Objective: To explore the methodology of the evidence-based expert consensus formulation process of traditional Chinese medicine(TCM) nursing taking stroke as an example.Methods: First, preliminary and comprehensive p...Objective: To explore the methodology of the evidence-based expert consensus formulation process of traditional Chinese medicine(TCM) nursing taking stroke as an example.Methods: First, preliminary and comprehensive presentation of all stroke-related symptoms and corresponding TCM nursing techniques involved were revealed through bibliometric analysis. Then, selection of stroke symptoms and TCM nursing techniques for inclusion in the consensus was performed using an expert consultation method. Next, we determined the search strategy for a precise evidence search;conducted an evaluation of evidence quality and the grade of the evidence;and completed evidence extraction, evidence analysis, and evidence synthesis based on the included symptoms and TCM nursing techniques. The Delphi method was then applied to determine the strength of each recommendation and the choice of nursing care points by referring to the Grading of Recommendations, Assessment, Development, and Evaluations grid. Finally, we conducted an external expert validation of the Delphi results to form an expert consensus guideline.Results: Through the bibliometric analysis, 22 stroke symptoms and 18 TCM nursing techniques were identified in the literature. Then, after expert consultation, 22 symptoms and 111 pairs of symptoms combined with TCM nursing techniques were selected for the evidence search. Evidence integration yielded 10 stroke symptoms corresponding to 29 bodies of evidence;these 10 symptoms were retained through the Delphi consultation, and recommendation strength results for 26 recommendations were obtained. A total of 9 symptoms were further retained for expert external validation to form 24 recommendations, with a recommendation process score range of 7.64-9.99 points and a more scientific and standardized recommendation-formation process.Conclusion: Owing to the current limited conditions of evidence-based resources for TCM nursing, the present consensus-building process represents only a preliminary exploration of an evidence-based expert consensus for TCM nursing to provide a reference for a more scientific and standardized methodology.展开更多
BACKGROUND Hypernatremia represents a significant electrolyte imbalance associated with numerous adverse outcomes,particularly in cases of intensive care unit(ICU)-acquired hypernatremia(IAH).Nevertheless,its relevanc...BACKGROUND Hypernatremia represents a significant electrolyte imbalance associated with numerous adverse outcomes,particularly in cases of intensive care unit(ICU)-acquired hypernatremia(IAH).Nevertheless,its relevance in patients with septic shock remains uncertain.AIM To identify independent risk factors and their predictive efficacy for IAH to improve outcomes in patients with septic shock.METHODS In the present retrospective single-center study,a cohort of 157 septic shock patients with concurrent hypernatremia in the ICU at The First Affiliated Hospital of Soochow University,between August 1,2018,and May 31,2023,were analyzed.Patients were categorized based on the timing of hypernatremia occurrence into the IAH group(n=62),the non-IAH group(n=41),and the normonatremia group(n=54).RESULTS In the present study,there was a significant association between the high serum sodium concentrations,excessive persistent inflammation,immunosuppression and catabolism syndrome and chronic critical illness,while rapid recovery had an apparent association with normonatremia.Moreover,multivariable analyses revealed the following independent risk factors for IAH:Total urinary output over the preceding three days[odds ratio(OR)=1.09;95%CI:1.02–1.17;P=0.014],enteral nutrition(EN)sodium content of 500 mg(OR=2.93;95%CI:1.13–7.60;P=0.027),and EN sodium content of 670 mg(OR=6.19;95%CI:1.75–21.98;P=0.005)were positively correlated with the development of IAH.Notably,the area under the curve for total urinary output over the preceding three days was 0.800(95%CI:0.678–0.922,P=0.001).Furthermore,maximum serum sodium levels,the duration of hypernatremia,and varying sodium correction rates were significantly associated with 28-day in-hospital mortality in septic shock patients(P<0.05).CONCLUSION The present findings illustrate that elevated serum sodium level was significantly associated with a poor prognosis in septic shock patients in the ICU.It is highly recommended that hypernatremia be considered a potentially important prognostic indicator for the outcome of septic shock.展开更多
In order to solve the problems of the traditional flame detection method, such as low detection accuracy, slow detection speed and lack of real-time detection ability. An improved high speed flame detection method bas...In order to solve the problems of the traditional flame detection method, such as low detection accuracy, slow detection speed and lack of real-time detection ability. An improved high speed flame detection method based on YOLOv7 is proposed. Based on YOLOv7 and combined with ConvNeXtBlock, CN-B network module was constructed, and YOLOv7-CN-B flame detection method was proposed. Compared with the YOLOv7 method, this flame detection method is lighter and has stronger flame feature extraction ability. 2059 open flame data sets labeled with single flame categories were used to avoid the enhancement effect brought by high-quality data sets, so that the comparative experimental effect completely depended on the performance of the flame detection method itself. The results show that the accuracy of YOLOv7-CN-B method is improved by 5% and mAP is improved by 2.1% compared with YOLOv7 method. The detection speed reached 149.25 FPS, and the single detection speed reached 11.9 ms. The experimental results show that the YOLOv7-CN-B method has better performance than the mainstream algorithm.展开更多
Sepsis,characterized as life-threatening organ dysfunction resulting from dysregulated host responses to infection,remains a significant challenge in clinical practice.Despite advancements in understanding host-bacter...Sepsis,characterized as life-threatening organ dysfunction resulting from dysregulated host responses to infection,remains a significant challenge in clinical practice.Despite advancements in understanding host-bacterial interactions,molecular responses,and therapeutic approaches,the mortality rate associated with sepsis has consistently ranged between 10%and 16%.This elevated mortality highlights critical gaps in our comprehension of sepsis etiology.Traditionally linked to bacterial and fungal pathogens,recent outbreaks of acute viral infections,including Middle East respiratory syndrome coronavirus(MERS-CoV),influenza virus,and severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),among other regional epidemics,have underscored the role of viral pathogenesis in sepsis,particularly when critically ill patients exhibit classic symptoms indicative of sepsis.However,many cases of viral-induced sepsis are frequently underdiagnosed because standard evaluations typically exclude viral panels.Moreover,these viruses not only activate conventional pattern recognition receptors(PRRs)and retinoic acid-inducible gene-I(RIG-I)-like receptors(RLRs)but also initiate primary antiviral pathways such as cyclic guanosine monophosphate adenosine monophosphate(GMP-AMP)synthase(cGAS)-stimulator of interferon genes(STING)signaling and interferon response mechanisms.Such activations lead to cellular stress,metabolic disturbances,and extensive cell damage that exacerbate tissue injury while leading to a spectrum of clinical manifestations.This complexity poses substantial challenges for the clinical management of affected cases.In this review,we elucidate the definition and diagnosis criteria for viral sepsis while synthesizing current knowledge regarding its etiology,epidemiology,and pathophysiology,molecular mechanisms involved therein as well as their impact on immune-mediated organ damage.Additionally,we discuss clinical considerations related to both existing therapies and advanced treatment interventions,aiming to enhance the comprehensive understanding surrounding viral sepsis.展开更多
304H austenitic stainless steel wire was investigated,emphasizing microstructural deformation,martensite phase transformation,and residual magnetic properties during drawing.Utilizing several microstructural observati...304H austenitic stainless steel wire was investigated,emphasizing microstructural deformation,martensite phase transformation,and residual magnetic properties during drawing.Utilizing several microstructural observation techniques,the volume fraction of martensite,modes of grain deformation in distinct regions,and the phase relationship between austenite and martensite were comprehensively characterized.In addition,a finite element simulation with representative volume elements specific to different zones also offers insights into strain responses during the drawing process.Results from the first-pass drawing reveal that there exists a higher volume fraction of martensite in the central region of 304H austenitic stainless steel wire compared to edge areas.This discrepancy is attributed to a concentrated presence of shear slip system{111}<110>γcrystallographic orientation,primarily accumulating in the central region obeying the Kurdjumov-Sachs path.Subsequent to the second drawing pass,the cumulative shear deformation within distinct regions of the steel wire became more pronounced.This resulted in a progressive augmentation of the volume fraction of martensite in both the central and peripheral regions of the steel wire.Concurrently,this led to a discernible elevation in the overall residual magnetism of the steel wire.展开更多
To address the prominent problems faced by customer churn in telecom enterprise management, a telecom customer churn prediction model integrating GA-XGBoost and SHAP is proposed. By using the ADASYN algorithm for data...To address the prominent problems faced by customer churn in telecom enterprise management, a telecom customer churn prediction model integrating GA-XGBoost and SHAP is proposed. By using the ADASYN algorithm for data processing on the unbalanced sample set;based on the GA-XGBoost model, the XGBoost algorithm is used to construct the telecom customer churn prediction model, and the hyperparameters of the model are optimized by using the genetic algorithm. The experimental results show that compared with traditional machine learning methods such as GBDT, decision tree, KNN and single XGBoost model, the improved XGBoost model has better performance in recall, F1 value and AUC value;the GA-XGBoost model is integrated with SHAP framework to analyze and explain the important features affecting telecom customer churn, which is more in line with the telecom industry to predict customer the actual situation of churn.展开更多
We present a graphics processing units(GPU)parallelization based three-dimensional time-dependent Schrödinger equation(3D-TDSE)code to simulate the interaction between single-active-electron atom/molecule and arb...We present a graphics processing units(GPU)parallelization based three-dimensional time-dependent Schrödinger equation(3D-TDSE)code to simulate the interaction between single-active-electron atom/molecule and arbitrary types of laser pulses with either velocity gauge or length gauge in Cartesian coordinates.Split-operator method combined with fast Fourier transforms(FFT)is used to perform the time evolution.Sample applications in different scenarios,such as stationary state energies,photon ionization spectra,attosecond clocks,and high-order harmonic generation(HHG),are given for the hydrogen atom.Repeatable results can be obtained with the benchmark program PCTDSE,which is a 3DTDSE Fortran solver parallelized using message passing interface(MPI)library.With the help of GPU acceleration and vectorization strategy,our code running on a single NVIDIA 3090 RTX GPU can achieve about 10 times faster computation speed than PCTDSE running on a 144 Intel Xeon CPU cores server with the same accuracy.In addition,3D-GTDSE can also be modified slightly to simulate non-adiabatic dynamics involving the coupling of nuclear and electronic wave packets,as well as pure nuclear wave packet dynamics in the presence of strong laser fields within 3 dimensions.Additionally,we have also discussed the limitations and shortcomings of our code in utilizing GPU memory.The 3D-GTDSE code provides an alternative tool for studying the ultrafast nonlinear dynamics under strong laser fields.展开更多
Supply chain management usually faces problems such as high empty rate of transportation, unreasonable inventory management, and large material consumption caused by inaccurate market demand forecasts. To solve these ...Supply chain management usually faces problems such as high empty rate of transportation, unreasonable inventory management, and large material consumption caused by inaccurate market demand forecasts. To solve these problems, using artificial intelligence and big data technology to achieve market demand forecasting and intelligent decision-making is becoming a strategic technology trend of supply chain management in the future. Firstly, this paper makes a visual analysis of the historical data of the Stock Keeping Unit (SKU);Then, the characteristic factors affecting the future demand are constructed from the storage level, product level, historical usage of SKU, etc;Finally, a supply chain demand forecasting algorithm based on SSA-XGBoost model has proposed around three aspects of feature engineering, parameter optimization and model integration, and is compared with other machine learning models. The experiment shows that the forecasting result of SSA-XGBoost forecasting model is highly consistent with the actual value, so it is of practical significance to adopt this forecasting model to solve the supply chain demand forecasting problem.展开更多
基金supported by the Best Practice Spotlight Organization (Ottawa, Canada)Key Research Project of the Beijing University of Chinese Medicine (2020-JYB-ZDGG-075Beijing, China)
文摘Objective: To explore the methodology of the evidence-based expert consensus formulation process of traditional Chinese medicine(TCM) nursing taking stroke as an example.Methods: First, preliminary and comprehensive presentation of all stroke-related symptoms and corresponding TCM nursing techniques involved were revealed through bibliometric analysis. Then, selection of stroke symptoms and TCM nursing techniques for inclusion in the consensus was performed using an expert consultation method. Next, we determined the search strategy for a precise evidence search;conducted an evaluation of evidence quality and the grade of the evidence;and completed evidence extraction, evidence analysis, and evidence synthesis based on the included symptoms and TCM nursing techniques. The Delphi method was then applied to determine the strength of each recommendation and the choice of nursing care points by referring to the Grading of Recommendations, Assessment, Development, and Evaluations grid. Finally, we conducted an external expert validation of the Delphi results to form an expert consensus guideline.Results: Through the bibliometric analysis, 22 stroke symptoms and 18 TCM nursing techniques were identified in the literature. Then, after expert consultation, 22 symptoms and 111 pairs of symptoms combined with TCM nursing techniques were selected for the evidence search. Evidence integration yielded 10 stroke symptoms corresponding to 29 bodies of evidence;these 10 symptoms were retained through the Delphi consultation, and recommendation strength results for 26 recommendations were obtained. A total of 9 symptoms were further retained for expert external validation to form 24 recommendations, with a recommendation process score range of 7.64-9.99 points and a more scientific and standardized recommendation-formation process.Conclusion: Owing to the current limited conditions of evidence-based resources for TCM nursing, the present consensus-building process represents only a preliminary exploration of an evidence-based expert consensus for TCM nursing to provide a reference for a more scientific and standardized methodology.
基金Supported by The National Natural Science Foundation of China,No.82072130Key Medical Research Projects in Jiangsu Province,No.ZD2022021Suzhou Clinical Medical Center for Anesthesiology,No.Szlcyxzxj202102。
文摘BACKGROUND Hypernatremia represents a significant electrolyte imbalance associated with numerous adverse outcomes,particularly in cases of intensive care unit(ICU)-acquired hypernatremia(IAH).Nevertheless,its relevance in patients with septic shock remains uncertain.AIM To identify independent risk factors and their predictive efficacy for IAH to improve outcomes in patients with septic shock.METHODS In the present retrospective single-center study,a cohort of 157 septic shock patients with concurrent hypernatremia in the ICU at The First Affiliated Hospital of Soochow University,between August 1,2018,and May 31,2023,were analyzed.Patients were categorized based on the timing of hypernatremia occurrence into the IAH group(n=62),the non-IAH group(n=41),and the normonatremia group(n=54).RESULTS In the present study,there was a significant association between the high serum sodium concentrations,excessive persistent inflammation,immunosuppression and catabolism syndrome and chronic critical illness,while rapid recovery had an apparent association with normonatremia.Moreover,multivariable analyses revealed the following independent risk factors for IAH:Total urinary output over the preceding three days[odds ratio(OR)=1.09;95%CI:1.02–1.17;P=0.014],enteral nutrition(EN)sodium content of 500 mg(OR=2.93;95%CI:1.13–7.60;P=0.027),and EN sodium content of 670 mg(OR=6.19;95%CI:1.75–21.98;P=0.005)were positively correlated with the development of IAH.Notably,the area under the curve for total urinary output over the preceding three days was 0.800(95%CI:0.678–0.922,P=0.001).Furthermore,maximum serum sodium levels,the duration of hypernatremia,and varying sodium correction rates were significantly associated with 28-day in-hospital mortality in septic shock patients(P<0.05).CONCLUSION The present findings illustrate that elevated serum sodium level was significantly associated with a poor prognosis in septic shock patients in the ICU.It is highly recommended that hypernatremia be considered a potentially important prognostic indicator for the outcome of septic shock.
文摘In order to solve the problems of the traditional flame detection method, such as low detection accuracy, slow detection speed and lack of real-time detection ability. An improved high speed flame detection method based on YOLOv7 is proposed. Based on YOLOv7 and combined with ConvNeXtBlock, CN-B network module was constructed, and YOLOv7-CN-B flame detection method was proposed. Compared with the YOLOv7 method, this flame detection method is lighter and has stronger flame feature extraction ability. 2059 open flame data sets labeled with single flame categories were used to avoid the enhancement effect brought by high-quality data sets, so that the comparative experimental effect completely depended on the performance of the flame detection method itself. The results show that the accuracy of YOLOv7-CN-B method is improved by 5% and mAP is improved by 2.1% compared with YOLOv7 method. The detection speed reached 149.25 FPS, and the single detection speed reached 11.9 ms. The experimental results show that the YOLOv7-CN-B method has better performance than the mainstream algorithm.
基金supported by the National Natural Science Foundation of China(82372176,82272217,82002026,81971818)the Hubei Provincial Key Research and Development Program of China(2023BCB091)the National Key Research and Development Program of China(2021YFC2500802,2021YFC2300200).
文摘Sepsis,characterized as life-threatening organ dysfunction resulting from dysregulated host responses to infection,remains a significant challenge in clinical practice.Despite advancements in understanding host-bacterial interactions,molecular responses,and therapeutic approaches,the mortality rate associated with sepsis has consistently ranged between 10%and 16%.This elevated mortality highlights critical gaps in our comprehension of sepsis etiology.Traditionally linked to bacterial and fungal pathogens,recent outbreaks of acute viral infections,including Middle East respiratory syndrome coronavirus(MERS-CoV),influenza virus,and severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),among other regional epidemics,have underscored the role of viral pathogenesis in sepsis,particularly when critically ill patients exhibit classic symptoms indicative of sepsis.However,many cases of viral-induced sepsis are frequently underdiagnosed because standard evaluations typically exclude viral panels.Moreover,these viruses not only activate conventional pattern recognition receptors(PRRs)and retinoic acid-inducible gene-I(RIG-I)-like receptors(RLRs)but also initiate primary antiviral pathways such as cyclic guanosine monophosphate adenosine monophosphate(GMP-AMP)synthase(cGAS)-stimulator of interferon genes(STING)signaling and interferon response mechanisms.Such activations lead to cellular stress,metabolic disturbances,and extensive cell damage that exacerbate tissue injury while leading to a spectrum of clinical manifestations.This complexity poses substantial challenges for the clinical management of affected cases.In this review,we elucidate the definition and diagnosis criteria for viral sepsis while synthesizing current knowledge regarding its etiology,epidemiology,and pathophysiology,molecular mechanisms involved therein as well as their impact on immune-mediated organ damage.Additionally,we discuss clinical considerations related to both existing therapies and advanced treatment interventions,aiming to enhance the comprehensive understanding surrounding viral sepsis.
基金funded by National Natural Science Foundation of China(52201084 and 52231003)Major Program(JD)of Hubei Province(2023BAA019)+2 种基金China Scholarship Council(CSC)Postdoctoral Station of metallurgical Engineering of Wuhan University of Science and Technology(WUST)Postdoctoral workstation of Zhejiang Jincheng New Material Co.,Ltd.
文摘304H austenitic stainless steel wire was investigated,emphasizing microstructural deformation,martensite phase transformation,and residual magnetic properties during drawing.Utilizing several microstructural observation techniques,the volume fraction of martensite,modes of grain deformation in distinct regions,and the phase relationship between austenite and martensite were comprehensively characterized.In addition,a finite element simulation with representative volume elements specific to different zones also offers insights into strain responses during the drawing process.Results from the first-pass drawing reveal that there exists a higher volume fraction of martensite in the central region of 304H austenitic stainless steel wire compared to edge areas.This discrepancy is attributed to a concentrated presence of shear slip system{111}<110>γcrystallographic orientation,primarily accumulating in the central region obeying the Kurdjumov-Sachs path.Subsequent to the second drawing pass,the cumulative shear deformation within distinct regions of the steel wire became more pronounced.This resulted in a progressive augmentation of the volume fraction of martensite in both the central and peripheral regions of the steel wire.Concurrently,this led to a discernible elevation in the overall residual magnetism of the steel wire.
文摘To address the prominent problems faced by customer churn in telecom enterprise management, a telecom customer churn prediction model integrating GA-XGBoost and SHAP is proposed. By using the ADASYN algorithm for data processing on the unbalanced sample set;based on the GA-XGBoost model, the XGBoost algorithm is used to construct the telecom customer churn prediction model, and the hyperparameters of the model are optimized by using the genetic algorithm. The experimental results show that compared with traditional machine learning methods such as GBDT, decision tree, KNN and single XGBoost model, the improved XGBoost model has better performance in recall, F1 value and AUC value;the GA-XGBoost model is integrated with SHAP framework to analyze and explain the important features affecting telecom customer churn, which is more in line with the telecom industry to predict customer the actual situation of churn.
基金supported by the GHfund A(Grant No.ghfund202407013663)the Fundamental Research Funds for the Central Universities(Grant No.GK202207012)+4 种基金Shaanxi Province(Grant No.QCYRCXM-2022-241)the National Key Research and Development Program of China(Grant No.2022YFE0134200)Guangdong Basic and Applied Basic Research Foundation(Grant No.2025A1515011117)the Natural Science Foundation of Jilin Province(Grant No.20220101016JC)the National Natural Science Foundation of China(Grant Nos.12374238,11934004,and 11974230)。
文摘We present a graphics processing units(GPU)parallelization based three-dimensional time-dependent Schrödinger equation(3D-TDSE)code to simulate the interaction between single-active-electron atom/molecule and arbitrary types of laser pulses with either velocity gauge or length gauge in Cartesian coordinates.Split-operator method combined with fast Fourier transforms(FFT)is used to perform the time evolution.Sample applications in different scenarios,such as stationary state energies,photon ionization spectra,attosecond clocks,and high-order harmonic generation(HHG),are given for the hydrogen atom.Repeatable results can be obtained with the benchmark program PCTDSE,which is a 3DTDSE Fortran solver parallelized using message passing interface(MPI)library.With the help of GPU acceleration and vectorization strategy,our code running on a single NVIDIA 3090 RTX GPU can achieve about 10 times faster computation speed than PCTDSE running on a 144 Intel Xeon CPU cores server with the same accuracy.In addition,3D-GTDSE can also be modified slightly to simulate non-adiabatic dynamics involving the coupling of nuclear and electronic wave packets,as well as pure nuclear wave packet dynamics in the presence of strong laser fields within 3 dimensions.Additionally,we have also discussed the limitations and shortcomings of our code in utilizing GPU memory.The 3D-GTDSE code provides an alternative tool for studying the ultrafast nonlinear dynamics under strong laser fields.
文摘Supply chain management usually faces problems such as high empty rate of transportation, unreasonable inventory management, and large material consumption caused by inaccurate market demand forecasts. To solve these problems, using artificial intelligence and big data technology to achieve market demand forecasting and intelligent decision-making is becoming a strategic technology trend of supply chain management in the future. Firstly, this paper makes a visual analysis of the historical data of the Stock Keeping Unit (SKU);Then, the characteristic factors affecting the future demand are constructed from the storage level, product level, historical usage of SKU, etc;Finally, a supply chain demand forecasting algorithm based on SSA-XGBoost model has proposed around three aspects of feature engineering, parameter optimization and model integration, and is compared with other machine learning models. The experiment shows that the forecasting result of SSA-XGBoost forecasting model is highly consistent with the actual value, so it is of practical significance to adopt this forecasting model to solve the supply chain demand forecasting problem.
