Axion searches at CERN with the CAST Telescope

The CERN Axion Solar Telescope (CAST) searches for axions coming from photon to axion conversion in the sun's core, as stated by the Primakoff effect. Axions arise in particle physics as a consequence of the breaking of Peccei-Quinn symmetry which has been introduced as a solution to the strong CP problem. As cosmological axions they are candidates for at least some part of cold Dark Matter.They are also expected to be produced copiously in stellar interiors with energies as high as the thermal photons undergoing photon to axion conversion. In our sun the axion energy spectrum peaks at about 4.4 keV, extending up to 10 keV. CAST collected preliminary data in 2002 and data taking with its full capability will start in the beginning of 2003.Comment: NEB-X Conference on "New Developments in Gravity", May 30-June 2, 2002, Chalkidiki, GREECE. 5 pages, 2 figure

Low energy recoil detection with a spherical proportional counter

We present low energy recoil detection results in the keV energy region, from measurements performed with the Spherical Proportional Counter (SPC). An ${}^{241}Am-{}^{9}{Be}$ fast neutron source is used in order to obtain neutron-nucleus elastic scattering events inside the gaseous volume of the detector. The detector performance in the $keV$ energy region was resolved by observing the $5.9\ keV$ line of a ${}^{55}Fe$ X-ray source, with energy resolution of $9\%$ ($\sigma$). The toolkit GEANT4 was used to simulate the irradiation of the detector by an ${}^{241}Am-{}^{9}{Be}$ source, while SRIM was used to calculate the Ionization Quenching Factor (IQF). The GEANT4 simulated energy deposition spectrum in addition with the SRIM calculated quenching factor provide valuable insight to the experimental results. The performance of the SPC in low energy recoil detection makes the detector a good candidate for a wide range of applications, including Supernova or reactor neutrino detection and Dark Matter (WIMP) searches (via coherent elastic scattering).Comment: 16 pages, 16 figures, preprin

Using the Process Digital Twin as a tool for companies to evaluate the Return on Investment of manufacturing automation

The fourth industrial revolution is gaining momentum, but still lacks full realization. Several studies suggest that many companies around the world have begun the digital transformation undertaking, but most are still far from full adoption and yet fail to see the full economic potential, being stuck in what has been called "pilot purgatory”. Digitalization is largely recognized as an accelerator and enabler for full automation in manufacturing, but companies are still struggling to assess the return on investment and the impact on operational performance indicators. Therefore, companies, especially SMEs characterized by dynamic, high-value, high-mix, and low-volume contexts, are reluctant to invest further. By incorporating simulation, data analytics and behavioral models, digital twins may also be used to support automation solutions ramp-up, demonstrate their impact evaluation, usage scenarios, eliminating the need for physical prototypes, reducing development time, and improving quality. Few forward-thinking companies are pursuing the digital transformation path, while the majority are clipping the wings of a transformation that is essential for a sustainable manufacturing. This paper describes a theoretical approach to exploit the digital twin technology to gather insights towards a realistic economical assessment of full automation solutions, to back and encourage investments to realize the potential of the digital manufacturing transformation. The approach is being tested under the European Union’s Horizon 2020 research and innovation program under grant agreement No. 958363, which provides an opportunity to assess how the various components of the method are constructed, how complex they are, and what level of effort is required, using a practical example

Comparative numerical analysis for cost and embodied carbon optimisation of steel building structures

The study investigates an area of sustainable structural design that is often overlooked in practical engineering applications. Specifically, a novel method to optimise the cost and embodied carbon performance of steel building structures simultaneously is explored in this paper. To achieve this, a parametric design model was developed to rapidly analyse code compliant structural configurations based on project specific constraints and rigorous testing of multiple steel beams (UB sections), floor construction typologies (precast or composite) and column layouts that could not be performed manually by engineering practitioners. Detailed objective functions are embedded in the model to compute the cost and life cycle carbon emissions of different material types used in the structure. Results from a comparative numerical analysis of a real case study illustrate that the proposed optimisation approach could guide structural engineers towards areas of the solution space with realistic design configurations, enabling them to effectively evaluate cost and carbon trade-offs. This significant contribution implies that the optimisation model could reduce the time required for the design and analysis of multiple structural configurations especially during the early stages of a project. Overall, the paper suggests that the deployment of automated design procedures can enhance the quality as well as the efficiency of the optimisation analysis.The research described in this paper was financially supported by Innovate UK through the ‘Innovative engineering approach for material, carbon and cost efficiency of steel buildings’ project with reference number 10247

The distribution of snow black carbon observed in the Arctic and compared to the GISS-PUCCINI model

In this study, we evaluate the ability of the latest NASA GISS composition-climate model, GISS-E2-PUCCINI, to simulate the spatial distribution of snow BC (sBC) in the Arctic relative to present-day observations. Radiative forcing due to BC deposition onto Arctic snow and sea ice is also estimated. Two sets of model simulations are analyzed, where meteorology is linearly relaxed towards National Centers for Environmental Prediction (NCEP) and towards NASA Modern Era Reanalysis for Research and Applications (MERRA) reanalyses. Results indicate that the modeled concentrations of sBC are comparable with present-day observations in and around the Arctic Ocean, except for apparent underestimation at a few sites in the Russian Arctic. That said, the model has some biases in its simulated spatial distribution of BC deposition to the Arctic. The simulations from the two model runs are roughly equal, indicating that discrepancies between model and observations come from other sources. Underestimation of biomass burning emissions in Northern Eurasia may be the main cause of the low biases in the Russian Arctic. Comparisons of modeled aerosol BC (aBC) with long-term surface observations at Barrow, Alert, Zeppelin and Nord stations show significant underestimation in winter and spring concentrations in the Arctic (most significant in Alaska), although the simulated seasonality of aBC has been greatly improved relative to earlier model versions. This is consistent with simulated biases in vertical profiles of aBC, with underestimation in the lower and middle troposphere but overestimation in the upper troposphere and lower stratosphere, suggesting that the wet removal processes in the current model may be too weak or that vertical transport is too rapid, although the simulated BC lifetime seems reasonable. The combination of observations and modeling provides a comprehensive distribution of sBC over the Arctic. On the basis of this distribution, we estimate the decrease in snow and sea ice albedo and the resulting radiative forcing. We suggest that the albedo reduction due to BC deposition presents significant space-time variations, with highest mean reductions of 1.25% in the Russian Arctic, which are much larger than those in other Arctic regions (0.39% to 0.64%). The averaged value over the Arctic north of 66° N is 0.4–0.6% during spring, leading to regional surface radiative forcings of 0.7, 1.1 and 1.0 W m<sup>−2</sup> in spring 2007, 2008 and 2009, respectively

Ground-based aerosol optical depth trends at three high-altitude sites in Switzerland and Southern Germany from 1995–2010

Ground-based aerosol optical depth (AOD) climatologies at three high-altitude sites in Switzerland (Jungfraujoch and Davos) and Southern Germany (Hohenpeissenberg) are updated and re-calibrated for the period 1995 – 2010. In addition, AOD time-series are augmented with previously unreported data, and are homogenized for the first time. Trend analysis revealed weak AOD trends (λ = 500 nm) at Jungfraujoch (JFJ; +0.007 decade-1), Davos (DAV; +0.002 decade-1) and Hohenpeissenberg (HPB; -0.011 decade-1) where the JFJ and HPB trends were statistically significant at the 95% and 90% confidence levels. However, a linear trend for the JFJ 1995 – 2005 period was found to be more appropriate than for 1995 – 2010 due to the influence of stratospheric AOD which gave a trend -0.003 decade-1 (significant at 95% level). When correcting for a recently available stratospheric AOD time-series, accounting for Pinatubo (1991) and more recent volcanic eruptions, the 1995 – 2010 AOD trends decreased slightly at DAV and HPB but remained weak at +0.000 decade-1 and -0.013 decade-1 (significant at 95% level). The JFJ 1995 – 2005 AOD time-series similarly decreased to -0.003 decade-1 (significant at 95% level). We conclude that despite a more detailed re40 analysis of these three time-series, which have been extended by five years to the end of 2010, a significant decrease in AOD at these three high-altitude sites has still not been observed

Quantitative assessment of the variability in chemical profiles from source apportionment analysis of PM10 and PM2.5 at different sites within a large metropolitan area

The study aims to assess the differences between the chemical profiles of the major anthropogenic and natural PM sources in two areas with different levels of urbanization and traffic density within the same urban agglomeration. A traffic site and an urban background site in the Athens Metropolitan Area have been selected for this comparison. For both sites, eight sources were identified, with seven of them being common for the two sites (Mineral Dust, non-Exhaust Emissions, Exhaust Emissions, Heavy Oil Combustion, Sulfates & Organics, Sea Salt and Biomass Burning) and one, site-specific (Nitrates for the traffic site and Aged Sea Salt for the urban background site). The similarity between the source profiles was quantified using two statistical analysis tools, Pearson correlation (PC) and Standardized Identity Distance (SID). According to Pearson coefficients five out of the eight source profiles present high (PC > 0.8) correlation (Mineral Dust, Biomass Burning, Sea Salt, Sulfates and Heavy Oil Combustion), one presented moderate (0.8 > PC > 0.6) correlation (Exhaust) and two low/no (PC < 0.6) correlation (non-Exhaust, Nitrates/Aged Sea Salt). The source profiles that appear to be more correlated are those of sources that are not expected to have high spatial variability because there are either natural/secondary and thus have a regional character or are emitted outside the urban agglomeration and are transported to both sites. According to SID four out of the eight sources have high statistical correlation (SID < 1) in the two sites (Mineral Dust, Sea salt, Sulfates, Heavy Oil Combustion). Biomass Burning was found to be the source that yielded different results from the two methodologies. The careful examination of the source profile of that source revealed the reason for this discrepancy. SID takes all the species of the profile equally into account, while PC might be disproportionally affected by a few numbers of species with very high concentrations. It is suggested, based on the findings of this work, that the combined use of both tools can lead the users to a thorough evaluation of the similarity of source profiles. This work is, to the best of our knowledge, the first time a study is focused on the quantitative comparison of the source profiles for sites inside the same urban agglomeration using statistical indicators.The study was supported by “CALIBRA/EYIE” (MIS 5002799) and “PANhellenic infrastructure for Atmospheric Composition and climatE change” (MIS 5021516) implemented under the Action “Reinforcement of the Research and Innovation Infrastructure”, funded by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014–2020) and co-financed by Greece and the European Union (European Regional Development Fund). Collection and chemical analysis of samples were supported by LIFE + AIRUSE EU project (ENV/ES/584). Partial support was also received by H2020 ERAPLANET/SMURBS ERANET GA No 689443.Peer reviewe

Size resolved mass concentration and elemental composition of atmospheric aerosols over the Eastern Mediterranean area

International audienceA Berner low pressure impactor was used to collect size-segregated aerosol samples at Finokalia, located on the north-eastern coast of Crete, Greece during July 2000 and January 2001. Several samples were also collected during the summer campaign aboard the research vessel "AEGAIEO" in the Aegean Sea. Gravimetric analysis and inversion techniques yielded daily PM1 and PM10 mass concentrations. The samples were also analysed by PIXE giving the elemental size distributions of Al, Si, K, Ca, Ti, Mn, Fe, Sr, S, Cl, Ni, V, Cu, Cr, Zn, and Pb. The crustal elements and sea-salt had a unimodal supermicron size distribution. Sulphur was found predominantly in submicron fractions. K, V, and Ni exhibited a bimodal distribution with a submicron mode produced by forest fires and oil combustion. The anthropogenic elements had broad and not well-defined distributions. The time series for PM1 and PM10 mass and elemental concentrations showed both daily and seasonal variation. Higher mass concentrations were observed during two incursions of Saharan dust, whilst higher concentrations of S, Cu, Zn, and Pb were encountered in samples collected in air masses arriving from northern Greece or the western coast of Turkey. Elevated concentrations of chlorine were found in samples with air masses either originating above the Atlantic Ocean and arriving at Finokalia via western Europe or recirculating over the western coast of the Black Sea

Characterization of a murine mixed neuron-glia model and cellular responses to regulatory T cell-derived factors

Abstract One of the unmet clinical needs in demyelinating diseases such as Multiple Sclerosis (MS) is to provide therapies that actively enhance the process of myelin regeneration (remyelination) in the central nervous system (CNS). Oligodendrocytes, the myelinating cells of the CNS, play a central role in remyelination and originate from oligodendrocyte progenitor cells (OPCs). We recently showed that depletion of regulatory T cells (Treg) impairs remyelination in vivo, and that Treg-secreted factors directly enhance oligodendrocyte differentiation. Here we aim to further characterize the dynamics of Treg-enhanced oligodendrocyte differentiation as well as elucidate the cellular components of a murine mixed neuron-glia model. Murine mixed neuron-glia cultures were generated from P2–7 C57BL/6 mice and characterized for percentage of neuronal and glial cell populations prior to treatment at 7 days in vitro (div) as well as after treatment with Treg-conditioned media at multiple timepoints up to 12 div. Mixed neuron-glia cultures consisted of approximately 30% oligodendroglial lineage cells, 20% neurons and 10% microglia. Furthermore, a full layer of astrocytes, that could not be quantified, was present. Treatment with Treg-conditioned media enhanced the proportion of MBP+ oligodendrocytes and decreased the proportion of PDGFRα+ OPCs, but did not affect OPC proliferation or survival. Treg-enhanced oligodendrocyte differentiation was not caused by Treg polarizing factors, was dependent on the number of activation cycles Treg underwent and was robustly achieved by using 5% conditioned media. These studies provide in-depth characterization of a murine mixed neuron-glia model as well as further insights into the dynamics of Treg-enhanced oligodendrocyte differentiation