Expression And Activity Of Novel Nitrate Reductase Enzymes In Chattonella Subsalsa And Implications For Competitive Dynamics In Marine Environments

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Author: Yanfei Wang
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ISBN: 9781369353792
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Expression And Activity Of Novel Nitrate Reductase Enzymes In Chattonella Subsalsa And Implications For Competitive Dynamics In Marine Environments by Yanfei Wang


Original Title: Expression And Activity Of Novel Nitrate Reductase Enzymes In Chattonella Subsalsa And Implications For Competitive Dynamics In Marine Environments

Chattonella subsalsa is a harmful alga that can form fish-killing blooms and cause severe damage to the ecosystem. In Delaware Inland Bays, C. subsalsa has formed mixed blooms with other species in recent years. The reason for the persistence of these blooms and the capacity for these species to avoid competitive exclusion remains unknown. Nitrogen is a limiting source in the aquatic environment, and its input may stimulate blooms dominated by C. subsalsa. Therefore, competing for nitrogen source may contribute to the success and survival of this species. For organisms to use nitrate as a nitrogen source, nitrate reductase catalyzes the first and also rate limiting step in nitrate assimilation. Algal nitrate reductase is responsive to nitrogen source, temperature, light intensity and its endogenous diel rhythm. In plants, it is also regulated by reversible phosphorylation of a conserved serine residue in the hinge 1 region, and sequential binding of 14-3-3 proteins at the post-translational level. However, 14-3-3 binding motifs within nitrate reductase were only found in plants, but not in algae. Previous research found a novel nitrate reductase, NR2-2/2HbN (NR2), in C. subsalsa, and this enzyme has a 2/2 hemoglobin domain within its hinge 2 region. In this research, another novel nitrate reductase, NR3, was found in this alga, and its sequence indicates the presence of a 14-3-3 binding motif in the hinge 1 region. To date, this is the first report for the presence of the 14-3-3 binding motif in algal nitrate reductase. In Chapter 2, the sequence of NR3 was analyzed and compared with nitrate reductase sequences in algae and plants. The presence of a putative 14-3-3 binding motif in this enzyme was discussed. The expression and activity of nitrate reductase in C. subsalsa were measured in response to light, nitrogen source, and temperature. The results indicate that, at the gene expression level, both NR2 and NR3 were regulated by light and nitrogen source, while only NR2 was regulated by temperature. At the protein translational level, evidence was provided that NR activity was regulated by nitrogen and temperature by reversible phosphorylation and binding of 14-3-3 proteins, while NR activity in response to light may be regulated by alternative mechanisms. In Chapter 3, natural C. subsalsa blooms were stimulated by different nitrogen sources in two mesocosm experiments. One pulse of nitrogen was added to the first mesocosm experiment, while repeated pulses of nitrogen along with phosphate were added to the second mesocosm experiment. The growth rate of C. subsalsa and the entire assemblage, as well as NR2 and NR3 expression, were tested in order to investigate the implications of NR expression to the competition and survival of C. subsalsa in a dynamic environment. The results indicate that C. subsalsa out-competed other species with a low nitrogen concentration. Several strategies for the survival and success of C. subsalsa in the low nitrogen-loading environment were proposed based on the results: 1). C. subsalsa performed surge uptake and could store nitrogen; 2). C. subsalsa was capable of utilizing nitrate produced by nitrogen fixers or released by dead cells; 3). C. subsalsa regulates NR2 and NR3 expression differentially in response to different nitrogen conditions, such that NR2 may benefit C. subsalsa in favorable environments with a high concentration of nitrate, while NR3 may benefit C. subsalsa in a more dynamic and unfavorable environment with ammonium as the dominant nitrogen source.

Optimization And Regularization For Computational Inverse Problems And Applications

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Author: Yanfei Wang
Publisher: Springer Science & Business Media
ISBN: 9783642137426
Size: 80.16 MB
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Optimization And Regularization For Computational Inverse Problems And Applications by Yanfei Wang


Original Title: Optimization And Regularization For Computational Inverse Problems And Applications

"Optimization and Regularization for Computational Inverse Problems and Applications" focuses on advances in inversion theory and recent developments with practical applications, particularly emphasizing the combination of optimization and regularization for solving inverse problems. This book covers both the methods, including standard regularization theory, Fejer processes for linear and nonlinear problems, the balancing principle, extrapolated regularization, nonstandard regularization, nonlinear gradient method, the nonmonotone gradient method, subspace method and Lie group method; and the practical applications, such as the reconstruction problem for inverse scattering, molecular spectra data processing, quantitative remote sensing inversion, seismic inversion using the Lie group method, and the gravitational lensing problem. Scientists, researchers and engineers, as well as graduate students engaged in applied mathematics, engineering, geophysics, medical science, image processing, remote sensing and atmospheric science will benefit from this book. Dr. Yanfei Wang is a Professor at the Institute of Geology and Geophysics, Chinese Academy of Sciences, China. Dr. Sc. Anatoly G. Yagola is a Professor and Assistant Dean of the Physical Faculty, Lomonosov Moscow State University, Russia. Dr. Changchun Yang is a Professor and Vice Director of the Institute of Geology and Geophysics, Chinese Academy of Sciences, China.

Computational Methods For Applied Inverse Problems

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Author: Yanfei Wang
Publisher: Walter de Gruyter
ISBN: 3110259052
Size: 73.67 MB
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Computational Methods For Applied Inverse Problems by Yanfei Wang


Original Title: Computational Methods For Applied Inverse Problems

This monograph reports recent advances of inversion theory and recent developments with practical applications in frontiers of sciences, especially inverse design and novel computational methods for inverse problems. Readers who do research in applied mathematics, engineering, geophysics, biomedicine, image processing, remote sensing, and environmental science will benefit from the contents since the book incorporates a background of using statistical and non-statistical methods, e.g., regularization and optimization techniques for solving practical inverse problems.

Hyperpolarized Xenon 129 Magnetic Resonance

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Author: Thomas Meersmann
Publisher: Royal Society of Chemistry
ISBN: 1849738890
Size: 36.20 MB
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Hyperpolarized Xenon 129 Magnetic Resonance by Thomas Meersmann


Original Title: Hyperpolarized Xenon 129 Magnetic Resonance

Providing the first comprehensive book on the current state of hyperpolarized Xenon-129 NMR and MRI, this book is guaranteed to appeal to a wide range of scientists interested in this growing field. It is intended to create synergy between the various communities working with this noble gas. Covering all topics from the production of the hyperpolarized gas to its applications, the editors have invited a leading team of experts to combine the physical chemistry within the various topics and across disciplines. The scope will range from the fundamental aspects of optical pumping to practical aspects of hyperpolarizers and hp-xenon handling. The applications section will focus on hyperpolarized xenon-129 detected in the dissolved phase or micro porous media where the chemical shift of xenon-129 can be used as a diagnostic probe. Appealing to researchers in the biomedical field and materials sciences, this reference book will provide background reading and future looking material in one place.

Chemical Synthesis And Applications Of Graphene And Carbon Materials

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Author: Markus Antonietti
Publisher: John Wiley & Sons
ISBN: 3527332081
Size: 58.10 MB
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Chemical Synthesis And Applications Of Graphene And Carbon Materials by Markus Antonietti


Original Title: Chemical Synthesis And Applications Of Graphene And Carbon Materials

This ready reference and handbook is unique in its focus on synthesis and the application of graphene and other carbon materials with an emphasis on chemistry aspects. To this extent, it deals with top-down and bottom-up approaches across the different length scales for graphene from polycyclic aromatic hydrocarbons to graphene nanoribbons and graphene sheets, as well as carbon materials from quantum dots, nanostructured particles, and fibers, right up to tubes, bulk structures, and much more besides. In so doing, it presents the best synthetic methods: pyrolysis, chemical vapor deposition, templating and surface-mediated synthesis, self-assembly, surface-grafting and modification. Edited by two excellent, experienced and highly renowned editors, both of whom are directors of Max Planck Institutes.

Multidimensional Liquid Chromatography

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Author: Steven A. Cohen
Publisher: John Wiley & Sons
ISBN: 9780470276259
Size: 71.94 MB
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Multidimensional Liquid Chromatography by Steven A. Cohen


Original Title: Multidimensional Liquid Chromatography

Multidimensional Liquid Chromatography (MDLC) is a very powerful separation technique for analyzing exceptionally complex samples in one step. This authoritative reference presents a number of recent contributions that help define the current art and science of MDLC. Topics covered include instrumentation, theory, methods development, and applications of MDLC in the life sciences and in industrial chemistry. With the information to help you perform very difficult separations of complex samples, this reference includes chapters contributed by leading experts or teams of experts.

Kernel Methods For Remote Sensing Data Analysis

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Author: Gustau Camp-Valls
Publisher: John Wiley & Sons
ISBN: 0470749008
Size: 20.39 MB
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Kernel Methods For Remote Sensing Data Analysis by Gustau Camp-Valls


Original Title: Kernel Methods For Remote Sensing Data Analysis

Kernel methods have long been established as effective techniques in the framework of machine learning and pattern recognition, and have now become the standard approach to many remote sensing applications. With algorithms that combine statistics and geometry, kernel methods have proven successful across many different domains related to the analysis of images of the Earth acquired from airborne and satellite sensors, including natural resource control, detection and monitoring of anthropic infrastructures (e.g. urban areas), agriculture inventorying, disaster prevention and damage assessment, and anomaly and target detection. Presenting the theoretical foundations of kernel methods (KMs) relevant to the remote sensing domain, this book serves as a practical guide to the design and implementation of these methods. Five distinct parts present state-of-the-art research related to remote sensing based on the recent advances in kernel methods, analysing the related methodological and practical challenges: Part I introduces the key concepts of machine learning for remote sensing, and the theoretical and practical foundations of kernel methods. Part II explores supervised image classification including Super Vector Machines (SVMs), kernel discriminant analysis, multi-temporal image classification, target detection with kernels, and Support Vector Data Description (SVDD) algorithms for anomaly detection. Part III looks at semi-supervised classification with transductive SVM approaches for hyperspectral image classification and kernel mean data classification. Part IV examines regression and model inversion, including the concept of a kernel unmixing algorithm for hyperspectral imagery, the theory and methods for quantitative remote sensing inverse problems with kernel-based equations, kernel-based BRDF (Bidirectional Reflectance Distribution Function), and temperature retrieval KMs. Part V deals with kernel-based feature extraction and provides a review of the principles of several multivariate analysis methods and their kernel extensions. This book is aimed at engineers, scientists and researchers involved in remote sensing data processing, and also those working within machine learning and pattern recognition.

Advances In Mechanical And Electronic Engineering

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Author: David Jin
Publisher: Springer Science & Business Media
ISBN: 3642315070
Size: 76.71 MB
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Advances In Mechanical And Electronic Engineering by David Jin


Original Title: Advances In Mechanical And Electronic Engineering

This book includes the volume 1 of the proceedings of the 2012 International Conference on Mechanical and Electronic Engineering(ICMEE2012), held at June 23-24,2012 in Hefei, China. The conference provided a rare opportunity to bring together worldwide researchers who are working in the fields. This volume 1 is focusing on Mechanical Engineering and Automation as well as Vehicle Engineering and Technology.

Double Parameterized Regularization Inversion Method For Migration Velocity Analysis In Transversely Isotropic Media With A Vertical Symmetry Axis

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Double Parameterized Regularization Inversion Method For Migration Velocity Analysis In Transversely Isotropic Media With A Vertical Symmetry Axis by


Original Title: Double Parameterized Regularization Inversion Method For Migration Velocity Analysis In Transversely Isotropic Media With A Vertical Symmetry Axis

ABSTRACT Simultaneous estimation of velocity gradients and anisotropic parameters from seismic reflection data is one of the main challenges in transversely isotropic media with a vertical symmetry axis migration velocity analysis. In migration velocity analysis, we usually construct the objective function using the l2 norm along with a linear conjugate gradient scheme to solve the inversion problem. Nevertheless, for seismic data this inversion scheme is not stable and may not converge in finite time. In order to ensure the uniform convergence of parameter inversion and improve the efficiency of migration velocity analysis, this paper develops a double parameterized regularization model and gives the corresponding algorithms. The model is based on the combination of the l2 norm and the non‐smooth l1 norm. For solving such an inversion problem, the quasi‐Newton method is utilized to make the iterative process stable, which can ensure the positive definiteness of the Hessian matrix. Numerical simulation indicates that this method allows fast convergence to the true model and simultaneously generates inversion results with a higher accuracy. Therefore, our proposed method is very promising for practical migration velocity analysis in anisotropic media.

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