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
This study investigates the fracture characteristics and the fracture process zone(FPZ)of mode I fracture in sandstone,aiming to analyze the propagation behaviors of mode I crack under different freeze-thaw cycles.Sem...This study investigates the fracture characteristics and the fracture process zone(FPZ)of mode I fracture in sandstone,aiming to analyze the propagation behaviors of mode I crack under different freeze-thaw cycles.Semicircular bending tests(SCB)were conducted using different freeze-thaw cycles to evaluate mode I fracture toughness,FPZ dynamics,and macroscopic microscopic features.Digital image correlation(DIC)and scanning electron microscopy(SEM)techniques were employed for detailed analysis.Experimental results reveal that freeze-thaw cycling leads to the widening of both preexisting and newly formed microcracks between internal particles.Under external loading,crack propagation deviates from prefabricated paths,forming serrated crack patterns.The FPZ initiates at the prefabricated crack tip and extends toward the loading end,exhibiting an arcshaped tip shape.The FPZ length increases with loading but decreases after reaching a peak value.With additional freeze-thaw cycles,the maximum FPZ length first increases and then diminishes.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
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
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 surface energy budget is closely related to freeze-thaw processes and is also a key issue for land surface process research in permafrost regions.In this study,in situ data collected from 2005 to 2015 at the Tangg...The surface energy budget is closely related to freeze-thaw processes and is also a key issue for land surface process research in permafrost regions.In this study,in situ data collected from 2005 to 2015 at the Tanggula site were used to analyze surface energy regimes,the interaction between surface energy budget and freeze-thaw processes.The results confirmed that surface energy flux in the permafrost region of the Qinghai-Tibetan Plateau exhibited obvious seasonal variations.Annual average net radiation(R_(n))for 2010 was 86.5 W m^(-2),with the largest being in July and smallest in November.Surface soil heat flux(G_(0))was positive during warm seasons but negative in cold seasons with annual average value of 2.7 W m^(-2).Variations in R_(n) and G_(0) were closely related to freeze-thaw processes.Sensible heat flux(H)was the main energy budget component during cold seasons,whereas latent heat flux(LE)dominated surface energy distribution in warm seasons.Freeze-thaw processes,snow cover,precipitation,and surface conditions were important influence factors for surface energy flux.Albedo was strongly dependent on soil moisture content and ground surface state,increasing significantly when land surface was covered with deep snow,and exhibited negative correlation with surface soil moisture content.Energy variation was significantly related to active layer thaw depth.Soil heat balance coefficient K was>1 during the investigation time period,indicating the permafrost in the Tanggula area tended to degrade.展开更多
The response of vegetation productivity to precipitation is becoming a worldwide concern.Most reports on responses of vegetation to precipitation trends are based on the growth season.In the soil freeze/thaw process,t...The response of vegetation productivity to precipitation is becoming a worldwide concern.Most reports on responses of vegetation to precipitation trends are based on the growth season.In the soil freeze/thaw process,the soil water phase and heat transport change can affect root growth,especially during the thawing process in early spring.A field experiment with increased precipitation(control,increased 25%and increased 50%)was conducted to measure the effects of soil water in early spring on above-and below-ground productivity in an alpine steppe over two growing seasons from June 2017 to September 2018.The increased 50%treatment significantly increased the soil moisture at the 10 cm depth,there was no difference in soil moisture between the increased 25%treatment and the control in the growing season,which was not consistent in the freeze/thaw process.Increased soil moisture during the non-growing season retarded root growth.Increased precipitation in the freezing-thawing period can partially offset the difference between the control and increased precipitation plots in both above-and below-ground biomass.展开更多
The active-layer soils overlying the permafrost are the most thermodynamically active zone of rock or soil and play important roles in the earth-atmosphere energy system. The processes of thawing and freezing and thei...The active-layer soils overlying the permafrost are the most thermodynamically active zone of rock or soil and play important roles in the earth-atmosphere energy system. The processes of thawing and freezing and their associated complex hydrothermal coupling can significantly affect variation in mean annual temperatures and the formation of ground ice in permafrost regions. Using soil-temperature and-moisture data obtained from the active layer between September 2011 and October 2014 in the permafrost region of the Nanweng'he River in the Da Xing'anling Mountains, the freeze-thaw characteristics of the permafrost were studied. Based on analysis of ground-temperature variation and hydrothermal transport characteristics, the thawing and freezing processes of the active layer were divided into three stages:(1) autumn-winter freezing,(2) winter freeze-up, and(3) spring-summer thawing. Variations in the soil temperature and moisture were analyzed during each stage of the freeze-thaw process, and the effects of the soil moisture and ground vegetation on the freeze-thaw are discussed in this paper. The study's results show that thawing in the active layer was unidirectional, while the ground freezing was bidirectional(upward from the bottom of the active layer and downward from the ground surface).During the annual freeze-thaw cycle, the migration of soil moisture had different characteristics at different stages. In general, during a freezing-thawing cycle, the soil-water molecules migrate downward, i.e., soil moisture transports from the entire active layer to the upper limit of the permafrost. In the meantime, freeze-thaw in the active layer can be significantly affected by the soil-moisture content and vegetation.展开更多
The freeze-thaw （FT） processes affect an area of 46.3% in China. It is essential for soil and water conservation and ecological construction to elucidate the mechanisms of the FF processes and its associated soil er...The freeze-thaw （FT） processes affect an area of 46.3% in China. It is essential for soil and water conservation and ecological construction to elucidate the mechanisms of the FF processes and its associated soil erosion processes. In this research, we designed the control simulation experiments to promote the understanding of FT-water combined erosion processes. The results showed that the runoff of freeze-thaw slope （FTS） decreased by 8% compared to the control slope （CS）, and the total sediment yield of the FTS was 1.10 times that of the CS. The sediment yield rate from the FTS was significantly greater than that from the CS after 9 min of runoff （P〈0.01）. Both in FTS and CS treatments, the relationships between cumulative runoff and sediment yield can be fitted well with power functions （R2〉0.98, P〈0.01）. Significant differences in the mean weight diameter （MWD） values of particles were between the CS and the FTS treatments in the erosion were smaller than those under FTS for both washed and observed for washed particles and splashed particles process （P〈0.05）. The mean MWD values under CS splashed particles. The ratio of the absolute value of a regression coefficient between the CS and the FTS was 1.15, being roughly correspondent with the ratio of K between the two treatments. Therefore, the parameter a of the power function between cumulative runoff and sediment yield could be an acceptable indicator for expressing the soil erodibility. In conclusion, the FTS exhibited an increase in soil erosion compared to the CS.展开更多
In order to investigate water and chloride ion transport in damaged concrete, three types of concrete were prepared, freeze-thawing（F-T） cycling and compressive loading were adopted to induce damage to concrete. Ult...In order to investigate water and chloride ion transport in damaged concrete, three types of concrete were prepared, freeze-thawing（F-T） cycling and compressive loading were adopted to induce damage to concrete. Ultrasonic pulse velocity technique was used for evaluating the damage degree of concrete, and the defects of damaged concrete were also detected by X-CT. Water absorption and chloride ion penetrability were used for describing the transport properties of damaged concrete. Effects of damage degree on the water absorption rate and chloride ion penetrability were investigated in detail and the relationships were also established. The results show that the water absorption of concrete makes various responses to damage degree due to the difference of concrete type and damage method. For same concrete with similar damage degree, the water absorption rate of F-T damaged concrete is usually larger than that of concrete damaged by loading. The chloride ion penetrability of damaged concrete increases linearly with increasing damage degree, which is more sensitive to damage degree if the original penetrability of sound concrete is higher.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
Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley a...Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley additive explanation(SHAP)to predict the flue pressure and take targeted adjustment measures.First,the sintering process data were collected and processed.A flue pressure prediction model was then constructed after comparing different feature selection methods and model algorithms using SHAP+extremely random-ized trees(ET).The prediction accuracy of the model within the error range of±0.25 kPa was 92.63%.SHAP analysis was employed to improve the interpretability of the prediction model.The effects of various sintering operation parameters on flue pressure,the relation-ship between the numerical range of key operation parameters and flue pressure,the effect of operation parameter combinations on flue pressure,and the prediction process of the flue pressure prediction model on a single sample were analyzed.A flue pressure optimization module was also constructed and analyzed when the prediction satisfied the judgment conditions.The operating parameter combination was then pushed.The flue pressure was increased by 5.87%during the verification process,achieving a good optimization effect.展开更多
Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the p...Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.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 projects(Grant No.:52304118)supported by National Natural Science Foundation of China,the Scientific Research Foundation for High-level Talents of Anhui University of Science and Technology(2023yjrc18)the Open Fund of the State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mine(Grant No.:SKLMRDPC23KF08).
文摘This study investigates the fracture characteristics and the fracture process zone(FPZ)of mode I fracture in sandstone,aiming to analyze the propagation behaviors of mode I crack under different freeze-thaw cycles.Semicircular bending tests(SCB)were conducted using different freeze-thaw cycles to evaluate mode I fracture toughness,FPZ dynamics,and macroscopic microscopic features.Digital image correlation(DIC)and scanning electron microscopy(SEM)techniques were employed for detailed analysis.Experimental results reveal that freeze-thaw cycling leads to the widening of both preexisting and newly formed microcracks between internal particles.Under external loading,crack propagation deviates from prefabricated paths,forming serrated crack patterns.The FPZ initiates at the prefabricated crack tip and extends toward the loading end,exhibiting an arcshaped tip shape.The FPZ length increases with loading but decreases after reaching a peak value.With additional freeze-thaw cycles,the maximum FPZ length first increases and then diminishes.
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.
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supported by the National Natural Science Foundation of China(Grant Nos.42071093,41671070)the National Key Research and Development Program of China(2020YFA0608500)+1 种基金the State Key Laboratory of Cryospheric Science(SKLCS-ZZ-2020)the National Natural Science Foundation of China(Grant Nos.41941015,42071093,41690142,41771076,41601078,and 41571069)。
文摘The surface energy budget is closely related to freeze-thaw processes and is also a key issue for land surface process research in permafrost regions.In this study,in situ data collected from 2005 to 2015 at the Tanggula site were used to analyze surface energy regimes,the interaction between surface energy budget and freeze-thaw processes.The results confirmed that surface energy flux in the permafrost region of the Qinghai-Tibetan Plateau exhibited obvious seasonal variations.Annual average net radiation(R_(n))for 2010 was 86.5 W m^(-2),with the largest being in July and smallest in November.Surface soil heat flux(G_(0))was positive during warm seasons but negative in cold seasons with annual average value of 2.7 W m^(-2).Variations in R_(n) and G_(0) were closely related to freeze-thaw processes.Sensible heat flux(H)was the main energy budget component during cold seasons,whereas latent heat flux(LE)dominated surface energy distribution in warm seasons.Freeze-thaw processes,snow cover,precipitation,and surface conditions were important influence factors for surface energy flux.Albedo was strongly dependent on soil moisture content and ground surface state,increasing significantly when land surface was covered with deep snow,and exhibited negative correlation with surface soil moisture content.Energy variation was significantly related to active layer thaw depth.Soil heat balance coefficient K was>1 during the investigation time period,indicating the permafrost in the Tanggula area tended to degrade.
基金funded by the Second Tibetan Plateau Scientific Explorationthe Strategic Priority Research Program of Chinese Academy of Sciences+1 种基金the National Natural Science Foundation,grant number 2019QZKK0404,XDA20020401,41977284by the Doctoral Science Foundation of Henan Polytechnic University(B2019-019)。
文摘The response of vegetation productivity to precipitation is becoming a worldwide concern.Most reports on responses of vegetation to precipitation trends are based on the growth season.In the soil freeze/thaw process,the soil water phase and heat transport change can affect root growth,especially during the thawing process in early spring.A field experiment with increased precipitation(control,increased 25%and increased 50%)was conducted to measure the effects of soil water in early spring on above-and below-ground productivity in an alpine steppe over two growing seasons from June 2017 to September 2018.The increased 50%treatment significantly increased the soil moisture at the 10 cm depth,there was no difference in soil moisture between the increased 25%treatment and the control in the growing season,which was not consistent in the freeze/thaw process.Increased soil moisture during the non-growing season retarded root growth.Increased precipitation in the freezing-thawing period can partially offset the difference between the control and increased precipitation plots in both above-and below-ground biomass.
基金supported by the National Natural Science Foundation of China(Grant No.41401081)the State Key Laboratory of Frozen Soils Engineering(Grant Nos.SKLFSE-ZT-41,SKLFSE-ZT-20and SKLFSE-ZT-12)
文摘The active-layer soils overlying the permafrost are the most thermodynamically active zone of rock or soil and play important roles in the earth-atmosphere energy system. The processes of thawing and freezing and their associated complex hydrothermal coupling can significantly affect variation in mean annual temperatures and the formation of ground ice in permafrost regions. Using soil-temperature and-moisture data obtained from the active layer between September 2011 and October 2014 in the permafrost region of the Nanweng'he River in the Da Xing'anling Mountains, the freeze-thaw characteristics of the permafrost were studied. Based on analysis of ground-temperature variation and hydrothermal transport characteristics, the thawing and freezing processes of the active layer were divided into three stages:(1) autumn-winter freezing,(2) winter freeze-up, and(3) spring-summer thawing. Variations in the soil temperature and moisture were analyzed during each stage of the freeze-thaw process, and the effects of the soil moisture and ground vegetation on the freeze-thaw are discussed in this paper. The study's results show that thawing in the active layer was unidirectional, while the ground freezing was bidirectional(upward from the bottom of the active layer and downward from the ground surface).During the annual freeze-thaw cycle, the migration of soil moisture had different characteristics at different stages. In general, during a freezing-thawing cycle, the soil-water molecules migrate downward, i.e., soil moisture transports from the entire active layer to the upper limit of the permafrost. In the meantime, freeze-thaw in the active layer can be significantly affected by the soil-moisture content and vegetation.
基金supported by the National Basic Research Program of China(2016YFC040240X)the National Natural Science Foundation of China(41471226,41330858)the Independent Research Foundation of State Key Laboratory Base of Eco-Hydraulic Engineering in Arid Area(2016KFKT-8)
文摘The freeze-thaw （FT） processes affect an area of 46.3% in China. It is essential for soil and water conservation and ecological construction to elucidate the mechanisms of the FF processes and its associated soil erosion processes. In this research, we designed the control simulation experiments to promote the understanding of FT-water combined erosion processes. The results showed that the runoff of freeze-thaw slope （FTS） decreased by 8% compared to the control slope （CS）, and the total sediment yield of the FTS was 1.10 times that of the CS. The sediment yield rate from the FTS was significantly greater than that from the CS after 9 min of runoff （P〈0.01）. Both in FTS and CS treatments, the relationships between cumulative runoff and sediment yield can be fitted well with power functions （R2〉0.98, P〈0.01）. Significant differences in the mean weight diameter （MWD） values of particles were between the CS and the FTS treatments in the erosion were smaller than those under FTS for both washed and observed for washed particles and splashed particles process （P〈0.05）. The mean MWD values under CS splashed particles. The ratio of the absolute value of a regression coefficient between the CS and the FTS was 1.15, being roughly correspondent with the ratio of K between the two treatments. Therefore, the parameter a of the power function between cumulative runoff and sediment yield could be an acceptable indicator for expressing the soil erodibility. In conclusion, the FTS exhibited an increase in soil erosion compared to the CS.
基金Funded by the Major State Basic Research Development Program of China(973 Program)(No.2015CB655102)the National Natural Science Foundation of China(Nos.51178106,51378116&51408597)the Scientific and Technological Research and Development plan of China Railway Corporation(No.2013G001-A-2)
文摘In order to investigate water and chloride ion transport in damaged concrete, three types of concrete were prepared, freeze-thawing（F-T） cycling and compressive loading were adopted to induce damage to concrete. Ultrasonic pulse velocity technique was used for evaluating the damage degree of concrete, and the defects of damaged concrete were also detected by X-CT. Water absorption and chloride ion penetrability were used for describing the transport properties of damaged concrete. Effects of damage degree on the water absorption rate and chloride ion penetrability were investigated in detail and the relationships were also established. The results show that the water absorption of concrete makes various responses to damage degree due to the difference of concrete type and damage method. For same concrete with similar damage degree, the water absorption rate of F-T damaged concrete is usually larger than that of concrete damaged by loading. The chloride ion penetrability of damaged concrete increases linearly with increasing damage degree, which is more sensitive to damage degree if the original penetrability of sound concrete is higher.
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).
基金supported by the General Program of the National Natural Science Foundation of China(No.52274326)the China Baowu Low Carbon Metallurgy Innovation Foundation(No.BWLCF202109)the Seventh Batch of Ten Thousand Talents Plan of China(No.ZX20220553).
文摘Sinter is the core raw material for blast furnaces.Flue pressure,which is an important state parameter,affects sinter quality.In this paper,flue pressure prediction and optimization were studied based on the shapley additive explanation(SHAP)to predict the flue pressure and take targeted adjustment measures.First,the sintering process data were collected and processed.A flue pressure prediction model was then constructed after comparing different feature selection methods and model algorithms using SHAP+extremely random-ized trees(ET).The prediction accuracy of the model within the error range of±0.25 kPa was 92.63%.SHAP analysis was employed to improve the interpretability of the prediction model.The effects of various sintering operation parameters on flue pressure,the relation-ship between the numerical range of key operation parameters and flue pressure,the effect of operation parameter combinations on flue pressure,and the prediction process of the flue pressure prediction model on a single sample were analyzed.A flue pressure optimization module was also constructed and analyzed when the prediction satisfied the judgment conditions.The operating parameter combination was then pushed.The flue pressure was increased by 5.87%during the verification process,achieving a good optimization effect.
基金supported by the National Natural Science Foundation of China(51767017)the Basic Research Innovation Group Project of Gansu Province(18JR3RA133)the Industrial Support and Guidance Project of Universities in Gansu Province(2022CYZC-22).
文摘Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.
