Overall functional adaptation of porcine ASC and BMSC during adipogenic and osteogenic differentiation. by Massimo Bionaz (177852)

“…The analysis suggested that ASC during adipogenic differentiation (panel A) had a large transcriptomics change (<b>↰ (red arrow)</b> genes whose transcription was increased; <b>↰ (green arrow)</b> genes whose transcription was decreased; larger the size larger the number) with a more pronounce number of down-regulated compared to up-regulated genes. …”

Dataset for: Vascular narrowing in pulmonary arterial hypertension is heterogeneous: rethinking resistance by Nina Rol (3929081)

“…Conclusions - Narrowing of resistance vessels is heterogeneous: not all vessels are narrowed, and the decrease in internal diameters, even within a single order, vary largely. …”

Decoder inferred using the extensive information model. by Kaushik J. Lakshminarasimhan (5782289)

“…<p><b>(A)</b> Decoding weights were inferred in the subspace of 2 leading principal components of noise covariance (solid circles). …”

Baseline characteristics for pneumonia. by Mathias Aagaard Christensen (19139443)

“…</p><p>Results</p><p>Models were generated for atrial fibrillation, venous thromboembolism and pneumonia as genetics only, clinical features only and a combined model. For venous thromboembolism, the ROC-AUCs were 60.1% [59.6%-60.4%], 63.4% [63.2%-63.4%] and 66.6% [66.2%-66.9%] for the linear models and 51.5% [49.4%-53.4%], 63.2% [61.2%-65.0%] and 62.6% [60.7%-64.5%] for the deep learning SNP, clinical and combined models, respectively. …”

Late effects of total body irradiation on hematopoietic recovery and immune function in rhesus macaques by Laura P. Hale (148029)

“…This study investigated hematopoietic recovery and immune function in rhesus macaques Cross-sectionally (at a single time point) 2 to 5 years after exposure to a single large dose (6.5 to 8.4 Gray) of total body radiation (TBI) derived from linear accelerator-derived photons (2 MeV, 80 cGy/minute) or Cobalt 60-derived gamma irradiation (60 cGy/min). …”

Image_13_Assessing the Sensitivity of Global Maize Price to Regional Productions Using Statistical and Machine Learning Methods.tif by Rotem Zelingher (10909332)

“…More specifically, our models reveal that a yearly yield gain of +8% in Northern America negatively impacts the global maize price by about –7%, while a decrease of –0.1% is expected to increase global maize price by more than +7%. …”

Image_11_Assessing the Sensitivity of Global Maize Price to Regional Productions Using Statistical and Machine Learning Methods.tif by Rotem Zelingher (10909332)

“…More specifically, our models reveal that a yearly yield gain of +8% in Northern America negatively impacts the global maize price by about –7%, while a decrease of –0.1% is expected to increase global maize price by more than +7%. …”

Image_1_Assessing the Sensitivity of Global Maize Price to Regional Productions Using Statistical and Machine Learning Methods.tif by Rotem Zelingher (10909332)

“…More specifically, our models reveal that a yearly yield gain of +8% in Northern America negatively impacts the global maize price by about –7%, while a decrease of –0.1% is expected to increase global maize price by more than +7%. …”

Image_1_Assessing the Sensitivity of Global Maize Price to Regional Productions Using Statistical and Machine Learning Methods.tif by Rotem Zelingher (10909332)

“…More specifically, our models reveal that a yearly yield gain of +8% in Northern America negatively impacts the global maize price by about –7%, while a decrease of –0.1% is expected to increase global maize price by more than +7%. …”

Image_15_Assessing the Sensitivity of Global Maize Price to Regional Productions Using Statistical and Machine Learning Methods.tif by Rotem Zelingher (10909332)

“…More specifically, our models reveal that a yearly yield gain of +8% in Northern America negatively impacts the global maize price by about –7%, while a decrease of –0.1% is expected to increase global maize price by more than +7%. …”

Image_6_Assessing the Sensitivity of Global Maize Price to Regional Productions Using Statistical and Machine Learning Methods.tif by Rotem Zelingher (10909332)

“…More specifically, our models reveal that a yearly yield gain of +8% in Northern America negatively impacts the global maize price by about –7%, while a decrease of –0.1% is expected to increase global maize price by more than +7%. …”

Image_10_Assessing the Sensitivity of Global Maize Price to Regional Productions Using Statistical and Machine Learning Methods.tif by Rotem Zelingher (10909332)

“…More specifically, our models reveal that a yearly yield gain of +8% in Northern America negatively impacts the global maize price by about –7%, while a decrease of –0.1% is expected to increase global maize price by more than +7%. …”

Image_8_Assessing the Sensitivity of Global Maize Price to Regional Productions Using Statistical and Machine Learning Methods.tif by Rotem Zelingher (10909332)

“…More specifically, our models reveal that a yearly yield gain of +8% in Northern America negatively impacts the global maize price by about –7%, while a decrease of –0.1% is expected to increase global maize price by more than +7%. …”

Image_4_Assessing the Sensitivity of Global Maize Price to Regional Productions Using Statistical and Machine Learning Methods.tif by Rotem Zelingher (10909332)

“…More specifically, our models reveal that a yearly yield gain of +8% in Northern America negatively impacts the global maize price by about –7%, while a decrease of –0.1% is expected to increase global maize price by more than +7%. …”

Image_10_Assessing the Sensitivity of Global Maize Price to Regional Productions Using Statistical and Machine Learning Methods.tif by Rotem Zelingher (10909332)

“…More specifically, our models reveal that a yearly yield gain of +8% in Northern America negatively impacts the global maize price by about –7%, while a decrease of –0.1% is expected to increase global maize price by more than +7%. …”

Data_Sheet_1_Assessing the Sensitivity of Global Maize Price to Regional Productions Using Statistical and Machine Learning Methods.PDF by Rotem Zelingher (10909332)

“…More specifically, our models reveal that a yearly yield gain of +8% in Northern America negatively impacts the global maize price by about –7%, while a decrease of –0.1% is expected to increase global maize price by more than +7%. …”

Image_6_Assessing the Sensitivity of Global Maize Price to Regional Productions Using Statistical and Machine Learning Methods.tif by Rotem Zelingher (10909332)

“…More specifically, our models reveal that a yearly yield gain of +8% in Northern America negatively impacts the global maize price by about –7%, while a decrease of –0.1% is expected to increase global maize price by more than +7%. …”

Image_5_Assessing the Sensitivity of Global Maize Price to Regional Productions Using Statistical and Machine Learning Methods.tif by Rotem Zelingher (10909332)

“…More specifically, our models reveal that a yearly yield gain of +8% in Northern America negatively impacts the global maize price by about –7%, while a decrease of –0.1% is expected to increase global maize price by more than +7%. …”

Image_12_Assessing the Sensitivity of Global Maize Price to Regional Productions Using Statistical and Machine Learning Methods.tif by Rotem Zelingher (10909332)

“…More specifically, our models reveal that a yearly yield gain of +8% in Northern America negatively impacts the global maize price by about –7%, while a decrease of –0.1% is expected to increase global maize price by more than +7%. …”

Image_8_Assessing the Sensitivity of Global Maize Price to Regional Productions Using Statistical and Machine Learning Methods.tif by Rotem Zelingher (10909332)

“…More specifically, our models reveal that a yearly yield gain of +8% in Northern America negatively impacts the global maize price by about –7%, while a decrease of –0.1% is expected to increase global maize price by more than +7%. …”