Dataset for "Self-Supporting Shell Lattices: Explicit Design Method and Neural Accelerated Evolutionary Optimization" (Virtual and Physical Prototyping) by Haoran Hu (22579169)

Distributions of the goodness-of-fit (GoF) values for all tested approaches and parameter spaces. by Kevin J. Wischnewski (21354521)

In vitro and in vivo DMS structure probing of ModT isoforms. by Tina Lenče (20428084)

Accuracy of the Generalized WTA. by Ori Hendler (21262937)

A structure determination protocol based on combined analysis of 3D-ED data, powder XRD data, solid-state NMR data and DFT-D calculations reveals the structure of a new polymorph o... by Christopher Smalley (19655662)

Role of stimulus parameters. by Jiamu Jiang (19959616)

Exploration and Design of Carbon Dot-Based Long Afterglow Materials Using Active Machine Learning and Quantum Chemical Simulations by Hongwei Yang (1367979)

“…Long afterglow materials based on carbon dots (CDs) have attracted extensive attention in the field of optics due to their low cost and nontoxic properties. However, the targeted synthesis of specific properties of complex and unknown structures such as CDs remains a daunting challenge. …”

Model-based sex classification accuracies. by Kevin J. Wischnewski (21354521)

A.) Pictorial representation of light-harvesting structures evolved for different values of the cost <i>χ.</i> by Callum Gray (2691769)

Combination of X‑ray Absorption Spectroscopy and Atomistic Simulations Reveals Features of Correlated Disorder in Quartz-like Germanium Oxide by Harshini Venkata Annadata (21622696)

“…In this paper, we establish correlated disorder in quartz-like germanium oxide (q-GeO₂) by examining the extended local structure around Ge under ambient conditions as well as in low-temperature conditions. By integrating experimental X-ray absorption spectroscopy with reverse Monte Carlo/evolutionary algorithm and ab initio molecular dynamics simulations, we could pinpoint correlated disorder, which is different from the disorder due to thermal motion. …”

TNP-TMA BC biomarker panels. by Robert T. Heussner (21989911)

“…Existing computational methods overlook both cell population heterogeneity across modalities and spatial information, which are critical for effectively completing this task. …”

Executable Power: Syntax as Infrastructure in Predictive Societies by Agustin V. Startari (21179732)

Correlation analysis between CD70 copy number alteration and immune cell infiltration. by Kang Liu (423471)

The recognition performance of subject 5. by Yue Yuan (113839)

“…Then, four features representing hand motion intentions are extracted from the VMFs to form the initial feature space. Next, the ReliefF algorithm is used to remove redundant features from the feature space. …”

The recognition performance of subject 1. by Yue Yuan (113839)

“…Then, four features representing hand motion intentions are extracted from the VMFs to form the initial feature space. Next, the ReliefF algorithm is used to remove redundant features from the feature space. …”

Basic hand movements. by Yue Yuan (113839)

“…Then, four features representing hand motion intentions are extracted from the VMFs to form the initial feature space. Next, the ReliefF algorithm is used to remove redundant features from the feature space. …”

S1 File - by Yue Yuan (113839)

“…Then, four features representing hand motion intentions are extracted from the VMFs to form the initial feature space. Next, the ReliefF algorithm is used to remove redundant features from the feature space. …”

The recognition performance of subject 3. by Yue Yuan (113839)

“…Then, four features representing hand motion intentions are extracted from the VMFs to form the initial feature space. Next, the ReliefF algorithm is used to remove redundant features from the feature space. …”

The recognition performance of subject 4. by Yue Yuan (113839)

“…Then, four features representing hand motion intentions are extracted from the VMFs to form the initial feature space. Next, the ReliefF algorithm is used to remove redundant features from the feature space. …”

The recognition performance of subject 2. by Yue Yuan (113839)

“…Then, four features representing hand motion intentions are extracted from the VMFs to form the initial feature space. Next, the ReliefF algorithm is used to remove redundant features from the feature space. …”