Pupillary behavior in relation to wavelength and age

Pupil light reflex can be used as a non-invasive ocular predictor of cephalic autonomic nervous system integrity. Spectral sensitivity of the pupil's response to light has, for some time, been an interesting issue. It has generally, however, only been investigated with the use of white light and studies with monochromatic wavelengths are scarce. This study investigates the effects of wavelength and age within three parameters of the pupil light reflex (amplitude of response, latency, and velocity of constriction) in a large sample of younger and older adults (N = 97), in mesopic conditions. Subjects were exposed to a single light stimulus at four different wavelengths: white (5600° K), blue (450 nm), green (510 nm), and red (600 nm). Data was analyzed appropriately, and, when applicable, using the General Linear Model (GLM), Randomized Complete Block Design (RCBD), Student's t-test and/or ANCOVA. Across all subjects, pupillary response to light had the greatest amplitude and shortest latency in white and green light conditions. In regards to age, older subjects (46-78 years) showed an increased latency in white light and decreased velocity of constriction in green light compared to younger subjects (18-45 years old). This study provides data patterns on parameters of wavelength-dependent pupil reflexes to light in adults and it contributes to the large body of pupillometric research. It is hoped that this study will add to the overall evaluation of cephalic autonomic nervous system integrity.

Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers

The paper develops a novel realized matrix-exponential stochastic volatility model of multivariate returns and realized covariances that incorporates asymmetry and long memory (hereafter the RMESV-ALM model). The matrix exponential transformation guarantees the positivedefiniteness of the dynamic covariance matrix. The contribution of the paper ties in with Robert Basmann’s seminal work in terms of the estimation of highly non-linear model specifications (“Causality tests and observationally equivalent representations of econometric models”, Journal of Econometrics, 1988, 39(1-2), 69–104), especially for developing tests for leverage and spillover effects in the covariance dynamics. Efficient importance sampling is used to maximize the likelihood function of RMESV-ALM, and the finite sample properties of the quasi-maximum likelihood estimator of the parameters are analysed. Using high frequency data for three US financial assets, the new model is estimated and evaluated. The forecasting performance of the new model is compared with a novel dynamic realized matrix-exponential conditional covariance model. The volatility and co-volatility spillovers are examined via the news impact curves and the impulse response functions from returns to volatility and co-volatility.

Avaliação comparativa da remodelação óssea periimplantar em implantes com junção cone-morse e hexágono externo: estudo clínico randomizado controlado, duplo cego, boca dividida

Background: Several theories, such as the biological width formation, the inflammatory reactions due to the implant-abutment microgap contamination, and the periimplant stress/strain concentration causing bone microdamage accumulation, have been suggested to explain early periimplant bone loss. However, it is yet not well understood to which extent the implant-abutment connection type may influence the remodeling process around dental implants. Aim: to evaluate clinical, bacteriological, and biomechanical parameters related to periimplant bone loss at the crestal region, comparing external hexagon (EH) and Morse-taper (MT) connections. Materials and methods: Twelve patients with totally edentulous mandibles received four custom made Ø 3.8 x 13 mm implants in the interforaminal region of the mandible, with the same design, but different prosthetic connections (two of them EH or MT, randomly placed based on a split-mouth design), and a immediate implant- supported prosthesis. Clinical parameters (periimplant probing pocket depth, modified gingival index and mucosal thickness) were evaluated at 6 sites around the implants, at a 12 month follow-up. The distance from the top of the implant to the first bone-to-implant contact – IT-FBIC was evaluated on standardized digital peri-apical radiographs acquired at 1, 3, 6 and 12 months follow-up. Samples of the subgingival microbiota were collected 1, 3 and 6 months after implant loading. DNA were extracted and used for the quantification of Tanerella forsythia, Porphyromonas gingivalis, Aggragatibacter actinomycetemcomitans, Prevotella intermedia and Fusobacterium nucleatum. Comparison among multiple periods of observation were performed using repeated-measures Analysis of Variance (ANOVA), followed by a Tukey post-hoc test, while two-period based comparisons were made using paired t- test. Further, 36 computer-tomographic based finite element (FE) models were accomplished, simulating each patient in 3 loading conditions. The results for the peak EQV strain in periimplant bone were interpreted by means of a general linear model (ANOVA). Results: The variation in periimplant bone loss assessed by means of radiographs was significantly different between the connection types (P<0.001). Mean IT-FBIC was 1.17±0.44 mm for EH, and 0.17±0.54 mm for MT, considering all evaluated time periods. All clinical parameters presented not significant differences. No significant microbiological differences could be observed between both connection types. Most of the collected samples had very few pathogens, meaning that these regions were healthy from a microbiological point of view. In FE analysis, a significantly higher peak of EQV strain (P=0.005) was found for EH (mean 3438.65 µ∑) compared to MT (mean 840.98 µ∑) connection. Conclusions: Varying implant-abutment connection type will result in diverse periimplant bone remodeling, regardless of clinical and microbiological conditions. This fact is more likely attributed to the singular loading transmission through different implant-abutment connections to the periimplant bone. The present findings suggest that Morse-taper connection is more efficient to prevent periimplant bone loss, compared to an external hexagon connection.

Facial affect processing inbipolar disorder:a magnetoencephalography study

Background: Identifying biological markers to aid diagnosis of bipolar disorder (BD) is critically important. To be considered a possible biological marker, neural patterns in BD should be discriminant from those in healthy individuals (HI). We examined patterns of neuromagnetic responses revealed by magnetoencephalography (MEG) during implicit emotion-processing using emotional (happy, fearful, sad) and neutral facial expressions, in sixteen BD and sixteen age- and gender-matched healthy individuals. Methods: Neuromagnetic data were recorded using a 306-channel whole-head MEG ELEKTA Neuromag System, and preprocessed using Signal Space Separation as implemented in MaxFilter (ELEKTA). Custom Matlab programs removed EOG and ECG signals from filtered MEG data, and computed means of epoched data (0-250ms, 250-500ms, 500-750ms). A generalized linear model with three factors (individual, emotion intensity and time) compared BD and HI. A principal component analysis of normalized mean channel data in selected brain regions identified principal components that explained 95% of data variation. These components were used in a quadratic support vector machine (SVM) pattern classifier. SVM classifier performance was assessed using the leave-one-out approach. Results: BD and HI showed significantly different patterns of activation for 0-250ms within both left occipital and temporal regions, specifically for neutral facial expressions. PCA analysis revealed significant differences between BD and HI for mild fearful, happy, and sad facial expressions within 250-500ms. SVM quadratic classifier showed greatest accuracy (84%) and sensitivity (92%) for neutral faces, in left occipital regions within 500-750ms. Conclusions: MEG responses may be used in the search for disease specific neural markers.

Advances in Dynamic Modeling and Computation for Count Data

A class of multi-process models is developed for collections of time indexed count data. Autocorrelation in counts is achieved with dynamic models for the natural parameter of the binomial distribution. In addition to modeling binomial time series, the framework includes dynamic models for multinomial and Poisson time series. Markov chain Monte Carlo (MCMC) and Po ́lya-Gamma data augmentation (Polson et al., 2013) are critical for fitting multi-process models of counts. To facilitate computation when the counts are high, a Gaussian approximation to the P ́olya- Gamma random variable is developed.

Three applied analyses are presented to explore the utility and versatility of the framework. The first analysis develops a model for complex dynamic behavior of themes in collections of text documents. Documents are modeled as a “bag of words”, and the multinomial distribution is used to characterize uncertainty in the vocabulary terms appearing in each document. State-space models for the natural parameters of the multinomial distribution induce autocorrelation in themes and their proportional representation in the corpus over time.

The second analysis develops a dynamic mixed membership model for Poisson counts. The model is applied to a collection of time series which record neuron level firing patterns in rhesus monkeys. The monkey is exposed to two sounds simultaneously, and Gaussian processes are used to smoothly model the time-varying rate at which the neuron’s firing pattern fluctuates between features associated with each sound in isolation.

The third analysis presents a switching dynamic generalized linear model for the time-varying home run totals of professional baseball players. The model endows each player with an age specific latent natural ability class and a performance enhancing drug (PED) use indicator. As players age, they randomly transition through a sequence of ability classes in a manner consistent with traditional aging patterns. When the performance of the player significantly deviates from the expected aging pattern, he is identified as a player whose performance is consistent with PED use.

All three models provide a mechanism for sharing information across related series locally in time. The models are fit with variations on the P ́olya-Gamma Gibbs sampler, MCMC convergence diagnostics are developed, and reproducible inference is emphasized throughout the dissertation.

Bidding For Parking: The Impact of University Affiliation on Predicting Bid Values in Dutch Auctions of On-Campus Parking Permits

Parking is often underpriced and expanding its capacity is expensive; universities need a better way of reducing congestion outside of building costly parking garages. Demand based pricing mechanisms, such as auctions, offer a possible solution to the problem by promising to reduce parking at peak times. However, faculty, students, and staff at universities have systematically different parking needs, leading to different parking valuations. In this study, I determine the impact university affiliation has on predicting bid values cast in three Dutch Auctions of on-campus parking permits sold at Chapman University in Fall 2010. Using clustering techniques crosschecked with university demographic information to detect affiliation groups, I ran a log-linear regression, finding that university affiliation had a larger effect on bid amount than on lot location and fraction of auction duration. Generally, faculty were predicted to have higher bids whereas students were predicted to have lower bids.

Modelagem dinâmica e simulação computacional de poços de petróleo verticais e direcionais com elevação por bombeio mecânico

LINS, Filipe C. A. et al. Modelagem dinâmica e simulação computacional de poços de petróleo verticais e direcionais com elevação por bombeio mecânico. In: CONGRESSO BRASILEIRO DE PESQUISA E DESENVOLVIMENTO EM PETRÓLEO E GÁS, 5. 2009, Fortaleza, CE. Anais... Fortaleza: CBPDPetro, 2009.

Spatial modeling of data with excessive zeros applied to reindeer pellet-group counts

We analyze a real data set pertaining to reindeer fecal pellet-group counts obtained from a survey conducted in a forest area in northern Sweden. In the data set, over 70% of counts are zeros, and there is high spatial correlation. We use conditionally autoregressive random effects for modeling of spatial correlation in a Poisson generalized linear mixed model (GLMM), quasi-Poisson hierarchical generalized linear model (HGLM), zero-inflated Poisson (ZIP), and hurdle models. The quasi-Poisson HGLM allows for both under- and overdispersion with excessive zeros, while the ZIP and hurdle models allow only for overdispersion. In analyzing the real data set, we see that the quasi-Poisson HGLMs can perform better than the other commonly used models, for example, ordinary Poisson HGLMs, spatial ZIP, and spatial hurdle models, and that the underdispersed Poisson HGLMs with spatial correlation fit the reindeer data best. We develop R codes for fitting these models using a unified algorithm for the HGLMs. Spatial count response with an extremely high proportion of zeros, and underdispersion can be successfully modeled using the quasi-Poisson HGLM with spatial random effects.

Learning environment, preparedness and satisfaction in osteopathy in Europe: The PreSS study

Objective: 1) to assess the preparedness to practice and satisfaction in learning environment amongst new graduates from European osteopathic institutions; 2) to compare the results of preparedness to practice and satisfaction in learning environment between and within countries where osteopathy is regulated and where regulation is still to be achieved; 3) to identify possible correlations between learning environment and preparedness to practice. Method: Osteopathic education providers of full-time education located in Europe were enrolled, and their final year students were contacted to complete a survey. Measures used were: Dundee Ready Educational Environment Measure (DREEM), the Association of American Medical Colleges (AAMC) and a demographic questionnaire. Scores were compared across institutions using one-way ANOVA and generalised linear model. Results: Nine European osteopathic education institutions participated in the study (4 located in Italy, 2 in the UK, 1 in France, 1 in Belgium and 1 in the Netherlands) and 243 (77%) of their final-year students completed the survey. The DREEM total score mean was 121.4 (SEM: 1.66) whilst the AAMC was 17.58 (SEM:0.35). A generalised linear model found a significant association between not-regulated countries and total score as well as subscales DREEM scores (p<0.001). Learning environment and preparedness to practice were significantly positively correlated (r=0.76; p<0.01). Discussion: A perceived higher level of preparedness and satisfaction was found amongst students from osteopathic institutions located in countries without regulation compared to those located in countries where osteopathy is regulated; however, all institutions obtained a 'more positive than negative' result. Moreover, in general, cohorts with fewer than 20 students scored significantly higher compared to larger student cohorts. Finally, an overall positive correlation between students' preparedness and satisfaction were found across all institutions recruited.

Analyse des tendances des séries temporelles de la concentration en azote minéral dissous dans les trois principaux estuaires de la façade Manche-Atlantique

Estuaries are areas which, from their structure, their fonctioning, and their localisation, are subject to significant contribution of nutrients. One of the objectif of the RNO, the French network for coastal water quality monitoring, is to assess the levels and trends of nutrient concentrations in estuaries. A linear model was used in order to describe and to explain the total dissolved nitrogen concentration evolution in the three most important estuaries on the Chanel-Atlantic front (Seine, Loire and Gironde). As a first step, the selection of a reliable data set was performed. Then total dissolved nitrogen evolution schemes in estuary environment were graphically studied, and allowed a resonable choice of covariables. The salinity played a major role in explaining nitrogen concentration variability in estuary, and dilution lines were proved to be a useful tool to detect outlying observations and to model the nitrogenlsalinity relation. Increasing trends were detected by the model, with a high magnitude in Seine, intermediate in Loire, and lower in Gironde. The non linear trend estimated in Loire and Seine estuaries could be due to important interannual variations as suggest in graphics. In the objective of the QUADRIGE database valorisation, a discussion on the statistical model, and on the RNO hydrological data sampling strategy, allowed to formulate suggestions towards a better exploitation of nutrient data.

Assessing the influence of abiotic factors and leaf-level properties on the stability of growing-season canopy greenness in a deciduous forest

Maps depicting spatial pattern in the stability of summer greenness could advance understanding of how forest ecosystems will respond to global changes such as a longer growing season. Declining summer greenness, or “greendown”, is spectrally related to declining near-infrared reflectance and is observed in most remote sensing time series to begin shortly after peak greenness at the end of spring and extend until the beginning of leaf coloration in autumn,. Understanding spatial patterns in the strength of greendown has recently become possible with the advancement of Landsat phenology products, which show that greendown patterns vary at scales appropriate for linking these patterns to proposed environmental forcing factors. This study tested two non-mutually exclusive hypotheses for how leaf measurements and environmental factors correlate with greendown and decreasing NIR reflectance across sites. At the landscape scale, we used linear regression to test the effects of maximum greenness, elevation, slope, aspect, solar irradiance and canopy rugosity on greendown. Secondly, we used leaf chemical traits and reflectance observations to test the effect of nitrogen availability and intrinsic water use efficiency on leaf-level greendown, and landscape-level greendown measured from Landsat. The study was conducted using Quercus alba canopies across 21 sites of an eastern deciduous forest in North America between June and August 2014. Our linear model explained greendown variance with an R2=0.47 with maximum greenness as the greatest model effect. Subsequent models excluding one model effect revealed elevation and aspect were the two topographic factors that explained the greatest amount of greendown variance. Regression results also demonstrated important interactions between all three variables, with the greatest interaction showing that aspect had greater influence on greendown at sites with steeper slopes. Leaf-level reflectance was correlated with foliar δ13C (proxy for intrinsic water use efficiency), but foliar δ13C did not translate into correlations with landscape-level variation in greendown from Landsat. Therefore, we conclude that Landsat greendown is primarily indicative of landscape position, with a small effect of canopy structure, and no measureable effect of leaf reflectance. With this understanding of Landsat greendown we can better explain the effects of landscape factors on vegetation reflectance and perhaps on phenology, which would be very useful for studying phenology in the context of global climate change

Modelagem dinâmica e simulação computacional de poços de petróleo verticais e direcionais com elevação por bombeio mecânico

LINS, Filipe C. A. et al. Modelagem dinâmica e simulação computacional de poços de petróleo verticais e direcionais com elevação por bombeio mecânico. In: CONGRESSO BRASILEIRO DE PESQUISA E DESENVOLVIMENTO EM PETRÓLEO E GÁS, 5. 2009, Fortaleza, CE. Anais... Fortaleza: CBPDPetro, 2009.

Efeitos dos fatores ambientais na comunidade de macrófitas em pequenos cursos lóticos perenes subtropicais

Neste estudo foi investigado como a distribuição das espécies e a produção de biomassa de macrófitas aquáticas são influenciadas pelas condições físico-químicas do ambiente. Também foi avaliado como uma espécie com maior potencial competitivo pode interferir na diversidade de espécies da comunidade macrofítica. Para tanto, em cada um dos três arroios, foram dispostos seis transecções, perpendiculares à margem. Em cada transecção foram demarcadas três unidades amostrais de 1m², nas quais foram registrados os parâmetros fitossociológicos cobertura e frequência relativas e valor de importância. A diversidade de espécies foi estimada pelo índice de Shannon, utilizando os valores de cobertura de espécies. Para determinar a biomassa das macrófitas aquáticas foram usados quadrats de 0,25m², alocados dentro da unidade amostral de 1m² usadas para quantificar os dados fitossociológicos, nos mesmos pontos onde foi feito o levantamento de cobertura da vegetação. Utilizamos como variáveis preditoras a velocidade da corrente, radiação solar incidente, coeficiente de sombreamento, vegetação ripária arbórea adjacente, nitrogênio orgânico dissolvido, carbono orgânico dissolvido e condutividade elétrica. Foram registradas 32 espécies de macrófitas aquáticas, distribuídas em 19 famílias e 28 gêneros. Conforme Análise de Correspondência Canônica (CCA), as espécies com maiores valores de biomassa foram relacionadas a unidades amostrais com alta incidência luminosa. As unidades amostrais com dominância de Pistia stratiotes apresentaram menor diversidade de espécies indicando que esta espécie, quando encontra condições que permitam sua proliferação, pode excluir espécies de menor potencial competitivo. De acordo com GLM (Generalized Linear Model), a ausência de vegetação ripária ou presente em apenas uma das margens e baixas velocidades de corrente configura-se em condições favoráveis ao estabelecimento e desenvolvimento de macrófitas aquáticas, possibilitando produção maiores valores de biomassa.

Interaction between mercury (Hg), arsenic (As) and selenium (Se) affects the activity of glutathione S-transferase in breast milk: possible relationship with fish and shellfish intake

Breast milk is regarded as an ideal source of nutrients for the growth and development of neonates, but it can also be a potential source of pollutants. Mothers can be exposed to different contaminants as a result of their lifestyle and environmental pollution. Mercury (Hg) and arsenic (As) could adversely affect the development of fetal and neonatal nervous system. Some fish and shellfish are rich in selenium (Se), an essential trace element that forms part of several enzymes related to the detoxification process, including glutathione S-transferase (GST). The goal of this study was to determine the interaction between Hg, As and Se and analyze its effect on the activity of GST in breast milk. Milk samples were collected from women between day 7 and 10 postpartum. The GST activity was determined spectrophotometrically; total Hg, As and Se concentrations were measured by atomic absorption spectrometry. To explain the possible association of Hg, As and Se concentrations with GST activity in breast milk, generalized linear models were constructed. The model explained 44% of the GST activity measured in breast milk. The GLM suggests that GST activity was positively correlated with Hg, As and Se concentrations. The activity of the enzyme was also explained by the frequency of consumption of marine fish and shellfish in the diet of the breastfeeding women.

Variational ensemble Kalman filtering applied to data assimilation problems in computational fluid dynamics

One challenge on data assimilation (DA) methods is how the error covariance for the model state is computed. Ensemble methods have been proposed for producing error covariance estimates, as error is propagated in time using the non-linear model. Variational methods, on the other hand, use the concepts of control theory, whereby the state estimate is optimized from both the background and the measurements. Numerical optimization schemes are applied which solve the problem of memory storage and huge matrix inversion needed by classical Kalman filter methods. Variational Ensemble Kalman filter (VEnKF), as a method inspired the Variational Kalman Filter (VKF), enjoys the benefits from both ensemble methods and variational methods. It avoids filter inbreeding problems which emerge when the ensemble spread underestimates the true error covariance. In VEnKF this is tackled by resampling the ensemble every time measurements are available. One advantage of VEnKF over VKF is that it needs neither tangent linear code nor adjoint code. In this thesis, VEnKF has been applied to a two-dimensional shallow water model simulating a dam-break experiment. The model is a public code with water height measurements recorded in seven stations along the 21:2 m long 1:4 m wide flume’s mid-line. Because the data were too sparse to assimilate the 30 171 model state vector, we chose to interpolate the data both in time and in space. The results of the assimilation were compared with that of a pure simulation. We have found that the results revealed by the VEnKF were more realistic, without numerical artifacts present in the pure simulation. Creating a wrapper code for a model and DA scheme might be challenging, especially when the two were designed independently or are poorly documented. In this thesis we have presented a non-intrusive approach of coupling the model and a DA scheme. An external program is used to send and receive information between the model and DA procedure using files. The advantage of this method is that the model code changes needed are minimal, only a few lines which facilitate input and output. Apart from being simple to coupling, the approach can be employed even if the two were written in different programming languages, because the communication is not through code. The non-intrusive approach is made to accommodate parallel computing by just telling the control program to wait until all the processes have ended before the DA procedure is invoked. It is worth mentioning the overhead increase caused by the approach, as at every assimilation cycle both the model and the DA procedure have to be initialized. Nonetheless, the method can be an ideal approach for a benchmark platform in testing DA methods. The non-intrusive VEnKF has been applied to a multi-purpose hydrodynamic model COHERENS to assimilate Total Suspended Matter (TSM) in lake Säkylän Pyhäjärvi. The lake has an area of 154 km2 with an average depth of 5:4 m. Turbidity and chlorophyll-a concentrations from MERIS satellite images for 7 days between May 16 and July 6 2009 were available. The effect of the organic matter has been computationally eliminated to obtain TSM data. Because of computational demands from both COHERENS and VEnKF, we have chosen to use 1 km grid resolution. The results of the VEnKF have been compared with the measurements recorded at an automatic station located at the North-Western part of the lake. However, due to TSM data sparsity in both time and space, it could not be well matched. The use of multiple automatic stations with real time data is important to elude the time sparsity problem. With DA, this will help in better understanding the environmental hazard variables for instance. We have found that using a very high ensemble size does not necessarily improve the results, because there is a limit whereby additional ensemble members add very little to the performance. Successful implementation of the non-intrusive VEnKF and the ensemble size limit for performance leads to an emerging area of Reduced Order Modeling (ROM). To save computational resources, running full-blown model in ROM is avoided. When the ROM is applied with the non-intrusive DA approach, it might result in a cheaper algorithm that will relax computation challenges existing in the field of modelling and DA.