Theme 6 results—socio-economics. by Corey J. A. Bradshaw (8032406)

Data_Sheet_1_Improvements in mental health associated with increased electronic communication and deterioration in physical health in adults aged 50+ during the COVID-19 pandemic.D... by Shay Musbat (18861388)

“…</p>Objective<p>This longitudinal study aims to provide a quantitative analysis of the COVID-19 impact on the physical, mental, and social parameters in adults aged 50 and older before, in the early stages, and during the COVID-19 pandemic.…”

Comparison of molecular and metabolic changes caused by 24 hours treatment of SF188 pediatric glioblastoma cells with PI-103 or TMZ at 2×GI₅₀. by Nada M. S. Al-Saffar (454143)

Table 1_Microglial adenosine A2A receptor in the paraventricular thalamic nucleus regulates pain sensation and analgesic effects independent of opioid and cannabinoid receptors.doc... by Yiping Cao (1229856)

“…Pharmacological activation of local PVT A_2AR with its agonist CGS21680 induced significantly decreased 50% paw withdrawal threshold (50%PWTs) and paw withdrawal latency (PWLs), as measured by the Von Frey test and Hargreaves test in adult mice. …”

Image 1_Microglial adenosine A2A receptor in the paraventricular thalamic nucleus regulates pain sensation and analgesic effects independent of opioid and cannabinoid receptors.tif by Yiping Cao (1229856)

“…Pharmacological activation of local PVT A_2AR with its agonist CGS21680 induced significantly decreased 50% paw withdrawal threshold (50%PWTs) and paw withdrawal latency (PWLs), as measured by the Von Frey test and Hargreaves test in adult mice. …”

Image 2_Microglial adenosine A2A receptor in the paraventricular thalamic nucleus regulates pain sensation and analgesic effects independent of opioid and cannabinoid receptors.tif by Yiping Cao (1229856)

“…Pharmacological activation of local PVT A_2AR with its agonist CGS21680 induced significantly decreased 50% paw withdrawal threshold (50%PWTs) and paw withdrawal latency (PWLs), as measured by the Von Frey test and Hargreaves test in adult mice. …”

Image_5_Appetitively motivated tasks in the IntelliCage reveal a higher motivational cost of spatial learning in male than female mice.TIFF by Martina Nigri (12104966)

β-diversity patterns are revealed with increasing sequencing depths between communities that differ only by random processes. by Ryoko Oono (4691824)

LSTM model structure. by Yeongha Kim (12174924)

“…We compare the prediction error of the existing and proposed models with the COVID-19 prediction results reported from five US states: California, Texas, Florida, New York, and Illinois. …”

Proposed model architecture. by Yeongha Kim (12174924)

“…We compare the prediction error of the existing and proposed models with the COVID-19 prediction results reported from five US states: California, Texas, Florida, New York, and Illinois. …”

Week 3 prediction using Seq2Seq model. by Yeongha Kim (12174924)

“…We compare the prediction error of the existing and proposed models with the COVID-19 prediction results reported from five US states: California, Texas, Florida, New York, and Illinois. …”

Week 1 prediction using Seq2Seq model. by Yeongha Kim (12174924)

“…We compare the prediction error of the existing and proposed models with the COVID-19 prediction results reported from five US states: California, Texas, Florida, New York, and Illinois. …”

Compare related work with our research. by Yeongha Kim (12174924)

“…We compare the prediction error of the existing and proposed models with the COVID-19 prediction results reported from five US states: California, Texas, Florida, New York, and Illinois. …”

Week 3 prediction using LSTM model. by Yeongha Kim (12174924)

“…We compare the prediction error of the existing and proposed models with the COVID-19 prediction results reported from five US states: California, Texas, Florida, New York, and Illinois. …”

Seq2Seq model structure. by Yeongha Kim (12174924)

“…We compare the prediction error of the existing and proposed models with the COVID-19 prediction results reported from five US states: California, Texas, Florida, New York, and Illinois. …”

Week 2 prediction using Seq2Seq model. by Yeongha Kim (12174924)

“…We compare the prediction error of the existing and proposed models with the COVID-19 prediction results reported from five US states: California, Texas, Florida, New York, and Illinois. …”

Week 1 prediction using LSTM model. by Yeongha Kim (12174924)

“…We compare the prediction error of the existing and proposed models with the COVID-19 prediction results reported from five US states: California, Texas, Florida, New York, and Illinois. …”

Week 2 prediction using LSTM model. by Yeongha Kim (12174924)

“…We compare the prediction error of the existing and proposed models with the COVID-19 prediction results reported from five US states: California, Texas, Florida, New York, and Illinois. …”

Google trends keywords used to train the model. by Yeongha Kim (12174924)

“…We compare the prediction error of the existing and proposed models with the COVID-19 prediction results reported from five US states: California, Texas, Florida, New York, and Illinois. …”

Seq2Seq model structure. by Yeongha Kim (12174924)

“…We compare the prediction error of the existing and proposed models with the COVID-19 prediction results reported from five US states: California, Texas, Florida, New York, and Illinois. …”