Effect of 0.1mM salicylic acid (SA) or hydrogen peroxide (H₂O₂) and salt treatment (0 and 75 mM NaCl) on shoots (A) and roots (B) DW of lentil plants. by Amal Bouallegue (21512298)

Effect of 0.1mM salicylic acid (SA) or hydrogen peroxide (H₂O₂) and salt treatment (0 and 75 mM NaCl) on the superoxide dismutase activity (SOD) in shoots (A)... by Amal Bouallegue (21512298)

Effect of 0.1mM salicylic acid (SA) or hydrogen peroxide (H₂O₂) and salt treatment (0 and 75 mM NaCl) on malondialdehyde (MDA) level in shoots (A) and roots (... by Amal Bouallegue (21512298)

Effect of 0.1mM salicylic acid (SA) or hydrogen peroxide (H₂O₂) and salt treatment (0 and 75 mM NaCl) on hydrogen peroxide (H₂O₂) conten... by Amal Bouallegue (21512298)

Major hyperparameters of RF-SVR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Pseudo code for coupling model execution process. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Major hyperparameters of RF-MLPR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Results of RF algorithm screening factors. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Schematic diagram of the basic principles of SVR. by Jintao Li (448681)

“…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R² value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …”

Effects of MC treatment on protein expression in DNBS-induced colitis rats. by Jin-Hwa Kim (101817)

Gene expression of the <i>hsp70Ab</i>-group and <i>hsp68</i> genes after baculovirus infection under different heat shock stimuli. by Enrique Paz-Cortés (20988196)

The performance of eigenvectors of the covariance matrix in a model with more complex population structure. by Joshua G. Schraiber (8027060)

Impact of including phylogenetic eigenvectors on detection of coevolution of gene-expression levels in fungi. by Joshua G. Schraiber (8027060)

Performance of different methods for controlling confounding in Felsenstein’s worst case. by Joshua G. Schraiber (8027060)

Attitude towards NTDs in the study Area. by Uchechukwu M. Chukwuocha (6685790)

“…<div><p>Background</p><p>Neglected Tropical Diseases (NTDs) continue to significantly impact marginalized communities, contributing to high morbidity, stigma, and social exclusion. …”

Dataset of results. by Uchechukwu M. Chukwuocha (6685790)

“…<div><p>Background</p><p>Neglected Tropical Diseases (NTDs) continue to significantly impact marginalized communities, contributing to high morbidity, stigma, and social exclusion. …”

Respondents’ perception about the public artwork. by Uchechukwu M. Chukwuocha (6685790)

“…<div><p>Background</p><p>Neglected Tropical Diseases (NTDs) continue to significantly impact marginalized communities, contributing to high morbidity, stigma, and social exclusion. …”

Sex- and age-related changes in individual variance and behavioural repeatability. by Andréa L. Johnson (22505376)

Myeloid knockout <i>VANGL2</i> exacerbates the progression of DSS-induced colitis in mice. by Huaji Jiang (16907514)

Down-regulation of VANGL2 in IBD patients triggers overt activation of NLRP3 inflammasome. by Huaji Jiang (16907514)