Search Results (416,435)

Person-centered navigation (PCN) in healthcare refers to a proactive collaboration among professionals, researchers, patients, and their families to guide individuals toward timely access to screening, treatment, follow-up, and psychosocial support. PCN—which includes professional, peer, and virtual guidance, is particularly crucial for rare cancers, where affected individuals face uncertainty, limited support, financial strain, and difficulties accessing relevant information, testing, and other services. The Canadian Cholangiocarcinoma Collaborative (C3) prioritizes PCN implementation to address these challenges in the context of Biliary Tract Cancers (BTCs). C3 uses a virtual PCN model and staffs a “C3 Research Navigator” who provides clinical and research navigation such as personalized guidance and support, facilitating access to molecular testing, clinical trials, and case reviews through national multidisciplinary rounds. C3 also supports a national network of BTC experts, a patient research registry, and advocacy activities. C3’s implementation strategies include co-design, timely delivery of support, and optimal outcomes across its many initiatives. Future priorities include expanding the C3 network, enhancing user engagement, and further integrating its innovative approach into routine care. Full article

The swift advancements in autonomous vehicle systems have facilitated their implementation across various industries, including agriculture. However, studies primarily focus on passenger vehicles, with fewer examining autonomous trucks. Therefore, this study reviews autonomous truck systems implementation in North Dakota’s agricultural industry to develop comprehensive technology readiness frameworks and strategic deployment approaches. The review integrates systematic literature review and event history analysis of 52 studies, categorized using Social–Ecological–Technological Systems framework across six dimensions: technological, economic, social change, legal, environmental, and implementation challenges. The Technology Readiness Level (TRL) analysis reveals 39.5% of technologies achieving commercial readiness (TRL 8–9), including GPS/RTK positioning and V2V communication demonstrated through Minn-Dak Farmers Cooperative deployments, while gaps exist in TRL 4–6 technologies, particularly cold-weather operations. Nonetheless, challenges remain, including legislative fragmentation, inadequate rural infrastructure, and barriers to public acceptance. The study provides evidence-based recommendations that support a strategic three-phase deployment approach for the adoption of autonomous trucks in agriculture. Full article

Participation in organized sport is widely encouraged for youth development, yet positive outcomes are not guaranteed. Parents play a pivotal role in shaping young athletes’ experiences, requiring emotional support, interpersonal skills, and self-regulation. This study examines the meanings parents attribute to their children’s sports participation and how young athletes construct their experiences under parental and coaching influences. An interpretive phenomenological methodology involved semi-structured interviews with coaches, focus groups with parents, and open-ended questionnaires to young athletes. Seventeen players (M = 11.2 years, SD = 0.59), nineteen parents (M = 47.6 years, SD = 3.61), and two coaches from the same football club volunteered to participate in the study. Participants were selected through purposive sampling to ensure a homogeneous experience. The findings reveal that parental involvement balances support and pressure, while trust-building between parents and coaches significantly impacts the athletes’ experiences. The evolving role of technology and the importance of social dynamics within teams also emerged as critical factors. Intrinsic motivation, fostering emotional bonding through the sport, and adopting a developmental rather than purely competitive framework were emphasized factors identified as supporting positive youth sport experiences. These findings offer insights into how interconnected relationships among parents, coaches, and athletes influence children’s sports engagement and development. Full article

If implemented properly in architectural design, passive measures can contribute to achieving the desired comfort in a building while reducing its energy consumption. Glazed additions in the form of sunspaces or greenhouses can influence the improvement of building energy efficiency and, at the same time, create appealing and pleasant building extensions. Through energy simulations performed using EnergyPlus software, this study aims to analyze the potential contribution of glazed additions to a detached house to reducing energy consumption and creating additional space for living. Research was performed as a case study at the following locations: Niš (Serbia), Berlin (Germany), and Tromsø (Norway). For the purposes of this study, five models (M0–M4) were developed and subjected to analysis across two different scenarios. The results of the conducted research showed that the integration of glazed elements can significantly contribute to energy savings: maximum total annual savings regarding heating and cooling go from 21% for Tromsø, up to 32% for Berlin and 40% for Niš, depending on whether the building to which the glazed element(s) is/are attached is insulated or not and the number and the position of glazed elements. Although glazed additions can create a pleasant microclimate around the house, the overheating observed in the study indicates that proper ventilation and shading are mandatory, especially in more southern locations. Full article

Rheumatoid arthritis (RA) is a chronic systemic inflammatory disorder primarily targeting joints, leading to pain, swelling, and stiffness. RA results from the body’s own immune system attacking its own tissues. Currently, there are various treatments available for RA including disease-modifying antirheumatic drugs (DMARDs) and NSAIDs. Leflunomide (LEF) is a USFDA-approved synthetic DMARD which is being widely prescribed for the management of RA; however, it faces several challenges such as prolonged drug elimination, hepatotoxicity, and others. LEF exerts its therapeutic effects by inhibiting dihydroorotate dehydrogenase (DHODH), thereby suppressing pyrimidine synthesis and modulating immune responses. Emerging nanotechnology-based therapies help in encountering the current challenges faced in LEF delivery to RA patients. This review enlists the LEF’s pharmacokinetics, mechanism of action, and clinical efficacy in RA management. A comparative analysis with methotrexate, biologics, and other targeted therapies, highlighting its role in monotherapy and combination regimens and the safety concerns, including hepatotoxicity, gastrointestinal effects, and teratogenicity, is discussed alongside recommended monitoring strategies. Additionally, emerging trends in novel formulations and drug delivery approaches are explored to enhance efficacy and minimize adverse effects. Overall, LEF remains a perfect remedy for RA patients, specifically individuals contraindicated with drugs like methotrexate. The therapeutic applicability of LEF could be enhanced by developing more customized treatments and advanced drug delivery approaches. Full article

Negative Ion Source Neutral beam Injection (NNBI), as a critical auxiliary heating system for magnetic confinement fusion devices, directly affects the plasma heating efficiency of tokamak devices through the reliability of its beam source system. The single-shot experiment constitutes a significant experimental program for NNBI. This study addresses the frequent equipment failures encountered by the NNBI beam source system during a cycle of experiments, employing fault tree analysis (FTA) to conduct a systematic reliability assessment. Utilizing the AutoFTA 3.9 software platform, a fault tree model of the beam source system was established. Minimal cut set analysis was performed to identify the system’s weak points. The research employed AutoFTA 3.9 for both qualitative analysis and quantitative calculations, obtaining the failure probabilities of critical components. Furthermore, the F-V importance measure and mean time between failures (MTBF) were applied to analyze the system. This provides a theoretical basis and practical engineering guidance for enhancing the operational reliability of the NNBI system. The evaluation methodology developed in this study can be extended and applied to the reliability analysis of other high-power particle acceleration systems. Full article

Accurate and robust spatial perception is fundamental for dynamic 3D city modeling and urban environmental sensing. High-resolution remote sensing data, particularly LiDAR point clouds, are pivotal for these tasks due to their lighting invariance and precise geometric information. However, processing and aligning sequential LiDAR point clouds in complex urban environments presents significant challenges: traditional point-based or feature-matching methods are often sensitive to urban dynamics (e.g., moving vehicles and pedestrians) and struggle to establish reliable correspondences. While deep learning offers solutions, current approaches for point cloud alignment exhibit key limitations: self-supervised losses often neglect inherent alignment uncertainties, and supervised methods require costly pixel-level correspondence annotations. To address these challenges, we propose UnMinkLO-Net, an end-to-end self-supervised LiDAR odometry framework. Our method is as follows: (1) we efficiently encode 3D point cloud structures using voxel-based sparse convolution, and (2) we model inherent alignment uncertainty via covariance matrices, enabling novel self-supervised loss based on uncertainty modeling. Extensive evaluations on the KITTI urban dataset demonstrate UnMinkLO-Net’s effectiveness in achieving highly accurate point cloud registration. Our self-supervised approach, eliminating the need for manual annotations, provides a powerful foundation for processing and analyzing LiDAR data within multi-sensor urban sensing frameworks. Full article

The paper presents the results of investigations into the relationship between selected water quality parameters and hydrological streamflow drought in a small river situated in the Mazovian Lowlands in Poland. As hydrological streamflow drought periods become more frequent in Poland, investigations about the relationship between flow and water quality parameters can be an essential contribution to a better understanding of the impact of low flow on the status of water rivers. Data from a three-year study of a small lowland river along with significant agricultural land management was used to analyze the connection between low flows and specific water quality indicators. The separation of low-flow data from water discharge records was achieved using two criteria: Q90% (the discharge value from a flow duration curve) and a minimum low-flow duration of 10 days. During these periods, the concentration of water quality indicators was determined based on collected water samples. In total, 30 samples were gathered and examined for pH, suspended sediments, dissolved substances, hardness, ammonium, nitrates, nitrites, phosphates, total phosphorus, chloride, sulfate, calcium, magnesium, and water temperature during sampling. The study’s main aim was to describe the relation between hydrological streamflow droughts and chosen water quality parameters. The analysis results demonstrate an inverse statistically significant relationship between concentration and low-flow values for total hardness and sulfate. In contrast, there was a direct relationship between nutrient indicators, suspended sediment concentration, and river hydrological streamflow drought. Statistical tests were applied to compare the datasets between years, revealing statistical differences only for nutrient indicators. Full article

Refining the land use structure can boost land utilization efficiency and curtail regional carbon emissions. Nevertheless, prior research has predominantly concentrated on static linear planning analysis. It has failed to account for how future dynamic alterations in driving factors (such as GDP and population) affect simulation outcomes and how the land use spatial configuration impacts the attainment of the carbon-neutrality goal. In this research, 1 km spatial resolution LULC products were employed to meticulously simulate multiple land use scenarios across China at the national level from 2030 to 2060. This was performed by taking into account the dynamic changes in driving factors. Subsequently, an analysis was carried out on the low-carbon land use spatial structure required to reach the carbon-neutrality target. The findings are as follows: (1) When employing the PLUS (Patch—based Land Use Simulation) model to conduct simulations of various land use scenarios in China by taking into account the dynamic alterations in driving factors, a high degree of precision was attained across diverse scenarios. The sustainable development scenario demonstrated the best performance, with kappa, OA, and FoM values of 0.9101, 93.15%, and 0.3895, respectively. This implies that the simulation approach based on dynamic factors is highly suitable for national-scale applications. (2) The simulation accuracy of the PLUS and GeoSOS-FLUS (Systems for Geographical Modeling and Optimization, Simulation of Future Land Utilization) models was validated for six scenarios by extrapolating the trends of influencing factors. Moreover, a set of scenarios was added to each model as a control group without extrapolation. The present research demonstrated that projecting the trends of factors having an impact notably improved the simulation precision of both the PLUS and GeoSOS-FLUS models. When contrasted with the GeoSOS-FLUS model, the PLUS model attained superior simulation accuracy across all six scenarios. The highest precision indicators were observed in the sustainable development scenario, with kappa, OA, and FoM values reaching 0.9101, 93.15%, and 0.3895, respectively. The precise simulation method of the PLUS model, which considers the dynamic changes in influencing factors, is highly applicable at the national scale. (3) Under the sustainable development scenario, it is anticipated that China’s land use carbon emissions will reach their peak in 2030 and achieve the carbon-neutrality target by 2060. Net carbon emissions are expected to decline by 14.36% compared to the 2020 levels. From the perspective of dynamic changes in influencing factors, the PLUS model was used to accurately simulate China’s future land use. Based on these simulations, multi-scenario predictions of future carbon emissions were made, and the results uncover the spatiotemporal evolution characteristics of China’s carbon emissions. This study aims to offer a solid scientific basis for policy-making related to China’s low-carbon economy and high-quality development. It also intends to present Chinese solutions and key paths for achieving carbon peak and carbon neutrality. Full article

Protein–polyelectrolyte nanostructures assembled via electrostatic interactions offer versatile applications in biomedicine, tissue engineering, and food science. However, several open questions remain regarding their intermolecular interactions and the influence of external conditions—such as temperature and pH—on their assembly, stability, and responsiveness. This study explores the formation and stability of networks between poly(acrylic acid) (PAA) and lysozyme (LYZ) at the nanoscale upon thermal treatment, using a combination of experimental and simulation measures. Experimental techniques of static and dynamic light scattering (SLS and DLS), Fourier transform infrared spectroscopy (FTIR), and circular dichroism (CD) are combined with all-atom molecular dynamics simulations. Model systems consisting of multiple PAA and LYZ molecules explore collective assembly and complexation in aqueous solution. Experimental results indicate that electrostatic complexation occurs between PAA and LYZ at pH values below LYZ’s isoelectric point. This leads to the formation of nanoparticles (NPs) with radii ranging from 100 to 200 nm, most pronounced at a PAA/LYZ mass ratio of 0.1. These complexes disassemble at pH 12, where both LYZ and PAA are negatively charged. However, when complexes are thermally treated (TT), they remain stable, which is consistent with earlier findings. Atomistic simulations demonstrate that thermal treatment induces partially reversible structural changes, revealing key microscopic features involved in the stabilization of the formed network. Although electrostatic interactions dominate under all pH and temperature conditions, thermally induced conformational changes reorganize the binding pattern, resulting in an increased number of contacts between LYZ and PAA upon thermal treatment. The altered hydration associated with conformational rearrangements emerges as a key contributor to the stability of the thermally treated complexes, particularly under conditions of strong electrostatic repulsion at pH 12. Moreover, enhanced polymer chain associations within the network are observed, which play a crucial role in complex stabilization. These insights contribute to the rational design of protein–polyelectrolyte materials, revealing the origins of association under thermally induced structural rearrangements. Full article

The contamination of drinking water by per- and polyfluoroalkyl substances (PFASs) presents a global concern due to their extreme persistence, driven by strong C–F bonds. This study investigated the potential of graphene as a filtration material for PFAS removal, focusing on six key compounds regulated by the U.S. EPA: PFOA, PFNA, GenX, PFBS, PFOS, and PFHxS. Using molecular simulations, adsorption energy, diffusion coefficients, and PFAS-to-graphene distances were analyzed. The results showed that adsorption strength increased with molecular weight; PFOS (500 g/mol) exhibited the strongest adsorption (−171 kcal/mol). Compounds with sulfonic acid head groups (e.g., PFOS) had stronger interactions than those with carboxylate groups (e.g., PFNA), highlighting the importance of head group chemistry. Shorter graphene-to-PFAS distances also aligned with higher adsorption energies. PFOS, for example, had the shortest distance at 8.23 Å (head) and 6.15 Å (tail) from graphene. Diffusion coefficients decreased with increasing molecular weight and carbon chain length, with lower molecules like PFBS (four carbon atoms) diffusing more rapidly than heavier ones like PFOS and PFNA. Interestingly, graphene enhanced PFAS mobility in water, likely by disrupting the water structure and lowering intermolecular resistance. These results highlight graphene’s promise as a high-performance material for PFAS removal and future water purification technologies. Full article

This article presents the design, development, and evaluation of an AI-based assistant tailored to support users in the application of the Specific Operations Risk Assessment (SORA) methodology for unmanned aircraft systems. Built on a customized language model, the assistant was trained using system-level instructions with the goal of translating complex regulatory concepts into clear and actionable guidance. The approach combines structured definitions, contextualized examples, constrained response behavior, and references to authoritative sources such as JARUS and EASA. Rather than substituting expert or regulatory roles, the assistant provides process-oriented support, helping users understand and complete the various stages of risk assessment. The model’s effectiveness is illustrated through practical interaction scenarios, demonstrating its value across educational, operational, and advisory use cases, and its potential to contribute to the digital transformation of safety and compliance processes in the drone ecosystem. Full article

Accurate cloud segmentation is critical for astronomical observations and solar forecasting. However, traditional threshold- and texture-based methods suffer from limited accuracy (65–80%) under complex conditions such as thin cirrus or twilight transitions. Although the deep-learning segmentation method based on U-Net effectively captures low-level and high-level features and achieves significant progress in accuracy, current methods still lack interpretability and multi-scale feature integration and usually produce fuzzy boundaries or fragmented predictions. In this paper, we propose multi-scale CAM, an explainable AI (XAI) framework that integrates class activation mapping (CAM) with hierarchical feature fusion to quantify pixel-level attention across hierarchical features, thereby enhancing the model’s discriminative capability. To achieve precise segmentation, we integrate CAM into an improved U-Net architecture, incorporating multi-scale CAM attention for adaptive feature fusion and dilated residual modules for large-scale context extraction. Experimental results on the SWINSEG dataset demonstrate that our method outperforms existing state-of-the-art methods, improving recall by 3.06%, F1 score by 1.49%, and MIoU by 2.21% over the best baseline. The proposed framework balances accuracy, interpretability, and computational efficiency, offering a trustworthy solution for cloud detection systems in operational settings. Full article

A newly emerging disease affecting Schizolobium parahyba (commonly known as pachaco), termed “decline and dieback,” has been reported in association with the fungal pathogens Fusarium sp. and Botryodiplodia sp. This study assessed the antagonistic potential of two Trichoderma sp. isolates (CEP-01 and CEP-02) against these phytopathogens under controlled laboratory conditions. The effects of three temperature regimes (5 ± 2 °C, 24 ± 2 °C, and 30 ± 2 °C) on the growth and inhibitory activity of two Trichoderma spp. isolates were evaluated using a completely randomized design. The first experiment included six treatments with five replicates, while the second comprised twelve treatments, also with five replicates. All assays were conducted on PDA medium. No fungal growth was observed at 5 ± 2 °C. However, at 24 ± 2 °C and 30 ± 2 °C, both isolates reached maximum growth within 72 h. At 24 ± 2 °C, both Trichoderma spp. isolates exhibited inhibitory activity against Fusarium sp. FE07 and FE08, with radial growth inhibition percentages (RGIP) ranging from 37.6% to 44.4% and 52,8% to 54.6%, respectively. When combined, the isolates achieved up to 60% inhibition against Fusarium sp., while Botryodiplodia sp. was inhibited by 40%. At 30 ± 2 °C, the antagonistic activity of Trichoderma sp. CEP-01 declined (25.6–32.4% RGIP), whereas Trichoderma sp. CEP-02 showed increased inhibition (60.3%–67.2%). The combination of isolates exhibited the highest inhibitory effect against Fusarium sp. FE07 and FE08 (68.4%–69.3%). Nonetheless, the inhibitory effect on Botryodiplodia sp. BIOT was reduced under elevated temperatures across all treatments. These findings reinforce the potential of Trichoderma spp. isolates as a viable and eco-friendly alternative for the biological control of pathogens affecting S. parahyba, contributing to more sustainable disease management practices. The observed inhibitory capacity of Trichoderma sp., especially under optimal temperature conditions, highlights its potential for application in integrated disease management programs, contributing to forest health and reducing reliance on chemical products. Full article

Air pollution is linked to childhood mortality and morbidity in low- and middle-income countries globally. There is growing evidence linking air pollution to asthma and other respiratory diseases in children. Studies have shown that children are likely to experience asthma due to their narrow airways and their heightened sensitivity to environmental irritants. This study aims to investigate the relationship between ambient air pollution and respiratory diseases in children under the age of 5. The study will be conducted in the informal township of Alexandra, north of Johannesburg, South Africa. A quantitative approach will be used in this cross-sectional analytical study. Data will be collected using different tools that include a questionnaire to determine the prevalence of asthma and respiratory disease and potential risk factors. While environmental air pollution will be measured using Radiello passive samplers and Gillian pumps. Data will be analyzed using the latest version of the STATANow/MP 19.5 software. Furthermore, health risk assessment will be conducted for lifetime non-carcinogenic and carcinogenic risk estimation following the USEPA framework. The study will identify environmental triggers that exacerbate asthma and other respiratory conditions in other similar community settings and will contribute to the body of knowledge in public health. Ethical approval was obtained from the Research Ethics Committee, Faculty of Health Sciences at the University of Johannesburg. Full article