Signal Detection Theory and Single Observation Designs: Methods and Indices for Advertising Recognition Testing

Two simulations assessed the statistical bias, consistency, and efficiency of 4 different signal detection theory (SDT) sensitivity measures; a corrected-hit probability, the traditional d′ statistic, and 2 nonparametric measures collected from a collapsed-data procedure. Overall, results reinforce evidence that collapsed procedures produce relatively unbiased and efficient estimators. Recommendations for the best approach to using SDT for advertisement recognition testing are offered

Calibration of consumer knowledge of the web

Abstract Calibration of consumer knowledge of the web refers to the correspondence between accuracy and confidence in knowledge of the web. Being well-calibrated means that a person is realistic in his or her assessment of the level of knowledge that he or she possesses. This study finds that involvement leads to better calibration and that calibration is higher for procedural knowledge and common knowledge, as compared to declarative knowledge and specialized knowledge. Neither usage, nor experience, has any effect on calibration of knowledge of the web. No difference in calibration is observed between genders. But, in agreement with previous findings, this study also finds that males are more confident in their knowledge of the web. The results point out that calibration could be more a function of knowledge-specific factors and less that of individual-specific factors. The study also identifies flow and frustration with the web as consequences of calibration of knowledge of the web and draws the attention of future researchers to examine these aspects

RNAG: a new Gibbs sampler for predicting RNA secondary structure for unaligned sequences

Motivation: RNA secondary structure plays an important role in the function of many RNAs, and structural features are often key to their interaction with other cellular components. Thus, there has been considerable interest in the prediction of secondary structures for RNA families. In this article, we present a new global structural alignment algorithm, RNAG, to predict consensus secondary structures for unaligned sequences. It uses a blocked Gibbs sampling algorithm, which has a theoretical advantage in convergence time. This algorithm iteratively samples from the conditional probability distributions P(Structure | Alignment) and P(Alignment | Structure). Not surprisingly, there is considerable uncertainly in the high-dimensional space of this difficult problem, which has so far received limited attention in this field. We show how the samples drawn from this algorithm can be used to more fully characterize the posterior space and to assess the uncertainty of predictions

A global sampling approach to designing and reengineering RNA secondary structures

The development of algorithms for designing artificial RNA sequences that fold into specific secondary structures has many potential biomedical and synthetic biology applications. To date, this problem remains computationally difficult, and current strategies to address it resort to heuristics and stochastic search techniques. The most popular methods consist of two steps: First a random seed sequence is generated; next, this seed is progressively modified (i.e. mutated) to adopt the desired folding properties. Although computationally inexpensive, this approach raises several questions such as (i) the influence of the seed; and (ii) the efficiency of single-path directed searches that may be affected by energy barriers in the mutational landscape. In this article, we present RNA-ensign, a novel paradigm for RNA design. Instead of taking a progressive adaptive walk driven by local search criteria, we use an efficient global sampling algorithm to examine large regions of the mutational landscape under structural and thermodynamical constraints until a solution is found. When considering the influence of the seeds and the target secondary structures, our results show that, compared to single-path directed searches, our approach is more robust, succeeds more often and generates more thermodynamically stable sequences. An ensemble approach to RNA design is thus well worth pursuing as a complement to existing approaches. RNA-ensign is available at http://csb.cs.mcgill.ca/RNAensign.National Science Foundation (U.S.). Graduate Research Fellowship ProgramNatural Sciences and Engineering Research Council of Canada (NSERC) (RGPIN ) (386596-10)Fonds québécois de la recherche sur la nature et les technologies (PR-146375)National Institutes of Health (U.S.) (Grant GM081871)Natural Sciences and Engineering Research Council of Canada (NSERC)National Institutes of Health (U.S.

Structural characterization of naturally occurring RNA single mismatches

RNA is known to be involved in several cellular processes; however, it is only active when it is folded into its correct 3D conformation. The folding, bending and twisting of an RNA molecule is dependent upon the multitude of canonical and non-canonical secondary structure motifs. These motifs contribute to the structural complexity of RNA but also serve important integral biological functions, such as serving as recognition and binding sites for other biomolecules or small ligands. One of the most prevalent types of RNA secondary structure motifs are single mismatches, which occur when two canonical pairs are separated by a single non-canonical pair. To determine sequence–structure relationships and to identify structural patterns, we have systematically located, annotated and compared all available occurrences of the 30 most frequently occurring single mismatch-nearest neighbor sequence combinations found in experimentally determined 3D structures of RNA-containing molecules deposited into the Protein Data Bank. Hydrogen bonding, stacking and interaction of nucleotide edges for the mismatched and nearest neighbor base pairs are described and compared, allowing for the identification of several structural patterns. Such a database and comparison will allow researchers to gain insight into the structural features of unstudied sequences and to quickly look-up studied sequences

Sequence Conservation and Functional Constraint on Intergenic Spacers in Reduced Genomes of the Obligate Symbiont Buchnera

Analyses of genome reduction in obligate bacterial symbionts typically focus on the removal and retention of protein-coding regions, which are subject to ongoing inactivation and deletion. However, these same forces operate on intergenic spacers (IGSs) and affect their contents, maintenance, and rates of evolution. IGSs comprise both non-coding, non-functional regions, including decaying pseudogenes at varying stages of recognizability, as well as functional elements, such as genes for sRNAs and regulatory control elements. The genomes of Buchnera and other small genome symbionts display biased nucleotide compositions and high rates of sequence evolution and contain few recognizable regulatory elements. However, IGS lengths are highly correlated across divergent Buchnera genomes, suggesting the presence of functional elements. To identify functional regions within the IGSs, we sequenced two Buchnera genomes (from aphid species Uroleucon ambrosiae and Acyrthosiphon kondoi) and applied a phylogenetic footprinting approach to alignments of orthologous IGSs from a total of eight Buchnera genomes corresponding to six aphid species. Inclusion of these new genomes allowed comparative analyses at intermediate levels of divergence, enabling the detection of both conserved elements and previously unrecognized pseudogenes. Analyses of these genomes revealed that 232 of 336 IGS alignments over 50 nucleotides in length displayed substantial sequence conservation. Conserved alignment blocks within these IGSs encompassed 88 Shine-Dalgarno sequences, 55 transcriptional terminators, 5 Sigma-32 binding sites, and 12 novel small RNAs. Although pseudogene formation, and thus IGS formation, are ongoing processes in these genomes, a large proportion of intergenic spacers contain functional sequences

Gamification and Mobile Marketing Effectiveness

A variety of business sectors have been buffeted by the diffusion of mobile technology, a trend that presents a variety of difficult challenges but interesting opportunities to marketers. One such opportunity is gamification, which, one hopes, will enhance appeal to mobile consumers. Our sense from both personal experience and the literature is that the gamified mobile apps currently offered by firms mostly miss the mark. We provide a systematic overview of game design and note how principles derived from that field are highly applicable to gamification in mobile marketing settings. We are aided by the work of Schell (2008), whose Elemental Game Tetrad Model allows us to offer a coherent look at how gamification should affect mobile marketing outcomes

Note---Derivation of Covariance Probit Elasticities

The full covariance probit model is highly regarded due to the flexibility with which it can represent cross brand effects. Explicit formulae for these cross brand effects for the general N brand case have never appeared in print, nor have the direct elasticities for the model. This note fills that omission.marketing: estimation/statistical techniques, marketing: choice models