Formalizing the Mapping of UML Conceptual Schemas to Column-oriented Databases

International audienceNowadays, most organizations need to improve their decision-making process using Big Data. To achieve this, they have to store Big Data, perform an analysis, and transform the results into useful and valuable information. To perform this, it's necessary to deal with new challenges in designing and creating data warehouse. Traditionally, creating a data warehouse followed well-governed process based on relational databases. The influence of Big Data challenged this traditional approach primarily due to the changing nature of data. As a result, using NoSQL databases has become a necessity to handle Big Data challenges. In this article, the authors show how to create a data warehouse on NoSQL systems. They propose the Object2NoSQL process that generates column-oriented physical models starting from a UML conceptual model. To ensure efficient automatic transformation, they propose a logical model that exhibits a sufficient degree of independence so as to enable its mapping to one or more column-oriented platforms. The authors provide experiments of their approach using a case study in the health care field

A psychosocial perspective in the explanation of patients' drug-taking behavior

The goal of this study was to examine the applicability of the Health Belief (HBM) and Theory of Reasoned Action (TRA) models in predicting drug-taking compliance behavior among female patients with uncomplicated urinary tract infections. Thirty-eight percent of the respondents were compliant, 25% finished all of their medication, but missed one or more doses during the course of therapy, and 37% did not finish all of their medication as directed. Two HBM and three TRA variables had a statistically significant relationship with compliance: barriers and benefits (HBM) and belief strength, outcome evaluation, and behavioral intention (TRA). HBM variables explained 10% of the variance in the compliance variable. Adding the TRA variables to the model explained an additional 19% of the variance. Social influence variables (normative expectations, motivation to comply, and subjective norms) had a significant influence in the prediction of behavioral intention, but not in the prediction of compliance behavior. Suggestions for improving compliance based on these findings include: simplification of drug therapy by customizing and simplifying the regimen, continued patient reminders of the therapy's value, and benchmarks for patients to evaluate the success or failure of therapy. A frank and open discussion from the start of therapy about its complexity, the medication's side effects, time and fiscal constraints, and other factors which may modify patients' perception of the likelihood of compliance is an important key to improving patients' compliance behavior.Health Belief Model Theory of Reasoned Action compliance health beliefs drug-taking behavior

Polymorphisms of XRCC1 and XRCC3 genes and susceptibility to breast cancer

Mammalian cells are constantly exposed to a wide variety of genotoxic agents from both endogenous and exogenous sources. Genetic variability in DNA repair may contribute to human cancer risk. We used a case-control study design (162 cases and 302 controls) to test the association between three amino acid substitution variants of DNA repair genes ( XRCC1 Arg194Trp, XRCC1 Arg399Gln, and XRCC3 Thr241Met) and breast cancer susceptibility. We found a weak association between the XRCC1 194Trp allele and breast cancer risk (adjusted odds ratio (OR)=1.98; 95% confidence interval (CI)=0.85–4.63). We also found a potential gene-gene interaction between the XRCC1 194Trp allele and XRCC3 241Met allele and breast cancer risk (adjusted OR=8.74; 95% CI=1.13–67.53). Although larger studies are needed to validate the study results, our data suggest that amino acid substitution variants of XRCC1 and XRCC3 genes may contribute to breast cancer susceptibility