Search Results (110)

This systematic literature review examines the development of a conceptual certification framework for solar panel reuse, positioned within the broader context of the circular economy. It emphasizes sustainable production and consumption in response to the climate crisis and resource depletion. This review was conducted using Scopus and Google Scholar, following a structured search strategy. A final set of 63 sources, including peer-reviewed journal articles, conference papers, and gray literature recommended by domain experts, were selected to analyze existing certification frameworks across various sectors, focusing on their relevance to solar panel reuse. Key aspects of product reuse such as safety, quality, and technical standards are explored, highlighting the unique challenges associated with the long lifespans and environmental exposure of solar panels. Through this analysis, this study reveals the core elements vital for an effective certification framework. While structured certification frameworks are essential for sustainability, empirical evidence on their effectiveness in the solar panel reuse remains scarce, and regulatory inconsistencies add complexity. Using established practices in electronics, batteries, and other high-liability sectors as an anchor, the proposed framework, emerging from this systematic review, aims to extend solar panels’ lifecycle, contributing to environmental sustainability and socio-economic equity. The findings provide valuable insights for policymakers, industry stakeholders, and researchers by addressing key certification gaps and identifying future research directions in solar panel reuse standardization. Full article

Groundwater serves as a vital resource for sustainable water supply, particularly in semi-arid regions where surface water availability is limited. This study explores groundwater potential zones in the East Desert, Qift–Qena, Egypt, using a multidisciplinary approach that integrates remote sensing (RS), geographic information systems (GIS), geostatistics, and field validation with water wells to develop a comprehensive groundwater potential mapping framework. Sentinel-2 imagery, ALOS PALSAR DEM, and SMAP datasets were utilized to derive critical thematic layers, including land use/land cover, vegetation indices, soil moisture, drainage density, slope, and elevation. The results of the groundwater potentiality map of the study area from RS reveal four distinct zones: low, moderate, high, and very high. The analysis indicates a notable spatial variability in groundwater potential, with “high” (34.1%) and “low” (33.8%) potential zones dominating the landscape, while “very high” potential areas (4.8%) are relatively scarce. The limited extent of “very high” potential zones, predominantly concentrated along the Nile River valley, underscores the river’s critical role as the primary source of groundwater recharge. Moderate potential zones include places where infiltration is possible but limited, such as gently sloping terrain or regions with slightly broken rock structures, and they account for 27.3%. These layers were combined with geostatistical analysis of data from 310 groundwater wells, which provided information on static water level (SWL) and total dissolved solids (TDS). GIS was employed to assign weights to the thematic layers based on their influence on groundwater recharge and facilitated the spatial integration and visualization of the results. Geostatistical interpolation methods ensured the reliable mapping of subsurface parameters. The assessment utilizing pre-existing well data revealed a significant concordance between the delineated potential zones and the actual availability of groundwater resources. The findings of this study could significantly improve groundwater management in semi-arid/arid zones, offering a strategic response to water scarcity challenges. Full article

Disaster logistics presents a highly complex decision-making challenge under conditions of uncertainty, where the timely and efficient allocation of scarce resources is essential to minimize human suffering. In this context, we propose a novel Quantum-Inspired Hyperheuristic Framework (QHHF) designed to solve Dynamic Multi-Objective Combinatorial Optimization Problems (DMOCOPs) arising in disaster relief operations. The proposed framework integrates Quantum-Inspired Evolutionary Algorithms (QIEAs), which facilitate diverse and explorative solution generation, with a Reinforcement Learning (RL)-based hyperheuristic capable of dynamically selecting the most suitable low-level heuristic in response to evolving disaster conditions. A dynamic multi-objective mathematical model is formulated to simultaneously minimize total travel cost and risk exposure, while maximizing priority-weighted demand satisfaction. The model captures real-world complexity through time-dependent variables, stochastic demand variations, and fluctuating transportation risks. Extensive simulations using real-world disaster scenarios demonstrate the effectiveness of the proposed approach in generating high-quality solutions within stringent response time constraints. Comparative evaluations reveal that QHHF consistently outperforms traditional heuristics and metaheuristics in terms of adaptability, scalability, and solution quality across multiple objective trade-offs. Notably, our method achieves a 9.6% reduction in total travel cost, a 6.5% decrease in cumulative risk exposure, and a 4.7% increase in priority-weighted demand satisfaction when benchmarked against existing techniques. This work contributes both to the advancement of hyperheuristic theory and to the development of practical, AI-enabled decision-support tools for emergency logistics management. Full article

Global vegetation growth is dynamically influenced and regulated by hydrological processes. Understanding vegetation responses to terrestrial water storage (TWS) dynamics is crucial for predicting ecosystem resilience and guiding water resource management under climate change. This study investigated global vegetation responses to a terrestrial water storage anomaly (TWSA) using NDVI and TWSA datasets from January 2004 to December 2023. We proposed a Pearson-ACF time lag analysis method that combined dynamic windowing and enhanced accuracy to capture spatial correlations and temporal lag effects in vegetation responses to TWS changes. The results showed the following: (1) Positive NDVI-TWSA correlations were prominent in low-latitude tropical regions, whereas negative responses occurred mainly north of 30°N and in South American rainforest, covering 38.96% of the global vegetated land. (2) Response patterns varied by vegetation type: shrubland, grassland, and cropland exhibited short lags (1–4 months), while tree cover, herbaceous wetland, mangroves, and moss and lichen typically presented delayed responses (8–9 months). (3) Significant bidirectional Granger causality was identified in 16.39% of vegetated regions, mainly in eastern Asia, central North America, and central South America. These findings underscored the vital role of vegetation in the global water cycle, providing support for vegetation prediction, water resource planning, and adaptive water management in water-scarce regions. Full article

Lake surface water area (LSWA) and lake surface water temperature (LSWT) are critical indicators of climate change, responding rapidly to global warming. However, studies on the synergistic variations of LSWA and LSWT are scarce, and the coupling relationships among lakes with different environmental characteristics remain unclear. In this study, the relative growth rate of LSWA (RK_LSWA); the absolute growth rates of annual maximum, mean, and minimum LSWTs (i.e., K_{LSWT_max}, K_{LSWT_mean}, K_{LSWT_min}); and the absolute growth rates of the difference between maximum and minimum LSWT (LSWT_mmd) (K_{LSWT_mmd}) were investigated across more than 4000 lakes in China using long-term Landsat data, and their coupling relationships among different lake types (i.e., permafrost and non-permafrost recharge, endorheic or exorheic lakes, and natural and artificial lakes) were comprehensively analyzed. Results indicate significant differences in the trends of LSWA and LSWT, as well as their interrelationships across various regions and lake types. In the Qinghai–Tibet Plateau (QTP), 57.8% of lakes showed an increasing trend in LSWA, with 2.4% of the lakes showing moderate expansion (RK_LSWA values of 0.1–0.2), while over 27.5% of lakes in the South China (SC) region displayed shrinkage in LSWA (RK_LSWA values were between −0.1~0%/year). Regarding LSWTs, 49.8% of lakes in the QTP exhibited a K_{LSWT_max} greater than 0, and 47.9% of lakes showed a K_{LSWT_mean} greater than 0. In contrast, 48.1% of lakes in the Middle and Lower Yangtze River Plain (MLYP) had a K_{LSWT_max} less than 0, and 48.5% of lakes had a K_{LSWT_mean} less than 0. Additionally, lakes supplied by permanent permafrost demonstrated more significant growth in both LSWA and LSWT than those supplied by non-permanent permafrost. Further analysis revealed that approximately 20.2% of the lakes experienced a concurrent increase in both mean LSWT and LSWA, whereas around 18.9% of the lakes exhibited a simultaneous rise in both LSWT_mmd and LSWA. This suggests that the expansion of lakes in China is correlated with both rising temperatures and greater temperature differences. This study provides deeper insights into the response of Chinese lakes to climate change and offers important references for lake resource management and ecological conservation. Full article

Water planning and governance strategies must adapt to challenges associated with population growth, climate change, and projected water shortages. In the Western United States, agriculture is the dominant water use, and agricultural water users are being asked to conserve or share their water with other uses. Managing scarce water supplies at the local level often involves creative solutions, many of which are not well documented, especially in the agricultural sector. It is therefore critical to understand ideas to manage scarce water resources from the perspective of agricultural water users and those who work with them. In our research, we used interviews to explore how agricultural water users are managing increasing water scarcity in the Middle Rio Grande basin of central New Mexico and what enables or prevents them from taking innovative action to manage water scarcity. We hypothesized that we would find undocumented water use innovations born out of water users’ responses to lower and more variable water availability in recent years. We primarily recruited interviewees through snowball sampling, with a total of 42 (47%) agricultural water users, decision makers, and non-profit leaders influencing agricultural water governance in the basin accepting our invitation to participate. Our approximately one-hour, semi-structured and open-ended interviews explored agricultural water users’ lived experiences with water governance and opportunities to manage water scarcity. The interviews were recorded, transcribed, coded, and analyzed using HyperRESEARCH software (version 4.5.4). Our results did not support our hypothesis. Instead, we found that agricultural water users struggled to implement well-known innovations amid the pressures of water scarcity, supply uncertainty, administrative complexity, and constraints on their time, labor, and money. Water users and decision makers were mutually interested in implementing innovations in crop choice, flexibility in water storage, use, and management, stricter enforcement of water use efficiency, and access to more efficient irrigation equipment. However, high costs, a lack of knowledge, education, and training, and challenges related to water distribution and scheduling prevented agricultural water users from accessing these and other innovations. Recommendations include incentive-based policies to promote agricultural water use innovations that require high initial costs, improved water accounting at the basin and regional levels to promote flexible and reliable access to agricultural water, targeted education and outreach programming on alternative irrigation methods and cropping patterns, and improved access to irrigation scheduling information to support agricultural water users in planning for water scarcity. Full article

The comprehension of seasonal patterns of evapotranspiration (ET), as well as the interactive response to environmental factors, holds paramount importance for illuminating the intricate interaction within the carbon–water cycle of desert riparian forest ecosystems. Nonetheless, the driving mechanism behind ET changes is complex, and different components show significant differences in response to the same factor. Moreover, water resources are scarce in the region, and sustainable water resources management in arid regions usually aims to maximize transpiration (T) and minimize evaporation (E); therefore, reasonable calculation of ET components is urgent to effectively assess water resources consumption and improve water use efficiency. This discussion assessed the suitability and reliability of different methods for partitioning ET within the desert oasis in Northwestern China, calculated water use efficiency (WUE), and explored the differences in the response patterns of ET, transpiration (T), and WUE to environmental elements of constructive Populus euphratica forests in this region during the growing season. Continuous measurements of meteorological, soil, and vegetation factors were collected from 2014 to 2021 to facilitate this investigation. This study demonstrated that the underlying water use efficiency (uWUE) method effectively partitions ET into vegetation T and soil evaporation (E). Seasonal variations in ET and T were predominantly driven by temperature (Ta), radiation (Rn), soil moisture, and leaf area index (LAI). In addition, the exchange of water and carbon across different scales was governed by distinct regulatory mechanisms, where canopy-level WUE (WUEc) primarily depended on climatic conditions, while ecosystem-level WUE (WUEe) was more strongly influenced by vegetation structural characteristics. This study provided valuable insights into the ET characteristics, influencing factors, and water–carbon consumption mechanisms of desert vegetation in arid regions, and the conclusions of the discussion may provide theoretical insights for policymakers and ecosystem managers interested in preserving the ecological balance of arid regions. Full article

Background: Sleep quality is crucial for patient recovery and well-being, yet hospitalized patients often suffer from poor sleep due to environmental disruptions, clinical routines, and psychosocial stressors. While these challenges are well-documented, qualitative insights into nurses’ perspectives—essential frontline providers shaping the sleep environment—are scarce, especially within rapidly evolving healthcare systems like Saudi Arabia’s. This study explores nurses’ perceptions of factors influencing patient sleep quality in a private hospital in Al Ahsa, Saudi Arabia, and identifies strategies for improvement. Methods: We conducted a qualitative, cross-sectional study using semi-structured interviews with 14 registered nurses from diverse nationalities, specialties (Obstetrics/Gynecology, Medical-Surgical, Pediatrics, Intensive Care, Orthopedics, Bariatrics), and experience levels. Interviews were conducted in Arabic or English, audio-recorded, transcribed, and thematically analyzed using ATLAS.ti software. Roy’s Adaptation Model guided the examination of environmental, patient-specific, and systemic factors affecting sleep. Findings: Four primary themes emerged: (1). Environmental Factors: noise from alarms, equipment, family presence, and late-night activities, along with abrupt lighting changes, consistently disrupted sleep. (2). Patient-Specific Factors: pain, emotional distress, cultural expectations, and family involvement influenced sleep experiences. (3). Systemic and Contextual Factors: language barriers, infrastructural disparities between private and governmental hospitals, and limited resources can impeded effective sleep-promoting strategies. (4). Role of Health Technology: nurses recognized the potential of innovations like smart lighting and wearable monitors to enhance sleep quality but faced challenges in implementation due to knowledge gaps and limited familiarity. Roy’s Adaptation Model highlighted how effective adaptation through physiological and cognitive–emotional pathways, as observed by nurses, was facilitated or hindered by these factors. Conclusions: Enhancing in-hospital sleep quality requires a holistic, culturally sensitive approach that integrates environmental modifications, patient-centered care, and systemic improvements. Strategic investments in staff communication training, infrastructural upgrades, language support services, and the adoption of health technologies can promote adaptive responses and optimize patient rest. By leveraging theory-driven insights and context-specific strategies, healthcare systems—particularly those undergoing rapid development—can better support nurses in fostering restorative sleep environments as a fundamental component of patient-centered care, thereby enhancing patient recovery, satisfaction, and overall well-being. Full article

Green energy consumption is a pressing global environmental issue that necessitates the optimization of food system circularity to effectively utilize natural resources. The rise of food technology has introduced upcycled food as a promising solution for reducing food waste and promoting sustainability. Despite its potential, research on consumer attitudes toward upcycled food remains scarce. This study investigates the role of upcycled food in shaping Taiwanese consumers’ behaviors in response to environmental challenges, utilizing the value–attitude–behavior (VAB) model with a focus on variables such as “product novelty”, “green perceived value”, and “ethical consumption”. Using convenience sampling, 297 valid responses were collected, achieving a response rate of 91.1%. Findings indicate that health values significantly enhance positive attitudes toward upcycled food, which in turn positively influences behavioral intentions. However, neither green perceived value nor product novelty significantly affected these intentions. These insights highlight the importance of prioritizing health values, consumer attitudes, and ethical consumption in marketing strategies for upcycled food to engage potential consumers and promote environmental sustainability. This study addresses a critical gap in the existing literature and suggests a strategic direction for the food industry. Full article

Background: Nutrition and adequate dietary intake during pregnancy strongly influence the health and well-being of the mother, as well as the physical and cognitive development of the unborn child. While previous studies have documented factors associated with the dietary behaviour of pregnant women in Ethiopia, a comprehensive overview is missing. Objective: The aim of this study was to close this research gap. Methodology: We conducted a mapping review, including 37 studies published between 2000 and 2022 in our analysis. Dietary behaviour refers to all phenomena related to food choice, eating behaviour and dietary intake. We used an innovative approach by integrating a socio-ecological framework with UNICEF’s conceptual framework on maternal and child nutrition, which specifies multidimensional individual, underlying and enabling determinants associated with the nutritional status of women. Importantly, we integrated a focus on care for women and healthy environments. Results: A total of 68 factors were identified as influencing the dietary behaviour of pregnant women, with a focus on the intra- (31/68) and interpersonal (21/68) levels, while factors at the community (11/68) and the institutional levels (5/68) were scarce. Few studies investigated socio-cultural aspects, such as gender roles, decision-making power and workload of women, psychological factors and eating practices related to food taboos. None of the studies explored the influence of resources at the institutional level. Conclusions: This attests that the focus in maternal nutrition is still placed on the individual responsibility of women, instead of addressing the structural conditions that would enable women to access resources such as land, education and nutrition information. Full article

Food insecurity remains a pressing issue globally, exacerbated in regions like sub-Saharan Africa, where rural communities face significant challenges in accessing nutritious food. The Eastern Cape Province of South Africa is particularly vulnerable, with high levels of poverty and limited infrastructure contributing to food insecurity among its rural households. In response to these challenges, family food gardens have emerged as a promising strategy to enhance local food production, improve dietary diversity, and foster economic resilience within these communities. Despite the potential benefits of family food gardens, empirical evidence of their effectiveness in mitigating food insecurity at the household level in the Eastern Cape Province is scarce and remains limited. Understanding the factors that influence the success of these gardens, including socio-economic, environmental, and institutional determinants, is crucial for optimizing their impact and scalability. Hence, this study sought to comprehensively explore and investigate the role of family food gardens in improving food security within rural households in the Eastern Cape Province. It seeks to identify the determinants that contribute to the success of these gardens and their potential to alleviate food insecurity. The study made use of a descriptive research design, and the study utilized purposive sampling to gather data from 130 rural households via structured questionnaires. Data analyses incorporated in the study included the Household Dietary Diversity Score and logit regression model to explore the impacts and determinants of family food gardens on food security. The study findings underscore the significant positive contributions of family food gardens to rural communities. They serve as vital sources of fresh crops and vegetables, supplementing household nutrition and providing temporary employment. Constraints identified in the study include financial limitations, theft, water scarcity, inadequate fencing, and limited market access. The study insights highlight the fact that socio-economic and institutional factors such as age, gender, household income, and access to credit are critical influencers of family food garden success. These empirical results offer practical implications for policymakers, governmental agencies, and local communities seeking to promote sustainable agricultural practices and alleviate food insecurity. The research highlights how essential family food gardens are for improving food security among rural families in the Eastern Cape Province. The findings suggest that a joint effort is needed from the government, policymakers, NGOs, and local communities to overcome challenges and make the most of social and economic resources. By working together, these groups can enhance the role of family food gardens, making them a more effective solution for local food production and a stronger defence against food insecurity in the region. Full article

Explorations of the current attitudes and practices of dietitians regarding the gut microbiota in health are scarce. In this online survey, we assessed the attitudes and practices of dietitians across Europe concerning gut microbiome parameters and the manipulation of the gut microbiota. Pre-graduate dietetic students and other professionals were also invited to participate. The potential interest and preferences of the participants for future educational initiatives about the gut microbiota and the educational resources used were further explored. A total of 179 full responses were recorded (dietitians, n = 155), mainly from the southern and western regions. Most of the participants (>90.0%) believed that probiotics and prebiotics have a place in nutritional practice and that fermented foods with live microbial cultures should be a part of food-based dietary guidelines. A strong belief in the beneficial roles of probiotics and prebiotics in some health situations was also reported among the participants. Most of the dietitians recognised the importance of gut microbiota manipulation and advised the use of probiotics and prebiotics in dietary practice, and they felt quite confident applying the relevant information in their daily practice. Nevertheless, misconceptions were identified, and further guideline-oriented education is necessary. The interest in future e-learning initiatives was high among the participants, and the sources of knowledge, educative formats, and potential areas for further educational efforts were indicated. Full article

Hydrological modeling plays a vital role in water-resource management and climate-change studies in hyper-arid regions. In the present investigation, surface runoff was estimated by a Soil and Water Assessment Tool (SWAT) model for Wadi Al-Aqul, Saudi Arabia. The Sequential Uncertainty Fitting version 2 (SUFI-2) technique in SWAT-CUP was adopted for the sensitivity analysis, calibration, and validation of the SWAT model’s components. The observational runoff data were scarce and only available from 1979 to 1984; such data scarcity is a common problem in hyper-arid regions. The results show good agreement with the observed daily runoff, as indicated by a Pearson Correlation Coefficient (r) of 0.86, a regression (R²) of 0.76, and a Nash–Sutcliffe coefficient (NSE) of 0.61. Error metrics, including the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), were notably low at 0.05 and 0.58, respectively. In the daily validation, the model continued to perform well, with a correlation of 0.76 and regression of 0.58. As a new approach, fitted parameters of daily calibration were incorporated into the monthly simulation, and they demonstrated an even better performance. The correlation coefficient (regression) and Nash–Sutcliffe were found to be extremely high during the calibration period of the monthly simulation, reaching 0.97 (0.95) and 0.73, respectively; meanwhile, they reached 0.99 (0.98) and 0.63 in the validation period, respectively. The sensitivity analysis using the SUFI-2 algorithm highlighted that, in the streamflow estimation, the Curve Number (CN) was found to be the most responsive parameter, followed by Soil Bulk Density (SOL_BD). Notably, the monthly results showed a higher performance than the daily results, indicating the inherent capability of the model in regard to data aggregation and reducing the impact of random fluctuations. These findings highlight the applicability of the SWAT model in predicting runoff and its implication for climate-change studies in hyper-arid regions. Full article

The centuries-old history of dam construction, from the Saad el-Kafara Dam to global expansion in the 1950s, highlights the importance of these structures in water resource management. The Jucazinho Dam, built in 1998, emerged as a response to the scarcity of water in the Agreste region of Pernambuco, Brazil. After having less than 1% of its water storage capacity in 2016, the dam recovered in 2020 after interventions by the local water utility. In this context, the reliability of influent flow prediction models for dams becomes crucial for managers. This study proposed hydrological models based on artificial intelligence that aim to generate flow series, and we evaluated the adaptability of these models for the operation of the Jucazinho Dam. Data normalization between 0 and 1 was applied to avoid the predominance of variables with high values. The model was based on machine learning and employed support vector regression (SVM), random forest (RF) and artificial neural networks (ANNs), as provided by the Python Sklearn library. The selection of the monitoring stations took place via the Brazilian National Water and Sanitation Agency’s (ANA) HIDROWEB portal, and we used Spearman’s correlation to identify the relationship between precipitation and flow. The evaluation of the performance of the model involved graphical analyses and statistical criteria such as the Nash–Sutcliffe model efficiency coefficient (NSE), the percentage of bias (PBIAS), the coefficient of determination (R²) and the root mean standard deviation ratio (RSR). The results of the statistical coefficients for the test data indicated unsatisfactory performance for long-term predictions (8, 16 and 32 days ahead), revealing a downward trend in the quality of the fit with an increase in the forecast horizon. The SVM model stood out by obtaining the best indices of NSE, PBIAS, R² and RSR. The graphical results of the SVM models showed underestimation of the flow values with an increase in the forecast horizon due to the sensitivity of the SVM to complex patterns in the time series. On the other hand, the RF and ANN models showed hyperestimation of the flow values as the number of forecast days increased, which was mainly attributed to overfitting. In summary, this study highlights the relevance of artificial intelligence in flow prediction for the efficient management of dams, especially in water scarcity and data-scarce scenarios. A proper choice of models and the ensuring of reliable input data are crucial for obtaining accurate forecasts and can contribute to water security and the effective operation of dams such as Jucazinho. Full article

Sophora alopecuroides has important uses in medicine, wind breaking, and sand fixation. The CHY-zinc-finger and RING-finger (CHYR) proteins are crucial for plant growth, development, and environmental adaptation; however, genetic data regarding the CHYR family remain scarce. We aimed to investigate the CHYR gene family in S. alopecuroides and its response to abiotic stress, and identified 18 new SaCHYR genes from S. alopecuroides whole-genome data, categorized into 3 subclasses through a phylogenetic analysis. Gene structure, protein domains, and conserved motifs analyses revealed an exon–intron structure and conserved domain similarities. A chromosome localization analysis showed distribution across 12 chromosomes. A promoter analysis revealed abiotic stress-, light-, and hormone-responsive elements. An RNA-sequencing expression pattern analysis revealed positive responses of SaCHYR genes to salt, alkali, and drought stress. SaCHYR4 overexpression considerably enhanced alkali and drought tolerance in Arabidopsis thaliana. These findings shed light on SaCHYR’s function and the resistance mechanisms of S. alopecuroides, presenting new genetic resources for crop resistance breeding. Full article