Signal Processing in Periodically Forced Gradient Frequency Neural Networks

PubMed Central

Kim, Ji Chul; Large, Edward W.

2015-01-01

Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing. PMID:26733858

Dual Rate Adaptive Control for an Industrial Heat Supply Process Using Signal Compensation Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chai, Tianyou; Jia, Yao; Wang, Hong

The industrial heat supply process (HSP) is a highly nonlinear cascaded process which uses a steam valve opening as its control input, the steam flow-rate as its inner loop output and the supply water temperature as its outer loop output. The relationship between the heat exchange rate and the model parameters, such as steam density, entropy, and fouling correction factor and heat exchange efficiency are unknown and nonlinear. Moreover, these model parameters vary in line with steam pressure, ambient temperature and the residuals caused by the quality variations of the circulation water. When the steam pressure and the ambient temperaturemore » are of high values and are subjected to frequent external random disturbances, the supply water temperature and the steam flow-rate would interact with each other and fluctuate a lot. This is also true when the process exhibits unknown characteristic variations of the process dynamics caused by the unexpected changes of the heat exchange residuals. As a result, it is difficult to control the supply water temperature and the rates of changes of steam flow-rate well inside their targeted ranges. In this paper, a novel compensation signal based dual rate adaptive controller is developed by representing the unknown variations of dynamics as unmodeled dynamics. In the proposed controller design, such a compensation signal is constructed and added onto the control signal obtained from the linear deterministic model based feedback control design. Such a compensation signal aims at eliminating the unmodeled dynamics and the rate of changes of the currently sample unmodeled dynamics. A successful industrial application is carried out, where it has been shown that both the supply water temperature and the rate of the changes of the steam flow-rate can be controlled well inside their targeted ranges when the process is subjected to unknown variations of its dynamics.« less

Online tracking of instantaneous frequency and amplitude of dynamical system response

NASA Astrophysics Data System (ADS)

Frank Pai, P.

2010-05-01

This paper presents a sliding-window tracking (SWT) method for accurate tracking of the instantaneous frequency and amplitude of arbitrary dynamic response by processing only three (or more) most recent data points. Teager-Kaiser algorithm (TKA) is a well-known four-point method for online tracking of frequency and amplitude. Because finite difference is used in TKA, its accuracy is easily destroyed by measurement and/or signal-processing noise. Moreover, because TKA assumes the processed signal to be a pure harmonic, any moving average in the signal can destroy the accuracy of TKA. On the other hand, because SWT uses a constant and a pair of windowed regular harmonics to fit the data and estimate the instantaneous frequency and amplitude, the influence of any moving average is eliminated. Moreover, noise filtering is an implicit capability of SWT when more than three data points are used, and this capability increases with the number of processed data points. To compare the accuracy of SWT and TKA, Hilbert-Huang transform is used to extract accurate time-varying frequencies and amplitudes by processing the whole data set without assuming the signal to be harmonic. Frequency and amplitude trackings of different amplitude- and frequency-modulated signals, vibrato in music, and nonlinear stationary and non-stationary dynamic signals are studied. Results show that SWT is more accurate, robust, and versatile than TKA for online tracking of frequency and amplitude.

Artificial Neural Network-Based Early-Age Concrete Strength Monitoring Using Dynamic Response Signals.

PubMed

Kim, Junkyeong; Lee, Chaggil; Park, Seunghee

2017-06-07

Concrete is one of the most common materials used to construct a variety of civil infrastructures. However, since concrete might be susceptible to brittle fracture, it is essential to confirm the strength of concrete at the early-age stage of the curing process to prevent unexpected collapse. To address this issue, this study proposes a novel method to estimate the early-age strength of concrete, by integrating an artificial neural network algorithm with a dynamic response measurement of the concrete material. The dynamic response signals of the concrete, including both electromechanical impedances and guided ultrasonic waves, are obtained from an embedded piezoelectric sensor module. The cross-correlation coefficient of the electromechanical impedance signals and the amplitude of the guided ultrasonic wave signals are selected to quantify the variation in dynamic responses according to the strength of the concrete. Furthermore, an artificial neural network algorithm is used to verify a relationship between the variation in dynamic response signals and concrete strength. The results of an experimental study confirm that the proposed approach can be effectively applied to estimate the strength of concrete material from the early-age stage of the curing process.

Artificial Neural Network-Based Early-Age Concrete Strength Monitoring Using Dynamic Response Signals

PubMed Central

Kim, Junkyeong; Lee, Chaggil; Park, Seunghee

2017-01-01

Concrete is one of the most common materials used to construct a variety of civil infrastructures. However, since concrete might be susceptible to brittle fracture, it is essential to confirm the strength of concrete at the early-age stage of the curing process to prevent unexpected collapse. To address this issue, this study proposes a novel method to estimate the early-age strength of concrete, by integrating an artificial neural network algorithm with a dynamic response measurement of the concrete material. The dynamic response signals of the concrete, including both electromechanical impedances and guided ultrasonic waves, are obtained from an embedded piezoelectric sensor module. The cross-correlation coefficient of the electromechanical impedance signals and the amplitude of the guided ultrasonic wave signals are selected to quantify the variation in dynamic responses according to the strength of the concrete. Furthermore, an artificial neural network algorithm is used to verify a relationship between the variation in dynamic response signals and concrete strength. The results of an experimental study confirm that the proposed approach can be effectively applied to estimate the strength of concrete material from the early-age stage of the curing process. PMID:28590456

Dynamic pathway modeling of signal transduction networks: a domain-oriented approach.

PubMed

Conzelmann, Holger; Gilles, Ernst-Dieter

2008-01-01

Mathematical models of biological processes become more and more important in biology. The aim is a holistic understanding of how processes such as cellular communication, cell division, regulation, homeostasis, or adaptation work, how they are regulated, and how they react to perturbations. The great complexity of most of these processes necessitates the generation of mathematical models in order to address these questions. In this chapter we provide an introduction to basic principles of dynamic modeling and highlight both problems and chances of dynamic modeling in biology. The main focus will be on modeling of s transduction pathways, which requires the application of a special modeling approach. A common pattern, especially in eukaryotic signaling systems, is the formation of multi protein signaling complexes. Even for a small number of interacting proteins the number of distinguishable molecular species can be extremely high. This combinatorial complexity is due to the great number of distinct binding domains of many receptors and scaffold proteins involved in signal transduction. However, these problems can be overcome using a new domain-oriented modeling approach, which makes it possible to handle complex and branched signaling pathways.

Working Memory and Hearing Aid Processing: Literature Findings, Future Directions, and Clinical Applications

PubMed Central

Souza, Pamela; Arehart, Kathryn; Neher, Tobias

2015-01-01

Working memory—the ability to process and store information—has been identified as an important aspect of speech perception in difficult listening environments. Working memory can be envisioned as a limited-capacity system which is engaged when an input signal cannot be readily matched to a stored representation or template. This “mismatch” is expected to occur more frequently when the signal is degraded. Because working memory capacity varies among individuals, those with smaller capacity are expected to demonstrate poorer speech understanding when speech is degraded, such as in background noise. However, it is less clear whether (and how) working memory should influence practical decisions, such as hearing treatment. Here, we consider the relationship between working memory capacity and response to specific hearing aid processing strategies. Three types of signal processing are considered, each of which will alter the acoustic signal: fast-acting wide-dynamic range compression, which smooths the amplitude envelope of the input signal; digital noise reduction, which may inadvertently remove speech signal components as it suppresses noise; and frequency compression, which alters the relationship between spectral peaks. For fast-acting wide-dynamic range compression, a growing body of data suggests that individuals with smaller working memory capacity may be more susceptible to such signal alterations, and may receive greater amplification benefit with “low alteration” processing. While the evidence for a relationship between wide-dynamic range compression and working memory appears robust, the effects of working memory on perceptual response to other forms of hearing aid signal processing are less clear cut. We conclude our review with a discussion of the opportunities (and challenges) in translating information on individual working memory into clinical treatment, including clinically feasible measures of working memory. PMID:26733899

Method and system for detecting a failure or performance degradation in a dynamic system such as a flight vehicle

NASA Technical Reports Server (NTRS)

Miller, Robert H. (Inventor); Ribbens, William B. (Inventor)

2003-01-01

A method and system for detecting a failure or performance degradation in a dynamic system having sensors for measuring state variables and providing corresponding output signals in response to one or more system input signals are provided. The method includes calculating estimated gains of a filter and selecting an appropriate linear model for processing the output signals based on the input signals. The step of calculating utilizes one or more models of the dynamic system to obtain estimated signals. The method further includes calculating output error residuals based on the output signals and the estimated signals. The method also includes detecting one or more hypothesized failures or performance degradations of a component or subsystem of the dynamic system based on the error residuals. The step of calculating the estimated values is performed optimally with respect to one or more of: noise, uncertainty of parameters of the models and un-modeled dynamics of the dynamic system which may be a flight vehicle or financial market or modeled financial system.

Social costs enforce honesty of a dynamic signal of motivation.

PubMed

Ligon, Russell A; McGraw, Kevin J

2016-10-26

Understanding the processes that promote signal reliability may provide important insights into the evolution of diverse signalling strategies among species. The signals that animals use to communicate must comprise mechanisms that prohibit or punish dishonesty, and social costs of dishonesty have been demonstrated for several fixed morphological signals (e.g. colour badges of birds and wasps). The costs maintaining the honesty of dynamic signals, which are more flexible and potentially cheatable, are unknown. Using an experimental manipulation of the dynamic visual signals used by male veiled chameleons (Chamaeleo calyptratus) during aggressive interactions, we tested the idea that the honesty of rapid colour change signals is maintained by social costs. Our results reveal that social costs are an important mechanism maintaining the honesty of these dynamic colour signals-'dishonest' chameleons whose experimentally manipulated coloration was incongruent with their contest behaviour received more physical aggression than 'honest' individuals. This is the first demonstration, to the best our knowledge, that the honesty of a dynamic signal of motivation-physiological colour change-can be maintained by the social costliness of dishonesty. Behavioural responses of signal receivers, irrespective of any specific detection mechanisms, therefore prevent chameleon cheaters from prospering. © 2016 The Author(s).

Cellular Decision Making by Non-Integrative Processing of TLR Inputs.

PubMed

Kellogg, Ryan A; Tian, Chengzhe; Etzrodt, Martin; Tay, Savaş

2017-04-04

Cells receive a multitude of signals from the environment, but how they process simultaneous signaling inputs is not well understood. Response to infection, for example, involves parallel activation of multiple Toll-like receptors (TLRs) that converge on the nuclear factor κB (NF-κB) pathway. Although we increasingly understand inflammatory responses for isolated signals, it is not clear how cells process multiple signals that co-occur in physiological settings. We therefore examined a bacterial infection scenario involving co-stimulation of TLR4 and TLR2. Independent stimulation of these receptors induced distinct NF-κB dynamic profiles, although surprisingly, under co-stimulation, single cells continued to show ligand-specific dynamic responses characteristic of TLR2 or TLR4 signaling rather than a mixed response, comprising a cellular decision that we term "non-integrative" processing. Iterating modeling and microfluidic experiments revealed that non-integrative processing occurred through interaction of switch-like NF-κB activation, receptor-specific processing timescales, cell-to-cell variability, and TLR cross-tolerance mediated by multilayer negative feedback. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Social costs enforce honesty of a dynamic signal of motivation

PubMed Central

McGraw, Kevin J.

2016-01-01

Understanding the processes that promote signal reliability may provide important insights into the evolution of diverse signalling strategies among species. The signals that animals use to communicate must comprise mechanisms that prohibit or punish dishonesty, and social costs of dishonesty have been demonstrated for several fixed morphological signals (e.g. colour badges of birds and wasps). The costs maintaining the honesty of dynamic signals, which are more flexible and potentially cheatable, are unknown. Using an experimental manipulation of the dynamic visual signals used by male veiled chameleons (Chamaeleo calyptratus) during aggressive interactions, we tested the idea that the honesty of rapid colour change signals is maintained by social costs. Our results reveal that social costs are an important mechanism maintaining the honesty of these dynamic colour signals—‘dishonest’ chameleons whose experimentally manipulated coloration was incongruent with their contest behaviour received more physical aggression than ‘honest’ individuals. This is the first demonstration, to the best our knowledge, that the honesty of a dynamic signal of motivation—physiological colour change—can be maintained by the social costliness of dishonesty. Behavioural responses of signal receivers, irrespective of any specific detection mechanisms, therefore prevent chameleon cheaters from prospering. PMID:27798310

Welding quality evaluation of resistance spot welding using the time-varying inductive reactance signal

NASA Astrophysics Data System (ADS)

Zhang, Hongjie; Hou, Yanyan; Yang, Tao; Zhang, Qian; Zhao, Jian

2018-05-01

In the spot welding process, a high alternating current is applied, resulting in a time-varying electromagnetic field surrounding the welder. When measuring the welding voltage signal, the impedance of the measuring circuit consists of two parts: dynamic resistance relating to weld nugget nucleation event and inductive reactance caused by mutual inductance. The aim of this study is to develop a method to acquire the dynamic reactance signal and to discuss the possibility of using this signal to evaluate the weld quality. For this purpose, a series of experiments were carried out. The reactance signals under different welding conditions were compared and the results showed that the morphological feature of the reactance signal was closely related to the welding current and it was also significantly influenced by some abnormal welding conditions. Some features were extracted from the reactance signal and combined to construct weld nugget strength and diameter prediction models based on the radial basis function (RBF) neural network. In addition, several features were also used to monitor the expulsion in the welding process by using Fisher linear discriminant analysis. The results indicated that using the dynamic reactance signal to evaluate weld quality is possible and feasible.

MACF1 regulates the migration of pyramidal neurons via microtubule dynamics and GSK-3 signaling

PubMed Central

Ka, Minhan; Jung, Eui-Man; Mueller, Ulrich; Kim, Woo-Yang

2014-01-01

Neuronal migration and subsequent differentiation play critical roles for establishing functional neural circuitry in the developing brain. However, the molecular mechanisms that regulate these processes are poorly understood. Here, we show that microtubule actin crosslinking factor 1 (MACF1) determines neuronal positioning by regulating microtubule dynamics and mediating GSK-3 signaling during brain development. First, using MACF1 floxed allele mice and in utero gene manipulation, we find that MACF1 deletion suppresses migration of cortical pyramidal neurons and results in aberrant neuronal positioning in the developing brain. The cell autonomous deficit in migration is associated with abnormal dynamics of leading processes and centrosomes. Furthermore, microtubule stability is severely damaged in neurons lacking MACF1, resulting in abnormal microtubule dynamics. Finally, MACF1 interacts with and mediates GSK-3 signaling in developing neurons. Our findings establish a cellular mechanism underlying neuronal migration and provide insights into the regulation of cytoskeleton dynamics in developing neurons. PMID:25224226

MACF1 regulates the migration of pyramidal neurons via microtubule dynamics and GSK-3 signaling.

PubMed

Ka, Minhan; Jung, Eui-Man; Mueller, Ulrich; Kim, Woo-Yang

2014-11-01

Neuronal migration and subsequent differentiation play critical roles for establishing functional neural circuitry in the developing brain. However, the molecular mechanisms that regulate these processes are poorly understood. Here, we show that microtubule actin crosslinking factor 1 (MACF1) determines neuronal positioning by regulating microtubule dynamics and mediating GSK-3 signaling during brain development. First, using MACF1 floxed allele mice and in utero gene manipulation, we find that MACF1 deletion suppresses migration of cortical pyramidal neurons and results in aberrant neuronal positioning in the developing brain. The cell autonomous deficit in migration is associated with abnormal dynamics of leading processes and centrosomes. Furthermore, microtubule stability is severely damaged in neurons lacking MACF1, resulting in abnormal microtubule dynamics. Finally, MACF1 interacts with and mediates GSK-3 signaling in developing neurons. Our findings establish a cellular mechanism underlying neuronal migration and provide insights into the regulation of cytoskeleton dynamics in developing neurons. Copyright © 2014 Elsevier Inc. All rights reserved.

Regulation of branching dynamics by axon-intrinsic asymmetries in Tyrosine Kinase Receptor signaling

PubMed Central

Zschätzsch, Marlen; Oliva, Carlos; Langen, Marion; De Geest, Natalie; Özel, Mehmet Neset; Williamson, W Ryan; Lemon, William C; Soldano, Alessia; Munck, Sebastian; Hiesinger, P Robin; Sanchez-Soriano, Natalia; Hassan, Bassem A

2014-01-01

Axonal branching allows a neuron to connect to several targets, increasing neuronal circuit complexity. While axonal branching is well described, the mechanisms that control it remain largely unknown. We find that in the Drosophila CNS branches develop through a process of excessive growth followed by pruning. In vivo high-resolution live imaging of developing brains as well as loss and gain of function experiments show that activation of Epidermal Growth Factor Receptor (EGFR) is necessary for branch dynamics and the final branching pattern. Live imaging also reveals that intrinsic asymmetry in EGFR localization regulates the balance between dynamic and static filopodia. Elimination of signaling asymmetry by either loss or gain of EGFR function results in reduced dynamics leading to excessive branch formation. In summary, we propose that the dynamic process of axon branch development is mediated by differential local distribution of signaling receptors. DOI: http://dx.doi.org/10.7554/eLife.01699.001 PMID:24755286

A dynamic multi-channel speech enhancement system for distributed microphones in a car environment

NASA Astrophysics Data System (ADS)

Matheja, Timo; Buck, Markus; Fingscheidt, Tim

2013-12-01

Supporting multiple active speakers in automotive hands-free or speech dialog applications is an interesting issue not least due to comfort reasons. Therefore, a multi-channel system for enhancement of speech signals captured by distributed distant microphones in a car environment is presented. Each of the potential speakers in the car has a dedicated directional microphone close to his position that captures the corresponding speech signal. The aim of the resulting overall system is twofold: On the one hand, a combination of an arbitrary pre-defined subset of speakers' signals can be performed, e.g., to create an output signal in a hands-free telephone conference call for a far-end communication partner. On the other hand, annoying cross-talk components from interfering sound sources occurring in multiple different mixed output signals are to be eliminated, motivated by the possibility of other hands-free applications being active in parallel. The system includes several signal processing stages. A dedicated signal processing block for interfering speaker cancellation attenuates the cross-talk components of undesired speech. Further signal enhancement comprises the reduction of residual cross-talk and background noise. Subsequently, a dynamic signal combination stage merges the processed single-microphone signals to obtain appropriate mixed signals at the system output that may be passed to applications such as telephony or a speech dialog system. Based on signal power ratios between the particular microphone signals, an appropriate speaker activity detection and therewith a robust control mechanism of the whole system is presented. The proposed system may be dynamically configured and has been evaluated for a car setup with four speakers sitting in the car cabin disturbed in various noise conditions.

Multidimensional biochemical information processing of dynamical patterns

NASA Astrophysics Data System (ADS)

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Multidimensional biochemical information processing of dynamical patterns.

PubMed

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

Obstacle penetrating dynamic radar imaging system

DOEpatents

Romero, Carlos E [Livermore, CA; Zumstein, James E [Livermore, CA; Chang, John T [Danville, CA; Leach, Jr Richard R. [Castro Valley, CA

2006-12-12

An obstacle penetrating dynamic radar imaging system for the detection, tracking, and imaging of an individual, animal, or object comprising a multiplicity of low power ultra wideband radar units that produce a set of return radar signals from the individual, animal, or object, and a processing system for said set of return radar signals for detection, tracking, and imaging of the individual, animal, or object. The system provides a radar video system for detecting and tracking an individual, animal, or object by producing a set of return radar signals from the individual, animal, or object with a multiplicity of low power ultra wideband radar units, and processing said set of return radar signals for detecting and tracking of the individual, animal, or object.

Coactosin accelerates cell dynamism by promoting actin polymerization.

PubMed

Hou, Xubin; Katahira, Tatsuya; Ohashi, Kazumasa; Mizuno, Kensaku; Sugiyama, Sayaka; Nakamura, Harukazu

2013-07-01

During development, cells dynamically move or extend their processes, which are achieved by actin dynamics. In the present study, we paid attention to Coactosin, an actin binding protein, and studied its role in actin dynamics. Coactosin was associated with actin and Capping protein in neural crest cells and N1E-115 neuroblastoma cells. Accumulation of Coactosin to cellular processes and its association with actin filaments prompted us to reveal the effect of Coactosin on cell migration. Coactosin overexpression induced cellular processes in cultured neural crest cells. In contrast, knock-down of Coactosin resulted in disruption of actin polymerization and of neural crest cell migration. Importantly, Coactosin was recruited to lamellipodia and filopodia in response to Rac signaling, and mutated Coactosin that cannot bind to F-actin did not react to Rac signaling, nor support neural crest cell migration. It was also shown that deprivation of Rac signaling from neural crest cells by dominant negative Rac1 (DN-Rac1) interfered with neural crest cell migration, and that co-transfection of DN-Rac1 and Coactosin restored neural crest cell migration. From these results we have concluded that Coactosin functions downstream of Rac signaling and that it is involved in neurite extension and neural crest cell migration by actively participating in actin polymerization. Copyright © 2013 Elsevier Inc. All rights reserved.

Dynamic single sideband modulation for realizing parametric loudspeaker

NASA Astrophysics Data System (ADS)

Sakai, Shinichi; Kamakura, Tomoo

2008-06-01

A parametric loudspeaker, that presents remarkably narrow directivity compared with a conventional loudspeaker, is newly produced and examined. To work the loudspeaker optimally, we prototyped digitally a single sideband modulator based on the Weaver method and appropriate signal processing. The processing techniques are to change the carrier amplitude dynamically depending on the envelope of audio signals, and then to operate the square root or fourth root to the carrier amplitude for improving input-output acoustic linearity. The usefulness of the present modulation scheme has been verified experimentally.

A Simple Microscopy Assay to Teach the Processes of Phagocytosis and Exocytosis

ERIC Educational Resources Information Center

Gray, Ross; Gray, Andrew; Fite, Jessica L.; Jordan, Renee; Stark, Sarah; Naylor, Kari

2012-01-01

Phagocytosis and exocytosis are two cellular processes involving membrane dynamics. While it is easy to understand the purpose of these processes, it can be extremely difficult for students to comprehend the actual mechanisms. As membrane dynamics play a significant role in many cellular processes ranging from cell signaling to cell division to…

Isospin equilibration processes and dipolar signals: Coherent cluster production

NASA Astrophysics Data System (ADS)

Papa, M.; Berceanu, I.; Acosta, L.; Agodi, C.; Auditore, L.; Cardella, G.; Chatterjee, M. B.; Dell'Aquila, D.; De Filippo, E.; Francalanza, L.; Lanzalone, G.; Lombardo, I.; Maiolino, C.; Martorana, N.; Pagano, A.; Pagano, E. V.; Pirrone, S.; Politi, G.; Quattrocchi, L.; Rizzo, F.; Russotto, P.; Trifiró, A.; Trimarchi, M.; Verde, G.; Vigilante, M.

2017-11-01

The total dipolar signal related to multi-break-up processes induced on the system ^{48}Ca +{^{27}Al} at 40MeV/nucleon has been investigated with the CHIMERA multi-detector. Experimental data related to semi-peripheral collisions are shown and compared with CoMD-III calculations. The strong connection between the dipolar signal as obtained from the detected fragments and the dynamics of the isospin equilibration processes is also shortly discussed.

An ultrasonic flowmeter for measuring dynamic liquid flow

NASA Technical Reports Server (NTRS)

Carpini, T. D.; Monteith, J. H.

1978-01-01

A novel oscillating pipe system was developed to provide dynamic calibration wherein small sinusoidal signals with amplitudes of 0.5 to 10% of the steady-state flow were added to the steady-state flow by oscillating the flowmeter relative to the fixed pipes in the flow system. Excellent agreement was obtained between the dynamic velocities derived from an accelerometer mounted on the oscillating pipe system and those sensed by the flowmeter at frequencies of 7, 19, and 30 Hz. Also described were the signal processing techniques used to retrieve the small sinusoidal signals which were obscured by the fluid turbulence.

Dynamic and diverse sugar signaling

PubMed Central

Li, Lei; Sheen, Jen

2016-01-01

Sugars fuel life and exert numerous regulatory actions that are fundamental to all life forms. There are two principal mechanisms underlie sugar “perception and signal transduction” in biological systems. Direct sensing and signaling is triggered via sugar-binding sensors with a broad range of affinity and specificity, whereas sugar-derived bioenergetic molecules and metabolites modulate signaling proteins and indirectly relay sugar signals. This review discusses the emerging sugar signals and potential sugar sensors discovered in plant systems. The findings leading to informative understanding of physiological regulation by sugars are considered and assessed. Comparative transcriptome analyses highlight the primary and dynamic sugar responses and reveal the convergent and specific regulators of key biological processes in the sugar-signaling network. PMID:27423125

Dynamic Spectral Structure Specifies Vowels for Adults and Children

PubMed Central

Nittrouer, Susan; Lowenstein, Joanna H.

2014-01-01

The dynamic specification account of vowel recognition suggests that formant movement between vowel targets and consonant margins is used by listeners to recognize vowels. This study tested that account by measuring contributions to vowel recognition of dynamic (i.e., time-varying) spectral structure and coarticulatory effects on stationary structure. Adults and children (four-and seven-year-olds) were tested with three kinds of consonant-vowel-consonant syllables: (1) unprocessed; (2) sine waves that preserved both stationary coarticulated and dynamic spectral structure; and (3) vocoded signals that primarily preserved that stationary, but not dynamic structure. Sections of two lengths were removed from syllable middles: (1) half the vocalic portion; and (2) all but the first and last three pitch periods. Adults performed accurately with unprocessed and sine-wave signals, as long as half the syllable remained; their recognition was poorer for vocoded signals, but above chance. Seven-year-olds performed more poorly than adults with both sorts of processed signals, but disproportionately worse with vocoded than sine-wave signals. Most four-year-olds were unable to recognize vowels at all with vocoded signals. Conclusions were that both dynamic and stationary coarticulated structures support vowel recognition for adults, but children attend to dynamic spectral structure more strongly because early phonological organization favors whole words. PMID:25536845

Acousto-optic RF signal acquisition system

NASA Astrophysics Data System (ADS)

Bloxham, Laurence H.

1990-09-01

This paper describes the architecture and performance of a prototype Acousto-Optic RF Signal Acquisition System designed to intercept, automatically identify, and track communication signals in the VHF band. The system covers 28.0 to 92.0 MHz with five manually selectable, dual conversion; 12.8 MHZ bandwidth front ends. An acousto-optic spectrum analyzer (AOSA) implemented using a tellurium dioxide (Te02) Bragg cell is used to channelize the 12.8 MHz pass band into 512 25 KHz channels. Polarization switching is used to suppress optical noise. Excellent isolation and dynamic range are achieved by using a linear array of 512 custom 40/50 micron fiber optic cables to collect the light at the focal plane of the AOSA and route the light to individual photodetectors. The photodetectors are operated in the photovoltaic mode to compress the greater than 60 dB input optical dynamic range into an easily processed electrical signal. The 512 signals are multiplexed and processed as a line in a video image by a customized digital image processing system. The image processor simultaneously analyzes the channelized signal data and produces a classical waterfall display.

Dynamic tracking down-conversion signal processing method based on reference signal for grating heterodyne interferometer

NASA Astrophysics Data System (ADS)

Wang, Guochao; Yan, Shuhua; Zhou, Weihong; Gu, Chenhui

2012-08-01

Traditional displacement measurement systems by grating, which purely make use of fringe intensity to implement fringe count and subdivision, have rigid demands for signal quality and measurement condition, so they are not easy to realize measurement with nanometer precision. Displacement measurement with the dual-wavelength and single-grating design takes advantage of the single grating diffraction theory and the heterodyne interference theory, solving quite well the contradiction between large range and high precision in grating displacement measurement. To obtain nanometer resolution and nanometer precision, high-power subdivision of interference fringes must be realized accurately. A dynamic tracking down-conversion signal processing method based on the reference signal is proposed. Accordingly, a digital phase measurement module to realize high-power subdivision on field programmable gate array (FPGA) was designed, as well as a dynamic tracking down-conversion module using phase-locked loop (PLL). Experiments validated that a carrier signal after down-conversion can constantly maintain close to 100 kHz, and the phase-measurement resolution and phase precision are more than 0.05 and 0.2 deg, respectively. The displacement resolution and the displacement precision, corresponding to the phase results, are 0.139 and 0.556 nm, respectively.

Signal Processing Methods for Liquid Rocket Engine Combustion Stability Assessments

NASA Technical Reports Server (NTRS)

Kenny, R. Jeremy; Lee, Erik; Hulka, James R.; Casiano, Matthew

2011-01-01

The J2X Gas Generator engine design specifications include dynamic, spontaneous, and broadband combustion stability requirements. These requirements are verified empirically based high frequency chamber pressure measurements and analyses. Dynamic stability is determined with the dynamic pressure response due to an artificial perturbation of the combustion chamber pressure (bomb testing), and spontaneous and broadband stability are determined from the dynamic pressure responses during steady operation starting at specified power levels. J2X Workhorse Gas Generator testing included bomb tests with multiple hardware configurations and operating conditions, including a configuration used explicitly for engine verification test series. This work covers signal processing techniques developed at Marshall Space Flight Center (MSFC) to help assess engine design stability requirements. Dynamic stability assessments were performed following both the CPIA 655 guidelines and a MSFC in-house developed statistical-based approach. The statistical approach was developed to better verify when the dynamic pressure amplitudes corresponding to a particular frequency returned back to pre-bomb characteristics. This was accomplished by first determining the statistical characteristics of the pre-bomb dynamic levels. The pre-bomb statistical characterization provided 95% coverage bounds; these bounds were used as a quantitative measure to determine when the post-bomb signal returned to pre-bomb conditions. The time for post-bomb levels to acceptably return to pre-bomb levels was compared to the dominant frequency-dependent time recommended by CPIA 655. Results for multiple test configurations, including stable and unstable configurations, were reviewed. Spontaneous stability was assessed using two processes: 1) characterization of the ratio of the peak response amplitudes to the excited chamber acoustic mode amplitudes and 2) characterization of the variability of the peak response's frequency over the test duration. This characterization process assists in evaluating the discreteness of a signal as well as the stability of the chamber response. Broadband stability was assessed using a running root-mean-square evaluation. These techniques were also employed, in a comparative analysis, on available Fastrac data, and these results are presented here.

Self-Organization Processes at the Intracellular Level

NASA Astrophysics Data System (ADS)

Ponce Dawson, Silvina

2003-03-01

In spite of their relatively small sizes, cells are incredibly complex objects in which various sorts of self-organizing processes occur. Cell division is an example of a process that nearly all cells undergo in which a concerted sequence of events takes place. What are the signals that tell the cell to move along this sequence? Clearly, this is a self-organized process. Microtubules (long polymers that are part of the cytoskeleton) and calcium signals play a major role during cell division. In this course we will focus on some features of microtubule dynamics and calcium signals that are amenable to modeling. In both of these biological systems, behaviors at a single molecule level are key determinants of the self-organized dynamics that is observed at larger scales. Thus, the modeling of these systems presents interesting challenges which require novel strategies. Their study may not only provide answers for biologically motivated questions, but is also a natural setting in which the transition between particle-like and mean-field models can be explored. In this course we will first give a brief biological introduction on the structure of eukaryotic cells, microtubule dynamics and intracellular calcium signals. We will then describe some of the models that have been presented in the literature and discuss the spatio-temporal dynamics that they predict, comparing them with observed behaviors in vitro or in vivo. We will end with a discussion on the virtues and limitations of the various modeling strategies described.

[Real-time detection and processing of medical signals under windows using Lcard analog interfaces].

PubMed

Kuz'min, A A; Belozerov, A E; Pronin, T V

2008-01-01

Multipurpose modular software for an analog interface based on Lcard 761 is considered. Algorithms for pipeline processing of medical signals under Windows with dynamic control of computational resources are suggested. The software consists of user-friendly completable modifiable modules. The module hierarchy is based on object-oriented heritage principles, which make it possible to construct various real-time systems for long-term detection, processing, and imaging of multichannel medical signals.

Processing oscillatory signals by incoherent feedforward loops

NASA Astrophysics Data System (ADS)

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).

Processing Oscillatory Signals by Incoherent Feedforward Loops

PubMed Central

Zhang, Carolyn; You, Lingchong

2016-01-01

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 the 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 exhibit temporal adaptation, where the system is desensitized to a sustained input. This property serves as the foundation for distinguishing input 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 the IFFL components dictate the input range for which the network is able to decode pulsatile dynamics. In addition, a match between the network parameters and input signal characteristics is required for optimal “counting”. We elucidate one potential mechanism by which information processing occurs in natural networks, and our work has implications in the design of synthetic gene circuits for this purpose. PMID:27623175

Sequential pattern formation governed by signaling gradients

NASA Astrophysics Data System (ADS)

Jörg, David J.; Oates, Andrew C.; Jülicher, Frank

2016-10-01

Rhythmic and sequential segmentation of the embryonic body plan is a vital developmental patterning process in all vertebrate species. However, a theoretical framework capturing the emergence of dynamic patterns of gene expression from the interplay of cell oscillations with tissue elongation and shortening and with signaling gradients, is still missing. Here we show that a set of coupled genetic oscillators in an elongating tissue that is regulated by diffusing and advected signaling molecules can account for segmentation as a self-organized patterning process. This system can form a finite number of segments and the dynamics of segmentation and the total number of segments formed depend strongly on kinetic parameters describing tissue elongation and signaling molecules. The model accounts for existing experimental perturbations to signaling gradients, and makes testable predictions about novel perturbations. The variety of different patterns formed in our model can account for the variability of segmentation between different animal species.

Förster resonance energy transfer as a tool to study photoreceptor biology

PubMed Central

Hovan, Stephanie C.; Howell, Scott; Park, Paul S.-H.

2010-01-01

Vision is initiated in photoreceptor cells of the retina by a set of biochemical events called phototransduction. These events occur via coordinated dynamic processes that include changes in secondary messenger concentrations, conformational changes and post-translational modifications of signaling proteins, and protein-protein interactions between signaling partners. A complete description of the orchestration of these dynamic processes is still unavailable. Described in this work is the first step in the development of tools combining fluorescent protein technology, Förster resonance energy transfer (FRET), and transgenic animals that have the potential to reveal important molecular insights about the dynamic processes occurring in photoreceptor cells. We characterize the fluorescent proteins SCFP3A and SYFP2 for use as a donor-acceptor pair in FRET assays, which will facilitate the visualization of dynamic processes in living cells. We also demonstrate the targeted expression of these fluorescent proteins to the rod photoreceptor cells of Xenopus laevis, and describe a general method for detecting FRET in these cells. The general approaches described here can address numerous types of questions related to phototransduction and photoreceptor biology by providing a platform to visualize dynamic processes in molecular detail within a native context. PMID:21198205

Inverting dynamic force microscopy: From signals to time-resolved interaction forces

PubMed Central

Stark, Martin; Stark, Robert W.; Heckl, Wolfgang M.; Guckenberger, Reinhard

2002-01-01

Transient forces between nanoscale objects on surfaces govern friction, viscous flow, and plastic deformation, occur during manipulation of matter, or mediate the local wetting behavior of thin films. To resolve transient forces on the (sub) microsecond time and nanometer length scale, dynamic atomic force microscopy (AFM) offers largely unexploited potential. Full spectral analysis of the AFM signal completes dynamic AFM. Inverting the signal formation process, we measure the time course of the force effective at the sensing tip. This approach yields rich insight into processes at the tip and dispenses with a priori assumptions about the interaction, as it relies solely on measured data. Force measurements on silicon under ambient conditions demonstrate the distinct signature of the interaction and reveal that peak forces exceeding 200 nN are applied to the sample in a typical imaging situation. These forces are 2 orders of magnitude higher than those in covalent bonds. PMID:12070341

Image-plane processing of visual information

NASA Technical Reports Server (NTRS)

Huck, F. O.; Fales, C. L.; Park, S. K.; Samms, R. W.

1984-01-01

Shannon's theory of information is used to optimize the optical design of sensor-array imaging systems which use neighborhood image-plane signal processing for enhancing edges and compressing dynamic range during image formation. The resultant edge-enhancement, or band-pass-filter, response is found to be very similar to that of human vision. Comparisons of traits in human vision with results from information theory suggest that: (1) Image-plane processing, like preprocessing in human vision, can improve visual information acquisition for pattern recognition when resolving power, sensitivity, and dynamic range are constrained. Improvements include reduced sensitivity to changes in lighter levels, reduced signal dynamic range, reduced data transmission and processing, and reduced aliasing and photosensor noise degradation. (2) Information content can be an appropriate figure of merit for optimizing the optical design of imaging systems when visual information is acquired for pattern recognition. The design trade-offs involve spatial response, sensitivity, and sampling interval.

Preliminary development of digital signal processing in microwave radiometers

NASA Technical Reports Server (NTRS)

Stanley, W. D.

1980-01-01

Topics covered involve a number of closely related tasks including: the development of several control loop and dynamic noise model computer programs for simulating microwave radiometer measurements; computer modeling of an existing stepped frequency radiometer in an effort to determine its optimum operational characteristics; investigation of the classical second order analog control loop to determine its ability to reduce the estimation error in a microwave radiometer; investigation of several digital signal processing unit designs; initiation of efforts to develop required hardware and software for implementation of the digital signal processing unit; and investigation of the general characteristics and peculiarities of digital processing noiselike microwave radiometer signals.

Modeling of Receptor Tyrosine Kinase Signaling: Computational and Experimental Protocols.

PubMed

Fey, Dirk; Aksamitiene, Edita; Kiyatkin, Anatoly; Kholodenko, Boris N

2017-01-01

The advent of systems biology has convincingly demonstrated that the integration of experiments and dynamic modelling is a powerful approach to understand the cellular network biology. Here we present experimental and computational protocols that are necessary for applying this integrative approach to the quantitative studies of receptor tyrosine kinase (RTK) signaling networks. Signaling by RTKs controls multiple cellular processes, including the regulation of cell survival, motility, proliferation, differentiation, glucose metabolism, and apoptosis. We describe methods of model building and training on experimentally obtained quantitative datasets, as well as experimental methods of obtaining quantitative dose-response and temporal dependencies of protein phosphorylation and activities. The presented methods make possible (1) both the fine-grained modeling of complex signaling dynamics and identification of salient, course-grained network structures (such as feedback loops) that bring about intricate dynamics, and (2) experimental validation of dynamic models.

Dynamical states, possibilities and propagation of stress signal

PubMed Central

Malik, Md. Zubbair; Ali, Shahnawaz; Singh, Soibam Shyamchand; Ishrat, Romana; Singh, R. K. Brojen

2017-01-01

The stress driven dynamics of Notch-Wnt-p53 cross-talk is subjected to a few possible dynamical states governed by simple fractal rules, and allowed to decide its own fate by choosing one of these states which are contributed from long range correlation with varied fluctuations due to active molecular interaction. The topological properties of the networks corresponding to these dynamical states have hierarchical features with assortive structure. The stress signal driven by nutlin and modulated by mediator GSK3 acts as anti-apoptotic signal in this system, whereas, the stress signal driven by Axin and modulated by GSK3 behaves as anti-apoptotic for a certain range of Axin and GSK3 interaction, and beyond which the signal acts as favor-apoptotic signal. However, this stress system prefers to stay in an active dynamical state whose counterpart complex network is closest to hierarchical topology with exhibited roles of few interacting hubs. During the propagation of stress signal, the system allows the propagator pathway to inherit all possible properties of the state to the receiver pathway/pathways with slight modifications, indicating efficient information processing and democratic sharing of responsibilities in the system via cross-talk. The increase in the number of cross-talk pathways in the system favors to establish self-organization. PMID:28106087

Dynamical states, possibilities and propagation of stress signal.

PubMed

Malik, Md Zubbair; Ali, Shahnawaz; Singh, Soibam Shyamchand; Ishrat, Romana; Singh, R K Brojen

2017-01-20

The stress driven dynamics of Notch-Wnt-p53 cross-talk is subjected to a few possible dynamical states governed by simple fractal rules, and allowed to decide its own fate by choosing one of these states which are contributed from long range correlation with varied fluctuations due to active molecular interaction. The topological properties of the networks corresponding to these dynamical states have hierarchical features with assortive structure. The stress signal driven by nutlin and modulated by mediator GSK3 acts as anti-apoptotic signal in this system, whereas, the stress signal driven by Axin and modulated by GSK3 behaves as anti-apoptotic for a certain range of Axin and GSK3 interaction, and beyond which the signal acts as favor-apoptotic signal. However, this stress system prefers to stay in an active dynamical state whose counterpart complex network is closest to hierarchical topology with exhibited roles of few interacting hubs. During the propagation of stress signal, the system allows the propagator pathway to inherit all possible properties of the state to the receiver pathway/pathways with slight modifications, indicating efficient information processing and democratic sharing of responsibilities in the system via cross-talk. The increase in the number of cross-talk pathways in the system favors to establish self-organization.

Comparison of angular dependence of magnetic Barkhausen noise of hysteresis and initial magnetization curve in API5L steel

NASA Astrophysics Data System (ADS)

Chávez-Gonzalez, A. F.; Martínez-Ortiz, P.; Pérez-Benítez, J. A.; Espina-Hernández, J. H.; Caleyo, F.

2018-01-01

This work analyzes the differences between the magnetic Barkhausen noise corresponding to the initial magnetization curve and Barkhausen noise corresponding to one branch of the hysteresis loop in API-5L steel. The outcomes show that the Barkhausen noise signal corresponding to the initial magnetization curve and that corresponding to the hysteresis are significantly different. This difference is due to the presence of different processes of the domain wall dynamics in both phenomena. To study the processes present in magnetization dynamics for an applied field of H > 0, research into the angular dependence of a Barkhausen signal using applied field bands has revealed that a Barkhausen signal corresponding to the initial magnetization curve is more suitable than a Barkhausen signal corresponding to the hysteresis loop.

Dynamics and control of the ERK signaling pathway: Sensitivity, bistability, and oscillations.

PubMed

Arkun, Yaman; Yasemi, Mohammadreza

2018-01-01

Cell signaling is the process by which extracellular information is transmitted into the cell to perform useful biological functions. The ERK (extracellular-signal-regulated kinase) signaling controls several cellular processes such as cell growth, proliferation, differentiation and apoptosis. The ERK signaling pathway considered in this work starts with an extracellular stimulus and ends with activated (double phosphorylated) ERK which gets translocated into the nucleus. We model and analyze this complex pathway by decomposing it into three functional subsystems. The first subsystem spans the initial part of the pathway from the extracellular growth factor to the formation of the SOS complex, ShC-Grb2-SOS. The second subsystem includes the activation of Ras which is mediated by the SOS complex. This is followed by the MAPK subsystem (or the Raf-MEK-ERK pathway) which produces the double phosphorylated ERK upon being activated by Ras. Although separate models exist in the literature at the subsystems level, a comprehensive model for the complete system including the important regulatory feedback loops is missing. Our dynamic model combines the existing subsystem models and studies their steady-state and dynamic interactions under feedback. We establish conditions under which bistability and oscillations exist for this important pathway. In particular, we show how the negative and positive feedback loops affect the dynamic characteristics that determine the cellular outcome.

Evaluation of interaction dynamics of concurrent processes

NASA Astrophysics Data System (ADS)

Sobecki, Piotr; Białasiewicz, Jan T.; Gross, Nicholas

2017-03-01

The purpose of this paper is to present the wavelet tools that enable the detection of temporal interactions of concurrent processes. In particular, the determination of interaction coherence of time-varying signals is achieved using a complex continuous wavelet transform. This paper has used electrocardiogram (ECG) and seismocardiogram (SCG) data set to show multiple continuous wavelet analysis techniques based on Morlet wavelet transform. MATLAB Graphical User Interface (GUI), developed in the reported research to assist in quick and simple data analysis, is presented. These software tools can discover the interaction dynamics of time-varying signals, hence they can reveal their correlation in phase and amplitude, as well as their non-linear interconnections. The user-friendly MATLAB GUI enables effective use of the developed software what enables to load two processes under investigation, make choice of the required processing parameters, and then perform the analysis. The software developed is a useful tool for researchers who have a need for investigation of interaction dynamics of concurrent processes.

Quantitative analysis of phosphoinositide 3-kinase (PI3K) signaling using live-cell total internal reflection fluorescence (TIRF) microscopy.

PubMed

Johnson, Heath E; Haugh, Jason M

2013-12-02

This unit focuses on the use of total internal reflection fluorescence (TIRF) microscopy and image analysis methods to study the dynamics of signal transduction mediated by class I phosphoinositide 3-kinases (PI3Ks) in mammalian cells. The first four protocols cover live-cell imaging experiments, image acquisition parameters, and basic image processing and segmentation. These methods are generally applicable to live-cell TIRF experiments. The remaining protocols outline more advanced image analysis methods, which were developed in our laboratory for the purpose of characterizing the spatiotemporal dynamics of PI3K signaling. These methods may be extended to analyze other cellular processes monitored using fluorescent biosensors. Copyright © 2013 John Wiley & Sons, Inc.

Imaging of dynamic ion signaling during root gravitropism.

PubMed

Monshausen, Gabriele B

2015-01-01

Gravitropic signaling is a complex process that requires the coordinated action of multiple cell types and tissues. Ca(2+) and pH signaling are key components of gravitropic signaling cascades and can serve as useful markers to dissect the molecular machinery mediating plant gravitropism. To monitor dynamic ion signaling, imaging approaches combining fluorescent ion sensors and confocal fluorescence microscopy are employed, which allow the visualization of pH and Ca(2+) changes at the level of entire tissues, while also providing high spatiotemporal resolution. Here, I describe procedures to prepare Arabidopsis seedlings for live cell imaging and to convert a microscope for vertical stage fluorescence microscopy. With this imaging system, ion signaling can be monitored during all phases of the root gravitropic response.

High-performance wavelet engine

NASA Astrophysics Data System (ADS)

Taylor, Fred J.; Mellot, Jonathon D.; Strom, Erik; Koren, Iztok; Lewis, Michael P.

1993-11-01

Wavelet processing has shown great promise for a variety of image and signal processing applications. Wavelets are also among the most computationally expensive techniques in signal processing. It is demonstrated that a wavelet engine constructed with residue number system arithmetic elements offers significant advantages over commercially available wavelet accelerators based upon conventional arithmetic elements. Analysis is presented predicting the dynamic range requirements of the reported residue number system based wavelet accelerator.

Signal detection via residence-time asymmetry in noisy bistable devices.

PubMed

Bulsara, A R; Seberino, C; Gammaitoni, L; Karlsson, M F; Lundqvist, B; Robinson, J W C

2003-01-01

We introduce a dynamical readout description for a wide class of nonlinear dynamic sensors operating in a noisy environment. The presence of weak unknown signals is assessed via the monitoring of the residence time in the metastable attractors of the system, in the presence of a known, usually time-periodic, bias signal. This operational scenario can mitigate the effects of sensor noise, providing a greatly simplified readout scheme, as well as significantly reduced processing procedures. Such devices can also show a wide variety of interesting dynamical features. This scheme for quantifying the response of a nonlinear dynamic device has been implemented in experiments involving a simple laboratory version of a fluxgate magnetometer. We present the results of the experiments and demonstrate that they match the theoretical predictions reasonably well.

Singular spectrum and singular entropy used in signal processing of NC table

NASA Astrophysics Data System (ADS)

Wang, Linhong; He, Yiwen

2011-12-01

NC (numerical control) table is a complex dynamic system. The dynamic characteristics caused by backlash, friction and elastic deformation among each component are so complex that they have become the bottleneck of enhancing the positioning accuracy, tracking accuracy and dynamic behavior of NC table. This paper collects vibration acceleration signals from NC table, analyzes the signals with SVD (singular value decomposition) method, acquires the singular spectrum and calculates the singular entropy of the signals. The signal characteristics and their regulations of NC table are revealed via the characteristic quantities such as singular spectrum, singular entropy etc. The steep degrees of singular spectrums can be used to discriminate complex degrees of signals. The results show that the signals in direction of driving axes are the simplest and the signals in perpendicular direction are the most complex. The singular entropy values can be used to study the indetermination of signals. The results show that the signals of NC table are not simple signal nor white noise, the entropy values in direction of driving axe are lower, the entropy values increase along with the increment of driving speed and the entropy values at the abnormal working conditions such as resonance or creeping etc decrease obviously.

Fractal dimension and nonlinear dynamical processes

NASA Astrophysics Data System (ADS)

McCarty, Robert C.; Lindley, John P.

1993-11-01

Mandelbrot, Falconer and others have demonstrated the existence of dimensionally invariant geometrical properties of non-linear dynamical processes known as fractals. Barnsley defines fractal geometry as an extension of classical geometry. Such an extension, however, is not mathematically trivial Of specific interest to those engaged in signal processing is the potential use of fractal geometry to facilitate the analysis of non-linear signal processes often referred to as non-linear time series. Fractal geometry has been used in the modeling of non- linear time series represented by radar signals in the presence of ground clutter or interference generated by spatially distributed reflections around the target or a radar system. It was recognized by Mandelbrot that the fractal geometries represented by man-made objects had different dimensions than the geometries of the familiar objects that abound in nature such as leaves, clouds, ferns, trees, etc. The invariant dimensional property of non-linear processes suggests that in the case of acoustic signals (active or passive) generated within a dispersive medium such as the ocean environment, there exists much rich structure that will aid in the detection and classification of various objects, man-made or natural, within the medium.

Radar echo processing with partitioned de-ramp

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dubbert, Dale F.; Tise, Bertice L.

2013-03-19

The spurious-free dynamic range of a wideband radar system is increased by apportioning de-ramp processing across analog and digital processing domains. A chirp rate offset is applied between the received waveform and the reference waveform that is used for downconversion to the intermediate frequency (IF) range. The chirp rate offset results in a residual chirp in the IF signal prior to digitization. After digitization, the residual IF chirp is removed with digital signal processing.

[Situational awareness: you won't see it unless you understand it].

PubMed

Graafland, Maurits; Schijven, Marlies P

2015-01-01

In dynamic, high-risk environments such as the modern operating theatre, healthcare providers are required to identify a multitude of signals correctly and in time. Errors resulting from failure to identify or interpret signals correctly lead to calamities. Medical training curricula focus largely on teaching technical skills and knowledge, not on the cognitive skills needed to interact appropriately with fast-changing, complex environments in practice. The term 'situational awareness' describes the dynamic process of receiving, interpreting and processing information in such dynamic environments. Improving situational awareness in high-risk environments should be part of medical curricula. In addition, the flood of information in high-risk environments should be presented more clearly and effectively. It is important that physicians become more involved in this regard.

Grey signal processing and data reconstruction in the non-diffracting beam triangulation measurement system

NASA Astrophysics Data System (ADS)

Meng, Hao; Wang, Zhongyu; Fu, Jihua

2008-12-01

The non-diffracting beam triangulation measurement system possesses the advantages of longer measurement range, higher theoretical measurement accuracy and higher resolution over the traditional laser triangulation measurement system. Unfortunately the measurement accuracy of the system is greatly degraded due to the speckle noise, the CCD photoelectric noise and the background light noise in practical applications. Hence, some effective signal processing methods must be applied to improve the measurement accuracy. In this paper a novel effective method for removing the noises in the non-diffracting beam triangulation measurement system is proposed. In the method the grey system theory is used to process and reconstruct the measurement signal. Through implementing the grey dynamic filtering based on the dynamic GM(1,1), the noises can be effectively removed from the primary measurement data and the measurement accuracy of the system can be improved as a result.

Weak temporal signals can synchronize and accelerate the transition dynamics of biopolymers under tension.

PubMed

Kim, Won Kyu; Hyeon, Changbong; Sung, Wokyung

2012-09-04

In addition to thermal noise, which is essential to promote conformational transitions in biopolymers, the cellular environment is replete with a spectrum of athermal fluctuations that are produced from a plethora of active processes. To understand the effect of athermal noise on biological processes, we studied how a small oscillatory force affects the thermally induced folding and unfolding transition of an RNA hairpin, whose response to constant tension had been investigated extensively in both theory and experiments. Strikingly, our molecular simulations performed under overdamped condition show that even at a high (low) tension that renders the hairpin (un)folding improbable, a weak external oscillatory force at a certain frequency can synchronously enhance the transition dynamics of RNA hairpin and increase the mean transition rate. Furthermore, the RNA dynamics can still discriminate a signal with resonance frequency even when the signal is mixed among other signals with nonresonant frequencies. In fact, our computational demonstration of thermally induced resonance in RNA hairpin dynamics is a direct realization of the phenomena called stochastic resonance and resonant activation. Our study, amenable to experimental tests using optical tweezers, is of great significance to the folding of biopolymers in vivo that are subject to the broad spectrum of cellular noises.

47 CFR 73.756 - System specifications for double-sideband (DBS) modulated emissions in the HF broadcasting service.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 4 2010-10-01 2010-10-01 false System specifications for double-sideband (DBS... Stations § 73.756 System specifications for double-sideband (DBS) modulated emissions in the HF... processing. If audio-frequency signal processing is used, the dynamic range of the modulating signal shall be...

47 CFR 73.757 - System specifications for single-sideband (SSB) modulated emissions in the HF broadcasting service.

Code of Federal Regulations, 2011 CFR

2011-10-01

... dB per octave. (4) Modulation processing. If audio-frequency signal processing is used, the dynamic... broadcasting service. (a) System parameters—(1) Channel spacing. In a mixed DSB, SSB and digital environment... emission is one giving the same audio-frequency signal-to-noise ratio at the receiver output as the...

A lateral signalling pathway coordinates shape volatility during cell migration

PubMed Central

Zhang, Liang; Luga, Valbona; Armitage, Sarah K.; Musiol, Martin; Won, Amy; Yip, Christopher M.; Plotnikov, Sergey V.; Wrana, Jeffrey L.

2016-01-01

Cell migration is fundamental for both physiological and pathological processes. Migrating cells usually display high dynamics in morphology, which is orchestrated by an integrative array of signalling pathways. Here we identify a novel pathway, we term lateral signalling, comprised of the planar cell polarity (PCP) protein Pk1 and the RhoGAPs, Arhgap21/23. We show that the Pk1–Arhgap21/23 complex inhibits RhoA, is localized on the non-protrusive lateral membrane cortex and its disruption leads to the disorganization of the actomyosin network and altered focal adhesion dynamics. Pk1-mediated lateral signalling confines protrusive activity and is regulated by Smurf2, an E3 ubiquitin ligase in the PCP pathway. Furthermore, we demonstrate that dynamic interplay between lateral and protrusive signalling generates cyclical fluctuations in cell shape that we quantify here as shape volatility, which strongly correlates with migration speed. These studies uncover a previously unrecognized lateral signalling pathway that coordinates shape volatility during productive cell migration. PMID:27226243

Signal processing: opportunities for superconductive circuits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ralston, R.W.

1985-03-01

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 examplesmore » of superconductive implementations given. A canonic signal-processing system is then configured using these components and digital output circuits to highlight the important issues of dynamic range, accuracy and equivalent computation rate. (Reprints)« less

Dynamics Govern Specificity of a Protein-Protein Interface: Substrate Recognition by Thrombin.

PubMed

Fuchs, Julian E; Huber, Roland G; Waldner, Birgit J; Kahler, Ursula; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R

2015-01-01

Biomolecular recognition is crucial in cellular signal transduction. Signaling is mediated through molecular interactions at protein-protein interfaces. Still, specificity and promiscuity of protein-protein interfaces cannot be explained using simplistic static binding models. Our study rationalizes specificity of the prototypic protein-protein interface between thrombin and its peptide substrates relying solely on binding site dynamics derived from molecular dynamics simulations. We find conformational selection and thus dynamic contributions to be a key player in biomolecular recognition. Arising entropic contributions complement chemical intuition primarily reflecting enthalpic interaction patterns. The paradigm "dynamics govern specificity" might provide direct guidance for the identification of specific anchor points in biomolecular recognition processes and structure-based drug design.

Discovery of Intramolecular Signal Transduction Network Based on a New Protein Dynamics Model of Energy Dissipation

PubMed Central

Ma, Cheng-Wei; Xiu, Zhi-Long; Zeng, An-Ping

2012-01-01

A novel approach to reveal intramolecular signal transduction network is proposed in this work. To this end, a new algorithm of network construction is developed, which is based on a new protein dynamics model of energy dissipation. A key feature of this approach is that direction information is specified after inferring protein residue-residue interaction network involved in the process of signal transduction. This enables fundamental analysis of the regulation hierarchy and identification of regulation hubs of the signaling network. A well-studied allosteric enzyme, E. coli aspartokinase III, is used as a model system to demonstrate the new method. Comparison with experimental results shows that the new approach is able to predict all the sites that have been experimentally proved to desensitize allosteric regulation of the enzyme. In addition, the signal transduction network shows a clear preference for specific structural regions, secondary structural types and residue conservation. Occurrence of super-hubs in the network indicates that allosteric regulation tends to gather residues with high connection ability to collectively facilitate the signaling process. Furthermore, a new parameter of propagation coefficient is defined to determine the propagation capability of residues within a signal transduction network. In conclusion, the new approach is useful for fundamental understanding of the process of intramolecular signal transduction and thus has significant impact on rational design of novel allosteric proteins. PMID:22363664

Visualization of Plasticity in Fear-Evoked Calcium Signals in Midbrain Dopamine Neurons

ERIC Educational Resources Information Center

Gore, Bryan B.; Soden, Marta E.; Zweifel, Larry S.

2014-01-01

Dopamine is broadly implicated in fear-related processes, yet we know very little about signaling dynamics in these neurons during active fear conditioning. We describe the direct imaging of calcium signals of dopamine neurons during Pavlovian fear conditioning using fiber-optic confocal microscopy coupled with the genetically encoded calcium…

Ultrasensitive dual phosphorylation dephosphorylation cycle kinetics exhibits canonical competition behavior

NASA Astrophysics Data System (ADS)

Huang, Qingdao; Qian, Hong

2009-09-01

We establish a mathematical model for a cellular biochemical signaling module in terms of a planar differential equation system. The signaling process is carried out by two phosphorylation-dephosphorylation reaction steps that share common kinase and phosphatase with saturated enzyme kinetics. The pair of equations is particularly simple in the present mathematical formulation, but they are singular. A complete mathematical analysis is developed based on an elementary perturbation theory. The dynamics exhibits the canonical competition behavior in addition to bistability. Although widely understood in ecological context, we are not aware of a full range of biochemical competition in a simple signaling network. The competition dynamics has broad implications to cellular processes such as cell differentiation and cancer immunoediting. The concepts of homogeneous and heterogeneous multisite phosphorylation are introduced and their corresponding dynamics are compared: there is no bistability in a heterogeneous dual phosphorylation system. A stochastic interpretation is also provided that further gives intuitive understanding of the bistable behavior inside the cells.

Two-dimensional signal processing with application to image restoration

NASA Technical Reports Server (NTRS)

Assefi, T.

1974-01-01

A recursive technique for modeling and estimating a two-dimensional signal contaminated by noise is presented. A two-dimensional signal is assumed to be an undistorted picture, where the noise introduces the distortion. Both the signal and the noise are assumed to be wide-sense stationary processes with known statistics. Thus, to estimate the two-dimensional signal is to enhance the picture. The picture representing the two-dimensional signal is converted to one dimension by scanning the image horizontally one line at a time. The scanner output becomes a nonstationary random process due to the periodic nature of the scanner operation. Procedures to obtain a dynamical model corresponding to the autocorrelation function of the scanner output are derived. Utilizing the model, a discrete Kalman estimator is designed to enhance the image.

Dynamic Synchronous Capture Algorithm for an Electromagnetic Flowmeter.

PubMed

Fanjiang, Yong-Yi; Lu, Shih-Wei

2017-04-10

This paper proposes a dynamic synchronous capture (DSC) algorithm to calculate the flow rate for an electromagnetic flowmeter. The characteristics of the DSC algorithm can accurately calculate the flow rate signal and efficiently convert an analog signal to upgrade the execution performance of a microcontroller unit (MCU). Furthermore, it can reduce interference from abnormal noise. It is extremely steady and independent of fluctuations in the flow measurement. Moreover, it can calculate the current flow rate signal immediately (m/s). The DSC algorithm can be applied to the current general MCU firmware platform without using DSP (Digital Signal Processing) or a high-speed and high-end MCU platform, and signal amplification by hardware reduces the demand for ADC accuracy, which reduces the cost.

Dynamic Synchronous Capture Algorithm for an Electromagnetic Flowmeter

PubMed Central

Fanjiang, Yong-Yi; Lu, Shih-Wei

2017-01-01

This paper proposes a dynamic synchronous capture (DSC) algorithm to calculate the flow rate for an electromagnetic flowmeter. The characteristics of the DSC algorithm can accurately calculate the flow rate signal and efficiently convert an analog signal to upgrade the execution performance of a microcontroller unit (MCU). Furthermore, it can reduce interference from abnormal noise. It is extremely steady and independent of fluctuations in the flow measurement. Moreover, it can calculate the current flow rate signal immediately (m/s). The DSC algorithm can be applied to the current general MCU firmware platform without using DSP (Digital Signal Processing) or a high-speed and high-end MCU platform, and signal amplification by hardware reduces the demand for ADC accuracy, which reduces the cost. PMID:28394306

All-digital signal-processing open-loop fiber-optic gyroscope with enlarged dynamic range.

PubMed

Wang, Qin; Yang, Chuanchuan; Wang, Xinyue; Wang, Ziyu

2013-12-15

We propose and realize a new open-loop fiber-optic gyroscope (FOG) with an all-digital signal-processing (DSP) system where an all-digital phase-locked loop is employed for digital demodulation to eliminate the variation of the source intensity and suppress the bias drift. A Sagnac phase-shift tracking method is proposed to enlarge the dynamic range, and, with its aid, a new open-loop FOG, which can achieve a large dynamic range and high sensitivity at the same time, is realized. The experimental results show that compared with the conventional open-loop FOG with the same fiber coil and optical devices, the proposed FOG reduces the bias instability from 0.259 to 0.018 deg/h, and the angle random walk from 0.031 to 0.006 deg/h(1/2), moreover, enlarges the dynamic range to ±360 deg/s, exceeding the maximum dynamic range ±63 deg/s of the conventional open-loop FOG.

A method of noise reduction in heterodyne interferometric vibration metrology by combining auto-correlation analysis and spectral filtering

NASA Astrophysics Data System (ADS)

Hao, Hongliang; Xiao, Wen; Chen, Zonghui; Ma, Lan; Pan, Feng

2018-01-01

Heterodyne interferometric vibration metrology is a useful technique for dynamic displacement and velocity measurement as it can provide a synchronous full-field output signal. With the advent of cost effective, high-speed real-time signal processing systems and software, processing of the complex signals encountered in interferometry has become more feasible. However, due to the coherent nature of the laser sources, the sequence of heterodyne interferogram are corrupted by a mixture of coherent speckle and incoherent additive noise, which can severely degrade the accuracy of the demodulated signal and the optical display. In this paper, a new heterodyne interferometric demodulation method by combining auto-correlation analysis and spectral filtering is described leading to an expression for the dynamic displacement and velocity of the object under test that is significantly more accurate in both the amplitude and frequency of the vibrating waveform. We present a mathematical model of the signals obtained from interferograms that contain both vibration information of the measured objects and the noise. A simulation of the signal demodulation process is presented and used to investigate the noise from the system and external factors. The experimental results show excellent agreement with measurements from a commercial Laser Doppler Velocimetry (LDV).

[INVITED] Evaluation of process observation features for laser metal welding

NASA Astrophysics Data System (ADS)

Tenner, Felix; Klämpfl, Florian; Nagulin, Konstantin Yu.; Schmidt, Michael

2016-06-01

In the present study we show how fast the fluid dynamics change when changing the laser power for different feed rates during laser metal welding. By the use of two high-speed cameras and a data acquisition system we conclude how fast we have to image the process to measure the fluid dynamics with a very high certainty. Our experiments show that not all process features which can be measured during laser welding do represent the process behavior similarly well. Despite the good visibility of the vapor plume the monitoring of its movement is less suitable as an input signal for a closed-loop control. The features measured inside the keyhole show a good correlation with changes of process parameters. Due to its low noise, the area of the keyhole opening is well suited as an input signal for a closed-loop control of the process.

Characterization of time dynamical evolution of electroencephalographic epileptic records

NASA Astrophysics Data System (ADS)

Rosso, Osvaldo A.; Mairal, María. Liliana

2002-09-01

Since traditional electrical brain signal analysis is mostly qualitative, the development of new quantitative methods is crucial for restricting the subjectivity in the study of brain signals. These methods are particularly fruitful when they are strongly correlated with intuitive physical concepts that allow a better understanding of the brain dynamics. The processing of information by the brain is reflected in dynamical changes of the electrical activity in time, frequency, and space. Therefore, the concomitant studies require methods capable of describing the qualitative variation of the signal in both time and frequency. The entropy defined from the wavelet functions is a measure of the order/disorder degree present in a time series. In consequence, this entropy evaluates over EEG time series gives information about the underlying dynamical process in the brain, more specifically of the synchrony of the group cells involved in the different neural responses. The total wavelet entropy results independent of the signal energy and becomes a good tool for detecting dynamical changes in the system behavior. In addition the total wavelet entropy has advantages over the Lyapunov exponents, because it is parameter free and independent of the stationarity of the time series. In this work we compared the results of the time evolution of the chaoticity (Lyapunov exponent as a function of time) with the corresponding time evolution of the total wavelet entropy in two different EEG records, one provide by depth electrodes and other by scalp ones.

SPICODYN: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.

PubMed

Pastore, Vito Paolo; Godjoski, Aleksandar; Martinoia, Sergio; Massobrio, Paolo

2018-01-01

We implemented an automated and efficient open-source software for the analysis of multi-site neuronal spike signals. The software package, named SPICODYN, has been developed as a standalone windows GUI application, using C# programming language with Microsoft Visual Studio based on .NET framework 4.5 development environment. Accepted input data formats are HDF5, level 5 MAT and text files, containing recorded or generated time series spike signals data. SPICODYN processes such electrophysiological signals focusing on: spiking and bursting dynamics and functional-effective connectivity analysis. In particular, for inferring network connectivity, a new implementation of the transfer entropy method is presented dealing with multiple time delays (temporal extension) and with multiple binary patterns (high order extension). SPICODYN is specifically tailored to process data coming from different Multi-Electrode Arrays setups, guarantying, in those specific cases, automated processing. The optimized implementation of the Delayed Transfer Entropy and the High-Order Transfer Entropy algorithms, allows performing accurate and rapid analysis on multiple spike trains from thousands of electrodes.

Functional description of signal processing in the Rogue GPS receiver

NASA Technical Reports Server (NTRS)

Thomas, J. B.

1988-01-01

Over the past year, two Rogue GPS prototype receivers have been assembled and successfully subjected to a variety of laboratory and field tests. A functional description is presented of signal processing in the Rogue receiver, tracing the signal from RF input to the output values of group delay, phase, and data bits. The receiver can track up to eight satellites, without time multiplexing among satellites or channels, simultaneously measuring both group delay and phase for each of three channels (L1-C/A, L1-P, L2-P). The Rogue signal processing described requires generation of the code for all three channels. Receiver functional design, which emphasized accuracy, reliability, flexibility, and dynamic capability, is summarized. A detailed functional description of signal processing is presented, including C/A-channel and P-channel processing, carrier-aided averaging of group delays, checks for cycle slips, acquistion, and distinctive features.

Reservoir Computing Beyond Memory-Nonlinearity Trade-off.

PubMed

Inubushi, Masanobu; Yoshimura, Kazuyuki

2017-08-31

Reservoir computing is a brain-inspired machine learning framework that employs a signal-driven dynamical system, in particular harnessing common-signal-induced synchronization which is a widely observed nonlinear phenomenon. Basic understanding of a working principle in reservoir computing can be expected to shed light on how information is stored and processed in nonlinear dynamical systems, potentially leading to progress in a broad range of nonlinear sciences. As a first step toward this goal, from the viewpoint of nonlinear physics and information theory, we study the memory-nonlinearity trade-off uncovered by Dambre et al. (2012). Focusing on a variational equation, we clarify a dynamical mechanism behind the trade-off, which illustrates why nonlinear dynamics degrades memory stored in dynamical system in general. Moreover, based on the trade-off, we propose a mixture reservoir endowed with both linear and nonlinear dynamics and show that it improves the performance of information processing. Interestingly, for some tasks, significant improvements are observed by adding a few linear dynamics to the nonlinear dynamical system. By employing the echo state network model, the effect of the mixture reservoir is numerically verified for a simple function approximation task and for more complex tasks.

A nanobiosensor for dynamic single cell analysis during microvascular self-organization.

PubMed

Wang, S; Sun, J; Zhang, D D; Wong, P K

2016-10-14

The formation of microvascular networks plays essential roles in regenerative medicine and tissue engineering. Nevertheless, the self-organization mechanisms underlying the dynamic morphogenic process are poorly understood due to a paucity of effective tools for mapping the spatiotemporal dynamics of single cell behaviors. By establishing a single cell nanobiosensor along with live cell imaging, we perform dynamic single cell analysis of the morphology, displacement, and gene expression during microvascular self-organization. Dynamic single cell analysis reveals that endothelial cells self-organize into subpopulations with specialized phenotypes to form microvascular networks and identifies the involvement of Notch1-Dll4 signaling in regulating the cell subpopulations. The cell phenotype correlates with the initial Dll4 mRNA expression level and each subpopulation displays a unique dynamic Dll4 mRNA expression profile. Pharmacological perturbations and RNA interference of Notch1-Dll4 signaling modulate the cell subpopulations and modify the morphology of the microvascular network. Taken together, a nanobiosensor enables a dynamic single cell analysis approach underscoring the importance of Notch1-Dll4 signaling in microvascular self-organization.

Enhancement tuning and control for high dynamic range images in multi-scale locally adaptive contrast enhancement algorithms

NASA Astrophysics Data System (ADS)

Cvetkovic, Sascha D.; Schirris, Johan; de With, Peter H. N.

2009-01-01

For real-time imaging in surveillance applications, visibility of details is of primary importance to ensure customer confidence. If we display High Dynamic-Range (HDR) scenes whose contrast spans four or more orders of magnitude on a conventional monitor without additional processing, results are unacceptable. Compression of the dynamic range is therefore a compulsory part of any high-end video processing chain because standard monitors are inherently Low- Dynamic Range (LDR) devices with maximally two orders of display dynamic range. In real-time camera processing, many complex scenes are improved with local contrast enhancements, bringing details to the best possible visibility. In this paper, we show how a multi-scale high-frequency enhancement scheme, in which gain is a non-linear function of the detail energy, can be used for the dynamic range compression of HDR real-time video camera signals. We also show the connection of our enhancement scheme to the processing way of the Human Visual System (HVS). Our algorithm simultaneously controls perceived sharpness, ringing ("halo") artifacts (contrast) and noise, resulting in a good balance between visibility of details and non-disturbance of artifacts. The overall quality enhancement, suitable for both HDR and LDR scenes, is based on a careful selection of the filter types for the multi-band decomposition and a detailed analysis of the signal per frequency band.

Duplicate retention in signalling proteins and constraints from network dynamics.

PubMed

Soyer, O S; Creevey, C J

2010-11-01

Duplications are a major driving force behind evolution. Most duplicates are believed to fix through genetic drift, but it is not clear whether this process affects all duplications equally or whether there are certain gene families that are expected to show neutral expansions under certain circumstances. Here, we analyse the neutrality of duplications in different functional classes of signalling proteins based on their effects on response dynamics. We find that duplications involving intermediary proteins in a signalling network are neutral more often than those involving receptors. Although the fraction of neutral duplications in all functional classes increase with decreasing population size and selective pressure on dynamics, this effect is most pronounced for receptors, indicating a possible expansion of receptors in species with small population size. In line with such an expectation, we found a statistically significant increase in the number of receptors as a fraction of genome size in eukaryotes compared with prokaryotes. Although not confirmative, these results indicate that neutral processes can be a significant factor in shaping signalling networks and affect proteins from different functional classes differently. © 2010 The Authors. Journal Compilation © 2010 European Society For Evolutionary Biology.

Control of Mechanotransduction by Molecular Clutch Dynamics.

PubMed

Elosegui-Artola, Alberto; Trepat, Xavier; Roca-Cusachs, Pere

2018-05-01

The linkage of cells to their microenvironment is mediated by a series of bonds that dynamically engage and disengage, in what has been conceptualized as the molecular clutch model. Whereas this model has long been employed to describe actin cytoskeleton and cell migration dynamics, it has recently been proposed to also explain mechanotransduction (i.e., the process by which cells convert mechanical signals from their environment into biochemical signals). Here we review the current understanding on how cell dynamics and mechanotransduction are driven by molecular clutch dynamics and its master regulator, the force loading rate. Throughout this Review, we place a specific emphasis on the quantitative prediction of cell response enabled by combined experimental and theoretical approaches. Copyright © 2018 Elsevier Ltd. All rights reserved.

Dynamics Govern Specificity of a Protein-Protein Interface: Substrate Recognition by Thrombin

PubMed Central

Fuchs, Julian E.; Huber, Roland G.; Waldner, Birgit J.; Kahler, Ursula; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R.

2015-01-01

Biomolecular recognition is crucial in cellular signal transduction. Signaling is mediated through molecular interactions at protein-protein interfaces. Still, specificity and promiscuity of protein-protein interfaces cannot be explained using simplistic static binding models. Our study rationalizes specificity of the prototypic protein-protein interface between thrombin and its peptide substrates relying solely on binding site dynamics derived from molecular dynamics simulations. We find conformational selection and thus dynamic contributions to be a key player in biomolecular recognition. Arising entropic contributions complement chemical intuition primarily reflecting enthalpic interaction patterns. The paradigm “dynamics govern specificity” might provide direct guidance for the identification of specific anchor points in biomolecular recognition processes and structure-based drug design. PMID:26496636

ISLE (Image and Signal LISP Environment): A functional language interface for signal and image processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Azevedo, S.G.; Fitch, J.P.

1987-10-21

Conventional software interfaces that use imperative computer commands or menu interactions are often restrictive environments when used for researching new algorithms or analyzing processed experimental data. We found this to be true with current signal-processing software (SIG). As an alternative, ''functional language'' interfaces provide features such as command nesting for a more natural interaction with the data. The Image and Signal LISP Environment (ISLE) is an example of an interpreted functional language interface based on common LISP. Advantages of ISLE include multidimensional and multiple data-type independence through dispatching functions, dynamic loading of new functions, and connections to artificial intelligence (AI)more » software. 10 refs.« less

ISLE (Image and Signal Lisp Environment): A functional language interface for signal and image processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Azevedo, S.G.; Fitch, J.P.

1987-05-01

Conventional software interfaces which utilize imperative computer commands or menu interactions are often restrictive environments when used for researching new algorithms or analyzing processed experimental data. We found this to be true with current signal processing software (SIG). Existing ''functional language'' interfaces provide features such as command nesting for a more natural interaction with the data. The Image and Signal Lisp Environment (ISLE) will be discussed as an example of an interpreted functional language interface based on Common LISP. Additional benefits include multidimensional and multiple data-type independence through dispatching functions, dynamic loading of new functions, and connections to artificial intelligencemore » software.« less

[Research and realization of signal processing algorithms based on FPGA in digital ophthalmic ultrasonography imaging].

PubMed

Fang, Simin; Zhou, Sheng; Wang, Xiaochun; Ye, Qingsheng; Tian, Ling; Ji, Jianjun; Wang, Yanqun

2015-01-01

To design and improve signal processing algorithms of ophthalmic ultrasonography based on FPGA. Achieved three signal processing modules: full parallel distributed dynamic filter, digital quadrature demodulation, logarithmic compression, using Verilog HDL hardware language in Quartus II. Compared to the original system, the hardware cost is reduced, the whole image shows clearer and more information of the deep eyeball contained in the image, the depth of detection increases from 5 cm to 6 cm. The new algorithms meet the design requirements and achieve the system's optimization that they can effectively improve the image quality of existing equipment.

Analysis of cerebral vessels dynamics using experimental data with missed segments

NASA Astrophysics Data System (ADS)

Pavlova, O. N.; Abdurashitov, A. S.; Ulanova, M. V.; Shihalov, G. M.; Semyachkina-Glushkovskaya, O. V.; Pavlov, A. N.

2018-04-01

Physiological signals often contain various bad segments that occur due to artifacts, failures of the recording equipment or varying experimental conditions. The related experimental data need to be preprocessed to avoid such parts of recordings. In the case of few bad segments, they can simply be removed from the signal and its analysis is further performed. However, when there are many extracted segments, the internal structure of the analyzed physiological process may be destroyed, and it is unclear whether such signal can be used in diagnostic-related studies. In this paper we address this problem for the case of cerebral vessels dynamics. We perform analysis of simulated data in order to reveal general features of quantifying scaling features of complex signals with distinct correlation properties and show that the effects of data loss are significantly different for experimental data with long-range correlations and anti-correlations. We conclude that the cerebral vessels dynamics is significantly less sensitive to missed data fragments as compared with signals with anti-correlated statistics.

Synchronization transmission of laser pattern signal within uncertain switched network

NASA Astrophysics Data System (ADS)

Lü, Ling; Li, Chengren; Li, Gang; Sun, Ao; Yan, Zhe; Rong, Tingting; Gao, Yan

2017-06-01

We propose a new technology for synchronization transmission of laser pattern signal within uncertain network with controllable topology. In synchronization process, the connection of dynamic network can vary at all time according to different demands. Especially, we construct the Lyapunov function of network through designing a special semi-positive definite function, and the synchronization transmission of laser pattern signal within uncertain network with controllable topology can be realized perfectly, which effectively avoids the complicated calculation for solving the second largest eignvalue of the coupling matrix of the dynamic network in order to obtain the network synchronization condition. At the same time, the uncertain parameters in dynamic equations belonging to network nodes can also be identified accurately via designing the identification laws of uncertain parameters. In addition, there are not any limitations for the synchronization target of network in the new technology, in other words, the target can either be a state variable signal of an arbitrary node within the network or an exterior signal.

Signal propagation in cortical networks: a digital signal processing approach.

PubMed

Rodrigues, Francisco Aparecido; da Fontoura Costa, Luciano

2009-01-01

This work reports a digital signal processing approach to representing and modeling transmission and combination of signals in cortical networks. The signal dynamics is modeled in terms of diffusion, which allows the information processing undergone between any pair of nodes to be fully characterized in terms of a finite impulse response (FIR) filter. Diffusion without and with time decay are investigated. All filters underlying the cat and macaque cortical organization are found to be of low-pass nature, allowing the cortical signal processing to be summarized in terms of the respective cutoff frequencies (a high cutoff frequency meaning little alteration of signals through their intermixing). Several findings are reported and discussed, including the fact that the incorporation of temporal activity decay tends to provide more diversified cutoff frequencies. Different filtering intensity is observed for each community in those networks. In addition, the brain regions involved in object recognition tend to present the highest cutoff frequencies for both the cat and macaque networks.

On the degree distribution of horizontal visibility graphs associated with Markov processes and dynamical systems: diagrammatic and variational approaches

NASA Astrophysics Data System (ADS)

Lacasa, Lucas

2014-09-01

Dynamical processes can be transformed into graphs through a family of mappings called visibility algorithms, enabling the possibility of (i) making empirical time series analysis and signal processing and (ii) characterizing classes of dynamical systems and stochastic processes using the tools of graph theory. Recent works show that the degree distribution of these graphs encapsulates much information on the signals' variability, and therefore constitutes a fundamental feature for statistical learning purposes. However, exact solutions for the degree distributions are only known in a few cases, such as for uncorrelated random processes. Here we analytically explore these distributions in a list of situations. We present a diagrammatic formalism which computes for all degrees their corresponding probability as a series expansion in a coupling constant which is the number of hidden variables. We offer a constructive solution for general Markovian stochastic processes and deterministic maps. As case tests we focus on Ornstein-Uhlenbeck processes, fully chaotic and quasiperiodic maps. Whereas only for certain degree probabilities can all diagrams be summed exactly, in the general case we show that the perturbation theory converges. In a second part, we make use of a variational technique to predict the complete degree distribution for special classes of Markovian dynamics with fast-decaying correlations. In every case we compare the theory with numerical experiments.

47 CFR 73.756 - System specifications for double-sideband (DBS) modulated emissions in the HF broadcasting service.

Code of Federal Regulations, 2014 CFR

2014-10-01

.... Nominal carrier frequencies shall be integral multiples of 5 kHz. (2) Audio-frequency band. The upper limit of the audio-frequency band (at—3 dB) of the transmitter shall not exceed 4.5 kHz and the lower... processing. If audio-frequency signal processing is used, the dynamic range of the modulating signal shall be...

47 CFR 73.756 - System specifications for double-sideband (DBS) modulated emissions in the HF broadcasting service.

Code of Federal Regulations, 2012 CFR

2012-10-01

.... Nominal carrier frequencies shall be integral multiples of 5 kHz. (2) Audio-frequency band. The upper limit of the audio-frequency band (at—3 dB) of the transmitter shall not exceed 4.5 kHz and the lower... processing. If audio-frequency signal processing is used, the dynamic range of the modulating signal shall be...

47 CFR 73.756 - System specifications for double-sideband (DBS) modulated emissions in the HF broadcasting service.

Code of Federal Regulations, 2011 CFR

2011-10-01

.... Nominal carrier frequencies shall be integral multiples of 5 kHz. (2) Audio-frequency band. The upper limit of the audio-frequency band (at—3 dB) of the transmitter shall not exceed 4.5 kHz and the lower... processing. If audio-frequency signal processing is used, the dynamic range of the modulating signal shall be...

47 CFR 73.756 - System specifications for double-sideband (DBS) modulated emissions in the HF broadcasting service.

Code of Federal Regulations, 2013 CFR

2013-10-01

.... Nominal carrier frequencies shall be integral multiples of 5 kHz. (2) Audio-frequency band. The upper limit of the audio-frequency band (at—3 dB) of the transmitter shall not exceed 4.5 kHz and the lower... processing. If audio-frequency signal processing is used, the dynamic range of the modulating signal shall be...

Detection of a dynamic topography signal in last interglacial sea-level records

PubMed Central

Austermann, Jacqueline; Mitrovica, Jerry X.; Huybers, Peter; Rovere, Alessio

2017-01-01

Estimating minimum ice volume during the last interglacial based on local sea-level indicators requires that these indicators are corrected for processes that alter local sea level relative to the global average. Although glacial isostatic adjustment is generally accounted for, global scale dynamic changes in topography driven by convective mantle flow are generally not considered. We use numerical models of mantle flow to quantify vertical deflections caused by dynamic topography and compare predictions at passive margins to a globally distributed set of last interglacial sea-level markers. The deflections predicted as a result of dynamic topography are significantly correlated with marker elevations (>95% probability) and are consistent with construction and preservation attributes across marker types. We conclude that a dynamic topography signal is present in the elevation of last interglacial sea-level records and that the signal must be accounted for in any effort to determine peak global mean sea level during the last interglacial to within an accuracy of several meters. PMID:28695210

A digital-signal-processor-based optical tomographic system for dynamic imaging of joint diseases

NASA Astrophysics Data System (ADS)

Lasker, Joseph M.

Over the last decade, optical tomography (OT) has emerged as viable biomedical imaging modality. Various imaging systems have been developed that are employed in preclinical as well as clinical studies, mostly targeting breast imaging, brain imaging, and cancer related studies. Of particular interest are so-called dynamic imaging studies where one attempts to image changes in optical properties and/or physiological parameters as they occur during a system perturbation. To successfully perform dynamic imaging studies, great effort is put towards system development that offers increasingly enhanced signal-to-noise performance at ever shorter data acquisition times, thus capturing high fidelity tomographic data within narrower time periods. Towards this goal, I have developed in this thesis a dynamic optical tomography system that is, unlike currently available analog instrumentation, based on digital data acquisition and filtering techniques. At the core of this instrument is a digital signal processor (DSP) that collects, collates, and processes the digitized data set. Complementary protocols between the DSP and a complex programmable logic device synchronizes the sampling process and organizes data flow. Instrument control is implemented through a comprehensive graphical user interface which integrates automated calibration, data acquisition, and signal post-processing. Real-time data is generated at frame rates as high as 140 Hz. An extensive dynamic range (˜190 dB) accommodates a wide scope of measurement geometries and tissue types. Performance analysis demonstrates very low system noise (˜1 pW rms noise equivalent power), excellent signal precision (˜0.04%--0.2%) and long term system stability (˜1% over 40 min). Experiments on tissue phantoms validate spatial and temporal accuracy of the system. As a potential new application of dynamic optical imaging I present the first application of this method to use vascular hemodynamics as a means of characterizing joint diseases, especially effects of rheumatoid arthritis (RA) in the proximal interphalangeal finger joints. Using a dual-wavelength tomographic imaging system and previously implemented reconstruction scheme, I have performed initial dynamic imaging case studies on healthy volunteers and patients diagnosed with RA. These studies support our hypothesis that differences in the vascular and metabolic reactivity exist between affected and unaffected joints and can be used for diagnostic purposes.

Signal processing: opportunities for superconductive circuits

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ralston, R.W.

1985-03-01

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 andmore » 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.« less

Mitochondrial morphology transitions and functions: implications for retrograde signaling?

PubMed Central

Picard, Martin; Shirihai, Orian S.; Gentil, Benoit J.

2013-01-01

In response to cellular and environmental stresses, mitochondria undergo morphology transitions regulated by dynamic processes of membrane fusion and fission. These events of mitochondrial dynamics are central regulators of cellular activity, but the mechanisms linking mitochondrial shape to cell function remain unclear. One possibility evaluated in this review is that mitochondrial morphological transitions (from elongated to fragmented, and vice-versa) directly modify canonical aspects of the organelle's function, including susceptibility to mitochondrial permeability transition, respiratory properties of the electron transport chain, and reactive oxygen species production. Because outputs derived from mitochondrial metabolism are linked to defined cellular signaling pathways, fusion/fission morphology transitions could regulate mitochondrial function and retrograde signaling. This is hypothesized to provide a dynamic interface between the cell, its genome, and the fluctuating metabolic environment. PMID:23364527

Research on on-line monitoring technology for steel ball's forming process based on load signal analysis method

NASA Astrophysics Data System (ADS)

Li, Ying-jun; Ai, Chang-sheng; Men, Xiu-hua; Zhang, Cheng-liang; Zhang, Qi

2013-04-01

This paper presents a novel on-line monitoring technology to obtain forming quality in steel ball's forming process based on load signal analysis method, in order to reveal the bottom die's load characteristic in initial cold heading forging process of steel balls. A mechanical model of the cold header producing process is established and analyzed by using finite element method. The maximum cold heading force is calculated. The results prove that the monitoring on the cold heading process with upsetting force is reasonable and feasible. The forming defects are inflected on the three feature points of the bottom die signals, which are the initial point, infection point, and peak point. A novel PVDF piezoelectric force sensor which is simple on construction and convenient on installation is designed. The sensitivity of the PVDF force sensor is calculated. The characteristics of PVDF force sensor are analyzed by FEM. The PVDF piezoelectric force sensor is fabricated to acquire the actual load signals in the cold heading process, and calibrated by a special device. The measuring system of on-line monitoring is built. The characteristics of the actual signals recognized by learning and identification algorithm are in consistence with simulation results. Identification of actual signals shows that the timing difference values of all feature points for qualified products are not exceed ±6 ms, and amplitude difference values are less than ±3%. The calibration and application experiments show that PVDF force sensor has good static and dynamic performances, and is competent at dynamic measuring on upsetting force. It greatly improves automatic level and machining precision. Equipment capacity factor with damages identification method depends on grade of steel has been improved to 90%.

A comparison between the first-fit settings of two multichannel digital signal-processing strategies: music quality ratings and speech-in-noise scores.

PubMed

Higgins, Paul; Searchfield, Grant; Coad, Gavin

2012-06-01

The aim of this study was to determine which level-dependent hearing aid digital signal-processing strategy (DSP) participants preferred when listening to music and/or performing a speech-in-noise task. Two receiver-in-the-ear hearing aids were compared: one using 32-channel adaptive dynamic range optimization (ADRO) and the other wide dynamic range compression (WDRC) incorporating dual fast (4 channel) and slow (15 channel) processing. The manufacturers' first-fit settings based on participants' audiograms were used in both cases. Results were obtained from 18 participants on a quick speech-in-noise (QuickSIN; Killion, Niquette, Gudmundsen, Revit, & Banerjee, 2004) task and for 3 music listening conditions (classical, jazz, and rock). Participants preferred the quality of music and performed better at the QuickSIN task using the hearing aids with ADRO processing. A potential reason for the better performance of the ADRO hearing aids was less fluctuation in output with change in sound dynamics. ADRO processing has advantages for both music quality and speech recognition in noise over the multichannel WDRC processing that was used in the study. Further evaluations of which DSP aspects contribute to listener preference are required.

Fluid-Solid Interaction and Multiscale Dynamic Processes: Experimental Approach

NASA Astrophysics Data System (ADS)

Arciniega-Ceballos, Alejandra; Spina, Laura; Mendo-Pérez, Gerardo M.; Guzmán-Vázquez, Enrique; Scheu, Bettina; Sánchez-Sesma, Francisco J.; Dingwell, Donald B.

2017-04-01

The speed and the style of a pressure drop in fluid-filled conduits determines the dynamics of multiscale processes and the elastic interaction between the fluid and the confining solid. To observe this dynamics we performed experiments using fluid-filled transparent tubes (15-50 cm long, 2-4 cm diameter and 0.3-1 cm thickness) instrumented with high-dynamic piezoelectric sensors and filmed the evolution of these processes with a high speed camera. We analyzed the response of Newtonian fluids to slow and sudden pressure drops from 3 bar-10 MPa to ambient pressure. We used fluids with viscosities of mafic to intermediate silicate melts of 1 to 1000 Pa s and water. The processes observed are fluid mass expansion, fluid flow, jets, bubbles nucleation, growth, coalescence and collapse, degassing, foam building at the surface and vertical wagging. All these processes (in fine and coarse scales) are triggered by the pressure drop and are sequentially coupled in time while interacting with the solid. During slow decompression, the multiscale processes are recognized occurring within specific pressure intervals, and exhibit a localized distribution along the conduit. In this, degassing predominates near the surface and may present piston-like oscillations. In contrast, during sudden decompression the fluid-flow reaches higher velocities, the dynamics is dominated by a sequence of gas-packet pulses driving jets of the gas-fluid mixture. The evolution of this multiscale phenomenon generates complex non-stationary microseismic signals recorded along the conduit. We discuss distinctive characteristics of these signals depending on the decompression style and compare them with synthetics. These synthetics are obtained numerically under an averaging modeling scheme, that accounted for the stress-strain of the cyclic dynamic interaction between the fluid and the solid wall, assuming an incompressible and viscous fluid that flows while the elastic solid responds oscillating. Analysis of time series, both experimental and synthetics, synchronized with high-speed imaging enables the explanation and interpretation of distinct phases of the dynamics of these fluids and the extraction of time and frequency characteristics of the individual processes. We observed that the effects of both, pressure drop triggering function and viscosity, control the characteristics of the micro-signals in time and frequency. This suggests the great potential that experimental and numerical approaches provide to untangle from field volcanic seismograms the multiscale processes of the stress field, driving forces and fluid-rock interaction that determine the volcanic conduit dynamics.

Develop Advanced Nonlinear Signal Analysis Topographical Mapping System

NASA Technical Reports Server (NTRS)

Jong, Jen-Yi

1997-01-01

During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.

Analysis and control of the vibration of doubly fed wind turbine

NASA Astrophysics Data System (ADS)

Yu, Manye; Lin, Ying

2017-01-01

The fault phenomena of the violent vibration of certain doubly-fed wind turbine were researched comprehensively, and the dynamic characteristics, load and fault conditions of the system were discussed. Firstly, the structural dynamics analysis of wind turbine is made, and the dynamics mold is built. Secondly, the vibration testing of wind turbine is done with the German test and analysis systems BBM. Thirdly, signal should be analyzed and dealt with. Based on the experiment, spectrum analysis of the motor dynamic balance can be made by using signal processing toolbox of MATLAB software, and the analysis conclusions show that the vibration of wind turbine is caused by dynamic imbalance. The results show that integrating mechanical system dynamics theory with advanced test technology can solve the vibration problem more successfully, which is important in vibration diagnosis of mechanical equipment.

A robust color signal processing with wide dynamic range WRGB CMOS image sensor

NASA Astrophysics Data System (ADS)

Kawada, Shun; Kuroda, Rihito; Sugawa, Shigetoshi

2011-01-01

We have developed a robust color reproduction methodology by a simple calculation with a new color matrix using the formerly developed wide dynamic range WRGB lateral overflow integration capacitor (LOFIC) CMOS image sensor. The image sensor was fabricated through a 0.18 μm CMOS technology and has a 45 degrees oblique pixel array, the 4.2 μm effective pixel pitch and the W pixels. A W pixel was formed by replacing one of the two G pixels in the Bayer RGB color filter. The W pixel has a high sensitivity through the visible light waveband. An emerald green and yellow (EGY) signal is generated from the difference between the W signal and the sum of RGB signals. This EGY signal mainly includes emerald green and yellow lights. These colors are difficult to be reproduced accurately by the conventional simple linear matrix because their wave lengths are in the valleys of the spectral sensitivity characteristics of the RGB pixels. A new linear matrix based on the EGY-RGB signal was developed. Using this simple matrix, a highly accurate color processing with a large margin to the sensitivity fluctuation and noise has been achieved.

Propagation of kinetic uncertainties through a canonical topology of the TLR4 signaling network in different regions of biochemical reaction space

PubMed Central

2010-01-01

Background Signal transduction networks represent the information processing systems that dictate which dynamical regimes of biochemical activity can be accessible to a cell under certain circumstances. One of the major concerns in molecular systems biology is centered on the elucidation of the robustness properties and information processing capabilities of signal transduction networks. Achieving this goal requires the establishment of causal relations between the design principle of biochemical reaction systems and their emergent dynamical behaviors. Methods In this study, efforts were focused in the construction of a relatively well informed, deterministic, non-linear dynamic model, accounting for reaction mechanisms grounded on standard mass action and Hill saturation kinetics, of the canonical reaction topology underlying Toll-like receptor 4 (TLR4)-mediated signaling events. This signaling mechanism has been shown to be deployed in macrophages during a relatively short time window in response to lypopolysaccharyde (LPS) stimulation, which leads to a rapidly mounted innate immune response. An extensive computational exploration of the biochemical reaction space inhabited by this signal transduction network was performed via local and global perturbation strategies. Importantly, a broad spectrum of biologically plausible dynamical regimes accessible to the network in widely scattered regions of parameter space was reconstructed computationally. Additionally, experimentally reported transcriptional readouts of target pro-inflammatory genes, which are actively modulated by the network in response to LPS stimulation, were also simulated. This was done with the main goal of carrying out an unbiased statistical assessment of the intrinsic robustness properties of this canonical reaction topology. Results Our simulation results provide convincing numerical evidence supporting the idea that a canonical reaction mechanism of the TLR4 signaling network is capable of performing information processing in a robust manner, a functional property that is independent of the signaling task required to be executed. Nevertheless, it was found that the robust performance of the network is not solely determined by its design principle (topology), but this may be heavily dependent on the network's current position in biochemical reaction space. Ultimately, our results enabled us the identification of key rate limiting steps which most effectively control the performance of the system under diverse dynamical regimes. Conclusions Overall, our in silico study suggests that biologically relevant and non-intuitive aspects on the general behavior of a complex biomolecular network can be elucidated only when taking into account a wide spectrum of dynamical regimes attainable by the system. Most importantly, this strategy provides the means for a suitable assessment of the inherent variational constraints imposed by the structure of the system when systematically probing its parameter space. PMID:20230643

How input fluctuations reshape the dynamics of a biological switching system

NASA Astrophysics Data System (ADS)

Hu, Bo; Kessler, David A.; Rappel, Wouter-Jan; Levine, Herbert

2012-12-01

An important task in quantitative biology is to understand the role of stochasticity in biochemical regulation. Here, as an extension of our recent work [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.107.148101 107, 148101 (2011)], we study how input fluctuations affect the stochastic dynamics of a simple biological switch. In our model, the on transition rate of the switch is directly regulated by a noisy input signal, which is described as a non-negative mean-reverting diffusion process. This continuous process can be a good approximation of the discrete birth-death process and is much more analytically tractable. Within this setup, we apply the Feynman-Kac theorem to investigate the statistical features of the output switching dynamics. Consistent with our previous findings, the input noise is found to effectively suppress the input-dependent transitions. We show analytically that this effect becomes significant when the input signal fluctuates greatly in amplitude and reverts slowly to its mean.

Scaling Behavior in Mitochondrial Redox Fluctuations

PubMed Central

Ramanujan, V. Krishnan; Biener, Gabriel; Herman, Brian A.

2006-01-01

Scale-invariant long-range correlations have been reported in fluctuations of time-series signals originating from diverse processes such as heart beat dynamics, earthquakes, and stock market data. The common denominator of these apparently different processes is a highly nonlinear dynamics with competing forces and distinct feedback species. We report for the first time an experimental evidence for scaling behavior in NAD(P)H signal fluctuations in isolated mitochondria and intact cells isolated from the liver of a young (5-month-old) mouse. Time-series data were collected by two-photon imaging of mitochondrial NAD(P)H fluorescence and signal fluctuations were quantitatively analyzed for statistical correlations by detrended fluctuation analysis and spectral power analysis. Redox [NAD(P)H / NAD(P)+] fluctuations in isolated mitochondria and intact liver cells were found to display nonrandom, long-range correlations. These correlations are interpreted as arising due to the regulatory dynamics operative in Krebs' cycle enzyme network and electron transport chain in the mitochondria. This finding may provide a novel basis for understanding similar regulatory networks that govern the nonequilibrium properties of living cells. PMID:16565066

Heat dissipation guides activation in signaling proteins.

PubMed

Weber, Jeffrey K; Shukla, Diwakar; Pande, Vijay S

2015-08-18

Life is fundamentally a nonequilibrium phenomenon. At the expense of dissipated energy, living things perform irreversible processes that allow them to propagate and reproduce. Within cells, evolution has designed nanoscale machines to do meaningful work with energy harnessed from a continuous flux of heat and particles. As dictated by the Second Law of Thermodynamics and its fluctuation theorem corollaries, irreversibility in nonequilibrium processes can be quantified in terms of how much entropy such dynamics produce. In this work, we seek to address a fundamental question linking biology and nonequilibrium physics: can the evolved dissipative pathways that facilitate biomolecular function be identified by their extent of entropy production in general relaxation processes? We here synthesize massive molecular dynamics simulations, Markov state models (MSMs), and nonequilibrium statistical mechanical theory to probe dissipation in two key classes of signaling proteins: kinases and G-protein-coupled receptors (GPCRs). Applying machinery from large deviation theory, we use MSMs constructed from protein simulations to generate dynamics conforming to positive levels of entropy production. We note the emergence of an array of peaks in the dynamical response (transient analogs of phase transitions) that draw the proteins between distinct levels of dissipation, and we see that the binding of ATP and agonist molecules modifies the observed dissipative landscapes. Overall, we find that dissipation is tightly coupled to activation in these signaling systems: dominant entropy-producing trajectories become localized near important barriers along known biological activation pathways. We go on to classify an array of equilibrium and nonequilibrium molecular switches that harmonize to promote functional dynamics.

Nemo regulates cell dynamics and represses the expression of miple, a midkine/pleiotrophin cytokine, during ommatidial rotation

PubMed Central

Muñoz-Soriano, Verónica; Ruiz, Carlos; Pérez-Alonso, Manuel; Mlodzik, Marek; Paricio, Nuria

2013-01-01

Ommatidial rotation is one of the most important events for correct patterning of the Drosophila eye. Although several signaling pathways are involved in this process, few genes have been shown to specifically affect it. One of them is nemo (nmo), which encodes a MAP-like protein kinase that regulates the rate of rotation throughout the entire process, and serves as a link between core planar cell polarity (PCP) factors and the E-cadherin–β-catenin complex. To determine more precisely the role of nmo in ommatidial rotation, live-imaging analyses in nmo mutant and wild-type early pupal eye discs were performed. We demonstrate that ommatidial rotation is not a continuous process, and that rotating and non-rotating interommatidial cells are very dynamic. Our in vivo analyses also show that nmo regulates the speed of rotation and is required in cone cells for correct ommatidial rotation, and that these cells as well as interommatidial cells are less dynamic in nmo mutants. Furthermore, microarray analyses of nmo and wild-type larval eye discs led us to identify new genes and signaling pathways related to nmo function during this process. One of them, miple, encodes the Drosophila ortholog of the midkine/pleiotrophin secreted cytokines that are involved in cell migration processes. miple is highly up-regulated in nmo mutant discs. Indeed, phenotypic analyses reveal that miple overexpression leads to ommatidial rotation defects. Genetic interaction assays suggest that miple is signaling through Ptp99A, the Drosophila ortholog of the vertebrate midkine/pleiotrophin PTPζ receptor. Accordingly, we propose that one of the roles of Nmo during ommatial rotation is to repress miple expression, which may in turn affect the dynamics in E-cadherin–β-catenin complexes. PMID:23428616

Model of the best-of-N nest-site selection process in honeybees.

PubMed

Reina, Andreagiovanni; Marshall, James A R; Trianni, Vito; Bose, Thomas

2017-05-01

The ability of a honeybee swarm to select the best nest site plays a fundamental role in determining the future colony's fitness. To date, the nest-site selection process has mostly been modeled and theoretically analyzed for the case of binary decisions. However, when the number of alternative nests is larger than two, the decision-process dynamics qualitatively change. In this work, we extend previous analyses of a value-sensitive decision-making mechanism to a decision process among N nests. First, we present the decision-making dynamics in the symmetric case of N equal-quality nests. Then, we generalize our findings to a best-of-N decision scenario with one superior nest and N-1 inferior nests, previously studied empirically in bees and ants. Whereas previous binary models highlighted the crucial role of inhibitory stop-signaling, the key parameter in our new analysis is the relative time invested by swarm members in individual discovery and in signaling behaviors. Our new analysis reveals conflicting pressures on this ratio in symmetric and best-of-N decisions, which could be solved through a time-dependent signaling strategy. Additionally, our analysis suggests how ecological factors determining the density of suitable nest sites may have led to selective pressures for an optimal stable signaling ratio.

Model of the best-of-N nest-site selection process in honeybees

NASA Astrophysics Data System (ADS)

Reina, Andreagiovanni; Marshall, James A. R.; Trianni, Vito; Bose, Thomas

2017-05-01

The ability of a honeybee swarm to select the best nest site plays a fundamental role in determining the future colony's fitness. To date, the nest-site selection process has mostly been modeled and theoretically analyzed for the case of binary decisions. However, when the number of alternative nests is larger than two, the decision-process dynamics qualitatively change. In this work, we extend previous analyses of a value-sensitive decision-making mechanism to a decision process among N nests. First, we present the decision-making dynamics in the symmetric case of N equal-quality nests. Then, we generalize our findings to a best-of-N decision scenario with one superior nest and N -1 inferior nests, previously studied empirically in bees and ants. Whereas previous binary models highlighted the crucial role of inhibitory stop-signaling, the key parameter in our new analysis is the relative time invested by swarm members in individual discovery and in signaling behaviors. Our new analysis reveals conflicting pressures on this ratio in symmetric and best-of-N decisions, which could be solved through a time-dependent signaling strategy. Additionally, our analysis suggests how ecological factors determining the density of suitable nest sites may have led to selective pressures for an optimal stable signaling ratio.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jang, Junhwan; Hwang, Sungui; Park, Kyihwan, E-mail: khpark@gist.ac.kr

To utilize a time-of-flight-based laser scanner as a distance measurement sensor, the measurable distance and accuracy are the most important performance parameters to consider. For these purposes, the optical system and electronic signal processing of the laser scanner should be optimally designed in order to reduce a distance error caused by the optical crosstalk and wide dynamic range input. Optical system design for removing optical crosstalk problem is proposed in this work. Intensity control is also considered to solve the problem of a phase-shift variation in the signal processing circuit caused by object reflectivity. The experimental results for optical systemmore » and signal processing design are performed using 3D measurements.« less

Dynamic Singularity Spectrum Distribution of Sea Clutter

NASA Astrophysics Data System (ADS)

Xiong, Gang; Yu, Wenxian; Zhang, Shuning

2015-12-01

The fractal and multifractal theory have provided new approaches for radar signal processing and target-detecting under the background of ocean. However, the related research mainly focuses on fractal dimension or multifractal spectrum (MFS) of sea clutter. In this paper, a new dynamic singularity analysis method of sea clutter using MFS distribution is developed, based on moving detrending analysis (DMA-MFSD). Theoretically, we introduce the time information by using cyclic auto-correlation of sea clutter. For transient correlation series, the instantaneous singularity spectrum based on multifractal detrending moving analysis (MF-DMA) algorithm is calculated, and the dynamic singularity spectrum distribution of sea clutter is acquired. In addition, we analyze the time-varying singularity exponent ranges and maximum position function in DMA-MFSD of sea clutter. For the real sea clutter data, we analyze the dynamic singularity spectrum distribution of real sea clutter in level III sea state, and conclude that the radar sea clutter has the non-stationary and time-varying scale characteristic and represents the time-varying singularity spectrum distribution based on the proposed DMA-MFSD method. The DMA-MFSD will also provide reference for nonlinear dynamics and multifractal signal processing.

Non-invasive assessment of skeletal muscle activity

NASA Astrophysics Data System (ADS)

Merletti, Roberto; Orizio, Claudio; di Prampero, Pietro E.; Tesch, Per

2005-10-01

After the first 3 years (2002-2005), the MAP project has made available: - systems fo electrodes, signal conditioning and digital processing for multichannel simultaneously-detected EMG and MMG as well as for simultaneous electrical stimulation and EMG detection with artifact cancellation. - innovative non-invasive techniques for the extraction of individual motor unit action potentials (MUAPS) and individual motor and MMG contributions from the surface EMG interference signal and the MMG signal. - processing techniques for extractions of indicators of progressive fatigue from the electrically-elicited (M-wave) EMG signal. - techniques for the analysis of dynamic multichannel EMG during cyclic or explosive exercise (in collaboration with project EXER/MAP-MED-027).

T Cell Dynamic Activation and Functional Analysis in Nanoliter Droplet Microarray.

PubMed

Sarkar, Saheli; Motwani, Vinny; Sabhachandani, Pooja; Cohen, Noa; Konry, Tania

2015-06-01

Characterization of the heterogeneity in immune reactions requires assessing dynamic single cell responses as well as interactions between the various immune cell subsets. Maturation and activation of effector cells is regulated by cell contact-dependent and soluble factor-mediated paracrine signalling. Currently there are few methods available that allow dynamic investigation of both processes simultaneously without physically constraining non-adherent cells and eliminating crosstalk from neighboring cell pairs. We describe here a microfluidic droplet microarray platform that permits rapid functional analysis of single cell responses and co-encapsulation of heterotypic cell pairs, thereby allowing us to evaluate the dynamic activation state of primary T cells. The microfluidic droplet platform enables generation and docking of monodisperse nanoliter volume (0.523 nl) droplets, with the capacity of monitoring a thousand droplets per experiment. Single human T cells were encapsulated in droplets and stimulated on-chip with the calcium ionophore ionomycin. T cells were also co-encapsulated with dendritic cells activated by ovalbumin peptide, followed by dynamic calcium signal monitoring. Ionomycin-stimulated cells depicted fluctuation in calcium signalling compared to control. Both cell populations demonstrated marked heterogeneity in responses. Calcium signalling was observed in T cells immediately following contact with DCs, suggesting an early activation signal. T cells further showed non-contact mediated increase in calcium level, although this response was delayed compared to contact-mediated signals. Our results suggest that this nanoliter droplet array-based microfluidic platform is a promising technique for assessment of heterogeneity in various types of cellular responses, detection of early/delayed signalling events and live cell phenotyping of immune cells.

Pseudoscaffolds and anchoring proteins: the difference is in the details

PubMed Central

Aggarwal-Howarth, Stacey; Scott, John D.

2017-01-01

Pseudokinases and pseudophosphatases possess the ability to bind substrates without catalyzing their modification, thereby providing a mechanism to recruit potential phosphotargets away from active enzymes. Since many of these pseudoenzymes possess other characteristics such as localization signals, separate catalytic sites, and protein–protein interaction domains, they have the capacity to influence signaling dynamics in local environments. In a similar manner, the targeting of signaling enzymes to subcellular locations by A-kinase-anchoring proteins (AKAPs) allows for precise and local control of second messenger signaling events. Here, we will discuss how pseudoenzymes form ‘pseudoscaffolds’ and compare and contrast this compartment-specific regulatory role with the signal organization properties of AKAPs. The mitochondria will be the focus of this review, as they are dynamic organelles that influence a broad range of cellular processes such as metabolism, ATP synthesis, and apoptosis. PMID:28408477

A real time dynamic data acquisition and processing system for velocity, density, and total temperature fluctuation measurements

NASA Technical Reports Server (NTRS)

Clukey, Steven J.

1991-01-01

The real time Dynamic Data Acquisition and Processing System (DDAPS) is described which provides the capability for the simultaneous measurement of velocity, density, and total temperature fluctuations. The system of hardware and software is described in context of the wind tunnel environment. The DDAPS replaces both a recording mechanism and a separate data processing system. DDAPS receives input from hot wire anemometers. Amplifiers and filters condition the signals with computer controlled modules. The analog signals are simultaneously digitized and digitally recorded on disk. Automatic acquisition collects necessary calibration and environment data. Hot wire sensitivities are generated and applied to the hot wire data to compute fluctuations. The presentation of the raw and processed data is accomplished on demand. The interface to DDAPS is described along with the internal mechanisms of DDAPS. A summary of operations relevant to the use of the DDAPS is also provided.

Effects of Four Different Restoration Treatments on the Natural Abundance of 15N Stable Isotopes in Plants

PubMed Central

Temperton, Vicky M.; Märtin, Lea L. A.; Röder, Daniela; Lücke, Andreas; Kiehl, Kathrin

2012-01-01

δ15N signals in plant and soil material integrate over a number of biogeochemical processes related to nitrogen (N) and therefore provide information on net effects of multiple processes on N dynamics. In general little is known in many grassland restoration projects on soil–plant N dynamics in relation to the restoration treatments. In particular, δ15N signals may be a useful tool to assess whether abiotic restoration treatments have produced the desired result. In this study we used the range of abiotic and biotic conditions provided by a restoration experiment to assess to whether the restoration treatments and/or plant functional identity and legume neighborhood affected plant δ15N signals. The restoration treatments consisted of hay transfer and topsoil removal, thus representing increasing restoration effort, from no restoration measures, through biotic manipulation to major abiotic manipulation. We measured δ15N and %N in six different plant species (two non-legumes and four legumes) across the restoration treatments. We found that restoration treatments were clearly reflected in δ15N of the non-legume species, with very depleted δ15N associated with low soil N, and our results suggest this may be linked to uptake of ammonium (rather than nitrate). The two non-legume species differed considerably in their δ15N signals, which may be related to the two species forming different kinds of mycorrhizal symbioses. Plant δ15N signals could clearly separate legumes from non-legumes, but our results did not allow for an assessment of legume neighborhood effects on non-legume δ15N signals. We discuss our results in the light of what the δ15N signals may be telling us about plant–soil N dynamics and their potential value as an indicator for N dynamics in restoration. PMID:22645597

Learning Data Set Influence on Identification Accuracy of Gas Turbine Neural Network Model

NASA Astrophysics Data System (ADS)

Kuznetsov, A. V.; Makaryants, G. M.

2018-01-01

There are many gas turbine engine identification researches via dynamic neural network models. It should minimize errors between model and real object during identification process. Questions about training data set processing of neural networks are usually missed. This article presents a study about influence of data set type on gas turbine neural network model accuracy. The identification object is thermodynamic model of micro gas turbine engine. The thermodynamic model input signal is the fuel consumption and output signal is the engine rotor rotation frequency. Four types input signals was used for creating training and testing data sets of dynamic neural network models - step, fast, slow and mixed. Four dynamic neural networks were created based on these types of training data sets. Each neural network was tested via four types test data sets. In the result 16 transition processes from four neural networks and four test data sets from analogous solving results of thermodynamic model were compared. The errors comparison was made between all neural network errors in each test data set. In the comparison result it was shown error value ranges of each test data set. It is shown that error values ranges is small therefore the influence of data set types on identification accuracy is low.

Stochastic Online Learning in Dynamic Networks under Unknown Models

DTIC Science & Technology

2016-08-02

Repeated Game with Incomplete Information, IEEE International Conference on Acoustics, Speech, and Signal Processing. 20-MAR-16, Shanghai, China...in a game theoretic framework for the application of multi-seller dynamic pricing with unknown demand models. We formulated the problem as an...infinitely repeated game with incomplete information and developed a dynamic pricing strategy referred to as Competitive and Cooperative Demand Learning

A digital strategy for manometer dynamic enhancement. [for wind tunnel monitoring

NASA Technical Reports Server (NTRS)

Stoughton, J. W.

1978-01-01

Application of digital signal processing techniques to improve the non-linear dynamic characteristics of a sonar-type mercury manometer is described. The dynamic enhancement strategy quasi-linearizes the manometer characteristics and improves the effective bandwidth in the context of a wind-tunnel pressure regulation system. Model identification data and real-time hybrid simulation data demonstrate feasibility of approach.

A micromechanical analogue mixer with dynamic displacement amplification

NASA Astrophysics Data System (ADS)

Erismis, M. A.

2018-06-01

A new micromechanical device is proposed which is capable of modulation, demodulation and filtering operations. The device uses a patented 3-mass coupled micromechanical resonator which dynamically amplifies the displacement within a frequency range of interest. Modulation can be obtained by exciting different masses of the resonator with the data and the carrier signals. Demodulation can be obtained similarly by exciting the actuator with the input and carrier signals at the same time. With the help of dynamic motion amplification, filtering and signal amplification can be achieved simultaneously. A generic design approach is introduced which can be applied from kHz to MHz regime frequencies of interest. A sample mixer design for an silicon on insulator-based process is provided. A SPICE (Simulation Program with Integrated Circuit Emphasis)-based electro-mechanical co-simulation platform is also developed and the proposed mixer is simulated.

Design of signal reception and processing system of embedded ultrasonic endoscope

NASA Astrophysics Data System (ADS)

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.

A New Concept to Reveal Protein Dynamics Based on Energy Dissipation

PubMed Central

Ma, Cheng-Wei; Xiu, Zhi-Long; Zeng, An-Ping

2011-01-01

Protein dynamics is essential for its function, especially for intramolecular signal transduction. In this work we propose a new concept, energy dissipation model, to systematically reveal protein dynamics upon effector binding and energy perturbation. The concept is applied to better understand the intramolecular signal transduction during allostery of enzymes. The E. coli allosteric enzyme, aspartokinase III, is used as a model system and special molecular dynamics simulations are designed and carried out. Computational results indicate that the number of residues affected by external energy perturbation (i.e. caused by a ligand binding) during the energy dissipation process shows a sigmoid pattern. Using the two-state Boltzmann equation, we define two parameters, the half response time and the dissipation rate constant, which can be used to well characterize the energy dissipation process. For the allostery of aspartokinase III, the residue response time indicates that besides the ACT2 signal transduction pathway, there is another pathway between the regulatory site and the catalytic site, which is suggested to be the β15-αK loop of ACT1. We further introduce the term “protein dynamical modules” based on the residue response time. Different from the protein structural modules which merely provide information about the structural stability of proteins, protein dynamical modules could reveal protein characteristics from the perspective of dynamics. Finally, the energy dissipation model is applied to investigate E. coli aspartokinase III mutations to better understand the desensitization of product feedback inhibition via allostery. In conclusion, the new concept proposed in this paper gives a novel holistic view of protein dynamics, a key question in biology with high impacts for both biotechnology and biomedicine. PMID:22022616

Normative evidence accumulation in unpredictable environments

PubMed Central

Glaze, Christopher M; Kable, Joseph W; Gold, Joshua I

2015-01-01

In our dynamic world, decisions about noisy stimuli can require temporal accumulation of evidence to identify steady signals, differentiation to detect unpredictable changes in those signals, or both. Normative models can account for learning in these environments but have not yet been applied to faster decision processes. We present a novel, normative formulation of adaptive learning models that forms decisions by acting as a leaky accumulator with non-absorbing bounds. These dynamics, derived for both discrete and continuous cases, depend on the expected rate of change of the statistics of the evidence and balance signal identification and change detection. We found that, for two different tasks, human subjects learned these expectations, albeit imperfectly, then used them to make decisions in accordance with the normative model. The results represent a unified, empirically supported account of decision-making in unpredictable environments that provides new insights into the expectation-driven dynamics of the underlying neural signals. DOI: http://dx.doi.org/10.7554/eLife.08825.001 PMID:26322383

Signal Detection Techniques for Diagnostic Monitoring of Space Shuttle Main Engine Turbomachinery

NASA Technical Reports Server (NTRS)

Coffin, Thomas; Jong, Jen-Yi

1986-01-01

An investigation to develop, implement, and evaluate signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery is reviewed. A brief description of the Space Shuttle Main Engine (SSME) test/measurement program is presented. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques have been implemented on a computer and applied to dynamc signals. A laboratory evaluation of the methods with respect to signal detection capability is described. A unique coherence function (the hyper-coherence) was developed through the course of this investigation, which appears promising as a diagnostic tool. This technique and several other non-linear methods of signal analysis are presented and illustrated by application. Software for application of these techniques has been installed on the signal processing system at the NASA/MSFC Systems Dynamics Laboratory.

New methods of multimode fiber interferometer signal processing

NASA Astrophysics Data System (ADS)

Vitrik, Oleg B.; Kulchin, Yuri N.; Maxaev, Oleg G.; Kirichenko, Oleg V.; Kamenev, Oleg T.; Petrov, Yuri S.

1995-06-01

New methods of multimode fiber interferometers signal processing are suggested. For scheme of single fiber multimode interferometers with two excited modes, the method based on using of special fiber unit is developed. This unit provides the modes interaction and further sum optical field filtering. As a result the amplitude of output signal is modulated by external influence on interferometer. The stabilization of interferometer sensitivity is achieved by using additional special modulation of output signal. For scheme of single fiber multimode interferometers with excitation of wide mode spectrum, the signal of intermode interference is registered by photodiode matrix and then special electronic unit performs correlation processing. For elimination of temperature destabilization, the registered signal is adopted to multimode interferometers optical signal temperature changes. The achieved parameters for double mode scheme: temporary stability--0.6% per hour, sensitivity to interferometer length deviations--3,2 nm; for multimode scheme: temperature stability--(0.5%)/(K), temporary nonstability--0.2% per hour, sensitivity to interferometer length deviations--20 nm, dynamic range--35 dB.

Multi-GNSS high-rate RTK, PPP and novel direct phase observation processing method: application to precise dynamic displacement detection

NASA Astrophysics Data System (ADS)

Paziewski, Jacek; Sieradzki, Rafal; Baryla, Radoslaw

2018-03-01

This paper provides the methodology and performance assessment of multi-GNSS signal processing for the detection of small-scale high-rate dynamic displacements. For this purpose, we used methods of relative (RTK) and absolute positioning (PPP), and a novel direct signal processing approach. The first two methods are recognized as providing accurate information on position in many navigation and surveying applications. The latter is an innovative method for dynamic displacement determination with the use of GNSS phase signal processing. This method is based on the developed functional model with parametrized epoch-wise topocentric relative coordinates derived from filtered GNSS observations. Current regular kinematic PPP positioning, as well as medium/long range RTK, may not offer coordinate estimates with subcentimeter precision. Thus, extended processing strategies of absolute and relative GNSS positioning have been developed and applied for displacement detection. The study also aimed to comparatively analyze the developed methods as well as to analyze the impact of combined GPS and BDS processing and the dependence of the results of the relative methods on the baseline length. All the methods were implemented with in-house developed software allowing for high-rate precise GNSS positioning and signal processing. The phase and pseudorange observations collected with a rate of 50 Hz during the field test served as the experiment’s data set. The displacements at the rover station were triggered in the horizontal plane using a device which was designed and constructed to ensure a periodic motion of GNSS antenna with an amplitude of ~3 cm and a frequency of ~4.5 Hz. Finally, a medium range RTK, PPP, and direct phase observation processing method demonstrated the capability of providing reliable and consistent results with the precision of the determined dynamic displacements at the millimeter level. Specifically, the research shows that the standard deviation of the displacement residuals obtained as the difference between a benchmark-ultra-short baseline RTK solution and selected scenarios ranged between 1.1 and 3.4 mm. At the same time, the differences in the mean amplitude of the oscillations derived from the established scenarios did not exceed 1.3 mm, whereas the frequency of the motion detected with the use of Fourier transformation was the same.

Using Imaging Methods to Interrogate Radiation-Induced Cell Signaling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shankaran, Harish; Weber, Thomas J.; Freiin von Neubeck, Claere H.

2012-04-01

There is increasing emphasis on the use of systems biology approaches to define radiation induced responses in cells and tissues. Such approaches frequently rely on global screening using various high throughput 'omics' platforms. Although these methods are ideal for obtaining an unbiased overview of cellular responses, they often cannot reflect the inherent heterogeneity of the system or provide detailed spatial information. Additionally, performing such studies with multiple sampling time points can be prohibitively expensive. Imaging provides a complementary method with high spatial and temporal resolution capable of following the dynamics of signaling processes. In this review, we utilize specific examplesmore » to illustrate how imaging approaches have furthered our understanding of radiation induced cellular signaling. Particular emphasis is placed on protein co-localization, and oscillatory and transient signaling dynamics.« less

I. Advances in NMR Signal Processing. II. Spin Dynamics in Quantum Dissipative Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Yung-Ya

1998-11-01

Part I. Advances in IVMR Signal Processing. Improvements of sensitivity and resolution are two major objects in the development of NMR/MRI. A signal enhancement method is first presented which recovers signal from noise by a judicious combination of a priordmowledge to define the desired feasible solutions and a set theoretic estimation for restoring signal properties that have been lost due to noise contamination. The effect of noise can be significantly mitigated through the process of iteratively modifying the noisy data set to the smallest degree necessary so that it possesses a collection of prescribed properties and also lies closest tomore » the original data set. A novel detection-estimation scheme is then introduced to analyze noisy and/or strongly damped or truncated FIDs. Based on exponential modeling, the number of signals is detected based on information estimated using the matrix pencil method. theory and the spectral parameters are Part II. Spin Dynamics in body dipole-coupled systems Quantum Dissipative Systems. Spin dynamics in manyconstitutes one of the most fundamental problems in magnetic resonance and condensed-matter physics. Its many-spin nature precludes any rigorous treatment. ‘Therefore, the spin-boson model is adopted to describe in the rotating frame the influence of the dipolar local fields on a tagged spin. Based on the polaronic transform and a perturbation treatment, an analytical solution is derived, suggesting the existence of self-trapped states in the. strong coupling limit, i.e., when transverse local field >> longitudinal local field. Such nonlinear phenomena originate from the joint action of the lattice fluctuations and the reaction field. Under semiclassical approximation, it is found that the main effect of the reaction field is the renormalization of the Hamiltonian of interest. Its direct consequence is the two-step relaxation process: the spin is initially localized in a quasiequilibrium state, which is later detrapped by the lattice fluctuations in an extended time scale. Lowtemperature measurements and classical-spin simulations are carried out to verify the above analysis. To promote the implementation and future study on the topics described in this thesis, program packages of advanced NMR signal processing and many-spin FID simulations are summarized and listed in the Appendix.« less

Dimensional analysis of acoustically propagated signals

NASA Technical Reports Server (NTRS)

Hansen, Scott D.; Thomson, Dennis W.

1993-01-01

Traditionally, long term measurements of atmospherically propagated sound signals have consisted of time series of multiminute averages. Only recently have continuous measurements with temporal resolution corresponding to turbulent time scales been available. With modern digital data acquisition systems we now have the capability to simultaneously record both acoustical and meteorological parameters with sufficient temporal resolution to allow us to examine in detail relationships between fluctuating sound and the meteorological variables, particularly wind and temperature, which locally determine the acoustic refractive index. The atmospheric acoustic propagation medium can be treated as a nonlinear dynamical system, a kind of signal processor whose innards depend on thermodynamic and turbulent processes in the atmosphere. The atmosphere is an inherently nonlinear dynamical system. In fact one simple model of atmospheric convection, the Lorenz system, may well be the most widely studied of all dynamical systems. In this paper we report some results of our having applied methods used to characterize nonlinear dynamical systems to study the characteristics of acoustical signals propagated through the atmosphere. For example, we investigate whether or not it is possible to parameterize signal fluctuations in terms of fractal dimensions. For time series one such parameter is the limit capacity dimension. Nicolis and Nicolis were among the first to use the kind of methods we have to study the properties of low dimension global attractors.

Applied Nonlinear Dynamics and Stochastic Systems Near The Millenium. Proceedings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kadtke, J.B.; Bulsara, A.

These proceedings represent papers presented at the Applied Nonlinear Dynamics and Stochastic Systems conference held in San Diego, California in July 1997. The conference emphasized the applications of nonlinear dynamical systems theory in fields as diverse as neuroscience and biomedical engineering, fluid dynamics, chaos control, nonlinear signal/image processing, stochastic resonance, devices and nonlinear dynamics in socio{minus}economic systems. There were 56 papers presented at the conference and 5 have been abstracted for the Energy Science and Technology database.(AIP)

Computer Vision for Artificially Intelligent Robotic Systems

NASA Astrophysics Data System (ADS)

Ma, Chialo; Ma, Yung-Lung

1987-04-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts -- position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed bye the main control unit. In Pulse-Echo Signal Process Unit, we ultilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by u law coding method, and this data together with delay time T, angle information OH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Model, we use a narrow beam transducer and it's input voltage is 50V p-p. A RobOt equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Improved Performance Characteristics For Indium Antimonide Photovoltaic Detector Arrays Using A FET-Switched Multiplexing Technique

NASA Astrophysics Data System (ADS)

Ma, Yung-Lung; Ma, Chialo

1987-03-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts _ position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed by the main control unit. In Pulse-Echo Signal Process Unit, we utilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by p law coding method, and this data together with delay time T, angle information eH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Models, we use a narrow beam transducer and it's input voltage is 50V p-p. A Robot equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Nonlinear digital signal processing in mental health: characterization of major depression using instantaneous entropy measures of heartbeat dynamics.

PubMed

Valenza, Gaetano; Garcia, Ronald G; Citi, Luca; Scilingo, Enzo P; Tomaz, Carlos A; Barbieri, Riccardo

2015-01-01

Nonlinear digital signal processing methods that address system complexity have provided useful computational tools for helping in the diagnosis and treatment of a wide range of pathologies. More specifically, nonlinear measures have been successful in characterizing patients with mental disorders such as Major Depression (MD). In this study, we propose the use of instantaneous measures of entropy, namely the inhomogeneous point-process approximate entropy (ipApEn) and the inhomogeneous point-process sample entropy (ipSampEn), to describe a novel characterization of MD patients undergoing affective elicitation. Because these measures are built within a nonlinear point-process model, they allow for the assessment of complexity in cardiovascular dynamics at each moment in time. Heartbeat dynamics were characterized from 48 healthy controls and 48 patients with MD while emotionally elicited through either neutral or arousing audiovisual stimuli. Experimental results coming from the arousing tasks show that ipApEn measures are able to instantaneously track heartbeat complexity as well as discern between healthy subjects and MD patients. Conversely, standard heart rate variability (HRV) analysis performed in both time and frequency domains did not show any statistical significance. We conclude that measures of entropy based on nonlinear point-process models might contribute to devising useful computational tools for care in mental health.

Fault Detection and Diagnosis In Hall-Héroult Cells Based on Individual Anode Current Measurements Using Dynamic Kernel PCA

NASA Astrophysics Data System (ADS)

Yao, Yuchen; Bao, Jie; Skyllas-Kazacos, Maria; Welch, Barry J.; Akhmetov, Sergey

2018-04-01

Individual anode current signals in aluminum reduction cells provide localized cell conditions in the vicinity of each anode, which contain more information than the conventionally measured cell voltage and line current. One common use of this measurement is to identify process faults that can cause significant changes in the anode current signals. While this method is simple and direct, it ignores the interactions between anode currents and other important process variables. This paper presents an approach that applies multivariate statistical analysis techniques to individual anode currents and other process operating data, for the detection and diagnosis of local process abnormalities in aluminum reduction cells. Specifically, since the Hall-Héroult process is time-varying with its process variables dynamically and nonlinearly correlated, dynamic kernel principal component analysis with moving windows is used. The cell is discretized into a number of subsystems, with each subsystem representing one anode and cell conditions in its vicinity. The fault associated with each subsystem is identified based on multivariate statistical control charts. The results show that the proposed approach is able to not only effectively pinpoint the problematic areas in the cell, but also assess the effect of the fault on different parts of the cell.

Karst aquifer characterization using geophysical remote sensing of dynamic recharge events

NASA Astrophysics Data System (ADS)

Grapenthin, R.; Bilek, S. L.; Luhmann, A. J.

2017-12-01

Geophysical monitoring techniques, long used to make significant advances in a wide range of deeper Earth science disciplines, are now being employed to track surficial processes such as landslide, glacier, and river flow. Karst aquifers are another important hydrologic resource that can benefit from geophysical remote sensing, as this monitoring allows for safe, noninvasive karst conduit measurements. Conduit networks are typically poorly constrained, let alone the processes that occur within them. Geophysical monitoring can also provide a regionally integrated analysis to characterize subsurface architecture and to understand the dynamics of flow and recharge processes in karst aquifers. Geophysical signals are likely produced by several processes during recharge events in karst aquifers. For example, pressure pulses occur when water enters conduits that are full of water, and experiments suggest seismic signals result from this process. Furthermore, increasing water pressure in conduits during recharge events increases the load applied to conduit walls, which deforms the surrounding rock to yield measureable surface displacements. Measureable deformation should also occur with mass loading, with subsidence and rebound signals associated with increases and decreases of water mass stored in the aquifer, respectively. Additionally, geophysical signals will likely arise with turbulent flow and pore pressure change in the rock surrounding conduits. Here we present seismic data collected during a pilot study of controlled and natural recharge events in a karst aquifer system near Bear Spring, near Eyota, MN, USA as well as preliminary model results regarding the processes described above. In addition, we will discuss an upcoming field campaign where we will use seismometers, tiltmeters, and GPS instruments to monitor for recharge-induced responses in a FL, USA karst system with existing cave maps, coupling these geophysical observations with hydrologic and meteorologic data to map and characterize conduits and other features of the larger karst system and to monitor subsurface flow dynamics during recharge events.

Noise shaping in populations of coupled model neurons.

PubMed

Mar, D J; Chow, C C; Gerstner, W; Adams, R W; Collins, J J

1999-08-31

Biological information-processing systems, such as populations of sensory and motor neurons, may use correlations between the firings of individual elements to obtain lower noise levels and a systemwide performance improvement in the dynamic range or the signal-to-noise ratio. Here, we implement such correlations in networks of coupled integrate-and-fire neurons using inhibitory coupling and demonstrate that this can improve the system dynamic range and the signal-to-noise ratio in a population rate code. The improvement can surpass that expected for simple averaging of uncorrelated elements. A theory that predicts the resulting power spectrum is developed in terms of a stochastic point-process model in which the instantaneous population firing rate is modulated by the coupling between elements.

FIBER AND INTEGRATED OPTICS. OPTOELECTRONICS: Some characteristics of formation of volume dynamic holograms by concurrent waves propagating in resonant atomic media

NASA Astrophysics Data System (ADS)

Kirilenko, A. K.

1989-07-01

An investigation was made of the transient process of formation of volume dynamic holograms by light within the spectral limits of the D2 resonant absorption line of sodium. The observed asymmetry of the spectral distribution of the gain of the signal waves in the case of a concurrent interaction between four beams was attributed to different mechanisms of the interaction, the main of which were a four-wave interaction in the long-wavelength wing and transient two-beam energy transfer in the short-wavelength wing. The results obtained were used to recommend an experimental method for the determination of the relative contributions of these processes to the amplification of signal waves.

Fusion of spectral models for dynamic modeling of sEMG and skeletal muscle force.

PubMed

Potluri, Chandrasekhar; Anugolu, Madhavi; Chiu, Steve; Urfer, Alex; Schoen, Marco P; Naidu, D Subbaram

2012-01-01

In this paper, we present a method of combining spectral models using a Kullback Information Criterion (KIC) data fusion algorithm. Surface Electromyographic (sEMG) signals and their corresponding skeletal muscle force signals are acquired from three sensors and pre-processed using a Half-Gaussian filter and a Chebyshev Type- II filter, respectively. Spectral models - Spectral Analysis (SPA), Empirical Transfer Function Estimate (ETFE), Spectral Analysis with Frequency Dependent Resolution (SPFRD) - are extracted from sEMG signals as input and skeletal muscle force as output signal. These signals are then employed in a System Identification (SI) routine to establish the dynamic models relating the input and output. After the individual models are extracted, the models are fused by a probability based KIC fusion algorithm. The results show that the SPFRD spectral models perform better than SPA and ETFE models in modeling the frequency content of the sEMG/skeletal muscle force data.

Elucidating the Functional Roles of Spatial Organization in Cross-Membrane Signal Transduction by a Hybrid Simulation Method.

PubMed

Chen, Jiawen; Xie, Zhong-Ru; Wu, Yinghao

2016-07-01

The ligand-binding of membrane receptors on cell surfaces initiates the dynamic process of cross-membrane signal transduction. It is an indispensable part of the signaling network for cells to communicate with external environments. Recent experiments revealed that molecular components in signal transduction are not randomly mixed, but spatially organized into distinctive patterns. These patterns, such as receptor clustering and ligand oligomerization, lead to very different gene expression profiles. However, little is understood about the molecular mechanisms and functional impacts of this spatial-temporal regulation in cross-membrane signal transduction. In order to tackle this problem, we developed a hybrid computational method that decomposes a model of signaling network into two simulation modules. The physical process of binding between receptors and ligands on cell surfaces are simulated by a diffusion-reaction algorithm, while the downstream biochemical reactions are modeled by stochastic simulation of Gillespie algorithm. These two processes are coupled together by a synchronization framework. Using this method, we tested the dynamics of a simple signaling network in which the ligand binding of cell surface receptors triggers the phosphorylation of protein kinases, and in turn regulates the expression of target genes. We found that spatial aggregation of membrane receptors at cellular interfaces is able to either amplify or inhibit downstream signaling outputs, depending on the details of clustering mechanism. Moreover, by providing higher binding avidity, the co-localization of ligands into multi-valence complex modulates signaling in very different ways that are closely related to the binding affinity between ligand and receptor. We also found that the temporal oscillation of the signaling pathway that is derived from genetic feedback loops can be modified by the spatial clustering of membrane receptors. In summary, our method demonstrates the functional importance of spatial organization in cross-membrane signal transduction. The method can be applied to any specific signaling pathway in cells.

Demodulation processes in auditory perception

NASA Astrophysics Data System (ADS)

Feth, Lawrence L.

1994-08-01

The long range goal of this project is the understanding of human auditory processing of information conveyed by complex, time-varying signals such as speech, music or important environmental sounds. Our work is guided by the assumption that human auditory communication is a 'modulation - demodulation' process. That is, we assume that sound sources produce a complex stream of sound pressure waves with information encoded as variations ( modulations) of the signal amplitude and frequency. The listeners task then is one of demodulation. Much of past. psychoacoustics work has been based in what we characterize as 'spectrum picture processing.' Complex sounds are Fourier analyzed to produce an amplitude-by-frequency 'picture' and the perception process is modeled as if the listener were analyzing the spectral picture. This approach leads to studies such as 'profile analysis' and the power-spectrum model of masking. Our approach leads us to investigate time-varying, complex sounds. We refer to them as dynamic signals and we have developed auditory signal processing models to help guide our experimental work.

Continued reduction and analysis of data from the Dynamics Explorer Plasma Wave Instrument

NASA Technical Reports Server (NTRS)

Gurnett, Donald A.; Weimer, Daniel R.

1994-01-01

The plasma wave instrument on the Dynamics Explorer 1 spacecraft provided measurements of the electric and magnetic components of plasma waves in the Earth's magnetosphere. Four receiver systems processed signals from five antennas. Sixty-seven theses, scientific papers and reports were prepared from the data generated. Data processing activities and techniques used to analyze the data are described and highlights of discoveries made and research undertaken are tabulated.

Functional Imaging of Retinal Photoreceptors and Inner Neurons Using Stimulus-Evoked Intrinsic Optical Signals

PubMed Central

Yao, Xin-Cheng; Li, Yi-Chao

2013-01-01

Retinal development is a dynamic process both anatomically and functionally. High-resolution imaging and dynamic monitoring of photoreceptors and inner neurons can provide important information regarding the structure and function of the developing retina. In this chapter, we describe intrinsic optical signal (IOS) imaging as a high spatiotemporal resolution method for functional study of living retinal tissues. IOS imaging is based on near infrared (NIR) light detection of stimulus-evoked transient change of inherent optical characteristics of the cells. With no requirement for exogenous biomarkers, IOS imaging is totally noninvasive for functional mapping of stimulus-evoked spatiotemporal dynamics of the photoreceptors and inner retinal neurons. PMID:22688714

SPECIAL ISSUE ON OPTICAL PROCESSING OF INFORMATION: Circulatory fibre-optic memory loop with a built-in service channel

NASA Astrophysics Data System (ADS)

Pilipovich, V. A.; Esman, A. K.; Goncharenko, I. A.; Posed'ko, V. S.; Solonovich, I. F.

1995-10-01

A method for increasing the information capacity and enhancing the reliability of information storage in a dynamic fibre-optic memory is proposed. An additional built-in channel with counterpropagating circulation of signals is provided for this purpose. This additional channel can be used to transmit both information and service signals, such as address words, clock signals, correcting sequences, etc. The possibility of compensating the attenuation of an information signal by stimulated Raman scattering is considered.

Crk1/2-dependent signaling is necessary for podocyte foot process spreading in mouse models of glomerular disease

PubMed Central

George, Britta; Verma, Rakesh; Soofi, Abdulsalam A.; Garg, Puneet; Zhang, Jidong; Park, Tae-Ju; Giardino, Laura; Ryzhova, Larisa; Johnstone, Duncan B.; Wong, Hetty; Nihalani, Deepak; Salant, David J.; Hanks, Steven K.; Curran, Tom; Rastaldi, Maria Pia; Holzman, Lawrence B.

2012-01-01

The morphology of healthy podocyte foot processes is necessary for maintaining the characteristics of the kidney filtration barrier. In most forms of glomerular disease, abnormal filter barrier function results when podocytes undergo foot process spreading and retraction by remodeling their cytoskeletal architecture and intercellular junctions during a process known as effacement. The cell adhesion protein nephrin is necessary for establishing the morphology of the kidney podocyte in development by transducing from the specialized podocyte intercellular junction phosphorylation-mediated signals that regulate cytoskeletal dynamics. The present studies extend our understanding of nephrin function by showing that nephrin activation in cultured podocytes induced actin dynamics necessary for lamellipodial protrusion. This process required a PI3K-, Cas-, and Crk1/2-dependent signaling mechanism distinct from the previously described nephrin-Nck1/2 pathway necessary for assembly and polymerization of actin filaments. Our present findings also support the hypothesis that mechanisms governing lamellipodial protrusion in culture are similar to those used in vivo during foot process effacement in a subset of glomerular diseases. In mice, podocyte-specific deletion of Crk1/2 prevented foot process effacement in one model of podocyte injury and attenuated foot process effacement and associated proteinuria in a delayed fashion in a second model. In humans, focal adhesion kinase and Cas phosphorylation — markers of focal adhesion complex–mediated Crk-dependent signaling — was induced in minimal change disease and membranous nephropathy, but not focal segmental glomerulosclerosis. Together, these observations suggest that activation of a Cas-Crk1/2–dependent complex is necessary for foot process effacement observed in distinct subsets of human glomerular diseases. PMID:22251701

Optically modulated fluorescence bioimaging: visualizing obscured fluorophores in high background.

PubMed

Hsiang, Jung-Cheng; Jablonski, Amy E; Dickson, Robert M

2014-05-20

Fluorescence microscopy and detection have become indispensible for understanding organization and dynamics in biological systems. Novel fluorophores with improved brightness, photostability, and biocompatibility continue to fuel further advances but often rely on having minimal background. The visualization of interactions in very high biological background, especially for proteins or bound complexes at very low copy numbers, remains a primary challenge. Instead of focusing on molecular brightness of fluorophores, we have adapted the principles of high-sensitivity absorption spectroscopy to improve the sensitivity and signal discrimination in fluorescence bioimaging. Utilizing very long wavelength transient absorptions of kinetically trapped dark states, we employ molecular modulation schemes that do not simultaneously modulate the background fluorescence. This improves the sensitivity and ease of implementation over high-energy photoswitch-based recovery schemes, as no internal dye reference or nanoparticle-based fluorophores are needed to separate the desired signals from background. In this Account, we describe the selection process for and identification of fluorophores that enable optically modulated fluorescence to decrease obscuring background. Differing from thermally stable photoswitches using higher-energy secondary lasers, coillumination at very low energies depopulates transient dark states, dynamically altering the fluorescence and giving characteristic modulation time scales for each modulatable emitter. This process is termed synchronously amplified fluorescence image recovery (SAFIRe) microscopy. By understanding and optically controlling the dye photophysics, we selectively modulate desired fluorophore signals independent of all autofluorescent background. This shifts the fluorescence of interest to unique detection frequencies with nearly shot-noise-limited detection, as no background signals are collected. Although the fluorescence brightness is improved slightly, SAFIRe yields up to 100-fold improved signal visibility by essentially removing obscuring, unmodulated background (Richards, C. I.; J. Am. Chem. Soc. 2009, 131, 4619). While SAFIRe exhibits a wide, linear dynamic range, we have demonstrated single-molecule signal recovery buried within 200 nM obscuring dye. In addition to enabling signal recovery through background reduction, each dye exhibits a characteristic modulation frequency indicative of its photophysical dynamics. Thus, these characteristic time scales offer opportunities not only to expand the dimensionality of fluorescence imaging by using dark-state lifetimes but also to distinguish the dynamics of subpopulations on the basis of photophysical versus diffusional time scales, even within modulatable populations. The continued development of modulation for signal recovery and observation of biological dynamics holds great promise for studying a range of transient biological phenomena in natural environments. Through the development of a wide range of fluorescent proteins, organic dyes, and inorganic emitters that exhibit significant dark-state populations under steady-state illumination, we can drastically expand the applicability of fluorescence imaging to probe lower-abundance complexes and their dynamics.

The contribution of dynamic visual cues to audiovisual speech perception.

PubMed

Jaekl, Philip; Pesquita, Ana; Alsius, Agnes; Munhall, Kevin; Soto-Faraco, Salvador

2015-08-01

Seeing a speaker's facial gestures can significantly improve speech comprehension, especially in noisy environments. However, the nature of the visual information from the speaker's facial movements that is relevant for this enhancement is still unclear. Like auditory speech signals, visual speech signals unfold over time and contain both dynamic configural information and luminance-defined local motion cues; two information sources that are thought to engage anatomically and functionally separate visual systems. Whereas, some past studies have highlighted the importance of local, luminance-defined motion cues in audiovisual speech perception, the contribution of dynamic configural information signalling changes in form over time has not yet been assessed. We therefore attempted to single out the contribution of dynamic configural information to audiovisual speech processing. To this aim, we measured word identification performance in noise using unimodal auditory stimuli, and with audiovisual stimuli. In the audiovisual condition, speaking faces were presented as point light displays achieved via motion capture of the original talker. Point light displays could be isoluminant, to minimise the contribution of effective luminance-defined local motion information, or with added luminance contrast, allowing the combined effect of dynamic configural cues and local motion cues. Audiovisual enhancement was found in both the isoluminant and contrast-based luminance conditions compared to an auditory-only condition, demonstrating, for the first time the specific contribution of dynamic configural cues to audiovisual speech improvement. These findings imply that globally processed changes in a speaker's facial shape contribute significantly towards the perception of articulatory gestures and the analysis of audiovisual speech. Copyright © 2015 Elsevier Ltd. All rights reserved.

Hybrid photonic signal processing

NASA Astrophysics Data System (ADS)

Ghauri, Farzan Naseer

This thesis proposes research of novel hybrid photonic signal processing systems in the areas of optical communications, test and measurement, RF signal processing and extreme environment optical sensors. It will be shown that use of innovative hybrid techniques allows design of photonic signal processing systems with superior performance parameters and enhanced capabilities. These applications can be divided into domains of analog-digital hybrid signal processing applications and free-space---fiber-coupled hybrid optical sensors. The analog-digital hybrid signal processing applications include a high-performance analog-digital hybrid MEMS variable optical attenuator that can simultaneously provide high dynamic range as well as high resolution attenuation controls; an analog-digital hybrid MEMS beam profiler that allows high-power watt-level laser beam profiling and also provides both submicron-level high resolution and wide area profiling coverage; and all optical transversal RF filters that operate on the principle of broadband optical spectral control using MEMS and/or Acousto-Optic tunable Filters (AOTF) devices which can provide continuous, digital or hybrid signal time delay and weight selection. The hybrid optical sensors presented in the thesis are extreme environment pressure sensors and dual temperature-pressure sensors. The sensors employ hybrid free-space and fiber-coupled techniques for remotely monitoring a system under simultaneous extremely high temperatures and pressures.

Elementary signaling modes predict the essentiality of signal transduction network components

PubMed Central

2011-01-01

Background Understanding how signals propagate through signaling pathways and networks is a central goal in systems biology. Quantitative dynamic models help to achieve this understanding, but are difficult to construct and validate because of the scarcity of known mechanistic details and kinetic parameters. Structural and qualitative analysis is emerging as a feasible and useful alternative for interpreting signal transduction. Results In this work, we present an integrative computational method for evaluating the essentiality of components in signaling networks. This approach expands an existing signaling network to a richer representation that incorporates the positive or negative nature of interactions and the synergistic behaviors among multiple components. Our method simulates both knockout and constitutive activation of components as node disruptions, and takes into account the possible cascading effects of a node's disruption. We introduce the concept of elementary signaling mode (ESM), as the minimal set of nodes that can perform signal transduction independently. Our method ranks the importance of signaling components by the effects of their perturbation on the ESMs of the network. Validation on several signaling networks describing the immune response of mammals to bacteria, guard cell abscisic acid signaling in plants, and T cell receptor signaling shows that this method can effectively uncover the essentiality of components mediating a signal transduction process and results in strong agreement with the results of Boolean (logical) dynamic models and experimental observations. Conclusions This integrative method is an efficient procedure for exploratory analysis of large signaling and regulatory networks where dynamic modeling or experimental tests are impractical. Its results serve as testable predictions, provide insights into signal transduction and regulatory mechanisms and can guide targeted computational or experimental follow-up studies. The source codes for the algorithms developed in this study can be found at http://www.phys.psu.edu/~ralbert/ESM. PMID:21426566

Implication of high dynamic range and wide color gamut content distribution

NASA Astrophysics Data System (ADS)

Lu, Taoran; Pu, Fangjun; Yin, Peng; Chen, Tao; Husak, Walt

2015-09-01

High Dynamic Range (HDR) and Wider Color Gamut (WCG) content represents a greater range of luminance levels and a more complete reproduction of colors found in real-world scenes. The current video distribution environments deliver Standard Dynamic Range (SDR) signal. Therefore, there might be some significant implication on today's end-to-end ecosystem from content creation to distribution and finally to consumption. For SDR content, the common practice is to apply compression on Y'CbCr 4:2:0 using gamma transfer function and non-constant luminance 4:2:0 chroma subsampling. For HDR and WCG content, it is desirable to examine if such signal format still works well for compression, and it is interesting to know if the overall system performance can be further improved by exploring different signal formats and processing workflows. In this paper, we will provide some of our insight into those problems.

Automatic detection of slight parameter changes associated to complex biomedical signals using multiresolution q-entropy1.

PubMed

Torres, M E; Añino, M M; Schlotthauer, G

2003-12-01

It is well known that, from a dynamical point of view, sudden variations in physiological parameters which govern certain diseases can cause qualitative changes in the dynamics of the corresponding physiological process. The purpose of this paper is to introduce a technique that allows the automated temporal localization of slight changes in a parameter of the law that governs the nonlinear dynamics of a given signal. This tool takes, from the multiresolution entropies, the ability to show these changes as statistical variations at each scale. These variations are held in the corresponding principal component. Appropriately combining these techniques with a statistical changes detector, a complexity change detection algorithm is obtained. The relevance of the approach, together with its robustness in the presence of moderate noise, is discussed in numerical simulations and the automatic detector is applied to real and simulated biological signals.

Theoretical analysis of degradation mechanisms in the formation of morphogen gradients

NASA Astrophysics Data System (ADS)

Bozorgui, Behnaz; Teimouri, Hamid; Kolomeisky, Anatoly B.

2015-07-01

Fundamental biological processes of development of tissues and organs in multicellular organisms are governed by various signaling molecules, which are called morphogens. It is known that spatial and temporal variations in the concentration profiles of signaling molecules, which are frequently referred as morphogen gradients, lead to a cell differentiation via activating specific genes in a concentration-dependent manner. It is widely accepted that the establishment of the morphogen gradients involves multiple biochemical reactions and diffusion processes. One of the critical elements in the formation of morphogen gradients is a degradation of signaling molecules. We develop a new theoretical approach that provides a comprehensive description of the degradation mechanisms. It is based on the idea that the degradation works as an effective potential that drives the signaling molecules away from the source region. Utilizing the method of first-passage processes, the dynamics of the formation of morphogen gradients for various degradation mechanisms is explicitly evaluated. It is found that linear degradation processes lead to a dynamic behavior specified by times to form the morphogen gradients that depend linearly on the distance from the source. This is because the effective potential due to the degradation is quite strong. At the same time, nonlinear degradation mechanisms yield a quadratic scaling in the morphogen gradients formation times since the effective potentials are much weaker. Physical-chemical explanations of these phenomena are presented.

A high-efficiency real-time digital signal averager for time-of-flight mass spectrometry.

PubMed

Wang, Yinan; Xu, Hui; Li, Qingjiang; Li, Nan; Huang, Zhengxu; Zhou, Zhen; Liu, Husheng; Sun, Zhaolin; Xu, Xin; Yu, Hongqi; Liu, Haijun; Li, David D-U; Wang, Xi; Dong, Xiuzhen; Gao, Wei

2013-05-30

Analog-to-digital converter (ADC)-based acquisition systems are widely applied in time-of-flight mass spectrometers (TOFMS) due to their ability to record the signal intensity of all ions within the same pulse. However, the acquisition system raises the requirement for data throughput, along with increasing the conversion rate and resolution of the ADC. It is therefore of considerable interest to develop a high-performance real-time acquisition system, which can relieve the limitation of data throughput. We present in this work a high-efficiency real-time digital signal averager, consisting of a signal conditioner, a data conversion module and a signal processing module. Two optimization strategies are implemented using field programmable gate arrays (FPGAs) to enhance the efficiency of the real-time processing. A pipeline procedure is used to reduce the time consumption of the accumulation strategy. To realize continuous data transfer, a high-efficiency transmission strategy is developed, based on a ping-pong procedure. The digital signal averager features good responsiveness, analog bandwidth and dynamic performance. The optimal effective number of bits reaches 6.7 bits. For a 32 µs record length, the averager can realize 100% efficiency with an extraction frequency below 31.23 kHz by modifying the number of accumulation steps. In unit time, the averager yields superior signal-to-noise ratio (SNR) compared with data accumulation in a computer. The digital signal averager is combined with a vacuum ultraviolet single-photon ionization time-of-flight mass spectrometer (VUV-SPI-TOFMS). The efficiency of the real-time processing is tested by analyzing the volatile organic compounds (VOCs) from ordinary printed materials. In these experiments, 22 kinds of compounds are detected, and the dynamic range exceeds 3 orders of magnitude. Copyright © 2013 John Wiley & Sons, Ltd.

Towards the understanding of network information processing in biology

NASA Astrophysics Data System (ADS)

Singh, Vijay

Living organisms perform incredibly well in detecting a signal present in the environment. This information processing is achieved near optimally and quite reliably, even though the sources of signals are highly variable and complex. The work in the last few decades has given us a fair understanding of how individual signal processing units like neurons and cell receptors process signals, but the principles of collective information processing on biological networks are far from clear. Information processing in biological networks, like the brain, metabolic circuits, cellular-signaling circuits, etc., involves complex interactions among a large number of units (neurons, receptors). The combinatorially large number of states such a system can exist in makes it impossible to study these systems from the first principles, starting from the interactions between the basic units. The principles of collective information processing on such complex networks can be identified using coarse graining approaches. This could provide insights into the organization and function of complex biological networks. Here I study models of biological networks using continuum dynamics, renormalization, maximum likelihood estimation and information theory. Such coarse graining approaches identify features that are essential for certain processes performed by underlying biological networks. We find that long-range connections in the brain allow for global scale feature detection in a signal. These also suppress the noise and remove any gaps present in the signal. Hierarchical organization with long-range connections leads to large-scale connectivity at low synapse numbers. Time delays can be utilized to separate a mixture of signals with temporal scales. Our observations indicate that the rules in multivariate signal processing are quite different from traditional single unit signal processing.

Thickness-dependent carrier and phonon dynamics of topological insulator Bi2Te3 thin films.

PubMed

Zhao, Jie; Xu, Zhongjie; Zang, Yunyi; Gong, Yan; Zheng, Xin; He, Ke; Cheng, Xiang'ai; Jiang, Tian

2017-06-26

As a new quantum state of matter, topological insulators offer a new platform for exploring new physics, giving rise to fascinating new phenomena and new devices. Lots of novel physical properties of topological insulators have been studied extensively and are attributed to the unique electron-phonon interactions at the surface. Although electron behavior in topological insulators has been studied in detail, electron-phonon interactions at the surface of topological insulators are less understood. In this work, using optical pump-optical probe technology, we performed transient absorbance measurement on Bi 2 Te 3 thin films to study the dynamics of its hot carrier relaxation process and coherent phonon behavior. The excitation and dynamics of phonon modes are observed with a response dependent on the thickness of the samples. The thickness-dependent characteristic time, amplitude and frequency of the damped oscillating signals are acquired by fitting the signal profiles. The results clearly indicate that the electron-hole recombination process gradually become dominant with the increasing thickness which is consistent with our theoretical calculation. In addition, a frequency modulation phenomenon on the high-frequency oscillation signals induced by coherent optical phonons is observed.

Retrograde Signals: Integrators of Interorganellar Communication and Orchestrators of Plant Development.

PubMed

de Souza, Amancio; Wang, Jin-Zheng; Dehesh, Katayoon

2017-04-28

Interorganellar cooperation maintained via exquisitely controlled retrograde-signaling pathways is an evolutionary necessity for maintenance of cellular homeostasis. This signaling feature has therefore attracted much research attention aimed at improving understanding of the nature of these communication signals, how the signals are sensed, and ultimately the mechanism by which they integrate targeted processes that collectively culminate in organellar cooperativity. The answers to these questions will provide insight into how retrograde-signal-mediated regulatory mechanisms are recruited and which biological processes are targeted, and will advance our understanding of how organisms balance metabolic investments in growth against adaptation to environmental stress. This review summarizes the present understanding of the nature and the functional complexity of retrograde signals as integrators of interorganellar communication and orchestrators of plant development, and offers a perspective on the future of this critical and dynamic area of research.

Rho'ing in and out of cells: viral interactions with Rho GTPase signaling.

PubMed

Van den Broeke, Céline; Jacob, Thary; Favoreel, Herman W

2014-01-01

Rho GTPases are key regulators of actin and microtubule dynamics and organization. Increasing evidence shows that many viruses have evolved diverse interactions with Rho GTPase signaling and manipulate them for their own benefit. In this review, we discuss how Rho GTPase signaling interferes with many steps in the viral replication cycle, especially entry, replication, and spread. Seen the diversity between viruses, it is not surprising that there is considerable variability in viral interactions with Rho GTPase signaling. However, several largely common effects on Rho GTPases and actin architecture and microtubule dynamics have been reported. For some of these processes, the molecular signaling and biological consequences are well documented while for others we just begin to understand them. A better knowledge and identification of common threads in the different viral interactions with Rho GTPase signaling and their ultimate consequences for virus and host may pave the way toward the development of new antiviral drugs that may target different viruses.

Design and application of pulse information acquisition and analysis system with dynamic recognition in traditional Chinese medicine.

PubMed

Zhang, Jian; Niu, Xin; Yang, Xue-zhi; Zhu, Qing-wen; Li, Hai-yan; Wang, Xuan; Zhang, Zhi-guo; Sha, Hong

2014-09-01

To design the pulse information which includes the parameter of pulse-position, pulse-number, pulse-shape and pulse-force acquisition and analysis system with function of dynamic recognition, and research the digitalization and visualization of some common cardiovascular mechanism of single pulse. To use some flexible sensors to catch the radial artery pressure pulse wave and utilize the high frequency B mode ultrasound scanning technology to synchronously obtain the information of radial extension and axial movement, by the way of dynamic images, then the gathered information was analyzed and processed together with ECG. Finally, the pulse information acquisition and analysis system was established which has the features of visualization and dynamic recognition, and it was applied to serve for ten healthy adults. The new system overcome the disadvantage of one-dimensional pulse information acquisition and process method which was common used in current research area of pulse diagnosis in traditional Chinese Medicine, initiated a new way of pulse diagnosis which has the new features of dynamic recognition, two-dimensional information acquisition, multiplex signals combination and deep data mining. The newly developed system could translate the pulse signals into digital, visual and measurable motion information of vessel.

Acid-base equilibrium in aqueous solutions of 1,3-dimethylbarbituric acid as studied by 13C NMR spectroscopy

NASA Astrophysics Data System (ADS)

Gryff-Keller, A.; Kraska-Dziadecka, A.

2011-12-01

13C NMR spectra of 1,3-dimethylbarbituric acid in aqueous solutions of various acidities and for various solute concentrations have been recorded and interpreted. The spectra recorded at pH = 2 and below contain the signals of the neutral solute molecule exclusively, while the ones recorded at pH = 7 and above only the signals of the appropriate anion, which has been confirmed by theoretical GIAO-DFT calculations. The signals in the spectra recorded for solutions of pH < 7 show dynamic broadenings. The lineshape analysis of these signals has provided information on the kinetics of the processes running in the dynamic acid-base equilibrium. The kinetic data determined this way have been used to clarify the mechanisms of these processes. The numerical analysis has shown that under the investigated conditions deprotonation of the neutral solute molecules undergoes not only via a simple transfer of the C-H proton to water molecules but also through a process with participation of the barbiturate anions. Moreover, the importance of tautomerism, or association, or both these phenomena for the kinetics of the acid-base transformations in the investigated system has been shown. Qualitatively similar changes of 13C NMR spectra with the solution pH variation have been observed for the parent barbituric acid.

Alteration of the Cortical Actin Cytoskeleton Deregulates Ca2+ Signaling, Monospermic Fertilization, and Sperm Entry

PubMed Central

Puppo, A.; Chun, Jong T.; Gragnaniello, Giovanni; Garante, Ezio; Santella, Luigia

2008-01-01

Background When preparing for fertilization, oocytes undergo meiotic maturation during which structural changes occur in the endoplasmic reticulum (ER) that lead to a more efficient calcium response. During meiotic maturation and subsequent fertilization, the actin cytoskeleton also undergoes dramatic restructuring. We have recently observed that rearrangements of the actin cytoskeleton induced by actin-depolymerizing agents, or by actin-binding proteins, strongly modulate intracellular calcium (Ca2+) signals during the maturation process. However, the significance of the dynamic changes in F-actin within the fertilized egg has been largely unclear. Methodology/Principal Findings We have measured changes in intracellular Ca2+ signals and F-actin structures during fertilization. We also report the unexpected observation that the conventional antagonist of the InsP3 receptor, heparin, hyperpolymerizes the cortical actin cytoskeleton in postmeiotic eggs. Using heparin and other pharmacological agents that either hypo- or hyperpolymerize the cortical actin, we demonstrate that nearly all aspects of the fertilization process are profoundly affected by the dynamic restructuring of the egg cortical actin cytoskeleton. Conclusions/Significance Our findings identify important roles for subplasmalemmal actin fibers in the process of sperm-egg interaction and in the subsequent events related to fertilization: the generation of Ca2+ signals, sperm penetration, cortical granule exocytosis, and the block to polyspermy. PMID:18974786

Dynamic Characteristics of Buildings from Signal Processing of Ambient Vibration

NASA Astrophysics Data System (ADS)

Dobre, Daniela; Sorin Dragomir, Claudiu

2017-10-01

The experimental technique used to determine the dynamic characteristics of buildings is based on records of low intensity oscillations of the building produced by various natural factors, such as permanent agitation type microseismic motions, city traffic, wind etc. The possibility of recording these oscillations is provided by the latest seismic stations (Geosig and Kinemetrics digital accelerographs). The permanent microseismic agitation of the soil is a complex form of stationary random oscillations. The building filters the soil excitation, selects and increases the components of disruptive vibrations corresponding to its natural vibration periods. For some selected buildings, with different instrumentation schemes for the location of sensors (in free-field, at basement, ground floor, roof level), a correlation between the dynamic characteristics resulted from signal processing of ambient vibration and from a theoretical analysis will be presented. The interpretation of recording results could highlight the behavior of the whole structure. On the other hand, these results are compared with those from strong motions, or obtained from a complex dynamic analysis, and they are quite different, but they are explicable.

Shock Acceleration of Electrons and Synchrotron Emission from the Dynamical Ejecta of Neutron Star Mergers

NASA Astrophysics Data System (ADS)

Lee, Shiu-Hang; Maeda, Keiichi; Kawanaka, Norita

2018-05-01

Neutron star mergers (NSMs) eject energetic subrelativistic dynamical ejecta into circumbinary media. Analogous to supernovae and supernova remnants, the NSM dynamical ejecta are expected to produce nonthermal emission by electrons accelerated at a shock wave. In this paper, we present the expected radio and X-ray signals by this mechanism, taking into account nonlinear diffusive shock acceleration (DSA) and magnetic field amplification. We suggest that the NSM is unique as a DSA site, where the seed relativistic electrons are abundantly provided by the decays of r-process elements. The signal is predicted to peak at a few 100–1000 days after the merger, determined by the balance between the decrease of the number of seed electrons and the increase of the dissipated kinetic energy, due to the shock expansion. While the resulting flux can ideally reach the maximum flux expected from near-equipartition, the available kinetic energy dissipation rate of the NSM ejecta limits the detectability of such a signal. It is likely that the radio and X-ray emission are overwhelmed by other mechanisms (e.g., an off-axis jet) for an observer placed in a jet direction (i.e., for GW170817). However, for an off-axis observer, to be discovered once a number of NSMs are identified, the dynamical ejecta component is predicted to dominate the nonthermal emission. While the detection of this signal is challenging even with near-future facilities, this potentially provides a robust probe of the creation of r-process elements in NSMs.

A Surrogate Technique for Investigating Deterministic Dynamics in Discrete Human Movement.

PubMed

Taylor, Paul G; Small, Michael; Lee, Kwee-Yum; Landeo, Raul; O'Meara, Damien M; Millett, Emma L

2016-10-01

Entropy is an effective tool for investigation of human movement variability. However, before applying entropy, it can be beneficial to employ analyses to confirm that observed data are not solely the result of stochastic processes. This can be achieved by contrasting observed data with that produced using surrogate methods. Unlike continuous movement, no appropriate method has been applied to discrete human movement. This article proposes a novel surrogate method for discrete movement data, outlining the processes for determining its critical values. The proposed technique reliably generated surrogates for discrete joint angle time series, destroying fine-scale dynamics of the observed signal, while maintaining macro structural characteristics. Comparison of entropy estimates indicated observed signals had greater regularity than surrogates and were not only the result of stochastic but also deterministic processes. The proposed surrogate method is both a valid and reliable technique to investigate determinism in other discrete human movement time series.

A signal processing framework for simultaneous detection of multiple environmental contaminants

NASA Astrophysics Data System (ADS)

Chakraborty, Subhadeep; Manahan, Michael P.; Mench, Matthew M.

2013-11-01

The possibility of large-scale attacks using chemical warfare agents (CWAs) has exposed the critical need for fundamental research enabling the reliable, unambiguous and early detection of trace CWAs and toxic industrial chemicals. This paper presents a unique approach for the identification and classification of simultaneously present multiple environmental contaminants by perturbing an electrochemical (EC) sensor with an oscillating potential for the extraction of statistically rich information from the current response. The dynamic response, being a function of the degree and mechanism of contamination, is then processed with a symbolic dynamic filter for the extraction of representative patterns, which are then classified using a trained neural network. The approach presented in this paper promises to extend the sensing power and sensitivity of these EC sensors by augmenting and complementing sensor technology with state-of-the-art embedded real-time signal processing capabilities.

Roles of Diffusion Dynamics in Stem Cell Signaling and Three-Dimensional Tissue Development.

PubMed

McMurtrey, Richard J

2017-09-15

Recent advancements in the ability to construct three-dimensional (3D) tissues and organoids from stem cells and biomaterials have not only opened abundant new research avenues in disease modeling and regenerative medicine but also have ignited investigation into important aspects of molecular diffusion in 3D cellular architectures. This article describes fundamental mechanics of diffusion with equations for modeling these dynamic processes under a variety of scenarios in 3D cellular tissue constructs. The effects of these diffusion processes and resultant concentration gradients are described in the context of the major molecular signaling pathways in stem cells that both mediate and are influenced by gas and nutrient concentrations, including how diffusion phenomena can affect stem cell state, cell differentiation, and metabolic states of the cell. The application of these diffusion models and pathways is of vital importance for future studies of developmental processes, disease modeling, and tissue regeneration.

Intrinsic noise analysis and stochastic simulation on transforming growth factor beta signal pathway

NASA Astrophysics Data System (ADS)

Wang, Lu; Ouyang, Qi

2010-10-01

A typical biological cell lives in a small volume at room temperature; the noise effect on the cell signal transduction pathway may play an important role in its dynamics. Here, using the transforming growth factor-β signal transduction pathway as an example, we report our stochastic simulations of the dynamics of the pathway and introduce a linear noise approximation method to calculate the transient intrinsic noise of pathway components. We compare the numerical solutions of the linear noise approximation with the statistic results of chemical Langevin equations, and find that they are quantitatively in agreement with the other. When transforming growth factor-β dose decreases to a low level, the time evolution of noise fluctuation of nuclear Smad2—Smad4 complex indicates the abnormal enhancement in the transient signal activation process.

A new similarity index for nonlinear signal analysis based on local extrema patterns

NASA Astrophysics Data System (ADS)

Niknazar, Hamid; Motie Nasrabadi, Ali; Shamsollahi, Mohammad Bagher

2018-02-01

Common similarity measures of time domain signals such as cross-correlation and Symbolic Aggregate approximation (SAX) are not appropriate for nonlinear signal analysis. This is because of the high sensitivity of nonlinear systems to initial points. Therefore, a similarity measure for nonlinear signal analysis must be invariant to initial points and quantify the similarity by considering the main dynamics of signals. The statistical behavior of local extrema (SBLE) method was previously proposed to address this problem. The SBLE similarity index uses quantized amplitudes of local extrema to quantify the dynamical similarity of signals by considering patterns of sequential local extrema. By adding time information of local extrema as well as fuzzifying quantized values, this work proposes a new similarity index for nonlinear and long-term signal analysis, which extends the SBLE method. These new features provide more information about signals and reduce noise sensitivity by fuzzifying them. A number of practical tests were performed to demonstrate the ability of the method in nonlinear signal clustering and classification on synthetic data. In addition, epileptic seizure detection based on electroencephalography (EEG) signal processing was done by the proposed similarity to feature the potentials of the method as a real-world application tool.

Smart Sensors: Why and when the origin was and why and where the future will be

NASA Astrophysics Data System (ADS)

Corsi, C.

2013-12-01

Smart Sensors is a technique developed in the 70's when the processing capabilities, based on readout integrated with signal processing, was still far from the complexity needed in advanced IR surveillance and warning systems, because of the enormous amount of noise/unwanted signals emitted by operating scenario especially in military applications. The Smart Sensors technology was kept restricted within a close military environment exploding in applications and performances in the 90's years thanks to the impressive improvements in the integrated signal read-out and processing achieved by CCD-CMOS technologies in FPA. In fact the rapid advances of "very large scale integration" (VLSI) processor technology and mosaic EO detector array technology allowed to develop new generations of Smart Sensors with much improved signal processing by integrating microcomputers and other VLSI signal processors. inside the sensor structure achieving some basic functions of living eyes (dynamic stare, non-uniformity compensation, spatial and temporal filtering). New and future technologies (Nanotechnology, Bio-Organic Electronics, Bio-Computing) are lightning a new generation of Smart Sensors extending the Smartness from the Space-Time Domain to Spectroscopic Functional Multi-Domain Signal Processing. History and future forecasting of Smart Sensors will be reported.

Discriminating cascading processes in nonlinear optics: A QED analysis based on their molecular and geometric origin

NASA Astrophysics Data System (ADS)

Bennett, Kochise; Chernyak, Vladimir Y.; Mukamel, Shaul

2017-03-01

The nonlinear optical response of a system of molecules often contains contributions whereby the products of lower-order processes in two separate molecules give signals that appear on top of a genuine direct higher-order process with a single molecule. These many-body contributions are known as cascading and complicate the interpretation of multidimensional stimulated Raman and other nonlinear signals. In a quantum electrodynamic treatment, these cascading processes arise from second-order expansion in the molecular coupling to vacuum modes of the radiation field, i.e., single-photon exchange between molecules, which also gives rise to other collective effects. We predict the relative phase of the direct and cascading nonlinear signals and its dependence on the microscopic dynamics as well as the sample geometry. This phase may be used to identify experimental conditions for distinguishing the direct and cascading signals by their phase. Higher-order cascading processes involving the exchange of several photons between more than two molecules are discussed.

Understanding Volcanic Conduit Dynamics: from Experimental Fragmentation to Volcanic Eruptions

NASA Astrophysics Data System (ADS)

Arciniega-Ceballos, A.; Alatorre-Ibarguengoitia, M. A.; Scheu, B.; Dingwell, D. B.

2011-12-01

The investigation of conduit dynamics at high pressure, under controlled laboratory conditions is a powerful tool to understand the physics behind volcanic processes before an eruption. In this work, we analyze the characteristics of the seismic response of an "experimental volcano" focusing on the dynamics of the conduit behavior during the fragmentation process of volcanic rocks. The "experimental volcano" is represented by a shock tube apparatus, which consists of a low-pressure voluminous tank (3 x 0.40 m), for sample recovery; and a high-pressure pipe-like conduit (16.5 x 2,5 cm), which represents the volcanic source mechanism, where rock samples are pressurized and fragmented. These two serial steel pipes are connected and sealed by a set of diaphragms that bear pressures in a range of 4 to 20 MPa. The history of the overall process of an explosion consists of four steps: 1) the slow pressurization of the pipe-like conduit filled with solid pumice and gas, 2) the sudden removal of the diaphragms, 3) the rapid decompression of the system and 4) the ejection of the gas-particle mixture. Each step imprints distinctive features on the microseismic records, reflecting the conduit dynamics during the explosion. In this work we show how features such as waveform characteristics, the three components of the force system acting on the conduit, the independent components of the moment tensor, the volumetric change of the source mechanism, the arrival time of the shock wave and its velocity, are quantified from the experimental microseismic data. Knowing these features, each step of the eruptive process, the conduit conditions and the source mechanism characteristics can be determined. The procedure applied in this experimental approach allows the use of seismic field data to estimate volcanic conduit conditions before an eruption takes place. We state on the hypothesis that the physics behind the pressurization and depressurization process of any conduit is the same and the effects of such process on the conduit dynamics are independent of size. We first described the very-long period (VLP) and long-period (LP) signals, observed in many active volcanoes around the world, and from comparison of waveform characteristics with their experimental analogues (eLP and eVLP signals) we found remarkable similarities and equivalent physical meaning. Based on our experimental investigations and analysis of field data recorded during volcanic eruptions we may conclude that VLP signals are caused by the inflation-deflation behavior of the volcanic conduit due to the decompression process, and that LP signals are manly associated with cracking and fragmentation of the magmatic material (ash, magma and gas) filling the conduit and ascending to the surface. In addition, we accounted for the repetitive character of LP and VLP signals, as a consequence of contraction and dilatation of a steady non-destructive source mechanism, which systematically responds to pressure changes of the volcanic system.

P wave detection in ECG signals using an extended Kalman filter: an evaluation in different arrhythmia contexts.

PubMed

Rahimpour, M; Mohammadzadeh Asl, B

2016-07-01

Monitoring atrial activity via P waves, is an important feature of the arrhythmia detection procedure. The aim of this paper is to present an algorithm for P wave detection in normal and some abnormal records by improving existing methods in the field of signal processing. In contrast to the classical approaches, which are completely blind to signal dynamics, our proposed method uses the extended Kalman filter, EKF25, to estimate the state variables of the equations modeling the dynamic of an ECG signal. This method is a modified version of the nonlinear dynamical model previously introduced for a generation of synthetic ECG signals and fiducial point extraction in normal ones. It is capable of estimating the separate types of activity of the heart with reasonable accuracy and performs well in the presence of morphological variations in the waveforms and ectopic beats. The MIT-BIH Arrhythmia and QT databases have been used to evaluate the performance of the proposed method. The results show that this method has Se  =  98.38% and Pr  =  96.74% in the overall records (considering normal and abnormal rhythms).

Direct measurement of the propagation velocity of defects using coherent X-rays

DOE PAGES

Ulbrandt, Jeffrey G.; Rainville, Meliha G.; Wagenbach, Christa; ...

2016-03-28

The properties of artificially grown thin films are often strongly affected by the dynamic relationships between surface growth processes and subsurface structure. Coherent mixing of X-ray signals promises to provide an approach to better understand such processes. Here, we demonstrate the continuously variable mixing of surface and bulk scattering signals during realtime studies of sputter deposition of a-Si and a-WSi2 films by controlling the X-ray penetration and escape depths in coherent grazing-incidence small-angle X-ray scattering. Under conditions where the X-ray signal comes from both the growth surface and the thin film bulk, oscillations in temporal correlations arise from coherent interferencemore » between scattering from stationary bulk features and from the advancing surface. We also observe evidence that elongated bulk features propagate upwards at the same velocity as the surface. Moreover, a highly surface-sensitive mode is demonstrated that can access the surface dynamics independently of the subsurface structure.« less

Dynamic multiprotein assemblies shape the spatial structure of cell signaling.

PubMed

Nussinov, Ruth; Jang, Hyunbum

2014-01-01

Cell signaling underlies critical cellular decisions. Coordination, efficiency as well as fail-safe mechanisms are key elements. How the cell ensures that these hallmarks are at play are important questions. Cell signaling is often viewed as taking place through discrete and cross-talking pathways; oftentimes these are modularized to emphasize distinct functions. While simple, convenient and clear, such models largely neglect the spatial structure of cell signaling; they also convey inter-modular (or inter-protein) spatial separation that may not exist. Here our thesis is that cell signaling is shaped by a network of multiprotein assemblies. While pre-organized, the assemblies and network are loose and dynamic. They contain transiently-associated multiprotein complexes which are often mediated by scaffolding proteins. They are also typically anchored in the membrane, and their continuum may span the cell. IQGAP1 scaffolding protein which binds proteins including Raf, calmodulin, Mek, Erk, actin, and tens more, with actin shaping B-cell (and likely other) membrane-anchored nanoclusters and allosterically polymerizing in dynamic cytoskeleton formation, and Raf anchoring in the membrane along with Ras, provides a striking example. The multivalent network of dynamic proteins and lipids, with specific interactions forming and breaking, can be viewed as endowing gel-like properties. Collectively, this reasons that efficient, productive and reliable cell signaling takes place primarily through transient, preorganized and cooperative protein-protein interactions spanning the cell rather than stochastic, diffusion-controlled processes. Copyright © 2014 Elsevier Ltd. All rights reserved.

High dynamic range hyperspectral imaging for camouflage performance test and evaluation

NASA Astrophysics Data System (ADS)

Pearce, D.; Feenan, J.

2016-10-01

This paper demonstrates the use of high dynamic range processing applied to the specific technique of hyper-spectral imaging with linescan spectrometers. The technique provides an improvement in signal to noise for reflectance estimation. This is demonstrated for field measurements of rural imagery collected from a ground-based linescan spectrometer of rural scenes. Once fully developed, the specific application is expected to improve the colour estimation approaches and consequently the test and evaluation accuracy of camouflage performance tests. Data are presented on both field and laboratory experiments that have been used to evaluate the improvements granted by the adoption of high dynamic range data acquisition in the field of hyperspectral imaging. High dynamic ranging imaging is well suited to the hyperspectral domain due to the large variation in solar irradiance across the visible and short wave infra-red (SWIR) spectrum coupled with the wavelength dependence of the nominal silicon detector response. Under field measurement conditions it is generally impractical to provide artificial illumination; consequently, an adaptation of the hyperspectral imaging and re ectance estimation process has been developed to accommodate the solar spectrum. This is shown to improve the signal to noise ratio for the re ectance estimation process of scene materials in the 400-500 nm and 700-900 nm regions.

Discrete Dynamics Model for the Speract-Activated Ca2+ Signaling Network Relevant to Sperm Motility

PubMed Central

Espinal, Jesús; Aldana, Maximino; Guerrero, Adán; Wood, Christopher

2011-01-01

Understanding how spermatozoa approach the egg is a central biological issue. Recently a considerable amount of experimental evidence has accumulated on the relation between oscillations in intracellular calcium ion concentration ([Ca]) in the sea urchin sperm flagellum, triggered by peptides secreted from the egg, and sperm motility. Determination of the structure and dynamics of the signaling pathway leading to these oscillations is a fundamental problem. However, a biochemically based formulation for the comprehension of the molecular mechanisms operating in the axoneme as a response to external stimulus is still lacking. Based on experiments on the S. purpuratus sea urchin spermatozoa, we propose a signaling network model where nodes are discrete variables corresponding to the pathway elements and the signal transmission takes place at discrete time intervals according to logical rules. The validity of this model is corroborated by reproducing previous empirically determined signaling features. Prompted by the model predictions we performed experiments which identified novel characteristics of the signaling pathway. We uncovered the role of a high voltage-activated channel as a regulator of the delay in the onset of fluctuations after activation of the signaling cascade. This delay time has recently been shown to be an important regulatory factor for sea urchin sperm reorientation. Another finding is the participation of a voltage-dependent calcium-activated channel in the determination of the period of the fluctuations. Furthermore, by analyzing the spread of network perturbations we find that it operates in a dynamically critical regime. Our work demonstrates that a coarse-grained approach to the dynamics of the signaling pathway is capable of revealing regulatory sperm navigation elements and provides insight, in terms of criticality, on the concurrence of the high robustness and adaptability that the reproduction processes are predicted to have developed throughout evolution. PMID:21857937

Classifying acoustic signals into phoneme categories: average and dyslexic readers make use of complex dynamical patterns and multifractal scaling properties of the speech signal

PubMed Central

2015-01-01

Several competing aetiologies of developmental dyslexia suggest that the problems with acquiring literacy skills are causally entailed by low-level auditory and/or speech perception processes. The purpose of this study is to evaluate the diverging claims about the specific deficient peceptual processes under conditions of strong inference. Theoretically relevant acoustic features were extracted from a set of artificial speech stimuli that lie on a /bAk/-/dAk/ continuum. The features were tested on their ability to enable a simple classifier (Quadratic Discriminant Analysis) to reproduce the observed classification performance of average and dyslexic readers in a speech perception experiment. The ‘classical’ features examined were based on component process accounts of developmental dyslexia such as the supposed deficit in Envelope Rise Time detection and the deficit in the detection of rapid changes in the distribution of energy in the frequency spectrum (formant transitions). Studies examining these temporal processing deficit hypotheses do not employ measures that quantify the temporal dynamics of stimuli. It is shown that measures based on quantification of the dynamics of complex, interaction-dominant systems (Recurrence Quantification Analysis and the multifractal spectrum) enable QDA to classify the stimuli almost identically as observed in dyslexic and average reading participants. It seems unlikely that participants used any of the features that are traditionally associated with accounts of (impaired) speech perception. The nature of the variables quantifying the temporal dynamics of the speech stimuli imply that the classification of speech stimuli cannot be regarded as a linear aggregate of component processes that each parse the acoustic signal independent of one another, as is assumed by the ‘classical’ aetiologies of developmental dyslexia. It is suggested that the results imply that the differences in speech perception performance between average and dyslexic readers represent a scaled continuum rather than being caused by a specific deficient component. PMID:25834769

Information Processing Capacity of Dynamical Systems

NASA Astrophysics Data System (ADS)

Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Massar, Serge

2012-07-01

Many dynamical systems, both natural and artificial, are stimulated by time dependent external signals, somehow processing the information contained therein. We demonstrate how to quantify the different modes in which information can be processed by such systems and combine them to define the computational capacity of a dynamical system. This is bounded by the number of linearly independent state variables of the dynamical system, equaling it if the system obeys the fading memory condition. It can be interpreted as the total number of linearly independent functions of its stimuli the system can compute. Our theory combines concepts from machine learning (reservoir computing), system modeling, stochastic processes, and functional analysis. We illustrate our theory by numerical simulations for the logistic map, a recurrent neural network, and a two-dimensional reaction diffusion system, uncovering universal trade-offs between the non-linearity of the computation and the system's short-term memory.

The Temporal Dynamics of Visual Search: Evidence for Parallel Processing in Feature and Conjunction Searches

PubMed Central

McElree, Brian; Carrasco, Marisa

2012-01-01

Feature and conjunction searches have been argued to delineate parallel and serial operations in visual processing. The authors evaluated this claim by examining the temporal dynamics of the detection of features and conjunctions. The 1st experiment used a reaction time (RT) task to replicate standard mean RT patterns and to examine the shapes of the RT distributions. The 2nd experiment used the response-signal speed–accuracy trade-off (SAT) procedure to measure discrimination (asymptotic detection accuracy) and detection speed (processing dynamics). Set size affected discrimination in both feature and conjunction searches but affected detection speed only in the latter. Fits of models to the SAT data that included a serial component overpredicted the magnitude of the observed dynamics differences. The authors concluded that both features and conjunctions are detected in parallel. Implications for the role of attention in visual processing are discussed. PMID:10641310

Information Processing Capacity of Dynamical Systems

PubMed Central

Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Massar, Serge

2012-01-01

Many dynamical systems, both natural and artificial, are stimulated by time dependent external signals, somehow processing the information contained therein. We demonstrate how to quantify the different modes in which information can be processed by such systems and combine them to define the computational capacity of a dynamical system. This is bounded by the number of linearly independent state variables of the dynamical system, equaling it if the system obeys the fading memory condition. It can be interpreted as the total number of linearly independent functions of its stimuli the system can compute. Our theory combines concepts from machine learning (reservoir computing), system modeling, stochastic processes, and functional analysis. We illustrate our theory by numerical simulations for the logistic map, a recurrent neural network, and a two-dimensional reaction diffusion system, uncovering universal trade-offs between the non-linearity of the computation and the system's short-term memory. PMID:22816038

Random Matrix Theory in molecular dynamics analysis.

PubMed

Palese, Luigi Leonardo

2015-01-01

It is well known that, in some situations, principal component analysis (PCA) carried out on molecular dynamics data results in the appearance of cosine-shaped low index projections. Because this is reminiscent of the results obtained by performing PCA on a multidimensional Brownian dynamics, it has been suggested that short-time protein dynamics is essentially nothing more than a noisy signal. Here we use Random Matrix Theory to analyze a series of short-time molecular dynamics experiments which are specifically designed to be simulations with high cosine content. We use as a model system the protein apoCox17, a mitochondrial copper chaperone. Spectral analysis on correlation matrices allows to easily differentiate random correlations, simply deriving from the finite length of the process, from non-random signals reflecting the intrinsic system properties. Our results clearly show that protein dynamics is not really Brownian also in presence of the cosine-shaped low index projections on principal axes. Copyright © 2014 Elsevier B.V. All rights reserved.

Coordinated dynamic encoding in the retina using opposing forms of plasticity

PubMed Central

Kastner, David B.; Baccus, Stephen A.

2011-01-01

The range of natural inputs encoded by a neuron often exceeds its dynamic range. To overcome this limitation, neural populations divide their inputs among different cell classes, as with rod and cone photoreceptors, and adapt by shifting their dynamic range. We report that the dynamic behavior of retinal ganglion cells in salamanders, mice, and rabbits is divided into two opposing forms of short-term plasticity in different cell classes. One population of cells exhibited sensitization—a persistent elevated sensitivity following a strong stimulus. This novel dynamic behavior compensates for the information loss caused by the known process of adaptation occurring in a separate cell population. The two populations divide the dynamic range of inputs, with sensitizing cells encoding weak signals, and adapting cells encoding strong signals. In the two populations, the linear, threshold and adaptive properties are linked to preserve responsiveness when stimulus statistics change, with one population maintaining the ability to respond when the other fails. PMID:21909086

Gr-GDHP: A New Architecture for Globalized Dual Heuristic Dynamic Programming.

PubMed

Zhong, Xiangnan; Ni, Zhen; He, Haibo

2017-10-01

Goal representation globalized dual heuristic dynamic programming (Gr-GDHP) method is proposed in this paper. A goal neural network is integrated into the traditional GDHP method providing an internal reinforcement signal and its derivatives to help the control and learning process. From the proposed architecture, it is shown that the obtained internal reinforcement signal and its derivatives can be able to adjust themselves online over time rather than a fixed or predefined function in literature. Furthermore, the obtained derivatives can directly contribute to the objective function of the critic network, whose learning process is thus simplified. Numerical simulation studies are applied to show the performance of the proposed Gr-GDHP method and compare the results with other existing adaptive dynamic programming designs. We also investigate this method on a ball-and-beam balancing system. The statistical simulation results are presented for both the Gr-GDHP and the GDHP methods to demonstrate the improved learning and controlling performance.

Dynamic remodeling of membrane composition drives cell cycle through primary cilia excision

PubMed Central

Phua, Siew Cheng; Chiba, Shuhei; Suzuki, Masako; Su, Emily; Roberson, Elle C.; Pusapati, Ganesh V.; Setou, Mitsutoshi; Rohatgi, Rajat; Reiter, Jeremy F.; Ikegami, Koji; Inoue, Takanari

2017-01-01

The life cycle of a primary cilium begins in quiescence and ends prior to mitosis. In quiescent cells, primary cilium insulates itself from contiguous dynamic membrane processes on the cell surface to function as a stable signaling apparatus. Here, we demonstrate that basal restriction of ciliary structure dynamics is established by cilia-enriched phosphoinositide 5-phosphatase, Inpp5e. Growth induction displaces ciliary Inpp5e and accumulates phosphatidylinositol 4,5-bisphosphate to distal cilia. This triggers otherwise forbidden actin polymerization in primary cilia, which excises cilia tips in a process we call cilia decapitation. Whilst cilia disassembly is traditionally thought to occur solely through resorption, we show that an acute loss of IFT-B through cilia decapitation precedes resorption. Finally, we propose that cilia decapitation induces mitogenic signaling and constitutes a molecular link between the cilia life cycle and cell-division cycle. This newly defined ciliary mechanism may find significance in cell proliferation control during normal development and cancer. PMID:28086093

Investigation of Potential Triggered Tremor in Latin America and the Caribbean

NASA Astrophysics Data System (ADS)

Gonzalez-Huizar, H.; Velasco, A. A.; Peng, Z.

2012-12-01

Recent observations have shown that seismic waves generate transient stresses capable of triggering earthquakes and tectonic (or non-volcanic) tremor far away from the original earthquake source. However, the mechanisms behind remotely triggered seismicity still remain unclear. Triggered tremor signals can be particularly useful in investigating remote triggering processes, since in many cases, the tremor pulses are very clearly modulated by the passing surface waves. The temporal stress changes (magnitude and orientation) caused by seismic waves at the tremor source region can be calculated and correlated with tremor pulses, which allows for exploring the stresses involved in the triggering process. Some observations suggest that triggered and ambient tremor signals are generated under similar physical conditions; thus, investigating triggered tremor might also provide important clues on how and under what conditions ambient tremor signals generate. In this work we present some of the results and techniques we employ in the research of potential cases of triggered tectonic tremor in Latin America and the Caribbean. This investigation includes: (1) the triggered tremor detection, with the use of specific signal filters; (2) localization of the sources, using uncommon techniques like time reversal signals; (3) and the analysis of the stress conditions under which they are generated, by modeling the triggering waves related dynamic stress. Our results suggest that tremor can be dynamically triggered by both Love and Rayleigh waves and in broad variety of tectonic environments depending strongly on the dynamic stress amplitude and orientation. Investigating remotely triggered seismicity offers the opportunity to improve our knowledge about deformation mechanisms and the physics of rupture.

Analog signal processing for optical coherence imaging systems

NASA Astrophysics Data System (ADS)

Xu, Wei

Optical coherence tomography (OCT) and optical coherence microscopy (OCM) are non-invasive optical coherence imaging techniques, which enable micron-scale resolution, depth resolved imaging capability. Both OCT and OCM are based on Michelson interferometer theory. They are widely used in ophthalmology, gastroenterology and dermatology, because of their high resolution, safety and low cost. OCT creates cross sectional images whereas OCM obtains en face images. In this dissertation, the design and development of three increasingly complicated analog signal processing (ASP) solutions for optical coherence imaging are presented. The first ASP solution was implemented for a time domain OCT system with a Rapid Scanning Optical Delay line (RSOD)-based optical signal modulation and logarithmic amplifier (Log amp) based demodulation. This OCT system can acquire up to 1600 A-scans per second. The measured dynamic range is 106dB at 200A-scan per second. This OCT signal processing electronics includes an off-the-shelf filter box with a Log amp circuit implemented on a PCB board. The second ASP solution was developed for an OCM system with synchronized modulation and demodulation and compensation for interferometer phase drift. This OCM acquired micron-scale resolution, high dynamic range images at acquisition speeds up to 45,000 pixels/second. This OCM ASP solution is fully custom designed on a perforated circuit board. The third ASP solution was implemented on a single 2.2 mm x 2.2 mm complementary metal oxide semiconductor (CMOS) chip. This design is expandable to a multiple channel OCT system. A single on-chip CMOS photodetector and ASP channel was used for coherent demodulation in a time domain OCT system. Cross-sectional images were acquired with a dynamic range of 76dB (limited by photodetector responsivity). When incorporated with a bump-bonded InGaAs photodiode with higher responsivity, the expected dynamic range is close to 100dB.

Computer simulation studies on passive recruitment dynamics of lipids induced by the adsorption of charged nanoparticles.

PubMed

Li, Yang

2014-07-07

The recruitment dynamics of lipids in the biomembrane is believed to play an important role in a variety of cellular processes. In this work, we investigate the nanoparticle-induced recruitment dynamics of lipids in the heterogeneous phospholipid bilayers of distearoyl-phosphatidylcholine (DSPC) and dioleoyl-phosphatidylglycerol (DOPG) via coarse-grained molecular dynamics simulations. Three dynamic modes of individual charged DOPG lipid molecules have been taken into account in the recruitment process: lateral diffusion, protrusions, and flip-flops. Based on analysis of the mobility pattern of lipids, structural variations in the membrane as well as activation energy of the structure of lipid eyelids characterized by the potential of mean force, we have concluded that the electrostatic attraction of nanoparticles plays a crucial role in the recruitment process of lipids in phospholipid bilayers. These studies are consistent with experimental observations and to some extent give insight into the origin of some cellular processes such as signaling, formation of lipid rafts, and endocytosis.

Regulation of T cell receptor complex-mediated signaling by ubiquitin and ubiquitin-like modifications.

PubMed

Friend, Samantha F; Deason-Towne, Francina; Peterson, Lisa K; Berger, Allison J; Dragone, Leonard L

2014-01-01

Post-translational protein modifications are a dynamic method of regulating protein function in response to environmental signals. As with any cellular process, T cell receptor (TCR) complex-mediated signaling is highly regulated, since the strength and duration of TCR-generated signals governs T cell development and activation. While regulation of TCR complex-mediated signaling by phosphorylation has been well studied, regulation by ubiquitin and ubiquitin-like modifiers is still an emerging area of investigation. This review will examine how ubiquitin, E3 ubiquitin ligases, and other ubiquitin-like modifications such as SUMO and NEDD8 regulate TCR complex-mediated signaling.

Regulation of T cell receptor complex-mediated signaling by ubiquitin and ubiquitin-like modifications

PubMed Central

Friend, Samantha F; Deason-Towne, Francina; Peterson, Lisa K; Berger, Allison J; Dragone, Leonard L

2014-01-01

Post-translational protein modifications are a dynamic method of regulating protein function in response to environmental signals. As with any cellular process, T cell receptor (TCR) complex-mediated signaling is highly regulated, since the strength and duration of TCR-generated signals governs T cell development and activation. While regulation of TCR complex-mediated signaling by phosphorylation has been well studied, regulation by ubiquitin and ubiquitin-like modifiers is still an emerging area of investigation. This review will examine how ubiquitin, E3 ubiquitin ligases, and other ubiquitin-like modifications such as SUMO and NEDD8 regulate TCR complex-mediated signaling. PMID:25628960

Robust input design for nonlinear dynamic modeling of AUV.

PubMed

Nouri, Nowrouz Mohammad; Valadi, Mehrdad

2017-09-01

Input design has a dominant role in developing the dynamic model of autonomous underwater vehicles (AUVs) through system identification. Optimal input design is the process of generating informative inputs that can be used to generate the good quality dynamic model of AUVs. In a problem with optimal input design, the desired input signal depends on the unknown system which is intended to be identified. In this paper, the input design approach which is robust to uncertainties in model parameters is used. The Bayesian robust design strategy is applied to design input signals for dynamic modeling of AUVs. The employed approach can design multiple inputs and apply constraints on an AUV system's inputs and outputs. Particle swarm optimization (PSO) is employed to solve the constraint robust optimization problem. The presented algorithm is used for designing the input signals for an AUV, and the estimate obtained by robust input design is compared with that of the optimal input design. According to the results, proposed input design can satisfy both robustness of constraints and optimality. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Ligand-Induced Dynamics of Neurotrophin Receptors Investigated by Single-Molecule Imaging Approaches

PubMed Central

Marchetti, Laura; Luin, Stefano; Bonsignore, Fulvio; de Nadai, Teresa; Beltram, Fabio; Cattaneo, Antonino

2015-01-01

Neurotrophins are secreted proteins that regulate neuronal development and survival, as well as maintenance and plasticity of the adult nervous system. The biological activity of neurotrophins stems from their binding to two membrane receptor types, the tropomyosin receptor kinase and the p75 neurotrophin receptors (NRs). The intracellular signalling cascades thereby activated have been extensively investigated. Nevertheless, a comprehensive description of the ligand-induced nanoscale details of NRs dynamics and interactions spanning from the initial lateral movements triggered at the plasma membrane to the internalization and transport processes is still missing. Recent advances in high spatio-temporal resolution imaging techniques have yielded new insight on the dynamics of NRs upon ligand binding. Here we discuss requirements, potential and practical implementation of these novel approaches for the study of neurotrophin trafficking and signalling, in the framework of current knowledge available also for other ligand-receptor systems. We shall especially highlight the correlation between the receptor dynamics activated by different neurotrophins and the respective signalling outcome, as recently revealed by single-molecule tracking of NRs in living neuronal cells. PMID:25603178

An Over 90 dB Intra-Scene Single-Exposure Dynamic Range CMOS Image Sensor Using a 3.0 μm Triple-Gain Pixel Fabricated in a Standard BSI Process.

PubMed

Takayanagi, Isao; Yoshimura, Norio; Mori, Kazuya; Matsuo, Shinichiro; Tanaka, Shunsuke; Abe, Hirofumi; Yasuda, Naoto; Ishikawa, Kenichiro; Okura, Shunsuke; Ohsawa, Shinji; Otaka, Toshinori

2018-01-12

To respond to the high demand for high dynamic range imaging suitable for moving objects with few artifacts, we have developed a single-exposure dynamic range image sensor by introducing a triple-gain pixel and a low noise dual-gain readout circuit. The developed 3 μm pixel is capable of having three conversion gains. Introducing a new split-pinned photodiode structure, linear full well reaches 40 ke - . Readout noise under the highest pixel gain condition is 1 e - with a low noise readout circuit. Merging two signals, one with high pixel gain and high analog gain, and the other with low pixel gain and low analog gain, a single exposure dynamic rage (SEHDR) signal is obtained. Using this technology, a 1/2.7", 2M-pixel CMOS image sensor has been developed and characterized. The image sensor also employs an on-chip linearization function, yielding a 16-bit linear signal at 60 fps, and an intra-scene dynamic range of higher than 90 dB was successfully demonstrated. This SEHDR approach inherently mitigates the artifacts from moving objects or time-varying light sources that can appear in the multiple exposure high dynamic range (MEHDR) approach.

An Over 90 dB Intra-Scene Single-Exposure Dynamic Range CMOS Image Sensor Using a 3.0 μm Triple-Gain Pixel Fabricated in a Standard BSI Process †

PubMed Central

Takayanagi, Isao; Yoshimura, Norio; Mori, Kazuya; Matsuo, Shinichiro; Tanaka, Shunsuke; Abe, Hirofumi; Yasuda, Naoto; Ishikawa, Kenichiro; Okura, Shunsuke; Ohsawa, Shinji; Otaka, Toshinori

2018-01-01

To respond to the high demand for high dynamic range imaging suitable for moving objects with few artifacts, we have developed a single-exposure dynamic range image sensor by introducing a triple-gain pixel and a low noise dual-gain readout circuit. The developed 3 μm pixel is capable of having three conversion gains. Introducing a new split-pinned photodiode structure, linear full well reaches 40 ke−. Readout noise under the highest pixel gain condition is 1 e− with a low noise readout circuit. Merging two signals, one with high pixel gain and high analog gain, and the other with low pixel gain and low analog gain, a single exposure dynamic rage (SEHDR) signal is obtained. Using this technology, a 1/2.7”, 2M-pixel CMOS image sensor has been developed and characterized. The image sensor also employs an on-chip linearization function, yielding a 16-bit linear signal at 60 fps, and an intra-scene dynamic range of higher than 90 dB was successfully demonstrated. This SEHDR approach inherently mitigates the artifacts from moving objects or time-varying light sources that can appear in the multiple exposure high dynamic range (MEHDR) approach. PMID:29329210

A-law/Mu-law Dynamic Range Compression Deconvolution (Preprint)

DTIC Science & Technology

2008-02-04

noise filtering via the spectrum proportionality filter, and second the signal deblurring via the inverse filter. In this process for regions when...is the joint image of motion impulse response and the noisy blurred image with signal to noise ratio 5, 6(A’) is the gray level recovered image...joint image of motion impulse response and the noisy blurred image with signal to noise ratio 5, (A’) the gray level recovered image using the A-law

Nonparametric Simulation of Signal Transduction Networks with Semi-Synchronized Update

PubMed Central

Nassiri, Isar; Masoudi-Nejad, Ali; Jalili, Mahdi; Moeini, Ali

2012-01-01

Simulating signal transduction in cellular signaling networks provides predictions of network dynamics by quantifying the changes in concentration and activity-level of the individual proteins. Since numerical values of kinetic parameters might be difficult to obtain, it is imperative to develop non-parametric approaches that combine the connectivity of a network with the response of individual proteins to signals which travel through the network. The activity levels of signaling proteins computed through existing non-parametric modeling tools do not show significant correlations with the observed values in experimental results. In this work we developed a non-parametric computational framework to describe the profile of the evolving process and the time course of the proportion of active form of molecules in the signal transduction networks. The model is also capable of incorporating perturbations. The model was validated on four signaling networks showing that it can effectively uncover the activity levels and trends of response during signal transduction process. PMID:22737250

Seismic and infrasonic source processes in volcanic fluid systems

NASA Astrophysics Data System (ADS)

Matoza, Robin S.

Volcanoes exhibit a spectacular diversity in fluid oscillation processes, which lead to distinct seismic and acoustic signals in the solid earth and atmosphere. Volcano seismic waveforms contain rich information on the geometry of fluid migration, resonance effects, and transient and sustained pressure oscillations resulting from unsteady flow through subsurface cracks, fissures and conduits. Volcanic sounds contain information on shallow fluid flow, resonance in near-surface cavities, and degassing dynamics into the atmosphere. Since volcanoes have large spatial scales, the vast majority of their radiated atmospheric acoustic energy is infrasonic (<20 Hz). This dissertation presents observations from joint broadband seismic and infrasound array deployments at Mount St. Helens (MSH, Washington State, USA), Tungurahua (Ecuador), and Kilauea Volcano (Hawaii, USA), each providing data for several years. These volcanoes represent a broad spectrum of eruption styles ranging from hawaiian to plinian in nature. The catalogue of recorded infrasonic signals includes continuous broadband and harmonic tremor from persistent degassing at basaltic lava vents and tubes at Pu'u O'o (Kilauea), thousands of repetitive impulsive signals associated with seismic longperiod (0.5-5 Hz) events and the dynamics of the shallow hydrothermal system at MSH, rockfall signals from the unstable dacite dome at MSH, energetic explosion blast waves and gliding infrasonic harmonic tremor at Tungurahua volcano, and large-amplitude and long-duration broadband signals associated with jetting during vulcanian, subplinian and plinian eruptions at MSH and Tungurahua. We develop models for a selection of these infrasonic signals. For infrasonic long-period (LP) events at MSH, we investigate seismic-acoustic coupling from various buried source configurations as a means to excite infrasound waves in the atmosphere. We find that linear elastic seismic-acoustic transmission from the ground to atmosphere is inadequate to explain the observations, and propose that the signals may result from sudden containment failure of a pressurized hydrothermal crack. For the broadband eruption tremor signals, we propose that the infrasonic signals represent a low-frequency form of jet noise, analogous to the noise from man-made jet engines, but operating with larger spatial scales and consequently longer time-scales. For the persistent hawaiian tremor signals, we propose that bubble cloud oscillation in the upper section of a roiling magma conduit and vortex dynamics in the shallow degassing region act as broadband and harmonic tremor sources. We also consider infrasound propagation effects in a dynamic atmosphere and discuss their effects on recorded signals. This dissertation demonstrates that combined seismic and infrasonic data provide complementary perspectives on eruptive activity.

FIBRE AND INTEGRATED OPTICS. OPTICAL PROCESSING OF INFORMATION: Method for optical data processing based on a two-pulse photon echo

NASA Astrophysics Data System (ADS)

Zakharov, S. M.; Manykin, Eduard A.

1995-02-01

The principles of optical processing based on dynamic spatial—temporal properties of two-pulse photon echo signals are considered. The properties of a resonant medium as an on-line filter of temporal and spatial frequencies are discussed. These properties are due to the sensitivity of such a medium to the Fourier spectrum of the second exiting pulse. Degeneracy of quantum resonant systems, demonstrated by the coherent response dependence on the square of the amplitude of the second pulse, can be used for 'simultaneous' correlation processing of optical 'signals'. Various methods for the processing of the Fourier optical image are discussed.

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

PubMed

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.

Synchronization trigger control system for flow visualization

NASA Technical Reports Server (NTRS)

Chun, K. S.

1987-01-01

The use of cinematography or holographic interferometry for dynamic flow visualization in an internal combustion engine requires a control device that globally synchronizes camera and light source timing at a predefined shaft encoder angle. The device is capable of 0.35 deg resolution for rotational speeds of up to 73 240 rpm. This was achieved by implementing the shaft encoder signal addressed look-up table (LUT) and appropriate latches. The developed digital signal processing technique achieves 25 nsec of high speed triggering angle detection by using direct parallel bit comparison of the shaft encoder digital code with a simulated angle reference code, instead of using angle value comparison which involves more complicated computation steps. In order to establish synchronization to an AC reference signal whose magnitude is variant with the rotating speed, a dynamic peak followup synchronization technique has been devised. This method scrutinizes the reference signal and provides the right timing within 40 nsec. Two application examples are described.

Nephrin Tyrosine Phosphorylation Is Required to Stabilize and Restore Podocyte Foot Process Architecture

PubMed Central

New, Laura A.; Martin, Claire E.; Scott, Rizaldy P.; Platt, Mathew J.; Keyvani Chahi, Ava; Stringer, Colin D.; Lu, Peihua; Samborska, Bozena; Eremina, Vera; Takano, Tomoko; Simpson, Jeremy A.; Quaggin, Susan E.

2016-01-01

Podocytes are specialized epithelial cells of the kidney blood filtration barrier that contribute to permselectivity via a series of interdigitating actin–rich foot processes. Positioned between adjacent projections is a unique cell junction known as the slit diaphragm, which is physically connected to the actin cytoskeleton via the transmembrane protein nephrin. Evidence indicates that tyrosine phosphorylation of the intracellular tail of nephrin initiates signaling events, including recruitment of cytoplasmic adaptor proteins Nck1 and Nck2 that regulate actin cytoskeletal dynamics. Nephrin tyrosine phosphorylation is altered in human and experimental renal diseases characterized by pathologic foot process remodeling, prompting the hypothesis that phosphonephrin signaling directly influences podocyte morphology. To explore this possibility, we generated and analyzed knockin mice with mutations that disrupt nephrin tyrosine phosphorylation and Nck1/2 binding (nephrinY3F/Y3F mice). Homozygous nephrinY3F/Y3F mice developed progressive proteinuria accompanied by structural changes in the filtration barrier, including podocyte foot process effacement, irregular thickening of the glomerular basement membrane, and dilated capillary loops, with a similar but later onset phenotype in heterozygous animals. Furthermore, compared with wild-type mice, nephrinY3F/Y3F mice displayed delayed recovery in podocyte injury models. Profiling of nephrin tyrosine phosphorylation dynamics in wild-type mice subjected to podocyte injury indicated site-specific differences in phosphorylation at baseline, injury, and recovery, which correlated with loss of nephrin-Nck1/2 association during foot process effacement. Our results define an essential requirement for nephrin tyrosine phosphorylation in stabilizing podocyte morphology and suggest a model in which dynamic changes in phosphotyrosine-based signaling confer plasticity to the podocyte actin cytoskeleton. PMID:26802179

Acoustic measurements for the combustion diagnosis of diesel engines fuelled with biodiesels

NASA Astrophysics Data System (ADS)

Zhen, Dong; Wang, Tie; Gu, Fengshou; Tesfa, Belachew; Ball, Andrew

2013-05-01

In this paper, an experimental investigation was carried out on the combustion process of a compression ignition (CI) engine running with biodiesel blends under steady state operating conditions. The effects of biodiesel on the combustion process and engine dynamics were analysed for non-intrusive combustion diagnosis based on a four-cylinder, four-stroke, direct injection and turbocharged diesel engine. The signals of vibration, acoustic and in-cylinder pressure were measured simultaneously to find their inter-connection for diagnostic feature extraction. It was found that the sound energy level increases with the increase of engine load and speed, and the sound characteristics are closely correlated with the variation of in-cylinder pressure and combustion process. The continuous wavelet transform (CWT) was employed to analyse the non-stationary nature of engine noise in a higher frequency range. Before the wavelet analysis, time synchronous average (TSA) was used to enhance the signal-to-noise ratio (SNR) of the acoustic signal by suppressing the components which are asynchronous. Based on the root mean square (RMS) values of CWT coefficients, the effects of biodiesel fractions and operating conditions (speed and load) on combustion process and engine dynamics were investigated. The result leads to the potential of airborne acoustic measurements and analysis for engine condition monitoring and fuel quality evaluation.

An Assessment of Behavioral Dynamic Information Processing Measures in Audiovisual Speech Perception

PubMed Central

Altieri, Nicholas; Townsend, James T.

2011-01-01

Research has shown that visual speech perception can assist accuracy in identification of spoken words. However, little is known about the dynamics of the processing mechanisms involved in audiovisual integration. In particular, architecture and capacity, measured using response time methodologies, have not been investigated. An issue related to architecture concerns whether the auditory and visual sources of the speech signal are integrated “early” or “late.” We propose that “early” integration most naturally corresponds to coactive processing whereas “late” integration corresponds to separate decisions parallel processing. We implemented the double factorial paradigm in two studies. First, we carried out a pilot study using a two-alternative forced-choice discrimination task to assess architecture, decision rule, and provide a preliminary assessment of capacity (integration efficiency). Next, Experiment 1 was designed to specifically assess audiovisual integration efficiency in an ecologically valid way by including lower auditory S/N ratios and a larger response set size. Results from the pilot study support a separate decisions parallel, late integration model. Results from both studies showed that capacity was severely limited for high auditory signal-to-noise ratios. However, Experiment 1 demonstrated that capacity improved as the auditory signal became more degraded. This evidence strongly suggests that integration efficiency is vitally affected by the S/N ratio. PMID:21980314

High resolution, high rate x-ray spectrometer

DOEpatents

Goulding, F.S.; Landis, D.A.

1983-07-14

It is an object of the invention to provide a pulse processing system for use with detected signals of a wide dynamic range which is capable of very high counting rates, with high throughput, with excellent energy resolution and a high signal-to-noise ratio. It is a further object to provide a pulse processing system wherein the fast channel resolving time is quite short and substantially independent of the energy of the detected signals. Another object is to provide a pulse processing system having a pile-up rejector circuit which will allow the maximum number of non-interfering pulses to be passed to the output. It is also an object of the invention to provide new methods for generating substantially symmetrically triangular pulses for use in both the main and fast channels of a pulse processing system.

Reconfigurable nanoscale spin-wave directional coupler

PubMed Central

Wang, Qi; Pirro, Philipp; Verba, Roman; Slavin, Andrei; Hillebrands, Burkard; Chumak, Andrii V.

2018-01-01

Spin waves, and their quanta magnons, are prospective data carriers in future signal processing systems because Gilbert damping associated with the spin-wave propagation can be made substantially lower than the Joule heat losses in electronic devices. Although individual spin-wave signal processing devices have been successfully developed, the challenging contemporary problem is the formation of two-dimensional planar integrated spin-wave circuits. Using both micromagnetic modeling and analytical theory, we present an effective solution of this problem based on the dipolar interaction between two laterally adjacent nanoscale spin-wave waveguides. The developed device based on this principle can work as a multifunctional and dynamically reconfigurable signal directional coupler performing the functions of a waveguide crossing element, tunable power splitter, frequency separator, or multiplexer. The proposed design of a spin-wave directional coupler can be used both in digital logic circuits intended for spin-wave computing and in analog microwave signal processing devices. PMID:29376117

Characterizing scaling properties of complex signals with missed data segments using the multifractal analysis.

PubMed

Pavlov, A N; Pavlova, O N; Abdurashitov, A S; Sindeeva, O A; Semyachkina-Glushkovskaya, O V; Kurths, J

2018-01-01

The scaling properties of complex processes may be highly influenced by the presence of various artifacts in experimental recordings. Their removal produces changes in the singularity spectra and the Hölder exponents as compared with the original artifacts-free data, and these changes are significantly different for positively correlated and anti-correlated signals. While signals with power-law correlations are nearly insensitive to the loss of significant parts of data, the removal of fragments of anti-correlated signals is more crucial for further data analysis. In this work, we study the ability of characterizing scaling features of chaotic and stochastic processes with distinct correlation properties using a wavelet-based multifractal analysis, and discuss differences between the effect of missed data for synchronous and asynchronous oscillatory regimes. We show that even an extreme data loss allows characterizing physiological processes such as the cerebral blood flow dynamics.

Characterizing scaling properties of complex signals with missed data segments using the multifractal analysis

NASA Astrophysics Data System (ADS)

Pavlov, A. N.; Pavlova, O. N.; Abdurashitov, A. S.; Sindeeva, O. A.; Semyachkina-Glushkovskaya, O. V.; Kurths, J.

2018-01-01

The scaling properties of complex processes may be highly influenced by the presence of various artifacts in experimental recordings. Their removal produces changes in the singularity spectra and the Hölder exponents as compared with the original artifacts-free data, and these changes are significantly different for positively correlated and anti-correlated signals. While signals with power-law correlations are nearly insensitive to the loss of significant parts of data, the removal of fragments of anti-correlated signals is more crucial for further data analysis. In this work, we study the ability of characterizing scaling features of chaotic and stochastic processes with distinct correlation properties using a wavelet-based multifractal analysis, and discuss differences between the effect of missed data for synchronous and asynchronous oscillatory regimes. We show that even an extreme data loss allows characterizing physiological processes such as the cerebral blood flow dynamics.

Reconfigurable nanoscale spin-wave directional coupler.

PubMed

Wang, Qi; Pirro, Philipp; Verba, Roman; Slavin, Andrei; Hillebrands, Burkard; Chumak, Andrii V

2018-01-01

Spin waves, and their quanta magnons, are prospective data carriers in future signal processing systems because Gilbert damping associated with the spin-wave propagation can be made substantially lower than the Joule heat losses in electronic devices. Although individual spin-wave signal processing devices have been successfully developed, the challenging contemporary problem is the formation of two-dimensional planar integrated spin-wave circuits. Using both micromagnetic modeling and analytical theory, we present an effective solution of this problem based on the dipolar interaction between two laterally adjacent nanoscale spin-wave waveguides. The developed device based on this principle can work as a multifunctional and dynamically reconfigurable signal directional coupler performing the functions of a waveguide crossing element, tunable power splitter, frequency separator, or multiplexer. The proposed design of a spin-wave directional coupler can be used both in digital logic circuits intended for spin-wave computing and in analog microwave signal processing devices.

Perception of the dynamic visual vertical during sinusoidal linear motion.

PubMed

Pomante, A; Selen, L P J; Medendorp, W P

2017-10-01

The vestibular system provides information for spatial orientation. However, this information is ambiguous: because the otoliths sense the gravitoinertial force, they cannot distinguish gravitational and inertial components. As a consequence, prolonged linear acceleration of the head can be interpreted as tilt, referred to as the somatogravic effect. Previous modeling work suggests that the brain disambiguates the otolith signal according to the rules of Bayesian inference, combining noisy canal cues with the a priori assumption that prolonged linear accelerations are unlikely. Within this modeling framework the noise of the vestibular signals affects the dynamic characteristics of the tilt percept during linear whole-body motion. To test this prediction, we devised a novel paradigm to psychometrically characterize the dynamic visual vertical-as a proxy for the tilt percept-during passive sinusoidal linear motion along the interaural axis (0.33 Hz motion frequency, 1.75 m/s 2 peak acceleration, 80 cm displacement). While subjects ( n =10) kept fixation on a central body-fixed light, a line was briefly flashed (5 ms) at different phases of the motion, the orientation of which had to be judged relative to gravity. Consistent with the model's prediction, subjects showed a phase-dependent modulation of the dynamic visual vertical, with a subject-specific phase shift with respect to the imposed acceleration signal. The magnitude of this modulation was smaller than predicted, suggesting a contribution of nonvestibular signals to the dynamic visual vertical. Despite their dampening effect, our findings may point to a link between the noise components in the vestibular system and the characteristics of dynamic visual vertical. NEW & NOTEWORTHY A fundamental question in neuroscience is how the brain processes vestibular signals to infer the orientation of the body and objects in space. We show that, under sinusoidal linear motion, systematic error patterns appear in the disambiguation of linear acceleration and spatial orientation. We discuss the dynamics of these illusory percepts in terms of a dynamic Bayesian model that combines uncertainty in the vestibular signals with priors based on the natural statistics of head motion. Copyright © 2017 the American Physiological Society.

Striatal and Hippocampal Entropy and Recognition Signals in Category Learning: Simultaneous Processes Revealed by Model-Based fMRI

ERIC Educational Resources Information Center

Davis, Tyler; Love, Bradley C.; Preston, Alison R.

2012-01-01

Category learning is a complex phenomenon that engages multiple cognitive processes, many of which occur simultaneously and unfold dynamically over time. For example, as people encounter objects in the world, they simultaneously engage processes to determine their fit with current knowledge structures, gather new information about the objects, and…

Automated smoother for the numerical decoupling of dynamics models.

PubMed

Vilela, Marco; Borges, Carlos C H; Vinga, Susana; Vasconcelos, Ana Tereza R; Santos, Helena; Voit, Eberhard O; Almeida, Jonas S

2007-08-21

Structure identification of dynamic models for complex biological systems is the cornerstone of their reverse engineering. Biochemical Systems Theory (BST) offers a particularly convenient solution because its parameters are kinetic-order coefficients which directly identify the topology of the underlying network of processes. We have previously proposed a numerical decoupling procedure that allows the identification of multivariate dynamic models of complex biological processes. While described here within the context of BST, this procedure has a general applicability to signal extraction. Our original implementation relied on artificial neural networks (ANN), which caused slight, undesirable bias during the smoothing of the time courses. As an alternative, we propose here an adaptation of the Whittaker's smoother and demonstrate its role within a robust, fully automated structure identification procedure. In this report we propose a robust, fully automated solution for signal extraction from time series, which is the prerequisite for the efficient reverse engineering of biological systems models. The Whittaker's smoother is reformulated within the context of information theory and extended by the development of adaptive signal segmentation to account for heterogeneous noise structures. The resulting procedure can be used on arbitrary time series with a nonstationary noise process; it is illustrated here with metabolic profiles obtained from in-vivo NMR experiments. The smoothed solution that is free of parametric bias permits differentiation, which is crucial for the numerical decoupling of systems of differential equations. The method is applicable in signal extraction from time series with nonstationary noise structure and can be applied in the numerical decoupling of system of differential equations into algebraic equations, and thus constitutes a rather general tool for the reverse engineering of mechanistic model descriptions from multivariate experimental time series.

Biomedical signal and image processing.

PubMed

Cerutti, Sergio; Baselli, Giuseppe; Bianchi, Anna; Caiani, Enrico; Contini, Davide; Cubeddu, Rinaldo; Dercole, Fabio; Rienzo, Luca; Liberati, Diego; Mainardi, Luca; Ravazzani, Paolo; Rinaldi, Sergio; Signorini, Maria; Torricelli, Alessandro

2011-01-01

Generally, physiological modeling and biomedical signal processing constitute two important paradigms of biomedical engineering (BME): their fundamental concepts are taught starting from undergraduate studies and are more completely dealt with in the last years of graduate curricula, as well as in Ph.D. courses. Traditionally, these two cultural aspects were separated, with the first one more oriented to physiological issues and how to model them and the second one more dedicated to the development of processing tools or algorithms to enhance useful information from clinical data. A practical consequence was that those who did models did not do signal processing and vice versa. However, in recent years,the need for closer integration between signal processing and modeling of the relevant biological systems emerged very clearly [1], [2]. This is not only true for training purposes(i.e., to properly prepare the new professional members of BME) but also for the development of newly conceived research projects in which the integration between biomedical signal and image processing (BSIP) and modeling plays a crucial role. Just to give simple examples, topics such as brain–computer machine or interfaces,neuroengineering, nonlinear dynamical analysis of the cardiovascular (CV) system,integration of sensory-motor characteristics aimed at the building of advanced prostheses and rehabilitation tools, and wearable devices for vital sign monitoring and others do require an intelligent fusion of modeling and signal processing competences that are certainly peculiar of our discipline of BME.

A crossover trial comparing wide dynamic range compression and frequency compression in hearing aids for tinnitus therapy.

PubMed

Hodgson, Shirley-Anne; Herdering, Regina; Singh Shekhawat, Giriraj; Searchfield, Grant D

2017-01-01

It has been suggested that frequency lowering may be a superior tinnitus reducing digital signal processing (DSP) strategy in hearing aids than conventional amplification. A crossover trial was undertaken to determine if frequency compression (FC) was superior to wide dynamic range compression (WDRC) in reducing tinnitus. A 6-8-week crossover trial of two digital signal-processing techniques (WDRC and 2 WDRC with FC) was undertaken in 16 persons with high-frequency sensorineural hearing loss and chronic tinnitus. WDRC resulted in larger improvements in Tinnitus Functional Index and rating scale scores than WDRC with FC. The tinnitus improvements obtained with both processing types appear to be due to reduced hearing handicap and possibly decreased tinnitus audibility. Hearing aids are useful assistive devices in the rehabilitation of tinnitus. FC was very successful in a few individuals but was not superior to WDRC across the sample. It is recommended that WDRC remain as the default first choice tinnitus hearing aid processing strategy for tinnitus. FC should be considered as one of the many other options for selection based on individual hearing needs. Implications of Rehabilitation Hearing aids can significantly reduce the effects of tinnitus after 6-8 weeks of use. Addition of frequency compression digital signal processing does not appear superior to standard amplitude compression alone. Improvements in tinnitus were correlated with reductions in hearing handicap.

Dynamic Interaction- and Phospho-Proteomics Reveal Lck as a Major Signaling Hub of CD147 in T Cells.

PubMed

Supper, Verena; Hartl, Ingrid; Boulègue, Cyril; Ohradanova-Repic, Anna; Stockinger, Hannes

2017-03-15

Numerous publications have addressed CD147 as a tumor marker and regulator of cytoskeleton, cell growth, stress response, or immune cell function; however, the molecular functionality of CD147 remains incompletely understood. Using affinity purification, mass spectrometry, and phosphopeptide enrichment of isotope-labeled peptides, we examined the dynamic of the CD147 microenvironment and the CD147-dependent phosphoproteome in the Jurkat T cell line upon treatment with T cell stimulating agents. We identified novel dynamic interaction partners of CD147 such as CD45, CD47, GNAI2, Lck, RAP1B, and VAT1 and, furthermore, found 76 CD147-dependent phosphorylation sites on 57 proteins. Using the STRING protein network database, a network between the CD147 microenvironment and the CD147-dependent phosphoproteins was generated and led to the identification of key signaling hubs around the G proteins RAP1B and GNB1, the kinases PKCβ, PAK2, Lck, and CDK1, and the chaperone HSPA5. Gene ontology biological process term analysis revealed that wound healing-, cytoskeleton-, immune system-, stress response-, phosphorylation- and protein modification-, defense response to virus-, and TNF production-associated terms are enriched within the microenvironment and the phosphoproteins of CD147. With the generated signaling network and gene ontology biological process term grouping, we identify potential signaling routes of CD147 affecting T cell growth and function. Copyright © 2017 by The American Association of Immunologists, Inc.

Quantitative Microscopic Analysis of Plasma Membrane Receptor Dynamics in Living Plant Cells.

PubMed

Luo, Yu; Russinova, Eugenia

2017-01-01

Plasma membrane-localized receptors are essential for cellular communication and signal transduction. In Arabidopsis thaliana, BRASSINOSTEROID INSENSITIVE1 (BRI1) is one of the receptors that is activated by binding to its ligand, the brassinosteroid (BR) hormone, at the cell surface to regulate diverse plant developmental processes. The availability of BRI1 in the plasma membrane is related to its signaling output and is known to be controlled by the dynamic endomembrane trafficking. Advances in fluorescence labeling and confocal microscopy techniques enabled us to gain a better understanding of plasma membrane receptor dynamics in living cells. Here we describe different quantitative microscopy methods to monitor the relative steady-state levels of the BRI1 protein in the plasma membrane of root epidermal cells and its relative exocytosis and recycling rates. The methods can be applied also to analyze similar dynamics of other plasma membrane-localized receptors.

Effect of driving voltage polarity on dynamic response characteristics of electrowetting liquid lens

NASA Astrophysics Data System (ADS)

Na, Xie; Ning, Zhang; Rong-Qing, Xu

2018-05-01

A test device is developed for studying the dynamic process of an electrowetting liquid lens. By analyzing the light signals through the liquid lens, the dynamical properties of the lens are investigated. In our experiment, three types of pulse, i.e., sine, bipolar pulse, and single pulse signals, are employed to drive the liquid lens, and the dynamic characteristics of the lens are subsequently analyzed. The results show that the positive and negative polarities of the driving voltage can cause a significant difference in the response of the liquid lens; meanwhile, the lens’s response to the negative polarity of the driving voltage is clearer. We use the theory of charge restraint to explain this phenomenon, and it is concluded that the negative ions are more easily restrained by a dielectric layer. This work gives direct guidance for practical applications based on an electrowetting liquid lens.

Identification of Dynamic Patterns of Speech-Evoked Auditory Brainstem Response Based on Ensemble Empirical Mode Decomposition and Nonlinear Time Series Analysis Methods

NASA Astrophysics Data System (ADS)

Mozaffarilegha, Marjan; Esteki, Ali; Ahadi, Mohsen; Nazeri, Ahmadreza

The speech-evoked auditory brainstem response (sABR) shows how complex sounds such as speech and music are processed in the auditory system. Speech-ABR could be used to evaluate particular impairments and improvements in auditory processing system. Many researchers used linear approaches for characterizing different components of sABR signal, whereas nonlinear techniques are not applied so commonly. The primary aim of the present study is to examine the underlying dynamics of normal sABR signals. The secondary goal is to evaluate whether some chaotic features exist in this signal. We have presented a methodology for determining various components of sABR signals, by performing Ensemble Empirical Mode Decomposition (EEMD) to get the intrinsic mode functions (IMFs). Then, composite multiscale entropy (CMSE), the largest Lyapunov exponent (LLE) and deterministic nonlinear prediction are computed for each extracted IMF. EEMD decomposes sABR signal into five modes and a residue. The CMSE results of sABR signals obtained from 40 healthy people showed that 1st, and 2nd IMFs were similar to the white noise, IMF-3 with synthetic chaotic time series and 4th, and 5th IMFs with sine waveform. LLE analysis showed positive values for 3rd IMFs. Moreover, 1st, and 2nd IMFs showed overlaps with surrogate data and 3rd, 4th and 5th IMFs showed no overlap with corresponding surrogate data. Results showed the presence of noisy, chaotic and deterministic components in the signal which respectively corresponded to 1st, and 2nd IMFs, IMF-3, and 4th and 5th IMFs. While these findings provide supportive evidence of the chaos conjecture for the 3rd IMF, they do not confirm any such claims. However, they provide a first step towards an understanding of nonlinear behavior of auditory system dynamics in brainstem level.

Acousto-Optic Processing of 2-D Signals Using Temporal and Spatial Integration.

DTIC Science & Technology

1983-05-31

Documents includes data on: Architectures; Coherence Properties of Pulsed Laser Diodes; Acousto - optic device data; Dynamic Range Issues; Image correlation; Synthetic aperture radar; 2-D Fourier transform; and Moments.

Structural and Dynamic Insights into the Mechanism of Allosteric Signal Transmission in ERK2-Mediated MKP3 Activation.

PubMed

Lu, Chang; Liu, Xin; Zhang, Chen-Song; Gong, Haipeng; Wu, Jia-Wei; Wang, Zhi-Xin

2017-11-21

The mitogen-activated protein kinases (MAPKs) are key components of cellular signal transduction pathways, which are down-regulated by the MAPK phosphatases (MKPs). Catalytic activity of the MKPs is controlled both by their ability to recognize selective MAPKs and by allosteric activation upon binding to MAPK substrates. Here, we use a combination of experimental and computational techniques to elucidate the molecular mechanism for the ERK2-induced MKP3 activation. Mutational and kinetic study shows that the 334 FNFM 337 motif in the MKP3 catalytic domain is essential for MKP3-mediated ERK2 inactivation and is responsible for ERK2-mediated MKP3 activation. The long-term molecular dynamics (MD) simulations further reveal a complete dynamic process in which the catalytic domain of MKP3 gradually changes to a conformation that resembles an active MKP catalytic domain over the time scale of the simulation, providing a direct time-dependent observation of allosteric signal transmission in ERK2-induced MKP3 activation.

Calcium and ROS: A mutual interplay

PubMed Central

Görlach, Agnes; Bertram, Katharina; Hudecova, Sona; Krizanova, Olga

2015-01-01

Calcium is an important second messenger involved in intra- and extracellular signaling cascades and plays an essential role in cell life and death decisions. The Ca2+ signaling network works in many different ways to regulate cellular processes that function over a wide dynamic range due to the action of buffers, pumps and exchangers on the plasma membrane as well as in internal stores. Calcium signaling pathways interact with other cellular signaling systems such as reactive oxygen species (ROS). Although initially considered to be potentially detrimental byproducts of aerobic metabolism, it is now clear that ROS generated in sub-toxic levels by different intracellular systems act as signaling molecules involved in various cellular processes including growth and cell death. Increasing evidence suggests a mutual interplay between calcium and ROS signaling systems which seems to have important implications for fine tuning cellular signaling networks. However, dysfunction in either of the systems might affect the other system thus potentiating harmful effects which might contribute to the pathogenesis of various disorders. PMID:26296072

Broadband true time delay for microwave signal processing, using slow light based on stimulated Brillouin scattering in optical fibers.

PubMed

Chin, Sanghoon; Thévenaz, Luc; Sancho, Juan; Sales, Salvador; Capmany, José; Berger, Perrine; Bourderionnet, Jérôme; Dolfi, Daniel

2010-10-11

We experimentally demonstrate a novel technique to process broadband microwave signals, using all-optically tunable true time delay in optical fibers. The configuration to achieve true time delay basically consists of two main stages: photonic RF phase shifter and slow light, based on stimulated Brillouin scattering in fibers. Dispersion properties of fibers are controlled, separately at optical carrier frequency and in the vicinity of microwave signal bandwidth. This way time delay induced within the signal bandwidth can be manipulated to correctly act as true time delay with a proper phase compensation introduced to the optical carrier. We completely analyzed the generated true time delay as a promising solution to feed phased array antenna for radar systems and to develop dynamically reconfigurable microwave photonic filters.

Improved signal recovery for flow cytometry based on ‘spatially modulated emission’

NASA Astrophysics Data System (ADS)

Quint, S.; Wittek, J.; Spang, P.; Levanon, N.; Walther, T.; Baßler, M.

2017-09-01

Recently, the technique of ‘spatially modulated emission’ has been introduced (Baßler et al 2008 US Patent 0080181827A1; Kiesel et al 2009 Appl. Phys. Lett. 94 041107; Kiesel et al 2011 Cytometry A 79A 317-24) improving the signal-to-noise ratio (SNR) for detecting bio-particles in the field of flow cytometry. Based on this concept, we developed two advanced signal processing methods which further enhance the SNR and selectivity for cell detection. The improvements are achieved by adapting digital filtering methods from RADAR technology and mainly address inherent offset elimination, increased signal dynamics and moreover reduction of erroneous detections due to processing artifacts. We present a comprehensive theory on SNR gain and provide experimental results of our concepts.

Dynamic intervention: pathogen disarmament of mitochondrial-based immune surveillance.

PubMed

Holland, Robin L; Blanke, Steven R

2014-11-12

In this issue of Cell Host & Microbe, Suzuki et al. (2014) describe a Vibrio cholerae Type-III-secreted effector that targets mitochondrial dynamics to dampen host innate immune signaling. This suggests that mammalian hosts possess surveillance mechanisms to monitor pathogen-mediated alterations in the integrity of normal cellular processes and organelles. Copyright © 2014 Elsevier Inc. All rights reserved.

Stochastic nonlinear dynamics pattern formation and growth models

PubMed Central

Yaroslavsky, Leonid P

2007-01-01

Stochastic evolutionary growth and pattern formation models are treated in a unified way in terms of algorithmic models of nonlinear dynamic systems with feedback built of a standard set of signal processing units. A number of concrete models is described and illustrated by numerous examples of artificially generated patterns that closely imitate wide variety of patterns found in the nature. PMID:17908341

Space-time dynamics of Stem Cell Niches: a unified approach for Plants.

PubMed

Pérez, Maria Del Carmen; López, Alejandro; Padilla, Pablo

2013-06-01

Many complex systems cannot be analyzed using traditional mathematical tools, due to their irreducible nature. This makes it necessary to develop models that can be implemented computationally to simulate their evolution. Examples of these models are cellular automata, evolutionary algorithms, complex networks, agent-based models, symbolic dynamics and dynamical systems techniques. We review some representative approaches to model the stem cell niche in Arabidopsis thaliana and the basic biological mechanisms that underlie its formation and maintenance. We propose a mathematical model based on cellular automata for describing the space-time dynamics of the stem cell niche in the root. By making minimal assumptions on the cell communication process documented in experiments, we classify the basic developmental features of the stem-cell niche, including the basic structural architecture, and suggest that they could be understood as the result of generic mechanisms given by short and long range signals. This could be a first step in understanding why different stem cell niches share similar topologies, not only in plants. Also the fact that this organization is a robust consequence of the way information is being processed by the cells and to some extent independent of the detailed features of the signaling mechanism.

Space-time dynamics of stem cell niches: a unified approach for plants.

PubMed

Pérez, Maria del Carmen; López, Alejandro; Padilla, Pablo

2013-04-02

Many complex systems cannot be analyzed using traditional mathematical tools, due to their irreducible nature. This makes it necessary to develop models that can be implemented computationally to simulate their evolution. Examples of these models are cellular automata, evolutionary algorithms, complex networks, agent-based models, symbolic dynamics and dynamical systems techniques. We review some representative approaches to model the stem cell niche in Arabidopsis thaliana and the basic biological mechanisms that underlie its formation and maintenance. We propose a mathematical model based on cellular automata for describing the space-time dynamics of the stem cell niche in the root. By making minimal assumptions on the cell communication process documented in experiments, we classify the basic developmental features of the stem-cell niche, including the basic structural architecture, and suggest that they could be understood as the result of generic mechanisms given by short and long range signals. This could be a first step in understanding why different stem cell niches share similar topologies, not only in plants. Also the fact that this organization is a robust consequence of the way information is being processed by the cells and to some extent independent of the detailed features of the signaling mechanism.

Spatio-temporal diffusion of dynamic PET images

NASA Astrophysics Data System (ADS)

Tauber, C.; Stute, S.; Chau, M.; Spiteri, P.; Chalon, S.; Guilloteau, D.; Buvat, I.

2011-10-01

Positron emission tomography (PET) images are corrupted by noise. This is especially true in dynamic PET imaging where short frames are required to capture the peak of activity concentration after the radiotracer injection. High noise results in a possible bias in quantification, as the compartmental models used to estimate the kinetic parameters are sensitive to noise. This paper describes a new post-reconstruction filter to increase the signal-to-noise ratio in dynamic PET imaging. It consists in a spatio-temporal robust diffusion of the 4D image based on the time activity curve (TAC) in each voxel. It reduces the noise in homogeneous areas while preserving the distinct kinetics in regions of interest corresponding to different underlying physiological processes. Neither anatomical priors nor the kinetic model are required. We propose an automatic selection of the scale parameter involved in the diffusion process based on a robust statistical analysis of the distances between TACs. The method is evaluated using Monte Carlo simulations of brain activity distributions. We demonstrate the usefulness of the method and its superior performance over two other post-reconstruction spatial and temporal filters. Our simulations suggest that the proposed method can be used to significantly increase the signal-to-noise ratio in dynamic PET imaging.

Load-induced modulation of signal transduction networks.

PubMed

Jiang, Peng; Ventura, Alejandra C; Sontag, Eduardo D; Merajver, Sofia D; Ninfa, Alexander J; Del Vecchio, Domitilla

2011-10-11

Biological signal transduction networks are commonly viewed as circuits that pass along information--in the process amplifying signals, enhancing sensitivity, or performing other signal-processing tasks--to transcriptional and other components. Here, we report on a "reverse-causality" phenomenon, which we call load-induced modulation. Through a combination of analytical and experimental tools, we discovered that signaling was modulated, in a surprising way, by downstream targets that receive the signal and, in doing so, apply what in physics is called a load. Specifically, we found that non-intuitive changes in response dynamics occurred for a covalent modification cycle when load was present. Loading altered the response time of a system, depending on whether the activity of one of the enzymes was maximal and the other was operating at its minimal rate or whether both enzymes were operating at submaximal rates. These two conditions, which we call "limit regime" and "intermediate regime," were associated with increased or decreased response times, respectively. The bandwidth, the range of frequency in which the system can process information, decreased in the presence of load, suggesting that downstream targets participate in establishing a balance between noise-filtering capabilities and a circuit's ability to process high-frequency stimulation. Nodes in a signaling network are not independent relay devices, but rather are modulated by their downstream targets.

System for Processing Coded OFDM Under Doppler and Fading

NASA Technical Reports Server (NTRS)

Tsou, Haiping; Darden, Scott; Lee, Dennis; Yan, Tsun-Yee

2005-01-01

An advanced communication system has been proposed for transmitting and receiving coded digital data conveyed as a form of quadrature amplitude modulation (QAM) on orthogonal frequency-division multiplexing (OFDM) signals in the presence of such adverse propagation-channel effects as large dynamic Doppler shifts and frequency-selective multipath fading. Such adverse channel effects are typical of data communications between mobile units or between mobile and stationary units (e.g., telemetric transmissions from aircraft to ground stations). The proposed system incorporates novel signal processing techniques intended to reduce the losses associated with adverse channel effects while maintaining compatibility with the high-speed physical layer specifications defined for wireless local area networks (LANs) as the standard 802.11a of the Institute of Electrical and Electronics Engineers (IEEE 802.11a). OFDM is a multi-carrier modulation technique that is widely used for wireless transmission of data in LANs and in metropolitan area networks (MANs). OFDM has been adopted in IEEE 802.11a and some other industry standards because it affords robust performance under frequency-selective fading. However, its intrinsic frequency-diversity feature is highly sensitive to synchronization errors; this sensitivity poses a challenge to preserve coherence between the component subcarriers of an OFDM system in order to avoid intercarrier interference in the presence of large dynamic Doppler shifts as well as frequency-selective fading. As a result, heretofore, the use of OFDM has been limited primarily to applications involving small or zero Doppler shifts. The proposed system includes a digital coherent OFDM communication system that would utilize enhanced 802.1la-compatible signal-processing algorithms to overcome effects of frequency-selective fading and large dynamic Doppler shifts. The overall transceiver design would implement a two-frequency-channel architecture (see figure) that would afford frequency diversity for reducing the adverse effects of multipath fading. By using parallel concatenated convolutional codes (also known as Turbo codes) across the dual-channel and advanced OFDM signal processing within each channel, the proposed system is intended to achieve at least an order of magnitude improvement in received signal-to-noise ratio under adverse channel effects while preserving spectral efficiency.

Energy shadowing correction of ultrasonic pulse-echo records by digital signal processing

NASA Technical Reports Server (NTRS)

Kishoni, D.; Heyman, J. S.

1986-01-01

Attention is given to a numerical algorithm that, via signal processing, enables the dynamic correction of the shadowing effect of reflections on ultrasonic displays. The algorithm was applied to experimental data from graphite-epoxy composite material immersed in a water bath. It is concluded that images of material defects with the shadowing corrections allow for a more quantitative interpretation of the material state. It is noted that the proposed algorithm is fast and simple enough to be adopted for real time applications in industry.

Dimension from covariance matrices.

PubMed

Carroll, T L; Byers, J M

2017-02-01

We describe a method to estimate embedding dimension from a time series. This method includes an estimate of the probability that the dimension estimate is valid. Such validity estimates are not common in algorithms for calculating the properties of dynamical systems. The algorithm described here compares the eigenvalues of covariance matrices created from an embedded signal to the eigenvalues for a covariance matrix of a Gaussian random process with the same dimension and number of points. A statistical test gives the probability that the eigenvalues for the embedded signal did not come from the Gaussian random process.

Low-noise pulse conditioner

DOEpatents

Bird, David A.

1983-01-01

A low-noise pulse conditioner is provided for driving electronic digital processing circuitry directly from differentially induced input pulses. The circuit uses a unique differential-to-peak detector circuit to generate a dynamic reference signal proportional to the input peak voltage. The input pulses are compared with the reference signal in an input network which operates in full differential mode with only a passive input filter. This reduces the introduction of circuit-induced noise, or jitter, generated in ground referenced input elements normally used in pulse conditioning circuits, especially speed transducer processing circuits.

Low-noise pulse conditioner

DOEpatents

Bird, D.A.

1981-06-16

A low-noise pulse conditioner is provided for driving electronic digital processing circuitry directly from differentially induced input pulses. The circuit uses a unique differential-to-peak detector circuit to generate a dynamic reference signal proportional to the input peak voltage. The input pulses are compared with the reference signal in an input network which operates in full differential mode with only a passive input filter. This reduces the introduction of circuit-induced noise, or jitter, generated in ground referenced input elements normally used in pulse conditioning circuits, especially speed transducer processing circuits. This circuit may be used for conditioning the sensor signal from the Fidler coil in a gas centrifuge for separation of isotopic gaseous mixtures.

Dynamic Neurovascular Coupling and Uncoupling during Ictal Onset, Propagation, and Termination Revealed by Simultaneous In Vivo Optical Imaging of Neural Activity and Local Blood Volume

PubMed Central

Zhao, Mingrui; Schwartz, Theodore H.

2013-01-01

Traditional models of ictal propagation involve the concept of an initiation site and a progressive outward march of activation. The process of neurovascular coupling, whereby the brain supplies oxygenated blood to metabolically active neurons presumably results in a similar outward cascade of hyperemia. However, ictal neurovascular coupling has never been assessed in vivo using simultaneous measurements of membrane potential change and hyperemia with wide spatial sampling. In an acute rat ictal model, using simultaneous intrinsic optical signal (IOS) and voltage-sensitive dye (VSD) imaging of cerebral blood volume and membrane potential changes, we demonstrate that seizures consist of multiple dynamic multidirectional waves of membrane potential change with variable onset sites that spread through a widespread network. Local blood volume evolves on a much slower spatiotemporal scale. At seizure onset, the VSD waves extend beyond the IOS signal. During evolution, spatial correlation with hemodynamic signal only exists briefly at the maximal spread of the VSD signal. At termination, the IOS signal extends spatially and temporally beyond the VSD waves. Hence, vascular reactivity evolves in a separate but parallel fashion to membrane potential changes resulting in a mechanism of neurovascular coupling and uncoupling, which is as dynamic as the seizure itself. PMID:22499798

Phase-sensitive, through-amplification with a double-pumped JPC

NASA Astrophysics Data System (ADS)

Sliwa, K. M.; Hatridge, M.; Frattini, N. E.; Narla, A.; Shankar, S.; Devoret, M. H.

The Josephson Parametric Converter (JPC) is now routinely used as a quantum-limited signal processing device for superconducting qubit experiments. The JPC consists of two modes, the signal and the idler, that are coupled by a ring of Josephson junctions that implements a non-degenerate, three-wave mixing process. This device is conventionally operated as either a phase-preserving parametric amplifier, or a coherent frequency converter, by pumping it at the sum or difference of the signal and idler frequencies, respectively. Here we present a novel double-pumping scheme based on theory by Metelmann and Clerk where a coherent conversion process and a gain process are simultaneously imposed between the signal and idler modes. The interference of these two processes results in a phase-sensitive amplifier with only forward gain, and which breaks the traditional gain-bandwidth limit of parametric amplification. We present results on phase-sensitive amplification with increased bandwidth, and on noise performance and dynamic range that are comparable to the traditional mode of operation. Work supported by ARO, AFOSR, NSF and YINQE.

Method and apparatus for analog signal conditioner for high speed, digital x-ray spectrometer

DOEpatents

Warburton, William K.; Hubbard, Bradley

1999-01-01

A signal processing system which accepts input from an x-ray detector-preamplifier and produces a signal of reduced dynamic range for subsequent analog-to-digital conversion. The system conditions the input signal to reduce the number of bits required in the analog-to-digital converter by removing that part of the input signal which varies only slowly in time and retaining the amplitude of the pulses which carry information about the x-rays absorbed by the detector. The parameters controlling the signal conditioner's operation can be readily supplied in digital form, allowing it to be integrated into a feedback loop as part of a larger digital x-ray spectroscopy system.

Major transcriptome re-organisation and abrupt changes in signalling, cell cycle and chromatin regulation at neural differentiation in vivo.

PubMed

Olivera-Martinez, Isabel; Schurch, Nick; Li, Roman A; Song, Junfang; Halley, Pamela A; Das, Raman M; Burt, Dave W; Barton, Geoffrey J; Storey, Kate G

2014-08-01

Here, we exploit the spatial separation of temporal events of neural differentiation in the elongating chick body axis to provide the first analysis of transcriptome change in progressively more differentiated neural cell populations in vivo. Microarray data, validated against direct RNA sequencing, identified: (1) a gene cohort characteristic of the multi-potent stem zone epiblast, which contains neuro-mesodermal progenitors that progressively generate the spinal cord; (2) a major transcriptome re-organisation as cells then adopt a neural fate; and (3) increasing diversity as neural patterning and neuron production begin. Focussing on the transition from multi-potent to neural state cells, we capture changes in major signalling pathways, uncover novel Wnt and Notch signalling dynamics, and implicate new pathways (mevalonate pathway/steroid biogenesis and TGFβ). This analysis further predicts changes in cellular processes, cell cycle, RNA-processing and protein turnover as cells acquire neural fate. We show that these changes are conserved across species and provide biological evidence for reduced proteasome efficiency and a novel lengthening of S phase. This latter step may provide time for epigenetic events to mediate large-scale transcriptome re-organisation; consistent with this, we uncover simultaneous downregulation of major chromatin modifiers as the neural programme is established. We further demonstrate that transcription of one such gene, HDAC1, is dependent on FGF signalling, making a novel link between signals that control neural differentiation and transcription of a core regulator of chromatin organisation. Our work implicates new signalling pathways and dynamics, cellular processes and epigenetic modifiers in neural differentiation in vivo, identifying multiple new potential cellular and molecular mechanisms that direct differentiation. © 2014. Published by The Company of Biologists Ltd.

The dynamic of FUS-induced BBB Opening in Mouse Brain assessed by contrast enhanced MRI

NASA Astrophysics Data System (ADS)

Jenne, Jürgen W.; Krafft, Axel J.; Maier, Florian; Krause, Marie N.; Kleber, Susanne; Huber, Peter E.; Martin-Villalba, Ana; Bock, Michael

2010-03-01

Focused ultrasound (FUS) in combination with the administration of gas-filled microbubbles, can induce a localized and reversible opening of the blood brain barrier (BBB). Contrast enhanced magnetic resonance imaging (MRI) has been demonstrated as a precise tool to monitor such a local BBB disruption. However, the opening/closing mechanisms of the BBB with FUS are still largely unknown. In this ongoing project, we study the BBB opening dynamics in mouse brain comparing an interstitial and an intravascular MR contrast agent (CA). FUS in mouse brain was performed with an MRI compatible treatment setup (1.7 MHz fix-focus US transducer, f' = 68 mm, NA = 0.44; focus: 8.1 mm length; O/ = 1.1 mm) in a 1.5 T whole body MRI system. For BBB opening, forty 10 ms-long FUS-pulses were applied at a repetition rate of 1 Hz at 1 MPa. The i.v. administration of the micro bubbles (50 μl SonoVue®) was started simultaneously with FUS exposure. To analyze the BBB opening process, short-term and long-term MRI signal dynamics of the interstitial MR contrast agent Magnevist® and the intravascular CA Vasovist® (Bayer-Schering) were studied. To assess short-term signal dynamics, T1-weighted inversion recovery turbo FLASH images (1s) were repeatedly acquired. Repeated 3D FLASH acquisitions (90 s) were used to assess long-term MRI signal dynamics. The short-term MRI signal enhancements showed comparable time constants for both types of MR contrast agents: 1.1 s (interstitial) vs. 0.8 s (intravascular). This time constant may serve as a time constant of the BBB opening process with the given FUS exposure parameters. For the long-term signal dynamics the intravascular CA (62±10 min) showed a fife times greater time constant as the interstitial contrast agent (12±10 min). This might be explained by the high molecular weight (˜60 kDa) of the intravascular Vasovist due to its reversible binding to blood serum albumin resulting in a prolonged half-life in the blood stream compared to the interstitial CA. As the intravascular CA offers a much longer time window for therapy assessment, FUS-BBB therapy control with an intravascular CA might be favorable.

A Nonlinear Dynamical Systems based Model for Stochastic Simulation of Streamflow

NASA Astrophysics Data System (ADS)

Erkyihun, S. T.; Rajagopalan, B.; Zagona, E. A.

2014-12-01

Traditional time series methods model the evolution of the underlying process as a linear or nonlinear function of the autocorrelation. These methods capture the distributional statistics but are incapable of providing insights into the dynamics of the process, the potential regimes, and predictability. This work develops a nonlinear dynamical model for stochastic simulation of streamflows. In this, first a wavelet spectral analysis is employed on the flow series to isolate dominant orthogonal quasi periodic timeseries components. The periodic bands are added denoting the 'signal' component of the time series and the residual being the 'noise' component. Next, the underlying nonlinear dynamics of this combined band time series is recovered. For this the univariate time series is embedded in a d-dimensional space with an appropriate lag T to recover the state space in which the dynamics unfolds. Predictability is assessed by quantifying the divergence of trajectories in the state space with time, as Lyapunov exponents. The nonlinear dynamics in conjunction with a K-nearest neighbor time resampling is used to simulate the combined band, to which the noise component is added to simulate the timeseries. We demonstrate this method by applying it to the data at Lees Ferry that comprises of both the paleo reconstructed and naturalized historic annual flow spanning 1490-2010. We identify interesting dynamics of the signal in the flow series and epochal behavior of predictability. These will be of immense use for water resources planning and management.

Interoceptive signals impact visual processing: Cardiac modulation of visual body perception.

PubMed

Ronchi, Roberta; Bernasconi, Fosco; Pfeiffer, Christian; Bello-Ruiz, Javier; Kaliuzhna, Mariia; Blanke, Olaf

2017-09-01

Multisensory perception research has largely focused on exteroceptive signals, but recent evidence has revealed the integration of interoceptive signals with exteroceptive information. Such research revealed that heartbeat signals affect sensory (e.g., visual) processing: however, it is unknown how they impact the perception of body images. Here we linked our participants' heartbeat to visual stimuli and investigated the spatio-temporal brain dynamics of cardio-visual stimulation on the processing of human body images. We recorded visual evoked potentials with 64-channel electroencephalography while showing a body or a scrambled-body (control) that appeared at the frequency of the on-line recorded participants' heartbeat or not (not-synchronous, control). Extending earlier studies, we found a body-independent effect, with cardiac signals enhancing visual processing during two time periods (77-130 ms and 145-246 ms). Within the second (later) time-window we detected a second effect characterised by enhanced activity in parietal, temporo-occipital, inferior frontal, and right basal ganglia-insula regions, but only when non-scrambled body images were flashed synchronously with the heartbeat (208-224 ms). In conclusion, our results highlight the role of interoceptive information for the visual processing of human body pictures within a network integrating cardio-visual signals of relevance for perceptual and cognitive aspects of visual body processing. Copyright © 2017 Elsevier Inc. All rights reserved.

Application of Ensemble Detection and Analysis to Modeling Uncertainty in Non Stationary Process

NASA Technical Reports Server (NTRS)

Racette, Paul

2010-01-01

Characterization of non stationary and nonlinear processes is a challenge in many engineering and scientific disciplines. Climate change modeling and projection, retrieving information from Doppler measurements of hydrometeors, and modeling calibration architectures and algorithms in microwave radiometers are example applications that can benefit from improvements in the modeling and analysis of non stationary processes. Analyses of measured signals have traditionally been limited to a single measurement series. Ensemble Detection is a technique whereby mixing calibrated noise produces an ensemble measurement set. The collection of ensemble data sets enables new methods for analyzing random signals and offers powerful new approaches to studying and analyzing non stationary processes. Derived information contained in the dynamic stochastic moments of a process will enable many novel applications.

An Internet of Things based physiological signal monitoring and receiving system for virtual enhanced health care network.

PubMed

Rajan, J Pandia; Rajan, S Edward

2018-01-01

Wireless physiological signal monitoring system designing with secured data communication in the health care system is an important and dynamic process. We propose a signal monitoring system using NI myRIO connected with the wireless body sensor network through multi-channel signal acquisition method. Based on the server side validation of the signal, the data connected to the local server is updated in the cloud. The Internet of Things (IoT) architecture is used to get the mobility and fast access of patient data to healthcare service providers. This research work proposes a novel architecture for wireless physiological signal monitoring system using ubiquitous healthcare services by virtual Internet of Things. We showed an improvement in method of access and real time dynamic monitoring of physiological signal of this remote monitoring system using virtual Internet of thing approach. This remote monitoring and access system is evaluated in conventional value. This proposed system is envisioned to modern smart health care system by high utility and user friendly in clinical applications. We claim that the proposed scheme significantly improves the accuracy of the remote monitoring system compared to the other wireless communication methods in clinical system.

Raman and Autofluorescence Spectrum Dynamics along the HRG-Induced Differentiation Pathway of MCF-7 Cells

PubMed Central

Morita, Shin-ichi; Takanezawa, Sota; Hiroshima, Michio; Mitsui, Toshiyuki; Ozaki, Yukihiro; Sako, Yasushi

2014-01-01

Cellular differentiation proceeds along complicated pathways, even when it is induced by extracellular signaling molecules. One of the major reasons for this complexity is the highly multidimensional internal dynamics of cells, which sometimes causes apparently stochastic responses in individual cells to extracellular stimuli. Therefore, to understand cell differentiation, it is necessary to monitor the internal dynamics of cells at single-cell resolution. Here, we used a Raman and autofluorescence spectrum analysis of single cells to detect dynamic changes in intracellular molecular components. MCF-7 cells are a human cancer-derived cell line that can be induced to differentiate into mammary-gland-like cells with the addition of heregulin (HRG) to the culture medium. We measured the spectra in the cytoplasm of MCF-7 cells during 12 days of HRG stimulation. The Raman scattering spectrum, which was the major component of the signal, changed with time. A multicomponent analysis of the Raman spectrum revealed that the dynamics of the major components of the intracellular molecules, including proteins and lipids, changed cyclically along the differentiation pathway. The background autofluorescence signals of Raman scattering also provided information about the differentiation process. Using the total information from the Raman and autofluorescence spectra, we were able to visualize the pathway of cell differentiation in the multicomponent phase space. PMID:25418290

Ultra-Low Power Dynamic Knob in Adaptive Compressed Sensing Towards Biosignal Dynamics.

PubMed

Wang, Aosen; Lin, Feng; Jin, Zhanpeng; Xu, Wenyao

2016-06-01

Compressed sensing (CS) is an emerging sampling paradigm in data acquisition. Its integrated analog-to-information structure can perform simultaneous data sensing and compression with low-complexity hardware. To date, most of the existing CS implementations have a fixed architectural setup, which lacks flexibility and adaptivity for efficient dynamic data sensing. In this paper, we propose a dynamic knob (DK) design to effectively reconfigure the CS architecture by recognizing the biosignals. Specifically, the dynamic knob design is a template-based structure that comprises a supervised learning module and a look-up table module. We model the DK performance in a closed analytic form and optimize the design via a dynamic programming formulation. We present the design on a 130 nm process, with a 0.058 mm (2) fingerprint and a 187.88 nJ/event energy-consumption. Furthermore, we benchmark the design performance using a publicly available dataset. Given the energy constraint in wireless sensing, the adaptive CS architecture can consistently improve the signal reconstruction quality by more than 70%, compared with the traditional CS. The experimental results indicate that the ultra-low power dynamic knob can provide an effective adaptivity and improve the signal quality in compressed sensing towards biosignal dynamics.

Imaging dynamic redox processes with genetically encoded probes.

PubMed

Ezeriņa, Daria; Morgan, Bruce; Dick, Tobias P

2014-08-01

Redox signalling plays an important role in many aspects of physiology, including that of the cardiovascular system. Perturbed redox regulation has been associated with numerous pathological conditions; nevertheless, the causal relationships between redox changes and pathology often remain unclear. Redox signalling involves the production of specific redox species at specific times in specific locations. However, until recently, the study of these processes has been impeded by a lack of appropriate tools and methodologies that afford the necessary redox species specificity and spatiotemporal resolution. Recently developed genetically encoded fluorescent redox probes now allow dynamic real-time measurements, of defined redox species, with subcellular compartment resolution, in intact living cells. Here we discuss the available genetically encoded redox probes in terms of their sensitivity and specificity and highlight where uncertainties or controversies currently exist. Furthermore, we outline major goals for future probe development and describe how progress in imaging methodologies will improve our ability to employ genetically encoded redox probes in a wide range of situations. This article is part of a special issue entitled "Redox Signalling in the Cardiovascular System." Copyright © 2014 Elsevier Ltd. All rights reserved.

Novel dental dynamic depth profilometric imaging using simultaneous frequency-domain infrared photothermal radiometry and laser luminescence

NASA Astrophysics Data System (ADS)

Nicolaides, Lena; Mandelis, Andreas

2000-01-01

A high-spatial-resolution dynamic experimental imaging setup, which can provide simultaneous measurements of laser- induced frequency-domain infrared photothermal radiometric and luminescence signals from defects in teeth, has been developed for the first time. The major findings of this work are: (1) radiometric images are complementary to (anticorrelated with) luminescence images, as a result of the nature of the two physical signal generation processes; (2) the radiometric amplitude exhibits much superior dynamic (signal resolution) range to luminescence in distinguishing between intact and cracked sub-surface structures in the enamel; (3) the radiometric signal (amplitude and phase) produces dental images with much better defect localization, delineation, and resolution; (4) radiometric images (amplitude and phase) at a fixed modulation frequency are depth profilometric, whereas luminescence images are not; and (5) luminescence frequency responses from enamel and hydroxyapatite exhibit two relaxation lifetimes, the longer of which (approximately ms) is common to all and is not sensitive to the defect state and overall quality of the enamel. Simultaneous radiometric and luminescence frequency scans for the purpose of depth profiling were performed and a quantitative theoretical two-lifetime rate model of dental luminescence was advanced.

Single-Molecule Imaging Reveals the Activation Dynamics of Intracellular Protein Smad3 on Cell Membrane

NASA Astrophysics Data System (ADS)

Li, Nan; Yang, Yong; He, Kangmin; Zhang, Fayun; Zhao, Libo; Zhou, Wei; Yuan, Jinghe; Liang, Wei; Fang, Xiaohong

2016-09-01

Smad3 is an intracellular protein that plays a key role in propagating transforming growth factor β (TGF-β) signals from cell membrane to nucleus. However whether the transient process of Smad3 activation occurs on cell membrane and how it is regulated remains elusive. Using advanced live-cell single-molecule fluorescence microscopy to image and track fluorescent protein-labeled Smad3, we observed and quantified, for the first time, the dynamics of individual Smad3 molecules docking to and activation on the cell membrane. It was found that Smad3 docked to cell membrane in both unstimulated and stimulated cells, but with different diffusion rates and dissociation kinetics. The change in its membrane docking dynamics can be used to study the activation of Smad3. Our results reveal that Smad3 binds with type I TGF-β receptor (TRI) even in unstimulated cells. Its activation is regulated by TRI phosphorylation but independent of receptor endocytosis. This study offers new information on TGF-β/Smad signaling, as well as a new approach to investigate the activation of intracellular signaling proteins for a better understanding of their functions in signal transduction.

Coherent fifth-order visible-infrared spectroscopies: ultrafast nonequilibrium vibrational dynamics in solution.

PubMed

Lynch, Michael S; Slenkamp, Karla M; Cheng, Mark; Khalil, Munira

2012-07-05

Obtaining a detailed description of photochemical reactions in solution requires measuring time-evolving structural dynamics of transient chemical species on ultrafast time scales. Time-resolved vibrational spectroscopies are sensitive probes of molecular structure and dynamics in solution. In this work, we develop doubly resonant fifth-order nonlinear visible-infrared spectroscopies to probe nonequilibrium vibrational dynamics among coupled high-frequency vibrations during an ultrafast charge transfer process using a heterodyne detection scheme. The method enables the simultaneous collection of third- and fifth-order signals, which respectively measure vibrational dynamics occurring on electronic ground and excited states on a femtosecond time scale. Our data collection and analysis strategy allows transient dispersed vibrational echo (t-DVE) and dispersed pump-probe (t-DPP) spectra to be extracted as a function of electronic and vibrational population periods with high signal-to-noise ratio (S/N > 25). We discuss how fifth-order experiments can measure (i) time-dependent anharmonic vibrational couplings, (ii) nonequilibrium frequency-frequency correlation functions, (iii) incoherent and coherent vibrational relaxation and transfer dynamics, and (iv) coherent vibrational and electronic (vibronic) coupling as a function of a photochemical reaction.

Reconstruction of dynamical systems from resampled point processes produced by neuron models

NASA Astrophysics Data System (ADS)

Pavlova, Olga N.; Pavlov, Alexey N.

2018-04-01

Characterization of dynamical features of chaotic oscillations from point processes is based on embedding theorems for non-uniformly sampled signals such as the sequences of interspike intervals (ISIs). This theoretical background confirms the ability of attractor reconstruction from ISIs generated by chaotically driven neuron models. The quality of such reconstruction depends on the available length of the analyzed dataset. We discuss how data resampling improves the reconstruction for short amount of data and show that this effect is observed for different types of mechanisms for spike generation.

Serotonin 2A Receptor Signaling Underlies LSD-induced Alteration of the Neural Response to Dynamic Changes in Music.

PubMed

Barrett, Frederick S; Preller, Katrin H; Herdener, Marcus; Janata, Petr; Vollenweider, Franz X

2017-09-28

Classic psychedelic drugs (serotonin 2A, or 5HT2A, receptor agonists) have notable effects on music listening. In the current report, blood oxygen level-dependent (BOLD) signal was collected during music listening in 25 healthy adults after administration of placebo, lysergic acid diethylamide (LSD), and LSD pretreated with the 5HT2A antagonist ketanserin, to investigate the role of 5HT2A receptor signaling in the neural response to the time-varying tonal structure of music. Tonality-tracking analysis of BOLD data revealed that 5HT2A receptor signaling alters the neural response to music in brain regions supporting basic and higher-level musical and auditory processing, and areas involved in memory, emotion, and self-referential processing. This suggests a critical role of 5HT2A receptor signaling in supporting the neural tracking of dynamic tonal structure in music, as well as in supporting the associated increases in emotionality, connectedness, and meaningfulness in response to music that are commonly observed after the administration of LSD and other psychedelics. Together, these findings inform the neuropsychopharmacology of music perception and cognition, meaningful music listening experiences, and altered perception of music during psychedelic experiences. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System

PubMed Central

Milde, Moritz B.; Blum, Hermann; Dietmüller, Alexander; Sumislawska, Dora; Conradt, Jörg; Indiveri, Giacomo; Sandamirskaya, Yulia

2017-01-01

Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS) mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition. We developed a neural network architecture that can cope with device variability and verified its robustness in different environmental situations, e.g., moving obstacles, moving target, clutter, and poor light conditions. We demonstrate how this network, combined with the properties of the DVS, allows the robot to avoid obstacles using a simple biologically-inspired dynamics. We also show how a Dynamic Neural Field for target acquisition can be implemented in spiking neuromorphic hardware. This work demonstrates an implementation of working obstacle avoidance and target acquisition using mixed signal analog/digital neuromorphic hardware. PMID:28747883

Obstacle Avoidance and Target Acquisition for Robot Navigation Using a Mixed Signal Analog/Digital Neuromorphic Processing System.

PubMed

Milde, Moritz B; Blum, Hermann; Dietmüller, Alexander; Sumislawska, Dora; Conradt, Jörg; Indiveri, Giacomo; Sandamirskaya, Yulia

2017-01-01

Neuromorphic hardware emulates dynamics of biological neural networks in electronic circuits offering an alternative to the von Neumann computing architecture that is low-power, inherently parallel, and event-driven. This hardware allows to implement neural-network based robotic controllers in an energy-efficient way with low latency, but requires solving the problem of device variability, characteristic for analog electronic circuits. In this work, we interfaced a mixed-signal analog-digital neuromorphic processor ROLLS to a neuromorphic dynamic vision sensor (DVS) mounted on a robotic vehicle and developed an autonomous neuromorphic agent that is able to perform neurally inspired obstacle-avoidance and target acquisition. We developed a neural network architecture that can cope with device variability and verified its robustness in different environmental situations, e.g., moving obstacles, moving target, clutter, and poor light conditions. We demonstrate how this network, combined with the properties of the DVS, allows the robot to avoid obstacles using a simple biologically-inspired dynamics. We also show how a Dynamic Neural Field for target acquisition can be implemented in spiking neuromorphic hardware. This work demonstrates an implementation of working obstacle avoidance and target acquisition using mixed signal analog/digital neuromorphic hardware.

Applying Online Monitoring for Nuclear Power Plant Instrumentation and Control

NASA Astrophysics Data System (ADS)

Hashemian, H. M.

2010-10-01

This paper presents a practical review of the state-of-the-art means for applying OLM data acquisition in nuclear power plant instrumentation and control, qualifying or validating the OLM data, and then analyzing it for static and dynamic performance monitoring applications. Whereas data acquisition for static or steady-state OLM applications can require sample rates of anywhere from 1 to 10 seconds to 1 minutes per sample, for dynamic data acquisition, higher sampling frequencies are required (e.g., 100 to 1000 Hz) using a dedicated data acquisition system capable of providing isolation, anti-aliasing and removal of extraneous noise, and analog-to-digital (A/D) conversion. Qualifying the data for use with OLM algorithms can involve removing data `dead' spots (for static data) and calculating, examining, and trending amplitude probability density, variance, skewness, and kurtosis. For static OLM applications with redundant signals, trending and averaging qualification techniques are used, and for single or non-redundant signals physical and empirical modeling are used. Dynamic OLM analysis is performed in the frequency domain and/or time domain, and is based on the assumption that sensors' or transmitters' dynamic characteristics are linear and that the input noise signal (i.e., the process fluctuations) has proper spectral characteristics.

Toward high fidelity spectral sensing and RF signal processing in silicon photonic and nano-opto-mechanical platforms

NASA Astrophysics Data System (ADS)

Siddiqui, Aleem; Reinke, Charles; Shin, Heedeuk; Jarecki, Robert L.; Starbuck, Andrew L.; Rakich, Peter

2017-05-01

The performance of electronic systems for radio-frequency (RF) spectrum analysis is critical for agile radar and communications systems, ISR (intelligence, surveillance, and reconnaissance) operations in challenging electromagnetic (EM) environments, and EM-environment situational awareness. While considerable progress has been made in size, weight, and power (SWaP) and performance metrics in conventional RF technology platforms, fundamental limits make continued improvements increasingly difficult. Alternatively, we propose employing cascaded transduction processes in a chip-scale nano-optomechanical system (NOMS) to achieve a spectral sensor with exceptional signal-linearity, high dynamic range, narrow spectral resolution and ultra-fast sweep times. By leveraging the optimal capabilities of photons and phonons, the system we pursue in this work has performance metrics scalable well beyond the fundamental limitations inherent to all electronic systems. In our device architecture, information processing is performed on wide-bandwidth RF-modulated optical signals by photon-mediated phononic transduction of the modulation to the acoustical-domain for narrow-band filtering, and then back to the optical-domain by phonon-mediated phase modulation (the reverse process). Here, we rely on photonics to efficiently distribute signals for parallel processing, and on phononics for effective and flexible RF-frequency manipulation. This technology is used to create RF-filters that are insensitive to the optical wavelength, with wide center frequency bandwidth selectivity (1-100GHz), ultra-narrow filter bandwidth (1-100MHz), and high dynamic range (70dB), which we will present. Additionally, using this filter as a building block, we will discuss current results and progress toward demonstrating a multichannel-filter with a bandwidth of < 10MHz per channel, while minimizing cumulative optical/acoustic/optical transduced insertion-loss to ideally < 10dB. These proposed metric represent significant improvements over RF-platforms.

C, N, P export regimes from headwater catchments to downstream reaches

NASA Astrophysics Data System (ADS)

Dupas, R.; Musolff, A.; Jawitz, J. W.; Rao, P. S.; Jaeger, C. G.; Fleckenstein, J. H.; Rode, M.; Borchardt, D.

2017-12-01

Excessive amounts of nutrients and dissolved organic matter in freshwater bodies affect aquatic ecosystems. In this study, the spatial and temporal variability in nitrate (NO3), dissolved organic carbon (DOC) and soluble reactive phosphorus (SRP) was analyzed in the Selke river continuum from headwaters draining 1 - 3 km² catchments to downstream reaches representing spatially integrated signals from 184 - 456 km² catchments (part of TERENO - Terrestrial Environmental Observatories, in Germany). Three headwater catchments were selected as archetypes of the main landscape units (land use x lithology) present in the Selke catchment. Export regimes in headwater catchments were interpreted in terms of NO3, DOC and SRP land-to-stream transfer processes. Headwater signals were subtracted from downstream signals, with the differences interpreted in terms of in-stream processes and contribution of point-source emissions. The seasonal dynamics for NO3 were opposite those of DOC and SRP in all three headwater catchments, and spatial differences also showed NO3 contrasting with DOC and SRP. These dynamics were interpreted as the result of the interplay of hydrological and biogeochemical processes, for which riparian zones were hypothesized to play a determining role. In the two downstream reaches, NO3 was transported almost conservatively, whereas DOC was consumed and produced in the upper and lower river sections, respectively. The natural export regime of SRP in the three headwater catchments mimicked a point-source signal, which may lead to overestimation of domestic contributions in the downstream reaches. Monitoring the river continuum from headwaters to downstream reaches proved effective to investigate jointly land-to-stream and in-stream transport and transformation processes.

Engineering Synthetic Proteins to Generate Ca2+ Signals in Mammalian Cells.

PubMed

Qudrat, Anam; Truong, Kevin

2017-03-17

The versatility of Ca 2+ signals allows it to regulate diverse cellular processes such as migration, apoptosis, motility and exocytosis. In some receptors (e.g., VEGFR2), Ca 2+ signals are generated upon binding their ligand(s) (e.g., VEGF-A). Here, we employed a design strategy to engineer proteins that generate a Ca 2+ signal upon binding various extracellular stimuli by creating fusions of protein domains that oligomerize to the transmembrane domain and the cytoplasmic tail of the VEGFR2. To test the strategy, we created chimeric proteins that generate Ca 2+ signals upon stimulation with various extracellular stimuli (e.g., rapamycin, EDTA or extracellular free Ca 2+ ). By coupling these chimeric proteins that generate Ca 2+ signals with proteins that respond to Ca 2+ signals, we rewired, for example, dynamic cellular blebbing to increases in extracellular free Ca 2+ . Thus, using this design strategy, it is possible to engineer proteins to generate a Ca 2+ signal to rewire a wide range of extracellular stimuli to a wide range of Ca 2+ -activated processes.

ISLE (Image and Signal Processing LISP Environment) reference manual

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sherwood, R.J.; Searfus, R.M.

1990-01-01

ISLE is a rapid prototyping system for performing image and signal processing. It is designed to meet the needs of a person doing development of image and signal processing algorithms in a research environment. The image and signal processing modules in ISLE form a very capable package in themselves. They also provide a rich environment for quickly and easily integrating user-written software modules into the package. ISLE is well suited to applications in which there is a need to develop a processing algorithm in an interactive manner. It is straightforward to develop the algorithms, load it into ISLE, apply themore » algorithm to an image or signal, display the results, then modify the algorithm and repeat the develop-load-apply-display cycle. ISLE consists of a collection of image and signal processing modules integrated into a cohesive package through a standard command interpreter. ISLE developer elected to concentrate their effort on developing image and signal processing software rather than developing a command interpreter. A COMMON LISP interpreter was selected for the command interpreter because it already has the features desired in a command interpreter, it supports dynamic loading of modules for customization purposes, it supports run-time parameter and argument type checking, it is very well documented, and it is a commercially supported product. This manual is intended to be a reference manual for the ISLE functions The functions are grouped into a number of categories and briefly discussed in the Function Summary chapter. The full descriptions of the functions and all their arguments are given in the Function Descriptions chapter. 6 refs.« less

Calcium signaling in taste cells: regulation required.

PubMed

Medler, Kathryn F

2010-11-01

Peripheral taste receptor cells depend on distinct calcium signals to generate appropriate cellular responses that relay taste information to the central nervous system. Some taste cells have conventional chemical synapses and rely on calcium influx through voltage-gated calcium channels. Other taste cells lack these synapses and depend on calcium release from stores to formulate an output signal through a hemichannel. Despite the importance of calcium signaling in taste cells, little is known about how these signals are regulated. This review summarizes recent studies that have identified 2 calcium clearance mechanisms expressed in taste cells, including mitochondrial calcium uptake and sodium/calcium exchangers (NCXs). These studies identified a unique constitutive calcium influx that contributes to maintaining appropriate calcium homeostasis in taste cells and the role of the mitochondria and exchangers in this process. The additional role of NCXs in the regulation of evoked calcium responses is also discussed. Clearly, calcium signaling is a dynamic process in taste cells and appears to be more complex than has previously been appreciated.

Models and signal processing for an implanted ethanol bio-sensor.

PubMed

Han, Jae-Joon; Doerschuk, Peter C; Gelfand, Saul B; O'Connor, Sean J

2008-02-01

The understanding of drinking patterns leading to alcoholism has been hindered by an inability to unobtrusively measure ethanol consumption over periods of weeks to months in the community environment. An implantable ethanol sensor is under development using microelectromechanical systems technology. For safety and user acceptability issues, the sensor will be implanted subcutaneously and, therefore, measure peripheral-tissue ethanol concentration. Determining ethanol consumption and kinetics in other compartments from the time course of peripheral-tissue ethanol concentration requires sophisticated signal processing based on detailed descriptions of the relevant physiology. A statistical signal processing system based on detailed models of the physiology and using extended Kalman filtering and dynamic programming tools is described which can estimate the time series of ethanol concentration in blood, liver, and peripheral tissue and the time series of ethanol consumption based on peripheral-tissue ethanol concentration measurements.

Hebbian learning in a model with dynamic rate-coded neurons: an alternative to the generative model approach for learning receptive fields from natural scenes.

PubMed

Hamker, Fred H; Wiltschut, Jan

2007-09-01

Most computational models of coding are based on a generative model according to which the feedback signal aims to reconstruct the visual scene as close as possible. We here explore an alternative model of feedback. It is derived from studies of attention and thus, probably more flexible with respect to attentive processing in higher brain areas. According to this model, feedback implements a gain increase of the feedforward signal. We use a dynamic model with presynaptic inhibition and Hebbian learning to simultaneously learn feedforward and feedback weights. The weights converge to localized, oriented, and bandpass filters similar as the ones found in V1. Due to presynaptic inhibition the model predicts the organization of receptive fields within the feedforward pathway, whereas feedback primarily serves to tune early visual processing according to the needs of the task.

Fast reversible learning based on neurons functioning as anisotropic multiplex hubs

NASA Astrophysics Data System (ADS)

Vardi, Roni; Goldental, Amir; Sheinin, Anton; Sardi, Shira; Kanter, Ido

2017-05-01

Neural networks are composed of neurons and synapses, which are responsible for learning in a slow adaptive dynamical process. Here we experimentally show that neurons act like independent anisotropic multiplex hubs, which relay and mute incoming signals following their input directions. Theoretically, the observed information routing enriches the computational capabilities of neurons by allowing, for instance, equalization among different information routes in the network, as well as high-frequency transmission of complex time-dependent signals constructed via several parallel routes. In addition, this kind of hubs adaptively eliminate very noisy neurons from the dynamics of the network, preventing masking of information transmission. The timescales for these features are several seconds at most, as opposed to the imprint of information by the synaptic plasticity, a process which exceeds minutes. Results open the horizon to the understanding of fast and adaptive learning realities in higher cognitive brain's functionalities.

A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring.

PubMed

Martinek, Radek; Nedoma, Jan; Fajkus, Marcel; Kahankova, Radana; Konecny, Jaromir; Janku, Petr; Kepak, Stanislav; Bilik, Petr; Nazeran, Homer

2017-04-18

This paper focuses on the design, realization, and verification of a novel phonocardiographic- based fiber-optic sensor and adaptive signal processing system for noninvasive continuous fetal heart rate (fHR) monitoring. Our proposed system utilizes two Mach-Zehnder interferometeric sensors. Based on the analysis of real measurement data, we developed a simplified dynamic model for the generation and distribution of heart sounds throughout the human body. Building on this signal model, we then designed, implemented, and verified our adaptive signal processing system by implementing two stochastic gradient-based algorithms: the Least Mean Square Algorithm (LMS), and the Normalized Least Mean Square (NLMS) Algorithm. With this system we were able to extract the fHR information from high quality fetal phonocardiograms (fPCGs), filtered from abdominal maternal phonocardiograms (mPCGs) by performing fPCG signal peak detection. Common signal processing methods such as linear filtering, signal subtraction, and others could not be used for this purpose as fPCG and mPCG signals share overlapping frequency spectra. The performance of the adaptive system was evaluated by using both qualitative (gynecological studies) and quantitative measures such as: Signal-to-Noise Ratio-SNR, Root Mean Square Error-RMSE, Sensitivity-S+, and Positive Predictive Value-PPV.

A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring

PubMed Central

Martinek, Radek; Nedoma, Jan; Fajkus, Marcel; Kahankova, Radana; Konecny, Jaromir; Janku, Petr; Kepak, Stanislav; Bilik, Petr; Nazeran, Homer

2017-01-01

This paper focuses on the design, realization, and verification of a novel phonocardiographic- based fiber-optic sensor and adaptive signal processing system for noninvasive continuous fetal heart rate (fHR) monitoring. Our proposed system utilizes two Mach-Zehnder interferometeric sensors. Based on the analysis of real measurement data, we developed a simplified dynamic model for the generation and distribution of heart sounds throughout the human body. Building on this signal model, we then designed, implemented, and verified our adaptive signal processing system by implementing two stochastic gradient-based algorithms: the Least Mean Square Algorithm (LMS), and the Normalized Least Mean Square (NLMS) Algorithm. With this system we were able to extract the fHR information from high quality fetal phonocardiograms (fPCGs), filtered from abdominal maternal phonocardiograms (mPCGs) by performing fPCG signal peak detection. Common signal processing methods such as linear filtering, signal subtraction, and others could not be used for this purpose as fPCG and mPCG signals share overlapping frequency spectra. The performance of the adaptive system was evaluated by using both qualitative (gynecological studies) and quantitative measures such as: Signal-to-Noise Ratio—SNR, Root Mean Square Error—RMSE, Sensitivity—S+, and Positive Predictive Value—PPV. PMID:28420215

Four dimensional material movies: High speed phase-contrast tomography by backprojection along dynamically curved paths.

PubMed

Ruhlandt, A; Töpperwien, M; Krenkel, M; Mokso, R; Salditt, T

2017-07-26

We present an approach towards four dimensional (4d) movies of materials, showing dynamic processes within the entire 3d structure. The method is based on tomographic reconstruction on dynamically curved paths using a motion model estimated by optical flow techniques, considerably reducing the typical motion artefacts of dynamic tomography. At the same time we exploit x-ray phase contrast based on free propagation to enhance the signal from micron scale structure recorded with illumination times down to a millisecond (ms). The concept is demonstrated by observing the burning process of a match stick in 4d, using high speed synchrotron phase contrast x-ray tomography recordings. The resulting movies reveal the structural changes of the wood cells during the combustion.

Autogenic Deposits as A Potential Recorder of High-Frequency Signals: The Role of Autogenic Processes Revisited

NASA Astrophysics Data System (ADS)

Li, H.; Plink-Bjorklund, P.

2017-12-01

Studies (e.g., Jerolmack and Paola, 2010) have suggested that autogenic processes act as a filter for high-frequency environmental signals, and the underlying assumption is that autogenic processes can cause fluctuations in sediment and water discharge that modify or shred the signal. This assumption, however, fails to recognize that autogenic processes and their final products are dynamic and that they can respond to allogenic forcings. We compile a database containing published field studies, physical experiments, and numerical modeling works, and analyze the data under different boundary conditions. Our analyses suggest different conclusions. Autogenic processes are intrinsic to the sedimentary system, and they possess distinct patterns under steady boundary conditions. Upon changing boundary conditions, the autogenic patterns are also likely to change (depending on the magnitude of the change in the boundary conditions). Therefore, the pattern change provides us with the opportunity to restore the high-frequency signals that may not pass through the transfer zone. Here we present the theoretical basis for using autogenic deposits to infer high-frequency signals as well as modern and ancient field examples, physical experiments, and modeling works to illustrate the autogenic response to allogenic forcings. The field studies show the potential of using autogenic deposits to restore short-term climatic variability. The experiments demonstrate that autogenic processes in rivers are closely linked to sediment and water discharge. The modeling examples reveal the counteracting effects of some autogenic processes to form a self-organized pattern under a set of specific boundary conditions. We also highlight the limitations and challenges that need more research efforts to restore high-frequency signals. Some critical issues include the magnitude of the signals, the effect of the interference between different signals, and the incompleteness of the autogenic deposits.

Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)

NASA Astrophysics Data System (ADS)

Raskovic, Dejan

Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.

Intentional strategies that make co-actors more predictable: the case of signaling.

PubMed

Pezzulo, Giovanni; Dindo, Haris

2013-08-01

Pickering & Garrod (P&G) explain dialogue dynamics in terms of forward modeling and prediction-by-simulation mechanisms. Their theory dissolves a strict segregation between production and comprehension processes, and it links dialogue to action-based theories of joint action. We propose that the theory can also incorporate intentional strategies that increase communicative success: for example, signaling strategies that help remaining predictable and forming common ground.

NF-κB dynamics show digital activation and analog information processing in cells

NASA Astrophysics Data System (ADS)

Tay, Savas; Hughey, Jake; Lee, Timothy; Lipniacki, Tomasz; Covert, Markus; Quake, Stephen

2010-03-01

Cells operate in ever changing environments using extraordinary communication capabilities. Cell-to-cell communication is mediated by signaling molecules that form spatiotemporal concentration gradients, which requires cells to respond to a wide range of signal intensities. We used high-throughput microfluidic cell culture, quantitative gene expression analysis and mathematical modeling to investigate how single mammalian cells respond to different concentrations of the signaling molecule TNF-α via the transcription factor NF-κB. We measured NF-κB activity in thousands of live cells under TNF-α doses covering four orders of magnitude. In contrast to population studies, the activation is a stochastic, switch-like process at the single cell level with fewer cells responding at lower doses. The activated cells respond fully and express early genes independent of the TNF-α concentration, while only high dose stimulation results in the expression of late genes. Cells also encode a set of analog parameters such as the NF-κB peak intensity, response time and number of oscillations to modulate the outcome. We developed a stochastic model that reproduces both the digital and analog dynamics as well as the gene expression profiles at all measured conditions, constituting a broadly applicable model for TNF-α induced NF-κB signaling in various types of cells.

Read My Lips: Brain Dynamics Associated with Audiovisual Integration and Deviance Detection.

PubMed

Tse, Chun-Yu; Gratton, Gabriele; Garnsey, Susan M; Novak, Michael A; Fabiani, Monica

2015-09-01

Information from different modalities is initially processed in different brain areas, yet real-world perception often requires the integration of multisensory signals into a single percept. An example is the McGurk effect, in which people viewing a speaker whose lip movements do not match the utterance perceive the spoken sounds incorrectly, hearing them as more similar to those signaled by the visual rather than the auditory input. This indicates that audiovisual integration is important for generating the phoneme percept. Here we asked when and where the audiovisual integration process occurs, providing spatial and temporal boundaries for the processes generating phoneme perception. Specifically, we wanted to separate audiovisual integration from other processes, such as simple deviance detection. Building on previous work employing ERPs, we used an oddball paradigm in which task-irrelevant audiovisually deviant stimuli were embedded in strings of non-deviant stimuli. We also recorded the event-related optical signal, an imaging method combining spatial and temporal resolution, to investigate the time course and neuroanatomical substrate of audiovisual integration. We found that audiovisual deviants elicit a short duration response in the middle/superior temporal gyrus, whereas audiovisual integration elicits a more extended response involving also inferior frontal and occipital regions. Interactions between audiovisual integration and deviance detection processes were observed in the posterior/superior temporal gyrus. These data suggest that dynamic interactions between inferior frontal cortex and sensory regions play a significant role in multimodal integration.

Functional link between plasma membrane spatiotemporal dynamics, cancer biology, and dietary membrane-altering agents.

PubMed

Erazo-Oliveras, Alfredo; Fuentes, Natividad R; Wright, Rachel C; Chapkin, Robert S

2018-06-02

The cell plasma membrane serves as a nexus integrating extra- and intracellular components, which together enable many of the fundamental cellular signaling processes that sustain life. In order to perform this key function, plasma membrane components assemble into well-defined domains exhibiting distinct biochemical and biophysical properties that modulate various signaling events. Dysregulation of these highly dynamic membrane domains can promote oncogenic signaling. Recently, it has been demonstrated that select membrane-targeted dietary bioactives (MTDBs) have the ability to remodel plasma membrane domains and subsequently reduce cancer risk. In this review, we focus on the importance of plasma membrane domain structural and signaling functionalities as well as how loss of membrane homeostasis can drive aberrant signaling. Additionally, we discuss the intricacies associated with the investigation of these membrane domain features and their associations with cancer biology. Lastly, we describe the current literature focusing on MTDBs, including mechanisms of chemoprevention and therapeutics in order to establish a functional link between these membrane-altering biomolecules, tuning of plasma membrane hierarchal organization, and their implications in cancer prevention.

Development of nanoscale structure in LAT-based signaling complexes

PubMed Central

2016-01-01

ABSTRACT The adapter molecule linker for activation of T cells (LAT) plays a crucial role in forming signaling complexes induced by stimulation of the T cell receptor (TCR). These multi-molecular complexes are dynamic structures that activate highly regulated signaling pathways. Previously, we have demonstrated nanoscale structure in LAT-based complexes where the adapter SLP-76 (also known as LCP2) localizes to the periphery of LAT clusters. In this study, we show that initially LAT and SLP-76 are randomly dispersed throughout the clusters that form upon TCR engagement. The segregation of LAT and SLP-76 develops near the end of the spreading process. The local concentration of LAT also increases at the same time. Both changes require TCR activation and an intact actin cytoskeleton. These results demonstrate that the nanoscale organization of LAT-based signaling complexes is dynamic and indicates that different kinds of LAT-based complexes appear at different times during T cell activation. PMID:27875277

Dynamic Receptor Team Formation Can Explain the High Signal Transduction Gain in Escherichia coli

NASA Astrophysics Data System (ADS)

Albert, R.; Chiu, Y.; Othmer, H.

2004-05-01

Evolution has provided many organisms with sophisticated sensory systems that enable them to respond to signals in their environment. The response frequently involves alteration in the pattern of movement, such as the chemokinesis of the bacterium Escherichia coli, which swims by rotating its flagella. When rotated counterclockwise (CCW) the flagella coalesce into a propulsive bundle, producing a relatively straight ``run'', and when rotated clockwise (CW) they fly apart, resulting in a ``tumble'' which reorients the cell with little translocation. A stochastic process generates the runs and tumbles, and in a chemoeffector gradient runs that carry the cell in a favorable direction are extended. The overall structure of the signal transduction pathways is well-characterized in E. coli, but important details are still not understood. Only recently has a source of gain in the signal transduction network been identified experimentally, and here we present a mathematical model based on dynamic assembly of receptor teams that can explain this observation.

Smad Signaling Dynamics: Insights from a Parsimonious Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wiley, H. S.; Shankaran, Harish

2008-09-09

The molecular mechanisms that transmit information from cell surface receptors to the nucleus are exceedingly complex; thus, much effort has been expended in developing computational models to understand these processes. A recent study on modeling the nuclear-cytoplasmic shuttling of Smad2-Smad4 complexes in response to transforming growth factor β (TGF-β) receptor activation has provided substantial insight into how this signaling network translates the degree of TGF-β receptor activation (input) into the amount of nuclear Smad2-Smad4 complexes (output). The study addressed this question by combining a simple, mechanistic model with targeted experiments, an approach that proved particularly powerful for exploring the fundamentalmore » properties of a complex signaling network. The mathematical model revealed that Smad nuclear-cytoplasmic dynamics enables a proportional, but time-delayed coupling between the input and the output. As a result, the output can faithfully track gradual changes in the input, while the rapid input fluctuations that constitute signaling noise are dampened out.« less

Dynamic balancing of dual-rotor system with very little rotating speed difference.

PubMed

Yang, Jian; He, Shi-zheng; Wang, Le-qin

2003-01-01

Unbalanced vibration in dual-rotor rotating machinery was studied with numerical simulations and experiments. A new method is proposed to separate vibration signals of inner and outer rotors for a system with very little difference in rotating speeds. Magnitudes and phase values of unbalance defects can be obtained directly by sampling the vibration signal synchronized with reference signal. The balancing process is completed by the reciprocity influence coefficients of inner and outer rotors method. Results showed the advantage of such method for a dual-rotor system as compared with conventional balancing.

Aerospace Applications Conference, Steamboat Springs, CO, Feb. 1-8, 1986, Digest

NASA Astrophysics Data System (ADS)

The present conference considers topics concerning the projected NASA Space Station's systems, digital signal and data processing applications, and space science and microwave applications. Attention is given to Space Station video and audio subsystems design, clock error, jitter, phase error and differential time-of-arrival in satellite communications, automation and robotics in space applications, target insertion into synthetic background scenes, and a novel scheme for the computation of the discrete Fourier transform on a systolic processor. Also discussed are a novel signal parameter measurement system employing digital signal processing, EEPROMS for spacecraft applications, a unique concurrent processor architecture for high speed simulation of dynamic systems, a dual polarization flat plate antenna, Fresnel diffraction, and ultralinear TWTs for high efficiency satellite communications.

Method and apparatus for analog signal conditioner for high speed, digital x-ray spectrometer

DOEpatents

Warburton, W.K.; Hubbard, B.

1999-02-09

A signal processing system which accepts input from an x-ray detector-preamplifier and produces a signal of reduced dynamic range for subsequent analog-to-digital conversion is disclosed. The system conditions the input signal to reduce the number of bits required in the analog-to-digital converter by removing that part of the input signal which varies only slowly in time and retaining the amplitude of the pulses which carry information about the x-rays absorbed by the detector. The parameters controlling the signal conditioner`s operation can be readily supplied in digital form, allowing it to be integrated into a feedback loop as part of a larger digital x-ray spectroscopy system. 13 figs.

Brain signal complexity rises with repetition suppression in visual learning.

PubMed

Lafontaine, Marc Philippe; Lacourse, Karine; Lina, Jean-Marc; McIntosh, Anthony R; Gosselin, Frédéric; Théoret, Hugo; Lippé, Sarah

2016-06-21

Neuronal activity associated with visual processing of an unfamiliar face gradually diminishes when it is viewed repeatedly. This process, known as repetition suppression (RS), is involved in the acquisition of familiarity. Current models suggest that RS results from interactions between visual information processing areas located in the occipito-temporal cortex and higher order areas, such as the dorsolateral prefrontal cortex (DLPFC). Brain signal complexity, which reflects information dynamics of cortical networks, has been shown to increase as unfamiliar faces become familiar. However, the complementarity of RS and increases in brain signal complexity have yet to be demonstrated within the same measurements. We hypothesized that RS and brain signal complexity increase occur simultaneously during learning of unfamiliar faces. Further, we expected alteration of DLPFC function by transcranial direct current stimulation (tDCS) to modulate RS and brain signal complexity over the occipito-temporal cortex. Participants underwent three tDCS conditions in random order: right anodal/left cathodal, right cathodal/left anodal and sham. Following tDCS, participants learned unfamiliar faces, while an electroencephalogram (EEG) was recorded. Results revealed RS over occipito-temporal electrode sites during learning, reflected by a decrease in signal energy, a measure of amplitude. Simultaneously, as signal energy decreased, brain signal complexity, as estimated with multiscale entropy (MSE), increased. In addition, prefrontal tDCS modulated brain signal complexity over the right occipito-temporal cortex during the first presentation of faces. These results suggest that although RS may reflect a brain mechanism essential to learning, complementary processes reflected by increases in brain signal complexity, may be instrumental in the acquisition of novel visual information. Such processes likely involve long-range coordinated activity between prefrontal and lower order visual areas. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Analysis of the seismic signals generated by controlled single-block rockfalls on soft clay shales sediments: the Rioux Bourdoux slope experiment (French Alps).

NASA Astrophysics Data System (ADS)

Hibert, Clément; Provost, Floriane; Malet, Jean-Philippe; Bourrier, Franck; Berger, Frédéric; Bornemann, Pierrick; Borgniet, Laurent; Tardif, Pascal; Mermin, Eric

2016-04-01

Understanding the dynamics of rockfalls is critical to mitigate the associated hazards but is made very difficult by the nature of these natural disasters that makes them hard to observe directly. Recent advances in seismology allow to determine the dynamics of the largest landslides on Earth from the very low-frequency seismic waves they generate. However, the vast majority of rockfalls that occur worldwide are too small to generate such low-frequency seismic waves and thus these methods cannot be used to reconstruct their dynamics. However, if seismic sensors are close enough, these events will generate high-frequency seismic signals. Unfortunately we cannot yet use these high-frequency seismic records to infer parameters synthetizing the rockfall dynamics as the source of these waves is not well understood. One of the first steps towards understanding the physical processes involved in the generation of high-frequency seismic waves by rockfalls is to study the link between the dynamics of a single block propagating along a well-known path and the features of the seismic signal generated. We conducted controlled releases of single blocks of limestones in a gully of clay-shales (e.g. black marls) in the Rioux Bourdoux torrent (French Alps). 28 blocks, with masses ranging from 76 kg to 472 kg, were released. A monitoring network combining high-velocity cameras, a broadband seismometer and an array of 4 high-frequency seismometers was deployed near the release area and along the travel path. The high-velocity cameras allow to reconstruct the 3D trajectories of the blocks, to estimate their velocities and the position of the different impacts with the slope surface. These data are compared to the seismic signals recorded. As the distance between the block and the seismic sensors at the time of each impact is known, we can determine the associated seismic signal amplitude corrected from propagation and attenuation effects. We can further compare the velocity, the energy and the momentum of the block at each impact to the true amplitude and the energy of the corresponding part of the seismic signal. Finding potential correlations and scaling laws between the dynamics of the source and the high-frequency seismic signal features constitutes an important breakthrough to understand more complex slope movements that involve multiple blocks or granular flows. This approach may lead to future developments of methods able to determine the dynamics of a large variety of slope movements directly from the seismic signals they generate.

Parallel Processing of Broad-Band PPM Signals

NASA Technical Reports Server (NTRS)

Gray, Andrew; Kang, Edward; Lay, Norman; Vilnrotter, Victor; Srinivasan, Meera; Lee, Clement

2010-01-01

A parallel-processing algorithm and a hardware architecture to implement the algorithm have been devised for timeslot synchronization in the reception of pulse-position-modulated (PPM) optical or radio signals. As in the cases of some prior algorithms and architectures for parallel, discrete-time, digital processing of signals other than PPM, an incoming broadband signal is divided into multiple parallel narrower-band signals by means of sub-sampling and filtering. The number of parallel streams is chosen so that the frequency content of the narrower-band signals is low enough to enable processing by relatively-low speed complementary metal oxide semiconductor (CMOS) electronic circuitry. The algorithm and architecture are intended to satisfy requirements for time-varying time-slot synchronization and post-detection filtering, with correction of timing errors independent of estimation of timing errors. They are also intended to afford flexibility for dynamic reconfiguration and upgrading. The architecture is implemented in a reconfigurable CMOS processor in the form of a field-programmable gate array. The algorithm and its hardware implementation incorporate three separate time-varying filter banks for three distinct functions: correction of sub-sample timing errors, post-detection filtering, and post-detection estimation of timing errors. The design of the filter bank for correction of timing errors, the method of estimating timing errors, and the design of a feedback-loop filter are governed by a host of parameters, the most critical one, with regard to processing very broadband signals with CMOS hardware, being the number of parallel streams (equivalently, the rate-reduction parameter).

High-rate RTK and PPP multi-GNSS positioning for small-scale dynamic displacements monitoring

NASA Astrophysics Data System (ADS)

Paziewski, Jacek; Sieradzki, Rafał; Baryła, Radosław; Wielgosz, Pawel

2017-04-01

The monitoring of dynamic displacements and deformations of engineering structures such as buildings, towers and bridges is of great interest due to several practical and theoretical reasons. The most important is to provide information required for safe maintenance of the constructions. High temporal resolution and precision of GNSS observations predestine this technology to be applied to most demanding application in terms of accuracy, availability and reliability. GNSS technique supported by appropriate processing methodology may meet the specific demands and requirements of ground and structures monitoring. Thus, high-rate multi-GNSS signals may be used as reliable source of information on dynamic displacements of ground and engineering structures, also in real time applications. In this study we present initial results of application of precise relative GNSS positioning for detection of small scale (cm level) high temporal resolution dynamic displacements. Methodology and algorithms applied in self-developed software allowing for relative positioning using high-rate dual-frequency phase and pseudorange GPS+Galileo observations are also given. Additionally, an approach was also made to use the Precise Point Positioning technique to such application. In the experiment were used the observations obtained from high-rate (20 Hz) geodetic receivers. The dynamic displacements were simulated using specially constructed device moving GNSS antenna with dedicated amplitude and frequency. The obtained results indicate on possibility of detection of dynamic displacements of the GNSS antenna even at the level of few millimetres using both relative and Precise Point Positioning techniques after suitable signals processing.

The Relationship Between Intensity Coding and Binaural Sensitivity in Adults With Cochlear Implants.

PubMed

Todd, Ann E; Goupell, Matthew J; Litovsky, Ruth Y

Many bilateral cochlear implant users show sensitivity to binaural information when stimulation is provided using a pair of synchronized electrodes. However, there is large variability in binaural sensitivity between and within participants across stimulation sites in the cochlea. It was hypothesized that within-participant variability in binaural sensitivity is in part affected by limitations and characteristics of the auditory periphery which may be reflected by monaural hearing performance. The objective of this study was to examine the relationship between monaural and binaural hearing performance within participants with bilateral cochlear implants. Binaural measures included dichotic signal detection and interaural time difference discrimination thresholds. Diotic signal detection thresholds were also measured. Monaural measures included dynamic range and amplitude modulation detection. In addition, loudness growth was compared between ears. Measures were made at three stimulation sites per listener. Greater binaural sensitivity was found with larger dynamic ranges. Poorer interaural time difference discrimination was found with larger difference between comfortable levels of the two ears. In addition, poorer diotic signal detection thresholds were found with larger differences between the dynamic ranges of the two ears. No relationship was found between amplitude modulation detection thresholds or symmetry of loudness growth and the binaural measures. The results suggest that some of the variability in binaural hearing performance within listeners across stimulation sites can be explained by factors nonspecific to binaural processing. The results are consistent with the idea that dynamic range and comfortable levels relate to peripheral neural survival and the width of the excitation pattern which could affect the fidelity with which central binaural nuclei process bilateral inputs.

In-process deformation measurements of translucent high speed fibre-reinforced disc rotors

NASA Astrophysics Data System (ADS)

Philipp, Katrin; Filippatos, Angelos; Koukourakis, Nektarios; Kuschmierz, Robert; Leithold, Christoph; Langkamp, Albert; Fischer, Andreas; Czarske, Jürgen

2015-07-01

The high stiffness to weight ratio of glass fibre-reinforced polymers (GFRP) makes them an attractive material for rotors e.g. in the aerospace industry. We report on recent developments towards non-contact, in-situ deformation measurements with temporal resolution up to 200 µs and micron measurement uncertainty. We determine the starting point of damage evolution inside the rotor material through radial expansion measurements. This leads to a better understanding of dynamic material behaviour regarding damage evolution and the prediction of damage initiation and propagation. The measurements are conducted using a novel multi-sensor system consisting of four laser Doppler distance (LDD) sensors. The LDD sensor, a two-wavelength Mach-Zehnder interferometer was already successfully applied for dynamic deformation measurements at metallic rotors. While translucency of the GFRP rotor material limits the applicability of most optical measurement techniques due to speckles from both surface and volume of the rotor, the LDD profits from speckles and is not disturbed by backscattered laser light from the rotor volume. The LDD sensor evaluates only signals from the rotor surface. The anisotropic glass fibre-reinforcement results in a rotationally asymmetric dynamic deformation. A novel signal processing algorithm is applied for the combination of the single sensor signals to obtain the shape of the investigated rotors. In conclusion, the applied multi-sensor system allows high temporal resolution dynamic deformation measurements. First investigations regarding damage evolution inside GFRP are presented as an important step towards a fundamental understanding of the material behaviour and the prediction of damage initiation and propagation.

Quantitative proteomics reveals a dynamic association of proteins to detergent-resistant membranes upon elicitor signaling in tobacco.

PubMed

Stanislas, Thomas; Bouyssie, David; Rossignol, Michel; Vesa, Simona; Fromentin, Jérôme; Morel, Johanne; Pichereaux, Carole; Monsarrat, Bernard; Simon-Plas, Françoise

2009-09-01

A large body of evidence from the past decade supports the existence, in membrane from animal and yeast cells, of functional microdomains playing important roles in protein sorting, signal transduction, or infection by pathogens. In plants, as previously observed for animal microdomains, detergent-resistant fractions, enriched in sphingolipids and sterols, were isolated from plasma membrane. A characterization of their proteic content revealed their enrichment in proteins involved in signaling and response to biotic and abiotic stress and cell trafficking suggesting that these domains were likely to be involved in such physiological processes. In the present study, we used (14)N/(15)N metabolic labeling to compare, using a global quantitative proteomics approach, the content of tobacco detergent-resistant membranes extracted from cells treated or not with cryptogein, an elicitor of defense reaction. To analyze the data, we developed a software allowing an automatic quantification of the proteins identified. The results obtained indicate that, although the association to detergent-resistant membranes of most proteins remained unchanged upon cryptogein treatment, five proteins had their relative abundance modified. Four proteins related to cell trafficking (four dynamins) were less abundant in the detergent-resistant membrane fraction after cryptogein treatment, whereas one signaling protein (a 14-3-3 protein) was enriched. This analysis indicates that plant microdomains could, like their animal counterpart, play a role in the early signaling process underlying the setup of defense reaction. Furthermore proteins identified as differentially associated to tobacco detergent-resistant membranes after cryptogein challenge are involved in signaling and vesicular trafficking as already observed in similar studies performed in animal cells upon biological stimuli. This suggests that the ways by which the dynamic association of proteins to microdomains could participate in the regulation of the signaling process may be conserved between plant and animals.

Quantitative Proteomics Reveals a Dynamic Association of Proteins to Detergent-resistant Membranes upon Elicitor Signaling in Tobacco*

PubMed Central

Stanislas, Thomas; Bouyssie, David; Rossignol, Michel; Vesa, Simona; Fromentin, Jérôme; Morel, Johanne; Pichereaux, Carole; Monsarrat, Bernard; Simon-Plas, Françoise

2009-01-01

A large body of evidence from the past decade supports the existence, in membrane from animal and yeast cells, of functional microdomains playing important roles in protein sorting, signal transduction, or infection by pathogens. In plants, as previously observed for animal microdomains, detergent-resistant fractions, enriched in sphingolipids and sterols, were isolated from plasma membrane. A characterization of their proteic content revealed their enrichment in proteins involved in signaling and response to biotic and abiotic stress and cell trafficking suggesting that these domains were likely to be involved in such physiological processes. In the present study, we used 14N/15N metabolic labeling to compare, using a global quantitative proteomics approach, the content of tobacco detergent-resistant membranes extracted from cells treated or not with cryptogein, an elicitor of defense reaction. To analyze the data, we developed a software allowing an automatic quantification of the proteins identified. The results obtained indicate that, although the association to detergent-resistant membranes of most proteins remained unchanged upon cryptogein treatment, five proteins had their relative abundance modified. Four proteins related to cell trafficking (four dynamins) were less abundant in the detergent-resistant membrane fraction after cryptogein treatment, whereas one signaling protein (a 14-3-3 protein) was enriched. This analysis indicates that plant microdomains could, like their animal counterpart, play a role in the early signaling process underlying the setup of defense reaction. Furthermore proteins identified as differentially associated to tobacco detergent-resistant membranes after cryptogein challenge are involved in signaling and vesicular trafficking as already observed in similar studies performed in animal cells upon biological stimuli. This suggests that the ways by which the dynamic association of proteins to microdomains could participate in the regulation of the signaling process may be conserved between plant and animals. PMID:19525550

Dissociable brain mechanisms underlying the conscious and unconscious control of behavior.

PubMed

van Gaal, Simon; Lamme, Victor A F; Fahrenfort, Johannes J; Ridderinkhof, K Richard

2011-01-01

Cognitive control allows humans to overrule and inhibit habitual responses to optimize performance in challenging situations. Contradicting traditional views, recent studies suggest that cognitive control processes can be initiated unconsciously. To further capture the relation between consciousness and cognitive control, we studied the dynamics of inhibitory control processes when triggered consciously versus unconsciously in a modified version of the stop task. Attempts to inhibit an imminent response were often successful after unmasked (visible) stop signals. Masked (invisible) stop signals rarely succeeded in instigating overt inhibition but did trigger slowing down of response times. Masked stop signals elicited a sequence of distinct ERP components that were also observed on unmasked stop signals. The N2 component correlated with the efficiency of inhibitory control when elicited by unmasked stop signals and with the magnitude of slowdown when elicited by masked stop signals. Thus, the N2 likely reflects the initiation of inhibitory control, irrespective of conscious awareness. The P3 component was much reduced in amplitude and duration on masked versus unmasked stop trials. These patterns of differences and similarities between conscious and unconscious cognitive control processes are discussed in a framework that differentiates between feedforward and feedback connections in yielding conscious experience.

Visualizing Time: How Linguistic Metaphors Are Incorporated into Displaying Instruments in the Process of Interpreting Time-Varying Signals

ERIC Educational Resources Information Center

Garcia-Belmonte, Germà

2017-01-01

Spatial visualization is a well-established topic of education research that has allowed improving science and engineering students' skills on spatial relations. Connections have been established between visualization as a comprehension tool and instruction in several scientific fields. Learning about dynamic processes mainly relies upon static…

A Computational Model Predicting Disruption of Blood Vessel Development

EPA Science Inventory

Vascular development is a complex process regulated by dynamic biological networks that vary in topology and state across different tissues and developmental stages. Signals regulating de novo blood vessel formation (vasculogenesis) and remodeling (angiogenesis) come from a varie...

Signal processing system for electrotherapy applications

NASA Astrophysics Data System (ADS)

Płaza, Mirosław; Szcześniak, Zbigniew

2017-08-01

The system of signal processing for electrotherapeutic applications is proposed in the paper. The system makes it possible to model the curve of threshold human sensitivity to current (Dalziel's curve) in full medium frequency range (1kHz-100kHz). The tests based on the proposed solution were conducted and their results were compared with those obtained according to the assumptions of High Tone Power Therapy method and referred to optimum values. Proposed system has high dynamics and precision of mapping the curve of threshold human sensitivity to current and can be used in all methods where threshold curves are modelled.

Bacterial Serine/Threonine Protein Kinases in Host-Pathogen Interactions*

PubMed Central

Canova, Marc J.; Molle, Virginie

2014-01-01

In bacterial pathogenesis, monitoring and adapting to the dynamically changing environment in the host and an ability to disrupt host immune responses are critical. The virulence determinants of pathogenic bacteria include the sensor/signaling proteins of the serine/threonine protein kinase (STPK) family that have a dual role of sensing the environment and subverting specific host defense processes. STPKs can sense a wide range of signals and coordinate multiple cellular processes to mount an appropriate response. Here, we review some of the well studied bacterial STPKs that are essential virulence factors and that modify global host responses during infection. PMID:24554701

Bacterial serine/threonine protein kinases in host-pathogen interactions.

PubMed

Canova, Marc J; Molle, Virginie

2014-04-04

In bacterial pathogenesis, monitoring and adapting to the dynamically changing environment in the host and an ability to disrupt host immune responses are critical. The virulence determinants of pathogenic bacteria include the sensor/signaling proteins of the serine/threonine protein kinase (STPK) family that have a dual role of sensing the environment and subverting specific host defense processes. STPKs can sense a wide range of signals and coordinate multiple cellular processes to mount an appropriate response. Here, we review some of the well studied bacterial STPKs that are essential virulence factors and that modify global host responses during infection.

Electroencephalographic compression based on modulated filter banks and wavelet transform.

PubMed

Bazán-Prieto, Carlos; Cárdenas-Barrera, Julián; Blanco-Velasco, Manuel; Cruz-Roldán, Fernando

2011-01-01

Due to the large volume of information generated in an electroencephalographic (EEG) study, compression is needed for storage, processing or transmission for analysis. In this paper we evaluate and compare two lossy compression techniques applied to EEG signals. It compares the performance of compression schemes with decomposition by filter banks or wavelet Packets transformation, seeking the best value for compression, best quality and more efficient real time implementation. Due to specific properties of EEG signals, we propose a quantization stage adapted to the dynamic range of each band, looking for higher quality. The results show that the compressor with filter bank performs better than transform methods. Quantization adapted to the dynamic range significantly enhances the quality.

Detection of weak signals through nonlinear relaxation times for a Brownian particle in an electromagnetic field.

PubMed

Jiménez-Aquino, J I; Romero-Bastida, M

2011-07-01

The detection of weak signals through nonlinear relaxation times for a Brownian particle in an electromagnetic field is studied in the dynamical relaxation of the unstable state, characterized by a two-dimensional bistable potential. The detection process depends on a dimensionless quantity referred to as the receiver output, calculated as a function of the nonlinear relaxation time and being a characteristic time scale of our system. The latter characterizes the complete dynamical relaxation of the Brownian particle as it relaxes from the initial unstable state of the bistable potential to its corresponding steady state. The one-dimensional problem is also studied to complement the description.

A parallel unbalanced digitization architecture to reduce the dynamic range of multiple signals

NASA Astrophysics Data System (ADS)

Vallérian, Mathieu; HuÅ£u, Florin; Villemaud, Guillaume; Miscopein, Benoît; Risset, Tanguy

2016-05-01

Technologies employed in urban sensor networks are permanently evolving, and thus the gateways employed to collect data in such kind of networks have to be very flexible in order to be compliant with the new communication standards. A convenient way to do that is to digitize all the received signals in one shot and then to digitally perform the signal processing, as it is done in software-defined radio (SDR). All signals can be emitted with very different features (bandwidth, modulation type, and power level) in order to respond to the various propagation conditions. Their difference in terms of power levels is a problem when digitizing them together, as no current commercial analog-to-digital converter (ADC) can provide a fine enough resolution to digitize this high dynamic range between the weakest possible signal in the presence of a stronger signal. This paper presents an RF front end receiver architecture capable of handling this problem by using two ADCs of lower resolutions. The architecture is validated through a set of simulations using Keysight's ADS software. The main validation criterion is the bit error rate comparison with a classical receiver.

Studying Cellular Signal Transduction with OMIC Technologies.

PubMed

Landry, Benjamin D; Clarke, David C; Lee, Michael J

2015-10-23

In the gulf between genotype and phenotype exists proteins and, in particular, protein signal transduction systems. These systems use a relatively limited parts list to respond to a much longer list of extracellular, environmental, and/or mechanical cues with rapidity and specificity. Most signaling networks function in a highly non-linear and often contextual manner. Furthermore, these processes occur dynamically across space and time. Because of these complexities, systems and "OMIC" approaches are essential for the study of signal transduction. One challenge in using OMIC-scale approaches to study signaling is that the "signal" can take different forms in different situations. Signals are encoded in diverse ways such as protein-protein interactions, enzyme activities, localizations, or post-translational modifications to proteins. Furthermore, in some cases, signals may be encoded only in the dynamics, duration, or rates of change of these features. Accordingly, systems-level analyses of signaling may need to integrate multiple experimental and/or computational approaches. As the field has progressed, the non-triviality of integrating experimental and computational analyses has become apparent. Successful use of OMIC methods to study signaling will require the "right" experiments and the "right" modeling approaches, and it is critical to consider both in the design phase of the project. In this review, we discuss common OMIC and modeling approaches for studying signaling, emphasizing the philosophical and practical considerations for effectively merging these two types of approaches to maximize the probability of obtaining reliable and novel insights into signaling biology. Copyright © 2015 Elsevier Ltd. All rights reserved.

New levels of language processing complexity and organization revealed by granger causation.

PubMed

Gow, David W; Caplan, David N

2012-01-01

Granger causation analysis of high spatiotemporal resolution reconstructions of brain activation offers a new window on the dynamic interactions between brain areas that support language processing. Premised on the observation that causes both precede and uniquely predict their effects, this approach provides an intuitive, model-free means of identifying directed causal interactions in the brain. It requires the analysis of all non-redundant potentially interacting signals, and has shown that even "early" processes such as speech perception involve interactions of many areas in a strikingly large network that extends well beyond traditional left hemisphere perisylvian cortex that play out over hundreds of milliseconds. In this paper we describe this technique and review several general findings that reframe the way we think about language processing and brain function in general. These include the extent and complexity of language processing networks, the central role of interactive processing dynamics, the role of processing hubs where the input from many distinct brain regions are integrated, and the degree to which task requirements and stimulus properties influence processing dynamics and inform our understanding of "language-specific" localized processes.

Dynamic association with donor cell filopodia and lipid-modification are essential features of Wnt8a during patterning of the zebrafish neuroectoderm.

PubMed

Luz, Marta; Spannl-Müller, Stephanie; Özhan, Günes; Kagermeier-Schenk, Birgit; Rhinn, Muriel; Weidinger, Gilbert; Brand, Michael

2014-01-01

Wnt proteins are conserved signaling molecules that regulate pattern formation during animal development. Many Wnt proteins are post-translationally modified by addition of lipid adducts. Wnt8a provides a crucial signal for patterning the anteroposterior axis of the developing neural plate in vertebrates. However, it is not clear how this protein propagates from its source, the blastoderm margin, to the target cells in the prospective neural plate, and how lipid-modifications might influence Wnt8a propagation and activity. We have dynamically imaged biologically active, fluorescently tagged Wnt8a in living zebrafish embryos. We find that Wnt8a localizes to membrane-associated, punctate structures in live tissue. In Wnt8a expressing cells, these puncta are found on filopodial cellular processes, from where the protein can be released. In addition, Wnt8a is found colocalized with Frizzled receptor-containing clusters on signal receiving cells. Combining in vitro and in vivo assays, we compare the roles of conserved Wnt8a residues in cell and non-cell-autonomous signaling activity and secretion. Non-signaling Wnt8 variants show these residues can regulate Wnt8a distribution in producing cell membranes and filopodia as well as in the receiving tissue. Together, our results show that Wnt8a forms dynamic clusters found on filopodial donor cell and on signal receiving cell membranes. Moreover, they demonstrate a differential requirement of conserved residues in Wnt8a protein for distribution in producing cells and receiving tissue and signaling activity during neuroectoderm patterning.

Dynamic Association with Donor Cell Filopodia and Lipid-Modification Are Essential Features of Wnt8a during Patterning of the Zebrafish Neuroectoderm

PubMed Central

Luz, Marta; Spannl-Müller, Stephanie; Özhan, Günes; Kagermeier-Schenk, Birgit; Rhinn, Muriel; Weidinger, Gilbert; Brand, Michael

2014-01-01

Background Wnt proteins are conserved signaling molecules that regulate pattern formation during animal development. Many Wnt proteins are post-translationally modified by addition of lipid adducts. Wnt8a provides a crucial signal for patterning the anteroposterior axis of the developing neural plate in vertebrates. However, it is not clear how this protein propagates from its source, the blastoderm margin, to the target cells in the prospective neural plate, and how lipid-modifications might influence Wnt8a propagation and activity. Results We have dynamically imaged biologically active, fluorescently tagged Wnt8a in living zebrafish embryos. We find that Wnt8a localizes to membrane-associated, punctate structures in live tissue. In Wnt8a expressing cells, these puncta are found on filopodial cellular processes, from where the protein can be released. In addition, Wnt8a is found colocalized with Frizzled receptor-containing clusters on signal receiving cells. Combining in vitro and in vivo assays, we compare the roles of conserved Wnt8a residues in cell and non-cell-autonomous signaling activity and secretion. Non-signaling Wnt8 variants show these residues can regulate Wnt8a distribution in producing cell membranes and filopodia as well as in the receiving tissue. Conclusions Together, our results show that Wnt8a forms dynamic clusters found on filopodial donor cell and on signal receiving cell membranes. Moreover, they demonstrate a differential requirement of conserved residues in Wnt8a protein for distribution in producing cells and receiving tissue and signaling activity during neuroectoderm patterning. PMID:24427298

Hydrogen exchange differences between chemoreceptor signaling complexes localize to functionally important subdomains.

PubMed

Koshy, Seena S; Li, Xuni; Eyles, Stephen J; Weis, Robert M; Thompson, Lynmarie K

2014-12-16

The goal of understanding mechanisms of transmembrane signaling, one of many key life processes mediated by membrane proteins, has motivated numerous studies of bacterial chemotaxis receptors. Ligand binding to the receptor causes a piston motion of an α helix in the periplasmic and transmembrane domains, but it is unclear how the signal is then propagated through the cytoplasmic domain to control the activity of the associated kinase CheA. Recent proposals suggest that signaling in the cytoplasmic domain involves opposing changes in dynamics in different subdomains. However, it has been difficult to measure dynamics within the functional system, consisting of extended arrays of receptor complexes with two other proteins, CheA and CheW. We have combined hydrogen exchange mass spectrometry with vesicle template assembly of functional complexes of the receptor cytoplasmic domain to reveal that there are significant signaling-associated changes in exchange, and these changes localize to key regions of the receptor involved in the excitation and adaptation responses. The methylation subdomain exhibits complex changes that include slower hydrogen exchange in complexes in a kinase-activating state, which may be partially consistent with proposals that this subdomain is stabilized in this state. The signaling subdomain exhibits significant protection from hydrogen exchange in complexes in a kinase-activating state, suggesting a tighter and/or larger interaction interface with CheA and CheW in this state. These first measurements of the stability of protein subdomains within functional signaling complexes demonstrate the promise of this approach for measuring functionally important protein dynamics within the various physiologically relevant states of multiprotein complexes.

Hydrogen Exchange Differences between Chemoreceptor Signaling Complexes Localize to Functionally Important Subdomains

PubMed Central

2015-01-01

The goal of understanding mechanisms of transmembrane signaling, one of many key life processes mediated by membrane proteins, has motivated numerous studies of bacterial chemotaxis receptors. Ligand binding to the receptor causes a piston motion of an α helix in the periplasmic and transmembrane domains, but it is unclear how the signal is then propagated through the cytoplasmic domain to control the activity of the associated kinase CheA. Recent proposals suggest that signaling in the cytoplasmic domain involves opposing changes in dynamics in different subdomains. However, it has been difficult to measure dynamics within the functional system, consisting of extended arrays of receptor complexes with two other proteins, CheA and CheW. We have combined hydrogen exchange mass spectrometry with vesicle template assembly of functional complexes of the receptor cytoplasmic domain to reveal that there are significant signaling-associated changes in exchange, and these changes localize to key regions of the receptor involved in the excitation and adaptation responses. The methylation subdomain exhibits complex changes that include slower hydrogen exchange in complexes in a kinase-activating state, which may be partially consistent with proposals that this subdomain is stabilized in this state. The signaling subdomain exhibits significant protection from hydrogen exchange in complexes in a kinase-activating state, suggesting a tighter and/or larger interaction interface with CheA and CheW in this state. These first measurements of the stability of protein subdomains within functional signaling complexes demonstrate the promise of this approach for measuring functionally important protein dynamics within the various physiologically relevant states of multiprotein complexes. PMID:25420045

Extracting a respiratory signal from raw dynamic PET data that contain tracer kinetics.

PubMed

Schleyer, P J; Thielemans, K; Marsden, P K

2014-08-07

Data driven gating (DDG) methods provide an alternative to hardware based respiratory gating for PET imaging. Several existing DDG approaches obtain a respiratory signal by observing the change in PET-counts within specific regions of acquired PET data. Currently, these methods do not allow for tracer kinetics which can interfere with the respiratory signal and introduce error. In this work, we produced a DDG method for dynamic PET studies that exhibit tracer kinetics. Our method is based on an existing approach that uses frequency-domain analysis to locate regions within raw PET data that are subject to respiratory motion. In the new approach, an optimised non-stationary short-time Fourier transform was used to create a time-varying 4D map of motion affected regions. Additional processing was required to ensure that the relationship between the sign of the respiratory signal and the physical direction of movement remained consistent for each temporal segment of the 4D map. The change in PET-counts within the 4D map during the PET acquisition was then used to generate a respiratory curve. Using 26 min dynamic cardiac NH3 PET acquisitions which included a hardware derived respiratory measurement, we show that tracer kinetics can severely degrade the respiratory signal generated by the original DDG method. In some cases, the transition of tracer from the liver to the lungs caused the respiratory signal to invert. The new approach successfully compensated for tracer kinetics and improved the correlation between the data-driven and hardware based signals. On average, good correlation was maintained throughout the PET acquisitions.

Analysis of a dynamic model of guard cell signaling reveals the stability of signal propagation

NASA Astrophysics Data System (ADS)

Gan, Xiao; Albert, RéKa

Analyzing the long-term behaviors (attractors) of dynamic models of biological systems can provide valuable insight into biological phenotypes and their stability. We identified the long-term behaviors of a multi-level, 70-node discrete dynamic model of the stomatal opening process in plants. We reduce the model's huge state space by reducing unregulated nodes and simple mediator nodes, and by simplifying the regulatory functions of selected nodes while keeping the model consistent with experimental observations. We perform attractor analysis on the resulting 32-node reduced model by two methods: 1. converting it into a Boolean model, then applying two attractor-finding algorithms; 2. theoretical analysis of the regulatory functions. We conclude that all nodes except two in the reduced model have a single attractor; and only two nodes can admit oscillations. The multistability or oscillations do not affect the stomatal opening level in any situation. This conclusion applies to the original model as well in all the biologically meaningful cases. We further demonstrate the robustness of signal propagation by showing that a large percentage of single-node knockouts does not affect the stomatal opening level. Thus, we conclude that the complex structure of this signal transduction network provides multiple information propagation pathways while not allowing extensive multistability or oscillations, resulting in robust signal propagation. Our innovative combination of methods offers a promising way to analyze multi-level models.

Dynamic Decision Making in Complex Task Environments: Principles and Neural Mechanisms

DTIC Science & Technology

2013-03-01

Dynamical models of cognition . Mathematical models of mental processes. Human performance optimization. U U U U Dr. Jay Myung 703-696-8487 Reset 1...we have continued to develop a neurodynamic theory of decision making, using a combination of computational and experimental approaches, to address...a long history in the field of human cognitive psychology. The theoretical foundations of this research can be traced back to signal detection

Inference of Spatio-Temporal Functions Over Graphs via Multikernel Kriged Kalman Filtering

NASA Astrophysics Data System (ADS)

Ioannidis, Vassilis N.; Romero, Daniel; Giannakis, Georgios B.

2018-06-01

Inference of space-time varying signals on graphs emerges naturally in a plethora of network science related applications. A frequently encountered challenge pertains to reconstructing such dynamic processes, given their values over a subset of vertices and time instants. The present paper develops a graph-aware kernel-based kriged Kalman filter that accounts for the spatio-temporal variations, and offers efficient online reconstruction, even for dynamically evolving network topologies. The kernel-based learning framework bypasses the need for statistical information by capitalizing on the smoothness that graph signals exhibit with respect to the underlying graph. To address the challenge of selecting the appropriate kernel, the proposed filter is combined with a multi-kernel selection module. Such a data-driven method selects a kernel attuned to the signal dynamics on-the-fly within the linear span of a pre-selected dictionary. The novel multi-kernel learning algorithm exploits the eigenstructure of Laplacian kernel matrices to reduce computational complexity. Numerical tests with synthetic and real data demonstrate the superior reconstruction performance of the novel approach relative to state-of-the-art alternatives.

Dynamic hysteresis in a one-dimensional Ising model: application to allosteric proteins.

PubMed

Graham, I; Duke, T A J

2005-06-01

We solve exactly the problem of dynamic hysteresis for a finite one-dimensional Ising model at low temperature. We find that the area of the hysteresis loop, as the field is varied periodically, scales as the square root of the field frequency for a large range of frequencies. Below a critical frequency there is a correction to the scaling law, resulting in a linear relationship between hysteresis area and frequency. The one-dimensional Ising model provides a simplified description of switchlike behavior in allosteric proteins, such as hemoglobin. Thus our analysis predicts the switching dynamics of allosteric proteins when they are exposed to a ligand concentration which changes with time. Many allosteric proteins bind a regulator that is maintained at a nonequilibrium concentration by active signal transduction processes. In the light of our analysis, we discuss to what extent allosteric proteins can respond to changes in regulator concentration caused by an upstream signaling event, while remaining insensitive to the intrinsic nonequilibrium fluctuations in regulator level which occur in the absence of a signal.

Collective Calcium Signaling of Defective Multicellular Networks

NASA Astrophysics Data System (ADS)

Potter, Garrett; Sun, Bo

2015-03-01

A communicating multicellular network processes environmental cues into collective cellular dynamics. We have previously demonstrated that, when excited by extracellular ATP, fibroblast monolayers generate correlated calcium dynamics modulated by both the stimuli and gap junction communication between the cells. However, just as a well-connected neural network may be compromised by abnormal neurons, a tissue monolayer can also be defective with cancer cells, which typically have down regulated gap junctions. To understand the collective cellular dynamics in a defective multicellular network we have studied the calcium signaling of co-cultured breast cancer cells and fibroblast cells in various concentrations of ATP delivered through microfluidic devices. Our results demonstrate that cancer cells respond faster, generate singular spikes, and are more synchronous across all stimuli concentrations. Additionally, fibroblast cells exhibit persistent calcium oscillations that increase in regularity with greater stimuli. To interpret these results we quantitatively analyzed the immunostaining of purigenic receptors and gap junction channels. The results confirm our hypothesis that collective dynamics are mainly determined by the availability of gap junction communications.

A bunch to bucket phase detector for the RHIC LLRF upgrade platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, K.S.; Harvey, M.; Hayes, T.

2011-03-28

As part of the overall development effort for the RHIC LLRF Upgrade Platform [1,2,3], a generic four channel 16 bit Analog-to-Digital Converter (ADC) daughter module was developed to provide high speed, wide dynamic range digitizing and processing of signals from DC to several hundred megahertz. The first operational use of this card was to implement the bunch to bucket phase detector for the RHIC LLRF beam control feedback loops. This paper will describe the design and performance features of this daughter module as a bunch to bucket phase detector, and also provide an overview of its place within the overallmore » LLRF platform architecture as a high performance digitizer and signal processing module suitable to a variety of applications. In modern digital control and signal processing systems, ADCs provide the interface between the analog and digital signal domains. Once digitized, signals are then typically processed using algorithms implemented in field programmable gate array (FPGA) logic, general purpose processors (GPPs), digital signal processors (DSPs) or a combination of these. For the recently developed and commissioned RHIC LLRF Upgrade Platform, we've developed a four channel ADC daughter module based on the Linear Technology LTC2209 16 bit, 160 MSPS ADC and the Xilinx V5FX70T FPGA. The module is designed to be relatively generic in application, and with minimal analog filtering on board, is capable of processing signals from DC to 500 MHz or more. The module's first application was to implement the bunch to bucket phase detector (BTB-PD) for the RHIC LLRF system. The same module also provides DC digitizing of analog processed BPM signals used by the LLRF system for radial feedback.« less

Accelerated dynamic cardiac MRI exploiting sparse-Kalman-smoother self-calibration and reconstruction (k  -  t SPARKS)

NASA Astrophysics Data System (ADS)

Park, Suhyung; Park, Jaeseok

2015-05-01

Accelerated dynamic MRI, which exploits spatiotemporal redundancies in k  -  t space and coil dimension, has been widely used to reduce the number of signal encoding and thus increase imaging efficiency with minimal loss of image quality. Nonetheless, particularly in cardiac MRI it still suffers from artifacts and amplified noise in the presence of time-drifting coil sensitivity due to relative motion between coil and subject (e.g. free breathing). Furthermore, a substantial number of additional calibrating signals is to be acquired to warrant accurate calibration of coil sensitivity. In this work, we propose a novel, accelerated dynamic cardiac MRI with sparse-Kalman-smoother self-calibration and reconstruction (k  -  t SPARKS), which is robust to time-varying coil sensitivity even with a small number of calibrating signals. The proposed k  -  t SPARKS incorporates Kalman-smoother self-calibration in k  -  t space and sparse signal recovery in x  -   f space into a single optimization problem, leading to iterative, joint estimation of time-varying convolution kernels and missing signals in k  -  t space. In the Kalman-smoother calibration, motion-induced uncertainties over the entire time frames were included in modeling state transition while a coil-dependent noise statistic in describing measurement process. The sparse signal recovery iteratively alternates with the self-calibration to tackle the ill-conditioning problem potentially resulting from insufficient calibrating signals. Simulations and experiments were performed using both the proposed and conventional methods for comparison, revealing that the proposed k  -  t SPARKS yields higher signal-to-error ratio and superior temporal fidelity in both breath-hold and free-breathing cardiac applications over all reduction factors.

Accelerated dynamic cardiac MRI exploiting sparse-Kalman-smoother self-calibration and reconstruction (k  -  t SPARKS).

PubMed

Park, Suhyung; Park, Jaeseok

2015-05-07

Accelerated dynamic MRI, which exploits spatiotemporal redundancies in k  -  t space and coil dimension, has been widely used to reduce the number of signal encoding and thus increase imaging efficiency with minimal loss of image quality. Nonetheless, particularly in cardiac MRI it still suffers from artifacts and amplified noise in the presence of time-drifting coil sensitivity due to relative motion between coil and subject (e.g. free breathing). Furthermore, a substantial number of additional calibrating signals is to be acquired to warrant accurate calibration of coil sensitivity. In this work, we propose a novel, accelerated dynamic cardiac MRI with sparse-Kalman-smoother self-calibration and reconstruction (k  -  t SPARKS), which is robust to time-varying coil sensitivity even with a small number of calibrating signals. The proposed k  -  t SPARKS incorporates Kalman-smoother self-calibration in k  -  t space and sparse signal recovery in x  -   f space into a single optimization problem, leading to iterative, joint estimation of time-varying convolution kernels and missing signals in k  -  t space. In the Kalman-smoother calibration, motion-induced uncertainties over the entire time frames were included in modeling state transition while a coil-dependent noise statistic in describing measurement process. The sparse signal recovery iteratively alternates with the self-calibration to tackle the ill-conditioning problem potentially resulting from insufficient calibrating signals. Simulations and experiments were performed using both the proposed and conventional methods for comparison, revealing that the proposed k  -  t SPARKS yields higher signal-to-error ratio and superior temporal fidelity in both breath-hold and free-breathing cardiac applications over all reduction factors.

The Dynamic Performance of Flexural Ultrasonic Transducers.

PubMed

Feeney, Andrew; Kang, Lei; Rowlands, George; Dixon, Steve

2018-01-18

Flexural ultrasonic transducers are principally used as proximity sensors and for industrial metrology. Their operation relies on a piezoelectric ceramic to generate a flexing of a metallic membrane, which delivers the ultrasound signal. The performance of flexural ultrasonic transducers has been largely limited to excitation through a short voltage burst signal at a designated mechanical resonance frequency. However, a steady-state amplitude response is not generated instantaneously in a flexural ultrasonic transducer from a drive excitation signal, and differences in the drive characteristics between transmitting and receiving transducers can affect the measured response. This research investigates the dynamic performance of flexural ultrasonic transducers using acoustic microphone measurements and laser Doppler vibrometry, supported by a detailed mechanical analog model, in a process which has not before been applied to the flexural ultrasonic transducer. These techniques are employed to gain insights into the physics of their vibration behaviour, vital for the optimisation of industrial ultrasound systems.

The Dynamic Performance of Flexural Ultrasonic Transducers

PubMed Central

Kang, Lei; Rowlands, George; Dixon, Steve

2018-01-01

Flexural ultrasonic transducers are principally used as proximity sensors and for industrial metrology. Their operation relies on a piezoelectric ceramic to generate a flexing of a metallic membrane, which delivers the ultrasound signal. The performance of flexural ultrasonic transducers has been largely limited to excitation through a short voltage burst signal at a designated mechanical resonance frequency. However, a steady-state amplitude response is not generated instantaneously in a flexural ultrasonic transducer from a drive excitation signal, and differences in the drive characteristics between transmitting and receiving transducers can affect the measured response. This research investigates the dynamic performance of flexural ultrasonic transducers using acoustic microphone measurements and laser Doppler vibrometry, supported by a detailed mechanical analog model, in a process which has not before been applied to the flexural ultrasonic transducer. These techniques are employed to gain insights into the physics of their vibration behaviour, vital for the optimisation of industrial ultrasound systems. PMID:29346297

Imaging calcium sparks in cardiac myocytes.

PubMed

Guatimosim, Silvia; Guatimosim, Cristina; Song, Long-Sheng

2011-01-01

Calcium ions play fundamental roles in many cellular processes in virtually all type of cells. The use of Ca(2+) sensitive fluorescent indicators has proven to be an indispensable tool for studying the spatio-temporal dynamics of intracellular calcium ([Ca(2+)](i)). With the aid of laser scanning confocal microscopy and new generation of Ca(2+) indicators, highly localized, short-lived Ca(2+) signals, namely Ca(2+) sparks, were revealed as elementary Ca(2+) release events during excitation-contraction coupling in cardiomyocytes. Since the discovery of Ca(2+) sparks in 1993, the demonstration of dynamic Ca(2+) micro-domains in living cardiomyocytes has revolutionized our understanding of Ca(2+)-mediated signal transduction in normal and diseased hearts. In this chapter, we have described a commonly used method for recording local and global Ca(2+) signals in cardiomyocytes using the fluorescent indicator fluo-4 acetoxymethyl (AM) and laser scanning confocal microscopy.

Dissecting single-molecule signal transduction in carbon nanotube circuits with protein engineering

PubMed Central

Choi, Yongki; Olsen, Tivoli J.; Sims, Patrick C.; Moody, Issa S.; Corso, Brad L.; Dang, Mytrang N.; Weiss, Gregory A.; Collins, Philip G.

2013-01-01

Single molecule experimental methods have provided new insights into biomolecular function, dynamic disorder, and transient states that are all invisible to conventional measurements. A novel, non-fluorescent single molecule technique involves attaching single molecules to single-walled carbon nanotube field-effective transistors (SWNT FETs). These ultrasensitive electronic devices provide long-duration, label-free monitoring of biomolecules and their dynamic motions. However, generalization of the SWNT FET technique first requires design rules that can predict the success and applicability of these devices. Here, we report on the transduction mechanism linking enzymatic processivity to electrical signal generation by a SWNT FET. The interaction between SWNT FETs and the enzyme lysozyme was systematically dissected using eight different lysozyme variants synthesized by protein engineering. The data prove that effective signal generation can be accomplished using a single charged amino acid, when appropriately located, providing a foundation to widely apply SWNT FET sensitivity to other biomolecular systems. PMID:23323846

Changes in expression and secretion patterns of fibroblast growth factor 8 and Sonic Hedgehog signaling pathway molecules during murine neural stem/progenitor cell differentiation in vitro☆

PubMed Central

Lu, Jiang; Lu, Kehuan; Li, Dongsheng

2012-01-01

In the present study, we investigated the dynamic expression of fibroblast growth factor 8 and Sonic Hedgehog signaling pathway related factors in the process of in vitro hippocampal neural stem/progenitor cell differentiation from embryonic Sprague-Dawley rats or embryonic Kunming species mice, using fluorescent quantitative reverse transcription-PCR and western blot analyses. Results demonstrated that the dynamic expression of fibroblast growth factor 8 was similar to fibroblast growth factor receptor 1 expression but not to other fibroblast growth factor receptors. Enzyme-linked immunosorbent assay demonstrated that fibroblast growth factor 8 and Sonic Hedgehog signaling pathway protein factors were secreted by neural cells into the intercellular niche. Our experimental findings indicate that fibroblast growth factor 8 and Sonic Hedgehog expression may be related to the differentiation of neural stem/progenitor cells. PMID:25624789

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system

PubMed Central

2010-01-01

Background The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the “in silico” stochastic event based modeling approach to find the molecular dynamics of the system. Results In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Conclusions Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics. PMID:21143785

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system.

PubMed

Ghosh, Preetam; Ghosh, Samik; Basu, Kalyan; Das, Sajal K; Zhang, Chaoyang

2010-12-01

The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the "in silico" stochastic event based modeling approach to find the molecular dynamics of the system. In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics.

Phase analysis of coherent radial-breathing-mode phonons in carbon nanotubes: Implications for generation and detection processes

NASA Astrophysics Data System (ADS)

Shimura, Akihiko; Yanagi, Kazuhiro; Yoshizawa, Masayuki

2018-01-01

In time-resolved pump-probe spectroscopy of carbon nanotubes, the fundamental understanding of the optical generation and detection processes of radial-breathing-mode (RBM) phonons has been inconsistent among the previous reports. In this study, the tunable-pumping/broadband-probing scheme was used to fully reveal the amplitude and phase of the phonon-modulated signals. We observed that signals detected off resonantly to excitonic transitions are delayed by π /2 radians with respect to resonantly detected signals, which demonstrates that RBM phonons are detected through dynamically modulating the linear response, not through adiabatically modulating the light absorption. Furthermore, we found that the initial phases are independent of the pump detuning across the first (E11) and the second (E22) excitonic resonances, evidencing that the RBM phonons are generated by the displacive excitation rather than stimulated Raman process.

Nonlinear analysis of pupillary dynamics.

PubMed

Onorati, Francesco; Mainardi, Luca Tommaso; Sirca, Fabiola; Russo, Vincenzo; Barbieri, Riccardo

2016-02-01

Pupil size reflects autonomic response to different environmental and behavioral stimuli, and its dynamics have been linked to other autonomic correlates such as cardiac and respiratory rhythms. The aim of this study is to assess the nonlinear characteristics of pupil size of 25 normal subjects who participated in a psychophysiological experimental protocol with four experimental conditions, namely “baseline”, “anger”, “joy”, and “sadness”. Nonlinear measures, such as sample entropy, correlation dimension, and largest Lyapunov exponent, were computed on reconstructed signals of spontaneous fluctuations of pupil dilation. Nonparametric statistical tests were performed on surrogate data to verify that the nonlinear measures are an intrinsic characteristic of the signals. We then developed and applied a piecewise linear regression model to detrended fluctuation analysis (DFA). Two joinpoints and three scaling intervals were identified: slope α0, at slow time scales, represents a persistent nonstationary long-range correlation, whereas α1 and α2, at middle and fast time scales, respectively, represent long-range power-law correlations, similarly to DFA applied to heart rate variability signals. Of the computed complexity measures, α0 showed statistically significant differences among experimental conditions (p<0.001). Our results suggest that (a) pupil size at constant light condition is characterized by nonlinear dynamics, (b) three well-defined and distinct long-memory processes exist at different time scales, and (c) autonomic stimulation is partially reflected in nonlinear dynamics. (c) autonomic stimulation is partially reflected in nonlinear dynamics.

Dynamic Polymorphic Reconfiguration to Effectively Cloak a Circuit’s Function

DTIC Science & Technology

2011-03-24

86 B . RSA Traces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 2.1...56 22 SEMA of Separate Square and Multiply Trace with key (E B5) - RSA Version B ...56 23 Separate Square and Multiply Trace after signal processing - RSA Version B

How seismic waves can be used to understand and constrain landslide dynamics

NASA Astrophysics Data System (ADS)

Mangeney, A.; Favreau, P.; Moretti, L.; Lucas, A.; Le Friant, A.; Bouchut, F.

2010-12-01

Gravitational instabilities such as debris flows, landslide or avalanches play a key role in erosion processes on the Earth’s surface and represent one of the major natural hazard threatening life and property in mountainous, volcanic, seismic and coastal areas. Despite the great amount of experimental, numerical and field studies, the understanding of landslide dynamics is still an open question. In particular, there is no consensus to explain the high mobility of natural avalanches. Field measurements relevant to the dynamics of natural landslides are scarce. This is due to their unpredictability and destructive power and prevents detailed investigation of the mechanical properties of the flowing material. Recent studies have shown that the seismic signal generated by landslides provides a unique way to detect gravitational instabilities and to get information on their dynamics and geometrical characteristics. In particular, Favreau et al. [2009] show that simulation of landslides and generated seismic waves reproduce the main features of the recorded low frequency seismic signal, making it possible to discriminate between possible alternative scenarios for flow dynamics and to provide first estimates of the rheological parameters. We propose here to go further in this direction by investigating the following key questions: What is the effect of the topography and of the landslide volume on the generated seismic signal? What is the sensitivity of the generated seismic signal to the mechanical behavior of the landslide? At what distance and frequency is the point source approximation correct? To address these issues, numerical simulation of two well constrained landslides has been performed: the 2.5 Mm3 Thurwieser landslide that occurred in Italy in 2004 and the 60 Mm3 Boxing Day debris avalanche that occurred in Montserrat in 1997 during the volcanic eruption. For both landslides, simulation shows the major role of topography curvature on the generated seismic signal even for the signal recorded as far as 450 km from the source. Furthermore, comparison between observed and simulated seismic signal in Montserrat provides insights into the time sequence of the gravitational events associated to the eruption.

Primary sex determination of placental mammals: a modelling study uncovers dynamical developmental constraints in the formation of Sertoli and granulosa cells.

PubMed

Sánchez, Lucas; Chaouiya, Claudine

2016-05-26

Primary sex determination in placental mammals is a very well studied developmental process. Here, we aim to investigate the currently established scenario and to assess its adequacy to fully recover the observed phenotypes, in the wild type and perturbed situations. Computational modelling allows clarifying network dynamics, elucidating crucial temporal constrains as well as interplay between core regulatory modules. Relying on a comprehensive revision of the literature, we define a logical model that integrates the current knowledge of the regulatory network controlling this developmental process. Our analysis indicates the necessity for some genes to operate at distinct functional thresholds and for specific developmental conditions to ensure the reproducibility of the sexual pathways followed by bi-potential gonads developing into either testes or ovaries. Our model thus allows studying the dynamics of wild type and mutant XX and XY gonads. Furthermore, the model analysis reveals that the gonad sexual fate results from the operation of two sub-networks associated respectively with an initiation and a maintenance phases. At the core of the process is the resolution of two connected feedback loops: the mutual inhibition of Sox9 and ß-catenin at the initiation phase, which in turn affects the mutual inhibition between Dmrt1 and Foxl2, at the maintenance phase. Three developmental signals related to the temporal activity of those sub-networks are required: a signal that determines Sry activation, marking the beginning of the initiation phase, and two further signals that define the transition from the initiation to the maintenance phases, by inhibiting the Wnt4 signalling pathway on the one hand, and by activating Foxl2 on the other hand. Our model reproduces a wide range of experimental data reported for the development of wild type and mutant gonads. It also provides a formal support to crucial aspects of the gonad sexual development and predicts gonadal phenotypes for mutations not tested yet.

High spatial resolution distributed optical fiber dynamic strain sensor with enhanced frequency and strain resolution.

PubMed

Masoudi, Ali; Newson, Trevor P

2017-01-15

A distributed optical fiber dynamic strain sensor with high spatial and frequency resolution is demonstrated. The sensor, which uses the ϕ-OTDR interrogation technique, exhibited a higher sensitivity thanks to an improved optical arrangement and a new signal processing procedure. The proposed sensing system is capable of fully quantifying multiple dynamic perturbations along a 5 km long sensing fiber with a frequency and spatial resolution of 5 Hz and 50 cm, respectively. The strain resolution of the sensor was measured to be 40 nε.

Constitutional dynamic self-sensing in a zinc(II)/polyiminofluorenes system.

PubMed

Giuseppone, Nicolas; Lehn, Jean-Marie

2004-09-22

The interaction of an external effector, ZnII ions, with a constitutional dynamic library of fluorescent polyiminofluorenes leads to component exchange, which generates an entity responding by a change in emission to the effector that has induced its formation. The overall coupled system displays a tuning of optical signal, resulting from two synergistic processes: adaptative constitutional reorganization and self-sensing. In broader terms, this work highlights the perspectives opened by constitutional dynamic chemistry toward the design of smart materials, capable of expressing different latent properties in response to environmental conditions.

Controlling Complex Systems and Developing Dynamic Technology

NASA Astrophysics Data System (ADS)

Avizienis, Audrius Victor

In complex systems, control and understanding become intertwined. Following Ilya Prigogine, we define complex systems as having control parameters which mediate transitions between distinct modes of dynamical behavior. From this perspective, determining the nature of control parameters and demonstrating the associated dynamical phase transitions are practically equivalent and fundamental to engaging with complexity. In the first part of this work, a control parameter is determined for a non-equilibrium electrochemical system by studying a transition in the morphology of structures produced by an electroless deposition reaction. Specifically, changing the size of copper posts used as the substrate for growing metallic silver structures by the reduction of Ag+ from solution under diffusion-limited reaction conditions causes a dynamical phase transition in the crystal growth process. For Cu posts with edge lengths on the order of one micron, local forces promoting anisotropic growth predominate, and the reaction produces interconnected networks of Ag nanowires. As the post size is increased above 10 microns, the local interfacial growth reaction dynamics couple with the macroscopic diffusion field, leading to spatially propagating instabilities in the electrochemical potential which induce periodic branching during crystal growth, producing dendritic deposits. This result is interesting both as an example of control and understanding in a complex system, and as a useful combination of top-down lithography with bottom-up electrochemical self-assembly. The second part of this work focuses on the technological development of devices fabricated using this non-equilibrium electrochemical process, towards a goal of integrating a complex network as a dynamic functional component in a neuromorphic computing device. Self-assembled networks of silver nanowires were reacted with sulfur to produce interfacial "atomic switches": silver-silver sulfide junctions, which exhibit complex dynamics (e.g. both short- and long-term changes in conductivity) in response to applied voltage signals. Characterization of these atomic switch networks (ASNs) brought out interesting parallels to biological neural networks, including power-law scaling in the statistics of electrical signal propagation and dynamic self-organization of differentiated subnetworks. A reservoir computing (RC) strategy was employed to utilize measurements of electrical signals dynamically generated in ASNs to perform time-series memory and manipulation tasks including a parity test and arbitrary waveform generation. These results represent the useful integration of a complex network into a dynamic physical RC device.

Dynamic in vivo imaging of small animal brain using pulsed laser diode-based photoacoustic tomography system

NASA Astrophysics Data System (ADS)

Upputuri, Paul Kumar; Pramanik, Manojit

2017-09-01

We demonstrate dynamic in vivo imaging using a low-cost portable pulsed laser diode (PLD)-based photoacoustic tomography system. The system takes advantage of an 803-nm PLD having high-repetition rate ˜7000 Hz combined with a fast-scanning single-element ultrasound transducer leading to a 5 s cross-sectional imaging. Cortical vasculature is imaged in scan time of 5 s with high signal-to-noise ratio ˜48. To examine the ability for dynamic imaging, we monitored the fast uptake and clearance process of indocyanine green in the rat brain. The system will find applications to study neurofunctional activities, characterization of pharmacokinetic, and biodistribution profiles in the development process of drugs or imaging agents.

Analysis of brain patterns using temporal measures

DOEpatents

Georgopoulos, Apostolos

2015-08-11

A set of brain data representing a time series of neurophysiologic activity acquired by spatially distributed sensors arranged to detect neural signaling of a brain (such as by the use of magnetoencephalography) is obtained. The set of brain data is processed to obtain a dynamic brain model based on a set of statistically-independent temporal measures, such as partial cross correlations, among groupings of different time series within the set of brain data. The dynamic brain model represents interactions between neural populations of the brain occurring close in time, such as with zero lag, for example. The dynamic brain model can be analyzed to obtain the neurophysiologic assessment of the brain. Data processing techniques may be used to assess structural or neurochemical brain pathologies.

A Robust Dynamic Heart-Rate Detection Algorithm Framework During Intense Physical Activities Using Photoplethysmographic Signals

PubMed Central

Song, Jiajia; Li, Dan; Ma, Xiaoyuan; Teng, Guowei; Wei, Jianming

2017-01-01

Dynamic accurate heart-rate (HR) estimation using a photoplethysmogram (PPG) during intense physical activities is always challenging due to corruption by motion artifacts (MAs). It is difficult to reconstruct a clean signal and extract HR from contaminated PPG. This paper proposes a robust HR-estimation algorithm framework that uses one-channel PPG and tri-axis acceleration data to reconstruct the PPG and calculate the HR based on features of the PPG and spectral analysis. Firstly, the signal is judged by the presence of MAs. Then, the spectral peaks corresponding to acceleration data are filtered from the periodogram of the PPG when MAs exist. Different signal-processing methods are applied based on the amount of remaining PPG spectral peaks. The main MA-removal algorithm (NFEEMD) includes the repeated single-notch filter and ensemble empirical mode decomposition. Finally, HR calibration is designed to ensure the accuracy of HR tracking. The NFEEMD algorithm was performed on the 23 datasets from the 2015 IEEE Signal Processing Cup Database. The average estimation errors were 1.12 BPM (12 training datasets), 2.63 BPM (10 testing datasets) and 1.87 BPM (all 23 datasets), respectively. The Pearson correlation was 0.992. The experiment results illustrate that the proposed algorithm is not only suitable for HR estimation during continuous activities, like slow running (13 training datasets), but also for intense physical activities with acceleration, like arm exercise (10 testing datasets). PMID:29068403

Structural dynamics of the cell nucleus: basis for morphology modulation of nuclear calcium signaling and gene transcription.

PubMed

Queisser, Gillian; Wiegert, Simon; Bading, Hilmar

2011-01-01

Neuronal morphology plays an essential role in signal processing in the brain. Individual neurons can undergo use-dependent changes in their shape and connectivity, which affects how intracellular processes are regulated and how signals are transferred from one cell to another in a neuronal network. Calcium is one of the most important intracellular second messengers regulating cellular morphologies and functions. In neurons, intracellular calcium levels are controlled by ion channels in the plasma membrane such as NMDA receptors (NMDARs), voltage-gated calcium channels (VGCCs) and certain α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) as well as by calcium exchange pathways between the cytosol and internal calcium stores including the endoplasmic reticulum and mitochondria. Synaptic activity and the subsequent opening of ligand and/or voltage-gated calcium channels can initiate cytosolic calcium transients which propagate towards the cell soma and enter the nucleus via its nuclear pore complexes (NPCs) embedded in the nuclear envelope. We recently described the discovery that in hippocampal neurons the morphology of the nucleus affects the calcium dynamics within the nucleus. Here we propose that nuclear infoldings determine whether a nucleus functions as an integrator or detector of oscillating calcium signals. We outline possible ties between nuclear mophology and transcriptional activity and discuss the importance of extending the approach to whole cell calcium signal modeling in order to understand synapse-to-nucleus communication in healthy and dysfunctional neurons.

Pseudo Asynchronous Level Crossing adc for ecg Signal Acquisition.

PubMed

Marisa, T; Niederhauser, T; Haeberlin, A; Wildhaber, R A; Vogel, R; Goette, J; Jacomet, M

2017-02-07

A new pseudo asynchronous level crossing analogue-to-digital converter (adc) architecture targeted for low-power, implantable, long-term biomedical sensing applications is presented. In contrast to most of the existing asynchronous level crossing adc designs, the proposed design has no digital-to-analogue converter (dac) and no continuous time comparators. Instead, the proposed architecture uses an analogue memory cell and dynamic comparators. The architecture retains the signal activity dependent sampling operation by generating events only when the input signal is changing. The architecture offers the advantages of smaller chip area, energy saving and fewer analogue system components. Beside lower energy consumption the use of dynamic comparators results in a more robust performance in noise conditions. Moreover, dynamic comparators make interfacing the asynchronous level crossing system to synchronous processing blocks simpler. The proposed adc was implemented in [Formula: see text] complementary metal-oxide-semiconductor (cmos) technology, the hardware occupies a chip area of 0.0372 mm 2 and operates from a supply voltage of [Formula: see text] to [Formula: see text]. The adc's power consumption is as low as 0.6 μW with signal bandwidth from [Formula: see text] to [Formula: see text] and achieves an equivalent number of bits (enob) of up to 8 bits.

Efficient dynamic events discrimination technique for fiber distributed Brillouin sensors.

PubMed

Galindez, Carlos A; Madruga, Francisco J; Lopez-Higuera, Jose M

2011-09-26

A technique to detect real time variations of temperature or strain in Brillouin based distributed fiber sensors is proposed and is investigated in this paper. The technique is based on anomaly detection methods such as the RX-algorithm. Detection and isolation of dynamic events from the static ones are demonstrated by a proper processing of the Brillouin gain values obtained by using a standard BOTDA system. Results also suggest that better signal to noise ratio, dynamic range and spatial resolution can be obtained. For a pump pulse of 5 ns the spatial resolution is enhanced, (from 0.541 m obtained by direct gain measurement, to 0.418 m obtained with the technique here exposed) since the analysis is concentrated in the variation of the Brillouin gain and not only on the averaging of the signal along the time. © 2011 Optical Society of America

Phase-selective entrainment of nonlinear oscillator ensembles

DOE PAGES

Zlotnik, Anatoly V.; Nagao, Raphael; Kiss, Istvan Z.; ...

2016-03-18

The ability to organize and finely manipulate the hierarchy and timing of dynamic processes is important for understanding and influencing brain functions, sleep and metabolic cycles, and many other natural phenomena. However, establishing spatiotemporal structures in biological oscillator ensembles is a challenging task that requires controlling large collections of complex nonlinear dynamical units. In this report, we present a method to design entrainment signals that create stable phase patterns in ensembles of heterogeneous nonlinear oscillators without using state feedback information. We demonstrate the approach using experiments with electrochemical reactions on multielectrode arrays, in which we selectively assign ensemble subgroups intomore » spatiotemporal patterns with multiple phase clusters. As a result, the experimentally confirmed mechanism elucidates the connection between the phases and natural frequencies of a collection of dynamical elements, the spatial and temporal information that is encoded within this ensemble, and how external signals can be used to retrieve this information.« less

Non-Equlibrium Driven Dynamics of Continuous Attractors in Place Cell Networks

NASA Astrophysics Data System (ADS)

Zhong, Weishun; Kim, Hyun Jin; Schwab, David; Murugan, Arvind

Attractors have found much use in neuroscience as a means of information processing and decision making. Examples include associative memory with point and continuous attractors, spatial navigation and planning using place cell networks, dynamic pattern recognition among others. The functional use of such attractors requires the action of spatially and temporally varying external driving signals and yet, most theoretical work on attractors has been in the limit of small or no drive. We take steps towards understanding the non-equilibrium driven dynamics of continuous attractors in place cell networks. We establish an `equivalence principle' that relates fluctuations under a time-dependent external force to equilibrium fluctuations in a `co-moving' frame with only static forces, much like in Newtonian physics. Consequently, we analytically derive a network's capacity to encode multiple attractors as a function of the driving signal size and rate of change.

Actin Engine in Immunological Synapse

PubMed Central

Piragyte, Indre

2012-01-01

T cell activation and function require physical contact with antigen presenting cells at a specialized junctional structure known as the immunological synapse. Once formed, the immunological synapse leads to sustained T cell receptor-mediated signalling and stabilized adhesion. High resolution microscopy indeed had a great impact in understanding the function and dynamic structure of immunological synapse. Trends of recent research are now moving towards understanding the mechanical part of immune system, expanding our knowledge in mechanosensitivity, force generation, and biophysics of cell-cell interaction. Actin cytoskeleton plays inevitable role in adaptive immune system, allowing it to bear dynamic and precise characteristics at the same time. The regulation of mechanical engine seems very complicated and overlapping, but it enables cells to be very sensitive to external signals such as surface rigidity. In this review, we focus on actin regulators and how immune cells regulate dynamic actin rearrangement process to drive the formation of immunological synapse. PMID:22916042

Phase-selective entrainment of nonlinear oscillator ensembles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zlotnik, Anatoly V.; Nagao, Raphael; Kiss, Istvan Z.

The ability to organize and finely manipulate the hierarchy and timing of dynamic processes is important for understanding and influencing brain functions, sleep and metabolic cycles, and many other natural phenomena. However, establishing spatiotemporal structures in biological oscillator ensembles is a challenging task that requires controlling large collections of complex nonlinear dynamical units. In this report, we present a method to design entrainment signals that create stable phase patterns in ensembles of heterogeneous nonlinear oscillators without using state feedback information. We demonstrate the approach using experiments with electrochemical reactions on multielectrode arrays, in which we selectively assign ensemble subgroups intomore » spatiotemporal patterns with multiple phase clusters. As a result, the experimentally confirmed mechanism elucidates the connection between the phases and natural frequencies of a collection of dynamical elements, the spatial and temporal information that is encoded within this ensemble, and how external signals can be used to retrieve this information.« less

Phase-selective entrainment of nonlinear oscillator ensembles

NASA Astrophysics Data System (ADS)

Zlotnik, Anatoly; Nagao, Raphael; Kiss, István Z.; Li-Shin, Jr.

2016-03-01

The ability to organize and finely manipulate the hierarchy and timing of dynamic processes is important for understanding and influencing brain functions, sleep and metabolic cycles, and many other natural phenomena. However, establishing spatiotemporal structures in biological oscillator ensembles is a challenging task that requires controlling large collections of complex nonlinear dynamical units. In this report, we present a method to design entrainment signals that create stable phase patterns in ensembles of heterogeneous nonlinear oscillators without using state feedback information. We demonstrate the approach using experiments with electrochemical reactions on multielectrode arrays, in which we selectively assign ensemble subgroups into spatiotemporal patterns with multiple phase clusters. The experimentally confirmed mechanism elucidates the connection between the phases and natural frequencies of a collection of dynamical elements, the spatial and temporal information that is encoded within this ensemble, and how external signals can be used to retrieve this information.

Growth-mediated autochemotactic pattern formation in self-propelling bacteria

NASA Astrophysics Data System (ADS)

Mukherjee, Mrinmoy; Ghosh, Pushpita

2018-01-01

Bacteria, while developing a multicellular colony or biofilm, can undergo pattern formation by diverse intricate mechanisms. One such route is directional movement or chemotaxis toward or away from self-secreted or externally employed chemicals. In some bacteria, the self-produced signaling chemicals or autoinducers themselves act as chemoattractants or chemorepellents and thereby regulate the directional movements of the cells in the colony. In addition, bacteria follow a certain growth kinetics which is integrated in the process of colony development. Here, we study the interplay of bacterial growth dynamics, cell motility, and autochemotactic motion with respect to the self-secreted diffusive signaling chemicals in spatial pattern formation. Using a continuum model of motile bacteria, we show growth can act as a crucial tuning parameter in determining the spatiotemporal dynamics of a colony. In action of growth dynamics, while chemoattraction toward autoinducers creates arrested phase separation, pattern transitions and suppression can occur for a fixed chemorepulsive strength.

Dynamic system classifier.

PubMed

Pumpe, Daniel; Greiner, Maksim; Müller, Ewald; Enßlin, Torsten A

2016-07-01

Stochastic differential equations describe well many physical, biological, and sociological systems, despite the simplification often made in their derivation. Here the usage of simple stochastic differential equations to characterize and classify complex dynamical systems is proposed within a Bayesian framework. To this end, we develop a dynamic system classifier (DSC). The DSC first abstracts training data of a system in terms of time-dependent coefficients of the descriptive stochastic differential equation. Thereby the DSC identifies unique correlation structures within the training data. For definiteness we restrict the presentation of the DSC to oscillation processes with a time-dependent frequency ω(t) and damping factor γ(t). Although real systems might be more complex, this simple oscillator captures many characteristic features. The ω and γ time lines represent the abstract system characterization and permit the construction of efficient signal classifiers. Numerical experiments show that such classifiers perform well even in the low signal-to-noise regime.

Palytoxins and cytoskeleton: An overview.

PubMed

Louzao, M Carmen; Ares, Isabel R; Cagide, Eva; Espiña, Begoña; Vilariño, Natalia; Alfonso, Amparo; Vieytes, Mercedes R; Botana, Luis M

2011-03-01

Cytoskeleton is a dynamic structure essential for a wide variety of normal cellular processes, including the maintenance of cell shape and morphology, volume regulation, membrane dynamics and signal transduction. Cytoskeleton is organized into microtubules, actin meshwork and intermediate filaments. Actin has been identified as a major target for destruction during apoptosis and is also important under pathological conditions such as cancers. Several natural compounds actively modulate actin organization by specific signaling cascades being useful tools to study cytoskeleton dynamics. Palytoxin is a large bioactive compound, first isolated from zoanthids, with a complex structure and different analogs such as ostreocin-D or ovatoxin-a. This toxin has been identified as a potent tumor promoter and cytotoxic molecule, which leads to actin filament distortion and triggers cell death or apoptosis. In this review we report the findings on the involvement of palytoxin and analogues modulating the actin cytoskeleton within different cellular models. Copyright © 2010 Elsevier Ltd. All rights reserved.

Visualization of Notch signaling oscillation in cells and tissues.

PubMed

Shimojo, Hiromi; Harima, Yukiko; Kageyama, Ryoichiro

2014-01-01

The Notch signaling effectors Hes1 and Hes7 exhibit oscillatory expression with a period of about 2-3 h during embryogenesis. Hes1 oscillation is important for proliferation and differentiation of neural stem cells, whereas Hes7 oscillation regulates periodic formation of somites. Continuous expression of Hes1 and Hes7 inhibits these developmental processes. Thus, expression dynamics are very important for gene functions, but it is difficult to distinguish between oscillatory and persistent expression by conventional methods such as in situ hybridization and immunostaining. Here, we describe time-lapse imaging methods using destabilized luciferase reporters and a highly sensitive cooled charge-coupled device camera, which can monitor dynamic gene expression. Furthermore, the expression of two genes can be examined simultaneously by a dual reporter system using two-color luciferase reporters. Time-lapse imaging analyses reveal how dynamically gene expression changes in many biological events.

Radioastronomic signal processing cores for the SKA radio telescope

NASA Astrophysics Data System (ADS)

Comorett, G.; Chiarucc, S.; Belli, C.

Modern radio telescopes require the processing of wideband signals, with sample rates from tens of MHz to tens of GHz, and are composed from hundreds up to a million of individual antennas. Digital signal processing of these signals include digital receivers (the digital equivalent of the heterodyne receiver), beamformers, channelizers, spectrometers. FPGAs present the advantage of providing a relatively low power consumption, relative to GPUs or dedicated computers, a wide signal data path, and high interconnectivity. Efficient algorithms have been developed for these applications. Here we will review some of the signal processing cores developed for the SKA telescope. The LFAA beamformer/channelizer architecture is based on an oversampling channelizer, where the channelizer output sampling rate and channel spacing can be set independently. This is useful where an overlap between adjacent channels is required to provide an uniform spectral coverage. The architecture allows for an efficient and distributed channelization scheme, with a final resolution corresponding to a million of spectral channels, minimum leakage and high out-of-band rejection. An optimized filter design procedure is used to provide an equiripple response with a very large number of spectral channels. A wideband digital receiver has been designed in order to select the processed bandwidth of the SKA Mid receiver. The receiver extracts a 2.5 MHz bandwidth form a 14 GHz input bandwidth. The design allows for non-integer ratios between the input and output sampling rates, with a resource usage comparable to that of a conventional decimating digital receiver. Finally, some considerations on quantization of radioastronomic signals are presented. Due to the stochastic nature of the signal, quantization using few data bits is possible. Good accuracies and dynamic range are possible even with 2-3 bits, but the nonlinearity in the correlation process must be corrected in post-processing. With at least 6 bits it is possible to have a very linear response of the instrument, with nonlinear terms below 80 dB, providing the signal amplitude is kept within bounds.

Real Time Data Acquisition and Online Signal Processing for Magnetoencephalography

NASA Astrophysics Data System (ADS)

Rongen, H.; Hadamschek, V.; Schiek, M.

2006-06-01

To establish improved therapies for patients suffering from severe neurological and psychiatric diseases, a demand controlled and desynchronizing brain-pacemaker has been developed with techniques from statistical physics and nonlinear dynamics. To optimize the novel therapeutic approach, brain activity is investigated with a Magnetoencephalography (MEG) system prior to surgery. For this, a real time data acquisition system for a 148 channel MEG and online signal processing for artifact rejection, filtering, cross trial phase resetting analysis and three-dimensional (3-D) reconstruction of the cerebral current sources was developed. The developed PCI bus hardware is based on a FPGA and DSP design, using the benefits from both architectures. The reconstruction and visualization of the 3-D volume data is done by the PC which hosts the real time DAQ and pre-processing board. The framework of the MEG-online system is introduced and the architecture of the real time DAQ board and online reconstruction is described. In addition we show first results with the MEG-Online system for the investigation of dynamic brain activities in relation to external visual stimulation, based on test data sets.

Dynamic ubiquitin signaling in cell cycle regulation

PubMed Central

Gilberto, Samuel

2017-01-01

The cell division cycle is driven by a collection of enzymes that coordinate DNA duplication and separation, ensuring that genomic information is faithfully and perpetually maintained. The activity of the effector proteins that perform and coordinate these biological processes oscillates by regulated expression and/or posttranslational modifications. Ubiquitylation is a cardinal cellular modification and is long known for driving cell cycle transitions. In this review, we emphasize emerging concepts of how ubiquitylation brings the necessary dynamicity and plasticity that underlie the processes of DNA replication and mitosis. New studies, often focusing on the regulation of chromosomal proteins like DNA polymerases or kinetochore kinases, are demonstrating that ubiquitylation is a versatile modification that can be used to fine-tune these cell cycle events, frequently through processes that do not involve proteasomal degradation. Understanding how the increasing variety of identified ubiquitin signals are transduced will allow us to develop a deeper mechanistic perception of how the multiple factors come together to faithfully propagate genomic information. Here, we discuss these and additional conceptual challenges that are currently under study toward understanding how ubiquitin governs cell cycle regulation. PMID:28684425

Dynamic ubiquitin signaling in cell cycle regulation.

PubMed

Gilberto, Samuel; Peter, Matthias

2017-08-07

The cell division cycle is driven by a collection of enzymes that coordinate DNA duplication and separation, ensuring that genomic information is faithfully and perpetually maintained. The activity of the effector proteins that perform and coordinate these biological processes oscillates by regulated expression and/or posttranslational modifications. Ubiquitylation is a cardinal cellular modification and is long known for driving cell cycle transitions. In this review, we emphasize emerging concepts of how ubiquitylation brings the necessary dynamicity and plasticity that underlie the processes of DNA replication and mitosis. New studies, often focusing on the regulation of chromosomal proteins like DNA polymerases or kinetochore kinases, are demonstrating that ubiquitylation is a versatile modification that can be used to fine-tune these cell cycle events, frequently through processes that do not involve proteasomal degradation. Understanding how the increasing variety of identified ubiquitin signals are transduced will allow us to develop a deeper mechanistic perception of how the multiple factors come together to faithfully propagate genomic information. Here, we discuss these and additional conceptual challenges that are currently under study toward understanding how ubiquitin governs cell cycle regulation. © 2017 Gilberto and Peter.

Engineering dynamical control of cell fate switching using synthetic phospho-regulons

PubMed Central

Gordley, Russell M.; Williams, Reid E.; Bashor, Caleb J.; Toettcher, Jared E.; Yan, Shude; Lim, Wendell A.

2016-01-01

Many cells can sense and respond to time-varying stimuli, selectively triggering changes in cell fate only in response to inputs of a particular duration or frequency. A common motif in dynamically controlled cells is a dual-timescale regulatory network: although long-term fate decisions are ultimately controlled by a slow-timescale switch (e.g., gene expression), input signals are first processed by a fast-timescale signaling layer, which is hypothesized to filter what dynamic information is efficiently relayed downstream. Directly testing the design principles of how dual-timescale circuits control dynamic sensing, however, has been challenging, because most synthetic biology methods have focused solely on rewiring transcriptional circuits, which operate at a single slow timescale. Here, we report the development of a modular approach for flexibly engineering phosphorylation circuits using designed phospho-regulon motifs. By then linking rapid phospho-feedback with slower downstream transcription-based bistable switches, we can construct synthetic dual-timescale circuits in yeast in which the triggering dynamics and the end-state properties of the ON state can be selectively tuned. These phospho-regulon tools thus open up the possibility to engineer cells with customized dynamical control. PMID:27821768

Detecting critical state before phase transition of complex systems by hidden Markov model

NASA Astrophysics Data System (ADS)

Liu, Rui; Chen, Pei; Li, Yongjun; Chen, Luonan

Identifying the critical state or pre-transition state just before the occurrence of a phase transition is a challenging task, because the state of the system may show little apparent change before this critical transition during the gradual parameter variations. Such dynamics of phase transition is generally composed of three stages, i.e., before-transition state, pre-transition state, and after-transition state, which can be considered as three different Markov processes. Thus, based on this dynamical feature, we present a novel computational method, i.e., hidden Markov model (HMM), to detect the switching point of the two Markov processes from the before-transition state (a stationary Markov process) to the pre-transition state (a time-varying Markov process), thereby identifying the pre-transition state or early-warning signals of the phase transition. To validate the effectiveness, we apply this method to detect the signals of the imminent phase transitions of complex systems based on the simulated datasets, and further identify the pre-transition states as well as their critical modules for three real datasets, i.e., the acute lung injury triggered by phosgene inhalation, MCF-7 human breast cancer caused by heregulin, and HCV-induced dysplasia and hepatocellular carcinoma.

Single-Molecule Imaging of Cellular Signaling

NASA Astrophysics Data System (ADS)

De Keijzer, Sandra; Snaar-Jagalska, B. Ewa; Spaink, Herman P.; Schmidt, Thomas

Single-molecule microscopy is an emerging technique to understand the function of a protein in the context of its natural environment. In our laboratory this technique has been used to study the dynamics of signal transduction in vivo. A multitude of signal transduction cascades are initiated by interactions between proteins in the plasma membrane. These cascades start by binding a ligand to its receptor, thereby activating downstream signaling pathways which finally result in complex cellular responses. To fully understand these processes it is important to study the initial steps of the signaling cascades. Standard biological assays mostly call for overexpression of the proteins and high concentrations of ligand. This sets severe limits to the interpretation of, for instance, the time-course of the observations, given the large temporal spread caused by the diffusion-limited binding processes. Methods and limitations of single-molecule microscopy for the study of cell signaling are discussed on the example of the chemotactic signaling of the slime-mold Dictyostelium discoideum. Single-molecule studies, as reviewed in this chapter, appear to be one of the essential methodologies for the full spatiotemporal clarification of cellular signaling, one of the ultimate goals in cell biology.

High resolution signal-processing method for extrinsic Fabry-Perot interferometric sensors

NASA Astrophysics Data System (ADS)

Xie, Jiehui; Wang, Fuyin; Pan, Yao; Wang, Junjie; Hu, Zhengliang; Hu, Yongming

2015-03-01

In this paper, a signal-processing method for optical fiber extrinsic Fabry-Perot interferometric sensors is presented. It achieves both high resolution and absolute measurement of the dynamic change of cavity length with low sampling points in wavelength domain. In order to improve the demodulation accuracy, the reflected interference spectrum is cleared by Discrete Wavelet Transform and adjusted by the Hilbert transform. Then the cavity length is interrogated by the cross correlation algorithm. The continuous tests show the resolution of cavity length is only 36.7 pm. Moreover, the corresponding resolution of cavity length is only 1 pm on the low frequency range below 420 Hz, and the corresponding power spectrum shows the possibility of detecting the ultra-low frequency signals based on spectra detection.

Inverse analysis of water profile in starch by non-contact photopyroelectric method

NASA Astrophysics Data System (ADS)

Frandas, A.; Duvaut, T.; Paris, D.

2000-07-01

The photopyroelectric (PPE) method in a non-contact configuration was proposed to study water migration in starch sheets used for biodegradable packaging. A 1-D theoretical model was developed, allowing the study of samples having a water profile characterized by an arbitrary continuous function. An experimental setup was designed or this purpose which included the choice of excitation source, detection of signals, signal and data processing, and cells for conditioning the samples. We report here the development of an inversion procedure allowing for the determination of the parameters that influence the PPE signal. This procedure led to the optimization of experimental conditions in order to identify the parameters related to the water profile in the sample, and to monitor the dynamics of the process.

Frodo proteins: modulators of Wnt signaling in vertebrate development.

PubMed

Brott, Barbara K; Sokol, Sergei Y

2005-09-01

The Frodo/dapper (Frd) proteins are recently discovered signaling adaptors, which functionally and physically interact with Wnt and Nodal signaling pathways during vertebrate development. The Frd1 and Frd2 genes are expressed in dynamic patterns in early embryos, frequently in cells undergoing epithelial-mesenchymal transition. The Frd proteins function in multiple developmental processes, including mesoderm and neural tissue specification, early morphogenetic cell movements, and organogenesis. Loss-of-function studies using morpholino antisense oligonucleotides demonstrate that the Frd proteins regulate Wnt signal transduction in a context-dependent manner and may be involved in Nodal signaling. The identification of Frd-associated factors and cellular targets of the Frd proteins should shed light on the molecular mechanisms underlying Frd functions in embryonic development and in cancer.

NFκB signaling regulates embryonic and adult neurogenesis

PubMed Central

ZHANG, Yonggang; HU, Wenhui

2013-01-01

Both embryonic and adult neurogenesis involves the self-renewal/proliferation, survival, migration and lineage differentiation of neural stem/progenitor cells. Such dynamic process is tightly regulated by intrinsic and extrinsic factors and complex signaling pathways. Misregulated neurogenesis contributes much to a large range of neurodevelopmental defects and neurodegenerative diseases. The signaling of NFκB regulates many genes important in inflammation, immunity, cell survival and neural plasticity. During neurogenesis, NFκB signaling mediates the effect of numerous niche factors such as cytokines, chemokines, growth factors, extracellular matrix molecules, but also crosstalks with other signaling pathways such as Notch, Shh, Wnt/β-catenin. This review summarizes current progress on the NFκB signaling in all aspects of neurogenesis, focusing on the novel role of NFκB signaling in initiating early neural differentiation of neural stem cells and embryonic stem cells. PMID:24324484

Characterizing Speech Intelligibility in Noise After Wide Dynamic Range Compression.

PubMed

Rhebergen, Koenraad S; Maalderink, Thijs H; Dreschler, Wouter A

The effects of nonlinear signal processing on speech intelligibility in noise are difficult to evaluate. Often, the effects are examined by comparing speech intelligibility scores with and without processing measured at fixed signal to noise ratios (SNRs) or by comparing the adaptive measured speech reception thresholds corresponding to 50% intelligibility (SRT50) with and without processing. These outcome measures might not be optimal. Measuring at fixed SNRs can be affected by ceiling or floor effects, because the range of relevant SNRs is not know in advance. The SRT50 is less time consuming, has a fixed performance level (i.e., 50% correct), but the SRT50 could give a limited view, because we hypothesize that the effect of most nonlinear signal processing algorithms at the SRT50 cannot be generalized to other points of the psychometric function. In this article, we tested the value of estimating the entire psychometric function. We studied the effect of wide dynamic range compression (WDRC) on speech intelligibility in stationary, and interrupted speech-shaped noise in normal-hearing subjects, using a fast method-based local linear fitting approach and by two adaptive procedures. The measured performance differences for conditions with and without WDRC for the psychometric functions in stationary noise and interrupted speech-shaped noise show that the effects of WDRC on speech intelligibility are SNR dependent. We conclude that favorable and unfavorable effects of WDRC on speech intelligibility can be missed if the results are presented in terms of SRT50 values only.

Inhomogeneous Point-Processes to Instantaneously Assess Affective Haptic Perception through Heartbeat Dynamics Information

NASA Astrophysics Data System (ADS)

Valenza, G.; Greco, A.; Citi, L.; Bianchi, M.; Barbieri, R.; Scilingo, E. P.

2016-06-01

This study proposes the application of a comprehensive signal processing framework, based on inhomogeneous point-process models of heartbeat dynamics, to instantaneously assess affective haptic perception using electrocardiogram-derived information exclusively. The framework relies on inverse-Gaussian point-processes with Laguerre expansion of the nonlinear Wiener-Volterra kernels, accounting for the long-term information given by the past heartbeat events. Up to cubic-order nonlinearities allow for an instantaneous estimation of the dynamic spectrum and bispectrum of the considered cardiovascular dynamics, as well as for instantaneous measures of complexity, through Lyapunov exponents and entropy. Short-term caress-like stimuli were administered for 4.3-25 seconds on the forearms of 32 healthy volunteers (16 females) through a wearable haptic device, by selectively superimposing two levels of force, 2 N and 6 N, and two levels of velocity, 9.4 mm/s and 65 mm/s. Results demonstrated that our instantaneous linear and nonlinear features were able to finely characterize the affective haptic perception, with a recognition accuracy of 69.79% along the force dimension, and 81.25% along the velocity dimension.

Massive Black-Hole Binary Mergers: Dynamics, Environments & Expected Detections

NASA Astrophysics Data System (ADS)

Kelley, Luke Zoltan

2018-05-01

This thesis studies the populations and dynamics of massive black-hole binaries and their mergers, and explores the implications for electromagnetic and gravitational-wave signals that will be detected in the near future. Massive black-holes (MBH) reside in the centers of galaxies, and when galaxies merge, their MBH interact and often pair together. We base our study on the populations of MBH and galaxies from the `Illustris' cosmological hydrodynamic simulations. The bulk of the binary merger dynamics, however, are unresolved in cosmological simulations. We implement a suite of comprehensive physical models for the merger process, like dynamical friction and gravitational wave emission, which are added in post-processing. Contrary to many previous studies, we find that the most massive binaries with near equal-mass companions are the most efficient at coalescing; though the process still typically takes gigayears.From the data produced by these MBH binary populations and their dynamics, we calculate the expected gravitational wave (GW) signals: both the stochastic, GW background of countless unresolved sources, and the GW foreground of individually resolvable binaries which resound above the noise. Ongoing experiments, called pulsar timing arrays, are sensitive to both of these types of signals. We find that, while the current lack of detections is unsurprising, both the background and foreground will plausibly be detected in the next decade. Unlike previous studies which have predicted the foreground to be significantly harder to detect than the background, we find their typical amplitudes are comparable.With traditional electromagnetic observations, there has also been a dearth of confirmed detections of MBH binary systems. We use our binaries, combined with models of emission from accreting MBH systems, to make predictions for the occurrence rate of systems observable using photometric, periodic-variability surveys. These variables should be detectable in current surveys, and indeed, we expect many candidates recently identified to be true binaries - though a significant fraction are likely false positives. Overall, this thesis finds the science of MBH binaries at an exciting cusp: just before incredible breakthroughs in observations, both electromagnetically and in the new age of gravitational wave astrophysics.

Predicting Essential Components of Signal Transduction Networks: A Dynamic Model of Guard Cell Abscisic Acid Signaling

PubMed Central

Li, Song; Assmann, Sarah M; Albert, Réka

2006-01-01

Plants both lose water and take in carbon dioxide through microscopic stomatal pores, each of which is regulated by a surrounding pair of guard cells. During drought, the plant hormone abscisic acid (ABA) inhibits stomatal opening and promotes stomatal closure, thereby promoting water conservation. Dozens of cellular components have been identified to function in ABA regulation of guard cell volume and thus of stomatal aperture, but a dynamic description is still not available for this complex process. Here we synthesize experimental results into a consistent guard cell signal transduction network for ABA-induced stomatal closure, and develop a dynamic model of this process. Our model captures the regulation of more than 40 identified network components, and accords well with previous experimental results at both the pathway and whole-cell physiological level. By simulating gene disruptions and pharmacological interventions we find that the network is robust against a significant fraction of possible perturbations. Our analysis reveals the novel predictions that the disruption of membrane depolarizability, anion efflux, actin cytoskeleton reorganization, cytosolic pH increase, the phosphatidic acid pathway, or K+ efflux through slowly activating K+ channels at the plasma membrane lead to the strongest reduction in ABA responsiveness. Initial experimental analysis assessing ABA-induced stomatal closure in the presence of cytosolic pH clamp imposed by the weak acid butyrate is consistent with model prediction. Simulations of stomatal response as derived from our model provide an efficient tool for the identification of candidate manipulations that have the best chance of conferring increased drought stress tolerance and for the prioritization of future wet bench analyses. Our method can be readily applied to other biological signaling networks to identify key regulatory components in systems where quantitative information is limited. PMID:16968132

Redox Signaling Mechanisms in Nervous System Development.

PubMed

Olguín-Albuerne, Mauricio; Morán, Julio

2018-06-20

Numerous studies have demonstrated the actions of reactive oxygen species (ROS) as regulators of several physiological processes. In this study, we discuss how redox signaling mechanisms operate to control different processes such as neuronal differentiation, oligodendrocyte differentiation, dendritic growth, and axonal growth. Recent Advances: Redox homeostasis regulates the physiology of neural stem cells (NSCs). Notably, the neuronal differentiation process of NSCs is determined by a change toward oxidative metabolism, increased levels of mitochondrial ROS, increased activity of NADPH oxidase (NOX) enzymes, decreased levels of Nrf2, and differential regulation of different redoxins. Furthermore, during the neuronal maturation processes, NOX and MICAL produce ROS to regulate cytoskeletal dynamics, which control the dendritic and axonal growth, as well as the axonal guidance. The redox homeostasis changes are, in part, attributed to cell metabolism and compartmentalized production of ROS, which is regulated, sensed, and transduced by different molecules such as thioredoxins, glutaredoxins, peroxiredoxins, and nucleoredoxin to control different signaling pathways in different subcellular regions. The study of how these elements cooperatively act is essential for the understanding of nervous system development, as well as the application of regenerative therapies that recapitulate these processes. The information about these topics in the last two decades leads us to the conclusion that the role of ROS signaling in development of the nervous system is more important than it was previously believed and makes clear the importance of exploring in more detail the mechanisms of redox signaling. Antioxid. Redox Signal. 28, 1603-1625.

Some dynamics of signaling games.

PubMed

Huttegger, Simon; Skyrms, Brian; Tarrès, Pierre; Wagner, Elliott

2014-07-22

Information transfer is a basic feature of life that includes signaling within and between organisms. Owing to its interactive nature, signaling can be investigated by using game theory. Game theoretic models of signaling have a long tradition in biology, economics, and philosophy. For a long time the analyses of these games has mostly relied on using static equilibrium concepts such as Pareto optimal Nash equilibria or evolutionarily stable strategies. More recently signaling games of various types have been investigated with the help of game dynamics, which includes dynamical models of evolution and individual learning. A dynamical analysis leads to more nuanced conclusions as to the outcomes of signaling interactions. Here we explore different kinds of signaling games that range from interactions without conflicts of interest between the players to interactions where their interests are seriously misaligned. We consider these games within the context of evolutionary dynamics (both infinite and finite population models) and learning dynamics (reinforcement learning). Some results are specific features of a particular dynamical model, whereas others turn out to be quite robust across different models. This suggests that there are certain qualitative aspects that are common to many real-world signaling interactions.

Some dynamics of signaling games

PubMed Central

Huttegger, Simon; Skyrms, Brian; Tarrès, Pierre; Wagner, Elliott

2014-01-01

Information transfer is a basic feature of life that includes signaling within and between organisms. Owing to its interactive nature, signaling can be investigated by using game theory. Game theoretic models of signaling have a long tradition in biology, economics, and philosophy. For a long time the analyses of these games has mostly relied on using static equilibrium concepts such as Pareto optimal Nash equilibria or evolutionarily stable strategies. More recently signaling games of various types have been investigated with the help of game dynamics, which includes dynamical models of evolution and individual learning. A dynamical analysis leads to more nuanced conclusions as to the outcomes of signaling interactions. Here we explore different kinds of signaling games that range from interactions without conflicts of interest between the players to interactions where their interests are seriously misaligned. We consider these games within the context of evolutionary dynamics (both infinite and finite population models) and learning dynamics (reinforcement learning). Some results are specific features of a particular dynamical model, whereas others turn out to be quite robust across different models. This suggests that there are certain qualitative aspects that are common to many real-world signaling interactions. PMID:25024209

Adaptive electric potential sensors for smart signal acquisition and processing

NASA Astrophysics Data System (ADS)

Prance, R. J.; Beardsmore-Rust, S.; Prance, H.; Harland, C. J.; Stiffell, P. B.

2007-07-01

Current applications of the Electric Potential Sensor operate in a strongly (capacitively) coupled limit, with the sensor physically close to or touching the source. This mode of operation screens the sensor effectively from the majority of external noise. To date however the full capability of these sensors operating in a remote mode has not been realised outside of a screened environment (Faraday cage). This paper describes the results of preliminary work in tailoring the response of the sensors to particular signals and so reject background noise, thereby enhancing both the dynamic range and signal to noise ratio significantly.

Calcium ions in aqueous solutions: Accurate force field description aided by ab initio molecular dynamics and neutron scattering

NASA Astrophysics Data System (ADS)

Martinek, Tomas; Duboué-Dijon, Elise; Timr, Štěpán; Mason, Philip E.; Baxová, Katarina; Fischer, Henry E.; Schmidt, Burkhard; Pluhařová, Eva; Jungwirth, Pavel

2018-06-01

We present a combination of force field and ab initio molecular dynamics simulations together with neutron scattering experiments with isotopic substitution that aim at characterizing ion hydration and pairing in aqueous calcium chloride and formate/acetate solutions. Benchmarking against neutron scattering data on concentrated solutions together with ion pairing free energy profiles from ab initio molecular dynamics allows us to develop an accurate calcium force field which accounts in a mean-field way for electronic polarization effects via charge rescaling. This refined calcium parameterization is directly usable for standard molecular dynamics simulations of processes involving this key biological signaling ion.

Dynamics and heterogeneity of a fate determinant during transition towards cell differentiation

DOE PAGES

Pelaez, Nicolas; Gavalda-Miralles, Arnau; Wang, Bao; ...

2015-11-19

Yan is an ETS-domain transcription factor responsible for maintaining Drosophila eye cells in a multipotent state. Yan is at the core of a regulatory network that determines the time and place in which cells transit from multipotency to one of several differentiated lineages. Using a fluorescent reporter for Yan expression, we observed a biphasic distribution of Yan in multipotent cells, with a rapid inductive phase and slow decay phase. Transitions to various differentiated states occurred over the course of this dynamic process, suggesting that Yan expression level does not strongly determine cell potential. Consistent with this conclusion, perturbing Yan expressionmore » by varying gene dosage had no effect on cell fate transitions. However, we observed that as cells transited to differentiation, Yan expression became highly heterogeneous and this heterogeneity was transient. Signals received via the EGF Receptor were necessary for the transience in Yan noise since genetic loss caused sustained noise. As a result, since these signals are essential for eye cells to differentiate, we suggest that dynamic heterogeneity of Yan is a necessary element of the transition process, and cell states are stabilized through noise reduction.« less

Extracellular Electrophysiological Measurements of Cooperative Signals in Astrocytes Populations

PubMed Central

Mestre, Ana L. G.; Inácio, Pedro M. C.; Elamine, Youssef; Asgarifar, Sanaz; Lourenço, Ana S.; Cristiano, Maria L. S.; Aguiar, Paulo; Medeiros, Maria C. R.; Araújo, Inês M.; Ventura, João; Gomes, Henrique L.

2017-01-01

Astrocytes are neuroglial cells that exhibit functional electrical properties sensitive to neuronal activity and capable of modulating neurotransmission. Thus, electrophysiological recordings of astroglial activity are very attractive to study the dynamics of glial signaling. This contribution reports on the use of ultra-sensitive planar electrodes combined with low noise and low frequency amplifiers that enable the detection of extracellular signals produced by primary cultures of astrocytes isolated from mouse cerebral cortex. Recorded activity is characterized by spontaneous bursts comprised of discrete signals with pronounced changes on the signal rate and amplitude. Weak and sporadic signals become synchronized and evolve with time to higher amplitude signals with a quasi-periodic behavior, revealing a cooperative signaling process. The methodology presented herewith enables the study of ionic fluctuations of population of cells, complementing the single cells observation by calcium imaging as well as by patch-clamp techniques. PMID:29109679

Extracellular Electrophysiological Measurements of Cooperative Signals in Astrocytes Populations.

PubMed

Mestre, Ana L G; Inácio, Pedro M C; Elamine, Youssef; Asgarifar, Sanaz; Lourenço, Ana S; Cristiano, Maria L S; Aguiar, Paulo; Medeiros, Maria C R; Araújo, Inês M; Ventura, João; Gomes, Henrique L

2017-01-01

Astrocytes are neuroglial cells that exhibit functional electrical properties sensitive to neuronal activity and capable of modulating neurotransmission. Thus, electrophysiological recordings of astroglial activity are very attractive to study the dynamics of glial signaling. This contribution reports on the use of ultra-sensitive planar electrodes combined with low noise and low frequency amplifiers that enable the detection of extracellular signals produced by primary cultures of astrocytes isolated from mouse cerebral cortex. Recorded activity is characterized by spontaneous bursts comprised of discrete signals with pronounced changes on the signal rate and amplitude. Weak and sporadic signals become synchronized and evolve with time to higher amplitude signals with a quasi-periodic behavior, revealing a cooperative signaling process. The methodology presented herewith enables the study of ionic fluctuations of population of cells, complementing the single cells observation by calcium imaging as well as by patch-clamp techniques.

Logical Modeling and Dynamical Analysis of Cellular Networks

PubMed Central

Abou-Jaoudé, Wassim; Traynard, Pauline; Monteiro, Pedro T.; Saez-Rodriguez, Julio; Helikar, Tomáš; Thieffry, Denis; Chaouiya, Claudine

2016-01-01

The logical (or logic) formalism is increasingly used to model regulatory and signaling networks. Complementing these applications, several groups contributed various methods and tools to support the definition and analysis of logical models. After an introduction to the logical modeling framework and to several of its variants, we review here a number of recent methodological advances to ease the analysis of large and intricate networks. In particular, we survey approaches to determine model attractors and their reachability properties, to assess the dynamical impact of variations of external signals, and to consistently reduce large models. To illustrate these developments, we further consider several published logical models for two important biological processes, namely the differentiation of T helper cells and the control of mammalian cell cycle. PMID:27303434

F-BAR family proteins, emerging regulators for cell membrane dynamic changes-from structure to human diseases.

PubMed

Liu, Suxuan; Xiong, Xinyu; Zhao, Xianxian; Yang, Xiaofeng; Wang, Hong

2015-05-09

Eukaryotic cell membrane dynamics change in curvature during physiological and pathological processes. In the past ten years, a novel protein family, Fes/CIP4 homology-Bin/Amphiphysin/Rvs (F-BAR) domain proteins, has been identified to be the most important coordinators in membrane curvature regulation. The F-BAR domain family is a member of the Bin/Amphiphysin/Rvs (BAR) domain superfamily that is associated with dynamic changes in cell membrane. However, the molecular basis in membrane structure regulation and the biological functions of F-BAR protein are unclear. The pathophysiological role of F-BAR protein is unknown. This review summarizes the current understanding of structure and function in the BAR domain superfamily, classifies F-BAR family proteins into nine subfamilies based on domain structure, and characterizes F-BAR protein structure, domain interaction, and functional relevance. In general, F-BAR protein binds to cell membrane via F-BAR domain association with membrane phospholipids and initiates membrane curvature and scission via Src homology-3 (SH3) domain interaction with its partner proteins. This process causes membrane dynamic changes and leads to seven important cellular biological functions, which include endocytosis, phagocytosis, filopodium, lamellipodium, cytokinesis, adhesion, and podosome formation, via distinct signaling pathways determined by specific domain-binding partners. These cellular functions play important roles in many physiological and pathophysiological processes. We further summarize F-BAR protein expression and mutation changes observed in various diseases and developmental disorders. Considering the structure feature and functional implication of F-BAR proteins, we anticipate that F-BAR proteins modulate physiological and pathophysiological processes via transferring extracellular materials, regulating cell trafficking and mobility, presenting antigens, mediating extracellular matrix degradation, and transmitting signaling for cell proliferation.

Using Seismic Signals to Forecast Volcanic Processes

NASA Astrophysics Data System (ADS)

Salvage, R.; Neuberg, J. W.

2012-04-01

Understanding seismic signals generated during volcanic unrest have the ability to allow scientists to more accurately predict and understand active volcanoes since they are intrinsically linked to rock failure at depth (Voight, 1988). In particular, low frequency long period signals (LP events) have been related to the movement of fluid and the brittle failure of magma at depth due to high strain rates (Hammer and Neuberg, 2009). This fundamentally relates to surface processes. However, there is currently no physical quantitative model for determining the likelihood of an eruption following precursory seismic signals, or the timing or type of eruption that will ensue (Benson et al., 2010). Since the beginning of its current eruptive phase, accelerating LP swarms (< 10 events per hour) have been a common feature at Soufriere Hills volcano, Montserrat prior to surface expressions such as dome collapse or eruptions (Miller et al., 1998). The dynamical behaviour of such swarms can be related to accelerated magma ascent rates since the seismicity is thought to be a consequence of magma deformation as it rises to the surface. In particular, acceleration rates can be successfully used in collaboration with the inverse material failure law; a linear relationship against time (Voight, 1988); in the accurate prediction of volcanic eruption timings. Currently, this has only been investigated for retrospective events (Hammer and Neuberg, 2009). The identification of LP swarms on Montserrat and analysis of their dynamical characteristics allows a better understanding of the nature of the seismic signals themselves, as well as their relationship to surface processes such as magma extrusion rates. Acceleration and deceleration rates of seismic swarms provide insights into the plumbing system of the volcano at depth. The application of the material failure law to multiple LP swarms of data allows a critical evaluation of the accuracy of the method which further refines current understanding of the relationship between seismic signals and volcanic eruptions. It is hoped that such analysis will assist the development of real time forecasting models.

Structural dynamics of the cell nucleus

PubMed Central

Wiegert, Simon; Bading, Hilmar

2011-01-01

Neuronal morphology plays an essential role in signal processing in the brain. Individual neurons can undergo use-dependent changes in their shape and connectivity, which affects how intracellular processes are regulated and how signals are transferred from one cell to another in a neuronal network. Calcium is one of the most important intracellular second messengers regulating cellular morphologies and functions. In neurons, intracellular calcium levels are controlled by ion channels in the plasma membrane such as NMDA receptors (NMDARs), voltage-gated calcium channels (VGCCs) and certain α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) as well as by calcium exchange pathways between the cytosol and internal calcium stores including the endoplasmic reticulum and mitochondria. Synaptic activity and the subsequent opening of ligand and/or voltage-gated calcium channels can initiate cytosolic calcium transients which propagate towards the cell soma and enter the nucleus via its nuclear pore complexes (NPCs) embedded in the nuclear envelope. We recently described the discovery that in hippocampal neurons the morphology of the nucleus affects the calcium dynamics within the nucleus. Here we propose that nuclear infoldings determine whether a nucleus functions as an integrator or detector of oscillating calcium signals. We outline possible ties between nuclear mophology and transcriptional activity and discuss the importance of extending the approach to whole cell calcium signal modeling in order to understand synapse-to-nucleus communication in healthy and dysfunctional neurons. PMID:21738832

Kalman Orbit Optimized Loop Tracking

NASA Technical Reports Server (NTRS)

Young, Lawrence E.; Meehan, Thomas K.

2011-01-01

Under certain conditions of low signal power and/or high noise, there is insufficient signal to noise ratio (SNR) to close tracking loops with individual signals on orbiting Global Navigation Satellite System (GNSS) receivers. In addition, the processing power available from flight computers is not great enough to implement a conventional ultra-tight coupling tracking loop. This work provides a method to track GNSS signals at very low SNR without the penalty of requiring very high processor throughput to calculate the loop parameters. The Kalman Orbit-Optimized Loop (KOOL) tracking approach constitutes a filter with a dynamic model and using the aggregate of information from all tracked GNSS signals to close the tracking loop for each signal. For applications where there is not a good dynamic model, such as very low orbits where atmospheric drag models may not be adequate to achieve the required accuracy, aiding from an IMU (inertial measurement unit) or other sensor will be added. The KOOL approach is based on research JPL has done to allow signal recovery from weak and scintillating signals observed during the use of GPS signals for limb sounding of the Earth s atmosphere. That approach uses the onboard PVT (position, velocity, time) solution to generate predictions for the range, range rate, and acceleration of the low-SNR signal. The low- SNR signal data are captured by a directed open loop. KOOL builds on the previous open loop tracking by including feedback and observable generation from the weak-signal channels so that the MSR receiver will continue to track and provide PVT, range, and Doppler data, even when all channels have low SNR.

Agent-based modeling of endotoxin-induced acute inflammatory response in human blood leukocytes.

PubMed

Dong, Xu; Foteinou, Panagiota T; Calvano, Steven E; Lowry, Stephen F; Androulakis, Ioannis P

2010-02-18

Inflammation is a highly complex biological response evoked by many stimuli. A persistent challenge in modeling this dynamic process has been the (nonlinear) nature of the response that precludes the single-variable assumption. Systems-based approaches offer a promising possibility for understanding inflammation in its homeostatic context. In order to study the underlying complexity of the acute inflammatory response, an agent-based framework is developed that models the emerging host response as the outcome of orchestrated interactions associated with intricate signaling cascades and intercellular immune system interactions. An agent-based modeling (ABM) framework is proposed to study the nonlinear dynamics of acute human inflammation. The model is implemented using NetLogo software. Interacting agents involve either inflammation-specific molecules or cells essential for the propagation of the inflammatory reaction across the system. Spatial orientation of molecule interactions involved in signaling cascades coupled with the cellular heterogeneity are further taken into account. The proposed in silico model is evaluated through its ability to successfully reproduce a self-limited inflammatory response as well as a series of scenarios indicative of the nonlinear dynamics of the response. Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades. The ABM framework developed in this study provides insight on the stochastic interactions of the mediators involved in the propagation of endotoxin signaling at the cellular response level. The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components. The hypothetical scenarios explored in this study would potentially improve our understanding of how manipulating the behavior of the molecular species could manifest into emergent behavior of the overall system.

Dynamics of the Wulong Landslide Revealed by Broadband Seismic Records

NASA Astrophysics Data System (ADS)

Huang, X.; Dan, Y.

2016-12-01

Long-period seismic signals are frequently used to trace the dynamic process of large scale landslides. The catastrophic WuLong landslide occurred at 14:51 on 5 June 2009 (Beijing time, UTC+8) in Wulong Prefecture, Southwest China. The topography in landslide area varies dramatically, enhancing the complexity in its movement characteristics. The mass started sliding northward on the upper part of the cliff located upon the west slope of the Tiejianggou gully, and shifted its movement direction to northeastward after being blocked by stable bedrock in front, leaving a scratch zone. The sliding mass then moved downward along the west slope of the gully until it collided with the east slope, and broke up into small pieces after the collision, forming a debris flow along the gully. We use long-period seismic signals extracted from eight broadband seismic stations within 250 km of the landslide to estimate its source time functions. Combining with topographic surveys done before and after the event, we can also resolve kinematic parameters of sliding mass, i.e. velocities, displacements and trajectories, perfectly characterizing its movement features. The runout trajectory deduced from source time functions is consistent with the sliding path, including two direction changing processes, corresponding to scratching the western bedrock and collision with the east slope respectively. Topographic variations can be reflected from estimated velocities. The maximum velocity of the sliding mass reaches 35 m/s before the collision with the east slope of the Tiejianggou gully, resulting from the height difference between the source zone and the deposition zone. What is important is that dynamics of scratching and collision can be characterized by source time functions. Our results confirm that long-period seismic signals are sufficient to characterize dynamics and kinematics of large scale landslides which occur in a region with complex topography.

The Relationship Between Intensity Coding and Binaural Sensitivity in Adults With Cochlear Implants

PubMed Central

Todd, Ann E.; Goupell, Matthew J.; Litovsky, Ruth Y.

2016-01-01

Objectives Many bilateral cochlear implant users show sensitivity to binaural information when stimulation is provided using a pair of synchronized electrodes. However, there is large variability in binaural sensitivity between and within participants across stimulation sites in the cochlea. It was hypothesized that within-participant variability in binaural sensitivity is in part affected by limitations and characteristics of the auditory periphery which may be reflected by monaural hearing performance. The objective of this study was to examine the relationship between monaural and binaural hearing performance within participants with bilateral cochlear implants. Design Binaural measures included dichotic signal detection and interaural time difference discrimination thresholds. Diotic signal detection thresholds were also measured. Monaural measures included dynamic range and amplitude modulation detection. In addition, loudness growth was compared between ears. Measures were made at three stimulation sites per listener. Results Greater binaural sensitivity was found with larger dynamic ranges. Poorer interaural time difference discrimination was found with larger difference between comfortable levels of the two ears. In addition, poorer diotic signal detection thresholds were found with larger differences between the dynamic ranges of the two ears. No relationship was found between amplitude modulation detection thresholds or symmetry of loudness growth and the binaural measures. Conclusions The results suggest that some of the variability in binaural hearing performance within listeners across stimulation sites can be explained by factors non-specific to binaural processing. The results are consistent with the idea that dynamic range and comfortable levels relate to peripheral neural survival and the width of the excitation pattern which could affect the fidelity with which central binaural nuclei process bilateral inputs. PMID:27787393

Rhodopsin photoactivation dynamics revealed by quasi-elastic neutron scattering

DOE PAGES

Bhowmik, Debsindhu; Shrestha, Utsab; Perera, Suchithranga M.d.c.; ...

2015-01-27

Rhodopsin is a G-protein-coupled receptor (GPCR) responsible for vision under dim light conditions. During rhodopsin photoactivation, the chromophore retinal undergoes cis-trans isomerization, and subsequently dissociates from the protein yielding the opsin apoprotein [1]. What are the changes in protein dynamics that occur during the rhodopsin photoactivation process? Here, we studied the microscopic dynamics of the dark-state rhodopsin and the ligand-free opsin using quasi-elastic neutron scattering (QENS). The QENS technique tracks the individual hydrogen atom motions in the protein molecules, because the neutron scattering cross-section of hydrogen is much higher than other atoms [2-4]. We used protein (rhodopsin/opsin) samples with CHAPSmore » detergent hydrated with heavy water. The solvent signal is suppressed due to the heavy water, so that only the signals from proteins and detergents are detected. The activation of proteins is confirmed at low temperatures up to 300 K by the mean-square displacement (MSD) analysis. Our QENS experiments conducted at temperatures ranging from 220 K to 300 K clearly indicate that the protein dynamic behavior increases with temperature. The relaxation time for the ligand-bound protein rhodopsin was longer compared to opsin, which can be correlated with the photoactivation. Moreover, the protein dynamics are orders of magnitude slower than the accompanying CHAPS detergent, which forms a band around the protein molecule in the micelle. Unlike the protein, the CHAPS detergent manifests localized motions that are the same as in the bulk empty micelles. Furthermore QENS provides unique understanding of the key dynamics involved in the activation of the GPCR involved in the visual process.« less

Upgrading a high-throughput spectrometer for high-frequency (<400 kHz) measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nishizawa, T., E-mail: nishizawa@wisc.edu; Nornberg, M. D.; Den Hartog, D. J.

2016-11-15

The upgraded spectrometer used for charge exchange recombination spectroscopy on the Madison Symmetric Torus resolves emission fluctuations up to 400 kHz. The transimpedance amplifier’s cutoff frequency was increased based upon simulations comparing the change in the measured photon counts for time-dynamic signals. We modeled each signal-processing stage of the diagnostic and scanned the filtering frequency to quantify the uncertainty in the photon counting rate. This modeling showed that uncertainties can be calculated based on assuming each amplification stage is a Poisson process and by calibrating the photon counting rate with a DC light source to address additional variation.

Upgrading a high-throughput spectrometer for high-frequency (<400 kHz) measurements

NASA Astrophysics Data System (ADS)

Nishizawa, T.; Nornberg, M. D.; Den Hartog, D. J.; Craig, D.

2016-11-01

The upgraded spectrometer used for charge exchange recombination spectroscopy on the Madison Symmetric Torus resolves emission fluctuations up to 400 kHz. The transimpedance amplifier's cutoff frequency was increased based upon simulations comparing the change in the measured photon counts for time-dynamic signals. We modeled each signal-processing stage of the diagnostic and scanned the filtering frequency to quantify the uncertainty in the photon counting rate. This modeling showed that uncertainties can be calculated based on assuming each amplification stage is a Poisson process and by calibrating the photon counting rate with a DC light source to address additional variation.

Discrete dynamic modeling of cellular signaling networks.

PubMed

Albert, Réka; Wang, Rui-Sheng

2009-01-01

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

Dynamics of NAD-metabolism: everything but constant.

PubMed

Opitz, Christiane A; Heiland, Ines

2015-12-01

NAD, as well as its phosphorylated form, NADP, are best known as electron carriers and co-substrates of various redox reactions. As such they participate in approximately one quarter of all reactions listed in the reaction database KEGG. In metabolic pathway analysis, the total amount of NAD is usually assumed to be constant. That means that changes in the redox state might be considered, but concentration changes of the NAD moiety are usually neglected. However, a growing number of NAD-consuming reactions have been identified, showing that this assumption does not hold true in general. NAD-consuming reactions are common characteristics of NAD(+)-dependent signalling pathways and include mono- and poly-ADP-ribosylation of proteins, NAD(+)-dependent deacetylation by sirtuins and the formation of messenger molecules such as cyclic ADP-ribose (cADPR) and nicotinic acid (NA)-ADP (NAADP). NAD-consuming reactions are thus involved in major signalling and gene regulation pathways such as DNA-repair or regulation of enzymes central in metabolism. All known NAD(+)-dependent signalling processes include the release of nicotinamide (Nam). Thus cellular NAD pools need to be constantly replenished, mostly by recycling Nam to NAD(+). This process is, among others, regulated by the circadian clock, causing complex dynamic changes in NAD concentration. As disturbances in NAD homoeostasis are associated with a large number of diseases ranging from cancer to diabetes, it is important to better understand the dynamics of NAD metabolism to develop efficient pharmacological invention strategies to target this pathway. © 2015 Authors; published by Portland Press Limited.

Initial tsunami signals in the lithosphere-ocean-atmosphere medium

NASA Astrophysics Data System (ADS)

Novik, O.; Ershov, S.; Mikhaylovskaya, I.

Satellite and ground based instrumentations for monitoring of dynamical processes under the Ocean floor 3 4 of the Earth surface and resulting catastrophic events should be adapted to unknown physical nature of transformation of the oceanic lithosphere s energy of seismogenic deformations into measurable acoustic electromagnetic EM temperature and hydrodynamic tsunami waves To describe the initial up to a tsunami wave far from a shore stage of this transformation and to understand mechanism of EM signals arising above the Ocean during seismic activation we formulate a nonlinear mathematical model of seismo-hydro-EM geophysical field interaction in the lithosphere-Ocean-atmosphere medium from the upper mantle under the Ocean up to the ionosphere domain D The model is based on the theory of elasticity electrodynamics fluid dynamics thermodynamics and geophysical data On the basis of this model and its mathematical investigation we calculate generation and propagation of different see above waves in the basin of a model marginal sea the data on the central part of the Sea of Japan were used At the moment t 0 the dynamic interaction process is supposed to be caused by weak may be precursory sub-vertical elastic displacements with the amplitude duration and main frequency of the order of a few cm sec and tenth of Hz respectively at the depth of 37 km under the sea level i e in the upper mantle Other seismic excitations may be considered as well The lithosphere EM signal is generated in the upper mantle conductive

Encoding frequency contrast in primate auditory cortex

PubMed Central

Scott, Brian H.; Semple, Malcolm N.

2014-01-01

Changes in amplitude and frequency jointly determine much of the communicative significance of complex acoustic signals, including human speech. We have previously described responses of neurons in the core auditory cortex of awake rhesus macaques to sinusoidal amplitude modulation (SAM) signals. Here we report a complementary study of sinusoidal frequency modulation (SFM) in the same neurons. Responses to SFM were analogous to SAM responses in that changes in multiple parameters defining SFM stimuli (e.g., modulation frequency, modulation depth, carrier frequency) were robustly encoded in the temporal dynamics of the spike trains. For example, changes in the carrier frequency produced highly reproducible changes in shapes of the modulation period histogram, consistent with the notion that the instantaneous probability of discharge mirrors the moment-by-moment spectrum at low modulation rates. The upper limit for phase locking was similar across SAM and SFM within neurons, suggesting shared biophysical constraints on temporal processing. Using spike train classification methods, we found that neural thresholds for modulation depth discrimination are typically far lower than would be predicted from frequency tuning to static tones. This “dynamic hyperacuity” suggests a substantial central enhancement of the neural representation of frequency changes relative to the auditory periphery. Spike timing information was superior to average rate information when discriminating among SFM signals, and even when discriminating among static tones varying in frequency. This finding held even when differences in total spike count across stimuli were normalized, indicating both the primacy and generality of temporal response dynamics in cortical auditory processing. PMID:24598525

Bacteriorhodopsin films for optical signal processing and data storage

NASA Technical Reports Server (NTRS)

Walkup, John F. (Principal Investigator); Mehrl, David J. (Principal Investigator)

1996-01-01

This report summarizes the research results obtained on NASA Ames Grant NAG 2-878 entitled 'Investigations of Bacteriorhodopsin Films for Optical Signal Processing and Data Storage.' Specifically we performed research, at Texas Tech University, on applications of Bacteriorhodopisin film to both (1) dynamic spatial filtering and (2) holographic data storage. In addition, measurements of the noise properties of an acousto-optical matrix-vestor multiplier built for NASA Ames by Photonic Systems Inc. were performed at NASA Ames' Photonics Laboratory. This research resulted in two papers presented at major optical data processing conferences and a journal paper which is to appear in APPLIED OPTICS. A new proposal for additional BR research has recently been submitted to NASA Ames Research Center.

Impulse processing: A dynamical systems model of incremental eye movements in the visual world paradigm

PubMed Central

Kukona, Anuenue; Tabor, Whitney

2011-01-01

The visual world paradigm presents listeners with a challenging problem: they must integrate two disparate signals, the spoken language and the visual context, in support of action (e.g., complex movements of the eyes across a scene). We present Impulse Processing, a dynamical systems approach to incremental eye movements in the visual world that suggests a framework for integrating language, vision, and action generally. Our approach assumes that impulses driven by the language and the visual context impinge minutely on a dynamical landscape of attractors corresponding to the potential eye-movement behaviors of the system. We test three unique predictions of our approach in an empirical study in the visual world paradigm, and describe an implementation in an artificial neural network. We discuss the Impulse Processing framework in relation to other models of the visual world paradigm. PMID:21609355

Noise analysis of the seismic system employed in the northern and southern California seismic nets

USGS Publications Warehouse

Eaton, J.P.

1984-01-01

The seismic networks have been designed and operated to support recording on Develocorders (less than 40db dynamic range) and analog magnetic tape (about 50 db dynamic range). The principal analysis of the records has been based on Develocorder films; and background earth noise levels have been adjusted to be about 1 to 2 mm p-p on the film readers. Since the traces are separated by only 10 to 12 mm on the reader screen, they become hopelessly tangled when signal amplitudes on several adjacent traces exceed 10 to 20 mm p-p. Thus, the background noise level is hardly more than 20 db below the level of largest readable signals. The situation is somewhat better on tape playbacks, but the high level of background noise set to accomodate processing from film records effectively limits the range of maximum-signal to background-earth-noise on high gain channels to a little more than 30 db. Introduction of the PDP 11/44 seismic data acquisition system has increased the potential dynamic range of recorded network signals to more than 60 db. To make use of this increased dynamic range we must evaluate the characteristics and performance of the seismic system. In particular, we must determine whether the electronic noise in the system is or can be made sufficiently low so that background earth noise levels can be lowered significantly to take advantage of the increased dynamic range of the digital recording system. To come to grips with the complex problem of system noise, we have carried out a number of measurements and experiments to evaluate critical components of the system as well as to determine the noise characteristics of the system as a whole.

Nonlinear Gap Junctions Enable Long-Distance Propagation of Pulsating Calcium Waves in Astrocyte Networks

PubMed Central

Goldberg, Mati; De Pittà, Maurizio; Volman, Vladislav; Berry, Hugues; Ben-Jacob, Eshel

2010-01-01

A new paradigm has recently emerged in brain science whereby communications between glial cells and neuron-glia interactions should be considered together with neurons and their networks to understand higher brain functions. In particular, astrocytes, the main type of glial cells in the cortex, have been shown to communicate with neurons and with each other. They are thought to form a gap-junction-coupled syncytium supporting cell-cell communication via propagating Ca2+ waves. An identified mode of propagation is based on cytoplasm-to-cytoplasm transport of inositol trisphosphate (IP3) through gap junctions that locally trigger Ca2+ pulses via IP3-dependent Ca2+-induced Ca2+ release. It is, however, currently unknown whether this intracellular route is able to support the propagation of long-distance regenerative Ca2+ waves or is restricted to short-distance signaling. Furthermore, the influence of the intracellular signaling dynamics on intercellular propagation remains to be understood. In this work, we propose a model of the gap-junctional route for intercellular Ca2+ wave propagation in astrocytes. Our model yields two major predictions. First, we show that long-distance regenerative signaling requires nonlinear coupling in the gap junctions. Second, we show that even with nonlinear gap junctions, long-distance regenerative signaling is favored when the internal Ca2+ dynamics implements frequency modulation-encoding oscillations with pulsating dynamics, while amplitude modulation-encoding dynamics tends to restrict the propagation range. As a result, spatially heterogeneous molecular properties and/or weak couplings are shown to give rise to rich spatiotemporal dynamics that support complex propagation behaviors. These results shed new light on the mechanisms implicated in the propagation of Ca2+ waves across astrocytes and the precise conditions under which glial cells may participate in information processing in the brain. PMID:20865153

Cytoskeletal Reorganization Drives Mesenchymal Condensation and Regulates Downstream Molecular Signaling.

PubMed

Ray, Poulomi; Chapman, Susan C

2015-01-01

Skeletal condensation occurs when specified mesenchyme cells self-organize over several days to form a distinctive cartilage template. Here, we determine how and when specified mesenchyme cells integrate mechanical and molecular information from their environment, forming cartilage condensations in the pharyngeal arches of chick embryos. By disrupting cytoskeletal reorganization, we demonstrate that dynamic cell shape changes drive condensation and modulate the response of the condensing cells to Fibroblast Growth Factor (FGF), Bone Morphogenetic Protein (BMP) and Transforming Growth Factor beta (TGF-β) signaling pathways. Rho Kinase (ROCK)-driven actomyosin contractions and Myosin II-generated differential cell cortex tension regulate these cell shape changes. Disruption of the condensation process inhibits the differentiation of the mesenchyme cells into chondrocytes, demonstrating that condensation regulates the fate of the mesenchyme cells. We also find that dorsal and ventral condensations undergo distinct cell shape changes. BMP signaling is instructive for dorsal condensation-specific cell shape changes. Moreover, condensations exhibit ventral characteristics in the absence of BMP signaling, suggesting that in the pharyngeal arches ventral morphology is the ground pattern. Overall, this study characterizes the interplay between cytoskeletal dynamics and molecular signaling in a self-organizing system during tissue morphogenesis.

Cytoskeletal Reorganization Drives Mesenchymal Condensation and Regulates Downstream Molecular Signaling

PubMed Central

Ray, Poulomi; Chapman, Susan C.

2015-01-01

Skeletal condensation occurs when specified mesenchyme cells self-organize over several days to form a distinctive cartilage template. Here, we determine how and when specified mesenchyme cells integrate mechanical and molecular information from their environment, forming cartilage condensations in the pharyngeal arches of chick embryos. By disrupting cytoskeletal reorganization, we demonstrate that dynamic cell shape changes drive condensation and modulate the response of the condensing cells to Fibroblast Growth Factor (FGF), Bone Morphogenetic Protein (BMP) and Transforming Growth Factor beta (TGF-β) signaling pathways. Rho Kinase (ROCK)-driven actomyosin contractions and Myosin II-generated differential cell cortex tension regulate these cell shape changes. Disruption of the condensation process inhibits the differentiation of the mesenchyme cells into chondrocytes, demonstrating that condensation regulates the fate of the mesenchyme cells. We also find that dorsal and ventral condensations undergo distinct cell shape changes. BMP signaling is instructive for dorsal condensation-specific cell shape changes. Moreover, condensations exhibit ventral characteristics in the absence of BMP signaling, suggesting that in the pharyngeal arches ventral morphology is the ground pattern. Overall, this study characterizes the interplay between cytoskeletal dynamics and molecular signaling in a self-organizing system during tissue morphogenesis. PMID:26237312

Microwave signal processing with photorefractive dynamic holography

NASA Astrophysics Data System (ADS)

Fotheringham, Edeline B.

Have you ever found yourself listening to the music playing from the closest stereo rather than to the bromidic (uninspiring) person speaking to you? Your ears receive information from two sources but your brain listens to only one. What if your cell phone could distinguish among signals sharing the same bandwidth too? There would be no "full" channels to stop you from placing or receiving a call. This thesis presents a nonlinear optical circuit capable of distinguishing uncorrelated signals that have overlapping temporal bandwidths. This so called autotuning filter is the size of a U.S. quarter dollar and requires less than 3 mW of optical power to operate. It is basically an oscillator in which the losses are compensated with dynamic holographic gain. The combination of two photorefractive crystals in the resonator governs the filter's winner-take-all dynamics through signal-competition for gain. This physical circuit extracts what is mathematically referred to as the largest principal component of its spatio-temporal input space. The circuit's practicality is demonstrated by its incorporation in an RF-photonic system. An unknown mixture of unknown microwave signals, received by an antenna array, constitutes the input to the system. The output electronically returns one of the original microwave signals. The front-end of the system down converts the 10 GHz microwave signals and amplifies them before the signals phase modulate optical beams. The optical carrier is suppressed from these beams so that it may not be considered as a signal itself to the autotuning filter. The suppression is achieved with two-beam coupling in a single photorefractive crystal. The filter extracts the more intense of the signals present on the carrier-suppressed input beams. The detection of the extracted signal restores the microwave signal to an electronic form. The system, without the receiving antenna array, is packaged in a 13 x 18 x 6″ briefcase. Its power consumption equals that of a regular 50 W household light bulb. The system was shipped to different parts of the country for real-time demonstrations of signal separation thus also validating its claim to robustness.

New Technologies in Amplification: Applications to the Pediatric Population.

ERIC Educational Resources Information Center

Kopun, Judy

1995-01-01

Discussion of technological advances in amplification for children with hearing impairments focuses on the advantages and limitations of fitting children with devices that have features such as dynamic-range compression, multiband signal processing, multimemory capability, digital feedback reduction, and frequency transposition. (Author/DB)

A Study on the Data Compression Technology-Based Intelligent Data Acquisition (IDAQ) System for Structural Health Monitoring of Civil Structures

PubMed Central

Jeon, Joonryong

2017-01-01

In this paper, a data compression technology-based intelligent data acquisition (IDAQ) system was developed for structural health monitoring of civil structures, and its validity was tested using random signals (El-Centro seismic waveform). The IDAQ system was structured to include a high-performance CPU with large dynamic memory for multi-input and output in a radio frequency (RF) manner. In addition, the embedded software technology (EST) has been applied to it to implement diverse logics needed in the process of acquiring, processing and transmitting data. In order to utilize IDAQ system for the structural health monitoring of civil structures, this study developed an artificial filter bank by which structural dynamic responses (acceleration) were efficiently acquired, and also optimized it on the random El-Centro seismic waveform. All techniques developed in this study have been embedded to our system. The data compression technology-based IDAQ system was proven valid in acquiring valid signals in a compressed size. PMID:28704945

A Study on the Data Compression Technology-Based Intelligent Data Acquisition (IDAQ) System for Structural Health Monitoring of Civil Structures.

PubMed

Heo, Gwanghee; Jeon, Joonryong

2017-07-12

In this paper, a data compression technology-based intelligent data acquisition (IDAQ) system was developed for structural health monitoring of civil structures, and its validity was tested using random signals (El-Centro seismic waveform). The IDAQ system was structured to include a high-performance CPU with large dynamic memory for multi-input and output in a radio frequency (RF) manner. In addition, the embedded software technology (EST) has been applied to it to implement diverse logics needed in the process of acquiring, processing and transmitting data. In order to utilize IDAQ system for the structural health monitoring of civil structures, this study developed an artificial filter bank by which structural dynamic responses (acceleration) were efficiently acquired, and also optimized it on the random El-Centro seismic waveform. All techniques developed in this study have been embedded to our system. The data compression technology-based IDAQ system was proven valid in acquiring valid signals in a compressed size.

Amplified Sensitivity of Nitrogen-Vacancy Spins in Nanodiamonds Using All-Optical Charge Readout.

PubMed

Hopper, David A; Grote, Richard R; Parks, Samuel M; Bassett, Lee C

2018-04-23

Nanodiamonds containing nitrogen-vacancy (NV) centers offer a versatile platform for sensing applications spanning from nanomagnetism to in vivo monitoring of cellular processes. In many cases, however, weak optical signals and poor contrast demand long acquisition times that prevent the measurement of environmental dynamics. Here, we demonstrate the ability to perform fast, high-contrast optical measurements of charge distributions in ensembles of NV centers in nanodiamonds and use the technique to improve the spin-readout signal-to-noise ratio through spin-to-charge conversion. A study of 38 nanodiamonds with sizes ranging between 20 and 70 nm, each hosting a small ensemble of NV centers, uncovers complex, multiple time scale dynamics due to radiative and nonradiative ionization and recombination processes. Nonetheless, the NV-containing nanodiamonds universally exhibit charge-dependent photoluminescence contrasts and the potential for enhanced spin readout using spin-to-charge conversion. We use the technique to speed up a T 1 relaxometry measurement by a factor of 5.

Irrelevant stimulus processing in ADHD: catecholamine dynamics and attentional networks.

PubMed

Aboitiz, Francisco; Ossandón, Tomás; Zamorano, Francisco; Palma, Bárbara; Carrasco, Ximena

2014-01-01

A cardinal symptom of attention deficit and hyperactivity disorder (ADHD) is a general distractibility where children and adults shift their attentional focus to stimuli that are irrelevant to the ongoing behavior. This has been attributed to a deficit in dopaminergic signaling in cortico-striatal networks that regulate goal-directed behavior. Furthermore, recent imaging evidence points to an impairment of large scale, antagonistic brain networks that normally contribute to attentional engagement and disengagement, such as the task-positive networks and the default mode network (DMN). Related networks are the ventral attentional network (VAN) involved in attentional shifting, and the salience network (SN) related to task expectancy. Here we discuss the tonic-phasic dynamics of catecholaminergic signaling in the brain, and attempt to provide a link between this and the activities of the large-scale cortical networks that regulate behavior. More specifically, we propose that a disbalance of tonic catecholamine levels during task performance produces an emphasis of phasic signaling and increased excitability of the VAN, yielding distractibility symptoms. Likewise, immaturity of the SN may relate to abnormal tonic signaling and an incapacity to build up a proper executive system during task performance. We discuss different lines of evidence including pharmacology, brain imaging and electrophysiology, that are consistent with our proposal. Finally, restoring the pharmacodynamics of catecholaminergic signaling seems crucial to alleviate ADHD symptoms; however, the possibility is open to explore cognitive rehabilitation strategies to top-down modulate network dynamics compensating the pharmacological deficits.

Ubx dynamically regulates Dpp signaling by repressing Dad expression during copper cell regeneration in the adult Drosophila midgut

PubMed Central

Li, Hongjie; Qi, Yanyan; Jasper, Heinrich

2016-01-01

The gastrointestinal (GI) tract of metazoans is lined by a series of regionally distinct epithelia. To maintain structure and function of the GI tract, regionally diversified differentiation of somatic stem cell (SC) lineages is critical. The adult Drosophila midgut provides an accessible model to study SC regulation and specification in a regionally defined manner. SCs of the posterior midgut (PM) have been studied extensively, but the control of SCs in the middle midgut (MM) is less well understood. The MM contains a stomach-like copper cell region (CCR) that is regenerated by gastric stem cells (GSSCs) and contains acid-secreting copper cells (CCs). Bmp-like Decapentaplegic (Dpp) signaling determines the identity of GSSCs, and is required for CC regeneration, yet the precise control of Dpp signaling activity in this lineage remains to be fully established. Here, we show that Dad, a negative feedback regulator of Dpp signaling, is dynamically regulated in the GSSC lineage to allow CC differentiation. Dad is highly expressed in GSSCs and their first daughter cells, the gastroblasts (GBs), but has to be repressed in differentiating CCs to allow Dpp-mediated differentiation into CCs. We find that the Hox gene ultrabithorax (Ubx) is required for this regulation. Loss of Ubx prevents Dad repression in the CCR, resulting in defective CC regeneration. Our study highlights the need for dynamic control of Dpp signaling activity in the differentiation of the GSSC lineage and identifies Ubx as a critical regulator of this process. PMID:27570230

Irrelevant stimulus processing in ADHD: catecholamine dynamics and attentional networks

PubMed Central

Aboitiz, Francisco; Ossandón, Tomás; Zamorano, Francisco; Palma, Bárbara; Carrasco, Ximena

2014-01-01

A cardinal symptom of attention deficit and hyperactivity disorder (ADHD) is a general distractibility where children and adults shift their attentional focus to stimuli that are irrelevant to the ongoing behavior. This has been attributed to a deficit in dopaminergic signaling in cortico-striatal networks that regulate goal-directed behavior. Furthermore, recent imaging evidence points to an impairment of large scale, antagonistic brain networks that normally contribute to attentional engagement and disengagement, such as the task-positive networks and the default mode network (DMN). Related networks are the ventral attentional network (VAN) involved in attentional shifting, and the salience network (SN) related to task expectancy. Here we discuss the tonic–phasic dynamics of catecholaminergic signaling in the brain, and attempt to provide a link between this and the activities of the large-scale cortical networks that regulate behavior. More specifically, we propose that a disbalance of tonic catecholamine levels during task performance produces an emphasis of phasic signaling and increased excitability of the VAN, yielding distractibility symptoms. Likewise, immaturity of the SN may relate to abnormal tonic signaling and an incapacity to build up a proper executive system during task performance. We discuss different lines of evidence including pharmacology, brain imaging and electrophysiology, that are consistent with our proposal. Finally, restoring the pharmacodynamics of catecholaminergic signaling seems crucial to alleviate ADHD symptoms; however, the possibility is open to explore cognitive rehabilitation strategies to top-down modulate network dynamics compensating the pharmacological deficits. PMID:24723897

Dynamic PET and Optical Imaging and Compartment Modeling using a Dual-labeled Cyclic RGD Peptide Probe

PubMed Central

Zhu, Lei; Guo, Ning; Li, Quanzheng; Ma, Ying; Jacboson, Orit; Lee, Seulki; Choi, Hak Soo; Mansfield, James R.; Niu, Gang; Chen, Xiaoyuan

2012-01-01

Purpose: The aim of this study is to determine if dynamic optical imaging could provide comparable kinetic parameters to that of dynamic PET imaging by a near-infrared dye/64Cu dual-labeled cyclic RGD peptide. Methods: The integrin αvβ3 binding RGD peptide was conjugated with a macrocyclic chelator 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) for copper labeling and PET imaging and a near-infrared dye ZW-1 for optical imaging. The in vitro biological activity of RGD-C(DOTA)-ZW-1 was characterized by cell staining and receptor binding assay. Sixty-min dynamic PET and optical imaging were acquired on a MDA-MB-435 tumor model. Singular value decomposition (SVD) method was applied to compute the dynamic optical signal from the two-dimensional optical projection images. Compartment models were used to quantitatively analyze and compare the dynamic optical and PET data. Results: The dual-labeled probe 64Cu-RGD-C(DOTA)-ZW-1 showed integrin specific binding in vitro and in vivo. The binding potential (Bp) derived from dynamic optical imaging (1.762 ± 0.020) is comparable to that from dynamic PET (1.752 ± 0.026). Conclusion: The signal un-mixing process using SVD improved the accuracy of kinetic modeling of 2D dynamic optical data. Our results demonstrate that 2D dynamic optical imaging with SVD analysis could achieve comparable quantitative results as dynamic PET imaging in preclinical xenograft models. PMID:22916074

Dynamic PET and Optical Imaging and Compartment Modeling using a Dual-labeled Cyclic RGD Peptide Probe.

PubMed

Zhu, Lei; Guo, Ning; Li, Quanzheng; Ma, Ying; Jacboson, Orit; Lee, Seulki; Choi, Hak Soo; Mansfield, James R; Niu, Gang; Chen, Xiaoyuan

2012-01-01

The aim of this study is to determine if dynamic optical imaging could provide comparable kinetic parameters to that of dynamic PET imaging by a near-infrared dye/(64)Cu dual-labeled cyclic RGD peptide. The integrin α(v)β(3) binding RGD peptide was conjugated with a macrocyclic chelator 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) for copper labeling and PET imaging and a near-infrared dye ZW-1 for optical imaging. The in vitro biological activity of RGD-C(DOTA)-ZW-1 was characterized by cell staining and receptor binding assay. Sixty-min dynamic PET and optical imaging were acquired on a MDA-MB-435 tumor model. Singular value decomposition (SVD) method was applied to compute the dynamic optical signal from the two-dimensional optical projection images. Compartment models were used to quantitatively analyze and compare the dynamic optical and PET data. The dual-labeled probe (64)Cu-RGD-C(DOTA)-ZW-1 showed integrin specific binding in vitro and in vivo. The binding potential (Bp) derived from dynamic optical imaging (1.762 ± 0.020) is comparable to that from dynamic PET (1.752 ± 0.026). The signal un-mixing process using SVD improved the accuracy of kinetic modeling of 2D dynamic optical data. Our results demonstrate that 2D dynamic optical imaging with SVD analysis could achieve comparable quantitative results as dynamic PET imaging in preclinical xenograft models.

Hardware for dynamic quantum computing.

PubMed

Ryan, Colm A; Johnson, Blake R; Ristè, Diego; Donovan, Brian; Ohki, Thomas A

2017-10-01

We describe the hardware, gateware, and software developed at Raytheon BBN Technologies for dynamic quantum information processing experiments on superconducting qubits. In dynamic experiments, real-time qubit state information is fed back or fed forward within a fraction of the qubits' coherence time to dynamically change the implemented sequence. The hardware presented here covers both control and readout of superconducting qubits. For readout, we created a custom signal processing gateware and software stack on commercial hardware to convert pulses in a heterodyne receiver into qubit state assignments with minimal latency, alongside data taking capability. For control, we developed custom hardware with gateware and software for pulse sequencing and steering information distribution that is capable of arbitrary control flow in a fraction of superconducting qubit coherence times. Both readout and control platforms make extensive use of field programmable gate arrays to enable tailored qubit control systems in a reconfigurable fabric suitable for iterative development.

Exploiting single-cell variability to infer the dynamics of immune responses

NASA Astrophysics Data System (ADS)

Höfer, Thomas

Cell division, differentiation, migration and death determine the dynamics of immune responses. These processes are regulated by a multitude of biochemical signals which, at present, cannot faithfully be reconstituted outside the living organism. However, quantitative measurements in living organisms have been limited. In recent years experimental techniques for the ``fate mapping'' of single immune cells have been developed that allow performing parallel single-cell experiments in an experimental animal. The resulting data are more informative about underlying biological processes than traditional measurements. I will show how the theory of stochastic dynamical systems can be used to infer the topology and dynamics of cell differentiation pathways from such data. The focus will be on joint theoretical and experimental work addressing: (i) the development of immune cells during hematopoiesis, and (ii) T cell responses to diverse pathogens. I will discuss questions on the nature of cellular variability that are posed by these new findings.

Light exposure at night disrupts host/cancer circadian regulatory dynamics: impact on the Warburg effect, lipid signaling and tumor growth prevention.

PubMed

Blask, David E; Dauchy, Robert T; Dauchy, Erin M; Mao, Lulu; Hill, Steven M; Greene, Michael W; Belancio, Victoria P; Sauer, Leonard A; Davidson, Leslie

2014-01-01

The central circadian clock within the suprachiasmatic nucleus (SCN) plays an important role in temporally organizing and coordinating many of the processes governing cancer cell proliferation and tumor growth in synchrony with the daily light/dark cycle which may contribute to endogenous cancer prevention. Bioenergetic substrates and molecular intermediates required for building tumor biomass each day are derived from both aerobic glycolysis (Warburg effect) and lipid metabolism. Using tissue-isolated human breast cancer xenografts grown in nude rats, we determined that circulating systemic factors in the host and the Warburg effect, linoleic acid uptake/metabolism and growth signaling activities in the tumor are dynamically regulated, coordinated and integrated within circadian time structure over a 24-hour light/dark cycle by SCN-driven nocturnal pineal production of the anticancer hormone melatonin. Dim light at night (LAN)-induced melatonin suppression disrupts this circadian-regulated host/cancer balance among several important cancer preventative signaling mechanisms, leading to hyperglycemia and hyperinsulinemia in the host and runaway aerobic glycolysis, lipid signaling and proliferative activity in the tumor.

Multiscale Behavior of Viscous Fluids Dynamics: Experimental Observations

NASA Astrophysics Data System (ADS)

Arciniega-Ceballos, Alejandra; Spina, Laura; Scheu, Bettina; Dingwell, Donald B.

2016-04-01

The dynamics of Newtonian fluids with viscosities of mafic to intermediate silicate melts (10-1000 Pa s) during slow decompression present multi-time scale processes. To observe these processes we have performed several experiments on silicon oil saturated with Argon gas for 72 hours, in a Plexiglas autoclave. The slow decompression, dropping from 10 MPa to ambient pressure, acting as the excitation mechanism, triggered several processes with their own distinct timescales. These processes generate complex non-stationary microseismic signals, which have been recorded with 7 high-dynamic piezoelectric sensors located along the conduit flanked by high-speed video recordings. The analysis in time and frequency of these time series and their correlation with the associated high-speed imaging enables the characterization of distinct phases and the extraction of the individual processes during the evolution of decompression of these viscous fluids. We have observed fluid-solid elastic interaction, degassing, fluid mass expansion and flow, bubble nucleation, growth, coalescence and collapse, foam building and vertical wagging. All these processes (in fine and coarse scales) are sequentially coupled in time, occur within specific pressure intervals, and exhibit a localized distribution along the conduit. Their coexistence and interactions constitute the stress field and driving forces that determine the dynamics of the conduit system. Our observations point to the great potential of this experimental approach in the understanding of volcanic conduit dynamics and volcanic seismicity.

Correlated receptor transport processes buffer single-cell heterogeneity

PubMed Central

Kallenberger, Stefan M.; Unger, Anne L.; Legewie, Stefan; Lymperopoulos, Konstantinos; Eils, Roland

2017-01-01

Cells typically vary in their response to extracellular ligands. Receptor transport processes modulate ligand-receptor induced signal transduction and impact the variability in cellular responses. Here, we quantitatively characterized cellular variability in erythropoietin receptor (EpoR) trafficking at the single-cell level based on live-cell imaging and mathematical modeling. Using ensembles of single-cell mathematical models reduced parameter uncertainties and showed that rapid EpoR turnover, transport of internalized EpoR back to the plasma membrane, and degradation of Epo-EpoR complexes were essential for receptor trafficking. EpoR trafficking dynamics in adherent H838 lung cancer cells closely resembled the dynamics previously characterized by mathematical modeling in suspension cells, indicating that dynamic properties of the EpoR system are widely conserved. Receptor transport processes differed by one order of magnitude between individual cells. However, the concentration of activated Epo-EpoR complexes was less variable due to the correlated kinetics of opposing transport processes acting as a buffering system. PMID:28945754

Nonlinear Blind Compensation for Array Signal Processing Application

PubMed Central

Ma, Hong; Jin, Jiang; Zhang, Hua

2018-01-01

Recently, nonlinear blind compensation technique has attracted growing attention in array signal processing application. However, due to the nonlinear distortion stemming from array receiver which consists of multi-channel radio frequency (RF) front-ends, it is too difficult to estimate the parameters of array signal accurately. A novel nonlinear blind compensation algorithm aims at the nonlinearity mitigation of array receiver and its spurious-free dynamic range (SFDR) improvement, which will be more precise to estimate the parameters of target signals such as their two-dimensional directions of arrival (2-D DOAs). Herein, the suggested method is designed as follows: the nonlinear model parameters of any channel of RF front-end are extracted to synchronously compensate the nonlinear distortion of the entire receiver. Furthermore, a verification experiment on the array signal from a uniform circular array (UCA) is adopted to testify the validity of our approach. The real-world experimental results show that the SFDR of the receiver is enhanced, leading to a significant improvement of the 2-D DOAs estimation performance for weak target signals. And these results demonstrate that our nonlinear blind compensation algorithm is effective to estimate the parameters of weak array signal in concomitance with strong jammers. PMID:29690571

Global navigation satellite system receiver for weak signals under all dynamic conditions

NASA Astrophysics Data System (ADS)

Ziedan, Nesreen Ibrahim

The ability of the Global Navigation Satellite System (GNSS) receiver to work under weak signal and various dynamic conditions is required in some applications. For example, to provide a positioning capability in wireless devices, or orbit determination of Geostationary and high Earth orbit satellites. This dissertation develops Global Positioning System (GPS) receiver algorithms for such applications. Fifteen algorithms are developed for the GPS C/A signal. They cover all the receiver main functions, which include acquisition, fine acquisition, bit synchronization, code and carrier tracking, and navigation message decoding. They are integrated together, and they can be used in any software GPS receiver. They also can be modified to fit any other GPS or GNSS signals. The algorithms have new capabilities. The processing and memory requirements are considered in the design to allow the algorithms to fit the limited resources of some applications; they do not require any assisting information. Weak signals can be acquired in the presence of strong interfering signals and under high dynamic conditions. The fine acquisition, bit synchronization, and tracking algorithms are based on the Viterbi algorithm and Extended Kalman filter approaches. The tracking algorithms capabilities increase the time to lose lock. They have the ability to adaptively change the integration length and the code delay separation. More than one code delay separation can be used in the same time. Large tracking errors can be detected and then corrected by a re-initialization and an acquisition-like algorithms. Detecting the navigation message is needed to increase the coherent integration; decoding it is needed to calculate the navigation solution. The decoding algorithm utilizes the message structure to enable its decoding for signals with high Bit Error Rate. The algorithms are demonstrated using simulated GPS C/A code signals, and TCXO clocks. The results have shown the algorithms ability to reliably work with 15 dB-Hz signals and acceleration over 6 g.

Asynchronous Data-Driven Classification of Weapon Systems

DTIC Science & Technology

2009-10-01

Classification of Weapon SystemsF Xin Jin† Kushal Mukherjee† Shalabh Gupta† Asok Ray † Shashi Phoha† Thyagaraju Damarla‡ xuj103@psu.edu kum162@psu.edu szg107...Orlando, FL. [8] A. Ray , “Symbolic dynamic analysis of complex systems for anomaly detection,” Signal Processing, vol. 84, no. 7, pp. 1115–1130, July...2004. [9] S. Gupta and A. Ray , “Symbolic dynamic filtering for data-driven pat- tern recognition,” PATTERN RECOGNITION: Theory and Application

Ab initio studies of ultrafast x-ray scattering of the photodissociation of iodine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Debnarova, Andrea; Techert, Simone; Schmatz, Stefan

2010-09-28

We computationally examine various aspects of the reaction dynamics of the photodissociation and recombination of molecular iodine. We use our recently proposed formalism to calculate time-dependent x-ray scattering signal changes from first principles. Different aspects of the dynamics of this prototypical reaction are studied, such as coherent and noncoherent processes, features of structural relaxation that are periodic in time versus nonperiodic dissociative processes, as well as small electron density changes caused by electronic excitation, all with respect to x-ray scattering. We can demonstrate that wide-angle x-ray scattering offers a possibility to study the changes in electron densities in nonperiodic systems,more » which render it a suitable technique for the investigation of chemical reactions from a structural dynamics point of view.« less

Frequency division multiplexed multi-color fluorescence microscope system

NASA Astrophysics Data System (ADS)

Le, Vu Nam; Yang, Huai Dong; Zhang, Si Chun; Zhang, Xin Rong; Jin, Guo Fan

2017-10-01

Grayscale camera can only obtain gray scale image of object, while the multicolor imaging technology can obtain the color information to distinguish the sample structures which have the same shapes but in different colors. In fluorescence microscopy, the current method of multicolor imaging are flawed. Problem of these method is affecting the efficiency of fluorescence imaging, reducing the sampling rate of CCD etc. In this paper, we propose a novel multiple color fluorescence microscopy imaging method which based on the Frequency division multiplexing (FDM) technology, by modulating the excitation lights and demodulating the fluorescence signal in frequency domain. This method uses periodic functions with different frequency to modulate amplitude of each excitation lights, and then combine these beams for illumination in a fluorescence microscopy imaging system. The imaging system will detect a multicolor fluorescence image by a grayscale camera. During the data processing, the signal obtained by each pixel of the camera will be processed with discrete Fourier transform, decomposed by color in the frequency domain and then used inverse discrete Fourier transform. After using this process for signals from all of the pixels, monochrome images of each color on the image plane can be obtained and multicolor image is also acquired. Based on this method, this paper has constructed and set up a two-color fluorescence microscope system with two excitation wavelengths of 488 nm and 639 nm. By using this system to observe the linearly movement of two kinds of fluorescent microspheres, after the data processing, we obtain a two-color fluorescence dynamic video which is consistent with the original image. This experiment shows that the dynamic phenomenon of multicolor fluorescent biological samples can be generally observed by this method. Compared with the current methods, this method can obtain the image signals of each color at the same time, and the color video's frame rate is consistent with the frame rate of the camera. The optical system is simpler and does not need extra color separation element. In addition, this method has a good filtering effect on the ambient light or other light signals which are not affected by the modulation process.

Modularized Smad-regulated TGFβ signaling pathway.

PubMed

Li, Yongfeng; Wang, Minli; Carra, Claudio; Cucinotta, Francis A

2012-12-01

The transforming Growth Factor β (TGFβ) signaling pathway is a prominent regulatory signaling pathway controlling various important cellular processes. TGFβ signaling can be induced by several factors including ionizing radiation. The pathway is regulated in a negative feedback loop through promoting the nuclear import of the regulatory Smads and a subsequent expression of inhibitory Smad7, that forms ubiquitin ligase with Smurf2, targeting active TGFβ receptors for degradation. In this work, we proposed a mathematical model to study the Smad-regulated TGFβ signaling pathway. By modularization, we are able to analyze mathematically each component subsystem and recover the nonlinear dynamics of the entire network system. Meanwhile the excitability, a common feature observed in the biological systems, in the TGFβ signaling pathway is discussed and supported as well by numerical simulation, indicating the robustness of the model. Published by Elsevier Inc.

Rapid encoding of relationships between spatially remote motion signals.

PubMed

Maruya, Kazushi; Holcombe, Alex O; Nishida, Shin'ya

2013-02-06

For visual processing, the temporal correlation of remote local motion signals is a strong cue to detect meaningful large-scale structures in the retinal image, because related points are likely to move together regardless of their spatial separation. While the processing of multi-element motion patterns involved in biological motion and optic flow has been studied intensively, the encoding of simpler pairwise relationships between remote motion signals remains poorly understood. We investigated this process by measuring the temporal rate limit for perceiving the relationship of two motion directions presented at the same time at different spatial locations. Compared to luminance or orientation, motion comparison was more rapid. Performance remained very high even when interstimulus separation was increased up to 100°. Motion comparison also remained rapid regardless of whether the two motion directions were similar to or different from each other. The exception was a dramatic slowing when the elements formed an orthogonal "T," in which two motions do not perceptually group together. Motion presented at task-irrelevant positions did not reduce performance, suggesting that the rapid motion comparison could not be ascribed to global optic flow processing. Our findings reveal the existence and unique nature of specialized processing that encodes long-range relationships between motion signals for quick appreciation of global dynamic scene structure.

Phase transitions in the common brainstem and related systems investigated by nonstationary time series analysis.

PubMed

Lambertz, M; Vandenhouten, R; Grebe, R; Langhorst, P

2000-01-14

Neuronal activities of the reticular formation (RF) of the lower brainstem and the nucleus tractus solitarii (NTS, first relay station of baroreceptor afferents) were recorded together in the anesthized dog with related parameters of EEG, respiration and cardiovascular system. The RF neurons are part of the common brainstem system (CBS) which participates in regulation and coordination of cardiovascular, respiratory, somatomotor systems, and vigilance. Multiple time series of these physiological subsystems yield useful information about internal dynamic coordination of the organism. Essential problems are nonlinearity and instationarity of the signals, due to the dynamic complexity of the systems. Several time-resolving methods are presented to describe nonlinear dynamic couplings in the time course, particularly during phase transitions. The methods are applied to the recorded signals representing the complex couplings of the physiological subsystems. Phase transitions in these systems are detected by recurrence plots of the instationary signals. The pointwise transinformation and the pointwise conditional coupling divergence are measures of the mutual interaction of the subsystems in the state space. If the signals show marked rhythms, instantaneous frequencies and their shiftings are demonstrated by time frequency distributions, and instantaneous phase differences show couplings of oscillating subsystems. Transient signal components are reconstructed by wavelet packet time selective transient reconstruction. These methods are useful means for analyzing coupling characteristics of the complex physiological system, and detailed analyses of internal dynamic coordination of subsystems become possible. During phase transitions of the functional organization (a) the rhythms of the central neuronal activities and the peripheral systems are altered, (b) changes in the coupling between CBS neurons and cardiovascular signals, respiration and the EEG, and (c) between NTS neurons (influenced by baroreceptor afferents) and CBS neurons occur, and (d) the processing of baroreceptor input at the NTS neurons changes. The results of this complex analysis, which could not be done formerly in this manner, confirm and complete former investigations on the dynamic organization of the CBS with its changing relations to peripheral and other central nervous subsystems.

Fault feature analysis of cracked gear based on LOD and analytical-FE method

NASA Astrophysics Data System (ADS)

Wu, Jiateng; Yang, Yu; Yang, Xingkai; Cheng, Junsheng

2018-01-01

At present, there are two main ideas for gear fault diagnosis. One is the model-based gear dynamic analysis; the other is signal-based gear vibration diagnosis. In this paper, a method for fault feature analysis of gear crack is presented, which combines the advantages of dynamic modeling and signal processing. Firstly, a new time-frequency analysis method called local oscillatory-characteristic decomposition (LOD) is proposed, which has the attractive feature of extracting fault characteristic efficiently and accurately. Secondly, an analytical-finite element (analytical-FE) method which is called assist-stress intensity factor (assist-SIF) gear contact model, is put forward to calculate the time-varying mesh stiffness (TVMS) under different crack states. Based on the dynamic model of the gear system with 6 degrees of freedom, the dynamic simulation response was obtained for different tooth crack depths. For the dynamic model, the corresponding relation between the characteristic parameters and the degree of the tooth crack is established under a specific condition. On the basis of the methods mentioned above, a novel gear tooth root crack diagnosis method which combines the LOD with the analytical-FE is proposed. Furthermore, empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) are contrasted with the LOD by gear crack fault vibration signals. The analysis results indicate that the proposed method performs effectively and feasibility for the tooth crack stiffness calculation and the gear tooth crack fault diagnosis.

The decay process of rotating unstable systems through the passage time distribution

NASA Astrophysics Data System (ADS)

Jiménez-Aquino, J. I.; Cortés, Emilio; Aquino, N.

2001-05-01

In this work we propose a general scheme to characterize, through the passage time distribution, the decay process of rotational unstable systems in the presence of external forces of large amplitude. The formalism starts with a matricial Langevin type equation formulated in the context of two dynamical representations given, respectively, by the vectors x and y, both related by a time dependent rotation matrix. The transformation preserves the norm of the vector and decouples the set of dynamical equations in the transformed space y. We study the dynamical characterization of the systems of two variables and show that the statistical properties of the passage time distribution are essentially equivalent in both dynamics. The theory is applied to the laser system studied in Dellunde et al. (Opt. Commun. 102 (1993) 277), where the effect of large injected signals on the transient dynamics of the laser has been studied in terms of complex electric field. The analytical results are compared with numerical simulation.

Motor-sensory confluence in tactile perception.

PubMed

Saig, Avraham; Gordon, Goren; Assa, Eldad; Arieli, Amos; Ahissar, Ehud

2012-10-03

Perception involves motor control of sensory organs. However, the dynamics underlying emergence of perception from motor-sensory interactions are not yet known. Two extreme possibilities are as follows: (1) motor and sensory signals interact within an open-loop scheme in which motor signals determine sensory sampling but are not affected by sensory processing and (2) motor and sensory signals are affected by each other within a closed-loop scheme. We studied the scheme of motor-sensory interactions in humans using a novel object localization task that enabled monitoring the relevant overt motor and sensory variables. We found that motor variables were dynamically controlled within each perceptual trial, such that they gradually converged to steady values. Training on this task resulted in improvement in perceptual acuity, which was achieved solely by changes in motor variables, without any change in the acuity of sensory readout. The within-trial dynamics is captured by a hierarchical closed-loop model in which lower loops actively maintain constant sensory coding, and higher loops maintain constant sensory update flow. These findings demonstrate interchangeability of motor and sensory variables in perception, motor convergence during perception, and a consistent hierarchical closed-loop perceptual model.

Dynamic curvature sensing employing ionic-polymer-metal composite sensors

NASA Astrophysics Data System (ADS)

Bahramzadeh, Yousef; Shahinpoor, Mohsen

2011-09-01

A dynamic curvature sensor is presented based on ionic-polymer-metal composite (IPMC) for curvature monitoring of deployable/inflatable dynamic space structures. Monitoring the curvature variation is of high importance in various engineering structures including shape monitoring of deployable/inflatable space structures in which the structural boundaries undergo a dynamic deployment process. The high sensitivity of IPMCs to the applied deformations as well as its flexibility make IPMCs a promising candidate for sensing of dynamic curvature changes. Herein, we explore the dynamic response of an IPMC sensor strip with respect to controlled curvature deformations subjected to different forms of input functions. Using a specially designed experimental setup, the voltage recovery effect, phase delay, and rate dependency of the output voltage signal of an IPMC curvature sensor are analyzed. Experimental results show that the IPMC sensor maintains the linearity, sensitivity, and repeatability required for curvature sensing. Besides, in order to describe the dynamic phenomena such as the rate dependency of the IPMC sensor, a chemo-electro-mechanical model based on the Poisson-Nernst-Planck (PNP) equation for the kinetics of ion diffusion is presented. By solving the governing partial differential equations the frequency response of the IPMC sensor is derived. The physical model is able to describe the dynamic properties of the IPMC sensor and the dependency of the signal on rate of excitations.

Research on Dynamic Torque Measurement of High Speed Rotating Axis Based on Whole Optical Fiber Technique

NASA Astrophysics Data System (ADS)

Ma, H. P.; Jin, Y. Q.; Ha, Y. W.; Liu, L. H.

2006-10-01

Non-contact torque measurement system of fiber grating is proposed in this paper. It is used for the dynamic torque measurement of the rotating axis in the spaceflight servo system. Optical fiber is used as sensing probe with high sensitivity, anti-electromagnetic interference, resistance to high temperature and corrosion. It is suitable to apply in a bad environment. Signals are processed by digital circuit and Single Chip Microcomputer. This project can realize super speed dynamic measurement and it is the first time to apply the project in the spaceflight system.

Dynamics of polymers in elongational flow studied by the neutron spin-echo technique

NASA Astrophysics Data System (ADS)

Rheinstädter, Maikel C.; Sattler, Rainer; Häußler, Wolfgang; Wagner, Christian

2010-09-01

The nanoscale fluctuation dynamics of semidilute high molecular weight polymer solutions of polyethylenoxide (PEO) in D 2O under non-equilibrium flow conditions were studied by the neutron spin-echo technique. The sample cell was in contraction flow geometry and provided a pressure driven flow with a high elongational component that stretched the polymers most efficiently. Neutron scattering experiments in dilute polymer solutions are challenging because of the low polymer concentration and corresponding small quasi-elastic signals. A relaxation process with relaxation times of about 10 ps was observed, which shows anisotropic dynamics with applied flow.

Multifractal spectrum of physiological signals: a mechanism-related approach

NASA Astrophysics Data System (ADS)

Pavlov, Alexey N.; Pavlova, Olga N.; Abdurashitov, Arkady S.; Arinushkin, Pavel A.; Runnova, Anastasiya E.; Semyachkina-Glushkovskaya, Oxana V.

2017-04-01

In this paper we discuss an approach for mechanism-related analysis of physiological signals performed with the wavelet-based multifractal formalism. This approach assumes estimation of the singularity spectrum for the band-pass filtered processes at different physiological conditions in order to provide explanation of the occurred changes in the Hölder exponents and the multi-fractality degree. We illustrate the considered approach using two examples, namely, the dynamics of the cerebral blood flow (CBF) and the electrical activity of the brain.

Time-resolved EPR study on the photochemical reactions of benzil

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mukai, Masahiro; Yamnauchi, Seigo; Hirota, Noboru

1992-04-16

TREPR and optical studies on the photochemical reactions of benzil in 2-propanol and benzene-TEA conclude that emissive signals are due to the reaction from T{sub n} produced via the S{sub n} pointing right T{sub n} intersystem crossing process. The free-pair radical-pair mechanism can account for the main features of the slow rise component of the chemically induced dynamic electron polarization signal of the ketyl radical in 2-propanol. 27 refs., 10 figs., 2 tabs.

Modularized TGFbeta-Smad Signaling Pathway

NASA Technical Reports Server (NTRS)

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.

Smartphone Cortex Controlled Real-Time Image Processing and Reprocessing for Concentration Independent LED Induced Fluorescence Detection in Capillary Electrophoresis.

PubMed

Szarka, Mate; Guttman, Andras

2017-10-17

We present the application of a smartphone anatomy based technology in the field of liquid phase bioseparations, particularly in capillary electrophoresis. A simple capillary electrophoresis system was built with LED induced fluorescence detection and a credit card sized minicomputer to prove the concept of real time fluorescent imaging (zone adjustable time-lapse fluorescence image processor) and separation controller. The system was evaluated by analyzing under- and overloaded aminopyrenetrisulfonate (APTS)-labeled oligosaccharide samples. The open source software based image processing tool allowed undistorted signal modulation (reprocessing) if the signal was inappropriate for the actual detection system settings (too low or too high). The novel smart detection tool for fluorescently labeled biomolecules greatly expands dynamic range and enables retrospective correction for injections with unsuitable signal levels without the necessity to repeat the analysis.

Dark matter RNA: an intelligent scaffold for the dynamic regulation of the nuclear information landscape

PubMed Central

St. Laurent, Georges; Savva, Yiannis A.; Kapranov, Philipp

2012-01-01

Perhaps no other topic in contemporary genomics has inspired such diverse viewpoints as the 95+% of the genome, previously known as “junk DNA,” that does not code for proteins. Here, we present a theory in which dark matter RNA plays a role in the generation of a landscape of spatial micro-domains coupled to the information signaling matrix of the nuclear landscape. Within and between these micro-domains, dark matter RNAs additionally function to tether RNA interacting proteins and complexes of many different types, and by doing so, allow for a higher performance of the various processes requiring them at ultra-fast rates. This improves signal to noise characteristics of RNA processing, trafficking, and epigenetic signaling, where competition and differential RNA binding among proteins drives the computational decisions inherent in regulatory events. PMID:22539933

Differential morphology and image processing.

PubMed

Maragos, P

1996-01-01

Image processing via mathematical morphology has traditionally used geometry to intuitively understand morphological signal operators and set or lattice algebra to analyze them in the space domain. We provide a unified view and analytic tools for morphological image processing that is based on ideas from differential calculus and dynamical systems. This includes ideas on using partial differential or difference equations (PDEs) to model distance propagation or nonlinear multiscale processes in images. We briefly review some nonlinear difference equations that implement discrete distance transforms and relate them to numerical solutions of the eikonal equation of optics. We also review some nonlinear PDEs that model the evolution of multiscale morphological operators and use morphological derivatives. Among the new ideas presented, we develop some general 2-D max/min-sum difference equations that model the space dynamics of 2-D morphological systems (including the distance computations) and some nonlinear signal transforms, called slope transforms, that can analyze these systems in a transform domain in ways conceptually similar to the application of Fourier transforms to linear systems. Thus, distance transforms are shown to be bandpass slope filters. We view the analysis of the multiscale morphological PDEs and of the eikonal PDE solved via weighted distance transforms as a unified area in nonlinear image processing, which we call differential morphology, and briefly discuss its potential applications to image processing and computer vision.

Conflicts as Aversive Signals

ERIC Educational Resources Information Center

Dreisbach, Gesine; Fischer, Rico

2012-01-01

Theories of human action control deal with the question of how cognitive control is dynamically adjusted to task demands. The conflict monitoring theory of anterior cingulate (ACC) function suggests that the ACC monitors for response conflicts in the ongoing processing stream thereby triggering the mobilization of cognitive control. Alternatively,…

Hybrid learning in signalling games

NASA Astrophysics Data System (ADS)

Barrett, Jeffrey A.; Cochran, Calvin T.; Huttegger, Simon; Fujiwara, Naoki

2017-09-01

Lewis-Skyrms signalling games have been studied under a variety of low-rationality learning dynamics. Reinforcement dynamics are stable but slow and prone to evolving suboptimal signalling conventions. A low-inertia trial-and-error dynamical like win-stay/lose-randomise is fast and reliable at finding perfect signalling conventions but unstable in the context of noise or agent error. Here we consider a low-rationality hybrid of reinforcement and win-stay/lose-randomise learning that exhibits the virtues of both. This hybrid dynamics is reliable, stable and exceptionally fast.

Simulation and characterization of a laterally-driven inertial micro-switch

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Wenguo; Wang, Yang; Wang, Huiying

2015-04-15

A laterally-driven inertial micro-switch was designed and fabricated using surface micromachining technology. The dynamic response process was simulated by ANSYS software, which revealed the vibration process of movable electrode when the proof mass is shocked by acceleration in sensitive direction. The test results of fabricated inertial micro-switches with and without anti-shock beams indicated that the contact process of micro-switch with anti-shock beams is more reliable than the one without anti-shock beams. The test results indicated that three contact signals had been observed in the contact process of the inertial switch without anti-shock beams, and only one contact signal in themore » inertial switch with anti-shock beams, which demonstrated that the anti-shock beams can effectively constrain the vibration in non-sensitive direction.« less

Evolutionary dynamics of language systems

PubMed Central

Wu, Chieh-Hsi; Hua, Xia; Dunn, Michael; Levinson, Stephen C.; Gray, Russell D.

2017-01-01

Understanding how and why language subsystems differ in their evolutionary dynamics is a fundamental question for historical and comparative linguistics. One key dynamic is the rate of language change. While it is commonly thought that the rapid rate of change hampers the reconstruction of deep language relationships beyond 6,000–10,000 y, there are suggestions that grammatical structures might retain more signal over time than other subsystems, such as basic vocabulary. In this study, we use a Dirichlet process mixture model to infer the rates of change in lexical and grammatical data from 81 Austronesian languages. We show that, on average, most grammatical features actually change faster than items of basic vocabulary. The grammatical data show less schismogenesis, higher rates of homoplasy, and more bursts of contact-induced change than the basic vocabulary data. However, there is a core of grammatical and lexical features that are highly stable. These findings suggest that different subsystems of language have differing dynamics and that careful, nuanced models of language change will be needed to extract deeper signal from the noise of parallel evolution, areal readaptation, and contact. PMID:29073028

Micro-electro-mechanical systems (MEMS) and agile lensing-based modules for communications, sensing and signal processing

NASA Astrophysics Data System (ADS)

Reza, Syed Azer

This dissertation proposes the use of the emerging Micro-Electro-Mechanical Systems (MEMS) and agile lensing optical device technologies to design novel and powerful signal conditioning and sensing modules for advanced applications in optical communications, physical parameter sensing and RF/optical signal processing. For example, these new module designs have experimentally demonstrated exceptional features such as stable loss broadband operations and high > 60 dB optical dynamic range signal filtering capabilities. The first part of the dissertation describes the design and demonstration of digital MEMS-based signal processing modules for communication systems and sensor networks using the TI DLP (Digital Light Processing) technology. Examples of such modules include optical power splitters, narrowband and broadband variable fiber optical attenuators, spectral shapers and filters. Compared to prior works, these all-digital designs have advantages of repeatability, accuracy, and reliability that are essential for advanced communications and sensor applications. The next part of the dissertation proposes, analyzes and demonstrates the use of analog opto-fluidic agile lensing technology for sensor networks and test and measurement systems. Novel optical module designs for distance sensing, liquid level sensing, three-dimensional object shape sensing and variable photonic delay lines are presented and experimentally demonstrated. Compared to prior art module designs, the proposed analog-mode modules have exceptional performances, particularly for extreme environments (e.g., caustic liquids) where the free-space agile beam-based sensor provide remote non-contact access for physical sensing operations. The dissertation also presents novel modules involving hybrid analog-digital photonic designs that make use of the different optical device technologies to deliver the best features of both analog and digital optical device operations and controls. Digital controls are achieved through the use of the digital MEMS technology and analog controls are realized by employing opto-fluidic agile lensing technology and acousto-optic technology. For example, variable fiber-optic attenuators and spectral filters are proposed using the hybrid design. Compared to prior art module designs, these hybrid designs provide a higher module dynamic range and increased resolution that are critical in various advanced system applications. In summary, the dissertation shows the added power of hybrid optical designs using both the digital and analog photonic signal processing versus just all-digital or all-analog module designs.

Visualizing time: how linguistic metaphors are incorporated into displaying instruments in the process of interpreting time-varying signals

NASA Astrophysics Data System (ADS)

Garcia-Belmonte, Germà

2017-06-01

Spatial visualization is a well-established topic of education research that has allowed improving science and engineering students' skills on spatial relations. Connections have been established between visualization as a comprehension tool and instruction in several scientific fields. Learning about dynamic processes mainly relies upon static spatial representations or images. Visualization of time is inherently problematic because time can be conceptualized in terms of two opposite conceptual metaphors based on spatial relations as inferred from conventional linguistic patterns. The situation is particularly demanding when time-varying signals are recorded using displaying electronic instruments, and the image should be properly interpreted. This work deals with the interplay between linguistic metaphors, visual thinking and scientific instrument mediation in the process of interpreting time-varying signals displayed by electronic instruments. The analysis draws on a simplified version of a communication system as example of practical signal recording and image visualization in a physics and engineering laboratory experience. Instrumentation delivers meaningful signal representations because it is designed to incorporate a specific and culturally favored time view. It is suggested that difficulties in interpreting time-varying signals are linked with the existing dual perception of conflicting time metaphors. The activation of specific space-time conceptual mapping might allow for a proper signal interpretation. Instruments play then a central role as visualization mediators by yielding an image that matches specific perception abilities and practical purposes. Here I have identified two ways of understanding time as used in different trajectories through which students are located. Interestingly specific displaying instruments belonging to different cultural traditions incorporate contrasting time views. One of them sees time in terms of a dynamic metaphor consisting of a static observer looking at passing events. This is a general and widespread practice common in the contemporary mass culture, which lies behind the process of making sense to moving images usually visualized by means of movie shots. In contrast scientific culture favored another way of time conceptualization (static time metaphor) that historically fostered the construction of graphs and the incorporation of time-dependent functions, as represented on the Cartesian plane, into displaying instruments. Both types of cultures, scientific and mass, are considered highly technological in the sense that complex instruments, apparatus or machines participate in their visual practices.

Energy transport pathway in proteins: Insights from non-equilibrium molecular dynamics with elastic network model.

PubMed

Wang, Wei Bu; Liang, Yu; Zhang, Jing; Wu, Yi Dong; Du, Jian Jun; Li, Qi Ming; Zhu, Jian Zhuo; Su, Ji Guo

2018-06-22

Intra-molecular energy transport between distant functional sites plays important roles in allosterically regulating the biochemical activity of proteins. How to identify the specific intra-molecular signaling pathway from protein tertiary structure remains a challenging problem. In the present work, a non-equilibrium dynamics method based on the elastic network model (ENM) was proposed to simulate the energy propagation process and identify the specific signaling pathways within proteins. In this method, a given residue was perturbed and the propagation of energy was simulated by non-equilibrium dynamics in the normal modes space of ENM. After that, the simulation results were transformed from the normal modes space to the Cartesian coordinate space to identify the intra-protein energy transduction pathways. The proposed method was applied to myosin and the third PDZ domain (PDZ3) of PSD-95 as case studies. For myosin, two signaling pathways were identified, which mediate the energy transductions form the nucleotide binding site to the 50 kDa cleft and the converter subdomain, respectively. For PDZ3, one specific signaling pathway was identified, through which the intra-protein energy was transduced from ligand binding site to the distant opposite side of the protein. It is also found that comparing with the commonly used cross-correlation analysis method, the proposed method can identify the anisotropic energy transduction pathways more effectively.

Visualization of Cortical Dynamics

NASA Astrophysics Data System (ADS)

Grinvald, Amiram

2003-03-01

Recent progress in studies of cortical dynamics will be reviewed including the combination of real time optical imaging based on voltage sensitive dyes, single and multi- unit recordings, LFP, intracellular recordings and microstimulation. To image the flow of neuronal activity from one cortical site to the next, in real time, we have used optical imaging based on newly designed voltage sensitive dyes and a Fuji 128x 128 fast camera which we modified. A factor of 20-40 fold improvement in the signal to noise ratio was obtained with the new dye during in vivo imaging experiments. This improvements has facilitates the exploration of cortical dynamics without signal averaging in the millisecond time domain. We confirmed that the voltage sensitive dye signal indeed reflects membrane potential changes in populations of neurons by showing that the time course of the intracellular activity recorded intracellularly from a single neuron was highly correlated in many cases with the optical signal from a small patch of cortex recorded nearby. We showed that the firing of single cortical neurons is not a random process but occurs when the on-going pattern of million of neurons is similar to the functional architecture map which correspond to the tuning properties of that neuron. Chronic optical imaging, combined with electrical recordings and microstimulation, over a long period of times of more than a year, was successfully applied also to the study of higher brain functions in the behaving macaque monkey.

Regulation of dopamine D1 receptor dynamics within the postsynaptic density of hippocampal glutamate synapses.

PubMed

Ladepeche, Laurent; Yang, Luting; Bouchet, Delphine; Groc, Laurent

2013-01-01

Dopamine receptor potently modulates glutamate signalling, synaptic plasticity and neuronal network adaptations in various pathophysiological processes. Although key intracellular signalling cascades have been identified, the cellular mechanism by which dopamine and glutamate receptor-mediated signalling interplay at glutamate synapse remain poorly understood. Among the cellular mechanisms proposed to aggregate D1R in glutamate synapses, the direct interaction between D1R and the scaffold protein PSD95 or the direct interaction with the glutamate NMDA receptor (NMDAR) have been proposed. To tackle this question we here used high-resolution single nanoparticle imaging since it provides a powerful way to investigate at the sub-micron resolution the dynamic interaction between these partners in live synapses. We demonstrate in hippocampal neuronal networks that dopamine D1 receptors (D1R) laterally diffuse within glutamate synapses, in which their diffusion is reduced. Disrupting the interaction between D1R and PSD95, through genetical manipulation and competing peptide, did not affect D1R dynamics in glutamatergic synapses. However, preventing the physical interaction between D1R and the GluN1 subunit of NMDAR abolished the synaptic stabilization of diffusing D1R. Together, these data provide direct evidence that the interaction between D1R and NMDAR in synapses participate in the building of the dopamine-receptor-mediated signalling, and most likely to the glutamate-dopamine cross-talk.

Enzyme Sequestration as a Tuning Point in Controlling Response Dynamics of Signalling Networks

PubMed Central

Ollivier, Julien F.; Soyer, Orkun S.

2016-01-01

Signalling networks result from combinatorial interactions among many enzymes and scaffolding proteins. These complex systems generate response dynamics that are often essential for correct decision-making in cells. Uncovering biochemical design principles that underpin such response dynamics is a prerequisite to understand evolved signalling networks and to design synthetic ones. Here, we use in silico evolution to explore the possible biochemical design space for signalling networks displaying ultrasensitive and adaptive response dynamics. By running evolutionary simulations mimicking different biochemical scenarios, we find that enzyme sequestration emerges as a key mechanism for enabling such dynamics. Inspired by these findings, and to test the role of sequestration, we design a generic, minimalist model of a signalling cycle, featuring two enzymes and a single scaffolding protein. We show that this simple system is capable of displaying both ultrasensitive and adaptive response dynamics. Furthermore, we find that tuning the concentration or kinetics of the sequestering protein can shift system dynamics between these two response types. These empirical results suggest that enzyme sequestration through scaffolding proteins is exploited by evolution to generate diverse response dynamics in signalling networks and could provide an engineering point in synthetic biology applications. PMID:27163612

Digital MOS integrated circuits

NASA Astrophysics Data System (ADS)

Elmasry, M. I.

MOS in digital circuit design is considered along with aspects of digital VLSI, taking into account a comparison of MOSFET logic circuits, 1-micrometer MOSFET VLSI technology, a generalized guide for MOSFET miniaturization, processing technologies, novel circuit structures for VLSI, and questions of circuit and system design for VLSI. MOS memory cells and circuits are discussed, giving attention to a survey of high-density dynamic RAM cell concepts, one-device cells for dynamic random-access memories, variable resistance polysilicon for high density CMOS Ram, high performance MOS EPROMs using a stacked-gate cell, and the optimization of the latching pulse for dynamic flip-flop sensors. Programmable logic arrays are considered along with digital signal processors, microprocessors, static RAMs, and dynamic RAMs.

Experimental Observations of Multiscale Dynamics of Viscous Fluid Behavior: Implications in Volcanic Systems

NASA Astrophysics Data System (ADS)

Arciniega-Ceballos, A.; Spina, L.; Scheu, B.; Dingwell, D. B.

2015-12-01

We have investigated the dynamics of Newtonian fluids with viscosities (10-1000 Pa s; corresponding to mafic to intermediate silicate melts) during slow decompression, in a Plexiglas shock tube. As an analogue fluid we used silicon oil saturated with Argon gas for 72 hours. Slow decompression, dropping from 10 MPa to ambient pressure, acts as the excitation mechanism, initiating several processes with their own distinct timescales. The evolution of this multi-timescale phenomenon generates complex non-stationary microseismic signals, which have been recorded with 7 high-dynamic piezoelectric sensors located along the conduit. Correlation analysis of these time series with the associated high-speed imaging enables characterization of distinct phases of the dynamics of these viscous fluids and the extraction of the time and the frequency characteristics of the individual processes. We have identified fluid-solid elastic interaction, degassing, fluid mass expansion and flow, bubble nucleation, growth, coalescence and collapse, foam building and vertical wagging. All these processes (in fine and coarse scales) are sequentially coupled in time, occur within specific pressure intervals, and exhibit a localized distribution in space. Their coexistence and interactions constitute the stress field and driving forces that determine the dynamics of the system. Our observations point to the great potential of this experimental approach in the understanding of volcanic processes and volcanic seismicity.

Large dynamic range terahertz spectrometers based on plasmonic photomixers (Conference Presentation)

NASA Astrophysics Data System (ADS)

Wang, Ning; Javadi, Hamid; Jarrahi, Mona

2017-02-01

Heterodyne terahertz spectrometers are highly in demand for space explorations and astrophysics studies. A conventional heterodyne terahertz spectrometer consists of a terahertz mixer that mixes a received terahertz signal with a local oscillator signal to generate an intermediate frequency signal in the radio frequency (RF) range, where it can be easily processed and detected by RF electronics. Schottky diode mixers, superconductor-insulator-superconductor (SIS) mixers and hot electron bolometer (HEB) mixers are the most commonly used mixers in conventional heterodyne terahertz spectrometers. While conventional heterodyne terahertz spectrometers offer high spectral resolution and high detection sensitivity levels at cryogenic temperatures, their dynamic range and bandwidth are limited by the low radiation power of existing terahertz local oscillators and narrow bandwidth of existing terahertz mixers. To address these limitations, we present a novel approach for heterodyne terahertz spectrometry based on plasmonic photomixing. The presented design replaces terahertz mixer and local oscillator of conventional heterodyne terahertz spectrometers with a plasmonic photomixer pumped by an optical local oscillator. The optical local oscillator consists of two wavelength-tunable continuous-wave optical sources with a terahertz frequency difference. As a result, the spectrometry bandwidth and dynamic range of the presented heterodyne spectrometer is not limited by radiation frequency and power restrictions of conventional terahertz sources. We demonstrate a proof-of-concept terahertz spectrometer with more than 90 dB dynamic range and 1 THz spectrometry bandwidth.

Single-cell resolution of intracellular T cell Ca2+ dynamics in response to frequency-based H2O2 stimulation.

PubMed

Kniss-James, Ariel S; Rivet, Catherine A; Chingozha, Loice; Lu, Hang; Kemp, Melissa L

2017-03-01

Adaptive immune cells, such as T cells, integrate information from their extracellular environment through complex signaling networks with exquisite sensitivity in order to direct decisions on proliferation, apoptosis, and cytokine production. These signaling networks are reliant on the interplay between finely tuned secondary messengers, such as Ca 2+ and H 2 O 2 . Frequency response analysis, originally developed in control engineering, is a tool used for discerning complex networks. This analytical technique has been shown to be useful for understanding biological systems and facilitates identification of the dominant behaviour of the system. We probed intracellular Ca 2+ dynamics in the frequency domain to investigate the complex relationship between two second messenger signaling molecules, H 2 O 2 and Ca 2+ , during T cell activation with single cell resolution. Single-cell analysis provides a unique platform for interrogating and monitoring cellular processes of interest. We utilized a previously developed microfluidic device to monitor individual T cells through time while applying a dynamic input to reveal a natural frequency of the system at approximately 2.78 mHz stimulation. Although our network was much larger with more unknown connections than previous applications, we are able to derive features from our data, observe forced oscillations associated with specific amplitudes and frequencies of stimuli, and arrive at conclusions about potential transfer function fits as well as the underlying population dynamics.

"Multiple partial recognitions in dynamic equilibrium" in the binding sites of proteins form the molecular basis of promiscuous recognition of structurally diverse ligands.

PubMed

Kohda, Daisuke

2018-04-01

Promiscuous recognition of ligands by proteins is as important as strict recognition in numerous biological processes. In living cells, many short, linear amino acid motifs function as targeting signals in proteins to specify the final destination of the protein transport. In general, the target signal is defined by a consensus sequence containing wild-characters, and hence represented by diverse amino acid sequences. The classical lock-and-key or induced-fit/conformational selection mechanism may not cover all aspects of the promiscuous recognition. On the basis of our crystallographic and NMR studies on the mitochondrial Tom20 protein-presequence interaction, we proposed a new hypothetical mechanism based on "a rapid equilibrium of multiple states with partial recognitions". This dynamic, multiple recognition mode enables the Tom20 receptor to recognize diverse mitochondrial presequences with nearly equal affinities. The plant Tom20 is evolutionally unrelated to the animal Tom20 in our study, but is a functional homolog of the animal/fungal Tom20. NMR studies by another research group revealed that the presequence binding by the plant Tom20 was not fully explained by simple interaction modes, suggesting the presence of a similar dynamic, multiple recognition mode. Circumstantial evidence also suggested that similar dynamic mechanisms may be applicable to other promiscuous recognitions of signal peptides by the SRP54/Ffh and SecA proteins.

Method of transmission of dynamic multibit digital images from micro-unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Petrov, E. P.; Kharina, N. L.

2018-01-01

In connection with successful usage of nanotechnologies in remote sensing great attention is paid to the systems in micro-unmanned aerial vehicles (MUAVs) capable to provide high spatial resolution of dynamic multibit digital images (MDI). Limited energy resources on board the MUAV do not allow transferring a large amount of video information in the shortest possible time. It keeps back the broad development of MUAV. The search for methods to shorten the transmission time of dynamic MDIs from MUAV over the radio channel leads to the methods of MDI compression without computational operations onboard the MUAV. The known compression codecs of video information can not be applied because of the limited energy resources. In this paper we propose a method for reducing the transmission time of dynamic MDIs without computational operations and distortions onboard the MUAV. To develop the method a mathematical apparatus of the theory of conditional Markov processes with discrete arguments was used. On its basis a mathematical model for the transformation of the MDI represented by binary images (BI) in the MDI, consisting of groups of neighboring BIs (GBI) transmitted by multiphase (MP) signals, is constructed. The algorithm for multidimensional nonlinear filtering of MP signals is synthesized, realizing the statistical redundancy of the MDI to compensate for the noise stability losses caused by the use of MP signals.

Signal processing and analysis for copper layer thickness measurement within a large variation range in the CMP process.

PubMed

Li, Hongkai; Zhao, Qian; Lu, Xinchun; Luo, Jianbin

2017-11-01

In the copper (Cu) chemical mechanical planarization (CMP) process, accurate determination of a process reaching the end point is of great importance. Based on the eddy current technology, the in situ thickness measurement of the Cu layer is feasible. Previous research studies focus on the application of the eddy current method to the metal layer thickness measurement or endpoint detection. In this paper, an in situ measurement system, which is independently developed by using the eddy current method, is applied to the actual Cu CMP process. A series of experiments are done for further analyzing the dynamic response characteristic of the output signal within different thickness variation ranges. In this study, the voltage difference of the output signal is used to represent the thickness of the Cu layer, and we can extract the voltage difference variations from the output signal fast by using the proposed data processing algorithm. The results show that the voltage difference decreases as thickness decreases in the conventional measurement range and the sensitivity increases at the same time. However, it is also found that there exists a thickness threshold, and the correlation is negative, when the thickness is more than the threshold. Furthermore, it is possible that the in situ measurement system can be used within a larger Cu layer thickness variation range by creating two calibration tables.

Untargeted metabolomics analysis reveals dynamic changes in azelaic acid- and salicylic acid derivatives in LPS-treated Nicotiana tabacum cells.

PubMed

Mhlongo, M I; Tugizimana, F; Piater, L A; Steenkamp, P A; Madala, N E; Dubery, I A

2017-01-22

To counteract biotic stress factors, plants employ multilayered defense mechanisms responsive to pathogen-derived elicitor molecules, and regulated by different phytohormones and signaling molecules. Here, lipopolysaccharide (LPS), a microbe-associated molecular pattern (MAMP) molecule, was used to induce defense responses in Nicotiana tabacum cell suspensions. Intracellular metabolites were extracted with methanol and analyzed using a liquid chromatography-mass spectrometry (UHPLC-qTOF-MS/MS) platform. The generated data were processed and examined with multivariate and univariate statistical tools. The results show time-dependent dynamic changes and accumulation of glycosylated signaling molecules, specifically those of azelaic acid, salicylic acid and methyl-salicylate as contributors to the altered metabolomic state in LPS-treated cells. Copyright © 2016 Elsevier Inc. All rights reserved.

Parametric and non-parametric modeling of short-term synaptic plasticity. Part I: computational study

PubMed Central

Marmarelis, Vasilis Z.; Berger, Theodore W.

2009-01-01

Parametric and non-parametric modeling methods are combined to study the short-term plasticity (STP) of synapses in the central nervous system (CNS). The nonlinear dynamics of STP are modeled by means: (1) previously proposed parametric models based on mechanistic hypotheses and/or specific dynamical processes, and (2) non-parametric models (in the form of Volterra kernels) that transforms the presynaptic signals into postsynaptic signals. In order to synergistically use the two approaches, we estimate the Volterra kernels of the parametric models of STP for four types of synapses using synthetic broadband input–output data. Results show that the non-parametric models accurately and efficiently replicate the input–output transformations of the parametric models. Volterra kernels provide a general and quantitative representation of the STP. PMID:18506609

Bounding filter - A simple solution to lack of exact a priori statistics.

NASA Technical Reports Server (NTRS)

Nahi, N. E.; Weiss, I. M.

1972-01-01

Wiener and Kalman-Bucy estimation problems assume that models describing the signal and noise stochastic processes are exactly known. When this modeling information, i.e., the signal and noise spectral densities for Wiener filter and the signal and noise dynamic system and disturbing noise representations for Kalman-Bucy filtering, is inexactly known, then the filter's performance is suboptimal and may even exhibit apparent divergence. In this paper a system is designed whereby the actual estimation error covariance is bounded by the covariance calculated by the estimator. Therefore, the estimator obtains a bound on the actual error covariance which is not available, and also prevents its apparent divergence.

Seismology of the moon and implications on internal structure, origin and evolution.

NASA Technical Reports Server (NTRS)

Ewing, M.; Latham, G.; Dorman, J.; Press, F.; Sutton, G.; Meissner, R.; Duennebier, F.; Nakamura, Y.; Kovach, R.

1971-01-01

The objective of the passive seismic experiment is to measure vibrations of the lunar surface produced by all natural and artificial sources of seismic energy and to use these data to deduce the internal structure and constitution of the moon and the nature of tectonic processes which may be active within the moon. Lunar seismic signals are discussed together with the sources of these signals, and aspects of lunar structure and dynamics. Seismic signals from approximately 250 natural events and from two man-made impacts have been recorded during seven months of operation of the two seismic stations installed during Apollo missions 11 and 12.

A Full Dynamic Compound Inverse Method for output-only element-level system identification and input estimation from earthquake response signals

NASA Astrophysics Data System (ADS)

Pioldi, Fabio; Rizzi, Egidio

2016-08-01

This paper proposes a new output-only element-level system identification and input estimation technique, towards the simultaneous identification of modal parameters, input excitation time history and structural features at the element-level by adopting earthquake-induced structural response signals. The method, named Full Dynamic Compound Inverse Method (FDCIM), releases strong assumptions of earlier element-level techniques, by working with a two-stage iterative algorithm. Jointly, a Statistical Average technique, a modification process and a parameter projection strategy are adopted at each stage to achieve stronger convergence for the identified estimates. The proposed method works in a deterministic way and is completely developed in State-Space form. Further, it does not require continuous- to discrete-time transformations and does not depend on initialization conditions. Synthetic earthquake-induced response signals from different shear-type buildings are generated to validate the implemented procedure, also with noise-corrupted cases. The achieved results provide a necessary condition to demonstrate the effectiveness of the proposed identification method.

Online Structural-Health Monitoring of Glass Fiber-Reinforced Thermoplastics Using Different Carbon Allotropes in the Interphase.

PubMed

Müller, Michael Thomas; Pötzsch, Hendrik Florian; Gohs, Uwe; Heinrich, Gert

2018-06-25

An electromechanical response behavior is realized by nanostructuring the glass fiber interphase with different highly electrically conductive carbon allotropes like carbon nanotubes (CNT), graphene nanoplatelets (GNP), or conductive carbon black (CB). The operational capability of these multifunctional glass fibers for an online structural-health monitoring is demonstrated in endless glass fiber-reinforced polypropylene. The electromechanical response behavior, during a static or dynamic three-point bending test of various carbon modifications, shows qualitative differences in the signal quality and sensitivity due to the different aspect ratios of the nanoparticles and the associated electrically conductive network densities in the interphase. Depending on the embedding position within the glass fiber-reinforced composite compression, shear and tension loadings of the fibers can be distinguished by different characteristics of the corresponding electrical signal. The occurrence of irreversible signal changes during the dynamic loading can be attributed to filler reorientation processes caused by polymer creeping or by destruction of electrically conductive paths by cracks in the glass fiber interphase.

Notch1-Dll4 signaling and mechanical force regulate leader cell formation during collective cell migration

PubMed Central

Riahi, Reza; Sun, Jian; Wang, Shue; Long, Min; Zhang, Donna D.; Wong, Pak Kin

2015-01-01

At the onset of collective cell migration, a subset of cells within an initially homogenous population acquires a distinct “leader” phenotype with characteristic morphology and motility. However, the factors driving leader cell formation as well as the mechanisms regulating leader cell density during the migration process remain to be determined. Here, we use single cell gene expression analysis and computational modeling to show that leader cell identity is dynamically regulated by Dll4 signaling through both Notch1 and cellular stress in a migrating epithelium. Time-lapse microscopy reveals that Dll4 is induced in leader cells after the creation of the cell-free region and leader cells are regulated via Notch1-Dll4 lateral inhibition. Furthermore, mechanical stress inhibits Dll4 expression and leader cell formation in the monolayer. Collectively, our findings suggest that a reduction of mechanical force near the boundary promotes Notch1-Dll4 signaling to dynamically regulate the density of leader cells during collective cell migration. PMID:25766473

Percolation Model of Sensory Transmission and Loss of Consciousness Under General Anesthesia

NASA Astrophysics Data System (ADS)

Zhou, David W.; Mowrey, David D.; Tang, Pei; Xu, Yan

2015-09-01

Neurons communicate with each other dynamically; how such communications lead to consciousness remains unclear. Here, we present a theoretical model to understand the dynamic nature of sensory activity and information integration in a hierarchical network, in which edges are stochastically defined by a single parameter p representing the percolation probability of information transmission. We validate the model by comparing the transmitted and original signal distributions, and we show that a basic version of this model can reproduce key spectral features clinically observed in electroencephalographic recordings of transitions from conscious to unconscious brain activities during general anesthesia. As p decreases, a steep divergence of the transmitted signal from the original was observed, along with a loss of signal synchrony and a sharp increase in information entropy in a critical manner; this resembles the precipitous loss of consciousness during anesthesia. The model offers mechanistic insights into the emergence of information integration from a stochastic process, laying the foundation for understanding the origin of cognition.

Dynamic protein interaction networks and new structural paradigms in signaling

PubMed Central

Csizmok, Veronika; Follis, Ariele Viacava; Kriwacki, Richard W.; Forman-Kay, Julie D.

2017-01-01

Understanding signaling and other complex biological processes requires elucidating the critical roles of intrinsically disordered proteins and regions (IDPs/IDRs), which represent ~30% of the proteome and enable unique regulatory mechanisms. In this review we describe the structural heterogeneity of disordered proteins that underpins these mechanisms and the latest progress in obtaining structural descriptions of ensembles of disordered proteins that are needed for linking structure and dynamics to function. We describe the diverse interactions of IDPs that can have unusual characteristics such as “ultrasensitivity” and “regulated folding and unfolding”. We also summarize the mounting data showing that large-scale assembly and protein phase separation occurs within a variety of signaling complexes and cellular structures. In addition, we discuss efforts to therapeutically target disordered proteins with small molecules. Overall, we interpret the remodeling of disordered state ensembles due to binding and post-translational modifications within an expanded framework for allostery that provides significant insights into how disordered proteins transmit biological information. PMID:26922996

Inertial processing of vestibulo-ocular signals

NASA Technical Reports Server (NTRS)

Hess, B. J.; Angelaki, D. E.

1999-01-01

New evidence for a central resolution of gravito-inertial signals has been recently obtained by analyzing the properties of the vestibulo-ocular reflex (VOR) in response to combined lateral translations and roll tilts of the head. It is found that the VOR generates robust compensatory horizontal eye movements independent of whether or not the interaural translatory acceleration component is canceled out by a gravitational acceleration component due to simultaneous roll-tilt. This response property of the VOR depends on functional semicircular canals, suggesting that the brain uses both otolith and semicircular canal signals to estimate head motion relative to inertial space. Vestibular information about dynamic head attitude relative to gravity is the basis for computing head (and body) angular velocity relative to inertial space. Available evidence suggests that the inertial vestibular system controls both head attitude and velocity with respect to a gravity-centered reference frame. The basic computational principles underlying the inertial processing of otolith and semicircular canal afferent signals are outlined.

Embryonic expression of the transforming growth factor beta ligand and receptor genes in chicken.

PubMed

Cooley, James R; Yatskievych, Tatiana A; Antin, Parker B

2014-03-01

Transforming growth factor-beta (TGFβ) signaling regulates a myriad of biological processes during embryogenesis, in the adult, and during the manifestation of disease. TGFβ signaling is propagated through one of three TGFβ ligands interacting with Type I and Type II receptors, and Type III co-receptors. Although TGFβ signaling is regulated partly by the combinatorial expression patterns of TGFβ receptors and ligands, a comprehensive gene expression analysis has not been published. Here we report the embryonic mRNA expression patterns in chicken embryos of the canonical TGFβ ligands (TGFB1, TGFB2, and TGFB3) and receptors (TGFBR1, TGFBR2, TGFBR3), plus the Activin A receptor, type 1 (ACVR1) and co receptor Endoglin (ENG) that also transduce TGFβ signaling. TGFB ligands and receptors show dynamic and frequently overlapping expression patterns in numerous embryonic cell layers and structures. Integrating expression information identifies combinations of ligands and receptors that are involved in specific developmental processes including somitogenesis, cardiogenesis and vasculogenesis. Copyright © 2013 Wiley Periodicals, Inc.

Acoustic emission evolution during sliding friction of Hadfield steel single crystal

NASA Astrophysics Data System (ADS)

Lychagin, D. V.; Novitskaya, O. S.; Kolubaev, A. V.; Sizova, O. V.

2017-12-01

Friction is a complex dynamic process. Direct observation of processes occurring in the friction zone is impossible due to a small size of a real contact area and, as a consequence, requires various additional methods applicable to monitor a tribological contact state. One of such methods consists in the analysis of acoustic emission data of a tribological contact. The use of acoustic emission entails the problem of interpreting physical sources of signals. In this paper, we analyze the evolution of acoustic emission signal frames in friction of Hadfield steel single crystals. The chosen crystallographic orientation of single crystals enables to identify four stages related to friction development as well as acoustic emission signals inherent in these stages. Acoustic emission signal parameters are studied in more detail by the short-time Fourier transform used to determine the time variation of the median frequency and its power spectrum. The results obtained will facilitate the development of a more precise method to monitor the tribological contact based on the acoustic emission method.

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

PubMed

Kappel, David; Legenstein, Robert; Habenschuss, Stefan; Hsieh, Michael; Maass, Wolfgang

2018-01-01

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is at least as large as the component that depends on the history of pre- and postsynaptic neural activity. These data are inconsistent with common models for network plasticity and raise the following questions: how can neural circuits maintain a stable computational function in spite of these continuously ongoing processes, and what could be functional uses of these ongoing processes? Here, we present a rigorous theoretical framework for these seemingly stochastic spine dynamics and rewiring processes in the context of reward-based learning tasks. We show that spontaneous synapse-autonomous processes, in combination with reward signals such as dopamine, can explain the capability of networks of neurons in the brain to configure themselves for specific computational tasks, and to compensate automatically for later changes in the network or task. Furthermore, we show theoretically and through computer simulations that stable computational performance is compatible with continuously ongoing synapse-autonomous changes. After reaching good computational performance it causes primarily a slow drift of network architecture and dynamics in task-irrelevant dimensions, as observed for neural activity in motor cortex and other areas. On the more abstract level of reinforcement learning the resulting model gives rise to an understanding of reward-driven network plasticity as continuous sampling of network configurations.

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning

PubMed Central

Habenschuss, Stefan; Hsieh, Michael

2018-01-01

Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is at least as large as the component that depends on the history of pre- and postsynaptic neural activity. These data are inconsistent with common models for network plasticity and raise the following questions: how can neural circuits maintain a stable computational function in spite of these continuously ongoing processes, and what could be functional uses of these ongoing processes? Here, we present a rigorous theoretical framework for these seemingly stochastic spine dynamics and rewiring processes in the context of reward-based learning tasks. We show that spontaneous synapse-autonomous processes, in combination with reward signals such as dopamine, can explain the capability of networks of neurons in the brain to configure themselves for specific computational tasks, and to compensate automatically for later changes in the network or task. Furthermore, we show theoretically and through computer simulations that stable computational performance is compatible with continuously ongoing synapse-autonomous changes. After reaching good computational performance it causes primarily a slow drift of network architecture and dynamics in task-irrelevant dimensions, as observed for neural activity in motor cortex and other areas. On the more abstract level of reinforcement learning the resulting model gives rise to an understanding of reward-driven network plasticity as continuous sampling of network configurations. PMID:29696150

Manipulating Models and Grasping the Ideas They Represent

ERIC Educational Resources Information Center

Bryce, T. G.; Blown, E. J.

2016-01-01

This article notes the convergence of recent thinking in neuroscience and grounded cognition regarding the way we understand mental representation and recollection: ideas are dynamic and multi-modal, actively created at the point of recall. Also, neurophysiologically, re-entrant signalling among cortical circuits allows non-conscious processing to…

Course Modules on Structural Health Monitoring with Smart Materials

ERIC Educational Resources Information Center

Shih, Hui-Ru; Walters, Wilbur L.; Zheng, Wei; Everett, Jessica

2009-01-01

Structural Health Monitoring (SHM) is an emerging technology that has multiple applications. SHM emerged from the wide field of smart structures, and it also encompasses disciplines such as structural dynamics, materials and structures, nondestructive testing, sensors and actuators, data acquisition, signal processing, and possibly much more. To…

Beyond histones - the expanding roles of protein lysine methylation.

PubMed

Wu, Zhouran; Connolly, Justin; Biggar, Kyle K

2017-09-01

A robust signaling network is essential for cell survival. At the molecular level, this is often mediated by as many as 200 different types of post-translational modifications (PTMs) that are made to proteins. These include well-documented examples such as phosphorylation, ubiquitination, acetylation and methylation. Of these modifications, non-histone protein lysine methylation has only recently emerged as a prevalent modification occurring on numerous proteins, thus extending its role well beyond the histone code. To date, this modification has been found to regulate protein activity, protein-protein interactions and interplay with other PTMs. As a result, lysine methylation is now known to be a coordinator of protein function and is a key driver in several cellular signaling events. Recent advances in mass spectrometry have also allowed the characterization of a growing number of lysine methylation events on an increasing number of proteins. As a result, we are now beginning to recognize lysine methylation as a dynamic event that is involved in a number of biological processes, including DNA damage repair, cell growth, metabolism and signal transduction among others. In light of current research advances, the stage is now set to study the extent of lysine methylation that exists within the entire proteome, its dynamics, and its association with physiological and pathological processes. © 2017 Federation of European Biochemical Societies.

Analysis of cardiovascular regulation.

PubMed

Wilhelm, F H; Grossman, P; Roth, W T

1999-01-01

Adequate characterization of hemodynamic and autonomic responses to physical and mental stress can elucidate underlying mechanisms of cardiovascular disease or anxiety disorders. We developed a physiological signal processing system for analysis of continuously recorded ECG, arterial blood pressure (BP), and respiratory signals using the programming language Matlab. Data collection devices are a 16-channel digital, physiological recorder (Vitaport), a finger arterial pressure transducer (Finapres), and a respiratory inductance plethysmograph (Respitrace). Besides the conventional analysis of the physiological channels, power spectral density and transfer functions of respiration, heart rate, and blood pressure variability are used to characterize respiratory sinus arrhythmia (RSA), 0.10-Hz BP oscillatory activity (Mayer-waves), and baroreflex sensitivity. The arterial pressure transducer waveforms permit noninvasive estimation of stroke volume, cardiac output, and systemic vascular resistance. Time trends in spectral composition of indices are assessed using complex demodulation. Transient dynamic changes of cardiovascular parameters at the onset of stress and recovery periods are quantified using a regression breakpoint model that optimizes piecewise linear curve fitting. Approximate entropy (ApEn) is computed to quantify the degree of chaos in heartbeat dynamics. Using our signal processing system we found distinct response patterns in subgroups of patients with coronary artery disease or anxiety disorders, which were related to specific pharmacological and behavioral factors.

Experimental Evaluation of the High-Speed Motion Vector Measurement by Combining Synthetic Aperture Array Processing with Constrained Least Square Method

NASA Astrophysics Data System (ADS)

Yokoyama, Ryouta; Yagi, Shin-ichi; Tamura, Kiyoshi; Sato, Masakazu

2009-07-01

Ultrahigh speed dynamic elastography has promising potential capabilities in applying clinical diagnosis and therapy of living soft tissues. In order to realize the ultrahigh speed motion tracking at speeds of over thousand frames per second, synthetic aperture (SA) array signal processing technology must be introduced. Furthermore, the overall system performance should overcome the fine quantitative evaluation in accuracy and variance of echo phase changes distributed across a tissue medium. On spatial evaluation of local phase changes caused by pulsed excitation on a tissue phantom, investigation was made with the proposed SA signal system utilizing different virtual point sources that were generated by an array transducer to probe each component of local tissue displacement vectors. The final results derived from the cross-correlation method (CCM) brought about almost the same performance as obtained by the constrained least square method (LSM) extended to successive echo frames. These frames were reconstructed by SA processing after the real-time acquisition triggered by the pulsed irradiation from a point source. The continuous behavior of spatial motion vectors demonstrated the dynamic generation and traveling of the pulsed shear wave at a speed of one thousand frames per second.

Inhomogeneous Point-Processes to Instantaneously Assess Affective Haptic Perception through Heartbeat Dynamics Information

PubMed Central

Valenza, G.; Greco, A.; Citi, L.; Bianchi, M.; Barbieri, R.; Scilingo, E. P.

2016-01-01

This study proposes the application of a comprehensive signal processing framework, based on inhomogeneous point-process models of heartbeat dynamics, to instantaneously assess affective haptic perception using electrocardiogram-derived information exclusively. The framework relies on inverse-Gaussian point-processes with Laguerre expansion of the nonlinear Wiener-Volterra kernels, accounting for the long-term information given by the past heartbeat events. Up to cubic-order nonlinearities allow for an instantaneous estimation of the dynamic spectrum and bispectrum of the considered cardiovascular dynamics, as well as for instantaneous measures of complexity, through Lyapunov exponents and entropy. Short-term caress-like stimuli were administered for 4.3–25 seconds on the forearms of 32 healthy volunteers (16 females) through a wearable haptic device, by selectively superimposing two levels of force, 2 N and 6 N, and two levels of velocity, 9.4 mm/s and 65 mm/s. Results demonstrated that our instantaneous linear and nonlinear features were able to finely characterize the affective haptic perception, with a recognition accuracy of 69.79% along the force dimension, and 81.25% along the velocity dimension. PMID:27357966

Linear friction weld process monitoring of fixture cassette deformations using empirical mode decomposition

NASA Astrophysics Data System (ADS)

Bakker, O. J.; Gibson, C.; Wilson, P.; Lohse, N.; Popov, A. A.

2015-10-01

Due to its inherent advantages, linear friction welding is a solid-state joining process of increasing importance to the aerospace, automotive, medical and power generation equipment industries. Tangential oscillations and forge stroke during the burn-off phase of the joining process introduce essential dynamic forces, which can also be detrimental to the welding process. Since burn-off is a critical phase in the manufacturing stage, process monitoring is fundamental for quality and stability control purposes. This study aims to improve workholding stability through the analysis of fixture cassette deformations. Methods and procedures for process monitoring are developed and implemented in a fail-or-pass assessment system for fixture cassette deformations during the burn-off phase. Additionally, the de-noised signals are compared to results from previous production runs. The observed deformations as a consequence of the forces acting on the fixture cassette are measured directly during the welding process. Data on the linear friction-welding machine are acquired and de-noised using empirical mode decomposition, before the burn-off phase is extracted. This approach enables a direct, objective comparison of the signal features with trends from previous successful welds. The capacity of the whole process monitoring system is validated and demonstrated through the analysis of a large number of signals obtained from welding experiments.

Estimating the Contribution of Dynamical Ejecta in the Kilonova Associated with GW170817

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Afrough, M.; Agarwal, B.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allen, G.; Allocca, A.; Altin, P. A.; Amato, A.; Ananyeva, A.; Anderson, S. B.; Anderson, W. G.; Angelova, S. V.; Antier, S.; Appert, S.; Arai, K.; Araya, M. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Atallah, D. V.; Aufmuth, P.; Aulbert, C.; AultONeal, K.; Austin, C.; Avila-Alvarez, A.; Babak, S.; Bacon, P.; Bader, M. K. M.; Bae, S.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Banagiri, S.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, D.; Barkett, K.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Bawaj, M.; Bayley, J. C.; Bazzan, M.; Bécsy, B.; Beer, C.; Bejger, M.; Belahcene, I.; Bell, A. S.; Bergmann, G.; Bernuzzi, S.; Bero, J. J.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Billman, C. R.; Birch, J.; Birney, R.; Birnholtz, O.; Biscans, S.; Biscoveanu, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackman, J.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Bode, N.; Boer, M.; Bogaert, G.; Bohe, A.; Bondu, F.; Bonilla, E.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bossie, K.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Broida, J. E.; Brooks, A. F.; Brown, D. D.; Brunett, S.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cabero, M.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderón Bustillo, J.; Callister, T. A.; Calloni, E.; Camp, J. B.; Canepa, M.; Canizares, P.; Cannon, K. C.; Cao, H.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Carney, M. F.; Casanueva Diaz, J.; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Cerdá-Durán, P.; Cerretani, G.; Cesarini, E.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chase, E.; Chassande-Mottin, E.; Chatterjee, D.; Chatziioannou, K.; Cheeseboro, B. D.; Chen, H. Y.; Chen, X.; Chen, Y.; Cheng, H.-P.; Chia, H.; Chincarini, A.; Chiummo, A.; Chmiel, T.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, A. J. K.; Chua, S.; Chung, A. K. W.; Chung, S.; Ciani, G.; Ciolfi, R.; Cirelli, C. E.; Cirone, A.; Clara, F.; Clark, J. A.; Clearwater, P.; Cleva, F.; Cocchieri, C.; Coccia, E.; Cohadon, P.-F.; Cohen, D.; Colla, A.; Collette, C. G.; Cominsky, L. R.; Constancio, M., Jr.; Conti, L.; Cooper, S. J.; Corban, P.; Corbitt, T. R.; Cordero-Carrión, I.; Corley, K. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Covas, P. B.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Creighton, J. D. E.; Creighton, T. D.; Cripe, J.; Crowder, S. G.; Cullen, T. J.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dal Canton, T.; Dálya, G.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dasgupta, A.; Da Silva Costa, C. F.; Dattilo, V.; Dave, I.; Davier, M.; Davis, D.; Daw, E. J.; Day, B.; De, S.; DeBra, D.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Demos, N.; Denker, T.; Dent, T.; De Pietri, R.; Dergachev, V.; De Rosa, R.; DeRosa, R. T.; De Rossi, C.; DeSalvo, R.; de Varona, O.; Devenson, J.; Dhurandhar, S.; Díaz, M. C.; Dietrich, T.; Di Fiore, L.; Di Giovanni, M.; Di Girolamo, T.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Renzo, F.; Doctor, Z.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorrington, I.; Douglas, R.; Dovale Álvarez, M.; Downes, T. P.; Drago, M.; Dreissigacker, C.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dupej, P.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Eisenstein, R. A.; Essick, R. C.; Estevez, D.; Etienne, Z. B.; Etzel, T.; Evans, M.; Evans, T. M.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Farinon, S.; Farr, B.; Farr, W. M.; Fauchon-Jones, E. J.; Favata, M.; Fays, M.; Fee, C.; Fehrmann, H.; Feicht, J.; Fejer, M. M.; Fernandez-Galiana, A.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Finstad, D.; Fiori, I.; Fiorucci, D.; Fishbach, M.; Fisher, R. P.; Fitz-Axen, M.; Flaminio, R.; Fletcher, M.; Fong, H.; Font, J. A.; Forsyth, P. W. F.; Forsyth, S. S.; Fournier, J.-D.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fries, E. M.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H.; Gadre, B. U.; Gaebel, S. M.; Gair, J. R.; Gammaitoni, L.; Ganija, M. R.; Gaonkar, S. G.; Garcia-Quiros, C.; Garufi, F.; Gateley, B.; Gaudio, S.; Gaur, G.; Gayathri, V.; Gehrels, N.; Gemme, G.; Genin, E.; Gennai, A.; George, D.; George, J.; Gergely, L.; Germain, V.; Ghonge, S.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glover, L.; Goetz, E.; Goetz, R.; Gomes, S.; Goncharov, B.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Grado, A.; Graef, C.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Gretarsson, E. M.; Groot, P.; Grote, H.; Grunewald, S.; Gruning, P.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Halim, O.; Hall, B. R.; Hall, E. D.; Hamilton, E. Z.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hannuksela, O. A.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Haster, C.-J.; Haughian, K.; Healy, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hinderer, T.; Hoak, D.; Hofman, D.; Holt, K.; Holz, D. E.; Hopkins, P.; Horst, C.; Hough, J.; Houston, E. A.; Howell, E. J.; Hreibi, A.; Hu, Y. M.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Indik, N.; Inta, R.; Intini, G.; Isa, H. N.; Isac, J.-M.; Isi, M.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W. W.; Johnson-McDaniel, N. K.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Junker, J.; Kalaghatgi, C. V.; Kalogera, V.; Kamai, B.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kapadia, S. J.; Karki, S.; Karvinen, K. S.; Kasprzack, M.; Kastaun, W.; Katolik, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kawabe, K.; Kawaguchi, K.; Kéfélian, F.; Keitel, D.; Kemball, A. J.; Kennedy, R.; Kent, C.; Key, J. S.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, Chunglee; Kim, J. C.; Kim, K.; Kim, W.; Kim, W. S.; Kim, Y.-M.; Kimbrell, S. J.; King, E. J.; King, P. J.; Kinley-Hanlon, M.; Kirchhoff, R.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Knowles, T. D.; Koch, P.; Koehlenbeck, S. M.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Krämer, C.; Kringel, V.; Królak, A.; Kuehn, G.; Kumar, P.; Kumar, R.; Kumar, S.; Kuo, L.; Kutynia, A.; Kwang, S.; Lackey, B. D.; Lai, K. H.; Landry, M.; Lang, R. N.; Lange, J.; Lantz, B.; Lanza, R. K.; Larson, S. L.; Lartaux-Vollard, A.; Lasky, P. D.; Laxen, M.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, H. W.; Lee, K.; Lehmann, J.; Lenon, A.; Leonardi, M.; Leroy, N.; Letendre, N.; Levin, Y.; Li, T. G. F.; Linker, S. D.; Littenberg, T. B.; Liu, J.; Liu, X.; Lo, R. K. L.; Lockerbie, N. A.; London, L. T.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lousto, C. O.; Lovelace, G.; Lück, H.; Lumaca, D.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Macas, R.; Macfoy, S.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña Hernandez, I.; Magaña-Sandoval, F.; Magaña Zertuche, L.; Magee, R. M.; Majorana, E.; Maksimovic, I.; Man, N.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markakis, C.; Markosyan, A. S.; Markowitz, A.; Maros, E.; Marquina, A.; Martelli, F.; Martellini, L.; Martin, I. W.; Martin, R. M.; Martynov, D. V.; Mason, K.; Massera, E.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Mastrogiovanni, S.; Matas, A.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McCuller, L.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McNeill, L.; McRae, T.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Mehmet, M.; Meidam, J.; Mejuto-Villa, E.; Melatos, A.; Mendell, G.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Metzdorff, R.; Meyers, P. M.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, A. L.; Miller, B. B.; Miller, J.; Millhouse, M.; Milovich-Goff, M. C.; Minazzoli, O.; Minenkov, Y.; Ming, J.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moffa, D.; Moggi, A.; Mogushi, K.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mours, B.; Mow-Lowry, C. M.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Muñiz, E. A.; Muratore, M.; Murray, P. G.; Napier, K.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Neilson, J.; Nelemans, G.; Nelson, T. J. N.; Nery, M.; Neunzert, A.; Nevin, L.; Newport, J. M.; Newton, G.; Ng, K. K. Y.; Nguyen, T. T.; Nichols, D.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Noack, A.; Nocera, F.; Nolting, D.; North, C.; Nuttall, L. K.; Oberling, J.; O'Dea, G. D.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Okada, M. A.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; Ormiston, R.; Ortega, L. F.; O'Shaughnessy, R.; Ossokine, S.; Ottaway, D. J.; Overmier, H.; Owen, B. J.; Pace, A. E.; Page, J.; Page, M. A.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, Howard; Pan, Huang-Wei; Pang, B.; Pang, P. T. H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Parida, A.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patil, M.; Patricelli, B.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perez, C. J.; Perreca, A.; Perri, L. M.; Pfeiffer, H. P.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pirello, M.; Pitkin, M.; Poe, M.; Poggiani, R.; Popolizio, P.; Porter, E. K.; Post, A.; Powell, J.; Prasad, J.; Pratt, J. W. W.; Pratten, G.; Predoi, V.; Prestegard, T.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rajan, C.; Rajbhandari, B.; Rakhmanov, M.; Ramirez, K. E.; Ramos-Buades, A.; Rapagnani, P.; Raymond, V.; Razzano, M.; Read, J.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Ren, W.; Reyes, S. D.; Ricci, F.; Ricker, P. M.; Rieger, S.; Riles, K.; Rizzo, M.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, R.; Romel, C. L.; Romie, J. H.; Rosińska, D.; Ross, M. P.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Rutins, G.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Sakellariadou, M.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sampson, L. M.; Sanchez, E. J.; Sanchez, L. E.; Sanchis-Gual, N.; Sandberg, V.; Sanders, J. R.; Sassolas, B.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Scheel, M.; Scheuer, J.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schulte, B. W.; Schutz, B. F.; Schwalbe, S. G.; Scott, J.; Scott, S. M.; Seidel, E.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Shaddock, D. A.; Shaffer, T. J.; Shah, A. A.; Shahriar, M. S.; Shaner, M. B.; Shao, L.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sieniawska, M.; Sigg, D.; Silva, A. D.; Singer, L. P.; Singh, A.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, B.; Smith, J. R.; Smith, R. J. E.; Somala, S.; Son, E. J.; Sonnenberg, J. A.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Spencer, A. P.; Srivastava, A. K.; Staats, K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stevenson, S. P.; Stone, R.; Stops, D. J.; Strain, K. A.; Stratta, G.; Strigin, S. E.; Strunk, A.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sunil, S.; Suresh, J.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.; Tait, S. C.; Talbot, C.; Talukder, D.; Tanner, D. B.; Tápai, M.; Taracchini, A.; Tasson, J. D.; Taylor, J. A.; Taylor, R.; Tewari, S. V.; Theeg, T.; Thies, F.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Toland, K.; Tonelli, M.; Tornasi, Z.; Torres-Forné, A.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trinastic, J.; Tringali, M. C.; Trozzo, L.; Tsang, K. W.; Tse, M.; Tso, R.; Tsukada, L.; Tsuna, D.; Tuyenbayev, D.; Ueno, K.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Varma, V.; Vass, S.; Vasúth, M.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Venugopalan, G.; Verkindt, D.; Vetrano, F.; Viceré, A.; Viets, A. D.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walet, R.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, J. Z.; Wang, W. H.; Wang, Y. F.; Ward, R. L.; Warner, J.; Was, M.; Watchi, J.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.; Wessel, E. K.; Weßels, P.; Westerweck, J.; Westphal, T.; Wette, K.; Whelan, J. T.; Whiting, B. F.; Whittle, C.; Wilken, D.; Williams, D.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Woehler, J.; Wofford, J.; Wong, K. W. K.; Worden, J.; Wright, J. L.; Wu, D. S.; Wysocki, D. M.; Xiao, S.; Yamamoto, H.; Yancey, C. C.; Yang, L.; Yap, M. J.; Yazback, M.; Yu, Hang; Yu, Haocun; Yvert, M.; Zadrożny, A.; Zanolin, M.; Zelenova, T.; Zendri, J.-P.; Zevin, M.; Zhang, L.; Zhang, M.; Zhang, T.; Zhang, Y.-H.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, S. J.; Zhu, X. J.; Zimmerman, A. B.; Zucker, M. E.; Zweizig, J.; (LIGO Scientific Collaboration; Virgo Collaboration

2017-12-01

The source of the gravitational-wave (GW) signal GW170817, very likely a binary neutron star merger, was also observed electromagnetically, providing the first multi-messenger observations of this type. The two-week-long electromagnetic (EM) counterpart had a signature indicative of an r-process-induced optical transient known as a kilonova. This Letter examines how the mass of the dynamical ejecta can be estimated without a direct electromagnetic observation of the kilonova, using GW measurements and a phenomenological model calibrated to numerical simulations of mergers with dynamical ejecta. Specifically, we apply the model to the binary masses inferred from the GW measurements, and use the resulting mass of the dynamical ejecta to estimate its contribution (without the effects of wind ejecta) to the corresponding kilonova light curves from various models. The distributions of dynamical ejecta mass range between {M}{ej}={10}-3-{10}-2 {M}⊙ for various equations of state, assuming that the neutron stars are rotating slowly. In addition, we use our estimates of the dynamical ejecta mass and the neutron star merger rates inferred from GW170817 to constrain the contribution of events like this to the r-process element abundance in the Galaxy when ejecta mass from post-merger winds is neglected. We find that if ≳10% of the matter dynamically ejected from binary neutron star (BNS) mergers is converted to r-process elements, GW170817-like BNS mergers could fully account for the amount of r-process material observed in the Milky Way.

Acoustic Signal Processing in Photorefractive Optical Systems.

NASA Astrophysics Data System (ADS)

Zhou, Gan

This thesis discusses applications of the photorefractive effect in the context of acoustic signal processing. The devices and systems presented here illustrate the ideas and optical principles involved in holographic processing of acoustic information. The interest in optical processing stems from the similarities between holographic optical systems and contemporary models for massively parallel computation, in particular, neural networks. An initial step in acoustic processing is the transformation of acoustic signals into relevant optical forms. A fiber-optic transducer with photorefractive readout transforms acoustic signals into optical images corresponding to their short-time spectrum. The device analyzes complex sound signals and interfaces them with conventional optical correlators. The transducer consists of 130 multimode optical fibers sampling the spectral range of 100 Hz to 5 kHz logarithmically. A physical model of the human cochlea can help us understand some characteristics of human acoustic transduction and signal representation. We construct a life-sized cochlear model using elastic membranes coupled with two fluid-filled chambers, and use a photorefractive novelty filter to investigate its response. The detection sensitivity is determined to be 0.3 angstroms per root Hz at 2 kHz. Qualitative agreement is found between the model response and physiological data. Delay lines map time-domain signals into space -domain and permit holographic processing of temporal information. A parallel optical delay line using dynamic beam coupling in a rotating photorefractive crystal is presented. We experimentally demonstrate a 64 channel device with 0.5 seconds of time-delay and 167 Hz bandwidth. Acoustic signal recognition is described in a photorefractive system implementing the time-delay neural network model. The system consists of a photorefractive optical delay-line and a holographic correlator programmed in a LiNbO_3 crystal. We demonstrate the recognition of synthesized chirps as well as spoken words. A photorefractive ring resonator containing an optical delay line can learn temporal information through self-organization. We experimentally investigate a system that learns by itself and picks out the most-frequently -presented signals from the input. We also give results demonstrating the separation of two orthogonal temporal signals into two competing ring resonators.

Acoustic wavefield and Mach wave radiation of flashing arcs in strombolian explosion measured by image luminance

NASA Astrophysics Data System (ADS)

Genco, Riccardo; Ripepe, Maurizio; Marchetti, Emanuele; Bonadonna, Costanza; Biass, Sebastien

2014-10-01

Explosive activity often generates visible flashing arcs in the volcanic plume considered as the evidence of the shock-front propagation induced by supersonic dynamics. High-speed image processing is used to visualize the pressure wavefield associated with flashing arcs observed in strombolian explosions. Image luminance is converted in virtual acoustic signal compatible with the signal recorded by pressure transducer. Luminance variations are moving with a spherical front at a 344.7 m/s velocity. Flashing arcs travel at the sound speed already 14 m above the vent and are not necessarily the evidence of a supersonic explosive dynamics. However, seconds later, the velocity of small fragments increases, and the spherical acousto-luminance wavefront becomes planar recalling the Mach wave radiation generated by large scale turbulence in high-speed jet. This planar wavefront forms a Mach angle of 55° with the explosive jet axis, suggesting an explosive dynamics moving at Mo = 1.22 Mach number.

Analytical and numerical analysis of imaging mechanism of dynamic scanning electron microscopy.

PubMed

Schröter, M-A; Holschneider, M; Sturm, H

2012-11-02

The direct observation of small oscillating structures with the help of a scanning electron beam is a new approach to study the vibrational dynamics of cantilevers and microelectromechanical systems. In the scanning electron microscope, the conventional signal of secondary electrons (SE, dc part) is separated from the signal response of the SE detector, which is correlated to the respective excitation frequency for vibration by means of a lock-in amplifier. The dynamic response is separated either into images of amplitude and phase shift or into real and imaginary parts. Spatial resolution is limited to the diameter of the electron beam. The sensitivity limit to vibrational motion is estimated to be sub-nanometer for high integration times. Due to complex imaging mechanisms, a theoretical model was developed for the interpretation of the obtained measurements, relating cantilever shapes to interaction processes consisting of incident electron beam, electron-lever interaction, emitted electrons and detector response. Conclusions drawn from this new model are compared with numerical results based on the Euler-Bernoulli equation.

Dynamic Receptor Team Formation Can Explain the High Signal Transduction Gain in Escherichia coli

PubMed Central

Albert, Réka; Chiu, Yu-wen; Othmer, Hans G.

2004-01-01

Evolution has provided many organisms with sophisticated sensory systems that enable them to respond to signals in their environment. The response frequently involves alteration in the pattern of movement, either by directed movement, a process called taxis, or by altering the speed or frequency of turning, which is called kinesis. Chemokinesis has been most thoroughly studied in the peritrichous bacterium Escherichia coli, which has four helical flagella distributed over the cell surface, and swims by rotating them. When rotated counterclockwise the flagella coalesce into a propulsive bundle, producing a relatively straight “run,” and when rotated clockwise they fly apart, resulting in a “tumble” which reorients the cell with little translocation. A stochastic process generates the runs and tumbles, and in a chemoeffector gradient, runs that carry the cell in a favorable direction are extended. The cell senses spatial gradients as temporal changes in receptor occupancy and changes the probability of counterclockwise rotation (the bias) on a fast timescale, but adaptation returns the bias to baseline on a slow timescale, enabling the cell to detect and respond to further concentration changes. The overall structure of the signal transduction pathways is well characterized in E. coli, but important details are still not understood. Only recently has a source of gain in the signal transduction network been identified experimentally, and here we present a mathematical model based on dynamic assembly of receptor teams that can explain this observation. PMID:15111386

Dynamic receptor team formation can explain the high signal transduction gain in Escherichia coli.

PubMed

Albert, Réka; Chiu, Yu-Wen; Othmer, Hans G

2004-05-01

Evolution has provided many organisms with sophisticated sensory systems that enable them to respond to signals in their environment. The response frequently involves alteration in the pattern of movement, either by directed movement, a process called taxis, or by altering the speed or frequency of turning, which is called kinesis. Chemokinesis has been most thoroughly studied in the peritrichous bacterium Escherichia coli, which has four helical flagella distributed over the cell surface, and swims by rotating them. When rotated counterclockwise the flagella coalesce into a propulsive bundle, producing a relatively straight "run," and when rotated clockwise they fly apart, resulting in a "tumble" which reorients the cell with little translocation. A stochastic process generates the runs and tumbles, and in a chemoeffector gradient, runs that carry the cell in a favorable direction are extended. The cell senses spatial gradients as temporal changes in receptor occupancy and changes the probability of counterclockwise rotation (the bias) on a fast timescale, but adaptation returns the bias to baseline on a slow timescale, enabling the cell to detect and respond to further concentration changes. The overall structure of the signal transduction pathways is well characterized in E. coli, but important details are still not understood. Only recently has a source of gain in the signal transduction network been identified experimentally, and here we present a mathematical model based on dynamic assembly of receptor teams that can explain this observation.

Dynamic neural activity during stress signals resilient coping

PubMed Central

Sinha, Rajita; Lacadie, Cheryl M.; Constable, R. Todd; Seo, Dongju

2016-01-01

Active coping underlies a healthy stress response, but neural processes supporting such resilient coping are not well-known. Using a brief, sustained exposure paradigm contrasting highly stressful, threatening, and violent stimuli versus nonaversive neutral visual stimuli in a functional magnetic resonance imaging (fMRI) study, we show significant subjective, physiologic, and endocrine increases and temporally related dynamically distinct patterns of neural activation in brain circuits underlying the stress response. First, stress-specific sustained increases in the amygdala, striatum, hypothalamus, midbrain, right insula, and right dorsolateral prefrontal cortex (DLPFC) regions supported the stress processing and reactivity circuit. Second, dynamic neural activation during stress versus neutral runs, showing early increases followed by later reduced activation in the ventrolateral prefrontal cortex (VLPFC), dorsal anterior cingulate cortex (dACC), left DLPFC, hippocampus, and left insula, suggested a stress adaptation response network. Finally, dynamic stress-specific mobilization of the ventromedial prefrontal cortex (VmPFC), marked by initial hypoactivity followed by increased VmPFC activation, pointed to the VmPFC as a key locus of the emotional and behavioral control network. Consistent with this finding, greater neural flexibility signals in the VmPFC during stress correlated with active coping ratings whereas lower dynamic activity in the VmPFC also predicted a higher level of maladaptive coping behaviors in real life, including binge alcohol intake, emotional eating, and frequency of arguments and fights. These findings demonstrate acute functional neuroplasticity during stress, with distinct and separable brain networks that underlie critical components of the stress response, and a specific role for VmPFC neuroflexibility in stress-resilient coping. PMID:27432990

Harnessing Proteasome Dynamics and Allostery in Drug Design

PubMed Central

Osmulski, Pawel A.

2014-01-01

Abstract Significance: The proteasome is the essential protease that is responsible for regulated cleavage of the bulk of intracellular proteins. Its central role in cellular physiology has been exploited in therapies against aggressive cancers where proteasome-specific competitive inhibitors that block proteasome active centers are very effectively used. However, drugs regulating this essential protease are likely to have broader clinical usefulness. The non-catalytic sites of the proteasome emerge as an attractive alternative target in search of highly specific and diverse proteasome regulators. Recent Advances: Crystallographic models of the proteasome leave the false impression of fixed structures with minimal molecular dynamics lacking long-distance allosteric signaling. However, accumulating biochemical and structural observations strongly support the notion that the proteasome is regulated by precise allosteric interactions arising from protein dynamics, encouraging the active search for allosteric regulators. Here, we discuss properties of several promising compounds that affect substrate gating and processing in antechambers, and interactions of the catalytic core with regulatory proteins. Critical Issues: Given the structural complexity of proteasome assemblies, it is a painstaking process to better understand their allosteric regulation and molecular dynamics. Here, we discuss the challenges and achievements in this field. We place special emphasis on the role of atomic force microscopy imaging in probing the allostery and dynamics of the proteasome, and in dissecting the mechanisms involving small-molecule allosteric regulators. Future Directions: New small-molecule allosteric regulators may become a next generation of drugs targeting the proteasome, which is critical to the development of new therapies in cancers and other diseases. Antioxid. Redox Signal. 21, 2286–2301. PMID:24410482

Dual-Schemata Model

NASA Astrophysics Data System (ADS)

Taniguchi, Tadahiro; Sawaragi, Tetsuo

In this paper, a new machine-learning method, called Dual-Schemata model, is presented. Dual-Schemata model is a kind of self-organizational machine learning methods for an autonomous robot interacting with an unknown dynamical environment. This is based on Piaget's Schema model, that is a classical psychological model to explain memory and cognitive development of human beings. Our Dual-Schemata model is developed as a computational model of Piaget's Schema model, especially focusing on sensori-motor developing period. This developmental process is characterized by a couple of two mutually-interacting dynamics; one is a dynamics formed by assimilation and accommodation, and the other dynamics is formed by equilibration and differentiation. By these dynamics schema system enables an agent to act well in a real world. This schema's differentiation process corresponds to a symbol formation process occurring within an autonomous agent when it interacts with an unknown, dynamically changing environment. Experiment results obtained from an autonomous facial robot in which our model is embedded are presented; an autonomous facial robot becomes able to chase a ball moving in various ways without any rewards nor teaching signals from outside. Moreover, emergence of concepts on the target movements within a robot is shown and discussed in terms of fuzzy logics on set-subset inclusive relationships.

Dynamic Agent Classification and Tracking Using an Ad Hoc Mobile Acoustic Sensor Network

NASA Astrophysics Data System (ADS)

Friedlander, David; Griffin, Christopher; Jacobson, Noah; Phoha, Shashi; Brooks, Richard R.

2003-12-01

Autonomous networks of sensor platforms can be designed to interact in dynamic and noisy environments to determine the occurrence of specified transient events that define the dynamic process of interest. For example, a sensor network may be used for battlefield surveillance with the purpose of detecting, identifying, and tracking enemy activity. When the number of nodes is large, human oversight and control of low-level operations is not feasible. Coordination and self-organization of multiple autonomous nodes is necessary to maintain connectivity and sensor coverage and to combine information for better understanding the dynamics of the environment. Resource conservation requires adaptive clustering in the vicinity of the event. This paper presents methods for dynamic distributed signal processing using an ad hoc mobile network of microsensors to detect, identify, and track targets in noisy environments. They seamlessly integrate data from fixed and mobile platforms and dynamically organize platforms into clusters to process local data along the trajectory of the targets. Local analysis of sensor data is used to determine a set of target attribute values and classify the target. Sensor data from a field test in the Marine base at Twentynine Palms, Calif, was analyzed using the techniques described in this paper. The results were compared to "ground truth" data obtained from GPS receivers on the vehicles.

Angular analysis of the cyclic impacting oscillations in a robotic grinding process

NASA Astrophysics Data System (ADS)

Rafieian, Farzad; Girardin, François; Liu, Zhaoheng; Thomas, Marc; Hazel, Bruce

2014-02-01

In a robotic machining process, a light-weight cutter or grinder is usually held by an articulated robot arm. Material removal is achieved by the rotating cutting tool while the robot end effector ensures that the tool follows a programmed trajectory in order to work on complex curved surfaces or to access hard-to-reach areas. One typical application of such process is maintenance and repair work on hydropower equipment. This paper presents an experimental study of the dynamic characteristics of material removal in robotic grinding, which is unlike conventional grinding due to the lower structural stiffness of the tool-holder robot. The objective of the study is to explore the cyclic nature of this mechanical operation to provide the basis for future development of better process control strategies. Grinding tasks that minimize the number of iterations to converge to the target surface can be better planned based on a good understanding and modeling of the cyclic material removal mechanism. A single degree of freedom dynamic analysis of the process suggests that material removal is performed through high-frequency impacts that mainly last for only a small fraction of the grinding disk rotation period. To detect these discrete cutting events in practice, a grinder is equipped with a rotary encoder. The encoder's signal is acquired through the angular sampling technique. A running cyclic synchronous average is applied to the speed signal to remove its non-cyclic events. The measured instantaneous rotational frequency clearly indicates the impacting nature of the process and captures the transient response excited by these cyclic impacts. The technique also locates the angular positions of cutting impacts in revolution cycles. It is thus possible to draw conclusions about the cyclic nature of dynamic changes in impact-cutting behavior when grinding with a flexible robot. The dynamics of the impacting regime and transient responses to impact-cutting excitations captured synchronously using the angular sampling technique provide feedback that can be used to regulate the material removal process. The experimental results also make it possible to correlate the energy required to remove a chip of metal through impacting with the measured drop in angular speed during grinding.

Neural Dynamics Underlying Target Detection in the Human Brain

PubMed Central

Bansal, Arjun K.; Madhavan, Radhika; Agam, Yigal; Golby, Alexandra; Madsen, Joseph R.

2014-01-01

Sensory signals must be interpreted in the context of goals and tasks. To detect a target in an image, the brain compares input signals and goals to elicit the correct behavior. We examined how target detection modulates visual recognition signals by recording intracranial field potential responses from 776 electrodes in 10 epileptic human subjects. We observed reliable differences in the physiological responses to stimuli when a cued target was present versus absent. Goal-related modulation was particularly strong in the inferior temporal and fusiform gyri, two areas important for object recognition. Target modulation started after 250 ms post stimulus, considerably after the onset of visual recognition signals. While broadband signals exhibited increased or decreased power, gamma frequency power showed predominantly increases during target presence. These observations support models where task goals interact with sensory inputs via top-down signals that influence the highest echelons of visual processing after the onset of selective responses. PMID:24553944

Signaling Molecules Governing Pluripotency and Early Lineage Commitments in Human Pluripotent Stem Cells

PubMed Central

Fathi, Ali; Eisa-Beygi, Shahram; Baharvand, Hossein

2017-01-01

Signaling in pluripotent stem cells is a complex and dynamic process involving multiple mediators, finely tuned to balancing pluripotency and differentiation states. Characterizing and modifying the necessary signaling pathways to attain desired cell types is required for stem-cell applications in various fields of regenerative medicine. These signals may help enhance the differentiation potential of pluripotent cells towards each of the embryonic lineages and enable us to achieve pure in vitro cultures of various cell types. This review provides a timely synthesis of recent advances into how maintenance of pluripotency in hPSCs is regulated by extrinsic cues, such as the fibroblast growth factor (FGF) and ACTIVIN signaling pathways, their interplay with other signaling pathways, namely, wingless- type MMTV integration site family (WNT) and mammalian target of rapamycin (mTOR), and the pathways governing the determination of multiple lineages. PMID:28670512

Subranging technique using superconducting technology

DOEpatents

Gupta, Deepnarayan

2003-01-01

Subranging techniques using "digital SQUIDs" are used to design systems with large dynamic range, high resolution and large bandwidth. Analog-to-digital converters (ADCs) embodying the invention include a first SQUID based "coarse" resolution circuit and a second SQUID based "fine" resolution circuit to convert an analog input signal into "coarse" and "fine" digital signals for subsequent processing. In one embodiment, an ADC includes circuitry for supplying an analog input signal to an input coil having at least a first inductive section and a second inductive section. A first superconducting quantum interference device (SQUID) is coupled to the first inductive section and a second SQUID is coupled to the second inductive section. The first SQUID is designed to produce "coarse" (large amplitude, low resolution) output signals and the second SQUID is designed to produce "fine" (low amplitude, high resolution) output signals in response to the analog input signals.

Frontal Cortex Activation Causes Rapid Plasticity of Auditory Cortical Processing

PubMed Central

Winkowski, Daniel E.; Bandyopadhyay, Sharba; Shamma, Shihab A.

2013-01-01

Neurons in the primary auditory cortex (A1) can show rapid changes in receptive fields when animals are engaged in sound detection and discrimination tasks. The source of a signal to A1 that triggers these changes is suspected to be in frontal cortical areas. How or whether activity in frontal areas can influence activity and sensory processing in A1 and the detailed changes occurring in A1 on the level of single neurons and in neuronal populations remain uncertain. Using electrophysiological techniques in mice, we found that pairing orbitofrontal cortex (OFC) stimulation with sound stimuli caused rapid changes in the sound-driven activity within A1 that are largely mediated by noncholinergic mechanisms. By integrating in vivo two-photon Ca2+ imaging of A1 with OFC stimulation, we found that pairing OFC activity with sounds caused dynamic and selective changes in sensory responses of neural populations in A1. Further, analysis of changes in signal and noise correlation after OFC pairing revealed improvement in neural population-based discrimination performance within A1. This improvement was frequency specific and dependent on correlation changes. These OFC-induced influences on auditory responses resemble behavior-induced influences on auditory responses and demonstrate that OFC activity could underlie the coordination of rapid, dynamic changes in A1 to dynamic sensory environments. PMID:24227723

System identification of timber masonry walls using shaking table test

NASA Astrophysics Data System (ADS)

Roy, Timir B.; Guerreiro, Luis; Bagchi, Ashutosh

2017-04-01

Dynamic study is important in order to design, repair and rehabilitation of structures. It has played an important role in the behavior characterization of structures; such as: bridges, dams, high rise buildings etc. There had been substantial development in this area over the last few decades, especially in the field of dynamic identification techniques of structural systems. Frequency Domain Decomposition (FDD) and Time Domain Decomposition are most commonly used methods to identify modal parameters; such as: natural frequency, modal damping and mode shape. The focus of the present research is to study the dynamic characteristics of typical timber masonry walls commonly used in Portugal. For that purpose, a multi-storey structural prototype of such wall has been tested on a seismic shake table at the National Laboratory for Civil Engineering, Portugal (LNEC). Signal processing has been performed of the output response, which is collected from the shaking table experiment of the prototype using accelerometers. In the present work signal processing of the output response, based on the input response has been done in two ways: FDD and Stochastic Subspace Identification (SSI). In order to estimate the values of the modal parameters, algorithms for FDD are formulated and parametric functions for the SSI are computed. Finally, estimated values from both the methods are compared to measure the accuracy of both the techniques.

A Modularized Efficient Framework for Non-Markov Time Series Estimation

NASA Astrophysics Data System (ADS)

Schamberg, Gabriel; Ba, Demba; Coleman, Todd P.

2018-06-01

We present a compartmentalized approach to finding the maximum a-posteriori (MAP) estimate of a latent time series that obeys a dynamic stochastic model and is observed through noisy measurements. We specifically consider modern signal processing problems with non-Markov signal dynamics (e.g. group sparsity) and/or non-Gaussian measurement models (e.g. point process observation models used in neuroscience). Through the use of auxiliary variables in the MAP estimation problem, we show that a consensus formulation of the alternating direction method of multipliers (ADMM) enables iteratively computing separate estimates based on the likelihood and prior and subsequently "averaging" them in an appropriate sense using a Kalman smoother. As such, this can be applied to a broad class of problem settings and only requires modular adjustments when interchanging various aspects of the statistical model. Under broad log-concavity assumptions, we show that the separate estimation problems are convex optimization problems and that the iterative algorithm converges to the MAP estimate. As such, this framework can capture non-Markov latent time series models and non-Gaussian measurement models. We provide example applications involving (i) group-sparsity priors, within the context of electrophysiologic specrotemporal estimation, and (ii) non-Gaussian measurement models, within the context of dynamic analyses of learning with neural spiking and behavioral observations.

Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex.

PubMed

Mejias, Jorge F; Murray, John D; Kennedy, Henry; Wang, Xiao-Jing

2016-11-01

Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding attentional processes, predictive coding, executive control, and a gamut of other brain functions. However, the underlying circuit mechanism remains poorly understood and represents a major challenge in neuroscience. We approached this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intralaminar, interlaminar, interareal, and whole cortex) scales. The model was tested by reproducing, as well as providing insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas, including the observation that feedforward pathways are associated with enhanced gamma (30 to 70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low-beta (8 to 15 Hz) oscillations. Furthermore, the model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of interareal signaling, as reported in recent monkey and human experiments, and suggests a mechanism for the observed context-dependent hierarchy dynamics. Together, this work highlights the necessity of multiscale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions.

Feedforward and feedback frequency-dependent interactions in a large-scale laminar network of the primate cortex

PubMed Central

Mejias, Jorge F.; Murray, John D.; Kennedy, Henry; Wang, Xiao-Jing

2016-01-01

Interactions between top-down and bottom-up processes in the cerebral cortex hold the key to understanding attentional processes, predictive coding, executive control, and a gamut of other brain functions. However, the underlying circuit mechanism remains poorly understood and represents a major challenge in neuroscience. We approached this problem using a large-scale computational model of the primate cortex constrained by new directed and weighted connectivity data. In our model, the interplay between feedforward and feedback signaling depends on the cortical laminar structure and involves complex dynamics across multiple (intralaminar, interlaminar, interareal, and whole cortex) scales. The model was tested by reproducing, as well as providing insights into, a wide range of neurophysiological findings about frequency-dependent interactions between visual cortical areas, including the observation that feedforward pathways are associated with enhanced gamma (30 to 70 Hz) oscillations, whereas feedback projections selectively modulate alpha/low-beta (8 to 15 Hz) oscillations. Furthermore, the model reproduces a functional hierarchy based on frequency-dependent Granger causality analysis of interareal signaling, as reported in recent monkey and human experiments, and suggests a mechanism for the observed context-dependent hierarchy dynamics. Together, this work highlights the necessity of multiscale approaches and provides a modeling platform for studies of large-scale brain circuit dynamics and functions. PMID:28138530

Dynamic in vivo imaging of small animal brain using pulsed laser diode-based photoacoustic tomography system.

PubMed

Upputuri, Paul Kumar; Pramanik, Manojit

2017-09-01

We demonstrate dynamic in vivo imaging using a low-cost portable pulsed laser diode (PLD)-based photoacoustic tomography system. The system takes advantage of an 803-nm PLD having high-repetition rate ∼7000  Hz combined with a fast-scanning single-element ultrasound transducer leading to a 5 s cross-sectional imaging. Cortical vasculature is imaged in scan time of 5 s with high signal-to-noise ratio ∼48. To examine the ability for dynamic imaging, we monitored the fast uptake and clearance process of indocyanine green in the rat brain. The system will find applications to study neurofunctional activities, characterization of pharmacokinetic, and biodistribution profiles in the development process of drugs or imaging agents. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Hierarchical random cellular neural networks for system-level brain-like signal processing.

PubMed

Kozma, Robert; Puljic, Marko

2013-09-01

Sensory information processing and cognition in brains are modeled using dynamic systems theory. The brain's dynamic state is described by a trajectory evolving in a high-dimensional state space. We introduce a hierarchy of random cellular automata as the mathematical tools to describe the spatio-temporal dynamics of the cortex. The corresponding brain model is called neuropercolation which has distinct advantages compared to traditional models using differential equations, especially in describing spatio-temporal discontinuities in the form of phase transitions. Phase transitions demarcate singularities in brain operations at critical conditions, which are viewed as hallmarks of higher cognition and awareness experience. The introduced Monte-Carlo simulations obtained by parallel computing point to the importance of computer implementations using very large-scale integration (VLSI) and analog platforms. Copyright © 2013 Elsevier Ltd. All rights reserved.

An analog neural hardware implementation using charge-injection multipliers and neutron-specific gain control.

PubMed

Massengill, L W; Mundie, D B

1992-01-01

A neural network IC based on a dynamic charge injection is described. The hardware design is space and power efficient, and achieves massive parallelism of analog inner products via charge-based multipliers and spatially distributed summing buses. Basic synaptic cells are constructed of exponential pulse-decay modulation (EPDM) dynamic injection multipliers operating sequentially on propagating signal vectors and locally stored analog weights. Individually adjustable gain controls on each neutron reduce the effects of limited weight dynamic range. A hardware simulator/trainer has been developed which incorporates the physical (nonideal) characteristics of actual circuit components into the training process, thus absorbing nonlinearities and parametric deviations into the macroscopic performance of the network. Results show that charge-based techniques may achieve a high degree of neural density and throughput using standard CMOS processes.

Rapid Protein Global Fold Determination Using Ultrasparse Sampling, High-Dynamic Range Artifact Suppression, and Time-Shared NOESY

PubMed Central

Coggins, Brian E.; Werner-Allen, Jonathan W.; Yan, Anthony; Zhou, Pei

2012-01-01

In structural studies of large proteins by NMR, global fold determination plays an increasingly important role in providing a first look at a target’s topology and reducing assignment ambiguity in NOESY spectra of fully-protonated samples. In this work, we demonstrate the use of ultrasparse sampling, a new data processing algorithm, and a 4-D time-shared NOESY experiment (1) to collect all NOEs in 2H/13C/15N-labeled protein samples with selectively-protonated amide and ILV methyl groups at high resolution in only four days, and (2) to calculate global folds from this data using fully automated resonance assignment. The new algorithm, SCRUB, incorporates the CLEAN method for iterative artifact removal, but applies an additional level of iteration, permitting real signals to be distinguished from noise and allowing nearly all artifacts generated by real signals to be eliminated. In simulations with 1.2% of the data required by Nyquist sampling, SCRUB achieves a dynamic range over 10000:1 (250× better artifact suppression than CLEAN) and completely quantitative reproduction of signal intensities, volumes, and lineshapes. Applied to 4-D time-shared NOESY data, SCRUB processing dramatically reduces aliasing noise from strong diagonal signals, enabling the identification of weak NOE crosspeaks with intensities 100× less than diagonal signals. Nearly all of the expected peaks for interproton distances under 5 Å were observed. The practical benefit of this method is demonstrated with structure calculations for 23 kDa and 29 kDa test proteins using the automated assignment protocol of CYANA, in which unassigned 4-D time-shared NOESY peak lists produce accurate and well-converged global fold ensembles, whereas 3-D peak lists either fail to converge or produce significantly less accurate folds. The approach presented here succeeds with an order of magnitude less sampling than required by alternative methods for processing sparse 4-D data. PMID:22946863

Dynamic facial expressions of emotion transmit an evolving hierarchy of signals over time.

PubMed

Jack, Rachael E; Garrod, Oliver G B; Schyns, Philippe G

2014-01-20

Designed by biological and social evolutionary pressures, facial expressions of emotion comprise specific facial movements to support a near-optimal system of signaling and decoding. Although highly dynamical, little is known about the form and function of facial expression temporal dynamics. Do facial expressions transmit diagnostic signals simultaneously to optimize categorization of the six classic emotions, or sequentially to support a more complex communication system of successive categorizations over time? Our data support the latter. Using a combination of perceptual expectation modeling, information theory, and Bayesian classifiers, we show that dynamic facial expressions of emotion transmit an evolving hierarchy of "biologically basic to socially specific" information over time. Early in the signaling dynamics, facial expressions systematically transmit few, biologically rooted face signals supporting the categorization of fewer elementary categories (e.g., approach/avoidance). Later transmissions comprise more complex signals that support categorization of a larger number of socially specific categories (i.e., the six classic emotions). Here, we show that dynamic facial expressions of emotion provide a sophisticated signaling system, questioning the widely accepted notion that emotion communication is comprised of six basic (i.e., psychologically irreducible) categories, and instead suggesting four. Copyright © 2014 Elsevier Ltd. All rights reserved.

Radar signal transmission and switching over optical networks

NASA Astrophysics Data System (ADS)

Esmail, Maged A.; Ragheb, Amr; Seleem, Hussein; Fathallah, Habib; Alshebeili, Saleh

2018-03-01

In this paper, we experimentally demonstrate a radar signal distribution over optical networks. The use of fiber enables us to distribute radar signals to distant sites with a low power loss. Moreover, fiber networks can reduce the radar system cost, by sharing precise and expensive radar signal generation and processing equipment. In order to overcome the bandwidth challenges in electrical switches, a semiconductor optical amplifier (SOA) is used as an all-optical device for wavelength conversion to the desired port (or channel) of a wavelength division multiplexing (WDM) network. Moreover, the effect of chromatic dispersion in double sideband (DSB) signals is combated by generating optical single sideband (OSSB) signals. The optimal values of the SOA device parameters required to generate an OSSB with a high sideband suppression ratio (SSR) are determined. We considered various parameters such as injection current, pump power, and probe power. In addition, the effect of signal wavelength conversion and transmission over fiber are studied in terms of signal dynamic range.

In situ sensing and modeling of molecular events at the cellular level

NASA Astrophysics Data System (ADS)

Yang, Ruiguo

We developed the Atomic Force Microscopy (AFM) based nanorobot in combination with other nanomechanical sensors for the investigation of cell signaling pathways. The AFM nanorobotics hinge on the superior spatial resolution of AFM in imaging and extends it into the measurement of biological processes and manipulation of biological matters. A multiple input single output control system was designed and implemented to solve the issues of nanomanipulation of biological materials, feedback, response frequency and nonlinearity. The AFM nanorobotic system therefore provide the human-directed position, velocity and force control with high frequency feedback, and more importantly it can feed the operator with the real-time imaging of manipulation result from the fast-imaging based local scanning. The use of the system has taken the study of cellular process at the molecular scale into a new level. The cellular response to the physiological conditions can be significantly manifested in cellular mechanics. Dynamic mechanical property has been regarded as biomarkers, sometimes even regulators of the signaling and physiological processes, thus the name mechanobiology. We sought to characterize the relationship between the structural dynamics and the molecular dynamics and the role of them in the regulation of cell behavior. We used the AFM nanorobotics to investigate the mechanical properties in real-time of cells that are stimulated by different chemical species. These reagents could result in similar ion channel responses but distinctive mechanical behaviors. We applied these measurement results to establish a model that describes the cellular stimulation and the mechanical property change, a "two-hit" model that comprises the loss of cell adhesion and the initiation of cell apoptosis. The first hit was verified by functional experiments: depletion of Calcium and nanosurgery to disrupt the cellular adhesion. The second hit was tested by a labeling of apoptotic markers that were revealed by flow cytometry. The model would then be able to decipher qualitatively the molecular dynamics infolded in the regulation of cell behavior. To decipher the signaling pathway quantitatively, we employed a nanomechanical sensor at the bottom of the cell, quartz crystal microbalance with energy dissipation monitoring (QCM-D) to monitor the change at the basal area of the cell. This would provide the real time focal adhesion information and would be used in accordance with the AFM measurement data on the top of the cell to build a more complete mechanical profile during the antibody induced signaling process. We developed a model from a systematic control perspective that considers the signaling cascade at certain stimulation as the controller and the mechanical and structural interaction of the cell as the plant. We firstly derived the plant model based on QCM-D and AFM measurement processes. A signaling pathway model was built on a grey box approach where part of the pathway map was delineated in detail while others were condensed into a single reaction. The model parameters were obtained by extracting the mechanical response from the experiment. The model refinements were conducted by testing a series of inhibition mechanisms and comparing the simulation data with the experimental data. The model was then used to predict the existences of certain reactions that are qualitatively reported in the literature.

Inferring infection hazard in wildlife populations by linking data across individual and population scales.

PubMed

Pepin, Kim M; Kay, Shannon L; Golas, Ben D; Shriner, Susan S; Gilbert, Amy T; Miller, Ryan S; Graham, Andrea L; Riley, Steven; Cross, Paul C; Samuel, Michael D; Hooten, Mevin B; Hoeting, Jennifer A; Lloyd-Smith, James O; Webb, Colleen T; Buhnerkempe, Michael G

2017-03-01

Our ability to infer unobservable disease-dynamic processes such as force of infection (infection hazard for susceptible hosts) has transformed our understanding of disease transmission mechanisms and capacity to predict disease dynamics. Conventional methods for inferring FOI estimate a time-averaged value and are based on population-level processes. Because many pathogens exhibit epidemic cycling and FOI is the result of processes acting across the scales of individuals and populations, a flexible framework that extends to epidemic dynamics and links within-host processes to FOI is needed. Specifically, within-host antibody kinetics in wildlife hosts can be short-lived and produce patterns that are repeatable across individuals, suggesting individual-level antibody concentrations could be used to infer time since infection and hence FOI. Using simulations and case studies (influenza A in lesser snow geese and Yersinia pestis in coyotes), we argue that with careful experimental and surveillance design, the population-level FOI signal can be recovered from individual-level antibody kinetics, despite substantial individual-level variation. In addition to improving inference, the cross-scale quantitative antibody approach we describe can reveal insights into drivers of individual-based variation in disease response, and the role of poorly understood processes such as secondary infections, in population-level dynamics of disease. © 2017 John Wiley & Sons Ltd/CNRS.

Inferring infection hazard in wildlife populations by linking data across individual and population scales

USGS Publications Warehouse

Pepin, Kim M.; Kay, Shannon L.; Golas, Ben D.; Shriner, Susan A.; Gilbert, Amy T.; Miller, Ryan S.; Graham, Andrea L.; Riley, Steven; Cross, Paul C.; Samuel, Michael D.; Hooten, Mevin B.; Hoeting, Jennifer A.; Lloyd-Smith, James O.; Webb, Colleen T.; Buhnerkempe, Michael G.

2017-01-01

Our ability to infer unobservable disease-dynamic processes such as force of infection (infection hazard for susceptible hosts) has transformed our understanding of disease transmission mechanisms and capacity to predict disease dynamics. Conventional methods for inferring FOI estimate a time-averaged value and are based on population-level processes. Because many pathogens exhibit epidemic cycling and FOI is the result of processes acting across the scales of individuals and populations, a flexible framework that extends to epidemic dynamics and links within-host processes to FOI is needed. Specifically, within-host antibody kinetics in wildlife hosts can be short-lived and produce patterns that are repeatable across individuals, suggesting individual-level antibody concentrations could be used to infer time since infection and hence FOI. Using simulations and case studies (influenza A in lesser snow geese and Yersinia pestis in coyotes), we argue that with careful experimental and surveillance design, the population-level FOI signal can be recovered from individual-level antibody kinetics, despite substantial individual-level variation. In addition to improving inference, the cross-scale quantitative antibody approach we describe can reveal insights into drivers of individual-based variation in disease response, and the role of poorly understood processes such as secondary infections, in population-level dynamics of disease.

Detecting the tipping points in a three-state model of complex diseases by temporal differential networks.

PubMed

Chen, Pei; Li, Yongjun; Liu, Xiaoping; Liu, Rui; Chen, Luonan

2017-10-26

The progression of complex diseases, such as diabetes and cancer, is generally a nonlinear process with three stages, i.e., normal state, pre-disease state, and disease state, where the pre-disease state is a critical state or tipping point immediately preceding the disease state. Traditional biomarkers aim to identify a disease state by exploiting the information of differential expressions for the observed molecules, but may fail to detect a pre-disease state because there are generally little significant differences between the normal and pre-disease states. Thus, it is challenging to signal the pre-disease state, which actually implies the disease prediction. In this work, by exploiting the information of differential associations among the observed molecules between the normal and pre-disease states, we propose a temporal differential network based computational method to accurately signal the pre-disease state or predict the occurrence of severe disease. The theoretical foundation of this work is the quantification of the critical state using dynamical network biomarkers. Considering that there is one stationary Markov process before reaching the tipping point, a novel index, inconsistency score (I-score), is proposed to quantitatively measure the change of the stationary processes from the normal state so as to detect the onset of pre-disease state. In other words, a drastic increase of I-score implies the high inconsistency with the preceding stable state and thus signals the upcoming critical transition. This approach is applied to the simulated and real datasets of three diseases, which demonstrates the effectiveness of our method for predicting the deterioration into disease states. Both functional analysis and pathway enrichment also validate the computational results from the perspectives of both molecules and networks. At the molecular network level, this method provides a computational way of unravelling the underlying mechanism of the dynamical progression when a biological system is near the tipping point, and thus detecting the early-warning signal of the imminent critical transition, which may help to achieve timely intervention. Moreover, the rewiring of differential networks effectively extracts discriminatively interpretable features, and systematically demonstrates the dynamical change of a biological system.

A Carrier Estimation Method Based on MLE and KF for Weak GNSS Signals.

PubMed

Zhang, Hongyang; Xu, Luping; Yan, Bo; Zhang, Hua; Luo, Liyan

2017-06-22

Maximum likelihood estimation (MLE) has been researched for some acquisition and tracking applications of global navigation satellite system (GNSS) receivers and shows high performance. However, all current methods are derived and operated based on the sampling data, which results in a large computation burden. This paper proposes a low-complexity MLE carrier tracking loop for weak GNSS signals which processes the coherent integration results instead of the sampling data. First, the cost function of the MLE of signal parameters such as signal amplitude, carrier phase, and Doppler frequency are used to derive a MLE discriminator function. The optimal value of the cost function is searched by an efficient Levenberg-Marquardt (LM) method iteratively. Its performance including Cramér-Rao bound (CRB), dynamic characteristics and computation burden are analyzed by numerical techniques. Second, an adaptive Kalman filter is designed for the MLE discriminator to obtain smooth estimates of carrier phase and frequency. The performance of the proposed loop, in terms of sensitivity, accuracy and bit error rate, is compared with conventional methods by Monte Carlo (MC) simulations both in pedestrian-level and vehicle-level dynamic circumstances. Finally, an optimal loop which combines the proposed method and conventional method is designed to achieve the optimal performance both in weak and strong signal circumstances.

Dynamic Interplay of Value and Sensory Information in High-Speed Decision Making.

PubMed

Afacan-Seref, Kivilcim; Steinemann, Natalie A; Blangero, Annabelle; Kelly, Simon P

2018-03-05

In dynamic environments, split-second sensorimotor decisions must be prioritized according to potential payoffs to maximize overall rewards. The impact of relative value on deliberative perceptual judgments has been examined extensively [1-6], but relatively little is known about value-biasing mechanisms in the common situation where physical evidence is strong but the time to act is severely limited. In prominent decision models, a noisy but statistically stationary representation of sensory evidence is integrated over time to an action-triggering bound, and value-biases are affected by starting the integrator closer to the more valuable bound. Here, we show significant departures from this account for humans making rapid sensory-instructed action choices. Behavior was best explained by a simple model in which the evidence representation-and hence, rate of accumulation-is itself biased by value and is non-stationary, increasing over the short decision time frame. Because the value bias initially dominates, the model uniquely predicts a dynamic "turn-around" effect on low-value cues, where the accumulator first launches toward the incorrect action but is then re-routed to the correct one. This was clearly exhibited in electrophysiological signals reflecting motor preparation and evidence accumulation. Finally, we construct an extended model that implements this dynamic effect through plausible sensory neural response modulations and demonstrate the correspondence between decision signal dynamics simulated from a behavioral fit of that model and the empirical decision signals. Our findings suggest that value and sensory information can exert simultaneous and dynamically countervailing influences on the trajectory of the accumulation-to-bound process, driving rapid, sensory-guided actions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Fiber-Optic Pressure Sensor With Dynamic Demodulation Developed

NASA Technical Reports Server (NTRS)

Lekki, John D.

2002-01-01

Researchers at the NASA Glenn Research Center developed in-house a method to detect pressure fluctuations using a fiber-optic sensor and dynamic signal processing. This work was in support of the Intelligent Systems Controls and Operations project under NASA's Information Technology Base Research Program. We constructed an optical pressure sensor by attaching a fiber-optic Bragg grating to a flexible membrane and then adhering the membrane to one end of a small cylinder. The other end of the cylinder was left open and exposed to pressure variations from a pulsed air jet. These pressure variations flexed the membrane, inducing a strain in the fiber-optic grating. This strain was read out optically with a dynamic spectrometer to record changes in the wavelength of light reflected from the grating. The dynamic spectrometer was built in-house to detect very small wavelength shifts induced by the pressure fluctuations. The spectrometer is an unbalanced interferometer specifically designed for maximum sensitivity to wavelength shifts. An optimum pathlength difference, which was determined empirically, resulted in a 14-percent sensitivity improvement over theoretically predicted path-length differences. This difference is suspected to be from uncertainty about the spectral power difference of the signal reflected from the Bragg grating. The figure shows the output of the dynamic spectrometer as the sensor was exposed to a nominally 2-kPa peak-to-peak square-wave pressure fluctuation. Good tracking, sensitivity, and signal-to-noise ratios are evident even though the sensor was constructed as a proof-of-concept and was not optimized in any way. Therefore the fiber-optic Bragg grating, which is normally considered a good candidate as a strain or temperature sensor, also has been shown to be a good candidate for a dynamic pressure sensor.