Infected necrotizing pancreatitis(INP)remains a life-threatening complication of acute pancreatitis.Despite advancements such as endoscopic ultrasound(EUS)-guided drainage,lumen-apposing metal stents,and protocolized ...Infected necrotizing pancreatitis(INP)remains a life-threatening complication of acute pancreatitis.Despite advancements such as endoscopic ultrasound(EUS)-guided drainage,lumen-apposing metal stents,and protocolized step-up strate-gies,the clinical practice remains heterogeneous,with variability in endoscopic strategies,procedural timing,device selection,and adjunctive techniques contri-buting to inconsistent outcomes.This review synthesizes current evidence to contribute to a structured framework integrating multidisciplinary team decision-making,advanced imaging(three-dimensional reconstruction,contrast-enhanced computed tomography/magnetic resonance imaging),EUS assessment,and biomarker-driven risk stratification(C-reactive protein,procalcitonin)to optimize patient selection,intervention timing,and complication management.Key stan-dardization components include endoscopic assessment and procedural strate-gies,optimal timing of intervention,personalized approaches for complex pan-creatic collections,and techniques to reduce the number of endoscopic debride-ments and mitigate complications.This work aims to enhance clinical outcomes,minimize practice heterogeneity,and establish a foundation for future research and guideline development in endoscopic management of INP.展开更多
To meet the challenge of mismatches between power supply and demand,modern buildings must schedule flexible energy loads in order to improve the efficiency of power grids.Furthermore,it is essential to understand the ...To meet the challenge of mismatches between power supply and demand,modern buildings must schedule flexible energy loads in order to improve the efficiency of power grids.Furthermore,it is essential to understand the effectiveness of flexibility management strategies under different climate conditions and extreme weather events.Using both typical and extreme weather data from cities in five major climate zones of China,this study investigates the energy flexibility potential of an office building under three short-term HVAC management strategies in the context of different climates.The results show that the peak load flexibility and overall energy performance of the three short-term strategies were affected by the surrounding climate conditions.The peak load reduction rate of the pre-cooling and zone temperature reset strategies declined linearly as outdoor temperature increased.Under extreme climate conditions,the daily peak-load time was found to be over two hours earlier than under typical conditions,and the intensive solar radiation found in the extreme conditions can weaken the correlation between peak load reduction and outdoor temperature,risking the ability of a building’s HVAC system to maintain a comfortable indoor environment.展开更多
This study investigated the application and the application value of intelligent emergency in emergency management in the big data environment.It addresses the neglect of the application value(performance)measurement ...This study investigated the application and the application value of intelligent emergency in emergency management in the big data environment.It addresses the neglect of the application value(performance)measurement of intelligent emergency,further improving the effectiveness of intelligent emergency management.First,approximately 3,900 documents from the intelligent emergency field are analyzed to determine the future research trend in intelligent emergency management.The socio-technical theory concerning technical and social systems is introduced.The emergency management system concepts of“technology enabling”and“enabling value creation”are defined according to bibliometric analysis and socio-technical theory.Second,a research framework that includes technology enabling and enabling value creation for the decision-making paradigm in emergency management according to the big data environment is constructed.A detailed analysis approach from intelligent emergency technology enabling to enabling value creation in emergency management is proposed.Finally,earthquake disasters are taken as examples,and specific analyses of the intelligent emergency enabling and enabling value creation are explored;enabling value creation is discussed based on measurable indicators.The clear concept of emergency management system technology enabling and enabling value creation,as well as the detailed analysis approach from intelligent emergency technology enabling to enabling value creation,provide a theoretical bases for scholars and practitioners to evaluate the value(performance)of intelligent emergency for the first time.展开更多
In the contemporary medical landscape,the burgeoning interest in natural therapies,particularly for managing gastrointestinal disorders,has brought traditional Chinese medicine(TCM)to the forefront.This article explai...In the contemporary medical landscape,the burgeoning interest in natural therapies,particularly for managing gastrointestinal disorders,has brought traditional Chinese medicine(TCM)to the forefront.This article explains the core principles and clinical applications of TCM in treating these conditions,furthering the discourse through an examination of integrated TCM strategies,as demonstrated in the study by Zhou et al.While TCM has shown promising clinical outcomes,it encounters significant hurdles in standardization,mechanistic research,and clinical validation.Future investigations should aim to solidify the scientific underpinnings of TCM and expand its use in gastrointestinal disease management,striving for a seamless fusion of traditional and contemporary medical practices.展开更多
Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.T...Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.To contribute to a better understanding of the state of the art of smart techniques for engineering projects,this paper provides a comprehensive review of multi-criteria decision-making(MCDM)techniques,intelligent techniques,and their applications in CEM.First,a comprehensive framework detailing smart technologies for construction projects is developed.Next,the characteristics of CEM are summarized.A bibliometric review is then conducted to investigate the keywords,journals,and clusters related to the application of smart techniques in CEM during 2000-2022.Recent advancements in intelligent techniques are also discussed under the following six topics:①big data technology;②computer vision;③speech recognition;④natural language processing;⑤machine learning;and⑥knowledge representation,understanding,and reasoning.The applications of smart techniques are then illustrated via underground space exploitation.Finally,future research directions for the sustainable development of smart construction are highlighted.展开更多
This paper introduces a high-precision bandgap reference(BGR)designed for battery management systems(BMS),fea-turing an ultra-low temperature coefficient(TC)and line sensitivity(LS).The BGR employs a current-mode sche...This paper introduces a high-precision bandgap reference(BGR)designed for battery management systems(BMS),fea-turing an ultra-low temperature coefficient(TC)and line sensitivity(LS).The BGR employs a current-mode scheme with chopped op-amps and internal clock generators to eliminate op-amp offset.A low dropout regulator(LDO)and a pre-regula-tor enhance output driving and LS,respectively.Curvature compensation enhances the TC by addressing higher-order nonlinear-ity.These approaches,effective near room temperature,employs trimming at both 20 and 60°C.When combined with fixed cur-vature correction currents,it achieves an ultra-low TC for each chip.Implemented in a CMOS 180 nm process,the BGR occu-pies 0.548 mm²and operates at 2.5 V with 84μA current draw from a 5 V supply.An average TC of 2.69 ppm/℃ with two-point trimming and 0.81 ppm/℃ with multi-point trimming are achieved over the temperature range of-40 to 125℃.It accommo-dates a load current of 1 mA and an LS of 42 ppm/V,making it suitable for precise BMS applications.展开更多
The rapid advent in artificial intelligence and big data has revolutionized the dynamic requirement in the demands of the computing resource for executing specific tasks in the cloud environment.The process of achievi...The rapid advent in artificial intelligence and big data has revolutionized the dynamic requirement in the demands of the computing resource for executing specific tasks in the cloud environment.The process of achieving autonomic resource management is identified to be a herculean task due to its huge distributed and heterogeneous environment.Moreover,the cloud network needs to provide autonomic resource management and deliver potential services to the clients by complying with the requirements of Quality-of-Service(QoS)without impacting the Service Level Agreements(SLAs).However,the existing autonomic cloud resource managing frameworks are not capable in handling the resources of the cloud with its dynamic requirements.In this paper,Coot Bird Behavior Model-based Workload Aware Autonomic Resource Management Scheme(CBBM-WARMS)is proposed for handling the dynamic requirements of cloud resources through the estimation of workload that need to be policed by the cloud environment.This CBBM-WARMS initially adopted the algorithm of adaptive density peak clustering for workloads clustering of the cloud.Then,it utilized the fuzzy logic during the process of workload scheduling for achieving the determining the availability of cloud resources.It further used CBBM for potential Virtual Machine(VM)deployment that attributes towards the provision of optimal resources.It is proposed with the capability of achieving optimal QoS with minimized time,energy consumption,SLA cost and SLA violation.The experimental validation of the proposed CBBMWARMS confirms minimized SLA cost of 19.21%and reduced SLA violation rate of 18.74%,better than the compared autonomic cloud resource managing frameworks.展开更多
With the deployment of ultra-dense low earth orbit(LEO)satellite constellations,LEO satellite access network(LEO-SAN)is envisioned to achieve global Internet coverage.Meanwhile,the civil aviation communications have i...With the deployment of ultra-dense low earth orbit(LEO)satellite constellations,LEO satellite access network(LEO-SAN)is envisioned to achieve global Internet coverage.Meanwhile,the civil aviation communications have increased dramatically,especially for providing airborne Internet services.However,due to dynamic service demands and onboard LEO resources over time and space,it poses huge challenges in satellite-aircraft access and service management in ultra-dense LEO satellite networks(UDLSN).In this paper,we propose a deep reinforcement learning-based approach for ultra-dense LEO satellite-aircraft access and service management.Firstly,we develop an airborne Internet architecture based on UDLSN and design a management mechanism including medium earth orbit satellites to guarantee lightweight management.Secondly,considering latency-sensitive and latency-tolerant services,we formulate the problem of satellite-aircraft access and service management for civil aviation to ensure service continuity.Finally,we propose a proximal policy optimization-based access and service management algorithm to solve the formulated problem.Simulation results demonstrate the convergence and effectiveness of the proposed algorithm with satisfying the service continuity when applying to the UDLSN.展开更多
Modern aircraft tend to use fuel thermal management systems to cool onboard heat sources.However,the design of heat transfer architectures for fuel thermal management systems relies on the experience of the engineers ...Modern aircraft tend to use fuel thermal management systems to cool onboard heat sources.However,the design of heat transfer architectures for fuel thermal management systems relies on the experience of the engineers and lacks theoretical guidance.This paper proposes a concise graph representation method based on graph theory for fuel thermal management systems,which can represent all possible connections between subsystems.A generalized optimization algorithm is proposed for fuel thermal management system architecture to minimize the heat sink.This algorithm can autonomously arrange subsystems with heat production differences and efficiently utilize the architecture of the fuel heat sink.At the same time,two evaluation indices are proposed from the perspective of subsystems.These indices intuitively and clearly show that the reason for the high efficiency of heat sink utilization is the balanced and moderate cooling of each subsystem and verify the rationality of the architecture optimization method.A set of simulations are also conducted,which demonstrate that the fuel tank temperature has no effect on the performance of the architecture.This paper provides a reference for the architectural design of aircraft fuel thermal management systems.The metrics used in this paper can also be utilized to evaluate the existing architecture.展开更多
Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and ...Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation systems.Fog computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end nodes.Consisting of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud computing.In smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system reliability.To address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog environments.This framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation systems.The FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud environments.Through simulation-based executions,tasks are allocated to the nearest available nodes with minimum latency.In the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of tasks.Upon successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.展开更多
Kawasaki disease(KD)is a significant pediatric vasculitis known for its potential to cause severe coronary artery complications.Despite the effectiveness of initial treatments,such as intravenous immunoglobulin,KD pat...Kawasaki disease(KD)is a significant pediatric vasculitis known for its potential to cause severe coronary artery complications.Despite the effectiveness of initial treatments,such as intravenous immunoglobulin,KD patients can experience long-term cardiovascular issues,as evidenced by a recent case report of an adult who suffered a ST-segment elevation myocardial infarction due to previous KD in the World Journal of Clinical Cases.This editorial emphasizes the critical need for long-term management and regular surveillance to prevent such complications.By drawing on recent research and case studies,we advocate for a structured approach to follow-up care that includes routine cardiac evaluations and preventive measures.展开更多
BACKGROUND Effective health management for high-risk stroke populations is essential.The hospital-community-home(HCH)collaborative health management(CHM)model leverages resources from hospitals,communities,and familie...BACKGROUND Effective health management for high-risk stroke populations is essential.The hospital-community-home(HCH)collaborative health management(CHM)model leverages resources from hospitals,communities,and families.By integrating patient information across these three domains,it facilitates the delivery of tailored guidance,health risk assessments,and three-in-one health education.AIM To explore the effects of the HCH-CHM model on stroke risk reduction in highrisk populations.METHODS In total,110 high-risk stroke patients screened in the community from January 2019 to January 2023 were enrolled,with 52 patients in the control group receiving routine health education and 58 in the observation group receiving HCH-CHM model interventions based on routine health education.Stroke awareness scores,health behavior levels,medication adherence,blood pressure,serum biochemical markers(systolic/diastolic blood pressure,total cholesterol,and triglyceride),and psychological measures(self-rating anxiety/depression scale)were evaluated and compared between groups.RESULTS The observation group showed statistically significant improvements in stroke awareness scores and health behavior levels compared to the control group(P<0.05),with notable enhancements in lifestyle and dietary habits(P<0.05)and reductions in postintervention systolic blood pressure,diastolic blood pressure,total cholesterol,triglyceride,self-rating anxiety scale,and self-rating depression scale scores(P<0.05).CONCLUSION The HCH-CHM model had a significant positive effect on high-risk stroke populations,effectively increasing disease awareness,improving health behavior and medication adherence,and appropriately ameliorating blood pressure,serum biochemical marker levels,and negative psychological symptoms.展开更多
This article provides a comprehensive analysis of the study by Hou et al,focusing on the complex interplay between psychological and physical factors in the postoperative recovery(POR)of patients with perianal disease...This article provides a comprehensive analysis of the study by Hou et al,focusing on the complex interplay between psychological and physical factors in the postoperative recovery(POR)of patients with perianal diseases.The study sheds light on how illness perception,anxiety,and depression significantly influence recovery outcomes.Hou et al developed a predictive model that demonstrated high accuracy in identifying patients at risk of poor recovery.The article explores the critical role of pre-operative psychological assessment,highlighting the need for mental health support and personalized recovery plans in enhancing POR quality.A multidisciplinary approach,integrating mental health professionals with surgeons,anesthesiologists,and other specialists,is emphasized to ensure comprehensive care for patients.The study’s findings serve as a call to integrate psychological care into surgical practice to optimize outcomes for patients with perianal diseases.展开更多
This editorial highlights a recently published study examining the effectiveness of music therapy combined with motivational interviewing(MI)in addressing an-xiety and depression among young and middle-aged patients f...This editorial highlights a recently published study examining the effectiveness of music therapy combined with motivational interviewing(MI)in addressing an-xiety and depression among young and middle-aged patients following percuta-neous coronary intervention.It further explores existing evidence and potential future research directions for MI in postoperative rehabilitation and chronic disease management.MI aims to facilitate behavioral change and promote healthier lifestyles by fostering a trusting relationship with patients and enhan-cing intrinsic motivation.Research has demonstrated its effectiveness in posto-perative recovery for oncological surgery,stroke,organ transplants,and gastroin-testinal procedures,as well as in managing chronic conditions such as diabetes,obesity,and periodontal disease.The approach is patient-centered,adaptable,cost-effective,and easily replicable,though its limitations include reliance on the therapist’s expertise,variability in individual responses,and insufficient long-term follow-up studies.Future research could focus on developing individualized and precise intervention models,exploring applications in digital health management,and confirming long-term outcomes to provide more compre-hensive support for patient rehabilitation.展开更多
Diabetic retinopathy(DR)remains a leading cause of vision impairment and blindness among individuals with diabetes,necessitating innovative approaches to screening and management.This editorial explores the transforma...Diabetic retinopathy(DR)remains a leading cause of vision impairment and blindness among individuals with diabetes,necessitating innovative approaches to screening and management.This editorial explores the transformative potential of artificial intelligence(AI)and machine learning(ML)in revolutionizing DR care.AI and ML technologies have demonstrated remarkable advancements in enhancing the accuracy,efficiency,and accessibility of DR screening,helping to overcome barriers to early detection.These technologies leverage vast datasets to identify patterns and predict disease progression with unprecedented precision,enabling clinicians to make more informed decisions.Furthermore,AI-driven solutions hold promise in personalizing management strategies for DR,incorpo-rating predictive analytics to tailor interventions and optimize treatment path-ways.By automating routine tasks,AI can reduce the burden on healthcare providers,allowing for a more focused allocation of resources towards complex patient care.This review aims to evaluate the current advancements and applic-ations of AI and ML in DR screening,and to discuss the potential of these techno-logies in developing personalized management strategies,ultimately aiming to improve patient outcomes and reduce the global burden of DR.The integration of AI and ML in DR care represents a paradigm shift,offering a glimpse into the future of ophthalmic healthcare.展开更多
Background: The availability of essential medicines and medical supplies is crucial for effectively delivering healthcare services. In Zambia, the Logistics Management Information System (LMIS) is a key tool for manag...Background: The availability of essential medicines and medical supplies is crucial for effectively delivering healthcare services. In Zambia, the Logistics Management Information System (LMIS) is a key tool for managing the supply chain of these commodities. This study aimed to evaluate the effectiveness of LMIS in ensuring the availability of essential medicines and medical supplies in public hospitals in the Copperbelt Province of Zambia. Materials and Methods: From February to April 2022, a cross-sectional study was conducted in 12 public hospitals across the Copperbelt Province. Data were collected using structured questionnaires, checklists, and stock control cards. The study assessed LMIS availability, training, and knowledge among pharmacy personnel, as well as data accuracy, product availability, and order fill rates. Descriptive statistics were used to analyse the data. Results: All surveyed hospitals had LMIS implemented and were using eLMIS as the primary LMIS. Only 47% and 48% of pharmacy personnel received training in eLMIS and Essential Medicines Logistics Improvement Program (EMLIP), respectively. Most personnel demonstrated good knowledge of LMIS, with 77.7% able to log in to eLMIS Facility Edition, 76.6% able to locate stock control cards in the system, and 78.7% able to perform transactions. However, data accuracy from physical and electronic records varied from 0% to 60%, and product availability ranged from 50% to 80%. Order fill rates from Zambia Medicines and Medical Supplies Agency (ZAMMSA) were consistently below 30%. Discrepancies were observed between physical stock counts and eLMIS records. Conclusion: This study found that most hospitals in the Copperbelt Province of Zambia have implemented LMIS use. While LMIS implementation is high in the Copperbelt Province of Zambia, challenges such as low training levels, data inaccuracies, low product availability, and order fill rates persist. Addressing these issues requires a comprehensive approach, including capacity building, data quality improvement, supply chain coordination, and investment in infrastructure and human resources. Strengthening LMIS effectiveness is crucial for improving healthcare delivery and patient outcomes in Zambia.展开更多
BACKGROUND Managing critical care emergencies in children with autism spectrum disorder(ASD)presents unique challenges due to their distinct sensory sensitivities,communication difficulties,and behavioral issues.Effec...BACKGROUND Managing critical care emergencies in children with autism spectrum disorder(ASD)presents unique challenges due to their distinct sensory sensitivities,communication difficulties,and behavioral issues.Effective strategies and protocols are essential for optimal care in these high-stress situations.AIM To systematically evaluate and synthesize current evidence on best practices for managing critical care emergencies in children with ASD.The review focuses on key areas,including sensory-friendly environments,communication strategies,behavioral management,and the role of multidisciplinary approaches.METHODS A comprehensive search was conducted across major medical databases,including PubMed,Embase,and Cochrane Library,for studies published between 2000 and 2023.Studies were selected based on their relevance to critical care management in children with ASD,encompassing randomized controlled trials,observational studies,qualitative research,and case studies.Data were extracted and analyzed to identify common themes,successful strategies,and areas for improvement.RESULTS The review identified 50 studies that met the inclusion criteria.Findings highlighted the importance of creating sensory-friendly environments,utilizing effective communication strategies,and implementing individualized behavioral management plans.These findings,derived from a comprehensive review of current evidence,provide valuable insights into the best practices for managing critical care emergencies in children with ASD.Sensory modifications,such as reduced lighting and noise,visual aids,and augmentative and alternative communication tools,enhanced patient comfort and cooperation.The involvement of multidisciplinary teams was crucial in delivering holistic care.Case studies provided practical insights and underscored the need for continuous refi-nement of protocols.CONCLUSION The review emphasizes the need for a tailored approach to managing critical care emergencies for children with ASD.Sensory-friendly adjustments,effective communication,and behavioral strategies supported by a mul-tidisciplinary team are integral to improving outcomes.Despite progress,ongoing refinement of care practices and protocols is necessary.This ongoing process addresses remaining challenges and engages healthcare professionals in continuous improvement of care for children with ASD in critical settings.展开更多
Climate change is becoming a major issue for agriculture and the well-being of farmers. The objective of this article is to identify and analyze the production factors that may influence the competitiveness level of a...Climate change is becoming a major issue for agriculture and the well-being of farmers. The objective of this article is to identify and analyze the production factors that may influence the competitiveness level of agricultural operations, as well as to establish a structural and functional typology of these farms. Using Principal component analysis (PCA) combined with hierarchical ascending classification (HAC) on 250 farmers, the study was able to set farms typology. Furthermore, variance analysis and econometric models (linear et quadratic) were also used for in-depth analysis. The results show the existence of three groups of farm (GA, GB, GC): GA (19.7%), GB (65.3%), and GC (15%). Drought spells and flood are the main climatic risks affecting rain-fed farm operations. For irrigated crops such as rice, the major constraints remain bird attacks, the invasion of pests and nematodes. Climate variability significantly increases the prevalence of morbidities in the region by raising the number of inactive individuals. This significantly and differentially affects the outcomes of these assets. Health expenditures represent a significant share (GB: 12% and GC: 11%) and a non-negligible share (GA: 8.4%). However, larger participations (GC) show better economic performance due to economies of scale, but all categories would benefit from adopting appropriate strategies to reduce losses and increase their resilience.展开更多
The development of sustainable sludge management systems requires looking at them with a new vision in which the concepts of SD(Sustainable Development)must integrate those of CE(Circular Economy),both concepts subjec...The development of sustainable sludge management systems requires looking at them with a new vision in which the concepts of SD(Sustainable Development)must integrate those of CE(Circular Economy),both concepts subject to the principles of TD(Thermodynamics),thus allowing the adoption of actions that are all the more effective the more complete the evaluation of the social dimension has been.This involves a new“Way of thinking”which sees the sludge system as the“Locomotive”of the entire wastewater/sludge treatment train and is developed through“Ways of acting”which includes both“Technical”actions to maximize recoveries of useful materials and/or or energy,and“Socio/Institutional”actions to overcome barriers linked to local cultures and traditions,also considering that the specific local context heavily influences the choices capable of satisfying the concepts of CE.It follows the need of issuing realistic and applicable regulations and overcoming social barriers,such as lack of infrastructure and/or qualified personnel,to achieve an effective integration of the concepts of CE with the more general ones of sustainability.展开更多
BACKGROUND Inadequate glycemic control in patients with type 2 diabetes(T2DM)is a major public health problem and a significant risk factor for the progression of diabetic complications.AIM To evaluate the effects of ...BACKGROUND Inadequate glycemic control in patients with type 2 diabetes(T2DM)is a major public health problem and a significant risk factor for the progression of diabetic complications.AIM To evaluate the effects of intensive and supportive glycemic management strategies over a 12-month period in individuals with T2DM with glycated hemoglobin(HbA1c)≥10%and varying backgrounds of glycemic control.METHODS This prospective observational study investigated glycemic control in patients with poorly controlled T2DM over 12 months.Participants were categorized into four groups based on prior glycemic history:Newly diagnosed,previously well controlled with recent worsening,previously off-target but now worsening,and HbA1c consistently above 10%.HbA1c levels were monitored quarterly,and patients received medical,educational,and dietary support as needed.The analysis focused on the success rates of good glycemic control and the associated factors within each group.RESULTS The study showed significant improvements in HbA1c levels in all participants.The most significant improvement was observed in individuals newly diagnosed with diabetes:65%achieved an HbA1c target of≤7%.The results varied between participants with different glycemic control histories,followed by decreasing success rates:39%in participants with previously good glycemic control,21%in participants whose glycemic control had deteriorated compared to before,and only 10%in participants with persistently poor control,with mean HbA1c levels of 6.3%,7.7%,8.2%,and 9.7%,respectively.After one year,65.2%of the“newly diagnosed patients”,39.3%in the“previously controlled group”,21.9%in the“previously off-target but now worsened'”group and 10%in the“poorly controlled from the start”group had achieved HbA1c levels of 7 and below.CONCLUSION In poorly controlled diabetes,the rate at which treatment goals are achieved is associated with the glycemic background characteristics,emphasizing the need for tailored strategies.Therefore,different and comprehensive treatment approaches are needed for patients with persistent uncontrolled diabetes.展开更多
基金Supported by the Education and Teaching Reform Project of the First Clinical College of Chongqing Medical University,No.CMER202305Natural Science Foundation of Xizang Autonomous Region,No.XZ2024ZR-ZY100(Z)Program for Youth Innovation in Future Medicine,Chongqing Medical University,China,No.W0138.
文摘Infected necrotizing pancreatitis(INP)remains a life-threatening complication of acute pancreatitis.Despite advancements such as endoscopic ultrasound(EUS)-guided drainage,lumen-apposing metal stents,and protocolized step-up strate-gies,the clinical practice remains heterogeneous,with variability in endoscopic strategies,procedural timing,device selection,and adjunctive techniques contri-buting to inconsistent outcomes.This review synthesizes current evidence to contribute to a structured framework integrating multidisciplinary team decision-making,advanced imaging(three-dimensional reconstruction,contrast-enhanced computed tomography/magnetic resonance imaging),EUS assessment,and biomarker-driven risk stratification(C-reactive protein,procalcitonin)to optimize patient selection,intervention timing,and complication management.Key stan-dardization components include endoscopic assessment and procedural strate-gies,optimal timing of intervention,personalized approaches for complex pan-creatic collections,and techniques to reduce the number of endoscopic debride-ments and mitigate complications.This work aims to enhance clinical outcomes,minimize practice heterogeneity,and establish a foundation for future research and guideline development in endoscopic management of INP.
基金National Key R&D Program of China of the 13th Five-Year Plan(No.2018YFD1100704)。
文摘To meet the challenge of mismatches between power supply and demand,modern buildings must schedule flexible energy loads in order to improve the efficiency of power grids.Furthermore,it is essential to understand the effectiveness of flexibility management strategies under different climate conditions and extreme weather events.Using both typical and extreme weather data from cities in five major climate zones of China,this study investigates the energy flexibility potential of an office building under three short-term HVAC management strategies in the context of different climates.The results show that the peak load flexibility and overall energy performance of the three short-term strategies were affected by the surrounding climate conditions.The peak load reduction rate of the pre-cooling and zone temperature reset strategies declined linearly as outdoor temperature increased.Under extreme climate conditions,the daily peak-load time was found to be over two hours earlier than under typical conditions,and the intensive solar radiation found in the extreme conditions can weaken the correlation between peak load reduction and outdoor temperature,risking the ability of a building’s HVAC system to maintain a comfortable indoor environment.
基金the National Natural Science Foundation of China(Grant No.:71771061).
文摘This study investigated the application and the application value of intelligent emergency in emergency management in the big data environment.It addresses the neglect of the application value(performance)measurement of intelligent emergency,further improving the effectiveness of intelligent emergency management.First,approximately 3,900 documents from the intelligent emergency field are analyzed to determine the future research trend in intelligent emergency management.The socio-technical theory concerning technical and social systems is introduced.The emergency management system concepts of“technology enabling”and“enabling value creation”are defined according to bibliometric analysis and socio-technical theory.Second,a research framework that includes technology enabling and enabling value creation for the decision-making paradigm in emergency management according to the big data environment is constructed.A detailed analysis approach from intelligent emergency technology enabling to enabling value creation in emergency management is proposed.Finally,earthquake disasters are taken as examples,and specific analyses of the intelligent emergency enabling and enabling value creation are explored;enabling value creation is discussed based on measurable indicators.The clear concept of emergency management system technology enabling and enabling value creation,as well as the detailed analysis approach from intelligent emergency technology enabling to enabling value creation,provide a theoretical bases for scholars and practitioners to evaluate the value(performance)of intelligent emergency for the first time.
基金Supported by the 2023 Government Funded Project of the Outstanding Talents Training Program in Clinical Medicine,No.ZF2023165Key Research and Development Projects of Hebei Province,No.18277731DNatural Science Foundation of Hebei Province,No.H202423105.
文摘In the contemporary medical landscape,the burgeoning interest in natural therapies,particularly for managing gastrointestinal disorders,has brought traditional Chinese medicine(TCM)to the forefront.This article explains the core principles and clinical applications of TCM in treating these conditions,furthering the discourse through an examination of integrated TCM strategies,as demonstrated in the study by Zhou et al.While TCM has shown promising clinical outcomes,it encounters significant hurdles in standardization,mechanistic research,and clinical validation.Future investigations should aim to solidify the scientific underpinnings of TCM and expand its use in gastrointestinal disease management,striving for a seamless fusion of traditional and contemporary medical practices.
基金funded by the project of Guangdong Provincial Basic and Applied Basic Research Fund Committee(2022A1515240073)the Pearl River Talent Recruitment Program(2019CX01G338),Guangdong Province.
文摘Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.To contribute to a better understanding of the state of the art of smart techniques for engineering projects,this paper provides a comprehensive review of multi-criteria decision-making(MCDM)techniques,intelligent techniques,and their applications in CEM.First,a comprehensive framework detailing smart technologies for construction projects is developed.Next,the characteristics of CEM are summarized.A bibliometric review is then conducted to investigate the keywords,journals,and clusters related to the application of smart techniques in CEM during 2000-2022.Recent advancements in intelligent techniques are also discussed under the following six topics:①big data technology;②computer vision;③speech recognition;④natural language processing;⑤machine learning;and⑥knowledge representation,understanding,and reasoning.The applications of smart techniques are then illustrated via underground space exploitation.Finally,future research directions for the sustainable development of smart construction are highlighted.
基金supported by the National Natural Science Foundation of China(NSFC)under grant No.62204235。
文摘This paper introduces a high-precision bandgap reference(BGR)designed for battery management systems(BMS),fea-turing an ultra-low temperature coefficient(TC)and line sensitivity(LS).The BGR employs a current-mode scheme with chopped op-amps and internal clock generators to eliminate op-amp offset.A low dropout regulator(LDO)and a pre-regula-tor enhance output driving and LS,respectively.Curvature compensation enhances the TC by addressing higher-order nonlinear-ity.These approaches,effective near room temperature,employs trimming at both 20 and 60°C.When combined with fixed cur-vature correction currents,it achieves an ultra-low TC for each chip.Implemented in a CMOS 180 nm process,the BGR occu-pies 0.548 mm²and operates at 2.5 V with 84μA current draw from a 5 V supply.An average TC of 2.69 ppm/℃ with two-point trimming and 0.81 ppm/℃ with multi-point trimming are achieved over the temperature range of-40 to 125℃.It accommo-dates a load current of 1 mA and an LS of 42 ppm/V,making it suitable for precise BMS applications.
文摘The rapid advent in artificial intelligence and big data has revolutionized the dynamic requirement in the demands of the computing resource for executing specific tasks in the cloud environment.The process of achieving autonomic resource management is identified to be a herculean task due to its huge distributed and heterogeneous environment.Moreover,the cloud network needs to provide autonomic resource management and deliver potential services to the clients by complying with the requirements of Quality-of-Service(QoS)without impacting the Service Level Agreements(SLAs).However,the existing autonomic cloud resource managing frameworks are not capable in handling the resources of the cloud with its dynamic requirements.In this paper,Coot Bird Behavior Model-based Workload Aware Autonomic Resource Management Scheme(CBBM-WARMS)is proposed for handling the dynamic requirements of cloud resources through the estimation of workload that need to be policed by the cloud environment.This CBBM-WARMS initially adopted the algorithm of adaptive density peak clustering for workloads clustering of the cloud.Then,it utilized the fuzzy logic during the process of workload scheduling for achieving the determining the availability of cloud resources.It further used CBBM for potential Virtual Machine(VM)deployment that attributes towards the provision of optimal resources.It is proposed with the capability of achieving optimal QoS with minimized time,energy consumption,SLA cost and SLA violation.The experimental validation of the proposed CBBMWARMS confirms minimized SLA cost of 19.21%and reduced SLA violation rate of 18.74%,better than the compared autonomic cloud resource managing frameworks.
基金supported in part by the National Key R&D Program of China under Grant 2020YFB1806104in part by Innovation and Entrepreneurship of Jiangsu Province High-level Talent Program+1 种基金in part by Natural Sciences and Engineering Research Council of Canada (NSERC)the support from Huawei
文摘With the deployment of ultra-dense low earth orbit(LEO)satellite constellations,LEO satellite access network(LEO-SAN)is envisioned to achieve global Internet coverage.Meanwhile,the civil aviation communications have increased dramatically,especially for providing airborne Internet services.However,due to dynamic service demands and onboard LEO resources over time and space,it poses huge challenges in satellite-aircraft access and service management in ultra-dense LEO satellite networks(UDLSN).In this paper,we propose a deep reinforcement learning-based approach for ultra-dense LEO satellite-aircraft access and service management.Firstly,we develop an airborne Internet architecture based on UDLSN and design a management mechanism including medium earth orbit satellites to guarantee lightweight management.Secondly,considering latency-sensitive and latency-tolerant services,we formulate the problem of satellite-aircraft access and service management for civil aviation to ensure service continuity.Finally,we propose a proximal policy optimization-based access and service management algorithm to solve the formulated problem.Simulation results demonstrate the convergence and effectiveness of the proposed algorithm with satisfying the service continuity when applying to the UDLSN.
文摘Modern aircraft tend to use fuel thermal management systems to cool onboard heat sources.However,the design of heat transfer architectures for fuel thermal management systems relies on the experience of the engineers and lacks theoretical guidance.This paper proposes a concise graph representation method based on graph theory for fuel thermal management systems,which can represent all possible connections between subsystems.A generalized optimization algorithm is proposed for fuel thermal management system architecture to minimize the heat sink.This algorithm can autonomously arrange subsystems with heat production differences and efficiently utilize the architecture of the fuel heat sink.At the same time,two evaluation indices are proposed from the perspective of subsystems.These indices intuitively and clearly show that the reason for the high efficiency of heat sink utilization is the balanced and moderate cooling of each subsystem and verify the rationality of the architecture optimization method.A set of simulations are also conducted,which demonstrate that the fuel tank temperature has no effect on the performance of the architecture.This paper provides a reference for the architectural design of aircraft fuel thermal management systems.The metrics used in this paper can also be utilized to evaluate the existing architecture.
基金supported by the Deanship of Scientific Research and Graduate Studies at King Khalid University under research grant number(R.G.P.2/93/45).
文摘Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation systems.Fog computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end nodes.Consisting of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud computing.In smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system reliability.To address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog environments.This framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation systems.The FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud environments.Through simulation-based executions,tasks are allocated to the nearest available nodes with minimum latency.In the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of tasks.Upon successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.
文摘Kawasaki disease(KD)is a significant pediatric vasculitis known for its potential to cause severe coronary artery complications.Despite the effectiveness of initial treatments,such as intravenous immunoglobulin,KD patients can experience long-term cardiovascular issues,as evidenced by a recent case report of an adult who suffered a ST-segment elevation myocardial infarction due to previous KD in the World Journal of Clinical Cases.This editorial emphasizes the critical need for long-term management and regular surveillance to prevent such complications.By drawing on recent research and case studies,we advocate for a structured approach to follow-up care that includes routine cardiac evaluations and preventive measures.
基金Supported by Guiding Project of Hebei Provincial Health Commission,No.20201190 and 20180220.
文摘BACKGROUND Effective health management for high-risk stroke populations is essential.The hospital-community-home(HCH)collaborative health management(CHM)model leverages resources from hospitals,communities,and families.By integrating patient information across these three domains,it facilitates the delivery of tailored guidance,health risk assessments,and three-in-one health education.AIM To explore the effects of the HCH-CHM model on stroke risk reduction in highrisk populations.METHODS In total,110 high-risk stroke patients screened in the community from January 2019 to January 2023 were enrolled,with 52 patients in the control group receiving routine health education and 58 in the observation group receiving HCH-CHM model interventions based on routine health education.Stroke awareness scores,health behavior levels,medication adherence,blood pressure,serum biochemical markers(systolic/diastolic blood pressure,total cholesterol,and triglyceride),and psychological measures(self-rating anxiety/depression scale)were evaluated and compared between groups.RESULTS The observation group showed statistically significant improvements in stroke awareness scores and health behavior levels compared to the control group(P<0.05),with notable enhancements in lifestyle and dietary habits(P<0.05)and reductions in postintervention systolic blood pressure,diastolic blood pressure,total cholesterol,triglyceride,self-rating anxiety scale,and self-rating depression scale scores(P<0.05).CONCLUSION The HCH-CHM model had a significant positive effect on high-risk stroke populations,effectively increasing disease awareness,improving health behavior and medication adherence,and appropriately ameliorating blood pressure,serum biochemical marker levels,and negative psychological symptoms.
基金Supported by National Research Foundation of Korea,No.NRF-2021S1A5A8062526.
文摘This article provides a comprehensive analysis of the study by Hou et al,focusing on the complex interplay between psychological and physical factors in the postoperative recovery(POR)of patients with perianal diseases.The study sheds light on how illness perception,anxiety,and depression significantly influence recovery outcomes.Hou et al developed a predictive model that demonstrated high accuracy in identifying patients at risk of poor recovery.The article explores the critical role of pre-operative psychological assessment,highlighting the need for mental health support and personalized recovery plans in enhancing POR quality.A multidisciplinary approach,integrating mental health professionals with surgeons,anesthesiologists,and other specialists,is emphasized to ensure comprehensive care for patients.The study’s findings serve as a call to integrate psychological care into surgical practice to optimize outcomes for patients with perianal diseases.
文摘This editorial highlights a recently published study examining the effectiveness of music therapy combined with motivational interviewing(MI)in addressing an-xiety and depression among young and middle-aged patients following percuta-neous coronary intervention.It further explores existing evidence and potential future research directions for MI in postoperative rehabilitation and chronic disease management.MI aims to facilitate behavioral change and promote healthier lifestyles by fostering a trusting relationship with patients and enhan-cing intrinsic motivation.Research has demonstrated its effectiveness in posto-perative recovery for oncological surgery,stroke,organ transplants,and gastroin-testinal procedures,as well as in managing chronic conditions such as diabetes,obesity,and periodontal disease.The approach is patient-centered,adaptable,cost-effective,and easily replicable,though its limitations include reliance on the therapist’s expertise,variability in individual responses,and insufficient long-term follow-up studies.Future research could focus on developing individualized and precise intervention models,exploring applications in digital health management,and confirming long-term outcomes to provide more compre-hensive support for patient rehabilitation.
文摘Diabetic retinopathy(DR)remains a leading cause of vision impairment and blindness among individuals with diabetes,necessitating innovative approaches to screening and management.This editorial explores the transformative potential of artificial intelligence(AI)and machine learning(ML)in revolutionizing DR care.AI and ML technologies have demonstrated remarkable advancements in enhancing the accuracy,efficiency,and accessibility of DR screening,helping to overcome barriers to early detection.These technologies leverage vast datasets to identify patterns and predict disease progression with unprecedented precision,enabling clinicians to make more informed decisions.Furthermore,AI-driven solutions hold promise in personalizing management strategies for DR,incorpo-rating predictive analytics to tailor interventions and optimize treatment path-ways.By automating routine tasks,AI can reduce the burden on healthcare providers,allowing for a more focused allocation of resources towards complex patient care.This review aims to evaluate the current advancements and applic-ations of AI and ML in DR screening,and to discuss the potential of these techno-logies in developing personalized management strategies,ultimately aiming to improve patient outcomes and reduce the global burden of DR.The integration of AI and ML in DR care represents a paradigm shift,offering a glimpse into the future of ophthalmic healthcare.
文摘Background: The availability of essential medicines and medical supplies is crucial for effectively delivering healthcare services. In Zambia, the Logistics Management Information System (LMIS) is a key tool for managing the supply chain of these commodities. This study aimed to evaluate the effectiveness of LMIS in ensuring the availability of essential medicines and medical supplies in public hospitals in the Copperbelt Province of Zambia. Materials and Methods: From February to April 2022, a cross-sectional study was conducted in 12 public hospitals across the Copperbelt Province. Data were collected using structured questionnaires, checklists, and stock control cards. The study assessed LMIS availability, training, and knowledge among pharmacy personnel, as well as data accuracy, product availability, and order fill rates. Descriptive statistics were used to analyse the data. Results: All surveyed hospitals had LMIS implemented and were using eLMIS as the primary LMIS. Only 47% and 48% of pharmacy personnel received training in eLMIS and Essential Medicines Logistics Improvement Program (EMLIP), respectively. Most personnel demonstrated good knowledge of LMIS, with 77.7% able to log in to eLMIS Facility Edition, 76.6% able to locate stock control cards in the system, and 78.7% able to perform transactions. However, data accuracy from physical and electronic records varied from 0% to 60%, and product availability ranged from 50% to 80%. Order fill rates from Zambia Medicines and Medical Supplies Agency (ZAMMSA) were consistently below 30%. Discrepancies were observed between physical stock counts and eLMIS records. Conclusion: This study found that most hospitals in the Copperbelt Province of Zambia have implemented LMIS use. While LMIS implementation is high in the Copperbelt Province of Zambia, challenges such as low training levels, data inaccuracies, low product availability, and order fill rates persist. Addressing these issues requires a comprehensive approach, including capacity building, data quality improvement, supply chain coordination, and investment in infrastructure and human resources. Strengthening LMIS effectiveness is crucial for improving healthcare delivery and patient outcomes in Zambia.
文摘BACKGROUND Managing critical care emergencies in children with autism spectrum disorder(ASD)presents unique challenges due to their distinct sensory sensitivities,communication difficulties,and behavioral issues.Effective strategies and protocols are essential for optimal care in these high-stress situations.AIM To systematically evaluate and synthesize current evidence on best practices for managing critical care emergencies in children with ASD.The review focuses on key areas,including sensory-friendly environments,communication strategies,behavioral management,and the role of multidisciplinary approaches.METHODS A comprehensive search was conducted across major medical databases,including PubMed,Embase,and Cochrane Library,for studies published between 2000 and 2023.Studies were selected based on their relevance to critical care management in children with ASD,encompassing randomized controlled trials,observational studies,qualitative research,and case studies.Data were extracted and analyzed to identify common themes,successful strategies,and areas for improvement.RESULTS The review identified 50 studies that met the inclusion criteria.Findings highlighted the importance of creating sensory-friendly environments,utilizing effective communication strategies,and implementing individualized behavioral management plans.These findings,derived from a comprehensive review of current evidence,provide valuable insights into the best practices for managing critical care emergencies in children with ASD.Sensory modifications,such as reduced lighting and noise,visual aids,and augmentative and alternative communication tools,enhanced patient comfort and cooperation.The involvement of multidisciplinary teams was crucial in delivering holistic care.Case studies provided practical insights and underscored the need for continuous refi-nement of protocols.CONCLUSION The review emphasizes the need for a tailored approach to managing critical care emergencies for children with ASD.Sensory-friendly adjustments,effective communication,and behavioral strategies supported by a mul-tidisciplinary team are integral to improving outcomes.Despite progress,ongoing refinement of care practices and protocols is necessary.This ongoing process addresses remaining challenges and engages healthcare professionals in continuous improvement of care for children with ASD in critical settings.
文摘Climate change is becoming a major issue for agriculture and the well-being of farmers. The objective of this article is to identify and analyze the production factors that may influence the competitiveness level of agricultural operations, as well as to establish a structural and functional typology of these farms. Using Principal component analysis (PCA) combined with hierarchical ascending classification (HAC) on 250 farmers, the study was able to set farms typology. Furthermore, variance analysis and econometric models (linear et quadratic) were also used for in-depth analysis. The results show the existence of three groups of farm (GA, GB, GC): GA (19.7%), GB (65.3%), and GC (15%). Drought spells and flood are the main climatic risks affecting rain-fed farm operations. For irrigated crops such as rice, the major constraints remain bird attacks, the invasion of pests and nematodes. Climate variability significantly increases the prevalence of morbidities in the region by raising the number of inactive individuals. This significantly and differentially affects the outcomes of these assets. Health expenditures represent a significant share (GB: 12% and GC: 11%) and a non-negligible share (GA: 8.4%). However, larger participations (GC) show better economic performance due to economies of scale, but all categories would benefit from adopting appropriate strategies to reduce losses and increase their resilience.
文摘The development of sustainable sludge management systems requires looking at them with a new vision in which the concepts of SD(Sustainable Development)must integrate those of CE(Circular Economy),both concepts subject to the principles of TD(Thermodynamics),thus allowing the adoption of actions that are all the more effective the more complete the evaluation of the social dimension has been.This involves a new“Way of thinking”which sees the sludge system as the“Locomotive”of the entire wastewater/sludge treatment train and is developed through“Ways of acting”which includes both“Technical”actions to maximize recoveries of useful materials and/or or energy,and“Socio/Institutional”actions to overcome barriers linked to local cultures and traditions,also considering that the specific local context heavily influences the choices capable of satisfying the concepts of CE.It follows the need of issuing realistic and applicable regulations and overcoming social barriers,such as lack of infrastructure and/or qualified personnel,to achieve an effective integration of the concepts of CE with the more general ones of sustainability.
文摘BACKGROUND Inadequate glycemic control in patients with type 2 diabetes(T2DM)is a major public health problem and a significant risk factor for the progression of diabetic complications.AIM To evaluate the effects of intensive and supportive glycemic management strategies over a 12-month period in individuals with T2DM with glycated hemoglobin(HbA1c)≥10%and varying backgrounds of glycemic control.METHODS This prospective observational study investigated glycemic control in patients with poorly controlled T2DM over 12 months.Participants were categorized into four groups based on prior glycemic history:Newly diagnosed,previously well controlled with recent worsening,previously off-target but now worsening,and HbA1c consistently above 10%.HbA1c levels were monitored quarterly,and patients received medical,educational,and dietary support as needed.The analysis focused on the success rates of good glycemic control and the associated factors within each group.RESULTS The study showed significant improvements in HbA1c levels in all participants.The most significant improvement was observed in individuals newly diagnosed with diabetes:65%achieved an HbA1c target of≤7%.The results varied between participants with different glycemic control histories,followed by decreasing success rates:39%in participants with previously good glycemic control,21%in participants whose glycemic control had deteriorated compared to before,and only 10%in participants with persistently poor control,with mean HbA1c levels of 6.3%,7.7%,8.2%,and 9.7%,respectively.After one year,65.2%of the“newly diagnosed patients”,39.3%in the“previously controlled group”,21.9%in the“previously off-target but now worsened'”group and 10%in the“poorly controlled from the start”group had achieved HbA1c levels of 7 and below.CONCLUSION In poorly controlled diabetes,the rate at which treatment goals are achieved is associated with the glycemic background characteristics,emphasizing the need for tailored strategies.Therefore,different and comprehensive treatment approaches are needed for patients with persistent uncontrolled diabetes.
