Comparison of simulation results. by Bo Xie (669374)

“…These values are significantly lower than the cable clamp’s breaking tensile strength of 70 kN, with peak values of 57.4 N and 94.1 N, respectively. …”

Technical parameters of the shearer. by Bo Xie (669374)

“…These values are significantly lower than the cable clamp’s breaking tensile strength of 70 kN, with peak values of 57.4 N and 94.1 N, respectively. …”

Simulation-related parameters. by Bo Xie (669374)

“…These values are significantly lower than the cable clamp’s breaking tensile strength of 70 kN, with peak values of 57.4 N and 94.1 N, respectively. …”

Chain drive specification parameters. by Bo Xie (669374)

“…These values are significantly lower than the cable clamp’s breaking tensile strength of 70 kN, with peak values of 57.4 N and 94.1 N, respectively. …”

Femoral tensile test data. by Bo Xie (669374)

“…These values are significantly lower than the cable clamp’s breaking tensile strength of 70 kN, with peak values of 57.4 N and 94.1 N, respectively. …”

Survey sample distribution. by Yin Liu (50073)

“…The results show that: (1) Based on the counterfactual hypothesis, if the farmers who obtain microcredit for poverty-alleviated population are not loaned, their production and operating income will decrease by 3.31%, that is, microcredit has a significant income-increasing effect, and the income-increasing effect of obtaining microcredit for the poverty-alleviated population on the monitoring objects is greater than the households that have lifted out of poverty. (2) The mechanism of action shows that the microcredit policy for the poverty- alleviated population promotes income increase by promoting farmers to increase material capital investment and social capital investment. (3) The income-increasing effect of obtain microcredit for poverty-alleviated population on the low-income initial endowment farmers is greater than that on high-income initial endowment farmers, and farmers with low-land initial endowment have a higher income increase effect, that is, a ‘raising the low ‘ effect. …”

Variable definition and descriptive statistics. by Yin Liu (50073)

“…The results show that: (1) Based on the counterfactual hypothesis, if the farmers who obtain microcredit for poverty-alleviated population are not loaned, their production and operating income will decrease by 3.31%, that is, microcredit has a significant income-increasing effect, and the income-increasing effect of obtaining microcredit for the poverty-alleviated population on the monitoring objects is greater than the households that have lifted out of poverty. (2) The mechanism of action shows that the microcredit policy for the poverty- alleviated population promotes income increase by promoting farmers to increase material capital investment and social capital investment. (3) The income-increasing effect of obtain microcredit for poverty-alleviated population on the low-income initial endowment farmers is greater than that on high-income initial endowment farmers, and farmers with low-land initial endowment have a higher income increase effect, that is, a ‘raising the low ‘ effect. …”

Robustness test. by Yin Liu (50073)

“…The results show that: (1) Based on the counterfactual hypothesis, if the farmers who obtain microcredit for poverty-alleviated population are not loaned, their production and operating income will decrease by 3.31%, that is, microcredit has a significant income-increasing effect, and the income-increasing effect of obtaining microcredit for the poverty-alleviated population on the monitoring objects is greater than the households that have lifted out of poverty. (2) The mechanism of action shows that the microcredit policy for the poverty- alleviated population promotes income increase by promoting farmers to increase material capital investment and social capital investment. (3) The income-increasing effect of obtain microcredit for poverty-alleviated population on the low-income initial endowment farmers is greater than that on high-income initial endowment farmers, and farmers with low-land initial endowment have a higher income increase effect, that is, a ‘raising the low ‘ effect. …”

Group differences in perceptual bias scores. by Daniel E. Lidstone (21567523)

Trends of the temperature, precipitation, and TVDI in the Santun River Irrigation Area, Xinjiang, during 2005–2023. by Yuxin Wei (11510974)

LEfSe Analysis. by Tejaswini Baral (14320736)

Analysis of cellular proliferation in βA3ΔG91 vs. WT mice lenses using BrdU assay. by Akosua K. Boateng (21672931)

IRE1 depletion increases chromosome instability. by Iratxe Zuazo-Gaztelu (21071939)

Complete list of 81 <i>CTSZ</i> SNPs present in Ugandan household contact study cohorts and their associations with TB severity. by Rachel K. Meade (22216529)

S1 File - A novel yeast-derived aldehyde-reducing compound MF001 protects against alcohol-induced liver damage by Eun-Ho Lee (2696890)

A Comparison of Pediatric Prehospital Opioid Encounters and Social Vulnerability by Stephen Sandelich (19991783)

“…The analysis demonstrated that as socioeconomic status (SES) improves, the likelihood of opioid-related activations increases significantly supported by a significant negative linear trend (Estimate = −0.2971, SE = 0.1172, z = −2.54, <i>p</i> = 0.0112. …”

Complexity comparison of different models. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”

Dynamic window based median filtering algorithm. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”

Flow of operation of improved KMA. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”

Improved DAE based on LSTM. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”