Search Results (2,078)

Background: The COVID-19 pandemic significantly disrupted various aspects of daily life, including hygiene routines, dietary habits, and access to dental care. This study aimed to evaluate the impact of the pandemic on the oral health-related and dietary behaviors and dietary pattern of patients from the West Pomeranian region of Poland. Methods: A cross-sectional survey was conducted among 100 healthy adult participants from the West Pomeranian region, including patients from the Pomeranian Medical University and private dental practices. A self-administered questionnaire consisting of 43 items was used to assess changes in hygiene, dietary behaviors, and the frequency of dental visits during the pandemic. Results: The majority of respondents were under 30 years of age, with women representing 56% of the sample. Most participants resided in large urban areas with populations exceeding 300,000. During the pandemic, 41% of participants maintained regular dental visits, while 37% reported experiencing dental problems; all those who sought care received appropriate treatment. Nearly half of the respondents had undergone quarantine due to SARS-CoV-2 exposure, and 38% expressed fear of infection. The results revealed a notable decline in preventive dental care during the pandemic: only 41% of participants reported maintaining regular dental check-ups. Additionally, 34% reported increased consumption of snacks, while 25% indicated more frequent alcohol intake. 22% of respondents experienced involuntary teeth clenching during the day, and 13% reported teeth grinding, These findings reflect a negative shift in health behaviors during the COVID-19 period. Conclusions: The pandemic had a substantial adverse effect on oral health behaviors, dietary choices, and the use of dental services. Nevertheless, participants demonstrated awareness of these changes and, following the pandemic, expressed an increased understanding of the importance of regular dental visits. It is necessary to implement preventive measures that increase awareness of the health consequences (such as dental caries and periodontal diseases) in order to reduce the neglect of routine dental check-ups. Full article

This study extends our previous investigation into whether multimodal large language models (MLLMs) can reason about physical reasoning, using a game environment as the testbed. Stability served as a foundational scenario to probe model understanding of physical reasoning. We evaluated twelve models, combining those from the earlier study with six additional open-weight models, across three tasks designed to capture different aspects of reasoning. Human participants were included as a reference point, consistently achieving the highest accuracy, underscoring the gap between model and human performance. Among MLLMs, the GPT series continued to perform strongly, with GPT-4o showing reliable results in image-based tasks, while the Qwen2.5-VL series reached the highest overall scores in this extended study and in some cases surpassed commercial counterparts. Simpler binary tasks yielded balanced performance across modalities, suggesting that models can capture certain basic aspects of reasoning, whereas more complex multiple-choice tasks led to sharp declines in accuracy. Structured inputs such as XML improved results in the prediction task, where Qwen2.5-VL outperformed GPT variants in our earlier work. These findings demonstrate progress in scaling and modality design for physical reasoning, while reaffirming that human participants remain superior across all tasks. Full article

Background: Local flaps are a cornerstone of reconstructive plastic surgery for oncological skin defects, ensuring functional recovery and aesthetic integration. Their selection, however, varies with surgeon experience. Generative artificial intelligence has emerged as a potential decision-support tool, although its clinical role remains uncertain. Methods: We evaluated three generative AI platforms (ChatGPT-5 by OpenAI, Grok by xAI, and Gemini by Google DeepMind) in their free-access versions available in September 2025. Ten preoperative photographs of suspected cutaneous neoplastic lesions from diverse facial and limb sites were submitted to each platform in a two-step task: concise description of site, size, and tissue involvement, followed by the single most suitable local flap for reconstruction. Outputs were compared with the unanimous consensus of experienced plastic surgeons. Results: Performance differed across models. ChatGPT-5 consistently described lesion size accurately and achieved complete concordance with surgeons in flap selection. Grok showed intermediate performance, tending to recognise tissue planes better than lesion size and proposing flaps that were often acceptable but not always the preferred choice. Gemini estimated size well, yet was inconsistent for anatomical site, tissue involvement, and flap recommendation. When partially correct answers were considered acceptable, differences narrowed but the overall ranking remained unchanged. Conclusion: Generative AI can support reconstructive reasoning from clinical images with variable reliability. In this series, ChatGPT-5 was the most dependable for local flap planning, suggesting a potential role in education and preliminary decision-making. Larger studies using standardised image acquisition and explicit uncertainty reporting are needed to confirm clinical applicability and safety. Full article

Diet is a key factor modulating the trade-off between fecundity and longevity, a cornerstone of life-history theory. While laboratory studies have demonstrated that high-protein-to-carbohydrate (P:C) ratio diets increase reproductive output at the cost of lifespan, it remains unclear how this trade-off operates in species exposed to natural dietary variability and prey choice. We tested whether diet-mediated trade-offs between fecundity and longevity are modulated by prey-insect type in the endangered tiger beetle, Cicindela anchoralis, a species with a short adult lifespan. Tiger beetles were offered a choice between a high-P:C diet (cricket) and low-P:C diet (ant). Tiger beetles consuming the high-P:C diet exhibited increased fecundity and reduced longevity, while those feeding on the low-P:C diet showed the opposite pattern. Despite these consequences, both sexes showed a consistent preference for the high-P:C diet, suggesting that beetles prioritize reproductive output over lifespan. These results suggest that prey-insect selection might be an adaptive way to boost reproductive success within a limited adult lifespan, which may raise tiger beetles’ intrinsic rate of natural increase. Our findings highlight the ecological relevance of diet-driven life-history trade-offs and offer practical guidance for mass propagation strategies to support endangered tiger beetle recovery. Full article

Oviposition attractants can enhance both the surveillance and control of container-breeding Aedes mosquitoes. Although green tea has been reported to attract Ae. aegypti, the specific bioactive botanical compounds responsible remain unidentified. We evaluated teas across fermentation stages (non-fermented, fully fermented, and post-fermented) at 5 g/L for gravid Ae. albopictus using dual-choice assays. The most attractive tea (Liu-pao) was further tested across concentrations (0.5–5 g/L) and infusion ages (1–28 days). Autoclaved vs. non-autoclaved infusions assessed microbial contributions, while headspace volatiles were analyzed via HS-SPME-GC-MS. Individual compounds (cedrol and linalool oxide) were bioassayed. Only Liu-pao tea consistently attracted Ae. albopictus (OAI ≥ 0.3), peaking at 5 g/L after 7–14 days (OAIs 0.73/0.67). A 0.5 g/L infusion aged 21–28 days also attracted Ae. aegypti (OAIs 0.89/0.63). Autoclaving did not reduce attraction, confirming volatile compounds, not live microbe-mediated effects. Cedrol (1 mg/L) elicited moderate attraction (OAI 0.29) in Ae. albopictus, while linalool oxide was inactive. Post-fermented Liu-pao tea acts as a potent botanical attractant for Aedes mosquitoes. Cedrol contributes partially, but whole tea infusions outperform single compounds. These findings support developing multi-volatile “attract-and-kill” strategies targeting gravid mosquitoes. Full article

Accurate hippocampal segmentation in 3D MRI is essential for neurodegenerative disease research and diagnosis. Preprocessing pipelines can strongly influence segmentation accuracy, yet their impact across datasets and in transfer learning scenarios remains underexplored. This study systematically compares a No Preprocessing (NP) pipeline and a Full Preprocessing (FP) pipeline for hippocampal segmentation on the EADC-ADNI HarP clinical dataset and the multi-site MSD dataset using a 3D U-Net with residual connections and dropout regularization. Evaluations employed standard overlap metrics, Hausdorff Distance (HD), and Wilcoxon signed-rank tests, complemented by qualitative analysis. Results show that NP consistently outperformed FP in Dice, Jaccard, and F1 metrics on HarP (e.g., Dice 0.8876 vs. 0.8753, p < 0.05), while FP achieved superior HD, indicating better boundary precision. Similar trends emerged in transfer learning from MSD to HarP, with NP improving overlap measures and FP maintaining lower HD. To test whether the findings generalize across architectures, experiments on Harp Dataset were also repeated with a 3D V-Net backbone, which reproduced the same trend. Comparative analysis with recent studies confirmed the competitiveness of the proposed approach despite lower input resolution and reduced model complexity. These findings highlight that preprocessing choice should be tailored to dataset characteristics and the target evaluation metric. The results provide practical guidance for selecting segmentation workflows in clinical and multi-center neuroimaging applications. Full article

When a technology provider (entrant) enters an emerging end market, he may outsource critical components from a competing conventional manufacturer (incumbent) or insource critical components. Under the outsourcing strategy, brand reputation spills over from the incumbent to the entrant—a phenomenon termed brand spillover. This paper investigates the sourcing strategy (insourcing or outsourcing) and contract choice (wholesale price contract or revenue share contract) in markets subject to brand spillover. We develop a game theoretic model consisting of one entrant with a new technology and one incumbent who sells the traditional product in the end market and the critical component to the entrant. We find that the entrant adopts the insourcing strategy only if his optimal quantity, including original market power and brand spillover, is intermediate. Otherwise, the outsourcing strategy with wholesale price contract is selected when his optimal quantity is low, while revenue-sharing contracts dominate at high quantity. Interestingly, when brand spillover intensity exceeds a threshold, both parties benefit from a higher level of brand spillover under the wholesale price contract. Full article

Alginate-hydroxyapatite (AL) scaffolds modified with fibronectin (FN) or bioactive glass (BGMS10) have recently been characterized for their physicochemical properties and proposed as promising candidates for bone regeneration. Here, we present their first systematic biological evaluation, focusing on adhesion, proliferation, osteogenic differentiation, and in vivo host response. We compared FN-, BG-, and unmodified AL scaffolds using an immortalized mesenchymal stromal cell line (M-SOD) and primary human bone marrow-derived (BM-MSCs) and adipose-derived stromal cells (ASCs). FN scaffolds enhanced initial adhesion across all cell types and supported proliferation in M-SODs, but primary BM-MSCs and ASCs showed minimal expansion, regardless of scaffold type. BG scaffolds promoted expression of late-stage osteogenic markers in BM-MSCs, consistent with their ion release profile, but had limited impact on ASCs. In vivo subcutaneous implantation of acellular scaffolds in nude mice revealed robust host cell infiltration and extracellular matrix deposition across all scaffold types, confirming biocompatibility and integration. However, vascularization remained limited and did not differ substantially between formulations. Together, these findings highlight a critical discrepancy between immortalized and primary stromal cell responses to scaffold cues, underscoring the choice of cell source when evaluating the biocompatibility of a novel scaffold. At the same time, the effective in vivo integration observed across scaffold types emphasizes the importance of host tissue responses for translational evaluation of functional biomaterials. Full article

Managing vehicle speed is crucial for reducing crash risks and crash severity. South Korea’s ‘Safety Speed 5030’ policy introduced lower urban speed limits to enhance road safety, but speed limit reductions alone may not be sufficient to change driver behavior. This paper investigates how spatial and environmental factors beyond speed limits affect drivers’ speed choice. Using point-level speed data from Jeju Island’s C-ITS dataset combined with GIS information, spatial econometric techniques were employed to capture spatial dependencies in speeding degree. Results show that a spatial lag model (SLM) outperforms ordinary least squares (OLS) and spatial error models (SEMs), providing higher explanatory power and more consistent parameter estimates. Key factors influencing drivers’ speed choice include road geometry (e.g., curvature, number of lanes), node-level features (e.g., intersections, property change points), and the presence of enforcement measures. The findings suggest that the reduction in speed limits alone may not guarantee a corresponding decrease in vehicle speed. This underlines that sustainable traffic safety requires not only regulation but also careful consideration of spatial and environmental contexts. Full article

Background: Respiratory syncytial virus (RSV) is a major cause of infant respiratory illness, leading to significant hospitalizations. Two preventive strategies exist: maternal vaccination and a long-acting monoclonal antibody for neonates. In The Netherlands, neonatal immunization is planned to start from autumn 2025 onward, contingent on acceptance by parents and healthcare professionals. Maternal vaccination is already available at own costs. Understanding acceptance, perceptions, and barriers is critical for effective implementation. This study explores these factors to inform strategies for optimal uptake. Methods: This mixed-method study involved semi-structured online interviews with 21 (expectant) mothers (EMs) and 32 healthcare professionals (HCPs) involved in maternal and neonatal care (e.g., pediatricians, youth doctors/nurses, obstetricians, midwives, and general practitioners) and a quantitative descriptive analysis of factors influencing EM choices. Interviews were transcribed and thematically analyzed. Results: Both EMs and HCPs showed strong support for RSV immunization, with a preference for maternal vaccination or a combined approach. Concerns about neonatal injections during the sensitive postpartum period and unfamiliarity with newborn injections (e.g., vitamin K) influenced preferences. EMs noted hesitation about additional pregnancy/postpartum vaccinations, emphasizing the importance of well-timed interventions. HCPs highlighted logistical challenges, such as defining responsibilities, navigating National Immunization Program (NIP) changes, and ensuring readiness. All interviewed individuals value the option to choose between strategies, necessitating informed decision-making and respect for preferences. EMs make their final decision together with their partner, supported by expert information and their personal environment. Conclusions: Support for RSV immunization is high, with maternal vaccination preferred, though neonatal immunization is accepted if appropriately timed. Providing clear personalized and consistent information, heightened public awareness of RSV’s impact, respecting individual choices, and offering options are key to maximizing uptake. Full article

Purpose: Luggage X-rays suffer from low contrast, material overlap, and noise; dual-energy imaging reduces ambiguity but creates colour biases that impair segmentation. This study aimed to (1) employ connotative fusion by embedding realistic detonator patches into real X-rays to simulate threats and enhance unattended detection without requiring ground-truth labels; (2) thoroughly evaluate fusion techniques in terms of balancing image quality, information content, contrast, and the preservation of meaningful features. Methods: A total of 1000 X-ray luggage images and 150 detonator images were used for fusion experiments based on deep learning, transform-based, and feature-driven methods. The proposed approach does not need ground truth supervision. Deep learning fusion techniques, including VGG, FusionNet, and AttentionFuse, enable the dynamic selection and combination of features from multiple input images. The transform-based fusion methods convert input images into different domains using mathematical transforms to enhance fine structures. The Nonsubsampled Contourlet Transform (NSCT), Curvelet Transform, and Laplacian Pyramid (LP) are employed. Feature-driven image fusion methods combine meaningful representations for easier interpretation. Singular Value Decomposition (SVD), Principal Component Analysis (PCA), Random Forest (RF), and Local Binary Pattern (LBP) are used to capture and compare texture details across source images. Entropy (EN), Standard Deviation (SD), and Average Gradient (AG) assess factors such as spatial resolution, contrast preservation, and information retention and are used to evaluate the performance of the analysed methods. Results: The results highlight the strengths and limitations of the evaluated techniques, demonstrating their effectiveness in producing sharpened fused X-ray images with clearly emphasized targets and enhanced structural details. Conclusions: The Laplacian Pyramid fusion method emerges as the most versatile choice for applications demanding a balanced trade-off. This is evidenced by its overall multi-criteria balance, supported by a composite (geometric mean) score on normalised metrics. It consistently achieves high performance across all evaluated metrics, making it reliable for detecting concealed threats under diverse imaging conditions. Full article

In the context of China’s increasingly competitive agricultural product branding, authenticity has become a pivotal mechanism for shaping consumer trust and willingness to pay. This study takes Perceived Brand Authenticity (PBA) as its focal construct and builds a chained mediation framework incorporating experiential quality (EQ) and consumer trust. Employing a dual-evidence strategy that combines structural discovery and causal validation, the study integrates Jaccard similarity clustering and PLS-SEM to examine both behavioral patterns and psychological mechanisms. Drawing on 636 valid survey responses from across China, the results reveal clear segmentation in channel choice, certification concern, and premium acceptance by gender, age, income, and education. Younger and highly educated consumers rely more on e-commerce and digital traceability, while middle-aged, older, and higher-income groups emphasize geographical indications and organic certification. The empirical analysis confirms that PBA has a significant positive effect on EQ and consumer trust, and that the chained mediation pathway “PBA → EQ → Trust → Purchase Intention” robustly captures the transmission mechanism of authenticity. The findings demonstrate that verifiable and consistent authenticity signals not only shape cross-group consumption structures but also strengthen trust and repurchase intentions through enhanced experiential quality. The core contribution of this study lies in advancing an evidence-based framework for sustainable agricultural branding. Theoretically, it reconceptualizes authenticity as a measurable governance mechanism rather than a rhetorical construct. Methodologically, it introduces a dual-evidence approach integrating Jaccard clustering and PLS-SEM to bridge structural and causal analyses. Practically, it proposes two governance tools—“evidence density” and “experiential variance”—which translate authenticity into actionable levers for precision marketing, trust management, and policy regulation. Together, these insights offer a replicable model for authenticity governance and consumer trust building in sustainable agri-food systems. Full article

Hydrologists need to predict extreme hydrological and meteorological events for design purposes, whose magnitude and probability are estimated using a probability distribution function (PDF). The choice of an appropriate PDF is crucial in describing the behavior of the phenomenon and the predictions can differ significantly depending on the PDF. So, the success of the probability distribution function in representing the data of extreme value series of natural events such as hydrology and climatology is of great importance. Depending on whether the series consists of maximum or minimum values, the theoretical probability density function must be appropriately fit to the right or left tail of the extreme data, which contains the most critical information. This study includes a combined evaluation of the performance of four different tests for selecting the appropriate probability distribution of maximum rainfall in Türkiye: Kolmogorov–Smirnov (KS) test, Anderson–Darling (AD) test, Probability Plot Correlation Coefficient (PPCC) test, and L-Moments Z^DIST test. Within the scope of the study, maximum rainfall series of seven rainfall durations from 15 to 1440 min, at rain gauge stations in 81 provinces of Türkiye, were examined. Goodness of fit was performed based on ranking using a combination of four different numerical tests (KS, AD, PPCC, Z^DIST). The probabilistic character of maximum rainfall was evaluated using a large dataset consisting of 567 time series with record lengths ranging from 45 to 80 years. The goodness of fit of distributions was examined from three different perspectives. The first is an examination considering rainfall durations, the second is a province-based examination, and the third is a general country-based assessment. In all three different perspectives, the Wakeby distribution was determined as the best fit candidate to represent the maximum rainfall in Türkiye. Full article

Urban models support sustainable, resilient, and equitable planning, but their validity hinges on underlying spatial data. This study examines the epistemological and technical consequences of relying on two dominant yet divergent platforms—OpenStreetMap (OSM) and Google Maps—for extracting proximity-based amenities within the 15-min city framework. Across four European contexts—Versilia, Gothenburg, Nice, and Vienna—we compare (i) data completeness and spatial coverage; (ii) semantic categories; and (iii) the effects of data heterogeneity on accessibility modelling. Findings show that OSM, while semantically consistent and openly accessible, systematically underrepresents peripheral amenities, introducing bias towards urban cores in accessibility metrics. Conversely, Google Maps provides broader coverage but is constrained by dependencies on extraction methods, opaque data structures, and ambiguous classification schemes, which hinder reproducibility, reduce interpretability, and limit its analytical robustness. These divergences yield distinct accessibility landscapes and competing readings of functionality and spatial equity. We argue that data source choice and protocol design are epistemological decisions and advocate transparent, hybrid strategies with cross-platform semantic harmonisation to strengthen robustness, equity, and policy relevance. Full article

The increasing implementation of drift-reduction regulations in agriculture has driven the widespread adoption of drift-reducing spray nozzles. However, concerns remain about their impact on the biological efficacy of foliar-applied herbicides, particularly at early weed growth stages. This study evaluated the bio-efficiency of various drift-reducing flat-fan nozzles across three weed species (Chenopodium album, Solanum nigrum, and Echinochloa crus-galli), two growth stages, and six herbicides differing in mode of action and formulation properties. Dose–response bioassays were conducted using eight nozzle–pressure combinations under controlled greenhouse conditions. Spray characteristics, including droplet size distribution, coverage, contact angle, and surface tension, were quantified to elucidate interactions affecting herbicide efficacy. The results showed that nozzle effects were more pronounced for high-surface-tension formulations and poorly wettable weed targets. Several coarser droplet drift-reducing nozzles (e.g., ID3, APTJ) showed inferior performance in controlling small C. album and S. nigrum targets with bentazon and erectophile E. crus-galli targets with cycloxydim. At the same time, nozzle choice was less critical for tembotrione and nicosulfuron spray solutions, which have low surface tension. Across weed species, growth stages, and herbicides, nozzles producing finer, slower droplets demonstrated superior and more consistent performance compared to those producing larger, faster droplets. These findings offer science-based guidance for selecting nozzle types that balance drift mitigation with effective weed control under current and future regulatory constraints. Full article