Search Results (73)

This paper evaluates neural-network approaches for lithium-ion battery state-of-charge (SoC) estimation under a unified pipeline, fixed data partitions, and identical preprocessing. We study FNNs trained with Levenberg–Marquardt (LM), Bayesian Regularization (BR), and Scaled Conjugate Gradient (SCG) across three hidden sizes (10, 20, 30) and three topologies: Fitting, Nonlinear Input–Output (Nonlinear I/O), and time-series NAR/NARX. Models are assessed using test MSE and RMSE, correlation (R), generalization gap, convergence indicators (final gradient, damping factor), wall time per epoch, and a relative compute-cost index. On the Fitting task, BR-Fitting-FNN with 20 neurons provides the best accuracy-efficiency balance, while LM-Fitting-FNN with 30 neurons reaches slightly lower error at a higher cost. For Nonlinear I/O, BR-Nonlinear I/O-FNN with 30 neurons achieves the lowest test MSE with clear evidence of effective weight shrinkage; LM-Nonlinear I/O-FNN with 20 neurons is a close alternative. In time-series settings, LM-NAR-FNN with 10 neurons attains the lowest test error and fastest epochs but shows a very negative gap that suggests test-split favorability; BR-NAR-FNN with 30 neurons is more costly yet consistently strong. For NARX, LM-NARX-FNN with 20 neurons yields the best test accuracy and robust convergence. Overall, BR delivers the most reliable accuracy–robustness trade-off as networks widen, LM often achieves the best raw accuracy with careful split validation, and SCG offers the lowest training cost when resources are limited. These results provide practical guidance for selecting SoC estimators to match accuracy targets, computing budgets, and deployment constraints in battery management systems. Full article

Background: Traditional dietary assessment methods face limitations including reporting bias and scalability challenges. Large language models (LLMs) offer potential for automated food classification, yet their validation in morphologically complex, non-English languages like Polish remains limited. Methods: We analyzed 1992 food items from a Polish long-term care facility (LTCF) cohort using three advanced LLMs (Claude Opus 4.5, Gemini 3 pro, and GPT-5.1-chat-latest) with two prompting strategies: a structured double-step prompt integrating NOVA and World Health Organization (WHO) criteria, and a simplified single-step prompt. Classifications were compared against consensus judgments from two human experts. Results: All LLMs showed high agreement with human experts (90.3–94.2%), but there were statistically significant differences in all pairwise comparisons (χ² = 1174.5–1897.1; p < 0.001). The structured prompt produced very high Recall for UNHEALTHY items at the cost of lower Specificity, whereas the simplified prompt achieved higher overall Accuracy and a more balanced Recall–Specificity profile, indicating a trade-off between strict guideline adherence and alignment with general human judgment. Conclusions: Advanced LLMs demonstrate near-expert accuracy in Polish-language dietary classification, enhancing workflow efficiency by shifting effort toward validation. Expert oversight remains essential, and multi-model consensus alongside language-specific validation can improve AI reliability in nutrition assessment. Full article

This article explores the impacts of various components of an international program on the professional development of both international and local student teachers. The primary data source comprised the participants’ narratives across four cohort years (2019, 2021, 2022, and 2024, n = 50), supplemented by focus group interviews (n = 3) with eleven students from the 2021 cohort. Data were analyzed deductively, guided by the overarching purpose of teacher education and Biesta’s three functions of education. Our findings reveal that the international program significantly enhances participants’ qualification as future teachers, notably in professional competence, pedagogical knowledge and skills, intercultural competence, and subjectification regarding the ability to make independent professional decisions for their future careers. Additionally, the inclusion of both international and local students provides mutual benefits, albeit to varying extents and in different ways. The results suggest that thoughtfully designed program components and the integration of international and local students in higher education yield substantial benefits for all participating student teachers. Full article

The accurate short-term forecasting (PV) of power is crucial for grid stability control, energy trading optimization, and renewable energy integration in smart grids. However, PV generation is extremely variable and non-linear due to environmental fluctuations, which challenge the conventional forecasting models. This study proposes a hybrid deep learning architecture, Wavelet Transform–Transformer–Temporal Convolutional Network–Efficient Channel Attention Network–Gated Recurrent Unit (WT–Transformer–TCN–ECANet–GRU), to capture the overall temporal complexity of PV data through integrating signal decomposition, global attention, local convolutional features, and temporal memory. The model begins by employing the Wavelet Transform (WT) to decompose the raw PV time series into multi-frequency components, thereby enhancing feature extraction and denoising. Long-term temporal dependencies are captured in a Transformer encoder, and a Temporal Convolutional Network (TCN) detects local features. Features are then adaptively recalibrated by an Efficient Channel Attention (ECANet) module and passed to a Gated Recurrent Unit (GRU) for sequence modeling. Multiscale learning, attention-driven robust filtering, and efficient encoding of temporality are enabled with the modular pipeline. We validate the model on a real-world, high-resolution dataset of a Moroccan university building comprising 95,885 five-min PV generation records. The model yielded the lowest error metrics among benchmark architectures with an MAE of 209.36, RMSE of 616.53, and an R² of 0.96884, outperforming LSTM, GRU, CNN-LSTM, and other hybrid deep learning models. These results suggest improved predictive accuracy and potential applicability for real-time grid operation integration, supporting applications such as energy dispatching, reserve management, and short-term load balancing. Full article

This paper presents a hybrid fast charging strategy for static wireless power transfer (WPT) systems that synergistically combines pulsed current and multi-stage current (MCM) modes to enable rapid yet battery-health-conscious electric vehicle (EV) charging, thereby promoting sustainable transportation. The proposed approach employs a memetic algorithm (MA) to dynamically optimize the charging parameters, achieving an optimal balance between speed and battery longevity while maintaining 90.78% system efficiency at the SAE J2954-standard 85 kHz operating frequency. A neural-network-based state of charge (SOC) estimator provides accurate real-time monitoring, complemented by MA-tuned PI control for enhanced resonance stability and adaptive pulsed current–MCM profiles for the optimal energy transfer. Simulations and experimental validation demonstrate faster charging compared to that using the conventional constant current–constant voltage (CC-CV) methods while effectively preserving the battery’s state of health (SOH)—a critical advantage that reduces the environmental impact of frequent battery replacements and minimizes the carbon footprint associated with raw material extraction and battery manufacturing. By addressing both the technical challenges of high-power WPT systems and the ecological imperative of battery preservation, this research bridges the gap between fast charging requirements and sustainable EV adoption, offering a practical solution that aligns with global decarbonization goals through optimized resource utilization and an extended battery service life. Full article

Background: Unhealthy food consumption in long-term care facilities (LTCFs) contributes to poor health outcomes among residents. This study aimed to assess its prevalence, identify demographic and physical risk factors, and propose targeted interventions. Methods: A mixed-methods study (2017–2021) analyzed data from 1000 Polish LTCF residents (aged 35–105 years). Anthropometric measurements, bioimpedance analyses, dietary assessments, and physical activity records were collected. Food items were classified as “healthy” or “unhealthy” using an AI-based Large Language Model (LLM), applying WHO guidelines and the NOVA classification system. Logistic regression and chi-square tests assessed associations between unhealthy food consumption and marital status, education level, mobility aid use, and portion control. Results: Unhealthy food consumption prevalence was 15.6%. Married residents had significantly higher rates than unmarried individuals (22.6% vs. 14.3%, p < 0.01). Lower educational attainment correlated with increased risk (partial primary education: 34.7% vs. tertiary education: 8.1%). Mobility aid users exhibited elevated consumption (cane: 34.6%; walker: 22.6%). Poor portion control showed the strongest association (OR = 3.2, 95% CI: 1.8–5.7). Conclusions: Marital status, educational disparities, mobility limitations, and portion control were key modifiable risk factors. Findings suggest the need for targeted nutrition programs, caregiver education, and policy reforms to improve dietary literacy and meal portioning. Future research should validate AI-based food classification methods, assess long-term intervention outcomes, and expand studies to diverse LTCF settings. These findings align with Poland’s National Health Programme and provide actionable insights for global LTCF populations. Full article

Groundwater systems are important for maintaining ecological balance and ensuring water supplies. However, under the combined pressures of shifting climate patterns and human activities, their responses to extreme events have become increasingly complex. As China’s largest freshwater lake, Poyang Lake supports critical water resources, ecological health, and climate adaptation efforts. Yet, the relationship between groundwater storage (GWS) and extreme hydrological events in this region remains insufficiently studied, hindering effective water management. This study investigates the GWS response to extreme events by downscaling Gravity Recovery and Climate Experiment (GRACE) data and validating it with five years of observed daily groundwater levels. Using GRACE, the Global Land Data Assimilation System (GLDAS), and ERA5 data, a convolutional neural network (CNN)–attention mechanism (A)–long short-term memory (LSTM) model was selected to downscale with high resolution (0.1° × 0.1°) and estimate recovery times for GWS to return to baseline. Our analysis revealed seasonal GWS fluctuations that are in phase with precipitation, evapotranspiration, and groundwater runoff. Recovery durations for extreme flood (2020) and drought (2022) events ranged from 0.8 to 3.1 months and 0.2 to 4.8 months, respectively. A strong correlation was observed between groundwater and meteorological droughts, while the correlation with agricultural drought was significantly weaker. These results indicate that precipitation and groundwater runoff are more sensitive to extreme events than evapotranspiration in influencing GWS changes. These findings highlight the significant sensitivity of precipitation and runoff to GWS, despite improved management efforts. Full article

Background: Multiple endocrine neoplasia type 2A (MEN 2A) is a rare hereditary cancer syndrome caused by pathogenic variants in the rearranged during transfection (RET) gene and is characterized by medullary thyroid carcinoma (MTC), pheochromocytoma (PHEO), primary hyperparathyroidism (PHPT), cutaneous lichen amyloidosis (CLA), and Hirschsprung’s disease. Phenotypic data on the RET C611Y variant remain sparse. Consequently, we aimed to establish a clinical risk profile. Methods: We conducted a nationwide study of all cases (n = 128) born after 1 January 1930 and recognized as carrying the RET C611Y variant in Denmark before 1 April 2021. Results: The median follow-up after birth was 47 years (range, 3–92). Age-related penetrance at age 70 years for MTC was 98% (CI, 91–100), for PHEO 24% (CI, 16–37), and for PHPT 10% (CI, 5–20). None had CLA or Hirschsprung’s disease. The age-related progression of MTC was significant (p < 0.001). The mean age at T0N0M0 was 16 years (CI, 12–20), at T1-4N0M0 38 years (CI, 34–42), at TxN1M0 45 years (CI, 38–53) and at TxNxM1 49 years (CI, 36–61). At the last follow-up, 56% of thyroidectomized cases (n = 103) were biochemically cured. Overall survival at 70 years was 74% (CI, 59–84). Conclusions: RET C611Y is associated with a very high penetrance of MTC and a low penetrance of PHEO and PHPT. CLA and Hirschsprung’s disease almost never occur. MTC seems moderately aggressive, but large variability can be seen. Overall survival may be comparable to that of the general population. Full article

Public spaces are vital for urban living, contributing to the environmental, social, and economic aspects of city life. Hatirjheel Lakefront, a newly developed recreational area in Dhaka, offers significant potential for enhancing accessibility and connectivity in a rapidly urbanizing metropolis. This study aims to evaluate global and local integration of access routes and propose strategies to improve pedestrian and vehicular connectivity using Space Syntax methodology and DepthmapX V10 software. The key findings indicate that while Hatirjheel demonstrates strong global integration, regional integration remains moderate, with certain access roads being underutilized due to poor connectivity. Recommendations include enhancing integration through connecting dead-end roads, improving pedestrian pathways, and constructing foot-over bridges to mitigate vehicular traffic barriers. This study contributes to urban planning by providing actionable insights to optimize accessibility in public spaces, supporting recreational and economic activities. The findings are critical for creating a more integrated urban fabric in Dhaka, ensuring sustainable urban growth. This research provides actionable strategies for urban planners to optimize the use of public spaces, reinforcing the role of Hatirjheel as a vital component of Dhaka’s urban network. Full article

We sequenced and analyzed the complete mitogenome of a Norwegian isolate of the octocoral Alcyonium digitatum using the Ion Torrent sequencing technology. The 18,790 bp circular mitochondrial genome was found to harbor the same set of 17 genes, which encode 14 protein subunits, two structural ribosomal RNAs and one tRNA, as reported in other octocorals. In addition, we detected a new tRNA^Pro-like gene sequence nested within the MutS protein coding region. This putative tRNA gene feature appears to be conserved among the octocorals but has not been reported previously. The A. digitatum mitogenome was also shown to harbor an optional gene (ORFA) that encodes a putative protein of 191 amino acids with unknown function. A mitogenome-based phylogenetic analysis, presented as a maximum likelihood tree, showed that A. digitatum clustered with high statistical confidence with two other Alcyonium species endemic to the Mediterranean Sea and the Southeast Pacific Ocean. Full article

This paper aims to identify the export competitiveness of agri-food products at the level of the European Union Member States, considering indicators/elements belonging to technical innovation (technical complexity) as well as qualitative elements. The main research problem is to examine the differences in the technical complexity of agri-food exports (EXPY) between EU Member States. Through detailed analysis of product categories and Member States’ performance, we have identified significant differences in the technical complexity of exports. Products such as dairy, meat, cereal and vegetable preparations were associated with high technical complexity, while fruit, tobacco and oils were classified in the low technical complexity category. We also identified Member States with exports characterised by high technical complexity, including Cyprus, Ireland and Luxembourg, and those with low technical complexity, such as Slovakia, Latvia and Croatia. These findings suggest the influence of various factors, such as economic specialisation, natural resources and R&D investment on shaping the agri-food export landscape in the European Union. In-depth analysis of these issues provides significant insights for understanding the economic and technical dynamics in the European agri-food sector. Full article

It has long been stated that children have the rights to protection from, e.g., abuse and to the provision of age-appropriate leisure, play, and recreational activities along with participation in all matters that concerns them. Yet, the full range of children’s rights to and in sport has not yet been explored in detail. To do so, it is relevant to turn to the Scandinavian countries, which are praised for promoting children’s rights and well-being, with organized sport forming part of the daily lives of many children and youths. In this paper, we examine the organizational policies in Scandinavian sport in order to develop foundational knowledge about how the range of children’s rights to and in sport may be supported. Comparing key policy documents of the major sports confederations in Denmark, Norway, and Sweden, these analyses identify great variety in the following: 1. when and how children’s rights to and in sport have been made explicit in the three countries; 2. whether the emphasis is on protection and/or provision of sport to children and youths or their participation in shaping sporting activities; 3. the degree to and ways in which such rights are regulated. In sum, our findings reflect a disparity between organizational policies in the three countries, with a more liberal and individualistic approach to public policy in the Danish context, providing some explanation of the only recent development in and scattered enaction of regulations to support children’s rights to and in sports. Furthermore, we identify that political attention has mainly been drawn to the protection and provision of sports to children and youths, while their participation in shaping sport is a shared challenge for sport confederations in the Scandinavian countries and beyond. Full article

Sustainable development is a core concept in regional development. Sustainability is characterized by supporting the building of resilient infrastructure and promoting the sustainable industry. In this context, sustainable transport is particularly important as it represents an opportunity for regional development. This research aims to quantify the impact of investments through structural instruments, specifically EU funds, on promoting a sustainable transport system and eliminating barriers from large-scale transport networks. This study focuses on the impact of these investments on regional economic development in Romania. The analysis used data from all eight development regions of the Romanian economy between 2014 and 2020. Panel data regression models, including the generalized difference method of moments (Dif-GMM) and the system GMM method (Sys GMM), were employed. This study confirms the idea that European structural and investment funds (ESIFs) play a positive role in promoting sustainable transport for regional economic development. Additionally, the quality of regional governance is identified as a key factor in economic development. This study, therefore, reveals a convergence effect between regions. Regions with a lower initial GDP per capita develop quicker compared to regions with a higher initial GDP per capita, indicating a “catch-up” effect. From a policy perspective, these issues can guide decision making and resource allocation. Full article

Non-governmental organizations (national and international) are important actors in addressing health issues in Kenya. Sandflea/jigger infections (tungiasis) are a public health challenge that severely affect children, older adults, and other vulnerable people in poor communities worldwide. In Kenya, NGOs have been involved in sandflea eradication for more than twenty years. Without treatment, the flea may cause debilitating infections and sores, resulting in difficulties with walking and grasping, as well as social harassment. This paper aims to shed light on health workers’ and volunteers’ perceptions of the government and civil society’s role in fighting jigger infections. Data were collected through a qualitative case study design, with a three-month fieldwork including participation in mobile jigger removal programs, 18 semi-structured in-depth interviews, informal talks, and observations, in five villages in Bungoma County. The thematic analysis of the data resulted in three recurring themes: (1) the NGO-driven jigger program as a (fragile) resource for local communities, (2) the need for more consistent collaboration between NGOs and public health services, and (3) the local perceptions of the governments’ responsibilities in combatting the plague. The findings imply that the 10-year-old national policy guidelines on the prevention and control of jigger infestations need to be updated; this includes the coordination of the public and private actors’ roles, the incorporation of lessons learned, and the need for a multisectoral One Health approach to combat the jigger menace in the country. Full article

The severity of disease resulting from classical swine fever virus (CSFV) infection is determined by several factors, including virus strain and host factors. The different outcomes of experimental studies in pigs with the same strain of CSFV emphasize the need to elucidate the influence of individual factors within experimental protocols. In this study, we investigated the outcome of disease after oral and intranasal inoculation with a moderately virulent CSFV strain in young pigs. To compare the two routes of inoculation, various infection parameters were examined during a period of two weeks. While all intranasally inoculated pigs (n = 5) were directly infected, this was only the case for two out of five pigs after oral inoculation. In addition, the intranasally inoculated pigs developed a more pronounced clinical disease and pathological lesions, as well as markedly more change in hematological and immunological parameters than the orally inoculated pigs. The wide variation among the orally inoculated pigs implied that statistical evaluation was markedly impaired, leaving this route of application less suitable for comparative studies on classical swine fever. Furthermore, our study provides additional details about the immunomodulatory effects of CSFV on the kinetics of CRP, TNF-α, and leukocyte sub-populations in pigs after infection with the CSFV strain Paderborn. Full article