172,480 research outputs found

    Epidemiological and economic impact of pandemic influenza in Chicago: Priorities for vaccine interventions.

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    The study objective is to estimate the epidemiological and economic impact of vaccine interventions during influenza pandemics in Chicago, and assist in vaccine intervention priorities. Scenarios of delay in vaccine introduction with limited vaccine efficacy and limited supplies are not unlikely in future influenza pandemics, as in the 2009 H1N1 influenza pandemic. We simulated influenza pandemics in Chicago using agent-based transmission dynamic modeling. Population was distributed among high-risk and non-high risk among 0-19, 20-64 and 65+ years subpopulations. Different attack rate scenarios for catastrophic (30.15%), strong (21.96%), and moderate (11.73%) influenza pandemics were compared against vaccine intervention scenarios, at 40% coverage, 40% efficacy, and unit cost of $28.62. Sensitivity analysis for vaccine compliance, vaccine efficacy and vaccine start date was also conducted. Vaccine prioritization criteria include risk of death, total deaths, net benefits, and return on investment. The risk of death is the highest among the high-risk 65+ years subpopulation in the catastrophic influenza pandemic, and highest among the high-risk 0-19 years subpopulation in the strong and moderate influenza pandemics. The proportion of total deaths and net benefits are the highest among the high-risk 20-64 years subpopulation in the catastrophic, strong and moderate influenza pandemics. The return on investment is the highest in the high-risk 0-19 years subpopulation in the catastrophic, strong and moderate influenza pandemics. Based on risk of death and return on investment, high-risk groups of the three age group subpopulations can be prioritized for vaccination, and the vaccine interventions are cost saving for all age and risk groups. The attack rates among the children are higher than among the adults and seniors in the catastrophic, strong, and moderate influenza pandemic scenarios, due to their larger social contact network and homophilous interactions in school. Based on return on investment and higher attack rates among children, we recommend prioritizing children (0-19 years) and seniors (65+ years) after high-risk groups for influenza vaccination during times of limited vaccine supplies. Based on risk of death, we recommend prioritizing seniors (65+ years) after high-risk groups for influenza vaccination during times of limited vaccine supplies

    Orion Aerodynamics for Hypersonic Free Molecular to Continuum Conditions

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    Numerical simulations are performed for the Orion Crew Module, previously known as the Crew Exploration Vehicle (CEV) Command Module, to characterize its aerodynamics during the high altitude portion of its reentry into the Earth's atmosphere, that is, from free molecular to continuum hypersonic conditions. The focus is on flow conditions similar to those that the Orion Crew Module would experience during a return from the International Space Station. The bulk of the calculations are performed with two direct simulation Monte Carlo (DSMC) codes, and these data are anchored with results from both free molecular and Navier-Stokes calculations. Results for aerodynamic forces and moments are presented that demonstrate their sensitivity to rarefaction, that is, for free molecular to continuum conditions (Knudsen numbers of 111 to 0.0003). Also included are aerodynamic data as a function of angle of attack for different levels of rarefaction and results that demonstrate the aerodynamic sensitivity of the Orion CM to a range of reentry velocities (7.6 to 15 km/s)

    Breaking a chaos-noise-based secure communication scheme

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    This paper studies the security of a secure communication scheme based on two discrete-time intermittently-chaotic systems synchronized via a common random driving signal. Some security defects of the scheme are revealed: 1) the key space can be remarkably reduced; 2) the decryption is insensitive to the mismatch of the secret key; 3) the key-generation process is insecure against known/chosen-plaintext attacks. The first two defects mean that the scheme is not secure enough against brute-force attacks, and the third one means that an attacker can easily break the cryptosystem by approximately estimating the secret key once he has a chance to access a fragment of the generated keystream. Yet it remains to be clarified if intermittent chaos could be used for designing secure chaotic cryptosystems.Comment: RevTeX4, 11 pages, 15 figure

    Dynamic Information Flow Tracking on Multicores

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    Dynamic Information Flow Tracking (DIFT) is a promising technique for detecting software attacks. Due to the computationally intensive nature of the technique, prior efficient implementations [21, 6] rely on specialized hardware support whose only purpose is to enable DIFT. Alternatively, prior software implementations are either too slow [17, 15] resulting in execution time increases as much as four fold for SPEC integer programs or they are not transparent [31] requiring source code modifications. In this paper, we propose the use of chip multiprocessors (CMP) to perform DIFT transparently and efficiently. We spawn a helper thread that is scheduled on a separate core and is only responsible for performing information flow tracking operations. This entails the communication of registers and flags between the main and helper threads. We explore software (shared memory) and hardware (dedicated interconnect) approaches to enable this communication. Finally, we propose a novel application of the DIFT infrastructure where, in addition to the detection of the software attack, DIFT assists in the process of identifying the cause of the bug in the code that enabled the exploit in the first place. We conducted detailed simulations to evaluate the overhead for performing DIFT and found that to be 48 % for SPEC integer programs

    CopyCAT: Taking Control of Neural Policies with Constant Attacks

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    We propose a new perspective on adversarial attacks against deep reinforcement learning agents. Our main contribution is CopyCAT, a targeted attack able to consistently lure an agent into following an outsider's policy. It is pre-computed, therefore fast inferred, and could thus be usable in a real-time scenario. We show its effectiveness on Atari 2600 games in the novel read-only setting. In this setting, the adversary cannot directly modify the agent's state -- its representation of the environment -- but can only attack the agent's observation -- its perception of the environment. Directly modifying the agent's state would require a write-access to the agent's inner workings and we argue that this assumption is too strong in realistic settings.Comment: AAMAS 202
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