Search Results (10,896)

To address the critical problem of 3D object detection in autonomous driving scenarios, we developed a novel digital twin architecture. This architecture combines AI models with geometric optics algorithms of camera systems for autonomous vehicles, characterized by low computational cost and high generalization capability. The architecture leverages monocular images to estimate the real-world heights and 3D positions of objects using vanishing lines and the pinhole camera model. The You Only Look Once (YOLOv11) object detection model is employed for accurate object category identification. These components are seamlessly integrated to construct a digital twin system capable of real-time reconstruction of the surrounding 3D environment. This enables the autonomous driving system to perform real-time monitoring and optimized decision-making. Compared with conventional deep-learning-based 3D object detection models, the architecture offers several notable advantages. Firstly, it mitigates the significant reliance on large-scale labeled datasets typically required by deep learning approaches. Secondly, its decision-making process inherently provides interpretability. Thirdly, it demonstrates robust generalization capabilities across diverse scenes and object types. Finally, its low computational complexity makes it particularly well-suited for resource-constrained in-vehicle edge devices. Preliminary experimental results validate the reliability of the proposed approach, showing a depth prediction error of less than 5% in driving scenarios. Furthermore, the proposed method achieves significantly faster runtime, corresponding to only 42, 27, and 22% of MonoAMNet, MonoSAID, and MonoDFNet, respectively. Full article

The civil Global Navigation Satellite System (GNSS) signal is broadcast with an open structure, making it vulnerable to spoofing attacks. Incorporating authentication data into GNSS signals is a significant measure to enhance system security. Precise Point Positioning (PPP) technology has garnered extensive attention for its ability to provide real-time services with centimeter-level accuracy. The PPP service features a high data update rate, with the validity period of the data being approximately ten to twenty seconds. This imposes more stringent requirements on the authentication data rate and the authentication time. Code Shift Keying (CSK) technology has emerged as a key candidate for satellite-based PPP signal design, as it can increase the data rate without requiring additional spectrum resources. This paper investigates authentication methods for CSK-modulated satellite-based PPP signals. Two approaches are proposed: phase modulation authentication and polarity modulation authentication. Simulation and analysis results indicate that the PPP signal with phase modulation authentication experiences less carrier-to-noise ratio (C/N₀) loss and has a higher detection probability. In contrast, the signal with polarity modulation authentication does not suffer from C/N₀ loss and achieves a higher data rate and a shorter authentication time. These findings can serve as valuable references for future GNSS signal design. Full article

Objectives: This study aimed to investigate the mediating roles of social skills and peer relationships in the association between mindfulness and spiritual well-being (SWB) among adolescents. Drawing on the mindfulness-to-meaning theory, the research sought to clarify how mindfulness supports adolescents’ spiritual well-being through social and relational mechanisms. Method: A correlational research design was employed with a sample of 761 adolescents attending high schools in Türkiye. Data were collected using the Mindful Attention Awareness Scale, Social Skills Scale, Peer Relations Scale, and the Three-Factor Spiritual Well-Being Scale. The hypothesized serial mediation model was tested using PROCESS Macro Model 6 with 5000 bootstrap samples. Results: Mindfulness was positively associated with SWB. Both social skills and peer relationships showed significant mediating effects. The serial indirect effect through social skills and peer relationships was also significant. Conclusions: Findings highlight mindfulness as a key psychosocial resource that enhances adolescents’ spiritual well-being through improved social skills and supportive peer relationships. School-based mindfulness programs should integrate peer interaction and social skills components to promote adolescents’ holistic development. Full article

Enterprise Resource Planning (ERP) projects have been the focus of extensive research in recent years. To overcome the challenges associated with these types of projects, one emerging and relatively unexplored stream of research has examined the application of agile project management (APM) in ERP implementation contexts. Despite its growing popularity, APM adoption remains complex, risky, and not yet fully understood. This study focuses on the critical role played by the customer in such projects, as it can either foster or hinder agility. A lack of customer collaboration can often be linked to the customer’s organizational culture (OC). Thus, this study aims to investigate the specific relationship between the customer’s OC and project agility in ERP implementation projects within small- and medium-sized enterprises (SMEs). To conceptualize OC, we adopted the Competing Values Framework (CVF), which distinguishes four cultural types: Clan, adhocracy, hierarchy, and market. Data were collected through an online questionnaire administered to 172 ERP end-users from Canadian SMEs who had participated in their organizations’ ERP implementation projects. The analysis was performed using SmartPLS version 4.1.0.9. The results confirm that customers characterized by a clan, adhocracy, or market culture positively influence project agility, while there was no significant effect of hierarchy culture on project agility. This study addresses several gaps in the literature and offers practical implications. The findings support the idea that vendors should better frame and justify introducing APM in ways that align with each customer’s cultural characteristics within ERP vendor–customer relationships. Full article

Building on social identity theory (SIT), this study investigates how socially responsible human resource management (SRHRM) shapes employees’ organizational citizenship behavior for the environment (OCBE). The proposed framework suggests that felt responsibility for the environment (FRE) serves as a psychological bridge between SRHRM and OCBE, while environmentally specific servant leadership (ESL) strengthens this linkage. Using three waves of matched data collected from 236 full-time employees across manufacturing, service, and technology firms in China, the study applies hierarchical regression and bootstrapping techniques to test the hypotheses. The results indicate that SRHRM has a significant positive effect on OCBE, and this relationship is partly explained by employees’ FRE. In addition, higher levels of ESL amplify the positive association between SRHRM and FRE and reinforce the overall indirect effect on OCBE, producing a statistically meaningful moderated mediation pattern. These findings add to existing knowledge by clarifying the psychological process through which SRHRM encourages employees’ voluntary pro-environmental actions. The study also underscores the role of leadership in shaping the impact of SRHRM, offering organizations practical directions for nurturing a culture of environmental responsibility. Full article

(1) Background: Interprofessional supervision is an emerging approach in health professions education that strengthens collaborative practice competencies while maintaining profession-specific expertise. Understanding current evidence regarding supervision models, outcomes, and implementation factors is crucial for advancing this field. (2) Methods: This narrative review analyzed 28 studies, including quantitative, qualitative, mixed-methods studies, and systematic reviews. Studies were analyzed for supervision models, outcome measures, evidence of effectiveness, and implementation factors. (3) Results: Six categories of interprofessional supervision models were identified: clinical practice-based, group supervision, competency-based training, skills training, case-based learning, and mentorship/coaching. Across models, interprofessional supervision consistently enhanced collaborative competencies, professional development, clinical skills, and organizational outcomes. Organizational support, structured curricula, interprofessional leadership, and individual readiness facilitated implementation success. Barriers included limited resources, professional silos, and challenges in curriculum integration. (4) Conclusions: Interprofessional supervision shows consistently positive outcomes across diverse models and settings, though more rigorous research designs and standardized outcome measures are needed. Successful implementation requires systematic attention to multiple factors at multiple levels, from organizational support to individual readiness. Interprofessional supervision is positioned for significant advancement through the application of implementation science frameworks and continued research on optimal model characteristics and implementation strategies. Full article

Sodium-ion batteries (SIBs) have attracted growing attention as an alternative to lithium-ion technologies for electric mobility and stationary energy-storage applications, owing to the wide availability of sodium resources, cost advantages, and comparatively favorable safety characteristics. Accurate state-of-health (SOH) estimation is essential for safe and reliable SIB deployment, yet existing data-driven methods still suffer from limited accuracy and interpretability, as well as a lack of dedicated aging datasets. This study proposes an explainable SOH estimation methodology based on a long short-term memory (LSTM) network combined with model-agnostic KernelSHAP analysis. Thirteen health indicators (HIs) are extracted from charge/discharge data and post-charge relaxation segments, and the most relevant indicators are selected via Pearson correlation screening as model inputs. Built on these HIs, an LSTM-based multi-step framework is developed to take HI sequences as input and forecast the SOH trajectory over the subsequent 20 cycles. Experimental results show that the proposed method achieves high accuracy and robust cross-cell generalization, with mean absolute error (MAE) below 1.0%, root-mean-square error (RMSE) below 1.2% across all cells, and an average RMSE of about 0.75% in the main cross-cell setting. KernelSHAP-based global and temporal analyses further clarify how different HIs and time positions influence SOH estimates, enhancing model transparency and physical interpretability. Full article

Cottonseed is an important resource for edible oil and protein. Here, we evaluated cottonseed oil, protein, and gossypol contents using traditional chemical methods and near-infrared reflectance spectroscopy (NIRS) in diverse upland cotton (n = 456) and sea island cotton (n = 205) germplasm. In upland cotton, oil content averaged 21.23 ± 3.98% (12.74–43.56%), protein averaged 23.63 ± 4.63% (15.53–49.79%), and gossypol averaged 1.47 ± 0.21 mg/g (0.06–2.07). Correlation analysis showed a significant negative association between oil and protein (r = −0.125, p < 0.01; confirmed by NIRS: r = −0.171, p < 0.01), a significant negative association between protein and gossypol (r = −0.375, p < 0.01), and a significant positive association between oil and gossypol (r = 0.409, p < 0.01). In sea island cotton, oil, protein, and gossypol contents averaged 24.82 ± 6.15% (14.64–41.43%), 25.75 ± 2.04% (18.84–39.00%), and 1.60 ± 0.15 mg/g (1.22–2.08), respectively. The oil–protein association was strongly negative by NIRS (r = −0.744, p < 0.01), whereas correlations with gossypol were weak and not significant by the traditional method. After screening and evaluation, high oil and protein varieties were identified in upland cotton (n = 15) and sea island cotton (n = 6). Fourteen extreme-oil upland materials were further used to examine flowering-date effects on oil accumulation and physiological indicators, showing rapid oil accumulation and a flowering-date-dependent maximum. Finally, qRT-PCR analysis of lipid-metabolism-related candidate genes showed that seven genes were expressed significantly higher in high-oil than in low-oil materials (p < 0.05), peaking at the late stage of oil accumulation. GhDGAT1 and GhDGAT2 showed positive regulatory effects on oil accumulation, whereas GhFAD3 and GhKCR2 showed negative regulatory effects. Collectively, these findings provide compositional benchmarks, clarify trait relationships, and identify candidate genes useful for breeding cotton cultivars with improved seed oil/protein traits. Full article

The current work focuses on the study of the long-term evaluation of wind potential and energy production for a specific wind farm siting position over a mountainous region in Hellas. It aims to calculate the probability of exceedance of the twenty-year normalized average annual net production of the wind farm based on ground wind measurements coupled with Copernicus ERA5 data via a measure–correlate–predict (MCP) method. The study proposes an integrated long-term wind resource assessment workflow that couples short-term mast data with a twenty-year ERA5 record via a refined MCP procedure including temporal shifting for complex terrain. It introduces a practical uncertainty framework that jointly treats measurement, MCP, and terrain effects through dRIX and propagates these to energy yield using a bin-wise power curve and Weibull weighting. The proposed methodology is both fast and readily available to end-users and provides a realistic estimate of the energy production and long-term wind distribution in the investigated area. The data and assumptions employed in the calculations are given in detail. The uncertainty of the parameters in the estimation of the wind potential of the broader area and the energy calculation is analyzed. The results of the calculations and the probability of exceedance curve of the normalized twenty-year average annual net production of the wind farm summarize all uncertainty sources, delivering bankable long-term energy projections for the specific case study. Full article

This study investigates the role of Agreeableness as a personality trait in promoting psychological well-being, with a specific focus on the potential mediating mechanism of social support, and how this pathway is influenced by family’s income. 3206 college students from China’s universities were recruited from Internet, randomly. Subjects were demanded to complete the Agreeableness Subscale of Chinese Big Five Inventory Brief version (CBF-PI-B), the Chinese Campbell Index of Well-Being (Campbell IWB), the Chinese Perceived Social Support Scale (PSSS) and demographic variables. The results, analyzed using a moderated mediation procedure, confirmed that perceived social support mediates the relationship between Agreeableness and subjective well-being. Furthermore, family yearly income was found to significantly moderate the first stage of this mediation pathway. Specifically, the positive associative effect of Agreeableness on perceived social support was stronger for individuals with lower annual family income. This result suggests that, for those with fewer economic resources, a prosocial and agreeable disposition is a particularly critical asset for building the social support networks that subsequently enhance well-being. The findings highlight the complex interplay between personality and socioeconomic context, indicating that social support serves as a healthy coping mechanism, the utility of which is conditionally shaped by an individual’s financial circumstances. Full article

Background: In response to the growing emotional support needs of patients in oncology, peer support was introduced into clinical teams in Quebec, Canada, in 2018. These peers, called accompanying patients (APs), are former cancer patients who use their experiential knowledge to provide support to patients during their oncology journey. This paper aims to identify APs’ perceptions of the program by including a diversity of perspectives. We include inexperienced and experienced APs, APs in different facilities, and APs in different cancer programs. Methods: We conducted a qualitative study based on 12 semi-structured interviews of APs between June and August 2024 in Quebec, Canada. We explored four themes, building on the Practice Change Model for qualitative analysis: APs’ sources of motivation, influences and environmental factors, resources available for AP integration, and the program’s effects. Results: 12 APs from 5 facilities participated in an interview. All the APs, both experienced and inexperienced, were highly motivated to participate in the program. Their motivations included a desire to give back to society, to help people and to give meaning to their illness. Both experienced and inexperienced APs were confident in their ability to accompany others. They were aware of their responsibilities and its limits regarding their role as an AP. They pointed out the program’s positive impact on their own emotional well-being and that of the patients. The program also benefited the clinical team, by limiting unhelpful demands from patients and saving time for clinicians. However, experienced APs did not feel well integrated into the healthcare team. Conclusions: We concluded that APs are highly motivated to be in the program. They perceived a need for the program in the current health system. They noted its beneficial effects on patients, on themselves, and on the clinical team. However, more resources need to be directed toward integrating APs into healthcare teams. Full article

To promote the resource utilization of high-titanium blast furnace slag (HTBFS) and advance the development of lightweight prefabricated structures, this study developed a lightweight HTBFS concrete composite beam (HTC composite beam) by replacing natural gravel and sand in concrete with HTBFS coarse and fine aggregates, and incorporating fly ash ceramsite to reduce self-weight. Symmetrically two-point bending tests were conducted on five HTC composite beams with different reinforcement ratios and precast heights, one Integrally cast HTC beam, and one ordinary concrete composite beam. The failure modes, load-carrying capacities, and deformation characteristics were evaluated. The loading process was also simulated using Abaqus, and the numerical results were compared with experimental data for validation. The results indicate that HTC composite beams satisfy the plane-section assumption; increasing the reinforcement ratio improves the load-carrying capacity, and the precast height has positive effect of HTC composite beams’ load-carrying. Compared with the ordinary concrete composite beam, the HTC composite beam exhibited a 12.30% higher load-carrying capacity, smaller deflection, and better deformation capacity. Multiple energy-based indices demonstrated that HTC composite beams possess favorable post-cracking plastic deformation capacity and stiffness retention. The difference between the finite element simulations and experimental results was less than 5%, confirming both the reliability of the numerical model and the accuracy of the experimental data. An economic analysis revealed that this structural system has significant potential for carbon reduction and cost savings, with an overall saving of approximately 141,000–500,000 CNY. These findings provide theoretical and engineering support for the application of HTC composite beams in prefabricated construction and have positive implications for reducing project costs and promoting the industrialization and low-carbon development of prefabricated buildings. Full article

Passenger-gathering behavior often triggers safety incidents such as stampedes due to overcrowding, posing significant challenges to public order maintenance and passenger safety. Traditional early warning algorithms for passenger-gathering behavior typically perform only global modeling of image appearance, neglecting the analysis of individual passenger actions in practical 3D physical space, leading to high false-alarm and missed-alarm rates. To address this issue, we decompose the modeling process into two stages: human pose estimation and gathering behavior recognition. Specifically, the pose of each individual in 3D space is first estimated from images, and then fused with global features to complete the early warning. This work focuses on the former stage and aims to develop an accurate and efficient human pose estimation model capable of real-time inference on resource-constrained devices. To this end, we propose a 3D human pose estimation framework that integrates a hybrid spatio-temporal Transformer with three collaborative agents. First, a reinforcement learning-based architecture search agent is designed to adaptively select among Global Self-Attention, Window Attention, and External Attention for each block to optimize the model structure. Second, a feedback optimization agent is developed to dynamically adjust the search process, balancing exploration and convergence. Third, a quantization agent is employed that leverages quantization-aware training (QAT) to generate an INT8 deployment-ready model with minimal loss in accuracy. Experiments conducted on the Human3.6M dataset demonstrate that the proposed method achieves a mean per joint position error (MPJPE) of 42.15 mm with only 4.38 M parameters and 19.39 GFLOPs under FP32 precision, indicating substantial potential for subsequent gathering behavior recognition tasks. Full article

Europe’s hydrogen strategy has centred almost exclusively on green hydrogen produced through renewable electrolysis as the cornerstone of its decarbonisation agenda. However, recent discoveries of naturally occurring “white hydrogen” in France, Spain, and other parts of Europe raise the prospect of a new, abundant, and low-cost clean energy resource. White hydrogen, generated geologically and extractable directly from subsurface reservoirs, could complement or even disrupt the current power-to-X pathway by offering production costs estimated at €0.75–1 per kilogram, far below today’s €6–8 for green hydrogen. Early geological findings suggest potentially vast reserves, yet the scale, renewability, and environmental impacts remain uncertain. This policy note critically reassesses the European Union’s hydrogen strategy in light of these developments, examining the economic, environmental, and regulatory implications of integrating white hydrogen. It argues for a balanced, adaptive approach: continuing to scale green hydrogen to meet near-term decarbonisation targets while fostering exploration, regulation, and pilot projects for white hydrogen. Such an approach can safeguard Europe’s climate ambitions, mitigate energy security risks, and avoid stranded investments, while positioning the EU to benefit if natural hydrogen proves viable at scale. Full article

It is widely recognized that outdoor and nature-based educational activities can significantly enhance pupils’ learning, increase environmental awareness and improve pupils’ well-being. At the same time, a growing body of literature supports that the extent to which outdoor learning is implemented depends largely on factors, such as the general institutional context of schools, social and geomorphological aspects and the teacher’s own motivation. The current study employs data collected from 507 primary, middle and high schools in Greece, using a structured questionnaire, and investigates the factors that prevent teachers from engaging in outdoor teaching activities in a green space, as well as those that encourage them to be involved in such educational learning approaches. The results identify institutional barriers, such as the demanding school curriculum, lack of financial resources, limited available time, and insufficient external support, as the main constraints preventing teachers from implementing outdoor activities in nature. On the other hand, it appears that altruistic and intrinsically driven factors, such as personal environmental interest, knowledge of the positive outcomes of environmental education, and a sense of social contribution, are the main factors promoting the adoption of outdoor green education approaches. Availability of green spaces and support by leadership also appear to promote teachers’ engagement in outdoor activities. The findings of the current study highlight the need for educational reforms, to include outdoor, nature-based learning in the school curriculum, provide training and financial support and enhance the confidence of teachers in outdoor, nature-based education. Addressing these barriers could enhance education’s role in fostering sustainable development and reconnecting pupils with nature. Full article