Sustainability in the Public Healthcare Sector: Insights From an Analytical Hierarchy Process Analysis.

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.

Interaction of drought-influencing factors for drought mitigation strategies in Lam Ta Kong Watershed, Khorat Plateau.

Generally, drought is influenced by both spatial characteristics and anthropogenic activities within an area. Drought vulnerability assessment is a critical tool that can be effectively used to develop proper drought mitigation strategies to prevent avoidable losses. To develop suitable drought mitigation strategies, the overall drought vulnerability must be assessed, and the interaction among drought-influencing factors in the area should be considered. Consequently, this study aimed to investigate the interactions among critical drought-influencing factors and drought vulnerability in the Lam Ta Kong Watershed via spatial analysis with the analytical hierarchy process (AHP) and geographical information system (GIS) technology. Ten drought-influencing factors were considered in the vulnerability assessment: slope, elevation, soil texture, soil fertility, stream density, precipitation, temperature, precipitation days, evaporation, and land use. The results indicated that the critical drought-influencing factors were precipitation, precipitation days, and land use, resulting in most of the watershed experiencing high drought vulnerability (35.1% of the watershed or 1810.83 km2). Moreover, this research highlighted the interactions among the critical drought-influencing factors. Precipitation interacted with precipitation days to cause drought vulnerability across the watershed, with a p-value <0.05. Similarly, the interactions between precipitation and land use and between precipitation days and land use, with p-values <0.05, showed that they were associated with and influenced by drought in the Lam Ta Kong Watershed. This study further indicated that appropriate drought mitigation strategies for this watershed must consider the interactions among these drought-influencing factors, as well as their specific interactions across the watershed.

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.

Geospatial insights into Alphonso mango cultivation: a comprehensive land suitability study in the coastal belt of Maharashtra, India.

Land suitability assessment is integral to the advancement of precision agriculture. This inquiry is focused on identifying optimal regions for cultivating Alphonso mango in the coastal belt of Maharashtra, spanning across Palghar, Raigad, Thane, Ratnagiri, and Sindhudurg districts. Employing a GIS-based Analytic Hierarchy Process (AHP) methodology, 10 crucial parameters have been considered, encompassing climatic, physical, and chemical soil characteristics: cation exchange capacity, organic carbon, slope, rainfall, soil pH, soil texture, mean annual soil temperature, base saturation, soil drainage, and soil depth. Weights are assigned to these parameters based on expert opinions and existing literature to determine their significance in developing a soil suitability map. The study reveals distinct land suitability zones for Alphonso mango cultivation. The land suitability map designates 25.78% of the study area as highly suitable, while 9.18% is considered unsuitable for Alphonso mango cultivation. To validate the study, the Receiver Operating Characteristic (ROC) curve has been employed, indicating an 83% approval rate for the reliability and performance of the soil suitability. The results categorise soil suitability classes, providing valuable insights for farmers and agricultural planners to make informed decisions regarding Alphonso mango cultivation in similar geoenvironmental regions.

Selection of an alternate cementitious mortar using ceramic tile dust waste: a hybrid MCDM approach.

Selection of a suitable alternative material from a pool of alternatives with many conflicting criteria becomes a Multi-Criteria Decision Making (MCDM) problem. In the present study, ternary blended mortars were prepared using ceramic tile dust waste (CTD), fly ash (FA), and ground granulated blast furnace slag (GGBFS) as binder components. Crusher dust (CD) was used as a fine aggregate component. Binder to aggregate ratios of 1:3 and 1:1 were prepared considering suitable flow. A total of 16 mortar mixes were cast. These mortars were tested for various conflicting criteria compressive strength, flexural strength, porosity, water absorption, bulk density, thermal conductivity, specific heat, thermal diffusivity, and thermal effusivity whose weightages obtained were 29.09%, 20.08%, 12.77%, 10.60%, 8.74%, 6.74%, 5.54%, 4.47%, and 1.97%, respectively, as per AHP analysis. Later, considering these different criteria and alternate mortars, it was observed that a 1:1 mortar with 20% CTD, 30% FA, and 50% GGBFS (RC20F30G50) is found to be the suitable mortar with the highest relative closeness coefficient of 0.861 and the highest net outranking flow of 0.316 with respect to MCDM techniques: technique for order of preference by similarity to ideal solution (TOPSIS) and preference ranking organization method for enrichment of evaluations (PROMETHEE-II), respectively. The ranking of the mortar in both methods complies with the relative weightages of the criteria and the performance of the mortars with respect to the above criteria.

Elevated homocysteine is negatively correlated with plasma cystathionine ß-synthase activity in givosiran-treated patients.

Givosiran is a subcutaneously administered, liver-targeted RNA interference (RNAi) therapeutic that has been approved for treating acute hepatic porphyria (AHP). Elevation in plasma homocysteine (hyperhomocysteinemia) has been reported in AHP patients, and treatment with givosiran has been reported to further increase homocysteine levels in some patients. The mechanism of homocysteine elevation during givosiran treatment is unknown, but has been hypothesized to be mediated by a reduction in activity of cystathionine ß-synthase (CBS), which uses homocysteine as a substrate. A liquid chromatography-tandem mass spectrometry-based assay was adapted to measure circulating CBS activity. Using plasma collected from the Phase III ENVISION study, CBS activity was measured to directly evaluate whether it is associated with elevated homocysteine levels in givosiran-treated patients. CBS activity was reduced following givosiran treatment and both homocysteine and methionine levels were inversely correlated with CBS activity. Following administration of a supplement containing vitamin B6, a cofactor for CBS, in four patients during the trial, plasma CBS activity was found to increase, mirroring a corresponding decrease in homocysteine levels. These results support the hypothesis that elevated homocysteine levels following givosiran treatment result from a reduction of CBS activity and that vitamin B6 supplementation lowers homocysteine levels by increasing CBS activity.

Multi-criteria GIS-based land suitability analysis for rice cultivation: a case study in Guilan Province, Iran.

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.

Comparative evaluation of different pre-treatment alternatives for granular media filters treating greywater and their ranking using analytical hierarchy process.

In this study, the performance of four different pre-treatment alternatives for granular media filtration, namely, settling, aeration, coarse media filtration and chemical coagulation were compared experimentally. Further, analytical hierarchy process (AHP) was used to compare their performance based on economic, environmental, technical and performance criteria. Performance of settling and aeration were evaluated up to 24 h duration. The coarse media filter was intermittently operated with 10 L of greywater in downflow mode while alum was used for chemical coagulation. Experimental results showed that settling up to 6 h did not show significant removal of different pollutants whereas 24 h settling resulted in moderate removal of turbidity and organic content but was not efficient in the removal of nutrients and faecal coliforms. Chemical coagulation reduced 93, 66, 48 and 97% of turbidity, COD, NH4-N and faecal coliforms, respectively from greywater but resulted in excessive sludge generation and is difficult to adopt on-site and requires skilled supervision. Coarse filtration of greywater resulted in 61, 41, 36 and 35% removal of turbidity, COD, PO4-P and faecal coliforms, respectively. Considering different criteria AHP gave coarse filtration as the best pre-treatment option to the granular media filters treating greywater.

Novel approach evaluating powdered raw and hydrothermally treated syenite as stonemeal for tropical environments: Potential effects on groundwater quality and agricultural suitability.

Soluble fertilizers, particularly potash, are often prohibitively expensive or unavailable in Africa. Consequently, alternatives such as powdered silicate rocks, both raw and hydrothermally treated, are being explored as potential solutions, especially for acidic tropical soils. This study investigates the possible impacts of these rocks (syenite) on groundwater quality, which is a critical factor for agricultural activities. The powdered raw material underwent chemical and mineralogical characterization, including X-ray fluorescence and X-ray diffraction, followed by quantitative evaluation of materials by scanning electron microscopy. Both raw and 46 hydrothermally treated materials were subjected to sequential leaching cycles (1, 24, and 192 h) using deionized water, and the resulting leachates were analyzed by inductively coupled plasma atomic emission spectroscopy. Parameters such as electrical conductivity, total dissolved solids, soluble sodium percentage, sodium adsorption ratio, magnesium hazard, Kelly's ratio, and permeability index were also evaluated. Results from the 47 leachates indicated that 64 % of the samples exhibited excellent to acceptable water quality for irrigation purposes across all parameters. Conversely, 6 % to 13 % fell into the doubtful category, and 2 % to 24 % were classified as unsuitable. Consistency index and ratios of approximately 0.07 and 0.042, respectively, were determined using multi-criteria decision analysis (analytic hierarchy process: AHP), confirming the coherence of the decision and pairwise comparison matrix. The weighted coefficients for each criterion ranged from 0.06 to 0.2. Consequently, the optimal sample (Treatment 23) was identified, showing a hydrothermal temperature of 176 °C, a time of 3.9 h, a normality of 4.62, and a liquid-solid ratio of 0.24. This treatment met all high-water quality standards, including low salinity and sodium hazard, as corroborated by the US salinity laboratory and Wilcox diagrams. Furthermore, due to their nutrient release, low concentration of toxic elements, and effective buffering capacity (pH âˆ¼ 10.6), these powdered syenites are suitable for application in acidic soils.

An efficient molten steel slag gas quenching process: Integrating carbon solidification and waste heat recovery.

The iron and steel-making industries have garnered significant attention in research related to low-carbon transitions and the reuse of steel slag. This industry is known for its high carbon emissions and the substantial amount of steel slag it generates. To address these challenges, a waste heat recovery process route has been developed for molten steel slag, which integrates CO2 capture and fixation as well as efficient utilization of steel slag. This process involves the use of lime kiln flue gas from the steel plant as the gas quenching agent, thereby mitigating carbon emissions and facilitating carbonation conversion of steel slag while simultaneously recovering waste heat. The established carbonation model of steel slag reveals that the insufficient diffusion of CO2 gas molecules within the product layer is the underlying mechanism hindering the carbonation performance of steel slag. This finding forms the basis for enhancing the carbonation performance of steel slag. The results of Aspen Plus simulation indicate that 1 t of steel slag (with a carbonation conversion rate of 15.169 %) can fix 55.19 kg of CO2, process 6.08 kmol of flue gas (with a carbon capture rate of 92.733 %), and recover 2.04 GJ of heat, 0.43 GJ of exergy, and 0.68 MWh of operating cost. These findings contribute to the development of sustainable and efficient solutions for steel slag management, with potential applications in the steel production industry and other relevant fields.

Cost, Usability, Credibility, Fairness, Accountability, Transparency, and Explainability Framework for Safe and Effective Large Language Models in Medical Education: Narrative Review and Qualitative Study.

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.

Integrated assessment of groundwater vulnerability in arid areas combining classical vulnerability index and AHP model.

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.

Mapping flood susceptibility with PROMETHEE multi-criteria analysis method.

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.

Evaluating lecturer performance in Vietnam: An application of fuzzy AHP and fuzzy TOPSIS methods.

Higher education is regarded as being of paramount importance in Vietnam and as being essential to raising the level of the country's labor force and promoting economic progress. Evaluation of lecturers is one of the institution's activities and a crucial component of managing human resources in higher education institutions. How to evaluate faculty members' overall performance using a range of criteria is one of the key evaluation-related challenges. This study presents a method that uses fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to assess and rank the performance of lecturers. Specifically, the evaluation framework is developed by identifying criteria and sub-criteria based on a comprehensive review of existing literature. Following that, the fuzzy AHP approach is used to determine the weights of the criteria and sub-criteria using the pairwise comparisons. The Fuzzy TOPSIS approach is employed to assess and prioritize lecturers identified through expert evaluation. When applied in group decision-making, utilizing fuzzy AHP and fuzzy TOPSIS promotes agreement among decision-makers and diminishes uncertainty in decision-making processes. The utilization of the multiple criterion measurement approach can then be used to carry out the evaluation. The suggested framework is also demonstrated via a case study. The use of this framework can improve the evaluation's objectivity, accuracy, and scientific methodology. It is believed that this work will assist managers of higher education institutions improve their standards for educational quality.

Assessment of vulnerability to flood risk in the Padma River Basin using hydro-morphometric modeling and flood susceptibility mapping.

An evaluation of flood vulnerability is needed to identify flood risk locations and determine mitigation methods. This research introduces an integrated method combining hydro-morphometric modeling and flood susceptibility mapping to assess Padma River Basin's flood risk. Flood zoning, flooding classes, and resource flood risk were explicitly analyzed in this river basin study. Flood risk was calculated using GIS-based hydro-morphometric modeling. Using Horton's and Strahler's methods, drainage density, stream density, and stream order of the Padma River Basin were determined. The Padma River Basin has five sub-basins: A, B, C, D, and E, with stream densities of 0.53 km-2, 0.13 km-2, 0.25 km-2, 0.30 km-2, and 0.28 km-2 and drainage densities of 0.63 km-1, 0.16 km-1, 0.29 km-1, 0.35 km-1, and 0.33 km-1, respectively. Sub-basin A is the most prone to floods due to its high stream and drainage density, whereas B and C are the least susceptible. This study used elevation, TWI, slope, precipitation, NDVI, distance from road, drainage density, distance from river, LU/LC, and soil type to create a flood vulnerability map incorporating GIS and AHP with pair-wise comparison matrix (PCM). The study's flood zoning shows that the northeastern part of this basin is more likely to flood than the southwestern part due to its elevation and high-order streams. Moderate River Flooding, the region's most hazardous flood class, covers 48.19% of the flooding area, including 1078.30 km2 of agricultural land, 94.86 km2 of bare soil, 486.39 km2 of settlements, 586.42 km2 of vegetation cover, and 39.34 km2 of water bodies. The developed hydro-morphometric model, the flood susceptibility map, and the analysis of this data may be utilized to offer long-term advance alarm insight into areas potentially to be invaded by a flood catastrophe, boosting hazard mitigation and planning.

Decision support system for community managed rainwater harvesting: A case study in the salinity-prone coastal region of Bangladesh.

Climate change-induced saline intrusion into both surface and groundwater, extreme weather events, and unregulated water usage are serious threats to the drinking water supply in coastal areas worldwide, especially in least-developed countries. This research developed a data-driven decision-making methodology to evaluate the performance of rainwater harvesting (RWH) systems in the saline-prone southwestern coastal region of Bangladesh. Twenty-five community managed RWH systems, recently piloted in two major coastal districts, were considered the case study to develop and validate this evaluation tool. The evaluation methodology integrates daily water models, lifetime cost analysis, Geographic Information System (GIS)-based parameters supported by the Analytical Hierarchy Process (AHP), and field observation. While the meteorological parameters as well as the hydrological and economic performance were found to be highly suitable, 36 % of the systems showed moderate performance, as challenges remain in ensuring proper operation and maintenance practices at the community level. However, 40 % of the systems showed high performance, with two systems showing very high suitability, which suggests community managed RWH systems as a sustainable adaptation for coastal water supply.

Selection and Optimization of Carbon-Reinforced Polyether Ether Ketone Process Parameters in 3D Printing-A Rotating Component Application.

The selection of process parameters is crucial in 3D printing for product manufacturing. These parameters govern the operation of production machinery and influence the mechanical properties, production time, and other aspects of the final product. The optimal process parameter settings vary depending on the product and printing application. This study identifies the most suitable cluster of process parameters for producing rotating components, specifically impellers, using carbon-reinforced Polyether Ether Ketone (CF-PEEK) thermoplastic filament. A mathematical programming technique using a rating method was employed to select the appropriate process parameters. The research concludes that an infill density of 70%, a layer height of 0.15 mm, a printing speed of 60 mm/s, a platform temperature of 195 °C, an extruder temperature of 445 °C, and an extruder travel speed of 95 mm/s are optimal process parameters for manufacturing rotating components using carbon-reinforced PEEK material.

Assessing the impact of green finance on sustainable tourism development in China.

The escalating urgency to address environmental degradation and promote sustainable development globally has emphasized the critical role of Green Finance (GF) in fostering responsible practices across industries. The tourism sector has drawn significant attention due to its substantial environmental impact, necessitating the implementation of robust financial mechanisms to mitigate its ecological footprint. China, recognized as a key player in the global tourism arena, the convergence of rapid economic expansion and the imperative for environmental conservation presents a distinctive set of challenges and opportunities. The study employed the Fuzzy Analytic Hierarchy Process (AHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodologies to systematically evaluate the impact of GF. The findings of fuzzy AHP indicate the critical role of environmental sustainability measures (GF2) as the topmost impacting factor. This refers to the practice of utilizing financial mechanisms and instruments to support initiatives that promote environmental conservation, minimize ecological footprints, and foster sustainable development. While financial allocation and effectiveness (GF1) and policy and regulatory framework impact (GF4) also hold significant importance in shaping sustainable tourism development. Moreover, the results of fuzzy TOPSIS identified top strategies such as green bond innovation for ecosystem regeneration (S1) and circular economy integration (S4), which can play a significant role in promoting sustainable tourism practices by facilitating initiatives aimed at ecosystem regeneration and integrating circular economy principles into the tourism industry.

Selection of optimal strategy for managing decentralized solar PV systems considering uncertain weather conditions.

Solar power is a promising source of energy that is environmentally friendly, sustainable, and renewable. Solar photovoltaic (PV) panels are the most common and mature technology used to harness solar energy. Unfortunately, these panels are prone to dust accumulation, which can have a significant impact on their efficiency. To maintain their effectiveness, solar photovoltaics s must be cleaned regularly. Eight main techniques are used to clean solar panels: natural, manual, mechanical, robotic, drone, coating, electrical, and acoustic. This study aims to identify the best cleaning method using multiple criteria decision-making (MCDM) techniques. Using the Analytical Hierarchy Process (AHP), Quality Function Deployment (QFD), Fuzzy Technique for Order of Preference by Similarities to Ideal Solution (FTOPSIS), and Preference Selection Index (PSI), this research evaluates all eight cleaning methods based on several criteria that are categorized under cost, performance, resource requirement, and safety in Abu Dhabi. The data are collected from surveys completed by experts in solar and sustainable energy. The AHP, QFD, and PSI results identified natural, manual, and surface coating as the best and most effective cleaning methods. Natural cleaning involves using rainwater primarily to remove dirt and dust; manual cleaning requires cleaning agents and wiping clothes; and surface coatings involve applying a layer of hydrophobic material to the panels to repel dust. Identifying the most effective cleaning method for dust removal from solar panels can ensure optimal efficiency recovery at minimal costs and resources.

Research on safety condition assessment methodology for single tower steel box girder suspension bridges over the sea based on improved AHP-fuzzy comprehensive evaluation.

In order to propose a reliable method for assessing the safety condition for single-tower steel box girder Suspension bridges over the sea, a condition monitoring system is established by installing sensors on the bridge structure. The system is capable of gathering monitoring data that influence the safety status of the bridge. These include cable tension, load on the main tower and pylon, bearing displacement, wind direction, wind speed, and ambient temperature and humidity. Furthermore, an improved Analytic Hierarchy Process (AHP) algorithm is developed by integrating a hybrid triangular fuzzy number logic structure. This improvement, coupled with comprehensive fuzzy evaluation methods, improves the consistency, weight determination, and security evaluation capabilities of the AHP algorithm. Finally, taking the No.2 Channel Bridge as an example and based on the data collected by the health monitoring system, the application of the safety assessment method proposed in this paper provides favorable results in evaluating the overall safety status of the bridge in practical engineering applications. This provides a basis for management decisions by bridge maintenance departments. This project confirms that the research results can provide a reliable method for assessing the security status of relevant areas.