124 research outputs found

    ORGANIC AGRICULTURE IN ROMANIA - AN IMPORTANT RESOURCE OF QUALITY RAW MATERIALS FOR INNOVATIVE FOODS

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    Organic foods, functional foods, Food supplements are designed and built from organic agricultural raw materials and natural food additives. In the last ten years, in Romania, there has been a significant increase in ecologically certified areas, an increase in organic cereal crops, areas cultivated with green harvested plants and permanent crops (orchards, vines, fruit bushes). These increases facilitate the obtaining of foods with high nutritional density and an increased processing efficiency. All these are part of the Sustainable Development Strategy of Romania in the period 2020-2030, approved in EC

    An agenda for future Social Sciences and Humanities research on energy efficiency : 100 priority research questions

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    Decades of techno-economic energy policymaking and research have meant evidence from the Social Sciences and Humanities (SSH)-including critical reflections on what changing a society's relation to energy (efficiency) even means-have been underutilised. In particular, (i) the SSH have too often been sidelined and/or narrowly pigeonholed by policymakers, funders, and other decision-makers when driving research agendas, and (ii) the setting of SSH-focused research agendas has not historically embedded inclusive and deliberative processes. The aim of this paper is to address these gaps through the production of a research agenda outlining future SSH research priorities for energy efficiency. A Horizon Scanning exercise was run, which sought to identify 100 priority SSH questions for energy efficiency research. This exercise included 152 researchers with prior SSH expertise on energy efficiency, who together spanned 62 (sub-)disciplines of SSH, 23 countries, and a full range of career stages. The resultant questions were inductively clustered into seven themes as follows: (1) Citizenship, engagement and knowledge exchange in relation to energy efficiency; (2) Energy efficiency in relation to equity, justice, poverty and vulnerability; (3) Energy efficiency in relation to everyday life and practices of energy consumption and production; (4) Framing, defining and measuring energy efficiency; (5) Governance, policy and political issues around energy efficiency; (6) Roles of economic systems, supply chains and financial mechanisms in improving energy efficiency; and (7) The interactions, unintended consequences and rebound effects of energy efficiency interventions. Given the consistent centrality of energy efficiency in policy programmes, this paper highlights that well-developed SSH approaches are ready to be mobilised to contribute to the development, and/or to understand the implications, of energy efficiency measures and governance solutions. Implicitly, it also emphasises the heterogeneity of SSH policy evidence that can be produced. The agenda will be of use for both (1) those new to the energy-SSH field (including policyworkers), for learnings on the capabilities and capacities of energy-SSH, and (2) established energy-SSH researchers, for insights on the collectively held futures of energy-SSH research.Peer reviewe

    Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

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    A measurement of the cosmic-ray spectrum for energies exceeding 4×10184{\times}10^{18} eV is presented, which is based on the analysis of showers with zenith angles greater than 6060^{\circ} detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above 5.3×10185.3{\times}10^{18} eV, the "ankle", the flux can be described by a power law EγE^{-\gamma} with index γ=2.70±0.02(stat)±0.1(sys)\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)} followed by a smooth suppression region. For the energy (EsE_\text{s}) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find Es=(5.12±0.25(stat)1.2+1.0(sys))×1019E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19} eV.Comment: Replaced with published version. Added journal reference and DO

    Identification of Lynch syndrome risk variants in the Romanian population.

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    To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadTwo familial forms of colorectal cancer (CRC), Lynch syndrome (LS) and familial adenomatous polyposis (FAP), are caused by rare mutations in DNA mismatch repair genes (MLH1, MSH2, MSH6, PMS2) and the genes APC and MUTYH, respectively. No information is available on the presence of high-risk CRC mutations in the Romanian population. We performed whole-genome sequencing of 61 Romanian CRC cases with a family history of cancer and/or early onset of disease, focusing the analysis on candidate variants in the LS and FAP genes. The frequencies of all candidate variants were assessed in a cohort of 688 CRC cases and 4567 controls. Immunohistochemical (IHC) staining for MLH1, MSH2, MSH6, and PMS2 was performed on tumour tissue. We identified 11 candidate variants in 11 cases; six variants in MLH1, one in MSH6, one in PMS2, and three in APC. Combining information on the predicted impact of the variants on the proteins, IHC results and previous reports, we found three novel pathogenic variants (MLH1:p.Lys84ThrfsTer4, MLH1:p.Ala586CysfsTer7, PMS2:p.Arg211ThrfsTer38), and two novel variants that are unlikely to be pathogenic. Also, we confirmed three previously published pathogenic LS variants and suggest to reclassify a previously reported variant of uncertain significance to pathogenic (MLH1:c.1559-1G>C).European Union EE

    The second knee in the cosmic ray spectrum observed with the surface detector of the Pierre Auger Observatory

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    Event-by-event reconstruction of the shower maximum XmaxX_{\mathrm{max}} with the Surface Detector of the Pierre Auger Observatory using deep learning

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