Approximate entropy normalized measures for analyzing social neurobiological systems

When considering time series data of variables describing agent interactions in social neurobiological systems, measures of regularity can provide a global understanding of such system behaviors. Approximate entropy (ApEn) was introduced as a nonlinear measure to assess the complexity of a system behavior by quantifying the regularity of the generated time series. However, ApEn is not reliable when assessing and comparing the regularity of data series with short or inconsistent lengths, which often occur in studies of social neurobiological systems, particularly in dyadic human movement systems. Here, the authors present two normalized, nonmodified measures of regularity derived from the original ApEn, which are less dependent on time series length. The validity of the suggested measures was tested in well-established series (random and sine) prior to their empirical application, describing the dyadic behavior of athletes in team games. The authors consider one of the ApEn normalized measures to generate the 95th percentile envelopes that can be used to test whether a particular social neurobiological system is highly complex (i.e., generates highly unpredictable time series). Results demonstrated that suggested measures may be considered as valid instruments for measuring and comparing complexity in systems that produce time series with inconsistent lengths.

A calculus for modeling and analyzing conversations in service-oriented computing

Dissertação apresentada para a obtenção do Grau de Doutor em Informática pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Analyzing Multiple Outcomes: Is it Really Worth the use of Multivariate Linear Regression?

In health related research it is common to have multiple outcomes of interest in a single study. These outcomes are often analysed separately, ignoring the correlation between them. One would expect that a multivariate approach would be a more efficient alternative to individual analyses of each outcome. Surprisingly, this is not always the case. In this article we discuss different settings of linear models and compare the multivariate and univariate approaches. We show that for linear regression models, the estimates of the regression parameters associated with covariates that are shared across the outcomes are the same for the multivariate and univariate models while for outcome-specific covariates the multivariate model performs better in terms of efficiency.

Web-application for gathering, analyzing, and processing health information about allergy data

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Report on ticks collected in the Southeast and Mid-West regions of Brazil: analyzing the potential transmission of tick-borne pathogens to man

Specimens of ticks were collected in 1993, 1996, 1997, and 1998, mostly from wild and domestic animals in the Southeast and Mid-West regions of Brazil. Nine species of Amblyommidae were identified: Anocentor nitens, Amblyomma cajennense, Amblyomma ovale, Amblyomma fulvum, Amblyomma striatum, Amblyomma rotundatum, Boophilus microplus, Boophilus annulatus, and Rhipicephalus sanguineus. The potential of these tick species as transmitters of pathogens to man was analyzed. A Flaviviridade Flavivirus was isolated from Amblyomma cajennense specimens collected from a sick capybara (Hydrochaeris hydrochaeris). Amblyomma cajennense is the main transmitter of Rickettsia rickettsii (=R. rickettsi), the causative agent of spotted fever in Brazil. Wild mammals, mainly capybaras and deer, infested by ticks and living in close contact with cattle, horses and dogs, offer the risk of transmission of wild zoonosis to these domestic animals and to man.

Analyzing the impact of HRM Systems on the organizational climate, culture and outcomes: The mediating role of HMR Strength, organizational climate and culture

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

SDAR: a package for plotting and analyzing stratigraphy data in R

Stratigraphic Columns (SC) are the most useful and common ways to represent the eld descriptions (e.g., grain size, thickness of rock packages, and fossil and lithological components) of rock sequences and well logs. In these representations the width of SC vary according to the grain size (i.e., the wider the strata, the coarser the rocks (Miall 1990; Tucker 2011)), and the thickness of each layer is represented at the vertical axis of the diagram. Typically these representations are drawn 'manually' using vector graphic editors (e.g., Adobe Illustrator®, CorelDRAW®, Inskape). Nowadays there are various software which automatically plot SCs, but there are not versatile open-source tools and it is very di cult to both store and analyse stratigraphic information. This document presents Stratigraphic Data Analysis in R (SDAR), an analytical package1 designed for both plotting and facilitate the analysis of Stratigraphic Data in R (R Core Team 2014). SDAR, uses simple stratigraphic data and takes advantage of the exible plotting tools available in R to produce detailed SCs. The main bene ts of SDAR are: (i) used to generate accurate and complete SC plot including multiple features (e.g., sedimentary structures, samples, fossil content, color, structural data, contacts between beds), (ii) developed in a free software environment for statistical computing and graphics, (iii) run on a wide variety of platforms (i.e., UNIX, Windows, and MacOS), (iv) both plotting and analysing functions can be executed directly on R's command-line interface (CLI), consequently this feature enables users to integrate SDAR's functions with several others add-on packages available for R from The Comprehensive R Archive Network (CRAN).

Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data

Crisis-affected communities and global organizations for international aid are becoming increasingly digital as consequence geotechnology popularity. Humanitarian sector changed in profound ways by adopting new technical approach to obtain information from area with difficult geographical or political access. Since 2011, turkey is hosting a growing number of Syrian refugees along southeastern region. Turkish policy of hosting them in camps and the difficulty created by governors to international aid group expeditions to get information, made such international organizations to investigate and adopt other approach in order to obtain information needed. They intensified its remote sensing approach. However, the majority of studies used very high-resolution satellite imagery (VHRSI). The study area is extensive and the temporal resolution of VHRSI is low, besides it is infeasible only using these sensors as unique approach for the whole area. The focus of this research, aims to investigate the potentialities of mid-resolution imagery (here only Landsat) to obtain information from region in crisis (here, southeastern Turkey) through a new web-based platform called Google Earth Engine (GEE). Hereby it is also intended to verify GEE currently reliability once the Application Programming Interface (API) is still in beta version. The finds here shows that the basic functions are trustworthy. Results pointed out that Landsat can recognize change in the spectral resolution clearly only for the first settlement. The ongoing modifications vary for each case. Overall, Landsat demonstrated high limitations, but need more investigations and may be used, with restriction, as a support of VHRSI.

Analyzing university spin-offs and supporting decision making in new venture creation

Magdeburg, Univ., Fak. für Wirtschaftswiss., Diss., 2008

Diagnosis of Rejection by Analyzing Ventricular Late Potentials in Heart Transplant Patients

Background: Heart transplant rejection originates slow and fragmented conduction. Signal-averaged ECG (SAECG) is a stratification method in the risk of rejection. Objective: To develop a risk score for rejection, using SAECG variables. Methods: We studied 28 transplant patients. First, we divided the sample into two groups based on the occurrence of acute rejection (5 with rejection and 23 without). In a second phase, we divided the sample considering the existence or not of rejection in at least one biopsy performed on the follow-up period (rejection pm1: 18 with rejection and 10 without). Results: On conventional ECG, the presence of fibrosis was the only criterion associated with acute rejection (OR = 19; 95% CI = 1.65-218.47; p = 0.02). Considering the rejection pm1, an association was found with the SAECG variables, mainly with RMS40 (OR = 0.97; 95% CI = 0.87-0.99; p = 0.03) and LAS40 (OR = 1.06; 95% IC = 1.01-1.11; p = 0.03). We formulated a risk score including those variables, and evaluated its discriminative performance in our sample. The presence of fibrosis with increasing of LAS40 and decreasing of RMS40 showed a good ability to distinguish between patients with and without rejection (AUC = 0.82; p < 0.01), assuming a cutoff point of sensitivity = 83.3% and specificity = 60%. Conclusion: The SAECG distinguished between patients with and without rejection. The usefulness of the proposed risk score must be demonstrated in larger follow-up studies.

Methods for analyzing the influence of molecular dynamics on neuronal activity

Magdeburg, Univ., Fak. für Informatik, Diss., 2015

Investigating polyhedra by oracles and analyzing simple extensions of polytopes

Otto-von-Guericke-Universität Magdeburg, Fakultät für Mathematik, Dissertation, 2016

Demographic Transitions: analyzing the effects of mortality on fertility

The effect of mortality reductions on fertility is one of the main mechanisms stressed by the recent growth literature in order to explain demographic transitions. We analyze the empirical relevance of this mechanism based on the experience of all countries since 1960. We distinguish between the effects on gross and net fertility, take into account the dynamic nature of the relationship and control for alternative explanatory factors and for endogeneity. Our results show that mortality plays a large role in fertility reductions, that the change in fertility behavior comes with a lag of about 10 years and that both net and gross fertility are affected. We find comparatively little support for explanations of the demographic transition based on economic development or technological change.

A Framework for Analyzing Language and Welfare

The paper proposes a general model that will encompass trade and social benefits of a common language, a preference for a variety of languages, the fundamental role of translators, an emotional attachment to maternal language, and the threat that globalization poses to the vast majority of languages. With respect to people’s emotional attachment, the model considers minorities to suffer losses from the subordinate status of their language. In addition, the model treats the threat to minority language as coming from the failure of the parents in the minority to transmit their maternal language (durably) to their children. Some familiar results occur. In particular, we encounter the usual social inefficiencies of decentralized solutions to language learning when the sole benefits of the learning are communicative benefits (though translation intervenes). However, these social inefficiencies assume a totally different air when the con-sumer gains of variety are brought in. One fundamental aim of the paper is to bring together contributions to the economics of language from labor economics, network externalities and international trade that are typically treated separately.

A Framework for Analyzing Language and Welfare

The paper proposes a general model that will encompass trade and social benefits of a common language, a preference for a variety of languages, the fundamental role of translators, an emo-tional attachment to maternal language, and the threat that globalization poses to the vast ma-jority of languages. With respect to people’s emotional attachment, the model considers minor-ities to suffer losses from the subordinate status of their language. In addition, the model treats the threat to minority language as coming from the failure of the parents in the minority to transmit their maternal language (durably) to their children. Some familiar results occur. In particular, we encounter the usual social inefficiencies of decentralized solutions to language learning when the sole benefits of the learning are communicative benefits (though translation intervenes). However, these social inefficiencies assume a totally different air when the con-sumer gains of variety are brought in. One fundamental aim of the paper is to bring together contributions to the economics of language from labor economics, network externalities and international trade that are typically treated separately.