In order to support the physical research on the EAST tokamak,a new positive ion source with designed beam energy of 120 keV was proposed to be developed.Accelerator structure is one of the key components of the ion s...In order to support the physical research on the EAST tokamak,a new positive ion source with designed beam energy of 120 keV was proposed to be developed.Accelerator structure is one of the key components of the ion source.Through the finite element analysis method,the electrostatic analyses of insulators and grid plates were carried out,the material and structure parameters of insulators were determined.The maximum electric field around each insulator is about 4 kV/mm,and the maximum electric field between grids is about 14 kV/mm,which can meet the 120 keV withstand voltage holding.The insulation system for the positive ion source accelerator with 120 keV is designed,and the connection and basic parameters of insulators and support flanges are analyzed and determined.展开更多
Decision support systems(DSS)based on physically based numerical models are standard tools used by water services and utilities.However,few DSS based on holistic approaches combining distributed hydrological,hydraulic...Decision support systems(DSS)based on physically based numerical models are standard tools used by water services and utilities.However,few DSS based on holistic approaches combining distributed hydrological,hydraulic,and hydrogeological models are operationally exploited.This holistic approach was adopted for the development of the AquaVar DSS,used for water resource management in the French Mediterranean Var watershed.The year 2019 marked the initial use of the DSS in its operational environment.Over the next 5 years,multiple hydrological events allowed to test the performance of the DSS.The results show that the tool is capable of simulating peak flows associated with two extreme rainfall events(storms Alex and Aline).For a moderate flood,the real-time functionality was able to simulate forecast discharges 26 h before the flood peak,with a maximum local error of 30%.Finally,simulations for the drought period 2022-2023 highlighted the essential need for DSS to evolve in line with changing climatic conditions,which give rise to unprecedented hydrological processes.The lessons learned from these first 5 years of AquaVar use under operational conditions are synthesized,addressing various topics such as DSS modularity,evolution,data positioning,technology,and governance.展开更多
BACKGROUND The treatment of patients with liver cancer after surgery with the artificial liver support system combined with traditional Chinese medicine(TCM)for strengthening the body and removing blood stasis is a ne...BACKGROUND The treatment of patients with liver cancer after surgery with the artificial liver support system combined with traditional Chinese medicine(TCM)for strengthening the body and removing blood stasis is a new idea.AIM To analyze the post-surgical effect of the artificial liver support system with TCM in patients with liver cancer.METHODS Ninety-eight patients with liver cancer who underwent surgical treatment at the Fifth People’s Hospital of Huai’an from January 2023-2024 were selected and divided into two groups(49 patients each)via random lottery method.Both groups underwent surgery.The control group received artificial liver support,and the observation group was additionally treated with TCM for strengthening the body and removing blood stasis.Gastrointestinal recovery,liver function,tumor marker levels,immune function,and safety were compared between both groups.RESULTS There were significant differences in the levels of indicators related to gastrointestinal recovery between the groups(P<0.05).After treatment,the levels of alanine aminotransferase,aspartate aminotransferase,total bilirubin,and gamma-glutamyl transpeptidase in the observation group were lower,whereas the albumin level was higher(P<0.05).After treatment,tumor marker levels in the observation group were relatively lower(P<0.05).After treatment,compared to the control group,the CD4+level in the observation group was higher and the CD8+level was lower(P<0.05).There was no significant difference in the incidence of adverse reactions between both groups(P>0.05).CONCLUSION Combining the artificial liver support system with TCM significantly improves liver and gastrointestinal functions,enhances immune responses,and reduces tumor marker levels with high safety,suggesting that it could be a promising approach for optimizing postoperative care and improving patient outcomes,potentially reducing complications and enhancing quality of life.展开更多
Objectives:Recently,the global esports industry has experienced remarkable growth,leading to an expansion in the scale and influence of professional player communities.However,despite this outward growth,systems to pr...Objectives:Recently,the global esports industry has experienced remarkable growth,leading to an expansion in the scale and influence of professional player communities.However,despite this outward growth,systems to protect players’mental health remain inadequate.Comprehensive analysis of structural risk factors,including performance pressure,public evaluation,and career instability,remains insufficient.This study,aimed to explore stressors encountered by esports athletes,coping strategies,and the role of social support systems in safeguarding mental health.Using the transactional model of stress and coping,the job demands–resources model,and social support theory,the study adopts an integrated perspective to examine challenges faced by athletes in the competitive esports environment.Methods:A qualitative case study was conducted involving in-depth interviews and nonparticipant observations with 11 esports athletes who competed at national or international levels,as well as two team managers.Thematic analysis identified recurring patterns in the data,and credibility was ensured through triangulation and cross-review among researchers.Results:Esports athletes experience multiple interacting stressors,including performance demands,emotional strain duringmatches,and continuous evaluation on socialmedia.In response,they employed coping strategies—problem-focused,emotion-focused,and avoidance-based,which provided temporary relief but often led to burnout and self-regulation failure owing to absence of support systems.Social support networks had ambivalent effects:while offering comfort,they also intensified pressure through negative feedback and high expectations from fans and online communities.Conclusion:The findings show that mental health issues among esports athletes are not only related to individual factors but are closely linked to performance-driven structures,competitive environments,and social relationships.This study integrates the transactional model of stress and coping,the JobDemands–Resourcesmodel,and social support theoryto provide comprehensive analysis.It also offers practical recommendations,including psychological counseling,emotional labor programs,and improved communication with families and fan communities.展开更多
Considering the characteristics of deep thick top coal roadway,in which the high ground stress,coal seam with low strength,and a large range of surrounding rock fragmentation,the pressure relief anchor box beam suppor...Considering the characteristics of deep thick top coal roadway,in which the high ground stress,coal seam with low strength,and a large range of surrounding rock fragmentation,the pressure relief anchor box beam support system with high strength is developed.The high-strength bearing characteristics and coupling yielding support mechanism of this support system are studied by the mechanical tests of composite members and the combined support system.The test results show that under the coupling effect of support members,the peak stress of the box-shaped support beam in the anchor box beam is reduced by 21.9%,and the average deformation is increased by 135.0%.The ultimate bending bearing capacity of the box-shaped support beam is 3.5 times that of traditional channel beam.The effective compressive stress zone applied by the high prestressed cable is expanded by 26.4%.On this basis,the field support comparison test by the anchor channel beam,the anchor I-shaped beam and the anchor box beam are carried out.Compared with those of the previous two,the surrounding rock convergence of the latter is decreased by 41.2%and 22.2%,respectively.The field test verifies the effectiveness of the anchor box beam support system.展开更多
Objective To develop and evaluate an automated system for digitizing audiograms,classifying hearing loss levels,and comparing their performance with traditional methods and otolaryngologists'interpretations.Design...Objective To develop and evaluate an automated system for digitizing audiograms,classifying hearing loss levels,and comparing their performance with traditional methods and otolaryngologists'interpretations.Designed and Methods We conducted a retrospective diagnostic study using 1,959 audiogram images from patients aged 7 years and older at the Faculty of Medicine,Vajira Hospital,Navamindradhiraj University.We employed an object detection approach to digitize audiograms and developed multiple machine learning models to classify six hearing loss levels.The dataset was split into 70%training(1,407 images)and 30%testing(352 images)sets.We compared our model's performance with classifications based on manually extracted audiogram values and otolaryngologists'interpretations.Result Our object detection-based model achieved an F1-score of 94.72%in classifying hearing loss levels,comparable to the 96.43%F1-score obtained using manually extracted values.The Light Gradient Boosting Machine(LGBM)model is used as the classifier for the manually extracted data,which achieved top performance with 94.72%accuracy,94.72%f1-score,94.72 recall,and 94.72 precision.In object detection based model,The Random Forest Classifier(RFC)model showed the highest 96.43%accuracy in predicting hearing loss level,with a F1-score of 96.43%,recall of 96.43%,and precision of 96.45%.Conclusion Our proposed automated approach for audiogram digitization and hearing loss classification performs comparably to traditional methods and otolaryngologists'interpretations.This system can potentially assist otolaryngologists in providing more timely and effective treatment by quickly and accurately classifying hearing loss.展开更多
This research aims to enhance Clinical Decision Support Systems(CDSS)within Wireless Body Area Networks(WBANs)by leveraging advanced machine learning techniques.Specifically,we target the challenges of accurate diagno...This research aims to enhance Clinical Decision Support Systems(CDSS)within Wireless Body Area Networks(WBANs)by leveraging advanced machine learning techniques.Specifically,we target the challenges of accurate diagnosis in medical imaging and sequential data analysis using Recurrent Neural Networks(RNNs)with Long Short-Term Memory(LSTM)layers and echo state cells.These models are tailored to improve diagnostic precision,particularly for conditions like rotator cuff tears in osteoporosis patients and gastrointestinal diseases.Traditional diagnostic methods and existing CDSS frameworks often fall short in managing complex,sequential medical data,struggling with long-term dependencies and data imbalances,resulting in suboptimal accuracy and delayed decisions.Our goal is to develop Artificial Intelligence(AI)models that address these shortcomings,offering robust,real-time diagnostic support.We propose a hybrid RNN model that integrates SimpleRNN,LSTM layers,and echo state cells to manage long-term dependencies effectively.Additionally,we introduce CG-Net,a novel Convolutional Neural Network(CNN)framework for gastrointestinal disease classification,which outperforms traditional CNN models.We further enhance model performance through data augmentation and transfer learning,improving generalization and robustness against data scarcity and imbalance.Comprehensive validation,including 5-fold cross-validation and metrics such as accuracy,precision,recall,F1-score,and Area Under the Curve(AUC),confirms the models’reliability.Moreover,SHapley Additive exPlanations(SHAP)and Local Interpretable Model-agnostic Explanations(LIME)are employed to improve model interpretability.Our findings show that the proposed models significantly enhance diagnostic accuracy and efficiency,offering substantial advancements in WBANs and CDSS.展开更多
This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weat...This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) model.Accurate meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support systems.Simulation of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and time-consuming.Therefore,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological parameters.Comprehensive evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South directions.The performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological parameters.Results show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single station.However,accuracy is slightly compromised when predicting wind speed components.Root mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of V-component.In conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.展开更多
BACKGROUND The increased expression of G3BP1 was positively correlated with the prognosis of liver failure.AIM To investigate the effect of G3BP1 on the prognosis of acute liver failure(ALF)and acute-on-chronic liver ...BACKGROUND The increased expression of G3BP1 was positively correlated with the prognosis of liver failure.AIM To investigate the effect of G3BP1 on the prognosis of acute liver failure(ALF)and acute-on-chronic liver failure(ACLF)after the treatment of artificial liver support system(ALSS).METHODS A total of 244 patients with ALF and ACLF were enrolled in this study.The levels of G3BP1 on admission and at discharge were detected.The validation set of 514 patients was collected to verify the predicted effect of G3BP1 and the viability of prognosis.RESULTS This study was shown that lactate dehydrogenase(LDH),alpha-fetoprotein(AFP)and prothrombin time were closely related to the prognosis of patients.After the ALSS treatment,the patient’amount of decreased G3BP1 index in difference of G3BP1 between the value of discharge and admission(difG3BP1)<0 group had a nearly 10-fold increased risk of progression compared with the amount of increased G3BP1 index.The subgroup analysis showed that the difG3BP1<0 group had a higher risk of progression,regardless of model for end-stage liver disease high-risk or low-risk group.At the same time,compared with the inflam matory marks[tumor necrosis factor-α,interleukin(IL)-1βand IL-18],G3BP1 had higher discrimination and was more stable in the model analysis and validation set.When combined with AFP and LDH,concordance index was respectively 0.84 and 0.8 in training and validation cohorts.CONCLUSION This study indicated that G3BP1 could predict the prognosis of ALF or ACLF patients treated with ALSS.The combination of G3BP1,AFP and LDH could accurately evaluate the disease condition and predict the clinical endpoint of patients.展开更多
In recent years,decision support systems(DSSs)have successfully deployed ontologies in their architecture.The result of such a use is information systems that assist users and organizations in semi-structured decision...In recent years,decision support systems(DSSs)have successfully deployed ontologies in their architecture.The result of such a use is information systems that assist users and organizations in semi-structured decision-making activities.Visitors from throughout Iran travel to different cities and regions every year,and they need help making their choices.Some of these tourists are unable to visit the beautiful areas of the destination city due to a lack of awareness.In this study,we design an ontology-based spatial DSS to find entertainment and tourism centers in Arak,Iran.The objective is to provide users with recommendations appropriate for the location,time,age group,type of activity,and other factors.In this model,the demands and concerns of tourists have been managed by creating a domain Web Ontology Language(OWL)for entertainment centers as a knowledge base in the Protégéenvironment.The developed webbased DSS operates on a client-server architecture using technologies such as Werkzeug and Flask.As a result,it makes it possible to ontology reasoning based on the HermiT engine to choose the right center and conduct a semantic search on classes related to the appropriate point of interest.The main distinction between the proposed methodology and the previous studies on spatial DSS is that criteria are object properties in an ontology.Therefore,decision support relies on real-time reasoning rather than transforming criteria into geospatial layers.The evaluation results confirmed efficient interaction with this system,purposeful information retrieval,and rapid decision-making process.The results also indicated that searching for a POI(point of interest)in the study area using the developed system is at least 30%more successful than a search engine or social media.Moreover,to overcome the cold start problem,the proposed technique might be utilized in conjunction with the POI recommender systems.展开更多
Background: Infertility is a complex disorder with significant psycho-social and economic consequences. It globally affects 10% - 15% of couples. In Cameroon, little is known about what women do to overcome the psycho...Background: Infertility is a complex disorder with significant psycho-social and economic consequences. It globally affects 10% - 15% of couples. In Cameroon, little is known about what women do to overcome the psychosocial aspects of the disease. Objectives: This study aimed to identify the support systems and coping strategies of infertile women attending the outpatient consultation unit of the Gynaecological Endoscopic Surgery and Reproductive Teaching Hospital (CHRACERH), Yaoundé, Cameroon. Methods: A hospital-based cross-sectional study was conducted from the 14th of March to the 6th of April 2023 at CHRACERH Yaoundé. A total of 190 participants were recruited using a convenience sampling method. Data regarding socio-demographic characteristics, support systems and coping strategies were collected using a pretested questionnaire. Descriptive and analytic statistics were conducted using SPSS version 25. Results: The mean age of participants was 39.52 ± 7.64 years. The majority 78.9% of participants were workers (public, private sector, or traders) and were Christians 95.8%. The most common source of psychological support was from family 76.8 and husbands 72.63%. Most of the participants 89.5% resorted to prayer and getting busy 48.4% as a coping strategy. There was no statistically significant relationship between coping strategies and psychological disorders p > 0.05. Conclusion: The main support system of participants was family, husband, and friends. Prayer, getting busy and adoption were the most common coping strategies. There is a need for the Ministry of Public Health and other stakeholders to put in place other support systems and coping strategies (FELICIA) used elsewhere and provide adequate health education and infection control to prevent infertility in Cameroon.展开更多
This study outlines the essential nursing strategies employed in the care of 10 patients experiencing vascular vagal reflex, managed with artificial liver support systems. It highlights a holistic nursing approach tai...This study outlines the essential nursing strategies employed in the care of 10 patients experiencing vascular vagal reflex, managed with artificial liver support systems. It highlights a holistic nursing approach tailored to the distinct clinical manifestations of these patients. Key interventions included early detection of psychological issues prior to initiating treatment, the implementation of comprehensive health education, meticulous monitoring of vital signs throughout the therapy, prompt emergency interventions when needed, adherence to prescribed medication protocols, and careful post-treatment observations including venous catheter management. Following rigorous treatment and dedicated nursing care, 7 patients demonstrated significant improvement and were subsequently discharged.展开更多
With the beginning of the information systems’ spreading, people started thinking about using them for making business decisions. Computer technology solutions, such as the Decision Support System, make the decision-...With the beginning of the information systems’ spreading, people started thinking about using them for making business decisions. Computer technology solutions, such as the Decision Support System, make the decision-making process less complex and simpler for problem-solving. In order to make a high-quality business decision, managers need to have a great deal of appropriate information. Nonetheless, this complicates the process of making appropriate decisions. In a situation like that, the possibility of using DSS is quite logical. The aim of this paper is to find out the intended use of DSS for medium and large business organizations in USA by applying the Technology Acceptance Model (TAM). Different models were developed in order to understand and predict the use of information systems, but the information systems community mostly used TAM to ensure this issue. The purpose of the research model is to determine the elements of analysis that contribute to these results. The sample for the research consisted of the target group that was supposed to have completed an online questionnaire about the manager’s use of DSS in medium and large American companies. The information obtained from the questionnaires was analyzed through the SPSS statistical software. The research has indicated that, this is primarily used due to a significant level of Perceived usefulness and For the Perceived ease of use.展开更多
The rapid development of the digital economy,driven by artificial intelligence(AI),is profoundly transforming traditional accounting practices and business models.The emergence of innovative models such as“wisdom+acc...The rapid development of the digital economy,driven by artificial intelligence(AI),is profoundly transforming traditional accounting practices and business models.The emergence of innovative models such as“wisdom+accounting”and“wisdom+financial sharing”has opened new avenues for enhancing enterprise decision-making support systems.This paper delves into the application of AI technology in accounting,examining its practical implementation and associated challenges.To mitigate potential risks arising from technological advancements,enterprises should establish robust and efficient intelligent financial systems.Additionally,organizations should foster a mindset of change within their accounting teams,improve the application of management information systems,strengthen internal control mechanisms,and continuously upgrade intelligent accounting software.Financial managers must adapt to the evolving landscape and proactively adjust their career paths and development strategies.展开更多
Objective:To design and implement a specialized nurse decision support system in the Department of Neurology and explore its effectiveness in preventing stroke-associated pneumonia(SAP).Methods:A decision support modu...Objective:To design and implement a specialized nurse decision support system in the Department of Neurology and explore its effectiveness in preventing stroke-associated pneumonia(SAP).Methods:A decision support module for specialized nurses was developed based on SAP-graded prevention strategies.A total of 664 neurology inpatients admitted to The First People’s Hospital of Xuzhou between July 2023 and September 2023 were selected as the conventional group,receiving standard nursing care.Another 704 neurology inpatients admitted between October 2023 and December 2023 were selected as the experimental group,receiving SAP-graded prevention strategies under the specialized nurse decision support system.The incidence of SAP in the two groups was compared.The occurrence of SAP was recorded using the Acute Ischemic Stroke-Associated Pneumonia Risk(A2DS2)scoring system.Swallowing function was evaluated using the Water Swallow Test(WST),and quality of life was assessed using the Swallowing Quality of Life(SWAL-QOL)scale.Results:The incidence of SAP in the experimental group was significantly lower than in the conventional group(P<0.05).After nursing interventions,the WST scores in the experimental group were lower,while the SWAL-QOL scores were higher compared to the conventional group(P<0.05).Conclusion:The design and implementation of a specialized nurse decision support system in the Department of Neurology significantly reduced the incidence of SAP in neurology inpatients,improved swallowing function,and enhanced quality of life.This approach shows promise for widespread application.展开更多
To address the challenges of current college student employment management,this study designed and implemented a machine learning-based decision support system for college student employment management.The system coll...To address the challenges of current college student employment management,this study designed and implemented a machine learning-based decision support system for college student employment management.The system collects and analyzes multidimensional data,uses machine learning algorithms for prediction and matching,provides personalized employment guidance for students,and provides decision support for universities and enterprises.The research results indicate that the system can effectively improve the efficiency and accuracy of employment guidance,promote school-enterprise cooperation,and achieve a win-win situation for all parties.展开更多
The focus of this paper is on a new concept framework and an architecture of an intelligent decision support syetem generator (DSSG). The framework results from a synthesis of two existing frameworks: Spragae and Bonc...The focus of this paper is on a new concept framework and an architecture of an intelligent decision support syetem generator (DSSG). The framework results from a synthesis of two existing frameworks: Spragae and Bonczek, while the architecture is a rooted partial order network. From our experience which comes out of the project of DSSG, we consider that they are keys of further research and development of DSS.展开更多
According to basic connotation and design principles of ecocity, a comparatively integrated index system is constructed in the paper. And at the same time using hierarchy grey comprehensive evaluation method, a hierar...According to basic connotation and design principles of ecocity, a comparatively integrated index system is constructed in the paper. And at the same time using hierarchy grey comprehensive evaluation method, a hierarchy grey comprehensive evaluation model of ecocity is established, then on the basis of the model, a comprehensive evaluation support system is developed, and the theoretical guidance supplied for construction of ecocity is provided.展开更多
In order to solve existing problems about the method of establishing traditional system structure of decision support system(DSS), O S chart is applied to describe object oriented system structure of general DSS, an...In order to solve existing problems about the method of establishing traditional system structure of decision support system(DSS), O S chart is applied to describe object oriented system structure of general DSS, and a new method of eight specific steps is proposed to establish object oriented system structure of DSS by using the method of O S chart, which is applied successfully to the development of the DSS for the energy system ecology engineering research of the Wangheqiu country. Supplying many scientific effective computing models, decision support ways and a lot of accurate reliable decision data, the DSS plays a critical part in helping engineering researchers to make correct decisions. Because the period for developing the DSS is relatively shorter, the new way improves the efficiency of establishing DSS greatly. It also makes the DSS of system structure more flexible and easy to expand.展开更多
The concept of organization decision support system （ODSS） is defined according to practical applications and novel understanding. And a framework for ODSS is designed. The framework has three components： infrastru...The concept of organization decision support system （ODSS） is defined according to practical applications and novel understanding. And a framework for ODSS is designed. The framework has three components： infrastructure, decision-making process and decision execution process. Infrastructure is responsible to transfer data and information. Decision-making process is the ODSS＇s soul to support decision-making. Decision execution process is to evaluate and execute decision results derived from decision-making process. The framework presents a kind of logic architecture. An example is given to verify and analyze the framework. The analysis shows that the framework has practical values, and has also reference values for understanding ODSS and for theoretical studies.展开更多
基金supported by National Natural Science Foundation of China(No.11975261)。
文摘In order to support the physical research on the EAST tokamak,a new positive ion source with designed beam energy of 120 keV was proposed to be developed.Accelerator structure is one of the key components of the ion source.Through the finite element analysis method,the electrostatic analyses of insulators and grid plates were carried out,the material and structure parameters of insulators were determined.The maximum electric field around each insulator is about 4 kV/mm,and the maximum electric field between grids is about 14 kV/mm,which can meet the 120 keV withstand voltage holding.The insulation system for the positive ion source accelerator with 120 keV is designed,and the connection and basic parameters of insulators and support flanges are analyzed and determined.
文摘Decision support systems(DSS)based on physically based numerical models are standard tools used by water services and utilities.However,few DSS based on holistic approaches combining distributed hydrological,hydraulic,and hydrogeological models are operationally exploited.This holistic approach was adopted for the development of the AquaVar DSS,used for water resource management in the French Mediterranean Var watershed.The year 2019 marked the initial use of the DSS in its operational environment.Over the next 5 years,multiple hydrological events allowed to test the performance of the DSS.The results show that the tool is capable of simulating peak flows associated with two extreme rainfall events(storms Alex and Aline).For a moderate flood,the real-time functionality was able to simulate forecast discharges 26 h before the flood peak,with a maximum local error of 30%.Finally,simulations for the drought period 2022-2023 highlighted the essential need for DSS to evolve in line with changing climatic conditions,which give rise to unprecedented hydrological processes.The lessons learned from these first 5 years of AquaVar use under operational conditions are synthesized,addressing various topics such as DSS modularity,evolution,data positioning,technology,and governance.
文摘BACKGROUND The treatment of patients with liver cancer after surgery with the artificial liver support system combined with traditional Chinese medicine(TCM)for strengthening the body and removing blood stasis is a new idea.AIM To analyze the post-surgical effect of the artificial liver support system with TCM in patients with liver cancer.METHODS Ninety-eight patients with liver cancer who underwent surgical treatment at the Fifth People’s Hospital of Huai’an from January 2023-2024 were selected and divided into two groups(49 patients each)via random lottery method.Both groups underwent surgery.The control group received artificial liver support,and the observation group was additionally treated with TCM for strengthening the body and removing blood stasis.Gastrointestinal recovery,liver function,tumor marker levels,immune function,and safety were compared between both groups.RESULTS There were significant differences in the levels of indicators related to gastrointestinal recovery between the groups(P<0.05).After treatment,the levels of alanine aminotransferase,aspartate aminotransferase,total bilirubin,and gamma-glutamyl transpeptidase in the observation group were lower,whereas the albumin level was higher(P<0.05).After treatment,tumor marker levels in the observation group were relatively lower(P<0.05).After treatment,compared to the control group,the CD4+level in the observation group was higher and the CD8+level was lower(P<0.05).There was no significant difference in the incidence of adverse reactions between both groups(P>0.05).CONCLUSION Combining the artificial liver support system with TCM significantly improves liver and gastrointestinal functions,enhances immune responses,and reduces tumor marker levels with high safety,suggesting that it could be a promising approach for optimizing postoperative care and improving patient outcomes,potentially reducing complications and enhancing quality of life.
文摘Objectives:Recently,the global esports industry has experienced remarkable growth,leading to an expansion in the scale and influence of professional player communities.However,despite this outward growth,systems to protect players’mental health remain inadequate.Comprehensive analysis of structural risk factors,including performance pressure,public evaluation,and career instability,remains insufficient.This study,aimed to explore stressors encountered by esports athletes,coping strategies,and the role of social support systems in safeguarding mental health.Using the transactional model of stress and coping,the job demands–resources model,and social support theory,the study adopts an integrated perspective to examine challenges faced by athletes in the competitive esports environment.Methods:A qualitative case study was conducted involving in-depth interviews and nonparticipant observations with 11 esports athletes who competed at national or international levels,as well as two team managers.Thematic analysis identified recurring patterns in the data,and credibility was ensured through triangulation and cross-review among researchers.Results:Esports athletes experience multiple interacting stressors,including performance demands,emotional strain duringmatches,and continuous evaluation on socialmedia.In response,they employed coping strategies—problem-focused,emotion-focused,and avoidance-based,which provided temporary relief but often led to burnout and self-regulation failure owing to absence of support systems.Social support networks had ambivalent effects:while offering comfort,they also intensified pressure through negative feedback and high expectations from fans and online communities.Conclusion:The findings show that mental health issues among esports athletes are not only related to individual factors but are closely linked to performance-driven structures,competitive environments,and social relationships.This study integrates the transactional model of stress and coping,the JobDemands–Resourcesmodel,and social support theoryto provide comprehensive analysis.It also offers practical recommendations,including psychological counseling,emotional labor programs,and improved communication with families and fan communities.
基金Project(2023YFC2907600)supported by the National Key Research and Development Program of ChinaProjects(42277174,42477166)supported by the National Natural Science Foundation of China+1 种基金Project(2024JCCXSB01)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(KFJJ24-01M)supported by the State Key Laboratory of Explosion Science and Safety Protection,Beijing Institute of Technology,China。
文摘Considering the characteristics of deep thick top coal roadway,in which the high ground stress,coal seam with low strength,and a large range of surrounding rock fragmentation,the pressure relief anchor box beam support system with high strength is developed.The high-strength bearing characteristics and coupling yielding support mechanism of this support system are studied by the mechanical tests of composite members and the combined support system.The test results show that under the coupling effect of support members,the peak stress of the box-shaped support beam in the anchor box beam is reduced by 21.9%,and the average deformation is increased by 135.0%.The ultimate bending bearing capacity of the box-shaped support beam is 3.5 times that of traditional channel beam.The effective compressive stress zone applied by the high prestressed cable is expanded by 26.4%.On this basis,the field support comparison test by the anchor channel beam,the anchor I-shaped beam and the anchor box beam are carried out.Compared with those of the previous two,the surrounding rock convergence of the latter is decreased by 41.2%and 22.2%,respectively.The field test verifies the effectiveness of the anchor box beam support system.
文摘Objective To develop and evaluate an automated system for digitizing audiograms,classifying hearing loss levels,and comparing their performance with traditional methods and otolaryngologists'interpretations.Designed and Methods We conducted a retrospective diagnostic study using 1,959 audiogram images from patients aged 7 years and older at the Faculty of Medicine,Vajira Hospital,Navamindradhiraj University.We employed an object detection approach to digitize audiograms and developed multiple machine learning models to classify six hearing loss levels.The dataset was split into 70%training(1,407 images)and 30%testing(352 images)sets.We compared our model's performance with classifications based on manually extracted audiogram values and otolaryngologists'interpretations.Result Our object detection-based model achieved an F1-score of 94.72%in classifying hearing loss levels,comparable to the 96.43%F1-score obtained using manually extracted values.The Light Gradient Boosting Machine(LGBM)model is used as the classifier for the manually extracted data,which achieved top performance with 94.72%accuracy,94.72%f1-score,94.72 recall,and 94.72 precision.In object detection based model,The Random Forest Classifier(RFC)model showed the highest 96.43%accuracy in predicting hearing loss level,with a F1-score of 96.43%,recall of 96.43%,and precision of 96.45%.Conclusion Our proposed automated approach for audiogram digitization and hearing loss classification performs comparably to traditional methods and otolaryngologists'interpretations.This system can potentially assist otolaryngologists in providing more timely and effective treatment by quickly and accurately classifying hearing loss.
基金supported by the“Human Resources Program in Energy Technology”of the Korea Institute of Energy Technology Evaluation and Planning(KETEP)and granted financial resources from the Ministry of Trade,Industry,and Energy,Korea(No.20204010600090).
文摘This research aims to enhance Clinical Decision Support Systems(CDSS)within Wireless Body Area Networks(WBANs)by leveraging advanced machine learning techniques.Specifically,we target the challenges of accurate diagnosis in medical imaging and sequential data analysis using Recurrent Neural Networks(RNNs)with Long Short-Term Memory(LSTM)layers and echo state cells.These models are tailored to improve diagnostic precision,particularly for conditions like rotator cuff tears in osteoporosis patients and gastrointestinal diseases.Traditional diagnostic methods and existing CDSS frameworks often fall short in managing complex,sequential medical data,struggling with long-term dependencies and data imbalances,resulting in suboptimal accuracy and delayed decisions.Our goal is to develop Artificial Intelligence(AI)models that address these shortcomings,offering robust,real-time diagnostic support.We propose a hybrid RNN model that integrates SimpleRNN,LSTM layers,and echo state cells to manage long-term dependencies effectively.Additionally,we introduce CG-Net,a novel Convolutional Neural Network(CNN)framework for gastrointestinal disease classification,which outperforms traditional CNN models.We further enhance model performance through data augmentation and transfer learning,improving generalization and robustness against data scarcity and imbalance.Comprehensive validation,including 5-fold cross-validation and metrics such as accuracy,precision,recall,F1-score,and Area Under the Curve(AUC),confirms the models’reliability.Moreover,SHapley Additive exPlanations(SHAP)and Local Interpretable Model-agnostic Explanations(LIME)are employed to improve model interpretability.Our findings show that the proposed models significantly enhance diagnostic accuracy and efficiency,offering substantial advancements in WBANs and CDSS.
文摘This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) model.Accurate meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support systems.Simulation of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and time-consuming.Therefore,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological parameters.Comprehensive evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South directions.The performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological parameters.Results show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single station.However,accuracy is slightly compromised when predicting wind speed components.Root mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of V-component.In conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.
文摘BACKGROUND The increased expression of G3BP1 was positively correlated with the prognosis of liver failure.AIM To investigate the effect of G3BP1 on the prognosis of acute liver failure(ALF)and acute-on-chronic liver failure(ACLF)after the treatment of artificial liver support system(ALSS).METHODS A total of 244 patients with ALF and ACLF were enrolled in this study.The levels of G3BP1 on admission and at discharge were detected.The validation set of 514 patients was collected to verify the predicted effect of G3BP1 and the viability of prognosis.RESULTS This study was shown that lactate dehydrogenase(LDH),alpha-fetoprotein(AFP)and prothrombin time were closely related to the prognosis of patients.After the ALSS treatment,the patient’amount of decreased G3BP1 index in difference of G3BP1 between the value of discharge and admission(difG3BP1)<0 group had a nearly 10-fold increased risk of progression compared with the amount of increased G3BP1 index.The subgroup analysis showed that the difG3BP1<0 group had a higher risk of progression,regardless of model for end-stage liver disease high-risk or low-risk group.At the same time,compared with the inflam matory marks[tumor necrosis factor-α,interleukin(IL)-1βand IL-18],G3BP1 had higher discrimination and was more stable in the model analysis and validation set.When combined with AFP and LDH,concordance index was respectively 0.84 and 0.8 in training and validation cohorts.CONCLUSION This study indicated that G3BP1 could predict the prognosis of ALF or ACLF patients treated with ALSS.The combination of G3BP1,AFP and LDH could accurately evaluate the disease condition and predict the clinical endpoint of patients.
文摘In recent years,decision support systems(DSSs)have successfully deployed ontologies in their architecture.The result of such a use is information systems that assist users and organizations in semi-structured decision-making activities.Visitors from throughout Iran travel to different cities and regions every year,and they need help making their choices.Some of these tourists are unable to visit the beautiful areas of the destination city due to a lack of awareness.In this study,we design an ontology-based spatial DSS to find entertainment and tourism centers in Arak,Iran.The objective is to provide users with recommendations appropriate for the location,time,age group,type of activity,and other factors.In this model,the demands and concerns of tourists have been managed by creating a domain Web Ontology Language(OWL)for entertainment centers as a knowledge base in the Protégéenvironment.The developed webbased DSS operates on a client-server architecture using technologies such as Werkzeug and Flask.As a result,it makes it possible to ontology reasoning based on the HermiT engine to choose the right center and conduct a semantic search on classes related to the appropriate point of interest.The main distinction between the proposed methodology and the previous studies on spatial DSS is that criteria are object properties in an ontology.Therefore,decision support relies on real-time reasoning rather than transforming criteria into geospatial layers.The evaluation results confirmed efficient interaction with this system,purposeful information retrieval,and rapid decision-making process.The results also indicated that searching for a POI(point of interest)in the study area using the developed system is at least 30%more successful than a search engine or social media.Moreover,to overcome the cold start problem,the proposed technique might be utilized in conjunction with the POI recommender systems.
文摘Background: Infertility is a complex disorder with significant psycho-social and economic consequences. It globally affects 10% - 15% of couples. In Cameroon, little is known about what women do to overcome the psychosocial aspects of the disease. Objectives: This study aimed to identify the support systems and coping strategies of infertile women attending the outpatient consultation unit of the Gynaecological Endoscopic Surgery and Reproductive Teaching Hospital (CHRACERH), Yaoundé, Cameroon. Methods: A hospital-based cross-sectional study was conducted from the 14th of March to the 6th of April 2023 at CHRACERH Yaoundé. A total of 190 participants were recruited using a convenience sampling method. Data regarding socio-demographic characteristics, support systems and coping strategies were collected using a pretested questionnaire. Descriptive and analytic statistics were conducted using SPSS version 25. Results: The mean age of participants was 39.52 ± 7.64 years. The majority 78.9% of participants were workers (public, private sector, or traders) and were Christians 95.8%. The most common source of psychological support was from family 76.8 and husbands 72.63%. Most of the participants 89.5% resorted to prayer and getting busy 48.4% as a coping strategy. There was no statistically significant relationship between coping strategies and psychological disorders p > 0.05. Conclusion: The main support system of participants was family, husband, and friends. Prayer, getting busy and adoption were the most common coping strategies. There is a need for the Ministry of Public Health and other stakeholders to put in place other support systems and coping strategies (FELICIA) used elsewhere and provide adequate health education and infection control to prevent infertility in Cameroon.
文摘This study outlines the essential nursing strategies employed in the care of 10 patients experiencing vascular vagal reflex, managed with artificial liver support systems. It highlights a holistic nursing approach tailored to the distinct clinical manifestations of these patients. Key interventions included early detection of psychological issues prior to initiating treatment, the implementation of comprehensive health education, meticulous monitoring of vital signs throughout the therapy, prompt emergency interventions when needed, adherence to prescribed medication protocols, and careful post-treatment observations including venous catheter management. Following rigorous treatment and dedicated nursing care, 7 patients demonstrated significant improvement and were subsequently discharged.
文摘With the beginning of the information systems’ spreading, people started thinking about using them for making business decisions. Computer technology solutions, such as the Decision Support System, make the decision-making process less complex and simpler for problem-solving. In order to make a high-quality business decision, managers need to have a great deal of appropriate information. Nonetheless, this complicates the process of making appropriate decisions. In a situation like that, the possibility of using DSS is quite logical. The aim of this paper is to find out the intended use of DSS for medium and large business organizations in USA by applying the Technology Acceptance Model (TAM). Different models were developed in order to understand and predict the use of information systems, but the information systems community mostly used TAM to ensure this issue. The purpose of the research model is to determine the elements of analysis that contribute to these results. The sample for the research consisted of the target group that was supposed to have completed an online questionnaire about the manager’s use of DSS in medium and large American companies. The information obtained from the questionnaires was analyzed through the SPSS statistical software. The research has indicated that, this is primarily used due to a significant level of Perceived usefulness and For the Perceived ease of use.
文摘The rapid development of the digital economy,driven by artificial intelligence(AI),is profoundly transforming traditional accounting practices and business models.The emergence of innovative models such as“wisdom+accounting”and“wisdom+financial sharing”has opened new avenues for enhancing enterprise decision-making support systems.This paper delves into the application of AI technology in accounting,examining its practical implementation and associated challenges.To mitigate potential risks arising from technological advancements,enterprises should establish robust and efficient intelligent financial systems.Additionally,organizations should foster a mindset of change within their accounting teams,improve the application of management information systems,strengthen internal control mechanisms,and continuously upgrade intelligent accounting software.Financial managers must adapt to the evolving landscape and proactively adjust their career paths and development strategies.
文摘Objective:To design and implement a specialized nurse decision support system in the Department of Neurology and explore its effectiveness in preventing stroke-associated pneumonia(SAP).Methods:A decision support module for specialized nurses was developed based on SAP-graded prevention strategies.A total of 664 neurology inpatients admitted to The First People’s Hospital of Xuzhou between July 2023 and September 2023 were selected as the conventional group,receiving standard nursing care.Another 704 neurology inpatients admitted between October 2023 and December 2023 were selected as the experimental group,receiving SAP-graded prevention strategies under the specialized nurse decision support system.The incidence of SAP in the two groups was compared.The occurrence of SAP was recorded using the Acute Ischemic Stroke-Associated Pneumonia Risk(A2DS2)scoring system.Swallowing function was evaluated using the Water Swallow Test(WST),and quality of life was assessed using the Swallowing Quality of Life(SWAL-QOL)scale.Results:The incidence of SAP in the experimental group was significantly lower than in the conventional group(P<0.05).After nursing interventions,the WST scores in the experimental group were lower,while the SWAL-QOL scores were higher compared to the conventional group(P<0.05).Conclusion:The design and implementation of a specialized nurse decision support system in the Department of Neurology significantly reduced the incidence of SAP in neurology inpatients,improved swallowing function,and enhanced quality of life.This approach shows promise for widespread application.
文摘To address the challenges of current college student employment management,this study designed and implemented a machine learning-based decision support system for college student employment management.The system collects and analyzes multidimensional data,uses machine learning algorithms for prediction and matching,provides personalized employment guidance for students,and provides decision support for universities and enterprises.The research results indicate that the system can effectively improve the efficiency and accuracy of employment guidance,promote school-enterprise cooperation,and achieve a win-win situation for all parties.
文摘The focus of this paper is on a new concept framework and an architecture of an intelligent decision support syetem generator (DSSG). The framework results from a synthesis of two existing frameworks: Spragae and Bonczek, while the architecture is a rooted partial order network. From our experience which comes out of the project of DSSG, we consider that they are keys of further research and development of DSS.
文摘According to basic connotation and design principles of ecocity, a comparatively integrated index system is constructed in the paper. And at the same time using hierarchy grey comprehensive evaluation method, a hierarchy grey comprehensive evaluation model of ecocity is established, then on the basis of the model, a comprehensive evaluation support system is developed, and the theoretical guidance supplied for construction of ecocity is provided.
文摘In order to solve existing problems about the method of establishing traditional system structure of decision support system(DSS), O S chart is applied to describe object oriented system structure of general DSS, and a new method of eight specific steps is proposed to establish object oriented system structure of DSS by using the method of O S chart, which is applied successfully to the development of the DSS for the energy system ecology engineering research of the Wangheqiu country. Supplying many scientific effective computing models, decision support ways and a lot of accurate reliable decision data, the DSS plays a critical part in helping engineering researchers to make correct decisions. Because the period for developing the DSS is relatively shorter, the new way improves the efficiency of establishing DSS greatly. It also makes the DSS of system structure more flexible and easy to expand.
基金This project was supported by the National Natural Science Foundation of China (70371052).
文摘The concept of organization decision support system （ODSS） is defined according to practical applications and novel understanding. And a framework for ODSS is designed. The framework has three components： infrastructure, decision-making process and decision execution process. Infrastructure is responsible to transfer data and information. Decision-making process is the ODSS＇s soul to support decision-making. Decision execution process is to evaluate and execute decision results derived from decision-making process. The framework presents a kind of logic architecture. An example is given to verify and analyze the framework. The analysis shows that the framework has practical values, and has also reference values for understanding ODSS and for theoretical studies.
