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 curre...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.展开更多
The well-developed multifunctional wearable electronic device has fed the demand for human medicine and health monitoring in complex situations.However,the advancement of nuclear technology,especially irradiation medi...The well-developed multifunctional wearable electronic device has fed the demand for human medicine and health monitoring in complex situations.However,the advancement of nuclear technology,especially irradiation medicine and safety inspections,has increased the exposure risk of irradiation safety workers.Traditional irradiation detectors are stiff and incompatible with the skin,and lack human health monitoring function,thus it’s vital to apply these flexible sensors for irradiation warning.Here,we report a novel composite gel device synthesized through solution processes by combining the Cs_(3)Cu_(2)I_(5):Zn nanoscintillator with the pre-patterned biocompatible gel,exhibiting a bi-functional response to motion/vibration sensing and sensitive irradiation warning.These wearable devices achieve a pressure sensitivity of up to 34 kPa^(-1)in a low-pressure range (0–3 kPa),a low limit of detection (LoD) down to 1.4 Pa,enabling health monitoring functions of pulse monitoring,finger bending,and elbow bending.Simultaneously,the device scintillates under X-ray irradiation among a wide dose rate range of 54–1167μGy_(air)s^(-1).The robust device shows no obvious signal loss after 4000 compression cycles and also excellent irradiation resistance over 50 days,broadening the path for designing and realizing new functional wearable devices.展开更多
Onlineγ-spectrometry systems for inland waters,most of which extract samples in situ and in real time,are able to produce reliable activity concentration measurements for waterborne radionuclides only when they are d...Onlineγ-spectrometry systems for inland waters,most of which extract samples in situ and in real time,are able to produce reliable activity concentration measurements for waterborne radionuclides only when they are distributed relatively uniformly and enter into a steady-state diffusion regime in the measurement chamber.To protect residents’health and ensure the safety of the living environment,better timeliness is required for this measurement method.To address this issue,this study established a mathematical model of the online waterγ-spectrometry system so that rapid warning and activity estimates can be obtained for water under non-steady-state(NSS)conditions.In addition,the detection efficiency of the detector for radionuclides during the NSS diffusion process was determined by applying the computational fluid dynamics technique in conjunction with Monte Carlo simulations.On this basis,a method was developed that allowed the online waterγ-spectrometry system to provide rapid warning and activity concentration estimates for radionuclides in water.Subsequent analysis of the NSS-mode measurements of^(40)K radioactive solutions with different activity concentrations determined the optimum warning threshold and measurement time for producing accurate activity concentration estimates for radionuclides.The experimental results show that the proposed NSS measurement method is able to give warning and yield accurate activity concentration estimates for radionuclides 55.42 and 69.42 min after the entry of a 10 Bq/L^(40)K radioactive solution into the measurement chamber,respectively.These times are much shorter than the 90 min required by the conventional measurement method.Furthermore,the NSS measurement method allows the measurement system to give rapid(within approximately 15 min)warning when the activity concentrations of some radionuclides reach their respective limits stipulated in the Guidelines for Drinking-water Quality of the WHO,suggesting that this method considerably enhances the warning capacity of in situ online waterγ-spectrometry systems.展开更多
Fire warning is vital to human life,economy and ecology.However,the development of effective warning systems faces great challenges of fast response,adjustable threshold and remote detecting.Here,we propose an intelli...Fire warning is vital to human life,economy and ecology.However,the development of effective warning systems faces great challenges of fast response,adjustable threshold and remote detecting.Here,we propose an intelligent self-powered remote IoT fire warning system,by employing single-walled carbon nanotube/titanium carbide thermoelectric composite films.The flexible films,prepared by a convenient solution mixing,display p-type characteristic with excellent high-temperature stability,flame retardancy and TE(power factor of 239.7±15.8μW m^(-1) K^(-2))performances.The comprehensive morphology and structural analyses shed light on the underlying mechanisms.And the assembled TE devices(TEDs)exhibit fast fire warning with adjustable warning threshold voltages(1–10 mV).Excitingly,an ultrafast fire warning response time of~0.1 s at 1 mV threshold voltage is achieved,rivaling many state-of-the-art systems.Furthermore,TE fire warning systems reveal outstanding stability after 50 repeated cycles and desired durability even undergoing 180 days of air exposure.Finally,a TED-based wireless intelligent fire warning system has been developed by coupling an amplifier,analogto-digital converter and Bluetooth module.By combining TE characteristics,high-temperature stability and flame retardancy with wireless IoT signal transmission,TE-based hybrid system developed here is promising for next-generation self-powered remote IoT fire warning applications.展开更多
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 fa...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.展开更多
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 per...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.展开更多
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
Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powe...Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powerful tool for the early warning of rock burst. In this study, an MS multi-parameter index system was established and the critical values of each index were estimated based on the normalized multi-information warning model of coal-rock dynamic failure. This index system includes bursting strain energy(BSE) index, time-space-magnitude independent information(TSMII) indices and timespace-magnitude compound information(TSMCI) indices. On the basis of this multi-parameter index system, a comprehensive analysis was conducted via introducing the R-value scoring method to calculate the weights of each index. To calibrate the multi-parameter index system and the associated comprehensive analysis, the weights of each index were first confirmed using historical MS data occurred in LW402102 of Hujiahe Coal Mine(China) over a period of four months. This calibrated comprehensive analysis of MS multi-parameter index system was then applied to pre-warn the occurrence of a subsequent rock burst incident in LW 402103. The results demonstrate that this multi-parameter index system combined with the comprehensive analysis are capable of quantitatively pre-warning rock burst risk.展开更多
The network is a major platform for implementing new cyber-telecom crimes.Therefore,it is important to carry out monitoring and early warning research on new cyber-telecom crime platforms,which will lay the foundation...The network is a major platform for implementing new cyber-telecom crimes.Therefore,it is important to carry out monitoring and early warning research on new cyber-telecom crime platforms,which will lay the foundation for the establishment of prevention and control systems to protect citizens’property.However,the deep-learning methods applied in the monitoring and early warning of new cyber-telecom crime platforms have some apparent drawbacks.For instance,the methods suffer from data-distribution differences and tremendous manual efforts spent on data labeling.Therefore,a monitoring and early warning method for new cyber-telecom crime platforms based on the BERT migration learning model is proposed.This method first identifies the text data and their tags,and then performs migration training based on a pre-training model.Finally,the method uses the fine-tuned model to predict and classify new cyber-telecom crimes.Experimental analysis on the crime data collected by public security organizations shows that higher classification accuracy can be achieved using the proposed method,compared with the deep-learning method.展开更多
BACKGROUND:This study was undertaken to validate the use of the modified early warning score(MEWS) as a predictor of patient mortality and intensive care unit(ICU)/ high dependency(HD)admission in an Asian population....BACKGROUND:This study was undertaken to validate the use of the modified early warning score(MEWS) as a predictor of patient mortality and intensive care unit(ICU)/ high dependency(HD)admission in an Asian population.METHODS:The MEWS was applied to a retrospective cohort of 1 024 critically ill patients presenting to a large Asian tertiary emergency department(ED) between November 2006 and December2007.Individual MEWS was calculated based on vital signs parameters on arrival at ED.Outcomes of mortality and ICU/HD admission were obtained from hospital records.The ability of the composite MEWS and its individual components to predict mortality within 30 days from ED visit was assessed.Sensitivity,specificity,positive and negative predictive values were derived and compared with values from other cohorts.A MEWS of ≥4 was chosen as the cut-off value for poor prognosis based on previous studies.RESULTS:A total of 311(30.4%) critically ill patients were presented with a MEWS ≥4.Their mean age was 61.4 years(SD 18.1) with a male to female ratio of 1.10.Of the 311 patients,53(17%)died within 30 days,64(20.6%) were admitted to ICU and 86(27.7%) were admitted to HD.The area under the receiver operating characteristic curve was 0.71 with a sensitivity of 53.0%and a specificity of 72.1%in addition to a positive predictive value(PPV) of 17.0%and a negative predictive value(NPV)of 93.4%(MEWS cut-off of ≥4) for predicting mortality.CONCLUSION:The composite MEWS did not perform well in predicting poor patient outcomes for critically ill patients presenting to an ED.展开更多
Using the new technologies such as information technology, communication technology and electronic control technology, vehicle collision warning system（CWS） can acquire road condition, adjacent vehicle march conditi...Using the new technologies such as information technology, communication technology and electronic control technology, vehicle collision warning system（CWS） can acquire road condition, adjacent vehicle march condition as well as its dynamics performance continuously, then it can forecast the oncoming potential collision and give a warning. Based on the analysis of driver＇s driving behavior, algorithm＇s warning norms are determined. Based on warning norms adopting machine vision method, the cooperation collision warning algorithm（CWA） model with multi-input and multi-output is established which is used in supporting vehicle CWS. The CWA is tested using the actual data and the result shows that this algorithm can identify and carry out warning for vehicle collision efficiently, which has important meaning for improving the vehicle travel safety.展开更多
In this paper, the early warning signals of abrupt temperature change in different regions of China are investigated. Seven regions are divided on the basis of different climate temperature patterns, obtained through ...In this paper, the early warning signals of abrupt temperature change in different regions of China are investigated. Seven regions are divided on the basis of different climate temperature patterns, obtained through the rotated empirical orthogonal function, and the signal-to-noise temperature ratios for each region are then calculated. Based on the concept of critical slowing down, the temperature data that contain noise in the different regions of China are preprocessed to study the early warning signals of abrupt climate change. First, the Mann-Kendall method is used to identify the instant of abrupt climate change in the temperature data. Second, autocorrelation coefficients that can identify critical slowing down are calculated. The results show that the critical slowing down phenomenon appeared in temperature data about 5-10 years before abrupt climate change occurred, which indicates that the critical slowing down phenomenon is a possible early warning signal for abrupt climate change, and that noise has less influence on the detection results of the early warning signals. Accordingly, this demonstrates that the model is reliable in identifying the early warning signals of abrupt climate change based on detecting the critical slowing down phenomenon, which provides an experimental basis for the actual application of the method.展开更多
Objective To examine if the variations at sea level would be able to predict subsequent susceptibility to acute altitude sickness in subjects upon a rapid ascent to high altitude.Methods One hundred and six Han nation...Objective To examine if the variations at sea level would be able to predict subsequent susceptibility to acute altitude sickness in subjects upon a rapid ascent to high altitude.Methods One hundred and six Han nationality male individuals were recruited to this research.Dynamic electrocardiogram,treadmill exercise test,echocardiography,routine blood examination and biochemical analysis were performed when subjects at sea level and entering the plateau respectively.Then multiple regression analysis was performed to construct a multiple linear regression equation using the Lake Louise Score as dependent variable to predict the risk factors at sea level related to acute mountain sickness(AMS).Results Approximately 49.05%of the individuals developed AMS.The tricuspid annular plane systolic excursion(22.0+2.66 vs.23.2+3.19 mm,t=l.998,P=0.048)was significantly lower in the AMS group at sea level,while count of eosinophil[(0.264+0.393)×109/L vs.(0.126+0.084)×109/L,t=-2.040,P—0.045],percentage of diflerences exceeding 50 ms between adjacent normal number of intervals(PNN50,9.66%±5.40%vs.6.98%±5.66%,t=-2.229,P=0.028)and heart rate variability triangle index(57.1+16.1 vs.50.6+12.7,t=-2.271,P=0.025)were significantly higher.After acute exposure to high altitude,C-reactive protein(0.098+0.103 vs.0.062+0.045 g/L,t=-2.132,P=0.037),aspartate aminotransferase(19.7+6.7275.17,3±3.95 U/L,t=-2.231,P=0.028)and creatinine(85.1±12.9 vs.77.7±11.2 mmol/L,t=3.162,P=0.002)were significantly higher in the AMS group,while alkaline phosphatase(71.7+18.2 vs.80.6+20.2 U/L,t=2.389,P=0.019),standard deviation of normal-to-normal RR intervals(126.5+35.9 vs.143.3+36.4 ms,t—2.320,P—0.022),ejection time(276.9+50.8 vs.313.8+48.9 ms,t—3.641,P—0.001)and heart rate variability triangle index(37.1+12.9 vs.41.9+11.1,t=2.O2O,P=0.047)were significantly lower.Using the Lake Louise Score as the dependent variable,prediction equation were established to estimate AMS:Lake Louise Score=3.783+0.281Xeosinophil-0.219Xalkaline phosphatase+O.O32XPNN50.Conclusions We elucidated the differences of pl^siological variables as well as noninvasive cardiovascular indicators for subjects after high altitude exposure compared with those at sea level.We also created an acute high altitude reaction early warning equation based on the physiological variables and noninvasive cardiovascular indicators at sea level.展开更多
Synchronous generators are important components of power systems and are necessary to maintain its normal and stable operation.To perform the fault diagnosis of mild inter-turn short circuit in the excitation winding ...Synchronous generators are important components of power systems and are necessary to maintain its normal and stable operation.To perform the fault diagnosis of mild inter-turn short circuit in the excitation winding of a synchronous generator,a gate recurrent unit-convolutional neural network(GRU-CNN)model whose structural parameters were determined by improved particle swarm optimization(IPSO)is proposed.The outputs of the model are the excitation current and reactive power.The total offset distance,which is the fusion of the offset distance of the excitation current and offset distance of the reactive power,was selected as the fault judgment criterion.The fusion weights of the excitation current and reactive power were determined using the anti-entropy weighting method.The fault-warning threshold and fault-warning ratio were set according to the normal total offset distance,and the fault warning time was set according to the actual situation.The fault-warning time and fault-warning ratio were used to avoid misdiagnosis.The proposed method was verified experimentally.展开更多
Smart fire alarm sensor(FAS)materials with mechanically robust,excellent flame retardancy as well as ultra-sensitive temperature-responsive capability are highly attractive platforms for fire safety application.Howeve...Smart fire alarm sensor(FAS)materials with mechanically robust,excellent flame retardancy as well as ultra-sensitive temperature-responsive capability are highly attractive platforms for fire safety application.However,most reported FAS materials can hardly provide sensitive,continuous and reliable alarm signal output due to their undesirable temperature-responsive,flame-resistant and mechanical performances.To overcome these hurdles,herein,we utilize the multi-amino molecule,named HCPA,that can serve as triple-roles including cross-linker,fire retardant and reducing agent for decorating graphene oxide(GO)sheets and obtaining the GO/HCPA hybrid networks.Benefiting from the formation of multi-interactions in hybrid network,the optimized GO/HCPA network exhibits significant increment in mechanical strength,e.g.,tensile strength and toughness increase of~2.3and~5.7 times,respectively,compared to the control one.More importantly,based on P and N doping and promoting thermal reduction effect on GO network,the excellent flame retardancy(withstanding~1200℃flame attack),ultra-fast fire alarm response time(~0.6 s)and ultra-long alarming period(>600 s)are obtained,representing the best comprehensive performance of GO-based FAS counterparts.Furthermore,based on GO/HCPA network,the fireproof coating is constructed and applied in polymer foam and exhibited exceptional fire shielding performance.This work provides a new idea for designing and fabricating desirable FAS materials and fireproof coatings.展开更多
As a new technical means that can detect abnormal signs of water inrush in advance and give an early warning,the automatic monitoring and early warning of water inrush in mines has been widely valued in recent years.D...As a new technical means that can detect abnormal signs of water inrush in advance and give an early warning,the automatic monitoring and early warning of water inrush in mines has been widely valued in recent years.Due to the many factors affecting water inrush and the complicated water inrush mechanism,many factors close to water inrush may have precursory abnormal changes.At present,the existing monitoring and early warning system mainly uses a few monitoring indicators such as groundwater level,water influx,and temperature,and performs water inrush early warning through the abnormal change of a single factor.However,there are relatively few multi-factor comprehensive early warning identification models.Based on the analysis of the abnormal changes of precursor factors in multiple water inrush cases,11 measurable and effective indicators including groundwater flow field,hydrochemical field and temperature field are proposed.Finally,taking Hengyuan coal mine as an example,6 indicators with long-term monitoring data sequences were selected to establish a single-index hierarchical early-warning recognition model,a multi-factor linear recognition model,and a comprehensive intelligent early-warning recognition model.The results show that the correct rate of early warning can reach 95.2%.展开更多
Firefighting protective clothing is a crucial protective equipment for firefighters to minimize skin burn and ensure safety firefighting operation and rescue mission.A recent increasing concern is to develop self-powe...Firefighting protective clothing is a crucial protective equipment for firefighters to minimize skin burn and ensure safety firefighting operation and rescue mission.A recent increasing concern is to develop self-powered fire warning materials that can be incorporated into the firefighting clothing to achieve active fire protection for firefighters before the protective clothing catches fire on fireground.However,it is still a challenge to facilely design and manufacture thermoelectric(TE)textile(TET)-based fire warning electronics with dynamic surface conformability and breathability.Here,we develop an alternate coaxial wet-spinning strategy to continuously produce alternating p/n-type TE aerogel fibers involving n-type Ti_(3)C_(2)T_(x)MXene and p-type MXene/SWCNT-COOH as core materials,and tough aramid nanofiber as protective shell,which simultaneously ensure the flexibility and high-efficiency TE power generation.With such alternating p/n-type TE fibers,TET-based self-powered fire warning sensors with high mechanical stability and wearability are successfully fabricated through stitching the alternating p-n segment TE fibers into aramid fabric.The results indicate that TET-based fire warning electronics containing 50 p-n pairs produce the open-circuit voltage of 7.5 mV with a power density of 119.79 nW cm-2 at a temperature difference of 300℃.The output voltage signal is then calculated as corresponding surface temperature of firefighting clothing based on a linear relationship between TE voltage and temperature.The fire alarm response time and flame-retardant properties are further displayed.Such self-powered fire warning electronics are true textiles that offer breathability and compatibility with body movement,demonstrating their potential application in firefighting clothing.展开更多
BACKGROUND:To evaluate the accuracy of National Early Warning Score(NEWS)in predicting clinical outcomes(28-day mortality,intensive care unit[ICU]admission,and mechanical ventilation use)for septic patients with commu...BACKGROUND:To evaluate the accuracy of National Early Warning Score(NEWS)in predicting clinical outcomes(28-day mortality,intensive care unit[ICU]admission,and mechanical ventilation use)for septic patients with community-acquired pneumonia(CAP)compared with other commonly used severity scores(CURB65,Pneumonia Severity Index[PSI],Sequential Organ Failure Assessment[SOFA],quick SOFA[qSOFA],and Mortality in Emergency Department Sepsis[MEDS])and admission lactate level.METHODS:Adult patients diagnosed with CAP admitted between January 2017 and May 2019 with admission SOFA≥2 from baseline were enrolled.Demographic characteristics were collected.The primary outcome was the 28-day mortality after admission,and the secondary outcome included ICU admission and mechanical ventilation use.Outcome prediction value of parameters above was compared using receiver operating characteristics(ROC)curves.Cox regression analyses were carried out to determine the risk factors for the 28-day mortality.Kaplan-Meier survival curves were plotted and compared using optimal cut-off values of qSOFA and NEWS.RESULTS:Among the 340 enrolled patients,90 patients were dead after a 28-day follow-up,62 patients were admitted to ICU,and 84 patients underwent mechanical ventilation.Among single predictors,NEWS achieved the largest area under the receiver operating characteristic(AUROC)curve in predicting the 28-day mortality(0.861),ICU admission(0.895),and use of mechanical ventilation(0.873).NEWS+lactate,similar to MEDS+lactate,outperformed other combinations of severity score and admission lactate in predicting the 28-day mortality(AUROC 0.866)and ICU admission(AUROC 0.905),while NEWS+lactate did not outperform other combinations in predicting mechanical ventilation(AUROC 0.886).Admission lactate only improved the predicting performance of CURB65 and qSOFA in predicting the 28-day mortality and ICU admission.CONCLUSIONS:NEWS could be a valuable predictor in septic patients with CAP in emergency departments.Admission lactate did not predict well the outcomes or improve the severity scores.A qSOFA≥2 and a NEWS≥9 were strongly associated with the 28-day mortality,ICU admission,and mechanical ventilation of septic patients with CAP in the emergency departments.展开更多
Firstly, the early warning index system of coal mine safety production was given from four aspects as per- sonnel, environment, equipment and management. Then, improvement measures which are additional momentum method...Firstly, the early warning index system of coal mine safety production was given from four aspects as per- sonnel, environment, equipment and management. Then, improvement measures which are additional momentum method, adaptive learning rate, particle swarm optimization algorithm, variable weight method and asynchronous learning factor, are used to optimize BP neural network models. Further, the models are applied to a comparative study on coal mine safety warning instance. Results show that the identification precision of MPSO-BP network model is higher than GBP and PSO-BP model, and MPSO- BP model can not only effectively reduce the possibility of the network falling into a local minimum point, but also has fast convergence and high precision, which will provide the scientific basis for the forewarnin~ management of coal mine safetv production.展开更多
In recent years, the phenomenon of a critical slowing down has demonstrated its major potential in discovering whether a complex dynamic system tends to abruptly change at critical points. This research on the Pacific...In recent years, the phenomenon of a critical slowing down has demonstrated its major potential in discovering whether a complex dynamic system tends to abruptly change at critical points. This research on the Pacific decadal oscillation(PDO) index has been made on the basis of the critical slowing down principle in order to analyze its early warning signal of abrupt change. The chaotic characteristics of the PDO index sequence at different times are determined by using the largest Lyapunov exponent(LLE). The relationship between the regional sea surface temperature(SST) background field and the early warning signal of the PDO abrupt change is further studied through calculating the variance of the SST in the PDO region and the spatial distribution of the autocorrelation coefficient, thereby providing the experimental foundation for the extensive application of the method of the critical slowing down phenomenon. Our results show that the phenomenon of critical slowing down, such as the increase of the variance and autocorrelation coefficient, will continue for six years before the abrupt change of the PDO index. This phenomenon of the critical slowing down can be regarded as one of the early warning signals of an abrupt change. Through calculating the LLE of the PDO index during different times, it is also found that the strongest chaotic characteristics of the system occurred between 1971 and 1975 in the early stages of an abrupt change(1976), and the system was at the stage of a critical slowing down, which proves the reliability of the early warning signal of abrupt change discovered in 1970 from the mechanism. In addition, the variance of the SST,along with the spatial distribution of the autocorrelation coefficient in the corresponding PDO region, also demonstrates the corresponding relationship between the change of the background field of the SST and the change of the PDO.展开更多
基金supported by the National Natural Science Foundation of China(U2033204,51976209)the Natural Science Foundation of Hefei(2022019)supported by Youth Innovative Promotion Association CAS(Y201768)。
文摘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.
基金financially supported by the National Natural Science Foundation of China (No. 52173166 and 22105083)the Project of Science and Technology Development Plan of Jilin Province (No. 20230101025JC)+1 种基金Xiaomi Young Scholar Projectthe Fundamental Research Funds for the Central Universities, JLU, and JLUSTIRT (2017TD-06)。
文摘The well-developed multifunctional wearable electronic device has fed the demand for human medicine and health monitoring in complex situations.However,the advancement of nuclear technology,especially irradiation medicine and safety inspections,has increased the exposure risk of irradiation safety workers.Traditional irradiation detectors are stiff and incompatible with the skin,and lack human health monitoring function,thus it’s vital to apply these flexible sensors for irradiation warning.Here,we report a novel composite gel device synthesized through solution processes by combining the Cs_(3)Cu_(2)I_(5):Zn nanoscintillator with the pre-patterned biocompatible gel,exhibiting a bi-functional response to motion/vibration sensing and sensitive irradiation warning.These wearable devices achieve a pressure sensitivity of up to 34 kPa^(-1)in a low-pressure range (0–3 kPa),a low limit of detection (LoD) down to 1.4 Pa,enabling health monitoring functions of pulse monitoring,finger bending,and elbow bending.Simultaneously,the device scintillates under X-ray irradiation among a wide dose rate range of 54–1167μGy_(air)s^(-1).The robust device shows no obvious signal loss after 4000 compression cycles and also excellent irradiation resistance over 50 days,broadening the path for designing and realizing new functional wearable devices.
基金supported by the National Natural Science Foundation of China(No.42127807)Natural Science Foundation of Sichuan Province of China(Project No.2023NSFSC0008)+1 种基金Uranium Geology Program of China Nuclear Geology(No.202205-6)the Sichuan Science and Technology Program(No.2021JDTD0018)。
文摘Onlineγ-spectrometry systems for inland waters,most of which extract samples in situ and in real time,are able to produce reliable activity concentration measurements for waterborne radionuclides only when they are distributed relatively uniformly and enter into a steady-state diffusion regime in the measurement chamber.To protect residents’health and ensure the safety of the living environment,better timeliness is required for this measurement method.To address this issue,this study established a mathematical model of the online waterγ-spectrometry system so that rapid warning and activity estimates can be obtained for water under non-steady-state(NSS)conditions.In addition,the detection efficiency of the detector for radionuclides during the NSS diffusion process was determined by applying the computational fluid dynamics technique in conjunction with Monte Carlo simulations.On this basis,a method was developed that allowed the online waterγ-spectrometry system to provide rapid warning and activity concentration estimates for radionuclides in water.Subsequent analysis of the NSS-mode measurements of^(40)K radioactive solutions with different activity concentrations determined the optimum warning threshold and measurement time for producing accurate activity concentration estimates for radionuclides.The experimental results show that the proposed NSS measurement method is able to give warning and yield accurate activity concentration estimates for radionuclides 55.42 and 69.42 min after the entry of a 10 Bq/L^(40)K radioactive solution into the measurement chamber,respectively.These times are much shorter than the 90 min required by the conventional measurement method.Furthermore,the NSS measurement method allows the measurement system to give rapid(within approximately 15 min)warning when the activity concentrations of some radionuclides reach their respective limits stipulated in the Guidelines for Drinking-water Quality of the WHO,suggesting that this method considerably enhances the warning capacity of in situ online waterγ-spectrometry systems.
基金supported by the Guangdong Basic and Applied Basic Research Foundation(2022A1515110296,2022A1515110432)the Shenzhen Science and Technology Program(No.20231120171032001,20231122125728001).
文摘Fire warning is vital to human life,economy and ecology.However,the development of effective warning systems faces great challenges of fast response,adjustable threshold and remote detecting.Here,we propose an intelligent self-powered remote IoT fire warning system,by employing single-walled carbon nanotube/titanium carbide thermoelectric composite films.The flexible films,prepared by a convenient solution mixing,display p-type characteristic with excellent high-temperature stability,flame retardancy and TE(power factor of 239.7±15.8μW m^(-1) K^(-2))performances.The comprehensive morphology and structural analyses shed light on the underlying mechanisms.And the assembled TE devices(TEDs)exhibit fast fire warning with adjustable warning threshold voltages(1–10 mV).Excitingly,an ultrafast fire warning response time of~0.1 s at 1 mV threshold voltage is achieved,rivaling many state-of-the-art systems.Furthermore,TE fire warning systems reveal outstanding stability after 50 repeated cycles and desired durability even undergoing 180 days of air exposure.Finally,a TED-based wireless intelligent fire warning system has been developed by coupling an amplifier,analogto-digital converter and Bluetooth module.By combining TE characteristics,high-temperature stability and flame retardancy with wireless IoT signal transmission,TE-based hybrid system developed here is promising for next-generation self-powered remote IoT fire warning applications.
基金supported by the National Key R&D Program of China(2022YFB2404300)the National Natural Science Foundation of China(NSFC Nos.52177217 and 52106244)。
文摘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.
基金supported by the Health and Medical Research Fund of the Food and Health Bureau of the Hong Kong Special Administrative Region(Project No.19201161)Seed Fund from the University of Hong Kong.
文摘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.
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.
基金provided by the State Key Research Development Program of China (No.2016YFC0801403)Key Research Development Program of Jiangsu Provence (No.BE2015040)+1 种基金National Natural Science Foundation of China (Nos.51674253,51734009 and 51604270)Natural Science Foundation of Jiangsu Province (No.BK20171191)
文摘Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powerful tool for the early warning of rock burst. In this study, an MS multi-parameter index system was established and the critical values of each index were estimated based on the normalized multi-information warning model of coal-rock dynamic failure. This index system includes bursting strain energy(BSE) index, time-space-magnitude independent information(TSMII) indices and timespace-magnitude compound information(TSMCI) indices. On the basis of this multi-parameter index system, a comprehensive analysis was conducted via introducing the R-value scoring method to calculate the weights of each index. To calibrate the multi-parameter index system and the associated comprehensive analysis, the weights of each index were first confirmed using historical MS data occurred in LW402102 of Hujiahe Coal Mine(China) over a period of four months. This calibrated comprehensive analysis of MS multi-parameter index system was then applied to pre-warn the occurrence of a subsequent rock burst incident in LW 402103. The results demonstrate that this multi-parameter index system combined with the comprehensive analysis are capable of quantitatively pre-warning rock burst risk.
基金supported in part by the Basic Public Welfare Research Program of Zhejiang Province under Grant LGF20G030001.
文摘The network is a major platform for implementing new cyber-telecom crimes.Therefore,it is important to carry out monitoring and early warning research on new cyber-telecom crime platforms,which will lay the foundation for the establishment of prevention and control systems to protect citizens’property.However,the deep-learning methods applied in the monitoring and early warning of new cyber-telecom crime platforms have some apparent drawbacks.For instance,the methods suffer from data-distribution differences and tremendous manual efforts spent on data labeling.Therefore,a monitoring and early warning method for new cyber-telecom crime platforms based on the BERT migration learning model is proposed.This method first identifies the text data and their tags,and then performs migration training based on a pre-training model.Finally,the method uses the fine-tuned model to predict and classify new cyber-telecom crimes.Experimental analysis on the crime data collected by public security organizations shows that higher classification accuracy can be achieved using the proposed method,compared with the deep-learning method.
基金supported by grants from SingHealth Talent Development Fund,Singapore(TDF/CS001/2006)InfoComm Research Cluster,Nanyang Technological University,Singapore(2006ICT09)
文摘BACKGROUND:This study was undertaken to validate the use of the modified early warning score(MEWS) as a predictor of patient mortality and intensive care unit(ICU)/ high dependency(HD)admission in an Asian population.METHODS:The MEWS was applied to a retrospective cohort of 1 024 critically ill patients presenting to a large Asian tertiary emergency department(ED) between November 2006 and December2007.Individual MEWS was calculated based on vital signs parameters on arrival at ED.Outcomes of mortality and ICU/HD admission were obtained from hospital records.The ability of the composite MEWS and its individual components to predict mortality within 30 days from ED visit was assessed.Sensitivity,specificity,positive and negative predictive values were derived and compared with values from other cohorts.A MEWS of ≥4 was chosen as the cut-off value for poor prognosis based on previous studies.RESULTS:A total of 311(30.4%) critically ill patients were presented with a MEWS ≥4.Their mean age was 61.4 years(SD 18.1) with a male to female ratio of 1.10.Of the 311 patients,53(17%)died within 30 days,64(20.6%) were admitted to ICU and 86(27.7%) were admitted to HD.The area under the receiver operating characteristic curve was 0.71 with a sensitivity of 53.0%and a specificity of 72.1%in addition to a positive predictive value(PPV) of 17.0%and a negative predictive value(NPV)of 93.4%(MEWS cut-off of ≥4) for predicting mortality.CONCLUSION:The composite MEWS did not perform well in predicting poor patient outcomes for critically ill patients presenting to an ED.
基金Sponsored by the Special Development Foundation of High School’s Doctor Subject of China (20030006007)
文摘Using the new technologies such as information technology, communication technology and electronic control technology, vehicle collision warning system（CWS） can acquire road condition, adjacent vehicle march condition as well as its dynamics performance continuously, then it can forecast the oncoming potential collision and give a warning. Based on the analysis of driver＇s driving behavior, algorithm＇s warning norms are determined. Based on warning norms adopting machine vision method, the cooperation collision warning algorithm（CWA） model with multi-input and multi-output is established which is used in supporting vehicle CWS. The CWA is tested using the actual data and the result shows that this algorithm can identify and carry out warning for vehicle collision efficiently, which has important meaning for improving the vehicle travel safety.
基金Project supported by the National Basic Research Program of China(Grant Nos.2012CB955902 and 2013CB430204)the National Natural Science Foundation of China(Grant Nos.41175067,41275074,and 41105033)the Special Scientific Research Project for Public Interest,China(Grant No.GYHY201106015)
文摘In this paper, the early warning signals of abrupt temperature change in different regions of China are investigated. Seven regions are divided on the basis of different climate temperature patterns, obtained through the rotated empirical orthogonal function, and the signal-to-noise temperature ratios for each region are then calculated. Based on the concept of critical slowing down, the temperature data that contain noise in the different regions of China are preprocessed to study the early warning signals of abrupt climate change. First, the Mann-Kendall method is used to identify the instant of abrupt climate change in the temperature data. Second, autocorrelation coefficients that can identify critical slowing down are calculated. The results show that the critical slowing down phenomenon appeared in temperature data about 5-10 years before abrupt climate change occurred, which indicates that the critical slowing down phenomenon is a possible early warning signal for abrupt climate change, and that noise has less influence on the detection results of the early warning signals. Accordingly, this demonstrates that the model is reliable in identifying the early warning signals of abrupt climate change based on detecting the critical slowing down phenomenon, which provides an experimental basis for the actual application of the method.
基金National Science and Technology Major Projects for Major New Drugs Innovation and Development(2014ZX09J14102-02A)Special Topic on Military Health Care(17bjz41)National Natural Science Foundation of China(81170249 and 30700305).
文摘Objective To examine if the variations at sea level would be able to predict subsequent susceptibility to acute altitude sickness in subjects upon a rapid ascent to high altitude.Methods One hundred and six Han nationality male individuals were recruited to this research.Dynamic electrocardiogram,treadmill exercise test,echocardiography,routine blood examination and biochemical analysis were performed when subjects at sea level and entering the plateau respectively.Then multiple regression analysis was performed to construct a multiple linear regression equation using the Lake Louise Score as dependent variable to predict the risk factors at sea level related to acute mountain sickness(AMS).Results Approximately 49.05%of the individuals developed AMS.The tricuspid annular plane systolic excursion(22.0+2.66 vs.23.2+3.19 mm,t=l.998,P=0.048)was significantly lower in the AMS group at sea level,while count of eosinophil[(0.264+0.393)×109/L vs.(0.126+0.084)×109/L,t=-2.040,P—0.045],percentage of diflerences exceeding 50 ms between adjacent normal number of intervals(PNN50,9.66%±5.40%vs.6.98%±5.66%,t=-2.229,P=0.028)and heart rate variability triangle index(57.1+16.1 vs.50.6+12.7,t=-2.271,P=0.025)were significantly higher.After acute exposure to high altitude,C-reactive protein(0.098+0.103 vs.0.062+0.045 g/L,t=-2.132,P=0.037),aspartate aminotransferase(19.7+6.7275.17,3±3.95 U/L,t=-2.231,P=0.028)and creatinine(85.1±12.9 vs.77.7±11.2 mmol/L,t=3.162,P=0.002)were significantly higher in the AMS group,while alkaline phosphatase(71.7+18.2 vs.80.6+20.2 U/L,t=2.389,P=0.019),standard deviation of normal-to-normal RR intervals(126.5+35.9 vs.143.3+36.4 ms,t—2.320,P—0.022),ejection time(276.9+50.8 vs.313.8+48.9 ms,t—3.641,P—0.001)and heart rate variability triangle index(37.1+12.9 vs.41.9+11.1,t=2.O2O,P=0.047)were significantly lower.Using the Lake Louise Score as the dependent variable,prediction equation were established to estimate AMS:Lake Louise Score=3.783+0.281Xeosinophil-0.219Xalkaline phosphatase+O.O32XPNN50.Conclusions We elucidated the differences of pl^siological variables as well as noninvasive cardiovascular indicators for subjects after high altitude exposure compared with those at sea level.We also created an acute high altitude reaction early warning equation based on the physiological variables and noninvasive cardiovascular indicators at sea level.
文摘Synchronous generators are important components of power systems and are necessary to maintain its normal and stable operation.To perform the fault diagnosis of mild inter-turn short circuit in the excitation winding of a synchronous generator,a gate recurrent unit-convolutional neural network(GRU-CNN)model whose structural parameters were determined by improved particle swarm optimization(IPSO)is proposed.The outputs of the model are the excitation current and reactive power.The total offset distance,which is the fusion of the offset distance of the excitation current and offset distance of the reactive power,was selected as the fault judgment criterion.The fusion weights of the excitation current and reactive power were determined using the anti-entropy weighting method.The fault-warning threshold and fault-warning ratio were set according to the normal total offset distance,and the fault warning time was set according to the actual situation.The fault-warning time and fault-warning ratio were used to avoid misdiagnosis.The proposed method was verified experimentally.
基金The research work was financially supported by the Australian Research Council(Nos.DE190101176,FT190100188,DP190102992,IC170100032)the National Natural Science Foundation of China(51973047)+2 种基金the Project for the Science and Technology Program of Hangzhou(20201203B136,20201203B134)the International Collaboration Programs of Guangdong Province(2020A0505100010)Open access funding provided by Shanghai Jiao Tong University
文摘Smart fire alarm sensor(FAS)materials with mechanically robust,excellent flame retardancy as well as ultra-sensitive temperature-responsive capability are highly attractive platforms for fire safety application.However,most reported FAS materials can hardly provide sensitive,continuous and reliable alarm signal output due to their undesirable temperature-responsive,flame-resistant and mechanical performances.To overcome these hurdles,herein,we utilize the multi-amino molecule,named HCPA,that can serve as triple-roles including cross-linker,fire retardant and reducing agent for decorating graphene oxide(GO)sheets and obtaining the GO/HCPA hybrid networks.Benefiting from the formation of multi-interactions in hybrid network,the optimized GO/HCPA network exhibits significant increment in mechanical strength,e.g.,tensile strength and toughness increase of~2.3and~5.7 times,respectively,compared to the control one.More importantly,based on P and N doping and promoting thermal reduction effect on GO network,the excellent flame retardancy(withstanding~1200℃flame attack),ultra-fast fire alarm response time(~0.6 s)and ultra-long alarming period(>600 s)are obtained,representing the best comprehensive performance of GO-based FAS counterparts.Furthermore,based on GO/HCPA network,the fireproof coating is constructed and applied in polymer foam and exhibited exceptional fire shielding performance.This work provides a new idea for designing and fabricating desirable FAS materials and fireproof coatings.
基金financially supported by the National Key Research and Development Program of China(No.2019YFC1805400)。
文摘As a new technical means that can detect abnormal signs of water inrush in advance and give an early warning,the automatic monitoring and early warning of water inrush in mines has been widely valued in recent years.Due to the many factors affecting water inrush and the complicated water inrush mechanism,many factors close to water inrush may have precursory abnormal changes.At present,the existing monitoring and early warning system mainly uses a few monitoring indicators such as groundwater level,water influx,and temperature,and performs water inrush early warning through the abnormal change of a single factor.However,there are relatively few multi-factor comprehensive early warning identification models.Based on the analysis of the abnormal changes of precursor factors in multiple water inrush cases,11 measurable and effective indicators including groundwater flow field,hydrochemical field and temperature field are proposed.Finally,taking Hengyuan coal mine as an example,6 indicators with long-term monitoring data sequences were selected to establish a single-index hierarchical early-warning recognition model,a multi-factor linear recognition model,and a comprehensive intelligent early-warning recognition model.The results show that the correct rate of early warning can reach 95.2%.
基金This work was financially supported by the Opening Project of National Local Joint Laboratory for Advanced Textile Processing and Clean Production(FX2022006)Guiding Project of Natural Science Foundation of Hubei province(2022CFC072)+2 种基金Guiding Project of Scientific Research Plan of Education Department of Hubei Province(B2022081)Shenghong Key Scientific Research Project of Emergency Support and Public Safety Fiber Materials and Products(2022-rw0101)Science and Technology Guidance Program of China National Textile and Apparel Council(2022002).
文摘Firefighting protective clothing is a crucial protective equipment for firefighters to minimize skin burn and ensure safety firefighting operation and rescue mission.A recent increasing concern is to develop self-powered fire warning materials that can be incorporated into the firefighting clothing to achieve active fire protection for firefighters before the protective clothing catches fire on fireground.However,it is still a challenge to facilely design and manufacture thermoelectric(TE)textile(TET)-based fire warning electronics with dynamic surface conformability and breathability.Here,we develop an alternate coaxial wet-spinning strategy to continuously produce alternating p/n-type TE aerogel fibers involving n-type Ti_(3)C_(2)T_(x)MXene and p-type MXene/SWCNT-COOH as core materials,and tough aramid nanofiber as protective shell,which simultaneously ensure the flexibility and high-efficiency TE power generation.With such alternating p/n-type TE fibers,TET-based self-powered fire warning sensors with high mechanical stability and wearability are successfully fabricated through stitching the alternating p-n segment TE fibers into aramid fabric.The results indicate that TET-based fire warning electronics containing 50 p-n pairs produce the open-circuit voltage of 7.5 mV with a power density of 119.79 nW cm-2 at a temperature difference of 300℃.The output voltage signal is then calculated as corresponding surface temperature of firefighting clothing based on a linear relationship between TE voltage and temperature.The fire alarm response time and flame-retardant properties are further displayed.Such self-powered fire warning electronics are true textiles that offer breathability and compatibility with body movement,demonstrating their potential application in firefighting clothing.
基金Capital Clinical Characteristic Application Research of Beijing Municipal Science & Technology Commission (Z171100001017057).
文摘BACKGROUND:To evaluate the accuracy of National Early Warning Score(NEWS)in predicting clinical outcomes(28-day mortality,intensive care unit[ICU]admission,and mechanical ventilation use)for septic patients with community-acquired pneumonia(CAP)compared with other commonly used severity scores(CURB65,Pneumonia Severity Index[PSI],Sequential Organ Failure Assessment[SOFA],quick SOFA[qSOFA],and Mortality in Emergency Department Sepsis[MEDS])and admission lactate level.METHODS:Adult patients diagnosed with CAP admitted between January 2017 and May 2019 with admission SOFA≥2 from baseline were enrolled.Demographic characteristics were collected.The primary outcome was the 28-day mortality after admission,and the secondary outcome included ICU admission and mechanical ventilation use.Outcome prediction value of parameters above was compared using receiver operating characteristics(ROC)curves.Cox regression analyses were carried out to determine the risk factors for the 28-day mortality.Kaplan-Meier survival curves were plotted and compared using optimal cut-off values of qSOFA and NEWS.RESULTS:Among the 340 enrolled patients,90 patients were dead after a 28-day follow-up,62 patients were admitted to ICU,and 84 patients underwent mechanical ventilation.Among single predictors,NEWS achieved the largest area under the receiver operating characteristic(AUROC)curve in predicting the 28-day mortality(0.861),ICU admission(0.895),and use of mechanical ventilation(0.873).NEWS+lactate,similar to MEDS+lactate,outperformed other combinations of severity score and admission lactate in predicting the 28-day mortality(AUROC 0.866)and ICU admission(AUROC 0.905),while NEWS+lactate did not outperform other combinations in predicting mechanical ventilation(AUROC 0.886).Admission lactate only improved the predicting performance of CURB65 and qSOFA in predicting the 28-day mortality and ICU admission.CONCLUSIONS:NEWS could be a valuable predictor in septic patients with CAP in emergency departments.Admission lactate did not predict well the outcomes or improve the severity scores.A qSOFA≥2 and a NEWS≥9 were strongly associated with the 28-day mortality,ICU admission,and mechanical ventilation of septic patients with CAP in the emergency departments.
文摘Firstly, the early warning index system of coal mine safety production was given from four aspects as per- sonnel, environment, equipment and management. Then, improvement measures which are additional momentum method, adaptive learning rate, particle swarm optimization algorithm, variable weight method and asynchronous learning factor, are used to optimize BP neural network models. Further, the models are applied to a comparative study on coal mine safety warning instance. Results show that the identification precision of MPSO-BP network model is higher than GBP and PSO-BP model, and MPSO- BP model can not only effectively reduce the possibility of the network falling into a local minimum point, but also has fast convergence and high precision, which will provide the scientific basis for the forewarnin~ management of coal mine safetv production.
基金supported by the National Natural Science Foundation of China(Grant Nos.41175067 and 41305056)the National Basic Research Program of China(Grant No.2012CB955901)+1 种基金the Special Scientific Research Project for Public Interest of China(Grant No.GYHY201506001)the Special Fund for Climate Change of China Meteorological Administration(Grant No.CCSF201525)
文摘In recent years, the phenomenon of a critical slowing down has demonstrated its major potential in discovering whether a complex dynamic system tends to abruptly change at critical points. This research on the Pacific decadal oscillation(PDO) index has been made on the basis of the critical slowing down principle in order to analyze its early warning signal of abrupt change. The chaotic characteristics of the PDO index sequence at different times are determined by using the largest Lyapunov exponent(LLE). The relationship between the regional sea surface temperature(SST) background field and the early warning signal of the PDO abrupt change is further studied through calculating the variance of the SST in the PDO region and the spatial distribution of the autocorrelation coefficient, thereby providing the experimental foundation for the extensive application of the method of the critical slowing down phenomenon. Our results show that the phenomenon of critical slowing down, such as the increase of the variance and autocorrelation coefficient, will continue for six years before the abrupt change of the PDO index. This phenomenon of the critical slowing down can be regarded as one of the early warning signals of an abrupt change. Through calculating the LLE of the PDO index during different times, it is also found that the strongest chaotic characteristics of the system occurred between 1971 and 1975 in the early stages of an abrupt change(1976), and the system was at the stage of a critical slowing down, which proves the reliability of the early warning signal of abrupt change discovered in 1970 from the mechanism. In addition, the variance of the SST,along with the spatial distribution of the autocorrelation coefficient in the corresponding PDO region, also demonstrates the corresponding relationship between the change of the background field of the SST and the change of the PDO.
