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.

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.

Government's public panic emergency capacity assessment and response strategies under sudden epidemics: A fuzzy Petri net-based approach.

In the post-epidemic era, public panic has emerged as a highly significant secondary disaster, necessitating an urgent enhancement of emergency management capabilities by governments at all levels. In order to ensure a robust assessment of the government's ability to manage public panic, it is crucial to effectively address the influence of uncertain and ambiguous factors associated with such scenarios. This paper proposes a governmental public panic emergency management capability assessment method based on fuzzy Petri nets. By analyzing the factors influencing public panic across the four evolutionary stages, namely gestation, outbreak, diffusion, and fading, we establish a hierarchical evaluation index system for assessing emergency management capabilities. Additionally, we develop a range of multi-scenario emergency management strategies. To address the challenges posed by uncertainty, randomness, fuzziness, and insufficient statistical data within the assessment index system, we introduce fuzzy Petri nets and fuzzy reasoning rules to evaluate the emergency management capability of the assessment system and derive the optimal emergency management strategy. According to example simulations, the effectiveness and practicality of models and rules constructed using fuzzy Petri nets are demonstrated, highlighting their superiority over traditional assessment methods. This comprehensive approach equips the government with a versatile toolkit for effectively managing public panic emergencies.

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.

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.

Evaluation of primary-level credit environment, indicator system and empirical analysis: A case study of credit construction in China county and district.

Townships (towns, streets) represent the foundational layer of China's administrative structure, and the quality of their credit environment is crucial for underpinning the development of a primary-level social credit system. This initiative aims to accelerate the establishment of the social credit system and cultivate a trustworthy economic and social environment. Starting from the three major fields of government, business and society, and focusing on integrity culture and credit innovation, the article proposes an innovative evaluation framework for primary-level credit environment and it can become a point of reference as a policy tool in international evaluation programs. Using clustering and the coefficient of variation methods, we quantitatively refine our indicator system, establishing a set of criteria to assess the primary-level credit environment. We incorporate hierarchical analysis, the entropy weight method, and machine learning models to conduct a comprehensive evaluation of the credit environments within 24 townships (towns, streets) of Fuyang District in Hangzhou City for the year 2023. The findings underscore the need for a realistic appraisal of the current state and deficiencies of the primary-level credit environment. We advocate for the bolstering of credit development within governmental, business, and societal realms. It's imperative to leverage the normative influence of honesty and integrity culture, enhance the breadth and application of credit innovations, and thereby foster the high-quality growth of the primary-level social credit system.

Dynamic evolution and obstacle factor analysis of green development in China's agriculture and rural areas based on entropy-based TOPSIS model.

Green development of agriculture and rural areas (GDARA) is an essential part of rural revitalization and high-quality development. Based on 2011 to 2020 provincial panel data from China, the entropy-based Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) model is constructed to measure the level of GDARA, finding that the overall level during the sample period was positive. Then the regional differences mainly from intra-regional were revealed by the methods of Dagum Gini coefficient and Kernel density estimation and were shrinking overall. Besides, the results of Markov chain transfer matrix show the dynamic characteristics clearly, which the low-level regions shift to the middle and high levels with a greater probability. The results of the spatial autocorrelation test display that GDARA has a spatial clustering effect. Finally, the industrial upgrading and the business income of leisure agriculture are respectively proven to hinder GDARA at most by the Obstacle degree model empirically. Based on a series of empirical tests, a few relevant policy recommendations are proposed to promote the road to strong agriculture and rural areas in China.

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.

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.

Characterizing the water resource-environment-ecology system harmony in Chinese cities using integrated datasets: A Beautiful China perspective assessment.

Integrated management and synergistic improvement of the water system is a topic of widespread concern. This study innovatively integrates three functions of quality assessment, synergy evaluation, and driving influence determination to establish a systematic framework assessing water system harmony. A case study of 336 Chinese cities is further performed by combining multi-scale and multi-source datasets. The results show China's water system quality has improved from 2015 to 2022. Development in the water resource, environment, and ecology subsystems have been differentiated, with 0.05 %, 4.33 %, and -1.64 % changes, respectively. The degradation of water ecology and the weak synergy with the other two subsystems have limited China's water system harmony. Water environment improvement played a contributive role in improving the water system quality. The contribution structure of water resources, environment, and ecology has shifted towards equilibrium in recent years. We found and highlighted the north-south differentiation of water system harmony in Chinese cities. The Beijing-Tianjin-Hebei and its surroundings, the Yangtze River Delta, and the middle reaches of the Yangtze River are identified as priority regions for water system harmony improvement. The primary contribution of this study is to propose an assessing concept of water resource-environment-ecology system harmony, establish well-structured assessment methods, and integrate the multiple data sources. The novel methods and findings, including the indicator system, application of data mining and decomposing methods, and the city-level water system harmony map, deconstruct and quantify the complex and diverse water system, supporting clearer and more efficient water management policymaking.

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.

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.

Proposal to measure tourism development within a destination and segment its different territories.

Tourism offers a means of promoting a local development strategy capable of harnessing the resources available within a territory. In order to do this, we must know the potential for tourism development in each territory, as well as the factors that would condition it. In this article, a methodology (based on the design of a system of indicators, the construction of composite indexes, and segmentation by means of cluster analysis) is proposed to measure tourism development within an emerging country and segment its different territories. The case study chosen to validate this methodology is Ecuador, a country with interesting tourist potential, where individual cities have very different levels of tourism development. The results highlight the factors that drive or constrain the degree of tourism development presented by the cities analysed, thereby facilitating decision-making for major stakeholders in each of them.

Performance Evaluation of Urban Emergency Governance: Conceptual Connotations and Empirical Research Based on the Crisis Life Cycle Theory.

Although scholars have discussed in depth about the evaluation content and the construction of evaluation index system of emergency management and crisis management, a unified and standardized interpretation of system construction concepts and empirical research on the performance evaluation of urban emergency management is still lacking. In view of this, this paper is based on the theory of the  crisis life cycle, with the four phases of urban emergency management and the content of the task as a clue, constructed a performance evaluation index system containing 12 primary indicators and 44 secondary indicators, and centered on the emergency management work situation of S city. The study reveals that emergency management underperforms in S city, with a score of 5.948, qualifying as the "defined level". The "prevention and preparedness stage" receives poor evaluation, indicating a significant bias for crisis response instead of prevention. The report suggests the improvement of emergency material stockpile planning, the formation of grassroots emergency response teams, the emergency management publicity, and special emergency drill plans, etc., with a view to providing reference for city managers to comprehensively review and evaluate the emergency management system, and to promote the construction of a more systematic, complete and scientific urban emergency management system.

Measurement and factor analysis of carbon neutrality development level in eastern China.

The Chinese government has officially announced that China's carbon dioxide emissions will reach to peak before 2030 and achieve carbon neutrality before 2060. Based on the carbon neutrality development of 12 provinces and cities in eastern China from 2010 to 2019, this paper constructs an evaluation index system, and it uses the entropy weight method and coefficient of variation method to measure the carbon neutrality development level in the eastern China. The results show that from 2010 to 2019, the changes of carbon source level in 12 provinces and cities in the eastern China are lower than the changes in carbon sink level, and the changes of carbon source and sink level in most provinces and cities show the increasing trend. Spatially, the carbon neutral development level shows the differentiation characteristics of "low in the middle, high in the north and south." The main factors affecting the carbon neutrality level of eastern provinces and cities include policy, economic development and industrial structure, energy intensity and structure, urban development, and population size ecological environment. High-value areas are mainly distributed in Heilongjiang Province, Jilin Province and Fujian Province. Low-value areas are mainly distributed in Jiangsu Province and Shandong Province. Eastern China still needs to strengthen its emphasis on low-carbon policies. For Shandong Province, Jiangsu Province, and Hebei Province, policies should be introduced to reduce carbon sources, accelerate their industrial upgrading, and optimize their energy use structure. For Beijing City, Shanghai City, Heilongjiang Province, and Jilin Province, policies should be introduced to develop carbon sinks while maintaining their low carbon source levels. For Beijing City and Shanghai City, policies related to green and low-carbon technologies should be introduced to promote the development of carbon sink capacity through low-carbon technologies in limited urban areas.

The development and application of a two-step surveillance process for Healthy China Initiative based on wide coverage interagency data.

BACKGROUND: Healthy China is a nationwide health strategy aiming at improving health from diverse dimensions, and strengthening high-quality assessment is essential for its stimulation. However, there is limited evidence in the surveillance of the actual performance of the initiative at regional levels. This study innovatively proposes a two-step surveillance process which comprehensively monitors Healthy China Initiative based on regional realities, thus provides guidance for policymaking. METHODS: A flexible indicator system was firstly developed basing on Delphi survey and focus group discussions. And then the Analysis Hierarchical Process and the TOPSIS method were used to determine the weights of indicators and calculate comprehensive indexes as the surveillance outcomes. A pilot study was conducted in a typical area in China to verify the applicability of the process. RESULTS: Following the surveillance process and basing on the implementation of Healthy China Initiative in the target region, an indicator system comprised of 5 domains and 23 indicators with weights was first developed specifically for the pilot area. Then 1848 interagency data of the study area were collected from 8 provincial institutions/departments to calculate the indexes and ranks of the five domains which were health level, healthy living, disease prevention and control, health service, and healthy environment. The outcomes showed that Healthy China Initiative in the pilot area had been constantly improved since the strategy proposed, while there were still issues to be tackled such as the deficient monitoring mechanisms and unevenly development progress. CONCLUSIONS: This study proposed a pragmatic surveillance process with indicators which could be tailored for specific context of target regions and produce meaningful surveillance outcomes to inform decision-making for policymakers, and also provided a theoretical foundation as well as empirical evidence for further health strategies and plannings assessment studies.

Study on the spatial distribution of urban carbon emissions at the micro level based on multisource data.

Global warming is currently an area of concern. Human activities are the leading cause of urban greenhouse gas intensification. Inversing the spatial distribution of carbon emissions at microscopic scales such as communities or controlling detailed planning plots can capture the critical emission areas of carbon emissions, thus providing scientific guidance for intracity low-carbon development planning. Using the Sino-Singapore Tianjin Eco-city as an example, this paper uses night-light images and statistical yearbooks to perform linear fitting within the Beijing-Tianjin-Hebei city-county region and then uses fine-scale data such as points of interest, road networks, and mobile signaling data to construct spatial characteristic indicators of carbon emissions distribution and assign weights to each indicator through the analytic hierarchy process. As a result, the spatial distribution of carbon emissions based on detailed control planning plots is calculated. The results show that among the selected indicators, the population distribution significantly influences carbon emissions, with a weight of 0.384. The spatial distribution of carbon emissions is relatively distinctive. The primary carbon emissions are from the Sino-Singapore Cooperation Zone due to its rapid urban construction and development. In contrast, carbon emissions from other areas are sparse, as there is mostly unused land under construction.

Responsibly shaping technology innovation for the energy transition: an RRI indicator system as a tool.

Efforts to reduce global greenhouse gas emissions have had limited success. For many, the hopes rest on new energy innovations to advance the energy transition process. In this paper, we develop a Responsible Research and Innovation (RRI) base indicator system to steer the design of innovations in the field of energy transition innovations and, thus, improve social acceptance of these innovations. We propose a guideline for its application to assist R&D performing organizations and funding organizations in the design, selection, and communication of research proposals. The indicator system is intended to promote early integration of environmental and social aspects, support the formation of teams aware of the different responsibility aspects of innovation, and monitor progress in regard to relevant RRI dimensions.

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.