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Psicoterapias breves
As psicoterapias breves são uma modalidade de atendimento aplicável em contextos institucionais, especialmente na saúde pública. Apesar da disseminação de que essas psicoterapias seriam uma 'abreviação' temporal da modalidade de longo prazo, elas exigem, na realidade, conhecimento teórico-técnico que possibilitem que uma psicoterapia seja breve e tenha bons resultados. O livro reúne contribuições de psicoterapeutas e pesquisadores sobre propostas de psicoterapia breve de diferentes orientações teóricas que permitirão ao leitor uma visão ampla da teoria e da prática dessa modalidade de psicoterapia. Inicia-se com uma seção que trata de aspectos teórico-técnicos mais gerais para, em seguida, apresentar algumas das diversas propostas que praticamos na atualidade.
Clínica de Orientação Psicanalítica
Este livro enfoca debates teóricos, técnicos, práticos e de pesquisa sobre intervenções clínicas com famílias, formação de psicoterapeutas e clínicos em nível de graduação e pós-graduação, relatos de serviços de atendimento psicoterápico focados em diversos públicos, psicoterapia breve psicodinâmica de adultos, processos grupais e uso de tecnologias em processo de formação de psicoterapeutas. Traz contribuições de diversos profissionais e pesquisadores vinculados a instituições de ensino superior públicas, privadas, confessionais e autarquias, o que potencializa condições de leitores conhecerem a obra e verem suas realidades espelhadas nessas contribuições.
Jellyfish and Polyps
This Special Issue of Marine Drugs gathers recent investigations on the proteomes, metabolomes, transcriptomes, and the associated microbiomes of marine jellyfish and polyps, including bioactivity studies of their compounds and more generally, on their biotechnological potential, witnessing the increasingly recognized importance of Cnidaria as a largely untapped Blue Growth resource for new drug discovery. These researches evoke the outstanding ecological importance of cnidarians in marine ecosystems worldwide, calling for a global monitoring and conservation of marine biodiversity, so that the biotechnological exploitation of marine living resources will be carried out to conserve and sustainably use the natural capital of the oceans.
An Overview of the Pre-suppression Society of Jesus in Spain
In An Overview of the Pre-suppression Society of Jesus in Spain, Patricia W. Manning offers a survey of the Society of Jesus in Spain from its origins in Ignatius of Loyola’s early preaching to the aftereffects of its expulsion. Rather than nurture the nascent order, Loyola’s homeland was often ambivalent. His pre-Jesuit freelance sermonizing prompted investigations. The young Society confronted indifference and interference from the Spanish monarchy and outright opposition from other religious orders. This essay outlines the order’s ministerial and pedagogical activities, its relationship with women and with royal institutions, including the Spanish Inquisition, and Spanish members’ roles in theological debates concerning casuistry, free will, and the immaculate conception. It also considers the impact of Jesuits’ non-religious writings.
Borges and Dante
Originally presented as the author's thesis (doctorate--University College, London, 2001).
The Diary of Heinrich Witt (10 vols.)
The diary of Heinrich Witt (1799-1892) is the most extensive private diary written in Latin America known to us today. Written in English by a German migrant who lived in Lima, it is a unique source for the history of Peru, and for international trade and migration.
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...
Psychodynamic Psychiatry in Clinical Practice
It is difficult to improve on a classic, but the fifth edition of Psychodynamic Psychiatry in Clinical Practice does just that, offering the updates readers expect with a deft reorganization that integrates DSM-5® with the author's emphasis on psychodynamic thinking. The individual patient is never sacrificed to the diagnostic category, yet clinicians will find the guidance they need to apply DSM-5® appropriately. Each chapter has been systematically updated to reflect the myriad and manifold changes in the 9 years since the previous edition's publication. All 19 chapters have new references and cutting-edge material that will prepare psychiatrists and residents to treat patients with comp...
Statistical Models for Test Equating, Scaling, and Linking
The goal of this book is to emphasize the formal statistical features of the practice of equating, linking, and scaling. The book encourages the view and discusses the quality of the equating results from the statistical perspective (new models, robustness, fit, testing hypotheses, statistical monitoring) as opposed to placing the focus on the policy and the implications, which although very important, represent a different side of the equating practice. The book contributes to establishing “equating” as a theoretical field, a view that has not been offered often before. The tradition in the practice of equating has been to present the knowledge and skills needed as a craft, which implie...
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.
