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Interstitial oxygen embrittles titanium, particularly at cryogenic temperatures, which necessitates a stringent control of oxygen content in fabricating titanium and its alloys. Here, we propose a structural strategy, via grain refinement, to alleviate this problem. Compared to a coarse-grained counterpart that is extremely brittle at 77 K, the uniform elongation of an ultrafine-grained (UFG) microstructure (grain size ~ 2.0 µm) in Ti-0.3wt.%O is successfully increased by an order of magnitude, maintaining an ultrahigh yield strength inherent to the UFG microstructure. This unique strength-ductility synergy in UFG Ti-0.3wt.%O is achieved via the combined effects of diluted grain boundary segregation of oxygen that helps to improve the grain boundary cohesive energy and enhanced
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http://dx.doi.org/10.1038/s41467-023-36030-0 | DOI Listing |
Curr Dev Nutr
September 2025
Department of Health, Nutrition, and Food Sciences, Florida State University, Tallahassee, FL, United States.
Background: The objective of this study was to compare the effects of daily consumption of white potatoes compared with white rice on cardiometabolic health in individuals with type-2 diabetes (T2D).
Objective: To determine the effects of white potato consumption compared to white rice (a commonly consumed refined grain) on indices of glycemic control and cardiovascular health in individuals with overweight or obesity and T2D.
Methods: In this randomized crossover study, comparative control trial, 24 adults with T2D [45-80 y, body mass index (kg/m) 25-40] consumed baked white potatoes (100 g) or calorie-matched white rice (75 g) daily for 12 wk, separated by a 2-wk washout, with assessments of glycemic control, lipids, inflammation, blood pressure, endothelial function, and body composition at baseline (only 1 baseline visit included as a covariate in statistical analyses), 6 wk, and 12 wk.
iScience
September 2025
State Key Laboratory of Advanced Marine Materials, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China.
Super austenitic stainless steels (SASS) face challenges like galvanic corrosion and antibacterial performance when welded to carbon steel (Q235) in marine environments. This study demonstrates that adding 1.0 wt% cerium (Ce) to SASS refines the heat-affected zone (HAZ) grain structure (from 7 μm to 2 μm), suppresses detrimental σ-phase precipitation, and forms a dense oxide film.
View Article and Find Full Text PDFRSC Adv
September 2025
Laboratory of Spectroscopic Characterization and Optical Materials, Faculty of Sciences, University of Sfax B.P. 1171 3000 Sfax Tunisia
Lithium metavanadate (LiVO) is a material of growing interest due to its monoclinic 2/ structure, which supports efficient lithium-ion diffusion through one-dimensional channels. This study presents a detailed structural, electrical, and dielectric characterization of LiVO synthesized a solid-state reaction, employing X-ray diffraction (XRD), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS), and impedance/dielectric spectroscopy across a temperature range of 473-673 K and frequency range of 10 Hz to 1 MHz. XRD and Rietveld refinement confirmed high crystallinity and single-phase purity with lattice parameters = 10.
View Article and Find Full Text PDFJ Med Imaging (Bellingham)
September 2025
Vanderbilt University, Data Science Institute, Nashville, Tennessee, United States.
Purpose: Recent developments in computational pathology have been driven by advances in vision foundation models (VFMs), particularly the Segment Anything Model (SAM). This model facilitates nuclei segmentation through two primary methods: prompt-based zero-shot segmentation and the use of cell-specific SAM models for direct segmentation. These approaches enable effective segmentation across a range of nuclei and cells.
View Article and Find Full Text PDFFront Artif Intell
August 2025
Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada.
Precision livestock farming increasingly relies on non-invasive, high-fidelity systems capable of monitoring cattle with minimal disruption to behavior or welfare. Conventional identification methods, such as ear tags and wearable sensors, often compromise animal comfort and produce inconsistent data under real-world farm conditions. This study introduces Dairy DigiD, a deep learning-based biometric classification framework that categorizes dairy cattle into four physiologically defineda groups-young, mature milking, pregnant, and dry cows-using high-resolution facial images.
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