Big Data and Metadata Framework Environment developed by the Big Data Science Center (BDSC) at Shanghai Synchrotron Radiation Facility (SSRF) by Alessandro Sepe (10304915)

Subjects:

my-home-is-my-secret.zip by Anna Brauer (11266881)

“…</p> <p><br></p> <p>The material contains two folders; each contains an implementation of the algorithm, one in Java and one in Python.<br> </p> <p><br></p> <p>The Python script includes a function (example()) demonstrating how the mechanism class ('STT') may be used. …”

Known compounds and new lessons: structural and electronic basis of flavonoid-based bioactivities by Rohan J. Meshram (6563189)

“…Abbreviations2′HFN-2′</p><p>hydroxy flavonone</p>2D<p>2 dimension</p>3D<p>3 dimension</p>3H7MF<p>3-hydroxy-7-methoxy flavone</p>4′HFN-4′<p>hydroxy flavonone</p>4′MF- 4′<p>methoxy flavone</p>7HFN<p>7-hydroxy flavonone</p>CHARMM<p>Chemistry at Harvard Macromolecular Mechanics</p>COX<p>cyclooxygenase</p>COX-1<p>cyclooxygenase-1</p>COX-2<p>cyclooxygenase-2</p>DM<p>dipole moment</p>DPPH- 2, 2<p>diphenyl-1-picryl hydrazine</p>EA<p>electron affinities</p>EGFR<p>epidermal growth factor receptor</p>E-HOMO<p>Highest occupied molecular orbital energy</p>E-LUMO<p>Lowest unoccupied molecular orbital energy</p>EPA<p>eicosapentaenoic acid</p>FROG2<p>FRee Online druG conformation generation</p>GA<p>Genetic Algorithm</p>GROMACS<p>GROningen MAchine for Chemical Simulations</p>HOMO<p>Highest occupied molecular orbital</p>IP<p>Ionization potential</p>LOMO<p>Lowest unoccupied molecular orbital</p>MD<p>Molecular dynamics</p>MO<p>Molecular orbital</p>NAMD<p>Nanoscale Molecular Dynamics</p>NSAIDs<p>Non-Steroidal Anti Inflammatory Drugs</p>Ns<p>nanoseconds</p>NVE<p>Ensemble-constant-energy, constant-volume, Constant particle ensemble</p>PDB-ID<p>Protein Data Bank Identifier</p>PME<p>Particle Mesh Ewald</p>PyRX<p>Python Prescription</p>RMSD<p>Root-Mean-Square Deviation</p>RMSF<p>Root-Mean-Square Fluctuation</p>RLS<p>reactive lipid species</p>ROS<p>Reactive Oxygen Species</p>SASA<p>solvent accessible surface area</p>SMILES<p>simplified molecular-input line-entry system</p>SOR<p>superoxide anion radical</p>UFF<p>Universal force field</p>VEGF<p>vascular endothelial growth factor</p>VEGFR<p>vascular endothelial growth factor receptor</p>VMD<p>Visual molecular dynamics</p><p></p> <p>hydroxy flavonone</p> <p>2 dimension</p> <p>3 dimension</p> <p>3-hydroxy-7-methoxy flavone</p> <p>hydroxy flavonone</p> <p>methoxy flavone</p> <p>7-hydroxy flavonone</p> <p>Chemistry at Harvard Macromolecular Mechanics</p> <p>cyclooxygenase</p> <p>cyclooxygenase-1</p> <p>cyclooxygenase-2</p> <p>dipole moment</p> <p>diphenyl-1-picryl hydrazine</p> <p>electron affinities</p> <p>epidermal growth factor receptor</p> <p>Highest occupied molecular orbital energy</p> <p>Lowest unoccupied molecular orbital energy</p> <p>eicosapentaenoic acid</p> <p>FRee Online druG conformation generation</p> <p>Genetic Algorithm</p> <p>GROningen MAchine for Chemical Simulations</p> <p>Highest occupied molecular orbital</p> <p>Ionization potential</p> <p>Lowest unoccupied molecular orbital</p> <p>Molecular dynamics</p> <p>Molecular orbital</p> <p>Nanoscale Molecular Dynamics</p> <p>Non-Steroidal Anti Inflammatory Drugs</p> <p>nanoseconds</p> <p>Ensemble-constant-energy, constant-volume, Constant particle ensemble</p> <p>Protein Data Bank Identifier</p> <p>Particle Mesh Ewald</p> <p>Python Prescription</p> <p>Root-Mean-Square Deviation</p> <p>Root-Mean-Square Fluctuation</p> <p>reactive lipid species</p> <p>Reactive Oxygen Species</p> <p>solvent accessible surface area</p> <p>simplified molecular-input line-entry system</p> <p>superoxide anion radical</p> <p>Universal force field</p> <p>vascular endothelial growth factor</p> <p>vascular endothelial growth factor receptor</p> <p>Visual molecular dynamics</p> <p>Communicated by Ramaswamy H. …”

NanoDB: Research Activity Data Management System by Lorenci Gjurgjaj (19702207)

“…Cross-Platform Compatibility: Works on Windows, macOS, and Linux. In a Python environment or as an executable. Ease of Implementation: Using the flexibility of the Python framework all the data setup and algorithm can me modified and new functions can be easily added. …”

PREDICTION OF DEM PARAMETERS OF COATED FERTILIZER PARTICLES BASED ON GA-BP NEURAL NETWORK by Xin Du (208780)

“…The predicted values matched the expected output values, indicating that the GA-BP neural network can accurately predict the nonlinear function output, and the network predicted output can be approximated as the actual output of the function. …”

Code and Data for 'Fabrication and testing of lensed fiber optic probes for distance sensing using common path low coherence interferometry' by Radu Stancu (21165068)

“…Distance Sensing</p><p dir="ltr">Code and data to demonstrate extracting distance sensing data from A-scans and to generate Fig. 8 using the algorithm described in Fig. 7. Functions to generate distance measurements are in 'distance_sensing_utilities.py' and an example of how to use this on data in the 'data' folder is in 'distance_sensing_example.py', which generates Fig 8. …”

A dynamically changing bistable switch enhances robustness and accuracy of transitions in time and space. by Jan Rombouts (5007665)

“…B) Function used to make the shape of the switch dependent on the total amount of protein, by coupling <i>a</i> to <i>X</i>_<i>T</i>. …”

Brain-in-the-Loop Learning for Intelligent Vehicle Decision-Making by Xiaofei Zhang (16483224)

“…In this paper, we utilize functional near-infrared spectroscopy (fNIRS) signals as real-time human risk-perception feedback to establish a brain-in-the-loop (BiTL) trained artificial intelligence algorithm for decision-making. …”

Map Matching on Low Sampling Rate Trajectories Through Deep Inverse Reinforcement Learning and Multi Intention Modeling by Reza Safarzadeh (18072472)

“…</li><li>`mm_sequence`: Contains codes and functions related to map matching sequence which includes functions for processing and matching sequences of GPS points to the underlying road network.…”

MOMA compared to MFA-derived estimates, carbon yield efficiencies and CBA co-factor profile comparison across unconstrained, manually curated and experimentally constrained solutio... by Laura de Arroyo Garcia (9226096)

“…MOMA ranges were estimated using the wild type solution as a reference and sequentially implementing the single-gene knockouts studied by Long et al. (2019) [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1008125#pcbi.1008125.ref046" target="_blank">46</a>], with biomass formation as the objective function. MFA ranges were extracted from a pre-existing dataset (Long et al., 2019), using a Python algorithm to select the minimal and maximal flux ranges.…”

Code by Baoqiang Chen (21099509)

“…We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …”

Core data by Baoqiang Chen (21099509)

“…We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …”

Data_Sheet_1_Exploring changes in depression and radiology-related publications research focus: A bibliometrics and content analysis based on natural language processing.docx by Kangtao Wang (9177766)

“…The unsupervised Leuven algorithm was used to build a network to identify relationships between research focus.…”

Mechanomics Code - JVT by Carlo Vittorio Cannistraci (5854046)

“…The functions were tested respectively in: MATLAB 2018a or youger, Python 3.9.4, R 4.0.3.…”

Table_5_MeiosisOnline: A Manually Curated Database for Tracking and Predicting Genes Associated With Meiosis.XLSX by Xiaohua Jiang (177009)

“…Annotation information was provided for both meiotic genes and predicted candidates, including basic information, function, protein–protein interaction (PPI), and expression data. …”

Image_4_MeiosisOnline: A Manually Curated Database for Tracking and Predicting Genes Associated With Meiosis.TIF by Xiaohua Jiang (177009)

“…Annotation information was provided for both meiotic genes and predicted candidates, including basic information, function, protein–protein interaction (PPI), and expression data. …”

Table_8_MeiosisOnline: A Manually Curated Database for Tracking and Predicting Genes Associated With Meiosis.XLSX by Xiaohua Jiang (177009)

“…Annotation information was provided for both meiotic genes and predicted candidates, including basic information, function, protein–protein interaction (PPI), and expression data. …”

Table_3_MeiosisOnline: A Manually Curated Database for Tracking and Predicting Genes Associated With Meiosis.XLSX by Xiaohua Jiang (177009)

“…Annotation information was provided for both meiotic genes and predicted candidates, including basic information, function, protein–protein interaction (PPI), and expression data. …”

Table_6_MeiosisOnline: A Manually Curated Database for Tracking and Predicting Genes Associated With Meiosis.XLSX by Xiaohua Jiang (177009)

“…Annotation information was provided for both meiotic genes and predicted candidates, including basic information, function, protein–protein interaction (PPI), and expression data. …”

Table_4_MeiosisOnline: A Manually Curated Database for Tracking and Predicting Genes Associated With Meiosis.XLSX by Xiaohua Jiang (177009)

“…Annotation information was provided for both meiotic genes and predicted candidates, including basic information, function, protein–protein interaction (PPI), and expression data. …”