Dynamic smoothness parameter for fast gradient methods

We present and computationally evaluate a variant of the fast gradient method by Nesterov that is capable of exploiting information, even if approximate, about the optimal value of the problem. This information is available in some applications, among which the computation of bounds for hard integer programs. We show that dynamically changing the smoothness parameter of the algorithm using this information results in a better convergence profile of the algorithm in practice

On the Computational Efficiency of Subgradient Methods: a Case Study with Lagrangian Bounds

Subgradient methods (SM) have long been the preferred way to solve the large-scale Nondifferentiable Optimization problems arising from the solution of Lagrangian Duals (LD) of Integer Programs (IP). Although other methods can have better convergence rate in practice, SM have certain advantages that may make them competitive under the right conditions. Furthermore, SM have significantly progressed in recent years, and new versions have been proposed with better theoretical and practical performances in some applications. We computationally evaluate a large class of SM in order to assess if these improvements carry over to the IP setting. For this we build a unified scheme that covers many of the SM proposed in the literature, comprised some often overlooked features like projection and dynamic generation of variables. We fine-tune the many algorithmic parameters of the resulting large class of SM, and we test them on two different Lagrangian duals of the Fixed-Charge Multicommodity Capacitated Network Design problem, in order to assess the impact of the characteristics of the problem on the optimal algorithmic choices. Our results show that, if extensive tuning is performed, SM can be competitive with more sophisticated approaches when the tolerance required for solution is not too tight, which is the case when solving LDs of IPs

Dynamic Smoothness Parameter for Fast Gradient Methods

We present and computationally evaluate a variant of the fast gradient method by Nesterov that is capable of exploiting information, even if approximate, about the optimal value of the problem. This information is available in some applications, among which the computation of bounds for hard integer programs. We show that dynamically changing the smoothness parameter of the algorithm using this information results in a better convergence profile of the algorithm in practice

High genetic connectivity among large populations of Pteronotus gymnonotus in bat caves in Brazil and its implications for conservation

Bat caves in the Neotropical region harbor exceptional bat populations (> 100,000 individuals). These populations play a wider role in ecological interactions, are vulnerable due to their restriction to caves, and have a disproportionate conservation value. Current knowledge of bat caves in Brazil is still small. However, systematic monitoring of some bat caves in northeastern Brazil shows that they experience strong population fluctuations over short periods of time, suggesting large-scale movements between roosts and a much broader use of the landscape than previously considered. Spatio-temporal reproductive connectivity between distant populations would change our understanding of the use of roosts among bat species in Brazil, and important gaps in knowledge of long-distance bat movements in the country would be filled. Here, we used ddRADseq data to analyze the genetic structure of Pteronotus gymnonotus across nine bat caves over 700 km. Our results indicate the lack of a clear geographic structure with gene flow among all the caves analyzed, suggesting that P. gymnonotus uses a network of bat caves geographically segregated hundreds of kilometers apart. Facing strong anthropogenic impacts and an underrepresentation of caves in conservation action plans worldwide, the genetic connectivity demonstrated here confirms that bat caves are priority sites for bat and speleological conservation in Brazil and elsewhere. Moreover, our results demonstrate a warning call: the applied aspects of the environmental licensing process of the mining sector and its impact must be reviewed, not only in Brazil, but wherever this licensing process affects caves having exceptional bat populations.Peer reviewe

Should I stay or should I go? Climate change effects on the future of Neotropical savannah bats

AbstractMost extant species are survivors of the last climate change event 20,000 years ago. While past events took place over thousands of years, current climate change is occurring much faster, over a few decades. We modelled the potential distribution area of bat species in the Brazilian Cerrado, a Neotropical savannah, and assessed the potential impacts of climate change up to 2050 in two scenarios. First we evaluated what the impact on the distributions of bat species would be if they were unable to move to areas where climate conditions might be similar to current ones. The novelty of our paper is that, based on least-cost-path analyses, we identified potential corridors that could be managed now to mitigate potential impacts of climate change. Our results indicate that on average, in the future bat species would find similar climate conditions 281 km southeast from current regions. If bat species were not able to move to new suitable areas and were unable to adapt, then 36 species (31.6%) could lose >80% of their current distribution area, and five species will lose more than 98% of their distribution area in the Brazilian Cerrado. In contrast, if bat species are able to reach such areas, then the number of highly impacted species will be reduced to nine, with none of them likely to disappear from the Cerrado. We present measures that could be implemented immediately to mitigate future climate change impacts

Tcf7l2 plays pleiotropic roles in the control of glucose homeostasis, pancreas morphology, vascularization and regeneration

Type 2 diabetes (T2D) is a disease characterized by impaired insulin secretion. The Wnt signaling transcription factor Tcf7l2 is to date the T2D-associated gene with the largest effect on disease susceptibility. However, the mechanisms by which TCF7L2 variants affect insulin release from \u3b2-cells are not yet fully understood. By taking advantage of a tcf7l2 zebrafish mutant line, we first show that these animals are characterized by hyperglycemia and impaired islet development. Moreover, we demonstrate that the zebrafish tcf7l2 gene is highly expressed in the exocrine pancreas, suggesting potential bystander effects on \u3b2-cell growth, differentiation and regeneration. Finally, we describe a peculiar vascular phenotype in tcf7l2 mutant larvae, characterized by significant reduction in the average number and diameter of pancreatic islet capillaries. Overall, the zebrafish Tcf7l2 mutant, characterized by hyperglycemia, pancreatic and vascular defects, and reduced regeneration proves to be a suitable model to study the mechanism of action and the pleiotropic effects of Tcf7l2, the most relevant T2D GWAS hit in human populations