Search Results (1,836)

This paper develops a mathematically grounded neuro-fuzzy control framework for IoT-enabled irrigation systems in precision agriculture. A discrete-time, physically motivated model of soil moisture is formulated to capture the nonlinear water dynamics driven by evapotranspiration, irrigation, and drainage in the crop root zone. A Mamdani-type fuzzy controller is designed to approximate the optimal irrigation strategy, and an equivalent Takagi–Sugeno (TS) representation is derived, enabling a rigorous stability analysis based on Input-to-State Stability (ISS) theory and Linear Matrix Inequalities (LMIs). Online parameter estimation is performed using a Recursive Least Squares (RLS) algorithm applied to real IoT field data collected from a drip-irrigated orchard. To enhance prediction accuracy and long-term adaptability, the fuzzy controller is augmented with lightweight artificial neural network (ANN) modules for evapotranspiration estimation and slow adaptation of membership-function parameters. This work provides one of the first mathematically certified neuro-fuzzy irrigation controllers integrating ANN-based estimation with Input-to-State Stability (ISS) and LMI-based stability guarantees. Under mild Lipschitz continuity and boundedness assumptions, the resulting neuro-fuzzy closed-loop system is proven to be uniformly ultimately bounded. Experimental validation in an operational IoT setup demonstrates accurate soil-moisture regulation, with a tracking error below 2%, and approximately 28% reduction in water consumption compared to fixed-schedule irrigation. The proposed framework is validated on a real IoT deployment and positioned relative to existing intelligent irrigation approaches. Full article

This study examines consumer behavior, preferences, and knowledge regarding honey in Kosovo to inform more effective production, marketing, and policy strategies. Data were collected from 503 respondents through an online questionnaire and analyzed using a combination of artificial neural networks (ANN), decision tree modeling (CHAID), and ordinal logistic regression. The results show a high prevalence of honey consumption, strong preference for locally produced honey, and significant variability in consumer willingness to pay (WTP) based on knowledge, income, and trusted information sources. ANN identified recommendations and product familiarity as primary predictors of WTP, while the decision tree highlighted knowledge and income as key variables for segmentation. The ordinal logistic regression confirmed the importance of perceived quality and product attributes, particularly botanical and geographical origin, in shaping purchasing decisions. The use of complementary statistical models enhanced both predictive power and interpretability. The findings highlight the crucial role of consumer education and trust cues in fostering sustainable honey markets in Kosovo. Full article

Introduction: The COVID-19 pandemic had significant effects on mental health and lifestyle behaviours, especially among university students who experienced academic disruptions, social isolation, and fewer social interactions. Alcohol consumption has long been part of student culture. Still, the influence of post-pandemic academic reintegration on drinking patterns and psychological distress remains relatively unexplored, particularly in countries like Portugal, where student traditions heavily shape consumption habits. This study aimed to describe the prevalence of alcohol consumption, depression, anxiety, and stress in a sample of Portuguese university students during the post-pandemic academic period, and to explore associations with sociodemographic variables. Methods: A cross-sectional study was conducted in November 2021 with 90 students from a private higher education institution in northern Portugal. Data were collected via an online questionnaire including sociodemographic information, the Alcohol Use Disorders Identification Test (AUDIT), and the Depression, Anxiety and Stress Scale (DASS-21). Result: The majority of the participants were not at risk of alcohol addiction (95.3%). In total, 15.1% of students reported anxiety symptoms ranging from severe to extremely severe. A binomial logistic regression was performed to ascertain the effects of being away from home and psychological distress (DASS-42 score), on the likelihood that participants were at risk of alcohol addiction (Level 3 and 4 in the AUDIT scale). The logistic regression model was statistically significant, χ²(2) = 9.20, p = 0.010. Living away from home was associated with a substantially lower likelihood of high-risk status (B = −2.79, p = 0.034), corresponding to an odds ratio of 0.06, indicating a strong protective effect. DASS-42 total score was positively associated with high-risk status (B = 0.04, p = 0.039), such that higher psychological distress increased the odds of being classified as high risk. Conclusions: The findings reveal a low prevalence of alcohol risk but heightened symptoms of anxiety, depression, and stress. Psychological distress notably increases the likelihood of hazardous alcohol use, emphasising the importance of targeted mental health and alcohol-use interventions among university students. Full article

Background/Objectives: To promote sustainable and healthy diets, increased consumption of pulses (the edible grains of legumes) is recommended. Adolescence is a period in which perceptions and behaviours develop that can impact lifelong dietary behaviours. Therefore, this study aimed to understand how Australian adolescents perceive healthy, sustainable diets and perceive and consume pulses. Methods: Students (11–17 years old, median = 15 years, n = 33) in Brisbane, Australia, participated in school-based face-to-face focus groups and an online survey. Results: Students’ perceptions of healthy and sustainable dietary behaviours largely focused on the health aspects of food and consideration of food waste. The main factors that adolescents identified as influencing the health and sustainability of their diet were a lack of perceived responsibility for the impact of their meal choices and lack of knowledge of what constitutes a healthy and sustainable diet. Most students were unfamiliar with the term ‘pulses’ and lacked a desire to consume pulses more often. Consumption of pulses was below recommendations in national and international dietary guidelines. The main factors that adolescents identified as influencing pulse consumption related to students’ lack of capability to prepare pulses and the limited opportunities to access pulse-based foods. Conclusions: Perceptions of sustainable diets and pulses were very limited, and a lack of knowledge, skills, and limited availability were identified as barriers to their consumption. Education and cooking classes, in conjunction with increased availability of tasty pulse foods, are recommended to increase students’ pulse consumption as part of a healthy and sustainable diet. Full article

Background/Objectives: The overconsumption of animal-derived proteins represents a threat to both the environment and our health. Although there is widespread agreement that reducing meat consumption represents a more sustainable alternative, few studies have explored the implicit relations guiding these food choices. This empirical study explores meat consumption and vegetarianism through the lens of Relational Frame Theory. It is hypothesized that people who eat meat have different relational responses to images of meat and plant-based alternatives than vegetarians. Methods: We used the Implicit Attribute Classification Task (IMPACT) to measure relational responses, testing whether omnivores find plant-based proteins (1) less tasty, (2) less familiar, and (3) more expensive than vegetarians do. We registered the response latencies and calculated D-scores from 110 participants who completed an online test. Results: The study failed to find any statistically significant differences in the IMPACT measures between omnivores and vegetarians, given our specific participants and stimuli. Conclusions: Relational responding measures offer a useful approach to understanding consumer choices. However, they are highly sensitive to the task parameters and could be enhanced by further integration with other consumer behavior models when explaining meat consumption. Full article

Background: Tribulus terrestris (Tt) is a popular herbal supplement marketed to enhance fitness performance, despite inconclusive evidence regarding its efficacy and safety. This study aimed to investigate the prevalence of TT use, awareness, and motivations for its use among recreational athletes in Italy, helping to address the lack of empirical data describing who actually uses Tt, for what purposes, and with what behavioral risks. Methods: A cross-sectional anonymous survey was administered between May and October 2024 across Italian gyms and fitness clubs using Microsoft Forms. A total of 696 individuals initiated the questionnaire; after removal of duplicate, incomplete and ineligible entries, 510 responses were analyzed. Two indicators of Tt consumption were assessed: ever use and current use, with the latter designated as the primary outcome. A multivariable logistic regression evaluated predictors of current Tt use, entering sex, age category (18–24, 25–34, 35–44, ≥45 years), and motivation for supplement consumption. Results: Current Tt use was reported by 7.8% of respondents, while 10.5% declared ever using a Tt-containing product. Motivation was the only independent predictor of Tt consumption (p = 0.012). Individuals reporting performance enhancement as their primary motivation were markedly more likely to currently use Tt, compared with those using supplements for other purposes (adjusted OR ≈ 18.5; p = 0.008). Neither sex (p = 0.918) nor age category (p = 0.519) significantly predicted Tt use. Admission of anabolic steroid use was infrequent but was linked to online purchasing from potentially unregulated sources. Conclusions: Tt consumption in fitness settings is driven predominantly by performance-oriented expectations rather than demographic characteristics. The observed discrepancy between consumer beliefs and scientific evidence suggests a pressing need for educational interventions and regulatory vigilance in sports nutrition. Public health policies should focus on improving label literacy, strengthening consumer protection, and countering misinformation within supplement marketing environments. Full article

The growing global environmental crisis calls for fundamental transformations in production and consumption systems, but the understanding of how circular economy strategies translate into quantifiable environmental benefits remains fragmented across sectors and geographies. The objective of this study is to synthesize current scientific knowledge on the circular economy as an environmental mitigation strategy, identifying conceptual convergences, methodological patterns, geographic distributions, and critical knowledge gaps. A systematic review combined with a bibliometric analysis of 62 peer-reviewed articles published between 2018 and 2024, retrieved from Scopus, Web of Science, ScienceDirect, Springer Link and Wiley Online Library, was conducted following the PRISMA 2020 guidelines. The results reveal a marked methodological convergence around life cycle assessment, with Europe dominating the scientific output (58% of the corpus). Four complementary conceptual frameworks emerged, emphasizing closed-loop material flows, environmental performance, integration of economic sustainability and business model innovation. The thematic analysis identified bioenergy and waste valorization as the most mature implementation pathways, constituting 23% of the research emphasis. However, critical gaps remain: geographic concentration limits the transferability of knowledge to diverse socioeconomic contexts; social, cultural and behavioral dimensions remain underexplored (12% of publications); and environmental justice considerations receive negligible attention. Crucially, the evidence reveals nonlinear relationships between circularity metrics and environmental outcomes, calling into question automatic benefits assumptions. This review contributes to an integrative synthesis that advances theoretical understanding of circularity-environment relationships while providing evidence-based guidance for researchers, practitioners, and policy makers involved in transitions to the circular economy. Full article

Background: Adolescence is a formative period for lifelong dietary patterns, yet Korean adolescents show low fruit and vegetable intake, high sugar and sodium consumption, and rising obesity, highlighting the importance of multidimensional assessment that integrates behavioral, cultural, environmental, and competency-related factors. Methods: A total of 1010 adolescents aged 12–18 years completed an online cross-sectional survey assessing food intake, dietary and physical activity behaviors, dietary culture, and Food Literacy (FL) competencies. Standardized scores were used for hierarchical and K-means clustering to identify dietary practice patterns, and between-cluster differences were examined using ANOVA. Correlation and regression analyses were conducted to examine associations between Dietary Guideline Adherence (DGA) and FL. Results: Four clusters were identified—selective intake–low support (20.4%), regular habits–unbalanced intake (33.3%), high adherence (23.2%), and low adherence (23.1%)—with significant differences in DGA total and domain scores (p < 0.001). The high-adherence cluster showed balanced intake, regular routines, and strong household support, whereas the low-adherence cluster showed poor diet quality, irregular behaviors, and lower socioeconomic status. FL differed across clusters (p < 0.001) and correlated with DGA (r = 0.496, p < 0.01). Total FL predicted DGA (β = 0.496, p < 0.001), explaining 25% of its variance (R² = 0.246). Conclusions: Adolescent diet quality appears to be associated with behavioral, cultural, and competency-related factors. These findings suggest that cluster-specific strategies—such as fat–sugar–sodium reduction, promotion of low-sodium and diverse diets, and maintenance of balanced-dietary patterns—may support tailored school- and community-based nutrition programs and inform further longitudinal and intervention research. Full article

The article presents an approach to synthesizing artificial intelligence agents (AI agents), in particular, control and decision support systems for process operators in various industries. Such a system contains an identifier in the feedback loop that generates digital predictive associative search models of the Just-in-Time Learning (JITL) type. It is demonstrated that the system can simultaneously solve (outside the control loop) two additional tasks: online operator pre-training and mutual adaptation of the operator and the system based on real-world production data. Solving the latter task is crucial for teaching the operator and the system collaborative handling of abnormal situations. AI agents improve control efficiency through self-learning, personalized operator support, and intelligent interface. Stabilization of process variables and minimization of deviations from optimal conditions make it possible to operate process plants close to constraints with sustainable product qualities. Along with higher yield of target product(s), this reduces equipment wear and tear, utilities consumption and associated harmful emissions. This is the key merit of Model Predictive Control (MPC) systems, which justify their application. JITL-type models proposed in the article are more precise than conventional ones used in MPC; therefore, they enable the operation even closer to process constraints. Altogether, this further improves the reliability of production systems and contributes to their sustainable development. Full article

With the rapid development of urban rail transit, train operation control is required to meet increasingly stringent demands in terms of energy consumption, comfort, punctuality, and precise stopping. The optimization and tracking control of speed profiles are two critical issues in ensuring the performance of automatic train operation systems. However, conventional model predictive control (MPC) methods are highly dependent on parameter settings and show limited adaptability, while heuristic optimization approaches such as the whale optimization algorithm (WOA) often suffer from premature convergence and insufficient robustness. To overcome these limitations, this study proposes an optimized model predictive controller using the multi-objective whale optimization algorithm (MPC-MOWOA) for urban rail train tracking control. In the improved optimization algorithm, a nonlinear convergence mechanism and the Tchebycheff decomposition method are introduced to enhance convergence accuracy and population diversity, which enables effective optimization of the initial parameters of the MPC. During real-time operation, the MPC is further enhanced by integrating a fuzzy satisfaction function that adaptively adjusts the softening factor. In addition, the control coefficients are corrected online according to the speed error and its rate of change, thereby improving adaptability of the control system. Taking the section from Lvshun New Port to Tieshan Town on Dalian Metro Line 12 as the study case, the proposed control algorithm was deployed on a TMS320F28335 embedded processor platform, and hardware-in-the-loop simulation experiments (HILSEs) were conducted under the same simulation environment, a unified train dynamic model, consistent operating conditions, and an identical evaluation index system. The results indicate that, compared with the Fuzzy-PID control method, the proposed control strategy reduces the integral of time-weighted absolute error nearly by 39.6% and decreases energy consumption nearly by 5.9%, while punctuality, stopping accuracy, and comfort are improved nearly by 33.2%, 12.4%, and 7.1%, respectively. These results not only verify the superior performance of the proposed MPC-MOWOA, but also demonstrate its capability for real-time implementation on embedded processors, thereby overcoming the limitations of purely MATLAB-based offline simulations and exhibiting strong potential for practical engineering applications in urban rail transit. Full article

The circadian cycle regulates metabolism in response to external stimuli, such as light exposure, sleep schedules, and eating patterns. However, misalignment between internal biological rhythms and social demands can compromise food choices, potentially leading to overweight and obesity. This research aimed to assess how a person’s chronotype links to social jet lag (SJL), which in turn would relate to their nutritional status and food consumption patterns as a university student. 617 students from a State University located in the State of Paraná, Brazil, completed a cross-sectional research study that collected sociodemographic information/anthropometrics by means of an online survey. It included self-reported height/weight data and dietary habits. The Munich Chronotype Questionnaire (MCTQ) was utilized to determine each participant’s chronotype classification and SJL calculation. Researchers found that nearly half of the students (49.3%) displayed an Intermediate Chronotype, which is associated with a diet that contained elements of the “Mixed” Diet, meaning there are equal portions of healthy food (Fresh Fruits, Beans, etc.) and unhealthy foods (Sweetened Beverages). The multivariate logistic regression analyses identified age as a significant predictor of obesity risk (OR: 1.15, p < 0.001), while dietary habits such as fruit consumption played a protective role. Additionally, having a breakfast protected them from being classified as obese compared to those who did not eat breakfast (OR = 0.59). Contrary to expectations, late-night supper was not a statistically significant predictor in the adjusted model. Predictors of an Intermediate chronotype included being male and eating morning snacks regularly. The results of this study suggest that students with an intermediate chronotype will predictably have skewed eating patterns, such as skipping breakfast and eating late—both of which affect obesity risks. Nutritional strategies for university students should focus on promoting circadian regularity and optimizing meal timing. Full article

Shiitake mushrooms (Lentinula edodes) are widely consumed as a key health food in the Republic of Korea. However, they face declining production value and consumption, necessitating a shift from production-focused research to an understanding of consumer demand. The aim of this study was to quantify Korean consumers’ trade-offs among key shiitake attributes and to derive actionable marketing strategies to expand domestic consumption. We conducted an online survey (n = 500) to quantify consumer utility for four key attributes: cap size (two levels), cap color (two levels), origin (two levels: domestic (Korean) and imported (Chinese)), and price (four levels per 500 g). The results identified price as the most important attribute (relative importance = 46.41%), followed by origin (19.85%), cap color (17.10%), and cap size (16.64%). Utility analysis (part-worths) revealed a distinct dual preference: consumers value both low-priced shiitake (KRW 4000 (USD 2.9)/500 g) for personal consumption and high-priced options (KRW 13,000 (USD 9.5)/500 g) for gifting. Consumers showed a clear preference for dark-colored caps, while the aggregate-level utility difference between origin levels was small. A Logit model simulation indicated the highest predicted shares for profiles priced at KRW 13,000 (15.9%) and KRW 4000 (15.7%), consistent with a polarized value–premium structure. These findings indicate that Korean producers should adopt a dual strategy: developing low-cost products to stimulate general consumption while simultaneously marketing high-quality, dark-colored, domestically produced shiitake as premium gift items, thereby establishing effective food choice strategies in a competitive market. Although the empirical setting is the Republic of Korea (with ‘Chinese’ included only as an imported-origin level representing the main foreign competitor), the findings speak to broader specialty-food contexts where import competition and dual-purpose purchasing (everyday use vs. gifting) shape attribute trade-offs. Full article

This study examines consumer opinions and behavior toward international food standards related to sustainability and environmental responsibility. For the data collection process, a structured questionnaire was distributed online and completed by 1064 participants. The study focuses on assessing consumer awareness of food standards, the extent to which these standards influence purchasing decisions, and the demographic factors affecting such choices. The findings reveal a growing interest in sustainable products, particularly among younger age groups. However, the study also identifies significant gaps in knowledge and understanding of international standards, which hinder the adoption of more responsible consumption practices. It concludes with recommendations to improve awareness, transparency, and food labeling, as well as to promote sustainable consumption through coordinated policies and educational initiatives. Full article

The growth of e-commerce in emerging economies presents a critical opportunity to steer digital consumption toward sustainability, yet the mechanisms that drive online green purchases in these contexts remain underexplored. This study examines how green digital marketing signals, specifically eco-labeling and sustainability claims, influence the online purchase intention for sustainable coffee in urban Ethiopia, introducing digital literacy as a key moderating factor. Grounded in an integrated framework of Signaling Theory and the Theory of Planned Behavior, the research model was tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) on data from 451 urban e-commerce consumers. The results confirm that both eco-labeling and sustainability claims significantly enhance purchase intention, with green trust serving as a significant partial mediator. A pivotal finding is that digital literacy positively and significantly moderates the relationship between green trust and purchase intention, indicating that consumers with higher digital competence are more effective at translating trust into purchase decisions. These findings underscore that the success of online green marketing is contingent not only on signal credibility but also on user capability, offering crucial insights for platform design and policy in emerging digital markets. Full article

This study re-examines generational differences in media literacy and news consumption within the evolving digital landscape. It expands on the well-known dichotomy of Digital Natives and Digital Immigrants by proposing a new conceptual framework that introduces the terms Analog Anchors and Digital Floaters. These terms aim to reflect the heterogeneity and fluidity more accurately, the adaptive nature of users’ engagement with digital media. A quantitative survey was conducted using an online questionnaire distributed to Greek participants (N = 1020) through a non-probability convenience sampling method. The analysis revealed significant variations in digital literacy, news consumption habits, and skepticism toward the media across generations. Findings indicate that the relationships with technology and information are not linear or age-bound but are shaped by cultural, cognitive, and social parameters. High levels of media skepticism observed across all age groups further challenge traditional divides. As a result, this study argues for a paradigm shift that captures the complexity of media literacy in the platform era, moving from static generational labels towards a more dynamic understanding of users as Analog Anchors and Digital Floaters. Full article