Search Results (6,432)

This study highlights the spatial, seasonal, and climatic variations in bird species richness across Türkiye, a country with rich avian richness situated at the intersection of major migratory routes. Bird species richness was calculated for each province. Differences between regions, Köppen–Geiger climate classes, and seasons were analyzed using the Kruskal–Wallis method. Non-parametric analysis of longitudinal data in factorial experiments was also employed to determine seasonal differences within regions and climate classes. The results revealed significant spatial variations in species richness, particularly between temperate and cold climate regions. While seasonal differences were generally less pronounced, they were critical for both migratory and resident bird species. Wetlands, coastal areas, and transitional habitats were identified as biodiversity hotspots for both resident and migratory birds. This study underscores the need to integrate regional, climatic, and seasonal variations into ecosystem-based management plans. Protecting critical habitats, enhancing connectivity through ecological corridors, and adopting adaptive conservation strategies are essential for sustaining Türkiye’s rich avian diversity. These results provide valuable insights for conservation planning and emphasize the importance of addressing spatial and seasonal dynamics to ensure long-term biodiversity preservation. Full article

Background/Objective: Executive functions (EFs) are essential in the daily management of arthritis, as they influence treatment adherence, decision-making, and the ability to cope with disease-related challenges. The objective of this study was to compare EFs alongside functional status and quality of life in patients with rheumatoid arthritis (RA) and psoriatic arthritis (PsA) and examine their associations with disease activity and clinical variables. Methods: In this cross-sectional study, 140 patients (70 RA, 70 PsA) were assessed using the Stroop-TBAG, Wisconsin Card Sorting Test (WCST), and Adult Executive Functioning Inventory (ADEXI). Functional status and quality of life were measured with the Health Assessment Questionnaire (HAQ) and WHOQOL-BREF, respectively. Correlations with disease activity (DAS28-CRP), age, and disease duration were examined. Results: RA patients had significantly higher disease activity and longer disease duration. They showed poorer performance on the Stroop Test (color–word time: 61.6 ± 14.8 vs. 52.4 ± 10.9 s, p < 0.001; errors: 3.2 ± 2.1 vs. 2.1 ± 1.5, p = 0.001), more WCST perseverative errors (p = 0.002), and higher ADEXI inhibition scores (13.9 ± 2.5 vs. 12.9 ± 3.0, p = 0.013). DAS28-CRP was correlated with EF impairments, disability, and poorer quality of life in RA (p < 0.05). In PsA, EFs remained relatively stable, although higher disease activity was associated with worse HAQ scores (p = 0.001). Treatment type was not linked to EF, but patients on combination therapy reported lower physical (p = 0.009) and psychological (p = 0.014) quality of life, along with higher HAQ scores (p = 0.016). Conclusions: This study revealed that patients with RA exhibit more pronounced executive dysfunction, along with lower ADL skills and quality of life compared to those with PsA. These findings highlight the need for multidimensional assessment strategies in inflammatory arthritis, especially in RA, where cognitive and functional outcomes are closely tied to clinical burden. Full article

The objective of this study is to analyze microphysical parameters affecting visibility parameterizations of a freezing fog case that occurred on 19 February 2022, during the Cold Fog Amongst Complex Terrain (CFACT) project conducted in a high-elevation alpine valley in Utah, USA. Observations are collected using visibility, droplet spectra, ice crystal spectra, and aerosol spectral instruments, as well as in-situ meteorological instruments. Particle phase is determined from relative humidity with respect to water (RH_w) as well as ground cloud imaging probe (GCIP), ceilometer (CL61) depolarization ratio, and icing accumulation on the platforms. Results showed that freezing droplet density can affect visibility (Vis) up to 100 m during Vis less than 1 km. In addition, increasing volume can lead to up to a 2 μm increase in droplet radius due to a change in the chemical composition of aerosols from Sodium Chloride (NaCl) to Ammonium Nitrate (NH₄NO₃). Overall, comparisons suggested that Vis parameterizations are highly variable, and freezing fog conditions resulted in lower Vis values compared to warm fog microphysical parameterizations. Furthermore, riming of freezing fog conditions can lead to more than 50% uncertainty in Vis. It is concluded that changing aerosol composition and freezing fog droplet density and riming can play a major role in Vis simulations. Full article

Background/Objectives: Vitex agnus-castus has been traditionally used to treat hormonal disorders, and recent evidence suggests its potential anticancer properties. However, its effects on gastric cancer remain unclear. Methods: This study examined the cytotoxic, apoptotic, and anti-metastatic effects of hydroalcoholic Vitex agnus-castus seed extract in gastric cancer cells. Antioxidant capacity (DPPH, ABTS) and total phenolic and flavonoid contents were analyzed. Cytotoxicity was assessed using the MTT assay in HGC27, MKN45, and AGS gastric cancer cell lines and CCD-1072Sk fibroblasts. Apoptosis, mitochondrial membrane potential (MMP), and cell cycle changes were evaluated via Annexin V-FITC/PI, Rhodamine 123, and PI staining, respectively. RT-qPCR and gene enrichment analyses were conducted to investigate the molecular mechanisms. Apoptosis-related protein expression was analyzed through enzyme-linked immunosorbent assay (ELISA). Results: The extract exhibited high antioxidant activity and a significant phenolic content. It reduced cell viability in a dose-dependent manner in gastric cancer cells, while exerting low toxicity in fibroblasts. It significantly increased apoptosis, induced G0/G1-phase cell cycle arrest, upregulated pro-apoptotic genes (CASP3, CASP7, TP53, BCL2L11), and downregulated anti-apoptotic genes (XIAP, NOL3). Gene enrichment analysis highlighted pathways like apoptosis, necrosis, and cysteine endopeptidase activity. The extract also disrupted MMP, inhibited migration and spheroid formation, suppressed EMT markers (SNAIL, SLUG, TWIST1, N-CADHERIN), and upregulated E-CADHERIN. The expression of Caspase 3 and Bax proteins increased and Bcl2 protein decreased. Conclusions: These findings suggest that Vitex agnus-castus seed extract exerts strong anticancer effects in gastric cancer cells by promoting apoptosis, reducing proliferation, and inhibiting migration. Further studies are warranted to explore its clinical relevance. Full article

The IoE forms the foundation of the modern digital ecosystem by enabling seamless connectivity and data exchange among smart devices, sensors, and systems. However, the inherent nature of this structure, characterized by high heterogeneity, distribution, and resource constraints, renders traditional security approaches insufficient in areas such as data privacy, authentication, access control, and scalable protection. Moreover, centralized security systems face increasing fragility due to single points of failure, various AI-based attacks, including adversarial learning, model poisoning, and deepfakes, and the rising threat of quantum computers to encryption protocols. This study systematically examines the individual and integrated solution potentials of technologies such as Blockchain, Edge Computing, Artificial Intelligence, and Quantum-Resilient Cryptography within the scope of IoE security. Comparative analyses are provided based on metrics such as energy consumption, latency, computational load, and security level, while centralized and decentralized models are evaluated through a multi-layered security lens. In addition to the proposed multi-layered architecture, the study also structures solution methods and technology integrations specific to IoE environments. Classifications, architectural proposals, and the balance between performance and security are addressed from both theoretical and practical perspectives. Furthermore, a future vision is presented regarding federated learning-based privacy-preserving AI solutions, post-quantum digital signatures, and lightweight consensus algorithms. In this context, the study reveals existing vulnerabilities through an interdisciplinary approach and proposes a holistic framework for sustainable, scalable, and quantum-compatible IoE security. Full article

Sensor selection in IoT-based smart healthcare systems is a complex fuzzy decision-making problem due to the presence of numerous uncertain and interdependent evaluation criteria. Traditional fuzzy multi-criteria decision-making (MCDM) approaches often assume independence among criteria and rely on aggregation operators that impose sharp transitions between preference levels. These assumptions can lead to decision outcomes with insufficient differentiation, limited discriminatory capacity, and potential issues in consistency and sensitivity. To overcome these limitations, this study proposes a novel fuzzy decision-making framework by integrating Quasi-D-Overlap functions into the fuzzy MARCOS (Measurement of Alternatives and Ranking According to Compromise Solution) method. Quasi-D-Overlap functions represent a generalized extension of classical overlap operators, capable of capturing partial overlaps and interdependencies among criteria while preserving essential mathematical properties such as associativity and boundedness. This integration enables a more intuitive, flexible, and semantically rich modeling of real-world fuzzy decision problems. In the context of real-time health monitoring, a case study is conducted using a hybrid edge–cloud architecture, involving sensor tasks such as heartrate monitoring and glucose level estimation. The results demonstrate that the proposed method provides greater stability, enhanced discrimination, and improved responsiveness to weight variations compared to traditional fuzzy MCDM techniques. Furthermore, it effectively supports decision-makers in identifying optimal sensor alternatives by balancing critical factors such as accuracy, energy consumption, latency, and error tolerance. Overall, the study fills a significant methodological gap in fuzzy MCDM literature and introduces a robust fuzzy aggregation strategy that facilitates interpretable, consistent, and reliable decision making in dynamic and uncertain healthcare environments. Full article

This study develops and validates an artificial intelligence (AI)-assisted internship learning platform for automotive electronics based on the Llama 3 large language model, aiming to enhance pedagogical effectiveness within vocational training contexts. Addressing critical issues such as the persistent theory–practice gap and limited innovation capability prevalent in existing curricula, we leverage the natural language processing (NLP) capabilities of Llama 3 through fine-tuning based on transfer learning to establish a specialized knowledge base encompassing fundamental circuit principles and fault diagnosis protocols. The implementation employs the Hugging Face Transformers library with optimized hyperparameters, including a learning rate of 5 × 10⁻⁵ across five training epochs. Post-training evaluations revealed an accuracy of 89.7% on validation tasks (representing a 12.4% improvement over the baseline model), a semantic comprehension precision of 92.3% in technical question-and-answer assessments, a mathematical computation accuracy of 78.4% (highlighting this as a current limitation), and a latency of 6.3 s under peak operational workloads (indicating a system bottleneck). Although direct trials involving students were deliberately avoided, the platform’s technical feasibility was validated through multidimensional benchmarking against established models (BERT-base and GPT-2), confirming superior domain adaptability (F1 = 0.87) and enhanced error tolerance (σ² = 1.2). Notable limitations emerged in numerical reasoning tasks (Cohen’s d = 1.15 compared to human experts) and in real-time responsiveness deterioration when exceeding 50 concurrent users. The study concludes that Llama 3 demonstrates considerable promise for automotive electronics skills development. Proposed future enhancements include integrating symbolic AI modules to improve computational reliability, implementing Kubernetes-based load balancing to ensure latency below 2 s at scale, and conducting longitudinal pedagogical validation studies with trainees. This research provides a robust technical foundation for AI-driven vocational education, especially suited to mechatronics fields that require close integration between theoretical knowledge and practical troubleshooting skills. Full article

To address the issue that existing raisin foreign object removal equipment cannot eliminate surface contaminants adhered to raisins through non-washing methods, this paper proposes an adhesive foreign object removal method based on “rapid freezing–rolling extrusion separation-airflow screening”. A raisin adhesive foreign object removal device was designed based on this method. The separation and removal processes of adhesive foreign objects were analyzed and optimized through simulation, followed by device fabrication and performance testing. Starting from the separation process of raisins and adhesive foreign objects, we conducted experimental studies on quick-freezing separation, determined the most suitable separation method based on experimental results, and performed structural design of the equipment accordingly. To conduct simulation analysis and optimization, material parameters were calibrated. The working process of foreign object separation was simulated and optimized using discrete element method (DEM) simulation, verifying the equipment’s separation capability for different adhesive foreign objects while determining the optimal rotational speed of 600 r/min. Through EDEM-Fluent coupled simulation, the working process of foreign object removal was analyzed and optimized, validating the influence of flow field on foreign object removal and determining the optimal air velocity of 11 m/s. The equipment was ultimately fabricated, with further parameter optimization and comprehensive performance testing conducted. The final optimal rotational speed and air velocity were determined as 650 r/min and 11 m/s, respectively. In terms of comprehensive performance, the equipment achieved a separation rate of 93.76%, damage rate of 3.05%, residue rate of 4.28%, removal rate of 94.52%, carry-over ratio of 71:1, and processing capacity of 120 kg/h. Full article

Natural enemies commonly probe larval bodies and frass with their antennae for prey hunting. However, the attractants to natural enemies emitted directly from hosts and host-associated tissues remained largely unknown. Here, we used two generalist noctuid species, Helicoverpa armigera (Hübner) and Spodoptera frugiperda (JE Smith), along with the larval endoparasitoid Microplitis mediator (Haliday) to address the question. Extracts of larval frass of both the noctuid species were strongly attractive to M. mediator females when hosts were fed either maize, cotton, soybean leaves, or an artificial diet without leaf tissues. By using a combination of electrophysiological measurements and behavioral tests, we found that the attractiveness of frass mainly relied on a volatile compound ethyl palmitate. The compound was likely to be a by-product of host digestion involving gut bacteria because an antibiotic supplement in diets reduced the production of the compound in frass and led to the decreased attractiveness of frass to the parasitoids. In contrast, extracts of the larval bodies of both the noctuid species appeared to be less attractive to the parasitoids than their respective fecal extracts, independently of types of food supplied to the larvae. Altogether, larval frass of the two noctuid species was likely to be more important than their bodies in attracting the endoparasitoid species, and the main attractant of frass was probably one of the common metabolites of digestion involving gut microbes, and its emission is likely to be independent of host plant species. Full article

This study evaluates the effectiveness of various rejuvenating oils, including soybean oil (N-oil), waste frying oil (F-oil), byproduct oil (W-oil), and aromatic hydrocarbon oil (A-oil), in restoring aged asphalt coatings by reducing asphaltene flocculation and improving colloidal stability. The rejuvenators were incorporated into aged asphalt binder via direct mixing at controlled dosages. Their effects were assessed using microscopy, droplet diffusion analysis, rheological testing (DSR and BBR), and molecular dynamics simulations. The aim is to compare the compatibility, solubility behavior, and rejuvenation potential of plant-based and mineral-based oils. The results indicate that N-oil and F-oil promote asphaltene aggregation, which supports structural rebuilding. In contrast, A-oil and W-oil act as solvents that disperse asphaltenes. Among the tested oils, N-oil exhibited the best overall performance in enhancing flowability, low-temperature flexibility, and chemical compatibility. This study presents a novel method to evaluate rejuvenator effectiveness by quantifying colloidal stability through grayscale analysis of droplet diffusion patterns. This integrated approach offers both mechanistic insights and practical guidance for selecting bio-based rejuvenators in asphalt recycling. Full article

This study investigates the seasonal effectiveness of high-efficiency particulate air (HEPA) purifiers and window-opening behaviors in three London nurseries, using continuous indoor and outdoor PM_2.5 monitoring, window state and air purifier use, and occupant questionnaire data collected from March 2021 to February 2022. Of the approximately 40–50 nurseries contacted, only three agreed to participate. Results show that HEPA purifiers substantially reduced indoor particulate matter (PM_2.5), with the greatest effect observed during the heating season when windows remained closed for longer periods. Seasonal and behavioral analysis indicated more frequent and longer window opening in the non-heating season (windows were open 41.5% of the time on average, compared to 34.2% during the heating season) driven by both ventilation needs and heightened COVID-19 concerns. Predictive modeling identified indoor temperature as the main driver of window opening, while carbon dioxide (CO₂) had a limited effect. In addition, window opening often increased indoor PM_2.5 under prevailing outdoor air quality conditions, with mean concentrations rising from 2.73 µg/m³ (closed) to 3.45 µg/m³ (open), thus reducing the apparent benefit of air purifiers. These findings underscore the complex interplay between mechanical purification and occupant-controlled ventilation, highlighting the need to adapt indoor air quality (IAQ) strategies to both seasonal and behavioral factors in educational settings. Full article

This paper conducts a rigorous study on the spectral properties and operator-space distances of perturbed Dirichlet–Neumann tridiagonal (PDNT) Toeplitz matrices, with emphasis on their asymptotic behaviors. We establish explicit closed-form solutions for the eigenvalues and associated eigenvectors, highlighting their fundamental importance for characterizing matrix stability in the presence of perturbations. By exploiting the structural characteristics of PDNT Toeplitz matrices, we obtain closed-form expressions quantifying the distance to normality, the deviation from normality. Full article

Early blight, caused by the pathogen Alternaria solani, is a major fungal disease impacting potato production globally, with reported yield losses of up to 40% in susceptible varieties. As one of the most common diseases affecting potatoes, its incidence has been steadily increasing year after year. This study aimed to elucidate the molecular mechanisms underlying resistance to early blight by comparing gene expression profiles in resistant (B1) and susceptible (D30) potato seedlings. Transcriptome sequencing was conducted at three time points post-infection (3, 7, and 10 dpi) to identify differentially expressed genes (DEGs). Weighted Gene Co-expression Network Analysis (WGCNA) and pathway enrichment analyses were performed to explore resistance-associated pathways and hub genes. Over 11,537 DEGs were identified, with the highest number observed at 10 dpi. Genes such as LOC102603761 and LOC102573998 were significantly differentially expressed across multiple comparisons. In the resistant B1 variety, upregulated genes were enriched in plant–pathogen interaction, MAPK signaling, hormonal signaling, and secondary metabolite biosynthesis pathways, particularly flavonoid biosynthesis, which likely contributes to biochemical defense against A. solani. WGCNA identified 24 distinct modules, with hub transcription factors (e.g., WRKY33, MYB, and NAC) as key regulators of resistance. These findings highlight critical molecular pathways and candidate genes involved in early blight resistance, providing a foundation for further functional studies and breeding strategies to enhance potato resilience. Full article

Background/Objectives: The aim of this research is to analyze the effect of paclitaxel on endoplasmic reticulum (ER) stress in spermatogenic cells. Methods: In the study, spermatogonium (GC1) and spermatocyte (GC2) cell lines were used. The IC50 dose of paclitaxel was calculated using an MTT assay. Each cell line was separated into two different groups: control (GC1-C, GC2-C) and paclitaxel-treated (GC1-P, GC2-P). The control cells were incubated under standard culture conditions. The paclitaxel group cells were incubated in culture medium containing the paclitaxel IC50 dose for 24 h. After the experiments, all groups were stained with GRP78, p-PERK, and p-eIF2α antibodies using semi-quantitative immunocytochemistry. Results: Paclitaxel showed cytotoxicity. In the experimental model of the paclitaxel-treated cells, all the markers showed elevated levels of immunoreactivity, indicating ER stress. Conclusions: Paclitaxel administration triggered ER stress in spermatogenic cells. Studies of ER-related stress mechanisms in spermatogenic cells with further advanced molecular analyses will be important for therapeutic strategies. Full article

This study examines how teacher–student relationships and school engagement change across online and in-school learning, based on the experiences of 105 cross-regional secondary vocational students in China. Using questionnaire surveys, the study explores students’ perceptions and learning needs in both settings. The findings confirm that teachers play a consistently positive role in promoting student engagement across both online and in-school learning modalities. While affective engagement was higher during online learning, driven by stronger teacher responsiveness and improved student–teacher relationships, students reported increased pride in their schools after returning home, reflecting a renewed appreciation. In-school learning was associated with higher behavioral engagement and greater motivation, despite tensions over intensified academic tasks. Online learning facilitated cognitive engagement through easier vocabulary searches; nevertheless, poor home environments reduced motivation. Enhancing engagement may require offering students autonomy, valuing their input, and clarifying the relevance of the learning content. Full article