while keeping its compressive stiffness strong enough.

Description: Effectively predicting the spatial distribution of oil and gas contributes to delineating promising target areas for further exploration. Determining the location of hydrocarbon is a complex and uncertain decision problem. This paper proposes a method for predicting the spatial distribution of oil and gas resource based on Bayesian network. In this method, qualitative dependency relationship between the hydrocarbon occurrence and key geologic factors is obtained using Bayesian network structure learning by integrating the available geoscience information and the current exploration results and then using Bayesian network topology structure to predict the probability of hydrocarbon occurrence in the undiscovered area; finally, the probability map of hydrocarbon-bearing is formed by interpolation method. The proposed method and workflow are further illustrated using an example from the Carboniferous Huanglong Formation (C2hl) in the eastern part of the Sichuan Basin in China. The prediction results show that the coincidence rate between the results of 248 known exploration wells and the predicted results reaches 89.5%, and it has been found that the gas fields are basically located in the high value area of the hydrocarbon-bearing probability map. The application results show that the Bayesian network method can effectively predict the spatial distribution of oil and gas resources, thereby reducing exploration risks, optimizing exploration targets, and improving exploration benefits.

Description: This paper proposes a novel predictive strategy based on a model predictive control (MPC) for the interior permanent magnet synchronous motors (IPMSMs) driven by a three-level simplified neutral-point clamped inverter (3L-SNPC) for electric vehicle applications (EVAs). Based on the prediction of the future behavior of the controlled variables, a predefined multiobjective cost function incorporates the control objectives which are evaluated for every sampling period to generate the optimal switching state applied directly to the inverter without the modulation stage. The control objectives in this paper are tracking current capacity, neutral-point voltage balancing, common-mode voltage control, and switching frequency reduction. The principal concepts of the novel scheme are summarized as follows: first, the delay compensation based on the long horizon of prediction is adopted by a multilevel power converter structure. Second, based on the modified Lyapunov candidate function, both stability and recursive feasibility are ensured of the proposed predictive scheme. Third, the practicability of the real-time implementation is improved by the proposed “static voltage vector” (SVV) and “single state variation” (SSV) principles. Finally, the proposed concepts are implemented in the novel predictive control formulation as additional constraints without compromising the complexity and the good performances of the predictive controller. Therefore, only the switching states that guarantee the stability and the reduction of calculation burden criteria are considered in the evaluation of cost function. The proposed predictive scheme based on the “SVV” principle has demonstrated superior performance in simulation compared with the proposed scheme with the “SSV” principle. The computational burden and switching frequency rates are reduced by 35% and 56.22%, respectively.

Description: To study the seismic response law of the immersed tunnel under different structural stiffnesses, three groups of shaking table models of immersed tunnel are carried out, including free-field model, flexible tunnel model, and rigid tunnel model. The similarities and differences of the pore water pressure and acceleration time-history between the free site and liquefiable soil layer around the flexible and rigid immersed tube tunnel are analyzed. The results show that, compared with the soil layer at the same position in the free-field, both the amplitude of acceleration and frequency component in the surrounding soil layer are affected by the stiffness of tunnel, and the influence comes greater with the larger stiffness of tunnel. When the input amplitude of seismic ground motion is small, the soil layer in the free field and the flexible tunnels share the same acceleration amplification law. The development law of pore pressure in the soil layer of test 1 was similar to test 2 but was quite different from test 3. Specifically, when the tunnel stiffness is smaller, the surrounding soil layer is easier to liquefy, with greater influence of the tunnel stiffness on the development law of pore pressure in the surrounding soil layer. The lower the soil buried depth is, the faster the pore pressure dissipates. The growth rate of tunnel strain is related to the stiffness of the structure. Generally speaking, the strain growth rate of the structure with smaller stiffness is higher under moderate earthquakes. The smaller the tunnel stiffness is, the more adaptable the tunnel is to the movement of the surrounding soil layer.

Description: Human motion prediction aims at predicting the future poses according to the motion dynamics given by the sequence of history poses. We present a new hierarchical static-dynamic encoder-decoder structure to predict the human motion with residual CNNs. Specifically, to better mine the law of the motion, a new residual CNN-based structure, v-CMU, is proposed to encode not only the static information but also the dynamic information. Based on v-CMU, a hierarchical structure is proposed to model different correlations between the different given poses and the predicted pose. Moreover, a new loss function combining the static and dynamic information is introduced in the decoder to guide the prediction of the future poses. Our framework features two-folds: (1) more effective dynamics mined due to the fusion of information of the poses and the dynamic information between poses and the hierarchical structure; (2) better decoding or prediction performance, thanks to the mid-level supervision introduced by the new loss function considering both the static and dynamic losses. Extensive experiments show that our algorithm can achieve state-of-the-art performance on the challenging G3D and FNTU datasets. The code is available at https://github.com/liujin0/SDnet.

Description: It is of great significance to comprehensively and reasonably identify the key nodes in the WeChat epidemic information dissemination system. First, the recognition results can be used to guide the spread of epidemic-related information in WeChat, such as accelerating the spread of valuable information or monitoring the spread of rumors. Secondly, the analysis of key nodes helps us understand the evolution of the epidemic information dissemination network in WeChat, and the analysis of key nodes also helps us understand the modes and methods of epidemic-related information dissemination in WeChat. Finally, the results of these studies may be generalized to other fields of social life. This paper analyzes the composition of and relationship between epidemic-related information dissemination systems in WeChat and proposes a Supernetwork model for WeChat epidemic information dissemination on this basis. In this study, a comprehensive identification method of key nodes of the WeChat epidemic information dissemination system under the Supernetwork vision was constructed, and the method is analyzed and verified through examples in this paper.

Description: Aiming at the problem that the stability of the quadruped robot is decreased as its leg momentum is too high, a stable balance adjustment structure of the quadruped robot based on the bionic lateral swing posture is proposed. First, the leg structure of the quadruped robot is improved and designed by using the mechanism of the lateral swing posture of the leg of the hoof animal. Then, the D-H method is used to construct the corresponding leg kinematics model and determine the generalized coordinates of the leg joints in the lateral swing posture. The torque expression of the quadruped robot when it is tilted is established. Based on the differential equation of momentum of the hip joint and its static stability analysis, the static stability conditions in the upright posture and the bionic lateral swing posture are given. Finally, the experimental simulation and comparative analysis of the upright posture and the lateral swing posture of the quadruped robot are proposed by using the Adams virtual prototype technology. The simulation results show that as the angle of lateral swing increases, the peak value of the positive flip torque of the quadruped robot body increases accordingly, while the degree of tilt decreases accordingly, which shows that the bionic lateral swing posture of the quadruped robot has higher static stability than the traditional upright posture. This research provides a technical reference for the design and optimization of the offline continuous gait of the robot and the improvement of stability.

Description: The main emphasis on this paper is to analyze the axisymmetric flow and heat transfer in a liquid film over an unsteady radially stretching surface in the presence of a transverse magnetic field. The similarity transformations are used to reduce the highly nonlinear governing partial differential equations for momentum and energy into a set of ordinary differential equations. A numerical scheme is developed for the reduced nonlinear differential equations for the velocity and temperature fields. The literature survey shows that the present problem of thin film flow over a radially stretching sheet has not been studied before. The features of the flow and heat transfer characteristic for different values of governing parameters such as unsteadiness parameter, Prandtl number, Eckert number, and magnetic parameter are thoroughly examined. This study noticed that, by increasing the magnetic parameter and unsteadiness parameter, film thickness decreases.

Description: In order to extract more information that affects customer arrears behavior, the feature extraction method is used to extend the low-dimensional features to the high-dimensional features for the warning problem of user arrears risk model of electric charge recovery (ECR). However, there are many irrelevant or redundant features in data, which affect prediction accuracy. In order to reduce the dimension of the feature and improve the prediction result, an improved hybrid feature selection algorithm is proposed, integrating nonlinear inertia weight binary particle swarm optimization with shrinking encircling and exploration mechanism (NBPSOSEE) with sequential backward selection (SBS), namely, NBPSOSEE-SBS, for selecting the optimal feature subset. NBPSOSEE-SBS can not only effectively reduce the redundant or irrelevant features from the feature subset selected by NBPSOSEE but also improve the accuracy of classification. The experimental results show that the proposed NBPSOSEE-SBS can effectively reduce a large number of redundant features and stably improve the prediction results in the case of low execution time, compared with one state-of-the-art optimization algorithm, and seven well-known wrapper-based feature selection approaches for the risk prediction of ECR for power customers.

Description: Immersed boundary-lattice Boltzmann method (IB-LBM) has become a popular method for studying fluid-structure interaction (FSI) problems. However, the performance issues of the IB-LBM have to be considered when simulating the practical problems. The Graphics Processing Units (GPUs) from NVIDIA offer a possible solution for the parallel computing, while the CPU is a multicore processor that can also improve the parallel performance. This paper proposes a parallel algorithm for IB-LBM on a CPU-GPU heterogeneous platform, in which the CPU not only controls the launch of the kernel function but also performs calculations. According to the relatively local calculation characteristics of IB-LBM and the features of the heterogeneous platform, the flow field is divided into two parts: GPU computing domain and CPU computing domain. CUDA and OpenMP are used for parallel computing on the two computing domains, respectively. Since the calculation time is less than the data transmission time, a buffer is set at the junction of two computational domains. The size of the buffer determines the number of the evolution of the flow field before the data exchange. Therefore, the number of communications can be reduced by increasing buffer size. The performance of the method was investigated and analyzed using the traditional metric MFLUPS. The new algorithm is applied to the computational simulation of red blood cells (RBCs) in Poiseuille flow and through a microchannel.

Description: The representation and selection of action features directly affect the recognition effect of human action recognition methods. Single feature is often affected by human appearance, environment, camera settings, and other factors. Aiming at the problem that the existing multimodal feature fusion methods cannot effectively measure the contribution of different features, this paper proposed a human action recognition method based on RGB-D image features, which makes full use of the multimodal information provided by RGB-D sensors to extract effective human action features. In this paper, three kinds of human action features with different modal information are proposed: RGB-HOG feature based on RGB image information, which has good geometric scale invariance; D-STIP feature based on depth image, which maintains the dynamic characteristics of human motion and has local invariance; and S-JRPF feature-based skeleton information, which has good ability to describe motion space structure. At the same time, multiple K-nearest neighbor classifiers with better generalization ability are used to integrate decision-making classification. The experimental results show that the algorithm achieves ideal recognition results on the public G3D and CAD60 datasets.

Description: This research is conducted on the characters and trends of traffic flow in highway maintenance work areas under typical maintenance work forms. In order to improve the safety of the highway maintenance work area, a data monitoring method based on the combination of mixed speed measurement and background difference method were developed. During the on-site detection, the starting point of the warning zone, the starting point of the upstream transition zone, the starting point of the working zone, the midpoint of the working zone, and the six speed measurement sections of the working zone were collected at the end point and the end zone. In the video detection, the background subtraction was used, and the morphological denoting method and the connected domain analysis method were used to retain the vehicle foreground. After analyzing the connection domain and removing the wrong target, the vehicle target area is extracted from research. The research finally obtained the traffic flow characteristics of the start point of the warning zone, the start point of the upstream transition zone, the start point of the work zone, the midpoint of the work zone, the end point of the work zone, and the end point of the downstream transition zone. The study also obtained the traffic volume and the change trend of headway. The combination of mixed velocity method and background difference method is helpful for data monitoring in typical highway maintenance work areas. The measured data results are helpful for studying the distribution characteristics and trends of traffic flow in typical highway maintenance work areas.

Description: We quantify the strength and the directionality of information transfer between the Ghana stock market index and its component stocks as well as observe the same among the individual stocks on the market using transfer entropy. The information flow between the market index and its components and among individual stocks is measured by the effective transfer entropy of the daily logarithm returns generated from the daily market index and stock prices of 32 stocks ranging from 2nd January 2009 to 16th February 2018. We find a bidirectional and unidirectional flow of information between the GSE index and its component stocks, and the stocks dominate the information exchange. Among the individual stocks, SCB is the most active stock in the information exchange as it is the stock that receives the highest amount of information, but the most informative source is EGL (an insurance company) that has the highest net information outflow while the most information sink is PBC that has the highest net information inflow. We further categorize the stocks into 9 stock market sectors and find the insurance sector to be the largest source of information which confirms our earlier findings. Surprisingly, the oil and gas sector is the information sink. Our results confirm the fact that other sectors including oil and gas mitigate their risk exposures through insurance companies and are always expectant of information originating from the insurance sector in relation to regulatory compliance issues. It is our firm conviction that this study would allow stakeholders of the market to make informed buy, sell, or hold decisions.

Description: A floor aquifuge usually bends and fails when mining above a confined aquifer, which may lead to water inrush disaster. The floor aquifuge was simplified as a thin disc model in this paper, and a series of coupled bending-seepage tests of sandstone were carried out by a patent test system. The variation characteristics of load-displacement, load-time, and permeability-time were analyzed. The deflection and stress in the thin disc rock samples were deduced; the initiation and propagation of cracks were analyzed. The failure behavior of the thin disc rock samples was described. It shows the following: (1) The bending failure behavior relates to the stress distribution and crack evolution inside the thin disc. (2) The main cause of crack initiation is a tension-shear failure. (3) The 5 mm thickness thin discs form petal-shaped cracks, due to tensile stress, while petal-shaped cracks only appear at the cap block of the 10 mm discs, which are sheared into two pieces along the conical surface with an inclination about 45°. (4) Water inrush occurs after bending failure in the floor aquifuge, and it is an opportune moment to grout along the crack propagation trend lines to prevent the water inrush disasters.

Description: Evapotranspiration (ET) is an essential component of watershed hydrological cycle. Spatial-temporal variations analyses of evapotranspiration and potential evapotranspiration (PET) have remarkable theoretical and practical significances for understanding the interaction between climate changes and hydrological cycle and optimal allocation of water resources under global warming background. The MODIS-estimated ET agreed well with basin evapotranspiration from water balance principle methods in the study. The spatiotemporal variations results based on MOD16 ET data showed the following: (1) multiyear mean ET and PET were 464.2 mm and 1192.2 mm, and annual ET showed an upward trend at a rate of 3.48 mm/a, while PET decreased significantly at a rate of −8.18 mm/a. The annual ET trend showed a complemental relationship with PET; (2) at the seasonal scale, ET was highest in summer and least in winter, while PET was higher in spring and summer. The change of ET and PET in spring and summer had a great contribution to the annual variations; (3) ET and PET in the northern part were significantly stronger than those in the western and southern parts; (4) ET in cropland increased significantly, while PET decreased obviously in grass and forest; (5) changes of ET and PET were closely related to climatic factors. The rise in temperature caused the increase in ET and the decrease of wind speed contributed more to the decrease in PET. The results can provide a scientific basis for water resources planning and management.

Description: Facing more and more severe global warming problems, renewable energy, as an alternative to traditional fossil fuels, is attracting more and more attentions due to its capability of reducing carbon emission. This paper considers two-tier HetNets with orthogonal frequency division multiple access (OFDMA), where the macro base station (MBS) is powered by power grid and small base stations (SBSs) have hybrid energy supplies. Through smart grid, SBSs can share their renewable energy with each other. We consider the problem of cross-layer interference caused by spectrum reuse, the burst of user data, and the randomness of renewable energy arrivals. Through energy cooperation, this paper investigates maximizing the time-average energy efficiency of SBSs. Based on user data queue and SBS energy queue, the optimal problem is decoupled into two subproblems by Lyapunov optimization: resource allocation subproblem and energy scheduling and energy cooperation subproblem. By solving two subproblems, the online solution to the optimization problem is obtained. Through theoretical analysis and simulations, both user data queues and energy queues have an upper bound, the network is stable, and the proposed algorithm performs better than the basic algorithm without energy cooperation.

Description: Objective. Since early diagnosis is very important for treating gastric cancer (GC), we aimed to detect serum small proline-rich protein2A (SPRR2A) to verify its diagnostic value for GC patients. Methods. Serum samples were collected from 200 patients with GC, 100 patients with gastritis, 40 patients with rectal cancer (RC), 50 patients with colon cancer (CC), and 100 healthy controls. An enzyme-linked immunosorbent assay (ELISA) detection kit was applied to measure serum SPRR2A concentration. The correlations between serum SPRR2A and carcinoembryonic antigen (CEA), clinical pathological parameters of GC, and receiver operating characteristic (ROC) curve were also analyzed. Results. The median serum SPRR2A concentration in GC patients was significantly higher than those in healthy controls and gastritis or colorectal cancer patients (P

Description: This work introduces a computational method for solving the linear two-dimensional fuzzy Fredholm integral equation of the second form (2D-FFIE-2) based on triangular basis functions. We have used the parametric form of fuzzy functions and transformed a 2D-FFIE-2 with three variables in crisp case to a linear Fredholm integral equation of the second kind. First, a method based on the use of two m-sets of orthogonal functions of triangular form is implemented on the integral equation under study to be changed to coupled algebraic equation system. In order to solve these two schemes, a finite iterative algorithm is then applied to evaluate the coefficients that provided the approximate solution of the integral problems. Three examples are given to clarify the efficiency and accuracy of the method. The obtained numerical results are compared with other direct and exact solutions.

Description: Athletes usually take nutritional supplements and perform the specialized training to improve the performance of sport. A quick assessment of their athletic status will help to understand the current physical function of athletes’ status and the effect of nutritional supplementation. Human urine, as one of the most important body indicators, is composed of many metabolites, which can provide effective monitoring information for physical conditions. In this study, temperature-dependent near-infrared spectroscopy (NIRS) technology was used to collect the spectra of athlete’s urine for evaluating the feasibility of rapidly detecting the exercise state of the basketball player. To obtain the detection results accurately, several chemometrics methods including principal component analysis (PCA), variables selection method of variable importance in projection (VIP), continuous 1D wavelet transform (CWT), and partial least square-discriminant analysis (PLS-DA) were employed to develop a classifier to distinguish the physical status of athletes. The optimal classifying results were obtained by wavelet-PLS-DA classifier, whose average precision, sensitivity, and specificity are all above 0.95, and the overall accuracy of all samples is 0.97. These results demonstrate that temperature-dependent NIRS can be used to rapidly assess the physical function of athlete’s status and the effect of nutritional supplementation is feasible. It can be believed that temperature-dependent NIR spectroscopy will obtain applications more widely in the future.

Description: Nonalcoholic fatty liver disease (NAFLD) is currently the most common chronic liver disease worldwide in part due to the concomitant obesity pandemic and insulin resistance (IR). It is increasingly becoming evident that NAFLD is a disease affecting numerous extrahepatic vital organs and regulatory pathways. The molecular mechanisms underlying the nonalcoholic steatosis formation are poorly understood, and little information is available on the pathways that are responsible for the progressive hepatocellular damage that follows lipid accumulation. Recently, much research has focused on the identification of the epigenetic modifications that contribute to NAFLD pathogenesis. Noncoding RNAs (ncRNAs) are one of such epigenetic factors that could be implicated in the NAFLD development and progression. In this review, we summarize the current knowledge of the genetic and epigenetic factors potentially underlying the disease. Particular emphasis will be put on the contribution of microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs) to the pathophysiology of NAFLD as well as their potential use as therapeutic targets or as markers for the prediction and the progression of the disease.

Description: This paper aims to improve the metallurgical properties of vanadium-titanium magnetite (VTM) concentrates pellets by applying solid waste containing B2O3. Thus, the effects of adding B2O3 on the drop strength, compressive strength, pores area ratio, high-temperature metallurgical properties, and microstructure of VTM pellets were studied through pelletizing and roasting experiments. Results show that the addition of B2O3 reagent is not conducive to the increase of the drop strength of the green pellets. Nevertheless, the compressive strength and fracture toughness of the roasted pellets can be improved by adding more B2O3 during the pelletizing. The reduction degree of VTM pellets is firstly decreased and then increased with the added B2O3 amount. It is possible to improve the compaction degree and restrain the reduction-pulverization degree of the pellet by a low amount of additive (B2O3). The reduction-expansion performance of VTM pellets, in turn, can be raised by adding B2O3.

Description: Recently, wide applications of fuzzy set theory have attracted the attention of both researchers and practitioners. Fuzzy portfolio develops as a new area in the research field of investment portfolio. This paper investigates the major research hotspots, development trend, and evolution of fuzzy portfolio, which provides a systematic review of the current fuzzy portfolio literature. CiteSpace, the most commonly used bibliometrics software, is used in this article. According to the 602 articles with 15132 references, several conclusions can be summarized as follows: (1) Fuzzy portfolio becomes increasingly interdisciplinary with the connections among “Computer Science” and so on. (2) Most contributive authors are Markowitz and Zadeh. (3) South China University of Technology makes excellent performance in this research area and China is the most influential country. (4) European Journal of Operations Research is the cradle of plenty of crucial fuzzy portfolio investigations. (5) We find some research hotspots helpful to make scientific predictions of future trends by analyzing the keywords. By utilizing the effective bibliometric methods, we provide a comprehensive analysis and deep insights into the fuzzy portfolio research, enabling the individuals, especially the new beginners who are interested in this area to learn fuzzy portfolio, which will be of great help for their future explorations.

Description: In this work, a general geometric nonlinear model of straight thin-walled box beams (STBBs) under combined eccentric and axial loads is established. In order to accurately reflect the behavior of STBB, the additional shear lag warping is added to enrich the displacement field. It is necessary to define the section shape function to describe the local section deformation. Therefore, extension, bending, torsion, distortion, and shear lag effects are expressed by the generalized coordinate method. Based on the stability of transverse unconstrained box beam theory, meaningful higher-order solutions can be obtained by defining a set of coupled deformation modes. The equilibrium equation is discretized by the Galerkin method, and the Newton–Raphson incremental method is used to derive and solve the nonlinear governing equations. On this basis, the analytical expression of stiffness matrix is established. For solving the stability problem, the effectiveness of the proposed method is verified by comparing the calculation results of shell element (Ansys) with other theories. Numerical examples even show that the proposed method can not only get the influence of shear lag but also obtain the variation of lateral buckling of the beam model.

Description: In this article, a modified Polak-Ribière-Polyak (PRP) conjugate gradient method is proposed for image restoration. The presented method can generate sufficient descent directions without any line search conditions. Under some mild conditions, this method is globally convergent with the Armijo line search. Moreover, the linear convergence rate of the modified PRP method is established. The experimental results of unconstrained optimization, image restoration, and compressive sensing show that the proposed method is promising and competitive with other conjugate gradient methods.

Description: EFA (extended factored approach) algorithm is the main method of space-time adaptive processing technology (STAP) for airborne phased array radar, but it is faced with many problems, such as large number of samples and large amount of calculation. Therefore, this paper uses a method of spatial data dimensionality reduction processing based on cyclic iterative calculation to optimize its STAP. The final experimental results show that, after spatial data dimensionality reduction processing optimization, the STAP performance of EFA algorithm is further expanded in the range of sample number adaptation; especially in the case of small sample number, the optimized STAP performance has been basically close to the ideal compared with other optimization schemes; tap performance also proves that the optimization scheme in this paper has better convergence speed and STAP performance.

Description: This paper reviews the progress of the multiple population mortality model and the defects in parameter estimation and proposes an effective method to improve the performance of the mortality model. We set up a multiple population group, using the data of mainland China, Hong Kong (China), and Japan, to test fitting performance and forecasting performance. Using the TSWLS and TSSVD methods in a multiple population stochastic mortality model has advantages in fitting performance and robustness. In addition, the forecasting value of mortality ratio between any two populations can converge to a fixed constant in a certain time period which obeys the regular of human biological characteristics.

Description: The gut microbiota has been presumed to have a role in the pathogenesis of type 1 diabetes (T1D). Significant changes in the microbial composition of T1D patients have been reported in several case-control studies. This study is aimed at systematically reviewing the existing literature, which has investigated the alterations of the intestinal microbiome in T1D patients compared with healthy controls (HCs) using 16S ribosomal RNA-targeted sequencing. The databases of MEDLINE, EMBASE, Web of Science, and the Cochrane Library were searched until April 2019 for case-control studies comparing the composition of the intestinal microbiome in T1D patients and HCs based on 16S rRNA gene sequencing techniques. The Newcastle-Ottawa Scale was used to assess the methodological quality. Ten articles involving 260 patients with T1D and 276 HCs were included in this systematic review. The quality scores of all included studies were 6–8 points. In summary, a decreased microbiota diversity and a significantly distinct pattern of clustering with regard to β-diversity were observed in T1D patients when compared with HCs. At the phylum level, T1D was characterised by a reduced ratio of Firmicutes/Bacteroidetes in the structure of the gut community, although no consistent conclusion was reached. At the genus or species level, T1D patients had a reduced abundance of Clostridium and Prevotella compared with HCs, whereas Bacteroides and Ruminococcus were found to be more enriched in T1D patients. This systematic review identified that there is a close association between the gut microbiota and development of T1D. Moreover, gut dysbiosis might be involved in the pathogenesis of T1D, although the causative role of gut microbiota remains to be established. Further well-controlled prospective studies are needed to better understand the role of the intestinal microbiome in the pathogenesis of T1D, which may help explore novel microbiota-based strategies to prevent and treat T1D.

Description: Scientific evaluation of the competitiveness of China’s dairy industry is of great significance to the development of regional dairy industry. In view of the fact that the existing evaluation model cannot solve the dynamic nonlinear optimization problem, this paper established a projection pursuit model based on accelerating genetic algorithm and carried on the comprehensive evaluation and dynamic analysis on the competitiveness of dairy industry in China’s 31 provinces and cities (not including Hong Kong, Macao, and Taiwan) from five dimensions, namely, basic factors of production, the industry demand conditions, the enterprise competitiveness and growth force, related and supporting industries, and the natural environmental elements. It was found that firstly, from the perspective of time, the development trend of China’s dairy industry basically shows a positive trend. With the improvement of national living standards, the competitiveness of the dairy industry is also constantly improved. Secondly, from the perspective of space, regional differences in the competitiveness of the dairy industry are significant. Inner Mongolia, Heilongjiang, Shandong, and Hebei are at the forefront of the development of the industry, while the development of the dairy industry in the rest of the region has a big gap with those areas. From the perspective of regional layout, the advantageous region of China’s dairy industry has been preliminarily formed, and the competitive advantage is mainly concentrated in the northern region. Accordingly, the countermeasures and suggestions to enhance the competitiveness of China’s dairy industry were put forward.

Description: In this paper, we consider the problem of investment and reinsurance with time delay under the compound Poisson model of two-dimensional dependent claims. Suppose an insurance company controls the claim risk of two kinds of dependent insurance businesses by purchasing proportional reinsurance and invests its wealth in a financial market composed of a risk-free asset and a risk asset. The risk asset price process obeys the geometric Brownian motion. By introducing the capital flow related to the historical performance of the insurer, the wealth process described by stochastic delay differential equation (SDDE) is obtained. The extended HJB equation is obtained by using the stochastic control theory under the framework of game theory. Under the reinsurance expected premium principle, optimal time-consistent investment and reinsurance strategy and the corresponding value function are obtained. Finally, the influence of model parameters on the optimal strategy is explained by numerical analysis.

Description: For the long-term sustainable development, the modern enterprises should consider both competition and cooperation. In the current studies of corporate competition strategies and games, the quantification of cooperation-competition (coopetition) between enterprises is not deeply investigated. In this paper, we establish a coopetition game model of oligarchic enterprises in the industry by using the quantitative altruistic factor and nonlinear cost function, analyze the influence of altruistic factor on equilibrium variables, and then validate it in the generation side market. The following conclusions are drawn: (1) the coopetition of any form will increase the market equilibrium price and the total equilibrium profit of the industry, which induces the motivation and intention of cooperation between oligarchic enterprises. (2) The increased unilateral altruism is instable and unsustainable because it will produce an altruistic threshold that makes the total equilibrium profit of the industry increase and then decrease. The unilateral altruism of high-cost generation companies is more beneficial for increasing the total equilibrium profit of the industry, but it is realized in a difficult way. Due to a higher initial altruism level, there is lack of motivation for the increased unilateral altruism. (3) The mutually altruistic coopetition is the most effective way for improving the total equilibrium profit of the industry, but it is hard to finally achieve the complete monopoly because of cost differentiation. (4) The established game model of generation market is more universal and provides a certain quantitative interpretation for electricity crisis.

Description: In this paper, we further study the dynamic characteristics of the Yu–Wang chaotic system obtained by Yu and Wang in 2012. The system can show a four-wing chaotic attractor in any direction, including all 3D spaces and 2D planes. For this reason, our interest is focused on multistability generation and chaotic FPGA implementation. The stability analysis, bifurcation diagram, basin of attraction, and Lyapunov exponent spectrum are given as the methods to analyze the dynamic behavior of this system. The analyses show that each system parameter has different coexistence phenomena including coexisting chaotic, coexisting stable node, and coexisting limit cycle. Some remarkable features of the system are that it can generate transient one-wing chaos, transient two-wing chaos, and offset boosting. These phenomena have not been found in previous studies of the Yu–Wang chaotic system, so they are worth sharing. Then, the RK4 algorithm of the Verilog 32-bit floating-point standard format is used to realize the autonomous multistable 4D Yu–Wang chaotic system on FPGA, so that it can be applied in embedded engineering based on chaos. Experiments show that the maximum operating frequency of the Yu–Wang chaotic oscillator designed based on FPGA is 161.212 MHz.

Description: To achieve numerical simulation of large deformation evolution processes in underground engineering, the barycentric interpolation test function is established in this paper based on the manifold cover idea. A large-deformation numerical simulation method is proposed by the double discrete method with the fixed Euler background mesh and moving material points, with discontinuous damage processes implemented by continuous simulation. The material particles are also the integration points. This method is called the manifold cover Lagrangian integral point method based on barycentric interpolation. The method uses the Euler mesh as the background integral mesh and describes the deformation behavior of macroscopic objects through the motion of particles between meshes. Therefore, this method can avoid the problem of computation termination caused by the distortion of the mesh in the calculation process. In addition, this method can keep material particles moving without limits in the set region, which makes it suitable for simulating large deformation and collapse problems in geotechnical engineering. Taking a typical slope as an example, the results of a slope slip surface obtained using the manifold cover Lagrangian integral point method based on barycentric interpolation proposed in this paper were basically consistent with the theoretical analytical method. Hence, the correctness of the method was verified. The method was then applied for simulating the collapse process of the side slope, thereby confirming the feasibility of the method for computing large deformations.

Description: Viscoelastic artificial boundary elements are one of the most commonly used artificial boundaries when solving dynamic soil-structure interactions or near-field wave propagation problems. However, due to the lack of clear and practical stability criteria for the explicit algorithm that considers the influence of viscoelastic artificial boundary elements, the determination of the stable time increment in such numerical analyses is still a challenge. In this study, we proposed a numerical stability analysis method for the explicit algorithm with a 3D viscoelastic artificial boundary element based on the idea of a subsystem. Through this method, the artificial boundary subsystem that controls the stability of the overall numerical system is determined, and the analytical solution for the stability condition of the explicit integration algorithm with 3D viscoelastic artificial boundary elements is obtained. On this basis, the maximum time increment for solving dynamic problems with viscoelastic artificial boundary elements can be determined.

Description: This paper proposes effective evidence on the correlation between trend and self-organized criticality (SOC) of the power outage sequence in China. Taking the data series of blackouts from 1981 to 2014 in the China power grid as the research object, the method of V/S is introduced into the analysis of the power system blackout sequence to demonstrate their prominent long-time correlations. It also verifies the probability distribution of load loss about blackout size in the China power grid has a tail feature, which shows that the time series of blackouts in the China power grid is consistent with SOC. Meanwhile, a kind of mathematical statistics analysis is presented to prove that there is a seasonal trend of blackouts, and the blackout frequency and blackout size have not decreased over time but have an upward trend in the China power grid, thereby indicating that blackout risk may be increasing with time. The last 34 years’ data samples of power failure accidents in the China power grid are used to test the proposed method, and the numerical results show that the proposed self-organized criticality and trend analysis method can pave the way for further exploration of the mechanism of power failure in the China power grid.

Description: In this paper, an extended car-following model with consideration of the driver’s desire for smooth driving and the self-stabilizing control in historical velocity data is constructed. Moreover, for better reflecting the reality, we also integrate the velocity uncertainty into the new model to analyze the internal characteristics of traffic flow in situation where the historical velocity data are uncertain. Then, the model’s linear stability condition is inferred by utilizing linear stability analysis, and the modified Korteweg-de Vries (mKdV) equation is also obtained to depict the evolution properties of traffic congestion. According to the theoretical analysis, we observe that the degree of traffic congestion is alleviated when the control signal is considered, and the historical time gap and the velocity uncertainty also play a role in affecting the stability of traffic flow. Finally, some numerical simulation experiments are implemented and the experiments’ results demonstrate that the control signals including the self-stabilizing control, the driver’s desire for smooth driving, the historical time gap, and the velocity uncertainty are of avail to improve the traffic jam, which are consistent with the theoretical analytical results.

Description: In the present study, the current control method of the model predictive control is applied to the field-oriented control induction motor. The augmentation model of the motor is initially established based on the stator current equation, which performs the current predictive control and formulates the new cost function by means of tracking error. Then, the influence of parameter error on the current control stability in the prediction model is analysed, and the current static error is corrected according to the correlation between the input and feedback. Finally, a simple and effective three-vector control strategy is proposed. Moreover, three adjacent basic voltage vectors are utilized, and then six candidate voltage vectors are synthesized in each sector to replace eight basic voltage vectors in the conventional model predictive control (MPC). The obtained results show that synthesized vectors, which have arbitrary amplitude and direction, significantly expand the coverage of the system’s control set, reduce the torque and flux pulsation in the conventional MPC, and improve the steady-state performance of the system. Finally, the dSPACE platform is employed to validate the performed experiment. It is concluded that the proposed method can reduce the torque and flux pulse, perform the induction motor current control, and improve the steady-state performance of the system.

Description: Predicting vehicle carbon emissions on vertical curve sections can provide guidance for low-carbon vertical profile designs. Given that the influence of vertical curve design indicators on the fuel consumption and CO2 emissions of vehicles are underexplored, this study filled this research gap by establishing a theoretical carbon emission model of vehicles on vertical curve sections. The carbon emission model was established based on Xu’s vehicle energy conversion model, the conversion model of energy, fuel consumption, and CO2 emissions. The accuracy of the theoretical carbon emission model and the CO2 emission rules on vertical curve sections were verified by field test results. Field tests were carried out on flat sections, longitudinal slope sections, and various types of vertical curve sections, with five common types of vehicles maintaining cruising speed. The carbon emission rate effects on the vertical curve are closely related to the gradient and irrelevant of the radius. On the vertical profile composed with downhill/asymmetric/symmetrical vertical curve with a gradient greater than the balance gradient, the carbon emission rate is determined by the gradient and radius. The influence of the gradient on carbon emissions of vehicle on these vertical profiles was more significant than the radius. The radius is irrelevant to the carbon emission rate on the other forms of vertical profile. These results may benefit highway designers and engineers by providing guidelines regarding the environmental effects of highway vertical curve indexes.

Description: In recent years, fuzzy set theory and possibility theory have been widely used to deal with an uncertain decision environment characterized by vagueness and ambiguity in the financial market. Considering that the expected return rate of investors may not be a fixed real number but can be an interval number, this paper establishes an interval-valued possibilistic mean-variance portfolio selection model. In this model, the return rate of assets is regarded as a fuzzy number, and the expected return rate of assets is measured by the interval-valued possibilistic mean of fuzzy numbers. Therefore, the possibilistic portfolio selection model is transformed into an interval-valued optimization model. The optimal solution of the model is obtained by using the order relations of interval numbers. Finally, a numerical example is given. Through the numerical example, it is shown that, when compared with the traditional possibilistic model, the proposed model has more constraints and can better reflect investor psychology. It is an extension of the traditional possibilistic model and offers greater flexibility in reflecting investor expectations.

Description: In this study, the design of a novel model based on nonlinear third-order Emden–Fowler delay differential (EF-DD) equations is presented along with two types using the sense of delay differential and standard form of the second-order EF equation. The singularity at ξ = 0 at single or multiple points of each type of the designed EF-DD model are discussed. The detail of shape factors and delayed points is provided for both types of the designed third-order EF-DD model. For the verification and validation of the model, two numerical examples are presented of each case and numerical results have been performed using the artificial neural network along with the hybrid of global and local capabilities. The comparison of the obtained numerical results with the exact solutions shows the perfection and correctness of the designed third-order EF-DD model.

Description: The optimal amount of fertilizer application which was needed by the trees and the factors that influence the fertilization have an intricated nonlinear relationship. According to the problems that the traditional fertilization prediction model has, such as lacking of the scalability and practicality, this paper initiates an accurate fertilization prediction model that was based on the GRA-PSO-BP neural network which can make the accurate fertilization come true and improve the economic benefits of forest industry. This paper uses the GRA method to determine the input of the neural network as the site index and make the forest age, nutrient content of the advantage trees, biomass of the advantage trees, biomass of average trees, and target yield as the output numbers of the Actual amount of fertilizer applied. During the calculation process, the global particle swarm optimization algorithm is used to optimize the initial numbers and threshold numbers of BP neural network which build a phased GRA-PSO-BP accurate fertilization model. Compared with the prediction algorithm of full input variate that is based on the single BP neural network and the prediction algorithm of full input variate that is based on PSO-BP Neural Network, the GRA method can determine the key factors that influence the amount of fertilizer applied in different forest areas and modify the prediction model to improve the scalability and accuracy of the prediction and finally achieve the precision fertilization as the data of different forests updated, so we can see that the prediction result of this paper is more accurate. The result demonstrates that the GRA-PSO-BP neural network Segment fertilization model is more accurate than the traditional BP neural network and BP Neural Network that was optimized by the PSO algorithm, and specifically, the error of the predicted amount of fertilizer application and the actual amount of fertilizer application is less than 5%, which can effectively guide the fertilization in stages.

Description: The research on autonomous recognition mechanism for survivability has vigorously been growing up. A method of autonomous cognitive model and quantitative analysis for survivable system was proposed based on cognitive computing technology. Firstly, a cognitive model for survivable system with cross-layer perception ability was established, a self-feedback evolution mode of cognitive unit based on monitor-decide-execute loop structure was improved, and a self-configuration of cognitive unit is realized. Then, combined with the cognitive state transition graph, the analysis of cognitive performance for survivable systems based on dynamic cognitive behavioral changes was constructed. Finally, the cognitive processes of survivable system were described by using formal modeling. Simulation validated the influence degree of test parameters on system survivability from two perspectives of the probability of intrusion detection systems vulnerability and attacks detected. Results show that enhancing the rate of monitoring actions change and the rate of performing actions change obviously improved the cognitive performance of survivable system.

Description: This paper proposes a novel decoupled approach of a regenerative braking system for an electric city bus, aiming at improving the utilization of the kinetic energy for rear axle during a braking process. Three contributions are added to distinguish from the previous research. Firstly, an energy-flow model of the electric bus is established to identify the characteristic parameters which affect the energy-saving efficiency of the vehicle, while the key parameters (e.g., driving cycles and the recovery rate of braking energy) are also analyzed. Secondly, a decoupled braking energy recovery scheme together with the control strategy is developed based on the characteristics of the power assistance for electric city bus which equips an air braking system, as well as the regulatory requirements of ECE R13. At last, the energy consumption of the electric city bus is analyzed by both the simulation and vehicle tests, when the superimposed and the decoupled regenerative braking system are, respectively, employed for the vehicle. The simulation and actual road test results show that compared with the superposition braking system of the basic vehicle, the decoupled braking energy recovery system after the reform can improve the braking energy recovery rate and vehicle energy-saving degree. The decoupled energy recovery system scheme and control strategy proposed in this paper can be adopted by bus factories to reduce the energy consumption of pure-electric buses.

Description: This study addresses one of the most essential distributed control problems in multiagent systems, called the average consensus issue, using a new event-triggered sampling control perspective. Although the continuous-time sampling for average consensus has provided good results currently, a systematic investigation into the continuous-time agent dynamics with sampled-data control inputs under an event-triggered mechanism is critically lacking. The problem considered in this paper can be formulated into an average consensus problem of hybrid systems. The method considers three types of control schemes, among which periodic sampling is integrant. The first scheme is a classical sampling controller reinvestigated through a lemma. The second scheme realizes aperiodic control update as well as periodic communication, while the third scheme achieves both aspects aperiodically. Corresponding sufficient conditions of the aforementioned three schemes are derived such that the asymptotic stability of systems is ensured by using algebraic graph theory, matrix analysis, and Lyapunov theory. The constraints for the allowed sampling period, event parameter, and maximum eigenvalue of graph Laplacian are explicitly derived. Moreover, the potential Zeno behavior of agents due to the sampling control theory is avoided. Thus, a digitally implementable technique is provided. Finally, some numerical examples are provided to verify the effectiveness of the proposed theoretical analysis.

Description: This research intends to construct a signless Laplacian spectrum of the complement of any k-regular graph G with order n. Through application of the join of two arbitrary graphs, a new class of Q-borderenergetic graphs is determined with proof. As indicated in the research, with a regular Q-borderenergetic graph, sequences of regular Q-borderenergetic graphs can be constructed. The procedures for such a construction are determined and demonstrated. Significantly, all the possible regular Q-borderenergetic graphs of order 7

Description: Current research in biometrics aims to develop high-performance tools, which would make it possible to better extract the traits specific to each individual and to grasp their discriminating characteristics. This research is based on high-level analyses of images, captured from the candidate to identify, for a better understanding and interpretation of these signals. Several biometric identification systems exist. The recognition systems based on the iris have many advantages and they are among the most reliable. In this paper, we propose a new approach based on biometric iris authentication. A new scheme was made in this work that consists of calculating a three-dimensional head pose to capture a good iris image from a video sequence which affects the identification results. From this image, we were able to locate the iris and analyse its texture by intelligent use of Meyer wavelets. Our approach was evaluated and approved through two databases CASIA Iris Distance and MiraclHB. The comparative study showed its effectiveness compared to those in the literature.

Description: Stability of a high-speed craft is an essential matter, and porpoising is one of the most critical instabilities that could occur in some planing hulls due to inappropriate design. In this paper, the porpoising phenomenon and variation of step location yielding resistance reduction are studied through experimental and numerical methods. The investigated models include a single-step model and a nonstep model with the same general shape, but with different step location. The nonstep model is previously tested, but the single-step model is examined in the present study. The nonstep model experiences porpoising at 8 m/s speed, but the single-step model remains stable at the same speed. A three-dimensional CFD analysis is conducted using the finite volume method (FVM). On the contrary, the volume of fluid (VOF) scheme is used for free surface modeling, and the overset mesh technique is implemented within StarCCM+ software. The CFD results of total hydrodynamic resistance and dynamic trim angle are compared against the experimental data. The numerical results are in good agreement with the experimental data. Subsequently, ten different stepped models are simulated to examine their effects. The longitudinal distance between steps and aft of these models are in the range of 19 to 50 percent of the length of models. The obtained results show that as steps are located farther than aft, the models become more stable, and resistance increases due to trim reduction. Finally, the optimum location of the step is extracted with the aim of minimizing the resistance through the design of experiment (DOE) method. Based on the DOE method, it is observed that the sensitivity of the drag value to the step location is higher than the speed.

Description: The use of sunlight for photocatalytic oxidation is an ideal strategy, but it is limited by factors such as insufficient light absorption intensity of the photocatalyst and easy recombination of photogenerated electron holes. TiO2 is favored by researchers as an environment-friendly catalyst. In this paper, TiO2 is combined with WO3 to obtain a nanofiber with excellent catalytic performance under sunlight. The WO3/TiO2 composite nanofibers were synthesized by using the electrospinning method. The X-ray diffraction (XRD) analysis indicated that WO3 was successfully integrated onto the surface of TiO2. The photodegradation performance and photocurrent analysis of the prepared nanofibers showed that the addition of WO3 really improved the photocatalytic performance of TiO2 nanofibers, methylene blue (MB) degradation rate increased from 72% to 96%, and 5% was the optimal composite mole percentage of W to Ti. The scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), UV-Vis diffuse reflectance spectra (UV-Vis DRS), and Brunauer-Emmett-Teller (BET) analysis further characterized the properties of 5% WO3/TiO2 nanofibers. The H2 generation rate of 5% WO3/TiO2 nanofibers was 107.15 μmol·g−1·h−1, in comparison with that of TiO2 nanofibers (73.21 μmol·g−1·h−1) under the same condition. The 5% WO3/TiO2 produced ·OH under illumination, which played an important role in the MB degradation. Also, the enhanced photocatalytic mechanism was also proposed based on the detailed analysis of the band gap and the active species trapping experiment. The results indicated that the effective separation of Z-scheme photogenerated electron-hole pairs and transfer system constructed between TiO2 and WO3 endowed the excellent photocatalytic activity of 5% WO3/TiO2 nanofibers.

Description: The pseudopotential lattice Boltzmann method (LBM) with a tunable surface tension term is applied to study a droplet impact on a moving thin film. The Re effects of dimensionless parameters on the upstream and downstream crown evolution are studied, including Reynolds number (Re), Weber number (We), liquid film thickness, and horizontal velocity of the liquid film. The movement of the liquid film causes the asymmetry development of the upstream and downstream crown. Both the instability of upstream and downstream crowns increases with the increase of Re and We, and the upstream crown becomes more prone to break up. And a critical value of film thickness exists with the height of the upstream and downstream liquid crowns reaches the maximum value. And the velocity of liquid film restrains the development of the height of the upstream and downstream crowns, but it promotes the growth of the crown radius.

Description: In this article, an algorithm is proposed for creating an ensemble classifier. The name of the algorithm is the F-score subspace method (FsBoost). According to this method, the features are selected with the F-score and classified with different or the same classifiers. In the next step, the ensemble classifier is created. Two versions that are named FsBoost.V1 and FsBoost.V2 have been developed based on classification by the same or different classifiers. According to the results obtained, the results are consistent with the literature. Besides, a higher accuracy rate is obtained compared with many algorithms in the literature. The algorithm is fast because it has a few steps. It is thought that the algorithm will be successful due to these advantages.

Description: In this study, the effect of the roughness parameter during the peristaltic transport of a Newtonian fluid in a nonuniform channel has been explored. The motivation of this study comes from various research studies in the area of life sciences and engineering, which reveal that the wall of living beings’ arteries and all other surfaces have roughness to some extent. As peristalsis is a major mode of transporting biological fluids in various organs, the effect of surface roughness during peristaltic flow becomes very significant. The problem of peristaltic motion of a Newtonian fluid through a rough nonuniform channel having sinusoidal-shaped roughness has been investigated in the current work. To analyze the flow, analytic formulation of pressure rise, friction force, velocity, and pressure gradient has been carried out under the low Reynolds number and long-wavelength approximation. Results obtained for zero surface roughness from the current model are in complete agreement with previous studies available in the literature that have been carried out without considering the surface roughness of the wall. Numerical outcomes for the properties mentioned above have been plotted for analyzing the impact of roughness on the physical and flow parameters.

Description: In view of the poor performance of the original mathematical model of assembly construction project precost budget, a mathematical model of assembly construction project precost budget based on improved neural network algorithm is proposed. This paper investigates the cost content of assembly construction project and analyzes its early cost. It finds that the early cost of assembly construction project includes component production cost, transportation component cost, and installation component cost. Based on the improved neural network algorithm to build an improved neural network model, the improved neural network model to mine the cost data in the early stage of assembly construction project is used. In this paper, the earned value variable is introduced to transform the project duration and project cost in the early stage of the prefabricated construction project into quantifiable cost data, and the earned value analysis method is used to estimate the implementation cost of the prefabricated construction project. According to the result of cost estimation, the mathematical model of precost budget of prefabricated construction project is built based on the project parameters. In order to prove that the cost budget performance of the mathematical model based on the improved neural network algorithm in the early stage of assembly construction project is better, the original mathematical model is compared with the mathematical model, the experimental results show that the cost budget performance of the model is better than the original model, and the cost budget performance is improved.

Description: Unripe plantain has been considered as having commercial potential or used as an ingredient for other foods. Information on the physicochemical and carotenoid properties of flours from hybrid plantain cultivars in the literature is limited. This study was conducted to determine the physicochemical properties and carotenoid contents of unripe plantain flour from selected hybrid plantain cultivars using standard laboratory methods. The unripe plantain pulps of four varieties (PITA 26, PITA 27, Mbi Egome and Agbagba (control)) used in this study were cabinet dried at 65°C for 48 h and milled into flour. The result showed that moisture content ranged from 6.15 to 7.27%, Ash (2.01–3.69%), Fat (0.49–1.20%), Protein (2.47–2.99%), Fibre (0.73–0.97%), Sugar (6.29–9.33%), starch (84.34–104.96%), total carotenoid content (2.96–24.19 µg/g). Potassium ranged from 328.30–528.50 mg/kg, Calcium (9.46–11.98 mg/kg), Magnesium (24.73–29.11 mg/kg), Sodium (6.30–7.24 mg/kg), Zinc (0.12–0.29 mg/kg), and manganese (0.03–0.15 mg/kg). The L∗ (Lightness) ranged from 62.88 to 67.00. Bulk density ranged from 0.72 to 0.77 g/ml, WAC (143.59–174.08), OAC (98.07–100.66%), swelling power capacity (10.63 to 11.82%), solubility (5.58–6.71%), and dispersibility (86.50–88.00%). Peak viscosity ranged from 568.17 to 761.64 RVU, final viscosity (378.53–496.58 RVU), and peak temperature (81.62–83.23°C). The results suggest that the hybrid plantain cultivars could be used to produce good quality plantain flours with improved physicochemical and pasting properties.

Description: The role of green supplier evaluation and selection (GSES) in supply chain management is increasingly appreciated due to the intensification of competition, raising public consciousness, and environmental issues. To improve GSES, a large number of approaches have been proposed in the past decades. However, few attempts have been made to systematically review and classify the literature in this field. The objective of this study is to afford a comprehensive review of the studies which aim to develop models and methods in helping enterprises to assess and select the right green suppliers. To achieve this goal, a total of 193 journal articles extracted from the Scopus database over the period of 2009 to 2020 were chosen and reviewed. These publications were classified into ten categories based on their adopted GSES models and analyzed concerning the evaluation criteria, criteria weighting methods, and performance evaluation methods. Moreover, a bibliometric analysis was conducted according to the frequency of supplier selection methods, citation number, publication year, journal, country, and application area. This study supports practitioners, managers, and researchers in effectively recognizing and applying the GSES models to enhance organizational competitiveness and provides an insight into its state of the art.

Description: Nanosuspensions are widely reported to enhance the solubility of poorly soluble drugs. In addition to enhancement in solubility, improvement of stability and therapeutic efficacy would be an added advantage. In the present study, premilling and subsequent high-pressure homogenization were carried out to produce naringenin nanosuspension. Hydroxypropyl methylcellulose and sodium dodecyl sulfate were evaluated for their performance as stabilizers under various homogenization cycles. The prepared nanosuspensions were studied for average particle size and size distribution, zeta potential, solubility, drug release, antioxidant activity, and in vitro antitumor activity. It was observed that both hydroxypropyl methylcellulose-stabilized nanosuspension and sodium dodecyl sulfate-stabilized nanosuspension produced an enhancement in physical stability, antioxidant potential, and in vitro cytotoxicity compared with naringenin. Furthermore, hydroxypropyl methylcellulose-stabilized nanosuspension was found to be better than sodium dodecyl sulfate-stabilized nanosuspension in terms of particle size and size distribution, storage stability, and drug release. This study showed that nanosuspension formulations could be a potential strategy for improving dissolution and antitumor activity of naringenin.

Description: In recent years, with the expansion of university enrollment in China, the cost of running a school is getting higher and higher. Under the circumstance of insufficient state investment in higher education, the education charge paid by students has become an important source of the university income. It has become a hot topic of social concern to formulate a reasonable charging model to enable more students to enter higher education institutions. In this paper, we mainly put forward the basic differential equation models describing the problem of higher education charges in China. Through the qualitative analysis of these two basic models, we draw several conditions for universities to maintain or stabilize their education charges and give some suggestions on macrocontrol of university education charges in China.

Description: Deep learning-based object detection method has been applied in various fields, such as ITS (intelligent transportation systems) and ADS (autonomous driving systems). Meanwhile, text detection and recognition in different scenes have also attracted much attention and research effort. In this article, we propose a new object-text detection and recognition method termed “DetReco” to detect objects and texts and recognize the text contents. The proposed method is composed of object-text detection network and text recognition network. YOLOv3 is used as the algorithm for the object-text detection task and CRNN is employed to deal with the text recognition task. We combine the datasets of general objects and texts together to train the networks. At test time, the detection network detects various objects in an image. Then, the text images are passed to the text recognition network to derive the text contents. The experiments show that the proposed method achieves 78.3 mAP (mean Average Precision) for general objects and 72.8 AP (Average Precision) for texts in regard to detection performance. Furthermore, the proposed method is able to detect and recognize affine transformed or occluded texts with robustness. In addition, for the texts detected around general objects, the text contents can be used as the identifier to distinguish the object.

Description: The estimation of continuous and simultaneous multijoint angle based on surface electromyography (sEMG) signal is of considerable significance in rehabilitation practice. However, there are few studies on the continuous joint angle of multiple joints at present. In this paper, the wavelet packet energy entropy (WPEE) of the special subspace was investigated as a feature of the sEMG signal. An Elman neural network optimized by genetic algorithm (GA) was established to estimate the joint angle of shoulder and elbow. First, the accuracy of the method is verified by estimating the angle of the shoulder joint. Then, this method was used to simultaneously and continuously estimate the shoulder and elbow joint angle. Six subjects flexed and extended the upper limbs according to the intended movements of the experiment. The results show that this method can obtain a decent performance with a RMSE of 3.4717 and R2 of 0.8283 in shoulder movement and with a RMSE of 4.1582 and R2 of 0.8114 in continuous synchronous movement of the shoulder and elbow.

Description: The horses were trotted in a straight line, and the acceleration data were recorded from the movement of the horse’s head. Inertial sensors were used to collect the information. The sample entropy was used to characterize the dynamics of horse gait. The gait of sound and lame horses was compared, and the sound horses had smaller values of the sample entropy. The effects of sedative detomidine on the gait of lame horses were also examined. The values of sample entropy for sedated horses were smaller than the values of the sample entropy for untreated horses. The sample entropy can provide important information about the dynamics of the equine gait.

Description: This paper introduces the synthesis of mesoporous silica nanoparticles (MSNs) with three different groups such as amine, thiol, and sulfonic acid, along the internal surface. Trimethyl[3-(trimethoxysilyl)propyl]ammonium chloride was used to modify the external surface of the nanomaterials. Such materials allow control of the drug release from MSN pores. Multifunctional MSNs were loaded with doxycycline (Doxy) to study their capacities and uploading time. The loading profile indicates that sulfonic groups in the internal surface were the most efficient surfaces with a loading capacity of ca. 35% in 90 min in acidic media.

Description: The Longmendian Ag–Pb–Zn deposit is located in the southern margin of the North China Craton, and the mineralization occurs mainly in quartz veins, altered gneissic wallrocks, and minor fault breccias in the Taihua Group. Based on vein crosscutting relations, mineral assemblages, and paragenesis, the mineralization can be divided into three stages: (1) quartz–pyrite, (2) quartz–polymetallic sulfides, and (3) quartz–carbonate–polymetallic sulfides. Wallrock alteration can be divided into three zones, i.e., chlorite–sericite, quartz–carbonate–sericite, and silicate. Fluid inclusions in all Stage 1 to 3 quartz are dominated by vapor-liquid two-phase aqueous type (W-type). Petrographic and microthermometric analyses of the fluid inclusions indicate that the homogenization temperatures of Stages 1, 2, and 3 are 198–332°C, 132–260°C, and 97–166°C, with salinities of 4.0–13.3, 1.1–13.1, and 1.9–7.6 wt% NaCleqv, respectively. The vapor comprises primarily H2O, with some CO2, H2, CO, N2, and CH4. The liquid phase contains Ca2+, Na+, K+, SO42−, Cl−, and F−. The sulfides have δ34S=–1.42 to +2.35‰ and 208Pb/204Pb=37.771 to 38.795, 207Pb/204Pb=15.388 to 15.686, and 206Pb/204Pb=17.660 to 18.101. The H–C–O–S–Pb isotope compositions indicate that the ore-forming materials may have been derived from the Taihua Group and the granitic magma. The fluid boiling and cooling and mixing with meteoric water may have been critical for the Ag–Pb–Zn ore precipitation. Geological and geochemical characteristics of the Longmendian deposit indicate that the deposit is best classified as medium- to low-temperature intermediate-sulfidation (LS/IS) epithermal-type, related to Cretaceous crustal-extension-related granitic magmatism.

Description: Data Envelopment Analysis is one of the paramount mathematical methods to compute the general performance of organizations, which utilizes similar sources to produce similar outputs. Original DEA schemes involve crisp information of inputs and outputs that may not always be accessible in real-world applications. Nevertheless, in some cases, the values of the data are information with indeterminacy, impreciseness, vagueness, inconsistent, and incompleteness. Furthermore, the conventional DEA models have been originally formulated solely for desirable outputs. However, undesirable outputs may additionally be present in the manufacturing system, which wishes to be minimized. To tackle the mentioned issues and in order to obtain a reliable measurement that keeps original advantage of DEA and considers the influence of undesirable factors under the indeterminate environments, this paper presents a neutrosophic DEA model with undesirable outputs. The recommended technique is based on the aggregation operator and has a simple construction. Finally, an example is given to illustrate the new model and ranking approach in details.