Search Results (1,218)

The environmentally sustainable decontamination of chemical warfare agents (CWAs) remains a critical challenge. This study reports the solar-driven photocatalytic degradation of live CWAs—GD, HD, HN1, and HN2—using titanium dioxide (TiO₂) under natural sunlight. Experiments were conducted in an OPCW-designated laboratory to ensure authenticity and practical relevance. TiO₂ exhibited substantial photocatalytic activity, achieving 60% degradation of GD, 63% of HD, 76% of HN1, and 93% of HN2 after 6 h. High-resolution mass spectrometry (HR-MS) analysis suggested plausible degradation pathways for nitrogen mustards consistent with the higher apparent reactivity of HN2; detailed identification of intermediates and reactive oxygen species remains a subject for future investigation. These findings provide mechanistic insights into the photocatalytic behavior of nitrogen-based agents and address a notable gap in studies that have largely focused on sulfur mustards and nerve agents. Beyond military applications, this solar-assisted photocatalytic approach provides mechanistic information relevant to the green remediation of highly toxic organic contaminants and broader chemical hazard mitigation. This work contributes foundational knowledge toward eco-friendly decontamination technologies capable of mitigating diverse CWA threats. Full article

Background/Objectives: Latent fingerprints are routinely recovered from conventional porous and non-porous substrates; however, biologically active surfaces such as plant leaves are generally regarded as unsuitable for dactyloscopic evidence. Because vegetation is frequently present at crime scenes, this study aimed to systematically evaluate whether plant leaves can retain usable friction ridge detail and to determine the durability and forensic value of such traces under laboratory and outdoor conditions. Methods: Latent fingerprints were deposited on leaves of multiple plant species (maple, ash, dandelion, bird cherry, chestnut, climbing ivy, and five-leaved ivy) under dry and hydrated conditions and at defined time intervals after deposition. Visualization was performed using several powders, with SupraNano Fluorescent Green magnetic powder providing the best performance. Developed impressions were photographed using controlled illumination and evaluated using automated quality assessment (NFIQ 2.0) and comparison software (Innovatrics IDkit 9.1.7.1004). Additional experiments examined living, growing leaves exposed to natural weather conditions for extended periods. Results: Usable ridge detail was successfully visualized on all tested species. Bottom leaf surfaces and hydrated samples generally provided better preservation and contrast. Identifiable traces persisted for up to 20 h on detached leaves and for up to 35 days on living leaves despite growth-related deformation. Under outdoor exposure, fingerprints on ivy remained visible and comparable for up to 60 days. Although overall automated quality scores were reduced by background venation, selected impressions achieved measurable comparison scores and successful matches. Conclusions: Plant leaves can serve as unconventional yet viable carriers of latent fingerprints. Magnetic fluorescent powder development combined with careful documentation enables recovery of forensically useful ridge detail even after prolonged environmental exposure. These findings expand the range of substrates that should be considered during crime scene processing and provide practical guidance for evidence collection on vegetation. Full article

This article investigates the intricate interplay between ressentiment—as social emotion—social love, and solidarity in democratic societies, focusing on the urban environment as the primary stage where these processes materialize. Far from being a marginal emotion, ressentiment is deeply intertwined with democratic life, arising from the gap between proclaimed values and lived conditions. It represents an affective reaction to the perceived betrayal of the promise of equality inscribed in democratic ideals. The discussion explores how perceptions of injustice can fracture trust and intensify divisions, but also how they, under certain conditions, can be redirected toward political engagement and common action. The city, characterized by density, diversity, and the continuous negotiation of difference, can serve as a privileged arena for this transformation. Urban space does not merely reflect inequalities; it actively shapes social processes and provides the infrastructure through which collective sentiments are articulated. In this context, “social love” is conceptualized not as a sentimental aspiration, but as a relational force capable of redirecting the moral indignation of ressentiment, far from strategies of grievance politics toward constructive forms of social and political belonging. Cities can function as laboratories of solidarity where grievances are reframed into collective projects that strengthen social cohesion. Mitigating the destructive potential of ressentiment requires addressing its structural roots through inclusive urban policies and dialogical spaces. An approach grounded in social love can counter fragmentation, mobilizing emotions in the service of substantive equality. In this perspective, the city can become a space and a laboratory for change, where resentment can be channeled as a generative force capable of sustaining widespread forms of social love and a sense of the common good. Full article

Salmonella remains one of the most critical zoonotic pathogens in the poultry sector, linked to animal disease, foodborne illness, and the global crisis of antimicrobial resistance (AMR). Poultry acts as a major reservoir, enabling Salmonella transmission from hatchery to retail products through horizontal, vertical, and environmental routes. Despite the use of biosecurity, vaccination, antibiotics, and chemical decontamination, effective and sustainable control across the poultry value chain remains difficult, particularly in the face of rising multidrug-resistant strains and growing consumer concerns over chemical residues. Bacteriophages (phages), viruses that selectively infect and lyse bacteria, have emerged as a promising biological alternative for Salmonella control. Although many studies have reported the effectiveness of phages against bacterial species, including Salmonella, in the poultry industry, reports on their full potential to combat antimicrobial-resistant Salmonella across the entire poultry value chain remain limited. Therefore, this review synthesizes current evidence on the application of phages throughout the poultry value chain, including on-farm interventions, processing plant decontamination, and food packaging and storage. Findings from the reviewed articles indicate over a 90% reduction in Salmonella spp. in poultry farms and post-harvest meat, along with lower mortality in phage-treated groups compared to untreated groups; however, these outcomes depend on several factors (e.g., phage strains, concentrations, application methods, and environmental conditions). Laboratory, pilot, and field studies consistently demonstrate that phage preparations, especially when formulated as cocktails or combined with complementary interventions, can achieve substantial reductions in Salmonella, including antibiotic-resistant serovars, in live birds, eggs, poultry environments, and meat products. Unlike antibiotics and chemical sanitizers, phages act with high specificity, preserving beneficial microbiota and maintaining the sensory and nutritional quality of poultry products. Their safety has been supported by toxicological and genomic assessments, and several phage-based products have obtained regulatory approval, including Generally Recognized as Safe (GRAS) status for food applications in the United States. By integrating efficacy, safety, regulatory, and practical deployment data, this review highlights bacteriophages as a scientifically validated and One Health–aligned tool capable of reducing Salmonella transmission from farm to fork across the poultry value chain, thereby laying the foundation for their future adoption in the poultry industry. Phage-based interventions offer a sustainable pathway to enhance food safety, limit antimicrobial resistance (AMR) dissemination, and strengthen consumer confidence in poultry products. However, the major limitation is the emergence of phage-resistant bacterial strains, as well as the potential involvement of some phages in the transfer of resistance and virulence genes, which could raise public concern. Nevertheless, the use of phage cocktails and whole-genome sequencing, involving tools such as ResFinder and virulence finder, can facilitate the selection of safe phages for application. Full article

Water is an indispensable resource for the survival of all living organisms on Earth. However, many coastal villages continue to face challenges in accessing potable water, particularly during extended droughts. This comprehensive study evaluates the implementation and performance of a solar desalination system that employs photovoltaic (PV) panels and a parabolic solar concentrator to meet clean water demand in a drought-prone area of Indonesia. The system harnesses both solar-generated electricity and thermal energy to power an advanced desalination apparatus, effectively converting seawater into safe drinking water. Over a rigorous 4-month testing period, the device maintained an average steam outlet temperature of 105.9 °C, enabling a direct single-stage evaporation and condensation desalination process. Under optimal sunlight conditions, the system produced 1500 mL of purified water every 30 min, resulting in a total daily output of approximately 12 L (1500 mL × 8 cycles over 4 h). Laboratory analysis revealed a decrease in pH from 8.0 in raw seawater to 6.8 in treated water after post-treatment pH adjustment, meeting established safety standards for human consumption. Electrical conductivity measurements fell from 40–50 mS/cm to 480–500 µS/cm, confirming substantial salt removal. These results demonstrate the system’s capacity to generate potable water using sustainable energy sources and support circular economy principles by repurposing renewable resources for water desalination in water-scarce environments. Full article

Insects secrete volatile organic compounds (VOCs) for various reasons, such as intra- or inter-species communication, attracting mates, or repelling predators. The volatiles from indoor insect pests, e.g., phenolic secretions, can impact inhabitants in various ways, causing allergies, skin and eye irritations, etc. The Mupli beetle (Luprops tristis Fabricius, 1801) is one such nuisance pest that aggregates in great numbers in indoor spaces, especially near rubber plantations in tropical African and Asian countries. This study aimed to understand the whole-body volatilome of L. tristis, comprising the first detailed study of volatiles in this insect, particularly under aggregation and laboratory conditions. Whole-body VOCs were collected from sets of 500 and 1000 beetles at different time intervals and analysed by solvent-assisted desorption followed by gas chromatography–mass spectrometry (GC-MS). Compounds released by the Mupli beetle, such as 1-Octadecanesulphonyl chloride, Decane-1,1′-oxybis-, n-Nonadecanol-1 and n-Heptadecanol-1, are reported in the literature to be allergens that cause allergic reactions such as skin and eye irritations in humans. This understanding may indicate the possible reasons for the allergic reactions in people living in these insect-inhabited indoor spaces. We also report and describe the design and development of an economically feasible glass chamber for the dynamic headspace collection of volatiles released by these beetles. Full article

Anthropocene pressures underscore that human well-being and societal resilience depend on both biodiversity and geodiversity, the latter providing the abiotic foundation of Earth’s life-support systems. Despite increasing emphasis on systems thinking, participation, and action, Environmental Education and Education for Sustainable Development often underrepresent this abiotic dimension and leave ethical commitments insufficiently articulated. Addressing these gaps, this concept paper develops a convergence framework that integrates geoethics, geoeducation, and geoenvironmental education within the broader domains of EE and ESD. Drawing on interdisciplinary scholarship, geoethics is positioned as a normative lens that clarifies principles for responsible human–Earth relations, including responsibility, justice, respect for Earth processes, transparency in science communication, prudent resource use, and risk-aware decision-making. Geoeducation is conceptualized as the pedagogical vehicle through which these values are translated into competencies such as geoliteracy, systems thinking, critical reflection, ethical deliberation, and evidence-informed action, while geoenvironmental education provides the integrative content domain linking biotic, abiotic, and cultural dimensions. Place-based learning functions as the primary implementation pathway, with protected landscapes and UNESCO Global Geoparks serving as exemplary “living laboratories” where geoconservation, education, and sustainable development are co-produced with local communities. The paper advances three interrelated contributions: (a) a conceptual convergence framework, (b) an operational definition of geoethical awareness, and (c) a programmatic model linking geoethical values to competencies, pedagogies, indicators, and place-based implementation strategies. Operationalized through a Theory of Change and a translation matrix connecting principles to educational outcomes, the framework provides a foundation for future empirical research, curriculum development, teacher education, and the cultivation of geo-citizenship, stewardship, and more resilient human–Earth relationships. Full article

Osteoarthritis (OA) is a highly prevalent musculoskeletal disorder and a major cause of disability, posing growing challenges for healthcare systems worldwide. Conventional supervised clinical assessments provide valuable insights but are largely limited to cross-sectional snapshots and often fail to reflect the variability of real-world functioning, physical activity patterns, and symptom fluctuations experienced by individuals with OA, especially those with knee OA. This perspective introduces a multisensor digital phenotyping framework for smart knee OA assessment, integrating supervised laboratory evaluations with unsupervised continuous monitoring in daily living environments using wearable sensors, smart insoles, activity trackers, and mobile devices. Feasibility was tested in 40 participants (20 knee OA patients, 20 controls). Raw data from questionnaires, electronic goniometry, dynamometry, force plate, connected insoles, and seven-day home monitoring were harmonized via a standardized pipeline aligned with the ICF framework. The pipeline employed anomaly detection, missing data imputation, z-score normalization, and cloud-based storage. This framework is envisioned to facilitate advanced data integration and machine-learning-ready analytics, enabling longitudinal monitoring, pattern recognition, and individualized health profiling. By conceptually bridging cross-sectional and continuous sensing modalities, this approach has the potential to enhance ecological validity, support earlier identification of functional decline, and inform data-driven clinical decision-making. Key methodological, technological, and ethical challenges—including data quality, interpretability, privacy, digital literacy, and clinical adoption—are also highlighted. Overall, this paper underscores the promise of AI-enabled multisensor digital phenotyping to advance smart, personalized, and precision healthcare for individuals with knee OA. Full article

The evolution of 5G networks has introduced new challenges in securing mobile infrastructures against increasingly sophisticated cyber threats. Intrusion detection in such environments has been widely studied using traditional datasets such as the Canadian Institute for Cybersecurity Intrusion Detection Systems CICIDS2017, the University of New South Wales-Network Behavior UNSW-NB15, and The Network Security Laboratory-Knowledge Discovery in Databases NSL-KDD; however, these benchmarks lack the architectural complexity and protocol diversity inherent to 5G networks. More recent research has adopted the 5G-NIDD dataset (5G Network Intrusion Detection Dataset), which provides realistic traffic generated from a live 5G testbed, including various attack scenarios targeting MEC servers and core network components. Nevertheless, existing works using 5G-NIDD often focus on limited subsets of attacks, rely on unsupervised or federated learning approaches, and lack comprehensive evaluations of supervised learning models. In contrast, this study leverages the entire 5G-NIDD dataset, encompassing all available attack scenarios, and conducts a systematic comparison of multiple supervised learning algorithms. A systematic evaluation of supervised learning algorithms is conducted using key performance metrics such as accuracy, precision, recall and F1-score to identify the most effective model for intrusion detection in 5G environments. Specifically, this study focuses on four supervised learning algorithms, K-Nearest Neighbors (KNNs), Support Vector Machines (SVMs), Logistic Regression (LR), and Naive Bayes (NB), to determine not only which achieves the highest detection accuracy but also which offers the best balance between predictive performance and computational efficiency in realistic 5G environments. To assess robustness and adaptability, the proposed models are further validated on two widely used benchmark datasets, namely CICIDS2017 and UNSW-NB15, as part of an extended analysis. This cross-dataset evaluation highlights each algorithm’s strengths and limitations under diverse network traffic conditions and attack scenarios. The results aim to validate the applicability of supervised learning approaches to intrusion detection in next-generation network infrastructures, while also emphasizing the importance of balancing predictive accuracy with computational efficiency for real-world deployment. Full article

Environmental pollution has emerged as one of the most significant threats to human and ecosystem health, with growing evidence suggesting that chronic exposure to toxic substances may accelerate aging. The concept of gerontogens, toxic compounds capable of accelerating this biological process, has gained increasing attention in toxicological research, particularly in the context of global demographic shifts toward older populations. Current research on gerontogens relies heavily on invertebrate models with short lifespans, such as Caenorhabditis elegans, Drosophila melanogaster, and Saccharomyces cerevisiae, which are valuable for studying conserved mechanisms in aging pathways, but present significant limitations for translational accuracy to many aspects of vertebrate biology. Vertebrate models traditionally employed in toxicology, including mice and zebrafish, require substantially longer experimental timelines and higher financial investments, making lifetime exposure and aging assays particularly challenging. In this context, the turquoise killifish Nothobranchius furzeri emerges as a highly promising vertebrate model for aging toxicology research. Recognized as the shortest-lived vertebrate species maintained under laboratory conditions, N. furzeri reaches sexual maturity within 14 days and displays complete senescence by 4 months of age, at which point individuals are considered elderly, offering a decisive advantage over conventional vertebrate models. Furthermore, its capacity for embryonic diapause enables practical embryo storage, long-distance transport, and synchronized hatching, greatly facilitating experimental designs. Although N. furzeri is well established in gerontological research, with studies addressing hallmarks of aging such as telomere shortening, neurodegeneration, and cellular senescence, its application in ecotoxicology remains remarkably limited, with fewer than 10 published studies to date. This article argues that N. furzeri may represent a critical bridge between toxicology and aging research, offering an efficient and translationally relevant platform for investigating the effects of environmental contaminants on vertebrate aging. Current limitations of the model, such as lack of husbandry standardization, are also discussed. Expanding its use in this field holds considerable potential for advancing evidence-based strategies in public health and environmental conservation related to chronic exposure to contaminants. Full article

In this work, the development and validation of an AI- and sensor-based inline quality monitoring system for the analysis of particle size distributions (PSDs) of comminuted construction and demolition waste (CDW) material flows are described. In this, a custom-developed multitask CNN (CDW-MT-CNN) was developed using manually sieve analyzed particles. This model is able to rapidly and simultaneously predict the particle class and weight, essential for the determination of the PSD. The single particle data are then aggregated per raw image, usually consisting of around 1000 particles for full-scale experiments, to acquire a per-image PSD. The inline mounted RGB line scan sensor records high-resolution images in subsecond frequencies. With an inference time of around 54 ms for a single image, this model would be able to provide a PSD every minute in a full-scale plant. For the purpose of inline monitoring of CDW material flows in a comminution process, such intervals are sufficient according to experts and solve existing gaps regarding the upscaling of laboratory-developed systems. Together with the high predictive performance of the model, especially in terms of classification (82% accuracy), it is shown that this technology has potential for monitoring in full-scale plants, for instance by offering operators new insights to improve operation efficiency. Further research should focus on increasing the precision for weight prediction, for instance by increasing the labeled data set with a larger number of unique particles and on methods to verify the performance of the model on pilot or full-scale plants during live operation. Full article

Objectives: Karting imposes high neuromuscular demands on the forearm during dynamic steering, gripping and braking. This study examined whether a single high-velocity, low-amplitude (HVLA) manipulation of the elbow acutely modified surface EMG_RMS amplitude and EMG median frequency responses during standardized isometric forearm testing after simulated karting load, rather than EMG activity during dynamic driving itself. Methods: In this randomized, sham-controlled, within-subject trial, 15 drivers completed a single-session within-participant protocol in which one upper limb was randomly allocated to receive elbow HVLA manipulation (manipulated limb) and the contralateral limb received a standardized sham procedure (sham limb) involving therapist contact and low-grade oscillatory movement without end-range pre-tension or thrust. Drivers completed two 8 min simulated races separated by the allocated manual procedure. Surface electromyography (EMG) from four forearm muscles was collected outside the karting task during standardized laboratory-based isometric forearm contractions at baseline, after race 1, post-intervention, and after race 2. EMG was not recorded during real-time steering, braking, vibration exposure or competitive driving. The extensor carpi radialis (ECR) was specified as the principal muscle of interest because the HVLA technique pre-tensioned the common extensor origin and radial wrist extensors. The primary outcome was ECR mean EMG_RMS amplitude, expressed in µV, across the four measurement time points; the primary statistical test was the condition × time interaction. ECR maximal EMG_RMS amplitude and ECR median frequency were treated as secondary outcomes, whereas ECU, FCR, and FCU outcomes were treated as exploratory anatomical specificity outcomes. Mixed-model ANOVAs compared maximal and mean EMG amplitudes and median frequency between manipulated and sham limbs, treating limb condition and time as repeated within-participant factors. Results: For the primary outcome, ECR mean EMG_RMS amplitude showed a main effect of condition (p = 0.023) and a condition × time interaction (p < 0.001). As a secondary amplitude outcome, ECR maximal EMG_RMS amplitude showed a main effect of time (p = 0.009) and a condition × time interaction (p < 0.001), with higher post-manipulation values in the manipulated limb. No consistent limb-condition effects were found for the other muscles, and EMG median frequency showed only modest time-related changes (p = 0.031) without between-condition differences. Conclusions: A single-elbow manipulation produced short-lived, muscle-specific increases in ECR activation after simulated racing, whereas broader neuromuscular changes were not evident. These findings indicate only transient modulation of ECR surface EMG amplitude in a small sample of screened karting drivers and do not demonstrate improved recovery, neuromuscular efficiency, sport performance, or injury prevention. Because EMG was assessed during standardized isometric contractions rather than during dynamic steering, braking, vibration exposure or competitive racing, the findings should not be interpreted as direct evidence of altered neuromuscular behaviour during actual kart driving. Larger studies including force, performance, clinical, fatigue-specific and dynamic driving EMG outcomes are required. Full article

By studying and analysing a great number of textile metal threads from different time periods in Croatia, from archaeological sites to preserved specimens from various museum collections, change can be seen through the centuries. Metal threads decorate textiles not only for aesthetic purposes, but also to display wealth, assert authority, and command respect. Primarily, such decorated clothing was worn for liturgical purposes, ceremonial folk customs, or to mark high military ranks. Through the characteristics of these threads, one can see the change in the customs and lives of the people who used them in different ways and for different purposes. The shine and luxury that the first gold metal threads have can be achieved with lower quality threads like silver, copper, and their alloys. As the quality of metal textile threads decreased, they became cheaper and more applicable in everyday life. The use of metal textile threads on clothing increased, and through the century, they became a clothing part for all people, not just the privileged. Analyses of metal threads were performed with scanning electron microscopy with an energy-dispersive X-ray detector (SEM-EDX) due to its sensitivity and suitability for the observation of metal threads from various textiles. The type of textile cores from the combined textile metal threads was determined through a laboratory optical microscope. Differences have been observed between archaeological and historical textile metal threads in terms of physical properties, as well as textile and metal composition. Archaeological samples are combined textile metal threads that have a metal component of gilded silver and a textile component of silk. While more recent historical samples have different types of metal threads, from individual threads of lamellae and wires to combined textile metal threads. Most samples have cotton as a textile component, while copper, alone or in alloys, predominates in the metal threads. Full article

Hurricanes cause severe impacts on lives, livelihoods, and essential systems. Hurricane Melissa impacted Jamaica as a Category 5 cyclone, resulting in estimated losses of approximately 41% of national GDP (US$8.8 billion) and eliciting widespread damage to housing, healthcare, agriculture, and urban infrastructure. Agriculture sustained heavy losses, with 41,000 hectares of damaged farmland and the loss of more than 1 million livestock animals. These impacts resulted in exposed animal closures with biological hazards. Using systems thinking, the PESTHEEL framework, and a One Health lens, we argue for viewing Hurricane Melissa as series of cascading inter-related One Health threats of waterborne and vector-borne diseases, zoonoses, antimicrobial resistance, degraded indoor and outdoor air quality, chemical pollution, and shifting migration and border dynamics. These each unfold at different timings. A structured synthesis for Jamaica and other Caribbean Small Island Developing States is provided by integrating systems thinking, One Health, and the PESTHEEL framework. Immediate and lagged risk pathways are identified, and practical risk reduction actions are proposed to support anticipatory, multisectoral recovery: enhanced syndromic, laboratory, wastewater, vector, and rodent surveillance; resilient WASH and shelter systems; non-insecticidal and integrated vector management; biosecure aid and border protocols; environmental toxicology monitoring; and climate–health intelligence. Full article

This study develops an end-to-end workflow, from laboratory measurements to Eulerian–Eulerian two-phase simulations with SedFoam, to investigate bed erosion in free-surface open-channel flow over a deformable granular bed. Experiments were conducted with a calibrated non-cohesive deposit of epoxy-coated spherical beads under steady, fully turbulent, subcritical conditions. Particle Image Velocimetry provided mean-flow and turbulence data, while a 3D camera workflow supplied bed-elevation fields and time-resolved maps of sediment rearrangement. These datasets were used to constrain a staged numerical strategy in which single-phase hydrodynamics were first reproduced and then extended to live-bed morphodynamics. Validation over a rigid bed showed that the 2006 k–$\omega$ closure, combined with a rough-wall treatment, reproduced the measured mean-velocity profiles and provided acceptable turbulent kinetic energy levels, yielding dynamically consistent near-bed shear conditions. In live-bed conditions, the simulations reproduced the streamwise organization of scour and deposition, predicted cumulative erosion rates of the correct order of magnitude, and captured bedform migration consistent with time-resolved bed reconstructions. The numerical results were compared with repeated experiments while accounting for run-to-run variability and the metrological limits of the 3D camera. This work proposes a transferable experimental–numerical methodology for assessing the predictive capability of live-bed morphodynamic simulations, in which hydraulic characterization, three-dimensional bed monitoring, erosion/deposition metrics, and repeated experiments are combined within a common comparison procedure. Full article