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
Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and...Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and biosafety concerns.In this study,we propose a high-precision automated colony extraction and separation system that combines large-field imaging and artificial intelligence(AI)to facilitate intelligent screening and localization of colonies.Firstly,a large-field imaging system was developed to capture high-resolution images of 90 mm Petri dishes,achieving a physical resolution of 13.2μm and an imaging speed of 13 frames per second.Subsequently,AI technology was employed for the automatic recognition and localiza-tion of colonies,enabling the selection of target colonies with diameters ranging from 1.9 to 2.3 mm.Next,a three-axis motion control platform was designed,accompanied by a path planning algorithm for the efficient extraction of colonies.An electronic pipette was employed for accurate colony collection.Additionally,a bacterial suspension concentration measurement module was developed,incorporating a 650 nm laser diode as the light source,achieving a measurement accuracy of 0.01 McFarland concentration(MCF).Finally,the system’s performance was validated through the preparation of an Esckerichia coli(E.coli)suspension.After 17 hours of cultivation,E.coli was extracted four times,achieving the target concentration set by the system.This work is expected to enable rapid and accurate microbial sample preparation,significantly reducing de-tection cycles and alleviating the workload of healthcare personnel.展开更多
The Lord’s Lawn:Dispatches from East Africa By J.D.BREEN Independently published The book offers a clear-eyed,often wry account of two weeks crossing Tanzania and Kenya.The author traces landscapes older than memory,...The Lord’s Lawn:Dispatches from East Africa By J.D.BREEN Independently published The book offers a clear-eyed,often wry account of two weeks crossing Tanzania and Kenya.The author traces landscapes older than memory,wildlife indifferent to human itineraries,and societies shaped as much by colonial boundaries and modern bureaucracy as by geology and climate.From Zanzibar to the Serengeti,and from Amboseli and Kilimanjaro to the Masai Mara,the essays weave together history,anthropology,politics and personal reflection without sentimentality or cynicism.Africa is not explained or simplified;it is encountered briefly and imperfectly,on its own terms.展开更多
The microstructure of high Nb-TiAl alloys was optimized by the addition of a small amount of Ta elements to further improve their properties.A series of Ti46Al1.5Cr8Nb-xTa(x=0.2,0.4,0.6,0.8,1.0,at.%)alloys were prepar...The microstructure of high Nb-TiAl alloys was optimized by the addition of a small amount of Ta elements to further improve their properties.A series of Ti46Al1.5Cr8Nb-xTa(x=0.2,0.4,0.6,0.8,1.0,at.%)alloys were prepared by vacuum arc melting.The microstructure,mechanical properties,and related influencing mechanisms were systematically investigated.The results indicate that the solidification microstructure of the Ti46Al1.5Cr8Nb-xTa alloys comprises theγ-TiAl phase,α_(2)-Ti_(3)Al phase,and B2 phase.As the Ta content increases from 0.2 at.%to 1.0 at.%,the content ofα_(2)phase and B2 phase increases,while theγphase content decreases.Among them,the B2 phase shows the most pronounced change,being significantly refined,with its content increasing from 12.49%to 21.91%.In addition,the average size of the lamellar colony decreases from 160.65 to 94.44μm.The addition of the Ta element shifts the solidification path toward lower aluminum concentrations,leading to changes in phase content.The tantalum-induced increase in the B2 phase and enhanced supercooling at the solidification front provide the basis for lamellar colony refinement.Compressive testing at room temperature reveals that the Ti46 Al1.5 Cr8 Nb0.4 Ta alloy exhibits optimal compressive properties,achieving a compressive strength of 2,434 MPa and a compressive strain of 33.1%.The improvement of its properties is attributed to a combination of lamellar colony refinement,solid solution strengthening resulting from the incorporation of Ta element,and a reduction in the c/a of theγphase.展开更多
By MAMADOU DIOUF,Seagull Books.Africa in the World’s Time.In this book,distinguished historian Mamadou Diouf repositions Africa at the centre of global historical imagination.Countering long-standing colonial narrati...By MAMADOU DIOUF,Seagull Books.Africa in the World’s Time.In this book,distinguished historian Mamadou Diouf repositions Africa at the centre of global historical imagination.Countering long-standing colonial narratives that relegated the continent to the margins,Diouf uncovers the intellectual,artistic,and cultural traditions through which Africans have continuously interpreted,debated,and rewritten their own histories.展开更多
With the increasing complexity of logistics operations,traditional static vehicle routing models are no longer sufficient.In practice,customer demands often arise dynamically,and multi-depot systems are commonly used ...With the increasing complexity of logistics operations,traditional static vehicle routing models are no longer sufficient.In practice,customer demands often arise dynamically,and multi-depot systems are commonly used to improve efficiency.This paper first introduces a vehicle routing problem with the goal of minimizing operating costs in a multi-depot environment with dynamic demand.New customers appear in the delivery process at any time and are periodically optimized according to time slices.Then,we propose a scheduling system TS-DPU based on an improved ant colony algorithm TS-ACO to solve this problem.The classical ant colony algorithm uses spatial distance to select nodes,while TS-ACO considers the impact of both temporal and spatial distance on node selection.Meanwhile,we adopt Cordeau’s Multi-Depot Vehicle Routing Problem with Time Windows(MDVRPTW)dataset to evaluate the performance of our system.According to the experimental results,TS-ACO,which considers spatial and temporal distance,is more effective than the classical ACO,which only considers spatial distance.展开更多
The Intrusion Detection System(IDS)is a security mechanism developed to observe network traffic and recognize suspicious or malicious activities.Clustering algorithms are often incorporated into IDS;however,convention...The Intrusion Detection System(IDS)is a security mechanism developed to observe network traffic and recognize suspicious or malicious activities.Clustering algorithms are often incorporated into IDS;however,conventional clustering-based methods face notable drawbacks,including poor scalability in handling high-dimensional datasets and a strong dependence of outcomes on initial conditions.To overcome the performance limitations of existing methods,this study proposes a novel quantum-inspired clustering algorithm that relies on a similarity coefficient-based quantum genetic algorithm(SC-QGA)and an improved quantum artificial bee colony algorithm hybrid K-means(IQABC-K).First,the SC-QGA algorithmis constructed based on quantum computing and integrates similarity coefficient theory to strengthen genetic diversity and feature extraction capabilities.For the subsequent clustering phase,the process based on the IQABC-K algorithm is enhanced with the core improvement of adaptive rotation gate and movement exploitation strategies to balance the exploration capabilities of global search and the exploitation capabilities of local search.Simultaneously,the acceleration of convergence toward the global optimum and a reduction in computational complexity are facilitated by means of the global optimum bootstrap strategy and a linear population reduction strategy.Through experimental evaluation with multiple algorithms and diverse performance metrics,the proposed algorithm confirms reliable accuracy on three datasets:KDD CUP99,NSL_KDD,and UNSW_NB15,achieving accuracy of 98.57%,98.81%,and 98.32%,respectively.These results affirm its potential as an effective solution for practical clustering applications.展开更多
Safeguarding modern networks from cyber intrusions has become increasingly challenging as attackers continually refine their evasion tactics.Although numerousmachine-learning-based intrusion detection systems(IDS)have...Safeguarding modern networks from cyber intrusions has become increasingly challenging as attackers continually refine their evasion tactics.Although numerousmachine-learning-based intrusion detection systems(IDS)have been developed,their effectiveness is often constrained by high dimensionality and redundant features that degrade both accuracy and efficiency.This study introduces a hybrid feature-selection framework that integrates the exploration capability of Prairie Dog Optimization(PDO)with the exploitation behavior of Ant Colony Optimization(ACO).The proposed PDO–ACO algorithm identifies a concise yet discriminative subset of features from the NSLKDD dataset and evaluates them using a Support Vector Machine(SVM)classifier.Experimental analyses reveal that the PDO–ACO model achieves superior detection accuracy of 98%while significantly lowering false alarms and computational overhead.Further validation on the CEC2017 benchmark suite confirms the robustness and adaptability of the hybrid model across diverse optimization landscapes,positioning PDO–ACO as an efficient and scalable approach for intelligent intrusion detection.展开更多
This paper presents Dual Adaptive Neural Topology(Dual ANT),a distributed dual-network metaadaptive framework that enhances ant-colony-based multi-agent coordination with online introspection,adaptive parameter contro...This paper presents Dual Adaptive Neural Topology(Dual ANT),a distributed dual-network metaadaptive framework that enhances ant-colony-based multi-agent coordination with online introspection,adaptive parameter control,and privacy-preserving interactions.This approach improves standard Ant Colony Optimization(ACO)with two lightweight neural components:a forward network that estimates swarm efficiency in real time and an inverse network that converts these descriptors into parameter adaptations.To preserve the privacy of individual trajectories in shared pheromone maps,we introduce a locally differentially private pheromone update mechanism that adds calibrated noise to each agent’s pheromone deposit while preserving the efficacy of the global pheromone signal.The resulting systemenables agents to dynamically and autonomously adapt their coordination strategies under challenging and dynamic conditions,including varying obstacle layouts,uncertain target locations,and time-varying disturbances.Extensive simulations of large grid-based search tasks demonstrated that Dual ANT achieved faster convergence,higher robustness,and improved scalability compared to advanced baselines such asMulti-StrategyACO and Hierarchical ACO.The meta-adaptive feedback loop compensates for the performance degradation caused by privacy noise and prevents premature stagnation by triggering Levy flight exploration only when necessary.展开更多
In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a ...In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a composition solution under their budget constraints.Existing studies typically evaluate satisfaction solely based on energy transmission capacity,while overlooking critical factors such as price and trustworthiness of the provider,leading to a mismatch between optimization outcomes and user needs.To address this gap,we construct a user satisfaction evaluation model for multi-user and multi-provider scenarios,systematically incorporating service price,transmission capacity,and trustworthiness into the satisfaction assessment framework.Furthermore,we propose a Budget-Aware Preference Adjustment Model that predicts users’baseline preference weights from historical data and dynamically adjusts them according to budget levels,thereby reflecting user preferences more realistically under varying budget constraints.In addition,to tackle the composition optimization problem,we develop a ReflectiveEvolutionary Large Language Model—Guided Ant Colony Optimization algorithm,which leverages the reflective evolution capability of large language models to iteratively generate and refine heuristic information that guides the search process.Experimental results demonstrate that the proposed framework effectively integrates personalized preferences with budget sensitivity,accurately predicts users’preferences,and significantly enhances their satisfaction under complex constraints.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
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
Swarm Intelligence (SI) is a collective behavior that emerges from interaction between individuals in a group. Typical SI includes fish schooling, ant foraging, bird migration, and so on. A great deal of models have b...Swarm Intelligence (SI) is a collective behavior that emerges from interaction between individuals in a group. Typical SI includes fish schooling, ant foraging, bird migration, and so on. A great deal of models have been introduced to characterize the mechanism of SI. This article reviews several typical models and classifies them into four categories: self-driven particle models, with Boids model as the primary example;pheromone communication models, including the ant colony pheromone model which serves as the foundation for ant colony optimization;leadership decision models, utilizing the hierarchical dynamics model of pigeon flock as a prime instance;empirical research models, which employ the topological rule model of starling flock as a classic model. On this basis, each type of model is elaborated upon in terms of its typical model overview, applications, and model evaluation. More specifically, multi-agent swarm control, path optimization and obstacle avoidance, formation and consensus control, trajectory tracking in the dense crowd and social networks analysis are surveyed in the application of each category, respectively. Furthermore, the more precise and effective modeling techniques for leadership decision and empirical research models are described. Limitations and potential directions for further exploration in the study of SI are presented.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
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
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Standard bacterial suspensions play a crucial role in microbiological diagnosis.Traditional prepar-ation methods,which rely heavily on manual operations,face challenges such as poor reproducibility,low ef-ficiency,and biosafety concerns.In this study,we propose a high-precision automated colony extraction and separation system that combines large-field imaging and artificial intelligence(AI)to facilitate intelligent screening and localization of colonies.Firstly,a large-field imaging system was developed to capture high-resolution images of 90 mm Petri dishes,achieving a physical resolution of 13.2μm and an imaging speed of 13 frames per second.Subsequently,AI technology was employed for the automatic recognition and localiza-tion of colonies,enabling the selection of target colonies with diameters ranging from 1.9 to 2.3 mm.Next,a three-axis motion control platform was designed,accompanied by a path planning algorithm for the efficient extraction of colonies.An electronic pipette was employed for accurate colony collection.Additionally,a bacterial suspension concentration measurement module was developed,incorporating a 650 nm laser diode as the light source,achieving a measurement accuracy of 0.01 McFarland concentration(MCF).Finally,the system’s performance was validated through the preparation of an Esckerichia coli(E.coli)suspension.After 17 hours of cultivation,E.coli was extracted four times,achieving the target concentration set by the system.This work is expected to enable rapid and accurate microbial sample preparation,significantly reducing de-tection cycles and alleviating the workload of healthcare personnel.
文摘The Lord’s Lawn:Dispatches from East Africa By J.D.BREEN Independently published The book offers a clear-eyed,often wry account of two weeks crossing Tanzania and Kenya.The author traces landscapes older than memory,wildlife indifferent to human itineraries,and societies shaped as much by colonial boundaries and modern bureaucracy as by geology and climate.From Zanzibar to the Serengeti,and from Amboseli and Kilimanjaro to the Masai Mara,the essays weave together history,anthropology,politics and personal reflection without sentimentality or cynicism.Africa is not explained or simplified;it is encountered briefly and imperfectly,on its own terms.
基金the financial support by the Major Science and Technology Achievement Transformation Project in Heilongjiang Province(No.ZC2023SH0075)the National Natural Science Foundation of China(Nos.52425401,U2441255,52474377,and 52371015)+1 种基金the Young Elite Scientists Sponsorship·Program by CAST(No.2021QNRC001)the Henan Provincial Key Research and Development&Promotion Special Program(No.251111231400)。
文摘The microstructure of high Nb-TiAl alloys was optimized by the addition of a small amount of Ta elements to further improve their properties.A series of Ti46Al1.5Cr8Nb-xTa(x=0.2,0.4,0.6,0.8,1.0,at.%)alloys were prepared by vacuum arc melting.The microstructure,mechanical properties,and related influencing mechanisms were systematically investigated.The results indicate that the solidification microstructure of the Ti46Al1.5Cr8Nb-xTa alloys comprises theγ-TiAl phase,α_(2)-Ti_(3)Al phase,and B2 phase.As the Ta content increases from 0.2 at.%to 1.0 at.%,the content ofα_(2)phase and B2 phase increases,while theγphase content decreases.Among them,the B2 phase shows the most pronounced change,being significantly refined,with its content increasing from 12.49%to 21.91%.In addition,the average size of the lamellar colony decreases from 160.65 to 94.44μm.The addition of the Ta element shifts the solidification path toward lower aluminum concentrations,leading to changes in phase content.The tantalum-induced increase in the B2 phase and enhanced supercooling at the solidification front provide the basis for lamellar colony refinement.Compressive testing at room temperature reveals that the Ti46 Al1.5 Cr8 Nb0.4 Ta alloy exhibits optimal compressive properties,achieving a compressive strength of 2,434 MPa and a compressive strain of 33.1%.The improvement of its properties is attributed to a combination of lamellar colony refinement,solid solution strengthening resulting from the incorporation of Ta element,and a reduction in the c/a of theγphase.
文摘By MAMADOU DIOUF,Seagull Books.Africa in the World’s Time.In this book,distinguished historian Mamadou Diouf repositions Africa at the centre of global historical imagination.Countering long-standing colonial narratives that relegated the continent to the margins,Diouf uncovers the intellectual,artistic,and cultural traditions through which Africans have continuously interpreted,debated,and rewritten their own histories.
基金supported by the Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology.
文摘With the increasing complexity of logistics operations,traditional static vehicle routing models are no longer sufficient.In practice,customer demands often arise dynamically,and multi-depot systems are commonly used to improve efficiency.This paper first introduces a vehicle routing problem with the goal of minimizing operating costs in a multi-depot environment with dynamic demand.New customers appear in the delivery process at any time and are periodically optimized according to time slices.Then,we propose a scheduling system TS-DPU based on an improved ant colony algorithm TS-ACO to solve this problem.The classical ant colony algorithm uses spatial distance to select nodes,while TS-ACO considers the impact of both temporal and spatial distance on node selection.Meanwhile,we adopt Cordeau’s Multi-Depot Vehicle Routing Problem with Time Windows(MDVRPTW)dataset to evaluate the performance of our system.According to the experimental results,TS-ACO,which considers spatial and temporal distance,is more effective than the classical ACO,which only considers spatial distance.
基金supported by the NSFC(Grant Nos.62176273,62271070,62441212)The Open Foundation of State Key Laboratory of Networking and Switching Technology(Beijing University of Posts and Telecommunications)under Grant SKLNST-2024-1-062025Major Project of the Natural Science Foundation of Inner Mongolia(2025ZD008).
文摘The Intrusion Detection System(IDS)is a security mechanism developed to observe network traffic and recognize suspicious or malicious activities.Clustering algorithms are often incorporated into IDS;however,conventional clustering-based methods face notable drawbacks,including poor scalability in handling high-dimensional datasets and a strong dependence of outcomes on initial conditions.To overcome the performance limitations of existing methods,this study proposes a novel quantum-inspired clustering algorithm that relies on a similarity coefficient-based quantum genetic algorithm(SC-QGA)and an improved quantum artificial bee colony algorithm hybrid K-means(IQABC-K).First,the SC-QGA algorithmis constructed based on quantum computing and integrates similarity coefficient theory to strengthen genetic diversity and feature extraction capabilities.For the subsequent clustering phase,the process based on the IQABC-K algorithm is enhanced with the core improvement of adaptive rotation gate and movement exploitation strategies to balance the exploration capabilities of global search and the exploitation capabilities of local search.Simultaneously,the acceleration of convergence toward the global optimum and a reduction in computational complexity are facilitated by means of the global optimum bootstrap strategy and a linear population reduction strategy.Through experimental evaluation with multiple algorithms and diverse performance metrics,the proposed algorithm confirms reliable accuracy on three datasets:KDD CUP99,NSL_KDD,and UNSW_NB15,achieving accuracy of 98.57%,98.81%,and 98.32%,respectively.These results affirm its potential as an effective solution for practical clustering applications.
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2026R500)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Safeguarding modern networks from cyber intrusions has become increasingly challenging as attackers continually refine their evasion tactics.Although numerousmachine-learning-based intrusion detection systems(IDS)have been developed,their effectiveness is often constrained by high dimensionality and redundant features that degrade both accuracy and efficiency.This study introduces a hybrid feature-selection framework that integrates the exploration capability of Prairie Dog Optimization(PDO)with the exploitation behavior of Ant Colony Optimization(ACO).The proposed PDO–ACO algorithm identifies a concise yet discriminative subset of features from the NSLKDD dataset and evaluates them using a Support Vector Machine(SVM)classifier.Experimental analyses reveal that the PDO–ACO model achieves superior detection accuracy of 98%while significantly lowering false alarms and computational overhead.Further validation on the CEC2017 benchmark suite confirms the robustness and adaptability of the hybrid model across diverse optimization landscapes,positioning PDO–ACO as an efficient and scalable approach for intelligent intrusion detection.
基金funded by the Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia,under project number NBU-FFR-2026-2441-02.
文摘This paper presents Dual Adaptive Neural Topology(Dual ANT),a distributed dual-network metaadaptive framework that enhances ant-colony-based multi-agent coordination with online introspection,adaptive parameter control,and privacy-preserving interactions.This approach improves standard Ant Colony Optimization(ACO)with two lightweight neural components:a forward network that estimates swarm efficiency in real time and an inverse network that converts these descriptors into parameter adaptations.To preserve the privacy of individual trajectories in shared pheromone maps,we introduce a locally differentially private pheromone update mechanism that adds calibrated noise to each agent’s pheromone deposit while preserving the efficacy of the global pheromone signal.The resulting systemenables agents to dynamically and autonomously adapt their coordination strategies under challenging and dynamic conditions,including varying obstacle layouts,uncertain target locations,and time-varying disturbances.Extensive simulations of large grid-based search tasks demonstrated that Dual ANT achieved faster convergence,higher robustness,and improved scalability compared to advanced baselines such asMulti-StrategyACO and Hierarchical ACO.The meta-adaptive feedback loop compensates for the performance degradation caused by privacy noise and prevents premature stagnation by triggering Levy flight exploration only when necessary.
基金supported by the National Natural Science Foundation of China under Grant 62472264the Natural Science Distinguished Youth Foundation of Shandong Province under Grant ZR2025QA13。
文摘In the wireless energy transmission service composition optimization problem,a key challenge is accurately capturing users’preferences for service criteria under complex influencing factors,and optimally selecting a composition solution under their budget constraints.Existing studies typically evaluate satisfaction solely based on energy transmission capacity,while overlooking critical factors such as price and trustworthiness of the provider,leading to a mismatch between optimization outcomes and user needs.To address this gap,we construct a user satisfaction evaluation model for multi-user and multi-provider scenarios,systematically incorporating service price,transmission capacity,and trustworthiness into the satisfaction assessment framework.Furthermore,we propose a Budget-Aware Preference Adjustment Model that predicts users’baseline preference weights from historical data and dynamically adjusts them according to budget levels,thereby reflecting user preferences more realistically under varying budget constraints.In addition,to tackle the composition optimization problem,we develop a ReflectiveEvolutionary Large Language Model—Guided Ant Colony Optimization algorithm,which leverages the reflective evolution capability of large language models to iteratively generate and refine heuristic information that guides the search process.Experimental results demonstrate that the proposed framework effectively integrates personalized preferences with budget sensitivity,accurately predicts users’preferences,and significantly enhances their satisfaction under complex constraints.
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.
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.
基金co-supported by the National Natural Science Foundation of China(No.61873017)the Academic Excellence Foundation of Beihang University for PhD Students,China.
文摘Swarm Intelligence (SI) is a collective behavior that emerges from interaction between individuals in a group. Typical SI includes fish schooling, ant foraging, bird migration, and so on. A great deal of models have been introduced to characterize the mechanism of SI. This article reviews several typical models and classifies them into four categories: self-driven particle models, with Boids model as the primary example;pheromone communication models, including the ant colony pheromone model which serves as the foundation for ant colony optimization;leadership decision models, utilizing the hierarchical dynamics model of pigeon flock as a prime instance;empirical research models, which employ the topological rule model of starling flock as a classic model. On this basis, each type of model is elaborated upon in terms of its typical model overview, applications, and model evaluation. More specifically, multi-agent swarm control, path optimization and obstacle avoidance, formation and consensus control, trajectory tracking in the dense crowd and social networks analysis are surveyed in the application of each category, respectively. Furthermore, the more precise and effective modeling techniques for leadership decision and empirical research models are described. Limitations and potential directions for further exploration in the study of SI are presented.
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 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.
