Design patterns and pspects : modular designs with seamless run-time integration

Some solutions proposed in the original design pattern literature were shaped by techniques as well as language deficiencies from object-oriented software development. However, new modularity constructs, composition and transformation mechanisms offered by aspect-oriented programming address deficiencies of object-oriented modeling. This suggests classical design pattern solutions to be revisited. In our paper we point out that aspect-oriented programming not only allows for alternative representations of proposed solutions, but also for better solutions in the first place. We advocate a native aspect-oriented approach to design patterns that emphasizes on improving design pattern solutions both during development and at run-time. We use a simple yet effective method to analyze and describe different solutions on the basis of variation points, fixed parts, variable parts, and optional glue, employing dynamic run-time weaving

Towards Normalizing the Edit Distance Using a Genetic Algorithms Based Scheme

The normalized edit distance is one of the distances derived from the edit distance. It is useful in some applications because it takes into account the lengths of the two strings compared. The normalized edit distance is not defined in terms of edit operations but rather in terms of the edit path. In this paper we propose a new derivative of the edit distance that also takes into consideration the lengths of the two strings, but the new distance is related directly to the edit distance. The particularity of the new distance is that it uses the genetic algorithms to set the values of the parameters it uses. We conduct experiments to test the new distance and we obtain promising results.Comment: The 8th International Conference on Advanced Data Mining and Applications (ADMA 2012

Gene phylogenies and protein–protein interactions: possible artifacts resulting from shared protein interaction partners

The study of gene families critically depends on the correct reconstruction of gene genealogies, as for instance in the case of transcription factor genes like Hox genes and Dlx gene families. Proteins belonging to the same family are likely to share some of the same protein interaction partners and may thus face a similar selective environment. This common selective environment can induce co-evolutionary pressures and thus can give rise to correlated rates and patterns of evolution among members of a gene family. In this study, we simulate the evolution of a family of sequences which share a set of interaction partners. Depending on the amount of sequence dedicated to protein–protein interaction and the relative rate parameters of sequence evolution three outcomes are possible: if the fraction of the sequence dedicated to interaction with common co-factors is low and the time since divergence is small, the trees based on sequence information tend to be correct. If the time since gene duplication is long two possible outcomes are observed in our simulations. If the rate of evolution of the interaction partner is small compared to the rate of evolution of the focal protein family, the reconstructed trees tend towards star phylogenies. As the rate of evolution of the interaction partner approaches that of the focal protein family the reconstructed phylogenies tend to be incorrectly resolved. We conclude that the genealogies of gene families can be hard to estimate, in particular if the proteins interact with a conserved set of binding partners, as is likely the case for transcription factors

Initial Staging of Locally Advanced Rectal Cancer and Regional Lymph Nodes: Comparison of Diffusion-Weighted MRI With 18F-FDG-PET/CT.

The aim of the study was to compare diffusion-weighted MRI (DW-MRI) parameters with 18F-FDG PET/CT in primary locally advanced rectal cancer (LARC). From October 2012 to September 2014, 24 patients with histologically confirmed and untreated LARC (T3-T4) prospectively underwent a pelvic 1.5-T DW-MRI (b = 0 s/mm, b = 600 s/mm2) and a whole-body 18F-FDG PET/CT, before neoadjuvant therapy. The 2 examinations were performed on the same day. Two readers measured 18F-FDG SUVmax and SUVmean of the rectal tumor and of the pathological regional lymph nodes on PET/CT and compared these with minimum and mean values of the ADC (ADCmin and ADCmean) on maps generated from DW-MRI. The diagnostic performance of ADC values in identifying pathological lymph nodes was also assessed. Regarding tumors (n = 24), we found a significant negative correlation between SUVmean and corresponding ADCmean values (ρ = -0.61, P = 0.0017) and between ADCmin and SUVmax (ρ = -0.66, P = 0.0005). Regarding the lymph nodes (n = 63), there was a significant negative correlation between ADCmean and SUVmean values (ρ = -0.38, P = 0.0021), but not between ADCmin and SUVmax values (ρ = -0.11, P = 0.41). Neither ADCmean nor ADCmin values helped distinguish pathological from benign lymph nodes (AUC of 0.24 [confidence interval, 0.10-0.38] and 0.41 [confidence interval, 0.22-0.60], respectively). The correlations between ADCmean and SUVmean suggest an association between tumor cellularity and metabolic activity in untreated LARC and in regional lymph nodes. However, compared with 18F-FDG PET/CT, ADC values are not reliable for identifying pathological lymph nodes

A Discriminative Model of Stochastic Edit Distance in the form of a Conditional Transducer

pages 240-252International audienceMany real-world applications such as spell-checking or DNA analysis use the Levenshtein edit-distance to compute similarities between strings. In practice, the costs of the primitive edit operations (insertion, deletion and substitution of symbols) are generally hand-tuned. In this paper, we propose an algorithm to learn these costs. The underlying model is a probabilitic transducer, computed by using grammatical inference techniques, that allows us to learn both the structure and the probabilities of the model. Beyond the fact that the learned transducers are neither deterministic nor stochastic in the standard terminology, they are conditional, thus independant from the distributions of the input strings. Finally, we show through experiments that our method allows us to design cost functions that depend on the string context where the edit operations are used. In other words, we get kinds of \textit{context-sensitive} edit distances

Faster Approximate String Matching for Short Patterns

We study the classical approximate string matching problem, that is, given strings $P$ and $Q$ and an error threshold $k$, find all ending positions of substrings of $Q$ whose edit distance to $P$ is at most $k$. Let $P$ and $Q$ have lengths $m$ and $n$, respectively. On a standard unit-cost word RAM with word size $w \geq \log n$ we present an algorithm using time $$O(nk \cdot \min(\frac{\log^2 m}{\log n},\frac{\log^2 m\log w}{w}) + n)$$ When $P$ is short, namely, $m = 2^{o(\sqrt{\log n})}$ or $m = 2^{o(\sqrt{w/\log w})}$ this improves the previously best known time bounds for the problem. The result is achieved using a novel implementation of the Landau-Vishkin algorithm based on tabulation and word-level parallelism.Comment: To appear in Theory of Computing System

Rebuttal to Hasan and Pedraza in comments and controversies: "Improving the reliability of manual and automated methods for hippocampal and amygdala volume measurements"

Here we address the critiques offered by Hasan and Pedraza to our recently published manuscript comparing the performance of two automated segmentation programs, FSL/FIRST and FreeSurfer (Morey R, Petty C, Xu Y, Pannu Hayes J, Wagner H, Lewis D, LaBar K, Styner M, McCarthy G. (2009): A comparison of automated segmentation and manual tracing for quantifying of hippocampal and amygdala volumes. Neuroimage 45:855-866). We provide an assessment and discussion of their specific critiques. Hasan and Pedraza bring up some important points concerning our omission of sample demographic features and inclusion of left and right hemisphere volumes as independent measures in correlational analyses. We present additional data on demographic attributes of our sample and correlations analyzed separately on left and right hemispheres of the amygdala and hippocampus. While their commentary aids the reader to more critically asses our study, it falls short of substantiating that our omissions ought to lead readers to significantly revise their interpretations. Further research will help to disentangle the advantages and limitations of the various freely-available automated segmentation software packages

Class of correlated random networks with hidden variables

We study a class models of correlated random networks in which vertices are characterized by \textit{hidden variables} controlling the establishment of edges between pairs of vertices. We find analytical expressions for the main topological properties of these models as a function of the distribution of hidden variables and the probability of connecting vertices. The expressions obtained are checked by means of numerical simulations in a particular example. The general model is extended to describe a practical algorithm to generate random networks with an \textit{a priori} specified correlation structure. We also present an extension of the class, to map non-equilibrium growing networks to networks with hidden variables that represent the time at which each vertex was introduced in the system