A Highly Linear and Wide Input Range Four-Quadrant CMOS Analog Multiplier Using Active Feedback

NASA Astrophysics Data System (ADS)

Huang, Zhangcai; Jiang, Minglu; Inoue, Yasuaki

Analog multipliers are one of the most important building blocks in analog signal processing circuits. The performance with high linearity and wide input range is usually required for analog four-quadrant multipliers in most applications. Therefore, a highly linear and wide input range four-quadrant CMOS analog multiplier using active feedback is proposed in this paper. Firstly, a novel configuration of four-quadrant multiplier cell is presented. Its input dynamic range and linearity are improved significantly by adding two resistors compared with the conventional structure. Then based on the proposed multiplier cell configuration, a four-quadrant CMOS analog multiplier with active feedback technique is implemented by two operational amplifiers. Because of both the proposed multiplier cell and active feedback technique, the proposed multiplier achieves a much wider input range with higher linearity than conventional structures. The proposed multiplier was fabricated by a 0.6µm CMOS process. Experimental results show that the input range of the proposed multiplier can be up to 5.6Vpp with 0.159% linearity error on VX and 4.8Vpp with 0.51% linearity error on VY for ±2.5V power supply voltages, respectively.

Automatic image equalization and contrast enhancement using Gaussian mixture modeling.

PubMed

Celik, Turgay; Tjahjadi, Tardi

2012-01-01

In this paper, we propose an adaptive image equalization algorithm that automatically enhances the contrast in an input image. The algorithm uses the Gaussian mixture model to model the image gray-level distribution, and the intersection points of the Gaussian components in the model are used to partition the dynamic range of the image into input gray-level intervals. The contrast equalized image is generated by transforming the pixels' gray levels in each input interval to the appropriate output gray-level interval according to the dominant Gaussian component and the cumulative distribution function of the input interval. To take account of the hypothesis that homogeneous regions in the image represent homogeneous silences (or set of Gaussian components) in the image histogram, the Gaussian components with small variances are weighted with smaller values than the Gaussian components with larger variances, and the gray-level distribution is also used to weight the components in the mapping of the input interval to the output interval. Experimental results show that the proposed algorithm produces better or comparable enhanced images than several state-of-the-art algorithms. Unlike the other algorithms, the proposed algorithm is free of parameter setting for a given dynamic range of the enhanced image and can be applied to a wide range of image types.

Logarithmic circuit with wide dynamic range

NASA Technical Reports Server (NTRS)

Wiley, P. H.; Manus, E. A. (Inventor)

1978-01-01

A circuit deriving an output voltage that is proportional to the logarithm of a dc input voltage susceptible to wide variations in amplitude includes a constant current source which forward biases a diode so that the diode operates in the exponential portion of its voltage versus current characteristic, above its saturation current. The constant current source includes first and second, cascaded feedback, dc operational amplifiers connected in negative feedback circuit. An input terminal of the first amplifier is responsive to the input voltage. A circuit shunting the first amplifier output terminal includes a resistor in series with the diode. The voltage across the resistor is sensed at the input of the second dc operational feedback amplifier. The current flowing through the resistor is proportional to the input voltage over the wide range of variations in amplitude of the input voltage.

Extended range radiation dose-rate monitor

DOEpatents

Valentine, Kenneth H.

1988-01-01

An extended range dose-rate monitor is provided which utilizes the pulse pileup phenomenon that occurs in conventional counting systems to alter the dynamic response of the system to extend the dose-rate counting range. The current pulses from a solid-state detector generated by radiation events are amplified and shaped prior to applying the pulses to the input of a comparator. The comparator generates one logic pulse for each input pulse which exceeds the comparator reference threshold. These pulses are integrated and applied to a meter calibrated to indicate the measured dose-rate in response to the integrator output. A portion of the output signal from the integrator is fed back to vary the comparator reference threshold in proportion to the output count rate to extend the sensitive dynamic detection range by delaying the asymptotic approach of the integrator output toward full scale as measured by the meter.

SDR input power estimation algorithms

NASA Astrophysics Data System (ADS)

Briones, J. C.; Nappier, J. M.

The General Dynamics (GD) S-Band software defined radio (SDR) in the Space Communications and Navigation (SCAN) Testbed on the International Space Station (ISS) provides experimenters an opportunity to develop and demonstrate experimental waveforms in space. The SDR has an analog and a digital automatic gain control (AGC) and the response of the AGCs to changes in SDR input power and temperature was characterized prior to the launch and installation of the SCAN Testbed on the ISS. The AGCs were used to estimate the SDR input power and SNR of the received signal and the characterization results showed a nonlinear response to SDR input power and temperature. In order to estimate the SDR input from the AGCs, three algorithms were developed and implemented on the ground software of the SCAN Testbed. The algorithms include a linear straight line estimator, which used the digital AGC and the temperature to estimate the SDR input power over a narrower section of the SDR input power range. There is a linear adaptive filter algorithm that uses both AGCs and the temperature to estimate the SDR input power over a wide input power range. Finally, an algorithm that uses neural networks was designed to estimate the input power over a wide range. This paper describes the algorithms in detail and their associated performance in estimating the SDR input power.

SDR Input Power Estimation Algorithms

NASA Technical Reports Server (NTRS)

Nappier, Jennifer M.; Briones, Janette C.

2013-01-01

The General Dynamics (GD) S-Band software defined radio (SDR) in the Space Communications and Navigation (SCAN) Testbed on the International Space Station (ISS) provides experimenters an opportunity to develop and demonstrate experimental waveforms in space. The SDR has an analog and a digital automatic gain control (AGC) and the response of the AGCs to changes in SDR input power and temperature was characterized prior to the launch and installation of the SCAN Testbed on the ISS. The AGCs were used to estimate the SDR input power and SNR of the received signal and the characterization results showed a nonlinear response to SDR input power and temperature. In order to estimate the SDR input from the AGCs, three algorithms were developed and implemented on the ground software of the SCAN Testbed. The algorithms include a linear straight line estimator, which used the digital AGC and the temperature to estimate the SDR input power over a narrower section of the SDR input power range. There is a linear adaptive filter algorithm that uses both AGCs and the temperature to estimate the SDR input power over a wide input power range. Finally, an algorithm that uses neural networks was designed to estimate the input power over a wide range. This paper describes the algorithms in detail and their associated performance in estimating the SDR input power.

Quantitative myocardial perfusion from static cardiac and dynamic arterial CT

NASA Astrophysics Data System (ADS)

Bindschadler, Michael; Branch, Kelley R.; Alessio, Adam M.

2018-05-01

Quantitative myocardial blood flow (MBF) estimation by dynamic contrast enhanced cardiac computed tomography (CT) requires multi-frame acquisition of contrast transit through the blood pool and myocardium to inform the arterial input and tissue response functions. Both the input and the tissue response functions for the entire myocardium are sampled with each acquisition. However, the long breath holds and frequent sampling can result in significant motion artifacts and relatively high radiation dose. To address these limitations, we propose and evaluate a new static cardiac and dynamic arterial (SCDA) quantitative MBF approach where (1) the input function is well sampled using either prediction from pre-scan timing bolus data or measured from dynamic thin slice ‘bolus tracking’ acquisitions, and (2) the whole-heart tissue response data is limited to one contrast enhanced CT acquisition. A perfusion model uses the dynamic arterial input function to generate a family of possible myocardial contrast enhancement curves corresponding to a range of MBF values. Combined with the timing of the single whole-heart acquisition, these curves generate a lookup table relating myocardial contrast enhancement to quantitative MBF. We tested the SCDA approach in 28 patients that underwent a full dynamic CT protocol both at rest and vasodilator stress conditions. Using measured input function plus single (enhanced CT only) or plus double (enhanced and contrast free baseline CT’s) myocardial acquisitions yielded MBF estimates with root mean square (RMS) error of 1.2 ml/min/g and 0.35 ml/min/g, and radiation dose reductions of 90% and 83%, respectively. The prediction of the input function based on timing bolus data and the static acquisition had an RMS error compared to the measured input function of 26.0% which led to MBF estimation errors greater than threefold higher than using the measured input function. SCDA presents a new, simplified approach for quantitative perfusion imaging with an acquisition strategy offering substantial radiation dose and computational complexity savings over dynamic CT.

SRG110 Stirling Generator Dynamic Simulator Vibration Test Results and Analysis Correlation

NASA Technical Reports Server (NTRS)

Suarez, Vicente J.; Lewandowski, Edward J.; Callahan, John

2006-01-01

The U.S. Department of Energy (DOE), Lockheed Martin (LM), and NASA Glenn Research Center (GRC) have been developing the Stirling Radioisotope Generator (SRG110) for use as a power system for space science missions. The launch environment enveloping potential missions results in a random input spectrum that is significantly higher than historical RPS launch levels and is a challenge for designers. Analysis presented in prior work predicted that tailoring the compliance at the generator-spacecraft interface reduced the dynamic response of the system thereby allowing higher launch load input levels and expanding the range of potential generator missions. To confirm analytical predictions, a dynamic simulator representing the generator structure, Stirling convertors and heat sources was designed and built for testing with and without a compliant interface. Finite element analysis was performed to guide the generator simulator and compliant interface design so that test modes and frequencies were representative of the SRG110 generator. This paper presents the dynamic simulator design, the test setup and methodology, test article modes and frequencies and dynamic responses, and post-test analysis results. With the compliant interface, component responses to an input environment exceeding the SRG110 qualification level spectrum were all within design allowables. Post-test analysis included finite element model tuning to match test frequencies and random response analysis using the test input spectrum. Analytical results were in good overall agreement with the test results and confirmed previous predictions that the SRG110 power system may be considered for a broad range of potential missions, including those with demanding launch environments.

SRG110 Stirling Generator Dynamic Simulator Vibration Test Results and Analysis Correlation

NASA Technical Reports Server (NTRS)

Lewandowski, Edward J.; Suarez, Vicente J.; Goodnight, Thomas W.; Callahan, John

2007-01-01

The U.S. Department of Energy (DOE), Lockheed Martin (LM), and NASA Glenn Research Center (GRC) have been developing the Stirling Radioisotope Generator (SRG110) for use as a power system for space science missions. The launch environment enveloping potential missions results in a random input spectrum that is significantly higher than historical radioisotope power system (RPS) launch levels and is a challenge for designers. Analysis presented in prior work predicted that tailoring the compliance at the generator-spacecraft interface reduced the dynamic response of the system thereby allowing higher launch load input levels and expanding the range of potential generator missions. To confirm analytical predictions, a dynamic simulator representing the generator structure, Stirling convertors and heat sources were designed and built for testing with and without a compliant interface. Finite element analysis was performed to guide the generator simulator and compliant interface design so that test modes and frequencies were representative of the SRG110 generator. This paper presents the dynamic simulator design, the test setup and methodology, test article modes and frequencies and dynamic responses, and post-test analysis results. With the compliant interface, component responses to an input environment exceeding the SRG110 qualification level spectrum were all within design allowables. Post-test analysis included finite element model tuning to match test frequencies and random response analysis using the test input spectrum. Analytical results were in good overall agreement with the test results and confirmed previous predictions that the SRG110 power system may be considered for a broad range of potential missions, including those with demanding launch environments.

Output-only modal dynamic identification of frames by a refined FDD algorithm at seismic input and high damping

NASA Astrophysics Data System (ADS)

Pioldi, Fabio; Ferrari, Rosalba; Rizzi, Egidio

2016-02-01

The present paper deals with the seismic modal dynamic identification of frame structures by a refined Frequency Domain Decomposition (rFDD) algorithm, autonomously formulated and implemented within MATLAB. First, the output-only identification technique is outlined analytically and then employed to characterize all modal properties. Synthetic response signals generated prior to the dynamic identification are adopted as input channels, in view of assessing a necessary condition for the procedure's efficiency. Initially, the algorithm is verified on canonical input from random excitation. Then, modal identification has been attempted successfully at given seismic input, taken as base excitation, including both strong motion data and single and multiple input ground motions. Rather than different attempts investigating the role of seismic response signals in the Time Domain, this paper considers the identification analysis in the Frequency Domain. Results turn-out very much consistent with the target values, with quite limited errors in the modal estimates, including for the damping ratios, ranging from values in the order of 1% to 10%. Either seismic excitation and high values of damping, resulting critical also in case of well-spaced modes, shall not fulfill traditional FFD assumptions: this shows the consistency of the developed algorithm. Through original strategies and arrangements, the paper shows that a comprehensive rFDD modal dynamic identification of frames at seismic input is feasible, also at concomitant high damping.

Global Swath and Gridded Data Tiling

NASA Technical Reports Server (NTRS)

Thompson, Charles K.

2012-01-01

This software generates cylindrically projected tiles of swath-based or gridded satellite data for the purpose of dynamically generating high-resolution global images covering various time periods, scaling ranges, and colors called "tiles." It reconstructs a global image given a set of tiles covering a particular time range, scaling values, and a color table. The program is configurable in terms of tile size, spatial resolution, format of input data, location of input data (local or distributed), number of processes run in parallel, and data conditioning.

Measuring circuit

DOEpatents

Sun, Shan C.; Chaprnka, Anthony G.

1977-01-11

An automatic gain control circuit functions to adjust the magnitude of an input signal supplied to a measuring circuit to a level within the dynamic range of the measuring circuit while a log-ratio circuit adjusts the magnitude of the output signal from the measuring circuit to the level of the input signal and optimizes the signal-to-noise ratio performance of the measuring circuit.

Simulative method for determining the optimal operating conditions for a cooling plate for lithium-ion battery cell modules

NASA Astrophysics Data System (ADS)

Smith, Joshua; Hinterberger, Michael; Hable, Peter; Koehler, Juergen

2014-12-01

Extended battery system lifetime and reduced costs are essential to the success of electric vehicles. An effective thermal management strategy is one method of enhancing system lifetime increasing vehicle range. Vehicle-typical space restrictions favor the minimization of battery thermal management system (BTMS) size and weight, making their production and subsequent vehicle integration extremely difficult and complex. Due to these space requirements, a cooling plate as part of a water-glycerol cooling circuit is commonly implemented. This paper presents a computational fluid dynamics (CFD) model and multi-objective analysis technique for determining the thermal effect of coolant flow rate and inlet temperature in a cooling plate-at a range of vehicle operating conditions-on a battery system, thereby providing a dynamic input for one-dimensional models. Traditionally, one-dimensional vehicular thermal management system models assume a static heat input from components such as a battery system: as a result, the components are designed for a set coolant input (flow rate and inlet temperature). Such a design method is insufficient for dynamic thermal management models and control strategies, thereby compromising system efficiency. The presented approach allows for optimal BMTS design and integration in the vehicular coolant circuit.

Dynamic responses of railroad car models to vertical and lateral rail inputs

NASA Technical Reports Server (NTRS)

Sewall, J. L.; Parrish, R. V.; Durling, B. J.

1971-01-01

Simplified dynamic models were applied in a study of vibration in a high-speed railroad car. The mathematical models used were a four-degree-of-freedom model for vertical responses to vertical rail inputs and a ten-degree-of-freedom model for lateral response to lateral or rolling (cross-level) inputs from the rails. Elastic properties of the passenger car body were represented by bending and torsion of a uniform beam. Rail-to-car (truck) suspensions were modeled as spring-mass-dashpot oscillators. Lateral spring nonlinearities approximating certain complicated truck mechanisms were introduced. The models were excited by displacement and, in some cases, velocity inputs from the rails by both deterministic (including sinusoidal) and random input functions. Results were obtained both in the frequency and time domains. Solutions in the time domain for the lateral model were obtained for a wide variety of transient and random inputs generated on-line by an analog computer. Variations in one of the damping properties of the lateral car suspension gave large fluctuations in response over a range of car speeds for a given input. This damping coefficient was significant in reducing lateral car responses that were higher for nonlinear springs for three different inputs.

A probabilistic model of debris-flow delivery to stream channels, demonstrated for the Coast Range of Oregon, USA

Treesearch

Daniel J. Miller; Kelly M. Burnett

2008-01-01

Debris flows are important geomorphic agents in mountainous terrains that shape channel environments and add a dynamic element to sediment supply and channel disturbance. Identification of channels susceptible to debris-flow inputs of sediment and organic debris, and quantification of the likelihood and magnitude of those inputs, are key tasks for characterizing...

Detailed numerical investigation of the dissipative stochastic mechanics based neuron model.

PubMed

Güler, Marifi

2008-10-01

Recently, a physical approach for the description of neuronal dynamics under the influence of ion channel noise was proposed in the realm of dissipative stochastic mechanics (Güler, Phys Rev E 76:041918, 2007). Led by the presence of a multiple number of gates in an ion channel, the approach establishes a viewpoint that ion channels are exposed to two kinds of noise: the intrinsic noise, associated with the stochasticity in the movement of gating particles between the inner and the outer faces of the membrane, and the topological noise, associated with the uncertainty in accessing the permissible topological states of open gates. Renormalizations of the membrane capacitance and of a membrane voltage dependent potential function were found to arise from the mutual interaction of the two noisy systems. The formalism therein was scrutinized using a special membrane with some tailored properties giving the Rose-Hindmarsh dynamics in the deterministic limit. In this paper, the resultant computational neuron model of the above approach is investigated in detail numerically for its dynamics using time-independent input currents. The following are the major findings obtained. The intrinsic noise gives rise to two significant coexisting effects: it initiates spiking activity even in some range of input currents for which the corresponding deterministic model is quiet and causes bursting in some other range of input currents for which the deterministic model fires tonically. The renormalization corrections are found to augment the above behavioral transitions from quiescence to spiking and from tonic firing to bursting, and, therefore, the bursting activity is found to take place in a wider range of input currents for larger values of the correction coefficients. Some findings concerning the diffusive behavior in the voltage space are also reported.

Fast and High Dynamic Range Imaging with Superconducting Tunnel Junction Detectors

NASA Astrophysics Data System (ADS)

Matsuo, Hiroshi

2014-08-01

We have demonstrated a combined test of the submillimeter-wave SIS photon detectors and GaAs-JFET cryogenic integrated circuits. A relatively large background photo-current can be read out by fast-reset integrating amplifiers. An integration time of 1 ms enables fast frame rate readout and large dynamic range imaging, with an expected dynamic range of 8,000 in 1 ms. Ultimate fast and high dynamic range performance of superconducting tunnel junction detectors (STJ) will be obtained when photon counting capabilities are employed. In the terahertz frequencies, when input photon rate of 100 MHz is measured, the photon bunching gives us enough timing resolution to be used as phase information of intensity fluctuation. Application of photon statistics will be a new tool in the terahertz frequency region. The design parameters of STJ terahertz photon counting detectors are discussed.

Practical input optimization for aircraft parameter estimation experiments. Ph.D. Thesis, 1990

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

1993-01-01

The object of this research was to develop an algorithm for the design of practical, optimal flight test inputs for aircraft parameter estimation experiments. A general, single pass technique was developed which allows global optimization of the flight test input design for parameter estimation using the principles of dynamic programming with the input forms limited to square waves only. Provision was made for practical constraints on the input, including amplitude constraints, control system dynamics, and selected input frequency range exclusions. In addition, the input design was accomplished while imposing output amplitude constraints required by model validity and considerations of safety during the flight test. The algorithm has multiple input design capability, with optional inclusion of a constraint that only one control move at a time, so that a human pilot can implement the inputs. It is shown that the technique can be used to design experiments for estimation of open loop model parameters from closed loop flight test data. The report includes a new formulation of the optimal input design problem, a description of a new approach to the solution, and a summary of the characteristics of the algorithm, followed by three example applications of the new technique which demonstrate the quality and expanded capabilities of the input designs produced by the new technique. In all cases, the new input design approach showed significant improvement over previous input design methods in terms of achievable parameter accuracies.

Neural Networks for Rapid Design and Analysis

NASA Technical Reports Server (NTRS)

Sparks, Dean W., Jr.; Maghami, Peiman G.

1998-01-01

Artificial neural networks have been employed for rapid and efficient dynamics and control analysis of flexible systems. Specifically, feedforward neural networks are designed to approximate nonlinear dynamic components over prescribed input ranges, and are used in simulations as a means to speed up the overall time response analysis process. To capture the recursive nature of dynamic components with artificial neural networks, recurrent networks, which use state feedback with the appropriate number of time delays, as inputs to the networks, are employed. Once properly trained, neural networks can give very good approximations to nonlinear dynamic components, and by their judicious use in simulations, allow the analyst the potential to speed up the analysis process considerably. To illustrate this potential speed up, an existing simulation model of a spacecraft reaction wheel system is executed, first conventionally, and then with an artificial neural network in place.

Extrasynaptic Glutamate Receptor Activation as Cellular Bases for Dynamic Range Compression in Pyramidal Neurons

PubMed Central

Oikonomou, Katerina D.; Short, Shaina M.; Rich, Matthew T.; Antic, Srdjan D.

2012-01-01

Repetitive synaptic stimulation overcomes the ability of astrocytic processes to clear glutamate from the extracellular space, allowing some dendritic segments to become submerged in a pool of glutamate, for a brief period of time. This dynamic arrangement activates extrasynaptic NMDA receptors located on dendritic shafts. We used voltage-sensitive and calcium-sensitive dyes to probe dendritic function in this glutamate-rich location. An excess of glutamate in the extrasynaptic space was achieved either by repetitive synaptic stimulation or by glutamate iontophoresis onto the dendrites of pyramidal neurons. Two successive activations of synaptic inputs produced a typical NMDA spike, whereas five successive synaptic inputs produced characteristic plateau potentials, reminiscent of cortical UP states. While NMDA spikes were coupled with brief calcium transients highly restricted to the glutamate input site, the dendritic plateau potentials were accompanied by calcium influx along the entire dendritic branch. Once initiated, the glutamate-mediated dendritic plateau potentials could not be interrupted by negative voltage pulses. Activation of extrasynaptic NMDA receptors in cellular compartments void of spines is sufficient to initiate and support plateau potentials. The only requirement for sustained depolarizing events is a surplus of free glutamate near a group of extrasynaptic receptors. Highly non-linear dendritic spikes (plateau potentials) are summed in a highly sublinear fashion at the soma, revealing the cellular bases of signal compression in cortical circuits. Extrasynaptic NMDA receptors provide pyramidal neurons with a function analogous to a dynamic range compression in audio engineering. They limit or reduce the volume of “loud sounds” (i.e., strong glutamatergic inputs) and amplify “quiet sounds” (i.e., glutamatergic inputs that barely cross the dendritic threshold for local spike initiation). Our data also explain why consecutive cortical UP states have uniform amplitudes in a given neuron. PMID:22934081

2.5 Gbit/s Optical Receiver Front-End Circuit with High Sensitivity and Wide Dynamic Range

NASA Astrophysics Data System (ADS)

Zhu, Tiezhu; Mo, Taishan; Ye, Tianchun

2017-12-01

An optical receiver front-end circuit is designed for passive optical network and fabricated in a 0.18 um CMOS technology. The whole circuit consists of a transimpedance amplifier (TIA), a single-ended to differential amplifier and an output driver. The TIA employs a cascode stage as the input stage and auxiliary amplifier to reduce the miller effect. Current injecting technique is employed to enlarge the input transistor's transconductance, optimize the noise performance and overcome the lack of voltage headroom. To achieve a wide dynamic range, an automatic gain control circuit with self-adaptive function is proposed. Experiment results show an optical sensitivity of -28 dBm for a bit error rate of 10-10 at 2.5 Gbit/s and a maxim input optical power of 2 dBm using an external photodiode. The chip occupies an area of 1×0.9 mm2 and consumes around 30 mW from single 1.8 V supply. The front-end circuit can be used in various optical receivers.

High-dynamic-range scene compression in humans

NASA Astrophysics Data System (ADS)

McCann, John J.

2006-02-01

Single pixel dynamic-range compression alters a particular input value to a unique output value - a look-up table. It is used in chemical and most digital photographic systems having S-shaped transforms to render high-range scenes onto low-range media. Post-receptor neural processing is spatial, as shown by the physiological experiments of Dowling, Barlow, Kuffler, and Hubel & Wiesel. Human vision does not render a particular receptor-quanta catch as a unique response. Instead, because of spatial processing, the response to a particular quanta catch can be any color. Visual response is scene dependent. Stockham proposed an approach to model human range compression using low-spatial frequency filters. Campbell, Ginsberg, Wilson, Watson, Daly and many others have developed spatial-frequency channel models. This paper describes experiments measuring the properties of desirable spatial-frequency filters for a variety of scenes. Given the radiances of each pixel in the scene and the observed appearances of objects in the image, one can calculate the visual mask for that individual image. Here, visual mask is the spatial pattern of changes made by the visual system in processing the input image. It is the spatial signature of human vision. Low-dynamic range images with many white areas need no spatial filtering. High-dynamic-range images with many blacks, or deep shadows, require strong spatial filtering. Sun on the right and shade on the left requires directional filters. These experiments show that variable scene- scenedependent filters are necessary to mimic human vision. Although spatial-frequency filters can model human dependent appearances, the problem still remains that an analysis of the scene is still needed to calculate the scene-dependent strengths of each of the filters for each frequency.

An analysis of I/O efficient order-statistic-based techniques for noise power estimation in the HRMS sky survey's operational system

NASA Technical Reports Server (NTRS)

Zimmerman, G. A.; Olsen, E. T.

1992-01-01

Noise power estimation in the High-Resolution Microwave Survey (HRMS) sky survey element is considered as an example of a constant false alarm rate (CFAR) signal detection problem. Order-statistic-based noise power estimators for CFAR detection are considered in terms of required estimator accuracy and estimator dynamic range. By limiting the dynamic range of the value to be estimated, the performance of an order-statistic estimator can be achieved by simpler techniques requiring only a single pass of the data. Simple threshold-and-count techniques are examined, and it is shown how several parallel threshold-and-count estimation devices can be used to expand the dynamic range to meet HRMS system requirements with minimal hardware complexity. An input/output (I/O) efficient limited-precision order-statistic estimator with wide but limited dynamic range is also examined.

Visual cortex responses reflect temporal structure of continuous quasi-rhythmic sensory stimulation.

PubMed

Keitel, Christian; Thut, Gregor; Gross, Joachim

2017-02-01

Neural processing of dynamic continuous visual input, and cognitive influences thereon, are frequently studied in paradigms employing strictly rhythmic stimulation. However, the temporal structure of natural stimuli is hardly ever fully rhythmic but possesses certain spectral bandwidths (e.g. lip movements in speech, gestures). Examining periodic brain responses elicited by strictly rhythmic stimulation might thus represent ideal, yet isolated cases. Here, we tested how the visual system reflects quasi-rhythmic stimulation with frequencies continuously varying within ranges of classical theta (4-7Hz), alpha (8-13Hz) and beta bands (14-20Hz) using EEG. Our findings substantiate a systematic and sustained neural phase-locking to stimulation in all three frequency ranges. Further, we found that allocation of spatial attention enhances EEG-stimulus locking to theta- and alpha-band stimulation. Our results bridge recent findings regarding phase locking ("entrainment") to quasi-rhythmic visual input and "frequency-tagging" experiments employing strictly rhythmic stimulation. We propose that sustained EEG-stimulus locking can be considered as a continuous neural signature of processing dynamic sensory input in early visual cortices. Accordingly, EEG-stimulus locking serves to trace the temporal evolution of rhythmic as well as quasi-rhythmic visual input and is subject to attentional bias. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

A human factors approach to range scheduling for satellite control

NASA Technical Reports Server (NTRS)

Wright, Cameron H. G.; Aitken, Donald J.

1991-01-01

Range scheduling for satellite control presents a classical problem: supervisory control of a large-scale dynamic system, with unwieldy amounts of interrelated data used as inputs to the decision process. Increased automation of the task, with the appropriate human-computer interface, is highly desirable. The development and user evaluation of a semi-automated network range scheduling system is described. The system incorporates a synergistic human-computer interface consisting of a large screen color display, voice input/output, a 'sonic pen' pointing device, a touchscreen color CRT, and a standard keyboard. From a human factors standpoint, this development represents the first major improvement in almost 30 years to the satellite control network scheduling task.

High dynamic range charge measurements

DOEpatents

De Geronimo, Gianluigi

2012-09-04

A charge amplifier for use in radiation sensing includes an amplifier, at least one switch, and at least one capacitor. The switch selectively couples the input of the switch to one of at least two voltages. The capacitor is electrically coupled in series between the input of the amplifier and the input of the switch. The capacitor is electrically coupled to the input of the amplifier without a switch coupled therebetween. A method of measuring charge in radiation sensing includes selectively diverting charge from an input of an amplifier to an input of at least one capacitor by selectively coupling an output of the at least one capacitor to one of at least two voltages. The input of the at least one capacitor is operatively coupled to the input of the amplifier without a switch coupled therebetween. The method also includes calculating a total charge based on a sum of the amplified charge and the diverted charge.

Propagating waves can explain irregular neural dynamics.

PubMed

Keane, Adam; Gong, Pulin

2015-01-28

Cortical neurons in vivo fire quite irregularly. Previous studies about the origin of such irregular neural dynamics have given rise to two major models: a balanced excitation and inhibition model, and a model of highly synchronized synaptic inputs. To elucidate the network mechanisms underlying synchronized synaptic inputs and account for irregular neural dynamics, we investigate a spatially extended, conductance-based spiking neural network model. We show that propagating wave patterns with complex dynamics emerge from the network model. These waves sweep past neurons, to which they provide highly synchronized synaptic inputs. On the other hand, these patterns only emerge from the network with balanced excitation and inhibition; our model therefore reconciles the two major models of irregular neural dynamics. We further demonstrate that the collective dynamics of propagating wave patterns provides a mechanistic explanation for a range of irregular neural dynamics, including the variability of spike timing, slow firing rate fluctuations, and correlated membrane potential fluctuations. In addition, in our model, the distributions of synaptic conductance and membrane potential are non-Gaussian, consistent with recent experimental data obtained using whole-cell recordings. Our work therefore relates the propagating waves that have been widely observed in the brain to irregular neural dynamics. These results demonstrate that neural firing activity, although appearing highly disordered at the single-neuron level, can form dynamical coherent structures, such as propagating waves at the population level. Copyright © 2015 the authors 0270-6474/15/351591-15$15.00/0.

High-sensitivity DPSK receiver for high-bandwidth free-space optical communication links.

PubMed

Juarez, Juan C; Young, David W; Sluz, Joseph E; Stotts, Larry B

2011-05-23

A high-sensitivity modem and high-dynamic range optical automatic gain controller (OAGC) have been developed to provide maximum link margin and to overcome the dynamic nature of free-space optical links. A sensitivity of -48.9 dBm (10 photons per bit) at 10 Gbps was achieved employing a return-to-zero differential phase shift keying based modem and a commercial Reed-Solomon forward error correction system. Low-noise optical gain was provided by an OAGC with a noise figure of 4.1 dB (including system required input loses) and a dynamic range of greater than 60 dB.

CMOS Amperometric ADC With High Sensitivity, Dynamic Range and Power Efficiency for Air Quality Monitoring.

PubMed

Li, Haitao; Boling, C Sam; Mason, Andrew J

2016-08-01

Airborne pollutants are a leading cause of illness and mortality globally. Electrochemical gas sensors show great promise for personal air quality monitoring to address this worldwide health crisis. However, implementing miniaturized arrays of such sensors demands high performance instrumentation circuits that simultaneously meet challenging power, area, sensitivity, noise and dynamic range goals. This paper presents a new multi-channel CMOS amperometric ADC featuring pixel-level architecture for gas sensor arrays. The circuit combines digital modulation of input currents and an incremental Σ∆ ADC to achieve wide dynamic range and high sensitivity with very high power efficiency and compact size. Fabricated in 0.5 [Formula: see text] CMOS, the circuit was measured to have 164 dB cross-scale dynamic range, 100 fA sensitivity while consuming only 241 [Formula: see text] and 0.157 [Formula: see text] active area per channel. Electrochemical experiments with liquid and gas targets demonstrate the circuit's real-time response to a wide range of analyte concentrations.

Note: A high dynamic range, linear response transimpedance amplifier.

PubMed

Eckel, S; Sushkov, A O; Lamoreaux, S K

2012-02-01

We have built a high dynamic range (nine decade) transimpedance amplifier with a linear response. The amplifier uses junction-gate field effect transistors (JFETs) to switch between three different resistors in the feedback of a low input bias current operational amplifier. This allows for the creation of multiple outputs, each with a linear response and a different transimpedance gain. The overall bandwidth of the transimpedance amplifier is set by the bandwidth of the most sensitive range. For our application, we demonstrate a three-stage amplifier with transimpedance gains of approximately 10(9)Ω, 3 × 10(7)Ω, and 10(4)Ω with a bandwidth of 100 Hz.

Optimal intravenous infusion to decrease the haematocrit level in patient of DHF infection

NASA Astrophysics Data System (ADS)

Handayani, D.; Nuraini, N.; Saragih, R.; Wijaya, K. P.; Naiborhu, J.

2014-02-01

The optimal control of infusion model for Dengue Hemorrhagic Fever (DHF) infection is formulated here. The infusion model will be presented in form of haematocrit level. The input control aim to normalize the haematocrit level and is expressed as infusion volume on mL/day. The stability near the equilibrium points will be analyzed. Numerical simulation shows the dynamic of each infection compartments which gives a description of within-host dynamic of dengue virus. These results show particularly that infected compartments tend to be vanished in ±15days after the onset of the virus. In fact, without any control added, the haematocrit level will decrease but not up to the normal level. Therefore the effective haematocrit normalization should be done with the treatment control. Control treatment for a fixed time using a control input can bring haematocrit level to normal range 42-47%. The optimal control in this paper is divided into three cases, i.e. fixed end point, constrained input, and tracking haematocrit state. Each case shows different infection condition in human body. However, all cases require that the haematocrit level to be in normal range in fixed final time.

Design of a Multi-Channel Front-End Readout ASIC With Low Noise and Large Dynamic Input Range for APD-Based PET Imaging

NASA Astrophysics Data System (ADS)

Fang, X. C.; Hu-Guo, Ch.; Ollivier-Henry, N.; Brasse, D.; Hu, Y.

2010-06-01

This paper represents the design of a low-noise, wide band multi-channel readout integrated circuit (IC) used as front end readout electronics of avalanche photo diodes (APD) dedicated to a small animal positron emission tomography (PET) system. The first ten-channel prototype chip (APD-Chip) of the analog parts has been designed and fabricated in a 0.35 μm CMOS process. Every channel of the APD_Chip includes a charge-sensitive preamplifier (CSA), a CR-(RC)2 shaper, and an analog buffer. In a channel, the CSA reads charge signals (10 bits dynamic range) from an APD array having 10 pF of capacitance per pixel. A linearized degenerated differential pair which ensures high linearity in all dynamical range is used as the high feedback resistor for preventing pile up of signals. The designed CSA has the capability of compensating automatically up to 200 nA leakage current from the detector. The CR-(RC)2 shaper filters and shapes the output signal of the CSA. An equivalent input noise charge obtained from test is 275 e -+ 10 e-/pF. In this paper the prototype is presented for both its theoretical analysis and its test results.

Reconstructing Interlaced High-Dynamic-Range Video Using Joint Learning.

PubMed

Inchang Choi; Seung-Hwan Baek; Kim, Min H

2017-11-01

For extending the dynamic range of video, it is a common practice to capture multiple frames sequentially with different exposures and combine them to extend the dynamic range of each video frame. However, this approach results in typical ghosting artifacts due to fast and complex motion in nature. As an alternative, video imaging with interlaced exposures has been introduced to extend the dynamic range. However, the interlaced approach has been hindered by jaggy artifacts and sensor noise, leading to concerns over image quality. In this paper, we propose a data-driven approach for jointly solving two specific problems of deinterlacing and denoising that arise in interlaced video imaging with different exposures. First, we solve the deinterlacing problem using joint dictionary learning via sparse coding. Since partial information of detail in differently exposed rows is often available via interlacing, we make use of the information to reconstruct details of the extended dynamic range from the interlaced video input. Second, we jointly solve the denoising problem by tailoring sparse coding to better handle additive noise in low-/high-exposure rows, and also adopt multiscale homography flow to temporal sequences for denoising. We anticipate that the proposed method will allow for concurrent capture of higher dynamic range video frames without suffering from ghosting artifacts. We demonstrate the advantages of our interlaced video imaging compared with the state-of-the-art high-dynamic-range video methods.

Extending Integrate-and-Fire Model Neurons to Account for the Effects of Weak Electric Fields and Input Filtering Mediated by the Dendrite.

PubMed

Aspart, Florian; Ladenbauer, Josef; Obermayer, Klaus

2016-11-01

Transcranial brain stimulation and evidence of ephaptic coupling have recently sparked strong interests in understanding the effects of weak electric fields on the dynamics of brain networks and of coupled populations of neurons. The collective dynamics of large neuronal populations can be efficiently studied using single-compartment (point) model neurons of the integrate-and-fire (IF) type as their elements. These models, however, lack the dendritic morphology required to biophysically describe the effect of an extracellular electric field on the neuronal membrane voltage. Here, we extend the IF point neuron models to accurately reflect morphology dependent electric field effects extracted from a canonical spatial "ball-and-stick" (BS) neuron model. Even in the absence of an extracellular field, neuronal morphology by itself strongly affects the cellular response properties. We, therefore, derive additional components for leaky and nonlinear IF neuron models to reproduce the subthreshold voltage and spiking dynamics of the BS model exposed to both fluctuating somatic and dendritic inputs and an extracellular electric field. We show that an oscillatory electric field causes spike rate resonance, or equivalently, pronounced spike to field coherence. Its resonance frequency depends on the location of the synaptic background inputs. For somatic inputs the resonance appears in the beta and gamma frequency range, whereas for distal dendritic inputs it is shifted to even higher frequencies. Irrespective of an external electric field, the presence of a dendritic cable attenuates the subthreshold response at the soma to slowly-varying somatic inputs while implementing a low-pass filter for distal dendritic inputs. Our point neuron model extension is straightforward to implement and is computationally much more efficient compared to the original BS model. It is well suited for studying the dynamics of large populations of neurons with heterogeneous dendritic morphology with (and without) the influence of weak external electric fields.

Extending Integrate-and-Fire Model Neurons to Account for the Effects of Weak Electric Fields and Input Filtering Mediated by the Dendrite

PubMed Central

Obermayer, Klaus

2016-01-01

Transcranial brain stimulation and evidence of ephaptic coupling have recently sparked strong interests in understanding the effects of weak electric fields on the dynamics of brain networks and of coupled populations of neurons. The collective dynamics of large neuronal populations can be efficiently studied using single-compartment (point) model neurons of the integrate-and-fire (IF) type as their elements. These models, however, lack the dendritic morphology required to biophysically describe the effect of an extracellular electric field on the neuronal membrane voltage. Here, we extend the IF point neuron models to accurately reflect morphology dependent electric field effects extracted from a canonical spatial “ball-and-stick” (BS) neuron model. Even in the absence of an extracellular field, neuronal morphology by itself strongly affects the cellular response properties. We, therefore, derive additional components for leaky and nonlinear IF neuron models to reproduce the subthreshold voltage and spiking dynamics of the BS model exposed to both fluctuating somatic and dendritic inputs and an extracellular electric field. We show that an oscillatory electric field causes spike rate resonance, or equivalently, pronounced spike to field coherence. Its resonance frequency depends on the location of the synaptic background inputs. For somatic inputs the resonance appears in the beta and gamma frequency range, whereas for distal dendritic inputs it is shifted to even higher frequencies. Irrespective of an external electric field, the presence of a dendritic cable attenuates the subthreshold response at the soma to slowly-varying somatic inputs while implementing a low-pass filter for distal dendritic inputs. Our point neuron model extension is straightforward to implement and is computationally much more efficient compared to the original BS model. It is well suited for studying the dynamics of large populations of neurons with heterogeneous dendritic morphology with (and without) the influence of weak external electric fields. PMID:27893786

A 1- to 10-GHz downconverter for high-resolution microwave survey

NASA Technical Reports Server (NTRS)

Mcwatters, D.

1994-01-01

A downconverter was designed, built, and tested for the High Resolution Microwave Survey project. The input frequency range is 1 to 10 GHz with instantaneous bandwidth of 350 MHz and dynamic range of 125 dB/Hz. Requirements were derived for the local oscillators and special design techniques were implemented to achieve the high degree of spectral purity required.

High dynamic range pixel architecture for advanced diagnostic medical x-ray imaging applications

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

Izadi, Mohammad Hadi; Karim, Karim S.

2006-05-15

The most widely used architecture in large-area amorphous silicon (a-Si) flat panel imagers is a passive pixel sensor (PPS), which consists of a detector and a readout switch. While the PPS has the advantage of being compact and amenable toward high-resolution imaging, small PPS output signals are swamped by external column charge amplifier and data line thermal noise, which reduce the minimum readable sensor input signal. In contrast to PPS circuits, on-pixel amplifiers in a-Si technology reduce readout noise to levels that can meet even the stringent requirements for low noise digital x-ray fluoroscopy (<1000 noise electrons). However, larger voltagesmore » at the pixel input cause the output of the amplified pixel to become nonlinear thus reducing the dynamic range. We reported a hybrid amplified pixel architecture based on a combination of PPS and amplified pixel designs that, in addition to low noise performance, also resulted in large-signal linearity and consequently higher dynamic range [K. S. Karim et al., Proc. SPIE 5368, 657 (2004)]. The additional benefit in large-signal linearity, however, came at the cost of an additional pixel transistor. We present an amplified pixel design that achieves the goals of low noise performance and large-signal linearity without the need for an additional pixel transistor. Theoretical calculations and simulation results for noise indicate the applicability of the amplified a-Si pixel architecture for high dynamic range, medical x-ray imaging applications that require switching between low exposure, real-time fluoroscopy and high-exposure radiography.« less

Density-dependent microbial turnover improves soil carbon model predictions of long-term litter manipulations

NASA Astrophysics Data System (ADS)

Georgiou, Katerina; Abramoff, Rose; Harte, John; Riley, William; Torn, Margaret

2017-04-01

Climatic, atmospheric, and land-use changes all have the potential to alter soil microbial activity via abiotic effects on soil or mediated by changes in plant inputs. Recently, many promising microbial models of soil organic carbon (SOC) decomposition have been proposed to advance understanding and prediction of climate and carbon (C) feedbacks. Most of these models, however, exhibit unrealistic oscillatory behavior and SOC insensitivity to long-term changes in C inputs. Here we diagnose the sources of instability in four models that span the range of complexity of these recent microbial models, by sequentially adding complexity to a simple model to include microbial physiology, a mineral sorption isotherm, and enzyme dynamics. We propose a formulation that introduces density-dependence of microbial turnover, which acts to limit population sizes and reduce oscillations. We compare these models to results from 24 long-term C-input field manipulations, including the Detritus Input and Removal Treatment (DIRT) experiments, to show that there are clear metrics that can be used to distinguish and validate the inherent dynamics of each model structure. We find that widely used first-order models and microbial models without density-dependence cannot readily capture the range of long-term responses observed across the DIRT experiments as a direct consequence of their model structures. The proposed formulation improves predictions of long-term C-input changes, and implies greater SOC storage associated with CO2-fertilization-driven increases in C inputs over the coming century compared to common microbial models. Finally, we discuss our findings in the context of improving microbial model behavior for inclusion in Earth System Models.

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

A 155-dB Dynamic Range Current Measurement Front End for Electrochemical Biosensing.

PubMed

Dai, Shanshan; Perera, Rukshan T; Yang, Zi; Rosenstein, Jacob K

2016-10-01

An integrated current measurement system with ultra wide dynamic range is presented and fabricated in a 180-nm CMOS technology. Its dual-mode design provides concurrent voltage and frequency outputs, without requiring an external clock source. An integrator-differentiator core provides a voltage output with a noise floor of 11.6 fA/ [Formula: see text] and a -3 dB cutoff frequency of 1.4 MHz. It is merged with an asynchronous current-to-frequency converter, which generates an output frequency linearly proportional to the input current. Together, the voltage and frequency outputs yield a current measurement range of 155 dB, spanning from 204 fA (100 Hz) or 1.25 pA (10 kHz) to 11.6 μA. The proposed architecture's low noise, wide bandwidth, and wide dynamic range make it ideal for measurements of highly nonlinear electrochemical and electrophysiological systems.

Josephson Parametric Reflection Amplifier with Integrated Directionality

NASA Astrophysics Data System (ADS)

Westig, M. P.; Klapwijk, T. M.

2018-06-01

A directional superconducting parametric amplifier in the GHz frequency range is designed and analyzed, suitable for low-power read-out of microwave kinetic inductance detectors employed in astrophysics and when combined with a nonreciprocal device at its input also for circuit quantum electrodynamics. It consists of a one-wavelength-long nondegenerate Josephson parametric reflection amplifier circuit. The device has two Josephson-junction oscillators, connected via a tailored impedance to an on-chip passive circuit which directs the in- to the output port. The amplifier provides a gain of 20 dB over a bandwidth of 220 MHz on the signal as well as on the idler portion of the amplified input and the total photon shot noise referred to the input corresponds to maximally approximately 1.3 photons per second per Hertz of bandwidth. We predict a factor of 4 increase in dynamic range compared to conventional Josephson parametric amplifiers.

Computational model of electrically coupled, intrinsically distinct pacemaker neurons.

PubMed

Soto-Treviño, Cristina; Rabbah, Pascale; Marder, Eve; Nadim, Farzan

2005-07-01

Electrical coupling between neurons with similar properties is often studied. Nonetheless, the role of electrical coupling between neurons with widely different intrinsic properties also occurs, but is less well understood. Inspired by the pacemaker group of the crustacean pyloric network, we developed a multicompartment, conductance-based model of a small network of intrinsically distinct, electrically coupled neurons. In the pyloric network, a small intrinsically bursting neuron, through gap junctions, drives 2 larger, tonically spiking neurons to reliably burst in-phase with it. Each model neuron has 2 compartments, one responsible for spike generation and the other for producing a slow, large-amplitude oscillation. We illustrate how these compartments interact and determine the dynamics of the model neurons. Our model captures the dynamic oscillation range measured from the isolated and coupled biological neurons. At the network level, we explore the range of coupling strengths for which synchronous bursting oscillations are possible. The spatial segregation of ionic currents significantly enhances the ability of the 2 neurons to burst synchronously, and the oscillation range of the model pacemaker network depends not only on the strength of the electrical synapse but also on the identity of the neuron receiving inputs. We also compare the activity of the electrically coupled, distinct neurons with that of a network of coupled identical bursting neurons. For small to moderate coupling strengths, the network of identical elements, when receiving asymmetrical inputs, can have a smaller dynamic range of oscillation than that of its constituent neurons in isolation.

Study of Static Microchannel Plate Saturation Effects for the Fast Plasma Investigation Dual Electron Spectrometers on NASA's Magnetospheric MultiScale Mission

NASA Technical Reports Server (NTRS)

Avanov, L. A.; Gliese, U.; Pollock, C. J.; Moore, T. E.; Chornay, D. J.; Barrie, A. C.; Kujawski, J. T.; Gershman, D. J.; Tucker, C. J.; Mariano, A.;

Rebound spiking in layer II medial entorhinal cortex stellate cells: Possible mechanism of grid cell function

PubMed Central

Shay, Christopher F.; Ferrante, Michele; Chapman, G. William; Hasselmo, Michael E.

2015-01-01

Rebound spiking properties of medial entorhinal cortex (mEC) stellate cells induced by inhibition may underlie their functional properties in awake behaving rats, including the temporal phase separation of distinct grid cells and differences in grid cell firing properties. We investigated rebound spiking properties using whole cell patch recording in entorhinal slices, holding cells near spiking threshold and delivering sinusoidal inputs, superimposed with realistic inhibitory synaptic inputs to test the capacity of cells to selectively respond to specific phases of inhibitory input. Stellate cells showed a specific phase range of hyperpolarizing inputs that elicited spiking, but non-stellate cells did not show phase specificity. In both cell types, the phase range of spiking output occurred between the peak and subsequent descending zero crossing of the sinusoid. The phases of inhibitory inputs that induced spikes shifted earlier as the baseline sinusoid frequency increased, while spiking output shifted to later phases. Increases in magnitude of the inhibitory inputs shifted the spiking output to earlier phases. Pharmacological blockade of h-current abolished the phase selectivity of hyperpolarizing inputs eliciting spikes. A network computational model using cells possessing similar rebound properties as found in vitro produces spatially periodic firing properties resembling grid cell firing when a simulated animal moves along a linear track. These results suggest that the ability of mEC stellate cells to fire rebound spikes in response to a specific range of phases of inhibition could support complex attractor dynamics that provide completion and separation to maintain spiking activity of specific grid cell populations. PMID:26385258

Jupiter's Auroral Energy Input Observed by Hisaki/EXCEED and its Modulations by Io's Volcanic Activity

NASA Astrophysics Data System (ADS)

Tao, C.; Kimura, T.; Tsuchiya, F.; Murakami, G.; Yoshioka, K.; Kita, H.; Yamazaki, A.; Kasaba, Y.; Yoshikawa, I.; Fujimoto, M.

2016-12-01

Aurora is an important indicator representing the momentum transfer from the fast-rotating outer planet to the magnetosphere and the energy input into the atmosphere through the magnetosphere-ionosphere coupling. Long-term monitoring of Jupiter's northern aurora was achieved by the Extreme Ultraviolet (EUV) spectrometer called EXCEED (Extreme Ultraviolet Spectroscope for Exospheric Dynamics) onboard JAXA's Earth-orbiting planetary space telescope Hisaki until today after its launch in September 2013. We have proceeded the statistical survey of the Jupiter's auroral energy input into the upper atmosphere. The auroral electron energy is estimated using a hydrocarbon color ratio (CR) adopted for the wavelength range of EXCEED, and the emission power in the long wavelength range 138.5-144.8 nm is used as an indicator of total emitted power before hydrocarbon absorption and auroral electron energy flux. Temporal dynamic variation of the auroral intensity was detected when Io's volcanic activity and thus EUV emission from the Io plasma torus are enhanced in the early 2015. Average of the total input power over 80 days increases by 10% with sometimes sporadically more than a factor of 3 upto 7, while the CR indicates the auroral electron energy decrease by 20% during the volcanic event compared to the other period. This indicates much more increase in the current system and Joule heating which contributes heating of the upper atmosphere. We will discuss the impact of this event on the upper atmosphere and ionosphere.

Simulating coupled carbon and nitrogen dynamics following mountain pine beetle outbreaks in the western United States

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

Edburg, Steven L.; Hicke, Jeffrey A.; Lawrence, David M.

2011-01-01

Insect outbreaks are major ecosystem disturbances, affecting a similar area as forest fires annually across North America. Tree mortality caused by epidemics of bark beetles alters carbon cycling in the first several years following the disturbance by reducing stand-level primary production and increasing decomposition rates. The few studies of biogeochemical cycling following outbreaks have shown a range of impacts from small responses of net carbon fluxes in the first several years after a severe outbreak to large forest areas that are sources of carbon to the atmosphere for decades. To gain more understanding about causes of this range of responses,more » we used an ecosystem model to assess impacts of different bark beetle outbreak conditions on coupled carbon and nitrogen cycling. We modified the Community Land Model with prognostic carbon and nitrogen to include prescribed bark beetle outbreaks. We then compared control simulations (without a bark beetle outbreak) to simulations with various mortality severity, durations of outbreak, and snagfall dynamics to quantify the range of carbon flux responses and recovery rates of net ecosystem exchange to a range of realistic outbreak conditions. Prescribed mortality by beetles reduced leaf area and thus productivity. Gross primary productivity decreased by as much as 80% for a severe outbreak (95% mortality) and by 10% for less severe outbreaks (25% mortality). Soil mineral nitrogen dynamics (immobilization and plant uptake) were important in governing post-outbreak productivity, and were strongly modulated by carbon inputs to the soil from killed trees. Initial increases in heterotrophic respiration caused by a pulse of labile carbon from roots were followed by a slight reduction (from pre-snagfall reduced inputs), then a secondary increase (from inputs due to snagfall). Secondary increases in heterotrophic respiration were largest for simulated windthrow of snags after a prescribed snagfall delay period. Net ecosystem productivity recovered within 40 years for all simulations, with the largest increases in the first 10 years. Our simulations illustrate that, given the large variability in bark beetle outbreak conditions, a wide range of responses in carbon and nitrogen dynamics can occur. The fraction of trees killed, timing of snagfall, snagfall rate, and management decisions as to whether or not to remove snags for harvesting or for fire prevention will have a major impact on post-outbreak carbon fluxes up to 100 years following an outbreak.« less

Shaper design in CMOS for high dynamic range

DOEpatents

De Geronimo, Gianluigi; Li, Shaorui

2015-06-30

An analog filter is presented that comprises a chain of filter stages, a feedback resistor for providing a negative feedback, and a feedback capacitor for providing a positive feedback. Each filter stage has an input node and an output node. The output node of a filter stage is connected to the input node of an immediately succeeding filter stage through a resistor. The feedback resistor has a first end connected to the output node of the last filter stage along the chain of filter stages, and a second end connected to the input node of a first preceding filter stage. The feedback capacitor has a first end connected to the output node of one of the chain of filter stages, and a second end connected to the input node of a second preceding filter stage.

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.

Robust Control for the Mercury Laser Altimeter

NASA Technical Reports Server (NTRS)

Rosenberg, Jacob S.

2006-01-01

Mercury Laser Altimeter Science Algorithms is a software system for controlling the laser altimeter aboard the Messenger spacecraft, which is to enter into orbit about Mercury in 2011. The software will control the altimeter by dynamically modifying hardware inputs for gain, threshold, channel-disable flags, range-window start location, and range-window width, by using ranging information provided by the spacecraft and noise counts from instrument hardware. In addition, because of severe bandwidth restrictions, the software also selects returns for downlink.

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.

Modeling and sliding mode predictive control of the ultra-supercritical boiler-turbine system with uncertainties and input constraints.

PubMed

Tian, Zhen; Yuan, Jingqi; Zhang, Xiang; Kong, Lei; Wang, Jingcheng

2018-05-01

The coordinated control system (CCS) serves as an important role in load regulation, efficiency optimization and pollutant reduction for coal-fired power plants. The CCS faces with tough challenges, such as the wide-range load variation, various uncertainties and constraints. This paper aims to improve the load tacking ability and robustness for boiler-turbine units under wide-range operation. To capture the key dynamics of the ultra-supercritical boiler-turbine system, a nonlinear control-oriented model is developed based on mechanism analysis and model reduction techniques, which is validated with the history operation data of a real 1000 MW unit. To simultaneously address the issues of uncertainties and input constraints, a discrete-time sliding mode predictive controller (SMPC) is designed with the dual-mode control law. Moreover, the input-to-state stability and robustness of the closed-loop system are proved. Simulation results are presented to illustrate the effectiveness of the proposed control scheme, which achieves good tracking performance, disturbance rejection ability and compatibility to input constraints. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Application of automatic gain control for radiometer diagnostic in SST-1 tokamak.

PubMed

Makwana, Foram R; Siju, Varsha; Edappala, Praveenlal; Pathak, S K

2017-12-01

This paper describes the characterisation of a negative feedback type of automatic gain control (AGC) circuit that will be an integral part of the heterodyne radiometer system operating at a frequency range of 75-86 GHz at SST-1 tokamak. The developed AGC circuit is a combination of variable gain amplifier and log amplifier which provides both gain and attenuation typically up to 15 dB and 45 dB, respectively, at a fixed set point voltage and it has been explored for the first time in tokamak radiometry application. The other important characteristics are that it exhibits a very fast response time of 390 ns to understand the fast dynamics of electron cyclotron emission and can operate at very wide input RF power dynamic range of around 60 dB that ensures signal level within the dynamic range of the detection system.

A 1-channel 3-band wide dynamic range compression chip for vibration transducer of implantable hearing aids.

PubMed

Kim, Dongwook; Seong, Kiwoong; Kim, Myoungnam; Cho, Jinho; Lee, Jyunghyun

2014-01-01

In this paper, a digital audio processing chip which uses a wide dynamic range compression (WDRC) algorithm is designed and implemented for implantable hearing aids system. The designed chip operates at a single voltage of 3.3V and drives a 16 bit parallel input and output at 32 kHz sample. The designed chip has 1-channel 3-band WDRC composed of a FIR filter bank, a level detector, and a compression part. To verify the performance of the designed chip, we measured the frequency separations of bands and compression gain control to reflect the hearing threshold level.

High-cut characteristics of the baroreflex neural arc preserve baroreflex gain against pulsatile pressure.

PubMed

Kawada, Toru; Zheng, Can; Yanagiya, Yusuke; Uemura, Kazunori; Miyamoto, Tadayoshi; Inagaki, Masashi; Shishido, Toshiaki; Sugimachi, Masaru; Sunagawa, Kenji

2002-03-01

A transfer function from baroreceptor pressure input to sympathetic nerve activity (SNA) shows derivative characteristics in the frequency range below 0.8 Hz in rabbits. These derivative characteristics contribute to a quick and stable arterial pressure (AP) regulation. However, if the derivative characteristics hold up to heart rate frequency, the pulsatile pressure input will yield a markedly augmented SNA signal. Such a signal would saturate the baroreflex signal transduction, thereby disabling the baroreflex regulation of AP. We hypothesized that the transfer gain at heart rate frequency would be much smaller than that predicted from extrapolating the derivative characteristics. In anesthetized rabbits (n = 6), we estimated the neural arc transfer function in the frequency range up to 10 Hz. The transfer gain was lost at a rate of -20 dB/decade when the input frequency exceeded 0.8 Hz. A numerical simulation indicated that the high-cut characteristics above 0.8 Hz were effective to attenuate the pulsatile signal and preserve the open-loop gain when the baroreflex dynamic range was finite.

Automatic dynamic range adjustment for ultrasound B-mode imaging.

PubMed

Lee, Yeonhwa; Kang, Jinbum; Yoo, Yangmo

2015-02-01

In medical ultrasound imaging, dynamic range (DR) is defined as the difference between the maximum and minimum values of the displayed signal to display and it is one of the most essential parameters that determine its image quality. Typically, DR is given with a fixed value and adjusted manually by operators, which leads to low clinical productivity and high user dependency. Furthermore, in 3D ultrasound imaging, DR values are unable to be adjusted during 3D data acquisition. A histogram matching method, which equalizes the histogram of an input image based on that from a reference image, can be applied to determine the DR value. However, it could be lead to an over contrasted image. In this paper, a new Automatic Dynamic Range Adjustment (ADRA) method is presented that adaptively adjusts the DR value by manipulating input images similar to a reference image. The proposed ADRA method uses the distance ratio between the log average and each extreme value of a reference image. To evaluate the performance of the ADRA method, the similarity between the reference and input images was measured by computing a correlation coefficient (CC). In in vivo experiments, the CC values were increased by applying the ADRA method from 0.6872 to 0.9870 and from 0.9274 to 0.9939 for kidney and liver data, respectively, compared to the fixed DR case. In addition, the proposed ADRA method showed to outperform the histogram matching method with in vivo liver and kidney data. When using 3D abdominal data with 70 frames, while the CC value from the ADRA method is slightly increased (i.e., 0.6%), the proposed method showed improved image quality in the c-plane compared to its fixed counterpart, which suffered from a shadow artifact. These results indicate that the proposed method can enhance image quality in 2D and 3D ultrasound B-mode imaging by improving the similarity between the reference and input images while eliminating unnecessary manual interaction by the user. Copyright © 2014 Elsevier B.V. All rights reserved.

Analysis of dynamic channel power equalization by using nonlinear amplifying Sagnac interferometer for ASK-WDM optical transmission

NASA Astrophysics Data System (ADS)

Qu, Feng; Liu, Xiaoming; Zhao, Jianhui

2004-05-01

A power equalization using an asymmetric nonlinear amplifying Sagnac interferometer (NASI) for ASK modulation is studied numerically. A nonreciprocal phase bias was proposed to be introduced into the structure. The nonreciprocal phase bias reduces not only the demanding for amplifier power or fiber non-linearity, but also increase the dynamic input power range. The power equalization is demonstrated for RZ modulation by nonlinear phase analysis and eye diagram simulation.

Linking Watershed Nitrogen Sources with Nitrogen Dynamics in Rivers of Western Oregon, USA

NASA Astrophysics Data System (ADS)

Sobota, D. J.; Compton, J.; Goodwin, K. E.

2012-12-01

We constructed contemporary nitrogen (N) budgets for 25 river basins in the Willamette River Basin (WRB) of western Oregon, USA, to improve the understanding of how recent trends in human-driven N loading have influenced riverine N dynamics in the region. Nearly 20% of WRB stream length is currently in fair or poor condition because of high N concentrations. Additionally, nitrate contamination of drinking water affects at least 8,000 people in the WRB. We hypothesized that 1) the majority of N inputs in the WRB would originate from agricultural activities in lowland portions of watersheds, 2) annual riverine N yield (kg/ha/yr) would correspond to annual per area watershed N inputs, and 3) riverine N yields would be seasonal and highest during winter due to the region's Mediterranean climate. We calculated average annual N inputs for each study basin by summing newly available datasets describing spatially explicit N inputs of synthetic fertilizer, atmospheric deposition, crop biological N2 fixation, biological N2 fixation by red alder (Alnus rubra Bong.), livestock manure, and point sources for the period 1996 - 2007. Annual and seasonal riverine N exports were estimated with the USGS model LOADEST calibrated to N concentration data collected during the study period. We estimated that two-thirds of total N input to the WRB study basins in the 2000s came from synthetic fertilizer application. Nearly all fertilizer application occurred on the lowlands near watershed mouths. We found a wide range of riverine N yields from the study basins, ranging from one to 70 kg N/ha/yr. Across the study basins, N export was more strongly correlated to fertilizer application rates than to percent of agricultural area in the watershed. Low watershed N yields reflected a high proportion of watershed area in the forested Cascade Mountain Range, which received low N inputs mainly from atmospheric deposition. N yields from study basins were strongly seasonal, with at least 50%, and often 75%, of annual N yield occurring in fall and winter months. Our results suggest that that spatially explicit data on specific crop types and crop practices are valuable for explaining spatial and temporal variation of nutrient concentrations in WRB rivers. This emphasizes the need for careful tracking of non-point N inputs to inform water quality monitoring and management.

Estimation of the longitudinal and lateral-directional aerodynamic parameters from flight data for the NASA F/A-18 HARV

NASA Technical Reports Server (NTRS)

Napolitano, Marcello R.

1996-01-01

This progress report presents the results of an investigation focused on parameter identification for the NASA F/A-18 HARV. This aircraft was used in the high alpha research program at the NASA Dryden Flight Research Center. In this study the longitudinal and lateral-directional stability derivatives are estimated from flight data using the Maximum Likelihood method coupled with a Newton-Raphson minimization technique. The objective is to estimate an aerodynamic model describing the aircraft dynamics over a range of angle of attack from 5 deg to 60 deg. The mathematical model is built using the traditional static and dynamic derivative buildup. Flight data used in this analysis were from a variety of maneuvers. The longitudinal maneuvers included large amplitude multiple doublets, optimal inputs, frequency sweeps, and pilot pitch stick inputs. The lateral-directional maneuvers consisted of large amplitude multiple doublets, optimal inputs and pilot stick and rudder inputs. The parameter estimation code pEst, developed at NASA Dryden, was used in this investigation. Results of the estimation process from alpha = 5 deg to alpha = 60 deg are presented and discussed.

Electrical pulse generator

DOEpatents

Norris, Neil J.

1979-01-01

A technique for generating high-voltage, wide dynamic range, shaped electrical pulses in the nanosecond range. Two transmission lines are coupled together by resistive elements distributed along the length of the lines. The conductance of each coupling resistive element as a function of its position along the line is selected to produce the desired pulse shape in the output line when an easily produced pulse, such as a step function pulse, is applied to the input line.

Dynamic control and information processing in chemical reaction systems by tuning self-organization behavior

NASA Astrophysics Data System (ADS)

Lebiedz, Dirk; Brandt-Pollmann, Ulrich

2004-09-01

Specific external control of chemical reaction systems and both dynamic control and signal processing as central functions in biochemical reaction systems are important issues of modern nonlinear science. For example nonlinear input-output behavior and its regulation are crucial for the maintainance of the life process that requires extensive communication between cells and their environment. An important question is how the dynamical behavior of biochemical systems is controlled and how they process information transmitted by incoming signals. But also from a general point of view external forcing of complex chemical reaction processes is important in many application areas ranging from chemical engineering to biomedicine. In order to study such control issues numerically, here, we choose a well characterized chemical system, the CO oxidation on Pt(110), which is interesting per se as an externally forced chemical oscillator model. We show numerically that tuning of temporal self-organization by input signals in this simple nonlinear chemical reaction exhibiting oscillatory behavior can in principle be exploited for both specific external control of dynamical system behavior and processing of complex information.

Impact of Cross-Axis Structural Dynamics on Validation of Linear Models for Space Launch System

NASA Technical Reports Server (NTRS)

Pei, Jing; Derry, Stephen D.; Zhou Zhiqiang; Newsom, Jerry R.

2014-01-01

A feasibility study was performed to examine the advisability of incorporating a set of Programmed Test Inputs (PTIs) during the Space Launch System (SLS) vehicle flight. The intent of these inputs is to provide validation to the preflight models for control system stability margins, aerodynamics, and structural dynamics. During October 2009, Ares I-X program was successful in carrying out a series of PTI maneuvers which provided a significant amount of valuable data for post-flight analysis. The resulting data comparisons showed excellent agreement with the preflight linear models across the frequency spectrum of interest. However unlike Ares I-X, the structural dynamics associated with the SLS boost phase configuration are far more complex and highly coupled in all three axes. This presents a challenge when implementing this similar system identification technique to SLS. Preliminary simulation results show noticeable mismatches between PTI validation and analytical linear models in the frequency range of the structural dynamics. An alternate approach was examined which demonstrates the potential for better overall characterization of the system frequency response as well as robustness of the control design.

Variation in active and passive resource inputs to experimental pools: mechanisms and possible consequences for food webs

USGS Publications Warehouse

Kraus, Johanna M.; Pletcher, Leanna T.; Vonesh, James R.

2010-01-01

1. Cross-ecosystem movements of resources, including detritus, nutrients and living prey, can strongly influence food web dynamics in recipient habitats. Variation in resource inputs is thought to be driven by factors external to the recipient habitat (e.g. donor habitat productivity and boundary conditions). However, inputs of or by ‘active’ living resources may be strongly influenced by recipient habitat quality when organisms exhibit behavioural habitat selection when crossing ecosystem boundaries. 2. To examine whether behavioural responses to recipient habitat quality alter the relative inputs of ‘active’ living and ‘passive’ detrital resources to recipient food webs, we manipulated the presence of caged predatory fish and measured biomass, energy and organic content of inputs to outdoor experimental pools of adult aquatic insects, frog eggs, terrestrial plant matter and terrestrial arthropods. 3. Caged fish reduced the biomass, energy and organic matter donated to pools by tree frog eggs by ∼70%, but did not alter insect colonisation or passive allochthonous inputs of terrestrial arthropods and plant material. Terrestrial plant matter and adult aquatic insects provided the most energy and organic matter inputs to the pools (40–50%), while terrestrial arthropods provided the least (7%). Inputs of frog egg were relatively small but varied considerably among pools and over time (3%, range = 0–20%). Absolute and proportional amounts varied by input type. 4. Aquatic predators can strongly affect the magnitude of active, but not passive, inputs and that the effect of recipient habitat quality on active inputs is variable. Furthermore, some active inputs (i.e. aquatic insect colonists) can provide similar amounts of energy and organic matter as passive inputs of terrestrial plant matter, which are well known to be important. Because inputs differ in quality and the trophic level they subsidise, proportional changes in input type could have strong effects on recipient food webs. 5. Cross-ecosystem resource inputs have previously been characterised as donor-controlled. However, control by the recipient food web could lead to greater feedback between resource flow and consumer dynamics than has been appreciated so far.

Dynamics of action potential initiation in the GABAergic thalamic reticular nucleus in vivo.

PubMed

Muñoz, Fabián; Fuentealba, Pablo

2012-01-01

Understanding the neural mechanisms of action potential generation is critical to establish the way neural circuits generate and coordinate activity. Accordingly, we investigated the dynamics of action potential initiation in the GABAergic thalamic reticular nucleus (TRN) using in vivo intracellular recordings in cats in order to preserve anatomically-intact axo-dendritic distributions and naturally-occurring spatiotemporal patterns of synaptic activity in this structure that regulates the thalamic relay to neocortex. We found a wide operational range of voltage thresholds for action potentials, mostly due to intrinsic voltage-gated conductances and not synaptic activity driven by network oscillations. Varying levels of synchronous synaptic inputs produced fast rates of membrane potential depolarization preceding the action potential onset that were associated with lower thresholds and increased excitability, consistent with TRN neurons performing as coincidence detectors. On the other hand the presence of action potentials preceding any given spike was associated with more depolarized thresholds. The phase-plane trajectory of the action potential showed somato-dendritic propagation, but no obvious axon initial segment component, prominent in other neuronal classes and allegedly responsible for the high onset speed. Overall, our results suggest that TRN neurons could flexibly integrate synaptic inputs to discharge action potentials over wide voltage ranges, and perform as coincidence detectors and temporal integrators, supported by a dynamic action potential threshold.

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.

Method and apparatus for creating time-optimal commands for linear systems

NASA Technical Reports Server (NTRS)

Seering, Warren P. (Inventor); Tuttle, Timothy D. (Inventor)

2004-01-01

A system for and method of determining an input command profile for substantially any dynamic system that can be modeled as a linear system, the input command profile for transitioning an output of the dynamic system from one state to another state. The present invention involves identifying characteristics of the dynamic system, selecting a command profile which defines an input to the dynamic system based on the identified characteristics, wherein the command profile comprises one or more pulses which rise and fall at switch times, imposing a plurality of constraints on the dynamic system, at least one of the constraints being defined in terms of the switch times, and determining the switch times for the input to the dynamic system based on the command profile and the plurality of constraints. The characteristics may be related to poles and zeros of the dynamic system, and the plurality of constraints may include a dynamics cancellation constraint which specifies that the input moves the dynamic system from a first state to a second state such that the dynamic system remains substantially at the second state.

Broadband dynamic phase matching of high-order harmonic generation by a high-peak-power soliton pump field in a gas-filled hollow photonic-crystal fiber.

PubMed

Serebryannikov, Evgenii E; von der Linde, Dietrich; Zheltikov, Aleksei M

2008-05-01

Hollow-core photonic-crystal fibers are shown to enable dynamically phase-matched high-order harmonic generation by a gigawatt soliton pump field. With a careful design of the waveguide structure and an appropriate choice of input-pulse and gas parameters, a remarkably broadband phase matching can be achieved for a soliton pump field and a large group of optical harmonics in the soft-x-ray-extreme-ultraviolet spectral range.

HEVC for high dynamic range services

NASA Astrophysics Data System (ADS)

Kim, Seung-Hwan; Zhao, Jie; Misra, Kiran; Segall, Andrew

2015-09-01

Displays capable of showing a greater range of luminance values can render content containing high dynamic range information in a way such that the viewers have a more immersive experience. This paper introduces the design aspects of a high dynamic range (HDR) system, and examines the performance of the HDR processing chain in terms of compression efficiency. Specifically it examines the relation between recently introduced Society of Motion Picture and Television Engineers (SMPTE) ST 2084 transfer function and the High Efficiency Video Coding (HEVC) standard. SMPTE ST 2084 is designed to cover the full range of an HDR signal from 0 to 10,000 nits, however in many situations the valid signal range of actual video might be smaller than SMPTE ST 2084 supported range. The above restricted signal range results in restricted range of code values for input video data and adversely impacts compression efficiency. In this paper, we propose a code value remapping method that extends the restricted range code values into the full range code values so that the existing standards such as HEVC may better compress the video content. The paper also identifies related non-normative encoder-only changes that are required for remapping method for a fair comparison with anchor. Results are presented comparing the efficiency of the current approach versus the proposed remapping method for HM-16.2.

A nonlinear autoregressive Volterra model of the Hodgkin-Huxley equations.

PubMed

Eikenberry, Steffen E; Marmarelis, Vasilis Z

2013-02-01

We propose a new variant of Volterra-type model with a nonlinear auto-regressive (NAR) component that is a suitable framework for describing the process of AP generation by the neuron membrane potential, and we apply it to input-output data generated by the Hodgkin-Huxley (H-H) equations. Volterra models use a functional series expansion to describe the input-output relation for most nonlinear dynamic systems, and are applicable to a wide range of physiologic systems. It is difficult, however, to apply the Volterra methodology to the H-H model because is characterized by distinct subthreshold and suprathreshold dynamics. When threshold is crossed, an autonomous action potential (AP) is generated, the output becomes temporarily decoupled from the input, and the standard Volterra model fails. Therefore, in our framework, whenever membrane potential exceeds some threshold, it is taken as a second input to a dual-input Volterra model. This model correctly predicts membrane voltage deflection both within the subthreshold region and during APs. Moreover, the model naturally generates a post-AP afterpotential and refractory period. It is known that the H-H model converges to a limit cycle in response to a constant current injection. This behavior is correctly predicted by the proposed model, while the standard Volterra model is incapable of generating such limit cycle behavior. The inclusion of cross-kernels, which describe the nonlinear interactions between the exogenous and autoregressive inputs, is found to be absolutely necessary. The proposed model is general, non-parametric, and data-derived.

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.

Circuit Motifs for Contrast-Adaptive Differentiation in Early Sensory Systems: The Role of Presynaptic Inhibition and Short-Term Plasticity

PubMed Central

Zhang, Danke; Wu, Si; Rasch, Malte J.

2015-01-01

In natural signals, such as the luminance value across of a visual scene, abrupt changes in intensity value are often more relevant to an organism than intensity values at other positions and times. Thus to reduce redundancy, sensory systems are specialized to detect the times and amplitudes of informative abrupt changes in the input stream rather than coding the intensity values at all times. In theory, a system that responds transiently to fast changes is called a differentiator. In principle, several different neural circuit mechanisms exist that are capable of responding transiently to abrupt input changes. However, it is unclear which circuit would be best suited for early sensory systems, where the dynamic range of the natural input signals can be very wide. We here compare the properties of different simple neural circuit motifs for implementing signal differentiation. We found that a circuit motif based on presynaptic inhibition (PI) is unique in a sense that the vesicle resources in the presynaptic site can be stably maintained over a wide range of stimulus intensities, making PI a biophysically plausible mechanism to implement a differentiator with a very wide dynamical range. Moreover, by additionally considering short-term plasticity (STP), differentiation becomes contrast adaptive in the PI-circuit but not in other potential neural circuit motifs. Numerical simulations show that the behavior of the adaptive PI-circuit is consistent with experimental observations suggesting that adaptive presynaptic inhibition might be a good candidate neural mechanism to achieve differentiation in early sensory systems. PMID:25723493

Circuit motifs for contrast-adaptive differentiation in early sensory systems: the role of presynaptic inhibition and short-term plasticity.

PubMed

Zhang, Danke; Wu, Si; Rasch, Malte J

2015-01-01

In natural signals, such as the luminance value across of a visual scene, abrupt changes in intensity value are often more relevant to an organism than intensity values at other positions and times. Thus to reduce redundancy, sensory systems are specialized to detect the times and amplitudes of informative abrupt changes in the input stream rather than coding the intensity values at all times. In theory, a system that responds transiently to fast changes is called a differentiator. In principle, several different neural circuit mechanisms exist that are capable of responding transiently to abrupt input changes. However, it is unclear which circuit would be best suited for early sensory systems, where the dynamic range of the natural input signals can be very wide. We here compare the properties of different simple neural circuit motifs for implementing signal differentiation. We found that a circuit motif based on presynaptic inhibition (PI) is unique in a sense that the vesicle resources in the presynaptic site can be stably maintained over a wide range of stimulus intensities, making PI a biophysically plausible mechanism to implement a differentiator with a very wide dynamical range. Moreover, by additionally considering short-term plasticity (STP), differentiation becomes contrast adaptive in the PI-circuit but not in other potential neural circuit motifs. Numerical simulations show that the behavior of the adaptive PI-circuit is consistent with experimental observations suggesting that adaptive presynaptic inhibition might be a good candidate neural mechanism to achieve differentiation in early sensory systems.

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

Dragone, A; /SLAC; Pratte, J.F.

An ASIC for the readout of signals from X-ray Active Matrix Pixel Sensor (XAMPS) detectors to be used at the Linac Coherent Light Source (LCLS) is presented. The X-ray Pump Probe (XPP) instrument, for which the ASIC has been designed, requires a large input dynamic range on the order of 104 photons at 8 keV with a resolution of half a photon FWHM. Due to the size of the pixel and the length of the readout line, large input capacitance is expected, leading to stringent requirement on the noise optimization. Furthermore, the large number of pixels needed for a goodmore » position resolution and the fixed LCLS beam period impose limitations on the time available for the single pixel readout. Considering the periodic nature of the LCLS beam, the ASIC developed for this application is a time-variant system providing low-noise charge integration, filtering and correlated double sampling. In order to cope with the large input dynamic range a charge pump scheme implementing a zero-balance measurement method has been introduced. It provides an on chip 3-bit coarse digital conversion of the integrated charge. The residual charge is sampled using correlated double sampling into analog memory and measured with the required resolution. The first 64 channel prototype of the ASIC has been fabricated in TSMC CMOS 0.25 {micro}m technology. In this paper, the ASIC architecture and performances are presented.« less

Biomass, production and woody detritus in an old coast redwood (Sequoia sempervirens) forest

USGS Publications Warehouse

Busing, R.T.; Fujimori, T.

2005-01-01

We examined aboveground biomass dynamics, aboveground net primary production (ANPP), and woody detritus input in an old Sequoia sempervirens stand over a three-decade period. Our estimates of aboveground biomass ranged from 3300 to 5800 Mg ha-1. Stem biomass estimates ranged from 3000 to 5200 Mg ha-1. Stem biomass declined 7% over the study interval. Biomass dynamics were patchy, with marked declines in recent tree-fall patches <0.05 ha in size. Larger tree-fall patches approaching 0.2 ha in size were observed outside the study plot. Our estimates of ANPP ranged from 6 to 14 Mg ha -1yr-1. Estimates of 7 to 10 Mg ha-1yr -1 were considered to be relatively accurate. Thus, our estimates based on long-term data corroborated the findings of earlier short-term studies. ANPP of old, pure stands of Sequoia was not above average for temperate forests. Even though production was potentially high on a per stem basis, it was moderate at the stand level. We obtained values of 797 m3 ha -1 and 262 Mg ha-1 for coarse woody detritus volume and mass, respectively. Fine woody detritus volume and mass were estimated at 16 m3 ha-1 and 5 Mg ha-1, respectively. Standing dead trees (or snags) comprised 7% of the total coarse detritus volume and 8% of the total mass. Coarse detritus input averaged 5.7 to 6.9 Mg ha -1yr-1. Assuming steady-state input and pool of coarse detritus, we obtained a decay rate constant of 0.022 to 0.026. The old-growth stand of Sequoia studied had extremely high biomass, but ANPP was moderate and the amount of woody detritus was not exceptionally large. Biomass accretion and loss were not rapid in this stand partly because of the slow population dynamics and low canopy turnover rate of Sequoia at the old-growth stage. Nomenclature: Hickman (1993). ?? Springer 2005.

Comparison of the dynamics of neural interactions between current-based and conductance-based integrate-and-fire recurrent networks

PubMed Central

Cavallari, Stefano; Panzeri, Stefano; Mazzoni, Alberto

2014-01-01

Models of networks of Leaky Integrate-and-Fire (LIF) neurons are a widely used tool for theoretical investigations of brain function. These models have been used both with current- and conductance-based synapses. However, the differences in the dynamics expressed by these two approaches have been so far mainly studied at the single neuron level. To investigate how these synaptic models affect network activity, we compared the single neuron and neural population dynamics of conductance-based networks (COBNs) and current-based networks (CUBNs) of LIF neurons. These networks were endowed with sparse excitatory and inhibitory recurrent connections, and were tested in conditions including both low- and high-conductance states. We developed a novel procedure to obtain comparable networks by properly tuning the synaptic parameters not shared by the models. The so defined comparable networks displayed an excellent and robust match of first order statistics (average single neuron firing rates and average frequency spectrum of network activity). However, these comparable networks showed profound differences in the second order statistics of neural population interactions and in the modulation of these properties by external inputs. The correlation between inhibitory and excitatory synaptic currents and the cross-neuron correlation between synaptic inputs, membrane potentials and spike trains were stronger and more stimulus-modulated in the COBN. Because of these properties, the spike train correlation carried more information about the strength of the input in the COBN, although the firing rates were equally informative in both network models. Moreover, the network activity of COBN showed stronger synchronization in the gamma band, and spectral information about the input higher and spread over a broader range of frequencies. These results suggest that the second order statistics of network dynamics depend strongly on the choice of synaptic model. PMID:24634645

Comparison of the dynamics of neural interactions between current-based and conductance-based integrate-and-fire recurrent networks.

PubMed

Cavallari, Stefano; Panzeri, Stefano; Mazzoni, Alberto

2014-01-01

Models of networks of Leaky Integrate-and-Fire (LIF) neurons are a widely used tool for theoretical investigations of brain function. These models have been used both with current- and conductance-based synapses. However, the differences in the dynamics expressed by these two approaches have been so far mainly studied at the single neuron level. To investigate how these synaptic models affect network activity, we compared the single neuron and neural population dynamics of conductance-based networks (COBNs) and current-based networks (CUBNs) of LIF neurons. These networks were endowed with sparse excitatory and inhibitory recurrent connections, and were tested in conditions including both low- and high-conductance states. We developed a novel procedure to obtain comparable networks by properly tuning the synaptic parameters not shared by the models. The so defined comparable networks displayed an excellent and robust match of first order statistics (average single neuron firing rates and average frequency spectrum of network activity). However, these comparable networks showed profound differences in the second order statistics of neural population interactions and in the modulation of these properties by external inputs. The correlation between inhibitory and excitatory synaptic currents and the cross-neuron correlation between synaptic inputs, membrane potentials and spike trains were stronger and more stimulus-modulated in the COBN. Because of these properties, the spike train correlation carried more information about the strength of the input in the COBN, although the firing rates were equally informative in both network models. Moreover, the network activity of COBN showed stronger synchronization in the gamma band, and spectral information about the input higher and spread over a broader range of frequencies. These results suggest that the second order statistics of network dynamics depend strongly on the choice of synaptic model.

Criticality meets learning: Criticality signatures in a self-organizing recurrent neural network

PubMed Central

Del Papa, Bruno; Priesemann, Viola

2017-01-01

Many experiments have suggested that the brain operates close to a critical state, based on signatures of criticality such as power-law distributed neuronal avalanches. In neural network models, criticality is a dynamical state that maximizes information processing capacities, e.g. sensitivity to input, dynamical range and storage capacity, which makes it a favorable candidate state for brain function. Although models that self-organize towards a critical state have been proposed, the relation between criticality signatures and learning is still unclear. Here, we investigate signatures of criticality in a self-organizing recurrent neural network (SORN). Investigating criticality in the SORN is of particular interest because it has not been developed to show criticality. Instead, the SORN has been shown to exhibit spatio-temporal pattern learning through a combination of neural plasticity mechanisms and it reproduces a number of biological findings on neural variability and the statistics and fluctuations of synaptic efficacies. We show that, after a transient, the SORN spontaneously self-organizes into a dynamical state that shows criticality signatures comparable to those found in experiments. The plasticity mechanisms are necessary to attain that dynamical state, but not to maintain it. Furthermore, onset of external input transiently changes the slope of the avalanche distributions – matching recent experimental findings. Interestingly, the membrane noise level necessary for the occurrence of the criticality signatures reduces the model’s performance in simple learning tasks. Overall, our work shows that the biologically inspired plasticity and homeostasis mechanisms responsible for the SORN’s spatio-temporal learning abilities can give rise to criticality signatures in its activity when driven by random input, but these break down under the structured input of short repeating sequences. PMID:28552964

Fuzzy logic-based flight control system design

NASA Astrophysics Data System (ADS)

Nho, Kyungmoon

The application of fuzzy logic to aircraft motion control is studied in this dissertation. The self-tuning fuzzy techniques are developed by changing input scaling factors to obtain a robust fuzzy controller over a wide range of operating conditions and nonlinearities for a nonlinear aircraft model. It is demonstrated that the properly adjusted input scaling factors can meet the required performance and robustness in a fuzzy controller. For a simple demonstration of the easy design and control capability of a fuzzy controller, a proportional-derivative (PD) fuzzy control system is compared to the conventional controller for a simple dynamical system. This thesis also describes the design principles and stability analysis of fuzzy control systems by considering the key features of a fuzzy control system including the fuzzification, rule-base and defuzzification. The wing-rock motion of slender delta wings, a linear aircraft model and the six degree of freedom nonlinear aircraft dynamics are considered to illustrate several self-tuning methods employing change in input scaling factors. Finally, this dissertation is concluded with numerical simulation of glide-slope capture in windshear demonstrating the robustness of the fuzzy logic based flight control system.

Chattering-Free Sliding Mode Control with Unmodeled Dynamics

NASA Technical Reports Server (NTRS)

Krupp, Don; Shtessel, Yuri B.

1999-01-01

Sliding mode control systems are valued for their robust accommodation of uncertainties and their ability to reject disturbances. In this paper, a design methodology is proposed to eliminate the chattering phenomenon affecting sliding mode controlled plants with input unmodeled actuator dynamics of second order or greater. The proposed controller design is based on the relative degrees of the plant and the unmodeled actuator dynamics and the ranges of the uncertainties of the plant and actuator. The controller utilizes the pass filter characteristics of the physical actuating device to provide a smoothing effect on the discontinuous control signal rather than introducing any artificial dynamics into the controller design thus eliminating chattering in the system's output response.

Study of soil aggregate breakdown dynamics under low dispersive ultrasonic energies with sedimentation and X-ray attenuation**

PubMed Central

Schomakers, Jasmin; Zehetner, Franz; Mentler, Axel; Ottner, Franz; Mayer, Herwig

2016-01-01

It has been increasingly recognized that soil organic matter stabilization is strongly controlled by physical binding within soil aggregates. It is therefore essential to measure soil aggregate stability reliably over a wide range of disruptive energies and different aggregate sizes. To this end, we tested high-accuracy ultrasonic dispersion in combination with subsequent sedimentation and X-ray attenuation. Three arable topsoils (notillage) from Central Europe were subjected to ultrasound at four different specific energy levels: 0.5, 6.7, 100 and 500 J cm−3, and the resulting suspensions were analyzed for aggregate size distribution by wet sieving (2 000-63 μm) and sedimentation/X-ray attenuation (63-2 μm). The combination of wet sieving and sedimentation technique allowed for a continuous analysis, at high resolution, of soil aggregate breakdown dynamics after defined energy inputs. Our results show that aggregate size distribution strongly varied with sonication energy input and soil type. The strongest effects were observed in the range of low specific energies (< 10 J cm−3), which previous studies have largely neglected. This shows that low ultrasonic energies are required to capture the full range of aggregate stability and release of soil organic matter upon aggregate breakdown. PMID:27099408

Study of soil aggregate breakdown dynamics under low dispersive ultrasonic energies with sedimentation and X-ray attenuation

NASA Astrophysics Data System (ADS)

Schomakers, Jasmin; Zehetner, Franz; Mentler, Axel; Ottner, Franz; Mayer, Herwig

2015-10-01

It has been increasingly recognized that soil organic matter stabilization is strongly controlled by physical binding within soil aggregates. It is therefore essential to measure soil aggregate stability reliably over a wide range of disruptive energies and different aggregate sizes. To this end, we tested highaccuracy ultrasonic dispersion in combination with subsequent sedimentation and X-ray attenuation. Three arable topsoils (notillage) from Central Europe were subjected to ultrasound at four different specific energy levels: 0.5, 6.7, 100 and 500 J cm-3, and the resulting suspensions were analyzed for aggregate size distribution by wet sieving (2 000-63 μm) and sedimentation/X-ray attenuation (63-2 μm). The combination of wet sieving and sedimentation technique allowed for a continuous analysis, at high resolution, of soil aggregate breakdown dynamics after defined energy inputs. Our results show that aggregate size distribution strongly varied with sonication energy input and soil type. The strongest effects were observed in the range of low specific energies (< 10 J cm-3), which previous studies have largely neglected. This shows that low ultrasonic energies are required to capture the full range of aggregate stability and release of soil organic matter upon aggregate breakdown.

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.

Observer-based perturbation extremum seeking control with input constraints for direct-contact membrane distillation process

NASA Astrophysics Data System (ADS)

Eleiwi, Fadi; Laleg-Kirati, Taous Meriem

2018-06-01

An observer-based perturbation extremum seeking control is proposed for a direct-contact membrane distillation (DCMD) process. The process is described with a dynamic model that is based on a 2D advection-diffusion equation model which has pump flow rates as process inputs. The objective of the controller is to optimise the trade-off between the permeate mass flux and the energy consumption by the pumps inside the process. Cases of single and multiple control inputs are considered through the use of only the feed pump flow rate or both the feed and the permeate pump flow rates. A nonlinear Lyapunov-based observer is designed to provide an estimation for the temperature distribution all over the designated domain of the DCMD process. Moreover, control inputs are constrained with an anti-windup technique to be within feasible and physical ranges. Performance of the proposed structure is analysed, and simulations based on real DCMD process parameters for each control input are provided.

BICMOS power detector for pulsed Rf power amplifiers

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

Bridge, Clayton D.

2016-10-01

A BiCMOS power detector for pulsed radio-frequency power amplifiers is proposed. Given the pulse waveform and a fraction of the power amplifier's input or output signal, the detector utilizes a low-frequency feedback loop to perform a successive approximation of the amplitude of the input signal. Upon completion of the successive approximation, the detector returns 9-bits representing the amplitude of the RF input signal. Using the pulse waveform from the power amplifier, the detector can dynamically adjust the rate of the binary search operation in order to return the updated amplitude information of the RF input signal at least every 1ms.more » The detector can handle pulse waveform frequencies from 50kHz to 10MHz with duty cycles in the range of 5- 50% and peak power levels of -10 to 10dBm. The signal amplitude measurement can be converted to a peak power measurement accurate to within ±0.6dB of the input RF power.« less

Genetic programs constructed from layered logic gates in single cells

PubMed Central

Moon, Tae Seok; Lou, Chunbo; Tamsir, Alvin; Stanton, Brynne C.; Voigt, Christopher A.

2014-01-01

Genetic programs function to integrate environmental sensors, implement signal processing algorithms and control expression dynamics1. These programs consist of integrated genetic circuits that individually implement operations ranging from digital logic to dynamic circuits2–6, and they have been used in various cellular engineering applications, including the implementation of process control in metabolic networks and the coordination of spatial differentiation in artificial tissues. A key limitation is that the circuits are based on biochemical interactions occurring in the confined volume of the cell, so the size of programs has been limited to a few circuits1,7. Here we apply part mining and directed evolution to build a set of transcriptional AND gates in Escherichia coli. Each AND gate integrates two promoter inputs and controls one promoter output. This allows the gates to be layered by having the output promoter of an upstream circuit serve as the input promoter for a downstream circuit. Each gate consists of a transcription factor that requires a second chaperone protein to activate the output promoter. Multiple activator–chaperone pairs are identified from type III secretion pathways in different strains of bacteria. Directed evolution is applied to increase the dynamic range and orthogonality of the circuits. These gates are connected in different permutations to form programs, the largest of which is a 4-input AND gate that consists of 3 circuits that integrate 4 inducible systems, thus requiring 11 regulatory proteins. Measuring the performance of individual gates is sufficient to capture the behaviour of the complete program. Errors in the output due to delays (faults), a common problem for layered circuits, are not observed. This work demonstrates the successful layering of orthogonal logic gates, a design strategy that could enable the construction of large, integrated circuits in single cells. PMID:23041931

Operation and tests of a DDC101 A/D

NASA Astrophysics Data System (ADS)

Nguyen, H.

1994-11-01

For the KTeV PMT laser monitoring system, one needs a high resolution device with a large dynamic range to be used for digitizing PIN photodiodes. The dynamic range should be wider than or comparable to the KTeV digitizer (17-bits). The Burr-Brown DDC101 is a precision, wide dynamic range, charge digitizing A/D converter with 20-bit resolution, packaged in a 28-pin plastic, double-wide DP. Low level current output devices such as photosensors can be directly connected to its input. The digital output can be clocked-out serially from the pins. For typical operations, a relatively wide gate of 1 msec should be used. The full scale charge is 500 pC for unipolar mode. The bipolar mode scale is +/- 250 pC. The advertised integral nonlinearity is 0.003% of FSR. This document describes only the basic DDC101 operations since full detail can be found in the DDC101 manual. Tests results are given in section 3.

Adaptation and inhibition underlie responses to time-varying interaural phase cues in a model of inferior colliculus neurons.

PubMed

Borisyuk, Alla; Semple, Malcolm N; Rinzel, John

2002-10-01

A mathematical model was developed for exploring the sensitivity of low-frequency inferior colliculus (IC) neurons to interaural phase disparity (IPD). The formulation involves a firing-rate-type model that does not include spikes per se. The model IC neuron receives IPD-tuned excitatory and inhibitory inputs (viewed as the output of a collection of cells in the medial superior olive). The model cell possesses cellular properties of firing rate adaptation and postinhibitory rebound (PIR). The descriptions of these mechanisms are biophysically reasonable, but only semi-quantitative. We seek to explain within a minimal model the experimentally observed mismatch between responses to IPD stimuli delivered dynamically and those delivered statically (McAlpine et al. 2000; Spitzer and Semple 1993). The model reproduces many features of the responses to static IPD presentations, binaural beat, and partial range sweep stimuli. These features include differences in responses to a stimulus presented in static or dynamic context: sharper tuning and phase shifts in response to binaural beats, and hysteresis and "rise-from-nowhere" in response to partial range sweeps. Our results suggest that dynamic response features are due to the structure of inputs and the presence of firing rate adaptation and PIR mechanism in IC cells, but do not depend on a specific biophysical mechanism. We demonstrate how the model's various components contribute to shaping the observed phenomena. For example, adaptation, PIR, and transmission delay shape phase advances and delays in responses to binaural beats, adaptation and PIR shape hysteresis in different ranges of IPD, and tuned inhibition underlies asymmetry in dynamic tuning properties. We also suggest experiments to test our modeling predictions: in vitro simulation of the binaural beat (phase advance at low beat frequencies, its dependence on firing rate), in vivo partial range sweep experiments (dependence of the hysteresis curve on parameters), and inhibition blocking experiments (to study inhibitory tuning properties by observation of phase shifts).

A comparison of digital zero-crossing and charge-comparison methods for neutron/γ-ray discrimination with liquid scintillation detectors

NASA Astrophysics Data System (ADS)

Nakhostin, M.

2015-10-01

In this paper, we have compared the performances of the digital zero-crossing and charge-comparison methods for n/γ discrimination with liquid scintillation detectors at low light outputs. The measurements were performed with a 2″×2″ cylindrical liquid scintillation detector of type BC501A whose outputs were sampled by means of a fast waveform digitizer with 10-bit resolution, 4 GS/s sampling rate and one volt input range. Different light output ranges were measured by operating the photomultiplier tube at different voltages and a new recursive algorithm was developed to implement the digital zero-crossing method. The results of our study demonstrate the superior performance of the digital zero-crossing method at low light outputs when a large dynamic range is measured. However, when the input range of the digitizer is used to measure a narrow range of light outputs, the charge-comparison method slightly outperforms the zero-crossing method. The results are discussed in regard to the effects of the quantization noise and the noise filtration performance of the zero-crossing filter.

Discrete filtering techniques applied to sequential GPS range measurements

NASA Technical Reports Server (NTRS)

Vangraas, Frank

1987-01-01

The basic navigation solution is described for position and velocity based on range and delta range (Doppler) measurements from NAVSTAR Global Positioning System satellites. The application of discrete filtering techniques is examined to reduce the white noise distortions on the sequential range measurements. A second order (position and velocity states) Kalman filter is implemented to obtain smoothed estimates of range by filtering the dynamics of the signal from each satellite separately. Test results using a simulated GPS receiver show a steady-state noise reduction, the input noise variance divided by the output noise variance, of a factor of four. Recommendations for further noise reduction based on higher order Kalman filters or additional delta range measurements are included.

Control Board Digital Interface Input Devices – Touchscreen, Trackpad, or Mouse?

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

Thomas A. Ulrich; Ronald L. Boring; Roger Lew

The authors collaborated with a power utility to evaluate input devices for use in the human system interface (HSI) for a new digital Turbine Control System (TCS) at a nuclear power plant (NPP) undergoing a TCS upgrade. A standalone dynamic software simulation of the new digital TCS and a mobile kiosk were developed to conduct an input device study to evaluate operator preference and input device effectiveness. The TCS software presented the anticipated HSI for the TCS and mimicked (i.e., simulated) the turbine systems’ responses to operator commands. Twenty-four licensed operators from the two nuclear power units participated in themore » study. Three input devices were tested: a trackpad, mouse, and touchscreen. The subjective feedback from the survey indicates the operators preferred the touchscreen interface. The operators subjectively rated the touchscreen as the fastest and most comfortable input device given the range of tasks they performed during the study, but also noted a lack of accuracy for selecting small targets. The empirical data suggest the mouse input device provides the most consistent performance for screen navigation and manipulating on screen controls. The trackpad input device was both empirically and subjectively found to be the least effective and least desired input device.« less

Analog-to-digital conversion to accommodate the dynamics of live music in hearing instruments.

PubMed

Hockley, Neil S; Bahlmann, Frauke; Fulton, Bernadette

2012-09-01

Hearing instrument design focuses on the amplification of speech to reduce the negative effects of hearing loss. Many amateur and professional musicians, along with music enthusiasts, also require their hearing instruments to perform well when listening to the frequent, high amplitude peaks of live music. One limitation, in most current digital hearing instruments with 16-bit analog-to-digital (A/D) converters, is that the compressor before the A/D conversion is limited to 95 dB (SPL) or less at the input. This is more than adequate for the dynamic range of speech; however, this does not accommodate the amplitude peaks present in live music. The hearing instrument input compression system can be adjusted to accommodate for the amplitudes present in music that would otherwise be compressed before the A/D converter in the hearing instrument. The methodology behind this technological approach will be presented along with measurements to demonstrate its effectiveness.

Jdpd: an open java simulation kernel for molecular fragment dissipative particle dynamics.

PubMed

van den Broek, Karina; Kuhn, Hubert; Zielesny, Achim

2018-05-21

Jdpd is an open Java simulation kernel for Molecular Fragment Dissipative Particle Dynamics with parallelizable force calculation, efficient caching options and fast property calculations. It is characterized by an interface and factory-pattern driven design for simple code changes and may help to avoid problems of polyglot programming. Detailed input/output communication, parallelization and process control as well as internal logging capabilities for debugging purposes are supported. The new kernel may be utilized in different simulation environments ranging from flexible scripting solutions up to fully integrated "all-in-one" simulation systems.

Review of Engine/Airframe/Drive Train Dynamic Interface Development Problems

DTIC Science & Technology

1978-06-01

dynamic interface problems associated with the Cd-54, S-61, CH-53, SH-3, S-58, SH-34, S-64, BLACK HAOK, and the ABC . The ultimate benefit will be the...drive systems of the CH-3C, CH-53A, and CH-54A helicopters. Prior to the shaft failure incident, the input drive shaft sytems had accumulated in...capability of the ABC aircraft. This aircraft has a large range in forward speed, zero to 280 knots. At high aircraft speeds, the rotor speed must be reduced

The Realization and Analysis of Capacitance Self Tracing (CST) Method for Wide Band Response Measurement of Carrier Type Dynamic Strain Amplifier

NASA Astrophysics Data System (ADS)

Kubodera, Shinji; Tanzawa, Tsutomu; Morisawa, Masayuki; Kiyohiro, Noriaki

Carrier type dynamic strain amplifiers are frequently used for stress measurement with strain gages. That is because the carrier type dynamic strain amplifier can conduct high precision measurement since it is highly resistant against hum noise from the power supply frequency in principle and is free from the thermoelectomotive force even if a metal contact is used in wiring to a Wheatstone bridge for measuring. A problem of the carrier type dynamic strain amplifier is generation of Capacitive component (hereinafter referred to as the C component) in an input cable connecting from the amplifier to the input sensor (Wheatstone bridge for measuring). The C component varies with cable length, cable materials, or ambient temperature change. The aforementioned changing adversely affects the stability of the amplifier. In this paper, we realize and analyze the method that increases the stability of amplifier by detecting, eliminating and self tracking the above C component constantly. Used carrier frequency at 12kHz and 28kHz. We made amplifiers with noise resistant and wide band frequency of measurement range and verified the theory of the Capacitance Self Tracing with the above amplifiers.

Dynamics of nonlinear feedback control.

PubMed

Snippe, H P; van Hateren, J H

2007-05-01

Feedback control in neural systems is ubiquitous. Here we study the mathematics of nonlinear feedback control. We compare models in which the input is multiplied by a dynamic gain (multiplicative control) with models in which the input is divided by a dynamic attenuation (divisive control). The gain signal (resp. the attenuation signal) is obtained through a concatenation of an instantaneous nonlinearity and a linear low-pass filter operating on the output of the feedback loop. For input steps, the dynamics of gain and attenuation can be very different, depending on the mathematical form of the nonlinearity and the ordering of the nonlinearity and the filtering in the feedback loop. Further, the dynamics of feedback control can be strongly asymmetrical for increment versus decrement steps of the input. Nevertheless, for each of the models studied, the nonlinearity in the feedback loop can be chosen such that immediately after an input step, the dynamics of feedback control is symmetric with respect to increments versus decrements. Finally, we study the dynamics of the output of the control loops and find conditions under which overshoots and undershoots of the output relative to the steady-state output occur when the models are stimulated with low-pass filtered steps. For small steps at the input, overshoots and undershoots of the output do not occur when the filtering in the control path is faster than the low-pass filtering at the input. For large steps at the input, however, results depend on the model, and for some of the models, multiple overshoots and undershoots can occur even with a fast control path.

Dynamics of Action Potential Initiation in the GABAergic Thalamic Reticular Nucleus In Vivo

PubMed Central

Muñoz, Fabián; Fuentealba, Pablo

2012-01-01

Understanding the neural mechanisms of action potential generation is critical to establish the way neural circuits generate and coordinate activity. Accordingly, we investigated the dynamics of action potential initiation in the GABAergic thalamic reticular nucleus (TRN) using in vivo intracellular recordings in cats in order to preserve anatomically-intact axo-dendritic distributions and naturally-occurring spatiotemporal patterns of synaptic activity in this structure that regulates the thalamic relay to neocortex. We found a wide operational range of voltage thresholds for action potentials, mostly due to intrinsic voltage-gated conductances and not synaptic activity driven by network oscillations. Varying levels of synchronous synaptic inputs produced fast rates of membrane potential depolarization preceding the action potential onset that were associated with lower thresholds and increased excitability, consistent with TRN neurons performing as coincidence detectors. On the other hand the presence of action potentials preceding any given spike was associated with more depolarized thresholds. The phase-plane trajectory of the action potential showed somato-dendritic propagation, but no obvious axon initial segment component, prominent in other neuronal classes and allegedly responsible for the high onset speed. Overall, our results suggest that TRN neurons could flexibly integrate synaptic inputs to discharge action potentials over wide voltage ranges, and perform as coincidence detectors and temporal integrators, supported by a dynamic action potential threshold. PMID:22279567

Effects of stick dynamics on helicopter flying qualities

NASA Technical Reports Server (NTRS)

Watson, Douglas C.; Schroeder, Jeffery A.

1990-01-01

An experiment that investigated the influence of typical helicopter force-feel system dynamics on roll-axis handling qualities was conducted in concurrent ground and inflight simulations. Variations in lateral control natural frequency and damping ratio, effected by changes in inertia and damping, were evaluated in a disturbance-rejection task. Pilot ratings indicated a preference for low-inertia feel systems, although measured performance was relatively constant over the range of stick characteristics. Force-sensing was compared with position sensing as the input to the control system. Force-sensing improved performance but did not improve pilot ratings. Overall, the results indicated that control-stick dynamics, at least within a reasonable range, did not have a significant effect on pilot-vehicle performance. However, the physical effort required to maintain a desired pilot/manipulator bandwidth became objectionable as the stick inertia increased beyond 5-7 lbm, which was reflected in the pilot ratings and comments.

Design of an ultra low power third order continuous time current mode ΣΔ modulator for WLAN applications.

PubMed

Behzadi, Kobra; Baghelani, Masoud

2014-05-01

This paper presents a third order continuous time current mode ΣΔ modulator for WLAN 802.11b standard applications. The proposed circuit utilized feedback architecture with scaled and optimized DAC coefficients. At circuit level, we propose a modified cascade current mirror integrator with reduced input impedance which results in more bandwidth and linearity and hence improves the dynamic range. Also, a very fast and precise novel dynamic latch based current comparator is introduced with low power consumption. This ultra fast comparator facilitates increasing the sampling rate toward GHz frequencies. The modulator exhibits dynamic range of more than 60 dB for 20 MHz signal bandwidth and OSR of 10 while consuming only 914 μW from 1.8 V power supply. The FoM of the modulator is calculated from two different methods, and excellent performance is achieved for proposed modulator.

Design of an ultra low power third order continuous time current mode ΣΔ modulator for WLAN applications

PubMed Central

Behzadi, Kobra; Baghelani, Masoud

2013-01-01

This paper presents a third order continuous time current mode ΣΔ modulator for WLAN 802.11b standard applications. The proposed circuit utilized feedback architecture with scaled and optimized DAC coefficients. At circuit level, we propose a modified cascade current mirror integrator with reduced input impedance which results in more bandwidth and linearity and hence improves the dynamic range. Also, a very fast and precise novel dynamic latch based current comparator is introduced with low power consumption. This ultra fast comparator facilitates increasing the sampling rate toward GHz frequencies. The modulator exhibits dynamic range of more than 60 dB for 20 MHz signal bandwidth and OSR of 10 while consuming only 914 μW from 1.8 V power supply. The FoM of the modulator is calculated from two different methods, and excellent performance is achieved for proposed modulator. PMID:25685504

Can Computer-Based Visual-Spatial Aids Lead to Increased Student Performance in Anatomy & Physiology?

ERIC Educational Resources Information Center

Kesner, Michael H.; Linzey, Alicia V.

2005-01-01

InterActive Physiology (IAP) is one of a new generation of anatomy and physiology learning aids with a broader range of sensory inputs than is possible from a static textbook or moderately dynamic lecture. This best-selling software has modules covering the muscular, respiratory, urinary, cardiovascular, and nervous systems plus a module on fluids…

Modeling the spatially dynamic distribution of humans in the Oregon (USA) coast range.

Treesearch

Jeffrey D. Kline; David L. Azuma; Alissa Moses

2003-01-01

A common approach to land use change analyses in multidisciplinary landscape-level studies is to delineate discrete forest and non-forest or urban and non-urban land use categories to serve as inputs into sets of integrated sub-models describing socioeconomic and ecological processes. Such discrete land use categories, however, may be inappropriate when the...

Utilization of extracellular information before ligand-receptor binding reaches equilibrium expands and shifts the input dynamic range

PubMed Central

Ventura, Alejandra C.; Bush, Alan; Vasen, Gustavo; Goldín, Matías A.; Burkinshaw, Brianne; Bhattacharjee, Nirveek; Folch, Albert; Brent, Roger; Chernomoretz, Ariel; Colman-Lerner, Alejandro

2014-01-01

Cell signaling systems sense and respond to ligands that bind cell surface receptors. These systems often respond to changes in the concentration of extracellular ligand more rapidly than the ligand equilibrates with its receptor. We demonstrate, by modeling and experiment, a general “systems level” mechanism cells use to take advantage of the information present in the early signal, before receptor binding reaches a new steady state. This mechanism, pre-equilibrium sensing and signaling (PRESS), operates in signaling systems in which the kinetics of ligand-receptor binding are slower than the downstream signaling steps, and it typically involves transient activation of a downstream step. In the systems where it operates, PRESS expands and shifts the input dynamic range, allowing cells to make different responses to ligand concentrations so high as to be otherwise indistinguishable. Specifically, we show that PRESS applies to the yeast directional polarization in response to pheromone gradients. Consideration of preexisting kinetic data for ligand-receptor interactions suggests that PRESS operates in many cell signaling systems throughout biology. The same mechanism may also operate at other levels in signaling systems in which a slow activation step couples to a faster downstream step. PMID:25172920

Benefits of Spacecraft Level Vibration Testing

NASA Technical Reports Server (NTRS)

Gordon, Scott; Kern, Dennis L.

2015-01-01

NASA-HDBK-7008 Spacecraft Level Dynamic Environments Testing discusses the approaches, benefits, dangers, and recommended practices for spacecraft level dynamic environments testing, including vibration testing. This paper discusses in additional detail the benefits and actual experiences of vibration testing spacecraft for NASA Goddard Space Flight Center (GSFC) and Jet Propulsion Laboratory (JPL) flight projects. JPL and GSFC have both similarities and differences in their spacecraft level vibration test approach: JPL uses a random vibration input and a frequency range usually starting at 5 Hz and extending to as high as 250 Hz. GSFC uses a sine sweep vibration input and a frequency range usually starting at 5 Hz and extending only to the limits of the coupled loads analysis (typically 50 to 60 Hz). However, both JPL and GSFC use force limiting to realistically notch spacecraft resonances and response (acceleration) limiting as necessary to protect spacecraft structure and hardware from exceeding design strength capabilities. Despite GSFC and JPL differences in spacecraft level vibration test approaches, both have uncovered a significant number of spacecraft design and workmanship anomalies in vibration tests. This paper will give an overview of JPL and GSFC spacecraft vibration testing approaches and provide a detailed description of spacecraft anomalies revealed.

Wind noise in hearing aids: I. Effect of wide dynamic range compression and modulation-based noise reduction.

PubMed

Chung, King

2012-01-01

The objectives of this study were: (1) to examine the effect of wide dynamic range compression (WDRC) and modulation-based noise reduction (NR) algorithms on wind noise levels at the hearing aid output; and (2) to derive effective strategies for clinicians and engineers to reduce wind noise in hearing aids. Three digital hearing aids were fitted to KEMAR. The noise output was recorded at flow velocities of 0, 4.5, 9.0, and 13.5 m/s in a wind tunnel as the KEMAR head was turned from 0° to 360°. Flow noise levels were compared between the 1:1 linear and 3:1 WDRC conditions, and between NR-activated and NR-deactivated conditions when the hearing aid was programmed to the directional and omnidirectional modes. The results showed that: (1) WDRC increased low-level noise and reduced high-level noise; and (2) different noise reduction algorithms provided different amounts of wind noise reduction in different microphone modes, frequency regions, flow velocities, and head angles. Wind noise can be reduced by decreasing the gain for low-level inputs, increasing the compression ratio for high-level inputs, and activating modulation-based noise reduction algorithms.

A digital prediction algorithm for a single-phase boost PFC

NASA Astrophysics Data System (ADS)

Qing, Wang; Ning, Chen; Weifeng, Sun; Shengli, Lu; Longxing, Shi

2012-12-01

A novel digital control algorithm for digital control power factor correction is presented, which is called the prediction algorithm and has a feature of a higher PF (power factor) with lower total harmonic distortion, and a faster dynamic response with the change of the input voltage or load current. For a certain system, based on the current system state parameters, the prediction algorithm can estimate the track of the output voltage and the inductor current at the next switching cycle and get a set of optimized control sequences to perfectly track the trajectory of input voltage. The proposed prediction algorithm is verified at different conditions, and computer simulation and experimental results under multi-situations confirm the effectiveness of the prediction algorithm. Under the circumstances that the input voltage is in the range of 90-265 V and the load current in the range of 20%-100%, the PF value is larger than 0.998. The startup and the recovery times respectively are about 0.1 s and 0.02 s without overshoot. The experimental results also verify the validity of the proposed method.

Energy dispersive CdTe and CdZnTe detectors for spectral clinical CT and NDT applications

NASA Astrophysics Data System (ADS)

Barber, W. C.; Wessel, J. C.; Nygard, E.; Iwanczyk, J. S.

2015-06-01

We are developing room temperature compound semiconductor detectors for applications in energy-resolved high-flux single x-ray photon-counting spectral computed tomography (CT), including functional imaging with nanoparticle contrast agents for medical applications and non-destructive testing (NDT) for security applications. Energy-resolved photon-counting can provide reduced patient dose through optimal energy weighting for a particular imaging task in CT, functional contrast enhancement through spectroscopic imaging of metal nanoparticles in CT, and compositional analysis through multiple basis function material decomposition in CT and NDT. These applications produce high input count rates from an x-ray generator delivered to the detector. Therefore, in order to achieve energy-resolved single photon counting in these applications, a high output count rate (OCR) for an energy-dispersive detector must be achieved at the required spatial resolution and across the required dynamic range for the application. The required performance in terms of the OCR, spatial resolution, and dynamic range must be obtained with sufficient field of view (FOV) for the application thus requiring the tiling of pixel arrays and scanning techniques. Room temperature cadmium telluride (CdTe) and cadmium zinc telluride (CdZnTe) compound semiconductors, operating as direct conversion x-ray sensors, can provide the required speed when connected to application specific integrated circuits (ASICs) operating at fast peaking times with multiple fixed thresholds per pixel provided the sensors are designed for rapid signal formation across the x-ray energy ranges of the application at the required energy and spatial resolutions, and at a sufficiently high detective quantum efficiency (DQE). We have developed high-flux energy-resolved photon-counting x-ray imaging array sensors using pixellated CdTe and CdZnTe semiconductors optimized for clinical CT and security NDT. We have also fabricated high-flux ASICs with a two dimensional (2D) array of inputs for readout from the sensors. The sensors are guard ring free and have a 2D array of pixels and can be tiled in 2D while preserving pixel pitch. The 2D ASICs have four energy bins with a linear energy response across sufficient dynamic range for clinical CT and some NDT applications. The ASICs can also be tiled in 2D and are designed to fit within the active area of the sensors. We have measured several important performance parameters including: the output count rate (OCR) in excess of 20 million counts per second per square mm with a minimum loss of counts due to pulse pile-up, an energy resolution of 7 keV full width at half-maximum (FWHM) across the entire dynamic range, and a noise floor about 20 keV. This is achieved by directly interconnecting the ASIC inputs to the pixels of the CdZnTe sensors incurring very little input capacitance to the ASICs. We present measurements of the performance of the CdTe and CdZnTe sensors including the OCR, FWHM energy resolution, noise floor, as well as the temporal stability and uniformity under the rapidly varying high flux expected in CT and NDT applications.

Energy dispersive CdTe and CdZnTe detectors for spectral clinical CT and NDT applications

PubMed Central

Barber, W. C.; Wessel, J. C.; Nygard, E.; Iwanczyk, J. S.

2014-01-01

We are developing room temperature compound semiconductor detectors for applications in energy-resolved high-flux single x-ray photon-counting spectral computed tomography (CT), including functional imaging with nanoparticle contrast agents for medical applications and non destructive testing (NDT) for security applications. Energy-resolved photon-counting can provide reduced patient dose through optimal energy weighting for a particular imaging task in CT, functional contrast enhancement through spectroscopic imaging of metal nanoparticles in CT, and compositional analysis through multiple basis function material decomposition in CT and NDT. These applications produce high input count rates from an x-ray generator delivered to the detector. Therefore, in order to achieve energy-resolved single photon counting in these applications, a high output count rate (OCR) for an energy-dispersive detector must be achieved at the required spatial resolution and across the required dynamic range for the application. The required performance in terms of the OCR, spatial resolution, and dynamic range must be obtained with sufficient field of view (FOV) for the application thus requiring the tiling of pixel arrays and scanning techniques. Room temperature cadmium telluride (CdTe) and cadmium zinc telluride (CdZnTe) compound semiconductors, operating as direct conversion x-ray sensors, can provide the required speed when connected to application specific integrated circuits (ASICs) operating at fast peaking times with multiple fixed thresholds per pixel provided the sensors are designed for rapid signal formation across the x-ray energy ranges of the application at the required energy and spatial resolutions, and at a sufficiently high detective quantum efficiency (DQE). We have developed high-flux energy-resolved photon-counting x-ray imaging array sensors using pixellated CdTe and CdZnTe semiconductors optimized for clinical CT and security NDT. We have also fabricated high-flux ASICs with a two dimensional (2D) array of inputs for readout from the sensors. The sensors are guard ring free and have a 2D array of pixels and can be tiled in 2D while preserving pixel pitch. The 2D ASICs have four energy bins with a linear energy response across sufficient dynamic range for clinical CT and some NDT applications. The ASICs can also be tiled in 2D and are designed to fit within the active area of the sensors. We have measured several important performance parameters including; the output count rate (OCR) in excess of 20 million counts per second per square mm with a minimum loss of counts due to pulse pile-up, an energy resolution of 7 keV full width at half maximum (FWHM) across the entire dynamic range, and a noise floor about 20keV. This is achieved by directly interconnecting the ASIC inputs to the pixels of the CdZnTe sensors incurring very little input capacitance to the ASICs. We present measurements of the performance of the CdTe and CdZnTe sensors including the OCR, FWHM energy resolution, noise floor, as well as the temporal stability and uniformity under the rapidly varying high flux expected in CT and NDT applications. PMID:25937684

Energy dispersive CdTe and CdZnTe detectors for spectral clinical CT and NDT applications.

PubMed

Barber, W C; Wessel, J C; Nygard, E; Iwanczyk, J S

2015-06-01

We are developing room temperature compound semiconductor detectors for applications in energy-resolved high-flux single x-ray photon-counting spectral computed tomography (CT), including functional imaging with nanoparticle contrast agents for medical applications and non destructive testing (NDT) for security applications. Energy-resolved photon-counting can provide reduced patient dose through optimal energy weighting for a particular imaging task in CT, functional contrast enhancement through spectroscopic imaging of metal nanoparticles in CT, and compositional analysis through multiple basis function material decomposition in CT and NDT. These applications produce high input count rates from an x-ray generator delivered to the detector. Therefore, in order to achieve energy-resolved single photon counting in these applications, a high output count rate (OCR) for an energy-dispersive detector must be achieved at the required spatial resolution and across the required dynamic range for the application. The required performance in terms of the OCR, spatial resolution, and dynamic range must be obtained with sufficient field of view (FOV) for the application thus requiring the tiling of pixel arrays and scanning techniques. Room temperature cadmium telluride (CdTe) and cadmium zinc telluride (CdZnTe) compound semiconductors, operating as direct conversion x-ray sensors, can provide the required speed when connected to application specific integrated circuits (ASICs) operating at fast peaking times with multiple fixed thresholds per pixel provided the sensors are designed for rapid signal formation across the x-ray energy ranges of the application at the required energy and spatial resolutions, and at a sufficiently high detective quantum efficiency (DQE). We have developed high-flux energy-resolved photon-counting x-ray imaging array sensors using pixellated CdTe and CdZnTe semiconductors optimized for clinical CT and security NDT. We have also fabricated high-flux ASICs with a two dimensional (2D) array of inputs for readout from the sensors. The sensors are guard ring free and have a 2D array of pixels and can be tiled in 2D while preserving pixel pitch. The 2D ASICs have four energy bins with a linear energy response across sufficient dynamic range for clinical CT and some NDT applications. The ASICs can also be tiled in 2D and are designed to fit within the active area of the sensors. We have measured several important performance parameters including; the output count rate (OCR) in excess of 20 million counts per second per square mm with a minimum loss of counts due to pulse pile-up, an energy resolution of 7 keV full width at half maximum (FWHM) across the entire dynamic range, and a noise floor about 20keV. This is achieved by directly interconnecting the ASIC inputs to the pixels of the CdZnTe sensors incurring very little input capacitance to the ASICs. We present measurements of the performance of the CdTe and CdZnTe sensors including the OCR, FWHM energy resolution, noise floor, as well as the temporal stability and uniformity under the rapidly varying high flux expected in CT and NDT applications.

An open tool for input function estimation and quantification of dynamic PET FDG brain scans.

PubMed

Bertrán, Martín; Martínez, Natalia; Carbajal, Guillermo; Fernández, Alicia; Gómez, Álvaro

2016-08-01

Positron emission tomography (PET) analysis of clinical studies is mostly restricted to qualitative evaluation. Quantitative analysis of PET studies is highly desirable to be able to compute an objective measurement of the process of interest in order to evaluate treatment response and/or compare patient data. But implementation of quantitative analysis generally requires the determination of the input function: the arterial blood or plasma activity which indicates how much tracer is available for uptake in the brain. The purpose of our work was to share with the community an open software tool that can assist in the estimation of this input function, and the derivation of a quantitative map from the dynamic PET study. Arterial blood sampling during the PET study is the gold standard method to get the input function, but is uncomfortable and risky for the patient so it is rarely used in routine studies. To overcome the lack of a direct input function, different alternatives have been devised and are available in the literature. These alternatives derive the input function from the PET image itself (image-derived input function) or from data gathered from previous similar studies (population-based input function). In this article, we present ongoing work that includes the development of a software tool that integrates several methods with novel strategies for the segmentation of blood pools and parameter estimation. The tool is available as an extension to the 3D Slicer software. Tests on phantoms were conducted in order to validate the implemented methods. We evaluated the segmentation algorithms over a range of acquisition conditions and vasculature size. Input function estimation algorithms were evaluated against ground truth of the phantoms, as well as on their impact over the final quantification map. End-to-end use of the tool yields quantification maps with [Formula: see text] relative error in the estimated influx versus ground truth on phantoms. The main contribution of this article is the development of an open-source, free to use tool that encapsulates several well-known methods for the estimation of the input function and the quantification of dynamic PET FDG studies. Some alternative strategies are also proposed and implemented in the tool for the segmentation of blood pools and parameter estimation. The tool was tested on phantoms with encouraging results that suggest that even bloodless estimators could provide a viable alternative to blood sampling for quantification using graphical analysis. The open tool is a promising opportunity for collaboration among investigators and further validation on real studies.

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).

Recurrent network dynamics reconciles visual motion segmentation and integration.

PubMed

Medathati, N V Kartheek; Rankin, James; Meso, Andrew I; Kornprobst, Pierre; Masson, Guillaume S

2017-09-12

In sensory systems, a range of computational rules are presumed to be implemented by neuronal subpopulations with different tuning functions. For instance, in primate cortical area MT, different classes of direction-selective cells have been identified and related either to motion integration, segmentation or transparency. Still, how such different tuning properties are constructed is unclear. The dominant theoretical viewpoint based on a linear-nonlinear feed-forward cascade does not account for their complex temporal dynamics and their versatility when facing different input statistics. Here, we demonstrate that a recurrent network model of visual motion processing can reconcile these different properties. Using a ring network, we show how excitatory and inhibitory interactions can implement different computational rules such as vector averaging, winner-take-all or superposition. The model also captures ordered temporal transitions between these behaviors. In particular, depending on the inhibition regime the network can switch from motion integration to segmentation, thus being able to compute either a single pattern motion or to superpose multiple inputs as in motion transparency. We thus demonstrate that recurrent architectures can adaptively give rise to different cortical computational regimes depending upon the input statistics, from sensory flow integration to segmentation.

Dynamic Fuzzy Model Development for a Drum-type Boiler-turbine Plant Through GK Clustering

NASA Astrophysics Data System (ADS)

Habbi, Ahcène; Zelmat, Mimoun

2008-10-01

This paper discusses a TS fuzzy model identification method for an industrial drum-type boiler plant using the GK fuzzy clustering approach. The fuzzy model is constructed from a set of input-output data that covers a wide operating range of the physical plant. The reference data is generated using a complex first-principle-based mathematical model that describes the key dynamical properties of the boiler-turbine dynamics. The proposed fuzzy model is derived by means of fuzzy clustering method with particular attention on structure flexibility and model interpretability issues. This may provide a basement of a new way to design model based control and diagnosis mechanisms for the complex nonlinear plant.

A Wide Dynamic Range Tapped Linear Array Image Sensor

NASA Astrophysics Data System (ADS)

Washkurak, William D.; Chamberlain, Savvas G.; Prince, N. Daryl

1988-08-01

Detectors for acousto-optic signal processing applications require fast transient response as well as wide dynamic range. There are two major choices of detectors: conductive or integration mode. Conductive mode detectors have an initial transient period before they reach then' i equilibrium state. The duration of 1 his period is dependent on light level as well as detector capacitance. At low light levels a conductive mode detector is very slow; response time is typically on the order of milliseconds. Generally. to obtain fast transient response an integrating mode detector is preferred. With integrating mode detectors. the dynamic range is determined by the charge storage capability of the tran-sport shift registers and the noise level of the image sensor. The conventional net hod used to improve dynamic range is to increase the shift register charge storage capability. To achieve a dynamic range of fifty thousand assuming two hundred noise equivalent electrons, a charge storage capability of ten million electrons would be required. In order to accommodate this amount of charge. unrealistic shift registers widths would be required. Therefore, with an integrating mode detector it is difficult to achieve a dynamic range of over four orders of magnitude of input light intensity. Another alternative is to solve the problem at the photodetector aml not the shift, register. DALSA's wide dynamic range detector utilizes an optimized, ion implant doped, profiled MOSFET photodetector specifically designed for wide dynamic range. When this new detector operates at high speed and at low light levels the photons are collected and stored in an integrating fashion. However. at bright light levels where transient periods are short, the detector switches into a conductive mode. The light intensity is logarithmically compressed into small charge packets, easily carried by the CCD shift register. As a result of the logarithmic conversion, dynamic ranges of over six orders of magnitide are obtained. To achieve the short integration times necessary in acousto-optic applications. t he wide dynamic range detector has been implemented into a tapped array architecture with eight outputs and 256 photoelements. Operation of each 01)1,1)111 at 16 MHz yields detector integration times of 2 micro-seconds. Buried channel two phase CCD shift register technology is utilized to minimize image sensor noise improve video output rates and increase ease of operation.

Computing the structural influence matrix for biological systems.

PubMed

Giordano, Giulia; Cuba Samaniego, Christian; Franco, Elisa; Blanchini, Franco

2016-06-01

We consider the problem of identifying structural influences of external inputs on steady-state outputs in a biological network model. We speak of a structural influence if, upon a perturbation due to a constant input, the ensuing variation of the steady-state output value has the same sign as the input (positive influence), the opposite sign (negative influence), or is zero (perfect adaptation), for any feasible choice of the model parameters. All these signs and zeros can constitute a structural influence matrix, whose (i, j) entry indicates the sign of steady-state influence of the jth system variable on the ith variable (the output caused by an external persistent input applied to the jth variable). Each entry is structurally determinate if the sign does not depend on the choice of the parameters, but is indeterminate otherwise. In principle, determining the influence matrix requires exhaustive testing of the system steady-state behaviour in the widest range of parameter values. Here we show that, in a broad class of biological networks, the influence matrix can be evaluated with an algorithm that tests the system steady-state behaviour only at a finite number of points. This algorithm also allows us to assess the structural effect of any perturbation, such as variations of relevant parameters. Our method is applied to nontrivial models of biochemical reaction networks and population dynamics drawn from the literature, providing a parameter-free insight into the system dynamics.

Response sensitivity of barrel neuron subpopulations to simulated thalamic input.

PubMed

Pesavento, Michael J; Rittenhouse, Cynthia D; Pinto, David J

2010-06-01

Our goal is to examine the relationship between neuron- and network-level processing in the context of a well-studied cortical function, the processing of thalamic input by whisker-barrel circuits in rodent neocortex. Here we focus on neuron-level processing and investigate the responses of excitatory and inhibitory barrel neurons to simulated thalamic inputs applied using the dynamic clamp method in brain slices. Simulated inputs are modeled after real thalamic inputs recorded in vivo in response to brief whisker deflections. Our results suggest that inhibitory neurons require more input to reach firing threshold, but then fire earlier, with less variability, and respond to a broader range of inputs than do excitatory neurons. Differences in the responses of barrel neuron subtypes depend on their intrinsic membrane properties. Neurons with a low input resistance require more input to reach threshold but then fire earlier than neurons with a higher input resistance, regardless of the neuron's classification. Our results also suggest that the response properties of excitatory versus inhibitory barrel neurons are consistent with the response sensitivities of the ensemble barrel network. The short response latency of inhibitory neurons may serve to suppress ensemble barrel responses to asynchronous thalamic input. Correspondingly, whereas neurons acting as part of the barrel circuit in vivo are highly selective for temporally correlated thalamic input, excitatory barrel neurons acting alone in vitro are less so. These data suggest that network-level processing of thalamic input in barrel cortex depends on neuron-level processing of the same input by excitatory and inhibitory barrel neurons.

Dual Brushless Resolver Rate Sensor

NASA Technical Reports Server (NTRS)

Howard, David E. (Inventor)

1997-01-01

A resolver rate sensor is disclosed in which dual brushless resolvers are mechanically coupled to the same output shaft. Diverse inputs are provided to each resolver by providing the first resolver with a DC input and the second resolver with an AC sinusoidal input. A trigonometric identity in which the sum of the squares of the sin and cosine components equal one is used to advantage in providing a sensor of increased accuracy. The first resolver may have a fixed or variable DC input to permit dynamic adjustment of resolver sensitivity thus permitting a wide range of coverage. In one embodiment of the invention the outputs of the first resolver are directly inputted into two separate multipliers and the outputs of the second resolver are inputted into the two separate multipliers, after being demodulated in a pair of demodulator circuits. The multiplied signals are then added in an adder circuit to provide a directional sensitive output. In another embodiment the outputs from the first resolver is modulated in separate modulator circuits and the output from the modulator circuits are used to excite the second resolver. The outputs from the second resolver are demodulated in separate demodulator circuit and added in an adder circuit to provide a direction sensitive rate output.

Input dependent cell assembly dynamics in a model of the striatal medium spiny neuron network.

PubMed

Ponzi, Adam; Wickens, Jeff

2012-01-01

The striatal medium spiny neuron (MSN) network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri-stimulus time histograms (PSTH) of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioral task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviorally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and outline the range of parameters where this behavior is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior.

Input Dependent Cell Assembly Dynamics in a Model of the Striatal Medium Spiny Neuron Network

PubMed Central

Ponzi, Adam; Wickens, Jeff

2012-01-01

The striatal medium spiny neuron (MSN) network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri-stimulus time histograms (PSTH) of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioral task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviorally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and outline the range of parameters where this behavior is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior. PMID:22438838

Dual Brushless Resolver Rate Sensor

NASA Technical Reports Server (NTRS)

Howard, David E. (Inventor)

1996-01-01

This invention relates to dual analog angular rate sensors which are implemented without the use of mechanical brushes. A resolver rate sensor which includes two brushless resolvers which are mechanically coupled to the same output shaft is provided with inputs which are provided to each resolver by providing the first resolver with a DC input and the second resolver with an AC sinusoidal input. A trigonometric identity in which the sum of the squares of the sin and cosine components equal one is used to advantage in providing a sensor of increased accuracy. The first resolver may have a fixed or variable DC input to permit dynamic adjustment of resolver sensitivity thus permitting a wide range of coverage. Novelty and advantages of the invention reside in the excitation of a resolver with a DC signal and in the utilization of two resolvers and the trigonometric identity of cos(exp 2)(theta) + sin(exp 2)(theta) = 1 to provide an accurate rate sensor which is sensitive to direction and accurate through zero rate.

A high speed and high gain CMOS receiver chip for a pulsed time-of-flight laser rangefinder

NASA Astrophysics Data System (ADS)

Yu, Jin-jin; Deng, Ruo-han; Yuan, Hong-hui; Chen, Yong-ping

2011-06-01

An integrated receiver channel for a pulsed time-of-flight (TOF) laser rangefinder has been designed. Pulsed TOF laser range finding devices using a laser diode transmitter can achieve millimeter-level distance measurement accuracy in a measurement range of several tens of meters to non-cooperative targets. The amplifier exploits the regulated cascade (RGC) configuration as the input-stage, thus achieving as large effective input trans-conductance as that of Si Bipolar or GaAs MESFET. The RGC input configuration isolates the input parasitic capacitance including photodiode capacitance from the bandwidth determination better than common-gate TIA. To enlarge the bandwidth, inductive peaking technology has been adopted. An active inductor (MOS-L) is used instead of spiral inductor in CMOS process. An R-2R resistor ladder is inserting between per-amplifier and post-amplifier as the variable attenuator for digital gain control purpose. The gain-bandwidth of a basic differential pair with resistive load is not large enough for broad band operation. A circuit solution to improve both gain and bandwidth of an amplifying stage is proposed. Traditional and modified Cherry-Hooper amplifiers are discussed and the cascading of several stages to constitute the post-amplifier is designed. The fully integrated one-chip solution is designed with Cadence IC design platform. The simulation result shows the bandwidth of the trans-impedance amplifier is 215MHz with the presence of a 2pF input capacitor and 5pF load capacitor. And the maximum trans-impedance gain is 136dB. The walk error is less than 1ns in 1:1000 dynamic range. The responsive time is less than 2.2ns.

Low noise and conductively cooled microchannel plates

NASA Technical Reports Server (NTRS)

Feller, W. B.

1990-01-01

Microchannel plate (MCP) dynamic range has recently been enhanced for both very low and very high input flux conditions. Improvements in MCP manufacturing technology reported earlier have led to MCPs with substantially reduced radioisotope levels, giving dramatically lower internal background-counting rates. An update is given on the Galileo low noise MCP. Also, new results in increasing the MCP linear counting range for high input flux densities are presented. By bonding the active face of a very low resistance MCP (less than 1 megaohm) to a substrate providing a conductive path for heat transport, the bias current limit (hence, MCP output count rate limit) can be increased up to two orders of magnitude. Normal pulse-counting MCP operation was observed at bias currents of several mA when a curved-channel MCP (80:1) was bonded to a ceramic multianode substrate; the MCP temperature rise above ambient was less than 40 C.

Comparison of LiDAR-derived data and high resolution true color imagery for extracting urban forest cover

Treesearch

Aaron E. Maxwell; Adam C. Riley; Paul Kinder

2013-01-01

Remote sensing has many applications in forestry. Light detection and ranging (LiDAR) and high resolution aerial photography have been investigated as means to extract forest data, such as biomass, timber volume, stand dynamics, and gap characteristics. LiDAR return intensity data are often overlooked as a source of input raster data for thematic map creation. We...

Variation in watershed nitrogen input and export across the Willamette River Basin

NASA Astrophysics Data System (ADS)

Goodwin, K. E.; Compton, J. E.; Sobota, D. J.

2011-12-01

Nitrogen (N) export from watersheds is influenced by hydrology, land use/cover, and the timing and spatial arrangement of N inputs and removal within basins. We examined the relationship between N input and watershed N export for 25 monitoring stations between 1996 and 2006 within the Willamette River Basin, western Oregon USA. We hypothesized that N export would be strongly correlated with N inputs, and that much of the N inputs comes from agricultural activities located in lowland portions of the basin. We also expected that N export would be strongly seasonal, reflecting the Mediterranean climate of the region. We found a wide range of export from the monitored WRB sub-basins, ranging from 1 to nearly 70 kg N ha-1 yr-1. Lower per unit area N export reflected a high proportion of watershed area in the predominantly forested Cascade Mountains, while the higher N export basins had a greater proportion of agricultural areas, particularly areas dominated by cultivated crops with high N requirements. Export of N varied greatly from year to year (up to nearly 200%), responding to interannual changes in precipitation and runoff. Export was strongly seasonal, with at least 50%, and often 75%, of the N export occurring during the fall and winter months. Snowmelt dominated Cascade Mountain streams tended to maintain flow and N export during the summer, compared with the basins draining Coast-Range and valley areas, which have less snow and spring rain inputs to maintain summer flow. Agricultural N inputs of synthetic and manure fertilizer were strongly correlated with N export from the sub-basins. Across the WRB, N export appears to be more strongly related to fertilizer application rates, as opposed to agricultural areas, indicating the importance of specific crops and crop practices as opposed to considering all agricultural lands the same in analyses of watershed N dynamics. This reinforces the need for careful tracking of N inputs to inform water quality monitoring and management. Annual N export was strongly driven by precipitation and runoff, suggesting that changes in hydrology will have important effects on N export downstream and to coastal areas in the future.

Perceptual Contrast Enhancement with Dynamic Range Adjustment

PubMed Central

Zhang, Hong; Li, Yuecheng; Chen, Hao; Yuan, Ding; Sun, Mingui

2013-01-01

Recent years, although great efforts have been made to improve its performance, few Histogram equalization (HE) methods take human visual perception (HVP) into account explicitly. The human visual system (HVS) is more sensitive to edges than brightness. This paper proposes to take use of this nature intuitively and develops a perceptual contrast enhancement approach with dynamic range adjustment through histogram modification. The use of perceptual contrast connects the image enhancement problem with the HVS. To pre-condition the input image before the HE procedure is implemented, a perceptual contrast map (PCM) is constructed based on the modified Difference of Gaussian (DOG) algorithm. As a result, the contrast of the image is sharpened and high frequency noise is suppressed. A modified Clipped Histogram Equalization (CHE) is also developed which improves visual quality by automatically detecting the dynamic range of the image with improved perceptual contrast. Experimental results show that the new HE algorithm outperforms several state-of-the-art algorithms in improving perceptual contrast and enhancing details. In addition, the new algorithm is simple to implement, making it suitable for real-time applications. PMID:24339452

Calibration of a universal indicated turbulence system

NASA Technical Reports Server (NTRS)

Chapin, W. G.

1977-01-01

Theoretical and experimental work on a Universal Indicated Turbulence Meter is described. A mathematical transfer function from turbulence input to output indication was developed. A random ergodic process and a Gaussian turbulence distribution were assumed. A calibration technique based on this transfer function was developed. The computer contains a variable gain amplifier to make the system output independent of average velocity. The range over which this independence holds was determined. An optimum dynamic response was obtained for the tubulation between the system pitot tube and pressure transducer by making dynamic response measurements for orifices of various lengths and diameters at the source end.

Dynamic Analysis of Spur Gear Transmissions (DANST). PC Version 3.00 User Manual

NASA Technical Reports Server (NTRS)

Oswald, Fred B.; Lin, Hsiang Hsi; Delgado, Irebert R.

1996-01-01

DANST is a FORTRAN computer program for static and dynamic analysis of spur gear systems. The program can be used for parametric studies to predict the static transmission error, dynamic load, tooth bending stress and other properties of spur gears as they are influenced by operating speed, torque, stiffness, damping, inertia, and tooth profile. DANST performs geometric modeling and dynamic analysis for low- or high-contact-ratio spur gears. DANST can simulate gear systems with contact ratios ranging from one to three. It was designed to be easy to use and it is extensively documented in several previous reports and by comments in the source code. This report describes installing and using a new PC version of DANST, covers input data requirements and presents examples.

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

L1 Adaptive Control Augmentation System with Application to the X-29 Lateral/Directional Dynamics: A Multi-Input Multi-Output Approach

NASA Technical Reports Server (NTRS)

Griffin, Brian Joseph; Burken, John J.; Xargay, Enric

2010-01-01

This paper presents an L(sub 1) adaptive control augmentation system design for multi-input multi-output nonlinear systems in the presence of unmatched uncertainties which may exhibit significant cross-coupling effects. A piecewise continuous adaptive law is adopted and extended for applicability to multi-input multi-output systems that explicitly compensates for dynamic cross-coupling. In addition, explicit use of high-fidelity actuator models are added to the L1 architecture to reduce uncertainties in the system. The L(sub 1) multi-input multi-output adaptive control architecture is applied to the X-29 lateral/directional dynamics and results are evaluated against a similar single-input single-output design approach.

Inevitable end-of-21st-century trends toward earlier surface runoff timing in California's Sierra Nevada Mountains

NASA Astrophysics Data System (ADS)

Schwartz, M. A.; Hall, A. D.; Sun, F.; Walton, D.; Berg, N.

2015-12-01

Hybrid dynamical-statistical downscaling is used to produce surface runoff timing projections for California's Sierra Nevada, a high-elevation mountain range with significant seasonal snow cover. First, future climate change projections (RCP8.5 forcing scenario, 2081-2100 period) from five CMIP5 global climate models (GCMs) are dynamically downscaled. These projections reveal that future warming leads to a shift toward earlier snowmelt and surface runoff timing throughout the Sierra Nevada region. Relationships between warming and surface runoff timing from the dynamical simulations are used to build a simple statistical model that mimics the dynamical model's projected surface runoff timing changes given GCM input or other statistically-downscaled input. This statistical model can be used to produce surface runoff timing projections for other GCMs, periods, and forcing scenarios to quantify ensemble-mean changes, uncertainty due to intermodel variability and consequences stemming from choice of forcing scenario. For all CMIP5 GCMs and forcing scenarios, significant trends toward earlier surface runoff timing occur at elevations below 2500m. Thus, we conclude that trends toward earlier surface runoff timing by the end-of-the-21st century are inevitable. The changes to surface runoff timing diagnosed in this study have implications for many dimensions of climate change, including impacts on surface hydrology, water resources, and ecosystems.

The situated HKB model: how sensorimotor spatial coupling can alter oscillatory brain dynamics

PubMed Central

Aguilera, Miguel; Bedia, Manuel G.; Santos, Bruno A.; Barandiaran, Xabier E.

2013-01-01

Despite the increase of both dynamic and embodied/situated approaches in cognitive science, there is still little research on how coordination dynamics under a closed sensorimotor loop might induce qualitatively different patterns of neural oscillations compared to those found in isolated systems. We take as a departure point the Haken-Kelso-Bunz (HKB) model, a generic model for dynamic coordination between two oscillatory components, which has proven useful for a vast range of applications in cognitive science and whose dynamical properties are well understood. In order to explore the properties of this model under closed sensorimotor conditions we present what we call the situated HKB model: a robotic model that performs a gradient climbing task and whose “brain” is modeled by the HKB equation. We solve the differential equations that define the agent-environment coupling for increasing values of the agent's sensitivity (sensor gain), finding different behavioral strategies. These results are compared with two different models: a decoupled HKB with no sensory input and a passively-coupled HKB that is also decoupled but receives a structured input generated by a situated agent. We can precisely quantify and qualitatively describe how the properties of the system, when studied in coupled conditions, radically change in a manner that cannot be deduced from the decoupled HKB models alone. We also present the notion of neurodynamic signature as the dynamic pattern that correlates with a specific behavior and we show how only a situated agent can display this signature compared to an agent that simply receives the exact same sensory input. To our knowledge, this is the first analytical solution of the HKB equation in a sensorimotor loop and qualitative and quantitative analytic comparison of spatially coupled vs. decoupled oscillatory controllers. Finally, we discuss the limitations and possible generalization of our model to contemporary neuroscience and philosophy of mind. PMID:23986692

Dynamic Organization of Hierarchical Memories

PubMed Central

Kurikawa, Tomoki; Kaneko, Kunihiko

2016-01-01

In the brain, external objects are categorized in a hierarchical way. Although it is widely accepted that objects are represented as static attractors in neural state space, this view does not take account interaction between intrinsic neural dynamics and external input, which is essential to understand how neural system responds to inputs. Indeed, structured spontaneous neural activity without external inputs is known to exist, and its relationship with evoked activities is discussed. Then, how categorical representation is embedded into the spontaneous and evoked activities has to be uncovered. To address this question, we studied bifurcation process with increasing input after hierarchically clustered associative memories are learned. We found a “dynamic categorization”; neural activity without input wanders globally over the state space including all memories. Then with the increase of input strength, diffuse representation of higher category exhibits transitions to focused ones specific to each object. The hierarchy of memories is embedded in the transition probability from one memory to another during the spontaneous dynamics. With increased input strength, neural activity wanders over a narrower state space including a smaller set of memories, showing more specific category or memory corresponding to the applied input. Moreover, such coarse-to-fine transitions are also observed temporally during transient process under constant input, which agrees with experimental findings in the temporal cortex. These results suggest the hierarchy emerging through interaction with an external input underlies hierarchy during transient process, as well as in the spontaneous activity. PMID:27618549

Focal plane infrared readout circuit

NASA Technical Reports Server (NTRS)

Pain, Bedabrata (Inventor)

2002-01-01

An infrared imager, such as a spectrometer, includes multiple infrared photodetectors and readout circuits for reading out signals from the photodetectors. Each readout circuit includes a buffered direct injection input circuit including a differential amplifier with active feedback provided through an injection transistor. The differential amplifier includes a pair of input transistors, a pair of cascode transistors and a current mirror load. Photocurrent from a photodetector can be injected onto an integration capacitor in the readout circuit with high injection efficiency at high speed. A high speed, low noise, wide dynamic range linear infrared multiplexer array for reading out infrared detectors with large capacitances can be achieved even when short exposure times are used. The effect of image lag can be reduced.

PyMUS: Python-Based Simulation Software for Virtual Experiments on Motor Unit System.

PubMed

Kim, Hojeong; Kim, Minjung

2018-01-01

We constructed a physiologically plausible computationally efficient model of a motor unit and developed simulation software that allows for integrative investigations of the input-output processing in the motor unit system. The model motor unit was first built by coupling the motoneuron model and muscle unit model to a simplified axon model. To build the motoneuron model, we used a recently reported two-compartment modeling approach that accurately captures the key cell-type-related electrical properties under both passive conditions (somatic input resistance, membrane time constant, and signal attenuation properties between the soma and the dendrites) and active conditions (rheobase current and afterhyperpolarization duration at the soma and plateau behavior at the dendrites). To construct the muscle unit, we used a recently developed muscle modeling approach that reflects the experimentally identified dependencies of muscle activation dynamics on isometric, isokinetic and dynamic variation in muscle length over a full range of stimulation frequencies. Then, we designed the simulation software based on the object-oriented programing paradigm and developed the software using open-source Python language to be fully operational using graphical user interfaces. Using the developed software, separate simulations could be performed for a single motoneuron, muscle unit and motor unit under a wide range of experimental input protocols, and a hierarchical analysis could be performed from a single channel to the entire system behavior. Our model motor unit and simulation software may represent efficient tools not only for researchers studying the neural control of force production from a cellular perspective but also for instructors and students in motor physiology classroom settings.

Wide-dynamic-range forward suppression in marmoset inferior colliculus neurons is generated centrally and accounts for perceptual masking.

PubMed

Nelson, Paul C; Smith, Zachary M; Young, Eric D

2009-02-25

An organism's ability to detect and discriminate sensory inputs depends on the recent stimulus history. For example, perceptual detection thresholds for a brief tone can be elevated by as much as 50 dB when following a masking stimulus. Previous work suggests that such forward masking is not a direct result of peripheral neural adaptation; the central pathway apparently modifies the representation in a way that further attenuates the input's response to short probe signals. Here, we show that much of this transformation is complete by the level of the inferior colliculus (IC). Single-neuron extracellular responses were recorded in the central nucleus of the awake marmoset IC. The threshold for a 20 ms probe tone presented at best frequency was determined for various masker-probe delays, over a range of masker sound pressure levels (SPLs) and frequencies. The most striking aspect of the data was the increased potency of forward maskers as their SPL was increased, despite the fact that the excitatory response to the masker was often saturating or nonmonotonic over the same range of levels. This led to probe thresholds at high masker levels that were almost always higher than those observed in the auditory nerve. Probe threshold shifts were not usually caused by a persistent excitatory response to the masker; instead we propose a wide-dynamic-range inhibitory mechanism locked to sound offset as an explanation for several key aspects of the data. These findings further delineate the role of subcortical auditory processing in the generation of a context-dependent representation of ongoing acoustic scenes.

Gain-adaptive vector quantization for medium-rate speech coding

NASA Technical Reports Server (NTRS)

Chen, J.-H.; Gersho, A.

1985-01-01

A class of adaptive vector quantizers (VQs) that can dynamically adjust the 'gain' of codevectors according to the input signal level is introduced. The encoder uses a gain estimator to determine a suitable normalization of each input vector prior to VQ coding. The normalized vectors have reduced dynamic range and can then be more efficiently coded. At the receiver, the VQ decoder output is multiplied by the estimated gain. Both forward and backward adaptation are considered and several different gain estimators are compared and evaluated. An approach to optimizing the design of gain estimators is introduced. Some of the more obvious techniques for achieving gain adaptation are substantially less effective than the use of optimized gain estimators. A novel design technique that is needed to generate the appropriate gain-normalized codebook for the vector quantizer is introduced. Experimental results show that a significant gain in segmental SNR can be obtained over nonadaptive VQ with a negligible increase in complexity.

Analog-to-Digital Conversion to Accommodate the Dynamics of Live Music in Hearing Instruments

PubMed Central

Bahlmann, Frauke; Fulton, Bernadette

2012-01-01

Hearing instrument design focuses on the amplification of speech to reduce the negative effects of hearing loss. Many amateur and professional musicians, along with music enthusiasts, also require their hearing instruments to perform well when listening to the frequent, high amplitude peaks of live music. One limitation, in most current digital hearing instruments with 16-bit analog-to-digital (A/D) converters, is that the compressor before the A/D conversion is limited to 95 dB (SPL) or less at the input. This is more than adequate for the dynamic range of speech; however, this does not accommodate the amplitude peaks present in live music. The hearing instrument input compression system can be adjusted to accommodate for the amplitudes present in music that would otherwise be compressed before the A/D converter in the hearing instrument. The methodology behind this technological approach will be presented along with measurements to demonstrate its effectiveness. PMID:23258618

Development and Implementation of Software for Visualizing and Editing Multidimensional Flight Simulation Input Data

NASA Technical Reports Server (NTRS)

Whelan, Todd Michael

1996-01-01

In a real-time or batch mode simulation that is designed to model aircraft dynamics over a wide range of flight conditions, a table look- up scheme is implemented to determine the forces and moments on the vehicle based upon the values of parameters such as angle of attack, altitude, Mach number, and control surface deflections. Simulation Aerodynamic Variable Interface (SAVI) is a graphical user interface to the flight simulation input data, designed to operate on workstations that support X Windows. The purpose of the application is to provide two and three dimensional visualization of the data, to allow an intuitive sense of the data set. SAVI also allows the user to manipulate the data, either to conduct an interactive study of the influence of changes on the vehicle dynamics, or to make revisions to data set based on new information such as flight test. This paper discusses the reasons for developing the application, provides an overview of its capabilities, and outlines the software architecture and operating environment.

Experimental Results From a 2kW Brayton Power Conversion Unit

NASA Technical Reports Server (NTRS)

Hervol, David; Mason, Lee; Birchenough, Arthur

2003-01-01

This paper presents experimental test results from operation of a 2 kWe Brayton power conversion unit. The Brayton converter was developed for a solar dynamic power system flight experiment planned for the Mir Space Station in 1997. The flight experiment was cancelled, but the converter was tested at Glenn Research Center as part of the Solar Dynamic Ground Test Demonstration system which included a solar concentrator, heat receiver, and space radiator. In preparation for the current testing, the heat receiver was removed and replaced with an electrical resistance heater, simulating the thermal input of a steady-state nuclear source. The converter was operated over a full range of thermal input power levels and rotor speeds to generate an overall performance map. The converter unit will serve as the centerpiece of a Nuclear Electric Propulsion Testbed at Glenn. Future potential uses for the Testbed include high voltage electrical controller development, integrated electric thruster testing and advanced radiator demonstration testing to help guide high power Brayton technology development for Nuclear Electric Propulsion (NEP).

Dynamical Characteristics Common to Neuronal Competition Models

PubMed Central

Shpiro, Asya; Curtu, Rodica; Rinzel, John; Rubin, Nava

2009-01-01

Models implementing neuronal competition by reciprocally inhibitory populations are widely used to characterize bistable phenomena such as binocular rivalry. We find common dynamical behavior in several models of this general type, which differ in their architecture in the form of their gain functions, and in how they implement the slow process that underlies alternating dominance. We focus on examining the effect of the input strength on the rate (and existence) of oscillations. In spite of their differences, all considered models possess similar qualitative features, some of which we report here for the first time. Experimentally, dominance durations have been reported to decrease monotonically with increasing stimulus strength (such as Levelt's “Proposition IV”). The models predict this behavior; however, they also predict that at a lower range of input strength dominance durations increase with increasing stimulus strength. The nonmonotonic dependency of duration on stimulus strength is common to both deterministic and stochastic models. We conclude that additional experimental tests of Levelt's Proposition IV are needed to reconcile models and perception. PMID:17065254

Adaptive learning and control for MIMO system based on adaptive dynamic programming.

PubMed

Fu, Jian; He, Haibo; Zhou, Xinmin

2011-07-01

Adaptive dynamic programming (ADP) is a promising research field for design of intelligent controllers, which can both learn on-the-fly and exhibit optimal behavior. Over the past decades, several generations of ADP design have been proposed in the literature, which have demonstrated many successful applications in various benchmarks and industrial applications. While many of the existing researches focus on multiple-inputs-single-output system with steepest descent search, in this paper we investigate a generalized multiple-input-multiple-output (GMIMO) ADP design for online learning and control, which is more applicable to a wide range of practical real-world applications. Furthermore, an improved weight-updating algorithm based on recursive Levenberg-Marquardt methods is presented and embodied in the GMIMO approach to improve its performance. Finally, we test the performance of this approach based on a practical complex system, namely, the learning and control of the tension and height of the looper system in a hot strip mill. Experimental results demonstrate that the proposed approach can achieve effective and robust performance.

A liquid lens switching-based motionless variable fiber-optic delay line

NASA Astrophysics Data System (ADS)

Khwaja, Tariq Shamim; Reza, Syed Azer; Sheikh, Mumtaz

2018-05-01

We present a Variable Fiber-Optic Delay Line (VFODL) module capable of imparting long variable delays by switching an input optical/RF signal between Single Mode Fiber (SMF) patch cords of different lengths through a pair of Electronically Controlled Tunable Lenses (ECTLs) resulting in a polarization-independent operation. Depending on intended application, the lengths of the SMFs can be chosen accordingly to achieve the desired VFODL operation dynamic range. If so desired, the state of the input signal polarization can be preserved with the use of commercially available polarization-independent ECTLs along with polarization-maintaining SMFs (PM-SMFs), resulting in an output polarization that is identical to the input. An ECTL-based design also improves power consumption and repeatability. The delay switching mechanism is electronically-controlled, involves no bulk moving parts, and can be fully-automated. The VFODL module is compact due to the use of small optical components and SMFs that can be packaged compactly.

Research on hysteresis loop considering the prestress effect and electrical input dynamics for a giant magnetostrictive actuator

NASA Astrophysics Data System (ADS)

Zhu, Yuchuan; Yang, Xulei; Wereley, Norman M.

2016-08-01

In this paper, focusing on the application-oriented giant magnetostrictive material (GMM)-based electro-hydrostatic actuator, which features an applied magnetic field at high frequency and high amplitude, and concentrating on the static and dynamic characteristics of a giant magnetostrictive actuator (GMA) considering the prestress effect on the GMM rod and the electrical input dynamics involving the power amplifier and the inductive coil, a methodology for studying the static and dynamic characteristics of a GMA using the hysteresis loop as a tool is developed. A GMA that can display the preforce on the GMM rod in real-time is designed, and a magnetostrictive model dependent on the prestress on a GMM rod instead of the existing quadratic domain rotation model is proposed. Additionally, an electrical input dynamics model to excite GMA is developed according to the simplified circuit diagram, and the corresponding parameters are identified by the experimental data. A dynamic magnetization model with the eddy current effect is deduced according to the Jiles-Atherton model and the Maxwell equations. Next, all of the parameters, including the electrical input characteristics, the dynamic magnetization and the mechanical structure of GMA, are identified by the experimental data from the current response, magnetization response and displacement response, respectively. Finally, a comprehensive comparison between the model results and experimental data is performed, and the results show that the test data agree well with the presented model results. An analysis on the relation between the GMA displacement response and the parameters from the electrical input dynamics, magnetization dynamics and mechanical structural dynamics is performed.

Multi-exposure high dynamic range image synthesis with camera shake correction

NASA Astrophysics Data System (ADS)

Li, Xudong; Chen, Yongfu; Jiang, Hongzhi; Zhao, Huijie

2017-10-01

Machine vision plays an important part in industrial online inspection. Owing to the nonuniform illuminance conditions and variable working distances, the captured image tends to be over-exposed or under-exposed. As a result, when processing the image such as crack inspection, the algorithm complexity and computing time increase. Multiexposure high dynamic range (HDR) image synthesis is used to improve the quality of the captured image, whose dynamic range is limited. Inevitably, camera shake will result in ghost effect, which blurs the synthesis image to some extent. However, existed exposure fusion algorithms assume that the input images are either perfectly aligned or captured in the same scene. These assumptions limit the application. At present, widely used registration based on Scale Invariant Feature Transform (SIFT) is usually time consuming. In order to rapidly obtain a high quality HDR image without ghost effect, we come up with an efficient Low Dynamic Range (LDR) images capturing approach and propose a registration method based on ORiented Brief (ORB) and histogram equalization which can eliminate the illumination differences between the LDR images. The fusion is performed after alignment. The experiment results demonstrate that the proposed method is robust to illumination changes and local geometric distortion. Comparing with other exposure fusion methods, our method is more efficient and can produce HDR images without ghost effect by registering and fusing four multi-exposure images.

Dynamic protein assembly by programmable DNA strand displacement.

PubMed

Chen, Rebecca P; Blackstock, Daniel; Sun, Qing; Chen, Wilfred

2018-04-01

Inspired by the remarkable ability of natural protein switches to sense and respond to a wide range of environmental queues, here we report a strategy to engineer synthetic protein switches by using DNA strand displacement to dynamically organize proteins with highly diverse and complex logic gate architectures. We show that DNA strand displacement can be used to dynamically control the spatial proximity and the corresponding fluorescence resonance energy transfer between two fluorescent proteins. Performing Boolean logic operations enabled the explicit control of protein proximity using multi-input, reversible and amplification architectures. We further demonstrate the power of this technology beyond sensing by achieving dynamic control of an enzyme cascade. Finally, we establish the utility of the approach as a synthetic computing platform that drives the dynamic reconstitution of a split enzyme for targeted prodrug activation based on the sensing of cancer-specific miRNAs.

Dynamic protein assembly by programmable DNA strand displacement

NASA Astrophysics Data System (ADS)

Chen, Rebecca P.; Blackstock, Daniel; Sun, Qing; Chen, Wilfred

2018-03-01

Inspired by the remarkable ability of natural protein switches to sense and respond to a wide range of environmental queues, here we report a strategy to engineer synthetic protein switches by using DNA strand displacement to dynamically organize proteins with highly diverse and complex logic gate architectures. We show that DNA strand displacement can be used to dynamically control the spatial proximity and the corresponding fluorescence resonance energy transfer between two fluorescent proteins. Performing Boolean logic operations enabled the explicit control of protein proximity using multi-input, reversible and amplification architectures. We further demonstrate the power of this technology beyond sensing by achieving dynamic control of an enzyme cascade. Finally, we establish the utility of the approach as a synthetic computing platform that drives the dynamic reconstitution of a split enzyme for targeted prodrug activation based on the sensing of cancer-specific miRNAs.

Is the Voter Model a Model for Voters?

NASA Astrophysics Data System (ADS)

Fernández-Gracia, Juan; Suchecki, Krzysztof; Ramasco, José J.; San Miguel, Maxi; Eguíluz, Víctor M.

2014-04-01

The voter model has been studied extensively as a paradigmatic opinion dynamics model. However, its ability to model real opinion dynamics has not been addressed. We introduce a noisy voter model (accounting for social influence) with recurrent mobility of agents (as a proxy for social context), where the spatial and population diversity are taken as inputs to the model. We show that the dynamics can be described as a noisy diffusive process that contains the proper anisotropic coupling topology given by population and mobility heterogeneity. The model captures statistical features of U.S. presidential elections as the stationary vote-share fluctuations across counties and the long-range spatial correlations that decay logarithmically with the distance. Furthermore, it recovers the behavior of these properties when the geographical space is coarse grained at different scales—from the county level through congressional districts, and up to states. Finally, we analyze the role of the mobility range and the randomness in decision making, which are consistent with the empirical observations.

Ideal free distribution or dynamic game? An agent-based simulation study of trawling strategies with varying information

NASA Astrophysics Data System (ADS)

Beecham, J. A.; Engelhard, G. H.

2007-10-01

An ecological economic model of trawling is presented to demonstrate the effect of trawling location choice strategy on net input (rate of economic gain of fish caught per time spent less costs). Fishing location choice is considered to be a dynamic process whereby trawlers chose from among a repertoire of plastic strategies that they modify if their gains fall below a fixed proportion of the mean gains of the fleet as a whole. The distribution of fishing across different areas of a fishery follows an approximate ideal free distribution (IFD) with varying noise due to uncertainty. The least-productive areas are not utilised because initial net input never reaches the mean yield of better areas subject to competitive exploitation. In cases, where there is a weak temporal autocorrelation between fish stocks in a specific location, a plastic strategy of local translocation between trawls mixed with longer-range translocation increases realised input. The trawler can change its translocation strategy in the light of information about recent trawling success compared to its long-term average but, in contrast to predictions of the Marginal Value Theorem (MVT) model, does not know for certain what it will find by moving, so may need to sample new patches. The combination of the two types of translocation mirrored beam-trawling strategies used by the Dutch fleet and the resultant distribution of trawling effort is confirmed by analysis of historical effort distribution of British otter trawling fleets in the North Sea. Fisheries exploitation represents an area where dynamic agent-based adaptive models may be a better representation of the economic dynamics of a fleet than classically inspired optimisation models.

(A)biotic processes control soil carbon dynamics: quantitative assessment of model complexity, stability and response to perturbations for improving ESMs

NASA Astrophysics Data System (ADS)

Georgiou, K.; Abramoff, R. Z.; Harte, J.; Riley, W. J.; Torn, M. S.

2016-12-01

As global temperatures and atmospheric CO2 concentrations continue to increase, soil microbial activity and decomposition of soil organic matter (SOM) are expected to follow suit, potentially limiting soil carbon storage. Traditional global- and ecosystem-scale models simulate SOM decomposition using linear kinetics, which are inherently unable to reproduce carbon-concentration feedbacks, such as priming of native SOM at elevated CO2 concentrations. Recent studies using nonlinear microbial models of SOM decomposition seek to capture these interactions, and several groups are currently integrating these microbial models into Earth System Models (ESMs). However, despite their widespread ability to exhibit nonlinear responses, these models vary tremendously in complexity and, consequently, dynamics. In this study, we explore, both analytically and numerically, the emergent oscillatory behavior and insensitivity of SOM stocks to carbon inputs that have been deemed `unrealistic' in recent microbial models. We discuss the sources of instability in four models of varying complexity, by sequentially reducing complexity of a detailed model that includes microbial physiology, a mineral sorption isotherm, and enzyme dynamics. We also present an alternative representation of microbial turnover that limits population sizes and, thus, reduces oscillations. We compare these models to several long-term carbon input manipulations, including the Detritus Input and Removal Treatment (DIRT) experiments, to show that there are clear metrics that can be used to distinguish and validate the inherent dynamics of each model structure. We find that traditional linear and nonlinear models cannot readily capture the range of long-term responses observed across the DIRT experiments as a direct consequence of their model structures, and that modifying microbial turnover results in more realistic predictions. Finally, we discuss our findings in the context of improving microbial model behavior for inclusion in ESMs.

Integration and dynamics of a renewable regenerative hydrogen fuel cell system

NASA Astrophysics Data System (ADS)

Bergen, Alvin Peter

2008-10-01

This thesis explores the integration and dynamics of residential scale renewable-regenerative energy systems which employ hydrogen for energy buffering. The development of the Integrated Renewable Energy Experiment (IRENE) test-bed is presented. IRENE is a laboratory-scale distributed energy system with a modular structure which can be readily re-configured to test newly developed components for generic regenerative systems. Key aspects include renewable energy conversion, electrolysis, hydrogen and electricity storage, and fuel cells. A special design feature of this test bed is the ability to accept dynamic inputs from and provide dynamic loads to real devices as well as from simulated energy sources/sinks. The integration issues encountered while developing IRENE and innovative solutions devised to overcome these barriers are discussed. Renewable energy systems that employ a regenerative approach to enable intermittent energy sources to service time varying loads rely on the efficient transfer of energy through the storage media. Experiments were conducted to evaluate the performance of the hydrogen energy buffer under a range of dynamic operating conditions. Results indicate that the operating characteristics of the electrolyser under transient conditions limit the production of hydrogen from excess renewable input power. These characteristics must be considered when designing or modeling a renewable-regenerative system. Strategies to mitigate performance degradation due to interruptions in the renewable power supply are discussed. Experiments were conducted to determine the response of the IRENE system to operating conditions that are representative of a residential scale, solar based, renewable-regenerative system. A control algorithm, employing bus voltage constraints and device current limitations, was developed to guide system operation. Results for a two week operating period that indicate that the system response is very dynamic but repeatable are presented. The overall system energy balance reveals that the energy input from the renewable source was sufficient to meet the demand load and generate a net surplus of hydrogen. The energy loss associated with the various system components as well as a breakdown of the unused renewable energy input is presented. In general, the research indicates that the technical challenges associated with hydrogen energy buffing can be overcome, but the round trip efficiency for the current technologies is low at only 22 percent.

TRAGEN: Computer program to simulate an aircraft steered to follow a specified verticle profile. User's guide

NASA Technical Reports Server (NTRS)

1983-01-01

The longitudinal dynamics of a medium range twin-jet or tri-jet transport aircraft are simulated. For the climbing trajectory, the thrust is constrained to maximum value, and for descent, the thrust is set at idle. For cruise, the aircraft is held in the trim condition. For climb or descent, the aircraft is steered to follow either (a) a fixed profile which is input to the program or (b) a profile computed at the beginning of that segment of the run. For climb, the aircraft is steered to maintain the given airspeed as a function of altitude. For descent, the aircraft is steered to maintain the given altitude as a function of range-to-go. In both cases, the control variable is angle-of-attack. The given output trajectory is presented and compared with the input trajectory. Step climb is treated just as climb. For cruise, the Breguet equations are used to compute the fuel burned to achieve a given range and to connect given initial and final values of altitude and Mach number.

Surface dynamics of voltage-gated ion channels.

PubMed

Heine, Martin; Ciuraszkiewicz, Anna; Voigt, Andreas; Heck, Jennifer; Bikbaev, Arthur

2016-07-03

Neurons encode information in fast changes of the membrane potential, and thus electrical membrane properties are critically important for the integration and processing of synaptic inputs by a neuron. These electrical properties are largely determined by ion channels embedded in the membrane. The distribution of most ion channels in the membrane is not spatially uniform: they undergo activity-driven changes in the range of minutes to days. Even in the range of milliseconds, the composition and topology of ion channels are not static but engage in highly dynamic processes including stochastic or activity-dependent transient association of the pore-forming and auxiliary subunits, lateral diffusion, as well as clustering of different channels. In this review we briefly discuss the potential impact of mobile sodium, calcium and potassium ion channels and the functional significance of this for individual neurons and neuronal networks.

Surface dynamics of voltage-gated ion channels

PubMed Central

Heine, Martin; Ciuraszkiewicz, Anna; Voigt, Andreas; Heck, Jennifer; Bikbaev, Arthur

2016-01-01

ABSTRACT Neurons encode information in fast changes of the membrane potential, and thus electrical membrane properties are critically important for the integration and processing of synaptic inputs by a neuron. These electrical properties are largely determined by ion channels embedded in the membrane. The distribution of most ion channels in the membrane is not spatially uniform: they undergo activity-driven changes in the range of minutes to days. Even in the range of milliseconds, the composition and topology of ion channels are not static but engage in highly dynamic processes including stochastic or activity-dependent transient association of the pore-forming and auxiliary subunits, lateral diffusion, as well as clustering of different channels. In this review we briefly discuss the potential impact of mobile sodium, calcium and potassium ion channels and the functional significance of this for individual neurons and neuronal networks. PMID:26891382

Tracking Movement of Plant Carbon Through Soil to Water by Lignin Phenol Stable Carbon Isotope Composition in a Small Agricultural Watershed

NASA Astrophysics Data System (ADS)

Crooker, K.; Filley, T.; Six, J.; Frey, J.

2005-12-01

Few studies integrate land cover, soil physical structure, and aquatic physical fractions when investigating the fate of agricultural carbon in watersheds. In crop systems that involve rotations of soy (a C3 plant) and corn (a C4 plant) the large intrinsic differences in stable carbon isotope values and lignin plus cutin chemistry enable tracking of plant carbon movement from soil fractions to DOM and overland flow during precipitation events. In a small (~3Km2) agricultural basin in central Indiana, we studied plant carbon dynamics in a soy/corn agricultural rotation (2004-2005) to determine the relative inputs of these two plants to soil fractions and the resultant contributions to dissolved, colloidal, and particulate organic matter when mobilized. Using bulk isotope values the fraction of carbon derived from corn in macroaggregates (>250 micron), microaggregates (53-250 mm), and silts plus clays (<53 mm) ranged from 39, 49, to 42%, respectively. Unlike bulk analyses, compound specific isotope analysis of lignin in the soil fractions revealed a wide range of relative inputs among the monomers with cinnamyl phenols being almost exclusively (~ 93%) derived from corn. Syringyl phenols ranged from 75-56% corn and vanillyl phenols ranged from 37-40% corn carbon. The relative input among the fractions mirrors closely the comparative plant chemistry abundances between soy and corn. During export of DOM from the land to the stream the relative abundance of plant source varied with discharge (0.05-1.8 m3/sec) as increases in flow increased the relative export of corn-derived C from the fields. Over the full range of flows lignin phenols varied from 0.05 to 82% corn-derived with the greatest relative corn input for cinnamyl and syringyl carbon. The trend with stream discharge indicates a progressive movement of particulate corn residues with overland flow. Ongoing studies look to resolve contributions of algae, bacteria and terrestrial plants to soil fractions and their mobilized components.

Rotorcraft control system design for uncertain vehicle dynamics using quantitative feedback theory

NASA Technical Reports Server (NTRS)

Hess, R. A.

1994-01-01

Quantitative Feedback Theory describes a frequency-domain technique for the design of multi-input, multi-output control systems which must meet time or frequency domain performance criteria when specified uncertainty exists in the linear description of the vehicle dynamics. This theory is applied to the design of the longitudinal flight control system for a linear model of the BO-105C rotorcraft. Uncertainty in the vehicle model is due to the variation in the vehicle dynamics over a range of airspeeds from 0-100 kts. For purposes of exposition, the vehicle description contains no rotor or actuator dynamics. The design example indicates the manner in which significant uncertainty exists in the vehicle model. The advantage of using a sequential loop closure technique to reduce the cost of feedback is demonstrated by example.

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

Braga, D.; Coleman-Smith, P. J.; Davinson, T.

We have designed a read-out ASIC for nuclear decay spectroscopy as part of the AIDA project - the Advanced Implantation Detector Array. AIDA will be installed in experiments at the Facility for Antiproton and Ion Research in GSI, Darmstadt. The AIDA ASIC will measure the signals when unstable nuclei are implanted into the detector, followed by the much smaller signals when the nuclei subsequently decay. Implant energies can be as high as 20 GeV; decay products need to be measured down to 25 keV within just a few microseconds of the initial implants. The ASIC uses two amplifiers per detectormore » channel, one covering the 20 GeV dynamic range, the other selectable over a 20 MeV or 1 GeV range. The amplifiers are linked together by bypass transistors which are normally switched off. The arrival of a large signal causes saturation of the low-energy amplifier and a fluctuation of the input voltage, which activates the link to the high-energy amplifier. The bypass transistors switch on and the input charge is integrated by the high-energy amplifier. The signal is shaped and stored by a peak-hold, then read out on a multiplexed output. Control logic resets the amplifiers and bypass circuit, allowing the low-energy amplifier to measure the subsequent decay signal. We present simulations and test results, demonstrating the AIDA ASIC operation over a wide range of input signals. (authors)« less

Uncertainty Quantification of the FUN3D-Predicted NASA CRM Flutter Boundary

NASA Technical Reports Server (NTRS)

Stanford, Bret K.; Massey, Steven J.

2017-01-01

A nonintrusive point collocation method is used to propagate parametric uncertainties of the flexible Common Research Model, a generic transport configuration, through the unsteady aeroelastic CFD solver FUN3D. A range of random input variables are considered, including atmospheric flow variables, structural variables, and inertial (lumped mass) variables. UQ results are explored for a range of output metrics (with a focus on dynamic flutter stability), for both subsonic and transonic Mach numbers, for two different CFD mesh refinements. A particular focus is placed on computing failure probabilities: the probability that the wing will flutter within the flight envelope.

Transistor analogs of emergent iono-neuronal dynamics.

PubMed

Rachmuth, Guy; Poon, Chi-Sang

2008-06-01

Neuromorphic analog metal-oxide-silicon (MOS) transistor circuits promise compact, low-power, and high-speed emulations of iono-neuronal dynamics orders-of-magnitude faster than digital simulation. However, their inherently limited input voltage dynamic range vs power consumption and silicon die area tradeoffs makes them highly sensitive to transistor mismatch due to fabrication inaccuracy, device noise, and other nonidealities. This limitation precludes robust analog very-large-scale-integration (aVLSI) circuits implementation of emergent iono-neuronal dynamics computations beyond simple spiking with limited ion channel dynamics. Here we present versatile neuromorphic analog building-block circuits that afford near-maximum voltage dynamic range operating within the low-power MOS transistor weak-inversion regime which is ideal for aVLSI implementation or implantable biomimetic device applications. The fabricated microchip allowed robust realization of dynamic iono-neuronal computations such as coincidence detection of presynaptic spikes or pre- and postsynaptic activities. As a critical performance benchmark, the high-speed and highly interactive iono-neuronal simulation capability on-chip enabled our prompt discovery of a minimal model of chaotic pacemaker bursting, an emergent iono-neuronal behavior of fundamental biological significance which has hitherto defied experimental testing or computational exploration via conventional digital or analog simulations. These compact and power-efficient transistor analogs of emergent iono-neuronal dynamics open new avenues for next-generation neuromorphic, neuroprosthetic, and brain-machine interface applications.

Linking dynamics of the inhibitory network to the input structure

PubMed Central

Komarov, Maxim

2017-01-01

Networks of inhibitory interneurons are found in many distinct classes of biological systems. Inhibitory interneurons govern the dynamics of principal cells and are likely to be critically involved in the coding of information. In this theoretical study, we describe the dynamics of a generic inhibitory network in terms of low-dimensional, simplified rate models. We study the relationship between the structure of external input applied to the network and the patterns of activity arising in response to that stimulation. We found that even a minimal inhibitory network can generate a great diversity of spatio-temporal patterning including complex bursting regimes with non-trivial ratios of burst firing. Despite the complexity of these dynamics, the network’s response patterns can be predicted from the rankings of the magnitudes of external inputs to the inhibitory neurons. This type of invariant dynamics is robust to noise and stable in densely connected networks with strong inhibitory coupling. Our study predicts that the response dynamics generated by an inhibitory network may provide critical insights about the temporal structure of the sensory input it receives. PMID:27650865

Dealing with uncertainty in modeling intermittent water supply

NASA Astrophysics Data System (ADS)

Lieb, A. M.; Rycroft, C.; Wilkening, J.

2015-12-01

Intermittency in urban water supply affects hundreds of millions of people in cities around the world, impacting water quality and infrastructure. Building on previous work to dynamically model the transient flows in water distribution networks undergoing frequent filling and emptying, we now consider the hydraulic implications of uncertain input data. Water distribution networks undergoing intermittent supply are often poorly mapped, and household metering frequently ranges from patchy to nonexistent. In the face of uncertain pipe material, pipe slope, network connectivity, and outflow, we investigate how uncertainty affects dynamical modeling results. We furthermore identify which parameters exert the greatest influence on uncertainty, helping to prioritize data collection.

Dynamics and Embedded Internet of Things Input Shaping Control for Overhead Cranes Transporting Multibody Payloads.

PubMed

Peláez, Gerardo; Vaugan, Joshua; Izquierdo, Pablo; Rubio, Higinio; García-Prada, Juan Carlos

2018-06-04

Input shaping is an Optimal Control feedforward strategy whose ability to define how and when a flexible dynamical system defined by Ordinary Differential Equations (ODEs) and computer controlled would move into its operative space, without command induced unwanted dynamics, has been exhaustively demonstrated. This work examines the issue of Embedded Internet of Things (IoT) Input Shaping with regard to real time control of multibody oscillatory systems whose dynamics are better described by differential algebraic equations (DAEs). An overhead crane hanging a double link multibody payload has been appointed as a benchmark case; it is a multibody, multimode system. This might be worst scenario to implement Input Shaping. The reasons can be found in the wide array of constraints that arise. Firstly, the reliability of the multibody model was tested on a Functional Mock-Up Interface (FMI) with the two link payload suspended from the trolley by comparing the experimental video tapping signals in time domain faced with the signals extracted from the multibody model. The FFTs of the simulated and the experimental signal contain the same frequency harmonics only with somewhat different power due to the real world light damping in the joints. The application of this approach may be extended to other cases i.e., the usefulness of mobile hydraulic cranes is limited because the payload is supported by an overhead cable under tension that allows oscillation to occur during crane motion. If the payload size is not negligible small when compared with the cable length may introduce an additional oscillatory mode that creates a multibody double pendulum. To give the insight into the double pendulum dynamics by Lagrangian methods two slender rods as payloads are analyzed dealing with the overhead crane and a composite revolute-revolute joint is proposed to model the cable of the hydraulic crane, both assumptions facilitates an affordable analysis. This allows developing a general study of this type of multibody payloads dynamics including its normal modes, modes ratios plus ranges of frequencies expected. Input Shapers were calculated for those multimodes of vibration by convolving Specified Insensitivity (SI) shapers for each mode plus a novel Direct SI-SI shaper well suited to reduce the computational requirements, i.e., the number of the shaper taps, to carry out the convolution sum in real time by the IoT device based on a single microcontroller working as the command generator. Several comparisons are presented for the shaped and unshaped responses using both the multibody model, the experimental FMI set-up and finally a real world hydraulic crane under slewing motion commanded by an analog Joystick connected by two RF modules 802.15.4 to the IoT device that carry out the convolution sum in real time. Input Shaping improves the performances for all the cases.

Direct energy inputs to the middle atmosphere

NASA Technical Reports Server (NTRS)

Rosenberg, T. J.; Lanzerotti, L. J.

1979-01-01

As a working definition of the extent of the middle atmosphere (MA), the height range from 30 to 100 km was adopted. The neutral and ionic composition and the dynamics within this height range are, for the most part, poorly understood. From available information, the importance of various particle and photon energy sources, including their variability, for ionization of the neutral atmosphere in this height range is assessed. The following topics are discussed: (1) penetration of the MA by particle and electromagnetic energy; (2) ionization sources for the MA; (3) galactic cosmic rays; (4) solar H Ly alpha, other EUV, and X-rays; (5) magnetospheric electrons and bremsstrahlung X-rays; and (6) solar cosmic rays.

Soil organic carbon dynamics jointly controlled by climate, carbon inputs, soil properties and soil carbon fractions.

PubMed

Luo, Zhongkui; Feng, Wenting; Luo, Yiqi; Baldock, Jeff; Wang, Enli

2017-10-01

Soil organic carbon (SOC) dynamics are regulated by the complex interplay of climatic, edaphic and biotic conditions. However, the interrelation of SOC and these drivers and their potential connection networks are rarely assessed quantitatively. Using observations of SOC dynamics with detailed soil properties from 90 field trials at 28 sites under different agroecosystems across the Australian cropping regions, we investigated the direct and indirect effects of climate, soil properties, carbon (C) inputs and soil C pools (a total of 17 variables) on SOC change rate (r C , Mg C ha -1  yr -1 ). Among these variables, we found that the most influential variables on r C were the average C input amount and annual precipitation, and the total SOC stock at the beginning of the trials. Overall, C inputs (including C input amount and pasture frequency in the crop rotation system) accounted for 27% of the relative influence on r C , followed by climate 25% (including precipitation and temperature), soil C pools 24% (including pool size and composition) and soil properties (such as cation exchange capacity, clay content, bulk density) 24%. Path analysis identified a network of intercorrelations of climate, soil properties, C inputs and soil C pools in determining r C . The direct correlation of r C with climate was significantly weakened if removing the effects of soil properties and C pools, and vice versa. These results reveal the relative importance of climate, soil properties, C inputs and C pools and their complex interconnections in regulating SOC dynamics. Ignorance of the impact of changes in soil properties, C pool composition and C input (quantity and quality) on SOC dynamics is likely one of the main sources of uncertainty in SOC predictions from the process-based SOC models. © 2017 John Wiley & Sons Ltd.

Light use efficiency of California redwood forest understory plants along a moisture gradient.

PubMed

Santiago, Louis S; Dawson, Todd E

2014-02-01

We investigated photosynthesis of five plant species growing in the understory at three sites (1,170-, 1,600- and 2,100-mm annual moisture inputs), along the geographical range of coastal California redwood forest, to determine whether greater inputs of rain and fog at northern sites enhance photosynthetic utilization of fluctuating light. Measurements of understory light environment and gas exchange were carried out to determine steady state and dynamic photosynthetic responses to light. Leaf area index ranged from 4.84 at the 2,100-mm site to 5.98 at the 1,170-mm site. Maximum rates of net photosynthesis and stomatal conductance (g) did not vary appreciably within species across sites. Photosynthetic induction after a change from low to high light was significantly greater in plants growing in lower light conditions regardless of site. Photosynthetic induction also increased with the rate of g in diffuse light, prior to the increase to saturating light levels. Post-illumination CO2 assimilation was the largest factor contributing to variation in C gain during simulated lightflecks. The duration of post-illumination photosynthetic activity, total CO2 assimilation per light received, and light use efficiency during simulated lightflecks increased significantly with moisture inputs in four out of five species. Increasing leaf N concentration with increasing moisture inputs in three out of five species, coupled with changes in leaf N isotopic composition with the onset of the summer fog season suggest that natural N deposition increases with rain and fog inputs and contributes to greater utilization of fluctuating light availability in coastal California redwood forests.

Design of a Programmable Gain, Temperature Compensated Current-Input Current-Output CMOS Logarithmic Amplifier.

PubMed

Ming Gu; Chakrabartty, Shantanu

2014-06-01

This paper presents the design of a programmable gain, temperature compensated, current-mode CMOS logarithmic amplifier that can be used for biomedical signal processing. Unlike conventional logarithmic amplifiers that use a transimpedance technique to generate a voltage signal as a logarithmic function of the input current, the proposed approach directly produces a current output as a logarithmic function of the input current. Also, unlike a conventional transimpedance amplifier the gain of the proposed logarithmic amplifier can be programmed using floating-gate trimming circuits. The synthesis of the proposed circuit is based on the Hart's extended translinear principle which involves embedding a floating-voltage source and a linear resistive element within a translinear loop. Temperature compensation is then achieved using a translinear-based resistive cancelation technique. Measured results from prototypes fabricated in a 0.5 μm CMOS process show that the amplifier has an input dynamic range of 120 dB and a temperature sensitivity of 230 ppm/°C (27 °C- 57°C), while consuming less than 100 nW of power.

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.

Legacy nutrient dynamics and patterns of catchment response under changing land use and management

NASA Astrophysics Data System (ADS)

Attinger, S.; Van, M. K.; Basu, N. B.

2017-12-01

Watersheds are complex heterogeneous systems that store, transform, and release water and nutrients under a broad distribution of both natural and anthropogenic controls. Many current watershed models, from complex numerical models to simpler reservoir-type models, are considered to be well-developed in their ability to predict fluxes of water and nutrients to streams and groundwater. They are generally less adept, however, at capturing watershed storage dynamics. In other words, many current models are run with an assumption of steady-state dynamics, and focus on nutrient flows rather than changes in nutrient stocks within watersheds. Although these commonly used modeling approaches may be able to adequately capture short-term watershed dynamics, they are unable to represent the clear nonlinearities or hysteresis responses observed in watersheds experiencing significant changes in nutrient inputs. To address such a lack, we have, in the present work, developed a parsimonious modeling approach designed to capture long-term catchment responses to spatial and temporal changes in nutrient inputs. In this approach, we conceptualize the catchment as a biogeochemical reactor that is driven by nutrient inputs, characterized internally by both biogeochemical degradation and residence or travel time distributions, resulting in a specific nutrient output. For the model simulations, we define a range of different scenarios to represent real-world changes in land use and management implemented to improve water quality. We then introduce the concept of state-space trajectories to describe system responses to these potential changes in anthropogenic forcings. We also increase model complexity, in a stepwise fashion, by dividing the catchment into multiple biogeochemical reactors, coupled in series or in parallel. Using this approach, we attempt to answer the following questions: (1) What level of model complexity is needed to capture observed system responses? (2) How can we explain different patterns of nonlinearity in watershed nutrient dynamics? And finally, how does the accumulation of nutrient legacies within watersheds impact current and future water quality?

Characteristic of a Digital Correlation Radiometer Back End with Finite Wordlength

NASA Technical Reports Server (NTRS)

Biswas, Sayak K.; Hyde, David W.; James, Mark W.; Cecil, Daniel J.

2017-01-01

The performance characteristic of a digital correlation radiometer signal processing back end (DBE) is analyzed using a simulator. The particular design studied here corresponds to the airborne Hurricane Imaging radiometer which was jointly developed by the NASA Marshall Space Flight Center, University of Michigan, University of Central Florida and NOAA. Laboratory and flight test data is found to be in accord with the simulation results. Overall design seems to be optimum for the typical input signal dynamic range. It was found that the performance of the digital kurtosis could be improved by lowering the DBE input power level. An unusual scaling between digital correlation channels observed in the instrument data is confirmed to be a DBE characteristic.

Deconvolution of time series in the laboratory

NASA Astrophysics Data System (ADS)

John, Thomas; Pietschmann, Dirk; Becker, Volker; Wagner, Christian

2016-10-01

In this study, we present two practical applications of the deconvolution of time series in Fourier space. First, we reconstruct a filtered input signal of sound cards that has been heavily distorted by a built-in high-pass filter using a software approach. Using deconvolution, we can partially bypass the filter and extend the dynamic frequency range by two orders of magnitude. Second, we construct required input signals for a mechanical shaker in order to obtain arbitrary acceleration waveforms, referred to as feedforward control. For both situations, experimental and theoretical approaches are discussed to determine the system-dependent frequency response. Moreover, for the shaker, we propose a simple feedback loop as an extension to the feedforward control in order to handle nonlinearities of the system.

Evidence for Dynamic Network Regulation of Drosophila Photoreceptor Function from Mutants Lacking the Neurotransmitter Histamine

PubMed Central

Dau, An; Friederich, Uwe; Dongre, Sidhartha; Li, Xiaofeng; Bollepalli, Murali K.; Hardie, Roger C.; Juusola, Mikko

2016-01-01

Synaptic feedback from interneurons to photoreceptors can help to optimize visual information flow by balancing its allocation on retinal pathways under changing light conditions. But little is known about how this critical network operation is regulated dynamically. Here, we investigate this question by comparing signaling properties and performance of wild-type Drosophila R1–R6 photoreceptors to those of the hdcJK910 mutant, which lacks the neurotransmitter histamine and therefore cannot transmit information to interneurons. Recordings show that hdcJK910 photoreceptors sample similar amounts of information from naturalistic stimulation to wild-type photoreceptors, but this information is packaged in smaller responses, especially under bright illumination. Analyses reveal how these altered dynamics primarily resulted from network overload that affected hdcJK910 photoreceptors in two ways. First, the missing inhibitory histamine input to interneurons almost certainly depolarized them irrevocably, which in turn increased their excitatory feedback to hdcJK910 R1–R6s. This tonic excitation depolarized the photoreceptors to artificially high potentials, reducing their operational range. Second, rescuing histamine input to interneurons in hdcJK910 mutant also restored their normal phasic feedback modulation to R1–R6s, causing photoreceptor output to accentuate dynamic intensity differences at bright illumination, similar to the wild-type. These results provide mechanistic explanations of how synaptic feedback connections optimize information packaging in photoreceptor output and novel insight into the operation and design of dynamic network regulation of sensory neurons. PMID:27047343

Unsupervised segmentation with dynamical units.

PubMed

Rao, A Ravishankar; Cecchi, Guillermo A; Peck, Charles C; Kozloski, James R

2008-01-01

In this paper, we present a novel network to separate mixtures of inputs that have been previously learned. A significant capability of the network is that it segments the components of each input object that most contribute to its classification. The network consists of amplitude-phase units that can synchronize their dynamics, so that separation is determined by the amplitude of units in an output layer, and segmentation by phase similarity between input and output layer units. Learning is unsupervised and based on a Hebbian update, and the architecture is very simple. Moreover, efficient segmentation can be achieved even when there is considerable superposition of the inputs. The network dynamics are derived from an objective function that rewards sparse coding in the generalized amplitude-phase variables. We argue that this objective function can provide a possible formal interpretation of the binding problem and that the implementation of the network architecture and dynamics is biologically plausible.

Characterization of noncontact piezoelectric transducer with conically shaped piezoelement

NASA Technical Reports Server (NTRS)

Williams, James H., Jr.; Ochi, Simeon C. U.

1988-01-01

The characterization of a dynamic surface displacement transducer (IQI Model 501) by a noncontact method is presented. The transducer is designed for ultrasonic as well as acoustic emission measurements and, according to the manufacturer, its characteristic features include a flat frequency response range which is from 50 to 1000 kHz and a quality factor Q of less than unity. The characterization is based on the behavior of the transducer as a receiver and involves exciting the transducer directly by transient pulse input stress signals of quasi-electrostatic origin and observing its response in a digital storage oscilloscope. Theoretical models for studying the response of the transducer to pulse input stress signals and for generating pulse stress signals are presented. The characteristic features of the transducer which include the central frequency f sub o, quality factor Q, and flat frequency response range are obtained by this noncontact characterization technique and they compare favorably with those obtained by a tone burst method which are also presented.

Real-Time Adaptive Control of Flow-Induced Cavity Tones

NASA Technical Reports Server (NTRS)

Kegerise, Michael A.; Cabell, Randolph H.; Cattafesta, Louis N.

2004-01-01

An adaptive generalized predictive control (GPC) algorithm was formulated and applied to the cavity flow-tone problem. The algorithm employs gradient descent to update the GPC coefficients at each time step. The adaptive control algorithm demonstrated multiple Rossiter mode suppression at fixed Mach numbers ranging from 0.275 to 0.38. The algorithm was also able t o maintain suppression of multiple cavity tones as the freestream Mach number was varied over a modest range (0.275 to 0.29). Controller performance was evaluated with a measure of output disturbance rejection and an input sensitivity transfer function. The results suggest that disturbances entering the cavity flow are colocated with the control input at the cavity leading edge. In that case, only tonal components of the cavity wall-pressure fluctuations can be suppressed and arbitrary broadband pressure reduction is not possible. In the control-algorithm development, the cavity dynamics are treated as linear and time invariant (LTI) for a fixed Mach number. The experimental results lend support this treatment.

Singularity perturbed zero dynamics of nonlinear systems

NASA Technical Reports Server (NTRS)

Isidori, A.; Sastry, S. S.; Kokotovic, P. V.; Byrnes, C. I.

1992-01-01

Stability properties of zero dynamics are among the crucial input-output properties of both linear and nonlinear systems. Unstable, or 'nonminimum phase', zero dynamics are a major obstacle to input-output linearization and high-gain designs. An analysis of the effects of regular perturbations in system equations on zero dynamics shows that whenever a perturbation decreases the system's relative degree, it manifests itself as a singular perturbation of zero dynamics. Conditions are given under which the zero dynamics evolve in two timescales characteristic of a standard singular perturbation form that allows a separate analysis of slow and fast parts of the zero dynamics.

Information encoder/decoder using chaotic systems

DOEpatents

Miller, Samuel Lee; Miller, William Michael; McWhorter, Paul Jackson

1997-01-01

The present invention discloses a chaotic system-based information encoder and decoder that operates according to a relationship defining a chaotic system. Encoder input signals modify the dynamics of the chaotic system comprising the encoder. The modifications result in chaotic, encoder output signals that contain the encoder input signals encoded within them. The encoder output signals are then capable of secure transmissions using conventional transmission techniques. A decoder receives the encoder output signals (i.e., decoder input signals) and inverts the dynamics of the encoding system to directly reconstruct the original encoder input signals.

Information encoder/decoder using chaotic systems

DOEpatents

Miller, S.L.; Miller, W.M.; McWhorter, P.J.

1997-10-21

The present invention discloses a chaotic system-based information encoder and decoder that operates according to a relationship defining a chaotic system. Encoder input signals modify the dynamics of the chaotic system comprising the encoder. The modifications result in chaotic, encoder output signals that contain the encoder input signals encoded within them. The encoder output signals are then capable of secure transmissions using conventional transmission techniques. A decoder receives the encoder output signals (i.e., decoder input signals) and inverts the dynamics of the encoding system to directly reconstruct the original encoder input signals. 32 figs.

Spike threshold dynamics in spinal motoneurons during scratching and swimming.

PubMed

Grigonis, Ramunas; Alaburda, Aidas

2017-09-01

Action potential threshold can vary depending on firing history and synaptic inputs. We used an ex vivo carapace-spinal cord preparation from adult turtles to study spike threshold dynamics in motoneurons during two distinct types of functional motor behaviour - fictive scratching and fictive swimming. The threshold potential depolarizes by about 10 mV within each burst of spikes generated during scratch and swim network activity and recovers between bursts to a slightly depolarized level. Slow synaptic integration resulting in a wave of membrane potential depolarization is the factor influencing the threshold potential within firing bursts during motor behaviours. Depolarization of the threshold potential decreases the excitability of motoneurons and may provide a mechanism for stabilization of the response of a motoneuron to intense synaptic inputs to maintain the motor commands within an optimal range for muscle activation. During functional spinal neural network activity motoneurons receive intense synaptic input, and this could modulate the threshold for action potential generation, providing the ability to dynamically adjust the excitability and recruitment order for functional needs. In the present study we investigated the dynamics of action potential threshold during motor network activity. Intracellular recordings from spinal motoneurons in an ex vivo carapace-spinal cord preparation from adult turtles were performed during two distinct types of motor behaviour - fictive scratching and fictive swimming. We found that the threshold of the first spike in episodes of scratching and swimming was the lowest. The threshold potential depolarizes by about 10 mV within each burst of spikes generated during scratch and swim network activity and recovers between bursts to a slightly depolarized level. Depolarization of the threshold potential results in decreased excitability of motoneurons. Synaptic inputs do not modulate the threshold of the first action potential during episodes of scratching or of swimming. There is no correlation between changes in spike threshold and interspike intervals within bursts. Slow synaptic integration that results in a wave of membrane potential depolarization rather than fast synaptic events preceding each spike is the factor influencing the threshold potential within firing bursts during motor behaviours. © 2017 The Authors. The Journal of Physiology © 2017 The Physiological Society.

Performance comparison for Barnes model 12-1000, Exotech model 100, and Ideas Inc. Biometer Mark 2

NASA Technical Reports Server (NTRS)

Robinson, B. (Principal Investigator)

1981-01-01

Results of tests show that all channels of all instruments, except channel 3 of the Biometer Mark 2, were stable in response to input signals were linear, and were adequately stable in response to temperature changes. The Biometer Mark 2 is labelled with an inappropriate description of the units measured and the dynamic range is a inappropriate for field measurements causing unnecessarily high fractional errors. This instrument is, therefore, quantization limited. The dynamic range and noise performance of the Model 12-1000 are appropriate for remote sensing field research. The field of view and performance of the Model 100A and the Model 12-1000 are satisfactory. The Biometer Mark 2 has not, as yet, been satisfactorily equipped with an acceptable field of view determining device. Neither the widely used aperture plate nor the 24 deg cone are acceptable.

Analysis of transistor and snubber turn-off dynamics in high-frequency high-voltage high-power converters

NASA Technical Reports Server (NTRS)

Wilson, P. M.; Wilson, T. G.; Owen, H. A., Jr.

1982-01-01

Dc to dc converters which operate reliably and efficiently at switching frequencies high enough to effect substantial reductions in the size and weight of converter energy storage elements are studied. A two winding current or voltage stepup (buck boost) dc-to-dc converter power stage submodule designed to operate in the 2.5-kW range, with an input voltage range of 110 to 180 V dc, and an output voltage of 250 V dc is emphasized. In order to assess the limitations of present day component and circuit technologies, a design goal switching frequency of 10 kHz was maintained. The converter design requirements represent a unique combination of high frequency, high voltage, and high power operation. The turn off dynamics of the primary circuit power switching transistor and its associated turn off snubber circuitry are investigated.

Analysis of transistor and snubber turn-off dynamics in high-frequency high-voltage high-power converters

NASA Astrophysics Data System (ADS)

Wilson, P. M.; Wilson, T. G.; Owen, H. A., Jr.

Dc to dc converters which operate reliably and efficiently at switching frequencies high enough to effect substantial reductions in the size and weight of converter energy storage elements are studied. A two winding current or voltage stepup (buck boost) dc-to-dc converter power stage submodule designed to operate in the 2.5-kW range, with an input voltage range of 110 to 180 V dc, and an output voltage of 250 V dc is emphasized. In order to assess the limitations of present day component and circuit technologies, a design goal switching frequency of 10 kHz was maintained. The converter design requirements represent a unique combination of high frequency, high voltage, and high power operation. The turn off dynamics of the primary circuit power switching transistor and its associated turn off snubber circuitry are investigated.

Piezoelectric tunable microwave superconducting cavity

NASA Astrophysics Data System (ADS)

Carvalho, N. C.; Fan, Y.; Tobar, M. E.

2016-09-01

In the context of engineered quantum systems, there is a demand for superconducting tunable devices, able to operate with high-quality factors at power levels equivalent to only a few photons. In this work, we developed a 3D microwave re-entrant cavity with such characteristics ready to provide a very fine-tuning of a high-Q resonant mode over a large dynamic range. This system has an electronic tuning mechanism based on a mechanically amplified piezoelectric actuator, which controls the resonator dominant mode frequency by changing the cavity narrow gap by very small displacements. Experiments were conducted at room and dilution refrigerator temperatures showing a large dynamic range up to 4 GHz and 1 GHz, respectively, and were compared to a finite element method model simulated data. At elevated microwave power input, nonlinear thermal effects were observed to destroy the superconductivity of the cavity due to the large electric fields generated in the small gap of the re-entrant cavity.

Active Sensor for Microwave Tissue Imaging with Bias-Switched Arrays.

PubMed

Foroutan, Farzad; Nikolova, Natalia K

2018-05-06

A prototype of a bias-switched active sensor was developed and measured to establish the achievable dynamic range in a new generation of active arrays for microwave tissue imaging. The sensor integrates a printed slot antenna, a low-noise amplifier (LNA) and an active mixer in a single unit, which is sufficiently small to enable inter-sensor separation distance as small as 12 mm. The sensor’s input covers the bandwidth from 3 GHz to 7.5 GHz. Its output intermediate frequency (IF) is 30 MHz. The sensor is controlled by a simple bias-switching circuit, which switches ON and OFF the bias of the LNA and the mixer simultaneously. It was demonstrated experimentally that the dynamic range of the sensor, as determined by its ON and OFF states, is 109 dB and 118 dB at resolution bandwidths of 1 kHz and 100 Hz, respectively.

Data compression of discrete sequence: A tree based approach using dynamic programming

NASA Technical Reports Server (NTRS)

Shivaram, Gurusrasad; Seetharaman, Guna; Rao, T. R. N.

1994-01-01

A dynamic programming based approach for data compression of a ID sequence is presented. The compression of an input sequence of size N to that of a smaller size k is achieved by dividing the input sequence into k subsequences and replacing the subsequences by their respective average values. The partitioning of the input sequence is carried with the intention of reducing the mean squared error in the reconstructed sequence. The complexity involved in finding the partitions which would result in such an optimal compressed sequence is reduced by using the dynamic programming approach, which is presented.

Vulnerability of dynamic systems

NASA Technical Reports Server (NTRS)

Siljak, D. D.

1976-01-01

Directed graphs are associated with dynamic systems in order to determine in any given system if each state can be reached by at least one input (input reachability), or can each state reach at least one output (output reachability). Then, the structural perturbations of a dynamic system are identified as lines or points removals from the corresponding digraph, and a system is considered vulnerable at those lines or points of the digraph whose removal destroys its input or output reachability. A suitable framework is formulated for resolving the problems of reachability and vulnerability which applies to both linear and nonlinear systems alike.

Ensemble Kalman Filter for Dynamic State Estimation of Power Grids Stochastically Driven by Time-correlated Mechanical Input Power

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

Rosenthal, William Steven; Tartakovsky, Alex; Huang, Zhenyu

State and parameter estimation of power transmission networks is important for monitoring power grid operating conditions and analyzing transient stability. Wind power generation depends on fluctuating input power levels, which are correlated in time and contribute to uncertainty in turbine dynamical models. The ensemble Kalman filter (EnKF), a standard state estimation technique, uses a deterministic forecast and does not explicitly model time-correlated noise in parameters such as mechanical input power. However, this uncertainty affects the probability of fault-induced transient instability and increased prediction bias. Here a novel approach is to model input power noise with time-correlated stochastic fluctuations, and integratemore » them with the network dynamics during the forecast. While the EnKF has been used to calibrate constant parameters in turbine dynamical models, the calibration of a statistical model for a time-correlated parameter has not been investigated. In this study, twin experiments on a standard transmission network test case are used to validate our time-correlated noise model framework for state estimation of unsteady operating conditions and transient stability analysis, and a methodology is proposed for the inference of the mechanical input power time-correlation length parameter using time-series data from PMUs monitoring power dynamics at generator buses.« less

Ensemble Kalman Filter for Dynamic State Estimation of Power Grids Stochastically Driven by Time-correlated Mechanical Input Power

DOE PAGES

Rosenthal, William Steven; Tartakovsky, Alex; Huang, Zhenyu

2017-10-31

State and parameter estimation of power transmission networks is important for monitoring power grid operating conditions and analyzing transient stability. Wind power generation depends on fluctuating input power levels, which are correlated in time and contribute to uncertainty in turbine dynamical models. The ensemble Kalman filter (EnKF), a standard state estimation technique, uses a deterministic forecast and does not explicitly model time-correlated noise in parameters such as mechanical input power. However, this uncertainty affects the probability of fault-induced transient instability and increased prediction bias. Here a novel approach is to model input power noise with time-correlated stochastic fluctuations, and integratemore » them with the network dynamics during the forecast. While the EnKF has been used to calibrate constant parameters in turbine dynamical models, the calibration of a statistical model for a time-correlated parameter has not been investigated. In this study, twin experiments on a standard transmission network test case are used to validate our time-correlated noise model framework for state estimation of unsteady operating conditions and transient stability analysis, and a methodology is proposed for the inference of the mechanical input power time-correlation length parameter using time-series data from PMUs monitoring power dynamics at generator buses.« less

Optical Data Processing for Missile Guidance.

DTIC Science & Technology

1981-10-01

CORRELATORS The dynamic range of a digital system is well-known to be large. But moreso , these sys- tems can handle low modulation data by proper...nor (4). Rather, it is similar to (4), but with a lower bias level b than the one present in the original imagery of (1). Moreso , the t(x) input is...they are unisensor moreso than multisensor data. In such cases, HPF preprocessing will degrade the output correlation as noted in (5]. Thus, both cases

Model-free iterative control of repetitive dynamics for high-speed scanning in atomic force microscopy.

PubMed

Li, Yang; Bechhoefer, John

2009-01-01

We introduce an algorithm for calculating, offline or in real time and with no explicit system characterization, the feedforward input required for repetitive motions of a system. The algorithm is based on the secant method of numerical analysis and gives accurate motion at frequencies limited only by the signal-to-noise ratio and the actuator power and range. We illustrate the secant-solver algorithm on a stage used for atomic force microscopy.

Investigation and optimization of low-frequency noise performance in readout electronics of dc superconducting quantum interference device

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

Zhao, Jing; Peter Grünberg Institute; Zhang, Yi

2014-05-15

We investigated and optimized the low-frequency noise characteristics of a preamplifier used for readout of direct current superconducting quantum interference devices (SQUIDs). When the SQUID output was detected directly using a room-temperature low-voltage-noise preamplifier, the low-frequency noise of a SQUID system was found to be dominated by the input current noise of the preamplifiers in case of a large dynamic resistance of the SQUID. To reduce the current noise of the preamplifier in the low-frequency range, we investigated the dependence of total preamplifier noise on the collector current and source resistance. When the collector current was decreased from 8.4 mAmore » to 3 mA in the preamplifier made of 3 parallel SSM2220 transistor pairs, the low-frequency total voltage noise of the preamplifier (at 0.1 Hz) decreased by about 3 times for a source resistance of 30 Ω whereas the white noise level remained nearly unchanged. Since the relative contribution of preamplifier's input voltage and current noise is different depending on the dynamic resistance or flux-to-voltage transfer of the SQUID, the results showed that the total noise of a SQUID system at low-frequency range can be improved significantly by optimizing the preamplifier circuit parameters, mainly the collector current in case of low-noise bipolar transistor pairs.« less

Investigation and optimization of low-frequency noise performance in readout electronics of dc superconducting quantum interference device

NASA Astrophysics Data System (ADS)

Zhao, Jing; Zhang, Yi; Lee, Yong-Ho; Krause, Hans-Joachim

2014-05-01

We investigated and optimized the low-frequency noise characteristics of a preamplifier used for readout of direct current superconducting quantum interference devices (SQUIDs). When the SQUID output was detected directly using a room-temperature low-voltage-noise preamplifier, the low-frequency noise of a SQUID system was found to be dominated by the input current noise of the preamplifiers in case of a large dynamic resistance of the SQUID. To reduce the current noise of the preamplifier in the low-frequency range, we investigated the dependence of total preamplifier noise on the collector current and source resistance. When the collector current was decreased from 8.4 mA to 3 mA in the preamplifier made of 3 parallel SSM2220 transistor pairs, the low-frequency total voltage noise of the preamplifier (at 0.1 Hz) decreased by about 3 times for a source resistance of 30 Ω whereas the white noise level remained nearly unchanged. Since the relative contribution of preamplifier's input voltage and current noise is different depending on the dynamic resistance or flux-to-voltage transfer of the SQUID, the results showed that the total noise of a SQUID system at low-frequency range can be improved significantly by optimizing the preamplifier circuit parameters, mainly the collector current in case of low-noise bipolar transistor pairs.

Robust Crossfeed Design for Hovering Rotorcraft

NASA Technical Reports Server (NTRS)

Catapang, David R.

1993-01-01

Control law design for rotorcraft fly-by-wire systems normally attempts to decouple angular responses using fixed-gain crossfeeds. This approach can lead to poor decoupling over the frequency range of pilot inputs and increase the load on the feedback loops. In order to improve the decoupling performance, dynamic crossfeeds may be adopted. Moreover, because of the large changes that occur in rotorcraft dynamics due to small changes about the nominal design condition, especially for near-hovering flight, the crossfeed design must be 'robust'. A new low-order matching method is presented here to design robust crossfeed compensators for multi-input, multi-output (MIMO) systems. The technique identifies degrees-of-freedom that can be decoupled using crossfeeds, given an anticipated set of parameter variations for the range of flight conditions of concern. Cross-coupling is then reduced for degrees-of-freedom that can use crossfeed compensation by minimizing off-axis response magnitude average and variance. Results are presented for the analysis of pitch, roll, yaw and heave coupling of the UH-60 Black Hawk helicopter in near-hovering flight. Robust crossfeeds are designed that show significant improvement in decoupling performance and robustness over nominal, single design point, compensators. The design method and results are presented in an easily used graphical format that lends significant physical insight to the design procedure. This plant pre-compensation technique is an appropriate preliminary step to the design of robust feedback control laws for rotorcraft.

Numeric Design and Performance Analysis of Solid Oxide Fuel Cell -- Gas Turbine Hybrids on Aircraft

NASA Astrophysics Data System (ADS)

Hovakimyan, Gevorg

The aircraft industry benefits greatly from small improvements in aircraft component design. One possible area of improvement is in the Auxiliary Power Unit (APU). Modern aircraft APUs are gas turbines located in the tail section of the aircraft that generate additional power when needed. Unfortunately the efficiency of modern aircraft APUs is low. Solid Oxide Fuel Cell/Gas Turbine (SOFC/GT) hybrids are one possible alternative for replacing modern gas turbine APUs. This thesis investigates the feasibility of replacing conventional gas turbine APUs with SOFC/GT APUs on aircraft. An SOFC/GT design algorithm was created in order to determine the specifications of an SOFC/GT APU. The design algorithm is comprised of several integrated modules which together model the characteristics of each component of the SOFC/GT system. Given certain overall inputs, through numerical analysis, the algorithm produces an SOFC/GT APU, optimized for specific power and efficiency, capable of performing to the required specifications. The SOFC/GT design is then input into a previously developed quasi-dynamic SOFC/GT model to determine its load following capabilities over an aircraft flight cycle. Finally an aircraft range study is conducted to determine the feasibility of the SOFC/GT APU as a replacement for the conventional gas turbine APU. The design results show that SOFC/GT APUs have lower specific power than GT systems, but have much higher efficiencies. Moreover, the dynamic simulation results show that SOFC/GT APUs are capable of following modern flight loads. Finally, the range study determined that SOFC/GT APUs are more attractive over conventional APUs for longer range aircraft.

A Froude-scaled model of a bedrock-alluvial channel reach: 2. Sediment cover

NASA Astrophysics Data System (ADS)

Hodge, Rebecca A.; Hoey, Trevor B.

2016-09-01

Previous research into sediment cover in bedrock-alluvial channels has focussed on total sediment cover, rather than the spatial distribution of cover within the channel. The latter is important because it determines the bedrock areas that are protected from erosion and the start and end of sediment transport pathways. We use a 1:10 Froude-scaled model of an 18 by 9 m reach of a bedrock-alluvial channel to study the production and erosion of sediment patches and hence the spatial relationships between flow, bed topography, and sediment dynamics. The hydraulic data from this bed are presented in the companion paper. In these experiments specified volumes of sediment were supplied at the upstream edge of the model reach as single inputs, at each of a range of discharges. This sediment formed patches, and once these stabilized, flow was steadily increased to erode the patches. In summary: (1) patches tend to initiate in the lowest areas of the bed, but areas of topographically induced high flow velocity can inhibit patch development; (2) at low sediment inputs the extent of sediment patches is determined by the bed topography and can be insensitive to the exact volume of sediment supplied; and (3) at higher sediment inputs more extensive patches are produced, stabilized by grain-grain and grain-flow interactions and less influenced by the bed topography. Bedrock topography can therefore be an important constraint on sediment patch dynamics, and topographic metrics are required that incorporate its within-reach variability. The magnitude and timing of sediment input events controls reach-scale sediment cover.

Multivariable control of vapor compression systems

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

He, X.D.; Liu, S.; Asada, H.H.

1999-07-01

This paper presents the results of a study of multi-input multi-output (MIMO) control of vapor compression cycles that have multiple actuators and sensors for regulating multiple outputs, e.g., superheat and evaporating temperature. The conventional single-input single-output (SISO) control was shown to have very limited performance. A low order lumped-parameter model was developed to describe the significant dynamics of vapor compression cycles. Dynamic modes were analyzed based on the low order model to provide physical insight of system dynamic behavior. To synthesize a MIMO control system, the Linear-Quadratic Gaussian (LQG) technique was applied to coordinate compressor speed and expansion valve openingmore » with guaranteed stability robustness in the design. Furthermore, to control a vapor compression cycle over a wide range of operating conditions where system nonlinearities become evident, a gain scheduling scheme was used so that the MIMO controller could adapt to changing operating conditions. Both analytical studies and experimental tests showed that the MIMO control could significantly improve the transient behavior of vapor compression cycles compared to the conventional SISO control scheme. The MIMO control proposed in this paper could be extended to the control of vapor compression cycles in a variety of HVAC and refrigeration applications to improve system performance and energy efficiency.« less

Experimental comparison of conventional and nonlinear model-based control of a mixing tank

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

Haeggblom, K.E.

1993-11-01

In this case study concerning control of a laboratory-scale mixing tank, conventional multiloop single-input single-output (SISO) control is compared with model-based'' control where the nonlinearity and multivariable characteristics of the process are explicitly taken into account. It is shown, especially if the operating range of the process is large, that the two outputs (level and temperature) cannot be adequately controlled by multiloop SISO control even if gain scheduling is used. By nonlinear multiple-input multiple-output (MIMO) control, on the other hand, very good control performance is obtained. The basic approach to nonlinear control used in this study is first to transformmore » the process into a globally linear and decoupled system, and then to design controllers for this system. Because of the properties of the resulting MIMO system, the controller design is very easy. Two nonlinear control system designs based on a steady-state and a dynamic model, respectively, are considered. In the dynamic case, both setpoint tracking and disturbance rejection can be addressed separately.« less

Forecasting runout of rock and debris avalanches

USGS Publications Warehouse

Iverson, Richard M.; Evans, S.G.; Mugnozza, G.S.; Strom, A.; Hermanns, R.L.

2006-01-01

Physically based mathematical models and statistically based empirical equations each may provide useful means of forecasting runout of rock and debris avalanches. This paper compares the foundations, strengths, and limitations of a physically based model and a statistically based forecasting method, both of which were developed to predict runout across three-dimensional topography. The chief advantage of the physically based model results from its ties to physical conservation laws and well-tested axioms of soil and rock mechanics, such as the Coulomb friction rule and effective-stress principle. The output of this model provides detailed information about the dynamics of avalanche runout, at the expense of high demands for accurate input data, numerical computation, and experimental testing. In comparison, the statistical method requires relatively modest computation and no input data except identification of prospective avalanche source areas and a range of postulated avalanche volumes. Like the physically based model, the statistical method yields maps of predicted runout, but it provides no information on runout dynamics. Although the two methods differ significantly in their structure and objectives, insights gained from one method can aid refinement of the other.

Integration of a versatile bridge concept in a 34 GHz pulsed/CW EPR spectrometer

NASA Astrophysics Data System (ADS)

Band, Alan; Donohue, Matthew P.; Epel, Boris; Madhu, Shraeya; Szalai, Veronika A.

2018-03-01

We present a 34 GHz continuous wave (CW)/pulsed electron paramagnetic resonance (EPR) spectrometer capable of pulse-shaping that is based on a versatile microwave bridge design. The bridge radio frequency (RF)-in/RF-out design (500 MHz to 1 GHz input/output passband, 500 MHz instantaneous input/output bandwidth) creates a flexible platform with which to compare a variety of excitation and detection methods utilizing commercially available equipment external to the bridge. We use three sources of RF input to implement typical functions associated with CW and pulse EPR spectroscopic measurements. The bridge output is processed via high speed digitizer and an in-phase/quadrature (I/Q) demodulator for pulsed work or sent to a wideband, high dynamic range log detector for CW. Combining this bridge with additional commercial hardware and new acquisition and control electronics, we have designed and constructed an adaptable EPR spectrometer that builds upon previous work in the literature and is functionally comparable to other available systems.

On a low-dimensional model for magnetostriction

NASA Astrophysics Data System (ADS)

Iyer, R. V.; Manservisi, S.

2006-02-01

In recent years, a low-dimensional model for thin magnetostrictive actuators that incorporated magneto-elastic coupling, inertial and damping effects, ferromagnetic hysteresis and classical eddy current losses was developed using energy-balance principles by Venkataraman and Krishnaprasad. This model, with the classical Preisach operator representing the hysteretic constitutive relation between the magnetic field and magnetization in the axial direction, proved to be very successful in capturing dynamic hysteresis effects with electrical inputs in the 0-50 Hz range and constant mechanical loading. However, it is well known that for soft ferromagnetic materials there exist excess losses in addition to the classical eddy current losses. In this work, we propose to extend the above mentioned model for a magnetostrictive rod actuator by including excess losses via a nonlinear resistive element in the actuator circuit. We then show existence and uniqueness of solutions for the proposed model for electrical voltage input in the space L2(0,T)∩L∞(0,T) and mechanical force input in the space L2(0,T).

Variable input observer for state estimation of high-rate dynamics

NASA Astrophysics Data System (ADS)

Hong, Jonathan; Cao, Liang; Laflamme, Simon; Dodson, Jacob

2017-04-01

High-rate systems operating in the 10 μs to 10 ms timescale are likely to experience damaging effects due to rapid environmental changes (e.g., turbulence, ballistic impact). Some of these systems could benefit from real-time state estimation to enable their full potential. Examples of such systems include blast mitigation strategies, automotive airbag technologies, and hypersonic vehicles. Particular challenges in high-rate state estimation include: 1) complex time varying nonlinearities of system (e.g. noise, uncertainty, and disturbance); 2) rapid environmental changes; 3) requirement of high convergence rate. Here, we propose using a Variable Input Observer (VIO) concept to vary the input space as the event unfolds. When systems experience high-rate dynamics, rapid changes in the system occur. To investigate the VIO's potential, a VIO-based neuro-observer is constructed and studied using experimental data collected from a laboratory impact test. Results demonstrate that the input space is unique to different impact conditions, and that adjusting the input space throughout the dynamic event produces better estimations than using a traditional fixed input space strategy.

Convergent properties of vestibular-related brain stem neurons in the gerbil

NASA Technical Reports Server (NTRS)

Kaufman, G. D.; Shinder, M. E.; Perachio, A. A.

2000-01-01

Three classes of vestibular-related neurons were found in and near the prepositus and medial vestibular nuclei of alert or decerebrate gerbils, those responding to: horizontal translational motion, horizontal head rotation, or both. Their distribution ratios were 1:2:2, respectively. Many cells responsive to translational motion exhibited spatiotemporal characteristics with both response gain and phase varying as a function of the stimulus vector angle. Rotationally sensitive neurons were distributed as Type I, II, or III responses (sensitive to ipsilateral, contralateral, or both directions, respectively) in the ratios of 4:6:1. Four tested factors shaped the response dynamics of the sampled neurons: canal-otolith convergence, oculomotor-related activity, rotational Type (I or II), and the phase of the maximum response. Type I nonconvergent cells displayed increasing gains with increasing rotational stimulus frequency (0.1-2.0 Hz, 60 degrees /s), whereas Type II neurons with convergent inputs had response gains that markedly decreased with increasing translational stimulus frequency (0.25-2.0 Hz, +/-0.1 g). Type I convergent and Type II nonconvergent neurons exhibited essentially flat gains across the stimulus frequency range. Oculomotor-related activity was noted in 30% of the cells across all functional types, appearing as burst/pause discharge patterns related to the fast phase of nystagmus during head rotation. Oculomotor-related activity was correlated with enhanced dynamic range compared with the same category that had no oculomotor-related response. Finally, responses that were in-phase with head velocity during rotation exhibited greater gains with stimulus frequency increments than neurons with out-of-phase responses. In contrast, for translational motion, neurons out of phase with head acceleration exhibited low-pass characteristics, whereas in-phase neurons did not. Data from decerebrate preparations revealed that although similar response types could be detected, the sampled cells generally had lower background discharge rates, on average one-third lower response gains, and convergent properties that differed from those found in the alert animals. On the basis of the dynamic response of identified cell types, we propose a pair of models in which inhibitory input from vestibular-related neurons converges on oculomotor neurons with excitatory inputs from the vestibular nuclei. Simple signal convergence and combinations of different types of vestibular labyrinth information can enrich the dynamic characteristics of the rotational and translational vestibuloocular responses.

Intracellular calcium dynamics permit a Purkinje neuron model to perform toggle and gain computations upon its inputs

PubMed Central

Forrest, Michael D.

2014-01-01

Without synaptic input, Purkinje neurons can spontaneously fire in a repeating trimodal pattern that consists of tonic spiking, bursting and quiescence. Climbing fiber input (CF) switches Purkinje neurons out of the trimodal firing pattern and toggles them between a tonic firing and a quiescent state, while setting the gain of their response to Parallel Fiber (PF) input. The basis to this transition is unclear. We investigate it using a biophysical Purkinje cell model under conditions of CF and PF input. The model can replicate these toggle and gain functions, dependent upon a novel account of intracellular calcium dynamics that we hypothesize to be applicable in real Purkinje cells. PMID:25191262

Discrimination of time-dependent inflow properties with a cooperative dynamical system.

PubMed

Ueno, Hiroshi; Tsuruyama, Tatsuaki; Nowakowski, Bogdan; Górecki, Jerzy; Yoshikawa, Kenichi

2015-10-01

Many physical, chemical, and biological systems exhibit a cooperative or sigmoidal response with respect to the input. In biochemistry, such behavior is called an allosteric effect. Here, we demonstrate that a system with such properties can be used to discriminate the amplitude or frequency of an external periodic perturbation. Numerical simulations performed for a model sigmoidal kinetics illustrate that there exists a narrow range of frequencies and amplitudes within which the system evolves toward significantly different states. Therefore, observation of system evolution should provide information about the characteristics of the perturbation. The discrimination properties for periodic perturbation are generic. They can be observed in various dynamical systems and for different types of periodic perturbation.

CFD comparison with centrifugal compressor measurements on a wide operating range

NASA Astrophysics Data System (ADS)

Le Sausse, P.; Fabrie, P.; Arnou, D.; Clunet, F.

2013-04-01

Centrifugal compressors are widely used in industrial applications thanks to their high efficiency. They are able to provide a wide operating range before reaching the flow barrier or surge limits. Performances and range are described by compressor maps obtained experimentally. After a description of performance test rig, this article compares measured centrifugal compressor performances with computational fluid dynamics results. These computations are performed at steady conditions with R134a refrigerant as fluid. Navier-Stokes equations, coupled with k-ɛ turbulence model, are solved by the commercial software ANSYS-CFX by means of volume finite method. Input conditions are varied in order to calculate several speed lines. Theoretical isentropic efficiency and theoretical surge line are finally compared to experimental data.

Wide range operation of regenerative optical parametric wavelength converter using ASE-degraded 43-Gb/s RZ-DPSK signals.

PubMed

Gao, Mingyi; Kurumida, Junya; Namiki, Shu

2011-11-07

For sustainable growth of the Internet, wavelength-tunable optical regeneration is the key to scaling up high energy-efficiency dynamic optical path networks while keeping the flexibility of the network. Wavelength-tunable optical parametric regenerator (T-OPR) based on the gain saturation effect of parametric amplification in a highly nonlinear fiber is promising for noise reduction in phase-shift keying signals. In this paper, we experimentally evaluated the T-OPR performance for ASE-degraded 43-Gb/s RZ-DPSK signals over a 20-nm input wavelength range between 1527 nm and 1547 nm. As a result, we achieved improved power penalty performance for the regenerated idler with a proper pump power range.

Dynamic Response of a Planetary Gear System Using a Finite Element/Contact Mechanics Model

NASA Technical Reports Server (NTRS)

Parker, Robert G.; Agashe, Vinayak; Vijayakar, Sandeep M.

2000-01-01

The dynamic response of a helicopter planetary gear system is examined over a wide range of operating speeds and torques. The analysis tool is a unique, semianalytical finite element formulation that admits precise representation of the tooth geometry and contact forces that are crucial in gear dynamics. Importantly, no a priori specification of static transmission error excitation or mesh frequency variation is required; the dynamic contact forces are evaluated internally at each time step. The calculated response shows classical resonances when a harmonic of mesh frequency coincides with a natural frequency. However, peculiar behavior occurs where resonances expected to be excited at a given speed are absent. This absence of particular modes is explained by analytical relationships that depend on the planetary configuration and mesh frequency harmonic. The torque sensitivity of the dynamic response is examined and compared to static analyses. Rotation mode response is shown to be more sensitive to input torque than translational mode response.

Laser fluence dependence on emission dynamics of ultrafast laser induced copper plasma

DOE PAGES

Anoop, K. K.; Harilal, S. S.; Philip, Reji; ...

2016-11-14

The characteristic emission features of a laser-produced plasma strongly depend strongly on the laser fluence. We investigated the spatial and temporal dynamics of neutrals and ions in femtosecond laser (800 nm, ≈ 40 fs, Ti:Sapphire) induced copper plasma in vacuum using both optical emission spectroscopy (OES) and spectrally resolved two-dimensional (2D) imaging methods over a wide fluence range of 0.5 J/cm 2-77.5 J/cm 2. 2D fast gated monochromatic images showed distinct plume splitting between the neutral and ions especially at moderate to higher fluence ranges. OES studies at low to moderate laser fluence regime confirm intense neutral line emission overmore » the ion emission whereas this trend changes at higher laser fluence with dominance of the latter. This evidences a clear change in the physical processes involved in femtosecond laser matter interaction at high input laser intensity. The obtained ion dynamics resulting from the OES, and spectrally resolved 2D imaging are compared with charged particle measurement employing Faraday cup and Langmuir probe and results showed good correlation.« less

Visual Detection Under Uncertainty Operates Via an Early Static, Not Late Dynamic, Non-Linearity

PubMed Central

Neri, Peter

2010-01-01

Signals in the environment are rarely specified exactly: our visual system may know what to look for (e.g., a specific face), but not its exact configuration (e.g., where in the room, or in what orientation). Uncertainty, and the ability to deal with it, is a fundamental aspect of visual processing. The MAX model is the current gold standard for describing how human vision handles uncertainty: of all possible configurations for the signal, the observer chooses the one corresponding to the template associated with the largest response. We propose an alternative model in which the MAX operation, which is a dynamic non-linearity (depends on multiple inputs from several stimulus locations) and happens after the input stimulus has been matched to the possible templates, is replaced by an early static non-linearity (depends only on one input corresponding to one stimulus location) which is applied before template matching. By exploiting an integrated set of analytical and experimental tools, we show that this model is able to account for a number of empirical observations otherwise unaccounted for by the MAX model, and is more robust with respect to the realistic limitations imposed by the available neural hardware. We then discuss how these results, currently restricted to a simple visual detection task, may extend to a wider range of problems in sensory processing. PMID:21212835

Faster turnover of new soil carbon inputs under increased atmospheric CO2.

PubMed

van Groenigen, Kees Jan; Osenberg, Craig W; Terrer, César; Carrillo, Yolima; Dijkstra, Feike A; Heath, James; Nie, Ming; Pendall, Elise; Phillips, Richard P; Hungate, Bruce A

2017-10-01

Rising levels of atmospheric CO 2 frequently stimulate plant inputs to soil, but the consequences of these changes for soil carbon (C) dynamics are poorly understood. Plant-derived inputs can accumulate in the soil and become part of the soil C pool ("new soil C"), or accelerate losses of pre-existing ("old") soil C. The dynamics of the new and old pools will likely differ and alter the long-term fate of soil C, but these separate pools, which can be distinguished through isotopic labeling, have not been considered in past syntheses. Using meta-analysis, we found that while elevated CO 2 (ranging from 550 to 800 parts per million by volume) stimulates the accumulation of new soil C in the short term (<1 year), these effects do not persist in the longer term (1-4 years). Elevated CO 2 does not affect the decomposition or the size of the old soil C pool over either temporal scale. Our results are inconsistent with predictions of conventional soil C models and suggest that elevated CO 2 might increase turnover rates of new soil C. Because increased turnover rates of new soil C limit the potential for additional soil C sequestration, the capacity of land ecosystems to slow the rise in atmospheric CO 2 concentrations may be smaller than previously assumed. © 2017 John Wiley & Sons Ltd.

Spiking Models for Level-Invariant Encoding

PubMed Central

Brette, Romain

2012-01-01

Levels of ecological sounds vary over several orders of magnitude, but the firing rate and membrane potential of a neuron are much more limited in range. In binaural neurons of the barn owl, tuning to interaural delays is independent of level differences. Yet a monaural neuron with a fixed threshold should fire earlier in response to louder sounds, which would disrupt the tuning of these neurons. How could spike timing be independent of input level? Here I derive theoretical conditions for a spiking model to be insensitive to input level. The key property is a dynamic change in spike threshold. I then show how level invariance can be physiologically implemented, with specific ionic channel properties. It appears that these ingredients are indeed present in monaural neurons of the sound localization pathway of birds and mammals. PMID:22291634

Design, Fabrication, and Modeling of a Novel Dual-Axis Control Input PZT Gyroscope.

PubMed

Chang, Cheng-Yang; Chen, Tsung-Lin

2017-10-31

Conventional gyroscopes are equipped with a single-axis control input, limiting their performance. Although researchers have proposed control algorithms with dual-axis control inputs to improve gyroscope performance, most have verified the control algorithms through numerical simulations because they lacked practical devices with dual-axis control inputs. The aim of this study was to design a piezoelectric gyroscope equipped with a dual-axis control input so that researchers may experimentally verify those control algorithms in future. Designing a piezoelectric gyroscope with a dual-axis control input is more difficult than designing a conventional gyroscope because the control input must be effective over a broad frequency range to compensate for imperfections, and the multiple mode shapes in flexural deformations complicate the relation between flexural deformation and the proof mass position. This study solved these problems by using a lead zirconate titanate (PZT) material, introducing additional electrodes for shielding, developing an optimal electrode pattern, and performing calibrations of undesired couplings. The results indicated that the fabricated device could be operated at 5.5±1 kHz to perform dual-axis actuations and position measurements. The calibration of the fabricated device was completed by system identifications of a new dynamic model including gyroscopic motions, electromechanical coupling, mechanical coupling, electrostatic coupling, and capacitive output impedance. Finally, without the assistance of control algorithms, the "open loop sensitivity" of the fabricated gyroscope was 1.82 μV/deg/s with a nonlinearity of 9.5% full-scale output. This sensitivity is comparable with those of other PZT gyroscopes with single-axis control inputs.

Using the virtual brain to reveal the role of oscillations and plasticity in shaping brain's dynamical landscape.

PubMed

Roy, Dipanjan; Sigala, Rodrigo; Breakspear, Michael; McIntosh, Anthony Randal; Jirsa, Viktor K; Deco, Gustavo; Ritter, Petra

2014-12-01

Spontaneous brain activity, that is, activity in the absence of controlled stimulus input or an explicit active task, is topologically organized in multiple functional networks (FNs) maintaining a high degree of coherence. These "resting state networks" are constrained by the underlying anatomical connectivity between brain areas. They are also influenced by the history of task-related activation. The precise rules that link plastic changes and ongoing dynamics of resting-state functional connectivity (rs-FC) remain unclear. Using the framework of the open source neuroinformatics platform "The Virtual Brain," we identify potential computational mechanisms that alter the dynamical landscape, leading to reconfigurations of FNs. Using a spiking neuron model, we first demonstrate that network activity in the absence of plasticity is characterized by irregular oscillations between low-amplitude asynchronous states and high-amplitude synchronous states. We then demonstrate the capability of spike-timing-dependent plasticity (STDP) combined with intrinsic alpha (8-12 Hz) oscillations to efficiently influence learning. Further, we show how alpha-state-dependent STDP alters the local area dynamics from an irregular to a highly periodic alpha-like state. This is an important finding, as the cortical input from the thalamus is at the rate of alpha. We demonstrate how resulting rhythmic cortical output in this frequency range acts as a neuronal tuner and, hence, leads to synchronization or de-synchronization between brain areas. Finally, we demonstrate that locally restricted structural connectivity changes influence local as well as global dynamics and lead to altered rs-FC.

Experimental investigation on the effects of non-cyclical frequency and amplitude variation on dynamic stall

NASA Astrophysics Data System (ADS)

Heintz, Kyle C.

An experimental study of a cambered airfoil undergoing non-cyclical, transient pitch trajectories and the resulting effects on the dynamic stall phenomenon is presented. Surface pressure measurements and airfoil incidence angle are acquired simultaneously to resolve instantaneous aerodynamic load coefficients at Mach numbers ranging from 0.2 to 0.4. Derived from these coefficients are various formulations of the aerodynamic damping factor, referred to copiously throughout. Using a two-motor mechanism, each providing independent frequency and amplitude input to the airfoil, unique pitch motions can be implemented by actively controlling the phase between inputs. This work primarily focuses on three pitch motion schemas, the first of which is a "chirp" style trajectory featuring concurrent exponential frequency growth and amplitude decay. Second, these parameters are tested separately to determine their individual contributions. Lastly, a novel dual harmonic pitch motion is devised which rapidly traverses dynamic stall regimes on an inter-cycle basis by modulating the static-stall penetration angle. Throughout all results presented, there is evidence that for consecutive pitch-cycles, the process of dynamic stall is affected when prior oscillations prior have undergone deeper stall-penetration angles. In other words when stall-penetration is descending, retreating from a regime of light or deep stall, statistics of load coefficients, such as damping coefficient, maximum lift, minimum quarter-chord moment, and their phase relationships, do not match the values seen when stall-penetration was growing. The outcomes herein suggest that the airfoil retains some memory of previous flow separation which has the potential to change the influence of the dynamic stall vortex.

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.

Do Variations in Detrital Inputs Influence Stable Soil Organic Matter? - An Experimental Approach

NASA Astrophysics Data System (ADS)

Lajtha, K.; Townsend, K.; Brewer, E.; Caldwell, B.; Kalbitz, K.; Plante, A.

2007-12-01

Recognition of the importance of feedbacks from plants in determining soil nutrient dynamics and C storage led to a large number of litter decomposition studies. Despite growing knowledge of short-term litter dynamics, we know relatively little about the fate of plant litter and its role in determining SOM content and nutrient cycling over time scales ranging from decades and centuries. To address this gap, we established long-term studies of controls on soil organic matter formation in an old-growth forest at the H.J. Andrews Experimental Forest, OR. This study complements a network of recently established similar experiments that pan climatic and soil gradients, as well as the original DIRT experiment established in the Wisconsin Arboretum in 1956 in both grassland and forested sites. The central goal of the DIRT project is to assess how rates and sources of plant litter inputs control the accumulation and dynamics of organic matter and nutrients in forest soils over decadal time scales. Treatment plots include doubled litter (needle) inputs , doubled wood, no above ground litter (screened) inputs, no root inputs (trenched), and no inputs (screened and trenched). For the 50th anniversary of the Wisconsin sites and the 10th anniversary of the H.J. Andrews site, we used sequential density fractionation of soils from all treatments to determine if adding or removing either below- or above-ground litter inputs influenced carbon stabilization as soil organic matter. After 50 years, double litter plots in both prairie and forested soils had higher %C in the 0-10 cm horizon. In the forested site, plots showed increased C content of the lightest fraction, which represents relatively young SOM with a short turnover time. However, the first two heavy fractions also showed increases in C with added aboveground litter, suggesting the importance of aboveground litter inputs to SOM in the forest. No such pattern existed for the prairie soil, and we hypothesize that this is because aboveground, labile litter adds very little to stabilized SOM in grasslands, and that root-derived C is the dominant control on SOM stabilization in grasslands. These results were confirmed with analysis of labile C (short -term respiration measurements) and acid hydrolysis resistant C across treatments. The relative contribution of aboveground vs. belowground litter was analyzed through the analysis of cutin and suberin acids, and we found that the detrital source of litter was retained in soils and could be fingerprinted through this analysis. Thermal analysis, including thermogravimetry (TG) and differential scanning calorimetry (DSC) performed simultaneously is currently being applied to explore both SOM quality and stability.

Bellman Ford algorithm - in Routing Information Protocol (RIP)

NASA Astrophysics Data System (ADS)

Krianto Sulaiman, Oris; Mahmud Siregar, Amir; Nasution, Khairuddin; Haramaini, Tasliyah

2018-04-01

In a large scale network need a routing that can handle a lot number of users, one of the solutions to cope with large scale network is by using a routing protocol, There are 2 types of routing protocol that is static and dynamic, Static routing is manually route input based on network admin, while dynamic routing is automatically route input formed based on existing network. Dynamic routing is efficient used to network extensively because of the input of route automatic formed, Routing Information Protocol (RIP) is one of dynamic routing that uses the bellman-ford algorithm where this algorithm will search for the best path that traversed the network by leveraging the value of each link, so with the bellman-ford algorithm owned by RIP can optimize existing networks.

2017 Guralp Affinity Digitizer Evaluation.

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

Merchant, Bion J.

Sandia National Laboratories has tested and evaluated two Guralp Affinity digitizers. The Affinity digitizers are intended to record sensor output for seismic and infrasound monitoring applications. The purpose of this digitizer evaluation is to measure the performance characteristics in such areas as power consumption, input impedance, sensitivity, full scale, self- noise, dynamic range, system noise, response, passband, and timing. The Affinity digitizers are being evaluated for potential use in the International Monitoring System (IMS) of the Comprehensive Nuclear Test-Ban-Treaty Organization (CTBTO).

A Completely Solid-State Tunable Ti:Sapphire Laser System

NASA Technical Reports Server (NTRS)

Guerra, David V.; Coyle, D. Barry; Krebs, Danny J.

1994-01-01

Compact, completely solid-state tunable pulsed laser system passively cooled developed for potential employment in aircraft and sounding-rocket lidar experiments. Ti:sapphire based laser system pumped with frequency-doubled diode-pumped Nd:YAG. Rugged, self-contained system extremely flexible and provides pulsed output at specific frequencies with low input-power requirements. In-situ measurements enables scientists to study upper-atmosphere dynamics. Tuning range easily extended to bands between 650-950 nm in order to study other atmospheric constituents.

Analysis of propellant feedline dynamics

NASA Technical Reports Server (NTRS)

Holster, J. L.; Astleford, W. J.; Gerlach, C. R.

1973-01-01

An analytical model and corresponding computer program for studying disturbances of liquid propellants in typical engine feedline systems were developed. The model includes the effects of steady turbulent mean flow, the influence of distributed compliances, the effects of local compliances, and various factors causing structural-hydraulic coupling. The computer program was set up such that the amplitude and phase of the terminal pressure/input excitation is calculated over any desired frequency range for an arbitrary assembly of various feedline components. A user's manual is included.

Learning enhances the relative impact of top-down processing in the visual cortex

PubMed Central

Makino, Hiroshi; Komiyama, Takaki

2015-01-01

Theories have proposed that in sensory cortices learning can enhance top-down modulation by higher brain areas while reducing bottom-up sensory inputs. To address circuit mechanisms underlying this process, we examined the activity of layer 2/3 (L2/3) excitatory neurons in the mouse primary visual cortex (V1) as well as L4 neurons, the main bottom-up source, and long-range top-down projections from the retrosplenial cortex (RSC) during associative learning over days using chronic two-photon calcium imaging. During learning, L4 responses gradually weakened, while RSC inputs became stronger. Furthermore, L2/3 acquired a ramp-up response temporal profile with learning, coinciding with a similar change in RSC inputs. Learning also reduced the activity of somatostatin-expressing inhibitory neurons (SOM-INs) in V1 that could potentially gate top-down inputs. Finally, RSC inactivation or SOM-IN activation was sufficient to partially reverse the learning-induced changes in L2/3. Together, these results reveal a learning-dependent dynamic shift in the balance between bottom-up and top-down information streams and uncover a role of SOM-INs in controlling this process. PMID:26167904

First full dynamic range calibration of the JUNGFRAU photon detector

NASA Astrophysics Data System (ADS)

Redford, S.; Andrä, M.; Barten, R.; Bergamaschi, A.; Brückner, M.; Dinapoli, R.; Fröjdh, E.; Greiffenberg, D.; Lopez-Cuenca, C.; Mezza, D.; Mozzanica, A.; Ramilli, M.; Ruat, M.; Ruder, C.; Schmitt, B.; Shi, X.; Thattil, D.; Tinti, G.; Vetter, S.; Zhang, J.

2018-01-01

The JUNGFRAU detector is a charge integrating hybrid silicon pixel detector developed at the Paul Scherrer Institut for photon science applications, in particular for the upcoming free electron laser SwissFEL. With a high dynamic range, analogue readout, low noise and three automatically switching gains, JUNGFRAU promises excellent performance not only at XFELs but also at synchrotrons in areas such as protein crystallography, ptychography, pump-probe and time resolved measurements. To achieve its full potential, the detector must be calibrated on a pixel-by-pixel basis. This contribution presents the current status of the JUNGFRAU calibration project, in which a variety of input charge sources are used to parametrise the energy response of the detector across four orders of magnitude of dynamic range. Building on preliminary studies, the first full calibration procedure of a JUNGFRAU 0.5 Mpixel module is described. The calibration is validated using alternative sources of charge deposition, including laboratory experiments and measurements at ESRF and LCLS. The findings from these measurements are presented. Calibrated modules have already been used in proof-of-principle style protein crystallography experiments at the SLS. A first look at selected results is shown. Aspects such as the conversion of charge to number of photons, treatment of multi-size pixels and the origin of non-linear response are also discussed.

A Physiologically Based Model of Orexinergic Stabilization of Sleep and Wake

PubMed Central

Fulcher, Ben D.; Phillips, Andrew J. K.; Postnova, Svetlana; Robinson, Peter A.

2014-01-01

The orexinergic neurons of the lateral hypothalamus (Orx) are essential for regulating sleep-wake dynamics, and their loss causes narcolepsy, a disorder characterized by severe instability of sleep and wake states. However, the mechanisms through which Orx stabilize sleep and wake are not well understood. In this work, an explanation of the stabilizing effects of Orx is presented using a quantitative model of important physiological connections between Orx and the sleep-wake switch. In addition to Orx and the sleep-wake switch, which is composed of mutually inhibitory wake-active monoaminergic neurons in brainstem and hypothalamus (MA) and the sleep-active ventrolateral preoptic neurons of the hypothalamus (VLPO), the model also includes the circadian and homeostatic sleep drives. It is shown that Orx stabilizes prolonged waking episodes via its excitatory input to MA and by relaying a circadian input to MA, thus sustaining MA firing activity during the circadian day. During sleep, both Orx and MA are inhibited by the VLPO, and the subsequent reduction in Orx input to the MA indirectly stabilizes sustained sleep episodes. Simulating a loss of Orx, the model produces dynamics resembling narcolepsy, including frequent transitions between states, reduced waking arousal levels, and a normal daily amount of total sleep. The model predicts a change in sleep timing with differences in orexin levels, with higher orexin levels delaying the normal sleep episode, suggesting that individual differences in Orx signaling may contribute to chronotype. Dynamics resembling sleep inertia also emerge from the model as a gradual sleep-to-wake transition on a timescale that varies with that of Orx dynamics. The quantitative, physiologically based model developed in this work thus provides a new explanation of how Orx stabilizes prolonged episodes of sleep and wake, and makes a range of experimentally testable predictions, including a role for Orx in chronotype and sleep inertia. PMID:24651580

Comparison of the Diagnostic Accuracy of DSC- and Dynamic Contrast-Enhanced MRI in the Preoperative Grading of Astrocytomas.

PubMed

Nguyen, T B; Cron, G O; Perdrizet, K; Bezzina, K; Torres, C H; Chakraborty, S; Woulfe, J; Jansen, G H; Sinclair, J; Thornhill, R E; Foottit, C; Zanette, B; Cameron, I G

2015-11-01

Dynamic contrast-enhanced MR imaging parameters can be biased by poor measurement of the vascular input function. We have compared the diagnostic accuracy of dynamic contrast-enhanced MR imaging by using a phase-derived vascular input function and "bookend" T1 measurements with DSC MR imaging for preoperative grading of astrocytomas. This prospective study included 48 patients with a new pathologic diagnosis of an astrocytoma. Preoperative MR imaging was performed at 3T, which included 2 injections of 5-mL gadobutrol for dynamic contrast-enhanced and DSC MR imaging. During dynamic contrast-enhanced MR imaging, both magnitude and phase images were acquired to estimate plasma volume obtained from phase-derived vascular input function (Vp_Φ) and volume transfer constant obtained from phase-derived vascular input function (K(trans)_Φ) as well as plasma volume obtained from magnitude-derived vascular input function (Vp_SI) and volume transfer constant obtained from magnitude-derived vascular input function (K(trans)_SI). From DSC MR imaging, corrected relative CBV was computed. Four ROIs were placed over the solid part of the tumor, and the highest value among the ROIs was recorded. A Mann-Whitney U test was used to test for difference between grades. Diagnostic accuracy was assessed by using receiver operating characteristic analysis. Vp_ Φ and K(trans)_Φ values were lower for grade II compared with grade III astrocytomas (P < .05). Vp_SI and K(trans)_SI were not significantly different between grade II and grade III astrocytomas (P = .08-0.15). Relative CBV and dynamic contrast-enhanced MR imaging parameters except for K(trans)_SI were lower for grade III compared with grade IV (P ≤ .05). In differentiating low- and high-grade astrocytomas, we found no statistically significant difference in diagnostic accuracy between relative CBV and dynamic contrast-enhanced MR imaging parameters. In the preoperative grading of astrocytomas, the diagnostic accuracy of dynamic contrast-enhanced MR imaging parameters is similar to that of relative CBV. © 2015 by American Journal of Neuroradiology.

Remaining dischargeable time prediction for lithium-ion batteries using unscented Kalman filter

NASA Astrophysics Data System (ADS)

Dong, Guangzhong; Wei, Jingwen; Chen, Zonghai; Sun, Han; Yu, Xiaowei

2017-10-01

To overcome the range anxiety, one of the important strategies is to accurately predict the range or dischargeable time of the battery system. To accurately predict the remaining dischargeable time (RDT) of a battery, a RDT prediction framework based on accurate battery modeling and state estimation is presented in this paper. Firstly, a simplified linearized equivalent-circuit-model is developed to simulate the dynamic characteristics of a battery. Then, an online recursive least-square-algorithm method and unscented-Kalman-filter are employed to estimate the system matrices and SOC at every prediction point. Besides, a discrete wavelet transform technique is employed to capture the statistical information of past dynamics of input currents, which are utilized to predict the future battery currents. Finally, the RDT can be predicted based on the battery model, SOC estimation results and predicted future battery currents. The performance of the proposed methodology has been verified by a lithium-ion battery cell. Experimental results indicate that the proposed method can provide an accurate SOC and parameter estimation and the predicted RDT can solve the range anxiety issues.

High resolution CMOS capacitance-frequency converter for biosensor applications

NASA Astrophysics Data System (ADS)

Ghoor, I. S.; Land, K.; Joubert, T.-H.

2016-02-01

This paper presents the design of a low-complexity, linear and sub-pF CMOS capacitance-frequency converter for reading out a capacitive bacterial bio/sensors with the endeavour of creating a universal bio/sensor readout module. Therefore the priority design objectives are a high resolution as well as an extensive dynamic range. The circuit is based on a method which outputs a digital frequency signal directly from a differential capacitance by the accumulation of charges produced by repetitive charge integration and charge preservation1. A prototype has been designed for manufacture in the 0.35 μm, 3.3V ams CMOS technology. At a 1MHz clock speed, the most pertinent results obtained for the designed converter are: (i) power consumption of 1.37mW; (ii) a resolution of at least 5 fF for sensitive capacitive transduction; and (iii) an input dynamic range of at least 43.5 dB from a measurable capacitance value range of 5 - 750 fF (iv) and a Pearson's coefficient of linearity of 0.99.

Compression wave studies in Blair dolomite

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

Grady, D.E.; Hollenbach, R.E.; Schuler, K.W.

Dynamic compression wave studies have been conducted on Blair dolomite in the stress range of 0-7.0 GPa. Impact techniques were used to generate stress impulse input functions, and diffuse surface laser interferometry provided the dynamic instrumentation. Experimental particle velocity profiles obtained by this method were coupled with the conservation laws of mass and momentum to determine the stress-strain and stress-modulus constitutive properties of the material. Comparison between dynamic and quasistatic uniaxial stress-strain curves uncovered significant differences. Energy dissipated in a complete load and unload cycle differed by almost an order of magnitude and the longitudinal moduli differed by as muchmore » as a factor of two. Blair dolomite was observed to yield under dynamic loading at 2.5 GPa. Below 2.5 GPa the loading waves had a finite risetime and exhibited steady propagation. A finite linear viscoelastic constitutive model satisfactorily predicted the observed wave propagation. We speculate that dynamic properties of preexisting cracks provides a physical mechanism for both the rate dependent steady wave behavior and the difference between dynamic and quasistatic response.« less

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.

Adaptation to sensory input tunes visual cortex to criticality

NASA Astrophysics Data System (ADS)

Shew, Woodrow L.; Clawson, Wesley P.; Pobst, Jeff; Karimipanah, Yahya; Wright, Nathaniel C.; Wessel, Ralf

2015-08-01

A long-standing hypothesis at the interface of physics and neuroscience is that neural networks self-organize to the critical point of a phase transition, thereby optimizing aspects of sensory information processing. This idea is partially supported by strong evidence for critical dynamics observed in the cerebral cortex, but the impact of sensory input on these dynamics is largely unknown. Thus, the foundations of this hypothesis--the self-organization process and how it manifests during strong sensory input--remain unstudied experimentally. Here we show in visual cortex and in a computational model that strong sensory input initially elicits cortical network dynamics that are not critical, but adaptive changes in the network rapidly tune the system to criticality. This conclusion is based on observations of multifaceted scaling laws predicted to occur at criticality. Our findings establish sensory adaptation as a self-organizing mechanism that maintains criticality in visual cortex during sensory information processing.

Life and dynamic capacity modeling for aircraft transmissions

NASA Technical Reports Server (NTRS)

Savage, Michael

1991-01-01

A computer program to simulate the dynamic capacity and life of parallel shaft aircraft transmissions is presented. Five basic configurations can be analyzed: single mesh, compound, parallel, reverted, and single plane reductions. In execution, the program prompts the user for the data file prefix name, takes input from a ASCII file, and writes its output to a second ASCII file with the same prefix name. The input data file includes the transmission configuration, the input shaft torque and speed, and descriptions of the transmission geometry and the component gears and bearings. The program output file describes the transmission, its components, their capabilities, locations, and loads. It also lists the dynamic capability, ninety percent reliability, and mean life of each component and the transmission as a system. Here, the program, its input and output files, and the theory behind the operation of the program are described.

Multibody dynamics model building using graphical interfaces

NASA Technical Reports Server (NTRS)

Macala, Glenn A.

1989-01-01

In recent years, the extremely laborious task of manually deriving equations of motion for the simulation of multibody spacecraft dynamics has largely been eliminated. Instead, the dynamicist now works with commonly available general purpose dynamics simulation programs which generate the equations of motion either explicitly or implicitly via computer codes. The user interface to these programs has predominantly been via input data files, each with its own required format and peculiarities, causing errors and frustrations during program setup. Recent progress in a more natural method of data input for dynamics programs: the graphical interface, is described.

Ab Initio Calculations of Transport in Titanium and Aluminum Mixtures

NASA Astrophysics Data System (ADS)

Walker, Nicholas; Novak, Brian; Tam, Ka Ming; Moldovan, Dorel; Jarrell, Mark

In classical molecular dynamics simulations, the self-diffusion and shear viscosity of titanium about the melting point have fallen within the ranges provided by experimental data. However, the experimental data is difficult to collect and has been rather scattered, making it of limited value for the validation of these calculations. By using ab initio molecular dynamics simulations within the density functional theory framework, the classical molecular dynamics data can be validated. The dynamical data from the ab initio molecular dynamics can also be used to calculate new potentials for use in classical molecular dynamics, allowing for more accurate classical dynamics simulations for the liquid phase. For metallic materials such as titanium and aluminum alloys, these calculations are very valuable due to an increasing demand for the knowledge of their thermophysical properties that drive the development of new materials. For example, alongside knowledge of the surface tension, viscosity is an important input for modeling the additive manufacturing process at the continuum level. We are developing calculations of the viscosity along with the self-diffusion for aluminum, titanium, and titanium-aluminum alloys with ab initio molecular dynamics. Supported by the National Science Foundation through cooperative agreement OIA-1541079 and the Louisiana Board of Regents.

Dynamical Adaptation in Photoreceptors

PubMed Central

Clark, Damon A.; Benichou, Raphael; Meister, Markus; Azeredo da Silveira, Rava

2013-01-01

Adaptation is at the heart of sensation and nowhere is it more salient than in early visual processing. Light adaptation in photoreceptors is doubly dynamical: it depends upon the temporal structure of the input and it affects the temporal structure of the response. We introduce a non-linear dynamical adaptation model of photoreceptors. It is simple enough that it can be solved exactly and simulated with ease; analytical and numerical approaches combined provide both intuition on the behavior of dynamical adaptation and quantitative results to be compared with data. Yet the model is rich enough to capture intricate phenomenology. First, we show that it reproduces the known phenomenology of light response and short-term adaptation. Second, we present new recordings and demonstrate that the model reproduces cone response with great precision. Third, we derive a number of predictions on the response of photoreceptors to sophisticated stimuli such as periodic inputs, various forms of flickering inputs, and natural inputs. In particular, we demonstrate that photoreceptors undergo rapid adaptation of response gain and time scale, over ∼ 300 ms—i. e., over the time scale of the response itself—and we confirm this prediction with data. For natural inputs, this fast adaptation can modulate the response gain more than tenfold and is hence physiologically relevant. PMID:24244119

Neural-adaptive control of single-master-multiple-slaves teleoperation for coordinated multiple mobile manipulators with time-varying communication delays and input uncertainties.

PubMed

Li, Zhijun; Su, Chun-Yi

2013-09-01

In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties for multiple mobile manipulators carrying a common object in a cooperative manner. Firstly, concise dynamics of teleoperation systems consisting of a single master robot, multiple coordinated slave robots, and the object are developed in the task space. To handle asymmetric time-varying delays in communication channels and unknown asymmetric input dead zones, the nonlinear dynamics of the teleoperation system are transformed into two subsystems through feedback linearization: local master or slave dynamics including the unknown input dead zones and delayed dynamics for the purpose of synchronization. Then, a model reference neural network control strategy based on linear matrix inequalities (LMI) and adaptive techniques is proposed. The developed control approach ensures that the defined tracking errors converge to zero whereas the coordination internal force errors remain bounded and can be made arbitrarily small. Throughout this paper, stability analysis is performed via explicit Lyapunov techniques under specific LMI conditions. The proposed adaptive neural network control scheme is robust against motion disturbances, parametric uncertainties, time-varying delays, and input dead zones, which is validated by simulation studies.

Nutrient dynamics in tropical rivers, lagoons, and coastal ecosystems of eastern Hainan Island, South China Sea

NASA Astrophysics Data System (ADS)

Li, R. H.; Liu, S. M.; Li, Y. W.; Zhang, G. L.; Ren, J. L.; Zhang, J.

2014-01-01

Nutrient dynamics based on field observations made along the eastern Hainan Island during the period 2006-2009 were investigated to understand nutrient biogeochemical processes, and to provide an overview of human perturbations of coastal ecosystems in this tropical region. The rivers showed seasonal variations in nutrient concentrations, with enrichment of dissolved inorganic nitrogen and dissolved silicate, and depletion of PO43-. High riverine concentrations of nitrate mainly originated from agricultural fertilizer inputs. The DIN : PO43- ratios ranged from 37 to 1063, suggesting preferential depletion of PO43- relative to nitrogen in rivers. Chemical weathering in the drainage area might explain the high levels of dissolved silicate. Aquaculture ponds contained high concentrations of NH4+ and dissolved organic nitrogen. The particulate phosphorus concentrations in the study area were lower than those reported for estuaries worldwide. The particulate silicate levels in rivers and lagoons were lower than the global average level. Nutrient biogeochemistry in coastal areas was affected by human activities (e.g., aquaculture, agriculture), and by natural phenomena including typhoons. The nutrient concentrations in coastal waters were low because of dispersion of land-derived nutrients in the sea. Nutrient budgets were built based on a steady-state box model, which showed that riverine fluxes are magnified by estuarine processes (e.g., regeneration, desorption) in estuaries and Laoyehai Lagoon, but not in Xiaohai Lagoon. Riverine and groundwater inputs were the major sources of nutrients to Xiaohai and Laoyehai lagoons, respectively, and riverine inputs and aquaculture effluents were the major sources for the eastern coast of Hainan Island. Nutrient inputs to the coastal ecosystem increased with typhoon-induced runoff of rainwater, elucidating the important influence of typhoons on small tropical rivers.

Hydrological heterogeneity, nutrient dynamics and water quality of a non-tidal lentic ecosystem (Lesina Lagoon, Italy)

NASA Astrophysics Data System (ADS)

Roselli, Leonilde; Fabbrocini, Adele; Manzo, Cristina; D'Adamo, Raffaele

2009-10-01

The dynamics of the Lesina coastal lagoon (Italy) in terms of nutrients, phytoplankton and chemical-physical parameters were evaluated, together with their functional relationships with freshwater inputs, in order to identify ecosystem responses to changes in driving forces in a Mediterranean non-tidal lentic environment. Lesina Lagoon is a shallow coastal environment characterised by limited exchange with coastal waters, which favours enrichment of nutrients and organic matter and benthic fluxes within the system. Lagoon-sea exchanges are influenced by human management. There is a steep salinity gradient from East to West. High nitrogen and silica values were found close to freshwater inputs, indicating wastewater discharges and agricultural runoff, especially in winter. Dissolved oxygen was well below saturation (65%) near sewage and runoff inputs in the western part of the lagoon during summer. Classification in accordance with EEA (2001) guidelines suggests the system is of "poor" or "bad" quality in terms of nitrogen concentrations in the eastern zone during the winter rainy period. In terms of phosphate concentrations, the majority of the stations fall into the "good" category, with only two stations (close to the sewage and runoff inputs) classed as "bad". In both cases, the raw nitrogen levels make the lagoon a P-limited system, especially in the eastern part. There was wide space-time variability in chlorophyll a concentrations, which ranged from 0.25 to 56 μg l -1. No relationships between chlorophyll a and nutrients were found, suggesting that autotrophic biomass may be controlled by a large number of internal and external forcing factors driving eutrophication processes. Water quality for this type of environment depends heavily on pressure from human activities but also on the management of sewage treatment plants, agricultural practices and the channels connecting the lagoon with the sea.

Dynamics of networks of excitatory and inhibitory neurons in response to time-dependent inputs.

PubMed

Ledoux, Erwan; Brunel, Nicolas

2011-01-01

We investigate the dynamics of recurrent networks of excitatory (E) and inhibitory (I) neurons in the presence of time-dependent inputs. The dynamics is characterized by the network dynamical transfer function, i.e., how the population firing rate is modulated by sinusoidal inputs at arbitrary frequencies. Two types of networks are studied and compared: (i) a Wilson-Cowan type firing rate model; and (ii) a fully connected network of leaky integrate-and-fire (LIF) neurons, in a strong noise regime. We first characterize the region of stability of the "asynchronous state" (a state in which population activity is constant in time when external inputs are constant) in the space of parameters characterizing the connectivity of the network. We then systematically characterize the qualitative behaviors of the dynamical transfer function, as a function of the connectivity. We find that the transfer function can be either low-pass, or with a single or double resonance, depending on the connection strengths and synaptic time constants. Resonances appear when the system is close to Hopf bifurcations, that can be induced by two separate mechanisms: the I-I connectivity and the E-I connectivity. Double resonances can appear when excitatory delays are larger than inhibitory delays, due to the fact that two distinct instabilities exist with a finite gap between the corresponding frequencies. In networks of LIF neurons, changes in external inputs and external noise are shown to be able to change qualitatively the network transfer function. Firing rate models are shown to exhibit the same diversity of transfer functions as the LIF network, provided delays are present. They can also exhibit input-dependent changes of the transfer function, provided a suitable static non-linearity is incorporated.

Comparison of quantitatively analyzed dynamic area-detector CT using various mathematic methods with FDG PET/CT in management of solitary pulmonary nodules.

PubMed

Ohno, Yoshiharu; Nishio, Mizuho; Koyama, Hisanobu; Fujisawa, Yasuko; Yoshikawa, Takeshi; Matsumoto, Sumiaki; Sugimura, Kazuro

2013-06-01

The objective of our study was to prospectively compare the capability of dynamic area-detector CT analyzed with different mathematic methods and PET/CT in the management of pulmonary nodules. Fifty-two consecutive patients with 96 pulmonary nodules underwent dynamic area-detector CT, PET/CT, and microbacterial or pathologic examinations. All nodules were classified into the following groups: malignant nodules (n = 57), benign nodules with low biologic activity (n = 15), and benign nodules with high biologic activity (n = 24). On dynamic area-detector CT, the total, pulmonary arterial, and systemic arterial perfusions were calculated using the dual-input maximum slope method; perfusion was calculated using the single-input maximum slope method; and extraction fraction and blood volume (BV) were calculated using the Patlak plot method. All indexes were statistically compared among the three nodule groups. Then, receiver operating characteristic analyses were used to compare the diagnostic capabilities of the maximum standardized uptake value (SUVmax) and each perfusion parameter having a significant difference between malignant and benign nodules. Finally, the diagnostic performances of the indexes were compared by means of the McNemar test. No adverse effects were observed in this study. All indexes except extraction fraction and BV, both of which were calculated using the Patlak plot method, showed significant differences among the three groups (p < 0.05). Areas under the curve of total perfusion calculated using the dual-input method, pulmonary arterial perfusion calculated using the dual-input method, and perfusion calculated using the single-input method were significantly larger than that of SUVmax (p < 0.05). The accuracy of total perfusion (83.3%) was significantly greater than the accuracy of the other indexes: pulmonary arterial perfusion (72.9%, p < 0.05), systemic arterial perfusion calculated using the dual-input method (69.8%, p < 0.05), perfusion (66.7%, p < 0.05), and SUVmax (60.4%, p < 0.05). Dynamic area-detector CT analyzed using the dual-input maximum slope method has better potential for the diagnosis of pulmonary nodules than dynamic area-detector CT analyzed using other methods and than PET/CT.

Short-Term Plasticity in a Computational Model of the Tail-Withdrawal Circuit in Aplysia

PubMed Central

Baxter, Douglas A.; Byrne, John H.

2007-01-01

The tail-withdrawal circuit of Aplysia provides a useful model system for investigating synaptic dynamics. Sensory neurons within the circuit manifest several forms of synaptic plasticity. Here, we developed a model of the circuit and investigated the ways in which depression (DEP) and potentiation (POT) contributed to information processing. DEP limited the amount of motor neuron activity that could be elicited by the monosynaptic pathway alone. POT within the monosynaptic pathway did not compensate for DEP. There was, however, a synergistic interaction between POT and the polysynaptic pathway. This synergism extended the dynamic range of the network, and the interplay between DEP and POT made the circuit responded preferentially to long-duration, low-frequency inputs. PMID:17957237

Study on Dynamic Alignment Technology of COIL Resonator

NASA Astrophysics Data System (ADS)

Xiong, M. D.; Zou, X. J.; Guo, J. H.; Jia, S. N.; Zhang2, Z. B.

2006-10-01

The performance of great power chemical oxygen-iodine laser (COIL) beam is decided mostly by resonator mirror maladjustment and environment vibration. To improve the performance of light beam, an auto-alignment device is used in COIL resonator, the device can keep COIL resonator collimating by adjusting the optical components of resonator. So the coupling model of COIL resonator is present. The multivariable self study fuzzy uncoupling arithmetic and six-dimensional micro drive technology are used to design a six-input-three-output uncoupling controller, resulting in the realization of the high precision dynamic alignment. The experiments indicate that the collimating range of this system is 8 mrad, precision is 5 urad and frequency response is 20Hz, which meet the demand of resonator alignment system.

Water surface modeling from a single viewpoint video.

PubMed

Li, Chuan; Pickup, David; Saunders, Thomas; Cosker, Darren; Marshall, David; Hall, Peter; Willis, Philip

2013-07-01

We introduce a video-based approach for producing water surface models. Recent advances in this field output high-quality results but require dedicated capturing devices and only work in limited conditions. In contrast, our method achieves a good tradeoff between the visual quality and the production cost: It automatically produces a visually plausible animation using a single viewpoint video as the input. Our approach is based on two discoveries: first, shape from shading (SFS) is adequate to capture the appearance and dynamic behavior of the example water; second, shallow water model can be used to estimate a velocity field that produces complex surface dynamics. We will provide qualitative evaluation of our method and demonstrate its good performance across a wide range of scenes.

Neural controller for adaptive movements with unforeseen payloads.

PubMed

Kuperstein, M; Wang, J

1990-01-01

A theory and computer simulation of a neural controller that learns to move and position a link carrying an unforeseen payload accurately are presented. The neural controller learns adaptive dynamic control from its own experience. It does not use information about link mass, link length, or direction of gravity, and it uses only indirect uncalibrated information about payload and actuator limits. Its average positioning accuracy across a large range of payloads after learning is 3% of the positioning range. This neural controller can be used as a basis for coordinating any number of sensory inputs with limbs of any number of joints. The feedforward nature of control allows parallel implementation in real time across multiple joints.

Real-Time Feedback Control of Flow-Induced Cavity Tones. Part 1; Fixed-Gain Control

NASA Technical Reports Server (NTRS)

Kegerise, M. A.; Cabell, R. H.; Cattafesta, L. N., III

2006-01-01

A generalized predictive control (GPC) algorithm was formulated and applied to the cavity flow-tone problem. The control algorithm demonstrated multiple Rossiter-mode suppression at fixed Mach numbers ranging from 0.275 to 0.38. Controller performance was evaluated with a measure of output disturbance rejection and an input sensitivity transfer function. The results suggest that disturbances entering the cavity flow are collocated with the control input at the cavity leading edge. In that case, only tonal components of the cavity wall-pressure fluctuations can be suppressed and arbitrary broadband pressure reduction is not possible with the present sensor/actuator arrangement. In the control-algorithm development, the cavity dynamics were treated as linear and time invariant (LTI) for a fixed Mach number. The experimental results lend support to that treatment.

Coupling between fluid dynamics and energy addition in arcjet and microwave thrusters

NASA Technical Reports Server (NTRS)

Micci, M. M.

1986-01-01

A new approach to numerically solving the problem of the constricted electric arcjet is presented. An Euler Implicit finite difference scheme is used to solve the full compressible Navier Stokes equations in two dimensions. The boundary and initial conditions represent the constrictor section of the arcjet, and hydrogen is used as a propellant. The arc is modeled as a Gaussian distribution across the centerline of the constrictor. Temperature, pressure and velocity profiles for steady state converged solutions show both axial and radial changes in distributions resulting from their interaction with the arc energy source for specific input conditions. The temperature rise is largest at the centerline where there is a the greatest concentration arc energy. The solution does not converge for all initial inputs and the limitations in the range of obtainable solutions are discussed.

Robust crossfeed design for hovering rotorcraft. M.S. Thesis

NASA Technical Reports Server (NTRS)

Catapang, David R.

1993-01-01

Control law design for rotorcraft fly-by-wire systems normally attempts to decouple angular responses using fixed-gain crossfeeds. This approach can lead to poor decoupling over the frequency range of pilot inputs and increase the load on the feedback loops. In order to improve the decoupling performance, dynamic crossfeeds may be adopted. Moreover, because of the large changes that occur in rotorcraft dynamics due to small changes about the nominal design condition, especially for near-hovering flight, the crossfeed design must be 'robust.' A new low-order matching method is presented here to design robost crossfeed compensators for multi-input, multi-output (MIMO) systems. The technique identifies degrees-of-freedom that can be decoupled using crossfeeds, given an anticipated set of parameter variations for the range of flight conditions of concern. Cross-coupling is then reduced for degrees-of-freedom that can use crossfeed compensation by minimizing off-axis response magnitude average and variance. Results are presented for the analysis of pitch, roll, yaw, and heave coupling of the UH-60 Black Hawk helicopter in near-hovering flight. Robust crossfeeds are designed that show significant improvement in decoupling performance and robustness over nominal, single design point, compensators. The design method and results are presented in an easily-used graphical format that lends significant physical insight to the design procedure. This plant pre-compensation technique is an appropriate preliminary step to the design of robust feedback control laws for rotorcraft.

Quantification of Plasma miRNAs by Digital PCR for Cancer Diagnosis

PubMed Central

Ma, Jie; Li, Ning; Guarnera, Maria; Jiang, Feng

2013-01-01

Analysis of plasma microRNAs (miRNAs) by quantitative polymerase chain reaction (qPCR) provides a potential approach for cancer diagnosis. However, absolutely quantifying low abundant plasma miRNAs is challenging with qPCR. Digital PCR offers a unique means for assessment of nucleic acids presenting at low levels in plasma. This study aimed to evaluate the efficacy of digital PCR for quantification of plasma miRNAs and the potential utility of this technique for cancer diagnosis. We used digital PCR to quantify the copy number of plasma microRNA-21-5p (miR-21–5p) and microRNA-335–3p (miR-335–3p) in 36 lung cancer patients and 38 controls. Digital PCR showed a high degree of linearity and quantitative correlation with miRNAs in a dynamic range from 1 to 10,000 copies/μL of input, with high reproducibility. qPCR exhibited a dynamic range from 100 to 1×107 copies/μL of input. Digital PCR had a higher sensitivity to detect copy number of the miRNAs compared with qPCR. In plasma, digital PCR could detect copy number of both miR-21–5p and miR-335–3p, whereas qPCR was only able to assess miR-21–5p. Quantification of the plasma miRNAs by digital PCR provided 71.8% sensitivity and 80.6% specificity in distinguishing lung cancer patients from cancer-free subjects. PMID:24277982

Fold-change detection and scalar symmetry of sensory input fields.

PubMed

Shoval, Oren; Goentoro, Lea; Hart, Yuval; Mayo, Avi; Sontag, Eduardo; Alon, Uri

2010-09-07

Recent studies suggest that certain cellular sensory systems display fold-change detection (FCD): a response whose entire shape, including amplitude and duration, depends only on fold changes in input and not on absolute levels. Thus, a step change in input from, for example, level 1 to 2 gives precisely the same dynamical output as a step from level 2 to 4, because the steps have the same fold change. We ask what the benefit of FCD is and show that FCD is necessary and sufficient for sensory search to be independent of multiplying the input field by a scalar. Thus, the FCD search pattern depends only on the spatial profile of the input and not on its amplitude. Such scalar symmetry occurs in a wide range of sensory inputs, such as source strength multiplying diffusing/convecting chemical fields sensed in chemotaxis, ambient light multiplying the contrast field in vision, and protein concentrations multiplying the output in cellular signaling systems. Furthermore, we show that FCD entails two features found across sensory systems, exact adaptation and Weber's law, but that these two features are not sufficient for FCD. Finally, we present a wide class of mechanisms that have FCD, including certain nonlinear feedback and feed-forward loops. We find that bacterial chemotaxis displays feedback within the present class and hence, is expected to show FCD. This can explain experiments in which chemotaxis searches are insensitive to attractant source levels. This study, thus, suggests a connection between properties of biological sensory systems and scalar symmetry stemming from physical properties of their input fields.

Design of the small pixel pitch ROIC

NASA Astrophysics Data System (ADS)

Liang, Qinghua; Jiang, Dazhao; Chen, Honglei; Zhai, Yongcheng; Gao, Lei; Ding, Ruijun

2014-11-01

Since the technology trend of the third generation IRFPA towards resolution enhancing has steadily progressed,the pixel pitch of IRFPA has been greatly reduced.A 640×512 readout integrated circuit(ROIC) of IRFPA with 15μm pixel pitch is presented in this paper.The 15μm pixel pitch ROIC design will face many challenges.As we all known,the integrating capacitor is a key performance parameter when considering pixel area,charge capacity and dynamic range,so we adopt the effective method of 2 by 2 pixels sharing an integrating capacitor to solve this problem.The input unit cell architecture will contain two paralleled sample and hold parts,which not only allow the FPA to be operated in full frame snapshot mode but also save relatively unit circuit area.Different applications need more matching input unit circuits. Because the dimension of 2×2 pixels is 30μm×30μm, an input stage based on direct injection (DI) which has medium injection ratio and small layout area is proved to be suitable for middle wave (MW) while BDI with three-transistor cascode amplifier for long wave(LW). By adopting the 0.35μm 2P4M mixed signal process, the circuit architecture can make the effective charge capacity of 7.8Me- per pixel with 2.2V output range for MW and 7.3 Me- per pixel with 2.6V output range for LW. According to the simulation results, this circuit works well under 5V power supply and achieves less than 0.1% nonlinearity.

Algorithm for predicting the evolution of series of dynamics of complex systems in solving information problems

NASA Astrophysics Data System (ADS)

Kasatkina, T. I.; Dushkin, A. V.; Pavlov, V. A.; Shatovkin, R. R.

2018-03-01

In the development of information, systems and programming to predict the series of dynamics, neural network methods have recently been applied. They are more flexible, in comparison with existing analogues and are capable of taking into account the nonlinearities of the series. In this paper, we propose a modified algorithm for predicting the series of dynamics, which includes a method for training neural networks, an approach to describing and presenting input data, based on the prediction by the multilayer perceptron method. To construct a neural network, the values of a series of dynamics at the extremum points and time values corresponding to them, formed based on the sliding window method, are used as input data. The proposed algorithm can act as an independent approach to predicting the series of dynamics, and be one of the parts of the forecasting system. The efficiency of predicting the evolution of the dynamics series for a short-term one-step and long-term multi-step forecast by the classical multilayer perceptron method and a modified algorithm using synthetic and real data is compared. The result of this modification was the minimization of the magnitude of the iterative error that arises from the previously predicted inputs to the inputs to the neural network, as well as the increase in the accuracy of the iterative prediction of the neural network.

Age-Related Differences in Cortical and Subcortical Activities during Observation and Motor Imagery of Dynamic Postural Tasks: An fMRI Study.

PubMed

Mouthon, A; Ruffieux, J; Mouthon, M; Hoogewoud, H-M; Annoni, J-M; Taube, W

2018-01-01

Age-related changes in brain activation other than in the primary motor cortex are not well known with respect to dynamic balance control. Therefore, the current study aimed to explore age-related differences in the control of static and dynamic postural tasks using fMRI during mental simulation of balance tasks. For this purpose, 16 elderly (72 ± 5 years) and 16 young adults (27 ± 5 years) were asked to mentally simulate a static and a dynamic balance task by motor imagery (MI), action observation (AO), or the combination of AO and MI (AO + MI). Age-related differences were detected in the form of larger brain activations in elderly compared to young participants, especially in the challenging dynamic task when applying AO + MI. Interestingly, when MI (no visual input) was contrasted to AO (visual input), elderly participants revealed deactivation of subcortical areas. The finding that the elderly demonstrated overactivation in mostly cortical areas in challenging postural conditions with visual input (AO + MI and AO) but deactivation in subcortical areas during MI (no vision) may indicate that elderly individuals allocate more cortical resources to the internal representation of dynamic postural tasks. Furthermore, it might be assumed that they depend more strongly on visual input to activate subcortical internal representations.

Age-Related Differences in Cortical and Subcortical Activities during Observation and Motor Imagery of Dynamic Postural Tasks: An fMRI Study

PubMed Central

Ruffieux, J.; Mouthon, M.; Hoogewoud, H.-M.; Taube, W.

2018-01-01

Age-related changes in brain activation other than in the primary motor cortex are not well known with respect to dynamic balance control. Therefore, the current study aimed to explore age-related differences in the control of static and dynamic postural tasks using fMRI during mental simulation of balance tasks. For this purpose, 16 elderly (72 ± 5 years) and 16 young adults (27 ± 5 years) were asked to mentally simulate a static and a dynamic balance task by motor imagery (MI), action observation (AO), or the combination of AO and MI (AO + MI). Age-related differences were detected in the form of larger brain activations in elderly compared to young participants, especially in the challenging dynamic task when applying AO + MI. Interestingly, when MI (no visual input) was contrasted to AO (visual input), elderly participants revealed deactivation of subcortical areas. The finding that the elderly demonstrated overactivation in mostly cortical areas in challenging postural conditions with visual input (AO + MI and AO) but deactivation in subcortical areas during MI (no vision) may indicate that elderly individuals allocate more cortical resources to the internal representation of dynamic postural tasks. Furthermore, it might be assumed that they depend more strongly on visual input to activate subcortical internal representations. PMID:29675037

Nonlinear Dynamic Models in Advanced Life Support

NASA Technical Reports Server (NTRS)

Jones, Harry

2002-01-01

To facilitate analysis, ALS systems are often assumed to be linear and time invariant, but they usually have important nonlinear and dynamic aspects. Nonlinear dynamic behavior can be caused by time varying inputs, changes in system parameters, nonlinear system functions, closed loop feedback delays, and limits on buffer storage or processing rates. Dynamic models are usually cataloged according to the number of state variables. The simplest dynamic models are linear, using only integration, multiplication, addition, and subtraction of the state variables. A general linear model with only two state variables can produce all the possible dynamic behavior of linear systems with many state variables, including stability, oscillation, or exponential growth and decay. Linear systems can be described using mathematical analysis. Nonlinear dynamics can be fully explored only by computer simulations of models. Unexpected behavior is produced by simple models having only two or three state variables with simple mathematical relations between them. Closed loop feedback delays are a major source of system instability. Exceeding limits on buffer storage or processing rates forces systems to change operating mode. Different equilibrium points may be reached from different initial conditions. Instead of one stable equilibrium point, the system may have several equilibrium points, oscillate at different frequencies, or even behave chaotically, depending on the system inputs and initial conditions. The frequency spectrum of an output oscillation may contain harmonics and the sums and differences of input frequencies, but it may also contain a stable limit cycle oscillation not related to input frequencies. We must investigate the nonlinear dynamic aspects of advanced life support systems to understand and counter undesirable behavior.

Effect of scaled Gaussian width (SGW) on fragment flow and multifragmentation in heavy-ion collisions

NASA Astrophysics Data System (ADS)

Rajni; Kumar, Suneel

2012-02-01

We have analyzed the role of interaction range on multifragmentation within the isospin-dependent quantum molecular dynamic (IQMD) model. We find that the effect of width of Gaussian wave packet associated with a nucleon depends on the mass of the colliding system. For a given set of input parameters, we find that width has a sizable effect. At the same time, we know that a different set of parameters can influence the reaction dynamics drastically. Hence, in our opinion it may not be possible to pin down the width to a very narrow level. A systematic study of mass effect ( 197Au, 124La, 124Sn, 107Sn in the breakup of a projectile spectator at intermediate energies has been performed. We also studied the disapperance of flow which demonstrates the effect of the scaled Gaussian width (SGW). Our studies shows that SGW influences the reaction dynamics.

Computation in Dynamically Bounded Asymmetric Systems

PubMed Central

Rutishauser, Ueli; Slotine, Jean-Jacques; Douglas, Rodney

2015-01-01

Previous explanations of computations performed by recurrent networks have focused on symmetrically connected saturating neurons and their convergence toward attractors. Here we analyze the behavior of asymmetrical connected networks of linear threshold neurons, whose positive response is unbounded. We show that, for a wide range of parameters, this asymmetry brings interesting and computationally useful dynamical properties. When driven by input, the network explores potential solutions through highly unstable ‘expansion’ dynamics. This expansion is steered and constrained by negative divergence of the dynamics, which ensures that the dimensionality of the solution space continues to reduce until an acceptable solution manifold is reached. Then the system contracts stably on this manifold towards its final solution trajectory. The unstable positive feedback and cross inhibition that underlie expansion and divergence are common motifs in molecular and neuronal networks. Therefore we propose that very simple organizational constraints that combine these motifs can lead to spontaneous computation and so to the spontaneous modification of entropy that is characteristic of living systems. PMID:25617645

Fuzzy Counter Propagation Neural Network Control for a Class of Nonlinear Dynamical Systems

PubMed Central

Sakhre, Vandana; Jain, Sanjeev; Sapkal, Vilas S.; Agarwal, Dev P.

2015-01-01

Fuzzy Counter Propagation Neural Network (FCPN) controller design is developed, for a class of nonlinear dynamical systems. In this process, the weight connecting between the instar and outstar, that is, input-hidden and hidden-output layer, respectively, is adjusted by using Fuzzy Competitive Learning (FCL). FCL paradigm adopts the principle of learning, which is used to calculate Best Matched Node (BMN) which is proposed. This strategy offers a robust control of nonlinear dynamical systems. FCPN is compared with the existing network like Dynamic Network (DN) and Back Propagation Network (BPN) on the basis of Mean Absolute Error (MAE), Mean Square Error (MSE), Best Fit Rate (BFR), and so forth. It envisages that the proposed FCPN gives better results than DN and BPN. The effectiveness of the proposed FCPN algorithms is demonstrated through simulations of four nonlinear dynamical systems and multiple input and single output (MISO) and a single input and single output (SISO) gas furnace Box-Jenkins time series data. PMID:26366169

Fuzzy Counter Propagation Neural Network Control for a Class of Nonlinear Dynamical Systems.

PubMed

Sakhre, Vandana; Jain, Sanjeev; Sapkal, Vilas S; Agarwal, Dev P

2015-01-01

Fuzzy Counter Propagation Neural Network (FCPN) controller design is developed, for a class of nonlinear dynamical systems. In this process, the weight connecting between the instar and outstar, that is, input-hidden and hidden-output layer, respectively, is adjusted by using Fuzzy Competitive Learning (FCL). FCL paradigm adopts the principle of learning, which is used to calculate Best Matched Node (BMN) which is proposed. This strategy offers a robust control of nonlinear dynamical systems. FCPN is compared with the existing network like Dynamic Network (DN) and Back Propagation Network (BPN) on the basis of Mean Absolute Error (MAE), Mean Square Error (MSE), Best Fit Rate (BFR), and so forth. It envisages that the proposed FCPN gives better results than DN and BPN. The effectiveness of the proposed FCPN algorithms is demonstrated through simulations of four nonlinear dynamical systems and multiple input and single output (MISO) and a single input and single output (SISO) gas furnace Box-Jenkins time series data.

The Impact of Structural Heterogeneity on Excitation-Inhibition Balance in Cortical Networks.

PubMed

Landau, Itamar D; Egger, Robert; Dercksen, Vincent J; Oberlaender, Marcel; Sompolinsky, Haim

2016-12-07

Models of cortical dynamics often assume a homogeneous connectivity structure. However, we show that heterogeneous input connectivity can prevent the dynamic balance between excitation and inhibition, a hallmark of cortical dynamics, and yield unrealistically sparse and temporally regular firing. Anatomically based estimates of the connectivity of layer 4 (L4) rat barrel cortex and numerical simulations of this circuit indicate that the local network possesses substantial heterogeneity in input connectivity, sufficient to disrupt excitation-inhibition balance. We show that homeostatic plasticity in inhibitory synapses can align the functional connectivity to compensate for structural heterogeneity. Alternatively, spike-frequency adaptation can give rise to a novel state in which local firing rates adjust dynamically so that adaptation currents and synaptic inputs are balanced. This theory is supported by simulations of L4 barrel cortex during spontaneous and stimulus-evoked conditions. Our study shows how synaptic and cellular mechanisms yield fluctuation-driven dynamics despite structural heterogeneity in cortical circuits. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Dynamic range considerations for EUV MAMA detectors. [Extreme UV Multianode Microchannel Array

NASA Technical Reports Server (NTRS)

Illing, Rainer M. E.; Bybee, Richard L.; Timothy, J. G.

1990-01-01

The multianode microchannel array (MAMA) has been chosen as the detector for two instruments on the ESA/NASA Solar Heliospheric Observatory. The response of the MAMA to the two extreme types of solar spectra, disk and corona, have been modeled with a view toward evaluating dynamic range effects present. The method of MAMA operation is discussed, with emphasis given to modeling the effect of electron cloud charge spreading to several detector anodes and amplifiers (n-fold events). Representative synthetic EUV spectra have been created. The detector response to these spectra is modeled by dissecting the input photon radiation field across the detector array into contributions to the various amplifier channels. The results of this dissection are shown for spectral regions across the entire wavelength region of interest. These results are used to identify regions in which total array photon counting rate or individual amplifier rate may exceed the design limits. This allows the design or operational modes to be tailored to eliminate the problem areas.

A low-power integrated humidity CMOS sensor by printing-on-chip technology.

PubMed

Lee, Chang-Hung; Chuang, Wen-Yu; Cowan, Melissa A; Wu, Wen-Jung; Lin, Chih-Ting

2014-05-23

A low-power, wide-dynamic-range integrated humidity sensing chip is implemented using a printable polymer sensing material with an on-chip pulse-width-modulation interface circuit. By using the inkjet printing technique, poly(3,4-ethylene-dioxythiophene)/polystyrene sulfonate that has humidity sensing features can be printed onto the top metal layer of a 0.35 μm CMOS IC. The developed printing-on-chip humidity sensor achieves a heterogeneous three dimensional sensor system-on-chip architecture. The humidity sensing of the implemented printing-on-chip sensor system is experimentally tested. The sensor shows a sensitivity of 0.98% to humidity in the atmosphere. The maximum dynamic range of the readout circuit is 9.8 MΩ, which can be further tuned by the frequency of input signal to fit the requirement of the resistance of printed sensor. The power consumption keeps only 154 μW. This printing-on-chip sensor provides a practical solution to fulfill an ultra-small integrated sensor for the applications in miniaturized sensing systems.

A Low-Power Integrated Humidity CMOS Sensor by Printing-on-Chip Technology

PubMed Central

Lee, Chang-Hung; Chuang, Wen-Yu; Cowan, Melissa A.; Wu, Wen-Jung; Lin, Chih-Ting

2014-01-01

A low-power, wide-dynamic-range integrated humidity sensing chip is implemented using a printable polymer sensing material with an on-chip pulse-width-modulation interface circuit. By using the inkjet printing technique, poly(3,4-ethylene-dioxythiophene)/polystyrene sulfonate that has humidity sensing features can be printed onto the top metal layer of a 0.35 μm CMOS IC. The developed printing-on-chip humidity sensor achieves a heterogeneous three dimensional sensor system-on-chip architecture. The humidity sensing of the implemented printing-on-chip sensor system is experimentally tested. The sensor shows a sensitivity of 0.98% to humidity in the atmosphere. The maximum dynamic range of the readout circuit is 9.8 MΩ, which can be further tuned by the frequency of input signal to fit the requirement of the resistance of printed sensor. The power consumption keeps only 154 μW. This printing-on-chip sensor provides a practical solution to fulfill an ultra-small integrated sensor for the applications in miniaturized sensing systems. PMID:24859027

Driver steering dynamics measured in car simulator under a range of visibility and roadmaking conditions

NASA Technical Reports Server (NTRS)

Allen, R. W.; Mcruer, D. T.

1977-01-01

A simulation experiment was conducted to determine the effect of reduced visibility on driver lateral (steering) control. The simulator included a real car cab and a single lane road image projected on a screen six feet in front of the driver. Simulated equations of motion controlled apparent car lane position in response to driver steering actions, wind gusts, and road curvature. Six drivers experienced a range of visibility conditions at various speeds with assorted roadmaking configurations (mark and gap lengths). Driver describing functions were measured and detailed parametric model fits were determined. A pursuit model employing a road curvature feedforward was very effective in explaining driver behavior in following randomly curving roads. Sampled-data concepts were also effective in explaining the combined effects of reduced visibility and intermittent road markings on the driver's dynamic time delay. The results indicate the relative importance of various perceptual variables as the visual input to the driver's steering control process is changed.

High dynamic range algorithm based on HSI color space

NASA Astrophysics Data System (ADS)

Zhang, Jiancheng; Liu, Xiaohua; Dong, Liquan; Zhao, Yuejin; Liu, Ming

2014-10-01

This paper presents a High Dynamic Range algorithm based on HSI color space. To keep hue and saturation of original image and conform to human eye vision effect is the first problem, convert the input image data to HSI color space which include intensity dimensionality. To raise the speed of the algorithm is the second problem, use integral image figure out the average of every pixel intensity value under a certain scale, as local intensity component of the image, and figure out detail intensity component. To adjust the overall image intensity is the third problem, we can get an S type curve according to the original image information, adjust the local intensity component according to the S type curve. To enhance detail information is the fourth problem, adjust the detail intensity component according to the curve designed in advance. The weighted sum of local intensity component after adjusted and detail intensity component after adjusted is final intensity. Converting synthetic intensity and other two dimensionality to output color space can get final processed image.

A model of anuran auditory periphery reveals frequency-dependent adaptation to be a contributing mechanism for two-tone suppression and amplitude modulation coding.

PubMed

Wotton, J M; Ferragamo, M J

2011-10-01

Anuran auditory nerve fibers (ANF) tuned to low frequencies display unusual frequency-dependent adaptation which results in a more phasic response to signals above best frequency (BF) and a more tonic response to signals below. A network model of the first two layers of the anuran auditory system was used to test the contribution of this dynamic peripheral adaptation on two-tone suppression and amplitude modulation (AM) tuning. The model included a peripheral sandwich component, leaky-integrate-and-fire cells and adaptation was implemented by means of a non-linear increase in threshold weighted by the signal frequency. The results of simulations showed that frequency-dependent adaptation was both necessary and sufficient to produce high-frequency-side two-tone suppression for the ANF and cells of the dorsal medullary nucleus (DMN). It seems likely that both suppression and this dynamic adaptation share a common mechanism. The response of ANFs to AM signals was influenced by adaptation and carrier frequency. Vector strength synchronization to an AM signal improved with increased adaptation. The spike rate response to a carrier at BF was the expected flat function with AM rate. However, for non-BF carrier frequencies the response showed a weak band-pass pattern due to the influence of signal sidebands and adaptation. The DMN received inputs from three ANFs and when the frequency tuning of inputs was near the carrier, then the rate response was a low-pass or all-pass shape. When most of the inputs were biased above or below the carrier, then band-pass responses were observed. Frequency-dependent adaptation enhanced the band-pass tuning for AM rate, particularly when the response of the inputs was predominantly phasic for a given carrier. Different combinations of inputs can therefore bias a DMN cell to be especially well suited to detect specific ranges of AM rates for a particular carrier frequency. Such selection of inputs would clearly be advantageous to the frog in recognizing distinct spectral and temporal parameters in communication calls. Copyright © 2011 Elsevier B.V. All rights reserved.

Attention model of binocular rivalry

PubMed Central

Rankin, James; Rinzel, John; Carrasco, Marisa; Heeger, David J.

2017-01-01

When the corresponding retinal locations in the two eyes are presented with incompatible images, a stable percept gives way to perceptual alternations in which the two images compete for perceptual dominance. As perceptual experience evolves dynamically under constant external inputs, binocular rivalry has been used for studying intrinsic cortical computations and for understanding how the brain regulates competing inputs. Converging behavioral and EEG results have shown that binocular rivalry and attention are intertwined: binocular rivalry ceases when attention is diverted away from the rivalry stimuli. In addition, the competing image in one eye suppresses the target in the other eye through a pattern of gain changes similar to those induced by attention. These results require a revision of the current computational theories of binocular rivalry, in which the role of attention is ignored. Here, we provide a computational model of binocular rivalry. In the model, competition between two images in rivalry is driven by both attentional modulation and mutual inhibition, which have distinct selectivity (feature vs. eye of origin) and dynamics (relatively slow vs. relatively fast). The proposed model explains a wide range of phenomena reported in rivalry, including the three hallmarks: (i) binocular rivalry requires attention; (ii) various perceptual states emerge when the two images are swapped between the eyes multiple times per second; (iii) the dominance duration as a function of input strength follows Levelt’s propositions. With a bifurcation analysis, we identified the parameter space in which the model’s behavior was consistent with experimental results. PMID:28696323

Dynamic modal estimation using instrumental variables

NASA Technical Reports Server (NTRS)

Salzwedel, H.

1980-01-01

A method to determine the modes of dynamical systems is described. The inputs and outputs of a system are Fourier transformed and averaged to reduce the error level. An instrumental variable method that estimates modal parameters from multiple correlations between responses of single input, multiple output systems is applied to estimate aircraft, spacecraft, and off-shore platform modal parameters.

Leaf-litter inputs from an invasive nitrogen-fixing tree influence organic-matter dynamics and nitrogen inputs in a Hawaiian river

Treesearch

Richard A. MacKenzie; Tracy N. Wiegner; Frances Kinslow; Nicole Cormier; Ayron M. Strauch

2013-01-01

Abstract. We examined how invasion of tropical riparian forests by an exotic N-fixing tree (Falcataria moluccana) affects organic-matter dynamics in a Hawaiian river by comparing early stages of leaf-litter breakdown between the exotic F. moluccana and native Metrosideros polymorpha trees. We examined early...

New multirate sampled-data control law structure and synthesis algorithm

NASA Technical Reports Server (NTRS)

Berg, Martin C.; Mason, Gregory S.; Yang, Gen-Sheng

1992-01-01

A new multirate sampled-data control law structure is defined and a new parameter-optimization-based synthesis algorithm for that structure is introduced. The synthesis algorithm can be applied to multirate, multiple-input/multiple-output, sampled-data control laws having a prescribed dynamic order and structure, and a priori specified sampling/update rates for all sensors, processor states, and control inputs. The synthesis algorithm is applied to design two-input, two-output tip position controllers of various dynamic orders for a sixth-order, two-link robot arm model.

Development and validation of the European Cluster Assimilation Techniques run libraries

NASA Astrophysics Data System (ADS)

Facskó, G.; Gordeev, E.; Palmroth, M.; Honkonen, I.; Janhunen, P.; Sergeev, V.; Kauristie, K.; Milan, S.

2012-04-01

The European Commission funded the European Cluster Assimilation Techniques (ECLAT) project as a collaboration of five leader European universities and research institutes. A main contribution of the Finnish Meteorological Institute (FMI) is to provide a wide range global MHD runs with the Grand Unified Magnetosphere Ionosphere Coupling simulation (GUMICS). The runs are divided in two categories: Synthetic runs investigating the extent of solar wind drivers that can influence magnetospheric dynamics, as well as dynamic runs using measured solar wind data as input. Here we consider the first set of runs with synthetic solar wind input. The solar wind density, velocity and the interplanetary magnetic field had different magnitudes and orientations; furthermore two F10.7 flux values were selected for solar radiation minimum and maximum values. The solar wind parameter values were constant such that a constant stable solution was archived. All configurations were run several times with three different (-15°, 0°, +15°) tilt angles in the GSE X-Z plane. The result of the 192 simulations named so called "synthetic run library" were visualized and uploaded to the homepage of the FMI after validation. Here we present details of these runs.

Simulating soil phosphorus dynamics for a phosphorus loss quantification tool.

PubMed

Vadas, Peter A; Joern, Brad C; Moore, Philip A

2012-01-01

Pollution of fresh waters by agricultural phosphorus (P) is a water quality concern. Because soils can contribute significantly to P loss in runoff, it is important to assess how management affects soil P status over time, which is often done with models. Our objective was to describe and validate soil P dynamics in the Annual P Loss Estimator (APLE) model. APLE is a user-friendly spreadsheet model that simulates P loss in runoff and soil P dynamics over 10 yr for a given set of runoff, erosion, and management conditions. For soil P dynamics, APLE simulates two layers in the topsoil, each with three inorganic P pools and one organic P pool. It simulates P additions to soil from manure and fertilizer, distribution among pools, mixing between layers due to tillage and bioturbation, leaching between and out of layers, crop P removal, and loss by surface runoff and erosion. We used soil P data from 25 published studies to validate APLE's soil P processes. Our results show that APLE reliably simulated soil P dynamics for a wide range of soil properties, soil depths, P application sources and rates, durations, soil P contents, and management practices. We validated APLE specifically for situations where soil P was increasing from excessive P inputs, where soil P was decreasing due to greater outputs than inputs, and where soil P stratification occurred in no-till and pasture soils. Successful simulations demonstrate APLE's potential to be applied to major management scenarios related to soil P loss in runoff and erosion. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Mechanisms of Gain Control by Voltage-Gated Channels in Intrinsically-Firing Neurons

PubMed Central

Patel, Ameera X.; Burdakov, Denis

2015-01-01

Gain modulation is a key feature of neural information processing, but underlying mechanisms remain unclear. In single neurons, gain can be measured as the slope of the current-frequency (input-output) relationship over any given range of inputs. While much work has focused on the control of basal firing rates and spike rate adaptation, gain control has been relatively unstudied. Of the limited studies on gain control, some have examined the roles of synaptic noise and passive somatic currents, but the roles of voltage-gated channels present ubiquitously in neurons have been less explored. Here, we systematically examined the relationship between gain and voltage-gated ion channels in a conductance-based, tonically-active, model neuron. Changes in expression (conductance density) of voltage-gated channels increased (Ca2+ channel), reduced (K+ channels), or produced little effect (h-type channel) on gain. We found that the gain-controlling ability of channels increased exponentially with the steepness of their activation within the dynamic voltage window (voltage range associated with firing). For depolarization-activated channels, this produced a greater channel current per action potential at higher firing rates. This allowed these channels to modulate gain by contributing to firing preferentially at states of higher excitation. A finer analysis of the current-voltage relationship during tonic firing identified narrow voltage windows at which the gain-modulating channels exerted their effects. As a proof of concept, we show that h-type channels can be tuned to modulate gain by changing the steepness of their activation within the dynamic voltage window. These results show how the impact of an ion channel on gain can be predicted from the relationship between channel kinetics and the membrane potential during firing. This is potentially relevant to understanding input-output scaling in a wide class of neurons found throughout the brain and other nervous systems. PMID:25816008

Modeling the Potential Effects of New Tobacco Products and Policies. A Dynamic Population Model for Multiple Product Use and Harm

DOE PAGES

Vugrin, Eric D.; Rostron, Brian L.; Verzi, Stephen J.; ...

2015-03-27

Background Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. Methods and Findings We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use formore » the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Conclusion Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health outcomes such as morbidity and disability.« less

Modeling the Potential Effects of New Tobacco Products and Policies: A Dynamic Population Model for Multiple Product Use and Harm

PubMed Central

Vugrin, Eric D.; Rostron, Brian L.; Verzi, Stephen J.; Brodsky, Nancy S.; Brown, Theresa J.; Choiniere, Conrad J.; Coleman, Blair N.; Paredes, Antonio; Apelberg, Benjamin J.

2015-01-01

Background Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. Methods and Findings We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use for the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Conclusion Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health outcomes such as morbidity and disability. PMID:25815840

Modeling the potential effects of new tobacco products and policies: a dynamic population model for multiple product use and harm.

PubMed

Vugrin, Eric D; Rostron, Brian L; Verzi, Stephen J; Brodsky, Nancy S; Brown, Theresa J; Choiniere, Conrad J; Coleman, Blair N; Paredes, Antonio; Apelberg, Benjamin J

2015-01-01

Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use for the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health outcomes such as morbidity and disability.

Modeling the Potential Effects of New Tobacco Products and Policies. A Dynamic Population Model for Multiple Product Use and Harm

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

Vugrin, Eric D.; Rostron, Brian L.; Verzi, Stephen J.

Background Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. Methods and Findings We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use formore » the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Conclusion Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health outcomes such as morbidity and disability.« less

Dynamic sensitivity analysis of biological systems

PubMed Central

Wu, Wu Hsiung; Wang, Feng Sheng; Chang, Maw Shang

2008-01-01

Background A mathematical model to understand, predict, control, or even design a real biological system is a central theme in systems biology. A dynamic biological system is always modeled as a nonlinear ordinary differential equation (ODE) system. How to simulate the dynamic behavior and dynamic parameter sensitivities of systems described by ODEs efficiently and accurately is a critical job. In many practical applications, e.g., the fed-batch fermentation systems, the system admissible input (corresponding to independent variables of the system) can be time-dependent. The main difficulty for investigating the dynamic log gains of these systems is the infinite dimension due to the time-dependent input. The classical dynamic sensitivity analysis does not take into account this case for the dynamic log gains. Results We present an algorithm with an adaptive step size control that can be used for computing the solution and dynamic sensitivities of an autonomous ODE system simultaneously. Although our algorithm is one of the decouple direct methods in computing dynamic sensitivities of an ODE system, the step size determined by model equations can be used on the computations of the time profile and dynamic sensitivities with moderate accuracy even when sensitivity equations are more stiff than model equations. To show this algorithm can perform the dynamic sensitivity analysis on very stiff ODE systems with moderate accuracy, it is implemented and applied to two sets of chemical reactions: pyrolysis of ethane and oxidation of formaldehyde. The accuracy of this algorithm is demonstrated by comparing the dynamic parameter sensitivities obtained from this new algorithm and from the direct method with Rosenbrock stiff integrator based on the indirect method. The same dynamic sensitivity analysis was performed on an ethanol fed-batch fermentation system with a time-varying feed rate to evaluate the applicability of the algorithm to realistic models with time-dependent admissible input. Conclusion By combining the accuracy we show with the efficiency of being a decouple direct method, our algorithm is an excellent method for computing dynamic parameter sensitivities in stiff problems. We extend the scope of classical dynamic sensitivity analysis to the investigation of dynamic log gains of models with time-dependent admissible input. PMID:19091016

Bistability and up/down state alternations in inhibition-dominated randomly connected networks of LIF neurons.

PubMed

Tartaglia, Elisa M; Brunel, Nicolas

2017-09-20

Electrophysiological recordings in cortex in vivo have revealed a rich variety of dynamical regimes ranging from irregular asynchronous states to a diversity of synchronized states, depending on species, anesthesia, and external stimulation. The average population firing rate in these states is typically low. We study analytically and numerically a network of sparsely connected excitatory and inhibitory integrate-and-fire neurons in the inhibition-dominated, low firing rate regime. For sufficiently high values of the external input, the network exhibits an asynchronous low firing frequency state (L). Depending on synaptic time constants, we show that two scenarios may occur when external inputs are decreased: (1) the L state can destabilize through a Hopf bifucation as the external input is decreased, leading to synchronized oscillations spanning d δ to β frequencies; (2) the network can reach a bistable region, between the low firing frequency network state (L) and a quiescent one (Q). Adding an adaptation current to excitatory neurons leads to spontaneous alternations between L and Q states, similar to experimental observations on UP and DOWN states alternations.

Integration of a versatile bridge concept in a 34 GHz pulsed/CW EPR spectrometer.

PubMed

Band, Alan; Donohue, Matthew P; Epel, Boris; Madhu, Shraeya; Szalai, Veronika A

2018-03-01

We present a 34 GHz continuous wave (CW)/pulsed electron paramagnetic resonance (EPR) spectrometer capable of pulse-shaping that is based on a versatile microwave bridge design. The bridge radio frequency (RF)-in/RF-out design (500 MHz to 1 GHz input/output passband, 500 MHz instantaneous input/output bandwidth) creates a flexible platform with which to compare a variety of excitation and detection methods utilizing commercially available equipment external to the bridge. We use three sources of RF input to implement typical functions associated with CW and pulse EPR spectroscopic measurements. The bridge output is processed via high speed digitizer and an in-phase/quadrature (I/Q) demodulator for pulsed work or sent to a wideband, high dynamic range log detector for CW. Combining this bridge with additional commercial hardware and new acquisition and control electronics, we have designed and constructed an adaptable EPR spectrometer that builds upon previous work in the literature and is functionally comparable to other available systems. Published by Elsevier Inc.

Membrane voltage fluctuations reduce spike frequency adaptation and preserve output gain in CA1 pyramidal neurons in a high conductance state

PubMed Central

Fernandez, Fernando R.; Broicher, Tilman; Truong, Alan; White, John A.

2011-01-01

Modulating the gain of the input-output function of neurons is critical for processing of stimuli and network dynamics. Previous gain control mechanisms have suggested that voltage fluctuations play a key role in determining neuronal gain in vivo. Here we show that, under increased membrane conductance, voltage fluctuations restore Na+ current and reduce spike frequency adaptation in rat hippocampal CA1 pyramidal neurons in vitro. As a consequence, membrane voltage fluctuations produce a leftward shift in the f-I relationship without a change in gain, relative to an increase in conductance alone. Furthermore, we show that these changes have important implications for the integration of inhibitory inputs. Due to the ability to restore Na+ current, hyperpolarizing membrane voltage fluctuations mediated by GABAA-like inputs can increase firing rate in a high conductance state. Finally, our data show that the effects on gain and synaptic integration are mediated by voltage fluctuations within a physiologically relevant range of frequencies (10–40 Hz). PMID:21389243

Delayed excitatory and inhibitory feedback shape neural information transmission

NASA Astrophysics Data System (ADS)

Chacron, Maurice J.; Longtin, André; Maler, Leonard

2005-11-01

Feedback circuitry with conduction and synaptic delays is ubiquitous in the nervous system. Yet the effects of delayed feedback on sensory processing of natural signals are poorly understood. This study explores the consequences of delayed excitatory and inhibitory feedback inputs on the processing of sensory information. We show, through numerical simulations and theory, that excitatory and inhibitory feedback can alter the firing frequency response of stochastic neurons in opposite ways by creating dynamical resonances, which in turn lead to information resonances (i.e., increased information transfer for specific ranges of input frequencies). The resonances are created at the expense of decreased information transfer in other frequency ranges. Using linear response theory for stochastically firing neurons, we explain how feedback signals shape the neural transfer function for a single neuron as a function of network size. We also find that balanced excitatory and inhibitory feedback can further enhance information tuning while maintaining a constant mean firing rate. Finally, we apply this theory to in vivo experimental data from weakly electric fish in which the feedback loop can be opened. We show that it qualitatively predicts the observed effects of inhibitory feedback. Our study of feedback excitation and inhibition reveals a possible mechanism by which optimal processing may be achieved over selected frequency ranges.

Computer program system for dynamic simulation and stability analysis of passive and actively controlled spacecraft. Volume 1. Theory

NASA Technical Reports Server (NTRS)

Bodley, C. S.; Devers, D. A.; Park, C. A.

1975-01-01

A theoretical development and associated digital computer program system is presented. The dynamic system (spacecraft) is modeled as an assembly of rigid and/or flexible bodies not necessarily in a topological tree configuration. The computer program system may be used to investigate total system dynamic characteristics including interaction effects between rigid and/or flexible bodies, control systems, and a wide range of environmental loadings. Additionally, the program system may be used for design of attitude control systems and for evaluation of total dynamic system performance including time domain response and frequency domain stability analyses. Volume 1 presents the theoretical developments including a description of the physical system, the equations of dynamic equilibrium, discussion of kinematics and system topology, a complete treatment of momentum wheel coupling, and a discussion of gravity gradient and environmental effects. Volume 2, is a program users' guide and includes a description of the overall digital program code, individual subroutines and a description of required program input and generated program output. Volume 3 presents the results of selected demonstration problems that illustrate all program system capabilities.

Gait-force model and inertial measurement unit-based measurements: A new approach for gait analysis and balance monitoring.

PubMed

Li, Xinan; Xu, Hongyuan; Cheung, Jeffrey T

2016-12-01

This work describes a new approach for gait analysis and balance measurement. It uses an inertial measurement unit (IMU) that can either be embedded inside a dynamically unstable platform for balance measurement or mounted on the lower back of a human participant for gait analysis. The acceleration data along three Cartesian coordinates is analyzed by the gait-force model to extract bio-mechanics information in both the dynamic state as in the gait analyzer and the steady state as in the balance scale. For the gait analyzer, the simple, noninvasive and versatile approach makes it appealing to a broad range of applications in clinical diagnosis, rehabilitation monitoring, athletic training, sport-apparel design, and many other areas. For the balance scale, it provides a portable platform to measure the postural deviation and the balance index under visual or vestibular sensory input conditions. Despite its simple construction and operation, excellent agreement has been demonstrated between its performance and the high-cost commercial balance unit over a wide dynamic range. The portable balance scale is an ideal tool for routine monitoring of balance index, fall-risk assessment, and other balance-related health issues for both clinical and household use.

New feature of the neutron color image intensifier

NASA Astrophysics Data System (ADS)

Nittoh, Koichi; Konagai, Chikara; Noji, Takashi; Miyabe, Keisuke

2009-06-01

We developed prototype neutron color image intensifiers with high-sensitivity, wide dynamic range and long-life characteristics. In the prototype intensifier (Gd-Type 1), a terbium-activated Gd 2O 2S is used as the input-screen phosphor. In the upgraded model (Gd-Type 2), Gd 2O 3 and CsI:Na are vacuum deposited to form the phosphor layer, which improved the sensitivity and the spatial uniformity. A europium-activated Y 2O 2S multi-color scintillator, emitting red, green and blue photons with different intensities, is utilized as the output screen of the intensifier. By combining this image intensifier with a suitably tuned high-sensitive color CCD camera, higher sensitivity and wider dynamic range could be simultaneously attained than that of the conventional P20-phosphor-type image intensifier. The results of experiments at the JRR-3M neutron radiography irradiation port (flux: 1.5×10 8 n/cm 2/s) showed that these neutron color image intensifiers can clearly image dynamic phenomena with a 30 frame/s video picture. It is expected that the color image intensifier will be used as a new two-dimensional neutron sensor in new application fields.

Binaural model-based dynamic-range compression.

PubMed

Ernst, Stephan M A; Kortlang, Steffen; Grimm, Giso; Bisitz, Thomas; Kollmeier, Birger; Ewert, Stephan D

2018-01-26

Binaural cues such as interaural level differences (ILDs) are used to organise auditory perception and to segregate sound sources in complex acoustical environments. In bilaterally fitted hearing aids, dynamic-range compression operating independently at each ear potentially alters these ILDs, thus distorting binaural perception and sound source segregation. A binaurally-linked model-based fast-acting dynamic compression algorithm designed to approximate the normal-hearing basilar membrane (BM) input-output function in hearing-impaired listeners is suggested. A multi-center evaluation in comparison with an alternative binaural and two bilateral fittings was performed to assess the effect of binaural synchronisation on (a) speech intelligibility and (b) perceived quality in realistic conditions. 30 and 12 hearing impaired (HI) listeners were aided individually with the algorithms for both experimental parts, respectively. A small preference towards the proposed model-based algorithm in the direct quality comparison was found. However, no benefit of binaural-synchronisation regarding speech intelligibility was found, suggesting a dominant role of the better ear in all experimental conditions. The suggested binaural synchronisation of compression algorithms showed a limited effect on the tested outcome measures, however, linking could be situationally beneficial to preserve a natural binaural perception of the acoustical environment.

Fiber optic vibration sensor using bifurcated plastic optical fiber

NASA Astrophysics Data System (ADS)

Abdullah, M.; Bidin, N.; Yasin, M.

2016-11-01

An extrinsic fiber optic vibration sensor is demonstrated for a fiber optic displacement sensor based on a bundled multimode fiber to measure a vibration frequency ranging from 100 until 3000 Hz. The front slope has a sensitivity of 0.1938mV/mm and linearity of 99.7% within a measurement range between 0.15-3.00 mm. By placing the diaphragm of the concave load-speaker within the linear range from the probe, the frequency of the vibration can be measured with error percentage of less than 1.54%. The graph of input against output frequency for low, medium and high frequency range show very high linearity up to 99%. Slope for low, medium, and high frequency range are calculated as 1.0026, 0.9934, and 1.0007 respectively. Simplicity, long term stability, low power consumption, wide dynamic and frequency ranges, noise reduction, ruggedness, linearity and light weight make it promising alternative to other well-establish methods for vibration frequency measurement.

Using computer simulations to determine the limitations of dynamic clamp stimuli applied at the soma in mimicking distributed conductance sources.

PubMed

Lin, Risa J; Jaeger, Dieter

2011-05-01

In previous studies we used the technique of dynamic clamp to study how temporal modulation of inhibitory and excitatory inputs control the frequency and precise timing of spikes in neurons of the deep cerebellar nuclei (DCN). Although this technique is now widely used, it is limited to interpreting conductance inputs as being location independent; i.e., all inputs that are biologically distributed across the dendritic tree are applied to the soma. We used computer simulations of a morphologically realistic model of DCN neurons to compare the effects of purely somatic vs. distributed dendritic inputs in this cell type. We applied the same conductance stimuli used in our published experiments to the model. To simulate variability in neuronal responses to repeated stimuli, we added a somatic white current noise to reproduce subthreshold fluctuations in the membrane potential. We were able to replicate our dynamic clamp results with respect to spike rates and spike precision for different patterns of background synaptic activity. We found only minor differences in the spike pattern generation between focal or distributed input in this cell type even when strong inhibitory or excitatory bursts were applied. However, the location dependence of dynamic clamp stimuli is likely to be different for each cell type examined, and the simulation approach developed in the present study will allow a careful assessment of location dependence in all cell types.

Evaluation of Two Guralp Preamplifiers for GS13 Seismometer Application.

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

Merchant, Bion J.

Sandia National Laboratories has tested and evaluated a new preamplifier, the Guralp Preamplifier for GS13, manufactured by Guralp. These preamplifiers are used to interface between Guralp digitizers and Geotech GS13 Seismometers. The purpose of the preamplifier evaluation was to measure the performance characteristics in such areas as power consumption, input impedance, sensitivity, full scale, self-noise, dynamic range, system noise, response, passband, and timing. The Guralp GS13 Preamplifiers are being evaluated for potential use in the International Monitoring System (IMS) of the Comprehensive Nuclear Test-Ban-Treaty Organization (CTBTO).

Computer modeling and simulation of human movement. Applications in sport and rehabilitation.

PubMed

Neptune, R R

2000-05-01

Computer modeling and simulation of human movement plays an increasingly important role in sport and rehabilitation, with applications ranging from sport equipment design to understanding pathologic gait. The complex dynamic interactions within the musculoskeletal and neuromuscular systems make analyzing human movement with existing experimental techniques difficult but computer modeling and simulation allows for the identification of these complex interactions and causal relationships between input and output variables. This article provides an overview of computer modeling and simulation and presents an example application in the field of rehabilitation.

A Compact 600 GHz Electronically Tunable Vector Measurement System for Submillimeter Wave Imaging

NASA Technical Reports Server (NTRS)

Dengler, Robert J.; Maiwald, Frank; Siegel, Peter H.

2006-01-01

A compact submillimeter wave transmission / reflection measurement system has been demonstrated at 560-635 GHz, with electronic tuning over the entire band. Maximum dynamic range measured at a single frequency is 90 dB (60 dB typical), and phase noise is less than +/- 2(deg). By using a frequency steerable lens at the source output and mixer input, the frequency agility of the system can be used to scan the source and receive beams, resulting in near real-time imaging capability using only a single pixel.

A GPS coverage model

NASA Technical Reports Server (NTRS)

Skidmore, Trent A.

1994-01-01

The results of several case studies using the Global Positioning System coverage model developed at Ohio University are summarized. Presented are results pertaining to outage area, outage dynamics, and availability. Input parameters to the model include the satellite orbit data, service area of interest, geometry requirements, and horizon and antenna mask angles. It is shown for precision-landing Category 1 requirements that the planned GPS 21 Primary Satellite Constellation produces significant outage area and unavailability. It is also shown that a decrease in the user equivalent range error dramatically decreases outage area and improves the service availability.

A parallel VLSI architecture for a digital filter using a number theoretic transform

NASA Technical Reports Server (NTRS)

Truong, T. K.; Reed, I. S.; Yeh, C. S.; Shao, H. M.

1983-01-01

The advantages of a very large scalee integration (VLSI) architecture for implementing a digital filter using fermat number transforms (FNT) are the following: It requires no multiplication. Only additions and bit rotations are needed. It alleviates the usual dynamic range limitation for long sequence FNT's. It utilizes the FNT and inverse FNT circuits 100% of the time. The lengths of the input data and filter sequences can be arbitraty and different. It is regular, simple, and expandable, and as a consequence suitable for VLSI implementation.

Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation.

PubMed

Augustin, Moritz; Ladenbauer, Josef; Baumann, Fabian; Obermayer, Klaus

2017-06-01

The spiking activity of single neurons can be well described by a nonlinear integrate-and-fire model that includes somatic adaptation. When exposed to fluctuating inputs sparsely coupled populations of these model neurons exhibit stochastic collective dynamics that can be effectively characterized using the Fokker-Planck equation. This approach, however, leads to a model with an infinite-dimensional state space and non-standard boundary conditions. Here we derive from that description four simple models for the spike rate dynamics in terms of low-dimensional ordinary differential equations using two different reduction techniques: one uses the spectral decomposition of the Fokker-Planck operator, the other is based on a cascade of two linear filters and a nonlinearity, which are determined from the Fokker-Planck equation and semi-analytically approximated. We evaluate the reduced models for a wide range of biologically plausible input statistics and find that both approximation approaches lead to spike rate models that accurately reproduce the spiking behavior of the underlying adaptive integrate-and-fire population. Particularly the cascade-based models are overall most accurate and robust, especially in the sensitive region of rapidly changing input. For the mean-driven regime, when input fluctuations are not too strong and fast, however, the best performing model is based on the spectral decomposition. The low-dimensional models also well reproduce stable oscillatory spike rate dynamics that are generated either by recurrent synaptic excitation and neuronal adaptation or through delayed inhibitory synaptic feedback. The computational demands of the reduced models are very low but the implementation complexity differs between the different model variants. Therefore we have made available implementations that allow to numerically integrate the low-dimensional spike rate models as well as the Fokker-Planck partial differential equation in efficient ways for arbitrary model parametrizations as open source software. The derived spike rate descriptions retain a direct link to the properties of single neurons, allow for convenient mathematical analyses of network states, and are well suited for application in neural mass/mean-field based brain network models.

Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation

PubMed Central

Baumann, Fabian; Obermayer, Klaus

2017-01-01

The spiking activity of single neurons can be well described by a nonlinear integrate-and-fire model that includes somatic adaptation. When exposed to fluctuating inputs sparsely coupled populations of these model neurons exhibit stochastic collective dynamics that can be effectively characterized using the Fokker-Planck equation. This approach, however, leads to a model with an infinite-dimensional state space and non-standard boundary conditions. Here we derive from that description four simple models for the spike rate dynamics in terms of low-dimensional ordinary differential equations using two different reduction techniques: one uses the spectral decomposition of the Fokker-Planck operator, the other is based on a cascade of two linear filters and a nonlinearity, which are determined from the Fokker-Planck equation and semi-analytically approximated. We evaluate the reduced models for a wide range of biologically plausible input statistics and find that both approximation approaches lead to spike rate models that accurately reproduce the spiking behavior of the underlying adaptive integrate-and-fire population. Particularly the cascade-based models are overall most accurate and robust, especially in the sensitive region of rapidly changing input. For the mean-driven regime, when input fluctuations are not too strong and fast, however, the best performing model is based on the spectral decomposition. The low-dimensional models also well reproduce stable oscillatory spike rate dynamics that are generated either by recurrent synaptic excitation and neuronal adaptation or through delayed inhibitory synaptic feedback. The computational demands of the reduced models are very low but the implementation complexity differs between the different model variants. Therefore we have made available implementations that allow to numerically integrate the low-dimensional spike rate models as well as the Fokker-Planck partial differential equation in efficient ways for arbitrary model parametrizations as open source software. The derived spike rate descriptions retain a direct link to the properties of single neurons, allow for convenient mathematical analyses of network states, and are well suited for application in neural mass/mean-field based brain network models. PMID:28644841

Metabolic liver function measured in vivo by dynamic (18)F-FDGal PET/CT without arterial blood sampling.

PubMed

Horsager, Jacob; Munk, Ole Lajord; Sørensen, Michael

2015-01-01

Metabolic liver function can be measured by dynamic PET/CT with the radio-labelled galactose-analogue 2-[(18)F]fluoro-2-deoxy-D-galactose ((18)F-FDGal) in terms of hepatic systemic clearance of (18)F-FDGal (K, ml blood/ml liver tissue/min). The method requires arterial blood sampling from a radial artery (arterial input function), and the aim of this study was to develop a method for extracting an image-derived, non-invasive input function from a volume of interest (VOI). Dynamic (18)F-FDGal PET/CT data from 16 subjects without liver disease (healthy subjects) and 16 patients with liver cirrhosis were included in the study. Five different input VOIs were tested: four in the abdominal aorta and one in the left ventricle of the heart. Arterial input function from manual blood sampling was available for all subjects. K*-values were calculated using time-activity curves (TACs) from each VOI as input and compared to the K-value calculated using arterial blood samples as input. Each input VOI was tested on PET data reconstructed with and without resolution modelling. All five image-derived input VOIs yielded K*-values that correlated significantly with K calculated using arterial blood samples. Furthermore, TACs from two different VOIs yielded K*-values that did not statistically deviate from K calculated using arterial blood samples. A semicircle drawn in the posterior part of the abdominal aorta was the only VOI that was successful for both healthy subjects and patients as well as for PET data reconstructed with and without resolution modelling. Metabolic liver function using (18)F-FDGal PET/CT can be measured without arterial blood samples by using input data from a semicircle VOI drawn in the posterior part of the abdominal aorta.

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

Using stable isotopes of dissolved oxygen for the determination of gas exchange in the Grand River, Ontario, Canada.

PubMed

Jamieson, Terra S; Schiff, Sherry L; Taylor, William D

2013-02-01

Gas exchange can be a key component of the dissolved oxygen (DO) mass balance in aquatic ecosystems. Quantification of gas transfer rates is essential for the estimation of DO production and consumption rates, and determination of assimilation capacities of systems receiving organic inputs. Currently, the accurate determination of gas transfer rate is a topic of debate in DO modeling, and there are a wide variety of approaches that have been proposed in the literature. The current study investigates the use of repeated measures of stable isotopes of O₂ and DO and a dynamic dual mass-balance model to quantify gas transfer coefficients (k) in the Grand River, Ontario, Canada. Measurements were conducted over a longitudinal gradient that reflected watershed changes from agricultural to urban. Values of k in the Grand River ranged from 3.6 to 8.6 day⁻¹, over discharges ranging from 5.6 to 22.4 m³ s⁻¹, with one high-flow event of 73.1 m³ s⁻¹. The k values were relatively constant over the range of discharge conditions studied. The range in discharge observed in this study is generally representative of non-storm and summer low-flow events; a greater range in k might be observed under a wider range of hydrologic conditions. Overall, k values obtained with the dual model for the Grand River were found to be lower than predicted by the traditional approaches evaluated, highlighting the importance of determining site-specific values of k. The dual mass balance approach provides a more constrained estimate of k than using DO only, and is applicable to large rivers where other approaches would be difficult to use. The addition of an isotopic mass balance provides for a corroboration of the input parameter estimates between the two balances. Constraining the range of potential input values allows for a direct estimate of k in large, productive systems where other k-estimation approaches may be uncertain or logistically infeasible. Copyright © 2012 Elsevier Ltd. All rights reserved.

Input apparatus for dynamic signature verification systems

DOEpatents

EerNisse, Errol P.; Land, Cecil E.; Snelling, Jay B.

1978-01-01

The disclosure relates to signature verification input apparatus comprising a writing instrument and platen containing piezoelectric transducers which generate signals in response to writing pressures.

Orientation dependent modulation of apparent speed: a model based on the dynamics of feed-forward and horizontal connectivity in V1 cortex.

PubMed

Seriès, Peggy; Georges, Sébastien; Lorenceau, Jean; Frégnac, Yves

2002-11-01

Psychophysical and physiological studies suggest that long-range horizontal connections in primary visual cortex participate in spatial integration and contour processing. Until recently, little attention has been paid to their intrinsic temporal properties. Recent physiological studies indicate, however, that the propagation of activity through long-range horizontal connections is slow, with time scales comparable to the perceptual scales involved in motion processing. Using a simple model of V1 connectivity, we explore some of the implications of this slow dynamics. The model predicts that V1 responses to a stimulus in the receptive field can be modulated by a previous stimulation, a few milliseconds to a few tens of milliseconds before, in the surround. We analyze this phenomenon and its possible consequences on speed perception, as a function of the spatio-temporal configuration of the visual inputs (relative orientation, spatial separation, temporal interval between the elements, sequence speed). We show that the dynamical interactions between feed-forward and horizontal signals in V1 can explain why the perceived speed of fast apparent motion sequences strongly depends on the orientation of their elements relative to the motion axis and can account for the range of speed for which this perceptual effect occurs (Georges, Seriès, Frégnac and Lorenceau, this issue).

Dynamic Time Expansion and Compression Using Nonlinear Waveguides

DOEpatents

Findikoglu, Alp T.; Hahn, Sangkoo F.; Jia, Quanxi

2004-06-22

Dynamic time expansion or compression of a small amplitude input signal generated with an initial scale is performed using a nonlinear waveguide. A nonlinear waveguide having a variable refractive index is connected to a bias voltage source having a bias signal amplitude that is large relative to the input signal to vary the reflective index and concomitant speed of propagation of the nonlinear waveguide and an electrical circuit for applying the small amplitude signal and the large amplitude bias signal simultaneously to the nonlinear waveguide. The large amplitude bias signal with the input signal alters the speed of propagation of the small-amplitude signal with time in the nonlinear waveguide to expand or contract the initial time scale of the small-amplitude input signal.

Dynamic time expansion and compression using nonlinear waveguides

DOEpatents

Findikoglu, Alp T [Los Alamos, NM; Hahn, Sangkoo F [Los Alamos, NM; Jia, Quanxi [Los Alamos, NM

2004-06-22

Dynamic time expansion or compression of a small-amplitude input signal generated with an initial scale is performed using a nonlinear waveguide. A nonlinear waveguide having a variable refractive index is connected to a bias voltage source having a bias signal amplitude that is large relative to the input signal to vary the reflective index and concomitant speed of propagation of the nonlinear waveguide and an electrical circuit for applying the small-amplitude signal and the large amplitude bias signal simultaneously to the nonlinear waveguide. The large amplitude bias signal with the input signal alters the speed of propagation of the small-amplitude signal with time in the nonlinear waveguide to expand or contract the initial time scale of the small-amplitude input signal.

Subranging scheme for SQUID sensors

NASA Technical Reports Server (NTRS)

Penanen, Konstantin I. (Inventor)

2008-01-01

A readout scheme for measuring the output from a SQUID-based sensor-array using an improved subranging architecture that includes multiple resolution channels (such as a coarse resolution channel and a fine resolution channel). The scheme employs a flux sensing circuit with a sensing coil connected in series to multiple input coils, each input coil being coupled to a corresponding SQUID detection circuit having a high-resolution SQUID device with independent linearizing feedback. A two-resolution configuration (course and fine) is illustrated with a primary SQUID detection circuit for generating a fine readout, and a secondary SQUID detection circuit for generating a course readout, both having feedback current coupled to the respective SQUID devices via feedback/modulation coils. The primary and secondary SQUID detection circuits function and derive independent feedback. Thus, the SQUID devices may be monitored independently of each other (and read simultaneously) to dramatically increase slew rates and dynamic range.

Competitive inhibition can linearize dose-response and generate a linear rectifier

PubMed Central

Savir, Yonatan; Tu, Benjamin P.; Springer, Michael

2015-01-01

Summary Many biological responses require a dynamic range that is larger than standard bi-molecular interactions allow, yet the also ability to remain off at low input. Here we mathematically show that an enzyme reaction system involving a combination of competitive inhibition, conservation of the total level of substrate and inhibitor, and positive feedback can behave like a linear rectifier—that is, a network motif with an input-output relationship that is linearly sensitive to substrate above a threshold but unresponsive below the threshold. We propose that the evolutionarily conserved yeast SAGA histone acetylation complex may possess the proper physiological response characteristics and molecular interactions needed to perform as a linear rectifier, and we suggest potential experiments to test this hypothesis. One implication of this work is that linear responses and linear rectifiers might be easier to evolve or synthetically construct than is currently appreciated. PMID:26495436

Competitive inhibition can linearize dose-response and generate a linear rectifier.

PubMed

Savir, Yonatan; Tu, Benjamin P; Springer, Michael

2015-09-23

Many biological responses require a dynamic range that is larger than standard bi-molecular interactions allow, yet the also ability to remain off at low input. Here we mathematically show that an enzyme reaction system involving a combination of competitive inhibition, conservation of the total level of substrate and inhibitor, and positive feedback can behave like a linear rectifier-that is, a network motif with an input-output relationship that is linearly sensitive to substrate above a threshold but unresponsive below the threshold. We propose that the evolutionarily conserved yeast SAGA histone acetylation complex may possess the proper physiological response characteristics and molecular interactions needed to perform as a linear rectifier, and we suggest potential experiments to test this hypothesis. One implication of this work is that linear responses and linear rectifiers might be easier to evolve or synthetically construct than is currently appreciated.

Dynamics and fate of SOC in tidal marshes along a salinity gradient (Scheldt estuary, Belgium)

NASA Astrophysics Data System (ADS)

Van de Broek, Marijn; Temmermann, Stijn; Merckx, Roel; Wang, Zhengang; Govers, Gerard

2016-04-01

Coastal ecosystems have been attributed the potential to store large amounts of organic carbon (OC), often referred to as blue carbon, of which a considerable amount is stored in tidal marsh soils. Large uncertainties still exist with respect to the amount and controlling factors of soil organic carbon (SOC) stored in these ecosystems. Moreover, most research has focused on SOC dynamics of saltmarshes, while brackish and freshwater marshes are often even more productive and thus receive even larger organic carbon inputs. Therefore, in this study the OC dynamics of tidal marsh soils along an estuarine gradient are studied in order to contribute to our knowledge of 1) the stocks, 2) the controlling factors and 3) the fate of SOC in tidal marshes with different environmental characteristics. This research thus contributes to a better understanding of the potential of coastal environments to store organic carbon under future climatic changes. Soil and vegetation samples are collected in tidal salt-, brackish- and freshwater marshes in the Scheldt estuary (Belgium - The Netherlands). At each tidal marsh, three replicate soil cores up to 1.5m depth in 0.03m increments are collected at locations with both a low and a high elevation. These cores are analyzed for OC, stable C and N isotopes, bulk density and texture. Incubation experiments of topsoil samples were conducted and both aboveground and belowground biomass were collected. The results show that SOC stocks (range: 13,5 - 35,4 kg OC m-2), standing biomass (range: 2000 - 7930 g DW m-2) and potential soil respiration of CO2 (range: 0,03 - 0,12 % per unit OC per day) decrease with increasing salinity. This shows that both the amount of OC from local macrophytes and the quality of the organic matter are important factors controlling the SOC stocks. In addition, based on the analysis of stable C and N isotopes, it appears that when a significant fraction of SOC is derived from local macrophytes, higher SOC stocks are found, while a change in aboveground vegetation type can have large effects on SOC accumulation. Moreover, as these marsh soils have been dated before, the observed depth patterns in SOC can be linked to historical changes (e.g. changes in vegetation). A calibrated model simulating sediment deposition in these marshes is coupled to a two-pool OC model to study the effect of sediment deposition rate on the fate of SOC, with most input information being collected at the field sites. This allows us to calculate the residence time of OC in these tidal marsh soils, a measure that is very uncertain, also for other ecosystems. The part concerning modelling is however still under progress at the moment of writing. This study shows to which extent OC stocks and dynamics of tidal marsh soils along a temperate estuary are controlled by 1) the amount and quality of OC input and 2) the contribution from different sources of OC, and uses these finding to construct a 1D model to simulate these dynamics through time.

Development of CCSDS DCT to Support Spacecraft Dynamic Events

NASA Technical Reports Server (NTRS)

Sidhwa, Anahita F

2011-01-01

This report discusses the development of Consultative Committee for Space Data Systems (CCSDS) Design Control Table (DCT) to support spacecraft dynamic events. The Consultative Committee for Space Data Systems (CCSDS) Design Control Table (DCT) is a versatile link calculation tool to analyze different kinds of radio frequency links. It started out as an Excel-based program, and is now being evolved into a Mathematica-based link analysis tool. The Mathematica platform offers a rich set of advanced analysis capabilities, and can be easily extended to a web-based architecture. Last year the CCSDS DCT's for the uplink, downlink, two-way, and ranging models were developed as well as the corresponding input and output interfaces. Another significant accomplishment is the integration of the NAIF SPICE library into the Mathematica computation platform.

Astronaut Risk Levels During Crew Module (CM) Land Landing

NASA Technical Reports Server (NTRS)

Lawrence, Charles; Carney, Kelly S.; Littell, Justin

2007-01-01

The NASA Engineering Safety Center (NESC) is investigating the merits of water and land landings for the crew exploration vehicle (CEV). The merits of these two options are being studied in terms of cost and risk to the astronauts, vehicle, support personnel, and general public. The objective of the present work is to determine the astronaut dynamic response index (DRI), which measures injury risks. Risks are determined for a range of vertical and horizontal landing velocities. A structural model of the crew module (CM) is developed and computational simulations are performed using a transient dynamic simulation analysis code (LS-DYNA) to determine acceleration profiles. Landing acceleration profiles are input in a human factors model that determines astronaut risk levels. Details of the modeling approach, the resulting accelerations, and astronaut risk levels are provided.

A study of the dynamic tire properties over a range of tire constructions

NASA Technical Reports Server (NTRS)

Nybakken, G. H.; Dodge, R. N.; Clark, S. K.

1973-01-01

The dynamic properties of four model aircraft tires of various construction were evaluated experimentally and compared with available theory. The experimental investigation consisted of measuring the cornering force and the self-aligning torque developed by the tires undergoing sinusoidal steering inputs while operating on a small scale, road-wheel tire testing apparatus. The force and moment data from the different tires are compared with both finite- and point-contact patch string theory predictions. In general, agreement between finite contact patch theory and experimental observation is good. A modified string theory is also presented in which coefficients for cornering force and self-aligning torque are determined separately. This theory improves the correspondence between the experimental and analytical data, particularly on tires with relatively high self-aligning torques.

Synthesis of diamond films at low temperature and study of nonlinear dynamic synthesis process

NASA Astrophysics Data System (ADS)

Zhao, Qingxun; Shang, Yong; Dong, Lifang; Fu, Guangsheng; Yan, Zheng; Yang, Jingfa

2002-09-01

In this paper, the experimental synthesis of diamond films and optical emission spectroscopy (OES) of the gaseous phase species are studied in the range of substrate temperature from Ts = 300°C to 850°C. The high quality sub-microcrystalline diamond films are successfully deposited at substrate temperature (330 ≍ 340)°C by adopting glow plasma assisted hot filament chemical vapor deposition (GPCVD). For the first time, in situ OES is applied to diagnose weak signal of GPCVD system when CH4 and H2 are used as the input gas, and the reactive species are identified in diamond growth processes. A primary model of diamond films growing at low temperature is presented by studying dynamic behavior for nonequilibrium plasma reactions.

DREAM-3D and the importance of model inputs and boundary conditions

NASA Astrophysics Data System (ADS)

Friedel, Reiner; Tu, Weichao; Cunningham, Gregory; Jorgensen, Anders; Chen, Yue

2015-04-01

Recent work on radiation belt 3D diffusion codes such as the Los Alamos "DREAM-3D" code have demonstrated the ability of such codes to reproduce realistic magnetospheric storm events in the relativistic electron dynamics - as long as sufficient "event-oriented" boundary conditions and code inputs such as wave powers, low energy boundary conditions, background plasma densities, and last closed drift shell (outer boundary) are available. In this talk we will argue that the main limiting factor in our modeling ability is no longer our inability to represent key physical processes that govern the dynamics of the radiation belts (radial, pitch angle and energy diffusion) but rather our limitations in specifying accurate boundary conditions and code inputs. We use here DREAM-3D runs to show the sensitivity of the modeled outcomes to these boundary conditions and inputs, and also discuss alternate "proxy" approaches to obtain the required inputs from other (ground-based) sources.

Complex cellular logic computation using ribocomputing devices.

PubMed

Green, Alexander A; Kim, Jongmin; Ma, Duo; Silver, Pamela A; Collins, James J; Yin, Peng

2017-08-03

Synthetic biology aims to develop engineering-driven approaches to the programming of cellular functions that could yield transformative technologies. Synthetic gene circuits that combine DNA, protein, and RNA components have demonstrated a range of functions such as bistability, oscillation, feedback, and logic capabilities. However, it remains challenging to scale up these circuits owing to the limited number of designable, orthogonal, high-performance parts, the empirical and often tedious composition rules, and the requirements for substantial resources for encoding and operation. Here, we report a strategy for constructing RNA-only nanodevices to evaluate complex logic in living cells. Our 'ribocomputing' systems are composed of de-novo-designed parts and operate through predictable and designable base-pairing rules, allowing the effective in silico design of computing devices with prescribed configurations and functions in complex cellular environments. These devices operate at the post-transcriptional level and use an extended RNA transcript to co-localize all circuit sensing, computation, signal transduction, and output elements in the same self-assembled molecular complex, which reduces diffusion-mediated signal losses, lowers metabolic cost, and improves circuit reliability. We demonstrate that ribocomputing devices in Escherichia coli can evaluate two-input logic with a dynamic range up to 900-fold and scale them to four-input AND, six-input OR, and a complex 12-input expression (A1 AND A2 AND NOT A1*) OR (B1 AND B2 AND NOT B2*) OR (C1 AND C2) OR (D1 AND D2) OR (E1 AND E2). Successful operation of ribocomputing devices based on programmable RNA interactions suggests that systems employing the same design principles could be implemented in other host organisms or in extracellular settings.

Convergent responses of nitrogen and phosphorus resorption to nitrogen inputs in a semiarid grassland

USGS Publications Warehouse

Lü, Xiao-Tao; Reed, Sasha; Yu, Qiang; He, Nian-Peng; Wang, Zheng-Wen; Han, Xing-Guo

2013-01-01

Human activities have significantly altered nitrogen (N) availability in most terrestrial ecosystems, with consequences for community composition and ecosystem functioning. Although studies of how changes in N availability affect biodiversity and community composition are relatively common, much less remains known about the effects of N inputs on the coupled biogeochemical cycling of N and phosphorus (P), and still fewer data exist regarding how increased N inputs affect the internal cycling of these two elements in plants. Nutrient resorption is an important driver of plant nutrient economies and of the quality of litter plants produce. Accordingly, resorption patterns have marked ecological implications for plant population and community fitness, as well as for ecosystem nutrient cycling. In a semiarid grassland in northern China, we studied the effects of a wide range of N inputs on foliar nutrient resorption of two dominant grasses, Leymus chinensis and Stipa grandis. After 4 years of treatments, N and P availability in soil and N and P concentrations in green and senesced grass leaves increased with increasing rates of N addition. Foliar N and P resorption significantly decreased along the N addition gradient, implying a resorption-mediated, positive plant–soil feedback induced by N inputs. Furthermore, N : P resorption ratios were negatively correlated with the rates of N addition, indicating the sensitivity of plant N and P stoichiometry to N inputs. Taken together, the results demonstrate that N additions accelerate ecosystem uptake and turnover of both N and P in the temperate steppe and that N and P cycles are coupled in dynamic ways. The convergence of N and P resorption in response to N inputs emphasizes the importance of nutrient resorption as a pathway by which plants and ecosystems adjust in the face of increasing N availability.

Eliminating Glutamatergic Input onto Horizontal Cells Changes the Dynamic Range and Receptive Field Organization of Mouse Retinal Ganglion Cells.

PubMed

Ströh, Sebastian; Puller, Christian; Swirski, Sebastian; Hölzel, Maj-Britt; van der Linde, Lea I S; Segelken, Jasmin; Schultz, Konrad; Block, Christoph; Monyer, Hannah; Willecke, Klaus; Weiler, Reto; Greschner, Martin; Janssen-Bienhold, Ulrike; Dedek, Karin

2018-02-21

In the mammalian retina, horizontal cells receive glutamatergic inputs from many rod and cone photoreceptors and return feedback signals to them, thereby changing photoreceptor glutamate release in a light-dependent manner. Horizontal cells also provide feedforward signals to bipolar cells. It is unclear, however, how horizontal cell signals also affect the temporal, spatial, and contrast tuning in retinal output neurons, the ganglion cells. To study this, we generated a genetically modified mouse line in which we eliminated the light dependency of feedback by deleting glutamate receptors from mouse horizontal cells. This genetic modification allowed us to investigate the impact of horizontal cells on ganglion cell signaling independent of the actual mode of feedback in the outer retina and without pharmacological manipulation of signal transmission. In control and genetically modified mice (both sexes), we recorded the light responses of transient OFF-α retinal ganglion cells in the intact retina. Excitatory postsynaptic currents (EPSCs) were reduced and the cells were tuned to lower temporal frequencies and higher contrasts, presumably because photoreceptor output was attenuated. Moreover, receptive fields of recorded cells showed a significantly altered surround structure. Our data thus suggest that horizontal cells are responsible for adjusting the dynamic range of retinal ganglion cells and, together with amacrine cells, contribute to the center/surround organization of ganglion cell receptive fields in the mouse. SIGNIFICANCE STATEMENT Horizontal cells represent a major neuronal class in the mammalian retina and provide lateral feedback and feedforward signals to photoreceptors and bipolar cells, respectively. The mode of signal transmission remains controversial and, moreover, the contribution of horizontal cells to visual processing is still elusive. To address the question of how horizontal cells affect retinal output signals, we recorded the light responses of transient OFF-α retinal ganglion cells in a newly generated mouse line. In this mouse line, horizontal cell signals were no longer modulated by light. With light response recordings, we show that horizontal cells increase the dynamic range of retinal ganglion cells for contrast and temporal changes and contribute to the center/surround organization of their receptive fields. Copyright © 2018 the authors 0270-6474/18/382015-14$15.00/0.

Characterizing chaotic dynamics from integrate-and-fire interspike intervals at the presence of noise

NASA Astrophysics Data System (ADS)

Mohammad, Yasir K.; Pavlova, Olga N.; Pavlov, Alexey N.

2016-04-01

We discuss the problem of quantifying chaotic dynamics at the input of the "integrate-and-fire" (IF) model from the output sequences of interspike intervals (ISIs) for the case when the fluctuating threshold level leads to the appearance of noise in ISI series. We propose a way to detect an ability of computing dynamical characteristics of the input dynamics and the level of noise in the output point processes. The proposed approach is based on the dependence of the largest Lyapunov exponent from the maximal orientation error used at the estimation of the averaged rate of divergence of nearby phase trajectories.

Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations.

PubMed

Hu, Eric Y; Bouteiller, Jean-Marie C; Song, Dong; Baudry, Michel; Berger, Theodore W

2015-01-01

Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations.

Volterra representation enables modeling of complex synaptic nonlinear dynamics in large-scale simulations

PubMed Central

Hu, Eric Y.; Bouteiller, Jean-Marie C.; Song, Dong; Baudry, Michel; Berger, Theodore W.

2015-01-01

Chemical synapses are comprised of a wide collection of intricate signaling pathways involving complex dynamics. These mechanisms are often reduced to simple spikes or exponential representations in order to enable computer simulations at higher spatial levels of complexity. However, these representations cannot capture important nonlinear dynamics found in synaptic transmission. Here, we propose an input-output (IO) synapse model capable of generating complex nonlinear dynamics while maintaining low computational complexity. This IO synapse model is an extension of a detailed mechanistic glutamatergic synapse model capable of capturing the input-output relationships of the mechanistic model using the Volterra functional power series. We demonstrate that the IO synapse model is able to successfully track the nonlinear dynamics of the synapse up to the third order with high accuracy. We also evaluate the accuracy of the IO synapse model at different input frequencies and compared its performance with that of kinetic models in compartmental neuron models. Our results demonstrate that the IO synapse model is capable of efficiently replicating complex nonlinear dynamics that were represented in the original mechanistic model and provide a method to replicate complex and diverse synaptic transmission within neuron network simulations. PMID:26441622

Preliminary Exploration of Adaptive State Predictor Based Human Operator Modeling

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Gregory, Irene M.

2012-01-01

Control-theoretic modeling of the human operator dynamic behavior in manual control tasks has a long and rich history. In the last two decades, there has been a renewed interest in modeling the human operator. There has also been significant work on techniques used to identify the pilot model of a given structure. The purpose of this research is to attempt to go beyond pilot identification based on collected experimental data and to develop a predictor of pilot behavior. An experiment was conducted to quantify the effects of changing aircraft dynamics on an operator s ability to track a signal in order to eventually model a pilot adapting to changing aircraft dynamics. A gradient descent estimator and a least squares estimator with exponential forgetting used these data to predict pilot stick input. The results indicate that individual pilot characteristics and vehicle dynamics did not affect the accuracy of either estimator method to estimate pilot stick input. These methods also were able to predict pilot stick input during changing aircraft dynamics and they may have the capability to detect a change in a subject due to workload, engagement, etc., or the effects of changes in vehicle dynamics on the pilot.

A comprehensive inversion approach for feedforward compensation of piezoactuator system at high frequency

NASA Astrophysics Data System (ADS)

Tian, Lizhi; Xiong, Zhenhua; Wu, Jianhua; Ding, Han

2016-09-01

Motion control of the piezoactuator system over broadband frequencies is limited due to its inherent hysteresis and system dynamics. One of the suggested ways is to use feedforward controller to linearize the input-output relationship of the piezoactuator system. Although there have been many feedforward approaches, it is still a challenge to develop feedforward controller for the piezoactuator system at high frequency. Hence, this paper presents a comprehensive inversion approach in consideration of the coupling of hysteresis and dynamics. In this work, the influence of dynamics compensation on the input-output relationship of the piezoactuator system is investigated first. With system dynamics compensation, the input-output relationship of the piezoactuator system will be further represented as rate-dependent nonlinearity due to the inevitable dynamics compensation error, especially at high frequency. Base on this result, the feedforward controller composed by a cascade of linear dynamics inversion and rate-dependent nonlinearity inversion is developed. Then, the system identification of the comprehensive inversion approach is proposed. Finally, experimental results show that the proposed approach can improve the performance on tracking of both periodic and non-periodic trajectories at medium and high frequency compared with the conventional feedforward approaches.

Single neuron computation: from dynamical system to feature detector.

PubMed

Hong, Sungho; Agüera y Arcas, Blaise; Fairhall, Adrienne L

2007-12-01

White noise methods are a powerful tool for characterizing the computation performed by neural systems. These methods allow one to identify the feature or features that a neural system extracts from a complex input and to determine how these features are combined to drive the system's spiking response. These methods have also been applied to characterize the input-output relations of single neurons driven by synaptic inputs, simulated by direct current injection. To interpret the results of white noise analysis of single neurons, we would like to understand how the obtained feature space of a single neuron maps onto the biophysical properties of the membrane, in particular, the dynamics of ion channels. Here, through analysis of a simple dynamical model neuron, we draw explicit connections between the output of a white noise analysis and the underlying dynamical system. We find that under certain assumptions, the form of the relevant features is well defined by the parameters of the dynamical system. Further, we show that under some conditions, the feature space is spanned by the spike-triggered average and its successive order time derivatives.

A compositional framework for reaction networks

NASA Astrophysics Data System (ADS)

Baez, John C.; Pollard, Blake S.

Reaction networks, or equivalently Petri nets, are a general framework for describing processes in which entities of various kinds interact and turn into other entities. In chemistry, where the reactions are assigned ‘rate constants’, any reaction network gives rise to a nonlinear dynamical system called its ‘rate equation’. Here we generalize these ideas to ‘open’ reaction networks, which allow entities to flow in and out at certain designated inputs and outputs. We treat open reaction networks as morphisms in a category. Composing two such morphisms connects the outputs of the first to the inputs of the second. We construct a functor sending any open reaction network to its corresponding ‘open dynamical system’. This provides a compositional framework for studying the dynamics of reaction networks. We then turn to statics: that is, steady state solutions of open dynamical systems. We construct a ‘black-boxing’ functor that sends any open dynamical system to the relation that it imposes between input and output variables in steady states. This extends our earlier work on black-boxing for Markov processes.

Scheme of Optical Image Encryption with Digital Information Input and Dynamic Encryption Key based on Two LC SLMs

NASA Astrophysics Data System (ADS)

Bondareva, A. P.; Cheremkhin, P. A.; Evtikhiev, N. N.; Krasnov, V. V.; Starikov, S. N.

Scheme of optical image encryption with digital information input and dynamic encryption key based on two liquid crystal spatial light modulators and operating with spatially-incoherent monochromatic illumination is experimentally implemented. Results of experiments on images optical encryption and numerical decryption are presented. Satisfactory decryption error of 0.20÷0.27 is achieved.

Dynamic control modification techniques in teleoperation of a flexible manipulator. M.S. Thesis

NASA Technical Reports Server (NTRS)

Magee, David Patrick

1991-01-01

The objective of this research is to reduce the end-point vibration of a large, teleoperated manipulator while preserving the usefulness of the system motion. A master arm is designed to measure desired joint angles as the user specifies a desired tip motion. The desired joint angles from the master arm are the inputs to an adaptive PD control algorithm that positions the end-point of the manipulator. As the user moves the tip of the master, the robot will vibrate at its natural frequencies which makes it difficult to position the end-point. To eliminate the tip vibration during teleoperated motions, an input shaping method is presented. The input shaping method transforms each sample of the desired input into a new set of impulses that do not excite the system resonances. The method is explained using the equation of motion for a simple, second-order system. The impulse response of such a system is derived and the constraint equations for vibrationless motion are presented. To evaluate the robustness of the method, a different residual vibration equation from Singer's is derived that more accurately represents the input shaping technique. The input shaping method is shown to actually increase the residual vibration in certain situations when the system parameters are not accurately specified. Finally, the implementation of the input shaping method to a system with varying parameters is shown to induce a vibration into the system. To eliminate this vibration, a modified command shaping technique is developed. The ability of the modified command shaping method to reduce vibration at the system resonances is tested by varying input perturbations to trajectories in a range of possible user inputs. By comparing the frequency responses of the transverse acceleration at the end-point of the manipulator, the modified method is compared to the original PD routine. The control scheme that produces the smaller magnitude of resonant vibration at the first natural frequency is considered the more effective control method.

Investigating Uncertainty in Predicting Carbon Dynamics in North American Biomes: Putting Support-Effect Bias in Perspective

NASA Technical Reports Server (NTRS)

Dungan, Jennifer L.; Brass, Jim (Technical Monitor)

2001-01-01

A fundamental strategy in NASA's Earth Observing System's (EOS) monitoring of vegetation and its contribution to the global carbon cycle is to rely on deterministic, process-based ecosystem models to make predictions of carbon flux over large regions. These models are parameterized (that is, the input variables are derived) using remotely sensed images such as those from the Moderate Resolution Imaging Spectroradiometer (MODIS), ground measurements and interpolated maps. Since early applications of these models, investigators have noted that results depend partly on the spatial support of the input variables. In general, the larger the support of the input data, the greater the chance that the effects of important components of the ecosystem will be averaged out. A review of previous work shows that using large supports can cause either positive or negative bias in carbon flux predictions. To put the magnitude and direction of these biases in perspective, we must quantify the range of uncertainty on our best measurements of carbon-related variables made on equivalent areas. In other words, support-effect bias should be placed in the context of prediction uncertainty from other sources. If the range of uncertainty at the smallest support is less than the support-effect bias, more research emphasis should probably be placed on support sizes that are intermediate between those of field measurements and MODIS. If the uncertainty range at the smallest support is larger than the support-effect bias, the accuracy of MODIS-based predictions will be difficult to quantify and more emphasis should be placed on field-scale characterization and sampling. This talk will describe methods to address these issues using a field measurement campaign in North America and "upscaling" using geostatistical estimation and simulation.

PyMUS: Python-Based Simulation Software for Virtual Experiments on Motor Unit System

PubMed Central

Kim, Hojeong; Kim, Minjung

2018-01-01

We constructed a physiologically plausible computationally efficient model of a motor unit and developed simulation software that allows for integrative investigations of the input–output processing in the motor unit system. The model motor unit was first built by coupling the motoneuron model and muscle unit model to a simplified axon model. To build the motoneuron model, we used a recently reported two-compartment modeling approach that accurately captures the key cell-type-related electrical properties under both passive conditions (somatic input resistance, membrane time constant, and signal attenuation properties between the soma and the dendrites) and active conditions (rheobase current and afterhyperpolarization duration at the soma and plateau behavior at the dendrites). To construct the muscle unit, we used a recently developed muscle modeling approach that reflects the experimentally identified dependencies of muscle activation dynamics on isometric, isokinetic and dynamic variation in muscle length over a full range of stimulation frequencies. Then, we designed the simulation software based on the object-oriented programing paradigm and developed the software using open-source Python language to be fully operational using graphical user interfaces. Using the developed software, separate simulations could be performed for a single motoneuron, muscle unit and motor unit under a wide range of experimental input protocols, and a hierarchical analysis could be performed from a single channel to the entire system behavior. Our model motor unit and simulation software may represent efficient tools not only for researchers studying the neural control of force production from a cellular perspective but also for instructors and students in motor physiology classroom settings. PMID:29695959

Guidelines for reducing dynamic loads in two-bladed teetering-hub downwind wind turbines

NASA Astrophysics Data System (ADS)

Wright, A. D.; Bir, G. S.; Butterfield, C. D.

1995-06-01

A major goal of the federal Wind Energy Program is the rapid development and validation of structural models to determine loads and response for a wide variety of different wind turbine configurations operating under extreme conditions. Such codes are crucial to the successful design of future advanced wind turbines. In previous papers the authors described steps they took to develop a model of a two-bladed teetering-hub downwind wind turbine using ADAMS (Automatic Dynamic Analysis of Mechanical Systems), as well as comparison of model predictions to test data. In this paper they show the use of this analytical model to study the influence of various turbine parameters on predicted system loads. They concentrate their study on turbine response in the frequency range of six to ten times the rotor rotational frequency (6P to 10P). Their goal is to identify the most important parameters which influence the response of this type of machine in this frequency range and give turbine designers some general design guidelines for designing two-bladed teetering-hub machines to be less susceptible to vibration. They study the effects of such parameters as blade edgewise and flapwise stiffness, tower top stiffness, blade tip-brake mass, low-speed shaft stiffness, nacelle mass momenta of inertia, and rotor speed. They show which parameters can be varied in order to make the turbine less responsive to such atmospheric inputs as wind shear and tower shadow. They then give designers a set of design guidelines in order to show how these machines can be designed to be less responsive to these inputs.

A globally calibrated scheme for generating daily meteorology from monthly statistics: Global-WGEN (GWGEN) v1.0

NASA Astrophysics Data System (ADS)

Sommer, Philipp S.; Kaplan, Jed O.

2017-10-01

While a wide range of Earth system processes occur at daily and even subdaily timescales, many global vegetation and other terrestrial dynamics models historically used monthly meteorological forcing both to reduce computational demand and because global datasets were lacking. Recently, dynamic land surface modeling has moved towards resolving daily and subdaily processes, and global datasets containing daily and subdaily meteorology have become available. These meteorological datasets, however, cover only the instrumental era of the last approximately 120 years at best, are subject to considerable uncertainty, and represent extremely large data files with associated computational costs of data input/output and file transfer. For periods before the recent past or in the future, global meteorological forcing can be provided by climate model output, but the quality of these data at high temporal resolution is low, particularly for daily precipitation frequency and amount. Here, we present GWGEN, a globally applicable statistical weather generator for the temporal downscaling of monthly climatology to daily meteorology. Our weather generator is parameterized using a global meteorological database and simulates daily values of five common variables: minimum and maximum temperature, precipitation, cloud cover, and wind speed. GWGEN is lightweight, modular, and requires a minimal set of monthly mean variables as input. The weather generator may be used in a range of applications, for example, in global vegetation, crop, soil erosion, or hydrological models. While GWGEN does not currently perform spatially autocorrelated multi-point downscaling of daily weather, this additional functionality could be implemented in future versions.

Coordinated three-dimensional motion of the head and torso by dynamic neural networks.

PubMed

Kim, J; Hemami, H

1998-01-01

The problem of trajectory tracking control of a three dimensional (3D) model of the human upper torso and head is considered. The torso and the head are modeled as two rigid bodies connected at one point, and the Newton-Euler method is used to derive the nonlinear differential equations that govern the motion of the system. The two-link system is driven by six pairs of muscle like actuators that possess physiologically inspired alpha like and gamma like inputs, and spindle like and Golgi tendon organ like outputs. These outputs are utilized as reflex feedback for stability and stiffness control, in a long loop feedback for the purpose of estimating the state of the system (somesthesis), and as part of the input to the controller. Ideal delays of different duration are included in the feedforward and feedback paths of the system to emulate such delays encountered in physiological systems. Dynamical neural networks are trained to learn effective control of the desired maneuvers of the system. The feasibility of the controller is demonstrated by computer simulation of the successful execution of the desired maneuvers. This work demonstrates the capabilities of neural circuits in controlling highly nonlinear systems with multidelays in their feedforward and feedback paths. The ultimate long range goal of this research is toward understanding the working of the central nervous system in controlling movement. It is an interdisciplinary effort relying on mechanics, biomechanics, neuroscience, system theory, physiology and anatomy, and its short range relevance to rehabilitation must be noted.

Field verification of KDOT's Superpave mixture properties to be used as inputs in the NCHRP mechanistic-empirical pavement design guide.

DOT National Transportation Integrated Search

2009-01-01

In the MechanisticEmpirical Pavement Design Guide (M-EPDG), prediction of flexible pavement response and performance needs an input of dynamic modulus of hot-mix asphalt (HMA) at all three levels of hierarchical inputs. This study was intended to ...

Blade loss transient dynamics analysis. Volume 3: User's manual for TETRA program

NASA Technical Reports Server (NTRS)

Black, G. R.; Gallardo, V. C.; Storace, A. S.; Sagendorph, F.

1981-01-01

The users manual for TETRA contains program logic, flow charts, error messages, input sheets, modeling instructions, option descriptions, input variable descriptions, and demonstration problems. The process of obtaining a NASTRAN 17.5 generated modal input file for TETRA is also described with a worked sample.

Testing of information condensation in a model reverberating spiking neural network.

PubMed

Vidybida, Alexander

2011-06-01

Information about external world is delivered to the brain in the form of structured in time spike trains. During further processing in higher areas, information is subjected to a certain condensation process, which results in formation of abstract conceptual images of external world, apparently, represented as certain uniform spiking activity partially independent on the input spike trains details. Possible physical mechanism of condensation at the level of individual neuron was discussed recently. In a reverberating spiking neural network, due to this mechanism the dynamics should settle down to the same uniform/ periodic activity in response to a set of various inputs. Since the same periodic activity may correspond to different input spike trains, we interpret this as possible candidate for information condensation mechanism in a network. Our purpose is to test this possibility in a network model consisting of five fully connected neurons, particularly, the influence of geometric size of the network, on its ability to condense information. Dynamics of 20 spiking neural networks of different geometric sizes are modelled by means of computer simulation. Each network was propelled into reverberating dynamics by applying various initial input spike trains. We run the dynamics until it becomes periodic. The Shannon's formula is used to calculate the amount of information in any input spike train and in any periodic state found. As a result, we obtain explicit estimate of the degree of information condensation in the networks, and conclude that it depends strongly on the net's geometric size.

Correlation of chemical shifts predicted by molecular dynamics simulations for partially disordered proteins.

PubMed

Karp, Jerome M; Eryilmaz, Ertan; Erylimaz, Ertan; Cowburn, David

2015-01-01

There has been a longstanding interest in being able to accurately predict NMR chemical shifts from structural data. Recent studies have focused on using molecular dynamics (MD) simulation data as input for improved prediction. Here we examine the accuracy of chemical shift prediction for intein systems, which have regions of intrinsic disorder. We find that using MD simulation data as input for chemical shift prediction does not consistently improve prediction accuracy over use of a static X-ray crystal structure. This appears to result from the complex conformational ensemble of the disordered protein segments. We show that using accelerated molecular dynamics (aMD) simulations improves chemical shift prediction, suggesting that methods which better sample the conformational ensemble like aMD are more appropriate tools for use in chemical shift prediction for proteins with disordered regions. Moreover, our study suggests that data accurately reflecting protein dynamics must be used as input for chemical shift prediction in order to correctly predict chemical shifts in systems with disorder.

Numerical modelling of gravel unconstrained flow experiments with the DAN3D and RASH3D codes

NASA Astrophysics Data System (ADS)

Sauthier, Claire; Pirulli, Marina; Pisani, Gabriele; Scavia, Claudio; Labiouse, Vincent

2015-12-01

Landslide continuum dynamic models have improved considerably in the last years, but a consensus on the best method of calibrating the input resistance parameter values for predictive analyses has not yet emerged. In the present paper, numerical simulations of a series of laboratory experiments performed at the Laboratory for Rock Mechanics of the EPF Lausanne were undertaken with the RASH3D and DAN3D numerical codes. They aimed at analysing the possibility to use calibrated ranges of parameters (1) in a code different from that they were obtained from and (2) to simulate potential-events made of a material with the same characteristics as back-analysed past-events, but involving a different volume and propagation path. For this purpose, one of the four benchmark laboratory tests was used as past-event to calibrate the dynamic basal friction angle assuming a Coulomb-type behaviour of the sliding mass, and this back-analysed value was then used to simulate the three other experiments, assumed as potential-events. The computational findings show good correspondence with experimental results in terms of characteristics of the final deposits (i.e., runout, length and width). Furthermore, the obtained best fit values of the dynamic basal friction angle for the two codes turn out to be close to each other and within the range of values measured with pseudo-dynamic tilting tests.

Wide bandwidth phase-locked loop circuit

NASA Technical Reports Server (NTRS)

Koudelka, Robert David (Inventor)

2005-01-01

A PLL circuit uses a multiple frequency range PLL in order to phase lock input signals having a wide range of frequencies. The PLL includes a VCO capable of operating in multiple different frequency ranges and a divider bank independently configurable to divide the output of the VCO. A frequency detector detects a frequency of the input signal and a frequency selector selects an appropriate frequency range for the PLL. The frequency selector automatically switches the PLL to a different frequency range as needed in response to a change in the input signal frequency. Frequency range hysteresis is implemented to avoid operating the PLL near a frequency range boundary.

Uncertainty Analysis for a Jet Flap Airfoil

NASA Technical Reports Server (NTRS)

Green, Lawrence L.; Cruz, Josue

2006-01-01

An analysis of variance (ANOVA) study was performed to quantify the potential uncertainties of lift and pitching moment coefficient calculations from a computational fluid dynamics code, relative to an experiment, for a jet flap airfoil configuration. Uncertainties due to a number of factors including grid density, angle of attack and jet flap blowing coefficient were examined. The ANOVA software produced a numerical model of the input coefficient data, as functions of the selected factors, to a user-specified order (linear, 2-factor interference, quadratic, or cubic). Residuals between the model and actual data were also produced at each of the input conditions, and uncertainty confidence intervals (in the form of Least Significant Differences or LSD) for experimental, computational, and combined experimental / computational data sets were computed. The LSD bars indicate the smallest resolvable differences in the functional values (lift or pitching moment coefficient) attributable solely to changes in independent variable, given just the input data points from selected data sets. The software also provided a collection of diagnostics which evaluate the suitability of the input data set for use within the ANOVA process, and which examine the behavior of the resultant data, possibly suggesting transformations which should be applied to the data to reduce the LSD. The results illustrate some of the key features of, and results from, the uncertainty analysis studies, including the use of both numerical (continuous) and categorical (discrete) factors, the effects of the number and range of the input data points, and the effects of the number of factors considered simultaneously.

Energy Input Flux in the Global Quiet-Sun Corona

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

Mac Cormack, Cecilia; Vásquez, Alberto M.; López Fuentes, Marcelo

We present first results of a novel technique that provides, for the first time, constraints on the energy input flux at the coronal base ( r ∼ 1.025 R {sub ⊙}) of the quiet Sun at a global scale. By combining differential emission measure tomography of EUV images, with global models of the coronal magnetic field, we estimate the energy input flux at the coronal base that is required to maintain thermodynamically stable structures. The technique is described in detail and first applied to data provided by the Extreme Ultraviolet Imager instrument, on board the Solar TErrestrial RElations Observatory mission,more » and the Atmospheric Imaging Assembly instrument, on board the Solar Dynamics Observatory mission, for two solar rotations with different levels of activity. Our analysis indicates that the typical energy input flux at the coronal base of magnetic loops in the quiet Sun is in the range ∼0.5–2.0 × 10{sup 5} (erg s{sup −1} cm{sup −2}), depending on the structure size and level of activity. A large fraction of this energy input, or even its totality, could be accounted for by Alfvén waves, as shown by recent independent observational estimates derived from determinations of the non-thermal broadening of spectral lines in the coronal base of quiet-Sun regions. This new tomography product will be useful for the validation of coronal heating models in magnetohydrodinamic simulations of the global corona.« less

Tiltrotor Aeroacoustic Code (TRAC) Prediction Assessment and Initial Comparisons with Tram Test Data

NASA Technical Reports Server (NTRS)

Burley, Casey L.; Brooks, Thomas F.; Charles, Bruce D.; McCluer, Megan

1999-01-01

A prediction sensitivity assessment to inputs and blade modeling is presented for the TiltRotor Aeroacoustic Code (TRAC). For this study, the non-CFD prediction system option in TRAC is used. Here, the comprehensive rotorcraft code, CAMRAD.Mod1, coupled with the high-resolution sectional loads code HIRES, predicts unsteady blade loads to be used in the noise prediction code WOPWOP. The sensitivity of the predicted blade motions, blade airloads, wake geometry, and acoustics is examined with respect to rotor rpm, blade twist and chord, and to blade dynamic modeling. To accomplish this assessment, an interim input-deck for the TRAM test model and an input-deck for a reference test model are utilized in both rigid and elastic modes. Both of these test models are regarded as near scale models of the V-22 proprotor (tiltrotor). With basic TRAC sensitivities established, initial TRAC predictions are compared to results of an extensive test of an isolated model proprotor. The test was that of the TiltRotor Aeroacoustic Model (TRAM) conducted in the Duits-Nederlandse Windtunnel (DNW). Predictions are compared to measured noise for the proprotor operating over an extensive range of conditions. The variation of predictions demonstrates the great care that must be taken in defining the blade motion. However, even with this variability, the predictions using the different blade modeling successfully capture (bracket) the levels and trends of the noise for conditions ranging from descent to ascent.

Tiltrotor Aeroacoustic Code (TRAC) Prediction Assessment and Initial Comparisons With TRAM Test Data

NASA Technical Reports Server (NTRS)

Burley, Casey L.; Brooks, Thomas F.; Charles, Bruce D.; McCluer, Megan

1999-01-01

A prediction sensitivity assessment to inputs and blade modeling is presented for the TiltRotor Aeroacoustic Code (TRAC). For this study, the non-CFD prediction system option in TRAC is used. Here, the comprehensive rotorcraft code, CAMRAD.Mod 1, coupled with the high-resolution sectional loads code HIRES, predicts unsteady blade loads to be used in the noise prediction code WOPWOP. The sensitivity of the predicted blade motions, blade airloads, wake geometry, and acoustics is examined with respect to rotor rpm, blade twist and chord, and to blade dynamic modeling. To accomplish this assessment. an interim input-deck for the TRAM test model and an input-deck for a reference test model are utilized in both rigid and elastic modes. Both of these test models are regarded as near scale models of the V-22 proprotor (tiltrotor). With basic TRAC sensitivities established, initial TRAC predictions are compared to results of an extensive test of an isolated model proprotor. The test was that of the TiltRotor Aeroacoustic Model (TRAM) conducted in the Duits-Nederlandse Windtunnel (DNW). Predictions are compared to measured noise for the proprotor operating over an extensive range of conditions. The variation of predictions demonstrates the great care that must be taken in defining the blade motion. However, even with this variability, the predictions using the different blade modeling successfully capture (bracket) the levels and trends of the noise for conditions ranging from descent to ascent.

Spin distribution of evaporation residues formed in complete and incomplete fusion in 16O+154Sm system

NASA Astrophysics Data System (ADS)

Singh, D.; Linda, Sneha B.; Giri, Pankaj K.; Mahato, Amritraj; Tripathi, R.; Kumar, Harish; Afzal Ansari, M.; Sathik, N. P. M.; Ali, Rahbar; Kumar, Rakesh; Muralithar, S.; Singh, R. P.

2017-11-01

Spin distributions for several evaporation residues populated in the 16O+154Sm system have been measured at projectile energy ≈ 6.2 MeV/A by using the charged particle-γ-coincidence technique. The measured spin distributions of the evaporation residues populated through incomplete fusion associated with 'fast' α and 2α-emission channels are found to be entirely different from fusion-evaporation channels. It is observed that the mean input angular momentum for the evaporation residues formed in incomplete fusion channel is relatively higher than that observed for evaporation residues in complete fusion channels. The feeding intensity profile of evaporation residues populated through complete fusion and incomplete fusion have also been studied. The incomplete fusion channels are found to have narrow range feeding only for high spin states, while complete fusion channels are strongly fed over a broad spin range and widely populated. Comparison of present results with earlier data suggests that the mean input angular momentum values are relatively smaller for spherical target than that of deformed target using the same projectile and incident energy highlighting the role of target deformation in incomplete fusion dynamics.

Influence of estuarine processes on spatiotemporal variation in bioavailable selenium

USGS Publications Warehouse

Stewart, Robin; Luoma, Samuel N.; Elrick, Kent A.; Carter, James L.; van der Wegen, Mick

2013-01-01

Dynamic processes (physical, chemical and biological) challenge our ability to quantify and manage the ecological risk of chemical contaminants in estuarine environments. Selenium (Se) bioavailability (defined by bioaccumulation), stable isotopes and molar carbon-tonitrogen ratios in the benthic clam Potamocorbula amurensis, an important food source for predators, were determined monthly for 17 yr in northern San Francisco Bay. Se concentrations in the clams ranged from a low of 2 to a high of 22 μg g-1 over space and time. Little of that variability was stochastic, however. Statistical analyses and preliminary hydrodynamic modeling showed that a constant mid-estuarine input of Se, which was dispersed up- and down-estuary by tidal currents, explained the general spatial patterns in accumulated Se among stations. Regression of Se bioavailability against river inflows suggested that processes driven by inflows were the primary driver of seasonal variability. River inflow also appeared to explain interannual variability but within the range of Se enrichment established at each station by source inputs. Evaluation of risks from Se contamination in estuaries requires the consideration of spatial and temporal variability on multiple scales and of the processes that drive that variability.

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.

Characterizing the Meso-scale Plasma Flows in Earth's Coupled Magnetosphere-Ionosphere-Thermosphere System

NASA Astrophysics Data System (ADS)

Gabrielse, C.; Nishimura, T.; Lyons, L. R.; Gallardo-Lacourt, B.; Deng, Y.; McWilliams, K. A.; Ruohoniemi, J. M.

2017-12-01

NASA's Heliophysics Decadal Survey put forth several imperative, Key Science Goals. The second goal communicates the urgent need to "Determine the dynamics and coupling of Earth's magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs...over a range of spatial and temporal scales." Sun-Earth connections (called Space Weather) have strong societal impacts because extreme events can disturb radio communications and satellite operations. The field's current modeling capabilities of such Space Weather phenomena include large-scale, global responses of the Earth's upper atmosphere to various inputs from the Sun, but the meso-scale ( 50-500 km) structures that are much more dynamic and powerful in the coupled system remain uncharacterized. Their influences are thus far poorly understood. We aim to quantify such structures, particularly auroral flows and streamers, in order to create an empirical model of their size, location, speed, and orientation based on activity level (AL index), season, solar cycle (F10.7), interplanetary magnetic field (IMF) inputs, etc. We present a statistical study of meso-scale flow channels in the nightside auroral oval and polar cap using SuperDARN. These results are used to inform global models such as the Global Ionosphere Thermosphere Model (GITM) in order to evaluate the role of meso-scale disturbances on the fully coupled magnetosphere-ionosphere-thermosphere system. Measuring the ionospheric footpoint of magnetospheric fast flows, our analysis technique from the ground also provides a 2D picture of flows and their characteristics during different activity levels that spacecraft alone cannot.

Soil properties and not inputs control carbon : nitrogen : phosphorus ratios in cropped soils in the long term

NASA Astrophysics Data System (ADS)

Frossard, Emmanuel; Buchmann, Nina; Bünemann, Else K.; Kiba, Delwende I.; Lompo, François; Oberson, Astrid; Tamburini, Federica; Traoré, Ouakoltio Y. A.

2016-02-01

Stoichiometric approaches have been applied to understand the relationship between soil organic matter dynamics and biological nutrient transformations. However, very few studies have explicitly considered the effects of agricultural management practices on the soil C : N : P ratio. The aim of this study was to assess how different input types and rates would affect the C : N : P molar ratios of bulk soil, organic matter and microbial biomass in cropped soils in the long term. Thus, we analysed the C, N, and P inputs and budgets as well as soil properties in three long-term experiments established on different soil types: the Saria soil fertility trial (Burkina Faso), the Wagga Wagga rotation/stubble management/soil preparation trial (Australia), and the DOK (bio-Dynamic, bio-Organic, and "Konventionell") cropping system trial (Switzerland). In each of these trials, there was a large range of C, N, and P inputs which had a strong impact on element concentrations in soils. However, although C : N : P ratios of the inputs were highly variable, they had only weak effects on soil C : N : P ratios. At Saria, a positive correlation was found between the N : P ratio of inputs and microbial biomass, while no relation was observed between the nutrient ratios of inputs and soil organic matter. At Wagga Wagga, the C : P ratio of inputs was significantly correlated to total soil C : P, N : P, and C : N ratios, but had no impact on the elemental composition of microbial biomass. In the DOK trial, a positive correlation was found between the C budget and the C to organic P ratio in soils, while the nutrient ratios of inputs were not related to those in the microbial biomass. We argue that these responses are due to differences in soil properties among sites. At Saria, the soil is dominated by quartz and some kaolinite, has a coarse texture, a fragile structure, and a low nutrient content. Thus, microorganisms feed on inputs (plant residues, manure). In contrast, the soil at Wagga Wagga contains illite and haematite, is richer in clay and nutrients, and has a stable structure. Thus, organic matter is protected from mineralization and can therefore accumulate, allowing microorganisms to feed on soil nutrients and to keep a constant C : N : P ratio. The DOK soil represents an intermediate situation, with high nutrient concentrations, but a rather fragile soil structure, where organic matter does not accumulate. We conclude that the study of C, N, and P ratios is important to understand the functioning of cropped soils in the long term, but that it must be coupled with a precise assessment of element inputs and budgets in the system and a good understanding of the ability of soils to stabilize C, N, and P compounds.

A Novel Concept for a Deformable Membrane Mirror for Correction of Large Amplitude Aberrations

NASA Technical Reports Server (NTRS)

Moore, Jim; Patrick, Brian

2006-01-01

Very large, light weight mirrors are being developed for applications in space. Due to launch mass and volume restrictions these mirrors will need to be much more flexible than traditional optics. The use of primary mirrors with these characteristics will lead to requirements for adaptive optics capable of correcting wave front errors with large amplitude relatively low spatial frequency aberrations. The use of low modulus membrane mirrors actuated with electrostatic attraction forces is a potential solution for this application. Several different electrostatic membrane mirrors are now available commercially. However, as the dynamic range requirement of the adaptive mirror is increased the separation distance between the membrane and the electrodes must increase to accommodate the required face sheet deformations. The actuation force applied to the mirror decreases inversely proportional to the square of the separation distance; thus for large dynamic ranges the voltage requirement can rapidly increase into the high voltage regime. Experimentation with mirrors operating in the KV range has shown that at the higher voltages a serious problem with electrostatic field cross coupling between actuators can occur. Voltage changes on individual actuators affect the voltage of other actuators making the system very difficult to control. A novel solution has been proposed that combines high voltage electrodes with mechanical actuation to overcome this problem. In this design an array of electrodes are mounted to a backing structure via light weight large dynamic range flextensional actuators. With this design the control input becomes the separation distance between the electrode and the mirror. The voltage on each of the actuators is set to a uniform relatively high voltage, thus the problem of cross talk between actuators is avoided and the favorable distributed load characteristic of electrostatic actuation is retained. Initial testing and modeling of this concept demonstrates that this is an attractive concept for increasing the dynamic range capability of electrostatic deformable mirrors.

Eleven years of crop diversification alters decomposition dynamics of litter mixtures incubated with soil

DOE PAGES

McDaniel, M. D.; Grandy, A. S.; Tiemann, L. K.; ...

2016-08-11

Agricultural crop rotations have been shown to increase soil carbon (C), nitrogen (N), and microbial biomass. The mechanisms behind these increases remain unclear, but may be linked to the diversity of crop residue inputs to soil organic matter (SOM). Here, we used a residue mixture incubation to examine how variation in long-term diversity of plant communities in agroecosystems influences decomposition of residue mixtures, thus providing a comparison of the effects of plant diversification on decomposition in the long term (via crop rotation) and short term (via residue mixtures). Three crop residue mixtures, ranging in diversity from two to four species,more » were incubated for 360 d with soils from five crop rotations, ranging from monoculture corn (mC) to a complex five-crop rotation. In response, we measured fundamental soil pools and processes underlying C and N cycling. These included soil respiration, inorganic N, microbial biomass, and extracellular enzymes. We hypothesized that soils with more diverse cropping histories would show greater synergistic mixture effects than mC. For most variables (except extracellular enzymes), crop rotation history, or the long-term history of plant diversity in the field, had a stronger effect on soil processes than mixture composition. In contrast to our hypothesis, the mC soil had nearly three and seven times greater synergistic mixture effects for respiration and microbial biomass N, respectively, compared with soils from crop rotations. This was due to the low response of the mC soils to poor quality residues (corn and wheat), likely resulting from a lack of available C and nutrients to cometabolize these residues. These results indicate that diversifying crop rotations in agricultural systems alter the decomposition dynamics of new residue inputs, which may be linked to the benefits of increasing crop rotation diversity on soil nutrient cycling, SOM dynamics, and yields.« less

A multiscale active structural model of the arterial wall accounting for smooth muscle dynamics.

PubMed

Coccarelli, Alberto; Edwards, David Hughes; Aggarwal, Ankush; Nithiarasu, Perumal; Parthimos, Dimitris

2018-02-01

Arterial wall dynamics arise from the synergy of passive mechano-elastic properties of the vascular tissue and the active contractile behaviour of smooth muscle cells (SMCs) that form the media layer of vessels. We have developed a computational framework that incorporates both these components to account for vascular responses to mechanical and pharmacological stimuli. To validate the proposed framework and demonstrate its potential for testing hypotheses on the pathogenesis of vascular disease, we have employed a number of pharmacological probes that modulate the arterial wall contractile machinery by selectively inhibiting a range of intracellular signalling pathways. Experimental probes used on ring segments from the rabbit central ear artery are: phenylephrine, a selective α 1-adrenergic receptor agonist that induces vasoconstriction; cyclopiazonic acid (CPA), a specific inhibitor of sarcoplasmic/endoplasmic reticulum Ca 2+ -ATPase; and ryanodine, a diterpenoid that modulates Ca 2+ release from the sarcoplasmic reticulum. These interventions were able to delineate the role of membrane versus intracellular signalling, previously identified as main factors in smooth muscle contraction and the generation of vessel tone. Each SMC was modelled by a system of nonlinear differential equations that account for intracellular ionic signalling, and in particular Ca 2+ dynamics. Cytosolic Ca 2+ concentrations formed the catalytic input to a cross-bridge kinetics model. Contractile output from these cellular components forms the input to the finite-element model of the arterial rings under isometric conditions that reproduces the experimental conditions. The model does not account for the role of the endothelium, as the nitric oxide production was suppressed by the action of L-NAME, and also due to the absence of shear stress on the arterial ring, as the experimental set-up did not involve flow. Simulations generated by the integrated model closely matched experimental observations qualitatively, as well as quantitatively within a range of physiological parametric values. The model also illustrated how increased intercellular coupling led to smooth muscle coordination and the genesis of vascular tone. © 2018 The Authors.

A comparison of individual and population-derived vascular input functions for quantitative DCE-MRI in rats.

PubMed

Hormuth, David A; Skinner, Jack T; Does, Mark D; Yankeelov, Thomas E

2014-05-01

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) can quantitatively and qualitatively assess physiological characteristics of tissue. Quantitative DCE-MRI requires an estimate of the time rate of change of the concentration of the contrast agent in the blood plasma, the vascular input function (VIF). Measuring the VIF in small animals is notoriously difficult as it requires high temporal resolution images limiting the achievable number of slices, field-of-view, spatial resolution, and signal-to-noise. Alternatively, a population-averaged VIF could be used to mitigate the acquisition demands in studies aimed to investigate, for example, tumor vascular characteristics. Thus, the overall goal of this manuscript is to determine how the kinetic parameters estimated by a population based VIF differ from those estimated by an individual VIF. Eight rats bearing gliomas were imaged before, during, and after an injection of Gd-DTPA. K(trans), ve, and vp were extracted from signal-time curves of tumor tissue using both individual and population-averaged VIFs. Extended model voxel estimates of K(trans) and ve in all animals had concordance correlation coefficients (CCC) ranging from 0.69 to 0.98 and Pearson correlation coefficients (PCC) ranging from 0.70 to 0.99. Additionally, standard model estimates resulted in CCCs ranging from 0.81 to 0.99 and PCCs ranging from 0.98 to 1.00, supporting the use of a population based VIF if an individual VIF is not available. Copyright © 2014 Elsevier Inc. All rights reserved.

Sierra Structural Dynamics User's Notes

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

Reese, Garth M.

2015-10-19

Sierra/SD provides a massively parallel implementation of structural dynamics finite element analysis, required for high fidelity, validated models used in modal, vibration, static and shock analysis of weapons systems. This document provides a users guide to the input for Sierra/SD. Details of input specifications for the different solution types, output options, element types and parameters are included. The appendices contain detailed examples, and instructions for running the software on parallel platforms.

Data-driven robust approximate optimal tracking control for unknown general nonlinear systems using adaptive dynamic programming method.

PubMed

Zhang, Huaguang; Cui, Lili; Zhang, Xin; Luo, Yanhong

2011-12-01

In this paper, a novel data-driven robust approximate optimal tracking control scheme is proposed for unknown general nonlinear systems by using the adaptive dynamic programming (ADP) method. In the design of the controller, only available input-output data is required instead of known system dynamics. A data-driven model is established by a recurrent neural network (NN) to reconstruct the unknown system dynamics using available input-output data. By adding a novel adjustable term related to the modeling error, the resultant modeling error is first guaranteed to converge to zero. Then, based on the obtained data-driven model, the ADP method is utilized to design the approximate optimal tracking controller, which consists of the steady-state controller and the optimal feedback controller. Further, a robustifying term is developed to compensate for the NN approximation errors introduced by implementing the ADP method. Based on Lyapunov approach, stability analysis of the closed-loop system is performed to show that the proposed controller guarantees the system state asymptotically tracking the desired trajectory. Additionally, the obtained control input is proven to be close to the optimal control input within a small bound. Finally, two numerical examples are used to demonstrate the effectiveness of the proposed control scheme.

Frequency-band signatures of visual responses to naturalistic input in ferret primary visual cortex during free viewing.

PubMed

Sellers, Kristin K; Bennett, Davis V; Fröhlich, Flavio

2015-02-19

Neuronal firing responses in visual cortex reflect the statistics of visual input and emerge from the interaction with endogenous network dynamics. Artificial visual stimuli presented to animals in which the network dynamics were constrained by anesthetic agents or trained behavioral tasks have provided fundamental understanding of how individual neurons in primary visual cortex respond to input. In contrast, very little is known about the mesoscale network dynamics and their relationship to microscopic spiking activity in the awake animal during free viewing of naturalistic visual input. To address this gap in knowledge, we recorded local field potential (LFP) and multiunit activity (MUA) simultaneously in all layers of primary visual cortex (V1) of awake, freely viewing ferrets presented with naturalistic visual input (nature movie clips). We found that naturalistic visual stimuli modulated the entire oscillation spectrum; low frequency oscillations were mostly suppressed whereas higher frequency oscillations were enhanced. In average across all cortical layers, stimulus-induced change in delta and alpha power negatively correlated with the MUA responses, whereas sensory-evoked increases in gamma power positively correlated with MUA responses. The time-course of the band-limited power in these frequency bands provided evidence for a model in which naturalistic visual input switched V1 between two distinct, endogenously present activity states defined by the power of low (delta, alpha) and high (gamma) frequency oscillatory activity. Therefore, the two mesoscale activity states delineated in this study may define the degree of engagement of the circuit with the processing of sensory input. Copyright © 2014 Elsevier B.V. All rights reserved.

A comprehensive study of the delay vector variance method for quantification of nonlinearity in dynamical systems

PubMed Central

Mandic, D. P.; Ryan, K.; Basu, B.; Pakrashi, V.

2016-01-01

Although vibration monitoring is a popular method to monitor and assess dynamic structures, quantification of linearity or nonlinearity of the dynamic responses remains a challenging problem. We investigate the delay vector variance (DVV) method in this regard in a comprehensive manner to establish the degree to which a change in signal nonlinearity can be related to system nonlinearity and how a change in system parameters affects the nonlinearity in the dynamic response of the system. A wide range of theoretical situations are considered in this regard using a single degree of freedom (SDOF) system to obtain numerical benchmarks. A number of experiments are then carried out using a physical SDOF model in the laboratory. Finally, a composite wind turbine blade is tested for different excitations and the dynamic responses are measured at a number of points to extend the investigation to continuum structures. The dynamic responses were measured using accelerometers, strain gauges and a Laser Doppler vibrometer. This comprehensive study creates a numerical and experimental benchmark for structurally dynamical systems where output-only information is typically available, especially in the context of DVV. The study also allows for comparative analysis between different systems driven by the similar input. PMID:26909175

Nitrogen and phosphorus limitation over long-term ecosystem development in terrestrial ecosystems.

PubMed

Menge, Duncan N L; Hedin, Lars O; Pacala, Stephen W

2012-01-01

Nutrient limitation to net primary production (NPP) displays a diversity of patterns as ecosystems develop over a range of timescales. For example, some ecosystems transition from N limitation on young soils to P limitation on geologically old soils, whereas others appear to remain N limited. Under what conditions should N limitation and P limitation prevail? When do transitions between N and P limitation occur? We analyzed transient dynamics of multiple timescales in an ecosystem model to investigate these questions. Post-disturbance dynamics in our model are controlled by a cascade of rates, from plant uptake (very fast) to litter turnover (fast) to plant mortality (intermediate) to plant-unavailable nutrient loss (slow) to weathering (very slow). Young ecosystems are N limited when symbiotic N fixation (SNF) is constrained and P weathering inputs are high relative to atmospheric N deposition and plant N:P demand, but P limited under opposite conditions. In the absence of SNF, N limitation is likely to worsen through succession (decades to centuries) because P is mineralized faster than N. Over long timescales (centuries and longer) this preferential P mineralization increases the N:P ratio of soil organic matter, leading to greater losses of plant-unavailable N versus P relative to plant N:P demand. These loss dynamics favor N limitation on older soils despite the rising organic matter N:P ratio. However, weathering depletion favors P limitation on older soils when continual P inputs (e.g., dust deposition) are low, so nutrient limitation at the terminal equilibrium depends on the balance of these input and loss effects. If NPP switches from N to P limitation over long time periods, the transition time depends most strongly on the P weathering rate. At all timescales SNF has the capacity to overcome N limitation, so nutrient limitation depends critically on limits to SNF.

Production of Carbon Occluded in Phytolith Is Season-Dependent in a Bamboo Forest in Subtropical China

PubMed Central

Huang, Zhang-Ting; Jiang, Pei-Kun; Chang, Scott Xiaochuan; Zhang, Yan; Ying, Yu-Qi

2014-01-01

Carbon (C) occluded in phytolith (PhytOC) is a stable form of C; when PhytOC is returned to the soil through litterfall it is stored in the soil which can be an effective way for long-term C sequestration. However, few estimates on the rate of PhytOC input to the soil are available. To better understand the seasonal dynamics of PhytOC production and the annual rate of stable C sequestration through PhytOC input, we quantified the monthly litterfall, phytolith and PhytOC return to the soil over a year in a typical Lei bamboo (Phyllostachys praecox) forest in subtropical China. The monthly litterfall ranged between 14.81 and 131.18 g m−2, and the phytolith concentration in the monthly litterfall samples ranged between 47.21 and 101.68 g kg−1 of litter mass, with the PhytOC concentration in the phytolith ranged between 29.4 and 44.9 g kg−1 of phytolith, equivalent to 1.8–3.6 g kg−1 of PhytOC in the litterfall (based on litterfall dry mass). The amount of phytolith input to the soil system was 292.21±69.12 (mean±SD) kg ha−1 yr−1, sequestering 41.45±9.32 kg CO2−e ha−1 yr−1 of C in the studied Lei bamboo forest. This rate of C sequestration through the formation of PhytOC found in this study falls within the range of rates for other grass-type species reported in the literature. We conclude that return of C occluded in phytolith to the soil can be a substantial source of stable soil C and finding means to increase PhytOC storage in the soil should be able to play a significant role in mitigating the rapidly increasing atmospheric CO2 concentration. PMID:25188462

Impact of environmental inputs on reverse-engineering approach to network structures.

PubMed

Wu, Jianhua; Sinfield, James L; Buchanan-Wollaston, Vicky; Feng, Jianfeng

2009-12-04

Uncovering complex network structures from a biological system is one of the main topic in system biology. The network structures can be inferred by the dynamical Bayesian network or Granger causality, but neither techniques have seriously taken into account the impact of environmental inputs. With considerations of natural rhythmic dynamics of biological data, we propose a system biology approach to reveal the impact of environmental inputs on network structures. We first represent the environmental inputs by a harmonic oscillator and combine them with Granger causality to identify environmental inputs and then uncover the causal network structures. We also generalize it to multiple harmonic oscillators to represent various exogenous influences. This system approach is extensively tested with toy models and successfully applied to a real biological network of microarray data of the flowering genes of the model plant Arabidopsis Thaliana. The aim is to identify those genes that are directly affected by the presence of the sunlight and uncover the interactive network structures associating with flowering metabolism. We demonstrate that environmental inputs are crucial for correctly inferring network structures. Harmonic causal method is proved to be a powerful technique to detect environment inputs and uncover network structures, especially when the biological data exhibit periodic oscillations.

A Neural-Dynamic Architecture for Concurrent Estimation of Object Pose and Identity

PubMed Central

Lomp, Oliver; Faubel, Christian; Schöner, Gregor

2017-01-01

Handling objects or interacting with a human user about objects on a shared tabletop requires that objects be identified after learning from a small number of views and that object pose be estimated. We present a neurally inspired architecture that learns object instances by storing features extracted from a single view of each object. Input features are color and edge histograms from a localized area that is updated during processing. The system finds the best-matching view for the object in a novel input image while concurrently estimating the object’s pose, aligning the learned view with current input. The system is based on neural dynamics, computationally operating in real time, and can handle dynamic scenes directly off live video input. In a scenario with 30 everyday objects, the system achieves recognition rates of 87.2% from a single training view for each object, while also estimating pose quite precisely. We further demonstrate that the system can track moving objects, and that it can segment the visual array, selecting and recognizing one object while suppressing input from another known object in the immediate vicinity. Evaluation on the COIL-100 dataset, in which objects are depicted from different viewing angles, revealed recognition rates of 91.1% on the first 30 objects, each learned from four training views. PMID:28503145

Management of postural sensory conflict and dynamic balance control in late-stage Parkinson's disease.

PubMed

Colnat-Coulbois, S; Gauchard, G C; Maillard, L; Barroche, G; Vespignani, H; Auque, J; Perrin, P P

2011-10-13

Parkinson's disease (PD) is known to affect postural control, especially in situations needing a change in balance strategy or when a concurrent task is simultaneously performed. However, few studies assessing postural control in patients with PD included homogeneous population in late stage of the disease. Thus, this study aimed to analyse postural control and strategies in a homogeneous population of patients with idiopathic advanced (late-stage) PD, and to determine the contribution of peripheral inputs in simple and more complex postural tasks, such as sensory conflicting and dynamic tasks. Twenty-four subjects with advanced PD (duration: median (M)=11.0 years, interquartile range (IQR)=4.3 years; Unified Parkinson's Disease Rating Scale (UPDRS): M "on-dopa"=13.5, IQR=7.8; UPDRS: M "off-dopa"=48.5, IQR=16.8; Hoehn and Yahr stage IV in all patients) and 48 age-matched healthy controls underwent static (SPT) and dynamic posturographic (DPT) tests and a sensory organization test (SOT). In SPT, patients with PD showed reduced postural control precision with increased oscillations in both anterior-posterior and medial-lateral planes. In SOT, patients with PD displayed reduced postural performances especially in situations in which visual and vestibular cues became predominant to organize balance control, as was the ability to manage balance in situations for which visual or proprioceptive inputs are disrupted. In DPT, postural restabilization strategies were often inefficient to maintain equilibrium resulting in falls. Postural strategies were often precarious, postural regulation involving more hip joint than ankle joint in patients with advanced PD than in controls. Difficulties in managing complex postural situations, such as sensory conflicting and dynamic situations might reflect an inadequate sensory organization suggesting impairment in central information processing. Copyright © 2011. Published by Elsevier Ltd.

Characterizing Feedback Control Mechanisms in Nonlinear Microbial Models of Soil Organic Matter Decomposition by Stability Analysis

NASA Astrophysics Data System (ADS)

Georgiou, K.; Tang, J.; Riley, W. J.; Torn, M. S.

2014-12-01

Soil organic matter (SOM) decomposition is regulated by biotic and abiotic processes. Feedback interactions between such processes may act to dampen oscillatory responses to perturbations from equilibrium. Indeed, although biological oscillations have been observed in small-scale laboratory incubations, the overlying behavior at the plot-scale exhibits a relatively stable response to disturbances in input rates and temperature. Recent studies have demonstrated the ability of microbial models to capture nonlinear feedbacks in SOM decomposition that linear Century-type models are unable to reproduce, such as soil priming in response to increased carbon input. However, these microbial models often exhibit strong oscillatory behavior that is deemed unrealistic. The inherently nonlinear dynamics of SOM decomposition have important implications for global climate-carbon and carbon-concentration feedbacks. It is therefore imperative to represent these dynamics in Earth System Models (ESMs) by introducing sub-models that accurately represent microbial and abiotic processes. In the present study we explore, both analytically and numerically, four microbe-enabled model structures of varying levels of complexity. The most complex model combines microbial physiology, a non-linear mineral sorption isotherm, and enzyme dynamics. Based on detailed stability analysis of the nonlinear dynamics, we calculate the system modes as functions of model parameters. This dependence provides insight into the source of state oscillations. We find that feedback mechanisms that emerge from careful representation of enzyme and mineral interactions, with parameter values in a prescribed range, are critical for both maintaining system stability and capturing realistic responses to disturbances. Corroborating and expanding upon the results of recent studies, we explain the emergence of oscillatory responses and discuss the appropriate microbe-enabled model structure for inclusion in ESMs.

Underestimation of myocardial blood flow by dynamic perfusion CT: Explanations by two-compartment model analysis and limited temporal sampling of dynamic CT.

PubMed

Ishida, Masaki; Kitagawa, Kakuya; Ichihara, Takashi; Natsume, Takahiro; Nakayama, Ryohei; Nagasawa, Naoki; Kubooka, Makiko; Ito, Tatsuro; Uno, Mio; Goto, Yoshitaka; Nagata, Motonori; Sakuma, Hajime

2016-01-01

Previous studies using dynamic perfusion CT and volume perfusion CT (VPCT) software consistently underestimated the stress myocardial blood flow (MBF) in normal myocardium to be 1.1-1.4 ml/min/g, whilst the O 15-water PET studies demonstrated the normal stress MBF of 3-5 ml/min/g. We hypothesized that the MBF determined by VPCT (MBF-VPCT) is actually presenting the blood-to-myocardium transfer constant, K1. In this study, we determined K1 using Patlak plot (K1-Patlak) and compared the results with MBF-VPCT. 17 patients (66 ± 9 years, 7 males) with suspected coronary artery disease (CAD) underwent stress dynamic perfusion CT, followed by rest coronary CT angiography (CTA). Arterial input and myocardial output curves were analyzed with Patlak plot to quantify myocardial K1. Significant CAD was defined as >50% stenosis on CTA. A simulation study was also performed to investigate the influence of limited temporal sampling in dynamic CT acquisition on K1 using the undersampling data generated from MRI. There were 3 patients with normal CTA, 7 patients with non-significant CAD, and 7 patients with significant CAD. K1-patlak was 0.98 ± 0.35 (range 0.22-1.67) ml/min/g, whereas MBF-VPCT was 0.83 ± 0.23 (range 0.34-1.40) ml/min/g. There was a linear relationship between them: (MBF-VPCT) = 0.58 x (K1-patlak) + 0.27 (r(2) = 0.65, p < 0.001). The simulation study done on MRI data demonstrated that Patlak plot substantially underestimated true K1 by 41% when true K1 was 2.0 ml/min/g with the temporal sampling of 2RR for arterial input and 4RR for myocardial output functions. The results of our study are generating hypothesis that MBF-VPCT is likely to be calculating K1-patlak equivalent, not MBF. In addition, these values may be substantially underestimated because of limited temporal sampling rate. Copyright © 2016 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Phase transition of Boolean networks with partially nested canalizing functions

NASA Astrophysics Data System (ADS)

Jansen, Kayse; Matache, Mihaela Teodora

2013-07-01

We generate the critical condition for the phase transition of a Boolean network governed by partially nested canalizing functions for which a fraction of the inputs are canalizing, while the remaining non-canalizing inputs obey a complementary threshold Boolean function. Past studies have considered the stability of fully or partially nested canalizing functions paired with random choices of the complementary function. In some of those studies conflicting results were found with regard to the presence of chaotic behavior. Moreover, those studies focus mostly on ergodic networks in which initial states are assumed equally likely. We relax that assumption and find the critical condition for the sensitivity of the network under a non-ergodic scenario. We use the proposed mathematical model to determine parameter values for which phase transitions from order to chaos occur. We generate Derrida plots to show that the mathematical model matches the actual network dynamics. The phase transition diagrams indicate that both order and chaos can occur, and that certain parameters induce a larger range of values leading to order versus chaos. The edge-of-chaos curves are identified analytically and numerically. It is shown that the depth of canalization does not cause major dynamical changes once certain thresholds are reached; these thresholds are fairly small in comparison to the connectivity of the nodes.

Disordered crystals from first principles I: Quantifying the configuration space

NASA Astrophysics Data System (ADS)

Kühne, Thomas D.; Prodan, Emil

2018-04-01

This work represents the first chapter of a project on the foundations of first-principle calculations of the electron transport in crystals at finite temperatures. We are interested in the range of temperatures, where most electronic components operate, that is, room temperature and above. The aim is a predictive first-principle formalism that combines ab-initio molecular dynamics and a finite-temperature Kubo-formula for homogeneous thermodynamic phases. The input for this formula is the ergodic dynamical system (Ω , G , dP) defining the thermodynamic crystalline phase, where Ω is the configuration space for the atomic degrees of freedom, G is the space group acting on Ω and dP is the ergodic Gibbs measure relative to the G-action. The present work develops an algorithmic method for quantifying (Ω , G , dP) from first principles. Using the silicon crystal as a working example, we find the Gibbs measure to be extremely well characterized by a multivariate normal distribution, which can be quantified using a small number of parameters. The latter are computed at various temperatures and communicated in the form of a table. Using this table, one can generate large and accurate thermally-disordered atomic configurations to serve, for example, as input for subsequent simulations of the electronic degrees of freedom.

Ankle Joint Intrinsic Dynamics is More Complex than a Mass-Spring-Damper Model.

PubMed

Sobhani Tehrani, Ehsan; Jalaleddini, Kian; Kearney, Robert E

2017-09-01

This paper describes a new small signal parametric model of ankle joint intrinsic mechanics in normal subjects. We found that intrinsic ankle mechanics is a third-order system and the second-order mass-spring-damper model, referred to as IBK, used by many researchers in the literature cannot adequately represent ankle dynamics at all frequencies in a number of important tasks. This was demonstrated using experimental data from five healthy subjects with no voluntary muscle contraction and at seven ankle positions covering the range of motion. We showed that the difference between the new third-order model and the conventional IBK model increased from dorsi to plantarflexed position. The new model was obtained using a multi-step identification procedure applied to experimental input/output data of the ankle joint. The procedure first identifies a non-parametric model of intrinsic joint stiffness where ankle position is the input and torque is the output. Then, in several steps, the model is converted into a continuous-time transfer function of ankle compliance, which is the inverse of stiffness. Finally, we showed that the third-order model is indeed structurally consistent with agonist-antagonist musculoskeletal structure of human ankle, which is not the case for the IBK model.

Development and Testing of a High Level Axial Array Duct Sound Source for the NASA Flow Impedance Test Facility

NASA Technical Reports Server (NTRS)

Johnson, Marty E.; Fuller, Chris R.; Jones, Michael G. (Technical Monitor)

2000-01-01

In this report both a frequency domain method for creating high level harmonic excitation and a time domain inverse method for creating large pulses in a duct are developed. To create controllable, high level sound an axial array of six JBL-2485 compression drivers was used. The pressure downstream is considered as input voltages to the sources filtered by the natural dynamics of the sources and the duct. It is shown that this dynamic behavior can be compensated for by filtering the inputs such that both time delays and phase changes are taken into account. The methods developed maximize the sound output while (i) keeping within the power constraints of the sources and (ii) maintaining a suitable level of reproduction accuracy. Harmonic excitation pressure levels of over 155dB were created experimentally over a wide frequency range (1000-4000Hz). For pulse excitation there is a tradeoff between accuracy of reproduction and sound level achieved. However, the accurate reproduction of a pulse with a maximum pressure level over 6500Pa was achieved experimentally. It was also shown that the throat connecting the driver to the duct makes it difficult to inject sound just below the cut-on of each acoustic mode (pre cut-on loading effect).

Random Testing and Model Checking: Building a Common Framework for Nondeterministic Exploration

NASA Technical Reports Server (NTRS)

Groce, Alex; Joshi, Rajeev

2008-01-01

Two popular forms of dynamic analysis, random testing and explicit-state software model checking, are perhaps best viewed as search strategies for exploring the state spaces introduced by nondeterminism in program inputs. We present an approach that enables this nondeterminism to be expressed in the SPIN model checker's PROMELA language, and then lets users generate either model checkers or random testers from a single harness for a tested C program. Our approach makes it easy to compare model checking and random testing for models with precisely the same input ranges and probabilities and allows us to mix random testing with model checking's exhaustive exploration of non-determinism. The PROMELA language, as intended in its design, serves as a convenient notation for expressing nondeterminism and mixing random choices with nondeterministic choices. We present and discuss a comparison of random testing and model checking. The results derive from using our framework to test a C program with an effectively infinite state space, a module in JPL's next Mars rover mission. More generally, we show how the ability of the SPIN model checker to call C code can be used to extend SPIN's features, and hope to inspire others to use the same methods to implement dynamic analyses that can make use of efficient state storage, matching, and backtracking.

Electron density and gas density measurements in a millimeter-wave discharge

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

Schaub, S. C., E-mail: sschaub@mit.edu; Hummelt, J. S.; Guss, W. C.

2016-08-15

Electron density and neutral gas density have been measured in a non-equilibrium air breakdown plasma using optical emission spectroscopy and two-dimensional laser interferometry, respectively. A plasma was created with a focused high frequency microwave beam in air. Experiments were run with 110 GHz and 124.5 GHz microwaves at powers up to 1.2 MW. Microwave pulses were 3 μs long at 110 GHz and 2.2 μs long at 124.5 GHz. Electron density was measured over a pressure range of 25 to 700 Torr as the input microwave power was varied. Electron density was found to be close to the critical density, where the collisional plasma frequency is equal tomore » the microwave frequency, over the pressure range studied and to vary weakly with input power. Neutral gas density was measured over a pressure range from 150 to 750 Torr at power levels high above the threshold for initiating breakdown. The two-dimensional structure of the neutral gas density was resolved. Intense, localized heating was found to occur hundreds of nanoseconds after visible plasma formed. This heating led to neutral gas density reductions of greater than 80% where peak plasma densities occurred. Spatial structure and temporal dynamics of gas heating at atmospheric pressure were found to agree well with published numerical simulations.« less

Illumination normalization of face image based on illuminant direction estimation and improved Retinex.

PubMed

Yi, Jizheng; Mao, Xia; Chen, Lijiang; Xue, Yuli; Rovetta, Alberto; Caleanu, Catalin-Daniel

2015-01-01

Illumination normalization of face image for face recognition and facial expression recognition is one of the most frequent and difficult problems in image processing. In order to obtain a face image with normal illumination, our method firstly divides the input face image into sixteen local regions and calculates the edge level percentage in each of them. Secondly, three local regions, which meet the requirements of lower complexity and larger average gray value, are selected to calculate the final illuminant direction according to the error function between the measured intensity and the calculated intensity, and the constraint function for an infinite light source model. After knowing the final illuminant direction of the input face image, the Retinex algorithm is improved from two aspects: (1) we optimize the surround function; (2) we intercept the values in both ends of histogram of face image, determine the range of gray levels, and stretch the range of gray levels into the dynamic range of display device. Finally, we achieve illumination normalization and get the final face image. Unlike previous illumination normalization approaches, the method proposed in this paper does not require any training step or any knowledge of 3D face and reflective surface model. The experimental results using extended Yale face database B and CMU-PIE show that our method achieves better normalization effect comparing with the existing techniques.

Bioluminescence in a complex coastal environment: 1. Temporal dynamics of nighttime water-leaving radiance

NASA Astrophysics Data System (ADS)

Moline, Mark A.; Oliver, Matthew J.; Mobley, Curtis D.; Sundman, Lydia; Bensky, Thomas; Bergmann, Trisha; Bissett, W. Paul; Case, James; Raymond, Erika H.; Schofield, Oscar M. E.

2007-11-01

Nighttime water-leaving radiance is a function of the depth-dependent distribution of both the in situ bioluminescence emissions and the absorption and scattering properties of the water. The vertical distributions of these parameters were used as inputs for a modified one-dimensional radiative transfer model to solve for spectral bioluminescence water-leaving radiance from prescribed depths of the water column. Variation in the water-leaving radiance was consistent with local episodic physical forcing events, with tidal forcing, terrestrial runoff, particulate accumulation, and biological responses influencing the shorter timescale dynamics. There was a >90 nm shift in the peak water-leaving radiance from blue (˜474 nm) to green as light propagated to the surface. In addition to clues in ecosystem responses to physical forcing, the temporal dynamics in intensity and spectral quality of water-leaving radiance provide suitable ranges for assessing detection. This may provide the information needed to estimate the depth of internal light sources in the ocean, which is discussed in part 2 of this paper.

A neural-network-based model for the dynamic simulation of the tire/suspension system while traversing road irregularities.

PubMed

Guarneri, Paolo; Rocca, Gianpiero; Gobbi, Massimiliano

2008-09-01

This paper deals with the simulation of the tire/suspension dynamics by using recurrent neural networks (RNNs). RNNs are derived from the multilayer feedforward neural networks, by adding feedback connections between output and input layers. The optimal network architecture derives from a parametric analysis based on the optimal tradeoff between network accuracy and size. The neural network can be trained with experimental data obtained in the laboratory from simulated road profiles (cleats). The results obtained from the neural network demonstrate good agreement with the experimental results over a wide range of operation conditions. The NN model can be effectively applied as a part of vehicle system model to accurately predict elastic bushings and tire dynamics behavior. Although the neural network model, as a black-box model, does not provide a good insight of the physical behavior of the tire/suspension system, it is a useful tool for assessing vehicle ride and noise, vibration, harshness (NVH) performance due to its good computational efficiency and accuracy.

Hysteresis compensation for piezoelectric actuators in single-point diamond turning

NASA Astrophysics Data System (ADS)

Wang, Haifeng; Hu, Dejin; Wan, Daping; Liu, Hongbin

2006-02-01

In recent years, interests have been growing for fast tool servo (FTS) systems to increase the capability of existing single-point diamond turning machines. Although piezoelectric actuator is the most universal base of FTS system due to its high stiffness, accuracy and bandwidth, nonlinearity in piezoceramics limits both the static and dynamic performance of piezoelectric-actuated control systems evidently. To compensate the nonlinear hysteresis behavior of piezoelectric actuators, a hybrid model coupled with Preisach model and feedforward neural network (FNN) has been described. Since the training of FNN does not require a special calibration sequence, it is possible for on-line identification and real-time implementation with general operating data of a specific piezoelectric actuator. To describe the rate dependent behavior of piezoelectric actuators, a hybrid dynamic model was developed to predict the response of piezoelectric actuators in a wider range of input frequency. Experimental results show that a maximal error of less than 3% was accomplished by this dynamic model.

New activity pattern in human interactive dynamics

NASA Astrophysics Data System (ADS)

Formentin, Marco; Lovison, Alberto; Maritan, Amos; Zanzotto, Giovanni

2015-09-01

We investigate the response function of human agents as demonstrated by written correspondence, uncovering a new pattern for how the reactive dynamics of individuals is distributed across the set of each agent’s contacts. In long-term empirical data on email, we find that the set of response times considered separately for the messages to each different correspondent of a given writer, generate a family of heavy-tailed distributions, which have largely the same features for all agents, and whose characteristic times grow exponentially with the rank of each correspondent. We furthermore show that this new behavioral pattern emerges robustly by considering weighted moving averages of the priority-conditioned response-time probabilities generated by a basic prioritization model. Our findings clarify how the range of priorities in the inputs from one’s environment underpin and shape the dynamics of agents embedded in a net of reactive relations. These newly revealed activity patterns might be universal, being present in other general interactive environments, and constrain future models of communication and interaction networks, affecting their architecture and evolution.

Cluster Synchronization of Diffusively Coupled Nonlinear Systems: A Contraction-Based Approach

NASA Astrophysics Data System (ADS)

Aminzare, Zahra; Dey, Biswadip; Davison, Elizabeth N.; Leonard, Naomi Ehrich

2018-04-01

Finding the conditions that foster synchronization in networked nonlinear systems is critical to understanding a wide range of biological and mechanical systems. However, the conditions proved in the literature for synchronization in nonlinear systems with linear coupling, such as has been used to model neuronal networks, are in general not strict enough to accurately determine the system behavior. We leverage contraction theory to derive new sufficient conditions for cluster synchronization in terms of the network structure, for a network where the intrinsic nonlinear dynamics of each node may differ. Our result requires that network connections satisfy a cluster-input-equivalence condition, and we explore the influence of this requirement on network dynamics. For application to networks of nodes with FitzHugh-Nagumo dynamics, we show that our new sufficient condition is tighter than those found in previous analyses that used smooth or nonsmooth Lyapunov functions. Improving the analytical conditions for when cluster synchronization will occur based on network configuration is a significant step toward facilitating understanding and control of complex networked systems.

Design and performance of clock-recovery GaAs ICs for high-speed optical communication systems

NASA Astrophysics Data System (ADS)

Imai, Yuhki; Sano, Eiichi; Nakamura, Makoto; Ishihara, Noboru; Kikuchi, Hiroyuki; Ono, Takashi

1993-05-01

Design and performance of clock-recovery GaAs ICs are presented. Four kinds of ICs were developed: a limiting amplifier, a tuning amplifier, a rectifier, and a differentiator. The cascaded limiting amplifier together with a tuning amplifier achieved a 58-dB gain and a 10-degree phase deviation with 20-dB input dynamic range at 10 GHz. A clock-recovery circuit successfully extracts a low-jitter 10-GHz clock signal of 1-dBm constant power from 10-Gb/s NRZ pseudorandom bit streams using a pulse pattern generator.

Establishing a learning foundation in a dynamically changing world: Insights from artificial language work

NASA Astrophysics Data System (ADS)

Gonzales, Kalim

It is argued that infants build a foundation for learning about the world through their incidental acquisition of the spatial and temporal regularities surrounding them. A challenge is that learning occurs across multiple contexts whose statistics can greatly differ. Two artificial language studies with 12-month-olds demonstrate that infants come prepared to parse statistics across contexts using the temporal and perceptual features that distinguish one context from another. These results suggest that infants can organize their statistical input with a wider range of features that typically considered. Possible attention, decision making, and memory mechanisms are discussed.

A sensorless method for measuring the point mobility of mechanical structures

NASA Astrophysics Data System (ADS)

Boulandet, R.; Michau, M.; Herzog, P.; Micheau, P.; Berry, A.

2016-09-01

This paper presents a convenient and cost-effective experimental tool for measuring the mobility characteristics of a mechanical structure. The objective is to demonstrate that the point mobility measurement can be performed using only an electrodynamic inertial exciter. Unlike previous work based on voice coil actuators, no load cell or accelerometer is needed. Instead, it is theoretically shown that the mobility characteristics of the structure can be estimated from variations in the electrical input impedance of the actuator fixed onto it, provided that the electromechanical parameters of the actuator are known. The proof of concept is made experimentally using a cheap commercially available actuator on a simply supported plate, leading to a good dynamic range from 100 Hz to 1 kHz. The methodology to assess the basic parameters of the actuator is also given. Measured data are compared to a standard shaker testing and the strengths and weaknesses of the sensorless mobility measuring device are discussed. It is believed that this sensorless mobility measuring device can be a convenient experimental tool to determine the dynamic characteristics of a wide range of mechanical structures.

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.

A high SFDR 6-bit 20-MS/s SAR ADC based on time-domain comparator

NASA Astrophysics Data System (ADS)

Xue, Han; Hua, Fan; Qi, Wei; Huazhong, Yang

2013-08-01

This paper presents a 6-bit 20-MS/s high spurious-free dynamic range (SFDR) and low power successive approximation register analog to digital converter (SAR ADC) for the radio-frequency (RF) transceiver front-end, especially for wireless sensor network (WSN) applications. This ADC adopts the modified common-centroid symmetry layout and the successive approximation register reset circuit to improve the linearity and dynamic range. Prototyped in a 0.18-μm 1P6M CMOS technology, the ADC performs a peak SFDR of 55.32 dB and effective number of bits (ENOB) of 5.1 bit for 10 MS/s. At the sample rate of 20 MS/s and the Nyquist input frequency, the 47.39-dB SFDR and 4.6-ENOB are achieved. The differential nonlinearity (DNL) is less than 0.83 LSB and the integral nonlinearity (INL) is less than 0.82 LSB. The experimental results indicate that this SAR ADC consumes a total of 522 μW power and occupies 0.98 mm2.

Effects and effectiveness of dynamic arm supports: a technical review.

PubMed

van der Heide, Loek A; Gelderblom, Gert Jan; de Witte, Luc P

2015-01-01

Numerous dynamic arm supports have been developed in recent decades to increase independence in the performance of activities of daily living. Much effort and money have been spent on their development and prescription, yet insight into their effects and effectiveness is lacking. This article is a systematic review of evaluations of dynamic arm supports. The 8 technical evaluations, 12 usability evaluations, and 27 outcome studies together make 47 evaluations. Technical evaluations were often used as input for new developments and directed at balancing quality, forces and torques, and range of motion of prototypes. Usability studies were mostly single-measure designs that had varying results as to whether devices were usable for potential users. An increased ability to perform activities of daily living and user satisfaction were reported in outcome studies. However, the use of dynamic arm supports in the home situation was reported to be low. Gaining insight into why devices are not used when their developers believe them to be effective seems crucial for every new dynamic arm support developed. The methodological quality of the outcome studies was often low, so it is important that this is improved in the future.

Dynamic Target Match Signals in Perirhinal Cortex Can Be Explained by Instantaneous Computations That Act on Dynamic Input from Inferotemporal Cortex

PubMed Central

Pagan, Marino

2014-01-01

Finding sought objects requires the brain to combine visual and target signals to determine when a target is in view. To investigate how the brain implements these computations, we recorded neural responses in inferotemporal cortex (IT) and perirhinal cortex (PRH) as macaque monkeys performed a delayed-match-to-sample target search task. Our data suggest that visual and target signals were combined within or before IT in the ventral visual pathway and then passed onto PRH, where they were reformatted into a more explicit target match signal over ∼10–15 ms. Accounting for these dynamics in PRH did not require proposing dynamic computations within PRH itself but, rather, could be attributed to instantaneous PRH computations performed upon an input representation from IT that changed with time. We found that the dynamics of the IT representation arose from two commonly observed features: individual IT neurons whose response preferences were not simply rescaled with time and variable response latencies across the population. Our results demonstrate that these types of time-varying responses have important consequences for downstream computation and suggest that dynamic representations can arise within a feedforward framework as a consequence of instantaneous computations performed upon time-varying inputs. PMID:25122904

Evaluation of Two Guralp Preamplifiers for GS21 Seismometer Application.

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

Merchant, Bion J.; Slad, George William

2015-08-01

Sandia National Laboratories has tested and evaluated two Guralp preamplifiers for use with a GS21 seismometer application. The two preamplifiers have a gain factor of 61.39. The purpose of the preamplifier evaluation was to determine a measured gain factor, transfer function, total harmonic distortion, self-noise, application passband, dynamic range, seismometer calibration pass-through, and to comment on any issues encountered during the evaluation. The test results included in this report were in response to static, tonal, and dynamic input signals. The Guralp GS21 preamplifiers are being evaluated for potential use in the International Monitoring System (IMS) of the Comprehensive Nuclear Test-Ban-Treatymore » Organization (CTBTO). Test methodologies used were based on IEEE Standards 1057 for Digitizing Waveform Recorders and 1241 for Analog to Digital Converters« less

Orbital Maneuvering Engine Feed System Coupled Stability Investigation, Computer User's Manual

NASA Technical Reports Server (NTRS)

Schuman, M. D.; Fertig, K. W.; Hunting, J. K.; Kahn, D. R.

1975-01-01

An operating manual for the feed system coupled stability model was given, in partial fulfillment of a program designed to develop, verify, and document a digital computer model that can be used to analyze and predict engine/feed system coupled instabilities in pressure-fed storable propellant propulsion systems over a frequency range of 10 to 1,000 Hz. The first section describes the analytical approach to modelling the feed system hydrodynamics, combustion dynamics, chamber dynamics, and overall engineering model structure, and presents the governing equations in each of the technical areas. This is followed by the program user's guide, which is a complete description of the structure and operation of the computerized model. Last, appendices provide an alphabetized FORTRAN symbol table, detailed program logic diagrams, computer code listings, and sample case input and output data listings.

Event detection and localization for small mobile robots using reservoir computing.

PubMed

Antonelo, E A; Schrauwen, B; Stroobandt, D

2008-08-01

Reservoir Computing (RC) techniques use a fixed (usually randomly created) recurrent neural network, or more generally any dynamic system, which operates at the edge of stability, where only a linear static readout output layer is trained by standard linear regression methods. In this work, RC is used for detecting complex events in autonomous robot navigation. This can be extended to robot localization tasks which are solely based on a few low-range, high-noise sensory data. The robot thus builds an implicit map of the environment (after learning) that is used for efficient localization by simply processing the input stream of distance sensors. These techniques are demonstrated in both a simple simulation environment and in the physically realistic Webots simulation of the commercially available e-puck robot, using several complex and even dynamic environments.

Nutrient dynamics in tropical rivers, estuarine-lagoons, and coastal ecosystems along the eastern Hainan Island

NASA Astrophysics Data System (ADS)

Li, R. H.; Liu, S. M.; Li, Y. W.; Zhang, G. L.; Ren, J. L.; Zhang, J.

2013-06-01

Nutrient dynamics were studied along the eastern Hainan Island based on field observations during 2006-2009, to understand nutrient biogeochemical processes and to have an overview of human perturbations on coastal ecosystems in this tropical region. The concentrations of nutrients in the rivers had seasonal variations enriched with dissolved inorganic nitrogen (DIN). High riverine concentrations of nitrate were mainly originated from agricultural fertilizer input. The ratios of DIN : PO43- ranged from 37 to 1063, suggesting preferential PO43- relative to nitrogen in the rivers. The areal yields of dissolved silicate (DSi) varied from 76 to 448 × 103 mol km-2 yr-1 due to erosion over the drainage area, inducing high levels of DSi among worldwide tropical systems. Aquaculture ponds contained high concentrations of NH4+ (up to 157 μM) and DON (up to 130 μM). Particulate phosphorus concentrations (0.5 ∼1.4 μM) were in lower level comparied with estuaries around the world. Particulate silicate levels in rivers and lagoons were lower than global average level. Nutrient biogeochemistry in coastal areas were affected by human activities (e.g. aquaculture, agriculture), as well as natural events such as typhoon. Nutrient concentrations were low because open sea water dispersed land-derived nutrients. Nutrient budgets were built based on a steady-state box model, which showed that riverine fluxes would be magnified by estuarine processes (e.g. regeneration, desorption) in the Wenchanghe/Wenjiaohe Estuary, Wanquan River estuary, and the Laoyehai Lagoon except in the Xiaohai Lagoon. Riverine and groundwater input were the major sources of nutrients to the Xiaohai Lagoon and the Laiyehai Lagoon, respectively. Riverine input and aquaculture effluent were the major sources of nutrients to the eastern coastal of Hainan Island. Nutrient inputs to the coastal ecosystem can be increased by typhoon-induced runoff of rainwater, and phytoplankton bloom in the sea would be caused.

Advances in Software Tools for Pre-processing and Post-processing of Overset Grid Computations

NASA Technical Reports Server (NTRS)

Chan, William M.

2004-01-01

Recent developments in three pieces of software for performing pre-processing and post-processing work on numerical computations using overset grids are presented. The first is the OVERGRID graphical interface which provides a unified environment for the visualization, manipulation, generation and diagnostics of geometry and grids. Modules are also available for automatic boundary conditions detection, flow solver input preparation, multiple component dynamics input preparation and dynamics animation, simple solution viewing for moving components, and debris trajectory analysis input preparation. The second is a grid generation script library that enables rapid creation of grid generation scripts. A sample of recent applications will be described. The third is the OVERPLOT graphical interface for displaying and analyzing history files generated by the flow solver. Data displayed include residuals, component forces and moments, number of supersonic and reverse flow points, and various dynamics parameters.

Adaptive Actor-Critic Design-Based Integral Sliding-Mode Control for Partially Unknown Nonlinear Systems With Input Disturbances.

PubMed

Fan, Quan-Yong; Yang, Guang-Hong

2016-01-01

This paper is concerned with the problem of integral sliding-mode control for a class of nonlinear systems with input disturbances and unknown nonlinear terms through the adaptive actor-critic (AC) control method. The main objective is to design a sliding-mode control methodology based on the adaptive dynamic programming (ADP) method, so that the closed-loop system with time-varying disturbances is stable and the nearly optimal performance of the sliding-mode dynamics can be guaranteed. In the first step, a neural network (NN)-based observer and a disturbance observer are designed to approximate the unknown nonlinear terms and estimate the input disturbances, respectively. Based on the NN approximations and disturbance estimations, the discontinuous part of the sliding-mode control is constructed to eliminate the effect of the disturbances and attain the expected equivalent sliding-mode dynamics. Then, the ADP method with AC structure is presented to learn the optimal control for the sliding-mode dynamics online. Reconstructed tuning laws are developed to guarantee the stability of the sliding-mode dynamics and the convergence of the weights of critic and actor NNs. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.

Modeling and validation of autoinducer-mediated bacterial gene expression in microfluidic environments

PubMed Central

Austin, Caitlin M.; Stoy, William; Su, Peter; Harber, Marie C.; Bardill, J. Patrick; Hammer, Brian K.; Forest, Craig R.

2014-01-01

Biosensors exploiting communication within genetically engineered bacteria are becoming increasingly important for monitoring environmental changes. Currently, there are a variety of mathematical models for understanding and predicting how genetically engineered bacteria respond to molecular stimuli in these environments, but as sensors have miniaturized towards microfluidics and are subjected to complex time-varying inputs, the shortcomings of these models have become apparent. The effects of microfluidic environments such as low oxygen concentration, increased biofilm encapsulation, diffusion limited molecular distribution, and higher population densities strongly affect rate constants for gene expression not accounted for in previous models. We report a mathematical model that accurately predicts the biological response of the autoinducer N-acyl homoserine lactone-mediated green fluorescent protein expression in reporter bacteria in microfluidic environments by accommodating these rate constants. This generalized mass action model considers a chain of biomolecular events from input autoinducer chemical to fluorescent protein expression through a series of six chemical species. We have validated this model against experimental data from our own apparatus as well as prior published experimental results. Results indicate accurate prediction of dynamics (e.g., 14% peak time error from a pulse input) and with reduced mean-squared error with pulse or step inputs for a range of concentrations (10 μM–30 μM). This model can help advance the design of genetically engineered bacteria sensors and molecular communication devices. PMID:25379076

Phase Difference between Model Cortical Areas Determines Level of Information Transfer

PubMed Central

ter Wal, Marije; Tiesinga, Paul H.

2017-01-01

Communication between cortical sites is mediated by long-range synaptic connections. However, these connections are relatively static, while everyday cognitive tasks demand a fast and flexible routing of information in the brain. Synchronization of activity between distant cortical sites has been proposed as the mechanism underlying such a dynamic communication structure. Here, we study how oscillatory activity affects the excitability and input-output relation of local cortical circuits and how it alters the transmission of information between cortical circuits. To this end, we develop model circuits showing fast oscillations by the PING mechanism, of which the oscillatory characteristics can be altered. We identify conditions for synchronization between two brain circuits and show that the level of intercircuit coherence and the phase difference is set by the frequency difference between the intrinsic oscillations. We show that the susceptibility of the circuits to inputs, i.e., the degree of change in circuit output following input pulses, is not uniform throughout the oscillation period and that both firing rate, frequency and power are differentially modulated by inputs arriving at different phases. As a result, an appropriate phase difference between the circuits is critical for the susceptibility windows of the circuits in the network to align and for information to be efficiently transferred. We demonstrate that changes in synchrony and phase difference can be used to set up or abolish information transfer in a network of cortical circuits. PMID:28232796

Segmentation and learning in the quantitative analysis of microscopy images

NASA Astrophysics Data System (ADS)

Ruggiero, Christy; Ross, Amy; Porter, Reid

2015-02-01

In material science and bio-medical domains the quantity and quality of microscopy images is rapidly increasing and there is a great need to automatically detect, delineate and quantify particles, grains, cells, neurons and other functional "objects" within these images. These are challenging problems for image processing because of the variability in object appearance that inevitably arises in real world image acquisition and analysis. One of the most promising (and practical) ways to address these challenges is interactive image segmentation. These algorithms are designed to incorporate input from a human operator to tailor the segmentation method to the image at hand. Interactive image segmentation is now a key tool in a wide range of applications in microscopy and elsewhere. Historically, interactive image segmentation algorithms have tailored segmentation on an image-by-image basis, and information derived from operator input is not transferred between images. But recently there has been increasing interest to use machine learning in segmentation to provide interactive tools that accumulate and learn from the operator input over longer periods of time. These new learning algorithms reduce the need for operator input over time, and can potentially provide a more dynamic balance between customization and automation for different applications. This paper reviews the state of the art in this area, provides a unified view of these algorithms, and compares the segmentation performance of various design choices.

Excitatory and inhibitory synaptic mechanisms at the first stage of integration in the electroreception system of the shark

PubMed Central

Rotem, Naama; Sestieri, Emanuel; Hounsgaard, Jorn; Yarom, Yosef

2014-01-01

High impulse rate in afferent nerves is a common feature in many sensory systems that serve to accommodate a wide dynamic range. However, the first stage of integration should be endowed with specific properties that enable efficient handling of the incoming information. In elasmobranches, the afferent nerve originating from the ampullae of Lorenzini targets specific neurons located at the Dorsal Octavolateral Nucleus (DON), the first stage of integration in the electroreception system. Using intracellular recordings in an isolated brainstem preparation from the shark we analyze the properties of this afferent pathway. We found that stimulating the afferent nerve activates a mixture of excitatory and inhibitory synapses mediated by AMPA-like and GABAA receptors, respectively. The excitatory synapses that are extremely efficient in activating the postsynaptic neurons display unusual voltage dependence, enabling them to operate as a current source. The inhibitory input is powerful enough to completely eliminate the excitatory action of the afferent nerve but is ineffective regarding other excitatory inputs. These observations can be explained by the location and efficiency of the synapses. We conclude that the afferent nerve provides powerful and reliable excitatory input as well as a feed-forward inhibitory input, which is partially presynaptic in origin. These results question the cellular location within the DON where cancelation of expected incoming signals occurs. PMID:24639631

Reservoir Computing Properties of Neural Dynamics in Prefrontal Cortex

PubMed Central

Procyk, Emmanuel; Dominey, Peter Ford

2016-01-01

Primates display a remarkable ability to adapt to novel situations. Determining what is most pertinent in these situations is not always possible based only on the current sensory inputs, and often also depends on recent inputs and behavioral outputs that contribute to internal states. Thus, one can ask how cortical dynamics generate representations of these complex situations. It has been observed that mixed selectivity in cortical neurons contributes to represent diverse situations defined by a combination of the current stimuli, and that mixed selectivity is readily obtained in randomly connected recurrent networks. In this context, these reservoir networks reproduce the highly recurrent nature of local cortical connectivity. Recombining present and past inputs, random recurrent networks from the reservoir computing framework generate mixed selectivity which provides pre-coded representations of an essentially universal set of contexts. These representations can then be selectively amplified through learning to solve the task at hand. We thus explored their representational power and dynamical properties after training a reservoir to perform a complex cognitive task initially developed for monkeys. The reservoir model inherently displayed a dynamic form of mixed selectivity, key to the representation of the behavioral context over time. The pre-coded representation of context was amplified by training a feedback neuron to explicitly represent this context, thereby reproducing the effect of learning and allowing the model to perform more robustly. This second version of the model demonstrates how a hybrid dynamical regime combining spatio-temporal processing of reservoirs, and input driven attracting dynamics generated by the feedback neuron, can be used to solve a complex cognitive task. We compared reservoir activity to neural activity of dorsal anterior cingulate cortex of monkeys which revealed similar network dynamics. We argue that reservoir computing is a pertinent framework to model local cortical dynamics and their contribution to higher cognitive function. PMID:27286251

Role of intraglomerular circuits in shaping temporally structured responses to naturalistic inhalation-driven sensory input to the olfactory bulb

PubMed Central

Carey, Ryan M.; Sherwood, William Erik; Shipley, Michael T.; Borisyuk, Alla

2015-01-01

Olfaction in mammals is a dynamic process driven by the inhalation of air through the nasal cavity. Inhalation determines the temporal structure of sensory neuron responses and shapes the neural dynamics underlying central olfactory processing. Inhalation-linked bursts of activity among olfactory bulb (OB) output neurons [mitral/tufted cells (MCs)] are temporally transformed relative to those of sensory neurons. We investigated how OB circuits shape inhalation-driven dynamics in MCs using a modeling approach that was highly constrained by experimental results. First, we constructed models of canonical OB circuits that included mono- and disynaptic feedforward excitation, recurrent inhibition and feedforward inhibition of the MC. We then used experimental data to drive inputs to the models and to tune parameters; inputs were derived from sensory neuron responses during natural odorant sampling (sniffing) in awake rats, and model output was compared with recordings of MC responses to odorants sampled with the same sniff waveforms. This approach allowed us to identify OB circuit features underlying the temporal transformation of sensory inputs into inhalation-linked patterns of MC spike output. We found that realistic input-output transformations can be achieved independently by multiple circuits, including feedforward inhibition with slow onset and decay kinetics and parallel feedforward MC excitation mediated by external tufted cells. We also found that recurrent and feedforward inhibition had differential impacts on MC firing rates and on inhalation-linked response dynamics. These results highlight the importance of investigating neural circuits in a naturalistic context and provide a framework for further explorations of signal processing by OB networks. PMID:25717156

An improved method to estimate reflectance parameters for high dynamic range imaging

NASA Astrophysics Data System (ADS)

Li, Shiying; Deguchi, Koichiro; Li, Renfa; Manabe, Yoshitsugu; Chihara, Kunihiro

2008-01-01

Two methods are described to accurately estimate diffuse and specular reflectance parameters for colors, gloss intensity and surface roughness, over the dynamic range of the camera used to capture input images. Neither method needs to segment color areas on an image, or to reconstruct a high dynamic range (HDR) image. The second method improves on the first, bypassing the requirement for specific separation of diffuse and specular reflection components. For the latter method, diffuse and specular reflectance parameters are estimated separately, using the least squares method. Reflection values are initially assumed to be diffuse-only reflection components, and are subjected to the least squares method to estimate diffuse reflectance parameters. Specular reflection components, obtained by subtracting the computed diffuse reflection components from reflection values, are then subjected to a logarithmically transformed equation of the Torrance-Sparrow reflection model, and specular reflectance parameters for gloss intensity and surface roughness are finally estimated using the least squares method. Experiments were carried out using both methods, with simulation data at different saturation levels, generated according to the Lambert and Torrance-Sparrow reflection models, and the second method, with spectral images captured by an imaging spectrograph and a moving light source. Our results show that the second method can estimate the diffuse and specular reflectance parameters for colors, gloss intensity and surface roughness more accurately and faster than the first one, so that colors and gloss can be reproduced more efficiently for HDR imaging.

Study on general theory of kinematics and dynamics of wheeled mobile robots

NASA Astrophysics Data System (ADS)

Tsukishima, Takahiro; Sasaki, Ken; Takano, Masaharu; Inoue, Kenji

1992-03-01

This paper proposes a general theory of kinematics and dynamics of wheeled mobile robots (WMRs). Unlike robotic manipulators which are modeled as 3-dimensional serial link mechanism, WMRs will be modeled as planar linkage mechanism with multiple links branching out from the base and/or another link. Since this model resembles a tree with branches, it will be called 'tree-structured-link'. The end of each link corresponds to the wheel which is in contact with the floor. In dynamics of WMR, equation of motion of a WMR is derived from joint input torques incorporating wheel dynamics. The wheel dynamics determines forces and moments acting on wheels as a function of slip velocity. This slippage of wheels is essential in dynamics of WMR. It will also be shown that the dynamics of WMR reduces to kinematics when slippage of wheels is neglected. Furthermore, the equation of dynamics is rewritten in velocity input form, since most of industrial motors are velocity controlled.

From homeostasis to behavior: Balanced activity in an exploration of embodied dynamic environmental-neural interaction.

PubMed

Hellyer, Peter John; Clopath, Claudia; Kehagia, Angie A; Turkheimer, Federico E; Leech, Robert

2017-08-01

In recent years, there have been many computational simulations of spontaneous neural dynamics. Here, we describe a simple model of spontaneous neural dynamics that controls an agent moving in a simple virtual environment. These dynamics generate interesting brain-environment feedback interactions that rapidly destabilize neural and behavioral dynamics demonstrating the need for homeostatic mechanisms. We investigate roles for homeostatic plasticity both locally (local inhibition adjusting to balance excitatory input) as well as more globally (regional "task negative" activity that compensates for "task positive", sensory input in another region) balancing neural activity and leading to more stable behavior (trajectories through the environment). Our results suggest complementary functional roles for both local and macroscale mechanisms in maintaining neural and behavioral dynamics and a novel functional role for macroscopic "task-negative" patterns of activity (e.g., the default mode network).

Neural field model to reconcile structure with function in primary visual cortex.

PubMed

Rankin, James; Chavane, Frédéric

2017-10-01

Voltage-sensitive dye imaging experiments in primary visual cortex (V1) have shown that local, oriented visual stimuli elicit stable orientation-selective activation within the stimulus retinotopic footprint. The cortical activation dynamically extends far beyond the retinotopic footprint, but the peripheral spread stays non-selective-a surprising finding given a number of anatomo-functional studies showing the orientation specificity of long-range connections. Here we use a computational model to investigate this apparent discrepancy by studying the expected population response using known published anatomical constraints. The dynamics of input-driven localized states were simulated in a planar neural field model with multiple sub-populations encoding orientation. The realistic connectivity profile has parameters controlling the clustering of long-range connections and their orientation bias. We found substantial overlap between the anatomically relevant parameter range and a steep decay in orientation selective activation that is consistent with the imaging experiments. In this way our study reconciles the reported orientation bias of long-range connections with the functional expression of orientation selective neural activity. Our results demonstrate this sharp decay is contingent on three factors, that long-range connections are sufficiently diffuse, that the orientation bias of these connections is in an intermediate range (consistent with anatomy) and that excitation is sufficiently balanced by inhibition. Conversely, our modelling results predict that, for reduced inhibition strength, spurious orientation selective activation could be generated through long-range lateral connections. Furthermore, if the orientation bias of lateral connections is very strong, or if inhibition is particularly weak, the network operates close to an instability leading to unbounded cortical activation.

Soil C dynamics under intensive oil palm plantations in poor tropical soils

NASA Astrophysics Data System (ADS)

Guillaume, Thomas; Ruegg, Johanna; Quezada, Juan Carlos; Buttler, Alexandre

2017-04-01

Oil palm cultivation mainly takes place on heavily-weathered tropical soils where nutrients are limiting factors for plant growth and microbial activity. Intensive fertilization and changes of C input by oil palms strongly affects soil C and nutrient dynamics, challenging long-term soil fertility. Oil palm plantations management offers unique opportunities to study soil C and nutrients interactions in field conditions because 1) they can be considered as long-term litter manipulation experiments since all aboveground C inputs are concentrated in frond pile areas and 2) mineral fertilizers are only applied in specific areas, i.e. weeded circle around the tree and interrows, but not in harvest paths. Here, we determined impacts of mineral fertilizer and organic matter input on soil organic carbon dynamics and microbial activity in mature oil palm plantation established on savanna grasslands. Rates of savanna-derived soil organic carbon (SOC) decomposition and oil palm-derived SOC net stabilization were determined using changes in isotopic signature of in C input following a shift from C4 (savanna) to C3 (oil palm) vegetation. Application of mineral fertilizer alone did not affect savanna-derived SOC decomposition or oil palm-derived SOC stabilization rates, but fertilization associated with higher C input lead to an increase of oil palm-derived SOC stabilization rates, with about 50% of topsoil SOC derived from oil palm after 9 years. High carbon and nutrients inputs did not increase microbial biomass but microorganisms were more active per unit of biomass and SOC. In conclusion, soil organic matter decomposition was limited by C rather than nutrients in the studied heavily-weathered soils. Fresh C and nutrient inputs did not lead to priming of old savanna-derived SOC but increased turnover and stabilization of new oil palm-derived SOC.

Unsteady hovering wake parameters identified from dynamic model tests, part 1

NASA Technical Reports Server (NTRS)

Hohenemser, K. H.; Crews, S. T.

1977-01-01

The development of a 4-bladed model rotor is reported that can be excited with a simple eccentric mechanism in progressing and regressing modes with either harmonic or transient inputs. Parameter identification methods were applied to the problem of extracting parameters for linear perturbation models, including rotor dynamic inflow effects, from the measured blade flapping responses to transient pitch stirring excitations. These perturbation models were then used to predict blade flapping response to other pitch stirring transient inputs, and rotor wake and blade flapping responses to harmonic inputs. The viability and utility of using parameter identification methods for extracting the perturbation models from transients are demonstrated through these combined analytical and experimental studies.

Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Linear Analysis.

PubMed

Henley, B C; Shin, D C; Zhang, R; Marmarelis, V Z

Compartmental and data-based modeling of cerebral hemodynamics are alternative approaches that utilize distinct model forms and have been employed in the quantitative study of cerebral hemodynamics. This paper examines the relation between a compartmental equivalent-circuit and a data-based input-output model of dynamic cerebral autoregulation (DCA) and CO2-vasomotor reactivity (DVR). The compartmental model is constructed as an equivalent-circuit utilizing putative first principles and previously proposed hypothesis-based models. The linear input-output dynamics of this compartmental model are compared with data-based estimates of the DCA-DVR process. This comparative study indicates that there are some qualitative similarities between the two-input compartmental model and experimental results.

An online input force time history reconstruction algorithm using dynamic principal component analysis

NASA Astrophysics Data System (ADS)

Prawin, J.; Rama Mohan Rao, A.

2018-01-01

The knowledge of dynamic loads acting on a structure is always required for many practical engineering problems, such as structural strength analysis, health monitoring and fault diagnosis, and vibration isolation. In this paper, we present an online input force time history reconstruction algorithm using Dynamic Principal Component Analysis (DPCA) from the acceleration time history response measurements using moving windows. We also present an optimal sensor placement algorithm to place limited sensors at dynamically sensitive spatial locations. The major advantage of the proposed input force identification algorithm is that it does not require finite element idealization of structure unlike the earlier formulations and therefore free from physical modelling errors. We have considered three numerical examples to validate the accuracy of the proposed DPCA based method. Effects of measurement noise, multiple force identification, different kinds of loading, incomplete measurements, and high noise levels are investigated in detail. Parametric studies have been carried out to arrive at optimal window size and also the percentage of window overlap. Studies presented in this paper clearly establish the merits of the proposed algorithm for online load identification.

Aircraft Fault Detection Using Real-Time Frequency Response Estimation

NASA Technical Reports Server (NTRS)

Grauer, Jared A.

2016-01-01

A real-time method for estimating time-varying aircraft frequency responses from input and output measurements was demonstrated. The Bat-4 subscale airplane was used with NASA Langley Research Center's AirSTAR unmanned aerial flight test facility to conduct flight tests and collect data for dynamic modeling. Orthogonal phase-optimized multisine inputs, summed with pilot stick and pedal inputs, were used to excite the responses. The aircraft was tested in its normal configuration and with emulated failures, which included a stuck left ruddervator and an increased command path latency. No prior knowledge of a dynamic model was used or available for the estimation. The longitudinal short period dynamics were investigated in this work. Time-varying frequency responses and stability margins were tracked well using a 20 second sliding window of data, as compared to a post-flight analysis using output error parameter estimation and a low-order equivalent system model. This method could be used in a real-time fault detection system, or for other applications of dynamic modeling such as real-time verification of stability margins during envelope expansion tests.

Associative memory model with spontaneous neural activity

NASA Astrophysics Data System (ADS)

Kurikawa, Tomoki; Kaneko, Kunihiko

2012-05-01

We propose a novel associative memory model wherein the neural activity without an input (i.e., spontaneous activity) is modified by an input to generate a target response that is memorized for recall upon the same input. Suitable design of synaptic connections enables the model to memorize input/output (I/O) mappings equaling 70% of the total number of neurons, where the evoked activity distinguishes a target pattern from others. Spontaneous neural activity without an input shows chaotic dynamics but keeps some similarity with evoked activities, as reported in recent experimental studies.

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

NASA Technical Reports Server (NTRS)

Hong, Steven W.; Curtiss, H. C., Jr.

1993-01-01

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

NASA Technical Reports Server (NTRS)

Hong, Steven W.; Curtiss, H. C., Jr.

1993-01-01

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives, resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

Near real-time traffic routing

NASA Technical Reports Server (NTRS)

Yang, Chaowei (Inventor); Xie, Jibo (Inventor); Zhou, Bin (Inventor); Cao, Ying (Inventor)

2012-01-01

A near real-time physical transportation network routing system comprising: a traffic simulation computing grid and a dynamic traffic routing service computing grid. The traffic simulator produces traffic network travel time predictions for a physical transportation network using a traffic simulation model and common input data. The physical transportation network is divided into a multiple sections. Each section has a primary zone and a buffer zone. The traffic simulation computing grid includes multiple of traffic simulation computing nodes. The common input data includes static network characteristics, an origin-destination data table, dynamic traffic information data and historical traffic data. The dynamic traffic routing service computing grid includes multiple dynamic traffic routing computing nodes and generates traffic route(s) using the traffic network travel time predictions.

Spiking and Excitatory/Inhibitory Input Dynamics of Barrel Cells in Response to Whisker Deflections of Varying Velocity and Angular Direction.

PubMed

Patel, Mainak

2018-01-15

The spiking of barrel regular-spiking (RS) cells is tuned for both whisker deflection direction and velocity. Velocity tuning arises due to thalamocortical (TC) synchrony (but not spike quantity) varying with deflection velocity, coupled with feedforward inhibition, while direction selectivity is not fully understood, though may be due partly to direction tuning of TC spiking. Data show that as deflection direction deviates from the preferred direction of an RS cell, excitatory input to the RS cell diminishes minimally, but temporally shifts to coincide with the time-lagged inhibitory input. This work constructs a realistic large-scale model of a barrel; model RS cells exhibit velocity and direction selectivity due to TC input dynamics, with the experimentally observed sharpening of direction tuning with decreasing velocity. The model puts forth the novel proposal that RS→RS synapses can naturally and simply account for the unexplained direction dependence of RS cell inputs - as deflection direction deviates from the preferred direction of an RS cell, and TC input declines, RS→RS synaptic transmission buffers the decline in total excitatory input and causes a shift in timing of the excitatory input peak from the peak in TC input to the delayed peak in RS input. The model also provides several experimentally testable predictions on the velocity dependence of RS cell inputs. This model is the first, to my knowledge, to study the interaction of direction and velocity and propose physiological mechanisms for the stimulus dependence in the timing and amplitude of RS cell inputs. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Dynamic Weakening (Extinction) of Simple Hydrocarbon-air Counterflow Diffusion Flames by Oscillatory Inflows

NASA Technical Reports Server (NTRS)

Pellett, G.; Kabaria, A.; Panigrahi, B.; Sammons, K.; Convery, J.; Wilson, L.

2005-01-01

This study of laminar non-premixed HC-air flames used an Oscillatory-input Opposed Jet Burner (OOJB) system developed from a previously well-characterized 7.2-mm Pyrex-nozzle OJB system. Over 600 dynamic Flame Strength (FS) measurements were obtained on unanchored (free-floating) laminar Counterflow Diffusion Flames (CFDF's). Flames were stabilized using plug inflows having steady-plus-sinusoidal axial velocities of varied magnitude, frequency, f, up to 1600 Hz, and phase angle from 0 (most data) to 360 degrees. Dynamic FS is defined as the maximum average air input velocity (U(sub air), at nozzle exit) a CFDF can sustain before strain-induced extinction occurs due to prescribed oscillatory peak-to-peak velocity inputs superimposed on steady inputs. Initially, dynamic flame extinction data were obtained at low f, and were supported by 25-120 Hz Hot-Wire cold-flow velocity data at nozzle exits. Later, expanded extinction data were supported by 4-1600 Hz Probe Microphone (PM) pk/pk P data at nozzle exits. The PM data were first obtained without flows, and later with cold stagnating flows, which better represent speaker-diaphragm dynamics during runs. The PM approach enabled characterizations of Dynamic Flame Weakening (DFW) of CFDF's from 8 to 1600 Hz. DFW was defined as % decrease in FS per Pascal of pk/pk P oscillation, namely, DFW = - 100 d(U(sub air) / U(sub air),0Hz) / d(pkpk P). The linear normalization with respect to acoustic pressure magnitude (and steady state (SS) FS) led to a DFW unaffected by strong internal resonances. For the C2H4/N2-air system, from 8 to 20 Hz, DFW is constant at 8.52 plus or minus 0.20 (% weakening)/Pa. This reflects a quasi-steady flame response to an acoustically induced dU(sub air)/dP. Also, it is surprisingly independent of C2H4/N2 mole fraction due to normalization by SS FS. From 20 to approximately 150 Hz, the C2H4/N2 air-flames weakened progressively less, with an inflection at approximately 70 Hz, and became asymptotically insensitive (DFW approximately 0) at approximately 300 Hz, which continued to 1600 Hz. The DFW of CH4-air flames followed a similar pattern, but showed much greater weakening than C2H4/N2-air flames; i.e., the quasi-steady DFW (8 to approximately 15 Hz) was 44.3 %/Pa, or approximately 5x larger, even though the 0 Hz (SS) FS was only 3.0 x smaller. The quasi-steady DFW's of C3H8-air and C2H6-air were intermediate at 34.8 and 20.9 %Pa, respectively. The DFW profiles of all four fuels, at various frequencies, correlated well but non-linearly with respective SS FS's. Notably, the DFW profile for C3H8 air fell more rapidly in the range greater than 15 to 60 Hz, compared with the 1- and 2-carbon fuels. This may indicate a shift in chemical kinetics, and/or O2 transport to a flame that moved closer to the fuel-side. In conclusion, Dynamic Flame Weakening limits appear significant and unique for each fuel, and correlate closely, but non-linearly, with Steady-State Flame Strengths at any given frequency. For reasons unknown, the dynamic flames didn't weaken more at intermediate frequencies (e.g., at 20-50 Hz) than they did at low frequencies (less than 15 Hz), where quasi-steady weakening appears to dominate. Quasi-steady flame weakening ostensibly represents a transient input strain rate maximum that just exceeds the steady-state strain-rate-limited extinction limit for a few cycles. Clearly, further detailed mechanistic understanding is needed in the fall-off region.

System identification and the modeling of sailing yachts

NASA Astrophysics Data System (ADS)

Legursky, Katrina

This research represents an exploration of sailing yacht dynamics with full-scale sailing motion data, physics-based models, and system identification techniques. The goal is to provide a method of obtaining and validating suitable physics-based dynamics models for use in control system design on autonomous sailing platforms, which have the capacity to serve as mobile, long range, high endurance autonomous ocean sensing platforms. The primary contributions of this study to the state-of-the-art are the formulation of a five degree-of-freedom (DOF) linear multi-input multi-output (MIMO) state space model of sailing yacht dynamics, the process for identification of this model from full-scale data, a description of the maneuvers performed during on-water tests, and an analysis method to validate estimated models. The techniques and results described herein can be directly applied to and tested on existing autonomous sailing platforms. A full-scale experiment on a 23ft monohull sailing yacht is developed to collect motion data for physics-based model identification. Measurements include 3 axes of accelerations, velocities, angular rates, and attitude angles in addition to apparent wind speed and direction. The sailing yacht herein is treated as a dynamic system with two control inputs, the rudder angle, deltaR, and the mainsail angle, delta B, which are also measured. Over 20 hours of full scale sailing motion data is collected, representing three sail configurations corresponding to a range of wind speeds: the Full Main and Genoa (abbrev. Genoa) for lower wind speeds, the Full Main and Jib (abbrev. Jib) for mid-range wind speeds, and the Reefed Main and Jib (abbrev. Reef) for the highest wind speeds. The data also covers true wind angles from upwind through a beam reach. A physics-based non-linear model to describe sailing yacht motion is outlined, including descriptions of methods to model the aerodynamics and hydrodynamics of a sailing yacht in surge, sway, roll, and yaw. Existing aerodynamic models for sailing yachts are unsuitable for control system design as they do not include a physical description of the sails' dynamic effect on the system. A new aerodynamic model is developed and validated using the full-scale sailing data which includes sail deflection as a control input to the system. The Maximum Likelihood Estimation (MLE) algorithm is used with non-linear simulation data to successfully estimate a set of hydrodynamic derivatives for a sailing yacht. It is shown that all sailing yacht models will contain a second order mode (referred to herein as Mode 1A.S or 4B.S) which is dependent upon trimmed roll angle. For the test yacht it is concluded that for this mode when the trimmed roll angle is, roll rate and roll angle are the dominant motion variables, and for surge velocity and yaw rate dominate. This second order mode is dynamically stable for . It transitions from stability in the higher values of to instability in the region defined by. These conclusions align with other work which has also found roll angle to be a driving factor in the dynamic behavior of a tall-ship (Johnson, Miles, Lasher, & Womack, 2009). It is also shown that all linear models also contain a first order mode, (referred to herein as Mode 3A.F or 1B.F), which lies very close to the origin of the complex plane indicating a long time constant. Measured models have indicated this mode can be stable or unstable. The eigenvector analysis reveals that the mode is stable if the surge contribution is < 40% and the sway contribution is > 20%. The small set of maneuvers necessary for model identification, quick OSLS estimation method, and detailed modal analysis of estimated models outlined in this work are immediately applicable to existing autonomous mono-hull sailing yachts, and could readily be adapted for use with other wind-powered vessel configurations such as wing-sails, catamarans, and tri-marans. (Abstract shortened by UMI.)

Destabilization of Human Balance Control by Static and Dynamic Head Tilts

NASA Technical Reports Server (NTRS)

Paloski, William H.; Wood, Scott J.; Feiveson, Alan H.; Black, F. Owen; Hwang, Emma Y.; Reschke, Millard F.

2004-01-01

To better understand the effects of varying head movement frequencies on human balance control, 12 healthy adult humans were studied during static and dynamic (0.14,0.33,0.6 Hz) head tilts of +/-30deg in the pitch and roll planes. Postural sway was measured during upright stance with eyes closed and altered somatosensory inputs provided by a computerized dynamic posturography (CDP) system. Subjects were able to maintain upright stance with static head tilts, although postural sway was increased during neck extension. Postural stability was decreased during dynamic head tilts, and the degree of destabilization varied directly with increasing frequency of head tilt. In the absence of vision and accurate foot support surface inputs, postural stability may be compromised during dynamic head tilts due to a decreased ability of the vestibular system to discern the orientation of gravity.

Measurements of dynamic and resilient moduli of roadway test sites.

DOT National Transportation Integrated Search

2013-12-01

This study developed a material input library of dynamic and resilient moduli of local : pavement materials for the Mechanistic Empirical Pavement Design Guide (MEPDG) : implementation in Georgia. A database includes: 1) dynamic moduli of asphalt con...

Heat Pipe Vapor Dynamics. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Issacci, Farrokh

1990-01-01

The dynamic behavior of the vapor flow in heat pipes is investigated at startup and during operational transients. The vapor is modeled as two-dimensional, compressible viscous flow in an enclosure with inflow and outflow boundary conditions. For steady-state and operating transients, the SIMPLER method is used. In this method a control volume approach is employed on a staggered grid which makes the scheme very stable. It is shown that for relatively low input heat fluxes the compressibility of the vapor flow is low and the SIMPLER scheme is suitable for the study of transient vapor dynamics. When the input heat flux is high or the process under a startup operation starts at very low pressures and temperatures, the vapor is highly compressible and a shock wave is created in the evaporator. It is shown that for a wide range of input heat fluxes, the standard methods, including the SIMPLER scheme, are not suitable. A nonlinear filtering technique, along with the centered difference scheme, are then used for shock capturing as well as for the solution of the cell Reynolds-number problem. For high heat flux, the startup transient phase involves multiple shock reflections in the evaporator region. Each shock reflection causes a significant increase in the local pressure and a large pressure drop along the heat pipe. Furthermore, shock reflections cause flow reversal in the evaporation region and flow circulations in the adiabatic region. The maximum and maximum-averaged pressure drops in different sections of the heat pipe oscillate periodically with time because of multiple shock reflections. The pressure drop converges to a constant value at steady state. However, it is significantly higher than its steady-state value at the initiation of the startup transient. The time for the vapor core to reach steady-state condition depends on the input heat flux, the heat pipe geometry, the working fluid, and the condenser conditions. However, the vapor transient time, for an Na-filled heat pipe is on the order of seconds. Depending on the time constant for the overall system, the vapor transient time may be very short. Therefore, the vapor core may be assumed to be quasi-steady in the transient analysis of a heat pipe operation.

Music preferences with hearing aids: effects of signal properties, compression settings, and listener characteristics.

PubMed

Croghan, Naomi B H; Arehart, Kathryn H; Kates, James M

2014-01-01

Current knowledge of how to design and fit hearing aids to optimize music listening is limited. Many hearing-aid users listen to recorded music, which often undergoes compression limiting (CL) in the music industry. Therefore, hearing-aid users may experience twofold effects of compression when listening to recorded music: music-industry CL and hearing-aid wide dynamic-range compression (WDRC). The goal of this study was to examine the roles of input-signal properties, hearing-aid processing, and individual variability in the perception of recorded music, with a focus on the effects of dynamic-range compression. A group of 18 experienced hearing-aid users made paired-comparison preference judgments for classical and rock music samples using simulated hearing aids. Music samples were either unprocessed before hearing-aid input or had different levels of music-industry CL. Hearing-aid conditions included linear gain and individually fitted WDRC. Combinations of four WDRC parameters were included: fast release time (50 msec), slow release time (1,000 msec), three channels, and 18 channels. Listeners also completed several psychophysical tasks. Acoustic analyses showed that CL and WDRC reduced temporal envelope contrasts, changed amplitude distributions across the acoustic spectrum, and smoothed the peaks of the modulation spectrum. Listener judgments revealed that fast WDRC was least preferred for both genres of music. For classical music, linear processing and slow WDRC were equally preferred, and the main effect of number of channels was not significant. For rock music, linear processing was preferred over slow WDRC, and three channels were preferred to 18 channels. Heavy CL was least preferred for classical music, but the amount of CL did not change the patterns of WDRC preferences for either genre. Auditory filter bandwidth as estimated from psychophysical tuning curves was associated with variability in listeners' preferences for classical music. Fast, multichannel WDRC often leads to poor music quality, whereas linear processing or slow WDRC are generally preferred. Furthermore, the effect of WDRC is more important for music preferences than music-industry CL applied to signals before the hearing-aid input stage. Variability in hearing-aid users' perceptions of music quality may be partially explained by frequency resolution abilities.

Low- and high-threshold primary afferent inputs to spinal lamina III antenna-type neurons.

PubMed

Fernandes, Elisabete C; Santos, Ines C; Kokai, Eva; Luz, Liliana L; Szucs, Peter; Safronov, Boris V

2018-06-21

and non-nociceptive sensory information. Antenna-type neurons with cell bodies located in lamina III and large dendritic trees extending from the superficial lamina I to deep lamina IV are best shaped for the integration of a wide variety of inputs arising from primary afferent fibers and intrinsic spinal circuitries. While the somatodendritic morphology, the hallmark of antenna neurons, has been well studied, little is still known about the axon structure and basic physiological properties of these cells. Here we did whole-cell recordings in a rat (P9-P12) spinal cord preparation with attached dorsal roots to examine the axon course, intrinsic firing properties and primary afferent inputs of antenna cells. Nine antenna cells were identified from a large sample of biocytin-filled lamina III neurons (n = 46). Axon of antenna cells showed intensive branching in laminae III-IV and, in half of the cases, issued dorsally directed collaterals reaching lamina I. Antenna cells exhibited tonic and rhythmic firing patterns; single spikes were followed by hyper- or depolarization. The neurons received monosynaptic inputs from the low-threshold Aβ afferents, Aδ afferents as well as from the high-threshold Aδ and C afferents. When selectively activated, C-fiber-driven mono- and polysynaptic EPSPs were sufficiently strong to evoke firing in the neurons. Thus, lamina III antenna neurons integrate low-threshold and nociceptive high-threshold primary afferent inputs, and can function as wide-dynamic-range neurons able to directly connect deep dorsal horn with the major nociceptive projection area lamina I.

Mode localization in the cooperative dynamics of protein recognition

NASA Astrophysics Data System (ADS)

Copperman, J.; Guenza, M. G.

2016-07-01

The biological function of proteins is encoded in their structure and expressed through the mediation of their dynamics. This paper presents a study on the correlation between local fluctuations, binding, and biological function for two sample proteins, starting from the Langevin Equation for Protein Dynamics (LE4PD). The LE4PD is a microscopic and residue-specific coarse-grained approach to protein dynamics, which starts from the static structural ensemble of a protein and predicts the dynamics analytically. It has been shown to be accurate in its prediction of NMR relaxation experiments and Debye-Waller factors. The LE4PD is solved in a set of diffusive modes which span a vast range of time scales of the protein dynamics, and provides a detailed picture of the mode-dependent localization of the fluctuation as a function of the primary structure of the protein. To investigate the dynamics of protein complexes, the theory is implemented here to treat the coarse-grained dynamics of interacting macromolecules. As an example, calculations of the dynamics of monomeric and dimerized HIV protease and the free Insulin Growth Factor II Receptor (IGF2R) domain 11 and its IGF2R:IGF2 complex are presented. Either simulation-derived or experimentally measured NMR conformers are used as input structural ensembles to the theory. The picture that emerges suggests a dynamical heterogeneous protein where biologically active regions provide energetically comparable conformational states that are trapped by a reacting partner in agreement with the conformation-selection mechanism of binding.

Functional expansion representations of artificial neural networks

NASA Technical Reports Server (NTRS)

Gray, W. Steven

1992-01-01

In the past few years, significant interest has developed in using artificial neural networks to model and control nonlinear dynamical systems. While there exists many proposed schemes for accomplishing this and a wealth of supporting empirical results, most approaches to date tend to be ad hoc in nature and rely mainly on heuristic justifications. The purpose of this project was to further develop some analytical tools for representing nonlinear discrete-time input-output systems, which when applied to neural networks would give insight on architecture selection, pruning strategies, and learning algorithms. A long term goal is to determine in what sense, if any, a neural network can be used as a universal approximator for nonliner input-output maps with memory (i.e., realized by a dynamical system). This property is well known for the case of static or memoryless input-output maps. The general architecture under consideration in this project was a single-input, single-output recurrent feedforward network.

Modeling Vegetation Growth Impact on Groundwater Recharge

NASA Astrophysics Data System (ADS)

Anurag, H.; Ng, G. H. C.; Tipping, R.

2017-12-01

Vegetation growth is affected by variability in climate and land-cover / land-use over a range of temporal and spatial scales. Vegetation also modifies water budget through interception and evapotranspiration and thus has a significant impact on groundwater recharge. Most groundwater recharge assessments represent vegetation using specified, static parameter, such as for leaf-area-index, but this neglects the effect of vegetation dynamics on recharge estimates. Our study addresses this gap by including vegetation growth in model simulations of recharge. We use NCAR's Community Land Model v4.5 with its BGC module (BGC is the new CLM4.5 biogeochemistry). It integrates prognostic vegetation growth with land-surface and subsurface hydrological processes and can thus capture the effect of vegetation on groundwater. A challenge, however, is the need to resolve uncertainties in model inputs ranging from vegetation growth parameters all the way down to the water table. We have compiled diverse data spanning meteorological inputs to subsurface geology and use these to implement ensemble model simulations to evaluate the possible effects of dynamic vegetation growth (versus specified, static vegetation parameterizations) on estimating groundwater recharge. We present preliminary results for select data-intensive test locations throughout the state of Minnesota (USA), which has a sharp east-west precipitation gradient that makes it an apt testbed for examining ecohydrologic relationships across different temperate climatic settings and ecosystems. Using the ensemble simulations, we examine the effect of seasonal to interannual variability of vegetation growth on recharge and water table depths, which has implications for predicting the combined impact of climate, vegetation, and geology on groundwater resources. Future work will include distributed model simulations over the entire state, as well as conditioning uncertain vegetation and subsurface parameters on remote sensing data and statewide water table records using data assimilation.

Switched integration amplifier-based photocurrent meter for accurate spectral responsivity measurement of photometers.

PubMed

Park, Seongchong; Hong, Kee-Suk; Kim, Wan-Seop

2016-03-20

This work introduces a switched integration amplifier (SIA)-based photocurrent meter for femtoampere (fA)-level current measurement, which enables us to measure a 10⁷ dynamic range of spectral responsivity of photometers even with a common lamp-based monochromatic light source. We described design considerations and practices about operational amplifiers (op-amps), switches, readout methods, etc., to compose a stable SIA of low offset current in terms of leakage current and gain peaking in detail. According to the design, we made six SIAs of different integration capacitance and different op-amps and evaluated their offset currents. They showed an offset current of (1.5-85) fA with a slow variation of (0.5-10) fA for an hour under opened input. Applying a detector to the SIA input, the offset current and its variation were increased and the SIA readout became noisier due to finite shunt resistance and nonzero shunt capacitance of the detector. One of the SIAs with 10 pF nominal capacitance was calibrated using a calibrated current source at the current level of 10 nA to 1 fA and at the integration time of 2 to 65,536 ms. As a result, we obtained a calibration formula for integration capacitance as a function of integration time rather than a single capacitance value because the SIA readout showed a distinct dependence on integration time at a given current level. Finally, we applied it to spectral responsivity measurement of a photometer. It is demonstrated that the home-made SIA of 10 pF was capable of measuring a 10⁷ dynamic range of spectral responsivity of a photometer.

[Quantifying rice (Oryza sativa L.) photo-assimilated carbon input into soil organic carbon pools following continuous 14C labeling].

PubMed

Nie, San-An; Zhou, Ping; Ge, Ti-Da; Tong, Cheng-Li; Xiao, He-Ai; Wu, Jin-Shui; Zhang, Yang-Zhu

2012-04-01

The microcosm experiment was carried out to quantify the input and distribution of photo-assimilated C into soil C pools by using a 14C continuous labeling technique. Destructive samplings of rice (Oryza sativa) were conducted after labeling for 80 days. The allocation of 14C-labeled photosynthates in plants and soil C pools such as dissolved organic C (DOC) and microbial biomass C (MBC) in rice-planted soil were examined over the 14C labeling span. The amounts of rice shoot and root biomass C was ranged from 1.86 to 5.60 g x pot(-1), 0.46 to 0.78 g x pot(-1) in different tested paddy soils after labeling for 80 days, respectively. The amount of 14C in the soil organic C (14C-SOC) was also dependent on the soils, ranged from 114.3 to 348.2 mg x kg(-1), accounting for 5.09% to 6.62% of the rice biomass 14C, respectively. The amounts of 14C in the dissolved organic C (14C-DOC) and in the microbial biomass C(14C-MBC), as proportions of 14C-SOC, were 2.21%-3.54% and 9.72% -17.2%, respectively. The 14C-DOC, 14C-MBC, and 14C-SOC as proportions of total DOC, MBC, and SOC, respectively, were 6.72% -14.64%, 1.70% -7.67%, and 0.73% -1.99%, respectively. Moreover, the distribution and transformation of root-derived C had a greater influence on the dynamics of DOC and MBC than on the dynamics of SOC. Further studies are required to ascertain the functional significance of soil microorganisms (such as C-sequestering bacteria and photosynthetic bacteria) in the paddy system.

Critical carbon input to maintain current soil organic carbon stocks in global wheat systems

PubMed Central

Wang, Guocheng; Luo, Zhongkui; Han, Pengfei; Chen, Huansheng; Xu, Jingjing

2016-01-01

Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1° × 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha−1 yr−1, with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content. PMID:26759192

Quantified carbon input for maintaining existing soil organic carbon stocks in global wheat systems

NASA Astrophysics Data System (ADS)

Wang, G.

2017-12-01

Soil organic carbon (SOC) dynamics in croplands is a crucial component of global carbon (C) cycle. Depending on local environmental conditions and management practices, typical C input is generally required to reduce or reverse C loss in agricultural soils. No studies have quantified the critical C input for maintaining SOC at global scale with high resolution. Such information will provide a baseline map for assessing soil C dynamics under potential changes in management practices and climate, and thus enable development of management strategies to reduce C footprint from farm to regional scales. We used the soil C model RothC to simulate the critical C input rates needed to maintain existing soil C level at 0.1°× 0.1° resolution in global wheat systems. On average, the critical C input was estimated to be 2.0 Mg C ha-1 yr-1, with large spatial variability depending on local soil and climatic conditions. Higher C inputs are required in wheat system of central United States and western Europe, mainly due to the higher current soil C stocks present in these regions. The critical C input could be effectively estimated using a summary model driven by current SOC level, mean annual temperature, precipitation, and soil clay content.

Dynamic adjustment in agricultural practices to economic incentives aiming to decrease fertilizer application.

PubMed

Sun, Shanxia; Delgado, Michael S; Sesmero, Juan P

2016-07-15

Input- and output-based economic policies designed to reduce water pollution from fertilizer runoff by adjusting management practices are theoretically justified and well-understood. Yet, in practice, adjustment in fertilizer application or land allocation may be sluggish. We provide practical guidance for policymakers regarding the relative magnitude and speed of adjustment of input- and output-based policies. Through a dynamic dual model of corn production that takes fertilizer as one of several production inputs, we measure the short- and long-term effects of policies that affect the relative prices of inputs and outputs through the short- and long-term price elasticities of fertilizer application, and also the total time required for different policies to affect fertilizer application through the adjustment rates of capital and land. These estimates allow us to compare input- and output-based policies based on their relative cost-effectiveness. Using data from Indiana and Illinois, we find that input-based policies are more cost-effective than their output-based counterparts in achieving a target reduction in fertilizer application. We show that input- and output-based policies yield adjustment in fertilizer application at the same speed, and that most of the adjustment takes place in the short-term. Copyright © 2016 Elsevier Ltd. All rights reserved.

Testing the Applicability of Nernst-Planck Theory in Ion Channels: Comparisons with Brownian Dynamics Simulations

PubMed Central

Song, Chen; Corry, Ben

2011-01-01

The macroscopic Nernst-Planck (NP) theory has often been used for predicting ion channel currents in recent years, but the validity of this theory at the microscopic scale has not been tested. In this study we systematically tested the ability of the NP theory to accurately predict channel currents by combining and comparing the results with those of Brownian dynamics (BD) simulations. To thoroughly test the theory in a range of situations, calculations were made in a series of simplified cylindrical channels with radii ranging from 3 to 15 Å, in a more complex ‘catenary’ channel, and in a realistic model of the mechanosensitive channel MscS. The extensive tests indicate that the NP equation is applicable in narrow ion channels provided that accurate concentrations and potentials can be input as the currents obtained from the combination of BD and NP match well with those obtained directly from BD simulations, although some discrepancies are seen when the ion concentrations are not radially uniform. This finding opens a door to utilising the results of microscopic simulations in continuum theory, something that is likely to be useful in the investigation of a range of biophysical and nano-scale applications and should stimulate further studies in this direction. PMID:21731672

Testing the applicability of Nernst-Planck theory in ion channels: comparisons with Brownian dynamics simulations.

PubMed

Song, Chen; Corry, Ben

2011-01-01

The macroscopic Nernst-Planck (NP) theory has often been used for predicting ion channel currents in recent years, but the validity of this theory at the microscopic scale has not been tested. In this study we systematically tested the ability of the NP theory to accurately predict channel currents by combining and comparing the results with those of Brownian dynamics (BD) simulations. To thoroughly test the theory in a range of situations, calculations were made in a series of simplified cylindrical channels with radii ranging from 3 to 15 Å, in a more complex 'catenary' channel, and in a realistic model of the mechanosensitive channel MscS. The extensive tests indicate that the NP equation is applicable in narrow ion channels provided that accurate concentrations and potentials can be input as the currents obtained from the combination of BD and NP match well with those obtained directly from BD simulations, although some discrepancies are seen when the ion concentrations are not radially uniform. This finding opens a door to utilising the results of microscopic simulations in continuum theory, something that is likely to be useful in the investigation of a range of biophysical and nano-scale applications and should stimulate further studies in this direction.

The Temporal Tuning of the Drosophila Motion Detectors Is Determined by the Dynamics of Their Input Elements.

PubMed

Arenz, Alexander; Drews, Michael S; Richter, Florian G; Ammer, Georg; Borst, Alexander

2017-04-03

Detecting the direction of motion contained in the visual scene is crucial for many behaviors. However, because single photoreceptors only signal local luminance changes, motion detection requires a comparison of signals from neighboring photoreceptors across time in downstream neuronal circuits. For signals to coincide on readout neurons that thus become motion and direction selective, different input lines need to be delayed with respect to each other. Classical models of motion detection rely on non-linear interactions between two inputs after different temporal filtering. However, recent studies have suggested the requirement for at least three, not only two, input signals. Here, we comprehensively characterize the spatiotemporal response properties of all columnar input elements to the elementary motion detectors in the fruit fly, T4 and T5 cells, via two-photon calcium imaging. Between these input neurons, we find large differences in temporal dynamics. Based on this, computer simulations show that only a small subset of possible arrangements of these input elements maps onto a recently proposed algorithmic three-input model in a way that generates a highly direction-selective motion detector, suggesting plausible network architectures. Moreover, modulating the motion detection system by octopamine-receptor activation, we find the temporal tuning of T4 and T5 cells to be shifted toward higher frequencies, and this shift can be fully explained by the concomitant speeding of the input elements. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cellular and Network Mechanisms Underlying Information Processing in a Simple Sensory System

NASA Technical Reports Server (NTRS)

Jacobs, Gwen; Henze, Chris; Biegel, Bryan (Technical Monitor)

2002-01-01

Realistic, biophysically-based compartmental models were constructed of several primary sensory interneurons in the cricket cercal sensory system. A dynamic atlas of the afferent input to these cells was used to set spatio-temporal parameters for the simulated stimulus-dependent synaptic inputs. We examined the roles of dendritic morphology, passive membrane properties, and active conductances on the frequency tuning of the neurons. The sensitivity of narrow-band low pass interneurons could be explained entirely by the electronic structure of the dendritic arbors and the dynamic sensitivity of the SIZ. The dynamic characteristics of interneurons with higher frequency sensitivity required models with voltage-dependent dendritic conductances.

Actor-critic-based optimal tracking for partially unknown nonlinear discrete-time systems.

PubMed

Kiumarsi, Bahare; Lewis, Frank L

2015-01-01

This paper presents a partially model-free adaptive optimal control solution to the deterministic nonlinear discrete-time (DT) tracking control problem in the presence of input constraints. The tracking error dynamics and reference trajectory dynamics are first combined to form an augmented system. Then, a new discounted performance function based on the augmented system is presented for the optimal nonlinear tracking problem. In contrast to the standard solution, which finds the feedforward and feedback terms of the control input separately, the minimization of the proposed discounted performance function gives both feedback and feedforward parts of the control input simultaneously. This enables us to encode the input constraints into the optimization problem using a nonquadratic performance function. The DT tracking Bellman equation and tracking Hamilton-Jacobi-Bellman (HJB) are derived. An actor-critic-based reinforcement learning algorithm is used to learn the solution to the tracking HJB equation online without requiring knowledge of the system drift dynamics. That is, two neural networks (NNs), namely, actor NN and critic NN, are tuned online and simultaneously to generate the optimal bounded control policy. A simulation example is given to show the effectiveness of the proposed method.

Quantification of net annual C input in terrestrial ecosystems of the Italian Peninsula under different land-uses

USDA-ARS?s Scientific Manuscript database

Soil organic matter (SOM) is a very important compartment of the biosphere: it represents the largest dynamic carbon (C) pool where the C is stored for the longest time period. Root inputs, as exudates and root slush, represent a major, where not the largest, annual contribution to soil C input. Roo...

Reconstruction of an input function from a dynamic PET water image using multiple tissue curves

NASA Astrophysics Data System (ADS)

Kudomi, Nobuyuki; Maeda, Yukito; Yamamoto, Yuka; Nishiyama, Yoshihiro

2016-08-01

Quantification of cerebral blood flow (CBF) is important for the understanding of normal and pathologic brain physiology. When CBF is assessed using PET with {{\\text{H}}2} 15O or C15O2, its calculation requires an arterial input function, which generally requires invasive arterial blood sampling. The aim of the present study was to develop a new technique to reconstruct an image derived input function (IDIF) from a dynamic {{\\text{H}}2} 15O PET image as a completely non-invasive approach. Our technique consisted of using a formula to express the input using tissue curve with rate constant parameter. For multiple tissue curves extracted from the dynamic image, the rate constants were estimated so as to minimize the sum of the differences of the reproduced inputs expressed by the extracted tissue curves. The estimated rates were used to express the inputs and the mean of the estimated inputs was used as an IDIF. The method was tested in human subjects (n  =  29) and was compared to the blood sampling method. Simulation studies were performed to examine the magnitude of potential biases in CBF and to optimize the number of multiple tissue curves used for the input reconstruction. In the PET study, the estimated IDIFs were well reproduced against the measured ones. The difference between the calculated CBF values obtained using the two methods was small as around  <8% and the calculated CBF values showed a tight correlation (r  =  0.97). The simulation showed that errors associated with the assumed parameters were  <10%, and that the optimal number of tissue curves to be used was around 500. Our results demonstrate that IDIF can be reconstructed directly from tissue curves obtained through {{\\text{H}}2} 15O PET imaging. This suggests the possibility of using a completely non-invasive technique to assess CBF in patho-physiological studies.

Effects of small-scale hydrogeologic heterogeneity on submarine groundwater discharge (SGD) dynamics in river dominated estuaries: example of Mobile Bay, Alabama

NASA Astrophysics Data System (ADS)

Montiel, D.; Dimova, N.

2017-12-01

Submarine groundwater discharge (SGD) is known to be an important pathway for nutrients and dissolved constituents in estuarine environments worldwide. Despite its limited contribution to the total fresh water flux to the ocean (5 - 10 %), SGD-derived material loadings can rival riverine inputs. Therefore, a good understanding of the coastal hydrogeology and subsequent SGD dynamics is crucial to further investigate constituent fluxes and its implications on small and large scale coastal ecosystems. We evaluated SGD in Mobile Bay (Alabama), the fourth largest estuary in the US, using a combination of radiotracer techniques (223Ra, 226Ra, and 222Rn), stable isotopes (δ 18O and δ 2H), geophysical surveys (continuous resistivity profiling (CRP) and electrical resistivity tomography (ERT)), and seepage meters during three consecutive years. A detailed examination of the entire shoreline of Mobile Bay using CRP, ERT imaging, and multiple sediment cores collection unveiled a heterogeneous (horizontal and vertical) distribution of the surficial coastal aquifer. This was reflected and confirmed by groundwater tracer measurements and direct measurements of SGD in the coastal zone. We found that SGD occurs mainly in the northeast section of Mobile Bay with a total flux that ranged between 0.9 and 13 × 105 m3 d-1 during dry and wet periods, which represents 0.4 - 2 % of the total fresh water inputs into the Bay. While total SGD is insignificant when accounting the whole water budget of Mobile Bay, we found that small-scale geology variations produce groundwater flow preferential pathways in particular areas where SGD inputs play an important role in the water and nutrient budgets.

Top-Down Modulation on Perceptual Decision with Balanced Inhibition through Feedforward and Feedback Inhibitory Neurons

PubMed Central

Wang, Cheng-Te; Lee, Chung-Ting; Wang, Xiao-Jing; Lo, Chung-Chuan

2013-01-01

Recent physiological studies have shown that neurons in various regions of the central nervous systems continuously receive noisy excitatory and inhibitory synaptic inputs in a balanced and covaried fashion. While this balanced synaptic input (BSI) is typically described in terms of maintaining the stability of neural circuits, a number of experimental and theoretical studies have suggested that BSI plays a proactive role in brain functions such as top-down modulation for executive control. Two issues have remained unclear in this picture. First, given the noisy nature of neuronal activities in neural circuits, how do the modulatory effects change if the top-down control implements BSI with different ratios between inhibition and excitation? Second, how is a top-down BSI realized via only excitatory long-range projections in the neocortex? To address the first issue, we systematically tested how the inhibition/excitation ratio affects the accuracy and reaction times of a spiking neural circuit model of perceptual decision. We defined an energy function to characterize the network dynamics, and found that different ratios modulate the energy function of the circuit differently and form two distinct functional modes. To address the second issue, we tested BSI with long-distance projection to inhibitory neurons that are either feedforward or feedback, depending on whether these inhibitory neurons do or do not receive inputs from local excitatory cells, respectively. We found that BSI occurs in both cases. Furthermore, when relying on feedback inhibitory neurons, through the recurrent interactions inside the circuit, BSI dynamically and automatically speeds up the decision by gradually reducing its inhibitory component in the course of a trial when a decision process takes too long. PMID:23626812

Accurate path integration in continuous attractor network models of grid cells.

PubMed

Burak, Yoram; Fiete, Ila R

2009-02-01

Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rat's velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of approximately 10-100 meters and approximately 1-10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other.

Top-down modulation on perceptual decision with balanced inhibition through feedforward and feedback inhibitory neurons.

PubMed

Wang, Cheng-Te; Lee, Chung-Ting; Wang, Xiao-Jing; Lo, Chung-Chuan

2013-01-01

Recent physiological studies have shown that neurons in various regions of the central nervous systems continuously receive noisy excitatory and inhibitory synaptic inputs in a balanced and covaried fashion. While this balanced synaptic input (BSI) is typically described in terms of maintaining the stability of neural circuits, a number of experimental and theoretical studies have suggested that BSI plays a proactive role in brain functions such as top-down modulation for executive control. Two issues have remained unclear in this picture. First, given the noisy nature of neuronal activities in neural circuits, how do the modulatory effects change if the top-down control implements BSI with different ratios between inhibition and excitation? Second, how is a top-down BSI realized via only excitatory long-range projections in the neocortex? To address the first issue, we systematically tested how the inhibition/excitation ratio affects the accuracy and reaction times of a spiking neural circuit model of perceptual decision. We defined an energy function to characterize the network dynamics, and found that different ratios modulate the energy function of the circuit differently and form two distinct functional modes. To address the second issue, we tested BSI with long-distance projection to inhibitory neurons that are either feedforward or feedback, depending on whether these inhibitory neurons do or do not receive inputs from local excitatory cells, respectively. We found that BSI occurs in both cases. Furthermore, when relying on feedback inhibitory neurons, through the recurrent interactions inside the circuit, BSI dynamically and automatically speeds up the decision by gradually reducing its inhibitory component in the course of a trial when a decision process takes too long.

Modeling Common-Sense Decisions in Artificial Intelligence

NASA Technical Reports Server (NTRS)

Zak, Michail

2010-01-01

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.

Even-order harmonic cancellation for off-quadrature biased Mach-Zehnder modulator with improved RF metrics using dual wavelength inputs and dual outputs.

PubMed

Devgan, Preetpaul S; Diehl, John F; Urick, Vincent J; Sunderman, Christopher E; Williams, Keith J

2009-05-25

We present a technique using a dual-output Mach-Zehnder modulator (MZM) with two wavelength inputs, one operating at low-bias and the other operating at high-bias, in order to cancel unwanted even-order harmonics in analog optical links. By using a dual-output MZM, this technique allows for two suppressed optical carriers to be transmitted to the receiver. Combined with optical amplification and balanced differential detection, the RF power of the fundamental is increased by 2 dB while the even-order harmonic is reduced by 47 dB, simultaneously. The RF noise figure and third-order spurious-free dynamic range (SFDR(3)) are improved by 5.4 dB and 3.6 dB, respectively. Using a wavelength sensitive, low V(pi) MZM allows the two wavelengths to be within 5.5 nm of each other for a frequency band from 10 MHz to 100 MHz and 10 nm for 1 GHz.

Markets, Herding and Response to External Information.

PubMed

Carro, Adrián; Toral, Raúl; San Miguel, Maxi

2015-01-01

We focus on the influence of external sources of information upon financial markets. In particular, we develop a stochastic agent-based market model characterized by a certain herding behavior as well as allowing traders to be influenced by an external dynamic signal of information. This signal can be interpreted as a time-varying advertising, public perception or rumor, in favor or against one of two possible trading behaviors, thus breaking the symmetry of the system and acting as a continuously varying exogenous shock. As an illustration, we use a well-known German Indicator of Economic Sentiment as information input and compare our results with Germany's leading stock market index, the DAX, in order to calibrate some of the model parameters. We study the conditions for the ensemble of agents to more accurately follow the information input signal. The response of the system to the external information is maximal for an intermediate range of values of a market parameter, suggesting the existence of three different market regimes: amplification, precise assimilation and undervaluation of incoming information.

GREAT: a gradient-based color-sampling scheme for Retinex.

PubMed

Lecca, Michela; Rizzi, Alessandro; Serapioni, Raul Paolo

2017-04-01

Modeling the local color spatial distribution is a crucial step for the algorithms of the Milano Retinex family. Here we present GREAT, a novel, noise-free Milano Retinex implementation based on an image-aware spatial color sampling. For each channel of a color input image, GREAT computes a 2D set of edges whose magnitude exceeds a pre-defined threshold. Then GREAT re-scales the channel intensity of each image pixel, called target, by the average of the intensities of the selected edges weighted by a function of their positions, gradient magnitudes, and intensities relative to the target. In this way, GREAT enhances the input image, adjusting its brightness, contrast and dynamic range. The use of the edges as pixels relevant to color filtering is justified by the importance that edges play in human color sensation. The name GREAT comes from the expression "Gradient RElevAnce for ReTinex," which refers to the threshold-based definition of a gradient relevance map for edge selection and thus for image color filtering.

A Diffusive Homeostatic Signal Maintains Neural Heterogeneity and Responsiveness in Cortical Networks

PubMed Central

Sweeney, Yann; Hellgren Kotaleski, Jeanette; Hennig, Matthias H.

2015-01-01

Gaseous neurotransmitters such as nitric oxide (NO) provide a unique and often overlooked mechanism for neurons to communicate through diffusion within a network, independent of synaptic connectivity. NO provides homeostatic control of intrinsic excitability. Here we conduct a theoretical investigation of the distinguishing roles of NO-mediated diffusive homeostasis in comparison with canonical non-diffusive homeostasis in cortical networks. We find that both forms of homeostasis provide a robust mechanism for maintaining stable activity following perturbations. However, the resulting networks differ, with diffusive homeostasis maintaining substantial heterogeneity in activity levels of individual neurons, a feature disrupted in networks with non-diffusive homeostasis. This results in networks capable of representing input heterogeneity, and linearly responding over a broader range of inputs than those undergoing non-diffusive homeostasis. We further show that these properties are preserved when homeostatic and Hebbian plasticity are combined. These results suggest a mechanism for dynamically maintaining neural heterogeneity, and expose computational advantages of non-local homeostatic processes. PMID:26158556

Intermediate Experimental Vehicle, ESA Programme Supersonic Transonic Aerodynamics

NASA Astrophysics Data System (ADS)

Sjors, Karin; Olsson, Jorgen; Maseland, Hans; de Cock, Koen; Dutheil, Sylvain; Bouleuc, Laurent; Cantinaud, Olivier; Tribot, Jean-Pierre; Mareschi, Vincenzo; Ferrarella, Daniella, Rufolo, Giuseppe

2011-05-01

The IXV project objectives are the design, development, manufacture and on ground and in flight verification of an autonomous European lifting and aerodynamically controlled re-entry system, which is highly flexible and manoeuvrable. The IXV vehicle is planned to be recovered in supersonic regime by means of a Descent and Recovery System (DRS). In that context, a specific aerodynamic identification was carried in order to provide data to be used for consolidating the AEDB (AErodynamic Data Base) and as inputs for the DRS sub-system activities. During the phase C2, a wind tunnel campaign was carried out at for the Mach number range M=1.7 to M=0.3 together with computational fluid dynamics simulation. The main objectives were to assess the aerodynamic forces and moments assuming high aileron setting in supersonic regime and to get preliminary aerodynamic data in subsonic regime to be used as input by the DRS team. The logic and the main results of these activities are presented and discussed in this paper.

Clutch pressure estimation for a power-split hybrid transmission using nonlinear robust observer

NASA Astrophysics Data System (ADS)

Zhou, Bin; Zhang, Jianwu; Gao, Ji; Yu, Haisheng; Liu, Dong

2018-06-01

For a power-split hybrid transmission, using the brake clutch to realize the transition from electric drive mode to hybrid drive mode is an available strategy. Since the pressure information of the brake clutch is essential for the mode transition control, this research designs a nonlinear robust reduced-order observer to estimate the brake clutch pressure. Model uncertainties or disturbances are considered as additional inputs, thus the observer is designed in order that the error dynamics is input-to-state stable. The nonlinear characteristics of the system are expressed as the lookup tables in the observer. Moreover, the gain matrix of the observer is solved by two optimization procedures under the constraints of the linear matrix inequalities. The proposed observer is validated by offline simulation and online test, the results have shown that the observer achieves significant performance during the mode transition, as the estimation error is within a reasonable range, more importantly, it is asymptotically stable.

Dynamic PET of human liver inflammation: impact of kinetic modeling with optimization-derived dual-blood input function.

PubMed

Wang, Guobao; Corwin, Michael T; Olson, Kristin A; Badawi, Ramsey D; Sarkar, Souvik

2018-05-30

The hallmark of nonalcoholic steatohepatitis is hepatocellular inflammation and injury in the setting of hepatic steatosis. Recent work has indicated that dynamic 18F-FDG PET with kinetic modeling has the potential to assess hepatic inflammation noninvasively, while static FDG-PET did not show a promise. Because the liver has dual blood supplies, kinetic modeling of dynamic liver PET data is challenging in human studies. The objective of this study is to evaluate and identify a dual-input kinetic modeling approach for dynamic FDG-PET of human liver inflammation. Fourteen human patients with nonalcoholic fatty liver disease were included in the study. Each patient underwent one-hour dynamic FDG-PET/CT scan and had liver biopsy within six weeks. Three models were tested for kinetic analysis: traditional two-tissue compartmental model with an image-derived single-blood input function (SBIF), model with population-based dual-blood input function (DBIF), and modified model with optimization-derived DBIF through a joint estimation framework. The three models were compared using Akaike information criterion (AIC), F test and histopathologic inflammation reference. The results showed that the optimization-derived DBIF model improved the fitting of liver time activity curves and achieved lower AIC values and higher F values than the SBIF and population-based DBIF models in all patients. The optimization-derived model significantly increased FDG K1 estimates by 101% and 27% as compared with traditional SBIF and population-based DBIF. K1 by the optimization-derived model was significantly associated with histopathologic grades of liver inflammation while the other two models did not provide a statistical significance. In conclusion, modeling of DBIF is critical for kinetic analysis of dynamic liver FDG-PET data in human studies. The optimization-derived DBIF model is more appropriate than SBIF and population-based DBIF for dynamic FDG-PET of liver inflammation. © 2018 Institute of Physics and Engineering in Medicine.

Adaptive optimal input design and parametric estimation of nonlinear dynamical systems: application to neuronal modeling.

PubMed

Madi, Mahmoud K; Karameh, Fadi N

2018-05-11

Many physical models of biological processes including neural systems are characterized by parametric nonlinear dynamical relations between driving inputs, internal states, and measured outputs of the process. Fitting such models using experimental data (data assimilation) is a challenging task since the physical process often operates in a noisy, possibly non-stationary environment; moreover, conducting multiple experiments under controlled and repeatable conditions can be impractical, time consuming or costly. The accuracy of model identification, therefore, is dictated principally by the quality and dynamic richness of collected data over single or few experimental sessions. Accordingly, it is highly desirable to design efficient experiments that, by exciting the physical process with smart inputs, yields fast convergence and increased accuracy of the model. We herein introduce an adaptive framework in which optimal input design is integrated with Square root Cubature Kalman Filters (OID-SCKF) to develop an online estimation procedure that first, converges significantly quicker, thereby permitting model fitting over shorter time windows, and second, enhances model accuracy when only few process outputs are accessible. The methodology is demonstrated on common nonlinear models and on a four-area neural mass model with noisy and limited measurements. Estimation quality (speed and accuracy) is benchmarked against high-performance SCKF-based methods that commonly employ dynamically rich informed inputs for accurate model identification. For all the tested models, simulated single-trial and ensemble averages showed that OID-SCKF exhibited (i) faster convergence of parameter estimates and (ii) lower dependence on inter-trial noise variability with gains up to around 1000 msec in speed and 81% increase in variability for the neural mass models. In terms of accuracy, OID-SCKF estimation was superior, and exhibited considerably less variability across experiments, in identifying model parameters of (a) systems with challenging model inversion dynamics and (b) systems with fewer measurable outputs that directly relate to the underlying processes. Fast and accurate identification therefore carries particular promise for modeling of transient (short-lived) neuronal network dynamics using a spatially under-sampled set of noisy measurements, as is commonly encountered in neural engineering applications. © 2018 IOP Publishing Ltd.

Formulation d'un modele mathematique par des techniques d'estimation de parametres a partir de donnees de vol pour l'helicoptere Bell 427 et l'avion F/A-18 servant a la recherches en aeroservoelasticite

NASA Astrophysics Data System (ADS)

Nadeau-Beaulieu, Michel

In this thesis, three mathematical models are built from flight test data for different aircraft design applications: a ground dynamics model for the Bell 427 helicopter, a prediction model for the rotor and engine parameters for the same helicopter type and a simulation model for the aeroelastic deflections of the F/A-18. In the ground dynamics application, the model structure is derived from physics where the normal force between the helicopter and the ground is modelled as a vertical spring and the frictional force is modelled with static and dynamic friction coefficients. The ground dynamics model coefficients are optimized to ensure that the model matches the landing data within the FAA (Federal Aviation Administration) tolerance bands for a level D flight simulator. In the rotor and engine application, rotors torques (main and tail), the engine torque and main rotor speed are estimated using a state-space model. The model inputs are nonlinear terms derived from the pilot control inputs and the helicopter states. The model parameters are identified using the subspace method and are further optimised with the Levenberg-Marquardt minimisation algorithm. The model built with the subspace method provides an excellent estimate of the outputs within the FAA tolerance bands. The F/A-18 aeroelastic state-space model is built from flight test. The research concerning this model is divided in two parts. Firstly, the deflection of a given structural surface on the aircraft following a differential ailerons control input is represented by a Multiple Inputs Single Outputs linear model whose inputs are the ailerons positions and the structural surfaces deflections. Secondly, a single state-space model is used to represent the deflection of the aircraft wings and trailing edge flaps following any control input. In this case the model is made non-linear by multiplying model inputs into higher order terms and using these terms as the inputs of the state-space equations. In both cases, the identification method is the subspace method. Most fit coefficients between the estimated and the measured signals are above 73% and most correlation coefficient are higher than 90%.

δ15N constraints on long-term nitrogen balances in temperate forests

USGS Publications Warehouse

Perakis, S.S.; Sinkhorn, E.R.; Compton, J.E.

2011-01-01

Biogeochemical theory emphasizes nitrogen (N) limitation and the many factors that can restrict N accumulation in temperate forests, yet lacks a working model of conditions that can promote naturally high N accumulation. We used a dynamic simulation model of ecosystem N and δ15N to evaluate which combination of N input and loss pathways could produce a range of high ecosystem N contents characteristic of forests in the Oregon Coast Range. Total ecosystem N at nine study sites ranged from 8,788 to 22,667 kg ha−1 and carbon (C) ranged from 188 to 460 Mg ha−1, with highest values near the coast. Ecosystem δ15N displayed a curvilinear relationship with ecosystem N content, and largely reflected mineral soil, which accounted for 96–98% of total ecosystem N. Model simulations of ecosystem N balances parameterized with field rates of N leaching required long-term average N inputs that exceed atmospheric deposition and asymbiotic and epiphytic N2-fixation, and that were consistent with cycles of post-fire N2-fixation by early-successional red alder. Soil water δ15NO3 − patterns suggested a shift in relative N losses from denitrification to nitrate leaching as N accumulated, and simulations identified nitrate leaching as the primary N loss pathway that constrains maximum N accumulation. Whereas current theory emphasizes constraints on biological N2-fixation and disturbance-mediated N losses as factors that limit N accumulation in temperate forests, our results suggest that wildfire can foster substantial long-term N accumulation in ecosystems that are colonized by symbiotic N2-fixing vegetation.

Modular 5-kW Power-Processing Unit Being Developed for the Next-Generation Ion Engine

NASA Technical Reports Server (NTRS)

Pinero, Luis R.; Bond, Thomas H.; Okada, Don; Phelps, Keith; Pyter, Janusz; Wiseman, Steve

2001-01-01

The NASA Glenn Research Center is developing a 5- to 10-kW ion engine for a broad range of mission applications. Simultaneously, a 5-kW breadboard power-processing unit (PPU) is being designed and fabricated by Boeing Electron Dynamic Devices, Torrance, California, under contract with Glenn. The beam supply, which processes up to 90 percent of the power into this unit, consists of four 1.1-kW power modules connected in parallel, equally sharing the output current. The modular design allows scalability to higher powers as well as the possibility of implementing an N + 1 redundant beam supply. A novel phaseshifted/pulse-width-modulated, dual full-bridge topology was chosen for this module design for its efficient switching characteristics. A breadboard version of the beam power supply module was assembled. Efficiencies ranging between 91.6 and 96.9 percent were measured for an input voltage range of 80 to 160 V, an output voltage range of 800 to 1500 V, and output powers from 0.3 to 1.0 kW. This beam supply could result in a PPU with a total efficiency between 93 and 95 percent at a nominal input voltage of 100 V. This is up to a 4-percent improvement over the state-of-the-art PPU used for the Deep Space 1 mission. A flight-packaged PPU is expected to weigh no more than 15 kg, which represents a 50-percent reduction in specific mass from the Deep Space 1 design. This will make 5-kW ion propulsion very attractive for many planetary missions.

Solving the two-dimensional Fokker-Planck equation for strongly correlated neurons

NASA Astrophysics Data System (ADS)

Deniz, Taşkın; Rotter, Stefan

2017-01-01

Pairs of neurons in brain networks often share much of the input they receive from other neurons. Due to essential nonlinearities of the neuronal dynamics, the consequences for the correlation of the output spike trains are generally not well understood. Here we analyze the case of two leaky integrate-and-fire neurons using an approach which is nonperturbative with respect to the degree of input correlation. Our treatment covers both weakly and strongly correlated dynamics, generalizing previous results based on linear response theory.

Transcending binary logic by gating three coupled quantum dots.

PubMed

Klein, Michael; Rogge, S; Remacle, F; Levine, R D

2007-09-01

Physical considerations supported by numerical solution of the quantum dynamics including electron repulsion show that three weakly coupled quantum dots can robustly execute a complete set of logic gates for computing using three valued inputs and outputs. Input is coded as gating (up, unchanged, or down) of the terminal dots. A nanosecond time scale switching of the gate voltage requires careful numerical propagation of the dynamics. Readout is the charge (0, 1, or 2 electrons) on the central dot.

Coupled dynamic systems and Le Chatelier's principle in noise control

NASA Astrophysics Data System (ADS)

Maidanik, G.; Becker, K. J.

2004-05-01

Investigation of coupling an externally driven dynamic system-a master dynamic system-to a passive one-an adjunct dynamic system-reveals that the response of the adjunct dynamic system affects the precoupled response of the master dynamic system. The responses, in the two dynamic systems when coupled, are estimated by the stored energies (Es) and (E0), respectively. Since the adjunct dynamic system, prior to coupling, was with zero (0) stored energy, E0s=0, the precoupled stored energy (E00) in the master dynamic system is expected to be reduced to (E0) when coupling is instituted; i.e., one expects E0

Adaptive and neuroadaptive control for nonnegative and compartmental dynamical systems

NASA Astrophysics Data System (ADS)

Volyanskyy, Kostyantyn Y.

Neural networks have been extensively used for adaptive system identification as well as adaptive and neuroadaptive control of highly uncertain systems. The goal of adaptive and neuroadaptive control is to achieve system performance without excessive reliance on system models. To improve robustness and the speed of adaptation of adaptive and neuroadaptive controllers several controller architectures have been proposed in the literature. In this dissertation, we develop a new neuroadaptive control architecture for nonlinear uncertain dynamical systems. The proposed framework involves a novel controller architecture with additional terms in the update laws that are constructed using a moving window of the integrated system uncertainty. These terms can be used to identify the ideal system weights of the neural network as well as effectively suppress system uncertainty. Linear and nonlinear parameterizations of the system uncertainty are considered and state and output feedback neuroadaptive controllers are developed. Furthermore, we extend the developed framework to discrete-time dynamical systems. To illustrate the efficacy of the proposed approach we apply our results to an aircraft model with wing rock dynamics, a spacecraft model with unknown moment of inertia, and an unmanned combat aerial vehicle undergoing actuator failures, and compare our results with standard neuroadaptive control methods. Nonnegative systems are essential in capturing the behavior of a wide range of dynamical systems involving dynamic states whose values are nonnegative. A sub-class of nonnegative dynamical systems are compartmental systems. These systems are derived from mass and energy balance considerations and are comprised of homogeneous interconnected microscopic subsystems or compartments which exchange variable quantities of material via intercompartmental flow laws. In this dissertation, we develop direct adaptive and neuroadaptive control framework for stabilization, disturbance rejection and noise suppression for nonnegative and compartmental dynamical systems with noise and exogenous system disturbances. We then use the developed framework to control the infusion of the anesthetic drug propofol for maintaining a desired constant level of depth of anesthesia for surgery in the face of continuing hemorrhage and hemodilution. Critical care patients, whether undergoing surgery or recovering in intensive care units, require drug administration to regulate physiological variables such as blood pressure, cardiac output, heart rate, and degree of consciousness. The rate of infusion of each administered drug is critical, requiring constant monitoring and frequent adjustments. In this dissertation, we develop a neuroadaptive output feedback control framework for nonlinear uncertain nonnegative and compartmental systems with nonnegative control inputs and noisy measurements. The proposed framework is Lyapunov-based and guarantees ultimate boundedness of the error signals. In addition, the neuroadaptive controller guarantees that the physical system states remain in the nonnegative orthant of the state space. Finally, the developed approach is used to control the infusion of the anesthetic drug propofol for maintaining a desired constant level of depth of anesthesia for surgery in the face of noisy electroencephalographic (EEG) measurements. Clinical trials demonstrate excellent regulation of unconsciousness allowing for a safe and effective administration of the anesthetic agent propofol. Furthermore, a neuroadaptive output feedback control architecture for nonlinear nonnegative dynamical systems with input amplitude and integral constraints is developed. Specifically, the neuroadaptive controller guarantees that the imposed amplitude and integral input constraints are satisfied and the physical system states remain in the nonnegative orthant of the state space. The proposed approach is used to control the infusion of the anesthetic drug propofol for maintaining a desired constant level of depth of anesthesia for noncardiac surgery in the face of infusion rate constraints and a drug dosing constraint over a specified period. In addition, the aforementioned control architecture is used to control lung volume and minute ventilation with input pressure constraints that also accounts for spontaneous breathing by the patient. Specifically, we develop a pressure- and work-limited neuroadaptive controller for mechanical ventilation based on a nonlinear multi-compartmental lung model. The control framework does not rely on any averaged data and is designed to automatically adjust the input pressure to the patient's physiological characteristics capturing lung resistance and compliance modeling uncertainty. Moreover, the controller accounts for input pressure constraints as well as work of breathing constraints. The effect of spontaneous breathing is incorporated within the lung model and the control framework. Finally, a neural network hybrid adaptive control framework for nonlinear uncertain hybrid dynamical systems is developed. The proposed hybrid adaptive control framework is Lyapunov-based and guarantees partial asymptotic stability of the closed-loop hybrid system; that is, asymptotic stability with respect to part of the closed-loop system states associated with the hybrid plant states. A numerical example is provided to demonstrate the efficacy of the proposed hybrid adaptive stabilization approach.

How uncertain is model-based prediction of copper loads in stormwater runoff?

PubMed

Lindblom, E; Ahlman, S; Mikkelsen, P S

2007-01-01

In this paper, we conduct a systematic analysis of the uncertainty related with estimating the total load of pollution (copper) from a separate stormwater drainage system, conditioned on a specific combination of input data, a dynamic conceptual pollutant accumulation-washout model and measurements (runoff volumes and pollutant masses). We use the generalized likelihood uncertainty estimation (GLUE) methodology and generate posterior parameter distributions that result in model outputs encompassing a significant number of the highly variable measurements. Given the applied pollution accumulation-washout model and a total of 57 measurements during one month, the total predicted copper masses can be predicted within a range of +/-50% of the median value. The message is that this relatively large uncertainty should be acknowledged in connection with posting statements about micropollutant loads as estimated from dynamic models, even when calibrated with on-site concentration data.

Adaptation without parameter change: Dynamic gain control in motion detection

PubMed Central

Borst, Alexander; Flanagin, Virginia L.; Sompolinsky, Haim

2005-01-01

Many sensory systems adapt their input-output relationship to changes in the statistics of the ambient stimulus. Such adaptive behavior has been measured in a motion detection sensitive neuron of the fly visual system, H1. The rapid adaptation of the velocity response gain has been interpreted as evidence of optimal matching of the H1 response to the dynamic range of the stimulus, thereby maximizing its information transmission. Here, we show that correlation-type motion detectors, which are commonly thought to underlie fly motion vision, intrinsically possess adaptive properties. Increasing the amplitude of the velocity fluctuations leads to a decrease of the effective gain and the time constant of the velocity response without any change in the parameters of these detectors. The seemingly complex property of this adaptation turns out to be a straightforward consequence of the multidimensionality of the stimulus and the nonlinear nature of the system. PMID:15833815

Estimated performance and future potential of solar dynamic and photovoltaic power systems for selected LEO and HEO missions

NASA Technical Reports Server (NTRS)

Bents, David J.; Lu, Cheng Y.

1989-01-01

Solar photovoltaic and thermal dynamic power systems for application to selected low-earth-orbit (LEO) and high-earth-orbit (HEO) missions are characterized in the regime 7 to 35 kWe. Input parameters to the characterization are varied to correspond to anticipated introduction of improved or new technologies. A comparative assessment is made of the two power system types for emerging technologies in cells and arrays, energy storage, optical surfaces, heat engines, thermal energy storage and thermal management. The assessment is made to common ground rules and assumptions. The four missions (Space Station, sun-synchronous, Van Allen belt, and GEO) are representative of the anticipated range of multikilowatt earth-orbit missions. The results give the expected performance, mass and drag of multikilowatt earth-orbiting solar power systems and show how the overall system figure of merit will improve as new component technologies are incorporated.

Improved performance of analog and digital acousto-optic modulation with feedback under profiled beam propagation for secure communication using chaos

NASA Astrophysics Data System (ADS)

Almehmadi, Fares S.; Chatterjee, Monish R.

2014-12-01

Using intensity feedback, the closed-loop behavior of an acousto-optic hybrid device under profiled beam propagation has been recently shown to exhibit wider chaotic bands potentially leading to an increase in both the dynamic range and sensitivity to key parameters that characterize the encryption. In this work, a detailed examination is carried out vis-à-vis the robustness of the encryption/decryption process relative to parameter mismatch for both analog and pulse code modulation signals, and bit error rate (BER) curves are used to examine the impact of additive white noise. The simulations with profiled input beams are shown to produce a stronger encryption key (i.e., much lower parametric tolerance thresholds) relative to simulations with uniform plane wave input beams. In each case, it is shown that the tolerance for key parameters drops by factors ranging from 10 to 20 times below those for uniform plane wave propagation. Results are shown to be at consistently lower tolerances for secure transmission of analog and digital signals using parameter tolerance measures, as well as BER performance measures for digital signals. These results hold out the promise for considerably greater information transmission security for such a system.

Multi-scale simulation of radiation damage accumulation and subsequent hardening in neutron-irradiated α-Fe

DOE PAGES

Dunn, Aaron; Dingreville, Remi; Capolungo, Laurent

2015-11-27

A hierarchical methodology is introduced to predict the effects of radiation damage and irradiation conditions on the yield stress and internal stress heterogeneity developments in polycrystalline α-Fe. Simulations of defect accumulation under displacement cascade damage conditions are performed using spatially resolved stochastic cluster dynamics. The resulting void and dislocation loop concentrations and average sizes are then input into a crystal plasticity formulation that accounts for the change in critical resolved shear stress due to the presence of radiation induced defects. The simulated polycrystalline tensile tests show a good match to experimental hardening data over a wide range of irradiation doses.more » With this capability, stress heterogeneity development and the effect of dose rate on hardening is investigated. The model predicts increased hardening at higher dose rates for low total doses. By contrast, at doses above 10 –2 dpa when cascade overlap becomes significant, the model does not predict significantly different hardening for different dose rates. In conclusion, the development of such a model enables simulation of radiation damage accumulation and associated hardening without relying on experimental data as an input under a wide range of irradiation conditions such as dose, dose rate, and temperature.« less

On the dynamics of Airy beams in nonlinear media with nonlinear losses.

PubMed

Ruiz-Jiménez, Carlos; Nóbrega, K Z; Porras, Miguel A

2015-04-06

We investigate on the nonlinear dynamics of Airy beams in a regime where nonlinear losses due to multi-photon absorption are significant. We identify the nonlinear Airy beam (NAB) that preserves the amplitude of the inward Hänkel component as an attractor of the dynamics. This attractor governs also the dynamics of finite-power (apodized) Airy beams, irrespective of the location of the entrance plane in the medium with respect to the Airy waist plane. A soft (linear) input long before the waist, however, strongly speeds up NAB formation and its persistence as a quasi-stationary beam in comparison to an abrupt input at the Airy waist plane, and promotes the formation of a new type of highly dissipative, fully nonlinear Airy beam not described so far.

The Role of Dynamic Storage in the Response to Snowmelt Conditions in the Southwestern United States: Flux Hysteresis at the Catchment Scale

NASA Astrophysics Data System (ADS)

Driscoll, J. M.; Meixner, T.; Ferré, T. P. A.; Williams, M. W.; Sickman, J. O.; Molotch, N. P.; Jepsen, S. M.

2014-12-01

The role of dynamic storage in catchment discharge response to earlier snowmelt timing has not been fully quantified. Green Lake 4 (GL4) and Emerald Lake Watershed (ELW) have similar high-elevation settings but GL4 has greater estimated storage capacity relative to ELW due to differences in physical structure. Daily catchment area-normalized input (modelled snowmelt estimates) and output (measured discharge) in conjunction with mineral weathering products (hydrochemical data) for eleven snowmelt seasons from GL4 (more storage) and ELW (less storage) were used to determine the role of dynamic storage at the catchment scale. Daily fluxes generally show snowmelt is greater than discharge initially, changing mid-season to discharge being greater than snowmelt, creating a counter-clockwise hysteresis loop for each snowmelt season. This hysteresis loop can be approximated with a least-squares fitted ellipse. The properties of fitted ellipses were used to quantify catchment response, which were then compared between catchments with different storage capacities (GL4 and ELW). The eccentricity of the fitted ellipses can be used to quantify delay between snowmelt and discharge due to connection to subsurface storage; narrower loops show minimal storage delay whereas wider loops show greater storage delay. Variability of mineral weathering products shows changes in contribution from stored water over the snowmelt season. Both catchments show a moderate linear correlation between fitted ellipse area and total snowmelt volume (GL4 R2=0.516, ELW R2=0.614). Ellipse eccentricity is more consistent among years in ELW (range=0.81-0.94) than in GL4 (range=0.54-0.95), indicating a more consistent hydrologic structure and connectivity to shallow storage at ELW. The linear correlation between seasonal eccentricity versus snowmelt timing is stronger in ELW than GL4 (R2=0.741 and 0.223, respectively). ELW shows hydrochemical response independent of snowmelt timing, whereas GL4 shows more variability. The larger storage capacity of GL4 allows for a greater range of physical and chemical response to input conditions. The limited storage capacity of ELW shows greater vulnerability of physical response to changes in snowmelt conditions, though chemical response remains constant regardless of snowmelt conditions.

Aircraft Hydraulic Systems Dynamic Analysis Component Data Handbook

DTIC Science & Technology

1980-04-01

82 13. QUINCKE TUBE ...................................... 85 14. 11EAT EXCHANGER ............. ................... 90...Input Parameters ....... ........... .7 61 )uincke Tube Input Parameters with Hole Locat ions 87 62 "rototype Quincke Tube Data ........... 89 6 3 Fo-,:ed...Elasticity (Line 3) PSI 1.6E7 FIGURE 58 HSFR INPUT DATA FOR PULSCO TYPE ACOUSTIC FILTER 84 13. QUINCKE TUBE A means to dampen acoustic noise at resonance

Digital signaling decouples activation probability and population heterogeneity.

PubMed

Kellogg, Ryan A; Tian, Chengzhe; Lipniacki, Tomasz; Quake, Stephen R; Tay, Savaş

2015-10-21

Digital signaling enhances robustness of cellular decisions in noisy environments, but it is unclear how digital systems transmit temporal information about a stimulus. To understand how temporal input information is encoded and decoded by the NF-κB system, we studied transcription factor dynamics and gene regulation under dose- and duration-modulated inflammatory inputs. Mathematical modeling predicted and microfluidic single-cell experiments confirmed that integral of the stimulus (or area, concentration × duration) controls the fraction of cells that activate NF-κB in the population. However, stimulus temporal profile determined NF-κB dynamics, cell-to-cell variability, and gene expression phenotype. A sustained, weak stimulation lead to heterogeneous activation and delayed timing that is transmitted to gene expression. In contrast, a transient, strong stimulus with the same area caused rapid and uniform dynamics. These results show that digital NF-κB signaling enables multidimensional control of cellular phenotype via input profile, allowing parallel and independent control of single-cell activation probability and population heterogeneity.

40 CFR 86.131-00 - Vehicle preparation.

Code of Federal Regulations, 2012 CFR

2012-07-01

... test dynamometer. This signal provides the input information that controls dynamometer dynamic inertia... implement dynamic inertia adjustments for a portion or all of their product line, this requirement is not...

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

Computational Design of Materials: Planetary Entry to Electric Aircraft and Beyond

NASA Technical Reports Server (NTRS)

Thompson, Alexander; Lawson, John W.

2014-01-01

NASA's projects and missions push the bounds of what is possible. To support the agency's work, materials development must stay on the cutting edge in order to keep pace. Today, researchers at NASA Ames Research Center perform multiscale modeling to aid the development of new materials and provide insight into existing ones. Multiscale modeling enables researchers to determine micro- and macroscale properties by connecting computational methods ranging from the atomic level (density functional theory, molecular dynamics) to the macroscale (finite element method). The output of one level is passed on as input to the next level, creating a powerful predictive model.

TEMPEST: A three-dimensional time-dependent computer program for hydrothermal analysis: Volume 1, Numerical methods and input instructions

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

Trent, D.S.; Eyler, L.L.; Budden, M.J.

This document describes the numerical methods, current capabilities, and the use of the TEMPEST (Version L, MOD 2) computer program. TEMPEST is a transient, three-dimensional, hydrothermal computer program that is designed to analyze a broad range of coupled fluid dynamic and heat transfer systems of particular interest to the Fast Breeder Reactor thermal-hydraulic design community. The full three-dimensional, time-dependent equations of motion, continuity, and heat transport are solved for either laminar or turbulent fluid flow, including heat diffusion and generation in both solid and liquid materials. 10 refs., 22 figs., 2 tabs.

Dynamic Range and Sensitivity Requirements of Satellite Ocean Color Sensors: Learning from the Past

NASA Technical Reports Server (NTRS)

Hu, Chuanmin; Feng, Lian; Lee, Zhongping; Davis, Curtiss O.; Mannino, Antonio; McClain, Charles R.; Franz, Bryan A.

2012-01-01

Sensor design and mission planning for satellite ocean color measurements requires careful consideration of the signal dynamic range and sensitivity (specifically here signal-to-noise ratio or SNR) so that small changes of ocean properties (e.g., surface chlorophyll-a concentrations or Chl) can be quantified while most measurements are not saturated. Past and current sensors used different signal levels, formats, and conventions to specify these critical parameters, making it difficult to make cross-sensor comparisons or to establish standards for future sensor design. The goal of this study is to quantify these parameters under uniform conditions for widely used past and current sensors in order to provide a reference for the design of future ocean color radiometers. Using measurements from the Moderate Resolution Imaging Spectroradiometer onboard the Aqua satellite (MODISA) under various solar zenith angles (SZAs), typical (L(sub typical)) and maximum (L(sub max)) at-sensor radiances from the visible to the shortwave IR were determined. The Ltypical values at an SZA of 45 deg were used as constraints to calculate SNRs of 10 multiband sensors at the same L(sub typical) radiance input and 2 hyperspectral sensors at a similar radiance input. The calculations were based on clear-water scenes with an objective method of selecting pixels with minimal cross-pixel variations to assure target homogeneity. Among the widely used ocean color sensors that have routine global coverage, MODISA ocean bands (1 km) showed 2-4 times higher SNRs than the Sea-viewing Wide Field-of-view Sensor (Sea-WiFS) (1 km) and comparable SNRs to the Medium Resolution Imaging Spectrometer (MERIS)-RR (reduced resolution, 1.2 km), leading to different levels of precision in the retrieved Chl data product. MERIS-FR (full resolution, 300 m) showed SNRs lower than MODISA and MERIS-RR with the gain in spatial resolution. SNRs of all MODISA ocean bands and SeaWiFS bands (except the SeaWiFS near-IR bands) exceeded those from prelaunch sensor specifications after adjusting the input radiance to L(sub typical). The tabulated L(sub typical), L(sub max), and SNRs of the various multiband and hyperspectral sensors under the same or similar radiance input provide references to compare sensor performance in product precision and to help design future missions such as the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission and the Pre-Aerosol-Clouds-Ecosystems (PACE) mission currently being planned by the U.S. National Aeronautics and Space Administration (NASA).

Pre-compound emission in low-energy heavy-ion interactions

NASA Astrophysics Data System (ADS)

Sharma, Manoj Kumar; Shuaib, Mohd.; Sharma, Vijay R.; Yadav, Abhishek; Singh, Pushpendra P.; Singh, Devendra P.; Unnati; Singh, B. P.; Prasad, R.

2017-11-01

Recent experimental studies have shown the presence of pre-compound emission component in heavy ion reactions at low projectile energy ranging from 4 to 7 MeV/nucleons. In earlier measurements strength of the pre-compound component has been estimated from the difference in forward-backward distributions of emitted particles. Present measurement is a part of an ongoing program on the study of reaction dynamics of heavy ion interactions at low energies aimed at investigating the effect of momentum transfer in compound, precompound, complete and incomplete fusion processes in heavy ion reactions. In the present work on the basis of momentum transfer the measurement of the recoil range distributions of heavy residues has been used to decipher the components of compound and pre-compound emission processes in the fusion of 16O projectile with 159Tb and 169Tm targets. The analysis of recoil range distribution measurements show two distinct linear momentum transfer components corresponding to pre-compound and compound nucleus processes are involved. In order to obtain the mean input angular momentum associated with compound and pre-compound emission processes, an online measurement of the spin distributions of the residues has been performed. The analysis of spin distribution indicate that the mean input angular momentum associated with pre-compound products is found to be relatively lower than that associated with compound nucleus process. The pre-compound components obtained from the present analysis are consistent with those obtained from the analysis of excitation functions.

Feedback control by online learning an inverse model.

PubMed

Waegeman, Tim; Wyffels, Francis; Schrauwen, Francis

2012-10-01

A model, predictor, or error estimator is often used by a feedback controller to control a plant. Creating such a model is difficult when the plant exhibits nonlinear behavior. In this paper, a novel online learning control framework is proposed that does not require explicit knowledge about the plant. This framework uses two learning modules, one for creating an inverse model, and the other for actually controlling the plant. Except for their inputs, they are identical. The inverse model learns by the exploration performed by the not yet fully trained controller, while the actual controller is based on the currently learned model. The proposed framework allows fast online learning of an accurate controller. The controller can be applied on a broad range of tasks with different dynamic characteristics. We validate this claim by applying our control framework on several control tasks: 1) the heating tank problem (slow nonlinear dynamics); 2) flight pitch control (slow linear dynamics); and 3) the balancing problem of a double inverted pendulum (fast linear and nonlinear dynamics). The results of these experiments show that fast learning and accurate control can be achieved. Furthermore, a comparison is made with some classical control approaches, and observations concerning convergence and stability are made.

Biometric verification in dynamic writing

NASA Astrophysics Data System (ADS)

George, Susan E.

2002-03-01

Pen-tablet devices capable of capturing the dynamics of writing record temporal and pressure information as well as the spatial pattern. This paper explores biometric verification based upon the dynamics of writing where writers are distinguished not on the basis of what they write (ie the signature), but how they write. We have collected samples of dynamic writing from 38 Chinese writers. Each writer was asked to provide 10 copies of a paragraph of text and the same number of signature samples. From the data we have extracted stroke-based primitives from the sentence data utilizing pen-up/down information and heuristic rules about the shape of the character. The x, y and pressure values of each primitive were interpolated into an even temporal range based upon a 20 msec sampling rate. We applied the Daubechies 1 wavelet transform to the x signal, y signal and pressure signal using the coefficients as inputs to a multi-layer perceptron trained with back-propagation on the sentence data. We found a sensitivity of 0.977 and specificity of 0.990 recognizing writers based on test primitives extracted from sentence data and measures of 0.916 and 0.961 respectively, from test primitives extracted from signature data.

Soil carbon dynamics beneath switchgrass as indicated by stable isotope analysis

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

Garten, C.T. Jr.; Wullschleger, S.D.

2000-04-01

Surface (0--40 cm) soil organic carbon (SOC) dynamics were studied beneath four switchgrass (Panicum virgatum L.) field trails in the southeastern US. Soil organic carbon was partitioned into particulate organic matter (POM) and mineral-associated organic matter (MOM). Most (75--90%) of the SOC at each study site was affiliated with MOM (<0.053 mm). Changes in stable carbon isotope ratios were used to derive carbon inputs to and losses from POM and MOM at each site. Inventories of existing SOC and new C{sub 4}-derived SOC beneath switchgrass decreased with increasing soil depth. Approximately 5 yr after establishment, 19 to 31% of themore » existing SOC inventories beneath switchgrass had been derived from new C{sub 4}-carbon inputs. Calculated turnover times of POM and MOM ranged from 2.4 to 4.3 yr and 26 to 40 yr, respectively. The turnover time of SOC in the POM fraction increased with decreasing mean annual temperature. A simple, two-compartment model was parameterized to predict the potential for soil carbon sequestration under switchgrass. An example calculation with the model indicated a measurable and verifiable recovery of soil carbon (=12% increase) on degraded lands through one decade of switchgrass production. The potential to sequester carbon through switchgrass cultivation will depend on initial soil carbon inventories, prevailing climate, soil types and site management.« less

Soil carbon dynamics beneath switchgrass as indicated by stable isotope analysis

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

Garten Jr, Charles T; Wullschleger, Stan D

2000-04-01

Surface (0-40 cm) soil organic carbon (SOC) dynamics were studied beneath four switchgrass (Panicum virgatum L.) field trials in the southeastern United States. Soil organic carbon was partitioned into particulate organic matter (POM) and mineral-associated organic matter (MOM). Most (75-90%) of the SOC at each study site was affiliated with MOM (<0.053 mm). Changes in stable carbon isotope ratios were used to derive carbon inputs to and losses from POM and MOM at each site. Inventories of existing SOC and new C4-derived SOC beneath switchgrass decreased with increasing soil depth. Approximately 5 yr after establishment, 19 to 31% of themore » existing SOC inventories beneath switchgrass had been derived from new C{sub 4}-carbon inputs. Calculated turnover times of POM and MOM ranged from 2.4 to 4.3 yr and 26 to 40 yr, respectively. The turnover time of SOC in the POM fraction increased with decreasing mean annual temperature. A simple, two-compartment model was parameterized to predict the potential for soil carbon sequestration under switchgrass. An example calculation with the model indicated a measurable and verifiable recovery of soil carbon ({approx}12% increase) on degraded lands through one decade of switchgrass production. The potential to sequester carbon through switchgrass cultivation will depend on initial soil carbon inventories, prevailing climate, soil type, and site management.« less

The water quality of the River Enborne, UK: insights from high-frequency monitoring

NASA Astrophysics Data System (ADS)

Halliday, Sarah; Skeffington, Richard; Wade, Andrew; Bowes, Mike; Gozzard, Emma; Palmer-Felgate, Elizabeth; Newman, Johnathan; Jarvie, Helen; Loewenthal, Matt

2014-05-01

The River Enborne is a rural lowland catchment, impacted by agricultural runoff, and septic tank and sewage treatment works (STWs) discharges. Between November 2009 and February 2012, the river was instrumented with in situ analytical equipment to take hourly measurements of total reactive phosphorus (TRP), using a Systea Micromac C; nitrate, using a Hach Lange Nitratax; and pH, chlorophyll, dissolved oxygen, conductivity, turbidity and water temperature, using a YSI 6600 Multi-parameter sonde. In addition, weekly 'grab samples' were also collected and analysed for a wide range of chemical determinands including major ions, nutrients, and trace elements. The catchment land use is largely agricultural, with wheat the dominant crop, and the average population density is 123 persons per sq. km. The river water is largely derived from calcareous groundwater, with a mean calcium concentration of 68.5 mg/l, and high nitrogen and phosphorus concentrations, with mean nitrate and TRP concentrations of 3.96 mg/l-N and 0.17 mg/l-P respectively. A mass-balance for the catchment demonstrated that agricultural fertiliser is the dominant source of annual loads of both nitrogen and phosphorus, accounting for 77 % and 84 % respectively. However, the concentration data show that sewage effluent discharges have a disproportionate effect on the river nitrogen and phosphorus dynamics, with the diurnal STW discharge signal discernable in the high-frequency nutrient dynamics. The nutrient dynamics and correlation structure of the data indicate a substantial contribution of groundwater and agricultural runoff to stream nitrate concentrations, whereas discharges from septic tank systems and sewage treatment works are a more important source of phosphorus. The high-frequency turbidity and conductivity dynamics reveal key information about the seasonal changes controlling the system dynamics, with marked differences in diurnal conductivity dynamics at the onset of riparian shading linked to the decreased importance of the photosynthetically-driven cycle of bicarbonate concentration. Only 4 % of the phosphorus input and 9 % of the nitrogen input is exported from the catchment by the river, highlighting the importance of catchment process understanding in predicting nutrient concentrations. High-frequency monitoring will be a key to developing this vital process understanding.

How the type of input function affects the dynamic response of conducting polymer actuators

NASA Astrophysics Data System (ADS)

Xiang, Xingcan; Alici, Gursel; Mutlu, Rahim; Li, Weihua

2014-10-01

There has been a growing interest in smart actuators typified by conducting polymer actuators, especially in their (i) fabrication, modeling and control with minimum external data and (ii) applications in bio-inspired devices, robotics and mechatronics. Their control is a challenging research problem due to the complex and nonlinear properties of these actuators, which cannot be predicted accurately. Based on an input-shaping technique, we propose a new method to improve the conducting polymer actuators’ command-following ability, while minimizing their electric power consumption. We applied four input functions with smooth characteristics to a trilayer conducting polymer actuator to experimentally evaluate its command-following ability under an open-loop control strategy and a simulated feedback control strategy, and, more importantly, to quantify how the type of input function affects the dynamic response of this class of actuators. We have found that the four smooth inputs consume less electrical power than sharp inputs such as a step input with discontinuous higher-order derivatives. We also obtained an improved transient response performance from the smooth inputs, especially under the simulated feedback control strategy, which we have proposed previously [X Xiang, R Mutlu, G Alici, and W Li, 2014 “Control of conducting polymer actuators without physical feedback: simulated feedback control approach with particle swarm optimization’, Journal of Smart Materials and Structure, 23]. The idea of using a smooth input command, which results in lower power consumption and better control performance, can be extended to other smart actuators. Consuming less electrical energy or power will have a direct effect on enhancing the operational life of these actuators.

Analytical solution for a class of network dynamics with mechanical and financial applications

NASA Astrophysics Data System (ADS)

Krejčí, P.; Lamba, H.; Melnik, S.; Rachinskii, D.

2014-09-01

We show that for a certain class of dynamics at the nodes the response of a network of any topology to arbitrary inputs is defined in a simple way by its response to a monotone input. The nodes may have either a discrete or continuous set of states and there is no limit on the complexity of the network. The results provide both an efficient numerical method and the potential for accurate analytic approximation of the dynamics on such networks. As illustrative applications, we introduce a quasistatic mechanical model with objects interacting via frictional forces and a financial market model with avalanches and critical behavior that are generated by momentum trading strategies.

Quantification of regional myocardial blood flow estimation with three-dimensional dynamic rubidium-82 PET and modified spillover correction model.

PubMed

Katoh, Chietsugu; Yoshinaga, Keiichiro; Klein, Ran; Kasai, Katsuhiko; Tomiyama, Yuuki; Manabe, Osamu; Naya, Masanao; Sakakibara, Mamoru; Tsutsui, Hiroyuki; deKemp, Robert A; Tamaki, Nagara

2012-08-01

Myocardial blood flow (MBF) estimation with (82)Rubidium ((82)Rb) positron emission tomography (PET) is technically difficult because of the high spillover between regions of interest, especially due to the long positron range. We sought to develop a new algorithm to reduce the spillover in image-derived blood activity curves, using non-uniform weighted least-squares fitting. Fourteen volunteers underwent imaging with both 3-dimensional (3D) (82)Rb and (15)O-water PET at rest and during pharmacological stress. Whole left ventricular (LV) (82)Rb MBF was estimated using a one-compartment model, including a myocardium-to-blood spillover correction to estimate the corresponding blood input function Ca(t)(whole). Regional K1 values were calculated using this uniform global input function, which simplifies equations and enables robust estimation of MBF. To assess the robustness of the modified algorithm, inter-operator repeatability of 3D (82)Rb MBF was compared with a previously established method. Whole LV correlation of (82)Rb MBF with (15)O-water MBF was better (P < .01) with the modified spillover correction method (r = 0.92 vs r = 0.60). The modified method also yielded significantly improved inter-operator repeatability of regional MBF quantification (r = 0.89) versus the established method (r = 0.82) (P < .01). A uniform global input function can suppress LV spillover into the image-derived blood input function, resulting in improved precision for MBF quantification with 3D (82)Rb PET.

A new rate-dependent model for high-frequency tracking performance enhancement of piezoactuator system

NASA Astrophysics Data System (ADS)

Tian, Lizhi; Xiong, Zhenhua; Wu, Jianhua; Ding, Han

2017-05-01

Feedforward-feedback control is widely used in motion control of piezoactuator systems. Due to the phase lag caused by incomplete dynamics compensation, the performance of the composite controller is greatly limited at high frequency. This paper proposes a new rate-dependent model to improve the high-frequency tracking performance by reducing dynamics compensation error. The rate-dependent model is designed as a function of the input and input variation rate to describe the input-output relationship of the residual system dynamics which mainly performs as phase lag in a wide frequency band. Then the direct inversion of the proposed rate-dependent model is used to compensate the residual system dynamics. Using the proposed rate-dependent model as feedforward term, the open loop performance can be improved significantly at medium-high frequency. Then, combining the with feedback controller, the composite controller can provide enhanced close loop performance from low frequency to high frequency. At the frequency of 1 Hz, the proposed controller presents the same performance as previous methods. However, at the frequency of 900 Hz, the tracking error is reduced to be 30.7% of the decoupled approach.

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.

Ultrastable low-noise current amplifier: a novel device for measuring small electric currents with high accuracy.

PubMed

Drung, D; Krause, C; Becker, U; Scherer, H; Ahlers, F J

2015-02-01

An ultrastable low-noise current amplifier (ULCA) is presented. The ULCA is a non-cryogenic instrument based on specially designed operational amplifiers and resistor networks. It involves two stages, the first providing a 1000-fold current gain and the second performing a current-to-voltage conversion via an internal 1 MΩ reference resistor or, optionally, an external standard resistor. The ULCA's transfer coefficient is highly stable versus time, temperature, and current amplitude within the full dynamic range of ±5 nA. The low noise level of 2.4 fA/√Hz helps to keep averaging times short at small input currents. A cryogenic current comparator is used to calibrate both input current gain and output transresistance, providing traceability to the quantum Hall effect. Within one week after calibration, the uncertainty contribution from short-term fluctuations and drift of the transresistance is about 0.1 parts per million (ppm). The long-term drift is typically 5 ppm/yr. A high-accuracy variant is available that shows improved stability of the input gain at the expense of a higher noise level of 7.5 fA/√Hz. The ULCA also allows the traceable generation of small electric currents or the calibration of high-ohmic resistors.

Ultrastable low-noise current amplifier: A novel device for measuring small electric currents with high accuracy

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

Drung, D.; Krause, C.; Becker, U.

2015-02-15

An ultrastable low-noise current amplifier (ULCA) is presented. The ULCA is a non-cryogenic instrument based on specially designed operational amplifiers and resistor networks. It involves two stages, the first providing a 1000-fold current gain and the second performing a current-to-voltage conversion via an internal 1 MΩ reference resistor or, optionally, an external standard resistor. The ULCA’s transfer coefficient is highly stable versus time, temperature, and current amplitude within the full dynamic range of ±5 nA. The low noise level of 2.4 fA/√Hz helps to keep averaging times short at small input currents. A cryogenic current comparator is used to calibratemore » both input current gain and output transresistance, providing traceability to the quantum Hall effect. Within one week after calibration, the uncertainty contribution from short-term fluctuations and drift of the transresistance is about 0.1 parts per million (ppm). The long-term drift is typically 5 ppm/yr. A high-accuracy variant is available that shows improved stability of the input gain at the expense of a higher noise level of 7.5 fA/√Hz. The ULCA also allows the traceable generation of small electric currents or the calibration of high-ohmic resistors.« less

Ultrastable low-noise current amplifier: A novel device for measuring small electric currents with high accuracy

NASA Astrophysics Data System (ADS)

Drung, D.; Krause, C.; Becker, U.; Scherer, H.; Ahlers, F. J.

2015-02-01

An ultrastable low-noise current amplifier (ULCA) is presented. The ULCA is a non-cryogenic instrument based on specially designed operational amplifiers and resistor networks. It involves two stages, the first providing a 1000-fold current gain and the second performing a current-to-voltage conversion via an internal 1 MΩ reference resistor or, optionally, an external standard resistor. The ULCA's transfer coefficient is highly stable versus time, temperature, and current amplitude within the full dynamic range of ±5 nA. The low noise level of 2.4 fA/√Hz helps to keep averaging times short at small input currents. A cryogenic current comparator is used to calibrate both input current gain and output transresistance, providing traceability to the quantum Hall effect. Within one week after calibration, the uncertainty contribution from short-term fluctuations and drift of the transresistance is about 0.1 parts per million (ppm). The long-term drift is typically 5 ppm/yr. A high-accuracy variant is available that shows improved stability of the input gain at the expense of a higher noise level of 7.5 fA/√Hz. The ULCA also allows the traceable generation of small electric currents or the calibration of high-ohmic resistors.

A 16 channel discriminator VME board with enhanced triggering capabilities

NASA Astrophysics Data System (ADS)

Borsato, E.; Garfagnini, A.; Menon, G.

2012-08-01

Electronics and data acquisition systems used in small and large scale laboratories often have to handle analog signals with varying polarity, amplitude and duration which have to be digitized to be used as trigger signals to validate the acquired data. In the specific case of experiments dealing with ionizing radiation, ancillary particle detectors (for instance plastic scintillators or Resistive Plate Chambers) are used to trigger and select the impinging particles for the experiment. A novel approach using commercial LVDS line receivers as discriminator devices is presented. Such devices, with a proper calibration, can handle positive and negative analog signals in a wide dynamic range (from 20 mV to 800 mV signal amplitude). The clear advantages, with respect to conventional discriminator devices, are reduced costs, high reliability of a mature technology and the possibility of high integration scale. Moreover, commercial discriminator boards with positive input signal and a wide threshold swing are not available on the market. The present paper describes the design and characterization of a VME board capable to handle 16 differential or single-ended input channels. The output digital signals, available independently for each input, can be combined in the board into three independent trigger logic units which provide additional outputs for the end user.

Physiological gain leads to high ISI variability in a simple model of a cortical regular spiking cell.

PubMed

Troyer, T W; Miller, K D

1997-07-01

To understand the interspike interval (ISI) variability displayed by visual cortical neurons (Softky & Koch, 1993), it is critical to examine the dynamics of their neuronal integration, as well as the variability in their synaptic input current. Most previous models have focused on the latter factor. We match a simple integrate-and-fire model to the experimentally measured integrative properties of cortical regular spiking cells (McCormick, Connors, Lighthall, & Prince, 1985). After setting RC parameters, the post-spike voltage reset is set to match experimental measurements of neuronal gain (obtained from in vitro plots of firing frequency versus injected current). Examination of the resulting model leads to an intuitive picture of neuronal integration that unifies the seemingly contradictory 1/square root of N and random walk pictures that have previously been proposed. When ISIs are dominated by postspike recovery, 1/square root of N arguments hold and spiking is regular; after the "memory" of the last spike becomes negligible, spike threshold crossing is caused by input variance around a steady state and spiking is Poisson. In integrate-and-fire neurons matched to cortical cell physiology, steady-state behavior is predominant, and ISIs are highly variable at all physiological firing rates and for a wide range of inhibitory and excitatory inputs.

The effects of variable sample biomass on comparative metagenomics.

PubMed

Chafee, Meghan; Maignien, Loïs; Simmons, Sheri L

2015-07-01

Longitudinal studies that integrate samples with variable biomass are essential to understand microbial community dynamics across space or time. Shotgun metagenomics is widely used to investigate these communities at the functional level, but little is known about the effects of combining low and high biomass samples on downstream analysis. We investigated the interacting effects of DNA input and library amplification by polymerase chain reaction on comparative metagenomic analysis using dilutions of a single complex template from an Arabidopsis thaliana-associated microbial community. We modified the Illumina Nextera kit to generate high-quality large-insert (680 bp) paired-end libraries using a range of 50 pg to 50 ng of input DNA. Using assembly-based metagenomic analysis, we demonstrate that DNA input level has a significant impact on community structure due to overrepresentation of low-GC genomic regions following library amplification. In our system, these differences were largely superseded by variations between biological replicates, but our results advocate verifying the influence of library amplification on a case-by-case basis. Overall, this study provides recommendations for quality filtering and de-replication prior to analysis, as well as a practical framework to address the issue of low biomass or biomass heterogeneity in longitudinal metagenomic surveys. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Bounding the errors for convex dynamics on one or more polytopes.

PubMed

Tresser, Charles

2007-09-01

We discuss the greedy algorithm for approximating a sequence of inputs in a family of polytopes lying in affine spaces by an output sequence made of vertices of the respective polytopes. More precisely, we consider here the case when the greed of the algorithm is dictated by the Euclidean norms of the successive cumulative errors. This algorithm can be interpreted as a time-dependent dynamical system in the vector space, where the errors live, or as a time-dependent dynamical system in an affine space containing copies of all the original polytopes. This affine space contains the inputs, as well as the inputs modified by adding the respective former errors; it is the evolution of these modified inputs that the dynamical system in affine space describes. Scheduling problems with many polytopes arise naturally, for instance, when the inputs are from a single polytope P, but one imposes the constraint that whenever the input belongs to a codimension n face, the output has to be in the same codimension n face (as when scheduling drivers among participants of a carpool). It has been previously shown that the error is bounded in the case of a single polytope by proving the existence of an arbitrary large convex invariant region for the dynamics in affine space: A region that is simultaneously invariant for several polytopes, each considered separately, was also constructed. It was then shown that there cannot be an invariant region in affine space in the general case of a family of polytopes. Here we prove the existence of an arbitrary large convex invariant set for the dynamics in the vector space in the case when the sizes of the polytopes in the family are bounded and the set of all the outgoing normals to all the faces of all the polytopes is finite. It was also previously known that starting from zero as the initial error set, the error set could not be saturated in finitely many steps in some cases with several polytopes: Contradicting a former conjecture, we show that the same happens for some single quadrilaterals and for a single pentagon with an axial symmetry. The disproof of that conjecture is the new piece of information that leads us to expect, and then to verify, as we recount here, that the proof that the errors are bounded in the general case could be a small step beyond the proof of the same statement for the single polytope case.

Bounding the errors for convex dynamics on one or more polytopes

NASA Astrophysics Data System (ADS)

Tresser, Charles

2007-09-01

We discuss the greedy algorithm for approximating a sequence of inputs in a family of polytopes lying in affine spaces by an output sequence made of vertices of the respective polytopes. More precisely, we consider here the case when the greed of the algorithm is dictated by the Euclidean norms of the successive cumulative errors. This algorithm can be interpreted as a time-dependent dynamical system in the vector space, where the errors live, or as a time-dependent dynamical system in an affine space containing copies of all the original polytopes. This affine space contains the inputs, as well as the inputs modified by adding the respective former errors; it is the evolution of these modified inputs that the dynamical system in affine space describes. Scheduling problems with many polytopes arise naturally, for instance, when the inputs are from a single polytope P, but one imposes the constraint that whenever the input belongs to a codimension n face, the output has to be in the same codimension n face (as when scheduling drivers among participants of a carpool). It has been previously shown that the error is bounded in the case of a single polytope by proving the existence of an arbitrary large convex invariant region for the dynamics in affine space: A region that is simultaneously invariant for several polytopes, each considered separately, was also constructed. It was then shown that there cannot be an invariant region in affine space in the general case of a family of polytopes. Here we prove the existence of an arbitrary large convex invariant set for the dynamics in the vector space in the case when the sizes of the polytopes in the family are bounded and the set of all the outgoing normals to all the faces of all the polytopes is finite. It was also previously known that starting from zero as the initial error set, the error set could not be saturated in finitely many steps in some cases with several polytopes: Contradicting a former conjecture, we show that the same happens for some single quadrilaterals and for a single pentagon with an axial symmetry. The disproof of that conjecture is the new piece of information that leads us to expect, and then to verify, as we recount here, that the proof that the errors are bounded in the general case could be a small step beyond the proof of the same statement for the single polytope case.

Parallel sort with a ranged, partitioned key-value store in a high perfomance computing environment

DOEpatents

Bent, John M.; Faibish, Sorin; Grider, Gary; Torres, Aaron; Poole, Stephen W.

2016-01-26

Improved sorting techniques are provided that perform a parallel sort using a ranged, partitioned key-value store in a high performance computing (HPC) environment. A plurality of input data files comprising unsorted key-value data in a partitioned key-value store are sorted. The partitioned key-value store comprises a range server for each of a plurality of ranges. Each input data file has an associated reader thread. Each reader thread reads the unsorted key-value data in the corresponding input data file and performs a local sort of the unsorted key-value data to generate sorted key-value data. A plurality of sorted, ranged subsets of each of the sorted key-value data are generated based on the plurality of ranges. Each sorted, ranged subset corresponds to a given one of the ranges and is provided to one of the range servers corresponding to the range of the sorted, ranged subset. Each range server sorts the received sorted, ranged subsets and provides a sorted range. A plurality of the sorted ranges are concatenated to obtain a globally sorted result.

Reduced order modeling and active flow control of an inlet duct

NASA Astrophysics Data System (ADS)

Ge, Xiaoqing

Many aerodynamic applications require the modeling of compressible flows in or around a body, e.g., the design of aircraft, inlet or exhaust duct, wind turbines, or tall buildings. Traditional methods use wind tunnel experiments and computational fluid dynamics (CFD) to investigate the spatial and temporal distribution of the flows. Although they provide a great deal of insight into the essential characteristics of the flow field, they are not suitable for control analysis and design due to the high physical/computational cost. Many model reduction methods have been studied to reduce the complexity of the flow model. There are two main approaches: linearization based input/output modeling and proper orthogonal decomposition (POD) based model reduction. The former captures mostly the local behavior near a steady state, which is suitable to model laminar flow dynamics. The latter obtains a reduced order model by projecting the governing equation onto an "optimal" subspace and is able to model complex nonlinear flow phenomena. In this research we investigate various model reduction approaches and compare them in flow modeling and control design. We propose an integrated model-based control methodology and apply it to the reduced order modeling and active flow control of compressible flows within a very aggressive (length to exit diameter ratio, L/D, of 1.5) inlet duct and its upstream contraction section. The approach systematically applies reduced order modeling, estimator design, sensor placement and control design to improve the aerodynamic performance. The main contribution of this work is the development of a hybrid model reduction approach that attempts to combine the best features of input/output model identification and POD method. We first identify a linear input/output model by using a subspace algorithm. We next project the difference between CFD response and the identified model response onto a set of POD basis. This trajectory is fit to a nonlinear dynamical model to augment the linear input/output model. Thus, the full system is decomposed into a dominant linear subsystem and a low order nonlinear subsystem. The hybrid model is then used for control design and compared with other modeling methods in CFD simulations. Numerical results indicate that the hybrid model accurately predicts the nonlinear behavior of the flow for a 2D diffuser contraction section model. It also performs best in terms of feedback control design and learning control. Since some outputs of interest (e.g., the AIP pressure recovery) are not observable during normal operations, static and dynamic estimators are designed to recreate the information from available sensor measurements. The latter also provides a state estimation for feedback controller. Based on the reduced order models and estimators, different controllers are designed to improve the aerodynamic performance of the contraction section and inlet duct. The integrated control methodology is evaluated with CFD simulations. Numerical results demonstrate the feasibility and efficacy of the active flow control based on reduced order models. Our reduced order models not only generate a good approximation of the nonlinear flow dynamics over a wide input range, but also help to design controllers that significantly improve the flow response. The tools developed for model reduction, estimator and control design can also be applied to wind tunnel experiment.

Pandemic recovery analysis using the dynamic inoperability input-output model.

PubMed

Santos, Joost R; Orsi, Mark J; Bond, Erik J

2009-12-01

Economists have long conceptualized and modeled the inherent interdependent relationships among different sectors of the economy. This concept paved the way for input-output modeling, a methodology that accounts for sector interdependencies governing the magnitude and extent of ripple effects due to changes in the economic structure of a region or nation. Recent extensions to input-output modeling have enhanced the model's capabilities to account for the impact of an economic perturbation; two such examples are the inoperability input-output model((1,2)) and the dynamic inoperability input-output model (DIIM).((3)) These models introduced sector inoperability, or the inability to satisfy as-planned production levels, into input-output modeling. While these models provide insights for understanding the impacts of inoperability, there are several aspects of the current formulation that do not account for complexities associated with certain disasters, such as a pandemic. This article proposes further enhancements to the DIIM to account for economic productivity losses resulting primarily from workforce disruptions. A pandemic is a unique disaster because the majority of its direct impacts are workforce related. The article develops a modeling framework to account for workforce inoperability and recovery factors. The proposed workforce-explicit enhancements to the DIIM are demonstrated in a case study to simulate a pandemic scenario in the Commonwealth of Virginia.

Extending the dynamic range of transcription factor action by translational regulation

NASA Astrophysics Data System (ADS)

Sokolowski, Thomas R.; Walczak, Aleksandra M.; Bialek, William; Tkačik, Gašper

2016-02-01

A crucial step in the regulation of gene expression is binding of transcription factor (TF) proteins to regulatory sites along the DNA. But transcription factors act at nanomolar concentrations, and noise due to random arrival of these molecules at their binding sites can severely limit the precision of regulation. Recent work on the optimization of information flow through regulatory networks indicates that the lower end of the dynamic range of concentrations is simply inaccessible, overwhelmed by the impact of this noise. Motivated by the behavior of homeodomain proteins, such as the maternal morphogen Bicoid in the fruit fly embryo, we suggest a scheme in which transcription factors also act as indirect translational regulators, binding to the mRNA of other regulatory proteins. Intuitively, each mRNA molecule acts as an independent sensor of the input concentration, and averaging over these multiple sensors reduces the noise. We analyze information flow through this scheme and identify conditions under which it outperforms direct transcriptional regulation. Our results suggest that the dual role of homeodomain proteins is not just a historical accident, but a solution to a crucial physics problem in the regulation of gene expression.

Effect of strain rate and temperature on mechanical properties of selected building Polish steels

NASA Astrophysics Data System (ADS)

Moćko, Wojciech; Kruszka, Leopold

2015-09-01

Currently, the computer programs of CAD type are basic tool for designing of various structures under impact loading. Application of the numerical calculations allows to substantially reduce amount of time required for the design stage of such projects. However, the proper use of computer aided designing technique requires input data for numerical software including elastic-plastic models of structural materials. This work deals with the constitutive model developed by Rusinek and Klepaczko (RK) applied for the modelling of mechanical behaviour of selected grades structural St0S, St3SX, 18GS and 34GS steels and presents here results of experimental and empirical analyses to describe dynamic elastic-plastic behaviours of tested materials at wide range of temperature. In order to calibrate the RK constitutive model, series of compression tests at wide range of strain rates, including static, quasi-static and dynamic investigations at lowered, room and elevated temperatures, were carried out using two testing stands: servo-hydraulic machine and split Hopkinson bar. The results were analysed to determine influence of temperature and strain rate on visco-plastic response of tested steels, and show good correlation with experimental data.

An ultra-small, multi-point, and multi-color photo-detection system with high sensitivity and high dynamic range.

PubMed

Anazawa, Takashi; Yamazaki, Motohiro

2017-12-05

Although multi-point, multi-color fluorescence-detection systems are widely used in various sciences, they would find wider applications if they are miniaturized. Accordingly, an ultra-small, four-emission-point and four-color fluorescence-detection system was developed. Its size (space between emission points and a detection plane) is 15 × 10 × 12 mm, which is three-orders-of-magnitude smaller than that of a conventional system. Fluorescence from four emission points with an interval of 1 mm on the same plane was respectively collimated by four lenses and split into four color fluxes by four dichroic mirrors. Then, a total of sixteen parallel color fluxes were directly input into an image sensor and simultaneously detected. The emission-point plane and the detection plane (the image-sensor surface) were parallel and separated by a distance of only 12 mm. The developed system was applied to four-capillary array electrophoresis and successfully achieved Sanger DNA sequencing. Moreover, compared with a conventional system, the developed system had equivalent high fluorescence-detection sensitivity (lower detection limit of 17 pM dROX) and 1.6-orders-of-magnitude higher dynamic range (4.3 orders of magnitude).

Effects of initial-state dynamics on collective flow within a coupled transport and viscous hydrodynamic approach

NASA Astrophysics Data System (ADS)

Chattopadhyay, Chandrodoy; Bhalerao, Rajeev S.; Ollitrault, Jean-Yves; Pal, Subrata

2018-03-01

We evaluate the effects of preequilibrium dynamics on observables in ultrarelativistic heavy-ion collisions. We simulate the initial nonequilibrium phase within a multiphase transport (AMPT) model, while the subsequent near-equilibrium evolution is modeled using (2+1)-dimensional relativistic viscous hydrodynamics. We match the two stages of evolution carefully by calculating the full energy-momentum tensor from AMPT and using it as input for the hydrodynamic evolution. We find that when the preequilibrium evolution is taken into account, final-state observables are insensitive to the switching time from AMPT to hydrodynamics. Unlike some earlier treatments of preequilibrium dynamics, we do not find the initial shear viscous tensor to be large. With a shear viscosity to entropy density ratio of 0.12, our model describes quantitatively a large set of experimental data on Pb+Pb collisions at the Large Hadron Collider over a wide range of centrality: differential anisotropic flow vn(pT) (n =2 -6 ) , event-plane correlations, correlation between v2 and v3, and cumulant ratio v2{4 } /v2{2 } .

Simulations of High Speed Fragment Trajectories

NASA Astrophysics Data System (ADS)

Yeh, Peter; Attaway, Stephen; Arunajatesan, Srinivasan; Fisher, Travis

2017-11-01

Flying shrapnel from an explosion are capable of traveling at supersonic speeds and distances much farther than expected due to aerodynamic interactions. Predicting the trajectories and stable tumbling modes of arbitrary shaped fragments is a fundamental problem applicable to range safety calculations, damage assessment, and military technology. Traditional approaches rely on characterizing fragment flight using a single drag coefficient, which may be inaccurate for fragments with large aspect ratios. In our work we develop a procedure to simulate trajectories of arbitrary shaped fragments with higher fidelity using high performance computing. We employ a two-step approach in which the force and moment coefficients are first computed as a function of orientation using compressible computational fluid dynamics. The force and moment data are then input into a six-degree-of-freedom rigid body dynamics solver to integrate trajectories in time. Results of these high fidelity simulations allow us to further understand the flight dynamics and tumbling modes of a single fragment. Furthermore, we use these results to determine the validity and uncertainty of inexpensive methods such as the single drag coefficient model.

Nonlinear optimal control for the synchronization of chaotic and hyperchaotic finance systems

NASA Astrophysics Data System (ADS)

Rigatos, G.; Siano, P.; Loia, V.; Ademi, S.; Ghosh, T.

2017-11-01

It is possible to make specific finance systems get synchronized to other finance systems exhibiting chaotic and hyperchaotic dynamics, by applying nonlinear optimal (H-infinity) control. This signifies that chaotic behavior can be generated in finance systems by exerting a suitable control input. Actually, a lead financial system is considered which exhibits inherently chaotic dynamics. Moreover, a follower finance system is introduced having parameters in its model that inherently prohibit the appearance of chaotic dynamics. Through the application of a suitable nonlinear optimal (H-infinity) control input it is proven that the follower finance system can replicate the chaotic dynamics of the lead finance system. By applying Lyapunov analysis it is proven that asymptotically the follower finance system gets synchronized with the lead system and that the tracking error between the state variables of the two systems vanishes.