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Now showing 1 - 10 of 14
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    EARLINET Single Calculus Chain – overview on methodology and strategy
    (München : European Geopyhsical Union, 2015) D'Amico, Giuseppe; Amodeo, A.; Baars, H.; Binietoglou, I.; Freudenthaler, V.; Mattis, I.; Wandinger, U.; Pappalardo, G.
    In this paper we describe the EARLINET Single Calculus Chain (SCC), a tool for the automatic analysis of lidar measurements. The development of this tool started in the framework of EARLINET-ASOS (European Aerosol Research Lidar Network – Advanced Sustainable Observation System); it was extended within ACTRIS (Aerosol, Clouds and Trace gases Research InfraStructure Network), and it is continuing within ACTRIS-2. The main idea was to develop a data processing chain that allows all EARLINET stations to retrieve, in a fully automatic way, the aerosol backscatter and extinction profiles starting from the raw lidar data of the lidar systems they operate. The calculus subsystem of the SCC is composed of two modules: a pre-processor module which handles the raw lidar data and corrects them for instrumental effects and an optical processing module for the retrieval of aerosol optical products from the pre-processed data. All input parameters needed to perform the lidar analysis are stored in a database to keep track of all changes which may occur for any EARLINET lidar system over the time. The two calculus modules are coordinated and synchronized by an additional module (daemon) which makes the whole analysis process fully automatic. The end user can interact with the SCC via a user-friendly web interface. All SCC modules are developed using open-source and freely available software packages. The final products retrieved by the SCC fulfill all requirements of the EARLINET quality assurance programs on both instrumental and algorithm levels. Moreover, the manpower needed to provide aerosol optical products is greatly reduced and thus the near-real-time availability of lidar data is improved. The high-quality of the SCC products is proven by the good agreement between the SCC analysis, and the corresponding independent manual retrievals. Finally, the ability of the SCC to provide high-quality aerosol optical products is demonstrated for an EARLINET intense observation period.
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    Target categorization of aerosol and clouds by continuous multiwavelength-polarization lidar measurements
    (Katlenburg-Lindau : Copernicus, 2017) Baars, Holger; Seifert, Patric; Engelmann, Ronny; Wandinger, Ulla
    Absolute calibrated signals at 532 and 1064 nm and the depolarization ratio from a multiwavelength lidar are used to categorize primary aerosol but also clouds in high temporal and spatial resolution. Automatically derived particle backscatter coefficient profiles in low temporal resolution (30 min) are applied to calibrate the lidar signals. From these calibrated lidar signals, new atmospheric parameters in temporally high resolution (quasi-particle-backscatter coefficients) are derived. By using thresholds obtained from multiyear, multisite EARLINET (European Aerosol Research Lidar Network) measurements, four aerosol classes (small; large, spherical; large, non-spherical; mixed, partly nonspherical) and several cloud classes (liquid, ice) are defined. Thus, particles are classified by their physical features (shape and size) instead of by source. The methodology is applied to 2 months of continuous observations (24 h a day, 7 days a week) with the multiwavelength-Raman-polarization lidar PollyXT during the High-Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) in spring 2013. Cloudnet equipment was operated continuously directly next to the lidar and is used for comparison. By discussing three 24 h case studies, it is shown that the aerosol discrimination is very feasible and informative and gives a good complement to the Cloudnet target categorization. Performing the categorization for the 2-month data set of the entire HOPE campaign, almost 1 million pixel (5 min×30 m) could be analysed with the newly developed tool. We find that the majority of the aerosol trapped in the planetary boundary layer (PBL) was composed of small particles as expected for a heavily populated and industrialized area. Large, spherical aerosol was observed mostly at the top of the PBL and close to the identified cloud bases, indicating the importance of hygroscopic growth of the particles at high relative humidity. Interestingly, it is found that on several days non-spherical particles were dispersed from the ground into the atmosphere.
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    Polarization lidar: An extended three-signal calibration approach
    (Katlenburg-Lindau : Copernicus, 2019) Jimenez, Cristofer; Ansmann, Albert; Engelmann, Ronny; Haarig, Moritz; Schmidt, Jörg; Wandinger, Ulla
    We present a new formalism to calibrate a threesignal polarization lidar and to measure highly accurate height profiles of the volume linear depolarization ratios under realistic experimental conditions. The methodology considers elliptically polarized laser light, angular misalignment of the receiver unit with respect to the main polarization plane of the laser pulses, and cross talk among the receiver channels. A case study of a liquid-water cloud observation demonstrates the potential of the new technique. Long-term observations of the calibration parameters corroborate the robustness of the method and the long-term stability of the three-signal polarization lidar. A comparison with a second polarization lidar shows excellent agreement regarding the derived volume linear polarization ratios in different scenarios: A biomass burning smoke event throughout the troposphere and the lower stratosphere up to 16 km in height, a dust case, and also a cirrus cloud case. © Author(s) 2019.
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    Topological data analysis of contagion maps for examining spreading processes on networks
    ([London] : Nature Publishing Group UK, 2015) Taylor, Dane; Klimm, Florian; Harrington, Heather A.; Kramár, Miroslav; Mischaikow, Konstantin; Porter, Mason A.; Mucha, Peter J.
    Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth’s surface; however, in modern contagions long-range edges—for example, due to airline transportation or communication media—allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct ‘contagion maps’ that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.
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    Partial cross mapping eliminates indirect causal influences
    ([London] : Nature Publishing Group UK, 2020) Leng, Siyang; Ma, Huanfei; Kurths, Jürgen; Lai, Ying-Cheng; Lin, Wei; Aihara, Kazuyuki; Chen, Luonan
    Causality detection likely misidentifies indirect causations as direct ones, due to the effect of causation transitivity. Although several methods in traditional frameworks have been proposed to avoid such misinterpretations, there still is a lack of feasible methods for identifying direct causations from indirect ones in the challenging situation where the variables of the underlying dynamical system are non-separable and weakly or moderately interacting. Here, we solve this problem by developing a data-based, model-independent method of partial cross mapping based on an articulated integration of three tools from nonlinear dynamics and statistics: phase-space reconstruction, mutual cross mapping, and partial correlation. We demonstrate our method by using data from different representative models and real-world systems. As direct causations are keys to the fundamental underpinnings of a variety of complex dynamics, we anticipate our method to be indispensable in unlocking and deciphering the inner mechanisms of real systems in diverse disciplines from data.
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    Poisoning of bubble propelled catalytic micromotors: The chemical environment matters
    (Cambridge [u.a.] : Royal Society of Chemistry, 2013) Zhao, G.; Sanchez, S.; Schmidt, O.G.; Pumera, M.
    Self-propelled catalytic microjets have attracted considerable attention in recent years and these devices have exhibited the ability to move in complex media. The mechanism of propulsion is via the Pt catalysed decomposition of H2O2 and it is understood that the Pt surface is highly susceptible to poisoning by sulphur-containing molecules. Here, we show that important extracellular thiols as well as basic organic molecules can significantly hamper the motion of catalytic microjet engines. This is due to two different mechanisms: (i) molecules such as dimethyl sulfoxide can quench the hydroxyl radicals produced at Pt surfaces and reduce the amount of oxygen gas generated and (ii) molecules containing -SH, -SSR, and -SCH3 moieties can poison the catalytically active platinum surface, inhibiting the motion of the jet engines. It is essential that the presence of such molecules in the environment be taken into consideration for future design and operation of catalytic microjet engines. We show this effect on catalytic micromotors prepared by both rolled-up and electrodeposition approaches, demonstrating that such poisoning is universal for Pt catalyzed micromotors. We believe that our findings will contribute significantly to this field to develop alternative systems or catalysts for self-propulsion when practical applications in the real environment are considered.
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    Estimated desert-dust ice nuclei profiles from polarization lidar: Methodology and case studies
    (München : European Geopyhsical Union, 2015) Mamouri, R.E.; Ansmann, A.
    A lidar method is presented that permits the estimation of height profiles of ice nuclei concentrations (INC) in desert dust layers. The polarization lidar technique is applied to separate dust and non-dust backscatter and extinction coefficients. The desert dust extinction coefficients σd are then converted to aerosol particle number concentrations APC280 which consider particles with radius > 280 nm only. By using profiles of APC280 and ambient temperature T along the laser beam, the profile of INC can be estimated within a factor of 3 by means of APC-T-INC parameterizations from the literature. The observed close relationship between σd at 500 nm and APC280 is of key importance for a successful INC retrieval. We studied this link by means of AERONET (Aerosol Robotic Network) sun/sky photometer observations at Morocco, Cabo Verde, Barbados, and Cyprus during desert dust outbreaks. The new INC retrieval method is applied to lidar observations of dust layers with the spaceborne lidar CALIOP (Cloud Aerosol Lidar with Orthogonal Polarization) during two overpasses over the EARLINET (European Aerosol Research Lidar Network) lidar site of the Cyprus University of Technology (CUT), Limassol (34.7° N, 33° E), Cyprus. The good agreement between the CALIOP and CUT lidar retrievals of σd, APC280, and INC profiles corroborates the potential of CALIOP to provide 3-D global desert dust APC280 and INC data sets.
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    The complexity of gene expression dynamics revealed by permutation entropy
    (London : BioMed Central Ltd., 2010) Sun, Xiaoliang; Zou, Yong; Nikiforova, Victoria; Kurths, Jürgen; Walther, Dirk
    Background: High complexity is considered a hallmark of living systems. Here we investigate the complexity of temporal gene expression patterns using the concept of Permutation Entropy (PE) first introduced in dynamical systems theory. The analysis of gene expression data has so far focused primarily on the identification of differentially expressed genes, or on the elucidation of pathway and regulatory relationships. We aim to study gene expression time series data from the viewpoint of complexity.Results: Applying the PE complexity metric to abiotic stress response time series data in Arabidopsis thaliana, genes involved in stress response and signaling were found to be associated with the highest complexity not only under stress, but surprisingly, also under reference, non-stress conditions. Genes with house-keeping functions exhibited lower PE complexity. Compared to reference conditions, the PE of temporal gene expression patterns generally increased upon stress exposure. High-complexity genes were found to have longer upstream intergenic regions and more cis-regulatory motifs in their promoter regions indicative of a more complex regulatory apparatus needed to orchestrate their expression, and to be associated with higher correlation network connectivity degree. Arabidopsis genes also present in other plant species were observed to exhibit decreased PE complexity compared to Arabidopsis specific genes.Conclusions: We show that Permutation Entropy is a simple yet robust and powerful approach to identify temporal gene expression profiles of varying complexity that is equally applicable to other types of molecular profile data.
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    Simultaneous statistical inference for epigenetic data
    (San Francisco, California, US : PLOS, 2015) Schildknecht, Konstantin; Olek, Sven; Dickhaus, Thorsten
    Epigenetic research leads to complex data structures. Since parametric model assumptions for the distribution of epigenetic data are hard to verify we introduce in the present work a nonparametric statistical framework for two-group comparisons. Furthermore, epigenetic analyses are often performed at various genetic loci simultaneously. Hence, in order to be able to draw valid conclusions for specific loci, an appropriate multiple testing correction is necessary. Finally, with technologies available for the simultaneous assessment of many interrelated biological parameters (such as gene arrays), statistical approaches also need to deal with a possibly unknown dependency structure in the data. Our statistical approach to the nonparametric comparison of two samples with independent multivariate observables is based on recently developed multivariate multiple permutation tests. We adapt their theory in order to cope with families of hypotheses regarding relative effects. Our results indicate that the multivariate multiple permutation test keeps the pre-assigned type I error level for the global null hypothesis. In combination with the closure principle, the family-wise error rate for the simultaneous test of the corresponding locus/parameter-specific null hypotheses can be controlled. In applications we demonstrate that group differences in epigenetic data can be detected reliably with our methodology.
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    A novel, low-volume method for organ culture of embryonic kidneys that allows development of cortico-medullary anatomical organization
    (San Francisco, Calif. : Public Library of Science, 2010) Sebinger, D.D.R.; Unbekandt, M.; Ganeva, V.V.; Ofenbauer, A.; Werner, C.; Davies, J.A.
    Here, we present a novel method for culturing kidneys in low volumes of medium that offers more organotypic development compared to conventional methods. Organ culture is a powerful technique for studying renal development. It recapitulates many aspects of early development very well, but the established techniques have some disadvantages: in particular, they require relatively large volumes (1-3 mls) of culture medium, which can make high-throughput screens expensive, they require porous (filter) substrates which are difficult to modify chemically, and the organs produced do not achieve good cortico-medullary zonation. Here, we present a technique of growing kidney rudiments in very low volumes of medium-around 85 microliters-using silicone chambers. In this system, kidneys grow directly on glass, grow larger than in conventional culture and develop a clear anatomical cortico-medullary zonation with extended loops of Henle. © 2010 Sebinger et al.