Energy management is an inspiring domain in developing of renewable energy sources.However,the growth of decentralized energy production is revealing an increased complexity for power grid managers,inferring more qual...Energy management is an inspiring domain in developing of renewable energy sources.However,the growth of decentralized energy production is revealing an increased complexity for power grid managers,inferring more quality and reliability to regulate electricity flows and less imbalance between electricity production and demand.The major objective of an energy management system is to achieve optimum energy procurement and utilization throughout the organization,minimize energy costs without affecting production,and minimize environmental effects.Modern energy management is an essential and complex subject because of the excessive consumption in residential buildings,which necessitates energy optimization and increased user comfort.To address the issue of energy management,many researchers have developed various frameworks;while the objective of each framework was to sustain a balance between user comfort and energy consumption,this problem hasn’t been fully solved because of how difficult it is to solve it.An inclusive and Intelligent Energy Management System(IEMS)aims to provide overall energy efficiency regarding increased power generation,increase flexibility,increase renewable generation systems,improve energy consumption,reduce carbon dioxide emissions,improve stability,and reduce energy costs.Machine Learning(ML)is an emerging approach that may be beneficial to predict energy efficiency in a better way with the assistance of the Internet of Energy(IoE)network.The IoE network is playing a vital role in the energy sector for collecting effective data and usage,resulting in smart resource management.In this research work,an IEMS is proposed for Smart Cities(SC)using the ML technique to better resolve the energy management problem.The proposed system minimized the energy consumption with its intelligent nature and provided better outcomes than the previous approaches in terms of 92.11% accuracy,and 7.89% miss-rate.展开更多
Hepatitis B virus(HBV)reactivation is a clinically significant challenge in disease management.This review explores the immunological mechanisms underlying HBV reactivation,emphasizing disease progression and manageme...Hepatitis B virus(HBV)reactivation is a clinically significant challenge in disease management.This review explores the immunological mechanisms underlying HBV reactivation,emphasizing disease progression and management.It delves into host immune responses and reactivation’s delicate balance,spanning innate and adaptive immunity.Viral factors’disruption of this balance,as are interac-tions between viral antigens,immune cells,cytokine networks,and immune checkpoint pathways,are examined.Notably,the roles of T cells,natural killer cells,and antigen-presenting cells are discussed,highlighting their influence on disease progression.HBV reactivation’s impact on disease severity,hepatic flares,liver fibrosis progression,and hepatocellular carcinoma is detailed.Management strategies,including anti-viral and immunomodulatory approaches,are critically analyzed.The role of prophylactic anti-viral therapy during immunosuppressive treatments is explored alongside novel immunotherapeutic interventions to restore immune control and prevent reactivation.In conclusion,this compre-hensive review furnishes a holistic view of the immunological mechanisms that propel HBV reactivation.With a dedicated focus on understanding its implic-ations for disease progression and the prospects of efficient management stra-tegies,this article contributes significantly to the knowledge base.The more profound insights into the intricate interactions between viral elements and the immune system will inform evidence-based approaches,ultimately enhancing disease management and elevating patient outcomes.The dynamic landscape of management strategies is critically scrutinized,spanning anti-viral and immunomodulatory approaches.The role of prophylactic anti-viral therapy in preventing reactivation during immunosuppressive treatments and the potential of innovative immunotherapeutic interventions to restore immune control and proactively deter reactivation.展开更多
Moyamoya disease (MMD) is a condition characterized by the gradual narrowing and blockage of blood vessels in the brain, specifically those in the circle of Willis and the arteries that supply it. This results in redu...Moyamoya disease (MMD) is a condition characterized by the gradual narrowing and blockage of blood vessels in the brain, specifically those in the circle of Willis and the arteries that supply it. This results in reduced blood flow and oxygen to the brain, leading to progressive symptoms and potential complications. The underlying pathophysiological mechanism remains elucidated. However, recent studies have highlighted numerous etiologic factors: abnormal immune complex responses, susceptibility genes, branched-chain amino acids, antibodies, heritable diseases, and acquired diseases, which may be the great potential triggers for the development of moyamoya disease. Its clinical presentation has varying degrees from transient asymptomatic events to significant neurological deficits. Moyamoya disease (MMD) shows different patterns in children and adults. Children with MMD are more susceptible to ischemic events due to decreased blood flow to the brain. Conversely, adults with MMD are more prone to hemorrhagic events involving brain bleeding. Children with MMD may experience a range of symptoms including motor impairments, sensory issues, seizures, headaches, dizziness, cognitive delays, or ongoing neurological problems. Although adults may present with similar clinical symptoms as children, they are more prone to experiencing sudden onset intraventricular, subarachnoid, or intracerebral hemorrhages. One of the challenges in moyamoya disease is the potential for misdiagnosis or delayed diagnosis, particularly when physicians fail to consider MMD as a possible cause in stroke patients. This review aims to provide a comprehensive overview of recent global studies on the pathophysiology of MMD, along with advancements in its management. Additionally, the review will delve into various surgical treatment options for MMD, as well as its rare occurrence alongside atrioventricular malformations. Exciting prospects include the use of autologous bone marrow transplant and the potential role of Connexin 43 protein treatment in the development of moyamoya disease.展开更多
Moyamoya disease(MMD),characterized by progressive internal carotid artery stenosis and collateral vessel formation,prompts cerebral perfusion complications and is stratified into idiopathic and Moyamoya syndrome subt...Moyamoya disease(MMD),characterized by progressive internal carotid artery stenosis and collateral vessel formation,prompts cerebral perfusion complications and is stratified into idiopathic and Moyamoya syndrome subtypes.A multifa-ceted approach toward MMD management addresses cerebral infarctions through revascularization surgery and adjunctive medical therapy,while also navigating risks such as intracranial hemorrhage and cerebral infarction resulting from arte-rial stenosis and fragile collateral vessels.Addressing antithrombotic management reveals a potential role for treatments like antiplatelet agents and anticoagulants,despite the ambiguous contribution of thrombosis to MMD-related infarctions and the critical balance between preventing ischemic events and averting hemo-rrhagic complications.Transcranial doppler has proven useful in thromboembolic detection,despite persisting challenges concerning the efficacy and safety of an-tithrombotic treatments.Furthermore,antihypertensive interventions aim to ma-nage blood pressure meticulously,especially during intracerebral hemorrhage,with recommendations and protocols varying based on the patient’s hypertension status.Additionally,lipid-lowering therapeutic strategies,particularly employing statins,are appraised for their possible beneficial role in MMD management,even as comprehensive data from disease-specific clinical trials remains elusive.Com-prehensive guidelines and protocols to navigate the multifaceted therapeutic ave-nues for MMD,while maintaining a delicate balance between efficacy and safety,warrant further meticulous research and development.This protocol manuscript seeks to elucidate the various aspects and challenges imbued in managing and navigating through the complex landscape of MMD treatment.展开更多
Objective: By the end of 2021, the aging rate of China’s population is 18.9%, and the prevalence rate of chronic diseases in the elderly population is increasing year by year, and chronic diseases have become the mai...Objective: By the end of 2021, the aging rate of China’s population is 18.9%, and the prevalence rate of chronic diseases in the elderly population is increasing year by year, and chronic diseases have become the main causes of death and health threats of Chinese residents. Therefore, how to manage this huge group well is crucial. This paper analyzes the value of health education in the process of health management for patients with chronic diseases. Methods: 102 patients with chronic diseases treated from January 2021 to December 2021 were divided into control group and experimental group by random number table method. The control group was given routine health management while the experimental group was given health education based on the control group, and the implementation effect was analyzed. Results: After management, the scores of chronic disease knowledge in the experimental group were significantly higher than those in the control group, and the dimensions of ESCA were higher than those in the control group, and P < 0.05;Conclusion: The implementation of health education in the process of chronic disease health management is helpful to improve patients’ self-care ability and better control disease progression.展开更多
This paper analyzes how artificial intelligence (AI) automation can improve warehouse management compared to emerging technologies like drone usage. Specifically, we evaluate AI’s impact on crucial warehouse function...This paper analyzes how artificial intelligence (AI) automation can improve warehouse management compared to emerging technologies like drone usage. Specifically, we evaluate AI’s impact on crucial warehouse functions—inventory tracking, order fulfillment, and logistics efficiency. Our findings indicate AI automation enables real-time inventory visibility, optimized picking routes, and dynamic delivery scheduling, which drones cannot match. AI better leverages data insights for intelligent decision-making across warehouse operations, supporting improved productivity and lower operating costs.展开更多
Objective: To analyze the effect of health management on improving the awareness rate of disease prevention and treatment in patients with prehypertension, so as to provide guidance for clinical management of patients...Objective: To analyze the effect of health management on improving the awareness rate of disease prevention and treatment in patients with prehypertension, so as to provide guidance for clinical management of patients with prehypertension. Methods: 108 patients diagnosed with prehypertension in our hospital were divided into a control group and an experimental group. The control group was not given management measures, while the experimental group was given health management. The incidence of hypertension and cognition level of hypertension knowledge were compared between the two groups after management. Results: The incidence of hypertension in the experimental group was 7.41% lower than that in the control group 29.63%. The cognitive level of hypertension in the patients (66.54 ± 1.25) was significantly higher than that in the patients without health management (41.45 ± 2.45), and P < 0.05;Conclusion: For patients with prehypertension, the implementation of health management is helpful to improve their cognition of hypertension, master related prevention knowledge, and reduce the incidence of hypertension.展开更多
A learning management system(LMS)is a software or web based application,commonly utilized for planning,designing,and assessing a particular learning procedure.Generally,the LMS offers a method of creating and deliveri...A learning management system(LMS)is a software or web based application,commonly utilized for planning,designing,and assessing a particular learning procedure.Generally,the LMS offers a method of creating and delivering content to the instructor,monitoring students’involvement,and validating their outcomes.Since mental health issues become common among studies in higher education globally,it is needed to properly determine it to improve mental stabi-lity.This article develops a new seven spot lady bird feature selection with opti-mal sparse autoencoder(SSLBFS-OSAE)model to assess students’mental health on LMS.The major aim of the SSLBFS-OSAE model is to determine the proper health status of the students with respect to depression,anxiety,and stress(DAS).The SSLBFS-OSAE model involves a new SSLBFS model to elect a useful set of features.In addition,OSAE model is applied for the classification of mental health conditions and the performance can be improved by the use of cuckoo search optimization(CSO)based parameter tuning process.The design of CSO algorithm for optimally tuning the SAE parameters results in enhanced classifica-tion outcomes.For examining the improved classifier results of the SSLBFS-OSAE model,a comprehensive results analysis is done and the obtained values highlighted the supremacy of the SSLBFS model over its recent methods interms of different measures.展开更多
By coordination and cooperation between multi-agents, this paper proposes the network of intelligent agents which can reduce the search time needed to finding a parking place. Based on multi-agent model, the fined sol...By coordination and cooperation between multi-agents, this paper proposes the network of intelligent agents which can reduce the search time needed to finding a parking place. Based on multi-agent model, the fined solution is designed to help drivers in finding a parking space at anytime and anywhere. Three services are offered: the search for a vacant place, directions to a parking space and booking a place for parking. The results of this study generated by the platform MATSim transport simulation, show that our approach optimizes the operation of vehicles in a parking need with the aim of reducing congestion, and improve traffic flow in urban area. A comparison between the first method where the vehicles are random and the second method where vehicles are steered to vacant parking spaces shows that the minimization of time looking for a parking space could improve circulation by reducing the number of cars in the morning of 2% and 0.7% of the evening. In addition, the traffic per hour per day was reduced by approximately 4.17%.展开更多
Tumor necrosis factor-α(TNF-α)antagonists,the first biologics approved for treating patients with inflammatory bowel disease(IBD),are effective for the induction and maintenance of remission and significantly improv...Tumor necrosis factor-α(TNF-α)antagonists,the first biologics approved for treating patients with inflammatory bowel disease(IBD),are effective for the induction and maintenance of remission and significantly improving prognosis.However,up to one-third of treated patients show primary nonresponse(PNR)to anti-TNF-αtherapies,and 23%-50%of IBD patients experience loss of response(LOR)to these biologics during subsequent treatment.There is still no recognized predictor for evaluating the efficacy of anti-TNF drugs.This review summarizes the existing predictors of PNR and LOR to anti-TNF in IBD patients.Most predictors remain controversial,and only previous surgical history,disease manifestations,drug concentrations,antidrug antibodies,serum albumin,some biologic markers,and some genetic markers may be potentially predictive.In addition,we also discuss the next steps of treatment for patients with PNR or LOR to TNF antagonists.Therapeutic drug monitoring plays an important role in treatment selection.Dose escalation,combination therapy,switching to a different anti-TNF drug,or switching to a biologic with a different mechanism of action can be selected based on the concentration of the drug and/or antidrug antibodies.展开更多
There is great heterogeneity among inflammatory bowel disease(IBD)patients in terms of pathogenesis,clinical manifestation,response to treatment,and prognosis,which requires the individualized and precision management...There is great heterogeneity among inflammatory bowel disease(IBD)patients in terms of pathogenesis,clinical manifestation,response to treatment,and prognosis,which requires the individualized and precision management of patients.Many studies have focused on prediction biomarkers and models for assessing IBD disease type,activity,severity,and prognosis.During the era of biologics,how to predict the response and side effects of patients to different treatments and how to quickly recognize the loss of response have also become important topics.Multiomics is a promising area for investigating the complex network of IBD pathogenesis.Integrating numerous amounts of data requires the use of artificial intelligence.展开更多
Introduction: Obesity is a preventable health condition, yet it remains a complex relapsing global health conundrum, triggering an array of comorbidities, including diabetes, dyslipidemia, hypertension, and mental hea...Introduction: Obesity is a preventable health condition, yet it remains a complex relapsing global health conundrum, triggering an array of comorbidities, including diabetes, dyslipidemia, hypertension, and mental health decline. This review intends to highlight the success of semaglutide for its therapeutic intervention for weight loss management in diabetics and non-diabetics and HbA1c reduction in type 2 diabetics. Methods: We searched and systematically reviewed the literature from within the past ten years on semaglutide utilization for weight loss and HbA1c reduction. Databases investigated included PMC, JAMA, Nature Medicine, and The Lancet, resulting in four original research articles that were systematically reviewed. Web consultations with WHO, CDC, and Healthy People 2030 were conducted to ascertain epidemiological obesity and diabetes data. AAFP and USPSTF references were included for obesity management and preventive care guidelines. Results: Based on results from systematically reviewing four original research studies, semaglutide can effectively reduce elevated weight and HbA1c, using the once-weekly subcutaneous injection formulation. A composite average percent weight loss of 8.27% (16 - 20 pounds) and an average HbA1c percent reduction rate of 1.07% (3 - 4 points) were attained. There were no major adverse events reported from any of the four original research studies related to the drug. Discussion: With evidence from several studies after its FDA approval, semaglutide delivers a promise for weight loss management and HbA1c reduction for appropriate patient populations. Clinician and patient education on its proper use should be continuously revisited.展开更多
Objective:To provide a comprehensive review on the existing research and evidence regarding artificial intelligence(AI)applications in the assessment and management of urinary stone disease.Methods:A comprehensive lit...Objective:To provide a comprehensive review on the existing research and evidence regarding artificial intelligence(AI)applications in the assessment and management of urinary stone disease.Methods:A comprehensive literature review was performed using PubMed,Scopus,and Google Scholar databases to identify publications about innovative concepts or supporting applications of AI in the improvement of every medical procedure relating to stone disease.The terms“endourology”,“artificial intelligence”,“machine learning”,and“urolithiasis”were used for searching eligible reports,while review articles,articles referring to automated procedures without AI application,and editorial comments were excluded from the final set of publications.The search was conducted from January 2000 to September 2023 and included manuscripts in the English language.Results: A total of 69 studies were identified.The main subjects were related to the detection of urinary stones,the prediction of the outcome of conservative or operative management,the optimization of operative procedures,and the elucidation of the relation of urinary stone chemistry with various factors.Conclusion: AI represents a useful tool that provides urologists with numerous amenities,which explains the fact that it has gained ground in the pursuit of stone disease management perfection.The effectiveness of diagnosis and therapy can be increased by using it as an alternative or adjunct to the already existing data.However,little is known concerning the potential of this vast field.Electronic patient records,containing big data,offer AI the opportunity to develop and analyze more precise and efficient diagnostic and treatment algorithms.Nevertheless,the existing applications are not generalizable in real-life practice,and high-quality studies are needed to establish the integration of AI in the management of urinary stone disease.展开更多
Safety is essential when building a strong transportation system.As a key development direction in the global railway system,the intelligent railway has safety at its core,making safety a top priority while pursuing t...Safety is essential when building a strong transportation system.As a key development direction in the global railway system,the intelligent railway has safety at its core,making safety a top priority while pursuing the goals of efficiency,convenience,economy,and environmental friendliness.This paper describes the state of the art and proposes a system architecture for intelligent railway systems.It also focuses on the development of railway safety technology at home and abroad,and proposes the active safety method and technology system based on advanced theoretical methods such as the in-depth integration of cyber–physical systems(CPS),data-driven models,and intelligent computing.Finally,several typical applications are demonstrated to verify the advancement and feasibility of active safety technology in intelligent railway systems.展开更多
Gastro-esophageal reflux disease(GERD)is a condition which is frequently faced by primary care physicians and gastroenterologists.Improving management of GERD is crucial to maximise both patient care and resource util...Gastro-esophageal reflux disease(GERD)is a condition which is frequently faced by primary care physicians and gastroenterologists.Improving management of GERD is crucial to maximise both patient care and resource utilization.In fact,the management of patients with GERD is complex and poses several questions to the clinician who faces them in clinical practice.For instance,many aspects should be considered,including the appropriateness of indication to endoscopy,the quality of the endoscopic examination,the use and interpretation of ambulatory reflux testing,and the choice and management of anti-reflux treatments,i.e.,protonpump inhibitors and surgery.Aim of the present review was to provide a comprehensive update on the clinical management of patients with GERD,through a literature review on the diagnosis and management of patients with GER symptoms.In details,we provide practice-oriented concise answers to clinical questions,with the aim of optimising patient management and healthcare resource use.展开更多
In the context of both the Virtual Power Plant (VPP) and microgrid(MG), the Energy Management System (EMS) is a key decision-maker forintegrating Distributed renewable Energy Resources (DERs) efficiently. TheEMS is re...In the context of both the Virtual Power Plant (VPP) and microgrid(MG), the Energy Management System (EMS) is a key decision-maker forintegrating Distributed renewable Energy Resources (DERs) efficiently. TheEMS is regarded as a strong enabler of providing the optimized schedulingcontrol in operation and management of usage of disperse DERs and RenewableEnergy reSources (RES) such as a small-size wind-turbine (WT) andphotovoltaic (PV) energies. The main objective to be pursued by the EMSis the minimization of the overall operating cost of the MG integrated VPPnetwork. However, the minimization of the power peaks is a new objective andopen issue to a well-functional EMS, along with the maximization of profitin the energy market. Thus, both objectives have to be taken into accountat the same time. Thus, this paper proposes the EMS application incorporatingpower offering strategy applying a nature-inspired algorithm such asParticle Swarm Optimization (PSO) algorithm, in order to find the optimalsolution of the objective function in the context of the overall operating cost,the coordination of DERs, and the energy losses in a MG integrated VPPnetwork. For a fair DERs coordination with minimized power fluctuationsin the power flow, the power offering strategies with an active power controland re-distribution are proposed. Simulation results show that the proposedMG integrated VPP model with PSO-based EMS employing EgalitarianreDistribution (ED) power offering strategy is most feasible option for theoverall operating cost of VPP revenue. The total operating cost of the proposedEMS with ED strategy is 40.98$ compared to 432.8$ of MGs only withoutEMS. It is concluded that each MGs in the proposed VPP model intelligentlyparticipates in energy trading market compliant with the objective function,to minimize the overall cost and the power fluctuation.展开更多
The introduction of several small and large-scale industries,malls,shopping complexes,and domestic applications has significantly increased energy consumption.The aim of the work is to simulate a technically viable an...The introduction of several small and large-scale industries,malls,shopping complexes,and domestic applications has significantly increased energy consumption.The aim of the work is to simulate a technically viable and economically optimum hybrid power system for residential buildings.The proposed micro-grid model includes four power generators:solar power,wind power,Electricity Board(EB)source,and a Diesel Generator(DG)set,with solar and wind power performing as major sources and the EB supply and DG set serving as backup sources.The core issue in direct current to alternate current conversion is harmonics distortion,a five-stage multilevel inverter is employed with the assistance of an intelligent control system is simulated and the optimum system configuration is estimated to reduce harmonics and improve the power quality.The monthly demand for residential buildings is 13-15 Megawatts.So,almost 433 Kilo-Watts(KW)of electricity is required every day,and if it is used for 8 h per day,50-60 KW of electricity is needed per hour.The overall micro-grid model’s operation and performance are established using MATLAB/SIMULINK software,and simulation results are provided.The simulation results show that the developed system is both cost-effective and environment friendly resulting in yearly cost reductions.展开更多
Computerized power management system with fast and optimal communication network overcomes all major dicrepencies of undue or inadequate load relief that were present in old conventional systems. This paper presents t...Computerized power management system with fast and optimal communication network overcomes all major dicrepencies of undue or inadequate load relief that were present in old conventional systems. This paper presents the basic perception and methodology of modern and true intelligent load management scheme in micro grids topology by employing TCP/IP protocol for fast and intelligent switching. The network understudy performs load management and power distribution intelligently in a unified network. Generated power is efficiently distributed among local loads through fast communication system of server in the form of source and clients in the form of loads through TCP/IP. The efficient use of information between server and clients enables to astutely control the load management in a power system of micro grids system. The processing time of above stated system comes out to be 10ms faster than others which ensure very less delay as compared to conventional methods. The Micro Grids system operating through TCP/IP control has been implemented in MATLAB/Simulink and results have been verified.展开更多
Approximately 1.5 billion chronic liver disease(CLD)cases have been estimated worldwide,encompassing a wide range of liver damage severities.Moreover,liver disease causes approximately 1.75 million deaths per year.CLD...Approximately 1.5 billion chronic liver disease(CLD)cases have been estimated worldwide,encompassing a wide range of liver damage severities.Moreover,liver disease causes approximately 1.75 million deaths per year.CLD is typically characterized by the silent and progressive deterioration of liver parenchyma due to an incessant inflammatory process,cell death,over deposition of extracellular matrix proteins,and dysregulated regeneration.Overall,these processes impair the correct function of this vital organ.Cirrhosis and liver cancer are the main complications of CLD,which accounts for 3.5%of all deaths worldwide.Liver transplantation is the optimal therapeutic option for advanced liver damage.The liver is one of the most common organs transplanted;however,only 10%of liver transplants are successful.In this context,regenerative medicine has made significant progress in the design of biomaterials,such as collagen matrix scaffolds,to address the limitations of organ transplantation(e.g.,low donation rates and biocompatibility).Thus,it remains crucial to continue with experimental and clinical studies to validate the use of collagen matrix scaffolds in liver disease.展开更多
Artificial intelligence(AI)technologies and sensors have recently received significant interest in intellectual agriculture.Accelerating the application of AI technologies and agriculture sensors in intellectual agric...Artificial intelligence(AI)technologies and sensors have recently received significant interest in intellectual agriculture.Accelerating the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart agriculture.Automatic irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation techniques.Automatic learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an agronomist.With this motivation,this study develops a modified black widow optimization with a deep belief network-based smart irrigation system(MBWODBN-SIS)for intelligent agriculture.The MBWODBN-SIS algorithm primarily enables the Internet of Things(IoT)based sensors to collect data forwarded to the cloud server for examination purposes.Besides,the MBWODBN-SIS technique applies the deep belief network(DBN)model for different types of irrigation classification:average,high needed,highly not needed,and not needed.The MBWO algorithm is used for the hyperparameter tuning process.A wideranging experiment was conducted,and the comparison study stated the enhanced outcomes of the MBWODBN-SIS approach to other DL models with maximum accuracy of 95.73%.展开更多
文摘Energy management is an inspiring domain in developing of renewable energy sources.However,the growth of decentralized energy production is revealing an increased complexity for power grid managers,inferring more quality and reliability to regulate electricity flows and less imbalance between electricity production and demand.The major objective of an energy management system is to achieve optimum energy procurement and utilization throughout the organization,minimize energy costs without affecting production,and minimize environmental effects.Modern energy management is an essential and complex subject because of the excessive consumption in residential buildings,which necessitates energy optimization and increased user comfort.To address the issue of energy management,many researchers have developed various frameworks;while the objective of each framework was to sustain a balance between user comfort and energy consumption,this problem hasn’t been fully solved because of how difficult it is to solve it.An inclusive and Intelligent Energy Management System(IEMS)aims to provide overall energy efficiency regarding increased power generation,increase flexibility,increase renewable generation systems,improve energy consumption,reduce carbon dioxide emissions,improve stability,and reduce energy costs.Machine Learning(ML)is an emerging approach that may be beneficial to predict energy efficiency in a better way with the assistance of the Internet of Energy(IoE)network.The IoE network is playing a vital role in the energy sector for collecting effective data and usage,resulting in smart resource management.In this research work,an IEMS is proposed for Smart Cities(SC)using the ML technique to better resolve the energy management problem.The proposed system minimized the energy consumption with its intelligent nature and provided better outcomes than the previous approaches in terms of 92.11% accuracy,and 7.89% miss-rate.
文摘Hepatitis B virus(HBV)reactivation is a clinically significant challenge in disease management.This review explores the immunological mechanisms underlying HBV reactivation,emphasizing disease progression and management.It delves into host immune responses and reactivation’s delicate balance,spanning innate and adaptive immunity.Viral factors’disruption of this balance,as are interac-tions between viral antigens,immune cells,cytokine networks,and immune checkpoint pathways,are examined.Notably,the roles of T cells,natural killer cells,and antigen-presenting cells are discussed,highlighting their influence on disease progression.HBV reactivation’s impact on disease severity,hepatic flares,liver fibrosis progression,and hepatocellular carcinoma is detailed.Management strategies,including anti-viral and immunomodulatory approaches,are critically analyzed.The role of prophylactic anti-viral therapy during immunosuppressive treatments is explored alongside novel immunotherapeutic interventions to restore immune control and prevent reactivation.In conclusion,this compre-hensive review furnishes a holistic view of the immunological mechanisms that propel HBV reactivation.With a dedicated focus on understanding its implic-ations for disease progression and the prospects of efficient management stra-tegies,this article contributes significantly to the knowledge base.The more profound insights into the intricate interactions between viral elements and the immune system will inform evidence-based approaches,ultimately enhancing disease management and elevating patient outcomes.The dynamic landscape of management strategies is critically scrutinized,spanning anti-viral and immunomodulatory approaches.The role of prophylactic anti-viral therapy in preventing reactivation during immunosuppressive treatments and the potential of innovative immunotherapeutic interventions to restore immune control and proactively deter reactivation.
文摘Moyamoya disease (MMD) is a condition characterized by the gradual narrowing and blockage of blood vessels in the brain, specifically those in the circle of Willis and the arteries that supply it. This results in reduced blood flow and oxygen to the brain, leading to progressive symptoms and potential complications. The underlying pathophysiological mechanism remains elucidated. However, recent studies have highlighted numerous etiologic factors: abnormal immune complex responses, susceptibility genes, branched-chain amino acids, antibodies, heritable diseases, and acquired diseases, which may be the great potential triggers for the development of moyamoya disease. Its clinical presentation has varying degrees from transient asymptomatic events to significant neurological deficits. Moyamoya disease (MMD) shows different patterns in children and adults. Children with MMD are more susceptible to ischemic events due to decreased blood flow to the brain. Conversely, adults with MMD are more prone to hemorrhagic events involving brain bleeding. Children with MMD may experience a range of symptoms including motor impairments, sensory issues, seizures, headaches, dizziness, cognitive delays, or ongoing neurological problems. Although adults may present with similar clinical symptoms as children, they are more prone to experiencing sudden onset intraventricular, subarachnoid, or intracerebral hemorrhages. One of the challenges in moyamoya disease is the potential for misdiagnosis or delayed diagnosis, particularly when physicians fail to consider MMD as a possible cause in stroke patients. This review aims to provide a comprehensive overview of recent global studies on the pathophysiology of MMD, along with advancements in its management. Additionally, the review will delve into various surgical treatment options for MMD, as well as its rare occurrence alongside atrioventricular malformations. Exciting prospects include the use of autologous bone marrow transplant and the potential role of Connexin 43 protein treatment in the development of moyamoya disease.
文摘Moyamoya disease(MMD),characterized by progressive internal carotid artery stenosis and collateral vessel formation,prompts cerebral perfusion complications and is stratified into idiopathic and Moyamoya syndrome subtypes.A multifa-ceted approach toward MMD management addresses cerebral infarctions through revascularization surgery and adjunctive medical therapy,while also navigating risks such as intracranial hemorrhage and cerebral infarction resulting from arte-rial stenosis and fragile collateral vessels.Addressing antithrombotic management reveals a potential role for treatments like antiplatelet agents and anticoagulants,despite the ambiguous contribution of thrombosis to MMD-related infarctions and the critical balance between preventing ischemic events and averting hemo-rrhagic complications.Transcranial doppler has proven useful in thromboembolic detection,despite persisting challenges concerning the efficacy and safety of an-tithrombotic treatments.Furthermore,antihypertensive interventions aim to ma-nage blood pressure meticulously,especially during intracerebral hemorrhage,with recommendations and protocols varying based on the patient’s hypertension status.Additionally,lipid-lowering therapeutic strategies,particularly employing statins,are appraised for their possible beneficial role in MMD management,even as comprehensive data from disease-specific clinical trials remains elusive.Com-prehensive guidelines and protocols to navigate the multifaceted therapeutic ave-nues for MMD,while maintaining a delicate balance between efficacy and safety,warrant further meticulous research and development.This protocol manuscript seeks to elucidate the various aspects and challenges imbued in managing and navigating through the complex landscape of MMD treatment.
文摘Objective: By the end of 2021, the aging rate of China’s population is 18.9%, and the prevalence rate of chronic diseases in the elderly population is increasing year by year, and chronic diseases have become the main causes of death and health threats of Chinese residents. Therefore, how to manage this huge group well is crucial. This paper analyzes the value of health education in the process of health management for patients with chronic diseases. Methods: 102 patients with chronic diseases treated from January 2021 to December 2021 were divided into control group and experimental group by random number table method. The control group was given routine health management while the experimental group was given health education based on the control group, and the implementation effect was analyzed. Results: After management, the scores of chronic disease knowledge in the experimental group were significantly higher than those in the control group, and the dimensions of ESCA were higher than those in the control group, and P < 0.05;Conclusion: The implementation of health education in the process of chronic disease health management is helpful to improve patients’ self-care ability and better control disease progression.
文摘This paper analyzes how artificial intelligence (AI) automation can improve warehouse management compared to emerging technologies like drone usage. Specifically, we evaluate AI’s impact on crucial warehouse functions—inventory tracking, order fulfillment, and logistics efficiency. Our findings indicate AI automation enables real-time inventory visibility, optimized picking routes, and dynamic delivery scheduling, which drones cannot match. AI better leverages data insights for intelligent decision-making across warehouse operations, supporting improved productivity and lower operating costs.
文摘Objective: To analyze the effect of health management on improving the awareness rate of disease prevention and treatment in patients with prehypertension, so as to provide guidance for clinical management of patients with prehypertension. Methods: 108 patients diagnosed with prehypertension in our hospital were divided into a control group and an experimental group. The control group was not given management measures, while the experimental group was given health management. The incidence of hypertension and cognition level of hypertension knowledge were compared between the two groups after management. Results: The incidence of hypertension in the experimental group was 7.41% lower than that in the control group 29.63%. The cognitive level of hypertension in the patients (66.54 ± 1.25) was significantly higher than that in the patients without health management (41.45 ± 2.45), and P < 0.05;Conclusion: For patients with prehypertension, the implementation of health management is helpful to improve their cognition of hypertension, master related prevention knowledge, and reduce the incidence of hypertension.
基金supported by the Researchers Supporting Program(TUMA-Project-2021-31)supported by the Researchers Supporting Program(TUMA-Project-2021-27)Almaarefa University,Riyadh,Saudi Arabia.
文摘A learning management system(LMS)is a software or web based application,commonly utilized for planning,designing,and assessing a particular learning procedure.Generally,the LMS offers a method of creating and delivering content to the instructor,monitoring students’involvement,and validating their outcomes.Since mental health issues become common among studies in higher education globally,it is needed to properly determine it to improve mental stabi-lity.This article develops a new seven spot lady bird feature selection with opti-mal sparse autoencoder(SSLBFS-OSAE)model to assess students’mental health on LMS.The major aim of the SSLBFS-OSAE model is to determine the proper health status of the students with respect to depression,anxiety,and stress(DAS).The SSLBFS-OSAE model involves a new SSLBFS model to elect a useful set of features.In addition,OSAE model is applied for the classification of mental health conditions and the performance can be improved by the use of cuckoo search optimization(CSO)based parameter tuning process.The design of CSO algorithm for optimally tuning the SAE parameters results in enhanced classifica-tion outcomes.For examining the improved classifier results of the SSLBFS-OSAE model,a comprehensive results analysis is done and the obtained values highlighted the supremacy of the SSLBFS model over its recent methods interms of different measures.
文摘By coordination and cooperation between multi-agents, this paper proposes the network of intelligent agents which can reduce the search time needed to finding a parking place. Based on multi-agent model, the fined solution is designed to help drivers in finding a parking space at anytime and anywhere. Three services are offered: the search for a vacant place, directions to a parking space and booking a place for parking. The results of this study generated by the platform MATSim transport simulation, show that our approach optimizes the operation of vehicles in a parking need with the aim of reducing congestion, and improve traffic flow in urban area. A comparison between the first method where the vehicles are random and the second method where vehicles are steered to vacant parking spaces shows that the minimization of time looking for a parking space could improve circulation by reducing the number of cars in the morning of 2% and 0.7% of the evening. In addition, the traffic per hour per day was reduced by approximately 4.17%.
文摘Tumor necrosis factor-α(TNF-α)antagonists,the first biologics approved for treating patients with inflammatory bowel disease(IBD),are effective for the induction and maintenance of remission and significantly improving prognosis.However,up to one-third of treated patients show primary nonresponse(PNR)to anti-TNF-αtherapies,and 23%-50%of IBD patients experience loss of response(LOR)to these biologics during subsequent treatment.There is still no recognized predictor for evaluating the efficacy of anti-TNF drugs.This review summarizes the existing predictors of PNR and LOR to anti-TNF in IBD patients.Most predictors remain controversial,and only previous surgical history,disease manifestations,drug concentrations,antidrug antibodies,serum albumin,some biologic markers,and some genetic markers may be potentially predictive.In addition,we also discuss the next steps of treatment for patients with PNR or LOR to TNF antagonists.Therapeutic drug monitoring plays an important role in treatment selection.Dose escalation,combination therapy,switching to a different anti-TNF drug,or switching to a biologic with a different mechanism of action can be selected based on the concentration of the drug and/or antidrug antibodies.
基金the Youth Program of National Natural Science Foundation of China,No.82000526the National High Level Hospital Clinical Research Funding,No.2022-PUMCH-A-072the National College Students’Innovation and Entrepreneurship Training Program,No.2022zglc06083.
文摘There is great heterogeneity among inflammatory bowel disease(IBD)patients in terms of pathogenesis,clinical manifestation,response to treatment,and prognosis,which requires the individualized and precision management of patients.Many studies have focused on prediction biomarkers and models for assessing IBD disease type,activity,severity,and prognosis.During the era of biologics,how to predict the response and side effects of patients to different treatments and how to quickly recognize the loss of response have also become important topics.Multiomics is a promising area for investigating the complex network of IBD pathogenesis.Integrating numerous amounts of data requires the use of artificial intelligence.
文摘Introduction: Obesity is a preventable health condition, yet it remains a complex relapsing global health conundrum, triggering an array of comorbidities, including diabetes, dyslipidemia, hypertension, and mental health decline. This review intends to highlight the success of semaglutide for its therapeutic intervention for weight loss management in diabetics and non-diabetics and HbA1c reduction in type 2 diabetics. Methods: We searched and systematically reviewed the literature from within the past ten years on semaglutide utilization for weight loss and HbA1c reduction. Databases investigated included PMC, JAMA, Nature Medicine, and The Lancet, resulting in four original research articles that were systematically reviewed. Web consultations with WHO, CDC, and Healthy People 2030 were conducted to ascertain epidemiological obesity and diabetes data. AAFP and USPSTF references were included for obesity management and preventive care guidelines. Results: Based on results from systematically reviewing four original research studies, semaglutide can effectively reduce elevated weight and HbA1c, using the once-weekly subcutaneous injection formulation. A composite average percent weight loss of 8.27% (16 - 20 pounds) and an average HbA1c percent reduction rate of 1.07% (3 - 4 points) were attained. There were no major adverse events reported from any of the four original research studies related to the drug. Discussion: With evidence from several studies after its FDA approval, semaglutide delivers a promise for weight loss management and HbA1c reduction for appropriate patient populations. Clinician and patient education on its proper use should be continuously revisited.
文摘Objective:To provide a comprehensive review on the existing research and evidence regarding artificial intelligence(AI)applications in the assessment and management of urinary stone disease.Methods:A comprehensive literature review was performed using PubMed,Scopus,and Google Scholar databases to identify publications about innovative concepts or supporting applications of AI in the improvement of every medical procedure relating to stone disease.The terms“endourology”,“artificial intelligence”,“machine learning”,and“urolithiasis”were used for searching eligible reports,while review articles,articles referring to automated procedures without AI application,and editorial comments were excluded from the final set of publications.The search was conducted from January 2000 to September 2023 and included manuscripts in the English language.Results: A total of 69 studies were identified.The main subjects were related to the detection of urinary stones,the prediction of the outcome of conservative or operative management,the optimization of operative procedures,and the elucidation of the relation of urinary stone chemistry with various factors.Conclusion: AI represents a useful tool that provides urologists with numerous amenities,which explains the fact that it has gained ground in the pursuit of stone disease management perfection.The effectiveness of diagnosis and therapy can be increased by using it as an alternative or adjunct to the already existing data.However,little is known concerning the potential of this vast field.Electronic patient records,containing big data,offer AI the opportunity to develop and analyze more precise and efficient diagnostic and treatment algorithms.Nevertheless,the existing applications are not generalizable in real-life practice,and high-quality studies are needed to establish the integration of AI in the management of urinary stone disease.
基金supported by the 2021 Chinese Academy of Engineering(CAE)International Top-level Forum on Engineering Science and Technology,“Safety and Governance of the High-Speed Railway”。
文摘Safety is essential when building a strong transportation system.As a key development direction in the global railway system,the intelligent railway has safety at its core,making safety a top priority while pursuing the goals of efficiency,convenience,economy,and environmental friendliness.This paper describes the state of the art and proposes a system architecture for intelligent railway systems.It also focuses on the development of railway safety technology at home and abroad,and proposes the active safety method and technology system based on advanced theoretical methods such as the in-depth integration of cyber–physical systems(CPS),data-driven models,and intelligent computing.Finally,several typical applications are demonstrated to verify the advancement and feasibility of active safety technology in intelligent railway systems.
文摘Gastro-esophageal reflux disease(GERD)is a condition which is frequently faced by primary care physicians and gastroenterologists.Improving management of GERD is crucial to maximise both patient care and resource utilization.In fact,the management of patients with GERD is complex and poses several questions to the clinician who faces them in clinical practice.For instance,many aspects should be considered,including the appropriateness of indication to endoscopy,the quality of the endoscopic examination,the use and interpretation of ambulatory reflux testing,and the choice and management of anti-reflux treatments,i.e.,protonpump inhibitors and surgery.Aim of the present review was to provide a comprehensive update on the clinical management of patients with GERD,through a literature review on the diagnosis and management of patients with GER symptoms.In details,we provide practice-oriented concise answers to clinical questions,with the aim of optimising patient management and healthcare resource use.
文摘In the context of both the Virtual Power Plant (VPP) and microgrid(MG), the Energy Management System (EMS) is a key decision-maker forintegrating Distributed renewable Energy Resources (DERs) efficiently. TheEMS is regarded as a strong enabler of providing the optimized schedulingcontrol in operation and management of usage of disperse DERs and RenewableEnergy reSources (RES) such as a small-size wind-turbine (WT) andphotovoltaic (PV) energies. The main objective to be pursued by the EMSis the minimization of the overall operating cost of the MG integrated VPPnetwork. However, the minimization of the power peaks is a new objective andopen issue to a well-functional EMS, along with the maximization of profitin the energy market. Thus, both objectives have to be taken into accountat the same time. Thus, this paper proposes the EMS application incorporatingpower offering strategy applying a nature-inspired algorithm such asParticle Swarm Optimization (PSO) algorithm, in order to find the optimalsolution of the objective function in the context of the overall operating cost,the coordination of DERs, and the energy losses in a MG integrated VPPnetwork. For a fair DERs coordination with minimized power fluctuationsin the power flow, the power offering strategies with an active power controland re-distribution are proposed. Simulation results show that the proposedMG integrated VPP model with PSO-based EMS employing EgalitarianreDistribution (ED) power offering strategy is most feasible option for theoverall operating cost of VPP revenue. The total operating cost of the proposedEMS with ED strategy is 40.98$ compared to 432.8$ of MGs only withoutEMS. It is concluded that each MGs in the proposed VPP model intelligentlyparticipates in energy trading market compliant with the objective function,to minimize the overall cost and the power fluctuation.
文摘The introduction of several small and large-scale industries,malls,shopping complexes,and domestic applications has significantly increased energy consumption.The aim of the work is to simulate a technically viable and economically optimum hybrid power system for residential buildings.The proposed micro-grid model includes four power generators:solar power,wind power,Electricity Board(EB)source,and a Diesel Generator(DG)set,with solar and wind power performing as major sources and the EB supply and DG set serving as backup sources.The core issue in direct current to alternate current conversion is harmonics distortion,a five-stage multilevel inverter is employed with the assistance of an intelligent control system is simulated and the optimum system configuration is estimated to reduce harmonics and improve the power quality.The monthly demand for residential buildings is 13-15 Megawatts.So,almost 433 Kilo-Watts(KW)of electricity is required every day,and if it is used for 8 h per day,50-60 KW of electricity is needed per hour.The overall micro-grid model’s operation and performance are established using MATLAB/SIMULINK software,and simulation results are provided.The simulation results show that the developed system is both cost-effective and environment friendly resulting in yearly cost reductions.
文摘Computerized power management system with fast and optimal communication network overcomes all major dicrepencies of undue or inadequate load relief that were present in old conventional systems. This paper presents the basic perception and methodology of modern and true intelligent load management scheme in micro grids topology by employing TCP/IP protocol for fast and intelligent switching. The network understudy performs load management and power distribution intelligently in a unified network. Generated power is efficiently distributed among local loads through fast communication system of server in the form of source and clients in the form of loads through TCP/IP. The efficient use of information between server and clients enables to astutely control the load management in a power system of micro grids system. The processing time of above stated system comes out to be 10ms faster than others which ensure very less delay as compared to conventional methods. The Micro Grids system operating through TCP/IP control has been implemented in MATLAB/Simulink and results have been verified.
文摘Approximately 1.5 billion chronic liver disease(CLD)cases have been estimated worldwide,encompassing a wide range of liver damage severities.Moreover,liver disease causes approximately 1.75 million deaths per year.CLD is typically characterized by the silent and progressive deterioration of liver parenchyma due to an incessant inflammatory process,cell death,over deposition of extracellular matrix proteins,and dysregulated regeneration.Overall,these processes impair the correct function of this vital organ.Cirrhosis and liver cancer are the main complications of CLD,which accounts for 3.5%of all deaths worldwide.Liver transplantation is the optimal therapeutic option for advanced liver damage.The liver is one of the most common organs transplanted;however,only 10%of liver transplants are successful.In this context,regenerative medicine has made significant progress in the design of biomaterials,such as collagen matrix scaffolds,to address the limitations of organ transplantation(e.g.,low donation rates and biocompatibility).Thus,it remains crucial to continue with experimental and clinical studies to validate the use of collagen matrix scaffolds in liver disease.
基金The APC was funded by Universidad Tecnológica Indoamérica with funding code INV-0012-002.
文摘Artificial intelligence(AI)technologies and sensors have recently received significant interest in intellectual agriculture.Accelerating the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart agriculture.Automatic irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation techniques.Automatic learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an agronomist.With this motivation,this study develops a modified black widow optimization with a deep belief network-based smart irrigation system(MBWODBN-SIS)for intelligent agriculture.The MBWODBN-SIS algorithm primarily enables the Internet of Things(IoT)based sensors to collect data forwarded to the cloud server for examination purposes.Besides,the MBWODBN-SIS technique applies the deep belief network(DBN)model for different types of irrigation classification:average,high needed,highly not needed,and not needed.The MBWO algorithm is used for the hyperparameter tuning process.A wideranging experiment was conducted,and the comparison study stated the enhanced outcomes of the MBWODBN-SIS approach to other DL models with maximum accuracy of 95.73%.
