Search Results (7,582)

Children with autism spectrum disorder (ASD) frequently struggle with emotion regulation, which can be influenced by parental practices and the supportive role of siblings in encouraging emotional and social development. The study aimed to examine the relationship between parenting practices and emotional regulation of children with ASD and to explore the mediating role of the prosocial behavior of siblings between parenting practices and emotional regulation in children with ASD. Additionally, this study investigated the moderating role of sibling gender in the relationship between prosocial behavior and emotional regulation. A total of 600 parents/caregivers aged 25–40 years (M = 32.91, SD = 4.23) of children with ASD were selected from special education institutes in Lahore, Pakistan, using a non-probability, purposive sampling method. Although the majority of respondents were mothers (94.5%), the term parenting practices is used to reflect a family-level caregiving construct rather than exclusively maternal behavior. Data were interpreted through IBM SPSS Statistics 23 and PROCESS macros, revealing that authoritative parenting had a significant positive relation with emotional regulation in children with ASD. Results also indicated that the prosocial behavior of siblings partially mediated the relationship between authoritative parenting and emotional regulation in children with ASD. Furthermore, sibling gender significantly moderated the indirect effect, with female siblings showing stronger facilitation of emotional regulation through prosocial behaviors compared to male siblings. Full article

Mixed Reality (MR) overlays digital content onto the physical world, holding significant promise for improving construction collaboration and inspection. This study investigates its current role via a quantitative, survey based methodology, collecting data from 125 global construction professionals. Descriptive statistics revealed limited MR adoption, with 40.8% of respondents using the technology rarely and just 12.8% reporting frequent usage. Reliability analysis confirmed strong internal consistency for perceived benefits (α = 0.935) and acceptable consistency for barriers (α = 0.762). Exploratory factor analysis (KMO = 0.932; Bartlett’s test of sphericity, p < 0.001) validated the unidimensionality of the benefits construct. Multiple regression analysis revealed no significant relationship between perceived benefits or barriers and MR usage frequency (R² = 0.011, p = 0.512). Chi square analysis found no significant regional differences in MR use (χ² = 115.4, p = 0.899), though this result warrants cautious interpretation given the sparse expected cell counts. The findings suggest that MR adoption may be influenced by factors beyond user perceptions, highlighting the importance of organisational readiness, training, and infrastructure support. Full article

Unsteady atmospheric disturbances significantly compromise the stability of ornithopters, necessitating advanced turbulence-mitigation strategies. In contrast, natural flyers display remarkable aerodynamic adaptability through dynamic flow-control mechanisms such as covert feathers, enabling stability across unsteady flow regimes. Drawing inspiration from this biological phenomenon, this study presents the modeling and hybrid control of a kestrel-based ornithopter equipped with a Nature-Inspired Flow Control Device (NFCD) that replicates the adaptive feather deployment mechanism observed in kestrels. A reduced-order multibody bond-graph model (BGM) of the full ornithopter is developed, incorporating the main body, propulsion system, rigid wings, and the NFCD subsystem. The model captures key fluid-structure-interaction (FSI) effects between morphing feathers and surrounding airflow. A Linear Quadratic Regulator (LQR) ensures optimal performance under nominal gust conditions (≤3 m/s), while an H₂ controller activates during high-intensity gusts (≥4 m/s) to enhance disturbance rejection through electromechanical feather actuation. A gain-scheduled transition is employed in the intermediate gust range (3–4 m/s) to ensure a smooth transition between controllers. Simulations indicate up to 70% reduction in gust-induced oscillations and 32% gust-mitigation efficiency, achieved through feather actuation in the NFCD combined with hybrid control, stabilizing the ornithopter in less than 1.4 s under higher gust conditions. The close correspondence between simulated responses and previously reported findings validates the proposed approach. Overall, by merging biomimetic aerodynamics, nature-inspired flow control, and advanced control design, the LQR-H₂ governed NFCD provides a promising pathway toward gust-tolerant ornithopters capable of resilient and stable flight in unsteady atmospheric environments. Full article

Long-term monitoring of radon (²²²Rn) and thoron (²²⁰Rn) radioactive gases has been used in earthquake forecasting. Seismic activity before earthquakes raises the levels of these gases, causing abnormalities in the baseline values of radon and thoron time series (RTTS) data. This study reports applications of kernel density estimation (KDE) and wavelet-based density estimation (WBDE) to detect anomalies in radon, thoron, and meteorological time-series data. Anomalies appearing in the RTTS data have been assessed for their potential correlation with seismic events. Using KDE and WBDE, radon anomalies were observed on 12 March, 15 August, 17 September, in the year 2017, and 19 January 2018. Thoron anomalies were recorded on 12 March, 15 August, 17 September 2017, and 28 February 2018. Irregularities in RTTS were observed several days before seismic events. Anomalies in RTTS, detected using KDE, successfully correlated five out of nine seismic events while WBDE identified four anomalies in RTTS which were successfully correlated with the corresponding seismic events. The wavelet transform has been used to reduce noise at higher decomposition levels in radon and thoron time series. Findings of the study reveal the potential of radon and thoron time series that can be used as precursors for earthquake forecasting. Full article

Autonomous driving (AD) systems remain vulnerable to rare, ambiguous, and out-of-label (OOL) hazards that are insufficiently represented in conventional training datasets. This work investigates perception robustness under such conditions by using the Challenge of Out-Of-Label (COOOL) benchmark dataset, which consists of 200 dashcam video sequences annotated with both common and uncommon traffic hazards. We analyze that the behavior of widely used methods in the perception of components and present a multimodal pipeline in which we integrate YOLO11x for object detection, Hough Transform for lane estimation, and GPT-4o for scene description, and for temporal modeling, we use Long Short-Term Memory (LSTM) networks. On the COOOL benchmark, YOLO11x achieves an $mAP@0.5$ of $54.1\%$ on the common object categories, whereas the detection of rare and OFL hazards remains challenging, with a recall of $72.6\%$. Incorporating temporal risk modeling improves hazard recall to $71.8\%$, indicating a modest but consistent gain in recognizing uncommon events. Hough Transform shows the stable behavior in standard conditions for lane estimation, with a mean lateral deviation of $8.9$ pixels in daylight scenes and $13.4$ pixels under low-light conditions. The temporal anomaly detection module attains an AUROC of $0.65$, reflecting the limitation but meaningful discrimination between nominal and anomalous driving situations. For interpretability, the GPT-4o scene description module generates context-aware textual explanations with an object coverage score of $0.72$ and a factual consistency rate of $78\%$, as assessed through manual inspection. The end-to-end pipeline operates at approximately 10–12 frames per second on a single GPU, supporting near-real-time analysis and optimization. Our results confirm that state-of-the-art perception models struggle with OOL hazards and that multimodal vision–language–temporal integration provides incremental improvements in robustness and interpretability when evaluated under the standardized out-of-distribution conditions. Full article

Background: Multidrug-resistant (MDR) Gram-negative bacilli (GNBs) significantly compromise the effective management of urinary tract infections (UTIs) worldwide. As antimicrobial resistance varies across regions, locally tailored data are essential to guide empirical therapy. This study investigated the prevalence, determinants, and temporal dynamics of MDR GNBs in UTI patients from Central Portugal between 2018 and 2022. Methods: We conducted a retrospective observational study at a hospital center in Central Portugal, analyzing data from 2018 to 2022. Data from 5194 UTI patients with GNB-positive cultures were analyzed. Binary logistic regression was used to identify determinants of MDR GNBs, defined as resistance to ≥1 agent in ≥3 antibiotic classes. Results: The study population had a mean age of 64.5 ± 25.3 years, and females represented two-thirds of the sample (67.0%). The overall prevalence of MDR GNBs was 35.8%. Advanced age (≥75 years), male sex, and specific treatment contexts—particularly day treatment and laboratory-only cases—were independently associated with MDR. SBL-producing Enterobacterales and non-fermenting GNBs showed the highest risk levels. Conclusions: MDR GNBs are highly prevalent among UTI patients in Central Portugal, and their increasing trend—particularly in 2022—highlights an urgent need for strengthened surveillance and updated empirical treatment strategies. The observed temporal increase highlights the urgent need for strengthened regional surveillance and updated empirical treatment guidelines. Full article

This paper presents two enhanced variants of the Artificial Protozoa Optimizer (APO), namely the Adaptive Balanced Artificial Protozoa Optimizer (AB-APO) and the Fractional Calculus-Enhanced Artificial Protozoa Optimizer (FC-APO), for optimal multi-Distributed Energy Resources (DERs) planning in smart radial distribution networks. The proposed framework addresses the coordinated allocation of Electric Vehicle Charging Stations (EVCSs), photovoltaic (PV) units, and Battery Energy Storage Systems (BESS). The AB-APO introduces an adaptive balancing mechanism that dynamically regulates exploration and exploitation to improve convergence stability and robustness, while the FC-APO incorporates fractional-order dynamics to embed long-memory effects, enhancing numerical stability and search smoothness. The proposed optimizers are evaluated on the IEEE-33 and IEEE-69 bus systems under eight DERs penetration scenarios. Simulation results demonstrate significant reductions in real and reactive power losses, improved voltage profiles, and effective mitigation of EV-induced network stress. Real power loss reductions exceeding 54%, 38.53%, 53.78%, 38.20%, 61.68%, and 60.72% are achieved for the IEEE-33 system, while reductions of 64.32%, 63.51%, 64.33%, 63.51%, 67.31%, and 67.04% are obtained for the IEEE-69 system across Scenarios 3–8. Overall, the results highlight the effectiveness of adaptive balancing and fractional-order modeling in strengthening APO-based optimization and confirm the suitability of the AB-APO and FC-APO as efficient planning tools for future smart distribution networks. Full article

In the face of escalating energy demand, this research proposes a demand-side management (DSM) strategy that focuses on appliance-level load shifting in residential environments. The proposed approach utilizes detailed energy consumption forecasts that are generated by ensemble machine learning models, which predict usage at both whole-household and individual appliance levels. This granular forecasting enables the development of customized load-shifting schedules for controllable devices. These schedules are optimized using a metaheuristic genetic algorithm (GA) with the objectives of minimizing consumer energy costs and reducing peak demand. The iterative nature of GA allows for continuous fine-tuning, thereby adapting to dynamic energy market conditions. The implemented DSM technique yields significant results, successfully reducing the daily energy consumption cost for shiftable appliances. Overall, the proposed system decreases the per-day consumer electricity cost from 237 cents (without DSM) to 208 cents (with DSM), achieving a 12.23% cost saving. Furthermore, it effectively mitigates peak demand, reducing it from 3.4 kW to 1.2 kW, which represents a substantial 64.7% reduction. These promising outcomes demonstrate the potential for substantial consumer savings while concurrently enhancing the overall efficiency and reliability of the power grid. Full article

Precision planting is critical for improving crop establishment and productivity in smallholder farming systems in Pakistan, where manual seeding remains labour-intensive, imprecise, and inefficient. The limited availability of suitable small planters and the impracticality of larger precision seeders for fragmented holdings further constrain mechanization. This study addressed these limitations by redesigning and enhancing a vertical-plate, single-row precision planter through the integration of a straight seed delivery path and shutter mechanism and evaluating it alongside three other manually operated precision planters. Laboratory experiments quantified the seed physical properties, metering accuracy, calibration performance, and seed damage, while field trials assessed the spacing precision, plant population, labour demand, field efficiency, and operating costs across 1000 m² test plots. The punch-wheel planter exhibited the best performance, achieving a spacing precision coefficient of 6.79%, a field efficiency of 88.2%, and the lowest operating cost (PKR 799 acre⁻¹), while the remaining planters also met acceptable operational standards. In comparison with manual sowing (20–25 man-hours acre⁻¹), precision planters reduced labour to 6–8 man-hours acre⁻¹, saving PKR 7000–9000 acre⁻¹. Enhanced spacing uniformity improved the stand establishment and yield potential. These low-cost precision planters reduce drudgery, particularly for women farmers, minimize soil disturbance, and contribute to the Sustainable Development Goals of the United Nations by promoting sustainable smallholder mechanization. Full article

This paper presents a fault-tolerant control (FTC) strategy for a six-degree-of-freedom (DoF) anthropomorphic manipulator operating under actuator faults and complex friction dynamics. The proposed framework integrates a backstepping control methodology with LuGre friction modeling and a feedforward neural network (FFNN) for friction estimation. Actuator faults are considered in the form of multiplicative efficiency losses and additive disturbances. An adaptive control law is developed to estimate and compensate for both friction and actuator faults in real time. The stability of the closed-loop system is guaranteed through Lyapunov theory. The simulation results validate the effectiveness and robustness of the proposed approach in ensuring precise trajectory tracking despite faults and friction uncertainties. Full article

Background/Objectives: Consanguine families are helpful to identify recessive candidate genes for inherited diseases, but can also show an unusual inheritance pattern of pathogenic mutations. In this case series, we demonstrate this in five consanguine families with epilepsy from Pakistan. Methods: We performed whole exome sequencing of respective index patients, analyzed the data using two different models for inheritance of mutations and determined the segregation pattern of relevant mutations in the families by bi-directional Sanger sequencing. Results: Apart from mutations in classical dominant epilepsy genes (TSC2, DEPDC5, and CACNA1I), pathogenic mutations in rare recessive epilepsy-related genes (PGAP2, NOVA2, and CCDC88C) were also identified. Interestingly, we were able to provide evidence that GALR2 is potentially an additional gene associated with a recessive form of epilepsy. In one family, a homozygous ‘pathogenic’ TRAF3IP1 p. Gly387* nonsense mutation was identified, which, most probably due to stop-codon read-through, did not contribute to the phenotype. Conclusions: Our case series of consanguine families with epilepsy exemplifies the inheritance pattern of mutations in rare recessive epilepsy genes, and shows that mutations in classical epilepsy genes showing dominant or sporadic inheritance can also be relevant. That requires the analysis of whole exome data on the basis of different inheritance models. Full article

This research paper focuses on the role of average working hours (AVHs) of the labor force in explaining the variation in QOL across countries, which is an important but unexplored area in the empirical literature. Using data from 62 countries and employing several econometric techniques, we show that long AVHs are detrimental for improved QOL. The sub-sample results demonstrate that AVHs have a significant detrimental impact on the QOL of the population only in the case of developing countries. However, in the case of developed countries, the influence of AVHs is insignificant as these countries are enjoying relatively reduced AVHs as compared to developing countries. Moreover, our results indicate that the labor force participation rate, human capital, government expenditures, internet use, and electricity consumption are the main driving forces behind a better QOL both in developed and developing countries. Finally, we found evidence that trade openness is an irrelevant factor in explaining the variation in QOL as it is insignificant in most of the specifications despite possessing a positive coefficient. Full article

Background/Objectives: Prostate cancer (PC) is one of the most commonly diagnosed malignancies globally; depending on the treatment strategy used, erectile dysfunction (ED) is a frequently reported adverse outcome among PC patients. The current study evaluated ED prevalence among Pakistani PC patients and its effects on physical, psychological, and social well-being, aiming to address critical gaps in survivorship care for this population. Methods: A cross-sectional, multicenter, observational, questionnaire-based study was conducted in Rawalpindi and Islamabad, Pakistan, from February to April 2025. Health-related quality of life (HRQoL) among PC patients was measured using the Short Form Health Survey 36 (SF-36), while ED prevalence and severity were assessed by the International Index of Erectile Function (IIEF) instrument. Results: Among N = 400 PC patients, surgical treatments predominated (radical prostatectomy: 61.0%; n = 244), while hormonal (androgen-deprivation therapy: 31.5%; n = 126) and chemotherapy (23.3%; n = 93) were also commonly utilized. ED experience was high among PC patients in the erectile function (40.8%; n = 163) and in the intercourse satisfaction (45.0%; n = 180) domains; these showed moderately strong and significant positive correlations across all SF-36 domains, particularly physical functioning (r = 0.52; p < 0.001) and social functioning (r = 0.49; p < 0.001). Regression analysis confirmed sexual function domains explained 60% of HRQoL variance (adjusted R² = 0.60). Conclusions: This study reveals high rates of treatment-related ED—and its biopsychosocial impact–among Pakistani PC patients, with significant negative impacts on HRQoL. The findings underscore the urgent need to integrate sexual health management into standard oncological care practices to improve holistic patient outcomes. Full article