Search Results (400)

The management of livestock manure is associated with substantial ammonia (NH₃) emissions and the accumulation of emerging contaminants, including antibiotics, antibiotic resistance genes (ARGs), and microplastics, posing risks to environmental quality and public health. Biochar has emerged as a promising strategy for mitigating gaseous emissions and reducing contaminant mobility during manure storage and composting processes. This review synthesizes recent research on the application of biochar in livestock manure management systems, focusing on NH₃ emissions, antibiotic degradation, ARG reduction, and microplastic removal. Particular attention is given to the effectiveness of biochar in mitigating pollutants during manure storage, housing operations, and composting processes. Across the literature, reported NH₃ mitigation efficiencies vary widely, from negligible effects to reductions exceeding 90–97%, depending on feedstock type, pyrolysis conditions, particle size, and application strategy. Biochar also promotes antibiotic degradation and ARG mitigation, with reductions of up to 98% reported in composting systems. Emerging evidence further suggests that biochar can reduce microplastics by approximately 15–64% in sludge composting. Plant-derived and chemically modified biochars generally outperform manure-derived biochars due to higher surface area, cation exchange capacity, and greater abundance of functional groups. The review highlights that activation treatments, co-composting strategies, and microbial interactions are key factors controlling pollutant mitigation efficiency. Despite promising outcomes, large-scale application remains limited by economic constraints, variability in biochar properties, and the lack of long-term field-scale validation. Future research should prioritize standardized production protocols, field implementation studies, and integrated environmental and economic assessments to support the practical adoption of biochar in sustainable livestock waste management systems. Full article

In Burke County, North Carolina, a Hepatitis A outbreak among unsheltered residents exposed gaps in access to clinic-based care and prompted early, ad hoc “backpack medicine” outreach efforts to deliver care directly in nontraditional settings. While this approach addressed immediate needs, it highlighted the inadequacy of isolated interventions, prompting local partners to pursue more structured, coordinated, and community-driven approaches to homeless health system design. This project report describes how Burke County Public Health, in partnership with the University of North Carolina at Chapel Hill, applied systems thinking, community coalition building, and human-centered design to transition from reactive outreach to a structured, sustainable mobile health delivery model for people experiencing homelessness. Guided by Community Coalition Action Theory (CCAT), partners used human-centered design methods to engage over 40 community stakeholders and 10 individuals with lived experience of homelessness or housing instability. Through empathy mapping, iterative prototyping, and thematic analysis, the team identified priority service gaps, defined operational requirements, and developed prototype service models, while building cross-agency readiness for implementation. Full article

Improving the decoding accuracy and information transfer rate (ITR) of steady-state visual evoked potential brain–computer interface (SSVEP-BCI) systems, while enhancing cross-subject generalization and reducing calibration cost, is essential for practical deployment. This study proposes an end-to-end framework that integrates adaptive filtering with semi-supervised domain adaptation. The framework incorporates a Gabor adaptive filter bank (G-AFB) to optimize time–frequency representations and extract features matched to individual neural responses. It also introduces a three-stage semi-supervised domain-adversarial neural network (TriS-DANN), which combines unsupervised pre-alignment and supervised fine-tuning to align cross-subject feature distributions and enable lightweight calibration. On the 1.0 s public benchmark dataset, G-AFB-tCNN achieved 89.13% accuracy, a 4.63 percentage-point improvement over its conventional filter-bank counterpart. On the 0.4 s in-house dataset, G-AFB-tCNN achieved 91.85% accuracy, a 3.22 percentage-point improvement over the conventional fixed filter bank. In transfer learning, TriS-DANN reached 86.60% accuracy using 0.4 s segments extracted from the stimulation period and only 23.07% of the available target-domain training/calibration trials, demonstrating higher efficiency and stability than conventional fine-tuning. These results support the proposed framework as a feasible route toward reliable, low-calibration SSVEP-BCI systems. Full article

Public spaces in informal settlements are often viewed as congested, unregulated, or residual areas, yet they play a central role in everyday urban life. This paper examines how public spaces are socially produced through everyday appropriation, interaction, and routine use in two informal settlements in Lahore, Pakistan. Using a qualitative comparative case-study design, the study draws on field observations, semi-structured interviews, questionnaires, activity mapping, photographic documentation, and spatial interpretation. The findings show that streets function as multifunctional public spaces rather than simple movement corridors. They support livelihood activities, children’s play, domestic extension, informal mobility, social gathering, and community visibility. The results also show that public space use varies by gender, age, time of day, and settlement morphology, with everyday practices shaped by the interaction between street layouts, housing forms, public–private thresholds, and local socio-cultural routines. The paper concludes that informal public spaces should not be understood only as signs of disorder or planning failure. They are adaptive socio-spatial systems that support livelihood, belonging, and everyday resilience. Recognizing these resident-led spatial practices can inform more sensitive upgrading approaches that improve physical conditions without erasing the social relations and everyday uses through which public space is produced. Full article

The real estate sector continues to face challenges such as inefficiencies, fraud risks, and high transaction costs stemming from opaque processes and heavy reliance on intermediaries. These challenges highlight the need for transparent and efficient solutions to support secure real estate transactions and management. While a growing body of literature has examined blockchain applications in real estate, existing studies are often fragmented and predominantly descriptive, with limited systematic synthesis of evidence and insufficient attention to governance and institutional contexts. This study aims to systematically examine and synthesise the benefits and challenges of blockchain technology in real estate, providing evidence-based insights for practitioners and policymakers. Using a Systematic Literature Review (SLR) approach, peer-reviewed publications from 2016 to 2025 were analysed to identify blockchain applications, reported outcomes, and implementation barriers. The findings reveal that blockchain has been applied in land registration (e.g., Sweden, India, Serbia), valuation systems, decentralised housing finance, and tokenised investment platforms (e.g., Exporo, RealT). The reported benefits include reduced fraud, enhanced transaction efficiency, transparency, and expanded investment access through fractional ownership. However, regulatory uncertainty, scalability limitations, data privacy risks, and low stakeholder awareness remain key barriers. Ethical issues such as digital exclusion and data exposure also require further consideration. Compared with the more advanced adoption observed in Europe and North America, supported by established regulatory frameworks and digital land governance initiatives, this review identifies relatively slower uptake in parts of the Asia-Pacific region, particularly in Australia and Malaysia. It highlights a critical need for future research on legal recognition, privacy-enhancing technologies, and governance frameworks, particularly regarding blockchain applications in property development and urban planning processes. By integrating technological and governance perspectives, this study provides a more comprehensive and structured understanding of blockchain adoption in real estate systems. Full article

Exposure to wildfire smoke has been a growing public health issue with the increasing effects of climate change. The increasing frequency and severity of wildfires fueled by higher global temperatures and shifting climate change patterns have left more people exposed to smoke for longer periods. This exposure is primarily driven by fine particulate matter (PM_2.5) and carbon monoxide (CO) and other toxic gases, causing harmful health impacts, particularly to the respiratory system and cardiovascular system. The potential to reduce health effects is dependent on the adaptive capacity of individuals, households, and communities in anticipating, responding to, and recovering from smoke events. Social vulnerability factors, including socioeconomic status, race/ethnicity, housing quality, and healthcare access, greatly influence how well individuals or communities can prepare for and respond to the effects of wildfire smoke exposure. Although simple protective steps are often possible, more expensive solutions are usually out of reach for the most marginalized groups, showing that the ability to adapt depends on the resources people have. This review aims to analyze the convergence of wildfire smoke exposure, social vulnerability, and adaptive capacity in vulnerable communities with specific reference to approaches to building community resilience. This study adopts a narrative integrative review approach to synthesize current interdisciplinary evidence on the health impacts of wildfire smoke, associated social inequities, and adaptive capacity strategies, while introducing an integrated conceptual framework linking social vulnerability, adaptive capacity, and community resilience. The findings of this review substantiate the necessity of integrated, equity-oriented adaptation responses, such as enhanced risk communication, sustainable climate change mitigation strategies, and improved access to healthcare and infrastructure. In conclusion, strengthening community resilience to wildfire smoke requires confronting structural social inequities while simultaneously enhancing the adaptive capacity of resource-constrained communities. Full article

The urban housing sector plays a significant role in global energy consumption and carbon emissions, making the sustainable transformation of domestic buildings essential to achieving climate goals. Urban housing is also linked to the energy transition, social equity, public health, and environmental resilience. The UK’s Warm Homes Plan (WHP) is seen as a key policy initiative that aims to improve energy efficiency and living conditions, and to promote the transition to a low-carbon future. This study provides an integrated review of retrofit assessment, policy mechanisms, and socio-environmental factors in the context of urban housing decarbonization. This study adopts a structured critical review approach to analyze retrofit strategies, low-carbon heating systems, renewable energy integration, and smart control technologies. The study highlights that retrofit assessment is not limited to technical performance but also includes social acceptability, affordability, and urban infrastructure compatibility. Furthermore, case study comparisons show that decarbonization outcomes are improved when technical measures are integrated with effective governance, stakeholder engagement, and local policy support. This study presents an integrated conceptual framework that links technical retrofit measures, policy coordination, and socio-environmental indicators. The results show that isolated technical solutions are insufficient for decarbonizing urban housing. Rather, a multi-dimensional planning approach is necessary to enable a sustainable, resilient, and socially inclusive housing transition. Full article

Smart city governance increasingly relies on AI-enabled planning systems, digital twins, vulnerability scoring tools, and capital investment platforms to allocate climate-resilient housing and infrastructure investments. Yet existing smart-urbanism and adaptation frameworks do not adequately specify how such systems should encode well-being, equity, and climate uncertainty when translating urban data into ranked projects and funded portfolios. This paper develops the Caring Urban Governance Framework for AI-enabled urban prioritization through a structured scoping review and conceptual framework analysis integrating climate-risk decision-making under deep uncertainty, built-environment pathways affecting psychosocial well-being, and public-sector algorithmic accountability. The framework proposes a five-layer architecture linking urban form and infrastructure, climate exposure and environmental resources, psychosocial mediators of well-being, algorithmic design choices, and institutional governance, with explicit feedback loops. Its main outputs are an auditable decision architecture, eight mechanism-based propositions for empirical testing, an operational specification matrix for objective functions, equity constraints, robust logic, and documentation, and an analytical validation of construct clarity, coherence, literature congruence, and operationalizability. The analysis argues that aligning AI-enabled urban prioritization with SDG 11 requires treating well-being-supportive living conditions as a decision objective, constraining optimization with equity conditions, and institutionalizing auditability and contestability to reduce distributive and psychosocial harm in public investment planning. Full article

As a policy-driven land use transition initiative bridging poverty eradication and sustainable development, China’s Poverty Alleviation Relocation (PAR) program exemplifies how state-led resettlement can reconfigure land use patterns while balancing immediate livelihood security with long-term community capacity development. The integration of large-scale PAR communities into new urbanization is a critical postrelocation task that is essential for consolidating poverty eradication achievements and enhancing endogenous development capacity. This study examined how the configuration of policy instruments shapes the endogenous development capacity of PAR communities during their transition to new urbanization. Employing a “tool–goal” analytical framework, we conducted a content analysis of 38 provincial-level policy documents (2021–present) using NVivo 20 software. The findings reveal that while local governments have established a preliminary policy system, structural imbalances persist: (1) uneven deployment of policy tools, (2) underutilization of demand-based policy tools, (3) tool–goal misalignment, and (4) insufficient market/societal participation in government-led measures. The discussion further reveals that the land use transition in the PAR program emphasizes the “living mode” (housing and public services) over the “livelihood mode” (productive resources and nonagricultural employment), creating structural dependency and leaving industrial land underutilized—as evidenced by weak policy support for industrial development (14.83%) and labour outmigration from resettlement areas. Drawing on the sustainable livelihoods framework, we further demonstrate how this exogenous-dominated policy mix disproportionately enhances physical and financial capital while constraining the accumulation of human and social capital—the very foundations of endogenous development capacity. To address these issues, we propose three key recommendations: (1) optimizing the policy mix to strengthen the endogenous development capacity of PAR communities; (2) realigning policy tools with objectives to achieve diversified yet coordinated goals; and (3) addressing implementation gaps to better leverage market mechanisms and social forces in promoting the sustainable urban integration of resettlement areas. Full article

The housing crisis in rapidly transforming earthquake zones represents the exhaustion of conventional construction paradigms. Unlike single-focused analyses, this study compares conventional reinforced concrete and modular steel systems from a holistic lifecycle perspective, using Turkey as a strategic laboratory for urban transformation. Employing qualitative content analysis, it maps in-depth interviews with 14 sector experts onto a ‘Dialectical Life Cycle Matrix’ via frequency-based consensus indicators. Expert assessments indicate that conventional methods face a structural bottleneck driven by architectural uniformity, labour-related weaknesses, rising costs, and prolonged durations, triggering seismic vulnerability, compromised living quality, and non-circular end-of-life outcomes. Modular systems counter this through factory-controlled rapid production, QA/QC mechanisms, and economies of scale, integrating guaranteed safety and the robust option of steel with R&D-driven human comfort. However, transitioning requires relinquishing deep-rooted advantages—financial flexibility, established order, regulatory comfort, cultural perception, and morphological harmony—introducing local trade-offs: high initial investment, geometric plot and logistical constraints, cultural barriers, and design concerns. Consequently, universal technologies cannot be directly transferred. To overcome Turkey’s local barriers, this study proposes a three-stage transition model: (I) civil and public-led legislative and workforce reforms; (II) financial innovation and gradual hybrid adaptation; and (III) industrial maturation transforming housing into a continuously updated living product. Full article

The real estate market is a complex and dynamic sector that plays a key role in economic stability and wealth generation. In many regions, real estate assets represent around 80% of household wealth, while rising housing prices have turned access to housing into a major social and economic challenge. In this context, the availability of accurate and accessible information is essential for decision-making by buyers, investors, and public administrations. This study proposes the development of an advanced technological tool based on Artificial Intelligence and Machine Learning techniques to predict and analyze real estate market dynamics within a specific geographic area. Using the city of Madrid as a case study, the research presents a digital application capable of estimating the market value of a property by analyzing comparable recently sold properties and incorporating key housing characteristics. By entering an address and a set of property features, the system generates a precise and data-driven valuation. The results demonstrate that AI-based approaches can significantly improve the accuracy and accessibility of real estate valuation processes. The proposed methodology enables real-time price estimation, graphical comparisons, and dynamic market analysis. Furthermore, the framework is scalable and can be extended to other geographic areas where relevant data are available, providing valuable insights for both academic research and practical decision-making in the real estate sector. Full article

Achieving sustainable urban development and optimizing the urban scale structure are central priorities in global governance. However, the relentless population agglomeration in Chinese megacities, despite astronomical living costs, presents a prominent “China Paradox” that seemingly defies classical spatial equilibrium theories. This study decodes this paradox by endogenizing the strategic land supply behaviors of local governments. Utilizing a comprehensive panel dataset of 287 Chinese prefecture-level cities from 2006 to 2020, we construct a multi-dimensional mediation framework and a panel threshold model to investigate how the structural misallocation of land—specifically, the pro-industrial and anti-residential bias—reshapes urban migration dynamics. Empirical results reveal that this land allocation bias acts as the fundamental institutional engine driving urban polarization. Analysis of the transmission pathways reveals a complex push–pull dynamic at the core of this paradox. The artificial restriction of residential land drives up housing prices, generating a profound centrifugal “push” force. However, this dispersion effect is entirely neutralized by two formidable centripetal “pull” forces: industrial co-agglomeration fueled by subsidized manufacturing land, and premium public service capitalization financed through lucrative land revenues. Furthermore, this demographic pull effect exhibits a pronounced inverted U-shaped dynamic, peaking during the rapid growth phase but diminishing precipitously once cities cross the threshold into highly developed megacities (LnGDP > 11.525). These findings highlight the ultimate unsustainability of the land-driven urbanization model. We propose a paradigm shift towards sustainable urban governance, advocating for stage-specific land supply reforms and the transition from monopolistic land finance to a sustainable property tax system to foster a spatially just and resilient urban hierarchy. Full article

Whether urban park supply effectively responds to residents’ actual use remains a critical issue for public service provision, residents’ health and well-being, and spatial equity in high-density cities. Conventional assessments based on static population data may fail to capture dynamic patterns of human activity, potentially obscuring mismatches between service provision and real demand. This study integrates mobile phone signaling data into a supply–demand assessment framework to evaluate urban park systems from a dynamic population perspective. The framework is applied to Shenzhen as a representative high-density megacity. Park supply is measured by service capacity, coverage, and accessibility, while demand is derived from observed visitation behavior. A Supply–Demand Ratio (SDR) index, combined with Getis-Ord Gi* analysis, is employed to identify spatial patterns of mismatch. The results reveal substantial supply–demand imbalances that are not captured by traditional static indicators, with approximately 30.9% of communities identified as significant cold spots. High-density central areas exhibit a persistent deficit in park services despite relatively high coverage levels, whereas peripheral areas with abundant ecological resources show relative surpluses. These patterns are closely associated with urban functional structure, population mobility, and jobs–housing separation. By uncovering the divergence between nominal accessibility and actual use, this study highlights the limitations of place-based planning approaches and underscores the need for a people-centered perspective. The findings point to the importance of shifting from “opportunity equity” to “outcome equity” in evaluating and improving urban public service provision to foster sustainable urban development. Full article

Population aging has become a significant global phenomenon, particularly in developing countries where urban systems are not fully prepared to support older adults. Although the concept of age-friendly cities has been widely promoted, many municipalities still lack an integrated database that links health, social, economic, and environmental dimensions to support policymaking and built-environment improvement. This study aims to develop and validate a four-dimensional healthy aging database framework for assessing age-friendly built environments and public facilities at the municipal level. A mixed-methods approach was employed, combining quantitative surveys, built-environment assessments, and functional ability evaluation using the Barthel Activities of Daily Living Index. The study was conducted in Rangsit Municipality, Thailand, as a case study. The results demonstrate that the proposed framework can systematically integrate multidimensional aging data and identify priority areas for housing improvement, public facility modification, and community services. The framework also supports evidence-based decision-making and place-based policy implementation for age-friendly urban development. This study contributes a practical database framework and assessment tool that can assist local governments in evidence-based, inclusive, and sustainable urban development and aging societies. Full article

The Research and Observation in Medium Earth Orbit (ROMEO) mission, developed at the University of Stuttgart‘s Institute of Space Systems, seeks to demonstrate a cost-effective exploitation of the medium Earth orbit (MEO) for sustainable access to space. It uses a green propulsion system with water as propellant to reach up to 2500 km altitude starting from a 450 km sun-synchronous orbit (SSO). This paper presents the design and intended use of the ROMEO satellite as well as its two in-house developed camera systems, the public relations (PR) and the near-infrared (NIR) camera system. The PR camera system features two silicon sensors with a Bayer color pattern in a compact, lightweight package and in a cold redundant setup to reduce the impact of radiation-related degradation. Their wide field of view (128 × 96°) allows imaging of the complete visible Earth in the mission‘s final orbit and supports calibration of the Earthshine telescope, which is the primary payload. The NIR camera system uses a commercial InGaAs sensor with a high quantum efficiency up to 1700 nm, coupled to a 100 mm focal length optics assembly that yields a ground sampling distance of 45 m in the initial orbit. Its scientific objectives include monitoring gas flares and wildfires, which are relevant to climate change research, and demonstrating an exoplanet transit detection—an unprecedented capability for a small satellite using a commercial off-the-shelf InGaAs sensor in the NIR spectrum. This paper demonstrates that ROMEO’s compact, low-mass camera systems meet mission constraints while enabling a broad spectrum of scientific and outreach activities. Full article