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
In the ultra-deep strata of the Tarim Basin,the vertical growth process of strike-slip faults remains unclear,and the vertical distribution of fractured-cavity carbonate reservoirs is complex.This paper investigates t...In the ultra-deep strata of the Tarim Basin,the vertical growth process of strike-slip faults remains unclear,and the vertical distribution of fractured-cavity carbonate reservoirs is complex.This paper investigates the vertical growth process of strike-slip faults through field outcrop observations in the Keping area,interpretation of seismic data from the Fuman Oilfield,Tarim Basim,NW China,and structural physical simulation experiments.The results are obtained mainly in four aspects.First,field outcrops and ultra-deep seismic profiles indicate a three-layer structure within the strike-slip fault,consisting of fault core,fracture zone and primary rock.The fault core can be classified into three parts vertically:fracture-cavity unit,fault clay and breccia zone.The distribution of fracture-cavity units demonstrates a distinct pattern of vertical stratification,owing to the structural characteristics and growth process of the slip-strike fault.Second,the ultra-deep seismic profiles show multiple fracture-cavity units in the strike-slip fault zone.These units can be classified into four types:top fractured,middle connected,deep terminated,and intra-layer fractured.Third,structural physical simulation experiments and ultra-deep seismic data interpretation reveal that the strike-slip faults have evolved vertically in three stages:segmental rupture,vertical growth,and connection and extension.The particle image velocimetry detection demonstrates that the initial fracture of the fault zone occurred at the top or bottom and then evolved into cavities gradually along with the fault growth,accompanied by the emergence of new fractures in the middle part of the strata,which subsequently connected with the deep and shallow cavities to form a complete fault zone.Fourth,the ultra-deep carbonate strata primarily develop three types of fractured-cavity reservoirs:flower-shaped fracture,large and deep fault and staggered overlap.The first two types are larger in size with better reservoir conditions,suggesting a significant exploration potential.展开更多
The operational readiness test(ORT),like weapon testing before firing,is becoming more and more important for systems used in the field.However,the test requirement of the ORT is distinctive.Specifically,the rule of s...The operational readiness test(ORT),like weapon testing before firing,is becoming more and more important for systems used in the field.However,the test requirement of the ORT is distinctive.Specifically,the rule of selecting test items should be changed in different test turns,and whether there is a fault is more important than where the fault is.The popular dependency matrix(D-matrix)processing algorithms becomes low efficient because they cannot change their optimizing direc-tion and spend unnecessary time on fault localization and isola-tion.To this end,this paper proposes a D-matrix processing algorithm named piecewise heuristic algorithm for D-matrix(PHAD).Its key idea is to use a piecewise function comprised of multiple different functions instead of the commonly used fixed function and switch subfunctions according to the test stage.In this manner,PHAD has the capability of changing optimizing direction,precisely matching the variant test requirements,and generating an efficient test sequence.The experiments on the random matrixes of different sizes and densities prove that the proposed algorithm performs better than the classical algo-rithms in terms of expected test cost(ETC)and other metrics.More generally,the piecewise heuristic function shows a new way to design D-matrix processing algorithm and a more flexi-ble heuristic function to meet more complicated test requirements.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 significant,novel,and high-impact research in the fields 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
With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance s...With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.展开更多
The in-flight heating process of cerium dioxide(CeO_(2))powders was investigated through experiments and numerical simulations.In the experiment,CeO_(2)powder(average size of 30μm)was injected into radio-frequency(RF...The in-flight heating process of cerium dioxide(CeO_(2))powders was investigated through experiments and numerical simulations.In the experiment,CeO_(2)powder(average size of 30μm)was injected into radio-frequency(RF)argon plasma,and the temperatures were measured using a DPV-2000 monitor.A model combining the electromagnetism,thermal flow,and heat transfer characteristics of powder during in-flight heating in argon plasma was proposed.The melting processes of CeO_(2)powders of different diameters,with and without thermal resistance effect,were investigated.Results show that the heating process of CeO_(2)powder particles consists of three main stages,one of which is relevant to a dimensionless parameter known as the Biot number.When the Biot value≥0.1,thermal resistance increases significantly,especially for the larger powders.The predicted temperature of the particles at the outlet(1800–2880 K)is in good agreement with the experimental result.展开更多
The hot compression deformation behavior of Mg-6Zn-1Mn-0.5Ca(ZM61-0.5Ca)and Mg-6Zn-1Mn-2Sn-0.5Ca(ZMT612-0.5Ca)alloys was investigated at deformation temperatures ranging from 250℃to 400℃and strain rates varying from...The hot compression deformation behavior of Mg-6Zn-1Mn-0.5Ca(ZM61-0.5Ca)and Mg-6Zn-1Mn-2Sn-0.5Ca(ZMT612-0.5Ca)alloys was investigated at deformation temperatures ranging from 250℃to 400℃and strain rates varying from 0.001 s^(-1) to 1 s^(-1).The results show that the addition of Sn promotes dynamic recrystallization(DRX),and CaMgSn phases can act as nucleation sites during the compression deformation.Flow stress increases with increasing the strain rate and decreasing the temperature.Both the ZM61-0.5Ca and ZMT612-0.5Ca alloys exhibit obvious DRX characteristics.CaMgSn phases can effectively inhibit dislocation motion with the addition of Sn,thus increasing the peak fl ow stress of the alloy.The addition of Sn increases the hot deformation activation energy of the ZM61-0.5Ca alloy from 199.654 kJ/mol to 276.649 kJ/mol,thus improving the thermal stability of the alloy.For the ZMT612-0.5Ca alloy,the optimal hot deformation parameters are determined to be a deformation temperature range of 350–400℃and a strain rate range of 0.001–0.01 s^(-1).展开更多
Refractory metals,including tungsten(W),tantalum(Ta),molybdenum(Mo),and niobium(Nb),play a vital role in industries,such as nuclear energy and aerospace,owing to their exceptional melting temperatures,thermal durabili...Refractory metals,including tungsten(W),tantalum(Ta),molybdenum(Mo),and niobium(Nb),play a vital role in industries,such as nuclear energy and aerospace,owing to their exceptional melting temperatures,thermal durability,and corrosion resistance.These metals have body-centered cubic crystal structure,characterized by limited slip systems and impeded dislocation motion,resulting in significant low-temperature brittleness,which poses challenges for the conventional processing.Additive manufacturing technique provides an innovative approach,enabling the production of intricate parts without molds,which significantly improves the efficiency of material usage.This review provides a comprehensive overview of the advancements in additive manufacturing techniques for the production of refractory metals,such as W,Ta,Mo,and Nb,particularly the laser powder bed fusion.In this review,the influence mechanisms of key process parameters(laser power,scan strategy,and powder characteristics)on the evolution of material microstructure,the formation of metallurgical defects,and mechanical properties were discussed.Generally,optimizing powder characteristics,such as sphericity,implementing substrate preheating,and formulating alloying strategies can significantly improve the densification and crack resistance of manufactured parts.Meanwhile,strictly controlling the oxygen impurity content and optimizing the energy density input are also the key factors to achieve the simultaneous improvement in strength and ductility of refractory metals.Although additive manufacturing technique provides an innovative solution for processing refractory metals,critical issues,such as residual stress control,microstructure and performance anisotropy,and process stability,still need to be addressed.This review not only provides a theoretical basis for the additive manufacturing of high-performance refractory metals,but also proposes forward-looking directions for their industrial application.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
Digital twin technology brings more opportunities and challenges to chemical engineering in both academic and industry.A complex process could have multiple digitalization needs,including simulation,monitoring,operato...Digital twin technology brings more opportunities and challenges to chemical engineering in both academic and industry.A complex process could have multiple digitalization needs,including simulation,monitoring,operator training,etc.;thus,a hierarchical digital twin would be a comprehensive solution to that.In this study,a novel and general framework of the digital twin is proposed for operations in process industry.With the hierarchical structure,the framework can handle various tasks driven by different roles in process industry,including managers,engineers,and operators.To complete these tasks,the framework consists of three modules:OAS(Operation Analysis System),OMS(Operation Monitoring System),and OTS(Operator Training System).Each module focuses on one unique type of demand from the staff,as well as interactions among them enabling efficient data sharing.Based on the hierarchical framework,a digital twin system is applied for one complex industrial nitration process,which successfully enhances the operation efficiency and safety in several industrial scenarios with different demands.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
Knowledge graphs,which combine structured representation with semantic modeling,have shown great potential in knowledge expression,causal inference,and automated reasoning,and are widely used in fields such as intelli...Knowledge graphs,which combine structured representation with semantic modeling,have shown great potential in knowledge expression,causal inference,and automated reasoning,and are widely used in fields such as intelligent question answering,decision support,and fault diagnosis.As high-speed train systems become increasingly intelligent and interconnected,fault patterns have grown more complex and dynamic.Knowledge graphs offer a promising solution to support the structured management and real-time reasoning of fault knowledge,addressing key requirements such as interpretability,accuracy,and continuous evolution in intelligent diagnostic systems.However,conventional knowledge graph construction relies heavily on domain expertise and specialized tools,resulting in high entry barriers for non-experts and limiting their practical application in frontline maintenance scenarios.To address this limitation,this paper proposes a fault knowledge modeling approach for high-speed trains that integrates structured logic diagrams with knowledge graphs.The method employs a seven-layer logic structure—comprising fault name,applicable vehicles,diagnostic logic,signal parameters,verification conditions,fault causes,and emergency measures—to transform unstructured knowledge into a visual and hierarchical representation.A semantic mapping mechanism is then used to automatically convert logic diagrams into machine-interpretable knowledge graphs,enabling dynamic reasoning and knowledge reuse.Furthermore,the proposed method establishes a three-layer architecture—logic structuring,knowledge graph transformation,and dynamic inference—to bridge human-expert logic with machinebased reasoning.Experimental validation and system implementation demonstrate that this approach not only improves knowledge interpretability and inference precision but also significantly enhances modeling efficiency and system maintainability.It provides a scalable and adaptable solution for intelligent operation and maintenance platforms in the high-speed rail domain.展开更多
This study investigated the effects of xu-argument-based continuation writing on learners’processing of source texts.Seventy-five participants were randomly assigned to three conditions:(1)continuation writing,(2)sum...This study investigated the effects of xu-argument-based continuation writing on learners’processing of source texts.Seventy-five participants were randomly assigned to three conditions:(1)continuation writing,(2)summary writing,or(3)reading comprehension.Eye-tracking data were collected during reading,measuring early(first fixation duration,first pass duration)and late(go-past time,total fixation duration)eye movements.During writing,source-text rereading was tracked via fixation counts and durations.Results showed that task type did not affect initial lexical access,as first fixation duration showed no group differences.However,both production groups exhibited significantly longer first pass durations than the reading comprehension group.Late measures revealed a gradient pattern:the continuation writing group spent significantly longer gopast time and total fixation duration than the summary writing group,which exceeded the reading comprehension group.This indicates that continuation tasks promoted deeper cognitive engagement during reading.During writing,the continuation writing group spent more time rereading the source text with higher fixation counts than the summary writing group.These findings suggest that continuation writing triggers more intensive reader-text interaction during pre-writing and enhances comprehension-production coupling through sustained attention to input during writing.This study sheds light on the cognitive mechanisms underlying the theoretical and pedagogical value of xu-argument.展开更多
Suancai has a lengthy history and a wide range of categories,which has some influence on the pickled diet culture around the world.Suancai production is transitioning to a large-scale,standardized production due to th...Suancai has a lengthy history and a wide range of categories,which has some influence on the pickled diet culture around the world.Suancai production is transitioning to a large-scale,standardized production due to the growth of the market.It has a unique flavor and is rich in nutrients,and its abundance of free amino acids,vitamins and phenolics has many positive effects on the human body.This review gives the types and history of suancai,as well as its impact on the world’s pickled culture.The changes in nutritional composition and flavor of suancai during fermentation are summarized.It presented the production technology and influencing factors of the northeast suancai,examined the quality and safety issues in suancai,and put forth some ideas and opinions on the standardization development of the suancai industry.It also summarized the geographic distribution and flora diversity of pickles around the world.In order to provide some knowledge and guidance for the promotion of modern industrial production in the suancai industry.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
Dynamic melt modification of polyethylene via the direct grafting of peroxide fragments shows promise for the development of processable functionalized materials.In this study,four linear low-density polyethylenes(LLD...Dynamic melt modification of polyethylene via the direct grafting of peroxide fragments shows promise for the development of processable functionalized materials.In this study,four linear low-density polyethylenes(LLDPEs)with comparable molecular weights but different short-chain branch(SCB)contents(ranging of 5-66 per 1000 carbon atoms)were modified via dynamic melt mixing using 2 wt% benzoyl peroxide at 145℃ and 50 r/min for 30 min.The influence of SCB content on the processability and structure of the resulting products was systematically investigated.All modified products exhibited good melt processability with melt flow rates(MFR)ranging from 0.46 g/10min to 1.07 g/10min.Products derived from low-SCB LLDPEs showed a lower MFR,higher cross-linking content,a larger number of long-chain branches,and a higher degree of benzoyl grafting.In contrast,those produced from high-SCB LLDPEs exhibited improved processability,reduced cross-linking,fewer long-chain branches,and lower benzoyl grafting levels.A detailed structural investigation of the soluble and insoluble fractions,which were separated using trichlorobenzene fractionation,was conducted to analyze the structural features of various modified products and demonstrate that the SCB content(i.e.,tertiary carbon density)significantly influences radical coupling during dynamic modification.Elevated tertiary carbon density,by introducing greater steric hindrance,suppresses radical coupling during dynamic modification,thereby reducing the efficiency of both crosslinking and peroxide fragment grafting.These findings provide new insights into the structure-reactivity relationships in peroxide-induced polyethylene modification and lay the foundation for tailoring material properties via dynamic processing.展开更多
Business Process Modelling(BPM)is essential for analyzing,improving,and automating the flow of information within organizations,but traditional approaches based on manual interpretation are slow,error-prone,and requir...Business Process Modelling(BPM)is essential for analyzing,improving,and automating the flow of information within organizations,but traditional approaches based on manual interpretation are slow,error-prone,and require a high level of expertise.This article proposes an innovative alternative solution that overcomes these limitations by automatically generating comprehensive Business Process Modelling and Notation(BPMN)diagrams solely from verbal descriptions of the processes to be modeled,utilizing Large Language Models(LLMs)and multimodal Artificial Intelligence(AI).Experimental results,based on video recordings of process explanations provided by an expert from an organization(in this case,the Commercial Courts of a public justice administration),demonstrate that the proposed methodology successfully enables the automatic generation of complete and accurate BPMN diagrams,leading to significant improvements in the speed,accuracy,and accessibility of process modeling.This research makes a substantial contribution to the field of business process modeling,as its methodology is groundbreaking in its use of LLMs and multimodal AI capabilities to handle different types of source material(text and video),combining several tools to minimize the number of queries and reduce the complexity of the prompts required for the automatic generation of successful BPMN diagrams.展开更多
While injection-induced seismicity has been widely studied,its implications for CO_(2)geological storage require reevaluation due to distinct fluid-rock interactions.This study develops a coupled hydromechanical model...While injection-induced seismicity has been widely studied,its implications for CO_(2)geological storage require reevaluation due to distinct fluid-rock interactions.This study develops a coupled hydromechanical model incorporating rate-and-state friction laws to investigate fault reactivation mechanisms during early-stage CO_(2)injection.The competing effects of pore pressure diffusion and fluid pressurization are systematically investigated,considering three key factors:permeability variations within fault damage zones,normal stress variation coefficients,and injection parameters.Numerical simulations reveal that slower CO_(2)migration causes limited pressure perturbation(<0.3 MPa over 15 d)compared to single-phase fluid injection.Fluid pressurization enhances fault strength and delays reactivation,though this stabilizing effect diminishes in low-permeability damage zones.Highly permeable damage zones promote larger rupture areas despite strengthening from pressurization,as reduced effective stress accelerates failure.Paradoxically,while fluid pressurization increases fault strength,it simultaneously elevates seismic risk through amplified stress drops during slip events.Temporal analysis shows that fluid pressurization dominates initial fault response,while sustained pore pressure diffusion ultimately drives reactivation.Increased normal stress variation coefficients and injection rates accelerate localized rupture initiation but restrict propagation due to non-critically stressed states.This discrepancy demonstrates that regions with positive Coulomb failure stress changes do not correlate well with actual slip zones.These findings highlight the critical interplay between transient pressurization effects and progressive pressure diffusion during early CO_(2)injection phases,providing crucial insights for seismic risk management in CO_(2)storage projects.展开更多
Partial least squares (PLS) model maximizes the covariance between process variables and quality variables,making it widely used in quality-related fault detection.However,traditional PLS methods focus primarily on li...Partial least squares (PLS) model maximizes the covariance between process variables and quality variables,making it widely used in quality-related fault detection.However,traditional PLS methods focus primarily on linear processes,leading to poor performance in dynamic nonlinear processes.In this paper,a novel quality-related fault detection method,named DiCAE-PLS,is developed by combining dynamic-inner convolutional autoencoder with PLS.In the proposed DiCAE-PLS method,latent features are first extracted through dynamic-inner convolutional autoencoder (DiCAE) to capture process dynamics and nonlinearity from process variables.Then,a PLS model is established to build the relationship between the extracted latent features and the final product quality.To detect quality-related faults,Hotelling's T^(2) statistic is employed.The developed quality-related fault detection is applied to the widely used industrial benchmark of the Tennessee.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”。
基金Supported by the National Natural Science Foundation of China(42362026)Key R&D Project of Xinjiang Uygur Autonomous Region(2024B01015).
文摘In the ultra-deep strata of the Tarim Basin,the vertical growth process of strike-slip faults remains unclear,and the vertical distribution of fractured-cavity carbonate reservoirs is complex.This paper investigates the vertical growth process of strike-slip faults through field outcrop observations in the Keping area,interpretation of seismic data from the Fuman Oilfield,Tarim Basim,NW China,and structural physical simulation experiments.The results are obtained mainly in four aspects.First,field outcrops and ultra-deep seismic profiles indicate a three-layer structure within the strike-slip fault,consisting of fault core,fracture zone and primary rock.The fault core can be classified into three parts vertically:fracture-cavity unit,fault clay and breccia zone.The distribution of fracture-cavity units demonstrates a distinct pattern of vertical stratification,owing to the structural characteristics and growth process of the slip-strike fault.Second,the ultra-deep seismic profiles show multiple fracture-cavity units in the strike-slip fault zone.These units can be classified into four types:top fractured,middle connected,deep terminated,and intra-layer fractured.Third,structural physical simulation experiments and ultra-deep seismic data interpretation reveal that the strike-slip faults have evolved vertically in three stages:segmental rupture,vertical growth,and connection and extension.The particle image velocimetry detection demonstrates that the initial fracture of the fault zone occurred at the top or bottom and then evolved into cavities gradually along with the fault growth,accompanied by the emergence of new fractures in the middle part of the strata,which subsequently connected with the deep and shallow cavities to form a complete fault zone.Fourth,the ultra-deep carbonate strata primarily develop three types of fractured-cavity reservoirs:flower-shaped fracture,large and deep fault and staggered overlap.The first two types are larger in size with better reservoir conditions,suggesting a significant exploration potential.
文摘The operational readiness test(ORT),like weapon testing before firing,is becoming more and more important for systems used in the field.However,the test requirement of the ORT is distinctive.Specifically,the rule of selecting test items should be changed in different test turns,and whether there is a fault is more important than where the fault is.The popular dependency matrix(D-matrix)processing algorithms becomes low efficient because they cannot change their optimizing direc-tion and spend unnecessary time on fault localization and isola-tion.To this end,this paper proposes a D-matrix processing algorithm named piecewise heuristic algorithm for D-matrix(PHAD).Its key idea is to use a piecewise function comprised of multiple different functions instead of the commonly used fixed function and switch subfunctions according to the test stage.In this manner,PHAD has the capability of changing optimizing direction,precisely matching the variant test requirements,and generating an efficient test sequence.The experiments on the random matrixes of different sizes and densities prove that the proposed algorithm performs better than the classical algo-rithms in terms of expected test cost(ETC)and other metrics.More generally,the piecewise heuristic function shows a new way to design D-matrix processing algorithm and a more flexi-ble heuristic function to meet more complicated test requirements.
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 significant,novel,and high-impact research in the fields 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funded by scientific research projects under Grant JY2024B011.
文摘With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.
基金National Natural Science Foundation of China(11875039)Shanxi Scholarship Council of China(2023-033)+2 种基金Fundamental Research Program of Shanxi Province(202303021221071)China Baowu Low Carbon Metallurgical Innovation Foundation(2022)2023 Anhui Major Industrial Innovation Plan Project。
文摘The in-flight heating process of cerium dioxide(CeO_(2))powders was investigated through experiments and numerical simulations.In the experiment,CeO_(2)powder(average size of 30μm)was injected into radio-frequency(RF)argon plasma,and the temperatures were measured using a DPV-2000 monitor.A model combining the electromagnetism,thermal flow,and heat transfer characteristics of powder during in-flight heating in argon plasma was proposed.The melting processes of CeO_(2)powders of different diameters,with and without thermal resistance effect,were investigated.Results show that the heating process of CeO_(2)powder particles consists of three main stages,one of which is relevant to a dimensionless parameter known as the Biot number.When the Biot value≥0.1,thermal resistance increases significantly,especially for the larger powders.The predicted temperature of the particles at the outlet(1800–2880 K)is in good agreement with the experimental result.
基金Sichuan Science and Technology Program(2025ZNSFSC1341)Fundamental Research Funds for the Central Universities(J2022-090,25CAFUC04087)。
文摘The hot compression deformation behavior of Mg-6Zn-1Mn-0.5Ca(ZM61-0.5Ca)and Mg-6Zn-1Mn-2Sn-0.5Ca(ZMT612-0.5Ca)alloys was investigated at deformation temperatures ranging from 250℃to 400℃and strain rates varying from 0.001 s^(-1) to 1 s^(-1).The results show that the addition of Sn promotes dynamic recrystallization(DRX),and CaMgSn phases can act as nucleation sites during the compression deformation.Flow stress increases with increasing the strain rate and decreasing the temperature.Both the ZM61-0.5Ca and ZMT612-0.5Ca alloys exhibit obvious DRX characteristics.CaMgSn phases can effectively inhibit dislocation motion with the addition of Sn,thus increasing the peak fl ow stress of the alloy.The addition of Sn increases the hot deformation activation energy of the ZM61-0.5Ca alloy from 199.654 kJ/mol to 276.649 kJ/mol,thus improving the thermal stability of the alloy.For the ZMT612-0.5Ca alloy,the optimal hot deformation parameters are determined to be a deformation temperature range of 350–400℃and a strain rate range of 0.001–0.01 s^(-1).
基金National MCF Energy R&D Program(2024YFE03260300)。
文摘Refractory metals,including tungsten(W),tantalum(Ta),molybdenum(Mo),and niobium(Nb),play a vital role in industries,such as nuclear energy and aerospace,owing to their exceptional melting temperatures,thermal durability,and corrosion resistance.These metals have body-centered cubic crystal structure,characterized by limited slip systems and impeded dislocation motion,resulting in significant low-temperature brittleness,which poses challenges for the conventional processing.Additive manufacturing technique provides an innovative approach,enabling the production of intricate parts without molds,which significantly improves the efficiency of material usage.This review provides a comprehensive overview of the advancements in additive manufacturing techniques for the production of refractory metals,such as W,Ta,Mo,and Nb,particularly the laser powder bed fusion.In this review,the influence mechanisms of key process parameters(laser power,scan strategy,and powder characteristics)on the evolution of material microstructure,the formation of metallurgical defects,and mechanical properties were discussed.Generally,optimizing powder characteristics,such as sphericity,implementing substrate preheating,and formulating alloying strategies can significantly improve the densification and crack resistance of manufactured parts.Meanwhile,strictly controlling the oxygen impurity content and optimizing the energy density input are also the key factors to achieve the simultaneous improvement in strength and ductility of refractory metals.Although additive manufacturing technique provides an innovative solution for processing refractory metals,critical issues,such as residual stress control,microstructure and performance anisotropy,and process stability,still need to be addressed.This review not only provides a theoretical basis for the additive manufacturing of high-performance refractory metals,but also proposes forward-looking directions for their industrial application.
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support of the“Pioneer”and“Leading Goose”Research&Development Program of Zhejiang(2024C01028)the State Key Laboratory of Industrial Control Technology,China(ICT2024C04)are gratefully acknowledged.
文摘Digital twin technology brings more opportunities and challenges to chemical engineering in both academic and industry.A complex process could have multiple digitalization needs,including simulation,monitoring,operator training,etc.;thus,a hierarchical digital twin would be a comprehensive solution to that.In this study,a novel and general framework of the digital twin is proposed for operations in process industry.With the hierarchical structure,the framework can handle various tasks driven by different roles in process industry,including managers,engineers,and operators.To complete these tasks,the framework consists of three modules:OAS(Operation Analysis System),OMS(Operation Monitoring System),and OTS(Operator Training System).Each module focuses on one unique type of demand from the staff,as well as interactions among them enabling efficient data sharing.Based on the hierarchical framework,a digital twin system is applied for one complex industrial nitration process,which successfully enhances the operation efficiency and safety in several industrial scenarios with different demands.
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.
基金support from the Scientific Funding for the Center of National Railway Intelligent Transportation System Engineering and Technology,China Academy of Railway Sciences Corporation Limited(Grant No.2023YJ354)。
文摘Knowledge graphs,which combine structured representation with semantic modeling,have shown great potential in knowledge expression,causal inference,and automated reasoning,and are widely used in fields such as intelligent question answering,decision support,and fault diagnosis.As high-speed train systems become increasingly intelligent and interconnected,fault patterns have grown more complex and dynamic.Knowledge graphs offer a promising solution to support the structured management and real-time reasoning of fault knowledge,addressing key requirements such as interpretability,accuracy,and continuous evolution in intelligent diagnostic systems.However,conventional knowledge graph construction relies heavily on domain expertise and specialized tools,resulting in high entry barriers for non-experts and limiting their practical application in frontline maintenance scenarios.To address this limitation,this paper proposes a fault knowledge modeling approach for high-speed trains that integrates structured logic diagrams with knowledge graphs.The method employs a seven-layer logic structure—comprising fault name,applicable vehicles,diagnostic logic,signal parameters,verification conditions,fault causes,and emergency measures—to transform unstructured knowledge into a visual and hierarchical representation.A semantic mapping mechanism is then used to automatically convert logic diagrams into machine-interpretable knowledge graphs,enabling dynamic reasoning and knowledge reuse.Furthermore,the proposed method establishes a three-layer architecture—logic structuring,knowledge graph transformation,and dynamic inference—to bridge human-expert logic with machinebased reasoning.Experimental validation and system implementation demonstrate that this approach not only improves knowledge interpretability and inference precision but also significantly enhances modeling efficiency and system maintainability.It provides a scalable and adaptable solution for intelligent operation and maintenance platforms in the high-speed rail domain.
文摘This study investigated the effects of xu-argument-based continuation writing on learners’processing of source texts.Seventy-five participants were randomly assigned to three conditions:(1)continuation writing,(2)summary writing,or(3)reading comprehension.Eye-tracking data were collected during reading,measuring early(first fixation duration,first pass duration)and late(go-past time,total fixation duration)eye movements.During writing,source-text rereading was tracked via fixation counts and durations.Results showed that task type did not affect initial lexical access,as first fixation duration showed no group differences.However,both production groups exhibited significantly longer first pass durations than the reading comprehension group.Late measures revealed a gradient pattern:the continuation writing group spent significantly longer gopast time and total fixation duration than the summary writing group,which exceeded the reading comprehension group.This indicates that continuation tasks promoted deeper cognitive engagement during reading.During writing,the continuation writing group spent more time rereading the source text with higher fixation counts than the summary writing group.These findings suggest that continuation writing triggers more intensive reader-text interaction during pre-writing and enhances comprehension-production coupling through sustained attention to input during writing.This study sheds light on the cognitive mechanisms underlying the theoretical and pedagogical value of xu-argument.
基金supported by the Foundation of National Dairy Technology Innovation Center(2022-Open Funding Project-12)Foundation of National Dairy Technology Innovation Center(2022-Scientific Research-9)+2 种基金Key Project of National Dairy Innovation Research Center of Inner Mongolia(2021-National Dairy Innovation Research Center-8)Key Projects of Research Operating Expenses of Provincial Research Institutes in Heilongjiang Province(CZKYF2021-2-B017)Key Project of Natural Science Foundation of Heilongjiang Province(ZD2022C007).
文摘Suancai has a lengthy history and a wide range of categories,which has some influence on the pickled diet culture around the world.Suancai production is transitioning to a large-scale,standardized production due to the growth of the market.It has a unique flavor and is rich in nutrients,and its abundance of free amino acids,vitamins and phenolics has many positive effects on the human body.This review gives the types and history of suancai,as well as its impact on the world’s pickled culture.The changes in nutritional composition and flavor of suancai during fermentation are summarized.It presented the production technology and influencing factors of the northeast suancai,examined the quality and safety issues in suancai,and put forth some ideas and opinions on the standardization development of the suancai industry.It also summarized the geographic distribution and flora diversity of pickles around the world.In order to provide some knowledge and guidance for the promotion of modern industrial production in the suancai industry.
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financially supported by the Science and Technology Project of PetroChina Company Limited,China(No.2022DJ6314)the National Natural Science Foundation of China(No.52173056)。
文摘Dynamic melt modification of polyethylene via the direct grafting of peroxide fragments shows promise for the development of processable functionalized materials.In this study,four linear low-density polyethylenes(LLDPEs)with comparable molecular weights but different short-chain branch(SCB)contents(ranging of 5-66 per 1000 carbon atoms)were modified via dynamic melt mixing using 2 wt% benzoyl peroxide at 145℃ and 50 r/min for 30 min.The influence of SCB content on the processability and structure of the resulting products was systematically investigated.All modified products exhibited good melt processability with melt flow rates(MFR)ranging from 0.46 g/10min to 1.07 g/10min.Products derived from low-SCB LLDPEs showed a lower MFR,higher cross-linking content,a larger number of long-chain branches,and a higher degree of benzoyl grafting.In contrast,those produced from high-SCB LLDPEs exhibited improved processability,reduced cross-linking,fewer long-chain branches,and lower benzoyl grafting levels.A detailed structural investigation of the soluble and insoluble fractions,which were separated using trichlorobenzene fractionation,was conducted to analyze the structural features of various modified products and demonstrate that the SCB content(i.e.,tertiary carbon density)significantly influences radical coupling during dynamic modification.Elevated tertiary carbon density,by introducing greater steric hindrance,suppresses radical coupling during dynamic modification,thereby reducing the efficiency of both crosslinking and peroxide fragment grafting.These findings provide new insights into the structure-reactivity relationships in peroxide-induced polyethylene modification and lay the foundation for tailoring material properties via dynamic processing.
基金funded by Fundación CajaCanarias and Fundación Bancaria“la Caixa”,grant number 2023DIG11.
文摘Business Process Modelling(BPM)is essential for analyzing,improving,and automating the flow of information within organizations,but traditional approaches based on manual interpretation are slow,error-prone,and require a high level of expertise.This article proposes an innovative alternative solution that overcomes these limitations by automatically generating comprehensive Business Process Modelling and Notation(BPMN)diagrams solely from verbal descriptions of the processes to be modeled,utilizing Large Language Models(LLMs)and multimodal Artificial Intelligence(AI).Experimental results,based on video recordings of process explanations provided by an expert from an organization(in this case,the Commercial Courts of a public justice administration),demonstrate that the proposed methodology successfully enables the automatic generation of complete and accurate BPMN diagrams,leading to significant improvements in the speed,accuracy,and accessibility of process modeling.This research makes a substantial contribution to the field of business process modeling,as its methodology is groundbreaking in its use of LLMs and multimodal AI capabilities to handle different types of source material(text and video),combining several tools to minimize the number of queries and reduce the complexity of the prompts required for the automatic generation of successful BPMN diagrams.
基金funded by Joint Funds of the National Natural Science Foundation of China(Grant No.U23A20671)the Major Project of Inner Mongolia Science and Technology(Grant No.2021ZD0034)the Creative Groups of Natural Science Foundation of Hubei Province,China(Grant No.2021CFA030).
文摘While injection-induced seismicity has been widely studied,its implications for CO_(2)geological storage require reevaluation due to distinct fluid-rock interactions.This study develops a coupled hydromechanical model incorporating rate-and-state friction laws to investigate fault reactivation mechanisms during early-stage CO_(2)injection.The competing effects of pore pressure diffusion and fluid pressurization are systematically investigated,considering three key factors:permeability variations within fault damage zones,normal stress variation coefficients,and injection parameters.Numerical simulations reveal that slower CO_(2)migration causes limited pressure perturbation(<0.3 MPa over 15 d)compared to single-phase fluid injection.Fluid pressurization enhances fault strength and delays reactivation,though this stabilizing effect diminishes in low-permeability damage zones.Highly permeable damage zones promote larger rupture areas despite strengthening from pressurization,as reduced effective stress accelerates failure.Paradoxically,while fluid pressurization increases fault strength,it simultaneously elevates seismic risk through amplified stress drops during slip events.Temporal analysis shows that fluid pressurization dominates initial fault response,while sustained pore pressure diffusion ultimately drives reactivation.Increased normal stress variation coefficients and injection rates accelerate localized rupture initiation but restrict propagation due to non-critically stressed states.This discrepancy demonstrates that regions with positive Coulomb failure stress changes do not correlate well with actual slip zones.These findings highlight the critical interplay between transient pressurization effects and progressive pressure diffusion during early CO_(2)injection phases,providing crucial insights for seismic risk management in CO_(2)storage projects.
基金supported in part by the National Natural Science Foundation of China(62573387)the Natural Science Foundation of Zhejiang province,China(LY24F030004)the Fundamental Research Funds of Zhejiang Sci-Tech University(25222139-Y).
文摘Partial least squares (PLS) model maximizes the covariance between process variables and quality variables,making it widely used in quality-related fault detection.However,traditional PLS methods focus primarily on linear processes,leading to poor performance in dynamic nonlinear processes.In this paper,a novel quality-related fault detection method,named DiCAE-PLS,is developed by combining dynamic-inner convolutional autoencoder with PLS.In the proposed DiCAE-PLS method,latent features are first extracted through dynamic-inner convolutional autoencoder (DiCAE) to capture process dynamics and nonlinearity from process variables.Then,a PLS model is established to build the relationship between the extracted latent features and the final product quality.To detect quality-related faults,Hotelling's T^(2) statistic is employed.The developed quality-related fault detection is applied to the widely used industrial benchmark of the Tennessee.
