Search Results (3,277)

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

The terahertz waves are electromagnetic waves with frequencies ranging from 0.1 to 10 THz, exhibiting characteristics of both microwave and infrared, including fingerprint characteristics, coherence, and safety. Due to the weak interactions among most organic macromolecules in substances, the vibrational modes of molecular frameworks, as well as dipole rotation and vibration transitions, often correspond to the terahertz spectral region. Consequently, there has been growing interest in applying terahertz technology within the food industry. This review summarizes the fundamental principles of terahertz spectroscopy for substance detection and highlights recent advances and applications in food analysis. Key applications include harmful contaminant detection, component analysis, quality assessment, and adulteration identification. Additionally, this review discusses current challenges in applying terahertz spectroscopy to food analysis, such as strong water absorption, matrix interference, and the lack of comprehensive spectral databases. Finally, the paper outlines future prospects, including the development of lightweight and cost-effective terahertz sources and detectors for on-site analysis, as well as the integration of terahertz spectroscopy with other modern detection technologies to enhance analytical performance. This work aims to serve as a reference for further research and development of terahertz spectroscopy in the food sector. Full article

The growing penetration of distributed photovoltaic (PV) systems presents significant operational challenges for power grids, driven by the scarcity of historical data and the high spatiotemporal variability of PV generation. To address these challenges, we propose Generative Reconstruction and Adaptive Identification via Latents (GRAIL), a unified, end-to-end framework that integrates generative modeling with adaptive clustering to discover latent structures and representative scenarios in PV datasets. GRAIL operates through a closed-loop mechanism where clustering feedback guides a cluster-aware data generation process, and the resulting generative augmentation strengthens partitioning in the latent space. Evaluated on a real-world, multi-site PV dataset with a high missing data rate of $45.4\%$, GRAIL consistently outperforms both classical clustering algorithms and deep embedding-based methods. Specifically, GRAIL achieves a Silhouette Score of 0.969, a Calinski–Harabasz index exceeding $4.132\times {10}^6$, and a Davies–Bouldin index of $0.042$, demonstrating superior intra-cluster compactness and inter-cluster separation. The framework also yields a normalized entropy of $0.994$, which indicates highly balanced partitioning. These results underscore that coupling data generation with clustering is a powerful strategy for expressive and robust structure learning in data-sparse environments. Notably, GRAIL achieves significant performance gains over the strongest deep learning baseline that lacks a generative component, securing the highest composite score among all evaluated methods. The framework is also computationally efficient. Its alternating optimization converges rapidly, and clustering and reconstruction metrics stabilize within approximately six iterations. Beyond quantitative performance, GRAIL produces physically interpretable clusters that correspond to distinct weather-driven regimes and capture cross-site dependencies. These clusters serve as compact and robust state descriptors, valuable for downstream applications such as PV forecasting, dispatch optimization, and intelligent energy management in modern power systems. Full article

With the strict requirements of national policies on truck dimensions, axle loads, and weight limits, along with the implementation of tolls based on vehicle types, rapid and accurate identification of vehicle axle types has become essential for toll station management. To address the limitations of existing methods in distinguishing between drive and driven axles, complex equipment setup, and image evidence retention, this article proposes a panoramic image detection technology for vehicle chassis based on enhanced ORB and YOLOv11. A portable vehicle chassis image acquisition system, based on area array cameras, was developed for rapid on-site deployment within 20 min, eliminating the requirement for embedded installation. The FeatureBooster (FB) module was employed to optimize the ORB algorithm’s feature matching, and combined with keyframe technology to achieve high-quality panoramic image stitching. After fine-tuning the FB model on a domain-specific area scan dataset, the number of feature matches increased to 151 ± 18, substantially outperforming both the pre-trained FB model and the baseline ORB. Experimental results on axle type recognition using the YOLOv11 algorithm combined with ORB and FB features demonstrated that the integrated approach achieved superior performance. On the overall test set, the model attained an mAP@50 of 0.989 and an mAP@50:95 of 0.780, along with a precision (P) of 0.98 and a recall (R) of 0.99. In nighttime scenarios, it maintained an mAP@50 of 0.977 and an mAP@50:95 of 0.743, with precision and recall both consistently at 0.98 and 0.99, respectively. The field verification shows that the real-time and accuracy of the system can provide technical support for the axle type recognition of toll stations. Full article

Protection of coastal cultural heritage is among the most urgent global priorities, as these sites face increasing threats from climate change, sea level rise, and human activity. This study emphasises the value of innovative geospatial tools and data ecosystems for timely risk assessment. The role of land administration systems, geospatial documentation of coastal cultural heritage sites, and the adoption of innovative techniques that combine various methodologies is crucial for timely action. The coastal management infrastructure in Greece is presented, outlining the key public authorities and national legislation, as well as the land administration and geospatial ecosystems and the various available geospatial ecosystems. We profile the Hellenic Cadastre and the Hellenic Archaeological Cadastre along with open geospatial resources, and introduce TRIQUETRA Decision Support System (DSS), produced through the EU’s Horizon project, and a Digital Twin methodology for hazard identification, quantification, and mitigation. Particular emphasis is given to the role of Digital Twin technology, which acts as a continuously updated virtual replica of coastal cultural heritage sites, integrating heterogeneous geospatial datasets such as cadastral information, photogrammetric 3D models, climate projections, and hazard simulations, allowing for stakeholders to test future scenarios of sea level rise, flooding, and erosion, offering an advanced tool for resilience planning. The approach is validated at the coastal archaeological site of Aegina Kolona, where a UAV-based SfM-MVS survey produced using high-resolution photogrammetric outputs, including a dense point cloud exceeding 60 million points, a 5 cm resolution Digital Surface Model, high-resolution orthomosaics with a ground sampling distance of 1 cm and 2.5 cm, and a textured 3D model using more than 6000 nadir and oblique images. These products provided a geospatial infrastructure for flood risk assessment under extreme rainfall events, following a multi-scale hydrologic–hydraulic modelling framework. Island-scale simulations using a 5 m Digital Elevation Model (DEM) were coupled with site-scale modelling based on the high-resolution UAV-derived DEM, allowing for the nested evaluation of water flow, inundation extents, and velocity patterns. This approach revealed spatially variable flood impacts on individual structures, highlighted the sensitivity of the results to watershed delineation and model resolution, and identified critical intervention windows for temporary protection measures. We conclude that integrating land administration systems, open geospatial data, and Digital Twin technology provides a practical pathway to proactive and efficient management, increasing resilience for coastal heritage against climate change threats. Full article

Historically, the Mediterranean Sea has been an area of cultural exchange and maritime commerce. One out of many submerged archaeological sites is the Roman shipwreck that was discovered in 2006 off the coast of Santo Stefano al Mare, in the Ligurian Sea, Italy. The wreck was dated to the 1st century B.C. and consists of a well-preserved cargo ship of Roman amphorae that were likely used for transporting wine. In this study, we present the results of the first underwater survey of the wreck using an Autonomous Underwater Vehicle (AUV) industrialized by Graal Tech. The AUV was equipped with a NORBIT WBMS multibeam sonar, a 450 kHz side-scan sonar, and inertial navigation systems. The AUV conducted multiple high-resolution surveys on the wreck site and the collected data were processed using geospatial analysis methods to highlight local anomalies directly related to the presence of the Roman shipwreck. The main feature was an accumulation of amphorae, covering an area of approximately 10 × 7 m with a maximum height of 1 m above the seabed. The results of this interdisciplinary work demonstrated the effectiveness of integrating AUV technologies with spatial analysis techniques for underwater archaeological applications. Furthermore, the success of this mission highlighted the potential for broader applications of AUVs in the study of the seafloor, such as monitoring seabed movements related to offshore underground energy storage or the identification of objects lying on the seabed, such as cables or pipelines. Full article

CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated protein) nucleases enable precise genome editing, but off-target cleavage remains a critical challenge. Here, we report the development of MAD7_HF, a high-fidelity variant of the MAD7 nuclease engineered through a bacterial screening system leveraging the DNA gyrase-targeting toxic gene ccdB. This system couples survival to efficient on-target cleavage and minimal off-target activity, mimicking the transient action required for high-precision editing. Through iterative selection and sequencing validation, we identified MAD7_HF, harboring three substitutions (R187C, S350T, K1019N) that enhanced discrimination between on- and off-target sites. In Escherichia coli assays, MAD7_HF exhibited a >20-fold reduction in off-target cleavage across multiple mismatch contexts while maintaining on-target efficiency comparable to wild-type MAD7. Structural modeling revealed that these mutations stabilize the guide RNA-DNA hybrid at on-target sites and weaken interactions with mismatched sequences. This work establishes a high-throughput bacterial screening strategy that allows the identification of Cas12a variants with improved specificity at a given target site, providing a useful framework for future efforts to develop precision genome-editing tools. Full article

Chlorpyrifos CPF (O,O-diethyl O-(3,5,6-trichloro-2-pyridyl) phosphorothioate), known also as Chlorpyrifos-ethyl, is one of the most utilized organophosphorus pesticides worldwide. Additionally, CPF could be used as a chemical warfare agent surrogate. Although its acute toxicity is not high, it is responsible for both a large number of intoxications and chronic, delayed neurological effects. In this work, it is reported for the first time the qualitative and quantitative response produced by CPF vapors, using a pocket-held Time-of-Flight Ion Mobility Spectrometer (ToF IMS) with a non-radioactive ionization source and ammonia doping, model LCD-3.2E (Smiths Detection Ltd.), operated near ambient temperature (below 30 °C). Spectra of CPF in positive ion mode included two distinct product ion peaks; thus, identification of CPF vapors by IMS relies on these peaks—the monomer M·NH₄⁺ with reduced ion mobility K₀ = ca. 1.76 cm² V⁻¹ s⁻¹ and the dimer M₂·NH₄⁺ with K₀ = ca. 1.47 cm² V⁻¹ s⁻¹ (where M may be assignable to CPF molecule)—and positive reactant ions (Pos RIP) have K₀ = ca. 2.25 cm² V⁻¹ s⁻¹. Excellent sensitivity, with a limit of detection LOD of 0.72 ppb_v (10.5 μg m⁻³) and a limit of quantification LOQ of 2.41 ppb_v (35.1 μg m⁻³), has been noticed; linear response was up to 100 ppb_v, while saturation occurs over ca. 1000 ppb_v (14.6 mg m⁻³). Our results demonstrate that this method provides a robust tool for both off-site and on-site detecting and quantifying CPF vapors at trace levels, which has strong implications for either industrial hygiene or forensic investigations concerning the pesticide Chlorpyrifos, as well as for monitoring of environmental contamination by organophosphorus pesticides. Full article

The rapid and reliable acquisition of canopy-related metrics is essential for improving decision support in viticultural management, particularly when monitoring individual vines for targeted interventions. This study presents a spatially explicit workflow that integrates Uncrewed Aerial System (UAS) imagery, 3D point-cloud analysis, and Object-Based Image Analysis (OBIA) to detect and monitor individual grapevines throughout the growing season. Vines are identified directly from 3D point clouds without the need for prior training data or predefined row structures, achieving a mean Euclidean distance of 10.7 cm to the reference points. The OBIA framework segments vine vegetation based on spectral and geometric features without requiring pre-clipping or manual masking. All non-vine elements—including soil, grass, and infrastructure—are automatically excluded, and detailed canopy masks are created for each plant. Vegetation indices are computed exclusively from vine canopy objects, ensuring that soil signals and internal canopy gaps do not bias the results. This enables accurate per-vine assessment of vigour. NDRE values were calculated at three phenological stages—flowering, veraison, and harvest—and analyzed using Local Indicators of Spatial Association (LISA) to detect spatial clusters and outliers. In contrast to value-based clustering methods, LISA accounts for spatial continuity and neighborhood effects, allowing the detection of stable low-vigour zones, expanding high-vigour clusters, and early identification of isolated stressed vines. A strong correlation (R² = 0.73) between per-vine NDRE values and actual yield demonstrates that NDRE-derived vigour reliably reflects vine productivity. The method provides a transferable, data-driven framework for site-specific vineyard management, enabling timely interventions at the individual plant level before stress propagates spatially. Full article

Seabed-related issues are common in offshore areas. This poses significant challenges for the design and construction of offshore engineering projects. Under unfavourable seabed soil conditions, foundations may fail to meet the load-bearing capacity requirements, resulting in severe settlement and tilting and, ultimately, the failure of offshore structures. Despite the critical nature of these challenges, a comprehensive literature review for the identification and risk analysis of various unfavourable seabed soil conditions is currently lacking. This paper provides an overview of five key challenges related to seabed soil conditions in China, namely thick, soft mud layers; shallow gas and pockmarks; sand liquefaction; dense sand layers; and boulder stones. The formation mechanisms, distribution areas and engineering characteristics of these conditions are discussed in detail, integrating insights from previous research. Data from site investigations of real-world offshore engineering projects are presented, based on which risk assessment is conducted. This study not only enhances our understanding of the identification, distribution and hazards associated with various unfavourable seabed soil conditions in offshore engineering but also offers guidance on utilizing investigation data for effective risk assessment. Full article

Red bricks serve as an important material for load-bearing or enclosing structures in traditional architecture and are widely used in construction projects both domestically and internationally. Fujian red bricks, due to geographical, trade, and immigration-related factors, have spread to Taiwan and various regions in Southeast Asia, giving rise to distinctive red brick architectural complexes. To further investigate the types of damage, such as cracking and missing bricks, that occur in traditional red brick buildings due to multiple factors, including climate and human activities, this study takes Fujian red brick buildings as its research subject. It employs the YOLOv12 rapid detection method to conduct technical support research on structural assessment, type detection, and damage localization of surface damage in red brick building materials. The experimental model was conducted through the following procedures: on-site photo collection, slice marking, creation of an image training set, establishment of an iterative model training, accuracy analysis, and experimental result verification. Based on this, the causes of damage types and corresponding countermeasures were analyzed. The objective of this study is to attempt to utilize computer vision image recognition technology to provide practical, automated detection and efficient identification methods for damage types in red brick building brick structures, particularly those involving physical and mechanical structural damage that severely threaten the overall structural safety of the building. This research model will reduce the complex manual processes typically involved, thereby improving work efficiency. This enables the development of customized intervention strategies with minimal impact and enhanced timeliness for the maintenance, repair, and preservation of red brick buildings, further advancing the practical application of intelligent protection for architectural heritage. Full article

Highly Hazardous Pesticides (HHPs) pose severe risks to human health and the environment, making it essential to understand their molecular stability and degradation pathways. In this study, the Quantum Theory of Atoms in Molecules (QTAIM) was applied to four representative organophosphate pesticides, allowing the identification of electronically weak bonds as intrinsic sites of lability. These findings are consistent with reported hydrolytic, oxidative, enzymatic, and microbial degradation routes. Importantly, QTAIM descriptors proved largely insensitive to solvation, confirming their intrinsic character within the molecular electronic structure. To complement QTAIM, conceptual DFT (Density Functional Theory) reactivity indices were analyzed, revealing that solvent effects induce more noticeable variations in global and local descriptors than in topological parameters. In addition, a Topological Analysis of the Fukui Function (TAFF) was performed, which mapped nucleophilic, electrophilic, and radical susceptibilities directly onto QTAIM basins. The TAFF analysis confirmed that bonds identified as weak by QTAIM (notably P–O, P–S, and P–N linkages) also coincide with the most reactive sites, thereby reinforcing their mechanistic role in degradation pathways. This integrated framework highlights the robustness of QTAIM, the sensitivity of global and local reactivity descriptors to solvation revealed by conceptual DFT, and the complementary insights provided by TAFF, contributing to risk assessment, remediation strategies, and the rational design of safer pesticides. Full article

Background: Tumor-associated macrophages (TAMs) are important contributors to tumor progression and metastasis. Therefore, the identification of molecules that mediate these cells’ tumor-promoting functions is highly warranted. VSIG4 has been proposed as a macrophage immune checkpoint. Hence, we aim to investigate this marker in preclinical models. Methods: Publicly available scRNAseq datasets of human colorectal (CRC) and triple-negative breast (TNBC) carcinomas and their murine counterparts were reanalyzed to investigate the expression of VSIG4 in the different TAM populations. Moreover, tumors were grown in Vsig4-deficient mice to evaluate the effect on primary tumor characteristics. Finally, since liver Kupffer cells and large peritoneal macrophages are at least partly VSIG4-high, and are implicated in metastasis to those organs, the dissemination of CRC cancer cells to those sites was assessed in the Vsig4-deficient mice. Results: We demonstrate that VSIG4 expression in human CRC and TNBC is mostly restricted to TAMs, and that its expression correlates with a worse prognosis. However, a striking finding was that no Vsig4 mRNA nor protein could be detected in the microenvironment of primary CRC and TNBC murine tumors, resulting in a similar tumor growth in wild type versus Vsig4-deficient mice. Moreover, no major differences were observed in metastatic tumor load in the liver and peritoneal cavity, apart from a reduced metastasis to the omentum in Vsig4-deficient animals. Conclusions: Murine cancer models are not suitable to investigate the role of VSIG4 in primary tumors and VSIG4 deficiency did not alter liver nor peritoneal cavity metastasis in murine models, with the exception of the omentum. Full article

Analysis of selection signatures in the genomes of farm animals enables the detection of genomic regions affected by selection and contributes to the identification of genes underlying adaptive and productive traits. This research aimed to identify loci under selection pressure and to detect candidate genes in Dzhalgin Merino sheep by performing a comparative genomic analysis with the related Australian Merino and Rambouillet breeds. A total of 293 animals were included in the analysis, comprising Dzhalgin Merino (n = 53), Australian Merino (n = 50), Australian Industry Merino (n = 88), and Rambouillet (n = 102). Whole-genome SNP genotyping data for Dzhalgin Merino were generated within this study, while data for Australian Merino, Australian Industry Merino, and Rambouillet were obtained from the SheepHapMap project. For the purposes of analysis, Australian Merino and Australian Industry Merino were combined into a single group (n = 138). To enhance the reliability of the results, three independent methods were employed to detect selection signatures: the fixation index (FST), analysis of linkage disequilibrium variation (varLD), and the cross-population number of segregating sites by length (xp-nSL). The study showed that Dzhalgin Merino have unique genetic signatures potentially associated with adaptation and productivity, which opens up new opportunities for their selection. The identified genes can become the basis for developing new breeding programs aimed at improving both the productive qualities and the adaptive abilities of the breed. Further research should be aimed at a detailed investigation of gene structure within loci under selection pressure and at clarifying the mechanisms by which these genes influence animal phenotypes. A total of 185 genes were identified within genomic regions exhibiting selection signatures. Among these, particular attention was given to EPHA6, MLLT3, ROBO1, KIAA0753, MED31, SLC13A5, and ELAVL4, which are involved in biological processes such as growth, development, and reproduction. The identified genes represent potential targets for breeding programs aimed at increasing productivity and adaptive capacity of the breed. Full article

Biomphalaria pfeifferi snails serve as the major intermediate host for intestinal schistosomiasis in Sudan. The genetic structure and infection status of 163 B. pfeifferi collected from six localities in Gezira State, Sudan (East Gezira, Greater Wadmedani, Hasahisa, North Umelgura, South Gezira, and Managil) were characterized. Cytochrome oxidase subunit I (COI) and 16S ribosomal RNA (16S rRNA) mitochondrial genes were used for B. pfeifferi molecular identification and genetic diversity investigation. Schistosoma mansoni infection was detected using the traditional cercarial shedding and molecular methods (Sm^F/R primers). Five COI haplotypes and ten 16S haplotypes were identified, with haplotype diversity of 0.50 for COI and 0.11 for 16S. High evolutionary divergence was observed between groups (Fst = 0.94) for the COI, and low genetic divergence (Fst = 0.04) for the 16S, indicating genetic divergence among Sudanese B. pfeifferi, with the 16S showing lower divergence than the COI, consistent with a post-bottleneck population expansion. Cercarial shedding detected an overall infection prevalence of 3.6% (8/219), with only two snails from Hasahisa shedding S. mansoni cercariae. The Sm^F/R primers revealed a higher infection prevalence of 7.4% (12/163), with all S. mansoni positive samples found at the Hasahisa site. Findings highlight the value of molecular diagnostic tools for accurate surveillance and emphasize the need for site-specific control strategies. Full article