Contextual factors multiplex to control multisensory processes.

This study analyzed high-density event-related potentials (ERPs) within an electrical neuroimaging framework to provide insights regarding the interaction between multisensory processes and stimulus probabilities. Specifically, we identified the spatiotemporal brain mechanisms by which the proportion of temporally congruent and task-irrelevant auditory information influences stimulus processing during a visual duration discrimination task. The spatial position (top/bottom) of the visual stimulus was indicative of how frequently the visual and auditory stimuli would be congruent in their duration (i.e., context of congruence). Stronger influences of irrelevant sound were observed when contexts associated with a high proportion of auditory-visual congruence repeated and also when contexts associated with a low proportion of congruence switched. Context of congruence and context transition resulted in weaker brain responses at 228 to 257 ms poststimulus to conditions giving rise to larger behavioral cross-modal interactions. Importantly, a control oddball task revealed that both congruent and incongruent audiovisual stimuli triggered equivalent non-linear multisensory interactions when congruence was not a relevant dimension. Collectively, these results are well explained by statistical learning, which links a particular context (here: a spatial location) with a certain level of top-down attentional control that further modulates cross-modal interactions based on whether a particular context repeated or changed. The current findings shed new light on the importance of context-based control over multisensory processing, whose influences multiplex across finer and broader time scales.

Heart Rate Variability (HRV) modifications in adult hemiplegic patients after botulinum toxin type A (nt-201) injection.

BACKGROUND: The most important adverse effect of BoNT-A is the systemic diffusion of the toxin. There is some evidence that the administration of high doses can increase the risk of systemic diffusion and the development of clinically evident adverse effects, however an international consensus does not exist about its maximum dose. AIM: The aim of this study was to evaluate changes in autonomic heart drive induced by high doses (higher than 600 units) of incobotulinumtoxinA injection in spastic stroke patients. Moreover, the treatment safety by monitoring adverse events occurrence was assessed. DESIGN: Case control study. POPULATION: Eleven stroke survivors with spastic hemiplegia. METHODS: Patients were treated with intramuscular focal injections of IncobotulinumtoxinA (NT 201; Xeomin®, Merz Pharmaceuticals GmbH, Frankfurt, Germany). Doses were below 12 units/Kg. Each patient underwent an ECG recording before injection and 10 days after treatment. Linear and non-linear Heart Rate variability (HRV) measures were derived from ECGs with a dedicated software. RESULTS: None of the variable considered showed statistically significant changes after BoNT-A injection. CONCLUSION: The use of incobotulinumtoxinA in adult patients at doses up to 12 units/kg seems to be safe regarding autonomic heart drive. CLINICAL REHABILITATION IMPACT: The use of IncobotulinumtoxinA up to 600 units could be a safe therapeutic option in spastic hemiplegic stroke survivors.

Are alcohol outlet densities strongly associated with alcohol-related outcomes? A critical review of recent evidence.

ISSUES: There have been reviews on the association between density of alcohol outlets and harm including studies published up to December 2008. Since then the number of publications has increased dramatically. The study reviews the more recent studies with regard to their utility to inform policy. APPROACH: A systematic review found more than 160 relevant studies (published between January 2009 and October 2014). The review focused on: (i) outlet density and assaultive or intimate partner violence; (ii) studies including individual level data; or (iii) 'natural experiments'. KEY FINDINGS: Despite overall evidence for an association between density and harm, there is little evidence on causal direction (i.e. whether demand leads to more supply or increased availability increases alcohol use and harm). When outlet types (e.g. bars, supermarkets) are analysed separately, studies are too methodologically diverse and partly contradictory to permit firm conclusions besides those pertaining to high outlet densities in areas such as entertainment districts. Outlet density commonly had little effect on individual-level alcohol use, and the few 'natural experiments' on restricting densities showed little or no effects. IMPLICATIONS AND CONCLUSIONS: Although outlet densities are likely to be positively related to alcohol use and harm, few policy recommendations can be given as effects vary across study areas, outlet types and outlet cluster size. Future studies should examine in detail outlet types, compare different outcomes associated with different strengths of association with alcohol, analyse non-linear effects and compare different methodologies. Purely aggregate-level studies examining total outlet density only should be abandoned. [Gmel G, Holmes J, Studer J. Are alcohol outlet densities strongly associated with alcohol-related outcomes? A critical review of recent evidence. Drug Alcohol Rev 2015].

Equating accelerometer estimates among youth: The Rosetta Stone 2.

OBJECTIVES: Different accelerometer cutpoints used by different researchers often yields vastly different estimates of moderate-to-vigorous intensity physical activity (MVPA). This is recognized as cutpoint non-equivalence (CNE), which reduces the ability to accurately compare youth MVPA across studies. The objective of this research is to develop a cutpoint conversion system that standardizes minutes of MVPA for six different sets of published cutpoints. DESIGN: Secondary data analysis. METHODS: Data from the International Children's Accelerometer Database (ICAD; Spring 2014) consisting of 43,112 Actigraph accelerometer data files from 21 worldwide studies (children 3-18 years, 61.5% female) were used to develop prediction equations for six sets of published cutpoints. Linear and non-linear modeling, using a leave one out cross-validation technique, was employed to develop equations to convert MVPA from one set of cutpoints into another. Bland Altman plots illustrate the agreement between actual MVPA and predicted MVPA values. RESULTS: Across the total sample, mean MVPA ranged from 29.7MVPAmind(-1) (Puyau) to 126.1MVPAmind(-1) (Freedson 3 METs). Across conversion equations, median absolute percent error was 12.6% (range: 1.3 to 30.1) and the proportion of variance explained ranged from 66.7% to 99.8%. Mean difference for the best performing prediction equation (VC from EV) was -0.110mind(-1) (limits of agreement (LOA), -2.623 to 2.402). The mean difference for the worst performing prediction equation (FR3 from PY) was 34.76mind(-1) (LOA, -60.392 to 129.910). CONCLUSIONS: For six different sets of published cutpoints, the use of this equating system can assist individuals attempting to synthesize the growing body of literature on Actigraph, accelerometry-derived MVPA.

O ajuste de funções matemáticas a dados experimentais

The least square method is analyzed. The basic aspects of the method are discussed. Emphasis is given in procedures that allow a simple memorization of the basic equations associated with the linear and non linear least square method, polinomial regression and multilinear method.

Study of the optical properties of TeO2-PbO-TiO2 glass system

We describe the preparation and some optical properties of high refractive index TeO2-PbO-TiO2 glass system. Highly homogeneous glasses were obtained by agitating the mixture during the melting process in an alumina crucible. The characterization was done by X-ray diffraction, Raman scattering, light absorption and linear refractive index measurements. The results show a change in the glass structure as the PbO content increases: the TeO4 trigonal bipyramids characteristics of TeO2 glasses transform into TeO3 trigonal pyramids. However, the measured refractive indices are almost independent of the glass composition. We show that third-order nonlinear optical susceptibilities calculated from the measured refractive indices using Lines' theoretical model are also independent of the glass composition.

Estudo das propriedades ópticas em vidros 0,3La2S3-0,7Ga2S 3

In this work we describe the synthesis and characterization of chalcogenide glass (0.3La2S3-0.7Ga2S 3) with low phonons frequencies. Several properties were measured like Sellmeier parameters, linear refractive index dispersion and material dispersion. Samples with the composition above were doped with Dy2S3. The absorption and emission characteristics were measured by electronic spectroscopy and fluorescence spectrum respectively. Raman and infrared spectroscopy shows that these glasses present low phonons frequencies and strucuture composed by GaS4 tetrahedrals. The Lines model was used for calculate the coefficients values of the non linear refractive index.

Métodos matemáticos para correção de interferências espectrais e efeitos interelementos na análise quantitativa por fluorescência de raios-X

One of the main problems in quantitative analysis of complex samples by x-ray fluorescence is related to interelemental (or matrix) effects. These effects appear as a result of interactions among sample elements, affecting the x-ray emission intensity in a non-linear manner. Basically, two main effects occur; intensity absorption and enhancement. The combination of these effects can lead to serious problems. Many studies have been carried out proposing mathematical methods to correct for these effects. Basic concepts and the main correction methods are discussed here.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Reaction Kinetics and Viscosity Modelling in the Fusion Syntheses of Ca- and Ca/Mg-resinates

Rosin is a natural product from pine forests and it is used as a raw material in resinate syntheses. Resinates are polyvalent metal salts of rosin acids and especially Ca- and Ca/Mg- resinates find wide application in the printing ink industry. In this thesis, analytical methods were applied to increase general knowledge of resinate chemistry and the reaction kinetics was studied in order to model the non linear solution viscosity increase during resinate syntheses by the fusion method. Solution viscosity in toluene is an important quality factor for resinates to be used in printing inks. The concept of critical resinate concentration, c crit, was introduced to define an abrupt change in viscosity dependence on resinate concentration in the solution. The concept was then used to explain the non-inear solution viscosity increase during resinate syntheses. A semi empirical model with two estimated parameters was derived for the viscosity increase on the basis of apparent reaction kinetics. The model was used to control the viscosity and to predict the total reaction time of the resinate process. The kinetic data from the complex reaction media was obtained by acid value titration and by FTIR spectroscopic analyses using a conventional calibration method to measure the resinate concentration and the concentration of free rosin acids. A multivariate calibration method was successfully applied to make partial least square (PLS) models for monitoring acid value and solution viscosity in both mid-infrared (MIR) and near infrared (NIR) regions during the syntheses. The calibration models can be used for on line resinate process monitoring. In kinetic studies, two main reaction steps were observed during the syntheses. First a fast irreversible resination reaction occurs at 235 °C and then a slow thermal decarboxylation of rosin acids starts to take place at 265 °C. Rosin oil is formed during the decarboxylation reaction step causing significant mass loss as the rosin oil evaporates from the system while the viscosity increases to the target level. The mass balance of the syntheses was determined based on the resinate concentration increase during the decarboxylation reaction step. A mechanistic study of the decarboxylation reaction was based on the observation that resinate molecules are partly solvated by rosin acids during the syntheses. Different decarboxylation mechanisms were proposed for the free and solvating rosin acids. The deduced kinetic model supported the analytical data of the syntheses in a wide resinate concentration region, over a wide range of viscosity values and at different reaction temperatures. In addition, the application of the kinetic model to the modified resinate syntheses gave a good fit. A novel synthesis method with the addition of decarboxylated rosin (i.e. rosin oil) to the reaction mixture was introduced. The conversion of rosin acid to resinate was increased to the level necessary to obtain the target viscosity for the product at 235 °C. Due to a lower reaction temperature than in traditional fusion synthesis at 265 °C, thermal decarboxylation is avoided. As a consequence, the mass yield of the resinate syntheses can be increased from ca. 70% to almost 100% by recycling the added rosin oil.

Aplicação da equação de Poisson-Boltzmann ao cálculo de propriedades dependentes do pH em proteínas

The ability of biomolecules to catalyze chemical reactions is due chiefly to their sensitivity to variations of the pH in the surrounding environment. The reason for this is that they are made up of chemical groups whose ionization states are modulated by pH changes that are of the order of 0.4 units. The determination of the protonation states of such chemical groups as a function of conformation of the biomolecule and the pH of the environment can be useful in the elucidation of important biological processes from enzymatic catalysis to protein folding and molecular recognition. In the past 15 years, the theory of Poisson-Boltzmann has been successfully used to estimate the pKa of ionizable sites in proteins yielding results, which may differ by 0.1 unit from the experimental values. In this study, we review the theory of Poisson-Boltzmann under the perspective of its application to the calculation of pKa in proteins.

Comportamento dinâmico-mecânico e relaxações em polímeros e blendas poliméricas

Dynamic mechanical analysis (DMA) is widely used in materials characterization. In this work, we briefly introduce the main concepts related to this technique such as, linear and non-linear viscoelasticity, relaxation time, response of material when it is submitted to a sinusoidal or other periodic stress. Moreover, the main applications of this technique in polymers and polymer blends are also presented. The discussion includes: phase behavior, crystallization; spectrum of relaxation as a function of frequency or temperature; correlation between the material damping and its acoustic and mechanical properties.

Size Effect and Notch Size Effect in Metal Fatigue

It is a well known phenomenon that the constant amplitude fatigue limit of a large component is lower than the fatigue limit of a small specimen made of the same material. In notched components the opposite occurs: the fatigue limit defined as the maximum stress at the notch is higher than that achieved with smooth specimens. These two effects have been taken into account in most design handbooks with the help of experimental formulas or design curves. The basic idea of this study is that the size effect can mainly be explained by the statistical size effect. A component subjected to an alternating load can be assumed to form a sample of initiated cracks at the end of the crack initiation phase. The size of the sample depends on the size of the specimen in question. The main objective of this study is to develop a statistical model for the estimation of this kind of size effect. It was shown that the size of a sample of initiated cracks shall be based on the stressed surface area of the specimen. In case of varying stress distribution, an effective stress area must be calculated. It is based on the decreasing probability of equally sized initiated cracks at lower stress level. If the distribution function of the parent population of cracks is known, the distribution of the maximum crack size in a sample can be defined. This makes it possible to calculate an estimate of the largest expected crack in any sample size. The estimate of the fatigue limit can now be calculated with the help of the linear elastic fracture mechanics. In notched components another source of size effect has to be taken into account. If we think about two specimens which have similar shape, but the size is different, it can be seen that the stress gradient in the smaller specimen is steeper. If there is an initiated crack in both of them, the stress intensity factor at the crack in the larger specimen is higher. The second goal of this thesis is to create a calculation method for this factor which is called the geometric size effect. The proposed method for the calculation of the geometric size effect is also based on the use of the linear elastic fracture mechanics. It is possible to calculate an accurate value of the stress intensity factor in a non linear stress field using weight functions. The calculated stress intensity factor values at the initiated crack can be compared to the corresponding stress intensity factor due to constant stress. The notch size effect is calculated as the ratio of these stress intensity factors. The presented methods were tested against experimental results taken from three German doctoral works. Two candidates for the parent population of initiated cracks were found: the Weibull distribution and the log normal distribution. Both of them can be used successfully for the prediction of the statistical size effect for smooth specimens. In case of notched components the geometric size effect due to the stress gradient shall be combined with the statistical size effect. The proposed method gives good results as long as the notch in question is blunt enough. For very sharp notches, stress concentration factor about 5 or higher, the method does not give sufficient results. It was shown that the plastic portion of the strain becomes quite high at the root of this kind of notches. The use of the linear elastic fracture mechanics becomes therefore questionable.

Um estudo teórico relativo à não-linearidade da ligação de hidrogênio em sistemas heterocíclicos C2H4O-C2H2 e C2H4S-C2H2

B3LYP/6-31G(d,p) calculations were used to determine the optimized geometries of the C2H4O-C2H2 and C2H4S-C2H2 heterocyclic hydrogen-bonded complexes. Results of structural, rotational, electronic and vibrational parameters indicate that the hydrogen bonding is non-linear due to the pi bond of the acetylene interacting with the hydrogen atoms of the methyl groups of the three-membered rings. Moreover, the theoretical investigation showed that the non-linearity is much more intriguing, since there is a structural disjunction on the acetylene within the heterocyclic system.

Biotransformation and endocrine disruptive effects of contaminants in ringed seals - implications for monitoring and risk assessment

Marine mammals are exposed to persistent organic pollutants (POPs), which may be biotransformed to metabolites some of which are highly toxic. Both POPs and their metabolites may lead to adverse health effects, which have been studied using various biomarkers. Changes in endocrine homeostasis have been suggested to be sensitive biomarkers for contaminant-related effects. The overall objective of this doctoral thesis was to investigate biotransformation capacity of POPs and their potential endocrine disruptive effects in two contrasting ringed seal populations from the low contaminated Svalbard area and from the highly contaminated Baltic Sea. Biotransformation capacity was studied by determining the relationships between congener-specific patterns and concentrations of polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), polybrominated diphenyl ethers (PBDEs) and their hydroxyl (OH)- and/or methylsulfonyl (MeSO₂)-metabolites, and catalytic activities of hepatic xenobiotic-metabolizing phase I and II enzymes. The results suggest that the biotransformation of PCBs, PBDEs and toxaphenes in ringed seals depends on the congener-specific halogen-substitution pattern. Biotransformation products detected in the seals included OH-PCBs, MeSO₂-PCBs and –DDE, pentachlorophenol, 4-OHheptachlorostyrene, and to a minor extent OH-PBDEs. The effects of life history state (moulting and fasting) on contaminant status and potential biomarkers for endocrine disruption, including hormone and vitamin homeostasis, were investigated in the low contaminated ringed seal population from Svalbard. Moulting/fasting status strongly affected thyroid, vitamin A and calcitriol homeostasis, body condition and concentrations of POPs and their OH-metabolites. In contrast, moulting/fasting status was not associated with variations in vitamin E levels. Endocrine disruptive effects on multiple endpoints were investigated in the two contrasting ringed seal populations. The results suggest that thyroid, vitamin A and calcitriol homeostasis may be affected by the exposure of contaminants and/or their metabolites in the Baltic ringed seals. Complex and non-linear relationships were observed between the contaminant levels and the endocrine variables. Positive relationships between circulating free and total thyroid hormone concentration ratios and OH-PCBs suggest that OH-PCBs may mediate the disruption of thyroid hormone transport in plasma. Species differences in thyroid and bone-related effects of contaminants were studied in ringed and grey seals from low contaminated references areas and from the highly contaminated Baltic Sea. The results indicate that these two species living at the same environment approximately at the same trophic level respond in a very different way to contaminant exposure. The results of this thesis suggest that the health status of the Baltic ringed seals has still improved during the last decade. PCB and DDE levels have decreased in these seals and the contaminant-related effects are different today than a decade ago. The health of the Baltic ringed seals is still suggested to be affected by the contaminant exposure. At the present level of the contaminant exposure the Baltic ringed seals seem to be at a zone where their body is able to compensate for the contaminant-mediated endocrine disruption. Based on the results of this thesis, several recommendations that could be applied on monitoring and assessing risk for contaminant effects are provided. Circulating OH-metabolites should be included in monitoring and risk assessment programs due to their high toxic potential. It should be noted that endogenous variables may have complex and highly variable responses to contaminant exposure including non-linear responses. These relationships may be further confounded by life history status. Therefore, it is highly recommended that when using variables related to endocrine homeostasis to investigate/monitor or assess the risk of contaminant effects in seals, the life history status of the animal should be carefully taken into consideration. This applies especially when using thyroid, vitamin A or calcitriolrelated parameters during moulting/fasting period. Extrapolations between species for assessing risk for contaminant effects in phocid seals should be avoided.