Image 1_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.jpeg حسب Jared Lichtarge (20548571)

"…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…"

Image 4_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.tiff حسب Jared Lichtarge (20548571)

"…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…"

Image 2_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.tiff حسب Jared Lichtarge (20548571)

"…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…"

<b>Neural Symbolic Vault: Symbolic Species and</b> <b>DNA Co-Encoding Research Bundle v1.0 (A+M[S] Archive)</b> حسب Jeffrey Siergiej (20937434)

"…</p><p><br></p><p dir="ltr"><br></p><p dir="ltr">Categories / Fields of Research (FOR codes):</p><p dir="ltr"><br></p><ul><li>Medical molecular engineering of nucleic acids and proteins</li><li>Genetically modified animals</li><li>Immunogenetics (incl. genetic immunology)</li><li>Symbolic Systems</li><li>Neural Engineering</li><li>Biomedical engineering not elsewhere classified</li><li>Quantum engineering systems (incl. computing and communications)</li></ul><p dir="ltr"><br></p><p dir="ltr"><br></p><p dir="ltr">Keywords:</p><p dir="ltr">Neural Symbolic Vault, symbolic-gene mutation, DNA-symbol compression, AxiomQoreEngine, A+M[S], Symbolic Token Ledger, artificial species generation, quantum DNA encoding, CLU math, mutation history registry, field interaction tracking</p><p dir="ltr"><br></p><p dir="ltr">Funding Statement:</p><p dir="ltr">No public funding declared. …"

Dendrogram of the stock prices. حسب Muhammad Hilal Alkhudaydi (21560690)

"…For this reason, having a solid understanding of the elements responsible for these uncertainties is absolutely necessary. …"

Descriptive statistics on stock prices. حسب Muhammad Hilal Alkhudaydi (21560690)

"…For this reason, having a solid understanding of the elements responsible for these uncertainties is absolutely necessary. …"

Correlation heatmap of the principal components. حسب Muhammad Hilal Alkhudaydi (21560690)

"…For this reason, having a solid understanding of the elements responsible for these uncertainties is absolutely necessary. …"

Identification of Neuronal Activity from Extracelullar Recordings with Ground-truth Patch Clamp حسب Carina Germer (18692413)

Spatial patterns of the CAPs estimated from both splits are reproducible and strongly correlated with at least one of the basis CAPs. حسب Kangjoo Lee (11648345)

Data Sheet 1_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.csv حسب Jared Lichtarge (20548571)

"…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…"

Video 2_Replicating associative learning of rodents with a neuromorphic robot in an open-field arena.mp4 حسب Tianze Liu (13922196)

Video 1_Replicating associative learning of rodents with a neuromorphic robot in an open-field arena.mp4 حسب Tianze Liu (13922196)

EEG Signals for Robust Cognitive Workload Recognition Under Noisy Conditions.zip حسب Fariya Bintay Shafi (21692408)

iNCog-EEG (ideal vs. Noisy Cognitive EEG for Workload Assessment) Dataset حسب Fariya Bintay Shafi (21692408)

The code for sample size calculation. حسب Ying Zhou (25031)

"…We collected basic clinical data and multimodal ultrasound data from these patients as predictive features, with clinical pregnancy as the predictive label, for model training. …"

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. …"

LSTM model’s equations. حسب Songsong Wang (8088293)

"…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…"

Parameter’s interpretation. حسب Songsong Wang (8088293)

"…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…"

The models’ training parameters. حسب Songsong Wang (8088293)

"…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…"