Search Results (460)

Sustainable development in rural communities faces significant challenges, such as inadequate infrastructure, poor resource management, and weak governance, especially in developing countries like Peru. This study aimed to develop a management model tailored to the local needs of smallholder communities in the Junín region, Peru, addressing social, economic, and environmental dimensions to improve quality of life. Using a descriptive mixed-method design with non-experimental and cross-sectional methods, 60 smallholder communities were evaluated based on criteria of access to information and relevance to sustainable development. Data collected through structured surveys and semi-structured interviews revealed a lack of inclusive participation, insufficient economic income, lack of financial transparency, and inadequate environmental practices. The proposed management model integrates strategies to improve community governance, foster inclusive participation, promote sustainable economic practices, and conserve the environment. It concludes that a comprehensive, flexible, and locally adapted approach, emphasizing transparency and community participation, is essential to achieving long-term sustainability in smallholder communities. Full article

Bridging the gap between Artificial Intelligence (AI)-driven generative design and robotic fabrication remains a critical challenge in architectural automation. While Generative Artificial Intelligence (GenAI) tools have advanced conceptual design workflows, their practical deployment in physical construction is hindered by the absence of structured, fabrication-aware datasets to train suitable AI models. This study introduces GDRF (Geometric Data for Robotic Fabrication), an automated pipeline for the generation, evaluation, and encoding of structurally feasible brick wall designs, enabling the creation of machine-learning-compatible data tailored for architectural robotic assembly. We developed a six-stage process that combines parametric modeling, algorithmic design generation, physics-based simulation, data encoding and storage, toolpath generation and assembly simulation, and physical robotic assembly with a robot. Over 33,000 wall configurations were synthetically generated and evaluated for structural stability, of which approximately 52% met the feasibility criteria. Stable and failed designs were identified through displacement-based criteria and encoded using dot-product-based rotational representation, reducing dimensionality while preserving critical geometric features. Comparative analysis revealed that brute-force generation produced more consistent outcomes, while random sampling achieved slightly higher local diversity. This study delivered a data pipeline and the BrickNet dataset, providing a foundation for future research in generative design, structural prediction, and autonomous robotic assembly. Full article

Deep neural network-based deep clustering has achieved remarkable success by unifying representation learning and clustering. However, conventional representation modules are typically not tailored for clustering, resulting in conflicting objectives that hinder the model’s ability to capture semantic structures with high intra-cluster cohesion and low inter-cluster separation. To overcome this limitation, we propose a novel framework called Triple-stream Contrastive Deep Embedding Clustering via Semantic Structure (TCSS). TCSS is composed of representation and clustering modules, with its innovation rooted in several key designs that ensure their synergistic interaction for modeling semantic structures. First, TCSS introduces a triple-stream input framework that processes the raw instance along with its limited and aggressive augmented views. This design enables a new triple-stream self-training clustering loss, which uncovers implicit cluster structures by contrasting the three input streams. Second, within this loss, a dynamic clustering structure factor is developed to represent the evolving semantic structure in the representation space, thereby constraining the clustering-prediction distribution. Third, TCSS integrates semantic structure-aware techniques, including a clustering-oriented negative sampling strategy and a triple-stream alignment scheme based on k-nearest neighbors and centroids, to refine semantic structures both locally and globally. Extensive experiments on five benchmark datasets demonstrate that TCSS outperforms state-of-the-art methods. Full article

Accurate agricultural parcel (AP) delineation from remote sensing imagery is critical for precision agriculture and effective land management. However, parcel boundaries are typically ambiguous, irregular, and challenging to segment precisely. Existing methods often struggle to adequately integrate high-level semantic information with fine-grained boundary details, leading to incomplete or blurred parcel outlines. To address these limitations, we introduce the Interactive Dual-Branch Transformer (IDBT), a novel segmentation framework designed to significantly enhance boundary localization. Our approach incorporates three key innovations: (1) a dual-branch architecture enabling bidirectional interactive information flow between semantic segmentation and boundary detection branches; (2) attention-enhanced Transformer backbones that facilitate optimized multi-scale feature fusion; and (3) a tailored supervision strategy that combines boundary-aware losses with point-wise refinement to sharpen ambiguous parcel edges. Extensive evaluations conducted on two public datasets demonstrate that IDBT outperforms current state-of-the-art methods, achieving high segmentation accuracy and boundary precision. Additionally, our approach exhibits robust transferability in cross-area experiments. Code will be made publicly available at the repository listed in the Data Availability Statement. Full article

Cities around the world are facing growing challenges related to climate change, urban sprawl, infrastructure strain, and digital transformation. In response, smart and sustainable urban development has become a global focus, aiming to integrate technology and environmental stewardship to improve the quality of life. The smart and sustainable city concept is typically applied at the city scale; however, its impact is most tangible at the neighborhood level, where residents interact directly with infrastructure, services, and community spaces. A variety of global frameworks have been developed to assess sustainability and technological integration. However, these models often fall short in addressing localized needs, particularly in regions with distinct environmental and cultural contexts. In Saudi Arabia, Vision 2030 emphasizes livability, sustainability, and digital transformation, yet there remains a lack of tailored tools to evaluate smart and sustainable progress at the neighborhood scale. This study develops HayyScore, a localized evaluation framework and prototype digital platform developed to assess neighborhood performance across five core categories: (i) Environment and Urban Resilience, (ii) Smart Infrastructure and Governance, (iii) Mobility and Accessibility, (iv) Quality of Life and Social Inclusion, and (v) Economy and Innovation. The HayyScore platform operationalizes this framework through an interactive web-based tool that allows users to input data through structured forms, calculate scores, receive category-based and overall certification levels, and view results through visual dashboards. The methodology involved a comprehensive review of global frameworks, expert input to define localized indicators, and iterative prototyping of the platform using Python 3.13.5 and Streamlit 1.45.1. To demonstrate its practical application, the prototype was tested on two Saudi neighborhoods: King Abdullah Petroleum Studies and Research Center (KAPSARC) and King Fahd University of Petroleum and Minerals (KFUPM). Key platform features include automated scoring logic, category weighting, certification generation, dynamic performance charts, and a rankings page for comparing multiple neighborhoods. The platform is designed to be scalable, with the ability to add new indicators, support multilingual access, and integrate with real-time data systems in future iterations. Full article

Foster carers are a hard-to-reach population who carry a vast bureaucratic and emotional load. They need tailored and specialised training, support, and advice regarding the digital lives of the children and young people (CYP) they care for. Looked-after CYP are vulnerable in multiple ways and are particularly at risk in the digital age. Their susceptibility to online risks raises complex challenges. The training programme Fostering in a Digital Age was designed to support foster carers’ understanding of and responses to the digital lives of looked-after CYP, including both positive and negative aspects. It is research-informed and provides relevant knowledge, resources, tools, and skills. This exploratory study sought the opinions of foster carers and social workers regarding the strengths and limitations of the programme and recommendations for improving it. Semi-structured interviews were conducted with ten foster carers who had completed the programme and ten social workers who accessed the programme for evaluation purposes. Participants’ experiences and reflections were analysed using thematic analysis. Resulting themes highlighted the relevance of the training programme, with participants recognising the importance of digital lives for looked-after CYP and the need for tailored guidance. The programme was viewed as flexible, accessible, and user-friendly, with comprehensive coverage of key concepts and reflective activities that enhanced carers’ understanding and confidence. Its child-centred and sustainable design enabled carers to apply learning “as and when” needed and to collaborate with CYP to promote safer digital engagement. However, some participants found the volume of resources overwhelming and reported navigation challenges or digital anxiety. Social workers emphasised professional and structural improvements, while carers focused on the programme’s relational benefits and practical relevance. Both groups recommended wider promotion through local authorities and fostering agencies and adaptations to make the programme suitable for social workers and carers with differing digital skills. Overall, fostering in a digital age effectively provided foster carers with tailored knowledge to support CYP online, prevent harm, and respond to adverse digital experiences, aligning with Self-Determination Theory by supporting carers’ autonomy, competence, and relatedness. This evaluation also revealed gaps in online safety knowledge among both foster carers and social workers, highlighting opportunities for the development of future training programmes. Full article

In response to growing clinical demands for more targeted and effective immunotherapies to treat cancer, biomaterial-based strategies have emerged as powerful tools for locally regulating immune responses. Among these, hydrogels, a class of biocompatible and tunable polymeric networks, are increasingly being leveraged for their high versatility and adaptability for creating tailored immune environments. By enabling controlled delivery of immune cues and direct cellular engineering, hydrogels utilized in vivo can precisely regulate both innate and adaptive immune responses while minimizing systemic toxicity. In this review, we outline essential hydrogel design features necessary for in vivo functionality including injectability, degradation kinetics, and immune-specific functionalization. Building on these principles, we explore how hydrogels have been employed to enhance T cell activation and dendritic cell maturation and guide macrophage reprogramming. Beyond cellular modulation, we further examine the use of hydrogels for cytokine and immunoregulatory agent delivery, tumor microenvironment remodeling, and the creation of tertiary-like lymphoid structures. Finally, we review recently completed and ongoing clinical trials of hydrogels in the cancer immunotherapy space. Together, these insights underscore the growing potential of in vivo hydrogel systems as immuno-interactive platforms capable of reshaping immune responses across diverse disease contexts. Full article

Bike lending offers a service that enables individuals to borrow bicycles for short-term use (i.e., ranging from 2 hours to 36 months), typically from designated locations within cities, campuses, or communities. Unlike bikesharing systems that typically rely on automated kiosks and/or undocked and free-floating devices for public access, bike lending involves a managed program with staff, similar to a library model. These programs can be administered by community organizations, bike shops, public libraries, and other local entities. They are typically community- or membership-based, with many programs associated with non-profit organizations or publicly owned and operated. In this paper, we investigate bike lending in the United States and Canada as of Spring 2024, including a literature review, the identification and characterization of bike lending programs (n = 55), expert interviews (n = 24), a survey of bike lending operators (n = 31), and 2 focus groups with a total of 12 participants. Insights from expert interviews and operator surveys highlight the experiences of professionals involved in bike lending. The focus groups capture the experiences of bike lending users. This paper finds that North American bike lending is often tailored to the specific needs of communities, such as youth, low-income individuals, and the general population. More sustained funding could support program expansion and diversify bike offerings. Enhancing cycling infrastructure, such as adding dedicated bike lanes and paths, could improve overall cycling safety and increase participation in bike lending programs. This study’s findings could help strengthen existing bike lending programs, guide the development of new initiatives and supportive policies, and enhance safe bicycle use for participants. Full article

This study systematically investigates the corrosion inhibition mechanism of imidazoline (IM) and gallic acid (GA) within boron nitride-reinforced epoxy-phenolic composite coatings (GIBE) for subsea crude oil pipelines. Microstructural characterization via field emission scanning electron microscopy (FE-SEM) and energy-dispersive X-ray spectroscopy (EDS) confirms the formation of a molecularly dispersed system in acetone, wherein IM promotes interfacial passivation through amino-metal coordination bonding with the substrate. Electrochemical impedance spectroscopy (EIS) demonstrates a strong positive correlation between IM content and corrosion resistance. GA facilitates self-healing capacity by forming Fe³⁺-chelated barriers at localized defects (as verified by X-Ray photoelectron spectroscopy (XPS) analysis of Fe³⁺–GA complexes); however, its inherent hydrophilicity introduces microchannels, as evidenced by a 28.6% reduction in the water contact angle, which ultimately compromises the barrier performance at elevated concentrations. The optimized formulation (5 wt.% IM with 2 wt.% GA) exhibits protective performance in simulated seawater at 60 °C: after 7 days of immersion, the low-frequency impedance modulus (|Z|_0.01Hz) reaches 6.28 × 10¹⁰ Ω·cm² with no visible corrosion at scribed regions; after 28 days, |Z|_0.01Hz remains above 10¹⁰ Ω·cm², surpassing the service durability threshold of conventional epoxy coatings under high-temperature saline conditions. This work proposes a novel engineering approach for designing anti-corrosion coatings tailored to marine extreme environments. Full article

This paper presents the design and implementation of a vision-based score detection system tailored for smart IoT basketball applications. The proposed architecture leverages a compact, low-cost device comprising a high-resolution overhead camera and a Raspberry Pi 5 microprocessor equipped with a hardware accelerator for real-time object detection. The detection pipeline integrates convolutional neural networks (YOLO-based) and custom preprocessing techniques to localize the basketball hoop and track the ball trajectory. A scoring event is confirmed when the ball enters the defined scoring zone with downward motion over multiple frames, effectively reducing false positives caused by occlusions, multiple balls, or irregular shot directions. The system is part of a scalable IoT analytics platform known as Koško, which provides real-time statistics, leaderboards, and user engagement tools through a web-based interface. Field tests were conducted using data collected from various public and school courts across Niš, Serbia, resulting in a robust and adaptable solution for automated basketball score monitoring in both indoor and outdoor environments. The methodology supports edge computing, multilingual deployment, and integration with smart coaching and analytics systems. Full article

Silicon (Si) anodes offer ultrahigh theoretical capacity (~4200 mAh g⁻¹) for next-generation lithium-ion batteries but suffer from severe mechanical degradation due to repetitive volume expansion (>300%). Conventional electrode-centric strategies face scalability limitations, shifting focus to electrolyte engineering as a critical solution. This review synthesizes recent advances in liquid electrolyte design for stabilizing Si anodes, emphasizing three key pillars: (i) Lithium salts that enable anion-derived inorganic-rich solid electrolyte interphase (SEI) layers with high fracture toughness; (ii) Solvent systems including carbonates, ethers, and phosphonates, where fluorination and steric hindrance tailor SEI elasticity; (iii) Functional additives (F/B/Si-containing) that form mechanically compliant interphases and scavenge detrimental species. Innovative architectures—high-concentration electrolytes (HCEs), localized HCEs (LHCEs), and weakly solvating electrolytes—are critically assessed for their ability to decouple ion transport from volume strain. The perspective highlights the imperative of hybrid solid–liquid interfaces to enable commercially viable Si anodes. Full article

Insulator defect detection in power inspection tasks faces significant challenges due to the large variations in defect sizes and complex backgrounds, which hinder the accurate identification of both small and large defects. To overcome these issues, we propose a novel dual-branch YOLO-based algorithm (DB-YOLO), built upon the YOLOv11 architecture. The model introduces two dedicated branches, each tailored for detecting large and small defects, respectively, thereby enhancing robustness and precision across multiple scales. To further strengthen global feature representation, the Mamba mechanism is integrated, improving the detection of large defects in cluttered scenes. An adaptive weighted CIoU loss function, designed based on defect size, is employed to refine localization during training. Additionally, ShuffleNetV2 is embedded as a lightweight backbone to boost inference speed without compromising accuracy. We evaluate DB-YOLO on the following three datasets: the open source CPLID, a self-built insulator defect dataset, and GC-10. Experimental results demonstrate that DB-YOLO achieves superior performance in both accuracy and real-time efficiency compared to existing state-of-the-art methods. These findings suggest that the proposed approach offers strong potential for practical deployment in real-world power inspection applications. Full article

Background/Objectives: The optimal duration of antibiotic therapy for bacterial prosthetic joint infections (PJI) remains a topic of considerable debate. Current recommendations are often based on limited evidence and expert consensus. Emerging data suggest that shorter antibiotic courses may be as effective as prolonged treatments in select cases. Shortening the duration of therapy offers several advantages, including a reduced risk of bacterial resistance, fewer adverse events, and cost savings. However, this approach must be carefully balanced with the individual patient’s risk of treatment failure. This narrative review aims to synthesize current evidence regarding the duration of antibiotic therapy in PJIs, according to surgical strategies—DAIR (debridement, antibiotics, and implant retention), one-stage exchange, two-stage exchange, and resection without reimplantation—and to identify parameters that may guide individualized and potentially shortened regimens. Methods: We conducted a comprehensive search of PubMed, Embase, and Cochrane Library databases through January 2025, including observational studies, randomized controlled trials, and international guidelines. Reference lists of key articles were also screened. Results: Studies on DAIR suggest that longer regimens (e.g., 8–12 weeks) are necessary, especially in staphylococcal infections, as confirmed by the DATIPO trial, which showed higher failure rates with 6 weeks compared to 12 weeks. Evidence on one-stage exchange is limited but increasingly suggests that 6 weeks may be sufficient in selected patients; however, no dedicated trial has confirmed this. In two-stage exchange, small retrospective series report successful outcomes with short antibiotic therapy combined with local antibiotics, but randomized trials show trends favoring longer regimens. For patients treated with permanent resection arthroplasty, arthrodesis, or amputation, antibiotic durations are highly variable, with few robust data. Across all strategies, most studies are limited by methodological weaknesses, including small sample sizes, retrospective design, lack of microbiological stratification, and heterogeneous outcome definitions. Conclusions: Despite growing interest in shortening antibiotic durations in PJIs, high-quality evidence remains limited. Until additional randomized trials are available—particularly in one- and two-stage exchange settings—12 weeks remains the safest reference duration for most patients, especially those with retained hardware. Future studies should incorporate stratification by infection type, causative organism, and host factors to define tailored and evidence-based antibiotic strategies. Full article

Informal settlements, urban areas with substandard housing conditions and inadequate infrastructure, are increasing in Africa’s sub-Saharan cities, fueled by rapid urbanization, economic challenges, and high housing prices. However, developers often ignore the green building (GB) concept when upgrading housing conditions for these communities. This study aims to investigate GB design strategies specifically for residential structures in Akabahizi to identify and propose practical strategies suitable for informal settlements such as Akabahizi and to develop sustainable housing solutions that enhance environmental quality and meet the needs of residents. Simulation software and combined qualitative and quantitative data collection techniques, including field surveys, interviews, and assessments of existing building conditions, constitute the methodology used in this study. The focus was on the influence of climatic factors, including temperature, precipitation, and wind, on design choices, particularly GB design and current residential buildings in Akabahizi. Based on the survey, 82.5% of residents support the GB concept, 87.4% recognize the importance of GB for community well-being, and 97.1% recognize the benefits of integrating energy-efficient technology for residents’ well-being. Questionnaire findings were considered in decision-making for the design of the new proposed structure to address challenges in the area. Optimized energy efficiency, daylight access, and thermal comfort resulting from courtyard design support GB design incorporating a courtyard as a robust and culturally relevant sustainable design framework tailored for Akabahizi. The courtyard provides green space that promotes social interaction, improves air quality, and delivers natural cooling elements that are essential for residential housing. The proposed new design, with green roof and renewable energy devices, improved material usage, and natural ventilation elements, outperformed the existing one in terms of lower levels of carbon emission for environmental protection. In conclusion, a collaborative effort is needed among various stakeholders, including architects, urban planners, and educational institutions, to promote and implement sustainable building practices. The study suggests that enhancing awareness, offering training opportunities, and empowering local professionals and residents alike can pave the way for improved living conditions and sustainable urban development in Akabahizi and similar informal settlements. Full article

A significant gap in specific nutritional guidelines for ruminants with compromised health exists. Due to their unique anatomy, physiology, and metabolic processes, further research is needed to establish accurate, evidence-based recommendations tailored to these animals. This review highlights the critical role of clinical ruminant nutrition and provides provisional recommendations based on studies in other species (e.g., changes in nutrient requirements in different morbidities available for humans and less for companion animals). These suggestions should be interpreted cautiously until more definitive, species-specific data become available. The review includes the foundational principles of clinical nutrition in ruminants, with particular emphasis on the pathophysiology of nutrient utilization. It explores the roles of energy, protein, vitamins, and minerals during illness or injury and discusses how these nutrients can be strategically applied in clinical interventions. Considerations for designing diets for compromised ruminants are also addressed, considering both physiological needs and the challenges posed by illness and injury states. Practical aspects of diet delivery during treatment are examined, including the indications, benefits, limitations, and potential side effects of route of feeding. Clinical nutrition can be administered orally, enterally (including rumen delivery) or parenteral, depending on the localization of the pathology and the integrity of the alimentary tract. Nutrients should be provided based on livestock requirements and pathophysiology and severity of the primary morbidity. Oral or ruminal provision of diet should be prioritized to maintain rumen functionality. Additionally, a list of pharmaconutrients with potential clinical applications in ruminant medicine is presented to encourage future research and integration into veterinary practice. The success of clinical nutritional interventions can be measured by improvements in appetite, behavior, and health of the compromised ruminant. Full article