The presence of stroke is being observed in young adults (under 50 years of age) without cardiovascular risk factors suffering from COVID-19. It is speculated whether there is really a significant increase, as few cases have yet been described, or whether the infection actually favors their development. Cerebrovascular events were more common in older patients with stroke risk factors such as hypertension and diabetes mellitus, and those who had elevated fibrin D-dimers. Multiple cases reports and series about cerebrovascular disease in COVID-19 has been informed. The mechanism that causes cerebral ischemia in COVID-19 remains undiscovered, however, progressively there is increasing evidence of a hypercoagulable state that could be or contribute to the cause of cerebrovascular disease. We review the current literature about cerebrovascular disease, both epidemiology and etiology. More studies are needed to understand COVID-19 neuropathogenesis and the presence of stroke in this patient.
Here, we proposed a six-dimensional semantic framework for outdoor thermal comfort assessments comprising four descriptive - ‘thermal sensation’, ‘humidity’, ‘wind’ and ‘solar radiation,’ plus two affective - ‘thermal pleasure’ and ‘thermal intensity’ dimensions. In Phase 1 an online questionnaire recruited 135 native English-speakers to place 76 climatic adjectives into this six-dimensional semantic space. Phase 2 launched a field study with another 22 subjects locating real-time
outdoor thermal experiences in the same semantic space. They were then asked to select from a subset of the 76 climatic adjectives those that best described their right here- right-now thermal experience. Validation was then performed by comparing coordinates of the 31 most frequently chosen adjectives in Phase 2 with those assigned to them in Phase 1. Good correlations (R2 > 0.65) of adjectives’ coordinates
between the two research phases indicate consistency regarding which adjectives best describe specific scenarios, regardless of seasons, locations, or current exposures.
In this database, we uploaded the average adjectives' scores achieved in the online questionnaire and the Retrieval process of the 10 most likely climatic adjectives to describe the thermal feelings based on the right-here-right-now thermal experience.
The maximum distance at which an electromagnetic (EM) logging while drilling (LWD) tool senses an approaching boundary is considered to be the depth of detection (DOD). Achieving a large DOD while keeping the tool itself compact is what we have always pursued. We proposed a novel transient multicomponent EM LWD method and studied its capability in detecting the formation boundary. Instead of using the transient triaxial measured data directly, a time domain detection mode is defined to sense the boundary. DOD of this time domain EM LWD method can reach tens of meters with a compact transmitter-receiver spacing. Based on the polarity of the signal, directional measurements can also be achieved. In addition, we find that the cross component decays much faster than the coaxial or coplanar components with time in the formation coordinate system. Thus, an algebraic method is proposed to determine the relative dip angle of stratified formation and the inversion process can be avoided. Theoretical simulation results indicate that this determination method obtains the true value at some particular moments. And it is still stable and valid even when considering some random measurement errors. Moreover, linear relationship between the distance to the boundary (DTB) and the time we measure it is established, providing a method to quickly determine the DTB.
Contributors:I Ketut Gede Darma Putra, I Made Suwija Putra, Putu Jhonarendra
The palmprint dataset is captured on left hand. Palmprint dataset is acquired from 15 people with 5 to 8 images of each person. To increase the amount of data in each person, the raw dataset was filtered with Gabor Filter. The characteristics of the Gabor Filter are good applied to palmprint image because the image has many variations of line direction and the thickness. The palmprint dataset has 20 to 32 images each class after applying the Gabor Filter. The author trains the palmprint dataset using the Convolutional Neural Network method.
This a data about the corona virus COVID-19. It contains the actual reported data. Also, it includes the predicted COVID-19 data in the future based on a model developed to predict in the future. The model used will be published in one of the journals later and will be found on my profile with title "Optimistic Prediction Model For the COVID-19 Coronavirus Pandemic based on the Reported Data Analysis".
The daily folder contains the daily data. The predicted folder contains the predicted data for each country. The total cases folder contains the total cases for each country. he section folder contains a latex code for plotting the figures for each country. Also the source file from European Centre for Disease Prevention and Control is included. More updated files available in the website of European Centre for Disease Prevention and Control.