Multivariate analysis of stable isotope data in the traceability process for birds

A análise isotópica tem se mostrado uma ferramenta de suma importância ao processo de rastreabilidade, no entanto, existem divergências nas análises estatísticas dos resultados, uma vez que os dados são dependentes e advindos de vários elementos químicos tais como Carbono, Hidrogênio, Oxigênio, Nitrogênio e Enxofre (CHON'S). Com o intuito de estabelecer a análise propícia para os dados de rastreabilidade em aves pela técnica de isótopos estáveis e avaliar a necessidade da análise conjunta das variáveis, foram usados dados de carbono-13 e de nitrogênio-15 de ovos (albúmen + gema) de poedeiras e músculo peitoral de frangos de corte, os quais foram submetidos à análise estatística univariada (Anova e complementada pelo teste de Tukey) e multivariada (Manova e Discriminante). Os dados foram analisados no software Minitab 16, e os resultados, consolidados na teoria, confirmam a necessidade de análise multivariada, mostrando também que a análise discriminante esclarece as dúvidas apresentadas nos resultados de outros métodos de análise comparados nesta pesquisa.

Analysis of procedures used in tooth avulsion by 100 dental surgeons

Accurate diagnosis and adequate treatment plan may constitute very complex tasks, particularly in tooth avulsion, because several variables are involved. In addition to the technical knowledge and clinical experience directed toward the quality of treatment, patient education may favorably influence the survival of replanted teeth. The aim of this study was to analyze the procedures used in the management of tooth avulsion by 100 dental surgeons (DSs). Thus, by means of a descriptive questionnaire, information was obtained about the profile of the professionals interviewed, procedures used in cases of tooth avulsion, and patient orientation and education. One hundred properly filled questionnaires were obtained. Descriptive statistics was used for the data, and the chi-squared statistics was employed (EPI-INFO 3.2 software). According to the results, this type of trauma is part of the routine of 15 DSs, although 71 have reported some experience with avulsed,teeth. Great deficiencies were found regarding root surface treatment and occlusal adjustment. Positive findings were related to socket treatment, adjunctive therapy, and patient education and orientation (extra-alveolar period, storage medium, manipulation of the avulsed tooth, replantation by the own patient). It was possible to conclude that 47.5% of the procedures reported by, 100 professionals interviewed are adequate, and patient education is favorable in 87.7% of cases, a fact that can positively interfere with the prognosis of tooth replantation.

Development and validation of the quantitative analysis of ampicillin sodium in powder for injection by Fourier-transform infrared spectroscopy (FT-IR)

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

Anxiety and depression in brazilian undergraduate students: the role of sociodemographic variables, undergraduate course characteristics and social skills

The prevalence of anxiety and depression disorders in undergraduate students is high and several variables can be influential. The aim is to verify the predictive value of social skills, sociodemographic variables, and course characteristics for depression and anxiety. A total of 1282 students of a public university, of both sexes and from different years and courses, participated in this study. Screening instruments for depression and anxiety were applied, as well as an instrument investigating social skills and a questionnaire covering socio demographic indicators and course characteristics. The data were analyzed using univariate analysis followed by multiple binary regression analysis in order to define the relevance of these depression and anxiety measures. The rates of anxiety and depression were 19.4% and 3.8%, respectively. The social skills and living situation were predictive of depression, with the social skills and course area (with higher prevalence for the exact and human sciences) remaining in the final model for anxiety. Such data have implications for psychological prevention and intervention with this population.

Detecting an abnormality in a recovery boiler using dynamic multivariate data analysis with parallel coordinate plots

Data visualization techniques are powerful in the handling and analysis of multivariate systems. One such technique known as parallel coordinates was used to support the diagnosis of an event, detected by a neural network-based monitoring system, in a boiler at a Brazilian Kraft pulp mill. Its attractiveness is the possibility of the visualization of several variables simultaneously. The diagnostic procedure was carried out step-by-step going through exploratory, explanatory, confirmatory, and communicative goals. This tool allowed the visualization of the boiler dynamics in an easier way, compared to commonly used univariate trend plots. In addition it facilitated analysis of other aspects, namely relationships among process variables, distinct modes of operation and discrepant data. The whole analysis revealed firstly that the period involving the detected event was associated with a transition between two distinct normal modes of operation, and secondly the presence of unusual changes in process variables at this time.

Assessment of field fertility and several in vitro sperm characteristics following the use of different Angus sires in a timed-AI program with suckled Nelore cows

In order to provide information that may help researchers to understand the main cause(s) of differences in bull fertility frequently observed in field trials, this study aimed to investigate conception rates as well as several in vitro sperm characteristics of different sires of unknown fertility utilized in a Timed-AI (TAI) program. Suckled Nelore cows submitted to the same TAI protocol were allocated into eight breeding groups of approximately 120 animals each. Frozen semen doses from three Angus bulls and three different batches from each bull were utilized. Approximately 100 doses from each batch were used in TAI. Sires, batches and AI technicians were equally distributed across breeding groups. Cows were examined for pregnancy diagnosis 40 d after TAI. For in vitro sperm analyses, the same thawing procedure was repeated in the laboratory to mimic field conditions. The following in vitro sperm characteristics were assessed: computerized motility, thermal resistance, plasma and acrosomal membrane integrity, lipid peroxidation, morphology, morphometry and chromatin structure. No effect of breeding group, body condition score, AI technician and sire was observed. However, some significant differences among bulls were detected in laboratory analyses. Semen from sire presenting numerically lower (P > 0.05) pregnancy/AI also presented lower (P < 0.05) values in all sperm characteristics analyzed in thermal resistance test at 4 h (Total Motility, Progressive Motility, Average Path Velocity, Straight-Line Velocity, Curvilinear Velocity, Amplitude of Lateral Head Displacement, Beat Cross Frequency, Straightness, Linearity, and Percentage of Rapidly Moving Cells), higher (P < 0.05) Major and Total Defects in sperm morphological test, lower (P < 0.05) Length, Ellipticity and Fourier parameter (Fourier 0) in sperm morphometric analysis as well as higher (P < 0.05) chromatin heterogeneity. It was concluded that, although no bull effect was observed in the field experiment, the sire that presented numerically lower pregnancy/AI also presented lower semen quality according to the laboratory analyses performed. (C) 2012 Elsevier B.V. All rights reserved.

Elucidating the internal structure of psychophysical timing performance in the sub-second and second range by utilizing confirmatory factor analysis

The most influential theoretical account in time psychophysics assumes the existence of a unitary internal clock based on neural counting. The distinct timing hypothesis, on the other hand, suggests an automatic timing mechanism for processing of durations in the sub-second range and a cognitively controlled timing mechanism for processing of durations in the range of seconds. Although several psychophysical approaches can be applied for identifying the internal structure of interval timing in the second and sub-second range, the existing data provide a puzzling picture of rather inconsistent results. In the present chapter, we introduce confirmatory factor analysis (CFA) to further elucidate the internal structure of interval timing performance in the sub-second and second range. More specifically, we investigated whether CFA would rather support the notion of a unitary timing mechanism or of distinct timing mechanisms underlying interval timing in the sub-second and second range, respectively. The assumption of two distinct timing mechanisms which are completely independent of each other was not supported by our data. The model assuming a unitary timing mechanism underlying interval timing in both the sub-second and second range fitted the empirical data much better. Eventually, we also tested a third model assuming two distinct, but functionally related mechanisms. The correlation between the two latent variables representing the hypothesized timing mechanisms was rather high and comparison of fit indices indicated that the assumption of two associated timing mechanisms described the observed data better than only one latent variable. Models are discussed in the light of the existing psychophysical and neurophysiological data.

THE USE OF MULTIVARIATE ANALYSIS OF COVARIANCE IN EVALUATING THE COMPARABILITY OF LABORATORY DETERMINATIONS IN COOPERATIVE STUDIES

The role of clinical chemistry has traditionally been to evaluate acutely ill or hospitalized patients. Traditional statistical methods have serious drawbacks in that they use univariate techniques. To demonstrate alternative methodology, a multivariate analysis of covariance model was developed and applied to the data from the Cooperative Study of Sickle Cell Disease.^ The purpose of developing the model for the laboratory data from the CSSCD was to evaluate the comparability of the results from the different clinics. Several variables were incorporated into the model in order to control for possible differences among the clinics that might confound any real laboratory differences.^ Differences for LDH, alkaline phosphatase and SGOT were identified which will necessitate adjustments by clinic whenever these data are used. In addition, aberrant clinic values for LDH, creatinine and BUN were also identified.^ The use of any statistical technique including multivariate analysis without thoughtful consideration may lead to spurious conclusions that may not be corrected for some time, if ever. However, the advantages of multivariate analysis far outweigh its potential problems. If its use increases as it should, the applicability to the analysis of laboratory data in prospective patient monitoring, quality control programs, and interpretation of data from cooperative studies could well have a major impact on the health and well being of a large number of individuals. ^

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

Quantitative analysis of morphological changes in yeast colonies growing on solid medium: the eccentricity and Fourier indices

The colony shape of four yeast species growing on agar medium wasmeasured for 116 days by image analysis. Initially, all the colonies are circular, with regular edges. The loss of circularity can be quantitatively estimated by the eccentricity index, Ei, calculated as the ratio between their orthogonal vertical and horizontal diameters. Ei can increase from 1 (complete circularity) to a maximum of 1.17–1.30, depending on the species. One colony inhibits its neighbour only when it has reached a threshold area. Then, Ei of the inhibited colony increases proportionally to the area of the inhibitory colony. The initial distance between colonies affects those threshold values but not the proportionality, Ei/area; this inhibition affects the shape but not the total surface of the colony. The appearance of irregularities in the edges is associated, in all the species, not with age but with nutrient exhaustion. The edge irregularity can be quantified by the Fourier index, Fi, calculated by the minimum number of Fourier coefficients that are needed to describe the colony contour with 99% fitness. An ad hoc function has been developed in Matlab v. 7.0 to automate the computation of the Fourier coefficients. In young colonies, Fi has a value between 2 (circumference) and 3 (ellipse). These values are maintained in mature colonies of Debaryomyces, but can reach values up to 14 in Saccharomyces.All the species studied showed the inhibition of growth in facing colony edges, but only three species showed edge irregularities associated with substrate exhaustion. Copyright © 2014 John Wiley & Sons, Ltd.

Impaired balance in developmental dyslexia? A meta-analysis of the contending evidence

Background: Developmental dyslexia is typically defined by deficits in phonological skills, but it is also associated with anomalous performance on measures of balance. Although balance assessments are included in several screening batteries for dyslexia, the association between impairments in literacy and deficits in postural stability could be due to the high co-occurrence of dyslexia with other developmental disorders in which impairments of motor behaviour are also prevalent. Methods: We identified 17 published studies that compared balance function between dyslexia and control samples and obtained effect-sizes for each. Contrast and association analyses were used to quantify the influence of hypothesised moderator variables on differences in effects across studies. Results: The mean effect-size of the balance deficit in dyslexia was .64 (95% CI = .44-.78) with heterogeneous findings across the population of studies. Probable co-occurrence of other developmental disorders and variability in intelligence scores in the dyslexia samples were the strongest moderator variables of effect-size. Conclusions: Balance deficits are associated with dyslexia, but these effects are apparently more strongly related to third variables other than to reading ability. Deficits of balance may indicate increased risk of developmental disorder, but are unlikely to be uniquely associated with dyslexia.

Analysis of β-amyloid (Aβ) deposition in the temporal lobe in Alzheimer's disease using Fourier (spectral) analysis

To determine the spatial pattern of ß-amyloid (Aß) deposition throughout the temporal lobe in Alzheimer's disease (AD). Methods: Sections of the complete temporal lobe from six cases of sporadic AD were immunolabelled with antibody against Aß. Fourier (spectral) analysis was used to identify sinusoidal patterns in the fluctuation of Aß deposition in a direction parallel to the pia mater or alveus. Results: Significant sinusoidal fluctuations in density were evident in 81/99 (82%) analyses. In 64% of analyses, two frequency components were present with density peaks of Aß deposits repeating every 500–1000 µm and at distances greater than 1000 µm. In 25% of analyses, three or more frequency components were present. The estimated period or wavelength (number of sample units to complete one full cycle) of the first and second frequency components did not vary significantly between gyri of the temporal lobe, but there was evidence that the fluctuations of the classic deposits had longer periods than the diffuse and primitive deposits. Conclusions: (i) Aß deposits exhibit complex sinusoidal fluctuations in density in the temporal lobe in AD; (ii) fluctuations in Aß deposition may reflect the formation of Aß deposits in relation to the modular and vascular structure of the cortex; and (iii) Fourier analysis may be a useful statistical method for studying the patterns of Aß deposition both in AD and in transgenic models of disease.

AIDS workplace *policy adoption and implementation in local government: An analysis of departmental variation

This is an empirical study whose purpose was to examine the process of innovation adoption as an adaptive response by a public organization and its subunits existing under varying degrees of environmental uncertainty. Meshing organization innovation research and contingency theory to form a theoretical framework, an exploratory case study design was undertaken in a large, metropolitan government located in an area with the fourth highest prevalence rate of HIV/AIDS in the country. A number of environmental and organizational factors were examined for their influence upon decision making in the adoption/non-adoption as well as implementation of any number of AIDS-related policies, practices, and programs.^ The major findings of the study are as follows. For the county government itself (macro level), no AIDS-specific workplace policies have been adopted. AIDS activities (AIDS education, AIDS Task Force, AIDS Coordinator, etc.), adopted county-wide early in the epidemic, have all been abandoned. Worker infection rates, in the aggregate and throughout the epidemic have been small. As a result, absent co-worker conflict (isolated and negligible), no increase in employee health care costs, no litigation regarding discrimination, and no major impact on workforce productivity, AIDS has basically become a non-issue at the strategic core of the organization. At the departmental level, policy adoption decisions varied widely. Here the predominant issue is occupational risk, i.e., both objective as well as perceived. As expected, more AIDS-related activities (policies, practices, and programs) were found in departments with workers known to have significant risk for exposure to the AIDS virus (fire rescue, medical examiner, police, etc.). AIDS specific policies, in the form of OSHA's Bloodborn Pathogen Standard, took place primarily because they were legislatively mandated. Union participation varied widely, although not necessarily based upon worker risk. In several departments, the union was a primary factor bringing about adoption decisions. Additional factors were identified and included organizational presence of AIDS expertise, availability of slack resources, and the existence of a policy champion. Other variables, such as subunit size, centralization of decision making, and formalization were not consistent factors explaining adoption decisions. ^

An analysis of authorship attribution: Identifying linguistic variables in oral and written discourse

This dissertation goes into the new field from applied linguistics called forensic linguistics, which studies the language as an evidence for criminal cases. There are many subfields within forensic linguistics, however, this study belongs to authorship attribution analysis, where the authorship of a text is attributed to an author through an exhaustive linguistic analysis. Within this field, this study analyzes the morphosyntactic and discursive-pragmatic variables that remain constant in the intra-variation or personal style of a speaker in the oral and written discourse, and at the same time have a high difference rate in the interspeaker variation, or from one speaker to another. The theoretical base of this study is the term used by professor Maria Teresa Turell called “idiolectal style”. This term establishes that the idiosyncratic choices that the speaker makes from the language build a style for each speaker that is constant in the intravariation of the speaker’s discourse. This study comes as a consequence of the problem appeared in authorship attribution analysis, where the absence of some known texts impedes the analysis for the attribution of the authorship of an uknown text. Thus, through a methodology based on qualitative analysis, where the variables are studied exhaustively, and on quantitative analysis, where the findings from qualitative analysis are statistically studied, some conclusions on the evidence of such variables in both oral and written discourses will be drawn. The results of this analysis will lead to further implications on deeper analyses where larger amount of data can be used.

Análise transversal da estrutura óssea e parâmetros hematológicos em futebolistas profissionais = : Cross-sectional analysis of bone structure and hematological parameters in professional soccer players

Universidade Estadual de Campinas. Faculdade de Educação Física