A cooperative deep learning model for fake news detection in online social networks.

Fake news, which considers and modifies facts for virality objectives, causes a lot of havoc on social media. It spreads faster than real news and produces a slew of issues, including disinformation, misunderstanding, and misdirection in the minds of readers. To combat the spread of fake news, detection algorithms are used, which examine news articles through temporal language processing.

Serosurveillance of foot-and-mouth disease in sheep and goat population of India.

Serological investigation to detect foot-and-mouth disease (FMD) virus circulation in the domestic small ruminant population of India was conducted. A total of 4407 and 4035 serum samples from sheep and goats, respectively were collected at random covering majority of the states across the country during 2010-2012. These samples were analyzed for antibodies against the non-structural proteins (NSP) of FMD virus in an indirect 3AB NSP ELISA and against the structural proteins (SP) in a liquid phase blocking (LPB) ELISA.