ClaritySpectra: Raman spectra analysis tool by Aaron Celestian (9395696)

“…</li><li>Pre-compiled database from RRUFF and SLOPP that includes Hey Index of classification, chemistry, locality, paragenesis, mineral evolution stage, etc.</li></ul><h3>PEAK FITTING </h3><ul><li>Automated background subtraction using asymmetric least squares fitting</li><li>A new suggested background feature that lets you preview the background that you like best</li><li>Interactive background fitting lets you further tune the background to perfection</li><li>Four choice of peaks: Gaussian, Lorentzian, Pseudo-Voigt, and the new Asymmetric Voigt functions</li><li>Overlapping view of how well the peaks fit with quality metrics</li><li>No need to define regions, the algorithm is smart enough to what a peak looks like.…”

Python code, input data, and outputs of Fourier analysis and Dynamic Time Warping from McGlasson et al. by Riley McGlasson (13876874)

“…</p> <h4><strong>Python Function Files:</strong></h4> <p>radarfuncs.py: Holds three functions used for FFT and DTW analysis.…”

Drug Release Nanoparticle System Design: Data Set Compilation and Machine Learning Modeling by Shan He (121220)

Subjects:

CMA-ES performance during the iterations of the normalization method according to the objective function with <i>t</i> = 0. by Sofya Feldman (19590649)

Table_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Presentation_2_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Table_2_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Image_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Presentation_3_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Presentation_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Table_3_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses by Dominykas Lukauskis (14143149)

“…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …”

Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses by Dominykas Lukauskis (14143149)

“…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …”

Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses by Dominykas Lukauskis (14143149)

“…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …”

DataSheet1_Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images.PDF by Niccolò Marini (11247936)

“…<p>Algorithms proposed in computational pathology can allow to automatically analyze digitized tissue samples of histopathological images to help diagnosing diseases. …”

Generalized Internal Coordinates for Creative Exploration of Interatomic Geometries by Aleksandr V. Marenich (1283298)

“…Our algorithm allows the user to create compound internal coordinates that are functions of other coordinates, as well as special-purpose coordinates for specific classes of problems. …”

Generalized Internal Coordinates for Creative Exploration of Interatomic Geometries by Aleksandr V. Marenich (1283298)

“…Our algorithm allows the user to create compound internal coordinates that are functions of other coordinates, as well as special-purpose coordinates for specific classes of problems. …”

Generalized Internal Coordinates for Creative Exploration of Interatomic Geometries by Aleksandr V. Marenich (1283298)

“…Our algorithm allows the user to create compound internal coordinates that are functions of other coordinates, as well as special-purpose coordinates for specific classes of problems. …”

Generalized Internal Coordinates for Creative Exploration of Interatomic Geometries by Aleksandr V. Marenich (1283298)

“…Our algorithm allows the user to create compound internal coordinates that are functions of other coordinates, as well as special-purpose coordinates for specific classes of problems. …”

BOFdat Step 3: Identifying species-specific metabolic end goals. by Jean-Christophe Lachance (6619307)