Listed python codes of our algorithm with explanations (Python 3.9 recommended). by Takayuki Niizato (162226)

EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit by Gonzalo Colmenarejo (650249)

“…For a RDKit molecule, it provides (i) a PNG binary string with an image of the molecule with color-highlighted functional groups; (ii) a list of sets of atom indices (idx), each set corresponding to a functional group; (iii) a list of pseudo-SMILES canonicalized strings for the full functional groups; and (iv) a list of RDKit labeled mol objects, one for each full functional group. …”

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

“…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …”

<b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

“…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…”

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

FAR-1: A Fast Integer Reduction Algorithm Compared to Collatz and Half-Collatz by Faizan Ali (21689861)

Subjects:

S1 File - by Yuh-Chin T. Huang (17867207)

Subjects:

S1 Dataset - by Yuh-Chin T. Huang (17867207)

Subjects:

Average quality scores of the models of the analysis set as a function of the <i>w</i>_<i>SP</i> with which the DOPE potential has been included in the objective function... by Giacomo Janson (8138517)

Flowchart of one iteration of the CE-Symm algorithm. by Spencer E. Bliven (6672755)

An expectation-maximization algorithm for finding noninvadable stationary states. by Robert Marsland (8616483)

“…<i>(b)</i> Metabolic byproducts move the relevant unperturbed state from <b>R</b>⁰ (gray ‘x’) to (black ‘x’), which is itself a function of the current environmental conditions. …”

Python scripts used to model CPU errors by Poisson distribution density mass function and to draw graph of Poisson events (needs Matplot, SciPy, PysimpleGUI and NumPy) by Santhosh Kumar Rajamani (13023678)

Multi-Objective Cooperative Paths Planning for Multiple Parafoils System Using a Genetic Algorithm by Chen Qi (2803873)

“…Parafoils’ paths are encoded by real matrix, and the cooperative relationship between parafoils is realized by paths fitness function. The random single point crossover and Gaussian mutation are introduced to accelerate algorithm convergence rate. …”

Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. by Yuanchen Zhao (12905580)

“…<p>(A), (B) Algorithm performance, evaluated over 50 simulated datasets generated as described in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1012590#pcbi.1012590.g001" target="_blank">Fig 1</a> with <i>N</i> = 3 true groups, 900 samples and 10% simulated measurement noise. …”

Results of the application of different clustering algorithms to average functional connectivity from healthy subjects. by Francisco Páscoa dos Santos (16510676)

“…<p>A) Resulting cluster inertia from applying the k-means algorithm described in the methods to empirical averaged functional connectivity from healthy subjects, with different numbers of clusters. …”

A Genetic Algorithm Approach for Compact Wave Function Representations in Spin-Adapted Bases by Maru Song (22593561)

“…We benchmark the strategy against one- and two-dimensional nearest-neighbor Heisenberg models, the one-dimensional next-nearest-neighbor Heisenberg model, and <i>selected</i> collinear ground and excited states of the nitrogenase P-cluster, employing intermediate CAS(48,40) active space ab initio Hamiltonians. …”

Benchmark functions. by Yun Qi (560401)

p-values of the Wilconxon rank-sum test at 0.05 significance level for CRLPO against other eight algorithms on 19 benchmark functions from table 1 with 1000 dimensions. by Aijun Zhu (822068)

“…<p>p-values of the Wilconxon rank-sum test at 0.05 significance level for CRLPO against other eight algorithms on 19 benchmark functions from table <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0251204#pone.0251204.t001" target="_blank">1</a> with 1000 dimensions.…”

p-values of the Wilconxon rank-sum test at 0.05 significance level for CRLPO against other eight algorithms on 19 benchmark functions from Table 1 with 30 dimensions. by Aijun Zhu (822068)

“…<p>p-values of the Wilconxon rank-sum test at 0.05 significance level for CRLPO against other eight algorithms on 19 benchmark functions from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0251204#pone.0251204.t001" target="_blank">Table 1</a> with 30 dimensions.…”

p-values of the Wilconxon rank-sum test at 0.05 significance level for CRLPO against other eight algorithms on 19 benchmark functions from Table 1 with 100 dimensions. by Aijun Zhu (822068)

“…<p>p-values of the Wilconxon rank-sum test at 0.05 significance level for CRLPO against other eight algorithms on 19 benchmark functions from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0251204#pone.0251204.t001" target="_blank">Table 1</a> with 100 dimensions.…”