Critical behavior of a contact process with aperiodic transition rates

We performed Monte Carlo simulations to investigate the steady-state critical behavior of a one-dimensional contact process with an aperiodic distribution of rates of transition. As in the presence of randomness, spatial fluctuations can lead to changes of critical behavior. For sufficiently weak fluctuations, we give numerical evidence to show that there is no departure from the universal critical behavior of the underlying uniform model. For strong spatial fluctuations, the analysis of the data indicates a change of critical universality class.

An entropy-based approach to automatic image segmentation of satellite images

An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation. (C) 2010 Elsevier B.V. All rights reserved.

Intrinsically Multivariate Predictive Genes

Canalizing genes possess such broad regulatory power, and their action sweeps across a such a wide swath of processes that the full set of affected genes are not highly correlated under normal conditions. When not active, the controlling gene will not be predictable to any significant degree by its subject genes, either alone or in groups, since their behavior will be highly varied relative to the inactive controlling gene. When the controlling gene is active, its behavior is not well predicted by any one of its targets, but can be very well predicted by groups of genes under its control. To investigate this question, we introduce in this paper the concept of intrinsically multivariate predictive (IMP) genes, and present a mathematical study of IMP in the context of binary genes with respect to the coefficient of determination (CoD), which measures the predictive power of a set of genes with respect to a target gene. A set of predictor genes is said to be IMP for a target gene if all properly contained subsets of the predictor set are bad predictors of the target but the full predictor set predicts the target with great accuracy. We show that logic of prediction, predictive power, covariance between predictors, and the entropy of the joint probability distribution of the predictors jointly affect the appearance of IMP genes. In particular, we show that high-predictive power, small covariance among predictors, a large entropy of the joint probability distribution of predictors, and certain logics, such as XOR in the 2-predictor case, are factors that favor the appearance of IMP. The IMP concept is applied to characterize the behavior of the gene DUSP1, which exhibits control over a central, process-integrating signaling pathway, thereby providing preliminary evidence that IMP can be used as a criterion for discovery of canalizing genes.

An information-theoretic approach to statistical dependence: Copula information

We discuss the connection between information and copula theories by showing that a copula can be employed to decompose the information content of a multivariate distribution into marginal and dependence components, with the latter quantified by the mutual information. We define the information excess as a measure of deviation from a maximum-entropy distribution. The idea of marginal invariant dependence measures is also discussed and used to show that empirical linear correlation underestimates the amplitude of the actual correlation in the case of non-Gaussian marginals. The mutual information is shown to provide an upper bound for the asymptotic empirical log-likelihood of a copula. An analytical expression for the information excess of T-copulas is provided, allowing for simple model identification within this family. We illustrate the framework in a financial data set. Copyright (C) EPLA, 2009

Evaluation of some metals in Brazilian coffees cultivated during the process of conversion from conventional to organic agriculture

The aim of this study was to evaluate the presence of nutrients and toxic elements in coffees cultivated during the process of conversion, on organic agriculture, in southwest Bahia, Brazil. Levels of the nutrients and toxic elements were determined in samples of soils and coffee tissues from two transitional organic farms by atomic absorption spectrometry (FAAS). The metals in soil samples were extracted by Mehlich1 and USEPA-3050 procedures. Coffee samples from both farms presented relatively high levels of Cd, Zn and Cu (0.75,45.4 and 14.9 mu g g(-1). respectively), but were still below the limits specified by the Brazilian Food Legislation. The application of statistical methods showed that this finding can be attributed to the addition of high amounts of organic matter during the flowering tree period which can act on the bioavailability of metal ions in soils. (C) 2009 Elsevier Ltd. All rights reserved.

Automatic devices for monitoring environmentally induced auto-oxidative degradation of artistic materials in conservation sites

This paper describes an automatic device for in situ and continuous monitoring of the ageing process occurring in natural and synthetic resins widely used in art and in the conservation and restoration of cultural artefacts. The results of tests carried out under accelerated ageing conditions are also presented. This easy-to-assemble palm-top device, essentially consists of oscillators based on quartz crystal resonators coated with films of the organic materials whose response to environmental stress is to be addressed. The device contains a microcontroller which selects at pre-defined time intervals the oscillators and records and stores their oscillation frequency. The ageing of the coatings, caused by the environmental stress and resulting in a shift in the oscillation frequency of the modified crystals, can be straightforwardly monitored in this way. The kinetics of this process reflects the level of risk damage associated with a specific microenvironment. In this case, natural and artificial resins, broadly employed in art and restoration of artistic and archaeological artefacts (dammar and Paraloid B72), were applied onto the crystals. The environmental stress was represented by visible and UV radiation, since the chosen materials are known to be photochemically active, to different extents. In the case of dammar, the results obtained are consistent with previous data obtained using a bench-top equipment by impedance analysis through discrete measurements and confirm that the ageing of this material is reflected in the gravimetric response of the modified quartz crystals. As for Paraloid B72, the outcome of the assays indicates that the resin is resistant to visible light, but is very sensitive to UV irradiation. The use of a continuous monitoring system, apart from being obviously more practical, is essential to identify short-term (i.e. reversible) events, like water vapour adsorption/desorption processes, and to highlight ageing trends or sudden changes of such trends. (C) 2007 Elsevier B.V. All rights reserved.

Mobile systems for monitoring Parkinson's disease

A challenge for the clinical management of Parkinson's disease (PD) is the large within- and between-patient variability in symptom profiles as well as the emergence of motor complications which represent a significant source of disability in patients. This thesis deals with the development and evaluation of methods and systems for supporting the management of PD by using repeated measures, consisting of subjective assessments of symptoms and objective assessments of motor function through fine motor tests (spirography and tapping), collected by means of a telemetry touch screen device. One aim of the thesis was to develop methods for objective quantification and analysis of the severity of motor impairments being represented in spiral drawings and tapping results. This was accomplished by first quantifying the digitized movement data with time series analysis and then using them in data-driven modelling for automating the process of assessment of symptom severity. The objective measures were then analysed with respect to subjective assessments of motor conditions. Another aim was to develop a method for providing comparable information content as clinical rating scales by combining subjective and objective measures into composite scores, using time series analysis and data-driven methods. The scores represent six symptom dimensions and an overall test score for reflecting the global health condition of the patient. In addition, the thesis presents the development of a web-based system for providing a visual representation of symptoms over time allowing clinicians to remotely monitor the symptom profiles of their patients. The quality of the methods was assessed by reporting different metrics of validity, reliability and sensitivity to treatment interventions and natural PD progression over time. Results from two studies demonstrated that the methods developed for the fine motor tests had good metrics indicating that they are appropriate to quantitatively and objectively assess the severity of motor impairments of PD patients. The fine motor tests captured different symptoms; spiral drawing impairment and tapping accuracy related to dyskinesias (involuntary movements) whereas tapping speed related to bradykinesia (slowness of movements). A longitudinal data analysis indicated that the six symptom dimensions and the overall test score contained important elements of information of the clinical scales and can be used to measure effects of PD treatment interventions and disease progression. A usability evaluation of the web-based system showed that the information presented in the system was comparable to qualitative clinical observations and the system was recognized as a tool that will assist in the management of patients.

Automating condition monitoring of vegetation on railway trackbeds and embankments

Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, as well as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of(human) raters’ visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithm which quantifies the vegetation cover was able to process 98% of the im-age data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%.Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance.A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust monitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed form the foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.

Recent developments in statistical methods for detecting genetic loci affecting phenotypic variability

A number of recent works have introduced statistical methods for detecting genetic loci that affect phenotypic variability, which we refer to as variability-controlling quantitative trait loci (vQTL). These are genetic variants whose allelic state predicts how much phenotype values will vary about their expected means. Such loci are of great potential interest in both human and non-human genetic studies, one reason being that a detected vQTL could represent a previously undetected interaction with other genes or environmental factors. The simultaneous publication of these new methods in different journals has in many cases precluded opportunity for comparison. We survey some of these methods, the respective trade-offs they imply, and the connections between them. The methods fall into three main groups: classical non-parametric, fully parametric, and semi-parametric two-stage approximations. Choosing between alternatives involves balancing the need for robustness, flexibility, and speed. For each method, we identify important assumptions and limitations, including those of practical importance, such as their scope for including covariates and random effects. We show in simulations that both parametric methods and their semi-parametric approximations can give elevated false positive rates when they ignore mean-variance relationships intrinsic to the data generation process. We conclude that choice of method depends on the trait distribution, the need to include non-genetic covariates, and the population size and structure, coupled with a critical evaluation of how these fit with the assumptions of the statistical model.

Statistical modelling of extreme rainfall in Madeira Island

Extreme rainfall events have triggered a significant number of flash floods in Madeira Island along its past and recent history. Madeira is a volcanic island where the spatial rainfall distribution is strongly affected by its rugged topography. In this thesis, annual maximum of daily rainfall data from 25 rain gauge stations located in Madeira Island were modelled by the generalised extreme value distribution. Also, the hypothesis of a Gumbel distribution was tested by two methods and the existence of a linear trend in both distributions parameters was analysed. Estimates for the 50– and 100–year return levels were also obtained. Still in an univariate context, the assumption that a distribution function belongs to the domain of attraction of an extreme value distribution for monthly maximum rainfall data was tested for the rainy season. The available data was then analysed in order to find the most suitable domain of attraction for the sampled distribution. In a different approach, a search for thresholds was also performed for daily rainfall values through a graphical analysis. In a multivariate context, a study was made on the dependence between extreme rainfall values from the considered stations based on Kendall’s τ measure. This study suggests the influence of factors such as altitude, slope orientation, distance between stations and their proximity of the sea on the spatial distribution of extreme rainfall. Groups of three pairwise associated stations were also obtained and an adjustment was made to a family of extreme value copulas involving the Marshall–Olkin family, whose parameters can be written as a function of Kendall’s τ association measures of the obtained pairs.

Multivariate analysis for the classification and differentiation of Madeira wines according to main grape varieties

In order to differentiate and characterize Madeira wines according to main grape varieties, the volatile composition (higher alcohols, fatty acids, ethyl esters and carbonyl compounds) was determined for 36 monovarietal Madeira wine samples elaborated from Boal, Malvazia, Sercial and Verdelho white grape varieties. The study was carried out by headspace solid-phase microextraction technique (HS-SPME), in dynamic mode, coupled with gas chromatography–mass spectrometry (GC–MS). Corrected peak area data for 42 analytes from the above mentioned chemical groups was used for statistical purposes. Principal component analysis (PCA) was applied in order to determine the main sources of variability present in the data sets and to establish the relation between samples (objects) and volatile compounds (variables). The data obtained by GC–MS shows that the most important contributions to the differentiation of Boal wines are benzyl alcohol and (E)-hex-3-en-1-ol. Ethyl octadecanoate, (Z)-hex-3-en-1-ol and benzoic acid are the major contributions in Malvazia wines and 2-methylpropan-1-ol is associated to Sercial wines. Verdelho wines are most correlated with 5-(ethoxymethyl)-furfural, nonanone and cis-9-ethyldecenoate. A 96.4% of prediction ability was obtained by the application of stepwise linear discriminant analysis (SLDA) using the 19 variables that maximise the variance of the initial data set.

Auto-eficácia de alunos de administração: um estudo com concluintes do curso de graduação em Administração no Estado do Pará

The current study presents the characteristics of self-efficacy of students of Administration course, who work and do not work. The study was conducted through a field research, descriptive, addressed quantitatively using statistical procedures. Was studied a population composed of 394 students distributed in three Higher Education Institutions, in the metropolitan region of Belém, in the State of Pará. The sampling was not probabilistic by accessibility, with a sample of 254 subjects. The instrument for data collection was a questionnaire composed of a set of questions divided into three sections: the first related to sociodemographic data, the second section was built to identify the work situation of the respondent and the third section was built with issues related to General Perceived Self-Efficacy Scale proposed by Schwarzer and Jerusalem (1999). Sociodemographic data were processed using methods of descriptive statistics. This procedure allowed characterizing the subjects of the sample. To identify the work situation, the analysis of frequency and percentage was used, which allowed to classify in percentage, the respondents who worked and those that did not work, and the data related to the scale of self-efficacy were processed quantitatively by the method of multivariate statistics using the software of program Statistical Package for Social Sciences for Windows - SPSS, version 17 from the process of Exploratory Factor Analysis. This procedure allowed characterizing the students who worked and the students who did not worked. The results were discussed based on Social Cognitive Theory from the construct of self-efficacy of Albert Bandura (1977). The study results showed a young sample, composed the majority of single women with work experience, and indicated that the characteristics of self-efficacy of students who work and students who do not work are different. The self-efficacy beliefs of students who do not work are based on psychological expectations, whereas the students who work demonstrated that their efficacy beliefs are sustained by previous experiences. A student who does not work proved to be reliant in their abilities to achieve a successful performance in their activities, believing it to be easy to achieve your goals and to face difficult situations at work, simply by invest a necessary effort and trust in their abilities. One who has experience working proved to be reliant in their abilities to conduct courses of action, although know that it is not easy to achieve your goals, and in unexpected situations showed its ability to solve difficult problems

Avaliação de metodologia de preparo de amostra de petróleo por digestão ácida auxiliada por microondas para determinação de metais por ICP-OES

This project describes a methodology optimization that would allow for a more efficient microwave assisted digestion process for petroleum samples. With the possible chance to vary various factors at once to see if any one factor was significant enough in the answers, experimental planning was used. Microwave assisted digestion allows, through the application of potency, an increasing number of collisions between the HNO3 and H2O2 molecules, favoring sample opening for complex matrixes. For this, a 24 factorial experimental planning was used, varying potency, time and the volumes for HNO3 65% and H2O2 30%. To achieve the desired answers, several elements were monitored (C, Cu, Cr, Fe, Ni, Zn and V) through Inductively coupled plasma atomic emission spectroscopy (ICP-OES). With this initial study it was noticed that the HNO3 was not a significant factor for any of the statistical studies for any of the analytes and the other 3 factors and their interactions showed statistical significance. A Box Behnken experimental planning was used taking in consideration 3 factors: H2O2 volume, time (min) and Potency (W), Nitric Acid kept at 4mL for a mass of 0,1g of petroleum. The results were extremely satisfying showing higher efficiency in the digestion process and taking in a responsibility between the answers for each analyte and the carbon monitoring was achieved in the following conditions: 7mL of H2O2, 700 Watts of potency and a reaction time of 7 minutes with 4mL de HNO3 for a mass of 0,1g of petroleum. The optimized digestion process was applied to four different petroleum samples and the analytes determined by ICP-OES

Influência de fatores biopsicossociais sobre a mortalidade de idosos no município de Santa Cruz/RN: um estudo prospectivo

The aging process if characterizes for a complex events network, from multidimensional nature, that encloses biological, social, psychic and functional aspects. The alteration of one or more aspects can speed up the aging process, anticipating limitations and until the death in the aged. For an adjusted confrontation of this question is necessary an interdisciplinary vision, in which the some areas of the knowledge can interact and with this to intervenes of the best possible form. Then, information derived from studies of aspects related to incidence, morbidity-mortality and transition patterns, involved in the health-illness process can more accurately identify risk groups thereby establishing links between social factors, illness, incapacity and death. Thus, this study aimed to identify, by a multidimensional vision, the risk factors of mortality in a coorth of elderly in a city in the interior of the state of Rio Grande do Norte (RN), Brazil. A prospective study carried out in Santa Cruz RN, where 310 elderly were randomly selected to form a baseline. The follow-up was 53 months. The predictive variables were divided into sociodemographic, physical health, neuropsychiatric and functional capacity. The statistical analysis carried out by bivariate analysis, survival analysis, followed by binary logistic regression and Cox regression, in the multivariate analysis, considering significant levels p < 0.05 and confidence interval (CI) of 95%. A total of 60 (19.3%) elderly died during the follow-up, where cardiovascular disease was the main cause. The survival was approximately 24.8 months. The study of general survival showed, at 12, 24, 36, and 48 months of observation, a survival rate of 97%, 54%, 31%, and 5% respectively, with a statistical difference in survival only observed for the variables of cognitive function and Basic Activities of Daily Living. In the logistic regression analysis, the risk factors identified were cognitive deficits (OR = 8.74), poor perception of health (OR = 3.89) and dependence for Basic Activities of Daily Living (OR = 3.96). In the Cox analysis, as well as dependence for Basic Activities of Daily Living (HR = 3.17), cognitive deficit (HR = 4.30) and stroke (CVA) (HR = 3.49) continued as independent risk factors for death. The risk factors found in the study can be interpreted as the primary predictors for death among elderly members of the community. Therefore, improvements in health conditions, with actions towards sustaining an autonomous life with special attention for elderly with cognitive impairment, could mean additional healthy quality of life, resulting in the reduction of premature mortality in this population

Correlations among behavior, performance and environment in broiler breeders using multivariate analysis

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