Three decades after the Soviet Union's collapse, Russia has transformed from a fringe player to a resurgent great power in Africa. The October 2019 Russia-Africa Summit in Sochi highlighted the appeal of Russia's normative agenda, the ubiquity of Russian military technology, and the breadth of Moscow's presence on the continent. Beneath the pageantry, a darker side of Russia's African resurgence looms large. From Libya to Madagascar, Russia has used sinister tactics to expand its influence, such as private military contractors, shadowy mining and energy deals with authoritarian regimes, and election interference campaigns. This book presents a chronological examination of Russia's post-Cold War foreign policy towards Africa, and outlines the factors that have enabled and impeded the growth of its influence. It pays special attention to the non-material factors behind this rising power; the domestic drivers of Russian decision-making; Moscow's relationships with fellow external powers; and African perspectives on Russia's geopolitical role. Samuel Ramani's analysis cites extensively both Russian-language media and academic sources, and his own interviews with Russian and African elites. His fascinating study challenges popular depictions of Russia as an opportunistic anti-Western actor, instead emphasizing Moscow's strategic commitment to Africa and the endurance of historical memory.
Eight years after annexing Crimea, Russia embarked on a full-scale invasion of Ukraine in February 2022. Vladimir Putin viewed this attack on a neighbour as a legacy-defining mission, which sought to restore a central element of Russia’s sphere of influence and undo Ukraine’s surprisingly resilient democratic experiment. These aspirations were swiftly eviscerated, as the conflict degenerated into a bloody war of attrition and the Russian economy crumbled under the weight of sanctions. This book argues that Putin’s desire to unite Russians around a common set of principles and consolidate his personal brand of authoritarianism prompted him to pursue a policy of global counter-revolution; it was this which inspired Russia’s military interventions in Crimea, Donbas and Syria, later steering Putin to war against Kyiv. Samuel Ramani explores why Putin opted for all-out regime change in Ukraine, rather than a smaller-scale intervention in Donbas, and considers the impact on his own regime’s legitimacy. This focus on the domestic drivers of invasion contrasts with alternative theories that highlight systemic factors, such as preventing NATO expansion. Ramani concludes by assessing the invasion’s implications for Russia’s long-term political and foreign policy trajectory, and how the international response to the conflict will reshape the global order.
Eight years after annexing Crimea, Russia embarked on a full-scale invasion of Ukraine in February 2022. Vladimir Putin viewed this attack on a neighbour as a legacy-defining mission, which sought to restore a central element of Russia’s sphere of influence and undo Ukraine’s surprisingly resilient democratic experiment. These aspirations were swiftly eviscerated, as the conflict degenerated into a bloody war of attrition and the Russian economy crumbled under the weight of sanctions. This book argues that Putin’s desire to unite Russians around a common set of principles and consolidate his personal brand of authoritarianism prompted him to pursue a policy of global counter-revolution; it was this which inspired Russia’s military interventions in Crimea, Donbas and Syria, later steering Putin to war against Kyiv. Samuel Ramani explores why Putin opted for all-out regime change in Ukraine, rather than a smaller-scale intervention in Donbas, and considers the impact on his own regime’s legitimacy. This focus on the domestic drivers of invasion contrasts with alternative theories that highlight systemic factors, such as preventing NATO expansion. Ramani concludes by assessing the invasion’s implications for Russia’s long-term political and foreign policy trajectory, and how the international response to the conflict will reshape the global order.
The use of diesel-powered equipment in underground mining operations provides many benefits to the industry. It also presents many challenges to the health and safety of workers as it is a significant source of submicrometer aerosols and noxious gases. This book was developed to assist the coal and metal/nonmetal underground mining industries in their efforts to reduce the exposure of workers to aerosols and gases from diesel-powered equipment. It includes information collected by researchers at the National Institute for Occupational Safety and Health/Office of Mine Safety and Health Research (NIOSH/OMSHR). Prior to the production of this text, the knowledge on this complex issue was fragmented. The goal of this volume is to make the information available in one easy-to-use reference. The book includes comprehensive, mine-specific programs for use by mechanics, mine ventilation engineers, industrial hygienists, mine managers, union health and safety representatives, and personnel responsible for the acquisition of diesel vehicles, engines, exhaust aftertreatment systems, fuels, and lubricants. The description of methods to reduce exposure to diesel aerosols includes curtailment of diesel particulate matter and gaseous emissions at their source, and controlling airborne pollutants with ventilation and personal protective equipment. This information should also help researchers in industry, government, and academia to identify areas that need to be addressed in future research and development efforts.
Distributed source coding is one of the key enablers for efficient cooperative communication. The potential applications range from wireless sensor networks, ad-hoc networks, and surveillance networks, to robust low-complexity video coding, stereo/Multiview video coding, HDTV, hyper-spectral and multispectral imaging, and biometrics. The book is divided into three sections: theory, algorithms, and applications. Part one covers the background of information theory with an emphasis on DSC; part two discusses designs of algorithmic solutions for DSC problems, covering the three most important DSC problems: Slepian-Wolf, Wyner-Ziv, and MT source coding; and part three is dedicated to a variety of potential DSC applications. Key features: Clear explanation of distributed source coding theory and algorithms including both lossless and lossy designs. Rich applications of distributed source coding, which covers multimedia communication and data security applications. Self-contained content for beginners from basic information theory to practical code implementation. The book provides fundamental knowledge for engineers and computer scientists to access the topic of distributed source coding. It is also suitable for senior undergraduate and first year graduate students in electrical engineering; computer engineering; signal processing; image/video processing; and information theory and communications.
Artificial Intelligence is at the top of the agenda for education leaders, scientists, technologists and policy makers in educating the next generation across the globe. Beyond applying AI in daily life applications and educational tools, understanding how to learn and teach AI is increasingly important. Despite these emerging technology breakthroughs, AI learning is still new to educators especially to K-16 teachers. There is a lack of evidence-based studies that inform them about AI learning, including design principles for building a set of curriculum content, and pedagogical approaches as well as technological tools. Teaching AI concepts and techniques from programming languages and developmentally appropriate learning tools (e.g., robotics, serious games, software, intelligent agents) across different education levels emerged in recent years. The primary purpose of this book is to respond to the need to conceptualize the emerging term “AI literacy” and investigate how to teach and learn AI in K-16 education settings. This book examines different aspects of learning artefacts, pedagogies, content knowledge and assessment methods of AI literacy education, from theoretical discussions to practical recommendations for curriculum and instructional design. An exhaustive summary of current evidence with examples is illustrated in this book, as well as cutting-edge research that serves as an AI literacy model for different countries’ contexts. Part I, “Conceptualizing AI literacy”, provides a detailed discussion on the development of the concepts and frameworks on AI literacy education, discusses the differences and similarities between AI in education (AIED) and AI literacy education, and illustrates the reasons why K-16 students need to learn AI. These concepts are brought together in Part II, “K-16 AI literacy education” to further summarize the pedagogies, learning content, learning tools and assessment methods to inform K-16 educators how to design their AI instruction at each education level. After that, part III “AI literacy for instructional designers” explores how instructional designers (i.e., AI developers and teachers) prepare themselves to become ready to design developmentally appropriate tools, platforms, services and curricula to empower students with AI literacy skills.
Electrochemical Phenomena in the Cathode Impedance Spectrum of PEM Fuel Cells: Fundamentals, Modelling, and Applications establishes how the electrochemical and diffusion mechanisms of a polymer electrolyte membrane fuel cell (PEMFC) are related to electrochemical impedance spectroscopy (EIS) measurements using physics-based impedance models derived from fundamental electrode and diffusion theories. The contribution of the different phenomena occurring at the different layers comprising the cathode on the impedance response of the PEMFC is revealed through EIS-modelling analysis. The relation between EIS measurements and polarisation curves representing the performance of PEMFCs is established. Insight is gained into how the EIS response of the PEMFC changes at different operating conditions e.g. relative humidity, load demand, gas reactant stoichiometry and temperature using physics-based impedance models. The application of impedance models with EIS measurements carried out in the individual cells comprising a PEMFC stack is demonstrated, while recent modelling approaches and other impedance models reported in the literature to represent the EIS response of the PEMFC are also considered and discussed. - Provides further understanding of ambiguities during the interpretation of the electrochemical impedance spectrum of the PEMFC - Includes impedance models written in MATLAB® for replication or application to other PEMFC-EIS measurements - Includes impedance spectra of the PEMFC at different operating conditions, electro/diffusion pathways for derivation of the impedance models and flowcharts for application of the impedance models with real-world measured EIS data
In view of the growing prevalence of AD worldwide, there is an urgent need for the development of better diagnostic tools and more effective therapeutic interventions. Indeed, much work in this field has been done during last decades. As such, a major goal of current clinical research in AD is to improve early detection of disease and presymptomatic detection of neuronal dysfunction, concurrently with the development of better tools to assess disease progression in this group of disorders. All these putative correlates are commonly referred to as AD-related biomarkers. The ideal biomarker should be easy to quantify and measure, reproducible, not subject to wide variation in the general population and unaffected by co- morbid factors. For evaluation of therapies, a biomarker needs to change linearly with disease progression and closely correlate with established clinico-pathological parameters of the disease. There is growing evidence that the use of biomarkers will increase our ability to better indentify the underlying biology of AD, especially in its early stages. These biomarkers will improve the detection of the patients suitable for research studies and drug trials, and they will contribute to a better management of the disease in the clinical practice. Indeed, much work in this field has been done during last decades. The vast number of important applications, combined with the untamed diversity of already identified biomarkers, show that there is a pressing need to structure the research made on AD biomarkers into a solid, comprehensive and easy to use tool to de deployed in clinical settings. To date there are few publications compiling results on this topic. That is why when I was asked to address this task I accepted inmediately. I am happy to present you a bundle of the best articles published about biomarkers for Alzheimer’s disease in recent times.
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