Relative mRNA levels of DNA methyltransferases (<i>Dnmt1</i>, <i>Dnmt3a</i>, and <i>Dnmt3b</i>; a) and microRNAs (<i>mir-29b</i>, <i>mir-148a</i>, and <i>mir-152</i>; b) in porcine... by Shuang Liang (211832)

Analysis of the impact of the NARS2 mutations on mitochondrial functions. by Mariella Simon (711384)

Kavain did not affect propofol potentiation, but modestly reduced propofol activation at α1β2γ2L GABA_ARs. by Han Chow Chua (817600)

Table 1_Gender differences in the association between sleep duration and diabetes in Chinese adults.docx by Haiyan Yu (356393)

“…</p>Conclusions<p>There was a U-shaped association between sleep duration and the risk of diabetes in women, with the lowest risk for diabetes at approximately 8–9h/day. …”

Data Sheet 1_Gender differences in the association between sleep duration and diabetes in Chinese adults.docx by Haiyan Yu (356393)

“…</p>Conclusions<p>There was a U-shaped association between sleep duration and the risk of diabetes in women, with the lowest risk for diabetes at approximately 8–9h/day. …”

Biophysics of root growth in soil. by Matthias Mimault (14755874)

Optimized MLP network model. by Yanlin Liu (398738)

“…Precision reaches 95.4%, reflecting an average enhancement of 19.2%, while sensitivity attains 84.1%, with an average improvement of 11.8%. The mean absolute error is only 1.16, exhibiting a 1.4 reduction compared to traditional models and confirming the effectiveness of the optimized model in prediction. …”

Sustainable development strategies. by Yanlin Liu (398738)

“…Precision reaches 95.4%, reflecting an average enhancement of 19.2%, while sensitivity attains 84.1%, with an average improvement of 11.8%. The mean absolute error is only 1.16, exhibiting a 1.4 reduction compared to traditional models and confirming the effectiveness of the optimized model in prediction. …”

S1 Data - by Yanlin Liu (398738)

“…Precision reaches 95.4%, reflecting an average enhancement of 19.2%, while sensitivity attains 84.1%, with an average improvement of 11.8%. The mean absolute error is only 1.16, exhibiting a 1.4 reduction compared to traditional models and confirming the effectiveness of the optimized model in prediction. …”

Experimental variable. by Yanlin Liu (398738)

“…Precision reaches 95.4%, reflecting an average enhancement of 19.2%, while sensitivity attains 84.1%, with an average improvement of 11.8%. The mean absolute error is only 1.16, exhibiting a 1.4 reduction compared to traditional models and confirming the effectiveness of the optimized model in prediction. …”

The particle model. by Matthias Mimault (14755874)

The lagged impact of different factors and scenarios on COVID-19 transmission during the Delta wave in 2021. by Eimear Cleary (6794792)

“…The deeper the shade of purple, the greater the increase in transmission risk, while the deeper the shade of green, the greater the decrease in Rt. <b>(C)</b> COVID-19 lag–response association for mobility level at 0.6, 0.8, 1.25, relative to the overall pre-pandemic mean level (1). …”

The lagged impact of different factors and scenarios on COVID-19 transmission during the initial wave of COVID-19 transmission in the second half of 2020. by Eimear Cleary (6794792)

“…The deeper the shade of purple, the greater the increase in RR of transmission, while the deeper the shade of green, the greater the decrease in RR. <b>(C)</b> COVID-19 lag–response association for mobility level at 0.8, 1.2, 1.4 relative to the overall pre-pandemic mean level (1). …”

Simulation showing how the softening and anisotropy coefficients vary in the roots of Pisum sativum in response to increases in soil strength using strain rate data from [15] and r... by Matthias Mimault (14755874)

Discrete outcome definitions. by Jesse M. Charlton (5495855)

“…Minimal changes in joint moments were observed but there was a consistent pattern of decreasing joint stiffness with increasing pain intensity. …”

Stone pine fruit traits by cone weight category. by Verónica Loewe-Muñoz (18107127)

“…Cone to pine nut yield (PY) and other traits were calculated and compared between categories using a mixed linear model. Regression trees were used to explain PY variability. …”

Stone pine fruit traits. by Verónica Loewe-Muñoz (18107127)

“…Cone to pine nut yield (PY) and other traits were calculated and compared between categories using a mixed linear model. Regression trees were used to explain PY variability. …”

Nutrient recommendation based on Indonesian RNI¹ used in the LP analyses. by Umi Fahmida (10007846)

Future applications for SPH models in root developmental biology. by Matthias Mimault (14755874)

Experimental setup. by Jesse M. Charlton (5495855)