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  • 1
    Publication Date: 2009-08-06
    Description: Alpha, beta, and gamma proteobacteria comprise approximately 68, 16, and 7% of all identified bacteria. In this study, bacterial communities that had fouled polyvinylidene fluoride microfiltration membranes, which are used for drinking water treatment, over an 18 month period were analyzed using the 16s rRNA gene clone library method. The alpha, beta, and gamma proteobacteria were composed of mainly Bradyrhizobium and Rhodopseudomonas, Ralstonia, and Legionella, respectively. The presence of a relatively high amount of alpha proteobacteria was due to the oligotrophic condition of the drinking water source, the Han River, tested in this specific case study. The second most prominent bacteria community was the beta proteobacteria, which are typically found in a freshwater environment. This finding supports the notion that the drinking water source was relatively clean. Analyses of the organic foulants indicated that they were most likely from extra cellular polymers and/or cell fractured chemicals from bacteria or micro-organisms, as identified using organic characterizing tools, including 3-D fluorescence excitation-emission matrix and Fourier transform IR analyses.
    Print ISSN: 1996-9457
    Electronic ISSN: 1996-9465
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by Copernicus on behalf of Delft University of Technology.
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Annals of biomedical engineering 27 (1999), S. 23-31 
    ISSN: 1573-9686
    Keywords: Nonlinear modeling ; Volterra kernels ; Laguerre expansion
    Source: Springer Online Journal Archives 1860-2000
    Topics: Medicine , Technology
    Notes: Abstract This article presents results of the use of a novel methodology employing principal dynamic modes (PDM) for modeling the nonlinear dynamics of renal autoregulation in rats. The analyzed experimental data are broadband (0–0.5 Hz) blood pressure-flow data generated by pseudorandom forcing and collected in normotensive and hypertensive rats for two levels of pressure forcing (as measured by the standard deviation of the pressure fluctuation). The PDMs are computed from first-order and second-order kernel estimates obtained from the data via the Laguerre expansion technique. The results demonstrate that two PDMs suffice for obtaining a satisfactory nonlinear dynamic model of renal autoregulation under these conditions, for both normotensive and hypertensive rats. Furthermore, the two PDMs appear to correspond to the two main autoregulatory mechanisms: the first to the myogenic and the second to the tubuloglomerular feedback (TGF) mechanism. This allows the study of the separate contributions of the two mechanisms to the autoregulatory response dynamics, as well as the effects of the level of pressure forcing and hypertension on the two distinct autoregulatory mechanisms. It is shown that the myogenic mechanism has a larger contribution and is affected only slightly, while the TGF mechanism is affected considerably by increasing pressure forcing or hypertension (the emergence of a second resonant peak and the decreased relative contribution to the response flow signal). © 1999 Biomedical Engineering Society. PAC99: 8719Uv
    Type of Medium: Electronic Resource
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  • 3
    ISSN: 1573-9686
    Keywords: ARMA ; NARMA ; Polynomial function ; Backpropagation ; Measurement noise ; Dynamic noise ; Deterministic ; Stochastic ; Recurrent neural network
    Source: Springer Online Journal Archives 1860-2000
    Topics: Medicine , Technology
    Notes: Abstract In this study, we introduce a new approach for estimating linear and nonlinear stochastic autoregressive moving average (ARMA) model parameters, given a corrupt signal, using artificial recurrent neural networks. This new approach is a two-step approach in which the parameters of the deterministic part of the stochastic ARMA model are first estimated via a three-layer artificial neural network (deterministic estimation step) and then reestimated using the prediction error as one of the inputs to the artificial neural networks in an iterative algorithm (stochastic estimation step). The prediction error is obtained by subtracting the corrupt signal of the estimated ARMA model obtained via the deterministic estimation step from the system output response. We present computer simulation examples to show the efficacy of the proposed stochastic recurrent neural network approach in obtaining accurate model predictions. Furthermore, we compare the performance of the new approach to that of the deterministic recurrent neural network approach. Using this simple two-step procedure, we obtain more robust model predictions than with the deterministic recurrent neural network approach despite the presence of significant amounts of either dynamic or measurement noise in the output signal. The comparison between the deterministic and stochastic recurrent neural network approaches is furthered by applying both approaches to experimentally obtained renal blood pressure and flow signals. © 1999 Biomedical Engineering Society. PAC99: 8710+e, 8719Uv, 0705Mh
    Type of Medium: Electronic Resource
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  • 4
    Publication Date: 2015-11-17
    Description: Primer design is a fundamental technique that is widely used for polymerase chain reaction (PCR). Although many methods have been proposed for primer design, they require a great deal of manual effort to generate feasible and valid primers, including homology tests on off-target sequences using BLAST-like tools. That approach is inconvenient for many target sequences of quantitative PCR (qPCR) due to considering the same stringent and allele-invariant constraints. To address this issue, we propose an entirely new method called MRPrimer that can design all feasible and valid primer pairs existing in a DNA database at once, while simultaneously checking a multitude of filtering constraints and validating primer specificity. Furthermore, MRPrimer suggests the best primer pair for each target sequence, based on a ranking method. Through qPCR analysis using 343 primer pairs and the corresponding sequencing and comparative analyses, we showed that the primer pairs designed by MRPrimer are very stable and effective for qPCR. In addition, MRPrimer is computationally efficient and scalable and therefore useful for quickly constructing an entire collection of feasible and valid primers for frequently updated databases like RefSeq. Furthermore, we suggest that MRPrimer can be utilized conveniently for experiments requiring primer design, especially real-time qPCR.
    Keywords: Nucleic acid amplification
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 5
  • 6
    Publication Date: 2004-04-01
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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  • 7
    Publication Date: 2015-06-25
    Description: The chemical composition and organic compounds of rainwater were investigated from June to December 2012 at Gwangju in Korea. The volume weighted mean of pH ranged from 3.83 to 8.90 with an average of 5.78. 50 % of rainwater samples had pH values below 5.6. The volume-weighted mean concentration (VWMC) of major ions followed the order: Cl− 〉 SO42− 〉 NH4+ 〉 Na+ 〉 NO3− 〉 Ca2+ 〉 Mg2+ 〉 K+. The VWMC of trace metals decreased in the order as follows Zn 〉 Al 〉 Fe 〉 Mn 〉 Pb 〉 Cu 〉 Ni 〉 Cd 〉 Cr. The VWMCs of major ions and trace metals were higher in winter than in summer. The high enrichment factors indicate that Zn, Pb, Cu, and Cd originated predominantly from anthropogenic sources. Factor analysis (principal component analysis) indicates the influence of anthropogenic pollutants, sea salt, and crustal materials on the chemical compositions of rainwater. Benzoic acids, 1H-Isoindole-1,3(2H)-dione, phthalic anhydride, benzene, acetic acids, 1,2-benzenedicarboxylic acids, benzonitrile, acetaldehyde, and acetamide were the most prominent pyrolysis fragments for rainwater organic compounds identified by pyrolysis gas chromatography/mass spectrometry (Py-GC/MS). The results indicate that anthropogenic sources are the most important factors affecting the organic composition of rainwater in urban area.
    Print ISSN: 1996-9473
    Electronic ISSN: 1996-9481
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by Copernicus on behalf of Delft University of Technology.
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  • 8
    Publication Date: 2015-11-03
    Description: Recently, rainwater composition affected by atmospheric pollutants has been the topic of intense study in East Asia because of its adverse environmental and human health effects. In the present study, the chemical composition and organic compounds of rainwater were investigated from June to December 2012 at Gwangju in Korea. The aim of this study is to determine the seasonal variation of rainwater chemical composition and to identify possible sources of inorganic and organic compounds. The volume-weighted mean of pH ranged from 3.83 to 8.90 with an average of 5.78. Of rainwater samples, 50 % had pH values below 5.6. The volume-weighted mean concentration (VWMC) of major ions followed the order Cl− 〉 SO42− 〉 NH4+ 〉 Na+ 〉 NO3− 〉 Ca2+ 〉 Mg2+ 〉 K+. The VWMC of trace metals decreased in the order Zn 〉 Al 〉 Fe 〉 Mn 〉 Pb 〉 Cu 〉 Ni 〉 Cd 〉 Cr. The VWMCs of major ions and trace metals were higher in winter than in summer. The high enrichment factors indicate that Zn, Pb, Cu, and Cd originated predominantly from anthropogenic sources. Factor analysis (principal component analysis) indicates the influence of anthropogenic pollutants, sea salt, and crustal materials on the chemical compositions of rainwater. Benzoic acids, 1H-isoindole-1,3(2H)-dione, phthalic anhydride, benzene, acetic acids, 1,2-benzenedicarboxylic acids, benzonitrile, acetaldehyde, and acetamide were the most prominent pyrolysis fragments for rainwater organic compounds identified by pyrolysis gas chromatography/mass spectrometry (Py-GC/MS). The results indicate that anthropogenic sources are the most important factors affecting the organic composition of rainwater in an urban area.
    Print ISSN: 1996-9457
    Electronic ISSN: 1996-9465
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by Copernicus on behalf of Delft University of Technology.
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  • 9
    Publication Date: 2011-08-24
    Description: 1. Are arterial blood pressure fluctuations buffered or reinforced by respiratory sinus arrhythmia (RSA)? There is still considerable debate about this simple question. Different results have been obtained, triggering a discussion as to whether or not the baroreflexes are responsible for RSA. We suspected that the measurements of different aspects of arterial pressure (mean arterial pressure (MAP) and systolic pressure (SP)) can explain the conflicting results. 2. Simultaneous recordings of beat-to-beat MAP, SP, left cardiac stroke volume (SV, pulsed ultrasound Doppler), heart rate (HR) and respiration (RE) were obtained in 10 healthy young adults during spontaneous respiration. In order to eliminate HR variations at respiratory frequency we used propranolol and atropine administration in the supine and tilted positions. Respiration-synchronous variation in the recorded variables was quantified by spectral analysis of the recordings of each of these variables, and the phase relations between them were determined by cross-spectral analysis. 3. MAP fluctuations increased after removing heart rate variations in both supine and tilted position, whereas SP fluctuations decreased in the supine position and increased in the head-up tilted position. 4. RSA buffers respiration-synchronous fluctuations in MAP in both positions. However, fluctuations in SP were reinforced by RSA in the supine and buffered in the tilted position.
    Keywords: Life Sciences (General)
    Type: The Journal of physiology (ISSN 0022-3751); Volume 536; Pt 1; 251-9
    Format: text
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  • 10
    Publication Date: 2019-07-13
    Description: The operation and the expected performance of a proposed automatic guideway transit system which uses low speed automated mixed traffic vehicles (AMTVs) were analyzed. Vehicle scheduling and headway control policies were evaluated with a transit system simulation model. The effect of mixed traffic interference on the average vehicle speed was examined with a vehicle pedestrian interface model. Control parameters regulating vehicle speed were evaluated for safe stopping and passenger comfort. Some preliminary data on the cost and operation of an experimental AMTV system are included. These data were the result of a separate task conducted at JPL, and were included as background information.
    Keywords: URBAN TECHNOLOGY AND TRANSPORTATION
    Type: NASA-CR-149279 , JPL-5040-45 , UMTA-RD-CA-06-0088-76-1 , PB-264527
    Format: application/pdf
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