ARHCS (Automatic Rainfall Half-Life Cluster System): A Landslides Early Warning System (LEWS) Using Cluster Analysis and Automatic Threshold Definition

A significant portion of Landslide Early Warning Systems (LEWS) relies on the definition of operational thresholds and the monitoring of cumulative rainfall for alert issuance. These thresholds can be obtained in various ways, but most often they are based on previous landslide data. This approach introduces several limitations. For instance, there is a requirement for the location to have been previously monitored in some way to have this type of information recorded. Another significant limitation is the need for information regarding the location and timing of incidents. Despite the current ease of obtaining location information (GPS, drone images, etc.), the timing of the event remains challenging to ascertain for a considerable portion of landslide data. Concerning rainfall monitoring, there are multiple ways to consider it, for instance, examining accumulations over various intervals (1 h, 6 h, 24 h, 72 h), as well as in the calculation of effective rainfall, which represents the precipitation that actually infiltrates the soil. However, in the vast majority of cases, both the thresholds and the rain monitoring approach are defined manually and subjectively, relying on the operators’ experience. This makes the process labor-intensive and time-consuming, hindering the establishment of a truly standardized and rapidly scalable methodology on a large scale. In this work, we propose a Landslides Early Warning System (LEWS) based on the concept of rainfall half-life and the determination of thresholds using Cluster Analysis and data inversion. The system is designed to be applied in extensive monitoring networks, such as the one utilized by Cemaden, Brazil’s National Center for Monitoring and Early Warning of Natural Disasters.

The Application of China's High Speed Railway Earthquake Early Warning System in Jakarta-Bandung HSR

Earthquake has a significant impact on operation safety of the high speed railway,and for Jakarta-Bandung High Speed Railway(HSR)in Indonesia where it is earthquake-prone,it is necessary to establish an earthquake early warning system to strengthen its earthquake resistance.Based on the principle and technical characteristics of China's high speed railway earthquake early warning system and combining the actual situations of Jakarta-Bandung HSR in Indonesia,this paper describes how to implement China's high speed railway earthquake early warning system in Jakarta-Bandung HSR.It focuses on optimizations in environmental adaptation design and seismic network interface design,earthquake attenuation model parameter adjustment and terminal software interface adjustment,so as to make the system better suit the local situations,and meet operation requirements and guarantee safe operation of Jakarta-Bandung HSR.

Effectiveness of Combined Application of Shock Index and Early Warning Scoring System in Patients with Acute Gastrointestinal Hemorrhage

Objective:To explore the effect of the combined application of the Shock Index(SI)and the Early Warning Score(EWS)in patients with acute gastrointestinal bleeding.Methods:Seventy patients with acute gastrointestinal bleeding admitted to a hospital from June 2022 to May 2024 were selected and randomly divided into two groups:the control group and the observation group,with 35 patients in each group.The control group received conventional emergency care measures,while the observation group received SI combined with NEWS emergency care measures.The treatment effects in both groups were compared.Results:The observation group had shorter waiting times for consultation(4.45±1.59 minutes),intravenous access establishment(6.79±2.52 minutes),hemostasis time(4.41±1.52 hours),and hospital stays(8.39±2.13 days)compared to the control group,which had times of 5.46±1.34 minutes,8.41±2.16 minutes,5.16±1.47 hours,and 10.26±2.98 days,respectively.The differences were statistically significant(P<0.05).Before management,there were no significant differences in the levels of hemoglobin,prealbumin,and serum protein between the two groups(P>0.05).However,after systematic emergency management,the serum indexes in both groups significantly improved,with the observation group showing greater improvement than the control group,and these differences were statistically significant(P<0.05).In the observation group,only one case of cardiovascular complications occurred during the rescue period,with an incidence rate of 2.86%.In contrast,the control group experienced eight cases of complications,including hemorrhagic shock,anemia,multi-organ failure,cardiovascular complications,and gastrointestinal rebleeding,with an incidence rate of 22.85%.The difference between the groups was statistically significant(P<0.05).Conclusion:The application of SI combined with EWS emergency care measures in patients with acute gastrointestinal hemorrhage can effectively improve serum indexes,shorten resuscitation time and hospital stay,and reduce the risk of complications such as hemorrhagic shock,anemia,infection,multi-organ failure,cardiovascular complications,acute renal failure,and gastrointestinal rebleeding.This approach has positive clinical application value.

WebGIS-based Early Warning System of Farmland Environmental Pollution Caused by Livestock Waste

[Objective]The paper was to quickly get the real-time dynamic status of regional farmland environmental pollution caused by livestock wastes.[Method] With WebGIS as spatial information platform,the network and digital early warning system of farmland environmental pollution caused by livestock wastes was established.[Result] The system realized the functions such as livestock wastes calculation,livestock information query and analysis,nitrogen load quantity estimation of livestock waste,early warning of farmland environmental pollution caused by livestock wastes and visual display of result.[Conclusion] The paper provided scientific basis for the relevant research on farmland environmental pollution caused by livestock wastes.

Construction of Cucumber Powdery Mildew Early Warning System in Solar Greenhouse Based on Internet of Things

ln order to explore the design and construction of cucumber powdery mildew warning system in solar greenhouse, internet of things technology was used to conduct the real-time dynamic monitoring of the incidence of cucumber powdery mildew and cucumber growth environment in solar greenhouse. The growth environ-ment included temperature and humidity of air and soil. Logistic regression model was used to construct cucumber powdery mildew warning model. The results showed that humidity characteristic variable （maximum air humidity） and temperature characteristic variable （maximum air temperature） had significant effects on the inci-dence probability of cucumber powdery mildew in solar greenhouse. And it was fea-sible to construct cucumber powdery mildew warning system in solar greenhouse with internet of things.

Design and Realization of Cold Disaster Early Warning System for Subtropics Aquaculture

By analyzing the subtropics aquaculture present situation,the necessity of the construction of cold disaster early warning system for subtropics aquaculture,the research goal and the duty were expounded. The system structure and the frame were introduced in detail. Several key questions and their solutions of the cold disaster early warning system for subtropics aquaculture were put forward.

Early Warning System of Important Meteorological Disasters in Hunan Province

Based on technologies of GRADS, Delphi, WEB and an SQLServer, distri- bution system for major meteorological disasters early warning information in Hunan Province was established. The system consists of warning tips, early warning for different media and early warning query statistics and the network terminal of the system platform includes a business database server, a message platform database server, a sending server and a receiving terminal. The system enjoys some func- tions, such as examination by different users, on-time updating and effectiveness of flood prevention, construction of excessive warning channel, construction of compre-hensive warning information platform and further improvement of information distribution. The system provides references for prevention and reduction of important me- teorological disasters in Hunan.

Early warning method for thermal runaway of lithium-ion batteries under thermal abuse condition based on online electrochemical impedance monitoring

Early warning of thermal runaway(TR)of lithium-ion batteries(LIBs)is a significant challenge in current application scenarios.Timely and effective TR early warning technology is urgently required considering the current fire safety situation of LIBs.In this work,we report an early warning method of TR with online electrochemical impedance spectroscopy(EIS)monitoring,which overcomes the shortcomings of warning methods based on traditional signals such as temperature,gas,and pressure with obvious delay and high cost.With in-situ data acquisition through accelerating rate calorimeter(ARC)-EIS test,the crucial features of TR were extracted using the RReliefF algorithm.TR mechanisms corresponding to the features at specific frequencies were analyzed.Finally,a three-level warning strategy for single battery,series module,and parallel module was formulated,which can successfully send out an early warning signal ahead of the self-heating temperature of battery under thermal abuse condition.The technology can provide a reliable basis for the timely intervention of battery thermal management and fire protection systems and is expected to be applied to electric vehicles and energy storage devices to realize early warning and improve battery safety.

Preliminary Study on Early-warning System of Ecological Security in Water-Level-Fluctuating Zone (WLFZ) of Three Gorges Reservoir

The area,the scope as well as some ecological environment questions in Three Gorges Reservoir was briefly introduced. Then its early warning-system frame was preliminarily constructed,which includes ecological security dynamic monitoring,ecological security appraisal,ecological security forecast and ecological security decision-making management. The synthetic evaluation indicator system of the ecological security quality were initially established,which includes ecological environment pollution,land use and land cover change,geological hazard and epidemic outbreaks. At the same time,29 evaluating indicators were selected,divides into the basic factors,response factors and inducing factors,which need to be Real-time monitored.

A Real-time Monitoring and Early Warning System for Landslides in Southwest China

Landslides not only cause property losses,but also kill and injure large numbers of people every year in the mountainous areas. These losses and casualties may be avoided to some extent by early warning systems for landslides. In this paper, a realtime monitoring network and a computer-aided automatic early warning system(EWS) are presented with details of their design and an example of application in the Longjingwan landslide, Kaiyang County, Guizhou Province. Then, according to principle simple method of landslide prediction, the setting of alarm levels and the design of appropriate counter-measures are presented. A four-level early warning system(Zero, Outlook, Attention and Warning) has been adopted, and the velocity threshold was selected as the main warning threshold for the landslide occurrence, but expert judgment is included in the EWS to avoid false alarms. A case study shows the applicability and reliability for landslide risk management, and recommendations are presented for other similar projects.

Effect of an inpatient nursing risk early warning and control system in Shanghai:A retrospective study of adverse events

Purpose:To avoid the nursing risk of inpatients,reduce the occurrence of nursing errors and improve the safety of inpatients.Methods:We established a nursing risk early warning and control system,which includes a safety supervisory network,risk screening and early warning tools,and a risk control process.Results:The qualified rates of risk control measures to prevent pressure ulcers,unplanned extubation and fall/fall from bed all increased.The incidence of reported nursing errors decreased.The number of mistakes in medication-giving decreased.Conclusion:The establishment of an inpatient early warning and control system could effectively avoid nursing risk,improve risk prevention abilities,improve patient safety,and improve nursing quality.

Present and future of new systemic therapies for early and intermediate stages of hepatocellular carcinoma

Hepatocellular carcinoma(HCC)is a high mortality neoplasm which usually appears on a cirrhotic liver.The therapeutic arsenal and subsequent prognostic outlook are intrinsically linked to the HCC stage at diagnosis.Notwithstanding the current deployment of treatments with curative intent(liver resection/local ablation and liver transplantation)in early and intermediate stages,a high rate of HCC recurrence persists,underscoring a pivotal clinical challenge.Emergent systemic therapies(ST),particularly immunotherapy,have demonstrate promising outcomes in terms of increase overall survival,but they are currently bound to the advanced stage of HCC.This review provides a comprehensive analysis of the literature,encompassing studies up to March 10,2024,evaluating the impact of novel ST in the early and intermediate HCC stages,specially focusing on the findings of neoadjuvant and adjuvant regimens,aimed at increasing significantly overall survival and recurrence-free survival after a treatment with curative intent.We also investigate the potential role of ST in enhancing the downstaging rate for the intermediate-stage HCC initially deemed ineligible for treatment with curative intent.Finally,we critically discuss about the current relevance of the results of these studies and the encouraging future implications of ST in the treatment schedules of early and intermediate HCC stages.

Effect of preload forces on multidimensional signal dynamic behaviours for battery early safety warning

Providing early safety warning for batteries in real-world applications is challenging.In this study,comprehensive thermal abuse experiments are conducted to clarify the multidimensional signal evolution of battery failure under various preload forces.The time-sequence relationship among expansion force,voltage,and temperature during thermal abuse under five categorised stages is revealed.Three characteristic peaks are identified for the expansion force,which correspond to venting,internal short-circuiting,and thermal runaway.In particular,an abnormal expansion force signal can be detected at temperatures as low as 42.4°C,followed by battery thermal runaway in approximately 6.5 min.Moreover,reducing the preload force can improve the effectiveness of the early-warning method via the expansion force.Specifically,reducing the preload force from 6000 to 1000 N prolongs the warning time(i.e.,227 to 398 s)before thermal runaway is triggered.Based on the results,a notable expansion force early-warning method is proposed that can successfully enable early safety warning approximately 375 s ahead of battery thermal runaway and effectively prevent failure propagation with module validation.This study provides a practical reference for the development of timely and accurate early-warning strategies as well as guidance for the design of safer battery systems.

An Early Warning System for Curved Road Based on OV7670 Image Acquisition and STM32

Nowadays,the number of vehicles in China has increased significantly.The increase of the number of vehicles has also led to the increasingly complex traffic situation and the urgent safety measures in need.However,the existing early warning devices such as geomagnetic,ultrasonic and infrared detection have some shortcomings like difficult installation and maintenance.In addition,geomagnetic detection will damage the road surface,while ultrasonic and infrared detection will be greatly affected by the environment.Considering the shortcomings of the existing solutions,this paper puts forward a solution of early warning for vehicle turning meeting based on image acquisition and microcontrollers.This solution combines image acquisition and processing technology,which uses image sensor to perceive traffic condition and image data analysis algorithm to process perceived image,and then utilize LED display screen to issue an early warning.

Comparing 11 early warning scores and three shock indices in early sepsis prediction in the emergency department

BACKGROUND:This study aimed to evaluate the discriminatory performance of 11 vital sign-based early warning scores(EWSs)and three shock indices in early sepsis prediction in the emergency department(ED).METHODS:We performed a retrospective study on consecutive adult patients with an infection over 3 months in a public ED in Hong Kong.The primary outcome was sepsis(Sepsis-3 definition)within 48 h of ED presentation.Using c-statistics and the DeLong test,we compared 11 EWSs,including the National Early Warning Score 2(NEWS2),Modified Early Warning Score,and Worthing Physiological Scoring System(WPS),etc.,and three shock indices(the shock index[SI],modified shock index[MSI],and diastolic shock index[DSI]),with Systemic Inflammatory Response Syndrome(SIRS)and quick Sequential Organ Failure Assessment(qSOFA)in predicting the primary outcome,intensive care unit admission,and mortality at different time points.RESULTS:We analyzed 601 patients,of whom 166(27.6%)developed sepsis.NEWS2 had the highest point estimate(area under the receiver operating characteristic curve[AUROC]0.75,95%CI 0.70-0.79)and was significantly better than SIRS,qSOFA,other EWSs and shock indices,except WPS,at predicting the primary outcome.However,the pooled sensitivity and specificity of NEWS2≥5 for the prediction of sepsis were 0.45(95%CI 0.37-0.52)and 0.88(95%CI 0.85-0.91),respectively.The discriminatory performance of all EWSs and shock indices declined when used to predict mortality at a more remote time point.CONCLUSION:NEWS2 compared favorably with other EWSs and shock indices in early sepsis prediction but its low sensitivity at the usual cut-off point requires further modification for sepsis screening.

Biological Early Warning and Emergency Management Support System for Water Pollution Accident

Water pollution accidents such as chemical spill and toxicants leach have become a serious issue in the world, which brings great threats to the aquatic ecosystem and drinking water safety. To detect unknown pollutions in time and take proper emergency actions, this study developed a system which integrated an online intelligent water quality monitoring device with a high efficient water quality model. The device is based on water quality probes and biological sensors which use fish motion as indicator. The numerical model is a combination of Euler and Lagrangian approaches. Finite element method is applied to simulate the flow field in an unstructured grid, and the pollutant be- haviours are traced through particle tracking. Oracle is used to manage the basic and monitoring data, and ArcSDE as well as ArclMS technologies are applied to make the system WebGIS-based so as to improve the data receiving and dispatching efficiency. The developed system has been successfully operated in Douhe Reservoir and Taihu Lake, China, where drinking water intakes are installed. It is seen from the applications that the online intelligent water qual- ity monitoring and emergency support system can be of great support to emergency management.

Multi-Lever EarlyWarning forWind and Photovoltaic Power Ramp Events Based on Neural Network and Fuzzy Logic

With the increasing penetration of renewable energy in power system,renewable energy power ramp events(REPREs),dominated by wind power and photovoltaic power,pose significant threats to the secure and stable operation of power systems.This paper presents an early warning method for REPREs based on long short-term memory(LSTM)network and fuzzy logic.First,the warning levels of REPREs are defined by assessing the control costs of various power control measures.Then,the next 4-h power support capability of external grid is estimated by a tie line power predictionmodel,which is constructed based on the LSTMnetwork.Finally,considering the risk attitudes of dispatchers,fuzzy rules are employed to address the boundary value attribution of the early warning interval,improving the rationality of power ramp event early warning.Simulation results demonstrate that the proposed method can generate reasonable early warning levels for REPREs,guiding decision-making for control strategy.

Study on the Analysis System of Meteorological and Geological Disaster Grades Early Warning of WebGIS

The method of realizing meteorological and geological disaster forecast and early warning information system in Qixian County of Shanxi Province was studied. According to meteorological factor parameter of the geological disasters for many years in Qixian County Land Bureau, and data of average meteorological element parameters that corresponded by evolution of geological disaster region each year, evaluation algorithm model of the forecast and eady warning of geological disasters in Qixian County was obtained, and the database of meteorological factor of geological disaster was established. On this basis, WebGIS geographic information system based on C/S and B/S which could real-time monitor geological disaster region was studied and designed. After data analysis system could evaluate the geological disaster forecast and early warning and make the real-time and accurate early warning, which greatly improved the timeliness of meteorological geological disasters forecast and early warning in Qixian County. System set of data processing and forecast and early warning issued in one, to realize the dynamic information release function of grade of geological disaster early warning, and had the characteristics of easy sharing, real-time dynamic update.

Validation and performance of three scoring systems for predicting primary non-function and early allograft failure after liver transplantation

Background: Primary non-function(PNF) and early allograft failure(EAF) after liver transplantation(LT) seriously affect patient outcomes. In clinical practice, effective prognostic tools for early identifying recipients at high risk of PNF and EAF were urgently needed. Recently, the Model for Early Allograft Function(MEAF), PNF score by King's College(King-PNF) and Balance-and-Risk-Lactate(BAR-Lac) score were developed to assess the risks of PNF and EAF. This study aimed to externally validate and compare the prognostic performance of these three scores for predicting PNF and EAF. Methods: A retrospective study included 720 patients with primary LT between January 2015 and December 2020. MEAF, King-PNF and BAR-Lac scores were compared using receiver operating characteristic(ROC) and the net reclassification improvement(NRI) and integrated discrimination improvement(IDI) analyses. Results: Of all 720 patients, 28(3.9%) developed PNF and 67(9.3%) developed EAF in 3 months. The overall early allograft dysfunction(EAD) rate was 39.0%. The 3-month patient mortality was 8.6% while 1-year graft-failure-free survival was 89.2%. The median MEAF, King-PNF and BAR-Lac scores were 5.0(3.5–6.3),-2.1(-2.6 to-1.2), and 5.0(2.0–11.0), respectively. For predicting PNF, MEAF and King-PNF scores had excellent area under curves(AUCs) of 0.872 and 0.891, superior to BAR-Lac(AUC = 0.830). The NRI and IDI analyses confirmed that King-PNF score had the best performance in predicting PNF while MEAF served as a better predictor of EAD. The EAF risk curve and 1-year graft-failure-free survival curve showed that King-PNF was superior to MEAF and BAR-Lac scores for stratifying the risk of EAF. Conclusions: MEAF, King-PNF and BAR-Lac were validated as practical and effective risk assessment tools of PNF. King-PNF score outperformed MEAF and BAR-Lac in predicting PNF and EAF within 6 months. BAR-Lac score had a huge advantage in the prediction for PNF without post-transplant variables. Proper use of these scores will help early identify PNF, standardize grading of EAF and reasonably select clinical endpoints in relative studies.

Study of Enterprises Marketing Risk Early Warning System Based on BP Neural Network Model

For effectively early warning the marketing risk caused along with the varied environment, a BP neural network method was introduced on the basis of analyzing the shortcomings of the risk early warning method, and combined with the practical conditions of dairy enterprises, the index system caused by the marketing risk was also studied. The＇principal component method was used for screening the indexes, the grades and critical values of the marketing risk were determined. Through the configuration of BP network, node processing and error analysis, the early warning resuits of the marketing risk were obtained. The results indicate that BP neural network method can be effectively applied through the function approach in the marketing early warning with incomplete information and complex varied conditions.