The linearly decreasing convergence factor a. by Junhao Wei (6816803)

Results of significance for regression factors. by Junxia Zhou (14381598)

“…Micro-cracks appeared in the cemented body by Day 7, resulting in a slight decrease in strength (3.92%) from Day 3 to Day 7. …”

The significance of the specific Nusselt number on a variety of factor. by Siva Sankari (2827295)

The significance of the specific Nusselt number on a variety of factors. by Siva Sankari (2827295)

The significance of the specific Nusselt number on a variety of factors. by Siva Sankari (2827295)

The significance of the specific Nusselt number on a variety of factors. by Siva Sankari (2827295)

Significant associations in GWAS. by Dai Nogimura (21445649)

Subjects:

BST2 overexpression decreased RSV multiplication. by Katherine Marougka (13015146)

eQTL analysis of significant SNPs. by Dai Nogimura (21445649)

Subjects:

Significant associations in the candidate gene approach. by Dai Nogimura (21445649)

Subjects:

Suggestive significant associations in the candidate gene approach. by Dai Nogimura (21445649)

Subjects:

Juvenile demyelination leads to a decrease in axonal complexity of PFC PV interneurons. by Sara Hijazi (21656615)

Subjects:

In individuals affected by PCA, there is a significant downregulation of genes associated with the cholesterol biosynthetic pathway. by Leemon Nikhila (22250736)

Comparison of questionnaire scores among genotypes for the significant associations. by Dai Nogimura (21445649)

Subjects:

Juvenile demyelination leads to a substantial decrease in potassium currents in PV interneurons of the PFC. by Sara Hijazi (21656615)

Subjects:

HFD decreases intermediate-term memory. by Tong Yue (6033305)

“…<p>(A) The survival rate of 10d <i>Canton-S</i> fed with ND or HFD was observed for 7 days. …”

Data from: Colony losses of stingless bees increase in agricultural areas, but decrease in forested areas by Malena Sibaja Leyton (18400983)

“…</p><p><br></p><p dir="ltr">#METADATA</p><p dir="ltr">#'data.frame': 472 obs. of 28 variables:</p><p dir="ltr"> #$ ID: Factor variable; a unique identity for the response to the survey</p><p dir="ltr"> #$ Year: Factor variable; six factors available (2016, 2017, 2018, 2019, 2020, 2021) representing the year for the response to the survey</p><p dir="ltr"> #$ N_dead_annual: Numeric variable; representing the number of colonies annually lost</p><p dir="ltr">#$ N_alive_annual: Numeric variable; representing the number of colonies annually alive</p><p dir="ltr"> #$ N_dead_dry: Numeric variable; representing the number of colonies lost during the dry season</p><p dir="ltr">#$ N_alive_dry: Numeric variable; representing the number of colonies alive during the dry season</p><p dir="ltr"> #$ N_dead_rainy: Numeric variable; representing the number of colonies lost during the rainy season</p><p dir="ltr">#$ N_alive_rainy: Numeric variable; representing the number of colonies alive during the rainy season</p><p dir="ltr"> #$ Education: Factor variable; four factors are available ("Self-taught","Learned from another melip","Intro training","Formal tech training"), representing the training level in meliponiculture</p><p dir="ltr"> #$ Operation_Size: Numeric variable; representing the number of colonies managed by the participant (in n)</p><p dir="ltr"> #$ propAgri: Numeric variable; representing the percentage of agricultural area surrounding the meliponary (in %)</p><p dir="ltr"> #$ propForest: Numeric variable; representing the percentage of forested area surrounding the meliponary (in %)</p><p dir="ltr">#$ temp.avg_annual: Numeric variable; representing the average annual temperature (in ºC)</p><p dir="ltr">#$ precip_annual_sum: Numeric variable; representing the total accumulated precipitation (in mm)</p><p dir="ltr">#$ precip_Oct_March_sum: Numeric variable; representing the total accumulated precipitation between October to March (in mm)</p><p dir="ltr">#$ precip_Apri_Sept_sum: Numeric variable; representing the total accumulated precipitation between April to September (in mm)</p><p dir="ltr">#$ temp.avg_Oct_March: Numeric variable; representing the total accumulated precipitation between October to March (in ºC)</p><p dir="ltr">#$ temp.avg_Apri_Sept: Numeric variable; representing the total accumulated precipitation between April to September (in ºC)</p><p dir="ltr"> #$ Importance_dead: Factor variable; three factors are available Normal","High","Very high"), representing the perception of the significance of annual colony losses</p><p dir="ltr"> #$ Climatic_environmental: Binary variable; representing if the participant considered climatic and environmental problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr"> #$ Contamination: Binary variable; representing if the participant considered contamination problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr"> #$ Nutritional: Binary variable; representing if the participant considered nutritional problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Sanitary: Binary variable; representing if the participant considered sanitary problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Queen: Binary variable; representing if the participant considered queen problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Time: Binary variable; representing if the participant considered time problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Economic: Binary variable; representing if the participant considered economic problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Attacks: Binary variable; representing if the participant considered time attacks as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Swarming: Binary variable; representing if the participant considered swarming problems as a potential driver (1) or not (0) of their annual colony losses</p><p><br></p>…”

Demonstration of decreased Aβ accumulation by DA-9601 treatment. by Mijung Lee (397790)

Knockdown of MRN complex decreases HBV cccDNA level. by Kaitao Zhao (3617825)

Knockdown of MRN complex decreases HBV cccDNA level. by Kaitao Zhao (3617825)