Search Results (643)

The investigations examined a potential reduction in discrepancies between the values of the unperturbed radiofrequency (RF) electromagnetic field (EMF) and values of the EMF measured by wearable equipment (personal exposure meters) impacted by the proximity of the human body. This was done by modelling distributed wearable (multi-location, with up to seven simultaneously locations) measurements. The performed numerical simulations mimicked distributed measurements in 24 environmental exposure scenarios (recognized as virtual measurements) covered: the horizontal or vertical propagation of the EMF and electric field vector polarization corresponding to typical conditions of far-field exposure from wireless communication systems (at a frequency of 100–3600 MHz). Physical tests using three EMF probes for simultaneous measurements have been also performed. Studies showed that the discrepancy in assessing EMF exposure by an on-body equipment and the parameters of the unperturbed EMF in the location under inspection (mimicking the contribution to measurement uncertainty from the human body proximity) may be significantly reduced by the appropriate use of a distributed measurement system. The use of averaged values, from at least three simultaneous measurements at relevant locations on the body, may reduce the uncertainty approximately threefold. Full article

Recently, it has been found that electrochemical sensing technology is one of the significant approaches for the monitoring of toxic and hazardous substances in food and the environment. Nitrofurazone (NFZ) and nitrofurantoin (NFT) possess a hazardous influence on the environment, aquatic life, and human health. Thus, various advanced materials such as graphene, carbon nanotubes, metal oxides, MXenes, layered double hydroxides (LDHs), polymers, metal–organic frameworks (MOFs), metal-based composites, etc. are widely used for the development of nitrofurazone and nitrofurantoin sensors. This review article summarizes the progress in the fabrication of electrode materials for nitrofurazone and nitrofurantoin sensing applications. The performance of the various electrode materials for nitrofurazone and nitrofurantoin monitoring are discussed. Various electrochemical sensing techniques such as square wave voltammetry (SWV), differential pulse voltammetry (DPV), linear sweep voltammetry (LSV), amperometry (AMP), cyclic voltammetry (CV), and chronoamperometry (CA) are discussed for the determination of NFZ and NFT. It is observed that DPV, SWV, and AMP/CA are more sensitive techniques compared to LSV and CV. The challenges, future perspectives, and limitations of NFZ and NFT sensors are also discussed. It is believed that present article may be useful for electrochemists as well materials scientists who are working to design electrode materials for electrochemical sensing applications. Full article

With the rapid progression of global industrialization and urbanization, emerging contaminants (ECs) have become pervasive in environmental media, posing considerable risks to ecosystems and human health. While multidisciplinary evidence continues to accumulate regarding their environmental persistence and bioaccumulative hazards, critical knowledge gaps persist in understanding their spatiotemporal distribution, cross-media migration mechanisms, and cascading ecotoxicological consequences. This review systematically investigates the global distribution patterns of ECs in aquatic environments over the past five years and evaluates their potential ecological risks. Furthermore, it examines the performance of various treatment technologies, focusing on economic cost, efficiency, and environmental sustainability. Methodologically aligned with PRISMA 2020 guidelines, this study implements dual independent screening protocols, stringent inclusion–exclusion criteria (n = 327 studies). Key findings reveal the following: (1) Occurrences of ECs show geographical clustering in highly industrialized river basins, particularly in Asia (37.05%), Europe (24.31%), and North America (14.01%), where agricultural pharmaceuticals and fluorinated compounds contribute disproportionately to environmental loading. (2) Complex transboundary pollutant transport through atmospheric deposition and oceanic currents, coupled with compound-specific partitioning behaviors across water–sediment–air interfaces. (3) Emerging hybrid treatment systems (e.g., catalytic membrane bioreactors, plasma-assisted advanced oxidation) achieve > 90% removal for recalcitrant ECs, though requiring 15–40% cost reductions for scalable implementation. This work provides actionable insights for developing adaptive regulatory frameworks and advancing green chemistry principles in environmental engineering practice. Full article

Background: As intelligent systems increasingly operate in high-risk environments, understanding how they perceive and respond to hazards is critical for ensuring safety. Methods: In this study, we conduct a comparative analysis of 60 real-world accident reports, 30 from process control systems (PCSs) and 30 from autonomous vehicles (AVs), to examine differences in risk triggers, perception paradigms, and interaction failures between humans and artificial intelligence (AI). Results: Our findings reveal that PCS risks are predominantly internal to the system and detectable through deterministic, rule-based mechanisms, whereas AVs’ risks are externally driven and managed via probabilistic, multi-modal sensor fusion. More importantly, despite these architectural differences, both domains exhibit recurring human–AI interaction failures, including over-reliance on automation, mode confusion, and delayed intervention. In the case of PCSs, these failures are historically tied to human–automation interaction; this article extrapolates these patterns to anticipate potential human–AI interaction challenges as AI adaptation increases. Conclusions: This study highlights the need for a hybrid risk perception framework and improved human-centered design to enhance situational awareness and responsiveness. While AI has not yet been implemented in PCS incident studies, this work interprets human–automation failures in these cases as indicative of potential challenges in human–AI interaction that may arise in future AI-integrated process systems. Implications extend to developing safer intelligent systems across industrial and transportation sectors. Full article

Background: Informal welders in Pretoria West face growing occupational safety risks due to hazardous working environments and limited regulatory oversight. Despite the high-risk nature of their work, many remain unaware of relevant safety legislation and inconsistently use personal protective equipment (PPE). This study aimed to investigate the occupational safety risks, challenges, and levels of compliance with safety practices among informal welders in Pretoria West, South Africa. Methods: A cross-sectional mixed-methods approach was employed, incorporating both qualitative and quantitative designs. Data were collected from 40 male welders (aged 20–55 years) using structured questionnaires, observational checklists, and semi-structured interviews. Descriptive statistics were generated using Microsoft Excel, while thematic content analysis was applied to the qualitative data. Results: Eighty-five percent (85%) of welders reported using gas welding, and more than half had received training in welding and PPE use; however, 47.5% had no formal training. A high prevalence of work-related injuries was reported, including burns, cuts, and eye damage. Common safety concerns identified were burns (42.5%), electric shocks (35%), and malfunctioning equipment. Observational data revealed inconsistent PPE use, particularly with flame-resistant overalls and eye protection. Qualitative insights highlighted challenges such as demanding client expectations, hazardous physical environments, and inadequate equipment maintenance. Many sites lacked compliance with occupational safety standards. Conclusion: The study reveals critical gaps in safety knowledge, training, and PPE compliance among informal welders. These deficiencies significantly elevate the risk of occupational injuries. Strengthening occupational health and safety regulations, improving access to PPE, and delivering targeted training interventions are essential to safeguard the well-being of welders and those in their surrounding communities. Full article

The green-chemical preparation of silver nanoparticles (AgNPs) offers a sustainable and environmentally friendly alternative to conventional synthesis methods, thereby representing a paradigm shift in the field of nanotechnology. The biological synthesis process, which involves the synthesis, characterization, and management of materials, as well as their further development at the nanoscale, is the most economical, environmentally friendly, and rapid synthesis process compared to physical and chemical processes. Ligustrum ovalifolium flower extract was used for the preparation of AgNPs. The synthesized AgNPs were examined by using UV–visible spectroscopy, XRD, SEM, and TEM analysis. It indicates that AgNPs were formed in good size. AgNPs were applied as a catalyst for the degradation of pollutants, such as methyl orange, Congo red, and methylene blue, which were degraded within 8–16 min. Additionally, the reduction of para-nitrophenol (PNP) to para-aminophenol (PAP) was achieved within 2 min. This work demonstrates a practical, reproducible, and efficient method for synthesizing cost-effective and stable AgNPs, which serve as active catalysts for the rapid degradation of hazardous organic dyes in an aqueous environment. Full article

In the present era, achieving sustainability requires the development of planning strategies to develop a safer urban infrastructure. This study examines the realistic aspects of cyclist safety by analysing cyclists’ fields of view, using Geographic Information Systems (GIS) and spatial data analysis. The research introduces novel geoprocessing tools-based GIS techniques that mathematically simulate cyclists’ angles of view and the distances to nearby environmental features. It provides precise insights into some potential hazards and infrastructure challenges encountered while cycling. This research focuses on managing and analysing the data collected, utilising OpenStreetMap (OSM) as vector-based supporting data. It integrates cyclists’ behavioural data with the urban environmental features encountered, such as intersections, road design, and traffic controls. The analysis is categorised into specific classes to evaluate the impacts of these aspects of the environment on cyclists’ behaviours. The current investigation highlights the importance of integrating the objective environmental elements surrounding the route with subjective perceptions and then determining the influence of these environmental elements on cyclists’ behaviours. Unlike previous studies that ignore cyclists’ visual perspectives in the context of real-world data, this work integrates objective GIS data with cyclists’ field of view-based modelling to identify high-risk areas and highlight the need for enhanced safety measures. The proposed approach equips urban planners and designers with data-informed strategies for creating safer cycling infrastructure, fostering sustainable mobility, and mitigating urban congestion. Full article

This paper presents a novel system designed to enhance pedestrian safety in urban environments by utilizing real-time video analysis and machine learning techniques. With a focus on the bustling streets of Macao, known for its high pedestrian traffic and complex road conditions, the proposed model alerts drivers to the presence of pedestrians, significantly reducing the risk of accidents. Leveraging the You Only Look Once algorithm, this research demonstrates how timely alerts can be generated based on risk assessments derived from video footage. The model is rigorously tested against diverse driving scenarios, providing robust accuracy in detecting potential hazards. A comparative analysis of various machine learning algorithms, including Gradient Boosting and Logistic Regression, underscores the effectiveness and reliability of the system. The key finding of this research indicates that dataset refinement and enhanced feature differentiation could lead to improved model performance. Ultimately, this work seeks to contribute to the development of smart city initiatives that prioritize safety through advanced technological solutions. This approach exemplifies a vision for more responsive and responsible urban transport systems. Full article

Geoarchaeological work and excavations of the Helike Project over the last 30 years in the Helike coastal plain, Gulf of Corinth, have yielded abundant evidence on ancient settlements, as well as the surrounding landscape and environmental changes that resulted from geological phenomena and catastrophic events. The research methods applied by the Helike Project followed a multidisciplinary approach, including combined archaeological excavations and palaeoseismological trenching, geophysical prospection, archaeometric, environmental, and soil micromorphology analyses, and computer-based landscape modelling. A wealth of settlement remains that were unearthed across the plain, ranging in date from the Early Helladic period (3rd millennium BC) to the Late Antiquity (5th century AD), indicates that the ancient inhabitants of the area chose to always resettle in the area by adjusting their ways of living to the geomorphology and natural hazards, prevailing each time. Our results show that disasters in the area increased between the Geometric and Roman times due to severe earthquakes that occurred approximately every 300 years. In particular, archaeological and geological finds recovered from the Late Classical–Hellenistic Helike settlement, which was revived in the western part of the plain shortly after the disastrous 373 BC earthquake, have enriched our knowledge regarding the historical seismicity of the region and past human–environment relationships. Full article

The mobile robot, which comprises a mobile platform and a robotic arm, has been widely adopted in industrial automation. Existing safe control methods with real-time trajectory alternation face difficulties in efficiently identifying threats from fast relative motion between humans and robots, causing hazards in environments of dense human–robot coexistence. This work firstly builds a safe mobile robot control framework in the kinematic sense. Secondly, the proximity between parts of a human and a mobile robot is efficiently solved by convex programming with parametric description of skew line segments. It is also no longer required to perform case-by-case analysis of skew line segments’ relative pose in space. Thirdly, a novel threatening index is proposed to select the most threatened human parts based on mutual projection of human–robot relative velocity and their common normal vector. Eventually, this index is incorporated into the safety constraint, showing the improved safe control performance in the simulated human–mobile robot coexistence scenario. Full article

This paper introduces a configuration and integration model for mobile robots deployed in emergency and special operations scenarios. The proposed method is designed for implementation within the operational technology (OT) domain, enforcing security protocols that ensure both data encryption and network isolation. The primary objective is to establish a dedicated operational environment encompassing a command and control center where the robotic network server resides, alongside real-time data storage from network clients and remote control of field-deployed mobile robots. Building on this infrastructure, operational strategies are developed to enable an efficient robotic response in critical situations. By leveraging remote robotic networks, significant benefits are achieved in terms of personnel safety and mission efficiency, minimizing response time and reducing the risk of injury to human operators during hazardous interventions. Unlike generic IoT or IoRT systems, this work focuses on secure robotic integration within segmented OT infrastructures. The technologies employed create a synergistic system that ensures data integrity, encryption, and safe user interaction through a web-based interface. Additionally, the system includes mobile robots and a read-only application positioned within a demilitarized zone (DMZ), allowing for secure data monitoring without granting control access to the robotic network, thus enabling cyber-physical isolation and auditability. Full article

Post-earthquake fires (PEFs) represent a complex, cascading hazard in which seismic damage creates ignition conditions that can overwhelm urban infrastructure and severely compromise structural integrity. Despite growing scholarly attention, the literature on PEFs remains fragmented across disciplines, lacking a consolidated understanding of structural vulnerabilities, urban-scale impacts, and response strategies. This study presents a systematic and thematic synthesis of 54 peer-reviewed articles, identified through a PRISMA-guided screening of 151 publications from the Web of Science Core Collection. By combining bibliometric mapping with thematic clustering, the review categorizes research into key methodological domains, including finite element modeling, experimental testing, probabilistic risk analysis, multi-hazard frameworks, urban simulation, and policy approaches. The findings reveal a dominant focus on structural fire resistance, particularly of seismically damaged concrete and steel systems, while highlighting emerging trends in sensor-based fire detection, AI integration, and urban resilience planning. However, critical research gaps persist in multi-hazard modeling, firefighting under partial collapse, behavioral responses, and the integration of spatial, infrastructural, and institutional factors. This study proposes an interdisciplinary research agenda that connects engineering, urban design, and disaster governance to inform adaptive, smart-city-based strategies for mitigating fire risks in seismic zones. This work contributes a comprehensive roadmap for advancing post-earthquake fire resilience in the built environment. Full article

The global demand for oils and lipids, particularly those derived from vegetable sources with high polyunsaturated fatty acid content, has posed significant challenges for the food industry. This trend is largely driven by growing consumer awareness of health and nutrition. To meet this demand, it is essential to not only identify richer sources of lipids but also develop efficient, sustainable, and environmentally friendly methods for their extraction, isolation, and characterization. In this context, the present work provides a comprehensive review of current perspectives on the extraction, isolation, and identification of lipids and fatty acids, comparing conventional and green methodologies for food applications. Ideally, analytical and processing methodologies for obtaining food-grade materials should prioritize low energy consumption, minimal or no use of hazardous substances, and the generation of non-polluting residues, thereby safeguarding both human health and the environment. In recent years, green extraction techniques have emerged as promising alternatives to conventional methods, offering partial or complete replacements, such as ultrasound-assisted extraction, microwave-assisted extraction, supercritical and subcritical fluid extraction, and others. However, significant advancements are still required to fully address these concerns. Techniques such as chromatography and spectrometry play pivotal roles in the isolation and identification process, especially gas chromatography coupled with mass spectrometry or with flame ionization detectors; while separating individual fatty acids based on their chain length and degree of unsaturation, reversed-phase high-performance liquid chromatography (HPLC) is quite a helpful approach. Furthermore, the isolation and structural elucidation of fatty acids are critical steps in ensuring the nutritional quality and commercial viability of lipid products. Full article

The increasing frequency and intensity of wildfires in hard-to-reach and hazardous areas represents a significant challenge for traditional firefighting methods. Wildfires pose a growing threat to the environment, property, and human lives. In many cases, conventional suppression techniques prove ineffective, highlighting the need for innovative and efficient solutions. Recent fires in the Bohemian Switzerland National Park in the Czech Republic; the Los Angeles area in California, USA; and the southeastern region of South Korea have underscored the necessity for alternative wildfire mitigation strategies. This article explores the potential of employing military technologies, such as artillery systems and specialized munitions, in wildfire suppression. The analysis includes a review of previous experiments, the research into non-standard methods, and an assessment of the risks and limitations associated with these approaches. Based on the research and simulations, it was found that one salvo (eight rounds) of fire-suppressant shells can cover up to 650 m² of terrain with suppressant. Finally, this article proposes a direction for further research aimed at integrating military and civilian technologies to enhance the effectiveness of wildfire response. This work contributes to the ongoing discussion on the integration of artillery capabilities into crisis management and provides a foundation for the future research in this field. Full article

Natural rubber skim latex is commonly discarded as waste or turned into skim natural rubber products such as skim crepe and skim blocks. It is challenging to retrieve all residual rubbers in skim latex since it has a very low rubber content and many non-rubber components like protein. Manufacturers conventionally utilize concentrated sulfuric acid as a coagulant. This method generates many effluents and hazardous pollutants that negatively impact the environment. This work presents an innovative method for enhancing the skim latex’s value by employing an ultrafiltration membrane. This study aims to establish a hydrophilic PVDF-TiO₂ mixed-matrix membrane. The skim latex was processed through a membrane-based ultrafiltration process, which yielded two products: skim latex concentrate and skim serum. Skim latex deposits that cause fouling on the membrane surface can be identified by SEM-EDX and FTIR analysis. The PVDF–PVP-TiO₂ mixed-matrix membrane generated the maximum skim serum flux of 12.72 L/m²h in contrast to the PVDF pure membranes, which showed a lower flux of 8.14 L/m²h. CHNS analysis shows that a greater amount of nitrogen, which is indicative of the protein composition, was successfully extracted by the membrane separation process. These particles may adhere to the membrane surface during filtration, obstructing or decreasing the number of fluid flow channels. The deposition reduces the effective size of membrane pores, leading to a decline in flux rate. The hydrophilic PVDF-TiO₂ mixed-matrix membrane developed in this study shows strong potential for application in the latex industry, specifically for treating natural rubber skim latex, a challenging by-product known for its high fouling potential. This innovative ultrafiltration approach offers a promising method to enhance the value of skim latex by enabling more efficient separation and recovery. Full article