Italic votive terracotta heads from the British Museum : a stylistic appraisal in their religious and historical settings

The thesis aims to examine a collection of Italic votive terracotta heads, dated between the early 4th and the late 2nd centuries B.C., in the British Museum. The study proposes a stylistic appraisal of the terracotta heads in their religious and historical settings divided into three parts. The first part includes the introduction and five chapters. In the first chapter is discussed the religious background: Greek healing gods) Italic and Roman healing cults and Aesculapios. The second chapter is concerned with the religiousness of the Italic peoples: their devoutness; the cults; the practice of the caput velatum. Chapter three deals with the notion of votive offering in the ancient world: the origin; in the Greek religious sphere; the votive offerings as an exchange, as substitution, as gifts; their place in the sanctuary; in the Italic religious sphere and their distribution on the Italian territory; the specialisation of sanctuaries; the anatomical ex-votos; miniaturisation of votives as substitution; fertility, puberty and well-being. Chapter four deals with ancient medicine and the anatomical votives: the dawn of medical science; the evidence of the anatomical votives; medical interpretation of the votives; representation of diseased organs. In chapter five are considered the sanctuary and the worshippers: the types of sanctuaries; the identification and location of sanctuaries; the evidence for healing cults; the votive deposits; the appearance and disappearance of anatomical votive terracottas; the historical background. The second part includes three chapters. Chapters ix considers the various stylistic influences: in pre-Roman Etruria; in central and southern Italy; the Roman influence; copies of famous sculptures and their relationship with votive terracottas. Chapter seven is a survey of the jewellery displayed on the female heads: crowns; diadems; earrings; necklaces. Chapter eight is a survey of the hairstyles displayed on both female and male heads. Chapter nine examines the technique of manufacture of the votive heads: the problems of mass-production; the workshops and the artisans; the specific, heads in the British Museum. The third part of this study includes an extensive catalogue of the female and male heads divided into groups according to their stylistic affinities. The catalogue is introduced by a section on the classification and terminology. The thesis is concluded by a synopsis of the focal points of part one and two integrated by the observations on the groups of heads in the catalogue

Modelling the effects of wood cambial age on the effective modulus of elasticity of poplar laminated veneer lumber

Key messageA modelling method is proposed to highlight the effect of cambial age on the effective modulus of elasticity of laminated veneer lumber (LVL) according to bending direction and veneer thickness. This approach is relevant for industrial purposes in order to optimize the performance of LVL products.ContextLVL is used increasingly in structural applications. It is obtained from a peeling process, where product’s properties depend on cambial age, hence depend on radial position in the log.AimsThis study aims to highlight how radial variations of properties and cambial age impact the mechanical behaviour of LVL panels.MethodsAn analytical mechanical model has been designed to predict the modulus of elasticity of samples made from poplar LVL panels. The originality of the model resides in the integration of different data from the literature dealing with the variation in wood properties along the radius of the log. The simulation of the peeling process leads to veneers with different mechanical properties, which are randomly assembled in LVL panels.ResultsThe model shows a correct mechanical behaviour prediction in comparison with experimental results of the literature, in particular with the decrease in MOE in LVL made of juvenile wood. It highlights that the bending direction and veneer thickness have no influence on the average MOE, but affect MOE dispersion.ConclusionThis paper proposed an adequate model to predict mechanical behaviour in the elastic domain of LVL panels based on the properties of raw wood material.ANR xyloforest, région Bourgogne franche-comt

TAKING CARE OF THE SICK ELDER PEOPLE AT HOME IN THE SPEECH OF FAMILIAL CARE TAKER

This investigation is about an exploratory, descriptive and in a qualitative approach study, which hadas its objective to know how the choice of the sick elderly peoples familial caretaker occurs and how the caretakerfeels in this role. The main caretaker was interviewed in home visits. The sample was constituted of nine familialcaretakers, mainly from the female sex: wives, daughters, daughters-in-law, granddaughters, and the husband. Forthe analysis of the data, the content analysis, following the methodological steps of Minayo, was used. Twoanalytical categories were elaborated: being a familial caretaker: is it an option or an obligation?, which shows thatthe choice of taking care is closely related to the feeling of obligation, but also to affection relations, gratitude andthe impossibility of choosing another caretaker, and being a sick elderly peoples familial caretaker that approachesfeelings of gratitude, resignation, inexperience in face of the care demands, physical and emotional tiredness, lossof freedom and solitude due to the activity in the caretaker

Développement d'un modèle logiciel de cellule sur processeurs multi-cœurs pour la simulation de morphogenèse de tissus

The main purpose of this thesis is to present tools built in order to numerically study the development of cellular tissues through an individual-based approach that includes biomechanical elements as well as an artificial chemistry. The objective of such proposals is to gain a better understanding of the mechanisms that rule the development of multicellular tissues using numerical simulation as a complement to in vitro and in vivo experiments. This objective is difcult to achieve. However technological means in the field of cellular and molecular biology allow the observation and the gathering of many data. Moreover, the development of multi-core devices allows the simulation of complex systems, such as multi-cellular systems. Multi-cellular systems exhibit mainly two levels of complexity : the first one concerns the potentially large amount of cells they contain, which requires a considerable computing power when this point is addressed through individual-based approach; the second level concerns the diversity of biological cells’ behaviors. This level requires specific algorithms, for example to deal with complex behavior such as mitosis. The conception of 1) models that integrate biological data and 2) dedicated algorithms adapted to heterogenous and multi-core devices make it possible to solve, at least to some extent, these two levels of complexity. In order to numerically study both healthy and pathological tissue developpement, we propose two elements. The first is a biomechanical cell model that includes the behaviors involved in tissue morphogenesis (mitosis, diferentiation, adhesion, migration, cell-cell signaling and apoptosis). The second element is a parallel simulator that relies on a non-specialized software architecture and on dedicated data structures and algorithms used to benefit from the power of multi-core hardware. In this document, we present several case studies that gives some validation elements of both our model and our simulator.L’objectif principal de cette thèse est de proposer des outils permettant l’étude numérique du développement de tissus cellulaires à travers une approche individus-centrée comprenant des aspects biomécaniques et chimiques. De telles propositions doivent permettre de mieux comprendre les mécanismes régissant le développement de tissus multi-cellulaires grâce à la simulation numérique, en complément d’expérimentations in vitro et in vivo. La réalisation de ces objectifs est difficile, mais les avancées dans les domaines de la biologie cellulaire et moléculaire permettent l’observation et la collecte d’un grand nombre de données. En outre, le développement de matériels parallèles permet la simulation de systèmes complexes tels que des systèmes multi-cellulaires. Les systèmes multi-cellulaires exhibent essentiellement deux niveaux de complexité lorsque l’on souhaite les simuler: le premier concerne le nombre potentiellement très important de cellules qu’ils contiennent, nécessitant alors une grande puissance de calcul; le second concerne la multiplicité des comportements des cellules vivantes, tant au niveau individuel que collectif, ce qui requiert des algorithmes bien spécifiques. La conception de modèles, intégrant à la fois des données biologiques pertinentes, des algorithmes adaptés et reposant sur des processeurs puissants permet de résoudre, au moins en partie, ces deux niveaux de complexité, mais doivent reposer sur une architecture logicielle dédiée. Dans l’idée d’étudier, en simulation numérique, le développement de tissus sains et pathologiques, nos travaux apportent deux éléments. Le premier est un modèle biomécanique de cellule virtuelle comportant des processus impliqués dans la morphogenèse de tissus tels que la division, la différentiation, l’adhésion, la migration, la signalisation et l’apoptose. Le second est un simulateur parallèle reposant sur une architecture logicielle généraliste ainsi que sur des structures de données et des algorithmes originaux permettant d’exploiter la puissance de calcul offerte par les matériels multi-cœurs. Nous présentons dans ce mémoire plusieurs cas d’études qui permettent d’apporter des éléments de validation sur la réalisation de notre modèle et de notre simulateur

Efficiency of use of alternative foods to inducing molt.

Projeto/Plano de Ação: 11.11.11.111

Efeitos do treinamento combinado e do treinamento de força sobre o comprometimento cognitivo em idosos : uma revisão descritiva

A idade é o principal fator para doenças crônicas como por exemplo, as neurodegenerativas. Nos últimos anos ocorreu um aumento exponencial no número de pessoas idosas. Então, estudos com estratégias para prevenir doenças cognitivas se tornaram cruciais. Desta forma, o objetivo desta revisão é avaliar os efeitos do treinamento de força (TF) e do treinamento combinado (TC) sobre a cognição de idosos com comprometimento cognitivo leve a severo. Três bases de dados foram analisadas através de termos relacionados aos idosos: TC, TF e cognição. Os estudos que foram selecionados incluindo como intervenção o TC e o TF, analisaram a cognição de idosos com comprometimentos cognitivos. Os resultados encontrados mostram que ambos os métodos de treinamento promovem melhoras na cognição de idosos com esses comprometimentos. Entretanto, a realização do TC promove melhoras cognitivas mais relevantes do que o TF isolado em idosos. Além disso, interrupções de intervenção maiores, como 12 meses e, com volume e definição para o estágio da doença resulta em melhor relevância.Age is the main factor for chronic diseases such as the neurodegenerative ones. In recent years it has been an exponential increase of the number of elderly people, which made crucial the need of studies with strategies to prevent cognitive diseases. Therefore, the aim of this resume is to evaluate the effects of strength training (SF) and combined training (CT) on the cognition of elderly people with mild to severe cognitive issues. Three databases were analyzed using terms related to the elderly, CT, ST and cognition. The selected studies included CT and ST as intervention and analyzed the cognition of elderly people with cognitive problems. The results found out that both training methods promote improvements in the cognition of elderly people with these issues. However, the performance of CT promotes more relevant improvements more than isolated TF in elderly people with cognitive issues. Furthermore, intervention interruptions longer than 12 months and with volume and definition for the stage of the disease are better relevance

Modelo classificador preditivo para avaliação da carga de trabalho de enfermagem : uma análise secundária de Big Data

Introdução: a avaliação da carga de trabalho de enfermagem é utilizada sistematicamente como parâmetro para o dimensionamento adequado de pessoal e para a gestão assistencial, por isso é importante investir em soluções inovadoras para transformar os sistemas de classificação de pacientes em modelos ágeis, objetivos e que possam ser automatizados. Objetivos: desenvolver um modelo classificador preditivo para avaliação da carga de trabalho de enfermagem, com base em registros do prontuário eletrônico de pacientes adultos hospitalizados. Identificar padrões nos dados que caracterizam a dependência de pacientes dos cuidados de enfermagem. Método: estudo observacional retrospectivo, em fontes secundárias de registros eletrônicos de pacientes, com uso de aprendizado supervisionado de máquina. O cenário do estudo incluiu doze unidades clínico-cirúrgicas de um hospital universitário de alta complexidade, que tem como pilares a assistência, o ensino e a pesquisa de excelência, além de uma cultura voltada para a qualidade, segurança e inovação. A amostra por conveniência constituiu-se de 43.871 avaliações de pacientes realizadas por enfermeiras assistenciais com o Sistema de Classificação de Pacientes de Perroca, que serviram como padrão ouro, e dados clínicos estruturados do prontuário eletrônico de 11.774 pacientes, do período 2015 a 2019, que constituíram as variáveis de interesse. A logística dos dados seguiu as etapas do Knowledge Discovery in Databases: estruturação do banco de dados analítico, mineração de dados com o algoritmo Random Forest e identificação de padrões nas variáveis que geraram o modelo classificador. Para a organização e análise dos dados foi utilizada a plataforma de ciência de dados Dataiku® e o software de processamento de Big Data PostgreSQL®. A análise dos dados ocorreu de forma exploratória, descritiva e preditiva. Resultados: a maioria dos pacientes do grande conjunto de dados concentrou-se na classe de cuidados semi-intensivos do Sistema de Classificação de Pacientes de Perroca. As variáveis que mais contribuíram para a predição em cada classe do modelo foram: o tempo de internação nos cuidados mínimos, o cuidado de enfermagem realizar banho de leito nos cuidados intermediários, o diagnóstico de enfermagem risco de quedas nos cuidados semi-intensivos e o cuidado de enfermagem implementar protocolo de prevenção e tratamento de feridas nos cuidados intensivos. O algoritmo classificou corretamente 72% das variáveis e a área sob a curva ROC foi 82%. Conclusão: o uso de algoritmo de aprendizado supervisionado de máquina possibilitou o desenvolvimento do modelo classificador de avaliação da carga de trabalho de enfermagem com dados do prontuário eletrônico do paciente. O Randon Forest identificou os padrões nos dados que caracterizam a dependência de pacientes dos cuidados de enfermagem, categorizando as variáveis nas classes às quais pertencem e demonstrando que técnicas de inteligência artificial podem ser efetivas para a automatização desta atividade.Introduction: Nursing workload assessments are systematically used as a parameter for adequate staffing and for care management; for this reason, it is important to invest in innovating solutions to turn patient classification systems into dynamic and objective models capable of being automated. Objectives: to develop a predictive classification model for Nursing workload assessments, based on electronic medical records of hospitalized adult patients, as well as to identify patterns in the data that characterize patients' dependence on Nursing care. Method: an observational and retrospective study conducted in secondary sources consisting of patients' electronic medical records, using supervised machine learning. The study setting included twelve clinical-surgical units of a high-complexity university hospital, with excellence in assistance, teaching and research as pillars, in addition to a culture targeted at quality, safety and innovation. The convenience sample was comprised by 43,871 evaluations of patients performed by clinical care nurses with the Perroca Patient Classification System, which served as the gold standard, as well as with structured clinical data from the electronic medical records of 11,774 patients from 2015 to 2019, which constituted the variables of interest. Data logistics followed the stages set forth in Knowledge Discovery in Databases: structuring of the analytical database, data mining with the Random Forest algorithm and identification of patterns in the variables that generate the classification model. The Dataiku® Data Science platform and the PostgreSQL® Big Data processing software program were used for data organization and analysis. Data analysis was exploratory, descriptive and predictive. Results: most of the patients from the Big Data set were concentrated in the semi-intensive care class from the Perroca Patient Classification System and the variables that most contributed to the prediction in each class of the model were as follows: hospitalization time in minimal care; nursing performing bed baths in intermediate care; risk of falls nursing diagnosis in semi-intensive care; and nursing implementing a wound prevention and treatment protocol in intensive care. The algorithm correctly classified 72% of the variables and the area under the ROC curve was 82%. Conclusion: using the supervised machine learning algorithm enabled developing the classification model for nursing workload assessments with data from patients' electronic medical records. The Random Forest identified the patterns in the data that characterize the patients' dependence on nursing care, categorizing the variables in the classes to which they belong and showing that artificial intelligence techniques can be effective to automate this activity.Introducción: las evaluaciones de la carga de trabajo en Enfermería se utilizan sistemáticamente como parámetro para dimensionar correctamente el personal y para la gestión asistencial; por ese motivo, es importante invertir en soluciones innovadoras con el fin de transformar los sistemas de clasificación de pacientes en modelos dinámicos, objetivos y que puedan automatizarse. Objetivos: desarrollar un modelo predictivo de clasificación para evaluaciones de la carga de trabajo en Enfermería, sobre la base de registros de historias clínicas de pacientes adultos internados, al igual que identificar patrones en los datos que caracterizan la dependencia de los pacientes en la atención de Enfermería. Método: estudio observacional y retrospectivo realizado en fuentes secundarias conformadas por historias clínicas electrónicas de pacientes, empleando aprendizaje automático supervisado. El escenario del estudio incluyó doce unidades clínico-quirúrgicas de un hospital universitario de alta complejidad, cuyos pilares son asistencia, enseñanza e investigación de excelencia, además de una cultura dirigida a la calidad, la seguridad y la innovación. La muestra por conveniencia estuvo compuesta por 43.871 evaluaciones de pacientes realizadas por enfermeras asistenciales con el Sistema de Clasificación de Perroca, que sirvieron como patrón de oro, al igual que por datos clínicos estructurados de las historias clínicas de 11.774 pacientes entre 2015 y 2019, que constituyeron las variables de interés. La logística de los datos siguió las etapas indicadas en Knowledge Discovery in Databases: estructuración de la base de datos analítica, minería de datos con el algoritmo Random Forest e identificación de patrones en las variables que generan el modelo de clasificación. Para organizar y analizar los datos se utilizaron la plataforma de Ciencia de Datos Dataiku® y el programa de software de procesamiento de Big Data PostgreSQL®. El análisis de los datos se realizó en forma exploratoria, descriptiva y predictiva. Resultados: la mayoría de los pacientes del conjunto de Big Data se concentró en la clase de cuidados semi- intensivos del Sistema de Clasificación de Pacientes de Perroca y las variables que más contribuyeron a las predicciones en cada clase del modelo fueron las siguientes: tiempo de internación en cuidados mínimos; el hecho de que el personal de Enfermería higienizara pacientes en la cama en cuidados intermedios; el diagnóstico de enfermería riesgo de caídas en cuidados semi-intensivos; y el hecho de que el personal de enfermería implementara un protocolo de prevención y tratamiento de heridas en cuidados intensivos. El algoritmo clasificó correctamente el 72% de las variables y el área por debajo de la curva ROC fue del 82%. Conclusión: utilizar el algoritmo de aprendizaje automático aupervisado permitió desarrollar el modelo de clasificación para evaluaciones de la carga de trabajo en Enfermería con datos de las historias clínicas de los pacientes. El Random Forest identificó los patrones en los datos que caracterizan la dependencia de los pacientes en la atención de Enfermería, categorizando así las variables en las clases a las que pertenecen y demostrando que las técnicas de inteligencia artificial pueden ser efectivas para automatizar esta actividad

An analysis of scientific literature about the use of central venous catheters in hospitalized adults

Objective: to characterize the scientific production related to the use of central venous catheter for patients hospitalized adults. Method: A literature search with VHL, in databases BDENF, LILACS and SCIELO, using the keywords: central venous catheter and an adult. 11 articles were selected for analysis. Results: The production on the theme is developed mainly for medical journals published in this knowledge area, approaching the incidence of infections and associated factors. Other aspects discussed relate to the indications for use of the CVC, and insertion site complications. With respect to nursing care, to prevent and minimize the amount of infections and maintain the proper functioning of the catheter, highlight hand washing as a measure paramount. Conclusion: The low current scientific production of nursing focusing on this issue points to the need to resume the clinical aspects of daily care for the hospitalized patient