Analysis of Regional Innovation Performance in Portugal - Results from an External Logistic Biplot Method

Portuguese strategic choices regarding innovation and R&D policy have, over the past two decades, produced various positive achievements, in which the regions of Lisbon and Algarve have taken the lead, and are the only ones in the country to converge towards the European average growth rate. Regarding the other Portuguese regions – despite significant national growth rates in the 1990s as well as a successful attempt to cope with the EMU –, these are lagging behind the EU average with respect to gross production, investment or employment generation. Meanwhile, one of the greatest public policy efforts was to diffuse much of the European funds across the entrepreneurial sector. After a long pathway, it is now timely to evaluate the firms‟ contribution to national and regional growth, their obstacles and impacts. For the purpose of this paper, innovation is used here as a major contributor to the policy evaluation process referred to above. Our investigation aims to explain the present performance of Portuguese firms located throughout the country and to explore those innovation determinants that have a region-specific connotation. To provide a thorough investigation, our analysis defines, on a regional basis, a set of firms‟ behavioural patterns regarding innovation. In our modelling, we employ a new methodology, viz. the External Logistic Biplot method, which is applied to an extensive sample of innovative institutions in Portugal. Variables such as „Promoting knowledge‟, „Management skills‟, „Promoting R&D‟, „Knowledge transfer‟, „Promoting partnership & cooperation‟, and „Orientation of public measures‟ have been identified as crucial determinants in earlier studies and are now used to describe regional institutional profiles. Such profiles exhibit a great variety in the way they combine these determinants to promote regional innovation. The creation of a gradient of capacity to dynamically innovate associated with each firm makes it possible to analyse the innovation gradient of each region in Portugal. Our paper presents and systematically investigates these findings and then reaches some policy conclusions.PTDC/CS-GEO/102961/200

Multitasking in the rural world: Technological change and sustainability

The rural world offers a heterogeneous picture caused by a rich past and varied responses to a diversity of socio-economic, demographic and political challenges. The present paper aims to trace new opportunities for rurality in the context of a metamorphosis of current production and consumption systems. Addressing issues like diversification, local competition or networking, rural firms are adapting to new conditions by segmenting and moving towards less concentrated forms, in an attempt to integrate the marketing of non-market commodities as the most adequate strategies for consumers. Such strategies that presuppose skills based on a specific know-how and technological improvements also oblige locals to enhance their knowledge basis and learning capacities, thereby facilitating a more environmentally sustainable production model that simultaneously stimulates balanced development. The case of biotechnology in the region of Andalusia (Spain) was used as an illustration to map out the above complex force field. The rural world suggests a new paradigm in which social participation is more needed and local and regional actors are encouraged to find meaningful compromises for the sustainable governance of natural resources and the advancement of social learning

Modelling innovation support systems for regional development - analysis of cluster structures in innovation in Portugal

The present article offers a concise theoretical conceptualization and operational analysis of the contribution of innovation to regional development. The latter concepts are closely related to geographical proximity, knowledge diffusion and filters and clustering. Institutional innovation profiles and regional patterns of innovation are two mutually linked, novel conceptual elements in this article. Next to a theoretical framing, the article employs the regional innovation systems concept as a vehicle to analyse institutional innovation profiles. Our case study addresses three Portuguese regions and their institutions, included in a web-based inventory of innovation agencies which offered the foundation for an extensive database. This data-set was analysed by means of a recently developed principal coordinates analysis followed by a Logistic Biplot approach (leading to a Voronoi mapping) to design a systemic typology of innovation structures where each institution is individually represented. There appears to be a significant difference in the regional innovation patterns resulting from the diverse institutional innovation profiles concerned. These profiles appear to be region specific. Our conclusion highlights the main advantages in the use of the method used for policy-makers and business companies.info:eu-repo/semantics/publishedVersio

Development of an automatic identification algorithm for antibiogram analysis

Routinely, diagnostic and microbiology laboratories perform antibiogram analysis which can present some difficulties leading to misreadings and intra and inter-reader deviations. An Automatic Identification Algorithm (AIA) has been proposed as a solution to overcome some issues associated with the disc diffusion method, which is the main goal of this work. AIA allows automatic scanning of inhibition zones obtained by antibiograms. More than 60 environmental isolates were tested using susceptibility tests which were performed for 12 different antibiotics for a total of 756 readings. Plate images were acquired and classified as standard or oddity. The inhibition zones were measured using the AIA and results were compared with reference method (human reading), using weighted kappa index and statistical analysis to evaluate, respectively, inter-reader agreement and correlation between AIA-based and human-based reading. Agreements were observed in 88% cases and 89% of the tests showed no difference or a o4 mm difference between AIA and human analysis, exhibiting a correlation index of 0.85 for all images, 0.90 for standards and 0.80 for oddities with no significant difference between automatic and manual method. AIA resolved some reading problems such as overlapping inhibition zones, imperfect microorganism seeding, non-homogeneity of the circumference, partial action of the antimicrobial, and formation of a second halo of inhibition. Furthermore, AIA proved to overcome some of the limitations observed in other automatic methods. Therefore, AIA may be a practical tool for automated reading of antibiograms in diagnostic and microbiology laboratoriesinfo:eu-repo/semantics/acceptedVersio

Profiling of lung SARS-CoV-2 and influenza virus infection dissects virus-specific host responses and gene signatures

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which emerged in late 2019 has spread globally, causing a pandemic of respiratory illness designated coronavirus disease 2019 (COVID-19). A better definition of the pulmonary host response to SARS-CoV-2 infection is required to understand viral pathogenesis and to validate putative COVID-19 biomarkers that have been proposed in clinical studies. METHODS: Here, we use targeted transcriptomics of formalin-fixed paraffin-embedded tissue using the NanoString GeoMX platform to generate an in-depth picture of the pulmonary transcriptional landscape of COVID-19, pandemic H1N1 influenza and uninfected control patients. RESULTS: Host transcriptomics showed a significant upregulation of genes associated with inflammation, type I interferon production, coagulation and angiogenesis in the lungs of COVID-19 patients compared to non-infected controls. SARS-CoV-2 was non-uniformly distributed in lungs (emphasising the advantages of spatial transcriptomics) with the areas of high viral load associated with an increased type I interferon response. Once the dominant cell type present in the sample, within patient correlations and patient-patient variation, had been controlled for, only a very limited number of genes were differentially expressed between the lungs of fatal influenza and COVID-19 patients. Strikingly, the interferon-associated gene IFI27, previously identified as a useful blood biomarker to differentiate bacterial and viral lung infections, was significantly upregulated in the lungs of COVID-19 patients compared to patients with influenza. CONCLUSION: Collectively, these data demonstrate that spatial transcriptomics is a powerful tool to identify novel gene signatures within tissues, offering new insights into the pathogenesis of SARS-COV-2 to aid in patient triage and treatment.Arutha Kulasinghe, Chin Wee Tan, Anna Flavia Ribeiro dos Santos Miggiolaro, James Monkman, Habib SadeghiRad, Dharmesh D. Bhuva, Jarbas da Silva Motta Junior, Caroline Busatta Vaz de Paula, Seigo Nagashima, Cristina Pellegrino Baena, Paulo Souza-Fonseca-Guimaraes, Lucia de Noronha, Timothy McCulloch, Gustavo Rodrigues Rossi, Caroline Cooper, Benjamin Tang, Kirsty R. Short, Melissa J. Davis, Fernando Souza-Fonseca-Guimaraes, Gabrielle T. Belz, and Ken O, Byrn