The aim of this work is mathematical education through the knowledge system and mathematical modeling. A net model of formation of mathematical knowledge as a deductive theory is suggested here. Within this model the ...The aim of this work is mathematical education through the knowledge system and mathematical modeling. A net model of formation of mathematical knowledge as a deductive theory is suggested here. Within this model the formation of deductive theory is represented as the development of a certain informational space, the elements of which are structured in the form of the orientated semantic net. This net is properly metrized and characterized by a certain system of coverings. It allows injecting net optimization parameters, regulating qualitative aspects of knowledge system under consideration. To regulate the creative processes of the formation and realization of mathematical know- edge, stochastic model of formation deductive theory is suggested here in the form of branching Markovian process, which is realized in the corresponding informational space as a semantic net. According to this stochastic model we can get correct foundation of criterion of optimization creative processes that leads to “great main points” strategy (GMP-strategy) in the process of realization of the effective control in the research work in the sphere of mathematics and its applications.展开更多
In this paper the Expendable Pattern Casting with dry sand Vacuum(EPC-V) process is used to manufacture iron matrix composites with tungsten carbide particle.Microstructures of the composites layers were analyzed.The ...In this paper the Expendable Pattern Casting with dry sand Vacuum(EPC-V) process is used to manufacture iron matrix composites with tungsten carbide particle.Microstructures of the composites layers were analyzed.The abrasive wear resistance of the composites layers were tested and compared with that of high chromium cast iron.The results show that the iron matrix composites with tungsten carbide particle have high hardness.The abrasive wear resistance of composites with tungsten carbide particle is higher than that of high chromium cast iron.The properties of the matrix materials have been improved remarkably.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
In this paper we examine the large deviations principle (LDP) for sequences of classic Cramér-Lundberg risk processes under suitable time and scale modifications, and also for a wide class of claim distributions ...In this paper we examine the large deviations principle (LDP) for sequences of classic Cramér-Lundberg risk processes under suitable time and scale modifications, and also for a wide class of claim distributions including (the non-super- exponential) exponential claims. We prove two large deviations principles: first, we obtain the LDP for risk processes on D∈[0,1] with the Skorohod topology. In this case, we provide an explicit form for the rate function, in which the safety loading condition appears naturally. The second theorem allows us to obtain the LDP for Aggregate Claims processes on D∈[0,∞) with a different time-scale modification. As an application of the first result we estimate the ruin probability, and for the second result we work explicit calculations for the case of exponential claims.展开更多
Perinatal hypoxic-ischemic-encephalopathy significantly contributes to neonatal death and life-long disability such as cerebral palsy. Advances in signal processing and machine learning have provided the research comm...Perinatal hypoxic-ischemic-encephalopathy significantly contributes to neonatal death and life-long disability such as cerebral palsy. Advances in signal processing and machine learning have provided the research community with an opportunity to develop automated real-time identification techniques to detect the signs of hypoxic-ischemic-encephalopathy in larger electroencephalography/amplitude-integrated electroencephalography data sets more easily. This review details the recent achievements, performed by a number of prominent research groups across the world, in the automatic identification and classification of hypoxic-ischemic epileptiform neonatal seizures using advanced signal processing and machine learning techniques. This review also addresses the clinical challenges that current automated techniques face in order to be fully utilized by clinicians, and highlights the importance of upgrading the current clinical bedside sampling frequencies to higher sampling rates in order to provide better hypoxic-ischemic biomarker detection frameworks. Additionally, the article highlights that current clinical automated epileptiform detection strategies for human neonates have been only concerned with seizure detection after the therapeutic latent phase of injury. Whereas recent animal studies have demonstrated that the latent phase of opportunity is critically important for early diagnosis of hypoxic-ischemic-encephalopathy electroencephalography biomarkers and although difficult, detection strategies could utilize biomarkers in the latent phase to also predict the onset of future seizures.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
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
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
To address the challenges of complex fluvial sandbody distribution and difficult remaining oil recovery in mature continental oilfields,this study focuses on key issues in reservoir identification such as ambiguous na...To address the challenges of complex fluvial sandbody distribution and difficult remaining oil recovery in mature continental oilfields,this study focuses on key issues in reservoir identification such as ambiguous narrow-channel boundaries and subdivision of multi-stage superimposed sandbodies.Taking the Upper Cretaceous continental sandstone in the Sazhong Oilfield of the Daqing Placanticline as an example,a technical system integrating OVT high-resolution processing,multi-attribute fusion,and varible-scale inversion was developed to establish a complete workflow from seismic processing to reservoir prediction and remaining oil recovery.The following results are obtained.First,the Offset Vector Tile(OVT)seismic processing technology is extended,for the first time,from fracture imaging to sandbody prediction,in order to address the weak seismic responses from boundaries of narrow and thin sandbodies.A geology-oriented OVT partitioning method is developed to significantly improve the imaging accuracy,enabling identification of channel sandbodies as narrow as 50 m.Second,an amplitude-coherence dual-attribute fusion method is proposed for predicting narrow channel boundaries between wells.Constrained by a sedimentary unit-level sequence chronostratigraphic framework,this method accurately delineates 800-2000 m long subaqueous distributary channels with bifurcation-convergence features.Third,considering the superimposition of multi-stage channels,a three-level variable-scale stratigraphic model(sandstone groups,sublayers,sedimentary units)is constructed to overcome single-scale modeling limitations,successfully characterizing key sedimentary features like meandering river“cut-offs”through 3D seismic inversion.Based on these advances,a direct link between seismic prediction and remaining oil recovery is established.The horizontal wells deployed using narrow-channel predictions encountered oil-bearing sandstones in the horizontal section by 97%,and achieved initial daily production of 12.5 t per well.Precise identification of individual channel boundaries within 17 composite sandbodies guided recovery processes in 135 wells,yielding an average daily increase of 2.8 t per well and a cumulative increase of 13.6×10^(4)t.展开更多
Dear Editor,In this letter,we focus on the algebraic relationship between the coefficient matrices and the solution of the stochastic algebraic Riccati equation.It is revealed that,if the coefficient matrices are in a...Dear Editor,In this letter,we focus on the algebraic relationship between the coefficient matrices and the solution of the stochastic algebraic Riccati equation.It is revealed that,if the coefficient matrices are in an algebra,then the solution(and also the control gain in many cases)is also in the same algebra.The main result is verified by a numerical simulation.展开更多
District Ghizer is a rugged mountainous territory which experiences several landslides each year. There are 16 major landslide areas and 53 villages that are at high risk to hazards. Keeping in view the severity of na...District Ghizer is a rugged mountainous territory which experiences several landslides each year. There are 16 major landslide areas and 53 villages that are at high risk to hazards. Keeping in view the severity of natural hazards, the present study was designed to generate landslide susceptibility map based on twelve causative factors viz., slope, aspect, elevation, drainage network, Stream Power Index (SPI), Topographic Wetness Index (TWI), lithological units, fault lines, rainfall, road network, land cover and soil texture. Soil texture was determined by particle size analysis and data for other factors were acquired from freely available sources. Analytical Hierarchy Process (AHP) was employed to identify major landslide causative factors in the district Ghizer. Further, a temporal assessment from 1999 till 2015 was generated to assess the impact of land cover change on landslides. It indicated that the barren soil/ exposed rocks and glaciers have reduced while the vegetation and water classes have shown increment. The total area that lies in moderate to very high landslide susceptible zones was 74.38%, while slope is the main landslide causative factor in the district Ghizer. Validation of the susceptibility map showed 88.1% of the landslides in the study area had occurred in the moderate to very high susceptible zones.展开更多
The prevailing idea so far about why the rainfall occurs was that after agglutination of water droplets with condensation nuclei, the size of the particle formed by the condensation nuclei connected with droplets of w...The prevailing idea so far about why the rainfall occurs was that after agglutination of water droplets with condensation nuclei, the size of the particle formed by the condensation nuclei connected with droplets of water increased considerably and caused its fall. This idea has led to numerous scientific publications in which empirical distribution functions of clouds’ water droplets sizes were proposed. Estimates values provided by these empirical distribution functions, in most cases, were validated by comparison with UHF Radar measurements. The condensation nuclei concept has not been sufficiently exploited and this has led meteorologists to error, in their attempt to describe the clouds, thinking that clouds were formed by liquid water droplets. Indeed, MBANE BIOUELE paradox (2005) confirms this embarrassing situation. In fact, when applying Archimedes theorem to a liquid water droplet suspended in the atmosphere, we obtain a meaningless inequality ?which makes believe that the densities of pure water in liquid and solid phases are much lower than that of the atmosphere considered at the sea level. This meaningless inequality is easy to contradict: of course, if you empty a bottle of pure liquid water in the ocean (where z is equal to 0), this water will not remain suspended in the air, i.e., application of Archimedes’ theorem allows realizing that there is no liquid (or solid) water droplet, suspended in the clouds. Indeed, all liquid (or solid) water droplets which are formed in clouds, fall under the effect of gravity and produce rains. This means that our current description of the clouds is totally wrong. In this study, we describe the clouds as a gas composed of dry air and saturated water vapor whose optical properties depend on temperature, i.e., when the temperature of a cloud decreases, the color of this gaseous system tends towards white.展开更多
Induction heating has important applications in science and industry. The method of induction heating can be successfully used for melting and heat treatment of titanium and zirconium alloys. Different applications us...Induction heating has important applications in science and industry. The method of induction heating can be successfully used for melting and heat treatment of titanium and zirconium alloys. Different applications using induction precise heating before plastic deformation are discussed in this paper. For alloys of many metals such as titanium, zirconium, niobium, tantalum, etc., it is important to provide precision heating with a high degree of homogeneity of the temperature field and strict adherence to the condition of heating. This is explained by polymorphism of the alloys based on these metals, their chemical activity at high temperatures and the specific thermal and electrical properties. It is very important for induction heating to define the extreme achievable unevenness of the temperature field. For special alloys it is necessary to use resistance furnaces for homogenization of billets’ temperature after heating in the inductors. Optimal control can be used for massive billets to reduce significantly the heating time, energy expenses and to improve the quality of the temperature field distribution. Optimization of induction heating process can be achieved by synchronous solution of the problem of optimal control and design with specially developed models.展开更多
Digital twin technology brings more opportunities and challenges to chemical engineering in both academic and industry.A complex process could have multiple digitalization needs,including simulation,monitoring,operato...Digital twin technology brings more opportunities and challenges to chemical engineering in both academic and industry.A complex process could have multiple digitalization needs,including simulation,monitoring,operator training,etc.;thus,a hierarchical digital twin would be a comprehensive solution to that.In this study,a novel and general framework of the digital twin is proposed for operations in process industry.With the hierarchical structure,the framework can handle various tasks driven by different roles in process industry,including managers,engineers,and operators.To complete these tasks,the framework consists of three modules:OAS(Operation Analysis System),OMS(Operation Monitoring System),and OTS(Operator Training System).Each module focuses on one unique type of demand from the staff,as well as interactions among them enabling efficient data sharing.Based on the hierarchical framework,a digital twin system is applied for one complex industrial nitration process,which successfully enhances the operation efficiency and safety in several industrial scenarios with different demands.展开更多
Accurately assessing the carbon sequestration capacity of forests is crucial for mitigating climate change.Traditional methods for estimating Gross Primary Productivity(GPP)of vegetation involve significant uncertaint...Accurately assessing the carbon sequestration capacity of forests is crucial for mitigating climate change.Traditional methods for estimating Gross Primary Productivity(GPP)of vegetation involve significant uncertainties.As a novel remote sensing approach,Solar-Induced chlorophyll Fluorescence(SIF)is directly related to photosynthesis and has demonstrated strong correlations with GPP across various ecosystems,climate zones,and spatial scales.Current GPP estimation methods based on SIF include Light Use Efficiency(LUE)models,the SCOPE process models,and the latest mechanistic light response(MLR)models.Future research should focus on improving the mechanistic understanding of SIF-related processes and promoting the integration of multi-source remote sensing data with SIF-based modeling to enhance the accuracy and universality of GPP estimation.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
Large quantities of blast furnace(BF) slag and CO_2 are discharged annually from iron and steel industries, along with a large amount of waste heat.The mineral carbonation of BF slag can not only reduce emissions of s...Large quantities of blast furnace(BF) slag and CO_2 are discharged annually from iron and steel industries, along with a large amount of waste heat.The mineral carbonation of BF slag can not only reduce emissions of solid waste but also realize the in-situ fixation of CO_2 with low energy consumption if integrated with the waste heat utilization.In this study, based on our previous works, Aspen Plus was employed to simulate and optimize the carbonation process and integrate the process energy.The effects of gehlenite extraction, MgSO_4 carbonation,and aluminum ammonium sulfate crystallization were studied systematically.The simulation results demonstrate that 2.57 kg of BF slag can sequester 1 kg of CO_2, requiring 5.34 MJ of energy(3.3 MJ heat and 2.04 MJ electricity), and this energy includes the capture of CO_2 from industrial flue gases.Approximately 60 kg net CO_2 emission reduction could be achieved for the disposal of one ton of BF slag.In addition, the by-product,aluminum ammonium sulfate, is a high value-added product.Preliminary economic analysis indicates that the profit for the whole process is 1127 CNY per ton of BF slag processed.展开更多
Smith predictor known as the time delay compensator was extended to control the process with inverse response.Modern robust control theory was employed to design the robust controller,which has only one parameter to b...Smith predictor known as the time delay compensator was extended to control the process with inverse response.Modern robust control theory was employed to design the robust controller,which has only one parameter to be determined with compromise among the rise time,undershoot,robustness and capability to reject disturbance of the closed loop system.The former two specifications can be assessed quantitatively and the latter two qualitatively.Examples show that the proposed method has significant improvements and wide applicable ranges for inverse response process.展开更多
The processes of heat and humidity transfer between air and water are what to be studied mainly in the paper, we put forward some main factors which influence the processes of heat and humidity transfer in the air was...The processes of heat and humidity transfer between air and water are what to be studied mainly in the paper, we put forward some main factors which influence the processes of heat and humidity transfer in the air washer. We come to the conclusion that we can change these main factors to achieve different heat and humidity transfer processes and decide processes of heat and humidity transfer of air and water with the initial temperature of spraying water in the air washer. All these results can make things convenient for the air conditioning management.展开更多
文摘The aim of this work is mathematical education through the knowledge system and mathematical modeling. A net model of formation of mathematical knowledge as a deductive theory is suggested here. Within this model the formation of deductive theory is represented as the development of a certain informational space, the elements of which are structured in the form of the orientated semantic net. This net is properly metrized and characterized by a certain system of coverings. It allows injecting net optimization parameters, regulating qualitative aspects of knowledge system under consideration. To regulate the creative processes of the formation and realization of mathematical know- edge, stochastic model of formation deductive theory is suggested here in the form of branching Markovian process, which is realized in the corresponding informational space as a semantic net. According to this stochastic model we can get correct foundation of criterion of optimization creative processes that leads to “great main points” strategy (GMP-strategy) in the process of realization of the effective control in the research work in the sphere of mathematics and its applications.
文摘In this paper the Expendable Pattern Casting with dry sand Vacuum(EPC-V) process is used to manufacture iron matrix composites with tungsten carbide particle.Microstructures of the composites layers were analyzed.The abrasive wear resistance of the composites layers were tested and compared with that of high chromium cast iron.The results show that the iron matrix composites with tungsten carbide particle have high hardness.The abrasive wear resistance of composites with tungsten carbide particle is higher than that of high chromium cast iron.The properties of the matrix materials have been improved remarkably.
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.
文摘In this paper we examine the large deviations principle (LDP) for sequences of classic Cramér-Lundberg risk processes under suitable time and scale modifications, and also for a wide class of claim distributions including (the non-super- exponential) exponential claims. We prove two large deviations principles: first, we obtain the LDP for risk processes on D∈[0,1] with the Skorohod topology. In this case, we provide an explicit form for the rate function, in which the safety loading condition appears naturally. The second theorem allows us to obtain the LDP for Aggregate Claims processes on D∈[0,∞) with a different time-scale modification. As an application of the first result we estimate the ruin probability, and for the second result we work explicit calculations for the case of exponential claims.
基金supported by the Auckland Medical Research Foundation,No.1117017(to CPU)
文摘Perinatal hypoxic-ischemic-encephalopathy significantly contributes to neonatal death and life-long disability such as cerebral palsy. Advances in signal processing and machine learning have provided the research community with an opportunity to develop automated real-time identification techniques to detect the signs of hypoxic-ischemic-encephalopathy in larger electroencephalography/amplitude-integrated electroencephalography data sets more easily. This review details the recent achievements, performed by a number of prominent research groups across the world, in the automatic identification and classification of hypoxic-ischemic epileptiform neonatal seizures using advanced signal processing and machine learning techniques. This review also addresses the clinical challenges that current automated techniques face in order to be fully utilized by clinicians, and highlights the importance of upgrading the current clinical bedside sampling frequencies to higher sampling rates in order to provide better hypoxic-ischemic biomarker detection frameworks. Additionally, the article highlights that current clinical automated epileptiform detection strategies for human neonates have been only concerned with seizure detection after the therapeutic latent phase of injury. Whereas recent animal studies have demonstrated that the latent phase of opportunity is critically important for early diagnosis of hypoxic-ischemic-encephalopathy electroencephalography biomarkers and although difficult, detection strategies could utilize biomarkers in the latent phase to also predict the onset of future seizures.
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.
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Supported by the China National Science and Technology Major Project(2025ZD1407000)PetroChina Science and Technology Major Project(2023ZZ22)。
文摘To address the challenges of complex fluvial sandbody distribution and difficult remaining oil recovery in mature continental oilfields,this study focuses on key issues in reservoir identification such as ambiguous narrow-channel boundaries and subdivision of multi-stage superimposed sandbodies.Taking the Upper Cretaceous continental sandstone in the Sazhong Oilfield of the Daqing Placanticline as an example,a technical system integrating OVT high-resolution processing,multi-attribute fusion,and varible-scale inversion was developed to establish a complete workflow from seismic processing to reservoir prediction and remaining oil recovery.The following results are obtained.First,the Offset Vector Tile(OVT)seismic processing technology is extended,for the first time,from fracture imaging to sandbody prediction,in order to address the weak seismic responses from boundaries of narrow and thin sandbodies.A geology-oriented OVT partitioning method is developed to significantly improve the imaging accuracy,enabling identification of channel sandbodies as narrow as 50 m.Second,an amplitude-coherence dual-attribute fusion method is proposed for predicting narrow channel boundaries between wells.Constrained by a sedimentary unit-level sequence chronostratigraphic framework,this method accurately delineates 800-2000 m long subaqueous distributary channels with bifurcation-convergence features.Third,considering the superimposition of multi-stage channels,a three-level variable-scale stratigraphic model(sandstone groups,sublayers,sedimentary units)is constructed to overcome single-scale modeling limitations,successfully characterizing key sedimentary features like meandering river“cut-offs”through 3D seismic inversion.Based on these advances,a direct link between seismic prediction and remaining oil recovery is established.The horizontal wells deployed using narrow-channel predictions encountered oil-bearing sandstones in the horizontal section by 97%,and achieved initial daily production of 12.5 t per well.Precise identification of individual channel boundaries within 17 composite sandbodies guided recovery processes in 135 wells,yielding an average daily increase of 2.8 t per well and a cumulative increase of 13.6×10^(4)t.
文摘Dear Editor,In this letter,we focus on the algebraic relationship between the coefficient matrices and the solution of the stochastic algebraic Riccati equation.It is revealed that,if the coefficient matrices are in an algebra,then the solution(and also the control gain in many cases)is also in the same algebra.The main result is verified by a numerical simulation.
文摘District Ghizer is a rugged mountainous territory which experiences several landslides each year. There are 16 major landslide areas and 53 villages that are at high risk to hazards. Keeping in view the severity of natural hazards, the present study was designed to generate landslide susceptibility map based on twelve causative factors viz., slope, aspect, elevation, drainage network, Stream Power Index (SPI), Topographic Wetness Index (TWI), lithological units, fault lines, rainfall, road network, land cover and soil texture. Soil texture was determined by particle size analysis and data for other factors were acquired from freely available sources. Analytical Hierarchy Process (AHP) was employed to identify major landslide causative factors in the district Ghizer. Further, a temporal assessment from 1999 till 2015 was generated to assess the impact of land cover change on landslides. It indicated that the barren soil/ exposed rocks and glaciers have reduced while the vegetation and water classes have shown increment. The total area that lies in moderate to very high landslide susceptible zones was 74.38%, while slope is the main landslide causative factor in the district Ghizer. Validation of the susceptibility map showed 88.1% of the landslides in the study area had occurred in the moderate to very high susceptible zones.
文摘The prevailing idea so far about why the rainfall occurs was that after agglutination of water droplets with condensation nuclei, the size of the particle formed by the condensation nuclei connected with droplets of water increased considerably and caused its fall. This idea has led to numerous scientific publications in which empirical distribution functions of clouds’ water droplets sizes were proposed. Estimates values provided by these empirical distribution functions, in most cases, were validated by comparison with UHF Radar measurements. The condensation nuclei concept has not been sufficiently exploited and this has led meteorologists to error, in their attempt to describe the clouds, thinking that clouds were formed by liquid water droplets. Indeed, MBANE BIOUELE paradox (2005) confirms this embarrassing situation. In fact, when applying Archimedes theorem to a liquid water droplet suspended in the atmosphere, we obtain a meaningless inequality ?which makes believe that the densities of pure water in liquid and solid phases are much lower than that of the atmosphere considered at the sea level. This meaningless inequality is easy to contradict: of course, if you empty a bottle of pure liquid water in the ocean (where z is equal to 0), this water will not remain suspended in the air, i.e., application of Archimedes’ theorem allows realizing that there is no liquid (or solid) water droplet, suspended in the clouds. Indeed, all liquid (or solid) water droplets which are formed in clouds, fall under the effect of gravity and produce rains. This means that our current description of the clouds is totally wrong. In this study, we describe the clouds as a gas composed of dry air and saturated water vapor whose optical properties depend on temperature, i.e., when the temperature of a cloud decreases, the color of this gaseous system tends towards white.
文摘Induction heating has important applications in science and industry. The method of induction heating can be successfully used for melting and heat treatment of titanium and zirconium alloys. Different applications using induction precise heating before plastic deformation are discussed in this paper. For alloys of many metals such as titanium, zirconium, niobium, tantalum, etc., it is important to provide precision heating with a high degree of homogeneity of the temperature field and strict adherence to the condition of heating. This is explained by polymorphism of the alloys based on these metals, their chemical activity at high temperatures and the specific thermal and electrical properties. It is very important for induction heating to define the extreme achievable unevenness of the temperature field. For special alloys it is necessary to use resistance furnaces for homogenization of billets’ temperature after heating in the inductors. Optimal control can be used for massive billets to reduce significantly the heating time, energy expenses and to improve the quality of the temperature field distribution. Optimization of induction heating process can be achieved by synchronous solution of the problem of optimal control and design with specially developed models.
基金support of the“Pioneer”and“Leading Goose”Research&Development Program of Zhejiang(2024C01028)the State Key Laboratory of Industrial Control Technology,China(ICT2024C04)are gratefully acknowledged.
文摘Digital twin technology brings more opportunities and challenges to chemical engineering in both academic and industry.A complex process could have multiple digitalization needs,including simulation,monitoring,operator training,etc.;thus,a hierarchical digital twin would be a comprehensive solution to that.In this study,a novel and general framework of the digital twin is proposed for operations in process industry.With the hierarchical structure,the framework can handle various tasks driven by different roles in process industry,including managers,engineers,and operators.To complete these tasks,the framework consists of three modules:OAS(Operation Analysis System),OMS(Operation Monitoring System),and OTS(Operator Training System).Each module focuses on one unique type of demand from the staff,as well as interactions among them enabling efficient data sharing.Based on the hierarchical framework,a digital twin system is applied for one complex industrial nitration process,which successfully enhances the operation efficiency and safety in several industrial scenarios with different demands.
基金sponsored by the National Natural Science Foundation of China(Grant number 42250205,42471510)the Open Found of Technology Innovation Center for Intelligent Monitoring and Spatial Regulation of Land Carbon Sinks,MNR(CUG-SRCS-0002)the Open Fund of Hubei Key Laboratory of Regional Ecological Process and Environmental Evolution(REEC-OF-202405).
文摘Accurately assessing the carbon sequestration capacity of forests is crucial for mitigating climate change.Traditional methods for estimating Gross Primary Productivity(GPP)of vegetation involve significant uncertainties.As a novel remote sensing approach,Solar-Induced chlorophyll Fluorescence(SIF)is directly related to photosynthesis and has demonstrated strong correlations with GPP across various ecosystems,climate zones,and spatial scales.Current GPP estimation methods based on SIF include Light Use Efficiency(LUE)models,the SCOPE process models,and the latest mechanistic light response(MLR)models.Future research should focus on improving the mechanistic understanding of SIF-related processes and promoting the integration of multi-source remote sensing data with SIF-based modeling to enhance the accuracy and universality of GPP estimation.
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Supported by the National Key Projects for Fundamental Research and Development of China(2016YFB0600904)
文摘Large quantities of blast furnace(BF) slag and CO_2 are discharged annually from iron and steel industries, along with a large amount of waste heat.The mineral carbonation of BF slag can not only reduce emissions of solid waste but also realize the in-situ fixation of CO_2 with low energy consumption if integrated with the waste heat utilization.In this study, based on our previous works, Aspen Plus was employed to simulate and optimize the carbonation process and integrate the process energy.The effects of gehlenite extraction, MgSO_4 carbonation,and aluminum ammonium sulfate crystallization were studied systematically.The simulation results demonstrate that 2.57 kg of BF slag can sequester 1 kg of CO_2, requiring 5.34 MJ of energy(3.3 MJ heat and 2.04 MJ electricity), and this energy includes the capture of CO_2 from industrial flue gases.Approximately 60 kg net CO_2 emission reduction could be achieved for the disposal of one ton of BF slag.In addition, the by-product,aluminum ammonium sulfate, is a high value-added product.Preliminary economic analysis indicates that the profit for the whole process is 1127 CNY per ton of BF slag processed.
文摘Smith predictor known as the time delay compensator was extended to control the process with inverse response.Modern robust control theory was employed to design the robust controller,which has only one parameter to be determined with compromise among the rise time,undershoot,robustness and capability to reject disturbance of the closed loop system.The former two specifications can be assessed quantitatively and the latter two qualitatively.Examples show that the proposed method has significant improvements and wide applicable ranges for inverse response process.
文摘The processes of heat and humidity transfer between air and water are what to be studied mainly in the paper, we put forward some main factors which influence the processes of heat and humidity transfer in the air washer. We come to the conclusion that we can change these main factors to achieve different heat and humidity transfer processes and decide processes of heat and humidity transfer of air and water with the initial temperature of spraying water in the air washer. All these results can make things convenient for the air conditioning management.
