Based on the interpersonal function in Halliday’s systemic functional grammar,"Miranda Warnings",the typical English Police Caution,is analyzed from the aspects of Mood system,Modality system and Appraisal ...Based on the interpersonal function in Halliday’s systemic functional grammar,"Miranda Warnings",the typical English Police Caution,is analyzed from the aspects of Mood system,Modality system and Appraisal system,with the aim of exploring its interpersonal meanings.Results show that:first,the declarative mood and interrogative mood used in the police caution protect the legitimate rights of the interrogated;second,the widely use of Low value modal verbs demonstrates a more humane and democratic legislation principle;and third,the absence of Affect resources and the frequent application of Capacity resources narrow the interpersonal distance between policeman and the interrogated,reflecting the transformation in policeman’s interrogation practices.展开更多
Flash floods are a major cause of death and destruction to property on a worldwide scale. In the UK sudden flooding has been the cause of the loss of over 60 lives during the last century. Forecasting these events to ...Flash floods are a major cause of death and destruction to property on a worldwide scale. In the UK sudden flooding has been the cause of the loss of over 60 lives during the last century. Forecasting these events to give enough warning is a major concern: after the 2004 flood at Boscastle, Cornwall UK the Environment Agency (2004) stated that it was not possible to provide a warning in such a fast reacting and small catchment. This is untrue since the Agency had already implemented a real time non-linear flow model as part of a flood warning system on the upper Brue in Somerset UK. This model is described in this paper as it has been applied to the Lynmouth flood of 1952, and briefly for the Boscastle catchment, both of which have an area of about 20 km2. The model uses locally measured SMD and saturated hydraulic conductivity data. With the addition of further parameters the model has been successfully used nationwide.展开更多
SUMMARIES OF TOP NEWS STORIES CHINA Safeguarding Gaokao Fairness This year’s gaokao,China’s national college entrance exam,began on 7 June,with a record 13.35 million students taking part.As one of the country’s mo...SUMMARIES OF TOP NEWS STORIES CHINA Safeguarding Gaokao Fairness This year’s gaokao,China’s national college entrance exam,began on 7 June,with a record 13.35 million students taking part.As one of the country’s most important annual events,the 2025 gaokao has seen extensive nation-wide efforts to ensure fairness,safety,and support for all candidates.Authorities have implemented a range of security and logistical measures to safeguard exam integrity.AI-powered monitoring systems have been rolled out in provinces like Jiangxi,Hubei,and Guangdong,enabling real-time behaviour analysis and early warnings without human intervention.These tools reduce pressure on staff and strengthen fairness.展开更多
Iced transmission line galloping poses a significant threat to the safety and reliability of power systems,leading directly to line tripping,disconnections,and power outages.Existing early warning methods of iced tran...Iced transmission line galloping poses a significant threat to the safety and reliability of power systems,leading directly to line tripping,disconnections,and power outages.Existing early warning methods of iced transmission line galloping suffer from issues such as reliance on a single data source,neglect of irregular time series,and lack of attention-based closed-loop feedback,resulting in high rates of missed and false alarms.To address these challenges,we propose an Internet of Things(IoT)empowered early warning method of transmission line galloping that integrates time series data from optical fiber sensing and weather forecast.Initially,the method applies a primary adaptive weighted fusion to the IoT empowered optical fiber real-time sensing data and weather forecast data,followed by a secondary fusion based on a Back Propagation(BP)neural network,and uses the K-medoids algorithm for clustering the fused data.Furthermore,an adaptive irregular time series perception adjustment module is introduced into the traditional Gated Recurrent Unit(GRU)network,and closed-loop feedback based on attentionmechanism is employed to update network parameters through gradient feedback of the loss function,enabling closed-loop training and time series data prediction of the GRU network model.Subsequently,considering various types of prediction data and the duration of icing,an iced transmission line galloping risk coefficient is established,and warnings are categorized based on this coefficient.Finally,using an IoT-driven realistic dataset of iced transmission line galloping,the effectiveness of the proposed method is validated through multi-dimensional simulation scenarios.展开更多
BACKGROUND Emphysematous pyelonephritis(EPN)is a life-threatening necrotizing renal parenchyma infection characterized by gas formation due to severe bacterial infection,predominantly affecting diabetic and immunocomp...BACKGROUND Emphysematous pyelonephritis(EPN)is a life-threatening necrotizing renal parenchyma infection characterized by gas formation due to severe bacterial infection,predominantly affecting diabetic and immunocompromised patients.It carries high morbidity and mortality,requiring early diagnosis and timely intervention.Various prognostic scoring systems help in triaging critically ill patients.The National Early Warning Score 2(NEWS 2)scoring system is a widely used physiological assessment tool that evaluates clinical deterioration based on vital parameters,but its standard form lacks specificity for risk stratification in EPN,necessitating modifications to improve treatment decisionmaking and prognostic accuracy in this critical condition.AIM To highlight the need to modify the NEWS 2 score to enable more intense monitoring and better treatment outcomes.METHODS This prospective study was done on all EPN patients admitted to our hospital over the past 12 years.A weighted average risk-stratification index was calculated for each of the three groups,mortality risk was calculated for each of the NEWS 2 scores,and the need for intervention for each of the three groups was calculated.The NEWS 2 score was subsequently modified with 0-6,7-14 and 15-20 scores included in groups 1,2 and 3,respectively.RESULTS A total of 171 patients with EPN were included in the study,with a predominant association with diabetes(90.6%)and a female-to-male ratio of 1.5:1.The combined prognostic scoring of the three groups was 10.7,13.0,and 21.9,respectively(P<0.01).All patients managed conservatively belonged to group 1(P<0.01).Eight patients underwent early nephrectomy,with six from group 3(P<0.01).Overall mortality was 8(4.7%),with seven from group 3(87.5%).The cutoff NEWS 2 score for mortality was identified to be 15,with a sensitivity of 87.5%,specificity of 96.9%,and an overall accuracy rate of 96.5%.The area under the curve to predict mortality based on the NEWS 2 score was 0.98,with a confidence interval of(0.97,1.0)and P<0.001.CONCLUSION Modified NEWS 2(mNEWS 2)score dramatically aids in the appropriate assessment of treatment-related outcomes.MNEWS 2 scores should become the practice standard to reduce the morbidity and mortality associated with this dreaded illness.展开更多
Due to batteries inconsistencies and potential faults in battery management systems,slight overcharging remains a common yet insufficiently understood safety risk,lacking effective warning methods.To illuminate the de...Due to batteries inconsistencies and potential faults in battery management systems,slight overcharging remains a common yet insufficiently understood safety risk,lacking effective warning methods.To illuminate the degradation behavior and failure mechanism of various overcharged states(100%SOC,105%SOC,110%SOC,and 115%SOC),multiple advanced in-situ characterization techniques(accelerating rate calorimeter,electrochemical impedance spectroscopy,ultrasonic scanning,and expansion instrument)were utilized.Additionally,re-overcharge-induced thermal runaway(TR)tests were conducted,with a specific emphasis on the evolution of the expansion force signal.Results indicated significant degradation at 110%SOC including conductivity loss,loss of lithium inventory,and loss of active material accompanied by internal gas generation.These failure behaviors slow down the expansion force rate during reovercharging,reducing the efficacy of active warnings that depend on rate thresholds of expansion force.Specifically,the warning time for 115%SOC battery is only 144 s,which is 740 s shorter than that for fresh battery,and the time to TR is advanced by 9 min.Moreover,the initial self-heating temperature(T1)is reduced by 62.4℃compared to that of fresh battery,reaching only 70.8℃.To address the low safety of overcharged batteries,a passive overcharge warning method utilizing relaxation expansion force was proposed,based on the continued gas generation after stopping charging,leading to a sustained increase in force.Compared to active methods that rely on thresholds of expansion force rate,the passive method can issue warnings 115 s earlier.By combining the passive and active warning methods,guaranteed effective overcharge warning can be issued 863-884 s before TR.This study introduces a novel perspective for enhancing the safety of batteries.展开更多
Coating microdefects and localized corrosion in coating/metal system are inevitable,accelerating the degradation of metal infrastructure.Early evaluating coating microdefects and detecting corrosion sites are urgent y...Coating microdefects and localized corrosion in coating/metal system are inevitable,accelerating the degradation of metal infrastructure.Early evaluating coating microdefects and detecting corrosion sites are urgent yet remain challenge to achieve.Herein,we propose a robust,universal and efficient fluorescence-based strategy for hierarchical warning of coating damage and metal corrosion by introducing the concepts of damage-induced fluorescence enhancement effect(DIE)and ionic-recognition induced quenching effect(RIQ).The coatings with dualresponsiveness for coating defect and steel corrosion are constructed by incorporating synthesized nanoprobes composed of metal organic frameworks(Ni–Zn-MOFs)loaded with Rhodamine B(RhB@MOFs).The initial damage to the coating causes an immediate intensification of fluorescence,while the specific ionic-recognition characteristic of RhB with Fe3t results in an evident fluorescence quenching,enabling the detection of coating damage and corrosion.Importantly,this nanoprobes are insensitive to the coating matrix and exhibit stable corrosion warning capability across various coating systems.Meanwhile,electrochemical investigations indicate that the impedance values of RM/EP maintain above 10^(8)Ωcm^(2)even after 60 days of immersion.Therefore,the incorporation of fluorescent nanoprobes greatly inhibits the intrusion of electrolytes into polymer and improves the corrosion protection performance of the coating.This powerful strategy towards dual-level damage warning provides insights for the development of long-term smart protective materials.展开更多
The traditional academic warning methods for students in higher vocational colleges are relatively backward,single,and have many influencing factors,which have a limited effect on improving their learning ability.A da...The traditional academic warning methods for students in higher vocational colleges are relatively backward,single,and have many influencing factors,which have a limited effect on improving their learning ability.A data set was established by collecting academic warning data of students in a certain university.The importance of the school,major,grade,and warning level for the students was analyzed using the Pearson correlation coefficient,random forest variable importance,and permutation importance.It was found that the characteristic of the major has a great impact on the academic warning level.Countermeasures such as dynamic adjustment of majors,reform of cognitive adaptation of courses,full-cycle academic support,and data-driven precise intervention were proposed to provide theoretical support and practical paths for universities to improve the efficiency of academic warning and enhance students’learning ability.展开更多
The level of ground shaking,as determined by the peak ground acceleration(PGA),can be used to analyze seismic hazard at a certain location and is crucial for constructing earthquake-resistant structures.Predicting the...The level of ground shaking,as determined by the peak ground acceleration(PGA),can be used to analyze seismic hazard at a certain location and is crucial for constructing earthquake-resistant structures.Predicting the PGA immediately after an earthquake occurs allows for the issuing of a warning by an earthquake early warning system.In this study,we propose a deep learning model,ConvMixer,to predict the PGA recorded by weak-motion velocity seismometers in Japan.We use 5-s threecomponent seismograms,from 2 s before until 3 s after the P-wave arrival time of the earthquake.Our dataset comprised more than 50,000 single-station waveforms recorded by 10 seismic stations in the K-NET,Kiki-NET,and Hi-Net networks between 2004 and 2023.The proposed ConvMixer is a patch-based model that extracts global features from input seismic data and predicts the PGA of an earthquake by combining depth and pointwise convolutions.The proposed ConvMixer network had a mean absolute error of 2.143 when applied to the test set and outperformed benchmark deep learning models.In addition,the proposed ConvMixer demonstrated the ability to predict the PGA at the corresponding station site based on 1-second waveforms obtained immediately after the arrival time of the P-wave.展开更多
Clarifying the mechanisms through which coal mining affects groundwater storage(GWS)variations is crucial for water resource conservation and sustainable development.The Ordos Mining Region in China,a key energy base ...Clarifying the mechanisms through which coal mining affects groundwater storage(GWS)variations is crucial for water resource conservation and sustainable development.The Ordos Mining Region in China,a key energy base in China with significant strategic importance,has undergone intensive coal mining activities that have substantially disrupted regional groundwater circulation.This study integrated data from the Gravity Recovery and Climate Experiment Satellite(GRACE)and Famine Early Warning Systems Network(FEWS NET)Land Data Assimilation System(FLDAS)models,combined with weighted downscaling methodology and water balance principles,to reconstruct high-resolution(0.01°)terrestrial water storage(TWS)and GWS changes in the Ordos Mining Region,China from April 2002 to December 2021.The accuracy of GWS variations were validated through pumping test measurements.Subsequently,Geodetector analysis was implemented to quantify the contributions of natural and anthropogenic factors to groundwater storage dynamics.Key findings include:1)TWS in the study area showed a fluctuating but overall decreasing trend,with a total reduction of 8901.11 mm during study period.The most significant annual decrease occurred in 2021,reaching 1696.77 mm.2)GWS exhibited an accelerated decline,with an average annual change rate of 44.35 mm/yr,totaling a decrease of 887.05 mm.The lowest annual groundwater storage level was recorded in 2020,reaching 185.69 mm.3)Precipitation(PRE)contributed the most to GWS variation(q=0.52),followed by coal mining water consumption(MWS)(q=0.41).The interaction between PRE and MWS exhibited a nonlinear enhancement effect on GWS changes(0.54).The synergistic effect of natural hydrological factors has a great influence on the change of GWS,but coal mining water consumption will continue to reduce GWS.These findings provide critical references for the management and regulation of groundwater resource in mining regions.展开更多
The World Meteorological Organization(WMO) is planning to implement a Global Multi-hazard Alert System(GMAS) to aggregate official warning^1 information issued by authorities around the world and to serve as a one-sto...The World Meteorological Organization(WMO) is planning to implement a Global Multi-hazard Alert System(GMAS) to aggregate official warning^1 information issued by authorities around the world and to serve as a one-stop shop to support the humanitarian organizations of the United Nations(UN), National Meteorological and Hydrological Services(NMHSs) and other global users including the media. It aims to enhance the authority and visibility of NMHSs and other alerting authorities. To aid effective dissemination of warnings to GMAS, the Common Alerting Protocol(CAP) was considered as a standard and robust format to use. In respect of GMAS infrastructure, the World Weather Information(WWIS) and the Severe Weather Information Centre(SWIC) of WMO as well as the WMO Alert Hub now being implemented are identified as core components, among others. The SWIC is being upgraded with GIS capability for displaying authoritative warnings and tropical cyclone(TC) information, and for use as a display platform of GMAS. Apart from warnings from NMHSs, authoritative TC warnings and advisories issued by Regional Specialized Meteorological Centres(RSMCs) and Tropical Cyclone Warning Centres(TCWCs) are also indispensable information for GMAS. As the existing TC warnings and advisories, now more or less in free text format, are mainly targeted for human users and are not intended for automatic parsing by computer software, it is proposed to make available the TC advisories in a machine-readable format so that TC information can be effectively ingested into GMAS and made available to the UN humanitarian organizations, NMHSs and other global users. In this respect, some enhancement measures to TC advisories are proposed. This calls for active collaboration of Members of the Typhoon Committee in the GMAS project.展开更多
Purpose–This study aims to design and validate an emergency response method for high-speed railway earthquake early warning(EEW)systems based on the Propagation of Local Undamped Motion(PLUM)principle in order to enh...Purpose–This study aims to design and validate an emergency response method for high-speed railway earthquake early warning(EEW)systems based on the Propagation of Local Undamped Motion(PLUM)principle in order to enhance the timeliness and accuracy of warnings under seismic threats.Design/methodology/approach–A hierarchical architecture of the railway EEW system was adopted,in which self-built stations along the railway serve as the backbone and the national seismic network provides supplementary data.Warning zones were designed along the railway using overlapping trapezoidal layouts to cover seismic stations and reduce inter-regional time delays.Offline replay experiments were conducted using 82 historical earthquake events and records from 61 seismic stations to evaluate the timeliness and accuracy of warning information.Findings–The results indicate that the PLUM-based early warning method can issue emergency response information before destructive seismic waves arrive.Multiple earthquake experiments demonstrated high reliability and stability,with effective detection across different magnitudes and epicentral distances.Furthermore,the trapezoidal overlapping zone design improved regional consistency and significantly reduced missed alerts.Originality/value–This work represents the first systematic application of the PLUM method to high-speed railway EEW in China.By integrating railway operational requirements,the proposed method provides a practical and robust emergency response strategy,offering new insights into seismic risk mitigation for China’s high-speed railways.展开更多
In order to solve the problems of high coupling and poor scalability of the traditional monomer early warning release system architecture,multi-level deployment in a complex network environment will lead to high inves...In order to solve the problems of high coupling and poor scalability of the traditional monomer early warning release system architecture,multi-level deployment in a complex network environment will lead to high investment in software and hardware and cannot achieve intensive multi-level deployment.This paper realizes the goal of system scalability by introducing micro service architecture and technology stack and realizes the goal of resource intensification by introducing the idea of a data forwarding agent.The designed architecture scheme has been practically applied in the“Jiangxi emergency early warning information release system software platform(phase I)project”(hereinafter referred to as“provincial emergency”),which meets the needs of flexible deployment of multi-level applications across meteorological wide area network(WAN),business private network of other commissions,offices,and bureaus,government extranet,Internet and other complex networks,and fully verifies the scientificity and rationality of the scheme.It has achieved the goal of intensive and scalable construction of provincial emergencies under the complex network environment,greatly improved the early warning capacity and communication capacity of emergencies and comprehensive disasters,provided a reliable guarantee for disaster prevention and reduction,and provided a reference for the construction of current and future early warning release system and capacity improvement project.展开更多
An effective warning system for flash floods along the upper River des Peres, a small urban stream in eastern Missouri, USA, is based on three enterprise-level, automated rain gauges.Because floods in this 25 km~2 bas...An effective warning system for flash floods along the upper River des Peres, a small urban stream in eastern Missouri, USA, is based on three enterprise-level, automated rain gauges.Because floods in this 25 km~2 basin develop rapidly and are commonly caused by small but intense thunderstorm cells, these rain gauges were necessarily deployed within the watershed, and immediate telemetry and processing of rainfall delivered in 5-minute intervals is required. Available data show that damaging floods in this area occur only 30 min to 3 h following the delivery of 38 mm of rainfall or more in a single hour. Water levels along this stream can rise more than 3 m/h. Since full deployment in Nov. 2021, our system has successfully predicted 3 significant floods with one false positive.展开更多
The collapse of rock masses in fault-developed zones poses significant safety challenges during the excavation of high-stress underground caverns. This study investigates the spatiotemporal evolution of the collapse m...The collapse of rock masses in fault-developed zones poses significant safety challenges during the excavation of high-stress underground caverns. This study investigates the spatiotemporal evolution of the collapse mechanisms of the cavern in the Yebatan Hydropower Station through using microseismic (MS) monitoring and displacement measurements. We developed a multi-parameter deformation early warning model that integrates three critical indicators: deformation rate, rate increment, and tangential angle of the deformation time curve. The results of the early warning model show a significant and abrupt increase in the deformation of the rock mass during the collapse process. The safety and stability of the local cavern in the face of excavation-induced disturbances are meticulously assessed utilizing MS data. Spatiotemporal analysis of the MS monitoring indicates a high frequency of MS events during the blasting phase, with a notable clustering of these events in the vicinity of the fault. These research results provide a valuable reference for risk warnings and stability assessments in the fault development zones of analogous caverns.展开更多
Combining the background of modern construction engineering site safety management,this article analyzes the real-time monitoring and alarm strategies for site construction safety under the integration of BIM and AI.T...Combining the background of modern construction engineering site safety management,this article analyzes the real-time monitoring and alarm strategies for site construction safety under the integration of BIM and AI.This includes the analysis of BIM and AI technologies and their integration advantages,real-time monitoring and alarm strategies for construction site safety based on BIM and AI integration,as well as the development direction of BIM and AI integration in real-time monitoring and alarm for construction site safety.It is hoped that through this analysis,a scientific reference can be provided for the digital and intelligent management of construction site safety,promoting the digital and intelligent development of its safety management work.展开更多
With the continuous advancement of the tiered diagnosis and treatment system,the medical consortium model has gained increasing attention as an important approach to promoting the vertical integration of healthcare re...With the continuous advancement of the tiered diagnosis and treatment system,the medical consortium model has gained increasing attention as an important approach to promoting the vertical integration of healthcare resources.Within this context,laboratory data,as a key component of healthcare information systems,urgently requires efficient sharing and intelligent analysis.This paper designs and constructs an intelligent early warning system for laboratory data based on a cloud platform tailored to the medical consortium model.Through standardized data formats and unified access interfaces,the system enables the integration and cleaning of laboratory data across multiple healthcare institutions.By combining medical rule sets with machine learning models,the system achieves graded alerts and rapid responses to abnormal key indicators and potential outbreaks of infectious diseases.Practical deployment results demonstrate that the system significantly improves the utilization efficiency of laboratory data,strengthens public health event monitoring,and optimizes inter-institutional collaboration.The paper also discusses challenges encountered during system implementation,such as inconsistent data standards,security and compliance concerns,and model interpretability,and proposes corresponding optimization strategies.These findings provide a reference for the broader application of intelligent medical early warning systems.展开更多
Thermal power generation systems have stringent requirements for water and steam quality,i.e.,condensate water quality is one of the critical issues.In this paper,we designed a two-layer model based on an autoencoder ...Thermal power generation systems have stringent requirements for water and steam quality,i.e.,condensate water quality is one of the critical issues.In this paper,we designed a two-layer model based on an autoencoder and expert knowledge to achieve the early warning and causal analysis of condensate water quality abnormalities.An early warning model using an autoencoder model is built based on the historical data affecting the condensate water quality.Next,an analytical model of condensate water quality abnormalities was then developed by combining expert knowledge and trend test algorithms.Two different datasets were used to test the proposed model,respectively.The accuracy of the autoencoder model in the short-period test set is 88.83%,which shows that the early warning model can accurately analyze the condensate water quality data and achieve the purpose of early warning.For the long-time period test set,the model can correctly identify each abnormality and simultaneously indicates the cause of the abnormal condensate water quality.The proposed model can correctly identify abnormal working conditions and it is applicable to other thermal power plants.展开更多
The earthquake early warning system is an effective means of disaster reduction to reduce losses caused by earthquakes,it can release earthquake warning information to the public before destructive seismic waves reach...The earthquake early warning system is an effective means of disaster reduction to reduce losses caused by earthquakes,it can release earthquake warning information to the public before destructive seismic waves reach the warning target area,and carry out automatic disposal of lifeline engineering facilities.Through the construction of the National Earthquake Intensity Rapid Reporting and Early Warning Project,an earthquake early warning network consisting of over 1900 monitoring stations has been established in the Beijing-Tianjin-Hebei Urban Agglomeration.The early warning system has achieved second level earthquake warning and minute level intensity rapid reporting.The implementation of these functions relies on the system's ability to timely,accurately,and reliably identify seismic waves.But with the development of social economy,the background noise of earthquake observation environment is becoming increasingly complex,which brings certain challenges to earthquake wave recognition,some interference events have the risk of triggering the earthquake warning system incorrectly.Therefore,this article focuses on seismic wave recognition in complex noise environments and proposes a seismic wave detection method based on triangulation to enhance the antiinterference ability and recognition accuracy of early warning systems.展开更多
文摘Based on the interpersonal function in Halliday’s systemic functional grammar,"Miranda Warnings",the typical English Police Caution,is analyzed from the aspects of Mood system,Modality system and Appraisal system,with the aim of exploring its interpersonal meanings.Results show that:first,the declarative mood and interrogative mood used in the police caution protect the legitimate rights of the interrogated;second,the widely use of Low value modal verbs demonstrates a more humane and democratic legislation principle;and third,the absence of Affect resources and the frequent application of Capacity resources narrow the interpersonal distance between policeman and the interrogated,reflecting the transformation in policeman’s interrogation practices.
文摘Flash floods are a major cause of death and destruction to property on a worldwide scale. In the UK sudden flooding has been the cause of the loss of over 60 lives during the last century. Forecasting these events to give enough warning is a major concern: after the 2004 flood at Boscastle, Cornwall UK the Environment Agency (2004) stated that it was not possible to provide a warning in such a fast reacting and small catchment. This is untrue since the Agency had already implemented a real time non-linear flow model as part of a flood warning system on the upper Brue in Somerset UK. This model is described in this paper as it has been applied to the Lynmouth flood of 1952, and briefly for the Boscastle catchment, both of which have an area of about 20 km2. The model uses locally measured SMD and saturated hydraulic conductivity data. With the addition of further parameters the model has been successfully used nationwide.
文摘SUMMARIES OF TOP NEWS STORIES CHINA Safeguarding Gaokao Fairness This year’s gaokao,China’s national college entrance exam,began on 7 June,with a record 13.35 million students taking part.As one of the country’s most important annual events,the 2025 gaokao has seen extensive nation-wide efforts to ensure fairness,safety,and support for all candidates.Authorities have implemented a range of security and logistical measures to safeguard exam integrity.AI-powered monitoring systems have been rolled out in provinces like Jiangxi,Hubei,and Guangdong,enabling real-time behaviour analysis and early warnings without human intervention.These tools reduce pressure on staff and strengthen fairness.
基金research was funded by Science and Technology Project of State Grid Corporation of China under grant number 5200-202319382A-2-3-XG.
文摘Iced transmission line galloping poses a significant threat to the safety and reliability of power systems,leading directly to line tripping,disconnections,and power outages.Existing early warning methods of iced transmission line galloping suffer from issues such as reliance on a single data source,neglect of irregular time series,and lack of attention-based closed-loop feedback,resulting in high rates of missed and false alarms.To address these challenges,we propose an Internet of Things(IoT)empowered early warning method of transmission line galloping that integrates time series data from optical fiber sensing and weather forecast.Initially,the method applies a primary adaptive weighted fusion to the IoT empowered optical fiber real-time sensing data and weather forecast data,followed by a secondary fusion based on a Back Propagation(BP)neural network,and uses the K-medoids algorithm for clustering the fused data.Furthermore,an adaptive irregular time series perception adjustment module is introduced into the traditional Gated Recurrent Unit(GRU)network,and closed-loop feedback based on attentionmechanism is employed to update network parameters through gradient feedback of the loss function,enabling closed-loop training and time series data prediction of the GRU network model.Subsequently,considering various types of prediction data and the duration of icing,an iced transmission line galloping risk coefficient is established,and warnings are categorized based on this coefficient.Finally,using an IoT-driven realistic dataset of iced transmission line galloping,the effectiveness of the proposed method is validated through multi-dimensional simulation scenarios.
文摘BACKGROUND Emphysematous pyelonephritis(EPN)is a life-threatening necrotizing renal parenchyma infection characterized by gas formation due to severe bacterial infection,predominantly affecting diabetic and immunocompromised patients.It carries high morbidity and mortality,requiring early diagnosis and timely intervention.Various prognostic scoring systems help in triaging critically ill patients.The National Early Warning Score 2(NEWS 2)scoring system is a widely used physiological assessment tool that evaluates clinical deterioration based on vital parameters,but its standard form lacks specificity for risk stratification in EPN,necessitating modifications to improve treatment decisionmaking and prognostic accuracy in this critical condition.AIM To highlight the need to modify the NEWS 2 score to enable more intense monitoring and better treatment outcomes.METHODS This prospective study was done on all EPN patients admitted to our hospital over the past 12 years.A weighted average risk-stratification index was calculated for each of the three groups,mortality risk was calculated for each of the NEWS 2 scores,and the need for intervention for each of the three groups was calculated.The NEWS 2 score was subsequently modified with 0-6,7-14 and 15-20 scores included in groups 1,2 and 3,respectively.RESULTS A total of 171 patients with EPN were included in the study,with a predominant association with diabetes(90.6%)and a female-to-male ratio of 1.5:1.The combined prognostic scoring of the three groups was 10.7,13.0,and 21.9,respectively(P<0.01).All patients managed conservatively belonged to group 1(P<0.01).Eight patients underwent early nephrectomy,with six from group 3(P<0.01).Overall mortality was 8(4.7%),with seven from group 3(87.5%).The cutoff NEWS 2 score for mortality was identified to be 15,with a sensitivity of 87.5%,specificity of 96.9%,and an overall accuracy rate of 96.5%.The area under the curve to predict mortality based on the NEWS 2 score was 0.98,with a confidence interval of(0.97,1.0)and P<0.001.CONCLUSION Modified NEWS 2(mNEWS 2)score dramatically aids in the appropriate assessment of treatment-related outcomes.MNEWS 2 scores should become the practice standard to reduce the morbidity and mortality associated with this dreaded illness.
基金supported by the National Natural Science Foundation of China(52476200,52106244)the Guangdong Basic and Applied Basic Research Foundation(2024A1515030124)+1 种基金the Science and Technology Project of China Southern Power Grid under Grant GDKJXM20230246(030100KC23020017)the Fundamental Research Funds for the Central Universities。
文摘Due to batteries inconsistencies and potential faults in battery management systems,slight overcharging remains a common yet insufficiently understood safety risk,lacking effective warning methods.To illuminate the degradation behavior and failure mechanism of various overcharged states(100%SOC,105%SOC,110%SOC,and 115%SOC),multiple advanced in-situ characterization techniques(accelerating rate calorimeter,electrochemical impedance spectroscopy,ultrasonic scanning,and expansion instrument)were utilized.Additionally,re-overcharge-induced thermal runaway(TR)tests were conducted,with a specific emphasis on the evolution of the expansion force signal.Results indicated significant degradation at 110%SOC including conductivity loss,loss of lithium inventory,and loss of active material accompanied by internal gas generation.These failure behaviors slow down the expansion force rate during reovercharging,reducing the efficacy of active warnings that depend on rate thresholds of expansion force.Specifically,the warning time for 115%SOC battery is only 144 s,which is 740 s shorter than that for fresh battery,and the time to TR is advanced by 9 min.Moreover,the initial self-heating temperature(T1)is reduced by 62.4℃compared to that of fresh battery,reaching only 70.8℃.To address the low safety of overcharged batteries,a passive overcharge warning method utilizing relaxation expansion force was proposed,based on the continued gas generation after stopping charging,leading to a sustained increase in force.Compared to active methods that rely on thresholds of expansion force rate,the passive method can issue warnings 115 s earlier.By combining the passive and active warning methods,guaranteed effective overcharge warning can be issued 863-884 s before TR.This study introduces a novel perspective for enhancing the safety of batteries.
基金support by the National Natural Science Foundation of China(52201077)the Natural Science Foundation of Shandong Province(ZR2022QE191)+1 种基金Elite Scheme of Shandong University of Science and Technology(0104060541123)Talent introduction and Research Start-up Fund of Shandong University of Science and Technology(0104060510124).
文摘Coating microdefects and localized corrosion in coating/metal system are inevitable,accelerating the degradation of metal infrastructure.Early evaluating coating microdefects and detecting corrosion sites are urgent yet remain challenge to achieve.Herein,we propose a robust,universal and efficient fluorescence-based strategy for hierarchical warning of coating damage and metal corrosion by introducing the concepts of damage-induced fluorescence enhancement effect(DIE)and ionic-recognition induced quenching effect(RIQ).The coatings with dualresponsiveness for coating defect and steel corrosion are constructed by incorporating synthesized nanoprobes composed of metal organic frameworks(Ni–Zn-MOFs)loaded with Rhodamine B(RhB@MOFs).The initial damage to the coating causes an immediate intensification of fluorescence,while the specific ionic-recognition characteristic of RhB with Fe3t results in an evident fluorescence quenching,enabling the detection of coating damage and corrosion.Importantly,this nanoprobes are insensitive to the coating matrix and exhibit stable corrosion warning capability across various coating systems.Meanwhile,electrochemical investigations indicate that the impedance values of RM/EP maintain above 10^(8)Ωcm^(2)even after 60 days of immersion.Therefore,the incorporation of fluorescent nanoprobes greatly inhibits the intrusion of electrolytes into polymer and improves the corrosion protection performance of the coating.This powerful strategy towards dual-level damage warning provides insights for the development of long-term smart protective materials.
基金supported by the Basic Ability Improvement Project of Young and Middle-Aged Teachers in Colleges and Universities of Guangxi(2022KY1922,2021KY1938).
文摘The traditional academic warning methods for students in higher vocational colleges are relatively backward,single,and have many influencing factors,which have a limited effect on improving their learning ability.A data set was established by collecting academic warning data of students in a certain university.The importance of the school,major,grade,and warning level for the students was analyzed using the Pearson correlation coefficient,random forest variable importance,and permutation importance.It was found that the characteristic of the major has a great impact on the academic warning level.Countermeasures such as dynamic adjustment of majors,reform of cognitive adaptation of courses,full-cycle academic support,and data-driven precise intervention were proposed to provide theoretical support and practical paths for universities to improve the efficiency of academic warning and enhance students’learning ability.
基金the National Research Institute of Astronomy and Geophysics (NRIAG) for supporting this work
文摘The level of ground shaking,as determined by the peak ground acceleration(PGA),can be used to analyze seismic hazard at a certain location and is crucial for constructing earthquake-resistant structures.Predicting the PGA immediately after an earthquake occurs allows for the issuing of a warning by an earthquake early warning system.In this study,we propose a deep learning model,ConvMixer,to predict the PGA recorded by weak-motion velocity seismometers in Japan.We use 5-s threecomponent seismograms,from 2 s before until 3 s after the P-wave arrival time of the earthquake.Our dataset comprised more than 50,000 single-station waveforms recorded by 10 seismic stations in the K-NET,Kiki-NET,and Hi-Net networks between 2004 and 2023.The proposed ConvMixer is a patch-based model that extracts global features from input seismic data and predicts the PGA of an earthquake by combining depth and pointwise convolutions.The proposed ConvMixer network had a mean absolute error of 2.143 when applied to the test set and outperformed benchmark deep learning models.In addition,the proposed ConvMixer demonstrated the ability to predict the PGA at the corresponding station site based on 1-second waveforms obtained immediately after the arrival time of the P-wave.
基金Under the National Key R&D Program Key Project(No.2021YFC3201201)National Natural Science Foundation of China(No.52360032)+2 种基金Basic Scientific Research Business Fee Project of Colleges And Universities Directly Under the Inner Mongolia Autonomous Region(No.JBYYWF2022001)Development Plan of Innovation Team of Colleges And Universities in Inner Mongolia Autonomous Region(No.NMGIRT2313)the Innovation Team of‘Grassland Talents’。
文摘Clarifying the mechanisms through which coal mining affects groundwater storage(GWS)variations is crucial for water resource conservation and sustainable development.The Ordos Mining Region in China,a key energy base in China with significant strategic importance,has undergone intensive coal mining activities that have substantially disrupted regional groundwater circulation.This study integrated data from the Gravity Recovery and Climate Experiment Satellite(GRACE)and Famine Early Warning Systems Network(FEWS NET)Land Data Assimilation System(FLDAS)models,combined with weighted downscaling methodology and water balance principles,to reconstruct high-resolution(0.01°)terrestrial water storage(TWS)and GWS changes in the Ordos Mining Region,China from April 2002 to December 2021.The accuracy of GWS variations were validated through pumping test measurements.Subsequently,Geodetector analysis was implemented to quantify the contributions of natural and anthropogenic factors to groundwater storage dynamics.Key findings include:1)TWS in the study area showed a fluctuating but overall decreasing trend,with a total reduction of 8901.11 mm during study period.The most significant annual decrease occurred in 2021,reaching 1696.77 mm.2)GWS exhibited an accelerated decline,with an average annual change rate of 44.35 mm/yr,totaling a decrease of 887.05 mm.The lowest annual groundwater storage level was recorded in 2020,reaching 185.69 mm.3)Precipitation(PRE)contributed the most to GWS variation(q=0.52),followed by coal mining water consumption(MWS)(q=0.41).The interaction between PRE and MWS exhibited a nonlinear enhancement effect on GWS changes(0.54).The synergistic effect of natural hydrological factors has a great influence on the change of GWS,but coal mining water consumption will continue to reduce GWS.These findings provide critical references for the management and regulation of groundwater resource in mining regions.
文摘The World Meteorological Organization(WMO) is planning to implement a Global Multi-hazard Alert System(GMAS) to aggregate official warning^1 information issued by authorities around the world and to serve as a one-stop shop to support the humanitarian organizations of the United Nations(UN), National Meteorological and Hydrological Services(NMHSs) and other global users including the media. It aims to enhance the authority and visibility of NMHSs and other alerting authorities. To aid effective dissemination of warnings to GMAS, the Common Alerting Protocol(CAP) was considered as a standard and robust format to use. In respect of GMAS infrastructure, the World Weather Information(WWIS) and the Severe Weather Information Centre(SWIC) of WMO as well as the WMO Alert Hub now being implemented are identified as core components, among others. The SWIC is being upgraded with GIS capability for displaying authoritative warnings and tropical cyclone(TC) information, and for use as a display platform of GMAS. Apart from warnings from NMHSs, authoritative TC warnings and advisories issued by Regional Specialized Meteorological Centres(RSMCs) and Tropical Cyclone Warning Centres(TCWCs) are also indispensable information for GMAS. As the existing TC warnings and advisories, now more or less in free text format, are mainly targeted for human users and are not intended for automatic parsing by computer software, it is proposed to make available the TC advisories in a machine-readable format so that TC information can be effectively ingested into GMAS and made available to the UN humanitarian organizations, NMHSs and other global users. In this respect, some enhancement measures to TC advisories are proposed. This calls for active collaboration of Members of the Typhoon Committee in the GMAS project.
文摘Purpose–This study aims to design and validate an emergency response method for high-speed railway earthquake early warning(EEW)systems based on the Propagation of Local Undamped Motion(PLUM)principle in order to enhance the timeliness and accuracy of warnings under seismic threats.Design/methodology/approach–A hierarchical architecture of the railway EEW system was adopted,in which self-built stations along the railway serve as the backbone and the national seismic network provides supplementary data.Warning zones were designed along the railway using overlapping trapezoidal layouts to cover seismic stations and reduce inter-regional time delays.Offline replay experiments were conducted using 82 historical earthquake events and records from 61 seismic stations to evaluate the timeliness and accuracy of warning information.Findings–The results indicate that the PLUM-based early warning method can issue emergency response information before destructive seismic waves arrive.Multiple earthquake experiments demonstrated high reliability and stability,with effective detection across different magnitudes and epicentral distances.Furthermore,the trapezoidal overlapping zone design improved regional consistency and significantly reduced missed alerts.Originality/value–This work represents the first systematic application of the PLUM method to high-speed railway EEW in China.By integrating railway operational requirements,the proposed method provides a practical and robust emergency response strategy,offering new insights into seismic risk mitigation for China’s high-speed railways.
文摘In order to solve the problems of high coupling and poor scalability of the traditional monomer early warning release system architecture,multi-level deployment in a complex network environment will lead to high investment in software and hardware and cannot achieve intensive multi-level deployment.This paper realizes the goal of system scalability by introducing micro service architecture and technology stack and realizes the goal of resource intensification by introducing the idea of a data forwarding agent.The designed architecture scheme has been practically applied in the“Jiangxi emergency early warning information release system software platform(phase I)project”(hereinafter referred to as“provincial emergency”),which meets the needs of flexible deployment of multi-level applications across meteorological wide area network(WAN),business private network of other commissions,offices,and bureaus,government extranet,Internet and other complex networks,and fully verifies the scientificity and rationality of the scheme.It has achieved the goal of intensive and scalable construction of provincial emergencies under the complex network environment,greatly improved the early warning capacity and communication capacity of emergencies and comprehensive disasters,provided a reliable guarantee for disaster prevention and reduction,and provided a reference for the construction of current and future early warning release system and capacity improvement project.
文摘An effective warning system for flash floods along the upper River des Peres, a small urban stream in eastern Missouri, USA, is based on three enterprise-level, automated rain gauges.Because floods in this 25 km~2 basin develop rapidly and are commonly caused by small but intense thunderstorm cells, these rain gauges were necessarily deployed within the watershed, and immediate telemetry and processing of rainfall delivered in 5-minute intervals is required. Available data show that damaging floods in this area occur only 30 min to 3 h following the delivery of 38 mm of rainfall or more in a single hour. Water levels along this stream can rise more than 3 m/h. Since full deployment in Nov. 2021, our system has successfully predicted 3 significant floods with one false positive.
基金Projects(52209132, 52309156) supported by the National Natural Science Foundation of ChinaProject(BK20251905) supported by the Natural Science Foundation of Jiangsu Province,China+2 种基金Project(252102320037) supported by the Henan Province Science and Technology Research,ChinaProject(CKWV20231173/KY) supported by the CRSRI Open Research Program,ChinaProject(2023KSD15) supported by the Open Research Fund of Hubei Provincial Key Laboratory of Construction and Management in Hydropower Engineering,China。
文摘The collapse of rock masses in fault-developed zones poses significant safety challenges during the excavation of high-stress underground caverns. This study investigates the spatiotemporal evolution of the collapse mechanisms of the cavern in the Yebatan Hydropower Station through using microseismic (MS) monitoring and displacement measurements. We developed a multi-parameter deformation early warning model that integrates three critical indicators: deformation rate, rate increment, and tangential angle of the deformation time curve. The results of the early warning model show a significant and abrupt increase in the deformation of the rock mass during the collapse process. The safety and stability of the local cavern in the face of excavation-induced disturbances are meticulously assessed utilizing MS data. Spatiotemporal analysis of the MS monitoring indicates a high frequency of MS events during the blasting phase, with a notable clustering of these events in the vicinity of the fault. These research results provide a valuable reference for risk warnings and stability assessments in the fault development zones of analogous caverns.
基金“Research on AI-Intelligent Management Technology for Construction Safety Based on BIM Technology and Smart Construction Site Scenarios”(Project No.:KJQN202401904)“Research on Intelligent Monitoring System for Construction Quality and Safety Based on BIM and AI Technologies”(Project No.:202412608006)。
文摘Combining the background of modern construction engineering site safety management,this article analyzes the real-time monitoring and alarm strategies for site construction safety under the integration of BIM and AI.This includes the analysis of BIM and AI technologies and their integration advantages,real-time monitoring and alarm strategies for construction site safety based on BIM and AI integration,as well as the development direction of BIM and AI integration in real-time monitoring and alarm for construction site safety.It is hoped that through this analysis,a scientific reference can be provided for the digital and intelligent management of construction site safety,promoting the digital and intelligent development of its safety management work.
文摘With the continuous advancement of the tiered diagnosis and treatment system,the medical consortium model has gained increasing attention as an important approach to promoting the vertical integration of healthcare resources.Within this context,laboratory data,as a key component of healthcare information systems,urgently requires efficient sharing and intelligent analysis.This paper designs and constructs an intelligent early warning system for laboratory data based on a cloud platform tailored to the medical consortium model.Through standardized data formats and unified access interfaces,the system enables the integration and cleaning of laboratory data across multiple healthcare institutions.By combining medical rule sets with machine learning models,the system achieves graded alerts and rapid responses to abnormal key indicators and potential outbreaks of infectious diseases.Practical deployment results demonstrate that the system significantly improves the utilization efficiency of laboratory data,strengthens public health event monitoring,and optimizes inter-institutional collaboration.The paper also discusses challenges encountered during system implementation,such as inconsistent data standards,security and compliance concerns,and model interpretability,and proposes corresponding optimization strategies.These findings provide a reference for the broader application of intelligent medical early warning systems.
基金supported by the Jingneng Shiyan Thermal Power Co.,Ltd.(TPRI/TR-CA-006-2023)Huaihe Energy Power Group Co.,Ltd.(TPRI/TR-CA-040-2023)Xi'an Thermal Power Research Institute Co.,Ltd.(TPRI/TR-CA-110-2021A/H1).
文摘Thermal power generation systems have stringent requirements for water and steam quality,i.e.,condensate water quality is one of the critical issues.In this paper,we designed a two-layer model based on an autoencoder and expert knowledge to achieve the early warning and causal analysis of condensate water quality abnormalities.An early warning model using an autoencoder model is built based on the historical data affecting the condensate water quality.Next,an analytical model of condensate water quality abnormalities was then developed by combining expert knowledge and trend test algorithms.Two different datasets were used to test the proposed model,respectively.The accuracy of the autoencoder model in the short-period test set is 88.83%,which shows that the early warning model can accurately analyze the condensate water quality data and achieve the purpose of early warning.For the long-time period test set,the model can correctly identify each abnormality and simultaneously indicates the cause of the abnormal condensate water quality.The proposed model can correctly identify abnormal working conditions and it is applicable to other thermal power plants.
基金supported by the Spark Program of Earthquake Science and Technology(No.XH23003C)。
文摘The earthquake early warning system is an effective means of disaster reduction to reduce losses caused by earthquakes,it can release earthquake warning information to the public before destructive seismic waves reach the warning target area,and carry out automatic disposal of lifeline engineering facilities.Through the construction of the National Earthquake Intensity Rapid Reporting and Early Warning Project,an earthquake early warning network consisting of over 1900 monitoring stations has been established in the Beijing-Tianjin-Hebei Urban Agglomeration.The early warning system has achieved second level earthquake warning and minute level intensity rapid reporting.The implementation of these functions relies on the system's ability to timely,accurately,and reliably identify seismic waves.But with the development of social economy,the background noise of earthquake observation environment is becoming increasingly complex,which brings certain challenges to earthquake wave recognition,some interference events have the risk of triggering the earthquake warning system incorrectly.Therefore,this article focuses on seismic wave recognition in complex noise environments and proposes a seismic wave detection method based on triangulation to enhance the antiinterference ability and recognition accuracy of early warning systems.
