SOS-convex Semi-algebraic Programs and its Applications to Robust Optimization: A Tractable Class of Nonsmooth Convex Optimization

In this paper, we introduce a new class of nonsmooth convex functions called SOS-convex semialgebraic functions extending the recently proposed notion of SOS-convex polynomials. This class of nonsmooth convex functions covers many common nonsmooth functions arising in the applications such as the Euclidean norm, the maximum eigenvalue function and the least squares functions with $\ell_1$-regularization or elastic net regularization used in statistics and compressed sensing. We show that, under commonly used strict feasibility conditions, the optimal value and an optimal solution of SOS-convex semi-algebraic programs can be found by solving a single semi-definite programming problem (SDP). We achieve the results by using tools from semi-algebraic geometry, convex-concave minimax theorem and a recently established Jensen inequality type result for SOS-convex polynomials. As an application, we outline how the derived results can be applied to show that robust SOS-convex optimization problems under restricted spectrahedron data uncertainty enjoy exact SDP relaxations. This extends the existing exact SDP relaxation result for restricted ellipsoidal data uncertainty and answers the open questions left in [Optimization Letters 9, 1-18(2015)] on how to recover a robust solution from the semi-definite programming relaxation in this broader setting

Rapid evolution of virulence and drug resistance in the emerging zoonotic pathogen Streptococcus suis

Background: Streptococcus suis is a zoonotic pathogen that infects pigs and can occasionally cause serious infections in humans. S. suis infections occur sporadically in human Europe and North America, but a recent major outbreak has been described in China with high levels of mortality. The mechanisms of S. suis pathogenesis in humans and pigs are poorly understood. Methodology/Principal Findings: The sequencing of whole genomes of S. suis isolates provides opportunities to investigate the genetic basis of infection. Here we describe whole genome sequences of three S. suis strains from the same lineage: one from European pigs, and two from human cases from China and Vietnam. Comparative genomic analysis was used to investigate the variability of these strains. S. suis is phylogenetically distinct from other Streptococcus species for which genome sequences are currently available. Accordingly, ,40% of the ,2 Mb genome is unique in comparison to other Streptococcus species. Finer genomic comparisons within the species showed a high level of sequence conservation; virtually all of the genome is common to the S. suis strains. The only exceptions are three ,90 kb regions, present in the two isolates from humans, composed of integrative conjugative elements and transposons. Carried in these regions are coding sequences associated with drug resistance. In addition, small-scale sequence variation has generated pseudogenes in putative virulence and colonization factors. Conclusions/Significance: The genomic inventories of genetically related S. suis strains, isolated from distinct hosts and diseases, exhibit high levels of conservation. However, the genomes provide evidence that horizontal gene transfer has contributed to the evolution of drug resistance

Ultra-soft 100 nm Thick Zero Poisson’s Ratio Film with 60% Reversible Compressibility

About a 100 nm thick multilayer film of nanoparticle monolayers and polymer layers is shown to behave like cellular-foam with a modulus below 100 KPa. The 1.25 cm radius film adhered to a rigid surface can be compressed reversibly to 60% strain. The more than four orders of magnitude lower modulus compared to its constituents is explained by considering local bending in the (nano)cellular structure, similar to cork and wings of beetles. As the rigidity of the polymer backbone is increased in just four monolayers the modulus of the composite increases by over 70%. Electro-optical map of the strain distribution over the area of compression and increase in modulus with thickness indicates the films have zero Poisson’s ratio

Zoonotic Transmission of mcr-1 Colistin Resistance Gene from Small-Scale Poultry Farms, Vietnam.

We investigated the consequences of colistin use in backyard chicken farms in Vietnam by examining the prevalence of mcr-1 in fecal samples from chickens and humans. Detection of mcr-1-carrying bacteria in chicken samples was associated with colistin use and detection in human samples with exposure to mcr-1-positive chickens

Comparing Student Models in Different Formalisms by Predicting their Impact on Help Success

Session: Student Modeling & PersonalizationInternational audienceWe describe a method to evaluate how student models affect ITS decision quality - their raison d'être. Given logs of randomized tutorial decisions and ensuing student performance, we train a classifier to predict tutor decision outcomes (success or failure) based on situation features, such as student and task. We define a decision policy that selects whichever tutor action the trained classifier predicts in the current situation is likeliest to lead to a successful outcome. The ideal but costly way to evaluate such a policy is to implement it in the tutor and collect new data, which may require months of tutor use by hundreds of students. Instead, we use historical data to simulate a policy by extrapolating its effects from the subset of randomized decisions that happened to follow the policy. We then compare policies based on alternative student models by their simulated impact on the success rate of tutorial decisions. We test the method on data logged by Project LISTEN's Reading Tutor, which chooses randomly which type of help to give on a word. We report the cross-validated accuracy of predictions based on four types of student models, and compare the resulting policies' expected success and coverage. The method provides a utility-relevant metric to compare student models expressed in different formalisms