Optimal vaccination in a stochastic epidemic model of two non-interacting populations

Developing robust, quantitative methods to optimize resource allocations in response to epidemics has the potential to save lives and minimize health care costs. In this paper, we develop and apply a computationally efficient algorithm that enables us to calculate the complete probability distribution for the final epidemic size in a stochastic Susceptible-Infected-Recovered (SIR) model. Based on these results, we determine the optimal allocations of a limited quantity of vaccine between two non-interacting populations. We compare the stochastic solution to results obtained for the traditional, deterministic SIR model. For intermediate quantities of vaccine, the deterministic model is a poor estimate of the optimal strategy for the more realistic, stochastic case.Comment: 21 pages, 7 figure

Temperature-Aware Leakage Minimization Techniques for Real-Time Systems

In this paper, we study the interdependencies between system's leakage and on-chip temperature. We show that the temperature variation caused by on-chip heat accumulation has a large impact in estimating the system's leakage energy. More importantly, we propose an online temperature-aware leakage minimization technique to demonstrate how to incorporate the temperature information to reduce energy consumption at real time. The basic idea is to run when the system is cool and the workload is high and to put the system to sleep when it is hot and the workload is light. The online algorithm has low run-time complexity and achieves significant leakage energy saving. In fact, we are able to get about 25% leakage reduction on both real life and artificial benchmarks. Comparing to our optimal offline algorithm, the above online algorithm provides similar energy savings with similar decisions on how to put the system to sleep and how to wake it up. Finally, our temperature-aware leakage minimization techniques can be combined with existing DVS methods to improve the total energy efficiency by further saving on leakage

Web Spoofing Revisited: SSL and Beyond

Can users believe what their browsers tell them? Even sophisticated Web users decide whether or not to trust a server based on browser cues such as location bar information, SSL icons, SSL warnings, certificate information, and response time. In their seminal work on Web spoofing, Felten et al showed how, in 1996, a malicious server could forge some of these cues. However, this work used genuine SSL sessions, and Web technology has evolved much since 1996. The Web has since become the pre-eminent medium for electronic service delivery to remote users, and the security of many commerce, government, and academic network applications critically rests on the assumption that users can authenticate the servers with which they interact. This situation raises the question: is the browser-user communication model today secure enough to warrant this assumption? In this paper, we answer this question by systematically showing how a malicious server can forge every one of the above cues. Our work extends the prior results by examining contemporary browsers, and by forging all of the SSL information a client sees, including the very existence of an SSL session (thus providing a cautionary tale about the security of one of the most common applications of PKI). We have made these techniques available for public demonstration, because anything less than working code would not convincingly answer the question. We also discuss implications and potential countermeasures, both short-term and long-term

Web Spoofing 2001

The Web is currently the pre-eminent medium for electronic service delivery to remote users. As a consequence, authentication of servers is more important than ever. Even sophisticated users base their decision whether or not to trust a site on browser cues---such as location bar information, SSL icons, SSL warnings, certificate information, response time, etc. In their seminal work on web spoofing, Felten et al showed how a malicious server could forge some of these cues---but using approaches that are no longer reproducible. However, subsequent evolution of Web tools has not only patched security holes---it has also added new technology to make pages more interactive and vivid. In this paper, we explore the feasibility of web spoofing using this new technology---and we show how, in many cases, every one of the above cues can be forged. In particular, we show how a malicious server can forge all the SSL information a client sees---thus providing a cautionary tale about the security of one of the most common applications of PKI. We stress that these techniques have been implemented, and are available for public demonstration

The Aemulus Project III: Emulation of the Galaxy Correlation Function

Using the N-body simulations of the AEMULUS Project, we construct an emulator for the non-linear clustering of galaxies in real and redshift space. We construct our model of galaxy bias using the halo occupation framework, accounting for possible velocity bias. The model includes 15 parameters, including both cosmological and galaxy bias parameters. We demonstrate that our emulator achieves ~ 1% precision at the scales of interest, 0.1<r<10 h^{-1} Mpc, and recovers the true cosmology when tested against independent simulations. Our primary parameters of interest are related to the growth rate of structure, f, and its degenerate combination fsigma_8. Using this emulator, we show that the constraining power on these parameters monotonically increases as smaller scales are included in the analysis, all the way down to 0.1 h^{-1} Mpc. For a BOSS-like survey, the constraints on fsigma_8 from r<30 h^{-1} Mpc scales alone are more than a factor of two tighter than those from the fiducial BOSS analysis of redshift-space clustering using perturbation theory at larger scales. The combination of real- and redshift-space clustering allows us to break the degeneracy between f and sigma_8, yielding a 9% constraint on f alone for a BOSS-like analysis. The current AEMULUS simulations limit this model to surveys of massive galaxies. Future simulations will allow this framework to be extended to all galaxy target types, including emission-line galaxies.Comment: 14 pages, 8 figures, 1 table; submitted to ApJ; the project webpage is available at https://aemulusproject.github.io ; typo in Figure 7 and caption updated, results unchange

The Aemulus Project I: Numerical Simulations for Precision Cosmology

The rapidly growing statistical precision of galaxy surveys has lead to a need for ever-more precise predictions of the observables used to constrain cosmological and galaxy formation models. The primary avenue through which such predictions will be obtained is suites of numerical simulations. These simulations must span the relevant model parameter spaces, be large enough to obtain the precision demanded by upcoming data, and be thoroughly validated in order to ensure accuracy. In this paper we present one such suite of simulations, forming the basis for the AEMULUS Project, a collaboration devoted to precision emulation of galaxy survey observables. We have run a set of 75 (1.05 h^-1 Gpc)^3 simulations with mass resolution and force softening of 3.51\times 10^10 (Omega_m / 0.3) ~ h^-1 M_sun and 20 ~ h^-1 kpc respectively in 47 different wCDM cosmologies spanning the range of parameter space allowed by the combination of recent Cosmic Microwave Background, Baryon Acoustic Oscillation and Type Ia Supernovae results. We present convergence tests of several observables including spherical overdensity halo mass functions, galaxy projected correlation functions, galaxy clustering in redshift space, and matter and halo correlation functions and power spectra. We show that these statistics are converged to 1% (2%) for halos with more than 500 (200) particles respectively and scales of r>200 ~ h^-1 kpc in real space or k ~ 3 h Mpc^-1 in harmonic space for z\le 1. We find that the dominant source of uncertainty comes from varying the particle loading of the simulations. This leads to large systematic errors for statistics using halos with fewer than 200 particles and scales smaller than k ~ 4 h^-1 Mpc. We provide the halo catalogs and snapshots detailed in this work to the community at https://AemulusProject.github.io.Comment: 16 pages, 12 figures, 3 Tables Project website: https://aemulusproject.github.io

The Aemulus Project II: Emulating the Halo Mass Function

Existing models for the dependence of the halo mass function on cosmological parameters will become a limiting source of systematic uncertainty for cluster cosmology in the near future. We present a halo mass function emulator and demonstrate improved accuracy relative to state-of-the-art analytic models. In this work, mass is defined using an overdensity criteria of 200 relative to the mean background density. Our emulator is constructed from the AEMULUS simulations, a suite of 40 N-body simulations with snapshots from z=3 to z=0. These simulations cover the flat wCDM parameter space allowed by recent Cosmic Microwave Background, Baryon Acoustic Oscillation and Type Ia Supernovae results, varying the parameters w, Omega_m, Omega_b, sigma_8, N_{eff}, n_s, and H_0. We validate our emulator using five realizations of seven different cosmologies, for a total of 35 test simulations. These test simulations were not used in constructing the emulator, and were run with fully independent initial conditions. We use our test simulations to characterize the modeling uncertainty of the emulator, and introduce a novel way of marginalizing over the associated systematic uncertainty. We confirm non-universality in our halo mass function emulator as a function of both cosmological parameters and redshift. Our emulator achieves better than 1% precision over much of the relevant parameter space, and we demonstrate that the systematic uncertainty in our emulator will remain a negligible source of error for cluster abundance studies through at least the LSST Year 1 data set.Comment: https://aemulusproject.github.io

Prion propagation can occur in a prokaryote and requires the ClpB chaperone

Prions are self-propagating protein aggregates that are characteristically transmissible. In mammals, the PrP protein can form a prion that causes the fatal transmissible spongiform encephalopathies. Prions have also been uncovered in fungi, where they act as heritable, protein-based genetic elements. We previously showed that the yeast prion protein Sup35 can access the prion conformation in Escherichia coli. Here, we demonstrate that E. coli can propagate the Sup35 prion under conditions that do not permit its de novo formation. Furthermore, we show that propagation requires the disaggregase activity of the ClpB chaperone. Prion propagation in yeast requires Hsp104 (a ClpB ortholog), and prior studies have come to conflicting conclusions about ClpB's ability to participate in this process. Our demonstration of ClpB-dependent prion propagation in E. coli suggests that the cytoplasmic milieu in general and a molecular machine in particular are poised to support protein-based heredity in the bacterial domain of life. DOI: http://dx.doi.org/10.7554/eLife.02949.00