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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Machine-learning models for Alzheimer’s disease diagnosis using neuroimaging data: survey, reproducibility, and generalizability evaluation by Maryam Akhavan Aghdam, Serdar Bozdag, Fahad Saeed, Alzheimer’s Disease Neuroimaging Initiative

“…To better understand the landscape, we surveyed the major preprocessing, data management, traditional machine-learning (ML), and deep learning (DL) techniques used for diagnosing AD using neuroimaging data such as structural magnetic resonance imaging (sMRI), functional magnetic resonance imaging (fMRI), and positron emission tomography (PET). …”
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The changes of left cardiac structure and function in the patients with non-dialysis chronic kidney disease and influencing factors by CHEN Cai-ming, CHEN Yuan, CHEN Yi, ZHANG Xiao-hong, WAN Jian-xin

“…Objective To analyze the changes of left ventricular structure and function in the patients with non-dialysis chronic kidney disease(ND-CKD)and the influencing factors.Methods The ND-CKD patients were enrolled from Jan.2013 to July 2014 in our hospital.All patients were subjected to echocardiography and the indexes were collected.Also the clinical data were collected.The indexes of left ventricular structure and function among different CKD groups were analyzed,and the correlation between the changes of cardiac structure and function were clinical data were also analyzed.Results 337 ND-CKD patients were enrolled,including 71 patients with CKD1 stage,37 patientswith CKD2 stage,28 patients with CKD3 stage,36 patients with CKD stage 4 and 165 patients with CKD stage 5.In pace with the progression of CKD,the data revealed that body mass index(BMI)and serum calcium were gradually declined(P<0.05),while blood urea nitrogen(BUN),serum creatinine(SCr),serum phosphorus,intact parathyroid hormone(iPTH)and Cystatin C gradually ascended(P<0.05).New bone metabolic markers revealed that in pace with the progression of CKD,25-(OH)-VitD gradually declined(P<0.05),but N-Osteocalcin(NOC),β-C-terminal telopeptide of typeⅠcollagen(β-CTX)and N-terminal peptide of typeⅠprocollagen(P1 NP)gradually ascended(P<0.05).Echocardiographic indexes revealed that in pace with the progression of CKD,left ventricular end diastolic dimension(LVDd),left ventricular end systolic dimension(LVDs),and left ventricular mass index(LVMI)gradually ascended(P<0.05)in cardiac structure,and SV gradually ascended(P<0.05)in cardiac function,while relative wall thickness(RWT),cardiac output(CO),left ventricular ejection fraction(LV-EF),fractional shortening(FS),and transmitral diastolic early peak inflow velocity/transmitral diastolic late peak inflow velocity(E/A)had no statistically significant difference,but E/A gradually declined and was less than1 after CKD2.Left ventricular geometric remodeling revealed that the normal LV geometry group gradually declined from CKD1 to CKD5,with84.5%,70.3%,64.3%,44.4%and38.2%respectively.The abnormal LV geometry groups gradually ascended from CKD1 to CKD5,and there were 32.1% with eccentric hypertrophy,15.2% with concentric hypertrophy,and 14.5% with concentric remodeling.Multiple linear regression revealed that the risk factors of RWT were age and serum phosphorus,the risk factor of LVDd was BMI,the risk factor of LVMI wasβ-CTX,the risk factor of SV was Cystatin C,and the protective factors of E/A were age,gender(female),Ca and BUN.Conclusions The left ventricular structure and function in the patients with ND-CKD were aggravated in pace with the progression of CKD.Age,renal function,serum phosphorus,serum calcium,iPTH,BMI andβ-CTX were related to the changes of left ventricular structure and function.…”
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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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Dynamic coupling of economic and energy structures in resource-based regions: a case study of Shanxi Province, China by Ende Hu, Zeyuan Shen, Xianghua Wang

“…Drawing on data from Shanxi Province spanning 2010 to 2022, this study constructs comprehensive indicator systems for both economic and energy structures. …”
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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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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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Civil structural health monitoring and machine learning: a comprehensive review by Asraar Anjum, Meftah Hrairi, Abdul Aabid, Norfazrina Yatim, Maisarah Ali

“…More robust prediction models may be produced by combining test data collected in the laboratory or field with ML. …”
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Civil Structural Health Monitoring and Machine Learning: A Comprehensive Review by Asraar Anjum, Meftah Hrairi, Abdul Aabid, Norfazrina Yatim, Maisarah Ali

“…More robust prediction models may be produced by combining test data collected in the laboratory or field with ML. …”
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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 structural biology compatible file format for atomic force microscopy by Yining Jiang, Zhaokun Wang, Simon Scheuring

“…Abstract Cryogenic electron microscopy (cryo-EM), X-ray crystallography, and nuclear magnetic resonance (NMR) contribute structural data that are interchangeable, cross-verifiable, and visualizable on common platforms, making them powerful tools for our understanding of protein structures. …”
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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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KARAŞAR, AN ALEVI-BEKTASHI SETTLEMENT IN BEYPAZARI (ADMINISTRATIVE, ECONOMIC AND SOCIAL STRUCTURE) by İsmail Yaşayanlar

“…This study evaluates the economic and social structure of Karaşar, an Alevi-Bektashi settlement, on the basis of data from tahrir, population and temettuat books in the Ottoman Archives. …”
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Bayesian variable selection with graphical structure learning: Applications in integrative genomics. by Suprateek Kundu, Yichen Cheng, Minsuk Shin, Ganiraju Manyam, Bani K Mallick, Veerabhadran Baladandayuthapani

“…This has motivated systematic data-driven approaches to integrate multi-dimensional structured datasets, since cancer development and progression is driven by numerous co-ordinated molecular alterations and the interactions between them. …”
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Advancing Structural Health Monitoring with Deep Belief Network-Based Classification by Álvaro Presno Vélez, Zulima Fernández Muñiz, Juan Luis Fernández Martínez

“…In recent years, deep learning techniques have emerged as powerful tools for analyzing the complex data generated by SHM systems. This study investigates the use of deep belief networks (DBNs) for classifying structural conditions before and after retrofitting, using both ambient and train-induced acceleration data. …”
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