The flow chart of literature selection process. by Danni Jiang (1722013)

Subjects:

Visualisation of significantly differentially expressed genes (DEGs). by Mohammed A. Alfattah (18271622)

Cell movement as the top GO process as revealed by Toppgene, an open source pathway analysis tool. by Afrooz Jahedi (14636554)

Subjects:

Data_Sheet_1_Parallelization of Neural Processing on Neuromorphic Hardware.pdf by Luca Peres (12524143)

“…This article presents novel multicore processing strategies on the SpiNNaker Neuromorphic hardware, addressing parallelization of Spiking Neural Network operations through allocation of dedicated computational units to specific tasks (such as neural and synaptic processing) to optimize performance. …”

Data_Sheet_1_Decoding time-resolved neural representations of orientation ensemble perception.docx by Ryuto Yashiro (19279171)

YOLOv11-RKNN model deployment process. by Zishuo Wang (6790781)

Data_Sheet_1_Time-Dependent Effects of Acute Handling on the Brain Monoamine System of the Salmonid Coregonus maraena.PDF by Joan Martorell-Ribera (9730202)

Data_Sheet_2_Expert and deep learning model identification of iEEG seizures and seizure onset times.DOCX by Sharanya Arcot Desai (11034072)

“…While these records provide invaluable information about the patient’s electrographic seizure and interictal activity patterns, manually classifying them into electrographic seizure/non-seizure activity, and manually identifying the seizure onset channels and times is an extremely time-consuming process. A convolutional neural network based Electrographic Seizure Classifier (ESC) model was developed in an earlier study. …”

Data_Sheet_1_Expert and deep learning model identification of iEEG seizures and seizure onset times.DOCX by Sharanya Arcot Desai (11034072)

“…While these records provide invaluable information about the patient’s electrographic seizure and interictal activity patterns, manually classifying them into electrographic seizure/non-seizure activity, and manually identifying the seizure onset channels and times is an extremely time-consuming process. A convolutional neural network based Electrographic Seizure Classifier (ESC) model was developed in an earlier study. …”

SEM image of 10-micron iron oxide particles. by Yang Li (7082)

Subjects:

Data_Sheet_1_Most Small Cerebral Cortical Veins Demonstrate Significant Flow Pulsatility: A Human Phase Contrast MRI Study at 7T.PDF by Ian D. Driver (6669422)

Data_Sheet_1_Striatal Volume Increase After Six Weeks of Selective Dopamine D2/3 Receptor Blockade in First-Episode, Antipsychotic-Naïve Schizophrenia Patients.docx by Helle G. Andersen (8869196)

“…This interaction was explained by a significant striatal volume increase of 2.1% in patients (Cohens d = 0.45). …”

Table_1_Using Home-Cage Monitoring to Determine the Impact of Timed Mating on Male Mouse Welfare.pdf by Joanna L. Moore (12121134)

Line fringe structured light generation process. by Guofeng Qin (11025170)

Summary of the effect of MPDD on SDLP across all participants, and also participants categorized by driving styles (“NS” (no significant), “+” (significant increase), and “-” (significant decrease)). by Mobina Faqani (22783963)

“…<p>Summary of the effect of MPDD on SDLP across all participants, and also participants categorized by driving styles (“NS” (no significant), “+” (significant increase), and “-” (significant decrease)).…”

Concentration of RebA and Steviol showed increased significantly, whereas stevioside showed significant decrease in all the transgenic lines. by Nazima Nasrullah (6874496)

“…<p>Concentration of RebA and Steviol showed increased significantly, whereas stevioside showed significant decrease in all the transgenic lines.…”

Image_4_The Benefit of Slice Timing Correction in Common fMRI Preprocessing Pipelines.TIF by David B. Parker (1890751)

“…We conclude that STC is a critical part of the preprocessing pipeline that can be extremely beneficial for fMRI processing. However, its effectiveness interacts with other preprocessing steps and with other scan parameters and conditions which may obscure its significant importance in the fMRI processing pipeline.…”

Image_2_The Benefit of Slice Timing Correction in Common fMRI Preprocessing Pipelines.TIF by David B. Parker (1890751)

“…We conclude that STC is a critical part of the preprocessing pipeline that can be extremely beneficial for fMRI processing. However, its effectiveness interacts with other preprocessing steps and with other scan parameters and conditions which may obscure its significant importance in the fMRI processing pipeline.…”

Image_3_The Benefit of Slice Timing Correction in Common fMRI Preprocessing Pipelines.TIF by David B. Parker (1890751)

“…We conclude that STC is a critical part of the preprocessing pipeline that can be extremely beneficial for fMRI processing. However, its effectiveness interacts with other preprocessing steps and with other scan parameters and conditions which may obscure its significant importance in the fMRI processing pipeline.…”

Table_1_The Benefit of Slice Timing Correction in Common fMRI Preprocessing Pipelines.DOCX by David B. Parker (1890751)

“…We conclude that STC is a critical part of the preprocessing pipeline that can be extremely beneficial for fMRI processing. However, its effectiveness interacts with other preprocessing steps and with other scan parameters and conditions which may obscure its significant importance in the fMRI processing pipeline.…”