Attention mechanism. by Zhe Hu (787283)

“…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”

Shape error measurement results statistics. by Zhe Hu (787283)

“…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”

Swimming endurance training reduces T-wave amplitude and area in <i>Mib1</i>^<i>flox</i><i>;Tnnt2</i>^<i>Cre</i> mice. by Vítor S. Fernandes (21262991)

“…<p><b>(A)</b> Representative QRS complex and T-wave, with (A’) a close-up of the T-wave in WT and <i>Mib1</i>^<i>flox</i><i>;Tnnt2</i>^<i>Cre</i> mice before the swimming protocol. …”

Targeted screen of 20 conserved neuronal RBPs reveals eight novel associative memory regulators. by Ashley N. Hayden (19871128)

“…Worms that are neuronally sensitive to RNAi, LC108<i>(usIS69[myo-2p</i>::<i>mCherry + unc119p</i>::<i>sid-1])</i>, were starved for 1 hour, conditioned for 1 hour, and tested immediately for 1x learning (0 min) via chemotaxis assays, or transferred onto holding plates with OP50 for 0.5, 1, or 2 hours after conditioning, then tested for STM and ITM changes. …”

Puriton’s modulation effects on WBC composition in BALF and serum IgE. by So-Hyeon Bok (8066696)

“…<p>(A) Puriton decreased the number of WBC which was increased by ovalbumin treatment. …”

Figure 5 from Multiplexed Imaging Mass Cytometry Reveals Tumor-immune Microenvironment–dependent Hormone Receptor Expression in Adult-Type Ovarian Granulosa Cell Tumors by Eleonora Y. Khlebus (20814571)

“…<b>D,</b> Volcano plot of DEGs between AGCT subtypes. The <i>x</i>-axis indicates the FC (log₂ scaled), and the <i>y</i>-axis shows the adjusted <i>P</i> value (log₁₀ scaled). …”

The global disability-adjusted life years (DALYs) for asthma attributable to nitrogen dioxide pollution from 1990 to 2021 and predicted the trends from 2022 to 2050 by Yaping Feng (427666)

“…</p> <p>The global age-standardized DALYs rate (ASDALYs) decreased from 4.80 [95%<i>UI</i>: −4.29 to 17.75] in 1990 to 2.48 [95%<i>UI</i>: −2.26 to 10.30] in 2021. …”

Model training and testing with H3K27Ac only emphasized the marker’s prominence in generalizing across the study’s GSC datasets. by Yusuke Suita (14381481)

“…The only dataset whose performance decreased is the study’s GSC2. This overall increase could be explained by a possible reduction in “noise” with the removal of the other epigenetic signals in training and the zeros that were proxies for those signals in testing.…”

Data Sheet 2_Insights from DCE-MRI: blood–brain barrier permeability in the context of MS relapses and methylprednisolone treatment.pdf by Stig P. Cramer (20908724)

“…</p>Objectives<p>To investigate the predictive value of K_i in relation to clinical MS relapses and MP treatment, comparing its performance with traditional MRI markers.…”

Fig 2 - by Bernát Nógrádi (12264843)

“…However, the ratio of successful diagnoses was drastically decreased in the MDs group if the initial diagnosis was a non-acute disease. …”

Simulation Parameter Settings. by Jinrong Liang (3918740)

“…After applying Taylor pruning to the model, its floating-point operations (FLOPs) were reduced from 40.5 M to 9.5 M, and its parameter memory was decreased from 2.6 M to 0.5 M. Notably, following fine-tuning, the model still achieved 100% MF recognition accuracy and an average absolute error of 0.34 dB for OSNR estimation under a sample length of 16,000 and fiber length of 160 km. …”

Complexity analysis of each model. by Jinrong Liang (3918740)

“…After applying Taylor pruning to the model, its floating-point operations (FLOPs) were reduced from 40.5 M to 9.5 M, and its parameter memory was decreased from 2.6 M to 0.5 M. Notably, following fine-tuning, the model still achieved 100% MF recognition accuracy and an average absolute error of 0.34 dB for OSNR estimation under a sample length of 16,000 and fiber length of 160 km. …”

The effect of CEP and PDS treatment on recombinant CCHFV. by Yutong Sui (11151669)

“…<p>(<b>A</b>) Schematic representation of the L, M, and S genome segments of CCHFV (Strain IbAr10200). …”

Immunoblots analysis of mitophagy-related protein expression. by Michael O. Isei (20500908)

“…Immunoblots of PINK1 and parkin protein expression <b>(A)</b>. Densitometry quantification of PINK1 and parkin show no significant changes across all tau groups <b>(B, C)</b>. …”

Radon transform of the constellation diagram. by Jinrong Liang (3918740)

“…After applying Taylor pruning to the model, its floating-point operations (FLOPs) were reduced from 40.5 M to 9.5 M, and its parameter memory was decreased from 2.6 M to 0.5 M. Notably, following fine-tuning, the model still achieved 100% MF recognition accuracy and an average absolute error of 0.34 dB for OSNR estimation under a sample length of 16,000 and fiber length of 160 km. …”

Table 2_Adherence to recombinant human growth hormone therapy in children: influencing factors and clinical implications.xlsx by Wenjing Chang (8334480)

“…However, non-adherence remains a significant challenge, affecting treatment efficacy and patient prognosis. …”

Table 1_Adherence to recombinant human growth hormone therapy in children: influencing factors and clinical implications.xlsx by Wenjing Chang (8334480)

“…However, non-adherence remains a significant challenge, affecting treatment efficacy and patient prognosis. …”

The process of Taylor score pruning. by Jinrong Liang (3918740)

“…After applying Taylor pruning to the model, its floating-point operations (FLOPs) were reduced from 40.5 M to 9.5 M, and its parameter memory was decreased from 2.6 M to 0.5 M. Notably, following fine-tuning, the model still achieved 100% MF recognition accuracy and an average absolute error of 0.34 dB for OSNR estimation under a sample length of 16,000 and fiber length of 160 km. …”

The principle of Radon transformation. by Jinrong Liang (3918740)

“…After applying Taylor pruning to the model, its floating-point operations (FLOPs) were reduced from 40.5 M to 9.5 M, and its parameter memory was decreased from 2.6 M to 0.5 M. Notably, following fine-tuning, the model still achieved 100% MF recognition accuracy and an average absolute error of 0.34 dB for OSNR estimation under a sample length of 16,000 and fiber length of 160 km. …”

Ring constellation diagram. by Jinrong Liang (3918740)

“…After applying Taylor pruning to the model, its floating-point operations (FLOPs) were reduced from 40.5 M to 9.5 M, and its parameter memory was decreased from 2.6 M to 0.5 M. Notably, following fine-tuning, the model still achieved 100% MF recognition accuracy and an average absolute error of 0.34 dB for OSNR estimation under a sample length of 16,000 and fiber length of 160 km. …”