Rainstorms are one of the most important types of natural disaster in China.In order to enhance the ability to forecast rainstorms in the short term,this paper explores how to combine a back-propagation neural network...Rainstorms are one of the most important types of natural disaster in China.In order to enhance the ability to forecast rainstorms in the short term,this paper explores how to combine a back-propagation neural network(BPNN)with synoptic diagnosis for predicting rainstorms,and analyzes the hit rates of rainstorms for the above two methods using the county of Tianquan as a case study.Results showed that the traditional synoptic diagnosis method still has an important referential meaning for most rainstorm types through synoptic typing and statistics of physical quantities based on historical cases,and the threat score(TS)of rainstorms was more than 0.75.However,the accuracy for two rainstorm types influenced by low-level easterly inverted troughs was less than 40%.The BPNN method efficiently forecasted these two rainstorm types;the TS and equitable threat score(ETS)of rainstorms were 0.80 and 0.79,respectively.The TS and ETS of the hybrid model that combined the BPNN and synoptic diagnosis methods exceeded the forecast score of multi-numerical simulations over the Sichuan Basin without exception.This kind of hybrid model enhanced the forecasting accuracy of rainstorms.The findings of this study provide certain reference value for the future development of refined forecast models with local features.展开更多
[Objective] This study aimed to analyze the cause of the generation of short-term heavy precipitations in a regional heavy rainstorm in Shannxi Province. [Method] Taking a heavy rainstorm covering most parts of Shaanx...[Objective] This study aimed to analyze the cause of the generation of short-term heavy precipitations in a regional heavy rainstorm in Shannxi Province. [Method] Taking a heavy rainstorm covering most parts of Shaanxi Province in late July 2010 as an example, data of five Doppler weather radars in Shaanxi Province were employed for a detailed analysis of the evolution of the heavy rainstorm pro- cess. [Result] Besides the good large-scale weather background conditions, the de- velopment and evolution of some mesoscale and small-scale weather systems direct- ly led to short-term heavy precipitations during the heavy rainstorm process, involv- ing the intrusion of moderate IS-scale weak cold air and presence of small-scale wind shear, convergence and adverse wind area. In addition, small-scale convection echoes were arranged in lines and formed a ＂train effect＂, which would also con- tribute to the generation of short-term heavy precipitation. [Conclusion] This study provided basic information for more clear and in-depth analysis of the formation mechanism of short-term heavy precipitations.展开更多
Load forecasting is of great significance to the development of new power systems.With the advancement of smart grids,the integration and distribution of distributed renewable energy sources and power electronics devi...Load forecasting is of great significance to the development of new power systems.With the advancement of smart grids,the integration and distribution of distributed renewable energy sources and power electronics devices have made power load data increasingly complex and volatile.This places higher demands on the prediction and analysis of power loads.In order to improve the prediction accuracy of short-term power load,a CNN-BiLSTMTPA short-term power prediction model based on the Improved Whale Optimization Algorithm(IWOA)with mixed strategies was proposed.Firstly,the model combined the Convolutional Neural Network(CNN)with the Bidirectional Long Short-Term Memory Network(BiLSTM)to fully extract the spatio-temporal characteristics of the load data itself.Then,the Temporal Pattern Attention(TPA)mechanism was introduced into the CNN-BiLSTM model to automatically assign corresponding weights to the hidden states of the BiLSTM.This allowed the model to differentiate the importance of load sequences at different time intervals.At the same time,in order to solve the problem of the difficulties of selecting the parameters of the temporal model,and the poor global search ability of the whale algorithm,which is easy to fall into the local optimization,the whale algorithm(IWOA)was optimized by using the hybrid strategy of Tent chaos mapping and Levy flight strategy,so as to better search the parameters of the model.In this experiment,the real load data of a region in Zhejiang was taken as an example to analyze,and the prediction accuracy(R2)of the proposed method reached 98.83%.Compared with the prediction models such as BP,WOA-CNN-BiLSTM,SSA-CNN-BiLSTM,CNN-BiGRU-Attention,etc.,the experimental results showed that the model proposed in this study has a higher prediction accuracy.展开更多
In the early hours of August 18 in 2022,a mountain flood disaster occurred in Datong Hui and Tu Autonomous County,Xining City,Qinghai Province,resulting in 31 deaths.This typical incident of multiple casualties result...In the early hours of August 18 in 2022,a mountain flood disaster occurred in Datong Hui and Tu Autonomous County,Xining City,Qinghai Province,resulting in 31 deaths.This typical incident of multiple casualties resulting from a mountain flood disaster caused by heavy precipitation.In this paper,the mountain flood disaster was analyzed from three aspects,the distribution of the observation station network,assessment of minute-level precipitation,and quantitative precipitation estimated by Xining radar data during August 17-18,2022.It aims to identify the critical gap in comprehensive monitoring systems,and explore effective monitoring methods and estimation algorithms of minute-level quantitative precipitation.Moreover,subsequent defense countermeasures were proposed.These findings offer significant guidance for enhancing meteorological disaster prevention capabilities,strengthening the first line of defense in disaster prevention and mitigation,and supporting evidence-based decision-making for local governments and flood control departments.展开更多
In the face of disasters,a strong organizational network is the foundation for eff ectively accomplishing emergency relief tasks.In an emergency response network comprising tasks and organizations,the failure of certa...In the face of disasters,a strong organizational network is the foundation for eff ectively accomplishing emergency relief tasks.In an emergency response network comprising tasks and organizations,the failure of certain organizations may cause large systemic losses owing to internal component associations.To analyze the response system’s robustness,we developed emergency response networks based on the associations between organizations and tasks.A cascading failure model was established considering task reassignment after organizational failure,and indicators in terms of tasks and structures were identified to observe robustness.In the proposed model,we developed random,bond-based,and bridge-based organizational failure modes,and average,capacity-based,and surplus-based reassignment programs.To validate the model,simulation experiments were conducted in the context of extreme rainstorms.The results show that bridge-based failures were the most damaging to network systems,and the average reassignment program was the least eff ective.The analysis of model parameters illustrates the critical eff ectiveness of individual organizational capability in enhancing system robustness.The proposed framework and model enrich the study of emergency response networks with favorable applicability,and the results can provide theoretical references for emergency management practices.展开更多
Based on the data of daily precipitation in 11 national ground meteorological observation stations in Jining City from 1981 to 2020,the interdecadal variation,intensity,range and spatial distribution of rainstorms in ...Based on the data of daily precipitation in 11 national ground meteorological observation stations in Jining City from 1981 to 2020,the interdecadal variation,intensity,range and spatial distribution of rainstorms in Jining City were analyzed.The results show that the number of rainstorm days and the total amount of rainstorms in Jining City had significant changes among different decades.There was a continuous upward trend from the 1980s to the early 21 st century and a decrease after the early 21 st century.Rainstorms had distinct seasonal characteristics.They were mainly concentrated in summer,especially in July and August.In terms of spatial distribution,the frequency and intensity of rainstorms in the southeastern regions were significantly higher than those in the northwestern regions.The above results can provide a scientific basis for flood control and disaster reduction in Jining City.展开更多
BACKGROUND Surgery is the first choice of treatment for patients with colorectal cancer.Traditional open surgery imparts great damage to the body of the patient and can easily cause adverse stress reactions.With the c...BACKGROUND Surgery is the first choice of treatment for patients with colorectal cancer.Traditional open surgery imparts great damage to the body of the patient and can easily cause adverse stress reactions.With the continuous development of medical technology,laparoscopic minimally invasive surgery has shown great advantages for the treatment of patients with celiac disease.AIM To investigate the short-term efficacy of laparoscopic radical surgery and traditional laparotomy for the treatment of colorectal cancer,and the differences in the risk analysis of unplanned reoperation after operation.METHODS As the research subjects,this study selected 100 patients with colorectal cancer who received surgical treatment at the Yulin First Hospital from January 2018 to January 2022.Among them,50 patients who underwent laparoscopic radical resection were selected as the research group and 50 patients who underwent traditional laparotomy were selected as the control group.Data pertaining to clinical indexes,gastrointestinal hormones,nutrition indexes,the levels of inflammatory factors,quality of life,Visual Analog Scale score,and the postoperative complications of the two groups of patients before and after treatment were collected,and the therapeutic effects in the two groups were analyzed and compared.RESULTS Compared with the control group,perioperative bleeding,peristalsis recovery time,and hospital stays were significantly shorter in the research group.After surgery,the levels of gastrin(GAS)and motilin(MTL)were decreased in both groups,and the fluctuation range of GAS and MTL observed in the research group was significantly lower than that recorded in the control group.The hemoglobin(Hb)levels increased after surgery,and the level of Hb in the research group was significantly higher compared with the control group.After the operation,the expression levels of tumor necrosis factor-α,interleukin-6,and C-reactive protein and the total incidence of complications were significantly lower in the research group compared with the control group.One year after the operation,the quality of life of the two groups was greatly improved,with the quality of life in the research group being significantly better.CONCLUSION Laparoscopy was effective for colorectal surgery by reducing the occurrence of complications and inflammatory stress reaction;moreover,the quality of life of patients was significantly improved,which warrants further promotion.展开更多
Based on conventional observation data,NCEP reanalysis data and observation data of automatic stations,a rainstorm weather process occurring in Shaoguan City during December 14-17,2013 was analyzed.The results show th...Based on conventional observation data,NCEP reanalysis data and observation data of automatic stations,a rainstorm weather process occurring in Shaoguan City during December 14-17,2013 was analyzed.The results show that the main causes of the winter rainstorm in Shaoguan City were the strong southwest airflow at 500 and 700 hPa,high humidity,the influence of a low-pressure trough at 850 hPa,and the southward movement of cold air on the ground.展开更多
An extraordinary tropical cyclone-remote rainstorm with a 24-hour precipitation amount of 624.1 mm occurred in Zhengzhou,China,on 20 July 2021,during which a severe hourly precipitation amount of 201.9 mm at 1700 LST(...An extraordinary tropical cyclone-remote rainstorm with a 24-hour precipitation amount of 624.1 mm occurred in Zhengzhou,China,on 20 July 2021,during which a severe hourly precipitation amount of 201.9 mm at 1700 LST(LST=UTC+8)caused significant economic losses and casualties.Observational analysis and backward trajectory modeling showed that low-level water vapor for this extraordinary rainstorm was transported by the southeasterly jet below 900 hPa from the intensifying Typhoon In-Fa(2021)in the western North Pacific(low-level southeasterly channel).Although the southerly flow between 900 and 800 hPa brought water vapor from the developing Typhoon Cempaka in the South China Sea(low-level southerly channel),it did not converge over Zhengzhou.展开更多
Styrene-butadiene-styrene(SBS)modified asphalt(SA)has long found effective applications in road construction materials.When combined with fillers,SBS-modified asphalt has demonstrated promising resistance to fatigue c...Styrene-butadiene-styrene(SBS)modified asphalt(SA)has long found effective applications in road construction materials.When combined with fillers,SBS-modified asphalt has demonstrated promising resistance to fatigue cracking caused by temperature fluctuations and aging.In this study,molybdenum disulfide(MoS_(2))and polyphosphoric acid(PPA)were ground in naphthenic oil(NO)and subjected to mechanical activation to create PPAmodified MoS_(2),referred to as OMS-PPA.By blending various ratios of OMS-PPA with SBS-modified asphalt,composite-modified asphalts were successfully developed to enhance their overall properties.To assess the mechanical characteristics and stability of these modified asphalts,various methods were employed,including penetration factor,flow activation energy,fluorescence microscopy,and dynamic shear rheology.Additionally,the short-term aging performance was evaluated using Fourier transform infrared(FTIR)spectroscopy and nanoindentation tests.The results revealed a 3.7%decrease in the penetration-temperature coefficient for SAOMS compared to SA,while 1-SA-OMS-PPA showed an even greater reduction of 7.1%.Furthermore,after short-term aging,carboxyl group generation in SA increased by 5.93%,while SA-OMS exhibited a smaller rise of 1.36%,and 1-SA-OMS-PPA saw an increase of just 0.93%.The study also highlighted significant improvements in the hardness of these materials.The hardness change ratio for SA-OMS decreased by 43.08%,while the ratio for 1-SA-OMS-PPA saw a notable reduction of 65.16% compared to unmodified SA.These findings suggest that OMS-PPA contributed to improvements in temperature sensitivity,particle dispersibility,and resistance to shortterm aging in asphalts.The results hold significant promise for the future development of advanced asphalt-based materials with potential high-value applications in flexible pavements for highways.展开更多
BACKGROUND Colorectal polyps(CPs)are important precursor lesions of colorectal cancer,and endoscopic surgery remains the primary treatment option.However,the shortterm recurrence rate post-surgery is high,and the risk...BACKGROUND Colorectal polyps(CPs)are important precursor lesions of colorectal cancer,and endoscopic surgery remains the primary treatment option.However,the shortterm recurrence rate post-surgery is high,and the risk factors for recurrence remain unknown.AIM To comprehensively explore risk factors for short-term recurrence of CPs after endoscopic surgery and develop a nomogram prediction model.METHODS Overall,362 patients who underwent endoscopic polypectomy between January 2022 and January 2024 at Nanjing Jiangbei Hospital were included.We screened basic demographic data,clinical and polyp characteristics,surgery-related information,and independent risk factors for CPs recurrence using univariate and multivariate logistic regression analyses.The multivariate analysis results were used to construct a nomogram prediction model,internally validated using Bootstrapping,with performance evaluated using area under the curve(AUC),calibration curve,and decision curve analysis.RESULTS CP re-occurred in 166(45.86%)of the 362 patients within 1 year post-surgery.Multivariate logistic regression analysis showed that age(OR=1.04,P=0.002),alcohol consumption(OR=2.07,P=0.012),Helicobacter pylori infection(OR=2.34,P<0.001),polyp number>2(OR=1.98,P=0.005),sessile polyps(OR=2.10,P=0.006),and adenomatous pathological type(OR=3.02,P<0.001)were independent risk factors for post-surgery recurrence.The nomogram prediction model showed good discriminatory(AUC=0.73)and calibrating power,and decision curve analysis showed that the model had good clinical benefit at risk probabilities>20%.CONCLUSION We identified multiple independent risk factors for short-term recurrence after endoscopic surgery.The nomogram prediction model showed a certain degree of differentiation,calibration,and potential clinical applicability.展开更多
With the increasing penetration of renewable energy in power systems,grid structures and operational paradigms are undergoing profound transformations.When subjected to disturbances,the interaction between power elect...With the increasing penetration of renewable energy in power systems,grid structures and operational paradigms are undergoing profound transformations.When subjected to disturbances,the interaction between power electronic devices and dynamic loads introduces strongly nonlinear dynamic characteristics in grid voltage responses,posing significant threats to system security and stability.To achieve reliable short-term voltage stability assessment under large-scale renewable integration,this paper innovatively proposes a response-driven online assessment method based on energy function theory.First,energy modeling of system components is performed based on energy function theory,followed by analysis of energy interaction mechanisms during voltage instability.To address the challenge of traditional energy functions in online applications,a convolutional neural network-long short-term memory(CNNLSTM)hybrid artificial Intelligence approach is introduced.By quantifying the contribution of each energy component to voltage stability,key energy terms are identified.The measurable electrical quantities corresponding to these key energies serve as inputs,while the energy at the voltage unstable equilibrium point(UEP)obtained from offline simulations is used as both the energy threshold and the output of the artificial intelligence model,enabling the construction of an artificial intelligence model for energy threshold prediction.The measurable electrical quantities corresponding to these key energies serve as inputs,while the energy at the unstable equilibrium point(UEP)obtained from offline simulations acts as the output,enabling the construction of an artificial intelligence model for energy threshold prediction.Real-time response data are fed into the model to predict the system's instantaneous energy threshold,which is then compared with the transient energy at fault clearance to evaluate stability.Validation on both a 3-machine,10-bus system and the New England 10-machine,39-bus system confirms the method's adaptability and accuracy.The simulation results demonstrate that the proposed short-term voltage stability assessment model outperforms other methods in both accuracy and computational efficiency.展开更多
Countries worldwide are advocating for energy transition initiatives to promote the construction of low-carbon energy systems.The low voltage ride through(LVRT)characteristics of renewable energy units and commutation...Countries worldwide are advocating for energy transition initiatives to promote the construction of low-carbon energy systems.The low voltage ride through(LVRT)characteristics of renewable energy units and commutation failures in line commutated converter high voltage direct current(LCC-HVDC)systems at the receiving end leads to short-term power shortage(STPS),which differs from traditional frequency stability issues.STPS occurs during the generator’s power angle swing phase,before the governor responds,and is on a timescale that is not related to primary frequency regulation.This paper addresses these challenges by examining the impact of LVRT on voltage stability,developing a frequency response model to analyze the mechanism of frequency instability caused by STPS,deriving the impact of STPS on the maximum frequency deviation,and introducing an energy deficiency factor to assess its impact on regional frequency stability.The East China Power Grid is used as a case study,where the energy deficiency factor is calculated to validate the proposed mechanism.STPS is mainly compensated by the rotor kinetic energy of the generators in this region,with minimal impact on other regions.It is concluded that the energy deficiency factor provides an effective explanation for the spatial distribution of the impact of STPS on system frequency.展开更多
A record-breaking prolonged and extreme rainstorm occurred in Henan province,China during 18–23 July 2021.Global and regional numerical weather prediction(NWP)models consistently underpredicted both the 24-h accumula...A record-breaking prolonged and extreme rainstorm occurred in Henan province,China during 18–23 July 2021.Global and regional numerical weather prediction(NWP)models consistently underpredicted both the 24-h accumulated rainfall amount and the 1-h extreme precipitation in Zhengzhou city.This study examines the potential impacts of data assimilation(DA)of atmospheric vertical profiles based on the train-based mobile observation(MO)platforms on precipitation forecasts.The research involved assimilating virtual train-based air temperature(Ta),relative humidity(RH),U and V components of wind profile data based on the ERA5 reanalysis datasets into the Weather Research and Forecasting(WRF)model using three-dimensional variational(3DVar)method.Analysis confirms the reliability of Ta,RH,and wind speed(WS)profiles from ERA5 reanalysis datasets.The assimilation of virtual train-based moisture profiles enhanced the RH analysis field.Furthermore,the forecasts more accurately represented the coverage and intensity of the 6-hour and 24-hour accumulated precipitation,as well as areas with maximum rainfall durations exceeding 20 hours.The threat score(TS)and bias metrics for 6-h,12-h and 24-h accumulated precipitation forecasts showed marked improvement for heavy to torrential rain in Henan province,particularly in the Central and Northern regions(hereinafter referred to region CNH).The TS for 24-h accumulated precipitation forecasts at 50 and 100 mm rainfall levels increased by 0.17 and 0.18 in Henan province,and by 0.13 and 0.18 in region CNH.During the rainstorm period,water vapor content increased substantially,with enhanced moisture transport from south of Henan province to region CNH driven by southwesterly winds,accompanied by significantly strengthened updrafts.These improvement in water vapor and upward motion ultimately enhanced the forecasts of this extreme rainstorm event.展开更多
Objectives:This study aimed to clarify the short-term symptoms,duration,and influencing factors in people recovering from coronavirus disease 2019(COVID-19)after China’s dynamic zero-COVID-19 policy was implemented i...Objectives:This study aimed to clarify the short-term symptoms,duration,and influencing factors in people recovering from coronavirus disease 2019(COVID-19)after China’s dynamic zero-COVID-19 policy was implemented in December 2022.Methods:We included data from a large-scale on-line survey conducted in China between January 14 and February 1,2023.Participants were individuals of all ages.Chi-squared tests and multivariate logistic regression analyses were performed to identify factors associated with different symptoms.Results:Overall,21,012 patients from seven regions of China were included in this study(female:71.22%).For most patients,the period from symptom onset to a negative nucleic acid test result was≤10 days(72.33%).The distribution of symptoms varied at different times,with respiratory(1-4 weeks)and psychocardiology(5-8 weeks)symptoms being the most common.Multivariate analysis identified male sex,no comorbidity,and living in northeast and northwest China(compared with central China)as independent factors associated with a lower risk of symptoms,while age(41-60 years)was a possible risk factor(compared with 18-40 years).Conclusions:Short-term respiratory and psychocardiology symptoms were the most common after COVID-19 recovery.Sex,age,geographical region,and comorbidities were potential influencing factors for the development of short-term symptoms.展开更多
This paper deeply explores the application strategies of short-term cost curves in the field of economics.Firstly,it elaborates on the basic theories and constituent elements of short-term cost curves.By drawing and a...This paper deeply explores the application strategies of short-term cost curves in the field of economics.Firstly,it elaborates on the basic theories and constituent elements of short-term cost curves.By drawing and analyzing the shortterm cost curve graphs,it presents the internal relationship between costs and output.Then,it focuses on researching its application strategies in multiple aspects such as enterprise production decisions,market pricing,and industry competition analysis.展开更多
In this study,a machine learning-based predictive model was developed for the Musa petti Wind Farm in Sri Lanka to address the need for localized forecasting solutions.Using data on wind speed,air temperature,nacelle ...In this study,a machine learning-based predictive model was developed for the Musa petti Wind Farm in Sri Lanka to address the need for localized forecasting solutions.Using data on wind speed,air temperature,nacelle position,and actual power,lagged features were generated to capture temporal dependencies.Among 24 evaluated models,the ensemble bagging approach achieved the best performance,with R^(2) values of 0.89 at 0 min and 0.75 at 60 min.Shapley Additive exPlanations(SHAP)analysis revealed that while wind speed is the primary driver for short-term predictions,air temperature and nacelle position become more influential at longer forecasting horizons.These findings underscore the reliability of short-term predictions and the potential benefits of integrating hybrid AI and probabilistic models for extended forecasts.Our work contributes a robust and explainable framework to support Sri Lanka’s renewable energy transition,and future research will focus on real-time deployment and uncertainty quantification.展开更多
Solar flares are violent solar outbursts which have a great influence on the space environment surrounding Earth,potentially causing disruption of the ionosphere and interference with the geomagnetic field,thus causin...Solar flares are violent solar outbursts which have a great influence on the space environment surrounding Earth,potentially causing disruption of the ionosphere and interference with the geomagnetic field,thus causing magnetic storms.Consequently,it is very important to accurately predict the time period of solar flares.This paper proposes a flare prediction model,based on physical images of active solar regions.We employ X-ray flux curves recorded directly by the Geostationary Operational Environmental Satellite,used as input data for the model,allowing us to largely avoid the influence of accidental errors,effectively improving the model prediction efficiency.A model based on the X-ray flux curve can predict whether there will be a flare event within 24 hours.The reverse can also be verified by the peak of the X-ray flux curve to see if a flare has occurred within the past 24 hours.The True Positive Rate and False Positive Rate of the prediction model,based on physical images of active regions are 0.6070 and 0.2410 respectively,and the accuracy and True Skill Statistics are 0.7590 and 0.5556.Our model can effectively improve prediction efficiency compared with models based on the physical parameters of active regions or magnetic field records,providing a simple method for solar flare prediction.展开更多
Background Lip reading uses lip images for visual speech recognition.Deep-learning-based lip reading has greatly improved performance in current datasets;however,most existing research ignores the significance of shor...Background Lip reading uses lip images for visual speech recognition.Deep-learning-based lip reading has greatly improved performance in current datasets;however,most existing research ignores the significance of short-term temporal dependencies of lip-shape variations between adjacent frames,which leaves space for further improvement in feature extraction.Methods This article presents a spatiotemporal feature fusion network(STDNet)that compensates for the deficiencies of current lip-reading approaches in short-term temporal dependency modeling.Specifically,to distinguish more similar and intricate content,STDNet adds a temporal feature extraction branch based on a 3D-CNN,which enhances the learning of dynamic lip movements in adjacent frames while not affecting spatial feature extraction.In particular,we designed a local–temporal block,which aggregates interframe differences,strengthening the relationship between various local lip regions through multiscale convolution.We incorporated the squeeze-and-excitation mechanism into the Global-Temporal Block,which processes a single frame as an independent unitto learn temporal variations across the entire lip region more effectively.Furthermore,attention pooling was introduced to highlight meaningful frames containing key semantic information for the target word.Results Experimental results demonstrated STDNet's superior performance on the LRW and LRW-1000,achieving word-level recognition accuracies of 90.2% and 53.56%,respectively.Extensive ablation experiments verified the rationality and effectiveness of its modules.Conclusions The proposed model effectively addresses short-term temporal dependency limitations in lip reading,and improves the temporal robustness of the model against variable-length sequences.These advancements validate the importance of explicit short-term dynamics modeling for practical lip-reading systems.展开更多
BACKGROUND Elsberg syndrome is a type of postinfectious lumbosacral radiculitis typically tri-ggered by neurotropic viruses and manifests as bladder/bowel dysfunction,saddle sensory disturbances(including hypoesthesia...BACKGROUND Elsberg syndrome is a type of postinfectious lumbosacral radiculitis typically tri-ggered by neurotropic viruses and manifests as bladder/bowel dysfunction,saddle sensory disturbances(including hypoesthesia,hyperesthesia,or dyse-sthesia),and variable neurological deficits.Typically self-limiting,it often res-ponds to antiviral and neurotropic therapies.However,in patients with comorbi-dities that confer susceptibility to peripheral neuropathy(e.g.,diabetes mellitus),timely escalation to neuromodulation strategies,such as spinal cord stimulation,may be warranted to optimize functional outcomes when conservative measures are inadequate.CASE SUMMARY A 60-year-old male with diabetes mellitus presented with severe bladder and bowel dysfunction persisting for more than two months,followed by left gluteal and perianal(saddle area)herpes zoster eruption that was accompanied by significant neuropathic pain.Following a suboptimal response to conservative therapy,the patient underwent implantation of a short-term spinal cord stimu-lation.Following a 10-day trial of continuous tonic stimulation,the percutaneous electrode lead was removed.The patients experienced no surgical complications,and after the procedure,the patient achieved complete restoration of bladder and bowel function and significant pain alleviation.Two-month follow-up confirmed sustained full recovery.CONCLUSION Early implementation of short-term spinal cord stimulation represents a pro-mising therapeutic approach for promoting neurological recovery in patients with Elsberg syndrome refractory to conservative management,especially those with predisposing comorbidities such as diabetes mellitus.展开更多
基金supported by the National Key Research and Development Program on Monitoring,Early Warning and Prevention of Major Natural Disasters [grant number 2018YFC1506006]the National Natural Science Foundation of China [grant numbers 41805054 and U20A2097]。
文摘Rainstorms are one of the most important types of natural disaster in China.In order to enhance the ability to forecast rainstorms in the short term,this paper explores how to combine a back-propagation neural network(BPNN)with synoptic diagnosis for predicting rainstorms,and analyzes the hit rates of rainstorms for the above two methods using the county of Tianquan as a case study.Results showed that the traditional synoptic diagnosis method still has an important referential meaning for most rainstorm types through synoptic typing and statistics of physical quantities based on historical cases,and the threat score(TS)of rainstorms was more than 0.75.However,the accuracy for two rainstorm types influenced by low-level easterly inverted troughs was less than 40%.The BPNN method efficiently forecasted these two rainstorm types;the TS and equitable threat score(ETS)of rainstorms were 0.80 and 0.79,respectively.The TS and ETS of the hybrid model that combined the BPNN and synoptic diagnosis methods exceeded the forecast score of multi-numerical simulations over the Sichuan Basin without exception.This kind of hybrid model enhanced the forecasting accuracy of rainstorms.The findings of this study provide certain reference value for the future development of refined forecast models with local features.
基金Supported by Special Fund for National Weather Service Forecaster of China (CMAYBY2011-050)~~
文摘[Objective] This study aimed to analyze the cause of the generation of short-term heavy precipitations in a regional heavy rainstorm in Shannxi Province. [Method] Taking a heavy rainstorm covering most parts of Shaanxi Province in late July 2010 as an example, data of five Doppler weather radars in Shaanxi Province were employed for a detailed analysis of the evolution of the heavy rainstorm pro- cess. [Result] Besides the good large-scale weather background conditions, the de- velopment and evolution of some mesoscale and small-scale weather systems direct- ly led to short-term heavy precipitations during the heavy rainstorm process, involv- ing the intrusion of moderate IS-scale weak cold air and presence of small-scale wind shear, convergence and adverse wind area. In addition, small-scale convection echoes were arranged in lines and formed a ＂train effect＂, which would also con- tribute to the generation of short-term heavy precipitation. [Conclusion] This study provided basic information for more clear and in-depth analysis of the formation mechanism of short-term heavy precipitations.
文摘Load forecasting is of great significance to the development of new power systems.With the advancement of smart grids,the integration and distribution of distributed renewable energy sources and power electronics devices have made power load data increasingly complex and volatile.This places higher demands on the prediction and analysis of power loads.In order to improve the prediction accuracy of short-term power load,a CNN-BiLSTMTPA short-term power prediction model based on the Improved Whale Optimization Algorithm(IWOA)with mixed strategies was proposed.Firstly,the model combined the Convolutional Neural Network(CNN)with the Bidirectional Long Short-Term Memory Network(BiLSTM)to fully extract the spatio-temporal characteristics of the load data itself.Then,the Temporal Pattern Attention(TPA)mechanism was introduced into the CNN-BiLSTM model to automatically assign corresponding weights to the hidden states of the BiLSTM.This allowed the model to differentiate the importance of load sequences at different time intervals.At the same time,in order to solve the problem of the difficulties of selecting the parameters of the temporal model,and the poor global search ability of the whale algorithm,which is easy to fall into the local optimization,the whale algorithm(IWOA)was optimized by using the hybrid strategy of Tent chaos mapping and Levy flight strategy,so as to better search the parameters of the model.In this experiment,the real load data of a region in Zhejiang was taken as an example to analyze,and the prediction accuracy(R2)of the proposed method reached 98.83%.Compared with the prediction models such as BP,WOA-CNN-BiLSTM,SSA-CNN-BiLSTM,CNN-BiGRU-Attention,etc.,the experimental results showed that the model proposed in this study has a higher prediction accuracy.
基金the Key Research and Development and Transformation Plan Project of Science and Technology Department of Qinghai Province in 2023(2023-SF-111).
文摘In the early hours of August 18 in 2022,a mountain flood disaster occurred in Datong Hui and Tu Autonomous County,Xining City,Qinghai Province,resulting in 31 deaths.This typical incident of multiple casualties resulting from a mountain flood disaster caused by heavy precipitation.In this paper,the mountain flood disaster was analyzed from three aspects,the distribution of the observation station network,assessment of minute-level precipitation,and quantitative precipitation estimated by Xining radar data during August 17-18,2022.It aims to identify the critical gap in comprehensive monitoring systems,and explore effective monitoring methods and estimation algorithms of minute-level quantitative precipitation.Moreover,subsequent defense countermeasures were proposed.These findings offer significant guidance for enhancing meteorological disaster prevention capabilities,strengthening the first line of defense in disaster prevention and mitigation,and supporting evidence-based decision-making for local governments and flood control departments.
基金supported by the National Natural Science Foundation of China(Grant Nos.72504070,72404024)。
文摘In the face of disasters,a strong organizational network is the foundation for eff ectively accomplishing emergency relief tasks.In an emergency response network comprising tasks and organizations,the failure of certain organizations may cause large systemic losses owing to internal component associations.To analyze the response system’s robustness,we developed emergency response networks based on the associations between organizations and tasks.A cascading failure model was established considering task reassignment after organizational failure,and indicators in terms of tasks and structures were identified to observe robustness.In the proposed model,we developed random,bond-based,and bridge-based organizational failure modes,and average,capacity-based,and surplus-based reassignment programs.To validate the model,simulation experiments were conducted in the context of extreme rainstorms.The results show that bridge-based failures were the most damaging to network systems,and the average reassignment program was the least eff ective.The analysis of model parameters illustrates the critical eff ectiveness of individual organizational capability in enhancing system robustness.The proposed framework and model enrich the study of emergency response networks with favorable applicability,and the results can provide theoretical references for emergency management practices.
基金the Project of Jining Meteorological Bureau(2023JNZL09).
文摘Based on the data of daily precipitation in 11 national ground meteorological observation stations in Jining City from 1981 to 2020,the interdecadal variation,intensity,range and spatial distribution of rainstorms in Jining City were analyzed.The results show that the number of rainstorm days and the total amount of rainstorms in Jining City had significant changes among different decades.There was a continuous upward trend from the 1980s to the early 21 st century and a decrease after the early 21 st century.Rainstorms had distinct seasonal characteristics.They were mainly concentrated in summer,especially in July and August.In terms of spatial distribution,the frequency and intensity of rainstorms in the southeastern regions were significantly higher than those in the northwestern regions.The above results can provide a scientific basis for flood control and disaster reduction in Jining City.
文摘BACKGROUND Surgery is the first choice of treatment for patients with colorectal cancer.Traditional open surgery imparts great damage to the body of the patient and can easily cause adverse stress reactions.With the continuous development of medical technology,laparoscopic minimally invasive surgery has shown great advantages for the treatment of patients with celiac disease.AIM To investigate the short-term efficacy of laparoscopic radical surgery and traditional laparotomy for the treatment of colorectal cancer,and the differences in the risk analysis of unplanned reoperation after operation.METHODS As the research subjects,this study selected 100 patients with colorectal cancer who received surgical treatment at the Yulin First Hospital from January 2018 to January 2022.Among them,50 patients who underwent laparoscopic radical resection were selected as the research group and 50 patients who underwent traditional laparotomy were selected as the control group.Data pertaining to clinical indexes,gastrointestinal hormones,nutrition indexes,the levels of inflammatory factors,quality of life,Visual Analog Scale score,and the postoperative complications of the two groups of patients before and after treatment were collected,and the therapeutic effects in the two groups were analyzed and compared.RESULTS Compared with the control group,perioperative bleeding,peristalsis recovery time,and hospital stays were significantly shorter in the research group.After surgery,the levels of gastrin(GAS)and motilin(MTL)were decreased in both groups,and the fluctuation range of GAS and MTL observed in the research group was significantly lower than that recorded in the control group.The hemoglobin(Hb)levels increased after surgery,and the level of Hb in the research group was significantly higher compared with the control group.After the operation,the expression levels of tumor necrosis factor-α,interleukin-6,and C-reactive protein and the total incidence of complications were significantly lower in the research group compared with the control group.One year after the operation,the quality of life of the two groups was greatly improved,with the quality of life in the research group being significantly better.CONCLUSION Laparoscopy was effective for colorectal surgery by reducing the occurrence of complications and inflammatory stress reaction;moreover,the quality of life of patients was significantly improved,which warrants further promotion.
文摘Based on conventional observation data,NCEP reanalysis data and observation data of automatic stations,a rainstorm weather process occurring in Shaoguan City during December 14-17,2013 was analyzed.The results show that the main causes of the winter rainstorm in Shaoguan City were the strong southwest airflow at 500 and 700 hPa,high humidity,the influence of a low-pressure trough at 850 hPa,and the southward movement of cold air on the ground.
基金supported by the National Natural Science Foundation of China(Grant No.42305007).
文摘An extraordinary tropical cyclone-remote rainstorm with a 24-hour precipitation amount of 624.1 mm occurred in Zhengzhou,China,on 20 July 2021,during which a severe hourly precipitation amount of 201.9 mm at 1700 LST(LST=UTC+8)caused significant economic losses and casualties.Observational analysis and backward trajectory modeling showed that low-level water vapor for this extraordinary rainstorm was transported by the southeasterly jet below 900 hPa from the intensifying Typhoon In-Fa(2021)in the western North Pacific(low-level southeasterly channel).Although the southerly flow between 900 and 800 hPa brought water vapor from the developing Typhoon Cempaka in the South China Sea(low-level southerly channel),it did not converge over Zhengzhou.
基金financially supported by the Key Research and Development Program of Hubei Province(Nos.2022BCA077 and 2022BCA082).
文摘Styrene-butadiene-styrene(SBS)modified asphalt(SA)has long found effective applications in road construction materials.When combined with fillers,SBS-modified asphalt has demonstrated promising resistance to fatigue cracking caused by temperature fluctuations and aging.In this study,molybdenum disulfide(MoS_(2))and polyphosphoric acid(PPA)were ground in naphthenic oil(NO)and subjected to mechanical activation to create PPAmodified MoS_(2),referred to as OMS-PPA.By blending various ratios of OMS-PPA with SBS-modified asphalt,composite-modified asphalts were successfully developed to enhance their overall properties.To assess the mechanical characteristics and stability of these modified asphalts,various methods were employed,including penetration factor,flow activation energy,fluorescence microscopy,and dynamic shear rheology.Additionally,the short-term aging performance was evaluated using Fourier transform infrared(FTIR)spectroscopy and nanoindentation tests.The results revealed a 3.7%decrease in the penetration-temperature coefficient for SAOMS compared to SA,while 1-SA-OMS-PPA showed an even greater reduction of 7.1%.Furthermore,after short-term aging,carboxyl group generation in SA increased by 5.93%,while SA-OMS exhibited a smaller rise of 1.36%,and 1-SA-OMS-PPA saw an increase of just 0.93%.The study also highlighted significant improvements in the hardness of these materials.The hardness change ratio for SA-OMS decreased by 43.08%,while the ratio for 1-SA-OMS-PPA saw a notable reduction of 65.16% compared to unmodified SA.These findings suggest that OMS-PPA contributed to improvements in temperature sensitivity,particle dispersibility,and resistance to shortterm aging in asphalts.The results hold significant promise for the future development of advanced asphalt-based materials with potential high-value applications in flexible pavements for highways.
文摘BACKGROUND Colorectal polyps(CPs)are important precursor lesions of colorectal cancer,and endoscopic surgery remains the primary treatment option.However,the shortterm recurrence rate post-surgery is high,and the risk factors for recurrence remain unknown.AIM To comprehensively explore risk factors for short-term recurrence of CPs after endoscopic surgery and develop a nomogram prediction model.METHODS Overall,362 patients who underwent endoscopic polypectomy between January 2022 and January 2024 at Nanjing Jiangbei Hospital were included.We screened basic demographic data,clinical and polyp characteristics,surgery-related information,and independent risk factors for CPs recurrence using univariate and multivariate logistic regression analyses.The multivariate analysis results were used to construct a nomogram prediction model,internally validated using Bootstrapping,with performance evaluated using area under the curve(AUC),calibration curve,and decision curve analysis.RESULTS CP re-occurred in 166(45.86%)of the 362 patients within 1 year post-surgery.Multivariate logistic regression analysis showed that age(OR=1.04,P=0.002),alcohol consumption(OR=2.07,P=0.012),Helicobacter pylori infection(OR=2.34,P<0.001),polyp number>2(OR=1.98,P=0.005),sessile polyps(OR=2.10,P=0.006),and adenomatous pathological type(OR=3.02,P<0.001)were independent risk factors for post-surgery recurrence.The nomogram prediction model showed good discriminatory(AUC=0.73)and calibrating power,and decision curve analysis showed that the model had good clinical benefit at risk probabilities>20%.CONCLUSION We identified multiple independent risk factors for short-term recurrence after endoscopic surgery.The nomogram prediction model showed a certain degree of differentiation,calibration,and potential clinical applicability.
基金the State Grid Shanxi Electric Power Company Science and Technology Project“Smart distribution network with a high proportion of distributed wind storage adaptability assessment and improvement strategy research”(520530230024).
文摘With the increasing penetration of renewable energy in power systems,grid structures and operational paradigms are undergoing profound transformations.When subjected to disturbances,the interaction between power electronic devices and dynamic loads introduces strongly nonlinear dynamic characteristics in grid voltage responses,posing significant threats to system security and stability.To achieve reliable short-term voltage stability assessment under large-scale renewable integration,this paper innovatively proposes a response-driven online assessment method based on energy function theory.First,energy modeling of system components is performed based on energy function theory,followed by analysis of energy interaction mechanisms during voltage instability.To address the challenge of traditional energy functions in online applications,a convolutional neural network-long short-term memory(CNNLSTM)hybrid artificial Intelligence approach is introduced.By quantifying the contribution of each energy component to voltage stability,key energy terms are identified.The measurable electrical quantities corresponding to these key energies serve as inputs,while the energy at the voltage unstable equilibrium point(UEP)obtained from offline simulations is used as both the energy threshold and the output of the artificial intelligence model,enabling the construction of an artificial intelligence model for energy threshold prediction.The measurable electrical quantities corresponding to these key energies serve as inputs,while the energy at the unstable equilibrium point(UEP)obtained from offline simulations acts as the output,enabling the construction of an artificial intelligence model for energy threshold prediction.Real-time response data are fed into the model to predict the system's instantaneous energy threshold,which is then compared with the transient energy at fault clearance to evaluate stability.Validation on both a 3-machine,10-bus system and the New England 10-machine,39-bus system confirms the method's adaptability and accuracy.The simulation results demonstrate that the proposed short-term voltage stability assessment model outperforms other methods in both accuracy and computational efficiency.
基金funded by the Technology Project of State Grid Corporation of China(Research on Safety and Stability Evaluation and Optimization Enhancement Technology of Flexible Ultra High Voltage Multiterminal DC System Adapting to the Background of“Sand and Gobi Deserts”),grant number J2024003。
文摘Countries worldwide are advocating for energy transition initiatives to promote the construction of low-carbon energy systems.The low voltage ride through(LVRT)characteristics of renewable energy units and commutation failures in line commutated converter high voltage direct current(LCC-HVDC)systems at the receiving end leads to short-term power shortage(STPS),which differs from traditional frequency stability issues.STPS occurs during the generator’s power angle swing phase,before the governor responds,and is on a timescale that is not related to primary frequency regulation.This paper addresses these challenges by examining the impact of LVRT on voltage stability,developing a frequency response model to analyze the mechanism of frequency instability caused by STPS,deriving the impact of STPS on the maximum frequency deviation,and introducing an energy deficiency factor to assess its impact on regional frequency stability.The East China Power Grid is used as a case study,where the energy deficiency factor is calculated to validate the proposed mechanism.STPS is mainly compensated by the rotor kinetic energy of the generators in this region,with minimal impact on other regions.It is concluded that the energy deficiency factor provides an effective explanation for the spatial distribution of the impact of STPS on system frequency.
基金R&D major projects from China State Railway Group Co.,Ltd.(K2022G039)Tibet Autonomous Region Science and Technology Program Project(XZ202402ZD0006-06)+1 种基金Open bidding project for selecting the best candidates from China Meteorological Administration(CMAJBGS202303)The Second Tibetan Plateau Scientific Expedition and Research(STEP)program(2019QZKK0105)。
文摘A record-breaking prolonged and extreme rainstorm occurred in Henan province,China during 18–23 July 2021.Global and regional numerical weather prediction(NWP)models consistently underpredicted both the 24-h accumulated rainfall amount and the 1-h extreme precipitation in Zhengzhou city.This study examines the potential impacts of data assimilation(DA)of atmospheric vertical profiles based on the train-based mobile observation(MO)platforms on precipitation forecasts.The research involved assimilating virtual train-based air temperature(Ta),relative humidity(RH),U and V components of wind profile data based on the ERA5 reanalysis datasets into the Weather Research and Forecasting(WRF)model using three-dimensional variational(3DVar)method.Analysis confirms the reliability of Ta,RH,and wind speed(WS)profiles from ERA5 reanalysis datasets.The assimilation of virtual train-based moisture profiles enhanced the RH analysis field.Furthermore,the forecasts more accurately represented the coverage and intensity of the 6-hour and 24-hour accumulated precipitation,as well as areas with maximum rainfall durations exceeding 20 hours.The threat score(TS)and bias metrics for 6-h,12-h and 24-h accumulated precipitation forecasts showed marked improvement for heavy to torrential rain in Henan province,particularly in the Central and Northern regions(hereinafter referred to region CNH).The TS for 24-h accumulated precipitation forecasts at 50 and 100 mm rainfall levels increased by 0.17 and 0.18 in Henan province,and by 0.13 and 0.18 in region CNH.During the rainstorm period,water vapor content increased substantially,with enhanced moisture transport from south of Henan province to region CNH driven by southwesterly winds,accompanied by significantly strengthened updrafts.These improvement in water vapor and upward motion ultimately enhanced the forecasts of this extreme rainstorm event.
基金funded by the Young Scientists Fund of the National Natural Science Foundation of China under 82305433,82305437.
文摘Objectives:This study aimed to clarify the short-term symptoms,duration,and influencing factors in people recovering from coronavirus disease 2019(COVID-19)after China’s dynamic zero-COVID-19 policy was implemented in December 2022.Methods:We included data from a large-scale on-line survey conducted in China between January 14 and February 1,2023.Participants were individuals of all ages.Chi-squared tests and multivariate logistic regression analyses were performed to identify factors associated with different symptoms.Results:Overall,21,012 patients from seven regions of China were included in this study(female:71.22%).For most patients,the period from symptom onset to a negative nucleic acid test result was≤10 days(72.33%).The distribution of symptoms varied at different times,with respiratory(1-4 weeks)and psychocardiology(5-8 weeks)symptoms being the most common.Multivariate analysis identified male sex,no comorbidity,and living in northeast and northwest China(compared with central China)as independent factors associated with a lower risk of symptoms,while age(41-60 years)was a possible risk factor(compared with 18-40 years).Conclusions:Short-term respiratory and psychocardiology symptoms were the most common after COVID-19 recovery.Sex,age,geographical region,and comorbidities were potential influencing factors for the development of short-term symptoms.
文摘This paper deeply explores the application strategies of short-term cost curves in the field of economics.Firstly,it elaborates on the basic theories and constituent elements of short-term cost curves.By drawing and analyzing the shortterm cost curve graphs,it presents the internal relationship between costs and output.Then,it focuses on researching its application strategies in multiple aspects such as enterprise production decisions,market pricing,and industry competition analysis.
文摘In this study,a machine learning-based predictive model was developed for the Musa petti Wind Farm in Sri Lanka to address the need for localized forecasting solutions.Using data on wind speed,air temperature,nacelle position,and actual power,lagged features were generated to capture temporal dependencies.Among 24 evaluated models,the ensemble bagging approach achieved the best performance,with R^(2) values of 0.89 at 0 min and 0.75 at 60 min.Shapley Additive exPlanations(SHAP)analysis revealed that while wind speed is the primary driver for short-term predictions,air temperature and nacelle position become more influential at longer forecasting horizons.These findings underscore the reliability of short-term predictions and the potential benefits of integrating hybrid AI and probabilistic models for extended forecasts.Our work contributes a robust and explainable framework to support Sri Lanka’s renewable energy transition,and future research will focus on real-time deployment and uncertainty quantification.
基金partially supported by the National Key R&D Program of China (2022YFE0133700)the National Natural Science Foundation of China(12273007)+4 种基金the Guizhou Provincial Excellent Young Science and Technology Talent Program (YQK[2023]006)the National SKA Program of China (2020SKA0110300)the National Natural Science Foundation of China(11963003)the Guizhou Provincial Basic Research Program (Natural Science)(ZK[2022]143)the Cultivation project of Guizhou University ([2020]76).
文摘Solar flares are violent solar outbursts which have a great influence on the space environment surrounding Earth,potentially causing disruption of the ionosphere and interference with the geomagnetic field,thus causing magnetic storms.Consequently,it is very important to accurately predict the time period of solar flares.This paper proposes a flare prediction model,based on physical images of active solar regions.We employ X-ray flux curves recorded directly by the Geostationary Operational Environmental Satellite,used as input data for the model,allowing us to largely avoid the influence of accidental errors,effectively improving the model prediction efficiency.A model based on the X-ray flux curve can predict whether there will be a flare event within 24 hours.The reverse can also be verified by the peak of the X-ray flux curve to see if a flare has occurred within the past 24 hours.The True Positive Rate and False Positive Rate of the prediction model,based on physical images of active regions are 0.6070 and 0.2410 respectively,and the accuracy and True Skill Statistics are 0.7590 and 0.5556.Our model can effectively improve prediction efficiency compared with models based on the physical parameters of active regions or magnetic field records,providing a simple method for solar flare prediction.
基金Supported by the National Key Research and Development Program of China(2023YFC3306201)the National Natural Science Foundation of China(61772125)the Fundamental Research Funds for the Central Universities(N2317004).
文摘Background Lip reading uses lip images for visual speech recognition.Deep-learning-based lip reading has greatly improved performance in current datasets;however,most existing research ignores the significance of short-term temporal dependencies of lip-shape variations between adjacent frames,which leaves space for further improvement in feature extraction.Methods This article presents a spatiotemporal feature fusion network(STDNet)that compensates for the deficiencies of current lip-reading approaches in short-term temporal dependency modeling.Specifically,to distinguish more similar and intricate content,STDNet adds a temporal feature extraction branch based on a 3D-CNN,which enhances the learning of dynamic lip movements in adjacent frames while not affecting spatial feature extraction.In particular,we designed a local–temporal block,which aggregates interframe differences,strengthening the relationship between various local lip regions through multiscale convolution.We incorporated the squeeze-and-excitation mechanism into the Global-Temporal Block,which processes a single frame as an independent unitto learn temporal variations across the entire lip region more effectively.Furthermore,attention pooling was introduced to highlight meaningful frames containing key semantic information for the target word.Results Experimental results demonstrated STDNet's superior performance on the LRW and LRW-1000,achieving word-level recognition accuracies of 90.2% and 53.56%,respectively.Extensive ablation experiments verified the rationality and effectiveness of its modules.Conclusions The proposed model effectively addresses short-term temporal dependency limitations in lip reading,and improves the temporal robustness of the model against variable-length sequences.These advancements validate the importance of explicit short-term dynamics modeling for practical lip-reading systems.
基金Supported by the Science and Technology Department of Sichuan Province,No.2023YFS0255。
文摘BACKGROUND Elsberg syndrome is a type of postinfectious lumbosacral radiculitis typically tri-ggered by neurotropic viruses and manifests as bladder/bowel dysfunction,saddle sensory disturbances(including hypoesthesia,hyperesthesia,or dyse-sthesia),and variable neurological deficits.Typically self-limiting,it often res-ponds to antiviral and neurotropic therapies.However,in patients with comorbi-dities that confer susceptibility to peripheral neuropathy(e.g.,diabetes mellitus),timely escalation to neuromodulation strategies,such as spinal cord stimulation,may be warranted to optimize functional outcomes when conservative measures are inadequate.CASE SUMMARY A 60-year-old male with diabetes mellitus presented with severe bladder and bowel dysfunction persisting for more than two months,followed by left gluteal and perianal(saddle area)herpes zoster eruption that was accompanied by significant neuropathic pain.Following a suboptimal response to conservative therapy,the patient underwent implantation of a short-term spinal cord stimu-lation.Following a 10-day trial of continuous tonic stimulation,the percutaneous electrode lead was removed.The patients experienced no surgical complications,and after the procedure,the patient achieved complete restoration of bladder and bowel function and significant pain alleviation.Two-month follow-up confirmed sustained full recovery.CONCLUSION Early implementation of short-term spinal cord stimulation represents a pro-mising therapeutic approach for promoting neurological recovery in patients with Elsberg syndrome refractory to conservative management,especially those with predisposing comorbidities such as diabetes mellitus.
