In 1965 Duwez et al. reported having generated an amorphous, stable phase of palladium-silicon in the region 15 to 23 atomic percent, at.%, silicon. These pioneering efforts have led to the development of solid materials that are now known as Bulk Metallic Glasses, BMG. In 2019 Rodríguez et al. discovered, computationally, that bulk amorphous Pd becomes magnetic, and so does porous/amorphous Pd. Puzzled by these results, the study of several solid binary systems in the Pd-rich zone was undertaken; in particular, the study of the glassy metallic alloy a-Pd[Formula: see text]Si[Formula: see text], for [Formula: see text], (c in at.%) to see what their topology is, what their electronic properties are and to inquire about their magnetism. In this work it is shown that this metallic glass is in fact magnetic in the region [Formula: see text]. Collaterally [Formula: see text] and [Formula: see text] magnetization curves are shown where the net magnetic moment is presented. The topology and the position of the first few peaks of the pair distribution functions, which agrees well with experiment, are also discussed. The BMGs produced experimentally so far are limited in size, but despite this limitation, recent industrial efforts have developed some useful devices that may revolutionize technology.
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http://dx.doi.org/10.1038/s41598-022-08656-5 | DOI Listing |
Sci Rep
December 2024
Radiating Systems Group, Department of Applied Physics, University of Santiago de Compostela, 15782, Santiago de Compostela, Spain.
The following paper presents the findings of a study conducted on the distances at which the field generated by a ϕ-symmetric circular Taylor aperture distribution can be classified as far-field, and also the efficiency across various study parameters. The [Formula: see text] transition integers that produce a monotonic distribution, which have been traditionally used and analyzed, are compared with those that yield a peaked distribution, and offer greater efficiency. Additionally, modified circular Taylor [Formula: see text] distributions featuring synthesized patterns with one or two depressed inner sidelobes, which have not been previously explored, are also examined.
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December 2024
Department of Surgery, The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center, Columbus, OH, USA.
Background: We sought to define whether and how hepatic ischemia/reperfusion (I/R) as manifested by perioperative aspartate aminotransferase (AST) and alanine aminotransaminase (ALT) levels impact long-term outcomes after curative-intent resection of hepatocellular carcinoma (HCC).
Patients And Methods: Intrasplenic injection of HCC cells was used to establish a murine model of HCC recurrence with versus without I/R injury. Patients who underwent curative resection for HCC were identified from a multi-institutional derivative cohort (DC) and separate external validation (VC) cohort.
Sci Rep
December 2024
Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, 632014, India.
This study explores the problem of train scheduling (or) train timetabling and its impact on the administration of railway management. This is a highly dependable and effective public transportation system. The problem considers both single and multiple tracks along with multiple platforms with varying train capacities (like speed, passengers, and so on).
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December 2024
Department of Mathematics, Faculty of Science, The Hashemite University, P.O.Box 330127, Zarqa, 13133, Jordan.
In this study, we developed a Caputo-Fractional Chlamydia pandemic model to describe the disease's spread. We demonstrated the model's positivity and boundedness, ensuring biological relevance. The existence and uniqueness of the model's solution were established, and we investigated the stability of the α-fractional order model.
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December 2024
ETH Zurich, Zurich, Switzerland.
Artificial intelligence (AI) provides considerable opportunities to assist human work. However, one crucial challenge of human-AI collaboration is that many AI algorithms operate in a black-box manner where the way how the AI makes predictions remains opaque. This makes it difficult for humans to validate a prediction made by AI against their own domain knowledge.
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