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1.
The Unmanned Systems Research Laboratory (USRL) : a new facility for UAV-based atmospheric observations
Maria Kezoudi, Christos Keleshis, Panayiota Antoniou, George Biskos, Murat Bronz, Christos Constantinides, Maximillien Desservettaz, Ru-Shan Gao, Joe Girdwood, Griša Močnik, 2021, original scientific article

Abstract: The Unmanned Systems Research Laboratory (USRL) of the Cyprus Institute is a new mobile exploratory platform of the EU Research Infrastructure Aerosol, Clouds and Trace Gases Research InfraStructure (ACTRIS). USRL offers exclusive Unmanned Aerial Vehicle (UAV)-sensor solutions that can be deployed anywhere in Europe and beyond, e.g., during intensive field campaigns through a transnational access scheme in compliance with the drone regulation set by the European Union Aviation Safety Agency (EASA) for the research, innovation, and training. UAV sensor systems play a growing role in the portfolio of Earth observation systems. They can provide cost-effective, spatial in-situ atmospheric observations which are complementary to stationary observation networks. They also have strong potential for calibrating and validating remote-sensing sensors and retrieval algorithms, mapping close-to-the-ground emission point sources and dispersion plumes, and evaluating the performance of atmospheric models. They can provide unique information relevant to the short- and long-range transport of gas and aerosol pollutants, radiative forcing, cloud properties, emission factors and a variety of atmospheric parameters. Since its establishment in 2015, USRL is participating in major international research projects dedicated to (1) the better understanding of aerosol-cloud interactions, (2) the profiling of aerosol optical properties in different atmospheric environments, (3) the vertical distribution of air pollutants in and above the planetary boundary layer, (4) the validation of Aeolus satellite dust products by utilizing novel UAV-balloon-sensor systems, and (5) the chemical characterization of ship and stack emissions. A comprehensive overview of the new UAV-sensor systems developed by USRL and their field deployments is presented here. This paper aims to illustrate the strong scientific potential of UAV-borne measurements in the atmospheric sciences and the need for their integration in Earth observation networks.
Keywords: landscape, proximity, still life, COVID-19, domesticity
Published in RUNG: 16.08.2021; Views: 1662; Downloads: 147
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2.
Still Life - natura morta : the landscapes of proximity
Saša Dobričić, Marco Acri, 2021, original scientific article

Keywords: landscape, proximity, Still Life, COVID-19, domesticity
Published in RUNG: 10.08.2021; Views: 1727; Downloads: 52
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3.
A NEW TOOL TO EVALUATE CORTISOL CONCENTRATIONS IN ANIMAL HAIR
Antonella Comin, Tanja Peric, Mara Colzani, Francesco De Vecchi, Cristina Bergamin, Alberto Prandi, 2018, published scientific conference contribution abstract

Abstract: The study of cortisol in hair requires the use of a highly sensitive assay. To date, hair cortisol concentrations (HCC) have been evaluated with different analytical methods as Radio Immune Assay (RIA), Enzyme Immunossay (EIA), Enzyme Linked Immunosorbent Assay (ELISA), ChemiLuminescent Immunoassay (CLIA) and High Performance Liquid Chromatography with Mass Spectrometry (HPLC/MS) or Liquid Chromatography with Tandem Mass Spectrometry (LC-MS/MS). Amplified luminescent proximity homogeneous assay (AlphaLISA) is an ELISA-like, nonradioactive technology first reported in 1994 [1]. This technology allows the quantitative detection of molecules of interest in a light-induced chemiluminescence immunoassay using a microplate without wash step. The aim of the study was to compare RIA with AlphaLISA method and examine the sensitivity in evaluating cortisol concentrations in animal hair of the Cortisol AlphaLISA kit (PerkinElmer, USA), originally suggested for the analysis of buffer and serum samples. The study has been carried out on 4 samples of calf, 4 samples of foal and 8 samples of sheep hair. After washing with isopropanol, two extracts were obtained from each hair sample. One extract has been evaluated for HCC by RIA as previously described [2,3]. The second extract has been reconstituted with the buffer provided by the Cortisol AlphaLISA Kit and HCC evaluated by the use of this commercially available kit. The preliminary results indicate that the Cortisol AlphaLISA Kit is capable to detect cortisol also in hair samples with high sensitivity, with a detection limit of 17 pg/ml. Intra- and inter-assay coefficients of variation (CVs) were 4.0% and 9.0%, respectively. Cortisol concentrations ranged between 1.31 and 16.94 pg/mg, 6.30 and 57.65 pg/mg, and 2.16 and 45.08 in calf, foal and sheep hair, respectively. The HCC obtained by Cortisol AlphaLISA Kit and RIA showed a good correlation (r=0.79, p<0.01). Considering the possibility to use a low amount of extracted sample, its no-washing procedure and the performances showed, we can conclude that the Cortisol AlphaLISA Kit can be considered an excellent tool to evaluate cortisol concentrations also in hair derived from animal species.
Keywords: hair, cortisol, analyses, method, AlphaLISA, Amplified luminescent proximity homogeneous assay
Published in RUNG: 09.04.2019; Views: 3379; Downloads: 0
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