The start-up process of Stokes＇ second problem of a viscoelastic material with fractional element is studied. The fluid above an infinite flat plane is set in motion by a sudden acceleration of the plate to steady os...The start-up process of Stokes＇ second problem of a viscoelastic material with fractional element is studied. The fluid above an infinite flat plane is set in motion by a sudden acceleration of the plate to steady oscillation. Exact solutions are obtained by using Laplace transform and Fourier transform. It is found that the relationship between the first peak value and the one of equal-amplitude oscillations depends on the distance from the plate. The amplitude decreases for increasing frequency and increasing distance.展开更多
A particle-in-cell Monte Carlo collision model of a discharge chamber is established to investigate the start-up process of a miniature ion thruster.We present the discharge characteristics at different stages(the ini...A particle-in-cell Monte Carlo collision model of a discharge chamber is established to investigate the start-up process of a miniature ion thruster.We present the discharge characteristics at different stages(the initial stage,development stage,and stable stage)according to the trend of the discharge current with time.The discharge current is the sum of the sidewall current and the backplate current.During the start-up process,the sidewall current lags behind the backplate current.The variation and distribution characteristics of the discharge current over time are determined by the electron density distribution and electric potential distribution.展开更多
Solid rocket motors have important applications in the propulsion of trans-media vehicles and underwater launched rockets.In this paper,the ignition start-up process of an underwater solid rocket motor across a wide d...Solid rocket motors have important applications in the propulsion of trans-media vehicles and underwater launched rockets.In this paper,the ignition start-up process of an underwater solid rocket motor across a wide depth range has been numerically studied.A novel multi-domain integrated model has been developed by combining the solid propellant ignition and combustion model with the volume of fluid multiphase model.This integrated model enables the coupled simulation of the propellant combustion and gas flow inside the motor,along with the gas jet evolution in the external water environment.The detailed flow field developments in the combustion chamber,nozzle,and wake field are carefully analyzed.The variation rules of the internal ballistics and thrust performance are also obtained.The effects of environmental medium and operating depth on the ignition start-up process are systematically discussed.The results show that the influence of the operating environment on the internal ballistic characteristics is primarily reflected in the initial period after the nozzle closure opens.The development of the gas jet in water lags significantly compared with that in air.As the water depth increases,the ignition delay time of the motor is shortened,and the morphology evolution of the gas jet is significantly compressed and accelerated.Furthermore,the necking and bulging of the jet boundary near the nozzle outlet and the consequent shock oscillations are intensified,resulting in stronger fluctuations in the wake pressure field and motor thrust.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
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
N-dodecanoyl homoserine lactone（C（12）-HSL）was detected in the supernatant of an anammox granular sludge reactor（AGSR）.C（12）-HSL could enhance the specific anammox activity of anammox biomass.Adding C（12）-HSL...N-dodecanoyl homoserine lactone（C（12）-HSL）was detected in the supernatant of an anammox granular sludge reactor（AGSR）.C（12）-HSL could enhance the specific anammox activity of anammox biomass.Adding C（12）-HSL-containing AGSR supernatant into the continuously stirred tank reactors reduced the start-up time of the anammox process from80 to 66 days.Moreover,the nitrogen loading rate was also enhanced to 1.6 times that of the control reactor.AHLs could increase the secretion of extracellular polymeric substances and anammox obtained better enrichment with the addition of AHLs-containing AGSR supernatant.Denaturing gradient gel electrophoresis analysis further revealed that AHLs played a role in mediating microbial community parameters.In conclusion,adding AHL-containing supernatant could be an effective and economical way to accelerate the start-up of anammox.展开更多
Expanded granular sludge bed （EGSB） reactor and bioaugmentation were employed to investigate biohydrogen production with molasses wastewater. The start-up experiments consisted of two stages. In the first stage （0 ...Expanded granular sludge bed （EGSB） reactor and bioaugmentation were employed to investigate biohydrogen production with molasses wastewater. The start-up experiments consisted of two stages. In the first stage （0 - 24d） seeded with activated sludge, the butyric acid type-fermentation formed when the initial expanding rate, organic loading rate （OLR）, the initial redox potential （ORP） and hydraulic retention time （HRT） were 10%, 10.0 kg COD/（m^3·d）, -215 mV and 6.7 h, respectively. At the beginning of the second stage on day 25, the novel hydrogen-producing fermentative bacterial strain B49 （AF481148 in EMBL） were inoculated into the reactor under the condition of OLR 16. 0 kg COD/（m^3·d）, ORP and HRT about - 139 mV and 6.7 h, respectively, and then the reaction system transformed to ethanol-type fermentation gradually with the increase in OLR. When OLR, ORP and HRT were about 94.3 kg COD/（m^3·d）, -250 mV and 1.7 h, respectively, the system achieved the maximum hydrogen-producing rate of 282.6 mL H2/L reactor·h and hydrogen percentage of 51% -53% in the biogas.展开更多
A new dynamic non-equilibrium mixing-pool model for simulating start-up and dynamic re-sponse of a distillation column is reported.The proposed model is established on the basis ofconsidering the two dimensional flow/...A new dynamic non-equilibrium mixing-pool model for simulating start-up and dynamic re-sponse of a distillation column is reported.The proposed model is established on the basis ofconsidering the two dimensional flow/mixing behavior of actual trays in a distillation column.Com-parison is made among the computed results of the start-up time and the dynamic response time bythe proposed and five other typical models.It is found that the computed time for both dynamicprocesses is longer by the model which considers any flow/mixing pattern than by the model withoutsuch concern.The inertia effect of flow/mixing seems to be important and can not be ignored inmodeling the transient process of distillation.The proposed model,which is believed to be suitableto large column,seems somewhat useful in predicting industrial distillation dynamics.展开更多
Micro-mobile heat pipe-cooled nuclear power plants are promising candidates for distributed energy resource power genera-tors and can be flexibly deployed in remote places to meet increasing electric power demands.How...Micro-mobile heat pipe-cooled nuclear power plants are promising candidates for distributed energy resource power genera-tors and can be flexibly deployed in remote places to meet increasing electric power demands.However,previous steady-state simulations and experiments have deviated significantly from actual micronuclear system operations.Hence,a transient analysis is required for performance optimization and safety assessment.In this study,a hardware-in-the-loop(HIL)approach was used to investigate the dynamic behavior of scaled-down heat pipe-cooled systems.The real-time features of the HIL architecture were interpreted and validated,and an optimal time step of 500 ms was selected for the thermal transient.The power transient was modeled using point kinetic equations,and a scaled-down thermal prototype was set up to avoid mod-eling unpredictable heat transfer behaviors and feeding temperature samples into the main program running on a desktop PC.A series of dynamic test results showed significant power and temperature oscillations during the transient process,owing to the inconsistency of the rapid nuclear reaction rate and large thermal inertia.The proposed HIL approach is stable and effective for further studying of the dynamic characteristics and control optimization of solid-state small nuclear-powered systems at an early prototyping stage.展开更多
This research paper investigates the role of Italian venture capital in supporting innovative start-ups in their early-stage process,which is usually focused on the creation of a new product or the development of a ne...This research paper investigates the role of Italian venture capital in supporting innovative start-ups in their early-stage process,which is usually focused on the creation of a new product or the development of a new service.The aim of the study is to observe and assess the key economic features of innovative start-ups funded at the beginning of the early-stage by venture capital funds and thereafter analyze the level of development of target companies at four years since the capital injection.The sample of deals created to describe this dynamic process is composed by investments realized between 1996 and 2012 and,in this way,according to the chosen methodology,it is representative of Italian venture capital role and contribution in the years from 1996 to 2016.The authors used for their empirical study a proprietary database,Venture Capital Monitor—VeMTM.Through the analysis of collected data,the paper describes the strategic importance of venture capital investments in early-stage opportunities both for target companies and the Italian socio-economic environment,and finds aggregate values of reference to quantitatively define the socio-economic outcome of this kind of operations.A final further contribution is provided by comparing the present results to the ones of two previous studies conducted by the authors.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
Recently published in Joule,Feng Liu and colleagues from Shanghai Jiaotong University reported a record-breaking 20.8%power conversion efficiency in organic solar cells(OSCs)with an interpenetrating fibril network act...Recently published in Joule,Feng Liu and colleagues from Shanghai Jiaotong University reported a record-breaking 20.8%power conversion efficiency in organic solar cells(OSCs)with an interpenetrating fibril network active layer morphology,featuring a bulk p-in structure and proper vertical segregation achieved through additive-assisted layer-by-layer deposition.This optimized hierarchical gradient fibrillar morphology and optical management synergistically facilitates exciton diffusion,reduces recombination losses,and enhances light capture capability.This approach not only offers a solution to achieving high-efficiency devices but also demonstrates the potential for commercial applications of OSCs.展开更多
Fenton and Fenton-like processes,which could produce highly reactive species to degrade organic contaminants,have been widely used in the field of wastewater treatment.Therein,the chemistry of Fenton process including...Fenton and Fenton-like processes,which could produce highly reactive species to degrade organic contaminants,have been widely used in the field of wastewater treatment.Therein,the chemistry of Fenton process including the nature of active oxidants,the complicated reactions involved,and the behind reason for its strongly pH-dependent performance,is the basis for the application of Fenton and Fenton-like processes in wastewater treatment.Nevertheless,the conflicting views still exist about the mechanism of the Fenton process.For instance,reaching a unanimous consensus on the nature of active oxidants(hydroxyl radical or tetravalent iron)in this process remains challenging.This review comprehensively examined the mechanism of the Fenton process including the debate on the nature of active oxidants,reactions involved in the Fenton process,and the behind reason for the pH-dependent degradation of contaminants in the Fenton process.Then,we summarized several strategies that promote the Fe(Ⅱ)/Fe(Ⅲ)cycle,reduce the competitive consumption of active oxidants by side reactions,and replace the Fenton reagent,thus improving the performance of the Fenton process.Furthermore,advances for the future were proposed including the demand for the high-accuracy identification of active oxidants and taking advantages of the characteristic of target contaminants during the degradation of contaminants by the Fenton process.展开更多
文摘The start-up process of Stokes＇ second problem of a viscoelastic material with fractional element is studied. The fluid above an infinite flat plane is set in motion by a sudden acceleration of the plate to steady oscillation. Exact solutions are obtained by using Laplace transform and Fourier transform. It is found that the relationship between the first peak value and the one of equal-amplitude oscillations depends on the distance from the plate. The amplitude decreases for increasing frequency and increasing distance.
文摘A particle-in-cell Monte Carlo collision model of a discharge chamber is established to investigate the start-up process of a miniature ion thruster.We present the discharge characteristics at different stages(the initial stage,development stage,and stable stage)according to the trend of the discharge current with time.The discharge current is the sum of the sidewall current and the backplate current.During the start-up process,the sidewall current lags behind the backplate current.The variation and distribution characteristics of the discharge current over time are determined by the electron density distribution and electric potential distribution.
基金supported by the National Level Project of China.
文摘Solid rocket motors have important applications in the propulsion of trans-media vehicles and underwater launched rockets.In this paper,the ignition start-up process of an underwater solid rocket motor across a wide depth range has been numerically studied.A novel multi-domain integrated model has been developed by combining the solid propellant ignition and combustion model with the volume of fluid multiphase model.This integrated model enables the coupled simulation of the propellant combustion and gas flow inside the motor,along with the gas jet evolution in the external water environment.The detailed flow field developments in the combustion chamber,nozzle,and wake field are carefully analyzed.The variation rules of the internal ballistics and thrust performance are also obtained.The effects of environmental medium and operating depth on the ignition start-up process are systematically discussed.The results show that the influence of the operating environment on the internal ballistic characteristics is primarily reflected in the initial period after the nozzle closure opens.The development of the gas jet in water lags significantly compared with that in air.As the water depth increases,the ignition delay time of the motor is shortened,and the morphology evolution of the gas jet is significantly compressed and accelerated.Furthermore,the necking and bulging of the jet boundary near the nozzle outlet and the consequent shock oscillations are intensified,resulting in stronger fluctuations in the wake pressure field and motor thrust.
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 Major State Science and Technology Water Projects (No. 2013ZX07202010)
文摘N-dodecanoyl homoserine lactone（C（12）-HSL）was detected in the supernatant of an anammox granular sludge reactor（AGSR）.C（12）-HSL could enhance the specific anammox activity of anammox biomass.Adding C（12）-HSL-containing AGSR supernatant into the continuously stirred tank reactors reduced the start-up time of the anammox process from80 to 66 days.Moreover,the nitrogen loading rate was also enhanced to 1.6 times that of the control reactor.AHLs could increase the secretion of extracellular polymeric substances and anammox obtained better enrichment with the addition of AHLs-containing AGSR supernatant.Denaturing gradient gel electrophoresis analysis further revealed that AHLs played a role in mediating microbial community parameters.In conclusion,adding AHL-containing supernatant could be an effective and economical way to accelerate the start-up of anammox.
文摘Expanded granular sludge bed （EGSB） reactor and bioaugmentation were employed to investigate biohydrogen production with molasses wastewater. The start-up experiments consisted of two stages. In the first stage （0 - 24d） seeded with activated sludge, the butyric acid type-fermentation formed when the initial expanding rate, organic loading rate （OLR）, the initial redox potential （ORP） and hydraulic retention time （HRT） were 10%, 10.0 kg COD/（m^3·d）, -215 mV and 6.7 h, respectively. At the beginning of the second stage on day 25, the novel hydrogen-producing fermentative bacterial strain B49 （AF481148 in EMBL） were inoculated into the reactor under the condition of OLR 16. 0 kg COD/（m^3·d）, ORP and HRT about - 139 mV and 6.7 h, respectively, and then the reaction system transformed to ethanol-type fermentation gradually with the increase in OLR. When OLR, ORP and HRT were about 94.3 kg COD/（m^3·d）, -250 mV and 1.7 h, respectively, the system achieved the maximum hydrogen-producing rate of 282.6 mL H2/L reactor·h and hydrogen percentage of 51% -53% in the biogas.
文摘A new dynamic non-equilibrium mixing-pool model for simulating start-up and dynamic re-sponse of a distillation column is reported.The proposed model is established on the basis ofconsidering the two dimensional flow/mixing behavior of actual trays in a distillation column.Com-parison is made among the computed results of the start-up time and the dynamic response time bythe proposed and five other typical models.It is found that the computed time for both dynamicprocesses is longer by the model which considers any flow/mixing pattern than by the model withoutsuch concern.The inertia effect of flow/mixing seems to be important and can not be ignored inmodeling the transient process of distillation.The proposed model,which is believed to be suitableto large column,seems somewhat useful in predicting industrial distillation dynamics.
基金This work was financially supported by the National Key R&D Program of China(No.2020YFB1901900)National Natural Science Foundation of China(No.12275175)+2 种基金Special Fund for Strengthening Industry of Shanghai(No.GYQJ-2018-2-02)Shanghai Rising Star Program(No.21QA1404200)the LingChuang Research Project of the China National Nuclear Corporation.
文摘Micro-mobile heat pipe-cooled nuclear power plants are promising candidates for distributed energy resource power genera-tors and can be flexibly deployed in remote places to meet increasing electric power demands.However,previous steady-state simulations and experiments have deviated significantly from actual micronuclear system operations.Hence,a transient analysis is required for performance optimization and safety assessment.In this study,a hardware-in-the-loop(HIL)approach was used to investigate the dynamic behavior of scaled-down heat pipe-cooled systems.The real-time features of the HIL architecture were interpreted and validated,and an optimal time step of 500 ms was selected for the thermal transient.The power transient was modeled using point kinetic equations,and a scaled-down thermal prototype was set up to avoid mod-eling unpredictable heat transfer behaviors and feeding temperature samples into the main program running on a desktop PC.A series of dynamic test results showed significant power and temperature oscillations during the transient process,owing to the inconsistency of the rapid nuclear reaction rate and large thermal inertia.The proposed HIL approach is stable and effective for further studying of the dynamic characteristics and control optimization of solid-state small nuclear-powered systems at an early prototyping stage.
文摘This research paper investigates the role of Italian venture capital in supporting innovative start-ups in their early-stage process,which is usually focused on the creation of a new product or the development of a new service.The aim of the study is to observe and assess the key economic features of innovative start-ups funded at the beginning of the early-stage by venture capital funds and thereafter analyze the level of development of target companies at four years since the capital injection.The sample of deals created to describe this dynamic process is composed by investments realized between 1996 and 2012 and,in this way,according to the chosen methodology,it is representative of Italian venture capital role and contribution in the years from 1996 to 2016.The authors used for their empirical study a proprietary database,Venture Capital Monitor—VeMTM.Through the analysis of collected data,the paper describes the strategic importance of venture capital investments in early-stage opportunities both for target companies and the Italian socio-economic environment,and finds aggregate values of reference to quantitatively define the socio-economic outcome of this kind of operations.A final further contribution is provided by comparing the present results to the ones of two previous studies conducted by the authors.
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.
基金Technology Development Program of Jilin Province(YDZJ202201ZYTS640)the National Key Research and Development Program of China(2022YFB4200400)funded by MOST+4 种基金the National Natural Science Foundation of China(52172048 and 52103221)Shandong Provincial Natural Science Foundation(ZR2021QB024 and ZR2021ZD06)Guangdong Basic and Applied Basic Research Foundation(2023A1515012323,2023A1515010943,and 2024A1515010023)the Qingdao New Energy Shandong Laboratory open Project(QNESL OP 202309)the Fundamental Research Funds of Shandong University.
文摘Recently published in Joule,Feng Liu and colleagues from Shanghai Jiaotong University reported a record-breaking 20.8%power conversion efficiency in organic solar cells(OSCs)with an interpenetrating fibril network active layer morphology,featuring a bulk p-in structure and proper vertical segregation achieved through additive-assisted layer-by-layer deposition.This optimized hierarchical gradient fibrillar morphology and optical management synergistically facilitates exciton diffusion,reduces recombination losses,and enhances light capture capability.This approach not only offers a solution to achieving high-efficiency devices but also demonstrates the potential for commercial applications of OSCs.
基金supported by the National Natural Science Foundation of China(Nos.22206050 and 52270047).
文摘Fenton and Fenton-like processes,which could produce highly reactive species to degrade organic contaminants,have been widely used in the field of wastewater treatment.Therein,the chemistry of Fenton process including the nature of active oxidants,the complicated reactions involved,and the behind reason for its strongly pH-dependent performance,is the basis for the application of Fenton and Fenton-like processes in wastewater treatment.Nevertheless,the conflicting views still exist about the mechanism of the Fenton process.For instance,reaching a unanimous consensus on the nature of active oxidants(hydroxyl radical or tetravalent iron)in this process remains challenging.This review comprehensively examined the mechanism of the Fenton process including the debate on the nature of active oxidants,reactions involved in the Fenton process,and the behind reason for the pH-dependent degradation of contaminants in the Fenton process.Then,we summarized several strategies that promote the Fe(Ⅱ)/Fe(Ⅲ)cycle,reduce the competitive consumption of active oxidants by side reactions,and replace the Fenton reagent,thus improving the performance of the Fenton process.Furthermore,advances for the future were proposed including the demand for the high-accuracy identification of active oxidants and taking advantages of the characteristic of target contaminants during the degradation of contaminants by the Fenton process.
