Similarity between the allegiance matrices of the multiplex SC-FC graph, the FC graph alone, and the SC graph alone, as a function of the topological scale for the group. by Arian Ashourvan (6685232)

Effects of Nash equilibrium speed changes with the non-sensory motor algorithm on encounters, agent numbers, and payoffs. by Hiroyuki Ichijo (13891153)

PREDICTING THE PERFORMANCE PARAMETERS OF CHISEL PLOW USING NEURAL NETWORK MODEL by Samy Marey (10383883)

“…<div><p>ABSTRACT This study examines the capability of an artificial neural network (ANN) approach using a backpropagation-learning algorithm to predict performance parameters for a chisel plow at three field sites with differing soils. …”

GSEA Analysis of Differentially Expressed Genes in High and Low-Risk Groups. by Jie Chu (293795)

GO/KEGG Enrichment Analysis of Differentially Expressed Genes in High and Low-Risk Groups. by Jie Chu (293795)

RMSE results. by YueSheng Jiang (19267984)

“…Among all kinds of space-time fusion methods, Fit-FC space-time fusion method based on weight Function is widely used. …”

Results of the Kherson Area Visual Assessment. by YueSheng Jiang (19267984)

“…Among all kinds of space-time fusion methods, Fit-FC space-time fusion method based on weight Function is widely used. …”

Work flow chart. by YueSheng Jiang (19267984)

“…Among all kinds of space-time fusion methods, Fit-FC space-time fusion method based on weight Function is widely used. …”

Experimental data. by YueSheng Jiang (19267984)

“…Among all kinds of space-time fusion methods, Fit-FC space-time fusion method based on weight Function is widely used. …”

Results of the PY area visual assessment. by YueSheng Jiang (19267984)

“…Among all kinds of space-time fusion methods, Fit-FC space-time fusion method based on weight Function is widely used. …”

Comparison of the improved LRM and RM results. by YueSheng Jiang (19267984)

Result charts for different window sizes. by YueSheng Jiang (19267984)

Image_2_Identification and verification of diagnostic biomarkers in recurrent pregnancy loss via machine learning algorithm and WGCNA.tif by Changqiang Wei (11454415)

“…Three hub genes, WBP11, ACTR2, and NCSTN, were identified using machine learning algorithms. ROC curves demonstrated a strong diagnostic value when the three hub genes were combined. …”

Image_1_Identification and verification of diagnostic biomarkers in recurrent pregnancy loss via machine learning algorithm and WGCNA.tif by Changqiang Wei (11454415)

“…Three hub genes, WBP11, ACTR2, and NCSTN, were identified using machine learning algorithms. ROC curves demonstrated a strong diagnostic value when the three hub genes were combined. …”

Image_3_Identification and verification of diagnostic biomarkers in recurrent pregnancy loss via machine learning algorithm and WGCNA.tif by Changqiang Wei (11454415)

“…Three hub genes, WBP11, ACTR2, and NCSTN, were identified using machine learning algorithms. ROC curves demonstrated a strong diagnostic value when the three hub genes were combined. …”

Application to Neuropixels dataset. by Rahul Biswas (14117086)

Data of PV, WT, FC, and utilized coefficients. by Obaid Aldosari (19797428)

Characteristics of biological processes involved in DKD. by Hailin Li (453832)

Overview of the spatial location of detected ICs inside the amygdala (left column, A), as well as their corresponding whole-brain FC maps (right column, B) for all ICs with dimensi... by Uriel K. A. Elvira (14307687)

A global view of gene ontology (GO) terms enriched in the set of gene pairs with gain-of-correlation (GOC) in resistant (RES) but not in susceptible (SUS) phenotypes. by Fang Liu (13271)