In the version of the article originally published in the volume 68,issue 12,2025 of Sci China Mater(pages 4413-4422,https://doi.org/10.1007/s40843-025-3667-7),the Chinese name of the co-first author(肖天孝)was incorr...In the version of the article originally published in the volume 68,issue 12,2025 of Sci China Mater(pages 4413-4422,https://doi.org/10.1007/s40843-025-3667-7),the Chinese name of the co-first author(肖天孝)was incorrect.The corrected Chinese name is:肖天笑.展开更多
Researchers are increasingly focused on enabling groups of multiple unmanned vehicles to operate cohesively in complex,real-world environments,where coordinated formation control and obstacle avoidance are essential f...Researchers are increasingly focused on enabling groups of multiple unmanned vehicles to operate cohesively in complex,real-world environments,where coordinated formation control and obstacle avoidance are essential for executing sophisticated collective tasks.This paper presents a Distributed Formation Control and Obstacle Avoidance(DFCOA)framework for multi-unmanned ground vehicles(UGV).DFCOA integrates a virtual leader structure for global guidance,an improved A^(*)path planning algorithm with an advanced cost function for efficient path planning,and a repulsive-force-based improved vector field histogram star(VFH^(*))technique for collision avoidance.The virtual leader generates a reference trajectory while enabling distributed execution;the improved A^(*)algorithm reduces planning time and number of nodes to determine the shortest path from the starting position to the goal;and the improved VFH^(*)uses 2D LiDAR data with inter-agent repulsive force to simultaneously avoid collision with obstacles and maintain safe inter-vehicle distances.The formation stability of the proposed DFCOA reaches 95.8%and 94.6%in two scenarios,with root mean square(RMS)centroid errors of 0.9516 and 1.0008 m,respectively.Velocity tracking is precise(velocity centroid error RMS of 0.2699 and 0.1700 m/s),and linear velocities closely match the desired 0.3 m/s.Safety metrics showed average collision risks of 0.7773 and 0.5143,with minimum inter-vehicle distances of 0.4702 and 0.8763 m,confirming collision-free navigation of four UGVs.DFCOA outperforms conventional methods in formation stability,path efficiency,and scalability,proving its suitability for decentralized multi-UGV applications.展开更多
To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework ba...To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.展开更多
Phytomelatonin,an emerging plant hormone,plays vital roles in plant growth,development,and stress adaptation(Arnao et al.,2022;Ullah et al.,2024).It acts both as a direct antioxidant and a signaling molecule,engaging ...Phytomelatonin,an emerging plant hormone,plays vital roles in plant growth,development,and stress adaptation(Arnao et al.,2022;Ullah et al.,2024).It acts both as a direct antioxidant and a signaling molecule,engaging complex networks and interacting with other phytohormones(Liu et al.,2022;Khan et al.,2023).Although phytomelatonin receptors(PMTRs)have been identified in many plants(Wei et al.,2018;Wang et al.,2022;Liu et al.,2025),the downstream signaling mechanisms,particularly receptor-mediated protein modifications and transcriptional regulation,remain poorly characterized.展开更多
High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging ...High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging foundation models and multimodal learning frameworks are enabling scalable and transferable representations of cellular states,while advances in interpretability and real-world data integration are bridging the gap between discovery and clinical application.This paper outlines a concise roadmap for AI-driven,transcriptome-centered multi-omics integration in precision medicine(Figure 1).展开更多
Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technol...Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technology overcomes the limitations of traditional single-organ models,providing a novel platform for investigating complex disease mechanisms and evaluating drug efficacy and toxicity.Although it demonstrates broad application prospects,its development still faces critical bottlenecks,including inadequate physiological coupling between organs,short functional maintenance durations,and limited real-time monitoring capabilities.Contemporary research is advancing along three key directions,including functional coupling,sensor integration,and full-process automation systems,to propel the technology toward enhanced levels of physiological relevance and predictive accuracy.展开更多
The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measu...The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%.展开更多
Based on activity calculation model, the activity coefficients of Ti, Al and Nb components of Ti 25Al 25Nb (mole fraction, %) melt, the vapor pressures of corresponding components and the evaporation loss rates were c...Based on activity calculation model, the activity coefficients of Ti, Al and Nb components of Ti 25Al 25Nb (mole fraction, %) melt, the vapor pressures of corresponding components and the evaporation loss rates were calculated. Utilizing these activity coefficients and the vapor pressures, the relative evaporation coefficient is used to judge the evaporation tendency of these components. The evaporation tendency among the three components were compared and the result shows that the evaporation tendency is that: AlTi>Nb. Evaporation loss rate increases with the increase of melting temperature and decreases with the increase of chamber pressure. There exists an impeding pressure p impe of Al element evaporation during induction skull melting process of Ti 25Al 25Nb alloy. The impeding pressure can be written as p impe =8.1 p e, where p e represents the equilibrium partial pressure. The calculation of evaporation loss of Al element also showed that when chamber pressure exceeds p impe , the Al volatilization losses could be ignored. In order to prevent the evaporation loss of components, the pressure in the vacuum chamber should not below p impe .展开更多
To study the measurement of distance under the condition of the frequency modulation (FM) multi component signal of a short range radar, the multi points scattering model of a target, the TLS ESPRIT (total least sq...To study the measurement of distance under the condition of the frequency modulation (FM) multi component signal of a short range radar, the multi points scattering model of a target, the TLS ESPRIT (total least square estimation of signal parameters via rotational invariance techniques) and the mathematical statistics methods were used. The method of computing single frequency signal's instantaneous frequency (IF) is unsuitable to the multi component signal. By using the method of the TLS ESPRIT combined with the mathematical statistics, the multi component signal's IF can be obtained. The computer simulation has shown that the method has the high accuracy for measuring the distance.展开更多
A general scheme for generating a multi-component integrable equation hierarchy is proposed. A simple 3M- dimensional loop algebra ~X is produced. By taking advantage of ~X a new isospectral problem is established and...A general scheme for generating a multi-component integrable equation hierarchy is proposed. A simple 3M- dimensional loop algebra ~X is produced. By taking advantage of ~X a new isospectral problem is established and then by making use of the Tu scheme the multi-component Dirac equation hierarchy is obtained. Finally, an expanding loop algebra ~FM of the loop algebra ~X is presented. Based on the ~FM, the multi-component integrable coupling system of the multi-component Dirac equation hierarchy is investigated. The method in this paper can be applied to other nonlinear evolution equation hierarchies.展开更多
This review focuses on the recent research progress in the multi-component assembly of luminescent rare earth hybrid materials, which is based on the luminescent rare earth compounds and two or more other building uni...This review focuses on the recent research progress in the multi-component assembly of luminescent rare earth hybrid materials, which is based on the luminescent rare earth compounds and two or more other building units, including the other photoactive species. It covers the multi-component luminescent rare earth hybrids which was assembled with different(a) organic-inorganic polymeric units,(b)nanoporous units,(c) nanoparticle composites or(d) other developing special units. Finally, future challenges and opportunities in this field are discussed. Herein it mainly focuses on the work of Yan's group in recent years.展开更多
Adsorption is one of the several techniques that has been successfully used for dyes removal.Since most industrial colored effluents contain several components including dyes,having a strong knowledge about the scope ...Adsorption is one of the several techniques that has been successfully used for dyes removal.Since most industrial colored effluents contain several components including dyes,having a strong knowledge about the scope of competitive adsorption process is a powerful key to design an appropriate system.This is mainly because of the complexity brought about by the increasing number of parameters needed for process description which complicates not only the process modeling but also the experimental data collection.A multicomponent adsorption model should be based on fundamental soundness,speed,and simplicity of calculation.For such systems,competition will change the adsorbent-adsorbate attractions.Thus,there is major concern to develop an accurate and reliable method to predict dye adsorption behavior in multi-component systems.This article covers topics such as the theory of dyes adsorption in multi-component systems along with applicable models according to the consistent theories presented by researchers.展开更多
This paper presents a flexible model and a robust algorithm for simulation of multi-stage multi-component separation processes in which multiple feeds, side streams, strippers and/or side heat exchangers are involved....This paper presents a flexible model and a robust algorithm for simulation of multi-stage multi-component separation processes in which multiple feeds, side streams, strippers and/or side heat exchangers are involved. The improved algorithm effectively accelerates the speed of convergence and offers better stability by introducing a damping factor for updating the stripping factor, and also reduces the requirement on the initial estimates by updating the Joacobian matrix directly with the stripping factor and enthalpy. On the other hand, an efficient algorithm was proposed to solve the approximate tri-diagonal matrix (containing the off-band elements) derived from the material balance equations (M equations) and phase equilibrium equations (E equations), the advantages and simplicity of the “insideout” technique of the Russell are retained. The present algorithm was demonstrated to be effective in simulating complex separation columns with typical case studies.展开更多
The segregation modes and characteristics of 1-6 mm multi-component lignite were studied in a microporous, vibrated, gas-fluidized bed of Φ110 mm ×400 mm. The effects of particle density and size, vibration freq...The segregation modes and characteristics of 1-6 mm multi-component lignite were studied in a microporous, vibrated, gas-fluidized bed of Φ110 mm ×400 mm. The effects of particle density and size, vibration frequency and amplitude, and gas velocity on these characteristics were considered. The average size, average density, size deviation coefficient, and density deviation coefficient were used to identify lignite size and density. The separation efficiency was adopted to evaluate the segregation performance,and the segregation mechanisms were explored. The results show that ε(size,max) of heterogeneous multisize-component lignite with K_(size) = 65% reaches 80% at f= 20 Hz, A = 5 mm, and N =(1,3). ε_(density,max) Of heterogeneous multi-density-component lignite with K_(density)= 25% reaches 50% at f = 15 Hz, A = 5 mm,and N =(1,1.5). The density segregations of 1-3 and 3-6 mm multi-component mixtures are remarkable,ε_(density,max)= 42% and 31% at f= 14 and 16 Hz, and A = 3 and 5 mm, respectively. The size segregation of 1-6 mm multi-component mixture is prominent and ε_(size,max)= 55% at f= 15 Hz, A = 5 mm. The mediumsized mixture with a narrow size distribution at low frequency is favorable for density segregation,and a mixture with a wider size distribution at high frequency is most favorable for size segregation.Precise control of gas flow and vibration as well as optimal design of the fluidized bed can improve the performance of segregation in the vibrated gas-fluidized bed.展开更多
An efficient and novel procedure for the preparation of pyrazolo[3,4-b]pyridine derivatives through multi-component reaction of aldehyde, 5-amino-3-methyl-1-phenylpyrazole and malononitrile or cyanoacetate in [bmim][B...An efficient and novel procedure for the preparation of pyrazolo[3,4-b]pyridine derivatives through multi-component reaction of aldehyde, 5-amino-3-methyl-1-phenylpyrazole and malononitrile or cyanoacetate in [bmim][BF4] is described in this paper. Advantages of the method presented here include mild conditions, high yields together with a green nature and ease of recovery and reuse of the reaction medium.展开更多
A mixture theory is developed for multi-component micropolar porous media with a combination of the hybrid mixture theory and the micropolar continuum theory. The system is modeled as multi-component micropolar elasti...A mixture theory is developed for multi-component micropolar porous media with a combination of the hybrid mixture theory and the micropolar continuum theory. The system is modeled as multi-component micropolar elastic solids saturated with multi- component micropolar viscous fluids. Balance equations are given through the mixture theory. Constitutive equations are developed based on the second law of thermodynamics and constitutive assumptions. Taking account of compressibility of solid phases, the volume fraction of fluid as an independent state variable is introduced in the free energy function, and the dynamic compatibility condition is obtained to restrict the change of pressure difference on the solid-fluid interface. The constructed constitutive equations are used to close the field equations. The linear field equations are obtained using a linearization procedure, and the micropolar thermo-hydro-mechanical component transport model is established. This model can be applied to practical problems, such as contaminant, drug, and pesticide transport. When the proposed model is supposed to be porous media, and both fluid and solid are single-component, it will almost agree with Eringen＇s model.展开更多
The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can caus...The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.展开更多
文摘In the version of the article originally published in the volume 68,issue 12,2025 of Sci China Mater(pages 4413-4422,https://doi.org/10.1007/s40843-025-3667-7),the Chinese name of the co-first author(肖天孝)was incorrect.The corrected Chinese name is:肖天笑.
文摘Researchers are increasingly focused on enabling groups of multiple unmanned vehicles to operate cohesively in complex,real-world environments,where coordinated formation control and obstacle avoidance are essential for executing sophisticated collective tasks.This paper presents a Distributed Formation Control and Obstacle Avoidance(DFCOA)framework for multi-unmanned ground vehicles(UGV).DFCOA integrates a virtual leader structure for global guidance,an improved A^(*)path planning algorithm with an advanced cost function for efficient path planning,and a repulsive-force-based improved vector field histogram star(VFH^(*))technique for collision avoidance.The virtual leader generates a reference trajectory while enabling distributed execution;the improved A^(*)algorithm reduces planning time and number of nodes to determine the shortest path from the starting position to the goal;and the improved VFH^(*)uses 2D LiDAR data with inter-agent repulsive force to simultaneously avoid collision with obstacles and maintain safe inter-vehicle distances.The formation stability of the proposed DFCOA reaches 95.8%and 94.6%in two scenarios,with root mean square(RMS)centroid errors of 0.9516 and 1.0008 m,respectively.Velocity tracking is precise(velocity centroid error RMS of 0.2699 and 0.1700 m/s),and linear velocities closely match the desired 0.3 m/s.Safety metrics showed average collision risks of 0.7773 and 0.5143,with minimum inter-vehicle distances of 0.4702 and 0.8763 m,confirming collision-free navigation of four UGVs.DFCOA outperforms conventional methods in formation stability,path efficiency,and scalability,proving its suitability for decentralized multi-UGV applications.
基金supported by the confidential research grant No.a8317。
文摘To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.
基金supported by the grants from the Key Research and Development Program of Xinjiang Uygur autonomous region in China(Grant No.2023B02017)the National Key Research and Development Program of China(Grant No.2024YFD2300703)+1 种基金the financial support from the Beijing Rural Revitalization Agricultural Science and Technology Project(Grant No.NY2401080000),BAIC01-2025the 2115 Talent Development Program of China Agricultural University.
文摘Phytomelatonin,an emerging plant hormone,plays vital roles in plant growth,development,and stress adaptation(Arnao et al.,2022;Ullah et al.,2024).It acts both as a direct antioxidant and a signaling molecule,engaging complex networks and interacting with other phytohormones(Liu et al.,2022;Khan et al.,2023).Although phytomelatonin receptors(PMTRs)have been identified in many plants(Wei et al.,2018;Wang et al.,2022;Liu et al.,2025),the downstream signaling mechanisms,particularly receptor-mediated protein modifications and transcriptional regulation,remain poorly characterized.
文摘High-throughput transcriptomics has evolved from bulk RNA-seq to single-cell and spatial profiling,yet its clinical translation still depends on effective integration across diverse omics and data modalities.Emerging foundation models and multimodal learning frameworks are enabling scalable and transferable representations of cellular states,while advances in interpretability and real-world data integration are bridging the gap between discovery and clinical application.This paper outlines a concise roadmap for AI-driven,transcriptome-centered multi-omics integration in precision medicine(Figure 1).
基金supported by the Shenzhen Medical Research Fund(Grant No.A2303049)Guangdong Basic and Applied Basic Research(Grant No.2023A1515010647)+1 种基金National Natural Science Foundation of China(Grant No.22004135)Shenzhen Science and Technology Program(Grant No.RCBS20210706092409020,GXWD20201231165807008,20200824162253002).
文摘Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technology overcomes the limitations of traditional single-organ models,providing a novel platform for investigating complex disease mechanisms and evaluating drug efficacy and toxicity.Although it demonstrates broad application prospects,its development still faces critical bottlenecks,including inadequate physiological coupling between organs,short functional maintenance durations,and limited real-time monitoring capabilities.Contemporary research is advancing along three key directions,including functional coupling,sensor integration,and full-process automation systems,to propel the technology toward enhanced levels of physiological relevance and predictive accuracy.
文摘The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%.
文摘Based on activity calculation model, the activity coefficients of Ti, Al and Nb components of Ti 25Al 25Nb (mole fraction, %) melt, the vapor pressures of corresponding components and the evaporation loss rates were calculated. Utilizing these activity coefficients and the vapor pressures, the relative evaporation coefficient is used to judge the evaporation tendency of these components. The evaporation tendency among the three components were compared and the result shows that the evaporation tendency is that: AlTi>Nb. Evaporation loss rate increases with the increase of melting temperature and decreases with the increase of chamber pressure. There exists an impeding pressure p impe of Al element evaporation during induction skull melting process of Ti 25Al 25Nb alloy. The impeding pressure can be written as p impe =8.1 p e, where p e represents the equilibrium partial pressure. The calculation of evaporation loss of Al element also showed that when chamber pressure exceeds p impe , the Al volatilization losses could be ignored. In order to prevent the evaporation loss of components, the pressure in the vacuum chamber should not below p impe .
基金Doctoral Programme Foundation of Institution of Higher Education of China.
文摘To study the measurement of distance under the condition of the frequency modulation (FM) multi component signal of a short range radar, the multi points scattering model of a target, the TLS ESPRIT (total least square estimation of signal parameters via rotational invariance techniques) and the mathematical statistics methods were used. The method of computing single frequency signal's instantaneous frequency (IF) is unsuitable to the multi component signal. By using the method of the TLS ESPRIT combined with the mathematical statistics, the multi component signal's IF can be obtained. The computer simulation has shown that the method has the high accuracy for measuring the distance.
文摘A general scheme for generating a multi-component integrable equation hierarchy is proposed. A simple 3M- dimensional loop algebra ~X is produced. By taking advantage of ~X a new isospectral problem is established and then by making use of the Tu scheme the multi-component Dirac equation hierarchy is obtained. Finally, an expanding loop algebra ~FM of the loop algebra ~X is presented. Based on the ~FM, the multi-component integrable coupling system of the multi-component Dirac equation hierarchy is investigated. The method in this paper can be applied to other nonlinear evolution equation hierarchies.
基金Project supported by the National Natural Science Foundation of China(21571142)the Developing Science Fund of Tongji University,the Natural Science Foundation of Zhejiang Province(LQ14B010001)the Natural Science Foundation of Ningbo,China(2016A610105)
文摘This review focuses on the recent research progress in the multi-component assembly of luminescent rare earth hybrid materials, which is based on the luminescent rare earth compounds and two or more other building units, including the other photoactive species. It covers the multi-component luminescent rare earth hybrids which was assembled with different(a) organic-inorganic polymeric units,(b)nanoporous units,(c) nanoparticle composites or(d) other developing special units. Finally, future challenges and opportunities in this field are discussed. Herein it mainly focuses on the work of Yan's group in recent years.
文摘Adsorption is one of the several techniques that has been successfully used for dyes removal.Since most industrial colored effluents contain several components including dyes,having a strong knowledge about the scope of competitive adsorption process is a powerful key to design an appropriate system.This is mainly because of the complexity brought about by the increasing number of parameters needed for process description which complicates not only the process modeling but also the experimental data collection.A multicomponent adsorption model should be based on fundamental soundness,speed,and simplicity of calculation.For such systems,competition will change the adsorbent-adsorbate attractions.Thus,there is major concern to develop an accurate and reliable method to predict dye adsorption behavior in multi-component systems.This article covers topics such as the theory of dyes adsorption in multi-component systems along with applicable models according to the consistent theories presented by researchers.
文摘This paper presents a flexible model and a robust algorithm for simulation of multi-stage multi-component separation processes in which multiple feeds, side streams, strippers and/or side heat exchangers are involved. The improved algorithm effectively accelerates the speed of convergence and offers better stability by introducing a damping factor for updating the stripping factor, and also reduces the requirement on the initial estimates by updating the Joacobian matrix directly with the stripping factor and enthalpy. On the other hand, an efficient algorithm was proposed to solve the approximate tri-diagonal matrix (containing the off-band elements) derived from the material balance equations (M equations) and phase equilibrium equations (E equations), the advantages and simplicity of the “insideout” technique of the Russell are retained. The present algorithm was demonstrated to be effective in simulating complex separation columns with typical case studies.
基金the National Natural Science Foundation of China (Nos. 51774283, 51174203)the Major International (Regional) Joint Research Project of NSFC (No. 51620105001) for the financial supports
文摘The segregation modes and characteristics of 1-6 mm multi-component lignite were studied in a microporous, vibrated, gas-fluidized bed of Φ110 mm ×400 mm. The effects of particle density and size, vibration frequency and amplitude, and gas velocity on these characteristics were considered. The average size, average density, size deviation coefficient, and density deviation coefficient were used to identify lignite size and density. The separation efficiency was adopted to evaluate the segregation performance,and the segregation mechanisms were explored. The results show that ε(size,max) of heterogeneous multisize-component lignite with K_(size) = 65% reaches 80% at f= 20 Hz, A = 5 mm, and N =(1,3). ε_(density,max) Of heterogeneous multi-density-component lignite with K_(density)= 25% reaches 50% at f = 15 Hz, A = 5 mm,and N =(1,1.5). The density segregations of 1-3 and 3-6 mm multi-component mixtures are remarkable,ε_(density,max)= 42% and 31% at f= 14 and 16 Hz, and A = 3 and 5 mm, respectively. The size segregation of 1-6 mm multi-component mixture is prominent and ε_(size,max)= 55% at f= 15 Hz, A = 5 mm. The mediumsized mixture with a narrow size distribution at low frequency is favorable for density segregation,and a mixture with a wider size distribution at high frequency is most favorable for size segregation.Precise control of gas flow and vibration as well as optimal design of the fluidized bed can improve the performance of segregation in the vibrated gas-fluidized bed.
基金the National Natural Science Foundation of China(No.20573034).
文摘An efficient and novel procedure for the preparation of pyrazolo[3,4-b]pyridine derivatives through multi-component reaction of aldehyde, 5-amino-3-methyl-1-phenylpyrazole and malononitrile or cyanoacetate in [bmim][BF4] is described in this paper. Advantages of the method presented here include mild conditions, high yields together with a green nature and ease of recovery and reuse of the reaction medium.
基金supported by the National Natural Science Foundation of China (No.50778013)the Natural Science Foundation of Beijing (No.8082020)
文摘A mixture theory is developed for multi-component micropolar porous media with a combination of the hybrid mixture theory and the micropolar continuum theory. The system is modeled as multi-component micropolar elastic solids saturated with multi- component micropolar viscous fluids. Balance equations are given through the mixture theory. Constitutive equations are developed based on the second law of thermodynamics and constitutive assumptions. Taking account of compressibility of solid phases, the volume fraction of fluid as an independent state variable is introduced in the free energy function, and the dynamic compatibility condition is obtained to restrict the change of pressure difference on the solid-fluid interface. The constructed constitutive equations are used to close the field equations. The linear field equations are obtained using a linearization procedure, and the micropolar thermo-hydro-mechanical component transport model is established. This model can be applied to practical problems, such as contaminant, drug, and pesticide transport. When the proposed model is supposed to be porous media, and both fluid and solid are single-component, it will almost agree with Eringen＇s model.
基金Projects(U22B2084,52275483,52075142)supported by the National Natural Science Foundation of ChinaProject(2023ZY01050)supported by the Ministry of Industry and Information Technology High Quality Development,China。
文摘The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.
