Using a Hybrid Multiattribute Decision-Making Model for Evaluating the Sustainable Development Potential of Characteristic Towns and Exploring Development Planning Strategies.

In recent years, with the development of 'China's new urbanization, the "characteristic town movement" with the development of industrial economy first has brought problems to a large number of rural settlements, such as no cultural planning, no consumption of industry, and no soul. Then, in reality, there are still a large number of rural settlements under the planning of the upper-level local government, with the goal of developing into a characteristic town in the future. Therefore, this study believes that there is an urgent need to build a framework for evaluating the construction potential of rural settlements with sustainable characteristic towns. Not only that but also a decision analysis model should be provided for real-world empirical cases. This model needs to cover the assessment of the sustainable development potential of characteristic towns as the goal and the formulation of improvement strategies. This study combines the data collection of current characteristic town development rating reports, applies data exploration technology to extract core impact elements and obtain hierarchical decision rules, integrates expert domain knowledge with DEMATEL technology, and establishes an impact network relationship diagram between core impact elements. At the same time, the representative characteristic town cases are assessed for their sustainable development potential, and the modified VIKOR technique is applied to clarify the actual problems of the empirical cases, in an attempt to determine whether the development potential and development plan of the characteristic town meet the sustainable development needs from the pre-evaluation mechanism.

PT-symmetric solitons and parameter discovery in self-defocusing saturable nonlinear Schrödinger equation via LrD-PINN.

We propose a physical information neural network with learning rate decay strategy (LrD-PINN) to predict the dynamics of symmetric, asymmetric, and antisymmetric solitons of the self-defocusing saturable nonlinear Schrödinger equation with the PT-symmetric potential and boost the predicted evolutionary distance by an order of magnitude. Taking symmetric solitons as an example, we explore the advantages of the learning rate decay strategy, analyze the anti-interference performance of the model, and optimize the network structure. In addition, the coefficients of the saturable nonlinearity strength and the modulation strength in the PT-symmetric potential are reconstructed from the dataset of symmetric soliton solutions. The application of more advanced machine learning techniques in the field of nonlinear optics can provide more powerful tools and richer ideas for the study of optical soliton dynamics.

Enhancing the Health and Well-Being of People with Chronic Diseases: Assessment and Sustainable Development Planning for Therapeutic Landscapes after Urban Expansion.

Under the influence of economic, environmental, and social structural changes, urban space expands and contracts to varying degrees and the everyday urban landscape changes in response. Over the past 20 years, a large number of cities in China have undergone a brief but rapid urban expansion and are moving toward shrinking cities. Most of these cities are now facing social problems such as an aging population and a high prevalence of chronic diseases. Therefore, the "therapeutic" role and impact of everyday landscapes in these cities need to be examined in the context of urban development processes through appropriate assessment methods. Therefore, this study applies the ANP-mV model to examine the therapeutic nature of everyday urban landscapes in different development periods, with the aim of enhancing the health and well-being of people with chronic diseases. Firstly, this study uses the city of Jinzhou in Northeast China as an example to develop a framework for assessing the therapeutic nature of everyday urban landscapes based on the health care needs of people with chronic diseases; secondly, it examines the therapeutic nature of the former Jinzhou Suburban Riverfront Forest Park as it has developed and evolved over the past 16 years; finally, it explores place-making and regeneration strategies for therapeutic landscapes from the perspectives of dynamic impact and sustainable development to enhance chronic illness patients' well-being. At the theoretical level, this study contributes by providing a methodology and research ideas for examining the "therapeutic" nature of everyday urban landscapes and proposing further development plans for renewal, constructing a framework for assessing therapeutic landscapes, and elucidating the relationship between networks of influence and the relative importance of various assessment dimensions/elements. At the practical application level, the contribution of this study is to provide local policymakers with a key decision basis for the future development planning of the East Lake Forest Park. The aim is to explore landscape creation and regeneration strategies for the East Lake Forest Park in the context of Jinzhou's progressive move toward a shrinking city, in order to sustain the well-being of the chronically ill.

Environmental Design Strategies to Decrease the Risk of Nosocomial Infection in Medical Buildings Using a Hybrid MCDM Model.

The prevention and control of nosocomial infection (NI) are becoming increasingly difficult, and its mechanism is becoming increasingly complex. A globally aging population means that an increasing proportion of patients have a susceptible constitution, and the frequent occurrence of severe infectious diseases has also led to an increase in the cost of prevention and control of NI. Medical buildings' spatial environment design for the prevention of NI has been a hot subject of considerable research, but few previous studies have summarized the design criteria for a medical building environment to control the risk of NI. Thus, there is no suitable evaluation framework to determine whether the spatial environment of a medical building is capable of inhibiting the spread of NI. In the context of the global spread of COVID-19, it is necessary to evaluate the performance of the existing medical building environment in terms of inhibiting the spread of NI and to verify current environmental improvement strategies for the efficient and rational use of resources. This study determines the key design elements for the spatial environment of medical buildings, constructs an evaluation framework using exploratory factor analysis, verifies the complex dominant influence relationship, and prioritizes criteria in the evaluation framework using the decision-making trial and evaluation laboratory- (DEMATEL-) based analytical network process (ANP) (DANP). Using representative real cases, this study uses the technique for order preference by similarity to ideal solution (TOPSIS) to evaluate and analyze the performance with the aspiration level of reducing the NI risk. A continuous and systematic transformation design strategy for these real cases is proposed. The main contributions of this study include the following: (1) it creates a systematic framework that allows hospital decision-makers to evaluate the spatial environment of medical buildings; (2) it provides a reference for making design decisions to improve the current situation using the results of a performance evaluation; (3) it draws an influential network relation map (INRM) and the training of influence weights (IWs) for criteria. The sources of practical problems can be identified by the proposed evaluation framework, and the corresponding strategy can be proposed to avoid the waste of resources for the prevention of epidemics.

Exploring Strategies for Improving Green Open Spaces in Old Downtown Residential Communities from the Perspective of Public Health to Enhance the Health and Well-Being of the Aged.

Based on the trend of global aging, people are paying more and more attention to the health of the elderly and the improvement of green open spaces. However, few studies have focused on strategies to improve green spaces in response to this trend. Especially, with the outbreak of COVID-19, an urgent need to develop a sustainable system strategy to improve the health of the elderly in residential communities in old districts has emerged. Traditional improvement strategies based on current situation evaluation often focus on the most prominent practical problems. Therefore, the objective of this study was to provide theoretical research and practical improvement strategies for green open spaces in old downtown residential communities to improve the health and well-being of the elderly. In response to this problem, this research proposes an alternative method based on causality (FDM-DANP-mV model), by extracting 23 green open space elements that affect the health of the elderly and dividing them into three dimensions, to form a preliminary evaluation framework. On this basis, the more effective and feasible standard elements are screened out, and the influence relationship behind the elements is clarified. Then, the sustainable development strategy is systematically discussed in three practical cases. This allows for the analysis of the present situation to not only identify the current significant problems but also to capture the source of the influence behind the real problems based on the clarification of the dominant influence relationship. The actual value of this study is to provide a key design decision basis for the improvement of the green open spaces in old downtown residential communities, aiming at avoiding waste to the greatest extent under the premise of limited resources and gradually promoting the improvement of the urban built environment to promote the health and well-being of the elderly.

Development and implementation of a dynamically updated big data intelligence platform from electronic health records for nasopharyngeal carcinoma research.

OBJECTIVE: To develop a big data intelligence platform for secondary use of electronic health records (EHRs) data to facilitate research for nasopharyngeal cancer (NPC). METHODS: This project was launched in 2015 and carried out by the cooperation of an academic cancer centre and a technology company. Patients diagnosed with NPC at Sun Yat-sen University Cancer Centre since January 2008 were included in the platform. Standard data elements were established to defined 981 variables for the platform. For each patient, data from 13 EHRs systems were extracted, integrated, structurized and normalized. Eight functional modules were constructed for the platform to facilitate the investigators to identify eligible patients, establish research projects, conduct statistical analysis, track the follow-up, search literature, etc. RESULTS: From January 2008 to December 2018, 54,703 patients diagnosed with NPC were included. Of these patients, 39,058 (71.4%) were male, and 15,645 (28.6%) were female; median age was 47 (interquartile range, 39-55) years. Of 981 variables, 341 were obtained from data structurization and normalization, of which 68 were generated by interacting multiple data sources via well-defined logical rules. The average precision rate, recall rate and F-measure for 341 variables were 0.97 ± 0.024, 0.92 ± 0.030, and 0.94 ± 0.027 respectively. The platform is regularly updated every seven days to include new patients and add new data for existing patients. Up to now, eight big data-driven retrospective studies have been published from the platform. CONCLUSION: Our big data intelligence platform demonstrates the feasibility of integrating EHRs data of routine healthcare, and offers an important perspective on real-world study of NPC. The continued efforts may be focus on data sharing among multiple hospitals and publicly releasing of data files. ADVANCES IN KNOWLEDGE: Our big data intelligence platform is the first disease-specific data platform for NPC research. It incorporates comprehensive EHRs data from routine healthcare, which can facilitate real-world study of NPC in risk stratification, decision-making and comorbidities management.

Use of a Modified DANP-mV Model to Improve Quality of Life in Rural Residents: The Empirical Case of Xingshisi Village, China.

Climate change-related anomalies have increased public concern regarding environmental protection. This has opened newer rural development avenues. In this regard, livability of villages is crucial; it can be evaluated based on the villagers' quality of life (QoL). The WHOQOL-BREF, a comprehensive cross-cultural and cross-disciplinary scale proposed by the World Health Organization to assess QoL, has aided in assessing and improving QoL in different regions. However, the factors of this instrument are mutually influential, necessitating an improvement strategy considering the entire system. This problem may be resolved using the DANP-mV model. However, the traditional DANP-mV model includes many items and responding to all of them is difficult for experts. Therefore, by using the case of Xingshisi Village in China, this study proposed a modified DANP-mV model to provide additional suggestions for systematic improvement of the QoL and livability in the village. Xingshisi is a model village built according to an aspirational benchmark; however, different from the traditional definition of a benchmark, this village exhibits room for improvement. Although the modified model reduces the number of questions from 650 to 168, its effect remains similar to that of the traditional model. Moreover, in the modified model, physical capacity (D1) presented the largest dimensional gap. The interaction among the factors indicated that considering the effect of the environment (D4) and developing a systematic improvement strategy are necessary to improve the livability of villages facing limited resources.

Using the D-DANP-mV Model to Explore the Continuous System Improvement Strategy for Sustainable Development of Creative Communities.

With globalization, the notion of "creative city" has become a core concept of many cities in the world development policies, with real properties being upgraded or used to change, renewal is being conducted, and creative industries are emerging. This trend has reached its peak in the past decade, with different forms and scales gathering global development momentum among the creative communities to promote the development of creative economies. In recent years, however, there was still skepticism about the sustainability of the current creative communities. Many scholars have pointed out that signs of unsustainability have begun to appear in many creative communities. To overcome these obstacles, the development of rational and highly effective improvement strategy requires a dynamic thinking process. Therefore, this study employs the DEMATEL-based ANP with modified VIKOR (D-DANP-mV) model in presenting an assessment framework for the sustainability of creative communities. This system is used to assess the sustainability of current creative communities and determine how to solve their problems. Thus, continuous and systemic improvement strategies can be developed to achieve the aim of sustainable development. Two creative communities in Taiwan, Taichung Cultural and Creative Industries Park (TCCIP), and Shen-Ji New Village (SJNV), are used as case studies in this study. Based on the concept of systematic improvement from fundamental issues, the results indicate that the improvement priorities can be determined by applying the D-DANP-mV model. This approach is different from those found by a conventional method with the hypothesis of independent criteria (e.g., diversification of creative talents in TCCIP), and cannot use for performance improvement (e.g., only can be used for ranking and selection among alternatives). Considering these points, unreasonable premises, biased errors, and lack of some real application functions in the process of resource allocation could be more efficient improvement strategies generated in this proposed model.