Functional enrichment and correlation analysis of hub DE-SRGs. by Xihao Shen (20347942)

Subjects:

Adaptive H-REMD simulation algorithm. by Danial Pourjafar-Dehkordi (7165523)

Generating the PSC kernel using a double exponential function. by Alireza Ghadimi (13839874)

Example of the CNF function for off-axis DHM holograms recorded in a non-telecentric configuration. by Raul Castañeda (13932971)

A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density. by Hassan Mehboob (8960273)

“…<p>A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density.…”

Cobalt-Complexed Acetylenic Tetrads, a Molecular Scaffold for Quadruple Ionic Functionalization Reactions by Gagik G. Melikyan (1532986)

“…A methodology was developed for introducing nucleophiles into the α- and α′-positions of the dicobalt hexacarbonyl-complexed acetylenic tetrads. A synthetic algorithm included the entry of a given nucleophile to both termini of the acetylenic tetrad <b>A</b> (α-Nu¹-α′-Nu¹; α-Nu²-α′-Nu²), or a pair of select nucleophiles arranged unsymmetrically in opposing sequences (α-Nu¹-α′-Nu²; α-Nu²-α′-Nu¹). …”

Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection by Samin Aref (4683934)

“…PLOS Complex Syst 2(9): e0000062. https://doi.org/10.1371/journal.pcsy.0000062</p><p dir="ltr">2) They license the new creations under the identical terms.</p><p dir="ltr"><br></p><p dir="ltr">For more information about the data, one may refer to the article below:</p><p dir="ltr">Aref S, Ng B (2025) Troika algorithm: Approximate optimization for accurate clique partitioning and clustering of weighted networks. …”

Cost functions implemented in Neuroptimus. by Máté Mohácsi (20469514)

If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. by Yuanchen Zhao (12905580)

“…<p>We compare the performance of the linear-regression-based Metropolis algorithm to a more expressive version that includes quadratic terms. …”

The cost function Φ(<i>x</i>, <i>w</i>) versus the number of iterations for different Gaussian noise levels: (a) <i>σ</i> = 10⁻² and (b) <i>σ</i> = 10⁻³.... by Limin Ma (556873)

Subjects: “…entropy regularization term…”

Accuracy, in terms of the Jaccard index, as a function of the number of iterations for the first four retinal image registrations (shown in different colours) with INSPIRE. by Johan Öfverstedt (14185817)

MAE versus the number of iterations for different Gaussian noise levels: (a) <i>σ</i> = 10⁻² and (b) <i>σ</i> = 10⁻³. by Limin Ma (556873)

Subjects: “…entropy regularization term…”

Functional and pathway enrichment analysis of LR-DEGs. (A) Top 10 BP terms. (B) Top 10 CC terms. (C) Top 10 MF terms. (D) Top 10 KEGG terms. P < 0.05 was considered statistically s... by Wannan Gao (22103659)

Line chart plotted using the k-value selection algorithm: (A) system 1; (B) system 2; (C) system 3. by Jingnan Yan (20727331)

Subjects:

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)

Subjects: “…entropy regularization term…”

3D profiles of <i>β</i> and λ with respect to the MAE for different Gaussian noise levels: (a) <i>σ</i> = 10⁻² and (b) <i>σ</i> = 10⁻³. by Limin Ma (556873)

Subjects: “…entropy regularization term…”

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)

Subjects: “…entropy regularization term…”

Python-based Monte Carlo Simulation Tool by Yangfan Jiang (9372782)

Mean RMSE and R² for the training and test phases of RBF by different training algorithms for temperature and humidity prediction. by Caixia Yan (6647072)

Mean RMSE and R² for the training and test phases of MLP by different training algorithms for temperature and humidity prediction. by Caixia Yan (6647072)