Management of wildlife populations and the creation of conservation programs depend on the evaluation of wildlife habitats. Habitat suitability mapping is a technique typically used to map appropriate environmental factors and assess species existence in different areas. This study aims to map wildlife habitat suitability sites in Former Dhidhessa wildlife sanctuary, Ethiopia, using GIS-based Analytical Hierarchal Process and Weighted Linear Combination Methods. This study used both primary and secondary data sources. Datasets used to collect data include Digital Elevation Model (DEM), Landsat 9 (OLI/TIRS) and population data. Beside, large mammalian species occurrence data obtained from field survey was used. To map wildlife habitat suitability sites in Former Dhidhessa wildlife sanctuary, environmental factors such as proximity of road network, distance to surface water, land use land cover types, slope, population density and topography were used with the integration of species occurrence data recorded from the study area. These environmental factors scaled to common ranges, and assigned appropriate weights. The quantile classification method was utilized to classify suitability index into five zones (unsuitable, less suitable, moderately suitable, suitable, and highly suitable) to produce the map. Accordingly, the model revealed that 18.9 % of the study area is highly suitable, 19.5 % is suitable, 19.9 % is moderately suitable, 19.5 % is less suitable, and 22.2 % is unsuitable for wildlife. About 58.3 % of the study area is currently identified as suitable for wildlife whereas 41.7 % is unsuitable. This showed that the former Dhidhessa wildlife sanctuary is still having large suitable habitats that can support wide ranges of wildlife. Hence, based on the developed preliminary habitat suitability indices and maps, the federal and local governments shall reevaluate the status of former Dhidhessa wildlife sanctuary and develop future conservation and management plans to enhance the conservation of wildlife and their habitats in the area.

Background This study aimed to identify sustainability priorities within Oman\'s healthcare sector using the analytical hierarchy process (AHP) methodology. Mainly, it focused on assessing the relative importance of economic, environmental, and social factors and their sub-elements in sustaining Oman\'s healthcare system. Methodology A semi-quantitative, cross-sectional design was employed to collect data from 23 Omani healthcare experts with at least 10 years of experience in five different public hospitals in Oman. The AHP methodology was used to analyze pairwise comparisons of sustainability factors and derive their priorities. The consistency ratio was calculated to ensure the reliability of the analysis, and the transitivity rule was applied to address inconsistencies in pairwise comparisons. Results The findings revealed a strong emphasis on environmental and social sustainability, with economic considerations ranking comparatively lower. Circular practices emerged as a key priority within the environmental domain, while patient satisfaction stood out within the social domain. The analysis showed the integration between healthcare, environmental health, and societal well-being, emphasizing the need for holistic approaches to sustainability. Conclusions This study contributes to the understanding of healthcare sustainability by providing empirical evidence of stakeholder preferences within Oman\'s healthcare system. By quantitatively assessing the relative importance of economic, environmental, and social factors, it informs decision-making and resource allocation toward sustainable healthcare development. The findings also support the argument for integrated approaches to healthcare sustainability that balance economic efficiency with environmental protection and social inclusion.

To explore the characteristics and evaluate the risk of heavy metals in groundwater at a typical smelter-contaminated site, this study focuses on a representative a historical arsenic smelting plant in Southwest China, where the primary historical products were metallic arsenic (∼1000 tons/year) and arsenic trioxide (∼2000 ton/year). The results demonstrated As and Pb as the main pollutants in soil, and As and Cd as main pollutants in groundwater through soil profiling and quarterly groundwater analysis. The maximum As and Pb in the surface soil were 76800 and 2290 mg/kg, respectively, with As vertically infiltrating the deep gravel-sand layer (18-20 m). The groundwater pollution distribution progressively increased along flow direction, influenced by seasonal surface runoff and infiltration fluctuations. The groundwater pollutant concentrations during the dry season notably surpassed those during the wet season, with maximum As and Cd concentrations of 111.64 mg/L and 19.85 μg/L during the dry season, respectively. Furthermore, the analytic hierarchy process (AHP) was applied to evaluate the comprehensive risk of contaminated-site across pollution source load, regional groundwater intrinsic vulnerability, and evaluation of nearby sensitive receptors. The results revealed that the carcinogenic risk of lead in surface soil was moderate to high, while arsenic posed a high carcinogenic risk, contributing to an overall carcinogenic risk proportion of 89.6% in surface soil. Exposure through groundwater intake was identified as the primary pathway, with carcinogenic and noncarcinogenic risks exceeding those through skin contact. The final weights result demonstrated that the principal risk factors are the intrinsic arsenic load and protective target characteristics of regional groundwater at this site. This study provides a reference for comprehensive assessments of similarly contaminated industrial and smelting sites.

Hemerocallis L. possesses abundant germplasm resources and holds significant value in terms of ornamental, edible, and medicinal aspects. However, the quality characteristics vary significantly depending on different varieties. Selection of a high-quality variety with a characteristic aroma can increase the economic value of Hemerocallis flowers. The analytic hierarchy process (AHP) is an effective decision-making method for comparing and evaluating multiple characteristic dimensions. By applying AHP, the aromatic character of 60 varieties of Hemerocallis flowers were analyzed and evaluated in the present study. Headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) was employed to identify volatile components in Hemerocallis flowers. Thirteen volatile components were found to contribute to the aroma of Hemerocallis flowers, which helps in assessing their potential applications in essential oil, aromatherapy, and medical treatment. These components include 2-phenylethanol, geraniol, linalool, nonanal, decanal, (E)-β-ocimene, α-farnesene, indole, nerolidol, 3-furanmethanol, 3-carene, benzaldehyde and benzenemethanol. The varieties with better aromatic potential can be selected from a large amount of data using an AHP model. This study provides a comprehensive understanding of the characteristics of the aroma components in Hemerocallis flowers, offers guidance for breeding, and enhances the economic value of Hemerocallis flowers.

BACKGROUND: The world has witnessed increased adoption of large language models (LLMs) in the last year. Although the products developed using LLMs have the potential to solve accessibility and efficiency problems in health care, there is a lack of available guidelines for developing LLMs for health care, especially for medical education.
OBJECTIVE: The aim of this study was to identify and prioritize the enablers for developing successful LLMs for medical education. We further evaluated the relationships among these identified enablers.
METHODS: A narrative review of the extant literature was first performed to identify the key enablers for LLM development. We additionally gathered the opinions of LLM users to determine the relative importance of these enablers using an analytical hierarchy process (AHP), which is a multicriteria decision-making method. Further, total interpretive structural modeling (TISM) was used to analyze the perspectives of product developers and ascertain the relationships and hierarchy among these enablers. Finally, the cross-impact matrix-based multiplication applied to a classification (MICMAC) approach was used to determine the relative driving and dependence powers of these enablers. A nonprobabilistic purposive sampling approach was used for recruitment of focus groups.
RESULTS: The AHP demonstrated that the most important enabler for LLMs was credibility, with a priority weight of 0.37, followed by accountability (0.27642) and fairness (0.10572). In contrast, usability, with a priority weight of 0.04, showed negligible importance. The results of TISM concurred with the findings of the AHP. The only striking difference between expert perspectives and user preference evaluation was that the product developers indicated that cost has the least importance as a potential enabler. The MICMAC analysis suggested that cost has a strong influence on other enablers. The inputs of the focus group were found to be reliable, with a consistency ratio less than 0.1 (0.084).
CONCLUSIONS: This study is the first to identify, prioritize, and analyze the relationships of enablers of effective LLMs for medical education. Based on the results of this study, we developed a comprehendible prescriptive framework, named CUC-FATE (Cost, Usability, Credibility, Fairness, Accountability, Transparency, and Explainability), for evaluating the enablers of LLMs in medical education. The study findings are useful for health care professionals, health technology experts, medical technology regulators, and policy makers.

Grasslands are crucial ecosystems that provide numerous ecological services and support biodiversity conservation. Grasslands undergo significant threats from both anthropogenic and natural sources, compromising their ability to maintain biodiversity, ecosystem services, and human well-being. However, grasslands are frequently ignored in sustainable development objectives. Adequate knowledge of how grassland degradation affects ecosystem services is essential for sustainable management and grassland ecological restoration. The Kachchh region in western India harbours a unique grassland ecosystem known as the Banni grassland, which once became the finest grassland in Asia. However, undesirable anthropogenic interventions have accelerated its degradation. This research paper aims to assess the suitability of different land areas in Banni for sustainable grassland restoration, considering ecological value as a primary criterion. In the present research, land suitability for grassland management was assessed using a geographical information system (GIS)-based multi criteria evolution (MCE) method with satellite data and the analytic hierarchy process (AHP). The ground truthing of the soil samples was carried out alongside. Slope, rainfall, infiltration rate, LULC, geomorphology, soil texture, soil organic carbon, water holding capacity, SAR, CEC, pH, EC, and soil nutrients were among the criteria used. The weights for each criterion were calculated using a pairwise comparison matrix, and the scores were allocated to sub criteria based on field work, expert opinions, and a literature review. The proposed method can be very useful for evaluating the state of the land and can help with the best possible planning for grassland development and conservation. Banni grassland has the potential to be developed into a critical zone observatory (CZO) in the future, and the present study, with further inputs, holds promise for furthering the cause of its sustainable management. Overall, this study underscores the importance of assessing land suitability for sustainable grassland management and highlights the potential for maximising the ecological value of grasslands in western India and beyond.

One of the most common respiratory chronic diseases is asthma, with 5-16 % of world prevalence. In chronic disease, prevention, diagnosis, management, and palliation are the strategies for a care model; the patient-self management is fundamental with the so-called therapeutic education (TE) to train the patient in the necessary skills. The challenge of TE grows when the patient is a child or a person with special needs, even more in public health care in low- and middle-income countries. This is a problematic human situation, that needs soft system thinking. In this research, the analytic hierarchy process was used to determine the perceived importance of the factors that affect children\'s asthma health care in a public health institution in Mexico. The soft systems methodology (SSM) was applied to learn about the disease self-management, in order to obtain activities models and an action plan. According to AHP, human resources and education were percived as the most important among the factors that affect children health care within the institution. The perceived importance of two main subfactors (human resources training and TE) was around 34 %, which emphasizes the need to generate strategies for the improvement of the education of patients and health care providers. In MSS, the rich vision, the CATWOE, the root definition, and an activities model were proposed, including the application of an instructional design methodology (ADDIE) for the development of learning objects of asthma for children. Desirable and feasible actions and recommendations include the update of the national clinical practice guides, the use of control measures such as the Asthma Control Test, and a daily asthma diary to register the daily status of the breathing capacity, the drug administration, and the potential trigger events. The proposed model can be used as part of a systemic patient-and-family centered approach for chronic care model (CCM), particularly in diseases unsuitable for prevention interventions.

The rapidly expanding Internet of Medical Things (IoMT) landscape fosters enormous opportunities for personalized healthcare, yet it also exposes patients and healthcare systems to diverse security threats. Heterogeneous IoMT devices present challenges that need comprehensive risk assessment due to their varying functionality, protocols, and vulnerabilities. Hence, to achieve the goal of having risk-free IoMT devices, the authors used a hybrid approach using fuzzy logic and the Fuzzy Analytical Hierarchy Process (FAHP) to evaluate risks, providing effective and useful results for developers and researchers. The presented approach specifies qualitative descriptors such as the frequency of occurrence, consequence severity, weight factor, and risk level. A case study with risk events in three different IoMT devices was carried out to illustrate the proposed method. We performed a Bluetooth Low Energy (BLE) attack on an oximeter, smartwatch, and smart peak flow meter to discover their vulnerabilities. Using the FAHP method, we calculated fuzzy weights and risk levels, which helped us to prioritize criteria and alternatives in decision-making. Smartwatches were found to have a risk level of 8.57 for injection attacks, which is of extreme importance and needs immediate attention. Conversely, jamming attacks registered the lowest risk level of 1, with 9 being the maximum risk level and 1 the minimum. Based on this risk assessment, appropriate security measures can be implemented to address the severity of potential threats. The findings will assist healthcare industry decision-makers in evaluating the relative importance of risk factors, aiding informed decisions through weight comparison.

Mechanical recycling is an indispensable tool for plastic waste (PW) recycling and has the highest share in the PW recycling sector in India. The transition to the circular economy of plastics (CEoP) needs a systemic perspective on the mechanical recycling processes. Nevertheless, the assessment of multiple parameters influencing the mechanical recycling of PW is a complex decision-making problem for the development of triple-bottom-line mechanical recycling. A systemic perspective of various mechanical recycling scenarios was performed by employing a multi-criteria decision-making approach to examine the complexity of interlinked factors in the present investigation. Analytical hierarchy process (AHP) integrated with grey relational analysis (GRA) was used to evaluate the criteria that directly influence quality-oriented mechanical recycling. Data were collected by conducting semi-structured interviews using a framed questionnaire in stakeholder engagement with mechanical recyclers of PW. The first level hierarchy included economy, technical, resource consumption and environmental criteria. These criteria were further categorized into various significant indices such as quality of recyclate, recyclability, water and energy consumption during recycling. The results of the integrated grey relational analysis indicated that the technical parameters including quality of recyclate, resource efficiency, PW processing rate and recyclability have a significant influence on mechanical recycling. Based on AHP-GRA, scenario MR6, i.e. manufacturing of PET strap from recycled PET flakes, was ranked the optimal mechanical process amongst the various scenarios. MR6 was followed by Straps and Films at the second and third rank. The lowest ranking was observed for polymer blend recycling. These processes with higher ranks produced good quality recyclate with better efficiency and recyclability. Moreover, these processes consumed optimal resources during manufacturing. These processes also exhibited less maintenance cost, high production rate, low chemical consumption and waste generation as well as implemented pollution control practices.

Among all other valuable natural resources, groundwater is crucial for global economic growth and food security. This study aimed to delineate groundwater potential zones (GWPZ) in the Gidabo watershed of the Main Ethiopian Rift. The demand for groundwater supplies for various applications has risen recently in the watershed due to rapid population upsurge. An integrated Geographical Information System, Remote Sensing, and Analytical Hierarchy Process (AHP) has been utilized. Eight groundwater regulating factors, including rainfall, elevation, drainage density, soil types, lineament density, slope, lithology, and land use/land cover, have been taken in the analysis. To assign suitable weights to each factor, AHP was employed, as each element contributes differently to groundwater occurrence. The weighted overlay analysis (WOA) technique was then used in the ArcGIS environment to integrate all thematic layers and generate a GWPZ map. The delineated GWPZ in the watershed was classified into five categories. The poor GWPZ covered 18.7 %, the low GWPZ covered 33.8 %, the moderate GWPZ covered 23.4 %, the high GWPZ covered 18.1 %, and the very high GWPZ covered 5.8 % of the area. Well and spring data were used to validate the model, and the ROC (Receiver Operating Characteristic) curve method was applied. The results showed good accuracy of 76.8 %. The result of this research can be valuable for planning and managing groundwater resources in the Gidabo watershed.