What is common between the censorship of the film Padmaavat and artificially high 'minimum' support prices for crops? If the police comes down so heavily on peaceful anti-CAA protestors, why did it not show the same harshness towards those violating the COVID-19 lockdown? Why is an otherwise powerful Election Commission unable to enforce free and fair elections within political parties or fully weed out criminals from politics? The common factor is faulty institutional design, which is eating away at the foundations of our society. Leaders come and go, but institutions stay forever. Only a consistent focus on better institutions can help India have a more robust economy, media, police, parliament, internet and cultural life. Yet, discussions on institutions have been restricted to academic circles. Keeping aside ideological biases of Left or Right, Caged Tiger brings alive the rich yet unseen story of India's institutions. It combines deep research and complex frameworks, converting them into the vocabulary and cultural context of millennials and Gen Z. It goes all the way back to the British Raj, exploring the origins of modern Indian institutions. Tracing additions by subsequent governments, from Nehru's to Modi's, it identifies policies that keep Indians suppressed and how each of us can change them. It is, in short, young India's guide to becoming smarter about the issues that matter.
This book focuses on an eminent technology called next generation sequencing (NGS) which has entirely changed the procedure of examining organisms and will have a great impact on biomedical research and disease diagnosis. Numerous computational challenges have been brought on by the rapid advancement of large-scale next-generation sequencing (NGS) technologies and their application. The term ""biomedical imaging"" refers to the use of a variety of imaging techniques (such as X-rays, CT scans, MRIs, ultrasounds, etc.) to get images of the interior organs of a human being for potential diagnostic, treatment planning, follow-up, and surgical purposes. In these circumstances, deep learning, a new learning method that uses multi-layered artificial neural networks (ANNs) for unsupervised, supervised, and semi-supervised learning, has attracted a lot of interest for applications to NGS and imaging, even when both of these data are used for the same group of patients. The three main research phenomena in biomedical research are disease classification, feature dimension reduction, and heterogeneity. AI approaches are used by clinical researchers to efficiently analyse extremely complicated biomedical datasets (e.g., multi-omic datasets. With the use of NGS data and biomedical imaging of various human organs, researchers may predict diseases using a variety of deep learning models. Unparalleled prospects to improve the work of radiologists, clinicians, and biomedical researchers, speed up disease detection and diagnosis, reduce treatment costs, and improve public health are presented by using deep learning models in disease prediction using NGS and biomedical imaging. This book influences a variety of critical disease data and medical images.
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