A centrality measure based on the time of first returns rather than the number of steps is developed and applied to finding proton traps and access points to proton highways in the doped perovskite oxides: AZr(0.875)D(0.125)O3, where A is Ba or Sr and the dopant D is Y or Al. The high centrality region near the dopant is wider in the SrZrO3 systems than the BaZrO3 systems. In the aluminum-doped systems, a region of intermediate centrality (secondary region) is found in a plane away from the dopant. Kinetic Monte Carlo (kMC) trajectories show that this secondary region is an entry to fast conduction planes in the aluminum-doped systems in contrast to the highest centrality area near the dopant trap. The yttrium-doped systems do not show this secondary region because the fast conduction routes are in the same plane as the dopant and hence already in the high centrality trapped area. This centrality measure complements kMC by highlighting key areas in trajectories. The limiting activation barriers found via kMC are in very good agreement with experiments and related to the barriers to escape dopant traps.
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http://dx.doi.org/10.1063/1.4917469 | DOI Listing |
J Phys Ther Sci
January 2025
Department of Rehabilitation, School of Health Sciences, Tokyo University of Technology: 5-23-22 Nishikamata, Ota-ku, Tokyo 144-8535, Japan.
[Purpose] This study aimed to clarify regional disparities in the provision of home-visit rehabilitation services across all prefectures in Japan by performing a secondary analysis of government data. [Participants and Methods] The number of home-visit rehabilitation sessions per prefecture was determined to estimate regional disparities. Furthermore, the data for 2013 and 2021 were compared to investigate changes in home-visit rehabilitation provision.
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Department of Life Sciences, Changzhi University, Changzhi, China.
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National Institute of Molecular Biology and Biotechnology, College of Science, University of the Philippines Diliman, Quezon City, Philippines.
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View Article and Find Full Text PDFUnlabelled: Structural RNAs exhibit a vast array of recurrent short 3D elements involving non-Watson-Crick interactions that help arrange canonical double helices into tertiary structures. We present CaCoFold-R3D, a probabilistic grammar that predicts these RNA 3D motifs (also termed modules) jointly with RNA secondary structure over a sequence or alignment. CaCoFold-R3D uses evolutionary information present in an RNA alignment to reliably identify canonical helices (including pseudoknots) by covariation.
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