Reduced costs of mixed-species pairings in flycatchers: by-product or female strategy?

Heterospecific matings are generally assumed to be unconditionally disadvantageous due to reduced viability or fertility of hybrid offspring. For female collared flycatchers (Ficedula albicollis) mated to male pied flycatchers (Ficedula hypoleuca), the cost of heterospecific pair formation is reduced due to high levels of conspecific extra-pair paternity and a male-biased offspring sex ratio. In order to investigate whether these cost-reducing mechanisms are the result of female mating strategies, rather than being a by-product of species incompatibilities, we manipulated the plumage of male collared flycatchers before pair formation to make them resemble male pied flycatchers. Since species incompatibilities are absent in this design, any systematic effect of manipulation on sex ratio or paternity would indicate a role of female mating strategy. Paternity was determined by means of a likelihood approach that controls the errors made in assigning a chick to be 'within-pair' or 'extra-pair'. Neither the sex ratio nor the male share of paternity was affected by the manipulation in a systematic manner. We therefore conclude that our experimental data provide no support for the suggestion that female behavioural strategies are markedly adjusted in response to formation of mixed-species pairs

The Architecture of a Software Library for String Processing

We present our project to develop a software library of basic tools and data structures for string processing. Our goal is to provide an environment for testing new algorithms as well as for prototyping. The library has a natural hierarchy comprising basic objects such as the alphabet and strings, data structures to manipulate these objects, and powerful algorithmic techniques driving these data structures. Furthermore, it has the natural taxonomy imposed by the underlying string processing tasks (such as static/dynamic, off-line/on-line, exact/approximate). We believe that our architecture presents a unified view of string processing encompassing recently developed techniques and insights -- this may be of independent interest to those who seek an introduction to this field. Our design is preliminary and we hope to refine it based on feedback. 1. Introduction String problems have attracted a lot of interest throughout the history of Computer Science. Many areas and applications have ..

Peer group and fuzzy metric to remove noise in images using heterogeneous computing

In this paper, we report a study on the parallelization of an algorithm for removing impulsive noise in images. The algorithm is based on the concept of peer group and fuzzy metric. We have developed implementations using Open Multi-Processing (OpenMP) and Compute Unified Device Architecture (CUDA) for Graphics Processing Unit (GPU). Many sequential algorithms have been proposed to remove noise, but their computational cost is excessive for real-time processing of large images. We developed implementations for a multi- core CPU, for a multi-GPU (several GPUs) and for a combination of both. These implementations were compared also with different sizes of the image in order to find out the settings with the best performance. A study is made using the shared memory and texture memory to minimize access time to data in GPU global memory. The result shows that when the image is distributed in multicore and multi-GPU a greater number of Mpixels/second are processed.This work was funded by the Spanish Ministry of Science and Innovation (Project TIN2008-06570-C04-04) and M. Guadalupe would also like to acknowledge DGEST ITCG for the scholarship awarded through the PROMEP program (Mexico)Sanchez, G.; Vidal Gimeno, VE.; Bataller Mascarell, J. (2012). Peer group and fuzzy metric to remove noise in images using heterogeneous computing. En Euro-Par 2011: Parallel Processing Workshops. Springer Verlag (Germany). 7155:502-510. https://doi.org/10.1007/978-3-642-29737-3S502510715