In recent years, Climate-Smart Forestry (CSF) has emerged as an innovative approach to sustainable forest management, aiming to enhance forest resilience and to balance the provision of ecosystem services facing climate-related threats. This study introduces for the first time a new composite climate-smart index (ICSF) to assess CSF. The methodological approach comprises the following steps: (i) the selection and evaluation of CSF indicators; (ii) the weighting of these indicators; and (iii) the assessment of CSF for Mediterranean forests in two distinct periods, specifically 2005 and 2015. Eight indicators were selected from a systematic literature review. The Analytic Hierarchy Process was applied to translate the preferences obtained through an online questionnaire from a network of CSF-expert stakeholders into weights, at both indicators and criteria levels (i.e., adaptation, mitigation, and the social dimension). Results reveals that indicators \"tree species composition\", \"forest damage\", and \"regeneration\" are of crucial importance for CSF assessment. The comparison of the CSF value between the years 2005 and 2015, shows a slight increase in CSF ratings. The ICSF serves as a comprehensive index of CSF covering all aspects of that concept, i.e. adaptation, mitigation, and the social dimension (including production). The national-scale analysis provides an overview of the dynamics that involve forest management of Mediterranean forests against climate change. The study offers a practicable method for CSF evaluation with its allover set of indicators, representing a suitable tool for supporting forest managers to mitigate the negative impacts of climate change.

The escalating global challenges of population growth, climate crisis, and resource depletion have intensified water scarcity, emphasizing the critical role of wastewater treatment (WWT) in environmental preservation. While discharging untreated wastewater poses extinction risks to various species, effective WWT operations are indispensable for ecosystem continuity and sustainable water sources. Recognizing the complexity of WWT management, this study delves into the potential of artificial intelligence (AI) in strategic planning and decision-making within the WWT domain. Through a comprehensive SWOT analysis, this study evaluates the strengths, weaknesses, opportunities, and threats associated with AI integration in WWT processes. Utilizing the SWOT analysis framework, key criteria are identified, and their importance weights are assessed via the interval-valued neutrosophic analytical hierarchy process (IVN-AHP). According to analysis, the strengths in WWT are crucial, but potential opportunities and threats should not be ignored. The results of the study highlight several key findings regarding the integration of AI in WWT processes. While concerns about the reduction in human resources and potential unemployment, as well as the activation time and high energy consumption of AI systems, are identified as significant challenges, the study underscores the success of AI in data analytics as a strong aspect. Specifically, advanced data analysis techniques and the ability to proactively prevent problems emerge as important strengths of AI in WWT. WWT operators and practitioners are encouraged to prioritize the adoption of advanced data analysis techniques and proactive problem-solving strategies to maximize the effectiveness of AI integration in WWT processes.

Throughout the history of coal mining in all countries of the world, large areas of goaf have been left behind, and sudden collapses and surface subsidence of large areas of goaf may occur, especially for mining areas with long mining cycles. The northern new district of the Liaoyuan mining area has been subjected to nearly half a century of mining activities, accompanied by a gradual accumulation of disasters, which have occurred frequently in recent years. In order to assess the stability of the goaf in the study area, this paper proposes a hybrid decision-making multi-factor integrated evaluation method. The distribution of underground goafs was determined using geophysical exploration techniques (seismic survey and transient electromagnetic method) and geological drilling exploration. First, an evaluation index system was established based on the specifications of the goaf, the ecological and geological environment, and the mining conditions; the system included 14 indicators. Two weight calculation methods, AHP-EWM, were employed to determine the comprehensive weight of each indicator by combining subjective and objective weights on the basis of improved game theory. Subsequently, the fuzzy comprehensive evaluation method was utilised to complete the stability rating of each block in the study area, and MapGIS and ArcGIS were employed to complete the drawing of the stability zoning map of the northern new district goaf. The study area was divided into three zones of stability, basic stability and instability, according to the critical value. These zones accounted for 23.03%, 36.45% and 40.52% of the total area of the study area, respectively. The comprehensive on-site investigation revealed a decrease in the size and number of collapse pits and the rate of damage to the houses from the unstable zone to the stable zone. This indicates that the results of the division are consistent with the actual situation. The classification results are consistent with the actual ground disaster situation, thus verifying the rationality and validity of the evaluation method. The results indicate that the stability of the study area is generally at the lower middle level.

An ecological revetment is a new type that combines natural vegetation with civil engineering technology to establish functions, such as flood control, drainage, ecology, and landscape. Various types of ecological and other bank protection lead to different bank protection effects. Urban river ecological bank protection can effectively prevent bank collapse and promote mutual infiltration between river water and soil and is important for maintaining the balance of the river ecosystem and enhancing the ecological service function of river bank protection. To scientifically and accurately evaluate the ecological protection of riverbanks, this study screened 16 evaluation indicators based on four aspects: structural stability, ecological functionality, landscape suitability, and socio-economic status. A comprehensive evaluation index system for urban river ecological protection was constructed and an urban river ecological protection evaluation model based on the AHP - TOPSIS method was established. The model was used to evaluate the ecological protection of the rivers in the study area. The results revealed that the evaluation value, 0.830, of the self-embedded retaining wall exhibited the best performance among the current slope protection types. In addition, structural stability is a crucial factor in river ecological revetments, and the evaluation results were consistent with the revetment type selected in actual engineering. Therefore, the evaluation system constructed in this study is reasonable and reliable and has strong generalizability. This study provides theoretical guidance for selecting ecological protection banks for future river management projects and has specific references important for academic research and the development of environmental protection banks.

OBJECTIVE: Acute porphyria is a chronic recurrent disease with late diagnosis, heterogeneous clinical presentations and potentially devastating complications. The study aimed at providing real-world evidence on the natural course of acute porphyria, patient characteristics, disease burden, and healthcare utilization before diagnosis.
METHODS: This observational study used anonymized claims data covering 8 365 867 persons from German statutory health insurance, spanning 6 years (2015-2020). Patients with at least one diagnosis of acute porphyria during the index period (2019-2020) were classified into three groups by attack frequency. These findings were compared with two age- and sex-adjusted reference groups: the general population and fibromyalgia patients. Prevalence over the index period was calculated for all porphyria patients and those with active acute porphyria.
RESULTS: We revealed a prevalence of 79.8 per 1 000 000 for acute porphyria, with 12.9 per 1 000 000 being active cases. Acute porphyria patients, particularly with frequent attacks, demonstrated a higher comorbidity burden compared to the general population. Within the year before the recorded diagnosis, patients with acute porphyria required a median of 23.0 physician visits, significantly higher than the general population\'s 16.0. Additionally, 33.8% were hospitalized at least once during this period, a notably higher proportion than the general population (19.3%).
CONCLUSIONS: This study\'s findings, collected before the introduction of givosiran, as the first approved preventive therapy for acute porphyria in Europe, highlight the need for healthcare strategies and policies tailored to the complex needs of acute porphyria patients. The significant healthcare demands, heightened comorbidity burden, and increased healthcare system utilization emphasize the urgency of developing a comprehensive support infrastructure for these patients. Also, these acute porphyria real-world findings provide additional insights on disease characteristics in Germany.

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.

Ensuring food security and sustainable resource management has become a paramount global concern, prompting significant attention to land suitability analysis for enhancing agricultural production. In this study, an AHP-weighted overlay method was employed to delineate rice cultivation suitability in Guilan province, Iran, a central hub for rice production. Sixteen climatic, topographic, and soil variables were integrated, and individual maps were reclassified to align with the specific requisites for rice production. The results revealed three suitability classes: including \'very suitable,\' \'suitable,\' and \'moderately suitable\', covering 91%, 6%, and 3% of the land, respectively. Soil attributes, particularly organic matter, significantly influenced suitability (weight value of 0.745), with topographic and soil factors outweighing climate in assessment. While salinity is generally absent, organic matter deficiency affects 44% of the land. Phosphorus imbalances are prevalent, with potassium toxicity observed in 10%. Microelement deficiencies, especially in iron and zinc, are noted. Additionally, the results indicated that topographic and soil attributes played a more significant role than climate-related factors in assessing land suitability for rice cultivation within the study area. This research provides a comprehensive spatial analysis of all variables in the study region, shedding light on the complexities of land suitability for rice cultivation. These findings contribute to the understanding of agricultural sustainability and resource management strategies in the context of food security.

Groundwater is the main source of water for agriculture, industry, and families in arid areas. At present, there is an urgent need to protect groundwater due to human activities. In this study, the Qingshui River Basin was selected as the study area. Based on the DRASTIC model, the DRASTIC-Land use type (DRASTICL) model and the analytic hierarchy process-DRASTICL (AHP-DRASTICL) model were constructed by optimizing the indicators and weights. And the three models were applied to calculate the groundwater vulnerability index (GVI), and the groundwater vulnerability map (GVM) was drawn. The validation results of Spearman correlation coefficient show that the DRASTICL model and the AHP-DRASTICL model have higher correlation, which indicates that the optimized model is more accurate. Among them, the AHP-DRASTICL model has the highest correlation coefficient (ρ = 0.92), which is more in line with the actual situation. The results of this study can provide scientific guidance for the protection and utilization of groundwater in the Qingshui River Basin. And it is of guiding significance for the study of groundwater vulnerability, especially for groundwater management in arid and semi-arid areas.

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.

On a global scale, flooding is the most devastating natural hazard with an increasingly negative impact on humans. It is necessary to accurately detect flood-prone areas. This research introduces and evaluates the Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) integrated with GIS in the field of flood susceptibility in comparison with two conventional multi-criteria decision analysis (MCDA) methods: analytical hierarchy process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The Spercheios river basin in Greece, which is a highly susceptible area, was selected as a case study. The application of these approaches and the completion of the study requires the creation of a geospatial database consisting of eight flood conditioning factors (elevation, slope, NDVI, TWI, geology, LULC, distance to river network, rainfall) and a flood inventory of flood (564 sites) and non-flood locations for validation. The weighting of the factors is based on the AHP method. The output values were imported into GIS and interpolated to map the flood susceptibility zones. The models were evaluated by area under the curve (AUC) and the statistical metrics of accuracy, root mean squared error (RMSE), and frequency ratio (FR). The PROMETHEE model is proven to be the most efficient with AUC = 97.21%. Statistical metrics confirm the superiority of PROMETHEE with 87.54% accuracy and 0.12 RMSE. The output maps revealed that the regions most prone to flooding are arable land in lowland areas with low gradients and quaternary formations. Very high susceptible zone covers approximately 15.00-19.50% of the total area and have the greatest FR values. The susceptibility maps need to be considered in the preparation of a flood risk management plan and utilized as a tool to mitigate the adverse impacts of floods.