Self-perception and dissatisfaction with weight does not depend on the frequency of physical activity

OBJECTIVE: To evaluate the level of satisfaction with body weight and the self-perception of the weight/height ratio and to verify the influence of the frequency of present and past physical activity on these variables. METHODS: Using questionnaires or interviews, we obtained height data, reported and desired weight, self-perception of the weight/height ratio, and the frequency of current physical activity in 844 adults (489 women). Of these, evaluated the frequency of physical activity during high school of 193 individuals,and we measured their height and weight. RESULTS: Less than 2/3 of the individuals had body mass index between 20 and 24.9 kg/m2. A tendency existed to overestimate height by less than 1 cm and to underestimate weight by less than 1kg. Desired weight was less than that reported (p<0.001), and only 20% were satisfied with their current weight. Only 42% of men and 25% of women exercised regularly. No association was found between the frequency of physical activity and the variables height, weight, and body mass index, and the level of satisfaction with current weight. CONCLUSION: Height and weight reported seem to be valid for epidemological studies, and great dissatisfaction with body weight and a distorted self-perception of height/weight ratio exists, especially in women, regardless of the frequency of physical activity.

Estudio de los modos de vida e historia biológica de las poblaciones humanas de la región central de argentina desde el registro bioarqueológico. Lifestyles and biological history of human populations of the central region of argentina from bioarchaeological record.

Se pretende aportar al estudio de la estructura, historia biológica y estilos de vida de las poblaciones que habitaron la región central de Argentina durante el Holoceno, desde una perspectiva que combina los aportes teóricos y metodológicos de la Genética del paisaje y la Bioarqueología. Interesa a) identificar barreras de diferenciación morfológica entre poblaciones, b) poner a prueba modelos poblacionales para explicar la variación observada e identificar las variables que contribuyan a dicha diferenciación, c) evaluar la congruencia de los resultados obtenidos, d) reconstruir los patrones de movilidad residencial de las poblaciones, e) estudiar sus patrones dietarios considerando diferencias temporales y espaciales, f) identificar indicadores de diversos tipos de estrés (nutricional, funcional), así como traumas, g) estudiar las historias tafonómicas del registro bioarqueológico regional, y h) proponer un modelo para explicar el poblamiento y la evolución local de las poblaciones que habitaron esta región, a partir de la información arqueológica y bioantropológica. Para el análisis de los patrones espaciales de variación biológica se trabajará a partir del registro de rasgos epigenéticos craneales, medidas lineales y datos obtenidos a partir de morfometría geométrica sobre fotografías en 2D sobre muestras arqueológicas procedentes de esta región y de otras regiones geográficas de la Argentina. Para el análisis de la estructura de la población se trabajará a partir del cálculo de la matriz R para datos morfológicos y sus estimaciones derivadas (distancia D², Fst, coordenadas principales) y la aplicación del modelo de Harpending y Ward. Desde la genética del paisaje, se realizarán análisis de autocorrelación espacial, barreras genéticas y análisis geoestadísticos (kriging). Para el estudio de los modos de vida a partir del registro bioarqueológico se relevarán patologías dento-alveolares y alteraciones vinculadas con la salud bucal tales como desgaste dental –a nivel micro y macroscópico- caries, abscesos, pérdidas dentales antemortem, cálculos, hipoplasias, marcadores esqueletales de salud y lesiones traumáticas. Se analizarán isótopos estables (δ13C, δ15N, 86Sr y 87Sr) en restos óseos humanos de diversos sitios arqueológicos con el objetivo de reconstruir patrones dietarios y analizar la movilidad residencial y migración de las poblaciones. Paralelamente, se establecerán procedimientos de control tafonómico de los restos óseos, y se harán análisis específicos para estudiar las historias tafonómicas y evaluar el grado de integridad de los contextos de depositación y de las colecciones en general. Estimamos que el análisis de los patrones espaciales y temporales de variabilidad morfológica craneofacial, así como el estudio de las dietas a partir de información isotópica y bioarqueológica, de las migraciones y la movilidad residencial de las poblaciones a partir de isótopos de estroncio, la reconstrucción de comportamientos y actividades cotidianas a partir de marcadores de estrés músculo-esqueletal, en un marco cronológico y espacial constituye un aporte novedoso y eficaz que permitirá incrementar de manera substancial la información sobre la evolución de las poblaciones originarias del centro del territorio argentino. The aim of this project is to study the structure, biological history and lifestyles of the people that inhabitated the central region of Argentina during the Holocene, from a perspective that combines theoretical and methodological contributions of Landscape Genetics and Bioarchaeology. To analyze the spatial patterns of biological variation we consider epigenetic cranial traits, linear measurements and data obtained from geometric morphometric on 2D photographs. Morphological variation will be focused on landscape genetics (autocorrelation, genetic barriers and geostatistical analysis –kriging-) and population structure (matrix R, D², Fst, principal coordinates, Harpendig and Ward model). For the study of lifestyles from bioarchaeological record we consider alveolar pathologies and disorders related to oral health such as tooth wear, micro and macroscopic level, caries, abscesses, antemortem tooth loss, hypoplasia, markers skeletal health and traumatic injuries, as well as taphonomic processes. Stable isotopes will be analyzed (δ13C, d15N, 86Sr and 87Sr) in human skeletal remains from various archaeological sites in order to reconstruct and analyze dietary patterns of residential mobility and migration of populations. It will be established procedures of taphonomic control on skeletal remains, analysis to study taphonomic histories and assess the degree of completeness of depositional context and collection, in general terms. We consider that analysis of spatial and temporal patterns of variability in craniofacial morphology and the study of health and diets from isotopic and bioarchaeological data, migration and residential mobility patterns from strontium isotopes, as well as activity patterns from stress markers is a novel and effective contribution that will substantially increase the information about the local evolution of populations that inhabitated the center of Argentina.

Ireland’s understudied flatfish: reproduction, age and growth of the dab Limanda limanda (L.) in Irish coastal waters

In Ireland, although flatfish form a valuable fishery, little is known about the smallest, the dab Limanda limanda. In this study, a variety of parameters of reproductive development, including ovarian phase description, gonadosomatic index (GSI), hepatosomatic index (HSI), relative condition (Kn) and oocyte size were analysed to provide information on the dab’s reproductive cycle and spawning periods. Sampling were collected monthly over an 18-month period using bottom trawls of the Irish coastline. A six phase macroscopic guide was developed for both sexes of dab, and verified using histology. In comparisons of macroscopic and microscopic phases, there was high agreement in the proposed female guide (86%), with males demonstratively lower (62%). No significant bias was observed between the the two reproductive methods. When the male macroscopic guide was examined, misclassification was high in phase 5 and phase 5 (41%), with 96% of misclassification occurring in adjacent phases. The sampled population was primarily composed of females, with ratios of females to males 1:0.6, although the predominance of females was less noticeable during the reproductive season. Oocyte growth in dab follows asynchronous development, and spawn over a protracted period indicating a batch spawning strategy. Spawning occurred mainly in early spring, with total regeneration of gonads by May. The length at which 50% of the population was reproductively mature was identified as 14cm and 17cm, for male and female dab, respectively. Precision and bias in age determinations using whole otoliths to age dab was investigated using six age readers from various institutions. Low levels of precision were obtained (CV: 10-23%) inferring the need for an alternative methodology. Precision and bias was influence by the level of experience of the reader, with ageing error attributed to interpretative differences and difficulty in edge determination. Sectioned otolith age determinations were subsequently compared to whole otolith age determinations using two age readers experienced in dab ageing. Although increased precision was observed in whole otoliths from previous estimates (CV=0%, 0% APE), sectioned otoliths were used for growth models. This was based on multinominal logistic regression on age length keys developed using both ageing methods. Biological data (length and age) for both sexes was applied to four growth models, where the Akaike criterion and Multi model Inference indicated the logistic model as having the best fit to the collected data. In general, female dab attained a longer length then males, with growth rates significantly different between the two sexes. Length weight relationships between the two sexes were also significantly different.

A Novel Memory-centric Architecture and Organization of Processors and Computers

The modern computer systems that are in use nowadays are mostly processor-dominant, which means that their memory is treated as a slave element that has one major task – to serve execution units data requirements. This organization is based on the classical Von Neumann's computer model, proposed seven decades ago in the 1950ties. This model suffers from a substantial processor-memory bottleneck, because of the huge disparity between the processor and memory working speeds. In order to solve this problem, in this paper we propose a novel architecture and organization of processors and computers that attempts to provide stronger match between the processing and memory elements in the system. The proposed model utilizes a memory-centric architecture, wherein the execution hardware is added to the memory code blocks, allowing them to perform instructions scheduling and execution, management of data requests and responses, and direct communication with the data memory blocks without using registers. This organization allows concurrent execution of all threads, processes or program segments that fit in the memory at a given time. Therefore, in this paper we describe several possibilities for organizing the proposed memory-centric system with multiple data and logicmemory merged blocks, by utilizing a high-speed interconnection switching network.

Fisheries of the United States / U.S. Department of the Interior, Fish and Wildlife Service, Bureau of Commercial Fisheries.

1996

Fisheries of the United States / U.S. Department of the Interior, Fish and Wildlife Service, Bureau of Commercial Fisheries.

2004

Fisheries of the United States / U.S. Department of the Interior, Fish and Wildlife Service, Bureau of Commercial Fisheries.

1992

Convergence across countries and regions: theory and empirics

This paper surveys the recent literature on convergence across countries and regions. I discuss the main convergence and divergence mechanisms identified in the literature and develop a simple model that illustrates their implications for income dynamics. I then review the existing empirical evidence and discuss its theoretical implications. Early optimism concerning the ability of a human capital-augmented neoclassical model to explain productivity differences across economies has been questioned on the basis of more recent contributions that make use of panel data techniques and obtain theoretically implausible results. Some recent research in this area tries to reconcile these findings with sensible theoretical models by exploring the role of alternative convergence mechanisms and the possible shortcomings of panel data techniques for convergence analysis.

Toward interoperable bioscience data.

To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.

Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.

Corruption and the Military in Politics: Theory and Evidence from around the World

Recent theoretical developments and case study evidence suggests a relationship between the military in politics and corruption. This study contributes to this literature by analyzing theoretically and empirically the role of the military in politics and corruption for the first time. By drawing on a cross sectional and panel data set covering a large number of countries, over the period 1984-2007, and using a variety of econometric methods substantial empirical support is found for a positive relationship between the military in politics and corruption. In sum, our results reveal that a one standard deviation increase in the military in politics leads to a 0.22 unit increase in corruption index. This relationship is shown to be robust to a variety of specification changes, different econometric techniques, different sample sizes, alternative corruption indices and the exclusion of outliers. This study suggests that the explanatory power of the military in politics is at least as important as the conventionally accepted causes of corruption, such as economic development.

Microstructure Order Flow: Statistical and Economic Evaluation of Nonlinear Forecasts

In this paper we propose a novel empirical extension of the standard market microstructure order flow model. The main idea is that heterogeneity of beliefs in the foreign exchange market can cause model instability and such instability has not been fully accounted for in the existing empirical literature. We investigate this issue using two di¤erent data sets and focusing on out- of-sample forecasts. Forecasting power is measured using standard statistical tests and, additionally, using an alternative approach based on measuring the economic value of forecasts after building a portfolio of assets. We nd there is a substantial economic value on conditioning on the proposed models.

Corruption and Financial Intermediation in a Panel of Regions: Cross-Border Effects of Corruption

The importance of financial market reforms in combating corruption has been highlighted in the theoretical literature but has not been systemically tested empirically. In this study we provide a first pass at testing this relationship using both linear and nonmonotonic forms of the relationship between corruption and financial intermediation. Our study finds a negative and statistically significant impact of financial intermediation on corruption. Specifically, the results imply that a one standard deviation increase in financial intermediation is associated with a decrease in corruption of 0.20 points, or 16 percent of the standard deviation in the corruption index and this relationship is shown to be robust to a variety of specification changes, including: (i) different sets of control variables; (ii) different econometrics techniques; (iii) different sample sizes; (iv) alternative corruption indices; (v) removal of outliers; (vi) different sets of panels; and (vii) allowing for cross country interdependence, contagion effects, of corruption.

Sparse regularization for fiber ODF reconstruction: from the suboptimality of ℓ2 and ℓ1 priors to ℓ0.

Diffusion MRI is a well established imaging modality providing a powerful way to probe the structure of the white matter non-invasively. Despite its potential, the intrinsic long scan times of these sequences have hampered their use in clinical practice. For this reason, a large variety of methods have been recently proposed to shorten the acquisition times. Among them, spherical deconvolution approaches have gained a lot of interest for their ability to reliably recover the intra-voxel fiber configuration with a relatively small number of data samples. To overcome the intrinsic instabilities of deconvolution, these methods use regularization schemes generally based on the assumption that the fiber orientation distribution (FOD) to be recovered in each voxel is sparse. The well known Constrained Spherical Deconvolution (CSD) approach resorts to Tikhonov regularization, based on an ℓ(2)-norm prior, which promotes a weak version of sparsity. Also, in the last few years compressed sensing has been advocated to further accelerate the acquisitions and ℓ(1)-norm minimization is generally employed as a means to promote sparsity in the recovered FODs. In this paper, we provide evidence that the use of an ℓ(1)-norm prior to regularize this class of problems is somewhat inconsistent with the fact that the fiber compartments all sum up to unity. To overcome this ℓ(1) inconsistency while simultaneously exploiting sparsity more optimally than through an ℓ(2) prior, we reformulate the reconstruction problem as a constrained formulation between a data term and a sparsity prior consisting in an explicit bound on the ℓ(0)norm of the FOD, i.e. on the number of fibers. The method has been tested both on synthetic and real data. Experimental results show that the proposed ℓ(0) formulation significantly reduces modeling errors compared to the state-of-the-art ℓ(2) and ℓ(1) regularization approaches.

The application of chemometrics on Infrared and Raman spectra as a tool for the forensic analysis of paints

The aim of this work is to evaluate the capabilities and limitations of chemometric methods and other mathematical treatments applied on spectroscopic data and more specifically on paint samples. The uniqueness of the spectroscopic data comes from the fact that they are multivariate - a few thousands variables - and highly correlated. Statistical methods are used to study and discriminate samples. A collection of 34 red paint samples was measured by Infrared and Raman spectroscopy. Data pretreatment and variable selection demonstrated that the use of Standard Normal Variate (SNV), together with removal of the noisy variables by a selection of the wavelengths from 650 to 1830 cm−1 and 2730-3600 cm−1, provided the optimal results for infrared analysis. Principal component analysis (PCA) and hierarchical clusters analysis (HCA) were then used as exploratory techniques to provide evidence of structure in the data, cluster, or detect outliers. With the FTIR spectra, the Principal Components (PCs) correspond to binder types and the presence/absence of calcium carbonate. 83% of the total variance is explained by the four first PCs. As for the Raman spectra, we observe six different clusters corresponding to the different pigment compositions when plotting the first two PCs, which account for 37% and 20% respectively of the total variance. In conclusion, the use of chemometrics for the forensic analysis of paints provides a valuable tool for objective decision-making, a reduction of the possible classification errors, and a better efficiency, having robust results with time saving data treatments.