Phase-field modeling of multi-domain evolution in ferromagnetic shape memory alloys and of polycrystalline thin film growth

The phase-field method is a powerful tool in computer-aided materials science as it allows for the analysis of the time-spatial evolution of microstructures on the mesoscale. A multi-phase-field model is adopted to run numerical simulations in two different areas of scientific interest: Polycrystalline thin films growth and the ferromagnetic shape memory effect. FFT-techniques, norm conservative integration and RVE-methods are necessary to make the coupled problems numerically feasible

Phase-field modeling of multi-domain evolution in ferromagnetic shape memory alloys and of polycrystalline thin film growth

The phase-field method is a powerful tool for the analysis of microstructure evolution. A multi-phase-field model is developed to run computer simulations in different areas of materials science: The anisotropic growth of MFI zeolite-like crystallites on a smooth substrate into a hydrothermal solution constituting thin films, and the analysis of the behavior of magnetic shape memory alloys, a class of active smart martensitic materials that are used as components in actuators and dampers

Characterization of Toll-like receptors in primary lung epithelial cells: strong impact of the TLR3 ligand poly(I:C) on the regulation of Toll-like receptors, adaptor proteins and inflammatory response

BACKGROUND: Bacterial and viral exacerbations play a crucial role in a variety of lung diseases including COPD or asthma. Since the lung epithelium is a major source of various inflammatory mediators that affect the immune response, we analyzed the inflammatory reaction of primary lung epithelial cells to different microbial molecules that are recognized by Toll-like receptors (TLR). METHODS: The effects of TLR ligands on primary small airway epithelial cells were analyzed in detail with respect to cytokine, chemokine and matrix metalloproteinase secretion. In addition, the regulation of the expression of TLRs and their adaptor proteins in small airway epithelial cells was investigated. RESULTS: Our data demonstrate that poly(I:C), a synthetic analog of viral dsRNA, mediated the strongest proinflammatory effects among the tested ligands, including an increased secretion of IL-6, IL-8, TNF-α, GM-CSF, GRO-α, TARC, MCP-1, MIP-3α, RANTES, IFN-β, IP-10 and ITAC as well as an increased release of MMP-1, MMP-8, MMP-9, MMP-10 and MMP-13. Furthermore, our data show that poly(I:C) as well as type-1 and type-2 cytokines have a pronounced effect on the expression of TLRs and molecules involved in TLR signaling in small airway epithelial cells. Poly(I:C) induced an elevated expression of TLR1, TLR2 and TLR3 and increased the gene expression of the general TLR adaptor MyD88 and IRAK-2. Simultaneously, poly(I:C) decreased the expression of TLR5, TLR6 and TOLLIP. CONCLUSION: Poly(I:C), an analog of viral dsRNA and a TLR3 ligand, triggers a strong inflammatory response in small airway epithelial cells that is likely to contribute to viral exacerbations of pulmonary diseases like asthma or COPD. The pronounced effects of poly(I:C) on the expression of Toll-like receptors and molecules involved in TLR signaling is assumed to influence the immune response of the lung epithelium to viral and bacterial infections. Likewise, the regulation of TLR expression by type-1 and type-2 cytokines is important considering the impact of exogenous and endogenous TLR ligands on Th1 or Th2 driven pulmonary inflammations like COPD or asthma, respectively

Effect of RNA quality on transcript intensity levels in microarray analysis of human post-mortem brain tissues

<p>Abstract</p> <p>Background</p> <p>Large-scale gene expression analysis of post-mortem brain tissue offers unique opportunities for investigating genetic mechanisms of psychiatric and neurodegenerative disorders. On the other hand microarray data analysis associated with these studies is a challenging task. In this publication we address the issue of low RNA quality data and corresponding data analysis strategies.</p> <p>Results</p> <p>A detailed analysis of effects of post chip RNA quality on the measured abundance of transcripts is presented. Overall Affymetrix GeneChip data (HG-U133_AB and HG-U133_Plus_2.0) derived from ten different brain regions was investigated. Post chip RNA quality being assessed by 5'/3' ratio of housekeeping genes was found to introduce a well pronounced systematic noise into the measured transcript expression levels. According to this study RNA quality effects have: 1) a "random" component which is introduced by the technology and 2) a systematic component which depends on the features of the transcripts and probes. Random components mainly account for numerous negative correlations of low-abundant transcripts. These negative correlations are not reproducible and are mainly introduced by an increased relative level of noise. Three major contributors to the systematic noise component were identified: the first is the probe set distribution, the second is the length of mRNA species, and the third is the stability of mRNA species. Positive correlations reflect the 5'-end to 3'-end direction of mRNA degradation whereas negative correlations result from the compensatory increase in stable and 3'-end probed transcripts. Systematic components affect the expressed transcripts by introducing irrelevant gene correlations and can strongly influence the results of the main experiment. A linear model correcting the effect of RNA quality on measured intensities was introduced.</p> <p>In addition the contribution of a number of pre-mortem and post-mortem attributes to the overall detected RNA quality effect was investigated. Brain pH, duration of agonal stage, post-mortem interval before sampling and donor's age of death within considered limits were found to have no significant contribution.</p> <p>Conclusion</p> <p>Basic conclusions for data analysis in expression profiling study are as follows: 1) testing for RNA quality dependency should be included in the preprocessing of the data; 2) investigating inter-gene correlation without regard to RNA quality effects could be misleading; 3) data normalization procedures relying on housekeeping genes either do not influence the correlation structure (if 3'-end intensities are used) or increase it for negatively correlated transcripts (if 5'-end or median intensities are included in normalization procedure); 4) sample sets should be matched with regard to RNA quality; 5) RMA preprocessing is more sensitive to RNA quality effect, than MAS 5.0.</p

Environmental kodaliths

Thesis (M.S.V.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1979.MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH.Includes bibliographical references (leaves 122-123).by Nina Mennerich Frankenheim.M.S.V.S

Proposing a Solution for a Self-Managed Data-Ecosystem in Production: Use-Case-Driven IT-OT-Integration with an Event-Driven IT-Architecture

With the development of publicly accessible broker systems within the last decade, the complexity of data-driven ecosystems is expected to become manageable for self-managed digitalisation. Having identified event-driven IT-architectures as a suitable solution for the architectural requirements of Industry 4.0, the producing industry is now offered a relevant alternative to prominent third-party ecosystems. Although the technical components are readily available, the realisation of an event-driven IT-architecture in production is often hindered by a lack of reference projects, and hence uncertainty about its success and risks. The research institute FIR and IT-expert synyx are thus developing an event-driven IT-architecture in the Center Smart Logistics' producing factory, which is designed to be a multi-agent testbed for members of the cluster. With the experience gained in industrial projects, a target IT-architecture was conceptualised that proposes a solution for a self-managed data-ecosystem based on open-source technologies. With the iterative integration of factory-relevant Industry 4.0 use cases, the target is continuously realised and validated. The paper presents the developed solution for a self-managed event-driven IT-architecture and presents the implications of the decisions made. Furthermore, the progress of two use cases, namely an IT-OT-integration and a smart product demonstrator for the research project BlueSAM, are presented to highlight the iterative technical implementability and merits, enabled by the architecture

Interference Mitigation Framework for Cellular Mobile Radio Networks

For today's cellular mobile communication networks, the needed capacity is hard to realize without much more of (expensive) bandwidth. Thus new standards like LTE were developed. LTE advanced is in discussion as the successor of LTE and cooperative multipoint transmission (CoMP) is one of the hot topics to increase the system's capacity. System simulations often show only weak gains of the signal-to-interference ratio due to high interference from noncooperating cells in the downlink. This paper presents an interference mitigation framework to overcome the hardest issue, that is, the low penetration rate of mobile stations that can be served from a cluster composed of their strongest cells in the network. The results obtained from simulation tools are discussed with values resulting from testbed on the TU Dresden. They show that the theoretical ideas can be transferred into gains on real systems

Antiferromagnetic Dimers of Ni(II) in the S=1 Spin-Ladder Na_2Ni_2(C_2O_4)_3(H_2O)_2

We report the synthesis, crystal structure and magnetic properties of the S=1 2-leg spin-ladder compound Na_2Ni_2(C_2O_4)_3(H_2O)_2. The magnetic properties were examined by magnetic susceptibility and pulsed high field magnetization measurements. The magnetic excitations have been measured in high field high frequency ESR. Although the Ni(II) ions form structurally a 2-leg ladder, an isolated dimer model consistently describes the observations very well. The analysis of the temperature dependent magnetization data leads to a magnetic exchange constant of J=43 K along the rungs of the ladder and an average value of the g-factor of 2.25. From the ESR measurements, we determined the single ion anisotropy to D=11.5 K. The validity of the isolated dimer model is supported by Quantum Monte Carlo calculations, performed for several ratios of interdimer and intradimer magnetic exchange and taking into account the experimentally determined single ion anisotropy. The results can be understood in terms of the different coordination and superexchange angles of the oxalate ligands along the rungs and legs of the 2-leg spin ladder.Comment: 8 pages, 10 figure