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ENSAIOS DE POLÍTICA CRIMINAL
O presente livro é resultado dos debates ocorridos na disciplina Política Criminal e Sistema Penal ministrada no primeiro semestre do ano de 2021 no Programa de Pós-Graduação em Direito da PUC Minas. Na ocasião, aprofundou-se a relação entre o neoliberalismo e as políticas criminais adotadas no país. As discussões foram pautadas a partir do pensamento de Franz Hinkelammert, que em seus trabalhos demonstra as matrizes de opressão e exclusão do neoliberalismo e a dinâmica do sacrifício habilitada pelo capitalismo global que impacta diretamente a sociedade contemporânea e pode ser identificada nas diversas ações adotadas pelo Estado Brasileiro. Estabelecendo o diálogo com outros autores foram produzidos ensaios acerca de algumas áreas que compõem a política criminal. Analisar as políticas criminais, entender o discurso presente em cada uma delas, realizar a devida crítica e resistência à presença do neoliberalismo em tais políticas de Estado são alguns dos objetivos desta obra. Klelia Canabrava Aleixo Professora do Programa de Pós-graduação em Direito da Pontifícia Universidade Católica de Minas Gerais.
Direito e Sociedade
A presente obra é resultado das práticas de pesquisa e extensão desenvolvidas pelos orientadores e ligantes no âmbito dos núcleos de estudos da Liga Acadêmica Jurídica de Minas Gerais. Contando com profundas reflexões sobre questões correlatas às mais diversas áreas do saber jurídico, os quatorze artigos que compõem a obra exploram relevantes temáticas atinentes à construção, interpretação e aplicação normativa, seja na dimensão dogmática, seja na dimensão axiológica, além de estudos de casos e discussões sobre matérias essencialmente atuais, em sintonia com o eixo central de abordagem. Com as investigações científicas desenvolvidas, espera-se que o leitor tenha em suas mãos uma obra suficientemente apta a lhe fornecer uma proveitosa leitura, despertando reflexões que auxiliem na construção de soluções para os desafios jurídicos da contemporaneidade.
The Atlantic Forest
The Atlantic Forest is one of the 36 hotspots for biodiversity conservation worldwide. It is a unique, large biome (more than 3000 km in latitude; 2500 in longitude), marked by high biodiversity, high degree of endemic species and, at the same time, extremely threatened. Approximately 70% of the Brazilian population lives in the area of this biome, which makes the conflict between biodiversity conservation and the sustainability of the human population a relevant issue. This book aims to cover: 1) the historical characterization and geographic variation of the biome; 2) the distribution of the diversity of some relevant taxa; 3) the main threats to biodiversity, and 4) possible opportunities to ensure the biodiversity conservation, and the economic and social sustainability. Also, it is hoped that this book can be useful for those involved in the development of public policies aimed at the conservation of this important global biome.
Seismic Attributes for Prospect Identification and Reservoir Characterization
Introducing the physical basis, mathematical implementation, and geologic expression of modern volumetric attributes including coherence, dip/azimuth, curvature, amplitude gradients, seismic textures, and spectral decomposition, the authors demonstrate the importance of effective colour display and sensitivity to seismic acquisition and processing.
Graph Representation Learning
Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical sy...
Federated Learning
How is it possible to allow multiple data owners to collaboratively train and use a shared prediction model while keeping all the local training data private? Traditional machine learning approaches need to combine all data at one location, typically a data center, which may very well violate the laws on user privacy and data confidentiality. Today, many parts of the world demand that technology companies treat user data carefully according to user-privacy laws. The European Union's General Data Protection Regulation (GDPR) is a prime example. In this book, we describe how federated machine learning addresses this problem with novel solutions combining distributed machine learning, cryptography and security, and incentive mechanism design based on economic principles and game theory. We explain different types of privacy-preserving machine learning solutions and their technological backgrounds, and highlight some representative practical use cases. We show how federated learning can become the foundation of next-generation machine learning that caters to technological and societal needs for responsible AI development and application.
The Abolition of the Brazilian Slave Trade
He covers a major aspect of the history of the international abolition of the slave trade.
A Guide to the Latin American Art Song Repertoire
A reference guide to the vast array of art song literature and composers from Latin America, this book introduces the music of Latin America from a singer's perspective and provides a basis for research into the songs of this richly musical area of the world. The book is divided by country into 22 chapters, with each chapter containing an introductory essay on the music of the region, a catalog of art songs for that country, and a list of publishers. Some chapters include information on additional sources. Singers and teachers may use descriptive annotations (language, poet) or pedagogical annotations (range, tessitura) to determine which pieces are appropriate for their voices or programming needs, or those of their students. The guide will be a valuable resource for vocalists and researchers, however familiar they may be with this glorious repertoire.
Information Technology - New Generations
This volume presents a collection of peer-reviewed, scientific articles from the 15th International Conference on Information Technology – New Generations, held at Las Vegas. The collection addresses critical areas of Machine Learning, Networking and Wireless Communications, Cybersecurity, Data Mining, Software Engineering, High Performance Computing Architectures, Computer Vision, Health, Bioinformatics, and Education.
Representation Learning for Natural Language Processing
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.
