Laboratory experimental evolution provides a window into the details of the evolutionary process. To investigate the consequences of long-term adaptation, we evolved 205 S. cerevisiae populations (124 haploid and 81 diploid) for ∼10,000 generations in three environments. We measured the dynamics of fitness changes over time, finding repeatable patterns of declining adaptability. Sequencing revealed that this phenotypic adaptation is coupled with a steady accumulation of mutations, widespread genetic parallelism, and historical contingency. In contrast to long-term evolution in E. coli, we do not observe long-term coexistence or populations with highly elevated mutation rates. We find that evolution in diploid populations involves both fixation of heterozygous mutations and frequent loss-of-heterozygosity events. Together, these results help distinguish aspects of evolutionary dynamics that are likely to be general features of adaptation across many systems from those that are specific to individual organisms and environmental conditions.

Abstract-Based on physical laws describing the multi-scale structure of turbulent flows, this article proposes a regularizer for fluid motion estimation from an image sequence. Regularization is achieved by imposing some scale invariance property between histograms of motion increments computed at different scales. By reformulating this problem from a Bayesian perspective, an algorithm is proposed to jointly estimate motion, regularization hyper-parameters, and to select the most likely physical prior among a set of models. Hyper-parameter and model inference is conducted by posterior maximization, obtained by marginalizing out non-Gaussian motion variables. The Bayesian estimator is assessed on several image sequences depicting synthetic and real turbulent fluid flows. Results obtained with the proposed approach exceed the state of the art results in fluid flow estimation.

Both interferon-␥ (IFN-␥) and interleukin (IL)-4 expression in T cells and IL-6 expression in cells of the monocyte/macrophage lineage were monitored using antigen 85B (Ag85B) protein and purified protein derivative (PPD) antigen in the early stages of tuberculosis (TB). We showed that the levels of cell-associated IFN-␥ and IL-4 (mRNA and intracellular cytokine) in Ag85B-stimulated T cells were significantly depressed in TB patients compared with those in healthy tuberculin reactors. On the other hand, the capacity of peripheral blood mononuclear cells (PBMC) to produce IL-6 spontaneously ex vivo was enhanced in patients (P < 0.001), but their corresponding capacities to respond to Ag85B were not significantly different from those of normal donors. After 2 months of antituberculosis therapy, the mean blastogenic responses of Ag85B-stimulated PBMC from seven TB patients were increased 6.1-fold (P ¼ 0.011). Furthermore, the proportions of both IFN-␥-(P < 0.01) and IL-4-(P ¼ 0.05) producing T cells were significantly increased. However, those of IL-6-producing cells were diminished in response to Ag85B (P ¼ 0.05). Our results suggest that there may be an altered regulation of IFN-␥, IL-4 and IL-6 to Ag85B in the early stages of TB.

The peer -to-peer (P2P)

Manufacturing enterprise decisions can be classified into four groups: business decisions, design decisions, engineering decisions, and production decisions. Numerous physical and software simulation techniques have been used to evaluate specific decisions by predicting their impact on the system as measured by one or more performance measures. In tbis paper, we focus on production decisions, where discrete-event simulation models perform that evaluation. We argue that such an evaluation is limited in time and scope, and does not capture the potential impact of these decisions on the whole enterprise. We propose integrating these discrete-event models with system dynamic models and we show the potential benefits of such an integration using an example of semiconductor enterprise.