Classifying minimally disabled multiple sclerosis patients from resting state functional connectivity.

Multiple sclerosis (MS), a variable and diffuse disease affecting white and gray matter, is known to cause functional connectivity anomalies in patients. However, related studies published to-date are post hoc; our hypothesis was that such alterations could discriminate between patients and healthy controls in a predictive setting, laying the groundwork for imaging-based prognosis. Using functional magnetic resonance imaging resting state data of 22 minimally disabled MS patients and 14 controls, we developed a predictive model of connectivity alterations in MS: a whole-brain connectivity matrix was built for each subject from the slow oscillations (<0.11Hz) of region-averaged time series, and a pattern recognition technique was used to learn a discriminant function indicating which particular functional connections are most affected by disease. Classification performance using strict cross-validation yielded a sensitivity of 82% (above chance at p<0.005) and specificity of 86% (p<0.01) to distinguish between MS patients and controls. The most discriminative connectivity changes were found in subcortical and temporal regions, and contralateral connections were more discriminative than ipsilateral connections. The pattern of decreased discriminative connections can be summarized post hoc in an index that correlates positively (ρ=0.61) with white matter lesion load, possibly indicating functional reorganisation to cope with increasing lesion load. These results are consistent with a subtle but widespread impact of lesions in white matter and in gray matter structures serving as high-level integrative hubs. These findings suggest that predictive models of resting state fMRI can reveal specific anomalies due to MS with high sensitivity and specificity, potentially leading to new non-invasive markers.

Climatic potential for wine grape production in the tropical north region of Minas Gerais State, Brazil

The tropical north region of Minas Gerais State is one of the least developed of Brazil and viticulture could be an alternative to develop its agriculture zone. The objective of this work was to evaluate the climatic potential of that region for wine grape production. The evaluations were carried out applying the Multicriteria Climatic Classification System (Geoviticulture MCC System), that utilizes three reference climatic indexes (Dryness Index - DI, Heliothermal Index - HI and Cool Night Index - CI). Three locations - Pirapora (17º 21'S, 44º56'W, 489m), Montes Claros (16º43'S, 43º52'W, 647m) and Diamantina (18º15'S, 43º36'W, 1297m) - and two potential production cycles along the year - October to March (spring-summer period) and April to September (autumn-winter period) - were evaluated. The results showed that in the spring-summer period (SS period) Pirapora and Montes Claros presented a 'humid, very warm and with warm nights' of viticultural climate, according to MCC System. For the autumn-winter period (AW period), those two regions presented a 'moderately dry, warm and with temperate nights' according to MCC System. Otherwise, the Diamantina SS period presented a 'humid, temperate warm and with temperate nights' viticultural climate. In the AW period, the Diamantina climatic condition values represent a 'subhumid, temperate and with cool nights' viticultural climate. Based on those results it can be concluded that the North Region of Minas Gerais State has a great climatic potential to became a grape-growing region for wine-making, specially in the autumn-winter period.

Ten years after the Prestige Oil Spill: seabird trophic ecology as indicator of long-term effects on the coastal marine ecosystem

Major oil spills can have long-term impacts since oil pollution does not only result in acute mortality of marine organisms, but also affects productivity levels, predator-prey dynamics, and damages habitats that support marine communities. However, despite the conservation implications of oil accidents, the monitoring and assessment of its lasting impacts still remains a difficult and daunting task. Here, we used European shags to evaluate the overall, lasting effects of the Prestige oil spill (2002) on the affected marine ecosystem. Using δ15N and Hg analysis, we trace temporal changes in feeding ecology potentially related to alterations of the food web due to the spill. Using climatic and oceanic data, we also investigate the influence of North Atlantic Oscillation (NAO) index, the sea surface temperature (SST) and the chlorophyll a (Chl a) on the observed changes. Analysis of δ15N and Hg concentrations revealed that after the Prestige oil spill, shag chicks abruptly switched their trophic level from a diet based on a high percentage of demersal-benthic fish to a higher proportion of pelagic/semi-pelagic species. There was no evidence that Chl a, SST and NAO reflected any particular changes or severity in environmental conditions for any year or season that may explain the sudden change observed in trophic level. Thus, this study highlighted an impact on the marine food web for at least three years. Our results provide the best evidence to date of the long-term consequences of the Prestige oil spill. They also show how, regardless of wider oceanographic variability, lasting impacts on predator-prey dynamics can be assessed using biochemical markers. This is particularly useful if larger scale and longer term monitoring of all trophic levels is unfeasible due to limited funding or high ecosystem complexity.

Metabolic connectivity as index of verbal working memory.

Positron emission tomography (PET) data are commonly analyzed in terms of regional intensity, while covariant information is not taken into account. Here, we searched for network correlates of healthy cognitive function in resting state PET data. PET with [(18)F]-fluorodeoxyglucose and a test of verbal working memory (WM) were administered to 35 young healthy adults. Metabolic connectivity was modeled at a group level using sparse inverse covariance estimation. Among 13 WM-relevant Brodmann areas (BAs), 6 appeared to be robustly connected. Connectivity within this network was significantly stronger in subjects with above-median WM performance. In respect to regional intensity, i.e., metabolism, no difference between groups was found. The results encourage examination of covariant patterns in FDG-PET data from non-neurodegenerative populations.

Ideal Body Size as a Mediator for the Gender-Specific Association Between Socioeconomic Status and Body Mass Index: Evidence From an Upper-Middle-Income Country in the African Region.

While obesity continues to rise globally, the associations between body size, gender, and socioeconomic status (SES) seem to vary in different populations, and little is known on the contribution of perceived ideal body size in the social disparity of obesity in African countries. We examined the gender and socioeconomic patterns of body mass index (BMI) and perceived ideal body size in the Seychelles, a middle-income small island state in the African region. We also assessed the potential role of perceived ideal body size as a mediator for the gender-specific association between SES and BMI. A population-based survey of 1,240 adults aged 25 to 64 years conducted in December 2013. Participants' BMI was calculated based on measured weight and height; ideal body size was assessed using a nine-silhouette instrument. Three SES indicators were considered: income, education, and occupation. BMI and perceived ideal body size were both higher among men of higher versus lower SES (p< .001) but lower among women of higher versus lower SES (p< .001), irrespective of the SES indicator used. Multivariate analysis showed a strong and direct association between perceived ideal body size and BMI in both men and women (p< .001) and was consistent with a potential mediating role of perceived ideal body size in the gender-specific associations between SES and BMI. Our study emphasizes the importance of gender and socioeconomic differences in BMI and ideal body size and suggests that public health interventions that promote perception of healthy weight could help mitigate SES-related disparities in BMI.

Self-rule Index for Local Authorities (Release 1.0)

Local autonomy is a highly valued feature of good governance. The continuous attempts of many European countries to strengthen the autonomy of local government show the importance given to decentralisation and far-reaching competences at the lowest units of a state. Measuring and comparing local autonomy, however, has proven to be a difficult task. Not only are there diverging ideas about the core elements of local autonomy, there are also considerable difficulties to apply specific concepts to different countries. This project suggests a comprehensive methodology to measure local autonomy. It analyses 39 European countries and reports changes between 1990 and 2014. A network of experts on local government assessed the autonomy of local government of their respective countries on the basis of a common code book. The eleven variables measured are located on seven imensions and can be combined to a "Local Autonomy Index" (LAI). The data show an increase of local autonomy between 1990 and 2005, especially in the new Central and Eastern European countries. Countries with a particularly high degree of local autonomy are Switzerland, the Nordic countries, Germany and Poland.

A state-space approach for measuring regional manufacturing production indices

In this paper we propose a latent variable model, in the spirit of Israilevich and Kuttner (1993), to measure regional manufacturing production. To test the validity of the proposed methodology, we have applied it for those Spanish regions that have a direct quantitative index. The results demonstrate the accuracy of the methodology proposed and show that it can overcome some of the difficulties of the indirect method applied by the INE, the Spanish National Institute of Statistics.

Is it possible to utilize VIX for a profitable trading strategy of S&P 500 Index?

The goal of this research was to make an overall sight to VIX® and how it can be used as a stock market indicator. Volatility index often referred as the fear index, measures how much it costs for investor to protect his/her S&P 500 position from fluctuations with options. Over the relatively short history of VIX it has been a successful timing coordinator and it has given incremental information about the market state adding its own psychological view of the amount of fear and greed. Correctly utilized VIX information gives a considerable advantage in timing market actions. In this paper we test how VIX works as a leading indicator of broad stock market index such as S&P 500 (SPX). The purpose of this paper is to find a working way to interpret VIX. The various tests are made on time series data ranging from the year 1990 to the year 2010. The 10-day simple moving average strategy gave significant profits from the whole time when VIX data is available. Strategy was able to utilize the increases of SPX in example portfolio value and was able to step aside when SPX was declining. At the times when portfolio was aside of S it was on safety fund like on treasury bills getting an annual yield of 3 percent. On the other side just a static number’s of VIX did not work as indicators in a profit making way.

Spatio-temporal modelling of the duration of the cotton cycle in the State Of Goiás, Brazil

The objective of this work was to develop and validate a mathematical model to estimate the duration of cotton (Gossypium hirsutum L. r. latifolium hutch) cycle in the State of Goiás, Brazil, by applying the method of growing degree-days (GD), and considering, simultaneously, its time-space variation. The model was developed as a linear combination of elevation, latitude, longitude, and Fourier series of time variation. The model parameters were adjusted by using multiple-linear regression to the observed GD accumulated with air temperature in the range of 15°C to 40°C. The minimum and maximum temperature records used to calculate the GD were obtained from 21 meteorological stations, considering data varying from 8 to 20 years of observation. The coefficient of determination, resulting from the comparison between the estimated and calculated GD along the year was 0.84. Model validation was done by comparing estimated and measured crop cycle in the period from cotton germination to the stage when 90 percent of bolls were opened in commercial crop fields. Comparative results showed that the model performed very well, as indicated by the Pearson correlation coefficient of 0.90 and Willmott agreement index of 0.94, resulting in a performance index of 0.85.

Mapping of summer crops in the State of Paraná, Brazil, through the 10-day spot vegetation NDVI composites

The search for low subjectivity area estimates has increased the use of remote sensing for agricultural monitoring and crop yield prediction, leading to more flexibility in data acquisition and lower costs comparing to traditional methods such as census and surveys. Low spatial resolution satellite images with higher frequency in image acquisition have shown to be adequate for cropland mapping and monitoring in large areas. The main goal of this study was to map the Summer crops in the State of Paraná, Brazil, using 10-day composition of NDVI SPOT Vegetation data for 2005/2006, 2006/2007 and 2007/2008 cropping seasons. For this, a supervised digital classification method with Parallelepiped algorithm in multitemporal RGB image composites was used, in order to generate masks of Summer cultures for each 10-day composition. Accuracy assessment was performed using Kappa index, overall accuracy and Willmott's concordance index, resulting in good levels of accuracy. This methodology allowed the accomplishment, with free and low resolution data, of the mapping of Summer cultures at State level.

Environmental comfort in constructions for Sindi and Guzera calves in the agreste region of the State of Paraiba, Brazil

The objective of this study was to evaluate the quality of air, bioclimatic indexes of facilities and physiological indices of Guzera and Sindhi calves, reared in climatic conditions of Agreste. The study was conducted at the experimental station of Alagoinha, PB, Brazil, using 16 calves of Sindi and Guzerá races. The average concentration of oxygen (20.85%), ammonia (1.99 ppm), carbon monoxide (<0.01 ppm), methane (0.13 ppm) and hydrogen sulfide (<0.01) within facilities, were within the limits established by the Brazilian and international standards, for both animals and workers. The bioclimatic index of temperature and humidity and the temperature of the black globe and humidity index were within the thermal comfort zone for cattle in most of the experimental period, the mean values of respiratory frequency (26.0 min mov-1) and skin temperature (32.3 °C) were higher in the hottest time of the day (1 pm) and rectal temperature (39.3 ºC) in the late afternoon (5 pm), but remained within normal ranges for the studied races. The races have good adaptability to climatic conditions in the region of the Paraibano Agreste, Brazil.

Thermal performance and concentration of gases in facilities for pigs in semiarid region from State of Paraiba - Brazil

The study was conducted in a facility for pigs during the nursery and finishing in the town of 'Montadas', in the semiarid of the state of Paraiba, Brazil, in the rainy and dry season, aiming to evaluate the concentration of oxygen, methane, carbon monoxide and ammonia, and the bioclimatic indexes: ambient temperature (AT), relative humidity (RH) and the index of black globe temperature and humidity (IBGTH). These indexes differed significantly (P>0.05) between the periods and times. The AT in the rainy season was in the thermal comfort zone(TCZ) in most of the times in the nursery; for the finishing phase, thermal discomfort occurred; during the dry season, there was thermal comfort in the nursery phase; in the finishing phase the thermal discomfort occurred at all times. In the rainy season, the IBGTH was in TCZ; in the dry season, it was above the TCZ. The RH in the rainy period was in the TCZ; in the dry season, in most of the times, below the range of the TCZ. The concentration of gases showed no differences (P > 0.05) between periods and between the times, and the carbon monoxide, hydrogen sulfide and methane were below 1.0 ppm, and the ammonia showed a mean of 5.2 ppm. None of the analyzed gases exceeded the limits established by Brazilian and international standards for animals and workers.

Spatial variability of the rainfall erosive potential in the State of Mato Grosso do Sul, Brazil

Information about rainfall erosivity is important during soil and water conservation planning. Thus, the spatial variability of rainfall erosivity of the state Mato Grosso do Sul was analyzed using ordinary kriging interpolation. For this, three pluviograph stations were used to obtain the regression equations between the erosivity index and the rainfall coefficient EI30. The equations obtained were applied to 109 pluviometric stations, resulting in EI30 values. These values were analyzed from geostatistical technique, which can be divided into: descriptive statistics, adjust to semivariogram, cross-validation process and implementation of ordinary kriging to generate the erosivity map.Highest erosivity values were found in central and northeast regions of the State, while the lowest values were observed in the southern region. In addition, high annual precipitation values not necessarily produce higher erosivity values.

Rainfall erosivity for the State of Rio de Janeiro estimated by artificial neural network

The Artificial Neural Networks (ANNs) are mathematical models method capable of estimating non-linear response plans. The advantage of these models is to present different responses of the statistical models. Thus, the objective of this study was to develop and to test ANNs for estimating rainfall erosivity index (EI30) as a function of the geographical location for the state of Rio de Janeiro, Brazil and generating a thematic visualization map. The characteristics of latitude, longitude e altitude using ANNs were acceptable to estimating EI30 and allowing visualization of the space variability of EI30. Thus, ANN is a potential option for the estimate of climatic variables in substitution to the traditional methods of interpolation.