Ihwg-μnir: A Miniaturised Near-infrared Gas Sensor Based On Substrate-integrated Hollow Waveguides Coupled To A Micro-nir-spectrophotometer.

A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.

Censored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution.

In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.

Factors Associated With The Age Of The Onset Of Diabetes In Women Aged 50 years Or More: A Population-based Study.

Investigate factors associated with the onset of diabetes in women aged more than 49 years. Cross-sectional, population-based study using self-reports with 622 women. The dependent variable was the age of occurrence of diabetes using the life table method. Cox multiple regression models were adjusted to analyse the onset of diabetes according to predictor variables. Sociodemographic, clinical and behavioural factors were evaluated. Of the 622 women interviewed, 22.7% had diabetes. The mean age at onset was 56 years. The factors associated with the age of occurrence of diabetes were self-rated health (very good, good) (coefficient=-0.792; SE of the coefficient=0.215; p=0.0001), more than two individuals living in the household (coefficient=0.656, SE of the coefficient=0.223; p=0.003), and body mass index (BMI) (kg/m(2)) at 20-30 years of age (coefficient= 0.056, SE of the coefficient=0.023; p=0.014). Self-rated health considered good or very good was associated with a higher rate of survival without diabetes. Sharing a home with two or more other people and a weight increase at 20-30 years of age was associated with the onset of type 2 diabetes.

Augmented Mixed Models For Clustered Proportion Data.

Often in biomedical research, we deal with continuous (clustered) proportion responses ranging between zero and one quantifying the disease status of the cluster units. Interestingly, the study population might also consist of relatively disease-free as well as highly diseased subjects, contributing to proportion values in the interval [0, 1]. Regression on a variety of parametric densities with support lying in (0, 1), such as beta regression, can assess important covariate effects. However, they are deemed inappropriate due to the presence of zeros and/or ones. To evade this, we introduce a class of general proportion density, and further augment the probabilities of zero and one to this general proportion density, controlling for the clustering. Our approach is Bayesian and presents a computationally convenient framework amenable to available freeware. Bayesian case-deletion influence diagnostics based on q-divergence measures are automatic from the Markov chain Monte Carlo output. The methodology is illustrated using both simulation studies and application to a real dataset from a clinical periodontology study.

Geographical Distribution Of The Association Between El Niño South Oscillation And Dengue Fever In The Americas: A Continental Analysis Using Geographical Information System-based Techniques.

El Niño South Oscillation (ENSO) is one climatic phenomenon related to the inter-annual variability of global meteorological patterns influencing sea surface temperature and rainfall variability. It influences human health indirectly through extreme temperature and moisture conditions that may accelerate the spread of some vector-borne viral diseases, like dengue fever (DF). This work examines the spatial distribution of association between ENSO and DF in the countries of the Americas during 1995-2004, which includes the 1997-1998 El Niño, one of the most important climatic events of 20(th) century. Data regarding the South Oscillation index (SOI), indicating El Niño-La Niña activity, were obtained from Australian Bureau of Meteorology. The annual DF incidence (AIy) by country was computed using Pan-American Health Association data. SOI and AIy values were standardised as deviations from the mean and plotted in bars-line graphics. The regression coefficient values between SOI and AIy (rSOI,AI) were calculated and spatially interpolated by an inverse distance weighted algorithm. The results indicate that among the five years registering high number of cases (1998, 2002, 2001, 2003 and 1997), four had El Niño activity. In the southern hemisphere, the annual spatial weighted mean centre of epidemics moved southward, from 6° 31' S in 1995 to 21° 12' S in 1999 and the rSOI,AI values were negative in Cuba, Belize, Guyana and Costa Rica, indicating a synchrony between higher DF incidence rates and a higher El Niño activity. The rSOI,AI map allows visualisation of a graded surface with higher values of ENSO-DF associations for Mexico, Central America, northern Caribbean islands and the extreme north-northwest of South America.

Modeling The Effects Of Temperature And Ph On The Resistance Of Alicyclobacillus Acidoterrestris In Conventional Heat-treated Fruit Beverages Through A Meta-analysis Approach.

In this work, all publicly-accessible published findings on Alicyclobacillus acidoterrestris heat resistance in fruit beverages as affected by temperature and pH were compiled. Then, study characteristics (protocols, fruit and variety, °Brix, pH, temperature, heating medium, culture medium, inactivation method, strains, etc.) were extracted from the primary studies, and some of them incorporated to a meta-analysis mixed-effects linear model based on the basic Bigelow equation describing the heat resistance parameters of this bacterium. The model estimated mean D* values (time needed for one log reduction at a temperature of 95 °C and a pH of 3.5) of Alicyclobacillus in beverages of different fruits, two different concentration types, with and without bacteriocins, and with and without clarification. The zT (temperature change needed to cause one log reduction in D-values) estimated by the meta-analysis model were compared to those ('observed' zT values) reported in the primary studies, and in all cases they were within the confidence intervals of the model. The model was capable of predicting the heat resistance parameters of Alicyclobacillus in fruit beverages beyond the types available in the meta-analytical data. It is expected that the compilation of the thermal resistance of Alicyclobacillus in fruit beverages, carried out in this study, will be of utility to food quality managers in the determination or validation of the lethality of their current heat treatment processes.

Projeto de caixa de madeira para manga (Mangifera Indica L.)

Losses of horticulture product in Brazil are significant and among the main causes are the use of inappropriate boxes and the absence of a cold chain. A project for boxes is proposed, based on computer simulations, optimization and experimental validation, trying to minimize the amount of wood associated with structural and ergonomic aspects and the effective area of the openings. Three box prototypes were designed and built using straight laths with different configurations and areas of openings (54% and 36%). The cooling efficiency of Tommy Atkins mango (Mangifera Indica L.) was evaluated by determining the cooling time for fruit packed in the wood models and packed in the commercially used cardboard boxes, submitted to cooling in a forced-air system, at a temperature of 6ºC and average relative humidity of 85.4±2.1%. The Finite Element Method was applied, for the dimensioning and structural optimization of the model with the best behavior in relation to cooling. All wooden boxes with fruit underwent vibration testing for two hours (20 Hz). There was no significant difference in average cooling time in the wooden boxes (36.08±1.44 min); however, the difference was significant in comparison to the cardboard boxes (82.63±29.64 min). In the model chosen for structural optimization (36% effective area of openings and two side laths), the reduction in total volume of material was 60% and 83% in the cross section of the columns. There was no indication of mechanical damage in the fruit after undergoing the vibration test. Computer simulations and structural study may be used as a support tool for developing projects for boxes, with geometric, ergonomic and thermal criteria.

Phase transitions in biodegradable films based on blends of gelatin and poly (vinyl alcohol)

The aim of this work was to study the effect of the hydrolysis degree (HD) and the concentration (C PVA) of two types of poly (vinyl alcohol) (PVA) and the effect of the type and the concentration of plasticizers on the phase properties of biodegradable films based on blends of gelatin and PVA, using a response-surface methodology. The films were made by casting and the studied properties were their glass (Tg) and melting (Tm) transition temperatures, which were determined by diferential scanning calorimetry (DSC). For the data obtained on the first scan, the fitting of the linear model was statistically significant and predictive only for the second melting temperature. In this case, the most important effect on the second Tm of the first scan was due to the HD of the PVA. In relation to the second scan, the linear model could be fit to Tg data with only two statistically significant parameters. Both the PVA and plasticizer concentrations had an important effect on Tg. Concerning the second Tm of the second scan, the linear model was fit to data with two statistically significant parameters, namely the HD and the plasticizer concentration. But, the most important effect was provoked by the HD of the PVA.

Swine deep bedding ashes as a mineral additive for cement based mortar

The sustainability of intensive swine production demands alternative destinations for the generated residues. Ashes from swine rice husk-based deep bedding were tested as a mineral addition for cement mortars. The ashes were obtained at 400 to 600ºC, ground and sieved through a 325 mesh sieve (# 0.045 mm). The characterization of the ashes included the determination of the index of pozzolanic activity with lime. The ashes were also tested as partial substitutes of Portland cement. The mortars were prepared using a cement:sand proportion of 1:1.5, and with water/cement ratio of 0.4. Three percentages of mass substitution of the cement were tested: 10, 20 and 30%. Mortar performances were assessed at 7 and 28 days determining their compressive strength. The chosen condition for calcinations at the laboratory scale was related to the maximum temperature of 600ºC since the resulting ashes contained vitreous materials and presented satisfactory values for the pozzolanic index under analysis. The pozzolanic activity indicated promising results for ashes produced at 600ºC as a replacement of up to 30% in cement masses.

Análise de jatos de baixos níveis associados aum sistema convectivo de mesoescala na américa do sul: um estudo de caso

The Levei Low Jet (LLJ) observed in the Porto Alegre metropolitan region, Rio Grande do Sul State, Brazil, was analyzed using 1989-2003 at 00:00 and 12:00 UTC upper-air observations. The LLJ classification criteria proposed by Bonner (1968) and modified by Whiteman et aI. (1997) were applied to determine the LLJ occurrence. Afterwards was selected a LLJ event, that was one of the most intense observed in the summer (01/27/2002 at 12:00 UTC), during the study period. ln this study were used as tools: atmospheric soundings, GOES-8 satellite images, and wind, temperature and specific humidity fields from GLOBAL, ETA and BRAMS models. Based on the numerical analysis was possible to verify that the three models overestimated the specific humidity and potential temperature values, at LLJ time occurrence. The wind speed was underestimated by the models. It was observed in the study region, at 12:00 UTC (LLJ detected hour in the Porto Alegre region), by three models, warm and wet air from north, generating conditions to Mesoscale Convective System (MCS) formation and intensification.

A contribution to the phytogeography of Brazilian campos: an analysis based on Poaceae

Twenty areas from eight Brazilian states were compared according to a list of 224 species of Poaceae. In order to determinate affinity patterns between the areas, a binary matrix was submitted to cluster and ordination analysis. The patterns found were then faced to climate and geographic position. The scores corresponding to the areas obtained from the cluster analysis showed a strong correlation to temperature. The scores corresponding to the species suggest a gradient that associates distribution patterns to the photosynthetic pathway (C3 or C4). The current results suggest that the traditional classification of the Southern American grasslands might require some modification in order to be broadly applicable in the Brazilian context.

A novel polar-based human face recognition computational model

Motivated by a recently proposed biologically inspired face recognition approach, we investigated the relation between human behavior and a computational model based on Fourier-Bessel (FB) spatial patterns. We measured human recognition performance of FB filtered face images using an 8-alternative forced-choice method. Test stimuli were generated by converting the images from the spatial to the FB domain, filtering the resulting coefficients with a band-pass filter, and finally taking the inverse FB transformation of the filtered coefficients. The performance of the computational models was tested using a simulation of the psychophysical experiment. In the FB model, face images were first filtered by simulated V1- type neurons and later analyzed globally for their content of FB components. In general, there was a higher human contrast sensitivity to radially than to angularly filtered images, but both functions peaked at the 11.3-16 frequency interval. The FB-based model presented similar behavior with regard to peak position and relative sensitivity, but had a wider frequency band width and a narrower response range. The response pattern of two alternative models, based on local FB analysis and on raw luminance, strongly diverged from the human behavior patterns. These results suggest that human performance can be constrained by the type of information conveyed by polar patterns, and consequently that humans might use FB-like spatial patterns in face processing.

The full Bayesian significance test for mixture models: results in gene expression clustering

Gene clustering is a useful exploratory technique to group together genes with similar expression levels under distinct cell cycle phases or distinct conditions. It helps the biologist to identify potentially meaningful relationships between genes. In this study, we propose a clustering method based on multivariate normal mixture models, where the number of clusters is predicted via sequential hypothesis tests: at each step, the method considers a mixture model of m components (m = 2 in the first step) and tests if in fact it should be m - 1. If the hypothesis is rejected, m is increased and a new test is carried out. The method continues (increasing m) until the hypothesis is accepted. The theoretical core of the method is the full Bayesian significance test, an intuitive Bayesian approach, which needs no model complexity penalization nor positive probabilities for sharp hypotheses. Numerical experiments were based on a cDNA microarray dataset consisting of expression levels of 205 genes belonging to four functional categories, for 10 distinct strains of Saccharomyces cerevisiae. To analyze the method's sensitivity to data dimension, we performed principal components analysis on the original dataset and predicted the number of classes using 2 to 10 principal components. Compared to Mclust (model-based clustering), our method shows more consistent results.

Dynamical models for computer viruses propagation

Nowadays, digital computer systems and networks are the main engineering tools, being used in planning, design, operation, and control of all sizes of building, transportation, machinery, business, and life maintaining devices. Consequently, computer viruses became one of the most important sources of uncertainty, contributing to decrease the reliability of vital activities. A lot of antivirus programs have been developed, but they are limited to detecting and removing infections, based on previous knowledge of the virus code. In spite of having good adaptation capability, these programs work just as vaccines against diseases and are not able to prevent new infections based on the network state. Here, a trial on modeling computer viruses propagation dynamics relates it to other notable events occurring in the network permitting to establish preventive policies in the network management. Data from three different viruses are collected in the Internet and two different identification techniques, autoregressive and Fourier analyses, are applied showing that it is possible to forecast the dynamics of a new virus propagation by using the data collected from other viruses that formerly infected the network. Copyright (c) 2008 J. R. C. Piqueira and F. B. Cesar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Evaluation of Antiproliferative, Anti-Type 2 Diabetes, and Antihypertension Potentials of Ellagitannins from Strawberries (Fragaria x ananassa Duch.) Using In Vitro Models

Strawberries represent the main source of ellagic acid derivatives in the Brazilian diet, corresponding to more than 50% of all phenolic compounds found in the fruit. There is a particular interest in the determination of the ellagic acid content in fruits because of possible chemopreventive benefits. In the present study, the potential health benefits of purified ellagitannins from strawberries were evaluated in relation to the antiproliferative activity and in vitro inhibition of alpha-amylase, alpha-glucosidase, and angiotensin I-converting enzyme (ACE) relevant for potential management of hyperglycemia and hypertension. Therefore, a comparison among ellagic acid, purified ellagitannins, and a strawberry extract was done to evaluate the possible synergistic effects of phenolics. In relation to the antiproliferative activity, it was observed that ellagic acid had the highest percentage inhibition of cell proliferation. The strawberry extract had lower efficacy in inhibiting the cell proliferation, indicating that in the case of this fruit there is no synergism. Purified ellagitannins had high alpha-amylase and ACE inhibitory activities. However, these compounds had low alpha-glucosidase inhibitory activity. These results suggested that the ellagitannins and ellagic acid have good potential for the management of hyperglycemia and hypertension linked to type 2 diabetes. However, further studies with animal and human models are needed to advance the in vitro assay-based biochemical rationale from this study.