Search Results (152,340)

Background: Peer-assisted learning (PAL) is used in medical education. Its impact in basic medical sciences remains unexplored, namely considering the perspectives of all the populations involved: students, undergraduate teaching assistants (UTAs), and faculty members. We evaluated the educational impact of a PAL programme in Histology and Embryology in a medical course at the Faculty of Medicine of the University of Porto (FMUP). Methods: A cross-sectional convergent mixed-methods study was conducted in the Histology and Embryology course. Tailored online questionnaires comprising Likert-type items and open-ended questions were replied to by students attending theoretical–practical classes with UTAs, the UTAs, and the professors. Internal consistency was assessed using Cronbach’s alpha. Students’ theoretical–practical examination scores were compared between classes with and without UTAs using the Mann–Whitney U test, and effect size (r) was calculated to estimate the magnitude of differences observed. Results: Students (n = 190) reported highly positive perceptions regarding the creation of a more approachable learning environment, clarification of doubts, and identification of histological structures and strongly recommended the extension of UTAs to other courses of the medical school. UTAs (n = 17) described gains in disciplinary understanding, broader perspectives on the medical curriculum, communication and public-speaking skills, teamwork, leadership, self-confidence, and interest in academic careers. Professors (n = 6) valued PAL for improving individual support, facilitating time management, and contributing to UTA training, while highlighting the need for structured pedagogical preparation. Students attending classes with UTAs achieved significantly higher theoretical–practical examination scores (p = 0.04; effect size r = 0.12). Conclusions: PAL was perceived as highly beneficial by all groups involved in the project, enhancing the learning environment, supporting knowledge consolidation, and developing pedagogical and interpersonal skills. A grade analysis indicated that PAL was associated with improved academic performance. These findings reinforce the value of integrating PAL initiatives into preclinical medical education while highlighting the importance of sustained tutor preparation and supervision. Full article

The male annihilation technique for Bactrocera dorsalis relies primarily on methyl eugenol (ME), which exclusively targets mature males and consequently misses the critical window for managing sexually immature males (SIM). To address this operational gap, we cross-validated male testicular development with ME responsiveness across a 1–12-day age gradient, improved a conventional sugar–vinegar–alcohol lure (SL), and evaluated the combinations of the optimized sugar–vinegar–alcohol lure (OSL) and ME using a 2 × 2 factorial field design. Laboratory assays revealed that ME capture rates and off-white-to-yellow testicular transitions were highly synchronized and strongly correlated; notably, males aged 1–4 days exhibited entirely off-white testes and negligible ME responsiveness, establishing testicular coloration as a robust physiological hallmark of immaturity. In field trials, OSL demonstrated stable attractancy across diurnal intervals, outperforming water controls but yielding captures statistically comparable to the conventional SL. Furthermore, incorporating ME into OSL significantly enhanced SIM captures; however, factorial analysis confirmed that their interaction was not statistically significant. Ultimately, these findings indicate that OSL and ME exert a significant, independent additive effect rather than a synergistic interaction on SIM attraction. This study provides a reliable physiological–behavioral diagnostic framework and a practical, low-cost direct-mixing strategy to extend the operational window of B. dorsalis management. Full article

Each financial market carries a unique “fractal signature” with its own distinct risk and return pattern. This study comparatively deciphers these fractal signatures of the leading stock market indices of the Emerging Seven (E7) countries (Turkey, India, Brazil, Mexico, Russia, China, Indonesia), using Multifractal Detrended Fluctuation Analysis (MFDFA) with data covering the 2021–2025 period. The findings reveal that all examined markets deviate from the classical random walk model and exhibit distinct multifractal characteristics. However, significant differences were observed among these signatures: in contrast to Russia’s chaotic structure, which showed extreme fragility to geopolitical shocks, the Chinese and Mexican markets presented a more stable and homogeneous risk profile. In all indices, it was found that small-scale fluctuations carry a strong long-memory effect (stable trends), while large-scale fluctuations assume a more random character (sudden shocks). This asymmetric behavior confirms the heterogeneous nature of investor expectations. For example, the generalized Hurst exponents H(q) ranged from 0.22 (RTS, Russia) to 0.73 (BIST100, Turkey), and the spectrum width Δα varied between 0.10 (Mexico) and 0.45 (Russia), confirming significant heterogeneity in market complexity. Turkey’s BIST100 index, with its structure encompassing both predictable and sudden-shock-prone dynamics, occupies a balanced position within this spectrum. Consequently, the study confirms that understanding these unique fractal signatures of emerging markets is a fundamental prerequisite for formulating effective risk management strategies and achieving global portfolio diversification. Full article

Assessment of the stability of inflammatory parameters in bovine blood samples is important because it enables evaluation of the impact of preanalytical factors on biomarker preservation, standardization of sample processing and storage conditions, as well as reliable and consistent interpretation of results in diagnostic and research studies. The aim of the work was to evaluate the stability of the most common inflammatory markers in the blood of cows in early lactation. The influence of the serum–clot contacts duration and the storage of the separated serum in 24 cows, at 25 °C and 4 °C, in intervals of 0–24 h, was examined. Concentrations of interleukin 1 and 6 (IL-1, IL-6), tumor necrosis factor α (TNF-α), interferon γ (IFN-γ), haptoglobin (Hp), serum amyloid A (SAA) and extracellular heat shock protein 70 (eHsp70) were determined by ELISA method, stability was assessed by ANOVA analysis and maximum permissible instability method. Stability was determined over a range of 2–15 h for IL-1, 8–24 h for IL-6, 9–13 h for TNF-α, 10–20 h for IFN-γ, 20–24 h for Hp, 15–24 h for SAA, and 9–12 h for eHsp70. The stability was strongly dependent on temperature and sample type, with storage at 4 °C providing the highest stability in most cases, while differences between serum and serum–clot samples were analyte-specific and less consistent compared to the effect of temperature. Full article

Bone is a dynamic specialized connective tissue that undergoes continuous remodeling to preserve its health. Bone health is influenced throughout life by a combination of genetic, hormonal, and environmental factors, as well as physical activity and diet. This study aims to evaluate the effects of diets with different fat content on the femurs of mice fed for 16 or 20 weeks on a normal diet (ND16w and ND20w) or a Western diet (WD16w and WD20w) and for 20 weeks with their combinations on a ketogenic diet (KD) (WD + ND20w, ND + KD20w, and WD + KD20w). Micro-CT analysis on femoral cancellous bone revealed a non-significant trend toward decreased bone volume fraction (BV/TV) and trabecular thickness in mice fed a combined WD + KD20w compared to WD20w. Cortical bone thickness was significantly lower in mice fed WD16w and WD20w compared to those fed ND16w and ND20w (p = 0.049 and p = 0.039, respectively), in mice fed WD20w Ct.Th increased compared to WD + ND20w (p = 0.024) and a strong decrease is evident when comparing WD + ND20w to WD + KD20w (p < 0.0004). Consistently, histological analysis revealed that the number of osteoclasts per bone perimeter on cancellous bone increases compared with ND20w with ND + KD20w (p = 0.007) and WD + ND20w with ND + KD20w (p = 0.0006). In addition, a decrease in osteoblasts was observed (p < 0.041) in cortical bone, comparing ND20w with ND + KD20w; this suggests that the KD may have differential effects depending on the baseline condition. Osteocyte numbers did not significantly change when comparing the different treatments. Masson staining supports micro-CT results on both cortical and cancellous bone. In conclusion, transition from a high-fat diet to a normal diet may partially restore cortical bone health, whereas transition to a ketogenic diet exerts a trend toward additional detrimental effects on trabecular bone. Full article

With the rapid development of intelligent connected vehicles and autonomous driving, real-time and accurate road condition perception has become increasingly critical. Aiming at the limitations of traditional direct and indirect detection methods, this paper proposes an ultrasonic-based real-time detection system for road roughness. Most urban roads today feature asphalt pavements; therefore, this system focuses its research on asphalt pavements. Under the same pavement type (asphalt roads), there is a strong correlation between pavement roughness and the friction coefficient. By measuring the roughness of different pavements, the friction coefficient is estimated using the fuzzy processing method. Then the system through measuring ultrasonic echo amplitude and sensor–road distance, combined with software digital filtering, dual-parameter compensation (distance and temperature–humidity), probabilistic statistical analysis, and fuzzy inference, the mapping relationship among echo signals, road roughness and friction coefficient is established. The system mainly includes an ultrasonic transceiver module, a hardware signal conditioning module, and an MCU-based data processing, display and transmission module. Both simulated experiments and real asphalt pavement tests are carried out for verification. The results show that the system can effectively suppress noise, compensate distance attenuation and environmental interference, and achieve accurate real-time detection of road roughness, with a relative error less than 10% compared with the reference value. The proposed system can provide reliable data support for vehicle active safety systems and autonomous driving applications. Full article

Urban flooding poses increasing risks globally due to climate change and urbanization, yet physics-based hydraulic models suffer from high computational costs that limit their application to flood analysis under various rainfall conditions. This study proposes an optimizer-improved tile-based convolutional neural network framework for efficient prediction of two-dimensional peak flooding maps under various rainfall scenarios. The framework integrates tile-based spatial learning for efficient localized flood-response learning and a combined Adam-VCA optimizer to mitigate local optimum convergence. The framework was applied to the Dorim basin in Seoul, South Korea, using 22 rainfall scenarios ranging from 10 to 800 mm, of which 20 scenarios were used for model training and 2 scenarios (500 mm and 700 mm) were reserved as independent test scenarios for performance evaluation. Prediction accuracy was evaluated using F1-score and critical success index (CSI), and Verification period based accuracy (VAC) and Peak flooding based accuracy (PAC) as study-specific depth-incorporated metrics. The proposed optimizer-improved CNN substantially outperformed the conventional CNN, achieving F1-score of 83.84%, CSI of 72.24%, VAC of 90.39%, and PAC of 70.93%, compared to 51.03%, 34.25%, 63.39%, and 47.29%, respectively. The results confirm the framework’s potential for efficient flooding assessment and urban flood risk management under diverse rainfall conditions. Full article

Background/Objectives: Digital intraoral photography is widely used for clinical documentation, longitudinal monitoring, and AI-assisted dental image analysis. However, specular highlights caused by saliva and intense illumination can obscure tooth texture and compromise image fidelity. This study aimed to develop an automated method for removing specular highlights from intraoral images while preserving tooth surface texture. Methods: A three-stage pipeline consisting of adaptive threshold prediction, mask generation, and image inpainting was proposed. Initially, the Hue, Saturation, Value (HSV) statistical features were extracted from each image and used to train a regression model that predicts an image-specific threshold. Subsequently, the predicted threshold was applied in the CIE LAB color space, followed by a condition-based dynamic adjustment algorithm to refine the mask area and distribution. Finally, an Aggregated Contextual Transformation (AOT)-based generator network was used to restore the masked regions. Results: The proposed dynamic adjustment reduced over-masking compared with regression-only processing and better preserved tooth surface texture. Pixel distribution analysis demonstrated a lower distributional discrepancy, with the Wasserstein distance reduced from 2.9601 to 1.3505 and the Kullback–Leibler divergence reduced from 0.3451 to 0.0618. In the clinical expert evaluation, the proposed method was preferred in 69.5% of the 200 evaluation responses, and the preference difference was statistically significant (p < 0.001). Conclusions: As a proof-of-concept study conducted under controlled conditions using synthetic images, the proposed pipeline reduced specular highlights while better preserving tooth surface texture than the baseline approaches. These findings suggest that the pipeline may support standardized preprocessing of dental image datasets, although broader applications such as long-term monitoring and AI-assisted diagnostic workflows require validation on real clinical photographs. Full article

Retrieval-Augmented Generation (RAG) grounds large language models in external evidence, but many RAG systems represent knowledge either as flat text chunks or as automatically constructed indexing graphs. This assumption is incomplete for curated thematic corpora, including religious scriptures, legal codes, clinical guidelines, educational taxonomies, policy documents, and library classification systems, where domain experts have already organized knowledge into thematic paths and citeable canonical units. This paper investigates how RAG can exploit such expert-authored structures while pruning evidence to a compact and query-specific set. We conduct a critical survey supported by a bibliometric analysis of 2815 Scopus-indexed RAG-related records exported on 26 May 2026, of which 2809 records were retained after duplicate removal. The bibliometric results indicate rapid growth in RAG research but limited explicit consolidation around curated thematic paths, canonical evidence units, or thematic path-guided evidence pruning. We therefore propose ThemePath-RAG, a retrieval framework that retrieves curated thematic paths as high-recall semantic routes, expands candidate canonical evidence, and applies query-aware scoring and global pruning before generation. To assess operational feasibility, we implement ThemePath-RAG for Qur’anic question answering and compare it with a Vector RAG baseline on 150 paired questions using RAGAS context relevance with gpt-4o-mini as the LLM evaluator. Both methods return approximately three final ayat per question. Vector RAG achieves higher mean context relevance than ThemePath-RAG ($0.920$ versus $0.798$; $p<0.001$). Thus, the proof of concept establishes the feasibility of thematic-path-guided retrieval and identifies evidence-selection challenges, rather than demonstrating superiority over conventional vector retrieval. The paper clarifies the framework’s relationship to GraphRAG, LightRAG, HippoRAG, PathRAG, ontology-based RAG, and AI-augmented bibliometric systems, and outlines a language-matched, multi-baseline evaluation agenda for future cross-domain validation. Full article

Autonomous driving systems rely on a sophisticated pipeline of artificial intelligence models to perceive, predict, and plan in dynamic environments. This review presents a systematic analysis of the machine learning and deep learning models underpinning vehicle autonomy, spanning classical convolutional neural networks (CNNs) for object detection and semantic segmentation to recurrent and Transformer-based architectures for trajectory prediction and motion planning. It also provides a critical examination of the autonomous vehicle sensor stack, including cameras, LiDAR, radar, ultrasonics, and GNSS/IMU as data acquisition systems, highlighting modality-specific AI challenges such as monocular depth estimation, 3D point cloud processing, and radar Doppler interpretation. The evolution of perception and decision-making pipelines is reviewed, contrasting modular architectures with end-to-end learning paradigms that directly map raw sensor data to control commands, and discussing their trade-offs in interpretability, safety assurance, and robustness to rare edge cases. We further survey specialized hardware accelerators and heterogeneous automotive SoCs designed to meet stringent real-time and power constraints. Industrial strategies are compared, including multi-modal sensor fusion and vision-centric approaches based on large-scale imitation learning. Finally, we identify open challenges related to robustness under adverse conditions, domain shift, causal ambiguity, and the need for interpretable and certifiable AI in safety-critical autonomous driving systems. Full article

Background/Objectives: Resveratrol, a natural polyphenol with anti-inflammatory and antioxidant properties, has emerged as a promising adjunctive agent in periodontal therapy. This systematic review and meta-analysis evaluated evidence from in vitro, in vivo, and human clinical studies regarding the effects of resveratrol on periodontal disease, with the clinical component focusing on systemically healthy non-smoking patients. Methods: Electronic searches of MEDLINE/PubMed, Scopus, Embase, and Web of Science were conducted for studies published between 2000 and 2025. Eligible studies included periodontal-related in vitro cell models, in vivo experimental periodontitis models, and randomized clinical trials assessing resveratrol as an adjunctive therapy. Data extraction, risk-of-bias assessment, and meta-analyses were conducted in accordance with PRISMA guidelines. Results: Fifteen studies were included (five in vitro, six in vivo, and five human randomized controlled trials). Meta-analysis showed the inhibitory effect of resveratrol on the lipopolysaccharide-induced protein expression of IL-1β, IL-6, TNF-α, and IL-8 in vitro, with low to moderate heterogeneity. In animal studies, resveratrol significantly attenuated ligature-induced dental alveolar bone loss, IL-1β protein, and relative mRNA expression. However, reductions in relative mRNA expressions of TNF-α and IL-6 were inconsistent and highly heterogeneous; in contrast, nanoparticle- and liposomal-modified resveratrol consistently and significantly reduced these mRNA levels. In human trials, adjunctive resveratrol was associated with improvements in probing pocket depth and clinical attachment level compared with root planing alone in patients with periodontitis, as well as reductions in bleeding and plaque indices in patients with periodontal diseases, including gingivitis and periodontitis. Conclusions: Resveratrol suppresses pro-inflammatory cytokine expression in vitro and attenuates alveolar bone loss in vivo, with enhanced and more consistent molecular effects observed using modified formulations. Preliminary clinical evidence suggests that resveratrol may be associated with modest adjunctive effects on periodontal outcomes in systemically healthy non-smokers. However, given the limited number of clinical trials, small sample sizes, heterogeneity among studies, short follow-up periods, and limited certainty of the evidence, these findings should be interpreted cautiously. Further well-designed RCTs with longer follow-up periods are required to determine their clinical relevance. Full article

The high energy demand driven by industrial development has transformed the power system from a single energy source to multiple energy systems (MESs). These systems, which involve thermal generators, combined heat-and-power (CHP) units, electrolyzers, fuel cells, etc., with realistic forecast uncertainty, are very operationally challenged. This paper proposes a Distributionally Robust Optimization (DRO) based on a Wasserstein-metric ambiguity set, which simultaneously optimizes the annual maintenance schedules and short-term operational dispatch across MESs. The ambiguity set is constructed using joint samples of forecast errors for the three carriers’ demand, allowing for a data-driven worst-case distribution approach that mitigates the excessive conservatism typically associated with conventional robust optimization (CRO). The penalties are explicitly enforced for load and renewable energy curtailments across each of the MESs with source-specific value-of-lost-load coefficients. The Wasserstein radius is improved by sensitivity analysis, obtaining a θ value of 0.20 as the cost reduction radius for a 40% RES penetration. Five RES penetration levels are implemented here on the IEEE 39-bus New England network, with CHP, electrolyzer, fuel cell, thermal storage, and hydrogen storage. The DRO reduces the total annual system cost by 56% compared to CRO, while reducing the unbalanced energy. Full article

Background/Objectives: Postoperative pulmonary complications (PPCs) are a major source of morbidity following cardiac surgery, particularly in older adults. While malnutrition is linked to adverse outcomes, the optimal screening tool for identifying patients at risk of PPCs remains uncertain. This study compared the predictive performance of the Geriatric Nutritional Risk Index (GNRI), Mini Nutritional Assessment–Short Form (MNA-SF), Prognostic Nutritional Index (PNI), and Nutrition Alert Form (NAF) for PPCs in older adults undergoing elective cardiac surgery. Methods: This prospective cohort study enrolled 217 patients aged ≥ 60 years at a tertiary university hospital. Preoperative nutritional status was assessed using the GNRI, MNA-SF, PNI, and NAF. The primary outcome was PPC development during hospitalization. Predictive performance was evaluated using receiver operating characteristic (ROC) curve analysis, and multivariable logistic regression identified independent predictors. Results: PPCs occurred in 86 patients (39.6%). Patients who developed PPCs had significantly higher NAF scores than those who did not (median [IQR]: 7.5 [3–12] vs. 5 [2–8], p < 0.001), whereas GNRI, MNA-SF, and PNI scores did not differ significantly. NAF demonstrated the highest predictive performance (AUC: 0.643, 95% CI: 0.567–0.719), followed by PNI, MNA-SF, and GNRI. However, after adjusting for clinical covariates, none of the nutritional assessment tools remained independently associated with PPCs. Conclusions: Among the four tools evaluated, NAF showed the highest predictive performance among the evaluated nutritional assessment tools; however, its discriminative ability was modest, and none of the nutritional assessment tools remained independently associated with PPCs after multivariable adjustment. Nutritional assessment should complement, rather than replace, established clinical risk factors in perioperative risk stratification. Full article

CO₂ foam fracturing has emerged as a promising stimulation technology for enhancing permeability and improving production performance in deep coalbed methane (CBM) reservoirs while providing additional potential for carbon utilization. However, the multiscale relationship between local mechanical degradation and macroscopic mechanical deterioration and fracture instability induced by CO₂ foam treatment remains insufficiently understood. In this study, four candidate coal samples originating from the Carboniferous–Permian No. 8+9 coal seam system were first comparatively characterized. Based on petrographic characteristics, mineralogical composition, and specimen integrity, representative bright coal and semi-dull coal samples from the Lüliang mining area were selected for subsequent multiscale mechanical investigations. Based on petrographic characteristics, mineralogical composition, and specimen integrity, representative bright coal and semi-dull coal samples from the Lüliang mining area were selected for petrographic analysis, X-ray diffraction (XRD), nanoindentation, conventional triaxial compression, and cracked chevron-notched Brazilian disc (CCNBD) fracture toughness tests. Coal specimens were immersed in CO₂ foam under reservoir-relevant conditions (50 °C, 20 MPa, foam quality of 65%) for different durations (0–6 days), and the coupled evolution of micromechanical properties, macroscopic mechanical behavior, and fracture resistance was evaluated. The results indicate that both coal types exhibit pronounced heterogeneity in maceral composition and mineral distribution. Bright coal is characterized by high vitrinite content and low mineral abundance, whereas semi-dull coal contains higher proportions of inertinite and minerals. Nanoindentation results reveal that mineral-rich regions possess significantly higher Young’s modulus and hardness than organic-matter-rich regions, highlighting pronounced micromechanical heterogeneity within the coal matrix. With increasing immersion time, the micromechanical properties of both coals exhibit a two-stage evolution characterized by rapid initial deterioration followed by a gradual stabilization trend. After 6 days of immersion, the average Young’s modulus and hardness of bright coal decreased by 40% and 30%, respectively, whereas those of semi-dull coal decreased by 30% and 17%. Simultaneously, macroscopic mechanical properties and fracture resistance continuously declined, with fracture toughness reductions of 74% and 55% for bright coal and semi-dull coal, respectively. Compared with semi-dull coal, bright coal exhibited higher damage sensitivity, evolving from dominant single-fracture failure to granular fragmentation, whereas semi-dull coal maintained a multi-crack composite shear failure mode. Combined micromechanical and macroscopic observations suggest that the observed mechanical deterioration may be associated with coupled effects of fluid–coal interaction, matrix softening, and progressive damage evolution. Although pore and crack evolution were not directly observed, the results suggest that coal structure plays an important role in governing damage transfer across scales and thereby influences fracture behavior and mechanical weakening. These findings provide insight into the multiscale mechanical response of coal under CO₂ foam treatment and may support the optimization of stimulation strategies for deep CBM reservoirs. Full article

Public space vitality is increasingly regarded as a central issue in the conservation and renewal of traditional villages, yet existing studies rarely combine spatial pattern analysis with residents’ perceptual evaluation within a single framework. Taking Yutu Village in southeastern Hubei, China, as a case, this study develops a Space–Event analytical framework integrating GIS-based spatial statistics with Importance–Performance Analysis (IPA). Semi-structured interviews, participatory mapping, and questionnaire surveys identified 58 public event units, 34 physical public spaces, and 241 event–space coordinate points. Kernel density estimation (KDE) and Ripley’s K-function analysis indicate a composite structure of one core, multiple centers, four axes, and five clusters. Historical and cultural events cluster around heritage buildings, daily life and production events extend along everyday movement corridors up to 155 m, and ritual and folk cultural events remain concentrated at small-scale ceremonial nodes. Based on 112 valid questionnaires, IPA-based evaluation shows negative gaps between importance and satisfaction across all 23 indicators (p < 0.001 for all items), with spatial narrative showing the largest gap (Δ = −1.66), while ritual-related indicators achieve the highest satisfaction scores, suggesting a degree of cultural resilience in ceremonial spaces. By cross-referencing spatial clustering types with IPA quadrants, the study proposes differentiated strategies, including narrative-oriented design for heritage spaces, connectivity enhancement for everyday networks, and protective maintenance for ritual nodes, offering an evidence-based framework transferable to comparable traditional village contexts. Full article