Fluctuating voltage levels in power grids necessitate automatic voltage regulators(AVRs)to ensure stability.This study examined the modeling and control of AVR in hydroelectric power plants using model predictive cont...Fluctuating voltage levels in power grids necessitate automatic voltage regulators(AVRs)to ensure stability.This study examined the modeling and control of AVR in hydroelectric power plants using model predictive control(MPC),which utilizes an extensive mathe-matical model of the voltage regulation system to optimize the control actions over a defined prediction horizon.This predictive feature enables MPC to minimize voltage deviations while accounting for operational constraints,thereby improving stability and performance under dynamic conditions.Thefindings were compared with those derived from an optimal proportional integral derivative(PID)con-troller designed using the artificial bee colony(ABC)algorithm.Although the ABC-PID method adjusts the PID parameters based on historical data,it may be difficult to adapt to real-time changes in system dynamics under constraints.Comprehensive simulations assessed both frameworks,emphasizing performance metrics such as disturbance rejection,response to load changes,and resilience to uncertainties.The results show that both MPC and ABC-PID methods effectively achieved accurate voltage regulation;however,MPC excelled in controlling overshoot and settling time—recording 0.0%and 0.25 s,respectively.This demonstrates greater robustness compared to conventional control methods that optimize PID parameters based on performance criteria derived from actual system behavior,which exhibited settling times and overshoots exceeding 0.41 s and 5.0%,respectively.The controllers were implemented using MATLAB/Simulink software,indicating a significant advancement for power plant engineers pursuing state-of-the-art automatic voltage regulations.展开更多
The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to indus...The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to industrial robots.Particle Swarm Optimization may frequently suffer from local optima and inaccuracies in identifying the geometric parameters,which are necessary for applications requiring high-accuracy performances.The proposed approach integrates pheromone-based learning of ACO with the D-H method of developing an error model;hence,the global search effectiveness together with the convergence accuracy is further improved.Comparison studies of the hybrid PSO-ACO algorithm show higher precision and effectiveness in the optimization of geometric error parameters compared to the traditional methods.This is a remarkable reduction of localization errors,thus yielding accuracy and reliability in industrial robotic systems,as the results show.This approach improves performance in those applications that demand high geometric calibration by reducing the geometric error.The paper provides an overview of input for developing robotics and automation,giving importance to precision in industrial engineering.The proposed hybrid methodology is a good way to enhance the working accuracy and effectiveness of industrial robots and shall enable their wide application to complex tasks that require a high degree of accuracy.展开更多
Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in s...Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in spinal cord injury.Previous studies have shown that microglia can promote neuronal survival by phagocytosing dead cells and debris and by releasing neuroprotective and anti-inflammatory factors.However,excessive activation of microglia can lead to persistent inflammation and contribute to the formation of glial scars,which hinder axonal regeneration.Despite this,the precise role and mechanisms of microglia during the acute phase of spinal cord injury remain controversial and poorly understood.To elucidate the role of microglia in spinal cord injury,we employed the colony-stimulating factor 1 receptor inhibitor PLX5622 to deplete microglia.We observed that sustained depletion of microglia resulted in an expansion of the lesion area,downregulation of brain-derived neurotrophic factor,and impaired functional recovery after spinal cord injury.Next,we generated a transgenic mouse line with conditional overexpression of brain-derived neurotrophic factor specifically in microglia.We found that brain-derived neurotrophic factor overexpression in microglia increased angiogenesis and blood flow following spinal cord injury and facilitated the recovery of hindlimb motor function.Additionally,brain-derived neurotrophic factor overexpression in microglia reduced inflammation and neuronal apoptosis during the acute phase of spinal cord injury.Furthermore,through using specific transgenic mouse lines,TMEM119,and the colony-stimulating factor 1 receptor inhibitor PLX73086,we demonstrated that the neuroprotective effects were predominantly due to brain-derived neurotrophic factor overexpression in microglia rather than macrophages.In conclusion,our findings suggest the critical role of microglia in the formation of protective glial scars.Depleting microglia is detrimental to recovery of spinal cord injury,whereas targeting brain-derived neurotrophic factor overexpression in microglia represents a promising and novel therapeutic strategy to enhance motor function recovery in patients with spinal cord injury.展开更多
In the eighteenth and nineteenth centuries,ornithology,based on shooting and skin collection,was regarded as an unsuitable pursuit for women.Simultaneously,colonial expansion was a dominantly masculine enterprise.From...In the eighteenth and nineteenth centuries,ornithology,based on shooting and skin collection,was regarded as an unsuitable pursuit for women.Simultaneously,colonial expansion was a dominantly masculine enterprise.From postcolonial and gendered perspectives,we can rediscover severely marginalized and overshadowed roles of women within the network of colonial ornithology,a particularly masculine and patriarchal branch of imperial science.This paper highlights the contributions of three skilled women artists:Sarah Stone,Elizabeth Gwillim,and Elizabeth Gould.As embodiments of the Victorian ideal of the"angel in the house",these women also functioned as metaphorical angels within colonial ornithology.They provided unwavering support to the male-dominated scientific and imperial endeavors,which,in turn,enabled their travel to colonial territories and access to exotic avifauna.Their work holds enduring value in both scientific and artistic contexts,while simultaneously revealing women's entanglement in and contribution to the imperial agenda.Beyond illustration,women also engaged in observation,documentation,collection,and trade of birds in colonial contexts,with some even commemorated in bird nomenclature.展开更多
In this paper,a fusion model based on a long short-term memory(LSTM)neural network and enhanced search ant colony optimization(ENSACO)is proposed to predict the power degradation trend of proton exchange membrane fuel...In this paper,a fusion model based on a long short-term memory(LSTM)neural network and enhanced search ant colony optimization(ENSACO)is proposed to predict the power degradation trend of proton exchange membrane fuel cells(PEMFC).Firstly,the Shapley additive explanations(SHAP)value method is used to select external characteristic parameters with high contributions as inputs for the data-driven approach.Next,a novel swarm optimization algorithm,the enhanced search ant colony optimization,is proposed.This algorithm improves the ant colony optimization(ACO)algorithm based on a reinforcement factor to avoid premature convergence and accelerate the convergence speed.Comparative experiments are set up to compare the performance differences between particle swarm optimization(PSO),ACO,and ENSACO.Finally,a data-driven method based on ENSACO-LSTM is proposed to predict the power degradation trend of PEMFCs.And actual aging data is used to validate the method.The results show that,within a limited number of iterations,the optimization capability of ENSACO is significantly stronger than that of PSO and ACO.Additionally,the prediction accuracy of the ENSACO-LSTM method is greatly improved,with an average increase of approximately 50.58%compared to LSTM,PSO-LSTM,and ACO-LSTM.展开更多
Security is the cor nerstone of a country's peace and stability and the prerequisite for its survival and development.All countries around the world regard security as their top priority.Since most Asian countries...Security is the cor nerstone of a country's peace and stability and the prerequisite for its survival and development.All countries around the world regard security as their top priority.Since most Asian countries suffered from colonial aggression and plundering for a long time in history,they as a whole attach special importance to national security.展开更多
SNAPSHOTS OF NOTABLE BOOKS ON AFRICA Dress Cultures in Zambia By KAREN TRANBERG HANSEN Cambridge University Press The author draws on more than 50 years of research and deep regional expertise to present a vivid and e...SNAPSHOTS OF NOTABLE BOOKS ON AFRICA Dress Cultures in Zambia By KAREN TRANBERG HANSEN Cambridge University Press The author draws on more than 50 years of research and deep regional expertise to present a vivid and engaging history of dress in Zambia from the late colonial era to the present.展开更多
Since it first appeared in 2022,the phenomenon referred to as Colony Collapse Disorder(CCD)has affected several regions of Morocco to varying degrees.In order to assess the possible impact of pesticides on the appeara...Since it first appeared in 2022,the phenomenon referred to as Colony Collapse Disorder(CCD)has affected several regions of Morocco to varying degrees.In order to assess the possible impact of pesticides on the appearance of this syndrome,we conducted a study aimed at evaluating the impact of pesticide use on the emergence of this syndrome through a year-long survey involving 160 beekeepers in the Beni Mellal–Khenifra Region(BKR)who also experienced an unprecedented desertion of hives during the same period.The majority of surveyed beekeepers practice mixed(45%)or migratory beekeeping(42%)and provide supplementary feeding(83.75%)to support their bees.Nearly 37.5%of the hives are located near crops treated with pesticides,exposing the bees to these chemicals.The results showed that the majority of beekeepers reported a cessation of queen laying(74.38%),high mortality rates among worker bees(81.25%),drones(65.63%),and queens(61.88%).Abnormal behaviors such as immobility with trembling(42.50%),reduced flights(47.50%),and disoriented navigation(28.75%)were also observed.Correlation analyses indicate that proximity to treated crops significantly increases the risk of queen laying cessation(Odds Ratio 6.0)and a reduction in waggle dances(Odds Ratio 2.41).Extended foraging flights show a borderline statistical significance(Odds Ratio 2.33),suggesting a disruption of natural food sources.These results highlight the potential impact of pesticides on colony health and bee behavior,pointing out the need to adapt beekeeping practices and implement protective measures against pesticides.展开更多
The genus Selenastrum comprises common coccoid green algae found in diverse habitats worldwide.This genus has a complex taxonomic history,but recent applications of molecular phylogenetic methods have removed some mem...The genus Selenastrum comprises common coccoid green algae found in diverse habitats worldwide.This genus has a complex taxonomic history,but recent applications of molecular phylogenetic methods have removed some members with similar morphologies from Selenastrum and established new genera.However,due to the lack of available molecular sequences and isolates,the species diversity of the genus has not been fully explored.We conducted a detailed examination of the taxonomy of genus Selenastrum based on 11 new strains collected from China.The multi-disciplinary study utilized morphology,ultrastructure,and phylogeny based on multiple molecular markers,and ITS-2 secondary structure.All the included strains of genus Selenastrum were clustered into two distinct clades.The members of one clade were similar morphologically to the type species Selenastrum bibraianum,whereas the strains of the other clade had distinctly different colony structures.Based on the latter clade’s larger colony cell numbers and independent phylogenetic position,we proposed that it as a new species of the genus Selenastrum,namely Selenastrum densum sp.nov.Additional taxa sampling and molecular data will help to discover additional new species and clarify the validity of morphological taxonomic characteristics within the genus Selenastrum.展开更多
Tick studies in Malaysia have experienced a dynamic evolution characterized by periods of growth,stagnation,and the potential for revival.Beginning during the colonial era in the early 1900s,tick studies were primaril...Tick studies in Malaysia have experienced a dynamic evolution characterized by periods of growth,stagnation,and the potential for revival.Beginning during the colonial era in the early 1900s,tick studies were primarily conducted by European scientists and curators,establishing the foundation for tick taxonomy in the region.Pioneering works by George Henry Falknier Nuttall and Cecil Warburton introduced several new tick species,including Haemaphysalis(H.)calva,H.mjoebergi,H.vidua and H.wellingtoni[1].However,some records from this period are now considered doubtful,for instance Amblyomma(A.)breviscutatum,A.clypeolatum and A.integrum.The 1929 description of Ornithodoros batuensis by Stanley Hirst[2]marked the first documentation of a soft tick species in Malaysia,setting the stage for subsequent research endeavours.The Golden Age of tick studies(early 1950s-late 1980s)in Malaysia saw a surge in tick research activities.展开更多
MADAGASCAR Colonial-Era Relics Reclaimed Madagascar has officially received colonial-era relics from France,marking a historic moment of remembrance and reconciliation.At a ceremony in Antananarivo on 2 September,thre...MADAGASCAR Colonial-Era Relics Reclaimed Madagascar has officially received colonial-era relics from France,marking a historic moment of remembrance and reconciliation.At a ceremony in Antananarivo on 2 September,three skulls of the Sakalava ethnic group were welcomed home after 128 years in France.One skull is believed to belong to King Toera.展开更多
African Lions.By GIGI ROMANO.Independently Published.In the book,Gigi Romano delivers an electrifying and deeply insightful chronicle of football’s evolution across Africa.Tracing its roots from the colonial era to t...African Lions.By GIGI ROMANO.Independently Published.In the book,Gigi Romano delivers an electrifying and deeply insightful chronicle of football’s evolution across Africa.Tracing its roots from the colonial era to the present day,this captivating narrative reveals how football transformed from a pastime introduced by foreign powers into a deeply embedded cultural force and source of immense national pride.展开更多
The Internet of Things(IoT)has emerged as an important future technology.IoT-Fog is a new computing paradigm that processes IoT data on servers close to the source of the data.In IoT-Fog computing,resource allocation ...The Internet of Things(IoT)has emerged as an important future technology.IoT-Fog is a new computing paradigm that processes IoT data on servers close to the source of the data.In IoT-Fog computing,resource allocation and independent task scheduling aim to deliver short response time services demanded by the IoT devices and performed by fog servers.The heterogeneity of the IoT-Fog resources and the huge amount of data that needs to be processed by the IoT-Fog tasks make scheduling fog computing tasks a challenging problem.This study proposes an Adaptive Firefly Algorithm(AFA)for dependent task scheduling in IoT-Fog computing.The proposed AFA is a modified version of the standard Firefly Algorithm(FA),considering the execution times of the submitted tasks,the impact of synchronization requirements,and the communication time between dependent tasks.As IoT-Fog computing depends mainly on distributed fog node servers that receive tasks in a dynamic manner,tackling the communications and synchronization issues between dependent tasks is becoming a challenging problem.The proposed AFA aims to address the dynamic nature of IoT-Fog computing environments.The proposed AFA mechanism considers a dynamic light absorption coefficient to control the decrease in attractiveness over iterations.The proposed AFA mechanism performance was benchmarked against the standard Firefly Algorithm(FA),Puma Optimizer(PO),Genetic Algorithm(GA),and Ant Colony Optimization(ACO)through simulations under light,typical,and heavy workload scenarios.In heavy workloads,the proposed AFA mechanism obtained the shortest average execution time,968.98 ms compared to 970.96,1352.87,1247.28,and 1773.62 of FA,PO,GA,and ACO,respectively.The simulation results demonstrate the proposed AFA’s ability to rapidly converge to optimal solutions,emphasizing its adaptability and efficiency in typical and heavy workloads.展开更多
Evacuation strategies play a crucial role in mitigating human casualties from geohazards.While evacuation simulations have been widely used to investigate crowd behavior in response to disasters such as fires and eart...Evacuation strategies play a crucial role in mitigating human casualties from geohazards.While evacuation simulations have been widely used to investigate crowd behavior in response to disasters such as fires and earthquakes,their application to investigating crowd behavior in response to geohazards in mountainous areas has been limited.In this study,a framework was developed for simulating and optimizing evacuation strategies in response to geohazards in mountainous areas that considers the behavioral characteristics of residents.First,a simulation scenario is constructed by analyzing satellite imagery of the region of interest to identify and classify various geographic features.Characteristic parameters are then embedded into a hybrid algorithm that combines the ant colony system algorithm with a social force model to simulate realistic evacuation scenarios that reflect crowd behavior during emergencies.Based on the results of numerical simulations,the existing configuration of shelter locations are optimized to address the chaos and congestion resulting from crowd behavior.As a case study,the proposed framework was applied to constructing geohazard scenarios for a community in the Longmen Mountains area of China and conducting numerical simulations to optimize the evacuation strategy.The results show that the optimized strategies helped facilitate the safe evacuation of residents.The proposed framework represents a multidisciplinary approach to developing evacuation strategies in response to geohazards in mountainous areas while considering crowd behavior.This research has practical implications for guiding public evacuations in mountain communities under the backdrop of geohazards and provides innovative solutions for crowd evacuations in similar scenarios.展开更多
Africa’s Buildings:Architecture and the Displacement of Cultural Heritage By ITOHAN I.OSAYIMWESE Princeton University Press This book is a groundbreaking history that exposes the systematic looting of Africa’s archi...Africa’s Buildings:Architecture and the Displacement of Cultural Heritage By ITOHAN I.OSAYIMWESE Princeton University Press This book is a groundbreaking history that exposes the systematic looting of Africa’s architectural heritage by Western collectors,museums,and colonial officials.展开更多
Nobel Prize winner Doris Lessing is a renowned writer in the contemporary British literary scene.Her debut novel The Grass is Singing is based on a case in which a black manservant kills a white mistress who is poor a...Nobel Prize winner Doris Lessing is a renowned writer in the contemporary British literary scene.Her debut novel The Grass is Singing is based on a case in which a black manservant kills a white mistress who is poor and mentally unbalanced.Doris Lessing arranges a tangible form of perception for the expression of the colonial discourse in the work by seeking the relationship between spatial structure and the writer’s value.This paper focuses on the spatial writing in The Grass is Singing and analyses it in depth with reference to the spatial critical theories of Henri Lefebvre and Michel Foucault.The oppressed and enslaved characters in the novel are analysed from three perspectives:physical space,social space and mental space respectively to explore how power oppression is made visible through space and the writer’s critique of colonial relations and racial discrimination as well as unequal gender relations.展开更多
In natural ecosystems,the timely abscission of seeds in wild plants is a crucial adaptive trait that contributes to reproductive success,population renewal,and colony expansion(Thurber et al.2010).In contrast,the tend...In natural ecosystems,the timely abscission of seeds in wild plants is a crucial adaptive trait that contributes to reproductive success,population renewal,and colony expansion(Thurber et al.2010).In contrast,the tendency for high seed shattering in domesticated crops,such as rice,not only reduces paddy yield but also complicates mechanized harvesting.展开更多
Despite the widespread use of Decision trees (DT) across various applications, their performance tends to suffer when dealing with imbalanced datasets, where the distribution of certain classes significantly outweighs...Despite the widespread use of Decision trees (DT) across various applications, their performance tends to suffer when dealing with imbalanced datasets, where the distribution of certain classes significantly outweighs others. Cost-sensitive learning is a strategy to solve this problem, and several cost-sensitive DT algorithms have been proposed to date. However, existing algorithms, which are heuristic, tried to greedily select either a better splitting point or feature node, leading to local optima for tree nodes and ignoring the cost of the whole tree. In addition, determination of the costs is difficult and often requires domain expertise. This study proposes a DT for imbalanced data, called Swarm-based Cost-sensitive DT (SCDT), using the cost-sensitive learning strategy and an enhanced swarm-based algorithm. The DT is encoded using a hybrid individual representation. A hybrid artificial bee colony approach is designed to optimize rules, considering specified costs in an F-Measure-based fitness function. Experimental results using datasets compared with state-of-the-art DT algorithms show that the SCDT method achieved the highest performance on most datasets. Moreover, SCDT also excels in other critical performance metrics, such as recall, precision, F1-score, and AUC, with notable results with average values of 83%, 87.3%, 85%, and 80.7%, respectively.展开更多
Natural Language Processing(NLP)has become essential in text classification,sentiment analysis,machine translation,and speech recognition applications.As these tasks become complex,traditionalmachine learning and deep...Natural Language Processing(NLP)has become essential in text classification,sentiment analysis,machine translation,and speech recognition applications.As these tasks become complex,traditionalmachine learning and deep learning models encounter challenges with optimization,parameter tuning,and handling large-scale,highdimensional data.Bio-inspired algorithms,which mimic natural processes,offer robust optimization capabilities that can enhance NLP performance by improving feature selection,optimizing model parameters,and integrating adaptive learning mechanisms.This review explores the state-of-the-art applications of bio-inspired algorithms—such as Genetic Algorithms(GA),Particle Swarm Optimization(PSO),and Ant Colony Optimization(ACO)—across core NLP tasks.We analyze their comparative advantages,discuss their integration with neural network models,and address computational and scalability limitations.Through a synthesis of existing research,this paper highlights the unique strengths and current challenges of bio-inspired approaches in NLP,offering insights into hybrid models and lightweight,resource-efficient adaptations for real-time processing.Finally,we outline future research directions that emphasize the development of scalable,effective bio-inspired methods adaptable to evolving data environments.展开更多
文摘Fluctuating voltage levels in power grids necessitate automatic voltage regulators(AVRs)to ensure stability.This study examined the modeling and control of AVR in hydroelectric power plants using model predictive control(MPC),which utilizes an extensive mathe-matical model of the voltage regulation system to optimize the control actions over a defined prediction horizon.This predictive feature enables MPC to minimize voltage deviations while accounting for operational constraints,thereby improving stability and performance under dynamic conditions.Thefindings were compared with those derived from an optimal proportional integral derivative(PID)con-troller designed using the artificial bee colony(ABC)algorithm.Although the ABC-PID method adjusts the PID parameters based on historical data,it may be difficult to adapt to real-time changes in system dynamics under constraints.Comprehensive simulations assessed both frameworks,emphasizing performance metrics such as disturbance rejection,response to load changes,and resilience to uncertainties.The results show that both MPC and ABC-PID methods effectively achieved accurate voltage regulation;however,MPC excelled in controlling overshoot and settling time—recording 0.0%and 0.25 s,respectively.This demonstrates greater robustness compared to conventional control methods that optimize PID parameters based on performance criteria derived from actual system behavior,which exhibited settling times and overshoots exceeding 0.41 s and 5.0%,respectively.The controllers were implemented using MATLAB/Simulink software,indicating a significant advancement for power plant engineers pursuing state-of-the-art automatic voltage regulations.
文摘The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to industrial robots.Particle Swarm Optimization may frequently suffer from local optima and inaccuracies in identifying the geometric parameters,which are necessary for applications requiring high-accuracy performances.The proposed approach integrates pheromone-based learning of ACO with the D-H method of developing an error model;hence,the global search effectiveness together with the convergence accuracy is further improved.Comparison studies of the hybrid PSO-ACO algorithm show higher precision and effectiveness in the optimization of geometric error parameters compared to the traditional methods.This is a remarkable reduction of localization errors,thus yielding accuracy and reliability in industrial robotic systems,as the results show.This approach improves performance in those applications that demand high geometric calibration by reducing the geometric error.The paper provides an overview of input for developing robotics and automation,giving importance to precision in industrial engineering.The proposed hybrid methodology is a good way to enhance the working accuracy and effectiveness of industrial robots and shall enable their wide application to complex tasks that require a high degree of accuracy.
基金supported by the National Natural Science Foundation of China,Nos.82072165 and 82272256(both to XM)the Key Project of Xiangyang Central Hospital,No.2023YZ03(to RM)。
文摘Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in spinal cord injury.Previous studies have shown that microglia can promote neuronal survival by phagocytosing dead cells and debris and by releasing neuroprotective and anti-inflammatory factors.However,excessive activation of microglia can lead to persistent inflammation and contribute to the formation of glial scars,which hinder axonal regeneration.Despite this,the precise role and mechanisms of microglia during the acute phase of spinal cord injury remain controversial and poorly understood.To elucidate the role of microglia in spinal cord injury,we employed the colony-stimulating factor 1 receptor inhibitor PLX5622 to deplete microglia.We observed that sustained depletion of microglia resulted in an expansion of the lesion area,downregulation of brain-derived neurotrophic factor,and impaired functional recovery after spinal cord injury.Next,we generated a transgenic mouse line with conditional overexpression of brain-derived neurotrophic factor specifically in microglia.We found that brain-derived neurotrophic factor overexpression in microglia increased angiogenesis and blood flow following spinal cord injury and facilitated the recovery of hindlimb motor function.Additionally,brain-derived neurotrophic factor overexpression in microglia reduced inflammation and neuronal apoptosis during the acute phase of spinal cord injury.Furthermore,through using specific transgenic mouse lines,TMEM119,and the colony-stimulating factor 1 receptor inhibitor PLX73086,we demonstrated that the neuroprotective effects were predominantly due to brain-derived neurotrophic factor overexpression in microglia rather than macrophages.In conclusion,our findings suggest the critical role of microglia in the formation of protective glial scars.Depleting microglia is detrimental to recovery of spinal cord injury,whereas targeting brain-derived neurotrophic factor overexpression in microglia represents a promising and novel therapeutic strategy to enhance motor function recovery in patients with spinal cord injury.
文摘In the eighteenth and nineteenth centuries,ornithology,based on shooting and skin collection,was regarded as an unsuitable pursuit for women.Simultaneously,colonial expansion was a dominantly masculine enterprise.From postcolonial and gendered perspectives,we can rediscover severely marginalized and overshadowed roles of women within the network of colonial ornithology,a particularly masculine and patriarchal branch of imperial science.This paper highlights the contributions of three skilled women artists:Sarah Stone,Elizabeth Gwillim,and Elizabeth Gould.As embodiments of the Victorian ideal of the"angel in the house",these women also functioned as metaphorical angels within colonial ornithology.They provided unwavering support to the male-dominated scientific and imperial endeavors,which,in turn,enabled their travel to colonial territories and access to exotic avifauna.Their work holds enduring value in both scientific and artistic contexts,while simultaneously revealing women's entanglement in and contribution to the imperial agenda.Beyond illustration,women also engaged in observation,documentation,collection,and trade of birds in colonial contexts,with some even commemorated in bird nomenclature.
基金Supported by the Major Science and Technology Project of Jilin Province(20220301010GX)the International Scientific and Technological Cooperation(20240402071GH).
文摘In this paper,a fusion model based on a long short-term memory(LSTM)neural network and enhanced search ant colony optimization(ENSACO)is proposed to predict the power degradation trend of proton exchange membrane fuel cells(PEMFC).Firstly,the Shapley additive explanations(SHAP)value method is used to select external characteristic parameters with high contributions as inputs for the data-driven approach.Next,a novel swarm optimization algorithm,the enhanced search ant colony optimization,is proposed.This algorithm improves the ant colony optimization(ACO)algorithm based on a reinforcement factor to avoid premature convergence and accelerate the convergence speed.Comparative experiments are set up to compare the performance differences between particle swarm optimization(PSO),ACO,and ENSACO.Finally,a data-driven method based on ENSACO-LSTM is proposed to predict the power degradation trend of PEMFCs.And actual aging data is used to validate the method.The results show that,within a limited number of iterations,the optimization capability of ENSACO is significantly stronger than that of PSO and ACO.Additionally,the prediction accuracy of the ENSACO-LSTM method is greatly improved,with an average increase of approximately 50.58%compared to LSTM,PSO-LSTM,and ACO-LSTM.
文摘Security is the cor nerstone of a country's peace and stability and the prerequisite for its survival and development.All countries around the world regard security as their top priority.Since most Asian countries suffered from colonial aggression and plundering for a long time in history,they as a whole attach special importance to national security.
文摘SNAPSHOTS OF NOTABLE BOOKS ON AFRICA Dress Cultures in Zambia By KAREN TRANBERG HANSEN Cambridge University Press The author draws on more than 50 years of research and deep regional expertise to present a vivid and engaging history of dress in Zambia from the late colonial era to the present.
文摘Since it first appeared in 2022,the phenomenon referred to as Colony Collapse Disorder(CCD)has affected several regions of Morocco to varying degrees.In order to assess the possible impact of pesticides on the appearance of this syndrome,we conducted a study aimed at evaluating the impact of pesticide use on the emergence of this syndrome through a year-long survey involving 160 beekeepers in the Beni Mellal–Khenifra Region(BKR)who also experienced an unprecedented desertion of hives during the same period.The majority of surveyed beekeepers practice mixed(45%)or migratory beekeeping(42%)and provide supplementary feeding(83.75%)to support their bees.Nearly 37.5%of the hives are located near crops treated with pesticides,exposing the bees to these chemicals.The results showed that the majority of beekeepers reported a cessation of queen laying(74.38%),high mortality rates among worker bees(81.25%),drones(65.63%),and queens(61.88%).Abnormal behaviors such as immobility with trembling(42.50%),reduced flights(47.50%),and disoriented navigation(28.75%)were also observed.Correlation analyses indicate that proximity to treated crops significantly increases the risk of queen laying cessation(Odds Ratio 6.0)and a reduction in waggle dances(Odds Ratio 2.41).Extended foraging flights show a borderline statistical significance(Odds Ratio 2.33),suggesting a disruption of natural food sources.These results highlight the potential impact of pesticides on colony health and bee behavior,pointing out the need to adapt beekeeping practices and implement protective measures against pesticides.
基金Supported by the National Natural Science Foundation of China(Nos.32370219,32270220,U22A20445)the Fundamental Research Program of Shanxi Province(No.202303021221082)+2 种基金the Open Project Program of Xinghuacun College of Shanxi University(Shanxi Institute of Brewing Technology and Industry)(No.XCSXU-KF-202320)the Yuncheng Salt Lake Protection and Utilization Research Institute of Shanxi,China(No.YHYJ-2023003)the Program for Young Scholar Talents of Wenying in Shanxi University。
文摘The genus Selenastrum comprises common coccoid green algae found in diverse habitats worldwide.This genus has a complex taxonomic history,but recent applications of molecular phylogenetic methods have removed some members with similar morphologies from Selenastrum and established new genera.However,due to the lack of available molecular sequences and isolates,the species diversity of the genus has not been fully explored.We conducted a detailed examination of the taxonomy of genus Selenastrum based on 11 new strains collected from China.The multi-disciplinary study utilized morphology,ultrastructure,and phylogeny based on multiple molecular markers,and ITS-2 secondary structure.All the included strains of genus Selenastrum were clustered into two distinct clades.The members of one clade were similar morphologically to the type species Selenastrum bibraianum,whereas the strains of the other clade had distinctly different colony structures.Based on the latter clade’s larger colony cell numbers and independent phylogenetic position,we proposed that it as a new species of the genus Selenastrum,namely Selenastrum densum sp.nov.Additional taxa sampling and molecular data will help to discover additional new species and clarify the validity of morphological taxonomic characteristics within the genus Selenastrum.
基金supported by the Higher Institution Centre of Excellence(HICoE)program(MO002-2019&TIDREC-2023)funded by the Bernhard Nocht Institute for Tropical Medicine,Hamburg,Germany[100-TNCPI/INT 16/6/2(005/2020)].
文摘Tick studies in Malaysia have experienced a dynamic evolution characterized by periods of growth,stagnation,and the potential for revival.Beginning during the colonial era in the early 1900s,tick studies were primarily conducted by European scientists and curators,establishing the foundation for tick taxonomy in the region.Pioneering works by George Henry Falknier Nuttall and Cecil Warburton introduced several new tick species,including Haemaphysalis(H.)calva,H.mjoebergi,H.vidua and H.wellingtoni[1].However,some records from this period are now considered doubtful,for instance Amblyomma(A.)breviscutatum,A.clypeolatum and A.integrum.The 1929 description of Ornithodoros batuensis by Stanley Hirst[2]marked the first documentation of a soft tick species in Malaysia,setting the stage for subsequent research endeavours.The Golden Age of tick studies(early 1950s-late 1980s)in Malaysia saw a surge in tick research activities.
文摘MADAGASCAR Colonial-Era Relics Reclaimed Madagascar has officially received colonial-era relics from France,marking a historic moment of remembrance and reconciliation.At a ceremony in Antananarivo on 2 September,three skulls of the Sakalava ethnic group were welcomed home after 128 years in France.One skull is believed to belong to King Toera.
文摘African Lions.By GIGI ROMANO.Independently Published.In the book,Gigi Romano delivers an electrifying and deeply insightful chronicle of football’s evolution across Africa.Tracing its roots from the colonial era to the present day,this captivating narrative reveals how football transformed from a pastime introduced by foreign powers into a deeply embedded cultural force and source of immense national pride.
基金the Deanship of Graduate Studies and Scientific Research at Najran University for funding this work under the Easy Funding Program grant code(NU/EFP/SERC/13/166).
文摘The Internet of Things(IoT)has emerged as an important future technology.IoT-Fog is a new computing paradigm that processes IoT data on servers close to the source of the data.In IoT-Fog computing,resource allocation and independent task scheduling aim to deliver short response time services demanded by the IoT devices and performed by fog servers.The heterogeneity of the IoT-Fog resources and the huge amount of data that needs to be processed by the IoT-Fog tasks make scheduling fog computing tasks a challenging problem.This study proposes an Adaptive Firefly Algorithm(AFA)for dependent task scheduling in IoT-Fog computing.The proposed AFA is a modified version of the standard Firefly Algorithm(FA),considering the execution times of the submitted tasks,the impact of synchronization requirements,and the communication time between dependent tasks.As IoT-Fog computing depends mainly on distributed fog node servers that receive tasks in a dynamic manner,tackling the communications and synchronization issues between dependent tasks is becoming a challenging problem.The proposed AFA aims to address the dynamic nature of IoT-Fog computing environments.The proposed AFA mechanism considers a dynamic light absorption coefficient to control the decrease in attractiveness over iterations.The proposed AFA mechanism performance was benchmarked against the standard Firefly Algorithm(FA),Puma Optimizer(PO),Genetic Algorithm(GA),and Ant Colony Optimization(ACO)through simulations under light,typical,and heavy workload scenarios.In heavy workloads,the proposed AFA mechanism obtained the shortest average execution time,968.98 ms compared to 970.96,1352.87,1247.28,and 1773.62 of FA,PO,GA,and ACO,respectively.The simulation results demonstrate the proposed AFA’s ability to rapidly converge to optimal solutions,emphasizing its adaptability and efficiency in typical and heavy workloads.
基金supported by the National Natural Science Foundation of China(Grant No.42471225)the Sichuan Science and Technology Program(Grant No.2022JDJQ0015)。
文摘Evacuation strategies play a crucial role in mitigating human casualties from geohazards.While evacuation simulations have been widely used to investigate crowd behavior in response to disasters such as fires and earthquakes,their application to investigating crowd behavior in response to geohazards in mountainous areas has been limited.In this study,a framework was developed for simulating and optimizing evacuation strategies in response to geohazards in mountainous areas that considers the behavioral characteristics of residents.First,a simulation scenario is constructed by analyzing satellite imagery of the region of interest to identify and classify various geographic features.Characteristic parameters are then embedded into a hybrid algorithm that combines the ant colony system algorithm with a social force model to simulate realistic evacuation scenarios that reflect crowd behavior during emergencies.Based on the results of numerical simulations,the existing configuration of shelter locations are optimized to address the chaos and congestion resulting from crowd behavior.As a case study,the proposed framework was applied to constructing geohazard scenarios for a community in the Longmen Mountains area of China and conducting numerical simulations to optimize the evacuation strategy.The results show that the optimized strategies helped facilitate the safe evacuation of residents.The proposed framework represents a multidisciplinary approach to developing evacuation strategies in response to geohazards in mountainous areas while considering crowd behavior.This research has practical implications for guiding public evacuations in mountain communities under the backdrop of geohazards and provides innovative solutions for crowd evacuations in similar scenarios.
文摘Africa’s Buildings:Architecture and the Displacement of Cultural Heritage By ITOHAN I.OSAYIMWESE Princeton University Press This book is a groundbreaking history that exposes the systematic looting of Africa’s architectural heritage by Western collectors,museums,and colonial officials.
文摘Nobel Prize winner Doris Lessing is a renowned writer in the contemporary British literary scene.Her debut novel The Grass is Singing is based on a case in which a black manservant kills a white mistress who is poor and mentally unbalanced.Doris Lessing arranges a tangible form of perception for the expression of the colonial discourse in the work by seeking the relationship between spatial structure and the writer’s value.This paper focuses on the spatial writing in The Grass is Singing and analyses it in depth with reference to the spatial critical theories of Henri Lefebvre and Michel Foucault.The oppressed and enslaved characters in the novel are analysed from three perspectives:physical space,social space and mental space respectively to explore how power oppression is made visible through space and the writer’s critique of colonial relations and racial discrimination as well as unequal gender relations.
基金supported by the National Natural Science Foundation of China(32372118 and 32188102)the Qian Qian Academician Workstation,China+3 种基金the Specific Research Fund of the Innovation Platform for Academicians of Hainan Province,China(YSPTZX202303)the Nanfan Special Project,Chinese Academy of Agricultural Sciences(ZDXM2315)the Chinese Academy of Agricultural Sciences Talent Plan-Outstanding Young Talentthe Zhejiang Province’s High-level Talent Special Support Plan-Young Talent,China。
文摘In natural ecosystems,the timely abscission of seeds in wild plants is a crucial adaptive trait that contributes to reproductive success,population renewal,and colony expansion(Thurber et al.2010).In contrast,the tendency for high seed shattering in domesticated crops,such as rice,not only reduces paddy yield but also complicates mechanized harvesting.
文摘Despite the widespread use of Decision trees (DT) across various applications, their performance tends to suffer when dealing with imbalanced datasets, where the distribution of certain classes significantly outweighs others. Cost-sensitive learning is a strategy to solve this problem, and several cost-sensitive DT algorithms have been proposed to date. However, existing algorithms, which are heuristic, tried to greedily select either a better splitting point or feature node, leading to local optima for tree nodes and ignoring the cost of the whole tree. In addition, determination of the costs is difficult and often requires domain expertise. This study proposes a DT for imbalanced data, called Swarm-based Cost-sensitive DT (SCDT), using the cost-sensitive learning strategy and an enhanced swarm-based algorithm. The DT is encoded using a hybrid individual representation. A hybrid artificial bee colony approach is designed to optimize rules, considering specified costs in an F-Measure-based fitness function. Experimental results using datasets compared with state-of-the-art DT algorithms show that the SCDT method achieved the highest performance on most datasets. Moreover, SCDT also excels in other critical performance metrics, such as recall, precision, F1-score, and AUC, with notable results with average values of 83%, 87.3%, 85%, and 80.7%, respectively.
基金supported by AIT Laboratory,FPT University,Danang Campus,Vietnam,2024.
文摘Natural Language Processing(NLP)has become essential in text classification,sentiment analysis,machine translation,and speech recognition applications.As these tasks become complex,traditionalmachine learning and deep learning models encounter challenges with optimization,parameter tuning,and handling large-scale,highdimensional data.Bio-inspired algorithms,which mimic natural processes,offer robust optimization capabilities that can enhance NLP performance by improving feature selection,optimizing model parameters,and integrating adaptive learning mechanisms.This review explores the state-of-the-art applications of bio-inspired algorithms—such as Genetic Algorithms(GA),Particle Swarm Optimization(PSO),and Ant Colony Optimization(ACO)—across core NLP tasks.We analyze their comparative advantages,discuss their integration with neural network models,and address computational and scalability limitations.Through a synthesis of existing research,this paper highlights the unique strengths and current challenges of bio-inspired approaches in NLP,offering insights into hybrid models and lightweight,resource-efficient adaptations for real-time processing.Finally,we outline future research directions that emphasize the development of scalable,effective bio-inspired methods adaptable to evolving data environments.
