Contributions to underwater glider path planning

[ES] La Planificación de Rutas o Caminos es un disciplina de Robótica que trata la búsqueda de caminos factibles u óptimos. Para la mayoría de vehículos y entornos, no es un problema trivial y por tanto nos encontramos con un gran diversidad de algoritmos para resolverlo, no sólo en Robótica e Inteligencia Artificial, sino también como parte de la literatura de Optimización, con Métodos Numéricos y Algoritmos Bio-inspirados, como Algoritmos Genéticos y el Algoritmo de la Colonia de Hormigas. El caso particular de escenarios de costes variables es considerablemente difícil de abordar porque el entorno en el que se mueve el vehículo cambia con el tiempo. El presente trabajo de tesis estudia este problema y propone varias soluciones prácticas para aplicaciones de Robótica Submarina.

Sonographic visualization and ultrasound-guided blockade of the greater occipital nerve: a comparison of two selective techniques confirmed by anatomical dissection

BACKGROUND: Local anaesthetic blocks of the greater occipital nerve (GON) are frequently performed in different types of headache, but no selective approaches exist. Our cadaver study compares the sonographic visibility of the nerve and the accuracy and specificity of ultrasound-guided injections at two different sites. METHODS: After sonographic measurements in 10 embalmed cadavers, 20 ultrasound-guided injections of the GON were performed with 0.1 ml of dye at the classical site (superior nuchal line) followed by 20 at a newly described site more proximal (C2, superficial to the obliquus capitis inferior muscle). The spread of dye and coloration of nerve were evaluated by dissection. RESULTS: The median sonographic diameter of the GON was 4.2 x 1.4 mm at the classical and 4.0 x 1.8 mm at the new site. The nerves were found at a median depth of 8 and 17.5 mm, respectively. In 16 of 20 in the classical approach and 20 of 20 in the new approach, the nerve was successfully coloured with the dye. This corresponds to a block success rate of 80% (95% confidence interval: 58-93%) vs 100% (95% confidence interval: 86-100%), which is statistically significant (McNemar's test, P=0.002). CONCLUSIONS: Our findings confirm that the GON can be visualized using ultrasound both at the level of the superior nuchal line and C2. This newly described approach superficial to the obliquus capitis inferior muscle has a higher success rate and should allow a more precise blockade of the nerve.

Allergen cross reactions: a problem greater than ever thought?

Cross reactions are an often observed phenomenon in patients with allergy. Sensitization against some allergens may cause reactions against other seemingly unrelated allergens. Today, cross reactions are being investigated on a per-case basis, analyzing blood serum specific IgE (sIgE) levels and clinical features of patients suffering from cross reactions. In this study, we evaluated the level of sIgE compared to patients' total IgE assuming epitope specificity is a consequence of sequence similarity.

Prevalence and impact of pain at the greater trochanter after open surgery for the treatment of femoro-acetabular impingement

Femoro-acetabular impingement can cause pain and degenerative changes of the hip joint. Traditionally, surgical dislocation of the hip joint has been performed for correction of pathologic abnormalities in the proximal part of the femur and the acetabulum. Failures of surgical treatment are often related to postoperative pain in the groin or in the area of the greater trochanter, associated with this surgical approach. The aim of our study was to determine the prevalence and functional impact of pain at the greater trochanter after surgical dislocation of the hip.

Semiparametric Latent Variable Regression Models for Spatio-temporal Modeling of Mobile Source Particles in the Greater Boston Area

Traffic particle concentrations show considerable spatial variability within a metropolitan area. We consider latent variable semiparametric regression models for modeling the spatial and temporal variability of black carbon and elemental carbon concentrations in the greater Boston area. Measurements of these pollutants, which are markers of traffic particles, were obtained from several individual exposure studies conducted at specific household locations as well as 15 ambient monitoring sites in the city. The models allow for both flexible, nonlinear effects of covariates and for unexplained spatial and temporal variability in exposure. In addition, the different individual exposure studies recorded different surrogates of traffic particles, with some recording only outdoor concentrations of black or elemental carbon, some recording indoor concentrations of black carbon, and others recording both indoor and outdoor concentrations of black carbon. A joint model for outdoor and indoor exposure that specifies a spatially varying latent variable provides greater spatial coverage in the area of interest. We propose a penalised spline formation of the model that relates to generalised kringing of the latent traffic pollution variable and leads to a natural Bayesian Markov Chain Monte Carlo algorithm for model fitting. We propose methods that allow us to control the degress of freedom of the smoother in a Bayesian framework. Finally, we present results from an analysis that applies the model to data from summer and winter separately

Towards greater accuracy in individual-tree mortality regression

Background mortality is an essential component of any forest growth and yield model. Forecasts of mortality contribute largely to the variability and accuracy of model predictions at the tree, stand and forest level. In the present study, I implement and evaluate state-of-the-art techniques to increase the accuracy of individual tree mortality models, similar to those used in many of the current variants of the Forest Vegetation Simulator, using data from North Idaho and Montana. The first technique addresses methods to correct for bias induced by measurement error typically present in competition variables. The second implements survival regression and evaluates its performance against the traditional logistic regression approach. I selected the regression calibration (RC) algorithm as a good candidate for addressing the measurement error problem. Two logistic regression models for each species were fitted, one ignoring the measurement error, which is the “naïve” approach, and the other applying RC. The models fitted with RC outperformed the naïve models in terms of discrimination when the competition variable was found to be statistically significant. The effect of RC was more obvious where measurement error variance was large and for more shade-intolerant species. The process of model fitting and variable selection revealed that past emphasis on DBH as a predictor variable for mortality, while producing models with strong metrics of fit, may make models less generalizable. The evaluation of the error variance estimator developed by Stage and Wykoff (1998), and core to the implementation of RC, in different spatial patterns and diameter distributions, revealed that the Stage and Wykoff estimate notably overestimated the true variance in all simulated stands, but those that are clustered. Results show a systematic bias even when all the assumptions made by the authors are guaranteed. I argue that this is the result of the Poisson-based estimate ignoring the overlapping area of potential plots around a tree. Effects, especially in the application phase, of the variance estimate justify suggested future efforts of improving the accuracy of the variance estimate. The second technique implemented and evaluated is a survival regression model that accounts for the time dependent nature of variables, such as diameter and competition variables, and the interval-censored nature of data collected from remeasured plots. The performance of the model is compared with the traditional logistic regression model as a tool to predict individual tree mortality. Validation of both approaches shows that the survival regression approach discriminates better between dead and alive trees for all species. In conclusion, I showed that the proposed techniques do increase the accuracy of individual tree mortality models, and are a promising first step towards the next generation of background mortality models. I have also identified the next steps to undertake in order to advance mortality models further.

Oral diacetylmorphine (heroin) yields greater morphine bioavailability than oral morphine: bioavailability related to dosage and prior opioid exposure

AIMS: In the Swiss heroin substitution trials, patients are treated with self-administered diacetylmorphine (heroin). Intravenous administration is not possible in patients that have venosclerosis. Earlier studies have demonstrated that oral diacetylmorphine may be used, although it is completely converted to morphine presystemically. Morphine bioavailability after high-dose oral diacetylmorphine is considerably higher than would be predicted from low-dose trials. The aim was to investigate whether the unexpectedly high bioavailability is due to a difference in the drug examined, and whether it depends on previous exposure or on dose. METHODS: Opioid-naive healthy volunteers and dependent patients from the Swiss heroin trials (n = 8 per group) received low doses of intravenous and oral deuterium-labelled morphine and diacetylmorphine, respectively. Patients also received a high oral diacetylmorphine dose. RESULTS: The maximum plasma concentration (C(max)) of morphine was twofold higher after oral diacetylmorphine than after morphine administration in both groups. However, morphine bioavailability was considerably higher in chronic users [diacetylmorphine 45.6% (95% confidence interval 40.0, 51.3), morphine 37.2% (30.1, 44.3)] than in naive subjects [diacetylmorphine 22.9% (16.4, 29.4), morphine 23.9% (16.5, 31.2)] after low oral doses (48.5 micromol) of either diacetylmorphine or morphine. Morphine clearance was similar in both groups. Moreover, oral absorption of morphine from diacetylmorphine was found to be dose dependent, with bioavailability reaching 64.2% (55.3, 73.1) for high diacetylmorphine doses (1601 micromol). CONCLUSIONS: Oral absorption of opioids is substance-, dose- and patient collective-dependent, suggesting that there may be a saturation of first-pass processes, the exact mechanism of which is not yet understood.

Overweight children have a greater proportion of fat mass relative to muscle mass in the upper limbs than in the lower limbs: implications for bone strength at the distal forearm

BACKGROUND: The influence of adiposity on upper-limb bone strength has rarely been studied in children, despite the high incidence of forearm fractures in this population. OBJECTIVE: The objective was to compare the influence of muscle and fat tissues on bone strength between the upper and lower limbs in prepubertal children. DESIGN: Bone mineral content, total bone cross-sectional area, cortical bone area (CoA), cortical thickness (CoTh) at the radius and tibia (4% and 66%, respectively), trabecular density (TrD), bone strength index (4% sites), cortical density (CoD), stress-strain index, and muscle and fat areas (66% sites) were measured by using peripheral quantitative computed tomography in 427 children (206 boys) aged 7-10 y. RESULTS: Overweight children (n = 93) had greater values for bone variables (0.3-1.3 SD; P < 0.0001) than did their normal-weight peers, except for CoD 66% and CoTh 4%. The between-group differences were 21-87% greater at the tibia than at the radius. After adjustment for muscle cross-sectional area, TrD 4%, bone mineral content, CoA, and CoTh 66% at the tibia remained greater in overweight children, whereas at the distal radius total bone cross-sectional area and CoTh were smaller in overweight children (P < 0.05). Overweight children had a greater fat-muscle ratio than did normal-weight children, particularly in the forearm (92 +/- 28% compared with 57 +/- 17%). Fat-muscle ratio correlated negatively with all bone variables, except for TrD and CoD, after adjustment for body weight (r = -0.17 to -0.54; P < 0.0001). CONCLUSIONS: Overweight children had stronger bones than did their normal-weight peers, largely because of greater muscle size. However, the overweight children had a high proportion of fat relative to muscle in the forearm, which is associated with reduced bone strength.