6x6 LUT-based multiplication. حسب Ayesha Waris (21368446)

"…<div><p>CRYSTALS-Kyber has been standardized by the National Institute of Standards and Technology (NIST) as a quantum-resistant algorithm in the post-quantum cryptography (PQC) competition. …"

Immunoassay of key anoikis-related genes. حسب Yufeng He (5673119)

Machine Learning Models for Efficient Property Prediction of ABX₃ Materials: A High-Throughput Approach حسب Soundous Touati (20282599)

"…Finally, these prediction models are employed to identify the possible space groups for each of the 1252 new ABX₃ formulas. Then, we predict the volume, the formation energy, and the band gap energy for each candidate space group. …"

Machine Learning Models for Efficient Property Prediction of ABX₃ Materials: A High-Throughput Approach حسب Soundous Touati (20282599)

"…Finally, these prediction models are employed to identify the possible space groups for each of the 1252 new ABX₃ formulas. Then, we predict the volume, the formation energy, and the band gap energy for each candidate space group. …"

Machine Learning Models for Efficient Property Prediction of ABX₃ Materials: A High-Throughput Approach حسب Soundous Touati (20282599)

"…Finally, these prediction models are employed to identify the possible space groups for each of the 1252 new ABX₃ formulas. Then, we predict the volume, the formation energy, and the band gap energy for each candidate space group. …"

Expression analysis of lncRNAs between the MCAO and sham groups. حسب Meimei Xu (744867)

Machine Learning Study of Methane Activation by Gas-Phase Species حسب Ying Xu (9172)

"…In this study, by assembling a data set encompassing a total of 134 gas-phase metal species documented in the literature for methane activation via the mechanism of oxidative addition, machine learning (ML) models based on the backpropagation artificial neural network algorithm have been established with a range of intrinsic electronic properties of these species as features and the experimental rate constants of the reactions with methane as the target variables. …"

Machine Learning Study of Methane Activation by Gas-Phase Species حسب Ying Xu (9172)

"…In this study, by assembling a data set encompassing a total of 134 gas-phase metal species documented in the literature for methane activation via the mechanism of oxidative addition, machine learning (ML) models based on the backpropagation artificial neural network algorithm have been established with a range of intrinsic electronic properties of these species as features and the experimental rate constants of the reactions with methane as the target variables. …"

Sequence patterns of Ig-domain variants in WebLogo format. حسب Caesar Tawfeeq (21087272)

Schematic representation of Ig-domains dimerization patterns and contact network A) VH:VL schematic parallel interface and conserved interactions B) CH1:CL schematic antiparallel i... حسب Caesar Tawfeeq (21087272)

Preprocessed Spatial Dynamic Wind Power Forecasting (SDWPF) Dataset from Baidu KDD Cup 2022 Challenge حسب Yuan Shi (22779782)

Breakdown of respondents. حسب Qunita Brown (19751520)

"…High quality data from Africa will afford diversity to global data sets, reducing bias in algorithms built for artificial intelligence technologies in healthcare. …"

Integrating drought warning water level with analytical hedging for reservoir water supply operation حسب Wenhua Wan (8051543)

"…</p><p dir="ltr">2. R codes for the HR-based DP algorithm, the processes deriving seasonal DWWL, and the statistical performance of HR with DWWL during typical drought years.…"

Linear mixed-effect model results. حسب Shirong Chen (22127046)

"…Additionally, we found three distinct preparatory reading patterns: <i><i>Fast Surface-level Preparatory Reading, Systematic Deep-level Preparatory Reading,</i></i> and <i><i>Extended Iterative Preparatory Reading,</i></i> each reflecting a distinct combination of cognitive investment and reading speed. …"

Visualizations of three clusters. حسب Shirong Chen (22127046)

"…Additionally, we found three distinct preparatory reading patterns: <i><i>Fast Surface-level Preparatory Reading, Systematic Deep-level Preparatory Reading,</i></i> and <i><i>Extended Iterative Preparatory Reading,</i></i> each reflecting a distinct combination of cognitive investment and reading speed. …"

Summary of three preparatory reading clusters. حسب Shirong Chen (22127046)

"…Additionally, we found three distinct preparatory reading patterns: <i><i>Fast Surface-level Preparatory Reading, Systematic Deep-level Preparatory Reading,</i></i> and <i><i>Extended Iterative Preparatory Reading,</i></i> each reflecting a distinct combination of cognitive investment and reading speed. …"

S1 File - حسب Xiaojie Feng (6873953)

Forward genetic screen identifies 28 dark yolk mutants. حسب McKenna Feltes (11242085)

EvoFuzzy حسب Hasini Nakulugamuwa-Gamage (17344420)

"…The algorithm evolves a population of networks using fuzzy trigonometric differential evolution, with gene expression predictions based on confidence levels applied through a fuzzy logic-based predictor.…"

TreeMap 2016: A tree-level model of the forests of the conterminous United States circa 2016 حسب Karin L. Riley (19657882)

"…The raster map of plot identifiers can be linked to the FIA databases available through the FIA DataMart (https://doi.org/10.2737/RDS-2001-FIADB) or to the text and SQL files included in this data publication to produce tree-level maps or to map other plot attributes. The accompanying database files included in this publication also contain attributes regarding the FIA plot CN (or control number, a unique identifier for each time a plot is measured), the subplot number, the tree record number, and for each tree: the status (live or dead), species, diameter, height, actual height (where broken), crown ratio, number of trees per acre, and a code for cause of death where applicable. …"