The algorithm for achieving the research objectives illustrating the process of developing a mathematical model of the braking moment as a function of tire deformation. by Bartosz Wieczorek (8098352)

Algorithm detection steps. by José M. Rivera-Arbeláez (12418512)

Horizontal central profiles produced for the 128-th row of the restored images with different Gaussian noise levels: (a) <i>σ</i> = 10⁻² and (b) <i>σ</i> = 10<sup>−3</su... by Limin Ma (556873)

Vertical central profiles produced for the 128-th column of the restored images with different Gaussian noise levels: (a) <i>σ</i> = 10⁻² and (b) <i>σ</i> = 10<sup>−3</s... by Limin Ma (556873)

Imperialist competition algorithm with quasi-opposition-based learning for function optimization and engineering design problems by Dongge Lei (6836915)

Table 1_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.xlsx by Peng Zhu (277243)

“…Functional enrichment analyses revealed that high FLAD1 expression is involved in crucial biological processes like copper ion detoxification and heme complex assembly. …”

Image 1_Integrative single-cell and spatial transcriptomics analysis reveals FLAD1 as a regulator of the immune microenvironment in hepatocellular carcinoma.tif by Peng Zhu (277243)

“…Functional enrichment analyses revealed that high FLAD1 expression is involved in crucial biological processes like copper ion detoxification and heme complex assembly. …”

The statistics of number of proteins and phosphorylation S/T/Y sites for different organisms. by Chao Wang (146527)

Subjects:

Convergence plots for solving IM for p2p-Gnutella06_uni_1-1000_uni_0.75-1 via (1 + 1)-WEA. by Alexander Andreev (16822333)

Subjects:

Table 6_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”

Table 7_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”

Table 3_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”

Table 2_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”

Table 4_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”

Table 5_Predictive prioritization of genes significantly associated with biotic and abiotic stresses in maize using machine learning algorithms.xlsx by Anjan Kumar Pradhan (9386369)

“…However, only one gene Zm00001eb038720 encoding RNA-binding protein AU-1/Ribonuclease E/G, predicted by the PLSDA algorithm, was found commonly expressed under both biotic and abiotic stress. …”

Illustration of the unrestricted model and its training algorithm. by Yuru Song (21300760)

Fixing λ_<i>L</i> = 1 and adjusting the size of λ_<i>G</i>, with the gradual increase of λ_<i>G</i>, the time resolution of the high-frequency part of... by Li Jiashen (20552690)

Numerical <i>RMSE</i> results for parameters estimation of MSX–60 module. by Ziad M. Ali (12516532)

WGCNA and machine learning algorithms. by Shushu Wang (6870191)

Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. by Gursimran Singh (575288)

Subjects: