The exploitable heap layouts are used to determine the exploitability of heap vulnerabilities in general-purpose applications.Prior studies have focused on using fuzzing-based methods to generate more exploitable heap...The exploitable heap layouts are used to determine the exploitability of heap vulnerabilities in general-purpose applications.Prior studies have focused on using fuzzing-based methods to generate more exploitable heap layouts.However,the exploitable heap layout cannot fully demonstrate the exploitability of a vulnerability,as it is uncertain whether the attacker can control the data covered by the overflow.In this paper,we propose the Heap Overflow Exploitability Evaluator(Hoee),a new approach to automatically reveal the exploitability of heap buffer overflow vulnerabilities by evaluating proof-of-concepts(PoCs)generated by fuzzers.Hoee leverages several techniques to collect dynamic information at runtime and recover heap object layouts in a fine-grained manner.The overflow context is carefully analyzed to determine whether the sensitive pointer is corrupted,tainted,or critically used.We evaluate Hoee on 34 real-world CVE vulnerabilities from 16 general-purpose programs.The results demonstrate that Hoee accurately identifies the key factors for developing exploits in vulnerable contexts and correctly recognizes the behavior of overflow.展开更多
In this study,a completely different approach to optimization is introduced through the development of a novel metaheuristic algorithm called the Barber Optimization Algorithm(BaOA).Inspired by the human interactions ...In this study,a completely different approach to optimization is introduced through the development of a novel metaheuristic algorithm called the Barber Optimization Algorithm(BaOA).Inspired by the human interactions between barbers and customers,BaOA captures two key processes:the customer’s selection of a hairstyle and the detailed refinement during the haircut.These processes are translated into a mathematical framework that forms the foundation of BaOA,consisting of two critical phases:exploration,representing the creative selection process,and exploitation,which focuses on refining details for optimization.The performance of BaOA is evaluated using 52 standard benchmark functions,including unimodal,high-dimensional multimodal,fixed-dimensional multimodal,and the Congress on Evolutionary Computation(CEC)2017 test suite.This comprehensive assessment highlights BaOA’s ability to balance exploration and exploitation effectively,resulting in high-quality solutions.A comparative analysis against twelve widely known metaheuristic algorithms further demonstrates BaOA’s superior performance,as it consistently delivers better results across most benchmark functions.To validate its real-world applicability,BaOA is tested on four engineering design problems,illustrating its capability to address practical challenges with remarkable efficiency.The results confirm BaOA’s versatility and reliability as an optimization tool.This study not only introduces an innovative algorithm but also establishes its effectiveness in solving complex problems,providing a foundation for future research and applications in diverse scientific and engineering domains.展开更多
Padma was 17 when the democratic reform was introduced in Xizang in 1959.Before the reform,the region had been ruled by feudal serfdom under a theocracy for centuries.Nearly one million serfs were subjected to estate-...Padma was 17 when the democratic reform was introduced in Xizang in 1959.Before the reform,the region had been ruled by feudal serfdom under a theocracy for centuries.Nearly one million serfs were subjected to estate-holders'cruel exploitation and oppression.Padma was one of them.展开更多
Economic violence is a form of domestic violence that extends beyond physical harm,affecting victims’economic stability and independence.This situation perpetuates gender inequality and also reinforces the cycle of g...Economic violence is a form of domestic violence that extends beyond physical harm,affecting victims’economic stability and independence.This situation perpetuates gender inequality and also reinforces the cycle of gender-based violence.With definitions of economic violence broadening to encompass a range of coercive and manipulative behaviors-from financial abuse in domestic violence scenarios to the economic harassment faced by stay-at-home moms-understanding this form of exploitation is crucial for crafting effective interventions.This article aims to delve into various facets of economic violence,including its definition,prevalence,and the stark realities it creates for its victims.Following the search of international databases:Social Work Abstracts(EBSCO),Psychology Abstracts,Family and Women Studies Worldwide,Psychiatry Online,Psych INFO(including Psych ARTICLES),PubMed,Wiley,and Scopus,60 peer-reviewed articles that met all inclusion criteria were included in the paper.Our review clarifies that looking forward,the call for a comprehensive understanding of economic violence,enhanced legal frameworks,and the strengthening of supportive networks underscore the multidisciplinary approach required to combat this issue effectively.展开更多
This paper introduces a novel optimization approach called Recuperated Seed Search Optimization(RSSO),designed to address challenges in solving mechanical engineering design problems.Many optimization techniques strug...This paper introduces a novel optimization approach called Recuperated Seed Search Optimization(RSSO),designed to address challenges in solving mechanical engineering design problems.Many optimization techniques struggle with slow convergence and suboptimal solutions due to complex,nonlinear natures.The Sperm Swarm Optimization(SSO)algorithm,which mimics the sperm’s movement to reach an egg,is one such technique.To improve SSO,researchers combined it with three strategies:opposition-based learning(OBL),Cauchy mutation(CM),and position clamping.OBL introduces diversity to SSO by exploring opposite solutions,speeding up convergence.CM enhances both exploration and exploitation capabilities throughout the optimization process.This combined approach,RSSO,has been rigorously tested on standard benchmark functions,real-world engineering problems,and through statistical analysis(Wilcoxon test).The results demonstrate that RSSO significantly outperforms other optimization algorithms,achieving faster convergence and better solutions.The paper details the RSSO algorithm,discusses its implementation,and presents comparative results that validate its effectiveness in solving complex engineering design challenges.展开更多
This study examined how exploitative leadership undermines employees’experience of flow with work role overload and traditionalist values.Data were collected from 361 staff members across diverse industries in China(...This study examined how exploitative leadership undermines employees’experience of flow with work role overload and traditionalist values.Data were collected from 361 staff members across diverse industries in China(females=58.17%,mean age=32.14,SD=5.83).Structural equation modeling results indicated that exploitative leadership reduces employees’work-related flow via increased role overload.Furthermore,employees’traditionality level moderates the exploitative leadership effects on role overload.Specifically,employees with higher traditionality reported lower role overload when experiencing exploitative leadership,suggesting that cultural values may buffer its negative impact.This study contributes to understanding the mechanism and contextual factors linking exploitative leadership to work-related flow,filling a gap in the literature.Organizations are encouraged to reduce exploitative leadership behaviors through leadership development programs and to consider employees’value orientations when designing work environments.展开更多
Heuristic optimization algorithms have been widely used in solving complex optimization problems in various fields such as engineering,economics,and computer science.These algorithms are designed to find high-quality ...Heuristic optimization algorithms have been widely used in solving complex optimization problems in various fields such as engineering,economics,and computer science.These algorithms are designed to find high-quality solutions efficiently by balancing exploration of the search space and exploitation of promising solutions.While heuristic optimization algorithms vary in their specific details,they often exhibit common patterns that are essential to their effectiveness.This paper aims to analyze and explore common patterns in heuristic optimization algorithms.Through a comprehensive review of the literature,we identify the patterns that are commonly observed in these algorithms,including initialization,local search,diversity maintenance,adaptation,and stochasticity.For each pattern,we describe the motivation behind it,its implementation,and its impact on the search process.To demonstrate the utility of our analysis,we identify these patterns in multiple heuristic optimization algorithms.For each case study,we analyze how the patterns are implemented in the algorithm and how they contribute to its performance.Through these case studies,we show how our analysis can be used to understand the behavior of heuristic optimization algorithms and guide the design of new algorithms.Our analysis reveals that patterns in heuristic optimization algorithms are essential to their effectiveness.By understanding and incorporating these patterns into the design of new algorithms,researchers can develop more efficient and effective optimization algorithms.展开更多
Drawing upon the Conservation of Resources theory,this study investigated the relationship between proactive personality and strengths use,as well as the mediating role of psychological safety and the moderating role ...Drawing upon the Conservation of Resources theory,this study investigated the relationship between proactive personality and strengths use,as well as the mediating role of psychological safety and the moderating role of exploitative leadership within this relationship.Data were collected from 368 employees(females=57.61%;mean age=32.35;SD=6.31)working in various organizations in China at two points in time with a two-week interval.We conducted structural equation modeling and a moderated mediation path analysis to test our hypotheses.The results demonstrated that proactive personality is positively related to strengths use and psychological safety partially mediates the association of proactive personality and strengths use.Furthermore,this study also found that exploitative leadership weakens the direct relationship between proactive personality and psychological safety and the indirect relationship of proactive personality with strengths use through psychological safety.This study identified the underlying mechanisms between proactive personality and strengths use.展开更多
The permeability of rocks is of utmost importance in the exploitation of deep geological resources.Current characterizations of rock permeability typically consider the influence of either pores or fractures alone.How...The permeability of rocks is of utmost importance in the exploitation of deep geological resources.Current characterizations of rock permeability typically consider the influence of either pores or fractures alone.However,deep reservoir rock formations are subjected to complex environments with coupling of high temperature and stress.As a result,deep reservoir rocks possess a complex structure comprising of pores and fractures,making it challenging to understand their impact on permeability.Comprehending this relationship is vital for the secure and efficient exploitation of deep geological resources.This study presents a permeability calculation model that enables simultaneously quantify the impacts of pore and fracture with full feature size.The model independently considers large-scale fractures’fractal properties and tortuosity while also addressing the distribution and size of small-scale pores.A tortuosity expression that incorporates the effects of thermal damage has been developed using the pore geometric elasticity method.Considering the distinct contributions of pores and fractures to rock permeability,a comprehensive rock permeability calculation model is established.This model has two main strengths:it thoroughly characterizes the influence of pore structures on permeability at multiple scales and precisely details how fractal attributes of fractures affect permeability.To validate the applicability of the model,this study conducted seepage experiments and microscopic observations,capturing the variations in permeability under thermo-mechanical coupling,while quantifying the geometric characteristics and spatial distribution of pores and fractures within the rock.By comparing the measured permeability results,the theoretical values demonstrated a commendable fit.In comparison to previous models,this innovative approach more accurately captures various flow characteristics of the rock under the influence of thermo-mechanical coupling.展开更多
Exploring dynamic mechanical responses and failure behaviors of hot dry rock(HDR)is significant for geothermal exploitation and stability assessment.In this study,via the split Hopkinson pressure bar(SHPB)system,a ser...Exploring dynamic mechanical responses and failure behaviors of hot dry rock(HDR)is significant for geothermal exploitation and stability assessment.In this study,via the split Hopkinson pressure bar(SHPB)system,a series of dynamic compression tests were conducted on granite treated by cyclic thermal shocks at different temperatures.We analyzed the effects of cyclic thermal shock on the thermal-related physical and dynamic mechanical behaviors of granite.Specifically,the P-wave velocity,dynamic strength,and elastic modulus of the tested granite decrease with increasing temperature and cycle number,while porosity and peak strain increase.The degradation law of dynamic mechanical properties could be described by a cubic polynomial.Cyclic thermal shock promotes shear cracks propagation,causing dynamic failure mode of granite to transition from splitting to tensile-shear composite failure,accompanied by surface spalling and debris splashing.Moreover,the thermal shock damage evolution and coupled failure mechanism of tested granite are discussed.The evolution of thermal shock damage with thermal shock cycle numbers shows an obvious S-shaped surface,featured by an exponential correlation with dynamic mechanical parameters.In addition,with increasing thermal shock temperature and cycles,granite mineral species barely change,but the length and width of thermal cracks increase significantly.The non-uniform expansion of minerals,thermal shock-induced cracking,and water-rock interaction are primary factors for deteriorating dynamic mechanical properties of granite under cyclic thermal shock.展开更多
In repeated zero-sum games,instead of constantly playing an equilibrium strategy of the stage game,learning to exploit the opponent given historical interactions could typically obtain a higher utility.However,when pl...In repeated zero-sum games,instead of constantly playing an equilibrium strategy of the stage game,learning to exploit the opponent given historical interactions could typically obtain a higher utility.However,when playing against a fully adaptive opponent,one would have dificulty identifying the opponent's adaptive dynamics and further exploiting its potential weakness.In this paper,we study the problem of optimizing against the adaptive opponent who uses no-regret learning.No-regret learning is a classic and widely-used branch of adaptive learning algorithms.We propose a general framework for online modeling no-regret opponents and exploiting their weakness.With this framework,one could approximate the opponent's no-regret learning dynamics and then develop a response plan to obtain a significant profit based on the inferences of the opponent's strategies.We employ two system identification architectures,including the recurrent neural network(RNN)and the nonlinear autoregressive exogenous model,and adopt an efficient greedy response plan within the framework.Theoretically,we prove the approximation capability of our RNN architecture at approximating specific no-regret dynamics.Empirically,we demonstrate that during interactions at a low level of non-stationarity,our architectures could approximate the dynamics with a low error,and the derived policies could exploit the no-regret opponent to obtain a decent utility.展开更多
This study employs experimental and analytical methods to quantitatively investigate the nonlinear geomechanical and physicochemical processes of multiphase and high-stress coal-bearing rock masses and non-equilibrium...This study employs experimental and analytical methods to quantitatively investigate the nonlinear geomechanical and physicochemical processes of multiphase and high-stress coal-bearing rock masses and non-equilibrium geological materials,as well as their interactions.The research encompasses following aspects,i.e.1)the relationship between volatile matter yield,geological age,and distance from magmatic deposits in Kuzbass coalfield;2)the impact of physicochemical property bifurcations on coal and gas outbursts;3)the variation law of coalbed methane content with burial depth;4)the relaxation energy of gas content;5)the specific surface area of coal;6)the relationship between heat release and deformation waves of Kuzbass coal samples of different orders under uniaxial compression;7)the gas outbursts in different mines in Kuzbass;8)the relationship between seismic energy and gas outburst concentration in coal mines;9)the influence of piston mechanism;10)the connection operation between Langmuir equation and Oparin equation;and 11)the equation of motion for structural media.The research results have created a prerequisite for establishing a unified theory of the interaction between nonlinear geomechanics and physicochemical processes in rock masses,which is of great significance for the safe development and utilization of underground resources.展开更多
This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural habitat.FLO draws its inspi...This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural habitat.FLO draws its inspiration from the sit-and-wait hunting strategy of these lizards.The algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases:(i)an exploration phase,which mimics the lizard’s sudden attack on its prey,and(ii)an exploitation phase,which simulates the lizard’s retreat to the treetops after feeding.To assess FLO’s efficacy in addressing optimization problems,its performance is rigorously tested on fifty-two standard benchmark functions.These functions include unimodal,high-dimensional multimodal,and fixed-dimensional multimodal functions,as well as the challenging CEC 2017 test suite.FLO’s performance is benchmarked against twelve established metaheuristic algorithms,providing a comprehensive comparative analysis.The simulation results demonstrate that FLO excels in both exploration and exploitation,effectively balancing these two critical aspects throughout the search process.This balanced approach enables FLO to outperform several competing algorithms in numerous test cases.Additionally,FLO is applied to twenty-two constrained optimization problems from the CEC 2011 test suite and four complex engineering design problems,further validating its robustness and versatility in solving real-world optimization challenges.Overall,the study highlights FLO’s superior performance and its potential as a powerful tool for tackling a wide range of optimization problems.展开更多
In this study,a new image-based method for the extraction and characterization of pore-throat network for unconventional hydrocarbon storage and exploitation is proposed.“Pore-throat solidity”,which is analogous to ...In this study,a new image-based method for the extraction and characterization of pore-throat network for unconventional hydrocarbon storage and exploitation is proposed.“Pore-throat solidity”,which is analogous to particle solidity,and a new method for automatic identification of pores and throats in tight sandstone oil reservoirs are introduced.Additionally,the“pore-throat combination”and“pure pore”are defined and distinguished by drawing the cumulative probability curve of the pore-throat solidity and by selecting an appropriate cutoff point.When the discrete grid set is recognized as a pore-throat combination,Legendre ellipse fitting and minimum Feret diameter are used.When the pore and throat grid sets are identified as pure pores,the pore diameter can be directly calculated.Using the new method,the analytical results for the physical parameters and pore radius agree well with most prior studies.The results comparing the maximum ball and the new model could also prove the accuracy of the latter's in micro and nano scales.The new model provides a more practical theoretical basis and a new calculation method for the rapid and accurate evaluation of the complex processes of oil migration.展开更多
Identifying the real fracture of rock hidden in acoustic emission(AE)source clusters(AE-depicted microcrack zone)remains challenging and crucial.Here we revealed the AE energy(representing dissipated energy)distributi...Identifying the real fracture of rock hidden in acoustic emission(AE)source clusters(AE-depicted microcrack zone)remains challenging and crucial.Here we revealed the AE energy(representing dissipated energy)distribution rule in the rock microcrack zone and proposed an AE-energy-based method for identifying the real fracture.(1)A set of fracture experiments were performed on granite using wedgeloading,and the fracture process was detected and recorded by AE.The microcrack zone associated with the energy dissipation was characterized by AE sources and energy distribution,utilizing our selfdeveloped AE analysis program(RockAE).(2)The accumulated AE energy,an index representing energy dissipation,across the AE-depicted microcrack zone followed the normal distribution model(the mean and variance relate to the real fracture path and the microcrack zone width).This result implies that the nucleation and coalescence of massive cracks(i.e.,real fracture generation process)are supposed to follow a normal distribution.(3)Then,we obtained the real fracture extension path by joining the peak positions of the AE energy normal distribution curve at different cross-sections of the microcrack zone.Consequently,we distinguished between the microcrack zone and the concealed real fracture within it.The deviation was validated as slight as 1–3 mm.展开更多
The analysis of hydrochemical characteristics and influencing factors of surface river on plateau is helpful to study water hydrological cycle and environmental evolution,which can scientifically guide rational develo...The analysis of hydrochemical characteristics and influencing factors of surface river on plateau is helpful to study water hydrological cycle and environmental evolution,which can scientifically guide rational development and utilization of water resources and planning of ecological environment protection.With the expansion and diversification of human activities,the quality of surface rivers will be more directly affected.Therefore,it is of great significance to pay attention to the hydrochemical characteristics of plateau surface rivers and the influence of human activities on their circulation and evolution.In this study,surface water in the Duoqu basin of Jinsha River located in Hengduan mountain region of Eastern Xizang was selected as the representative case.Twenty-three groups of surface water samples were collected to analyze the hydrochemical characteristics and ion sources based on correlation analysis,piper trigram,gibbs model,hydrogen and oxygen isotopic techniques.The results suggest the following:(1)The pH showed slight alkalinity with the value ranged from 7.25 to 8.62.Ca^(2+),Mg^(2+)and HCO_(3)^(–)were the main cations and anions.HCO_(3)^(-)Ca and HCO_(3)^(-)Ca·Mg were the primary hydrochemical types for the surface water of Duoqu River.The correlation analysis showed that TDS had the most significant correlation with Ca^(2+),Mg^(2+)and HCO_(3)^(–).Analysis on hydrogen and oxygen isotopes indicated that the surface rivers were mainly recharged by atmospheric precipitation and glacial melt water in this study area.(2)The surface water had a certain reverse cation alternating adsorption,and surface water ions were mainly derived from rock weathering,mainly controlled by weathering and dissolution of carbonates,and secondly by silicates and sodium rocks.(3)The influence of human activities was weak,while the development of cinnabar minerals had a certain impact on the hydrochemistry characteristics,which was the main factor for causing the increase of SO_(4)^(2–).The densely populated county towns and temples with frequent incense burning activities may cause some anomalies of surface water quality.At present,the Duoqu River watershed had gone through a certain influence of mineral exploitation,so the hydrological cycle and river eco-environment at watershed scale will still bound to be change.The results could provide basic support for better understanding water balance evolution as well as the ecological protection of Duoqu River watershed.展开更多
More and more accounts or devices are shared by multiple users in video applications,which makes it difficult to provide recommendation service.Existing recommendation schemes overlook multiuser sharing scenarios,and ...More and more accounts or devices are shared by multiple users in video applications,which makes it difficult to provide recommendation service.Existing recommendation schemes overlook multiuser sharing scenarios,and they cannot make effective use of the mixed information generated by multi-user when exploring users’potential interests.To solve these problems,this paper proposes an adaptive program recommendation system for multi-user sharing environment.Specifically,we first design an offline periodic identification module by building multi-user features and periodically predicting target user in future sessions,which can separate the profile of target user from mixed log records.Subsequently,an online recommendation module with adaptive timevarying exploration strategy is constructed by jointly using personal information and multi-user social information provided by identification module.On one hand,to learn the dynamic changes in user-interest,a time-varying linear upper confidence bound(LinUCB)based on personal information is designed.On the other hand,to reduce the risk of exploration,a timeinvariant LinUCB based on separated multi-user social information from one account/device is proposed to compute the quality scores of programs for each user,which is integrated into the time-varying LinUCB by cross-weighting strategy.Finally,experimental results validate the efficiency of the proposed scheme.展开更多
This paper introduces the Wolverine Optimization Algorithm(WoOA),a biomimetic method inspired by the foraging behaviors of wolverines in their natural habitats.WoOA innovatively integrates two primary strategies:scave...This paper introduces the Wolverine Optimization Algorithm(WoOA),a biomimetic method inspired by the foraging behaviors of wolverines in their natural habitats.WoOA innovatively integrates two primary strategies:scavenging and hunting,mirroring the wolverine’s adeptness in locating carrion and pursuing live prey.The algorithm’s uniqueness lies in its faithful simulation of these dual strategies,which are mathematically structured to optimize various types of problems effectively.The effectiveness of WoOA is rigorously evaluated using the Congress on Evolutionary Computation(CEC)2017 test suite across dimensions of 10,30,50,and 100.The results showcase WoOA’s robust performance in exploration,exploitation,and maintaining a balance between these phases throughout the search process.Compared to twelve established metaheuristic algorithms,WoOA consistently demonstrates a superior performance across diverse benchmark functions.Statistical analyses,including paired t-tests,Friedman test,and Wilcoxon rank-sum tests,validate WoOA’s significant competitive edge over its counterparts.Additionally,WoOA’s practical applicability is illustrated through its successful resolution of twenty-two constrained scenarios from the CEC 2011 suite and four complex engineering design challenges.These applications underscore WoOA’s efficacy in tackling real-world optimization challenges,further highlighting its potential for widespread adoption in engineering and scientific domains.展开更多
In this article,a novel metaheuristic technique named Far and Near Optimization(FNO)is introduced,offeringversatile applications across various scientific domains for optimization tasks.The core concept behind FNO lie...In this article,a novel metaheuristic technique named Far and Near Optimization(FNO)is introduced,offeringversatile applications across various scientific domains for optimization tasks.The core concept behind FNO lies inintegrating global and local search methodologies to update the algorithm population within the problem-solvingspace based on moving each member to the farthest and nearest member to itself.The paper delineates the theoryof FNO,presenting a mathematical model in two phases:(i)exploration based on the simulation of the movementof a population member towards the farthest member from itself and(ii)exploitation based on simulating themovement of a population member towards the nearest member from itself.FNO’s efficacy in tackling optimizationchallenges is assessed through its handling of the CEC 2017 test suite across problem dimensions of 10,30,50,and 100,as well as to address CEC 2020.The optimization results underscore FNO’s adeptness in exploration,exploitation,and maintaining a balance between them throughout the search process to yield viable solutions.Comparative analysis against twelve established metaheuristic algorithms reveals FNO’s superior performance.Simulation findings indicate FNO’s outperformance of competitor algorithms,securing the top rank as the mosteffective optimizer across a majority of benchmark functions.Moreover,the outcomes derived by employing FNOon twenty-two constrained optimization challenges from the CEC 2011 test suite,alongside four engineering designdilemmas,showcase the effectiveness of the suggested method in tackling real-world scenarios.展开更多
文摘The exploitable heap layouts are used to determine the exploitability of heap vulnerabilities in general-purpose applications.Prior studies have focused on using fuzzing-based methods to generate more exploitable heap layouts.However,the exploitable heap layout cannot fully demonstrate the exploitability of a vulnerability,as it is uncertain whether the attacker can control the data covered by the overflow.In this paper,we propose the Heap Overflow Exploitability Evaluator(Hoee),a new approach to automatically reveal the exploitability of heap buffer overflow vulnerabilities by evaluating proof-of-concepts(PoCs)generated by fuzzers.Hoee leverages several techniques to collect dynamic information at runtime and recover heap object layouts in a fine-grained manner.The overflow context is carefully analyzed to determine whether the sensitive pointer is corrupted,tainted,or critically used.We evaluate Hoee on 34 real-world CVE vulnerabilities from 16 general-purpose programs.The results demonstrate that Hoee accurately identifies the key factors for developing exploits in vulnerable contexts and correctly recognizes the behavior of overflow.
文摘In this study,a completely different approach to optimization is introduced through the development of a novel metaheuristic algorithm called the Barber Optimization Algorithm(BaOA).Inspired by the human interactions between barbers and customers,BaOA captures two key processes:the customer’s selection of a hairstyle and the detailed refinement during the haircut.These processes are translated into a mathematical framework that forms the foundation of BaOA,consisting of two critical phases:exploration,representing the creative selection process,and exploitation,which focuses on refining details for optimization.The performance of BaOA is evaluated using 52 standard benchmark functions,including unimodal,high-dimensional multimodal,fixed-dimensional multimodal,and the Congress on Evolutionary Computation(CEC)2017 test suite.This comprehensive assessment highlights BaOA’s ability to balance exploration and exploitation effectively,resulting in high-quality solutions.A comparative analysis against twelve widely known metaheuristic algorithms further demonstrates BaOA’s superior performance,as it consistently delivers better results across most benchmark functions.To validate its real-world applicability,BaOA is tested on four engineering design problems,illustrating its capability to address practical challenges with remarkable efficiency.The results confirm BaOA’s versatility and reliability as an optimization tool.This study not only introduces an innovative algorithm but also establishes its effectiveness in solving complex problems,providing a foundation for future research and applications in diverse scientific and engineering domains.
文摘Padma was 17 when the democratic reform was introduced in Xizang in 1959.Before the reform,the region had been ruled by feudal serfdom under a theocracy for centuries.Nearly one million serfs were subjected to estate-holders'cruel exploitation and oppression.Padma was one of them.
文摘Economic violence is a form of domestic violence that extends beyond physical harm,affecting victims’economic stability and independence.This situation perpetuates gender inequality and also reinforces the cycle of gender-based violence.With definitions of economic violence broadening to encompass a range of coercive and manipulative behaviors-from financial abuse in domestic violence scenarios to the economic harassment faced by stay-at-home moms-understanding this form of exploitation is crucial for crafting effective interventions.This article aims to delve into various facets of economic violence,including its definition,prevalence,and the stark realities it creates for its victims.Following the search of international databases:Social Work Abstracts(EBSCO),Psychology Abstracts,Family and Women Studies Worldwide,Psychiatry Online,Psych INFO(including Psych ARTICLES),PubMed,Wiley,and Scopus,60 peer-reviewed articles that met all inclusion criteria were included in the paper.Our review clarifies that looking forward,the call for a comprehensive understanding of economic violence,enhanced legal frameworks,and the strengthening of supportive networks underscore the multidisciplinary approach required to combat this issue effectively.
文摘This paper introduces a novel optimization approach called Recuperated Seed Search Optimization(RSSO),designed to address challenges in solving mechanical engineering design problems.Many optimization techniques struggle with slow convergence and suboptimal solutions due to complex,nonlinear natures.The Sperm Swarm Optimization(SSO)algorithm,which mimics the sperm’s movement to reach an egg,is one such technique.To improve SSO,researchers combined it with three strategies:opposition-based learning(OBL),Cauchy mutation(CM),and position clamping.OBL introduces diversity to SSO by exploring opposite solutions,speeding up convergence.CM enhances both exploration and exploitation capabilities throughout the optimization process.This combined approach,RSSO,has been rigorously tested on standard benchmark functions,real-world engineering problems,and through statistical analysis(Wilcoxon test).The results demonstrate that RSSO significantly outperforms other optimization algorithms,achieving faster convergence and better solutions.The paper details the RSSO algorithm,discusses its implementation,and presents comparative results that validate its effectiveness in solving complex engineering design challenges.
文摘This study examined how exploitative leadership undermines employees’experience of flow with work role overload and traditionalist values.Data were collected from 361 staff members across diverse industries in China(females=58.17%,mean age=32.14,SD=5.83).Structural equation modeling results indicated that exploitative leadership reduces employees’work-related flow via increased role overload.Furthermore,employees’traditionality level moderates the exploitative leadership effects on role overload.Specifically,employees with higher traditionality reported lower role overload when experiencing exploitative leadership,suggesting that cultural values may buffer its negative impact.This study contributes to understanding the mechanism and contextual factors linking exploitative leadership to work-related flow,filling a gap in the literature.Organizations are encouraged to reduce exploitative leadership behaviors through leadership development programs and to consider employees’value orientations when designing work environments.
文摘Heuristic optimization algorithms have been widely used in solving complex optimization problems in various fields such as engineering,economics,and computer science.These algorithms are designed to find high-quality solutions efficiently by balancing exploration of the search space and exploitation of promising solutions.While heuristic optimization algorithms vary in their specific details,they often exhibit common patterns that are essential to their effectiveness.This paper aims to analyze and explore common patterns in heuristic optimization algorithms.Through a comprehensive review of the literature,we identify the patterns that are commonly observed in these algorithms,including initialization,local search,diversity maintenance,adaptation,and stochasticity.For each pattern,we describe the motivation behind it,its implementation,and its impact on the search process.To demonstrate the utility of our analysis,we identify these patterns in multiple heuristic optimization algorithms.For each case study,we analyze how the patterns are implemented in the algorithm and how they contribute to its performance.Through these case studies,we show how our analysis can be used to understand the behavior of heuristic optimization algorithms and guide the design of new algorithms.Our analysis reveals that patterns in heuristic optimization algorithms are essential to their effectiveness.By understanding and incorporating these patterns into the design of new algorithms,researchers can develop more efficient and effective optimization algorithms.
基金supported by Youth Foundation of Beijing Wuzi University(Grant No.2024XJQN26).
文摘Drawing upon the Conservation of Resources theory,this study investigated the relationship between proactive personality and strengths use,as well as the mediating role of psychological safety and the moderating role of exploitative leadership within this relationship.Data were collected from 368 employees(females=57.61%;mean age=32.35;SD=6.31)working in various organizations in China at two points in time with a two-week interval.We conducted structural equation modeling and a moderated mediation path analysis to test our hypotheses.The results demonstrated that proactive personality is positively related to strengths use and psychological safety partially mediates the association of proactive personality and strengths use.Furthermore,this study also found that exploitative leadership weakens the direct relationship between proactive personality and psychological safety and the indirect relationship of proactive personality with strengths use through psychological safety.This study identified the underlying mechanisms between proactive personality and strengths use.
基金supported by the National Natural Science Foundation of China(Nos.52192625,52174082,and U22A20166)Guangdong Basic and Applied Basic Research Foundation(No.2025B1515020039)+3 种基金National Key Research and Development Program(No.2023YFF0723200)Shenzhen Science and Technology Program(No.RCYX20221008092903013)the Program for Guangdong Introducing Innovative and Entrepreneurial Teams(No.2019ZT08G315)the Natural Science Foundation of Chongqing(No.CSTB2022NSCQ-MSX1593).
文摘The permeability of rocks is of utmost importance in the exploitation of deep geological resources.Current characterizations of rock permeability typically consider the influence of either pores or fractures alone.However,deep reservoir rock formations are subjected to complex environments with coupling of high temperature and stress.As a result,deep reservoir rocks possess a complex structure comprising of pores and fractures,making it challenging to understand their impact on permeability.Comprehending this relationship is vital for the secure and efficient exploitation of deep geological resources.This study presents a permeability calculation model that enables simultaneously quantify the impacts of pore and fracture with full feature size.The model independently considers large-scale fractures’fractal properties and tortuosity while also addressing the distribution and size of small-scale pores.A tortuosity expression that incorporates the effects of thermal damage has been developed using the pore geometric elasticity method.Considering the distinct contributions of pores and fractures to rock permeability,a comprehensive rock permeability calculation model is established.This model has two main strengths:it thoroughly characterizes the influence of pore structures on permeability at multiple scales and precisely details how fractal attributes of fractures affect permeability.To validate the applicability of the model,this study conducted seepage experiments and microscopic observations,capturing the variations in permeability under thermo-mechanical coupling,while quantifying the geometric characteristics and spatial distribution of pores and fractures within the rock.By comparing the measured permeability results,the theoretical values demonstrated a commendable fit.In comparison to previous models,this innovative approach more accurately captures various flow characteristics of the rock under the influence of thermo-mechanical coupling.
基金The authors are grateful for the financial support from the National Natural Science Foundation of China(Grant Nos.52225904 and 52039007)the Natural Science Foundation of Sichuan Province(Grant No.2023NSFSC0377)supported by the New Cornerstone Science Foundation through the XPLORER PRIZE.
文摘Exploring dynamic mechanical responses and failure behaviors of hot dry rock(HDR)is significant for geothermal exploitation and stability assessment.In this study,via the split Hopkinson pressure bar(SHPB)system,a series of dynamic compression tests were conducted on granite treated by cyclic thermal shocks at different temperatures.We analyzed the effects of cyclic thermal shock on the thermal-related physical and dynamic mechanical behaviors of granite.Specifically,the P-wave velocity,dynamic strength,and elastic modulus of the tested granite decrease with increasing temperature and cycle number,while porosity and peak strain increase.The degradation law of dynamic mechanical properties could be described by a cubic polynomial.Cyclic thermal shock promotes shear cracks propagation,causing dynamic failure mode of granite to transition from splitting to tensile-shear composite failure,accompanied by surface spalling and debris splashing.Moreover,the thermal shock damage evolution and coupled failure mechanism of tested granite are discussed.The evolution of thermal shock damage with thermal shock cycle numbers shows an obvious S-shaped surface,featured by an exponential correlation with dynamic mechanical parameters.In addition,with increasing thermal shock temperature and cycles,granite mineral species barely change,but the length and width of thermal cracks increase significantly.The non-uniform expansion of minerals,thermal shock-induced cracking,and water-rock interaction are primary factors for deteriorating dynamic mechanical properties of granite under cyclic thermal shock.
基金the Science and Technology Innovation 2030-"New Generation Artificial Intelligence"Major Project(No.2018AAA0100901)。
文摘In repeated zero-sum games,instead of constantly playing an equilibrium strategy of the stage game,learning to exploit the opponent given historical interactions could typically obtain a higher utility.However,when playing against a fully adaptive opponent,one would have dificulty identifying the opponent's adaptive dynamics and further exploiting its potential weakness.In this paper,we study the problem of optimizing against the adaptive opponent who uses no-regret learning.No-regret learning is a classic and widely-used branch of adaptive learning algorithms.We propose a general framework for online modeling no-regret opponents and exploiting their weakness.With this framework,one could approximate the opponent's no-regret learning dynamics and then develop a response plan to obtain a significant profit based on the inferences of the opponent's strategies.We employ two system identification architectures,including the recurrent neural network(RNN)and the nonlinear autoregressive exogenous model,and adopt an efficient greedy response plan within the framework.Theoretically,we prove the approximation capability of our RNN architecture at approximating specific no-regret dynamics.Empirically,we demonstrate that during interactions at a low level of non-stationarity,our architectures could approximate the dynamics with a low error,and the derived policies could exploit the no-regret opponent to obtain a decent utility.
文摘This study employs experimental and analytical methods to quantitatively investigate the nonlinear geomechanical and physicochemical processes of multiphase and high-stress coal-bearing rock masses and non-equilibrium geological materials,as well as their interactions.The research encompasses following aspects,i.e.1)the relationship between volatile matter yield,geological age,and distance from magmatic deposits in Kuzbass coalfield;2)the impact of physicochemical property bifurcations on coal and gas outbursts;3)the variation law of coalbed methane content with burial depth;4)the relaxation energy of gas content;5)the specific surface area of coal;6)the relationship between heat release and deformation waves of Kuzbass coal samples of different orders under uniaxial compression;7)the gas outbursts in different mines in Kuzbass;8)the relationship between seismic energy and gas outburst concentration in coal mines;9)the influence of piston mechanism;10)the connection operation between Langmuir equation and Oparin equation;and 11)the equation of motion for structural media.The research results have created a prerequisite for establishing a unified theory of the interaction between nonlinear geomechanics and physicochemical processes in rock masses,which is of great significance for the safe development and utilization of underground resources.
文摘This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural habitat.FLO draws its inspiration from the sit-and-wait hunting strategy of these lizards.The algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases:(i)an exploration phase,which mimics the lizard’s sudden attack on its prey,and(ii)an exploitation phase,which simulates the lizard’s retreat to the treetops after feeding.To assess FLO’s efficacy in addressing optimization problems,its performance is rigorously tested on fifty-two standard benchmark functions.These functions include unimodal,high-dimensional multimodal,and fixed-dimensional multimodal functions,as well as the challenging CEC 2017 test suite.FLO’s performance is benchmarked against twelve established metaheuristic algorithms,providing a comprehensive comparative analysis.The simulation results demonstrate that FLO excels in both exploration and exploitation,effectively balancing these two critical aspects throughout the search process.This balanced approach enables FLO to outperform several competing algorithms in numerous test cases.Additionally,FLO is applied to twenty-two constrained optimization problems from the CEC 2011 test suite and four complex engineering design problems,further validating its robustness and versatility in solving real-world optimization challenges.Overall,the study highlights FLO’s superior performance and its potential as a powerful tool for tackling a wide range of optimization problems.
基金jointly supported by Beijing Natural Science Foundation(No.8232054)Young Elite Scientists Sponsorship Program by CAST(No.YESS20220094)+2 种基金Young Elite Scientists Sponsorship Program by BAST(No.BYESS2023182)Youth Innovation Promotion Association CAS(No.2023021)National Natural Science Foundation of China(No.41902132)。
文摘In this study,a new image-based method for the extraction and characterization of pore-throat network for unconventional hydrocarbon storage and exploitation is proposed.“Pore-throat solidity”,which is analogous to particle solidity,and a new method for automatic identification of pores and throats in tight sandstone oil reservoirs are introduced.Additionally,the“pore-throat combination”and“pure pore”are defined and distinguished by drawing the cumulative probability curve of the pore-throat solidity and by selecting an appropriate cutoff point.When the discrete grid set is recognized as a pore-throat combination,Legendre ellipse fitting and minimum Feret diameter are used.When the pore and throat grid sets are identified as pure pores,the pore diameter can be directly calculated.Using the new method,the analytical results for the physical parameters and pore radius agree well with most prior studies.The results comparing the maximum ball and the new model could also prove the accuracy of the latter's in micro and nano scales.The new model provides a more practical theoretical basis and a new calculation method for the rapid and accurate evaluation of the complex processes of oil migration.
基金supported by the National Natural Science Foundation of China(No.52274013)the Fundamental Research Funds for the Central Universities(No.2024ZDPYYQ1005)+1 种基金the National Key Research and Development Program of China(No.2021YFC2902103)the Independent Research Project of State Key Laboratory for Fine Exploration and Intelligent Development of Coal Resources,CUMT(No.SKLCRSM23X002).
文摘Identifying the real fracture of rock hidden in acoustic emission(AE)source clusters(AE-depicted microcrack zone)remains challenging and crucial.Here we revealed the AE energy(representing dissipated energy)distribution rule in the rock microcrack zone and proposed an AE-energy-based method for identifying the real fracture.(1)A set of fracture experiments were performed on granite using wedgeloading,and the fracture process was detected and recorded by AE.The microcrack zone associated with the energy dissipation was characterized by AE sources and energy distribution,utilizing our selfdeveloped AE analysis program(RockAE).(2)The accumulated AE energy,an index representing energy dissipation,across the AE-depicted microcrack zone followed the normal distribution model(the mean and variance relate to the real fracture path and the microcrack zone width).This result implies that the nucleation and coalescence of massive cracks(i.e.,real fracture generation process)are supposed to follow a normal distribution.(3)Then,we obtained the real fracture extension path by joining the peak positions of the AE energy normal distribution curve at different cross-sections of the microcrack zone.Consequently,we distinguished between the microcrack zone and the concealed real fracture within it.The deviation was validated as slight as 1–3 mm.
基金financially supported by the Geological Survey Project of China Geological Survey(DD20230077,DD20230456,DD20230424)。
文摘The analysis of hydrochemical characteristics and influencing factors of surface river on plateau is helpful to study water hydrological cycle and environmental evolution,which can scientifically guide rational development and utilization of water resources and planning of ecological environment protection.With the expansion and diversification of human activities,the quality of surface rivers will be more directly affected.Therefore,it is of great significance to pay attention to the hydrochemical characteristics of plateau surface rivers and the influence of human activities on their circulation and evolution.In this study,surface water in the Duoqu basin of Jinsha River located in Hengduan mountain region of Eastern Xizang was selected as the representative case.Twenty-three groups of surface water samples were collected to analyze the hydrochemical characteristics and ion sources based on correlation analysis,piper trigram,gibbs model,hydrogen and oxygen isotopic techniques.The results suggest the following:(1)The pH showed slight alkalinity with the value ranged from 7.25 to 8.62.Ca^(2+),Mg^(2+)and HCO_(3)^(–)were the main cations and anions.HCO_(3)^(-)Ca and HCO_(3)^(-)Ca·Mg were the primary hydrochemical types for the surface water of Duoqu River.The correlation analysis showed that TDS had the most significant correlation with Ca^(2+),Mg^(2+)and HCO_(3)^(–).Analysis on hydrogen and oxygen isotopes indicated that the surface rivers were mainly recharged by atmospheric precipitation and glacial melt water in this study area.(2)The surface water had a certain reverse cation alternating adsorption,and surface water ions were mainly derived from rock weathering,mainly controlled by weathering and dissolution of carbonates,and secondly by silicates and sodium rocks.(3)The influence of human activities was weak,while the development of cinnabar minerals had a certain impact on the hydrochemistry characteristics,which was the main factor for causing the increase of SO_(4)^(2–).The densely populated county towns and temples with frequent incense burning activities may cause some anomalies of surface water quality.At present,the Duoqu River watershed had gone through a certain influence of mineral exploitation,so the hydrological cycle and river eco-environment at watershed scale will still bound to be change.The results could provide basic support for better understanding water balance evolution as well as the ecological protection of Duoqu River watershed.
基金supported by the National Natural Science Foundation of China(Grant No.62277032,62231017,62071254)Education Scientific Planning Project of Jiangsu Province(Grant No.B/2022/01/150)Jiangsu Provincial Qinglan Project,the Special Fund for Urban and Rural Construction and Development in Jiangsu Province.
文摘More and more accounts or devices are shared by multiple users in video applications,which makes it difficult to provide recommendation service.Existing recommendation schemes overlook multiuser sharing scenarios,and they cannot make effective use of the mixed information generated by multi-user when exploring users’potential interests.To solve these problems,this paper proposes an adaptive program recommendation system for multi-user sharing environment.Specifically,we first design an offline periodic identification module by building multi-user features and periodically predicting target user in future sessions,which can separate the profile of target user from mixed log records.Subsequently,an online recommendation module with adaptive timevarying exploration strategy is constructed by jointly using personal information and multi-user social information provided by identification module.On one hand,to learn the dynamic changes in user-interest,a time-varying linear upper confidence bound(LinUCB)based on personal information is designed.On the other hand,to reduce the risk of exploration,a timeinvariant LinUCB based on separated multi-user social information from one account/device is proposed to compute the quality scores of programs for each user,which is integrated into the time-varying LinUCB by cross-weighting strategy.Finally,experimental results validate the efficiency of the proposed scheme.
文摘This paper introduces the Wolverine Optimization Algorithm(WoOA),a biomimetic method inspired by the foraging behaviors of wolverines in their natural habitats.WoOA innovatively integrates two primary strategies:scavenging and hunting,mirroring the wolverine’s adeptness in locating carrion and pursuing live prey.The algorithm’s uniqueness lies in its faithful simulation of these dual strategies,which are mathematically structured to optimize various types of problems effectively.The effectiveness of WoOA is rigorously evaluated using the Congress on Evolutionary Computation(CEC)2017 test suite across dimensions of 10,30,50,and 100.The results showcase WoOA’s robust performance in exploration,exploitation,and maintaining a balance between these phases throughout the search process.Compared to twelve established metaheuristic algorithms,WoOA consistently demonstrates a superior performance across diverse benchmark functions.Statistical analyses,including paired t-tests,Friedman test,and Wilcoxon rank-sum tests,validate WoOA’s significant competitive edge over its counterparts.Additionally,WoOA’s practical applicability is illustrated through its successful resolution of twenty-two constrained scenarios from the CEC 2011 suite and four complex engineering design challenges.These applications underscore WoOA’s efficacy in tackling real-world optimization challenges,further highlighting its potential for widespread adoption in engineering and scientific domains.
文摘In this article,a novel metaheuristic technique named Far and Near Optimization(FNO)is introduced,offeringversatile applications across various scientific domains for optimization tasks.The core concept behind FNO lies inintegrating global and local search methodologies to update the algorithm population within the problem-solvingspace based on moving each member to the farthest and nearest member to itself.The paper delineates the theoryof FNO,presenting a mathematical model in two phases:(i)exploration based on the simulation of the movementof a population member towards the farthest member from itself and(ii)exploitation based on simulating themovement of a population member towards the nearest member from itself.FNO’s efficacy in tackling optimizationchallenges is assessed through its handling of the CEC 2017 test suite across problem dimensions of 10,30,50,and 100,as well as to address CEC 2020.The optimization results underscore FNO’s adeptness in exploration,exploitation,and maintaining a balance between them throughout the search process to yield viable solutions.Comparative analysis against twelve established metaheuristic algorithms reveals FNO’s superior performance.Simulation findings indicate FNO’s outperformance of competitor algorithms,securing the top rank as the mosteffective optimizer across a majority of benchmark functions.Moreover,the outcomes derived by employing FNOon twenty-two constrained optimization challenges from the CEC 2011 test suite,alongside four engineering designdilemmas,showcase the effectiveness of the suggested method in tackling real-world scenarios.
