5 results on '"Belter, Bartosz"'
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2. D1.1: Technological status and capabilities of existing ICT Research Infrastructures
- Author
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Belter, Bartosz
- Abstract
Digital Infrastructures and the future Internet including 5G and beyond technologies are the main enabling factors contributing to the digital transformation of our society. The COVID-19 crisis has demonstrated the vital role of digital infrastructures and showed they should be reinforced. Their design, deployment and operation are critical, calling for a scientific instrument to support the research in this domain for computer science and infrastructure researchers, as well as for data driven scientific applications involving interdisciplinary aspects. This report summarizes the analysis of the current technological status and capabilities of existing ICT Research Infrastructures in Europe as it stands for the beginning of 2021. The analysis has been performed by the authors and reflects the knowledge gathered and processed by the authors using public documentation (e.g., available on the projects’ websites) and through personal communication between sources of information in particular Member States. This report does not intend to replace and override documentation prepared by larger communities and organizations (e.g., the European Commission, ESFRI or e-IRG). Instead, this report complements existing efforts made so far with a primary focus on ICT technologies related to SLICES and with new information received from Member States, not necessarily already included in above mentioned state-of-the-art reports. This report has been prepared by SLICES-DS Partners with support and advice from the following organisations: Poznan Supercomputing and Networking Center (Poland), Sorbonne University (France), INRIA (France), MTA Sztaki (Hungary), Technical University of Munich (Germany), UPV/EHU (Spain), UC3M (Spain), UCLAN (Cyprus), Université Du Luxembourg (Luxembourg), SIMULA (Norway), CNR (Italy), Mandat International (Switzerland), KTH (Sweden), University of Gent (Belgium) and RNP (Brazil). The document is intended at ESFRI stakeholders, policy makers, researchers and RI managers.
- Published
- 2022
- Full Text
- View/download PDF
3. A GWAS study highlights significant associations between a series of indels in a FLOWERING LOCUS T gene promoter and flowering time in white lupin (Lupinus albus L.).
- Author
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Rychel-Bielska, Sandra, Bielski, Wojciech, Surma, Anna, Annicchiarico, Paolo, Belter, Jolanta, Kozak, Bartosz, Galek, Renata, Harzic, Nathalie, and Książkiewicz, Michał
- Subjects
FLOWERING time ,LUPINUS albus ,LOCUS (Genetics) ,CLIMATE change adaptation ,GENOME-wide association studies ,LEGUMES - Abstract
Background: White lupin (Lupinus albus L.) is a high-protein Old World grain legume with remarkable food and feed production interest. It is sown in autumn or early spring, depending on the local agroclimatic conditions. This study aimed to identify allelic variants associated with vernalization responsiveness, in order to improve our knowledge of legume flowering regulatory pathways and develop molecular selection tools for the desired phenology as required for current breeding and adaptation to the changing climate. Results: Some 120 white lupin accessions originating from a wide range of environments of Europe, Africa, and Asia were phenotyped under field conditions in three environments with different intensities of vernalization, namely, a Mediterranean and a subcontinental climate sites of Italy under autumn sowing, and a suboceanic climate site of France under spring sowing. Two hundred sixty-two individual genotypes extracted from them were phenotyped in a greenhouse under long-day photoperiod without vernalization. Phenology data, and marker data generated by Diversity Arrays Technology sequencing (DArT-seq) and by PCR-based screening targeting published quantitative trait loci (QTLs) from linkage map and newly identified insertion/deletion polymorphisms in the promoter region of the FLOWERING LOCUS T homolog, LalbFTc1 gene (Lalb_Chr14g0364281), were subjected to a genome-wide association study (GWAS). Population structure followed differences in phenology and isolation by distance pattern. The GWAS highlighted numerous loci significantly associated with flowering time, including four LalbFTc1 gene promoter deletions: 2388 bp and 2126 bp deletions at the 5' end, a 264 bp deletion in the middle and a 28 bp deletion at the 3' end of the promoter. Besides LalbFTc1 deletions, this set contained DArT-seq markers that matched previously published major QTLs in chromosomes Lalb_Chr02, Lalb_Chr13 and Lalb_Chr16, and newly discovered QTLs in other chromosomes. Conclusions: This study highlighted novel QTLs for flowering time and validated those already published, thereby providing novel evidence on the convergence of FTc1 gene functional evolution into the vernalization pathway in Old World lupin species. Moreover, this research provided the set of loci specific for extreme phenotypes (the earliest or the latest) awaiting further implementation in marker-assisted selection for spring- or winter sowing. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
4. SLICES, a scientific instrument for the networking community
- Abstract
A science is defined by a set of encyclopedic knowledge related to facts or phenomena following rules or evidenced by experimentally-driven observations. Computer Science and in particular computer networks is a relatively new scientific domain maturing over years and adopting the best practices inherited from more fundamental disciplines. The design of past, present and future networking components and architectures have been assisted, among other methods, by experimentally-driven research and in particular by the deployment of test platforms, usually named as testbeds. However, often experimentally-driven networking research used scattered methodologies, based on ad-hoc, small-sized testbeds, producing hardly repeatable results. We believe that computer networks needs to adopt a more structured methodology, supported by appropriate instruments, to produce credible experimental results supporting radical and incremental innovations. This paper reports lessons learned from the design and operation of test platforms for the scientific community dealing with digital infrastructures. We introduce the SLICES initiative as the outcome of several years of evolution of the concept of a networking test platform transformed into a scientific instrument. We address the challenges, requirements and opportunities that our community is facing to manage the full research-life cycle necessary to support a scientific methodology.
- Published
- 2022
5. SLICES, a scientific instrument for the networking community
- Abstract
A science is defined by a set of encyclopedic knowledge related to facts or phenomena following rules or evidenced by experimentally-driven observations. Computer Science and in particular computer networks is a relatively new scientific domain maturing over years and adopting the best practices inherited from more fundamental disciplines. The design of past, present and future networking components and architectures have been assisted, among other methods, by experimentally-driven research and in particular by the deployment of test platforms, usually named as testbeds. However, often experimentally-driven networking research used scattered methodologies, based on ad-hoc, small-sized testbeds, producing hardly repeatable results. We believe that computer networks needs to adopt a more structured methodology, supported by appropriate instruments, to produce credible experimental results supporting radical and incremental innovations. This paper reports lessons learned from the design and operation of test platforms for the scientific community dealing with digital infrastructures. We introduce the SLICES initiative as the outcome of several years of evolution of the concept of a networking test platform transformed into a scientific instrument. We address the challenges, requirements and opportunities that our community is facing to manage the full research-life cycle necessary to support a scientific methodology.
- Published
- 2022
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