An example time series obtained from one rat in the vericiguat protocol. by Aimi Yokoi (16819464)

“…The red and yellow lines in the AP plot indicate 100-Hz resampled and 2-s moving averaged signals, respectively. …”

An example time series obtained from one rat in the SNP protocol. by Aimi Yokoi (16819464)

“…The red and yellow lines in the AP plot indicate 100-Hz resampled and 2-s moving averaged signals, respectively. …”

Probing the Sensitivity of the Orbitrap Lumos Mass Spectrometer Using a Standard Reference Protein in a Complex Background by Michaella J. Levy (1564081)

“…In contrast, when the peptides and fragments were both detected in the Orbitrap on either the Lumos or Q-Exactive Plus (FTFT mode), the lowest concentration of NIST monoclonal antibody detected was 50 pg. The Lumos can detect a single protein at a level 2500 times lower than the whole cell background and the combination of detecting ions in the Orbitrap and ion trap can improve the identification of low abundance proteins. …”

CavA and Vfr are regulators of global intracellular c-di-GMP levels in <i>A. baumannii</i>. by Lyuboslava G. Harkova (19557062)

“…Deletion of <i>cavA</i> reduced c-di-GMP levels by 66% (<b>A</b>) while disruption of <i>vfr</i> decreased them by 49% (<b>B</b>). …”

Plasmid constructs used in this study. by Zahra Hosseininia (22265113)

“…The <i>PRAME-AS</i> knockout cells showed a decrease in migration, proliferation, stemness, and viability. …”

Oligonucleotides used in this study. by Zahra Hosseininia (22265113)

“…The <i>PRAME-AS</i> knockout cells showed a decrease in migration, proliferation, stemness, and viability. …”

Ocean acidification at a coastal CO₂ vent induces expression of stress-related transcripts and transposable elements in the sea anemone <i>Anemonia viridis</i> by Ilona Urbarova (6197741)

“…We found that about 1.4% of the anemone transcripts, but only ~0.5% of the <i>Symbiodinium</i> sp. transcripts were differentially expressed. …”

2P excitation of DiO/DPA enables AP detection in a L5 pyramidal cell. A. by Ann E. Fink (312543)

“…Fluorescence traces were not inverted. <b>C</b>. Average of 50 trials showing fAPs and a DiO/DPA optical response to a 6.8 mV depolarization. …”

NAC suppresses Ang II–induced mitochondrial fission in mouse VSMCs. by Dong Ma (584680)

Zpg does not function as a hemichannel. by Yanina-Yasmin Pesch (13884117)

“…<p>(A-D) <i>zpg</i> mutants rescued with genomic rescue constructs in which one or more cysteine residues were mutated, hindering the formation of gap junctions, have rudimentary testes and no Zpg is detected by antibody staining (green in A-D; single channels depicted in grey in A’-D’; wt in A-A’; <i>zpg</i> C6S, B-B’:, <i>zpg</i> C145S, C-C’; <i>zpg</i> C236S, D-D’). …”

Characteristics of Gasless Combustion of Core–Shell Al@NiO Microparticles with Boosted Exothermic Performance by Shina Maini (19413980)

“…The PM composite was not able to be ignited at all by a 5 W laser, while the core–shell counterpart ignited at 2.55 ms and was completely combusted within 6.50 ms accompanying a violent impulse.…”

Characteristics of Gasless Combustion of Core–Shell Al@NiO Microparticles with Boosted Exothermic Performance by Shina Maini (19413980)

“…The PM composite was not able to be ignited at all by a 5 W laser, while the core–shell counterpart ignited at 2.55 ms and was completely combusted within 6.50 ms accompanying a violent impulse.…”

Maintenance of weight loss or stability in subjects with obesity: a retrospective longitudinal analysis of a real-world population by Maral DerSarkissian (504144)

“…</p> <p><b>Methods:</b> A retrospective observational longitudinal study of subjects with obesity was conducted using the General Electric Centricity electronic medical record database. …”

IG feature selection process. by Ahmed Muqdad Alnasrallah (21647492)

“…The proposed model employs Information Gain (IG) and Recursive Feature Elimination (RFE) in parallel to select the top 50% of features, from which intersection and union subsets are created, followed by a deep autoencoder (DAE) to reduce dimensionality without losing important data. …”

RFE feature selection process. by Ahmed Muqdad Alnasrallah (21647492)

“…The proposed model employs Information Gain (IG) and Recursive Feature Elimination (RFE) in parallel to select the top 50% of features, from which intersection and union subsets are created, followed by a deep autoencoder (DAE) to reduce dimensionality without losing important data. …”

CICID2017 dataset information. by Ahmed Muqdad Alnasrallah (21647492)

“…The proposed model employs Information Gain (IG) and Recursive Feature Elimination (RFE) in parallel to select the top 50% of features, from which intersection and union subsets are created, followed by a deep autoencoder (DAE) to reduce dimensionality without losing important data. …”

Shows the basic architecture of an autoencoder. by Ahmed Muqdad Alnasrallah (21647492)

“…The proposed model employs Information Gain (IG) and Recursive Feature Elimination (RFE) in parallel to select the top 50% of features, from which intersection and union subsets are created, followed by a deep autoencoder (DAE) to reduce dimensionality without losing important data. …”

Architecture of deep neural networks. by Ahmed Muqdad Alnasrallah (21647492)

“…The proposed model employs Information Gain (IG) and Recursive Feature Elimination (RFE) in parallel to select the top 50% of features, from which intersection and union subsets are created, followed by a deep autoencoder (DAE) to reduce dimensionality without losing important data. …”

Proposed model framework. by Ahmed Muqdad Alnasrallah (21647492)

“…The proposed model employs Information Gain (IG) and Recursive Feature Elimination (RFE) in parallel to select the top 50% of features, from which intersection and union subsets are created, followed by a deep autoencoder (DAE) to reduce dimensionality without losing important data. …”

WUSTL-EHMS-2020 dataset information. by Ahmed Muqdad Alnasrallah (21647492)

“…The proposed model employs Information Gain (IG) and Recursive Feature Elimination (RFE) in parallel to select the top 50% of features, from which intersection and union subsets are created, followed by a deep autoencoder (DAE) to reduce dimensionality without losing important data. …”