Long-term stability of dentin matrix following treatment with various natural collagen cross-linkers

Objectives: Collagen disorganization is one of the main degradation patterns found in unsuccessful adhesive restorations. The hypothesis of this study was that pretreatment using natural collagen cross-linking agents rich in proanthocyanidin (PA) would improve mechanical properties and stability over time of the dentin collagen and, thus, confer a more resistant and lasting substrate for adhesive restorations. Methods: PA-based extracts, from grape seed (GSE), cocoa seed (CSE), cranberry (CRE), cinnamon (CNE) and acai berry (ACE) were applied over the demineralized dentin. The apparent elastic modulus (E) of the treated dentin collagen was analyzed over a 12 month period. Specimens were immersed in the respective solution and E values were obtained by a micro-flexural test at baseline, 10, 30, 60, 120 and 240 min. Samples were stored in artificial saliva and re-tested after 3, 6 and 12 months. Data was analyzed using ANOVA and Tukey test. Results: GSE and CSE extracts showed a time-dependent effect and were able to improve [240 min (MPa): GSE = 108.96 +/- 56.08: CSE = 59.21 +/- 24.87] and stabilize the E of the organic matrix [12 months (MPa): GSE = 40.91 +/- 19.69; CSE = 42.11 +/- 13.46]. CRE and CNE extracts were able to maintain the E of collagen matrices constant over 12 months [CRE = 11.17 +/- 7.22; CNE = 9.96 +/- 6.11; MPa]. ACE (2.64 +/- 1.22 MPa) and control groups immersed in neat distilled water (1.37 +/- 0.69 MPa) and ethanol-water (0.95 +/- 0.33 MPa) showed no effect over dentin organic matrix and enable their degradation and reduction of mechanical properties. Significance: Some PA-based extracts were capable of improving and stabilizing collagen matrices through exogenous cross-links induction. (C) 2011 Elsevier Ltd. All rights reserved.

Influence of matrix composition on polymerization stress development of experimental composites

Objective. Stress development at the tooth/restoration interface is one of the most important reasons for failure of adhesive restorations. The aim of this study was to evaluate the influence of BisGMA/TEGDMA (B/T) and UDMA/TEGDMA (U/T) ratios on polymerization stress (PS) and on the variables related to its development: degree of conversion (DC), polymerization maximum rate (Rp(max)), volumetric shrinkage (VS), elastic modulus (E), stress relaxation (SR) and viscosity of experimental composites. Method. Composites were formulated containing B/T or U/T in mol% ratios of 2: 8, 3: 7, 4: 6, 5: 5, 6: 4, 7: 3 and 8: 2, and 15 wt% of fumed silica. PS was determined with a universal testing machine. VS was measured with a linometer. E and SR were obtained in three-point bending. DC and Rp(max) were determined by real time NIR spectroscopy and viscosity was measured in viscometer. Data were submitted to one-way ANOVA, Tukey test (alpha = 0.05%) and regression analyses. Results. PS, VS, E and DC decreased and viscosity and Rp(max) increased with base monomer content in both series. PS showed strong correlation with VS, DC and viscosity. PS, VS and DC were higher and viscosity was lower for UDMA-based materials. Significance. Reduced viscosity, kinetics parameters and molecular characteristics led UDMA-based composites to elevated conversion and relatively lower PS at lower TEGDMA contents, compared to B/T composites. (C) 2010 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Influence of Artificial Accelerated Aging on Dimensional Stability of Acrylic Resins Submitted to Different Storage Protocols

Purpose: The aim of this study was to evaluate the influence of artificial accelerated aging on dimensional stability of two types of acrylic resins (thermally and chemically activated) submitted to different protocols of storage. Materials and Methods: One hundred specimens were made using a Teflon matrix (1.5cmx0.5mm) with four imprint marks, following the lost-wax casting method. The specimens were divided into ten groups, according to the type of acrylic resin, aging procedure, and storage protocol (30 days). GI: acrylic resins thermally activated, aging, storage in artificial saliva for 16 hours, distilled water for 8 hours; GII: thermal, aging, artificial saliva for 16 hours, dry for 8 hours; GIII: thermal, no aging, artificial saliva for 16 hours, distilled water for 8 hours, GIV: thermal, no aging, artificial saliva for 16 hours, dry for 8 hours; GV: acrylic resins chemically activated, aging, artificial saliva for 16 hours, distilled water for 8 hours; GVI: chemical, aging, artificial saliva for 16 hours, dry for 8 hours; GVII: chemical, no aging, artificial saliva for 16 hours, distilled water for 8 hours; GVIII: chemical, no aging, artificial saliva for 16 hours, dry for 8 hours GIX: thermal, dry for 24 hours; and GX: chemical, dry for 24 hours. All specimens were photographed before and after treatment, and the images were evaluated by software (UTHSCSA-Image Tool) that made distance measurements between the marks in the specimens (mm), calculating the dimensional stability. Data were submitted to statistical analysis (two-way ANOVA, Tukey test, p = 0.05). Results: Statistical analysis showed that the specimens submitted to storage in water presented the largest distance between both axes (major and minor), statistically different (p < 0.05) from control groups. Conclusions: All acrylic resins presented dimensional changes, and the artificial accelerated aging and storage period influenced these alterations.

Performance of a Brazilian population on the test of functional health literacy in adults

OBJECTIVE: To analyze the scoring obtained by an instrument, which evaluates the ability to read and understand items in the health care setting, according to education and age. METHODS: The short version of the Test of Functional Health Literacy in Adults was administered to 312 healthy participants of different ages and years of schooling. The study was conducted between 2006 and 2007, in the city of São Paulo, Southeastern Brazil. The test includes actual materials such as pill bottles and appointment slips and measures reading comprehension, assessing the ability to read and correctly pronounce a list of words and understand both prose passages and numerical information. Pearson partial correlations and a multiple regression model were used to verify the association between its scores and education and age. RESULTS: The mean age of the sample was 47.3 years(sd=16.8) and the mean education was 9.7 years(sd=5; range: 1 - 17). A total of 32.4% of the sample showed literacy/numeracy deficits, scoring in the inadequate and marginal functional health literacy ranges. Among the elderly (65 years or older) this rate increased to 51.6%. There was a positive correlation between schooling and scores (r=0.74; p<0.01) and a negative correlation between age and the scores (r=-0.259; p<0.01). The correlation between the scores and age was not significant when the effects of education were held constant (rp=-0.031, p=0.584). A significant association (B=3.877, Beta =0.733; p<0.001) was found between schooling and scores. Age was not a significant predictor in this model (B=-0.035, Beta=-0.22; p=0.584). CONCLUSIONS: The short version of the Test of Functional Health Literacy in Adults was a suitable tool to assess health literacy in the study population. The high number of individuals classified as functional illiterates in this test highlights the importance of special assistance to help them properly understand directions for healthcare.

Institutional and matrix support and its relationship with primary healthcare

OBJECTIVE To analyze whether the level of institutional and matrix support is associated with better certification of primary healthcare teams.METHODS In this cross-sectional study, we evaluated two kinds of primary healthcare support – 14,489 teams received institutional support and 14,306 teams received matrix support. Logistic regression models were applied. In the institutional support model, the independent variable was “level of support” (as calculated by the sum of supporting activities for both modalities). In the matrix support model, in turn, the independent variables were the supporting activities. The multivariate analysis has considered variables with p < 0.20. The model was adjusted by the Hosmer-Lemeshow test.RESULTS The teams had institutional and matrix supporting activities (84.0% and 85.0%), respectively, with 55.0% of them performing between six and eight activities. For the institutional support, we have observed 1.96 and 3.77 chances for teams who had medium and high levels of support to have very good or good certification, respectively. For the matrix support, the chances of their having very good or good certification were 1.79 and 3.29, respectively. Regarding to the association between institutional support activities and the certification, the very good or good certification was positively associated with self-assessment (OR = 1.95), permanent education (OR = 1.43), shared evaluation (OR = 1.40), and supervision and evaluation of indicators (OR = 1.37). In regards to the matrix support, the very good or good certification was positively associated with permanent education (OR = 1.50), interventions in the territory (OR = 1.30), and discussion in the work processes (OR = 1.23).CONCLUSIONS In Brazil, supporting activities are being incorporated in primary healthcare, and there is an association between the level of support, both matrix and institutional, and the certification result.

Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

Artificial Intelligence in geospatial analysis: applications of self-organizing maps in the context of geographic information science.

A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Systems.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Information Systems Outsourcing Adoption

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Using artificial neural networks to generate trading signals for crude oil, copper and gold futures

In this thesis, a feed-forward, back-propagating Artificial Neural Network using the gradient descent algorithm is developed to forecast the directional movement of daily returns for WTI, gold and copper futures. Out-of-sample back-test results vary, with some predictive abilities for copper futures but none for either WTI or gold. The best statistically significant hit rate achieved was 57% for copper with an absolute return Sharpe Ratio of 1.25 and a benchmarked Information Ratio of 2.11.

A structured inventory of spiders (Arachnida, Araneae) in natural and artificial forest gaps at Porto Urucu, Western Brazilian Amazonia

A preliminary survey of the spider fauna in natural and artificial forest gap formations at “Porto Urucu”, a petroleum/natural gas production facility in the Urucu river basin, Coari, Amazonas, Brazil is presented. Sampling was conducted both occasionally and using a protocol composed of a suite of techniques: beating trays (32 samples), nocturnal manual samplings (48), sweeping nets (16), Winkler extractors (24), and pitfall traps (120). A total of 4201 spiders, belonging to 43 families and 393 morphospecies, were collected during the dry season, in July, 2003. Excluding the occasional samples, the observed richness was 357 species. In a performance test of seven species richness estimators, the Incidence Based Coverage Estimator (ICE) was the best fit estimator, with 639 estimated species. To evaluate differences in species richness associated with natural and artificial gaps, samples from between the center of the gaps up to 300 meters inside the adjacent forest matrix were compared through the inspection of the confidence intervals of individual-based rarefaction curves for each treatment. The observed species richness was significantly higher in natural gaps combined with adjacent forest than in the artificial gaps combined with adjacent forest. Moreover, a community similarity analysis between the fauna collected under both treatments demonstrated that there were considerable differences in species composition. The significantly higher abundance of Lycosidae in artificial gap forest is explained by the presence of herbaceous vegetation in the gaps themselves. Ctenidae was significantly more abundant in the natural gap forest, probable due to the increase of shelter availability provided by the fallen trees in the gaps themselves. Both families are identified as potential indicators of environmental change related to the establishment or recovery of artificial gaps in the study area.

The black-white test score gap widens with age?

We re-examine the theoretical concept of a production function for cognitive achievement, and argue that an indirect production function that depends upon the variables that constrain parents' choices is both moretractable from an econometric point of view, and more interesting from an economic point of view than is a direct production function that depends upon a detailed list of direct inputs such as number of books in the household. We estimate flexible econometric models of indirect production functions for two achievement measures from the Woodcock-Johnson Revised battery, using data from two waves of the Child Development Supplement to the PSID. Elasticities of achievement measures with respect to family income and parents' educational levels are positive and significant. Gaps between scores of black and white children narrow or remain constant as children grow older, a result that differs from previous findings in the literature. The elasticities of achievement scores with respect to family income are substantially higher for children of black families, and there are some notable difference in elasticities with respect to parents' educational levels across blacks and whites.

Ultimate test bench for pediatric biventricular assist device based on artificial muscles.

Ventricular assist devices (VADs) are used in treatment for terminal heart failure or as a bridge to transplantation. We created biVAD using the artificial muscles (AMs) that supports both ventricles at the same time. We developed the test bench (TB) as the in vitro evaluating system to enable the measurement of performance. The biVAD exerts different pressure between left and right ventricle like the heart physiologically does. The heart model based on child's heart was constructed in silicone. This model was fitted with the biVAD. Two pipettes containing water with an ultrasonic sensor placed on top of each and attached to ventricles reproduced the preload and the after load of each ventricle by the real-time measurement of the fluid height variation proportionally to the exerted pressure. The LabVIEW software extrapolated the displaced volume and the pressure generated by each side of our biVAD. The development of a standardized protocol permitted the validation of the TB for in vitro evaluation, measurement of the performances of the AM biVAD herein, and reproducibility of data.

Imaging Properties of MS Lesions Correlate with Attention Deficits in Early Multiple Sclerosis

Introduction: Cognitive impairment affects 40-65% of multiple sclerosis (MS) patients, often since early stages of the disease (relapsing remitting MS, RRMS). Frequently affected functions are memory, attention or executive abilities but the most sensitive measure of cognitive deficits in early MS is the information processing speed (Amato, 2008). MRI has been extensively exploited to investigate the substrate of cognitive dysfunction in MS but the underlying physiopathological mechanisms remain unclear. White matter lesion load, whole-brain atrophy and cortical lesions' number play a role but correlations are in some cases modest (Rovaris, 2006; Calabrese, 2009). In this study, we aimed at characterizing and correlating the T1 relaxation times of cortical and sub-cortical lesions with cognitive deficits detected by neuropsychological tests in a group of very early RR MS patients. Methods: Ten female patients with very early RRMS (age: 31.6 ±4.7y; disease duration: 3.8 ±1.9y; EDSS disability score: 1.8 ±0.4) and 10 age- and gender-matched healthy volunteers (mean age: 31.2 ±5.8y) were included in the study. All participants underwent the following neuropsychological tests: Rao's Brief Repeatable Battery of Neuropsychological tests (BRB-N), Stockings of Cambridge, Trail Making Test (TMT, part A and B), Boston Naming Test, Hooper Visual Organization Test and copy of the Rey-Osterrieth Complex Figure. Within 2 weeks from neuropsychological assessment, participants underwent brain MRI at 3T (Magnetom Trio a Tim System, Siemens, Germany) using a 32-channel head coil. The imaging protocol included 3D sequences with 1x1x1.2 mm3 resolution and 256x256x160 matrix, except for axial 2D-FLAIR: -DIR (T2-weighted, suppressing both WM and CSF; Pouwels, 2006) -MPRAGE (T1-weighted; Mugler, 1991) -MP2RAGE (T1-weighted with T1 maps; Marques, 2010) -FLAIR SPACE (only for patient 4-10, T2-weighted; Mugler, 2001) -2D Axial FLAIR (0.9x0.9x2.5 mm3, 256x256x44 matrix). Lesions were identified by one experienced neurologist and radiologist using all contrasts, manually contoured and assigned to regional locations (cortical or sub-cortical). Lesion number, volume and T1 relaxation time were calculated for lesions in each contrast and in a merged mask representing the union of the lesions from all contrasts. T1 relaxation times of lesions were normalized with the mean T1 value in corresponding control regions of the healthy subjects. Statistical analysis was performed using GraphPad InStat software. Cognitive scores were compared between patients and controls with paired t-tests; p values ≤ 0.05 were considered significant. Spearmann correlation tests were performed between the cognitive tests, which differed significantly between patients and controls, and lesions' i) number ii) volume iii) T1 relaxation time iv) disease duration and v) years of study. Results: Cortical and sub-cortical lesions count, T1 values and volume are reported in Table 1 (A and B). All early RRMS patients showed cortical lesions (CLs) and the majority consisted of CLs type I (lesions with a cortical component extending to the sub-cortical tissue). The rest of cortical lesions were characterized as type II (intra-cortical lesions). No type III/IV lesions (large sub-pial lesions) were detected. RRMS patients were slightly less educated (13.5±2.5y vs. 16.3±1.8y of study, p=0.02) than the controls. Signs of cortical dysfunction (i.e. impaired learning, language, visuo-spatial skills or gnosis) were rare in all patients. However, patients showed on average lower scores on measures of visual attention and information processing speed (TMT-part A: p=0.01; TMT-part B: p=0.006; PASAT-included in the BRB-N: p=0.04). The T1 relaxation values of CLs type I negatively correlated with the TMT-part A score (r=0.78, p<0.01). The correlations of TMT-part B score and PASAT score with T1 relaxation time of lesions as well and the correlation between TMT-part A, TMT-part B and PASAT score with lesions' i) number ii) volume iii) disease duration and iv) years of study did not reach significance. In order to preclude possible influences from partial volume effects on the T1 values, the correlation between lesion volume and T1 value of CLs type I was calculated; no correlation was found, suggesting that partial volume effects did not affect the statistics. Conclusions: The present pilot study reports for the first time the presence and the T1 characteristics at 3 T of cortical lesions in very early RRMS (< 6 y disease duration). It also shows that CLS type I represents the most frequent cortical lesion type in this cohort of RRMS patients. In addition, it reveals a negative correlation between the attentional test TMT-part A and the T1 properties of cortical lesions type I. In other words, lower attention deficits are concomitant with longer T1-relaxation time in cortical lesions. In respect to this last finding, it could be speculated that long relaxation time correspond to a certain degree of tissue loss that is enough to stimulate compensatory mechanisms. This hypothesis is in line with previous fMRI studies showing functional compensatory mechanisms to help maintaining normal or sub-normal attention performances in RR MS patients (Penner, 2003).