Service Capacity Research Articles

"I'm quite proud of how we've handled it": health professionals' experiences of returning additional findings from the 100,000 genomes project.

Participants in the 100,000 Genomes Project (100kGP) could consent to receive additional finding (AF) results, individual variants relating to genes associated with susceptibility to cancer and familial hypercholesterolemia (FH). In the study reported here, qualitative interviews were used to explore the experiences of National Health Service (NHS) professionals from across England who were tasked with returning over 80,000 "no AF" results and 700 positive AF results to 100kGP participants. Interviews were conducted with 45 professionals from a range of backgrounds, including Genetic Counsellors, Clinical Geneticists, FH Clinical Nurse Specialists and Clinical Scientists. Interviews were analysed using a codebook thematic analysis approach. Returning AF results has been a significant endeavour, with challenges for pathways, administrative processes and clinical and laboratory time when the capacity of NHS services is already stretched. Professionals discussed going "above and beyond" to prioritise patient care through pathway design, additional clinics, overtime, longer appointments and provision of follow-up appointments. Professionals also described facing practical and emotional challenges when returning AFs. Benefits for patients from receiving AFs in the 100kGP were highlighted and professionals were generally positive about offering clinically actionable AFs within routine NHS clinical care. Professionals were, however, cautious around the implementation of AFs into routine care and felt more research and discussion was needed to determine which AFs to offer, approaches to consent and communication of results, costs and the potential strain on NHS capacity and resources. Further consultation is required with careful review of pathways and resources before offering AFs in clinical practice.

Effects of low impact development on runoff pollution and water quality resilience in an urbanized estuary area

In urbanized estuary areas, water quality often deteriorates due to the impact of surface runoff or overflow during heavy rainfall events. Low impact development (LID) can mitigate this impact and improve water quality resilience. However, there were few studies on quantifying this effect of LID, particularly in estuary areas. In this study, water quality resilience is expressed as the abnormal rate of water quality during rainfall events and the time required for water quality to recover from abnormality to normal. In this study, a coupled Storm Water Management Model (SWMM) and Environmental Fluid Dynamic Code (EFDC) model is used to examine the effects of LID on runoff pollution and water quality resilience in the Shenzhen River estuary (including Shenzhen River and Deep Bay) in China. The results indicate that (1) The inflow volume into the estuary is not only affected by the drainage area but also by the service area and capacity of the sewer interception system; LID can reduce not only the stormwater runoff but also the overflow from the interception systems along rivers. (2) The marginal benefit of the LID proportion increase in pollution load reduction diminishes as the proportion of LID implementation increases. (3) LID can reduce the high value of pollution concentration caused by rainfall runoff; and the reduction effect on the rivers is greater than that on the bay. (4) The rivers and the estuary have a much higher abnormal rate than the inner bay and the outer bay; however, the estuary and the inner bay have longer recovery time than the rivers and the outer bay. The maximum abnormal rate, average abnormal rate, and recovery time of different indicators in the entire estuary area are decreased by 10%-189%, 6%-71%, and 0.8–1.1 cycles when the runoff from 80% of built-up area is treated by LID facilities; LID can significantly reduce abnormal rate of the rivers and recovery time of the inner bay. Therefore, the proposed metric and model can fully reflect the spatial variations in water quality resilience, and LID can enhance the water quality resilience of the urbanized estuary areas under rainfall.

A multi-period capacitated facility location problem with maximum travel time and backup service for locating and sizing EMS stations

Emergency medical services (EMS) is a system that provides emergency medical care for incidents involving serious illness or injury. The location of EMS stations plays an essential role in delivering effective and efficient medical services. Numerous location models have been developed for locating and sizing EMS stations. However, it remains challenging to satisfy all EMS planning criteria within a single location model. In this study, a multi-period capacitated facility location problem with maximum travel time and backup service (EMSLSP) is proposed for locating and sizing EMS stations. The most important criteria for EMS planning are taken into account in EMSLSP: the demand changes due to population mobility, the maximum service capacity of an ambulance, the maximum number of ambulances at each EMS station, the maximum travel time from each EMS station to the locations it serves, the full coverage of dynamic demand, the minimum percent of population covered by EMS service in a specific travel time, and a backup station for each demand location in case of need. A case study in Zhengzhou, a large city in China, demonstrates that effective and efficient locations and sizes of EMS stations can be determined by solving the EMSLSP with various planning parameters. Compared with the existing EMS systems, the average ambulance travel time and the percentage of the population served are significantly improved. Simulations of ambulance scheduling confirm that the relocated and resized EMS stations perform better than those in the existing system. The evaluation-optimization-simulation method outlined in this paper provides a comprehensive and effective approach for EMS station planning.

Experimental Investigations on the On-Site Crack Control of Pier Concrete in High-Altitude Environments

Concrete structures in high-altitude environments face many challenges. Establishing concrete crack control methods in high-altitude environments is crucial for enhancing the service capacity of concrete structures. In this study, a multi-field (hydration-temperature–humidity-constraint) coupling model was used to quantitatively assess the cracking risk of pier bodies at high altitude. On-site crack control tests were conducted on pier bodies using a micro-expansion anti-cracking agent to demonstrate the effectiveness of deformation shrinkage compensation in crack control at high altitudes. The results indicated that there was a risk of cracking in the pier body at high-altitude conditions, especially within 0.3 m from the pile cap and ±2.5 m from the center of the pier side surface. Compared with conventional piers, the micro-expansion anti-cracking agent approximately doubled the unit expansion deflection of piers at high temperatures while reducing the unit shrinkage deflection of piers by 11% to 12% at low temperatures. The concrete in conventional pier bodies was in a tension state after long-term hardening, while the concrete treated with the micro-expansive anti-cracking agent was in compression. Therefore, the deformation compensation effect of the micro-expansive anti-cracking agent was significant and reduced the risk of concrete cracking. In addition, early freezing had a significant impact on concrete strength, underscoring the importance of effective temperature control during the early stages of concrete placement in high-altitude environments.

Balancing power struggles: Understanding the dynamics between standards set by the government, adolescents, and staff at a therapeutic residential care facility

ABSTRACT During four days of observation at a therapeutic residential care (TRC) facility for adolescents with complex behavioral issues, we encountered a growing trend in the Norwegian child welfare system. High demand for institutional beds, along with reduced capacity in psychiatric services and the legal system, has led to increased reliance on the Duty to Assist obligation of the TRCs, administered by the Office for Children, Youth and Family Affairs (Bufetat) in Norway. This obligation is legally binding, ensuring the provision of justifiable treatment. Our observations of staff interactions and documentation analysis of an adolescent, Peter, revealed that staff’s ability to deliver appropriate care and manage high-risk situations is constrained by governmental standards set through law and regulation. Through the theoretical lens of power and discretion, we found that the combination of forced treatment at open institutions, with a strong emphasis on user involvement, creates a power struggle. Without clear practice standards, staff are left to rely on their own competencies in managing conflicts, resulting in inconsistent and unpredictable interactions. This inconsistency increases the likelihood that Peter will resist the care and treatment being offered.

Joint Action JACARDI: a context analysis on CVDs and diabetes policies and practices

Abstract Issue/problem Non-communicable diseases are the leading cause of death and disability in Europe, with 63 million people living with cardiovascular diseases (CVDs) and 32 million with diabetes (DM) in 2019. The EU-co-funded Joint Action on CVDs and diabetes (JACARDI), with 76 partners from 21 countries, aims to reduce CVDs and DM burden at European level through 142 pilot projects. Description of the problem For an effective and tailored pilots’ implementation, a preliminary step is to assess the current state of strategies and services for CVDs and DM prevention and management in Europe. We adopt the Gap Analysis methodology aiming to evaluate the gap between the current and the ideal state, the latter defined according to scientific evidence, best-practices, guidelines, and expert’s opinions. For this purpose, 12 questionnaires, one for CVDs and one for DM for six different thematic areas, were developed through a participatory approach that fostered the collaboration between the scientific coordination team and the project members. Results Questionnaires were sent to National Focal Points for health covering 29 European countries. We anticipate receiving responses from each country covering aspects related to the legal and strategic framework, the intersectoral and equity-oriented approaches, the funding and the service delivery and capacity for CVDs and DM. This information will be collected across each of the six thematic areas corresponding to six technical Work Packages (WP): health literacy, data, screening, integrated-care pathways, patients self-management, labour participation. The survey will be completed by June 2024, and results by WP and country will be presented. Lessons The context analysis, based on the Gap Analysis methodology, allows to identify gaps between the current and ideal state in CVDs and DM prevention and management. This will guide JACARDI’s pilots to address gaps and serve as a roadmap to inform European policy-makers. Key messages • The context analysis will provide an invaluable overview of the current European state of CVDs and DM prevention and management. • The context analysis will support JACARDI’s pilots in addressing identified gaps and policy-makers in shaping public health responses.

GP4ESP: a hybrid genetic algorithm and particle swarm optimization algorithm for edge server placement

Edge computing has attracted wide attention due to its ultra-low latency services, as well as the prevalence of smart devices and intelligent applications. Edge server placement (ESP) is one of the key issues needed to be addressed for effective and efficient request processing, by deciding which edge stations to equip with limited edge resources. Due to NP-hardness of ESP, some works have designed meta-heuristic algorithms for solving it. While these algorithms either exploited only one kind of meta-heuristic search strategies or separately perform two different meta-heuristic algorithms. This can result in limit performance of ESP solutions due to the “No Free Lunch” theorem. In addition, existing algorithms ignored the computing delay of edge servers (ESs) on request process, resulting in overestimation of the service quality. To address these issues, in this article, we first formulate ESP problem with the objective of minimizing the overall response time, considering heterogeneous edge servers with various service capacity. Then, to search effective or even the best ESP solutions, we propose a hybrid meta-heuristic algorithm (named GP4ESP) by taking advantage of both the powerful global search ability of genetic algorithm (GA) and the fast convergence of particle swarm optimization (PSO). GP4ESP effectively fuses the merits of GA and PS by integrating the swarm cognition of PSO into the evolutionary strategy of GA. At last, we conducted extensive simulation experiments to evaluate the performance of GP4ESP, and results show that GP4ESP achieves 18.2%–20.7% shorter overall response time, compared with eleven up-to-date ESP solving algorithms, and the performance improvement is stable as the scale of ESP is varied.

Unveiling the complexity of civil service effectiveness index: An asymmetric and ANN modeling

Unraveling the factors influencing civil service effectiveness becomes imperative in an era marked by escalating demands for efficient governance. This study attempts to meet this necessity by delving into the complex dynamics among core executive functions, mission support facilities, service delivery functions, and attributes, aiming to elucidate their collective impact on civil service effectiveness. Utilizing a unique methodological blend of Fuzzy-set Qualitative Comparative Analysis (fsQCA) and Artificial Neural Networks (ANN), it delves into the relationships among core executive functions, mission support facilities, service delivery functions, and attributes within the International Civil Service Effectiveness (InCiSE) Index framework. The research uses a configurational model that optimizes CSE and assesses the relative importance of various components. The study reveals significant correlations among the variables. It indicates that all CSE indicators influence but are not equally important in triggering the effectiveness of civil service administration. Key configurations, such as integrating strategic governance with mission support functions and high-level strategy with operational execution, are critical for enhancing civil service effectiveness. It underscores the importance of prioritizing core executive functions and attributes to improve civil service administration. Theoretically, the study enriches contingency theory and contributes to the civil service and administration literature by integrating a configurational approach with machine learning insights. Practically, it provides actionable insights for governance improvement, promoting the application of innovative methodologies in public service to enhance organizational environment and civil service capacities. Original in its approach, this study fills a gap in the literature by applying a hybrid fsQCA-ANN model to explore the configurational and construct ranks influencing civil service effectiveness, offering an inclusive analysis that triangulates qualitative and quantitative data. The findings indicate that civil service effectiveness is highly complex because of its process, involvement of diverse backgrounds of civil servants, critical understanding about the key pillars of good governance and service delivery mechanism. Thus, the findings advance academic understanding and provide practical strategies for policymakers and practitioners to foster better governance through targeted interventions that enhance transparency, accountability, and responsiveness in civil service organizations.

Analysis and Comprehensive Evaluation of Urban Green Space Information Based on Gaofen 7: Considering Beijing’s Fifth Ring Area as an Example

Urban green spaces constitute a vital component of the ecosystem. This study focused on urban green spaces located within the Fifth Ring Road of Beijing, using Gaofen 7 (GF-7) as the primary data source for analysis. The main objective was to develop a system for extracting and classifying urban green spaces in Beijing by applying deep learning and machine learning algorithms, and further, the results were validated with ground survey samples. This study provides detailed extraction and classification of urban green space coverage by creating a comprehensive evaluation system. The primary findings indicate that the deep learning algorithm enhances the precision of green space information extraction by 10.68% compared to conventional machine learning techniques, effectively suppresses “pretzel noise”, and eventually aids in extracting green space information with complete edges. The thorough assessment of green spaces within the study area indicated favorable outcomes showing the high service capacity of park green spaces. The overall classification accuracy of the final extraction results was 94.31%. Nonetheless, challenges, such as unequal distribution of green zones and a significant fragmentation level throughout the study area, were still encountered. Consequently, the use of GF-7 high-resolution imagery, in conjunction with the collaborative application of deep learning and machine learning techniques, enabled the acquisition of highly accurate information regarding urban green zone coverage. According to the established grading standards of evaluation indices, the landscape pattern of urban green spaces within the study area was comprehensively assessed. This evaluation offers essential data support for monitoring urban green spaces and planning landscape patterns, thereby contributing to the achievement of sustainable development objectives related to urban greening and ecological conservation.

Experience in using artificial intelligence services for diagnosing compression fracture of vertebral body based on computed tomography – from testing to trials

Backgraund:Osteoporosis (OP) is often diagnosed at the stage of complications. Compression fractures (CF) of the vertebral bodies, complications of OP, and predictors of subsequent fractures are often asymptomatic. CF can be detected on CT scan performed for other indications. We have analyzed approaches to using artificial intelligence services (AI services) generated for diagnosing CF of the vertebral bodies. Aims:Testing AI services to identify CF based on chest CT and to assess the possibility of their implementation into the practice of medical facilities of the Moscow Healthcare Department. Materials and methods:For setting a clinical task for AI services, basic diagnostic requirements in the direction of “Osteoporosis” are formed. AI services go through the following stages: self-testing, functional and calibration testing, trial and trial operation. The first three stages of testing are carried out on previously generated datasets. At the stages of trial and trial operation, AI services analyze CT examinations performed in medical facilities. An expert group of radiologists evaluates the diagnostic accuracy and functional capacity of AI services at all stages. The obtained quantitative metrics of the accuracy of AI services are compared with the target values ​​specified in the requirements. Results:From June 2021 to June 2022, two AI services (AI service №1 and AI service №2) which used different methods for identifying a presence of CF were tested. AI services successfully passed the self-testing stage (6), functional (5) and calibration (100) testing. The ROC AUC for AI service №1 was 0.99 and for AI service №2–0.91. The AI service №1 passed the trial stage without any significant remarks, while AI service №2 was sent for revision. After the trial operation stage, the following accuracy metrics were obtained: the ROC AUC for AI service №1 was 0.93; for AI service №2–0.92. At all stages, both AI services showed sufficient metrics for clinical validation. Conclusions:A testing of the performance of AI services in the direction of “Osteoporosis” was carried out. A high quality of diagnosis was demonstrated. AI services can act as an auxiliary tool in the medical decision support system.

Spatiotemporal evolution and development path of healthcare services supply in China

ObjectPromoting the accessibility and equity of healthcare services, as well as enhancing service capacity, are crucial for building a sound healthcare system. Particularly in the past two years of the normalized COVID-19 situation, this issue has garnered widespread attention in the academic community. This study aims to investigate and analyze the characteristics and trends of the spatial-temporal evolution of healthcare service supply levels in China. It also seeks to explore the influencing factors and pathways for development, with the goal of optimizing the allocation of healthcare resources.MethodsThis article uses the entropy weight TOPSIS method combined with Dagum Gini coefficient and Kernel density to evaluate the supply level of healthcare services in 31 provinces and cities in China from 2012 to 2020, and explores its development and spatial pattern characteristics. Then, through Moran index, panel regression model and spatial econometric testing, the spatial correlation problem and its influencing factors are further analyzed, and targeted policy recommendations are proposed based on it, laying the foundation for further promoting the balanced development of healthcare service supply capacity.Results(1) Healthcare services supply levels in various provinces and cities in China have significantly increased, with a shift in spatial distribution from ‘higher in the east and lower in the west’ to ‘convergence between east and west, with lower levels in the central regions.’ (2) Relative differences among regions are narrowing annually, primarily due to interactions between the four regions rather than within each region, with expanding impact of overlapping regions. (3) Absolute differences among regions are also decreasing, moving towards uniformity with a contraction of extension and a restraint on the trend towards multipolarization. (4) Spatial correlation between adjacent regions is weakening, eventually becoming non-significant, with fading spatial effects. (5) The correlation between local economic development, population factors, institutional arrangements, and the current state of supply is significant, and the research design and conclusions remain robust even after thorough consideration of spatial effects. The study explores the development pathways based on the objective existence of regional development and the controllable government actions.ConclusionThe overall level of healthcare service supply in China has improved, but regional differences still exist. The objective level of regional development and the subjective behavior of local governments have a significant impact on the supply of healthcare services. Therefore, it is recommended that each region adapt to local conditions, identify its own strengths and weaknesses, coordinate resource supply and demand, consider the impact of key factors, and optimize the allocation of healthcare development resources.

Resilience Capacity of Pre-hospital Emergency Medical Service (EMS) Providers and the Future Agenda for Sustainable Development of A Resilient EMS System in Thailand

In the current scenario, demand for emergency care is rising due to the shift in disease pattern all around the world, from growing burden of non-communicable diseases to the pre-existing communicable diseases. The principle aim of an emergency medical service (EMS) system is to prevent premature mortality, reduce pain and prevent long term disability. EMS workers serve on the front lines of emergency medical care, which is one of the most important components in an EMS system of any country. Since the latest pandemic has caused increased burn out and stress among the service providers with long term mental and physical effect which is yet to be researched in Thailand, and no study in particular have addressed to evaluate the resilience capacities of the front-line EMS workforce and identify components that influence their performance and response to emergencies. This study aims to measure the resilience capacity of pre-hospital EMS providers of Thailand along with providing recommendations to policy makers regarding EMS service provider future agendas and standard methods for proper workforce development in order to tackle future public health emergency situations. The respondents were EMTs, ENPs, paramedics, frontline rescuers working in the provinces as an EMS service provider under the ministry of public health (MOPH), National Institute of Emergency Medicine (NIEM), Thailand. Total 500 participated in the survey from 32 different provinces. Resilience capacity was divided into high, moderate and low; Components and factors were developed through literature review and grouping was done. With total 41 questions: Safety, Competencies, Wellness and Behavioral Health. Open ended questions reflected the perception and experiences of the EMS service providers regarding the strength and improvement areas of the EMS system in Thailand. The result from the survey shows that the EMS service providers have moderate resilience in terms of Behavioral Health which is related to their psychometric properties and main components to measure the resiliency scales. Similarly, in terms of Safety, Wellness and Competencies components the EMS services have shown moderate level of resilience capacity as a front-line worker in the emergency medical service system to prepare for the future public health emergencies. The findings of the research present the perception and opinions of various EMS providers working in different provinces of Thailand. This study explores the present status/situation of front-line workers of the EMS system in Thailand. The findings provide crucial recommendations to health policy makers for developing resilient EMS system and their workforce in Thailand focusing on pre-hospital care setting. This research suggests measurement tools and plans focusing on the EMS future agenda 2050.

Conceptual Analysis of the High-Touch, High-Tech Trend: The Suitability of Technology for Tourism Transformation in Rural Destinations

This research aims to evaluate the role of technology in rural tourism development, focusing on the match between technology and the capabilities of local communities. The method used is a quantitative approach, namely data collection through questionnaires distributed to three groups of respondents: local communities, technology providers and tourists. Two main research questions were identified: (1) Is the technology applied by the community service capacity in the tourist village? (2) How can technology be adapted to the needs of local communities and the experiences tourists desire? The research results show that appropriate technology can improve tourist experiences and empower local communities. However, reliance on technological trends without a strong foundation can decrease tourist interest. Therefore, this research concludes that the application of technology must be based on a deep understanding of the local context to avoid inappropriate investments and maintain tourism sustainability. These findings provide important insights for stakeholders in designing appropriate technology strategies for tourist villages. Keywords: rural tourism, technological progress, high technology, emerging markets, tourism services

Power allocation optimization strategy for multiple virtual power plants with diversified distributed flexibility resources

AbstractThe virtual power plant integrating the flexible resources in the distribution network can provide additional adjustment capacity for the auxiliary services of distribution network. However, the actual internal situation of distribution network including insufficient adjustable capacity of energy storage, unreasonable power allocation, and voltage overrun leads to the difficulties in optimization scheduling. Therefore, this paper proposes a power allocation optimization strategy of distributed electricity‐H2 virtual power plants (EHVPPs) with aggregated flexible resources. Specifically, a distributed EHVPP division method based on the granular K‐medoids clustering algorithm is proposed to realize the independent autonomy and coordinated interaction between EHVPPs, and in order to quantify the operation and regulation capacity of distributed EHVPPs, an aggregation approach of regulating feasible domains of flexibility resources based on the improved zonotope approximations is developed. Moreover, a power allocation strategy based on the flexibility weight factor is proposed to handle the calculated minimum deviation between the total active output of PV and the dispatching power command, realizing the self‐consistency of distributed EHVPPs. Comparative studies have demonstrated the superior performance of the proposed methodology in economic merits and self‐consistency efficiency.

Growing the peer workforce in rural mental health and social and emotional well-being services: A scoping review of the literature.

Growing the mental health peer workforce holds promise for rural communities, but we currently lack an understanding of the guidance available to support the development, implementation and sustainability of this workforce in rural settings. Study aims are to: (1) determine the extent and nature of the literature that provides guidance for growing the peer workforce in rural mental health services; and (2) identify and explore any guidance relevant to rural peer work services dedicated to First Nations communities, including those promoting social and emotional well-being within this body of literature. A scoping review method was employed to identify relevant peer-reviewed and grey literature published between 2013 and 2022 across PsychInfo, Medline, Embase and CINAHL, Scopus and Informit HealthInfoNet databases, as well as targeted organisation websites and Google Advanced Search. A total of 26 unique studies/projects were included from the US, UK, Canada and Australia with public mental health, non-government/for purpose and private sector service settings represented in the literature. Grey literature, such as reports of evaluations and frameworks, formed the majority of included texts. While there is a lesser volume of rurally focused literature relative to the general peer work literature, this is a rich body of knowledge, which includes guidance concerning services dedicated to First Nations communities. Via synthesis critical considerations were identified for the development, implementation and sustainability of peer work in rural mental health services across six domains: 'Working with community members and stakeholders', 'Organisational culture and governance', Working with others and in teams, Professional expertise and experience, Being part of and working in the community and 'Local mental health services capacity'. While there are considerations relevant across a range of settings, the domains of: 'working with community members and stakeholders', 'being part of and working in the community' and 'local mental health services capacity', capture additional, distinct and nuanced challenges and opportunities for growing the peer work in rural services. The literature offers insights valuable for service planning, policy development and the allocation of resources to support rural peer workforce growth.

Damage and Crack Propagation Mechanism of Q345 Specimen Based on Peridynamics with Temperature and Bolt Holes

With the increasing demand for the performance and design refinement of steel structures (including houses, bridges, and infrastructure), many structures have adopted ultimate bearing capacity in service. The design service lives of steel building structures are generally more than 50 years, and most of them contain bolted connections, which suffer from extreme conditions such as fire (high temperature) during service. When the structure contains defects or cracks and bolt holes, it is easy to produce stress concentration at the defect location, which leads to crack nucleation and crack propagation, reduces the bearing capacity of the structure, and causes the collapse of the structure and causes disasters. In the process of structural damage and crack propagation, the traditional method has some disadvantages, such as stress singularity, the mesh needing to be redivided, and the crack being restricted to mesh; however, the integral method of peridynamics (PD) can completely avoid these problems. Therefore, in this paper, the constitutive equation of PD in high temperature is derived according to the variation law of steel material properties when changed by temperature increase and peridynamics parameters; the damage and crack expansion characteristics of Q345 steel specimens with bolt holes and a central double-crack at 20 °C, 200 °C, 400 °C, and 600 °C were analyzed to clarify the structural damage and failure mechanism. This study is helpful for providing theoretical support for the design of high-temperature steel structures, improving the stability of the structure, and ensuring the bearing capacity of the structure and the safety of people’s lives and property.

Real-time optimal hierarchy control of HVAC system with maximized ancillary service support in smart buildings: An experimental approach

This article proposes a real-time optimum control algorithm for Heating, Ventilation, and Air Conditioning (HVAC) units of a commercial building aimed to maximize the ancillary power available for frequency regulation services. First, the prediction of energy consumption of air conditioning zones using long short-term memory (LSTM) is achieved, which helps forecast the aggregated regulation capacity bid of the building in the energy markets. Furthermore, to minimize energy costs and thermal discomfort of building dwellers, an optimization algorithm is designed considering the day-ahead electricity tariffs. Moreover, using installed sensors in a lab-scaled hardware prototype, the proposed algorithm is also shown to be capable of interacting with a Building Energy Management System (BEMS) and investigating the electrical and thermal properties of the HVAC unit. The BEMS controller uses an ethernet protocol to interface with the sensors installed at various operational points throughout the HVAC system. The optimal operation of the HVAC system has been executed with the real-time thermal feedback system, which counterbalances the uncertain thermal load or renewable power availability in the building confronted in real-time operation. The simulation results show the performance of the Artificial Neural Network (ANN) based compressor model in deep learning integrated with the other components of the HVAC unit and thermal model of the air-conditioning zone. Finally, the experimental results display the real-time implementation of multiple thermal and electrical conditions within the proposed control scheme of the HVAC unit. This shows the potential of ancillary services capacity through commercial buildings can be maximized with flexible loads and thereby help in power grid support.

Comprehensive evaluation of the implementation of close-type county medical alliance in Shandong Province using entropy weight TOPSIS method and non-integer rank sum ratio method

BackgroundTo improve the capacity of county medical and health services, China encourages all localities to pilot the close-type county medical alliance. In Shandong Province, medical alliances have been piloted in 47 counties, ranking first in the country. The objective of this study is to comprehensively evaluate the implementation of close-type county medical alliance in Shandong Province, identify the differences between different county regions, and analyze the reasons, so as to provide a reference for the construction of a new county medical and health service system with clear goals, powers and responsibilities, and division of labor.MethodsThe implementation of the close-type county medical alliance was comprehensively evaluated in 47 national pilot counties in Shandong Province using entropy weight TOPSIS method and non-integer rank sum ratio method. Variance analysis was used for comparison of the comprehensive evaluation results.ResultsThe weight coefficient of evaluation indicators was highest for information interconnection, at 18.06%, and lowest for orderly referral of patients, at 3.64%. There was no difference in results of the comprehensive evaluation of entropy weight TOPSIS method and non-integer rank sum ratio method. Comprehensively order the implementation status of each pilot county according to the relative paste progress, 13 counties Y5, Y11, Y14, Y16, Y20, Y25, Y26, Y27, Y28, Y32, Y33, Y40 and Y42 were ranked highest, whereas county Y37 was ranked lowest. Non-integer rank sum ratio method graded counties into three grades: excellent, good and average. Kruskal-Wallis nonparametric test showed that the difference between the grades was statistically significant (H\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\:=\\:$$\\end{document}37.099, p\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:<\\:$$\\end{document}0.001). Variance analysis based on comprehensive evaluation results showed that implementation status was not correlated with the county economic development level, the level of health resources input and the medical service ability of the lead hospital.ConclusionsOur findings indicated that the implementation of the close-type county medical alliance is significantly different between pilot counties, with a marked differentiation within the same urban area. Therefore, effective measures are recommended to reduce this gap, including promoting informatization empowerment of the county medical community, strengthening government responsibility and improving policy effectiveness.

The international cases of vaccinology education and its enlightenment to the discipline development in China

Vaccination is an effective public health measure to prevent and control vaccine-preventable diseases for individual and society. However, China currently confronts significant challenges, including a dearth of skilled professionals in the field of vaccination and disparities in the capacity for immunization services. This review introduced the experiences of four prime international vaccinology education models, including London School of Hygiene & Tropical Medicine, Johns Hopkins University, Leading International Vaccinology Education, and the Bill & Melinda Gates Foundation, in the aspect of personnel development, academic research and communication platforms establishment. It is supposed to give some insights and feasible suggestions on the establishment and advancement of vaccinology as a sub-discipline within high-level public health school in China, with the aim of development of a robust vaccinology education framework in China, which is essential for nurturing the next generation of public health leaders and practitioners for our country.

A two-layer economic resilience model for distribution network restoration after natural disasters

Improving the resilience of energy networks and minimizing outages is crucial, making the development of self-healing strategies essential for ensuring a continuous power supply and boosting resilience. As decentralized prosumers become more integrated into smart grids, innovative coordination methods are required to fully leverage their potential and improve the system's self-healing capabilities. Hence, in this paper, we present a decentralized two-layer model for active distribution networks (ADNs) incorporating commercial energy hubs, Parking lots (PLs), hydrogen refueling stations, and mobile units (MUs). This model aims to maximize the flexible capacities of flexible prosumers under emergencies and includes a dynamic mechanism for transporting hydrogen to refueling stations via trucks. In the first layer of the model, the AND operator provides the required services to flexible prosumers, including commercial energy hubs, PLs and hydrogen refueling stations. During this layer, the movement paths of mobile units, such as battery-based mobile storage units (MSUs) and mobile hydrogen units (MHUs), are determined. In the second layer, prosumers independently plan and decide the extent of their service contributions. Subsequently, with the actual service capacities established, the AND operator re-optimizes the initial planning to finalize the system schedule and precise movement paths of the mobile units. The proposed model was tested on a modified 83-bus distribution network using the CPLEX solver in GAMS. Simulation results demonstrate a 54.9 % reduction in forced load shedding (FLS) due to the dispatch of mobile units and a further 84.4 %% reduction in FLS from leveraging the flexible capacities of commercial energy hubs and PLs.