scholarly journals Long-Term Trends in Intra-Financial Sector Lending in the U.S. 1950 - 2012

2014 ◽  
Author(s):  
Juan Antonio Montecino ◽  
Iren Levina ◽  
Gerald Epstein
Keyword(s):  
Financial Sector ◽  
Long Term Trends ◽  
The U.S

Long-Term Trends in Intra-Financial Sector Lending in the United States (1950–2012)

2016 ◽  
Vol 42 (4) ◽  
pp. 611-629 ◽  
Author(s):  
Juan Antonio Montecino ◽  
Gerald Epstein ◽  
Iren Levina
Keyword(s):  
United States ◽  
Financial Sector ◽  
The United States ◽  
Long Term Trends

scholarly journals Long-Term Trends in Downwelling Spectral Infrared Radiance over the U.S. Southern Great Plains

2011 ◽  
Vol 24 (18) ◽  
pp. 4831-4843 ◽  
Author(s):  
P. Jonathan Gero ◽  
David D. Turner
Keyword(s):  
Great Plains ◽  
Climate Models ◽  
Southern Great Plains ◽  
Infrared Radiance ◽  
Term Change ◽  
Atmospheric Radiation Measurement ◽  
Long Term Trends ◽  
Thin Cloud ◽  
The U.S

Abstract A trend analysis was applied to a 14-yr time series of downwelling spectral infrared radiance observations from the Atmospheric Emitted Radiance Interferometer (AERI) located at the Atmospheric Radiation Measurement Program (ARM) site in the U.S. Southern Great Plains. The highly accurate calibration of the AERI instrument, performed every 10 min, ensures that any statistically significant trend in the observed data over this time can be attributed to changes in the atmospheric properties and composition, and not to changes in the sensitivity or responsivity of the instrument. The measured infrared spectra, numbering more than 800 000, were classified as clear-sky, thin cloud, and thick cloud scenes using a neural network method. The AERI data record demonstrates that the downwelling infrared radiance is decreasing over this 14-yr period in the winter, summer, and autumn seasons but it is increasing in the spring; these trends are statistically significant and are primarily due to long-term change in the cloudiness above the site. The AERI data also show many statistically significant trends on annual, seasonal, and diurnal time scales, with different trend signatures identified in the separate scene classifications. Given the decadal time span of the dataset, effects from natural variability should be considered in drawing broader conclusions. Nevertheless, this dataset has high value owing to the ability to infer possible mechanisms for any trends from the observations themselves and to test the performance of climate models.

Long-term Trends in Antidiabetes Drug Usage in the U.S.: Real-world Evidence in Patients Newly Diagnosed With Type 2 Diabetes

Diabetes Care ◽  
2017 ◽  
Vol 41 (1) ◽  
pp. 69-78 ◽  
Author(s):  
Olga Montvida ◽  
Jonathan Shaw ◽  
John J. Atherton ◽  
Frances Stringer ◽  
Sanjoy K. Paul
Keyword(s):  
Type 2 Diabetes ◽  
Real World ◽  
Newly Diagnosed ◽  
Drug Usage ◽  
Real World Evidence ◽  
Long Term Trends ◽  
The U.S

Long-term trends in precipitation and precipitation extremes and underlying mechanisms in the U.S. Great Basin during 1951-2013

2017 ◽  
Vol 122 (12) ◽  
pp. 6152-6169 ◽  
Author(s):  
Tingting Xue ◽  
Guoping Tang ◽  
Lin Sun ◽  
Yuzhen Wu ◽  
Yonglin Liu ◽  
...  
Keyword(s):  
Great Basin ◽  
Precipitation Extremes ◽  
Long Term Trends ◽  
Underlying Mechanisms ◽  
The U.S
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