Search Results (13,350)

This exploratory descriptive study investigated Japanese university students’ perspectives on generative artificial intelligence (generative AI) after guided exposure in an English course. An anonymous questionnaire completed by 83 students examined usage contexts, perceived benefits, practical difficulties, concerns, and instructional needs. Students generally evaluated generative AI positively, particularly for idea generation, learning assistance, and information gathering, and reported using it most often during independent study. Reported difficulties included overly long or inaccurate responses and challenges with prompt formulation. Concerns included overreliance, misinformation, and reduced human interaction. These results describe students’ self-reported perceptions at one point in time; they do not demonstrate changes in attitudes or learning outcomes. The findings provide context-specific information that may inform cautious piloting and evaluation of English activities supported by generative AI in comparable university settings. Full article

Synthetic Aperture Radar (SAR) possesses the capacity for all-weather imaging and is widely applied in target detection. However, robust SAR target detection remains challenging due to the limited availability of task-relevant labeled samples that jointly cover target categories, depression angles, and complex target–background contexts. In this paper, we propose a Data-Augmented Gather-and-Distribute Network (DA-GDNet) for SAR image target detection. By jointly optimizing at both the data and architectural levels, the proposed approach enhances the model’s capacity for target detection in complex backgrounds. Specifically, we design a SAR image data augmentation strategy that integrates three-dimensional modeling with deep learning. Meanwhile, we incorporate a Gather–Distribute (GD) mechanism and a Spatial Feature Enhancement Module (SFEM) to achieve efficient multi-scale feature fusion and enhance the saliency of target regions. Experimental results on the MSTAR dataset and ATRNet-STAR dataset demonstrate that DA-GDNet not only improves detection accuracy and robustness, but also significantly strengthens the model’s adaptability to variations in depression angles and complex backgrounds. Full article

The Scaly-sided Merganser (Mergus squamatus) is an endangered duck endemic to East Asia. It usually gathers in single-species flocks through winter. Existing field records focus almost entirely on southern winter flocks. No prior work has described lone individuals spending winter in northern China. We conducted standardized three-year winter surveys (2019–2022) across five isolated ice-free river patches along the Taizi River, Liaoning Province, northern China, to document habitat use and flocking behavior of one solitary male. Despite the availability of five discrete overwintering sites, the focal bird only occupied two patches characterized by dense riparian concealment and low human disturbance, avoiding open, highly disturbed sites. Resource Selection Function (RSF) modeling indicated habitat attributes (concealment and human disturbance) strongly predicted site use (AICc weight = 0.79), whereas the abundance of heterospecific flocking partners (Common Mergansers Mergus merganser) exerted negligible influence (AICc weight < 0.01). This solitary male associated only with Common Mergansers, the species with the closest phylogenetic relatedness (mitochondrial genetic distance = 0.04365), and never aggregated with other sympatric waterbirds. Model comparison confirmed phylogenetic relatedness outperformed dietary similarity as a predictor of heterospecific flocking (AICc weight = 0.76). Our three-year observations of this single individual demonstrate that, when conspecifics are absent and suitable winter habitat is limited, this male prioritized high-quality, low-disturbance ice-free patches over social aggregation opportunities, and selectively formed mixed flocks with its closest phylogenetic congener. This multi-year case study provides rare empirical baseline data for understanding winter behavioral trade-offs of endangered cavity-nesting waterfowl under severe frozen river conditions, though all conclusions herein apply only to this focal male and cannot be generalized to the entire species. Full article

Green finance has emerged as a critical mechanism for aligning capital markets with climate and sustainability objectives, particularly as economies face mounting pressure to transition away from carbon-intensive growth models. In hydrocarbon-dependent regions such as the Gulf Cooperation Council (GCC), this transition poses distinctive challenges that require integrated institutional, policy, and financial frameworks. The global transition toward sustainable finance has gathered significant momentum, with green capital markets emerging as a central mechanism for channeling investment toward climate and development objectives. Hydrocarbon-dependent economies face a distinctive challenge in this transition, as they must reconcile resource-based growth models with rising pressures for environmental accountability and low-carbon diversification. This study develops an integrated theoretical framework to examine how Gulf Cooperation Council (GCC) financial systems are transitioning toward green capital markets, drawing on institutional theory, environmental policy pathway analysis, and climate-finance alignment models. Using descriptive statistics from regional stock exchanges covering 2015–2024, the study maps key trends in sustainable asset growth, institutional investor preferences, and regulatory evolution across the GCC. Findings indicate progressive alignment with global ESG norms; sustainable asset valuations grew at 23.5% CAGR (UAE) and 18.7% CAGR (Saudi Arabia). A fixed-effects panel regression with panel-corrected standard errors is estimated across all six GCC economies; regulatory framework maturity emerges as the strongest predictor of green bond issuance (β = 0.47, p < 0.01). Cumulative green bond issuances reached USD 52.6 billion (2015–2024), with renewable energy accounting for 58.1% of the sectoral allocation and green transportation recording a 55.9% CAGR (2020–2024). Policy recommendations focus on GCC-wide harmonization of mandatory ESG disclosure, adoption of a unified green bond taxonomy, and expansion of concessional green financing mechanisms. Substantial cross-country heterogeneity is documented, driven by differences in energy policy commitment, financial market maturity, and institutional capacity. The proposed framework offers specific policy guidance to accelerate green financial integration in the GCC, emphasizing regulatory harmonization, institutional capacity-building, and alignment with SDG targets 7 and 13. The study contributes to the limited evidence base on green finance in hydrocarbon-dependent economies and provides a foundation for future empirical research. Given the small panel dimensions (N = 6 cross-sectional units; T = 10 years), this study is positioned as exploratory rather than confirmatory: the panel-regression estimates and the hypothesized institutional-to-policy-to-finance sequence are interpreted as associational patterns consistent with the proposed framework rather than as definitive causal tests, and the reported coefficients are offered as indicative magnitudes to be re-examined as longer GCC green-finance time series become available. Full article

Background/Objectives: Nanotechnology has become a transformative area in modern dentistry, providing new opportunities for better diagnosis, targeted drug delivery, improved restorative materials, antimicrobial treatments, and tissue regeneration. This scoping review outlines the scope, key developments, and future directions of nanotechnology use across all dental specialties, highlights emerging innovations, and identifies major translational challenges and research priorities. Methods: This review followed the Joanna Briggs Institute (JBI) methodology for scoping reviews and adhered to the PRISMA-ScR guidelines. These guidelines, originally by Arksey and O’Malley (2005) and later updated by Levac et al. (2010) and Peters et al. (2020, 2021), guided the process. The Population, Concept, and Context (PCC) framework guided the eligibility criteria. Included studies were primary research or reviews reporting nanotechnology applications in any dental specialty, published in English, with no date restriction. Excluded were non-peer-reviewed sources, conference abstracts without full text, studies unrelated to dental applications, and non-English publications. A comprehensive literature search was conducted across PubMed/MEDLINE, Scopus, and Web of Science. After screening titles and abstracts and reviewing full texts, 133 studies were included. Results: The included studies covered a wide range of fields such as restorative dentistry, implantology, periodontology, endodontics, drug delivery, tissue regeneration, oral diagnostics, antimicrobial applications, prosthodontics, orthodontics, and emerging technologies like nanorobotics and graphene-based systems. The most commonly reported nanomaterials were silver nanoparticles (AgNPs), calcium phosphate nanoparticles (CaP NPs), and polymeric nanoparticles such as PLGA and chitosan. Additionally, there was a notable increase in publications starting from 2019. Conclusions: Nanotechnology offers transformative possibilities in every area of dentistry. Nonetheless, challenges such as nanotoxicology safety, regulatory alignment, and effective clinical application need resolution. Essential steps include standardized characterization, gathering long-term safety data, and establishing international regulatory standards to ensure safe adoption of nano dentistry. Full article

The oilfield gathering and transportation system is an important component of oilfield energy use and therefore provides practical opportunities for supporting the dual-carbon goals through operating-parameter optimization. This study combined field cooling trials on high-water-cut well pipelines, thermal-hydraulic calculations of the downstream gathering network, regression-based surrogate models of the dehydration-station equipment, and coordinated system-level energy accounting. A constraint-based direct-search procedure initialized from the actual field operating condition was used to identify the best feasible operating point within the examined ranges. The search was terminated when a complete update cycle produced no further reduction in energy consumption while all engineering constraints remained satisfied. The field trials showed that the investigated well pipelines could be operated below the corresponding crude-oil pour points under the tested high-water-cut conditions. For the transfer-station-to-central-station stage, the original three-pipe heat-tracing process was adjusted to electric heating and hot-water blending according to the pipeline conditions. Within the central processing station, the equipment operating temperatures were coordinated with the upstream pipeline scheme. For the investigated operating condition, the resulting best feasible scheme produced a deterministic 3.18% reduction in total standard-coal-equivalent energy consumption. The results demonstrate the engineering value of coordinating low-temperature operating boundaries, pipeline heating processes, and station operating parameters in an existing high-water-cut gathering system. Full article

Background/Objectives: Previous studies hypothesized that significant exposure to lead (Pb) and/or cadmium (Cd) induces preeclampsia in pregnant women with subsequent unfavorable obstetric outcomes. This study aimed to compare maternal (Pb and Cd) and umbilical cord (Pb and Cd) levels between patients with preeclampsia and healthy control pregnant women and investigate the variables that are associated with preeclampsia. In addition, the possible influences of these heavy metals on birth weight were assessed. Methods: A case–control study involving 60 women in each group was conducted at the Maternity Hospital in Omdurman, Sudan, between January and June 2021, and included pregnant women residing in Omdurman city, Khartoum state, Sudan. A structured questionnaire was used to gather clinical and medical history. Maternal and cord blood concentrations of Pb and Cd were measured using an atomic absorption spectrophotometer. Univariate and multivariate binary logistic regression analyses were conducted to identify variables associated with preeclampsia. Results: The average maternal age in cases was 25.2 (6.1) years, and in the control group, it was 27.7 (7.2) years. All included participants were residing in Omdurman city, Khartoum state. Preeclampsia patients exhibited significantly elevated mean (SD) levels of umbilical cord Pb [14.2 (5.3) vs. 10.2 (4.5) µg/L, p < 0.001], and median (25th–75th quartile) maternal Cd [3.5 (2.0–6.7) vs. 3.0 (2.0–4.0) µg/L, p = 0.021] and umbilical cord Cd [5.0 (3.0–8.1) vs. 2.5 (1.0–4.0) µg/L, p < 0.001] compared with healthy controls. Mean (SD) of umbilical cord Pb level was lower than maternal Pb [14.2 (5.3) vs. 15.7 (7.8) µg/L, p = 0.246), but not reached statistical significance, while median (25th–75th quartile) concentration of umbilical cord Cd and maternal Cd remained comparable [5.0 (3.0–8.1) vs. 3.5 (2.0–6.7) µg/L, p = 0.093], in patients with preeclampsia. Levels of umbilical cord Cd correlated inversely with birth weight [Sperman’s correlation coefficient (rho) = −0.689, p = 0.013]. Umbilical cord Pb [aOR = 1.29; 1.09 to 1.54; p = 0.003], and Cd [aOR = 1.37; 1.08 to 1.73; p = 0.007], in addition to maternal Cd [aOR = 1.35; 1.06 to 1.72; p = 0.012], were among the variables that are significantly associated with preeclampsia in univariate and multivariate analysis. Conclusions: Umbilical cord Pb, maternal Cd, and umbilical cord Cd concentrations were elevated in pre-eclamptic patients compared with healthy parturient controls and associated with preeclampsia. The preferential higher availability of Cd, but not Pb, in fetal compared with maternal blood might explain why umbilical cord Cd, but not umbilical cord Pb, had a significant negative effect on birthweight. Full article

The formation of oil–water emulsions following reservoir-water breakthrough is widely observed during oil production. The viscosity of these polydisperse systems may increase sharply with increasing water cut, creating substantial operational difficulties in well-gathering systems and increasing hydraulic pressure losses. The rheological behaviour of oil emulsions is influenced by the phase ratio, flow velocity, degree of dispersion, temperature and several other parameters. However, no generally applicable model is currently available for describing the rheological behaviour and predicting the properties of oil emulsions, which are anomalous and rheologically complex systems. Therefore, developing a reliable method for estimating the viscosity of stable emulsions while accounting for increasing water content is of considerable practical importance. This study evaluates existing empirical correlations used to characterise the rheological properties of oil emulsions. The analysis shows that their application under oilfield conditions is associated with several limitations and that, in many cases, they are unsuitable for solving practical engineering problems. Accordingly, a mathematical model was developed and validated for estimating and predicting the viscosity of structurally stable oil emulsions as a function of water cut. The proposed model demonstrated good agreement with the experimental data and may be used for engineering calculations related to the production and transportation of water-cut oil. Full article

When implementing collaborative robot applications, it is paramount to use a human-centered development approach to ensure a positive user experience and increase acceptance. User Experience (UX) design methods involve validating user experience through evaluations as a basic principle. The earlier UX evaluations are carried out, the greater the added value that can be achieved. For collaborative robot applications, especially those involving large robot systems, these early evaluations are challenging since the entire application will not be available until the final stages of development. The proposed methodological approach to this problem utilizes a rudimentary, scaled test setup for early UX evaluations of the entire robot application, enabling user feedback to be incorporated into the development process early on. The method was applied in a project that developed a collaborative robot application for semi-automated liquid cargo handling in inland navigation. UX assessments were carried out using both the rudimentary test setup and a full-scale prototype in a later development phase. The comparison of both assessments proves the applicability of the proposed methodology. Serving as an overarching framework, this methodology encourages developers to test the entire collaborative robot application in user studies at an early stage, thereby gathering valuable user feedback. Full article

In increasingly digital and AI-mediated educational environments, adult learners are required to navigate complex information landscapes shaped by artificial intelligence, digital platforms, and algorithmically generated content. In such contexts, digital literacy can no longer be understood solely as the acquisition of technical competencies. Rather, contemporary digital literacy requires the evaluative and reflective capacities traditionally associated with critical literacy, including the ability to question assumptions, critically evaluate information, engage dialogically with knowledge, and recognise the technological and ideological systems that shape contemporary communication and knowledge production. Consequently, critical literacy has become particularly important within adult and lifelong learning as learners seek to participate meaningfully and ethically within digitally mediated societies. Drawing on Freirean pedagogy and transformative learning theory, this paper revisits critical literacy as a reflective, emancipatory, and socially situated practice grounded in critical consciousness and perspective transformation. It explores how digital technologies can support the development of critical literacy when embedded within learner-centred pedagogies. It further examines the pedagogical potential of digital tools including digital badges, Turnitin Clarity, and Gather to foster reflection, dialogue, writing development, communicative learning, and evaluative judgement. Rather than positioning technology as inherently transformative, this paper argues that it is the pedagogical framing of digital tools that determines their capacity to support critical engagement and learner agency, preserving human criticality within AI-mediated educational systems. This paper highlights the continuing relevance of transformative learning theory in contemporary digital contexts and argues that critical reflection and dialogic learning remain central to adult education in an era shaped by artificial intelligence and digital communication. It concludes that critically informed digital pedagogies can create meaningful opportunities for learners to develop the reflective and evaluative capacities necessary for informed participation in contemporary digital society. Full article

This paper examines worked-bone production at the Miaodigou (MDG) site, a key Middle Neolithic settlement in northern China, to assess the role of bone objects in craft production, subsistence, and social life. During the expansion of millet agriculture and pig domestication, a small group of community members continued to acquire wild animal resources and engage in bone working. This study analyzes 26 finished bone objects and 69 modified osseous fragments through technological analysis, microscopic use-wear analysis, and replication experiments. Results reveal a simple yet pragmatic production system and provide the first reconstruction of the Middle Yangshao worked-bone production sequence. Small-scale bone production reflects a limited but persistent tradition of wild resource exploitation, integrating procurement, manufacture, and use. It also highlights the diversity of subsistence and craft activities within an agriculture-based society, where hunting and gathering practices are often underrepresented. This study further clarifies the functions of two common but understudied tool types in Chinese Neolithic assemblages. Replication experiments show that some awls were likely used for loosening threads or cords, while so-called “knives or daggers” might function as scrapers for bast fibers or animal hides. Full article

Background: Health literacy is widely recognized as a fundamental determinant of chronic disease self-management. Despite the escalating burden of diabetes mellitus in Saudi Arabia, the relationship between health literacy and diabetes self-care management within specific urban–peripheral communities remains inadequately characterized. This study aimed to examine the relationship between health literacy and diabetes self-care management among adults with diabetes residing in southern Riyadh, and to examine associations with key sociodemographic variables, including age, income, gender, and educational attainment. Methods: A non-experimental, cross-sectional, correlational design was employed. A purposive sample of 92 adults with a confirmed diagnosis of diabetes was recruited from primary healthcare centers in southern Riyadh. Data were gathered using the Arabic-validated 12-item European Health Literacy Scale (HLS-Q12) and the 8-item Arabic Summary of Diabetes Self-Care Activities (SDSCA). Descriptive statistics and Spearman rank-order correlations were computed using IBM SPSS Statistics, Version 25. Results: A significant positive correlation was identified between health literacy and diabetes self-care management (rs = 0.64, 95% CI [0.50, 0.75], p < 0.01). Income level demonstrated significant positive associations with both health literacy (rs = 0.41, p < 0.01) and self-care practices (rs = 0.40, p < 0.01). Age exhibited significant negative correlations with health literacy (rs = −0.36, p < 0.01) and self-care management (rs = −0.49, p < 0.01). Educational attainment was significantly associated with both self-care management (rs = 0.29, p < 0.01) and health literacy (rs = 0.26, p < 0.05). Gender was not significantly associated with either outcome. Conclusions: Health literacy was significantly associated with diabetes self-care management in southern Riyadh and may represent a potentially modifiable target for nursing intervention. Findings point to the urgency of designing equity-sensitive, culturally responsive interventions targeting older adults and economically marginalized populations. These preliminary findings may carry implications for nursing practice, diabetes education, and health policy in Saudi Arabia, pending confirmation in larger, prospective samples. Full article

Dairy cow body condition score (BCS) is a practical, semi-quantitative indicator of body energy reserves and changes in energy balance. To improve five-class BCS detection under complex imaging conditions, this study developed UGT-YOLO by integrating a UniRepLKNet Block, a Gather-and-Distribute feature-fusion mechanism, and a Task-Aligned Dynamic Detection Head into YOLOv11n. The model was evaluated using a single publicly available dataset containing five adjacent BCS classes: 3.25, 3.50, 3.75, 4.00, and 4.25. Following redundancy removal and image-quality screening, 7015 original images were retained. Dataset partitioning was completed before data augmentation. The original images were divided at the source-video-sequence level into training, validation, and test subsets containing 5612, 702, and 701 images, respectively. Available cow identifiers were additionally used to keep images of the same identified animal within a single subset. Data augmentation was applied exclusively to the training subset, increasing the training set to 9639 images and producing a final experimental dataset of 11,042 images. UGT-YOLO achieved a precision of 84.3%, a recall of 81.1%, an mAP@0.5 of 88.5%, and an mAP@0.5:0.95 of 66.8%. Compared with YOLOv11n, these values increased by 4.8, 0.9, 2.8, and 4.5 percentage points, respectively. The parameter count increased from 2.6 to 6.5 million, and computational cost increased from 6.4 to 19.2 GFLOPs. Under an input resolution of 640 × 640 pixels, a batch size of 1, and FP32 inference on an NVIDIA GeForce RTX 3090, UGT-YOLO achieved a throughput of 68 frames s⁻¹. These results demonstrate an accuracy–complexity trade-off within the evaluated public dataset and restricted BCS range. Independent cow-level, cross-farm, full-range BCS, multi-scorer, and edge-device validation remains necessary. Full article

Wireless sensor networks (WSNs) are sophisticated monitoring systems that gather environmental data via wireless sensors. Numerous wireless sensors that have been placed to monitor and gather data on a particular environment make up these networks. Typically, a base station or central node wirelessly collects the data prior to analysis. As the battery in wireless sensors is both non-replaceable and non-rechargeable, it represents a key element. As a result, optimizing energy consumption in WSN has become a growing concern. One of the key challenges is consequently the creation of effective protocols for communication in WSNs. In this article, we provide a novel MSA (Mosquito Swarm Algorithm) technique for cluster formation and data routing. Simulations indicate that our proposed algorithm conserves the energy of the nodes and keeps them running for a greater number of survival rounds compared to LEACH (Low-Energy Adaptive Clustering Hierarchy) by a difference of 70.14%, PSO-R (Particle Swarm Optimization with routing) by a difference of 4.76%, and BA-R (Bat Algorithm with routing) by a difference of 2.52%. Our algorithm provides the highest throughput, surpassing LEACH by approximately 6.38%, PSO-R by almost 1%, and BA-R by 12.67%. Simulations indicate that our algorithm is highly effective at extending network longevity and increasing throughput, making it the preferred option to lower energy consumption in WSNs. Full article

The purpose of this paper is to derive and propose site-specific joint environmental contours for two eligible Offshore Wind Farm Organized Development Areas (OWFODAs) in the Aegean Sea, Greece. The contours are tailored primarily for the design, structural reliability assessment and definition of site-specific environmental load combinations of offshore wind turbines (OWTs); they are quantified based on publicly available 28-year data sets related to offshore wind and wave conditions, namely, wave height, $H_s$, wave peak period, $T_p$ and mean wind speed at the hub height of the wind turbine, ${\overline{u}}_{hub}$. A new methodology, using the modified Inverse First Order Reliability Method (IFORM), is proposed to accurately reflect the regional climate peculiarities, combined with fifth-order polynomials and a sigmoid function to fit the data of the Weibull parameters and correctly capture the low- and mid-range values of $H_s$, which are statistically far more frequent. Several results, in terms of 2D and 3D contour surfaces for two locations in each OWFODA, for 50-year and 100-year return periods are presented. Finally, two tables are cited: one gathering $H_s$ and $T_p$ values corresponding to the maximum ${\overline{u}}_{\mathrm{h}\mathrm{u}\mathrm{b}}$ conditions, and another gathering ${\overline{u}}_{\mathrm{h}\mathrm{u}\mathrm{b}}$ and $T_p$ values corresponding to the maximum $H_s$ conditions. The presented joint probability distributions and the environmental contour surfaces bridge metocean statistical modelling with renewable energy systems design. By providing site-specific joint metocean conditions, the proposed methodology supports offshore wind farm design and structural assessment, thereby contributing to sustainable wind energy development in the Aegean Sea. Full article