Convex Optimal Uncertainty Quantification

Optimal uncertainty quantification (OUQ) is a framework for numerical extreme-case analysis of stochastic systems with imperfect knowledge of the underlying probability distribution. This paper presents sufficient conditions under which an OUQ problem can be reformulated as a finite-dimensional convex optimization problem, for which efficient numerical solutions can be obtained. The sufficient conditions include that the objective function is piecewise concave and the constraints are piecewise convex. In particular, we show that piecewise concave objective functions may appear in applications where the objective is defined by the optimal value of a parameterized linear program.Comment: Accepted for publication in SIAM Journal on Optimizatio

Identification of a lineage of multipotent hematopoietic progenitors

All multipotent hematopoietic progenitors in C57BL-Thy-1.1 bone marrow are divided among three subpopulations of Thy-1.1^(lo) Sca-1^+ Lin^(-/lo) c-kit^+ cells: long-term reconstituting Mac-1^-CD4^-c-kit^+ cells and transiently reconstituting Mac-1^(lo)CD4^-or Mac-1^(lo) CD4^(lo) cells. This study shows that the same populations, with similar functional activities, exist in mice whose hematopoietic systems were reconstituted by hematopoietic stem cells after lethal irradiation. We demonstrate that these populations form a lineage of multipotent progenitors from long-term self-renewing stem cells to the most mature multipotent progenitor population. In reconstituted mice, Mac-1- CD4^-c-kit^+ cells gave rise to Mac-1^(lo)CD4^- cells, which gave rise to Mac-1^(lo)CD4^(lo) cells. Mac-1^- CD4^-c-kit^+ cells had long-term self-renewal potential, with each cell being capable of giving rise to more than 10^4 functionally similar Mac-1^-CD4^-c-kit^+ cells. At least half of Mac-1^(lo)CD4^- cells had transient self-renewal potential, detected in the spleen 7 days after reconstitution. Mac-1^(lo)CD4^(lo) cells did not have detectable self-renewal potential. The identification of a lineage of multipotent progenitors provides an important tool for identifying genes that regulate self-renewal and lineage commitment

Hybrid phase at the quantum melting of the Wigner crystal

We study the quantum melting of the two-dimensional Wigner crystal using a fixed node quantum Monte-Carlo approach. In addition to the two already known phases (Fermi liquid at large density and Wigner crystal at low density), we find a third stable phase at intermediate values of the density. The third phase has hybrid behaviors in between a liquid and a solid. This hybrid phase has the nodal structure of a Slater determinant constructed out of the bands of a triangular lattice.Comment: 5 pages, 4 figure

Consistency of Empirical Bayes And Kernel Flow For Hierarchical Parameter Estimation

Hierarchical modeling and learning has proven very powerful in the field of Gaussian process regression and kernel methods, especially for machine learning applications and, increasingly, within the field of inverse problems more generally. The classical approach to learning hierarchical information is through Bayesian formulations of the problem, implying a posterior distribution on the hierarchical parameters or, in the case of empirical Bayes, providing an optimization criterion for them. Recent developments in the machine learning literature have suggested new criteria for hierarchical learning, based on approximation theoretic considerations that can be interpreted as variants of cross-validation, and exploiting approximation consistency in data splitting. The purpose of this paper is to compare the empirical Bayesian and approximation theoretic approaches to hierarchical learning, in terms of large data consistency, variance of estimators, robustness of the estimators to model misspecification, and computational cost. Our analysis is rooted in the setting of Matérn-like Gaussian random field priors, with smoothness, amplitude and inverse lengthscale as hierarchical parameters, in the regression setting. Numerical experiments validate the theory and extend the scope of the paper beyond the Matérn setting

Numerical modelling for nanoparticle thermal migration with effects of shape of particles and magnetic field inside a porous enclosure

Computational modelling for nanoparticle migration inside a permeable space has been reported. Impacts of shape factor and radiation were included in the mathematical model. CVFEM was employed to analyse magnetic force impact. Impacts of magnetic radiative parameters, buoyancy forces and nanoparticle shape on nanomaterial behaviour were demonstrated. Utilizing the Darcy model helps us to predict the behaviour of porous media. Outputs revealed higher convective mode can be achieved with augmenting buoyancy force while opposite outcome appears when magnetic field is imposed. Thermal plume vanishes with the rise of conductive mode which is gained as Hartmann increases

Influence of upstream strut on hydrogen fuel distribution inside the supersonic combustion chamber

© 2020 Hydrogen Energy Publications LLC The efficient fuel mixing in the combustion tank enhances the overall performance of scramjet. Current attempt examines the existence of the strut on the fuel mixing of the multi hydrogen jets at supersonic flow. The numerical approach was employed to visualize the 3D flow behind the strut with multi fuel-jets. The free-stream Mach is 2.2, and four multi jets released hydrogen inside the combustor with the sonic condition. The impact of jet arrangements and the total pressure ratio on the mixing effect of the strut is fully described. Our results indicate that fuel mixing and penetration improved due to the formation of the large subsonic region behind the strut. According to achieved results, the increasing jet space from 1Dj to 5Dj raises the overall mixing to 15% in our proposed model

Ischemic Colitis Revealing Polyarteritis Nodosa

Ischemic colitis is one of the most common intestinal ischemic injuries. It results from impaired perfusion of blood to the bowel and is rarely caused by vasculitis. We report a case of ischemic colitis revealing polyarteritis nodosa (PAN) in a 55-year-old man. Histological examination of the resected colon led to the diagnosis of PAN

Effect of selective heart rate slowing in heart failure with preserved ejection fraction

Background Heart failure with preserved ejection fraction (HFpEF) is associated with significant morbidity and mortality but is currently refractory to therapy. Despite limited evidence, heart rate reduction has been advocated, on the basis of physiological considerations, as a therapeutic strategy in HFpEF. We tested the hypothesis that heart rate reduction improves exercise capacity in HFpEF. Methods and Results We conducted a randomized, crossover study comparing selective heart rate reduction with the If blocker ivabradine at 7.5 mg twice daily versus placebo for 2 weeks each in 22 symptomatic patients with HFpEF who had objective evidence of exercise limitation (peak oxygen consumption at maximal exercise [GraphicO2 peak] <80% predicted for age and sex). The result was compared with 22 similarly treated matched asymptomatic hypertensive volunteers. The primary end point was the change in GraphicO2 peak. Secondary outcomes included tissue Doppler–derived E/e′ at echocardiography, plasma brain natriuretic peptide, and quality-of-life scores. Ivabradine significantly reduced peak heart rate compared with placebo in the HFpEF (107 versus 129 bpm; P<0.0001) and hypertensive (127 versus 145 bpm; P=0.003) cohorts. Ivabradine compared with placebo significantly worsened the change in GraphicO2 peak in the HFpEF cohort (-2.1 versus 0.9 mL·kg−1·min−1; P=0.003) and significantly reduced submaximal exercise capacity, as determined by the oxygen uptake efficiency slope. No significant effects on the secondary end points were discernable. Conclusion Our observations bring into question the value of heart rate reduction with ivabradine for improving symptoms in a HFpEF population characterized by exercise limitation

Gotcha! I Know What You are Doing on the FPGA Cloud: Fingerprinting Co-Located Cloud FPGA Accelerators via Measuring Communication Links

In recent decades, due to the emerging requirements of computation acceleration, cloud FPGAs have become popular in public clouds. Major cloud service providers, e.g. AWS and Microsoft Azure have provided FPGA computing resources in their infrastructure and have enabled users to design and deploy their own accelerators on these FPGAs. Multi-tenancy FPGAs, where multiple users can share the same FPGA fabric with certain types of isolation to improve resource efficiency, have already been proved feasible. However, this also raises security concerns. Various types of side-channel attacks targeting multi-tenancy FPGAs have been proposed and validated. The awareness of security vulnerabilities in the cloud has motivated cloud providers to take action to enhance the security of their cloud environments. In FPGA security research papers, researchers always perform attacks under the assumption that attackers successfully co-locate with victims and are aware of the existence of victims on the same FPGA board. However, the way to reach this point, i.e., how attackers secretly obtain information regarding accelerators on the same fabric, is constantly ignored despite the fact that it is non-trivial and important for attackers. In this paper, we present a novel fingerprinting attack to gain the types of co-located FPGA accelerators. We utilize a seemingly non-malicious benchmark accelerator to sniff the communication link and collect performance traces of the FPGA-host communication link. By analyzing these traces, we are able to achieve high classification accuracy for fingerprinting co-located accelerators, which proves that attackers can use our method to perform cloud FPGA accelerator fingerprinting with a high success rate. As far as we know, this is the first paper targeting multi-tenant FPGA accelerator fingerprinting with the communication side-channel.Comment: To be published in ACM CCS 202