Function <i>χ</i>_<i>opt</i> superimposed with the phase-field function indicating the channel geometry. by Martina Bukač (20161460)

<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.…”

Left: the algorithm’s best estimate of where to put breakpoints for each number of breakpoints considered. by Zhengtian Li (5076704)

Attack and defense behaviors with the sensory–motor algorithm between multiple predators and prey. by Hiroyuki Ichijo (13891153)

ABIDE dataset subject demographics. by Alexandria M. Jensen (6494957)

Subjects:

Investigate the variation of the cost function in situations where many obstacles and other robots are detected. by Quoc Bao Diep (18452207)

Activation functions: Sigmoid function and ReLU function. by Wan-Hua Zhang (21601139)

Attack and defense behaviors with the sensory–motor algorithm between a single predator and a single prey. by Hiroyuki Ichijo (13891153)

Effects of Nash equilibrium attack and defense behaviors with the sensory–motor algorithm on encounters, agent numbers, and payoffs. by Hiroyuki Ichijo (13891153)

Using synthetic data to test group-searching algorithms in a context where the correct grouping of species is known and uniquely defined. by Yuanchen Zhao (12905580)

Attack and defense behaviors between a single predator and a single prey using the sensory–motor algorithm. by Hiroyuki Ichijo (13891153)

Indel markers generated by WheresWalker for each mutant. by McKenna Feltes (11242085)

Candidate lists generated by WheresWalker for each mutant. by McKenna Feltes (11242085)

Examples of between- and within-community Beta distributions. by Alexandria M. Jensen (6494957)

Subjects:

Background heterogeneity and sequencing depth improve WheresWalker SNPindex. by McKenna Feltes (11242085)

WheresWalker outperforms homozygosity density mapping for Maize mutant. by McKenna Feltes (11242085)

Overview of the wavess algorithm and R package. by Narmada Sambaturu (4989539)

Synthetic Realness: Authenticity as Algorithm (Reality Drift Working Paper Series, 2025) by Reality Drift Working Papers Series 2020-2025 (22445446)

“…<p dir="ltr">This paper explores the concept of synthetic realness: how authenticity is increasingly engineered by algorithms until the line between real and fake becomes functionally irrelevant. …”

WheresWalker pipeline utilizes WGS data to identify segregating SNPs and indels. by McKenna Feltes (11242085)

Bulk Segregant Analysis (BSA) homozygosity mapping mirrors WheresWalker output. by McKenna Feltes (11242085)