Diversity and genetic relatedness among genotypes of Vitis spp. using microsatellite molecular markers

The purpose of this research was to study the genetic diversity and genetic relatedness of 60 genotypes of grapevines derived from the Germplasm Bank of Embrapa Semiárido, Juazeiro, BA, Brazil. Seven previously characterized microsatellite markers were used: VVS2, VVMD5, VVMD7, VVMD27, VVMD3, ssrVrZAG79 and ssrVrZAG62. The expected heterozygosity (He) and polymorphic information content (PIC) were calculated, and the cluster analysis were processed to generate a dendrogram using the algorithm UPGMA. The He ranged from 81.8% to 88.1%, with a mean of 84.8%. The loci VrZAG79 and VVMD7 were the most informative, with a PIC of 87 and 86%, respectively, while VrZAG62 was the least informative, with a PIC value of 80%. Cluster analysis by UPGMA method allowed separation of the genotypes according to their genealogy and identification of possible parentage for the cultivars 'Dominga', 'Isaura', 'CG 26916', 'CG28467' and 'Roni Redi'.

Säästämispalveluiden henkilöasiakasmarkkinoiden segmentointi - Case: Merita Pankki Oyj

Tutkielman tavoitteena on säästämiskäyttäytymisen tutkiminen ja tarpeet tunnistavan segmentoinnin suorittaminen. Tavoitteena on muodostaa syvällinen näkemys säästämispalveluiden asiakkaista. Segmentointi perustetaan käyttäytymiselle. Tutkielma koostuu teoreettisesta ja empiirisestä osiosta. Teoreettinen osio on kirjoituspöytätutkimusta, jonka tietolähteinä ovat teoriakirjallisuuden lisäksi aiemmat tutkimukset pankkikäyttäytymisestä. Empiirisen osion aineisto on tilastollinen data 96 502 Merita Pankin asiakkaasta. Segmentointi suoritetaan K-klusterianalyysilla ja tuloksia tarkastellaan ristiintaulukoimalla. Tutkimus osoittaa säästämiskäyttäytymisen saavan erilaisia muotoja markkinoilla. Käyttäytymiselle perustuvalla segmentoinnilla syntyy viiden erilaisen säästäjätyypin profiilit. Tarkastelemalla tarjottuja palveluita ja asiakkaiden palvelukokonaisuuksia rinnakkain voidaan tunnistaa asiakkaiden tarpeita. Säästämispalveluiden markkinoiden yksityiskohtaisten tarpeiden tunnistamiseen tarvitaan tutkielmassa käytettyjen tietojen lisäksi kvantitatiivista tietoa asiakkaiden elämänkaaresta ja säästämisen tavoitteesta.

Exploring Different Types of Sharing: A Proposed Segmentation of the Market for "Sharing Businesses"

Sharing instead of buying is regaining traction among today's consumers. This study aims at identifying segments of sharing consumers to unearth potentially viable clusters of a consumer behavior that is a market of growing economic relevance. By means of a qualitative study and a survey with a roughly representative sample of 1121 Swiss-German and German consumers, a set of trait-related, motivational, and perceived socioeconomic variables is identified that can be used to group individuals into segments that differ with regard to their approach to sharing. A cluster analysis based on these variables suggests four potential clusters of sharing consumers-sharing idealists, sharing opponents, sharing pragmatists, and sharing normatives. Two sets of testable propositions are derived that can guide further research in this domain and pave the way to a more targeted approach to the growing market of "sharing" businesses.

PREVENTION OF CHILLING INJURY IN 'TOMMY ATKINS' MANGOES PREVIOUSLY STORED AT 5 ºC, USING HEAT TREATMENT AND RADIATION UV (UV-C)

ABSTRACT The objective of this study was to evaluate the effect of heat treatment and ultraviolet radiation (UV-C) in the prevention of chilling injury in mangoes cv. Tommy Atkins previously stored or not under injury condition after their transference to ambient condition. Fruits were divided into groups: two were hydrothermally treated (46.1 ºC/90 min; 55 ºC/5 min) and two were exposed to UV-C radiation (1.14 kJ m-2; 2.28 kJ m-2). These groups were stored under chilling injury conditions (5 ºC for 14 days), as established in preliminary tests. Other untreated groups were stored at 12 ºC or 5 ºC. After the storage period, they were transferred to ambient conditions (21.9 ºC; 55% RH) and the quality was evaluated. All the data were submitted to multivariate analysis as the tool to verify the simultaneous effect of the treatments under the quality parameters. The multivariate analysis indicated that the hydrothermal treatments at 46.1 °C/90 min and 55 °C/5 min and the UV-C radiation at doses of 1.14 kJ m-2 and 2.28 kJ m-2 were effective in minimized the symptoms of chilling injury in mangoes ‘Tommy Atkins’ stored at 5 °C for 14 days. However, after their transference to environmental condition at 21.9 °C, only the UV-C kept this control, especially at a dose of 2.28 kJ m-2. This treatment did not prevent the development of the characteristic color or affected the normal ripening and allowed the conservation of fruit for a period of 14 days at 5 °C, plus seven days of storage at environmental condition, which corresponds to the shipping transportation plus the time for sale.

Business models enhancing the diffusion of mobile Internet in emerging markets

Tämän tutkimuksen päätavoitteena oli selvittää, millaiset liiketoimintamallit soveltuvat mobiilin internet-liiketoiminnan harjoittamiseen kehittyvillä markkinoilla. Tavoitteena oli myös selvittää tekijöitä, jotka vaikuttavat mobiilin internetin diffuusioon. Tutkimus tehtiin käyttäen sekä kvantitatiivista että kvalitatiivista tutkimusmenetelmää. Klusterianalyysin avulla 40 Euroopan maasta muodostettiin sisäisesti homogeenisiä maaklustereita. Näiden klustereiden avulla oli mahdollista suunnitella erityyppisille markkinoille soveltuvat liiketoimintamallit. Haastatteluissa selvitettiin asiantuntijoiden näkemyksiä tekijöistä, jotka vaikuttavat mobiilin internetin diffuusioon kehittyvillä markkinoilla. Tutkimuksessa saatiin selville, että tärkeimmät liiketoimintamallin elementit kehittyvillä markkinoilla ovat hinnoittelu, arvotarjooma ja arvoverkko. Puutteellisen kiinteän verkon todettiin olevan yksi tärkeimmistä mobiilin internetin diffuusiota edistävistä tekijöistä kehittyvillä markkinoilla.

Polymorphisms in DNA-repair genes in a cohort of prostate cancer patients from different areas in Spain: heterogeneity between populations as a confounding factor in association studies

Background: Differences in the distribution of genotypes between individuals of the same ethnicity are an important confounder factor commonly undervalued in typical association studies conducted in radiogenomics. Objective: To evaluate the genotypic distribution of SNPs in a wide set of Spanish prostate cancer patients for determine the homogeneity of the population and to disclose potential bias. Design, Setting, and Participants: A total of 601 prostate cancer patients from Andalusia, Basque Country, Canary and Catalonia were genotyped for 10 SNPs located in 6 different genes associated to DNA repair: XRCC1 (rs25487, rs25489, rs1799782), ERCC2 (rs13181), ERCC1 (rs11615), LIG4 (rs1805388, rs1805386), ATM (rs17503908, rs1800057) and P53 (rs1042522). The SNP genotyping was made in a Biotrove OpenArrayH NT Cycler. Outcome Measurements and Statistical Analysis: Comparisons of genotypic and allelic frequencies among populations, as well as haplotype analyses were determined using the web-based environment SNPator. Principal component analysis was made using the SnpMatrix and XSnpMatrix classes and methods implemented as an R package. Non-supervised hierarchical cluster of SNP was made using MultiExperiment Viewer. Results and Limitations: We observed that genotype distribution of 4 out 10 SNPs was statistically different among the studied populations, showing the greatest differences between Andalusia and Catalonia. These observations were confirmed in cluster analysis, principal component analysis and in the differential distribution of haplotypes among the populations. Because tumor characteristics have not been taken into account, it is possible that some polymorphisms may influence tumor characteristics in the same way that it may pose a risk factor for other disease characteristics. Conclusion: Differences in distribution of genotypes within different populations of the same ethnicity could be an important confounding factor responsible for the lack of validation of SNPs associated with radiation-induced toxicity, especially when extensive meta-analysis with subjects from different countries are carried out.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PURPOSE: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. METHOD: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). RESULTS: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. CONCLUSION: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.

Identification and prospective validation of clinically relevant chronic obstructive pulmonary disease (COPD) subtypes.

Background Chronic obstructive pulmonary disease (COPD) is increasingly considered a heterogeneous condition. It was hypothesised that COPD, as currently defined, includes different clinically relevant subtypes. Methods To identify and validate COPD subtypes, 342 subjects hospitalised for the first time because of a COPD exacerbation were recruited. Three months after discharge, when clinically stable, symptoms and quality of life, lung function, exercise capacity, nutritional status, biomarkers of systemic and bronchial inflammation, sputum microbiology, CT of the thorax and echocardiography were assessed. COPD groups were identified by partitioning cluster analysis and validated prospectively against cause-specific hospitalisations and all-cause mortality during a 4 year follow-up. Results Three COPD groups were identified: group 1 (n ¼ 126, 67 years) was characterised by severe airflow limitation (postbronchodilator forced expiratory volume in 1 s (FEV 1 ) 38% predicted) and worse performance in most of the respiratory domains of the disease; group 2 (n ¼ 125, 69 years) showed milder airflow limitation (FEV 1 63% predicted); and group 3 (n ¼ 91, 67 years) combined a similarly milder airflow limitation (FEV 1 58% predicted) with a high proportion of obesity, cardiovascular disorders, iabetes and systemic inflammation. During follow-up, group 1 had more frequent hospitalisations due to COPD (HR 3.28, p < 0.001) and higher all-cause mortality (HR 2.36, p ¼ 0.018) than the other two groups, whereas group 3 had more admissions due to cardiovascular disease (HR 2.87, p ¼ 0.014). Conclusions In patients with COPD recruited at their first hospitalisation, three different COPD subtypes were identified and prospectively validated:"severe respiratory COPD","moderate respiratory COPD", and"systemic COPD'

Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns.

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs-locomotor bouts-matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior.

Measuring Intermediary Determinants of Early Childhood Health: A Composite Index Comparing Colombian Departments

In recent years there has been growing interest in composite indicators as an efficient tool of analysis and a method of prioritizing policies. This paper presents a composite index of intermediary determinants of child health using a multivariate statistical approach. The index shows how specific determinants of child health vary across Colombian departments (administrative subdivisions). We used data collected from the 2010 Colombian Demographic and Health Survey (DHS) for 32 departments and the capital city, Bogotá. Adapting the conceptual framework of Commission on Social Determinants of Health (CSDH), five dimensions related to child health are represented in the index: material circumstances, behavioural factors, psychosocial factors, biological factors and the health system. In order to generate the weight of the variables, and taking into account the discrete nature of the data, principal component analysis (PCA) using polychoric correlations was employed in constructing the index. From this method five principal components were selected. The index was estimated using a weighted average of the retained components. A hierarchical cluster analysis was also carried out. The results show that the biggest differences in intermediary determinants of child health are associated with health care before and during delivery.

Measuring early childhood health : a composite index comparing Colombian departments

This paper presents a composite index of early childhood health using a multivariate statistical approach. The index shows how child health varies across Colombian departments, -administrative subdivisions-. In recent years there has been growing interest in composite indicators as an efficient analysis tool and a way of prioritizing policies. These indicators not only enable multi-dimensional phenomena to be simplified but also make it easier to measure, visualize, monitor and compare a country’s performance in particular issues. We used data collected from the Colombian Demographic and Health Survey, DHS, for 32 departments and the capital city, Bogotá, in 2005 and 2010. The variables included in the index provide a measure of three dimensions related to child health: health status, health determinants and the health system. In order to generate the weight of the variables and take into account the discrete nature of the data, we employed a principal component analysis, PCA, using polychoric correlation. From this method, five principal components were selected. The index was estimated using a weighted average of the components retained. A hierarchical cluster analysis was also carried out. We observed that the departments ranking in the lowest positions are located on the Colombian periphery. They are departments with low per capita incomes and they present critical social indicators. The results suggest that the regional disparities in child health may be associated with differences in parental characteristics, household conditions and economic development levels, which makes clear the importance of context in the study of child health in Colombia.

Brief report : Academic amotivation in light of the dark side of identity formation

The study intended to determine motivational profiles of first-year undergraduates and aimed their characterization in terms of identity processes. First, a cluster analysis revealed five motivational profiles: combined (i.e., high quantity of motivation, low amotivation); intrinsic (i.e., high intrinsic, low introjected and external regulation, low amotivation); "demotivated" (i.e., very low quantity of motivation and amotivation); extrinsic (i.e., high extrinsic and identified regulation and low intrinsic and amotivation); and "amotivated" (i.e., low intrinsic and identified, very high amotivation). Second, using Lebart's (2000) methodology, the most characteristic identity processes were listed for each motivational cluster. Demotivated and amotivated profiles were refined in terms of adaptive and maladaptive forms of exploration. Notably, exploration in breadth and in depth were underrepresented in demotivated students compared to the total sample; commitment and ruminative exploration were under and overrepresented respectively in amotivated students. Educational and clinical implications are proposedand future research is suggested.

The unfathomable secret remains: a reverse engineering study of SEO factors on Google's search engine

The vast majority of users don’t seek results beyond the second page offered by the search engine, so if a site fails to be among the top 20 (second page), it says that this page does not have good SEO and, therefore, is not visible to the user. The overall objective of this project is to conduct a study to discover the factors that determine (or not) the positioning of websites in a search engine.

Uma introdução à análise exploratória de dados multivariados

The modern technological ability to handle large amounts of information confronts the chemist with the necessity to re-evaluate the statistical tools he routinely uses. Multivariate statistics furnishes theoretical bases for analyzing systems involving large numbers of variables. The mathematical calculations required for these systems are no longer an obstacle due to the existence of statistical packages that furnish multivariate analysis options. Here basic concepts of two multivariate statistical techniques, principal component and hierarchical cluster analysis that have received broad acceptance for treating chemical data are discussed.

Approximation to the theory of affinities to manage the problems of the groupping process

New economic and enterprise needs have increased the interest and utility of the methods of the grouping process based on the theory of uncertainty. A fuzzy grouping (clustering) process is a key phase of knowledge acquisition and reduction complexity regarding different groups of objects. Here, we considered some elements of the theory of affinities and uncertain pretopology that form a significant support tool for a fuzzy clustering process. A Galois lattice is introduced in order to provide a clearer vision of the results. We made an homogeneous grouping process of the economic regions of Russian Federation and Ukraine. The obtained results gave us a large panorama of a regional economic situation of two countries as well as the key guidelines for the decision-making. The mathematical method is very sensible to any changes the regional economy can have. We gave an alternative method of the grouping process under uncertainty.