ANOM analysis of evaluated criteria K1–K5. by Roman Vavrek (13200141)

“…The presented research works with five criteria, identified by the Institute for Economic and Social Reforms, and aims to quantify the agreement of the results of the assessment of the financial health of territorial self-government entities in 2020 using the TOPSIS technique with a gradually decreasing number of criteria. For this purpose, a total of 26 combinations of criteria are created, with the number of 5, 4, 3 and 2 used criteria, the importance of which is determined based on their absolute variability using the standard deviation method. …”

<i>Shroom3</i> is expressed throughout the mouse myocardium postnatally. by Jennifer L. Carleton (22208916)

Effect of desilication temperature on hybrid desilication by Nian Liu (29935)

Effect of alkali concentration on mixed desilication by Nian Liu (29935)

Adult <i>Shroom3</i>^<i>+</i>^<i>/Gt</i> mouse hearts show left ventricular thinning. by Jennifer L. Carleton (22208916)

“…C) Quantification of the thickness of the compact layers of 3-month-old hearts showed a significant decrease in left ventricle wall thickness in the heterozygous mice (P < 0.0001) when compared to the wild-type. …”

Calcitriol inhibits CaSki cell migration and suppresses MMP7 and MMP13 gene expression. by Euclides Avila (41023)

Effect of raw material ratios on desilication of mixed ores by Nian Liu (29935)

Embryos with compound <i>Shroom3</i>^<i>Gt/fl</i> alleles phenocopy <i>Shroom3</i>^<i>Gt/Gt</i> embryos. by Jennifer L. Carleton (22208916)

Protein-protein interaction network of upregulated genes in the <i>Acinetobacter baumannii smpB</i> mutant. by Techit Thavorasak (13138440)

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

Proposed metabolic pathways related to vanadate reduction and alanine production by <i>T</i>. <i>mesophilus</i> VROV1. by Bokyung Kim (622579)

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. …”

Article data. 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. …”

Overidentification test results. 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. …”

Quantile regression results. 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. …”

Instrumental variable regression results. 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. …”

Other robust regression results. 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. …”

Baseline regression results. 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. …”

Results of propensity score matching. 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. …”