Viral Gastroenteritis: Molecular Epidemiology and Pathogenesis provides a comprehensive review of research on viruses causing acute gastroenteritis in infants and young children, including coverage of rotaviruses, human caliciviruses, astroviruses, enteric adenoviruses, and viruses causing gastroenteritis more rarely. Includes general chapters on gastrointestinal physiology and pathophysiology, gastrointestinal immune mechanisms, immunodeficiencies and host genetics influencing susceptibility to viral gastroenteritis, and therapeutic and preventative approaches. The book also includes special sections on virus particle structures, replication cycles, pathogenesis, immunology, epidemiology, and preventative measures. This book covers both basic science and translational applications and is an appropriate resource for virologists, molecular biologists, epidemiologists, gastroenterologists, vaccinologists, and those with an interest in public health.

Now in its second edition, this accessible text presents a unified Bayesian treatment of state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models. The book focuses on discrete-time state space models and carefully introduces fundamental aspects related to optimal filtering and smoothing. In particular, it covers a range of efficient non-linear Gaussian filtering and smoothing algorithms, as well as Monte Carlo-based algorithms. This updated edition features new chapters on constructing state space models of practical systems, the discretization of continuous-time state space models, Gaussian filtering by enabling approximations, posterior linearization filtering, and the corresponding smoothers. Coverage of key topics is expanded, including extended Kalman filtering and smoothing, and parameter estimation. The book's practical, algorithmic approach assumes only modest mathematical prerequisites, suitable for graduate and advanced undergraduate students. Many examples are included, with Matlab and Python code available online, enabling readers to implement algorithms in their own projects.

Project work, driven by competent project leaders drives positive outcomes. Unfortunately these optimistic initial results are often short-sighted with few evaluations of their long-term impact. The research contained in Managing Sustainable Development Programmes reveals an extraordinary level of failure in the durability of large change programmes and projects in both the private and public sectors. In this book the authors question whether sustainable development be achieved within the framework of large publicly financed programmes. This strong critique of traditional programme implementation overturns much of our current thinking about project delivery and governance. The authors focus instead on sustainable change and development. They show how active ownership and collaboration between different actors and the dynamics of developmental learning can be used to create programmes and projects that contribute to innovation, employment and growth in a way that favours companies, employees, customers and society in a broader sense. The message at its heart is 'don't blame the project leader' but rather look for dynamic possession of projects, joint knowledge management and sharing with external stakeholders that will secure long-term effects.