The figures showed a comparison of the balanced and imbalanced sequences and performance of classifiers. by Solomon Shiferaw Beyene (9143178)

gmxapi usage examples. by M. Eric Irrgang (4487278)

S1 Graphical abstract - by José M. Rivera-Arbeláez (12418512)

“…<div><p>Engineered heart tissues (EHTs) have shown great potential in recapitulating tissue organization, functions, and cell-cell interactions of the human heart <i>in vitro</i>. …”

Brain-in-the-Loop Learning for Intelligent Vehicle Decision-Making by Xiaofei Zhang (16483224)

“…To achieve policy learning within limited BiTL training periods, we add two modification features to the proposed algorithm based on TD3. The experiment involving twenty participants has been conducted, and the results show that in continuously high-risk driving scenarios, compared to traditional reinforcement learning algorithms without human participation, the proposed algorithm can maintain a cautious driving policy and avoid potential collisions, validated with both proximal surrogate indicators and success rates. …”

Table1_Natural and artificial selection of multiple alleles revealed through genomic analyses.xlsx by Jana Biová (11287971)

“…Historical natural selection and breeding-related artificial selection both act to change the frequencies of different alleles of genes that control phenotypes. …”

Table8_Natural and artificial selection of multiple alleles revealed through genomic analyses.xlsx by Jana Biová (11287971)

“…Historical natural selection and breeding-related artificial selection both act to change the frequencies of different alleles of genes that control phenotypes. …”

Table4_Natural and artificial selection of multiple alleles revealed through genomic analyses.xlsx by Jana Biová (11287971)

“…Historical natural selection and breeding-related artificial selection both act to change the frequencies of different alleles of genes that control phenotypes. …”

Table3_Natural and artificial selection of multiple alleles revealed through genomic analyses.xlsx by Jana Biová (11287971)

“…Historical natural selection and breeding-related artificial selection both act to change the frequencies of different alleles of genes that control phenotypes. …”

Table2_Natural and artificial selection of multiple alleles revealed through genomic analyses.xlsx by Jana Biová (11287971)

“…Historical natural selection and breeding-related artificial selection both act to change the frequencies of different alleles of genes that control phenotypes. …”

Table7_Natural and artificial selection of multiple alleles revealed through genomic analyses.docx by Jana Biová (11287971)

“…Historical natural selection and breeding-related artificial selection both act to change the frequencies of different alleles of genes that control phenotypes. …”

Table5_Natural and artificial selection of multiple alleles revealed through genomic analyses.xlsx by Jana Biová (11287971)

“…Historical natural selection and breeding-related artificial selection both act to change the frequencies of different alleles of genes that control phenotypes. …”

DataSheet1_Natural and artificial selection of multiple alleles revealed through genomic analyses.docx by Jana Biová (11287971)

“…Historical natural selection and breeding-related artificial selection both act to change the frequencies of different alleles of genes that control phenotypes. …”

Table6_Natural and artificial selection of multiple alleles revealed through genomic analyses.xlsx by Jana Biová (11287971)

“…Historical natural selection and breeding-related artificial selection both act to change the frequencies of different alleles of genes that control phenotypes. …”

Table1_Natural and artificial selection of multiple alleles revealed through genomic analyses.DOCX by Jana Biová (11287971)

“…Historical natural selection and breeding-related artificial selection both act to change the frequencies of different alleles of genes that control phenotypes. …”

Spatiotemporal Soil Erosion Dataset for the Yarlung Tsangpo River Basin (1990–2100) by peng xin (21382394)

“…Additionally, a Genetic Algorithm (GA) was applied in each iteration to optimize the hyperparameters of the XGBoost model, which is crucial for enhancing both the efficiency and robustness of the model (Zhong and Liu, 2024; Zou et al., 2024). …”

Decoding fairness motivations - repository by Sebastian Speer (6489207)

“…All analysis were conducted in Python 2.7.</div><div><br></div><div><b>Behavioral Data:</b><br></div><div><br></div><div><u>Files:</u> </div><div><br></div><div><i>DifffereceOffers.csv </i>- Offers made by participants in Study 1</div><div><i>Diffs_W.csv</i> - Offers made by participants in Study 2</div><div><br></div><div><i>Individual-differences-in-offers2.png</i> - Plot of individual differences as illustrated in the paper</div><div><i>Individual-differences-MeanOffers.png </i>- Individual differences in mean offers in both games as illustrated in the Appendix</div><div><i>SocialvsNonSocial2.png </i>- Difference in Offers between Selfish and strategic players when playing against humans and computers</div><div><br></div><div>Behavioral Data, specfically Ultimatum Game and Dictator Game Offers and Plots resulting from behavioral analysis reported in the following paper:</div><div><br></div><div>S.P.H. …”

Skeletal_ Muscle_MRI_Registration by Lucia Fontana (9435020)

“…</p> <p>wxPython library was employed to develop the GUI, which is composed by two main windows – initial window and registration window – and 5 secondary frames for support functionalities. 3D images are presented with three views – axial, coronal and sagittal – with three sliders to adjust maximum value, minimum value, and gamma correction.…”