本文论述了图书馆期刊发布系统的计算机软件结构,介绍了在Microsof.tNET Framework2.0技术下图书馆期刊发布系统的优点与缺点,并结合本馆自身实例介绍了如何利用Microsoft公司最新的开发工具Visual Studio 2005来实现图书馆期刊发布系...本文论述了图书馆期刊发布系统的计算机软件结构,介绍了在Microsof.tNET Framework2.0技术下图书馆期刊发布系统的优点与缺点,并结合本馆自身实例介绍了如何利用Microsoft公司最新的开发工具Visual Studio 2005来实现图书馆期刊发布系统的计算机软件。展开更多
Microsoft．NET Framework中的安全性包含许多技术；基类库（BCL，Base Class Library）和ASP．NET中基于角色的安全、BCL中的密码系统类以及新的对使用访问控制列表（ACL，Access Control List）的支持即为其中的少数几个例子。公共语...Microsoft．NET Framework中的安全性包含许多技术；基类库（BCL，Base Class Library）和ASP．NET中基于角色的安全、BCL中的密码系统类以及新的对使用访问控制列表（ACL，Access Control List）的支持即为其中的少数几个例子。公共语言运行库（CLR，Common Language Runtime）提供的．NET安全性系列中的技术之一就是代码访问安全性（CAS，Code Access Security）。本文讨论．NET安全性中CAS的角色以及．NET Framework2．0的CAS中的一些关键的新功能和更改。展开更多
The preparation of carbon-based electromagnetic wave(EMW)absorbers possessing thin matching thickness,wide absorption bandwidth,strong absorption intensity,and low filling ratio remains a huge challenge.Metal-organic ...The preparation of carbon-based electromagnetic wave(EMW)absorbers possessing thin matching thickness,wide absorption bandwidth,strong absorption intensity,and low filling ratio remains a huge challenge.Metal-organic frameworks(MOFs)are ideal self-sacrificing templates for the construction of carbon-based EMW absorbers.In this work,bimetallic FeMn-MOF-derived MnFe_(2)O_(4)/C/graphene composites were fabricated via a two-step route of solvothermal reaction and the following pyrolysis treatment.The results re-veal the evolution of the microscopic morphology of carbon skeletons from loofah-like to octahedral and then to polyhedron and pomegran-ate after the adjustment of the Fe^(3+)to Mn^(2+)molar ratio.Furthermore,at the Fe^(3+)to Mn^(2+)molar ratio of 2:1,the obtained MnFe_(2)O_(4)/C/graphene composite exhibited the highest EMW absorption capacity.Specifically,a minimum reflection loss of-72.7 dB and a max-imum effective absorption bandwidth of 5.1 GHz were achieved at a low filling ratio of 10wt%.In addition,the possible EMW absorp-tion mechanism of MnFe_(2)O_(4)/C/graphene composites was proposed.Therefore,the results of this work will contribute to the construction of broadband and efficient carbon-based EMW absorbers derived from MOFs.展开更多
A thickness-controllable method for preparing metal-organic framework hollow nanofiowers on magnetic cores(Fe_(3)O_(4)@MOFs HFs)was demonstrated for the first time.The petal of magnetic core with hollow nanofiower str...A thickness-controllable method for preparing metal-organic framework hollow nanofiowers on magnetic cores(Fe_(3)O_(4)@MOFs HFs)was demonstrated for the first time.The petal of magnetic core with hollow nanofiower structure served as medium for assembling Ui O-66-NH_(2)shell with different thickness.To further improve its performance,Zr^(4+)was immobilized on the surface of Fe_(3)O_(4)@Ui O-66-NH_(2).Compared with conventional Fe_(3)O_(4)@Ui O-66-NH_(2)-Zr^(4+)nanospheres,the Fe_(3)O_(4)@Ui O-66-NH2-Zr4+HFs showed increased enrichment performance for phosphopeptides.The Fe_(3)O_(4)@Ui O-66-NH2-Zr4+HFs served as an attractive restricted-access adsorption material exhibited good selectivity(m_(β-casein):m_(BSA)=1:1000),high sensitivity(1.0 fmol)and excellent size-exclusion effect(m)((β-casein digests):m_(BSA)=1:200).Furthermore,the Fe_(3)O_(4)@Ui O-66-NH_(2)-Zr^(4+)HFs was successfully applied to the specific capture of ultratrace phosphopeptide from complex biological samples,revealing the great potential for the identification and analysis of trace phosphopeptides in clinical analysis.This work can be easily extended to the fabrication of diverse mag-MOF HFs with multifunctional and easy to post-modify properties,and open up a new avenue for the design and construction of new MOFs material.展开更多
Bridge networks are essential components of civil infrastructure,supporting communities by delivering vital services and facilitating economic activities.However,bridges are vulnerable to natural disasters,particularl...Bridge networks are essential components of civil infrastructure,supporting communities by delivering vital services and facilitating economic activities.However,bridges are vulnerable to natural disasters,particularly earthquakes.To develop an effective disaster management strategy,it is critical to identify reliable,robust,and efficient indicators.In this regard,Life-Cycle Cost(LCC)and Resilience(R)serve as key indicators to assist decision-makers in selecting the most effective disaster risk reduction plans.This study proposes an innova-tive LCC-R optimization framework to identify the most optimal retrofit strategies for bridge networks facing hazardous events during their lifespan.The proposed framework employs both single-and multi-objective opti-mization techniques to identify retrofit strategies that maximize the R index while minimizing the LCC for the under-study bridge networks.The considered retrofit strategies include various options such as different mate-rials(steel,CFRP,and GFRP),thicknesses,arrangements,and timing of retrofitting actions.The first step in the proposed framework involves constructing fragility curves by performing a series of nonlinear time-history incre-mental dynamic analyses for each case.In the subsequent step,the seismic resilience surfaces are calculated using the obtained fragility curves and assuming a recovery function.Next,the LCC is evaluated according to the pro-posed formulation for multiple seismic occurrences,which incorporates the effects of complete and incomplete repair actions resulting from previous multiple seismic events.For optimization purposes,the Non-Dominated Sorting Genetic Algorithm II(NSGA-II)evolutionary algorithm efficiently identifies the Pareto front to represent the optimal set of solutions.The study presents the most effective retrofit strategies for an illustrative bridge network,providing a comprehensive discussion and insights into the resulting tactical approaches.The findings underscore that the methodologies employed lead to logical and actionable retrofit strategies,paving the way for enhanced resilience and cost-effectiveness in bridge network management against seismic hazards.展开更多
The arbitrary discharge of tetracycline(TC)residuals has seriously influenced the ecosystem and human health.Laccase(Lac)-based biodegradation technology is considered a more effective way to remove TC due to its high...The arbitrary discharge of tetracycline(TC)residuals has seriously influenced the ecosystem and human health.Laccase(Lac)-based biodegradation technology is considered a more effective way to remove TC due to its high catalytic efficiency and less by-product.Nevertheless,free Lac suffers from poor stability,easy inactivation and difficult recovery,restricting its application.Immobilization of Lac is considered an efficient strategy for addressing these obstacles.In this study,a magnetic metal-organic framework of Fe_(3)O_(4)@SiO_(2)@UiO-66-NH_(2)(MMOF)was prepared and used as a carrier to immobilize Lac(Lac@MMOF)for TC degradation.Benefiting from the multiple binding sites,adsorption,and protection effect of MMOF,Lac@MMOF displayed a wider pH application range(2–7)and better thermal(15–85℃),repeatability,and storage stability than free Lac.Furthermore,owing to the synergism of MOF adsorption and Lac biocatalysis,the removal rate of Lac@MMOF for TC could be up to 98%at pH=7 within 1 hr,which was 1.29 and 1.24 times that of free Lac and MMOF,respectively.More importantly,Lac@MMOF could easily be separated from aqueous solution under a magnetic field and maintained good removal performance(80%)after five cycles.The degradation products were identified by applying LC-MS/MS,and possible degradation mechanisms and pathways were proposed.Finally,the antibacterial activity of intermediate products was evaluated using Escherichia coli,which revealed that the toxicity of TC was reduced effectively by the degradation of Lac@MMOF.Overall,Lac@MMOF is a green alternative for residual antibiotic removal in water.展开更多
Wireless Sensor Networks(WSNs)are one of the best technologies of the 21st century and have seen tremendous growth over the past decade.Much work has been put into its development in various aspects such as architectu...Wireless Sensor Networks(WSNs)are one of the best technologies of the 21st century and have seen tremendous growth over the past decade.Much work has been put into its development in various aspects such as architectural attention,routing protocols,location exploration,time exploration,etc.This research aims to optimize routing protocols and address the challenges arising from conflicting objectives in WSN environments,such as balancing energy consumption,ensuring routing reliability,distributing network load,and selecting the shortest path.Many optimization techniques have shown success in achieving one or two objectives but struggle to achieve the right balance between multiple conflicting objectives.To address this gap,this paper proposes an innovative approach that integrates Particle Swarm Optimization(PSO)with a fuzzy multi-objective framework.The proposed method uses fuzzy logic to effectively control multiple competing objectives to represent its major development beyond existing methods that only deal with one or two objectives.The search efficiency is improved by particle swarm optimization(PSO)which overcomes the large computational requirements that serve as a major drawback of existing methods.The PSO algorithm is adapted for WSNs to optimize routing paths based on fuzzy multi-objective fitness.The fuzzy logic framework uses predefined membership functions and rule-based reasoning to adjust routing decisions.These adjustments influence PSO’s velocity updates,ensuring continuous adaptation under varying network conditions.The proposed multi-objective PSO-fuzzy model is evaluated using NS-3 simulation.The results show that the proposed model is capable of improving the network lifetime by 15.2%–22.4%,increasing the stabilization time by 18.7%–25.5%,and increasing the residual energy by 8.9%–16.2% compared to the state-of-the-art techniques.The proposed model also achieves a 15%–24% reduction in load variance,demonstrating balanced routing and extended network lifetime.Furthermore,analysis using p-values obtained from multiple performance measures(p-values<0.05)showed that the proposed approach outperforms with a high level of confidence.The proposed multi-objective PSO-fuzzy model provides a robust and scalable solution to improve the performance of WSNs.It allows stable performance in networks with 100 to 300 nodes,under varying node densities,and across different base station placements.Computational complexity analysis has shown that the method fits well into large-scale WSNs and that the addition of fuzzy logic controls the power usage to make the system practical for real-world use.展开更多
Evolutionary algorithms have been extensively utilized in practical applications.However,manually designed population updating formulas are inherently prone to the subjective influence of the designer.Genetic programm...Evolutionary algorithms have been extensively utilized in practical applications.However,manually designed population updating formulas are inherently prone to the subjective influence of the designer.Genetic programming(GP),characterized by its tree-based solution structure,is a widely adopted technique for optimizing the structure of mathematical models tailored to real-world problems.This paper introduces a GP-based framework(GPEAs)for the autonomous generation of update formulas,aiming to reduce human intervention.Partial modifications to tree-based GP have been instigated,encompassing adjustments to its initialization process and fundamental update operations such as crossover and mutation within the algorithm.By designing suitable function sets and terminal sets tailored to the selected evolutionary algorithm,and ultimately derive an improved update formula.The Cat Swarm Optimization Algorithm(CSO)is chosen as a case study,and the GP-EAs is employed to regenerate the speed update formulas of the CSO.To validate the feasibility of the GP-EAs,the comprehensive performance of the enhanced algorithm(GP-CSO)was evaluated on the CEC2017 benchmark suite.Furthermore,GP-CSO is applied to deduce suitable embedding factors,thereby improving the robustness of the digital watermarking process.The experimental results indicate that the update formulas generated through training with GP-EAs possess excellent performance scalability and practical application proficiency.展开更多
The advancement of Internet of Things(IoT)technology is driving industries toward intelligent digital transformation,highlighting the crucial role of software engineering.Despite this,the integration of software engin...The advancement of Internet of Things(IoT)technology is driving industries toward intelligent digital transformation,highlighting the crucial role of software engineering.Despite this,the integration of software engineering into IoT engineering education remains underexplored.To address this gap,the School of Software at North University of China,in collaboration with QST Innovation Technology Group Co.,Ltd.(QST),has developed an innovative educational mechanism.This initiative focuses on the software engineering IoT track and optimizes the teaching process through the outcome-based education(OBE)concept.It incorporates military-industrial characteristics,introduces advanced information and technology curricula,and enhances laboratory infrastructure.The goal is to cultivate innovative talents with unique capabilities,thereby fostering the comprehensive development and application of IoT technology.展开更多
In this conceptual paper,the author develops and presents a strategic decision-making framework that applies game theory to evaluate smart and natural farming approaches in India.In the face of increasing pressures fr...In this conceptual paper,the author develops and presents a strategic decision-making framework that applies game theory to evaluate smart and natural farming approaches in India.In the face of increasing pressures from climate change,resource scarcity,and evolving socio-economic landscapes,agriculture must adapt to the challenges of a volatile,uncertain,complex,and ambiguous(VUCA)world.When integrated with the Provision of Urban Amenities in Rural Areas(PURA)framework,VUCA offers a dynamic system perspective that contextualizes uncertainty and institutional capacity in farming systems.This study applies a modified Spence signaling model to capture how farmers-categorized as smart or natural versus conventional-choose to signal their sustainability credentials in an environment of asymmetric information.Using a combination of payoff matrix modelling,Bayesian belief updating,and evolutionary game simulations,the paper identifies strategic equilibria under varying levels of policy support,consumer trust,and signal cost.Farmers’decisions to adopt smart technologies or organic certifications are modelled as costly but credible signals of quality.These signals are then interpreted by receivers such as consumers,investors,or policymakers,who in turn adjust their support or market preferences.The analysis reveals conditions under which separating,pooling,and semi-separating equilibria emerge,and how these outcomes impact farmer behaviour and systemic sustainability.Case studies from Indian states such as Andhra Pradesh,Karnataka,and Punjab demonstrate how real-world farming programs mirror theoretical outcomes under different signalling strategies.The study also presents a robust methodological structure,combining conceptual modelling with policy simulation and validation through comparative cases.By integrating environmental,technological,and institutional perspectives,this paper contributes a hybrid strategic framework aligned with India’s Green Revolution 2.0 goals.It offers practical recommendations for policy design,infrastructure planning,and market mechanisms that support the scaling of sustainable agricultural practices through credible signalling and game-theoretic insights.展开更多
Organophosphorus pesticides(OPPs)in foods pose a serious threat to human health,motivating the development of novel analytical methods for their rapid detection and quantification.A magnetic covalent organic framework...Organophosphorus pesticides(OPPs)in foods pose a serious threat to human health,motivating the development of novel analytical methods for their rapid detection and quantification.A magnetic covalent organic framework(M-COF)adsorbent for the magnetic solid-phase extraction(MSPE)of OPPs from foods was reported.M-COF was synthesized by the Schiff base condensation reaction of 1,3,5-tris(4-aminophenyl)benzene and 4,4-biphenyldicarboxaldehyde on the surface of amino-functionalized magnetic nanoparticles.Density functional theory(DFT)calculations showed that adsorption of OPPs onto the surface of M-COF involved hydrophobic effects,van der Waals interactions,π-πinteractions,halogen-N bonding,and hydrogen bonding.Combined with gas chromatography-mass spectrometry(GC-MS)technology,the MSPE method features low limits of detection for OPPs(0.002-0.015μg/L),good reproducibility(1.45%-6.14%),wide linear detection range(0.01-1μg/L,R≥0.9935),and satisfactory recoveries(87.3%-110.4%).The method was successfully applied for the trace analysis of OPPs in spiked fruit juices.展开更多
The development of organic frameworks with radical skeletons is desired.In this study,we report the development of a novel two-dimensional radical halogen-bonded organic framework(XOF).The radical monomer,benzimidazol...The development of organic frameworks with radical skeletons is desired.In this study,we report the development of a novel two-dimensional radical halogen-bonded organic framework(XOF).The radical monomer,benzimidazole triphenylmethyl(BTTM),was synthesized through the coupling of TTM radicals with benzimidazole.Initially,the benzimidazole units were coordinated with Ag^(+)ions to create a[N···Ag···N]^(+)framework.Subsequently,the addition of iodine led to the in situ replacement of Ag^(+)with I^(+)ions,forming[N···I···N]^(+)linkers and resulting in the creation of the XOF structure.The resulting XOF-HBTTM and XOF-BTTM structures demonstrated good-crystallinity,confirmed by PXRD,HR-TEM,SEAD,and SAXS analyses.EPR measurements confirmed the preservation of radical characteristics within the XOF framework.Furthermore,SQUID measurements indicated that XOF-BTTM exhibits spin moments of S=1/2 at 2 K,with a saturated magnetization strength peaking at 4.10 emu/g,a notable enhancement compared to 1.87 emu/g for the BTTM monomer.This improvement in magnetism is attributed to the extended spin density distribution and the presence of[N···I···N]^(+)interactions,as suggested by DFT calculations.Additionally,the radical XOF-BTTM exhibited significantly enhanced electrical conductivity,reaching up to 1.30×10^(-4)S/cm,which is two orders of magnitude higher than that of XOF-HBTTM.This increased conductivity is linked to a reduced HOMO-LUMO gap,higher carrier density,and the incorporation of triphenylmethyl radicals within the framework.This research highlights the potential of benzimidazolyl motifs in constructing functional XOFs and advances our understanding of radical organic frameworks.展开更多
Email communication plays a crucial role in both personal and professional contexts;however,it is frequently compromised by the ongoing challenge of spam,which detracts from productivity and introduces considerable se...Email communication plays a crucial role in both personal and professional contexts;however,it is frequently compromised by the ongoing challenge of spam,which detracts from productivity and introduces considerable security risks.Current spam detection techniques often struggle to keep pace with the evolving tactics employed by spammers,resulting in user dissatisfaction and potential data breaches.To address this issue,we introduce the Divide and Conquer-Generative Adversarial Network Squeeze and Excitation-Based Framework(DaC-GANSAEBF),an innovative deep-learning model designed to identify spam emails.This framework incorporates cutting-edge technologies,such as Generative Adversarial Networks(GAN),Squeeze and Excitation(SAE)modules,and a newly formulated Light Dual Attention(LDA)mechanism,which effectively utilizes both global and local attention to discern intricate patterns within textual data.This approach significantly improves efficiency and accuracy by segmenting scanned email content into smaller,independently evaluated components.The model underwent training and validation using four publicly available benchmark datasets,achieving an impressive average accuracy of 98.87%,outperforming leading methods in the field.These findings underscore the resilience and scalability of DaC-GANSAEBF,positioning it as a viable solution for contemporary spam detection systems.The framework can be easily integrated into existing technologies to enhance user security and reduce the risks associated with spam.展开更多
文摘Microsoft．NET Framework中的安全性包含许多技术；基类库（BCL，Base Class Library）和ASP．NET中基于角色的安全、BCL中的密码系统类以及新的对使用访问控制列表（ACL，Access Control List）的支持即为其中的少数几个例子。公共语言运行库（CLR，Common Language Runtime）提供的．NET安全性系列中的技术之一就是代码访问安全性（CAS，Code Access Security）。本文讨论．NET安全性中CAS的角色以及．NET Framework2．0的CAS中的一些关键的新功能和更改。
基金supported by the Natural Science Research Project of the Anhui Educational Committee,China(No.2022AH050827)the Open Research Fund Program of Anhui Province Key Laboratory of Specialty Polymers,Anhui University of Science and Technology,China(No.AHKLSP23-12)the Joint National-Local Engineering Research Center for Safe and Precise Coal Mining Fund,China(No.EC2022020)。
文摘The preparation of carbon-based electromagnetic wave(EMW)absorbers possessing thin matching thickness,wide absorption bandwidth,strong absorption intensity,and low filling ratio remains a huge challenge.Metal-organic frameworks(MOFs)are ideal self-sacrificing templates for the construction of carbon-based EMW absorbers.In this work,bimetallic FeMn-MOF-derived MnFe_(2)O_(4)/C/graphene composites were fabricated via a two-step route of solvothermal reaction and the following pyrolysis treatment.The results re-veal the evolution of the microscopic morphology of carbon skeletons from loofah-like to octahedral and then to polyhedron and pomegran-ate after the adjustment of the Fe^(3+)to Mn^(2+)molar ratio.Furthermore,at the Fe^(3+)to Mn^(2+)molar ratio of 2:1,the obtained MnFe_(2)O_(4)/C/graphene composite exhibited the highest EMW absorption capacity.Specifically,a minimum reflection loss of-72.7 dB and a max-imum effective absorption bandwidth of 5.1 GHz were achieved at a low filling ratio of 10wt%.In addition,the possible EMW absorp-tion mechanism of MnFe_(2)O_(4)/C/graphene composites was proposed.Therefore,the results of this work will contribute to the construction of broadband and efficient carbon-based EMW absorbers derived from MOFs.
基金sponsored by the National Natural Science Foundation of China (Nos. 22106038, 22204171 and 22076038)the Henan Provincial Science and Technology Research Project (No. 232102310112)+2 种基金the China Postdoctoral Science Foundation (No. 2022M713299)Natural Science Foundation of Henan Province, China (No. 202300410044)Henan key scientific research programs to Universities and Colleges (No. 22ZX003)。
文摘A thickness-controllable method for preparing metal-organic framework hollow nanofiowers on magnetic cores(Fe_(3)O_(4)@MOFs HFs)was demonstrated for the first time.The petal of magnetic core with hollow nanofiower structure served as medium for assembling Ui O-66-NH_(2)shell with different thickness.To further improve its performance,Zr^(4+)was immobilized on the surface of Fe_(3)O_(4)@Ui O-66-NH_(2).Compared with conventional Fe_(3)O_(4)@Ui O-66-NH_(2)-Zr^(4+)nanospheres,the Fe_(3)O_(4)@Ui O-66-NH2-Zr4+HFs showed increased enrichment performance for phosphopeptides.The Fe_(3)O_(4)@Ui O-66-NH2-Zr4+HFs served as an attractive restricted-access adsorption material exhibited good selectivity(m_(β-casein):m_(BSA)=1:1000),high sensitivity(1.0 fmol)and excellent size-exclusion effect(m)((β-casein digests):m_(BSA)=1:200).Furthermore,the Fe_(3)O_(4)@Ui O-66-NH_(2)-Zr^(4+)HFs was successfully applied to the specific capture of ultratrace phosphopeptide from complex biological samples,revealing the great potential for the identification and analysis of trace phosphopeptides in clinical analysis.This work can be easily extended to the fabrication of diverse mag-MOF HFs with multifunctional and easy to post-modify properties,and open up a new avenue for the design and construction of new MOFs material.
文摘Bridge networks are essential components of civil infrastructure,supporting communities by delivering vital services and facilitating economic activities.However,bridges are vulnerable to natural disasters,particularly earthquakes.To develop an effective disaster management strategy,it is critical to identify reliable,robust,and efficient indicators.In this regard,Life-Cycle Cost(LCC)and Resilience(R)serve as key indicators to assist decision-makers in selecting the most effective disaster risk reduction plans.This study proposes an innova-tive LCC-R optimization framework to identify the most optimal retrofit strategies for bridge networks facing hazardous events during their lifespan.The proposed framework employs both single-and multi-objective opti-mization techniques to identify retrofit strategies that maximize the R index while minimizing the LCC for the under-study bridge networks.The considered retrofit strategies include various options such as different mate-rials(steel,CFRP,and GFRP),thicknesses,arrangements,and timing of retrofitting actions.The first step in the proposed framework involves constructing fragility curves by performing a series of nonlinear time-history incre-mental dynamic analyses for each case.In the subsequent step,the seismic resilience surfaces are calculated using the obtained fragility curves and assuming a recovery function.Next,the LCC is evaluated according to the pro-posed formulation for multiple seismic occurrences,which incorporates the effects of complete and incomplete repair actions resulting from previous multiple seismic events.For optimization purposes,the Non-Dominated Sorting Genetic Algorithm II(NSGA-II)evolutionary algorithm efficiently identifies the Pareto front to represent the optimal set of solutions.The study presents the most effective retrofit strategies for an illustrative bridge network,providing a comprehensive discussion and insights into the resulting tactical approaches.The findings underscore that the methodologies employed lead to logical and actionable retrofit strategies,paving the way for enhanced resilience and cost-effectiveness in bridge network management against seismic hazards.
基金supported by the National Natural Science Foundation of China(No.U20A20133)the National Key Research and Development Program of China(No.2022YFF0606703).
文摘The arbitrary discharge of tetracycline(TC)residuals has seriously influenced the ecosystem and human health.Laccase(Lac)-based biodegradation technology is considered a more effective way to remove TC due to its high catalytic efficiency and less by-product.Nevertheless,free Lac suffers from poor stability,easy inactivation and difficult recovery,restricting its application.Immobilization of Lac is considered an efficient strategy for addressing these obstacles.In this study,a magnetic metal-organic framework of Fe_(3)O_(4)@SiO_(2)@UiO-66-NH_(2)(MMOF)was prepared and used as a carrier to immobilize Lac(Lac@MMOF)for TC degradation.Benefiting from the multiple binding sites,adsorption,and protection effect of MMOF,Lac@MMOF displayed a wider pH application range(2–7)and better thermal(15–85℃),repeatability,and storage stability than free Lac.Furthermore,owing to the synergism of MOF adsorption and Lac biocatalysis,the removal rate of Lac@MMOF for TC could be up to 98%at pH=7 within 1 hr,which was 1.29 and 1.24 times that of free Lac and MMOF,respectively.More importantly,Lac@MMOF could easily be separated from aqueous solution under a magnetic field and maintained good removal performance(80%)after five cycles.The degradation products were identified by applying LC-MS/MS,and possible degradation mechanisms and pathways were proposed.Finally,the antibacterial activity of intermediate products was evaluated using Escherichia coli,which revealed that the toxicity of TC was reduced effectively by the degradation of Lac@MMOF.Overall,Lac@MMOF is a green alternative for residual antibiotic removal in water.
基金funded by Deanship of Graduate studies and Scientific Research at Jouf University under grant No.(DGSSR-2023-2-02038).
文摘Wireless Sensor Networks(WSNs)are one of the best technologies of the 21st century and have seen tremendous growth over the past decade.Much work has been put into its development in various aspects such as architectural attention,routing protocols,location exploration,time exploration,etc.This research aims to optimize routing protocols and address the challenges arising from conflicting objectives in WSN environments,such as balancing energy consumption,ensuring routing reliability,distributing network load,and selecting the shortest path.Many optimization techniques have shown success in achieving one or two objectives but struggle to achieve the right balance between multiple conflicting objectives.To address this gap,this paper proposes an innovative approach that integrates Particle Swarm Optimization(PSO)with a fuzzy multi-objective framework.The proposed method uses fuzzy logic to effectively control multiple competing objectives to represent its major development beyond existing methods that only deal with one or two objectives.The search efficiency is improved by particle swarm optimization(PSO)which overcomes the large computational requirements that serve as a major drawback of existing methods.The PSO algorithm is adapted for WSNs to optimize routing paths based on fuzzy multi-objective fitness.The fuzzy logic framework uses predefined membership functions and rule-based reasoning to adjust routing decisions.These adjustments influence PSO’s velocity updates,ensuring continuous adaptation under varying network conditions.The proposed multi-objective PSO-fuzzy model is evaluated using NS-3 simulation.The results show that the proposed model is capable of improving the network lifetime by 15.2%–22.4%,increasing the stabilization time by 18.7%–25.5%,and increasing the residual energy by 8.9%–16.2% compared to the state-of-the-art techniques.The proposed model also achieves a 15%–24% reduction in load variance,demonstrating balanced routing and extended network lifetime.Furthermore,analysis using p-values obtained from multiple performance measures(p-values<0.05)showed that the proposed approach outperforms with a high level of confidence.The proposed multi-objective PSO-fuzzy model provides a robust and scalable solution to improve the performance of WSNs.It allows stable performance in networks with 100 to 300 nodes,under varying node densities,and across different base station placements.Computational complexity analysis has shown that the method fits well into large-scale WSNs and that the addition of fuzzy logic controls the power usage to make the system practical for real-world use.
文摘Evolutionary algorithms have been extensively utilized in practical applications.However,manually designed population updating formulas are inherently prone to the subjective influence of the designer.Genetic programming(GP),characterized by its tree-based solution structure,is a widely adopted technique for optimizing the structure of mathematical models tailored to real-world problems.This paper introduces a GP-based framework(GPEAs)for the autonomous generation of update formulas,aiming to reduce human intervention.Partial modifications to tree-based GP have been instigated,encompassing adjustments to its initialization process and fundamental update operations such as crossover and mutation within the algorithm.By designing suitable function sets and terminal sets tailored to the selected evolutionary algorithm,and ultimately derive an improved update formula.The Cat Swarm Optimization Algorithm(CSO)is chosen as a case study,and the GP-EAs is employed to regenerate the speed update formulas of the CSO.To validate the feasibility of the GP-EAs,the comprehensive performance of the enhanced algorithm(GP-CSO)was evaluated on the CEC2017 benchmark suite.Furthermore,GP-CSO is applied to deduce suitable embedding factors,thereby improving the robustness of the digital watermarking process.The experimental results indicate that the update formulas generated through training with GP-EAs possess excellent performance scalability and practical application proficiency.
基金supported in part by the Universityindustry Collaborative Education Program of the Ministry of Education under Grant No.202102383004。
文摘The advancement of Internet of Things(IoT)technology is driving industries toward intelligent digital transformation,highlighting the crucial role of software engineering.Despite this,the integration of software engineering into IoT engineering education remains underexplored.To address this gap,the School of Software at North University of China,in collaboration with QST Innovation Technology Group Co.,Ltd.(QST),has developed an innovative educational mechanism.This initiative focuses on the software engineering IoT track and optimizes the teaching process through the outcome-based education(OBE)concept.It incorporates military-industrial characteristics,introduces advanced information and technology curricula,and enhances laboratory infrastructure.The goal is to cultivate innovative talents with unique capabilities,thereby fostering the comprehensive development and application of IoT technology.
文摘In this conceptual paper,the author develops and presents a strategic decision-making framework that applies game theory to evaluate smart and natural farming approaches in India.In the face of increasing pressures from climate change,resource scarcity,and evolving socio-economic landscapes,agriculture must adapt to the challenges of a volatile,uncertain,complex,and ambiguous(VUCA)world.When integrated with the Provision of Urban Amenities in Rural Areas(PURA)framework,VUCA offers a dynamic system perspective that contextualizes uncertainty and institutional capacity in farming systems.This study applies a modified Spence signaling model to capture how farmers-categorized as smart or natural versus conventional-choose to signal their sustainability credentials in an environment of asymmetric information.Using a combination of payoff matrix modelling,Bayesian belief updating,and evolutionary game simulations,the paper identifies strategic equilibria under varying levels of policy support,consumer trust,and signal cost.Farmers’decisions to adopt smart technologies or organic certifications are modelled as costly but credible signals of quality.These signals are then interpreted by receivers such as consumers,investors,or policymakers,who in turn adjust their support or market preferences.The analysis reveals conditions under which separating,pooling,and semi-separating equilibria emerge,and how these outcomes impact farmer behaviour and systemic sustainability.Case studies from Indian states such as Andhra Pradesh,Karnataka,and Punjab demonstrate how real-world farming programs mirror theoretical outcomes under different signalling strategies.The study also presents a robust methodological structure,combining conceptual modelling with policy simulation and validation through comparative cases.By integrating environmental,technological,and institutional perspectives,this paper contributes a hybrid strategic framework aligned with India’s Green Revolution 2.0 goals.It offers practical recommendations for policy design,infrastructure planning,and market mechanisms that support the scaling of sustainable agricultural practices through credible signalling and game-theoretic insights.
基金supported by Key Research and Development Project of Shandong Province(2021ZDSYS12)National Natural Science Foundation of China(22076086,21777089)+3 种基金Taishan Scholar Program of Shandong Province(ts20190948)Shandong Province Science and Technology Small and Medium Enterprises Innovation Ability Enhancement Project(2023TSGC0689,2023TSGC0055)Natural Science Foundation of Shandong Province(ZR2021MB086,ZR2023QB035)Jinan City University and Institute Innovation Team Project(2021GXRC061,20228045,202333027)。
文摘Organophosphorus pesticides(OPPs)in foods pose a serious threat to human health,motivating the development of novel analytical methods for their rapid detection and quantification.A magnetic covalent organic framework(M-COF)adsorbent for the magnetic solid-phase extraction(MSPE)of OPPs from foods was reported.M-COF was synthesized by the Schiff base condensation reaction of 1,3,5-tris(4-aminophenyl)benzene and 4,4-biphenyldicarboxaldehyde on the surface of amino-functionalized magnetic nanoparticles.Density functional theory(DFT)calculations showed that adsorption of OPPs onto the surface of M-COF involved hydrophobic effects,van der Waals interactions,π-πinteractions,halogen-N bonding,and hydrogen bonding.Combined with gas chromatography-mass spectrometry(GC-MS)technology,the MSPE method features low limits of detection for OPPs(0.002-0.015μg/L),good reproducibility(1.45%-6.14%),wide linear detection range(0.01-1μg/L,R≥0.9935),and satisfactory recoveries(87.3%-110.4%).The method was successfully applied for the trace analysis of OPPs in spiked fruit juices.
基金supported by National Natural Science Foundation of China(Nos.22371218,21702153,52270070 and21801194)Natural Science Foundation of Zhejiang Province(No.LR22B020001)+1 种基金Wuhan Science and Technology Bureau(No.whkxjsj009)the support of the Core Facility of Wuhan University and the Large-scale Instrument and Equipment Sharing Foundation of Wuhan University。
文摘The development of organic frameworks with radical skeletons is desired.In this study,we report the development of a novel two-dimensional radical halogen-bonded organic framework(XOF).The radical monomer,benzimidazole triphenylmethyl(BTTM),was synthesized through the coupling of TTM radicals with benzimidazole.Initially,the benzimidazole units were coordinated with Ag^(+)ions to create a[N···Ag···N]^(+)framework.Subsequently,the addition of iodine led to the in situ replacement of Ag^(+)with I^(+)ions,forming[N···I···N]^(+)linkers and resulting in the creation of the XOF structure.The resulting XOF-HBTTM and XOF-BTTM structures demonstrated good-crystallinity,confirmed by PXRD,HR-TEM,SEAD,and SAXS analyses.EPR measurements confirmed the preservation of radical characteristics within the XOF framework.Furthermore,SQUID measurements indicated that XOF-BTTM exhibits spin moments of S=1/2 at 2 K,with a saturated magnetization strength peaking at 4.10 emu/g,a notable enhancement compared to 1.87 emu/g for the BTTM monomer.This improvement in magnetism is attributed to the extended spin density distribution and the presence of[N···I···N]^(+)interactions,as suggested by DFT calculations.Additionally,the radical XOF-BTTM exhibited significantly enhanced electrical conductivity,reaching up to 1.30×10^(-4)S/cm,which is two orders of magnitude higher than that of XOF-HBTTM.This increased conductivity is linked to a reduced HOMO-LUMO gap,higher carrier density,and the incorporation of triphenylmethyl radicals within the framework.This research highlights the potential of benzimidazolyl motifs in constructing functional XOFs and advances our understanding of radical organic frameworks.
基金funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,Saudi Arabia under Grant No.(GPIP:71-829-2024).
文摘Email communication plays a crucial role in both personal and professional contexts;however,it is frequently compromised by the ongoing challenge of spam,which detracts from productivity and introduces considerable security risks.Current spam detection techniques often struggle to keep pace with the evolving tactics employed by spammers,resulting in user dissatisfaction and potential data breaches.To address this issue,we introduce the Divide and Conquer-Generative Adversarial Network Squeeze and Excitation-Based Framework(DaC-GANSAEBF),an innovative deep-learning model designed to identify spam emails.This framework incorporates cutting-edge technologies,such as Generative Adversarial Networks(GAN),Squeeze and Excitation(SAE)modules,and a newly formulated Light Dual Attention(LDA)mechanism,which effectively utilizes both global and local attention to discern intricate patterns within textual data.This approach significantly improves efficiency and accuracy by segmenting scanned email content into smaller,independently evaluated components.The model underwent training and validation using four publicly available benchmark datasets,achieving an impressive average accuracy of 98.87%,outperforming leading methods in the field.These findings underscore the resilience and scalability of DaC-GANSAEBF,positioning it as a viable solution for contemporary spam detection systems.The framework can be easily integrated into existing technologies to enhance user security and reduce the risks associated with spam.
