Utilizing RNA-seq data in monotone iterative generalized linear model to elevate prior knowledge quality of the circRNA-miRNA-mRNA regulatory axis by Alikhan Anuarbekov, Jiří Kléma

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Status assessment and management strategy of a large bridge based on massive real time data by Feng Zhou, Zhihao Cui

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Reorganization of structural connectivity in the brain supports preservation of cognitive ability in healthy aging by Josh Neudorf, Kelly Shen, Anthony R. McIntosh

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The Information-Structural Status of Adjuncts: A Question-under-Discussion-Based Approach by Lisa Brunetti, Kordula De Kuthy, Arndt Riester

“…In this paper we present an analysis of the information structural properties of different types of verb and sentence modifying adjuncts under a QUD (question under discussion) approach. …”
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A continuous multi-night sleep database for exploring sleep structure similarity by Shaofei Ying, Junze Fu, Lin Wang, Haokai Zhang, Yue Yu, Hongqiong Wang, Jiaxin Xie, Tiejun Liu

“…Abstract The sleep structure of healthy adults varies across continuous nights but exhibits periodicity and regularity. …”
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A comprehensive dataset of therapeutic peptides on multi-function property and structure information by Baichuan Xiao, Yixiang Zhou, Long Zhao, Haodong Huang, Xuwen Fei, Yong-Biao Zhang

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Correlating pore space morphology with numerically computed soil gas diffusion for structured loam and sand, including stochastic 3D microstructure modeling by Benedikt Prifling, Matthias Weber, Maximilian Rötzer, Nadja Ray, Alexander Prechtel, Maxime Phalempin, Steffen Schlüter, Doris Vetterlein, Volker Schmidt

Subjects: “…Structure–property relationship…”
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Coherent Radio Emission from “Main-sequence Radio Pulse Emitters”: A New Stellar Diagnostic to Probe 3D Magnetospheric Structures by Barnali Das, Poonam Chandra, Véronique Petit

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Integrated systems biology and structural approaches to discover novel biomarkers and small molecule inhibitors using the gene expression data from drug-resistant breast cancer cell lines by Suad A. Alghamdi, Mohammed Alissa, Muhammad Suleman

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Mock Observations: Morphological Analysis of Galaxies in TNG100 Simulations by Jun-Yu Gong, Weipeng Lin, Lin Tang, Yanyao Lan

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Anatomy, histology, and electron microscopy of the cardiac conduction system. Current views and new data: review by L. B. Mitrofanova

“…The review provides a current view of the anatomy, histology, immunohistochemistry, electron microscopy, and electron immunocytochemistry of the cardiac conduction system (CCS) based on literature data and the author's own research over more than 30 years. …”
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High earnings through firm influence: the role of hierarchical structures in public procurement by Niclas Frederic Sturm, Cristian Candia, Bruno Damásio, Flávio L. Pinheiro

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Effects and mechanisms of digital economy development on corporate carbon emission intensity: empirical evidence from cross-country data by Da Yang, Zhao Yang, Haoze Wu

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Graph compression algorithm based on a two-level index structure by Gaochao LI, Ben LI, Yuhai LU, Mengya LIU, Yanbing LIU

“…The demand for the analysis and application of graph data in various fields is increasing day by day.The management of large-scale graph data with complicated structure and high degree of coupling faces two challenges:one is querying speed too slow,the other is space consumption too large.Facing the problems of long query time and large space occupation in graph data management,a two-level index compression algorithm named GComIdx for graph data was proposed.GComIdx algorithm used the ordered Key-Value structure to store the associated nodes and edges as closely as possible,and constructed two-level index and hash node index for efficient attribute query and neighbor query.Furthermore,GComIdx algorithm used a graph data compressed technology to compress the graph data before it directly stored in hard disk,which could effectively reduce the storing space consumption.The experimental results show that GComIdx algorithm can effectively reduce the initialization time of the graph data calculation and the disk space occupancy of the graph data storing,meanwhile,the query time is less than common graph databases and other Key-Value storage solutions.…”
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Modeling Techniques and Boundary Conditions in Abdominal Aortic Aneurysm Analysis: Latest Developments in Simulation and Integration of Machine Learning and Data-Driven Approaches by Burcu Ramazanli, Oyku Yagmur, Efe Cesur Sarioglu, Huseyin Enes Salman

“…Computational fluid dynamics (CFDs), finite element analysis (FEA), and fluid-structure interaction (FSI) are widely used to simulate AAA hemodynamics and biomechanics. …”
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A Review Investigation of Damage Identification in Structures via Internet of Things by Abolfazl Yosefi, Hamidreza Nasseri

“…The Internet of Things (IoT) offers a method for collecting and analyzing data on structures. This innovative approach holds the promise of identifying and preventing structural impairment by the IoT, thereby enhancing the safety and excellence of concrete and steel constructions. …”
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A Few Remarks on the Stochastic Structure of the Unemployment Rate in Poland by Gender by Stanisław Jaworski

“…It appeared that for Polish unemployment data that structure was not as it could have been expected. …”
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Mapping topographic structure in white matter pathways with level set trees. by Brian P Kent, Alessandro Rinaldo, Fang-Cheng Yeh, Timothy Verstynen

“…We show that level set trees can also be generalized to model pseudo-density functions in order to analyze a broader array of data types, including entire fiber streamlines. Finally, resampling methods show the reliability of the level set tree as a descriptive measure of topographic structure, illustrating its potential as a statistical descriptor in brain imaging analysis. …”
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An Ultrafast Optical Imaging System with Anamorphic Transformation Based on STEAM Structure by Guoqing Wang, Yuan Zhou, Rui Min, Fang Zhao, E Du, Xingquan Li, Cong Qiu, Dongrui Xiao, Chao Wang

“…In this paper, we propose an ultrafast optical imaging system with anamorphic transformation (AT) based on the STEAM structure, which has the benefit of data compression and changing group delay-related resolution. …”
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Dynamic graph structure and spatio-temporal representations in wind power forecasting by Zang Peng, Dong Wenqi, Wang Jing, Fu Jianglong

“…However, due to the stochastic and unstable nature of wind, it poses a real challenge to effectively analyze the correlations among multiple time series data for accurate prediction. In our study, an end-to-end framework called Dynamic Graph structure and Spatio-Temporal representation learning (DSTG) framework is proposed to achieve stable power forecasting by constructing graph data to capture the critical features in the data. …”
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