TY - JOUR A1 - Reinmuth-Selzle, K. A1 - Kampf, C. J. A1 - Lucas, K. A1 - Lang-Yona, N. A1 - Fröhlich-Nowoisky, J. A1 - Shiraiwa, M. A1 - Lakey, P. S. J. A1 - Lai, S. A1 - Liu, F. A1 - Kunert, A. T. A1 - Ziegler, K. A1 - Shen, F. A1 - Sgarbanti, R. A1 - Weber, B. A1 - Bellinghausen, I. A1 - Saloga, J. A1 - Weller, Michael G. A1 - Duschl, A. A1 - Schuppan, D. A1 - Pöschl, U. T1 - Air pollution and climate change effects on allergies in the anthropocene: Abundance, interaction, and modification of allergens and adjuvants N2 - Air pollution and climate change are potential drivers for the increasing burden of allergic diseases. The molecular mechanisms by which air pollutants and climate parameters may influence allergic diseases, however, are complex and elusive. This article provides an overview of physical, chemical and biological interactions between air pollution, climate change, allergens, adjuvants and the immune system, addressing how these interactions may promote the development of allergies. We reviewed and synthesized key findings from atmospheric, climate, and biomedical research. The current state of knowledge, open questions, and future research perspectives are outlined and discussed. The Anthropocene, as the present era of globally pervasive anthropogenic influence on planet Earth and, thus, on the human environment, is characterized by a strong increase of carbon dioxide, ozone, nitrogen oxides, and combustion- or traffic-related particulate matter in the atmosphere. These environmental factors can enhance the abundance and induce chemical modifications of allergens, increase oxidative stress in the human body, and skew the immune system toward allergic reactions. In particular, air pollutants can act as adjuvants and alter the immunogenicity of allergenic proteins, while climate change affects the atmospheric abundance and human exposure to bioaerosols and aeroallergens. To fully understand and effectively mitigate the adverse effects of air pollution and climate change on allergic diseases, several challenges remain to be resolved. Among these are the identification and quantification of immunochemical reaction pathways involving allergens and adjuvants under relevant environmental and physiological conditions. KW - Allergie KW - Klimaveränderung KW - Luftverschmutzung KW - Partikel KW - Ozon KW - Stickoxide KW - Allergene KW - Adjuvantien KW - PALM KW - DAMP PY - 2017 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-404531 DO - https://doi.org/10.1021/acs.est.6b04908 SN - 1520-5851 SN - 0013-936X VL - 51 IS - 8 SP - 4119 EP - 4141 PB - American Chemical Society (ACS) CY - Washington AN - OPUS4-40453 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Krishna, S. K. P. A1 - Puthiyaveetil, N. A1 - Kidangan, R. A1 - Unnikrishnakurup, Sreedhar A1 - Ziegler, Mathias A1 - Myrach, Philipp A1 - Balasubramaniam, Krishnan A1 - Purushothaman, B. T1 - Raw data based image processing algorithm for fast detection of surface breaking cracks N2 - The aim of this work is to illustrate the contribution of signal processing techniques in the field of Non-Destructive Evaluation. A component’s life evaluation is inevitably related to the presence of flaws in it. The detection and characterization of cracks prior to damage is a technologically and economically significant task and is of very importance when it comes to safety-relevant measures. The Laser Thermography is the most effective and advanced thermography method for Non-Destructive Evaluation. High capability for the detection of surface cracks and for the characterization of the geometry of artificial surface flaws in metallic samples of laser thermography is particularly encouraging. This is one of the non- contacting, fast and real time detection method. The presence of a vertical surface breaking crack will disturb the thermal footprint. The data processing method plays vital role in fast detection of the surface and sub-surface cracks. Currently in laser thermographic inspection lacks a compromising data processing algorithm which is necessary for the fast crack detection and also the analysis of data is done as part of post processing. In this work we introduced a raw data based image processing algorithm which results precise, better and fast crack detection. The algorithm we developed gives better results in both experimental and modeling data. By applying this algorithm we carried out a detailed investigation Variation of thermal contrast with crack parameters like depth and width. The algorithm we developed is applied for various surface temperature data from the 2D scanning model and also validated credibility of algorithm with experimental data. T2 - QNDE conference 2016 - Review of progress in quantitative nondestructive evaluation CY - Atlanta, GA, USA DA - 18.07.2016 KW - Crack Detection KW - Laserthermografie KW - Thermografie KW - Risserkennung PY - 2017 SN - 978-0-7354-1474-7 DO - https://doi.org/10.1063/1.4974723 SN - 0094-243X VL - 1806 IS - 1 SP - UNSP 140008, 1 EP - 9 PB - AIP Publishing CY - New York AN - OPUS4-39387 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -