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:

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)

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. …”

Working time of different processes (<i>h</i>). by Dawei Wang (471687)

Subjects:

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)

The recurrent T3D algorithm. by Neythen J. Treloar (8698251)

Environmental setup. by Parthiban Aravamudhan (15338781)

“…To create a structured valid dataset, a stacked model is made by implementing the two most popular dimensionality reduction techniques Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) algorithms. The brainwaves made us to hybridize Fast R-CNN and Gradient Boost Regression (GBR) which reduces the loss function, processing time and boosts the model’s performance. …”

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. …”

Schematic diagram depicting the <i>in-vitro</i> co-culture model setup. by Elias Vera-Siguenza (16993830)

Diagram of the proposed solution algorithm. by Vytautas Abromavičius (22008573)

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

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

Data_Sheet_1_SDA: a data-driven algorithm that detects functional states applied to the EEG of Guhyasamaja meditation.docx by Ekaterina Mikhaylets (17865407)

“…<p>The study presents a novel approach designed to detect time-continuous states in time-series data, called the State-Detecting Algorithm (SDA). The SDA operates on unlabeled data and detects optimal change-points among intrinsic functional states in time-series data based on an ensemble of Ward's hierarchical clustering with time-connectivity constraint. …”

Effect of the transmission probability function on epidemic spread. by Soler Gabriela Bayolo (21011810)

ADT: A Generalized Algorithm and Program for Beyond Born–Oppenheimer Equations of “<i>N</i>” Dimensional Sub-Hilbert Space by Koushik Naskar (7510592)

“…For the numerical case, user can directly provide <i>ab initio</i> data (adiabatic PESs and NACTs) as input files to this software or can generate those input files through in-built python codes interfacing MOLPRO followed by ADT calculation. …”