Variable importance of a partial least squares model for winter wheat yield prediction. by Keach Murakami (11576825)

Performance of machine learning models for winter wheat yield forecast. by Keach Murakami (11576825)

Osteoporosis screening among study participants. by Surakshya Khanal (19949745)

“…Frequencies, percentages, mean, and standard deviation were used to describe the characteristics of participants. …”

S1 Data - by Surakshya Khanal (19949745)

“…Frequencies, percentages, mean, and standard deviation were used to describe the characteristics of participants. …”

Practices towards the prevention of osteoporosis. by Surakshya Khanal (19949745)

“…Frequencies, percentages, mean, and standard deviation were used to describe the characteristics of participants. …”

Source of healthcare information. by Surakshya Khanal (19949745)

“…Frequencies, percentages, mean, and standard deviation were used to describe the characteristics of participants. …”

Individual characteristics of the participants. by Surakshya Khanal (19949745)

“…Frequencies, percentages, mean, and standard deviation were used to describe the characteristics of participants. …”

Tax-expressing cells form cell clumps. by Saumya Ramanayake (7879091)

Longer-term consequences of Tax expression on the host cell. by Saumya Ramanayake (7879091)

Results of the LMM analysis for IOP change. by Sayaka Kimura-Uchida (22793666)

“…The mean GMS was 2.46 ± 1.33 preoperatively, and decreased to 1.32 ± 1.31 at 3 months, and 1.60 ± 1.41 at 12 months postoperatively. …”

Results of the LMM analysis for GMS change. by Sayaka Kimura-Uchida (22793666)

“…The mean GMS was 2.46 ± 1.33 preoperatively, and decreased to 1.32 ± 1.31 at 3 months, and 1.60 ± 1.41 at 12 months postoperatively. …”

Surgical changes through ISIW implantation. by Sayaka Kimura-Uchida (22793666)

LM test of spatial panel model. by Li-Min Wang (783263)

“…We also analyzed the spatial distribution of ozone driving factors using the GTWR. The results show that: i) The average annual increase of ozone concentration in ambient air in China from 2015 to 2019 was 1.68<i>μg/m</i>^<i>3</i>, and 8.39<i>μg/m</i>^<i>3</i> elevated the year 2019 compared with 2015. ii) The Moran’s I value of ozone in ambient air was 0.027 in 2015 and 0.209 in 2019, showing the spatial distribution characteristics of "east heavy and west light" and "south low and north high". iii) Per capita GDP industrial structure, population density, land expansion, and urbanization rate have significant spillover effects on ozone concentration, and the regional spillover effect is greater than the local effect. …”

Descriptive statistics (2015–2019). by Li-Min Wang (783263)

“…We also analyzed the spatial distribution of ozone driving factors using the GTWR. The results show that: i) The average annual increase of ozone concentration in ambient air in China from 2015 to 2019 was 1.68<i>μg/m</i>^<i>3</i>, and 8.39<i>μg/m</i>^<i>3</i> elevated the year 2019 compared with 2015. ii) The Moran’s I value of ozone in ambient air was 0.027 in 2015 and 0.209 in 2019, showing the spatial distribution characteristics of "east heavy and west light" and "south low and north high". iii) Per capita GDP industrial structure, population density, land expansion, and urbanization rate have significant spillover effects on ozone concentration, and the regional spillover effect is greater than the local effect. …”

Spatial error model under nested matrix. by Li-Min Wang (783263)

“…We also analyzed the spatial distribution of ozone driving factors using the GTWR. The results show that: i) The average annual increase of ozone concentration in ambient air in China from 2015 to 2019 was 1.68<i>μg/m</i>^<i>3</i>, and 8.39<i>μg/m</i>^<i>3</i> elevated the year 2019 compared with 2015. ii) The Moran’s I value of ozone in ambient air was 0.027 in 2015 and 0.209 in 2019, showing the spatial distribution characteristics of "east heavy and west light" and "south low and north high". iii) Per capita GDP industrial structure, population density, land expansion, and urbanization rate have significant spillover effects on ozone concentration, and the regional spillover effect is greater than the local effect. …”

S1 Data - by Li-Min Wang (783263)

“…We also analyzed the spatial distribution of ozone driving factors using the GTWR. The results show that: i) The average annual increase of ozone concentration in ambient air in China from 2015 to 2019 was 1.68<i>μg/m</i>^<i>3</i>, and 8.39<i>μg/m</i>^<i>3</i> elevated the year 2019 compared with 2015. ii) The Moran’s I value of ozone in ambient air was 0.027 in 2015 and 0.209 in 2019, showing the spatial distribution characteristics of "east heavy and west light" and "south low and north high". iii) Per capita GDP industrial structure, population density, land expansion, and urbanization rate have significant spillover effects on ozone concentration, and the regional spillover effect is greater than the local effect. …”

Flow chart of urbanization ozone pollution. by Li-Min Wang (783263)

“…We also analyzed the spatial distribution of ozone driving factors using the GTWR. The results show that: i) The average annual increase of ozone concentration in ambient air in China from 2015 to 2019 was 1.68<i>μg/m</i>^<i>3</i>, and 8.39<i>μg/m</i>^<i>3</i> elevated the year 2019 compared with 2015. ii) The Moran’s I value of ozone in ambient air was 0.027 in 2015 and 0.209 in 2019, showing the spatial distribution characteristics of "east heavy and west light" and "south low and north high". iii) Per capita GDP industrial structure, population density, land expansion, and urbanization rate have significant spillover effects on ozone concentration, and the regional spillover effect is greater than the local effect. …”

Map of study area. by Erin Conlisk (163376)

Statins resulted in smaller neuronal soma size. by Shuk C. Tsoi (21192243)

S1 File - by Nicolas M. Philipp (13272198)

“…Further, despite the implementation of the fatiguing RSA protocol, over the course of the three time-points, participants seemed to perform the two jump tasks more efficiently, seen through significantly lower contraction times, greater eccentric (ECC) peak power, and greater ECC mean deceleration force within the CMJ following the RSA task. …”