一、作为哲学的AI for Process(一)郭为的哲学思想1.郭为是谁郭为是谁?他是一位哲学家。顺便说,他同时还领导着神州数码。为什么说郭为是哲学家呢?因为他在著作中谈到高深的哲学,如“数据如水,奔流不息,无界融合”。他引述古希腊哲学家...一、作为哲学的AI for Process(一)郭为的哲学思想1.郭为是谁郭为是谁?他是一位哲学家。顺便说,他同时还领导着神州数码。为什么说郭为是哲学家呢?因为他在著作中谈到高深的哲学,如“数据如水,奔流不息,无界融合”。他引述古希腊哲学家赫拉克利特所说的“万物流转”,又说“你不能两次踏进同一条河流,因为新的水不断地流过你的身旁”,他所表达的意思是“世界上唯一不变的就是变化”。展开更多
Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing addit...Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing additive-induced defects,and alleviating residual stress and deformation,all of which are critical for enhancing the mechanical performance of the manufactured parts.Integrating interlayer friction stir processing(FSP)into WAAM significantly enhances the quality of deposited materials.However,numerical simulation research focusing on elucidating the associated thermomechanical coupling mechanisms remains insufficient.A comprehensive numerical model was developed to simulate the thermomechanical coupling behavior in friction stir-assisted WAAM.The influence of post-deposition FSP on the coupled thermomechanical response of the WAAM process was analyzed quantitatively.Moreover,the residual stress distribution and deformation behavior under both single-layer and multilayer deposition conditions were investigated.Thermal analysis of different deposition layers in WAAM and friction stir-assisted WAAM was conducted.Results show that subsequent layer deposition induces partial remelting of the previously solidified layer,whereas FSP does not cause such remelting.Furthermore,thermal stress and deformation analysis confirm that interlayer FSP effectively mitigates residual stresses and distortion in WAAM components,thereby improving their structural integrity and mechanical properties.展开更多
Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational,organizational,or regulatory factors.These changes,referred to as incremental con...Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational,organizational,or regulatory factors.These changes,referred to as incremental concept drift,gradually alter the behavior or structure of processes,making their detection and localization a challenging task.Traditional process mining techniques frequently assume process stationarity and are limited in their ability to detect such drift,particularly from a control-flow perspective.The objective of this research is to develop an interpretable and robust framework capable of detecting and localizing incremental concept drift in event logs,with a specific emphasis on the structural evolution of control-flow semantics in processes.We propose DriftXMiner,a control-flow-aware hybrid framework that combines statistical,machine learning,and process model analysis techniques.The approach comprises three key components:(1)Cumulative Drift Scanner that tracks directional statistical deviations to detect early drift signals;(2)a Temporal Clustering and Drift-Aware Forest Ensemble(DAFE)to capture distributional and classification-level changes in process behavior;and(3)Petri net-based process model reconstruction,which enables the precise localization of structural drift using transition deviation metrics and replay fitness scores.Experimental validation on the BPI Challenge 2017 event log demonstrates that DriftXMiner effectively identifies and localizes gradual and incremental process drift over time.The framework achieves a detection accuracy of 92.5%,a localization precision of 90.3%,and an F1-score of 0.91,outperforming competitive baselines such as CUSUM+Histograms and ADWIN+Alpha Miner.Visual analyses further confirm that identified drift points align with transitions in control-flow models and behavioral cluster structures.DriftXMiner offers a novel and interpretable solution for incremental concept drift detection and localization in dynamic,process-aware systems.By integrating statistical signal accumulation,temporal behavior profiling,and structural process mining,the framework enables finegrained drift explanation and supports adaptive process intelligence in evolving environments.Its modular architecture supports extension to streaming data and real-time monitoring contexts.展开更多
The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurode...The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurodegenerative diseases are characterized by the progressive loss of neuronal structure and function.展开更多
Graphite,encompassing both natural graphite and synthetic graphite,and graphene,have been extensively utilized and investigated as anode materials and additives in lithium-ion batteries(LIBs).In the pursuit of carbon ...Graphite,encompassing both natural graphite and synthetic graphite,and graphene,have been extensively utilized and investigated as anode materials and additives in lithium-ion batteries(LIBs).In the pursuit of carbon neutrality,LIBs are expected to play a pivotal role in reducing CO_(2)emissions by decreasing reliance on fossil fuels and enabling the integration of renewable energy sources.Owing to their technological maturity and exceptional electrochemical performance,the global production of graphite and graphene for LIBs is projected to continue expanding.Over the past decades,numerous researchers have concentrated on reducing the material and energy input whilst optimising the electrochemical performance of graphite and graphene,through novel synthesis methods and various modifications at the laboratory scale.This review provides a comprehensive examination of the manufacturing methods,environmental impact,research progress,and challenges associated with graphite and graphene in LIBs from an industrial perspective,with a particular focus on the carbon footprint of production processes.Additionally,it considers emerging challenges and future development directions of graphite and graphene,offering significant insights for ongoing and future research in the field of green LIBs.展开更多
Achieving high-energy density remains a key objective for advanced energy storage systems.However,challenges,such as poor cathode conductivity,anode dendrite formation,polysulfide shuttling,and electrolyte degradation...Achieving high-energy density remains a key objective for advanced energy storage systems.However,challenges,such as poor cathode conductivity,anode dendrite formation,polysulfide shuttling,and electrolyte degradation,continue to limit performance and stability.Molecular and ionic dipole interactions have emerged as an effective strategy to address these issues by regulating ionic transport,modulating solvation structures,optimizing interfacial chemistry,and enhancing charge transfer kinetics.These interactions also stabilize electrode interfaces,suppress side reactions,and mitigate anode corrosion,collectively improving the durability of high-energy batteries.A deeper understanding of these mechanisms is essential to guide the design of next-generation battery materials.Herein,this review summarizes the development,classification,and advantages of dipole interactions in high-energy batteries.The roles of dipoles,including facilitating ion transport,controlling solvation dynamics,stabilizing the electric double layer,optimizing solid electrolyte interphase and cathode–electrolyte interface layers,and inhibiting parasitic reactions—are comprehensively discussed.Finally,perspectives on future research directions are proposed to advance dipole-enabled strategies for high-performance energy storage.This review aims to provide insights into the rational design of dipole-interactive systems and promote the progress of electrochemical energy storage technologies.展开更多
Machine learning-assisted methods for rapid and accurate prediction of temperature field,mushy zone,and grain size were proposed for the heating−cooling combined mold(HCCM)horizontal continuous casting of C70250 alloy...Machine learning-assisted methods for rapid and accurate prediction of temperature field,mushy zone,and grain size were proposed for the heating−cooling combined mold(HCCM)horizontal continuous casting of C70250 alloy plates.First,finite element simulations of casting processes were carried out with various parameters to build a dataset.Subsequently,different machine learning algorithms were employed to achieve high precision in predicting temperature fields,mushy zone locations,mushy zone inclination angle,and billet grain size.Finally,the process parameters were quickly optimized using a strategy consisting of random generation,prediction,and screening,allowing the mushy zone to be controlled to the desired target.The optimized parameters are 1234℃for heating mold temperature,47 mm/min for casting speed,and 10 L/min for cooling water flow rate.The optimized mushy zone is located in the middle of the second heat insulation section and has an inclination angle of roughly 7°.展开更多
The microbial degradation of aromatic organic pollutants is incomplete due to their metabolic characteristics,which can easily produce certain highly toxic intermediates.Therefore,this article designs a dual template ...The microbial degradation of aromatic organic pollutants is incomplete due to their metabolic characteristics,which can easily produce certain highly toxic intermediates.Therefore,this article designs a dual template molec-ularly imprinted sensor(DTMIP/Fe-Mn@C)for iron manganese metal nanomaterials,prepared Fe-Mn@C com-posite materials by a one pot method were coated on the surface of glassy carbon electrodes and covered with molecularly imprinted membranes through electropolymerization and elution methods,achieving real-time de-tection of specific intermediate products 2-methylbutyric acid(2-MBA)and 3-methylbutyric acid(3-MBA)de-graded by azo dyes.In order to determine the detection sensitivity and intensity range of the sensor,optimization experiments were conducted on various parameters that affect the detection performance,such as the type of func-tional monomer and its composition ratio with the template molecule,detection time window,environmental pH value,etc.Finally,o-Phenylenediamine was determined as the functional monomer,with a molar ratio of 1:1:6 to the template molecules 2-MBA and 3-MBA.Electrochemical testing was conducted in a neutral environment with an incubation time of 5 min and pH=7.The results indicate that the sensor has a relatively wide detection range,high sensitivity,obvious recognition features,and excellent stability for 2-MBA and 3-MBA.This new dual template molecularly imprinted sensor can quickly and accurately determine the safety of highly toxic interme-diates in the degradation process of aromatic organic pollutants,providing a theoretical basis and application potential for trace detection and real-time monitoring.展开更多
Unwarranted death of neurons is a major cause of neurodegenerative diseases.Since mature neurons are postmitotic and do not replicate,their death usually constitutes an irreversible step in pathology.A logical strateg...Unwarranted death of neurons is a major cause of neurodegenerative diseases.Since mature neurons are postmitotic and do not replicate,their death usually constitutes an irreversible step in pathology.A logical strategy to prevent neurodegeneration would then be to save all neurons that are still alive,i.e.protecting the ones that are still healthy as well as trying to rescue the ones that are damaged and in the process of dying.Regarding the latter,recent experiments have indicated that the possibility of reversing the cell death process and rescuing dying cells is more significant than previously anticipated.In many situations,the elimination of the cell death trigger alone enables dying cells to spontaneously repair their damage,recover,and survive.In this review,we explore the factors,which determine the fate of neurons engaged in the cell death process.A deeper insight into cell death mechanisms and the intrinsic capacity of cells to recover could pave the way for novel therapeutic approaches to neurodegenerative diseases.展开更多
Oil-fired construction machinery(OCM)is a major source of urban air pollutants and CO_(2) emissions,and elec-trification is a crucial pathway for improving air quality and achieving China’s dual carbon goals;however,...Oil-fired construction machinery(OCM)is a major source of urban air pollutants and CO_(2) emissions,and elec-trification is a crucial pathway for improving air quality and achieving China’s dual carbon goals;however,its feasibility has not been fully explored.This study uses data envelopment analysis and the analytic hierarchy process to establish a development potential index,covering technical efficiency,economic cost,application sce-narios,and charging time and range,with an empirical analysis conducted in Beijing.The findings indicated the high feasibility of replacing OCM with electric alternatives,especially within the low-power range.Based on 2023 registered coding dat1,it is projected that by 2030,electrification could reduce regional average con-centrations of CO,NO_(x),PM_(2.5) and VOCs by 12.2%to 56.4%and reduce CO_(2) by 11.7%to 56.9%.Owing to economic considerations,small-and medium-sized machinery are particularly feasible for electrification.Key recommendations include prioritizing the electrification of forklifts,lifting platforms,and small-sized machinery in high-emission areas,particularly in central urban districts.Policies such as carbon taxes,carbon markets,and performance grading systems are suggested to incentivize electrification,along with expanding high-emission restriction zones and improving energy infrastructure to support widespread electrification.展开更多
Microorganisms can colonize the surface of microplastics(MPs)to form a distinctive microbiome,known as a“plastisphere”which is regarded as an anthropogenic niche for microbial growth.However,bacterial community asse...Microorganisms can colonize the surface of microplastics(MPs)to form a distinctive microbiome,known as a“plastisphere”which is regarded as an anthropogenic niche for microbial growth.However,bacterial community assembly in virgin and aging MP plastispheres across different habitats is poorly understood.This study aims to assess the variations in bacterial community assembly across different niches and habitats with an in situ ex-periment,in which constructed forest wetland(FW),natural lake wetland(LW),and lotus pond wetland(LP)were habitats,and plastispheres of virgin and aging low-density polyethylene(LDPE)MPs,as well as surround-ing wetland soils were niches.Significant niche-related differences in bacterial communities were observed,with lower diversity and enrichment of potential plastic-degrading bacteria in the plastisphere than in the soil bacterial communities.Furthermore,habitat-related differences exerted a more pronounced influence on the beta-diversity patterns of the bacterial communities.The linear regression analyses indicated that the local species pool con-tributed more to bacterial community assembly in the LW wetland,whereas the relative abundance of species was the primary factor in the LP wetland.The null model analysis indicated that plastisphere bacterial communi-ties were predominantly driven by the stochastic process,with a more deterministic assembly observed in the LP wetland and soil bacterial communities.Additionally,the primary ecological process shaping plastisphere com-munities shifted from drift in the virgin LDPE to homogenising dispersal in the aging LDPE.This study provides new insights into the fate and ecological impacts of MPs in wetlands,thereby facilitating the effective regulations of plastic pollution.展开更多
Since Google introduced the concept of Knowledge Graphs(KGs)in 2012,their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition,extraction,representati...Since Google introduced the concept of Knowledge Graphs(KGs)in 2012,their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition,extraction,representation,modeling,fusion,computation,and storage.Within this framework,knowledge extraction,as the core component,directly determines KG quality.In military domains,traditional manual curation models face efficiency constraints due to data fragmentation,complex knowledge architectures,and confidentiality protocols.Meanwhile,crowdsourced ontology construction approaches from general domains prove non-transferable,while human-crafted ontologies struggle with generalization deficiencies.To address these challenges,this study proposes an OntologyAware LLM Methodology for Military Domain Knowledge Extraction(LLM-KE).This approach leverages the deep semantic comprehension capabilities of Large Language Models(LLMs)to simulate human experts’cognitive processes in crowdsourced ontology construction,enabling automated extraction of military textual knowledge.It concurrently enhances knowledge processing efficiency and improves KG completeness.Empirical analysis demonstrates that this method effectively resolves scalability and dynamic adaptation challenges in military KG construction,establishing a novel technological pathway for advancing military intelligence development.展开更多
Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination syst...Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination system for Connected and Automated Vehicles(CAVs)at single-lane intersections,particularly in the context of left-hand side driving on roads.The goal is to facilitate smooth right turns for certain vehicles without creating bottlenecks.We consider that all approaching vehicles share relevant information through vehicular communications.The Intersection Coordination Unit(ICU)processes this information and communicates the optimal crossing or turning times to the vehicles.The primary objective of this coordination is to minimize overall traffic delays,which also helps improve the fuel consumption of vehicles.By considering information from upcoming vehicles at the intersection,the coordination system solves an optimization problem to determine the best timing for executing right turns,ultimately minimizing the total delay for all vehicles.The proposed coordination system is evaluated at a typical urban intersection,and its performance is compared to traditional traffic systems.Numerical simulation results indicate that the proposed coordination system significantly enhances the average traffic speed and fuel consumption compared to the traditional traffic system in various scenarios.展开更多
Overweight and obesity has been a major public health problem globally.It was estimated that more than 2.1 billion adults were affected by overweight or obese in 2021 worldwide,about one fifth of whom lived in China^(...Overweight and obesity has been a major public health problem globally.It was estimated that more than 2.1 billion adults were affected by overweight or obese in 2021 worldwide,about one fifth of whom lived in China^([1]).By 2050,the country is forecast to remain the one with the largest population of overweight and obese globally^([1]),if no effective strategies were applied on overweight/obesity control.展开更多
Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods...Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods,based on reliable existing data stored in project management tools’datasets,automating this evaluation process becomes a natural step forward.In this context,our approach focuses on quantifying software developer expertise by using metadata from the task-tracking systems.For this,we mathematically formalize two categories of expertise:technology-specific expertise,which denotes the skills required for a particular technology,and general expertise,which encapsulates overall knowledge in the software industry.Afterward,we automatically classify the zones of expertise associated with each task a developer has worked on using Bidirectional Encoder Representations from Transformers(BERT)-like transformers to handle the unique characteristics of project tool datasets effectively.Finally,our method evaluates the proficiency of each software specialist across already completed projects from both technology-specific and general perspectives.The method was experimentally validated,yielding promising results.展开更多
This study examines the methods to plan the development of offshore oilfields over the years,which are used to support the decision-making on the development of offshore oilfields.About 100 papers are analysed and cat...This study examines the methods to plan the development of offshore oilfields over the years,which are used to support the decision-making on the development of offshore oilfields.About 100 papers are analysed and categorised into different groups of main early-stage decisions.The present study stands in contrast to the contributions of the operations research and system engineering review articles,on the one hand,and the petroleum engineering review articles,on the other.This is because it does not focus on one methodological approach,nor does it limit the literature analysis by offshore oilfield characteristics.Consequently,the present analysis may offer valuable insights,for instance,by identifying environmental planning decisions as a recent yet highly significant concern that is currently being imposed on decision-making process.Thus,it is evident that the incorporation of safety criteria within the technical-economic decision-making process for the design of production systems would be a crucial requirement at development phase.展开更多
The complexity of the seismicity pattern for the subduction zone along the oceanic plate triggered the outer rise events and revealed cyclic tectonic deformation conditions along the plate subduction zones.The outer r...The complexity of the seismicity pattern for the subduction zone along the oceanic plate triggered the outer rise events and revealed cyclic tectonic deformation conditions along the plate subduction zones.The outer rise earthquakes have been observed along the Sunda arc,following the estimated rupture area of the 2005 M_(W)8.6 Nias earthquakes.Here,we used kinematic waveform inversion(KIWI)to obtain the source parameters of the 14 May 2021 M_(W)6.6 event off the west coast of northern Sumatra and to define the fault plane that triggered this outer rise event.The KIWI algorithm allows two types of seismic source to be configured:the moment tensor model to describe the type of shear with six moment tensor components and the Eikonal model for the rupture of pure double-couple sources.This method was chosen for its flexibility to be applied for different sources of seismicity and also for the automated full-moment tensor solution with real-time monitoring.We used full waveform traces from 8 broadband seismic stations within 1000 km epicentral distances sourced from the Incorporated Research Institutions for Seismology(IRIS-IDA)and Geofon GFZ seismic record databases.The initial origin time and hypocenter values are obtained from the IRIS-IDA.The synthetic seismograms used in the inversion process are based on the existing regional green function database model and were accessed from the KIWI Tools Green's Function Database.The obtained scalar seismic moment value is 1.18×10^(19)N·m,equivalent to a moment magnitude M_(W)6.6.The source parameters are 140°,44°,and−99°for the strike,dip,and rake values at a centroid depth of 10.2 km,indicating that this event is a normal fault earthquake that occurred in the outer rise area.The outer rise events with normal faults typically occur at the shallow part of the plate,with nodal-plane dips predominantly in the range of 30°-60°on the weak oceanic lithosphere due to hydrothermal alteration.The stress regime around the plate subduction zone varies both temporally and spatially due to the cyclic influences of megathrust earthquakes.Tensional outer rise earthquakes tend to occur after the megathrust events.The relative timing of these events is not known due to the viscous relaxation of the down going slab and poroelastic response in the trench slope region.The occurrence of the 14 May 2021 earthquake shows the seismicity in the outer rise region in the strongly coupled Sunda arc subduction zone due to elastic bending stress within the duration of the seismic cycle.展开更多
Oxide dispersion strengthened(ODS)alloys are extensively used owing to high thermostability and creep strength contributed from uniformly dispersed fine oxides particles.However,the existence of these strengthening pa...Oxide dispersion strengthened(ODS)alloys are extensively used owing to high thermostability and creep strength contributed from uniformly dispersed fine oxides particles.However,the existence of these strengthening particles also deteriorates the processability and it is of great importance to establish accurate processing maps to guide the thermomechanical processes to enhance the formability.In this study,we performed particle swarm optimization-based back propagation artificial neural network model to predict the high temperature flow behavior of 0.25wt%Al2O3 particle-reinforced Cu alloys,and compared the accuracy with that of derived by Arrhenius-type constitutive model and back propagation artificial neural network model.To train these models,we obtained the raw data by fabricating ODS Cu alloys using the internal oxidation and reduction method,and conducting systematic hot compression tests between 400 and800℃with strain rates of 10^(-2)-10 S^(-1).At last,processing maps for ODS Cu alloys were proposed by combining processing parameters,mechanical behavior,microstructure characterization,and the modeling results achieved a coefficient of determination higher than>99%.展开更多
Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remain...Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remains one of the security challenges. is paper proposes LinguTimeX,a new framework that combines natural language processing with arti cial intelligence,along with explainable Arti cial Intelligence(AI)not only to detect CTC but also to provide insights into the decision process.LinguTimeX performs multidimensional feature extraction by fusing linguistic attributes with temporal network patterns to identify covert channels precisely.LinguTimeX demonstrates strong e ectiveness in detecting CTC across multiple languages;namely English,Arabic,and Chinese.Speci cally,the LSTM and RNN models achieved F1 scores of 90%on the English dataset,89%on the Arabic dataset,and 88%on the Chinese dataset,showcasing their superior performance and ability to generalize across multiple languages. is highlights their robustness in detecting CTCs within security systems,regardless of the language or cultural context of the data.In contrast,the DeepForest model produced F1-scores ranging from 86%to 87%across the same datasets,further con rming its e ectiveness in CTC detection.Although other algorithms also showed reasonable accuracy,the LSTM and RNN models consistently outperformed them in multilingual settings,suggesting that deep learning models might be better suited for this particular problem.展开更多
文摘一、作为哲学的AI for Process(一)郭为的哲学思想1.郭为是谁郭为是谁?他是一位哲学家。顺便说,他同时还领导着神州数码。为什么说郭为是哲学家呢?因为他在著作中谈到高深的哲学,如“数据如水,奔流不息,无界融合”。他引述古希腊哲学家赫拉克利特所说的“万物流转”,又说“你不能两次踏进同一条河流,因为新的水不断地流过你的身旁”,他所表达的意思是“世界上唯一不变的就是变化”。
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
基金National Key Research and Development Program of China(2022YFB4600902)Shandong Provincial Science Foundation for Outstanding Young Scholars(ZR2024YQ020)。
文摘Wire arc additive manufacturing(WAAM)has emerged as a promising approach for fabricating large-scale components.However,conventional WAAM still faces challenges in optimizing microstructural evolution,minimizing additive-induced defects,and alleviating residual stress and deformation,all of which are critical for enhancing the mechanical performance of the manufactured parts.Integrating interlayer friction stir processing(FSP)into WAAM significantly enhances the quality of deposited materials.However,numerical simulation research focusing on elucidating the associated thermomechanical coupling mechanisms remains insufficient.A comprehensive numerical model was developed to simulate the thermomechanical coupling behavior in friction stir-assisted WAAM.The influence of post-deposition FSP on the coupled thermomechanical response of the WAAM process was analyzed quantitatively.Moreover,the residual stress distribution and deformation behavior under both single-layer and multilayer deposition conditions were investigated.Thermal analysis of different deposition layers in WAAM and friction stir-assisted WAAM was conducted.Results show that subsequent layer deposition induces partial remelting of the previously solidified layer,whereas FSP does not cause such remelting.Furthermore,thermal stress and deformation analysis confirm that interlayer FSP effectively mitigates residual stresses and distortion in WAAM components,thereby improving their structural integrity and mechanical properties.
文摘Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational,organizational,or regulatory factors.These changes,referred to as incremental concept drift,gradually alter the behavior or structure of processes,making their detection and localization a challenging task.Traditional process mining techniques frequently assume process stationarity and are limited in their ability to detect such drift,particularly from a control-flow perspective.The objective of this research is to develop an interpretable and robust framework capable of detecting and localizing incremental concept drift in event logs,with a specific emphasis on the structural evolution of control-flow semantics in processes.We propose DriftXMiner,a control-flow-aware hybrid framework that combines statistical,machine learning,and process model analysis techniques.The approach comprises three key components:(1)Cumulative Drift Scanner that tracks directional statistical deviations to detect early drift signals;(2)a Temporal Clustering and Drift-Aware Forest Ensemble(DAFE)to capture distributional and classification-level changes in process behavior;and(3)Petri net-based process model reconstruction,which enables the precise localization of structural drift using transition deviation metrics and replay fitness scores.Experimental validation on the BPI Challenge 2017 event log demonstrates that DriftXMiner effectively identifies and localizes gradual and incremental process drift over time.The framework achieves a detection accuracy of 92.5%,a localization precision of 90.3%,and an F1-score of 0.91,outperforming competitive baselines such as CUSUM+Histograms and ADWIN+Alpha Miner.Visual analyses further confirm that identified drift points align with transitions in control-flow models and behavioral cluster structures.DriftXMiner offers a novel and interpretable solution for incremental concept drift detection and localization in dynamic,process-aware systems.By integrating statistical signal accumulation,temporal behavior profiling,and structural process mining,the framework enables finegrained drift explanation and supports adaptive process intelligence in evolving environments.Its modular architecture supports extension to streaming data and real-time monitoring contexts.
文摘The aging process is an inexorable fact throughout our lives and is considered a major factor in develo ping neurological dysfunctions associated with cognitive,emotional,and motor impairments.Aging-associated neurodegenerative diseases are characterized by the progressive loss of neuronal structure and function.
基金supported by European Union's Horizon Europe,UK Research and Innovation(UKRI).
文摘Graphite,encompassing both natural graphite and synthetic graphite,and graphene,have been extensively utilized and investigated as anode materials and additives in lithium-ion batteries(LIBs).In the pursuit of carbon neutrality,LIBs are expected to play a pivotal role in reducing CO_(2)emissions by decreasing reliance on fossil fuels and enabling the integration of renewable energy sources.Owing to their technological maturity and exceptional electrochemical performance,the global production of graphite and graphene for LIBs is projected to continue expanding.Over the past decades,numerous researchers have concentrated on reducing the material and energy input whilst optimising the electrochemical performance of graphite and graphene,through novel synthesis methods and various modifications at the laboratory scale.This review provides a comprehensive examination of the manufacturing methods,environmental impact,research progress,and challenges associated with graphite and graphene in LIBs from an industrial perspective,with a particular focus on the carbon footprint of production processes.Additionally,it considers emerging challenges and future development directions of graphite and graphene,offering significant insights for ongoing and future research in the field of green LIBs.
基金supported by the introduction of Talent Research Fund in Nanjing Institute of Technology(YKJ202204)the National Natural Science Foundation of China(52401282 and 52300206)the Natural Science Foundation of Jiangsu Province(BK20230701 and BK20230705).
文摘Achieving high-energy density remains a key objective for advanced energy storage systems.However,challenges,such as poor cathode conductivity,anode dendrite formation,polysulfide shuttling,and electrolyte degradation,continue to limit performance and stability.Molecular and ionic dipole interactions have emerged as an effective strategy to address these issues by regulating ionic transport,modulating solvation structures,optimizing interfacial chemistry,and enhancing charge transfer kinetics.These interactions also stabilize electrode interfaces,suppress side reactions,and mitigate anode corrosion,collectively improving the durability of high-energy batteries.A deeper understanding of these mechanisms is essential to guide the design of next-generation battery materials.Herein,this review summarizes the development,classification,and advantages of dipole interactions in high-energy batteries.The roles of dipoles,including facilitating ion transport,controlling solvation dynamics,stabilizing the electric double layer,optimizing solid electrolyte interphase and cathode–electrolyte interface layers,and inhibiting parasitic reactions—are comprehensively discussed.Finally,perspectives on future research directions are proposed to advance dipole-enabled strategies for high-performance energy storage.This review aims to provide insights into the rational design of dipole-interactive systems and promote the progress of electrochemical energy storage technologies.
基金financially supported by the National Key Research and Development Program of China (No. 2023YFB3812601)the National Natural Science Foundation of China (No. 51925401)the Young Elite Scientists Sponsorship Program by CAST, China (No. 2022QNRC001)。
文摘Machine learning-assisted methods for rapid and accurate prediction of temperature field,mushy zone,and grain size were proposed for the heating−cooling combined mold(HCCM)horizontal continuous casting of C70250 alloy plates.First,finite element simulations of casting processes were carried out with various parameters to build a dataset.Subsequently,different machine learning algorithms were employed to achieve high precision in predicting temperature fields,mushy zone locations,mushy zone inclination angle,and billet grain size.Finally,the process parameters were quickly optimized using a strategy consisting of random generation,prediction,and screening,allowing the mushy zone to be controlled to the desired target.The optimized parameters are 1234℃for heating mold temperature,47 mm/min for casting speed,and 10 L/min for cooling water flow rate.The optimized mushy zone is located in the middle of the second heat insulation section and has an inclination angle of roughly 7°.
基金supported by the Bingtuan Industrial Technology Research Institute,Bingtuan New materials Research Institute innovation platform project,Research initiation project of Shihezi University(No.RCZK202330)the Science and Technology Program-Regional Innovation Guidance Program(No.2023ZD080)Tianchi Talent Project(No.CZ002735).
文摘The microbial degradation of aromatic organic pollutants is incomplete due to their metabolic characteristics,which can easily produce certain highly toxic intermediates.Therefore,this article designs a dual template molec-ularly imprinted sensor(DTMIP/Fe-Mn@C)for iron manganese metal nanomaterials,prepared Fe-Mn@C com-posite materials by a one pot method were coated on the surface of glassy carbon electrodes and covered with molecularly imprinted membranes through electropolymerization and elution methods,achieving real-time de-tection of specific intermediate products 2-methylbutyric acid(2-MBA)and 3-methylbutyric acid(3-MBA)de-graded by azo dyes.In order to determine the detection sensitivity and intensity range of the sensor,optimization experiments were conducted on various parameters that affect the detection performance,such as the type of func-tional monomer and its composition ratio with the template molecule,detection time window,environmental pH value,etc.Finally,o-Phenylenediamine was determined as the functional monomer,with a molar ratio of 1:1:6 to the template molecules 2-MBA and 3-MBA.Electrochemical testing was conducted in a neutral environment with an incubation time of 5 min and pH=7.The results indicate that the sensor has a relatively wide detection range,high sensitivity,obvious recognition features,and excellent stability for 2-MBA and 3-MBA.This new dual template molecularly imprinted sensor can quickly and accurately determine the safety of highly toxic interme-diates in the degradation process of aromatic organic pollutants,providing a theoretical basis and application potential for trace detection and real-time monitoring.
基金supported by the following foundations:“Stichting Oogfonds Nederland(No.2023-26)”the“Landelijke Stichting voor Blinden en Slechtzienden(No.2023-24)”that contributed through UitZicht,ZonMw grant(No.435005020)a grant of the Chinese Scholarship Council(No.201809110169)(to TGMFG,CPMR,and WY).
文摘Unwarranted death of neurons is a major cause of neurodegenerative diseases.Since mature neurons are postmitotic and do not replicate,their death usually constitutes an irreversible step in pathology.A logical strategy to prevent neurodegeneration would then be to save all neurons that are still alive,i.e.protecting the ones that are still healthy as well as trying to rescue the ones that are damaged and in the process of dying.Regarding the latter,recent experiments have indicated that the possibility of reversing the cell death process and rescuing dying cells is more significant than previously anticipated.In many situations,the elimination of the cell death trigger alone enables dying cells to spontaneously repair their damage,recover,and survive.In this review,we explore the factors,which determine the fate of neurons engaged in the cell death process.A deeper insight into cell death mechanisms and the intrinsic capacity of cells to recover could pave the way for novel therapeutic approaches to neurodegenerative diseases.
基金supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China(No.2024ZD1200200).
文摘Oil-fired construction machinery(OCM)is a major source of urban air pollutants and CO_(2) emissions,and elec-trification is a crucial pathway for improving air quality and achieving China’s dual carbon goals;however,its feasibility has not been fully explored.This study uses data envelopment analysis and the analytic hierarchy process to establish a development potential index,covering technical efficiency,economic cost,application sce-narios,and charging time and range,with an empirical analysis conducted in Beijing.The findings indicated the high feasibility of replacing OCM with electric alternatives,especially within the low-power range.Based on 2023 registered coding dat1,it is projected that by 2030,electrification could reduce regional average con-centrations of CO,NO_(x),PM_(2.5) and VOCs by 12.2%to 56.4%and reduce CO_(2) by 11.7%to 56.9%.Owing to economic considerations,small-and medium-sized machinery are particularly feasible for electrification.Key recommendations include prioritizing the electrification of forklifts,lifting platforms,and small-sized machinery in high-emission areas,particularly in central urban districts.Policies such as carbon taxes,carbon markets,and performance grading systems are suggested to incentivize electrification,along with expanding high-emission restriction zones and improving energy infrastructure to support widespread electrification.
基金supported by Shanghai Municipal Natural Science Foundation,China(No.21ZR1446800)the National Natural Science Foundation of China(No.41877425)the Fundamental Research Funds for the Central Universities(No.226-2024-00052)。
文摘Microorganisms can colonize the surface of microplastics(MPs)to form a distinctive microbiome,known as a“plastisphere”which is regarded as an anthropogenic niche for microbial growth.However,bacterial community assembly in virgin and aging MP plastispheres across different habitats is poorly understood.This study aims to assess the variations in bacterial community assembly across different niches and habitats with an in situ ex-periment,in which constructed forest wetland(FW),natural lake wetland(LW),and lotus pond wetland(LP)were habitats,and plastispheres of virgin and aging low-density polyethylene(LDPE)MPs,as well as surround-ing wetland soils were niches.Significant niche-related differences in bacterial communities were observed,with lower diversity and enrichment of potential plastic-degrading bacteria in the plastisphere than in the soil bacterial communities.Furthermore,habitat-related differences exerted a more pronounced influence on the beta-diversity patterns of the bacterial communities.The linear regression analyses indicated that the local species pool con-tributed more to bacterial community assembly in the LW wetland,whereas the relative abundance of species was the primary factor in the LP wetland.The null model analysis indicated that plastisphere bacterial communi-ties were predominantly driven by the stochastic process,with a more deterministic assembly observed in the LP wetland and soil bacterial communities.Additionally,the primary ecological process shaping plastisphere com-munities shifted from drift in the virgin LDPE to homogenising dispersal in the aging LDPE.This study provides new insights into the fate and ecological impacts of MPs in wetlands,thereby facilitating the effective regulations of plastic pollution.
文摘Since Google introduced the concept of Knowledge Graphs(KGs)in 2012,their construction technologies have evolved into a comprehensive methodological framework encompassing knowledge acquisition,extraction,representation,modeling,fusion,computation,and storage.Within this framework,knowledge extraction,as the core component,directly determines KG quality.In military domains,traditional manual curation models face efficiency constraints due to data fragmentation,complex knowledge architectures,and confidentiality protocols.Meanwhile,crowdsourced ontology construction approaches from general domains prove non-transferable,while human-crafted ontologies struggle with generalization deficiencies.To address these challenges,this study proposes an OntologyAware LLM Methodology for Military Domain Knowledge Extraction(LLM-KE).This approach leverages the deep semantic comprehension capabilities of Large Language Models(LLMs)to simulate human experts’cognitive processes in crowdsourced ontology construction,enabling automated extraction of military textual knowledge.It concurrently enhances knowledge processing efficiency and improves KG completeness.Empirical analysis demonstrates that this method effectively resolves scalability and dynamic adaptation challenges in military KG construction,establishing a novel technological pathway for advancing military intelligence development.
基金supported by the Japan Society for the Promotion of Science(JSPS)Grants-in-Aid for Scientific Research(C)23K03898.
文摘Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination system for Connected and Automated Vehicles(CAVs)at single-lane intersections,particularly in the context of left-hand side driving on roads.The goal is to facilitate smooth right turns for certain vehicles without creating bottlenecks.We consider that all approaching vehicles share relevant information through vehicular communications.The Intersection Coordination Unit(ICU)processes this information and communicates the optimal crossing or turning times to the vehicles.The primary objective of this coordination is to minimize overall traffic delays,which also helps improve the fuel consumption of vehicles.By considering information from upcoming vehicles at the intersection,the coordination system solves an optimization problem to determine the best timing for executing right turns,ultimately minimizing the total delay for all vehicles.The proposed coordination system is evaluated at a typical urban intersection,and its performance is compared to traditional traffic systems.Numerical simulation results indicate that the proposed coordination system significantly enhances the average traffic speed and fuel consumption compared to the traditional traffic system in various scenarios.
文摘Overweight and obesity has been a major public health problem globally.It was estimated that more than 2.1 billion adults were affected by overweight or obese in 2021 worldwide,about one fifth of whom lived in China^([1]).By 2050,the country is forecast to remain the one with the largest population of overweight and obese globally^([1]),if no effective strategies were applied on overweight/obesity control.
基金supported by the project“Romanian Hub for Artificial Intelligence-HRIA”,Smart Growth,Digitization and Financial Instruments Program,2021–2027,MySMIS No.334906.
文摘Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods,based on reliable existing data stored in project management tools’datasets,automating this evaluation process becomes a natural step forward.In this context,our approach focuses on quantifying software developer expertise by using metadata from the task-tracking systems.For this,we mathematically formalize two categories of expertise:technology-specific expertise,which denotes the skills required for a particular technology,and general expertise,which encapsulates overall knowledge in the software industry.Afterward,we automatically classify the zones of expertise associated with each task a developer has worked on using Bidirectional Encoder Representations from Transformers(BERT)-like transformers to handle the unique characteristics of project tool datasets effectively.Finally,our method evaluates the proficiency of each software specialist across already completed projects from both technology-specific and general perspectives.The method was experimentally validated,yielding promising results.
基金the Strategic Research Plan of the Centre for Marine Technology and Ocean Engineering(CENTEC),which is financed by the Portuguese Foundation for Science and Technology(Fundação para a Ciência e a Tecnologia FCT)under contract UIDB/UIDP/00134/2020.
文摘This study examines the methods to plan the development of offshore oilfields over the years,which are used to support the decision-making on the development of offshore oilfields.About 100 papers are analysed and categorised into different groups of main early-stage decisions.The present study stands in contrast to the contributions of the operations research and system engineering review articles,on the one hand,and the petroleum engineering review articles,on the other.This is because it does not focus on one methodological approach,nor does it limit the literature analysis by offshore oilfield characteristics.Consequently,the present analysis may offer valuable insights,for instance,by identifying environmental planning decisions as a recent yet highly significant concern that is currently being imposed on decision-making process.Thus,it is evident that the incorporation of safety criteria within the technical-economic decision-making process for the design of production systems would be a crucial requirement at development phase.
基金supported by the National Natural Science Foundation of China(Grant No.42130312)。
文摘The complexity of the seismicity pattern for the subduction zone along the oceanic plate triggered the outer rise events and revealed cyclic tectonic deformation conditions along the plate subduction zones.The outer rise earthquakes have been observed along the Sunda arc,following the estimated rupture area of the 2005 M_(W)8.6 Nias earthquakes.Here,we used kinematic waveform inversion(KIWI)to obtain the source parameters of the 14 May 2021 M_(W)6.6 event off the west coast of northern Sumatra and to define the fault plane that triggered this outer rise event.The KIWI algorithm allows two types of seismic source to be configured:the moment tensor model to describe the type of shear with six moment tensor components and the Eikonal model for the rupture of pure double-couple sources.This method was chosen for its flexibility to be applied for different sources of seismicity and also for the automated full-moment tensor solution with real-time monitoring.We used full waveform traces from 8 broadband seismic stations within 1000 km epicentral distances sourced from the Incorporated Research Institutions for Seismology(IRIS-IDA)and Geofon GFZ seismic record databases.The initial origin time and hypocenter values are obtained from the IRIS-IDA.The synthetic seismograms used in the inversion process are based on the existing regional green function database model and were accessed from the KIWI Tools Green's Function Database.The obtained scalar seismic moment value is 1.18×10^(19)N·m,equivalent to a moment magnitude M_(W)6.6.The source parameters are 140°,44°,and−99°for the strike,dip,and rake values at a centroid depth of 10.2 km,indicating that this event is a normal fault earthquake that occurred in the outer rise area.The outer rise events with normal faults typically occur at the shallow part of the plate,with nodal-plane dips predominantly in the range of 30°-60°on the weak oceanic lithosphere due to hydrothermal alteration.The stress regime around the plate subduction zone varies both temporally and spatially due to the cyclic influences of megathrust earthquakes.Tensional outer rise earthquakes tend to occur after the megathrust events.The relative timing of these events is not known due to the viscous relaxation of the down going slab and poroelastic response in the trench slope region.The occurrence of the 14 May 2021 earthquake shows the seismicity in the outer rise region in the strongly coupled Sunda arc subduction zone due to elastic bending stress within the duration of the seismic cycle.
基金financial support of the National Natural Science Foundation of China(No.52371103)the Fundamental Research Funds for the Central Universities,China(No.2242023K40028)+1 种基金the Open Research Fund of Jiangsu Key Laboratory for Advanced Metallic Materials,China(No.AMM2023B01).financial support of the Research Fund of Shihezi Key Laboratory of AluminumBased Advanced Materials,China(No.2023PT02)financial support of Guangdong Province Science and Technology Major Project,China(No.2021B0301030005)。
文摘Oxide dispersion strengthened(ODS)alloys are extensively used owing to high thermostability and creep strength contributed from uniformly dispersed fine oxides particles.However,the existence of these strengthening particles also deteriorates the processability and it is of great importance to establish accurate processing maps to guide the thermomechanical processes to enhance the formability.In this study,we performed particle swarm optimization-based back propagation artificial neural network model to predict the high temperature flow behavior of 0.25wt%Al2O3 particle-reinforced Cu alloys,and compared the accuracy with that of derived by Arrhenius-type constitutive model and back propagation artificial neural network model.To train these models,we obtained the raw data by fabricating ODS Cu alloys using the internal oxidation and reduction method,and conducting systematic hot compression tests between 400 and800℃with strain rates of 10^(-2)-10 S^(-1).At last,processing maps for ODS Cu alloys were proposed by combining processing parameters,mechanical behavior,microstructure characterization,and the modeling results achieved a coefficient of determination higher than>99%.
基金This study is financed by the European Union-NextGenerationEU,through the National Recovery and Resilience Plan of the Republic of Bulgaria,Project No.BG-RRP-2.013-0001.
文摘Covert timing channels(CTC)exploit network resources to establish hidden communication pathways,posing signi cant risks to data security and policy compliance.erefore,detecting such hidden and dangerous threats remains one of the security challenges. is paper proposes LinguTimeX,a new framework that combines natural language processing with arti cial intelligence,along with explainable Arti cial Intelligence(AI)not only to detect CTC but also to provide insights into the decision process.LinguTimeX performs multidimensional feature extraction by fusing linguistic attributes with temporal network patterns to identify covert channels precisely.LinguTimeX demonstrates strong e ectiveness in detecting CTC across multiple languages;namely English,Arabic,and Chinese.Speci cally,the LSTM and RNN models achieved F1 scores of 90%on the English dataset,89%on the Arabic dataset,and 88%on the Chinese dataset,showcasing their superior performance and ability to generalize across multiple languages. is highlights their robustness in detecting CTCs within security systems,regardless of the language or cultural context of the data.In contrast,the DeepForest model produced F1-scores ranging from 86%to 87%across the same datasets,further con rming its e ectiveness in CTC detection.Although other algorithms also showed reasonable accuracy,the LSTM and RNN models consistently outperformed them in multilingual settings,suggesting that deep learning models might be better suited for this particular problem.
