Search Results (9,782)

To address the insufficient accuracy of short-term load forecasting caused by the strong randomness of distributed energy output, variable electricity consumption patterns, and complex meteorological factors, this study proposes a load forecasting method that integrates K-means scene clustering and a Transformer–BiGRU–Attention (CTBA) hybrid deep learning architecture. Different from conventional Transformer–BiGRU hybrid forecasters that train a single global predictor across all operating conditions, the proposed CTBA framework first partitions daily load curves into representative scenes and then routes each sample to a scene-specific Transformer–BiGRU–Attention predictor, thereby reducing distributional heterogeneity before temporal modeling. First, the K-means algorithm is used to perform scene clustering on historical daily load curves, and the optimal number of clusters is selected according to the silhouette coefficient and downstream prediction performance. Subsequently, the CTBA model is trained separately for each clustering subset. The Transformer encoder captures the long-range global dependencies of load sequences through the self-attention mechanism, the BiGRU module extracts local bidirectional temporal fluctuation features, and the Attention mechanism further focuses on key time nodes such as morning and evening peaks while fusing multi-source data including historical load, day-ahead electricity price, and multi-dimensional meteorological factors. Experimental results based on the German ENTSO-E power dataset show that the coefficient of determination R² of the proposed model reaches 0.9893, with MAE, RMSE, and MAPE as low as 0.0141, 0.0187, and 3.92%, respectively, which are significantly improved compared to benchmark models such as SVR, LSTM, CNN, and TCN-BiGRU. Ablation experiments further demonstrate that removing the clustering, Transformer, BiGRU, or attention layer will degrade performance, thus verifying the effectiveness and superiority of the method in short-term load forecasting and providing an accurate solution for the short-term load forecasting of power systems. Full article

Engaging students in sustainability challenges is often easier in theory than in practice. This study examines first-year French undergraduates’ patterns of engagement with the TEDS module (Transition Ecologique pour un Développement Soutenable), a nationwide programme developed in France to promote ecological transition and sustainable development. Data were collected through an online questionnaire comprising 24 closed- and open-ended questions exploring students’ self-reported familiarity with, understanding of, concern about, and self-reported intentions to engage in sustainability-related actions, as well as perceived learning needs and background characteristics. Only 18 questions (143 items) were included in the present analysis, covering all dimensions except those related to the evaluation of the training programme. Results indicate that environmental concern is the factor most strongly associated with self-reported engagement intention, despite persistent gaps in conceptual understanding, particularly regarding the Anthropocene and alternative socio-economic models. Knowledge score and concern are structured hierarchically according to issue visibility, with climate change ranking highest. Engagement depends not only on concern but also on perceived opportunities for action, yet students struggle to identify concrete pathways. The absence of significant differences across gender and disciplines points to a strong generational convergence that reshapes the determinants of environmental engagement. Overall, the key challenge for sustainability education is linking systemic knowledge to concrete contexts of learning and everyday life. Full article

Background: Osteochondral lesions of the talus (OLT) remain a challenging condition due to the limited regenerative potential of articular cartilage. Conventional bone marrow stimulation (BMS) techniques often result in fibrocartilage formation with inferior biomechanical properties. This study aimed to evaluate the safety and preliminary clinical efficacy of an arthroscopically assisted, single-stage injection of a heparin-conjugated fibrin hydrogel (HCFH) for OLT treatment. Methods: Twelve patients with symptomatic OLT underwent arthroscopic debridement, microfracturing, and HCFH injection containing autologous mesenchymal stromal cells (MSCs) and growth factors. Safety was assessed through systematic monitoring of adverse events (graded according to Common Terminology Criteria for Adverse Events criteria), wound healing, and serial laboratory inflammatory markers (leukocytes, erythrocyte sedimentation rate, C-reactive protein) during early and late follow-up. Clinical outcomes were evaluated using the Visual Analog Scale (VAS) and American Orthopedic Foot and Ankle Society score (AOFAS) preoperatively and at 6 and 12 months. Morphological assessment was performed using magnetic resonance imaging (MRI) with the modified Magnetic Resonance Observation of Cartilage Repair Tissue (MOCART) scoring system, evaluated independently by two blinded musculoskeletal radiologists. Results: No serious adverse events (Grade III–IV) were observed during the 12-month follow-up. All adverse events were mild (Grade I) and self-limited. A transient postoperative elevation in inflammatory markers was observed, returning to clinically acceptable levels by day 14. Significant improvements were noted in pain (VAS decreased from 6.0 to 2.0) and ankle function (AOFAS increased from 70.0 to 90.6) (p < 0.001). MRI demonstrated progressive morphological improvement, with the MOCART score increasing from 34.16 ± 17.1 at 6 months to 75 ± 5.43 at 12 months (p < 0.001). This increase corresponded with imaging features consistent with tissue maturation over time. The favorable MOCART outcomes observed in this study may be explained by the regenerative properties of heparin-conjugated fibrin hydrogels; however, larger randomized controlled trials with longer follow-up are needed to confirm the durability of the regenerated tissue. Interobserver agreement was substantial to almost perfect for MOCART scoring (κ = 0.68–0.84), with perfect agreement observed for surface assessment, bony defect/overgrowth, and cysts. Conclusions: Within the limitations of this study, single-stage HCFH injection demonstrated an acceptable safety profile and favorable preliminary clinical and radiological outcomes at 12 months. These findings suggest potential regenerative capability; however, controlled studies with larger cohorts and longer follow-up are required to determine comparative efficacy and long-term durability. Full article

In this study, we examine whether personality profiles moderate a recently proposed environmental behaviour–well-being model. The model is grounded in Self-Determination Theory, which suggests that pro-environmental behaviour may contribute to subjective well-being through the satisfaction of basic psychological needs. A total of 403 adolescents from four Lithuanian schools participated in this study. Participants were selected using a convenience sampling method, and the average participant age was 14.89 years (56.6% female). Structural equation modelling demonstrated acceptable model fit (CFI = 0.988, TLI = 0.986, NFI = 0.929, RMSEA = 0.043 [0.022–0.058], SRMR = 0.113, χ² (353) = 416.92, p = 0.011) and indicated that personality profiles moderate several pathways within the environmental behaviour–well-being model. Additionally, the results showed that pro-environmental behaviour and connectedness to nature did not significantly predict subjective well-being across all personality profiles. The findings highlight the importance of considering personality differences when designing sustainability-related educational interventions aimed at promoting environmental citizenship and improving subjective well-being. Full article

Pre-Cenomanian Nubia sandstone is recognized one of the most prolific reservoirs in the Gulf of Suez, Egypt. Accurately determining its reservoir rock type (RRT) is crucial for reservoir characterization and modeling, especially when the reservoir is extremely heterogeneous. This study addresses the critical challenge of characterization in extremely heterogeneous reservoirs by introducing a novel integrated workflow that bridges the gap between traditional sedimentological geology, traditional x-y approaches, and advanced machine learning methods. To achieve this, this study utilizes sedimentological core description, routine core analysis, and conventional well log data from two wells (well A and well B) located in the southern Gulf of Suez, Egypt. The results demonstrate that the complete Nubia interval in the southern Gulf of Suez can be separated into seven distinct lithofacies (LF1–LF7). The first six lithofacies comprise various types of sandstone, while the seventh is composed of shale. The traditional techniques used to predict the RRTs show that the normalized reservoir quality index (NRQI) was the most effective method for predicting the Nubia rock types. The machine learning K–means clustering and self-organizing map (SOM) techniques utilizing raw log data and principal component analysis (PCA) can properly predict the Nubia reservoir rock types. The reservoir quality ranges from poor to very good; well A is dominated by moderate reservoir quality, while well B exhibits predominantly very good reservoir quality. This discernible difference in reservoir quality between the two wells is probably attributed to post-depositional diagenetic processes and variations in sandstone texture. Full article

Eating behavior and eating habits are shaped from the earliest stages of life through interactions among biological, familial, social, and environmental factors. The aim of this narrative review is to integrate evidence on the early-life determinants of eating behavior and their influence on dietary intake from infancy to adolescence. A narrative review was conducted with a structured search approach prioritized on longitudinal studies, intervention trials, and policy evaluations when available, and using cross-sectional evidence mainly to describe patterns and sociodemographic factors. Synthesizing the current evidence, our framework proposes that breastfeeding, responsive complementary feeding, and self-regulatory parenting are associated with higher responsiveness to internal hunger, satiety cues, and preference for nutrient-dense foods. Conversely, coercive practices, early exposure to highly palatable foods, and the influence of food marketing are linked to dominant hedonic responses and impulsive consumption patterns. Furthermore, family environments characterized by stress or food insecurity, together with high access to low-nutrient foods, may increase vulnerability to poor eating habits and emotional eating during adolescence. Overall, the evidence highlights the need for preventive interventions that integrate parenting support, school food education, digital marketing regulation policies, and the promotion of healthy food environments across multiple sectors. Understanding the biological, psychological, and social factors linking early determinants to dietary intake and eating behaviors across development is essential for promoting a balanced relationship with food and preventing chronic diseases from an early age. Full article

Listeria monocytogenes is a ubiquitous Gram-positive bacterium responsible for listeriosis, a foodborne zoonotic disease affecting humans and animals. Although infection in immunocompetent individuals is often asymptomatic or limited to mild self-limiting gastroenteritis, Listeria monocytogenes may cause severe invasive disease in vulnerable groups, including pregnant women, neonates, elderly individuals, and immunocompromised patients. Although the incidence of listeriosis is relatively low compared with many other foodborne pathogens, the high hospitalization and mortality rates associated with clinical cases make this bacterium a major concern for food safety and public health. The evolutionary success of L. monocytogenes reflects the interaction between a conserved core genome and a dynamic accessory genome shaped by horizontal gene transfer (HGT), ecological selection, and expansion of specific clones. Transient intestinal carriage in humans and animals, potentially influenced by gut microbiome composition, creates ecological interfaces where plasmids, transposons, prophages, and integrative conjugative elements contribute to the exchange of antimicrobial resistance determinants, virulence factors, and stress tolerance systems. Virulence diversification is further influenced by the differential distribution of pathogenicity islands such as LIPI-1, LIPI-3, and LIPI-4 across specific clonal lineages. These evolutionary processes occur across interconnected farm, food-production, environmental, and clinical ecosystems consistent with the One Health framework. Advances in whole-genome sequencing have clarified lineage-specific gene flow, expansion of specific clones, and the dynamics of the resistome and mobilome in L. monocytogenes populations. This narrative review aims to synthesize current knowledge on the mobile genetic elements and ecological interfaces that shape horizontal gene transfer in L. monocytogenes. Its novelty lies in integrating antimicrobial resistance, virulence-associated genomic islands, stress adaptation, and gut microbiome-mediated selection within a One Health and metapopulation framework. The main message of this review is that HGT should be interpreted as a context-dependent contributor to L. monocytogenes adaptation, acting together with clonal background, ecological selection, and mobile genetic elements. Full article

Stock index price series are composed of superimposed multi-frequency components, including long-term trends, cyclical fluctuations, and stochastic noise. Effectively decoupling these heterogeneous components and modeling them separately is key to improving forecasting accuracy. Existing methods under the “decomposition–prediction” paradigm mostly employ fixed-scale decomposition, and the forecasting models are not specifically adapted to the non-stationary and high-noise characteristics of financial data, resulting in limitations in adaptivity and local dynamic capture. This paper proposes a frequency-aware adaptive multi-scale decomposition Transformer hybrid model (FAMS-Transformer). At the decomposition level, the fast Fourier transform is used to dynamically identify dominant cycles, thereby adaptively decoupling trends and fluctuations, overcoming the limitations of fixed-scale decomposition. At the forecasting level, a lightweight depthwise separable convolution is embedded between the self-attention and feedforward network of the Transformer encoder, enhancing the model’s ability to capture local temporal dynamics and achieving collaborative modeling of global dependencies and local information. Comparative experiments with 15 baseline models including LSTM, Transformer, TimesNet, and FreTS on three representative Chinese market indices—Shanghai Composite Index, Shenzhen Component Index, and Small and Medium Enterprises 100 Index—across four prediction horizons from one step to 15 steps demonstrate that FAMS-Transformer achieves the best forecasting accuracy in all scenarios. The coefficient of determination for 15-step prediction remains stably between 0.730 and 0.928. Moreover, the model still performs well on the S & P 500 dataset. Ablation studies and significance tests further validate the effectiveness of each core module and the statistical significance of the performance improvements. Full article

Objectives/Background: Regular physical activity is a key health behavior associated with physical and mental well-being. However, sustaining physical activity remains challenging among adults, and the psychological mechanisms that support continued engagement require further clarification. Grounded in Self-Determination Theory, this study examined the roles of autonomous motivation and controlled regulation in health behavior engagement, focusing on the mediating role of physical activity self-regulation strategies. Methods: A cross-sectional study was conducted with 468 Korean adults. Autonomous motivation and controlled regulation were assessed using the Behavioral Regulation in Exercise Questionnaire-3, and physical activity self-regulation strategies were measured using the Physical Activity Self-Regulation Scale. Health behavior engagement was assessed using a single-item measure based on the stages of change for exercise. Structural equation modeling with bootstrapping was used to examine direct and indirect relationships among the study variables. Results: Both autonomous motivation (β = 0.649, p < 0.001) and controlled regulation (β = 0.153, p < 0.001) were positively associated positive with self-regulation strategies. Self-regulation strategies were positively associated with health behavior engagement (β = 0.336, p < 0.001). Autonomous motivation showed both a significant direct effect (β = 0.131, p = 0.018) and a significant indirect effects through self-regulation strategies (bias-corrected 95% confidence interval [CI] [0.206, 0.420]) on health behavior engagement, indicating partial mediation. In contrast, controlled regulation showed no significant direct effect (β = −0.062, p = 0.144) but had a significant indirect effect through self-regulation strategies (bias-corrected 95% CI [0.043, 0.131]). Conclusions: Autonomous motivation appears to be a stronger predictor of health behavior engagement than controlled regulation, both directly and indirectly through self-regulation strategies. These findings highlight the importance of motivational quality and suggest that self-regulation strategies are a key mechanism through which motivation is translated into physical activity engagement among adults. Interventions should therefore combine autonomy-supportive approaches alongside the development of practical self-regulatory skills to promote sustained physical activity. Full article

Purpose: Vasomotor, sexual, and musculoskeletal symptoms are common adverse effects of adjuvant endocrine therapy in breast cancer survivors. Social media use has not been investigated with altered symptom perception in patients receiving adjuvant endocrine therapy. This study aimed to investigate whether social media use or addiction independently predicts endocrine therapy-related symptom burden in breast cancer survivors. Methods: A cross-sectional survey study was conducted among 153 breast cancer survivors receiving adjuvant endocrine therapy. The Social Media Use Scale (SMUS) and Bergen Social Media Addiction Scale (BSMAS) were assessed using validated Turkish versions of each scale. Endocrine therapy-related toxicities (specifically hot flashes, vaginal dryness, loss of libido, and musculoskeletal pain severity) were evaluated using specific self-reported 5-point Likert scale items. Results: All of the patients were female and menopausal, either neutral or induced with ovarian function suppression. In the univariate analysis, the BSMAS score showed a weak positive correlation with vasomotor/sexual symptoms (r = 0.194; p = 0.017), but this association disappeared after adjustment for clinical variables. Younger age was associated with greater vasomotor/sexual symptoms in univariate testing. Neither the SMUS nor BSMAS independently predicted musculoskeletal symptom severity in univariate and multivariate models, while higher educational attainment remained the only independent predictor of musculoskeletal pain severity (OR = 1.96; 95% CI: 1.06–3.57; p = 0.031). Conclusions: This study is unique in investigating unstructured social media use and endocrine therapy-related physical symptoms. In this cohort, unstructured social media use was not associated with the endocrine therapy-related physical symptom burden. While these cross-sectional findings do not support social media behavior as a significant predictor, clinical assessments should continue to prioritize established determinants such as age and educational background. Full article

Patients with diabetes and/or peripheral artery disease (PAD) are at risk for lower limb amputation and a subsequently higher mortality risk. Peer support interventions have been shown to increase diabetes self-management and glycemic control. This scoping review aims to synthesize the current literature on peer support interventions in reducing lower limb amputations. A PubMed search was conducted in June of 2023, excluding publications prior to 2000, focusing on two themes: (1) peer support and (2) the patient population of interest (i.e., individuals with diabetic foot disease and/or PAD). Studies were included if they addressed the population of interest, involved a peer support intervention to improve lower extremity health, and had outcomes pertaining to the health of the lower extremities or programmatic metrics such as participant satisfaction or program adherence. Out of 1730 publications initially identified, six met the inclusion criteria. These six studies were categorized as group foot care education studies (n = 4) or group cognitive behavioral studies (n = 2). The group foot care education studies showed mixed results, which varied from no effect to significant improvements in foot care, self-management, and complications. There was a trend of improvement in self-management behaviors and physical activity in cognitive behavioral interventions. Despite showing promise in other settings, there have been limited investigations of peer support interventions to improve lower extremity outcomes and avert amputations in persons with diabetes and/or PAD. Further studies are required to conclusively determine the efficacy of peer support interventions to reduce lower extremity amputation rates. Full article

To reveal the nonlinear instability mechanism by which the three-degree-of-freedom rotor system of a magnetic-liquid double suspension bearing transforms from stable suspension to periodic vibration, a nonlinear dynamic model considering electromagnetic suspension force, hydrostatic supporting force, rotor unbalance force, and liquid film resistance is established. The equilibrium point of the system is linearized, and the Hopf bifurcation boundary is determined using the Routh–Hurwitz criterion. Numerical simulations are then carried out to investigate the effects of the initial current i₀, supply flow rate q₀, and different initial disturbances on the displacement time histories, phase trajectories, and spatial phase trajectories of the rotor. The results show that, under the given system parameters, the Hopf bifurcation boundary is 0.61 A for the initial current and 9.62 × 10⁻⁵ m³/s for the supply flow rate. Current variation mainly affects electromagnetic stiffness and nonlinear electromagnetic force, whereas flow rate variation primarily changes the hydrostatic load capacity and oil film damping characteristics. Under different initial disturbances, the system may exhibit amplitude attenuation, recovery to stable suspension, or finite amplitude periodic vibration. Experimental results show good agreement with numerical simulations in terms of frequency spectra, displacement time histories, and phase trajectories, thereby verifying the effectiveness of the proposed three-degree-of-freedom dynamic model and Hopf bifurcation analysis method. The results can provide theoretical guidance for parameter matching, stability evaluation, and self-excited vibration suppression of magnetic-liquid double suspension bearings. Full article

Background/aim: Physical inactivity remains widespread globally, with most adults not achieving recommended physical activity levels. Exercise motives and goals, central to Self-Determination Theory, strongly influence sustained participation. The Bernese Motive and Goal Inventory (BMZI) is a validated tool to assess exercise motivation; however, no Arabic version exists. This study aimed to translate, culturally adapt, and validate the BMZI for Arabic-speaking adults. Methods: A web-based cross-sectional study was conducted in Saudi Arabia between September and October 2025 among native Arabic-speaking adults via social media and community networks. The survey included sociodemographic data, the Arabic version of the Bernese Motive and Goal Inventory (Ar-BMZI), the Sport Motivation Scale (SMS), and the SF-12 Health Survey. Reliability was assessed through Cronbach’s α, McDonald’s ω, and ICC for test–retest consistency; construct validity via exploratory and confirmatory factor analysis; and convergent validity by correlating Ar-BMZI with the Arabic-SMS and Arabic-SF-12 physical component. Results: A total of 680 participants were included, with a mean age of 30.4 ± 12.9 years. Most were female (61.6%) and held a bachelor’s degree (73.5%). Nearly half (50.9%) reported a low monthly income. The Ar-BMZI demonstrated strong overall psychometric performance. Internal consistency was excellent (Cronbach’s α = 0.883; ω = 0.868), and test–retest reliability indicated high stability over time (ICC = 0.870, 95% CI = 0.786–0.933). Convergent validity was supported by a moderate correlation with the Arabic Sport Motivation Scale (r = 0.613, p < 0.001) and a weak correlation with the SF-12 physical health domain (r = 0.098, p = 0.011), which supported discriminant validity. Exploratory principal component analysis with Varimax rotation identified a five-factor structure explaining 69.2% of the total variance, and confirmatory factor analysis further supported this structure, demonstrating an excellent model fit. Conclusions: The Ar-BMZI demonstrates high reliability and good validity, supporting its use among Arabic-speaking adults. Full article

Background: Adolescent mental health is a global concern, with lifestyle factors such as diet and physical activity (PA) playing a crucial role. While the Mediterranean Diet adherence (MDA) is known for its neuroprotective benefits on mental health, the mechanisms by which they are related remain unclear. Therefore, the aim of this study was twofold: (1) to examine the associations between MDA, PA, and screen time (ST) with anxiety symptoms, depression, stress, and total psychological distress in Chilean adolescents; and (2) to determine whether PA mediates the relationship between MDA and anxiety symptoms. Methods: A cross-sectional study was conducted with 322 Chilean school-aged adolescents 158 males and 164 females (14.98 ± 1.96 years). Mental health outcomes (depression, anxiety, and stress) and lifestyle behaviors, including MDA, PA, and ST, were comprehensively assessed using validated self-reported questionnaires. Results: After adjusting for age and sex, multiple linear regression models showed that higher MDA was significantly and inversely associated with anxiety (b = −0.23, p = 0.044), stress (b = −0.25, p = 0.022), and total psychological distress (b = −0.72, p = 0.022). Conversely, ST was identified as a consistent risk factor, positively predicting higher levels of anxiety (b = 0.45, p = 0.008), stress (b = 0.42, p = 0.008), and total distress (b = 1.11, p = 0.014). Furthermore, PA was inversely linked to anxiety (b = −0.35, p = 0.013) and successfully mediated the relationship between MDA and anxiety symptoms (Indirect Effect = −0.047, 95% CI: −0.10 to −0.01). No significant mediation effects were observed for depression or stress. Conclusions: The present study identifies robust inverse associations between MDA and symptoms of anxiety, depression, and stress in Chilean adolescents. A key finding is the specific pattern of relationships observed: while higher MDA is directly linked to lower levels of depression and stress, its association with anxiety is shared with levels of PA. Despite these findings, the cross-sectional nature of the study limits the establishment of causal relationships, and further longitudinal research is needed to confirm these directional pathways. Full article

Background/Objectives: People with disabilities face a disproportionately higher disease burden alongside reduced healthcare accessibility, resulting in elevated unmet healthcare needs (UHN). Understanding the factors that drive UHN—and whether these factors differ by disability status—is critical for developing targeted public health interventions. Methods: A secondary cross-sectional analysis was conducted using linked national survey and administrative data—specifically the Korea National Health and Nutrition Examination Survey (KNHANES) cycles VI to VIII (2013–2021) linked with National Health Insurance Service (NHIS) administrative records—to examine determinants of healthcare access and utilization barriers by disability status. Independent variables were selected based on Andersen’s Behavioral Model of Health Services Use for vulnerable populations, encompassing predisposing factors, enabling factors, and need factors (including functional status indicators). Interaction terms between disability status and sex, and between disability status and household income level, were introduced to identify effect modification by disability status. Results: People with registered disabilities had significantly higher UHN compared to those without disabilities. The contributing factors to UHN differed between the two groups, with sex and household income showing statistically significant interaction effects with disability status, indicating that their associations with UHN vary depending on whether an individual has a registered disability. Conclusions: UHN in people with disabilities is shaped by a distinct set of determinants compared to the general population. The overall pattern of contributing factors differed between people with and without disabilities across multiple dimensions. These findings highlight the need for tailored healthcare policies that account for the unique vulnerabilities of people with disabilities, rather than applying uniform strategies across all population groups. Full article