Sweat Lodges in Iron Age Iberian Peninsula: New Data, Typologies and Interpretations

Three questions on the study of NO Iberian Peninsula sweat lodges are posed. First, the new sauna of Monte Ornedo (Cantabria), the review of the one of Armea (Ourense), and the Cantabrian pedra formosa type are discussed. Second, the known types of sweat lodges are reconsidered underlining the differences between the Cantabrian and the Douro - Minho groups as these differences contribute to a better assessment of the saunas located out of those territories, such as those of Monte Ornedo or Ulaca. Third, a richer record demands a more specific terminology, a larger use of archaeometric analysis and the application of landscape archaeology or art history methodologies. In this way the range of interpretation of the sweat lodges is opened, as an example an essay is proposed that digs on some already known proposals and suggests that the saunas are material metaphors of wombs whose rationale derives from ideologies and ritual practices of Indo-European tradition.

Prevalence, types and factors associated with echocardiographic abnormalities among newly diagnosed diabetic patients at Mulago Hospital.

Background: The prevalence of Diabetes mellitus (DM) is on a rise in sub-Saharan Africa and will more than double by 2025. Cardiovascular disease (CVD) accounts for up to 2/3 of all deaths in the diabetic population. Of all the CVD deaths in DM, 3/4 occur in sub Saharan Africa (SSA). Non invasive identification of cardiac abnormalities, such as Left Ventricular Hypertrophy (LVH), diastolic and systolic dysfunction, is not part of diabetes complications surveillance programs in Uganda and there is limited data on this problem. This study sought to determine the prevalence, types and factors associated with echocardiographic abnormalities among newly diagnosed diabetic patients at Mulago National referral hospital in Uganda. Methods: In this cross sectional study conducted between June 2014 and December 2014, we recruited 202 newly diagnosed adult diabetic patients. Information on patients\' socio-demographics, bio-physical profile, biochemical testing and echocardiographic findings was obtained for all the participants using a pre-tested questionnaire. An abnormal echocardiogram in this study was defined as the presence of LVH, diastolic and/or systolic dysfunction and wall motion abnormality. Bivariate and multivariate logistic regression analyses were used to investigate the association of several parameters with echocardiographic abnormalities. Results: Of the 202 patients recruited, males were 102(50.5%) and the mean age was 46±15 years. Majority of patients had type 2 DM, 156(77.2%) and type 1 DM, 41(20.3%) with mean HbA1C of 13.9±5.3%. Mean duration of diabetes was 2 months. The prevalence of an abnormal echocardiogram was 67.8 % (95% CI 60%-74%). Diastolic dysfunction, systolic dysfunction, LVH and wall motion abnormalities were present in 55.0%, 21.8%, 19.3% and 4.0% of all the participants respectively. In bivariate logistic regression analysis, the factors associated with an abnormal echocardiogram were age (OR 1.09 [95% CI 1.06–1.12], P <0.0001), type 2 DM (OR 5.8[95% CI 2.77-12.07], P<0.0001), hypertension (OR 2.64[95% CI 1.44-4.85], P=0.002), obesity (OR 3.51[955 CI 1.25-9.84], P=0.017 and increased waist circumference (OR 1.02[95% CI 1.00-1.04], P=0.024. On Multiple logistic regression analysis, age was the only factor associated with an abnormal echocardiogram (OR 1.09[95%CI 1.05-1.15], P<0.0001). Conclusion: Echocardiographic abnormalities were common among newly diagnosed adults with DM. Traditional CVD risk factors were associated with an abnormal echocardiogram in this patient population. Due to a high prevalence of echocardiographic abnormalities among newly diagnosed diabetics, we recommend screening for cardiac disease especially in patients who present with traditional CVD risk factors. This will facilitate early diagnosis, management and hence better patient outcomes.

Description of the Argo GDAC File Checks: Data Format and Consistency Checks

Every Argo data file submitted by a DAC for distribution on the GDAC has its format and data consistency checked by the Argo FileChecker. Two types of checks are applied: 1. Format checks. Ensures the file formats match the Argo standards precisely. 2. Data consistency checks. Additional data consistency checks are performed on a file after it passes the format checks. These checks do not duplicate any of the quality control checks performed elsewhere. These checks can be thought of as “sanity checks” to ensure that the data are consistent with each other. The data consistency checks enforce data standards and ensure that certain data values are reasonable and/or consistent with other information in the files. Examples of the “data standard” checks are the “mandatory parameters” defined for meta-data files and the technical parameter names in technical data files. Files with format or consistency errors are rejected by the GDAC and are not distributed. Less serious problems will generate warnings and the file will still be distributed on the GDAC. Reference Tables and Data Standards: Many of the consistency checks involve comparing the data to the published reference tables and data standards. These tables are documented in the User’s Manual. (The FileChecker implements “text versions” of these tables.)

Atlas versus range maps: robustness of chorological relationships to distribution data types in European mammals

Aim Chorological relationships describe the patterns of distributional overlap among species. In addition to revealing biogeographical structure, the resulting clusters of species with similar geographical distributions can serve as natural units in conservation planning. Here, we assess the extent to which temporal, methodological and taxonomical differences in the source of species’ distribution data can affect the relationships that are found.

Spacecraft Collision Probability Calculation from Conjunction Data Message and High Precision Orbit Propagator

The increasing number of Resident Space Objects (RSOs) is a threat to spaceflight operations. Conjunction Data Messages (CDMs) are sent to satellite operators to warn for possible future collision and their probabilities. The research project described herein pushed forward an algorithm that is able to update the collision probability directly on-board starting from CDMs and the state vector of the hosting satellite which is constantly updated thanks to an onboard GNSS receiver. A large set of methods for computing the collision probability was analyzed in order to find the best ones for this application. The selected algorithm was then tested to assess and improve its performance. Finally, parts of the algorithm and external software were implemented on a Raspberry Pi 3B+ board to demonstrate the compatibility of this approach with computational resources similar to those typically available onboard modern spacecraft.

Iis--integrated Interactome System: A Web-based Platform For The Annotation, Analysis And Visualization Of Protein-metabolite-gene-drug Interactions By Integrating A Variety Of Data Sources And Tools.

High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

Autosomal recessive ataxias: 20 types, and counting

More than 140 years after the first description of Friedreich ataxia, autosomal recessive ataxias have become one of the more complex fields in Neurogenetics. Currently this group of diseases contains more than 20 clinical entities and an even larger number of associated genes. Some disorders are very rare, restricted to isolated populations, and others are found worldwide. An expressive number of recessive ataxias are treatable, and responsibility for an accurate diagnosis is high. The purpose of this review is to update the practitioner on clinical and pathophysiological aspects of these disorders and to present an algorithm to guide the diagnosis.

The young, tight, and low-mass binary TWA22AB: a new calibrator for evolutionary models? Orbit, spectral types, and temperature

Context. Tight binaries discovered in young, nearby associations are ideal targets for providing dynamical mass measurements to test the physics of evolutionary models at young ages and very low masses. Aims. We report the binarity of TWA22 for the first time. We aim at monitoring the orbit of this young and tight system to determine its total dynamical mass using an accurate distance determination. We also intend to characterize the physical properties (luminosity, effective temperature, and surface gravity) of each component based on near-infrared photometric and spectroscopic observations. Methods. We used the adaptive-optics assisted imager NACO to resolve the components, to monitor the complete orbit and to obtain the relative near-infrared photometry of TWA22 AB. The adaptive-optics assisted integral field spectrometer SINFONI was also used to obtain medium-resolution (R(lambda) = 1500-2000) spectra in JHK bands. Comparison with empirical and synthetic librairies were necessary for deriving the spectral type, the effective temperature, and the surface gravity for each component of the system. Results. Based on an accurate trigonometric distance (17.5 +/- 0.2 pc) determination, we infer a total dynamical mass of 220 +/- 21 M(Jup) for the system. From the complete set of spectra, we find an effective temperature T(eff) = 2900(-200)(+200) K for TWA22A and T(eff) = 2900(-100)(+200) for TWA22 B and surface gravities between 4.0 and 5.5 dex. From our photometry and an M6 +/- 1 spectral type for both components, we find luminosities of log(L/L(circle dot)) = -2.11 +/- 0.13 dex and log(L/L(circle dot)) = -2.30 +/- 0.16 dex for TWA22 A and B, respectively. By comparing these parameters with evolutionary models, we question the age and the multiplicity of this system. We also discuss a possible underestimation of the mass predicted by evolutionary models for young stars close to the substellar boundary.

Crystallization, data collection and data processing of maltose-binding protein (MalE) from the phytopathogen Xanthomonas axonopodis pv. citri

Maltose-binding protein is the periplasmic component of the ABC transporter responsible for the uptake of maltose/maltodextrins. The Xanthomonas axonopodis pv. citri maltose-binding protein MalE has been crystallized at 293 Kusing the hanging-drop vapour-diffusion method. The crystal belonged to the primitive hexagonal space group P6(1)22, with unit-cell parameters a = 123.59, b = 123.59, c = 304.20 angstrom, and contained two molecules in the asymetric unit. It diffracted to 2.24 angstrom resolution.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

Brazilian Network of Food Data Systems and LATINFOODS Regional Technical Compilation Committee: Food composition activities (2006-2009)

The Brazilian Network of Food Data Systems (BRASILFOODS) has been keeping the Brazilian Food Composition Database-USP (TBCA-USP) (http://www.fcf.usp.br/tabela) since 1998. Besides the constant compilation, analysis and update work in the database, the network tries to innovate through the introduction of food information that may contribute to decrease the risk for non-transmissible chronic diseases, such as the profile of carbohydrates and flavonoids in foods. In 2008, data on carbohydrates, individually analyzed, of 112 foods, and 41 data related to the glycemic response produced by foods widely consumed in the country were included in the TBCA-USP. Data (773) about the different flavonoid subclasses of 197 Brazilian foods were compiled and the quality of each data was evaluated according to the USDAs data quality evaluation system. In 2007, BRASILFOODS/USP and INFOODS/FAO organized the 7th International Food Data Conference ""Food Composition and Biodiversity"". This conference was a unique opportunity for interaction between renowned researchers and participants from several countries and it allowed the discussion of aspects that may improve the food composition area. During the period, the LATINFOODS Regional Technical Compilation Committee and BRASILFOODS disseminated to Latin America the Form and Manual for Data Compilation, version 2009, ministered a Food Composition Data Compilation course and developed many activities related to data production and compilation. (C) 2010 Elsevier Inc. All rights reserved.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Muscle fibre types and size distribution in sub-antarctic notothenioid fishes

The presumptive tonic muscles fibres of Cottoperca gobio, Champsocephalus esox, Harpagifer bispinis, Eleginops maclovinus, Patagonothen tessellata, P. cornucola and Paranotothenia magellanica stained weakly or were unstained for glycogen, lipid, succinic dehydrogenase (SDHase) and myosin ATPase (mATPase) activity. Slow, intermediate and fast twitch muscle fibres, distinguished on the basis of the pH stability of their mATPases, showed intense, moderate and low staining activity for SDHase, respectively. Slow fibres were the major component of the pectoral fin adductor profundis muscle. The proportion of different muscle fibre types varied from the proximal to distal end of the muscle, but showed relatively little variation between species. The myotomes contained a lateral superficial strip of red muscle composed of presumptive tonic, slow twitch and intermediate fibres, thickening to a major wedge at the horizontal septum. All species also had characteristic secondary dorsal and ventral wedges of red muscle. The relative abundance and localization of muscle fibre types in the red muscle varied between species and with body size in the protandric hermaphrodite E. maclovinus. The frequency distribution of diameters for fast twitch muscle fibres, the major component of deep white muscle, was determined in fish of a range of body sizes. The absence of fibres <20 mu m diameter was used as a criterion for the cessation of muscle fibre recruitment. Fibre recruitment had stopped in P, tessellata of 13.8 cm L-T and E, maclovinus of 32.8 cm L-T, equivalent to 49 and 36.5% of their recorded maximum sizes respectively. As a result in 20-cm P. tessellata, the maximum fibre diameter was 300 mu m and 36% of fibres were in excess of 200 mu m The unusually large maximum fibre diameter, the general arrangement of the red muscle layer and the extreme pH lability of the mATPase of fast twitch fibres are all common characters of the sub-Antarctic and Antarctic Notothenioids, including Cottoperca gobio, the suggested sister group to the Notothenidae. (C) 2000 The Fisheries Society of the British Isles.