Search Results (11,523)

The main objective of the study was to evaluate the colour changes generated by outdoor exposure on spruce (Picea abies L. Karst) samples used as shingles for the roof of a traditional Maramures gate. Additionally, samples made of oak (Quercus petraea Liebl.) have been used to simulate the gate pillar. The specimens have been treated with boiled linseed oil and exposed to the outdoor environment for nine months under two different trial positions. The colour and moisture content changes in the samples have been periodically evaluated. Reactions of the samples from two species have been analysed considering three different variables, such as exposure time, treatment chemical, and positioning during their outdoor exposure. The samples vertically positioned showed fewer discolouration compared to those with inclined exposure. The total variation in colour increased as the length of exposure time increased. After nine months, the highest variation, based on the ΔE* values, was recorded in the category of untreated samples exposed at an angle of 60° to the horizontal, which showed values of ΔE* = 24.87 for oak and ΔE* = 31.16 for spruce, respectively. The oil treatment had a significant impact only on spruce samples having orthogonal exposure. The findings of this study have the potential to provide a better understanding of such species used for construction applications in relation to weathering. Full article

The accuracy of Precise Orbit Determination (POD) for Global Navigation Satellite Systems (GNSS) critically depends on optimal tracking station selection. This study proposed and validates a novel framework that integrates a hybrid-weight Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) model with spherical k-means clustering, effectively resolving the challenge of balancing station data quality with uniform spatial distribution. The framework generates by first a comprehensive quality score for each station based on 40 indicators and then selects the top-scoring station from distinct geographical clusters to construct a well-distributed, high-quality network. To validate the methodology, we performed multi-GNSS POD using networks of 30, 60, and 90 stations selected by the proposed framework. The accuracy was assessed via two independent methods: orbit comparisons (Root Mean Square, RMS) against final Analysis Center (AC) orbits and Satellite Laser Ranging (SLR) validation. The results demonstrate that the optimized 60-station network (e.g., RMS of ~2.5, 5.3, 2.1, and 5.4 cm for GPS, GLONASS, Galileo, and BDS, respectively) achieves an accuracy comparable to that of a 90-station network. Moreover, a 30-station globally uniform network outperforms a 90-station network of high-quality but spatially clustered stations. This study provides an objective and quantitative solution for establishing efficient and reliable GNSS tracking networks, directly benefiting ACs and other high-precision applications. Full article

Generation expansion planning is critical for the sustainable development of power systems, particularly with the increasing integration of renewable energy sources like wind power. This paper presents an innovative generation expansion model identifying the optimal strategy for constructing new wind power plants. The model determines the ideal size of wind power generation and strategically allocates wind resources across multi-area power systems to maximize their capacity credit. A novel fuzzy set approach addresses wind power’s inherent uncertainty and variability, which models wind data uncertainty through membership functions for each stochastic parameter. This method enhances the accuracy of capacity credit calculations by effectively capturing the unpredictable nature of wind power. The model uses the Effective Load Carrying Capability (ELCC) as the objective function to measure the additional load that can be reliably supported by wind generation. Additionally, integrating a compressed-air energy storage system (CAESS) is introduced as a novel solution to mitigate the intermittency of wind power, further boosting the wind power plants’ capacity credit. By incorporating an energy storage system (ESS), the model ensures greater resource availability and flexibility. The study evaluates a multi-area power network, where each area has distinct conventional generation capacity, reliability metrics, load profiles, and wind data. A three-interconnected power system case study demonstrates the model’s effectiveness in increasing the load carrying capability of intermittent renewable resources, improving system reliability, and enhancing resilience. This study provides new insights into optimizing renewable energy integration by leveraging advanced uncertainty modeling and energy storage, contributing to the long-term sustainability of power systems. Full article

In real-world fire scenarios, complex lighting conditions and smoke interference significantly challenge the accuracy and robustness of traditional fire detection systems. Fusion of complementary modalities, such as visible light (RGB) and infrared (IR), is essential to enhance detection robustness. However, spatial shifts and geometric distortions occur in multi-modal image pairs collected by multi-source sensors due to installation deviations and inconsistent intrinsic parameters. Existing multi-modal fire detection frameworks typically depend on pre-registered data, which struggles to handle modal misalignment in practical deployment. To overcome this limitation, we propose an end-to-end multi-modal Fire Salient Object Detection framework capable of dynamically fusing cross-modal features without pre-registration. Specifically, the Channel Cross-enhancement Module (CCM) facilitates semantic interaction across modalities in salient regions, suppressing noise from spatial misalignment. The Deformable Alignment Module (DAM) achieves adaptive correction of geometric deviations through cascaded deformation compensation and dynamic offset learning. For validation, we constructed an unregistered indoor fire dataset (Indoor-Fire) covering common fire scenarios. Generalizability was further evaluated on an outdoor dataset (RGB-T Wildfire). To fully validate the effectiveness of the method in complex building fire scenarios, we conducted experiments using the Fire in historic buildings (Fire in historic buildings) dataset. Experimental results demonstrate that the F1-score reaches 83% on both datasets, with the IoU maintained above 70%. Notably, while maintaining high accuracy, the number of parameters (91.91 M) is only 28.1% of the second-best SACNet (327 M). This method provides a robust solution for unaligned or weakly aligned modal fusion caused by sensor differences and is highly suitable for deployment in intelligent firefighting systems. Full article

Building Information Modeling (BIM) is a transformative tool in Sustainable Design (SD), providing measurable benefits for efficiency, collaboration, and performance in architectural, engineering, and construction (AEC) practices. Despite its growing presence in academic curricula, a gap persists between students’ recognition of BIM’s sustainability potential and their confidence or ability to apply these concepts in real-world practice. This study examines students’ understanding and perceptions of BIM and Sustainable Design education, offering insights for enhancing curriculum integration and pedagogical strategies. The objectives are to: (1) assess students’ current understanding of BIM and Sustainable Design; (2) identify gaps and misconceptions in applying BIM to sustainability; (3) evaluate the effectiveness of existing teaching methods and curricula to inform future improvements; and (4) explore the alignment between students’ theoretical knowledge and practical abilities in using BIM for Sustainable Design. The research methodology includes a comprehensive literature review and a survey of 213 students from architecture and construction management programs. Results reveal that while most students recognize the value of BIM for early-stage sustainable design analysis, many lack confidence in their practical skills, highlighting a perception–practice gap. The paper examines current educational practices, identifies curriculum shortcomings, and proposes strategies, such as integrated, hands-on learning experiences, to better align academic instruction with industry needs. Distinct from previous studies that focused primarily on single-discipline or software-based training, this research provides an empirical, cross-program analysis of students’ perception–practice gaps and offers curriculum-level insights for sustainability-driven practice. These findings provide practical recommendations for enhancing BIM and sustainability education, thereby better preparing students to meet the demands of the evolving AEC sector. Full article

Background/Objectives: In computer graphics, virtual worlds are constructed and visualized through algorithmic processes. These environments are typically populated with objects defined by mathematical models, traditionally based on Euclidean geometry. However, there is increasing interest in exploring non-Euclidean geometries, which require adaptations of the modeling techniques used in Euclidean spaces. Methods: This paper focuses on defining parametric curves and surfaces within elliptic and hyperbolic geometries. We explore free-form splines interpreted as hierarchical motions along geodesics. Translation, rotation, and ruling are managed through supplementary curves to generate surfaces. We also discuss how to compute normal vectors, which are essential for animation and lighting. The rendering approach we adopt aligns with physical principles, assuming that light follows geodesic paths. Results: We extend the Kochanek–Bartels spline to both elliptic and hyperbolic geometries using a sequence of geodesic-based interpolations. Simple recursive formulas are introduced for derivative calculations. With well-defined translation and rotation in these curved spaces, we demonstrate the creation of ruled, extruded, and rotational surfaces. These results are showcased through a virtual reality application designed to navigate and visualize non-Euclidean spaces. Full article

Background/Objectives: Preclinical and clinical evidence supports a chaperone-based vaccination platform for cancer immunotherapy. The objective of this study is to interrogate the next generation of chaperone-based immune modulator, termed Flagrp170, which was constructed by fusing a defined NF-κB-activating microbial sequence with a large stress protein with a superior antigen-holding/presenting property in the setting of antigen-targeted cancer vaccination. Methods: Bone marrow-derived dendritic cells were treated with Flagrp170 protein or an unmodified parental chaperone molecule (i.e., Grp170), followed by an analysis of DC activation and DC-mediated T cell priming using both in vitro and in vivo models. Antitumor vaccine responses in mice receiving tumor antigens (e.g., gp100, Her2/neu) complexed with Flagrp170 or Grp170 were examined through multiple immune assays. The potential use of a Flagrp170-based chaperone vaccine to sensitize tumors to anti-PD-1 therapy was also evaluated. Results: Flagrp170 not only retains the intrinsic ability of the parent chaperone to facilitate antigen cross-presentation, but also acquires a unique capacity to stimulate DCs efficiently through the engagement of TLR5-NF-κB signaling. This chimeric chaperone shows superior activity compared to the unmodified parental molecule, resulting in enhanced DC activation and T cell priming. Vaccination with Flagrp170 complexed to tumor antigens induces a robust T cell response against primary tumors and metastases, a process critically dependent on CD8⁺ DCs. Additionally, the Flagrp170 chaperone vaccine can efficiently generate and expand tumor-reactive T cells. The consequent remodeling of the tumor microenvironment towards a Th1/Tc1 dominant immune phenotype significantly potentiates cancer responsiveness to anti-PD1 therapy. Conclusions: Given the safety and T cell stimulation profiles of the chaperone–antigen complex vaccine already established in our recent clinical trial, this new generation of chaperone cargo, capable of delivering both antigenic targets and pathogen-associated immunoactivating signals simultaneously, represents a promising strategy to potentially improve the low response rates in patients receiving immune checkpoint inhibitors. Full article

With the large-scale integration of single-phase distributed photovoltaic systems into distribution grids, issues such as mismatched generation and load, overvoltage, and three-phase imbalance may arise in the distribution network. A multi-objective optimization method for flexible distribution networks incorporating a four-leg soft open point (F-SOP) is proposed based on fuzzy chance constraints. First, a mathematical model for the F-SOP’s loss characteristics and power control was established based on the three-phase four-arm topology. Considering the impact of source load uncertainty on voltage regulation, a multi-objective complementary voltage regulation architecture is proposed based on fuzzy chance constraint programming. This architecture integrates F-SOP with conventional reactive power compensation devices. Next, a multi-objective collaborative optimization model for distribution networks is constructed, with network losses, overall voltage deviation, and three-phase imbalance as objective functions. The proposed model is linearized using second-order cone programming. Finally, using an improved IEEE 33-node distribution network as a case study, the effectiveness of the proposed method was analyzed and validated. The results indicate that this method can reduce network losses by 30.17%, decrease voltage deviation by 46.32%, and lower three-phase imbalance by 57.86%. This method holds significant importance for the sustainable development of distribution networks. Full article

Background/Objectives: Osteoporosis is caused by excessive osteoclast activation via the receptor activator nuclear factor kappa B ligand (RANKL), which is released from osteoblasts or osteocytes. RANKL regulates osteoclast activity by binding to the receptor activator of nuclear factor kappa B (RANK) in the canonical pathway or leucine-rich repeat-containing G protein-coupled receptor 4 (LGR4) in the non-canonical pathway. In this study, we attempted to develop an intact small-fragment protein based on RANKL by removing the RANK-binding site and transforming the amino acid residues at crucial sites to inhibit osteoclast activity and treat osteoporosis. Methods: We expressed a small-fragment variant of RANKL as a soluble glutathione S-transferase (GST) or 6x histidine (His)-tagged fusion protein using a GST- or His-binding domain tag expression vector system. To generate an intact form of small-fragment RANKL, ribosome-inactivating protein–His-fusion RANKL was purified using HisTrap affinity chromatography and treated with tobacco etch virus nuclear inclusion endopeptidase to remove the His-tag fusion protein. Tartrate-resistant acid phosphatase (TRAP) and bone resorption pit formation assays were performed to analyze the inhibitory effects on osteoclast differentiation and activation. Results: The intact forms of 225RANKL295P and 225RANKL295A showed the strongest inhibitory effects on TRAP activity and bone resorption pit formation. Conclusions: Using an optimal construct design, a large and diverse range of small RANKL fragments could be generated. This suggests that the generation of small-fragment RANKL provides a promising avenue for the advancement of novel therapeutic approaches to osteoporosis. Full article

Building archetypes are essential for advancing architectural theory and energy modeling, providing a foundation for scalable assessments of building performance and sustainability worldwide. In Saudi Arabia, educational buildings, especially those in public universities, are predominantly constructed using standardized and repetitive design templates, such as courtyard and prototype models, which have significant implications for energy efficiency, indoor environmental quality, and sustainability outcomes. Despite their prevalence, there is a notable lack of systematic research on the classification and distribution of these archetypes within the Saudi context, particularly regarding their impact on energy consumption and sustainable campus planning. This study addresses this gap by systematically collecting and analyzing data from 29 public universities across Saudi Arabia, employing GIS mapping to document building characteristics including age, region, urban context, masterplan typology, and architectural design. A cumulative weighting factor was applied to quantify the representativeness of archetypes, while chi-square tests and effect size metrics assessed the statistical concentration and significance of observed patterns. The results reveal a pronounced dominance of a small number of archetypes, especially standardized courtyard and identical design models, across the national stock, with the top 10% of archetype ranks accounting for the majority of buildings. This high degree of standardization enables efficient modeling, benchmarking, and targeted energy interventions, while also highlighting the need for greater contextual adaptation in future campus planning. While this study does not directly simulate building energy performance, it establishes a national-scale typological foundation that can support future simulation, benchmarking, and policy design. The developed GIS-based framework primarily serves managerial and planning objectives, offering a standardized reference for facility management, retrofitting prioritization, and strategic energy-efficiency planning in Saudi public universities. Full article

Prefabricated stations utilizing digital modeling techniques demonstrate significant advantages over traditional cast-in-place methods, including improved dimensional accuracy, reduced environmental impact, and minimized material waste. To maximize these benefits, this study develops a digital twin platform for prefabricated assembled superimposed stations through the integration of Digital Twin Scene–Entity–Relationship–Incident–Control (SERIC) modeling with IoT technology. The platform adopts a “1+5+N” architecture that implements model-data separation, lightweight processing, and model-data association for SERIC model management, while IoT-enabled data acquisition facilitates lifecycle data sharing. By integrating BIM models, engineering data, and IoT sensor inputs, the platform employs multi-source analytics to monitor construction progress, enhance safety surveillance, ensure quality control, and optimize designs. Implementation at Jinan Metro Line 8’s prefabricated underground station confirms the SERIC-IoT digital twin’s efficacy in advancing sustainable, high-quality rail transit development. Results demonstrate the platform’s capacity to improve construction efficiency and operational management, aligning with urban rail objectives prioritizing sustainability and technological innovation. This study establishes that integrating SERIC modeling with IoT in digital twin frameworks offers a robust approach to modernizing prefabricated station construction, with scalable applications for future smart transit infrastructure. Full article

This study, by analyzing processes taking place in physical education (PE) lessons, sought to identify how traits of self-confidence and intrinsic motivation developed in pupils with special educational needs (SEN). The research employed a micro-ethnographic study that was directed at the research object: opportunities to develop pupils’ traits of self-confidence and intrinsic motivation. Empirical data were gathered through video recordings of PE lessons. The sample comprised 36 first-grade pupils with severe SEN. Using reflexive thematic analysis, we identified themes and subthemes that revealed the development of emotional intelligence traits: self-confidence and intrinsic motivation, as well as themes and subthemes that revealed the manifestation of these traits in PE lessons. The study found that constructive dialogic interaction—emphasizing emotional support and strength-oriented, reciprocal teacher–pupil reflection—was the key factor in developing both self-confidence and intrinsic motivation. The study revealed distinctive features of self-confidence (demonstration of self-efficacy, positive self-assessment, reflection on the perception of strengths) and intrinsic motivation (choosing challenging tasks, determination and persistence, the need to improve skills and achieve better results). The empirical findings reflected universal methods for cultivating emotional intelligence traits that could be transferred to other educational contexts. The article presents a small part of the dissertation research data. Full article

Background/Objectives: This study aimed to develop and validate a Dietary Practices and Food Safety Literacy Scale comprehensively assessing competencies among Korean older adults in healthy dietary practices, hygiene, and food safety. Methods: Item development was informed by a literature review, national dietary guidelines, and existing literacy frameworks. Content validity was reviewed by a 10-member expert panel using the Delphi method. Construct validity was tested using exploratory factor analyses (EFA) and confirmatory factor analyses (CFA), and reliability was assessed through Cronbach’s α, composite reliability (CR), and average variance extracted (AVE). Results: EFA identified three factors—management, decision-making, and moderation competencies—comprising 13 items. Internal consistency was acceptable (α = 0.69–0.83), and CFA supported the three-factor structure (CFI = 0.919, RMSEA = 0.087). CR values exceeded 0.70, and AVE were close to or exceeded the recommended threshold. Conclusions: The scale demonstrates sound psychometric properties and provides a practical tool for identifying competency gaps in Dietary Practices and Food Safety Literacy. Its application may guide tailored health education and community-based interventions to promote healthy aging and support public health strategies in aging societies. By translating health information literacy into measurable, behavior-oriented domains, this tool bridges the gap between theoretical constructs and practical assessment. It can be incorporated into routine health monitoring, enabling policymakers and practitioners to design evidence-based interventions that enhance older adults’ dietary self-management and food safety awareness. Full article

Background/Objectives: Family-centred care is key in neonatal practice, yet parents’ and staff’s research experiences are understudied. This study aims to explore their perspectives to improve inclusiveness, communication, and effectiveness in future neonatal research design and implementation. Methods: This embedded qualitative study, conducted within the Right vEntricular function applicability in a Prediction mOdel to identify pReterm infanTs with early BronchoPulmonary Dysplasia (REPORT-BPD) feasibility study, employed a qualitative descriptive design. The sample included 10 healthcare professionals, evenly split between medical and nursing backgrounds, and 10 parents, equally distributed between mothers and fathers of preterm infants enrolled in the REPORT-BPD study. Data were collected through audio-recorded semi-structured interviews, then transcribed into Word, and imported into NVivo 14 for thematic analysis by three researchers. Results: The following four main themes were developed from 11 sub-themes that were initially extracted: (1) Trust and Assurance in the Study, reflecting the overall trust between parents and staff, emphasising its perceived study’s safety and minimal impact on the infant. (2) Emotional and Psychological Considerations, highlighting the emotional landscape of parents, including their anxieties, stressors, and support systems that help ease their concerns. (3) Communication and Engagement, underscoring the importance of effective communication and engagement between researchers and study participants. (4) Value from Participation and Constructive Feedback, capturing the dual focus on the value participants gain from their involvement in the study, and their constructive suggestions. Conclusions: This study highlights trust, communication, and emotional impact in neonatal research, emphasising ethical, family-centred design to improve engagement and recruitment in future studies. Full article

A major objective in recent years has been the use of membrane sensors for the purpose of monitoring and recognizing environmental pollutants in pharmaceuticals. Ketoprofen (KTP) is likely to be found in the environment, particularly in surface water bodies like rivers, because of its extensive use in medicine. The photodegradability of KTP and the prolonged exposure of river water to sunlight may facilitate its photodegradation. To measure KTP along with its main photo-degradation products, three membrane electrodes were fabricated using different plasticizers. Dioctyl phthalate (DOP), dibutyl sebacate (DBS), and o-nitrophenyloctyl ether (o-NPOE) membrane electrodes were constructed for the selective analysis of the investigated medication. The fabricated sensors were prepared using tetraoctyl ammonium chloride as an ion-pairing agent. A linear range of 1 × 10⁻⁵ M to 1 × 10⁻¹ M was shown by the electrodes. The slopes (in mV/decade) for the DOP, DBS, and o-NPOE membranes were −58.80 ± 0.90, −57.90 ± 0.80, and −56.80 ± 1.10, respectively. All test parameters were refined to enhance electrochemical performance. The synthesized membranes were successfully utilized to accurately measure KTP amidst its primary photodegradants. The fabricated sensors were effectively utilized to measure KTP in river water samples without requiring pre-treatment processes. Full article