Dice score for various <i>α</i> values (from the Eq 8) for the tracking of the CST and for the iFOD and PTT algorithms. حسب Thomas Durantel (20933812)

Test functions. حسب Kejia Liu (5699651)

"…Its restrictions block GEP from successfully handling high-dimensional along with complex optimization problems. …"

Test of polymethyl methacrylate (C₅O₂H₈) through algorithm: Curves of both objective function and fractional weight in the process of identifying third chemical constituent after H was assumed, i.e., step 2 in Figure 2. حسب Dong Hyeok Choi (12562048)

Risk and density functions for standard relapse from remission condition to disease <i>b</i> condition (similar shapes for standard relapse to disease <i>a</i>). حسب Benoîte de Saporta (20454662)

Comparison curve of objective function (J). حسب Wanjun Zhang (496858)

Table 1_SRC is a potential target of Arctigenin in treating triple-negative breast cancer: based on machine learning algorithms, molecular modeling and in Vitro test.xlsx حسب Yuezhou Huang (9998177)

"…</p>Results<p>Our study identified 183 AG-related targets, 5,193 differentially expressed genes, and 6,173 co-expression module genes associated with TNBC. Machine learning algorithms pinpointed 4 hub genes from 28 intersecting targets. …"

Table 2_SRC is a potential target of Arctigenin in treating triple-negative breast cancer: based on machine learning algorithms, molecular modeling and in Vitro test.xlsx حسب Yuezhou Huang (9998177)

"…</p>Results<p>Our study identified 183 AG-related targets, 5,193 differentially expressed genes, and 6,173 co-expression module genes associated with TNBC. Machine learning algorithms pinpointed 4 hub genes from 28 intersecting targets. …"

Table 3_SRC is a potential target of Arctigenin in treating triple-negative breast cancer: based on machine learning algorithms, molecular modeling and in Vitro test.docx حسب Yuezhou Huang (9998177)

"…</p>Results<p>Our study identified 183 AG-related targets, 5,193 differentially expressed genes, and 6,173 co-expression module genes associated with TNBC. Machine learning algorithms pinpointed 4 hub genes from 28 intersecting targets. …"

MD5 signatures from combined file regions حسب Paul A. Gagniuc (1818325)

<b>Gene Catalog and Associated Functional Data</b> for BioProject PRJNA1311452 حسب Satheeswaran Thangaraj (22187269)

Observed distributions of ARI ×100 from the FRECL partition after consensus clustering; against the number of runs. حسب Susana Conde (5495675)

Strong negative correlation between the precision of algorithms and the evolutionary distance from the training data. حسب Sven B. Gould (12237287)

Python code for a rule-based NLP model for mapping circular economy indicators to SDGs حسب Zahir Barahmand (18008947)

"…The package includes:</p><ul><li>The complete Python codebase implementing the classification algorithm</li><li>A detailed manual outlining model features, requirements, and usage instructions</li><li>Sample input CSV files and corresponding processed output files to demonstrate functionality</li><li>Keyword dictionaries for all 17 SDGs, distinguishing strong and weak matches</li></ul><p dir="ltr">These materials enable full reproducibility of the study, facilitate adaptation for related research, and offer transparency in the methodological framework.…"

Multimodal reference functions. حسب Ruiyu Zhan (21602031)

"…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …"

Quantum Simulation of Molecular Dynamics ProcessesA Benchmark Study Using a Classical Simulator and Present-Day Quantum Hardware حسب Tamila Kuanysheva (21546962)

"…Although Qiskit provides a general method for initializing wave functions, in most cases it generates deep quantum circuits. …"

Construction of the PRG score index using integrated machine learning algorithms. حسب Xiangxin Wu (22320058)

Rosenbrock function losses for . حسب Shikun Chen (14625352)

"…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …"

Rosenbrock function losses for . حسب Shikun Chen (14625352)

"…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …"

Levy function losses for . حسب Shikun Chen (14625352)

"…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …"

Rastrigin function losses for . حسب Shikun Chen (14625352)

"…The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. …"