Abstract

Abstract
The youngsters are technology intensive users, open to innovations and a very qualified group of consumers. They learn quickly and manage to explore more device features than adults. Ultimately, the success of many new digital technologies depends on their judgment. This research compares tweens and teens categorizations of electronic games and Internet. Assessing what attributes they consider enables engineers to and marketers to highlight the characteristics that matter to them during the development and marketing process. Methodologically this research is based on 26 focus group involving 104 teenagers and 103 tweens. A total of 55 attributes were associated with electronic games but only 29% were commonly shared with both groups of young participants. Whereas concerning Internet 46% of the 16 attributes verbalized were identical among tweens and teens. © 2012 AICIT.

Abstract
Scenes in real world have dynamic range of radiation that cannot be captured by conventional cameras. High dynamic range imaging is a technique to capture detail images where, in the field of image, intensity variation is extreme. This technique is very useful for biological imaging where the samples have very bright and very dark regions and both parts have useful information. In this article we propose a novel high dynamic range imaging technique based on compressive imaging that uses one single detector instead of camera (array of detectors) to capture an image. Combination of high dynamic range imaging and compressive imaging benefits from imaging with high dynamic range of radiation and advantages of compressive sampling; namely, imaging at regions of optical spectrum where conventional cameras are not readily available and single detectors are available. Additionally, as its name suggests, this technique requires less number of samples (compared to raster scanning). Our experimental results show that high dynamic range compressive imaging system is capable of capturing images with large intensity contrast.

Abstract
This paper deals with the design and implementation of a data model and operations for dealing with continuously changing spatial data in object-relational DBMS. The data model relies on abstract data types but we introduce modifications to the internal structure of the spatiotemporal data representations proposed in the literature, to reduce storage requirements and to enable the reutilization of data during the execution of the queries. We show how to implement spatiotemporal operations relying on the spatial functions released by the underlying DBMS and how to use the alternative data representations to reduce the volume of temporary data created in the evaluation of spatiotemporal operations. We also discuss on the advantages and disadvantages of the proposed solutions. © 2012 ACM.

Abstract
The present study aimed to investigate the relationship between achievement goals, anxiety, selfconfidence and subjective well-being (positive and negative affect, and satisfaction with life) through path analysis. The sample consisted of 169 Brazilian athletes (140 males and 29 females), aged between 17 and 59 years, of different sports and competitive levels. The questionnaires TEOSQ, CSAI-2, EBES and SWLS were applied the day before the competition, on-site training of athletes. Main results partially demonstrated that anxiety and self-confidence mediated the relationship between motivational orientations and subjective well-being. Based on modification indices of the structural model, regression coefficients were specified between ego orientation and negative affect, and between task orientation and the positive dimensions of well-being (positive affect and satisfaction). Results were discussed taking into account the theoretical and practical implications of these relationships. © FTCD/FIP-MOC.

Abstract
DNA-based methods for bacterial detection are increasingly acknowledged as specific, reliable and cost-effective alternatives or complements to the classical culture-based methods, facilitating early detection and presumptive diagnosis, in particular when symptomless plants and quarantine procedures are involved. The massive number of non-redundant bacterial DNA sequences available in gene banks nowadays, and the accessibility to resourceful bioinformatics tools to analyse those sequences, provide an excellent and extensive source for new genus-, species-, or biovar-specific molecular markers. In this study, we propose an in silico workflow framed by four successive criteria and using two web-based bioinformatics applications, CUPID and Insignia, to identify specific chromosomal loci for phytopathogenic bacteria belonging to the genus Agrobacterium (herein called 'agrobacteria'), useful as DNAmarkers to detect pathogenic strains (belonging to several species) of the genus. The selection criteria for the markers are: (i) retrieve the sequence overlaps between CUPID and Insignia databases using a C++ program developed by us in order to increase marker consistency; (ii) the chosen markers should undergo a BLAST (basic local alignment search tool) analysis to confirm their specificity; (iii) an evolutionary and comparative genomic analysis should allow to infer the likelihood of the putative markers being exclusive for the target taxon, and simultaneously ubiquitous within the taxon diversity; (iv) markers should be chosen regarding their suitability for a particular detection technique, e.g. PCR or hybridization profiling.