Wave energy resources assessment is a very important process before the exploitation and utilization of the wave energy. At present, the existing wave energy assessment is focused on theoretical wave energy conditions...Wave energy resources assessment is a very important process before the exploitation and utilization of the wave energy. At present, the existing wave energy assessment is focused on theoretical wave energy conditions for interesting areas. While the evaluation for exploitable wave energy conditions is scarcely ever performed. Generally speaking, the wave energy are non-exploitable under a high sea state and a lower sea state which must be ignored when assessing wave energy. Aiming at this situation, a case study of the East China Sea and the South China Sea is performed. First, a division basis between the theoretical wave energy and the exploitable wave energy is studied. Next, based on recent 20 a ERA-Interim wave field data, some indexes including the spatial and temporal distribution of wave power density, a wave energy exploitable ratio, a wave energy level, a wave energy stability, a total wave energy density, the seasonal variation of the total wave energy and a high sea condition frequency are calculated. And then the theoretical wave energy and the exploitable wave energy are compared each other; the distributions of the exploitable wave energy are assessed and a regional division for exploitable wave energy resources is carried out; the influence of the high sea state is evaluated. The results show that considering collapsing force of the high sea state and the utilization efficiency for wave energy, it is determined that the energy by wave with a significant wave height being not less 1 m or not greater than 4 m is the exploitable wave energy. Compared with the theoretical wave energy, the average wave power density, energy level, total wave energy density and total wave energy of the exploitable wave energy decrease obviously and the stability enhances somewhat. Pronounced differences between the theoretical wave energy and the exploitable wave energy are present. In the East China Sea and the South China Sea, the areas of an abundant and stable exploitable wave energy are primarily located in the north-central part of the South China Sea, the Luzon Strait, east of Taiwan, China and north of Ryukyu Islands; annual average exploitable wave power density values in these areas are approximately 10-15 kW/m; the exploitable coefficient of variation （COV） and seasonal variation （SV） values in these areas are less than 1.2 and 1, respectively. Some coastal areas of the Beibu Gulf, the Changjiang Estuary, the Hangzhou Bay and the Zhujiang Estuary are the poor areas of the wave energy. The areas of the high wave energy exploitable ratio is primarily in nearshore waters. The influence of the high sea state for the wave energy in nearshore waters is less than that in offshore waters. In the areas of the abundant wave energy, the influence of the high sea state for the wave energy is prominent and the utilization of wave energy is relatively difficult. The developed evaluation method may give some references for an exploitable wave energy assessment and is valuable for practical applications.展开更多
In recent years,the small pelagic fishery on the Pacific northwest coast of Mexico has significantly increased fishing pressure on thread herring Opisthonema spp.This fishery is regulated using a precautionary approac...In recent years,the small pelagic fishery on the Pacific northwest coast of Mexico has significantly increased fishing pressure on thread herring Opisthonema spp.This fishery is regulated using a precautionary approach(acceptable biological catch(ABC)and minimum catch size).However,due to fishing dynamics,fish aggregation habits and increased fishing mortality,periodic biomass assessments are necessary to estimate ABC and assess the resource status.The Catch-MSY approach was used to analyze historical series of thread herring catches off the western Baja California Sur(BCS,1981–2018)and the Gulf of California(GC,1972–2018)to estimate exploitable biomass and target reference points in order to obtain catch quotas.According to the results,in GC,the maximum biomass reached in 1972(at the beginning of fishery)and minimum biomass reached in 2015;the estimated exploitable biomass for 2019 was 42.2×10^(4) t;and the maximum sustainable yield(MSY)was 15.4×10^(4) t.In the western BCS coast,the maximum biomass was reached in 1981(at the beginning of fishery)and minimum biomass was reached in 2017;the estimated exploitable biomass for 2019 was 3.2×10^(4) t;and the MSY was 1.2×10^(4) t.Both stocks showed a decrease in biomass over the past years and were currently near to point of full exploitation.The results suggest that the use of the Catch-MSY method is suitable to obtain annual biomass estimates,in order to establish an ABC,to know the current state of the resource,and to avoid overcoming the potential recovery of the stocks.展开更多
Two estimaton methods are used to calculate the theoretical reservoir potential of China's oceanic thermal energy. One is based on the measured temperature difference between the surface water and the deep water, ...Two estimaton methods are used to calculate the theoretical reservoir potential of China's oceanic thermal energy. One is based on the measured temperature difference between the surface water and the deep water, the other on the net radiation energy income from solar insolation either measured or deduced. The results from these two methods are compared and examined. Then, the maximum amount of the exploitable thermal energy is calculated based on the assumption of a Carnot cycle efficiency. In the process of estimation, such factors as water depth, seasonal water temperature variation and geographic location have been taken into account.The theoretical reservoir capacity and the exploitable quantity of the thermal energy of China's four seas are thus estimated separately.展开更多
In order to correctly evaluate the exploitable groundwater resottrce in regional complex, thick Quaternary unconsolidated sediments, the whole Quaternary unconsolidated sediments are considered as a unified hydrogeolo...In order to correctly evaluate the exploitable groundwater resottrce in regional complex, thick Quaternary unconsolidated sediments, the whole Quaternary unconsolidated sediments are considered as a unified hydrogeological unit and a 3-D unsteady groundwater flow numerical model is adopted. Meanwhile, with the consideration of the dynamic changes of the porosity, the hydraulic conductivity and the specific storage with the groundwater level dropping during the exploitation process, an improved composite element seepage matrix adjustment method is applied to solve the unsteady flow problem of free surface. In order to eva- luate the exploitable groundwater resource in Cangzhou, Hebei Province, the hydrogeological conceptual model of Cangzhou is generalized to establish, a 3-D variable parameter numerical model of Cangzhou. Based on the prediction of the present groundwater exploitation, and by adjusting the groundwater exploitation layout, the exploitable groundwater resource is predicted. The model enjoys features like good convergence, good stability and high precision.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
The geothermal resources in hot dry rock(HDR)are considered the future trend in geothermal energy extraction due to their abundant reserves.However,exploitation of the resources is fraught with complexity and technica...The geothermal resources in hot dry rock(HDR)are considered the future trend in geothermal energy extraction due to their abundant reserves.However,exploitation of the resources is fraught with complexity and technical challenges arising from their unique characteristics of high temperature,high strength,and low permeability.With the continuous advancement of artificial intelligence(AI)technology,intelligent algorithms such as machine learning and evolutionary algorithms are gradually replacing or assisting traditional research methods,providing new solutions for HDR geothermal resource exploitation.This study first provides an overview of HDR geothermal resource exploitation technologies and AI methods.Then,the latest research progress is systematically reviewed in AI applications in HDR geothermal reservoir characterization,deep drilling,heat production,and operational parameter optimization.Additionally,this study discusses the potential limitations of AI methods in HDR geothermal resource exploitation and highlights the corresponding opportunities for AI's application.Notably,the study proposes the framework of an intelligent HDR exploitation system,offering a valuable reference for future research and practice.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
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
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
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
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
Exploitability assessment of vulnerabilities is important for both defenders and attackers.The ultimate way to assess the exploitability is crafting a working exploit.However,it usually takes tremendous hours and sign...Exploitability assessment of vulnerabilities is important for both defenders and attackers.The ultimate way to assess the exploitability is crafting a working exploit.However,it usually takes tremendous hours and significant manual efforts.To address this issue,automated techniques can be adopted.Existing solutions usually explore in depth the crashing paths,i.e.,paths taken by proof-of-concept(PoC)inputs triggering vulnerabilities,and assess exploitability by finding exploitable states along the paths.However,exploitable states do not always exist in crashing paths.Moreover,existing solutions heavily rely on symbolic execution and are not scalable in path exploration and exploit generation.In this paper,we propose a novel solution to generate exploit for userspace programs or facilitate the process of crafting a kernel UAF exploit.Technically,we utilize oriented fuzzing to explore diverging paths from vulnerability point.For userspace programs,we adopt a control-flow stitching solution to stitch crashing paths and diverging paths together to generate exploit.For kernel UAF,we leverage a lightweight symbolic execution to identify,analyze and evaluate the system calls valuable and useful for exploiting vulnerabilities.We have developed a prototype system and evaluated it on a set of 19 CTF(capture the flag)programs and 15 realworld Linux kernel UAF vulnerabilities.Experiment results showed it could generate exploit for most of the userspace test set,and it could also facilitate security mitigation bypassing and exploitability evaluation for kernel test set.展开更多
Exploitability assessment of vulnerabilities is important for both defenders and attackers.The ultimate way to assess the exploitability is crafting a working exploit.However,it usually takes tremendous hours and sign...Exploitability assessment of vulnerabilities is important for both defenders and attackers.The ultimate way to assess the exploitability is crafting a working exploit.However,it usually takes tremendous hours and significant manual efforts.To address this issue,automated techniques can be adopted.Existing solutions usually explore in depth the crashing paths,i.e.,paths taken by proof-of-concept(PoC)inputs triggering vulnerabilities,and assess exploitability by finding exploitable states along the paths.However,exploitable states do not always exist in crashing paths.Moreover,existing solutions heavily rely on symbolic execution and are not scalable in path exploration and exploit generation.In this paper,we propose a novel solution to generate exploit for userspace programs or facilitate the process of crafting a kernel UAF exploit.Technically,we utilize oriented fuzzing to explore diverging paths from vulnerability point.For userspace programs,we adopt a control-flow stitching solution to stitch crashing paths and diverging paths together to generate exploit.For kernel UAF,we leverage a lightweight symbolic execution to identify,analyze and evaluate the system calls valuable and useful for exploiting vulnerabilities.We have developed a prototype system and evaluated it on a set of 19 CTF(capture the flag)programs and 15 realworld Linux kernel UAF vulnerabilities.Experiment results showed it could generate exploit for most of the userspace test set,and it could also facilitate security mitigation bypassing and exploitability evaluation for kernel test set.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
基金The Dragon III Project of the European Space Agency and Ministry of Science and Technology of China under contract No.10412the Ocean Renewable Energy Special Fund Project of State Oceanic Administration of China under contract No.GHME2011ZC07the National Natural Science Foundation of China(NSFC)under contract No.41176157
文摘Wave energy resources assessment is a very important process before the exploitation and utilization of the wave energy. At present, the existing wave energy assessment is focused on theoretical wave energy conditions for interesting areas. While the evaluation for exploitable wave energy conditions is scarcely ever performed. Generally speaking, the wave energy are non-exploitable under a high sea state and a lower sea state which must be ignored when assessing wave energy. Aiming at this situation, a case study of the East China Sea and the South China Sea is performed. First, a division basis between the theoretical wave energy and the exploitable wave energy is studied. Next, based on recent 20 a ERA-Interim wave field data, some indexes including the spatial and temporal distribution of wave power density, a wave energy exploitable ratio, a wave energy level, a wave energy stability, a total wave energy density, the seasonal variation of the total wave energy and a high sea condition frequency are calculated. And then the theoretical wave energy and the exploitable wave energy are compared each other; the distributions of the exploitable wave energy are assessed and a regional division for exploitable wave energy resources is carried out; the influence of the high sea state is evaluated. The results show that considering collapsing force of the high sea state and the utilization efficiency for wave energy, it is determined that the energy by wave with a significant wave height being not less 1 m or not greater than 4 m is the exploitable wave energy. Compared with the theoretical wave energy, the average wave power density, energy level, total wave energy density and total wave energy of the exploitable wave energy decrease obviously and the stability enhances somewhat. Pronounced differences between the theoretical wave energy and the exploitable wave energy are present. In the East China Sea and the South China Sea, the areas of an abundant and stable exploitable wave energy are primarily located in the north-central part of the South China Sea, the Luzon Strait, east of Taiwan, China and north of Ryukyu Islands; annual average exploitable wave power density values in these areas are approximately 10-15 kW/m; the exploitable coefficient of variation （COV） and seasonal variation （SV） values in these areas are less than 1.2 and 1, respectively. Some coastal areas of the Beibu Gulf, the Changjiang Estuary, the Hangzhou Bay and the Zhujiang Estuary are the poor areas of the wave energy. The areas of the high wave energy exploitable ratio is primarily in nearshore waters. The influence of the high sea state for the wave energy in nearshore waters is less than that in offshore waters. In the areas of the abundant wave energy, the influence of the high sea state for the wave energy is prominent and the utilization of wave energy is relatively difficult. The developed evaluation method may give some references for an exploitable wave energy assessment and is valuable for practical applications.
基金The Fund of Secretaría Académica y de Investigación of the Instituto Politécnico Nacionalthe Fund of the National Council for Science and Technology(Mexico)+1 种基金Instituto Politécnico Nacionalthe Fund of the Comisión de Operación y Fomento de Actividades Académicas-Instituto Politécnico Nacional。
文摘In recent years,the small pelagic fishery on the Pacific northwest coast of Mexico has significantly increased fishing pressure on thread herring Opisthonema spp.This fishery is regulated using a precautionary approach(acceptable biological catch(ABC)and minimum catch size).However,due to fishing dynamics,fish aggregation habits and increased fishing mortality,periodic biomass assessments are necessary to estimate ABC and assess the resource status.The Catch-MSY approach was used to analyze historical series of thread herring catches off the western Baja California Sur(BCS,1981–2018)and the Gulf of California(GC,1972–2018)to estimate exploitable biomass and target reference points in order to obtain catch quotas.According to the results,in GC,the maximum biomass reached in 1972(at the beginning of fishery)and minimum biomass reached in 2015;the estimated exploitable biomass for 2019 was 42.2×10^(4) t;and the maximum sustainable yield(MSY)was 15.4×10^(4) t.In the western BCS coast,the maximum biomass was reached in 1981(at the beginning of fishery)and minimum biomass was reached in 2017;the estimated exploitable biomass for 2019 was 3.2×10^(4) t;and the MSY was 1.2×10^(4) t.Both stocks showed a decrease in biomass over the past years and were currently near to point of full exploitation.The results suggest that the use of the Catch-MSY method is suitable to obtain annual biomass estimates,in order to establish an ABC,to know the current state of the resource,and to avoid overcoming the potential recovery of the stocks.
文摘Two estimaton methods are used to calculate the theoretical reservoir potential of China's oceanic thermal energy. One is based on the measured temperature difference between the surface water and the deep water, the other on the net radiation energy income from solar insolation either measured or deduced. The results from these two methods are compared and examined. Then, the maximum amount of the exploitable thermal energy is calculated based on the assumption of a Carnot cycle efficiency. In the process of estimation, such factors as water depth, seasonal water temperature variation and geographic location have been taken into account.The theoretical reservoir capacity and the exploitable quantity of the thermal energy of China's four seas are thus estimated separately.
基金Project supported by the Major Research Project of Hebei Province(Grant No.CZCG2008008)
文摘In order to correctly evaluate the exploitable groundwater resottrce in regional complex, thick Quaternary unconsolidated sediments, the whole Quaternary unconsolidated sediments are considered as a unified hydrogeological unit and a 3-D unsteady groundwater flow numerical model is adopted. Meanwhile, with the consideration of the dynamic changes of the porosity, the hydraulic conductivity and the specific storage with the groundwater level dropping during the exploitation process, an improved composite element seepage matrix adjustment method is applied to solve the unsteady flow problem of free surface. In order to eva- luate the exploitable groundwater resource in Cangzhou, Hebei Province, the hydrogeological conceptual model of Cangzhou is generalized to establish, a 3-D variable parameter numerical model of Cangzhou. Based on the prediction of the present groundwater exploitation, and by adjusting the groundwater exploitation layout, the exploitable groundwater resource is predicted. The model enjoys features like good convergence, good stability and high precision.
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.
基金Open Research Fund of Key Laboratory of Deep Earth Science and Engineering,Grant/Award Number:DESEYU202303Fundamental Research Funds for the Central Universities,Grant/Award Number:DUT24GJ205。
文摘The geothermal resources in hot dry rock(HDR)are considered the future trend in geothermal energy extraction due to their abundant reserves.However,exploitation of the resources is fraught with complexity and technical challenges arising from their unique characteristics of high temperature,high strength,and low permeability.With the continuous advancement of artificial intelligence(AI)technology,intelligent algorithms such as machine learning and evolutionary algorithms are gradually replacing or assisting traditional research methods,providing new solutions for HDR geothermal resource exploitation.This study first provides an overview of HDR geothermal resource exploitation technologies and AI methods.Then,the latest research progress is systematically reviewed in AI applications in HDR geothermal reservoir characterization,deep drilling,heat production,and operational parameter optimization.Additionally,this study discusses the potential limitations of AI methods in HDR geothermal resource exploitation and highlights the corresponding opportunities for AI's application.Notably,the study proposes the framework of an intelligent HDR exploitation system,offering a valuable reference for future research and practice.
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.
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.
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.
基金This work is supported by the Key Laboratory of Network Assessment Technology,Chinese Academy of Sciences and Beijing Key Laboratory of Network Security and Protection Technology,as well as Beijing Municipal Science and Technology Project(No.Z181100002718002)National Natural Science Foundation of China(No.61572481 and 61602470,61772308,61472209,61502536,and U1736209)and Young Elite Scientists Sponsorship Program by CAST(No.2016QNRC001).
文摘Exploitability assessment of vulnerabilities is important for both defenders and attackers.The ultimate way to assess the exploitability is crafting a working exploit.However,it usually takes tremendous hours and significant manual efforts.To address this issue,automated techniques can be adopted.Existing solutions usually explore in depth the crashing paths,i.e.,paths taken by proof-of-concept(PoC)inputs triggering vulnerabilities,and assess exploitability by finding exploitable states along the paths.However,exploitable states do not always exist in crashing paths.Moreover,existing solutions heavily rely on symbolic execution and are not scalable in path exploration and exploit generation.In this paper,we propose a novel solution to generate exploit for userspace programs or facilitate the process of crafting a kernel UAF exploit.Technically,we utilize oriented fuzzing to explore diverging paths from vulnerability point.For userspace programs,we adopt a control-flow stitching solution to stitch crashing paths and diverging paths together to generate exploit.For kernel UAF,we leverage a lightweight symbolic execution to identify,analyze and evaluate the system calls valuable and useful for exploiting vulnerabilities.We have developed a prototype system and evaluated it on a set of 19 CTF(capture the flag)programs and 15 realworld Linux kernel UAF vulnerabilities.Experiment results showed it could generate exploit for most of the userspace test set,and it could also facilitate security mitigation bypassing and exploitability evaluation for kernel test set.
基金supported by the Key Laboratory of Network Assessment TechnologyChinese Academy of Sciences and Beijing Key Laboratory of Network Security and Protection Technology+2 种基金Beijing Municipal Science and Technology Project(No.Z181100002718002)National Natural Science Foundation of China(No.61572481 and 61602470,61772308,61472209,61502536,and U1736209)Young Elite Scientists Sponsorship Program by CAST(No.2016QNRC001).
文摘Exploitability assessment of vulnerabilities is important for both defenders and attackers.The ultimate way to assess the exploitability is crafting a working exploit.However,it usually takes tremendous hours and significant manual efforts.To address this issue,automated techniques can be adopted.Existing solutions usually explore in depth the crashing paths,i.e.,paths taken by proof-of-concept(PoC)inputs triggering vulnerabilities,and assess exploitability by finding exploitable states along the paths.However,exploitable states do not always exist in crashing paths.Moreover,existing solutions heavily rely on symbolic execution and are not scalable in path exploration and exploit generation.In this paper,we propose a novel solution to generate exploit for userspace programs or facilitate the process of crafting a kernel UAF exploit.Technically,we utilize oriented fuzzing to explore diverging paths from vulnerability point.For userspace programs,we adopt a control-flow stitching solution to stitch crashing paths and diverging paths together to generate exploit.For kernel UAF,we leverage a lightweight symbolic execution to identify,analyze and evaluate the system calls valuable and useful for exploiting vulnerabilities.We have developed a prototype system and evaluated it on a set of 19 CTF(capture the flag)programs and 15 realworld Linux kernel UAF vulnerabilities.Experiment results showed it could generate exploit for most of the userspace test set,and it could also facilitate security mitigation bypassing and exploitability evaluation for kernel test set.
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.
