This paper presents a novel approach to continuously monitor very slow-moving translational landslides in mountainous terrain using conventional and experimental differential global navigation satellite system (d-GNSS) technologies. A key research question addressed is whether displacement trends captured by a radio-frequency "mobile" d-GNSS network compare with the spatial and temporal patterns in activity indicated by satellite interferometric synthetic aperture radar (InSAR) and unmanned aerial vehicle (UAV) photogrammetry. Field testing undertaken at Ripley Landslide, near Ashcroft in south-central British Columbia, Canada, demonstrates the applicability of new geospatial technologies to monitoring ground control points (GCPs) and railway infrastructure on a landslide with small and slow annual displacements (<10 cm/yr). Each technique records increased landslide activity and ground displacement in late winter and early spring. During this interval, river and groundwater levels are at their lowest levels, while ground saturation rapidly increases in response to the thawing of surficial earth materials, and the infiltration of snowmelt and runoff occurs by way of deep-penetrating tension cracks at the head scarp and across the main slide body. Research over the last decade provides vital information for government agencies, national railway companies, and other stakeholders to understand geohazard risk, predict landslide movement, improve the safety, security, and resilience of Canada's transportation infrastructure; and reduce risks to the economy, environment, natural resources, and public safety.
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http://dx.doi.org/10.1007/s11629-020-6552-y | DOI Listing |
Biomed Phys Eng Express
January 2025
Applied Sciences, Indian Institute of Information Technology Allahabad, Deoghat, Jhalwa, Allahabad, 211012, INDIA.
Photoacoustic tomography (PAT) is a non-destructive, non-ionizing, and rapidly expanding hybrid biomedical imaging technique, yet it faces challenges in obtaining clear images due to limited data from detectors or angles. As a result, the methodology suffers from significant streak artifacts and low-quality images. The integration of deep learning (DL), specifically convolutional neural networks (CNNs), has recently demonstrated powerful performance in various fields of PAT.
View Article and Find Full Text PDFJ Strength Cond Res
February 2025
Sports Medicine and Movement Laboratory, School of Kinesiology, Auburn University, Auburn Alabama.
Bordelon, NM, Agee, TW, Wasserberger, KW, Downs-Talmage, JL, Everhart, KM, and Oliver, GD. Field-testing measures related to youth baseball hitting performance. J Strength Cond Res 39(2): 210-216, 2025-The purpose of the study was to determine the relationship between field tests and youth hitting performance (batted-ball velocity).
View Article and Find Full Text PDFH*10 neutron dosimetry (unlike gamma dosimetry), requires consideration of neutron energy spectra due to the 20× variation of the weight factor over the thermal-to-fast energy range, as well as the neutron radiation field dose rates ranging from cosmic, ~.01 μSv h-1 levels to commonly encountered ~10-200 μSv h-1 in nuclear laboratories/processing plants, and upwards of 104 Sv h-1 in nuclear reactor environments. This paper discusses the outcome of the comparison of spectrum-weighted neutron dosimetry covering thermal-to-fast energy using the novel H*-TMFD spectroscopy-enabled sensor system in comparison with measurements using state-of-the-art neutron dosimetry systems at SRNS-Rotating Spectrometer (ROSPEC), and non-spectroscopic Eberline ASP2E ("Eberline") and Ludlum 42-49B ("Ludlum") survey instrumentation.
View Article and Find Full Text PDFBioinformatics
January 2025
Department of Statistics, University of Oxford, St Giles', Oxford, OX1 3LB, United Kingdom.
Motivation: Machine learning-based scoring functions (MLBSFs) have been found to exhibit inconsistent performance on different benchmarks and be prone to learning dataset bias. For the field to develop MLBSFs that learn a generalisable understanding of physics, a more rigorous understanding of how they perform is required.
Results: In this work, we compared the performance of a diverse set of popular MLBSFs (RFScore, SIGN, OnionNet-2, Pafnucy, and PointVS) to our proposed baseline models that can only learn dataset biases on a range of benchmarks.
PLoS One
January 2025
Chemical & Petroleum Engineering Department, United Arab Emirates University, Al Ain, United Arab Emirates.
Oil fields located in cold environments and deep-sea locations often face challenges with paraffin wax buildup in pipelines during long-distance crude oil transportation. Various strategies have been employed to address this issue, with chemical methods being the most effective and economical. However, traditional chemical inhibitors present problems due to their high toxicity and low biodegradability, leading to increased operational costs and environmental concerns.
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