A Solver for Complex-Valued Parametric Linear Systems

This work reports on a new software for solving linear systems involving affine-linear dependencies between complex-valued interval parameters. We discuss the implementation of a parametric residual iteration for linear interval systems by advanced communication between the system Mathematica and the library C-XSC supporting rigorous complex interval arithmetic. An example of AC electrical circuit illustrates the use of the presented software.

Using Bayesian methods for the estimation of uncertainty in complex statistical models

The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.

Evaluating functional network inference using simulations of complex biological systems.

MOTIVATION: Although many network inference algorithms have been presented in the bioinformatics literature, no suitable approach has been formulated for evaluating their effectiveness at recovering models of complex biological systems from limited data. To overcome this limitation, we propose an approach to evaluate network inference algorithms according to their ability to recover a complex functional network from biologically reasonable simulated data. RESULTS: We designed a simulator to generate data representing a complex biological system at multiple levels of organization: behaviour, neural anatomy, brain electrophysiology, and gene expression of songbirds. About 90% of the simulated variables are unregulated by other variables in the system and are included simply as distracters. We sampled the simulated data at intervals as one would sample from a biological system in practice, and then used the sampled data to evaluate the effectiveness of an algorithm we developed for functional network inference. We found that our algorithm is highly effective at recovering the functional network structure of the simulated system-including the irrelevance of unregulated variables-from sampled data alone. To assess the reproducibility of these results, we tested our inference algorithm on 50 separately simulated sets of data and it consistently recovered almost perfectly the complex functional network structure underlying the simulated data. To our knowledge, this is the first approach for evaluating the effectiveness of functional network inference algorithms at recovering models from limited data. Our simulation approach also enables researchers a priori to design experiments and data-collection protocols that are amenable to functional network inference.

Study of baleen whales’ ecology and interaction with maritime traffic activities to support management of a complex socio-ecological system

Thesis written in co-mentorship with Robert Michaud.

Temporal dynamics of stomatal conductance of plants under water deficit: can homeostasis be improved by more complex dynamics?

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Evaluation of the dentin-pulp complex after cavity preparation with ultrasonic diamond tip

The aim of this paper was to compare the dentin-pulp complex response to cavity preparation in human teeth using ultrasonic chemical vapor deposition (CVD) diamond tip and high-speed diamond bur. Class V buccal cavities were randomly prepared in 40 premolars from 14 patients aged 11 to 15 years. The cutting time was recorded and the cavities had the axial walls protected with gutta-percha and were filled with glass ionomer cement. The teeth were extracted at intervals of 0, 5, 10 and 20 days, and were decalcified, sectioned and stained by Hematoxylin & Eosin, Masson's Trichrome and Brown & Brenn techniques. The inflammatory response and cell disorganization were blindly evaluated by two examiners. The remaining dentin thickness (RDT) was measured by a linear scale using computer software. Statistical analysis by one-way ANOVA showed no statistically significant difference (P≤0.05) among the cavities prepared with either type of instrument, with mean RDT of 1132.50 mm. Cutting time and the pulp-dentin complex responses were analyzed statistically by Kruskal-Wallis and Dunn tests (P≤0.05). The ultrasonic CVD diamond tip took 5 times longer to prepare the cavities and there were no typical inflammatory pulp responses in cavities prepared with either type of cutting instrument, only mild to moderate cell disorganization was present. Even taking longer to cut the dental substrate, the ultrasonic CVD diamond tip produced similar pulp response compared to the conventional high-speed diamond bur.

Complex Call with Different Messages in Bokermannohyla ibitiguara (Anura, Hylidae), a Gladiator Frog of the Brazilian Cerrado

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Postactivation potentiation: effect of various recovery intervals on bench press power performance

Ferreira, SLA, Panissa, VLG, Miarka, B, and Franchini, E. Postactivation potentiation: effect of various recovery intervals on bench press power performance. J Strength Cond Res 26(3): 739-744, 2012-Postactivation potentiation (PAP) is a strategy used to improve performance in power activities. The aim of this study was to determine if power during bench press exercise was increased when preceded by 1 repetition maximum (1RM) in the same exercise and to determine which time interval could optimize PAP response. For this, 11 healthy male subjects (age, 25 +/- 4 years; height, 178 +/- 6 cm; body mass, 74 +/- 8 kg; bench press 1RM, 76 +/- 19 kg) underwent 6 sessions. Two control sessions were conducted to determine both bench press 1RM and power (6 repetitions at 50% 1RM). The 4 experimental sessions were composed of a 1RM exercise followed by power sets with different recovery intervals (1, 3, 5, and 7 minutes), performed on different days, and determined randomly. Power values were measured via Peak Power equipment (Cefise, Nova Odessa, Sao Paulo, Brazil). The conditions were compared using an analysis of variance with repeated measures, followed by a Tukey test. The significance level was set at p < 0.05. There was a significant increase in PAP in concentric contractions after 7 minutes of recovery compared with the control and 1-minute recovery conditions (p < 0.05). Our results indicated that 7 minutes of recovery has generated an increase in PAP in bench press and that such a strategy could be applied as an interesting alternative to enhance the performance in tasks aimed at increasing upper-body power performance.

Influence of cueing on the preparation and execution of untrained and trained complex motor responses

This study investigated the influence of cueing on the performance of untrained and trained complex motor responses. Healthy adults responded to a visual target by performing four sequential movements (complex response) or a single movement (simple response) of their middle finger. A visual cue preceded the target by an interval of 300, 1000, or 2000 ms. In Experiment 1, the complex and simple responses were not previously trained. During the testing session, the complex response pattern varied on a trial-by-trial basis following the indication provided by the visual cue. In Experiment 2, the complex response and the simple response were extensively trained beforehand. During the testing session, the trained complex response pattern was performed in all trials. The latency of the untrained and trained complex responses decreased from the short to the medium and long cue-target intervals. The latency of the complex response was longer than that of the simple response, except in the case of the trained responses and the long cue-target interval. These results suggest that the preparation of untrained complex responses cannot be completed in advance, this being possible, however, for trained complex responses when enough time is available. The duration of the 1st submovement, 1st pause and 2nd submovement of the untrained and the trained complex responses increased from the short to the long cue-target interval, suggesting that there is an increase of online programming of the response possibly related to the degree of certainty about the moment of target appearance.

PM(10) remote sensing from geostationary SEVIRI and polar-orbiting MODIS sensors over the complex terrain of the European Alpine region

The subject of this study is to investigate the capability of spaceborne remote sensing data to predict ground concentrations of PM10 over the European Alpine region using satellite derived Aerosol Optical Depth (AOD) from the geostationary Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and the polar-orbiting MODerate resolution Imaging Spectroradiometer (MODIS). The spatial and temporal resolutions of these aerosol products (10 km and 2 measurements per day for MODIS, ∼ 25 km and observation intervals of 15 min for SEVIRI) permit an evaluation of PM estimation from space at different spatial and temporal scales. Different empirical linear relationships between coincident AOD and PM10 observations are evaluated at 13 ground-based PM measurement sites, with the assumption that aerosols are vertically homogeneously distributed below the planetary Boundary Layer Height (BLH). The BLH and Relative Humidity (RH) variability are assessed, as well as their impact on the parameterization. The BLH has a strong influence on the correlation of daily and hourly time series, whilst RH effects are less clear and smaller in magnitude. Despite its lower spatial resolution and AOD accuracy, SEVIRI shows higher correlations than MODIS (rSEV∼ 0.7, rMOD∼ 0.6) with regard to daily averaged PM10. Advantages from MODIS arise only at hourly time scales in mountainous locations but lower correlations were found for both sensors at this time scale (r∼ 0.45). Moreover, the fraction of days in 2008 with at least one satellite observation was 27% for SEVIRI and 17% for MODIS. These results suggest that the frequency of observations plays an important role in PM monitoring, while higher spatial resolution does not generally improve the PM estimation. Ground-based Sun Photometer (SP) measurements are used to validate the satellite-based AOD in the study region and to discuss the impact of aerosols' micro-physical properties in the empirical models. A lower error limit of 30 to 60% in the PM10 assessment from space is estimated in the study area as a result of AOD uncertainties, variability of aerosols properties and the heterogeneity of ground measurement sites. It is concluded that SEVIRI has a similar capacity to map PM as sensors on board polar-orbiting platforms, with the advantage of a higher number of observations. However, the accuracy represents a serious limitation to the applicability of satellites for ground PM mapping, especially in mountainous areas.

Wide QRS-complex tachycardia with variable VA-conduction: what is the mechanism?

We describe the case of a 16-year-old woman with a surgically corrected tetralogy of Fallot presenting with recurrent wide-QRS-complex tachycardia. The tachycardia could be induced and terminated with ventricular stimulation only. QRS morphology during sinus rhythm and tachycardia was identical and variable VA-conduction was observed. Mapping of the tachycardia showed that variations of HH intervals preceded VV intervals. Therefore, a mechanism involving re-entry within the bundle branches was suggested. However, detailed mapping showed cranial to caudal depolarization of the His bundle, leading to the diagnosis of atrioventricular node re-entrant tachycardia. The tachycardia was abolished by radiofrequency catheter ablation of the slow AV nodal pathway. We conclude that variable VA conduction can occur in patients with atrioventricular node re-entrant tachycardia. The atrial tissue is not always an integral part of the re-entrant circuit.

The brain’s default state interacts with working memory processes in a complex and load-dependent manner

Recently, many studies about a network active during rest and deactivated during tasks emerged in the literature: the default mode network (DMN). Spatial and temporal DMN features are important markers for psychiatric diseases. Another prominent indicator of cognitive functioning, yielding information about the mental condition in health and disease, is working memory (WM) processing. In EEG studies, frontal-midline theta power has been shown to increase with load during WM retention in healthy subjects. From these findings, the conclusion can be drawn that an increase in resting state DMN activity may go along with an increase in theta power in high-load WM conditions. We followed this hypothesis in a study on 17 healthy subjects performing a visual Sternberg WM task. The DMN was obtained by a BOLD-ICA approach and its dynamics represented by the percent-strength during pre-stimulus periods. DMN dynamics were temporally correlated with EEG theta spectral power from retention intervals. This so-called covariance mapping yielded the spatial distribution of the theta EEG fluctuations associated with the dynamics of the DMN. In line with previous findings, theta power was increased at frontal-midline electrodes in high- versus low-load conditions during early WM retention. However, load-dependent correlations of DMN with theta power resulted in primarily positive correlations in low-load conditions, while during high-load conditions negative correlations of DMN activity and theta power were observed at frontal-midline electrodes. This DMN-dependent load effect reached significance during later retention. Our results show a complex and load-dependent interaction of pre-stimulus DMN activity and theta power during retention, varying over the course of the retention period. Since both, WM performance and DMN activity, are markers of mental health, our results could be important for further investigations of psychiatric populations.

Evaluation of Mycobacterium avium complex lung disease in women

Mycobacterium avium complex (MAC) is a ubiquitous organism responsible for most pulmonary and disseminated disease caused by non-tuberculosis (NTM) mycobacteria. Though MAC lung disease without predisposing factors is uncommon, in recent years it has been increasingly described in middle-aged and elderly women. Recognition and correct diagnosis, is often delayed due to the indolent nature of the disease. It is unclear if these women have significant clinical disease as or if their airways are simply colonized by the bacterium. This study describes the clinical presentation, identifies risk factors, and describes the clinical significance of MAC lung disease in HIV-negative women aged 50 or greater. ^ A hybrid study design utilizing both cross-sectional and case-control methodologies was used. A comparison population was selected from previously identified tuberculosis suspects found throughout Harris County. The study population had at least one acid fast bacillus pulmonary culture performed between 1/1/1998 and 12/31/2000 from a pulmonary source. Clinical presentation and symptoms were analyzed using a cross-sectional design. Past medical history and other risk factors were evaluated using a traditional case-control study design. Differences in categorical variables were estimated with the Chi Square or Fisher's Exact test as appropriate. Odds ratios and 95% confidence intervals were utilized to evaluate associations. Multivariate logistic regression was used to identify predictive factors for MAC. All statistical tests were two-sided and P-values <0.05 were considered statistically significant. ^ Culture confirmed MAC pulmonary cases were more likely to be white, have bronchiectasis, scoliosis, evidence of cavitation and pleural changes on chest radiography and granulomas on histopathologic examination than women whose pulmonary cultures were AFB negative. After controlling for selected risk factors, white race continued to be significantly associated with MAC lung disease (OR = 4.6, 95% CI = 2.3, 9.2). In addition, asthma history, smoking history and alcohol use were less likely to be evident among MAC cases in a multivariate analysis. Right upper and right middle lobe disease was further noted among clinically significant cases. Based on population data, MAC lung disease appears to represent a significant clinical syndrome in HIV-negative women thus supporting the theory of the Lady Windermere Syndrome. ^

Cretaceous-Tertiary ichthyoliths of brown clay intervals

The pattern of ichthyolith distribution established in sequences with stratigraphies based on calcareous or siliceous microfossils is used to provide age correlations for three deep-sea pelagic clay intervals that lack the better known microfossils. At Site 637, approximately 25 m of brown clay in Cores 103-637A-21R through 103-637A-23R underlies upper Miocene sediments and is of Paleocene to early Eocene age. At Site 639, 1.7 m of brown clay in Core 103-639C-2R is Eocene to Oligocene. At Site 640, 3.5 m of clay in Cores 103-640A-1R and 103-640A-2R contains a Cretaceous to Paleocene sequence, with the Cretaceous/Tertiary boundary between 84 and 103 cm in Section 103-640A-2R-1.

Chemistry of secondary minerals from the deep sheeted dike complex of ODP Holes 137-504B and 140-504B

Dolerites sampled from the lower sheeted dikes from Hole 504B during Ocean Drilling Program Legs 137 and 140, between 1562.4 and 2000.4 mbsf, were examined to document the mineralogy, petrography, and mineral parageneses associated with secondary alteration, to constrain the thermal history and composition of hydrothermal fluids. The main methods used were mineral chemical analyses by electron microprobe, X-ray diffraction, and cathodoluminescence microscopy. Temperatures of alteration were estimated on the basis of single and/or coexisting mineral chemistry. Permeability is important in controlling the type and extent of alteration in the studied dike section. At the meter-scale, intervals of weakly altered dolerites containing fresh olivine are interpreted as having experienced restricted exposure to hydrothermal fluids. At the centimeter- or millimeter-scale, alteration patches and extensively altered halos adjacent to veins reflect the permeability related to intergranular primary porosity and cracks. Most of the sheeted dike alteration in this case resulted from non-focused, pervasive fluid-rock interaction. This study confirms and extends the previous model for hydrothermal alteration at Hole 504B: hydrothermal alteration at the ridge axis followed by seawater recharge and off-axis alteration. The major new discoveries, all related to higher temperatures of alteration, are: (1) the presence of hydrothermal plagioclase (An80-95), (2) the presence of deuteric and/or hydrothermal diopside, and (3) the general increasing proportion of amphiboles, and particularly magnesio-hornblende with depth. We propose that the dolerites at Hole 504B were altered in five stages. Stage 1 occurred at high temperatures (less than 500° to 700°C) and involved late-magmatic formation of Na- and Ti-rich diopside, the hydrothermal formation of Na, Ti-poor diopside and the hydrothermal formation of an assemblage of An-rich plagioclase + hornblende. Stage 2 occurred at lower temperatures (250°-320°C) and is characterized by the appearance of actinolite, chlorite, chlorite-smectite, and/or talc (in low permeability zones) and albite. During Stage 3, quartz and epidote precipitated from evolved hydrothermal fluids at temperatures between 310° and 320°C. Anhydrite appeared during Stage 4 and likely precipitated directly from heated seawater. Stage 5 occurred off-axis at low temperatures (250°C) with laumontite and prehnite from evolved fluids.