Habitat fragmentation and adaptation: a reciprocal replant-transplant experiment among 15 populations of Lychnis flos-cuculi

1. Habitat fragmentation and variation in habitat quality can both affect plant performance, but their effects have rarely been studied in combination. We thus examined plant performance in response to differences in habitat quality for a species subject to habitat fragmentation, the common but declining perennial herb Lychnis flos-cuculi. 2. We reciprocally transplanted plants between 15 fen grasslands in north-east Switzerland and recorded plant performance for 4 years. 3. Variation between the 15 target sites was the most important factor and affected all measures of plant performance in all years. This demonstrates the importance of plastic responses to habitat quality for plant performance. 4. Plants from smaller populations produced fewer rosettes than plants from larger populations in the first year of the replant-transplant experiment. 5. Plant performance decreased with increasing ecological difference between grassland of origin and target grassland, indicating adaptation to ecological conditions. In contrast, plant performance was not influenced by microsatellite distance and hardly by geographic distance between grassland of origin and target grassland. 6. Plants originating from larger populations were better able to cope with larger ecological differences between transplantation site and site of origin. 7. Synthesis: In addition to the direct effects of target grasslands, both habitat fragmentation, through reduced population size, and adaptation to habitats of different quality, contributed to the performance of L. flos-cuculi. This underlines that habitat fragmentation also affects species that are still common. Moreover, it suggests that restoration projects involving L. flos-cuculi should use plant material from large populations living in habitats similar to the restoration site. Finally, our results bring into question whether plants in small habitat remnants will be able to cope with future environmental change.

Divergent adaptation of hepatitis C virus genotypes 1 and 3 to human leukocyte antigen-restricted immune pressure

Many hepatitis C virus (HCV) infections worldwide are with the genotype 1 and 3 strains of the virus. Cellular immune responses are known to be important in the containment of HCV genotype 1 infection, and many genotype 1 T cell targets (epitopes) that are presented by host human leukocyte antigens (HLAs) have been identified. In contrast, there is almost no information known about the equivalent responses to genotype 3. Immune escape mechanisms used by HCV include the evolution of viral polymorphisms (adaptations) that abrogate this host-viral interaction. Evidence of HCV adaptation to HLA-restricted immune pressure on HCV can be observed at the population level as viral polymorphisms associated with specific HLA types. To evaluate the escape patterns of HCV genotypes 1 and 3, we assessed the associations between viral polymorphisms and specific HLA types from 187 individuals with genotype 1a and 136 individuals with genotype 3a infection. We identified 51 HLA-associated viral polymorphisms (32 for genotype 1a and 19 for genotype 3a). Of these putative viral adaptation sites, six fell within previously published epitopes. Only two HLA-associated viral polymorphisms were common to both genotypes. In the remaining sites with HLA-associated polymorphisms, there was either complete conservation or no significant HLA association with viral polymorphism in the alternative genotype. This study also highlights the diverse mechanisms by which viral evasion of immune responses may be achieved and the role of genotype variation in these processes. CONCLUSION: There is little overlap in HLA-associated polymorphisms in the nonstructural proteins of HCV for the two genotypes, implying differences in the cellular immune pressures acting on these viruses and different escape profiles. These findings have implications for future therapeutic strategies to combat HCV infection, including vaccine design.

Model-Centric, Context-Aware Software Adaptation

Software must be constantly adapted to changing requirements. The time scale, abstraction level and granularity of adaptations may vary from short-term, fine-grained adaptation to long-term, coarse-grained evolution. Fine-grained, dynamic and context-dependent adaptations can be particularly difficult to realize in long-lived, large-scale software systems. We argue that, in order to effectively and efficiently deploy such changes, adaptive applications must be built on an infrastructure that is not just model-driven, but is both model-centric and context-aware. Specifically, this means that high-level, causally-connected models of the application and the software infrastructure itself should be available at run-time, and that changes may need to be scoped to the run-time execution context. We first review the dimensions of software adaptation and evolution, and then we show how model-centric design can address the adaptation needs of a variety of applications that span these dimensions. We demonstrate through concrete examples how model-centric and context-aware designs work at the level of application interface, programming language and runtime. We then propose a research agenda for a model-centric development environment that supports dynamic software adaptation and evolution.

Collision Detection: Broad Phase Adaptation from Multi-Core to Multi-GPU Architecture

We present in this paper several contributions on the collision detection optimization centered on hardware performance. We focus on the broad phase which is the first step of the collision detection process and propose three new ways of parallelization of the well-known Sweep and Prune algorithm. We first developed a multi-core model takes into account the number of available cores. Multi-core architecture enables us to distribute geometric computations with use of multi-threading. Critical writing section and threads idling have been minimized by introducing new data structures for each thread. Programming with directives, like OpenMP, appears to be a good compromise for code portability. We then proposed a new GPU-based algorithm also based on the "Sweep and Prune" that has been adapted to multi-GPU architectures. Our technique is based on a spatial subdivision method used to distribute computations among GPUs. Results show that significant speed-up can be obtained by passing from 1 to 4 GPUs in a large-scale environment.