Violencia doméstica y venta de cosa ajena

Traballo fin de grao (UDC.DER). Grao en Dereito. Curso 2015/201

Stuck in the sibling relationship : growing up with a sibling with a serious mental illness and how intimate relationships later in life may be affected

This theoretical study examines the experience of growing up with a sibling with a serious mental illness and how this phenomenon may then affect intimate relationships later in life. Theoretical perspectives of both trauma theory and object relations theory are applied to this phenomenon and how it affects the well siblings. Findings of the current study suggest that individuals internalize aspects of this early relationship and also internalize aspects of the relationship with their parents who are focusing so much care and attention on the mentally ill sibling. Patterns of maladaptive relationships may then continue to occur in the future. The findings highlight that it is important for clinicians to pay attention to the needs of the well siblings and work from a family systems framework while treating someone with a serious mental illness. When treating individuals in adulthood, it is also important to pay attention to early needs that may not have been met in childhood which may be contributing to unhealthy relationship patterns

Machine learning models for the prediction of pharmaceutical powder properties

Error on title page – year of award is 2023.Understanding how particle attributes affect the pharmaceutical manufacturing process performance remains a significant challenge for the industry, adding cost and time to the development of robust products and production routes. Tablet formation can be achieved by several techniques however, direct compression (DC) and granulation are the most widely used in industrial operations. DC is of particular interest as it offers lower-cost manufacturing and a streamlined process with fewer steps compared with other unit operations. However, to achieve the full potential benefits of DC for tablet manufacture, this places strict demands on material flow properties, blend uniformity, compactability, and lubrication, which need to be satisfied. DC is increasingly the preferred technique for pharmaceutical companies for oral solid dose manufacture, consequently making the flow prediction of pharmaceutical materials of increasing importance. Bulk properties are influenced by particle attributes, such as particle size and shape, which are defined during crystallization and/or milling processes. Currently, the suitability of raw materials and/or formulated blends for DC requires detailed characterization of the bulk properties. A key goal of digital design and Industry 4.0 concepts is through digital transformation of existing development steps be able to better predict properties whilst minimizing the amount of material and resources required to inform process selection during early- stage development. The work presented in Chapter 4 focuses on developing machine learning (ML) models to predict powder flow behaviour of routine, widely available pharmaceutical materials. Several datasets comprising powder attributes (particle size, shape, surface area, surface energy, and bulk density) and flow properties (flow function coefficient) have been built, for pure compounds, binary mixtures, and multicomponent formulations. Using these datasets, different ML models, including traditional ML (random forest, support vector machines, k nearest neighbour, gradient boosting, AdaBoost, Naïve Bayes, and logistic regression) classification and regression approaches, have been explored for the prediction of flow properties, via flow function coefficient. The models have been evaluated using multiple sampling methods and validated using external datasets, showing a performance over 80%, which is sufficiently high for their implementation to improve manufacturing efficiency. Finally, interpretability methods, namely SHAP (SHapley Additive exPlanaitions), have been used to understand the predictions of the machine learning models by determining how much each variable included in the training dataset has contributed to each final prediction. Chapter 5 expanded on the work presented in Chapter 4 by demonstrating the applicability of ML models for the classification of the viability of pharmaceutical formulations for continuous DC via flow function coefficient on their powder flow. More than 100 formulations were included in this model and the particle size and particle shape of the active pharmaceutical ingredients (APIs), the flow function coefficient of the APIs, and the concentration of the components of the formulations were used to build the training dataset. The ML models were evaluated using different sampling techniques, such as bootstrap sampling and 10-fold cross-validation, achieving a precision of 90%. Furthermore, Chapter 6 presents the comparison of two data-driven model approaches to predict powder flow: a Random Forest (RF) model and a Convolutional Neural Network (CNN) model. A total of 98 powders covering a wide range of particle sizes and shapes were assessed using static image analysis. The RF model was trained on the tabular data (particle size, aspect ratio, and circularity descriptors), and the CNN model was trained on the composite images. Both datasets were extracted from the same characterisation instrument. The data were split into training, testing, and validation sets. The results of the validation were used to compare the performance of the two approaches. The results revealed that both algorithms achieved a similar performance since the RF model and the CNN model achieved the same accuracy of 55%. Finally, other particle and bulk properties, i.e., bulk density, surface area, and surface energy, and their impact on the manufacturability and bioavailability of the drug product are explored in Chapter 7. The bulk density models achieved a high performance of 82%, the surface area models achieved a performance of 80%, and finally, the surface-energy models achieved a performance of 60%. The results of the models presented in this chapter pave the way to unified guidelines moving towards end-to-end continuous manufacturing by linking the manufacturability requirements and the bioavailability requirements.Understanding how particle attributes affect the pharmaceutical manufacturing process performance remains a significant challenge for the industry, adding cost and time to the development of robust products and production routes. Tablet formation can be achieved by several techniques however, direct compression (DC) and granulation are the most widely used in industrial operations. DC is of particular interest as it offers lower-cost manufacturing and a streamlined process with fewer steps compared with other unit operations. However, to achieve the full potential benefits of DC for tablet manufacture, this places strict demands on material flow properties, blend uniformity, compactability, and lubrication, which need to be satisfied. DC is increasingly the preferred technique for pharmaceutical companies for oral solid dose manufacture, consequently making the flow prediction of pharmaceutical materials of increasing importance. Bulk properties are influenced by particle attributes, such as particle size and shape, which are defined during crystallization and/or milling processes. Currently, the suitability of raw materials and/or formulated blends for DC requires detailed characterization of the bulk properties. A key goal of digital design and Industry 4.0 concepts is through digital transformation of existing development steps be able to better predict properties whilst minimizing the amount of material and resources required to inform process selection during early- stage development. The work presented in Chapter 4 focuses on developing machine learning (ML) models to predict powder flow behaviour of routine, widely available pharmaceutical materials. Several datasets comprising powder attributes (particle size, shape, surface area, surface energy, and bulk density) and flow properties (flow function coefficient) have been built, for pure compounds, binary mixtures, and multicomponent formulations. Using these datasets, different ML models, including traditional ML (random forest, support vector machines, k nearest neighbour, gradient boosting, AdaBoost, Naïve Bayes, and logistic regression) classification and regression approaches, have been explored for the prediction of flow properties, via flow function coefficient. The models have been evaluated using multiple sampling methods and validated using external datasets, showing a performance over 80%, which is sufficiently high for their implementation to improve manufacturing efficiency. Finally, interpretability methods, namely SHAP (SHapley Additive exPlanaitions), have been used to understand the predictions of the machine learning models by determining how much each variable included in the training dataset has contributed to each final prediction. Chapter 5 expanded on the work presented in Chapter 4 by demonstrating the applicability of ML models for the classification of the viability of pharmaceutical formulations for continuous DC via flow function coefficient on their powder flow. More than 100 formulations were included in this model and the particle size and particle shape of the active pharmaceutical ingredients (APIs), the flow function coefficient of the APIs, and the concentration of the components of the formulations were used to build the training dataset. The ML models were evaluated using different sampling techniques, such as bootstrap sampling and 10-fold cross-validation, achieving a precision of 90%. Furthermore, Chapter 6 presents the comparison of two data-driven model approaches to predict powder flow: a Random Forest (RF) model and a Convolutional Neural Network (CNN) model. A total of 98 powders covering a wide range of particle sizes and shapes were assessed using static image analysis. The RF model was trained on the tabular data (particle size, aspect ratio, and circularity descriptors), and the CNN model was trained on the composite images. Both datasets were extracted from the same characterisation instrument. The data were split into training, testing, and validation sets. The results of the validation were used to compare the performance of the two approaches. The results revealed that both algorithms achieved a similar performance since the RF model and the CNN model achieved the same accuracy of 55%. Finally, other particle and bulk properties, i.e., bulk density, surface area, and surface energy, and their impact on the manufacturability and bioavailability of the drug product are explored in Chapter 7. The bulk density models achieved a high performance of 82%, the surface area models achieved a performance of 80%, and finally, the surface-energy models achieved a performance of 60%. The results of the models presented in this chapter pave the way to unified guidelines moving towards end-to-end continuous manufacturing by linking the manufacturability requirements and the bioavailability requirements

A Europa da defesa : o fim do limbo

O presente artigo tem por objectivo examinar a sucessão de iniciativas europeias, levadas a cabo nos últimos cinquenta anos, tendentes à emergência de uma dimensão de integração nos domínios da segurança e defesa. Partindo da identificação das raízes históricas da aspiração da defesa comum nos primórdios do processo de construção europeia, assim como, do seu retumbante fracasso, este estudo procura aferir as circunstâncias político-diplomáticas que condicionaram o ressurgimento daquela ambição em 1992, no quadro da Política Externa e de Segurança Comum, e o seu subsequente reforço no âmbito da Política Europeia de Segurança e Defesa. O principal argumento deste estudo compagina-se com a ideia de que durante a primeira década do pós-Guerra Fria, por acção de inesperadas forças históricas e da convergência de vontade política, a questão da defesa europeia comum saiu irreversivelmente do seu estado de limbo histórico para integrar a psique dos líderes europeus e o topo da agenda comunitári

Estudio de los niveles de ácido docosahexaenoico (22:6n-3) en macrófagos peritoneales de ratón

Los ácidos grasos poliinsaturados (PUFAs) son ácidos grasos que contienen más de dos dobles enlaces en su cadena carbonada y son considerados importantes nutrientes bioactivos que regulan muchas condiciones fisiológicas. Las dos familias de PUFAs de mayor relevancia para la salud y nutrición humana, son la familia de los omega-6 (o n-6) y la de los omega-3 (o n-3). Esta diferenciación se basa en la localización del primer doble enlace a partir del grupo metilo terminal. Así, para los ácidos grasos omega-6, dicho doble enlace se encuentra entre el sexto y séptimo átomo de carbono, mientras que para los ácidos grasos omega-3 se sitúa entre el tercer y cuarto átomo de carbono.Máster en Investigación Biomédic

Nísia Floresta, trajetória de uma educadora, abolicionista e defensora da educação feminina no século XIX

1º Congresso Internacional Epistemologias do Sul: perspectivas críticas - 7 a 9 de novembro de 2016, realizada pela Universidade Federal da Integração Latino-Americana (UNILA).Este trabalho tem por objetivo apresentar a que é considerada por autores como Constância Lima Duarte (1995), a primeira representante feminista brasileira, Dionísia Gonçalves Pinto, que mais tarde se chamaria Nísia Floresta Brasileira Augusta, uma mulher preocupada e sensibilizada com as injustiças que aconteciam na sua época e que atentavam, entre tantas ocorrências, à intelectualidade do gênero feminino. E ainda, segundo Duarte (2008, p.100), parece ser que Nísia Floresta também foi uma das primeiras mulheres no Brasil a se manifestar publicamente contra o sistema escravocrata, ao lado de Maria Firmina do Reis (1825–1917). A ausência de estudos sobre Nísia Floresta e o ineditismo dos seus livros em uma época de silêncio intelectual para as mulheres justificam esta pesquisa

Mechanical characterization of cervical tissue

A multi-scale constitutive model for the nonpregnant cervical tissue is presented. The mechanical response of the cervix is described by a model which takes into account material properties at different structural hierarchies of tissue through a multi-scale coupling scheme. The model introduces the deformation mechanisms of collagen fibrils at the microscale into a macroscopic continuum description of the mechanical behavior of tissue. The mechanical behavior of the cervix is governed by the directional structures in the collagen fiber architecture. The prefer- entially aligned fibers are responsible for the typical anisotropic behavior to the material and the solid matrix (ground substance) originates its incompressible response. The model assumes uncoupled contributions of the matrix and collagen fibers. The matrix is modeled as a simple isotropic material. On the other hand, results from a constitutive model of randomly crimped collagen fibers are used to modeled the fibrous part, and a parameter to quantify the stochastic dispersion of the collagen orientation is introduced. The collective mechanical behavior of collagen fibers is presented in terms of an explicit expression for the strain-energy function (SEF). And at the macro-scale, the constitutive response of the cervical tissue is formulated by homogenizing a fiber-reinforced material. Non-destructive evaluation using ultrasonic signals is a well-established method to obtain physically relevant mechanical parameters. This work aims to understand the ultrasonic transmission through soft tissues, in order to develop a useful tool to quantify mechanical parameters, which may be applied as a future diagnosis method. To this end, experimental ultrasound measurements were carried out in soft tissue samples, as well as simulations by finite difference time-domain method. Finally, a comparative study between experimental and simulated signals is presented. Results show the ability to describe the mechanical behavior of the cervical tissue like a fiber reinforced material, and that the ultrasonic wave propagation phenomena can be exploited to reconstruct the mechanical properties of soft tissues, and thus to diagnose pathologies that manifest by tissue consistency changes.Se presenta un modelo constitutivo multi-escala para el tejido cervical de mujeres no embarazadas. La respuesta mecánica del cuello del útero se describe por un modelo que tiene en cuenta las propiedades del material en las diferentes jerarquías estructurales del tejido a través de un esquema de acoplamiento multi-escala. El comportamiento macromecánico del tejido introduce los mecanismos de deformación de la fibras de colágeno que ocurren en la escala microscópica. Las direcciones preferentes de las fibras de colágeno rigen el comportamiento mecánico del cervix, creando el comportamiento anisotrópico típico del tejido, siendo la matriz (sustancia fundamental) la responsable de su respuesta incompresible. El modelo supone contribuciones desacoplados para la matriz y las fibras de colágeno. La matriz se modela como un material isotrópico sencillo. Por otro lado, se utiliza un modelo constitutivo de fibras onduladas de colágeno para la parte fibrosa, donde se introduce un parámetro para cuantificar la dispersión estocástica en la orientación de las fibras. El comportamiento colectivo de las fibras de colágeno se presenta en términos de potencial de energía de deformación (SEF). La respuesta constitutiva del tejido cervical en la macro escala se formula para la homogeneización de un material reforzado con fibras. La evaluación no destructiva utilizando señales ultrasónicas es un método reconocido para obtener parámetros mecánicos físicamente pertinentes. Este trabajo tiene tiene como objetivo comprender la transmisión de ultrasonidos a través de los tejidos blandos, para conseguir una herramienta útil para cuantificar los parámetros mecánicos y convertirse en la base de un futuro método de diagnóstico. Se han realizado medidas experimentales con ultrasonidos y una simulación por el método de las diferencias finitas en muestras de tejido blando. Finalmente, se presenta un estudio comparativo entre las señales experimentales y simuladas. Los resultados muestran la capacidad de describir el comportamiento mecánico del tejido del cuello uterino como un material reforzado con fibras, y que los fenómenos de propagación de ondas ultrasónicas pueden ser explotados para reconstruir las propiedades mecánicas de los tejidos blandos por los que viajan, y por lo tanto, como herramienta para el diagnóstico de patologías que se manifiestan por cambios en la consistencia de los tejidos.Universidad de Granada. Departamento de Mecánica de Estructuras e Ingeniería Hidráulica. Máster Universitario en Estructuras, curso 2010-2011This work has been supported by the Ministry of Science and Innovation of Spain through FPI grant BES-2011-044970 within Proyect number DPI2010-17065 (MICINN)

The European Union’s partnership policy towards Brazil: more than meets the eye

Published online: 27 Nov 2015This article focuses on the evolving nature of the foreign policy of the European Union (EU) towards Brazil, which gained momentum and became more dynamic and denser after the establishment of a formal strategic partnership (SP) in 2007. It provides a historical overview of the institutional relations between Brussels and Brasília, before proceeding with an analysis of the main drivers behind this novel development. The study goes on to offer a critical examination of the implementation of the EU–Brazil SP by casting light on both its major achievements and the challenges it has faced. It concludes that the establishment of a formal strategic partnership with Brazil has contributed to the strengthening of the EU’s globally oriented partnership policy and ultimately to the incremental empowerment of the EU necessary to the assertion of its values, objectives and interests on the international stage.This article is part of a research project entitled 'The Strategic Partnerships of the European Union as an Instrument of Global Action: Rationale and Implications' (PTDC/CPJ-CPO/11325/2009), funded by the Portuguese Foundation of Science and Technology (FCT) and coordinated by Laura C Ferreira-Pereira. The author wishes to express her thanks to Joao Mourato Pinto for his assistance in the bibliographical researching of the topic. She would also like to thank Gelson Fonseca Junior, Janina Onuki, Carlos Eduardo Lins da Silva, Sergio Fausto, Alena Vysotskayaa G Vieira and three anonymous referees for insightful comments on an earlier draft of this work. Finally, the author gratefully acknowledges the insightful comments made by former high-ranking diplomats and Brazilian foreign policy experts during interviews conducted under conditions of anonymity

EU-Brazil relations as a developing field of study: state-of-the-art and perspectives on future Research

[Excerpt] Brazil’s recent rise in the political, economic and trade spheres has prompted the European Union (EU) to recalibrate its traditional relations with the country so as to match the former’s status as a twenty-first century ‘emerging power’ with international ambitions whilst circumventing the protracted EU–Mercosur free trade agreement.(undefined

English as a Vehicle for Citizenship Education

O presente estudo, inserido no âmbito do estágio do Mestrado em ensino de Inglês no 1º ciclo do ensino básico, desenvolvido numa escola portuguesa do 1º ciclo teve como objectivo responder às seguintes questões: ‘Como desenvolver a educação para a cidadania na aula de Inglês?’; ‘Será que quando a educação para a cidadania é explicita na aula de Inglês promove atitudes/pensamentos positivos em relação ao outro?’; e ‘Como posso desenvolver a minha prática de contar histórias?’. O estudo foi conduzido durante três meses, no primeiro período escolar, envolvendo um grupo de 23 alunos com idades compreendidas entre os 8 e os 9 anos no 3º ano do primeiro ciclo. Como metodologia de investigação foi usada uma pesquisa de acção em pequena escala. O estudo implicou uma abordagem qualitativa e quantitativa na recolha de dados que consistiu num diário e reflexões do professor, questionários, reflexões dos alunos e discussão na aula. Os resultados foram positivos, sendo que responderam, com sucesso, às três questões deste estudo. O estudo respondeu positivamente à primeira pergunta (Como desenvolver a educação para a cidadania na aula de Inglês?), na medida em que o passaporte, a história, a sua leitura e discussão, e o livro (mini book) se revelaram eficazes para desenvolver a educação para a cidadania na aula de Inglês. A segunda questão (Será que quando a educação para a cidadania é explicita na aula de Inglês promove atitudes/pensamentos positivos em relação ao outro?) teve como resposta atitudes positivas, demonstradas pelos alunos, quer nos inquéritos quer na discussão da história, no que respeita à aceitação dos outros e das suas diferenças. O estudo respondeu à questão três (Como posso desenvolver a minha prática de contar histórias?) ajudando a professora a desenvolver a sua capacidade para contar histórias na disciplina de Inglês. A professora desenvolveu técnicas para contar histórias e percebeu que estratégias podem resultar num melhor entendimento da história. Os questionários demonstraram uma alteração das atitudes dos alunos, tanto em relação à sua perceção acerca das histórias e do que podem aprender com elas, mas também como as mesmas podem, na disciplina de Inglês, ter um papel importante no ensino de temas como a educação para cidadania. Este estudo demonstrou que os professores devem ser encorajados a desenvolver a educação para a cidadania na disciplina de Inglês e que as histórias em Inglês são um veículo de promoção, não somente da língua, mas também da cidadania.The present study, inserted in the scope of the master's degree in the English teaching in the 1st cycle of basic education, developed in a Portuguese school of the 1st cycle, had as a main goal to answer the following questions: ‘How can I develop citizenship education in the English classroom?’; ‘Does making citizenship education more explicit during English lessons promote positive attitudes/thoughts in relation to the other?’; ‘How can I develop as a teacher storyteller?’. The study was conducted for three months, in the first school period, involving a group of 23 students aged between 8 and 9 years old in the 3rd year of the first cycle. As the investigation methodology, a small-scale action research was used. The study implied a qualitative and quantitative approach to the collection of data that consisted of reflections from the teacher, student questionnaires, and reflections and discussion in class. The results were positive and contributed to answering the three questions of this study. The activities in the study seemed to be effective for developing citizenship education in the English class, children demonstrated positive attitudes towards each other, respecting and accepting others and their differences. My storytelling skills also improved, as I learnt storytelling techniques and realized what strategies can result for a better understanding of the story. In addition, the data collected suggests a change in the student's attitudes in relation to their perception of stories and what they can learn from them. This study demonstrated that teachers should be encouraged to develop citizenship education in English classes and that storytelling in English is an appropriate vehicle to develop both language and citizenship