Environment, health and safety policy in small construction sites: an analysis of the situation in Brazil

This paper analyzes the safety, environmental and occupational health of workers in the small construction industry in Brazil. In this sector there are still many unsafe practices, which are very common in small work sites. We used a qualitative approach to understand these problems by long interviews with people who work directly in small construction sites, including occupational physicians, civil engineers, safety engineers, safety technicians, general foremen, construction workers, labor unionists and auditors. This paper aims to demonstrate that the "invisibility" of the small sites workers makes them less safe and therefore more prone to accidents, also weakening their health. The results show that small constructions workers are less visible to society and supervision because of their short periods of work. Therefore, they are also uncovered to the rigorous applicability of principles of safety and accident prevention. Thus, it has been seen in this field of work a precarious application of NR - 18, which was specifically made for the construction sites and it needs simplification to meet normative characteristics of small construction sites. In the State of Rio de Janeiro, some laws on small sites were recently created and implemented. This study concludes that the rules to work are not being taken as seriously as the legislation determinates, remaining practically unknown by many professionals, from the plot command, supervisors, engineers, architects and technicians who work on construction sites. This ignorance creates space for the lack of safety and consequently to accidents, leading to by weakness in the workers health. Therefore, the work process needs to be modified, the safety regulation must be disseminated through safer practices, promoting employee health and ensure that the work of small sites can be visible, especially ensuring the construction workers health and safety.

La dimensione di diritto fondamentale della maternità nel Diritto dell’Unione: politiche europee di conciliazione della vita famigliare e della vita professionale in tempo di crisi

Dissertação de mestrado em Direito da União Europeia

Para um (novo) modelo de intervenção penal na União Europeia: uma reflexão a partir do princípio de legalidade como limite material de atuação da Procuradoria Europeia

Tese de Doutoramento em Ciências Jurídicas (área de especialização em Ciências Jurídicas - Públicas)

A soft computing approach to kidney diseases evaluation

Kidney renal failure means that one’s kidney have unexpectedly stopped functioning, i.e., once chronic disease is exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapid deterioration of the renal function, but is often reversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis.The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow one to consider incomplete, unknown, and even contradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

Tribunais nacionais e tutela jurisdicional efetiva: da cooperação à integração judiciária no contencioso da união europeia

Tese de Doutoramento em Ciências Jurídicas (área de especialização em Ciências Jurídicas Públicas).

Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

An assessment of chronic kidney diseases

Kidney renal failure means that one’s kidney have unexpectedlystoppedfunctioning,i.e.,oncechronicdiseaseis exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapiddeteriorationoftherenalfunction,butisoftenreversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis. The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow onetoconsiderincomplete,unknown,and evencontradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

An evaluation of parchments' degradation a hybrid approach

Parchment stands for a multifaceted material made from animal skin, which has been used for centuries as a writing support or as bookbinding. Due to the historic value of objects made of parchment, understanding their degradation and their condition is of utmost importance to archives, libraries and museums, i.e., the assessment of parchment degradation is mandatory, although it is hard to do with traditional methodologies and tools for problem solving. Hence, in this work we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate Parchment Degradation and the respective Degree-of-Confidence that one has on such a happening.

Thrombophilia screening: An artificial neural network approach

Thrombotic disorders have severe consequences for the patients and for the society in general, being one of the main causes of death. These facts reveal that it is extremely important to be preventive; being aware of how probable is to have that kind of syndrome. Indeed, this work will focus on the development of a decision support system that will cater for an individual risk evaluation with respect to the surge of thrombotic complaints. The Knowledge Representation and Reasoning procedures used will be based on an extension to the Logic Programming language, allowing the handling of incomplete and/or default data. The computational framework in place will be centered on Artificial Neural Networks.

Artificial neural networks in diagnosis of liver diseases

Liver diseases have severe patients’ consequences, being one of the main causes of premature death. These facts reveal the centrality of one`s daily habits, and how important it is the early diagnosis of these kind of illnesses, not only to the patients themselves, but also to the society in general. Therefore, this work will focus on the development of a diagnosis support system to these kind of maladies, built under a formal framework based on Logic Programming, in terms of its knowledge representation and reasoning procedures, complemented with an approach to computing grounded on Artificial Neural Networks.

Logic programming and artificial neural networks in breast cancer detection

About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.

A educação como empoderamento na ótica do desenvolvimento: uma discussão de modelos

Apresentamos nesta comunicação uma tese de ressignificação da educação como empoderamento tendo como foco uma agenda de desenvolvimento justo, digno e inclusivo, e equacionamos os seus principais tipos ou modelos, partindo do princípio que o empoderamento, pelo facto de remeter para diversas conotações ideológicas, não permite almejar consensos quando se trata de o tomar como sinal distintivo ou imagem de marca de uma educação cuja aposta principal é a promoção de um desenvolvimento humano verdadeiramente empenhado em corresponder às expectativas normativas das pessoas em termos de justiça, respeito, dignidade, liberdade e direitos fundamentais para todos.

Brazilian norms for the International Affective Picture System (IAPS): comparison of the affective ratings for new stimuli between Brazilian and North-American subjects

OBJECTIVE: The study presents the Brazilian norms for 240 new stimuli from International Affective Picture System (IAPS), a database of affective images widely used in research, compared to the North-American normative ratings. METHODS: The participants were 448 Brazilian university students from several courses (269 women and 179 men) with mean age of 24.2 (SD = 7.8), that evaluated the IAPS pictures in the valence, arousal and dominance dimensions by the Self-Assessment Manikin (SAM) scales. Data were compared across the populations by Pearson linear correlation and Student's t-tests. RESULTS: Correlations were highly significant for all dimensions; however, Brazilians' averages for arousal were higher than North-Americans'. CONCLUSIONS: The results show stability in relation to the first part of the Brazilian standardization and they are also consistent with the North-American standards, despite minor differences relating to interpretation of the arousal dimension, demonstrating that IAPS is a reliable instrument for experimental studies in the Brazilian population.

Associations, causation and model in psychiatry

This paper discusses models, associations and causation in psychiatry. The different types of association (linear, positive, negative, exponential, partial, U shaped relationship, hidden and spurious) between variables involved in mental disorders are presented as well as the use of multiple regression analysis to disentangle interrelatedness amongst multiple variables. A useful model should have internal consistency, external validity and predictive power; be dynamic in order to accommodate new sound knowledge; and should fit facts rather than they other way around. It is argued that whilst models are theoretical constructs they also convey a style of reasoning and can change clinical practice. Cause and effect are complex phenomena in that the same cause can yield different effects. Conversely, the same effect can have a different range of causes. In mental disorders and human behaviour there is always a chain of events initiated by the indirect and remote cause; followed by intermediate causes; and finally the direct and more immediate cause. Causes of mental disorders are grouped as those: (i) which are necessary and sufficient; (ii) which are necessary but not sufficient; and (iii) which are neither necessary nor sufficient, but when present increase the risk for mental disorders.

Redes interorganizacionais nas políticas públicas: atores, conexões e configurações organizacionais

Tese de Doutoramento em Sociologia