Variação térmica e a distribuição têmporo-espacial da mortalidade por doenças cardiovasculares na cidade de Limeira/SP

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Decay of interspecific avian flock networks along a disturbance gradient in Amazonia

Our understanding of how anthropogenic habitat change shapes species interactions is in its infancy. This is in large part because analytical approaches such as network theory have only recently been applied to characterize complex community dynamics. Network models are a powerful tool for quantifying how ecological interactions are affected by habitat modification because they provide metrics that quantify community structure and function. Here, we examine how large-scale habitat alteration has affected ecological interactions among mixed-species flocking birds in Amazonian rainforest. These flocks provide a model system for investigating how habitat heterogeneity influences non-trophic interactions and the subsequent social structure of forest-dependent mixed-species bird flocks. We analyse 21 flock interaction networks throughout a mosaic of primary forest, fragments of varying sizes and secondary forest (SF) at the Biological Dynamics of Forest Fragments Project in central Amazonian Brazil. Habitat type had a strong effect on network structure at the levels of both species and flock. Frequency of associations among species, as summarized by weighted degree, declined with increasing levels of forest fragmentation and SF. At the flock level, clustering coefficients and overall attendance positively correlated with mean vegetation height, indicating a strong effect of habitat structure on flock cohesion and stability. Prior research has shown that trophic interactions are often resilient to large-scale changes in habitat structure because species are ecologically redundant. By contrast, our results suggest that behavioural interactions and the structure of non-trophic networks are highly sensitive to environmental change. Thus, a more nuanced, system-by-system approach may be needed when thinking about the resiliency of ecological networks.

Coffee adulteration: more than two decades of research

Abstract Coffee is a ubiquitous food product of considerable economic importance to the countries that produce and export it. The adulteration of roasted coffee is a strategy used to reduce costs. Conventional methods employed to identify adulteration in roasted and ground coffee involve optical and electron microscopy, which require pretreatment of samples and are time-consuming and subjective. Other analytical techniques have been studied that might be more reliable, reproducible, and widely applicable. The present review provides an overview of three analytical approaches (physical, chemical, and biological) to the identification of coffee adulteration. A total of 30 published papers are considered. It is concluded that despite the existence of a number of excellent studies in this area, there still remains a lack of a suitably sensitive and widely applicable methodology able to take into account the various different aspects of adulteration, considering coffee varieties, defective beans, and external agents.

Climatic oscillations shape the phylogeographical structure of Atlantic Forest fire-eye antbirds (Aves: Thamnophilidae)

In the present study, mitochondrial (mt)DNA sequence data were used to examine the genetic structure of fire-eye antbirds (genus Pyriglena) along the Atlantic Forest and the predictions derived from the river hypothesis and from a Last Glacial Maximum Pleistocene refuge paleomodel were compared to explain the patterns of genetic variation observed in these populations. A total of 266 individuals from 45 populations were sampled over a latitudinal transect and a number of phylogeographical and population genetics analytical approaches were employed to address these questions. The pattern of mtDNA variation observed in fire-eye antbirds provides little support for the view that populations were isolated by the modern course of major Atlantic Forest rivers. Instead, the data provide stronger support for the predictions of the refuge model. These results add to the mounting evidence that climatic oscillations appear to have played a substantial role in shaping the phylogeographical structure and possibly the diversification of many taxa in this region. However, the results also illustrate the potential for more complex climatic history and historical changes in the geographical distribution of Atlantic Forest than envisioned by the refuge model. (c) 2012 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, 105, 900824.

La sostenibilità organizzativa dei progetti agricoli di cooperazione internazionale allo sviluppo

The importance of organizational issues to assess the success of international development project has not been fully considered yet. After a brief overview, in 1st chapter, on main actors involved on international cooperation, in the 2nd chapter an analysis of the literature on the project success definition, focused on the success criteria and success factors, was carried out by surveying the contribution of different authors and approaches. Traditionally projects were perceived as successful when they met time, budget and performance goals, assuming a basic similarity among projects (universalistic approach). However, starting from a non-universalistic approach, the importance of organization’s effectiveness, in terms of Relations Sustainability, emerged as a dimension able to define and assess a project success. The identification of the factors influencing the relationship between and inside the organizations becomes consequently a priority. In 3th chapter, starting from a literature survey, the different analytical approaches related to the inter and intra-organization relationships are analysed. They involve two different groups: the first includes studies focused on the type of organizations relationship structure (Supply Chains, Networks, Clusters and Industrial Districts); the second group includes approaches related to the general theories on firms relationship interpretation (Transaction Costs Economics, Resource Based View, Organization Theory). The variables and logical frameworks provided by these different theoretical contributions are compared and classified in order to find out possible connections and/or juxtapositions. Being an exhaustive collection of the literature on the subject is impossible, the main goal is to underline the existence of potentially overlapping and/or integrating approaches examining the contribution provided by different representative authors. The survey showed first of all many variables in common between approaches coming from different disciplines; furthermore the non overlapping variables can be integrated contributing to a broader picture of the variables influencing the organization relations; in particular a theoretical design for the identification of connections between the inter and the intra-organizations relations was made possible. The results obtained in 3th chapter help to defining a general theoretical framework linking the different interpretative variables. Based on extensive research contributions on the factors influencing the relations between organizations, the 4th chapter expands the analysis of the influence of variables like Human Resource Management, Organizational Climate, Psychological Contract and KSA (Knowledge, Skills, Abilities) on the relation sustainability. A detailed analysis of these relations is provided and a research hypothesis are built. According to this new framework in 5th chapter a statistical analysis was performed to qualify and quantify the influence of Organizational Climate on the Relations Sustainability. To this end the Structural Equation Modeling (SEMs) has adopted as method for the definition of the latent variables and the measure of their relations. The results obtained are satisfactory. An effective strategy to motivate the respondents to participate in the survey seems to be at the moment one of the major obstacles to the analysis implementation since the organizational performances are not specifically required by the projects’ evaluation guidelines and they represent an increase in the project related transaction costs. Their explicit introduction in the project presentation guidelines should be explored as an opportunity to increase the chances of success of these projects.

Reactive halogen compounds in the marine boundary layer: method developments and field measurements

Reactive halogen compounds are known to play an important role in a wide variety of atmospheric processes such as atmospheric oxidation capacity and coastal new particle formation. In this work, novel analytical approaches combining diffusion denuder/impinger sampling techniques with gas chromatographic–mass spectrometric (GC–MS) determination are developed to measure activated chlorine compounds (HOCl and Cl2), activated bromine compounds (HOBr, Br2, BrCl, and BrI), activated iodine compounds (HOI and ICl), and molecular iodine (I2). The denuder/GC–MS methods have been used to field measurements in the marine boundary layer (MBL). High mixing ratios (of the order of 100 ppt) of activated halogen compounds and I2 are observed in the coastal MBL in Ireland, which explains the ozone destruction observed. The emission of I2 is found to correlate inversely with tidal height and correlate positively with the levels of O3 in the surrounding air. In addition the release is found to be dominated by algae species compositions and biomass density, which proves the “hot-spot” hypothesis of atmospheric iodine chemistry. The observations of elevated I2 concentrations substantially support the existence of higher concentrations of littoral iodine oxides and thus the connection to the strong ultra-fine particle formation events in the coastal MBL.

Measurement of the inclusive jet cross section in proton-proton collisions at root out s = 7 TeV with the ATLAS detector

The dominant process in hard proton-proton collisions is the production of hadronic jets.rnThese sprays of particles are produced by colored partons, which are struck out of their confinement within the proton.rnPrevious measurements of inclusive jet cross sections have provided valuable information for the determination of parton density functions and allow for stringent tests of perturbative QCD at the highest accessible energies.rnrnThis thesis will present a measurement of inclusive jet cross sections in proton-proton collisions using the ATLAS detector at the LHC at a center-of-mass energy of 7 TeV.rnJets are identified using the anti-kt algorithm and jet radii of R=0.6 and R=0.4.rnThey are calibrated using a dedicated pT and eta dependent jet calibration scheme.rnThe cross sections are measured for 40 GeV < pT <= 1 TeV and |y| < 2.8 in four bins of absolute rapidity, using data recorded in 2010 corresponding to an integrated luminosity of 3 pb^-1.rnThe data is fully corrected for detector effects and compared to theoretical predictions calculated at next-to-leading order including non-perturbative effects.rnThe theoretical predictions are found to agree with data within the experimental and theoretic uncertainties.rnrnThe ratio of cross sections for R=0.4 and R=0.6 is measured, exploiting the significant correlations of the systematic uncertainties, and is compared to recently developed theoretical predictions.rnThe underlying event can be characterized by the amount of transverse momentum per unit rapidity and azimuth, called rhoue.rnUsing analytical approaches to the calculation of non-perturbative corrections to jets, rhoue at the LHC is estimated using the ratio measurement.rnA feasibility study of a combined measurement of rhoue and the average strong coupling in the non-perturbative regime alpha_0 is presented and proposals for future jet measurements at the LHC are made.

Monitoring Butterfly Abundance: Beyond Pollard Walks

Most butterfly monitoring protocols rely on counts along transects (Pollard walks) to generate species abundance indices and track population trends. It is still too often ignored that a population count results from two processes: the biological process (true abundance) and the statistical process (our ability to properly quantify abundance). Because individual detectability tends to vary in space (e.g., among sites) and time (e.g., among years), it remains unclear whether index counts truly reflect population sizes and trends. This study compares capture-mark-recapture (absolute abundance) and count-index (relative abundance) monitoring methods in three species (Maculinea nausithous and Iolana iolas: Lycaenidae; Minois dryas: Satyridae) in contrasted habitat types. We demonstrate that intraspecific variability in individual detectability under standard monitoring conditions is probably the rule rather than the exception, which questions the reliability of count-based indices to estimate and compare specific population abundance. Our results suggest that the accuracy of count-based methods depends heavily on the ecology and behavior of the target species, as well as on the type of habitat in which surveys take place. Monitoring programs designed to assess the abundance and trends in butterfly populations should incorporate a measure of detectability. We discuss the relative advantages and inconveniences of current monitoring methods and analytical approaches with respect to the characteristics of the species under scrutiny and resources availability.

Metabolic predictors of inflammation, adhesion, and coagulability in healthy younger-aged adults

Elevated levels of inflammatory biomarkers are associated with the pathophysiology of cardiovascular diseases and are predictors of cardiovascular events. The objective of this study was to determine the unique contributions of metabolic factors as predictors of inflammation (C-reactive protein (CRP) and interleukin-6 (IL-6)), adhesion (soluble intercellular adhesion molecule-1 (sICAM-1)), and coagulation (D-dimer) in healthy younger-aged adults. Participants were 83 women and 92 men (mean age 30.04 years, s.d. +/- 4.8, range 22-39) of normal weight to moderate obese weight (mean BMI 24.4 kg/m(2), s.d. +/- 3.35, range 17-32). The primary data analytical approaches included Pearson correlation and multiple linear regression. Circulating levels of CRP, IL-6, sICAM-1, and D-dimer were determined in plasma. Higher levels of CRP were independently associated with higher BMI, a greater waist-to-hip ratio, female gender, and higher triglycerides (P < 0.001). Higher IL-6 levels were independently associated with a greater waist-to-hip ratio (P < 0.01). Higher levels of sICAM-1 were independently associated with higher BMI, higher triglycerides, and lower insulin resistance (P < 0.001). Higher D-dimer levels were independently associated with higher BMI and being female (P < 0.001). Having a higher BMI was most consistently associated with elevated biomarkers of inflammation, adhesion, and coagulation in this sample of healthy younger-aged adults, although female gender, insulin resistance, and lipid levels were also related to the biomarkers. The findings provide insight into the adverse cardiovascular risk associated with elevated body weight in younger adults.

Meta-model for calculating the mean energy demand of automated storage and retrieval systems

Energy efficiency has become an important research topic in intralogistics. Especially in this field the focus is placed on automated storage and retrieval systems (AS/RS) utilizing stacker cranes as these systems are widespread and consume a significant portion of the total energy demand of intralogistical systems. Numerical simulation models were developed to calculate the energy demand rather precisely for discrete single and dual command cycles. Unfortunately these simulation models are not suitable to perform fast calculations to determine a mean energy demand value of a complete storage aisle. For this purpose analytical approaches would be more convenient but until now analytical approaches only deliver results for certain configurations. In particular, for commonly used stacker cranes equipped with an intermediate circuit connection within their drive configuration there is no analytical approach available to calculate the mean energy demand. This article should address this research gap and present a calculation approach which enables planners to quickly calculate the energy demand of these systems.

Statistical characterization and development of summary measures of non-normal distributions of nuclear morphometry data from prostate cancer cells for use as prognostic indicators

Nuclear morphometry (NM) uses image analysis to measure features of the cell nucleus which are classified as: bulk properties, shape or form, and DNA distribution. Studies have used these measurements as diagnostic and prognostic indicators of disease with inconclusive results. The distributional properties of these variables have not been systematically investigated although much of the medical data exhibit nonnormal distributions. Measurements are done on several hundred cells per patient so summary measurements reflecting the underlying distribution are needed.^ Distributional characteristics of 34 NM variables from prostate cancer cells were investigated using graphical and analytical techniques. Cells per sample ranged from 52 to 458. A small sample of patients with benign prostatic hyperplasia (BPH), representing non-cancer cells, was used for general comparison with the cancer cells.^ Data transformations such as log, square root and 1/x did not yield normality as measured by the Shapiro-Wilks test for normality. A modulus transformation, used for distributions having abnormal kurtosis values, also did not produce normality.^ Kernel density histograms of the 34 variables exhibited non-normality and 18 variables also exhibited bimodality. A bimodality coefficient was calculated and 3 variables: DNA concentration, shape and elongation, showed the strongest evidence of bimodality and were studied further.^ Two analytical approaches were used to obtain a summary measure for each variable for each patient: cluster analysis to determine significant clusters and a mixture model analysis using a two component model having a Gaussian distribution with equal variances. The mixture component parameters were used to bootstrap the log likelihood ratio to determine the significant number of components, 1 or 2. These summary measures were used as predictors of disease severity in several proportional odds logistic regression models. The disease severity scale had 5 levels and was constructed of 3 components: extracapsulary penetration (ECP), lymph node involvement (LN+) and seminal vesicle involvement (SV+) which represent surrogate measures of prognosis. The summary measures were not strong predictors of disease severity. There was some indication from the mixture model results that there were changes in mean levels and proportions of the components in the lower severity levels. ^

High secondary aerosol contribution to particulate pollution during haze events in China

Rapid industrialization and urbanization in developing countries has led to an increase in air pollution, along a similar trajectory to that previously experienced by the developed nations. In China, particulate pollution is a serious environmental problem that is influencing air quality, regional and global climates, and human health. In response to the extremely severe and persistent haze pollution experienced by about 800 million people during the first quarter of 2013 (refs 4, 5), the Chinese State Council announced its aim to reduce concentrations of PM2.5 (particulate matter with an aerodynamic diameter less than 2.5micrometres) by up to 25 per cent relative to 2012 levels by 2017 (ref. 6). Such efforts however require elucidation of the factors governing the abundance and composition of PM2.5, which remain poorly constrained in China. Here we combine a comprehensive set of novel and state-of-the-art offline analytical approaches and statistical techniques to investigate the chemical nature and sources of particulate matter at urban locations in Beijing, Shanghai, Guangzhou and Xi'an during January 2013. We find that the severe haze pollution event was driven to a large extent by secondary aerosol formation, which contributed 30-77 per cent and 44-71 per cent (average for all four cities) of PM2.5 and of organic aerosol, respectively. On average, the contribution of secondary organic aerosol (SOA) and secondary inorganic aerosol (SIA) are found to be of similar importance (SOA/SIA ratios range from 0.6 to 1.4). Our results suggest that, in addition to mitigating primary particulate emissions, reducing the emissions of secondary aerosol precursors from, for example, fossil fuel combustion and biomass burning is likely to be important for controlling China's PM2.5 levels and for reducing the environmental, economic and health impacts resulting from particulate pollution.

The structural substrate of brain function: analysis of brain structural networks based on diffusion-weighted imaging

The brain is a complex neural network with a hierarchical organization and the mapping of its elements and connections is an important step towards the understanding of its function. Recent developments in diffusion-weighted imaging have provided the opportunity to reconstruct the whole-brain structural network in-vivo at a large scale level and to study the brain structural substrate in a framework that is close to the current understanding of brain function. However, methods to construct the connectome are still under development and they should be carefully evaluated. To this end, the first two studies included in my thesis aimed at improving the analytical tools specific to the methodology of brain structural networks. The first of these papers assessed the repeatability of the most common global and local network metrics used in literature to characterize the connectome, while in the second paper the validity of further metrics based on the concept of communicability was evaluated. Communicability is a broader measure of connectivity which accounts also for parallel and indirect connections. These additional paths may be important for reorganizational mechanisms in the presence of lesions as well as to enhance integration in the network. These studies showed good to excellent repeatability of global network metrics when the same methodological pipeline was applied, but more variability was detected when considering local network metrics or when using different thresholding strategies. In addition, communicability metrics have been found to add some insight into the integration properties of the network by detecting subsets of nodes that were highly interconnected or vulnerable to lesions. The other two studies used methods based on diffusion-weighted imaging to obtain knowledge concerning the relationship between functional and structural connectivity and about the etiology of schizophrenia. The third study integrated functional oscillations measured using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) as well as diffusion-weighted imaging data. The multimodal approach that was applied revealed a positive relationship between individual fluctuations of the EEG alpha-frequency and diffusion properties of specific connections of two resting-state networks. Finally, in the fourth study diffusion-weighted imaging was used to probe for a relationship between the underlying white matter tissue structure and season of birth in schizophrenia patients. The results are in line with the neurodevelopmental hypothesis of early pathological mechanisms as the origin of schizophrenia. The different analytical approaches selected in these studies also provide arguments for discussion of the current limitations in the analysis of brain structural networks. To sum up, the first studies presented in this thesis illustrated the potential of brain structural network analysis to provide useful information on features of brain functional segregation and integration using reliable network metrics. In the other two studies alternative approaches were presented. The common discussion of the four studies enabled us to highlight the benefits and possibilities for the analysis of the connectome as well as some current limitations.

The functional significance of EEG microstates-Associations with modalities of thinking

The momentary, global functional state of the brain is reflected by its electric field configuration. Cluster analytical approaches consistently extracted four head-surface brain electric field configurations that optimally explain the variance of their changes across time in spontaneous EEG recordings. These four configurations are referred to as EEG microstate classes A, B, C, and D and have been associated with verbal/phonological, visual, attention reorientation, and subjective interoceptive-autonomic processing, respectively. The present study tested these associations via an intra-individual and inter-individual analysis approach. The intra-individual approach tested the effect of task-induced increased modality-specific processing on EEG microstate parameters. The inter-individual approach tested the effect of personal modality-specific parameters on EEG microstate parameters. We obtained multichannel EEG from 61 healthy, right-handed, male students during four eyes-closed conditions: object-visualization, spatial-visualization, verbalization (6 runs each), and resting (7 runs). After each run, we assessed participants' degrees of object-visual, spatial-visual, and verbal thinking using subjective reports. Before and after the recording, we assessed modality-specific cognitive abilities and styles using nine cognitive tests and two questionnaires. The EEG of all participants, conditions, and runs was clustered into four classes of EEG microstates (A, B, C, and D). RMANOVAs, ANOVAs and post-hoc paired t-tests compared microstate parameters between conditions. TANOVAs compared microstate class topographies between conditions. Differences were localized using eLORETA. Pearson correlations assessed interrelationships between personal modality-specific parameters and EEG microstate parameters during no-task resting. As hypothesized, verbal as opposed to visual conditions consistently affected the duration, occurrence, and coverage of microstate classes A and B. Contrary to associations suggested by previous reports, parameters were increased for class A during visualization, and class B during verbalization. In line with previous reports, microstate D parameters were increased during no-task resting compared to the three internal, goal-directed tasks. Topographic differences between conditions concerned particular sub-regions of components of the metabolic default mode network. Modality-specific personal parameters did not consistently correlate with microstate parameters except verbal cognitive style which correlated negatively with microstate class A duration and positively with class C occurrence. This is the first study that aimed to induce EEG microstate class parameter changes based on their hypothesized functional significance. Beyond, the associations of microstate classes A and B with visual and verbal processing, respectively and microstate class D with interoceptive-autonomic processing, our results suggest that a finely-tuned interplay between all four EEG microstate classes is necessary for the continuous formation of visual and verbal thoughts, as well as interoceptive-autonomic processing. Our results point to the possibility that the EEG microstate classes may represent the head-surface measured activity of intra-cortical sources primarily exhibiting inhibitory functions. However, additional studies are needed to verify and elaborate on this hypothesis.

What Is Known about Testing for Discrimination: Lessons Learned by Comparing across Different Markets

The paper provides a fairly comprehensive examination of recent empirical work on discrimination within economics. The three major analytical approaches considered are traditional regression analysis of outcomes, paired testing or audits, and finally analysis of performance where higher group performance suggests that a group has been treated disfavorably. The review covers research in the labor, credit, and consumption markets, as well as recent studies of discrimination within the legal system. The review suggests that the validity of interpreting observed racial differences as discrimination depends heavily on whether the analysis is based on a sample that is representative of a population of individuals or households or based on a sample of market transactions, as well as the analyst?s ability to control for heterogeneity within that sample. Heterogeneous firm behavior and differentiated products, such as those found in labor and housing markets, also can confound empirical analyses of discrimination by confusing the allocation of individuals across firms or products with disparate treatment or by ignoring disparate impacts that might arise based on that allocation.