Shares of antibiotic substances on total prescription by quarter from 2013 to 2019 for female and male patients with UTI (N39.0, N30.0)(female: n = 1.681.255 prescriptions; male: n... by Thomas Hanslmeier (19949694)

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Tissue, days post-infection (dpi) and the top 10 most significant genes with increased and decreased expression with valid gene symbols for the response contrasts. by Gillian P. McHugo (8965919)

Candidates from the RF method. The top 25 random forest candidates ranked by mean decrease in accuracy and mean decrease in Gini Index are in the first and second columns, respecti... by Zoë Parker Cates (22184243)

Shares of antibiotic substances on total prescription in UTI treatment (N39.0, N30.0) by sex and age group in 2019 (female: n = 238.670 prescriptions; male: n = 40.641 prescription... by Thomas Hanslmeier (19949694)

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Shares of specialist groups prescribing 1^st, 2^nd, and 3^rd antibiotic prescriptions in UTI treatment of females (N39.0, N30.0) in 2018 and 2019. by Thomas Hanslmeier (19949694)

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Number of antibiotic prescriptions in female and male patients with UTI (N30.0 and/or N39.0). by Thomas Hanslmeier (19949694)

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Shares of antibiotic substances on total prescription in female patients with UTI (N39.0, N30.0) by physician specialties (GPs: n = 1.299.641 prescriptions; gynecologists n = 141.8... by Thomas Hanslmeier (19949694)

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Comparison of 1^st, 2^nd, and 3^rd antibiotic prescription. by Thomas Hanslmeier (19949694)

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UTI diagnoses by sex and physician specialty (2013–2019). by Thomas Hanslmeier (19949694)

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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)

Evolution from a single 20-year model simulation of a 5-year cycling strategy with DHA-PPQ used in the first five years, ASAQ in the following five years, AL during years 10-15, an... by Kien Trung Tran (12035464)

Innovation, nightlights and a continuous measure of city size. by Saul Estrin (8629173)

Selection frequencies plotted in decreasing order. by Hannah P. Rowe (7830599)

Trust change by gender. by Alain Abi-Rizk (8549358)

“…Results indicate that respondnatds from North America and Europe Experienced an increase in trust where as Africa and South America Witnessed a decline in trust. Males exhibited a greater decline in trust than females (p = 0.038), and undergraduate degree holders showed the largest decrease (p = 0.001). …”

Trust change by age group. by Alain Abi-Rizk (8549358)

“…Results indicate that respondnatds from North America and Europe Experienced an increase in trust where as Africa and South America Witnessed a decline in trust. Males exhibited a greater decline in trust than females (p = 0.038), and undergraduate degree holders showed the largest decrease (p = 0.001). …”

Trust change by education level. by Alain Abi-Rizk (8549358)

“…Results indicate that respondnatds from North America and Europe Experienced an increase in trust where as Africa and South America Witnessed a decline in trust. Males exhibited a greater decline in trust than females (p = 0.038), and undergraduate degree holders showed the largest decrease (p = 0.001). …”

Trust change by source of science information. by Alain Abi-Rizk (8549358)

“…Results indicate that respondnatds from North America and Europe Experienced an increase in trust where as Africa and South America Witnessed a decline in trust. Males exhibited a greater decline in trust than females (p = 0.038), and undergraduate degree holders showed the largest decrease (p = 0.001). …”

Trust levels before and after the COVID-19 pandemic (n = 10,000). by Alain Abi-Rizk (8549358)

Distribution of individual change in trust in science before and after the pandemic (n = 10,000). by Alain Abi-Rizk (8549358)

Lifespan of a single <i>T. utriculata</i> rosette. by Alexandra M. Campbell (3284094)