<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.…”

a) FO Function, b) FI function. by Huang Jiexian (17060975)

“…The SRL32 primitive (Reconfigurable Look up Tables—RLUTs) and DPR (Dynamic Partial Reconfiguration) are employed to reconfigure single round MISTY1 / KASUMI algorithms on the run-time. The RLUT based architecture attains dynamic logic functionality without extra hardware resources by internally modifying the LUT contents. …”

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. …”

<b>Algorithm Pseudocode</b> by Yibin Zhao (22425801)

HIL test results of low-adhesion road: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sideslip angle; (f) Yaw rate. by Honglei Pang (22693724)

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Braking performance and lateral stability on low-adhesion road surfaces: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle s... by Honglei Pang (22693724)

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Skin transfer function ankle render diagram. by Yuliang Yuan (4478698)

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Bone transfer function pelvis render diagram. by Yuliang Yuan (4478698)

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MOEA/D-ND algorithm flowchart. by Jun Sun (48981)

“…At the same time, in the actual working bandwidth, the optimized power amplifier saturation efficiency reaches 51.5%~61.9%, and the efficiency at 6dB power backoff is about 44.4%~56.5%. Overall, the algorithm proposed in the study is effective in optimizing power amplifiers and their matching networks, effectively solving the problem of insufficient efficiency in low power modes in traditional designs.…”

Reward function related parameters. by Honglei Pang (22693724)

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

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

Functional annotations of peaks. by Azusa Tanaka (540528)

Loss function curve graphs. by Huiying Zhang (200681)

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

a) DPR based Single Round MISTY1 / KASUMI, b) FI function. by Huang Jiexian (17060975)

Evaluation metrics graphs for different loss functions. by Huiying Zhang (200681)

A-B. The boxplots present the distribution of scores for IRF4 and ELANE immune-related functions in low-expression and high-expression groups. by Min-xiao Wang (20868922)

Weighting Function Fitting Process Diagram. by Jiahui Gan (22793753)

Differential analysis between the high- and low-risk score groups and functional analyses of DEGs. by Jian Wen (286688)

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