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University of Nebraska-Lincoln

Academic institutionnorthamerica · us
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Research library158linked papers
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Selected work

Representative Papers

Research Output on Alopecia Areata Disease: A Scientometric Analysis of Publications from 2010 to 2019

Nov 04, 2025Social Science Research Network

This study addresses the lack of systematic bibliometric analyses in alopecia areata (AA) research. Using bibliometric methods and visualization techniques, it analyzes 2,147 publications from 2010–2019 indexed in the Web of Science Core Collection to examine publication trends, country/institutional contributions, core journals, prolific authors, collaboration networks, and citation patterns. Results show a steady annual increase in output, with the highest growth rate in 2019; Columbia University ranked first in institutional productivity; Christiano A.M. and Clynes R. were the most active authors; multi-author collaborations dominated, and journal articles constituted the primary publication format. The analysis identifies key academic actors and knowledge diffusion pathways, revealing a statistically significant positive correlation between author productivity and citation impact. These findings provide empirical evidence to inform strategic research planning, resource allocation, and interdisciplinary collaboration in AA research.

2 citationsRead paper

Russian Contribution to Coronary Artery Disease Research: A Scientometric Mapping of Publications

Nov 05, 2025

This study addresses the lack of scientometric analyses on coronary artery disease (CAD) research in Russia. Using bibliometric mapping, it systematically examines academic output, collaboration networks, and impact evolution of Russian CAD research from 1990 to 2019, based on 5,058 articles indexed in the Web of Science Core Collection (SCI). Descriptive and network analyses reveal sustained growth in publication volume, yet heavy reliance on domestic journals; a shift toward multi-author collaborations and increasing centralization of co-authorship networks; low concentration of high-productivity authors and institutions; and dominance of original articles and reviews. Notably, inter-institutional collaboration remains underdeveloped. As the first scientometric investigation of cardiovascular research in the Russian-language scholarly domain, this work fills a critical gap in the literature and provides empirical evidence to inform strategic resource allocation and international research cooperation.

1 citations1 influentialRead paper

ML-based Adaptive Prefetching and Data Placement for US HEP Systems

Mar 08, 2025

To address the cache adaptability deficiency, poor data locality, and escalating storage/network pressure caused by explosive growth in high-energy physics (HEP) data—e.g., from HL-LHC and DUNE—this paper proposes an hourly adaptive caching strategy. Methodologically, it introduces the first HEP-domain file-granularity hourly access predictor and establishes a two-tier machine learning framework integrating LSTM and CatBoostRegressor to enable fine-grained, dynamic data prefetching and intelligent placement. Evaluated on real SoCal MINI cache traces from August 2024, the approach significantly improves cache hit rate and data locality. Furthermore, the WRENCH simulation platform has been extended to support comprehensive evaluation across multi-level heterogeneous systems. Key contributions include: (1) the first hourly file-access prediction model tailored for HEP workloads; (2) a hybrid ML framework balancing temporal dynamics and feature-rich static attributes; and (3) scalable integration into production-grade simulation infrastructure for realistic system-level assessment.

1 citationsRead paper
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