A smartphone application for personalized facial aesthetic monitoring.

BACKGROUND: Methods available at home for capturing facial images to track changes in skin quality and evaluate skincare treatments are limited. In this study, we developed a smartphone camera application (app) for personalized facial aesthetic monitoring. MATERIALS AND METHODS: A face alignment indicators (FAIN) system utilizing facial landmark detection, an artificial intelligence technique, to estimate key facial parts, was implemented into the app to maintain a consistent facial appearance during image capture. The FAIN system is composed of a fixed target indicator and an alignment indicator that dynamically changes its shape according to the user's face position, size, and orientation. Users align their faces to match the alignment indicator with the fixed target indicator, and the image is automatically captured when alignment is achieved. RESULTS: We investigated the app's effectiveness in ensuring a consistent facial appearance by analyzing both geometric and colorimetric data. Geometric information from captured faces and colorimetric data from stickers applied to the faces were utilized. The coefficients of variation (CVs) for the L*, a*, and b* values of the stickers were higher compared to those measured by a colorimeter, with CVs of 14.9 times, 8.14 times, and 4.41 times for L*, a*, and b*, respectively. To assess the feasibility of the app for facial aesthetic monitoring, we tracked changes in pseudo-skin color on the cheek of a participant using skin-colored stickers. As a result, we observed the smallest color difference ∆Eab of 1.901, which can be considered as the experimentally validated detection limit using images acquired by the app. CONCLUSION: While the current monitoring method is a relative quantification approach, it contributes to evidence-based evaluations of skincare treatments.

Toward a Medication Information Literacy Indicator System for Older Adults: A Delphi Study.

BACKGROUND: The safety of medication use among older adults is a growing concern, given the aging population. Despite widespread attention, the exploration of medication literacy in older adults, particularly from the perspective of information literacy, is in its nascent stages. METHODS: This study utilized the existing literature to define medication information literacy (MIL) as a theoretical framework. A two-round Delphi survey was conducted to identify the essential components of a MIL indicator system for older adults. The analytic hierarchy process (AHP) was then used to assign weights to each indicator. RESULTS: The study observed relatively high response rates in both rounds of the questionnaire, which, along with expert authority coefficients (Cr) of 0.86 and 0.89, underscores the credibility and expertise of the panellists. Additionally, Kendall's coefficient of concordance (Kendall's W) ranging from 0.157 to 0.33 (p < 0.05) indicates a consensus among experts on the identified indicators. Utilizing the Delphi process, a MIL indicator system for older adults was developed, comprising five primary and 23 secondary indicators. These indicators were weighted, with medication information cognition and acquisition emerging as pivotal factors in enhancing medication literacy among older adults. CONCLUSIONS: This study developed a MIL indicator system tailored for older adults using the Delphi approach. The findings can inform healthcare professionals in providing customized medication guidance and assist policymakers in crafting policies to enhance medication safety among older adults. PATIENT OR PUBLIC CONTRIBUTION: Patient and public engagement played a pivotal role in the development of our medication information literacy indicator system for older adults. Their involvement contributed to shaping research questions, facilitating study participation, and enriching evidence interpretation. Collaborations with experts in geriatric nursing, medicine, and public health, along with discussions with caregivers and individuals with lived experience, provided invaluable insights into medication management among older adults. Their input guided our research direction and ensured the relevance and comprehensiveness of our findings.

Evaluation of the water quality monitoring network layout based on driving-pressure-state-response framework and entropy weight TOPSIS model: A case study of Liao River, China.

The establishment of river water quality monitoring network is crucial for watershed protection. However, the evaluation process of monitoring network layout involves significant subjectivity and has not yet to form a complete indicator system. This study constructed an indicator system based on the DPSR (Driving-Pressure-State-Response) framework in the Liao River Basin, China. SWAT model and ArcGIS were used to quantify the indicators. And the entropy weight-TOPSIS method was employed to rank monitoring points. The results showed that pressure and state indicators had a greater impact on the network layout, with the indicator for proportion of land use in residential areas carrying the largest weight of 0.136. It suggested that the risk of river pollution remained high, and the governance strategies needed to be improved. Priority monitoring points were mainly located in the east and middle of the basin, consistent with the distribution of human activities such as urban areas and farmland. In addition, the redundancy of points should be avoided, and evaluation results should be adjusted based on the actual situation. The study provided an evaluation method for the layout of monitoring points.

Measuring the Success of Global Sports Governance: A Deep Trust Network Model Approach.

With the development of the economy and the improvement of living standards, people's needs have gradually changed, and sports has received increasing attention. At the same time, due to the significant efforts of all countries in sports, sports governance has also attracted considerable attention from scholars. However, the evaluation of global sports governance has rarely been discussed. This paper analyzes the principles for selecting indicators of global sports governance and develops a global sports governance evaluation indicator system consisting of 3 first-level indicators, 6 s-level indicators, and 14 third-level indicators. Additionally, this paper conducted an empirical study of the indicator system using the deep trust network model, and the results showed that the research on the evaluation index system of global sports governance based on the deep trust network model is feasible. Compared with the actual scores, the evaluation gaps for sports facility satisfaction, sports information satisfaction, and sports activity satisfaction were only 0.05, 0.09, and 0.05, respectively. Overall, this method is more accurate in analyzing the evaluation index system of global sports governance and can more directly and objectively reflect the shortcomings of current global sports governance, providing specific analysis of particular problems. The paper suggests that current global sports governance should focus on the coverage of sports facilities, attention to mass sports, satisfaction of sports activities, and promote in-depth development through both hard and soft governance measures.

Methodology for a preliminary assessment of water use sustainability in industries at sub-basin level.

The sustainability of industrial production, especially for highly water-demanding processes, is strictly related to water resource availability and to the dynamic interactions between natural and anthropogenic requirements over the spatial and temporal scales. The increase in industrial water demand raises the need to assess the related environmental sustainability, facing the occurrence of global and local water stress issues. The identification of reliable methodologies, based on simple indices and able to consider the impact on local water basins, may play a basilar role in water sustainability diagnosis and decision-making processes for water management and land use planning. The present work focalized on the definition of a methodology based on the calculation of indicators and indices in the view of providing a synthetic, simple, and site-specific assessment tool for industrial water cycle sustainability. The methodology was built starting from geo-referenced data on water availability and sectorial uses derived for Italian sub-basins. According to the data monthly time scale, the proposed indices allowed for an industrial water-related impacts assessment, able to take into account the seasonal variability of local resources. Three industrial factories, located in northern (SB1, SB2) and central (SB3) Italian sub-basins, were selected as case studies (CS1, CS2, CS3) to validate the methodology. The companies were directly involved and asked to provide some input data. The methodology is based on the calculation of three synthetic indexes: the Withdrawal and Consumption water Stress Index (WCSI) allowed for deriving a synthetic water stress level assessment at the sub-basin scale, also considering the spatial and temporal variations; the industrial water use sustainability assessment was achieved by calculating the Overall Factory-to-Basin Impact (OFBI) and the Internal Water Reuse (IWR) indices, which allowed a preliminary evaluation of the factories' impacts on the sub-basin water status, considering the related water uses and the overall pressures on the reference territorial context. The WCSI values highlighted significant differences between the northern sub-basins, characterised by limited water stress (WCSISB1 = 0.221; WCSISB2 = 0.047), and the central ones, more subjected to high stress (WCSISB3 = 0.413). The case studies CS1 and CS3 showed to exert a more significant impact on the local water resource (OFBICS1 = 0.18%; OFBICS2 = 0.192%) with respect to CS2 (OFBI = 0.002%), whereas the IWR index revealed the different company's attitude in implementing water reuse practices (IWRCS1 = 40%; IWRCS1 = 27%; IWRCS1 = 99%). The proposed methodology and the indices may also contribute to assessing the effectiveness of river basin management actions to pursue sustainable development goals.

The Construction of a Community Long-term Care Model for Home-based Elderly Individuals.

With rapidly aging populations, family care functions can become weakened, and community health services often lack unified standards. A standardized and professional community home-based long-term care model (CHLCM) for the elderly is urgently needed in many regions of China and in other countries. Here, we explored the indicators of the need for a CHLCM among elderly individuals, and we constructed a CHLCM. We created and distributed a questionnaire regarding the requirement of long-term care services, based on a literature review. The two-rounds Delphi method was used, involving 20 experts who were randomly selected from among the medical universities, community health service centers, and nursing homes in Nanning, Guangxi, China. The experts' enthusiasm rates in the questionnaire's two rounds were 95% and 100%, respectively. The authentic coefficient of the experts' consulting was 0.857, and that of the experts' academic level was 0.835; the judgement coefficient was 0.880 and the familiar coefficient was 0.855. The CHLCM includes service content and an evaluation. The coordination coefficients for the two primary, eight secondary, and 29 tertiary indicators were 0.200, 0.386, and 0.184, respectively (p<0.05). The experts' enthusiasm and authority were high. The coordination of the experts' agreement was sufficient, and the analysis results were reliable. The CHLCM includes 29 items that provide a foundation and references for the formulation of concrete indicators and subsequent research.

Sustainable development trial undertaking: Experience from China's innovation demonstration zones.

In December 2016, China proposed creating about ten sustainable development demonstration zones to create a batch of replicable and extendable demonstration models to fully realize the 2030 sustainable development goals (SDGs) and provide a reference for similar regions of emerging economies. It has now approved six cities that act as green and low carbon lifestyle laboratories. However, very few documents quantitatively evaluate this policy's natural, economic, and social impact. This article comprehensively uses dynamic stochastic general equilibrium (DSGE) methods and input-output methods to portray the urgency of sustainable development in China. This article sets the sustainable indicator system for the approved six cities and sets scenario simulations based on transformation needs for quantitative evaluation. The results show that demonstration zones policies would lead to a decline in the output of heavily polluting industries. However, in China's current coal-dominated energy structure, the degree of positive impact on the growth of clean industry output would be less than the intensity of the impact on heavily polluting industries.

Predictive analysis of water resource carrying capacity based on system dynamics and improved fuzzy comprehensive evaluation method in Henan Province.

The water resource carrying capacity (WRCC) is a carrying capacity of natural resources. It affects the application and expansion of the carrying capacity of water resources. This subject involves various elements, such as water resources, the ecological environment system, humans and their economic and social systems, and a wider range of biological groups and their survival needs. Based on the objective recognition of the complex relationship between the water resource system, ecological environment system, and economic and social system, the support scale of water resources and the ecological environment for economic and social development is studied. Current research on the carrying capacity of water resources has mostly shifted from the previously limited support capacity of water resources to include factors such as the population, economy, and ecology, establishing the internal relationships between the economics, water resources, and ecological environment. This reflects the comprehensive carrying capacity of the entire region (or river basin) of water resources and the ecological environment system on an overall economic and social scale. Based on the conceptual connotation of the WRCC and the actual problems facing water resources in Henan Province, the paper uses a system dynamics method to develop information feedback between the four subsystems of Henan Province: economic, population, water resource, and water environment subsystems. The index system of the WRCC in Henan Province is also determined. The weight of each index is comprehensively determined by a combination weighting method of the analytic hierarchy process and an entropy weight method, and then a fuzzy comprehensive evaluation method is used to evaluate the WRCC of Henan Province under four different development models. The validation period of the model is 2010-2020, and the forecast period is 2021-2030. The results indicate that during the period 2021-2030, the WRCC of Henan Province showed a slight upward trend overall under the four models, but the increase rates were different under the different models. Among the four models, the comprehensive model's benefit was the best, which not only maintained the healthy and stable development of the economy and society but also improved the pressure on the water resources and the quality of the water environment.

Quantitative analysis of economic and environmental benefits for land fallowing policy in the Beijing-Tianjin-Hebei region.

The Beijing-Tianjin-Hebei region (BTH region) is a major crop-producing region of China suffering from environment deterioration. Land fallowing policy is widely used as the solution of agriculture-related environment pollution, while it is difficult to derive a quantitative basis for policy-making. An indicator system was established to quantitatively analyse economic and environmental benefits of land fallow policies in the BTH region. The system consisted of 8 indicators to describe the water, air and economic influences caused by land fallowing policy such as the amount of nutrient discharged, the emission of PM2.5-related and greenhouse gas, and the input and output of agriculture production. SWAT (Soil and Water Assessment Tool) and IAP-N (Improving Anthropogenic Practices of managing reactive Nitrogen) models were used to quantify environmental indicators. Five scenarios with different planting patterns and fallow intensities were simulated for five years with different hydrological conditions. It is found that the influence of policy on water environment is highly sensitive to hydrological conditions, while the influence on air environment and economy are more affected by different policy settings in scenarios. The marginal utilities of the fallowed area are indicator-dependent. Planting alternative crops can decrease production costs and keep crop yields, while may also cause atmospheric environmental pollution if the crops have nitrogen fixing ability. Indicators also have spatial and temporal heterogeneity under different planting patterns and fallow intensities. A policy evaluation and associated uncertainty analysis is essential for effective implementation. The analysis framework established could support decision-making in regions facing agri-environmental problems.

Water sustainability assessment from the perspective of sustainable development capitals: Conceptual model and index based on literature review.

Decision-making associated with the promotion of water sustainability is subjected to uncertainties arising, on the one hand, from the current capacity of understanding socio-environmental systems and their temporality, complexity and multidimensionality; and, on the other hand, from the need to represent key aspects of these systems through data and information. Such a representation is often supported by indicators, indices and systems of indicators for relevant aspects of the problem and for a scenario under analysis. In this context, the main aim of this study was to develop a novel system of indicators for water sustainability assessment in river basins. Literature review and content analysis were used to define an analytical structure for the problem from the perspective of the natural, social and built capitals of related sustainable development assessment. Each capital has been hierarchically subdivided into categories, subcategories and attributes, leading to 54 aspects for water sustainability assessment. A list of indicators was compiled from the scientific and technical literature, linked to attributes, and associated with valuation ranges. This led to the proposition of the River Basin Water Sustainability Index (RBWSI) and sub-indices associated with categories and subcategories of the model. The timeframe and territorial scale relevant for assessment were defined as five-to-ten year periods and areas under the jurisdiction of river basin management committees, respectively. The new model and index thus proposed may be useful in water sustainability diagnostic and prognostic studies, such as required to assess the effectiveness of river basin management actions aimed at promoting sustainable development.

Sustainable development assessment from a capitals perspective: Analytical structure and indicator selection criteria.

Sustainable development assessment has been conducted considering its various dimensions, such as environmental, social, cultural and economic. In this paper, the representation of such dimensions is undertaken from the perspective of the natural, social and built capitals. These dimensions are usually represented by indicators, indexes and systems of indicators, but their abundance in the technical and scientific literatures without adequate analytical structures can impair assessment quality and speed. This study aimed to propose a structure for sustainable development assessment whereby key aspects and indicators can be identified, prioritised and meaningfully used from the perspective of sustainable development capitals. Content analysis of selected international papers and technical reports was undertaken to identify relevant analysis elements and their hierarchical order. This has led to a four-tier framework composed of three capitals, seven categories, 19 subcategories and 52 attributes, each of which can be measured with the aid of one or more locally relevant indicator(s) in the context of sustainable development assessment. Selection criteria for such indicators were compiled from the literature and are presented in terms of their political, management, data quality and economic relevance. This study may contribute to the development and refinement of structured sustainable development indicator systems with less analytical ambiguity, overlapping and gaps, and hence improve the representativeness of future assessment efforts.

Analysis on the Development of Digital Economy in Guangdong Province Based on Improved Entropy Method and Multivariate Statistical Analysis.

The lack of adequate indicators in the research of digital economy may lead to the shortage of data support on decision making for governments. To solve this problem, first we establish a digital economy indicator evaluation system by dividing the digital economy into four types: "basic type", "technology type", "integration type" and "service type" and select 5 indicators for each type. On this basis, the weight of each indicator is calculated to find the deficiencies in the development of some digital economic fields by the improved entropy method. By drawing on the empowerment idea of Analytic Hierarchy Process, the improved entropy method firstly compares the difference coefficient of indicators in pairs and maps the comparison results to the scales 1-9. Then, the judgment matrix is constructed based on the information entropy, which can solve as much as possible the problem that the difference among the weight of each indicator is too large in traditional entropy method. The results indicate that: the development of digital economy in Guangdong Province was relatively balanced from 2015 to 2018 and will be better in the future while the development of rural e-commerce in Guangdong Province is relatively backward, and there is an obvious digital gap between urban and rural areas. Next we extract two new variables respectively to replace the 20 indicators we select through principal component analysis and factor analysis methods in multivariate statistical analysis, which can retain the original information to the greatest extent and provide convenience for further research in the future. Finally, we and provide constructive comments of digital economy in Guangdong Province from 2015 to 2018.

An integrated model to evaluate the impact of social support on improving self-management of type 2 diabetes mellitus.

BACKGROUND: Type 2 Diabetes Mellitus (T2DM) is a chronic disease closely related to personal life style. Therefore, achieving effective self-management is one of the most important ways to control it. There is evidence that social support can help to improve the self-management ability of patients with T2DM, but which social support is more effective has been rarely explored. The purpose of this study is to construct an integrated model to analyze which social support has more significant impact on self-management of T2DM, and provide reasonable suggestions to health care providers on how to effectively play the role of social support. METHODS: We established a social support indicator evaluation system and proposed an integrated model that combines ANP (Analytical Network Process) and CRITIC (CRiteria Importance through Intercriteria Correlation) methods to evaluate the impact of social support on T2DM self-management from both subjective and objective perspectives. The weights calculated by the model will serve as the basis for us to judge the importance of different social support indicators. RESULTS: Informational support (weighting 49.26%) is the most important criteria, followed by tangible support (weighting 39.24%) and emotional support (weighting 11.51%). Among 11 sub-criteria, guidance (weighting 23.05%) and feedback (weighting 14.68%) are two most relevant with T2DM self-management. This result provides ideas and evidence for health care providers on how to offer more effective social support. CONCLUSION: To our knowledge, this is the first study in which Multi-Criteria Decision Making (MCDM) tools, specifically ANP and CRITIC, are used to evaluate the impact of social support on improving self-management of type 2 diabetes. The study suggests that incorporating two sub-indicators of guidance and feedback into the diabetes care programs may have great potential to improve T2DM self-management and further control patient blood glucose and reduce complications.

[Validation and optimization of the indicator system of risk assessment for mechanical cuts].

Objective: To validation and optimization the indicator system of risk assessment for mechanical cuts. Methods: The risk assessment index system of mechanical cutting injury established earlier was used to assess the risk of mechanical cutting injury in 40 cases of mechanical cutting injury registered from January 2015 to December 2017 and 40 similar positions without accidents in the same period. The multiple stepwise regression analysis was used to screen the indicator system, and to adjust the weight coefficient of each index. The total coincidence rate and Kappa value were compared between before and after optimization respectively. Results: The new index system has 3 first-class indicators, 10 second-class indicators and 14 three-class indicators, fewer than the old index system which has 3 first-class indicators, 10 second-class indicators, 34 three-class indicators. There three indicators have revamped in the first-class. The total of coincidence rates of the new and old indicator systems were 67.50% and 90.00%, the difference was statistically significant (P<0.01). The Kappa value were 0.35 and 0.80, respectively. Conclusion: The evaluation results with new indicator systems is more consistent with the actual hazard detection the the old indicator systems, and scientific, reasonable and practical, and the indicator system of risk assessment for mechanical cuts can be used for the risk assessment of mechanical cutting injuries.

Developing a geographical-meteorological indicator system and evaluating prediction models for alveolar echinococcosis in China.

BACKGROUND: Geographical and meteorological factors have been reported to influence the prevalence of echinococcosis, but there's a lack of indicator system and model. OBJECTIVE: To provide further insight into the impact of geographical and meteorological factors on AE prevalence and establish a theoretical basis for prevention and control. METHODS: Principal component and regression analysis were used to screen and establish a three-level indicator system. Relative weights were examined to determine the impact of each indicator, and five mathematical models were compared to identify the best predictive model for AE epidemic levels. RESULTS: By analyzing the data downloaded from the China Meteorological Data Service Center and Geospatial Data Cloud, we established the KCBIS, including 50 basic indicators which could be directly obtained online, 15 characteristic indicators which were linear combination of the basic indicators and showed a linear relationship with AE epidemic, and 8 key indicators which were characteristic indicators with a clearer relationships and fewer mixed effects. The relative weight analysis revealed that monthly precipitation, monthly cold days, the difference between negative and positive temperature anomalies, basic air temperature conditions, altitude, the difference between positive and negative atmospheric pressure anomalies, monthy extremely hot days, and monthly fresh breeze days were correlated with the natural logarithm of AE prevalence, with sequential decreases in their relative weights. The multinomial logistic regression model was the best predictor at epidemic levels 1, 3, 5, and 6, whereas the CART model was the best predictor at epidemic levels 2, 4, and 5.

Rural revitalization in China: Measurement indicators, regional differences and dynamic evolution.

It is crucial to scientifically assess China's rural revitalization and grasp its evolution laws. This paper constructs an indicator system to measure the level of rural revitalization in China from 2011 to 2021 using the entropy weight method. Then, we explore the spatial and temporal divergence and dynamic evolutionary characteristics of rural revitalization using the Dagum Gini coefficient and Kernel density. We found that the level of rural revitalization in China is low but fluctuating and increasing. Regionally, eastern China scores higher than central, western and northeastern China. In terms of dimensions, ecological livability scores are higher than prosperous industry, effective governance, affluent living and civilized countryside in that order. The regional differences in the level of rural revitalization are mainly reflected between regions, especially between eastern and western China, but the gap between regions is narrowing year by year. And the results of the Kernel density show that the level of rural revitalization in China shows a slow and balanced growth, but the eastern China shows a polarization growth. These findings can provide a comprehensive and objective outline of the advantages and shortcomings of rural revitalization development in China, and provide a policy reference for the comprehensive and stable promotion of rural revitalization construction.

Construction and assessment of an indicator system of stream conditions in a typical mountain landscape in Northeast China.

Stream ecosystem health assessments are crucial for the effective management of aquatic ecosystem service functions and the assessment of anthropogenic and climatic impacts on aquatic ecosystems. However, there is still a lack of comprehensive assessment methods based on complete ecosystem structures. This study improved an ecological health assessment system, which consists of 13 indicators based on ecosystem structure. The assessment system was applied to 30 streams on Changbai Mountain. The results showed that the comprehensive index of stream health (ISH) in Changbai Mountain was relatively high, and the ISH increased with the elevation gradient. The dominant factors controlling the ecosystem health level were water pH, water flow, vegetation coverage, total phosphorus (TP), and vegetation diversity index. All these results indicated that the damage caused by excessive deforestation and farmland occupation in recent years has not been fully reversed and that human disturbance from tourism may be the main reason for the low stream health at lower elevations. Our results suggest that the key to future work is to increase quantitative research on disturbance sensitivity and to develop economically viable restoration measures.

The role of large reservoirs in drought and flood disaster risk mitigation: A case of the Yellow River Basin.

The acceleration of water cycle processes in the context of global warming will exacerbate the frequency and intensity of extreme events and predispose to drought and flood disasters (DFD). The Yellow River Basin (YRB) is one of the basins with significant and sensitive impacts of climate change, comprehensive assessment and prediction of its DFD risk are of great significance for ecological protection and high-quality development. This study first constructed an evaluation index system for drought disaster risk and flood disaster risk based on hazard, vulnerability, exposure and the role of large reservoirs. Secondly, the weights of each evaluation index are established by the analytic hierarchy process. Finally, based on the four-factor theory of disasters, an evaluation model of DFD risk indicators is established. The impact of large reservoirs on DFD risk in the YRB is analyzed with emphasis. The results show that from 1990 to 2020, the drought disaster risk in the YRB is mainly distributed in the source area of the Yellow River and the northwest region (11.26-15.79 %), and the flood disaster risk is mainly distributed in the middle and lower reaches (30.04-31.29 %). Compared to scenarios without considering large reservoirs, the area at risk of high drought and high flood is reduced by 45.45 %, 44.22 % and 31.29 % in 2000, 2010 and 2020, respectively. Large reservoirs in the YRB play an important role in mitigating DFD risk, but their role is weakened with the enhancement of the emission scenario. Under the influence of different scenario models, the DFD risk in the YRB in 2030 and 2060 will increase, and the area of high drought and high flood risk in the middle and upper reaches of the basin will increase by 0.26-25.15 %. Therefore, the YRB should play the role of large reservoirs in DFD risk defense in its actions to cope with future climate change, while improving non-engineering measures such as early warning and emergency management systems to mitigate the impacts of disasters.

Construction of China's food security evaluation index system and spatiotemporal evolution.

Food security is a vital material foundation for a nation's development and has been a topic of significant concern on the international stage in recent years. With a population exceeding 1.4 billion, China is not only a major producer but also a substantial consumer of food. Ensuring food security in China is not only a top priority for its socio-economic development but also a driving force in maintaining the stability of the global food supply chain and reducing the number of hungry people worldwide. However, a lack of comprehensive research into the Chinese food security system remains. This study addresses this gap by constructing a comprehensive evaluation framework encompassing four dimensions: food supply, accessibility, production stability, and sustainability. Utilizing the Moran's Index and generating LISA (Local Indicators of Spatial Association) maps, we analyze the spatial correlations of food security. The Dagum Gini coefficient and kernel density estimation are applied to assess heterogeneity and spatial disparities. Furthermore, this research employs the Exponential Smoothing (ETS) model to forecast food security trends. The findings reveal that the overall composite food security score exhibited fluctuations, initially increasing and reaching its peak of 0.407 in 2003, followed by a subsequent sharp decline after 2019. Spatially, food security exhibits correlations, with the Huang-Huai-Hai Plain and Northeast regions consistently showing high-high clustering. In contrast, the Western and Southern regions exhibit low-low clustering at specific periods. The Dagum Gini coefficient indicates that overall food security disparities are relatively small. However, these disparities have gradually expanded in recent years, with inter-group differences becoming predominant after 2005. As indicated by the kernel density estimation, the dynamic distribution of food security initially widens and then narrows, suggesting a shift from dispersed to concentrated data distribution. This phenomenon is accompanied by polarization and convergence trends, particularly evident after 2015. According to the ETS model, the study forecasts a substantial risk of declining food security in China over the next decade, largely influenced by the ongoing pandemic. In conclusion, this research provides a comprehensive assessment of the changing status of food security in China. It offers early warnings through predictive analysis, addressing the existing research gaps in the field of food security.

Cleaner production evaluation system for textile industry: An empirical study from LCA perspectives.

The contradiction between the rapid textile expansion and intensive energy consumption, highly environmental pollution calls for the adoption of cleaner production (CP). However, current evaluation system mainly targeted on CP at production stage, guidance and support on the life cycle assessment is still in its infancy. Meanwhile few studies brought the combination of water conservation and carbon reduction into considerations. This study compared the existing CP evaluation systems including guidelines for the whole industry, standards for textile industry and indicators for the dyeing and finishing sector by quantifying the differences of indicator score compositions. Comparisons analysis from six aspects suggested that all the evaluation systems had relevant indicators regarding "pollutant emissions". "Management", "process equipment and techniques" and "resource and energy consumption" have also been well concerned while "product characteristic" seemed to be overlooked at current stage. From the perspective of whole life cycle, the key of textile processing is the "printing and dyeing" (44.23 %) followed by "fabric manufacturing"(28.85 %) and setting (15.38 %). With regards to the environmental impacts, resources depletion gained the highest attention since their indicator scores reached up to 25.71 %, 18.47 % and 20.62 % for EMAS, ERG 2018 and HJ-1852006. Cleaner production awareness and social impact also played significant roles in ISO 14031:2021 and WMG. Subsequently, a set of new comprehensive CP evaluation indicator system was established, including 3 scopes and 7 goals. The newly-built indicator system incorporated with life cycle perspectives gave a powerful tool to measure the CP level in textile industry and of CP will benefit from water reuse and energy utilization with high efficiency.