Enhancing older care services: a comprehensive internet + community home indicator system.

OBJECTIVE: Constructing a demand-oriented Internet + community home care service indicator system, starting from the actual needs of the elderly, and quantifying the demand into specific service contents that can be provided, so as to realize the effective supply of services. It aims to provide a theoretical basis for the government to formulate relevant aging policies and provide a reference basis for promoting the innovation and development of the Internet + elderly care model. METHODS: Based on existence needs, relationship needs and growth needs abbreviated as "Existence, Relatedness, Growth (ERG)" demand theory, through the discussion in the group meeting, form the expert consultation questionnaire of the demand-oriented Internet + community home care service indicator system, select experts in related fields to conduct two rounds of Delphi expert consultation, summarize the experts' opinions to determine the indicator system items, and use the Analytic Hierarchy Process (AHP) method to construct the judgment matrix to derive the weighting coefficients of the indicators, and establish the ultimate demand-oriented Internet + community home care service indicator system. RESULTS: The effective recovery rates for the two rounds of expert consoulation questionnaires were 100%, with expert authority coefficients of 0.852 and 0.868, respectively. The Kendall coefficients for the second round of expert views varied from 0.226 to 0.431, with coefficients of variation for all indexes less than 0.25.The finalized demand-oriented Internet + community home care service indicator system includes 3 first-level indicators, 10 s-level indicators, and 46 third-level indicators. The consistency ratios of indicator judgment matrices at all levels are less than 0.10, suggesting that the hierarchical analysis findings are consistent, implying that the weight coefficient distribution is appropriate. CONCLUSION: The demand-oriented Internet + community home care service Indicator System, which was created through expert consultation and AHP method, has reasonable content and is more dependable as an evaluation tool for reliably assessing demand for elderly servic.

A new performance evaluation indicator for the LEE Jong-wook Fellowship Program of Korea Foundation for International Healthcare to better assess its long-term educational impacts: a Delphi study.

PURPOSE: The Dr. LEE Jong-wook Fellowship Program, established by the Korea Foundation for International Healthcare (KOFIH), aims to strengthen healthcare capacity in partner countries. The aim of the study was to develop new performance evaluation indicators for the program to better assess long-term educational impact across various courses and professional roles. METHODS: A 3-stage process was employed. First, a literature review of established evaluation models (Kirkpatrick's 4 levels, CIPP model, OECD DAC criteria) was conducted to devise evaluation criteria. Second, these criteria were validated via a 2-round Delphi survey with 18 experts in training projects from May 2021 to June 2021. Third, the relative importance of the evaluation criteria was determined using the analytic hierarchy process (AHP), calculating weights and ensuring consistency through the consistency index (CI) and consistency ratio (CR), with CR values below 0.1 indicating acceptable consistency. RESULTS: The literature review led to a combined evaluation model, resulting in 4 evaluation areas, 20 items, and 92 indicators. The Delphi surveys confirmed the validity of these indicators, with content validity ratio values exceeding 0.444. The AHP analysis assigned weights to each indicator, and CR values below 0.1 indicated consistency. The final set of evaluation indicators was confirmed through a workshop with KFIH and adopted as the new evaluation tool. CONCLUSION: The developed evaluation framework provides a comprehensive tool for assessing the long-term outcomes of the Dr. LEE Jong-wook Fellowship Program. It enhances evaluation capabilities and supports improvements in the training program's effectiveness and international healthcare collaboration.

A GIS-MCDA approach to map environmental suitability of Posidonia oceanica meadows as blue nature-based solutions in the Mediterranean eco-region.

The growing environmental risks induced by interacting climate and human-induced pressures threaten the survival and growth of marine coastal ecosystems (MCEs) and the ecosystem services they provide. Nature-based solutions (NBS), consisting of ecosystem-based approaches, have emerged as vital tools for climate adaptation and mitigation facing biodiversity loss and societal challenges. Identifying suitable environmental conditions for implementing Blue-NBS in marine coastal areas is a key priority to drive robust and cost-effective nature-based adaptation pathways. This study developed a suitability model for Blue-NBS, with a specific focus on Posidonia oceanica meadows in the Mediterranean Sea under a baseline scenario. GIS-based Multiple Criteria Decision Analysis (MCDA) was applied for data integration and prioritization of different environmental variables in geomorphological (e.g., depth), water quality (WQ) (e.g., salinity), and climatic (e.g., thermal stress) sub-groups. Suitability classes and scores for each variable were determined using statistical distributions, ensuring a data-driven approach to defining environmental suitability. Variables' weights were derived from the Analytic Hierarchy Process (AHP) based on expert judgment and then combined with scores to generate suitability maps for managing Blue-NBS on seagrasses. Depth was found to be the most dominant environmental variable, with shallow areas (e.g., Northern Adriatic, Gulf of Gabés) showing higher suitability. The southern part of the Mediterranean (e.g., Egypt) reported relatively low scores for both climate and WQ, while the Northern Adriatic had the lowest WQ scores. This study represents the first attempt to evaluate Blue-NBS suitability for seagrass meadows at the eco-regional scale with geomorphologic, WQ, and climatic variables, providing decision support for the selection and allocation of Blue-NBS in different environmental settings. The resulting environmental suitability maps represent a basis for the integration of socio-economic and governance-related indicators into a more complex, multi-tier approach to support NBS mainstreaming.

Establishing an Evaluation Indicator System for User Satisfaction With Hypertension Management Apps: Combining User-Generated Content and Analytic Hierarchy Process.

BACKGROUND: Hypertension management apps (HMAs) can be effective in controlling blood pressure, but their actual impact is often suboptimal. Establishing a user satisfaction evaluation indicator system for HMAs can assist app developers in enhancing app design and functionality, while also helping users identify apps that best meet their needs. This approach aims to improve the overall effectiveness of app usage. OBJECTIVE: This study aims to systematically collect data on HMAs and their user reviews in the United States and China. It analyzes app usage patterns and functional characteristics, identifies factors influencing user satisfaction from existing research, and develops a satisfaction evaluation indicator system to provide more accurate recommendations for improving user satisfaction. METHODS: We conducted a descriptive statistical analysis to assess the development status of HMAs in both countries and applied the task-technology fit model to evaluate whether the app functionalities align with business needs. We separately summarized the factors influencing user satisfaction in both countries from previous research, utilized the analytic hierarchy process to develop an evaluation indicator system for HMA user satisfaction, and calculated satisfaction levels. Based on these findings, we propose improvements to enhance app functionality and user satisfaction. RESULTS: In terms of current development status, there were fewer HMAs and user reviews in China compared with the United States. Regarding app functional availability, fewer than 5% (4/91) of the apps achieved a demand fulfillment rate exceeding 80% (8/10). Overall, user satisfaction in both countries was low. CONCLUSIONS: In the United States, user satisfaction was lowest for advertising distribution, data synchronization, and reliability. By contrast, Chinese apps need improvements in cost efficiency and compatibility.

Optimizing Nutritional Decisions: A Particle Swarm Optimization-Simulated Annealing-Enhanced Analytic Hierarchy Process Approach for Personalized Meal Planning.

BACKGROUND/OBJECTIVE: Nutritionists play a crucial role in guiding individuals toward healthier lifestyles through personalized meal planning; however, this task involves navigating a complex web of factors, including health conditions, dietary restrictions, cultural preferences, and socioeconomic constraints. The Analytic Hierarchy Process (AHP) offers a valuable framework for structuring these multi-faceted decisions but inconsistencies can hinder its effectiveness in pairwise comparisons. METHODS: This paper proposes a novel hybrid Particle Swarm Optimization-Simulated Annealing (PSO-SA) algorithm to refine inconsistent AHP weight matrices, ensuring a consistent and accurate representation of the nutritionist's expertise and client preferences. Our approach merges PSO's global search capabilities with SA's local search precision, striking an optimal balance between exploration and exploitation. RESULTS: We demonstrate the practical utility of our algorithm through real-world use cases involving personalized meal planning for individuals with specific dietary needs and preferences. Results showcase the algorithm's efficiency in achieving consistency and surpassing standard PSO accuracy. CONCLUSION: By integrating the PSO-SA algorithm into a mobile app, we empower nutritionists with an advanced decision-making tool for creating tailored meal plans that promote healthier dietary choices and improved client outcomes. This research represents a significant advancement in multi-criteria decision-making for nutrition, offering a robust solution to the inconsistency challenge in AHP and paving the way for more effective and personalized dietary interventions.

Enhancing cassava grater design: A customer-driven approach using AHP, QFD, and TRIZ integration.

Due to consistent cassava cultivation, small-scale processing centers rely heavily on the cassava grater. However, these machines face stagnation in innovation and design evolution, leading to inefficiencies, limited capacity, and inconsistent output. Adding to these challenges is the competitive global market, demanding a focus on design enhancements. This study employs a multi-faceted approach involving the Analytic Hierarchy Process (AHP), Quality Function Deployment (QFD) and Theory of Inventive Problem Solving (TRIZ) to prioritize customer requirements, propose technically aligned solutions, and offer innovative design options for cassava graters. A total of 10 customer requirements (CR), 21 technical solutions (TS), and 63 innovative design options (IDO) were established and prioritized, aiming for easy adoption by fabricators, engineers, manufacturers, and artisans. Implementing these insights boosts cassava grater efficiency and productivity and significantly advances knowledge. This work presents a thorough scientific framework for product design, empowering local manufacturers to remain viable and relevant in the rapidly changing field of product enhancement.

Factors affecting small dental business in rural Germany: Evidence from Hessen.

OBJECTIVES: To determine how social factors influence career decisions of dental service providers, particularly focusing on examining the impact of dentists' origins. METHODS: Online survey of Hessian panel dentists, with pairwise comparisons to a set of factors impacting their decision-making process. An Analytic Hierarchy Process examined the weighting of influencing drivers in career choice. RESULTS: Dentists from rural backgrounds were more likely to establish practices in rural areas than those from urban origins. Origin correlated with entrepreneurial intentions and a strong association of rural origin. Dentists who grew up in rural areas were 4.19 times more likely to start a business. CONCLUSION: These findings may support efficient resource allocation and support for rural dental businesses.

Enhancing biometric system selection: A hybrid AHP-neutrosophic fuzzy TOPSIS approach.

A biometric system is essential in improving security and authentication processes across a variety of fields. Due to multiple criteria and alternatives, selecting the most suitable biometric system is a complex decision. We employ a hybrid approach in this study, combining the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with the Analytic Hierarchical Process (AHP). Biometric technologies are ranked using the TOPSIS method according to the relative weights that AHP determines. By applying the neutrosophic set theory, this approach effectively handles the ambiguity and vagueness inherent in decision-making. Fingerprint, face, Iris, Voice, Hand Veins, Hand geometry and signature are the seven biometric technologies that are incorporated in the framework. Seven essential characteristics are accuracy, security, acceptability, speed and efficiency, ease of collection, universality, distinctiveness used to evaluate these technologies. The model seeks to determine which biometric technology is best suited for a particular application or situation by taking these factors into account. This technique may be applied in other domains in the future.

Megacity solid waste disposal suitability mapping in Dhaka, Bangladesh: an integrated approach using remote sensing, GIS and statistics.

Selecting suitable Megacity Solid Waste Disposal (MSWD) sites is a challenging task in densely populated deltas of developing countries, exacerbated by limited public awareness about waste management. One of the major environmental concerns in Dhaka City, the world's densest megacity, is the presence of dumps close to surface water bodies resources. This study employed the Geographic Information System (GIS)-Analytic Hierarchy Process (AHP) framework to integrate geomorphological (slope and flow accumulation), geological (lithological and lineament), hydrogeological (depth to groundwater table and surface waterbody), socioeconomic (Land use land cover, distance to settlement, road, and airport), and climatological (wind direction) determinants, coupled by land-use and hydro-environmental analyses, to map optimal dumps (MSWDO) sites. The resulting preliminary (MSWDP) map revealed 15 potential landfill areas, covering approximately 5237 hectares (ha). Combining statistical analysis of restricted areas (settlements, water bodies, land use) with AHP-based ratings, the MSWDO map revealed two optimal locations (2285 ha). Additionally, the hydro-environmental analysis confirmed the unsuitability of northern sites due to shallow groundwater (< 5.43 m) and thin clay, leaving 11 options excluded. Sites 12 (Zone A, 2255 ha) and 15 (Zone B, 30 ha), with deeper groundwater tables and thicker clay layers, emerged as optimal choices for minimizing environmental risks and ensuring effective long-term waste disposal. This study successfully integrates remote sensing, geospatial data, and GIS-AHP modeling to facilitate the development of sustainable landfill strategies in similar South Asian delta megacities. Such an approach provides valuable insights for policymakers to implement cost-effective and sustainable waste management plans, potentially minimizing the environmental risks to achieve Sustainable Development Goals (SDGs) 6, 11, 13, and 15.

Developing an assessment tool for the healthy lifestyles of the occupational population in China: a modified Delphi-analytic hierarchy process study.

Lifestyle is an important factor affecting people's health. Evaluating and promoting healthy lifestyles among occupational population can not only improve work ability and efficiency, but also contribute to the prevention a variety of potential diseases. This study developed a preliminary index system based on literature review and group discussion. Two rounds of expert consultation were conducted on 12 experts using Delphi method. The questionnaire recovery rate of the two rounds of Delphi survey was over 85%, the expert authority coefficient was over 0.70, and Kendall W was 0.450 and 0.446, which were significant (P < 0.001). The weighting coefficient of each indicator was calculated using the hierarchical analysis method. Among them, the weighting coefficients of physical health lifestyle, mental health lifestyle, social adaptation lifestyle and occupational health lifestyle were 0.4133, 0.2922, 0.1078 and 0.1867, respectively. The consistency index CI = 0.024 and the consistency ratio CR = 0.027 of the first-level index judgment matrix. The weighting coefficient is acceptable and the indicators do not cause logical confusion. The healthy lifestyle assessment tool of the occupational population constructed in this study consists of 4 primary indicators, 13 secondary indicators and 45 tertiary indicators, which can provide a standardized and operable assessment tool for monitoring and evaluating the healthy lifestyle of the Chinese occupational population. At the same time, the weight analysis of various indicators through the analytic hierarchy process can also provide reference for the key areas of occupational health intervention.

Assessing forest fire dynamics and risk zones in Central Indian forests: a comparative study of the Khandwa and North Betul forest divisions of Madhya Pradesh.

Forest fires pose significant environmental and socioeconomic threats, particularly in regions such as Central India, where forest ecosystems are vital for biodiversity and local livelihoods. Understanding forest fire dynamics and identifying fire risk zones are crucial for effective mitigation. The current study explores the spatiotemporal dynamics of forest fires in the Khandwa and North Betul forest divisions in the Central Indian region over 22 years using Mann-Kendall and Sen's slope tests on MODIS (Moderate Resolution Imaging Spectroradiometer) fire point data. We found a nonsignificant increase in forest fires in both divisions. Khandwa showed a nonsignificant slope rise of more than three events per year, while North Betul revealed an increase of around one event per year. The lack of statistical significance suggests that upward trends of forest fire events may result from random fluctuations rather than consistent patterns. Spatial autocorrelation analysis revealed significant clustering of fire incidents in both regions. Khandwa confirmed moderate clustering (Moran's I = 0.043), whereas North Betul showed robust clustering (Moran's I = 0.096). Kernel density estimation further identified high-risk clusters in both divisions, necessitating zonal-wise targeted fire management strategies. Fire risk zonation was developed using the analytic hierarchy process (AHP), combining 10 environmental and socioeconomic factors. The AHP model, validated using MODIS fire data, showed reliable accuracy. The results revealed many of both divisions in the high- to very high-risk categories. Approximately, 45% of the area of the Khandwa and nearly 50% of the area of North Betul fall under high to very high fire risk zones. Khandwa's high-risk areas mainly lie in the northern and southeastern parts, while North Betul lies in the northwestern and north-eastern regions. The identified fire-prone areas indicate the pressing need for local or region-specific fire prevention and mitigation strategies. Thus, the findings of this study provide valuable insights into forest fire risk management and contribute to more focused research and methodological developments.

Practical evaluation of intelligent algorithms in ESG management of manufacturing enterprises.

ESG (Environmental, Social and Governance) management practice is an important part of promoting sustainable operation and development of manufacturing enterprises. Currently, traditional evaluation methods have limitations such as low efficiency and lack of objectivity. To improve the efficiency and accuracy of ESG evaluation and promote the optimization of ESG performance in manufacturing enterprises, this article combined data mining and analytic hierarchy process (AHP) to conduct effective research on ESG management practice evaluation in manufacturing enterprises. This article adopted the best priority search strategy to collect and process enterprise ESG data. By using AHP to construct hierarchical and segmented objectives for target problems, a performance evaluation index system for management practices was built based on the evaluation objectives and hierarchical priority order. Finally, based on the performance evaluation of ESG management practices, the K-nearest Neighbor algorithm was applied to analyze historical data of key indicators. According to the weights, various key indicators were re-integrated, achieving practical evaluation and decision support for enterprise ESG management. To verify the effectiveness of data mining and AHP, this article took Z enterprise as the research object and conducted empirical analysis on it. The results showed that in terms of evaluation accuracy, the method proposed in this article achieved the highest evaluation accuracy of 92.51%, 91.16%, and 91.75% in environmental, social, and governance dimension data use case evaluation, respectively. The conclusion indicated that data mining and AHP could improve the accuracy of ESG management practice evaluation in enterprises, provide reliable decision support for enterprise development, and help promote sustainable development of enterprises.

Exploring the Usage of Social Media Networking Platforms Among Medical Practitioners: Reasons, and Proposed Features for Improved Experience.

PURPOSE: This study aims to identify and prioritize the reasons for social media use among medical practitioners to facilitate the selection of the most appropriate social media platforms for healthcare providers. The findings of this study will help address the challenges posed by the wide variety of available social media platforms and assist healthcare providers in choosing platforms that best meet their professional needs. DESIGN/METHODOLOGY/APPROACH: This cross-sectional study was conducted in the period of two months, i.e., August and September 2021. This study is based on the AHP (Analytic Hierarchy Process) method of the MCDM (Multi-Criteria Decision-Making) approach. In the first phase, a four-hour brainstorming session was held to identify the medical Practitioner's reasons for social media usage; in the second phase, the identified reasons were linked with the top five social media platforms to determine the prioritized order of preference. FINDINGS: The top three reasons driving medical practitioners' usage of social media platforms include "Getting an update on current affairs," "Network with industry professionals," and "Healthy Lifestyle and Wellness Promotion." In contrast, the bottom three causes include "Advocacy for causes," "Get Updates about friends and family members," and "Opinions and ideas sharing." The prioritized order of social media platforms is LinkedIn, followed by Instagram, WhatsApp, Facebook, and Twitter. PRACTICAL IMPLICATIONS: This study helps solve the medical Practitioner's dilemma of selecting suitable social media platforms that serve their intended functions. In the future, it is expected that the usage of SM platforms will increase for causes such as Institution Branding and Healthcare Issues related Advocacy as well. ORIGINALITY/VALUE: Previous research has not adequately identified the reasons driving social media usage by physicians. This study is one of the few studies that has attempted to prioritize reasons for social media usage by physicians and has provided a prioritized list of social media platforms.

Bilateral Matching Method for Business Resources Based on Synergy Effects and Incomplete Data.

On the third-party cloud platform, to help enterprises accurately obtain high-quality and valuable business resources from the massive information resources, a bilateral matching method for business resources, based on synergy effects and incomplete data, is proposed. The method first utilizes a k-nearest neighbor imputation algorithm, based on comprehensive similarity, to fill in missing values. Then, it constructs a satisfaction evaluation index system for business resource suppliers and demanders, and the weights of the satisfaction evaluation indices are determined, based on the fuzzy analytic hierarchy process (FAHP) and the entropy weighting method (EWM). On this basis, a bilateral matching model is constructed with the objectives of maximizing the satisfaction of both the supplier and the demander, as well as achieving the synergy effect. Finally, the model is solved using the linear weighting method to obtain the most satisfactory business resources for both supply and demand. The effectiveness of the method is verified through a practical application and comparative experiments.

Urban flooding simulation and flood risk assessment based on the InfoWorks ICM model: A case study of the urban inland rivers in Zhengzhou, China.

Urban flooding intensifies with escalating urbanization. This study focuses on Xiong'er river as the study area and couples a 1D/2D urban flooding model using InfoWorks ICM (Integrated Catchment Modeling). Ten scenarios are set respectively with a rainfall return period of 5a 10a, 20a, 50a, and 100a, alongside rainfall durations of 1 and 24 h. Subsequently, the H-V (hazard-vulnerability) method was applied to evaluate urban flooding risk. Three indicators were selected for each of hazard factors and vulnerability factors. The relative weight values of each indicator factor were calculated using the AHP method. The result shows that (1) flood depth, rate, and duration escalate with longer rainfall return periods, yet decrease as the duration of rainfall increases; (2) as the rainfall return period lengthens, the proportion of node overflow rises, whereas it diminishes with longer rainfall durations, leading to an overall overloaded state in the pipeline network; and (3) the distribution in the research area is mainly low-risk areas, with very few extremely high-risk. Medium to high-risk areas are mainly distributed on both sides of the river, in densely built and low-lying urban areas. This study demonstrates that the model can accurately simulate urban flooding and provide insights for flood analyses in comparable regions.

Development of the Competency Evaluation Scale for Clinical Nutritionists in China: A Delphi Study.

Background: Clinical nutritionists are responsible for nutritional therapy in clinical practice, which significantly enhances patients' nutritional status. This study aims to develop and validate a competency evaluation scale to effectively assess the abilities of clinical nutritionists. Methods: The competency evaluation scale for clinical nutritionists was developed based on the iceberg model, utilizing literature review, semi-structured interviews, and the Delphi method. The weights of each indicator were calculated using the Analytic Hierarchy Process (AHP), and the validity and reliability of the scale were confirmed through questionnaire surveys. Results: The competency evaluation scale of clinical nutritionists comprised five primary indicators, twelve secondary indicators, and sixty-six tertiary indicators. The primary indicators, including professional theoretical knowledge, professional practical skills, humanistic practice ability, interpersonal communication ability, and professional development capability, have respective weights of 0.2168, 0.2120, 0.2042, 0.2022, and 0.1649. The Cronbach's α coefficients of the five dimensions of the scale were 0.970, 0.978, 0.969, 0.962, and 0.947, respectively. The results of the Exploratory Factor Analysis showed that the prerequisites for factor analysis were satisfied. Additionally, Bartlett's test of sphericity yielded a significance level of p < 0.001, confirming the scale's reliability and validity. Conclusions: The competency evaluation scale for clinical nutritionists developed in this study is of high scientific reliability and validity, which provides assessment criteria for the training and assessment of clinical nutritionists.

Optimization and Evaluation of Tourism Mascot Design Based on Analytic Hierarchy Process-Entropy Weight Method.

With the tourism industry continuing to boom, the importance of tourism mascots in promoting and publicizing tourism destinations is becoming increasingly prominent. Three core dimensions, market trend, appearance design, and audience feedback, are numerically investigated for deeply iterating tourism mascot design. Further, a subjective and objective evaluation weighting model based on the hierarchical analysis method (AHP) and entropy weighting method is proposed, aiming to utilize the advantages of these methods and ensure the entireness and correctness of results. Taking the mascots of six famous tourist attractions in Xi'an as an example, the feasibility and effectiveness of the evaluation model are verified. Data analysis and modeling results confirm that the three core evaluation indexes of scalability, innovation, and recommendation should be focused on in the design of tourism mascots in the three dimensions of market trends, appearance design, and audience feedback. The evaluation index scores are 0.1235, 0.1170, and 0.1123, respectively, which further illustrates the priority of mascot design. The evaluation model constructed by the research provides decision-makers with a comprehensive evaluation tool from the perspective of tourist experience, and also effectively assists the optimization process of mascot design. In addition, the model has good versatility and adaptability in structural design and evaluation logic and can be widely used in the optimization and evaluation research of brand mascots.

Optimization of the extraction process for Shenshou Taiyi powder based on Box-Behnken experimental design, standard relation, and FAHP-CRITIC methods.

BACKGROUND: Ancient classic prescription play a crucial role in the preservation and advancement of traditional Chinese medicine (TCM) theories. They represent a significant milestone in the ongoing development and transmission of TCM knowledge and practices and are considered one of the breakthroughs in the development of TCM inheritance. In the process of developing ancient classic prescriptions, many problems may still arise in ensuring quality consistency between traditional methods and modern production processes, among which the extraction process poses major challenges. This paper introduces a practical approach extracting an ancient classic prescription using a modern extraction process. The technique is demonstrated through the study of the extraction process of Shenshou Taiyi powder (STP). METHODS: This study focuses on optimising the STP extraction process to ensure consistency in the quality of the product obtained through ancient and modern processes using the standard relation and fuzzy analytic hierarchical process (FAHP) and criteria importance through intercriteria correlation (CRITIC) method integrated weights combined with the Box-Behnken response surface test. Using the contents of rosmarinic acid, isoimperatorin, puerarin, as well as the extract yield and fingerprint similarity as evaluation indexes of STP, the Box-Behnken response surface method was employed to examine the varying extraction parameters, including water addition ratio, extraction duration, and number of extractions. The weighted coefficients for each parameter were calculated by combining the benchmark correlation and FAHP-CRITIC method, deriving a comprehensive score. RESULTS: The optimal extraction process for STP consisted of a two extractions, each using at a tenfold quantity of water, performed for one hour. Process verification across three separate batches yielded a comprehensive score of 94.7, with a relative standard deviation of 0.76%. CONCLUSIONS: The application of the Box-Behnken response surface method combined with standard relation and FAHP-CRITIC approach proved to be stable and feasible for optimising the extraction process of STP.

Satellite-based rainwater harvesting sites assessment for Dera Ghazi Khan, Punjab, Pakistan.

Water scarcity in arid regions poses significant livelihood challenges and necessitates proactive measures such as rainwater harvesting (RWH) systems. This study focuses on identifying RWH sites in Dera Ghazi Khan (DG Khan) district, which recently experienced severe water shortages. Given the difficulty of large-scale ground surveys, satellite remote sensing data and Geographic Information System (GIS) techniques were utilized. The Analytic Hierarchy Process (AHP) approach was employed for site selection, considering various criteria, including land use/land cover, precipitation, geological features, slope, and drainage. Landsat 8 OLI imagery, GPM satellite precipitation data, soil maps, and SRTM DEM were key inputs. Integrating these data layers in GIS facilitated the production of an RWH potential map for the region. The study identified 9 RWH check dams, 12 farm ponds, and 17 percolation tanks as suitable for mitigating water scarcity, particularly for irrigation and livestock consumption during dry periods. The research region was classified into four RWH zones based on suitability, with 9% deemed Very Good, 33% Good, 53% Poor, and 5% Very Poor for RWH projects. The generated suitability map is a valuable tool for hydrologists, decision-makers, and stakeholders in identifying RWH potential in arid regions, thereby ensuring water reliability, efficiency, and socio-economic considerations.

Experimental Research on Crack Resistance of Steel-Polyvinyl Alcohol Hybrid Fiber-Reinforced Concrete.

This paper investigates the effects of steel fiber and PVA fiber hybrid blending on the compressive strength (fcc), splitting tensile strength (fts), compression energy (W1.0), and shrinkage properties of concrete. It also establishes a multi-factor crack resistance index evaluation model based on the Analytic Hierarchy Process (AHP) to comprehensively evaluate the crack resistance of concrete. The results show that the steel-PVA hybrid fiber (S-PVA HF) further enhances fcc, fts, the compression energy, and the shrinkage suppression properties of the concrete. The crack resistance of the steel-PVA hybrid fiber concrete (S-PVA HFRC) is the best when the proportion of steel fiber is 1.0% and that of the PVA fiber is 0.2%, and it increases up to 143% compared to the baseline concrete. The established concrete crack resistance evaluation model has a certain reliability.