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

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

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 $30\%$ of the budget for single-message protocols, $75\%$ of the budget for multi-message protocols, and $75\%$-$95\%$ of the budget for parallel composition. Additionally, our implementation for numerical amplification bounds has only $\tilde{O}(n)$ complexity and is highly efficient in practice, taking just $2$ minutes for $n=10^8$ 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

Poly(oxime-ester) Vitrimers with Catalyst-Free Bond Exchange.

Vitrimers are network polymers that undergo associative bond exchange reactions in the condensed phase above a threshold temperature, dictated by the exchangeable bonds comprising the vitrimer. For vitrimers, chemistries reliant on poorly nucleophilic bond exchange partners (e.g., hydroxy-functionalized alkanes) or poorly electrophilic exchangeable bonds, catalysts are required to lower the threshold temperature, which is undesirable in that catalyst leaching or deactivation diminishes its influence over time and may compromise reuse. Here we show how to access catalyst-free bond exchange reactions in catalyst-dependent polyester vitrimers by obviating conventional ester bonds in favor of oxime-esters. Poly(oxime-ester) (POE) vitrimers are synthesized using thiol-ene click chemistry, affording high stretchability and malleability. POE vitrimers are readily recycled with little degradation of their initial mechanical properties, suggesting exciting opportunities for sustainable plastics

Effects of dietary compound acidifiers supplementation on growth performance and intestinal health of juvenile American eels (Anguilla rostrata) cultured in cement tanks

This experiment was conducted to investigate the effects of compound acidifiers (CAs) on the growth performance and intestinal health of juvenile American eels (Anguilla rostrata) cultured in cement tanks. Six cement tanks with similar fish size and weight (approximately 4 g/fish and 87 kg/tank) were randomly divided into control group and CAs group with three replicates each. The fish of two groups were fed commercial diet and commercial diet supplemented with 4 g/kg CAs, respectively. The trial period was 56 days. The dietary CAs supplementation significantly increased final fish weight, weight gain rate, specific growth rate and feed intake (P0.05). Protease activity in intestine was increased significantly by CAs supplementation (P0.05). CAs supplementation significantly increased the villi length and thickness of the intestinal muscular layer (P<0.05). Dietary CAs supplementation increased the richness and the diversity of intestinal microbiota. At the phylum level, the higher relative abundances of Proteobacteria, Actinobacteria and Bacteroidetes and the lower relative abundance of Firmicutes were observed in CAs group compared to the control group. At the genus level, dietary CAs supplementation significantly increased the relative abundances of Faecalitalea, Sphingomonas, Sutterella and Mycobacterium (P<0.05). In conclusion, the dietary 4 g/kg CAs supplementation might improve the growth performance and intestinal health of juvenile American eels cultured in cement tanks