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
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
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
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
To explore the best preparation process for terminal blend(TB)composite-modified asphalt and to filter its formulation with excellent performance,this study evaluates the performance of TB composite modified asphalt b...To explore the best preparation process for terminal blend(TB)composite-modified asphalt and to filter its formulation with excellent performance,this study evaluates the performance of TB composite modified asphalt by physical property index,microscopic morphology,rheological testing,and infrared spectroscopy on multiple scales.The results show that the best preparation process for TB-modified asphalt is stirring at 260℃ for 4 h at 400 rpm,which significantly reduces the modification time of the asphalt.From a physical property viewpoint,the TB composite-modified asphalt sample with 5% styrene-butadiene-styrene(SBS)+1% aromatics+0.1% sulfur exhibits high-comprehensive,high-and low-temperature properties.More-over,its crosslinked mesh structure comprises black rubber particles uniformly interwoven in the middle,which further enhances the performance of the asphalt and results in an excellent performance formulation.In addition,the sample with 5%SBS content has a higher G*value and smaller δ value than that with 3%SBS content,indicating that its high-temperature resistance is improved.The effect of adding 3%SBS content on the viscoelastic ratio is,to some extent,less than that caused by 20% rubber powder.展开更多
High entropy alloys(HEAs)have recently attracted significant attention due to their exceptional mechanical properties and potential applications across various fields.Friction stir welding and processing(FSW/P),as not...High entropy alloys(HEAs)have recently attracted significant attention due to their exceptional mechanical properties and potential applications across various fields.Friction stir welding and processing(FSW/P),as notable solid-state welding and processing techniques,have been proved effectiveness in enhancing microstructures and mechanical properties of HEAs.This review article summarizes the current status of FSW/P of HEAs.The welding materials and conditions used for FSW/P in HEAs are reviewed and discussed.The effects of FSW/P on the evolutions of grain structure,texture,dislocation,and secondary phase for different HEAs are highlighted.Furthermore,the influences of FSW/P on the mechanical properties of various HEAs are analyzed.Finally,potential applications,challenges,and future directions of FSW/P in HEAs are forecasted.Overall,FSW/P enable to refine grains of HEAs through dynamic recrystallization and to activate diverse deformation mechanisms of HEAs through tailoring phase structures,thereby significantly improving the strength,hardness,and ductility of both single-and dual-phase HEAs.Future progress in this field will rely on comprehensive optimization of processing parameters and alloy composition,integration of multi-scale modeling with advanced characterization for in-depth exploration of microstructural mechanisms,systematic evaluation of functional properties,and effective bridging of the gap between laboratory research and industrial application.The review aims to provide an overview of recent advancements in the FSW/P of HEAs and encourage further research in this area.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
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
In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in...In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in real time by drawing bounding boxes around them.These bounding boxes are subsequently passed to a YOLOv11 classification model,which analyzes cropped images and assigns class labels.An additional counting module automatically tallies the detected fruits,offering a near-instantaneous estimation of quantity.The experimental results suggest high precision and recall for detection,high classification accuracy(across 15 classes),and near-perfect counting in real time.This paper presents a multi-stage pipeline for date fruit detection,classification,and automated counting,employing YOLOv11-based models to achieve high accuracy while maintaining real-time throughput.The results demonstrated that the detection precision exceeded 90%,the classification accuracy approached 92%,and the counting module correlated closely with the manual tallies.These findings confirm the potential of reducing manual labour and enhancing operational efficiency in post-harvesting processes.Future studies will include dataset expansion,user-centric interfaces,and integration with harvesting robotics.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
This paper presents a fault diagnosis method for process faults and sensor faults in a class of nonlinear uncertain systems.The fault detection and isolation architecture consists of a fault detection estimator and a ...This paper presents a fault diagnosis method for process faults and sensor faults in a class of nonlinear uncertain systems.The fault detection and isolation architecture consists of a fault detection estimator and a bank of adaptive isolation estimators,each corresponding to a particular fault type.Adaptive thresholds for fault detection and isolation are presented.Fault detectability conditions characterizing the class of process faults and sensor faults that are detectable by the presented method are derived.A simulation example of robotic arm is used to illustrate the effectiveness of the fault diagnosis method.展开更多
Abstract The Nansha ultra-crust layer-block is confined by ultra-crustal boundary faults of distinctive features, bordering the Kangtai-Shuangzi-Xiongnan extensional faulted zone on the north, the Baxian-Baram-Yoca-Cu...Abstract The Nansha ultra-crust layer-block is confined by ultra-crustal boundary faults of distinctive features, bordering the Kangtai-Shuangzi-Xiongnan extensional faulted zone on the north, the Baxian-Baram-Yoca-Cuyo nappe faulted zone on the south, the Wan'an-Natuna strike-slip tensional faulted zone on the west and the Mondoro-Panay strike-slip compressive faulted zone on the east. These faults take the top of the Nansha asthenosphere as their common detachmental surface. The Cenozoic dynamic process of the ultra-crust layer-block can be divided into four stages: K2-E21, during which the northern boundary faults extended, this ultra-crust layer-block was separated from the South China-Indosinian continental margin, the Palaeo-South China Sea subducted southwards and the Sibu accretion wedge was formed; E22-E31, during which the Southwest sub-sea basin extended and orogeny was active due to the collision of the Sibu accretion wedge; E32-N11, during which the central sub-sea basin extended, the Miri accretion wedge was formed and “A-type” subduction of the southern margin of the north Balawan occurred; N12-the present, during which large-scale thrusting and napping of the boundary faults in the south and mountain-building have taken place and the South China Sea stopped its extension.展开更多
To understand precursory phenomena before seismic fault sliP,this work focuses onearthquake nucleation process on a fault plane through numerical simulation.Rate and statedependent friction law with variable normal st...To understand precursory phenomena before seismic fault sliP,this work focuses onearthquake nucleation process on a fault plane through numerical simulation.Rate and statedependent friction law with variable normal stress is employed in the analysis.The resultsshow that in the late stage of nucleation process:(1)The maximum slip velocity ismonotonically accelerating;(2)The slipping hot spot(where the slip rate is maximum)migrates spontaneously from a certain instant,and such migration is spatially continuous;(3)When the maximum velocity reaches a detectable order of magnitude(at least one orderof magnitude greater than the loading rate),the remaining time is 20 hours or longer,andthe temporal variation of slip velocity beyond this point may be used as a precursoryindicator;(4)The average slip velocity is related to the remaining time by a log-log linearrelation,which means that a similar relation between rate of microseismicity and remainingtime may also exist;(5)when normal stress variation is taken展开更多
It is important to understand the process of multiphase carbon dioxide(CO_(2))leakage in faults for the risk assessment of carbon capture and storage(CCS).To quantitatively characterize the CO_(2)leakage process in th...It is important to understand the process of multiphase carbon dioxide(CO_(2))leakage in faults for the risk assessment of carbon capture and storage(CCS).To quantitatively characterize the CO_(2)leakage process in the fault,pressure sensors,fiber Bragg grating(FBG)temperature and strain sensors were simultaneously used to monitor CO_(2)leakage in the fault.Ten experiments were carried out,including five groups of gaseous CO_(2)leakage tests with initial pressures of 1-5 MPa and five groups of liquid CO_(2)leakage tests with initial pressures of 6-10 MPa.The results indicate that when liquid CO_(2)leaked with an initial pressure of 7-10 MPa,the pressure and temperature of CO_(2)dropped rapidly in the first few seconds and then remained unchanged.The behavior that CO_(2)continues to leak while maintaining temperature and pressure unchanged is defined as“temporary pseudo-sealing(TPS)”behavior,which continues for the first 1/3 of the leakage period.However,this TPS behavior did not occur in gaseous CO_(2)leakage.If only the pressure and temperature data were used to evaluate whether CO_(2)leakage occurred,we would misjudge the risk of leakage in CCS projects during the TPS period.The causes and conditions of TPS behavior were further studied experimentally.The results show that:(1)TPS behavior is caused by the phase transition energy generated when liquid CO_(2)leaks.(2)The condition for TPS behavior is a small leak aperture(0.2 mm).Only a small leakage rate can make the phase transition energy and pressure change from a dynamic equilibrium,and(3)The compression zone caused by the Bernoulli effect and fault“barrier”could reduce the CO_(2)leakage rate and further promote the occurrence of TPS behavior.This study provides technical and theoretical support for the quantitative characterization of the CO_(2)leakage process in faults of CCS projects.展开更多
Recent reports suggest that aging is not solely a physiological process in living beings;instead, it should be considered a pathological process or disease(Amorim et al., 2022). Consequently, this process involves a w...Recent reports suggest that aging is not solely a physiological process in living beings;instead, it should be considered a pathological process or disease(Amorim et al., 2022). Consequently, this process involves a wide range of factors, spanning from genetic to environmental factors, and even includes the gut microbiome(GM)(Mayer et al., 2022). All these processes coincide at some point in the inflammatory process, oxidative stress, and apoptosis, at different degrees in various organs and systems that constitute a living organism(Mayer et al., 2022;AguilarHernández et al., 2023).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.
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.
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 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Funded by the National Natural Science Foundation of China(No.52278446)。
文摘To explore the best preparation process for terminal blend(TB)composite-modified asphalt and to filter its formulation with excellent performance,this study evaluates the performance of TB composite modified asphalt by physical property index,microscopic morphology,rheological testing,and infrared spectroscopy on multiple scales.The results show that the best preparation process for TB-modified asphalt is stirring at 260℃ for 4 h at 400 rpm,which significantly reduces the modification time of the asphalt.From a physical property viewpoint,the TB composite-modified asphalt sample with 5% styrene-butadiene-styrene(SBS)+1% aromatics+0.1% sulfur exhibits high-comprehensive,high-and low-temperature properties.More-over,its crosslinked mesh structure comprises black rubber particles uniformly interwoven in the middle,which further enhances the performance of the asphalt and results in an excellent performance formulation.In addition,the sample with 5%SBS content has a higher G*value and smaller δ value than that with 3%SBS content,indicating that its high-temperature resistance is improved.The effect of adding 3%SBS content on the viscoelastic ratio is,to some extent,less than that caused by 20% rubber powder.
基金supported by National Natural Science Foundation of China(Grant No.52171032)Hebei Natural Science Foundation(Grant No.E2023501002)Fundamental Research Funds for the Central Universities(Grant No.2024GFYD003)。
文摘High entropy alloys(HEAs)have recently attracted significant attention due to their exceptional mechanical properties and potential applications across various fields.Friction stir welding and processing(FSW/P),as notable solid-state welding and processing techniques,have been proved effectiveness in enhancing microstructures and mechanical properties of HEAs.This review article summarizes the current status of FSW/P of HEAs.The welding materials and conditions used for FSW/P in HEAs are reviewed and discussed.The effects of FSW/P on the evolutions of grain structure,texture,dislocation,and secondary phase for different HEAs are highlighted.Furthermore,the influences of FSW/P on the mechanical properties of various HEAs are analyzed.Finally,potential applications,challenges,and future directions of FSW/P in HEAs are forecasted.Overall,FSW/P enable to refine grains of HEAs through dynamic recrystallization and to activate diverse deformation mechanisms of HEAs through tailoring phase structures,thereby significantly improving the strength,hardness,and ductility of both single-and dual-phase HEAs.Future progress in this field will rely on comprehensive optimization of processing parameters and alloy composition,integration of multi-scale modeling with advanced characterization for in-depth exploration of microstructural mechanisms,systematic evaluation of functional properties,and effective bridging of the gap between laboratory research and industrial application.The review aims to provide an overview of recent advancements in the FSW/P of HEAs and encourage further research in this area.
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%.
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 Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia,Grant No.KFU250098.
文摘In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in real time by drawing bounding boxes around them.These bounding boxes are subsequently passed to a YOLOv11 classification model,which analyzes cropped images and assigns class labels.An additional counting module automatically tallies the detected fruits,offering a near-instantaneous estimation of quantity.The experimental results suggest high precision and recall for detection,high classification accuracy(across 15 classes),and near-perfect counting in real time.This paper presents a multi-stage pipeline for date fruit detection,classification,and automated counting,employing YOLOv11-based models to achieve high accuracy while maintaining real-time throughput.The results demonstrated that the detection precision exceeded 90%,the classification accuracy approached 92%,and the counting module correlated closely with the manual tallies.These findings confirm the potential of reducing manual labour and enhancing operational efficiency in post-harvesting processes.Future studies will include dataset expansion,user-centric interfaces,and integration with harvesting robotics.
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.
文摘This paper presents a fault diagnosis method for process faults and sensor faults in a class of nonlinear uncertain systems.The fault detection and isolation architecture consists of a fault detection estimator and a bank of adaptive isolation estimators,each corresponding to a particular fault type.Adaptive thresholds for fault detection and isolation are presented.Fault detectability conditions characterizing the class of process faults and sensor faults that are detectable by the presented method are derived.A simulation example of robotic arm is used to illustrate the effectiveness of the fault diagnosis method.
文摘Abstract The Nansha ultra-crust layer-block is confined by ultra-crustal boundary faults of distinctive features, bordering the Kangtai-Shuangzi-Xiongnan extensional faulted zone on the north, the Baxian-Baram-Yoca-Cuyo nappe faulted zone on the south, the Wan'an-Natuna strike-slip tensional faulted zone on the west and the Mondoro-Panay strike-slip compressive faulted zone on the east. These faults take the top of the Nansha asthenosphere as their common detachmental surface. The Cenozoic dynamic process of the ultra-crust layer-block can be divided into four stages: K2-E21, during which the northern boundary faults extended, this ultra-crust layer-block was separated from the South China-Indosinian continental margin, the Palaeo-South China Sea subducted southwards and the Sibu accretion wedge was formed; E22-E31, during which the Southwest sub-sea basin extended and orogeny was active due to the collision of the Sibu accretion wedge; E32-N11, during which the central sub-sea basin extended, the Miri accretion wedge was formed and “A-type” subduction of the southern margin of the north Balawan occurred; N12-the present, during which large-scale thrusting and napping of the boundary faults in the south and mountain-building have taken place and the South China Sea stopped its extension.
基金The research was supported by State Key Basic Science Research Project under Grant No.G1998040704 and by China Seismological Bureau, the 9th Five-year Key Research Project under the contract No. 95-04-03-02-02.
文摘To understand precursory phenomena before seismic fault sliP,this work focuses onearthquake nucleation process on a fault plane through numerical simulation.Rate and statedependent friction law with variable normal stress is employed in the analysis.The resultsshow that in the late stage of nucleation process:(1)The maximum slip velocity ismonotonically accelerating;(2)The slipping hot spot(where the slip rate is maximum)migrates spontaneously from a certain instant,and such migration is spatially continuous;(3)When the maximum velocity reaches a detectable order of magnitude(at least one orderof magnitude greater than the loading rate),the remaining time is 20 hours or longer,andthe temporal variation of slip velocity beyond this point may be used as a precursoryindicator;(4)The average slip velocity is related to the remaining time by a log-log linearrelation,which means that a similar relation between rate of microseismicity and remainingtime may also exist;(5)when normal stress variation is taken
基金The research was partially supported by the Major Project of Inner Mongolia Science and Technology(Grant No.2021ZD0034)the National Natural Science Foundation of China(Grant Nos.41872210 and 41274111)The equipment and methodology we have developed for this research have applied for a national invention patent(ZL 202110708668.1).
文摘It is important to understand the process of multiphase carbon dioxide(CO_(2))leakage in faults for the risk assessment of carbon capture and storage(CCS).To quantitatively characterize the CO_(2)leakage process in the fault,pressure sensors,fiber Bragg grating(FBG)temperature and strain sensors were simultaneously used to monitor CO_(2)leakage in the fault.Ten experiments were carried out,including five groups of gaseous CO_(2)leakage tests with initial pressures of 1-5 MPa and five groups of liquid CO_(2)leakage tests with initial pressures of 6-10 MPa.The results indicate that when liquid CO_(2)leaked with an initial pressure of 7-10 MPa,the pressure and temperature of CO_(2)dropped rapidly in the first few seconds and then remained unchanged.The behavior that CO_(2)continues to leak while maintaining temperature and pressure unchanged is defined as“temporary pseudo-sealing(TPS)”behavior,which continues for the first 1/3 of the leakage period.However,this TPS behavior did not occur in gaseous CO_(2)leakage.If only the pressure and temperature data were used to evaluate whether CO_(2)leakage occurred,we would misjudge the risk of leakage in CCS projects during the TPS period.The causes and conditions of TPS behavior were further studied experimentally.The results show that:(1)TPS behavior is caused by the phase transition energy generated when liquid CO_(2)leaks.(2)The condition for TPS behavior is a small leak aperture(0.2 mm).Only a small leakage rate can make the phase transition energy and pressure change from a dynamic equilibrium,and(3)The compression zone caused by the Bernoulli effect and fault“barrier”could reduce the CO_(2)leakage rate and further promote the occurrence of TPS behavior.This study provides technical and theoretical support for the quantitative characterization of the CO_(2)leakage process in faults of CCS projects.
基金funded by CONAHCYT grant(252808)to GFCONAHCYT’s“Estancias Posdoctorales por México”program(662350)to HTB。
文摘Recent reports suggest that aging is not solely a physiological process in living beings;instead, it should be considered a pathological process or disease(Amorim et al., 2022). Consequently, this process involves a wide range of factors, spanning from genetic to environmental factors, and even includes the gut microbiome(GM)(Mayer et al., 2022). All these processes coincide at some point in the inflammatory process, oxidative stress, and apoptosis, at different degrees in various organs and systems that constitute a living organism(Mayer et al., 2022;AguilarHernández et al., 2023).
