Objective:Artemether is a semi-synthetic derivative of artemisinin and is widely used in the treatment of Plasmodium(P.)falciparum malaria.This study aimed to characterize the safety profile of artemether based on 15-...Objective:Artemether is a semi-synthetic derivative of artemisinin and is widely used in the treatment of Plasmodium(P.)falciparum malaria.This study aimed to characterize the safety profile of artemether based on 15-year data retrived from FDA adverse event reporting system(FAERS).Methods:This is a retrospective analysis on 15-year data of artemether-related adverse effects(AEs)retrieved from the FAERS.AEs were classified according to System Organ Class(SOC)and Preferred Terms(PT).Signal detection was performed using Reporting Odds Ratios(ROR),Proportional Reporting Ratios(PRR),and Empirical Bayes Geometric Mean(EBGM).Stratified analyses examined the impact of demographic factors such as sex,age,and time-to-onset.Temporal patterns and associated risk factors were also investigated.Results:Haemolytic anaemia and haemolysis emerged as the most frequently reported AEs,exhibiting significantly elevated RORs(males:ROR 381.36,95%CI 247.06-588.60;females:ROR 455.11,95%CI 286.43-723.12).Sex-specific differences were evident,with females showing a higher incidence of reproductive-related AEs,including spontaneous abortion and premature labour.Temporal trend analysis revealed that the majority of AEs occurred within the first 30 days after the initiation of artemether administration,indicating a rapid onset.The most affected SOCs were blood and lymphatic system disorders and hepatobiliary disorders.Conclusions:Artemether is associated with a notable frequency of early-onset AEs,particularly hematological and hepatobiliary disorders.The observed sex-specific vulnerability to reproductive AEs highlights the need for sex-conscious clinical approaches.Enhanced post-treatment monitoring and further investigations into the drug’s pharmacokinetics and mechanistic pathways are recommended.展开更多
This study takes"ocean heat waves"as a typical case to study the scientific definition,driving mechanisms,multi-dimensional impacts,and response strategies of extreme climate events.The definition of extreme...This study takes"ocean heat waves"as a typical case to study the scientific definition,driving mechanisms,multi-dimensional impacts,and response strategies of extreme climate events.The definition of extreme events requires a comprehensive consideration of statistical thresholds and social impacts.It is mainly driven by global warming caused by human emissions of greenhouse gases,and is also influenced by the interaction of natural variations such as ENSO.Extreme events cause systematic and cascading impacts on human health,infrastructure,agricultural economy,and ecosystems(especially marine ecosystems).Advanced technologies such as satellite remote sensing,climate models,and artificial intelligence have significantly enhanced their monitoring and prediction capabilities.However,effective responses still require a parallel strategy of mitigation and adaptation,and international cooperation is strengthened through the framework of the Paris Agreement.展开更多
Precipitation events,which follow a life cycle of initiation,development,and decay,represent the fundamental form of precipitation.Comprehensive and accurate detection of these events is crucial for effective water re...Precipitation events,which follow a life cycle of initiation,development,and decay,represent the fundamental form of precipitation.Comprehensive and accurate detection of these events is crucial for effective water resource management and flood control.However,current investigations on their spatio-temporal patterns remain limited,largely because of the lack of systematic detection indices that are specifically designed for precipitation events,which constrains event-scale research.In this study,we defined a set of precipitation event detection indices(PEDI)that consists of five conventional and fourteen extreme indices to characterize precipitation events from the perspectives of intensity,duration,and frequency.Applications of the PEDI revealed the spatial patterns of hourly precipitation events in China and its first-and second-order river basins from 2008 to 2017.Both conventional and extreme precipitation events displayed spatial distribution patterns that gradually decreased in intensity,duration,and frequency from southeast to northwest China.Compared with those in northwest China,the average values of most PEDIs in southeast China were usually 2-10 times greater for first-order river basins and 3-15 times greater for second-order basins.The PEDI could serve as a reference method for investigating precipitation events at global,regional,and basin scales.展开更多
Detector and event visualization are crucial components of high-energy physics(HEP)experimental software.Virtual reality(VR)technologies and multimedia development platforms,such as Unity,offer enhanced display effect...Detector and event visualization are crucial components of high-energy physics(HEP)experimental software.Virtual reality(VR)technologies and multimedia development platforms,such as Unity,offer enhanced display effects and flexible extensibility for visualization in HEP experiments.In this study,we present a VR-based method for detector and event displays in the Jiangmen Underground Neutrino Observatory(JUNO)experiment.This method shares the same detector geometry descriptions and event data model as those in the offline software and provides the necessary data conversion interfaces.The VR methodology facilitates an immersive exploration of the virtual environment in JUNO,enabling users to investigate the detector geometry,visualize event data,and tune the detector simulation and event reconstruction algorithms.Additionally,this approach supports applications in data monitoring,physics data analysis,and public outreach initiatives.展开更多
The Cooling-Storage-Ring External-target Experiment(CEE)at the Heavy Ion Research Facility in Lanzhou(HIRFL)is designed to study the properties of nuclear matter created in heavy-ion collisions at beam energies from a...The Cooling-Storage-Ring External-target Experiment(CEE)at the Heavy Ion Research Facility in Lanzhou(HIRFL)is designed to study the properties of nuclear matter created in heavy-ion collisions at beam energies from a few hundred MeV/u up to 1 GeV/u.It aims to facilitate research on the quantum chromodynamics(QCD)phase structure in the high-baryondensity region.Collective flow is a fundamental observable in heavy-ion collision experiments,providing information on the bulk properties of the produced matter.Although the standard event plane method has been widely used to measure collective flow,it is still important to validate and optimize this method for the CEE spectrometer.In this paper,we study the experimental procedures for measuring directed flow in^(238)U+^(238)U collisions at 500 MeV/u,using event planes reconstructed by Multi-Wire Drift Chamber and Zero Degree Calorimeter,respectively.Jet AA Microscopic(JAM)transport generator is used to generate events,and the detector response is simulated by the CEE Fast Simulation(CFS)package.Finally,the optimal kinematic region for proton directed flow measurements is discussed for the future CEE experiment.展开更多
Hydrological extremes,such as floods,droughts,and compound events,are extremely dangerous to human societies,ecosystems,and infrastructures,whose frequency and severity are affected by climate change more and more.Eff...Hydrological extremes,such as floods,droughts,and compound events,are extremely dangerous to human societies,ecosystems,and infrastructures,whose frequency and severity are affected by climate change more and more.Effective disaster preparedness,water resource management,and climate adaptation have to do with accurate prediction and extensive risk assessment.This review sums up recent progress in predictive modeling and risk assessment systems in the framework of hydrological extremes in the changing climatic conditions.Statistical and empirical techniques,including extreme value theory and nonstationary frequency analysis,give probabilistic information using historic records,whereas process-based models give an understanding of physical hydrological processes at different climate and land-use conditions.New information-based and hybrid methods that use machine learning and high-resolution data take advantage of the complexity and nonlinearities and enhance the predictive power.Hazard,exposure,vulnerability,and adaptive capacity risk assessment models allow predictive output to be translated into actionable decision support,with socio-economic aspects and analysis of the scenario.Case studies of various regions across the globe show the use of these techniques to address floods,droughts,and compound events,with success and current problems.The review also addresses current trends such as compound hazard,multi-hazard integration,AI-enabled modelling,and cross-sectoral decision support,and outlines research priorities of improving predictive capability and resilience.This review will inform researchers,policymakers,and practitioners by offering a synthesis of all the effects of the hydrological extremes in climate change to formulate sound strategies for alleviating these effects.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
Accurate identification of sediment sources and erosion hotspots is crucial for implementing targeted soil and water conservation measures.This study analyzed the temporal dynamics of sediment source contributions dur...Accurate identification of sediment sources and erosion hotspots is crucial for implementing targeted soil and water conservation measures.This study analyzed the temporal dynamics of sediment source contributions during seven rainfall events(A_(1)–A_(7))that generated both runoff and suspended sediment at the outlet of the Hantaichuan watershed,located in the wind–water erosion crisscross region of the northern Loess Plateau,China.A total of 82 suspended sediment samples were collected at the Xiangshawan hydrological station during 2021 and 2022.Additionally,145 soil samples were collected from three primary potential sources:sandy soil,loess soil,and Pisha sandstone.Mid-infrared(MIR)spectroscopy and geochemical fingerprinting were used to trace and quantify sediment sources.For MIRbased source apportionment,twelve predictive models were developed using partial least squares regression(PLSR)and support vector machine regression(SVMR)in combination with six spectral preprocessing techniques.The PLSR model with first-derivative Savitzky–Golay(SGD1)preprocessing achieved the best performance.Source apportionment results indicated that Pisha sandstone was the dominant sediment source(44.00%–72.23%),followed by sandy soil(14.23%–37.00%)and loess soil(10.01%–24.00%).Among the analyzed rainfall events,the contribution of Pisha sandstone was lowest in the small flow magnitude event A3(57.53%)and highest in the large flow magnitude event A6(63.48%),suggesting that sediment source composition was strongly controlled by rainfall event magnitude.Both MIR spectroscopic and geochemical fingerprinting methods showed high consistency,confirming MIR spectroscopy as a reliable,non-destructive,and cost-effective alternative for rapid sediment source apportionment and for supporting erosion control prioritization in highly erodible catchments.展开更多
This study examines a 1.32 m thick sediment sequence from the Cunge sag pond in the Litang Basin,eastern Tibetan Plateau,to assess the seismicity of the Litang fault during the Holocene.High-resolution geochemical,gra...This study examines a 1.32 m thick sediment sequence from the Cunge sag pond in the Litang Basin,eastern Tibetan Plateau,to assess the seismicity of the Litang fault during the Holocene.High-resolution geochemical,grain size,magnetic susceptibility,and total organic carbon indicators are employed to obtain a continuous record of changes in elemental,physical,and biological properties within the profile to identify seismic events.The seismic event layer generally comprises two sedimentary rhythms:a lower coarse sand layer and an upper fine silt-clay layer.These layers represent rapid deposition associated with fault activity(Earthquake A)and slower deposition during calm periods or earthquake recurrence intervals(Seismic interval A).Through six^(14)C dating,five seismic events have been identified in the Cunge sag pond section:E1(before 3955 a B.P.),E2(3713-3703 a B.P.),E3(3492-3392 a B.P.),E4(2031-1894 a B.P.),and E5(1384-1321 a B.P.).E1-E4 had shown a good consistency with the paleo-earthquake recorded by the trench,and whereas E5 is a newly identified seismic event,further improving the continuous earthquake sequence of the Litang fault.Based on existing trench data and the seismic event record from the Cunge sag pond,a total of 11 paleo-earthquakes are identified along the Litang fault since the Holocene.The paleo-earthquake activity of the Litang fault exhibits a clustered pattern,with recurrence intervals of both long periods(1000 a)and short periods(500 a).Since 5000 a,the interval between strong earthquake recurrences gradually decreases,indicating an increasing risk of strong earthquakes along the Litang fault.This study presents a continuous record of paleo-earthquakes along the Litang fault,eastern Tibetan Plateau,and can enhance the understanding of regional seismic activity.展开更多
Extreme rainfall events(EREs)frequently hit the middle and lower reaches of the Yellow River basin(YRB)during boreal summer.Recent observations have indicated that EREs exhibit teleconnection patterns across long spat...Extreme rainfall events(EREs)frequently hit the middle and lower reaches of the Yellow River basin(YRB)during boreal summer.Recent observations have indicated that EREs exhibit teleconnection patterns across long spatial distances.This study investigated ERE teleconnections in the YRB using the Event Synchronization(ES)method in combination with Complex Network(CN)theory.EREs in the YRB are significantly synchronized with other regions from regional to global scales.Additionally,high-resolution CMIP6 models in general show better skill in capturing these characteristics compared to low-resolution models.A further examination shows that the spatial synchronization patterns exhibit pronounced timescale dependence.Significant ERE synchronizations between the YRB and Europe were uncovered,where the YRB lags Eastern Europe by 3-5 days and Western Europe by 5-7 days,with Rossby wave propagation playing a key role.Wave trains from Europe propagate downstream along the Eurasian jet,inducing anomalous circulations over the YRB that enhance vertical upward motion and moisture transport,ultimately triggering EREs.Two distinct wave trains are observed:one is associated with Eastern Europe-YRB synchronization,occurring in the midlatitude region;the other is linked to Western Europe-YRB synchronization,positioned at higher latitudes.Notably,17.5%of Eastern Europe-YRB synchronization cases and 17.0%of Western Europe-YRB cases overlap.Quantitative analysis indicates that the synchronized events between Eastern(Western)Europe and the YRB account for roughly 28%(30%)of EREs in the YRB.These findings are critical for better understanding ERE mechanisms,offering guidance for forecasting and early warning capabilities for EREs in the YRB.展开更多
In this study,the mechanism and characteristics of the responseαparticles and the damage caused by them in CMOS active pixel(APS)sensors were investigated.A detection and compensation algorithm for dead pixels caused...In this study,the mechanism and characteristics of the responseαparticles and the damage caused by them in CMOS active pixel(APS)sensors were investigated.A detection and compensation algorithm for dead pixels caused byαparticle ionizing radiation was proposed,and the effects of dead-pixel compensation algorithms were compared and analyzed under different parameter conditions.The experimental results show thatαparticle response signal has highest accuracy at 9 dB gain,with an obvious“target-ring”distribution.With increasing cumulative dose,the CMOS APS pedestal tends to saturation while dead pixels continue increasing.Though some pixel damage recovers through natural annealing,the dead-to-noise ratio increases with irradiation time,reaching 32.54%after 72 h.A hierarchical clustering dead-pixel detection method is proposed,categorizing pixels into two types:those within and outside the response event.A classification compensation strategy combining mean and majority filtering is proposed.This compensation algorithm can address dead-pixel interference without affectingαparticle radiation response data.When iterated multiple times and with integration time exceeding 6.31 ms,the number of dead pixels can be effectively reduced.展开更多
A Good Start The annual“two sessions”are among the most important political events in China,during which the country outlines its economic and social policies,sets development priorities,and addresses issues that ma...A Good Start The annual“two sessions”are among the most important political events in China,during which the country outlines its economic and social policies,sets development priorities,and addresses issues that may affect the future of the global economy.展开更多
Recent studies have suggested that rapid warming over the Mongolian Plateau(MP)may intensify extreme heat events(EHEs).However,the characteristics and mechanisms driving summer EHEs over the MP(MP-EHEs)remain unclear....Recent studies have suggested that rapid warming over the Mongolian Plateau(MP)may intensify extreme heat events(EHEs).However,the characteristics and mechanisms driving summer EHEs over the MP(MP-EHEs)remain unclear.This study explores the interannual variations in summer MP-EHEs and their relationship with the summer soil moisture over the Inner Tibetan Plateau(TP-SM).The results reveal that changes in the MP-EHEs are linked to descending atmospheric motion induced by a local high-pressure system over the MP region.Descending motion further results in decreased mid-tolow-level cloud cover and increased shortwave radiation,thereby warming the surface and triggering summer MP-EHEs.Further analysis indicates that increased TP-SM results in a greater latent heat flux,triggering a local secondary circulation that reinforces the local high-pressure system over the MP region,thus serving to promote the occurrence of summer MPEHEs.Additionally,model results from the linear baroclinic model(LBM)and CMIP6 further confirm that variations in summer TP-SM contribute to the occurrence of the MP-EHEs.展开更多
The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risk...The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risks,including floods and droughts.Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms.Observational data reveal a 20th-century shift:increased rainfall pre-1950s,followed by aridification and partial recovery post-1980s,driven by both internal variability(e.g.,Atlantic Multidecadal Oscillation)and external forcings(greenhouse gases,aerosols),while ENSO drives interannual variability through ocean-atmosphere interactions.Future projections under greenhouse forcing suggest long-term monsoon intensification,though regional disparities and model uncertainties persist.Models indicate robust trends but struggle to quantify extremes,where thermodynamic effects(warming-induced moisture rise)uniformly boost heavy rainfall,while dynamical shifts(circulation changes)create spatial heterogeneity.Volcanic eruptions and proposed solar radiation modification(SRM)further complicate predictions:tropical eruptions suppress monsoons,whereas high-latitude events alter cross-equatorial flows,highlighting unresolved feedbacks.The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons.Critical challenges remain.Model biases and sparse 20th-century observational data hinder accurate attribution.The interplay between natural variability and anthropogenic forcings,along with nonlinear extreme precipitation risks under warming,demands deeper mechanistic insights.Additionally,SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation.Addressing these gaps necessitates enhanced observational networks,refined climate models,and interdisciplinary efforts to disentangle multiscale drivers,ultimately improving resilience strategies for monsoon-dependent regions.展开更多
Northern Xinjiang,an arid inland area in Northwest China,is highly vulnerable to air pollution under intensifying climate extremes,yet the relative roles of temperature and precipitation extremes remain insufficiently...Northern Xinjiang,an arid inland area in Northwest China,is highly vulnerable to air pollution under intensifying climate extremes,yet the relative roles of temperature and precipitation extremes remain insufficiently understood.Using multi-source datasets for 2000-2023,including China High Air Pollutants(CHAP)particulate matter 2.5(PM_(2.5)),particulate matter 10(PM_(10)),and ozone(O3)products and Expert Team on Climate Change Detection and Indices(ETCCDI)extreme climate indices derived from the European Centre for Medium-Range Weather Forecasts(ECMWF)Reanalysis v5(ERA5)-Land,together with trend detection,change-point analysis,pixel-wise Pearson correlation,and random forest(RF)modeling,we investigated the spatiotemporal evolution of major air pollutants and their responses to meteorological extremes in northern Xinjiang.PM_(2.5) and PM_(10) generally declined from 2000 to 2023,whereas O3 increased,indicating a shift from particulate-dominated pollution toward stronger photochemical pollution.Interannually,PM_(2.5) showed a rise-decline pattern,PM_(10) exhibited a rise-decline-rebound pattern,and O3 increased markedly after 2015.Clear seasonal contrasts were observed,with PM_(2.5) peaking in winter,PM_(10) in spring,and O3 in summer.During the same period,northern Xinjiang exhibited a pronounced warming-drying tendency,characterized by increasing heat-related indices,decreasing cold-related indices,reduced precipitation totals and heavy-rainfall frequency,and increasing consecutive dry days.Pollutant-climate relationships showed strong spatial heterogeneity and pollutant-specific contrasts across the Urumqi-Changji-Shihezi corridor,the Ili River Valley,and the Junggar Basin.PM_(2.5) responses to precipitation shifted from predominantly positive to negative,PM_(10) showed mainly negative associations with precipitation extremes,and O3 responses varied by subregion.Temperature-related extremes generally explained more pollutant variability than precipitation-related extremes,with PM_(2.5) showing the highest sensitivity.These findings highlight the coupled influences of warming,drying,emissions,and terrain-controlled transport on air quality and support region-specific,multi-pollutant strategies for coordinated climate adaptation and air pollution control in northern Xinjiang.展开更多
Objective:To identify the root causes of typical adverse drug events through the lens of patient experiences proposing novel strategies to mitigate preventable harm.Methods:A qualitative case study leveraging in-depth...Objective:To identify the root causes of typical adverse drug events through the lens of patient experiences proposing novel strategies to mitigate preventable harm.Methods:A qualitative case study leveraging in-depth interviews with patients and families,anchored by Interactive Patient Par ticipation Theory,to analyze 4 high-severity adverse drug events(ADE)cases.Cases were purposively sampled from 8 communities in China's National Adverse Event Monitor Center(2018-2023).Semi-structured interviews explored patient perspectives,with data analyzed via thematic coding and triangulation against clinical records.Results:Five interconnected themes emerged:(1)erosion of trust,(2)communication breakdowns,(3)information asymmetry,(4)environmental inadequacies,and(5)technological alienation.Notably,75% of participants had≤high school education,and 50% used≥7 medications daily,compounding ADE risks.Conclusions:We considered elements mentioned by theory,exploring trust,communication,information,and suppor t as the root causes.In addition,we added“adaptability to new technology”as an impor tant and necessary component.It is impor tant and necessary to analyze typical adverse drug events from the perspectives of patients.展开更多
On a summer morning in Boqiang Village,tucked beneath the emerald mountains of Fanshi County,Shanxi Province,the Ultra Trail Mount Wutai2025 commenced with the sound of the starting pistol-an event that was much more ...On a summer morning in Boqiang Village,tucked beneath the emerald mountains of Fanshi County,Shanxi Province,the Ultra Trail Mount Wutai2025 commenced with the sound of the starting pistol-an event that was much more than just a competition.As soon as the colorful smoke bombs lit up the sky,some2,000 runners from China and abroad set off to reach one of the country's most sacred Buddhist peaks.Over the past decade,this race has become a fixture on the global running calendar and a symbol of the growing popularity of endurance sports.展开更多
Background:The purpose of this study was to analyze and classify adverse drug events(ADEs)related to ceftazidime/avibactam reported in the Food and Drug Administration Adverse Event Reporting System(FAERS)database and...Background:The purpose of this study was to analyze and classify adverse drug events(ADEs)related to ceftazidime/avibactam reported in the Food and Drug Administration Adverse Event Reporting System(FAERS)database and to evaluate their potential safety signals since the drug’s market introduction.Methods:This analysis systematically extracted and filtered FAERS data for ceftazidime/avibactam from its market launch in 2015 to the last quarter of 2024,utilizing the Medical Dictionary for Regulatory Activities(MedDRA)terminology for ADE recoding.The analysis employed the reporting odds ratio(ROR)method to assess the strength of ADE signals and to identify significant diseases associated with infections,the hepatobiliary system,the urinary system,and the nervous system.Results:A review of 540 adverse reaction reports revealed significant signals of adverse effects related to infections,hepatobiliary disorders,urinary system issues,and neurological impairments,including pathogen resistance,liver and kidney function impairment,encephalopathy,thrombocytopenia,and toxic epidermal necrolysis.However,these issues require further clinical attention.Conclusion:Ceftazidime/avibactam is associated with a range of adverse reactions,necessitating enhanced clinical monitoring,particularly in patients with underlying liver or kidney dysfunction.Continuous risk assessment and vigilant monitoring are critical for its clinical use.However,this study is limited by inherent reporting biases and confounders associated with the spontaneous reporting database(FAERS).Future research should validate these signals through prospective cohort and mechanistic studies and explore personalized risk management strategies for high-risk populations.展开更多
The healthcare field is fraught with challenges associated with severe class imbalance,wherein such critical conditions like sepsis,cardiac arrest,and drug adverse reactions are rare but have dire clinical consequence...The healthcare field is fraught with challenges associated with severe class imbalance,wherein such critical conditions like sepsis,cardiac arrest,and drug adverse reactions are rare but have dire clinical consequences.This paper presents a new framework,Deep Reinforcement Adaptive Gradient Optimization Network to Mining Rare Events(DRAGON-MINE),to demonstrate how deep reinforcement learning can be used synergistically with adaptive gradient optimization and address the inherent weaknesses of current methods in the prediction of rare health events.The suggested architecture uses a dual-pathway consisting of a reinforcement learning agent to dynamically reweigh samples and an adaptive gradient optimizer to follow novel learning rates.With extensive experiments on the MIMIC-IV and eICU-CRD datasets,DRAGON-MINE consistently outperforms recent state-of-the-art methods for sepsis,cardiac arrest,and adverse drug reaction prediction,achieving AUROC values of 92.3%and 91.6%for sepsis prediction on MIMIC-IV and eICU-CRD,respectively,while consistently outperforming Transformer-,CNN-RNN-,and Fed-Ensemble-based methods across all evaluated tasks and datasets,with particularly strong gains observed in precision-recall performance under severe class imbalance.With its high sensitivity(88.4%)and specificity(90.2%),DRAGON-MINE enables reliable early warning of rare clinical events in critical care settings while minimizing false alarms,supporting safer clinical decision support systems,and demonstrating strong potential for scalable deployment across multi-institutional intensive care environments through federated learning.展开更多
文摘Objective:Artemether is a semi-synthetic derivative of artemisinin and is widely used in the treatment of Plasmodium(P.)falciparum malaria.This study aimed to characterize the safety profile of artemether based on 15-year data retrived from FDA adverse event reporting system(FAERS).Methods:This is a retrospective analysis on 15-year data of artemether-related adverse effects(AEs)retrieved from the FAERS.AEs were classified according to System Organ Class(SOC)and Preferred Terms(PT).Signal detection was performed using Reporting Odds Ratios(ROR),Proportional Reporting Ratios(PRR),and Empirical Bayes Geometric Mean(EBGM).Stratified analyses examined the impact of demographic factors such as sex,age,and time-to-onset.Temporal patterns and associated risk factors were also investigated.Results:Haemolytic anaemia and haemolysis emerged as the most frequently reported AEs,exhibiting significantly elevated RORs(males:ROR 381.36,95%CI 247.06-588.60;females:ROR 455.11,95%CI 286.43-723.12).Sex-specific differences were evident,with females showing a higher incidence of reproductive-related AEs,including spontaneous abortion and premature labour.Temporal trend analysis revealed that the majority of AEs occurred within the first 30 days after the initiation of artemether administration,indicating a rapid onset.The most affected SOCs were blood and lymphatic system disorders and hepatobiliary disorders.Conclusions:Artemether is associated with a notable frequency of early-onset AEs,particularly hematological and hepatobiliary disorders.The observed sex-specific vulnerability to reproductive AEs highlights the need for sex-conscious clinical approaches.Enhanced post-treatment monitoring and further investigations into the drug’s pharmacokinetics and mechanistic pathways are recommended.
基金Supported by the School-level Project of Sichuan Minzu College(XYZB2017ZB).
文摘This study takes"ocean heat waves"as a typical case to study the scientific definition,driving mechanisms,multi-dimensional impacts,and response strategies of extreme climate events.The definition of extreme events requires a comprehensive consideration of statistical thresholds and social impacts.It is mainly driven by global warming caused by human emissions of greenhouse gases,and is also influenced by the interaction of natural variations such as ENSO.Extreme events cause systematic and cascading impacts on human health,infrastructure,agricultural economy,and ecosystems(especially marine ecosystems).Advanced technologies such as satellite remote sensing,climate models,and artificial intelligence have significantly enhanced their monitoring and prediction capabilities.However,effective responses still require a parallel strategy of mitigation and adaptation,and international cooperation is strengthened through the framework of the Paris Agreement.
基金National Key Research and Development Program of China,No.2023YFC3206605,No.2021YFC3201102National Natural Science Foundation of China,No.41971035。
文摘Precipitation events,which follow a life cycle of initiation,development,and decay,represent the fundamental form of precipitation.Comprehensive and accurate detection of these events is crucial for effective water resource management and flood control.However,current investigations on their spatio-temporal patterns remain limited,largely because of the lack of systematic detection indices that are specifically designed for precipitation events,which constrains event-scale research.In this study,we defined a set of precipitation event detection indices(PEDI)that consists of five conventional and fourteen extreme indices to characterize precipitation events from the perspectives of intensity,duration,and frequency.Applications of the PEDI revealed the spatial patterns of hourly precipitation events in China and its first-and second-order river basins from 2008 to 2017.Both conventional and extreme precipitation events displayed spatial distribution patterns that gradually decreased in intensity,duration,and frequency from southeast to northwest China.Compared with those in northwest China,the average values of most PEDIs in southeast China were usually 2-10 times greater for first-order river basins and 3-15 times greater for second-order basins.The PEDI could serve as a reference method for investigating precipitation events at global,regional,and basin scales.
基金supported by the National Natural Science Foundation of China(Nos.12175321,W2443004,11975021,11675275,U1932101)Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA10010900)+2 种基金National Key Research and Development Program of China(Nos.2023YFA1606000 and 2020YFA0406400)National College Students Science and Technology Innovation ProjectUndergraduate Base Scientific Research Project of Sun Yat-sen University。
文摘Detector and event visualization are crucial components of high-energy physics(HEP)experimental software.Virtual reality(VR)technologies and multimedia development platforms,such as Unity,offer enhanced display effects and flexible extensibility for visualization in HEP experiments.In this study,we present a VR-based method for detector and event displays in the Jiangmen Underground Neutrino Observatory(JUNO)experiment.This method shares the same detector geometry descriptions and event data model as those in the offline software and provides the necessary data conversion interfaces.The VR methodology facilitates an immersive exploration of the virtual environment in JUNO,enabling users to investigate the detector geometry,visualize event data,and tune the detector simulation and event reconstruction algorithms.Additionally,this approach supports applications in data monitoring,physics data analysis,and public outreach initiatives.
基金supported in part by the National Key R&D Program of China(No.2024YFA1610700)the National Natural Science Foundation of China(No.12475147)。
文摘The Cooling-Storage-Ring External-target Experiment(CEE)at the Heavy Ion Research Facility in Lanzhou(HIRFL)is designed to study the properties of nuclear matter created in heavy-ion collisions at beam energies from a few hundred MeV/u up to 1 GeV/u.It aims to facilitate research on the quantum chromodynamics(QCD)phase structure in the high-baryondensity region.Collective flow is a fundamental observable in heavy-ion collision experiments,providing information on the bulk properties of the produced matter.Although the standard event plane method has been widely used to measure collective flow,it is still important to validate and optimize this method for the CEE spectrometer.In this paper,we study the experimental procedures for measuring directed flow in^(238)U+^(238)U collisions at 500 MeV/u,using event planes reconstructed by Multi-Wire Drift Chamber and Zero Degree Calorimeter,respectively.Jet AA Microscopic(JAM)transport generator is used to generate events,and the detector response is simulated by the CEE Fast Simulation(CFS)package.Finally,the optimal kinematic region for proton directed flow measurements is discussed for the future CEE experiment.
文摘Hydrological extremes,such as floods,droughts,and compound events,are extremely dangerous to human societies,ecosystems,and infrastructures,whose frequency and severity are affected by climate change more and more.Effective disaster preparedness,water resource management,and climate adaptation have to do with accurate prediction and extensive risk assessment.This review sums up recent progress in predictive modeling and risk assessment systems in the framework of hydrological extremes in the changing climatic conditions.Statistical and empirical techniques,including extreme value theory and nonstationary frequency analysis,give probabilistic information using historic records,whereas process-based models give an understanding of physical hydrological processes at different climate and land-use conditions.New information-based and hybrid methods that use machine learning and high-resolution data take advantage of the complexity and nonlinearities and enhance the predictive power.Hazard,exposure,vulnerability,and adaptive capacity risk assessment models allow predictive output to be translated into actionable decision support,with socio-economic aspects and analysis of the scenario.Case studies of various regions across the globe show the use of these techniques to address floods,droughts,and compound events,with success and current problems.The review also addresses current trends such as compound hazard,multi-hazard integration,AI-enabled modelling,and cross-sectoral decision support,and outlines research priorities of improving predictive capability and resilience.This review will inform researchers,policymakers,and practitioners by offering a synthesis of all the effects of the hydrological extremes in climate change to formulate sound strategies for alleviating these effects.
文摘Processes supported by process-aware information systems are subject to continuous and often subtle changes due to evolving operational,organizational,or regulatory factors.These changes,referred to as incremental concept drift,gradually alter the behavior or structure of processes,making their detection and localization a challenging task.Traditional process mining techniques frequently assume process stationarity and are limited in their ability to detect such drift,particularly from a control-flow perspective.The objective of this research is to develop an interpretable and robust framework capable of detecting and localizing incremental concept drift in event logs,with a specific emphasis on the structural evolution of control-flow semantics in processes.We propose DriftXMiner,a control-flow-aware hybrid framework that combines statistical,machine learning,and process model analysis techniques.The approach comprises three key components:(1)Cumulative Drift Scanner that tracks directional statistical deviations to detect early drift signals;(2)a Temporal Clustering and Drift-Aware Forest Ensemble(DAFE)to capture distributional and classification-level changes in process behavior;and(3)Petri net-based process model reconstruction,which enables the precise localization of structural drift using transition deviation metrics and replay fitness scores.Experimental validation on the BPI Challenge 2017 event log demonstrates that DriftXMiner effectively identifies and localizes gradual and incremental process drift over time.The framework achieves a detection accuracy of 92.5%,a localization precision of 90.3%,and an F1-score of 0.91,outperforming competitive baselines such as CUSUM+Histograms and ADWIN+Alpha Miner.Visual analyses further confirm that identified drift points align with transitions in control-flow models and behavioral cluster structures.DriftXMiner offers a novel and interpretable solution for incremental concept drift detection and localization in dynamic,process-aware systems.By integrating statistical signal accumulation,temporal behavior profiling,and structural process mining,the framework enables finegrained drift explanation and supports adaptive process intelligence in evolving environments.Its modular architecture supports extension to streaming data and real-time monitoring contexts.
基金supported by the National Key Scientific Research Project(Grant No.2023YFC3209303)jointly funded by the National Natural Sciences Foundation of China(Grant Nos.42577406 and 42077076)the National Natural Science Foundation of China and Yellow River Water Science Research Joint Fund(Grant No.U2243211).
文摘Accurate identification of sediment sources and erosion hotspots is crucial for implementing targeted soil and water conservation measures.This study analyzed the temporal dynamics of sediment source contributions during seven rainfall events(A_(1)–A_(7))that generated both runoff and suspended sediment at the outlet of the Hantaichuan watershed,located in the wind–water erosion crisscross region of the northern Loess Plateau,China.A total of 82 suspended sediment samples were collected at the Xiangshawan hydrological station during 2021 and 2022.Additionally,145 soil samples were collected from three primary potential sources:sandy soil,loess soil,and Pisha sandstone.Mid-infrared(MIR)spectroscopy and geochemical fingerprinting were used to trace and quantify sediment sources.For MIRbased source apportionment,twelve predictive models were developed using partial least squares regression(PLSR)and support vector machine regression(SVMR)in combination with six spectral preprocessing techniques.The PLSR model with first-derivative Savitzky–Golay(SGD1)preprocessing achieved the best performance.Source apportionment results indicated that Pisha sandstone was the dominant sediment source(44.00%–72.23%),followed by sandy soil(14.23%–37.00%)and loess soil(10.01%–24.00%).Among the analyzed rainfall events,the contribution of Pisha sandstone was lowest in the small flow magnitude event A3(57.53%)and highest in the large flow magnitude event A6(63.48%),suggesting that sediment source composition was strongly controlled by rainfall event magnitude.Both MIR spectroscopic and geochemical fingerprinting methods showed high consistency,confirming MIR spectroscopy as a reliable,non-destructive,and cost-effective alternative for rapid sediment source apportionment and for supporting erosion control prioritization in highly erodible catchments.
基金supported by the National Natural Science Foundation of China(42202131 and 42177184).
文摘This study examines a 1.32 m thick sediment sequence from the Cunge sag pond in the Litang Basin,eastern Tibetan Plateau,to assess the seismicity of the Litang fault during the Holocene.High-resolution geochemical,grain size,magnetic susceptibility,and total organic carbon indicators are employed to obtain a continuous record of changes in elemental,physical,and biological properties within the profile to identify seismic events.The seismic event layer generally comprises two sedimentary rhythms:a lower coarse sand layer and an upper fine silt-clay layer.These layers represent rapid deposition associated with fault activity(Earthquake A)and slower deposition during calm periods or earthquake recurrence intervals(Seismic interval A).Through six^(14)C dating,five seismic events have been identified in the Cunge sag pond section:E1(before 3955 a B.P.),E2(3713-3703 a B.P.),E3(3492-3392 a B.P.),E4(2031-1894 a B.P.),and E5(1384-1321 a B.P.).E1-E4 had shown a good consistency with the paleo-earthquake recorded by the trench,and whereas E5 is a newly identified seismic event,further improving the continuous earthquake sequence of the Litang fault.Based on existing trench data and the seismic event record from the Cunge sag pond,a total of 11 paleo-earthquakes are identified along the Litang fault since the Holocene.The paleo-earthquake activity of the Litang fault exhibits a clustered pattern,with recurrence intervals of both long periods(1000 a)and short periods(500 a).Since 5000 a,the interval between strong earthquake recurrences gradually decreases,indicating an increasing risk of strong earthquakes along the Litang fault.This study presents a continuous record of paleo-earthquakes along the Litang fault,eastern Tibetan Plateau,and can enhance the understanding of regional seismic activity.
基金the Guangdong Basic and Applied Basic Research Foundation (Grant No. 2023B1515020084)the National Natural Science Foundation of China (Grant Nos.42175068, 42475057, and 42261144687)
文摘Extreme rainfall events(EREs)frequently hit the middle and lower reaches of the Yellow River basin(YRB)during boreal summer.Recent observations have indicated that EREs exhibit teleconnection patterns across long spatial distances.This study investigated ERE teleconnections in the YRB using the Event Synchronization(ES)method in combination with Complex Network(CN)theory.EREs in the YRB are significantly synchronized with other regions from regional to global scales.Additionally,high-resolution CMIP6 models in general show better skill in capturing these characteristics compared to low-resolution models.A further examination shows that the spatial synchronization patterns exhibit pronounced timescale dependence.Significant ERE synchronizations between the YRB and Europe were uncovered,where the YRB lags Eastern Europe by 3-5 days and Western Europe by 5-7 days,with Rossby wave propagation playing a key role.Wave trains from Europe propagate downstream along the Eurasian jet,inducing anomalous circulations over the YRB that enhance vertical upward motion and moisture transport,ultimately triggering EREs.Two distinct wave trains are observed:one is associated with Eastern Europe-YRB synchronization,occurring in the midlatitude region;the other is linked to Western Europe-YRB synchronization,positioned at higher latitudes.Notably,17.5%of Eastern Europe-YRB synchronization cases and 17.0%of Western Europe-YRB cases overlap.Quantitative analysis indicates that the synchronized events between Eastern(Western)Europe and the YRB account for roughly 28%(30%)of EREs in the YRB.These findings are critical for better understanding ERE mechanisms,offering guidance for forecasting and early warning capabilities for EREs in the YRB.
基金supported by the National Natural Science Foundation of China(No.11905102)Hunan Provincial Postgraduate Research and Innovation Project(No.QL20230234)。
文摘In this study,the mechanism and characteristics of the responseαparticles and the damage caused by them in CMOS active pixel(APS)sensors were investigated.A detection and compensation algorithm for dead pixels caused byαparticle ionizing radiation was proposed,and the effects of dead-pixel compensation algorithms were compared and analyzed under different parameter conditions.The experimental results show thatαparticle response signal has highest accuracy at 9 dB gain,with an obvious“target-ring”distribution.With increasing cumulative dose,the CMOS APS pedestal tends to saturation while dead pixels continue increasing.Though some pixel damage recovers through natural annealing,the dead-to-noise ratio increases with irradiation time,reaching 32.54%after 72 h.A hierarchical clustering dead-pixel detection method is proposed,categorizing pixels into two types:those within and outside the response event.A classification compensation strategy combining mean and majority filtering is proposed.This compensation algorithm can address dead-pixel interference without affectingαparticle radiation response data.When iterated multiple times and with integration time exceeding 6.31 ms,the number of dead pixels can be effectively reduced.
文摘A Good Start The annual“two sessions”are among the most important political events in China,during which the country outlines its economic and social policies,sets development priorities,and addresses issues that may affect the future of the global economy.
基金supported by the National Natural Science Foundation of China(Grant No.42288101)the Young Scientists Fund of the National Natural Science Foundation of China(Grand No.42505018)the Shanghai“Science and Technology Innovation Action Plan”Venus Project(Grant No.23YF1437300)。
文摘Recent studies have suggested that rapid warming over the Mongolian Plateau(MP)may intensify extreme heat events(EHEs).However,the characteristics and mechanisms driving summer EHEs over the MP(MP-EHEs)remain unclear.This study explores the interannual variations in summer MP-EHEs and their relationship with the summer soil moisture over the Inner Tibetan Plateau(TP-SM).The results reveal that changes in the MP-EHEs are linked to descending atmospheric motion induced by a local high-pressure system over the MP region.Descending motion further results in decreased mid-tolow-level cloud cover and increased shortwave radiation,thereby warming the surface and triggering summer MP-EHEs.Further analysis indicates that increased TP-SM results in a greater latent heat flux,triggering a local secondary circulation that reinforces the local high-pressure system over the MP region,thus serving to promote the occurrence of summer MPEHEs.Additionally,model results from the linear baroclinic model(LBM)and CMIP6 further confirm that variations in summer TP-SM contribute to the occurrence of the MP-EHEs.
基金supported by the National Key Research and Development Program of China(Grant No.2020YFA0608904)the International Partnership Program of the Chinese Academy of Sciences(Grant Nos.060GJHZ2023079GC and 134111KYSB20160031)+1 种基金supported by the Office of Science,U.S.Department of Energy(DOE)Biological and Environmental Research as part of the Regional and Global Model Analysis program area through the Water Cycle and Climate Extremes Modeling(WACCEM)scientific focus areaoperated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830。
文摘The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risks,including floods and droughts.Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms.Observational data reveal a 20th-century shift:increased rainfall pre-1950s,followed by aridification and partial recovery post-1980s,driven by both internal variability(e.g.,Atlantic Multidecadal Oscillation)and external forcings(greenhouse gases,aerosols),while ENSO drives interannual variability through ocean-atmosphere interactions.Future projections under greenhouse forcing suggest long-term monsoon intensification,though regional disparities and model uncertainties persist.Models indicate robust trends but struggle to quantify extremes,where thermodynamic effects(warming-induced moisture rise)uniformly boost heavy rainfall,while dynamical shifts(circulation changes)create spatial heterogeneity.Volcanic eruptions and proposed solar radiation modification(SRM)further complicate predictions:tropical eruptions suppress monsoons,whereas high-latitude events alter cross-equatorial flows,highlighting unresolved feedbacks.The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons.Critical challenges remain.Model biases and sparse 20th-century observational data hinder accurate attribution.The interplay between natural variability and anthropogenic forcings,along with nonlinear extreme precipitation risks under warming,demands deeper mechanistic insights.Additionally,SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation.Addressing these gaps necessitates enhanced observational networks,refined climate models,and interdisciplinary efforts to disentangle multiscale drivers,ultimately improving resilience strategies for monsoon-dependent regions.
基金supported by the Tianshan Talent Training Program of Xinjiang Uygur Autonomous Region(2022TSYCLJ0011)the Key Research and Development(R&D)Program of Xinjiang Uygur Autonomous Region(2022B03021)the National Key R&D Program of China(2024YFC3713504).
文摘Northern Xinjiang,an arid inland area in Northwest China,is highly vulnerable to air pollution under intensifying climate extremes,yet the relative roles of temperature and precipitation extremes remain insufficiently understood.Using multi-source datasets for 2000-2023,including China High Air Pollutants(CHAP)particulate matter 2.5(PM_(2.5)),particulate matter 10(PM_(10)),and ozone(O3)products and Expert Team on Climate Change Detection and Indices(ETCCDI)extreme climate indices derived from the European Centre for Medium-Range Weather Forecasts(ECMWF)Reanalysis v5(ERA5)-Land,together with trend detection,change-point analysis,pixel-wise Pearson correlation,and random forest(RF)modeling,we investigated the spatiotemporal evolution of major air pollutants and their responses to meteorological extremes in northern Xinjiang.PM_(2.5) and PM_(10) generally declined from 2000 to 2023,whereas O3 increased,indicating a shift from particulate-dominated pollution toward stronger photochemical pollution.Interannually,PM_(2.5) showed a rise-decline pattern,PM_(10) exhibited a rise-decline-rebound pattern,and O3 increased markedly after 2015.Clear seasonal contrasts were observed,with PM_(2.5) peaking in winter,PM_(10) in spring,and O3 in summer.During the same period,northern Xinjiang exhibited a pronounced warming-drying tendency,characterized by increasing heat-related indices,decreasing cold-related indices,reduced precipitation totals and heavy-rainfall frequency,and increasing consecutive dry days.Pollutant-climate relationships showed strong spatial heterogeneity and pollutant-specific contrasts across the Urumqi-Changji-Shihezi corridor,the Ili River Valley,and the Junggar Basin.PM_(2.5) responses to precipitation shifted from predominantly positive to negative,PM_(10) showed mainly negative associations with precipitation extremes,and O3 responses varied by subregion.Temperature-related extremes generally explained more pollutant variability than precipitation-related extremes,with PM_(2.5) showing the highest sensitivity.These findings highlight the coupled influences of warming,drying,emissions,and terrain-controlled transport on air quality and support region-specific,multi-pollutant strategies for coordinated climate adaptation and air pollution control in northern Xinjiang.
基金supported by the Science and Technology Fund Project of Guizhou Health Commission(gzwkj2025-163)。
文摘Objective:To identify the root causes of typical adverse drug events through the lens of patient experiences proposing novel strategies to mitigate preventable harm.Methods:A qualitative case study leveraging in-depth interviews with patients and families,anchored by Interactive Patient Par ticipation Theory,to analyze 4 high-severity adverse drug events(ADE)cases.Cases were purposively sampled from 8 communities in China's National Adverse Event Monitor Center(2018-2023).Semi-structured interviews explored patient perspectives,with data analyzed via thematic coding and triangulation against clinical records.Results:Five interconnected themes emerged:(1)erosion of trust,(2)communication breakdowns,(3)information asymmetry,(4)environmental inadequacies,and(5)technological alienation.Notably,75% of participants had≤high school education,and 50% used≥7 medications daily,compounding ADE risks.Conclusions:We considered elements mentioned by theory,exploring trust,communication,information,and suppor t as the root causes.In addition,we added“adaptability to new technology”as an impor tant and necessary component.It is impor tant and necessary to analyze typical adverse drug events from the perspectives of patients.
文摘On a summer morning in Boqiang Village,tucked beneath the emerald mountains of Fanshi County,Shanxi Province,the Ultra Trail Mount Wutai2025 commenced with the sound of the starting pistol-an event that was much more than just a competition.As soon as the colorful smoke bombs lit up the sky,some2,000 runners from China and abroad set off to reach one of the country's most sacred Buddhist peaks.Over the past decade,this race has become a fixture on the global running calendar and a symbol of the growing popularity of endurance sports.
基金Intramural Project of The First Affiliated Hospital of Guangxi University of Chinese Medicine(2018QN008).
文摘Background:The purpose of this study was to analyze and classify adverse drug events(ADEs)related to ceftazidime/avibactam reported in the Food and Drug Administration Adverse Event Reporting System(FAERS)database and to evaluate their potential safety signals since the drug’s market introduction.Methods:This analysis systematically extracted and filtered FAERS data for ceftazidime/avibactam from its market launch in 2015 to the last quarter of 2024,utilizing the Medical Dictionary for Regulatory Activities(MedDRA)terminology for ADE recoding.The analysis employed the reporting odds ratio(ROR)method to assess the strength of ADE signals and to identify significant diseases associated with infections,the hepatobiliary system,the urinary system,and the nervous system.Results:A review of 540 adverse reaction reports revealed significant signals of adverse effects related to infections,hepatobiliary disorders,urinary system issues,and neurological impairments,including pathogen resistance,liver and kidney function impairment,encephalopathy,thrombocytopenia,and toxic epidermal necrolysis.However,these issues require further clinical attention.Conclusion:Ceftazidime/avibactam is associated with a range of adverse reactions,necessitating enhanced clinical monitoring,particularly in patients with underlying liver or kidney dysfunction.Continuous risk assessment and vigilant monitoring are critical for its clinical use.However,this study is limited by inherent reporting biases and confounders associated with the spontaneous reporting database(FAERS).Future research should validate these signals through prospective cohort and mechanistic studies and explore personalized risk management strategies for high-risk populations.
文摘The healthcare field is fraught with challenges associated with severe class imbalance,wherein such critical conditions like sepsis,cardiac arrest,and drug adverse reactions are rare but have dire clinical consequences.This paper presents a new framework,Deep Reinforcement Adaptive Gradient Optimization Network to Mining Rare Events(DRAGON-MINE),to demonstrate how deep reinforcement learning can be used synergistically with adaptive gradient optimization and address the inherent weaknesses of current methods in the prediction of rare health events.The suggested architecture uses a dual-pathway consisting of a reinforcement learning agent to dynamically reweigh samples and an adaptive gradient optimizer to follow novel learning rates.With extensive experiments on the MIMIC-IV and eICU-CRD datasets,DRAGON-MINE consistently outperforms recent state-of-the-art methods for sepsis,cardiac arrest,and adverse drug reaction prediction,achieving AUROC values of 92.3%and 91.6%for sepsis prediction on MIMIC-IV and eICU-CRD,respectively,while consistently outperforming Transformer-,CNN-RNN-,and Fed-Ensemble-based methods across all evaluated tasks and datasets,with particularly strong gains observed in precision-recall performance under severe class imbalance.With its high sensitivity(88.4%)and specificity(90.2%),DRAGON-MINE enables reliable early warning of rare clinical events in critical care settings while minimizing false alarms,supporting safer clinical decision support systems,and demonstrating strong potential for scalable deployment across multi-institutional intensive care environments through federated learning.
