Programa de reabilitação neuropsicológica das funções excutivas após traumatismo cranioencefálico

Orientadora: Profª. Drª. Ana Paula Almeida de PereiraDissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Humanas, Programa de Pós-Graduação em Psicologia. Defesa: Curitiba, 02/09/2016Inclui referências : f. 172-174;178-185Resumo: O trauma cranioencefálico (TCE) apresenta-se como uma condição de alta morbidade física e psicológica, com consequências sociais devastadoras. O TCE é, hoje, um problema crítico enfrentado pelos sistemas de saúde, tendo em vista que o grupo de mais alto risco para TCE são homens em idade para trabalho, e cerca de 60% deles não retornam ao trabalho devido às alterações cognitivas secundárias às lesões cerebrais. O objetivo deste trabalho é aplicar uma metodologia de avaliação de eficácia de um programa de reabilitação neuropsicológica das funções executivas para pacientes após TCE. Esta pesquisa privilegia a obtenção de dados por meio de situações experimentais planejadas, por intermédio da estimulação das funções executivas e do nível de autoconsciência dos déficits. Foram avaliados 9 participantes, com idades entre 21 e 43 anos, com diagnóstico de TCE e destes, 6 finalizaram o programa de reabilitação neuropsicológica. Para a elaboração dessa pesquisa foi definida como variável independente a reabilitação das funções executivas e como variável dependente o nível de autoconsciência. Do ponto de vista formal, a pesquisa apresenta um delineamento voltado para estudos experimentais de caso único. Nesse delineamento, o efeito da variável independente sobre a variável dependente é observado pela comparação do desempenho do participante no decorrer das sessões, na qual as frequências de comportamentos eram analisadas e, em dois momentos distintos, com base na avaliação neuropsicológica efetuada nas situações antes e depois do tratamento experimental. Os resultados produziram dois estudos, sendo o primeiro de revisão de literatura e o segundo apresenta um estudo da eficácia de um programa de intervenção neuropsicológica. A revisão de literatura foi realizada de forma sistemática, abrangendo os anos de 2010 a 2015, e constatou uma relação muito generalizada entre funcionamento cognitivo e nível ocupacional, sendo, portanto, difícil afirmar quais fatores estão mais relacionados com o retorno ao trabalho após TCE. No segundo estudo os resultados apontam para uma relação entre treinamento de funções executivas e melhora do nível de autoconsciência dos déficts, além de produzir resultados positivos em relação à diminuição de sintomas psiquiátricos. Concluiu-se que, após TCE, é comum pessoas experenciarem dificuldades em retornar ao trabalho e, estas não costumam ser referenciadas para testagem neuropsicológica, mesmo que apresentem relação direta com disfunção executiva. O segundo estudo sugeriu que reabilitação neuropsicológica das funções executivas produziu melhora na autorregulação emocional em todos os participantes envolvidos e melhora no nível de autoconsciência dos déficits. Além disso, a proposta metodológica de avaliação de programas clínicos de intervenção neuropsicológica contribui com a possibilidade de demonstração da eficácia da neuropsicologia quando se trata de reabilitação de pacientes pós lesão, no que se refere à diminuição de comportamentos disexecutivos. Palavras-Chave: Intervenção Neuropsicológica, Traumatismo Cranioencefálico, Função Executiva, Autoconsciência, Avaliação de Programas de Saúde.Abstract: Traumatic brain injury (TBI) is presented as a high physical and psychological morbid condition, with devastating social consequences. The acquirid brain injury is now a critical problem faced by health systems, given that the group at highest risk for TBI are working age men, and about 60% of them do not return to work due to secondary cognitive changes after brain injury. The objective of this work is to apply an efficiency assessment methodology of a neuropsychological rehabilitation program of executive functions in patients after TBI. This research focuses on obtaining data through experimental situations planned, through the stimulation of the executive functions and deficits self level. Nine (9) participants were evaluated, aged between 21 and 43 years, diagnosed as having TBI and of these, 6 started the neuropsychological rehabilitation program. For the preparation of this study was defined as an independent variable the rehabilitation of executive functions and as dependent variable the level of self-awareness. The research presented a focus on an experimental study of a single case. The results produced two studies, and a literature review and the second presents an assessment of neuropsychological intervention program. The literature review was conducted systematically, covering the years 2010-2015, and found a very general relationship between cognitive functioning and occupational level, it is therefore difficult to say which factors are more related to the return to work after TBI. In the second study, the results pointed out to a relationship between training executive functions and improved self-awareness level, besides producing positive results regarding the reduction of psychiatric symptoms. The second study results suggested that neuropsychological rehabilitation of executive functions produced improvement in emotional self-regulation in all the participants involved and improvement in autoconsciências level of deficits. Furthermore, the proposed methodology for evaluating clinical programs neuropsychological intervention contributes to the possibility of demonstrating the effectiveness of neuropsychological when dealing with rehabilitation after injury patients, as regards the reduction of disexecutivos behavior. Key Words: neuropsychological intervention; traumatic brain injury, employability, executive function, self-awarness

SHIELD: Thwarting Code Authorship Attribution

Authorship attribution has become increasingly accurate, posing a serious privacy risk for programmers who wish to remain anonymous. In this paper, we introduce SHIELD to examine the robustness of different code authorship attribution approaches against adversarial code examples. We define four attacks on attribution techniques, which include targeted and non-targeted attacks, and realize them using adversarial code perturbation. We experiment with a dataset of 200 programmers from the Google Code Jam competition to validate our methods targeting six state-of-the-art authorship attribution methods that adopt a variety of techniques for extracting authorship traits from source-code, including RNN, CNN, and code stylometry. Our experiments demonstrate the vulnerability of current authorship attribution methods against adversarial attacks. For the non-targeted attack, our experiments demonstrate the vulnerability of current authorship attribution methods against the attack with an attack success rate exceeds 98.5\% accompanied by a degradation of the identification confidence that exceeds 13\%. For the targeted attacks, we show the possibility of impersonating a programmer using targeted-adversarial perturbations with a success rate ranging from 66\% to 88\% for different authorship attribution techniques under several adversarial scenarios.Comment: 12 pages, 13 figure

Eleven fetal echocardiographic planes using 4-dimensional ultrasound with spatio-temporal image correlation (STIC): a logical approach to fetal heart volume analysis

<p>Abstract</p> <p>Background</p> <p>Theoretically, a cross-sectional image of any cardiac planes can be obtained from a STIC fetal heart volume dataset. We described a method to display 11 fetal echocardiographic planes from STIC volumes.</p> <p>Methods</p> <p>Fetal heart volume datasets were acquired by transverse acquisition from 200 normal fetuses at 15 to 40 weeks of gestation. Analysis of the volume datasets using the described technique to display 11 echocardiographic planes in the multiplanar display mode were performed offline.</p> <p>Results</p> <p>Volume datasets from 18 fetuses were excluded due to poor image resolution. The mean visualization rates for all echocardiographic planes at 15-17, 18-22, 23-27, 28-32 and 33-40 weeks of gestation fetuses were 85.6% (range 45.2-96.8%, N = 31), 92.9% (range 64.0-100%, N = 64), 93.4% (range 51.4-100%, N = 37), 88.7%(range 54.5-100%, N = 33) and 81.8% (range 23.5-100%, N = 17) respectively.</p> <p>Conclusions</p> <p>Overall, the applied technique can favorably display the pertinent echocardiographic planes. Description of the presented method provides a logical approach to explore the fetal heart volumes.</p

International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) - the propagation of knowledge in ultrasound for the improvement of OB/GYN care worldwide: experience of basic ultrasound training in Oman.

BACKGROUND: The aim of this study is to evaluate effectiveness of a new ISUOG (International Society of Ultrasound in Obstetrics and Gynecology) Outreach Teaching and Training Program delivered in Muscat, Oman. METHODS: Quantitative assessments to evaluate knowledge and practical skills were administered before and after an ultrasound course for sonologists attending the ISUOG Outreach Course, which took place in November, 2017, in Oman. Trainees were selected from each region of the country following a national vetting process conducted by the Oman Ministry of Health. Twenty-eight of the participants were included in the analysis. Pre- and post-training practical and theoretical scores were evaluated and compared. RESULTS: Participants achieved statistically significant improvements, on average by 47% (p < 0.001), in both theoretical knowledge and practical skills. Specifically, the mean score in the theoretical knowledge test significantly increased from 55.6% (± 14.0%) to 81.6% (± 8.2%), while in the practical test, the mean score increased from 44.6% (± 19.5%) to 65.7% (± 23.0%) (p < 0.001). Performance was improved post-course among 27/28 participants (96.4%) in the theoretical test (range: 14 to 200%) and among 24/28 (85.7%) trainees in the practical skills test (range: 5 to 217%). CONCLUSION: Application of the ISUOG Basic Training Curriculum and Outreach Teaching and Training Course improved the theoretical knowledge and practical skills of local health personnel. Long-term re-evaluation is, however, considered imperative to ascertain and ensure knowledge retention

Unveiling Vulnerabilities in Interpretable Deep Learning Systems with Query-Efficient Black-box Attacks

Deep learning has been rapidly employed in many applications revolutionizing many industries, but it is known to be vulnerable to adversarial attacks. Such attacks pose a serious threat to deep learning-based systems compromising their integrity, reliability, and trust. Interpretable Deep Learning Systems (IDLSes) are designed to make the system more transparent and explainable, but they are also shown to be susceptible to attacks. In this work, we propose a novel microbial genetic algorithm-based black-box attack against IDLSes that requires no prior knowledge of the target model and its interpretation model. The proposed attack is a query-efficient approach that combines transfer-based and score-based methods, making it a powerful tool to unveil IDLS vulnerabilities. Our experiments of the attack show high attack success rates using adversarial examples with attribution maps that are highly similar to those of benign samples which makes it difficult to detect even by human analysts. Our results highlight the need for improved IDLS security to ensure their practical reliability.Comment: arXiv admin note: text overlap with arXiv:2307.0649

Feature selection algorithms for Malaysian dengue outbreak detection model

Dengue fever is considered as one of the most common mosquito borne diseases worldwide. Dengue outbreak detection can be very useful in terms of practical efforts to overcome the rapid spread of the disease by providing the knowledge to predict the next outbreak occurrence. Many studies have been conducted to model and predict dengue outbreak using different data mining techniques. This research aimed to identify the best features that lead to better predictive accuracy of dengue outbreaks using three different feature selection algorithms; particle swarm optimization (PSO), genetic algorithm (GA) and rank search (RS). Based on the selected features, three predictive modeling techniques (J48, DTNB and Naive Bayes) were applied for dengue outbreak detection. The dataset used in this research was obtained from the Public Health Department, Seremban, Negeri Sembilan, Malaysia. The experimental results showed that the predictive accuracy was improved by applying feature selection process before the predictive modeling process. The study also showed the set of features to represent dengue outbreak detection for Malaysian health agencies