Mexico 1970: occupational stratification, income and region: an analysis of census data

Includes bibliography

The use of census data for national development planning Focus on the 2010 population and housing census

Includes bibliography.

An assessment of big data for official statistics in the Caribbean: Challenges and opportunities

The data revolution for sustainable development has triggered interest in the use of big data for official statistics such that theUnited Nations Economic and Social Council considers it to be almost an obligation for statistical organizations to explore big data. Big data has been promoted as a more timely and cheaper alternative to traditional sources of official data, and one that offers great potential for monitoring the sustainable development goals. However, privacy concerns, technology and capacity remain significant obstacles to the use of big data. This study makes a case for incorporating big data in official statitics in the Caribbean by highlight the opportunities that big data provides for the subregion, while suggesting ways to manage the challenges. It serves as a starting point for further discussions on the many facets of big data and provides an initial platform upon which a Caribbean big data strategy could be built.

Construção e ancoragem ontológica do vocabulário básico bilíngë do turismo para fins didáticos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Treatment of geophysical data as a non-stationary process

ABSTRACT: The Kalman-Bucy method is here analized and applied to the solution of a specific filtering problem to increase the signal message/noise ratio. The method is a time domain treatment of a geophysical process classified as stochastic non-stationary. The derivation of the estimator is based on the relationship between the Kalman-Bucy and Wiener approaches for linear systems. In the present work we emphasize the criterion used, the model with apriori information, the algorithm, and the quality as related to the results. The examples are for the ideal well-log response, and the results indicate that this method can be used on a variety of geophysical data treatments, and its study clearly offers a proper insight into modeling and processing of geophysical problems.

Postsurgical Alveolar Bone Graft Patients: Elaboration and Application of a Data-Gathering Instrument for Nutrition and Nursing

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Oral impacts on the daily performance of Brazilians assessed using a sociodental approach: analyses of national data

The aim of this study was to analyze the relationship between oral diseases and their impact on the daily performance of adult and elderly Brazilians, verify the association of oral diseases with socioeconomic and demographic features, and compare the standard estimate of need with the sociodental assessment of these same needs. The authors evaluated data from 17,398 Brazilians aged between 35-44 years and 65-74 years, taken from the cross-sectional Brazilian Oral Health Survey (Saúde Bucal Brasil - SBBrasil). Regression models were applied to assess associations among impacts on daily performance and income, schooling, gender, region, use of dental services, health perception and dental disease status. McNemar’s test was applied to compare standard versus impact-related estimates of need. The prevalence ratio of these impacts was associated with the sociodemographic versus health perceptions (p < 0.001) of adults and the elderly. Adults also had impacts associated with loss of periodontal attachment (p < 0.001). The prevalence of normative needs was 95.39% for adults and 99.76% for the elderly, whereas the impact-related estimate of need was 50.92% and 43.71%, respectively. The impacted-related approach had a statistically significant association with the normative estimate of need (p < 0.001). This study showed a relationship between oral impact on daily performance of adults and educational level. Sociodemographic features were also related to the impacts on both adults and the elderly, and to health perception. The impacts among the adults were related to the loss of periodontal attachment. In addition, the authors found a sizable difference between the standard versus the sociodental approach, in that the sociodental assessment needs were lower than the needs identified by the standard estimate of need.

Comparison of snow data assimilation system with GPS reflectometry snow depth in the Western United States

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The evolution of phylogeographic data sets

Empirical phylogeographic studies have progressively sampled greater numbers of loci over time, in part motivated by theoretical papers showing that estimates of key demographic parameters improve as the number of loci increases. Recently, next-generation sequencing has been applied to questions about organismal history, with the promise of revolutionizing the field. However, no systematic assessment of how phylogeographic data sets have changed over time with respect to overall size and information content has been performed. Here, we quantify the changing nature of these genetic data sets over the past 20years, focusing on papers published in Molecular Ecology. We found that the number of independent loci, the total number of alleles sampled and the total number of single nucleotide polymorphisms (SNPs) per data set has improved over time, with particularly dramatic increases within the past 5years. Interestingly, uniparentally inherited organellar markers (e.g. animal mitochondrial and plant chloroplast DNA) continue to represent an important component of phylogeographic data. Single-species studies (cf. comparative studies) that focus on vertebrates (particularly fish and to some extent, birds) represent the gold standard of phylogeographic data collection. Based on the current trajectory seen in our survey data, forecast modelling indicates that the median number of SNPs per data set for studies published by the end of the year 2016 may approach similar to 20000. This survey provides baseline information for understanding the evolution of phylogeographic data sets and underscores the fact that development of analytical methods for handling very large genetic data sets will be critical for facilitating growth of the field.

A Simpler and More Accurate AUTO-HDS Framework for Clustering and Visualization of Biological Data

In [1], the authors proposed a framework for automated clustering and visualization of biological data sets named AUTO-HDS. This letter is intended to complement that framework by showing that it is possible to get rid of a user-defined parameter in a way that the clustering stage can be implemented more accurately while having reduced computational complexity

Assessing the gain of biological data integration in gene networks inference

Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.

The accuracy of pathological data for the prediction of insignificant prostate cancer

Introduction: The widespread screening programs prompted a decrease in prostate cancer stage at diagnosis, and active surveillance is an option for patients who may harbor clinically insignificant prostate cancer (IPC). Pathologists include the possibility of an IPC in their reports based on the Gleason score and tumor volume. This study determined the accuracy of pathological data in the identification of IPC in radical prostatectomy (RP) specimens. Materials and Methods: Of 592 radical prostatectomy specimens examined in our laboratory from 2001 to 2010, 20 patients harbored IPC and exhibited biopsy findings suggestive of IPC. These biopsy features served as the criteria to define patients with potentially insignificant tumor in this population. The results of the prostate biopsies and surgical specimens of the 592 patients were compared. Results: The twenty patients who had IPC in both biopsy and RP were considered real positive cases. All patients were divided into groups based on their diagnoses following RP: true positives (n = 20), false positives (n = 149), true negatives (n = 421), false negatives (n = 2). The accuracy of the pathological data alone for the prediction of IPC was 91.4%, the sensitivity was 91% and the specificity was 74%. Conclusion: The identification of IPC using pathological data exclusively is accurate, and pathologists should suggest this in their reports to aid surgeons, urologists and radiotherapists to decide the best treatment for their patients.

Hyperinsulinemic hypoglycemia of the infancy. Analysis of clinical data from a Brazilian sample

Objective: To review the presentation of hyperinsulinemic hypoglycemia of the infancy (HHI), its treatment and histology in Brazilian pediatric endocrinology sections. Materials and method: The protocol analyzed data of birth, laboratory results, treatment, surgery, and pancreas histology. Results: Twenty-five cases of HHI from six centers were analyzed: 15 male, 3/25 born by vaginal delivery. The average age at diagnosis was 10.3 days. Glucose and insulin levels in the critical sample showed an average of 24.7 mg/dL and 26.3 UI/dL. Intravenous infusion of the glucose was greater than 10 mg/kg/min in all cases (M:19,1). Diazoxide was used in 15/25 of the cases, octreotide in 10, glucocorticoid in 8, growth hormone in 3, nifedipine in 2 and glucagon in 1. Ten of the cases underwent pancreatectomy and histology results showed the diffuse form of disease. Conclusion: This is the first critic review of a Brazilian sample with congenital HHI. Arq Bras Endocrinol Metab. 2012; 56(9): 666-71

Spatial-temporal variations in phytoplankton size and colored detrital matter absorption at global and regional scales, as derived from twelve years of SeaWiFS data (1998-2009)

A procedure has been proposed by Ciotti and Bricaud (2006) to retrieve spectral absorption coefficients of phytoplankton and colored detrital matter (CDM) from satellite radiance measurements. This was also the first procedure to estimate a size factor for phytoplankton, based on the shape of the retrieved algal absorption spectrum, and the spectral slope of CDM absorption. Applying this method to the global ocean color data set acquired by SeaWiFS over twelve years (1998-2009), allowed for a comparison of the spatial variations of chlorophyll concentration ([Chl]), algal size factor (S-f), CDM absorption coefficient (a(cdm)) at 443 nm, and spectral slope of CDM absorption (S-cdm). As expected, correlations between the derived parameters were characterized by a large scatter at the global scale. We compared temporal variability of the spatially averaged parameters over the twelve-year period for three oceanic areas of biogeochemical importance: the Eastern Equatorial Pacific, the North Atlantic and the Mediterranean Sea. In all areas, both S-f and a(cdm)(443) showed large seasonal and interannual variations, generally correlated to those of algal biomass. The CDM maxima appeared in some occasions to last longer than those of [Chl]. The spectral slope of CDM absorption showed very large seasonal cycles consistent with photobleaching, challenging the assumption of a constant slope commonly used in bio-optical models. In the Equatorial Pacific, the seasonal cycles of [Chl], S-f, a(cdm)(443) and S-cdm, as well as the relationships between these parameters, were strongly affected by the 1997-98 El Ni o/La Ni a event.

Gaussian deconvolution: a useful method for a form-free modeling of scattering data from mono- and multilayered planar systems

A new method for analysis of scattering data from lamellar bilayer systems is presented. The method employs a form-free description of the cross-section structure of the bilayer and the fit is performed directly to the scattering data, introducing also a structure factor when required. The cross-section structure (electron density profile in the case of X-ray scattering) is described by a set of Gaussian functions and the technique is termed Gaussian deconvolution. The coefficients of the Gaussians are optimized using a constrained least-squares routine that induces smoothness of the electron density profile. The optimization is coupled with the point-of-inflection method for determining the optimal weight of the smoothness. With the new approach, it is possible to optimize simultaneously the form factor, structure factor and several other parameters in the model. The applicability of this method is demonstrated by using it in a study of a multilamellar system composed of lecithin bilayers, where the form factor and structure factor are obtained simultaneously, and the obtained results provided new insight into this very well known system.