Efeito de exercícios de pilates clínico no controlo postural de jovens adultos com dor lombar não específica

Introdução: Os efeitos a longo prazo de exercícios de Pilates têm sido bem documentados, não entanto os seus efeitos imediatos no controlo postural estático e dinâmico de jovens adultos com dor lombar não específica permanecem por desvendar. Objetivo: Avaliar os efeitos imediatos de uma sessão composta por 4 exercícios de Pilates Clínico no controlo postural estático e dinâmico de jovens adultos com dor lombar não específica. Métodos: 46 estudantes universitários com dor lombar não específica participaram no estudo randomizado e controlado. Os participantes foram randomizados para um grupo de Pilates (n = 23, 10 do sexo masculino, idade: 21,8 ± 3,2 anos; peso: 64,5 ± 11,5 kg; altura: 1,70 ± 0,1 m) e um grupo controlo (n = 23, 9 do sexo masculino; idade: 22,8 ± 3,6 anos; peso: 62,5 ± 9,9 kg; altura: 1,68 ± 0,1 m). O controlo postural estático foi avaliado com uma plataforma de forças e o controlo postural dinâmico com o Star Excursion Balance Test, antes e depois da intervenção ou período de repouso. Para avaliar o controlo postural estático, os participantes estavam em posição ortostática, o mais quietos possível durante 90s, com os olhos fechados em superfície instável. A intervenção durou 20 minutos e consistiu em 4 exercícios de Pilates Clínico: single leg stretch (nível 1), pelvic press (nível 1), swimming (nível 1) e kneeling opposite arm and leg reach. Resultados: No momento de avaliação inicial, não foram encontradas diferenças estatisticamente significativas entre os grupos em nenhuma das variáveis. Após a intervenção, o grupo Pilates melhorou em todos as variáveis do controlo postural estático (COPx: 5,7 ± 1,0 para 5,1 ± 0,7 cm, p = 0,005; COPy: 4,4 ± 1,0 para 3,8 ± 0,7 cm, p < 0,001; comprimento total: 255,2 ± 55,9 para 210,5 ± 42,7 cm, p < 0,001 ; área: 11,5 ± 3,4 para 9,7 ± 2,7 cm2, p = 0,002 e velocidade : 2,8 ± 0,6 para 2,3 ± 0,5 cm/s, p < 0,001) e no Star Excursion Balance Test (anterior: 65,3 ± 8,3 para 68,6 ± 6,4%, p = 0,001; póstero-medial: 82,6 ± 11,7 para 89,5 ± 9,7%, p < 0,001; póstero-lateral: 83,9 ± 11,0 para 87,6 ± 10,2%, p < 0,001 e composite: 86,2 ± 12,4 para 91,1 ± 11,0%, p < 0,001). O grupo de controlo só melhorou na velocidade (2,8 ± 0,5 para 2,6 ± 0,5 cm/s, p = 0,009) e comprimento total (248,5 ± 45,3 para 237,3 ± 47,2 cm, p = 0,009) no controlo postural estático. No entanto, as melhorias no grupo Pilates foram significativamente maiores do que as do grupo de controlo. Conclusão: Os exercícios de Pilates Clínico melhoraram, no imediato, o controlo postural estático e dinâmico em jovens adultos com dor lombar não específica.

Validation of Electronic Health Record Phenotyping of Bipolar Disorder Cases and Controls

Objective: The study was designed to validate use of elec-tronic health records (EHRs) for diagnosing bipolar disorder and classifying control subjects. Method: EHR data were obtained from a health care system of more than 4.6 million patients spanning more than 20 years. Experienced clinicians reviewed charts to identify text features and coded data consistent or inconsistent with a diagnosis of bipolar disorder. Natural language processing was used to train a diagnostic algorithm with 95% specificity for classifying bipolar disorder. Filtered coded data were used to derive three additional classification rules for case subjects and one for control subjects. The positive predictive value (PPV) of EHR-based bipolar disorder and subphenotype di- agnoses was calculated against diagnoses from direct semi- structured interviews of 190 patients by trained clinicians blind to EHR diagnosis. Results: The PPV of bipolar disorder defined by natural language processing was 0.85. Coded classification based on strict filtering achieved a value of 0.79, but classifications based on less stringent criteria performed less well. No EHR- classified control subject received a diagnosis of bipolar dis- order on the basis of direct interview (PPV=1.0). For most subphenotypes, values exceeded 0.80. The EHR-based clas- sifications were used to accrue 4,500 bipolar disorder cases and 5,000 controls for genetic analyses. Conclusions: Semiautomated mining of EHRs can be used to ascertain bipolar disorder patients and control subjects with high specificity and predictive value compared with diagnostic interviews. EHRs provide a powerful resource for high-throughput phenotyping for genetic and clinical research.

Sinusite maxilar odontogénica

O seio maxilar é o seio paranasal mais susceptível a invasões bacterianas, tanto pelo óstio nasal, como pela cavidade oral. As sinusites maxilares têm como causas mais frequentes, as infecções víricas, rinites alérgicas ou não alérgicas, variações anatómicas, diabetes mellitus, fumar, nadar, mergulhar, escalar a altas atitudes, e as infecções e tratamentos dentários. A pesquisa bibliográfica, foi realizada sem quaisquer limitações temporais, com restrição linguística a Português, Espanhol e Inglês, sendo excluídos os artigos de outros idiomas; em vários livros e revistas, assim como artigos científicos obtidos, entre Maio e Julho de 2015, nos motores de busca Pubmed, ScienceDirect, Scielo, Elsevier e B-on. A sinusite maxilar odontogénica é uma doença infecto-inflamatória, habitualmente associada à ruptura da membrana de Schneider e a processos infecciosos dentários crónicos. Causa hiperplasia e hipertrofia da mucosa, o que origina sinais e sintomas próprios, assim como mudanças radiográficas perceptíveis. Existem diferentes etiologias de causa odontogénica: cárie, doença periodontal, quistos odontogénicos e iatrogenia – tratamento endodôntico não cirúrgico, cirurgia endodôntica, comunicações oro-antrais, implantes dentários, elevação do seio maxilar, cirurgia pré-protética e cirurgia ortognática – sendo que a iatrogenia é a mais comum (cerca de 56%). Esta patologia afecta com mais frequência indivíduos dos 42,7 aos 51, 7 anos, e preferencialmente a região molar, seguida dos pré-molares e em alguns casos, caninos. Os organismos que dominam na fase aguda e crónica, são sensivelmente os mesmos, mas em número diferente, e existe uma conexão entre a flora comensal periapical e a flora patogénica em caso de sinusite maxilar odontogénica. O diagnóstico é essencialmente clínico, no entanto existem diferentes exames complementares para confirmarem ou formarem o diagnóstico. Pela grande acessibilidade ao método radiográfico, torna-se fundamental que o médico dentista saiba diferencial as diversas patologias que afectam o seio maxilar. O tratamento abrange a eliminação da causa dentária e o tratamento farmacológico, da infecção, essencialmente à base de antibióticos, e da dor se esta existir. E o tratamento cirúrgico, que contempla a punção-lavagem sinusal, antrostomia intranasal, técnica de Caldwell-Luc e cirurgia sinusal endoscópica. Concluindo, o médico dentista deve ter um amplo conhecimento sobre esta patologia para que a possa reconhecer, tratar ou preveni-la.

Gait Regulation for Bipedal Locomotion

This work explores regulation of forward speed, step length, and slope walking for the passive-dynamic class of bipedal robots. Previously, an energy-shaping control for regulating forward speed has appeared in the literature; here we show that control to be a special case of a more general time-scaling control that allows for speed transitions in arbitrary time. As prior work has focused on potential energy shaping for fully actuated bipeds, we study in detail the shaping of kinetic energy for bipedal robots, giving special treatment to issues of underactuation. Drawing inspiration from features of human walking, an underactuated kinetic-shaping control is presented that provides efficient regulation of walking speed while adjusting step length. Previous results on energetic symmetries of bipedal walking are also extended, resulting in a control that allows regulation of speed and step length while walking on any slope. Finally we formalize the optimal gait regulation problem and propose a dynamic programming solution seeded with passive-dynamic limit cycles. Observations of the optimal solutions generated by this method reveal further similarities between passive dynamic walking and human locomotion and give insight into the structure of minimum-effort controls for walking.

Security and Trust in Distributed Computation

We propose three research problems to explore the relations between trust and security in the setting of distributed computation. In the first problem, we study trust-based adversary detection in distributed consensus computation. The adversaries we consider behave arbitrarily disobeying the consensus protocol. We propose a trust-based consensus algorithm with local and global trust evaluations. The algorithm can be abstracted using a two-layer structure with the top layer running a trust-based consensus algorithm and the bottom layer as a subroutine executing a global trust update scheme. We utilize a set of pre-trusted nodes, headers, to propagate local trust opinions throughout the network. This two-layer framework is flexible in that it can be easily extensible to contain more complicated decision rules, and global trust schemes. The first problem assumes that normal nodes are homogeneous, i.e. it is guaranteed that a normal node always behaves as it is programmed. In the second and third problems however, we assume that nodes are heterogeneous, i.e, given a task, the probability that a node generates a correct answer varies from node to node. The adversaries considered in these two problems are workers from the open crowd who are either investing little efforts in the tasks assigned to them or intentionally give wrong answers to questions. In the second part of the thesis, we consider a typical crowdsourcing task that aggregates input from multiple workers as a problem in information fusion. To cope with the issue of noisy and sometimes malicious input from workers, trust is used to model workers' expertise. In a multi-domain knowledge learning task, however, using scalar-valued trust to model a worker's performance is not sufficient to reflect the worker's trustworthiness in each of the domains. To address this issue, we propose a probabilistic model to jointly infer multi-dimensional trust of workers, multi-domain properties of questions, and true labels of questions. Our model is very flexible and extensible to incorporate metadata associated with questions. To show that, we further propose two extended models, one of which handles input tasks with real-valued features and the other handles tasks with text features by incorporating topic models. Our models can effectively recover trust vectors of workers, which can be very useful in task assignment adaptive to workers' trust in the future. These results can be applied for fusion of information from multiple data sources like sensors, human input, machine learning results, or a hybrid of them. In the second subproblem, we address crowdsourcing with adversaries under logical constraints. We observe that questions are often not independent in real life applications. Instead, there are logical relations between them. Similarly, workers that provide answers are not independent of each other either. Answers given by workers with similar attributes tend to be correlated. Therefore, we propose a novel unified graphical model consisting of two layers. The top layer encodes domain knowledge which allows users to express logical relations using first-order logic rules and the bottom layer encodes a traditional crowdsourcing graphical model. Our model can be seen as a generalized probabilistic soft logic framework that encodes both logical relations and probabilistic dependencies. To solve the collective inference problem efficiently, we have devised a scalable joint inference algorithm based on the alternating direction method of multipliers. The third part of the thesis considers the problem of optimal assignment under budget constraints when workers are unreliable and sometimes malicious. In a real crowdsourcing market, each answer obtained from a worker incurs cost. The cost is associated with both the level of trustworthiness of workers and the difficulty of tasks. Typically, access to expert-level (more trustworthy) workers is more expensive than to average crowd and completion of a challenging task is more costly than a click-away question. In this problem, we address the problem of optimal assignment of heterogeneous tasks to workers of varying trust levels with budget constraints. Specifically, we design a trust-aware task allocation algorithm that takes as inputs the estimated trust of workers and pre-set budget, and outputs the optimal assignment of tasks to workers. We derive the bound of total error probability that relates to budget, trustworthiness of crowds, and costs of obtaining labels from crowds naturally. Higher budget, more trustworthy crowds, and less costly jobs result in a lower theoretical bound. Our allocation scheme does not depend on the specific design of the trust evaluation component. Therefore, it can be combined with generic trust evaluation algorithms.

Predicting the metabolic energy costs of bipedalism using evolutionary robotics

To understand the evolution of bipedalism among the homnoids in an ecological context we need to be able to estimate theenerrgetic cost of locomotion in fossil forms. Ideally such an estimate would be based entirely on morphology since, except for the rare instances where footprints are preserved, this is hte only primary source of evidence available. In this paper we use evolutionary robotics techniques (genetic algoritms, pattern generators and mechanical modeling) to produce a biomimentic simulation of bipedalism based on human body dimensions. The mechnaical simulation is a seven-segment, two-dimensional model with motive force provided by tension generators representing the major muscle groups acting around the lower-limb joints. Metabolic energy costs are calculated from the muscel model, and bipedal gait is generated using a finite-state pattern generator whose parameters are produced using a genetic algorithm with locomotor economy (maximum distance for a fixed energy cost) as the fitness criterion. The model is validated by comparing the values it generates with those for modern humans. The result (maximum efficiency of 200 J m-1) is within 15% of the experimentally derived value, which is very encouraging and suggests that this is a useful analytic technique for investigating the locomotor behaviour of fossil forms. Initial work suggests that in the future this technique could be used to estimate other locomotor parameters such as top speed. In addition, the animations produced by this technique are qualitatively very convincing, which suggests that this may also be a useful technique for visualizing bipedal locomotion.