Search Results (368)

Consumers have become more interested in leading better and higher quality lives, and have become more aware of the health effects nutrition has on their body, stimulating the development of functional foods (FF), recognized for their ability to provide physiological benefits that go beyond conventional nutritional function. The evolution of this product category is supported by the progress of research on bioactive compounds and changing consumer preferences, but empirical evidence regarding the level of knowledge, acceptance and purchasing behavior of Romanian consumers remains insufficient. Meanwhile, technology in the food industry has evolved significantly in recent decades, creating opportunities for entrepreneurs and consumers. Using empirical evidence from a survey carried out on the consumers in the region of Transylvania, the study uses a cross-sectional observational design and investigates the awareness of and the population’s differences in perception and attitude on FF products depending on the generations and socio-economic situations consumers belong to, and the impact FF have on the market. The analysis focuses on food choice behaviors, degree of trust in health benefits and factors influencing the decision-making process. The results show that consumers are not aware of the FF concept, but understand the relation between food choice behaviors and personal health and act accordingly. Results also show that older consumers are more aware of their health, and younger consumers are more influenced by trends. This paper can be of importance to consumers, entrepreneurs, food and technological industries, governments and universities. Full article

Background/Objectives: Zero-calorie beverages (ZCB) are increasingly consumed by adolescents, yet their relationship with mental health remains unclear, and whether any association differs by sex has not been established. We examined the association between ZCB consumption and depressive symptoms in a nationally representative sample of Korean adolescents, with sex as a prespecified effect modifier. Methods: This cross-sectional study analyzed 50,972 adolescents aged 12–18 years (50.9% male; mean age, 15.0 years) from the 2025 Korea Youth Risk Behavior Web-based Survey. Self-reported ZCB consumption during the previous 7 days and depressive symptoms during the previous 12 months were assessed. ZCB consumption was categorized as none, ≤2/week, 3–6/week, or ≥1/day. Survey-weighted logistic regression estimated adjusted odds ratios (aORs) with 95% confidence intervals (CIs), with non-consumers as the reference. Effect modification by sex was assessed using interaction terms. Results: Depressive symptoms were reported by 12,954 adolescents (25.4%). ZCB consumption was associated with higher odds of depressive symptoms across consumption categories (aOR for ≥1/day 1.76, 95% CI 1.45–2.13; p for trend < 0.001), after adjustment for sociodemographic and lifestyle covariates. The association appeared stronger among females than among males (aOR 1.14 [95% CI 1.11–1.18] vs. 1.05 [1.02–1.08]; p for interaction < 0.001), though significant in both sexes, and persisted after additional adjustment for co-consumed sugar-sweetened and high-caffeine beverages. Conclusions: In this nationally representative sample, daily ZCB consumption was associated with depressive symptoms, with a stronger association observed among females. Prospective studies are warranted to clarify temporality and underlying mechanisms. Full article

Consumer behavior evolves unexpectedly, and understanding new perspectives according to market trends is a key factor in identifying the most commonly recurring consumption demands. In this context, this study aimed to examine the associations among green consumption orientation, consumer ethical beliefs and green purchasing intention. Based on a quantitative and explanatory study with the participation of 411 Peruvian consumers, this study demonstrated that green consumption orientation has a direct and negative association with consumers’ ethical beliefs, while green consumption orientation has a direct and positive association with green purchasing intention. Finally, green purchasing intention has a direct and negative association with the ethical beliefs of Peruvian consumers. These findings reveal a reconfiguration of the ethical framework of Peruvian consumers, where green consumption orientation acts as a catalyst for the intention to purchase eco-friendly products, but at the same time generates tensions with traditional ethical beliefs. This phenomenon suggests that consumers are developing new value systems that prioritize environmental sustainability over conventional ethical considerations, which represents both a challenge and an opportunity for companies seeking to position themselves in the green market. Full article

Accurate distance measurement in outdoor environments remains a challenging problem for mobile augmented reality (AR) systems due to sensor noise, environmental variability, and the limitations of single-modality approaches. Existing consumer AR solutions often prioritize usability over metric robustness, leading to performance degradation in large-scale or heterogeneous outdoor scenarios. This work presents EfMAR, an adaptive framework for outdoor mobile AR-based geospatial measurements that integrates multiple sensing modalities through a structured sensor fusion architecture. EfMAR combines visual SLAM, inertial sensing, depth information, and global positioning cues to improve robustness and consistency in distance estimation across diverse outdoor conditions. Beyond implementation, the framework formalizes a reusable architectural model for adaptive multi-sensor fusion, supporting reproducibility and future comparative research. A dedicated dataset is described, comprising 584 unique real-world evaluation instances collected across representative outdoor scenarios. External literature-derived data were utilized strictly as calibration baselines for modeled operational degradation profiles, maintaining methodological transparency. Performance evaluation focuses on analyzing relative behavior, stability, and variability across sensing approaches rather than establishing absolute accuracy benchmarks. Comparative results across multiple distance ranges and environments indicate that hybrid sensor fusion strategies exhibit more stable and consistent performance trends compared to single-modality solutions, particularly in challenging urban contexts. Dispersion analysis further highlights the influence of environmental factors such as lighting conditions and spatial scale on measurement variability. Overall, the results position EfMAR as a flexible and adaptive framework designed to enhance robustness in outdoor AR-based geospatial measurement tasks. By emphasizing consistency, transparency, and architectural generalization, this work contributes a practical foundation for future research and development in mobile AR sensing for real-world outdoor applications. Full article

Cardiovascular disease (CVD) remains the leading global cause of death, with approximately 17.9 million mortalities annually. Studies have shown that adopting healthy behaviors, i.e., a balanced diet, regular physical activity, and weight management, can reduce CVD risk. However, evaluating their long-term impact requires extensive data collection and analysis, which are both time-consuming and challenging. This study developed a novel mathematical framework integrating an agent-based model (ABM) to simulate CVD risk progression and established clinical guidelines into synthetic training data for machine learning (ML) classification. The ML model was trained entirely on synthetic data generated from World Health Organization/International Society of Hypertension cardiac risk indications, and validated using outcomes from a NetLogo simulation. The workflow does not use real patient data; instead, the expected simulation results serve as a reference to assess the ML model and synthetic data. The ABM, designed in NetLogo, exchanges agent characteristics with a trained ML model to classify individuals into appropriate CVD risk levels based on lifestyle and clinical parameters. The simulation indicated measurable risk progression (5–12%) by year 20 in individuals with both smoking and diabetes. A combined effect of high dietary intake and low physical activity showed over 20% risk increase, demonstrating the model’s capacity to capture dynamic risk interactions. The relationship between CVD risk and systolic blood pressure was also effectively reproduced. Additional scenarios confirmed the alignment of model outcomes with real-world trends, showing model self-consistency, identifying critical thresholds and population-level risk shifts through detailed tabular analysis. Beyond confirming known associations, the findings support the internal consistency of the model, highlighting its potential as a simulation based tool for studying cardiovascular risk patterns and supporting risk monitoring within controlled settings. Full article

Recently, the Japanese government has introduced ambitious policies for agricultural sustainability, specifically the MIDORI Strategy, aimed at reducing chemical fertilizer use, expanding organic farmland, and increasing calorie-based food self-sufficiency. To evaluate the feasibility of these goals, this study quantified nitrogen and phosphorus flows within the 2021 food and feed system using a normalized “Nutrient Index”. A scenario analysis was conducted using policy targets as parameters, where currently non-circulated waste streams were modeled as potential sources for domestic nutrient recovery. The results indicate that Scenario A (a 30% reduction of chemical fertilizers) is the most feasible, achieving significant improvements in circulation ratios through recovery of nutrients from sewage and livestock waste. While Scenario B (increasing organic farmland) shows similar trends, its success depends on technological advancements to mitigate the yield gap between organic and conventional systems. Scenario C (increasing calorie-based food self-sufficiency) presents the greatest challenge: maintaining current dietary patterns requires a great shift in nutrient recovery from waste. However, shifting dietary habits toward higher domestic rice consumption (Scenario C-2) significantly mitigates land and fertilizer demand. Achieving these targets requires a holistic approach that integrates technological infrastructure with socio-political shifts in land use planning and consumer behavior. Full article

Differential Liberation Expansion (DLE) and viscosity tests are core elements of the Pressure–Volume–Temperature (PVT) laboratory suite used to characterize reservoir oils under depletion and to support compositional modeling and reservoir simulation. Nevertheless, both DLE and viscosity testing remain expensive and time-consuming due to specialized equipment, strict operating procedures, and the need for experienced laboratory personnel. Building on our prior work that introduced the proximity-informed Local Interpolation Model (LIM) framework for Constant Composition Expansion (CCE), this study demonstrates how the same end-to-end, neighborhood-based workflow is applied to DLE and viscosity test data. A target fluid is embedded in a compositional–thermodynamic descriptor space and paired with a small set of thermodynamically similar fluids drawn from a PVT data archive. Within this locality, LIM is used to infer DLE behavior by combining local interpolation for key scalar quantities (e.g., saturation-point and endpoint PVT values) with shape-preserving reconstruction of pressure-dependent curves. For viscosity, the same approach reconstructs the oil viscosity curve ${\mu }_o\left(p\right)$ across the undersaturated and saturated regions. Evaluation on a proprietary database of DLE and viscosity tests shows strong agreement across diverse fluids for both DLE and oil viscosity trends. For example, across Tier 1–3 fluids, the mean curve mean absolute percentage error (MAPE) is 1.01% for $B_o$, 0.51% for ${\rho }_o$, and 1.32% for the liberated-gas $Z$-factor, while the conditioned baseline viscosity workflow yields a mean diphasic-branch MAPE of 7.75%. This supports reducing reliance on new DLE and viscosity measurements while maintaining engineering-grade fidelity in reservoir engineering and simulation workflows. This approach has been fully automated through software so it can be set up and directly utilized by the field operators on their own databases to significantly reduce their fluid sampling and laboratory analysis costs. Moreover, the proposed (artificial intelligence) AI model does not use others’ data, respecting data privacy and data ownership. Full article

Climate change constitutes a significant environmental challenge, and carbon footprint labeling has emerged as a key policy instrument to promote low-carbon consumption. This study examines long-term trends in consumer purchase intention for carbon-footprint-labeled products in Korea, drawing on nationwide survey data collected over an 11-year period (2009–2019). The results demonstrate that environmental concern, perceived severity of climate change, understanding of the carbon footprint system, and exposure to low-carbon and green media are positively associated with purchase intention. Among these factors, perceived contribution to greenhouse gas reduction is identified as the most influential and consistent determinant over time. Importantly, the analysis focuses on purchase intention rather than actual purchasing behavior. Given the well-documented attitude–behavior gap in sustainable consumption, the findings should be interpreted as indicative of behavioral intention. By documenting long-term changes in consumer perceptions and intentions, this research provides insights into the impact of environmental information on consumer decision-making and offers policy recommendations to enhance the effectiveness of carbon labeling. Full article

In the digital era, social media has become a potent tool, shaping perceptions, opinions, and behaviors among young people. It has transformed young people’s experiences with fashion, trends, and consumer culture. This examining how attitudes toward social media influencers affect youth fashion interest through social comparison, addressing a gap in the cultural context of Pakistan. It was hypothesized that positive attitudes toward social media influencers would predict youth fashion interest trends through the mediator of social comparison. This research paper adopts a quantitative approach, using a survey to gather data from university students in Rawalpindi and Islamabad, Pakistan. The results indicated a significant relationship among the variables. Mediation analysis supported the mediating role of social comparison in the relationship between attitudes towards social media influencers and youth fashion interest. For the mean comparison by gender, no significant differences were found between men and women regarding the study variables. The study extended Bandura’s social cognitive theory past mere observation of a model by explaining the mediating role of social comparison. Moreover, the study updated Festinger’s social comparison theory for the era of social media. Full article

The SAE J2841 utility factor (UF) estimates the fraction of driving expected to occur in charge-depleting (CD) mode for plug-in hybrid electric vehicles. Emerging in-use data suggest that real-world electric usage is lower than assumed, motivating a reassessment of how charging behavior and related factors should be incorporated into the UF curve. Using trip-level data from approximately 1000 PHEVs observed over one year, we develop a charging model that captures both population-level heterogeneity in charging frequency and day-to-day characteristic temporal patterns in individual charging. The charging behavior modeling is applied to NHTS driving data to generate UF curves spanning 5 to 200 miles (8 to 322 km) of CD range. When key behavioral features are included, the resulting CD driving fractions align closely with industry-provided data. Sensitivity analysis indicates that the assumed share of habitual non-chargers is among the most influential parameters affecting the gap between the original UF and in-use data. Multiple modeling approaches were used to explore the problem and compare results, including machine learning, logistic regression, and parametric methods. Additional factors such as blended CD operation and temperature effects are discussed within a modular framework for refining J2841. These findings inform ongoing discussions on PHEV utility representation in analytical and regulatory contexts. Full article

The application of rheological modeling in polyolefin-based systems has gained increasing attention in the context of sustainable materials and circular economy strategies. In particular, the use of recycled polyolefins reinforced with lignocellulosic fillers presents significant opportunities, but also introduces challenges associated with structural heterogeneity, degradation, and variability in processing behavior. Despite rheology’s central role in linking structure, processing, and properties, its use as a predictive tool in recycled systems remains insufficiently systematized. This work presents a systematic review conducted according to PRISMA guidelines to analyze the use of rheological models in polyolefin-based systems, with particular emphasis on their applicability to recycled materials and composite formulations. We analyze 50 studies using a structured data extraction protocol. The results show that rheological modeling approaches can be organized into a hierarchical framework ranging from indirect flow parameters and generalized Newtonian fluid models to viscoelastic, structural, multiscale, and hybrid approaches. However, these approaches are not evenly distributed across system types. Advanced models are predominantly applied to compositionally controlled systems, whereas recycled and post-consumer polyolefins are mainly addressed using simplified models or experimental characterization. The analysis further indicates that rheology is primarily used for data fitting and process simulation, with limited application as a predictive tool for material formulation. Quantitative trends reported in the literature indicate that filler incorporation typically increases viscosity by approximately 20–200%, depending on filler content, dispersion quality, and interfacial interactions. However, variability in experimental conditions and material heterogeneity significantly limits cross-study comparability. From a mechanistic perspective, the main limitation lies not in the availability of rheological models but in their adaptability to heterogeneous systems characterized by variable composition, degradation, and limited experimental accessibility. This review identifies a gap between the development of rheological models and their application in recycled polyolefin systems. Future progress on eco-composite design will require further development of integrative approaches that balance physical insight, predictive capability, and experimental feasibility. In this context, rheology should be repositioned from a post-characterization technique to a central tool for the design and optimization of sustainable polymer composites. From an applied perspective, these findings support the use of rheological parameters as practical indicators for guiding formulation strategies and optimizing processing conditions in recycled polyolefin-based materials. Full article

Under the coordinated implementation of the “dual carbon” goals and digital rural development strategy, digital technology has become a critical support for solving key problems in agricultural carbon reduction and advancing the green and low-carbon transformation of agriculture. Based on panel data from 31 provincial-level regions in China from 2010 to 2023, this study uses the fixed-effect model, mediating the effect model and threshold effect model to systematically examine the impact and transmission mechanism of digital technology on agricultural carbon emission intensity. The results show that: (1) Digital technology markedly lowers agricultural carbon emission intensity, and this conclusion remains steady after endogeneity correction and robustness checks. (2) Digital technology reduces emissions through two core channels: enhancing environmental regulation to constrain high-carbon behaviors via precise monitoring, and improving agricultural socialized services to promote intensive production and lower the adoption threshold of low-carbon technologies. (3) The emission reduction effect of digital technology exhibits a threshold characteristic related to agricultural industrial agglomeration, with the marginal effect of emission reduction showing an increasing trend as the agglomeration level rises. (4) The carbon reduction effect of digital technology shows obvious heterogeneity across grain production functional zones. The inhibitory effect is significant in major grain-producing areas and grain production–consumption balance areas, but not significant in major grain-consuming areas. (5) The carbon reduction effect also presents heterogeneity under different topographic relief conditions. The effect is significant in low-relief areas but not significant in high-relief areas, because complex terrain restricts the construction of digital infrastructure and large-scale application of digital technologies, which further reflects the regulatory role of natural geographical conditions. Accordingly, this paper proposes to strengthen the empowering role of digital technology in the green transformation of agriculture, attach importance to regional coordination and differentiated policy design, and comprehensively improve the capacity of agricultural carbon emission reduction and sequestration. Therefore, it is imperative to strengthen the enabling role of digital technology in the green transformation of agriculture, attach importance to regional coordination and differentiated policy design, and comprehensively enhance the capacity of agriculture for carbon emission reduction, sequestration and sustainable development. Full article

In this study, we examined cross-cultural interest in sustainable brands in Saudi Arabia and the United Kingdom in 2015–2025 as a dynamic proxy of consumer behavior and public awareness through the Google Trends tool. Due to the increasing significance of sustainability marketing as a part of environmental, social, and governance (ESG) strategies, the research focuses on the evolution of sustainability discourse as influenced by cultural environment, language, and policy frameworks. Sustainability-related search terms in English and Arabic were gathered in Google Trends monthly and aggregated to eliminate short-term variability and were compared through nonparametric Wilcoxon rank-sum tests and time-stability tests. The findings demonstrate that there is more stable and higher public interest in issues that relate to sustainability in the UK, which is an indicator of a well-established ESG and regulatory climate. Contrarily, Saudi Arabia shows a significant upsurge in search transactions on sustainability-related topics that occurred after 2018, when the country started implementing reforms to Vision 2030 and launched more environmental programs. The results indicate the importance of policy context and language in the formation of sustainability awareness and show the usefulness of Google Trends as a useful cross-national sustainability and marketing research tool. Full article

The increasing awareness of health among consumers has made the development of functional cereal products a major trend in the food industry. This study investigated the effects of grape seed extract (GSE) on the quality parameters of medium-gluten wheat flour and fresh wet noodles, with the aim of developing functional noodle products. GSE was incorporated at concentrations of 0%, 0.2%, 0.4%, 0.6%, and 1% (w/w). Its influence on dough properties—including farinographic characteristics, extensibility, and pasting behavior—as well as on noodle quality attributes (antioxidant activity, tensile strength, color, microstructure, total phenolic content, and sensory profile) was evaluated. The results indicated that at 1% GSE addition, the farinographic properties, extensibility, and pasting characteristics of the dough were consistently enhanced. Correspondingly, the noodle microstructure exhibited a more compact and ordered arrangement. Furthermore, increasing the level of GSE fortification led to a significant rise in the total phenolic content and antioxidant capacity of the noodles (p < 0.05). This study can provide key technical support for developing novel fresh wet noodle products that possess both excellent quality and antioxidant functionality, thereby contributing to the functional enhancement of staple food products and meeting consumer demand for healthier dietary options. Full article

Background: Adolescent obesity and depressive symptoms have increased concurrently, often presenting as co-occurrence. However, evidence on the timing of physical activity (e.g., weekday vs. weekend) and adherence to planetary health diets remains limited. This study examined these associations among adolescents in Zhejiang Province from 2022 to 2024. Methods: A total of 261,495 adolescents aged 11–18 years were included. Physical activity (PA) and dietary behaviors were assessed through the China Common Disease and Risk Factor Surveillance among Students questionnaire (reliability: Cronbach’s α = 0.84, validity: RMSEA = 0.07). The plant-based Planetary Health Diet Index (PHDI-green) adherence was defined as consuming at least one daily serving of both vegetables and fruits. Depressive symptoms were measured using the Center for Epidemiologic Studies Depression (CES-D) scale, and co-occurrence was defined as the coexistence of obesity and depressive symptoms. Temporal trends were tested using χ² tests. Sex-stratified logistic regression, restricted cubic spline analyses, and population attributable fraction (PAF) analyses were applied. Results: From 2022 to 2024, obesity (p for trend = 0.013) and depressive symptoms (p for trend = 0.003) increased significantly, while co-occurrence remained stable (p for trend = 0.058). Boys had higher obesity and co-occurrence, whereas girls showed higher depressive symptoms (all p < 0.001). Higher weekly PA, greater weekend PA and PHDI-green adherence were associated with reduced odds of obesity in both sexes (all p < 0.001). Weekend PA showed stronger associations with depressive symptoms among girls, while PHDI-green showed stronger inverse associations in boys (p for sex difference < 0.001). PAF analyses suggested that low weekend PA accounted for substantial proportions of cases (girls: obesity 10.17%, depressive symptoms 31.30%, co-occurrence 35.64%). Joint adherence to adequate PA and PHDI-green conferred the lowest odds of co-occurrence (boys: OR = 0.40, 95% CI: 0.34–0.46; girls: OR = 0.33, 95% CI: 0.26–0.43). Conclusions: Adherence to the Planetary Health Diet may be particularly relevant for boys, whereas PA—especially weekend PA—may be more strongly associated with health outcomes among girls. These findings suggest the importance of sex-specific and time-targeted behavioral strategies for obesity, depressive symptoms, and their co-occurrence in adolescents. Full article