Search Results (15,623)

Sebastes thompsoni is a cold-water rockfish of commercial and ecological value off the coast of Korea, requiring conservation management. We analyzed seven microsatellite loci to assess genetic diversity, population structure, and historical effective population size (N_e) of five populations obtained from the South and East Seas of Korea in 2018. The observed heterozygosity (H_O = 0.759–0.816) was higher than previously reported, and none of the STRUCTURE, DAPC, or AMOVA analyses detected geographic differentiation among samples from the South and East coasts of Korea, indicating a single population within these coasts. There was genetic flow between the five groups, with migration rates ranging from 4.1 to 19.11. However, the current N_e of all populations is estimated to be <1000, and VarEff-based reconstructions indicate a recent, severe bottleneck following an expansion approximately 600–1200 years ago (100–200 generations ago). This suggests that genetic diversity loss may persist in the future due to long-term habitat loss, fishing pressure, and ocean current fluctuations. Therefore, S. thompsoni should be established as a single management unit covering the Korean Peninsula coast, and habitat protection, overfishing control, genetic management type resource release using various mother and broodstock, and periodic genetic monitoring should be promoted. This study provides evidence to guide efforts to secure long-term genetic resilience and sustainable management of S. thompsoni in Korean coastal waters. Full article

Biological recolonization after cleaning remains a major challenge for the conservation of stone cultural heritage. As recolonization can start within months to a few years following intervention, developing rapid, field-deployable diagnostic approaches is crucial to better monitor microbial reappearance and to assess treatment performance in real time. Traditional evaluation methods lack the capacity to take into consideration non-cultivable microorganisms or assess functional traits relevant to recolonization. To bypass this gap, we applied on-site direct Whole-Genome Sequencing (Oxford Nanopore^® MinION™ sequencer) coupled with colorimetric analysis to understand the microbiome, resistome, and metabolic traits of subaerial biofilms present in untreated and treated (recolonized) areas of stone statues at the “Largo da Porta Férrea” (Coimbra’s UNESCO World Heritage site). Colorimetric analysis (ΔE of 32–40 in recolonized vs. 19–43 in untreated areas) and genomic data pointed out that the applied treatment provided only a short-term effect (roughly 4–5 years), with a marked decline in fungi (1–2% vs. 7–18%), coupled with an increased recolonization mainly by Cyanobacteriota (circa 35–45%) and several stress-resistant Bacteria (globally ~95% of reads vs. 73–79% in controls). Antimicrobial resistance profiles significantly differed between sites, with treated areas showing distinct and unique resistance genes, and plasmids containing the blaTEM-116 gene, which can indicate potential adaptive shifts in the resistomes profiles after intervention. Metabolic pathways analysis revealed that untreated areas retained more complete nitrogen and sulfur cycling gene sets, whereas treated areas showed reduced biogeochemical gene contents, consistent with earlier-stage recolonization steps. Given the current recolonization detection and the ongoing biofilm formation, routine monitoring efforts (e.g., every 6 months) are recommended. Overall, this study demonstrates the first on-site genomic characterization of recolonization events on heritage stone, providing a practical prompt-warning tool for conservation monitoring and future biofilm management strategies. Full article

Background/Objectives: The dengue virus remains endemic in over 100 countries, transmitted by mosquito bites. Current management relies on supportive care, as no highly effective vaccine or approved antiviral exists. The CYD-TDV (Dengvaxia^®) vaccine, licensed since 2015 with around 60% efficacy, raises the risk of severe dengue in seronegative children. The newer “Qdenga” vaccine offers up to 80% efficacy after a year but provides suboptimal protection against DENV-3 in seronegative individuals. Over the past two decades, virus-like particles (VLPs) have gained attention as safe, replication-incompetent vaccine platforms. This study evaluates the toxicity profile of dengue VLP-based antigens in BALB/c mice. Methods: A total of 80 BALB/C mice were randomly divided into two experimental groups: acute and chronic. Each group consisted of a treatment subgroup (10 males and 10 females) and a control subgroup (10 males and 10 females). In the acute group, the VLP was administered intramuscularly on day 1, while in the chronic group, a second VLP dose was given on day 14. The study was conducted over a 28-day period. Throughout the experiment, body temperature, body weight, mortality, and clinical signs were monitored regularly to assess the functional condition of various organs. Results: The results showed no notable alterations in mortality rates, body temperature, body weight, clinical signs, or histopathological observations of the examined organs across all groups, including in the hematological and blood biochemical parameters. Conclusions: The administration of tetravalent dengue VLP vaccine in BALB/c mice did not result in adverse effects in acute or chronic toxicity evaluations. Therefore, the VLP supports progression toward clinical evaluation, with dendritic cell activation providing additional rationale. Full article

Background/Objectives: Neisseria gonorrhoeae can develop resistance to antimicrobial treatments, posing a challenge to effective management of patients. Alberta, Canada, monitors the antimicrobial susceptibility of gonorrhea isolates to track resistance trends. This study aims to retrospectively analyze susceptibility data and demographic trends from gonorrhea cases in the province over a seven-year period. Methods: Antimicrobial susceptibility testing was performed using gradient strip methodology on gonorrhea isolates from Alberta, evaluating both historical and currently recommended antimicrobials for treatment of gonorrhea. Susceptibility testing results were interpreted using Clinical and Laboratory Standards Institute (CLSI) breakpoints. Provincial antimicrobial susceptibility testing data were analyzed using STATA v.17, incorporating antimicrobial resistance patterns and demographic information from provincial databases. Results: Between 2016 and 2022, 4056 N. gonorrhoeae isolates were cultured from 3617 individuals. All isolates tested were susceptible to ceftriaxone and cefixime, except for a single resistant isolate in 2018. Azithromycin susceptibility ranged from 99% to 88%, with the lowest susceptibility observed in 2018. Males exhibited higher rates of antimicrobial non-susceptibility than females across all drugs tested, except for tetracycline. Conclusions: Ongoing antimicrobial susceptibility surveillance in Alberta is crucial for identifying resistance trends and informing the development of effective treatment strategies for gonorrhea. Full article

Methane emissions from coal mines, especially surface operations, are spatially diffuse, presenting significant challenges for accurate quantification. Satellites such as TROPOMI, GHGSat, PRISMA, GaoFen-5, and GOSAT have been extensively used for detecting methane emissions at various scales, from individual point sources to regional and global assessments. Despite various advancements, methane quantification via satellite observations remains subject to several challenges. Various quantification methods for the same observation can produce variable results. Also, meteorological conditions, terrain complexity, and surface heterogeneity introduce uncertainties in emission estimates. The selection of wind speed and direction, along with retrieval-algorithm limitations, can lead to significant discrepancies in reported emissions. Additionally, satellite-based observations capture emissions only at specific overpass times, which may introduce temporal uncertainties compared to inventories derived from continuous emission estimations. This study provides a comprehensive review of satellite-based coal mine methane (CMM) monitoring, evaluating current methodologies, their limitations, and recent technological advancements. We discussed the potential of emerging machine-learning techniques, improved atmospheric modelling, and integrated observational approaches to enhance methane emission quantification. By refining satellite-based monitoring techniques and addressing existing challenges, this research will support the development of more accurate emission inventories and effective mitigation strategies for the coal mining sector. Full article

The rapid development of Intelligent Connected Vehicles (ICVs) and the Internet of Vehicles (IoV) has paved the way for new real-time monitoring and control systems. However, most existing telemetry solutions remain limited by high costs, reliance on cellular networks, lack of modularity, and insufficient field validation in competitive scenarios. To address this gap, this study presents the design, implementation, and real-world validation of a low-cost telemetry platform for electric race vehicles. The system integrates an ESP32-based data acquisition unit, LoRaWAN long-range communication, and real-time visualization via Node-RED on a Raspberry Pi gateway. The platform supports multiple sensors (voltage, current, temperature, Global Positioning System (GPS), speed) and uses a FreeRTOS multi-core architecture for efficient task distribution and consistent data sampling. Field testing was conducted during Colombia’s 2024 National Electric Drive Vehicle Competition (CNVTE), under actual race conditions. The telemetry system achieved sensor accuracy exceeding 95%, stable LoRa transmission with low latency, and consistent performance throughout the competition. Notably, teams using the system reported up to 12% improvements in energy efficiency compared to baseline trials, confirming the system’s technical feasibility and operational impact under real race conditions. This work contributes to the advancement of IoV research by providing a modular, replicable, and cost-effective telemetry architecture, field-validated for use in high-performance electric vehicles. The architecture generalizes to urban e-mobility fleets for energy-aware routing, predictive maintenance, and safety monitoring. Full article

The COVID-19 pandemic resulted in high morbidity and mortality, as well as severe social and economic disruption globally. Since the pandemic began in 2019, the severe acute respiratory syndrome, coronavirus 2, has undergone numerous changes, resulting in the emergence of new variants and subvariants. The emergence of new variants of the virus poses a challenge to scientists. There is currently no SARS-CoV-2 variant meeting the criteria of variants of concern, whereas the only variant of interest is JN.1, and there are six variants under monitoring: LP8.1, NP1.8.1, XEC, KP.3, KP.3.1.1 and the latest, XFG (Stratus). Although the latter appears to be more transmissible than the others, genomic evidence indicates that it is less aggressive than some recent variants. Nevertheless, continuous genomic surveillance of COVID-19 is still important to detect any new variants that could threaten public health. Numerous therapeutic strategies, such as drugs, vaccines, and nutritional supplements, are being used to treat COVID-19. This narrative review is an overview of COVID-19 and its various facets, from the number of cases to the therapies used, the current variants, and the ongoing clinical trials, specifically focusing on the most recent studies. Full article

Bathing water quality (BWQ) monitoring and prediction are essential to safeguard public health by informing bathers about the risk of exposure to faecal indicator bacteria (FIBs). Traditional monitoring approaches, such as manual sampling and laboratory analysis, while effective, are often constrained by delayed reporting, limited spatial and temporal coverage, and high operational costs. The integration of artificial intelligence (AI), particularly machine learning (ML), with automated data sources such as environmental sensors and satellite imagery has offered novel predictive and real-time monitoring opportunities in BWQ assessment. This systematic literature review synthesises current research on the application of AI in BWQ assessment, focusing on predictive modelling techniques and remote sensing approaches. Following the PRISMA methodology, 63 relevant studies are reviewed. The review identifies dominant modelling techniques such as Artificial Neural Networks (ANN), Deep Learning (DL), Decision Tree (DT), Random Forest (RF), Multiple Linear Regression (MLR), Support Vector Machine (SVM), and Hybrid and Ensemble Boosting algorithms. The integration of AI with remote sensing platforms such as Google Earth Engine (GEE) has improved the spatial and temporal solution of BWQ monitoring systems. The performance of modelling approaches varied depending on data availability, model flexibility, and integration with alternative data sources like remote sensing. Notable research gaps include short-term faecal pollution prediction and incomplete datasets on key environmental variables, data scarcity, and model interpretability of complex AI models. Emerging trends point towards the potential of near-real-time modelling, Internet of Things (IoT) integration, standardised data protocols, global data sharing, the development of explainable AI models, and integrating remote sensing and cloud-based systems. Future research should prioritise these areas while promoting the integration of AI-driven BWQ systems into public health monitoring and environmental management through multidisciplinary collaboration. Full article

State highway agencies usually measure Annual Average Daily Traffic (AADT) using traffic data from permanent detector stations within their system-wide traffic monitoring programs. Agencies also estimate the AADT at many other locations using short-term counts. Traffic counters at the permanent stations frequently malfunction, leading to periods of inaccurate or missing data. Addressing missing data in estimating AADT by highway agencies is important for sustainable infrastructure management. This study used extensive traffic data from permanent detector stations in the state of Montana to examine the effect of missing data on the accuracy of AADT estimation. On a rotational basis, one station was used to test the accuracy of AADT estimation, while the remaining stations (training stations) were used to develop the traffic adjustment factors. Data truncation at the training stations was conducted using two sampling techniques and three scenarios of data availability. The study results showed that the increase in AADT estimation error (inaccuracy) was not linearly proportional to the increase in the amount of missing data. Given the extreme scenarios of missing data examined in this study and the relatively lower effect on AADT estimation error, it can be concluded that the current practice in treating missing data does not involve a considerable compromise in the accuracy of AADT estimation. This highlights the robustness of the current estimation practice, suggesting that it can be effectively applied in statewide traffic monitoring programs without a significant loss of accuracy. Full article

The constant evolution of Decentralized Finance (DeFi) calls for the continuous monitoring of its developments and implications through a critical review of the academic literature. While DeFi holds promise for enhancing economic activity by expanding market access for enterprises and promoting financial inclusion, concerns remain that digital assets are primarily used for speculative purposes rather than for financing the real economy. This study employs bibliometric methods to investigate whether and how the current academic literature addresses the potential influence of DeFi on real economic dynamics. Employing bibliometric methods—including co-citation, bibliographic coupling, and keyword co-occurrence analyses—focused on DeFi-related publications in the Economics and Business subject areas within the Scopus database, the study maps the knowledge base, author networks, and thematic trends and their temporal evolution, supporting regulators, researchers, and practitioners. The findings reveal that the integration of DeFi with the real economy has received limited attention in scholarly research. This highlights the need for further investigation into DeFi’s implications for financial stability, productive investment, and long-term economic growth. Full article

Airborne microplastics (MPs) are a global issue, and there is an urgent need to prevent their spread in the environment. Sensitive and reliable methods are also needed to assess their deposition and effectively evaluate risk in terrestrial ecosystems. Current automated monitoring devices are expensive and do not enable large-scale mapping of MP deposition. As with other persistent atmospheric contaminants, developing accurate, cost-effective and easily applicable biomonitoring methods would therefore be highly beneficial. Cryptogams are among the most suitable biomonitors of airborne contaminants, and preliminary surveys show that epiphytic lichens accumulate higher concentrations of MPs in urban areas and near landfills than in control sites. However, the interaction between lichen thalli and MPs is weak and, as discussed in this review, the anthropogenic fibres and plastic fragments intercepted and retained by lichens probably do not reflect the levels in bulk atmospheric deposition. While emphasizing the need for studies evaluating the effectiveness of cryptogams in accumulating different types of airborne MPs under various meteorological conditions, this review also suggests directing future research efforts toward mosses, which seem to accumulate much higher concentrations of MPs than lichens in both active and passive biomonitoring surveys. Full article

The bioaccumulation of trace metals in edible crops is a key pathway of dietary exposure, with direct implications for environmental health and food safety. This study specifically investigated the bioaccumulation and soil–plant transfer of lithium (Li) in edible crops, alongside other selected trace metals (Cu, Mn, Sr, Zn), to understand its unique environmental mobility and dietary exposure risks in onion, garlic, green salad, cucumber, and zucchini cultivated across Romania. Forty-two paired samples of vegetable tissues and rhizosphere soils were collected from eleven agricultural regions, and were analyzed using spectroscopic techniques. Soils were predominantly neutral to slightly acidic, conditions that significantly affected metal mobility and uptake. Results revealed element-specific decoupling between soil and plant concentrations. Essential micronutrients (Zn, Cu) showed higher transfer factors, consistent with active physiological uptake, while toxic non-essential metals (Pb, Cd) remained below European regulatory thresholds, reflecting effective exclusion mechanisms. Lithium exhibited spatially heterogeneous transfer patterns, strongly influenced by local geochemical variability. Curvilinear soil–plant relationships for Fe, Zn, Sr, Mn, Cu, and Li further underscored the role of soil chemistry in shaping translocation. These findings establish a robust baseline for assessing dietary risks, confirming the current low-risk status of vegetables in the surveyed regions, and provide valuable guidance for sustainable agricultural management and food safety monitoring. Full article

Detection of planted tree seedlings at the individual level is crucial for monitoring forest ecosystems and supporting silvicultural management. The combination of deep learning (DL) object detection algorithms and remote sensing (RS) data from unmanned aerial vehicles (UAVs) offers efficient and cost-effective solutions. However, current methods predominantly rely on unimodal RS data sources, overlooking the multi-source nature of RS data, which may result in an insufficient representation of target features. Moreover, there is a lack of multimodal frameworks tailored explicitly for detecting planted tree seedlings. Consequently, we propose a multimodal object detection framework for this task by integrating texture information from digital orthophoto maps (DOMs) and geometric information from digital surface models (DSMs). We introduce alternate scanning fusion (ASF), a novel multimodal fusion module based on state space models (SSMs). The ASF can achieve global feature fusion while maintaining linear computational complexity. We embed ASF modules into a dual-backbone YOLOv5 object detection framework, enabling feature-level fusion between DOM and DSM for end-to-end detection. To train and evaluate the proposed framework, we establish the planted tree seedling (PTS) dataset. On the PTS dataset, our method achieves an AP50 of 72.6% for detecting planted tree seedlings, significantly outperforming the original YOLOv5 on unimodal data: 63.5% on DOM and 55.9% on DSM. Within the YOLOv5 framework, comparative experiments on both our PTS dataset and the public VEDAI benchmark demonstrate that the ASF surpasses representative fusion methods in multimodal detection accuracy while maintaining relatively low computational cost. Full article

Indoor air quality (IAQ) and thermal comfort influence the health and cognitive performance of school occupants. This study investigated carbon dioxide (CO₂), nitrogen dioxide (NO₂), thermal comfort, and ventilation rates (VRs) in eight naturally ventilated (NV) primary school classrooms in Ireland during October 2024, combining environmental monitoring with teacher surveys. Mean CO₂ concentrations ranged from 796 ppm to 2469 ppm, exceeding national guidelines in seven of the eight classrooms. NO₂ levels ranged from 3.4 µg/m³ to 7.2 µg/m³, with indoor/outdoor ratios increasing with VRs and influenced by window orientation and road proximity. Indoor temperatures remained within recommended limits, while relative humidity ranged from 53% to 78% mirroring CO₂ trends and exceeding guideline levels in classrooms with lower VRs and temperatures. Occupied VRs ranged from 1.2 L/p/s to 4.1 L/p/s with window opening behaviours, reliant on teachers’ perceptions of thermal comfort, accounting for 84% to 96% of VRs. Ventilation in NV classrooms is often insufficient, yet increasing VRs can compromise thermal comfort and increase ingress of outdoor pollutants and noise. The findings highlight the ineffectiveness of current school ventilation standards, which rely heavily on user operation. Integrating occupant-led strategies, including scheduled purging, awareness campaigns, and pre-emptive air quality alerting, into policy offers practical, immediate pathways to improving IAQ, fostering healthy, sustainable learning environments. Full article

Tropical agriculture requires sustainable irrigation solutions that balance water availability with quality and environmental protection. This review synthesizes current knowledge on riverbank filtration (RBF)—a nature-based technology for improving agricultural water quality—with objectives to elucidate design principles, water quality performance, and operational challenges specific to tropical contexts. Through systematic analysis of 128 peer-reviewed articles across topics including RBF hydrogeology, contaminant removal mechanisms, sediment transport, pathogen reduction, site selection criteria, and monitoring strategies, this work consolidates interdisciplinary evidence on RBF effectiveness for irrigation water supply. The Roldanillo–Unión–Toro (RUT) district in Valle del Cauca, Colombia, serves as a case study illustrating RBF application to sediment-rich, pathogen-prone rivers typical of tropical agricultural regions. While RBF is established for drinking water supply in temperate zones, its adaptation to tropical irrigation remains underexplored. This review identifies critical hydrogeological, environmental, and operational considerations for implementing RBF systems in tropical agricultural settings characterized by high water demand, seasonal variability, and challenging water quality conditions. Key findings are synthesized into a practitioner-oriented framework—covering site selection, design optimization, and adaptive management—intended to guide deployment of RBF for irrigation in tropical agricultural settings. Full article