849 research outputs found

    Assessing overall network structure in regional innovation policies: a case study of cluster policy in the West Midlands in the UK

    Get PDF
    Revisiting the theoretical roots of the key concepts of “embeddedness” and “networks” that underpin many recent regional innovation polices, this paper strives to achieve a more systematic understanding of the overall network structure of geographic agglomerations, which helps to form a more convincing model of regional development based on learning. This also helps to establish an analytical framework with indicators to assess the overall network structure in regional innovation policies. Employing the framework, the examination of cluster policy in the West Midlands highlights its weakness in addressing the overall cluster network structure and the contingent factors influencing the structure. The analysis suggests that there may be similar weaknesses in other regional innovation policies and the theories underpinning them as they share a common weakness in addressing the structural characteristics of overall networks

    Privacy Amplification via Shuffling: Unified, Simplified, and Tightened

    Full text link
    In decentralized settings, the shuffle model of differential privacy has emerged as a promising alternative to the classical local model. Analyzing privacy amplification via shuffling is a critical component in both single-message and multi-message shuffle protocols. However, current methods used in these two areas are distinct and specific, making them less convenient for protocol designers and practitioners. In this work, we introduce variation-ratio reduction as a unified framework for privacy amplification analyses in the shuffle model. This framework utilizes total variation bounds of local messages and probability ratio bounds of other users' blanket messages, converting them to indistinguishable levels. Our results indicate that the framework yields tighter bounds for both single-message and multi-message encoders (e.g., with local DP, local metric DP, or general multi-message randomizers). Specifically, for a broad range of local randomizers having extremal probability design, our amplification bounds are precisely tight. We also demonstrate that variation-ratio reduction is well-suited for parallel composition in the shuffle model and results in stricter privacy accounting for common sampling-based local randomizers. Our experimental findings show that, compared to existing amplification bounds, our numerical amplification bounds can save up to 30%30\% of the budget for single-message protocols, 75%75\% of the budget for multi-message protocols, and 75%75\%-95%95\% of the budget for parallel composition. Additionally, our implementation for numerical amplification bounds has only O~(n)\tilde{O}(n) complexity and is highly efficient in practice, taking just 22 minutes for n=108n=10^8 users. The code for our implementation can be found at \url{https://github.com/wangsw/PrivacyAmplification}.Comment: Code available at https://github.com/wangsw/PrivacyAmplificatio

    Thermal-bioconvection in a non-scattering suspension of phototactic microorganisms

    Full text link
    This article investigates the linear stability of thermal-bioconvection within a suspension containing phototactic microorganisms heated from below. In suspension, the upper surface is taken as stress-free, while the lower surface is taken as rigid. The resulting eigenvalue problem, including the bioconvection Rayleigh and thermal Rayleigh numbers, is resolved numerically. Changes in the critical total intensity and Lewis number do not impact the critical threshold of the thermal Rayleigh number; however, they notably influence the critical bioconvection Rayleigh number. The critical total intensity and Lewis number destabilize the suspension. It is observed that heating from below enhances the instability of the layer. At higher temperatures, Rayleigh-Beˊ\acute{e}nard convection dominates bioconvection, resulting in a single convection cell
    • 

    corecore