Reducing Interconnect Cost in NoC through Serialized Asynchronous Links

This work investigates the application of serialization as a means of reducing the number of wires in NoC combined with asynchronous links in order to simplify the clocking of the link. Throughput is reduced but savings in routing area and reduction in power could make this attractiv

Parameterized thermal macromodeling for fast and effective design of electronic components and systems

We present a parameterized macromodeling approach to perform fast and effective dynamic thermal simulations of electronic components and systems where key design parameters vary. A decomposition of the frequency-domain data samples of the thermal impedance matrix is proposed to improve the accuracy of the model and reduce the number of the computationally costly thermal simulations needed to build the macromodel. The methodology is successfully applied to analyze the impact of layout variations on the dynamic thermal behavior of a state-of-the-art 8-finger AlGaN/GaN HEMT grown on a SiC substrate

A New, Atypical Case of Cobalamin F Disorder Diagnosed by Whole Exome Sequencing

The Deciphering Developmental Disorders Study presents independent research commissioned by the Health Innovation Challenge Fund (HICF-1009-003), a parallel funding partnership between the Wellcome Trust and the Department of Health, and the Wellcome Trust Sanger Institute (WT098051). The views expressed in this publication are those of the author(s) and not necessarily those of the Wellcome Trust or the Department of Health. The research team acknowledges the support of the National Institute for Health Research, through the Comprehensive Clinical Research Network.Peer reviewedPublisher PD

The KSTE+I approach and the AI technologies:Evidence from the European regions

In this paper we integrate the insights of the Knowledge Spillover Theory of Entrepreneurship and Innovation (KSTE+I) with Schumpeter's idea that innovative entrepreneurs creatively apply available local knowledge, possibly mediated by Marshallian, Jacobian and Porter spillovers. In more detail, in this study we assess the degree of pervasiveness and the level of opportunities brought about by AI technologies by testing the possible correlation between the regional AI knowledge stock and the number of new innovative ventures (that is startups patenting in any technological field in the year of their foundation).Empirically, by focusing on 287 Nuts-2 European regions, we test whether the local AI stock of knowledge exerts an enabling role in fostering innovative entry within AI-related local industries (AI technologies as focused enablers) and within non AI-related local industries, as well (AI technologies as generalised enablers).Results from Negative Binomial fixed-effect and Poisson fixed-effect regressions (controlled for a variety of concurrent drivers of entrepreneurship) reveal that the local AI knowledge stock does promote the spread of innovative startups, so supporting both the KSTE+I approach and the enabling role of AI technologies; however, this relationship is confirmed only with regard to the sole high-tech/AI-related industries.<br/

The KSTE+I approach and the AI technologies:Evidence from the European regions

In this paper we integrate the insights of the Knowledge Spillover Theory of Entrepreneurship and Innovation (KSTE+I) with Schumpeter's idea that innovative entrepreneurs creatively apply available local knowledge, possibly mediated by Marshallian, Jacobian and Porter spillovers. In more detail, in this study we assess the degree of pervasiveness and the level of opportunities brought about by AI technologies by testing the possible correlation between the regional AI knowledge stock and the number of new innovative ventures (that is startups patenting in any technological field in the year of their foundation).Empirically, by focusing on 287 Nuts-2 European regions, we test whether the local AI stock of knowledge exerts an enabling role in fostering innovative entry within AI-related local industries (AI technologies as focused enablers) and within non AI-related local industries, as well (AI technologies as generalised enablers).Results from Negative Binomial fixed-effect and Poisson fixed-effect regressions (controlled for a variety of concurrent drivers of entrepreneurship) reveal that the local AI knowledge stock does promote the spread of innovative startups, so supporting both the KSTE+I approach and the enabling role of AI technologies; however, this relationship is confirmed only with regard to the sole high-tech/AI-related industries.<br/

Genomic analysis of Listeria monocytogenes diversity over a 10-year period in Uruguay

Listeria monocytogenes is a globally relevant foodborne pathogen and a major public health concern because of its ability to cause severe invasive disease and persist in food processing environments. This study aimed to characterize the genomic diversity of L. monocytogenes isolates collected in Uruguay from food and clinical cases of listeriosis between 2010 and 2019. The genomes sequences of 142 isolates representatives from a national collection were obtained and used for comparative genomic and phylogenetic analysis along with other 55 genomes from different geographical regions. The isolates belonged to lineages I (88%) and II (12%) and were distributed across 20 clonal complexes. The clonal complexes CC3, CC2, and CC1 were predominant. Notably, CC3 accounted for nearly one-third of the isolates and was evenly distributed between food and clinical sources, contrasting with its relatively low frequency in most international datasets. A novel sequence type (ST2832) and 112 new core genome MLST profiles were identified. The circulation of the rare clonal complex CC517 was detected, with evidence of persistence in food environments and a potential link to a human case. Comparative analysis revealed considerable virulence gene diversity, including specific distribution of LIPI-3 and LIPI-4 among lineages and clonal complexes, and the presence of truncated allelic variants of the inlA gene in food-derived lineage II isolates. Phylogenetic analysis showed strong concordance with MLST-based classification and reveals linkage among isolates form different sources suggesting epidemiological relation between food and human cases of listeriosis. This study provides the first comprehensive genomic overview of L. monocytogenes in Uruguay, revealing the predominance of lineage I isolates from food and clinical sources, a particular high prevalence of CC3 and the local circulation of the rare CC517. The results highlight the importance of whole genome and phylogenetic analysis as molecular epidemiology tools and show the contribution of including isolates from underrepresented regions in global genomic databases

Safety, immunogenicity, and efficacy of a COVID-19 vaccine (NVX-CoV2373) co-administered with seasonal influenza vaccines: an exploratory substudy of a randomised, observer-blinded, placebo-controlled, phase 3 trial

Background: Safety and immunogenicity of COVID-19 vaccines when co-administered with influenza vaccines have not yet been reported. Methods: A sub-study on influenza vaccine co-administration was conducted as part of the phase 3 randomised trial of NVX-CoV2373’s safety and efficacy; ~400 participants meeting main study entry criteria, with no contraindications to influenza vaccination, were enroled. After randomisation to receive NVX-CoV2373 or placebo, sub-study participants received an open-label influenza vaccine at the same time as the first dose of NVX-CoV2373. Reactogenicity was evaluated for 7 days post-vaccination plus monitoring for unsolicited adverse events (AEs), medically-attended AEs (MAAEs), and serious AEs (SAEs). Vaccine efficacy against COVID-19 was assessed. Findings: Sub-study participants were younger (median age 39; 6.7 % ≥65 years), more racially diverse, and had fewer comorbid conditions than main study participants. Reactogenicity events more common in co-administration group included tenderness (70.1% vs 57.6%) or pain (39.7% vs 29.3%) at injection site, fatigue (27.7% vs 19.4%), and muscle pain (28.3% vs 21.4%). Rates of unsolicited AEs, MAAEs, and SAEs were low and balanced between the two groups. Co-administration resulted in no change to influenza vaccine immune response, while a reduction in antibody responses to the NVX-CoV2373 vaccine was noted. Vaccine efficacy against COVID-19 was 87.5% (95% CI: -0.2, 98.4) in those 18-<65 years in the sub-study while efficacy in the main study was 89.8% (95% CI: 79.7, 95.5).  Interpretation: This is the first study to demonstrate safety, immunogenicity, and efficacy of a COVID-19 vaccine when co-administered with influenza vaccines

The KSTE+I approach and the AI technologies: Evidence from the European regions

In this paper we integrate the insights of the Knowledge Spillover Theory of Entrepreneurship and Innovation (KSTE+I) with Schumpeter's idea that innovative entrepreneurs creatively apply available local knowledge, possibly mediated by Marshallian, Jacobian and Porter spillovers. In more detail, in this study we assess the degree of pervasiveness and the level of opportunities brought about by AI technologies by testing the possible correlation between the regional AI knowledge stock and the number of new innovative ventures (that is startups patenting in any technological field in the year of their foundation). Empirically, by focusing on 287 Nuts-2 European regions, we test whether the local AI stock of knowledge exerts an enabling role in fostering innovative entry within AI-related local industries (AI technologies as focused enablers) and within non AI-related local industries, as well (AI technologies as generalised enablers). Results from Negative Binomial fixed-effect and Poisson fixed-effect regressions (controlled for a variety of concurrent drivers of entrepreneurship) reveal that the local AI knowledge stock does promote the spread of innovative startups, so supporting both the KSTE+I approach and the enabling role of AI technologies; however, this relationship is confirmed only with regard to the sole high-tech/AI-related industries