Search Results (198)

Radon exposure is a major health concern associated with an increased risk of lung cancer, particularly in smokers, highlighting the need for effective mitigation measures in enclosed spaces by improving indoor air quality (IAQ), thus ensuring more sustainable buildings. The Euratom Directive, a key piece of EU legislation, sets standards for the protection of workers and the general public from ionizing radiation throughout Europe. It requires member states to implement safety measures, set exposure limits, monitor radon levels, and develop emergency plans and mitigation strategies for nuclear accidents and radiation incidents. The directive also sets reference and action levels for indoor radon. The aim of this article is to analyze the legislation on indoor radon exposure in European countries and to evaluate the impact of the directive on the standardization of the action and intervention levels. By conducting a comprehensive legislative review, this study will compare the action levels, assess the directive’s ability to harmonize the regulations, and identify legislative trends and developments. In addition, it will examine the factors contributing to the discrepancies between countries and highlight areas for improvement to ensure adequate protection against the risks of radon exposure and thereby increase the sustainability of buildings. Full article

Meta-research in biomedical science is crucial for ensuring rigour, relevance, and transparency in an era marked by the exponential growth of scientific publications. This study examines global and historical trends in meta-research activities within biomedicine and investigates their relationship with health, science, and human development indicators. A systematic analysis of 9633 publications from Scopus, Web of Science, and PubMed was conducted, focusing on publication volume, citation impact, and geographic distribution. Regression analyses reveal a significant positive association between meta-research activity and the Human Development Index (HDI), suggesting that meta-research contributes to societal advancement by enhancing evidence-based decision-making in health. However, no association was found between meta-research output and research and development (R&D) expenditure, reflecting the minimal resource requirements of secondary data-driven studies compared to primary or experimental research. Meta-research activity correlates positively with clinical trial completion, indicating its role in refining study designs and addressing evidence gaps. These findings highlight the importance of expanding meta-research in underrepresented regions to promote equity in scientific advancement and improve the reliability of biomedical knowledge. This result underscores the need for targeted support for meta-research, particularly in low- and middle-income countries with limited scientific infrastructure and resources for new knowledge generation. Full article

Sustainability is under threat due to inefficient waste management. In the industrial sector, mechanisms such as value chains and producer obligations have advanced circular economy practices. However, in the agroforestry sector, open burning of waste remains prevalent, resulting in resource loss and heightened fire risks. This scenario jeopardizes the environmental, social, and economic pillars of sustainability, underscoring the need for legal frameworks to ensure waste recovery. This study proposes a regulatory framework to enhance the circular economy in agroforestry waste management. A benchmarking analysis was conducted to examine waste recovery systems where circular economy principles are successfully implemented. Insights from these systems were integrated with an in-depth assessment of the agroforestry biomass recovery chain to develop actionable regulatory measures. The proposed framework includes measures such as mandatory delivery of biomass, creation of aggregation centers, and incentives for biomass recovery. These measures are tailored to reduce fire risks, improve resource efficiency, and align stakeholders’ practices with sustainability goals. Visual tools, including comparative tables and diagrams, illustrate the framework’s impact. The study highlights the potential of regulatory interventions to promote agroforestry waste recovery, supporting sustainable development. Future work should focus on pilot implementations to validate the framework’s effectiveness in real-world scenarios. Full article

The main focus of this study, from a sustainable perspective, was to develop mineral circularity actions for the minimization of environmental impacts, generated over decades by the processing of run-of-mine (ROM) coal in the Catarinense coal basin–Brazil (CCB–Br), from the use of potential residual fractions (candidate residues) as raw materials for the production of organo-mineral fertilizers, or OMFs (candidate products). Therefore, the objective was to assess the potential of the residual fractions, generated in the distinct phases of ROM coal processing, as candidate waste for valorization, contributing directly to the advancement of the Sustainable Development Goals (SDGs). The samples from ROM processing resulted in 24 waste fractions identified by geological characteristics and a sustainable processing methodology. These fractions were subjected to a systematic analysis using the criteria for waste valorization CPQvA (classification (C) of hazardousness, potentiality (P), quantities/viability (Qv), and applicability (A)). Two samples were identified with significant potential for valorization in the agro-industry as sustainable raw materials for the organo-mineral fertilizers. Both samples exhibited neutral stock pH values (7.0 and 7.1), low percentage Fe₂O₃ content (4.2% and 3.2%), low SO₃ content (0.5% and 1.2%), and low total sulfur content (1.0%). These characteristics qualified the studied ROM samples as raw materials suitable for the production of organo-mineral fertilizers (OMFs), and which comply with Brazilian legislation. Full article

Background/Objectives: This study aimed to compare the association of ustekinumab (UST) drug clearance (CL) and trough drug concentrations with disease activity in patients with inflammatory bowel diseases (IBDs). Methods: A prospective cohort of 83 patients with IBD receiving maintenance therapy with 90 mg subcutaneous UST was analyzed using Bayesian PK modeling. UST concentrations and antibodies to UST (ATU) were collected at the trough and measured using a drug-tolerant homogenous mobility shift assay (HMSA). CL was estimated using Bayesian estimation methods with priors from a previous population pharmacokinetic study specifically reparametrized using HMSA. Outcomes were combined clinical and biochemical remission and endoscopic healing index (EHI) score, a validated marker of endoscopic active disease in IBD. Statistical analysis consisted of linear and nonlinear mixed effect models for repeated time-to-event analysis. Results: A total of 83 patients with IBD were enrolled (median age 42 years, 52% female) and evaluated across 312 dose cycles (median follow-up: 279 days, median of 3 cycles/patient). Median concentrations and CL were 5.0 µg/mL and 0.157 L/day, respectively. Most patients (89%) were exposed to other biologics before starting UST, which was associated with lower rates of clinical and biochemical remission (p = 0.01). Longitudinal changes in concentrations were not associated with remission (p = 0.53). Conversely, higher CL was associated with a lower likelihood of remission (p < 0.01). EHI > 50 points (endoscopic active disease, n = 303 cycles) was associated with higher UST CL (p < 0.01). Conclusions: UST CL was more strongly associated with clinical and biochemical outcomes than trough concentrations, highlighting its potential role in therapy optimization. Full article

The longevity of railway vehicles is an important factor in their mechanical and structural design. Fatigue is a major issue that affects the durability of railway components, and therefore, knowledge of the fatigue resistance characteristics of critical components, such as the leaf springs, must be extensively investigated. This research covers the fatigue resistance of chromium–vanadium alloy steel, usually designated as 51CrV4, from the high-cycle regime (HCF) (${10}^3$–${10}^4$) up to very high-cycle fatigue (VHCF) (${10}^9$) under the bending loading conditions typical of leaf springs and under uniaxial tension/compression loading, respectively, for a stress ratio, $R_{\sigma }$, of −1. Different test frequencies were considered (23, 150, and 20,000 Hz) despite the material not exhibiting a relatively significant frequency effect. In order to create a new fatigue prediction model, two prediction models, the Basquin SN linear regression model and the Castillo–Fernandez–Cantelli (CFC) model, were evaluated. According to the analysis carried out, the CFC model provided a better prediction of the fatigue failures than the SN model, especially when outlier failure data were considered. The investigation also examined the failure modes, observing multiple cracks for higher loads and single cracks that initiated on the surface or from internal inclusions at lower loading. The present investigation aims to provide a fatigue resistance prediction model encompassing the HCF and VHCF regions for the fatigue design of railway wagon leaf springs, or even for other components made of 51CrV4 with a tempered martensitic microstructure. Full article

As wildfires become more frequent and severe in the face of global environmental change, it becomes crucial not only to assess, prevent, and suppress them but also to manage the aftermath effectively. Given the temporal interconnections between these issues, we explored the concept of the “wildfire science loop”—a framework categorizing wildfire research into three stages: “before”, “during”, and “after” wildfires. Based on this partition, we performed a systematic review by linking particular topics and keywords to each stage, aiming to describe each one and quantify the volume of published research. The results from our review identified a substantial imbalance in the wildfire research landscape, with the post-fire stage being markedly underrepresented. Research focusing on the “after” stage is 1.5 times (or 46%) less prevalent than that on the “before” stage and 1.8 (or 77%) less than that on the “during” stage. This discrepancy is likely driven by a historical emphasis on prevention and suppression due to immediate societal needs. Aiming to address and overcome this imbalance, we present our perspectives regarding a strategic agenda to enhance our understanding of post-fire processes and outcomes, emphasizing the socioecological impacts of wildfires and the management of post-fire recovery in a multi-level and transdisciplinary approach. These proposals advocate integrating knowledge-driven research on burn severity and ecosystem mitigation/recovery with practical, application-driven management strategies and strategic policy development. This framework also supports a comprehensive agenda that spans short-term emergency responses to long-term adaptive management, ensuring that post-fire landscapes are better understood, managed, and restored. We emphasize the critical importance of the “after-fire” stage in breaking negative planning cycles, enhancing management practices, and implementing nature-based solutions with a vision of “building back better”. Strengthening a comprehensive and balanced research agenda focused on the “after-fire” stage will also enhance our ability to close the loop of socioecological processes involved in adaptive wildfire management and improve the alignment with international agendas such as the UN’s Decade on Ecosystem Restoration and the EU’s Nature Restoration Law. By addressing this research imbalance, we can significantly improve our ability to restore ecosystems, enhance post-fire resilience, and develop adaptive wildfire management strategies that are better suited to the challenges of a rapidly changing world. Full article

Background: The forest products industry plays a significant role in global carbon emissions, highlighting the need for sustainable practices to address the climate crisis. Reverse logistics (RL), focusing on the return, reuse, and recycling of materials, offers a promising approach to decarbonizing supply chains. However, its application within forest products supply chains remains underexplored. Methods: This study conducts a review of the literature on RL, its environmental implications, and its potential to reduce carbon emissions in forest products supply chains. Key areas examined include greenhouse gas reduction, waste management, and the promotion of circular economy principles. Additionally, the study evaluates case studies and models that integrate RL practices into forest-based industries. Results: The findings reveal that RL can significantly reduce greenhouse gas emissions by optimizing transportation routes, minimizing waste, and extending product life cycles. Incorporating these practices into forestry operations reduces the environmental impact and aligns with sustainable forestry goals. The study identifies gaps in current research, particularly regarding empirical data and the scalability of RL solutions. Conclusions: RL represents a critical strategy for decarbonizing forest products supply chains and advancing sustainable development. Future research should focus on developing standardized methodologies, enhancing technological integration, and fostering policy support to maximize its impact. These steps are essential to fully leverage RL as a tool for mitigating climate change and promoting a circular economy. Full article

The 2018 Sulawesi Earthquake and Tsunami serves as a backdrop for this work, which employs simple and straightforward remote sensing techniques to determine the extent of the destruction and indirectly evaluate the region’s vulnerability to such catastrophic events. Documenting damage from tsunamis is only meaningful shortly after the disaster has occurred because governmental agencies clean up debris and start the recovery process within a few hours after the destruction has occurred, deeming impact estimates unreliable. Sentinel-2 and Maxar WorldView-3 satellite images were used to calculate well-known environmental indices to delineate the tsunami-affected areas in Palu, Indonesia. The use of NDVI, NDSI, and NDWI indices has allowed for a quantifiable measure of the changes in vegetation, soil moisture, and water bodies, providing a clear demarcation of the tsunami’s impact on land cover. The final tsunami inundation map indicates that the areas most affected by the tsunami are found in the urban center, low-lying regions, and along the coast. This work charts the aftermath of one of Indonesia’s recent tsunamis but may also lay the groundwork for an easy, handy, and low-cost approach to quickly identify tsunami-affected zones. While previous studies have used high-resolution remote sensing methods such as LiDAR or SAR, our study emphasizes accessibility and simplicity, making it more feasible for resource-constrained regions or rapid disaster response. The scientific novelty lies in the integration of widely used environmental indices (dNDVI, dNDWI, and dNDSI) with threshold-based Decision Tree classification to delineate tsunami-affected areas. Unlike many studies that rely on advanced or proprietary tools, we demonstrate that comparable results can be achieved with cost-effective open-source data and straightforward methodologies. Additionally, we address the challenge of differentiating tsunami impacts from other phenomena (et, liquefaction) through index-based thresholds and propose a framework that is adaptable to other vulnerable coastal regions. Full article

This overview study investigates integrating advanced manufacturing technologies, specifically metal additive manufacturing (AM) and laser powder bed fusion (LPBF) processes, within Industry 4.0 and Industry 5.0 frameworks, to enhance sustainability and efficiency in industrial production and prototyping. The manufacturing sector, a significant contributor to global greenhouse gas emissions and resource consumption, is increasingly adopting technologies that reduce environmental impact while maintaining economic growth. Selective laser melting (SLM), as the subsection LPBF technologies, is highlighted for its capability to produce high-performance, lightweight, and complex components with minimal material waste, thus aligning with circular economy goals for metal alloys. Life cycle assessment (LCA) and life cycle costing (LCC) analyses are essential methods for evaluating the sustainability of any new technology. Sustainable technologies could support the concepts of the factory of the future (FoF), fulfilling the requirements of digital transformation and digital twins. This overview study reveals that implementing AM—specifically SLM—has the potential to reduce the environmental impact of manufacturing. It underscores the ability of these technologies to promote sustainable and efficient manufacturing practices, thereby accelerating the shift from Industry 4.0 to Industry 5.0. Full article

This study focuses on the development of a machine learning (ML) model to elaborate on predictions of structural damage in submerged structures due to ocean states and subsequently compares it to a real-life case of a 6-month experiment with a benthic lander bearing a multitude of sensors. The ML model uses wave parameters such as height, period and direction as input layers, which describe the ocean conditions, and strains in selected points of the lander structure as output layers. To streamline the dataset generation, a simplified approach was adopted, integrating analytical formulations based on Morison equations and numerical simulations through the Finite Element Method (FEM) of the designed lander. Subsequent validation involved Fluid–Structure Interaction (FSI) simulations, using a 2D Computational Fluid Dynamics (CFD)-based numerical wave tank of the entire ocean depth to access velocity profiles, and a restricted 3D CFD model incorporating the lander structure. A case study was conducted to empirically validate the simulated ML model, with the design and deployment of a benthic lander at 30 m depth. The lander was monitored using electrical and optical strain gauges. The strains measured during the testing period will provide empirical validation and may be used for extensive training of a more reliable model. Full article

Grapevines (Vitis vinifera L.) are one of the most economically relevant crops worldwide, yet they are highly vulnerable to various diseases, causing substantial economic losses for winegrowers. This systematic review evaluates the application of remote sensing and proximal tools for vineyard disease detection, addressing current capabilities, gaps, and future directions in sensor-based field monitoring of grapevine diseases. The review covers 104 studies published between 2008 and October 2024, identified through searches in Scopus and Web of Science, conducted on 25 January 2024, and updated on 10 October 2024. The included studies focused exclusively on the sensor-based detection of grapevine diseases, while excluded studies were not related to grapevine diseases, did not use remote or proximal sensing, or were not conducted in field conditions. The most studied diseases include downy mildew, powdery mildew, Flavescence dorée, esca complex, rots, and viral diseases. The main sensors identified for disease detection are RGB, multispectral, hyperspectral sensors, and field spectroscopy. A trend identified in recent published research is the integration of artificial intelligence techniques, such as machine learning and deep learning, to improve disease detection accuracy. The results demonstrate progress in sensor-based disease monitoring, with most studies concentrating on specific diseases, sensor platforms, or methodological improvements. Future research should focus on standardizing methodologies, integrating multi-sensor data, and validating approaches across diverse vineyard contexts to improve commercial applicability and sustainability, addressing both economic and environmental challenges. Full article

This research explores how climate change will affect building energy use across the UK by analysing both a conventional reference building design and a net-zero energy (NZEBs) alternative to assess how each would perform under future weather conditions. Using climate projections from databases like Prometheus and Meteonorm, along with simulation tools like EnergyPlus and Freds4Buildings, the study evaluates the energy performance, costs, and GHG emissions of a case study building under current weather conditions, with 2030, 2050, and 2080 forecasts in three different UK locations: Exeter, Manchester, and Aberdeen. Results indicate that heating demand will decrease consistently over time across all locations by as much as 21% by 2080 while cooling demand will rise sharply. NZEBs proved more resilient to these changes, using less energy and producing fewer GHG emissions than conventional buildings, with 89% reductions in emissions even with increased cooling needs. Accounting for future weather helps both understand the risks of conventional design, with a number of scenarios experiencing overheating in 2080 and ensure NZEBs can meet their goals during their entire lifespan despite the increases in energy needs. The study highlights both the impact of accounting for future weather forecasts during design and the increasing relevance of net-zero energy designs in mitigating the effects of climate change while offering practical insights for architects, policymakers, and energy planners, showing why future weather patterns need to be considered in sustainable building design to ensure buildings will achieve their carbon targets throughout their life. Full article

Background: This study explores the use of Mixed-Integer Linear Programming (MILP) models to optimize the collection and transportation of vineyard pruning biomass, a crucial resource for sustainable energy and material production. Efficient biomass logistics play a key role in supporting circular bioeconomy principles by improving resource utilization and reducing operational costs. Methods: Two optimization approaches are evaluated: a base MILP model designed for scenarios with single processing points and an advanced model that incorporates intermediate processing steps to enhance logistical efficiency. The models were tested using synthetic datasets simulating vineyard regions to assess their performance. Results: The models demonstrated significant improvements, achieving cost reductions of up to 30% while enhancing operational efficiency and resource utilization. The study highlights the scalability and real-world applicability of the proposed models. Conclusions: The findings underscore the potential of MILP models in optimizing biomass supply chains and advancing circular bioeconomy goals. However, key limitations, such as computational complexity and adaptability to dynamic environments, are noted. Future research should focus on real-time data integration, dynamic updates, and multi-objective optimization to improve model robustness and applicability across diverse supply chain scenarios. Full article

Global climate change is leading to increased wildfire activity in many parts of the world, and with increasing development, a heightened threat to communities in the wildland urban interface. Evaluating the potential for fire to affect communities and critical infrastructure is essential for effective response decision-making and resource prioritization, including evacuation planning, with changing weather conditions during the fire season. Using a receptor–pathway–source assessment framework, we estimate the potential source area from which a wildfire could spread to a community in British Columbia by projecting fire growth outward from the community’s perimeter. The outer perimeter of the source area is effectively an evacuation trigger line for the forecast period. The novel aspects of our method are inverting fire growth in both space and time by reversing the wind direction, the time course of hourly weather, and slope and aspect inputs to a time-evolving fire growth simulation model Prometheus. We also ran a forward simulation from the perimeter of a large fire that was threatening the community to the community edge and back. In addition, we conducted a series of experiments to examine the influence of varying environmental conditions and ignition patterns on the invertibility of fire growth simulations. These cases demonstrate that time-evolving fire growth simulations can be inverted for practical purposes, although caution is needed when interpreting results in areas with extensive non-fuel cover or complex community perimeters. The advantages of this method over conventional simulation from a fire source are that it can be used for pre-attack planning before fire arrival, and following fire arrival, it does not require having an up-to-the-minute map of the fire location. The advantage over the use of minimum travel time methods for inverse modeling is that it allows for changing weather during the forecast period. This procedure provides a practical tool to inform real-time wildfire response decisions around communities, including resource allocation and evacuation planning, that could be implemented with several time-evolving fire growth models. Full article