Impact of PAC dosage on HPST. by Peng Zhao (128233)

“…This paper was to study the optimal conditions of HPST, first, some single-factor tests were conducted to preliminarily explore the optimal range of influencing factors, and then response surface methodology (RSM) tests were performed to accurately determine the optimums of significant factors.The results showed that adding sludge can not improve the water quality of coagulation treatment, but it can significantly accelerate the coagulation settlement process, the sludge dosage, the coagulant dosage and sewage pH all impacted significantly on its coagulation effect, and existed inflection points. …”

Fiber types and muscle force in the soleus of 18-20-week-old WT and NMIIC KO mice. by Hiroki Hamaguchi (22783780)

Phenotypic characterization of 81-week-old NMIIC KO mice. by Hiroki Hamaguchi (22783780)

Pre- and post-study virus-specific IgG responses for bats in the SOSV-MARV and KASV-MARV experimental cohorts. by Amy J. Schuh (8520354)

Coupled gGM and CSF fMRI signal changes induced by a transient hypercapnia challenge. by Juliana Zimmermann (10507091)

Age-dependent expression of <i>ANXA1</i> gene in monocytes and their subtypes. by Juliane F. Tampé (19976538)

Volume distribution and sentiment of positive, negative, and neutral tweets. by Yuqi Zhang (286958)

Genes correlated with SARS-CoV-2 viral load over time are similarly expressed in independent datasets of SARS-CoV-2 infected lung and upper airway cells. by Vasanthi Avadhanula (259546)

Differential gene sets associated with the transcriptional host response to SARS-CoV-2 infection across serially collected samples. by Vasanthi Avadhanula (259546)

Differential expression patterns and functional gene groups associated with SARS-CoV-2 infection of nose organoids. by Vasanthi Avadhanula (259546)

“…<b>(c)</b> Similar to part b, but for genes decreased with SARS-CoV-2 infection. <b>(d)</b> Selected significantly enriched GO terms ⁴¹ within the genes over-expressed with SARS-CoV-2 infection in HNO204 (p<0.05, t-test). …”

Table 2 - by Rosanna Mary Rooney (17595801)

“…Despite a global decrease over the last 30 years, youth crime remains prevalent. …”

Distributions of Passenger Patience for the Period 1: (a) Histogram of Taxi Wait Times and PDF of Patience for 1^st Forced Stops in Zone 1; (b) CDFs of Taxi Wait Times an... by Fangyi Yang (18867853)

Developmental loss of <i>Shroom3</i> in the myocardium does not affect cardiomyocyte cross sectional area in adults. by Jennifer L. Carleton (22208916)

Serum hormone levels in WT, HET and HOM animals. by Wendy J. Bailey (14926392)

Data. by Haiwei Li (282229)

“…Furthermore, restricted cubic spline analysis revealed a significant linear relationship between PAL and CVD (nonlinear P > 0.05), indicating that the OR for CVD decreased with higher levels of PAL.…”

IFA reduced the capsular biosynthesis through altering bacterial metabolism. by Tingting Wang (123983)

Embryonic <i>Shroom3</i>^{<i>Gt</i>/<i>Gt</i>} hearts show left ventricular thinning. by Jennifer L. Carleton (22208916)

NeuN staining of 6-, 9-, and 12-month dLGN sections shows loss of thalamocortical cell bodies in the 5xFAD mice. by Shaylah McCool (20818280)

Regression results of the Callaway method. by Pu Miao (12886949)

“…During this lag period, the effect on the number of patent declines by 8.475% to 28.283%, while the impact on the number of citations of patents decreases by 55.696% to 73.214%. (4) The significant promotional effect of science and technology talent policies is most pronounced in non-state-owned enterprises and those with high R&D investment, but such policies do not have a notable impact on state-owned enterprises or those with low R&D investment. …”

Regression results of crowding out effects. by Pu Miao (12886949)

“…During this lag period, the effect on the number of patent declines by 8.475% to 28.283%, while the impact on the number of citations of patents decreases by 55.696% to 73.214%. (4) The significant promotional effect of science and technology talent policies is most pronounced in non-state-owned enterprises and those with high R&D investment, but such policies do not have a notable impact on state-owned enterprises or those with low R&D investment. …”