Search Results (84,596)

Organic food consumption has attracted increasing attention as consumers become more concerned about health, sustainability, product quality, and the reliability of food information. However, positive attitudes toward organic food do not necessarily translate into regular purchasing behaviour. This study investigates the factors associated with organic food purchase intention and self-reported adoption among consumers in Türkiye. Data were collected through an online survey from 893 consumers and analysed using partial least squares structural equation modelling (PLS-SEM). The model considers health concerns, personal image motivation, sustainable consumption orientation, content and naturalness expectations, packaging informativeness, and social media engagement as potential determinants of purchase intention and adoption. The findings support H1: all six antecedents were positively associated with purchase intention, with health concerns showing the strongest association (β = 0.225), followed by sustainable consumption orientation (β = 0.199). H2 was also supported: purchase intention was the strongest predictor of self-reported organic food adoption (β = 0.578), while personal image motivation and social media engagement showed significant direct associations. The mediation analysis further indicated that health concerns, sustainability orientation, content and naturalness expectations, and packaging informativeness were associated with adoption through purchase intention. These findings indicate that organic food adoption in Türkiye is associated with health and sustainability motives, product information, symbolic motivations, and digital engagement. Full article

Background/Objectives: As birth weight is related to later obesity risk, its associations with maternal pre-pregnancy body mass index (BMI) and leptin values in serum during pregnancy are of interest for obesity prevention. This study aimed to describe the association of leptin levels in maternal circulation and cord blood as well as pre-pregnancy BMI (pBMI) with infant anthropometry at birth and until the age of four months. Methods: Data on maternal pBMI, at delivery and four months after birth, and on infant weight and length at delivery and at age four months were collected in an observational study in Bangkok, Thailand. In a subgroup of 38 mother–infant dyads, leptin was measured in maternal blood serum at delivery and infant age 4 months and in cord and infant serum at 4 months. Associations were tested with correlation and multiple linear regression analyses in this explorative study. Results: The maternal serum leptin was 32.4 ± 17.8 ng/mL at delivery and 11.1 ± 8.9 ng/mL at four months (p < 0.001 for difference) and correlated (r = 0.45). Cord serum leptin was significantly higher in female than male infants (17.5 ± 9.8 ng/mL vs. 7.7 ± 4.9 ng/mL, p < 0.05) and not related to infant leptin at age four months. There was no significant association between maternal and cord serum leptin levels. Birth weight was strongly associated with pBMI (standardized β = 0.77, p < 0.001) and inversely related to maternal delivery leptin levels (standardized β = −0.44, p = 0.008), while the association with cord serum leptin was not significant. Conclusions: Our findings indicate that pBMI is strongly related to birth weight, while higher maternal leptin concentrations were independently associated with lower birth weight after accounting for pBMI. Cord serum leptin did not significantly correlate with maternal leptin levels and only tended to be positively associated with birth weight. Full article

This study investigated the intricate relationships among motivational intensity, foreign language enjoyment, boredom, shyness, and second-language (L2) willingness to communicate (WTC) in Pakistani university students. Using a quantitative cross-sectional de-sign, data were collected from 1050 English language learners via validated surveys. Partial Least-Squares Structural Equation Modeling (PLS-SEM) was employed to test a moderated-mediation model examining how psychological variables influence L2 communication behavior. Results revealed that motivational intensity was significantly associated with L2 WTC via both a direct pathway (β = 0.251, p < 0.001) and a statistical indirect pathway involving foreign language enjoyment (β = 0.410 from motivational intensity to enjoyment and β = 0.339 from enjoyment to WTC; specific indirect effect, β = 0.139, both p < 0.001). Shyness demonstrated a complex dual moderating role: while it significantly constrained the enjoyment–WTC pathway (β = −0.140, p < 0.001) and showed a strong adverse direct effect on WTC (β = −0.232, p < 0.001), it also strengthened the direct motivational intensity–WTC relationship, consistent with (β = 0.110, p < 0.001). Contrary to previous research conducted primarily in East Asian contexts, boredom showed no significant effects as either a direct predictor or moderator in the Pakistani context. The model explained 34.2% of the variance in L2 WTC. These findings extend the theoretical understanding of psychological mechanisms in L2 communication by revealing culturally specific patterns in a South Asian context, suggesting that multilingual environments may produce different psychological dynamics. Pedagogical implications stress the need to increase motivation alongside an understanding of the complex nature of personality variables within a particular cultural setting. Full article

Zinc is an essential trace element for human and plant growth and development. Exploiting naturally Zn-rich soil resources represents an important pathway to develop green characteristic agriculture, improve the nutritional quality of agricultural products, and advance agricultural sustainability aligned with the United Nations Sustainable Development Goals (SDGs2, 3 and 15). To clarify the geochemical characteristics and bioavailability of soil zinc in cultivated lands of the mid-low hilly region in southwestern Henan, and to scientifically evaluate the exploitation potential of Zn-rich land resources, this study selected the farming area of Fangcheng County, Henan Province, as its research object. Based on 1:50,000 land-quality geochemical survey data, 1602 topsoil samples and 61 paired wheat-grain–root-zone soil samples were collected. Multiple statistical approaches, including descriptive statistics, Universal Kriging spatial interpolation, Pearson correlation analysis and segmented regression, were adopted to systematically investigate Zn concentrations, spatial-distribution patterns, element paragenesis relationships and wheat Zn-accumulation characteristics in cultivated soils. Furthermore, the resource potential of Zn-rich land was assessed according to the Specification for Delineation and Identification of Natural Zn-Rich Land (DD2025-04). The results showed the following: (1) The mean Zn concentration of topsoil was 72.3 mg/kg (N = 1602, after removing 3σ outliers), which was higher than the national soil background value (67 mg/kg). With a coefficient of variation of 23.0%, soil Zn exhibited moderate enrichment and relatively uniform distribution. Its spatial pattern was dominated by geomorphic types, showing a north-high–south-low trend. Significant Zn-enrichment advantages were found in hilly areas, yellow-cinnamon soils, and regions covered by alluvial–proluvial and residual-slope parent materials, whereas Zn concentrations were markedly low in strongly alkaline soils. (2) Soil Zn was significantly positively correlated with Cd (r = 0.62), Cu (r = 0.51), V (r = 0.54) and Fe₂O₃ (r = 0.57), and moderately positively correlated with Se (r = 0.41) and Mo (r = 0.43). These correlations indicate homologous soil-forming parent-material sources and Zn-adsorption–enrichment mechanisms mediated by Fe-Mn oxides. The paragenetic relationship between soil Zn and Cd implies that heavy-metal ecological risks should be considered simultaneously during Zn-rich-land exploitation to guarantee ecological sustainability of cultivated land. (3) The average Zn concentration in wheat grains was 28.48 mg/kg, and the mean bioconcentration factor (BCF) was 0.42 (N = 61, averaged from individual sample-pair ratios), demonstrating a moderate Zn-accumulation capacity of wheat. Only a moderate correlation existed between total soil Zn and wheat-grain Zn, suggesting that high total soil Zn concentrations do not necessarily produce high-Zn crops. (4) Soil pH regulated Zn bioavailability: BCF was positively correlated with pH for samples with pH < 6.5 (R² = 0.116, p = 0.013), while a non-significant negative trend was observed for the subgroup pH ≥ 6.5 (R² = 0.269, p = 0.153). Wheat presented relatively high Zn-accumulation potential under neutral-pH conditions. Nevertheless, the observational dataset cannot confirm pH = 6.5 as a strict optimum threshold, which needs further validation through field-controlled experiments. Either extremely acidic or alkaline conditions may reduce available Zn supply via Zn leaching loss or hydroxide precipitation. (5) In accordance with DD2025-04, Zn-rich soils accounted for 21.85% of the study area, and Zn-enriched wheat grains occupied 21.31%, indicating abundant reserves of Zn-rich land resources. These findings can provide geochemical support for the scientific utilization of Zn-rich cultivated land, industrial layout of Zn-enriched wheat, and precise cultivated-land quality management in the hilly areas of southwestern Henan, promoting sustainable utilization of soil resources and nutrition-sensitive agricultural development. Full article

The Bandon Bay blue swimming crab supply chain in Surat Thani Province, Thailand, comprises multiple actor levels and operational activities whose locations do not necessarily correspond to actor labels. This study analyzes supply-chain route structures and functional activity allocation in the chain documented during 2018–2019 as a historical, multi-source descriptive case study. Data were collected from 400 fisher households, 17 collectors or buying stations, two processing plants, and downstream actors through questionnaires, interviews, field observations, product-flow tracing, small-group meetings, and secondary data. The analysis identified 17 routes and compared them across four structural configurations: direct-market, collector-led, processor-linked, and extended market-linkage configurations. Five activity groups were examined: aggregation and product flow, sorting and pre-delivery handling, transportation and delivery coordination, product transformation, and market linkage. The findings show that actor position and functional scope do not necessarily correspond on a one-to-one basis. Collectors performed a broad midstream role involving aggregation, handling, delivery coordination, market linkage, and, in some cases, product transformation. Reported constraints were associated with aggregation, handling, data systems, product transformation, and labor. The study provides a diagnostic route–activity framework for identifying sustainability-relevant assessment points, traceability-readiness needs, monitoring items, and intervention-readiness locations in multi-actor seafood supply chains, rather than measuring sustainability performance directly. Full article

The rapid growth of social media has intensified the spread of hate speech targeting individuals based on race, gender, religion, and sexual orientation, creating significant technical, social, and ethical challenges. To address this, we propose a comprehensive English–Norwegian framework that unifies multi-class, multi-label, and multi-task learning for hate speech detection while embedding fairness, transparency, and accountability. The framework comprises six phases, including ethical system design, English–Norwegian data collection, bias analysis and mitigation, explainable AI, and stakeholder validation. A 14K-instance English–Norwegian dataset was constructed from public social media posts and enriched with identity-specific attributes (religion, race, gender, and sexual orientation) using human-in-the-loop and model-assisted annotation. The modeling approach applies multi-label binary fine-tuning to detect potentially hateful, offensive, aggressive, and neutral content, alongside multi-task learning for mutually exclusive demographic attributes. To promote ethical AI, identity-related prediction sensitivity is addressed through synonym-based augmentation, identity-conditioned label-contrast augmentation, and balanced loss re-weighting. Transparency is ensured using LIME to provide token-level explanations of model decisions. On the combined held-out evaluation partition, NorBERT-small achieved a macro F1-score of 0.92 and multi-label subset accuracy of 0.94 for toxicity classification. Language-stratified analysis further yielded macro F1-scores of 0.92 for English-only, 0.89 for Norwegian-only, and 0.87 for English–Norwegian code-switched text, providing a more detailed assessment of performance across the different language conditions, and high aggregate F1-scores for social-attribute extraction; however, these aggregate results should be interpreted cautiously because several social-attribute classes are sparsely represented. Compared with the baseline model, the mitigation stage reduces prediction sensitivity to many of the evaluated identity substitutions, although residual disparities remain for some identity pairs. The Machine Learning (ML) and Deep Learning (DL) models are included as conventional reference baselines. Because the evaluated model families employ different architectures and task-specific training procedures, the cross-family results are interpreted descriptively rather than as evidence of the intrinsic superiority of any particular model family. The reported findings are specific to the evaluated corpus; cross-platform, cross-domain, and external-dataset generalization were not evaluated and are therefore not claimed. Full article

Tick-borne diseases are emerging worldwide due to the expanding distribution of tick vectors and represent an increasing public health concern. This study investigated the occurrence of major tick-borne pathogens in ticks collected from wild animals in Valle d’Aosta Region (Northwestern Italy) between 2017 and 2022. Tick pools were screened for Anaplasma spp., Borrelia burgdorferi s.l., Coxiella burnetii, Rickettsia spp., and Tick-Borne Encephalitis virus (TBEV). Most collected ticks were morphologically identified as Ixodes ricinus. Overall, 15.2% of the 158 analyzed pools tested positive for at least one pathogen. Rickettsia spp. was the most frequently detected pathogen (10.7%), with multiple species identified, including R. helvetica, R. monacensis, R. slovaca, and R. raoultii. Anaplasma phagocytophilum was detected in ticks collected from wild ungulates, whereas Borrelia burgdorferi s.l. was only occasionally identified. No samples tested positive for TBEV or C. burnetii. Rickettsia spp. positivity was higher in ticks collected from ungulates and in I. ricinus, although these differences were not statistically significant. These findings provide new insights into tick ecology in Alpine ecosystems, highlighting the circulation of potentially zoonotic pathogens and the altitudinal presence of ticks in the Alps up to 1800–2300 m a.s.l. The study contributes valuable epidemiological data and supports the need for continued surveillance within a One Health framework. Full article

Background: Lifestyle modification is central to type 2 diabetes mellitus (T2DM) management, but adherence is difficult to assess in routine care. We developed a pragmatic Lifestyle Compliance Index (LCI) from routinely collected behavioral variables and examined its cross-sectional associations with cardio-renal-metabolic measures. Objectives: To describe the LCI, compare outcomes across adherence categories, evaluate adjusted associations, and quantify incremental discrimination for prevalent metabolic and renal abnormalities. Methods: Adults with T2DM attending a specialized outpatient diabetes clinic in Romania were assessed using a standardized clinical questionnaire and routine laboratory data. The LCI combined seven binary behaviors and graded physical activity (0–2 points; theoretical range 0–9). Group comparisons, unadjusted bivariate and adjusted multivariable regressions, false discovery rate correction, and stratified five-fold cross-validated logistic models were used. Results: Among 232 participants, 231 had a complete LCI; low, moderate, and high adherence included 84 (36.4%), 94 (40.7%), and 53 (22.9%) participants, respectively. Higher LCI scores were associated with lower adiposity, HbA1c, TyG index, triglycerides, creatinine, and SCORE2-Diabetes risk and with higher eGFR. In models adjusted for age, sex, and diabetes duration, each LCI point was associated with lower odds of obesity (aOR 0.749), elevated TyG index (0.757), albuminuria (0.716), reduced eGFR (0.802), and HbA1c ≥ 7% (0.833). Adding LCI improved cross-validated discrimination most for albuminuria (AUC 0.482 to 0.642), obesity (0.489 to 0.619), and elevated TyG index (0.524 to 0.646). The baseline albuminuria AUC was below chance, and the extended AUC remained modest. Conclusions: In this cross-sectional sample, higher self-reported lifestyle adherence was associated with a more favorable cardio-renal-metabolic profile. The LCI should be considered exploratory until validated against objective measures and tested in larger prospective populations. Full article

Demand for nature-based recreation has increased the need for recreational-service planning in National Forest Parks (NFPs). Existing studies evaluate recreational services, but translating findings into actionable planning remains challenging. This study developed a vLLM-assisted framework linking indicator prioritization, image-based diagnosis, optimization simulation, and model-based reassessment. Questionnaire data comprised 238 responses from eight NFPs in Hangzhou, with 23 predictors measured predominantly at the park level. SHAP analysis ranked the recreational-service dimensions by predictive importance: facility (25.6%), activity (21.6%), tourist use experience (19.7%), information (17.5%), and accessibility (15.6%). Their weights guided image-based assessment of 73 NFPs across the Yangtze River Delta. Of 353,608 tourist-generated images collected, 96,876 passed screening. Human-reference evaluation showed correlations between model and human dimension scores of 0.815–0.898. Image diagnosis highlighted visible problems in signage, resting and public-service facilities, environmental interpretation, activity-space organization, and path legibility. Optimization simulation increased the mean model-assessed composite score of 365 selected low-scoring scenes from 6.26 to 7.32 (16.93%), with higher park-grouped means in 71 of 73 NFPs. The framework provides a scalable pathway for translating satisfaction-informed priorities into scene-level recreational-service diagnosis and visual planning support. Full article

This study investigates the impact mechanism of perceived crowding on consumer impulsive buying in the context of internet-famous supermarkets. Based on environmental psychology, this study proposes a moderated mediation model. Survey data from 565 tourists, collected between December 2024 and January 2026, were analyzed using structural equation modeling with SPSS 27.0, AMOS 28.0, and PROCESS macro 4.1. The results reveal that perceived social and spatial crowding exert divergent effects on impulsive buying and positive and negative emotions. Positive emotions act as a significant mediator between spatial crowding and impulsive buying, whereas social crowding drives impulsive buying primarily through direct social contagion rather than emotional pathways. Furthermore, while brand trust was hypothesized to broadly moderate this process, results reveal a limited and counterintuitive moderating role. It significantly interacts only with perceived social crowding, unexpectedly dampening its positive effects on both impulsive buying and positive emotions, whereas all other moderation and moderated mediation hypotheses remain unsupported. This research clarifies the distinct emotional mechanisms of perceived crowding and the specific suppressing role of brand trust, enriching environmental psychology and cognitive appraisal theory while providing practical guidance for the sustainable development of internet-famous retail. Full article

Modern network infrastructures are under attack from increasingly sophisticated attacks that static, rule-based defenses cannot adequately mitigate. We introduce a multilayer anomaly detection and mitigation framework for Software-Defined Networking (SDN) environments consisting of four integrated subsystems: (i) a Micro-segmentation Integrated Management and Defense System (MIMDS), (ii) an Adaptive CNN-LSTM-Attention Deep Packet Inspection (MCLA-DPI) module, (iii) a Hybrid Adaptive Cyberattack Prediction (KBGM) framework, and (iv) an AI-driven log analysis pipeline. Detection, prediction and containment operate in parallel (as opposed to conventional approaches) and correlate results through a common risk-scoring mechanism to coordinate policy enforcement via OpenFlow and P4-compatible data planes. The experimental evaluation shows promising performance. MIMDS achieves 94.3%. detection accuracy with full traffic isolation in 10.1 s. MCLA-DPI achieves 98.9% classification accuracy with 14 ms inference latency, outperforming baseline models SVM and LSTM on encrypted traffic. KBGM achieves 98.4% detection accuracy with 7.2 ms mean response time on the CICIDS2017 dataset. All modules are trained in federated learning to preserve data locality with continuous improvements of the global model. The results collectively demonstrate quantifiable improvements over single-paradigm approaches in detection fidelity, response latency, resource efficiency, and privacy compliance. An ablation study isolates the contribution of integration itself. Removing the coordination layer while retaining all four detectors reduces accuracy from 0.892 to 0.634 and raises the false-positive rate from 0.031 to 0.436, while peak rule installation rises from 22.3 to 98.4 rules per second and oscillation events increase by two orders of magnitude; the integrated framework also exceeds its strongest individual subsystem, which reaches 0.831 accuracy at a false-positive rate of 0.117. These figures are obtained from the released reference implementation over a synthetic campaign and are reported separately from the component measurements. Full article

Many existing deep-learning models for brain-tumor diagnosis report very high accuracy, yet they often suffer from overfitting, limited generalizability, and poor robustness, which reduces their clinical reliability. First, a large and diverse dataset was assembled from multiple publicly available sources to reduce data bias. Next, a series of regularization and calibration techniques were applied, including label smoothing, mixup augmentation ($\alpha =0.4$), exponential moving average (EMA) of model weights to prevent overfitting, stabilize training, and temperature scaling to calibrate predicted probabilities. Since brain-tumor diagnosis directly affects critical clinical decisions, both model accuracy and reliability of its predictions are essential. For that, six diverse, powerful pretrained backbones (ConvNeXt, EfficientNetV2, DenseNet201, Swin, ViT, and DINOv3) were used as frozen feature extractors under pure transfer learning. On top of these frozen features, lightweight classification heads were trained using concatenation, attention, and gated fusion. Then, the predicted-class probabilities from the selected heads were combined and passed to a logistic-regression meta-learner to produce the final prediction, with the aim of improving accuracy and reliability. This architecture is computationally efficient because only lightweight classifiers and a logistic meta-learner are trained, while the heavy backbones remain frozen. The best-performing variant on TEST2, attn_fp_ens , was further evaluated using synchronized 10-fold cross-validation on the TRAIN set. The best-performing TEST variant, the gated-fusion ensemble with fingerprint features (gated_fp_ens), achieved 99.33% test accuracy and 99.28% macro-F1. Under domain shift on the external hospital dataset (TEST2), the attention-fusion ensemble with fingerprint features (attn_fp_ens) showed the strongest performance among the evaluated variants, achieving 95.16% accuracy and 94.11% macro-F1. The TEST2 dataset was collected from a local hospital for external evaluation. Full article

This study examines entrepreneurs’ awareness and preventive activities regarding the environment and employees as key elements of the Quality 5.0 concept. Quantitative research was conducted among 380 manufacturing companies in Greater Poland that had not implemented or certified a quality management system. Data were collected using CATI interviews using an original questionnaire assessing the importance and implementation of 24 preventive management factors, with a detailed analysis of 10 factors. The findings identify maintaining good relations with the environment (K2), careful supplier selection and continuous evaluation (K3), improving employee qualifications and skills (K7), and ensuring occupational safety and ergonomics (K8) as the most important preventive management factors. The combined IPA and paired analyses identify K7—improving employee qualifications and skills—as the clearest improvement priority: it was the only factor in the “concentrate here” quadrant, had the largest importance–implementation gap (0.34), and the largest rank-biserial effect (r_rb = 0.639). K2—maintaining good relations with the environment—and K8—ensuring occupational safety and ergonomics—combined high importance with high implementation and should therefore be maintained, while K5—selection of employees based on their competencies—also warrants attention due to its gap of 0.28. Paired Wilcoxon tests showed statistically significant implementation shortfalls for all ten factors after Holm correction, indicating that the gap between perceived importance and implementation is systematic. Participatory management (K6) received the lowest importance and implementation ratings, although its large paired effect suggests that its relatively low IPA priority should not be interpreted as evidence of low relevance. Associations with company size and years in operation were generally weak and factor-specific. The results contribute to understanding preventive management as a basis for sustainable, human-centered, and proactive Quality 5.0 practices. They suggest that managerial priorities should consider both the relative IPA position and the magnitude of importance–implementation gaps, with particular attention to employee competence development and participatory management. The results emphasize the role of preventive management practices in supporting the Quality 5.0 concept and provide practical guidance for organizations seeking to strengthen sustainable, employee-oriented, and proactive management approaches. Full article

Whether a well-organized scene facilitates visual search may depend on when in the search process the benefit is expressed. We tested this possibility in a virtual-office task in which 48 adults searched for targets varying in salience. Salience was manipulated between participants, whereas layout (grid, clustered, or random) and clutter (low, medium, or high) varied within participants. Mouse responses and eye position (120 Hz) were collected across 1296 target-present trials. Accuracy was broadly comparable across conditions, but reaction time (RT), time to first fixation (TTFF), fixation duration in the Target AOI, and fixation duration in the Clutter AOI each showed a three-way interaction. The transition data were particularly informative under high clutter. For grid layouts, clutter-to-target transitions occurred on 47.3% of transitions, clutter-to-clutter self-transitions on 20.5%, and the target was first reached after 0.89 intervening transitions on average. The respective values for random layouts were 11.2%, 64.2%, and 6.39. Thus, the benefit of the grid was not consistently present at initial target capture. It became most evident in the way gaze was redirected among regions as the search unfolded. Spatial regularity therefore seems to limit later search costs by making attentional reallocation and gaze-path correction more efficient. Full article

Background/Objectives: Hospital malnutrition is a prevalent and clinically significant issue associated with prolonged hospital stays, increased complications, and mortality. Although nurses play a key role in monitoring nutritional status and delivering nutrition care, many lack confidence and do not perceive nutrition care as part of their primary responsibilities. This study assessed nurses’ self-perceived nutrition care competence, identified associated factors, and examined their objectively scored nutrition knowledge alongside self-reported nutrition care competence. Methods: A cross-sectional study was conducted among unit nurses providing direct patient care at a tertiary hospital in Korea. Data were collected using a structured questionnaire assessing participant characteristics, nutrition education–related characteristics, nutrition knowledge, and self-perceived nutrition care competence. Data were analyzed using descriptive statistics, group comparisons, correlation analyses, and multiple linear regression analyses. Results: Among 206 recruited nurses, data from 185 were analyzed. The mean self-perceived nutrition care competence score was 72.24 ± 12.48 (possible range: 24–120). Greater clinical experience, pediatric unit practice, previous nutrition-related education, and higher nutrition knowledge were independently associated with self-perceive nutrition care competence. The mean nutrition knowledge score was 13.81 ± 2.69 (69.1% correct). Notably, although nurses recognized the importance of nutrition care and expressed willingness to receive education, participation in nutrition-related training was limited. Conclusions: Self-perceived nutrition care competence was associated with both individual and practice environment factors. Despite the high perceived need for and willingness to participate in nutrition education, previous participation in nutrition-related education was limited. These findings support consideration of educational and organizational strategies to facilitate nutrition care in nursing practice. Full article