Search Results (190)

Precise identification and quantification of fish movement states are of significant importance for conducting fish behavior research and guiding aquaculture production, with object tracking serving as a key technical approach for achieving behavioral quantification. The traditional DeepSORT algorithm has been widely applied to object tracking tasks; however, in practical aquaculture environments, high-density cultured fish exhibit visual characteristics such as similar textural features and frequent occlusions, leading to high misidentification rates and frequent ID switching during the tracking process. This study proposes an underwater fish object tracking method based on the improved DeepSORT algorithm, utilizing ResNet as the backbone network, embedding Deformable Convolutional Networks v2 to enhance adaptive receptive field capabilities, introducing Triplet Loss function to improve discrimination ability among similar fish, and integrating Convolutional Block Attention Module to enhance key feature learning. Finally, by combining the aforementioned improvement modules, the ReID feature extraction network was redesigned and optimized. Experimental results demonstrate that the improved algorithm significantly enhances tracking performance under frequent occlusion conditions, with the MOTA metric improving from 64.26% to 66.93% and the IDF1 metric improving from 53.73% to 63.70% compared to the baseline algorithm, providing more reliable technical support for underwater fish behavior analysis. Full article

The increasing disparity in global food distribution has amplified the urgency of addressing food waste and food insecurity, both of which exacerbate economic, environmental, and social inequalities. Traditional food bank models often struggle with logistical inefficiencies, limited accessibility, and a lack of transparency in food distribution, hindering their effectiveness in mitigating these challenges. This study proposes a novel Food Bank Network Redesign (FBNR) that leverages the Quito Metro system to create a decentralized food bank network, enhancing efficiency and equity in food redistribution by introducing strategically positioned donation lockers at metro stations for convenient drop-offs, with donations transported using spare metro capacity to designated stations for collection by charities, reducing reliance on dedicated transportation. To ensure transparency and operational efficiency, we integrate a blockchain-based traceability system with smart contracts, enabling secure, real-time tracking of donations to enhance stakeholder trust, prevent food loss, and ensure regulatory compliance. We develop a multi-objective optimization framework that balances food waste reduction, transportation cost minimization, and social impact maximization, supported by a mixed-integer linear programming (MIP) model to optimize donation allocation based on urban demand patterns. By combining decentralized logistics, blockchain-enhanced traceability, and advanced optimization techniques, this study offers a scalable and adaptable framework for urban food redistribution, improving food security in Quito while providing a replicable blueprint for cities worldwide seeking to implement circular and climate-resilient food supply chains. Full article

Road crashes impose significant societal costs, and while links between static land use and safety are established, the long-term impacts of dynamic land use conversions remain under-explored. This study addresses this gap by investigating and quantifying how specific land use transitions over a decade influence subsequent road crash frequency in Metropolitan Melbourne. Our objective was to understand which conversion pathways pose the greatest risks or offer safety benefits, informing urban planning and policy. Utilizing extensive observational data covering numerous land use conversions, we employed Negative Binomial models (selected as the best fit over Poisson and quasi-Poisson alternatives) to analyze the association between various transition types and crash occurrences in surrounding areas. The analysis revealed distinct and statistically significant safety outcomes. Major findings indicate that transitions introducing intensified activity and vulnerable road users, such as converting agricultural land or parks to educational facilities (e.g., Agri → Edu, coefficient ≈ +0.10; Park → Edu, ≈+0.12), or intensifying land use in previously less active zones (e.g., Park → Com, ≈+0.07; Trans → Park, ≈+0.10), significantly elevate long-term crash risk, particularly when infrastructure is inadequate. Conversely, conversions creating low-traffic, nature-focused environments (e.g., Water → Park, ≈–0.16) or channeling activity onto well-suited infrastructure (e.g., Trans → Com, ≈–0.12) demonstrated substantial reductions in crash frequency. The critical role of context-specific infrastructure adaptation, highlighted by increased risks in some park conversions (e.g., Com → Park, ≈+0.06), emerged as a key mediator of safety outcomes. These findings underscore the necessity of integrating dynamic, long-term road safety considerations into land use planning, mandating appropriate infrastructure redesign during conversions, and prioritizing interventions for identified high-risk transition scenarios to foster safer and more sustainable urban development. Full article

This study evaluated the effects of different clear aligner (CA) designs on forces and moments during maxillary second molar distalization. Four designs were tested: attachment only (group 1), neither attachment nor enhanced structure (group 2), a combination of attachment and enhanced structure (group 3), and enhanced structure only (group 4). CAs were fabricated from thermoformed polyethylene terephthalate glycol with 30 CAs per group. Forces and moments were measured using a multi-axis transducer as the molars were distally displaced by 0.25 mm. All groups experienced buccodistal and intrusive forces. Group 3 showed the highest distalizing force (Fy = 2.51 ± 0.37 N) and intrusive force (Fz = −2.04 ± 0.48 N) and also the largest rotational moment (Mz = 3.89 ± 0.71 Nmm). Groups 3 and 4 (with enhanced structures) demonstrated significant intrusive forces (p < 0.05). Most groups exhibited mesiodistal angulation, lingual inclination, and distal rotational moments. Group 2 had the lowest moment-to-force ratio (Mx/Fy = 3.27 ± 0.44 mm), indicating inefficient bodily movement. Group 3 demonstrated significantly greater moments across all axes compared to other groups. The results indicate that designs incorporating enhanced structures with attachments increase CA stiffness and applied forces/moments, enhancing distalization efficiency while minimizing vertical side effects. This suggests that, clinically, reinforced CAs can serve as a simple yet effective modification to existing protocols in Class II orthodontic cases, enabling more efficient molar distalization without requiring complete appliance redesign or additional fabrication and allowing easy adaptation to individual treatment needs. Full article

Maintaining quality of life through functional autonomy is crucial for supporting aging in place. While assistive technologies and architectural adaptations have received significant attention, there is limited knowledge on how older adults independently adapt domestic routines using everyday household products. Background/Objectives: This study aimed to explore how functionally independent older adults manage key domestic tasks and to identify user-driven adaptations that could inform inclusive product design. Methods: We conducted a qualitative field study involving non-participant observations and in-depth case studies with 20 older adults aged 65–85 living in urban Chile. Participants were observed while performing cooking, dishwashing, and waste disposal activities. Thematic analysis and axial coding, based on grounded theory principles, were applied to identify adaptation strategies and usability barriers. Results: Participants employed a range of adaptation strategies across tasks, including temporal redistribution of effort, spatial reorganization, informal tool use, and reliance on social support. These adaptations reflected creative and situated responses to physical and environmental constraints. Many strategies could be interpreted as emergent user solutions, offering practical insights for the inclusive and low-cost redesign of everyday objects. Conclusions: Older adults actively modify their interactions with domestic environments to preserve autonomy and functionality. Recognizing and incorporating these emergent user adaptations into product design processes can strengthen inclusive design practices, support aging in place, and inform public health strategies aimed at promoting independence among aging populations. Full article

This study investigates the integration of ChatGPT in Philippine higher education institutions (HEIs) through narrative inquiry, employing Clandinin and Connelly’s three-dimensional framework (temporality, sociality, place) to explore the lived experiences of 18 participants (10 students, 8 faculty). The research identifies three global themes: (1) the need for strong ethical guidelines amid widespread but tacit “silent acceptance” of AI use, (2) faculty efforts to adapt traditional pedagogy while addressing concerns about critical thinking erosion, and (3) strategies to optimize ChatGPT’s utility without exacerbating inequities. Participant narratives reveal divergent adoption patterns: urban stakeholders leverage ChatGPT for efficiency and learning augmentation, while rural counterparts face infrastructural barriers that deepen the urban–rural divide. Students report evolving ethical engagement, from initial dependency to reflective use, whereas faculty grapple with academic integrity and assessment redesign. The findings underscore how cultural resistance, institutional policy gaps, and technological disparities shape ChatGPT’s uneven adoption, reinforcing existing educational inequalities. This study contributes to the literature on AI in education by proposing context-sensitive strategies for equitable integration, including offline AI tools for rural areas, faculty training programs, and transparent policy frameworks. By centering stakeholder narratives, the research advocates for culturally grounded AI adoption that balances innovation with pedagogical integrity, offering a model for Global South contexts facing similar challenges. Full article

The transition from a linear to a more circular economy has pressured companies from different sectors to implement circular business strategies and redesign their existing business models or even create new ones. The aim of this investigation is to identify the different circular business strategies adopted by Portuguese companies in the textile and clothing industry and evaluate their impact on the sustainability of the business. This article presents a framework of strategies to guide managers in addressing the challenges of moving from fast to more sustainable fashion. This exploratory research is based on a qualitative methodology, relying on semi-structured interviews with the managers of six companies in the textile and clothing sector in Portugal that have implemented circular practices. The primary data collection took place between 20 July and 30 September 2022. The results show that companies have supported their circular economy practices mainly through product life extension strategies (mostly based on durable product design) and resource use reduction strategies, with resource recovery being the most common. The use of personalized product design and clothing repair strategies is still largely unexplored by companies. The findings also suggest that companies have to adapt their way of production and market relationships with consumers in order to accommodate the practices of a circular economy in their businesses. In the future, a quantitative approach could also provide new insights, as well as longitudinal and cross-country comparison studies. Full article

Accurate detection of dangerous driving behaviors is crucial for improving the safety of intelligent transportation systems. However, existing methods often struggle with limited feature extraction capabilities and insufficient attention to multiscale and contextual information. To overcome these limitations, we propose YOLO-AFR (YOLO with Adaptive Feature Refinement) for dangerous driving behavior detection. YOLO-AFR builds upon the YOLOv12 architecture and introduces three key innovations: (1) the redesign of the original A2C2f module by introducing a Feature-Refinement Feedback Network (FRFN), resulting in a new A2C2f-FRFN structure that adaptively refines multiscale features, (2) the integration of self-calibrated convolution (SC-Conv) modules in the backbone to enhance multiscale contextual modeling, and (3) the employment of a SEAM-based detection head to improve global contextual awareness and prediction accuracy. These three modules combine to form a Calibration-Refinement Loop, which progressively reduces redundancy and enhances discriminative features layer by layer. We evaluate YOLO-AFR on two public driver behavior datasets, YawDD-E and SfdDD. Experimental results show that YOLO-AFR significantly outperforms the baseline YOLOv12 model, achieving improvements of 1.3% and 1.8% in mAP@0.5, and 2.6% and 12.3% in mAP@0.5:0.95 on the YawDD-E and SfdDD datasets, respectively, demonstrating its superior performance in complex driving scenarios while maintaining high inference speed. Full article

As faculty in a college of education, we have undertaken a multi-year process to redesign pathways leading to teacher certification. Throughout this process, we have confronted challenges in recruiting and retaining teachers, concluding these issues stem from deeper inequities in the current design of the education workforce. To address this, we have implemented new models of educator preparation designed to foster social justice and ensure educators and students alike can thrive. These models emphasize the roles of educators and how they work together as a team with distributed expertise with embedded growth opportunities, and clear paths for career advancement. These models are designed to create inclusive and supportive environments. Central to this redesign, we created holistic systems of care, mitigated long-standing barriers to entry, specialization, and advancement for educators, and liberated content, resulting in increased access for individuals wanting to become educators. In this article, we share insights from our journey of redesigning educator preparation to meet the needs of preservice teachers equipping them to adapt skillfully to dynamic educational demands. Our work aims to reshape educator preparation through fostering a more inclusive, resilient, and sustainable workforce adept to the needs of ever-shifting educational systems. Full article

Background: Resilience is a cornerstone attribute for nursing students, enabling them to adapt to stressful situations encountered during their educational journey and subsequent healthcare career. Objective: This qualitative study aimed to explore nursing instructors’ experiences promoting resilience among nursing students during clinical education. Methods: Focus groups were conducted with 27 instructors from four nursing colleges in Thailand. Data were analyzed using Braun and Clarke’s inductive thematic analysis approach, guided by the Unitary Caring Science Resilience-Building Model. Results: Two main themes emerged: (1) Challenges to Nursing Students’ Resilience and (2) Support Strategies for Enhancing Resilience. Challenges included bridging theory and practice, upholding confidence in clinical skills, adapting to new clinical environments, and managing expectations. Support strategies encompassed providing comprehensive preparation, fostering open communication, implementing peer support systems, and utilizing reflective practice. Conclusions: The findings highlight the complex interplay of factors affecting nursing students’ resilience and the multifaceted approaches instructors use to support it. This study underscores the need for a holistic approach to nursing education that addresses clinical competence and psychological well-being. Implications include curriculum redesign to bridge the theory–practice gap, enhanced instructor training in mentorship and resilience-building, implementation of comprehensive student support systems, and technology integration to support learning and resilience. Full article

IMUs (inertial measurement units) and cameras are popular sensors for autonomous localization due to their convenient integration. This article proposes a collaborative localization method, the CICEKF (collaborative IMU-aided camera extended Kalman filter), with a loosely coupled and two-step structure for the autonomous locomotion estimation of collaborative robots. The first step is for single-robot localization estimation, fusing and connecting the IMU and visual measurement data on the velocity level, which can improve the robustness and adaptability of different visual measurement approaches without redesigning the visual optimization process. The second step is for estimating the relative configuration of multiple robots, which further fuses the individual motion information to estimate the relative translation and rotation reliably. The simulation and experiment demonstrate that both steps of the filter are capable of accomplishing locomotion estimation missions, standalone or collaboratively. Full article

Future systems of systems (SoSs) must adapt rapidly to evolving environments and stakeholder needs, yet conventional system engineering approaches often lack the flexibility to accommodate such change without costly re-engineering. Addressing this gap, this study proposes a novel, generic architecture model for self-organized adaptive platform SoSs, emphasizing a modular, layered structure that enables dynamic integration and reconfiguration of sub-units for diverse missions. The research is grounded in a comprehensive review of complex SoS theory and platform system design, focusing on physical platforms with central management. Methodologically, this study develops a logical architecture for electronics and software, detailing the roles and interactions of each architectural layer and component. The model’s efficacy is demonstrated through its application to the F-35 Joint Strike Fighter, where it identified opportunities to enhance the aircraft’s adaptability and self-organization. Results indicate that early adoption of this generic architecture can significantly reduce design and redesign costs, prevent over-specification, and promote lifecycle adaptability across various platform types—including land, air, and sea systems. The proposed architecture thus offers a robust foundation for future adaptive SoSs, supporting efficient evolution in response to unpredictable operational demands. Full article

Accurately detecting rice panicles in complex field environments remains challenging due to their small size, dense distribution, diverse growth directions, and easy confusion with the background. To accurately detect rice panicles, this study proposes OE-YOLO, an enhanced framework derived from YOLOv11, incorporating three synergistic innovations. First, oriented bounding boxes (OBB) replace horizontal bounding boxes (HBB) to precisely capture features of rice panicles across different heights and growth stages. Second, the backbone network is redesigned with EfficientNetV2, leveraging its compound scaling strategy to balance multi-scale feature extraction and computational efficiency. Third, a C3k2_DConv module improved by dynamic convolution is introduced, enabling input-adaptive kernel fusion to amplify discriminative features while suppressing background interference. Extensive experiments on rice Unmanned Aerial Vehicle (UAV) imagery demonstrate OE-YOLO’s superiority, achieving 86.9% mAP50 and surpassing YOLOv8-obb and YOLOv11 by 2.8% and 8.3%, respectively, with only 2.45 M parameters and 4.8 GFLOPs. The model has also been validated at flight heights of 3 m and 10 m and during the heading and filling stages, achieving mAP50 improvements of 8.3%, 6.9%, 6.7%, and 16.6% compared to YOLOv11, respectively, demonstrating the generalization capability of the model. These advancements demonstrated OE-YOLO as a computationally frugal yet highly accurate solution for real-time crop monitoring, addressing critical needs in precision agriculture for robust, oriented detection under resource constraints. Full article

Refugee camps are typically designed as temporary sustainable settlements, prioritizing logistics over cultural considerations, which can lead to environments being misaligned with the lived experiences of displaced populations. This study addresses the challenge of traditional humanitarian camp designs that prioritize logistical efficiency over cultural and socio-cultural needs, leading to environments that do not align with the lived experiences of displaced populations. Focusing on the Zaatari Syrian Refugee Camp in Jordan, the research employs a structured questionnaire distributed among 102 households to investigate how refugees have reconfigured the camp’s original grid layout into more cohesive clustered patterns, informed by the principles of defensible space theory. Key findings reveal that refugees actively transform public courtyards into semi-private spaces, driven by cultural imperatives and safety needs. Statistical analyses confirm significant correlations between clustering behaviors and the attributes of defensible space, particularly the zones of influence and boundary demarcation, enhancing community resilience and accessibility. However, the study finds a limited predictive power overall, indicating that while these adaptations are significant, factors such as natural surveillance and territorial behavior do not exhibit strong influences on clustering dynamics. These findings have important implications for humanitarian planning and design. They highlight the necessity for more culturally sensitive and flexible approaches that prioritize refugee agencies and communal identity in camp layouts. This research advocates for a hybrid planning approach that integrates socio-cultural values, promoting resilience and quality of life among refugees. By aligning spatial designs with the social and cultural realities of refugee communities, humanitarian actors can enhance the effectiveness of their interventions, ultimately contributing to more sustainable and inclusive urban environments as part of broader goals related to urban planning and development. Future research is encouraged to explore these practices in diverse refugee contexts, providing further validation of these findings and enhancing the applicability of these design principles in global humanitarian efforts. Full article

Cereals are the basis of the human diet, and among them, after rice and corn, wheat is the most cultivated in the world. Drought, conflicts, and high prices affect food security in many countries. The CHANGE-UP project funded by the PRIMA program aims at redesigning agricultural systems for the Mediterranean area to make them more resilient to climate change, and includes, among other agronomic innovations, the cultivation and characterization of perennial wheat genotypes. In this study, four perennial wheat lines, 235a, 20238, OK72, and 11955, grown in Italy, were examined for their technological and chemical composition and rheological properties and compared with the perennial species Thinopyrum intemedium (Kernza^®) and to a modern durum wheat variety, used as controls. On average, all the perennial genotypes presented very small kernels along with high protein content, total antioxidant capacity, and mineral content, and genotypes OK72 and 11955 presented good test weight values. Line 235a had the best gluten quality, whereas line 20238 reported the worst values for bread-making aptitude. Results indicate that perennial grains could adapt to the Italian environment and manifest their nutritional and technological potential, constituting promising raw materials for enhancing diversification in nutrition by sustainable agriculture based on agroecological principles. Full article