Information of GaoFen data selected. by Ziheng Song (14380161)

“…The Open-pit mining affected areas showed the largest decline, reaching 68.3%. The <i>FVC</i> in the underground mining areas had a downward trend, but self-healing effect after mining was also observed. (2) The overall <i>FVC</i> in the study area was positively correlated with the number of precipitation days. (3) There were differences in the sensitivity to mining disturbance for different landform in the underground mining areas. (4) Although the <i>FVC</i> in the Old mining areas had recovered to the level of Natural growth control area, but the annual fluctuation was larger, which might mean lower ecological stability.…”

S1 Data - by Jordan K. Abbott (8934239)

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Nightlight densities in the lowest, around the median and the highest ranked cities in the sample and the distribution of firms in each city. by Saul Estrin (8629173)

Median time to viral suppression among persons with post-ART viral load tests in Jamaica by ARV initiation year, sex and treatment site, 2017–2019 (N = 2049). by Anya Cushnie (11269155)

<i>FVC</i> variation based on Landsat and GaoFen satellites. by Ziheng Song (14380161)

DataSheet_1_Albinism in the largest extant amphibian: A metabolic, endocrine, or immune problem?.pdf by Liming Chang (2847938)

“…Albino individuals exhibited shifted transcription of MHC I isotypes, and the albino-specific isotype was characterized by increased charges and decreased space in the antigen- binding pocket, implying a drastic change in antigen specificity and a potential risk of autoimmune disorders.…”

Blocking the MAPK pathway with UO126 decreases jagged expression and migratory ability. by Megan K. Fentress (17304814)

The model develops larger place fields with shallower phase precession in areas of higher running speed. by Eloy Parra-Barrero (15461005)

GI-1d-a: Comparison of estimates of people for dataset A (left bar) and B (right bar) per region. The largest discrepancies occur in areas of NE, SE and SW Germany and adjacent reg... by Isabell Schmidt (6331013)

Population changes of <i>M</i>. <i>bavaricum</i> (a) and cocci (b) in Earth’s field (red symbols), zero field (black symbols) and alternating field (blue symbols) as a function of... by Xuegang Mao (599968)

Hospital admission rate for chronic non-communicable diseases (NCDs) in Brazil according to the type of NCD. by Rafael Alves Guimarães (4526788)

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Hospital admissions for chronic non-communicable diseases (NCDs) in Brazil before and after the onset of the coronavirus disease pandemic according to the type of NCD and age group... by Rafael Alves Guimarães (4526788)

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Poisson multiple regression models of the impact of the coronavirus disease pandemic on the hospitalization rate for diabetes mellitus in Brazil according to subgroups by age group... by Rafael Alves Guimarães (4526788)

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Hospital admissions for chronic non-communicable diseases (NCDs) in Brazil before and after the onset of the coronavirus disease pandemic according to the type of NCD and region of... by Rafael Alves Guimarães (4526788)

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Hospital admissions for chronic non-communicable diseases (NCDs) in Brazil before and after the onset of the coronavirus disease pandemic according to the type of NCD. by Rafael Alves Guimarães (4526788)

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Poisson multiple regression models of the impact of the coronavirus disease pandemic on the hospitalization rate for cardiovascular disease in Brazil according to subgroups by age... by Rafael Alves Guimarães (4526788)

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Hospital admissions for chronic non-communicable diseases (NCDs) in Brazil before and after the onset of the coronavirus disease pandemic according to the type of NCD and sex. by Rafael Alves Guimarães (4526788)

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Fig 4 - by Rafael Alves Guimarães (4526788)

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Poisson multiple regression models of the impact of the coronavirus disease pandemic on hospital admissions for chronic non-communicable diseases (NCDs) in Brazil according to the... by Rafael Alves Guimarães (4526788)

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Poisson multiple regression models of the impact of the coronavirus disease pandemic on the hospitalization rate for cancer in Brazil according to subgroups by age group, sex, and... by Rafael Alves Guimarães (4526788)

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