Processing oscillatory signals by incoherent feedforward loops

Science.gov (United States)

Zhang, Carolyn; Wu, Feilun; Tsoi, Ryan; Shats, Igor; You, Lingchong

From the timing of amoeba development to the maintenance of stem cell pluripotency,many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression.While networks underlying this signal decoding are diverse,many are built around a common motif, the incoherent feedforward loop (IFFL),where an input simultaneously activates an output and an inhibitor of the output.With appropriate parameters,this motif can generate temporal adaptation,where the system is desensitized to a sustained input.This property serves as the foundation for distinguishing signals with varying temporal profiles.Here,we use quantitative modeling to examine another property of IFFLs,the ability to process oscillatory signals.Our results indicate that the system's ability to translate pulsatile dynamics is limited by two constraints.The kinetics of IFFL components dictate the input range for which the network can decode pulsatile dynamics.In addition,a match between the network parameters and signal characteristics is required for optimal ``counting''.We elucidate one potential mechanism by which information processing occurs in natural networks with implications in the design of synthetic gene circuits for this purpose. This work was partially supported by the National Science Foundation Graduate Research Fellowship (CZ).

Illuminating cell signaling: Using Vibrio harveyi in an introductory biology laboratory.

Science.gov (United States)

Hrizo, Stacy L; Kaufmann, Nancy

2009-05-01

Cell signaling is an essential cellular process that is performed by all living organisms. Bacteria communicate with each other using a chemical language in a signaling pathway that allows bacteria to evaluate the size of their population, determine when they have reached a critical mass (quorum sensing), and then change their behavior in unison to carry out processes that require many cells acting together to be effective. Here, we describe a laboratory exercise in which the students observe the induction of bioluminescence or light production as an output of the quorum sensing pathway in Vibrio harveyi. Using both wildtype and mutant bacterial strains they explore the induction of community behavior via cell-cell communication by determining whether there is a correlation between the density of the bacterial population and the production of light by the bacterial culture. Using data from a cross-feeding assay the students make predictions about the identity of their strains and directly test these predictions using conditioned media from various liquid cultures. This two part exercise is designed for an introductory biology course to begin familiarizing students with collecting data, making predictions based upon the data and directly testing their hypotheses using a model organism with a cell signaling pathway that has a simple visual output: light production. Copyright © 2009 International Union of Biochemistry and Molecular Biology, Inc.

Basic digital signal processing

CERN Document Server

Lockhart, Gordon B

1985-01-01

Basic Digital Signal Processing describes the principles of digital signal processing and experiments with BASIC programs involving the fast Fourier theorem (FFT). The book reviews the fundamentals of the BASIC program, continuous and discrete time signals including analog signals, Fourier analysis, discrete Fourier transform, signal energy, power. The text also explains digital signal processing involving digital filters, linear time-variant systems, discrete time unit impulse, discrete-time convolution, and the alternative structure for second order infinite impulse response (IIR) sections.

General programmed system for physiological signal processing

Energy Technology Data Exchange (ETDEWEB)

Tournier, E; Monge, J; Magnet, C; Sonrel, C

1975-01-01

Improvements made to the general programmed signal acquisition and processing system, Plurimat S, are described, the aim being to obtain a less specialized system adapted to the biological and medical field. In this modified system the acquisition will be simplified. The standard processings offered will be integrated to a real advanced language which will enable the user to create his own processings, the loss of speed being compensated by a greater flexibility and universality. The observation screen will be large and the quality of the recording very good so that a large signal fraction may be displayed. The data will be easily indexed and filed for subsequent display and processing. This system will be used for two kinds of task: it can either be specialized, as an integral part of measurement and diagnostic preparation equipment used routinely in clinical work (e.g. vectocardiographic examination), or its versatility can be used for studies of limited duration to gain information in a given field or to study new diagnosis or treatment methods.

The newest digital signal processing

International Nuclear Information System (INIS)

Lee, Chae Uk

2002-08-01

This book deal with the newest digital signal processing, which contains introduction on conception of digital signal processing, constitution and purpose, signal and system such as signal, continuos signal, discrete signal and discrete system, I/O expression on impress response, convolution, mutual connection of system and frequency character,z transform of definition, range, application of z transform and relationship with laplace transform, Discrete fourier, Fast fourier transform on IDFT algorithm and FFT application, foundation of digital filter of notion, expression, types, frequency characteristic of digital filter and design order of filter, Design order of filter, Design of FIR digital filter, Design of IIR digital filter, Adaptive signal processing, Audio signal processing, video signal processing and application of digital signal processing.

Branching processes in biology

CERN Document Server

Kimmel, Marek

2015-01-01

This book provides a theoretical background of branching processes and discusses their biological applications. Branching processes are a well-developed and powerful set of tools in the field of applied probability. The range of applications considered includes molecular biology, cellular biology, human evolution and medicine. The branching processes discussed include Galton-Watson, Markov, Bellman-Harris, Multitype, and General Processes. As an aid to understanding specific examples, two introductory chapters, and two glossaries are included that provide background material in mathematics and in biology. The book will be of interest to scientists who work in quantitative modeling of biological systems, particularly probabilists, mathematical biologists, biostatisticians, cell biologists, molecular biologists, and bioinformaticians. The authors are a mathematician and cell biologist who have collaborated for more than a decade in the field of branching processes in biology for this new edition. This second ex...

Information theory and signal transduction systems: from molecular information processing to network inference.

Science.gov (United States)

Mc Mahon, Siobhan S; Sim, Aaron; Filippi, Sarah; Johnson, Robert; Liepe, Juliane; Smith, Dominic; Stumpf, Michael P H

2014-11-01

Sensing and responding to the environment are two essential functions that all biological organisms need to master for survival and successful reproduction. Developmental processes are marshalled by a diverse set of signalling and control systems, ranging from systems with simple chemical inputs and outputs to complex molecular and cellular networks with non-linear dynamics. Information theory provides a powerful and convenient framework in which such systems can be studied; but it also provides the means to reconstruct the structure and dynamics of molecular interaction networks underlying physiological and developmental processes. Here we supply a brief description of its basic concepts and introduce some useful tools for systems and developmental biologists. Along with a brief but thorough theoretical primer, we demonstrate the wide applicability and biological application-specific nuances by way of different illustrative vignettes. In particular, we focus on the characterisation of biological information processing efficiency, examining cell-fate decision making processes, gene regulatory network reconstruction, and efficient signal transduction experimental design. Copyright © 2014 Elsevier Ltd. All rights reserved.

Signals, processes, and systems an interactive multimedia introduction to signal processing

CERN Document Server

Karrenberg, Ulrich

2013-01-01

This is a very new concept for learning Signal Processing, not only from the physically-based scientific fundamentals, but also from the didactic perspective, based on modern results of brain research. The textbook together with the DVD form a learning system that provides investigative studies and enables the reader to interactively visualize even complex processes. The unique didactic concept is built on visualizing signals and processes on the one hand, and on graphical programming of signal processing systems on the other. The concept has been designed especially for microelectronics, computer technology and communication. The book allows to develop, modify, and optimize useful applications using DasyLab - a professional and globally supported software for metrology and control engineering. With the 3rd edition, the software is also suitable for 64 bit systems running on Windows 7. Real signals can be acquired, processed and played on the sound card of your computer. The book provides more than 200 pre-pr...

Topological signal processing

CERN Document Server

Robinson, Michael

2014-01-01

Signal processing is the discipline of extracting information from collections of measurements. To be effective, the measurements must be organized and then filtered, detected, or transformed to expose the desired information.  Distortions caused by uncertainty, noise, and clutter degrade the performance of practical signal processing systems. In aggressively uncertain situations, the full truth about an underlying signal cannot be known.  This book develops the theory and practice of signal processing systems for these situations that extract useful, qualitative information using the mathematics of topology -- the study of spaces under continuous transformations.  Since the collection of continuous transformations is large and varied, tools which are topologically-motivated are automatically insensitive to substantial distortion. The target audience comprises practitioners as well as researchers, but the book may also be beneficial for graduate students.

Machine intelligence and signal processing

CERN Document Server

Vatsa, Mayank; Majumdar, Angshul; Kumar, Ajay

2016-01-01

This book comprises chapters on key problems in machine learning and signal processing arenas. The contents of the book are a result of a 2014 Workshop on Machine Intelligence and Signal Processing held at the Indraprastha Institute of Information Technology. Traditionally, signal processing and machine learning were considered to be separate areas of research. However in recent times the two communities are getting closer. In a very abstract fashion, signal processing is the study of operator design. The contributions of signal processing had been to device operators for restoration, compression, etc. Applied Mathematicians were more interested in operator analysis. Nowadays signal processing research is gravitating towards operator learning – instead of designing operators based on heuristics (for example wavelets), the trend is to learn these operators (for example dictionary learning). And thus, the gap between signal processing and machine learning is fast converging. The 2014 Workshop on Machine Intel...

Thematic minireview series: cell biology of G protein signaling.

Science.gov (United States)

Dohlman, Henrik G

2015-03-13

This thematic series is on the topic of cell signaling from a cell biology perspective, with a particular focus on G proteins. G protein-coupled receptors (GPCRs, also known as seven-transmembrane receptors) are typically found at the cell surface. Upon agonist binding, these receptors will activate a GTP-binding G protein at the cytoplasmic face of the plasma membrane. Additionally, there is growing evidence that G proteins can also be activated by non-receptor binding partners, and they can signal from non-plasma membrane compartments. The production of second messengers at multiple, spatially distinct locations represents a type of signal encoding that has been largely neglected. The first minireview in the series describes biosensors that are being used to monitor G protein signaling events in live cells. The second describes the implementation of antibody-based biosensors to dissect endosome signaling by G proteins and their receptors. The third describes the function of a non-receptor, cytoplasmic activator of G protein signaling, called GIV (Girdin). Collectively, the advances described in these articles provide a deeper understanding and emerging opportunities for new pharmacology. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

VLSI signal processing technology

CERN Document Server

Swartzlander, Earl

1994-01-01

This book is the first in a set of forthcoming books focussed on state-of-the-art development in the VLSI Signal Processing area. It is a response to the tremendous research activities taking place in that field. These activities have been driven by two factors: the dramatic increase in demand for high speed signal processing, especially in consumer elec­ tronics, and the evolving microelectronic technologies. The available technology has always been one of the main factors in determining al­ gorithms, architectures, and design strategies to be followed. With every new technology, signal processing systems go through many changes in concepts, design methods, and implementation. The goal of this book is to introduce the reader to the main features of VLSI Signal Processing and the ongoing developments in this area. The focus of this book is on: • Current developments in Digital Signal Processing (DSP) pro­ cessors and architectures - several examples and case studies of existing DSP chips are discussed in...

MICROSLEEPS AND THEIR DETECTION FROM THE BIOLOGICAL SIGNALS

Directory of Open Access Journals (Sweden)

Martin Holub

2017-12-01

Full Text Available Microsleeps (MS are a frequently discussed topic due to their fatal consequences. Their detection is necessary for the purpose of sleep laboratories, where they provide an option for the quantifying rate of sleep deprivation level and objective evaluation of subjective sleepiness. Many studies are dealing with this topic for automotive usage to design a fatigue countermeasure device. We made a research of recent attitude to the development of the automated MS detection methods. We created an overview of several MS detection approaches based on the measurement of biological signals. We also summarized the changes in EEG, EOG and ECG signals, which have been published over the last few years. The reproducible changes in the entire EEG spectrum, primarily with the increased activity of delta and theta, were noticed during a transition to fatigue. There were observed changes of blinking rate and reduction of eye movements during the fatigue tasks. MS correspond with variations in the autonomic regulation of the cardiovascular function, which can be quantified by HRV parameters. The decrease in HR, VLF, and LF/HF before falling asleep was revealed. EEG signal, especially its slow wave activity, considered to be the most predictive and reliable for the level of alertness. In spite of the detection from EEG signal is the most common method, EOG based approaches can also be very efficient and more driver-friendly. Besides, the signal processing in the time domain can improve the detection accuracy of the short events like MS.

Biomedical signal and image processing

CERN Document Server

Najarian, Kayvan

2012-01-01

INTRODUCTION TO DIGITAL SIGNAL AND IMAGE PROCESSINGSignals and Biomedical Signal ProcessingIntroduction and OverviewWhat is a ""Signal""?Analog, Discrete, and Digital SignalsProcessing and Transformation of SignalsSignal Processing for Feature ExtractionSome Characteristics of Digital ImagesSummaryProblemsFourier TransformIntroduction and OverviewOne-Dimensional Continuous Fourier TransformSampling and NYQUIST RateOne-Dimensional Discrete Fourier TransformTwo-Dimensional Discrete Fourier TransformFilter DesignSummaryProblemsImage Filtering, Enhancement, and RestorationIntroduction and Overview

Ultrahigh bandwidth signal processing

DEFF Research Database (Denmark)

Oxenløwe, Leif Katsuo

2016-01-01

Optical time lenses have proven to be very versatile for advanced optical signal processing. Based on a controlled interplay between dispersion and phase-modulation by e.g. four-wave mixing, the processing is phase-preserving, an hence useful for all types of data signals including coherent multi......-level modulation founats. This has enabled processing of phase-modulated spectrally efficient data signals, such as orthogonal frequency division multiplexed (OFDM) signa In that case, a spectral telescope system was used, using two time lenses with different focal lengths (chirp rates), yielding a spectral...... regeneratio These operations require a broad bandwidth nonlinear platform, and novel photonic integrated nonlinear platform like aluminum gallium arsenide nano-waveguides used for 1.28 Tbaud optical signal processing will be described....

Fundamentals of adaptive signal processing

CERN Document Server

Uncini, Aurelio

2015-01-01

This book is an accessible guide to adaptive signal processing methods that equips the reader with advanced theoretical and practical tools for the study and development of circuit structures and provides robust algorithms relevant to a wide variety of application scenarios. Examples include multimodal and multimedia communications, the biological and biomedical fields, economic models, environmental sciences, acoustics, telecommunications, remote sensing, monitoring, and, in general, the modeling and prediction of complex physical phenomena. The reader will learn not only how to design and implement the algorithms but also how to evaluate their performance for specific applications utilizing the tools provided. While using a simple mathematical language, the employed approach is very rigorous. The text will be of value both for research purposes and for courses of study.

Signal processing for radiation detectors

CERN Document Server

Nakhostin, Mohammad

2018-01-01

This book provides a clear understanding of the principles of signal processing of radiation detectors. It puts great emphasis on the characteristics of pulses from various types of detectors and offers a full overview on the basic concepts required to understand detector signal processing systems and pulse processing techniques. Signal Processing for Radiation Detectors covers all of the important aspects of signal processing, including energy spectroscopy, timing measurements, position-sensing, pulse-shape discrimination, and radiation intensity measurement. The book encompasses a wide range of applications so that readers from different disciplines can benefit from all of the information. In addition, this resource: * Describes both analog and digital techniques of signal processing * Presents a complete compilation of digital pulse processing algorithms * Extrapolates content from more than 700 references covering classic papers as well as those of today * Demonstrates concepts with more than 340 origin...

Digital signal processing the Tevatron BPM signals

International Nuclear Information System (INIS)

Cancelo, G.; James, E.; Wolbers, S.

2005-01-01

The Beam Position Monitor (TeV BPM) readout system at Fermilab's Tevatron has been updated and is currently being commissioned. The new BPMs use new analog and digital hardware to achieve better beam position measurement resolution. The new system reads signals from both ends of the existing directional stripline pickups to provide simultaneous proton and antiproton measurements. The signals provided by the two ends of the BPM pickups are processed by analog band-pass filters and sampled by 14-bit ADCs at 74.3MHz. A crucial part of this work has been the design of digital filters that process the signal. This paper describes the digital processing and estimation techniques used to optimize the beam position measurement. The BPM electronics must operate in narrow-band and wide-band modes to enable measurements of closed-orbit and turn-by-turn positions. The filtering and timing conditions of the signals are tuned accordingly for the operational modes. The analysis and the optimized result for each mode are presented

Digital signal processing

CERN Document Server

O'Shea, Peter; Hussain, Zahir M

2011-01-01

In three parts, this book contributes to the advancement of engineering education and that serves as a general reference on digital signal processing. Part I presents the basics of analog and digital signals and systems in the time and frequency domain. It covers the core topics: convolution, transforms, filters, and random signal analysis. It also treats important applications including signal detection in noise, radar range estimation for airborne targets, binary communication systems, channel estimation, banking and financial applications, and audio effects production. Part II considers sel

Signal Processing and Neural Network Simulator

Science.gov (United States)

Tebbe, Dennis L.; Billhartz, Thomas J.; Doner, John R.; Kraft, Timothy T.

1995-04-01

The signal processing and neural network simulator (SPANNS) is a digital signal processing simulator with the capability to invoke neural networks into signal processing chains. This is a generic tool which will greatly facilitate the design and simulation of systems with embedded neural networks. The SPANNS is based on the Signal Processing WorkSystemTM (SPWTM), a commercial-off-the-shelf signal processing simulator. SPW provides a block diagram approach to constructing signal processing simulations. Neural network paradigms implemented in the SPANNS include Backpropagation, Kohonen Feature Map, Outstar, Fully Recurrent, Adaptive Resonance Theory 1, 2, & 3, and Brain State in a Box. The SPANNS was developed by integrating SAIC's Industrial Strength Neural Networks (ISNN) Software into SPW.

Foundations of signal processing

CERN Document Server

Vetterli, Martin; Goyal, Vivek K

2014-01-01

This comprehensive and engaging textbook introduces the basic principles and techniques of signal processing, from the fundamental ideas of signals and systems theory to real-world applications. Students are introduced to the powerful foundations of modern signal processing, including the basic geometry of Hilbert space, the mathematics of Fourier transforms, and essentials of sampling, interpolation, approximation and compression. The authors discuss real-world issues and hurdles to using these tools, and ways of adapting them to overcome problems of finiteness and localisation, the limitations of uncertainty and computational costs. Standard engineering notation is used throughout, making mathematical examples easy for students to follow, understand and apply. It includes over 150 homework problems and over 180 worked examples, specifically designed to test and expand students' understanding of the fundamentals of signal processing, and is accompanied by extensive online materials designed to aid learning, ...

Digital signal processing with kernel methods

CERN Document Server

Rojo-Alvarez, José Luis; Muñoz-Marí, Jordi; Camps-Valls, Gustavo

2018-01-01

A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can quickly get up to speed in order to begin developing the concepts and application software in their own research. Digital Signal Processing with Kernel Methods provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field. It also offers example applications and detailed benchmarking experiments with real and synthetic datasets throughout. Readers can find further worked examples with Matlab source code on a website developed by the authors. * Presents the necess...

Advanced digital signal processing and noise reduction

CERN Document Server

Vaseghi, Saeed V

2008-01-01

Digital signal processing plays a central role in the development of modern communication and information processing systems. The theory and application of signal processing is concerned with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete and noisy and therefore noise reduction, the removal of channel distortion, and replacement of lost samples are important parts of a signal processing system. The fourth edition of Advanced Digital Signal Processing and Noise Reduction updates an

Fast digitizing and digital signal processing of detector signals

International Nuclear Information System (INIS)

Hannaske, Roland

2008-01-01

A fast-digitizer data acquisition system recently installed at the neutron time-of-flight experiment nELBE, which is located at the superconducting electron accelerator ELBE of Forschungszentrum Dresden-Rossendorf, is tested with two different detector types. Preamplifier signals from a high-purity germanium detector are digitized, stored and finally processed. For a precise determination of the energy of the detected radiation, the moving-window deconvolution algorithm is used to compensate the ballistic deficit and different shaping algorithms are applied. The energy resolution is determined in an experiment with γ-rays from a 22 Na source and is compared to the energy resolution achieved with analogously processed signals. On the other hand, signals from the photomultipliers of barium fluoride and plastic scintillation detectors are digitized. These signals have risetimes of a few nanoseconds only. The moment of interaction of the radiation with the detector is determined by methods of digital signal processing. Therefore, different timing algorithms are implemented and tested with data from an experiment at nELBE. The time resolutions achieved with these algorithms are compared to each other as well as to reference values coming from analog signal processing. In addition to these experiments, some properties of the digitizing hardware are measured and a program for the analysis of stored, digitized data is developed. The analysis of the signals shows that the energy resolution achieved with the 10-bit digitizer system used here is not competitive to a 14-bit peak-sensing ADC, although the ballistic deficit can be fully corrected. However, digital methods give better result in sub-ns timing than analog signal processing. (orig.)

SignalPlant: an open signal processing software platform.

Science.gov (United States)

Plesinger, F; Jurco, J; Halamek, J; Jurak, P

2016-07-01

The growing technical standard of acquisition systems allows the acquisition of large records, often reaching gigabytes or more in size as is the case with whole-day electroencephalograph (EEG) recordings, for example. Although current 64-bit software for signal processing is able to process (e.g. filter, analyze, etc) such data, visual inspection and labeling will probably suffer from rather long latency during the rendering of large portions of recorded signals. For this reason, we have developed SignalPlant-a stand-alone application for signal inspection, labeling and processing. The main motivation was to supply investigators with a tool allowing fast and interactive work with large multichannel records produced by EEG, electrocardiograph and similar devices. The rendering latency was compared with EEGLAB and proves significantly faster when displaying an image from a large number of samples (e.g. 163-times faster for 75  ×  10(6) samples). The presented SignalPlant software is available free and does not depend on any other computation software. Furthermore, it can be extended with plugins by third parties ensuring its adaptability to future research tasks and new data formats.

Mathematical modeling of biological processes

CERN Document Server

Friedman, Avner

2014-01-01

This book on mathematical modeling of biological processes includes a wide selection of biological topics that demonstrate the power of mathematics and computational codes in setting up biological processes with a rigorous and predictive framework. Topics include: enzyme dynamics, spread of disease, harvesting bacteria, competition among live species, neuronal oscillations, transport of neurofilaments in axon, cancer and cancer therapy, and granulomas. Complete with a description of the biological background and biological question that requires the use of mathematics, this book is developed for graduate students and advanced undergraduate students with only basic knowledge of ordinary differential equations and partial differential equations; background in biology is not required. Students will gain knowledge on how to program with MATLAB without previous programming experience and how to use codes in order to test biological hypothesis.

Piecewise deterministic processes in biological models

CERN Document Server

Rudnicki, Ryszard

2017-01-01

This book presents a concise introduction to piecewise deterministic Markov processes (PDMPs), with particular emphasis on their applications to biological models. Further, it presents examples of biological phenomena, such as gene activity and population growth, where different types of PDMPs appear: continuous time Markov chains, deterministic processes with jumps, processes with switching dynamics, and point processes. Subsequent chapters present the necessary tools from the theory of stochastic processes and semigroups of linear operators, as well as theoretical results concerning the long-time behaviour of stochastic semigroups induced by PDMPs and their applications to biological models. As such, the book offers a valuable resource for mathematicians and biologists alike. The first group will find new biological models that lead to interesting and often new mathematical questions, while the second can observe how to include seemingly disparate biological processes into a unified mathematical theory, and...

Handbook of Signal Processing in Acoustics

CERN Document Server

Havelock, David; Vorländer, Michael

2009-01-01

The Handbook of Signal Processing in Acoustics presents signal processing as it is practiced in the field of acoustics. The Handbook is organized by areas of acoustics, with recognized leaders coordinating the self-contained chapters of each section. It brings together a wide range of perspectives from over 100 authors to reveal the interdisciplinary nature of signal processing in acoustics. Success in acoustic applications often requires juggling both the acoustic and the signal processing parameters of the problem. This handbook brings the key issues from both into perspective and is complementary to other reference material on the two subjects. It is a unique resource for experts and practitioners alike to find new ideas and techniques within the diversity of signal processing in acoustics.

Signal Processing

International Nuclear Information System (INIS)

Anon.

1992-01-01

Signal processing techniques, extensively used nowadays to maximize the performance of audio and video equipment, have been a key part in the design of hardware and software for high energy physics detectors since pioneering applications in the UA1 experiment at CERN in 1979

Fractional Processes and Fractional-Order Signal Processing Techniques and Applications

CERN Document Server

Sheng, Hu; Qiu, TianShuang

2012-01-01

Fractional processes are widely found in science, technology and engineering systems. In Fractional Processes and Fractional-order Signal Processing, some complex random signals, characterized by the presence of a heavy-tailed distribution or non-negligible dependence between distant observations (local and long memory), are introduced and examined from the ‘fractional’ perspective using simulation, fractional-order modeling and filtering and realization of fractional-order systems. These fractional-order signal processing (FOSP) techniques are based on fractional calculus, the fractional Fourier transform and fractional lower-order moments. Fractional Processes and Fractional-order Signal Processing: • presents fractional processes of fixed, variable and distributed order studied as the output of fractional-order differential systems; • introduces FOSP techniques and the fractional signals and fractional systems point of view; • details real-world-application examples of FOSP techniques to demonstr...

Plant synthetic biology for molecular engineering of signalling and development.

Science.gov (United States)

Nemhauser, Jennifer L; Torii, Keiko U

2016-03-02

Molecular genetic studies of model plants in the past few decades have identified many key genes and pathways controlling development, metabolism and environmental responses. Recent technological and informatics advances have led to unprecedented volumes of data that may uncover underlying principles of plants as biological systems. The newly emerged discipline of synthetic biology and related molecular engineering approaches is built on this strong foundation. Today, plant regulatory pathways can be reconstituted in heterologous organisms to identify and manipulate parameters influencing signalling outputs. Moreover, regulatory circuits that include receptors, ligands, signal transduction components, epigenetic machinery and molecular motors can be engineered and introduced into plants to create novel traits in a predictive manner. Here, we provide a brief history of plant synthetic biology and significant recent examples of this approach, focusing on how knowledge generated by the reference plant Arabidopsis thaliana has contributed to the rapid rise of this new discipline, and discuss potential future directions.

Quantum Biology

Directory of Open Access Journals (Sweden)

Alessandro Sergi

2009-06-01

Full Text Available A critical assessment of the recent developmentsof molecular biology is presented.The thesis that they do not lead to a conceptualunderstanding of life and biological systems is defended.Maturana and Varela's concept of autopoiesis is briefly sketchedand its logical circularity avoided by postulatingthe existence of underlying living processes,entailing amplification from the microscopic to the macroscopic scale,with increasing complexity in the passage from one scale to the other.Following such a line of thought, the currently accepted model of condensed matter, which is based on electrostatics and short-ranged forces,is criticized. It is suggested that the correct interpretationof quantum dispersion forces (van der Waals, hydrogen bonding, and so onas quantum coherence effects hints at the necessity of includinglong-ranged forces (or mechanisms for them incondensed matter theories of biological processes.Some quantum effects in biology are reviewedand quantum mechanics is acknowledged as conceptually important to biology since withoutit most (if not all of the biological structuresand signalling processes would not even exist. Moreover, it is suggested that long-rangequantum coherent dynamics, including electron polarization,may be invoked to explain signal amplificationprocess in biological systems in general.

Cell biology symposium: Membrane trafficking and signal transduction

Science.gov (United States)

In general, membrane trafficking is a broad group of processes where proteins and other large molecules are distributed throughout the cell as well as adjacent extracellular spaces. Whereas signal transduction is a process where signals are transmitted through a series of chemical or molecular event...

Signal processing: opportunities for superconductive circuits

International Nuclear Information System (INIS)

Ralston, R.W.

1985-01-01

Prime motivators in the evolution of increasingly sophisticated communication and detection systems are the needs for handling ever wider signal bandwidths and higher data processing speeds. These same needs drive the development of electronic device technology. Until recently the superconductive community has been tightly focused on digital devices for high speed computers. The purpose of this paper is to describe opportunities and challenges which exist for both analog and digital devices in a less familiar area, that of wideband signal processing. The function and purpose of analog signal-processing components, including matched filters, correlators and Fourier transformers, will be described and examples of superconductive implementations given. A canonic signal-processing system is then configured using these components in combination with analog/digital converters and digital output circuits to highlight the important issues of dynamic range, accuracy and equivalent computation rate. Superconductive circuits hold promise for processing signals of 10-GHz bandwidth. Signal processing systems, however, can be properly designed and implemented only through a synergistic combination of the talents of device physicists, circuit designers, algorithm architects and system engineers. An immediate challenge to the applied superconductivity community is to begin sharing ideas with these other researchers

Fundamentals of statistical signal processing

CERN Document Server

Kay, Steven M

1993-01-01

A unified presentation of parameter estimation for those involved in the design and implementation of statistical signal processing algorithms. Covers important approaches to obtaining an optimal estimator and analyzing its performance; and includes numerous examples as well as applications to real- world problems. MARKETS: For practicing engineers and scientists who design and analyze signal processing systems, i.e., to extract information from noisy signals — radar engineer, sonar engineer, geophysicist, oceanographer, biomedical engineer, communications engineer, economist, statistician, physicist, etc.

Radar signal processing and its applications

CERN Document Server

Hummel, Robert; Stoica, Petre; Zelnio, Edmund

2003-01-01

Radar Signal Processing and Its Applications brings together in one place important contributions and up-to-date research results in this fast-moving area. In twelve selected chapters, it describes the latest advances in architectures, design methods, and applications of radar signal processing. The contributors to this work were selected from the leading researchers and practitioners in the field. This work, originally published as Volume 14, Numbers 1-3 of the journal, Multidimensional Systems and Signal Processing, will be valuable to anyone working or researching in the field of radar signal processing. It serves as an excellent reference, providing insight into some of the most challenging issues being examined today.

Method for increasing nuclear magnetic resonance signals in living biological tissue

International Nuclear Information System (INIS)

Krongrad, A.

1995-01-01

A method of enhancing a magnetic resonance comprising the steps of administering a quantity of a selected magnetic isotope to a living biological tissue at a concentration greater than the naturally occurring concentration of such isotope and detecting magnetic resonance signal from the administered magnetic isotope in the living biological tissue. (author)

Silicon Photonics for Signal Processing of Tbit/s Serial Data Signals

DEFF Research Database (Denmark)

Oxenløwe, Leif Katsuo; Ji, Hua; Galili, Michael

2012-01-01

In this paper, we describe our recent work on signal processing of terabit per second optical serial data signals using pure silicon waveguides. We employ nonlinear optical signal processing in nanoengineered silicon waveguides to perform demultiplexing and optical waveform sampling of 1.28-Tbit/...

Digital signal processing an experimental approach

CERN Document Server

Engelberg, Shlomo

2008-01-01

Digital Signal Processing is a mathematically rigorous but accessible treatment of digital signal processing that intertwines basic theoretical techniques with hands-on laboratory instruction. Divided into three parts, the book covers various aspects of the digital signal processing (DSP) ""problem."" It begins with the analysis of discrete-time signals and explains sampling and the use of the discrete and fast Fourier transforms. The second part of the book???covering digital to analog and analog to digital conversion???provides a practical interlude in the mathematical content before Part II

Signal Conditioning An Introduction to Continuous Wave Communication and Signal Processing

CERN Document Server

Das, Apurba

2012-01-01

"Signal Conditioning” is a comprehensive introduction to electronic signal processing. The book presents the mathematical basics including the implications of various transformed domain representations in signal synthesis and analysis in an understandable and lucid fashion and illustrates the theory through many applications and examples from communication systems. The ease to learn is supported by well-chosen exercises which give readers the flavor of the subject. Supplementary electronic materials available on http://extras.springer.com including MATLAB codes illuminating applications in the domain of one dimensional electrical signal processing, image processing and speech processing. The book is an introduction for students with a basic understanding in engineering or natural sciences.

Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

Science.gov (United States)

Si, Qian

Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.

Signal processing in microdosimetry

International Nuclear Information System (INIS)

Arbel, A.

1984-01-01

Signals occurring in microdosimetric measurements cover a dynamic range of 100 dB at a counting rate which normally stays below 10 4 but could increase significantly in case of an accident. The need for high resolution at low energies, non-linear signal processing to accommodate the specified dynamic range, easy calibration and thermal stability are conflicting requirements which pose formidable design problems. These problems are reviewed, and a practical approach to their solution is given employing a single processing channel. (author)

Neural networks in signal processing

International Nuclear Information System (INIS)

Govil, R.

2000-01-01

Nuclear Engineering has matured during the last decade. In research and design, control, supervision, maintenance and production, mathematical models and theories are used extensively. In all such applications signal processing is embedded in the process. Artificial Neural Networks (ANN), because of their nonlinear, adaptive nature are well suited to such applications where the classical assumptions of linearity and second order Gaussian noise statistics cannot be made. ANN's can be treated as nonparametric techniques, which can model an underlying process from example data. They can also adopt their model parameters to statistical change with time. Algorithms in the framework of Neural Networks in Signal processing have found new applications potentials in the field of Nuclear Engineering. This paper reviews the fundamentals of Neural Networks in signal processing and their applications in tasks such as recognition/identification and control. The topics covered include dynamic modeling, model based ANN's, statistical learning, eigen structure based processing and generalization structures. (orig.)

Radiation signal processing system

International Nuclear Information System (INIS)

Bennett, M.; Knoll, G.; Strange, D.

1980-01-01

An improved signal processing system for radiation imaging apparatus comprises: a radiation transducer producing transducer signals proportional to apparent spatial coordinates of detected radiation events; means for storing true spatial coordinates corresponding to a plurality of predetermined apparent spatial coordinates relative to selected detected radiation events said means for storing responsive to said transducer signal and producing an output signal representative of said true spatial coordinates; and means for interpolating the true spatial coordinates of the detected radiation events located intermediate the stored true spatial coordinates, said means for interpolating communicating with said means for storing

Interactive Teaching of Adaptive Signal Processing

OpenAIRE

Stewart, R W; Harteneck, M; Weiss, S

2000-01-01

Over the last 30 years adaptive digital signal processing has progressed from being a strictly graduate level advanced class in signal processing theory to a topic that is part of the core curriculum for many undergraduate signal processing classes. The key reason is the continued advance of communications technology, with its need for echo control and equalisation, and the widespread use of adaptive filters in audio, biomedical, and control applications. In this paper we will review the basi...

A signal theoretic introduction to random processes

CERN Document Server

Howard, Roy M

2015-01-01

A fresh introduction to random processes utilizing signal theory By incorporating a signal theory basis, A Signal Theoretic Introduction to Random Processes presents a unique introduction to random processes with an emphasis on the important random phenomena encountered in the electronic and communications engineering field. The strong mathematical and signal theory basis provides clarity and precision in the statement of results. The book also features:  A coherent account of the mathematical fundamentals and signal theory that underpin the presented material Unique, in-depth coverage of

Mechanisms of Wnt signaling and control.

Science.gov (United States)

Grainger, Stephanie; Willert, Karl

2018-03-30

The Wnt signaling pathway is a highly conserved system that regulates complex biological processes across all metazoan species. At the cellular level, secreted Wnt proteins serve to break symmetry and provide cells with positional information that is critical to the patterning of the entire body plan. At the organismal level, Wnt signals are employed to orchestrate fundamental developmental processes, including the specification of the anterior-posterior body axis, induction of the primitive streak and ensuing gastrulation movements, and the generation of cell and tissue diversity. Wnt functions extend into adulthood where they regulate stem cell behavior, tissue homeostasis, and damage repair. Disruption of Wnt signaling activity during embryonic development or in adults results in a spectrum of abnormalities and diseases, including cancer. The molecular mechanisms that underlie the myriad of Wnt-regulated biological effects have been the subject of intense research for over three decades. This review is intended to summarize our current understanding of how Wnt signals are generated and interpreted. This article is categorized under: Biological Mechanisms > Cell Signaling Developmental Biology > Stem Cell Biology and Regeneration. © 2018 Wiley Periodicals, Inc.

Advanced optical signal processing of broadband parallel data signals

DEFF Research Database (Denmark)

Oxenløwe, Leif Katsuo; Hu, Hao; Kjøller, Niels-Kristian

2016-01-01

Optical signal processing may aid in reducing the number of active components in communication systems with many parallel channels, by e.g. using telescopic time lens arrangements to perform format conversion and allow for WDM regeneration.......Optical signal processing may aid in reducing the number of active components in communication systems with many parallel channels, by e.g. using telescopic time lens arrangements to perform format conversion and allow for WDM regeneration....

System for monitoring an industrial or biological process

Science.gov (United States)

Gross, Kenneth C.; Wegerich, Stephan W.; Vilim, Rick B.; White, Andrew M.

1998-01-01

A method and apparatus for monitoring and responding to conditions of an industrial process. Industrial process signals, such as repetitive manufacturing, testing and operational machine signals, are generated by a system. Sensor signals characteristic of the process are generated over a time length and compared to reference signals over the time length. The industrial signals are adjusted over the time length relative to the reference signals, the phase shift of the industrial signals is optimized to the reference signals and the resulting signals output for analysis by systems such as SPRT.

Digital Signal Processing applied to Physical Signals

CERN Document Server

Alberto, Diego; Musa, L

2011-01-01

It is well known that many of the scientific and technological discoveries of the XXI century will depend on the capability of processing and understanding a huge quantity of data. With the advent of the digital era, a fully digital and automated treatment can be designed and performed. From data mining to data compression, from signal elaboration to noise reduction, a processing is essential to manage and enhance features of interest after every data acquisition (DAQ) session. In the near future, science will go towards interdisciplinary research. In this work there will be given an example of the application of signal processing to different fields of Physics from nuclear particle detectors to biomedical examinations. In Chapter 1 a brief description of the collaborations that allowed this thesis is given, together with a list of the publications co-produced by the author in these three years. The most important notations, definitions and acronyms used in the work are also provided. In Chapter 2, the last r...

Digital signal processing and spectral analysis for scientists concepts and applications

CERN Document Server

Alessio, Silvia Maria

2016-01-01

This book covers the basics of processing and spectral analysis of monovariate discrete-time signals. The approach is practical, the aim being to acquaint the reader with the indications for and drawbacks of the various methods and to highlight possible misuses. The book is rich in original ideas, visualized in new and illuminating ways, and is structured so that parts can be skipped without loss of continuity. Many examples are included, based on synthetic data and real measurements from the fields of physics, biology, medicine, macroeconomics etc., and a complete set of MATLAB exercises requiring no previous experience of programming is provided. Prior advanced mathematical skills are not needed in order to understand the contents: a good command of basic mathematical analysis is sufficient. Where more advanced mathematical tools are necessary, they are included in an Appendix and presented in an easy-to-follow way. With this book, digital signal processing leaves the domain of engineering to address the ne...

Optimization of carrier frequency and duty cycle for pulse modulation of biological signals.

Science.gov (United States)

Tandon, S N; Singh, S; Sharma, P K; Khosla, S

1980-10-01

Digital modulation techniques are commonly used for the recording and transmission of biological signals. Hitherto, the choice of subcarrier frequency for recording or transmission of biological signals has been arbitary and this usually results in poor signal to noise ratio (SNR) due to the limited frequency characteristics of the system. In the present study the frequency characteristics of the system (first order approximation) has been taken to be that of a Butterworth filter. Computations based on this assumption show that for a given input signal there exists an optimum subcarrier frequency and a corresponding optimum duty cycle which would give maximum SNR of the system. For convenience, a nomogram has been prepared and it has been shown that for a given frequency response of the system, the nomogram could be used for selecting an optimum subcarrier frequency and a corresponding duty cycle. The theoretical formulations have been verified with experimental work.

Electronic devices for analog signal processing

CERN Document Server

Rybin, Yu K

2012-01-01

Electronic Devices for Analog Signal Processing is intended for engineers and post graduates and considers electronic devices applied to process analog signals in instrument making, automation, measurements, and other branches of technology. They perform various transformations of electrical signals: scaling, integration, logarithming, etc. The need in their deeper study is caused, on the one hand, by the extension of the forms of the input signal and increasing accuracy and performance of such devices, and on the other hand, new devices constantly emerge and are already widely used in practice, but no information about them are written in books on electronics. The basic approach of presenting the material in Electronic Devices for Analog Signal Processing can be formulated as follows: the study with help from self-education. While divided into seven chapters, each chapter contains theoretical material, examples of practical problems, questions and tests. The most difficult questions are marked by a diamon...

Wearable System for Acquisition and Monitoring of Biological Signals

Science.gov (United States)

Piccinini, D. J.; Andino, N. B.; Ponce, S. D.; Roberti, MA; López, y. N.

2016-04-01

This paper presents a modular, wearable system for acquisition and wireless transmission of biological signals. Configurable slaves for different signals (such as ECG, EMG, inertial sensors, and temperature) based in the ADS1294 Medical Analog Front End are connected to a Master, based in the CC3200 microcontroller, both from Texas Instruments. The slaves are configurable according to the specific application, providing versatility to the wearable system. The battery consumption is reduced, through a couple of Li-ion batteries and the circuit has also a battery charger. A custom made box was designed and fabricated in a 3D printer, preserving the requirements of low cost, low weight and safety recommendations.

Hybrid Thermochemical/Biological Processing

Science.gov (United States)

Brown, Robert C.

The conventional view of biorefineries is that lignocellulosic plant material will be fractionated into cellulose, hemicellulose, lignin, and terpenes before these components are biochemically converted into market products. Occasionally, these plants include a thermochemical step at the end of the process to convert recalcitrant plant components or mixed waste streams into heat to meet thermal energy demands elsewhere in the facility. However, another possibility for converting high-fiber plant materials is to start by thermochemically processing it into a uniform intermediate product that can be biologically converted into a bio-based product. This alternative route to bio-based products is known as hybrid thermochemical/biological processing. There are two distinct approaches to hybrid processing: (a) gasification followed by fermentation of the resulting gaseous mixture of carbon monoxide (CO), hydrogen (H2), and carbon dioxide (CO2) and (b) fast pyrolysis followed by hydrolysis and/or fermentation of the anhydrosugars found in the resulting bio-oil. This article explores this "cart before the horse" approach to biorefineries.

Lactation Biology Symposium: Lactocrine signaling and developmental programming

Science.gov (United States)

Lactocrine signaling is defined as transmission of bioactive factors from mother to offspring as a consequence of nursing. Lactocrine transmission of signaling molecules may be an evolutionarily conserved process through which bioactive factors necessary for support of neonatal development are deliv...

Handbook of signal processing systems

CERN Document Server

Deprettere, Ed; Leupers, Rainer; Takala, Jarmo

2013-01-01

Handbook of Signal Processing Systems is organized in three parts. The first part motivates representative applications that drive and apply state-of-the art methods for design and implementation of signal processing systems; the second part discusses architectures for implementing these applications; the third part focuses on compilers and simulation tools, describes models of computation and their associated design tools and methodologies. This handbook is an essential tool for professionals in many fields and researchers of all levels.

Development of an Ontology-Directed Signal Processing Toolbox

Energy Technology Data Exchange (ETDEWEB)

Stephen W. Lang

2011-05-27

This project was focused on the development of tools for the automatic configuration of signal processing systems. The goal is to develop tools that will be useful in a variety of Government and commercial areas and useable by people who are not signal processing experts. In order to get the most benefit from signal processing techniques, deep technical expertise is often required in order to select appropriate algorithms, combine them into a processing chain, and tune algorithm parameters for best performance on a specific problem. Therefore a significant benefit would result from the assembly of a toolbox of processing algorithms that has been selected for their effectiveness in a group of related problem areas, along with the means to allow people who are not signal processing experts to reliably select, combine, and tune these algorithms to solve specific problems. Defining a vocabulary for problem domain experts that is sufficiently expressive to drive the configuration of signal processing functions will allow the expertise of signal processing experts to be captured in rules for automated configuration. In order to test the feasibility of this approach, we addressed a lightning classification problem, which was proposed by DOE as a surrogate for problems encountered in nuclear nonproliferation data processing. We coded a toolbox of low-level signal processing algorithms for extracting features of RF waveforms, and demonstrated a prototype tool for screening data. We showed examples of using the tool for expediting the generation of ground-truth metadata, for training a signal recognizer, and for searching for signals with particular characteristics. The public benefits of this approach, if successful, will accrue to Government and commercial activities that face the same general problem - the development of sensor systems for complex environments. It will enable problem domain experts (e.g. analysts) to construct signal and image processing chains without

Principles for integrating reactive species into in vivo biological processes: Examples from exercise physiology.

Science.gov (United States)

Margaritelis, Nikos V; Cobley, James N; Paschalis, Vassilis; Veskoukis, Aristidis S; Theodorou, Anastasios A; Kyparos, Antonios; Nikolaidis, Michalis G

2016-04-01

The equivocal role of reactive species and redox signaling in exercise responses and adaptations is an example clearly showing the inadequacy of current redox biology research to shed light on fundamental biological processes in vivo. Part of the answer probably relies on the extreme complexity of the in vivo redox biology and the limitations of the currently applied methodological and experimental tools. We propose six fundamental principles that should be considered in future studies to mechanistically link reactive species production to exercise responses or adaptations: 1) identify and quantify the reactive species, 2) determine the potential signaling properties of the reactive species, 3) detect the sources of reactive species, 4) locate the domain modified and verify the (ir)reversibility of post-translational modifications, 5) establish causality between redox and physiological measurements, 6) use selective and targeted antioxidants. Fulfilling these principles requires an idealized human experimental setting, which is certainly a utopia. Thus, researchers should choose to satisfy those principles, which, based on scientific evidence, are most critical for their specific research question. Copyright © 2015 Elsevier Inc. All rights reserved.

Advances in heuristic signal processing and applications

CERN Document Server

Chatterjee, Amitava; Siarry, Patrick

2013-01-01

There have been significant developments in the design and application of algorithms for both one-dimensional signal processing and multidimensional signal processing, namely image and video processing, with the recent focus changing from a step-by-step procedure of designing the algorithm first and following up with in-depth analysis and performance improvement to instead applying heuristic-based methods to solve signal-processing problems. In this book the contributing authors demonstrate both general-purpose algorithms and those aimed at solving specialized application problems, with a spec

Fluctuating Thermodynamics for Biological Processes

Science.gov (United States)

Ham, Sihyun

Because biomolecular processes are largely under thermodynamic control, dynamic extension of thermodynamics is necessary to uncover the mechanisms and driving factors of fluctuating processes. The fluctuating thermodynamics technology presented in this talk offers a practical means for the thermodynamic characterization of conformational dynamics in biomolecules. The use of fluctuating thermodynamics has the potential to provide a comprehensive picture of fluctuating phenomena in diverse biological processes. Through the application of fluctuating thermodynamics, we provide a thermodynamic perspective on the misfolding and aggregation of the various proteins associated with human diseases. In this talk, I will present the detailed concepts and applications of the fluctuating thermodynamics technology for elucidating biological processes. This work was supported by Samsung Science and Technology Foundation under Project Number SSTF-BA1401-13.

Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance.

Science.gov (United States)

Poplová, Michaela; Sovka, Pavel; Cifra, Michal

2017-01-01

Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.

Nonlinear filtering for LIDAR signal processing

Directory of Open Access Journals (Sweden)

D. G. Lainiotis

1996-01-01

Full Text Available LIDAR (Laser Integrated Radar is an engineering problem of great practical importance in environmental monitoring sciences. Signal processing for LIDAR applications involves highly nonlinear models and consequently nonlinear filtering. Optimal nonlinear filters, however, are practically unrealizable. In this paper, the Lainiotis's multi-model partitioning methodology and the related approximate but effective nonlinear filtering algorithms are reviewed and applied to LIDAR signal processing. Extensive simulation and performance evaluation of the multi-model partitioning approach and its application to LIDAR signal processing shows that the nonlinear partitioning methods are very effective and significantly superior to the nonlinear extended Kalman filter (EKF, which has been the standard nonlinear filter in past engineering applications.

Application of wavelet transform in seismic signal processing

International Nuclear Information System (INIS)

Ghasemi, M. R.; Mohammadzadeh, A.; Salajeghe, E.

2005-01-01

Wavelet transform is a new tool for signal analysis which can perform a simultaneous signal time and frequency representations. Under Multi Resolution Analysis, one can quickly determine details for signals and their properties using Fast Wavelet Transform algorithms. In this paper, for a better physical understanding of a signal and its basic algorithms, Multi Resolution Analysis together with wavelet transforms in a form of Digital Signal Processing will be discussed. For a Seismic Signal Processing, sets of Orthonormal Daubechies Wavelets are suggested. when dealing with the application of wavelets in SSP, one may discuss about denoising from the signal and data compression existed in the signal, which is important in seismic signal data processing. Using this techniques, EL-Centro and Nagan signals were remodeled with a 25% of total points, resulted in a satisfactory results with an acceptable error drift. Thus a total of 1559 and 2500 points for EL-centro and Nagan seismic curves each, were reduced to 389 and 625 points respectively, with a very reasonable error drift, details of which are recorded in the paper. Finally, the future progress in signal processing, based on wavelet theory will be appointed

Signal processing for cognitive radios

CERN Document Server

Jayaweera, Sudharman K

2014-01-01

This book covers power electronics, in depth, by presenting the basic principles and application details, and it can be used both as a textbook and reference book.  Introduces the specific type of CR that has gained the most research attention in recent years: the CR for Dynamic Spectrum Access (DSA). Provides signal processing solutions to each task by relating the tasks to materials covered in Part II. Specialized chapters then discuss specific signal processing algorithms required for DSA and DSS cognitive radios  

Improved elucidation of biological processes linked to diabetic nephropathy by single probe-based microarray data analysis.

Directory of Open Access Journals (Sweden)

Clemens D Cohen

Full Text Available BACKGROUND: Diabetic nephropathy (DN is a complex and chronic metabolic disease that evolves into a progressive fibrosing renal disorder. Effective transcriptomic profiling of slowly evolving disease processes such as DN can be problematic. The changes that occur are often subtle and can escape detection by conventional oligonucleotide DNA array analyses. METHODOLOGY/PRINCIPAL FINDINGS: We examined microdissected human renal tissue with or without DN using Affymetrix oligonucleotide microarrays (HG-U133A by standard Robust Multi-array Analysis (RMA. Subsequent gene ontology analysis by Database for Annotation, Visualization and Integrated Discovery (DAVID showed limited detection of biological processes previously identified as central mechanisms in the development of DN (e.g. inflammation and angiogenesis. This apparent lack of sensitivity may be associated with the gene-oriented averaging of oligonucleotide probe signals, as this includes signals from cross-hybridizing probes and gene annotation that is based on out of date genomic data. We then examined the same CEL file data using a different methodology to determine how well it could correlate transcriptomic data with observed biology. ChipInspector (CI is based on single probe analysis and de novo gene annotation that bypasses probe set definitions. Both methods, RMA and CI, used at default settings yielded comparable numbers of differentially regulated genes. However, when verified by RT-PCR, the single probe based analysis demonstrated reduced background noise with enhanced sensitivity and fewer false positives. CONCLUSIONS/SIGNIFICANCE: Using a single probe based analysis approach with de novo gene annotation allowed an improved representation of the biological processes linked to the development and progression of DN. The improved analysis was exemplified by the detection of Wnt signaling pathway activation in DN, a process not previously reported to be involved in this disease.

Signal processing in noise waveform radar

CERN Document Server

Kulpa, Krzysztof

2013-01-01

This book is devoted to the emerging technology of noise waveform radar and its signal processing aspects. It is a new kind of radar, which use noise-like waveform to illuminate the target. The book includes an introduction to basic radar theory, starting from classical pulse radar, signal compression, and wave radar. The book then discusses the properties, difficulties and potential of noise radar systems, primarily for low-power and short-range civil applications. The contribution of modern signal processing techniques to making noise radar practical are emphasized, and application examples

Processing of acoustic signal in rock desintegration

Directory of Open Access Journals (Sweden)

Futó Jozef

2002-12-01

Full Text Available For the determination of an effective rock disintegration for a given tool and rock type it is needed to define an optimal disintegration regime. Optimisation of the disintegration process by drilling denotes the finding out an appropriate couple of input parameters of disintegration, i.e. the thrust and revolutions for a quasi-equal rock environment. The disintegration process can be optimised to reach the maximum immediate drilling rate, to reach the minimum specific disintegration energy or to reach the maximum ratio of immediate drilling rate and specific disintegration energy. For the determination of the optimal thrust and revolutions it is needed to monitor the disintegration process. Monitoring of the disintegration process in real conditions is complicated by unfavourable factors, such as the presence of water, dust, vibrations etc. Following our present experience in the monitoring of drilling or full-profile driving, we try to replace the monitoring of input values by monitoring of the scanned acoustic signal. This method of monitoring can extend the optimisation of disintegration process in the technical practice. Its advantage consists in the registration of one acoustic signal by an appropriate microphone. Monitoring of acoustic signal is used also in monitoring of metal machining by milling and turning jobs. The research results of scanning of the acoustic signal in machining of metals are encouraging. Acoustic signal can be processed by different statistical parameters. The paper decribes some results of monitoring of the acoustic signal in rock disintegration on the drilling stand of the Institute of Geotechnics SAS in Košice. The acoustic signal has been registered and processed in no-load run of electric motor, in no-load run of electric motor with a drilling fluid, and in the Ruskov andesite drilling. Registration and processing of the acoustic signal is solved as a part of the research grant task within the basic research

Ultrafast Nonlinear Signal Processing in Silicon Waveguides

DEFF Research Database (Denmark)

Oxenløwe, Leif Katsuo; Mulvad, Hans Christian Hansen; Hu, Hao

2012-01-01

We describe recent demonstrations of exploiting highly nonlinear silicon waveguides for ultrafast optical signal processing. We describe wavelength conversion and serial-to-parallel conversion of 640 Gbit/s data signals and 1.28 Tbit/s demultiplexing and all-optical sampling.......We describe recent demonstrations of exploiting highly nonlinear silicon waveguides for ultrafast optical signal processing. We describe wavelength conversion and serial-to-parallel conversion of 640 Gbit/s data signals and 1.28 Tbit/s demultiplexing and all-optical sampling....

Radar signal analysis and processing using Matlab

CERN Document Server

Mahafza, Bassem R

2008-01-01

Offering radar-related software for the analysis and design of radar waveform and signal processing, this book provides comprehensive coverage of radar signals and signal processing techniques and algorithms. It contains numerous graphical plots, common radar-related functions, table format outputs, and end-of-chapter problems. The complete set of MATLAB[registered] functions and routines are available for download online.

Invariance algorithms for processing NDE signals

Science.gov (United States)

Mandayam, Shreekanth; Udpa, Lalita; Udpa, Satish S.; Lord, William

1996-11-01

Signals that are obtained in a variety of nondestructive evaluation (NDE) processes capture information not only about the characteristics of the flaw, but also reflect variations in the specimen's material properties. Such signal changes may be viewed as anomalies that could obscure defect related information. An example of this situation occurs during in-line inspection of gas transmission pipelines. The magnetic flux leakage (MFL) method is used to conduct noninvasive measurements of the integrity of the pipe-wall. The MFL signals contain information both about the permeability of the pipe-wall and the dimensions of the flaw. Similar operational effects can be found in other NDE processes. This paper presents algorithms to render NDE signals invariant to selected test parameters, while retaining defect related information. Wavelet transform based neural network techniques are employed to develop the invariance algorithms. The invariance transformation is shown to be a necessary pre-processing step for subsequent defect characterization and visualization schemes. Results demonstrating the successful application of the method are presented.

PSpice for digital signal processing

CERN Document Server

Tobin, Paul

2007-01-01

PSpice for Digital Signal Processing is the last in a series of five books using Cadence Orcad PSpice version 10.5 and introduces a very novel approach to learning digital signal processing (DSP). DSP is traditionally taught using Matlab/Simulink software but has some inherent weaknesses for students particularly at the introductory level. The 'plug in variables and play' nature of these software packages can lure the student into thinking they possess an understanding they don't actually have because these systems produce results quicklywithout revealing what is going on. However, it must be

Noise removal in extended depth of field microscope images through nonlinear signal processing.

Science.gov (United States)

Zahreddine, Ramzi N; Cormack, Robert H; Cogswell, Carol J

2013-04-01

Extended depth of field (EDF) microscopy, achieved through computational optics, allows for real-time 3D imaging of live cell dynamics. EDF is achieved through a combination of point spread function engineering and digital image processing. A linear Wiener filter has been conventionally used to deconvolve the image, but it suffers from high frequency noise amplification and processing artifacts. A nonlinear processing scheme is proposed which extends the depth of field while minimizing background noise. The nonlinear filter is generated via a training algorithm and an iterative optimizer. Biological microscope images processed with the nonlinear filter show a significant improvement in image quality and signal-to-noise ratio over the conventional linear filter.

Wavelet data processing of micro-Raman spectra of biological samples

Science.gov (United States)

Camerlingo, C.; Zenone, F.; Gaeta, G. M.; Riccio, R.; Lepore, M.

2006-02-01

A wavelet multi-component decomposition algorithm is proposed for processing data from micro-Raman spectroscopy (μ-RS) of biological tissue. The μ-RS has been recently recognized as a promising tool for the biopsy test and in vivo diagnosis of degenerative human tissue pathologies, due to the high chemical and structural information contents of this spectroscopic technique. However, measurements of biological tissues are usually hampered by typically low-level signals and by the presence of noise and background components caused by light diffusion or fluorescence processes. In order to overcome these problems, a numerical method based on discrete wavelet transform is used for the analysis of data from μ-RS measurements performed in vitro on animal (pig and chicken) tissue samples and, in a preliminary form, on human skin and oral tissue biopsy from normal subjects. Visible light μ-RS was performed using a He-Ne laser and a monochromator with a liquid nitrogen cooled charge coupled device equipped with a grating of 1800 grooves mm-1. The validity of the proposed data procedure has been tested on the well-characterized Raman spectra of reference acetylsalicylic acid samples.

Signal processing for boiling noise detection

International Nuclear Information System (INIS)

Ledwidge, T.J.; Black, J.L.

1989-01-01

The present paper deals with investigations of acoustic signals from a boiling experiment performed on the KNS I loop at KfK Karlsruhe. Signals have been analysed in frequency as well as in time domain. Signal characteristics successfully used to detect the boiling process have been found in time domain. (author). 6 refs, figs

Proceedings of the IEEE Machine Learning for Signal Processing XVII

DEFF Research Database (Denmark)

The seventeenth of a series of workshops sponsored by the IEEE Signal Processing Society and organized by the Machine Learning for Signal Processing Technical Committee (MLSP-TC). The field of machine learning has matured considerably in both methodology and real-world application domains and has...... become particularly important for solution of problems in signal processing. As reflected in this collection, machine learning for signal processing combines many ideas from adaptive signal/image processing, learning theory and models, and statistics in order to solve complex real-world signal processing......, and two papers from the winners of the Data Analysis Competition. The program included papers in the following areas: genomic signal processing, pattern recognition and classification, image and video processing, blind signal processing, models, learning algorithms, and applications of machine learning...

Acoustic MIMO signal processing

CERN Document Server

Huang, Yiteng; Chen, Jingdong

2006-01-01

A timely and important book addressing a variety of acoustic signal processing problems under multiple-input multiple-output (MIMO) scenarios. It uniquely investigates these problems within a unified framework offering a novel and penetrating analysis.

Process Dissociation and Mixture Signal Detection Theory

Science.gov (United States)

DeCarlo, Lawrence T.

2008-01-01

The process dissociation procedure was developed in an attempt to separate different processes involved in memory tasks. The procedure naturally lends itself to a formulation within a class of mixture signal detection models. The dual process model is shown to be a special case. The mixture signal detection model is applied to data from a widely…

Digital signal processing with Matlab examples

CERN Document Server

Giron-Sierra, Jose Maria

2017-01-01

This is the first volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This book includes MATLAB codes to illustrate each of the main steps of the theory, offering a self-contained guide suitable for independent study. The code is embedded in the text, helping readers to put into practice the ideas and methods discussed. The book is divided into three parts, the first of which introduces readers to periodic and non-periodic signals. The second part is devoted to filtering, which is an important and commonly used application. The third part addresses more advanced topics, including the analysis of real-world non-stationary signals and data, e.g. structural fatigue, earthquakes, electro-encephalograms, birdsong, etc. The book’s last chapter focuses on modulation, an example of the intentional use of non-stationary signals.

Digital signal processing for NDT

International Nuclear Information System (INIS)

Georgel, B.

1994-01-01

NDT begins to adapt and use the most recent developments of digital signal and image processing. We briefly sum up the main characteristics of NDT situations (particularly noise and inverse problem formulation) and comment on techniques already used or just emerging (SAFT, split spectrum, adaptive learning network, noise reference filtering, stochastic models, neural networks). This survey is focused on ultrasonics, eddy currents and X-ray radiography. The final objective of end users (availability of automatic diagnosis systems) cannot be achieved only by signal processing algorithms. A close cooperation with other techniques such as artificial intelligence has therefore to be implemented. (author). 20 refs

A Friendly-Biological Reactor SIMulator (BioReSIM for studying biological processes in wastewater treatment processes

Directory of Open Access Journals (Sweden)

Raul Molina

2014-12-01

Full Text Available Biological processes for wastewater treatments are inherently dynamic systems because of the large variations in the influent wastewater flow rate, concentration composition and the adaptive behavior of the involved microorganisms. Moreover, the sludge retention time (SRT is a critical factor to understand the bioreactor performances when changes in the influent or in the operation conditions take place. Since SRT are usually in the range of 10-30 days, the performance of biological reactors needs a long time to be monitored in a regular laboratory demonstration, limiting the knowledge that can be obtained in the experimental lab practice. In order to overcome this lack, mathematical models and computer simulations are useful tools to describe biochemical processes and predict the overall performance of bioreactors under different working operation conditions and variations of the inlet wastewater composition. The mathematical solution of the model could be difficult as numerous biochemical processes can be considered. Additionally, biological reactors description (mass balance, etc. needs models represented by partial or/and ordinary differential equations associated to algebraic expressions, that require complex computational codes to obtain the numerical solutions. Different kind of software for mathematical modeling can be used, from large degree of freedom simulators capable of free models definition (as AQUASIM, to closed predefined model structure programs (as BIOWIN. The first ones usually require long learning curves, whereas the second ones could be excessively rigid for specific wastewater treatment systems. As alternative, we present Biological Reactor SIMulator (BioReSIM, a MATLAB code for the simulation of sequencing batch reactors (SBR and rotating biological contactors (RBC as biological systems of suspended and attached biomass for wastewater treatment, respectively. This BioReSIM allows the evaluation of simple and complex

Signal processing methods for MFE plasma diagnostics

International Nuclear Information System (INIS)

Candy, J.V.; Casper, T.; Kane, R.

1985-02-01

The application of various signal processing methods to extract energy storage information from plasma diamagnetism sensors occurring during physics experiments on the Tandom Mirror Experiment-Upgrade (TMX-U) is discussed. We show how these processing techniques can be used to decrease the uncertainty in the corresponding sensor measurements. The algorithms suggested are implemented using SIG, an interactive signal processing package developed at LLNL

All-optical signal processing of OTDM and OFDM signals based on time-domain Optical Fourier Transformation

DEFF Research Database (Denmark)

Clausen, Anders; Guan, Pengyu; Mulvad, Hans Christian Hansen

2014-01-01

All-optical time-domain Optical Fourier Transformation utilised for signal processing of ultra-high-speed OTDM signals and OFDM signals will be presented.......All-optical time-domain Optical Fourier Transformation utilised for signal processing of ultra-high-speed OTDM signals and OFDM signals will be presented....

Financial signal processing and machine learning

CERN Document Server

Kulkarni,Sanjeev R; Dmitry M. Malioutov

2016-01-01

The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analy...

Graphics processing units in bioinformatics, computational biology and systems biology.

Science.gov (United States)

Nobile, Marco S; Cazzaniga, Paolo; Tangherloni, Andrea; Besozzi, Daniela

2017-09-01

Several studies in Bioinformatics, Computational Biology and Systems Biology rely on the definition of physico-chemical or mathematical models of biological systems at different scales and levels of complexity, ranging from the interaction of atoms in single molecules up to genome-wide interaction networks. Traditional computational methods and software tools developed in these research fields share a common trait: they can be computationally demanding on Central Processing Units (CPUs), therefore limiting their applicability in many circumstances. To overcome this issue, general-purpose Graphics Processing Units (GPUs) are gaining an increasing attention by the scientific community, as they can considerably reduce the running time required by standard CPU-based software, and allow more intensive investigations of biological systems. In this review, we present a collection of GPU tools recently developed to perform computational analyses in life science disciplines, emphasizing the advantages and the drawbacks in the use of these parallel architectures. The complete list of GPU-powered tools here reviewed is available at http://bit.ly/gputools. © The Author 2016. Published by Oxford University Press.

Signals and Systems in Biomedical Engineering Signal Processing and Physiological Systems Modeling

CERN Document Server

Devasahayam, Suresh R

2013-01-01

The use of digital signal processing is ubiquitous in the field of physiology and biomedical engineering. The application of such mathematical and computational tools requires a formal or explicit understanding of physiology. Formal models and analytical techniques are interlinked in physiology as in any other field. This book takes a unitary approach to physiological systems, beginning with signal measurement and acquisition, followed by signal processing, linear systems modelling, and computer simulations. The signal processing techniques range across filtering, spectral analysis and wavelet analysis. Emphasis is placed on fundamental understanding of the concepts as well as solving numerical problems. Graphs and analogies are used extensively to supplement the mathematics. Detailed models of nerve and muscle at the cellular and systemic levels provide examples for the mathematical methods and computer simulations. Several of the models are sufficiently sophisticated to be of value in understanding real wor...

Television picture signal processing

NARCIS (Netherlands)

1998-01-01

Field or frame memories are often used in television receivers for video signal processing functions, such as noise reduction and/or flicker reduction. Television receivers also have graphic features such as teletext, menu-driven control systems, multilingual subtitling, an electronic TV-Guide, etc.

Wavelets and multiscale signal processing

CERN Document Server

Cohen, Albert

1995-01-01

Since their appearance in mid-1980s, wavelets and, more generally, multiscale methods have become powerful tools in mathematical analysis and in applications to numerical analysis and signal processing. This book is based on "Ondelettes et Traitement Numerique du Signal" by Albert Cohen. It has been translated from French by Robert D. Ryan and extensively updated by both Cohen and Ryan. It studies the existing relations between filter banks and wavelet decompositions and shows how these relations can be exploited in the context of digital signal processing. Throughout, the book concentrates on the fundamentals. It begins with a chapter on the concept of multiresolution analysis, which contains complete proofs of the basic results. The description of filter banks that are related to wavelet bases is elaborated in both the orthogonal case (Chapter 2), and in the biorthogonal case (Chapter 4). The regularity of wavelets, how this is related to the properties of the filters and the importance of regularity for t...

Correlation of Respiratory Signals and Electrocardiogram Signals via Empirical Mode Decomposition

KAUST Repository

El Fiky, Ahmed Osama

2011-05-24

Recently Electrocardiogram (ECG) signals are being broadly used as an essential diagnosing tool in different clinical applications as they carry a reliable representation not only for cardiac activities, but also for other associated biological processes, like respiration. However, the process of recording and collecting them has usually suffered from the presence of some undesired noises, which in turn affects the reliability of such representations.Therefore, de-noising ECG signals became a hot research field for signal processing experts to ensure better and clear representation of the different cardiac activities. Given the nonlinear and non-stationary properties of ECGs, it is not a simple task to cancel the undesired noise terms without affecting the biological physics of them. In this study, we are interested in correlating the ECG signals with respiratory parameters, specifically the lung volume and lung pressure. We have focused on the concept of de-noising ECG signals by means of signal decomposition using an algorithm called the Empirical Mode Decomposition (EMD) where the original ECG signals are being decomposed into a set of intrinsic mode functions (IMF). Then, we have provided criteria based on which some of these IMFs have been adapted to reconstruct de-noised ECG version. Finally, we have utilized de-noised ECGs as well as IMFs for to study the correlation with lung volume and lung pressure. These correlation studies have showed some clear resemblance especially between the oscillations of ECGs and lung pressures.

Non-commutative tomography and signal processing

International Nuclear Information System (INIS)

Mendes, R Vilela

2015-01-01

Non-commutative tomography is a technique originally developed and extensively used by Professors M A Man’ko and V I Man’ko in quantum mechanics. Because signal processing deals with operators that, in general, do not commute with time, the same technique has a natural extension to this domain. Here, a review is presented of the theory and some applications of non-commutative tomography for time series as well as some new results on signal processing on graphs. (paper)

Signalign: An Ontology of DNA as Signal for Comparative Gene Structure Prediction Using Information-Coding-and-Processing Techniques.

Science.gov (United States)

Yu, Ning; Guo, Xuan; Gu, Feng; Pan, Yi

2016-03-01

Conventional character-analysis-based techniques in genome analysis manifest three main shortcomings-inefficiency, inflexibility, and incompatibility. In our previous research, a general framework, called DNA As X was proposed for character-analysis-free techniques to overcome these shortcomings, where X is the intermediates, such as digit, code, signal, vector, tree, graph network, and so on. In this paper, we further implement an ontology of DNA As Signal, by designing a tool named Signalign for comparative gene structure analysis, in which DNA sequences are converted into signal series, processed by modified method of dynamic time warping and measured by signal-to-noise ratio (SNR). The ontology of DNA As Signal integrates the principles and concepts of other disciplines including information coding theory and signal processing into sequence analysis and processing. Comparing with conventional character-analysis-based methods, Signalign can not only have the equivalent or superior performance, but also enrich the tools and the knowledge library of computational biology by extending the domain from character/string to diverse areas. The evaluation results validate the success of the character-analysis-free technique for improved performances in comparative gene structure prediction.

The Signal Validation method of Digital Process Instrumentation System on signal conditioner for SMART

International Nuclear Information System (INIS)

Moon, Hee Gun; Park, Sang Min; Kim, Jung Seon; Shon, Chang Ho; Park, Heui Youn; Koo, In Soo

2005-01-01

The function of PIS(Process Instrumentation System) for SMART is to acquire the process data from sensor or transmitter. The PIS consists of signal conditioner, A/D converter, DSP(Digital Signal Process) and NIC(Network Interface Card). So, It is fully digital system after A/D converter. The PI cabinet and PDAS(Plant Data Acquisition System) in commercial plant is responsible for data acquisition of the sensor or transmitter include RTD, TC, level, flow, pressure and so on. The PDAS has the software that processes each sensor data and PI cabinet has the signal conditioner, which is need for maintenance and test. The signal conditioner has the potentiometer to adjust the span and zero for test and maintenance. The PIS of SMART also has the signal conditioner which has the span and zero adjust same as the commercial plant because the signal conditioner perform the signal condition for AD converter such as 0∼10Vdc. But, To adjust span and zero is manual test and calibration. So, This paper presents the method of signal validation and calibration, which is used by digital feature in SMART. There are I/E(current to voltage), R/E(resistor to voltage), F/E(frequency to voltage), V/V(voltage to voltage). Etc. In this paper show only the signal validation and calibration about I/E converter that convert level, pressure, flow such as 4∼20mA into signal for AD conversion such as 0∼10Vdc

Processing Electromyographic Signals to Recognize Words

Science.gov (United States)

Jorgensen, C. C.; Lee, D. D.

2009-01-01

A recently invented speech-recognition method applies to words that are articulated by means of the tongue and throat muscles but are otherwise not voiced or, at most, are spoken sotto voce. This method could satisfy a need for speech recognition under circumstances in which normal audible speech is difficult, poses a hazard, is disturbing to listeners, or compromises privacy. The method could also be used to augment traditional speech recognition by providing an additional source of information about articulator activity. The method can be characterized as intermediate between (1) conventional speech recognition through processing of voice sounds and (2) a method, not yet developed, of processing electroencephalographic signals to extract unspoken words directly from thoughts. This method involves computational processing of digitized electromyographic (EMG) signals from muscle innervation acquired by surface electrodes under a subject's chin near the tongue and on the side of the subject s throat near the larynx. After preprocessing, digitization, and feature extraction, EMG signals are processed by a neural-network pattern classifier, implemented in software, that performs the bulk of the recognition task as described.

Digital signal processing application in nuclear spectroscopy

Directory of Open Access Journals (Sweden)

O. V. Zeynalova

2009-06-01

Full Text Available Digital signal processing algorithms for nuclear particle spectroscopy are described along with a digital pile-up elimination method applicable to equidistantly sampled detector signals pre-processed by a charge-sensitive preamplifier. The signal processing algorithms provided as recursive one- or multi-step procedures which can be easily programmed using modern computer programming languages. The influence of the number of bits of the sampling analogue-to-digital converter to the final signal-to-noise ratio of the spectrometer considered. Algorithms for a digital shaping-filter amplifier, for a digital pile-up elimination scheme and for ballistic deficit correction were investigated using a high purity germanium detector. The pile-up elimination method was originally developed for fission fragment spectroscopy using a Frisch-grid back-to-back double ionisation chamber and was mainly intended for pile-up elimination in case of high alpha-radioactivity of the fissile target. The developed pile-up elimination method affects only the electronic noise generated by the preamplifier. Therefore, the influence of the pile-up elimination scheme on the final resolution of the spectrometer investigated in terms of the distance between piled-up pulses. The efficiency of developed algorithms compared with other signal processing schemes published in literature.

Signal processing for smart cards

Science.gov (United States)

Quisquater, Jean-Jacques; Samyde, David

2003-06-01

In 1998, Paul Kocher showed that when a smart card computes cryptographic algorithms, for signatures or encryption, its consumption or its radiations leak information. The keys or the secrets hidden in the card can then be recovered using a differential measurement based on the intercorrelation function. A lot of silicon manufacturers use desynchronization countermeasures to defeat power analysis. In this article we detail a new resynchronization technic. This method can be used to facilitate the use of a neural network to do the code recognition. It becomes possible to reverse engineer a software code automatically. Using data and clock separation methods, we show how to optimize the synchronization using signal processing. Then we compare these methods with watermarking methods for 1D and 2D signal. The very last watermarking detection improvements can be applied to signal processing for smart cards with very few modifications. Bayesian processing is one of the best ways to do Differential Power Analysis, and it is possible to extract a PIN code from a smart card in very few samples. So this article shows the need to continue to set up effective countermeasures for cryptographic processors. Although the idea to use advanced signal processing operators has been commonly known for a long time, no publication explains that results can be obtained. The main idea of differential measurement is to use the cross-correlation of two random variables and to repeat consumption measurements on the processor to be analyzed. We use two processors clocked at the same external frequency and computing the same data. The applications of our design are numerous. Two measurements provide the inputs of a central operator. With the most accurate operator we can improve the signal noise ratio, re-synchronize the acquisition clock with the internal one, or remove jitter. The analysis based on consumption or electromagnetic measurements can be improved using our structure. At first sight

All-optical signal processing data communication and storage applications

CERN Document Server

Eggleton, Benjamin

2015-01-01

This book provides a comprehensive review of the state-of-the art of optical signal processing technologies and devices. It presents breakthrough solutions for enabling a pervasive use of optics in data communication and signal storage applications. It presents presents optical signal processing as solution to overcome the capacity crunch in communication networks. The book content ranges from the development of innovative materials and devices, such as graphene and slow light structures, to the use of nonlinear optics for secure quantum information processing and overcoming the classical Shannon limit on channel capacity and microwave signal processing. Although it holds the promise for a substantial speed improvement, today’s communication infrastructure optics remains largely confined to the signal transport layer, as it lags behind electronics as far as signal processing is concerned. This situation will change in the near future as the tremendous growth of data traffic requires energy efficient and ful...

Digital signal processing theory and practice

CERN Document Server

Rao, K Deergha

2018-01-01

The book provides a comprehensive exposition of all major topics in digital signal processing (DSP). With numerous illustrative examples for easy understanding of the topics, it also includes MATLAB-based examples with codes in order to encourage the readers to become more confident of the fundamentals and to gain insights into DSP. Further, it presents real-world signal processing design problems using MATLAB and programmable DSP processors. In addition to problems that require analytical solutions, it discusses problems that require solutions using MATLAB at the end of each chapter. Divided into 13 chapters, it addresses many emerging topics, which are not typically found in advanced texts on DSP. It includes a chapter on adaptive digital filters used in the signal processing problems for faster acceptable results in the presence of changing environments and changing system requirements. Moreover, it offers an overview of wavelets, enabling readers to easily understand the basics and applications of this po...

Grating geophone signal processing based on wavelet transform

Science.gov (United States)

Li, Shuqing; Zhang, Huan; Tao, Zhifei

2008-12-01

Grating digital geophone is designed based on grating measurement technique benefiting averaging-error effect and wide dynamic range to improve weak signal detected precision. This paper introduced the principle of grating digital geophone and its post signal processing system. The signal acquisition circuit use Atmega 32 chip as core part and display the waveform on the Labwindows through the RS232 data link. Wavelet transform is adopted this paper to filter the grating digital geophone' output signal since the signal is unstable. This data processing method is compared with the FIR filter that widespread use in current domestic. The result indicates that the wavelet algorithm has more advantages and the SNR of seismic signal improve obviously.

An introduction to digital signal processing

CERN Document Server

Karl, John H

1989-01-01

An Introduction to Digital Signal Processing is written for those who need to understand and use digital signal processing and yet do not wish to wade through a multi-semester course sequence. Using only calculus-level mathematics, this book progresses rapidly through the fundamentals to advanced topics such as iterative least squares design of IIR filters, inverse filters, power spectral estimation, and multidimensional applications--all in one concise volume.This book emphasizes both the fundamental principles and their modern computer implementation. It presents and demonstrates how si

Interleukins and their signaling pathways in the Reactome biological pathway database.

Science.gov (United States)

Jupe, Steve; Ray, Keith; Roca, Corina Duenas; Varusai, Thawfeek; Shamovsky, Veronica; Stein, Lincoln; D'Eustachio, Peter; Hermjakob, Henning

2018-04-01

There is a wealth of biological pathway information available in the scientific literature, but it is spread across many thousands of publications. Alongside publications that contain definitive experimental discoveries are many others that have been dismissed as spurious, found to be irreproducible, or are contradicted by later results and consequently now considered controversial. Many descriptions and images of pathways are incomplete stylized representations that assume the reader is an expert and familiar with the established details of the process, which are consequently not fully explained. Pathway representations in publications frequently do not represent a complete, detailed, and unambiguous description of the molecules involved; their precise posttranslational state; or a full account of the molecular events they undergo while participating in a process. Although this might be sufficient to be interpreted by an expert reader, the lack of detail makes such pathways less useful and difficult to understand for anyone unfamiliar with the area and of limited use as the basis for computational models. Reactome was established as a freely accessible knowledge base of human biological pathways. It is manually populated with interconnected molecular events that fully detail the molecular participants linked to published experimental data and background material by using a formal and open data structure that facilitates computational reuse. These data are accessible on a Web site in the form of pathway diagrams that have descriptive summaries and annotations and as downloadable data sets in several formats that can be reused with other computational tools. The entire database and all supporting software can be downloaded and reused under a Creative Commons license. Pathways are authored by expert biologists who work with Reactome curators and editorial staff to represent the consensus in the field. Pathways are represented as interactive diagrams that include as

Signal processing techniques for sodium boiling noise detection

International Nuclear Information System (INIS)

1989-05-01

At the Specialists' Meeting on Sodium Boiling Detection organized by the International Working Group on Fast Reactors (IWGFR) of the International Atomic Energy Agency at Chester in the United Kingdom in 1981 various methods of detecting sodium boiling were reported. But, it was not possible to make a comparative assessment of these methods because the signal condition in each experiment was different from others. That is why participants of this meeting recommended that a benchmark test should be carried out in order to evaluate and compare signal processing methods for boiling detection. Organization of the Co-ordinated Research Programme (CRP) on signal processing techniques for sodium boiling noise detection was also recommended at the 16th meeting of the IWGFR. The CRP on Signal Processing Techniques for Sodium Boiling Noise Detection was set up in 1984. Eight laboratories from six countries have agreed to participate in this CRP. The overall objective of the programme was the development of reliable on-line signal processing techniques which could be used for the detection of sodium boiling in an LMFBR core. During the first stage of the programme a number of existing processing techniques used by different countries have been compared and evaluated. In the course of further work, an algorithm for implementation of this sodium boiling detection system in the nuclear reactor will be developed. It was also considered that the acoustic signal processing techniques developed for boiling detection could well make a useful contribution to other acoustic applications in the reactor. This publication consists of two parts. Part I is the final report of the co-ordinated research programme on signal processing techniques for sodium boiling noise detection. Part II contains two introductory papers and 20 papers presented at four research co-ordination meetings since 1985. A separate abstract was prepared for each of these 22 papers. Refs, figs and tabs

An energy-efficient communication method based on the relationships between biological signals for ubiquitous health monitoring.

Science.gov (United States)

Kwon, Hyok Chon; Na, Doosu; Ko, Byung Geun; Lee, Songjun

2008-01-01

Wireless sensor networks have been studied in the area of intelligent transportation systems, disaster perception, environment monitoring, ubiquitous healthcare, home network, and so on. For the ubiquitous healthcare, the previous systems collect the sensed health related data at portable devices without regard to correlations of various biological signals to determine the health conditions. It is not the energy-efficient method to gather a lot of information into a specific node to decide the health condition. Since the biological signals are related with each other to estimate certain body condition, it is necessary to be collected selectively by their relationship for energy efficiency of the networked nodes. One of researches about low power consumption is the reduction of the amount of packet transmission. In this paper, a health monitoring system, which allows the transmission of the reduced number of packets by means of setting the routing path considered the relations of biological signals, is proposed.

High-speed optical coherence tomography signal processing on GPU

International Nuclear Information System (INIS)

Li Xiqi; Shi Guohua; Zhang Yudong

2011-01-01

The signal processing speed of spectral domain optical coherence tomography (SD-OCT) has become a bottleneck in many medical applications. Recently, a time-domain interpolation method was proposed. This method not only gets a better signal-to noise ratio (SNR) but also gets a faster signal processing time for the SD-OCT than the widely used zero-padding interpolation method. Furthermore, the re-sampled data is obtained by convoluting the acquired data and the coefficients in time domain. Thus, a lot of interpolations can be performed concurrently. So, this interpolation method is suitable for parallel computing. An ultra-high optical coherence tomography signal processing can be realized by using graphics processing unit (GPU) with computer unified device architecture (CUDA). This paper will introduce the signal processing steps of SD-OCT on GPU. An experiment is performed to acquire a frame SD-OCT data (400A-linesx2048 pixel per A-line) and real-time processed the data on GPU. The results show that it can be finished in 6.208 milliseconds, which is 37 times faster than that on Central Processing Unit (CPU).

Analogue Signal Processing: Collected Papers 1994-95

DEFF Research Database (Denmark)

1996-01-01

This document is a collection of the papers presented at international conferences and in international journals by the analogue signal processing group of Electronics Institute, Technical University of Denmark, in 1994 and 1995.......This document is a collection of the papers presented at international conferences and in international journals by the analogue signal processing group of Electronics Institute, Technical University of Denmark, in 1994 and 1995....

Detection, Characterization, and Biological Effect of Quorum-Sensing Signaling Molecules in Peanut-Nodulating Bradyrhizobia

Directory of Open Access Journals (Sweden)

Walter Giordano

2012-03-01

Full Text Available Bacteria of the genus Bradyrhizobium are able to establish a symbiotic relationship with peanut (Arachis hypogaea root cells and to fix atmospheric nitrogen by converting it to nitrogenous compounds. Quorum sensing (QS is a cell-cell communication mechanism employed by a variety of bacterial species to coordinate behavior at a community level through regulation of gene expression. The QS process depends on bacterial production of various signaling molecules, among which the N-acylhomoserine lactones (AHLs are most commonly used by Gram-negative bacteria. Some previous reports have shown the production of QS signaling molecules by various rhizobia, but little is known regarding mechanisms of communication among peanut-nodulating strains. The aims of this study were to identify and characterize QS signals produced by peanut-nodulating bradyrhizobial strains and to evaluate their effects on processes related to cell interaction. Detection of AHLs in 53 rhizobial strains was performed using the biosensor strains Agrobacterium tumefaciens NTL4 (pZLR4 and Chromobacterium violaceum CV026 for AHLs with long and short acyl chains, respectively. None of the strains screened were found to produce AHLs with short acyl chains, but 14 strains produced AHLs with long acyl chains. These 14 AHL-producing strains were further studied by quantification of β-galactosidase activity levels (AHL-like inducer activity in NTL4 (pZLR4. Strains displaying moderate to high levels of AHL-like inducer activity were subjected to chemical identification of signaling molecules by high-performance liquid chromatography coupled to mass spectrometry (LC-MS/MS. For each AHL-producing strain, we found at least four different AHLs, corresponding to N-hexanoyl-DL-homoserine lactone (C6, N-(3-oxodecanoyl-L-homoserine lactone (3OC10, N-(3-oxododecanoyl-L-homoserine lactone (3OC12, and N-(3-oxotetradecanoyl-L-homoserine lactone (3OC14. Biological roles of 3OC10, 3OC12, and 3OC14 AHLs

Hot topics: Signal processing in acoustics

Science.gov (United States)

Gaumond, Charles F.

2005-09-01

Signal processing in acoustics is a multidisciplinary group of people that work in many areas of acoustics. We have chosen two areas that have shown exciting new applications of signal processing to acoustics or have shown exciting and important results from the use of signal processing. In this session, two hot topics are shown: the use of noiselike acoustic fields to determine sound propagation structure and the use of localization to determine animal behaviors. The first topic shows the application of correlation on geo-acoustic fields to determine the Greens function for propagation through the Earth. These results can then be further used to solve geo-acoustic inverse problems. The first topic also shows the application of correlation using oceanic noise fields to determine the Greens function through the ocean. These results also have utility for oceanic inverse problems. The second topic shows exciting results from the detection, localization, and tracking of marine mammals by two different groups. Results from detection and localization of bullfrogs are shown, too. Each of these studies contributed to the knowledge of animal behavior. [Work supported by ONR.

Proceedings of IEEE Machine Learning for Signal Processing Workshop XV

DEFF Research Database (Denmark)

Larsen, Jan

These proceedings contains refereed papers presented at the Fifteenth IEEE Workshop on Machine Learning for Signal Processing (MLSP’2005), held in Mystic, Connecticut, USA, September 28-30, 2005. This is a continuation of the IEEE Workshops on Neural Networks for Signal Processing (NNSP) organized...... by the NNSP Technical Committee of the IEEE Signal Processing Society. The name of the Technical Committee, hence of the Workshop, was changed to Machine Learning for Signal Processing in September 2003 to better reflect the areas represented by the Technical Committee. The conference is organized...... by the Machine Learning for Signal Processing Technical Committee with sponsorship of the IEEE Signal Processing Society. Following the practice started two years ago, the bound volume of the proceedings is going to be published by IEEE following the Workshop, and we are pleased to offer to conference attendees...

Transcript and hormone analyses reveal the involvement of ABA-signalling, hormone crosstalk and genotype-specific biological processes in cold-shock response in wheat

Czech Academy of Sciences Publication Activity Database

Kalapos, S.; Dobrev, Petre; Nagy, T.; Vítámvás, P.; Gyorgyey, J.; Kocsy, G.; Marincs, F.; Galiba, G.

2016-01-01

Roč. 253, DEC (2016), s. 86-97 ISSN 0168-9452 Institutional support: RVO:61389030 Keywords : complex phytohormone responses * abscisic-acid biosynthesis * frost-resistance * stress responses * gene-expression * chromosome 5a * triticum-monococcum * regulatory network * basal resistance * abiotic stresses * ABA-Signalling * Carbon metabolism * Freezing-tolerance * Gene ontology * Plant hormones * Short-term cold-shock * Triticum aestivum Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.437, year: 2016

Signal Processing Methods Monitor Cranial Pressure

Science.gov (United States)

2010-01-01

Dr. Norden Huang, of Goddard Space Flight Center, invented a set of algorithms (called the Hilbert-Huang Transform, or HHT) for analyzing nonlinear and nonstationary signals that developed into a user-friendly signal processing technology for analyzing time-varying processes. At an auction managed by Ocean Tomo Federal Services LLC, licenses of 10 U.S. patents and 1 domestic patent application related to HHT were sold to DynaDx Corporation, of Mountain View, California. DynaDx is now using the licensed NASA technology for medical diagnosis and prediction of brain blood flow-related problems, such as stroke, dementia, and traumatic brain injury.

Receptor downregulation and desensitization enhance the information processing ability of signalling receptors

Directory of Open Access Journals (Sweden)

Resat Haluk

2007-11-01

Full Text Available Abstract Background In addition to initiating signaling events, the activation of cell surface receptors also triggers regulatory processes that restrict the duration of signaling. Acute attenuation of signaling can be accomplished either via ligand-induced internalization of receptors (endocytic downregulation or via ligand-induced receptor desensitization. These phenomena have traditionally been viewed in the context of adaptation wherein the receptor system enters a refractory state in the presence of sustained ligand stimuli and thereby prevents the cell from over-responding to the ligand. Here we use the epidermal growth factor receptor (EGFR and G-protein coupled receptors (GPCR as model systems to respectively examine the effects of downregulation and desensitization on the ability of signaling receptors to decode time-varying ligand stimuli. Results Using a mathematical model, we show that downregulation and desensitization mechanisms can lead to tight and efficient input-output coupling thereby ensuring synchronous processing of ligand inputs. Frequency response analysis indicates that upstream elements of the EGFR and GPCR networks behave like low-pass filters with the system being able to faithfully transduce inputs below a critical frequency. Receptor downregulation and desensitization increase the filter bandwidth thereby enabling the receptor systems to decode inputs in a wider frequency range. Further, system-theoretic analysis reveals that the receptor systems are analogous to classical mechanical over-damped systems. This analogy enables us to metaphorically describe downregulation and desensitization as phenomena that make the systems more resilient in responding to ligand perturbations thereby improving the stability of the system resting state. Conclusion Our findings suggest that in addition to serving as mechanisms for adaptation, receptor downregulation and desensitization can play a critical role in temporal information

Software for biomedical engineering signal processing laboratory experiments.

Science.gov (United States)

Tompkins, Willis J; Wilson, J

2009-01-01

In the early 1990's we developed a special computer program called UW DigiScope to provide a mechanism for anyone interested in biomedical digital signal processing to study the field without requiring any other instrument except a personal computer. There are many digital filtering and pattern recognition algorithms used in processing biomedical signals. In general, students have very limited opportunity to have hands-on access to the mechanisms of digital signal processing. In a typical course, the filters are designed non-interactively, which does not provide the student with significant understanding of the design constraints of such filters nor their actual performance characteristics. UW DigiScope 3.0 is the first major update since version 2.0 was released in 1994. This paper provides details on how the new version based on MATLAB! works with signals, including the filter design tool that is the programming interface between UW DigiScope and processing algorithms.

IEEE International Workshop on Machine Learning for Signal Processing: Preface

DEFF Research Database (Denmark)

Tao, Jianhua

The 21st IEEE International Workshop on Machine Learning for Signal Processing will be held in Beijing, China, on September 18–21, 2011. The workshop series is the major annual technical event of the IEEE Signal Processing Society's Technical Committee on Machine Learning for Signal Processing...

Book: Marine Bioacoustic Signal Processing and Analysis

Science.gov (United States)

2011-09-30

physicists , and mathematicians . However, more and more biologists and psychologists are starting to use advanced signal processing techniques and...Book: Marine Bioacoustic Signal Processing and Analysis 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT ...chapters than it should be, since the project must be finished by Dec. 31. I have started setting aside 2 hours of uninterrupted per workday to work

Analogue Signal Processing: Collected Papers 1996-97

DEFF Research Database (Denmark)

1997-01-01

This document is a collection of the papers presented at international conferences and in international journals by the analogue signal processing group of the Department of Information Technology, Technical University of Denmark, in 1996 and 1997.......This document is a collection of the papers presented at international conferences and in international journals by the analogue signal processing group of the Department of Information Technology, Technical University of Denmark, in 1996 and 1997....

Spies and Bloggers: New Synthetic Biology Tools to Understand Microbial Processes in Soils and Sediments

Science.gov (United States)

Masiello, C. A.; Silberg, J. J.; Cheng, H. Y.; Del Valle, I.; Fulk, E. M.; Gao, X.; Bennett, G. N.

2017-12-01

Microbes can be programmed through synthetic biology to report on their behavior, informing researchers when their environment has triggered changes in their gene expression (e.g. in response to shifts in O2 or H2O), or when they have participated in a specific step of an elemental cycle (e.g. denitrification). This use of synthetic biology has the potential to significantly improve our understanding of microbes' roles in elemental and water cycling, because it allows reporting on the environment from the perspective of a microbe, matching the measurement scale exactly to the scale that a microbe experiences. However, synthetic microbes have not yet seen wide use in soil and sediment laboratory experiments because synthetic organisms typically report by fluorescing, making their signals difficult to detect outside the petri dish. We are developing a new suite of microbial programs that report instead by releasing easily-detected gases, allowing the real-time, noninvasive monitoring of behaviors in sediments and soils. Microbial biosensors can, in theory, be programmed to detect dynamic processes that contribute to a wide range of geobiological processes, including C cycling (biofilm production, methanogenesis, and synthesis of extracellular enzymes that degrade organic matter), N cycling (expression of enzymes that underlie different steps of the N cycle) and potentially S cycling. We will provide an overview of the potential uses of gas-reporting biosensors in soil and sediment lab experiments, and will report the development of the systematics of these sensors. Successful development of gas biosensors for laboratory use will require addressing issues including: engineering the intensity and selectivity of microbial gas production to maximize the signal to noise ratio; normalizing the gas reporter signal to cell population size, managing gas diffusion effects on signal shape; and developing multiple gases that can be used in parallel.

Biological Systems Thinking for Control Engineering Design

Directory of Open Access Journals (Sweden)

D. J. Murray-Smith

2004-01-01

Full Text Available Artificial neural networks and genetic algorithms are often quoted in discussions about the contribution of biological systems thinking to engineering design. This paper reviews work on the neuromuscular system, a field in which biological systems thinking could make specific contributions to the development and design of automatic control systems for mechatronics and robotics applications. The paper suggests some specific areas in which a better understanding of this biological control system could be expected to contribute to control engineering design methods in the future. Particular emphasis is given to the nonlinear nature of elements within the neuromuscular system and to processes of neural signal processing, sensing and system adaptivity. Aspects of the biological system that are of particular significance for engineering control systems include sensor fusion, sensor redundancy and parallelism, together with advanced forms of signal processing for adaptive and learning control. 

Introductory Biology Textbooks Under-Represent Scientific Process

Directory of Open Access Journals (Sweden)

Dara B. Duncan

2011-08-01

Full Text Available Attrition of undergraduates from Biology majors is a long-standing problem. Introductory courses that fail to engage students or spark their curiosity by emphasizing the open-ended and creative nature of biological investigation and discovery could contribute to student detachment from the field. Our hypothesis was that introductory biology books devote relatively few figures to illustration of the design and interpretation of experiments or field studies, thereby de-emphasizing the scientific process.To investigate this possibility, we examined figures in six Introductory Biology textbooks published in 2008. On average, multistep scientific investigations were presented in fewer than 5% of the hundreds of figures in each book. Devoting such a small percentage of figures to the processes by which discoveries are made discourages an emphasis on scientific thinking. We suggest that by increasing significantly the illustration of scientific investigations, textbooks could support undergraduates’ early interest in biology, stimulate the development of design and analytical skills, and inspire some students to participate in investigations of their own.

Modeling laser velocimeter signals as triply stochastic Poisson processes

Science.gov (United States)

Mayo, W. T., Jr.

1976-01-01

Previous models of laser Doppler velocimeter (LDV) systems have not adequately described dual-scatter signals in a manner useful for analysis and simulation of low-level photon-limited signals. At low photon rates, an LDV signal at the output of a photomultiplier tube is a compound nonhomogeneous filtered Poisson process, whose intensity function is another (slower) Poisson process with the nonstationary rate and frequency parameters controlled by a random flow (slowest) process. In the present paper, generalized Poisson shot noise models are developed for low-level LDV signals. Theoretical results useful in detection error analysis and simulation are presented, along with measurements of burst amplitude statistics. Computer generated simulations illustrate the difference between Gaussian and Poisson models of low-level signals.

Signal Processing in Medical Ultrasound B-mode Imaging

International Nuclear Information System (INIS)

Song, Tai Kyong

2000-01-01

Ultrasonic imaging is the most widely used modality among modern imaging device for medical diagnosis and the system performance has been improved dramatically since early 90's due to the rapid advances in DSP performance and VLSI technology that made it possible to employ more sophisticated algorithms. This paper describes 'main stream' digital signal processing functions along with the associated implementation considerations in modern medical ultrasound imaging systems. Topics covered include signal processing methods for resolution improvement, ultrasound imaging system architectures, roles and necessity of the applications of DSP and VLSI technology in the development of the medical ultrasound imaging systems, and array signal processing techniques for ultrasound focusing

Deficient Biological Motion Perception in Schizophrenia: Results from a Motion Noise Paradigm

Directory of Open Access Journals (Sweden)

Jejoong eKim

2013-07-01

Full Text Available Background: Schizophrenia patients exhibit deficient processing of perceptual and cognitive information. However, it is not well understood how basic perceptual deficits contribute to higher level cognitive problems in this mental disorder. Perception of biological motion, a motion-based cognitive recognition task, relies on both basic visual motion processing and social cognitive processing, thus providing a useful paradigm to evaluate the potentially hierarchical relationship between these two levels of information processing. Methods: In this study, we designed a biological motion paradigm in which basic visual motion signals were manipulated systematically by incorporating different levels of motion noise. We measured the performances of schizophrenia patients (n=21 and healthy controls (n=22 in this biological motion perception task, as well as in coherent motion detection, theory of mind, and a widely used biological motion recognition task. Results: Schizophrenia patients performed the biological motion perception task with significantly lower accuracy than healthy controls when perceptual signals were moderately degraded by noise. A more substantial degradation of perceptual signals, through using additional noise, impaired biological motion perception in both groups. Performance levels on biological motion recognition, coherent motion detection and theory of mind tasks were also reduced in patients. Conclusion: The results from the motion-noise biological motion paradigm indicate that in the presence of visual motion noise, the processing of biological motion information in schizophrenia is deficient. Combined with the results of poor basic visual motion perception (coherent motion task and biological motion recognition, the association between basic motion signals and biological motion perception suggests a need to incorporate the improvement of visual motion perception in social cognitive remediation.

Oxygen in human health from life to death – An approach to teaching redox biology and signaling to graduate and medical students

Directory of Open Access Journals (Sweden)

Margaret M. Briehl

2015-08-01

Full Text Available In the absence of oxygen human life is measured in minutes. In the presence of oxygen, normal metabolism generates reactive species (ROS that have the potential to cause cell injury contributing to human aging and disease. Between these extremes, organisms have developed means for sensing oxygen and ROS and regulating their cellular processes in response. Redox signaling contributes to the control of cell proliferation and death. Aberrant redox signaling underlies many human diseases. The attributes acquired by altered redox homeostasis in cancer cells illustrate this particularly well. This teaching review and the accompanying illustrations provide an introduction to redox biology and signaling aimed at instructors of graduate and medical students.

Ultra-Fast Optical Signal Processing in Nonlinear Silicon Waveguides

DEFF Research Database (Denmark)

Oxenløwe, Leif Katsuo; Galili, Michael; Pu, Minhao

2011-01-01

We describe recent demonstrations of exploiting highly nonlinear silicon nanowires for processing Tbit/s optical data signals. We perform demultiplexing and optical waveform sampling of 1.28 Tbit/s and wavelength conversion of 640 Gbit/s data signals.......We describe recent demonstrations of exploiting highly nonlinear silicon nanowires for processing Tbit/s optical data signals. We perform demultiplexing and optical waveform sampling of 1.28 Tbit/s and wavelength conversion of 640 Gbit/s data signals....

A soft-core processor architecture optimised for radar signal processing applications

CSIR Research Space (South Africa)

Broich, R

2013-12-01

Full Text Available -performance soft-core processing architecture is proposed. To develop such a processing architecture, data and signal-flow characteristics of common radar signal processing algorithms are analysed. Each algorithm is broken down into signal processing...

SignalPlant: an open signal processing software platform

Czech Academy of Sciences Publication Activity Database

Plešinger, Filip; Jurčo, Juraj; Halámek, Josef; Jurák, Pavel

2016-01-01

Roč. 37, č. 7 (2016), N38-N48 ISSN 0967-3334 R&D Projects: GA ČR GAP103/11/0933; GA MŠk(CZ) LO1212; GA ČR GAP102/12/2034 Institutional support: RVO:68081731 Keywords : data visualization * software * signal processing * ECG * EEG Subject RIV: FS - Medical Facilities ; Equipment Impact factor: 2.058, year: 2016

Digital signal processing for He3 proportional counter

International Nuclear Information System (INIS)

Zeynalov, Sh.S.; Ahmadov, Q.S.

2010-01-01

Full text : Data acquisition systems for nuclear spectroscopy have traditionally been based on systems with analog shaping amplifiers followed by analog-to-digital converters. Recently, however, new systems based on digital signal processing make possible to replace the analog shaping and timing circuitry the numerical algorithms to derive properties of the pulse such as its amplitude. DSP is a fully numerical analysis of the detector pulse signals and this technique demonstrates significant advantages over analog systems in some circumstances. From a mathematical point of view, one can consider the signal evolution from the detector to the ADC as a sequence of transformations that can be described by precisely defined mathematical expressions. Digital signal processing with ADCs has the possibility to utilize further information on the signal pulses from radiation detectors. In the experiment each step of the signal generation in the 3He filled proportional counter was described using digital signal processing techniques (DSP). The electronic system has consisted of a detector, a preamplifier and a digital oscilloscope. The pulses from the detector were digitized using a digital storage oscilloscope. This oscilloscope allowed signal digitization with accuracy of 8 bit (256 levels) and with frequency of up to 5 * 10 8 samples/s. As a neutron source was used Cf-252. To obtain detector output current pulse I(t) created by the motions of the ions/electrons pairs was written an algorithm which can easily be programmed using modern computer programming languages.

Phonocardiography Signal Processing

CERN Document Server

Abbas, Abbas K

2009-01-01

The auscultation method is an important diagnostic indicator for hemodynamic anomalies. Heart sound classification and analysis play an important role in the auscultative diagnosis. The term phonocardiography refers to the tracing technique of heart sounds and the recording of cardiac acoustics vibration by means of a microphone-transducer. Therefore, understanding the nature and source of this signal is important to give us a tendency for developing a competent tool for further analysis and processing, in order to enhance and optimize cardiac clinical diagnostic approach. This book gives the

Proceedings of IEEE Machine Learning for Signal Processing Workshop XVI

DEFF Research Database (Denmark)

Larsen, Jan

These proceedings contains refereed papers presented at the sixteenth IEEE Workshop on Machine Learning for Signal Processing (MLSP'2006), held in Maynooth, Co. Kildare, Ireland, September 6-8, 2006. This is a continuation of the IEEE Workshops on Neural Networks for Signal Processing (NNSP......). The name of the Technical Committee, hence of the Workshop, was changed to Machine Learning for Signal Processing in September 2003 to better reflect the areas represented by the Technical Committee. The conference is organized by the Machine Learning for Signal Processing Technical Committee...... the same standard as the printed version and facilitates the reading and searching of the papers. The field of machine learning has matured considerably in both methodology and real-world application domains and has become particularly important for solution of problems in signal processing. As reflected...

Digital signal processing algorithms for nuclear particle spectroscopy

International Nuclear Information System (INIS)

Zejnalova, O.; Zejnalov, Sh.; Hambsch, F.J.; Oberstedt, S.

2007-01-01

Digital signal processing algorithms for nuclear particle spectroscopy are described along with a digital pile-up elimination method applicable to equidistantly sampled detector signals pre-processed by a charge-sensitive preamplifier. The signal processing algorithms are provided as recursive one- or multi-step procedures which can be easily programmed using modern computer programming languages. The influence of the number of bits of the sampling analogue-to-digital converter on the final signal-to-noise ratio of the spectrometer is considered. Algorithms for a digital shaping-filter amplifier, for a digital pile-up elimination scheme and for ballistic deficit correction were investigated using a high purity germanium detector. The pile-up elimination method was originally developed for fission fragment spectroscopy using a Frisch-grid back-to-back double ionization chamber and was mainly intended for pile-up elimination in case of high alpha-radioactivity of the fissile target. The developed pile-up elimination method affects only the electronic noise generated by the preamplifier. Therefore the influence of the pile-up elimination scheme on the final resolution of the spectrometer is investigated in terms of the distance between pile-up pulses. The efficiency of the developed algorithms is compared with other signal processing schemes published in literature

Registration and processing of acoustic signal in rock drilling

Directory of Open Access Journals (Sweden)

Futó Jozef

2002-03-01

Full Text Available For the determination of an effective rock disintegration for a given tool and rock type it is needed to define an optimal disintegration regime. Optimisation of the disintegration process by drilling denotes the finding out an appropriate couple of input parameters of disintegration, i.e. the thrust and revolutions for a quasi-equal rock environment. The disintegration process can be optimised to reach the maximum immediate drilling rate, to reach the minimum specific disintegration energy or to reach the maximum ratio of immediate drilling rate and specific disintegration energy. For the determination of the optimal thrust and revolutions it is needed to monitor the disintegration process. Monitoring of the disintegration process in real conditions is complicated by unfavourable factors, such as the presence of water, dust, vibrations etc. Following our present experience in the monitoring of drilling or full-profile driving, we try to replace the monitoring of input values by monitoring of the scanned acoustic signal. This method of monitoring can extend the optimisation of disintegration process in the technical practice. Its advantage consists in the registration of one acoustic signal by an appropriate microphone. Monitoring of acoustic signal is used also in monitoring of metal machining by milling and turning jobs. The research results of scanning of the acoustic signal in machining of metals are encouraging. Acoustic signal can be processed by different statistical parameters. The paper decribes some results of monitoring of the acoustic signal in rock disintegration on the drilling stand of the Institute of Geotechnics SAS in Košice. The acoustic signal has been registered and processed in no-load run of electric motor, in no-load run of electric motor with a drilling fluid, and in the Ruskov andesite drilling. Registration and processing of the acoustic signal is solved as a part of the research grant task within the basic research

Profile of science process skills of Preservice Biology Teacher in General Biology Course

Science.gov (United States)

Susanti, R.; Anwar, Y.; Ermayanti

2018-04-01

This study aims to obtain portrayal images of science process skills among preservice biology teacher. This research took place in Sriwijaya University and involved 41 participants. To collect the data, this study used multiple choice test comprising 40 items to measure the mastery of science process skills. The data were then analyzed in descriptive manner. The results showed that communication aspect outperfomed the other skills with that 81%; while the lowest one was identifying variables and predicting (59%). In addition, basic science process skills was 72%; whereas for integrated skills was a bit lower, 67%. In general, the capability of doing science process skills varies among preservice biology teachers.

Deep Learning in Visual Computing and Signal Processing

OpenAIRE

Xie, Danfeng; Zhang, Lei; Bai, Li

2017-01-01

Deep learning is a subfield of machine learning, which aims to learn a hierarchy of features from input data. Nowadays, researchers have intensively investigated deep learning algorithms for solving challenging problems in many areas such as image classification, speech recognition, signal processing, and natural language processing. In this study, we not only review typical deep learning algorithms in computer vision and signal processing but also provide detailed information on how to apply...

Removing Background Noise with Phased Array Signal Processing

Science.gov (United States)

Podboy, Gary; Stephens, David

2015-01-01

Preliminary results are presented from a test conducted to determine how well microphone phased array processing software could pull an acoustic signal out of background noise. The array consisted of 24 microphones in an aerodynamic fairing designed to be mounted in-flow. The processing was conducted using Functional Beam forming software developed by Optinav combined with cross spectral matrix subtraction. The test was conducted in the free-jet of the Nozzle Acoustic Test Rig at NASA GRC. The background noise was produced by the interaction of the free-jet flow with the solid surfaces in the flow. The acoustic signals were produced by acoustic drivers. The results show that the phased array processing was able to pull the acoustic signal out of the background noise provided the signal was no more than 20 dB below the background noise level measured using a conventional single microphone equipped with an aerodynamic forebody.

Detectors and signal processing for high-energy physics

International Nuclear Information System (INIS)

Rehak, P.

1981-01-01

Basic principles of the particle detection and signal processing for high-energy physics experiments are presented. It is shown that the optimum performance of a properly designed detector system is not limited by incidental imperfections, but solely by more fundamental limitations imposed by the quantum nature and statistical behavior of matter. The noise sources connected with the detection and signal processing are studied. The concepts of optimal filtering and optimal detector/amplifying device matching are introduced. Signal processing for a liquid argon calorimeter is analyzed in some detail. The position detection in gas counters is studied. Resolution in drift chambers for the drift coordinate measurement as well as the second coordinate measurement is discussed

Digital signals processing using non-linear orthogonal transformation in frequency domain

Directory of Open Access Journals (Sweden)

Ivanichenko E.V.

2017-12-01

Full Text Available The rapid progress of computer technology in recent decades led to a wide introduction of methods of digital information processing practically in all fields of scientific research. In this case, among various applications of computing one of the most important places is occupied by digital processing systems signals (DSP that are used in data processing remote solution tasks of navigation of aerospace and marine objects, communications, radiophysics, digital optics and in a number of other applications. Digital Signal Processing (DSP is a dynamically developing an area that covers both technical and software tools. Related areas for digital signal processing are theory information, in particular, the theory of optimal signal reception and theory pattern recognition. In the first case, the main problem is signal extraction against a background of noise and interference of a different physical nature, and in the second - automatic recognition, i.e. classification and signal identification. In the digital processing of signals under a signal, we mean its mathematical description, i.e. a certain real function, containing information on the state or behavior of a physical system under an event that can be defined on a continuous or discrete space of time variation or spatial coordinates. In the broad sense, DSP systems mean a complex algorithmic, hardware and software. As a rule, systems contain specialized technical means of preliminary (or primary signal processing and special technical means for secondary processing of signals. Means of pretreatment are designed to process the original signals observed in general case against a background of random noise and interference of a different physical nature and represented in the form of discrete digital samples, for the purpose of detecting and selection (selection of the useful signal and evaluation characteristics of the detected signal. A new method of digital signal processing in the frequency

Attracting and repelling in homogeneous signal processes

International Nuclear Information System (INIS)

Downarowicz, T; Grzegorek, P; Lacroix, Y

2010-01-01

Attracting and repelling are discussed on two levels: in abstract signal processes and in signal processes arising as returns to a fixed set in an ergodic dynamical system. In the first approach, among other things, we give three examples in which the sum of two Poisson (hence neutral—neither attracting nor repelling) processes comes out either neutral or attracting, or repelling, depending on how the two processes depend on each other. The main new result of the second type concerns so-called 'composite events' in the form of a union of all cylinders over blocks belonging to the δ-ball in the Hamming distance around a fixed block. We prove that in a typical ergodic nonperiodic process the majority of such 'composite events' reveal strong attracting. We discuss the practical interpretation of this result

Multivariate Analysis for the Processing of Signals

Directory of Open Access Journals (Sweden)

Beattie J.R.

2014-01-01

Full Text Available Real-world experiments are becoming increasingly more complex, needing techniques capable of tracking this complexity. Signal based measurements are often used to capture this complexity, where a signal is a record of a sample’s response to a parameter (e.g. time, displacement, voltage, wavelength that is varied over a range of values. In signals the responses at each value of the varied parameter are related to each other, depending on the composition or state sample being measured. Since signals contain multiple information points, they have rich information content but are generally complex to comprehend. Multivariate Analysis (MA has profoundly transformed their analysis by allowing gross simplification of the tangled web of variation. In addition MA has also provided the advantage of being much more robust to the influence of noise than univariate methods of analysis. In recent years, there has been a growing awareness that the nature of the multivariate methods allows exploitation of its benefits for purposes other than data analysis, such as pre-processing of signals with the aim of eliminating irrelevant variations prior to analysis of the signal of interest. It has been shown that exploiting multivariate data reduction in an appropriate way can allow high fidelity denoising (removal of irreproducible non-signals, consistent and reproducible noise-insensitive correction of baseline distortions (removal of reproducible non-signals, accurate elimination of interfering signals (removal of reproducible but unwanted signals and the standardisation of signal amplitude fluctuations. At present, the field is relatively small but the possibilities for much wider application are considerable. Where signal properties are suitable for MA (such as the signal being stationary along the x-axis, these signal based corrections have the potential to be highly reproducible, and highly adaptable and are applicable in situations where the data is noisy or

2012 Proceedings of the International Conference on Communications, Signal Processing, and Systems

CERN Document Server

Wang, Wei; Mu, Jiasong; Liang, Jing; Zhang, Baoju; Pi, Yiming; Zhao, Chenglin

2012-01-01

Communications, Signal Processing, and Systems is a collection of contributions coming out of the International Conference on Communications, Signal Processing, and Systems (CSPS) held October 2012. This book provides the state-of-art developments of Communications, Signal Processing, and Systems, and their interactions in multidisciplinary fields, such as Smart Grid. The book also examines Radar Systems, Sensor Networks, Radar Signal Processing, Design and Implementation of Signal Processing Systems and Applications. Written by experts and students in the fields of Communications, Signal Processing, and Systems.

Discrete random signal processing and filtering primer with Matlab

CERN Document Server

Poularikas, Alexander D

2013-01-01

Engineers in all fields will appreciate a practical guide that combines several new effective MATLAB® problem-solving approaches and the very latest in discrete random signal processing and filtering.Numerous Useful Examples, Problems, and Solutions - An Extensive and Powerful ReviewWritten for practicing engineers seeking to strengthen their practical grasp of random signal processing, Discrete Random Signal Processing and Filtering Primer with MATLAB provides the opportunity to doubly enhance their skills. The author, a leading expert in the field of electrical and computer engineering, offe

Advanced Signal Processing for Wireless Multimedia Communications

Directory of Open Access Journals (Sweden)

Xiaodong Wang

2000-01-01

Full Text Available There is at present a worldwide effort to develop next-generation wireless communication systems. It is envisioned that many of the future wireless systems will incorporate considerable signal-processing intelligence in order to provide advanced services such as multimedia transmission. In general, wireless channels can be very hostile media through which to communicate, due to substantial physical impediments, primarily radio-frequency interference and time-arying nature of the channel. The need of providing universal wireless access at high data-rate (which is the aim of many merging wireless applications presents a major technical challenge, and meeting this challenge necessitates the development of advanced signal processing techniques for multiple-access communications in non-stationary interference-rich environments. In this paper, we present some key advanced signal processing methodologies that have been developed in recent years for interference suppression in wireless networks. We will focus primarily on the problem of jointly suppressing multiple-access interference (MAI and intersymbol interference (ISI, which are the limiting sources of interference for the high data-rate wireless systems being proposed for many emerging application areas, such as wireless multimedia. We first present a signal subspace approach to blind joint suppression of MAI and ISI. We then discuss a powerful iterative technique for joint interference suppression and decoding, so-called Turbo multiuser detection, that is especially useful for wireless multimedia packet communications. We also discuss space-time processing methods that employ multiple antennas for interference rejection and signal enhancement. Finally, we touch briefly on the problems of suppressing narrowband interference and impulsive ambient noise, two other sources of radio-frequency interference present in wireless multimedia networks.

Signal and image processing in medical applications

CERN Document Server

Kumar, Amit; Rahim, B Abdul; Kumar, D Sravan

2016-01-01

This book highlights recent findings on and analyses conducted on signals and images in the area of medicine. The experimental investigations involve a variety of signals and images and their methodologies range from very basic to sophisticated methods. The book explains how signal and image processing methods can be used to detect and forecast abnormalities in an easy-to-follow manner, offering a valuable resource for researchers, engineers, physicians and bioinformatics researchers alike.

Streamlining digital signal processing a tricks of the trade guidebook

CERN Document Server

2012-01-01

Streamlining Digital Signal Processing, Second Edition, presents recent advances in DSP that simplify or increase the computational speed of common signal processing operations and provides practical, real-world tips and tricks not covered in conventional DSP textbooks. It offers new implementations of digital filter design, spectrum analysis, signal generation, high-speed function approximation, and various other DSP functions. It provides:Great tips, tricks of the trade, secrets, practical shortcuts, and clever engineering solutions from seasoned signal processing professionalsAn assortment.

Synchronization of developmental processes and defense signaling by growth regulating transcription factors.

Directory of Open Access Journals (Sweden)

Jinyi Liu

Full Text Available Growth regulating factors (GRFs are a conserved class of transcription factor in seed plants. GRFs are involved in various aspects of tissue differentiation and organ development. The implication of GRFs in biotic stress response has also been recently reported, suggesting a role of these transcription factors in coordinating the interaction between developmental processes and defense dynamics. However, the molecular mechanisms by which GRFs mediate the overlaps between defense signaling and developmental pathways are elusive. Here, we report large scale identification of putative target candidates of Arabidopsis GRF1 and GRF3 by comparing mRNA profiles of the grf1/grf2/grf3 triple mutant and those of the transgenic plants overexpressing miR396-resistant version of GRF1 or GRF3. We identified 1,098 and 600 genes as putative targets of GRF1 and GRF3, respectively. Functional classification of the potential target candidates revealed that GRF1 and GRF3 contribute to the regulation of various biological processes associated with defense response and disease resistance. GRF1 and GRF3 participate specifically in the regulation of defense-related transcription factors, cell-wall modifications, cytokinin biosynthesis and signaling, and secondary metabolites accumulation. GRF1 and GRF3 seem to fine-tune the crosstalk between miRNA signaling networks by regulating the expression of several miRNA target genes. In addition, our data suggest that GRF1 and GRF3 may function as negative regulators of gene expression through their association with other transcription factors. Collectively, our data provide new insights into how GRF1 and GRF3 might coordinate the interactions between defense signaling and plant growth and developmental pathways.

A Comparative Study of Compression Methods and the Development of CODEC Program of Biological Signal for Emergency Telemedicine Service

Energy Technology Data Exchange (ETDEWEB)

Yoon, T.S.; Kim, J.S. [Changwon National University, Changwon (Korea); Lim, Y.H. [Visionite Co., Ltd., Seoul (Korea); Yoo, S.K. [Yonsei University, Seoul (Korea)

2003-05-01

In an emergency telemedicine system such as the High-quality Multimedia based Real-time Emergency Telemedicine(HMRET) service, it is very important to examine the status of the patient continuously using the multimedia data including the biological signals(ECG, BP, Respiration, S{sub p}O{sub 2}) of the patient. In order to transmit these data real time through the communication means which have the limited transmission capacity, it is also necessary to compress the biological data besides other multimedia data. For this purpose, we investigate and compare the ECG compression techniques in the time domain and in the wavelet transform domain, and present an effective lossless compression method of the biological signals using JPEG Huffman table for an emergency telemedicine system. And, for the HMRET service, we developed the lossless compression and reconstruction program of the biological signals in MSVC++ 6.0 using DPCM method and JPEG Huffman table, and tested in an internet environment. (author). 15 refs., 17 figs., 7 tabs.

Redox-capacitor to connect electrochemistry to redox-biology.

Science.gov (United States)

Kim, Eunkyoung; Leverage, W Taylor; Liu, Yi; White, Ian M; Bentley, William E; Payne, Gregory F

2014-01-07

It is well-established that redox-reactions are integral to biology for energy harvesting (oxidative phosphorylation), immune defense (oxidative burst) and drug metabolism (phase I reactions), yet there is emerging evidence that redox may play broader roles in biology (e.g., redox signaling). A critical challenge is the need for tools that can probe biologically-relevant redox interactions simply, rapidly and without the need for a comprehensive suite of analytical methods. We propose that electrochemistry may provide such a tool. In this tutorial review, we describe recent studies with a redox-capacitor film that can serve as a bio-electrode interface that can accept, store and donate electrons from mediators commonly used in electrochemistry and also in biology. Specifically, we (i) describe the fabrication of this redox-capacitor from catechols and the polysaccharide chitosan, (ii) discuss the mechanistic basis for electron exchange, (iii) illustrate the properties of this redox-capacitor and its capabilities for promoting redox-communication between biology and electrodes, and (iv) suggest the potential for enlisting signal processing strategies to "extract" redox information. We believe these initial studies indicate broad possibilities for enlisting electrochemistry and signal processing to acquire "systems level" redox information from biology.

Digital signal processing for He3 proportional counter

International Nuclear Information System (INIS)

Ahmadov, Q.S.; Institute of Radiation Problems, ANAS, Baku

2011-01-01

Full text: Data acquisition systems for nuclear spectroscopy have traditionally been based on systems with analog shaping amplifiers followed by analog-to-digital converters. Recently, however, new systems based on digital signal processing allow us to replace the analog shaping and timing circuitry the numerical algorithms to derive properties of the pulse such as its amplitude. DSP is a fully numerical analysis of the detector pulse signals and this technique demonstrates significant advantages over analog systems in some circumstances. From a mathematical point of view, one can consider the signal evolution from the detector to the ADC as a sequence of transformations that can be described by precisely defined mathematical expressions.Digital signal processing with ADCs has the possibility to utilize further information on the signal pulses from radiation detectors [1] [2]. In the experiment each step of the signal generation in the 3He filled proportional counter was described using digital signal processing techniques (DSP). The electronic system has consisted of a detector, a preamplifier and a digital oscilloscope. The pulses from the detector were digitized using a OTSZS-02 (250USB)-4 digital storage oscilloscope from ZAO R UDNEV-SHILYAYEV . This oscilloscope allowed signal digitization with accuracy of 8 bit(256 levels) and with frequency of up to 5.10''8 samples/s. As a neutron source was used Cf-252.To obtain detector output current pulse I(t) created by the motions of the ions/electrons pairs was written an algorithm which can easily be programmed using modern computer programming languages

Biomedical signal acquisition, processing and transmission using smartphone

International Nuclear Information System (INIS)

Roncagliolo, Pablo; Arredondo, Luis; Gonzalez, AgustIn

2007-01-01

This article describes technical aspects involved in the programming of a system of acquisition, processing and transmission of biomedical signals by using mobile devices. This task is aligned with the permanent development of new technologies for the diagnosis and sickness treatment, based on the feasibility of measuring continuously different variables as electrocardiographic signals, blood pressure, oxygen concentration, pulse or simply temperature. The contribution of this technology is settled on its portability and low cost, which allows its massive use. Specifically this work analyzes the feasibility of acquisition and the processing of signals from a standard smartphone. Work results allow to state that nowadays these equipments have enough processing capacity to execute signals acquisition systems. These systems along with external servers make it possible to imagine a near future where the possibility of making continuous measures of biomedical variables will not be restricted only to hospitals but will also begin to be more frequently used in the daily life and at home

Biomedical signal acquisition, processing and transmission using smartphone

Energy Technology Data Exchange (ETDEWEB)

Roncagliolo, Pablo [Department of Electronics, Universidad Tecnica Federico Santa Maria, Casilla 110-V, ValparaIso (Chile); Arredondo, Luis [Department of Biomedical Engineering, Universidad de ValparaIso, Casilla 123-V, ValparaIso (Chile); Gonzalez, AgustIn [Department of Electronics, Universidad Tecnica Federico Santa MarIa, Casilla 110-V, ValparaIso (Chile)

2007-11-15

This article describes technical aspects involved in the programming of a system of acquisition, processing and transmission of biomedical signals by using mobile devices. This task is aligned with the permanent development of new technologies for the diagnosis and sickness treatment, based on the feasibility of measuring continuously different variables as electrocardiographic signals, blood pressure, oxygen concentration, pulse or simply temperature. The contribution of this technology is settled on its portability and low cost, which allows its massive use. Specifically this work analyzes the feasibility of acquisition and the processing of signals from a standard smartphone. Work results allow to state that nowadays these equipments have enough processing capacity to execute signals acquisition systems. These systems along with external servers make it possible to imagine a near future where the possibility of making continuous measures of biomedical variables will not be restricted only to hospitals but will also begin to be more frequently used in the daily life and at home.

Biomedical signal acquisition, processing and transmission using smartphone

Science.gov (United States)

Roncagliolo, Pablo; Arredondo, Luis; González, Agustín

2007-11-01

This article describes technical aspects involved in the programming of a system of acquisition, processing and transmission of biomedical signals by using mobile devices. This task is aligned with the permanent development of new technologies for the diagnosis and sickness treatment, based on the feasibility of measuring continuously different variables as electrocardiographic signals, blood pressure, oxygen concentration, pulse or simply temperature. The contribution of this technology is settled on its portability and low cost, which allows its massive use. Specifically this work analyzes the feasibility of acquisition and the processing of signals from a standard smartphone. Work results allow to state that nowadays these equipments have enough processing capacity to execute signals acquisition systems. These systems along with external servers make it possible to imagine a near future where the possibility of making continuous measures of biomedical variables will not be restricted only to hospitals but will also begin to be more frequently used in the daily life and at home.

Multidimensional Signal Processing for Sensing & Communications

Science.gov (United States)

2015-07-29

Spectrum Sensing,” submitted to IEEE Intl. Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Cancun, Mexico , 13-16 Dec. 2015...Sensing,” submitted to IEEE Intl. Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Cancun, Mexico , 13-16 Dec. 2015...diversity in echolocating mammals ,” IEEE Signal Processing Magazine, vol. 26, no. 1, pp. 65- 75, Jan. 2009. DISTRIBUTION A: Distribution approved for

Quaternion Fourier transforms for signal and image processing

CERN Document Server

Ell, Todd A; Sangwine, Stephen J

2014-01-01

Based on updates to signal and image processing technology made in the last two decades, this text examines the most recent research results pertaining to Quaternion Fourier Transforms. QFT is a central component of processing color images and complex valued signals. The book's attention to mathematical concepts, imaging applications, and Matlab compatibility render it an irreplaceable resource for students, scientists, researchers, and engineers.

Linear signal processing using silicon micro-ring resonators

DEFF Research Database (Denmark)

Peucheret, Christophe; Ding, Yunhong; Ou, Haiyan

2012-01-01

We review our recent achievements on the use of silicon micro-ring resonators for linear optical signal processing applications, including modulation format conversion, phase-to-intensity modulation conversion and waveform shaping.......We review our recent achievements on the use of silicon micro-ring resonators for linear optical signal processing applications, including modulation format conversion, phase-to-intensity modulation conversion and waveform shaping....

Methods and systems for the processing of physiological signals

International Nuclear Information System (INIS)

Cosnac, B. de; Gariod, R.; Max, J.; Monge, V.

1975-01-01

This note is a general survey of the processing of physiological signals. After an introduction about electrodes and their limitations, the physiological nature of the main signals are shortly recalled. Different methods (signal averaging, spectral analysis, shape morphological analysis) are described as applications to the fields of magnetocardiography, electro-encephalography, cardiography, electronystagmography. As for processing means (single portable instruments and programmable), they are described through the example of application to rheography and to the Plurimat'S general system. As a conclusion the methods of signal processing are dominated by the morphological analysis of curves and by the necessity of a more important introduction of the statistical classification. As for the instruments, microprocessors will appear but specific operators linked to computer will certainly grow [fr

Python for signal processing featuring IPython notebooks

CERN Document Server

Unpingco, José

2013-01-01

This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to ""experiment and learn"" as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remai

Perturbation Biology: Inferring Signaling Networks in Cellular Systems

Science.gov (United States)

Miller, Martin L.; Gauthier, Nicholas P.; Jing, Xiaohong; Kaushik, Poorvi; He, Qin; Mills, Gordon; Solit, David B.; Pratilas, Christine A.; Weigt, Martin; Braunstein, Alfredo; Pagnani, Andrea; Zecchina, Riccardo; Sander, Chris

2013-01-01

We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology. PMID:24367245

Pseudo random signal processing theory and application

CERN Document Server

Zepernick, Hans-Jurgen

2013-01-01

In recent years, pseudo random signal processing has proven to be a critical enabler of modern communication, information, security and measurement systems. The signal's pseudo random, noise-like properties make it vitally important as a tool for protecting against interference, alleviating multipath propagation and allowing the potential of sharing bandwidth with other users. Taking a practical approach to the topic, this text provides a comprehensive and systematic guide to understanding and using pseudo random signals. Covering theoretical principles, design methodologies and applications

pySPACE-a signal processing and classification environment in Python.

Science.gov (United States)

Krell, Mario M; Straube, Sirko; Seeland, Anett; Wöhrle, Hendrik; Teiwes, Johannes; Metzen, Jan H; Kirchner, Elsa A; Kirchner, Frank

2013-01-01

In neuroscience large amounts of data are recorded to provide insights into cerebral information processing and function. The successful extraction of the relevant signals becomes more and more challenging due to increasing complexities in acquisition techniques and questions addressed. Here, automated signal processing and machine learning tools can help to process the data, e.g., to separate signal and noise. With the presented software pySPACE (http://pyspace.github.io/pyspace), signal processing algorithms can be compared and applied automatically on time series data, either with the aim of finding a suitable preprocessing, or of training supervised algorithms to classify the data. pySPACE originally has been built to process multi-sensor windowed time series data, like event-related potentials from the electroencephalogram (EEG). The software provides automated data handling, distributed processing, modular build-up of signal processing chains and tools for visualization and performance evaluation. Included in the software are various algorithms like temporal and spatial filters, feature generation and selection, classification algorithms, and evaluation schemes. Further, interfaces to other signal processing tools are provided and, since pySPACE is a modular framework, it can be extended with new algorithms according to individual needs. In the presented work, the structural hierarchies are described. It is illustrated how users and developers can interface the software and execute offline and online modes. Configuration of pySPACE is realized with the YAML format, so that programming skills are not mandatory for usage. The concept of pySPACE is to have one comprehensive tool that can be used to perform complete signal processing and classification tasks. It further allows to define own algorithms, or to integrate and use already existing libraries.

Gene-ontology enrichment analysis in two independent family-based samples highlights biologically plausible processes for autism spectrum disorders.

LENUS (Irish Health Repository)

Anney, Richard J L

2012-02-01

Recent genome-wide association studies (GWAS) have implicated a range of genes from discrete biological pathways in the aetiology of autism. However, despite the strong influence of genetic factors, association studies have yet to identify statistically robust, replicated major effect genes or SNPs. We apply the principle of the SNP ratio test methodology described by O\\'Dushlaine et al to over 2100 families from the Autism Genome Project (AGP). Using a two-stage design we examine association enrichment in 5955 unique gene-ontology classifications across four groupings based on two phenotypic and two ancestral classifications. Based on estimates from simulation we identify excess of association enrichment across all analyses. We observe enrichment in association for sets of genes involved in diverse biological processes, including pyruvate metabolism, transcription factor activation, cell-signalling and cell-cycle regulation. Both genes and processes that show enrichment have previously been examined in autistic disorders and offer biologically plausibility to these findings.

Enhancement of the automatic ultrasonic signal processing system using digital technology

International Nuclear Information System (INIS)

Koo, In Soo; Park, H. Y.; Suh, Y. S.; Kim, D. Hoon; Huh, S.; Sung, S. H.; Jang, G. S.; Ryoo, S. G.; Choi, J. H.; Kim, Y. H.; Lee, J. C.; Kim, D. Hyun; Park, H. J.; Kim, Y. C.; Lee, J. P.; Park, C. H.; Kim, M. S.

1999-12-01

The objective of this study is to develop the automatic ultrasonic signal processing system which can be used in the inspection equipment to assess the integrity of the reactor vessel by enhancing the performance of the ultrasonic signal processing system. Main activities of this study divided into three categories such as the development of the circuits for generating ultrasonic signal and receiving the signal from the inspection equipment, the development of signal processing algorithm and H/W of the data processing system, and the development of the specification for application programs and system S/W for the analysis and evaluation computer. The results of main activities are as follows 1) the design of the ultrasonic detector and the automatic ultrasonic signal processing system by using the investigation of the state-of-the-art technology in the inside and outside of the country. 2) the development of H/W and S/W of the data processing system based on the results. Especially, the H/W of the data processing system, which have both advantages of digital and analog controls through the real-time digital signal processing, was developed using the DSP which can process the digital signal in the real-time, and was developed not only firmware of the data processing system in order for the peripherals but also the test algorithm of specimen for the calibration. The application programs and the system S/W of the analysis/evaluation computer were developed. Developed equipment was verified by the performance test. Based on developed prototype for the automatic ultrasonic signal processing system, the localization of the overall ultrasonic inspection equipment for nuclear industries would be expected through the further studies of the H/W establishment of real applications, developing the S/W specification of the analysis computer. (author)

All-optical signal processing for optical packet switching networks

NARCIS (Netherlands)

Liu, Y.; Hill, M.T.; Calabretta, N.; Tangdiongga, E.; Geldenhuys, R.; Zhang, S.; Li, Z.; Waardt, de H.; Khoe, G.D.; Dorren, H.J.S.; Iftekharuddin, K.M.; awwal, A.A.S.

2005-01-01

We discuss how all-optical signal processing might play a role in future all-optical packet switched networks. We introduce a concept of optical packet switches that employ entirely all-optical signal processing technology. The optical packet switch is made out of three functional blocks: the

Synthetic Biology: Tools to Design, Build, and Optimize Cellular Processes

Science.gov (United States)

Young, Eric; Alper, Hal

2010-01-01

The general central dogma frames the emergent properties of life, which make biology both necessary and difficult to engineer. In a process engineering paradigm, each biological process stream and process unit is heavily influenced by regulatory interactions and interactions with the surrounding environment. Synthetic biology is developing the tools and methods that will increase control over these interactions, eventually resulting in an integrative synthetic biology that will allow ground-up cellular optimization. In this review, we attempt to contextualize the areas of synthetic biology into three tiers: (1) the process units and associated streams of the central dogma, (2) the intrinsic regulatory mechanisms, and (3) the extrinsic physical and chemical environment. Efforts at each of these three tiers attempt to control cellular systems and take advantage of emerging tools and approaches. Ultimately, it will be possible to integrate these approaches and realize the vision of integrative synthetic biology when cells are completely rewired for biotechnological goals. This review will highlight progress towards this goal as well as areas requiring further research. PMID:20150964

Synthetic Biology: Tools to Design, Build, and Optimize Cellular Processes

Directory of Open Access Journals (Sweden)

Eric Young

2010-01-01

Full Text Available The general central dogma frames the emergent properties of life, which make biology both necessary and difficult to engineer. In a process engineering paradigm, each biological process stream and process unit is heavily influenced by regulatory interactions and interactions with the surrounding environment. Synthetic biology is developing the tools and methods that will increase control over these interactions, eventually resulting in an integrative synthetic biology that will allow ground-up cellular optimization. In this review, we attempt to contextualize the areas of synthetic biology into three tiers: (1 the process units and associated streams of the central dogma, (2 the intrinsic regulatory mechanisms, and (3 the extrinsic physical and chemical environment. Efforts at each of these three tiers attempt to control cellular systems and take advantage of emerging tools and approaches. Ultimately, it will be possible to integrate these approaches and realize the vision of integrative synthetic biology when cells are completely rewired for biotechnological goals. This review will highlight progress towards this goal as well as areas requiring further research.

Synthetic biology: tools to design, build, and optimize cellular processes.

Science.gov (United States)

Young, Eric; Alper, Hal

2010-01-01

The general central dogma frames the emergent properties of life, which make biology both necessary and difficult to engineer. In a process engineering paradigm, each biological process stream and process unit is heavily influenced by regulatory interactions and interactions with the surrounding environment. Synthetic biology is developing the tools and methods that will increase control over these interactions, eventually resulting in an integrative synthetic biology that will allow ground-up cellular optimization. In this review, we attempt to contextualize the areas of synthetic biology into three tiers: (1) the process units and associated streams of the central dogma, (2) the intrinsic regulatory mechanisms, and (3) the extrinsic physical and chemical environment. Efforts at each of these three tiers attempt to control cellular systems and take advantage of emerging tools and approaches. Ultimately, it will be possible to integrate these approaches and realize the vision of integrative synthetic biology when cells are completely rewired for biotechnological goals. This review will highlight progress towards this goal as well as areas requiring further research.

Time reversal signal processing in acoustic emission testing

Czech Academy of Sciences Publication Activity Database

Převorovský, Zdeněk; Krofta, Josef; Kober, Jan; Dvořáková, Zuzana; Chlada, Milan; Dos Santos, S.

2014-01-01

Roč. 19, č. 12 (2014) ISSN 1435-4934. [European Conference on Non-Destructive Testing (ECNDT 2014) /11./. Praha, 06.10.2014-10.10.2014] Institutional support: RVO:61388998 Keywords : acoustic emission (AE) * ultrasonic testing (UT) * signal processing * source location * time reversal acoustic s * acoustic emission * signal processing and transfer Subject RIV: BI - Acoustic s http://www.ndt.net/events/ECNDT2014/app/content/Slides/637_Prevorovsky.pdf

Recent Advancements in Semiconductor-based Optical Signal Processing

DEFF Research Database (Denmark)

Nielsen, M L; Mørk, Jesper

2006-01-01

Significant advancements in technology and basic understanding of device physics are bringing optical signal processing closer to a commercial breakthrough. In this paper we describe the main challenges in high-speed SOA-based switching.......Significant advancements in technology and basic understanding of device physics are bringing optical signal processing closer to a commercial breakthrough. In this paper we describe the main challenges in high-speed SOA-based switching....

Liquid Argon TPC Signal Formation, Signal Processing and Hit Reconstruction

Energy Technology Data Exchange (ETDEWEB)

Baller, Bruce [Fermilab

2017-03-11

This document describes the early stage of the reconstruction chain that was developed for the ArgoNeuT and MicroBooNE experiments at Fermilab. These experiments study accelerator neutrino interactions that occur in a Liquid Argon Time Projection Chamber. Reconstructing the properties of particles produced in these interactions requires knowledge of the micro-physics processes that affect the creation and transport of ionization electrons to the readout system. A wire signal deconvolution technique was developed to convert wire signals to a standard form for hit reconstruction, to remove artifacts in the electronics chain and to remove coherent noise.

Regulation of Early Steps of GPVI Signal Transduction by Phosphatases: A Systems Biology Approach.

Directory of Open Access Journals (Sweden)

Joanne L Dunster

2015-11-01

Full Text Available We present a data-driven mathematical model of a key initiating step in platelet activation, a central process in the prevention of bleeding following Injury. In vascular disease, this process is activated inappropriately and causes thrombosis, heart attacks and stroke. The collagen receptor GPVI is the primary trigger for platelet activation at sites of injury. Understanding the complex molecular mechanisms initiated by this receptor is important for development of more effective antithrombotic medicines. In this work we developed a series of nonlinear ordinary differential equation models that are direct representations of biological hypotheses surrounding the initial steps in GPVI-stimulated signal transduction. At each stage model simulations were compared to our own quantitative, high-temporal experimental data that guides further experimental design, data collection and model refinement. Much is known about the linear forward reactions within platelet signalling pathways but knowledge of the roles of putative reverse reactions are poorly understood. An initial model, that includes a simple constitutively active phosphatase, was unable to explain experimental data. Model revisions, incorporating a complex pathway of interactions (and specifically the phosphatase TULA-2, provided a good description of the experimental data both based on observations of phosphorylation in samples from one donor and in those of a wider population. Our model was used to investigate the levels of proteins involved in regulating the pathway and the effect of low GPVI levels that have been associated with disease. Results indicate a clear separation in healthy and GPVI deficient states in respect of the signalling cascade dynamics associated with Syk tyrosine phosphorylation and activation. Our approach reveals the central importance of this negative feedback pathway that results in the temporal regulation of a specific class of protein tyrosine phosphatases in

Biological processes influencing contaminant release from sediments

International Nuclear Information System (INIS)

Reible, D.D.

1996-01-01

The influence of biological processes, including bioturbation, on the mobility of contaminants in freshwater sediments is described. Effective mass coefficients are estimated for tubificid oligochaetes as a function of worm behavior and biomass density. The mass transfer coefficients were observed to be inversely proportional to water oxygen content and proportional to the square root of biomass density. The sediment reworking and contaminant release are contrasted with those of freshwater amphipods. The implications of these and other biological processes for contaminant release and i n-situ remediation of soils and sediments are summarized. 4 figs., 1 tab

Treatment of slaughter wastewater by coagulation sedimentation-anaerobic biological filter and biological contact oxidation process

Science.gov (United States)

Sun, M.; Yu, P. F.; Fu, J. X.; Ji, X. Q.; Jiang, T.

2017-08-01

The optimal process parameters and conditions for the treatment of slaughterhouse wastewater by coagulation sedimentation-AF - biological contact oxidation process were studied to solve the problem of high concentration organic wastewater treatment in the production of small and medium sized slaughter plants. The suitable water temperature and the optimum reaction time are determined by the experiment of precipitation to study the effect of filtration rate and reflux ratio on COD and SS in anaerobic biological filter and the effect of biofilm thickness and gas water ratio on NH3-N and COD in biological contact oxidation tank, and results show that the optimum temperature is 16-24°C, reaction time is 20 min in coagulating sedimentation, the optimum filtration rate is 0.6 m/h, and the optimum reflux ratio is 300% in anaerobic biological filter reactor. The most suitable biological film thickness range of 1.8-2.2 mm and the most suitable gas water ratio is 12:1-14:1 in biological contact oxidation pool. In the coupling process of continuous operation for 80 days, the average effluent’s mass concentrations of COD, TP and TN were 15.57 mg/L, 40 mg/L and 0.63 mg/L, the average removal rates were 98.93%, 86.10%, 88.95%, respectively. The coupling process has stable operation effect and good effluent quality, and is suitable for the industrial application.

pySPACE - A Signal Processing and Classification Environment in Python

Directory of Open Access Journals (Sweden)

Mario Michael Krell

2013-12-01

Full Text Available In neuroscience large amounts of data are recorded to provide insights into cerebral information processing and function. The successful extraction of the relevant signals becomes more and more challenging due to increasing complexities in acquisition techniques and questions addressed. Here, automated signal processing and machine learning tools can help to process the data, e.g., to separate signal and noise. With the presented software pySPACE (http://pyspace.github.io/pyspace, signal processing algorithms can be compared and applied automatically on time series data, either with the aim of finding a suitable preprocessing, or of training supervised algorithms to classify the data. pySPACE originally has been built to process multi-sensor windowed time series data, like event-related potentials from the electroencephalogram (EEG. The software provides automated data handling, distributed processing, modular build-up of signal processing chains and tools for visualization and performance evaluation. Included in the software are various algorithms like temporal and spatial filters, feature generation and selection, classification algorithms and evaluation schemes. Further, interfaces to other signal processing tools are provided and, since pySPACE is a modular framework, it can be extended with new algorithms according to individual needs. In the presented work, the structural hierarchies are described. It is illustrated how users and developers can interface the software and execute offline and online modes. Configuration of pySPACE is realized with the YAML format, so that programming skills are not mandatory for usage. The concept of pySPACE is to have one comprehensive tool that can be used to perform complete signal processing and classification tasks. It further allows to define own algorithms, or to integrate and use already existing libraries.

Digital signal processing - growth of a technology

International Nuclear Information System (INIS)

Peek, J.B.H.

1985-01-01

The rapid development of microelectronics has led to an increasing extent in circuits and systems for digital signal processing. This happened first in professional applications, e.g. geophysics, astronomy and space flight, and now, with the Compact Disc player, these techniques have entered the consumer field. In the near future digital TV applications will undoubtedly follow. This article outlines a number of the developments behind the advancing 'digitization' of modern technology. The article also considers the main advantages and disadvantages of digital signal processing the main modules now used and some common applications. Particular attention is paid to medical applications. (Auth.)

Applying advanced digital signal processing techniques in industrial radioisotopes applications

International Nuclear Information System (INIS)

Mahmoud, H.K.A.E.

2012-01-01

Radioisotopes can be used to obtain signals or images in order to recognize the information inside the industrial systems. The main problems of using these techniques are the difficulty of identification of the obtained signals or images and the requirement of skilled experts for the interpretation process of the output data of these applications. Now, the interpretation of the output data from these applications is performed mainly manually, depending heavily on the skills and the experience of trained operators. This process is time consuming and the results typically suffer from inconsistency and errors. The objective of the thesis is to apply the advanced digital signal processing techniques for improving the treatment and the interpretation of the output data from the different Industrial Radioisotopes Applications (IRA). This thesis focuses on two IRA; the Residence Time Distribution (RTD) measurement and the defect inspection of welded pipes using a gamma source (gamma radiography). In RTD measurement application, this thesis presents methods for signal pre-processing and modeling of the RTD signals. Simulation results have been presented for two case studies. The first case study is a laboratory experiment for measuring the RTD in a water flow rig. The second case study is an experiment for measuring the RTD in a phosphate production unit. The thesis proposes an approach for RTD signal identification in the presence of noise. In this approach, after signal processing, the Mel Frequency Cepstral Coefficients (MFCCs) and polynomial coefficients are extracted from the processed signal or from one of its transforms. The Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), and Discrete Sine Transform (DST) have been tested and compared for efficient feature extraction. Neural networks have been used for matching of the extracted features. Furthermore, the Power Density Spectrum (PDS) of the RTD signal has been also used instead of the discrete

High-speed optical signal processing using time lenses

DEFF Research Database (Denmark)

Galili, Michael; Hu, Hao; Guan, Pengyu

2015-01-01

This paper will discuss time lenses and their broad range of applications. A number of recent demonstrations of complex high-speed optical signal processing using time lenses will be outlined with focus on the operating principle.......This paper will discuss time lenses and their broad range of applications. A number of recent demonstrations of complex high-speed optical signal processing using time lenses will be outlined with focus on the operating principle....

Interaction of Herbal Compounds with Biological Targets: A Case Study with Berberine

Directory of Open Access Journals (Sweden)

Xiao-Wu Chen

2012-01-01

Full Text Available Berberine is one of the main alkaloids found in the Chinese herb Huang lian (Rhizoma Coptidis, which has been reported to have multiple pharmacological activities. This study aimed to analyze the molecular targets of berberine based on literature data followed by a pathway analysis using the PANTHER program. PANTHER analysis of berberine targets showed that the most classes of molecular functions include receptor binding, kinase activity, protein binding, transcription activity, DNA binding, and kinase regulator activity. Based on the biological process classification of in vitro berberine targets, those targets related to signal transduction, intracellular signalling cascade, cell surface receptor-linked signal transduction, cell motion, cell cycle control, immunity system process, and protein metabolic process are most frequently involved. In addition, berberine was found to interact with a mixture of biological pathways, such as Alzheimer’s disease-presenilin and -secretase pathways, angiogenesis, apoptosis signalling pathway, FAS signalling pathway, Hungtington disease, inflammation mediated by chemokine and cytokine signalling pathways, interleukin signalling pathway, and p53 pathways. We also explored the possible mechanism of action for the anti-diabetic effect of berberine. Further studies are warranted to elucidate the mechanisms of action of berberine using systems biology approach.

Multibeam swath bathymetry signal processing techniques

Digital Repository Service at National Institute of Oceanography (India)

Ranade, G.; Sudhakar, T.

Mathematical advances and the advances in the real time signal processing techniques in the recent times, have considerably improved the state of art in the bathymetry systems. These improvements have helped in developing high resolution swath...

All-Optical Signal Processing using Silicon Devices

DEFF Research Database (Denmark)

Oxenløwe, Leif Katsuo; Pu, Minhao; Ding, Yunhong

2014-01-01

This paper presents an overview of recent wo rk on the use of silicon waveguides for processing optical data signals. We will describe ultra-fast, ultra-broadband, polarisation-insensitive and phase-sensitive applications including processing of spectrally-efficient data formats and optical phase...

A Measurement System of Electric Signals on Standing Trees

Directory of Open Access Journals (Sweden)

Hao TIAN

2014-01-01

Full Text Available The standing tree electric signal (STES, defined as the electric potential difference between standing trees and the surrounding soil, can be utilized to reflect the biological nature of the trees. This signal should be measured precisely because it can also be collected and used as the electric power energy. In this paper, the automatic measurement system of standing tree biological electric signal based on MSP430 MCU. First of all, the basic structure of the presented system is introduced and it includes three modules: amplification module of the standing tree electric signal, the acquisition and processing of the signal module and the serial communication module. Then, the performances of the built system are respectively validated by the Poplar, Planetree, and Platanus in Beijing Forestry University. The result indicated that the relative error of this system is less than 2 %. The presented system can be considered as the foundation of the subsequent study on the mechanism of the biological electric signal and the application of the biological electric energy on standing trees.

Reconstruction and signal propagation analysis of the Syk signaling network in breast cancer cells.

Directory of Open Access Journals (Sweden)

Aurélien Naldi

2017-03-01

Full Text Available The ability to build in-depth cell signaling networks from vast experimental data is a key objective of computational biology. The spleen tyrosine kinase (Syk protein, a well-characterized key player in immune cell signaling, was surprisingly first shown by our group to exhibit an onco-suppressive function in mammary epithelial cells and corroborated by many other studies, but the molecular mechanisms of this function remain largely unsolved. Based on existing proteomic data, we report here the generation of an interaction-based network of signaling pathways controlled by Syk in breast cancer cells. Pathway enrichment of the Syk targets previously identified by quantitative phospho-proteomics indicated that Syk is engaged in cell adhesion, motility, growth and death. Using the components and interactions of these pathways, we bootstrapped the reconstruction of a comprehensive network covering Syk signaling in breast cancer cells. To generate in silico hypotheses on Syk signaling propagation, we developed a method allowing to rank paths between Syk and its targets. We first annotated the network according to experimental datasets. We then combined shortest path computation with random walk processes to estimate the importance of individual interactions and selected biologically relevant pathways in the network. Molecular and cell biology experiments allowed to distinguish candidate mechanisms that underlie the impact of Syk on the regulation of cortactin and ezrin, both involved in actin-mediated cell adhesion and motility. The Syk network was further completed with the results of our biological validation experiments. The resulting Syk signaling sub-networks can be explored via an online visualization platform.

Digital signal processing in power system protection and control

CERN Document Server

Rebizant, Waldemar; Wiszniewski, Andrzej

2011-01-01

Digital Signal Processing in Power System Protection and Control bridges the gap between the theory of protection and control and the practical applications of protection equipment. Understanding how protection functions is crucial not only for equipment developers and manufacturers, but also for their users who need to install, set and operate the protection devices in an appropriate manner. After introductory chapters related to protection technology and functions, Digital Signal Processing in Power System Protection and Control presents the digital algorithms for signal filtering, followed

Surface light scattering: integrated technology and signal processing

DEFF Research Database (Denmark)

Lading, L.; Dam-Hansen, C.; Rasmussen, E.

1997-01-01

systems representing increasing levels of integration are considered. It is demonstrated that efficient signal and data processing can be achieved by evaluation of the statistics of the derivative of the instantaneous phase of the detector signal. (C) 1997 Optical Society of America....

A FPGA-based signal processing unit for a GEM array detector

International Nuclear Information System (INIS)

Yen, W.W.; Chou, H.P.

2013-06-01

in the present study, a signal processing unit for a GEM one-dimensional array detector is presented to measure the trajectory of photoelectrons produced by cosmic X-rays. The present GEM array detector system has 16 signal channels. The front-end unit provides timing signals from trigger units and energy signals from charge sensitive amplifies. The prototype of the processing unit is implemented using commercial field programmable gate array circuit boards. The FPGA based system is linked to a personal computer for testing and data analysis. Tests using simulated signals indicated that the FPGA-based signal processing unit has a good linearity and is flexible for parameter adjustment for various experimental conditions (authors)

Mathematical principles of signal processing Fourier and wavelet analysis

CERN Document Server

Brémaud, Pierre

2002-01-01

Fourier analysis is one of the most useful tools in many applied sciences. The recent developments of wavelet analysis indicates that in spite of its long history and well-established applications, the field is still one of active research. This text bridges the gap between engineering and mathematics, providing a rigorously mathematical introduction of Fourier analysis, wavelet analysis and related mathematical methods, while emphasizing their uses in signal processing and other applications in communications engineering. The interplay between Fourier series and Fourier transforms is at the heart of signal processing, which is couched most naturally in terms of the Dirac delta function and Lebesgue integrals. The exposition is organized into four parts. The first is a discussion of one-dimensional Fourier theory, including the classical results on convergence and the Poisson sum formula. The second part is devoted to the mathematical foundations of signal processing - sampling, filtering, digital signal proc...

All-optical microwave signal processing based on optical phase modulation

Science.gov (United States)

Zeng, Fei

This thesis presents a theoretical and experimental study of optical phase modulation and its applications in all-optical microwave signal processing, which include all-optical microwave filtering, all-optical microwave mixing, optical code-division multiple-access (CDMA) coding, and ultrawideband (UWB) signal generation. All-optical microwave signal processing can be considered as the use of opto-electronic devices and systems to process microwave signals in the optical domain, which provides several significant advantages such as low loss, low dispersion, light weight, high time bandwidth products, and immunity to electromagnetic interference. In conventional approaches, the intensity of an optical carrier is modulated by a microwave signal based on direct modulation or external modulation. The intensity-modulated optical signal is then fed to a photonic circuit or system to achieve specific signal processing functionalities. The microwave signal being processed is usually obtained based on direct detection, i.e., an opto-electronic conversion by use of a photodiode. In this thesis, the research efforts are focused on the optical phase modulation and its applications in all-optical microwave signal processing. To avoid using coherent detection which is complicated and costly, simple and effective phase modulation to intensity modulation (PM-IM) conversion schemes are pursued. Based on a theoretical study of optical phase modulation, two approaches to achieving PM-IM conversions are proposed. In the first approach, the use of chromatic dispersion induced by a dispersive device to alter the phase relationships among the sidebands and the optical carrier of a phase-modulated optical signal to realize PM-IM conversion is investigated. In the second approach, instead of using a dispersive device, the PM-IM conversion is realized based on optical frequency discrimination implemented using an optical filter. We show that the proposed PM-IM conversion schemes can be

K-mean clustering algorithm for processing signals from compound semiconductor detectors

International Nuclear Information System (INIS)

Tada, Tsutomu; Hitomi, Keitaro; Wu, Yan; Kim, Seong-Yun; Yamazaki, Hiromichi; Ishii, Keizo

2011-01-01

The K-mean clustering algorithm was employed for processing signal waveforms from TlBr detectors. The signal waveforms were classified based on its shape reflecting the charge collection process in the detector. The classified signal waveforms were processed individually to suppress the pulse height variation of signals due to the charge collection loss. The obtained energy resolution of a 137 Cs spectrum measured with a 0.5 mm thick TlBr detector was 1.3% FWHM by employing 500 clusters.

Processing scarce biological samples for light and transmission electron microscopy

Directory of Open Access Journals (Sweden)

P Taupin

2008-06-01

Full Text Available Light microscopy (LM and transmission electron microscopy (TEM aim at understanding the relationship structure-function. With advances in biology, isolation and purification of scarce populations of cells or subcellular structures may not lead to enough biological material, for processing for LM and TEM. A protocol for preparation of scarce biological samples is presented. It is based on pre-embedding the biological samples, suspensions or pellets, in bovine serum albumin (BSA and bis-acrylamide (BA, cross-linked and polymerized. This preparation provides a simple and reproducible technique to process biological materials, present in limited quantities that can not be amplified, for light and transmission electron microscopy.

Haptic teleoperation systems signal processing perspective

CERN Document Server

Lee, Jae-young

2015-01-01

This book examines the signal processing perspective in haptic teleoperation systems. This text covers the topics of prediction, estimation, architecture, data compression, and error correction that can be applied to haptic teleoperation systems. The authors begin with an overview of haptic teleoperation systems, then look at a Bayesian approach to haptic teleoperation systems. They move onto a discussion of haptic data compression, haptic data digitization and forward error correction.   ·         Presents haptic data prediction/estimation methods that compensate for unreliable networks   ·         Discusses haptic data compression that reduces haptic data size over limited network bandwidth and haptic data error correction that compensate for packet loss problem   ·         Provides signal processing techniques used with existing control architectures.

Signal and image processing for monitoring and testing at EDF

International Nuclear Information System (INIS)

Georgel, B.; Garreau, D.

1992-04-01

The quality of monitoring and non destructive testing devices in plants and utilities today greatly depends on the efficient processing of signal and image data. In this context, signal or image processing techniques, such as adaptive filtering or detection or 3D reconstruction, are required whenever manufacturing nonconformances or faulty operation have to be recognized and identified. This paper reviews the issues of industrial image and signal processing, by briefly considering the relevant studies and projects under way at EDF. (authors). 1 fig., 11 refs

Social multimedia signals a signal processing approach to social network phenomena

CERN Document Server

Roy, Suman Deb

2014-01-01

This book provides a comprehensive coverage of the state-of-the-art in understanding media popularity and trends in online social networks through social multimedia signals. With insights from the study of popularity and sharing patterns of online media, trend spread in social media, social network analysis for multimedia and visualizing diffusion of media in online social networks. In particular, the book will address the following important issues: Understanding social network phenomena from a signal processing point of view; The existence and popularity of multimedia as shared and social me

EURASIP journal on bioinformatics & systems biology

National Research Council Canada - National Science Library

2006-01-01

"The overall aim of "EURASIP Journal on Bioinformatics and Systems Biology" is to publish research results related to signal processing and bioinformatics theories and techniques relevant to a wide...

Blind I/Q Signal Separation-Based Solutions for Receiver Signal Processing

Directory of Open Access Journals (Sweden)

Visa Koivunen

2005-09-01

Full Text Available This paper introduces some novel digital signal processing (DSP-based approaches to some of the most fundamental tasks of radio receivers, namely, channel equalization, carrier synchronization, and I/Q mismatch compensation. The leading principle is to show that all these problems can be solved blindly (i.e., without training signals by forcing the I and Q components of the observed data as independent as possible. Blind signal separation (BSS is then introduced as an efficient tool to carry out these tasks, and simulation examples are used to illustrate the performance of the proposed approaches. The main application area of the presented carrier synchronization and I/Q mismatch compensation techniques is in direct-conversion type receivers, while the proposed channel equalization principles basically apply to any radio architecture.

Digital signal processing for wireless communication using Matlab

CERN Document Server

Gopi, E S

2016-01-01

This book examines signal processing techniques used in wireless communication illustrated by using the Matlab program. The author discusses these techniques as they relate to Doppler spread; delay spread; Rayleigh and Rician channel modeling; rake receiver; diversity techniques; MIMO and OFDM -based transmission techniques; and array signal processing. Related topics such as detection theory, link budget, multiple access techniques, and spread spectrum are also covered.   ·         Illustrates signal processing techniques involved in wireless communication using Matlab ·         Discusses multiple access techniques such as Frequency division multiple access, Time division multiple access, and Code division multiple access ·         Covers band pass modulation techniques such as Binary phase shift keying, Differential phase shift keying, Quadrature phase shift keying, Binary frequency shift keying, Minimum shift keying, and Gaussian minimum shift keying.

An implementation of signal processing algorithms for ultrasonic NDE

International Nuclear Information System (INIS)

Ericsson, L.; Stepinski, T.

1994-01-01

Probability of detection flaws during ultrasonic pulse-echo inspection is often limited by the presence of backscattered echoes from the material structure. A digital signal processing technique for removal of this material noise, referred to as split spectrum processing (SSP), has been developed and verified using laboratory experiments during the last decade. The authors have performed recently a limited scale evaluation of various SSP techniques for ultrasonic signals acquired during the inspection of welds in austenitic steel. They have obtained very encouraging results that indicate promising capabilities of the SSP for inspection of nuclear power plants. Thus, a more extensive investigation of the technique using large amounts of ultrasonic data is motivated. This analysis should employ different combinations of materials, flaws and transducers. Due to the considerable number of ultrasonic signals required to verify the technique for future practical use, a custom-made computer software is necessary. At the request of the Swedish nuclear power industry the authors have developed such a program package. The program provides a user-friendly graphical interface and is intended for processing of B-scan data in a flexible way. Assembled in the program are a number of signal processing algorithms including traditional Split Spectrum Processing and the more recent Cut Spectrum Processing algorithm developed by them. The program and some results obtained using the various algorithms are presented in the paper

Self-Organized Biological Dynamics and Nonlinear Control

Science.gov (United States)

Walleczek, Jan

2006-04-01

The frontiers and challenges of biodynamics research Jan Walleczek; Part I. Nonlinear Dynamics in Biology and Response to Stimuli: 1. External signals and internal oscillation dynamics - principal aspects and response of stimulated rhythmic processes Friedemann Kaiser; 2. Nonlinear dynamics in biochemical and biophysical systems: from enzyme kinetics to epilepsy Raima Larter, Robert Worth and Brent Speelman; 3. Fractal mechanisms in neural control: human heartbeat and gait dynamics in health and disease Chung-Kang Peng, Jeffrey M. Hausdorff and Ary L. Goldberger; 4. Self-organising dynamics in human coordination and perception Mingzhou Ding, Yanqing Chen, J. A. Scott Kelso and Betty Tuller; 5. Signal processing in biochemical reaction networks Adam P. Arkin; Part II. Nonlinear Sensitivity of Biological Systems to Electromagnetic Stimuli: 6. Electrical signal detection and noise in systems with long-range coherence Paul C. Gailey; 7. Oscillatory signals in migrating neutrophils: effects of time-varying chemical and electrical fields Howard R. Petty; 8. Enzyme kinetics and nonlinear biochemical amplification in response to static and oscillating magnetic fields Jan Walleczek and Clemens F. Eichwald; 9. Magnetic field sensitivity in the hippocampus Stefan Engström, Suzanne Bawin and W. Ross Adey; Part III. Stochastic Noise-Induced Dynamics and Transport in Biological Systems: 10. Stochastic resonance: looking forward Frank Moss; 11. Stochastic resonance and small-amplitude signal transduction in voltage-gated ion channels Sergey M. Bezrukov and Igor Vodyanoy; 12. Ratchets, rectifiers and demons: the constructive role of noise in free energy and signal transduction R. Dean Astumian; 13. Cellular transduction of periodic and stochastic energy signals by electroconformational coupling Tian Y. Tsong; Part IV. Nonlinear Control of Biological and Other Excitable Systems: 14. Controlling chaos in dynamical systems Kenneth Showalter; 15. Electromagnetic fields and biological

ECG signal processing

NARCIS (Netherlands)

2009-01-01

A system extracts an ECG signal from a composite signal (308) representing an electric measurement of a living subject. Identification means (304) identify a plurality of temporal segments (309) of the composite signal corresponding to a plurality of predetermined segments (202,204,206) of an ECG

Single photon laser altimeter simulator and statistical signal processing

Science.gov (United States)

Vacek, Michael; Prochazka, Ivan

2013-05-01

Spaceborne altimeters are common instruments onboard the deep space rendezvous spacecrafts. They provide range and topographic measurements critical in spacecraft navigation. Simultaneously, the receiver part may be utilized for Earth-to-satellite link, one way time transfer, and precise optical radiometry. The main advantage of single photon counting approach is the ability of processing signals with very low signal-to-noise ratio eliminating the need of large telescopes and high power laser source. Extremely small, rugged and compact microchip lasers can be employed. The major limiting factor, on the other hand, is the acquisition time needed to gather sufficient volume of data in repetitive measurements in order to process and evaluate the data appropriately. Statistical signal processing is adopted to detect signals with average strength much lower than one photon per measurement. A comprehensive simulator design and range signal processing algorithm are presented to identify a mission specific altimeter configuration. Typical mission scenarios (celestial body surface landing and topographical mapping) are simulated and evaluated. The high interest and promising single photon altimeter applications are low-orbit (˜10 km) and low-radial velocity (several m/s) topographical mapping (asteroids, Phobos and Deimos) and landing altimetry (˜10 km) where range evaluation repetition rates of ˜100 Hz and 0.1 m precision may be achieved. Moon landing and asteroid Itokawa topographical mapping scenario simulations are discussed in more detail.

Design of signal reception and processing system of embedded ultrasonic endoscope

Science.gov (United States)

Li, Ming; Yu, Feng; Zhang, Ruiqiang; Li, Yan; Chen, Xiaodong; Yu, Daoyin

2009-11-01

Embedded Ultrasonic Endoscope, based on embedded microprocessor and embedded real-time operating system, sends a micro ultrasonic probe into coelom through the biopsy channel of the Electronic Endoscope to get the fault histology features of digestive organs by rotary scanning, and acquires the pictures of the alimentary canal mucosal surface. At the same time, ultrasonic signals are processed by signal reception and processing system, forming images of the full histology of the digestive organs. Signal Reception and Processing System is an important component of Embedded Ultrasonic Endoscope. However, the traditional design, using multi-level amplifiers and special digital processing circuits to implement signal reception and processing, is no longer satisfying the standards of high-performance, miniaturization and low power requirements that embedded system requires, and as a result of the high noise that multi-level amplifier brought, the extraction of small signal becomes hard. Therefore, this paper presents a method of signal reception and processing based on double variable gain amplifier and FPGA, increasing the flexibility and dynamic range of the Signal Reception and Processing System, improving system noise level, and reducing power consumption. Finally, we set up the embedded experiment system, using a transducer with the center frequency of 8MHz to scan membrane samples, and display the image of ultrasonic echo reflected by each layer of membrane, with a frame rate of 5Hz, verifying the correctness of the system.

RF applications in digital signal processing

CERN Document Server

Schilcher, T

2008-01-01

Ever higher demands for stability, accuracy, reproducibility, and monitoring capability are being placed on Low-Level Radio Frequency (LLRF) systems of particle accelerators. Meanwhile, continuing rapid advances in digital signal processing technology are being exploited to meet these demands, thus leading to development of digital LLRF systems. The rst part of this course will begin by focusing on some of the important building-blocks of RF signal processing including mixer theory and down-conversion, I/Q (amplitude and phase) detection, digital down-conversion (DDC) and decimation, concluding with a survey of I/Q modulators. The second part of the course will introduce basic concepts of feedback systems, including examples of digital cavity eld and phase control, followed by radial loop architectures. Adaptive feed-forward systems used for the suppression of repetitive beam disturbances will be examined. Finally, applications and principles of system identi cation approaches will be summarized.

Silicon nanowires for ultra-fast and ultrabroadband optical signal processing

DEFF Research Database (Denmark)

Ji, Hua; Hu, Hao; Pu, Minhao

2015-01-01

In this paper, we present recent research on silicon nanowires for ultra-fast and ultra-broadband optical signal processing at DTU Fotonik. The advantages and limitations of using silicon nanowires for optical signal processing are revealed through experimental demonstrations of various optical...

Signal processing method for Johnson noise thermometry

International Nuclear Information System (INIS)

Hwang, I. G.; Moon, B. S.; Kinser, Rpger

2003-01-01

The development of Johnson Noise Thermometry requires a high sensitive preamplifier circuit to pick up the temperature-related noise on the sensing element. However, the random noise generated in this amplification circuit causes a significant erroneous influence to the measurement. This paper describes signal processing mechanism of the Johnson Noise Thermometry system which is underway of development in collaboration between KAERI and ORNL. It adopts two identical amplifier channels and utilizes a digital signal processing technique to remove the independent noise of each channel. The CPSD(Cross Power Spectral Density) function is used to cancel the independent noise and the differentiation of narrow or single frequency peak from the CPSD data separates the common mode electromagnetic interference noise

ATP signals

DEFF Research Database (Denmark)

Novak, Ivana

2016-01-01

The Department of Biology at the University of Copenhagen explains the function of ATP signalling in the pancreas......The Department of Biology at the University of Copenhagen explains the function of ATP signalling in the pancreas...

Illuminating Cell Signaling: Using "Vibrio harveyi" in an Introductory Biology Laboratory

Science.gov (United States)

Hrizo, Stacy L.; Kaufmann, Nancy

2009-01-01

Cell signaling is an essential cellular process that is performed by all living organisms. Bacteria communicate with each other using a chemical language in a signaling pathway that allows bacteria to evaluate the size of their population, determine when they have reached a critical mass (quorum sensing), and then change their behavior in unison…

Nanobody-Based Biologics for Modulating Purinergic Signaling in Inflammation and Immunity

Directory of Open Access Journals (Sweden)

Stephan Menzel

2018-03-01

Full Text Available Adenosine triphosphate (ATP and nicotinamide adenine dinucleotide (NAD+ are released as danger signals from cells during infection and sterile inflammation. In the extracellular compartment ATP is converted by CD39, CD73, and other ecto-enzymes into metabolites that modulate the activity of T cells and macrophages. While ATP mediates pro-inflammatory signals via P2X7 and other P2 receptors, adenosine triggers anti-inflammatory signaling via the adenosine 2a receptor (Adora2a and other P1 receptors. The latter also plays a role in maintaining an immunosuppressive tumor microenvironment. NAD+ is converted by CD38, CD203 and other ecto-enzymes to the Ca2+ mobilizing messengers cyclic ADP-ribose and ADP-ribose, and to adenosine. Recent findings on the roles of CD38, CD39, CD73, CD203, P2X7, and Adora2a in inflammation and immunity underscore the potential of these proteins as drug targets. However, available small molecule inhibitors often lack specificity and mediate unwanted off-target toxicity. Nanobodies – single domain antibodies derived from heavy chain antibodies that naturally occur in camelids – display a propensity to bind functional epitopes not accessible to conventional antibodies. Like conventional antibodies, nanobodies and nanobody-based biologics are highly specific and have well-understood, tunable in vivo pharmacodynamics with little if any toxicity. Nanobodies thus represent attractive alternatives to small molecule inhibitors for modulating purinergic signaling in inflammation and immunity. Here we review recent progress made in developing nanobodies against key targets of purinergic signaling.

Nanobody-Based Biologics for Modulating Purinergic Signaling in Inflammation and Immunity.

Science.gov (United States)

Menzel, Stephan; Schwarz, Nicole; Haag, Friedrich; Koch-Nolte, Friedrich

2018-01-01

Adenosine triphosphate (ATP) and nicotinamide adenine dinucleotide (NAD + ) are released as danger signals from cells during infection and sterile inflammation. In the extracellular compartment ATP is converted by CD39, CD73, and other ecto-enzymes into metabolites that modulate the activity of T cells and macrophages. While ATP mediates pro-inflammatory signals via P2X7 and other P2 receptors, adenosine triggers anti-inflammatory signaling via the adenosine 2a receptor (Adora2a) and other P1 receptors. The latter also plays a role in maintaining an immunosuppressive tumor microenvironment. NAD + is converted by CD38, CD203 and other ecto-enzymes to the Ca 2+ mobilizing messengers cyclic ADP-ribose and ADP-ribose, and to adenosine. Recent findings on the roles of CD38, CD39, CD73, CD203, P2X7, and Adora2a in inflammation and immunity underscore the potential of these proteins as drug targets. However, available small molecule inhibitors often lack specificity and mediate unwanted off-target toxicity. Nanobodies - single domain antibodies derived from heavy chain antibodies that naturally occur in camelids - display a propensity to bind functional epitopes not accessible to conventional antibodies. Like conventional antibodies, nanobodies and nanobody-based biologics are highly specific and have well-understood, tunable in vivo pharmacodynamics with little if any toxicity. Nanobodies thus represent attractive alternatives to small molecule inhibitors for modulating purinergic signaling in inflammation and immunity. Here we review recent progress made in developing nanobodies against key targets of purinergic signaling.

Fast, multi-channel real-time processing of signals with microsecond latency using graphics processing units

Energy Technology Data Exchange (ETDEWEB)

Rath, N., E-mail: Nikolaus@rath.org; Levesque, J. P.; Mauel, M. E.; Navratil, G. A.; Peng, Q. [Department of Applied Physics and Applied Mathematics, Columbia University, 500 W 120th St, New York, New York 10027 (United States); Kato, S. [Department of Information Engineering, Nagoya University, Nagoya (Japan)

2014-04-15

Fast, digital signal processing (DSP) has many applications. Typical hardware options for performing DSP are field-programmable gate arrays (FPGAs), application-specific integrated DSP chips, or general purpose personal computer systems. This paper presents a novel DSP platform that has been developed for feedback control on the HBT-EP tokamak device. The system runs all signal processing exclusively on a Graphics Processing Unit (GPU) to achieve real-time performance with latencies below 8 μs. Signals are transferred into and out of the GPU using PCI Express peer-to-peer direct-memory-access transfers without involvement of the central processing unit or host memory. Tests were performed on the feedback control system of the HBT-EP tokamak using forty 16-bit floating point inputs and outputs each and a sampling rate of up to 250 kHz. Signals were digitized by a D-TACQ ACQ196 module, processing done on an NVIDIA GTX 580 GPU programmed in CUDA, and analog output was generated by D-TACQ AO32CPCI modules.

Fast, multi-channel real-time processing of signals with microsecond latency using graphics processing units

International Nuclear Information System (INIS)

Rath, N.; Levesque, J. P.; Mauel, M. E.; Navratil, G. A.; Peng, Q.; Kato, S.

2014-01-01

Fast, digital signal processing (DSP) has many applications. Typical hardware options for performing DSP are field-programmable gate arrays (FPGAs), application-specific integrated DSP chips, or general purpose personal computer systems. This paper presents a novel DSP platform that has been developed for feedback control on the HBT-EP tokamak device. The system runs all signal processing exclusively on a Graphics Processing Unit (GPU) to achieve real-time performance with latencies below 8 μs. Signals are transferred into and out of the GPU using PCI Express peer-to-peer direct-memory-access transfers without involvement of the central processing unit or host memory. Tests were performed on the feedback control system of the HBT-EP tokamak using forty 16-bit floating point inputs and outputs each and a sampling rate of up to 250 kHz. Signals were digitized by a D-TACQ ACQ196 module, processing done on an NVIDIA GTX 580 GPU programmed in CUDA, and analog output was generated by D-TACQ AO32CPCI modules

An introduction to stochastic processes with applications to biology

CERN Document Server

Allen, Linda J S

2010-01-01

An Introduction to Stochastic Processes with Applications to Biology, Second Edition presents the basic theory of stochastic processes necessary in understanding and applying stochastic methods to biological problems in areas such as population growth and extinction, drug kinetics, two-species competition and predation, the spread of epidemics, and the genetics of inbreeding. Because of their rich structure, the text focuses on discrete and continuous time Markov chains and continuous time and state Markov processes.New to the Second EditionA new chapter on stochastic differential equations th

Photonic Ultra-Wideband 781.25-Mb/s Signal Generation and Transmission Incorporating Digital Signal Processing Detection

DEFF Research Database (Denmark)

Gibbon, Timothy Braidwood; Yu, Xianbin; Tafur Monroy, Idelfonso

2009-01-01

The generation of photonic ultra-wideband (UWB) impulse signals using an uncooled distributed-feedback laser is proposed. For the first time, we experimentally demonstrate bit-for-bit digital signal processing (DSP) bit-error-rate measurements for transmission of a 781.25-Mb/s photonic UWB signal...

Fixed-point signal processing

CERN Document Server

Padgett, Wayne T

2009-01-01

This book is intended to fill the gap between the ""ideal precision"" digital signal processing (DSP) that is widely taught, and the limited precision implementation skills that are commonly required in fixed-point processors and field programmable gate arrays (FPGAs). These skills are often neglected at the university level, particularly for undergraduates. We have attempted to create a resource both for a DSP elective course and for the practicing engineer with a need to understand fixed-point implementation. Although we assume a background in DSP, Chapter 2 contains a review of basic theory

All-optical signal processing of OTDM and OFDM signals based on time-domain optical fourier transformation

DEFF Research Database (Denmark)

Galili, Michael; Guan, Pengyu; Lillieholm, Mads

2017-01-01

In the talk, we will review recent work on optical signal processing based on time lenses. Various applications of optical Fourier transformation for optical communications will be discussed.......In the talk, we will review recent work on optical signal processing based on time lenses. Various applications of optical Fourier transformation for optical communications will be discussed....

Systems biology integration of proteomic data in rodent models of depression reveals involvement of the immune response and glutamatergic signaling.

Science.gov (United States)

Carboni, Lucia; Nguyen, Thanh-Phuong; Caberlotto, Laura

2016-12-01

The pathophysiological basis of major depression is incompletely understood. Recently, numerous proteomic studies have been performed in rodent models of depression to investigate the molecular underpinnings of depressive-like behaviours with an unbiased approach. The objective of the study is to integrate the results of these proteomic studies in depression models to shed light on the most relevant molecular pathways involved in the disease. Network analysis is performed integrating preexisting proteomic data from rodent models of depression. The IntAct mouse and the HRPD are used as reference protein-protein interaction databases. The functionality analyses of the networks are then performed by testing overrepresented GO biological process terms and pathways. Functional enrichment analyses of the networks revealed an association with molecular processes related to depression in humans, such as those involved in the immune response. Pathways impacted by clinically effective antidepressants are modulated, including glutamatergic signaling and neurotrophic responses. Moreover, dysregulations of proteins regulating energy metabolism and circadian rhythms are implicated. The comparison with protein pathways modulated in depressive patients revealed significant overlapping. This systems biology study supports the notion that animal models can contribute to the research into the biology and therapeutics of depression. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ultrafast optical signal processing using semiconductor quantum dot amplifiers

DEFF Research Database (Denmark)

Berg, Tommy Winther; Mørk, Jesper

2002-01-01

The linear and nonlinear properties of quantum dot amplifiers are discussed on the basis of an extensive theoretical model. These devices show great potential for linear amplification as well as ultrafast signal processing.......The linear and nonlinear properties of quantum dot amplifiers are discussed on the basis of an extensive theoretical model. These devices show great potential for linear amplification as well as ultrafast signal processing....

Hyperpolarized NMR Probes for Biological Assays

Directory of Open Access Journals (Sweden)

Sebastian Meier

2014-01-01

Full Text Available During the last decade, the development of nuclear spin polarization enhanced (hyperpolarized molecular probes has opened up new opportunities for studying the inner workings of living cells in real time. The hyperpolarized probes are produced ex situ, introduced into biological systems and detected with high sensitivity and contrast against background signals using high resolution NMR spectroscopy. A variety of natural, derivatized and designed hyperpolarized probes has emerged for diverse biological studies including assays of intracellular reaction progression, pathway kinetics, probe uptake and export, pH, redox state, reactive oxygen species, ion concentrations, drug efficacy or oncogenic signaling. These probes are readily used directly under natural conditions in biofluids and are often directly developed and optimized for cellular assays, thus leaving little doubt about their specificity and utility under biologically relevant conditions. Hyperpolarized molecular probes for biological NMR spectroscopy enable the unbiased detection of complex processes by virtue of the high spectral resolution, structural specificity and quantifiability of NMR signals. Here, we provide a survey of strategies used for the selection, design and use of hyperpolarized NMR probes in biological assays, and describe current limitations and developments.

Structural health monitoring an advanced signal processing perspective

CERN Document Server

Chen, Xuefeng; Mukhopadhyay, Subhas

2017-01-01

This book highlights the latest advances and trends in advanced signal processing (such as wavelet theory, time-frequency analysis, empirical mode decomposition, compressive sensing and sparse representation, and stochastic resonance) for structural health monitoring (SHM). Its primary focus is on the utilization of advanced signal processing techniques to help monitor the health status of critical structures and machines encountered in our daily lives: wind turbines, gas turbines, machine tools, etc. As such, it offers a key reference guide for researchers, graduate students, and industry professionals who work in the field of SHM.

A new signal development process and sound system for diverting fish from water intakes

International Nuclear Information System (INIS)

Klinet, D.A.; Loeffelman, P.H.; van Hassel, J.H.

1992-01-01

This paper reports that American Electric Power Service Corporation has explored the feasibility of using a patented signal development process and underwater sound system to divert fish away from water intake areas. The effect of water intakes on fish is being closely scrutinized as hydropower projects are re-licensed. The overall goal of this four-year research project was to develop an underwater guidance system which is biologically effective, reliable and cost-effective compared to other proposed methods of diversion, such as physical screens. Because different fish species have various listening ranges, it was essential to the success of this experiment that the sound system have a great amount of flexibility. Assuming a fish's sounds are heard by the same kind of fish, it was necessary to develop a procedure and acquire instrumentation to properly analyze the sounds that the target fish species create to communicate and any artificial signals being generated for diversion

Neural Parallel Engine: A toolbox for massively parallel neural signal processing.

Science.gov (United States)

Tam, Wing-Kin; Yang, Zhi

2018-05-01

Large-scale neural recordings provide detailed information on neuronal activities and can help elicit the underlying neural mechanisms of the brain. However, the computational burden is also formidable when we try to process the huge data stream generated by such recordings. In this study, we report the development of Neural Parallel Engine (NPE), a toolbox for massively parallel neural signal processing on graphical processing units (GPUs). It offers a selection of the most commonly used routines in neural signal processing such as spike detection and spike sorting, including advanced algorithms such as exponential-component-power-component (EC-PC) spike detection and binary pursuit spike sorting. We also propose a new method for detecting peaks in parallel through a parallel compact operation. Our toolbox is able to offer a 5× to 110× speedup compared with its CPU counterparts depending on the algorithms. A user-friendly MATLAB interface is provided to allow easy integration of the toolbox into existing workflows. Previous efforts on GPU neural signal processing only focus on a few rudimentary algorithms, are not well-optimized and often do not provide a user-friendly programming interface to fit into existing workflows. There is a strong need for a comprehensive toolbox for massively parallel neural signal processing. A new toolbox for massively parallel neural signal processing has been created. It can offer significant speedup in processing signals from large-scale recordings up to thousands of channels. Copyright © 2018 Elsevier B.V. All rights reserved.

A Signal Processing Method to Explore Similarity in Protein Flexibility

Directory of Open Access Journals (Sweden)

Simina Vasilache

2010-01-01

Full Text Available Understanding mechanisms of protein flexibility is of great importance to structural biology. The ability to detect similarities between proteins and their patterns is vital in discovering new information about unknown protein functions. A Distance Constraint Model (DCM provides a means to generate a variety of flexibility measures based on a given protein structure. Although information about mechanical properties of flexibility is critical for understanding protein function for a given protein, the question of whether certain characteristics are shared across homologous proteins is difficult to assess. For a proper assessment, a quantified measure of similarity is necessary. This paper begins to explore image processing techniques to quantify similarities in signals and images that characterize protein flexibility. The dataset considered here consists of three different families of proteins, with three proteins in each family. The similarities and differences found within flexibility measures across homologous proteins do not align with sequence-based evolutionary methods.

Fetal Cardiac Doppler Signal Processing Techniques: Challenges and Future Research Directions

Directory of Open Access Journals (Sweden)

Saeed Abdulrahman Alnuaimi

2017-12-01

Full Text Available The fetal Doppler Ultrasound (DUS is commonly used for monitoring fetal heart rate and can also be used for identifying the event timings of fetal cardiac valve motions. In early-stage fetuses, the detected Doppler signal suffers from noise and signal loss due to the fetal movements and changing fetal location during the measurement procedure. The fetal cardiac intervals, which can be estimated by measuring the fetal cardiac event timings, are the most important markers of fetal development and well-being. To advance DUS-based fetal monitoring methods, several powerful and well-advanced signal processing and machine learning methods have recently been developed. This review provides an overview of the existing techniques used in fetal cardiac activity monitoring and a comprehensive survey on fetal cardiac Doppler signal processing frameworks. The review is structured with a focus on their shortcomings and advantages, which helps in understanding fetal Doppler cardiogram signal processing methods and the related Doppler signal analysis procedures by providing valuable clinical information. Finally, a set of recommendations are suggested for future research directions and the use of fetal cardiac Doppler signal analysis, processing, and modeling to address the underlying challenges.

Genomic signal processing for DNA sequence clustering.

Science.gov (United States)

Mendizabal-Ruiz, Gerardo; Román-Godínez, Israel; Torres-Ramos, Sulema; Salido-Ruiz, Ricardo A; Vélez-Pérez, Hugo; Morales, J Alejandro

2018-01-01

Genomic signal processing (GSP) methods which convert DNA data to numerical values have recently been proposed, which would offer the opportunity of employing existing digital signal processing methods for genomic data. One of the most used methods for exploring data is cluster analysis which refers to the unsupervised classification of patterns in data. In this paper, we propose a novel approach for performing cluster analysis of DNA sequences that is based on the use of GSP methods and the K-means algorithm. We also propose a visualization method that facilitates the easy inspection and analysis of the results and possible hidden behaviors. Our results support the feasibility of employing the proposed method to find and easily visualize interesting features of sets of DNA data.

Systems Biology Graphical Notation: Process Description language Level 1 Version 1.3.

Science.gov (United States)

Moodie, Stuart; Le Novère, Nicolas; Demir, Emek; Mi, Huaiyu; Villéger, Alice

2015-09-04

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Process Description language represents biological entities and processes between these entities within a network. SBGN PD focuses on the mechanistic description and temporal dependencies of biological interactions and transformations. The nodes (elements) are split into entity nodes describing, e.g., metabolites, proteins, genes and complexes, and process nodes describing, e.g., reactions and associations. The edges (connections) provide descriptions of relationships (or influences) between the nodes, such as consumption, production, stimulation and inhibition. Among all three languages of SBGN, PD is the closest to metabolic and regulatory pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm.

Science.gov (United States)

Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence

2012-08-29

Mathematical modeling is used as a Systems Biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and predict the effect of perturbations. This article presents an algorithm for modeling biological networks in a discrete framework with continuous time. There exist two major types of mathematical modeling approaches: (1) quantitative modeling, representing various chemical species concentrations by real numbers, mainly based on differential equations and chemical kinetics formalism; (2) and qualitative modeling, representing chemical species concentrations or activities by a finite set of discrete values. Both approaches answer particular (and often different) biological questions. Qualitative modeling approach permits a simple and less detailed description of the biological systems, efficiently describes stable state identification but remains inconvenient in describing the transient kinetics leading to these states. In this context, time is represented by discrete steps. Quantitative modeling, on the other hand, can describe more accurately the dynamical behavior of biological processes as it follows the evolution of concentration or activities of chemical species as a function of time, but requires an important amount of information on the parameters difficult to find in the literature. Here, we propose a modeling framework based on a qualitative approach that is intrinsically continuous in time. The algorithm presented in this article fills the gap between qualitative and quantitative modeling. It is based on continuous time Markov process applied on a Boolean state space. In order to describe the temporal evolution of the biological process we wish to model, we explicitly specify the transition rates for each node. For that purpose, we built a language that can be seen as a generalization of Boolean equations. Mathematically, this approach can be translated in a set of ordinary differential

Telemetry System of Biological Parameters

Directory of Open Access Journals (Sweden)

Jan Spisak

2005-01-01

Full Text Available The mobile telemetry system of biological parameters serves for reading and wireless data transfer of measured values of selected biological parameters to an outlying computer. It concerns basically long time monitoring of vital function of car pilot.The goal of this projects is to propose mobile telemetry system for reading, wireless transfer and processing of biological parameters of car pilot during physical and psychical stress. It has to be made with respect to minimal consumption, weight and maximal device mobility. This system has to eliminate signal noise, which is created by biological artifacts and disturbances during the data transfer.

Pulse shaping for all-optical signal processing of ultra-high bit rate serial data signals

DEFF Research Database (Denmark)

Palushani, Evarist

The following thesis concerns pulse shaping and optical waveform manipulation for all-optical signal processing of ultra-high bit rate serial data signals, including generation of optical pulses in the femtosecond regime, serial-to-parallel conversion and terabaud coherent optical time division...

Smart signal processing for an evolving electric grid

Science.gov (United States)

Silva, Leandro Rodrigues Manso; Duque, Calos Augusto; Ribeiro, Paulo F.

2015-12-01

Electric grids are interconnected complex systems consisting of generation, transmission, distribution, and active loads, recently called prosumers as they produce and consume electric energy. Additionally, these encompass a vast array of equipment such as machines, power transformers, capacitor banks, power electronic devices, motors, etc. that are continuously evolving in their demand characteristics. Given these conditions, signal processing is becoming an essential assessment tool to enable the engineer and researcher to understand, plan, design, and operate the complex and smart electronic grid of the future. This paper focuses on recent developments associated with signal processing applied to power system analysis in terms of characterization and diagnostics. The following techniques are reviewed and their characteristics and applications discussed: active power system monitoring, sparse representation of power system signal, real-time resampling, and time-frequency (i.e., wavelets) applied to power fluctuations.

Stochastic transport processes in discrete biological systems

CERN Document Server

Frehland, Eckart

1982-01-01

These notes are in part based on a course for advanced students in the applications of stochastic processes held in 1978 at the University of Konstanz. These notes contain the results of re­ cent studies on the stochastic description of ion transport through biological membranes. In particular, they serve as an introduction to an unified theory of fluctuations in complex biological transport systems. We emphasize that the subject of this volume is not to introduce the mathematics of stochastic processes but to present a field of theoretical biophysics in which stochastic methods are important. In the last years the study of membrane noise has become an important method in biophysics. Valuable information on the ion transport mechanisms in membranes can be obtained from noise analysis. A number of different processes such as the opening and closing of ion channels have been shown to be sources of the measured current or voltage fluctuations. Bio­ logical 'transport systems can be complex. For example, the tr...

Cyclic LTI Systems in Digital Signal Processing

National Research Council Canada - National Science Library

Vaidyanathan, P

1998-01-01

.... While circular convolution has been the centerpiece of many algorithms in signal processing for decades, such freedom, especially from the viewpoint of linear system theory, has not been studied in the past...

Acoustic Emission Signal Processing Technique to Characterize Reactor In-Pile Phenomena

Energy Technology Data Exchange (ETDEWEB)

Vivek Agarwal; Magdy Samy Tawfik; James A Smith

2014-07-01

Existing and developing advanced sensor technologies and instrumentation will allow non-intrusive in-pile measurement of temperature, extension, and fission gases when coupled with advanced signal processing algorithms. The transmitted measured sensor signals from inside to the outside of containment structure are corrupted by noise and are attenuated, thereby reducing the signal strength and signal-to-noise ratio. Identification and extraction of actual signal (representative of an in-pile phenomenon) is a challenging and complicated process. In this paper, empirical mode decomposition technique is proposed to reconstruct actual sensor signal by partially combining intrinsic mode functions. Reconstructed signal corresponds to phenomena and/or failure modes occurring inside the reactor. In addition, it allows accurate non-intrusive monitoring and trending of in-pile phenomena.

Hidden Markov processes theory and applications to biology

CERN Document Server

Vidyasagar, M

2014-01-01

This book explores important aspects of Markov and hidden Markov processes and the applications of these ideas to various problems in computational biology. The book starts from first principles, so that no previous knowledge of probability is necessary. However, the work is rigorous and mathematical, making it useful to engineers and mathematicians, even those not interested in biological applications. A range of exercises is provided, including drills to familiarize the reader with concepts and more advanced problems that require deep thinking about the theory. Biological applications are t

Information theory based approaches to cellular signaling.

Science.gov (United States)

Waltermann, Christian; Klipp, Edda

2011-10-01

Cells interact with their environment and they have to react adequately to internal and external changes such changes in nutrient composition, physical properties like temperature or osmolarity and other stresses. More specifically, they must be able to evaluate whether the external change is significant or just in the range of noise. Based on multiple external parameters they have to compute an optimal response. Cellular signaling pathways are considered as the major means of information perception and transmission in cells. Here, we review different attempts to quantify information processing on the level of individual cells. We refer to Shannon entropy, mutual information, and informal measures of signaling pathway cross-talk and specificity. Information theory in systems biology has been successfully applied to identification of optimal pathway structures, mutual information and entropy as system response in sensitivity analysis, and quantification of input and output information. While the study of information transmission within the framework of information theory in technical systems is an advanced field with high impact in engineering and telecommunication, its application to biological objects and processes is still restricted to specific fields such as neuroscience, structural and molecular biology. However, in systems biology dealing with a holistic understanding of biochemical systems and cellular signaling only recently a number of examples for the application of information theory have emerged. This article is part of a Special Issue entitled Systems Biology of Microorganisms. Copyright © 2011 Elsevier B.V. All rights reserved.

Ultrasonic signal processing for sizing under-clad flaws

International Nuclear Information System (INIS)

Shankar, R.; Paradiso, T.J.; Lane, S.S.; Quinn, J.R.

1985-01-01

Ultrasonic digital data were collected from underclad cracks in sample pressure vessel specimen blocks. These blocks were weld cladded under different processes to simulate actual conditions in US Pressure Water Reactors. Each crack was represented by a flaw-echo dynamic curve which is a plot of the transducer motion on the surface as a function of the ultrasonic response into the material. Crack depth sizing was performed by identifying in the dynamic curve the crack tip diffraction signals from the upper and lower tips. This paper describes the experimental procedure, digital signal processing methods used and algorithms developed for crack depth sizing

Maglev Train Signal Processing Architecture Based on Nonlinear Discrete Tracking Differentiator.

Science.gov (United States)

Wang, Zhiqiang; Li, Xiaolong; Xie, Yunde; Long, Zhiqiang

2018-05-24

In a maglev train levitation system, signal processing plays an important role for the reason that some sensor signals are prone to be corrupted by noise due to the harsh installation and operation environment of sensors and some signals cannot be acquired directly via sensors. Based on these concerns, an architecture based on a new type of nonlinear second-order discrete tracking differentiator is proposed. The function of this signal processing architecture includes filtering signal noise and acquiring needed signals for levitation purposes. The proposed tracking differentiator possesses the advantages of quick convergence, no fluttering, and simple calculation. Tracking differentiator's frequency characteristics at different parameter values are studied in this paper. The performance of this new type of tracking differentiator is tested in a MATLAB simulation and this tracking-differentiator is implemented in Very-High-Speed Integrated Circuit Hardware Description Language (VHDL). In the end, experiments are conducted separately on a test board and a maglev train model. Simulation and experiment results show that the performance of this novel signal processing architecture can fulfill the real system requirement.

Maglev Train Signal Processing Architecture Based on Nonlinear Discrete Tracking Differentiator

Directory of Open Access Journals (Sweden)

Zhiqiang Wang

2018-05-01

Full Text Available In a maglev train levitation system, signal processing plays an important role for the reason that some sensor signals are prone to be corrupted by noise due to the harsh installation and operation environment of sensors and some signals cannot be acquired directly via sensors. Based on these concerns, an architecture based on a new type of nonlinear second-order discrete tracking differentiator is proposed. The function of this signal processing architecture includes filtering signal noise and acquiring needed signals for levitation purposes. The proposed tracking differentiator possesses the advantages of quick convergence, no fluttering, and simple calculation. Tracking differentiator’s frequency characteristics at different parameter values are studied in this paper. The performance of this new type of tracking differentiator is tested in a MATLAB simulation and this tracking-differentiator is implemented in Very-High-Speed Integrated Circuit Hardware Description Language (VHDL. In the end, experiments are conducted separately on a test board and a maglev train model. Simulation and experiment results show that the performance of this novel signal processing architecture can fulfill the real system requirement.

Digital signal processing for velocity measurements in dynamical material's behaviour studies

International Nuclear Information System (INIS)

Devlaminck, Julien; Luc, Jerome; Chanal, Pierre-Yves

2014-01-01

In this work, we describe different configurations of optical fiber interferometers (types Michelson and Mach-Zehnder) used to measure velocities during dynamical material's behaviour studies. We detail the algorithms of processing developed and optimized to improve the performance of these interferometers especially in terms of time and frequency resolutions. Three methods of analysis of interferometric signals were studied. For Michelson interferometers, the time-frequency analysis of signals by Short-Time Fourier Transform (STFT) is compared to a time-frequency analysis by Continuous Wavelet Transform (CWT). The results have shown that the CWT was more suitable than the STFT for signals with low signal-to-noise, and low velocity and high acceleration areas. For Mach- Zehnder interferometers, the measurement is carried out by analyzing the phase shift between three interferometric signals (Triature processing). These three methods of digital signal processing were evaluated, their measurement uncertainties estimated, and their restrictions or operational limitations specified from experimental results performed on a pulsed power machine. (authors)

Students’ learning activities while studying biological process diagrams

NARCIS (Netherlands)

Kragten, M.; Admiraal, W.; Rijlaarsdam, G.

2015-01-01

Process diagrams describe how a system functions (e.g. photosynthesis) and are an important type of representation in Biology education. In the present study, we examined students’ learning activities while studying process diagrams, related to their resulting comprehension of these diagrams. Each

Advanced Signal Processing for MIMO-OFDM Receivers

DEFF Research Database (Denmark)

Manchón, Carles Navarro

This thesis deals with a wide range of topics within the research area of advanced baseband receiver design for wireless communication systems. In particular, the work focuses on signal processing algorithms for receivers in multiple-input multiple-output (MIMO) orthogonal frequency-division mult......This thesis deals with a wide range of topics within the research area of advanced baseband receiver design for wireless communication systems. In particular, the work focuses on signal processing algorithms for receivers in multiple-input multiple-output (MIMO) orthogonal frequency...... the structure of the receiver with the hope that the resulting heuristic architecture will exhibit the desired behavior and performance. On the other hand, one can employ analytical frameworks to pose the problem as the optimization of a global objective function subject to certain constraints. This work...

Beacon Editor: Capturing Signal Transduction Pathways Using the Systems Biology Graphical Notation Activity Flow Language.

Science.gov (United States)

Elmarakeby, Haitham; Arefiyan, Mostafa; Myers, Elijah; Li, Song; Grene, Ruth; Heath, Lenwood S

2017-12-01

The Beacon Editor is a cross-platform desktop application for the creation and modification of signal transduction pathways using the Systems Biology Graphical Notation Activity Flow (SBGN-AF) language. Prompted by biologists' requests for enhancements, the Beacon Editor includes numerous powerful features for the benefit of creation and presentation.

Real-time digital signal processing fundamentals, implementations and applications

CERN Document Server

Kuo, Sen M; Tian, Wenshun

2013-01-01

Combines both the DSP principles and real-time implementations and applications, and now updated with the new eZdsp USB Stick, which is very low cost, portable and widely employed at many DSP labs. Real-Time Digital Signal Processing introduces fundamental digital signal processing (DSP) principles and will be updated to include the latest DSP applications, introduce new software development tools and adjust the software design process to reflect the latest advances in the field. In the 3rd edition of the book, the key aspect of hands-on experiments will be enhanced to make the DSP principle

Fourier analysis and stochastic processes

CERN Document Server

Brémaud, Pierre

2014-01-01

This work is unique as it provides a uniform treatment of the Fourier theories of functions (Fourier transforms and series, z-transforms), finite measures (characteristic functions, convergence in distribution), and stochastic processes (including arma series and point processes). It emphasises the links between these three themes. The chapter on the Fourier theory of point processes and signals structured by point processes is a novel addition to the literature on Fourier analysis of stochastic processes. It also connects the theory with recent lines of research such as biological spike signals and ultrawide-band communications. Although the treatment is mathematically rigorous, the convivial style makes the book accessible to a large audience. In particular, it will be interesting to anyone working in electrical engineering and communications, biology (point process signals) and econometrics (arma models). A careful review of the prerequisites (integration and probability theory in the appendix, Hilbert spa...

High signal to noise ratio THz spectroscopy with ASOPS and signal processing schemes for mapping and controlling molecular and bulk relaxation processes

International Nuclear Information System (INIS)

Hadjiloucas, S; Walker, G C; Bowen, J W; Becerra, V M; Zafiropoulos, A; Galvao, R K H

2009-01-01

Asynchronous Optical Sampling has the potential to improve signal to noise ratio in THz transient sperctrometry. The design of an inexpensive control scheme for synchronising two femtosecond pulse frequency comb generators at an offset frequency of 20 kHz is discussed. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing recorded THz transients in the time and frequency domain are outlined. Finally, possibilities for femtosecond pulse shaping using genetic algorithms are mentioned.

High signal to noise ratio THz spectroscopy with ASOPS and signal processing schemes for mapping and controlling molecular and bulk relaxation processes

Energy Technology Data Exchange (ETDEWEB)

Hadjiloucas, S; Walker, G C; Bowen, J W; Becerra, V M [Cybernetics, School of Systems Engineering, University of Reading, RG6 6AY (United Kingdom); Zafiropoulos, A [Biosystems Engineering Department, School of Agricultural Technology, Technological Educational Institute of Larissa, 411 10, Larissa (Greece); Galvao, R K H, E-mail: s.hadjiloucas@reading.ac.u [Divisao de Engenharia Eletronica, Instituto Tecnologico de Aeronautica, Sao Jose dos Campos, SP, 12228-900 Brazil (Brazil)

2009-08-01

Asynchronous Optical Sampling has the potential to improve signal to noise ratio in THz transient sperctrometry. The design of an inexpensive control scheme for synchronising two femtosecond pulse frequency comb generators at an offset frequency of 20 kHz is discussed. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing recorded THz transients in the time and frequency domain are outlined. Finally, possibilities for femtosecond pulse shaping using genetic algorithms are mentioned.

Students' Ability to Solve Process-Diagram Problems in Secondary Biology Education

Science.gov (United States)

Kragten, Marco; Admiraal, Wilfried; Rijlaarsdam, Gert

2015-01-01

Process diagrams are important tools in biology for explaining processes such as protein synthesis, compound cycles and the like. The aim of the present study was to measure the ability to solve process-diagram problems in biology and its relationship with prior knowledge, spatial ability and working memory. For this purpose, we developed a test…

Frames and operator theory in analysis and signal processing

CERN Document Server

Larson, David R; Nashed, Zuhair; Nguyen, Minh Chuong; Papadakis, Manos

2008-01-01

This volume contains articles based on talks presented at the Special Session Frames and Operator Theory in Analysis and Signal Processing, held in San Antonio, Texas, in January of 2006. Recently, the field of frames has undergone tremendous advancement. Most of the work in this field is focused on the design and construction of more versatile frames and frames tailored towards specific applications, e.g., finite dimensional uniform frames for cellular communication. In addition, frames are now becoming a hot topic in mathematical research as a part of many engineering applications, e.g., matching pursuits and greedy algorithms for image and signal processing. Topics covered in this book include: Application of several branches of analysis (e.g., PDEs; Fourier, wavelet, and harmonic analysis; transform techniques; data representations) to industrial and engineering problems, specifically image and signal processing. Theoretical and applied aspects of frames and wavelets. Pure aspects of operator theory empha...

CERN Technical Training 2003: Learning for the LHC ! DISP-2003 - Digital Signal Processing

CERN Multimedia

2003-01-01

DISP-2003 - Digital Signal Processing DISP-2003 is a two-term course given by CERN and University of Lausanne (UNIL) experts within the framework of the Technical Training Programme. The course will review the current techniques dealing with Digital Signal Processing, and it is intended for an audience who work or will work on digital signal processing aspects, and who need an introductory or refresher/update course. The course will be in English, with question and answers also in French. Spring 2 Term: DISP-2003: Advanced Digital Signal Processing 30 April 2003 - 21 May 2003, 4 lectures, Wednesdays afternoon (attendance cost: 40.- CHF, registration required) Lecturers: Léonard Studer, UNIL; Laurent Deniau, AT-MTM; Elena Wildner, AT-MAS Programme: Intelligent signal processing (ISP). Non-linear time series analysis. Image processing. Wavelets. (Basic concepts and definitions have been introduced during the previous Spring 1 Term: DISP-2003: Introduction to Digital Signal Processing). DISP-2003 is open...

Wavelet-Based Signal Processing of Electromagnetic Pulse Generated Waveforms

National Research Council Canada - National Science Library

Ardolino, Richard S

2007-01-01

This thesis investigated and compared alternative signal processing techniques that used wavelet-based methods instead of traditional frequency domain methods for processing measured electromagnetic pulse (EMP) waveforms...

Magnetic Nanotweezers for Interrogating Biological Processes in Space and Time.

Science.gov (United States)

Kim, Ji-Wook; Jeong, Hee-Kyung; Southard, Kaden M; Jun, Young-Wook; Cheon, Jinwoo

2018-04-17

The ability to sense and manipulate the state of biological systems has been extensively advanced during the past decade with the help of recent developments in physical tools. Unlike standard genetic and pharmacological perturbation techniques-knockdown, overexpression, small molecule inhibition-that provide a basic on/off switching capability, these physical tools provide the capacity to control the spatial, temporal, and mechanical properties of the biological targets. Among the various physical cues, magnetism offers distinct advantages over light or electricity. Magnetic fields freely penetrate biological tissues and are already used for clinical applications. As one of the unique features, magnetic fields can be transformed into mechanical stimuli which can serve as a cue in regulating biological processes. However, their biological applications have been limited due to a lack of high-performance magnetism-to-mechanical force transducers with advanced spatiotemporal capabilities. In this Account, we present recent developments in magnetic nanotweezers (MNTs) as a useful tool for interrogating the spatiotemporal control of cells in living tissue. MNTs are composed of force-generating magnetic nanoparticles and field generators. Through proper design and the integration of individual components, MNTs deliver controlled mechanical stimulation to targeted biomolecules at any desired space and time. We first discuss about MNT configuration with different force-stimulation modes. By modulating geometry of the magnetic field generator, MNTs exert pulling, dipole-dipole attraction, and rotational forces to the target specifically and quantitatively. We discuss the key physical parameters determining force magnitude, which include magnetic field strength, magnetic field gradient, magnetic moment of the magnetic particle, as well as distance between the field generator and the particle. MNTs also can be used over a wide range of biological time scales. By simply

Boolean Models of Biological Processes Explain Cascade-Like Behavior.

Science.gov (United States)

Chen, Hao; Wang, Guanyu; Simha, Rahul; Du, Chenghang; Zeng, Chen

2016-01-29

Biological networks play a key role in determining biological function and therefore, an understanding of their structure and dynamics is of central interest in systems biology. In Boolean models of such networks, the status of each molecule is either "on" or "off" and along with the molecules interact with each other, their individual status changes from "on" to "off" or vice-versa and the system of molecules in the network collectively go through a sequence of changes in state. This sequence of changes is termed a biological process. In this paper, we examine the common perception that events in biomolecular networks occur sequentially, in a cascade-like manner, and ask whether this is likely to be an inherent property. In further investigations of the budding and fission yeast cell-cycle, we identify two generic dynamical rules. A Boolean system that complies with these rules will automatically have a certain robustness. By considering the biological requirements in robustness and designability, we show that those Boolean dynamical systems, compared to an arbitrary dynamical system, statistically present the characteristics of cascadeness and sequentiality, as observed in the budding and fission yeast cell- cycle. These results suggest that cascade-like behavior might be an intrinsic property of biological processes.

Application of wavelet analysis to signal processing methods for eddy-current test

International Nuclear Information System (INIS)

Chen, G.; Yoneyama, H.; Yamaguchi, A.; Uesugi, N.

1998-01-01

This study deals with the application of wavelet analysis to detection and characterization of defects from eddy-current and ultrasonic testing signals of a low signal-to-noise ratio. Presented in this paper are the methods for processing eddy-current testing signals of heat exchanger tubes of a steam generator in a nuclear power plant. The results of processing eddy-current testing signals of tube testpieces with artificial flaws show that the flaw signals corrupted by noise and/or non-defect signals can be effectively detected and characterized by using the wavelet methods. (author)

2nd International Symposium on Signal Processing and Intelligent Recognition Systems

CERN Document Server

Bandyopadhyay, Sanghamitra; Krishnan, Sri; Li, Kuan-Ching; Mosin, Sergey; Ma, Maode

2016-01-01

This Edited Volume contains a selection of refereed and revised papers originally presented at the second International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS-2015), December 16-19, 2015, Trivandrum, India. The program committee received 175 submissions. Each paper was peer reviewed by at least three or more independent referees of the program committee and the 59 papers were finally selected. The papers offer stimulating insights into biometrics, digital watermarking, recognition systems, image and video processing, signal and speech processing, pattern recognition, machine learning and knowledge-based systems. The book is directed to the researchers and scientists engaged in various field of signal processing and related areas. .

Processing of seismic signals from a seismometer network

International Nuclear Information System (INIS)

Key, F.A.; Warburton, P.J.

1983-08-01

A description is given of the Seismometer Network Analysis Computer (SNAC) which processes short period data from a network of seismometers (UKNET). The nine stations of the network are distributed throughout the UK and their outputs are transmitted to a control laboratory (Blacknest) where SNAC monitors the data for seismic signals. The computer gives an estimate of the source location of the detected signals and stores the waveforms. The detection logic is designed to maintain high sensitivity without excessive ''false alarms''. It is demonstrated that the system is able to detect seismic signals at an amplitude level consistent with a network of single stations and, within the limitations of signal onset time measurements made by machine, can locate the source of the seismic disturbance. (author)

IDP++: signal and image processing algorithms in C++ version 4.1

International Nuclear Information System (INIS)

Lehman, S.K.

1996-11-01

IDP++ (Image and Data Processing in C++) is a collection of signal and image processing algorithms written in C++. It is a compiled signal processing environment which supports four data types of up to four dimensions. It is developed within Lawrence Livermore National Laboratory's Image and Data Processing group as a partial replacement for View. IDP ++ takes advantage of the latest, implemented and actually working, object-oriented compiler technology to provide 'information hiding.' Users need only know C, not C++. Signals are treated like any other variable with a defined set of operators and functions in an intuitive manner. IDP++ is designed for real-time environment where interpreted processing packages are less efficient. IDP++ exists for both SUNs and Silicon Graphics using their most current compilers

Digital signal and image processing using Matlab

CERN Document Server

Blanchet , Gérard

2015-01-01

The most important theoretical aspects of Image and Signal Processing (ISP) for both deterministic and random signals, the theory being supported by exercises and computer simulations relating to real applications.   More than 200 programs and functions are provided in the MATLAB® language, with useful comments and guidance, to enable numerical experiments to be carried out, thus allowing readers to develop a deeper understanding of both the theoretical and practical aspects of this subject.  Following on from the first volume, this second installation takes a more practical stance, provi

Digital signal and image processing using MATLAB

CERN Document Server

Blanchet , Gérard

2014-01-01

This fully revised and updated second edition presents the most important theoretical aspects of Image and Signal Processing (ISP) for both deterministic and random signals. The theory is supported by exercises and computer simulations relating to real applications. More than 200 programs and functions are provided in the MATLABÒ language, with useful comments and guidance, to enable numerical experiments to be carried out, thus allowing readers to develop a deeper understanding of both the theoretical and practical aspects of this subject. This fully revised new edition updates : - the

DBPM signal processing with field programmable gate arrays

International Nuclear Information System (INIS)

Lai Longwei; Yi Xing; Zhang Ning; Yang Guisen; Wang Baopeng; Xiong Yun; Leng Yongbin; Yan Yingbing

2011-01-01

DBPM system performance is determined by the design and implementation of beam position signal processing algorithm. In order to develop the system, a beam position signal processing algorithm is implemented on FPGA. The hardware is a PMC board ICS-1554A-002 (GE Corp.) with FPGA chip XC5VSX95T. This paper adopts quadrature frequency mixing to down convert high frequency signal to base. Different from conventional method, the mixing is implemented by CORDIC algorithm. The algorithm theory and implementation details are discussed in this paper. As the board contains no front end gain controller, this paper introduces a published patent-pending technique that has been adopted to realize the function in digital logic. The whole design is implemented with VHDL language. An on-line evaluation has been carried on SSRF (Shanghai Synchrotron Radiation Facility)storage ring. Results indicate that the system turn-by-turn data can measure the real beam movement accurately,and system resolution is 1.1μm. (authors)

Redox processes in radiation biology and cancer

International Nuclear Information System (INIS)

Greenstock, C.L.

1981-01-01

Free-radical intermediates, particularly the activated oxygen species OH, O - 2 , and 1 O 2 , are implicated in many types of radiation damage to biological systems. In addition, these same species may be formed, either directly or indirectly through biochemical redox reactions, in both essential and aberrant metabolic processes. Cell survival and adaptation to an environment containing ionizing radiation and other physical and chemical carcinogens ultimately depend upon the cell's ability to maintain optimal function in response to free-radical damage at the chemical level. Many of these feedback control mechanisms are redox controlled. Radiation chemical techniques using selective radical scavengers, such as product analysis and pulse radiolysis, enable us to generate, observe, and characterize individually the nature and reactivity of potentially damaging free radicals. From an analysis of the chemical kinetics of free-radical involvement in biological damage, redox mechanisms are proposed to describe the early processes of radiation damage, redox mechanisms are proposed to describe the early processes of radiation damage, its protection and sensitization, and the role of free radicals in radiation and chemical carcinogenesis

2015 International Conference on Machine Learning and Signal Processing

CERN Document Server

Woo, Wai; Sulaiman, Hamzah; Othman, Mohd; Saat, Mohd

2016-01-01

This book presents important research findings and recent innovations in the field of machine learning and signal processing. A wide range of topics relating to machine learning and signal processing techniques and their applications are addressed in order to provide both researchers and practitioners with a valuable resource documenting the latest advances and trends. The book comprises a careful selection of the papers submitted to the 2015 International Conference on Machine Learning and Signal Processing (MALSIP 2015), which was held on 15–17 December 2015 in Ho Chi Minh City, Vietnam with the aim of offering researchers, academicians, and practitioners an ideal opportunity to disseminate their findings and achievements. All of the included contributions were chosen by expert peer reviewers from across the world on the basis of their interest to the community. In addition to presenting the latest in design, development, and research, the book provides access to numerous new algorithms for machine learni...

Optimisation in signal and image processing

CERN Document Server

Siarry, Patrick

2010-01-01

This book describes the optimization methods most commonly encountered in signal and image processing: artificial evolution and Parisian approach; wavelets and fractals; information criteria; training and quadratic programming; Bayesian formalism; probabilistic modeling; Markovian approach; hidden Markov models; and metaheuristics (genetic algorithms, ant colony algorithms, cross-entropy, particle swarm optimization, estimation of distribution algorithms, and artificial immune systems).

Liquid argon TPC signal formation, signal processing and reconstruction techniques

Science.gov (United States)

Baller, B.

2017-07-01

This document describes a reconstruction chain that was developed for the ArgoNeuT and MicroBooNE experiments at Fermilab. These experiments study accelerator neutrino interactions that occur in a Liquid Argon Time Projection Chamber. Reconstructing the properties of particles produced in these interactions benefits from the knowledge of the micro-physics processes that affect the creation and transport of ionization electrons to the readout system. A wire signal deconvolution technique was developed to convert wire signals to a standard form for hit reconstruction, to remove artifacts in the electronics chain and to remove coherent noise. A unique clustering algorithm reconstructs line-like trajectories and vertices in two dimensions which are then matched to create of 3D objects. These techniques and algorithms are available to all experiments that use the LArSoft suite of software.

Techware: www.sspnet.eu: A Web Portal for Social Signal Processing

NARCIS (Netherlands)

Vinciarelli, Alessandro; Ortega, A.; Pantic, Maja

In this issue, “Best of the Web‿ focuses on introducing the social signal processing network (SSPNet), a large European collaboration aimed at establishing a research community in social signal processing (SSP), the new, emerging domain aimed at bringing social intelligence in computers.

Nonlinear Silicon Photonic Signal Processing Devices for Future Optical Networks

Directory of Open Access Journals (Sweden)

Cosimo Lacava

2017-01-01

Full Text Available In this paper, we present a review on silicon-based nonlinear devices for all optical nonlinear processing of complex telecommunication signals. We discuss some recent developments achieved by our research group, through extensive collaborations with academic partners across Europe, on optical signal processing using silicon-germanium and amorphous silicon based waveguides as well as novel materials such as silicon rich silicon nitride and tantalum pentoxide. We review the performance of four wave mixing wavelength conversion applied on complex signals such as Differential Phase Shift Keying (DPSK, Quadrature Phase Shift Keying (QPSK, 16-Quadrature Amplitude Modulation (QAM and 64-QAM that dramatically enhance the telecom signal spectral efficiency, paving the way to next generation terabit all-optical networks.

Digital signal processing at GEND's data center

International Nuclear Information System (INIS)

Jackson, J.E.

1977-01-01

The conversion and recording of analog signals in digital form has been an active element in the manufacturing operations of the General Electric Neutron Devices Department (GEND) since 1966. The first computerized data system for these digitized waveforms was implemented at GEND's data center approximately two years later during 1968. The evolution and integration of these two activities at GEND are addressed in this paper. Beginning with the tester--data center interface, emphasis is placed on previous approaches, current capabilities, near-term trends, and future requirements. The digitizing process has developed into a firmly established set of hardware and associated software techniques which has proven itself as an accurate, reliable procedure for capturing waveform characteristics. The most important aspect of this process is the recent trend toward increased sampling rates and a greater number of digitized parameters per operation. The combined effect is a tremendous increase in output data volumes. Since digital signal processing carries the potential for significant contributions to manufacturing quality and reliability, as well as engineering design and development, increased activity in this area appears extremely desirable. 11 figures

Biologic phosphorus elimination - influencing parameters, boundary conditions, process optimation

International Nuclear Information System (INIS)

Dai Xiaohu.

1992-01-01

This paper first presents a systematic study of the basic process of biologic phosphorus elimination as employed by the original 'Phoredox (Main Stream) Process'. The conditions governing the process and the factors influencing its performance were determined by trial operation. A stationary model was developed for the purpose of modelling biologic phosphorus elimination in such a main stream process and optimising the dimensioning. The validity of the model was confirmed by operational data given in the literature and by operational data from the authors' own semitechnical-scale experimental plant. The model permits simulation of the values to be expected for effluent phosphorus and phosphate concentrations for given influent data and boundary conditions. It is thus possible to dimension a plant for accomodation of the original Phoredox (Main Stream) Process or any similar phosphorus eliminating plant that is to work according to the principle of the main stream process. (orig./EF) [de

Systems biology of adipose tissue metabolism: regulation of growth, signaling and inflammation.

Science.gov (United States)

Manteiga, Sara; Choi, Kyungoh; Jayaraman, Arul; Lee, Kyongbum

2013-01-01

Adipose tissue (AT) depots actively regulate whole body energy homeostasis by orchestrating complex communications with other physiological systems as well as within the tissue. Adipocytes readily respond to hormonal and nutritional inputs to store excess nutrients as intracellular lipids or mobilize the stored fat for utilization. Co-ordinated regulation of metabolic pathways balancing uptake, esterification, and hydrolysis of lipids is accomplished through positive and negative feedback interactions of regulatory hubs comprising several pleiotropic protein kinases and nuclear receptors. Metabolic regulation in adipocytes encompasses biogenesis and remodeling of uniquely large lipid droplets (LDs). The regulatory hubs also function as energy and nutrient sensors, and integrate metabolic regulation with intercellular signaling. Over-nutrition causes hypertrophic expansion of adipocytes, which, through incompletely understood mechanisms, initiates a cascade of metabolic and signaling events leading to tissue remodeling and immune cell recruitment. Macrophage activation and polarization toward a pro-inflammatory phenotype drives a self-reinforcing cycle of pro-inflammatory signals in the AT, establishing an inflammatory state. Sustained inflammation accelerates lipolysis and elevates free fatty acids in circulation, which robustly correlates with development of obesity-related diseases. The adipose regulatory network coupling metabolism, growth, and signaling of multiple cell types is exceedingly complex. While components of the regulatory network have been individually studied in exquisite detail, systems approaches have rarely been utilized to comprehensively assess the relative engagements of the components. Thus, need and opportunity exist to develop quantitative models of metabolic and signaling networks to achieve a more complete understanding of AT biology in both health and disease. Copyright © 2013 Wiley Periodicals, Inc.

The Ubiquitin System and Jasmonate Signaling

Directory of Open Access Journals (Sweden)

Astrid Nagels Durand

2016-01-01

Full Text Available The ubiquitin (Ub system is involved in most, if not all, biological processes in eukaryotes. The major specificity determinants of this system are the E3 ligases, which bind and ubiquitinate specific sets of proteins and are thereby responsible for target recruitment to the proteasome or other cellular processing machineries. The Ub system contributes to the regulation of the production, perception and signal transduction of plant hormones. Jasmonic acid (JA and its derivatives, known as jasmonates (JAs, act as signaling compounds regulating plant development and plant responses to various biotic and abiotic stress conditions. We provide here an overview of the current understanding of the Ub system involved in JA signaling.

PC add on card for processing of LSC signals

International Nuclear Information System (INIS)

Jadhav, S.R.; Nikhare, D.M.; Gurna, R.K.; Paulson, Molly; Kulkarni, C.P.; Vaidya, P.P.

2001-01-01

This paper describes PC- add on card developed at Electronics Division for processing of LSC signals. This card uses highly integrated digital and analog circuits, for entire processing of signals available from preamplifiers to get complete beta energy spectrum corresponding to coincident events in Liquid Scintillation Counting. LSC card along with High Voltage PC-add on card gives complete electronics required for LSC system. This card is also used in automatic LSC system along with interface circuits, which are used to control mechanical movements. (author)

Ultrafast signal processing in quantum dot amplifiers through effective spectral holeburning

DEFF Research Database (Denmark)

Berg, Tommy Winther; Mørk, Jesper; Uskov, A. V.

2002-01-01

suitable for ultrafast signal processing. The basis of this property is that the process of spectral hole burning (SHB) can become very effective. We consider a traveling wave optical amplifier consisting of the dot states, which interact with the optical signal (no inhomogeneous broadening included...

Tutorial: Signal Processing in Brain-Computer Interfaces

NARCIS (Netherlands)

Garcia Molina, G.

2010-01-01

Research in Electroencephalogram (EEG) based Brain-Computer Interfaces (BCIs) has been considerably expanding during the last few years. Such an expansion owes to a large extent to the multidisciplinary and challenging nature of BCI research. Signal processing undoubtedly constitutes an essential

New signal processing methods for the evaluation of eddy current NDT data

International Nuclear Information System (INIS)

Anon.

1987-01-01

Signal processing and pattern recognition methods play a crucial role in a number of areas associated with nondestructive evaluation. Defect characterization schemes often involve mapping the signal onto an appropriate feature domain and using pattern recognition techniques for classification. In addition, signal processing methods are also used to acquire, enhance, restore, and compress data. EPRI Project RP 2673-4 is concerned with developing new signal processing and pattern recognition techniques for evaluating eddy current signals. Efforts under this project have focused on three closely related areas. The thrust has been to: (1) develop a scheme to compress eddy current signals for the purposes of storing them in a compact form, (2) develop a robust clustering algorithm capable of discarding feature vectors that fall in the gray areas between clusters, and (3) investigate the feasibility of designing and developing a digital eddyscope

Hybrid digital signal processing and neural networks applications in PWRs

International Nuclear Information System (INIS)

Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

1991-01-01

Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications

Low-pass parabolic FFT filter for airborne and satellite lidar signal processing.

Science.gov (United States)

Jiao, Zhongke; Liu, Bo; Liu, Enhai; Yue, Yongjian

2015-10-14

In order to reduce random errors of the lidar signal inversion, a low-pass parabolic fast Fourier transform filter (PFFTF) was introduced for noise elimination. A compact airborne Raman lidar system was studied, which applied PFFTF to process lidar signals. Mathematics and simulations of PFFTF along with low pass filters, sliding mean filter (SMF), median filter (MF), empirical mode decomposition (EMD) and wavelet transform (WT) were studied, and the practical engineering value of PFFTF for lidar signal processing has been verified. The method has been tested on real lidar signal from Wyoming Cloud Lidar (WCL). Results show that PFFTF has advantages over the other methods. It keeps the high frequency components well and reduces much of the random noise simultaneously for lidar signal processing.

Design and measurement of signal processing system for cavity beam position monitor

International Nuclear Information System (INIS)

Wang Baopeng; Leng Yongbin; Yu Luyang; Zhou Weimin; Yuan Renxian; Chen Zhichu

2013-01-01

In this paper, in order to achieve the output signal processing of cavity beam position monitor (CBPM), we develop a digital intermediate frequency receiver architecture based signal processing system, which consists of radio frequency (RF) front end and high speed data acquisition board. The beam position resolution in the CBPM signal processing system is superior to 1 μm. Two signal processing algorithms, fast Fourier transform (FFT) and digital down converter (DDC), are evaluated offline using MATLAB platform, and both can be used to achieve, the CW input signal, position resolutions of 0.31 μm and 0.10 μm at -16 dBm. The DDC algorithm for its good compatibility is downloaded into the FPGA to realize online measurement, reaching the position resolution of 0.49 μm due to truncation error. The whole system works well and the performance meets design target. (authors)

Filtering and spectral processing of 1-D signals using cellular neural networks

NARCIS (Netherlands)

Moreira-Tamayo, O.; Pineda de Gyvez, J.

1996-01-01

This paper presents cellular neural networks (CNN) for one-dimensional discrete signal processing. Although CNN has been extensively used in image processing applications, little has been done for 1-dimensional signal processing. We propose a novel CNN architecture to carry out these tasks. This

Process for sewage biological treatment from uranium

International Nuclear Information System (INIS)

Popa, K.; Cecal, A.; Craciun, I.

2004-01-01

The invention relates to the sewage treatment, in particular to the sewage biological treatmen from radioactive waste, namely from uranium. The process dor sewage biological treatment from uranium includes cultivation in the sewage of the aquatic plants Lemna minor and Spirulina platensis. The plants cultivation is carried out in two stages. In the first stage for cultivation is used Lemna minor in the second stage - Spirulina platensis . After finishing the plant cultivation it is carried out separation of their biomass. The result of the invention consists in increasing the uranyl ions by the biomass of plants cultivated in the sewage

Process for sewage biological treatment from uranium

International Nuclear Information System (INIS)

Popa, Karin; Cecal, Alexandru; Craciun, Iftimie Ionel; Rudic, Valeriu; Gulea, Aurelian; Cepoi, Liliana

2004-01-01

The invention relates to the sewage treatment, in particular to the sewage biological treatment from radioactive waste, namely from uranium. The process for sewage biological treatment from uranium includes cultivation in the sewage of the aquatic plants Lemna minor and Spirulina platensis. The plant cultivation is carried out in two stages. In the first stage for cultivation is used Lemna minor and in the second stage - Spirulina platensis. After finishing the plant cultivation it is carried out separation of their biomass. The result of the invention consists in increasing the uranyl ions accumulation by the biomass of plants cultivated in the sewage.

Tunable signal processing in synthetic MAP kinase cascades.

Science.gov (United States)

O'Shaughnessy, Ellen C; Palani, Santhosh; Collins, James J; Sarkar, Casim A

2011-01-07

The flexibility of MAPK cascade responses enables regulation of a vast array of cell fate decisions, but elucidating the mechanisms underlying this plasticity is difficult in endogenous signaling networks. We constructed insulated mammalian MAPK cascades in yeast to explore how intrinsic and extrinsic perturbations affect the flexibility of these synthetic signaling modules. Contrary to biphasic dependence on scaffold concentration, we observe monotonic decreases in signal strength as scaffold concentration increases. We find that augmenting the concentration of sequential kinases can enhance ultrasensitivity and lower the activation threshold. Further, integrating negative regulation and concentration variation can decouple ultrasensitivity and threshold from the strength of the response. Computational analyses show that cascading can generate ultrasensitivity and that natural cascades with different kinase concentrations are innately biased toward their distinct activation profiles. This work demonstrates that tunable signal processing is inherent to minimal MAPK modules and elucidates principles for rational design of synthetic signaling systems. Copyright © 2011 Elsevier Inc. All rights reserved.

Visible light communications modulation and signal processing

CERN Document Server

Wang, Zhaocheng; Huang, Wei; Xu, Zhengyuan

2018-01-01

This informative new book on state-of-the-art visible light communication (VLC) provides, for the first time, a systematical and advanced treatment of modulation and signal processing for VLC. Visible Light Communications: Modulation and Signal Processing offers a practical guide to designing VLC, linking academic research with commercial applications. In recent years, VLC has attracted attention from academia and industry since it has many advantages over the traditional radio frequency, including wide unregulated bandwidth, high security, and low cost. It is a promising complementary technique in 5G and beyond wireless communications, especially in indoor applications. However, lighting constraints have not been fully considered in the open literature when considering VLC system design, and its importance has been underestimated. That’s why this book—written by a team of experts with both academic research experience and industrial development experience in the field—is so welcome. To help readers u...

Feasibility of Johnson Noise Thermometry based on Digital Signal Processing Techniques

International Nuclear Information System (INIS)

Hwang, In Koo; Kim, Yang Mo

2014-01-01

This paper presents an implementation strategy of noise thermometry based on a digital signal processing technique and demonstrates its feasibilities. A key factor in its development is how to extract the small thermal noise signal from other noises, for example, random noise from amplifiers and continuous electromagnetic interference from the environment. The proposed system consists of two identical amplifiers and uses a cross correlation function to cancel the random noise of the amplifiers. Then, the external interference noises are eliminated by discriminating the difference in the peaks between the thermal signal and external noise. The gain of the amplifiers is estimated by injecting an already known pilot signal. The experimental simulation results of signal processing methods have demonstrated that the proposed approach is an effective method in eliminating an external noise signal and performing gain correction for development of the thermometry

Monitoring of drilling process with the application of acoustic signal

Directory of Open Access Journals (Sweden)

Labaš Milan

2000-09-01

Full Text Available Monitoring of rock disintegration process at drilling, scanning of input quantities: thrust F, revolution n and the course of some output quantities: the drilling rate v and the power input P are needed for the control of this process. We can calculate the specific volume work of rock disintegration w and ϕ - quotient of drilling rate v and the specific volume work of disintegration w from the presented quantities.Works on an expertimental stand showed that the correlation relationships between the input and output quantities can be found by scanning the accompanying sound of the drilling proces.Research of the rock disintegration with small-diameter diamond drill tools and different rock types is done at the Institute of Geotechnics. The aim of this research is the possibility of monitoring and controlling the rock disintegration process with the application of acoustic signal. The acoustic vibrations accompanying the drilling process are recorded by a microphone placed in a defined position in the acoustic space. The drilling device (drilling stand, the drilling tool and the rock are the source of sound. Two basic sound states exist in the drilling stand research : the noise at no-load running and the noise at the rotary drilling of rock. Suitable quantities for optimizing the rock disintegration process are searched by the study of the acoustic signal. The dominant frequencies that characterize the disintegration process for the given rock and tool are searched by the analysis of the acoustic signal. The analysis of dominant frequencies indicates the possibility of determining an optimal regime for the maximal drilling rate. Extreme of the specific disintegration energy is determinated by the dispersion of the dominant frequency.The scanned acoustic signal is processed by the Fourier transformation. The Fourier transformation facilitates the distribution of the general non-harmonic periodic process into harmonic components. The harmonic

Missile signal processing common computer architecture for rapid technology upgrade

Science.gov (United States)

Rabinkin, Daniel V.; Rutledge, Edward; Monticciolo, Paul

2004-10-01

Interceptor missiles process IR images to locate an intended target and guide the interceptor towards it. Signal processing requirements have increased as the sensor bandwidth increases and interceptors operate against more sophisticated targets. A typical interceptor signal processing chain is comprised of two parts. Front-end video processing operates on all pixels of the image and performs such operations as non-uniformity correction (NUC), image stabilization, frame integration and detection. Back-end target processing, which tracks and classifies targets detected in the image, performs such algorithms as Kalman tracking, spectral feature extraction and target discrimination. In the past, video processing was implemented using ASIC components or FPGAs because computation requirements exceeded the throughput of general-purpose processors. Target processing was performed using hybrid architectures that included ASICs, DSPs and general-purpose processors. The resulting systems tended to be function-specific, and required custom software development. They were developed using non-integrated toolsets and test equipment was developed along with the processor platform. The lifespan of a system utilizing the signal processing platform often spans decades, while the specialized nature of processor hardware and software makes it difficult and costly to upgrade. As a result, the signal processing systems often run on outdated technology, algorithms are difficult to update, and system effectiveness is impaired by the inability to rapidly respond to new threats. A new design approach is made possible three developments; Moore's Law - driven improvement in computational throughput; a newly introduced vector computing capability in general purpose processors; and a modern set of open interface software standards. Today's multiprocessor commercial-off-the-shelf (COTS) platforms have sufficient throughput to support interceptor signal processing requirements. This application

Nuclear spectrometry signal acquisition and processing system based on LabVIEW and C

International Nuclear Information System (INIS)

Chen Xiaojun; Fang Fang; Chen Mingchi; Jiang Zancheng; Wang Min

2008-01-01

The process of designing nuclear spectrometry signal acquisition and processing system based on virtual instrument technology is showed in this article. For the deficiency of LabVIEW in big data analyzing and processing, a method is presented in which C programmer is inserted and applied in signal smoothing, peak searching and area of the peak calculating. A complete nuclear spectrometry signal acquisition, processing and document management system is implemented. (authors)

Low power digital signal processing

DEFF Research Database (Denmark)

Paker, Ozgun

2003-01-01

hardwired ASICs and more than 6 21 times lower than current state of the art low-power DSP processors. An orthogonal but practical contribution of this thesis is the test bench implementation. A PCI-based FPGA board has been used to equip a standard desktop PC with tester facilities. The test bench proved...... to be a viable alternative to conventional expensive test equipment. Finally, the work presented in this thesis has been published at several IEEE workshops and conferences, and in the Journal of VLSI Signal Processing....

Regulation of IGF-1 signaling by microRNAs

Directory of Open Access Journals (Sweden)

Hwa Jin eJung

2015-01-01

Full Text Available The insulin-like growth factor 1 (IGF-1 signaling pathway regulates critical biological processes including development, homeostasis, and aging. Dysregulation of this pathway has been implicated in a myriad of diseases such as cancers, neurodegenerative diseases, and metabolic disorders, making the IGF-1 signaling pathway a prime target to develop therapeutic and intervention strategies. Recently, small non-coding RNA molecules in ~22 nucleotide length, microRNAs (miRNAs, have emerged as a new regulator of biological processes in virtually all organ systems and increasing studies are linking altered miRNA function to disease mechanisms. A miRNA binds to 3’UTRs of multiple target genes and coordinately down-regulates their expression, thereby exerting a profound influence on gene regulatory networks. Here we review the components of the IGF-1 signaling pathway that are known targets of miRNA regulation, and highlight recent studies that suggest therapeutic potential of these miRNAs against various diseases.

Signal processing for the profoundly deaf.

Science.gov (United States)

Boothyroyd, A

1990-01-01

Profound deafness, defined here as a hearing loss in excess of 90 dB, is characterized by high thresholds, reduced hearing range in the intensity and frequency domains, and poor resolution in the frequency and time domains. The high thresholds call for hearing aids with unusually high gains or remote microphones that can be placed close to the signal source. The former option creates acoustic feedback problems for which digital signal processing may yet offer solutions. The latter option calls for carrier wave technology that is already available. The reduced frequency and intensity ranges would appear to call for frequency and/or amplitude compression. It might also be argued, however, that any attempts to compress the acoustic signal into the limited hearing range of the profoundly deaf will be counterproductive because of poor frequency and time resolution, especially when the signal is present in noise. In experiments with a 2-channel compression system, only 1 of 9 subjects showed an improvement of perception with the introduction of fast-release (20 ms) compression. The other 8 experienced no benefit or a slight deterioration of performance. These results support the concept of providing the profoundly deaf with simpler, rather than more complex, patterns, perhaps through the use of feature extraction hearing aids. Data from users of cochlear implants already employing feature extraction techniques also support this concept.

Tongue and Taste Organ Biology and Function: Homeostasis Maintained by Hedgehog Signaling.

Science.gov (United States)

Mistretta, Charlotte M; Kumari, Archana

2017-02-10

The tongue is an elaborate complex of heterogeneous tissues with taste organs of diverse embryonic origins. The lingual taste organs are papillae, composed of an epithelium that includes specialized taste buds, the basal lamina, and a lamina propria core with matrix molecules, fibroblasts, nerves, and vessels. Because taste organs are dynamic in cell biology and sensory function, homeostasis requires tight regulation in specific compartments or niches. Recently, the Hedgehog (Hh) pathway has emerged as an essential regulator that maintains lingual taste papillae, taste bud and progenitor cell proliferation and differentiation, and neurophysiological function. Activating or suppressing Hh signaling, with genetic models or pharmacological agents used in cancer treatments, disrupts taste papilla and taste bud integrity and can eliminate responses from taste nerves to chemical stimuli but not to touch or temperature. Understanding Hh regulation of taste organ homeostasis contributes knowledge about the basic biology underlying taste disruptions in patients treated with Hh pathway inhibitors.

Optimal and adaptive methods of processing hydroacoustic signals (review)

Science.gov (United States)

Malyshkin, G. S.; Sidel'nikov, G. B.

2014-09-01

Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.

Digital Signal Processing and Control for the Study of Gene Networks

Science.gov (United States)

Shin, Yong-Jun

2016-04-01

Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks.

Signal processing for 5G algorithms and implementations

CERN Document Server

Luo, Fa-Long

2016-01-01

A comprehensive and invaluable guide to 5G technology, implementation and practice in one single volume. For all things 5G, this book is a must-read. Signal processing techniques have played the most important role in wireless communications since the second generation of cellular systems. It is anticipated that new techniques employed in 5G wireless networks will not only improve peak service rates significantly, but also enhance capacity, coverage, reliability , low-latency, efficiency, flexibility, compatibility and convergence to meet the increasing demands imposed by applications such as big data, cloud service, machine-to-machine (M2M) and mission-critical communications. This book is a comprehensive and detailed guide to all signal processing techniques employed in 5G wireless networks. Uniquely organized into four categories, New Modulation and &n sp;Coding, New Spatial Processing, New Spectrum Opportunities and New System-level Enabling Technologies, it covers everything from network architecture...

Power systems signal processing for smart grids

NARCIS (Netherlands)

Ribeiro, P.F.; Duque, C.A.; Da Silveira, P.M.; Cerqueira, A.S.

2013-01-01

With special relation to smart grids, this book provides clear and comprehensive explanation of how Digital Signal Processing (DSP) and Computational Intelligence (CI) techniques can be applied to solve problems in the power system. Its unique coverage bridges the gap between DSP, electrical power

Broadband Nonlinear Signal Processing in Silicon Nanowires

DEFF Research Database (Denmark)

Yvind, Kresten; Pu, Minhao; Hvam, Jørn Märcher

The fast non-linearity of silicon allows Tbit/s optical signal processing. By choosing suitable dimensions of silicon nanowires their dispersion can be tailored to ensure a high nonlinearity at power levels low enough to avoid significant two-photon abso We have fabricated low insertion...

Computer Aided Teaching of Digital Signal Processing.

Science.gov (United States)

Castro, Ian P.

1990-01-01

Describes a microcomputer-based software package developed at the University of Surrey for teaching digital signal processing to undergraduate science and engineering students. Menu-driven software capabilities are explained, including demonstration of qualitative concepts and experimentation with quantitative data, and examples are given of…

Some Aspects of Process Computers Configuration Control in Nuclear Power Plant Krsko - Process Computer Signal Configuration Database (PCSCDB)

International Nuclear Information System (INIS)

Mandic, D.; Kocnar, R.; Sucic, B.

2002-01-01

During the operation of NEK and other nuclear power plants it has been recognized that certain issues related to the usage of digital equipment and associated software in NPP technological process protection, control and monitoring, is not adequately addressed in the existing programs and procedures. The term and the process of Process Computers Configuration Control joins three 10CFR50 Appendix B quality requirements of Process Computers application in NPP: Design Control, Document Control and Identification and Control of Materials, Parts and Components. This paper describes Process Computer Signal Configuration Database (PCSCDB), that was developed and implemented in order to resolve some aspects of Process Computer Configuration Control related to the signals or database points that exist in the life cycle of different Process Computer Systems (PCS) in Nuclear Power Plant Krsko. PCSCDB is controlled, master database, related to the definition and description of the configurable database points associated with all Process Computer Systems in NEK. PCSCDB holds attributes related to the configuration of addressable and configurable real time database points and attributes related to the signal life cycle references and history data such as: Input/Output signals, Manually Input database points, Program constants, Setpoints, Calculated (by application program or SCADA calculation tools) database points, Control Flags (example: enable / disable certain program feature) Signal acquisition design references to the DCM (Document Control Module Application software for document control within Management Information System - MIS) and MECL (Master Equipment and Component List MIS Application software for identification and configuration control of plant equipment and components) Usage of particular database point in particular application software packages, and in the man-machine interface features (display mimics, printout reports, ...) Signals history (EEAR Engineering

Small Displacement Detection of Biological Signals Using the Cyclic Frequency Method

Directory of Open Access Journals (Sweden)

Dan Zhang

2015-01-01

Full Text Available A new signal processing method called the Cyclic Frequency method is proposed for small displacement detection of vital signals such as heart rate and respiration using the CW radar method. We have presented experimental results of small displacement detection to confirm the validity of the method. The displacement amplitude 2.5 mm can be detected with a propagation frequency of 24.15 GHz. We may increase the propagation frequency for smaller displacement amplitude or target velocity.

Integrated Circuits for Analog Signal Processing

CERN Document Server

2013-01-01

  This book presents theory, design methods and novel applications for integrated circuits for analog signal processing.  The discussion covers a wide variety of active devices, active elements and amplifiers, working in voltage mode, current mode and mixed mode.  This includes voltage operational amplifiers, current operational amplifiers, operational transconductance amplifiers, operational transresistance amplifiers, current conveyors, current differencing transconductance amplifiers, etc.  Design methods and challenges posed by nanometer technology are discussed and applications described, including signal amplification, filtering, data acquisition systems such as neural recording, sensor conditioning such as biomedical implants, actuator conditioning, noise generators, oscillators, mixers, etc.   Presents analysis and synthesis methods to generate all circuit topologies from which the designer can select the best one for the desired application; Includes design guidelines for active devices/elements...

CERN Technical Training 2003: Learning for the LHC! DISP-2003 - Digital Signal Processing

CERN Multimedia

2003-01-01

DISP-2003 is a two-term course given by CERN and University of Lausanne (UNIL) experts within the framework of the Technical Training Programme. The course will review the current techniques dealing with Digital Signal Processing, and it is intended for an audience who work or will work on digital signal processing aspects, and who need an introductory or refresher/update course. The course will be in English, with question and answers also in French. Spring 2 Term: DISP-2003: Advanced Digital Signal Processing 30 April 2003 - 21 May 2003, 4 lectures, Wednesdays afternoon. Attendance cost: 40.- CHF, registration required. Lecturers: Léonard Studer, UNIL; Laurent Deniau, AT-MTM; Elena Wildner, AT-MAS. Programme: Intelligent signal processing (ISP). Non-linear time series analysis. Image processing. Wavelets. Basic concepts and definitions have been introduced during the previous Spring 1 Term: DISP-2003: Introduction to Digital Signal Processing. DISP-2003 is open to all people interested, but registrat...

Stochastic processes, multiscale modeling, and numerical methods for computational cellular biology

CERN Document Server

2017-01-01

This book focuses on the modeling and mathematical analysis of stochastic dynamical systems along with their simulations. The collected chapters will review fundamental and current topics and approaches to dynamical systems in cellular biology. This text aims to develop improved mathematical and computational methods with which to study biological processes. At the scale of a single cell, stochasticity becomes important due to low copy numbers of biological molecules, such as mRNA and proteins that take part in biochemical reactions driving cellular processes. When trying to describe such biological processes, the traditional deterministic models are often inadequate, precisely because of these low copy numbers. This book presents stochastic models, which are necessary to account for small particle numbers and extrinsic noise sources. The complexity of these models depend upon whether the biochemical reactions are diffusion-limited or reaction-limited. In the former case, one needs to adopt the framework of s...

Signal Processing Device (SPD) for networked radiation monitoring system

International Nuclear Information System (INIS)

Dharmapurikar, A.; Bhattacharya, S.; Mukhopadhyay, P.K.; Sawhney, A.; Patil, R.K.

2010-01-01

A networked radiation and parameter monitoring system with three tier architecture is being developed. Signal Processing Device (SPD) is a second level sub-system node in the network. SPD is an embedded system which has multiple input channels and output communication interfaces. It acquires and processes data from first level parametric sensor devices, and sends to third level devices in response to request commands received from host. It also performs scheduled diagnostic operations and passes on the information to host. It supports inputs in the form of differential digital signals and analog voltage signals. SPD communicates with higher level devices over RS232/RS422/USB channels. The system has been designed with main requirements of minimal power consumption and harsh environment in radioactive plants. This paper discusses the hardware and software design details of SPD. (author)

Generation and coherent detection of QPSK signal using a novel method of digital signal processing

Science.gov (United States)

Zhao, Yuan; Hu, Bingliang; He, Zhen-An; Xie, Wenjia; Gao, Xiaohui

2018-02-01

We demonstrate an optical quadrature phase-shift keying (QPSK) signal transmitter and an optical receiver for demodulating optical QPSK signal with homodyne detection and digital signal processing (DSP). DSP on the homodyne detection scheme is employed without locking the phase of the local oscillator (LO). In this paper, we present an extracting one-dimensional array of down-sampling method for reducing unwanted samples of constellation diagram measurement. Such a novel scheme embodies the following major advantages over the other conventional optical QPSK signal detection methods. First, this homodyne detection scheme does not need strict requirement on LO in comparison with linear optical sampling, such as having a flat spectral density and phase over the spectral support of the source under test. Second, the LabVIEW software is directly used for recovering the QPSK signal constellation without employing complex DSP circuit. Third, this scheme is applicable to multilevel modulation formats such as M-ary PSK and quadrature amplitude modulation (QAM) or higher speed signals by making minor changes.

Digital signal processing reveals circadian baseline oscillation in majority of mammalian genes.

Directory of Open Access Journals (Sweden)

Andrey A Ptitsyn

2007-06-01

Full Text Available In mammals, circadian periodicity has been described for gene expression in the hypothalamus and multiple peripheral tissues. It is accepted that 10%-15% of all genes oscillate in a daily rhythm, regulated by an intrinsic molecular clock. Statistical analyses of periodicity are limited by the small size of datasets and high levels of stochastic noise. Here, we propose a new approach applying digital signal processing algorithms separately to each group of genes oscillating in the same phase. Combined with the statistical tests for periodicity, this method identifies circadian baseline oscillation in almost 100% of all expressed genes. Consequently, circadian oscillation in gene expression should be evaluated in any study related to biological pathways. Changes in gene expression caused by mutations or regulation of environmental factors (such as photic stimuli or feeding should be considered in the context of changes in the amplitude and phase of genetic oscillations.

Nuclear pulse signal processing technique based on blind deconvolution method

International Nuclear Information System (INIS)

Hong Pengfei; Yang Lei; Fu Tingyan; Qi Zhong; Li Dongcang; Ren Zhongguo

2012-01-01

In this paper, we present a method for measurement and analysis of nuclear pulse signal, with which pile-up signal is removed, the signal baseline is restored, and the original signal is obtained. The data acquisition system includes FPGA, ADC and USB. The FPGA controls the high-speed ADC to sample the signal of nuclear radiation, and the USB makes the ADC work on the Slave FIFO mode to implement high-speed transmission status. Using the LabVIEW, it accomplishes online data processing of the blind deconvolution algorithm and data display. The simulation and experimental results demonstrate advantages of the method. (authors)

Test of Science Process Skills of Biology Students towards Developing of Learning Exercises

Directory of Open Access Journals (Sweden)

Judith S. Rabacal

2016-11-01

Full Text Available This is a descriptive study aimed to determine the academic achievement on science process skills of the BS Biology Students of Northern Negros State College of Science and Technology, Philippines with the end view of developing learning exercises which will enhance their academic achievement on basic and integrated science process skills. The data in this study were obtained using a validated questionnaire. Mean was the statistical tool used to determine the academic achievement on the above mentioned science process skills; t-test for independent means was used to determine significant difference on the academic achievement of science process skills of BS Biology students while Pearson Product Moment of Correlation Coefficient was used to determine the significant relationship between basic and integrated science process skills of the BS Biology students. A 0.05 level of significance was used to determine whether the hypothesis set in the study will be rejected or accepted. Findings revealed that the academic achievement on basic and integrated science process skills of the BS Biology students was average. Findings revealed that there are no significant differences on the academic performance of the BS Biology students when grouped according to year level and gender. Findings also revealed that there is a significant difference on the academic achievement between basic and integrated science process skills of the BS Biology students. Findings revealed that there is a significant relationship between academic achievement on the basic and integrated science process skills of the BS Biology students.

Nuclear Receptor Signaling Atlas: Opening Access to the Biology of Nuclear Receptor Signaling Pathways.

Science.gov (United States)

Becnel, Lauren B; Darlington, Yolanda F; Ochsner, Scott A; Easton-Marks, Jeremy R; Watkins, Christopher M; McOwiti, Apollo; Kankanamge, Wasula H; Wise, Michael W; DeHart, Michael; Margolis, Ronald N; McKenna, Neil J

2015-01-01

Signaling pathways involving nuclear receptors (NRs), their ligands and coregulators, regulate tissue-specific transcriptomes in diverse processes, including development, metabolism, reproduction, the immune response and neuronal function, as well as in their associated pathologies. The Nuclear Receptor Signaling Atlas (NURSA) is a Consortium focused around a Hub website (www.nursa.org) that annotates and integrates diverse 'omics datasets originating from the published literature and NURSA-funded Data Source Projects (NDSPs). These datasets are then exposed to the scientific community on an Open Access basis through user-friendly data browsing and search interfaces. Here, we describe the redesign of the Hub, version 3.0, to deploy "Web 2.0" technologies and add richer, more diverse content. The Molecule Pages, which aggregate information relevant to NR signaling pathways from myriad external databases, have been enhanced to include resources for basic scientists, such as post-translational modification sites and targeting miRNAs, and for clinicians, such as clinical trials. A portal to NURSA's Open Access, PubMed-indexed journal Nuclear Receptor Signaling has been added to facilitate manuscript submissions. Datasets and information on reagents generated by NDSPs are available, as is information concerning periodic new NDSP funding solicitations. Finally, the new website integrates the Transcriptomine analysis tool, which allows for mining of millions of richly annotated public transcriptomic data points in the field, providing an environment for dataset re-use and citation, bench data validation and hypothesis generation. We anticipate that this new release of the NURSA database will have tangible, long term benefits for both basic and clinical research in this field.

Nuclear Receptor Signaling Atlas: Opening Access to the Biology of Nuclear Receptor Signaling Pathways.

Directory of Open Access Journals (Sweden)

Lauren B Becnel

Full Text Available Signaling pathways involving nuclear receptors (NRs, their ligands and coregulators, regulate tissue-specific transcriptomes in diverse processes, including development, metabolism, reproduction, the immune response and neuronal function, as well as in their associated pathologies. The Nuclear Receptor Signaling Atlas (NURSA is a Consortium focused around a Hub website (www.nursa.org that annotates and integrates diverse 'omics datasets originating from the published literature and NURSA-funded Data Source Projects (NDSPs. These datasets are then exposed to the scientific community on an Open Access basis through user-friendly data browsing and search interfaces. Here, we describe the redesign of the Hub, version 3.0, to deploy "Web 2.0" technologies and add richer, more diverse content. The Molecule Pages, which aggregate information relevant to NR signaling pathways from myriad external databases, have been enhanced to include resources for basic scientists, such as post-translational modification sites and targeting miRNAs, and for clinicians, such as clinical trials. A portal to NURSA's Open Access, PubMed-indexed journal Nuclear Receptor Signaling has been added to facilitate manuscript submissions. Datasets and information on reagents generated by NDSPs are available, as is information concerning periodic new NDSP funding solicitations. Finally, the new website integrates the Transcriptomine analysis tool, which allows for mining of millions of richly annotated public transcriptomic data points in the field, providing an environment for dataset re-use and citation, bench data validation and hypothesis generation. We anticipate that this new release of the NURSA database will have tangible, long term benefits for both basic and clinical research in this field.

Quantitative phosphoproteomics to characterize signaling networks

DEFF Research Database (Denmark)

Rigbolt, Kristoffer T G; Blagoev, Blagoy

2012-01-01

for analyzing protein phosphorylation at a system-wide scale and has become the intuitive strategy for comprehensive characterization of signaling networks. Contemporary phosphoproteomics use highly optimized procedures for sample preparation, mass spectrometry and data analysis algorithms to identify......Reversible protein phosphorylation is involved in the regulation of most, if not all, major cellular processes via dynamic signal transduction pathways. During the last decade quantitative phosphoproteomics have evolved from a highly specialized area to a powerful and versatile platform...... and quantify thousands of phosphorylations, thus providing extensive overviews of the cellular signaling networks. As a result of these developments quantitative phosphoproteomics have been applied to study processes as diverse as immunology, stem cell biology and DNA damage. Here we review the developments...

Static Mapping of Functional Programs: An Example in Signal Processing

Directory of Open Access Journals (Sweden)

Jack B. Dennis

1996-01-01

Full Text Available Complex signal-processing problems are naturally described by compositions of program modules that process streams of data. In this article we discuss how such compositions may be analyzed and mapped onto multiprocessor computers to effectively exploit the massive parallelism of these applications. The methods are illustrated with an example of signal processing for an optical surveillance problem. Program transformation and analysis are used to construct a program description tree that represents the given computation as an acyclic interconnection of stream-processing modules. Each module may be mapped to a set of threads run on a group of processing elements of a target multiprocessor. Performance is considered for two forms of multiprocessor architecture, one based on conventional DSP technology and the other on a multithreaded-processing element design.

Active Interaction Mapping as a tool to elucidate hierarchical functions of biological processes.

Science.gov (United States)

Farré, Jean-Claude; Kramer, Michael; Ideker, Trey; Subramani, Suresh

2017-07-03

Increasingly, various 'omics data are contributing significantly to our understanding of novel biological processes, but it has not been possible to iteratively elucidate hierarchical functions in complex phenomena. We describe a general systems biology approach called Active Interaction Mapping (AI-MAP), which elucidates the hierarchy of functions for any biological process. Existing and new 'omics data sets can be iteratively added to create and improve hierarchical models which enhance our understanding of particular biological processes. The best datatypes to further improve an AI-MAP model are predicted computationally. We applied this approach to our understanding of general and selective autophagy, which are conserved in most eukaryotes, setting the stage for the broader application to other cellular processes of interest. In the particular application to autophagy-related processes, we uncovered and validated new autophagy and autophagy-related processes, expanded known autophagy processes with new components, integrated known non-autophagic processes with autophagy and predict other unexplored connections.

A Versatile Multichannel Digital Signal Processing Module for Microcalorimeter Arrays

Science.gov (United States)

Tan, H.; Collins, J. W.; Walby, M.; Hennig, W.; Warburton, W. K.; Grudberg, P.

2012-06-01

Different techniques have been developed for reading out microcalorimeter sensor arrays: individual outputs for small arrays, and time-division or frequency-division or code-division multiplexing for large arrays. Typically, raw waveform data are first read out from the arrays using one of these techniques and then stored on computer hard drives for offline optimum filtering, leading not only to requirements for large storage space but also limitations on achievable count rate. Thus, a read-out module that is capable of processing microcalorimeter signals in real time will be highly desirable. We have developed multichannel digital signal processing electronics that are capable of on-board, real time processing of microcalorimeter sensor signals from multiplexed or individual pixel arrays. It is a 3U PXI module consisting of a standardized core processor board and a set of daughter boards. Each daughter board is designed to interface a specific type of microcalorimeter array to the core processor. The combination of the standardized core plus this set of easily designed and modified daughter boards results in a versatile data acquisition module that not only can easily expand to future detector systems, but is also low cost. In this paper, we first present the core processor/daughter board architecture, and then report the performance of an 8-channel daughter board, which digitizes individual pixel outputs at 1 MSPS with 16-bit precision. We will also introduce a time-division multiplexing type daughter board, which takes in time-division multiplexing signals through fiber-optic cables and then processes the digital signals to generate energy spectra in real time.

A Study on Signal Group Processing of AUTOSAR COM Module

International Nuclear Information System (INIS)

Lee, Jeong-Hwan; Hwang, Hyun Yong; Han, Tae Man; Ahn, Yong Hak

2013-01-01

In vehicle, there are many ECU(Electronic Control Unit)s, and ECUs are connected to networks such as CAN, LIN, FlexRay, and so on. AUTOSAR COM(Communication) which is a software platform of AUTOSAR(AUTomotive Open System ARchitecture) in the international industry standards of automotive electronic software processes signals and signal groups for data communications between ECUs. Real-time and reliability are very important for data communications in the vehicle. Therefore, in this paper, we analyze functions of signals and signal groups used in COM, and represent that functions of signal group are more efficient than signals in real-time data synchronization and network resource usage between the sender and receiver.

A Study on Signal Group Processing of AUTOSAR COM Module

Science.gov (United States)

Lee, Jeong-Hwan; Hwang, Hyun Yong; Han, Tae Man; Ahn, Yong Hak

2013-06-01

In vehicle, there are many ECU(Electronic Control Unit)s, and ECUs are connected to networks such as CAN, LIN, FlexRay, and so on. AUTOSAR COM(Communication) which is a software platform of AUTOSAR(AUTomotive Open System ARchitecture) in the international industry standards of automotive electronic software processes signals and signal groups for data communications between ECUs. Real-time and reliability are very important for data communications in the vehicle. Therefore, in this paper, we analyze functions of signals and signal groups used in COM, and represent that functions of signal group are more efficient than signals in real-time data synchronization and network resource usage between the sender and receiver.

Nuclear pulse signal processing techniques based on blind deconvolution method

International Nuclear Information System (INIS)

Hong Pengfei; Yang Lei; Qi Zhong; Meng Xiangting; Fu Yanyan; Li Dongcang

2012-01-01

This article presents a method of measurement and analysis of nuclear pulse signal, the FPGA to control high-speed ADC measurement of nuclear radiation signals and control the high-speed transmission status of the USB to make it work on the Slave FIFO mode, using the LabVIEW online data processing and display, using the blind deconvolution method to remove the accumulation of signal acquisition, and to restore the nuclear pulse signal with a transmission speed, real-time measurements show that the advantages. (authors)

The mathematical theory of signal processing and compression-designs

Science.gov (United States)

Feria, Erlan H.

2006-05-01

The mathematical theory of signal processing, named processor coding, will be shown to inherently arise as the computational time dual of Shannon's mathematical theory of communication which is also known as source coding. Source coding is concerned with signal source memory space compression while processor coding deals with signal processor computational time compression. Their combination is named compression-designs and referred as Conde in short. A compelling and pedagogically appealing diagram will be discussed highlighting Conde's remarkable successful application to real-world knowledge-aided (KA) airborne moving target indicator (AMTI) radar.

New challenges in signal processing in astrophysics: the SKA case

International Nuclear Information System (INIS)

Faulkner, Andrew; Zarb-Adami, Kristian; De Vaate, Jan Geralt Bij

2015-01-01

Signal processing and communications are driving the latest generation of radio telescopes with major developments taking place for use on the Square Kilometre Array, SKA, the next generation low frequency radio telescope. The data rates and processing performance that can be achieved with currently available components means that concepts from the earlier days of radio astronomy, phased arrays, can be used at higher frequencies, larger bandwidths and higher numbers of beams. Indeed it has been argued that the use of dishes as a mechanical beamformer only gained strong acceptance to mitigate the processing load from phased array technology. The balance is changing and benefits in both performance and cost can be realised. In this paper we will mostly consider the signal processing implementation and control for very large phased arrays consisting of hundreds of thousands of antennas or even millions of antennas. They can use current technology for the initial deployments. These systems are very large extending to hundreds of racks with thousands of signal processing modules that link through high-speed, but commercially available data networking devices. There are major challenges to accurately calibrate the arrays, mitigate power consumption and make the system maintainable

Modeling fMRI signals can provide insights into neural processing in the cerebral cortex.

Science.gov (United States)

Vanni, Simo; Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo

2015-08-01

Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals. Copyright © 2015 the American Physiological Society.

Probability, random variables, and random processes theory and signal processing applications

CERN Document Server

Shynk, John J

2012-01-01

Probability, Random Variables, and Random Processes is a comprehensive textbook on probability theory for engineers that provides a more rigorous mathematical framework than is usually encountered in undergraduate courses. It is intended for first-year graduate students who have some familiarity with probability and random variables, though not necessarily of random processes and systems that operate on random signals. It is also appropriate for advanced undergraduate students who have a strong mathematical background. The book has the following features: Several app

Signal processing for non-destructive testing of railway tracks

Science.gov (United States)

Heckel, Thomas; Casperson, Ralf; Rühe, Sven; Mook, Gerhard

2018-04-01

Increased speed, heavier loads, altered material and modern drive systems result in an increasing number of rail flaws. The appearance of these flaws also changes continually due to the rapid change in damage mechanisms of modern rolling stock. Hence, interpretation has become difficult when evaluating non-destructive rail testing results. Due to the changed interplay between detection methods and flaws, the recorded signals may result in unclassified types of rail flaws. Methods for automatic rail inspection (according to defect detection and classification) undergo continual development. Signal processing is a key technology to master the challenge of classification and maintain resolution and detection quality, independent of operation speed. The basic ideas of signal processing, based on the Glassy-Rail-Diagram for classification purposes, are presented herein. Examples for the detection of damages caused by rolling contact fatigue also are given, and synergetic effects of combined evaluation of diverse inspection methods are shown.

Myoelectric signal processing for control of powered limb prostheses.

Science.gov (United States)

Parker, P; Englehart, K; Hudgins, B

2006-12-01

Progress in myoelectric control technology has over the years been incremental, due in part to the alternating focus of the R&D between control methodology and device hardware. The technology has over the past 50 years or so moved from single muscle control of a single prosthesis function to muscle group activity control of multifunction prostheses. Central to these changes have been developments in the means of extracting information from the myoelectric signal. This paper gives an overview of the myoelectric signal processing challenge, a brief look at the challenge from an historical perspective, the state-of-the-art in myoelectric signal processing for prosthesis control, and an indication of where this field is heading. The paper demonstrates that considerable progress has been made in providing clients with useful and reliable myoelectric communication channels, and that exciting work and developments are on the horizon.

iBiology: communicating the process of science.

Science.gov (United States)

Goodwin, Sarah S

2014-08-01

The Internet hosts an abundance of science video resources aimed at communicating scientific knowledge, including webinars, massive open online courses, and TED talks. Although these videos are efficient at disseminating information for diverse types of users, they often do not demonstrate the process of doing science, the excitement of scientific discovery, or how new scientific knowledge is developed. iBiology (www.ibiology.org), a project that creates open-access science videos about biology research and science-related topics, seeks to fill this need by producing videos by science leaders that make their ideas, stories, and experiences available to anyone with an Internet connection. © 2014 Goodwin. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Regulation of G protein-coupled receptor signalling: focus on the cardiovascular system and regulator of G protein signalling proteins

NARCIS (Netherlands)

Hendriks-Balk, Mariëlle C.; Peters, Stephan L. M.; Michel, Martin C.; Alewijnse, Astrid E.

2008-01-01

G protein-coupled receptors (GPCRs) are involved in many biological processes. Therefore, GPCR function is tightly controlled both at receptor level and at the level of signalling components. Well-known mechanisms by which GPCR function can be regulated comprise desensitization/resensitization

Improvement of the characterization of ultrasonic data by means of digital signal processing

International Nuclear Information System (INIS)

Bieth, M.; Romy, D.; Weigel, D.

1985-01-01

The digital signal processing method for averaging using minima developed by Framatome allows to improve signal-to-noise ratio up to 7 dB during ultrasonic testing of cast stainless steel structures (primary pipes of PWR power plants). Application of digital signal processing to industrial testing conditions requires the availability of a fast analog-digital converter capable of real time processings which has been developed by CGR [fr

Heat transfer and fluid flow in biological processes advances and applications

CERN Document Server

Becker, Sid

2015-01-01

Heat Transfer and Fluid Flow in Biological Processes covers emerging areas in fluid flow and heat transfer relevant to biosystems and medical technology. This book uses an interdisciplinary approach to provide a comprehensive prospective on biofluid mechanics and heat transfer advances and includes reviews of the most recent methods in modeling of flows in biological media, such as CFD. Written by internationally recognized researchers in the field, each chapter provides a strong introductory section that is useful to both readers currently in the field and readers interested in learning more about these areas. Heat Transfer and Fluid Flow in Biological Processes is an indispensable reference for professors, graduate students, professionals, and clinical researchers in the fields of biology, biomedical engineering, chemistry and medicine working on applications of fluid flow, heat transfer, and transport phenomena in biomedical technology. Provides a wide range of biological and clinical applications of fluid...

Crosstalk between Wnt Signaling and RNA Processing in Colorectal Cancer

Directory of Open Access Journals (Sweden)

Michael Bordonaro

2013-01-01

Full Text Available RNA processing involves a variety of processes affecting gene expression, including the removal of introns through RNA splicing, as well as 3' end processing (cleavage and polyadenylation. Alternative RNA processing is fundamentally important for gene regulation, and aberrant processing is associated with the initiation and progression of cancer. Deregulated Wnt signaling, which is the initiating event in the development of most cases of human colorectal cancer (CRC, has been linked to modified RNA processing, which may contribute to Wnt-mediated colonic carcinogenesis. Crosstalk between Wnt signaling and alternative RNA splicing with relevance to CRC includes effects on the expression of Rac1b, an alternatively spliced gene associated with tumorigenesis, which exhibits alternative RNA splicing that is influenced by Wnt activity. In addition, Tcf4, a crucial component of Wnt signaling, also exhibits alternative splicing, which is likely involved in colonic tumorigenesis. Modulation of 3' end formation, including of the Wnt target gene COX-2, also can influence the neoplastic process, with implications for CRC. While many human genes are dependent on introns and splicing for normal levels of gene expression, naturally intronless genes exist with a unique metabolism that allows for intron-independent gene expression. Effects of Wnt activity on the RNA metabolism of the intronless Wnt-target gene c-jun is a likely contributor to cancer development. Further, butyrate, a breakdown product of dietary fiber and a histone deacetylase inhibitor, upregulates Wnt activity in CRC cells, and also modulates RNA processing; therefore, the interplay between Wnt activity, the modulation of this activity by butyrate, and differential RNA metabolism in colonic cells can significantly influence tumorigenesis. Determining the role played by altered RNA processing in Wnt-mediated neoplasia may lead to novel interventions aimed at restoring normal RNA metabolism for

Crosstalk between Wnt Signaling and RNA Processing in Colorectal Cancer.

Science.gov (United States)

Bordonaro, Michael

2013-01-01

RNA processing involves a variety of processes affecting gene expression, including the removal of introns through RNA splicing, as well as 3' end processing (cleavage and polyadenylation). Alternative RNA processing is fundamentally important for gene regulation, and aberrant processing is associated with the initiation and progression of cancer. Deregulated Wnt signaling, which is the initiating event in the development of most cases of human colorectal cancer (CRC), has been linked to modified RNA processing, which may contribute to Wnt-mediated colonic carcinogenesis. Crosstalk between Wnt signaling and alternative RNA splicing with relevance to CRC includes effects on the expression of Rac1b, an alternatively spliced gene associated with tumorigenesis, which exhibits alternative RNA splicing that is influenced by Wnt activity. In addition, Tcf4, a crucial component of Wnt signaling, also exhibits alternative splicing, which is likely involved in colonic tumorigenesis. Modulation of 3' end formation, including of the Wnt target gene COX-2, also can influence the neoplastic process, with implications for CRC. While many human genes are dependent on introns and splicing for normal levels of gene expression, naturally intronless genes exist with a unique metabolism that allows for intron-independent gene expression. Effects of Wnt activity on the RNA metabolism of the intronless Wnt-target gene c-jun is a likely contributor to cancer development. Further, butyrate, a breakdown product of dietary fiber and a histone deacetylase inhibitor, upregulates Wnt activity in CRC cells, and also modulates RNA processing; therefore, the interplay between Wnt activity, the modulation of this activity by butyrate, and differential RNA metabolism in colonic cells can significantly influence tumorigenesis. Determining the role played by altered RNA processing in Wnt-mediated neoplasia may lead to novel interventions aimed at restoring normal RNA metabolism for therapeutic benefit

Diversity of Neuropeptide Cell-Cell Signaling Molecules Generated by Proteolytic Processing Revealed by Neuropeptidomics Mass Spectrometry

Science.gov (United States)

Hook, Vivian; Lietz, Christopher B.; Podvin, Sonia; Cajka, Tomas; Fiehn, Oliver

2018-04-01

Neuropeptides are short peptides in the range of 3-40 residues that are secreted for cell-cell communication in neuroendocrine systems. In the nervous system, neuropeptides comprise the largest group of neurotransmitters. In the endocrine system, neuropeptides function as peptide hormones to coordinate intercellular signaling among target physiological systems. The diversity of neuropeptide functions is defined by their distinct primary sequences, peptide lengths, proteolytic processing of pro-neuropeptide precursors, and covalent modifications. Global, untargeted neuropeptidomics mass spectrometry is advantageous for defining the structural features of the thousands to tens of thousands of neuropeptides present in biological systems. Defining neuropeptide structures is the basis for defining the proteolytic processing pathways that convert pro-neuropeptides into active peptides. Neuropeptidomics has revealed that processing of pro-neuropeptides occurs at paired basic residues sites, and at non-basic residue sites. Processing results in neuropeptides with known functions and generates novel peptides representing intervening peptide domains flanked by dibasic residue processing sites, identified by neuropeptidomics. While very short peptide products of 2-4 residues are predicted from pro-neuropeptide dibasic processing sites, such peptides have not been readily identified; therefore, it will be logical to utilize metabolomics to identify very short peptides with neuropeptidomics in future studies. Proteolytic processing is accompanied by covalent post-translational modifications (PTMs) of neuropeptides comprising C-terminal amidation, N-terminal pyroglutamate, disulfide bonds, phosphorylation, sulfation, acetylation, glycosylation, and others. Neuropeptidomics can define PTM features of neuropeptides. In summary, neuropeptidomics for untargeted, global analyses of neuropeptides is essential for elucidation of proteases that generate diverse neuropeptides for cell

PKD signaling and pancreatitis

Science.gov (United States)

Yuan, Jingzhen; Pandol, Stephen J.

2016-01-01

Background Acute pancreatitis is a serious medical disorder with no current therapies directed to the molecular pathogenesis of the disorder. Inflammation, inappropriate intracellular activation of digestive enzymes, and parenchymal acinar cell death by necrosis are the critical pathophysiologic processes of acute pancreatitis. Thus, it is necessary to elucidate the key molecular signals that mediate these pathobiologic processes and develop new therapeutic strategies to attenuate the appropriate signaling pathways in order to improve outcomes for this disease. A novel serine/threonine protein kinase D (PKD) family has emerged as key participants in signal transduction, and this family is increasingly being implicated in the regulation of multiple cellular functions and diseases. Methods This review summarizes recent findings of our group and others regarding the signaling pathway and the biological roles of the PKD family in pancreatic acinar cells. In particular, we highlight our studies of the functions of PKD in several key pathobiologic processes associated with acute pancreatitis in experimental models. Results Our findings reveal that PKD signaling is required for NF-κB activation/inflammation, intracellular zymogen activation, and acinar cell necrosis in rodent experimental pancreatitis. Novel small-molecule PKD inhibitors attenuate the severity of pancreatitis in both in vitro and in vivo experimental models. Further, this review emphasizes our latest advances in the therapeutic application of PKD inhibitors to experimental pancreatitis after the initiation of pancreatitis. Conclusions These novel findings suggest that PKD signaling is a necessary modulator in key initiating pathobiologic processes of pancreatitis, and that it constitutes a novel therapeutic target for treatments of this disorder. PMID:26879861

Diversity of Neuropeptide Cell-Cell Signaling Molecules Generated by Proteolytic Processing Revealed by Neuropeptidomics Mass Spectrometry

Science.gov (United States)

Hook, Vivian; Lietz, Christopher B.; Podvin, Sonia; Cajka, Tomas; Fiehn, Oliver

2018-05-01

Neuropeptides are short peptides in the range of 3-40 residues that are secreted for cell-cell communication in neuroendocrine systems. In the nervous system, neuropeptides comprise the largest group of neurotransmitters. In the endocrine system, neuropeptides function as peptide hormones to coordinate intercellular signaling among target physiological systems. The diversity of neuropeptide functions is defined by their distinct primary sequences, peptide lengths, proteolytic processing of pro-neuropeptide precursors, and covalent modifications. Global, untargeted neuropeptidomics mass spectrometry is advantageous for defining the structural features of the thousands to tens of thousands of neuropeptides present in biological systems. Defining neuropeptide structures is the basis for defining the proteolytic processing pathways that convert pro-neuropeptides into active peptides. Neuropeptidomics has revealed that processing of pro-neuropeptides occurs at paired basic residues sites, and at non-basic residue sites. Processing results in neuropeptides with known functions and generates novel peptides representing intervening peptide domains flanked by dibasic residue processing sites, identified by neuropeptidomics. While very short peptide products of 2-4 residues are predicted from pro-neuropeptide dibasic processing sites, such peptides have not been readily identified; therefore, it will be logical to utilize metabolomics to identify very short peptides with neuropeptidomics in future studies. Proteolytic processing is accompanied by covalent post-translational modifications (PTMs) of neuropeptides comprising C-terminal amidation, N-terminal pyroglutamate, disulfide bonds, phosphorylation, sulfation, acetylation, glycosylation, and others. Neuropeptidomics can define PTM features of neuropeptides. In summary, neuropeptidomics for untargeted, global analyses of neuropeptides is essential for elucidation of proteases that generate diverse neuropeptides for cell

Phenol wastewater remediation: advanced oxidation processes coupled to a biological treatment.

Science.gov (United States)

Rubalcaba, A; Suárez-Ojeda, M E; Stüber, F; Fortuny, A; Bengoa, C; Metcalfe, I; Font, J; Carrera, J; Fabregat, A

2007-01-01

Nowadays, there are increasingly stringent regulations requiring more and more treatment of industrial effluents to generate product waters which could be easily reused or disposed of to the environment without any harmful effects. Therefore, different advanced oxidation processes were investigated as suitable precursors for the biological treatment of industrial effluents containing phenol. Wet air oxidation and Fenton process were tested batch wise, while catalytic wet air oxidation and H2O2-promoted catalytic wet air oxidation processes were studied in a trickle bed reactor, the last two using over activated carbon as catalyst. Effluent characterisation was made by means of substrate conversion (using high liquid performance chromatography), chemical oxygen demand and total organic carbon. Biodegradation parameters (i.e. maximum oxygen uptake rate and oxygen consumption) were obtained from respirometric tests using activated sludge from an urban biological wastewater treatment plant (WWTP). The main goal was to find the proper conditions in terms of biodegradability enhancement, so that these phenolic effluents could be successfully treated in an urban biological WWTP. Results show promising research ways for the development of efficient coupled processes for the treatment of wastewater containing toxic or biologically non-degradable compounds.

4th International Conference on Communications, Signal Processing, and Systems

CERN Document Server

Mu, Jiasong; Wang, Wei; Zhang, Baoju

2016-01-01

This book brings together papers presented at the 4th International Conference on Communications, Signal Processing, and Systems, which provides a venue to disseminate the latest developments and to discuss the interactions and links between these multidisciplinary fields. Spanning topics ranging from Communications, Signal Processing and Systems, this book is aimed at undergraduate and graduate students in Electrical Engineering, Computer Science and Mathematics, researchers and engineers from academia and industry as well as government employees (such as NSF, DOD, DOE, etc).

Algorithm-Architecture Matching for Signal and Image Processing

CERN Document Server

Gogniat, Guy; Morawiec, Adam; Erdogan, Ahmet

2011-01-01

Advances in signal and image processing together with increasing computing power are bringing mobile technology closer to applications in a variety of domains like automotive, health, telecommunication, multimedia, entertainment and many others. The development of these leading applications, involving a large diversity of algorithms (e.g. signal, image, video, 3D, communication, cryptography) is classically divided into three consecutive steps: a theoretical study of the algorithms, a study of the target architecture, and finally the implementation. Such a linear design flow is reaching its li

Optical signal acquisition and processing in future accelerator diagnostics

International Nuclear Information System (INIS)

Jackson, G.P.; Elliott, A.

1992-01-01

Beam detectors such as striplines and wall current monitors rely on matched electrical networks to transmit and process beam information. Frequency bandwidth, noise immunity, reflections, and signal to noise ratio are considerations that require compromises limiting the quality of the measurement. Recent advances in fiber optics related technologies have made it possible to acquire and process beam signals in the optical domain. This paper describes recent developments in the application of these technologies to accelerator beam diagnostics. The design and construction of an optical notch filter used for a stochastic cooling system is used as an example. Conceptual ideas for future beam detectors are also presented

Design and implementation of a hybrid circuit system for micro sensor signal processing

International Nuclear Information System (INIS)

Wang Zhuping; Chen Jing; Liu Ruqing

2011-01-01

This paper covers a micro sensor analog signal processing circuit system (MASPS) chip with low power and a digital signal processing circuit board implementation including hardware connection and software design. Attention has been paid to incorporate the MASPS chip into the digital circuit board. The ultimate aim is to form a hybrid circuit used for mixed-signal processing, which can be applied to a micro sensor flow monitoring system. (semiconductor integrated circuits)

Nicotine, alcohol and cocaine coupling to reward processes via endogenous morphine signaling: the dopamine-morphine hypothesis.

Science.gov (United States)

Stefano, George B; Bianchi, Enrica; Guarna, Massimo; Fricchione, Gregory L; Zhu, Wei; Cadet, Patrick; Mantione, Kirk J; Casares, Federico M; Kream, Richard M; Esch, Tobias

2007-06-01

Pleasure is described as a state or feeling of happiness and satisfaction resulting from an experience that one enjoys. We examine the neurobiological factors underlying reward processes and pleasure phenomena. With regard to possible negative effects of pleasure, we focus on addiction and motivational toxicity. Pleasure can serve cognition, productivity and health, but simultaneously promotes addiction and other negative behaviors. It is a complex neurobiological phenomenon, relying on reward circuitry or limbic activity. These processes involve dopaminergic signaling. Moreover, nicotine, cocaine and alcohol appear to exert their pleasure providing action via endogenous morphinergic mechanisms. Natural rewarding activities are necessary for survival and appetitive motivation, usually governing beneficial biological behaviors like eating, sex and reproduction. Social contacts can further facilitate the positive effects exerted by pleasurable experiences. However, artificial stimulants can be detrimental, since flexibility and normal control of behavior are deteriorated. Additionally, addictive drugs are capable of directly acting on reward pathways, now, in part, via endogenous morphine processes.

Total focusing method with correlation processing of antenna array signals

Science.gov (United States)

Kozhemyak, O. A.; Bortalevich, S. I.; Loginov, E. L.; Shinyakov, Y. A.; Sukhorukov, M. P.

2018-03-01

The article proposes a method of preliminary correlation processing of a complete set of antenna array signals used in the image reconstruction algorithm. The results of experimental studies of 3D reconstruction of various reflectors using and without correlation processing are presented in the article. Software ‘IDealSystem3D’ by IDeal-Technologies was used for experiments. Copper wires of different diameters located in a water bath were used as a reflector. The use of correlation processing makes it possible to obtain more accurate reconstruction of the image of the reflectors and to increase the signal-to-noise ratio. The experimental results were processed using an original program. This program allows varying the parameters of the antenna array and sampling frequency.

Degradation alternatives for a commercial fungicide in water: biological, photo-Fenton, and coupled biological photo-Fenton processes.

Science.gov (United States)

López-Loveira, Elsa; Ariganello, Federico; Medina, María Sara; Centrón, Daniela; Candal, Roberto; Curutchet, Gustavo

2017-11-01

Imazalil (IMZ) is a widely used fungicide for the post-harvest treatment of citrus, classified as "likely to be carcinogenic in humans" for EPA, that can be only partially removed by conventional biological treatment. Consequently, specific or combined processes should be applied to prevent its release to the environment. Biological treatment with adapted microorganism consortium, photo-Fenton, and coupled biological photo-Fenton processes were tested as alternatives for the purification of water containing high concentration of the fungicide and the coadjutants present in the commercial formulation. IMZ-resistant consortium with the capacity to degrade IMZ in the presence of a C-rich co-substrate was isolated from sludge coming from a fruit packaging company wastewater treatment plant. This consortium was adapted to resist and degrade the organics present in photo-Fenton-oxidized IMZ water solution. Bacteria colonies from the consortia were isolated and identified. The effect of H 2 O 2 initial concentration and dosage on IMZ degradation rate, average oxidation state (AOS), organic acid concentration, oxidation, and mineralization percentage after photo-Fenton process was determined. The application of biological treatment to the oxidized solutions notably decreased the total organic carbon (TOC) in solution. The effect of the oxidation degree, limited by H 2 O 2 concentration and dosage, on the percentage of mineralization obtained after the biological treatment was determined and explained in terms of changes in AOS. The concentration of H 2 O 2 necessary to eliminate IMZ by photo-Fenton and to reduce TOC and chemical oxygen demand (COD) by biological treatment, in order to allow the release of the effluents to rivers with different flows, was estimated.

Towards a heterarchical approach to biology and cognition

DEFF Research Database (Denmark)

Bruni, Luis Emilio; Giorgi, Franco

2015-01-01

to the different scientific disciplines working towards a multilevel integrative perspective of biological and cognitive processes, such as systems and integrative biology and neuroscience, social and cultural neuroscience, social signal transduction and psychoneuroimmunology, for instance. We argue...... that structures and substrates are by necessity organized hierarchically, while communication processes – and their embeddedness – are rather organized heterarchically. Before getting into the implications of the heterarchical approach and its congeniality with the semiotic perspective to biology and cognition...... complementarity of bottom-up and top-down causal links. This should contribute to account for the integration, interpretation and response to complex aggregates of information at different levels of organization in a developmental context. We illustrate the dialectical nature of embedded heterarchical processes...

Advances in biomedical signal and image processing – A systematic review

Directory of Open Access Journals (Sweden)

J. Rajeswari

Full Text Available Biomedical signal and image processing establish a dynamic area of specialization in both academic as well as research aspects of biomedical engineering. The concepts of signal and image processing have been widely used for extracting the physiological information in implementing many clinical procedures for sophisticated medical practices and applications. In this paper, the relationship between electrophysiological signals, i.e., electrocardiogram (ECG, electromyogram (EMG, electroencephalogram (EEG and functional image processing and their derived interactions have been discussed. Examples have been investigated in various case studies such as neurosciences, functional imaging, and cardiovascular system, by using different algorithms and methods. The interaction between the extracted information obtained from multiple signals and modalities seems to be very promising. The advanced algorithms and methods in the area of information retrieval based on time-frequency representation have been investigated. Finally, some examples of algorithms have been discussed in which the electrophysiological signals and functional images have been properly extracted and have a significant impact on various biomedical applications. Keywords: Biomedical signals and images, Processing, Analysis

Signal processing in an acousto-optical spectral colorimeter

Science.gov (United States)

Emeljanov, Sergey P.; Kludzin, Victor V.; Kochin, Leonid B.; Medvedev, Sergey V.; Polosin, Lev L.; Sokolov, Vladimir K.

2002-02-01

The algorithms of spectrometer signals processing in the acousto-optical spectral colorimeter, proposed earlier are discussed. This processing is directional on distortion elimination of an optical system spectral characteristics and photoelectric transformations, and also for calculation of tristimulus coefficients X,Y,Z in an international colorimetric system of a CIE - 31 and transformation them in coordinates of recommended CIE uniform contrast systems LUV and LAB.

Unique portable signal acquisition/processing station

International Nuclear Information System (INIS)

Garron, R.D.; Azevedo, S.G.

1983-01-01

At Lawrence Livermore National Laboratory, there are experimental applications requiring digital signal acquisition as well as data reduction and analysis. A prototype Signal Acquisition/Processing Station (SAPS) has been constructed and is currently undergoing tests. The system employs an LSI-11/23 computer with Data Translation analog-to-digital hardware. SAPS is housed in a roll-around cart which has been designed to withstand most subtle EMI/RFI environments. A user-friendly menu allows a user to access powerful data acquisition packages with a minimum of training. The software architecture of SAPS involves two operating systems, each being transparent to the user. Since this is a general purpose workstation with several units being utilized, an emphasis on low cost, reliability, and maintenance was stressed during conception and design. The system is targeted for mid-range frequency data acquisition; between a data logger and a transient digitizer

Clustering method to process signals from a CdZnTe detector

International Nuclear Information System (INIS)

Zhang, Lan; Takahashi, Hiroyuki; Fukuda, Daiji; Nakazawa, Masaharu

2001-01-01

The poor mobility of holes in a compound semiconductor detector results in the imperfect collection of the primary charge deposited in the detector. Furthermore the fluctuation of the charge loss efficiency due to the change in the hole collection path length seriously degrades the energy resolution of the detector. Since the charge collection efficiency varies with the signal waveform, we can expect the improvement of the energy resolution through a proper waveform signal processing method. We developed a new digital signal processing technique, a clustering method which derives typical patterns containing the information on the real situation inside a detector from measured signals. The obtained typical patterns for the detector are then used for the pattern matching method. Measured signals are classified through analyzing the practical waveform variation due to the charge trapping, the electric field and the crystal defect etc. Signals with similar shape are placed into the same cluster. For each cluster we calculate an average waveform as a reference pattern. Using these reference patterns obtained from all the clusters, we can classify other measured signal waveforms from the same detector. Then signals are independently processed according to the classified category and form corresponding spectra. Finally these spectra are merged into one spectrum by multiplying normalization coefficients. The effectiveness of this method was verified with a CdZnTe detector of 2 mm thick and a 137 Cs gamma-ray source. The obtained energy resolution as improved to about 8 keV (FWHM). Because the clustering method is only related to the measured waveforms, it can be applied to any type and size of detectors and compatible with any type of filtering methods. (author)

Influence of different natural physical fields on biological processes

Science.gov (United States)

Mashinsky, A. L.

2001-01-01

In space flight conditions gravity, magnetic, and electrical fields as well as ionizing radiation change both in size, and in direction. This causes disruptions in the conduct of some physical processes, chemical reactions, and metabolism in living organisms. In these conditions organisms of different phylogenetic level change their metabolic reactions undergo changes such as disturbances in ionic exchange both in lower and in higher plants, changes in cell morphology for example, gyrosity in Proteus ( Proteus vulgaris), spatial disorientation in coleoptiles of Wheat ( Triticum aestivum) and Pea ( Pisum sativum) seedlings, mutational changes in Crepis ( Crepis capillaris) and Arabidopsis ( Arabidopsis thaliana) seedling. It has been found that even in the absence of gravity, gravireceptors determining spatial orientation in higher plants under terrestrial conditions are formed in the course of ontogenesis. Under weightlessness this system does not function and spatial orientation is determined by the light flux gradient or by the action of some other factors. Peculiarities of the formation of the gravireceptor apparatus in higher plants, amphibians, fish, and birds under space flight conditions have been observed. It has been found that the system in which responses were accompanied by phase transition have proven to be gravity-sensitive under microgravity conditions. Such reactions include also the process of photosynthesis which is the main energy production process in plants. In view of the established effects of microgravity and different natural physical fields on biological processes, it has been shown that these processes change due to the absence of initially rigid determination. The established biological effect of physical fields influence on biological processes in organisms is the starting point for elucidating the role of gravity and evolutionary development of various organisms on Earth.

Creating biological nanomaterials using synthetic biology

International Nuclear Information System (INIS)

Rice, MaryJoe K; Ruder, Warren C

2014-01-01

Synthetic biology is a new discipline that combines science and engineering approaches to precisely control biological networks. These signaling networks are especially important in fields such as biomedicine and biochemical engineering. Additionally, biological networks can also be critical to the production of naturally occurring biological nanomaterials, and as a result, synthetic biology holds tremendous potential in creating new materials. This review introduces the field of synthetic biology, discusses how biological systems naturally produce materials, and then presents examples and strategies for incorporating synthetic biology approaches in the development of new materials. In particular, strategies for using synthetic biology to produce both organic and inorganic nanomaterials are discussed. Ultimately, synthetic biology holds the potential to dramatically impact biological materials science with significant potential applications in medical systems. (review)

Creating biological nanomaterials using synthetic biology.

Science.gov (United States)

Rice, MaryJoe K; Ruder, Warren C

2014-02-01

Synthetic biology is a new discipline that combines science and engineering approaches to precisely control biological networks. These signaling networks are especially important in fields such as biomedicine and biochemical engineering. Additionally, biological networks can also be critical to the production of naturally occurring biological nanomaterials, and as a result, synthetic biology holds tremendous potential in creating new materials. This review introduces the field of synthetic biology, discusses how biological systems naturally produce materials, and then presents examples and strategies for incorporating synthetic biology approaches in the development of new materials. In particular, strategies for using synthetic biology to produce both organic and inorganic nanomaterials are discussed. Ultimately, synthetic biology holds the potential to dramatically impact biological materials science with significant potential applications in medical systems.

Signal processing issues in reflection tomography

Science.gov (United States)

Cadalli, Nail

2001-12-01

This dissertation focuses on signal modeling and processing issues of the following problems in reflection tomography: synthetic aperture radar (SAR) imaging of a runway and surroundings from an aircraft approaching for landing, acoustic imaging of objects buried in soil, and lidar imaging of underwater objects. The highly squinted geometry of runway imaging necessitates the incorporation of wavefront curvature into the signal model. We investigate the feasibility of using the wavenumber-domain (ω - k) SAR inversion algorithm, which models the actual curvature of the wavefront, for runway imaging. We demonstrate the aberrations that the algorithm can produce when the squint angle is close to 90° and show that high-quality reconstruction is still possible provided that the interpolation is performed accurately enough, which can be achieved by increasing the temporal sampling rate. We compare the performance with that of a more general inversion method (GIM) that solves the measurement equation directly. The performances of both methods are comparable in the noise- free case. Being inherently robust to noise, GIM produces superior results in the noisy case. We also present a solution to the left-right ambiguity of runway imaging using interferometric processing. In imaging of objects buried in soil, we pursue an acoustic approach primarily for detection and imaging of cultural artifacts. We have developed a mathematical model and associated computer software in order to simulate the signals acquired by the actual experimental system, and a bistatic SAR-type algorithm for reconstruction. In the reconstructions from simulated data, objects were detectable, but near-field objects suffered from shifts and smears. To account for wavefront curvature, we formulated processing of the simulated data using the 3-D version of the monostatic ω - k algorithm. In lidar imaging of underwater objects, we formulate the problem as a 3-D tomographic reconstruction problem. We have

100 years after Smoluchowski: stochastic processes in cell biology

International Nuclear Information System (INIS)

Holcman, D; Schuss, Z

2017-01-01

100 years after Smoluchowski introduced his approach to stochastic processes, they are now at the basis of mathematical and physical modeling in cellular biology: they are used for example to analyse and to extract features from a large number (tens of thousands) of single molecular trajectories or to study the diffusive motion of molecules, proteins or receptors. Stochastic modeling is a new step in large data analysis that serves extracting cell biology concepts. We review here Smoluchowski’s approach to stochastic processes and provide several applications for coarse-graining diffusion, studying polymer models for understanding nuclear organization and finally, we discuss the stochastic jump dynamics of telomeres across cell division and stochastic gene regulation. (topical review)

Distortions caused by the signal processing in analog AM modulators

International Nuclear Information System (INIS)

Njau, E.C.

1988-08-01

Complete analytical expressions for distortions caused by signal processing in analog AM modulators are developed. The salient features in these expressions are shown to be consistent with displays of actual spectra of AM signals. Finally suggestions are given on how the distortions may be practically minimized. (author). 6 refs, 3 figs

Dissection of the insulin signaling pathway via quantitative phosphoproteomics

DEFF Research Database (Denmark)

Krüger, Marcus; Kratchmarova, Irina; Blagoev, Blagoy

2008-01-01

spectrum of the tyrosine phosphorylation cascade, we have defined the tyrosine-phosphoproteome of the insulin signaling pathway, using high resolution mass spectrometry in combination with phosphotyrosine immunoprecipitation and stable isotope labeling by amino acids in cell culture (SILAC......The insulin signaling pathway is of pivotal importance in metabolic diseases, such as diabetes, and in cellular processes, such as aging. Insulin activates a tyrosine phosphorylation cascade that branches to create a complex network affecting multiple biological processes. To understand the full...

A probablistic neural network classification system for signal and image processing

Energy Technology Data Exchange (ETDEWEB)

Bowman, B. [Lawrence Livermore National Lab., CA (United States)

1994-11-15

The Acoustical Heart Valve Analysis Package is a system for signal and image processing and classification. It is being developed in both Matlab and C, to provide an interactive, interpreted environment, and has been optimized for large scale matrix operations. It has been used successfully to classify acoustic signals from implanted prosthetic heart valves in human patients, and will be integrated into a commercial Heart Valve Screening Center. The system uses several standard signal processing algorithms, as well as supervised learning techniques using the probabilistic neural network (PNN). Although currently used for the acoustic heart valve application, the algorithms and modular design allow it to be used for other applications, as well. We will describe the signal classification system, and show results from a set of test valves.

Wnt secretion and signaling in Caenorhabditis elegans

NARCIS (Netherlands)

Yang, P.T.

2008-01-01

Wnt proteins are a highly conserved family of signaling molecules that play a central role during development and in adult tissue homeostasis. Wnt proteins regulate a variety of biological processes, ranging from cell proliferation and cell fate determination to cell migration, axon guidance and

Analog integrated circuits design for processing physiological signals.

Science.gov (United States)

Li, Yan; Poon, Carmen C Y; Zhang, Yuan-Ting

2010-01-01

Analog integrated circuits (ICs) designed for processing physiological signals are important building blocks of wearable and implantable medical devices used for health monitoring or restoring lost body functions. Due to the nature of physiological signals and the corresponding application scenarios, the ICs designed for these applications should have low power consumption, low cutoff frequency, and low input-referred noise. In this paper, techniques for designing the analog front-end circuits with these three characteristics will be reviewed, including subthreshold circuits, bulk-driven MOSFETs, floating gate MOSFETs, and log-domain circuits to reduce power consumption; methods for designing fully integrated low cutoff frequency circuits; as well as chopper stabilization (CHS) and other techniques that can be used to achieve a high signal-to-noise performance. Novel applications using these techniques will also be discussed.

Signal Transduction of Sphingosine-1-Phosphate G Protein—Coupled Receptors

Directory of Open Access Journals (Sweden)

Nicholas Young

2006-01-01

Full Text Available Sphingosine-1-phosphate (S1P is a bioactive lipid capable of eliciting dramatic effects in a variety of cell types. Signaling by this molecule is by a family of five G protein—coupled receptors named S1P1–5 that signal through a variety of pathways to regulate cell proliferation, migration, cytoskeletal organization, and differentiation. These receptors are expressed in a wide variety of tissues and cell types, and their cellular effects contribute to important biological and pathological functions of S1P in many processes, including angiogenesis, vascular development, lymphocyte trafficking, and cancer. This review will focus on the current progress in the field of S1P receptor signaling and biology.

Intelligent sensor networks the integration of sensor networks, signal processing and machine learning

CERN Document Server

Hu, Fei

2012-01-01

Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, incl

First-order Convex Optimization Methods for Signal and Image Processing

DEFF Research Database (Denmark)

Jensen, Tobias Lindstrøm

2012-01-01

In this thesis we investigate the use of first-order convex optimization methods applied to problems in signal and image processing. First we make a general introduction to convex optimization, first-order methods and their iteration complexity. Then we look at different techniques, which can...... be used with first-order methods such as smoothing, Lagrange multipliers and proximal gradient methods. We continue by presenting different applications of convex optimization and notable convex formulations with an emphasis on inverse problems and sparse signal processing. We also describe the multiple...

Dysphagia Screening: Contributions of Cervical Auscultation Signals and Modern Signal-Processing Techniques

Science.gov (United States)

Dudik, Joshua M.; Coyle, James L.

2015-01-01

Cervical auscultation is the recording of sounds and vibrations caused by the human body from the throat during swallowing. While traditionally done by a trained clinician with a stethoscope, much work has been put towards developing more sensitive and clinically useful methods to characterize the data obtained with this technique. The eventual goal of the field is to improve the effectiveness of screening algorithms designed to predict the risk that swallowing disorders pose to individual patients’ health and safety. This paper provides an overview of these signal processing techniques and summarizes recent advances made with digital transducers in hopes of organizing the highly varied research on cervical auscultation. It investigates where on the body these transducers are placed in order to record a signal as well as the collection of analog and digital filtering techniques used to further improve the signal quality. It also presents the wide array of methods and features used to characterize these signals, ranging from simply counting the number of swallows that occur over a period of time to calculating various descriptive features in the time, frequency, and phase space domains. Finally, this paper presents the algorithms that have been used to classify this data into ‘normal’ and ‘abnormal’ categories. Both linear as well as non-linear techniques are presented in this regard. PMID:26213659

Instantaneous and Frequency-Warped Signal Processing Techniques for Auditory Source Separation.

Science.gov (United States)

Wang, Avery Li-Chun

This thesis summarizes several contributions to the areas of signal processing and auditory source separation. The philosophy of Frequency-Warped Signal Processing is introduced as a means for separating the AM and FM contributions to the bandwidth of a complex-valued, frequency-varying sinusoid p (n), transforming it into a signal with slowly-varying parameters. This transformation facilitates the removal of p (n) from an additive mixture while minimizing the amount of damage done to other signal components. The average winding rate of a complex-valued phasor is explored as an estimate of the instantaneous frequency. Theorems are provided showing the robustness of this measure. To implement frequency tracking, a Frequency-Locked Loop algorithm is introduced which uses the complex winding error to update its frequency estimate. The input signal is dynamically demodulated and filtered to extract the envelope. This envelope may then be remodulated to reconstruct the target partial, which may be subtracted from the original signal mixture to yield a new, quickly-adapting form of notch filtering. Enhancements to the basic tracker are made which, under certain conditions, attain the Cramer -Rao bound for the instantaneous frequency estimate. To improve tracking, the novel idea of Harmonic -Locked Loop tracking, using N harmonically constrained trackers, is introduced for tracking signals, such as voices and certain musical instruments. The estimated fundamental frequency is computed from a maximum-likelihood weighting of the N tracking estimates, making it highly robust. The result is that harmonic signals, such as voices, can be isolated from complex mixtures in the presence of other spectrally overlapping signals. Additionally, since phase information is preserved, the resynthesized harmonic signals may be removed from the original mixtures with relatively little damage to the residual signal. Finally, a new methodology is given for designing linear-phase FIR filters

Dominating biological networks.

Directory of Open Access Journals (Sweden)

Tijana Milenković

Full Text Available Proteins are essential macromolecules of life that carry out most cellular processes. Since proteins aggregate to perform function, and since protein-protein interaction (PPI networks model these aggregations, one would expect to uncover new biology from PPI network topology. Hence, using PPI networks to predict protein function and role of protein pathways in disease has received attention. A debate remains open about whether network properties of "biologically central (BC" genes (i.e., their protein products, such as those involved in aging, cancer, infectious diseases, or signaling and drug-targeted pathways, exhibit some topological centrality compared to the rest of the proteins in the human PPI network.To help resolve this debate, we design new network-based approaches and apply them to get new insight into biological function and disease. We hypothesize that BC genes have a topologically central (TC role in the human PPI network. We propose two different concepts of topological centrality. We design a new centrality measure to capture complex wirings of proteins in the network that identifies as TC those proteins that reside in dense extended network neighborhoods. Also, we use the notion of domination and find dominating sets (DSs in the PPI network, i.e., sets of proteins such that every protein is either in the DS or is a neighbor of the DS. Clearly, a DS has a TC role, as it enables efficient communication between different network parts. We find statistically significant enrichment in BC genes of TC nodes and outperform the existing methods indicating that genes involved in key biological processes occupy topologically complex and dense regions of the network and correspond to its "spine" that connects all other network parts and can thus pass cellular signals efficiently throughout the network. To our knowledge, this is the first study that explores domination in the context of PPI networks.

Soft-core dataflow processor architecture optimised for radar signal processing: Article

CSIR Research Space (South Africa)

Broich, R

2014-10-01

Full Text Available Current radar signal processors lack either performance or flexibility. Custom soft-core processors exhibit potential in high-performance signal processing applications, yet remain relatively unexplored in research literature. In this paper, we use...

Real-time radar signal processing using GPGPU (general-purpose graphic processing unit)

Science.gov (United States)

Kong, Fanxing; Zhang, Yan Rockee; Cai, Jingxiao; Palmer, Robert D.

2016-05-01

This study introduces a practical approach to develop real-time signal processing chain for general phased array radar on NVIDIA GPUs(Graphical Processing Units) using CUDA (Compute Unified Device Architecture) libraries such as cuBlas and cuFFT, which are adopted from open source libraries and optimized for the NVIDIA GPUs. The processed results are rigorously verified against those from the CPUs. Performance benchmarked in computation time with various input data cube sizes are compared across GPUs and CPUs. Through the analysis, it will be demonstrated that GPGPUs (General Purpose GPU) real-time processing of the array radar data is possible with relatively low-cost commercial GPUs.

From spectral holeburning memory to spatial-spectral microwave signal processing

International Nuclear Information System (INIS)

Babbitt, Wm Randall; Barber, Zeb W; Harrington, Calvin; Mohan, R Krishna; Sharpe, Tia; Bekker, Scott H; Chase, Michael D; Merkel, Kristian D; Stiffler, Colton R; Traxinger, Aaron S; Woidtke, Alex J

2014-01-01

Many storage and processing systems based on spectral holeburning have been proposed that access the broad bandwidth and high dynamic range of spatial-spectral materials, but only recently have practical systems been developed that exceed the performance and functional capabilities of electronic devices. This paper reviews the history of the proposed applications of spectral holeburning and spatial-spectral materials, from frequency domain optical memory to microwave photonic signal processing systems. The recent results of a 20 GHz bandwidth high performance spectrum monitoring system with the additional capability of broadband direction finding demonstrates the potential for spatial-spectral systems to be the practical choice for solving demanding signal processing problems in the near future. (paper)

Signal processing in urodynamics: towards high definition urethral pressure profilometry.

Science.gov (United States)

Klünder, Mario; Sawodny, Oliver; Amend, Bastian; Ederer, Michael; Kelp, Alexandra; Sievert, Karl-Dietrich; Stenzl, Arnulf; Feuer, Ronny

2016-03-22

Urethral pressure profilometry (UPP) is used in the diagnosis of stress urinary incontinence (SUI) which is a significant medical, social, and economic problem. Low spatial pressure resolution, common occurrence of artifacts, and uncertainties in data location limit the diagnostic value of UPP. To overcome these limitations, high definition urethral pressure profilometry (HD-UPP) combining enhanced UPP hardware and signal processing algorithms has been developed. In this work, we present the different signal processing steps in HD-UPP and show experimental results from female minipigs. We use a special microtip catheter with high angular pressure resolution and an integrated inclination sensor. Signals from the catheter are filtered and time-correlated artifacts removed. A signal reconstruction algorithm processes pressure data into a detailed pressure image on the urethra's inside. Finally, the pressure distribution on the urethra's outside is calculated through deconvolution. A mathematical model of the urethra is contained in a point-spread-function (PSF) which is identified depending on geometric and material properties of the urethra. We additionally investigate the PSF's frequency response to determine the relevant frequency band for pressure information on the urinary sphincter. Experimental pressure data are spatially located and processed into high resolution pressure images. Artifacts are successfully removed from data without blurring other details. The pressure distribution on the urethra's outside is reconstructed and compared to the one on the inside. Finally, the pressure images are mapped onto the urethral geometry calculated from inclination and position data to provide an integrated image of pressure distribution, anatomical shape, and location. With its advanced sensing capabilities, the novel microtip catheter collects an unprecedented amount of urethral pressure data. Through sequential signal processing steps, physicians are provided with

Diffusion processes and related topics in biology

CERN Document Server

Ricciardi, Luigi M

1977-01-01

These notes are based on a one-quarter course given at the Department of Biophysics and Theoretical Biology of the University of Chicago in 1916. The course was directed to graduate students in the Division of Biological Sciences with interests in population biology and neurobiology. Only a slight acquaintance with probability and differential equations is required of the reader. Exercises are interwoven with the text to encourage the reader to play a more active role and thus facilitate his digestion of the material. One aim of these notes is to provide a heuristic approach, using as little mathematics as possible, to certain aspects of the theory of stochastic processes that are being increasingly employed in some of the population biol­ ogy and neurobiology literature. While the subject may be classical, the nov­ elty here lies in the approach and point of view, particularly in the applica­ tions such as the approach to the neuronal firing problem and its related dif­ fusion approximations. It is a ple...

Implementation and optimization of ultrasound signal processing algorithms on mobile GPU

Science.gov (United States)

Kong, Woo Kyu; Lee, Wooyoul; Kim, Kyu Cheol; Yoo, Yangmo; Song, Tai-Kyong

2014-03-01

A general-purpose graphics processing unit (GPGPU) has been used for improving computing power in medical ultrasound imaging systems. Recently, a mobile GPU becomes powerful to deal with 3D games and videos at high frame rates on Full HD or HD resolution displays. This paper proposes the method to implement ultrasound signal processing on a mobile GPU available in the high-end smartphone (Galaxy S4, Samsung Electronics, Seoul, Korea) with programmable shaders on the OpenGL ES 2.0 platform. To maximize the performance of the mobile GPU, the optimization of shader design and load sharing between vertex and fragment shader was performed. The beamformed data were captured from a tissue mimicking phantom (Model 539 Multipurpose Phantom, ATS Laboratories, Inc., Bridgeport, CT, USA) by using a commercial ultrasound imaging system equipped with a research package (Ultrasonix Touch, Ultrasonix, Richmond, BC, Canada). The real-time performance is evaluated by frame rates while varying the range of signal processing blocks. The implementation method of ultrasound signal processing on OpenGL ES 2.0 was verified by analyzing PSNR with MATLAB gold standard that has the same signal path. CNR was also analyzed to verify the method. From the evaluations, the proposed mobile GPU-based processing method has no significant difference with the processing using MATLAB (i.e., PSNRe., 11.31). From the mobile GPU implementation, the frame rates of 57.6 Hz were achieved. The total execution time was 17.4 ms that was faster than the acquisition time (i.e., 34.4 ms). These results indicate that the mobile GPU-based processing method can support real-time ultrasound B-mode processing on the smartphone.

Interactions between visceral afferent signaling and stimulus processing

Directory of Open Access Journals (Sweden)

Hugo D Critchley

2015-08-01

Full Text Available Visceral afferent signals to the brain influence thoughts, feelings and behaviour. Here we highlight the findings of a set of empirical investigations in humans concerning body-mind interaction that focus on how feedback from states of autonomic arousal shapes cognition and emotion. There is a longstanding debate regarding the contribution of the body, to mental processes. Recent theoretical models broadly acknowledge the role of (autonomically-mediated physiological arousal to emotional, social and motivational behaviours, yet the underlying mechanisms are only partially characterized. Neuroimaging is overcoming this shortfall; first, by demonstrating correlations between autonomic change and discrete patterns of evoked, and task-independent, neural activity; second, by mapping the central consequences of clinical perturbations in autonomic response and; third, by probing how dynamic fluctuations in peripheral autonomic state are integrated with perceptual, cognitive and emotional processes. Building on the notion that an important source of the brain’s representation of physiological arousal is derived from afferent information from arterial baroreceptors, we have exploited the phasic nature of these signals to show their differential contribution to the processing of emotionally-salient stimuli. This recent work highlights the facilitation at neural and behavioral levels of fear and threat processing that contrasts with the more established observations of the inhibition of central pain processing during baroreceptors activation. The implications of this body-brain-mind axis are discussed.

Classical and spatial stochastic processes with applications to biology

CERN Document Server

Schinazi, Rinaldo B

2014-01-01

The revised and expanded edition of this textbook presents the concepts and applications of random processes with the same illuminating simplicity as its first edition, but with the notable addition of substantial modern material on biological modeling. While still treating many important problems in fields such as engineering and mathematical physics, the book also focuses on the highly relevant topics of cancerous mutations, influenza evolution, drug resistance, and immune response. The models used elegantly apply various classical stochastic models presented earlier in the text, and exercises are included throughout to reinforce essential concepts. The second edition of Classical and Spatial Stochastic Processes is suitable as a textbook for courses in stochastic processes at the advanced-undergraduate and graduate levels, or as a self-study resource for researchers and practitioners in mathematics, engineering, physics, and mathematical biology. Reviews of the first edition: An appetizing textbook for a f...

Modularized TGFbeta-Smad Signaling Pathway

Science.gov (United States)

Li, Yongfeng; Wang, M.; Carra, C.; Cucinotta, F. A.

2011-01-01

The Transforming Growth Factor beta (TGFbeta) signaling pathway is a prominent regulatory signaling pathway controlling various important cellular processes. It can be induced by several factors, including ionizing radiation. It is regulated by Smads in a negative feedback loop through promoting increases in the regulatory Smads in the cell nucleus, and subsequent expression of inhibitory Smad, Smad7 to form a ubiquitin ligase with Smurf targeting active TGF receptors for degradation. In this work, we proposed a mathematical model to study the radiation-induced Smad-regulated TGF signaling pathway. By modularization, we are able to analyze each module (subsystem) and recover the nonlinear dynamics of the entire network system. Meanwhile the excitability, a common feature observed in the biological systems, along the TGF signaling pathway is discussed by mathematical analysis and numerical simulation.

Influences of excluded volume of molecules on signaling processes on the biomembrane.

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Masashi Fujii

Full Text Available We investigate the influences of the excluded volume of molecules on biochemical reaction processes on 2-dimensional surfaces using a model of signal transduction processes on biomembranes. We perform simulations of the 2-dimensional cell-based model, which describes the reactions and diffusion of the receptors, signaling proteins, target proteins, and crowders on the cell membrane. The signaling proteins are activated by receptors, and these activated signaling proteins activate target proteins that bind autonomously from the cytoplasm to the membrane, and unbind from the membrane if activated. If the target proteins bind frequently, the volume fraction of molecules on the membrane becomes so large that the excluded volume of the molecules for the reaction and diffusion dynamics cannot be negligible. We find that such excluded volume effects of the molecules induce non-trivial variations of the signal flow, defined as the activation frequency of target proteins, as follows. With an increase in the binding rate of target proteins, the signal flow varies by i monotonically increasing; ii increasing then decreasing in a bell-shaped curve; or iii increasing, decreasing, then increasing in an S-shaped curve. We further demonstrate that the excluded volume of molecules influences the hierarchical molecular distributions throughout the reaction processes. In particular, when the system exhibits a large signal flow, the signaling proteins tend to surround the receptors to form receptor-signaling protein clusters, and the target proteins tend to become distributed around such clusters. To explain these phenomena, we analyze the stochastic model of the local motions of molecules around the receptor.

Signal processing for passive detection and classification of underwater acoustic signals

Science.gov (United States)

Chung, Kil Woo

2011-12-01

This dissertation examines signal processing for passive detection, classification and tracking of underwater acoustic signals for improving port security and the security of coastal and offshore operations. First, we consider the problem of passive acoustic detection of a diver in a shallow water environment. A frequency-domain multi-band matched-filter approach to swimmer detection is presented. The idea is to break the frequency contents of the hydrophone signals into multiple narrow frequency bands, followed by time averaged (about half of a second) energy calculation over each band. Then, spectra composed of such energy samples over the chosen frequency bands are correlated to form a decision variable. The frequency bands with highest Signal/Noise ratio are used for detection. The performance of the proposed approach is demonstrated for experimental data collected for a diver in the Hudson River. We also propose a new referenceless frequency-domain multi-band detector which, unlike other reference-based detectors, does not require a diver specific signature. Instead, our detector matches to a general feature of the diver spectrum in the high frequency range: the spectrum is roughly periodic in time and approximately flat when the diver exhales. The performance of the proposed approach is demonstrated by using experimental data collected from the Hudson River. Moreover, we present detection, classification and tracking of small vessel signals. Hydroacoustic sensors can be applied for the detection of noise generated by vessels, and this noise can be used for vessel detection, classification and tracking. This dissertation presents recent improvements aimed at the measurement and separation of ship DEMON (Detection of Envelope Modulation on Noise) acoustic signatures in busy harbor conditions. Ship signature measurements were conducted in the Hudson River and NY Harbor. The DEMON spectra demonstrated much better temporal stability compared with the full ship

Signal Processing Effects for Ultrasonic Guided Wave Scanning of Composites

International Nuclear Information System (INIS)

Roth, D.J.; Cosgriff, L.M.; Martin, R.E.; Burns, E.A.; Teemer, L.

2005-01-01

The goal of this ongoing work is to optimize experimental variables for a guided wave scanning method to obtain the most revealing and accurate images of defect conditions in composite materials. This study focuses on signal processing effects involved in forming guided wave scan images. Signal processing is involved at two basic levels for deriving ultrasonic guided wave scan images. At the primary level, NASA GRC has developed algorithms to extract over 30 parameters from the multimode signal and its power spectral density. At the secondary level, there are many variables for which values must be chosen that affect actual computation of these parameters. In this study, a ceramic matrix composite sample having a delamination is characterized using the ultrasonic guided wave scan method. Energy balance and decay rate parameters of the guided wave at each scan location are calculated to form images. These images are compared with ultrasonic c-scan and thermography images. The effect of the time portion of the waveform processed on image quality is assessed by comparing with images formed using the total waveform acquired

A digital signal processing system for coherent laser radar

Science.gov (United States)

Hampton, Diana M.; Jones, William D.; Rothermel, Jeffry

1991-01-01

A data processing system for use with continuous-wave lidar is described in terms of its configuration and performance during the second survey mission of NASA'a Global Backscatter Experiment. The system is designed to estimate a complete lidar spectrum in real time, record the data from two lidars, and monitor variables related to the lidar operating environment. The PC-based system includes a transient capture board, a digital-signal processing (DSP) board, and a low-speed data-acquisition board. Both unprocessed and processed lidar spectrum data are monitored in real time, and the results are compared to those of a previous non-DSP-based system. Because the DSP-based system is digital it is slower than the surface-acoustic-wave signal processor and collects 2500 spectra/s. However, the DSP-based system provides complete data sets at two wavelengths from the continuous-wave lidars.

Time-Frequency Analysis of Non-Stationary Biological Signals with Sparse Linear Regression Based Fourier Linear Combiner

Directory of Open Access Journals (Sweden)

Yubo Wang

2017-06-01

Full Text Available It is often difficult to analyze biological signals because of their nonlinear and non-stationary characteristics. This necessitates the usage of time-frequency decomposition methods for analyzing the subtle changes in these signals that are often connected to an underlying phenomena. This paper presents a new approach to analyze the time-varying characteristics of such signals by employing a simple truncated Fourier series model, namely the band-limited multiple Fourier linear combiner (BMFLC. In contrast to the earlier designs, we first identified the sparsity imposed on the signal model in order to reformulate the model to a sparse linear regression model. The coefficients of the proposed model are then estimated by a convex optimization algorithm. The performance of the proposed method was analyzed with benchmark test signals. An energy ratio metric is employed to quantify the spectral performance and results show that the proposed method Sparse-BMFLC has high mean energy (0.9976 ratio and outperforms existing methods such as short-time Fourier transfrom (STFT, continuous Wavelet transform (CWT and BMFLC Kalman Smoother. Furthermore, the proposed method provides an overall 6.22% in reconstruction error.

Time-Frequency Analysis of Non-Stationary Biological Signals with Sparse Linear Regression Based Fourier Linear Combiner.

Science.gov (United States)

Wang, Yubo; Veluvolu, Kalyana C

2017-06-14

It is often difficult to analyze biological signals because of their nonlinear and non-stationary characteristics. This necessitates the usage of time-frequency decomposition methods for analyzing the subtle changes in these signals that are often connected to an underlying phenomena. This paper presents a new approach to analyze the time-varying characteristics of such signals by employing a simple truncated Fourier series model, namely the band-limited multiple Fourier linear combiner (BMFLC). In contrast to the earlier designs, we first identified the sparsity imposed on the signal model in order to reformulate the model to a sparse linear regression model. The coefficients of the proposed model are then estimated by a convex optimization algorithm. The performance of the proposed method was analyzed with benchmark test signals. An energy ratio metric is employed to quantify the spectral performance and results show that the proposed method Sparse-BMFLC has high mean energy (0.9976) ratio and outperforms existing methods such as short-time Fourier transfrom (STFT), continuous Wavelet transform (CWT) and BMFLC Kalman Smoother. Furthermore, the proposed method provides an overall 6.22% in reconstruction error.

Fetal QRS extraction from abdominal recordings via model-based signal processing and intelligent signal merging

International Nuclear Information System (INIS)

Haghpanahi, Masoumeh; Borkholder, David A

2014-01-01

Noninvasive fetal ECG (fECG) monitoring has potential applications in diagnosing congenital heart diseases in a timely manner and assisting clinicians to make more appropriate decisions during labor. However, despite advances in signal processing and machine learning techniques, the analysis of fECG signals has still remained in its preliminary stages. In this work, we describe an algorithm to automatically locate QRS complexes in noninvasive fECG signals obtained from a set of four electrodes placed on the mother’s abdomen. The algorithm is based on an iterative decomposition of the maternal and fetal subspaces and filtering of the maternal ECG (mECG) components from the fECG recordings. Once the maternal components are removed, a novel merging technique is applied to merge the signals and detect the fetal QRS (fQRS) complexes. The algorithm was trained and tested on the fECG datasets provided by the PhysioNet/CinC challenge 2013. The final results indicate that the algorithm is able to detect fetal peaks for a variety of signals with different morphologies and strength levels encountered in clinical practice. (paper)

State of the art of biological hydrogen production processes

International Nuclear Information System (INIS)

Loubette, N.; Junker, M.

2006-01-01

Our report gives an overview of hydrogen production processes with bacteria or algae. 4 main processes are described: water biophotolysis, photo- fermentation biological CO conversion and dark fermentation. Chemical phenomena which lead to hydrogen generation are exp/aired. Performances, limits and outlook are given for each process. Main projects, programs and key players involved in this field of research have been listed. This paper resumes few results of this report. (authors)

State of the art of biological hydrogen production processes

International Nuclear Information System (INIS)

Nicolas Loubette; Michel Junker

2006-01-01

Our report gives an overview of hydrogen production processes with bacteria or algae. 4 main processes are described: water bio-photolysis, photo-fermentation biological CO conversion and dark fermentation. Chemical phenomena which lead to hydrogen generation are explained. Performances, limits and outlook are given for each process. Main projects, programs and key players involved in this field of research have been listed. This paper resumes few results of this report. (authors)

Digital Signal Processing for a Sliceable Transceiver for Optical Access Networks

DEFF Research Database (Denmark)

Saldaña Cercos, Silvia; Wagner, Christoph; Vegas Olmos, Juan José

2015-01-01

Methods to upgrade the network infrastructure to cope with current traffic demands has attracted increasing research efforts. A promising alternative is signal slicing. Signal slicing aims at re-using low bandwidth equipment to satisfy high bandwidth traffic demands. This technique has been used...... also for implementing full signal path symmetry in real-time oscilloscopes to provide performance and signal fidelity (i.e. lower noise and jitter). In this paper the key digital signal processing (DSP) subsystems required to achieve signal slicing are surveyed. It also presents, for the first time...... penalty is reported for 10 Gbps. Power savings of the order of hundreds of Watts can be obtained when using signal slicing as an alternative to 10 Gbps implemented access networks....

12th International Conference on Intelligent Information Hiding and Multimedia Signal Processing

CERN Document Server

Tsai, Pei-Wei; Huang, Hsiang-Cheh

2017-01-01

This volume of Smart Innovation, Systems and Technologies contains accepted papers presented in IIH-MSP-2016, the 12th International Conference on Intelligent Information Hiding and Multimedia Signal Processing. The conference this year was technically co-sponsored by Tainan Chapter of IEEE Signal Processing Society, Fujian University of Technology, Chaoyang University of Technology, Taiwan Association for Web Intelligence Consortium, Fujian Provincial Key Laboratory of Big Data Mining and Applications (Fujian University of Technology), and Harbin Institute of Technology Shenzhen Graduate School. IIH-MSP 2016 is held in 21-23, November, 2016 in Kaohsiung, Taiwan. The conference is an international forum for the researchers and professionals in all areas of information hiding and multimedia signal processing. .

An introduction to audio content analysis applications in signal processing and music informatics

CERN Document Server

Lerch, Alexander

2012-01-01

"With the proliferation of digital audio distribution over digital media, audio content analysis is fast becoming a requirement for designers of intelligent signal-adaptive audio processing systems. Written by a well-known expert in the field, this book provides quick access to different analysis algorithms and allows comparison between different approaches to the same task, making it useful for newcomers to audio signal processing and industry experts alike. A review of relevant fundamentals in audio signal processing, psychoacoustics, and music theory, as well as downloadable MATLAB files are also included"--

Wnts and wing: Wnt signaling in vertebrate limb development and musculoskeletal morphogenesis.

Science.gov (United States)

Yang, Yingzi

2003-11-01

In the past twenty years, secreted signaling molecules of the Wnt family have been found to play a central role in controlling embryonic development from hydra to human. In the developing vertebrate limb, Wnt signaling is required for limb bud initiation, early limb patterning (which is governed by several well-characterized signaling centers), and, finally, late limb morphogenesis events. Wnt ligands are unique, in that they can activate several different receptor-mediated signal transduction pathways. The most extensively studied Wnt pathway is the canonical Wnt pathway, which controls gene expression by stabilizing beta-catenin in regulating a diverse array of biological processes. Recently, more attention has been given to the noncanonical Wnt pathway, which is beta-catenin-independent. The noncanonical Wnt pathway signals through activating Ca(2+) flux, JNK activation, and both small and heterotrimeric G proteins, to induce changes in gene expression, cell adhesion, migration, and polarity. Abnormal Wnt signaling leads to developmental defects and human diseases affecting either tissue development or homeostasis. Further understanding of the biological function and signaling mechanism of Wnt signaling is essential for the development of novel preventive and therapeutic approaches of human diseases. This review provides a critical perspective on how Wnt signaling regulates different developmental processes. As Wnt signaling in tumor formation has been reviewed extensively elsewhere, this part is not included in the review of the clinical significance of Wnt signaling.

Processing laboratory of radio sterilized biological tissues

International Nuclear Information System (INIS)

Aguirre H, Paulina; Zarate S, Herman; Silva R, Samy; Hitschfeld, Mario

2005-01-01

The nuclear development applications have also reached those areas related to health. The risk of getting contagious illnesses through applying biological tissues has been one of the paramount worries to be solved since infectious illnesses might be provoked by virus, fungis or bacterias coming from donors or whether they have been introduced by means of intermediate stages before the use of these tissues. Therefore it has been concluded that the tissue allografts must be sterilized. The sterilization of medical products has been one of the main applications of the ionizing radiations and that it is why the International Organization of Atomic Energy began in the 70s promoting works related to the biological tissue sterilization and pharmaceutical products. The development of different tissue preservation methods has made possible the creation of tissue banks in different countries, to deal with long-term preservation. In our country, a project was launched in 1998, 'Establishment of a Tissue Bank in Latino america', this project was supported by the OIEA through the project INT/ 6/ 049, and was the starting of the actual Processing Laboratory of Radioesterilized Biological Tissues (LPTR), leaded by the Chilean Nuclear Energy Commission (CCHEN). This first organization is part of a number of entities compounding the Tissue Bank in Chile, organizations such as the Transplantation Promotion Corporation hospitals and the LPTR. The working system is carried out by means of the interaction between the hospitals and the laboratory. The medical professionals perform the procuring of tissues in the hospitals, then send them to the LPTR where they are processed and sterilized with ionizing radiation. The cycle ends up with the tissues return released to the hospitals, where they are used, and then the result information is sent to the LPTR as a form of feedback. Up to now, human skin has been processed (64 donors), amniotic membranes (35 donors) and pig skin (175 portions

An open-loop system design for deep space signal processing applications

Science.gov (United States)

Tang, Jifei; Xia, Lanhua; Mahapatra, Rabi

2018-06-01

A novel open-loop system design with high performance is proposed for space positioning and navigation signal processing. Divided by functions, the system has four modules, bandwidth selectable data recorder, narrowband signal analyzer, time-delay difference of arrival estimator and ANFIS supplement processor. A hardware-software co-design approach is made to accelerate computing capability and improve system efficiency. Embedded with the proposed signal processing algorithms, the designed system is capable of handling tasks with high accuracy over long period of continuous measurements. The experiment results show the Doppler frequency tracking root mean square error during 3 h observation is 0.0128 Hz, while the TDOA residue analysis in correlation power spectrum is 0.1166 rad.

Calcium as a signal integrator in developing epithelial tissues.

Science.gov (United States)

Brodskiy, Pavel A; Zartman, Jeremiah J

2018-05-16

Decoding how tissue properties emerge across multiple spatial and temporal scales from the integration of local signals is a grand challenge in quantitative biology. For example, the collective behavior of epithelial cells is critical for shaping developing embryos. Understanding how epithelial cells interpret a diverse range of local signals to coordinate tissue-level processes requires a systems-level understanding of development. Integration of multiple signaling pathways that specify cell signaling information requires second messengers such as calcium ions. Increasingly, specific roles have been uncovered for calcium signaling throughout development. Calcium signaling regulates many processes including division, migration, death, and differentiation. However, the pleiotropic and ubiquitous nature of calcium signaling implies that many additional functions remain to be discovered. Here we review a selection of recent studies to highlight important insights into how multiple signals are transduced by calcium transients in developing epithelial tissues. Quantitative imaging and computational modeling have provided important insights into how calcium signaling integration occurs. Reverse-engineering the conserved features of signal integration mediated by calcium signaling will enable novel approaches in regenerative medicine and synthetic control of morphogenesis.

Stream computing for biomedical signal processing: A QRS complex detection case-study.

Science.gov (United States)

Murphy, B M; O'Driscoll, C; Boylan, G B; Lightbody, G; Marnane, W P

2015-01-01

Recent developments in "Big Data" have brought significant gains in the ability to process large amounts of data on commodity server hardware. Stream computing is a relatively new paradigm in this area, addressing the need to process data in real time with very low latency. While this approach has been developed for dealing with large scale data from the world of business, security and finance, there is a natural overlap with clinical needs for physiological signal processing. In this work we present a case study of streams processing applied to a typical physiological signal processing problem: QRS detection from ECG data.

Laser Doppler Blood Flow Imaging Using a CMOS Imaging Sensor with On-Chip Signal Processing

Directory of Open Access Journals (Sweden)

Cally Gill

2013-09-01

Full Text Available The first fully integrated 2D CMOS imaging sensor with on-chip signal processing for applications in laser Doppler blood flow (LDBF imaging has been designed and tested. To obtain a space efficient design over 64 × 64 pixels means that standard processing electronics used off-chip cannot be implemented. Therefore the analog signal processing at each pixel is a tailored design for LDBF signals with balanced optimization for signal-to-noise ratio and silicon area. This custom made sensor offers key advantages over conventional sensors, viz. the analog signal processing at the pixel level carries out signal normalization; the AC amplification in combination with an anti-aliasing filter allows analog-to-digital conversion with a low number of bits; low resource implementation of the digital processor enables on-chip processing and the data bottleneck that exists between the detector and processing electronics has been overcome. The sensor demonstrates good agreement with simulation at each design stage. The measured optical performance of the sensor is demonstrated using modulated light signals and in vivo blood flow experiments. Images showing blood flow changes with arterial occlusion and an inflammatory response to a histamine skin-prick demonstrate that the sensor array is capable of detecting blood flow signals from tissue.