Search Results (1,112)

The Marburg virus (MARV) is a zoonotic pathogen that causes a high case fatality rate of up to 100% in humans. In response to Marburg virus disease (MVD) outbreaks in the Kagera region, an ecological investigation was initiated to map the population and ecological threat to the reservoir host of MARV: Egyptian fruit bats. The investigation conducted from October 2023 to December 2024 included interviews with local authorities to locate all known autochthonous bat colonies in the region. Bat species confirmation was performed using high-resolution melting analysis (HRMA) and DNA barcoding, targeting two mitochondrial genes: cytochrome oxidase 1 (COI) and 16S rRNA. We found five considerably large cave-dwelling Egyptian fruit bat colonies (with approximately 100,000 individuals) at the geolocations between 1°06′04.2″ and 2°26′35.8″ S latitude and 30°40′49.7″ and 31°51′19.8″ E longitude. The study also provides the first confirmed identification of Egyptian fruit bats (Rousettus aegyptiacus) (accession numbers: PV700530-PV700534) in major bat colonies in the Kagera River Basin ecosystem. Cave-dwelling Egyptian fruit bats in mines face higher risks, and thus, attention is needed to prevent this species from becoming more vulnerable to extinction. The loss of bat roosting sites and subsequent population declines are primarily driven by the destructive practice of burning car tyres and logs, a method used to eliminate colonies through toxic smoke and heat. The collection of guano and partially eaten fruits in mining caves, as well as daily contact with Egyptian fruit bats in mines, homes, and churches, have become major potential risk factors for MARV transmission to humans. Increased threats to bats in the Kagera region warrant the implementation of conservation strategies that ensure the survival of the bat populations and inform policies on MVD risk reduction in Tanzania and the broader East African region. Full article

Multisensory behavioral research is increasingly aiming to move beyond traditional laboratories and into real-world settings. Smartphones offer a promising platform for this purpose, but their use in psychophysical experiments requires rigorous validation of their ability to precisely present multisensory stimuli and record reaction times (RTs). To date, no study has systematically assessed the feasibility of conducting RT-based multisensory paradigms on smartphones. In this study, we developed a reproducible validation method to quantify smartphones’ temporal precision in synchronized auditory–tactile stimulus delivery and RT logging. Applying this method to five Android devices, we identified two with sufficient precision. We also introduced a technique to enhance RT measurement by combining touchscreen and accelerometer data, effectively doubling the measure resolution—from 8.33 ms (limited by a 120 Hz refresh rate) to 4 ms. Using a top-performing device identified through our validation, we conducted an audio–tactile RT experiment with 20 healthy participants. Looming sounds were presented through headphones during a tactile detection task. Results showed that looming sounds reduced tactile RTs by 20–25 ms compared to static sounds, replicating a well-established multisensory effect linked to peripersonal space. These findings present a robust method for validating smartphones for cognitive research and demonstrate that high-precision audio–tactile paradigms can be reliably implemented on mobile devices. This work lays the groundwork for rigorous, scalable, and ecologically valid multisensory behavioral studies in naturalistic environments, expanding participant reach and enhancing the relevance of multisensory research. Full article

Schizopygopsis younghusbandi is an endemic and ecologically important fish species on the Tibetan Plateau. However, its dietary carbohydrate requirement remains unexplored, limiting the development of cost-effective and physiological-friendly artificial feed. This study investigated the effects of different dietary carbohydrate levels on the growth performance, antioxidant capacity, and hepatointestinal morphology of S.younghusbandi. Six experimental diets were formulated with graded carbohydrate levels of 9% (C9), 12% (C12), 15% (C15), 18% (C18), 21% (C21), and 24% (C24). A total of 720 fish (initial weight 37.49 ± 0.25 g) were randomly allocated to six groups in quadruplicate (30 fish per replicate) and reared in tanks (0.6 m × 0.5 m × 0.4 m) for 8 weeks. Results demonstrated that the diet in the C12 group significantly improved weight gain rate (WGR), specific growth rate (SGR), and feed conversion ratio (FCR) (p < 0.05). Regression fitting analysis on growth performance indicated that the optimal carbohydrate level ranged from 10.42% to 10.49%. Additionally, the C12 group exhibited enhanced total superoxide dismutase (T-SOD) activities and reduced malondialdehyde (MDA) content in the liver, along with reduced interleukin-1β (IL-1β) levels in the serum (p < 0.05). Histological analysis revealed superior hepatointestinal integrity in the C12 group, characterized by lower hepatic lipid droplet accumulation, reduced vacuolation, decreased hepatosomatic index (HSI) (p < 0.05), as well as higher intestinal villus height and muscle thickness (p < 0.05). In conclusion, the C12 group optimally enhanced the growth, antioxidant response, and hepatointestinal health of S. younghusbandi, indicating that the suitable dietary carbohydrate level for this species is 12%. Full article

Background/Objectives: Despite their ecological significance, DNA barcoding data for African rainforest Orthoptera remain underrepresented globally, limiting progress in species discovery, biodiversity assessment, and conservation. This study aimed to generate molecular data for morphologically identified Serpusia Karsch, 1891 species to evaluate their taxonomic status. Methods: Specimens were collected from multiple sites in Cameroon and analyzed using DNA barcoding with COI-5P and 16S rDNA markers. Species delimitation was performed with Automatic Barcode Gap Discovery, and phylogenetic relationships were inferred using Maximum Likelihood and Bayesian Inference. Additionally, external morphology and the male phallic complex were examined. Results: Molecular analyses delineated 19 MOTUs, five corresponding to Serpusia opacula, seven to Serpusia succursor and the remainder to outgroups. Similarity-based assignments matched these MOTUs to 19 BINs. Phylogenetic reconstruction revealed S. opacula and S. succursor as two genetically distinct clades, with the S. opacula group more closely related to Aresceutica Karsch, 1896 than to the S. succursor group. Accordingly, we established a new genus, Paraserpusia gen. nov., to accommodate S. succursor. Within the S. opacula group, five species are recognized: one previously described (S. opacula) and four new species (S. kennei sp. nov., S. missoupi sp. nov., S. seinoi sp. nov., and S. verhaaghi sp. nov.). The former S. succursor, now Paraserpusia succursor, is divided into six well-supported lineages, five of which are formally described here (P. hoeferi sp. nov., P. husemanni sp. nov., P. kekeunoui sp. nov., P. tamessei sp. nov., and P. tindoi sp. nov.). A haplotype network based on COI-5P sequences corroborates three major clades corresponding to the S. opacula group, the S. succursor group, and Aresceutica. Diagnostic morphological differences between Serpusia and Paraserpusia are consistently supported across characters. Conclusions: This integrative approach reveals substantial hidden diversity within Serpusia and highlights the importance of combining molecular and morphological data to uncover and formally describe previously overlooked taxa. Full article

Artificial intelligence (AI) offers several opportunities in wildfire management, particularly for improving short- and long-term fire occurrence forecasting, spread modeling, and decision-making. When properly adapted beyond research into real-world settings, AI can significantly reduce risks to human life, as well as ecological and economic damages. However, despite increasingly sophisticated research, the operational use of AI in wildfire contexts remains limited. In this article, we review the main domains of wildfire management where AI has been applied—susceptibility mapping, prediction, detection, simulation, and impact assessment—and highlight critical limitations that hinder practical adoption. These include challenges with dataset imbalance and accessibility, the inadequacy of commonly used metrics, the choice of prediction formats, and the computational costs of large-scale models, all of which reduce model trustworthiness and applicability. Beyond synthesizing existing work, our survey makes four explicit contributions: (1) we provide a reproducible taxonomy supported by detailed dataset tables, emphasizing both the reliability and shortcomings of frequently used data sources; (2) we propose evaluation guidance tailored to imbalanced and spatial tasks, stressing the importance of using accurate metrics and format; (3) we provide a complete state of the art, highlighting important issues and recommendations to enhance models’ performances and reliability from susceptibility to damage analysis; (4) we introduce a deployment checklist that considers cost, latency, required expertise, and integration with decision-support and optimization systems. By bridging the gap between laboratory-oriented models and real-world validation, our work advances prior reviews and aims to strengthen confidence in AI-driven wildfire management while guiding future research toward operational applicability. Full article

The passenger car market has experienced a radical shift: the rise of SUV, crossover vehicles, but also Battery Electric Vehicle (BEV) and Plug-In Hybrid Vehicle (PHEV), has blurred the borders between traditional vehicle segments as well as body types, resulting in reduced applicability of conventional taxonomies of vehicle types. This study aims to provide an overview of the vehicle market by proposing a new, machine-learning-based segmentation of the entire German vehicle fleet covering the past years. We merge over 40 million registered vehicles with a technical specifications database and apply data-mining techniques to derive an improved market segmentation. We demonstrate that unsupervised learning techniques, specifically Ward and k-means clustering, yield clusters with enhanced separation, clarity, and practical usability. Clustering was applied to both raw technical features and engineered features designed to capture aspects of economy, ecology, usability, and performance. The silhouette scores can reach 0.19, a significant increase over the +0.05/−0.05 scores of the existing vehicle segments or chassis types. Full article

Non-human primates (NHPs) are close relatives of humans and can serve as hosts for many zoonotic pathogens. They play crucial role in spreading antimicrobial resistant bacteria (AMR) to humans across various ecological niches. The spread of antimicrobial resistance in NHPs may complicate wildlife conservation efforts, as it may threaten domestic livestock, endangered species as well as human’s health. This review analyses the existing literature on the prevalence of AMR in NHP species, including Rhinopithecus roxellana, Macaca fascicularis, and Sapajus nigritus, to create awareness in all stake holders involve in the fight against AMR on the serious potential threats that these primates pose. Methods: We performed a comprehensive literature search using the PubMed (National Library of Medicine-NLM), Scopus (Elsevier), Web of Science Core Collection (Clarivate Analytics), Springer Link (Springer), and Science Direct (Elsevier) databases until January, 2025. The search strategy combined terms from the areas of non-human primates, antibiotic resistance, antimicrobial resistance, and antibacterial resistance genes (ARGs). Studies that isolated bacteria from NHPs and assessed phenotypic resistance to specific antibiotics as well as studies that identified ARGs in bacteria isolated from NHPs were included. Data were synthesised thematically across all included studies. Results: A total of 37 studies were included (explained as Cercopithecidae (n = 23), Callithrix (n = 6), Cebidae (n = 4), Hominidae (n = 3), and Atelidae (n = 1)). The results showed that the most common ARB across the various NHPs and geographical settings was Staphylococcus spp. (45.95%) and Escherichia spp. (29.73%). The tested antibiotics that showed high levels of resistance in NHPs included Tetracycline (40.54%), Ciprofloxacin (32.43%), and Erythromycin (24.34%), whereas ermC, tetA, tetM, aadA, aph (3″)-II, and qnrS1 were the most widely distributed antibiotic resistance genes in the studies. Conclusion: NHPs are potential natural reservoirs of AMR, therefore global policy makers should consider making NHPs an indicator species for monitoring the spread of ARB. Full article

Greenways offer sustainable benefits at ecological, cultural and economic levels, enhancing human well-being. Landscape performance assessment is a crucial task for evaluating these benefits and guiding the sustainable development of greenways. To clarify the characteristics and roles of landscape performance in the development of the US greenway system, text analysis was conducted using KH Coder, and a meta-analysis was performed on three databases to select research cases on greenway performance evaluation in the US. The results show that the evaluation of social performance is higher than that of ecological and economic performances, and the data related to economic performance is more difficult to obtain. The efficacy of greenway projects varies with the construction stage and is influenced by social background and target benefits. The sustainability characteristics of high co-occurrence relationships are key to guiding greenway performance assessment, which helps in selecting indicators for evaluating greenways and providing references for improving planning directions. In the future, innovative technical means tailored to the goals of greenway landscapes should be used for performance evaluation. Full article

Against the backdrop of global population growth and intensified resource competition, the sustainable development of the water-energy-food system (WEF) is facing challenges. Wetlands, as key ecological hubs, play a crucial role in regulating water cycles, energy metabolism, and food production, thus serving as a breakthrough point for resolving the bottleneck of resource synergy. Incorporating wetlands into the WEF framework helps us comprehensively understand and optimize the interrelationships among water, energy, and food. This paper proposes an indicator system based on WEFW to study the coupling of water-energy-food-wetland systems and analyzes the evolution of the comprehensive development index of WEFW and its coupling relationship in Jiangxi Province from 2001 to 2022. It uses the grey correlation model to explore the sustainable development capacity of wetland resources, water resources, energy resources, and food resources in Jiangxi Province, and employs a geographical detector model to quantify the contribution of wetlands to WEFW. The research results show that (1) the comprehensive evaluation of WEFW systems in various cities in Jiangxi Province has generally improved, but there is imbalance in regional development. Cities such as Nanchang and Jiujiang have performed well, while cities like Jingdezhen and Xinyu need to enhance resource integration and sustainable development. (2) The coupling coordination degree (CCD) has experienced a process of “stability-fluctuation-recovery”, with a significant increase after 2014, and the spatial differentiation characteristics are obvious. (3) Wetlands play a dominant role in the spatial differentiation of CCD, and their interaction with water, energy, and food resources significantly enhance the explanatory power of their impact on CCD. (4) The grey model indicates that the CCDs of WEFW systems in most cities of Jiangxi Province have a projected annual growth rate of 1.8% (2022–2032), reaching 0.71–0.73 in leading cities. These results emphasize the importance of wetland protection and sustainable resource management in promoting regional coordinated development. The research and prediction of the coupling coordination relationship of water-energy-food-wetland systems can provide a scientific basis for the sustainable development of Jiangxi Province and also offer important scientific references for other regions to achieve a balance between ecological protection and resource utilization. Full article

Farmland shelterbelts are vital ecological infrastructure for sustaining agriculture in arid regions, where high winds, soil erosion, and water scarcity severely constrain productivity. While their protective functions—reducing wind speed, controlling erosion, moderating microclimates, and enhancing yields—are well documented, previous studies have largely examined individual structural elements in isolation, leaving their interactive effects and trade-offs poorly understood. This review synthesizes current research on the structural optimization of shelterbelts, emphasizing the critical relationship between their physical and biological attributes and their protective functions. Key structural parameters—such as optical porosity, height, width, orientation, and species composition—are examined for their individual and interactive impacts on shelterbelt performance. Empirical and modeling studies indicate that moderate porosity maximizes wind reduction efficiency and extends the leeward protection zone, while multi-row, multi-species configurations effectively suppress soil erosion and improve microclimate conditions. Sheltered areas experience reduced evapotranspiration, increased humidity, and moderated temperatures, collectively enhancing crop water use efficiency and yielding significant improvements in crop production. Advanced methodologies, including field monitoring, wind tunnel testing, computational fluid dynamics, and remote sensing, are employed to quantify benefits and refine designs. A multi-objective optimization framework is essential to balance competing goals: maximizing wind reduction, minimizing water consumption, enhancing biodiversity, and ensuring economic viability. Future challenges involve adapting designs to climate change, integrating water-efficient and native species, leveraging artificial intelligence for predictive modeling, and addressing socio-economic barriers to implementation. Building on this evidence, we propose a multi-objective optimization framework to balance competing goals: maximizing wind protection, minimizing water use, enhancing biodiversity, and ensuring economic viability. We identify key research gaps including unresolved porosity thresholds, the climate resilience of alternative species compositions, and the limited application of optimization algorithms and outline future priorities such as region-specific design guidelines, AI-driven predictive models, and policy incentives. This review offers a novel, trade-off–aware synthesis to guide next-generation shelterbelt design in arid agriculture. Full article

Rail transport is widely regarded as an efficient and environmentally sustainable mode of mobility, although lifecycle emissions from infrastructure can diminish its ecological benefits. This study assesses a novel slab track system design that replaces conventional concrete components with recycled polymeric composite sleepers, supporting circular economy objectives. Analytical calculations (per EN 16432-2 and EN 13230-6) and finite element analysis (FEA) were conducted on a 2.6 m polymeric composite sleeper model under static vertical loading. The results demonstrate that bonded base layers comprising asphalt and hydraulically bound materials reduce bending stresses within the sleeper to 1.307 N/mm², substantially below the 5.50 N/mm² observed without bound layers and well below both characteristic fatigue limits. Laboratory validation via strain-gauge measurements corroborates the numerical model. Despite minor torsional effects from first-batch production, the polymeric composite sleeper design is structurally viable for slab track applications. The methodology is directly transferable to alternative composite designs, allowing material-based adaptation of mechanical performance. These findings support the use of recycled polymeric composite sleepers in slab track systems, combining structural adequacy with enhanced circularity. Further research can base itself on the findings and should incorporate long-term durability testing. Full article

Global environmental and sustainability concerns are increasingly pressuring industries in all developing economies to align their supply chain operations with ecological, social, and economic responsibilities. This study investigates the extent to which Sustainable Supply Chain Management (SSCM) enablers are influencing firm-level productivity in a developing economy, and how effectively the practices of SSCM mediate this relationship. This research aims to determine the extent to which Sustainable Supply Chain Management (SSCM) enablers influence firm-level productivity in a developing economy, and how effectively SSCM practices mediates this relationship. Building on the Diffusion of Innovation (DOI) theory, the research adopts a well-structured design and employs Structural Equation Modeling (SEM) to test the designed conceptual framework. The findings show that, while direct effects of enablers on productivity are limited, SSCM practices play a critical mediating role in translating these enablers into measurable performance-based improvements. The study contributes theoretical insights by extending DOI theory into the pharmaceutical supply chain context and offers practical guidance for managers and policymakers in developing economies by seeking to enhance competitiveness through sustainable practices. Full article

Entomopathogenic nematodes (EPNs) are valuable biological control agents and research models in agriculture and ecology. Traditional extraction and rearing methods for EPNs, such as the Baermann funnel and White trap, work well but have limitations in efficiency and practicality. The NEMA Device, constructed from PVC components, was designed to address these limitations by combining extraction and rearing into a single tool with improved portability, scalability, and ease of use. The efficiency of the NEMA Device was evaluated by comparing it to the conventional Baermann funnel extraction method and the White trap method for nematode multiplication. Validation of the instrument was performed using two nematode species, Steinernema khuongi and Heterorhabditis bacteriophora, which vary in size and can be used for pest control. Our results demonstrated that the NEMA Device achieved higher recovery rates of both S. khuongi and H. bacteriophora compared to the Baermann method. Additionally, the production rate of nematodes using the NEMA Device was comparable to that of the White trap method, with no significant difference observed between the two methods. The NEMA Device offers a standardized, cost-effective methodology for the extraction and multiplication of EPNs, enhancing the accessibility and efficiency of studying these agriculturally important nematodes and potentially improving biological control outcomes. Full article

Background/Objectives: As global aging accelerates, there is a pressing and empirically substantiated demand for integrated and sustainable strategies, as evidenced by the rising prevalence rates of chronic conditions, social isolation, and digital exclusion among older adults worldwide. These factors underscore the urgent need for multidimensional interventions that simultaneously target physical, psychological, and social well-being. The HOPE-FIT (Hybrid Outreach Program for Exercise and Follow-up Integrated Training) model and the SAGE (Senior Active Guided Exercise) program were designed to address this need through a hybrid framework. These programs foster inclusive aging by explicitly bridging digitally underserved groups and mobility-restricted populations into mainstream health promotion systems through tailored exercise, psychosocial support, and smart-home technologies, thereby functioning as a scalable meta-model across healthcare, community, and policy domains. Methods: HOPE-FIT was developed through a formative, multi-phase process grounded in the RE-AIM framework and a Hybrid Type II effectiveness–implementation design. The program combines professional health coaching, home-based and digital exercise routines, Acceptance and Commitment Performance Training (ACPT)-based psychological strategies, and smart-home monitoring technologies. Empirical data from pilot studies, large-scale surveys (N = 1000), and in-depth user evaluations were incorporated to strengthen validity and contextual adaptation. Culturally tailored content and participatory feedback from older adults further informed ecological validity and program refinement. Implementation Strategy/Framework: The theoretical foundation integrates implementation science with behavioral and digital health. The RE-AIM framework guided reach, fidelity, and maintenance planning, while the Hybrid E–I design enabled the concurrent evaluation of effectiveness outcomes and contextual implementation strategies. Institutional partnerships with community centers, public health organizations, and welfare agencies further facilitated the translation of the model into real-world aging contexts. Dissemination Plan: The multi-pronged dissemination strategy includes international symposia, interdisciplinary academic networks, policy briefs, localized community deployment, and secure, authenticated data sharing for reproducibility. This design facilitates evidence-informed policy, empowers practitioners, and advances digital health equity. Ultimately, HOPE-FIT constitutes a scalable and inclusive model that concretely addresses health disparities and promotes active, dignified aging across systems and disciplines. Full article

The terpeno-heterocyclic molecular hybrids are a new and promising class of modern organic and medicinal chemistry, because their molecules exhibit high and selective biological activity, natural origins, and good biocompatibility, and, usually, they are less toxic. The reported norlabdane-heterocyclic hybrids were synthesized by classical and new, original, and environmentally friendly methods, which include coupling reactions of norlabdane derivatives (such as carboxylic acids, acyl chlorides, or bromides) with individual heterocyclic compounds, as well as heterocyclization reactions of certain norlabdane intermediates like hydrazides, thiosemicarbazones, or hydrazinecarbothioamides. The aforementioned norlabdanes were derived from (+)-sclareolide 2, which is readily obtained from (−)-sclareol 1, a labdane-type diterpenoid extracted from the waste biomass of Clary sage (Salvia sclarea L.) that remains after essential oil extraction. All synthesized compounds were tested against various fungal strains and bacterial species, with many exhibiting significant antifungal and antibacterial activity. These findings support the potential application of the synthesized compounds in the treatment of diseases caused by fungi and bacteria. Additionally, the use of plant-based waste materials as starting resources highlights the economic and ecological value of this approach. This review summarizes experimental data on the synthesis and biological activity of norlabdane: diazine, 1,2,4-triazole and carbazole, 1,3,4-oxadiazole, 1,3,4-thiadiazole, 1,3-thiazole, 1,3-benzothiazole and 1,3-benzimidazole hybrids performed by our research group covering the period from 2013 to the present. Full article