Search Results (24,187)

Stomoxys is a genus of blood-sucking dipteran flies from the family Muscidae with approximately 18 species reported globally. This study sought to identify and determine the apparent densities (ADs) and species richness of Stomoxys species occurring in three land-use setups, namely communal farming areas, commercial farms, and private game farms in the north-eastern part of KwaZulu-Natal Province (KZN), South Africa. Thirty-four H-traps were set up across 10 different localities over 30 days of sampling. A total of 1306 Stomoxys flies with an average of 1.28 flies/trap/day were captured, and six Stomoxys species were identified. S. n. niger was the most abundant species (82.3%), followed by S. calcitrans (13.1%), S. taeniatus (1.9%), S. n. bilineatus (0.84%), S. sitiens (1.1%), and S. boueti (0.7%) was the least collected. This study highlights the need to explore this genus further as it demonstrates that more than one species exists in north-eastern KZN. Furthermore, these flies co-exist with tsetse flies (Glossina spp.), meaning that vector control measures should incorporate all potential vectors of animal trypanosomosis and other vector-borne diseases that occur in the area. Full article

Background/Objectives: This study examines the impact of long-term institutionalization on the linguistic and communicative abilities of people diagnosed with schizophrenia, focusing on the influence of educational background. Schizophrenia is characterized by cognitive and social deficits, including disruptions to language use and communicative engagement. Prolonged institutionalization can exacerbate these impairments by depriving individuals of essential social interactions and cognitive stimulation. Methods: A case series approach was employed with 18 participants, and validated assessment tools such as the Montreal Evaluation of Communication and the Boston Diagnostic Aphasia Test were used to measure communicative performance. Results: Participants with higher educational attainment (nine or more years of schooling) who had been institutionalized for ten years or more exhibited significantly better performance than their less-educated counterparts across various communication domains, including comprehension of linguistic prosody, lexical fluency, and auditory comprehension. This implies that completing a higher degree may mitigate the cognitive decline impact of prolonged stays in an institution. However, the study design does not allow us to ascertain whether education functions as a mitigating factor. Conclusions: The results highlight the importance of incorporating educational considerations into therapeutic strategies for individuals with schizophrenia, especially those experiencing long-term institutionalization. Providing enhanced educational opportunities within institutional settings could mitigate the adverse effects of prolonged confinement and foster improved communication and social skills. These findings are consistent with research on cognitive reserve, which suggests that education fosters adaptive strategies and the utilization of alternative neural pathways. This enables individuals to maintain communication skills despite the cognitive impairment associated with schizophrenia. Full article

The modern job market demands soft and future skills from both technical and non-technical professionals. It is often challenging to teach these competencies in a traditional academic setting. This paper presents an effective approach for developing these skills through a short, intensive, joint project. While our case study is an Erasmus+ program, the methodology can be applied within various frameworks. We use problem-based and active learning, along with group work, to teach. The approach also emphasizes diversity by arranging multidisciplinary student groups to work on software development tasks. In our project, less than half of the participants had a computer science background, demonstrating that these tasks are engaging for non-technical students. The multicultural and international environment of the project is crucial in a global working environment, and its brief, intense nature helps simulate real-world stressful situations. This methodology provides a practical way to prepare students for the demands of the modern workplace. The results confirmed the effectiveness of the project in developing certain key skills, though not all competencies showed a measurable increase during the event’s short duration. Full article

To improve the energy efficiency and indoor environmental quality of rural dwellings in China’s cold regions, this study selected a typical rural dwelling in Linyi, Shandong Province, as a case study. Integrating field measurements with parametric simulations, the Orthogonal Experimental Design method was employed to systematically evaluate the impacts of 12 envelope design parameters on building energy demand (ED_tot, ED_H, ED_C), thermal comfort (PNT_ave), daylight performance (UDI_ave), and economic outcomes (retrofit cost and return on investment, ROI). Three sets of orthogonal experiments with varying value ranges (Case 1–3) were conducted. The results revealed that U-Window and SHGC are the most critical factors influencing energy demand and thermal comfort, while light transmittance (Trans) exerts the greatest influence on daylighting. The economic analysis demonstrated that window material is the primary determinant of retrofit costs, whereas building depth and the south window-to-wall ratio (WWR-South) significantly affect ROI. Additional range and variance analyses quantified the significance of each parameter and revealed nonlinear influence patterns. This research provides data support and decision-making references for the energy-efficient retrofit and multi-objective optimization of rural dwellings in cold regions, offering strong practical implications. Full article

This study explores the potential of paper chromatography for evaluating the condition of used engine oils. A set of 25 oil samples was collected from vehicles operated under real driving conditions and analyzed using both laboratory methods (FTIR spectroscopy, viscosity measurements) and commercial paper test kits. The aim was to quantitatively assess chromatographic spot parameters and investigate their relationships with physicochemical changes in the oil. Refined indicators based on diffusion and contamination zones were proposed and compared with parameters such as oxidation, sulfonation, nitration, and viscosity. The results showed mostly moderate correlations, with only partial consistency between chromatographic and laboratory-derived data. Nevertheless, the analysis highlights that paper chromatography may provide rapid and accessible additional insights for oil condition monitoring, although it cannot substitute standard laboratory testing. Full article

In modern livestock production, obtaining accurate body weight measurements for pigs is essential for feeding management and economic assessment, yet conventional weighing is laborious and can stress animals. To address these limitations, we developed a contactless image-based pipeline that first uses BiRefNet for high-precision background removal and YOLOv11-seg to extract the pig dorsal mask from top-view RGB images; from these masks we designed and extracted 17 representative phenotypic features (for example, dorsal area, convex hull area, major/minor axes, curvature metrics and Hu moments) and included camera height as a calibration input. We then compared eight machine-learning and deep-learning regressors to map features to body weight. The segmentation pipeline achieved mAP₅₀–₉₅ = 0.995 on the validation set, and the XGBoost regressor gave the best test performance (MAE = 3.9350 kg, RMSE = 5.2372 kg, R² = 0.9814). These results indicate the method provides accurate, low-cost and computationally efficient weight prediction from simple RGB images, supporting frequent, noninvasive monitoring and practical deployment in smart-farming settings. Full article

Introduction. Post-traumatic stress disorder (PTSD) remains one of the best-described yet also one of the most heterogeneous psychiatric disorders. Existing neuroimaging studies point to key changes in the hippocampus, amygdala, and prefrontal cortex, but the role of PTSD duration in modulating these changes has not been fully explained. Objectives. The aim of the study was to assess the impact of PTSD duration (≤5 years vs. >5 years) on volumetric and microstructural brain parameters, using multiple Magnetic Resonance Imaging (MRI) sequences (3D Ax BRAVO, Cube T2 FLAIR, Diffusion Tensor Imaging—DTI) and a set of macroscopic morphometric measurements. Methods. The study included 92 participants: 33 with PTSD of ≤5 years duration, 31 with PTSD > 5 years, and 28 healthy controls. Volume and diffusion parameters of six Regions of Interest (ROIs) (hippocampus, amygdala, prefrontal cortex—right and left) were evaluated, along with their associations with nine brain measurements (including width of the third ventricle, corpus callosum, and lateral fissures). Statistical analyses included the Kruskal–Wallis test with Compact Letter Display (CLD) correction and Spearman correlations. Results. (1) The volume of the right hippocampus was significantly greater in the PTSD > 5 years group compared to controls (p = 0.006), with intermediate values in the PTSD ≤ 5 years group. (2) In the left amygdala, an increase in Fractional Anisotropy (FA) and related anisotropy measures was observed in PTSD > 5 years (p ≈ 0.02), without volumetric changes. (3) In the left prefrontal cortex, diffusivity was reduced in PTSD ≤ 5 years (p = 0.035), partially normalizing after >5 years. (4) Correlation analysis revealed that chronic PTSD strengthens the negative associations between hippocampal microstructure and both the width of the amygdala and the interhemispheric fissure, indicating a progressive reorganization of fronto-limbic networks. Conclusions. PTSD induces region- and time-dependent brain changes: (a) adaptive/hypertrophic protection of the right hippocampus after many years of illness, (b) cumulative microstructural reorganization of the left amygdala, and (c) transient impairment of diffusion in the left prefrontal cortex in early PTSD. These findings highlight the necessity of considering the temporal dimension in planning therapeutic interventions and in the search for biomarkers of PTSD progression. Full article

To improve the accuracy of deformation prediction in concrete buildings and large-scale infrastructures such as dams, this study proposes an Attention-BiLSTM model integrated with a parameter-optimized Variational Mode Decomposition (VMD). Specifically, the Pelican Optimization Algorithm (POA) is employed to optimize VMD parameters, enhancing signal decomposition efficiency for structural deformation time series. The optimized VMD is then coupled with a BiLSTM network embedded with an attention mechanism, forming a hybrid prediction framework that captures both temporal dependencies and key feature weights in monitoring data. Using three sets of engineering-measured deformation datasets, the proposed model is validated through comparative analyses with conventional single models (e.g., standalone BiLSTM and VMD-BiLSTM without attention). Results demonstrate that the developed model achieves superior accuracy and stability, significantly outperforming all comparative methods, with the highest R² reaching 0.996, while reducing MAE and RMSE by over 60% and 30%, respectively. Quantitative evaluation indicators (e.g., RMSE, MAE, and R²) confirm that the approach effectively captures both short-term fluctuations and long-term trends of structural deformation. These findings verify its reliability and applicability for intelligent safety monitoring of concrete buildings and infrastructures. Full article

Background: Hand–eye coordination is essential for daily functioning and sports performance, but standardized digital protocols for its reliable assessment are limited. This study aimed to evaluate the intra-examiner repeatability and inter-examiner reproducibility of a computerized protocol (COI-SV^®) for assessing hand–eye coordination in healthy adults, as well as the influence of age and sex. Methods: Seventy-eight adults completed four sessions of a computerized visual–motor task requiring rapid and accurate responses to randomly presented targets. Accuracy and response times were analyzed using repeated-measures and reliability analyses. Results: Accuracy showed a small session effect and minor examiner differences on the first day, whereas response times were consistent across sessions. Men generally responded faster than women, and response times increased slightly with age. Overall, reliability indices indicated moderate-to-good repeatability and reproducibility for both accuracy and response time measures. Conclusions: The COI-SV^® protocol provides a robust, objective, and reproducible measurement of hand–eye coordination, supporting its use in clinical, sports, and research settings. Full article

Over the years, researchers have developed several speed estimation techniques using wearable inertial measurement units (IMUs). In this paper, we introduce a medium-scale dataset, containing measurements of walking/running at speeds ranging from 4.0 km/h (1.11 m/s) to 9.5 km/h (2.64 m/s) in increments of 0.5 km/h (0.14 m/s) from 33 healthy subjects wearing IMUs. We name it the “Speed” dataset. In summary, we present accelerometer and gyroscope data from 12 speeds and 22 subject-independent sets with the full range of 12 speeds. The data in each set consists of overlapping sections of 250 time samples (corresponding to 2.5 s, sampled at 100 Hz), and six dimensions (corresponding to the three axes of the accelerometer and three axes of the gyroscope). Each speed set contains 1775 examples. We benchmark the existing approaches used in the literature for the purpose of speed estimation on this dataset. These include support vector regression, Gaussian Process Regression, and shallow neural networks. We then design a deep Convolutional Neural Network (CNN), SpeedNet, for baseline results. The proposed SpeedNet yields an average Root Mean Square Error (RMSE) of 0.4819 km/h (0.13 m/s), following a subject-independent approach. Then, the SpeedNet obtained from the subject-independent approach are adapted using a portion of subject-specific data. The average RMSE for the remainder of the data for all subjects then drops down to 0.1747 km/h (0.05 m/s). The suggested SpeedNet yields a lower RMSE in comparison to the other approaches. In addition, we also compare the proposed method to others in terms of the average testing time, to give an idea of computational complexity. The proposed SpeedNet, despite being more accurate, yields real-time performance. Full article

Since its introduction, the construct of executive functions (EFs) has been associated with a set of tests to assess these functions and a brain network centered in the associative frontal brain regions. While the majority of perspectives have endorsed these associations, some studies have started casting doubts on them. In this article, the association between the construct of EFs, the tests used to assess them, and the involvement of frontal regions is examined. A sample of 28 patients with brain injuries was divided into three subgroups according to the region of the injury (anterior, posterior, antero-posterior). Patients were assessed with a battery of tests, including 25 measures of EFs and 6 control measures. A series of regression models revealed no significant differences in performance across the three groups. Findings indicate that the EF tests are not specific enough to differentiate EFs and brain injuries. The alleged reference of EFs to the frontal areas of the brain should attribute a higher role to other associative areas. The present study provides recommendations about how the EFs concept could be improved through methodological refinements and/or its dissemination. Full article

This paper introduces a gesture-controlled conversational interface driven by a local AI model, aimed at improving accessibility and facilitating hands-free interaction within digital environments. The technology utilizes real-time hand gesture recognition via a typical laptop camera and connects with a local AI engine to produce customized learning materials. Users can peruse educational documents, obtain topic summaries, and generate automated quizzes with intuitive gestures, including lateral finger movements, a two-finger gesture, or an open palm, without the need for conventional input devices. Upon selection of a file, the AI model analyzes its whole content, producing a structured summary and a multiple-choice assessment, both of which are immediately saved for subsequent inspection. A unified set of gestures facilitates seamless navigating within the user interface and the opened documents. The system underwent testing with university students and faculty (n = 31), utilizing assessment measures such as gesture detection accuracy, command-response latency, and user satisfaction. The findings demonstrate that the system offers a seamless, hands-free user experience with significant potential for usage in accessibility, human–computer interaction, and intelligent interface design. This work advances the creation of multimodal AI-driven educational aids, providing a pragmatic framework for gesture-based document navigation and intelligent content enhancement. Full article

Background/Objectives: Outpatient stroke rehabilitation is expanding as inpatient episodes shorten. Virtual reality (VR) exergaming can extend practice and standardize progression, but setting-specific effectiveness and implementation factors remain unclear. This scoping review mapped VR exergaming in outpatient stroke care and identified technology typologies and functional outcomes. Methods: Guided by the JBI Manual and PRISMA-ScR, searches of MEDLINE, Embase, CENTRAL, Scopus, and Web of Science were conducted in April 2025. The study included adults post-stroke undergoing VR exergaming programs with movement tracking delivered in clinic-based outpatient or home-based outpatient settings. Interventions focused on functional rehabilitation using interactive VR. Results: Sixty-six studies met the criteria, forty-four clinic-based and twenty-two home-based. Serious games accounted for 65% of interventions and commercial exergames for 35%. Superiority on a prespecified functional endpoint was reported in 41% of trials, 29% showed within-group improvement only, and 30% found no between-group difference; effects were more consistent in supervised clinic programs than in home-based implementations. Signals were most consistent for commercial off-the-shelf and camera-based systems. Gloves or haptics and locomotor platforms were promising but less studied. Head-mounted display interventions showed mixed findings. Adherence was generally high, and adverse events were infrequent and mild. Conclusions: VR exergaming appears clinically viable for outpatient stroke rehabilitation, with the most consistent gains in supervised clinic-based programs; home-based effects are more variable and sensitive to dose and supervision. Future work should compare platform types by therapeutic goal; embed mechanistic measures; strengthen home delivery with dose control and remote supervision; and standardize the reporting of fidelity, adherence, and cost. Full article

Research that explores which computational thinking (CT) skills resonate with the abilities and interests of preschoolers is limited. Even more limited is the availability of assessments that can be used to measure young children’s CT learning. This study describes the process employed to generate a series of developmentally appropriate assessment tasks designed to draw inferences of young children’s learning of CT components and engagement in CT practices. Assessment tasks were designed and pilot-tested with a sample of 57 preschool children in Virginia and California. Item responses were coded and analyzed using classical test theory to examine item difficulty and discrimination. The reliability of the final set of items was calculated using Cronbach’s alpha. The overall difficulty of the items was relatively high, and discrimination values were generally adequate. The total summated score was also found to be reliable. Our assessment and design process reveals challenges and shares ideas for item formats that allow gathering evidence of young children’s CT learning. Full article

Sleep monitoring is critical for diagnosing and treating sleep disorders. Although polysomnography (PSG) remains the clinical gold standard, its complexity, discomfort, and lack of portability limit its applicability for long-term and home-based monitoring. To overcome these challenges, this study introduces a novel flexible headband system designed for multi-modal physiological signal acquisition, incorporating dry electrodes, a six-axis inertial measurement unit (IMU), and a temperature sensor. The device supports eight EEG channels and enables wireless data transmission via Bluetooth, ensuring user convenience and reliable long-term monitoring in home environments. To rigorously evaluate the system’s performance, we conducted comprehensive assessments involving 13 subjects over two consecutive nights, comparing its outputs with conventional PSG. Experimental results demonstrate the system’s low power consumption, ultra-low input noise, and robust signal fidelity, confirming its viability for overnight sleep tracking. Further validation was performed using the self-collected HBSleep dataset (over 184 h recordings of the 13 subjects), where state-of-the-art sleep staging models (DeepSleepNet, TinySleepNet, and AttnSleepNet) were applied. The system achieved an overall accuracy exceeding 75%, with AttnSleepNet emerging as the top-performing model, highlighting its compatibility with advanced machine learning frameworks. These results underscore the system’s potential as a reliable, comfortable, and practical solution for accurate sleep monitoring in non-clinical settings. Full article