Weight and plasma biochemistry. by Søren Egstrand (10906087)

“…In the present study, we found significant diurnal rhythmicity of <i>Casr</i>, encoding the Cinacalcet drug target in hyperplastic parathyroid glands (p = 0.006). …”

Baseline clinical data. by Lu-Jin Cheng (21743350)

“…In vitro experiments showed that the addition of Gal-9 led to a significant increase in the proportion of TIM-3⁺M1 and TIM-3⁺M2 macrophages and a decrease in M1 cell proportions and M1/M2 ratio. …”

Final dataset. by Keiko Ochiai (21453423)

“…While a significant association between these attributes was observed, a comprehensive path analysis revealed that each attribute independently correlated with higher SDQ scores, suggesting that child maltreatment leads to these difficulties through accelerated aging and decreased eye contact. …”

Demographic Characteristics of Participants. by Keiko Ochiai (21453423)

“…While a significant association between these attributes was observed, a comprehensive path analysis revealed that each attribute independently correlated with higher SDQ scores, suggesting that child maltreatment leads to these difficulties through accelerated aging and decreased eye contact. …”

Illustrative diagram of the three crash types. by Chun-Chieh Chao (2681722)

“…</p><p>Results</p><p>Significant risk factors for overtaking crashes included heavy goods vehicles (HGVs) as crash partners (AOR = 1.30, 95% CI 1.27–1.33), and elderly crash partners (AOR = 2.01, 95% CI = 1.94–2.09), and decreased risk in rural area with speed limits of 20–30 miles per hour (AOR = 0.45, 95% CI = 0.43–0.47). …”

Multivariate logistic regression results. by Chun-Chieh Chao (2681722)

“…</p><p>Results</p><p>Significant risk factors for overtaking crashes included heavy goods vehicles (HGVs) as crash partners (AOR = 1.30, 95% CI 1.27–1.33), and elderly crash partners (AOR = 2.01, 95% CI = 1.94–2.09), and decreased risk in rural area with speed limits of 20–30 miles per hour (AOR = 0.45, 95% CI = 0.43–0.47). …”

Univariate logistic regression results. by Chun-Chieh Chao (2681722)

“…</p><p>Results</p><p>Significant risk factors for overtaking crashes included heavy goods vehicles (HGVs) as crash partners (AOR = 1.30, 95% CI 1.27–1.33), and elderly crash partners (AOR = 2.01, 95% CI = 1.94–2.09), and decreased risk in rural area with speed limits of 20–30 miles per hour (AOR = 0.45, 95% CI = 0.43–0.47). …”

Some examples of selected Chinese characters. by Weijia Zhu (65481)

“…To address these challenges, we propose esFont, a novel guided Diffusion framework. …”

Ferroptosis Induction by a New Pyrrole Derivative in Triple Negative Breast Cancer and Colorectal Cancer by Domiziana Masci (4224451)

“…Furthermore, lactoperoxidase, malondialdehyde, and Fe­(II) levels significantly increased in <b>12</b>-treated tissues, whereas superoxide dismutase concentrations decreased. …”

Ferroptosis Induction by a New Pyrrole Derivative in Triple Negative Breast Cancer and Colorectal Cancer by Domiziana Masci (4224451)

“…Furthermore, lactoperoxidase, malondialdehyde, and Fe­(II) levels significantly increased in <b>12</b>-treated tissues, whereas superoxide dismutase concentrations decreased. …”

Summary of correlations in previous studies. by Dan Kuang (136225)

“…Furthermore, the infection rates of SARS-CoV-2, as estimated by the model, ranged from 0.012% (P5-P95: 0.004% - 0.020%) at the lowest baseline to 3.27% (P5-P95: 1.23% - 5.69%) at the peak of the epidemic, with 15.1% (P5-P95: 5.65% - 26.2%) of individuals infected during the epidemic wave between March 4th and June 15th. Additionally, we did not observe any COVID-19 outbreaks or cluster infections at the Chengdu 2023 FISU World University Games village, and there was no significant difference in the concentrations of SARS-CoV-2 in athletes before and after check-in at the village.…”

The characteristics of nine WWTPs. by Dan Kuang (136225)

“…Furthermore, the infection rates of SARS-CoV-2, as estimated by the model, ranged from 0.012% (P5-P95: 0.004% - 0.020%) at the lowest baseline to 3.27% (P5-P95: 1.23% - 5.69%) at the peak of the epidemic, with 15.1% (P5-P95: 5.65% - 26.2%) of individuals infected during the epidemic wave between March 4th and June 15th. Additionally, we did not observe any COVID-19 outbreaks or cluster infections at the Chengdu 2023 FISU World University Games village, and there was no significant difference in the concentrations of SARS-CoV-2 in athletes before and after check-in at the village.…”

Primers for RT-qPCR. by Jiaoyang Li (2862269)

“…To elucidate the function of NSP2 during PRRSV infection, we identified SH3KBP1 as an NSP2-interacting host protein using mass spectrometry. …”

Validation and predictive accuracy of the cerebrovascular model, by Hadi Esfandi (21387211)

“…Next, we combined blood flow data from non-bifurcating capillaries at all tested ABNP levels (10 steps) into a single dataset and calculated the means and standard deviations across layers L1-L4, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0321053#pone.0321053.g006" target="_blank">Fig 6</a>(b-c). …”

Oligonucleotide primers for gene expression. by Cian Reid (17274007)

“…This hyper-induction of IL-6 was observed most significantly in response to TLR1/2 stimulation in TUS positive calves. …”

Calf health information. by Cian Reid (17274007)

“…This hyper-induction of IL-6 was observed most significantly in response to TLR1/2 stimulation in TUS positive calves. …”

Mean parameter values for the selected crops. by Gourab Saha (8987405)

“…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”

Performance comparison of ML models. by Gourab Saha (8987405)

“…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”

Comparative data of different soil samples. by Gourab Saha (8987405)

“…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”

Confusion matrix of random forest model. by Gourab Saha (8987405)

“…In this article, we present a complete integrated design of a smart IoT-based suitable agricultural land and crop selection, along with an irrigation system using agricultural mapping, machine learning, and fuzzy logic for precision agriculture. …”