INTRODUCTION LITRATURE REVIEW The study of the dispersion of airborne biological materials as pollen, spores, micro- organisms or viruses. Aerobiology is branch of biology that studies organic particles, such as bacteria, fungal spores, very small insect, pollen grains and viruses, which are passively transported by the air(Spieksma, 1991) Aerobiology have traditionally been involved in the measurement and reporting of airborne pollen and fungal spores as a service to allergy sufferers(Larsson, 1993). In 2002 algae and other small water borne organisms were discovered to inhibit clouds. A large cloud has about as much water as a shallow lake of the same geographic size. Aerobiology is rapidly developing science which also involves interactions with engineering and meteorology.
South Asia today is among the most unstable regions in the world, riddled by both intra- and inter-state conflict. This book presents a comprehensive technical analysis of the trade–conflict relationship within the region, and explores how South Asia demonstrates underperformance of its potential for economic integration. Using the gravity model framework, the book highlights quantitative estimates of the cost of conflict in terms of loss of trade for South Asia. Other variables representative of political and economic regimes are also included to make the model comprehensive, and the book goes on to discuss how the analysis reveals the overriding significance of the India–Pakistan relationship in the regional landscape. It looks at how the results of the econometric exercise reveal the extent to which a common border, when disputed, becomes a barrier rather than a facilitator to trade and, additionally, the extent to which long standing and persistent conflict can debilitate trade relationships. The book is a useful contribution for students and scholars of South Asian studies and international political economy, and assists in formulating policy to correct the anti-home bias that is evident in trade patterns of the South Asian economies.
On a hot April morning in 1673, two young Mughal nobles, Shamsher and his sister Zeenat, leave Shahjahanabad for a trip down the royal highway to the market town of Narnaul. The reluctant Shamsher is on a secret mission for his father; an excited Zeenat on one of her own. Their journey takes them through the shattered landscape of a recently crushed uprising – one different from those the Mughal Empire frequently spawned, of petty warlords fired by dreams of kingship. This revolt was rumoured to have been inspired by Kabir and led by a witch; her militant followers, many of them women and all of them rabble, called themselves ‘Followers of Truth’. The rebels were defeated, but the questions remained: Where had they come from and what did they want? Had Kabir, the revered saint–poet of Banaras, really incited violence? Why couldn’t the inclusiveness fostered by Emperor Akbar hold the realm together? What role did the firangis have to play? Or was it all simply because of the bigot on the throne? Set twelve years into the rule of the austere Aurangzeb Alamgir, in a time of impossible wealth and unbearable want, of brilliant architectural extravaganzas amidst ancient traditions of squalor, and of a caste society on the threshold of capitalism, Amita Kanekar’s powerful and intricately woven novel tells the story of an unlikely rebellion that almost brought imperial Dilli to its knees.
The Present Book, Concise Encyclopaedia Of India, Is A Compendium Of Diverse Aspects Of India Which Is One Of The Oldest Civilisations With A Kaleidoscopic Variety, Rich Cultural Heritage And Multifaceted Socio-Economic Progress. The Idea Behind Bringing Out This Book Is To Help One And All In Understanding The Country And Its Unity In Diversity. In Its Three Volumes, The Encyclopaedia Encompasses A Remarkably Wide Range Of Topics Related To India Its History, Physiography, People, Population, National Symbols, National Leaders, Languages And Literatures, Art, Culture, Defence, Education, Economy, Polity, Foreign Policy And Relations, Scientific And Technological Developments, Law And Justice, Sports, Festivals, Transport, Communication And Related Activities. In Addition, A Profile Of All Its 28 States And 7 Union Territories Has Also Been Provided. Furthermore, It Provides An Accessible, Authoritative Account Of The Latest Developments Made In Varied Fields Alongwith The Data From The Central And State Governments, Their Establishments, Constitutional Bodies, Autonomous And Semi-Autonomous Bodies And The Like.The Book Is Comprehensive, Self-Contained And User-Friendly, As The Emphasis Throughout Is On Ensuring That Readers, Particularly Students, Receive Worthwhile, Authentic Information Instead Of Irrelevant And Outdated Details. It Will Definitely Prove An Invaluable Reference Book To Students Of Different Educational Levels And Candidates Preparing For Civil Services Examinations Or Other Competitive Exams And Interviews For Various Jobs. Besides Students, The Researchers, Executives In Government And Private Sector And Also The Common Man Will Find It Highly Informative.
This book describes in detail various aspects of fluoride toxicity in animals. Animals, like human beings, suffer from the toxic effects of excess fluoride intake. They show pathological changes in their teeth and bone, together with a marked reduction in appetite, productive and reproductive potentials, which can result in severe economic losses in the dairy industry. Laboratory and wild animals also suffer from this ailment. Animal suffering and economic losses alike can be minimized through early diagnosis of the problem and by adopting suitable preventive and therapeutic measures. The book details the susceptibility of different animal species, important sources of toxicity, clinical signs and symptoms, pathophysiology, diagnostic methods, preventive and therapeutic approaches. It offers a valuable resource for scientists working in the fields of toxicology, veterinary science, animal nutrition, and environmental science, as well as for public health workers, animal welfare activists, public health veterinarians, field veterinarians, medical professionals and all others interested in the subject.
Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key FeaturesIntroduces and then uses TensorFlow 2 and Keras right from the startTeaches key machine and deep learning techniquesUnderstand the fundamentals of deep learning and machine learning through clear explanations and extensive code samplesBook Description Deep Learning with TensorFlow 2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside TensorFlow (TF) and Keras. You’ll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow is the machine learning library of choice for professional applications, while Keras offers a simple and powerful Python API for accessing TensorFlow. TensorFlow 2 provides full Keras integration, making advanced machine learning easier and more convenient than ever before. This book also introduces neural networks with TensorFlow, runs through the main applications (regression, ConvNets (CNNs), GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML. What you will learnBuild machine learning and deep learning systems with TensorFlow 2 and the Keras APIUse Regression analysis, the most popular approach to machine learningUnderstand ConvNets (convolutional neural networks) and how they are essential for deep learning systems such as image classifiersUse GANs (generative adversarial networks) to create new data that fits with existing patternsDiscover RNNs (recurrent neural networks) that can process sequences of input intelligently, using one part of a sequence to correctly interpret anotherApply deep learning to natural human language and interpret natural language texts to produce an appropriate responseTrain your models on the cloud and put TF to work in real environmentsExplore how Google tools can automate simple ML workflows without the need for complex modelingWho this book is for This book is for Python developers and data scientists who want to build machine learning and deep learning systems with TensorFlow. This book gives you the theory and practice required to use Keras, TensorFlow 2, and AutoML to build machine learning systems. Some knowledge of machine learning is expected.
Most people view cultural heritage sites as static places, frozen in time. In Cultural Landscapes in India, Amita Sinha subverts the idea of heritage as static and examines the ways that landscapes influence culture and that culture influences landscapes. The book centers around imagining, enacting, and reclaiming landscapes as subjects and settings of living cultural heritage. Drawing on case studies from different regions of India, Sinha offers new interpretations of links between land and culture using different ways of seeing—transcendental, romantic, and utilitarian. The idea of cultural landscape can be seen in ancient practices such as circumambulation and immersion in bodies of water that sustain engagement with natural elements. Pilgrim towns, medieval forts, religious sites, and contemporary memorial parks are sites of memory where myth and history converge. Engaging with these spaces allows us to reconstruct collective memory and reclaim not only historic landscapes, but ways of seeing, making, and remembering. Cultural Landscapes in India makes the case for reclaiming iconic landscapes and rethinking conventional approaches to conservation that take into consideration performative landscape as heritage.
This text discusses the principal political and constitutional questions that have arisen in the states of Bangladesh, India, Pakistan and Sri Lanka following fifty years of independence. In Sri Lanka the pressing problems have been around the inter-ethnic civil war, experiments with constitutional designs, widespread prevalence of corruption and the recrudescence of Buddhist militancy. In India it has been corruption, Hindu nationalism and general political instability. In Bangladesh and Pakistan it has been the role of the military, the state and religion. A general theme is an analysis of the malaise that is prevalent and how and why this was inherited, despite the colonial legacy of parliamentary democracy, the steel framework of a trained bureaucracy, the independence of the judiciary and the rule of law.
Take the next step in implementing various common and not-so-common neural networks with Tensorflow 1.x About This Book Skill up and implement tricky neural networks using Google's TensorFlow 1.x An easy-to-follow guide that lets you explore reinforcement learning, GANs, autoencoders, multilayer perceptrons and more. Hands-on recipes to work with Tensorflow on desktop, mobile, and cloud environment Who This Book Is For This book is intended for data analysts, data scientists, machine learning practitioners and deep learning enthusiasts who want to perform deep learning tasks on a regular basis and are looking for a handy guide they can refer to. People who are slightly familiar with neural networks, and now want to gain expertise in working with different types of neural networks and datasets, will find this book quite useful. What You Will Learn Install TensorFlow and use it for CPU and GPU operations Implement DNNs and apply them to solve different AI-driven problems. Leverage different data sets such as MNIST, CIFAR-10, and Youtube8m with TensorFlow and learn how to access and use them in your code. Use TensorBoard to understand neural network architectures, optimize the learning process, and peek inside the neural network black box. Use different regression techniques for prediction and classification problems Build single and multilayer perceptrons in TensorFlow Implement CNN and RNN in TensorFlow, and use it to solve real-world use cases. Learn how restricted Boltzmann Machines can be used to recommend movies. Understand the implementation of Autoencoders and deep belief networks, and use them for emotion detection. Master the different reinforcement learning methods to implement game playing agents. GANs and their implementation using TensorFlow. In Detail Deep neural networks (DNNs) have achieved a lot of success in the field of computer vision, speech recognition, and natural language processing. The entire world is filled with excitement about how deep networks are revolutionizing artificial intelligence. This exciting recipe-based guide will take you from the realm of DNN theory to implementing them practically to solve the real-life problems in artificial intelligence domain. In this book, you will learn how to efficiently use TensorFlow, Google's open source framework for deep learning. You will implement different deep learning networks such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Deep Q-learning Networks (DQNs), and Generative Adversarial Networks (GANs) with easy to follow independent recipes. You will learn how to make Keras as backend with TensorFlow. With a problem-solution approach, you will understand how to implement different deep neural architectures to carry out complex tasks at work. You will learn the performance of different DNNs on some popularly used data sets such as MNIST, CIFAR-10, Youtube8m, and more. You will not only learn about the different mobile and embedded platforms supported by TensorFlow but also how to set up cloud platforms for deep learning applications. Get a sneak peek of TPU architecture and how they will affect DNN future. By using crisp, no-nonsense recipes, you will become an expert in implementing deep learning techniques in growing real-world applications and research areas such as reinforcement learning, GANs, autoencoders and more. Style and approach This book consists of hands-on recipes where you'll deal with real-world problems. You'll execute a series of tasks as you walk through data mining challenges using TensorFlow 1.x. Your one-stop solution for common and not-so-common pain points, this is a book that you must have on the shelf.
This book offers a unique re-conceptualization of Marxism in bringing together leading scholars across disciplines — history, philosophy, economics, politics, sociology, and literary and culture studies — into one comprehensive corpus. It demonstrates the engaging relevance of the perspectives and techniques of the analyses adopted by Karl Marx, Frederich Engels and contemporary Marxists, and will be immensely useful to scholars and researchers across social sciences as well as general readers interested in Marxism.
[A] delightful book' NAMITA GOKHALE 'A must-read' KIRAN MANRAL 'Deeply researched' PAVAN K. VARMA What makes the Big Fat Indian Wedding so central to our lives? The wedding is the most celebrated event in Indian society. It forms the heart of a multi-billion-dollar industry driving fashion, food, music, entertainment and our desire for companionship. In The Shaadi Story, social entrepreneur Amita Sahaya takes a fascinating look at the history, religious traditions, societal attitudes, industry and modern adaptations of the North Indian Hindu wedding and beyond. Across seven chapters structured like the traditional ritual of the saptapadi, this book illuminates the seven different aspects of the quintessential Indian wedding. Drawing on ancient Sanskrit scriptures, western philosophies, Bollywood movies and the voices of young Indians, this book is an in-depth examination of our evolving ideas of love and relationships through the prism of our society’s most elaborate celebration. Enlightening and entertaining, The Shaadi Story is a remarkable exploration of Indian weddings and marriages and what makes them tick.
Build smarter systems by combining artificial intelligence and the Internet of Things—two of the most talked about topics today Key FeaturesLeverage the power of Python libraries such as TensorFlow and Keras to work with real-time IoT dataProcess IoT data and predict outcomes in real time to build smart IoT modelsCover practical case studies on industrial IoT, smart cities, and home automationBook Description There are many applications that use data science and analytics to gain insights from terabytes of data. These apps, however, do not address the challenge of continually discovering patterns for IoT data. In Hands-On Artificial Intelligence for IoT, we cover various aspects of artificial intelligence (AI) and its implementation to make your IoT solutions smarter. This book starts by covering the process of gathering and preprocessing IoT data gathered from distributed sources. You will learn different AI techniques such as machine learning, deep learning, reinforcement learning, and natural language processing to build smart IoT systems. You will also leverage the power of AI to handle real-time data coming from wearable devices. As you progress through the book, techniques for building models that work with different kinds of data generated and consumed by IoT devices such as time series, images, and audio will be covered. Useful case studies on four major application areas of IoT solutions are a key focal point of this book. In the concluding chapters, you will leverage the power of widely used Python libraries, TensorFlow and Keras, to build different kinds of smart AI models. By the end of this book, you will be able to build smart AI-powered IoT apps with confidence. What you will learnApply different AI techniques including machine learning and deep learning using TensorFlow and KerasAccess and process data from various distributed sourcesPerform supervised and unsupervised machine learning for IoT dataImplement distributed processing of IoT data over Apache Spark using the MLLib and H2O.ai platformsForecast time-series data using deep learning methodsImplementing AI from case studies in Personal IoT, Industrial IoT, and Smart CitiesGain unique insights from data obtained from wearable devices and smart devicesWho this book is for If you are a data science professional or a machine learning developer looking to build smart systems for IoT, Hands-On Artificial Intelligence for IoT is for you. If you want to learn how popular artificial intelligence (AI) techniques can be used in the Internet of Things domain, this book will also be of benefit. A basic understanding of machine learning concepts will be required to get the best out of this book.
Implement TensorFlow's offerings such as TensorBoard, TensorFlow.js, TensorFlow Probability, and TensorFlow Lite to build smart automation projects Key FeaturesUse machine learning and deep learning principles to build real-world projectsGet to grips with TensorFlow's impressive range of module offeringsImplement projects on GANs, reinforcement learning, and capsule networkBook Description TensorFlow has transformed the way machine learning is perceived. TensorFlow Machine Learning Projects teaches you how to exploit the benefits—simplicity, efficiency, and flexibility—of using TensorFlow in various real-world projects. With the help of this book, you’ll not only learn how to build advanced projects using different datasets but also be able to tackle common challenges using a range of libraries from the TensorFlow ecosystem. To start with, you’ll get to grips with using TensorFlow for machine learning projects; you’ll explore a wide range of projects using TensorForest and TensorBoard for detecting exoplanets, TensorFlow.js for sentiment analysis, and TensorFlow Lite for digit classification. As you make your way through the book, you’ll build projects in various real-world domains, incorporating natural language processing (NLP), the Gaussian process, autoencoders, recommender systems, and Bayesian neural networks, along with trending areas such as Generative Adversarial Networks (GANs), capsule networks, and reinforcement learning. You’ll learn how to use the TensorFlow on Spark API and GPU-accelerated computing with TensorFlow to detect objects, followed by how to train and develop a recurrent neural network (RNN) model to generate book scripts. By the end of this book, you’ll have gained the required expertise to build full-fledged machine learning projects at work. What you will learnUnderstand the TensorFlow ecosystem using various datasets and techniquesCreate recommendation systems for quality product recommendationsBuild projects using CNNs, NLP, and Bayesian neural networksPlay Pac-Man using deep reinforcement learningDeploy scalable TensorFlow-based machine learning systemsGenerate your own book script using RNNsWho this book is for TensorFlow Machine Learning Projects is for you if you are a data analyst, data scientist, machine learning professional, or deep learning enthusiast with basic knowledge of TensorFlow. This book is also for you if you want to build end-to-end projects in the machine learning domain using supervised, unsupervised, and reinforcement learning techniques
This book analyses India’s trade policy evolution in the last two decades in the broad context of trends and patterns in global trade and in particular, with reference to the emergence of global value chains (GVCs). Through an in-depth analysis of its trade policy evolution in the 2000s, the author explains India’s limited share of global merchandise trade, especially manufacturing trade and relatively low GVC integration. The book discusses India’s trade policy, pattern and global trade participation not just in the comparative context of China as is true of most analyses relating to the Indian economy, economic reforms and trade liberalization in India but also in the context of regional economies like Vietnam, Thailand, Malaysia, Bangladesh and other emerging market economies (EMEs) that have successfully integrated with GVCs/ RVCs in the period under reference. Progress and nature of India’s value chain participation relative to other economies has been evaluated in this context. The book further examines policy developments with respect to traditional trade measures like tariffs and export schemes, trade and GVC related policies in special economic zones (SEZs) as well as GVC-facilitating policy instruments such as regional/ free trading agreements (RTAs/FTAs) and investment treaties. Three sectoral case studies - automobiles, textiles and apparel and electronics - are presented to examine India’s participation in these dynamic GVC intensive sectors. An important study of one of the fastest growing economies in the world for almost two decades, this book will be of substantial interest to academics and policymakers in the fields of Economics, International Economics, Foreign Policy, Economic Relations, Economic Diplomacy, Indian- Southeast/East Asian Economics.
This book highlights the genomic findings, observations, and analysis of DNA/RNA sequences and protein structure of the dreadful virus of this decade- COVID-19. The Corona group of viruses though known species, the strain that caused the Pandemic of 2019 is a completely new strain, belonging to the same corona family with a novel genetic make-up. This makes it a new pathogen which is causing the current outbreak leaving the global scientific community clueless of any therapeutic breakthrough. NCOV enjoys life threatening pathogenicity with mysterious genetic annotations. This book details and offers insights into its viral genetic arrangement, Virulence factors, probable mutations leading to the evolution of this new strain and more. It contains chapters on Virus evolutionary status and Genetic makeup leading to its pathogenicity which can be a new insight in understanding the nature of this clever microorganism and can pave way to the development of new drugs and Vaccines or a novel diagnostic approach for the early prognosis of the disease. A dedicated chapter on annotation of NCOV-19 virulence genes, translation of the genes to protein product, annotation of the antigenic sites on these proteins is also included. In all, this brief is a complete genomic annotation insight of NCOV-19 using AI, Data analytics and Bioinformatics analysis. In the current situation, this book is an extensive preliminary resource for Medical practitioners, Researchers, Academicians, Scientists, Biochemists, Bioinformaticians and other professionals interested in understanding the genetics of Novel Coronavirus 19, the best possible drug targets, ideal vaccine candidates and novel prognostic and diagnostic biomarkers.
Build cutting edge machine and deep learning systems for the lab, production, and mobile devices Key FeaturesUnderstand the fundamentals of deep learning and machine learning through clear explanations and extensive code samplesImplement graph neural networks, transformers using Hugging Face and TensorFlow Hub, and joint and contrastive learningLearn cutting-edge machine and deep learning techniquesBook Description Deep Learning with TensorFlow and Keras teaches you neural networks and deep learning techniques using TensorFlow (TF) and Keras. You'll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow 2.x focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs based on Keras, and flexible model building on any platform. This book uses the latest TF 2.0 features and libraries to present an overview of supervised and unsupervised machine learning models and provides a comprehensive analysis of deep learning and reinforcement learning models using practical examples for the cloud, mobile, and large production environments. This book also shows you how to create neural networks with TensorFlow, runs through popular algorithms (regression, convolutional neural networks (CNNs), transformers, generative adversarial networks (GANs), recurrent neural networks (RNNs), natural language processing (NLP), and graph neural networks (GNNs)), covers working example apps, and then dives into TF in production, TF mobile, and TensorFlow with AutoML. What you will learnLearn how to use the popular GNNs with TensorFlow to carry out graph mining tasksDiscover the world of transformers, from pretraining to fine-tuning to evaluating themApply self-supervised learning to natural language processing, computer vision, and audio signal processingCombine probabilistic and deep learning models using TensorFlow ProbabilityTrain your models on the cloud and put TF to work in real environmentsBuild machine learning and deep learning systems with TensorFlow 2.x and the Keras APIWho this book is for This hands-on machine learning book is for Python developers and data scientists who want to build machine learning and deep learning systems with TensorFlow. This book gives you the theory and practice required to use Keras, TensorFlow, and AutoML to build machine learning systems. Some machine learning knowledge would be useful. We don't assume TF knowledge.
This book gives an overview of various interactomes involved in dorsal ventral (DV) and anterior posterior (AP) guidance, their mechanisms of action, subcellular localizations, and functional roles. It will provide readers a better understanding of the development of the nervous system, which in turn will help to find cures to various neural and other disorders. In nematodes there are two types of guidance systems, including DV and AP guidance. The signaling process that guides the growth cones along the DV axis has remained intact in both vertebrates and invertebrates. The adaptor protein UNC-53 appears to play a part in migration along the AP axis in both worms and their human homologs. “Neuron Navigators” (NAV) are also involved in nervous system development
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