Search Results (1,907)

Small Island Developing States (SIDS) face ongoing challenges in balancing agricultural sustainability with economic growth due to limited land resources, rapid urbanisation, climate change, and reliance on food imports. This study explores the evolution of land use and the future of agriculture in Mauritius from 2002 to 2022, using satellite imagery, policy reviews, and stakeholder interviews. Findings show a 9% decrease in agricultural and non-agricultural vegetation cover, alongside a doubling of built-up areas from 10% to 20%, indicating continued land conversion pressures. The analysis highlights major barriers to agricultural sustainability, including declining food self-sufficiency, an ageing farming population, and slow movements towards sustainable practices caused by low profitability and weak institutional support. Diverging priorities among government agencies, sugar companies, smallholder farmers, and NGOs further hinder coordinated policy efforts. To address these challenges, the study identifies strategies for aligning economic and environmental goals through integrated land-use planning, boosting productivity, and providing targeted support for sustainable ecological farming systems. Policy recommendations include protecting agricultural land, encouraging agroecological practices, alleviating labour shortages, and promoting multi-stakeholder engagement within policy development. Overall, this research enhances understanding of land-use dynamics and agricultural resilience in SIDS, offering practical insights for policymakers and practitioners working towards sustainable food systems amid spatial and climatic constraints. Full article

The increasing emphasis on sustainability in construction materials has led to a surge of research focused on recycled aggregate self-compacting concrete (RA-SCC). However, the critical gap in predicting the compressive strength of concrete remains challenging because of the nonlinear interactions among the mix’s constituents. The distinct contribution of this study is to develop an interpretable machine learning (ML) framework to accurately forecast the compressive strength of RA-SCC and identify the most influential mix parameters. A dataset comprising 400 experimental samples was compiled, incorporating eight input variables: age, cement strength, cement, fly ash, blast furnace slag, water, recycled aggregate, and superplasticizer, with compressive strength as the output variable. Four ML algorithms such as support vector regression (SVR), random forest (RF), Multilayer Perceptron (MLP), and extreme gradient boosting (XGBoost) were trained and optimized using Bayesian-based hyperparameter tuning combined with 10-fold cross-validation. Among the evaluated models, XGBoost demonstrated superior accuracy, with R² = 0.98 and RMSE = 2.95 MPa during training, and R² = 0.96 with RMSE = 3.25 MPa during testing, confirming its robustness and minimal overfitting. SHAP (SHapley Additive exPlanations) evaluation indicates that superplasticizer, cement, and cement strength were the most dominant factors influencing compressive strength, whereas higher water content showed a negative impact. The developed framework demonstrates that explainable ML can effectively capture the complex nonlinear behavior of RA-SCC, offering a reliable tool for mix design optimization and sustainable concrete production. These findings contribute to advancing data-driven decision making in eco-efficient materials engineering. Full article

This study examines the role of different factors in supporting the sustainable use of Artificial Intelligence (AI) technologies in higher education, particularly in the context of student interactions with intelligent and human-centered learning tools. Using Structural Equation Modeling (SEM) and Artificial Neural Networks (ANN) within the Technology Acceptance Model (TAM), the research provides a detailed look at how trust influences students’ attitudes and behaviors toward AI-based learning platforms. Data were gathered from 200 students at Occidental Mindoro State College to analyze the effects of social influence, self-efficacy, perceived ease of use, perceived risk, attitude toward use, behavioral intention, acceptance, and actual use. Results from SEM indicate that perceived risk and ease of use have a stronger impact on AI adoption than perceived usefulness and trust. The ANN analysis further shows that acceptance is the most important factor influencing actual AI use, reflecting the complex, non-linear relationships between trust, risk, and adoption. These findings highlight the need for AI systems that are adaptive, transparent, and designed with the user experience in mind. By building interfaces that are more intuitive and reliable, educators and designers can strengthen human–AI interaction and promote responsible and lasting integration of AI in education. Full article

Eutectogels, obtained from the combination of deep eutectic systems (DESs) or natural deep eutectic systems (NADESs) with polymers, represent a new class of sustainable soft materials. Combining the tunable properties of DESs, such as low volatility, ionic conductivity, and biocompatibility, with the structural integrity of gels, these materials can be designed to have improved mechanical flexibility, self-healing ability, and environmental stability. Recent research focused on understanding how the composition of DESs, polymer type, or crosslinking mechanisms influence the physicochemical behavior and performance of eutectogels. Advances in this field enabled their use in diverse biotechnological applications, particularly in drug delivery, transdermal systems, wound healing, and tissue engineering, where they demonstrate improved biofunctionality and adaptability compared to traditional hydrogels. Nevertheless, challenges related to scalability, reproducibility, long-term stability, and toxicity must be addressed to reach their full potential. Progress in this area relies on multidisciplinary efforts between green chemistry, materials science, and bioengineering. Overcoming these hurdles could allow eutectogels to evolve from academic concepts into a new generation of sustainable, high-performance soft materials with broad applicability in the biotechnology field. Full article

Against the backdrop of China’s “dual carbon” strategy and regional integration, enhancing green innovation efficiency (GIE) has become a core issue for the Yangtze River Delta Urban Agglomeration (YRDUA) in achieving sustainable and high-quality development. This study employs the Super EBM model to measure the GIE of 41 cities in the YRDUA from 2012 to 2022 and further integrates a modified gravity model with social network analysis to uncover the structural complexity and spatial directionality of its spatial association network. In addition, the Exponential Random Graph Model (ERGM) is applied to explore the formation mechanisms of the green innovation efficiency network. Results show the following: (1) GIE presents a fluctuating upward trend, with the mean rising from 0.747 in 2012 to 0.906 in 2022 and disparities gradually narrowing, but provincial gradients persist, implying potential “Matthew effect” risks. (2) Network density continues to increase, with S-density rising from 0.0061 in 2012 to 0.0335 in 2022; supporting and basic connections serve as key drivers of network complexity, whereas the significant decline of edge connections may weaken the network’s extensibility. (3) Node connections display preference and attachment, causing polarization; transitivity and triadic cooperation rise markedly, increasing by 41.89% and 40.86%, respectively, reflecting strong self-organization. (4) Reciprocity and agglomeration drive network formation, and economic and technological differences promote it, while disparities in innovation input and government roles vary across periods. Geographic distance hinders formation, though its effect is weakening. These findings enhance the methodological approaches to sustainability research and provide insights for optimizing regional cooperation and advancing green integration in the YRDUA. Full article

Industry 5.0 introduces a shift toward human-centric, sustainable, and resilient industrial ecosystems, emphasizing intelligent automation, collaboration, and adaptive operations. Predictive Maintenance (PdM) plays a critical role in this transition, addressing the limitations of traditional maintenance approaches in increasingly complex and data-driven environments. The convergence of Artificial Intelligence and the Industrial Internet of Things, referred to as the Artificial Intelligence of Things (AIoT), enables real-time sensing, learning, and decision-making for advanced fault detection, Remaining Useful Life estimation, and prescriptive maintenance actions. This study provides a systematic and structured review of AIoT-enabled PdM aligned with Industry 5.0 objectives. It presents a unified taxonomy integrating AI models, Industrial Internet of Things (IIoT) infrastructures, and AIoT architectures; reviews AI-driven techniques, sector-specific implementations in manufacturing, transportation, and energy; and analyzes emerging paradigms such as Edge–Cloud collaboration, federated learning, self-supervised learning, and digital twins for autonomous and privacy-preserving maintenance. Furthermore, this paper synthesizes strengths, limitations, and cross-industry challenges, and outlines future research directions centered on explainability, data quality and heterogeneity, resource-constrained intelligence, cybersecurity, and human–AI collaboration. By bridging technological advancements with Industry 5.0 principles, this review contributes a comprehensive foundation for the development of scalable, trustworthy, and next-generation AIoT-based predictive maintenance systems. Full article

The present research examines how employees perceive their firms’ CSR initiatives that ultimately translate into desired attitudes and behaviors, i.e., employee environmental commitment (EEC) and knowledge sharing (KS) at the workplace, by underpinning social identity theory. However, when do undesired working conditions, i.e., Perception of Politics (POP), adversely influence these desired outcomes? We deliberately selected 45 firms in the services and manufacturing sectors of Pakistan operating in larger metropolitan cities and prevalent tourist destinations, and actively participating in CSR activities. Thereafter, three self-administered surveys were conducted by employing a time-lagged design with two temporal breaks. A total of 655 surveys were distributed among middle managers across selected firms. Accordingly, it is found that employees who strongly identify with their organizations tend to align their personal values with organizational sustainability efforts and actively participate in environmentally responsible practices. They also demonstrate a greater willingness to share knowledge and enhance the organization’s collective intelligence. However, when employees perceive a high level of political behavior within the organization, their trust in its ethical standards diminishes, leading to various negative attitudes and behaviors in the workplace. This research contributed in two ways to the existing literature: (a) by examining the employees’ understandings of firms’ CSR engagements and their trickle-down effect on EEC and KS, (b) and studying when POP adversely effects the above relationship. Full article

Microwave heating has a good number of advantages in the synthesis of inorganic compounds when opportunely exploited. A deep knowledge of the interaction of the electromagnetic waves and matter is necessary to optimize irradiation of the reactor vessel so as to obtain homogeneous heating for homogeneous nucleation and growth of particles, localized heating of starting self-sustained high-temperature synthesis, and generation of a superfast heating and cooling profile to obtain metastable crystals. Case studies of pure oxides, mixed oxides, composites, phosphates, zeolites, and high-entropy alloys are discussed in the international frame of the academic and industrial research covering the last 20 years of microwave chemistry where Italian researchers covered a relevant role. Full article

Background: Antibiotic resistance is a pressing public health concern, exacerbated by the prescribing of antibiotics in primary care settings when they are not clinically indicated. Research shows that providers often feel pressured to prescribe antibiotics in response to patients’ expectations. To address this challenge, we developed a theory-informed video intervention to enhance antibiotic stewardship communication skills among current and future primary care providers, with emphasis on college health settings. The intervention consisted of five videos targeting core skills: explaining diagnosis and treatment, discussing antibiotic risks, advising on symptom management, offering patient support, and navigating visits with emerging adults. Program effectiveness was assessed immediately and three months post-intervention. Methods: Providers and medical students (N = 135) completed a three-wave study. At baseline, they reported demographics, perceived importance of the five skill sets, as well as self-efficacy, and completed closed- and open-ended skill assessment. Two weeks later, participants viewed the intervention videos, reassessed their skills, and rated their motivation to improve. Three months after video exposure, they completed the same skill assessments. Results: Participants showed improvements in all communication skills immediately post-intervention, except for supporting patients. While some skills showed sustained improvements at three months, the overall long-term effects were less pronounced. Perceived skill importance, baseline self-efficacy, and post-intervention motivation moderated these effects. Conclusions: A brief video-based intervention effectively enhanced current and future providers’ antibiotic stewardship communication skills. Sustaining these gains, however, requires ongoing reinforcement. Notably, the intervention was especially beneficial for those with low motivation and self-efficacy, key targets for such programs. Full article

The transition to sustainable food systems requires communication strategies that resonate with consumers’ values, not only technological innovation. This study examines how values-centric communication can shape German consumers’ responses to alternative proteins, focusing on insect-based snacks. A desk-based synthesis of recent studies, guided by Schwartz’s value theory, identified Tradition and Security as dominant drivers of food choice and yielded five communication requirements: Cultural familiarity, Emotional safety, Simplicity and clarity, Trust and credibility, and Routine integration. These were operationalised into communication guidelines and short on-pack claims, which were applied to a refined packaging prototype. An exploratory focus group (N = 7) then compared reactions to the original versus the refined packaging, analysed using McGuire’s communication–persuasion stages. Within this small exploratory group, participants reported that familiar formats, a reassuring tone, clear visual hierarchy, and salient trust cues made them more willing to consider trying the product, whereas information overload, claim–image incongruence, value-incongruent brand naming, and delayed recognition of insect content appeared to impede acceptance. The study contributes an integrative analytic lens combining Schwartz’s value theory with McGuire’s model and a set of testable guidelines for value-aligned food communication. Because the empirical evidence is based on a single small student focus group with fixed presentation order, bundled manipulations, and hypothetical intentions, these results are exploratory and self-reported and should be interpreted cautiously; future research should employ counterbalanced factorial designs with behavioural outcomes. Full article

In 2016, the South African government approved free oral PrEP distribution among high-risk groups like female sex workers (FSWs) to reduce new HIV infections. Despite the availability, unique barriers exist that challenge PrEP persistence, including limited knowledge, side effects, stigma, and mobility that hinder adherence. As such, engaging FSWs in the design of an FSW-led intervention program is crucial to promote PrEP uptake, adherence, and retention. Processes of an intervention mapping approach were applied to design and develop the program in KwaZulu-Natal, South Africa. A needs analysis was completed through existing literature and through engagements with FSWs, FSW peer educators, and a healthcare provider. The working group, comprising eight FSW peer educators and a researcher, co-created the intervention following a six-step mapping process. A total of six meetings took place, during which intervention determinants, change objectives, theory-based methods, and the intervention program were discussed and formulated, as well as implementing partners and the evaluation plan identified. The program focuses on the development of agency, self-efficacy, and hope among FSWs and aims to destigmatize PrEP through positive messaging, equipping FSWs with the ability to differentiate PrEP from ARVs given to people living with HIV. Through role-playing, participants will practice discussing PrEP with their intimate partners and friends, receive suggestions on managing pill supply and side effects, and be equipped to become PrEP ambassadors. The introduction of PrEP as a pill for high-risk groups can be stigmatizing. Therefore, it is crucial to involve marginalized groups in the design and implementation of their interventions to foster acceptance and develop a sense of ownership, ensuring the programs’ sustainability. Full article

Leakage from defective buried pipelines can lead to progressive soil erosion and void formation, ultimately resulting in ground collapse or sinkhole development. To better understand the underlying mechanisms of this process, this research utilizes a coupled computational fluid dynamics (CFD)–discrete element method (DEM) modeling approach to investigate soil erosion processes driven by water leakage from defective underground pipelines. The numerical model captures fluid–particle interactions at both macroscopic and microscopic scales, providing detailed insights into erosion initiation, void zone evolution, and particle transport dynamics under varying hydraulic and geometric conditions. Parametric studies were conducted to evaluate the effects of exfiltration pressure, defect size, and particle diameter on erosion behavior. Results show that erosion intensity and particle migration increase with hydraulic pressure up to a threshold, beyond which compaction and particle bridging reduce sustained transport. The intermediate defect size (12.7 mm) consistently produced the most continuous and stable erosion channels, while smaller and larger defects exhibited localized or asymmetric detachment patterns. Particle size strongly influenced erosion susceptibility, with finer grains mobilized more readily under the same flow conditions. The CFD–DEM simulations successfully reproduce the nonlinear and self-reinforcing nature of internal erosion, revealing how hydraulic gradients and particle rearrangement govern the transition from local detachment to large-scale cavity development. These findings advance the understanding of subsurface instability mechanisms around leaking pipelines and provide a physically consistent CFD–DEM framework that aligns well with published studies. The model effectively reproduces the key stages of erosion observed in the literature, offering a valuable tool for assessing erosion-induced risks and for designing preventive measures to protect buried infrastructure. Full article

Obesity remains a major global health challenge, with glucagon-like peptide-1 receptor agonists (GLP-1RAs) providing substantial yet sensitive benefits in weight reduction, glycemic control, and cardiovascular protection. Despite robust trial data, real-world persistence is limited by cost, tolerability, and hedonic adaptation. Intermittent fasting and time-restricted eating offer physiologically complementary, low-cost strategies that enhance fat oxidation, insulin sensitivity, and metabolic flexibility while engaging behavioral mechanisms of self-control and dietary regularity. This narrative review synthesizes current evidence and proposes a pragmatic, phased framework integrating GLP-1RA therapy with structured intermittent fasting and protein-optimized nutrition. The model emphasizes sequential initiation, transition, and maintenance phases designed to align pharmacologic appetite suppression with lifestyle-driven metabolic remodeling. Mechanistically, GLP-1RAs target vascular and neuroendocrine pathways, whereas fasting activates nutrient-sensing networks (AMPK, mTOR, sirtuins) associated with autophagy and longevity. Combined application may preserve lean mass, improve psychological autonomy, and reduce healthcare costs. Future research should validate this hybrid strategy in randomized trials assessing long-term weight durability, functional outcomes, and cost-effectiveness. By uniting pharmacologic potency with behavioral sustainability, phased GLP-1–fasting integration may represent an effective, affordable, and longevity-oriented paradigm for metabolic health. Full article

Overweight and obesity are major public health concerns among children and adolescents worldwide. The most prevalent form is exogenous–constitutional obesity, which is driven by a sedentary lifestyle and an unhealthy diet in which caloric intake exceeds energy expenditure. Beyond their association with chronic disease, these factors are closely linked to deficits in cognitive development and executive functions essential for learning (including working memory, sustained attention, planning, behavioral self-regulation, and cognitive flexibility). Oxidative stress (OS), characterized by the accumulation of reactive oxygen species (ROS) in cells and extracellular fluids, is a significant potential mediator in childhood obesity and an important contributor to its comorbidities. The antioxidant defense system (AOD)’s activity largely depends on levels of trace element cofactors, which determine the body’s resistance to adverse environmental factors (the “maladaptation phenomenon”). OS and trace element deficiencies contribute to the development of morphological changes in the brain, thus serving as a critical connecting link between childhood obesity and cognitive impairment. Non-pharmacological interventions are the most accessible and effective approach for prevention and treatment. Bioactive compounds derived from food and natural plants, classified as antioxidants and phytopreparations, may represent a promising complementary approach. These compounds are most effective when used in combination with sustained lifestyle modifications in children. Research in this area can help define future directions for study and develop targeted intervention strategies in the pediatric population. The aim of this review is to examine the relationship between OS, antioxidant cofactor micronutrients, and cognitive outcomes in childhood obesity and to explore mechanisms, evidence, and therapeutic opportunities. Full article

Background: A key barrier to realizing the full potential and long-term collection of patient-reported outcomes (PROs) is the limited understanding of user experience (UX) factors that influence sustained patient engagement with digital PRO tools. Most existing research focuses on disease-specific or country-specific solutions, leaving a gap in identifying shared UX determinants that could inform scalable, cross-disease European digital health frameworks. This fragmentation hinders interoperability and increases development costs by requiring separate tools for each context. This case study aims to address this gap by identifying key UX features that optimize PRO collection across diverse chronic conditions in Europe within the Health Outcomes Observatory project, enhancing continuous (primary use) and large-scale (secondary use) data collection. Objective: This study aimed to identify and analyze key UX factors that support adoption and sustained use of PRO collection tools among patients with chronic diseases across multiple European countries. Methods: Patient focus groups were conducted in four chronic disease areas: cancer, inflammatory bowel disease (IBD), and diabetes (type I and II) across six European countries. Participants were recruited purposively through national patient advisory boards to ensure diversity in age, gender, and disease type. Sessions were moderated by trained qualitative researchers following a standardized guide, and discussions were transcribed verbatim and coded in researcher pairs to ensure intercoder reliability through iterative consensus. A modified thematic analysis, guided deductively by the UX Honeycomb model and inductively by emergent themes, was used to identify cross-disease UX determinants. Results: In total, 17 patients and patient representatives participated (76% female; 4 diabetes, 6 IBD and 7 cancer). We identified six core UX factors driving patient engagement for all disease groups: compatibility with other technologies, direct communication with the care team, personalization, ability to share data, the need for educational material and data protection were identified as key aspects of PRO technologies. However, the customizability of the app is crucial. Not all disease groups had the same needs, and participants specifically requested that the app provide information relevant to their own condition. Disease-specific needs, like T1D patients desiring glucose monitoring integration, were identified. IBD patients highlighted flare detection abilities and cancer patients especially sought side-effect comparisons. Conclusions: Our findings indicate that a unified yet customizable PRO platform can address shared UX needs across diseases, improving patient engagement and data quality. Incorporating features such as seamless data transfer, personalization, feedback, and strong privacy measures can foster trust and long-term adoption across European contexts. In addition to some disease-specific issues, most needs for the backbone of the app were shared among the disease areas. This shows that a shared app between diseases might be preferable and, in case of comorbidities, could ease self-management for patients. Last, to ensure full potential for every user and every disease, customization is crucial. Full article