Computing Functions by Approximating the Input

ERIC Educational Resources Information Center

Goldberg, Mayer

2012-01-01

In computing real-valued functions, it is ordinarily assumed that the input to the function is known, and it is the output that we need to approximate. In this work, we take the opposite approach: we show how to compute the values of some transcendental functions by approximating the input to these functions, and obtaining exact answers for their…

Transforming the Way We Teach Function Transformations

ERIC Educational Resources Information Center

Faulkenberry, Eileen Durand; Faulkenberry, Thomas J.

2010-01-01

In this article, the authors discuss "function," a well-defined rule that relates inputs to outputs. They have found that by using the input-output definition of "function," they can examine transformations of functions simply by looking at changes to input or output and the respective changes to the graph. Applying transformations to the input…

Optimal inverse functions created via population-based optimization.

PubMed

Jennings, Alan L; Ordóñez, Raúl

2014-06-01

Finding optimal inputs for a multiple-input, single-output system is taxing for a system operator. Population-based optimization is used to create sets of functions that produce a locally optimal input based on a desired output. An operator or higher level planner could use one of the functions in real time. For the optimization, each agent in the population uses the cost and output gradients to take steps lowering the cost while maintaining their current output. When an agent reaches an optimal input for its current output, additional agents are generated in the output gradient directions. The new agents then settle to the local optima for the new output values. The set of associated optimal points forms an inverse function, via spline interpolation, from a desired output to an optimal input. In this manner, multiple locally optimal functions can be created. These functions are naturally clustered in input and output spaces allowing for a continuous inverse function. The operator selects the best cluster over the anticipated range of desired outputs and adjusts the set point (desired output) while maintaining optimality. This reduces the demand from controlling multiple inputs, to controlling a single set point with no loss in performance. Results are demonstrated on a sample set of functions and on a robot control problem.

Speech versus manual control of camera functions during a telerobotic task

NASA Technical Reports Server (NTRS)

Bierschwale, John M.; Sampaio, Carlos E.; Stuart, Mark A.; Smith, Randy L.

1989-01-01

Voice input for control of camera functions was investigated in this study. Objective were to (1) assess the feasibility of a voice-commanded camera control system, and (2) identify factors that differ between voice and manual control of camera functions. Subjects participated in a remote manipulation task that required extensive camera-aided viewing. Each subject was exposed to two conditions, voice and manual input, with a counterbalanced administration order. Voice input was found to be significantly slower than manual input for this task. However, in terms of remote manipulator performance errors and subject preference, there was no difference between modalities. Voice control of continuous camera functions is not recommended. It is believed that the use of voice input for discrete functions, such as multiplexing or camera switching, could aid performance. Hybrid mixes of voice and manual input may provide the best use of both modalities. This report contributes to a better understanding of the issues that affect the design of an efficient human/telerobot interface.

Noninvasive quantification of cerebral metabolic rate for glucose in rats using 18F-FDG PET and standard input function

PubMed Central

Hori, Yuki; Ihara, Naoki; Teramoto, Noboru; Kunimi, Masako; Honda, Manabu; Kato, Koichi; Hanakawa, Takashi

2015-01-01

Measurement of arterial input function (AIF) for quantitative positron emission tomography (PET) studies is technically challenging. The present study aimed to develop a method based on a standard arterial input function (SIF) to estimate input function without blood sampling. We performed 18F-fluolodeoxyglucose studies accompanied by continuous blood sampling for measurement of AIF in 11 rats. Standard arterial input function was calculated by averaging AIFs from eight anesthetized rats, after normalization with body mass (BM) and injected dose (ID). Then, the individual input function was estimated using two types of SIF: (1) SIF calibrated by the individual's BM and ID (estimated individual input function, EIFNS) and (2) SIF calibrated by a single blood sampling as proposed previously (EIF1S). No significant differences in area under the curve (AUC) or cerebral metabolic rate for glucose (CMRGlc) were found across the AIF-, EIFNS-, and EIF1S-based methods using repeated measures analysis of variance. In the correlation analysis, AUC or CMRGlc derived from EIFNS was highly correlated with those derived from AIF and EIF1S. Preliminary comparison between AIF and EIFNS in three awake rats supported an idea that the method might be applicable to behaving animals. The present study suggests that EIFNS method might serve as a noninvasive substitute for individual AIF measurement. PMID:25966947

Noninvasive quantification of cerebral metabolic rate for glucose in rats using (18)F-FDG PET and standard input function.

PubMed

Hori, Yuki; Ihara, Naoki; Teramoto, Noboru; Kunimi, Masako; Honda, Manabu; Kato, Koichi; Hanakawa, Takashi

2015-10-01

Measurement of arterial input function (AIF) for quantitative positron emission tomography (PET) studies is technically challenging. The present study aimed to develop a method based on a standard arterial input function (SIF) to estimate input function without blood sampling. We performed (18)F-fluolodeoxyglucose studies accompanied by continuous blood sampling for measurement of AIF in 11 rats. Standard arterial input function was calculated by averaging AIFs from eight anesthetized rats, after normalization with body mass (BM) and injected dose (ID). Then, the individual input function was estimated using two types of SIF: (1) SIF calibrated by the individual's BM and ID (estimated individual input function, EIF(NS)) and (2) SIF calibrated by a single blood sampling as proposed previously (EIF(1S)). No significant differences in area under the curve (AUC) or cerebral metabolic rate for glucose (CMRGlc) were found across the AIF-, EIF(NS)-, and EIF(1S)-based methods using repeated measures analysis of variance. In the correlation analysis, AUC or CMRGlc derived from EIF(NS) was highly correlated with those derived from AIF and EIF(1S). Preliminary comparison between AIF and EIF(NS) in three awake rats supported an idea that the method might be applicable to behaving animals. The present study suggests that EIF(NS) method might serve as a noninvasive substitute for individual AIF measurement.

Fuzzy Neuron: Method and Hardware Realization

NASA Technical Reports Server (NTRS)

Krasowski, Michael J.; Prokop, Norman F.

2014-01-01

This innovation represents a method by which single-to-multi-input, single-to-many-output system transfer functions can be estimated from input/output data sets. This innovation can be run in the background while a system is operating under other means (e.g., through human operator effort), or may be utilized offline using data sets created from observations of the estimated system. It utilizes a set of fuzzy membership functions spanning the input space for each input variable. Linear combiners associated with combinations of input membership functions are used to create the output(s) of the estimator. Coefficients are adjusted online through the use of learning algorithms.

Layer-specific input to distinct cell types in layer 6 of monkey primary visual cortex.

PubMed

Briggs, F; Callaway, E M

2001-05-15

Layer 6 of monkey V1 contains a physiologically and anatomically diverse population of excitatory pyramidal neurons. Distinctive arborization patterns of axons and dendrites within the functionally specialized cortical layers define eight types of layer 6 pyramidal neurons and suggest unique information processing roles for each cell type. To address how input sources contribute to cellular function, we examined the laminar sources of functional excitatory input onto individual layer 6 pyramidal neurons using scanning laser photostimulation. We find that excitatory input sources correlate with cell type. Class I neurons with axonal arbors selectively targeting magnocellular (M) recipient layer 4Calpha receive input from M-dominated layer 4B, whereas class I neurons whose axonal arbors target parvocellular (P) recipient layer 4Cbeta receive input from P-dominated layer 2/3. Surprisingly, these neuronal types do not differ significantly in the inputs they receive directly from layers 4Calpha or 4Cbeta. Class II cells, which lack dense axonal arbors within layer 4C, receive excitatory input from layers targeted by their local axons. Specifically, type IIA cells project axons to and receive input from the deep but not superficial layers. Type IIB neurons project to and receive input from the deepest and most superficial, but not middle layers. Type IIC neurons arborize throughout the cortical layers and tend to receive inputs from all cortical layers. These observations have implications for the functional roles of different layer 6 cell types in visual information processing.

Analysis and selection of optimal function implementations in massively parallel computer

DOEpatents

Archer, Charles Jens [Rochester, MN; Peters, Amanda [Rochester, MN; Ratterman, Joseph D [Rochester, MN

2011-05-31

An apparatus, program product and method optimize the operation of a parallel computer system by, in part, collecting performance data for a set of implementations of a function capable of being executed on the parallel computer system based upon the execution of the set of implementations under varying input parameters in a plurality of input dimensions. The collected performance data may be used to generate selection program code that is configured to call selected implementations of the function in response to a call to the function under varying input parameters. The collected performance data may be used to perform more detailed analysis to ascertain the comparative performance of the set of implementations of the function under the varying input parameters.

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.

Variance-based interaction index measuring heteroscedasticity

NASA Astrophysics Data System (ADS)

Ito, Keiichi; Couckuyt, Ivo; Poles, Silvia; Dhaene, Tom

2016-06-01

This work is motivated by the need to deal with models with high-dimensional input spaces of real variables. One way to tackle high-dimensional problems is to identify interaction or non-interaction among input parameters. We propose a new variance-based sensitivity interaction index that can detect and quantify interactions among the input variables of mathematical functions and computer simulations. The computation is very similar to first-order sensitivity indices by Sobol'. The proposed interaction index can quantify the relative importance of input variables in interaction. Furthermore, detection of non-interaction for screening can be done with as low as 4 n + 2 function evaluations, where n is the number of input variables. Using the interaction indices based on heteroscedasticity, the original function may be decomposed into a set of lower dimensional functions which may then be analyzed separately.

Genetic algorithm based input selection for a neural network function approximator with applications to SSME health monitoring

NASA Technical Reports Server (NTRS)

Peck, Charles C.; Dhawan, Atam P.; Meyer, Claudia M.

1991-01-01

A genetic algorithm is used to select the inputs to a neural network function approximator. In the application considered, modeling critical parameters of the space shuttle main engine (SSME), the functional relationship between measured parameters is unknown and complex. Furthermore, the number of possible input parameters is quite large. Many approaches have been used for input selection, but they are either subjective or do not consider the complex multivariate relationships between parameters. Due to the optimization and space searching capabilities of genetic algorithms they were employed to systematize the input selection process. The results suggest that the genetic algorithm can generate parameter lists of high quality without the explicit use of problem domain knowledge. Suggestions for improving the performance of the input selection process are also provided.

Compact universal logic gates realized using quantization of current in nanodevices.

PubMed

Zhang, Wancheng; Wu, Nan-Jian; Yang, Fuhua

2007-12-12

This paper proposes novel universal logic gates using the current quantization characteristics of nanodevices. In nanodevices like the electron waveguide (EW) and single-electron (SE) turnstile, the channel current is a staircase quantized function of its control voltage. We use this unique characteristic to compactly realize Boolean functions. First we present the concept of the periodic-threshold threshold logic gate (PTTG), and we build a compact PTTG using EW and SE turnstiles. We show that an arbitrary three-input Boolean function can be realized with a single PTTG, and an arbitrary four-input Boolean function can be realized by using two PTTGs. We then use one PTTG to build a universal programmable two-input logic gate which can be used to realize all two-input Boolean functions. We also build a programmable three-input logic gate by using one PTTG. Compared with linear threshold logic gates, with the PTTG one can build digital circuits more compactly. The proposed PTTGs are promising for future smart nanoscale digital system use.

Differential inputs to striatal cholinergic and parvalbumin interneurons imply functional distinctions

PubMed Central

Klug, Jason R; Engelhardt, Max D; Cadman, Cara N; Li, Hao; Smith, Jared B; Ayala, Sarah; Williams, Elora W; Hoffman, Hilary

2018-01-01

Striatal cholinergic (ChAT) and parvalbumin (PV) interneurons exert powerful influences on striatal function in health and disease, yet little is known about the organization of their inputs. Here using rabies tracing, electrophysiology and genetic tools, we compare the whole-brain inputs to these two types of striatal interneurons and dissect their functional connectivity in mice. ChAT interneurons receive a substantial cortical input from associative regions of cortex, such as the orbitofrontal cortex. Amongst subcortical inputs, a previously unknown inhibitory thalamic reticular nucleus input to striatal PV interneurons is identified. Additionally, the external segment of the globus pallidus targets striatal ChAT interneurons, which is sufficient to inhibit tonic ChAT interneuron firing. Finally, we describe a novel excitatory pathway from the pedunculopontine nucleus that innervates ChAT interneurons. These results establish the brain-wide direct inputs of two major types of striatal interneurons and allude to distinct roles in regulating striatal activity and controlling behavior. PMID:29714166

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.

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.

Transfer Function Control for Biometric Monitoring System

NASA Technical Reports Server (NTRS)

Chmiel, Alan J. (Inventor); Grodinsky, Carlos M. (Inventor); Humphreys, Bradley T. (Inventor)

2015-01-01

A modular apparatus for acquiring biometric data may include circuitry operative to receive an input signal indicative of a biometric condition, the circuitry being configured to process the input signal according to a transfer function thereof and to provide a corresponding processed input signal. A controller is configured to provide at least one control signal to the circuitry to programmatically modify the transfer function of the modular system to facilitate acquisition of the biometric data.

Gaussian-input Gaussian mixture model for representing density maps and atomic models.

PubMed

Kawabata, Takeshi

2018-07-01

A new Gaussian mixture model (GMM) has been developed for better representations of both atomic models and electron microscopy 3D density maps. The standard GMM algorithm employs an EM algorithm to determine the parameters. It accepted a set of 3D points with weights, corresponding to voxel or atomic centers. Although the standard algorithm worked reasonably well; however, it had three problems. First, it ignored the size (voxel width or atomic radius) of the input, and thus it could lead to a GMM with a smaller spread than the input. Second, the algorithm had a singularity problem, as it sometimes stopped the iterative procedure due to a Gaussian function with almost zero variance. Third, a map with a large number of voxels required a long computation time for conversion to a GMM. To solve these problems, we have introduced a Gaussian-input GMM algorithm, which considers the input atoms or voxels as a set of Gaussian functions. The standard EM algorithm of GMM was extended to optimize the new GMM. The new GMM has identical radius of gyration to the input, and does not suddenly stop due to the singularity problem. For fast computation, we have introduced a down-sampled Gaussian functions (DSG) by merging neighboring voxels into an anisotropic Gaussian function. It provides a GMM with thousands of Gaussian functions in a short computation time. We also have introduced a DSG-input GMM: the Gaussian-input GMM with the DSG as the input. This new algorithm is much faster than the standard algorithm. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Existence conditions for unknown input functional observers

NASA Astrophysics Data System (ADS)

Fernando, T.; MacDougall, S.; Sreeram, V.; Trinh, H.

2013-01-01

This article presents necessary and sufficient conditions for the existence and design of an unknown input Functional observer. The existence of the observer can be verified by computing a nullspace of a known matrix and testing some matrix rank conditions. The existence of the observer does not require the satisfaction of the observer matching condition (i.e. Equation (16) in Hou and Muller 1992, 'Design of Observers for Linear Systems with Unknown Inputs', IEEE Transactions on Automatic Control, 37, 871-875), is not limited to estimating scalar functionals and allows for arbitrary pole placement. The proposed observer always exists when a state observer exists for the unknown input system, and furthermore, the proposed observer can exist even in some instances when an unknown input state observer does not exist.

INFANT HEALTH PRODUCTION FUNCTIONS: WHAT A DIFFERENCE THE DATA MAKE

PubMed Central

Reichman, Nancy E.; Corman, Hope; Noonan, Kelly; Dave, Dhaval

2008-01-01

SUMMARY We examine the extent to which infant health production functions are sensitive to model specification and measurement error. We focus on the importance of typically unobserved but theoretically important variables (typically unobserved variables, TUVs), other non-standard covariates (NSCs), input reporting, and characterization of infant health. The TUVs represent wantedness, taste for risky behavior, and maternal health endowment. The NSCs include father characteristics. We estimate the effects of prenatal drug use, prenatal cigarette smoking, and First trimester prenatal care on birth weight, low birth weight, and a measure of abnormal infant health conditions. We compare estimates using self-reported inputs versus input measures that combine information from medical records and self-reports. We find that TUVs and NSCs are significantly associated with both inputs and outcomes, but that excluding them from infant health production functions does not appreciably affect the input estimates. However, using self-reported inputs leads to overestimated effects of inputs, particularly prenatal care, on outcomes, and using a direct measure of infant health does not always yield input estimates similar to those when using birth weight outcomes. The findings have implications for research, data collection, and public health policy. PMID:18792077

Factor analysis for delineation of organ structures, creation of in- and output functions, and standardization of multicenter kinetic modeling

NASA Astrophysics Data System (ADS)

Schiepers, Christiaan; Hoh, Carl K.; Dahlbom, Magnus; Wu, Hsiao-Ming; Phelps, Michael E.

1999-05-01

PET imaging can quantify metabolic processes in-vivo; this requires the measurement of an input function which is invasive and labor intensive. A non-invasive, semi-automated, image based method of input function generation would be efficient, patient friendly, and allow quantitative PET to be applied routinely. A fully automated procedure would be ideal for studies across institutions. Factor analysis (FA) was applied as processing tool for definition of temporally changing structures in the field of view. FA has been proposed earlier, but the perceived mathematical difficulty has prevented widespread use. FA was utilized to delineate structures and extract blood and tissue time-activity-curves (TACs). These TACs were used as input and output functions for tracer kinetic modeling, the results of which were compared with those from an input function obtained with serial blood sampling. Dynamic image data of myocardial perfusion studies with N-13 ammonia, O-15 water, or Rb-82, cancer studies with F-18 FDG, and skeletal studies with F-18 fluoride were evaluated. Correlation coefficients of kinetic parameters obtained with factor and plasma input functions were high. Linear regression usually furnished a slope near unity. Processing time was 7 min/patient on an UltraSPARC. Conclusion: FA can non-invasively generate input functions from image data eliminating the need for blood sampling. Output (tissue) functions can be simultaneously generated. The method is simple, requires no sophisticated operator interaction and has little inter-operator variability. FA is well suited for studies across institutions and standardized evaluations.

Significance of Input Correlations in Striatal Function

PubMed Central

Yim, Man Yi; Aertsen, Ad; Kumar, Arvind

2011-01-01

The striatum is the main input station of the basal ganglia and is strongly associated with motor and cognitive functions. Anatomical evidence suggests that individual striatal neurons are unlikely to share their inputs from the cortex. Using a biologically realistic large-scale network model of striatum and cortico-striatal projections, we provide a functional interpretation of the special anatomical structure of these projections. Specifically, we show that weak pairwise correlation within the pool of inputs to individual striatal neurons enhances the saliency of signal representation in the striatum. By contrast, correlations among the input pools of different striatal neurons render the signal representation less distinct from background activity. We suggest that for the network architecture of the striatum, there is a preferred cortico-striatal input configuration for optimal signal representation. It is further enhanced by the low-rate asynchronous background activity in striatum, supported by the balance between feedforward and feedback inhibitions in the striatal network. Thus, an appropriate combination of rates and correlations in the striatal input sets the stage for action selection presumably implemented in the basal ganglia. PMID:22125480

Parallel, but Dissociable, Processing in Discrete Corticostriatal Inputs Encodes Skill Learning.

PubMed

Kupferschmidt, David A; Juczewski, Konrad; Cui, Guohong; Johnson, Kari A; Lovinger, David M

2017-10-11

Changes in cortical and striatal function underlie the transition from novel actions to refined motor skills. How discrete, anatomically defined corticostriatal projections function in vivo to encode skill learning remains unclear. Using novel fiber photometry approaches to assess real-time activity of associative inputs from medial prefrontal cortex to dorsomedial striatum and sensorimotor inputs from motor cortex to dorsolateral striatum, we show that associative and sensorimotor inputs co-engage early in action learning and disengage in a dissociable manner as actions are refined. Disengagement of associative, but not sensorimotor, inputs predicts individual differences in subsequent skill learning. Divergent somatic and presynaptic engagement in both projections during early action learning suggests potential learning-related in vivo modulation of presynaptic corticostriatal function. These findings reveal parallel processing within associative and sensorimotor circuits that challenges and refines existing views of corticostriatal function and expose neuronal projection- and compartment-specific activity dynamics that encode and predict action learning. Published by Elsevier Inc.

Aircraft signal definition for flight safety system monitoring system

NASA Technical Reports Server (NTRS)

Gibbs, Michael (Inventor); Omen, Debi Van (Inventor)

2003-01-01

A system and method compares combinations of vehicle variable values against known combinations of potentially dangerous vehicle input signal values. Alarms and error messages are selectively generated based on such comparisons. An aircraft signal definition is provided to enable definition and monitoring of sets of aircraft input signals to customize such signals for different aircraft. The input signals are compared against known combinations of potentially dangerous values by operational software and hardware of a monitoring function. The aircraft signal definition is created using a text editor or custom application. A compiler receives the aircraft signal definition to generate a binary file that comprises the definition of all the input signals used by the monitoring function. The binary file also contains logic that specifies how the inputs are to be interpreted. The file is then loaded into the monitor function, where it is validated and used to continuously monitor the condition of the aircraft.

Genetic inhibition of neurotransmission reveals role of glutamatergic input to dopamine neurons in high-effort behavior.

PubMed

Hutchison, M A; Gu, X; Adrover, M F; Lee, M R; Hnasko, T S; Alvarez, V A; Lu, W

2018-05-01

Midbrain dopamine neurons are crucial for many behavioral and cognitive functions. As the major excitatory input, glutamatergic afferents are important for control of the activity and plasticity of dopamine neurons. However, the role of glutamatergic input as a whole onto dopamine neurons remains unclear. Here we developed a mouse line in which glutamatergic inputs onto dopamine neurons are specifically impaired, and utilized this genetic model to directly test the role of glutamatergic inputs in dopamine-related functions. We found that while motor coordination and reward learning were largely unchanged, these animals showed prominent deficits in effort-related behavioral tasks. These results provide genetic evidence that glutamatergic transmission onto dopaminergic neurons underlies incentive motivation, a willingness to exert high levels of effort to obtain reinforcers, and have important implications for understanding the normal function of the midbrain dopamine system.

A grid spacing control technique for algebraic grid generation methods

NASA Technical Reports Server (NTRS)

Smith, R. E.; Kudlinski, R. A.; Everton, E. L.

1982-01-01

A technique which controls the spacing of grid points in algebraically defined coordinate transformations is described. The technique is based on the generation of control functions which map a uniformly distributed computational grid onto parametric variables defining the physical grid. The control functions are smoothed cubic splines. Sets of control points are input for each coordinate directions to outline the control functions. Smoothed cubic spline functions are then generated to approximate the input data. The technique works best in an interactive graphics environment where control inputs and grid displays are nearly instantaneous. The technique is illustrated with the two-boundary grid generation algorithm.

Joint statistics of strongly correlated neurons via dimensionality reduction

NASA Astrophysics Data System (ADS)

Deniz, Taşkın; Rotter, Stefan

2017-06-01

The relative timing of action potentials in neurons recorded from local cortical networks often shows a non-trivial dependence, which is then quantified by cross-correlation functions. Theoretical models emphasize that such spike train correlations are an inevitable consequence of two neurons being part of the same network and sharing some synaptic input. For non-linear neuron models, however, explicit correlation functions are difficult to compute analytically, and perturbative methods work only for weak shared input. In order to treat strong correlations, we suggest here an alternative non-perturbative method. Specifically, we study the case of two leaky integrate-and-fire neurons with strong shared input. Correlation functions derived from simulated spike trains fit our theoretical predictions very accurately. Using our method, we computed the non-linear correlation transfer as well as correlation functions that are asymmetric due to inhomogeneous intrinsic parameters or unequal input.

Comparing fixed and variable-width Gaussian networks.

PubMed

Kůrková, Věra; Kainen, Paul C

2014-09-01

The role of width of Gaussians in two types of computational models is investigated: Gaussian radial-basis-functions (RBFs) where both widths and centers vary and Gaussian kernel networks which have fixed widths but varying centers. The effect of width on functional equivalence, universal approximation property, and form of norms in reproducing kernel Hilbert spaces (RKHS) is explored. It is proven that if two Gaussian RBF networks have the same input-output functions, then they must have the same numbers of units with the same centers and widths. Further, it is shown that while sets of input-output functions of Gaussian kernel networks with two different widths are disjoint, each such set is large enough to be a universal approximator. Embedding of RKHSs induced by "flatter" Gaussians into RKHSs induced by "sharper" Gaussians is described and growth of the ratios of norms on these spaces with increasing input dimension is estimated. Finally, large sets of argminima of error functionals in sets of input-output functions of Gaussian RBFs are described. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Functional recovery of odor representations in regenerated sensory inputs to the olfactory bulb

PubMed Central

Cheung, Man C.; Jang, Woochan; Schwob, James E.; Wachowiak, Matt

2014-01-01

The olfactory system has a unique capacity for recovery from peripheral damage. After injury to the olfactory epithelium (OE), olfactory sensory neurons (OSNs) regenerate and re-converge on target glomeruli of the olfactory bulb (OB). Thus far, this process has been described anatomically for only a few defined populations of OSNs. Here we characterize this regeneration at a functional level by assessing how odor representations carried by OSN inputs to the OB recover after massive loss and regeneration of the sensory neuron population. We used chronic imaging of mice expressing synaptopHluorin in OSNs to monitor odor representations in the dorsal OB before lesion by the olfactotoxin methyl bromide and after a 12 week recovery period. Methyl bromide eliminated functional inputs to the OB, and these inputs recovered to near-normal levels of response magnitude within 12 weeks. We also found that the functional topography of odor representations recovered after lesion, with odorants evoking OSN input to glomerular foci within the same functional domains as before lesion. At a finer spatial scale, however, we found evidence for mistargeting of regenerated OSN axons onto OB targets, with odorants evoking synaptopHluorin signals in small foci that did not conform to a typical glomerular structure but whose distribution was nonetheless odorant-specific. These results indicate that OSNs have a robust ability to reestablish functional inputs to the OB and that the mechanisms underlying the topography of bulbar reinnervation during development persist in the adult and allow primary sensory representations to be largely restored after massive sensory neuron loss. PMID:24431990

Matrix Methods for Estimating the Coherence Functions from Estimates of the Cross-Spectral Density Matrix

DOE PAGES

Smallwood, D. O.

1996-01-01

It is shown that the usual method for estimating the coherence functions (ordinary, partial, and multiple) for a general multiple-input! multiple-output problem can be expressed as a modified form of Cholesky decomposition of the cross-spectral density matrix of the input and output records. The results can be equivalently obtained using singular value decomposition (SVD) of the cross-spectral density matrix. Using SVD suggests a new form of fractional coherence. The formulation as a SVD problem also suggests a way to order the inputs when a natural physical order of the inputs is absent.

Cryptographic Boolean Functions with Biased Inputs

DTIC Science & Technology

2015-07-31

theory of random graphs developed by Erdős and Rényi [2]. The graph properties in a random graph expressed as such Boolean functions are used by...distributed Bernoulli variates with the parameter p. Since our scope is within the area of cryptography , we initiate an analysis of cryptographic...Boolean functions with biased inputs, which we refer to as µp-Boolean functions, is a common generalization of Boolean functions which stems from the

Synaptic control of the shape of the motoneuron pool input-output function

PubMed Central

Heckman, Charles J.

2017-01-01

Although motoneurons have often been considered to be fairly linear transducers of synaptic input, recent evidence suggests that strong persistent inward currents (PICs) in motoneurons allow neuromodulatory and inhibitory synaptic inputs to induce large nonlinearities in the relation between the level of excitatory input and motor output. To try to estimate the possible extent of this nonlinearity, we developed a pool of model motoneurons designed to replicate the characteristics of motoneuron input-output properties measured in medial gastrocnemius motoneurons in the decerebrate cat with voltage-clamp and current-clamp techniques. We drove the model pool with a range of synaptic inputs consisting of various mixtures of excitation, inhibition, and neuromodulation. We then looked at the relation between excitatory drive and total pool output. Our results revealed that the PICs not only enhance gain but also induce a strong nonlinearity in the relation between the average firing rate of the motoneuron pool and the level of excitatory input. The relation between the total simulated force output and input was somewhat more linear because of higher force outputs in later-recruited units. We also found that the nonlinearity can be increased by increasing neuromodulatory input and/or balanced inhibitory input and minimized by a reciprocal, push-pull pattern of inhibition. We consider the possibility that a flexible input-output function may allow motor output to be tuned to match the widely varying demands of the normal motor repertoire. NEW & NOTEWORTHY Motoneuron activity is generally considered to reflect the level of excitatory drive. However, the activation of voltage-dependent intrinsic conductances can distort the relation between excitatory drive and the total output of a pool of motoneurons. Using a pool of realistic motoneuron models, we show that pool output can be a highly nonlinear function of synaptic input but linearity can be achieved through adjusting the time course of excitatory and inhibitory synaptic inputs. PMID:28053245

Impact Response Characteristics of Polymeric Materials

DTIC Science & Technology

1981-11-01

amplitude-frequency domain. In the language of signal communications an input signal given by some time dependence FAt) is introduced into a " channel ...fixed and not altered by the signal. The channel can be charac- terized by its own function H(t), called the transfer function. This concept can be...rcpresented schematically as follows: Input Signal - [ Channel ] -- Output Signal At) H(t) G(t) In our case the input signal is the impact event, the output

The human motor neuron pools receive a dominant slow‐varying common synaptic input

PubMed Central

Negro, Francesco; Yavuz, Utku Şükrü

2016-01-01

Key points Motor neurons in a pool receive both common and independent synaptic inputs, although the proportion and role of their common synaptic input is debated.Classic correlation techniques between motor unit spike trains do not measure the absolute proportion of common input and have limitations as a result of the non‐linearity of motor neurons.We propose a method that for the first time allows an accurate quantification of the absolute proportion of low frequency common synaptic input (<5 Hz) to motor neurons in humans.We applied the proposed method to three human muscles and determined experimentally that they receive a similar large amount (>60%) of common input, irrespective of their different functional and control properties.These results increase our knowledge about the role of common and independent input to motor neurons in force control. Abstract Motor neurons receive both common and independent synaptic inputs. This observation is classically based on the presence of a significant correlation between pairs of motor unit spike trains. The functional significance of different relative proportions of common input across muscles, individuals and conditions is still debated. One of the limitations in our understanding of correlated input to motor neurons is that it has not been possible so far to quantify the absolute proportion of common input with respect to the total synaptic input received by the motor neurons. Indeed, correlation measures of pairs of output spike trains only allow for relative comparisons. In the present study, we report for the first time an approach for measuring the proportion of common input in the low frequency bandwidth (<5 Hz) to a motor neuron pool in humans. This estimate is based on a phenomenological model and the theoretical fitting of the experimental values of coherence between the permutations of groups of motor unit spike trains. We demonstrate the validity of this theoretical estimate with several simulations. Moreover, we applied this method to three human muscles: the abductor digiti minimi, tibialis anterior and vastus medialis. Despite these muscles having different functional roles and control properties, as confirmed by the results of the present study, we estimate that their motor pools receive a similar and large (>60%) proportion of common low frequency oscillations with respect to their total synaptic input. These results suggest that the central nervous system provides a large amount of common input to motor neuron pools, in a similar way to that for muscles with different functional and control properties. PMID:27151459

Transfer functions for protein signal transduction: application to a model of striatal neural plasticity.

PubMed

Scheler, Gabriele

2013-01-01

We present a novel formulation for biochemical reaction networks in the context of protein signal transduction. The model consists of input-output transfer functions, which are derived from differential equations, using stable equilibria. We select a set of "source" species, which are interpreted as input signals. Signals are transmitted to all other species in the system (the "target" species) with a specific delay and with a specific transmission strength. The delay is computed as the maximal reaction time until a stable equilibrium for the target species is reached, in the context of all other reactions in the system. The transmission strength is the concentration change of the target species. The computed input-output transfer functions can be stored in a matrix, fitted with parameters, and even recalled to build dynamical models on the basis of state changes. By separating the temporal and the magnitudinal domain we can greatly simplify the computational model, circumventing typical problems of complex dynamical systems. The transfer function transformation of biochemical reaction systems can be applied to mass-action kinetic models of signal transduction. The paper shows that this approach yields significant novel insights while remaining a fully testable and executable dynamical model for signal transduction. In particular we can deconstruct the complex system into local transfer functions between individual species. As an example, we examine modularity and signal integration using a published model of striatal neural plasticity. The modularizations that emerge correspond to a known biological distinction between calcium-dependent and cAMP-dependent pathways. Remarkably, we found that overall interconnectedness depends on the magnitude of inputs, with higher connectivity at low input concentrations and significant modularization at moderate to high input concentrations. This general result, which directly follows from the properties of individual transfer functions, contradicts notions of ubiquitous complexity by showing input-dependent signal transmission inactivation.

Using model order tests to determine sensory inputs in a motion study

NASA Technical Reports Server (NTRS)

Repperger, D. W.; Junker, A. M.

1977-01-01

In the study of motion effects on tracking performance, a problem of interest is the determination of what sensory inputs a human uses in controlling his tracking task. In the approach presented here a simple canonical model (FID or a proportional, integral, derivative structure) is used to model the human's input-output time series. A study of significant changes in reduction of the output error loss functional is conducted as different permutations of parameters are considered. Since this canonical model includes parameters which are related to inputs to the human (such as the error signal, its derivatives and integration), the study of model order is equivalent to the study of which sensory inputs are being used by the tracker. The parameters are obtained which have the greatest effect on reducing the loss function significantly. In this manner the identification procedure converts the problem of testing for model order into the problem of determining sensory inputs.

Uncertainty importance analysis using parametric moment ratio functions.

PubMed

Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen

2014-02-01

This article presents a new importance analysis framework, called parametric moment ratio function, for measuring the reduction of model output uncertainty when the distribution parameters of inputs are changed, and the emphasis is put on the mean and variance ratio functions with respect to the variances of model inputs. The proposed concepts efficiently guide the analyst to achieve a targeted reduction on the model output mean and variance by operating on the variances of model inputs. The unbiased and progressive unbiased Monte Carlo estimators are also derived for the parametric mean and variance ratio functions, respectively. Only a set of samples is needed for implementing the proposed importance analysis by the proposed estimators, thus the computational cost is free of input dimensionality. An analytical test example with highly nonlinear behavior is introduced for illustrating the engineering significance of the proposed importance analysis technique and verifying the efficiency and convergence of the derived Monte Carlo estimators. Finally, the moment ratio function is applied to a planar 10-bar structure for achieving a targeted 50% reduction of the model output variance. © 2013 Society for Risk Analysis.

Evaluating the Evidence Surrounding Pontine Cholinergic Involvement in REM Sleep Generation

PubMed Central

Grace, Kevin P.; Horner, Richard L.

2015-01-01

Rapid eye movement (REM) sleep – characterized by vivid dreaming, motor paralysis, and heightened neural activity – is one of the fundamental states of the mammalian central nervous system. Initial theories of REM sleep generation posited that induction of the state required activation of the “pontine REM sleep generator” by cholinergic inputs. Here, we review and evaluate the evidence surrounding cholinergic involvement in REM sleep generation. We submit that: (i) the capacity of pontine cholinergic neurotransmission to generate REM sleep has been firmly established by gain-of-function experiments, (ii) the function of endogenous cholinergic input to REM sleep generating sites cannot be determined by gain-of-function experiments; rather, loss-of-function studies are required, (iii) loss-of-function studies show that endogenous cholinergic input to the PTF is not required for REM sleep generation, and (iv) cholinergic input to the pontine REM sleep generating sites serve an accessory role in REM sleep generation: reinforcing non-REM-to-REM sleep transitions making them quicker and less likely to fail. PMID:26388832

Observations of the directional distribution of the wind energy input function over swell waves

NASA Astrophysics Data System (ADS)

Shabani, Behnam; Babanin, Alex V.; Baldock, Tom E.

2016-02-01

Field measurements of wind stress over shallow water swell traveling in different directions relative to the wind are presented. The directional distribution of the measured stresses is used to confirm the previously proposed but unverified directional distribution of the wind energy input function. The observed wind energy input function is found to follow a much narrower distribution (β∝cos⁡3.6θ) than the Plant (1982) cosine distribution. The observation of negative stress angles at large wind-wave angles, however, indicates that the onset of negative wind shearing occurs at about θ≈ 50°, and supports the use of the Snyder et al. (1981) directional distribution. Taking into account the reverse momentum transfer from swell to the wind, Snyder's proposed parameterization is found to perform exceptionally well in explaining the observed narrow directional distribution of the wind energy input function, and predicting the wind drag coefficients. The empirical coefficient (ɛ) in Snyder's parameterization is hypothesised to be a function of the wave shape parameter, with ɛ value increasing as the wave shape changes between sinusoidal, sawtooth, and sharp-crested shoaling waves.

Observer-Based Adaptive NN Control for a Class of Uncertain Nonlinear Systems With Nonsymmetric Input Saturation.

PubMed

Yong-Feng Gao; Xi-Ming Sun; Changyun Wen; Wei Wang

2017-07-01

This paper is concerned with the problem of adaptive tracking control for a class of uncertain nonlinear systems with nonsymmetric input saturation and immeasurable states. The radial basis function of neural network (NN) is employed to approximate unknown functions, and an NN state observer is designed to estimate the immeasurable states. To analyze the effect of input saturation, an auxiliary system is employed. By the aid of adaptive backstepping technique, an adaptive tracking control approach is developed. Under the proposed adaptive tracking controller, the boundedness of all the signals in the closed-loop system is achieved. Moreover, distinct from most of the existing references, the tracking error can be bounded by an explicit function of design parameters and saturation input error. Finally, an example is given to show the effectiveness of the proposed method.

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.

Automated manual transmission clutch controller

DOEpatents

Lawrie, Robert E.; Reed, Jr., Richard G.; Rausen, David J.

1999-11-30

A powertrain system for a hybrid vehicle. The hybrid vehicle includes a heat engine, such as a diesel engine, and an electric machine, which operates as both an electric motor and an alternator, to power the vehicle. The hybrid vehicle also includes a manual-style transmission configured to operate as an automatic transmission from the perspective of the driver. The engine and the electric machine drive an input shaft which in turn drives an output shaft of the transmission. In addition to driving the transmission, the electric machine regulates the speed of the input shaft in order to synchronize the input shaft during either an upshift or downshift of the transmission by either decreasing or increasing the speed of the input shaft. When decreasing the speed of the input shaft, the electric motor functions as an alternator to produce electrical energy which may be stored by a storage device. Operation of the transmission is controlled by a transmission controller which receives input signals and generates output signals to control shift and clutch motors to effect smooth launch, upshift shifts, and downshifts of the transmission, so that the transmission functions substantially as an automatic transmission from the perspective of the driver, while internally substantially functioning as a manual transmission.

Automated manual transmission shift sequence controller

DOEpatents

Lawrie, Robert E.; Reed, Richard G.; Rausen, David J.

2000-02-01

A powertrain system for a hybrid vehicle. The hybrid vehicle includes a heat engine, such as a diesel engine, and an electric machine, which operates as both, an electric motor and an alternator, to power the vehicle. The hybrid vehicle also includes a manual-style transmission configured to operate as an automatic transmission from the perspective of the driver. The engine and the electric machine drive an input shaft which in turn drives an output shaft of the transmission. In addition to driving the transmission, the electric machine regulates the speed of the input shaft in order to synchronize the input shaft during either an upshift or downshift of the transmission by either decreasing or increasing the speed of the input shaft. When decreasing the speed of the input shaft, the electric motor functions as an alternator to produce electrical energy which may be stored by a storage device. Operation of the transmission is controlled by a transmission controller which receives input signals and generates output signals to control shift and clutch motors to effect smooth launch, upshift shifts, and downshifts of the transmission, so that the transmission functions substantially as an automatic transmission from the perspective of the driver, while internally substantially functioning as a manual transmission.

Automated manual transmission mode selection controller

DOEpatents

Lawrie, Robert E.

1999-11-09

A powertrain system for a hybrid vehicle. The hybrid vehicle includes a heat engine, such as a diesel engine, and an electric machine, which operates as both an electric motor and an alternator, to power the vehicle. The hybrid vehicle also includes a manual-style transmission configured to operate as an automatic transmission from the perspective of the driver. The engine and the electric machine drive an input shaft which in turn drives an output shaft of the transmission. In addition to driving the transmission, the electric machine regulates the speed of the input shaft in order to synchronize the input shaft during either an upshift or downshift of the transmission by either decreasing or increasing the speed of the input shaft. When decreasing the speed of the input shaft, the electric motor functions as an alternator to produce electrical energy which may be stored by a storage device. Operation of the transmission is controlled by a transmission controller which receives input signals and generates output signals to control shift and clutch motors to effect smooth launch, upshift shifts, and downshifts of the transmission, so that the transmission functions substantially as an automatic transmission from the perspective of the driver, while internally substantially functioning as a manual transmission.

Automated manual transmission controller

DOEpatents

Lawrie, Robert E.; Reed, Jr., Richard G.; Bernier, David R.

1999-12-28

A powertrain system for a hybrid vehicle. The hybrid vehicle includes a heat engine, such as a diesel engine, and an electric machine, which operates as both an electric motor and an alternator, to power the vehicle. The hybrid vehicle also includes a manual-style transmission configured to operate as an automatic transmission from the perspective of the driver. The engine and the electric machine drive an input shaft which in turn drives an output shaft of the transmission. In addition to driving the transmission, the electric machine regulates the speed of the input shaft in order to synchronize the input shaft during either an upshift or downshift of the transmission by either decreasing or increasing the speed of the input shaft. When decreasing the speed of the input shaft, the electric motor functions as an alternator to produce electrical energy which may be stored by a storage device. Operation of the transmission is controlled by a transmission controller which receives input signals and generates output signals to control shift and clutch motors to effect smooth launch, upshift shifts, and downshifts of the transmission, so that the transmission functions substantially as an automatic transmission from the perspective of the driver, while internally substantially functioning as a manual transmission.

Production Economics of Private Forestry: A Comparison of Industrial and Nonindustrial Forest Owners

Treesearch

David H. Newman; David N. Wear

1993-01-01

This paper compares the producrion behavior of industrial and nonindustrial private forestland owners in the southeastern U.S. using a restricted profit function. Profits are modeled as a function of two outputs, sawtimber and pulpwood. one variable input, regeneration effort. and two quasi-fixed inputs, land and growing stock. Although an identical profit function is...

Multiple kernel learning using single stage function approximation for binary classification problems

NASA Astrophysics Data System (ADS)

Shiju, S.; Sumitra, S.

2017-12-01

In this paper, the multiple kernel learning (MKL) is formulated as a supervised classification problem. We dealt with binary classification data and hence the data modelling problem involves the computation of two decision boundaries of which one related with that of kernel learning and the other with that of input data. In our approach, they are found with the aid of a single cost function by constructing a global reproducing kernel Hilbert space (RKHS) as the direct sum of the RKHSs corresponding to the decision boundaries of kernel learning and input data and searching that function from the global RKHS, which can be represented as the direct sum of the decision boundaries under consideration. In our experimental analysis, the proposed model had shown superior performance in comparison with that of existing two stage function approximation formulation of MKL, where the decision functions of kernel learning and input data are found separately using two different cost functions. This is due to the fact that single stage representation helps the knowledge transfer between the computation procedures for finding the decision boundaries of kernel learning and input data, which inturn boosts the generalisation capacity of the model.

The Effects of a Change in the Variability of Irrigation Water

NASA Astrophysics Data System (ADS)

Lyon, Kenneth S.

1983-10-01

This paper examines the short-run effects upon several variables of an increase in the variability of an input. The measure of an increase in the variability is the "mean preserving spread" suggested by Rothschild and Stiglitz (1970). The variables examined are real income (utility), expected profits, expected output, the quantity used of the controllable input, and the shadow price of the stochastic input. Four striking features of the results follow: (1) The concepts that have been useful in summarizing deterministic comparative static results are nearly absent when an input is stochastic. (2) Most of the signs of the partial derivatives depend upon more than concavity of the utility and production functions. (3) If the utility function is not "too" risk averse, then the risk-neutral results hold for the risk-aversion case. (4) If the production function is Cobb-Douglas, then definite results are achieved if the utility function is linear or if the "degree of risk-aversion" is "small."

Sinusoidal input describing function for hysteresis followed by elementary backlash

NASA Technical Reports Server (NTRS)

Ringland, R. F.

1976-01-01

The author proposes a new sinusoidal input describing function which accounts for the serial combination of hysteresis followed by elementary backlash in a single nonlinear element. The output of the hysteresis element drives the elementary backlash element. Various analytical forms of the describing function are given, depending on the a/A ratio, where a is the half width of the hysteresis band or backlash gap, and A is the amplitude of the assumed input sinusoid, and on the value of the parameter representing the fraction of a attributed to the backlash characteristic. The negative inverse describing function is plotted on a gain-phase plot, and it is seen that a relatively small amount of backlash leads to domination of the backlash character in the describing function. The extent of the region of the gain-phase plane covered by the describing function is such as to guarantee some form of limit cycle behavior in most closed-loop systems.

Probabilistic Density Function Method for Stochastic ODEs of Power Systems with Uncertain Power Input

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

Wang, Peng; Barajas-Solano, David A.; Constantinescu, Emil

Wind and solar power generators are commonly described by a system of stochastic ordinary differential equations (SODEs) where random input parameters represent uncertainty in wind and solar energy. The existing methods for SODEs are mostly limited to delta-correlated random parameters (white noise). Here we use the Probability Density Function (PDF) method for deriving a closed-form deterministic partial differential equation (PDE) for the joint probability density function of the SODEs describing a power generator with time-correlated power input. The resulting PDE is solved numerically. A good agreement with Monte Carlo Simulations shows accuracy of the PDF method.

Flexible and re-configurable optical three-input XOR logic gate of phase-modulated signals with multicast functionality for potential application in optical physical-layer network coding.

PubMed

Lu, Guo-Wei; Qin, Jun; Wang, Hongxiang; Ji, XuYuefeng; Sharif, Gazi Mohammad; Yamaguchi, Shigeru

2016-02-08

Optical logic gate, especially exclusive-or (XOR) gate, plays important role in accomplishing photonic computing and various network functionalities in future optical networks. On the other hand, optical multicast is another indispensable functionality to efficiently deliver information in optical networks. In this paper, for the first time, we propose and experimentally demonstrate a flexible optical three-input XOR gate scheme for multiple input phase-modulated signals with a 1-to-2 multicast functionality for each XOR operation using four-wave mixing (FWM) effect in single piece of highly-nonlinear fiber (HNLF). Through FWM in HNLF, all of the possible XOR operations among input signals could be simultaneously realized by sharing a single piece of HNLF. By selecting the obtained XOR components using a followed wavelength selective component, the number of XOR gates and the participant light in XOR operations could be flexibly configured. The re-configurability of the proposed XOR gate and the function integration of the optical logic gate and multicast in single device offer the flexibility in network design and improve the network efficiency. We experimentally demonstrate flexible 3-input XOR gate for four 10-Gbaud binary phase-shift keying signals with a multicast scale of 2. Error-free operations for the obtained XOR results are achieved. Potential application of the integrated XOR and multicast function in network coding is also discussed.

Peak-Seeking Control Using Gradient and Hessian Estimates

NASA Technical Reports Server (NTRS)

Ryan, John J.; Speyer, Jason L.

2010-01-01

A peak-seeking control method is presented which utilizes a linear time-varying Kalman filter. Performance function coordinate and magnitude measurements are used by the Kalman filter to estimate the gradient and Hessian of the performance function. The gradient and Hessian are used to command the system toward a local extremum. The method is naturally applied to multiple-input multiple-output systems. Applications of this technique to a single-input single-output example and a two-input one-output example are presented.

ENHANCED RECOVERY METHODS FOR 85KR AGE-DATING GROUNDWATER: ROYAL WATERSHED, MAINE

EPA Science Inventory

Potential widespread use of ⁸⁵Kr, having a constant input function in the northern hemisphere, for groundwater age-dating would advance watershed investigations. The current input function of tritium is not sufficient to estimate young modern recharge waters. While tri...

Short-Term Memory in Mathematics-Proficient and Mathematics-Disabled Students as a Function of Input-Modality/Output-Modality Pairings.

ERIC Educational Resources Information Center

Webster, Raymond E.

1980-01-01

A significant two-way input modality by output modality interaction suggested that short term memory capacity among the groups differed as a function of the modality used to present the items in combination with the output response required. (Author/CL)

Functional Differences between Statistical Learning with and without Explicit Training

ERIC Educational Resources Information Center

Batterink, Laura J.; Reber, Paul J.; Paller, Ken A.

2015-01-01

Humans are capable of rapidly extracting regularities from environmental input, a process known as statistical learning. This type of learning typically occurs automatically, through passive exposure to environmental input. The presumed function of statistical learning is to optimize processing, allowing the brain to more accurately predict and…

Smart mobility solution with multiple input Output interface.

PubMed

Sethi, Aartika; Deb, Sujay; Ranjan, Prabhat; Sardar, Arghya

2017-07-01

Smart wheelchairs are commonly used to provide solution for mobility impairment. However their usage is limited primarily due to high cost owing from sensors required for giving input, lack of adaptability for different categories of input and limited functionality. In this paper we propose a smart mobility solution using smartphone with inbuilt sensors (accelerometer, camera and speaker) as an input interface. An Emotiv EPOC+ is also used for motor imagery based input control synced with facial expressions in cases of extreme disability. Apart from traction, additional functions like home security and automation are provided using Internet of Things (IoT) and web interfaces. Although preliminary, our results suggest that this system can be used as an integrated and efficient solution for people suffering from mobility impairment. The results also indicate a decent accuracy is obtained for the overall system.

Synaptology of physiologically identified ganglion cells in the cat retina: a comparison of retinal X- and Y-cells.

PubMed

Weber, A J; Stanford, L R

1994-05-15

It has long been known that a number of functionally different types of ganglion cells exist in the cat retina, and that each responds differently to visual stimulation. To determine whether the characteristic response properties of different retinal ganglion cell types might reflect differences in the number and distribution of their bipolar and amacrine cell inputs, we compared the percentages and distributions of the synaptic inputs from bipolar and amacrine cells to the entire dendritic arbors of physiologically characterized retinal X- and Y-cells. Sixty-two percent of the synaptic input to the Y-cell was from amacrine cell terminals, while the X-cells received approximately equal amounts of input from amacrine and bipolar cells. We found no significant difference in the distributions of bipolar or amacrine cell inputs to X- and Y-cells, or ON-center and OFF-center cells, either as a function of dendritic branch order or distance from the origin of the dendritic arbor. While, on the basis of these data, we cannot exclude the possibility that the difference in the proportion of bipolar and amacrine cell input contributes to the functional differences between X- and Y-cells, the magnitude of this difference, and the similarity in the distributions of the input from the two afferent cell types, suggest that mechanisms other than a simple predominance of input from amacrine or bipolar cells underlie the differences in their response properties. More likely, perhaps, is that the specific response features of X- and Y-cells originate in differences in the visual responses of the bipolar and amacrine cells that provide their input, or in the complex synaptic arrangements found among amacrine and bipolar cell terminals and the dendrites of specific types of retinal ganglion cells.

Oculomotor learning revisited: a model of reinforcement learning in the basal ganglia incorporating an efference copy of motor actions

PubMed Central

Fee, Michale S.

2012-01-01

In its simplest formulation, reinforcement learning is based on the idea that if an action taken in a particular context is followed by a favorable outcome, then, in the same context, the tendency to produce that action should be strengthened, or reinforced. While reinforcement learning forms the basis of many current theories of basal ganglia (BG) function, these models do not incorporate distinct computational roles for signals that convey context, and those that convey what action an animal takes. Recent experiments in the songbird suggest that vocal-related BG circuitry receives two functionally distinct excitatory inputs. One input is from a cortical region that carries context information about the current “time” in the motor sequence. The other is an efference copy of motor commands from a separate cortical brain region that generates vocal variability during learning. Based on these findings, I propose here a general model of vertebrate BG function that combines context information with a distinct motor efference copy signal. The signals are integrated by a learning rule in which efference copy inputs gate the potentiation of context inputs (but not efference copy inputs) onto medium spiny neurons in response to a rewarded action. The hypothesis is described in terms of a circuit that implements the learning of visually guided saccades. The model makes testable predictions about the anatomical and functional properties of hypothesized context and efference copy inputs to the striatum from both thalamic and cortical sources. PMID:22754501

Oculomotor learning revisited: a model of reinforcement learning in the basal ganglia incorporating an efference copy of motor actions.

PubMed

Fee, Michale S

2012-01-01

In its simplest formulation, reinforcement learning is based on the idea that if an action taken in a particular context is followed by a favorable outcome, then, in the same context, the tendency to produce that action should be strengthened, or reinforced. While reinforcement learning forms the basis of many current theories of basal ganglia (BG) function, these models do not incorporate distinct computational roles for signals that convey context, and those that convey what action an animal takes. Recent experiments in the songbird suggest that vocal-related BG circuitry receives two functionally distinct excitatory inputs. One input is from a cortical region that carries context information about the current "time" in the motor sequence. The other is an efference copy of motor commands from a separate cortical brain region that generates vocal variability during learning. Based on these findings, I propose here a general model of vertebrate BG function that combines context information with a distinct motor efference copy signal. The signals are integrated by a learning rule in which efference copy inputs gate the potentiation of context inputs (but not efference copy inputs) onto medium spiny neurons in response to a rewarded action. The hypothesis is described in terms of a circuit that implements the learning of visually guided saccades. The model makes testable predictions about the anatomical and functional properties of hypothesized context and efference copy inputs to the striatum from both thalamic and cortical sources.

Altered functional connectivity of the amygdaloid input nuclei in adolescents and young adults with autism spectrum disorder: a resting state fMRI study.

PubMed

Rausch, Annika; Zhang, Wei; Haak, Koen V; Mennes, Maarten; Hermans, Erno J; van Oort, Erik; van Wingen, Guido; Beckmann, Christian F; Buitelaar, Jan K; Groen, Wouter B

2016-01-01

Amygdala dysfunction is hypothesized to underlie the social deficits observed in autism spectrum disorders (ASD). However, the neurobiological basis of this hypothesis is underspecified because it is unknown whether ASD relates to abnormalities of the amygdaloid input or output nuclei. Here, we investigated the functional connectivity of the amygdaloid social-perceptual input nuclei and emotion-regulation output nuclei in ASD versus controls. We collected resting state functional magnetic resonance imaging (fMRI) data, tailored to provide optimal sensitivity in the amygdala as well as the neocortex, in 20 adolescents and young adults with ASD and 25 matched controls. We performed a regular correlation analysis between the entire amygdala (EA) and the whole brain and used a partial correlation analysis to investigate whole-brain functional connectivity uniquely related to each of the amygdaloid subregions. Between-group comparison of regular EA correlations showed significantly reduced connectivity in visuospatial and superior parietal areas in ASD compared to controls. Partial correlation analysis revealed that this effect was driven by the left superficial and right laterobasal input subregions, but not the centromedial output nuclei. These results indicate reduced connectivity of specifically the amygdaloid sensory input channels in ASD, suggesting that abnormal amygdalo-cortical connectivity can be traced down to the socio-perceptual pathways.

Factorizing the motion sensitivity function into equivalent input noise and calculation efficiency.

PubMed

Allard, Rémy; Arleo, Angelo

2017-01-01

The photopic motion sensitivity function of the energy-based motion system is band-pass peaking around 8 Hz. Using an external noise paradigm to factorize the sensitivity into equivalent input noise and calculation efficiency, the present study investigated if the variation in photopic motion sensitivity as a function of the temporal frequency is due to a variation of equivalent input noise (e.g., early temporal filtering) or calculation efficiency (ability to select and integrate motion). For various temporal frequencies, contrast thresholds for a direction discrimination task were measured in presence and absence of noise. Up to 15 Hz, the sensitivity variation was mainly due to a variation of equivalent input noise and little variation in calculation efficiency was observed. The sensitivity fall-off at very high temporal frequencies (from 15 to 30 Hz) was due to a combination of a drop of calculation efficiency and a rise of equivalent input noise. A control experiment in which an artificial temporal integration was applied to the stimulus showed that an early temporal filter (generally assumed to affect equivalent input noise, not calculation efficiency) could impair both the calculation efficiency and equivalent input noise at very high temporal frequencies. We conclude that at the photopic luminance intensity tested, the variation of motion sensitivity as a function of the temporal frequency was mainly due to early temporal filtering, not to the ability to select and integrate motion. More specifically, we conclude that photopic motion sensitivity at high temporal frequencies is limited by internal noise occurring after the transduction process (i.e., neural noise), not by quantal noise resulting from the probabilistic absorption of photons by the photoreceptors as previously suggested.

SNP ID-info: SNP ID searching and visualization platform.

PubMed

Yang, Cheng-Hong; Chuang, Li-Yeh; Cheng, Yu-Huei; Wen, Cheng-Hao; Chang, Phei-Lang; Chang, Hsueh-Wei

2008-09-01

Many association studies provide the relationship between single nucleotide polymorphisms (SNPs), diseases and cancers, without giving a SNP ID, however. Here, we developed the SNP ID-info freeware to provide the SNP IDs within inputting genetic and physical information of genomes. The program provides an "SNP-ePCR" function to generate the full-sequence using primers and template inputs. In "SNPosition," sequence from SNP-ePCR or direct input is fed to match the SNP IDs from SNP fasta-sequence. In "SNP search" and "SNP fasta" function, information of SNPs within the cytogenetic band, contig position, and keyword input are acceptable. Finally, the SNP ID neighboring environment for inputs is completely visualized in the order of contig position and marked with SNP and flanking hits. The SNP identification problems inherent in NCBI SNP BLAST are also avoided. In conclusion, the SNP ID-info provides a visualized SNP ID environment for multiple inputs and assists systematic SNP association studies. The server and user manual are available at http://bio.kuas.edu.tw/snpid-info.

Orientation selectivity and the functional clustering of synaptic inputs in primary visual cortex

PubMed Central

Wilson, Daniel E.; Whitney, David E.; Scholl, Benjamin; Fitzpatrick, David

2016-01-01

The majority of neurons in primary visual cortex are tuned for stimulus orientation, but the factors that account for the range of orientation selectivities exhibited by cortical neurons remain unclear. To address this issue, we used in vivo 2-photon calcium imaging to characterize the orientation tuning and spatial arrangement of synaptic inputs to the dendritic spines of individual pyramidal neurons in layer 2/3 of ferret visual cortex. The summed synaptic input to individual neurons reliably predicted the neuron’s orientation preference, but did not account for differences in orientation selectivity among neurons. These differences reflected a robust input-output nonlinearity that could not be explained by spike threshold alone, and was strongly correlated with the spatial clustering of co-tuned synaptic inputs within the dendritic field. Dendritic branches with more co-tuned synaptic clusters exhibited greater rates of local dendritic calcium events supporting a prominent role for functional clustering of synaptic inputs in dendritic nonlinearities that shape orientation selectivity. PMID:27294510

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

Smallwood, D.O.

In a previous paper Smallwood and Paez (1991) showed how to generate realizations of partially coherent stationary normal time histories with a specified cross-spectral density matrix. This procedure is generalized for the case of multiple inputs with a specified cross-spectral density function and a specified marginal probability density function (pdf) for each of the inputs. The specified pdfs are not required to be Gaussian. A zero memory nonlinear (ZMNL) function is developed for each input to transform a Gaussian or normal time history into a time history with a specified non-Gaussian distribution. The transformation functions have the property that amore » transformed time history will have nearly the same auto spectral density as the original time history. A vector of Gaussian time histories are then generated with the specified cross-spectral density matrix. These waveforms are then transformed into the required time history realizations using the ZMNL function.« less

Universal Approximation by Using the Correntropy Objective Function.

PubMed

Nayyeri, Mojtaba; Sadoghi Yazdi, Hadi; Maskooki, Alaleh; Rouhani, Modjtaba

2017-10-16

Several objective functions have been proposed in the literature to adjust the input parameters of a node in constructive networks. Furthermore, many researchers have focused on the universal approximation capability of the network based on the existing objective functions. In this brief, we use a correntropy measure based on the sigmoid kernel in the objective function to adjust the input parameters of a newly added node in a cascade network. The proposed network is shown to be capable of approximating any continuous nonlinear mapping with probability one in a compact input sample space. Thus, the convergence is guaranteed. The performance of our method was compared with that of eight different objective functions, as well as with an existing one hidden layer feedforward network on several real regression data sets with and without impulsive noise. The experimental results indicate the benefits of using a correntropy measure in reducing the root mean square error and increasing the robustness to noise.

Three-input majority function as the unique optimal function for the bias amplification using nonlocal boxes

NASA Astrophysics Data System (ADS)

Mori, Ryuhei

2016-11-01

Brassard et al. [Phys. Rev. Lett. 96, 250401 (2006), 10.1103/PhysRevLett.96.250401] showed that shared nonlocal boxes with a CHSH (Clauser, Horne, Shimony, and Holt) probability greater than 3/+√{6 } 6 yield trivial communication complexity. There still exists a gap with the maximum CHSH probability 2/+√{2 } 4 achievable by quantum mechanics. It is an interesting open question to determine the exact threshold for the trivial communication complexity. Brassard et al.'s idea is based on recursive bias amplification by the three-input majority function. It was not obvious if another choice of function exhibits stronger bias amplification. We show that the three-input majority function is the unique optimal function, so that one cannot improve the threshold 3/+√{6 } 6 by Brassard et al.'s bias amplification. In this work, protocols for computing the function used for the bias amplification are restricted to be nonadaptive protocols or a particular adaptive protocol inspired by Pawłowski et al.'s protocol for information causality [Nature (London) 461, 1101 (2009), 10.1038/nature08400]. We first show an adaptive protocol inspired by Pawłowski et al.'s protocol, and then show that the adaptive protocol improves upon nonadaptive protocols. Finally, we show that the three-input majority function is the unique optimal function for the bias amplification if we apply the adaptive protocol to each step of the bias amplification.

Model predictive controller design for boost DC-DC converter using T-S fuzzy cost function

NASA Astrophysics Data System (ADS)

Seo, Sang-Wha; Kim, Yong; Choi, Han Ho

2017-11-01

This paper proposes a Takagi-Sugeno (T-S) fuzzy method to select cost function weights of finite control set model predictive DC-DC converter control algorithms. The proposed method updates the cost function weights at every sample time by using T-S type fuzzy rules derived from the common optimal control engineering knowledge that a state or input variable with an excessively large magnitude can be penalised by increasing the weight corresponding to the variable. The best control input is determined via the online optimisation of the T-S fuzzy cost function for all the possible control input sequences. This paper implements the proposed model predictive control algorithm in real time on a Texas Instruments TMS320F28335 floating-point Digital Signal Processor (DSP). Some experimental results are given to illuminate the practicality and effectiveness of the proposed control system under several operating conditions. The results verify that our method can yield not only good transient and steady-state responses (fast recovery time, small overshoot, zero steady-state error, etc.) but also insensitiveness to abrupt load or input voltage parameter variations.

Rail-to-rail differential input amplification stage with main and surrogate differential pairs

DOEpatents

Britton, Jr., Charles Lanier; Smith, Stephen Fulton

2007-03-06

An operational amplifier input stage provides a symmetrical rail-to-rail input common-mode voltage without turning off either pair of complementary differential input transistors. Secondary, or surrogate, transistor pairs assume the function of the complementary differential transistors. The circuit also maintains essentially constant transconductance, constant slew rate, and constant signal-path supply current as it provides rail-to-rail operation.

The biological function of consciousness

PubMed Central

Earl, Brian

2014-01-01

This research is an investigation of whether consciousness—one's ongoing experience—influences one's behavior and, if so, how. Analysis of the components, structure, properties, and temporal sequences of consciousness has established that, (1) contrary to one's intuitive understanding, consciousness does not have an active, executive role in determining behavior; (2) consciousness does have a biological function; and (3) consciousness is solely information in various forms. Consciousness is associated with a flexible response mechanism (FRM) for decision-making, planning, and generally responding in nonautomatic ways. The FRM generates responses by manipulating information and, to function effectively, its data input must be restricted to task-relevant information. The properties of consciousness correspond to the various input requirements of the FRM; and when important information is missing from consciousness, functions of the FRM are adversely affected; both of which indicate that consciousness is the input data to the FRM. Qualitative and quantitative information (shape, size, location, etc.) are incorporated into the input data by a qualia array of colors, sounds, and so on, which makes the input conscious. This view of the biological function of consciousness provides an explanation why we have experiences; why we have emotional and other feelings, and why their loss is associated with poor decision-making; why blindsight patients do not spontaneously initiate responses to events in their blind field; why counter-habitual actions are only possible when the intended action is in mind; and the reason for inattentional blindness. PMID:25140159

Influence of speckle image reconstruction on photometric precision for large solar telescopes

NASA Astrophysics Data System (ADS)

Peck, C. L.; Wöger, F.; Marino, J.

2017-11-01

Context. High-resolution observations from large solar telescopes require adaptive optics (AO) systems to overcome image degradation caused by Earth's turbulent atmosphere. AO corrections are, however, only partial. Achieving near-diffraction limited resolution over a large field of view typically requires post-facto image reconstruction techniques to reconstruct the source image. Aims: This study aims to examine the expected photometric precision of amplitude reconstructed solar images calibrated using models for the on-axis speckle transfer functions and input parameters derived from AO control data. We perform a sensitivity analysis of the photometric precision under variations in the model input parameters for high-resolution solar images consistent with four-meter class solar telescopes. Methods: Using simulations of both atmospheric turbulence and partial compensation by an AO system, we computed the speckle transfer function under variations in the input parameters. We then convolved high-resolution numerical simulations of the solar photosphere with the simulated atmospheric transfer function, and subsequently deconvolved them with the model speckle transfer function to obtain a reconstructed image. To compute the resulting photometric precision, we compared the intensity of the original image with the reconstructed image. Results: The analysis demonstrates that high photometric precision can be obtained for speckle amplitude reconstruction using speckle transfer function models combined with AO-derived input parameters. Additionally, it shows that the reconstruction is most sensitive to the input parameter that characterizes the atmospheric distortion, and sub-2% photometric precision is readily obtained when it is well estimated.

The relative degree enhancement problem for MIMO nonlinear systems

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

Schoenwald, D.A.; Oezguener, Ue.

1995-07-01

The authors present a result for linearizing a nonlinear MIMO system by employing partial feedback - feedback at all but one input-output channel such that the SISO feedback linearization problem is solvable at the remaining input-output channel. The partial feedback effectively enhances the relative degree at the open input-output channel provided the feedback functions are chosen to satisfy relative degree requirements. The method is useful for nonlinear systems that are not feedback linearizable in a MIMO sense. Several examples are presented to show how these feedback functions can be computed. This strategy can be combined with decentralized observers for amore » completely decentralized feedback linearization result for at least one input-output channel.« less

Production Function Geometry with "Knightian" Total Product

ERIC Educational Resources Information Center

Truett, Dale B.; Truett, Lila J.

2007-01-01

Authors of principles and price theory textbooks generally illustrate short-run production using a total product curve that displays first increasing and then diminishing marginal returns to employment of the variable input(s). Although it seems reasonable that a temporary range of increasing returns to variable inputs will likely occur as…

AESOP: An interactive computer program for the design of linear quadratic regulators and Kalman filters

NASA Technical Reports Server (NTRS)

Lehtinen, B.; Geyser, L. C.

1984-01-01

AESOP is a computer program for use in designing feedback controls and state estimators for linear multivariable systems. AESOP is meant to be used in an interactive manner. Each design task that the program performs is assigned a "function" number. The user accesses these functions either (1) by inputting a list of desired function numbers or (2) by inputting a single function number. In the latter case the choice of the function will in general depend on the results obtained by the previously executed function. The most important of the AESOP functions are those that design,linear quadratic regulators and Kalman filters. The user interacts with the program when using these design functions by inputting design weighting parameters and by viewing graphic displays of designed system responses. Supporting functions are provided that obtain system transient and frequency responses, transfer functions, and covariance matrices. The program can also compute open-loop system information such as stability (eigenvalues), eigenvectors, controllability, and observability. The program is written in ANSI-66 FORTRAN for use on an IBM 3033 using TSS 370. Descriptions of all subroutines and results of two test cases are included in the appendixes.

Ranking Hearing Aid Input-Output Functions for Understanding Low-, Conversational-, and High-Level Speech in Multitalker Babble

ERIC Educational Resources Information Center

Chung, King; Killion, Mead C.; Christensen, Laurel A.

2007-01-01

Purpose: To determine the rankings of 6 input-output functions for understanding low-level, conversational, and high-level speech in multitalker babble without manipulating volume control for listeners with normal hearing, flat sensorineural hearing loss, and mildly sloping sensorineural hearing loss. Method: Peak clipping, compression limiting,…

Econometric analysis of fire suppression production functions for large wildland fires

Treesearch

Thomas P. Holmes; David E. Calkin

2013-01-01

In this paper, we use operational data collected for large wildland fires to estimate the parameters of economic production functions that relate the rate of fireline construction with the level of fire suppression inputs (handcrews, dozers, engines and helicopters). These parameter estimates are then used to evaluate whether the productivity of fire suppression inputs...

Models for forecasting energy use in the US farm sector

NASA Astrophysics Data System (ADS)

Christensen, L. R.

1981-07-01

Econometric models were developed and estimated for the purpose of forecasting electricity and petroleum demand in US agriculture. A structural approach is pursued which takes account of the fact that the quantity demanded of any one input is a decision made in conjunction with other input decisions. Three different functional forms of varying degrees of complexity are specified for the structural cost function, which describes the cost of production as a function of the level of output and factor prices. Demand for materials (all purchased inputs) is derived from these models. A separate model which break this demand up into demand for the four components of materials is used to produce forecasts of electricity and petroleum is a stepwise manner.

A new polytopic approach for the unknown input functional observer design

NASA Astrophysics Data System (ADS)

Bezzaoucha, Souad; Voos, Holger; Darouach, Mohamed

2018-03-01

In this paper, a constructive procedure to design Functional Unknown Input Observers for nonlinear continuous time systems is proposed under the Polytopic Takagi-Sugeno framework. An equivalent representation for the nonlinear model is achieved using the sector nonlinearity transformation. Applying the Lyapunov theory and the ? attenuation, linear matrix inequalities conditions are deduced which are solved for feasibility to obtain the observer design matrices. To cope with the effect of unknown inputs, classical approach of decoupling the unknown input for the linear case is used. Both algebraic and solver-based solutions are proposed (relaxed conditions). Necessary and sufficient conditions for the existence of the functional polytopic observer are given. For both approaches, the general and particular cases (measurable premise variables, full state estimation with full and reduced order cases) are considered and it is shown that the proposed conditions correspond to the one presented for standard linear case. To illustrate the proposed theoretical results, detailed numerical simulations are presented for a Quadrotor Aerial Robots Landing and a Waste Water Treatment Plant. Both systems are highly nonlinear and represented in a T-S polytopic form with unmeasurable premise variables and unknown inputs.

Applications of information theory, genetic algorithms, and neural models to predict oil flow

NASA Astrophysics Data System (ADS)

Ludwig, Oswaldo; Nunes, Urbano; Araújo, Rui; Schnitman, Leizer; Lepikson, Herman Augusto

2009-07-01

This work introduces a new information-theoretic methodology for choosing variables and their time lags in a prediction setting, particularly when neural networks are used in non-linear modeling. The first contribution of this work is the Cross Entropy Function (XEF) proposed to select input variables and their lags in order to compose the input vector of black-box prediction models. The proposed XEF method is more appropriate than the usually applied Cross Correlation Function (XCF) when the relationship among the input and output signals comes from a non-linear dynamic system. The second contribution is a method that minimizes the Joint Conditional Entropy (JCE) between the input and output variables by means of a Genetic Algorithm (GA). The aim is to take into account the dependence among the input variables when selecting the most appropriate set of inputs for a prediction problem. In short, theses methods can be used to assist the selection of input training data that have the necessary information to predict the target data. The proposed methods are applied to a petroleum engineering problem; predicting oil production. Experimental results obtained with a real-world dataset are presented demonstrating the feasibility and effectiveness of the method.

Versatile tunable current-mode universal biquadratic filter using MO-DVCCs and MOSFET-based electronic resistors.

PubMed

Chen, Hua-Pin

2014-01-01

This paper presents a versatile tunable current-mode universal biquadratic filter with four-input and three-output employing only two multioutput differential voltage current conveyors (MO-DVCCs), two grounded capacitors, and a well-known method for replacement of three grounded resistors by MOSFET-based electronic resistors. The proposed configuration exhibits high-output impedance which is important for easy cascading in the current-mode operations. The proposed circuit can be used as either a two-input three-output circuit or a three-input single-output circuit. In the operation of two-input three-output circuit, the bandpass, highpass, and bandreject filtering responses can be realized simultaneously while the allpass filtering response can be easily obtained by connecting appropriated output current directly without using additional stages. In the operation of three-input single-output circuit, all five generic filtering functions can be easily realized by selecting different three-input current signals. The filter permits orthogonal controllability of the quality factor and resonance angular frequency, and no inverting-type input current signals are imposed. All the passive and active sensitivities are low. Postlayout simulations were carried out to verify the functionality of the design.

Versatile Tunable Current-Mode Universal Biquadratic Filter Using MO-DVCCs and MOSFET-Based Electronic Resistors

PubMed Central

2014-01-01

This paper presents a versatile tunable current-mode universal biquadratic filter with four-input and three-output employing only two multioutput differential voltage current conveyors (MO-DVCCs), two grounded capacitors, and a well-known method for replacement of three grounded resistors by MOSFET-based electronic resistors. The proposed configuration exhibits high-output impedance which is important for easy cascading in the current-mode operations. The proposed circuit can be used as either a two-input three-output circuit or a three-input single-output circuit. In the operation of two-input three-output circuit, the bandpass, highpass, and bandreject filtering responses can be realized simultaneously while the allpass filtering response can be easily obtained by connecting appropriated output current directly without using additional stages. In the operation of three-input single-output circuit, all five generic filtering functions can be easily realized by selecting different three-input current signals. The filter permits orthogonal controllability of the quality factor and resonance angular frequency, and no inverting-type input current signals are imposed. All the passive and active sensitivities are low. Postlayout simulations were carried out to verify the functionality of the design. PMID:24982963

Trigeminal, Visceral and Vestibular Inputs May Improve Cognitive Functions by Acting through the Locus Coeruleus and the Ascending Reticular Activating System: A New Hypothesis

PubMed Central

De Cicco, Vincenzo; Tramonti Fantozzi, Maria P.; Cataldo, Enrico; Barresi, Massimo; Bruschini, Luca; Faraguna, Ugo; Manzoni, Diego

2018-01-01

It is known that sensory signals sustain the background discharge of the ascending reticular activating system (ARAS) which includes the noradrenergic locus coeruleus (LC) neurons and controls the level of attention and alertness. Moreover, LC neurons influence brain metabolic activity, gene expression and brain inflammatory processes. As a consequence of the sensory control of ARAS/LC, stimulation of a sensory channel may potential influence neuronal activity and trophic state all over the brain, supporting cognitive functions and exerting a neuroprotective action. On the other hand, an imbalance of the same input on the two sides may lead to an asymmetric hemispheric excitability, leading to an impairment in cognitive functions. Among the inputs that may drive LC neurons and ARAS, those arising from the trigeminal region, from visceral organs and, possibly, from the vestibular system seem to be particularly relevant in regulating their activity. The trigeminal, visceral and vestibular control of ARAS/LC activity may explain why these input signals: (1) affect sensorimotor and cognitive functions which are not directly related to their specific informational content; and (2) are effective in relieving the symptoms of some brain pathologies, thus prompting peripheral activation of these input systems as a complementary approach for the treatment of cognitive impairments and neurodegenerative disorders. PMID:29358907

Consideration of plant behaviour in optimal servo-compensator design

NASA Astrophysics Data System (ADS)

Moase, W. H.; Manzie, C.

2016-07-01

Where the most prevalent optimal servo-compensator formulations penalise the behaviour of an error system, this paper considers the problem of additionally penalising the actual states and inputs of the plant. Doing so has the advantage of enabling the penalty function to better resemble an economic cost. This is especially true of problems where control effort needs to be sensibly allocated across weakly redundant inputs or where one wishes to use penalties to soft-constrain certain states or inputs. It is shown that, although the resulting cost function grows unbounded as its horizon approaches infinity, it is possible to formulate an equivalent optimisation problem with a bounded cost. The resulting optimisation problem is similar to those in earlier studies but has an additional 'correction term' in the cost function, and a set of equality constraints that arise when there are redundant inputs. A numerical approach to solve the resulting optimisation problem is presented, followed by simulations on a micro-macro positioner that illustrate the benefits of the proposed servo-compensator design approach.

Performances estimation of a rotary traveling wave ultrasonic motor based on two-dimension analytical model.

PubMed

Ming, Y; Peiwen, Q

2001-03-01

The understanding of ultrasonic motor performances as a function of input parameters, such as the voltage amplitude, driving frequency, the preload on the rotor, is a key to many applications and control of ultrasonic motor. This paper presents performances estimation of the piezoelectric rotary traveling wave ultrasonic motor as a function of input voltage amplitude and driving frequency and preload. The Love equation is used to derive the traveling wave amplitude on the stator surface. With the contact model of the distributed spring-rigid body between the stator and rotor, a two-dimension analytical model of the rotary traveling wave ultrasonic motor is constructed. Then the performances of stead rotation speed and stall torque are deduced. With MATLAB computational language and iteration algorithm, we estimate the performances of rotation speed and stall torque versus input parameters respectively. The same experiments are completed with the optoelectronic tachometer and stand weight. Both estimation and experiment results reveal the pattern of performance variation as a function of its input parameters.

Cell type-specific long-range connections of basal forebrain circuit.

PubMed

Do, Johnny Phong; Xu, Min; Lee, Seung-Hee; Chang, Wei-Cheng; Zhang, Siyu; Chung, Shinjae; Yung, Tyler J; Fan, Jiang Lan; Miyamichi, Kazunari; Luo, Liqun; Dan, Yang

2016-09-19

The basal forebrain (BF) plays key roles in multiple brain functions, including sleep-wake regulation, attention, and learning/memory, but the long-range connections mediating these functions remain poorly characterized. Here we performed whole-brain mapping of both inputs and outputs of four BF cell types - cholinergic, glutamatergic, and parvalbumin-positive (PV+) and somatostatin-positive (SOM+) GABAergic neurons - in the mouse brain. Using rabies virus -mediated monosynaptic retrograde tracing to label the inputs and adeno-associated virus to trace axonal projections, we identified numerous brain areas connected to the BF. The inputs to different cell types were qualitatively similar, but the output projections showed marked differences. The connections to glutamatergic and SOM+ neurons were strongly reciprocal, while those to cholinergic and PV+ neurons were more unidirectional. These results reveal the long-range wiring diagram of the BF circuit with highly convergent inputs and divergent outputs and point to both functional commonality and specialization of different BF cell types.

Analysis of nystagmus response to a pseudorandom velocity input

NASA Technical Reports Server (NTRS)

Lessard, C. S.

1986-01-01

Space motion sickness was not reported during the first Apollo missions; however, since Apollo 8 through the current Shuttle and Skylab missions, approximately 50% of the crewmembers have experienced instances of space motion sickness. Space motion sickness, renamed space adaptation syndrome, occurs primarily during the initial period of a mission until habilation takes place. One of NASA's efforts to resolve the space adaptation syndrome is to model the individual's vestibular response for basis knowledge and as a possible predictor of an individual's susceptibility to the disorder. This report describes a method to analyse the vestibular system when subjected to a pseudorandom angular velocity input. A sum of sinusoids (pseudorandom) input lends itself to analysis by linear frequency methods. Resultant horizontal ocular movements were digitized, filtered and transformed into the frequency domain. Programs were developed and evaluated to obtain the (1) auto spectra of input stimulus and resultant ocular resonse, (2) cross spectra, (3) the estimated vestibular-ocular system transfer function gain and phase, and (4) coherence function between stimulus and response functions.

Improved prescribed performance control for air-breathing hypersonic vehicles with unknown deadzone input nonlinearity.

PubMed

Wang, Yingyang; Hu, Jianbo

2018-05-19

An improved prescribed performance controller is proposed for the longitudinal model of an air-breathing hypersonic vehicle (AHV) subject to uncertain dynamics and input nonlinearity. Different from the traditional non-affine model requiring non-affine functions to be differentiable, this paper utilizes a semi-decomposed non-affine model with non-affine functions being locally semi-bounded and possibly in-differentiable. A new error transformation combined with novel prescribed performance functions is proposed to bypass complex deductions caused by conventional error constraint approaches and circumvent high frequency chattering in control inputs. On the basis of backstepping technique, the improved prescribed performance controller with low structural and computational complexity is designed. The methodology guarantees the altitude and velocity tracking error within transient and steady state performance envelopes and presents excellent robustness against uncertain dynamics and deadzone input nonlinearity. Simulation results demonstrate the efficacy of the proposed method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Design of High Quality Chemical XOR Gates with Noise Reduction.

PubMed

Wood, Mackenna L; Domanskyi, Sergii; Privman, Vladimir

2017-07-05

We describe a chemical XOR gate design that realizes gate-response function with filtering properties. Such gate-response function is flat (has small gradients) at and in the vicinity of all the four binary-input logic points, resulting in analog noise suppression. The gate functioning involves cross-reaction of the inputs represented by pairs of chemicals to produce a practically zero output when both are present and nearly equal. This cross-reaction processing step is also designed to result in filtering at low output intensities by canceling out the inputs if one of the latter has low intensity compared with the other. The remaining inputs, which were not reacted away, are processed to produce the output XOR signal by chemical steps that result in filtering at large output signal intensities. We analyze the tradeoff resulting from filtering, which involves loss of signal intensity. We also discuss practical aspects of realizations of such XOR gates. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Functional transformations of odor inputs in the mouse olfactory bulb.

PubMed

Adam, Yoav; Livneh, Yoav; Miyamichi, Kazunari; Groysman, Maya; Luo, Liqun; Mizrahi, Adi

2014-01-01

Sensory inputs from the nasal epithelium to the olfactory bulb (OB) are organized as a discrete map in the glomerular layer (GL). This map is then modulated by distinct types of local neurons and transmitted to higher brain areas via mitral and tufted cells. Little is known about the functional organization of the circuits downstream of glomeruli. We used in vivo two-photon calcium imaging for large scale functional mapping of distinct neuronal populations in the mouse OB, at single cell resolution. Specifically, we imaged odor responses of mitral cells (MCs), tufted cells (TCs) and glomerular interneurons (GL-INs). Mitral cells population activity was heterogeneous and only mildly correlated with the olfactory receptor neuron (ORN) inputs, supporting the view that discrete input maps undergo significant transformations at the output level of the OB. In contrast, population activity profiles of TCs were dense, and highly correlated with the odor inputs in both space and time. Glomerular interneurons were also highly correlated with the ORN inputs, but showed higher activation thresholds suggesting that these neurons are driven by strongly activated glomeruli. Temporally, upon persistent odor exposure, TCs quickly adapted. In contrast, both MCs and GL-INs showed diverse temporal response patterns, suggesting that GL-INs could contribute to the transformations MCs undergo at slow time scales. Our data suggest that sensory odor maps are transformed by TCs and MCs in different ways forming two distinct and parallel information streams.

Design Sensitivity Method for Sampling-Based RBDO with Fixed COV

DTIC Science & Technology

2015-04-29

contours of the input model at initial design d0 and RBDO optimum design dopt are shown. As the limit state functions are not linear and some input...Glasser, M. L., Moore, R. A., and Scott, T. C., 1990, "Evaluation of Classes of Definite Integrals Involving Elementary Functions via...Differentiation of Special Functions," Applicable Algebra in Engineering, Communication and Computing, 1(2), pp. 149-165. [25] Cho, H., Bae, S., Choi, K. K

Inverse optimal design of input-to-state stabilisation for affine nonlinear systems with input delays

NASA Astrophysics Data System (ADS)

Cai, Xiushan; Meng, Lingxin; Zhang, Wei; Liu, Leipo

2018-03-01

We establish robustness of the predictor feedback control law to perturbations appearing at the system input for affine nonlinear systems with time-varying input delay and additive disturbances. Furthermore, it is shown that it is inverse optimal with respect to a differential game problem. All of the stability and inverse optimality proofs are based on the infinite-dimensional backstepping transformation and an appropriate Lyapunov functional. A single-link manipulator subject to input delays and disturbances is given to illustrate the validity of the proposed method.

Designable DNA-binding domains enable construction of logic circuits in mammalian cells.

PubMed

Gaber, Rok; Lebar, Tina; Majerle, Andreja; Šter, Branko; Dobnikar, Andrej; Benčina, Mojca; Jerala, Roman

2014-03-01

Electronic computer circuits consisting of a large number of connected logic gates of the same type, such as NOR, can be easily fabricated and can implement any logic function. In contrast, designed genetic circuits must employ orthogonal information mediators owing to free diffusion within the cell. Combinatorial diversity and orthogonality can be provided by designable DNA- binding domains. Here, we employed the transcription activator-like repressors to optimize the construction of orthogonal functionally complete NOR gates to construct logic circuits. We used transient transfection to implement all 16 two-input logic functions from combinations of the same type of NOR gates within mammalian cells. Additionally, we present a genetic logic circuit where one input is used to select between an AND and OR function to process the data input using the same circuit. This demonstrates the potential of designable modular transcription factors for the construction of complex biological information-processing devices.

User's manual for a parameter identification technique. [with options for model simulation for fixed input forcing functions and identification from wind tunnel and flight measurements

NASA Technical Reports Server (NTRS)

Kanning, G.

1975-01-01

A digital computer program written in FORTRAN is presented that implements the system identification theory for deterministic systems using input-output measurements. The user supplies programs simulating the mathematical model of the physical plant whose parameters are to be identified. The user may choose any one of three options. The first option allows for a complete model simulation for fixed input forcing functions. The second option identifies up to 36 parameters of the model from wind tunnel or flight measurements. The third option performs a sensitivity analysis for up to 36 parameters. The use of each option is illustrated with an example using input-output measurements for a helicopter rotor tested in a wind tunnel.

Input and output constraints-based stabilisation of switched nonlinear systems with unstable subsystems and its application

NASA Astrophysics Data System (ADS)

Chen, Chao; Liu, Qian; Zhao, Jun

2018-01-01

This paper studies the problem of stabilisation of switched nonlinear systems with output and input constraints. We propose a recursive approach to solve this issue. None of the subsystems are assumed to be stablisable while the switched system is stabilised by dual design of controllers for subsystems and a switching law. When only dealing with bounded input, we provide nested switching controllers using an extended backstepping procedure. If both input and output constraints are taken into consideration, a Barrier Lyapunov Function is employed during operation to construct multiple Lyapunov functions for switched nonlinear system in the backstepping procedure. As a practical example, the control design of an equilibrium manifold expansion model of aero-engine is given to demonstrate the effectiveness of the proposed design method.

The Influence of Prosodic Input in the Second Language Classroom: Does It Stimulate Child Acquisition of Word Order and Function Words?

ERIC Educational Resources Information Center

Campfield, Dorota E.; Murphy, Victoria A.

2017-01-01

This paper reports on an intervention study with young Polish beginners (mean age: 8 years, 3 months) learning English at school. It seeks to identify whether exposure to rhythmic input improves knowledge of word order and function words. The "prosodic bootstrapping hypothesis", relevant in developmental psycholinguistics, provided the…

Full wave modulator-demodulator amplifier apparatus. [for generating rectified output signal

NASA Technical Reports Server (NTRS)

Black, J. M. (Inventor)

1974-01-01

A full-wave modulator-demodulator apparatus is described including an operational amplifier having a first input terminal coupled to a circuit input terminal, and a second input terminal alternately coupled to the circuit input terminal. A circuit is ground by a switching circuit responsive to a phase reference signal and the operational amplifier is alternately switched between a non-inverting mode and an inverting mode. The switching circuit includes three field-effect transistors operatively associated to provide the desired switching function in response to an alternating reference signal of the same frequency as an AC input signal applied to the circuit input terminal.

Model Based Predictive Control of Multivariable Hammerstein Processes with Fuzzy Logic Hypercube Interpolated Models

PubMed Central

Coelho, Antonio Augusto Rodrigues

2016-01-01

This paper introduces the Fuzzy Logic Hypercube Interpolator (FLHI) and demonstrates applications in control of multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) processes with Hammerstein nonlinearities. FLHI consists of a Takagi-Sugeno fuzzy inference system where membership functions act as kernel functions of an interpolator. Conjunction of membership functions in an unitary hypercube space enables multivariable interpolation of N-dimensions. Membership functions act as interpolation kernels, such that choice of membership functions determines interpolation characteristics, allowing FLHI to behave as a nearest-neighbor, linear, cubic, spline or Lanczos interpolator, to name a few. The proposed interpolator is presented as a solution to the modeling problem of static nonlinearities since it is capable of modeling both a function and its inverse function. Three study cases from literature are presented, a single-input single-output (SISO) system, a MISO and a MIMO system. Good results are obtained regarding performance metrics such as set-point tracking, control variation and robustness. Results demonstrate applicability of the proposed method in modeling Hammerstein nonlinearities and their inverse functions for implementation of an output compensator with Model Based Predictive Control (MBPC), in particular Dynamic Matrix Control (DMC). PMID:27657723

Numerical Function Generators Using LUT Cascades

DTIC Science & Technology

2007-06-01

either algebraically (for example, sinðxÞ) or as a table of input/ output values. The user defines the numerical function by using the syntax of Scilab ...defined function in Scilab or specify it directly. Note that, by changing the parser of our system, any format can be used for the design entry. First...Methods for Multiple-Valued Input Address Generators,” Proc. 36th IEEE Int’l Symp. Multiple-Valued Logic (ISMVL ’06), May 2006. [29] Scilab 3.0, INRIA-ENPC

Effect of Increased Intensity of Physiotherapy on Patient Outcomes After Stroke: An Economic Literature Review and Cost-Effectiveness Analysis

PubMed Central

Chan, B

2015-01-01

Background Functional improvements have been seen in stroke patients who have received an increased intensity of physiotherapy. This requires additional costs in the form of increased physiotherapist time. Objectives The objective of this economic analysis is to determine the cost-effectiveness of increasing the intensity of physiotherapy (duration and/or frequency) during inpatient rehabilitation after stroke, from the perspective of the Ontario Ministry of Health and Long-term Care. Data Sources The inputs for our economic evaluation were extracted from articles published in peer-reviewed journals and from reports from government sources or the Canadian Stroke Network. Where published data were not available, we sought expert opinion and used inputs based on the experts' estimates. Review Methods The primary outcome we considered was cost per quality-adjusted life-year (QALY). We also evaluated functional strength training because of its similarities to physiotherapy. We used a 2-state Markov model to evaluate the cost-effectiveness of functional strength training and increased physiotherapy intensity for stroke inpatient rehabilitation. The model had a lifetime timeframe with a 5% annual discount rate. We then used sensitivity analyses to evaluate uncertainty in the model inputs. Results We found that functional strength training and higher-intensity physiotherapy resulted in lower costs and improved outcomes over a lifetime. However, our sensitivity analyses revealed high levels of uncertainty in the model inputs, and therefore in the results. Limitations There is a high level of uncertainty in this analysis due to the uncertainty in model inputs, with some of the major inputs based on expert panel consensus or expert opinion. In addition, the utility outcomes were based on a clinical study conducted in the United Kingdom (i.e., 1 study only, and not in an Ontario or Canadian setting). Conclusions Functional strength training and higher-intensity physiotherapy may result in lower costs and improved health outcomes. However, these results should be interpreted with caution. PMID:26366241

Hydrogeologic controls on summer stream temperatures in the McKenzie River basin, Oregon

Treesearch

Christina Tague; Michael Farrell; Gordon Grant; Sarah Lewis; Serge Rey

2007-01-01

Stream temperature is a complex function of energy inputs including solar radiation and latent and sensible heat transfer. In streams where groundwater inputs are significant, energy input through advection can also be an important control on stream temperature. For an individual stream reach, models of stream temperature can take advantage of direct measurement or...

Separation of input function for rapid measurement of quantitative CMRO2 and CBF in a single PET scan with a dual tracer administration method

NASA Astrophysics Data System (ADS)

Kudomi, Nobuyuki; Watabe, Hiroshi; Hayashi, Takuya; Iida, Hidehiro

2007-04-01

Cerebral metabolic rate of oxygen (CMRO2), oxygen extraction fraction (OEF) and cerebral blood flow (CBF) images can be quantified using positron emission tomography (PET) by administrating 15O-labelled water (H152O) and oxygen (15O2). Conventionally, those images are measured with separate scans for three tracers C15O for CBV, H152O for CBF and 15O2 for CMRO2, and there are additional waiting times between the scans in order to minimize the influence of the radioactivity from the previous tracers, which results in a relatively long study period. We have proposed a dual tracer autoradiographic (DARG) approach (Kudomi et al 2005), which enabled us to measure CBF, OEF and CMRO2 rapidly by sequentially administrating H152O and 15O2 within a short time. Because quantitative CBF and CMRO2 values are sensitive to arterial input function, it is necessary to obtain accurate input function and a drawback of this approach is to require separation of the measured arterial blood time-activity curve (TAC) into pure water and oxygen input functions under the existence of residual radioactivity from the first injected tracer. For this separation, frequent manual sampling was required. The present paper describes two calculation methods: namely a linear and a model-based method, to separate the measured arterial TAC into its water and oxygen components. In order to validate these methods, we first generated a blood TAC for the DARG approach by combining the water and oxygen input functions obtained in a series of PET studies on normal human subjects. The combined data were then separated into water and oxygen components by the present methods. CBF and CMRO2 were calculated using those separated input functions and tissue TAC. The quantitative accuracy in the CBF and CMRO2 values by the DARG approach did not exceed the acceptable range, i.e., errors in those values were within 5%, when the area under the curve in the input function of the second tracer was larger than half of the first one. Bias and deviation in those values were also compatible to that of the conventional method, when noise was imposed on the arterial TAC. We concluded that the present calculation based methods could be of use for quantitatively calculating CBF and CMRO2 with the DARG approach.

Hierarchical resilience with lightweight threads.

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

Wheeler, Kyle Bruce

2011-10-01

This paper proposes methodology for providing robustness and resilience for a highly threaded distributed- and shared-memory environment based on well-defined inputs and outputs to lightweight tasks. These inputs and outputs form a failure 'barrier', allowing tasks to be restarted or duplicated as necessary. These barriers must be expanded based on task behavior, such as communication between tasks, but do not prohibit any given behavior. One of the trends in high-performance computing codes seems to be a trend toward self-contained functions that mimic functional programming. Software designers are trending toward a model of software design where their core functions are specifiedmore » in side-effect free or low-side-effect ways, wherein the inputs and outputs of the functions are well-defined. This provides the ability to copy the inputs to wherever they need to be - whether that's the other side of the PCI bus or the other side of the network - do work on that input using local memory, and then copy the outputs back (as needed). This design pattern is popular among new distributed threading environment designs. Such designs include the Barcelona STARS system, distributed OpenMP systems, the Habanero-C and Habanero-Java systems from Vivek Sarkar at Rice University, the HPX/ParalleX model from LSU, as well as our own Scalable Parallel Runtime effort (SPR) and the Trilinos stateless kernels. This design pattern is also shared by CUDA and several OpenMP extensions for GPU-type accelerators (e.g. the PGI OpenMP extensions).« less

Enhanced Response Time of Electrowetting Lenses with Shaped Input Voltage Functions.

PubMed

Supekar, Omkar D; Zohrabi, Mo; Gopinath, Juliet T; Bright, Victor M

2017-05-16

Adaptive optical lenses based on the electrowetting principle are being rapidly implemented in many applications, such as microscopy, remote sensing, displays, and optical communication. To characterize the response of these electrowetting lenses, the dependence upon direct current (DC) driving voltage functions was investigated in a low-viscosity liquid system. Cylindrical lenses with inner diameters of 2.45 and 3.95 mm were used to characterize the dynamic behavior of the liquids under DC voltage electrowetting actuation. With the increase of the rise time of the input exponential driving voltage, the originally underdamped system response can be damped, enabling a smooth response from the lens. We experimentally determined the optimal rise times for the fastest response from the lenses. We have also performed numerical simulations of the lens actuation with input exponential driving voltage to understand the variation in the dynamics of the liquid-liquid interface with various input rise times. We further enhanced the response time of the devices by shaping the input voltage function with multiple exponential rise times. For the 3.95 mm inner diameter lens, we achieved a response time improvement of 29% when compared to the fastest response obtained using single-exponential driving voltage. The technique shows great promise for applications that require fast response times.

DefEX: Hands-On Cyber Defense Exercise for Undergraduate Students

DTIC Science & Technology

2011-07-01

Injection, and 4) File Upload. Next, the students patched the associated flawed Perl and PHP Hypertext Preprocessor ( PHP ) code. Finally, students...underlying script. The Zora XSS vulnerability existed in a PHP file that echoed unfiltered user input back to the screen. To eliminate the...vulnerability, students filtered the input using the PHP htmlentities function and retested the code. The htmlentities function translates certain ambiguous

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.

Variable Delay Element For Jitter Control In High Speed Data Links

DOEpatents

Livolsi, Robert R.

2002-06-11

A circuit and method for decreasing the amount of jitter present at the receiver input of high speed data links which uses a driver circuit for input from a high speed data link which comprises a logic circuit having a first section (1) which provides data latches, a second section (2) which provides a circuit generates a pre-destorted output and for compensating for level dependent jitter having an OR function element and a NOR function element each of which is coupled to two inputs and to a variable delay element as an input which provides a bi-modal delay for pulse width pre-distortion, a third section (3) which provides a muxing circuit, and a forth section (4) for clock distribution in the driver circuit. A fifth section is used for logic testing the driver circuit.

Time delay between the SYMH and the solar wind energy input during intense storms determined by response function analysis

NASA Astrophysics Data System (ADS)

Cao, X.; Du, A.

2014-12-01

We statistically studied the response time of the SYMH to the solar wind energy input ɛ by using the RFA approach. The average response time was 64 minutes. There was no clear trend among these events concerning to the minimum SYMH and storm type. It seems that the response time of magnetosphere to the solar wind energy input is independent on the storm intensity and the solar wind condition. The response function shows one peak even when the solar wind energy input and the SYMH have multi-peak. The response time exhibits as the intrinsic property of the magnetosphere that stands for the typical formation time of the ring current. This may be controlled by magnetospheric temperature, average number density, the oxygen abundance et al.

A five-primary photostimulator suitable for studying intrinsically photosensitive retinal ganglion cell functions in humans

PubMed Central

Cao, Dingcai; Nicandro, Nathaniel; Barrionuevo, Pablo A.

2015-01-01

Intrinsically photosensitive retinal ganglion cells (ipRGCs) can respond to light directly through self-contained photopigment, melanopsin. IpRGCs also receive synaptic inputs from rods and cones. Thus, studying ipRGC functions requires a novel photostimulating method that can account for all of the photoreceptor inputs. Here, we introduced an inexpensive LED-based five-primary photostimulator that can control the excitations of rods, S-, M-, L-cones, and melanopsin-containing ipRGCs in humans at constant background photoreceptor excitation levels, a critical requirement for studying the adaptation behavior of ipRGCs with rod, cone, or melanopsin input. We described the theory and technical aspects (including optics, electronics, software, and calibration) of the five-primary photostimulator. Then we presented two preliminary studies using the photostimulator we have implemented to measure melanopsin-mediated pupil responses and temporal contrast sensitivity function (TCSF). The results showed that the S-cone input to pupil responses was antagonistic to the L-, M- or melanopsin inputs, consistent with an S-OFF and (L + M)-ON response property of primate ipRGCs (Dacey et al., 2005). In addition, the melanopsin-mediated TCSF had a distinctive pattern compared with L + M or S-cone mediated TCSF. Other than controlling individual photoreceptor excitation independently, the five-primary photostimulator has the flexibility in presenting stimuli modulating any combination of photoreceptor excitations, which allows researchers to study the mechanisms by which ipRGCs combine various photoreceptor inputs. PMID:25624466

From free energy to expected energy: Improving energy-based value function approximation in reinforcement learning.

PubMed

Elfwing, Stefan; Uchibe, Eiji; Doya, Kenji

2016-12-01

Free-energy based reinforcement learning (FERL) was proposed for learning in high-dimensional state and action spaces. However, the FERL method does only really work well with binary, or close to binary, state input, where the number of active states is fewer than the number of non-active states. In the FERL method, the value function is approximated by the negative free energy of a restricted Boltzmann machine (RBM). In our earlier study, we demonstrated that the performance and the robustness of the FERL method can be improved by scaling the free energy by a constant that is related to the size of network. In this study, we propose that RBM function approximation can be further improved by approximating the value function by the negative expected energy (EERL), instead of the negative free energy, as well as being able to handle continuous state input. We validate our proposed method by demonstrating that EERL: (1) outperforms FERL, as well as standard neural network and linear function approximation, for three versions of a gridworld task with high-dimensional image state input; (2) achieves new state-of-the-art results in stochastic SZ-Tetris in both model-free and model-based learning settings; and (3) significantly outperforms FERL and standard neural network function approximation for a robot navigation task with raw and noisy RGB images as state input and a large number of actions. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Engine control techniques to account for fuel effects

DOEpatents

Kumar, Shankar; Frazier, Timothy R.; Stanton, Donald W.; Xu, Yi; Bunting, Bruce G.; Wolf, Leslie R.

2014-08-26

A technique for engine control to account for fuel effects including providing an internal combustion engine and a controller to regulate operation thereof, the engine being operable to combust a fuel to produce an exhaust gas; establishing a plurality of fuel property inputs; establishing a plurality of engine performance inputs; generating engine control information as a function of the fuel property inputs and the engine performance inputs; and accessing the engine control information with the controller to regulate at least one engine operating parameter.

Software-hardware complex for the input of telemetric information obtained from rocket studies of the radiation of the earth's upper atmosphere

NASA Astrophysics Data System (ADS)

Bazdrov, I. I.; Bortkevich, V. S.; Khokhlov, V. N.

2004-10-01

This paper describes a software-hardware complex for the input into a personal computer of telemetric information obtained by means of telemetry stations TRAL KR28, RTS-8, and TRAL K2N. Structural and functional diagrams are given of the input device and the hardware complex. Results that characterize the features of the input process and selective data of optical measurements of atmospheric radiation are given. © 2004

High speed high dynamic range high accuracy measurement system

DOEpatents

Deibele, Craig E.; Curry, Douglas E.; Dickson, Richard W.; Xie, Zaipeng

2016-11-29

A measuring system includes an input that emulates a bandpass filter with no signal reflections. A directional coupler connected to the input passes the filtered input to electrically isolated measuring circuits. Each of the measuring circuits includes an amplifier that amplifies the signal through logarithmic functions. The output of the measuring system is an accurate high dynamic range measurement.

Aspects and Some Results on Passivity and Positivity of Dynamic Systems

NASA Astrophysics Data System (ADS)

De la Sen, M.

2017-12-01

This paper is devoted to discuss certain aspects of passivity results in dynamic systems and the characterization of the regenerative systems counterparts. In particular, the various concepts of passivity as standard passivity, strict input passivity, strict output passivity and very strict passivity (i.e. joint strict input and output passivity) are given and related to the existence of a storage function and a dissipation function. Later on, the obtained results are related to external positivity of systems and positivity or strict positivity of the transfer matrices and transfer functions in the time-invariant case. On the other hand, it is discussed how to achieve or how eventually to increase the passivity effects via linear feedback by the synthesis of the appropriate feed-forward or feedback controllers or, simply, by adding a positive parallel direct input-output matrix interconnection gain.

Local and Long-Range Circuit Connections to Hilar Mossy Cells in the Dentate Gyrus

PubMed Central

Sun, Yanjun; Grieco, Steven F.; Holmes, Todd C.

2017-01-01

Abstract Hilar mossy cells are the prominent glutamatergic cell type in the dentate hilus of the dentate gyrus (DG); they have been proposed to have critical roles in the DG network. To better understand how mossy cells contribute to DG function, we have applied new viral genetic and functional circuit mapping approaches to quantitatively map and compare local and long-range circuit connections of mossy cells and dentate granule cells in the mouse. The great majority of inputs to mossy cells consist of two parallel inputs from within the DG: an excitatory input pathway from dentate granule cells and an inhibitory input pathway from local DG inhibitory neurons. Mossy cells also receive a moderate degree of excitatory and inhibitory CA3 input from proximal CA3 subfields. Long range inputs to mossy cells are numerically sparse, and they are only identified readily from the medial septum and the septofimbrial nucleus. In comparison, dentate granule cells receive most of their inputs from the entorhinal cortex. The granule cells receive significant synaptic inputs from the hilus and the medial septum, and they also receive direct inputs from both distal and proximal CA3 subfields, which has been underdescribed in the existing literature. Our slice-based physiological mapping studies further supported the identified circuit connections of mossy cells and granule cells. Together, our data suggest that hilar mossy cells are major local circuit integrators and they exert modulation of the activity of dentate granule cells as well as the CA3 region through “back-projection” pathways. PMID:28451637

Transient Response in a Dendritic Neuron Model for Current Injected at One Branch

PubMed Central

Rinzel, John; Rall, Wilfrid

1974-01-01

Mathematical expressions are obtained for the response function corresponding to an instantaneous pulse of current injected to a single dendritic branch in a branched dendritic neuron model. The theoretical model assumes passive membrane properties and the equivalent cylinder constraint on branch diameters. The response function when used in a convolution formula enables one to compute the voltage transient at any specified point in the dendritic tree for an arbitrary current injection at a given input location. A particular numerical example, for a brief current injection at a branch terminal, illustrates the attenuation and delay characteristics of the depolarization peak as it spreads throughout the neuron model. In contrast to the severe attenuation of voltage transients from branch input sites to the soma, the fraction of total input charge actually delivered to the soma and other trees is calculated to be about one-half. This fraction is independent of the input time course. Other numerical examples, which compare a branch terminal input site with a soma input site, demonstrate that, for a given transient current injection, the peak depolarization is not proportional to the input resistance at the injection site and, for a given synaptic conductance transient, the effective synaptic driving potential can be significantly reduced, resulting in less synaptic current flow and charge, for a branch input site. Also, for the synaptic case, the two inputs are compared on the basis of the excitatory post-synaptic potential (EPSP) seen at the soma and the total charge delivered to the soma. PMID:4424185

Food choice as a key management strategy for functional gastrointestinal symptoms.

PubMed

Gibson, Peter R; Shepherd, Susan J

2012-05-01

Recognition of food components that induce functional gut symptoms in patient's functional bowel disorders (FBD) has been challenging. Food directly or indirectly provides considerable afferent input into the enteric nervous system. There is an altered relationship between the afferent input and perception/efferent response in FBD. Defining the nature of food-related stimuli may provide a means of minimizing such an input and gut symptoms. Using this premise, reducing the intake of FODMAPs (fermentable oligo-, di-, and mono-saccharides and polyols)--poorly absorbed short-chain carbohydrates that, by virtue of their small molecular size and rapid fermentability, will distend the intestinal lumen with liquid and gas--improves symptoms in the majority of patients. Well-developed methodologies to deliver the diet via dietician-led education are available. Another abundant source of afferent input is natural and added food chemicals (such as salicylates, amines, and glutamates). Studies are needed to assess the efficacy of the low food chemical dietary approach. A recent placebo-controlled trial of FODMAP-poor gluten provided the first valid evidence that non-celiac gluten intolerance might actually exist, but its prevalence and underlying mechanisms require elucidation. Food choice via the low FODMAP and potentially other dietary strategies is now a realistic and efficacious therapeutic approach for functional gut symptoms.

The Event Related Brain Potential as an Index of Information Processing, Cognitive Activity, and Skill Acquisition: A Program of Basic Research.

DTIC Science & Technology

1985-02-28

psychophysiological function in question. For example, for most measurements of the cardiovascular system, data are available only at each heart beat ...function of the duration of the charging period, *i . and hence will be proportional to the inter- beat interval (and inversely °°. • .*~* 14 information (0... beat interval. Thus, the output will lag the input. 2.3 Computer Access to Voltage x Time Functions 2.3.1 Digital Input and Analog-to-Digital Conversion

Production Functions for Water Delivery Systems: Analysis and Estimation Using Dual Cost Function and Implicit Price Specifications

NASA Astrophysics Data System (ADS)

Teeples, Ronald; Glyer, David

1987-05-01

Both policy and technical analysis of water delivery systems have been based on cost functions that are inconsistent with or are incomplete representations of the neoclassical production functions of economics. We present a full-featured production function model of water delivery which can be estimated from a multiproduct, dual cost function. The model features implicit prices for own-water inputs and is implemented as a jointly estimated system of input share equations and a translog cost function. Likelihood ratio tests are performed showing that a minimally constrained, full-featured production function is a necessary specification of the water delivery operations in our sample. This, plus the model's highly efficient and economically correct parameter estimates, confirms the usefulness of a production function approach to modeling the economic activities of water delivery systems.

Methods and circuitry for reconfigurable SEU/SET tolerance

NASA Technical Reports Server (NTRS)

Shuler, Jr., Robert L. (Inventor)

2010-01-01

A device is disclosed in one embodiment that has multiple identical sets of programmable functional elements, programmable routing resources, and majority voters that correct errors. The voters accept a mode input for a redundancy mode and a split mode. In the redundancy mode, the programmable functional elements are identical and are programmed identically so the voters produce an output corresponding to the majority of inputs that agree. In a split mode, each voter selects a particular programmable functional element output as the output of the voter. Therefore, in the split mode, the programmable functional elements can perform different functions, operate independently, and/or be connected together to process different parts of the same problem.

Ultra-low input transcriptomics reveal the spore functional content and phylogenetic affiliations of poorly studied arbuscular mycorrhizal fungi

PubMed Central

Beaudet, Denis; Chen, Eric C H; Mathieu, Stephanie; Yildirir, Gokalp; Ndikumana, Steve; Dalpé, Yolande; Séguin, Sylvie; Farinelli, Laurent; Stajich, Jason E; Corradi, Nicolas

2018-01-01

Abstract Arbuscular mycorrhizal fungi (AMF) are a group of soil microorganisms that establish symbioses with the vast majority of land plants. To date, generation of AMF coding information has been limited to model genera that grow well axenically; Rhizoglomus and Gigaspora. Meanwhile, data on the functional gene repertoire of most AMF families is non-existent. Here, we provide primary large-scale transcriptome data from eight poorly studied AMF species (Acaulospora morrowiae, Diversispora versiforme, Scutellospora calospora, Racocetra castanea, Paraglomus brasilianum, Ambispora leptoticha, Claroideoglomus claroideum and Funneliformis mosseae) using ultra-low input ribonucleic acid (RNA)-seq approaches. Our analyses reveals that quiescent spores of many AMF species harbour a diverse functional diversity and solidify known evolutionary relationships within the group. Our findings demonstrate that RNA-seq data obtained from low-input RNA are reliable in comparison to conventional RNA-seq experiments. Thus, our methodology can potentially be used to deepen our understanding of fungal microbial function and phylogeny using minute amounts of RNA material. PMID:29211832

Optimal nonlinear codes for the perception of natural colours.

PubMed

von der Twer, T; MacLeod, D I

2001-08-01

We discuss how visual nonlinearity can be optimized for the precise representation of environmental inputs. Such optimization leads to neural signals with a compressively nonlinear input-output function the gradient of which is matched to the cube root of the probability density function (PDF) of the environmental input values (and not to the PDF directly as in histogram equalization). Comparisons between theory and psychophysical and electrophysiological data are roughly consistent with the idea that parvocellular (P) cells are optimized for precision representation of colour: their contrast-response functions span a range appropriately matched to the environmental distribution of natural colours along each dimension of colour space. Thus P cell codes for colour may have been selected to minimize error in the perceptual estimation of stimulus parameters for natural colours. But magnocellular (M) cells have a much stronger than expected saturating nonlinearity; this supports the view that the function of M cells is mainly to detect boundaries rather than to specify contrast or lightness.

[Application of numerical convolution in in vivo/in vitro correlation research].

PubMed

Yue, Peng

2009-01-01

This paper introduced the conception and principle of in vivo/in vitro correlation (IVIVC) and convolution/deconvolution methods, and elucidated in details the convolution strategy and method for calculating the in vivo absorption performance of the pharmaceutics according to the their pharmacokinetic data in Excel, then put the results forward to IVIVC research. Firstly, the pharmacokinetic data ware fitted by mathematical software to make up the lost points. Secondly, the parameters of the optimal fitted input function were defined by trail-and-error method according to the convolution principle in Excel under the hypothesis that all the input functions fit the Weibull functions. Finally, the IVIVC between in vivo input function and the in vitro dissolution was studied. In the examples, not only the application of this method was demonstrated in details but also its simplicity and effectiveness were proved by comparing with the compartment model method and deconvolution method. It showed to be a powerful tool for IVIVC research.

Method and apparatus for loss of control inhibitor systems

NASA Technical Reports Server (NTRS)

A'Harrah, Ralph C. (Inventor)

2007-01-01

Active and adaptive systems and methods to prevent loss of control incidents by providing tactile feedback to a vehicle operator are disclosed. According to the present invention, an operator gives a control input to an inceptor. An inceptor sensor measures an inceptor input value of the control input. The inceptor input is used as an input to a Steady-State Inceptor Input/Effector Output Model that models the vehicle control system design. A desired effector output from the inceptor input is generated from the model. The desired effector output is compared to an actual effector output to get a distortion metric. A feedback force is generated as a function of the distortion metric. The feedback force is used as an input to a feedback force generator which generates a loss of control inhibitor system (LOCIS) force back to the inceptor. The LOCIS force is felt by the operator through the inceptor.

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.

Noniterative computation of infimum in H(infinity) optimisation for plants with invariant zeros on the j(omega)-axis

NASA Technical Reports Server (NTRS)

Chen, B. M.; Saber, A.

1993-01-01

A simple and noniterative procedure for the computation of the exact value of the infimum in the singular H(infinity)-optimization problem is presented, as a continuation of our earlier work. Our problem formulation is general and we do not place any restrictions in the finite and infinite zero structures of the system, and the direct feedthrough terms between the control input and the controlled output variables and between the disturbance input and the measurement output variables. Our method is applicable to a class of singular H(infinity)-optimization problems for which the transfer functions from the control input to the controlled output and from the disturbance input to the measurement output satisfy certain geometric conditions. In particular, the paper extends the result of earlier work by allowing these two transfer functions to have invariant zeros on the j(omega) axis.

Parallel processing of afferent olfactory sensory information

PubMed Central

Vaaga, Christopher E.

2016-01-01

Key points The functional synaptic connectivity between olfactory receptor neurons and principal cells within the olfactory bulb is not well understood.One view suggests that mitral cells, the primary output neuron of the olfactory bulb, are solely activated by feedforward excitation.Using focal, single glomerular stimulation, we demonstrate that mitral cells receive direct, monosynaptic input from olfactory receptor neurons.Compared to external tufted cells, mitral cells have a prolonged afferent‐evoked EPSC, which serves to amplify the synaptic input.The properties of presynaptic glutamate release from olfactory receptor neurons are similar between mitral and external tufted cells.Our data suggest that afferent input enters the olfactory bulb in a parallel fashion. Abstract Primary olfactory receptor neurons terminate in anatomically and functionally discrete cortical modules known as olfactory bulb glomeruli. The synaptic connectivity and postsynaptic responses of mitral and external tufted cells within the glomerulus may involve both direct and indirect components. For example, it has been suggested that sensory input to mitral cells is indirect through feedforward excitation from external tufted cells. We also observed feedforward excitation of mitral cells with weak stimulation of the olfactory nerve layer; however, focal stimulation of an axon bundle entering an individual glomerulus revealed that mitral cells receive monosynaptic afferent inputs. Although external tufted cells had a 4.1‐fold larger peak EPSC amplitude, integration of the evoked currents showed that the synaptic charge was 5‐fold larger in mitral cells, reflecting the prolonged response in mitral cells. Presynaptic afferents onto mitral and external tufted cells had similar quantal amplitude and release probability, suggesting that the larger peak EPSC in external tufted cells was the result of more synaptic contacts. The results of the present study indicate that the monosynaptic afferent input to mitral cells depends on the strength of odorant stimulation. The enhanced spiking that we observed in response to brief afferent input provides a mechanism for amplifying sensory information and contrasts with the transient response in external tufted cells. These parallel input paths may have discrete functions in processing olfactory sensory input. PMID:27377344

Theory of nonstationary Hawkes processes

NASA Astrophysics Data System (ADS)

Tannenbaum, Neta Ravid; Burak, Yoram

2017-12-01

We expand the theory of Hawkes processes to the nonstationary case, in which the mutually exciting point processes receive time-dependent inputs. We derive an analytical expression for the time-dependent correlations, which can be applied to networks with arbitrary connectivity, and inputs with arbitrary statistics. The expression shows how the network correlations are determined by the interplay between the network topology, the transfer functions relating units within the network, and the pattern and statistics of the external inputs. We illustrate the correlation structure using several examples in which neural network dynamics are modeled as a Hawkes process. In particular, we focus on the interplay between internally and externally generated oscillations and their signatures in the spike and rate correlation functions.

Computer program for single input-output, single-loop feedback systems

NASA Technical Reports Server (NTRS)

1976-01-01

Additional work is reported on a completely automatic computer program for the design of single input/output, single loop feedback systems with parameter uncertainly, to satisfy time domain bounds on the system response to step commands and disturbances. The inputs to the program are basically the specified time-domain response bounds, the form of the constrained plant transfer function and the ranges of the uncertain parameters of the plant. The program output consists of the transfer functions of the two free compensation networks, in the form of the coefficients of the numerator and denominator polynomials, and the data on the prescribed bounds and the extremes actually obtained for the system response to commands and disturbances.

The Construct of Attention in Schizophrenia

PubMed Central

Luck, Steven J.; Gold, James M.

2008-01-01

Schizophrenia is widely thought to involve deficits of attention. However, the term attention can be defined so broadly that impaired performance on virtually any task could be construed as evidence for a deficit in attention, and this has slowed cumulative progress in understanding attention deficits in schizophrenia. To address this problem, we divide the general concept of attention into two distinct constructs: input selection, the selection of task-relevant inputs for further processing; and rule selection, the selective activation of task-appropriate rules. These constructs are closely tied to working memory, because input selection mechanisms are used to control the transfer of information into working memory and because working memory stores the rules used by rule selection mechanisms. These constructs are also closely tied to executive function, because executive systems are used to guide input selection and because rule selection is itself at key aspect of executive function. Within the domain of input selection, it is important to distinguish between the control of selection—the processes that guide attention to task-relevant inputs—and the implementation of selection—the processes that enhance the processing of the relevant inputs and suppress the irrelevant inputs. Current evidence suggests that schizophrenia involves a significant impairment in the control of selection but little or no impairment in the implementation of selection. Consequently, the CNTRICS participants agreed by consensus that attentional control should be a priority target for measurement and treatment research in schizophrenia. PMID:18374901

Input Shaping to Reduce Solar Array Structural Vibrations

NASA Technical Reports Server (NTRS)

Doherty, Michael J.; Tolson, Robert J.

1998-01-01

Structural vibrations induced by actuators can be minimized using input shaping. Input shaping is a feedforward method in which actuator commands are convolved with shaping functions to yield a shaped set of commands. These commands are designed to perform the maneuver while minimizing the residual structural vibration. In this report, input shaping is extended to stepper motor actuators. As a demonstration, an input-shaping technique based on pole-zero cancellation was used to modify the Solar Array Drive Assembly (SADA) actuator commands for the Lewis satellite. A series of impulses were calculated as the ideal SADA output for vibration control. These impulses were then discretized for use by the SADA stepper motor actuator and simulated actuator outputs were used to calculate the structural response. The effectiveness of input shaping is limited by the accuracy of the knowledge of the modal frequencies. Assuming perfect knowledge resulted in significant vibration reduction. Errors of 10% in the modal frequencies caused notably higher levels of vibration. Controller robustness was improved by incorporating additional zeros in the shaping function. The additional zeros did not require increased performance from the actuator. Despite the identification errors, the resulting feedforward controller reduced residual vibrations to the level of the exactly modeled input shaper and well below the baseline cases. These results could be easily applied to many other vibration-sensitive applications involving stepper motor actuators.

Predicting binaural responses from monaural responses in the gerbil medial superior olive

PubMed Central

Plauška, Andrius; Borst, J. Gerard

2016-01-01

Accurate sound source localization of low-frequency sounds in the horizontal plane depends critically on the comparison of arrival times at both ears. A specialized brainstem circuit containing the principal neurons of the medial superior olive (MSO) is dedicated to this comparison. MSO neurons are innervated by segregated inputs from both ears. The coincident arrival of excitatory inputs from both ears is thought to trigger action potentials, with differences in internal delays creating a unique sensitivity to interaural time differences (ITDs) for each cell. How the inputs from both ears are integrated by the MSO neurons is still debated. Using juxtacellular recordings, we tested to what extent MSO neurons from anesthetized Mongolian gerbils function as simple cross-correlators of their bilateral inputs. From the measured subthreshold responses to monaural wideband stimuli we predicted the rate-ITD functions obtained from the same MSO neuron, which have a damped oscillatory shape. The rate of the oscillations and the position of the peaks and troughs were accurately predicted. The amplitude ratio between dominant and secondary peaks of the rate-ITD function, captured in the width of its envelope, was not always exactly reproduced. This minor imperfection pointed to the methodological limitation of using a linear representation of the monaural inputs, which disregards any temporal sharpening occurring in the cochlear nucleus. The successful prediction of the major aspects of rate-ITD curves supports a simple scheme in which the ITD sensitivity of MSO neurons is realized by the coincidence detection of excitatory monaural inputs. PMID:27009164

A Web Browsing System by Eye-gaze Input

NASA Astrophysics Data System (ADS)

Abe, Kiyohiko; Owada, Kosuke; Ohi, Shoichi; Ohyama, Minoru

We have developed an eye-gaze input system for people with severe physical disabilities, such as amyotrophic lateral sclerosis (ALS) patients. This system utilizes a personal computer and a home video camera to detect eye-gaze under natural light. The system detects both vertical and horizontal eye-gaze by simple image analysis, and does not require special image processing units or sensors. We also developed the platform for eye-gaze input based on our system. In this paper, we propose a new web browsing system for physically disabled computer users as an application of the platform for eye-gaze input. The proposed web browsing system uses a method of direct indicator selection. The method categorizes indicators by their function. These indicators are hierarchized relations; users can select the felicitous function by switching indicators group. This system also analyzes the location of selectable object on web page, such as hyperlink, radio button, edit box, etc. This system stores the locations of these objects, in other words, the mouse cursor skips to the object of candidate input. Therefore it enables web browsing at a faster pace.

Investigation of synapse formation and function in a glutamatergic-GABAergic two-neuron microcircuit.

PubMed

Chang, Chia-Ling; Trimbuch, Thorsten; Chao, Hsiao-Tuan; Jordan, Julia-Christine; Herman, Melissa A; Rosenmund, Christian

2014-01-15

Neural circuits are composed of mainly glutamatergic and GABAergic neurons, which communicate through synaptic connections. Many factors instruct the formation and function of these synapses; however, it is difficult to dissect the contribution of intrinsic cell programs from that of extrinsic environmental effects in an intact network. Here, we perform paired recordings from two-neuron microculture preparations of mouse hippocampal glutamatergic and GABAergic neurons to investigate how synaptic input and output of these two principal cells develop. In our reduced preparation, we found that glutamatergic neurons showed no change in synaptic output or input regardless of partner neuron cell type or neuronal activity level. In contrast, we found that glutamatergic input caused the GABAergic neuron to modify its output by way of an increase in synapse formation and a decrease in synaptic release efficiency. These findings are consistent with aspects of GABAergic synapse maturation observed in many brain regions. In addition, changes in GABAergic output are cell wide and not target-cell specific. We also found that glutamatergic neuronal activity determined the AMPA receptor properties of synapses on the partner GABAergic neuron. All modifications of GABAergic input and output required activity of the glutamatergic neuron. Because our system has reduced extrinsic factors, the changes we saw in the GABAergic neuron due to glutamatergic input may reflect initiation of maturation programs that underlie the formation and function of in vivo neural circuits.

Correction of I/Q channel errors without calibration

DOEpatents

Doerry, Armin W.; Tise, Bertice L.

2002-01-01

A method of providing a balanced demodular output for a signal such as a Doppler radar having an analog pulsed input; includes adding a variable phase shift as a function of time to the input signal, applying the phase shifted input signal to a demodulator; and generating a baseband signal from the input signal. The baseband signal is low-pass filtered and converted to a digital output signal. By removing the variable phase shift from the digital output signal, a complex data output is formed that is representative of the output of a balanced demodulator.

Business Process Improvement Applied to Written Temporary Duty Travel Orders within the United States Air Force

DTIC Science & Technology

1993-12-01

Generally Accepted Process While neither DoD Directives nor USAF Regulations specify exact mandatory TDY order processing methods, most USAF units...functional input. Finally, TDY order processing functional experts at Hanscom, Los Angeles and McClellan AFBs provided inputs based on their experiences...current electronic auditing capabilities. 81 DTPS Initiative. This DFAS-initiated action to standardize TDY order processing throughout DoD is currently

A single-layer platform for Boolean logic and arithmetic through DNA excision in mammalian cells

PubMed Central

Weinberg, Benjamin H.; Hang Pham, N. T.; Caraballo, Leidy D.; Lozanoski, Thomas; Engel, Adrien; Bhatia, Swapnil; Wong, Wilson W.

2017-01-01

Genetic circuits engineered for mammalian cells often require extensive fine-tuning to perform their intended functions. To overcome this problem, we present a generalizable biocomputing platform that can engineer genetic circuits which function in human cells with minimal optimization. We used our Boolean Logic and Arithmetic through DNA Excision (BLADE) platform to build more than 100 multi-input-multi-output circuits. We devised a quantitative metric to evaluate the performance of the circuits in human embryonic kidney and Jurkat T cells. Of 113 circuits analysed, 109 functioned (96.5%) with the correct specified behavior without any optimization. We used our platform to build a three-input, two-output Full Adder and six-input, one-output Boolean Logic Look Up Table. We also used BLADE to design circuits with temporal small molecule-mediated inducible control and circuits that incorporate CRISPR/Cas9 to regulate endogenous mammalian genes. PMID:28346402

Emergence of binocular functional properties in a monocular neural circuit

PubMed Central

Ramdya, Pavan; Engert, Florian

2010-01-01

Sensory circuits frequently integrate converging inputs while maintaining precise functional relationships between them. For example, in mammals with stereopsis, neurons at the first stages of binocular visual processing show a close alignment of receptive-field properties for each eye. Still, basic questions about the global wiring mechanisms that enable this functional alignment remain unanswered, including whether the addition of a second retinal input to an otherwise monocular neural circuit is sufficient for the emergence of these binocular properties. We addressed this question by inducing a de novo binocular retinal projection to the larval zebrafish optic tectum and examining recipient neuronal populations using in vivo two-photon calcium imaging. Notably, neurons in rewired tecta were predominantly binocular and showed matching direction selectivity for each eye. We found that a model based on local inhibitory circuitry that computes direction selectivity using the topographic structure of both retinal inputs can account for the emergence of this binocular feature. PMID:19160507

Convergence and objective functions of some fault/noise-injection-based online learning algorithms for RBF networks.

PubMed

Ho, Kevin I-J; Leung, Chi-Sing; Sum, John

2010-06-01

In the last two decades, many online fault/noise injection algorithms have been developed to attain a fault tolerant neural network. However, not much theoretical works related to their convergence and objective functions have been reported. This paper studies six common fault/noise-injection-based online learning algorithms for radial basis function (RBF) networks, namely 1) injecting additive input noise, 2) injecting additive/multiplicative weight noise, 3) injecting multiplicative node noise, 4) injecting multiweight fault (random disconnection of weights), 5) injecting multinode fault during training, and 6) weight decay with injecting multinode fault. Based on the Gladyshev theorem, we show that the convergence of these six online algorithms is almost sure. Moreover, their true objective functions being minimized are derived. For injecting additive input noise during training, the objective function is identical to that of the Tikhonov regularizer approach. For injecting additive/multiplicative weight noise during training, the objective function is the simple mean square training error. Thus, injecting additive/multiplicative weight noise during training cannot improve the fault tolerance of an RBF network. Similar to injective additive input noise, the objective functions of other fault/noise-injection-based online algorithms contain a mean square error term and a specialized regularization term.

Determining A Purely Symbolic Transfer Function from Symbol Streams: Theory and Algorithms

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

Griffin, Christopher H

Transfer function modeling is a \\emph{standard technique} in classical Linear Time Invariant and Statistical Process Control. The work of Box and Jenkins was seminal in developing methods for identifying parameters associated with classicalmore » $(r,s,k)$$ transfer functions. Discrete event systems are often \\emph{used} for modeling hybrid control structures and high-level decision problems. \\emph{Examples include} discrete time, discrete strategy repeated games. For these games, a \\emph{discrete transfer function in the form of} an accurate hidden Markov model of input-output relations \\emph{could be used to derive optimal response strategies.} In this paper, we develop an algorithm \\emph{for} creating probabilistic \\textit{Mealy machines} that act as transfer function models for discrete event dynamic systems (DEDS). Our models are defined by three parameters, $$(l_1, l_2, k)$ just as the Box-Jenkins transfer function models. Here $$l_1$$ is the maximal input history lengths to consider, $$l_2$$ is the maximal output history lengths to consider and $k$ is the response lag. Using related results, We show that our Mealy machine transfer functions are optimal in the sense that they maximize the mutual information between the current known state of the DEDS and the next observed input/output pair.« less

Novel view synthesis by interpolation over sparse examples

NASA Astrophysics Data System (ADS)

Liang, Bodong; Chung, Ronald C.

2006-01-01

Novel view synthesis (NVS) is an important problem in image rendering. It involves synthesizing an image of a scene at any specified (novel) viewpoint, given some images of the scene at a few sample viewpoints. The general understanding is that the solution should bypass explicit 3-D reconstruction of the scene. As it is, the problem has a natural tie to interpolation, despite that mainstream efforts on the problem have been adopting formulations otherwise. Interpolation is about finding the output of a function f(x) for any specified input x, given a few input-output pairs {(xi,fi):i=1,2,3,...,n} of the function. If the input x is the viewpoint, and f(x) is the image, the interpolation problem becomes exactly NVS. We treat the NVS problem using the interpolation formulation. In particular, we adopt the example-based everything or interpolation (EBI) mechanism-an established mechanism for interpolating or learning functions from examples. EBI has all the desirable properties of a good interpolation: all given input-output examples are satisfied exactly, and the interpolation is smooth with minimum oscillations between the examples. We point out that EBI, however, has difficulty in interpolating certain classes of functions, including the image function in the NVS problem. We propose an extension of the mechanism for overcoming the limitation. We also present how the extended interpolation mechanism could be used to synthesize images at novel viewpoints. Real image results show that the mechanism has promising performance, even with very few example images.

Application of genetic algorithms to tuning fuzzy control systems

NASA Technical Reports Server (NTRS)

Espy, Todd; Vombrack, Endre; Aldridge, Jack

1993-01-01

Real number genetic algorithms (GA) were applied for tuning fuzzy membership functions of three controller applications. The first application is our 'Fuzzy Pong' demonstration, a controller that controls a very responsive system. The performance of the automatically tuned membership functions exceeded that of manually tuned membership functions both when the algorithm started with randomly generated functions and with the best manually-tuned functions. The second GA tunes input membership functions to achieve a specified control surface. The third application is a practical one, a motor controller for a printed circuit manufacturing system. The GA alters the positions and overlaps of the membership functions to accomplish the tuning. The applications, the real number GA approach, the fitness function and population parameters, and the performance improvements achieved are discussed. Directions for further research in tuning input and output membership functions and in tuning fuzzy rules are described.

A Within-subjects Experimental Protocol to Assess the Effects of Social Input on Infant EEG.

PubMed

St John, Ashley M; Kao, Katie; Chita-Tegmark, Meia; Liederman, Jacqueline; Grieve, Philip G; Tarullo, Amanda R

2017-05-03

Despite the importance of social interactions for infant brain development, little research has assessed functional neural activation while infants socially interact. Electroencephalography (EEG) power is an advantageous technique to assess infant functional neural activation. However, many studies record infant EEG only during one baseline condition. This protocol describes a paradigm that is designed to comprehensively assess infant EEG activity in both social and nonsocial contexts as well as tease apart how different types of social inputs differentially relate to infant EEG. The within-subjects paradigm includes four controlled conditions. In the nonsocial condition, infants view objects on computer screens. The joint attention condition involves an experimenter directing the infant's attention to pictures. The joint attention condition includes three types of social input: language, face-to-face interaction, and the presence of joint attention. Differences in infant EEG between the nonsocial and joint attention conditions could be due to any of these three types of input. Therefore, two additional conditions (one with language input while the experimenter is hidden behind a screen and one with face-to-face interaction) were included to assess the driving contextual factors in patterns of infant neural activation. Representative results demonstrate that infant EEG power varied by condition, both overall and differentially by brain region, supporting the functional nature of infant EEG power. This technique is advantageous in that it includes conditions that are clearly social or nonsocial and allows for examination of how specific types of social input relate to EEG power. This paradigm can be used to assess how individual differences in age, affect, socioeconomic status, and parent-infant interaction quality relate to the development of the social brain. Based on the demonstrated functional nature of infant EEG power, future studies should consider the role of EEG recording context and design conditions that are clearly social or nonsocial.

Evaluation of limited blood sampling population input approaches for kinetic quantification of [18F]fluorothymidine PET data.

PubMed

Contractor, Kaiyumars B; Kenny, Laura M; Coombes, Charles R; Turkheimer, Federico E; Aboagye, Eric O; Rosso, Lula

2012-03-24

Quantification of kinetic parameters of positron emission tomography (PET) imaging agents normally requires collecting arterial blood samples which is inconvenient for patients and difficult to implement in routine clinical practice. The aim of this study was to investigate whether a population-based input function (POP-IF) reliant on only a few individual discrete samples allows accurate estimates of tumour proliferation using [18F]fluorothymidine (FLT). Thirty-six historical FLT-PET data with concurrent arterial sampling were available for this study. A population average of baseline scans blood data was constructed using leave-one-out cross-validation for each scan and used in conjunction with individual blood samples. Three limited sampling protocols were investigated including, respectively, only seven (POP-IF7), five (POP-IF5) and three (POP-IF3) discrete samples of the historical dataset. Additionally, using the three-point protocol, we derived a POP-IF3M, the only input function which was not corrected for the fraction of radiolabelled metabolites present in blood. The kinetic parameter for net FLT retention at steady state, Ki, was derived using the modified Patlak plot and compared with the original full arterial set for validation. Small percentage differences in the area under the curve between all the POP-IFs and full arterial sampling IF was found over 60 min (4.2%-5.7%), while there were, as expected, larger differences in the peak position and peak height.A high correlation between Ki values calculated using the original arterial input function and all the population-derived IFs was observed (R2 = 0.85-0.98). The population-based input showed good intra-subject reproducibility of Ki values (R2 = 0.81-0.94) and good correlation (R2 = 0.60-0.85) with Ki-67. Input functions generated using these simplified protocols over scan duration of 60 min estimate net PET-FLT retention with reasonable accuracy.

IGDS/TRAP Interface Program (ITIP). Detailed Design Specification (DDS). [network flow diagrams for coal gasification studies

NASA Technical Reports Server (NTRS)

Jefferys, S.; Johnson, W.; Lewis, R.; Rich, R.

1981-01-01

The software modules which comprise the IGDS/TRAP Interface Program are described. A hierarchical input processing output (HIPO) chart for each user command is given. The description consists of: (1) function of the user command; (2) calling sequence; (3) moduls which call this use command; (4) modules called by this user command; (5) IGDS commands used by this user command; and (6) local usage of global registers. Each HIPO contains the principal functions performed within the module. Also included with each function are a list of the inputs which may be required to perform the function and a list of the outputs which may be created as a result of performing the function.

About influence of input rate random part of nonstationary queue system on statistical estimates of its macroscopic indicators

NASA Astrophysics Data System (ADS)

Korelin, Ivan A.; Porshnev, Sergey V.

2018-05-01

A model of the non-stationary queuing system (NQS) is described. The input of this model receives a flow of requests with input rate λ = λdet (t) + λrnd (t), where λdet (t) is a deterministic function depending on time; λrnd (t) is a random function. The parameters of functions λdet (t), λrnd (t) were identified on the basis of statistical information on visitor flows collected from various Russian football stadiums. The statistical modeling of NQS is carried out and the average statistical dependences are obtained: the length of the queue of requests waiting for service, the average wait time for the service, the number of visitors entered to the stadium on the time. It is shown that these dependencies can be characterized by the following parameters: the number of visitors who entered at the time of the match; time required to service all incoming visitors; the maximum value; the argument value when the studied dependence reaches its maximum value. The dependences of these parameters on the energy ratio of the deterministic and random component of the input rate are investigated.

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.

Dual-afferent sensory input training for voluntary movement after stroke: A pilot randomized controlled study.

PubMed

Bae, Seahyun; Kim, Kyung-Yoon

2017-01-01

Stimulation through afferent sensory input is necessary to improve voluntary functional movement in stroke patients. Dual-afferent sensory input, which combines electromyography-triggered functional electric stimulation (ETFES) and action observation, was investigated to determine its effects on voluntary movements in stroke patients. This study was conducted on 18 patients with left hemiplegia diagnosed between 6 and 24 months prior. The 9 subjects in the dual-afferent sensory input (DASI) group underwent ETFES with action observation training for 4 weeks (20 min/d, 5 d/wk), while the 9 control group subjects underwent functional electric stimulation (FES) for the same duration. The outcome measures were the movement-related cortical potential (MRCP), H-reflex, electromyography (EMG), and balance. The control and DASI groups showed significant increases in MRCP, muscle activity, and balance, while H-reflex was significantly decreased. MRCP and balance showed significant differences between DASI and control groups. DASI stimulates voluntary movement in patients, causes rapid activation of the cerebral cortex, and reduces excessive excitation of spinal motor neurons. Therefore, DASI, which stimulates voluntary movement, has a greater effect on brain activation in stroke patients.

Measurement of myocardial blood flow by cardiovascular magnetic resonance perfusion: comparison of distributed parameter and Fermi models with single and dual bolus.

PubMed

Papanastasiou, Giorgos; Williams, Michelle C; Kershaw, Lucy E; Dweck, Marc R; Alam, Shirjel; Mirsadraee, Saeed; Connell, Martin; Gray, Calum; MacGillivray, Tom; Newby, David E; Semple, Scott Ik

2015-02-17

Mathematical modeling of cardiovascular magnetic resonance perfusion data allows absolute quantification of myocardial blood flow. Saturation of left ventricle signal during standard contrast administration can compromise the input function used when applying these models. This saturation effect is evident during application of standard Fermi models in single bolus perfusion data. Dual bolus injection protocols have been suggested to eliminate saturation but are much less practical in the clinical setting. The distributed parameter model can also be used for absolute quantification but has not been applied in patients with coronary artery disease. We assessed whether distributed parameter modeling might be less dependent on arterial input function saturation than Fermi modeling in healthy volunteers. We validated the accuracy of each model in detecting reduced myocardial blood flow in stenotic vessels versus gold-standard invasive methods. Eight healthy subjects were scanned using a dual bolus cardiac perfusion protocol at 3T. We performed both single and dual bolus analysis of these data using the distributed parameter and Fermi models. For the dual bolus analysis, a scaled pre-bolus arterial input function was used. In single bolus analysis, the arterial input function was extracted from the main bolus. We also performed analysis using both models of single bolus data obtained from five patients with coronary artery disease and findings were compared against independent invasive coronary angiography and fractional flow reserve. Statistical significance was defined as two-sided P value < 0.05. Fermi models overestimated myocardial blood flow in healthy volunteers due to arterial input function saturation in single bolus analysis compared to dual bolus analysis (P < 0.05). No difference was observed in these volunteers when applying distributed parameter-myocardial blood flow between single and dual bolus analysis. In patients, distributed parameter modeling was able to detect reduced myocardial blood flow at stress (<2.5 mL/min/mL of tissue) in all 12 stenotic vessels compared to only 9 for Fermi modeling. Comparison of single bolus versus dual bolus values suggests that distributed parameter modeling is less dependent on arterial input function saturation than Fermi modeling. Distributed parameter modeling showed excellent accuracy in detecting reduced myocardial blood flow in all stenotic vessels.

Magnetic tunnel junction based spintronic logic devices

NASA Astrophysics Data System (ADS)

Lyle, Andrew Paul

The International Technology Roadmap for Semiconductors (ITRS) predicts that complimentary metal oxide semiconductor (CMOS) based technologies will hit their last generation on or near the 16 nm node, which we expect to reach by the year 2025. Thus future advances in computational power will not be realized from ever-shrinking device sizes, but rather by 'outside the box' designs and new physics, including molecular or DNA based computation, organics, magnonics, or spintronic. This dissertation investigates magnetic logic devices for post-CMOS computation. Three different architectures were studied, each relying on a different magnetic mechanism to compute logic functions. Each design has it benefits and challenges that must be overcome. This dissertation focuses on pushing each design from the drawing board to a realistic logic technology. The first logic architecture is based on electrically connected magnetic tunnel junctions (MTJs) that allow direct communication between elements without intermediate sensing amplifiers. Two and three input logic gates, which consist of two and three MTJs connected in parallel, respectively were fabricated and are compared. The direct communication is realized by electrically connecting the output in series with the input and applying voltage across the series connections. The logic gates rely on the fact that a change in resistance at the input modulates the voltage that is needed to supply the critical current for spin transfer torque switching the output. The change in resistance at the input resulted in a voltage margin of 50--200 mV and 250--300 mV for the closest input states for the three and two input designs, respectively. The two input logic gate realizes the AND, NAND, NOR, and OR logic functions. The three input logic function realizes the Majority, AND, NAND, NOR, and OR logic operations. The second logic architecture utilizes magnetostatically coupled nanomagnets to compute logic functions, which is the basis of Magnetic Quantum Cellular Automata (MQCA). MQCA has the potential to be thousands of times more energy efficient than CMOS technology. While interesting, these systems are academic unless they can be interfaced into current technologies. This dissertation pushed past a major hurdle by experimentally demonstrating a spintronic input/output (I/O) interface for the magnetostatically coupled nanomagnets by incorporating MTJs. This spintronic interface allows individual nanomagnets to be programmed using spin transfer torque and read using magneto resistance structure. Additionally the spintronic interface allows statistical data on the reliability of the magnetic coupling utilized for data propagation to be easily measured. The integration of spintronics and MQCA for an electrical interface to achieve a magnetic logic device with low power creates a competitive post-CMOS logic device. The final logic architecture that was studied used MTJs to compute logic functions and magnetic domain walls to communicate between gates. Simulations were used to optimize the design of this architecture. Spin transfer torque was used to compute logic function at each MTJ gate and was used to drive the domain walls. The design demonstrated that multiple nanochannels could be connected to each MTJ to realize fan-out from the logic gates. As a result this logic scheme eliminates the need for intermediate reads and conversions to pass information from one logic gate to another.

Replacing Fortran Namelists with JSON

NASA Astrophysics Data System (ADS)

Robinson, T. E., Jr.

2017-12-01

Maintaining a log of input parameters for a climate model is very important to understanding potential causes for answer changes during the development stages. Additionally, since modern Fortran is now interoperable with C, a more modern approach to software infrastructure to include code written in C is necessary. Merging these two separate facets of climate modeling requires a quality control for monitoring changes to input parameters and model defaults that can work with both Fortran and C. JSON will soon replace namelists as the preferred key/value pair input in the GFDL model. By adding a JSON parser written in C into the model, the input can be used by all functions and subroutines in the model, errors can be handled by the model instead of by the internal namelist parser, and the values can be output into a single file that is easily parsable by readily available tools. Input JSON files can handle all of the functionality of a namelist while being portable between C and Fortran. Fortran wrappers using unlimited polymorphism are crucial to allow for simple and compact code which avoids the need for many subroutines contained in an interface. Errors can be handled with more detail by providing information about location of syntax errors or typos. The output JSON provides a ground truth for values that the model actually uses by providing not only the values loaded through the input JSON, but also any default values that were not included. This kind of quality control on model input is crucial for maintaining reproducibility and understanding any answer changes resulting from changes in the input.

Optimal control of LQR for discrete time-varying systems with input delays

NASA Astrophysics Data System (ADS)

Yin, Yue-Zhu; Yang, Zhong-Lian; Yin, Zhi-Xiang; Xu, Feng

2018-04-01

In this work, we consider the optimal control problem of linear quadratic regulation for discrete time-variant systems with single input and multiple input delays. An innovative and simple method to derive the optimal controller is given. The studied problem is first equivalently converted into a problem subject to a constraint condition. Last, with the established duality, the problem is transformed into a static mathematical optimisation problem without input delays. The optimal control input solution to minimise performance index function is derived by solving this optimisation problem with two methods. A numerical simulation example is carried out and its results show that our two approaches are both feasible and very effective.

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

Speech versus manual control of camera functions during a telerobotic task

NASA Technical Reports Server (NTRS)

Bierschwale, John M.; Sampaio, Carlos E.; Stuart, Mark A.; Smith, Randy L.

1993-01-01

This investigation has evaluated the voice-commanded camera control concept. For this particular task, total voice control of continuous and discrete camera functions was significantly slower than manual control. There was no significant difference between voice and manual input for several types of errors. There was not a clear trend in subjective preference of camera command input modality. Task performance, in terms of both accuracy and speed, was very similar across both levels of experience.

Mechanisms of information decoding in a cascade system of gene expression

NASA Astrophysics Data System (ADS)

Wang, Haohua; Yuan, Zhanjiang; Liu, Peijiang; Zhou, Tianshou

2016-05-01

Biotechnology advances have allowed investigation of heterogeneity of cellular responses to stimuli on the single-cell level. Functionally, this heterogeneity can compromise cellular responses to environmental signals, and it can also enlarge the repertoire of possible cellular responses and hence increase the adaptive nature of cellular behaviors. However, the mechanism of how this response heterogeneity is generated remains elusive. Here, by systematically analyzing a representative cellular signaling system, we show that (1) the upstream activator always amplifies the downstream burst frequency (BF) but the noiseless activator performs better than the noisy one, remarkably for small or moderate input signal strengths, and the repressor always reduces the downstream BF but the difference in the reducing effect between noiseless and noise repressors is very small; (2) both the downstream burst size and mRNA mean are a monotonically increasing function of the activator strength but a monotonically decreasing function of the repressor strength; (3) for repressor-type input, there is a noisy signal strength such that the downstream mRNA noise arrives at an optimal level, but for activator-type input, the output noise intensity is fundamentally a monotonically decreasing function of the input strength. Our results reveal the essential mechanisms of both signal information decoding and cellular response heterogeneity, whereas our analysis provides a paradigm for analyzing dynamics of noisy biochemical signaling systems.

Distinct pattern separation related transfer functions in human CA3/dentate and CA1 revealed using high-resolution fMRI and variable mnemonic similarity

PubMed Central

Lacy, Joyce W.; Yassa, Michael A.; Stark, Shauna M.; Muftuler, L. Tugan; Stark, Craig E.L.

2011-01-01

Producing and maintaining distinct (orthogonal) neural representations for similar events is critical to avoiding interference in long-term memory. Recently, our laboratory provided the first evidence for separation-like signals in the human CA3/dentate. Here, we extended this by parametrically varying the change in input (similarity) while monitoring CA1 and CA3/dentate for separation and completion-like signals using high-resolution fMRI. In the CA1, activity varied in a graded fashion in response to increases in the change in input. In contrast, the CA3/dentate showed a stepwise transfer function that was highly sensitive to small changes in input. PMID:21164173

Input-current shaped ac to dc converters

NASA Technical Reports Server (NTRS)

1986-01-01

The problem of achieving near unity power factor while supplying power to a dc load from a single phase ac source of power is examined. Power processors for this application must perform three functions: input current shaping, energy storage, and output voltage regulation. The methods available for performing each of these three functions are reviewed. Input current shaping methods are either active or passive, with the active methods divided into buck-like and boost-like techniques. In addition to large reactances, energy storage methods include resonant filters, active filters, and active storage schemes. Fast voltage regulation can be achieved by post regulation or by supplementing the current shaping topology with an extra switch. Some indications of which methods are best suited for particular applications concludes the discussion.

Tuning fuzzy PD and PI controllers using reinforcement learning.

PubMed

Boubertakh, Hamid; Tadjine, Mohamed; Glorennec, Pierre-Yves; Labiod, Salim

2010-10-01

In this paper, we propose a new auto-tuning fuzzy PD and PI controllers using reinforcement Q-learning (QL) algorithm for SISO (single-input single-output) and TITO (two-input two-output) systems. We first, investigate the design parameters and settings of a typical class of Fuzzy PD (FPD) and Fuzzy PI (FPI) controllers: zero-order Takagi-Sugeno controllers with equidistant triangular membership functions for inputs, equidistant singleton membership functions for output, Larsen's implication method, and average sum defuzzification method. Secondly, the analytical structures of these typical fuzzy PD and PI controllers are compared to their classical counterpart PD and PI controllers. Finally, the effectiveness of the proposed method is proven through simulation examples. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Robust adaptive fuzzy tracking control for pure-feedback stochastic nonlinear systems with input constraints.

PubMed

Wang, Huanqing; Chen, Bing; Liu, Xiaoping; Liu, Kefu; Lin, Chong

2013-12-01

This paper is concerned with the problem of adaptive fuzzy tracking control for a class of pure-feedback stochastic nonlinear systems with input saturation. To overcome the design difficulty from nondifferential saturation nonlinearity, a smooth nonlinear function of the control input signal is first introduced to approximate the saturation function; then, an adaptive fuzzy tracking controller based on the mean-value theorem is constructed by using backstepping technique. The proposed adaptive fuzzy controller guarantees that all signals in the closed-loop system are bounded in probability and the system output eventually converges to a small neighborhood of the desired reference signal in the sense of mean quartic value. Simulation results further illustrate the effectiveness of the proposed control scheme.

Strategies for mapping synaptic inputs on dendrites in vivo by combining two-photon microscopy, sharp intracellular recording, and pharmacology

PubMed Central

Levy, Manuel; Schramm, Adrien E.; Kara, Prakash

2012-01-01

Uncovering the functional properties of individual synaptic inputs on single neurons is critical for understanding the computational role of synapses and dendrites. Previous studies combined whole-cell patch recording to load neurons with a fluorescent calcium indicator and two-photon imaging to map subcellular changes in fluorescence upon sensory stimulation. By hyperpolarizing the neuron below spike threshold, the patch electrode ensured that changes in fluorescence associated with synaptic events were isolated from those caused by back-propagating action potentials. This technique holds promise for determining whether the existence of unique cortical feature maps across different species may be associated with distinct wiring diagrams. However, the use of whole-cell patch for mapping inputs on dendrites is challenging in large mammals, due to brain pulsations and the accumulation of fluorescent dye in the extracellular milieu. Alternatively, sharp intracellular electrodes have been used to label neurons with fluorescent dyes, but the current passing capabilities of these high impedance electrodes may be insufficient to prevent spiking. In this study, we tested whether sharp electrode recording is suitable for mapping functional inputs on dendrites in the cat visual cortex. We compared three different strategies for suppressing visually evoked spikes: (1) hyperpolarization by intracellular current injection, (2) pharmacological blockade of voltage-gated sodium channels by intracellular QX-314, and (3) GABA iontophoresis from a perisomatic electrode glued to the intracellular electrode. We found that functional inputs on dendrites could be successfully imaged using all three strategies. However, the best method for preventing spikes was GABA iontophoresis with low currents (5–10 nA), which minimally affected the local circuit. Our methods advance the possibility of determining functional connectivity in preparations where whole-cell patch may be impractical. PMID:23248588

Synaptic inputs from stroke-injured brain to grafted human stem cell-derived neurons activated by sensory stimuli.

PubMed

Tornero, Daniel; Tsupykov, Oleg; Granmo, Marcus; Rodriguez, Cristina; Grønning-Hansen, Marita; Thelin, Jonas; Smozhanik, Ekaterina; Laterza, Cecilia; Wattananit, Somsak; Ge, Ruimin; Tatarishvili, Jemal; Grealish, Shane; Brüstle, Oliver; Skibo, Galina; Parmar, Malin; Schouenborg, Jens; Lindvall, Olle; Kokaia, Zaal

2017-03-01

Transplanted neurons derived from stem cells have been proposed to improve function in animal models of human disease by various mechanisms such as neuronal replacement. However, whether the grafted neurons receive functional synaptic inputs from the recipient's brain and integrate into host neural circuitry is unknown. Here we studied the synaptic inputs from the host brain to grafted cortical neurons derived from human induced pluripotent stem cells after transplantation into stroke-injured rat cerebral cortex. Using the rabies virus-based trans-synaptic tracing method and immunoelectron microscopy, we demonstrate that the grafted neurons receive direct synaptic inputs from neurons in different host brain areas located in a pattern similar to that of neurons projecting to the corresponding endogenous cortical neurons in the intact brain. Electrophysiological in vivo recordings from the cortical implants show that physiological sensory stimuli, i.e. cutaneous stimulation of nose and paw, can activate or inhibit spontaneous activity in grafted neurons, indicating that at least some of the afferent inputs are functional. In agreement, we find using patch-clamp recordings that a portion of grafted neurons respond to photostimulation of virally transfected, channelrhodopsin-2-expressing thalamo-cortical axons in acute brain slices. The present study demonstrates, for the first time, that the host brain regulates the activity of grafted neurons, providing strong evidence that transplanted human induced pluripotent stem cell-derived cortical neurons can become incorporated into injured cortical circuitry. Our findings support the idea that these neurons could contribute to functional recovery in stroke and other conditions causing neuronal loss in cerebral cortex. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Cell-type specific circuit connectivity of hippocampal CA1 revealed through Cre-dependent rabies tracing

PubMed Central

Sun, Yanjun; Nguyen, Amanda; Nguyen, Joseph; Le, Luc; Saur, Dieter; Choi, Jiwon; Callaway, Edward M.; Xu, Xiangmin

2014-01-01

Summary We applied a new Cre-dependent, genetically modified rabies-based tracing system to map direct synaptic connections to CA1 excitatory and inhibitory neuron types in mouse hippocampus. We found common inputs to excitatory and inhibitory CA1 neurons from CA3, CA2, entorhinal cortex and the medial septum (MS), and unexpectedly also from the subiculum. Excitatory CA1 neurons receive inputs from both cholinergic and GABAergic MS neurons while inhibitory CA1 neurons receive a great majority of input from GABAergic MS neurons; both cell types also receive weaker input from glutamatergic MS neurons. Comparisons of inputs to CA1 PV+ interneurons versus SOM+ interneurons showed similar strengths of input from the subiculum, but PV+ interneurons receive much stronger input than SOM+ neurons from CA3, entorhinal cortex and MS. Differential input from CA3 to specific CA1 cell types was also demonstrated functionally using laser scanning photostimulation and whole cell recordings. PMID:24656815

Haptic over visual information in the distribution of visual attention after tool-use in near and far space.

PubMed

Park, George D; Reed, Catherine L

2015-10-01

Despite attentional prioritization for grasping space near the hands, tool-use appears to transfer attentional bias to the tool's end/functional part. The contributions of haptic and visual inputs to attentional distribution along a tool were investigated as a function of tool-use in near (Experiment 1) and far (Experiment 2) space. Visual attention was assessed with a 50/50, go/no-go, target discrimination task, while a tool was held next to targets appearing near the tool-occupied hand or tool-end. Target response times (RTs) and sensitivity (d-prime) were measured at target locations, before and after functional tool practice for three conditions: (1) open-tool: tool-end visible (visual + haptic inputs), (2) hidden-tool: tool-end visually obscured (haptic input only), and (3) short-tool: stick missing tool's length/end (control condition: hand occupied but no visual/haptic input). In near space, both open- and hidden-tool groups showed a tool-end, attentional bias (faster RTs toward tool-end) before practice; after practice, RTs near the hand improved. In far space, the open-tool group showed no bias before practice; after practice, target RTs near the tool-end improved. However, the hidden-tool group showed a consistent tool-end bias despite practice. Lack of short-tool group results suggested that hidden-tool group results were specific to haptic inputs. In conclusion, (1) allocation of visual attention along a tool due to tool practice differs in near and far space, and (2) visual attention is drawn toward the tool's end even when visually obscured, suggesting haptic input provides sufficient information for directing attention along the tool.

DialBetics With a Multimedia Food Recording Tool, FoodLog: Smartphone-Based Self-Management for Type 2 Diabetes.

PubMed

Waki, Kayo; Aizawa, Kiyoharu; Kato, Shigeko; Fujita, Hideo; Lee, Hanae; Kobayashi, Haruka; Ogawa, Makoto; Mouri, Keisuke; Kadowaki, Takashi; Ohe, Kazuhiko

2015-05-01

Diabetes self-management education is an essential element of diabetes care. Systems based on information and communication technology (ICT) for supporting lifestyle modification and self-management of diabetes are promising tools for helping patients better cope with diabetes. An earlier study had determined that diet improved and HbA1c declined for the patients who had used DialBetics during a 3-month randomized clinical trial. The objective of the current study was to test a more patient-friendly version of DialBetics, whose development was based on the original participants' feedback about the previous version of DialBetics. DialBetics comprises 4 modules: data transmission, evaluation, exercise input, and food recording and dietary evaluation. Food recording uses a multimedia food record, FoodLog. A 1-week pilot study was designed to determine if usability and compliance improved over the previous version, especially with the new meal-input function. In the earlier 3-month, diet-evaluation study, HbA1c had declined a significant 0.4% among those who used DialBetics compared with the control group. In the current 1-week study, input of meal photos was higher than with the previous version (84.8 ± 13.2% vs 77.1% ± 35.1% in the first 2 weeks of the 3-month trial). Interviews after the 1-week study showed that 4 of the 5 participants thought the meal-input function improved; the fifth found input easier, but did not consider the result an improvement. DialBetics with FoodLog was shown to be an effective and convenient tool, its new meal-photo input function helping provide patients with real-time support for diet modification. © 2015 Diabetes Technology Society.

DialBetics With a Multimedia Food Recording Tool, FoodLog

PubMed Central

Waki, Kayo; Aizawa, Kiyoharu; Kato, Shigeko; Fujita, Hideo; Lee, Hanae; Kobayashi, Haruka; Ogawa, Makoto; Mouri, Keisuke; Kadowaki, Takashi; Ohe, Kazuhiko

2015-01-01

Background: Diabetes self-management education is an essential element of diabetes care. Systems based on information and communication technology (ICT) for supporting lifestyle modification and self-management of diabetes are promising tools for helping patients better cope with diabetes. An earlier study had determined that diet improved and HbA1c declined for the patients who had used DialBetics during a 3-month randomized clinical trial. The objective of the current study was to test a more patient-friendly version of DialBetics, whose development was based on the original participants’ feedback about the previous version of DialBetics. Method: DialBetics comprises 4 modules: data transmission, evaluation, exercise input, and food recording and dietary evaluation. Food recording uses a multimedia food record, FoodLog. A 1-week pilot study was designed to determine if usability and compliance improved over the previous version, especially with the new meal-input function. Results: In the earlier 3-month, diet-evaluation study, HbA1c had declined a significant 0.4% among those who used DialBetics compared with the control group. In the current 1-week study, input of meal photos was higher than with the previous version (84.8 ± 13.2% vs 77.1% ± 35.1% in the first 2 weeks of the 3-month trial). Interviews after the 1-week study showed that 4 of the 5 participants thought the meal-input function improved; the fifth found input easier, but did not consider the result an improvement. Conclusions: DialBetics with FoodLog was shown to be an effective and convenient tool, its new meal-photo input function helping provide patients with real-time support for diet modification. PMID:25883164

Photovoltaic power system tests on an 8-kilowatt single-phase line-commutated inverter

NASA Technical Reports Server (NTRS)

Stover, J. B.

1978-01-01

Efficiency and power factor were measured as functions of solar array voltage and current. The effects of input shunt capacitance and series inductance were determined. Tests were conducted from 15 to 75 percent of the 8 kW rated inverter input power. Measured efficiencies ranged from 76 percent to 88 percent at about 50 percent of rated inverter input power. Power factor ranged from 36 percent to 72 percent.

Phasic Firing in Vasopressin Cells: Understanding Its Functional Significance through Computational Models

PubMed Central

MacGregor, Duncan J.; Leng, Gareth

2012-01-01

Vasopressin neurons, responding to input generated by osmotic pressure, use an intrinsic mechanism to shift from slow irregular firing to a distinct phasic pattern, consisting of long bursts and silences lasting tens of seconds. With increased input, bursts lengthen, eventually shifting to continuous firing. The phasic activity remains asynchronous across the cells and is not reflected in the population output signal. Here we have used a computational vasopressin neuron model to investigate the functional significance of the phasic firing pattern. We generated a concise model of the synaptic input driven spike firing mechanism that gives a close quantitative match to vasopressin neuron spike activity recorded in vivo, tested against endogenous activity and experimental interventions. The integrate-and-fire based model provides a simple physiological explanation of the phasic firing mechanism involving an activity-dependent slow depolarising afterpotential (DAP) generated by a calcium-inactivated potassium leak current. This is modulated by the slower, opposing, action of activity-dependent dendritic dynorphin release, which inactivates the DAP, the opposing effects generating successive periods of bursting and silence. Model cells are not spontaneously active, but fire when perturbed by random perturbations mimicking synaptic input. We constructed one population of such phasic neurons, and another population of similar cells but which lacked the ability to fire phasically. We then studied how these two populations differed in the way that they encoded changes in afferent inputs. By comparison with the non-phasic population, the phasic population responds linearly to increases in tonic synaptic input. Non-phasic cells respond to transient elevations in synaptic input in a way that strongly depends on background activity levels, phasic cells in a way that is independent of background levels, and show a similar strong linearization of the response. These findings show large differences in information coding between the populations, and apparent functional advantages of asynchronous phasic firing. PMID:23093929

Reconfigurable Fault Tolerance for FPGAs

NASA Technical Reports Server (NTRS)

Shuler, Robert, Jr.

2010-01-01

The invention allows a field-programmable gate array (FPGA) or similar device to be efficiently reconfigured in whole or in part to provide higher capacity, non-redundant operation. The redundant device consists of functional units such as adders or multipliers, configuration memory for the functional units, a programmable routing method, configuration memory for the routing method, and various other features such as block RAM, I/O (random access memory, input/output) capability, dedicated carry logic, etc. The redundant device has three identical sets of functional units and routing resources and majority voters that correct errors. The configuration memory may or may not be redundant, depending on need. For example, SRAM-based FPGAs will need some type of radiation-tolerant configuration memory, or they will need triple-redundant configuration memory. Flash or anti-fuse devices will generally not need redundant configuration memory. Some means of loading and verifying the configuration memory is also required. These are all components of the pre-existing redundant FPGA. This innovation modifies the voter to accept a MODE input, which specifies whether ordinary voting is to occur, or if redundancy is to be split. Generally, additional routing resources will also be required to pass data between sections of the device created by splitting the redundancy. In redundancy mode, the voters produce an output corresponding to the two inputs that agree, in the usual fashion. In the split mode, the voters select just one input and convey this to the output, ignoring the other inputs. In a dual-redundant system (as opposed to triple-redundant), instead of a voter, there is some means to latch or gate a state update only when both inputs agree. In this case, the invention would require modification of the latch or gate so that it would operate normally in redundant mode, and would separately latch or gate the inputs in non-redundant mode.

Organization of dopamine and serotonin system: Anatomical and functional mapping of monosynaptic inputs using rabies virus.

PubMed

Ogawa, Sachie K; Watabe-Uchida, Mitsuko

2017-05-02

Dopamine and serotonin play critical roles in flexible behaviors and are related to various psychiatric and motor disorders. This paper reviews the global organization of dopamine and serotonin systems through recent findings using a modified rabies virus. We first introduce methods for comprehensive mapping of monosynaptic inputs. We then describe quantitative comparisons across the data regarding monosynaptic inputs to dopamine neurons versus serotonin neurons. There is surprising similarity between the input to dopamine neurons in the ventral tegmental area (VTA) and the input to serotonin neurons in the dorsal raphe (DR), suggesting functional interactions between these systems. We next introduce studies of mapping monosynaptic inputs to subpopulations of dopamine neurons specified by their projection targets. It was found that the population of dopamine neurons that project to the tail of the striatum (TS) forms an anatomically distinct outlier, suggesting a unique function. From these series of anatomical studies, we propose that there are three information flows that regulate these neuromodulatory systems: the midline stream to serotonin neurons in median raphe (MR) and B6, the central stream to value-coding dopamine neurons and serotonin neurons in rostral DR, and the lateral stream to TS-projecting dopamine neurons. Finally we introduce a new approach to investigate firing patterns of monosynaptic inputs to dopamine neurons in behaving animals. Combining anatomical and physiological findings, we propose that within the central stream, dopamine neurons broadcast a central teaching signal rather than personal teaching signals to multiple brain areas, which are computed in a redundant way in multi-layered neural circuits. Examination of global organization of the dopamine and serotonin circuits not only revealed the complexity of the systems but also revealed some principles of their organization. We will also discuss limitations, practical issues and the possibility of future improvements of the rabies virus-mediated tracing system. Copyright © 2017 Elsevier Inc. All rights reserved.

Ultra-low input transcriptomics reveal the spore functional content and phylogenetic affiliations of poorly studied arbuscular mycorrhizal fungi.

PubMed

Beaudet, Denis; Chen, Eric C H; Mathieu, Stephanie; Yildirir, Gokalp; Ndikumana, Steve; Dalpé, Yolande; Séguin, Sylvie; Farinelli, Laurent; Stajich, Jason E; Corradi, Nicolas

2017-12-02

Arbuscular mycorrhizal fungi (AMF) are a group of soil microorganisms that establish symbioses with the vast majority of land plants. To date, generation of AMF coding information has been limited to model genera that grow well axenically; Rhizoglomus and Gigaspora. Meanwhile, data on the functional gene repertoire of most AMF families is non-existent. Here, we provide primary large-scale transcriptome data from eight poorly studied AMF species (Acaulospora morrowiae, Diversispora versiforme, Scutellospora calospora, Racocetra castanea, Paraglomus brasilianum, Ambispora leptoticha, Claroideoglomus claroideum and Funneliformis mosseae) using ultra-low input ribonucleic acid (RNA)-seq approaches. Our analyses reveals that quiescent spores of many AMF species harbour a diverse functional diversity and solidify known evolutionary relationships within the group. Our findings demonstrate that RNA-seq data obtained from low-input RNA are reliable in comparison to conventional RNA-seq experiments. Thus, our methodology can potentially be used to deepen our understanding of fungal microbial function and phylogeny using minute amounts of RNA material. © The Author 2017. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Generalization and capacity of extensively large two-layered perceptrons.

PubMed

Rosen-Zvi, Michal; Engel, Andreas; Kanter, Ido

2002-09-01

The generalization ability and storage capacity of a treelike two-layered neural network with a number of hidden units scaling as the input dimension is examined. The mapping from the input to the hidden layer is via Boolean functions; the mapping from the hidden layer to the output is done by a perceptron. The analysis is within the replica framework where an order parameter characterizing the overlap between two networks in the combined space of Boolean functions and hidden-to-output couplings is introduced. The maximal capacity of such networks is found to scale linearly with the logarithm of the number of Boolean functions per hidden unit. The generalization process exhibits a first-order phase transition from poor to perfect learning for the case of discrete hidden-to-output couplings. The critical number of examples per input dimension, alpha(c), at which the transition occurs, again scales linearly with the logarithm of the number of Boolean functions. In the case of continuous hidden-to-output couplings, the generalization error decreases according to the same power law as for the perceptron, with the prefactor being different.

Implementing wavelet inverse-transform processor with surface acoustic wave device.

PubMed

Lu, Wenke; Zhu, Changchun; Liu, Qinghong; Zhang, Jingduan

2013-02-01

The objective of this research was to investigate the implementation schemes of the wavelet inverse-transform processor using surface acoustic wave (SAW) device, the length function of defining the electrodes, and the possibility of solving the load resistance and the internal resistance for the wavelet inverse-transform processor using SAW device. In this paper, we investigate the implementation schemes of the wavelet inverse-transform processor using SAW device. In the implementation scheme that the input interdigital transducer (IDT) and output IDT stand in a line, because the electrode-overlap envelope of the input IDT is identical with the one of the output IDT (i.e. the two transducers are identical), the product of the input IDT's frequency response and the output IDT's frequency response can be implemented, so that the wavelet inverse-transform processor can be fabricated. X-112(0)Y LiTaO(3) is used as a substrate material to fabricate the wavelet inverse-transform processor. The size of the wavelet inverse-transform processor using this implementation scheme is small, so its cost is low. First, according to the envelope function of the wavelet function, the length function of the electrodes is defined, then, the lengths of the electrodes can be calculated from the length function of the electrodes, finally, the input IDT and output IDT can be designed according to the lengths and widths for the electrodes. In this paper, we also present the load resistance and the internal resistance as the two problems of the wavelet inverse-transform processor using SAW devices. The solutions to these problems are achieved in this study. When the amplifiers are subjected to the input end and output end for the wavelet inverse-transform processor, they can eliminate the influence of the load resistance and the internal resistance on the output voltage of the wavelet inverse-transform processor using SAW device. Copyright © 2012 Elsevier B.V. All rights reserved.

Generalized compliant motion primitive

NASA Technical Reports Server (NTRS)

Backes, Paul G. (Inventor)

1994-01-01

This invention relates to a general primitive for controlling a telerobot with a set of input parameters. The primitive includes a trajectory generator; a teleoperation sensor; a joint limit generator; a force setpoint generator; a dither function generator, which produces telerobot motion inputs in a common coordinate frame for simultaneous combination in sensor summers. Virtual return spring motion input is provided by a restoration spring subsystem. The novel features of this invention include use of a single general motion primitive at a remote site to permit the shared and supervisory control of the robot manipulator to perform tasks via a remotely transferred input parameter set.

Automated method for relating regional pulmonary structure and function: integration of dynamic multislice CT and thin-slice high-resolution CT

NASA Astrophysics Data System (ADS)

Tajik, Jehangir K.; Kugelmass, Steven D.; Hoffman, Eric A.

1993-07-01

We have developed a method utilizing x-ray CT for relating pulmonary perfusion to global and regional anatomy, allowing for detailed study of structure to function relationships. A thick slice, high temporal resolution mode is used to follow a bolus contrast agent for blood flow evaluation and is fused with a high spatial resolution, thin slice mode to obtain structure- function detail. To aid analysis of blood flow, we have developed a software module, for our image analysis package (VIDA), to produce the combined structure-function image. Color coded images representing blood flow, mean transit time, regional tissue content, regional blood volume, regional air content, etc. are generated and imbedded in the high resolution volume image. A text file containing these values along with a voxel's 3-D coordinates is also generated. User input can be minimized to identifying the location of the pulmonary artery from which the input function to a blood flow model is derived. Any flow model utilizing one input and one output function can be easily added to a user selectable list. We present examples from our physiologic based research findings to demonstrate the strengths of combining dynamic CT and HRCT relative to other scanning modalities to uniquely characterize pulmonary normal and pathophysiology.

Robustness, evolvability, and the logic of genetic regulation.

PubMed

Payne, Joshua L; Moore, Jason H; Wagner, Andreas

2014-01-01

In gene regulatory circuits, the expression of individual genes is commonly modulated by a set of regulating gene products, which bind to a gene's cis-regulatory region. This region encodes an input-output function, referred to as signal-integration logic, that maps a specific combination of regulatory signals (inputs) to a particular expression state (output) of a gene. The space of all possible signal-integration functions is vast and the mapping from input to output is many-to-one: For the same set of inputs, many functions (genotypes) yield the same expression output (phenotype). Here, we exhaustively enumerate the set of signal-integration functions that yield identical gene expression patterns within a computational model of gene regulatory circuits. Our goal is to characterize the relationship between robustness and evolvability in the signal-integration space of regulatory circuits, and to understand how these properties vary between the genotypic and phenotypic scales. Among other results, we find that the distributions of genotypic robustness are skewed, so that the majority of signal-integration functions are robust to perturbation. We show that the connected set of genotypes that make up a given phenotype are constrained to specific regions of the space of all possible signal-integration functions, but that as the distance between genotypes increases, so does their capacity for unique innovations. In addition, we find that robust phenotypes are (i) evolvable, (ii) easily identified by random mutation, and (iii) mutationally biased toward other robust phenotypes. We explore the implications of these latter observations for mutation-based evolution by conducting random walks between randomly chosen source and target phenotypes. We demonstrate that the time required to identify the target phenotype is independent of the properties of the source phenotype.

Robustness, Evolvability, and the Logic of Genetic Regulation

PubMed Central

Moore, Jason H.; Wagner, Andreas

2014-01-01

In gene regulatory circuits, the expression of individual genes is commonly modulated by a set of regulating gene products, which bind to a gene’s cis-regulatory region. This region encodes an input-output function, referred to as signal-integration logic, that maps a specific combination of regulatory signals (inputs) to a particular expression state (output) of a gene. The space of all possible signal-integration functions is vast and the mapping from input to output is many-to-one: for the same set of inputs, many functions (genotypes) yield the same expression output (phenotype). Here, we exhaustively enumerate the set of signal-integration functions that yield idential gene expression patterns within a computational model of gene regulatory circuits. Our goal is to characterize the relationship between robustness and evolvability in the signal-integration space of regulatory circuits, and to understand how these properties vary between the genotypic and phenotypic scales. Among other results, we find that the distributions of genotypic robustness are skewed, such that the majority of signal-integration functions are robust to perturbation. We show that the connected set of genotypes that make up a given phenotype are constrained to specific regions of the space of all possible signal-integration functions, but that as the distance between genotypes increases, so does their capacity for unique innovations. In addition, we find that robust phenotypes are (i) evolvable, (ii) easily identified by random mutation, and (iii) mutationally biased toward other robust phenotypes. We explore the implications of these latter observations for mutation-based evolution by conducting random walks between randomly chosen source and target phenotypes. We demonstrate that the time required to identify the target phenotype is independent of the properties of the source phenotype. PMID:23373974

Biophotonic logic devices based on quantum dots and temporally-staggered Förster energy transfer relays

NASA Astrophysics Data System (ADS)

Claussen, Jonathan C.; Algar, W. Russ; Hildebrandt, Niko; Susumu, Kimihiro; Ancona, Mario G.; Medintz, Igor L.

2013-11-01

Integrating photonic inputs/outputs into unimolecular logic devices can provide significantly increased functional complexity and the ability to expand the repertoire of available operations. Here, we build upon a system previously utilized for biosensing to assemble and prototype several increasingly sophisticated biophotonic logic devices that function based upon multistep Förster resonance energy transfer (FRET) relays. The core system combines a central semiconductor quantum dot (QD) nanoplatform with a long-lifetime Tb complex FRET donor and a near-IR organic fluorophore acceptor; the latter acts as two unique inputs for the QD-based device. The Tb complex allows for a form of temporal memory by providing unique access to a time-delayed modality as an alternate output which significantly increases the inherent computing options. Altering the device by controlling the configuration parameters with biologically based self-assembly provides input control while monitoring changes in emission output of all participants, in both a spectral and temporal-dependent manner, gives rise to two input, single output Boolean Logic operations including OR, AND, INHIBIT, XOR, NOR, NAND, along with the possibility of gate transitions. Incorporation of an enzymatic cleavage step provides for a set-reset function that can be implemented repeatedly with the same building blocks and is demonstrated with single input, single output YES and NOT gates. Potential applications for these devices are discussed in the context of their constituent parts and the richness of available signal.

Biophotonic logic devices based on quantum dots and temporally-staggered Förster energy transfer relays.

PubMed

Claussen, Jonathan C; Algar, W Russ; Hildebrandt, Niko; Susumu, Kimihiro; Ancona, Mario G; Medintz, Igor L

2013-12-21

Integrating photonic inputs/outputs into unimolecular logic devices can provide significantly increased functional complexity and the ability to expand the repertoire of available operations. Here, we build upon a system previously utilized for biosensing to assemble and prototype several increasingly sophisticated biophotonic logic devices that function based upon multistep Förster resonance energy transfer (FRET) relays. The core system combines a central semiconductor quantum dot (QD) nanoplatform with a long-lifetime Tb complex FRET donor and a near-IR organic fluorophore acceptor; the latter acts as two unique inputs for the QD-based device. The Tb complex allows for a form of temporal memory by providing unique access to a time-delayed modality as an alternate output which significantly increases the inherent computing options. Altering the device by controlling the configuration parameters with biologically based self-assembly provides input control while monitoring changes in emission output of all participants, in both a spectral and temporal-dependent manner, gives rise to two input, single output Boolean Logic operations including OR, AND, INHIBIT, XOR, NOR, NAND, along with the possibility of gate transitions. Incorporation of an enzymatic cleavage step provides for a set-reset function that can be implemented repeatedly with the same building blocks and is demonstrated with single input, single output YES and NOT gates. Potential applications for these devices are discussed in the context of their constituent parts and the richness of available signal.

The area centralis in the chicken retina contains efferent target amacrine cells

PubMed Central

Weller, Cynthia; Lindstrom, Sarah H.; De Grip, Willem J.; Wilson, Martin

2012-01-01

The retinas of birds receive a substantial efferent, or centrifugal, input from a midbrain nucleus. The function of this input is presently unclear but previous work in the pigeon has shown that efferent input is excluded from the area centralis, suggesting that the functions of the area centralis and the efferent system are incompatible. Using an antibody specific to rods, we have identified the area centralis in another species, the chicken, and mapped the distribution of the unique amacrine cells that are the postsynaptic partners of efferent fibers. Efferent target amacrine cells are found within the chicken area centralis and their density is continuous across the border of the area centralis. In contrast to the pigeon retina then, we conclude that the chicken area centralis receives efferent input. We suggest that the difference between the 2 species is attributable to the presence of a fovea within the area centralis of the pigeon and its absence from that of the chicken. PMID:19296862

Integrate-and-fire models with an almost periodic input function

NASA Astrophysics Data System (ADS)

Kasprzak, Piotr; Nawrocki, Adam; Signerska-Rynkowska, Justyna

2018-02-01

We investigate leaky integrate-and-fire models (LIF models for short) driven by Stepanov and μ-almost periodic functions. Special attention is paid to the properties of the firing map and its displacement, which give information about the spiking behavior of the considered system. We provide conditions under which such maps are well-defined and are uniformly continuous. We show that the LIF models with Stepanov almost periodic inputs have uniformly almost periodic displacements. We also show that in the case of μ-almost periodic drives it may happen that the displacement map is uniformly continuous, but is not μ-almost periodic (and thus cannot be Stepanov or uniformly almost periodic). By allowing discontinuous inputs, we extend some previous results, showing, for example, that the firing rate for the LIF models with Stepanov almost periodic input exists and is unique. This is a starting point for the investigation of the dynamics of almost-periodically driven integrate-and-fire systems.

Generalization of some hidden subgroup algorithms for input sets of arbitrary size

NASA Astrophysics Data System (ADS)

Poslu, Damla; Say, A. C. Cem

2006-05-01

We consider the problem of generalizing some quantum algorithms so that they will work on input domains whose cardinalities are not necessarily powers of two. When analyzing the algorithms we assume that generating superpositions of arbitrary subsets of basis states whose cardinalities are not necessarily powers of two perfectly is possible. We have taken Ballhysa's model as a template and have extended it to Chi, Kim and Lee's generalizations of the Deutsch-Jozsa algorithm and to Simon's algorithm. With perfectly equal superpositions of input sets of arbitrary size, Chi, Kim and Lee's generalized Deutsch-Jozsa algorithms, both for evenly-distributed and evenly-balanced functions, worked with one-sided error property. For Simon's algorithm the success probability of the generalized algorithm is the same as that of the original for input sets of arbitrary cardinalities with equiprobable superpositions, since the property that the measured strings are all those which have dot product zero with the string we search, for the case where the function is 2-to-1, is not lost.

Maximally informative pairwise interactions in networks

PubMed Central

Fitzgerald, Jeffrey D.; Sharpee, Tatyana O.

2010-01-01

Several types of biological networks have recently been shown to be accurately described by a maximum entropy model with pairwise interactions, also known as the Ising model. Here we present an approach for finding the optimal mappings between input signals and network states that allow the network to convey the maximal information about input signals drawn from a given distribution. This mapping also produces a set of linear equations for calculating the optimal Ising-model coupling constants, as well as geometric properties that indicate the applicability of the pairwise Ising model. We show that the optimal pairwise interactions are on average zero for Gaussian and uniformly distributed inputs, whereas they are nonzero for inputs approximating those in natural environments. These nonzero network interactions are predicted to increase in strength as the noise in the response functions of each network node increases. This approach also suggests ways for how interactions with unmeasured parts of the network can be inferred from the parameters of response functions for the measured network nodes. PMID:19905153

Optimization of autoregressive, exogenous inputs-based typhoon inundation forecasting models using a multi-objective genetic algorithm

NASA Astrophysics Data System (ADS)

Ouyang, Huei-Tau

2017-07-01

Three types of model for forecasting inundation levels during typhoons were optimized: the linear autoregressive model with exogenous inputs (LARX), the nonlinear autoregressive model with exogenous inputs with wavelet function (NLARX-W) and the nonlinear autoregressive model with exogenous inputs with sigmoid function (NLARX-S). The forecast performance was evaluated by three indices: coefficient of efficiency, error in peak water level and relative time shift. Historical typhoon data were used to establish water-level forecasting models that satisfy all three objectives. A multi-objective genetic algorithm was employed to search for the Pareto-optimal model set that satisfies all three objectives and select the ideal models for the three indices. Findings showed that the optimized nonlinear models (NLARX-W and NLARX-S) outperformed the linear model (LARX). Among the nonlinear models, the optimized NLARX-W model achieved a more balanced performance on the three indices than the NLARX-S models and is recommended for inundation forecasting during typhoons.

Partial information decomposition as a unified approach to the specification of neural goal functions.

PubMed

Wibral, Michael; Priesemann, Viola; Kay, Jim W; Lizier, Joseph T; Phillips, William A

2017-03-01

In many neural systems anatomical motifs are present repeatedly, but despite their structural similarity they can serve very different tasks. A prime example for such a motif is the canonical microcircuit of six-layered neo-cortex, which is repeated across cortical areas, and is involved in a number of different tasks (e.g. sensory, cognitive, or motor tasks). This observation has spawned interest in finding a common underlying principle, a 'goal function', of information processing implemented in this structure. By definition such a goal function, if universal, cannot be cast in processing-domain specific language (e.g. 'edge filtering', 'working memory'). Thus, to formulate such a principle, we have to use a domain-independent framework. Information theory offers such a framework. However, while the classical framework of information theory focuses on the relation between one input and one output (Shannon's mutual information), we argue that neural information processing crucially depends on the combination of multiple inputs to create the output of a processor. To account for this, we use a very recent extension of Shannon Information theory, called partial information decomposition (PID). PID allows to quantify the information that several inputs provide individually (unique information), redundantly (shared information) or only jointly (synergistic information) about the output. First, we review the framework of PID. Then we apply it to reevaluate and analyze several earlier proposals of information theoretic neural goal functions (predictive coding, infomax and coherent infomax, efficient coding). We find that PID allows to compare these goal functions in a common framework, and also provides a versatile approach to design new goal functions from first principles. Building on this, we design and analyze a novel goal function, called 'coding with synergy', which builds on combining external input and prior knowledge in a synergistic manner. We suggest that this novel goal function may be highly useful in neural information processing. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Higher order visual input to the mushroom bodies in the bee, Bombus impatiens.

PubMed

Paulk, Angelique C; Gronenberg, Wulfila

2008-11-01

To produce appropriate behaviors based on biologically relevant associations, sensory pathways conveying different modalities are integrated by higher-order central brain structures, such as insect mushroom bodies. To address this function of sensory integration, we characterized the structure and response of optic lobe (OL) neurons projecting to the calyces of the mushroom bodies in bees. Bees are well known for their visual learning and memory capabilities and their brains possess major direct visual input from the optic lobes to the mushroom bodies. To functionally characterize these visual inputs to the mushroom bodies, we recorded intracellularly from neurons in bumblebees (Apidae: Bombus impatiens) and a single neuron in a honeybee (Apidae: Apis mellifera) while presenting color and motion stimuli. All of the mushroom body input neurons were color sensitive while a subset was motion sensitive. Additionally, most of the mushroom body input neurons would respond to the first, but not to subsequent, presentations of repeated stimuli. In general, the medulla or lobula neurons projecting to the calyx signaled specific chromatic, temporal, and motion features of the visual world to the mushroom bodies, which included sensory information required for the biologically relevant associations bees form during foraging tasks.

Incorporating engine health monitoring capability into the SSME Block II controller

NASA Astrophysics Data System (ADS)

Clarke, James W.; Copa, Roderick J.

An account is given of the architecture of the SSME's Block II controller's architecture, its incorporation of smart input electronics (SIE), and the potential benefits of this technology in SSME health-monitoring capabilities. SIE allows the Block II controller to conduct its control functions while simultaneously furnishing the computational capabilities and sensor input interface for any newly defined health-monitoring functions. It is expected that the SIE technology may be directly transferred to any follow-on engine design.

Standards application and development plan for solar thermal technologies

NASA Astrophysics Data System (ADS)

Cobb, H. R. W.

1981-07-01

Functional and standards matrices, developed from input from ST users and from the industry that will be continually reviewed and updated as commercial aspects develop are presented. The matrices highlight codes, standards, test methods, functions and definitions that need to be developed. They will be submitted through ANSI for development by national consensus bodies. A contingency action is proposed for standards development if specific input is lacking at the committee level or if early development of a standard would hasten commercialization or gain needed jurisdictional acceptance.

Ride quality flight testing

NASA Technical Reports Server (NTRS)

Swaim, R. L.

1978-01-01

The ride quality experienced by passengers is a function of airframe rigid-body, elastic dynamic responses, autopilot, and stability augmentation system control inputs. A frequency response method has been developed to select sinusoidal elevator input time histories yielding vertical load factor distributions, within a given limit, as a function of fuselage station. The numerical technique is illustrated by applying two-degree-of-freedom short-period and first symmetric mode equations of motion to a B-1 aircraft at Mach 0.85 during sea level flight conditions.

Activity and function recognition for moving and static objects in urban environments from wide-area persistent surveillance inputs

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Bobick, Aaron; Jones, Eric

2010-04-01

In this paper, we describe results from experimental analysis of a model designed to recognize activities and functions of moving and static objects from low-resolution wide-area video inputs. Our model is based on representing the activities and functions using three variables: (i) time; (ii) space; and (iii) structures. The activity and function recognition is achieved by imposing lexical, syntactic, and semantic constraints on the lower-level event sequences. In the reported research, we have evaluated the utility and sensitivity of several algorithms derived from natural language processing and pattern recognition domains. We achieved high recognition accuracy for a wide range of activity and function types in the experiments using Electro-Optical (EO) imagery collected by Wide Area Airborne Surveillance (WAAS) platform.

Emotion and the Cardiovascular System: Postulated Role of Inputs From the Medial Prefrontal Cortex to the Dorsolateral Periaqueductal Gray.

PubMed

Dampney, Roger

2018-01-01

The midbrain periaqueductal gray (PAG) plays a major role in generating different types of behavioral responses to emotional stressors. This review focuses on the role of the dorsolateral (dl) portion of the PAG, which on the basis of anatomical and functional studies, appears to have a unique and distinctive role in generating behavioral, cardiovascular and respiratory responses to real and perceived emotional stressors. In particular, the dlPAG, but not other parts of the PAG, receives direct inputs from the primary auditory cortex and from the secondary visual cortex. In addition, there are strong direct inputs to the dlPAG, but not other parts of the PAG, from regions within the medial prefrontal cortex that in primates correspond to cortical areas 10 m, 25 and 32. I first summarise the evidence that the inputs to the dlPAG arising from visual, auditory and olfactory signals trigger defensive behavioral responses supported by appropriate cardiovascular and respiratory effects, when such signals indicate the presence of a real external threat, such as the presence of a predator. I then consider the functional roles of the direct inputs from the medial prefrontal cortex, and propose the hypothesis that these inputs are activated by perceived threats, that are generated as a consequence of complex cognitive processes. I further propose that the inputs from areas 10 m, 25 and 32 are activated under different circumstances. The input from cortical area 10 m is of special interest, because this cortical area exists only in primates and is much larger in the brain of humans than in all other primates.

Emotion and the Cardiovascular System: Postulated Role of Inputs From the Medial Prefrontal Cortex to the Dorsolateral Periaqueductal Gray

PubMed Central

Dampney, Roger

2018-01-01

The midbrain periaqueductal gray (PAG) plays a major role in generating different types of behavioral responses to emotional stressors. This review focuses on the role of the dorsolateral (dl) portion of the PAG, which on the basis of anatomical and functional studies, appears to have a unique and distinctive role in generating behavioral, cardiovascular and respiratory responses to real and perceived emotional stressors. In particular, the dlPAG, but not other parts of the PAG, receives direct inputs from the primary auditory cortex and from the secondary visual cortex. In addition, there are strong direct inputs to the dlPAG, but not other parts of the PAG, from regions within the medial prefrontal cortex that in primates correspond to cortical areas 10 m, 25 and 32. I first summarise the evidence that the inputs to the dlPAG arising from visual, auditory and olfactory signals trigger defensive behavioral responses supported by appropriate cardiovascular and respiratory effects, when such signals indicate the presence of a real external threat, such as the presence of a predator. I then consider the functional roles of the direct inputs from the medial prefrontal cortex, and propose the hypothesis that these inputs are activated by perceived threats, that are generated as a consequence of complex cognitive processes. I further propose that the inputs from areas 10 m, 25 and 32 are activated under different circumstances. The input from cortical area 10 m is of special interest, because this cortical area exists only in primates and is much larger in the brain of humans than in all other primates. PMID:29881334

Whole-Brain Mapping of Direct Inputs to and Axonal Projections from GABAergic Neurons in the Parafacial Zone.

PubMed

Su, Yun-Ting; Gu, Meng-Yang; Chu, Xi; Feng, Xiang; Yu, Yan-Qin

2018-06-01

The GABAergic neurons in the parafacial zone (PZ) play an important role in sleep-wake regulation and have been identified as part of a sleep-promoting center in the brainstem, but the long-range connections mediating this function remain poorly characterized. Here, we performed whole-brain mapping of both the inputs and outputs of the GABAergic neurons in the PZ of the mouse brain. We used the modified rabies virus EnvA-ΔG-DsRed combined with a Cre/loxP gene-expression strategy to map the direct monosynaptic inputs to the GABAergic neurons in the PZ, and found that they receive inputs mainly from the hypothalamic area, zona incerta, and parasubthalamic nucleus in the hypothalamus; the substantia nigra, pars reticulata and deep mesencephalic nucleus in the midbrain; and the intermediate reticular nucleus and medial vestibular nucleus (parvocellular part) in the pons and medulla. We also mapped the axonal projections of the PZ GABAergic neurons with adeno-associated virus, and defined the reciprocal connections of the PZ GABAergic neurons with their input and output nuclei. The newly-found inputs and outputs of the PZ were also listed compared with the literature. This cell-type-specific neuronal whole-brain mapping of the PZ GABAergic neurons may reveal the circuits underlying various functions such as sleep-wake regulation.

Using machine-learning methods to analyze economic loss function of quality management processes

NASA Astrophysics Data System (ADS)

Dzedik, V. A.; Lontsikh, P. A.

2018-05-01

During analysis of quality management systems, their economic component is often analyzed insufficiently. To overcome this issue, it is necessary to withdraw the concept of economic loss functions from tolerance thinking and address it. Input data about economic losses in processes have a complex form, thus, using standard tools to solve this problem is complicated. Use of machine learning techniques allows one to obtain precise models of the economic loss function based on even the most complex input data. Results of such analysis contain data about the true efficiency of a process and can be used to make investment decisions.

Multilayer neural networks with extensively many hidden units.

PubMed

Rosen-Zvi, M; Engel, A; Kanter, I

2001-08-13

The information processing abilities of a multilayer neural network with a number of hidden units scaling as the input dimension are studied using statistical mechanics methods. The mapping from the input layer to the hidden units is performed by general symmetric Boolean functions, whereas the hidden layer is connected to the output by either discrete or continuous couplings. Introducing an overlap in the space of Boolean functions as order parameter, the storage capacity is found to scale with the logarithm of the number of implementable Boolean functions. The generalization behavior is smooth for continuous couplings and shows a discontinuous transition to perfect generalization for discrete ones.

Rationale choosing interval of a piecewise-constant approximation of input rate of non-stationary queue system

NASA Astrophysics Data System (ADS)

Korelin, Ivan A.; Porshnev, Sergey V.

2018-01-01

The paper demonstrates the possibility of calculating the characteristics of the flow of visitors to objects carrying out mass events passing through checkpoints. The mathematical model is based on the non-stationary queuing system (NQS) where dependence of requests input rate from time is described by the function. This function was chosen in such way that its properties were similar to the real dependencies of speed of visitors arrival on football matches to the stadium. A piecewise-constant approximation of the function is used when statistical modeling of NQS performing. Authors calculated the dependencies of the queue length and waiting time for visitors to service (time in queue) on time for different laws. Time required to service the entire queue and the number of visitors entering the stadium at the beginning of the match were calculated too. We found the dependence for macroscopic quantitative characteristics of NQS from the number of averaging sections of the input rate.

Towards practical control design using neural computation

NASA Technical Reports Server (NTRS)

Troudet, Terry; Garg, Sanjay; Mattern, Duane; Merrill, Walter

1991-01-01

The objective is to develop neural network based control design techniques which address the issue of performance/control effort tradeoff. Additionally, the control design needs to address the important issue if achieving adequate performance in the presence of actuator nonlinearities such as position and rate limits. These issues are discussed using the example of aircraft flight control. Given a set of pilot input commands, a feedforward net is trained to control the vehicle within the constraints imposed by the actuators. This is achieved by minimizing an objective function which is the sum of the tracking errors, control input rates and control input deflections. A tradeoff between tracking performance and control smoothness is obtained by varying, adaptively, the weights of the objective function. The neurocontroller performance is evaluated in the presence of actuator dynamics using a simulation of the vehicle. Appropriate selection of the different weights in the objective function resulted in the good tracking of the pilot commands and smooth neurocontrol. An extension of the neurocontroller design approach is proposed to enhance its practicality.

Identification of modal parameters including unmeasured forces and transient effects

NASA Astrophysics Data System (ADS)

Cauberghe, B.; Guillaume, P.; Verboven, P.; Parloo, E.

2003-08-01

In this paper, a frequency-domain method to estimate modal parameters from short data records with known input (measured) forces and unknown input forces is presented. The method can be used for an experimental modal analysis, an operational modal analysis (output-only data) and the combination of both. A traditional experimental and operational modal analysis in the frequency domain starts respectively, from frequency response functions and spectral density functions. To estimate these functions accurately sufficient data have to be available. The technique developed in this paper estimates the modal parameters directly from the Fourier spectra of the outputs and the known input. Instead of using Hanning windows on these short data records the transient effects are estimated simultaneously with the modal parameters. The method is illustrated, tested and validated by Monte Carlo simulations and experiments. The presented method to process short data sequences leads to unbiased estimates with a small variance in comparison to the more traditional approaches.

Control of electrochemical signals from quantum dots conjugated to organic materials by using DNA structure in an analog logic gate.

PubMed

Chen, Qi; Yoo, Si-Youl; Chung, Yong-Ho; Lee, Ji-Young; Min, Junhong; Choi, Jeong-Woo

2016-10-01

Various bio-logic gates have been studied intensively to overcome the rigidity of single-function silicon-based logic devices arising from combinations of various gates. Here, a simple control tool using electrochemical signals from quantum dots (QDs) was constructed using DNA and organic materials for multiple logic functions. The electrochemical redox current generated from QDs was controlled by the DNA structure. DNA structure, in turn, was dependent on the components (organic materials) and the input signal (pH). Independent electrochemical signals from two different logic units containing QDs were merged into a single analog-type logic gate, which was controlled by two inputs. We applied this electrochemical biodevice to a simple logic system and achieved various logic functions from the controlled pH input sets. This could be further improved by choosing QDs, ionic conditions, or DNA sequences. This research provides a feasible method for fabricating an artificial intelligence system. Copyright © 2016 Elsevier B.V. All rights reserved.

Mathematical models of the simplest fuzzy PI/PD controllers with skewed input and output fuzzy sets.

PubMed

Mohan, B M; Sinha, Arpita

2008-07-01

This paper unveils mathematical models for fuzzy PI/PD controllers which employ two skewed fuzzy sets for each of the two-input variables and three skewed fuzzy sets for the output variable. The basic constituents of these models are Gamma-type and L-type membership functions for each input, trapezoidal/triangular membership functions for output, intersection/algebraic product triangular norm, maximum/drastic sum triangular conorm, Mamdani minimum/Larsen product/drastic product inference method, and center of sums defuzzification method. The existing simplest fuzzy PI/PD controller structures derived via symmetrical fuzzy sets become special cases of the mathematical models revealed in this paper. Finally, a numerical example along with its simulation results are included to demonstrate the effectiveness of the simplest fuzzy PI controllers.

Identifying a Probabilistic Boolean Threshold Network From Samples.

PubMed

Melkman, Avraham A; Cheng, Xiaoqing; Ching, Wai-Ki; Akutsu, Tatsuya

2018-04-01

This paper studies the problem of exactly identifying the structure of a probabilistic Boolean network (PBN) from a given set of samples, where PBNs are probabilistic extensions of Boolean networks. Cheng et al. studied the problem while focusing on PBNs consisting of pairs of AND/OR functions. This paper considers PBNs consisting of Boolean threshold functions while focusing on those threshold functions that have unit coefficients. The treatment of Boolean threshold functions, and triplets and -tuplets of such functions, necessitates a deepening of the theoretical analyses. It is shown that wide classes of PBNs with such threshold functions can be exactly identified from samples under reasonable constraints, which include: 1) PBNs in which any number of threshold functions can be assigned provided that all have the same number of input variables and 2) PBNs consisting of pairs of threshold functions with different numbers of input variables. It is also shown that the problem of deciding the equivalence of two Boolean threshold functions is solvable in pseudopolynomial time but remains co-NP complete.

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.

Three Essays on the Economics of Education

ERIC Educational Resources Information Center

Herrmann, Mariesa Ann

2012-01-01

This dissertation consists of essays on three inputs into the educational production function: curriculum, peers, and teachers. The chapters are linked by their focus on understanding the importance of these inputs for student achievement and by their exploitation of the exact timing of events (i.e., student mobility, receipt of special education…

Kinetic quantitation of cerebral PET-FDG studies without concurrent blood sampling: statistical recovery of the arterial input function.

PubMed

O'Sullivan, F; Kirrane, J; Muzi, M; O'Sullivan, J N; Spence, A M; Mankoff, D A; Krohn, K A

2010-03-01

Kinetic quantitation of dynamic positron emission tomography (PET) studies via compartmental modeling usually requires the time-course of the radio-tracer concentration in the arterial blood as an arterial input function (AIF). For human and animal imaging applications, significant practical difficulties are associated with direct arterial sampling and as a result there is substantial interest in alternative methods that require no blood sampling at the time of the study. A fixed population template input function derived from prior experience with directly sampled arterial curves is one possibility. Image-based extraction, including requisite adjustment for spillover and recovery, is another approach. The present work considers a hybrid statistical approach based on a penalty formulation in which the information derived from a priori studies is combined in a Bayesian manner with information contained in the sampled image data in order to obtain an input function estimate. The absolute scaling of the input is achieved by an empirical calibration equation involving the injected dose together with the subject's weight, height and gender. The technique is illustrated in the context of (18)F -Fluorodeoxyglucose (FDG) PET studies in humans. A collection of 79 arterially sampled FDG blood curves are used as a basis for a priori characterization of input function variability, including scaling characteristics. Data from a series of 12 dynamic cerebral FDG PET studies in normal subjects are used to evaluate the performance of the penalty-based AIF estimation technique. The focus of evaluations is on quantitation of FDG kinetics over a set of 10 regional brain structures. As well as the new method, a fixed population template AIF and a direct AIF estimate based on segmentation are also considered. Kinetics analyses resulting from these three AIFs are compared with those resulting from radially sampled AIFs. The proposed penalty-based AIF extraction method is found to achieve significant improvements over the fixed template and the segmentation methods. As well as achieving acceptable kinetic parameter accuracy, the quality of fit of the region of interest (ROI) time-course data based on the extracted AIF, matches results based on arterially sampled AIFs. In comparison, significant deviation in the estimation of FDG flux and degradation in ROI data fit are found with the template and segmentation methods. The proposed AIF extraction method is recommended for practical use.

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

Design of Robust Controllers for a Multiple Input-Multiple Output Control System with Uncertain Parameters Application to the Lateral and Longitudinal Modes of the KC-135 Transport Aircraft

DTIC Science & Technology

1984-12-01

input/output relationship. These are obtained from the design specifications (10:68i-684). Note that the first digit of the subscript of bkj refers...to the output and the second digit to the input. Thus, bkj is.a function of the response requirements on the output, Yk’ due to the input, r.. 169 . A...NXPMAX pNYPMAX, IPLOT) C C C* LIBARY OF PLOT SUBR(OUTINES PSNTCT NLIEPRINTER ONLY~ C* C C C SUP’ LPLOTS C C C DIMENSION IXY(101,71)918UF(100) COMMON /HOPY

Modal Parameter Identification of a Flexible Arm System

NASA Technical Reports Server (NTRS)

Barrington, Jason; Lew, Jiann-Shiun; Korbieh, Edward; Wade, Montanez; Tantaris, Richard

1998-01-01

In this paper an experiment is designed for the modal parameter identification of a flexible arm system. This experiment uses a function generator to provide input signal and an oscilloscope to save input and output response data. For each vibrational mode, many sets of sine-wave inputs with frequencies close to the natural frequency of the arm system are used to excite the vibration of this mode. Then a least-squares technique is used to analyze the experimental input/output data to obtain the identified parameters for this mode. The identified results are compared with the analytical model obtained by applying finite element analysis.

Synchronization properties of coupled chaotic neurons: The role of random shared input

NASA Astrophysics Data System (ADS)

Kumar, Rupesh; Bilal, Shakir; Ramaswamy, Ram

2016-06-01

Spike-time correlations of neighbouring neurons depend on their intrinsic firing properties as well as on the inputs they share. Studies have shown that periodically firing neurons, when subjected to random shared input, exhibit asynchronicity. Here, we study the effect of random shared input on the synchronization of weakly coupled chaotic neurons. The cases of so-called electrical and chemical coupling are both considered, and we observe a wide range of synchronization behaviour. When subjected to identical shared random input, there is a decrease in the threshold coupling strength needed for chaotic neurons to synchronize in-phase. The system also supports lag-synchronous states, and for these, we find that shared input can cause desynchronization. We carry out a master stability function analysis for a network of such neurons and show agreement with the numerical simulations. The contrasting role of shared random input for complete and lag synchronized neurons is useful in understanding spike-time correlations observed in many areas of the brain.

Synchronization properties of coupled chaotic neurons: The role of random shared input

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

Kumar, Rupesh; Bilal, Shakir; Ramaswamy, Ram

Spike-time correlations of neighbouring neurons depend on their intrinsic firing properties as well as on the inputs they share. Studies have shown that periodically firing neurons, when subjected to random shared input, exhibit asynchronicity. Here, we study the effect of random shared input on the synchronization of weakly coupled chaotic neurons. The cases of so-called electrical and chemical coupling are both considered, and we observe a wide range of synchronization behaviour. When subjected to identical shared random input, there is a decrease in the threshold coupling strength needed for chaotic neurons to synchronize in-phase. The system also supports lag–synchronous states,more » and for these, we find that shared input can cause desynchronization. We carry out a master stability function analysis for a network of such neurons and show agreement with the numerical simulations. The contrasting role of shared random input for complete and lag synchronized neurons is useful in understanding spike-time correlations observed in many areas of the brain.« less

Advanced information processing system: Local system services

NASA Technical Reports Server (NTRS)

Burkhardt, Laura; Alger, Linda; Whittredge, Roy; Stasiowski, Peter

1989-01-01

The Advanced Information Processing System (AIPS) is a multi-computer architecture composed of hardware and software building blocks that can be configured to meet a broad range of application requirements. The hardware building blocks are fault-tolerant, general-purpose computers, fault-and damage-tolerant networks (both computer and input/output), and interfaces between the networks and the computers. The software building blocks are the major software functions: local system services, input/output, system services, inter-computer system services, and the system manager. The foundation of the local system services is an operating system with the functions required for a traditional real-time multi-tasking computer, such as task scheduling, inter-task communication, memory management, interrupt handling, and time maintenance. Resting on this foundation are the redundancy management functions necessary in a redundant computer and the status reporting functions required for an operator interface. The functional requirements, functional design and detailed specifications for all the local system services are documented.

Canonical multi-valued input Reed-Muller trees and forms

NASA Technical Reports Server (NTRS)

Perkowski, M. A.; Johnson, P. D.

1991-01-01

There is recently an increased interest in logic synthesis using EXOR gates. The paper introduces the fundamental concept of Orthogonal Expansion, which generalizes the ring form of the Shannon expansion to the logic with multiple-valued (mv) inputs. Based on this concept we are able to define a family of canonical tree circuits. Such circuits can be considered for binary and multiple-valued input cases. They can be multi-level (trees and DAG's) or flattened to two-level AND-EXOR circuits. Input decoders similar to those used in Sum of Products (SOP) PLA's are used in realizations of multiple-valued input functions. In the case of the binary logic the family of flattened AND-EXOR circuits includes several forms discussed by Davio and Green. For the case of the logic with multiple-valued inputs, the family of the flattened mv AND-EXOR circuits includes three expansions known from literature and two new expansions.

Visual and proprioceptive interaction in patients with bilateral vestibular loss☆

PubMed Central

Cutfield, Nicholas J.; Scott, Gregory; Waldman, Adam D.; Sharp, David J.; Bronstein, Adolfo M.

2014-01-01

Following bilateral vestibular loss (BVL) patients gradually adapt to the loss of vestibular input and rely more on other sensory inputs. Here we examine changes in the way proprioceptive and visual inputs interact. We used functional magnetic resonance imaging (fMRI) to investigate visual responses in the context of varying levels of proprioceptive input in 12 BVL subjects and 15 normal controls. A novel metal-free vibrator was developed to allow vibrotactile neck proprioceptive input to be delivered in the MRI system. A high level (100 Hz) and low level (30 Hz) control stimulus was applied over the left splenius capitis; only the high frequency stimulus generates a significant proprioceptive stimulus. The neck stimulus was applied in combination with static and moving (optokinetic) visual stimuli, in a factorial fMRI experimental design. We found that high level neck proprioceptive input had more cortical effect on brain activity in the BVL patients. This included a reduction in visual motion responses during high levels of proprioceptive input and differential activation in the midline cerebellum. In early visual cortical areas, the effect of high proprioceptive input was present for both visual conditions but in lateral visual areas, including V5/MT, the effect was only seen in the context of visual motion stimulation. The finding of a cortical visuo-proprioceptive interaction in BVL patients is consistent with behavioural data indicating that, in BVL patients, neck afferents partly replace vestibular input during the CNS-mediated compensatory process. An fMRI cervico-visual interaction may thus substitute the known visuo-vestibular interaction reported in normal subject fMRI studies. The results provide evidence for a cortical mechanism of adaptation to vestibular failure, in the form of an enhanced proprioceptive influence on visual processing. The results may provide the basis for a cortical mechanism involved in proprioceptive substitution of vestibular function in BVL patients. PMID:25061564

Visual and proprioceptive interaction in patients with bilateral vestibular loss.

PubMed

Cutfield, Nicholas J; Scott, Gregory; Waldman, Adam D; Sharp, David J; Bronstein, Adolfo M

2014-01-01

Following bilateral vestibular loss (BVL) patients gradually adapt to the loss of vestibular input and rely more on other sensory inputs. Here we examine changes in the way proprioceptive and visual inputs interact. We used functional magnetic resonance imaging (fMRI) to investigate visual responses in the context of varying levels of proprioceptive input in 12 BVL subjects and 15 normal controls. A novel metal-free vibrator was developed to allow vibrotactile neck proprioceptive input to be delivered in the MRI system. A high level (100 Hz) and low level (30 Hz) control stimulus was applied over the left splenius capitis; only the high frequency stimulus generates a significant proprioceptive stimulus. The neck stimulus was applied in combination with static and moving (optokinetic) visual stimuli, in a factorial fMRI experimental design. We found that high level neck proprioceptive input had more cortical effect on brain activity in the BVL patients. This included a reduction in visual motion responses during high levels of proprioceptive input and differential activation in the midline cerebellum. In early visual cortical areas, the effect of high proprioceptive input was present for both visual conditions but in lateral visual areas, including V5/MT, the effect was only seen in the context of visual motion stimulation. The finding of a cortical visuo-proprioceptive interaction in BVL patients is consistent with behavioural data indicating that, in BVL patients, neck afferents partly replace vestibular input during the CNS-mediated compensatory process. An fMRI cervico-visual interaction may thus substitute the known visuo-vestibular interaction reported in normal subject fMRI studies. The results provide evidence for a cortical mechanism of adaptation to vestibular failure, in the form of an enhanced proprioceptive influence on visual processing. The results may provide the basis for a cortical mechanism involved in proprioceptive substitution of vestibular function in BVL patients.

Working with and Visualizing Big Data Efficiently with Python for the DARPA XDATA Program

DTIC Science & Technology

2017-08-01

same function to be used with scalar inputs, input arrays of the same shape, or even input arrays of dimensionality in some cases. Most of the math ... math operations on values ● Split-apply-combine: similar to group-by operations in databases ● Join: combine two datasets using common columns 4.3.3...Numba - Continue to increase SIMD performance with support for fast math flags and improved support for AVX, Intel’s large vector

Axisymmetric Wave Transfer Functions of Flexible Tubes

NASA Astrophysics Data System (ADS)

Pinnington, R. J.

1997-07-01

The input and transfer impedances of fluid-filled pipes are calculated by using a wave approach. The pipe walls can have orthotropic elastic properties associated with braided rubber hose. The input and transfer impedances of a water-filled plain rubber hose are plotted for zero pressurization and positive and negative pressure. It is found that the pressure for this case does not greatly affect the stiffness. Input and transfer impedances are also plotted for a braided rubber hose which demonstrates the significant pressure stiffening effects found in practice.

Disinfection by electrohydraulic treatment.

PubMed

Allen, M; Soike, K

1967-04-28

Electrohydraulic treatment was applied to suspensions of Escherichia coli, spores of Bacillus subtilis var. niger, Saccharomyces cerevisiae, and bacteriophage T2 at an input energy that, in most cases, was below the energy required to sterilize. The input energy was held relatively constant for each of these microorganisms, but the capacitance and voltage were varied. Data are presented which show the degree of disinfection as a function of capacitance and voltage. In all cases, the degree of disinfection for a given input energy increases as both capacitance and voltage are lowered.

Motion video compression system with neural network having winner-take-all function

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi (Inventor); Sheu, Bing J. (Inventor)

1997-01-01

A motion video data system includes a compression system, including an image compressor, an image decompressor correlative to the image compressor having an input connected to an output of the image compressor, a feedback summing node having one input connected to an output of the image decompressor, a picture memory having an input connected to an output of the feedback summing node, apparatus for comparing an image stored in the picture memory with a received input image and deducing therefrom pixels having differences between the stored image and the received image and for retrieving from the picture memory a partial image including the pixels only and applying the partial image to another input of the feedback summing node, whereby to produce at the output of the feedback summing node an updated decompressed image, a subtraction node having one input connected to received the received image and another input connected to receive the partial image so as to generate a difference image, the image compressor having an input connected to receive the difference image whereby to produce a compressed difference image at the output of the image compressor.

Input-to-state stability of time-varying nonlinear discrete-time systems via indefinite difference Lyapunov functions.

PubMed

Li, Huijuan; Liu, Anping; Zhang, Linli

2018-06-01

In this paper, we propose new sufficient criteria for input-to-state stability (ISS) of time-varying nonlinear discrete-time systems via indefinite difference Lyapunov functions. The proposed sufficient conditions for ISS of system are more relaxed than for ISS with respect to Lyapunov functions with negative definite difference. We prove system is ISS by two methods. The first way is to prove system is ISS by indefinite difference ISS Lyapunov functions. The second method is to prove system is ISS via introducing an auxiliary system and indefinite difference robust Lyapunov functions. The comparison of the sufficient conditions for ISS obtained via the two methods is discussed. The effectiveness of our results is illustrated by three numerical examples. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

A Unified Approach to Adaptive Neural Control for Nonlinear Discrete-Time Systems With Nonlinear Dead-Zone Input.

PubMed

Liu, Yan-Jun; Gao, Ying; Tong, Shaocheng; Chen, C L Philip

2016-01-01

In this paper, an effective adaptive control approach is constructed to stabilize a class of nonlinear discrete-time systems, which contain unknown functions, unknown dead-zone input, and unknown control direction. Different from linear dead zone, the dead zone, in this paper, is a kind of nonlinear dead zone. To overcome the noncausal problem, which leads to the control scheme infeasible, the systems can be transformed into a m -step-ahead predictor. Due to nonlinear dead-zone appearance, the transformed predictor still contains the nonaffine function. In addition, it is assumed that the gain function of dead-zone input and the control direction are unknown. These conditions bring about the difficulties and the complicacy in the controller design. Thus, the implicit function theorem is applied to deal with nonaffine dead-zone appearance, the problem caused by the unknown control direction can be resolved through applying the discrete Nussbaum gain, and the neural networks are used to approximate the unknown function. Based on the Lyapunov theory, all the signals of the resulting closed-loop system are proved to be semiglobal uniformly ultimately bounded. Moreover, the tracking error is proved to be regulated to a small neighborhood around zero. The feasibility of the proposed approach is demonstrated by a simulation example.

Motor Control of Human Spinal Cord Disconnected from the Brain and Under External Movement.

PubMed

Mayr, Winfried; Krenn, Matthias; Dimitrijevic, Milan R

2016-01-01

Motor control after spinal cord injury is strongly depending on residual ascending and descending pathways across the lesion. The individually altered neurophysiology is in general based on still intact sublesional control loops with afferent sensory inputs linked via interneuron networks to efferent motor outputs. Partial or total loss of translesional control inputs reduces and alters the ability to perform voluntary movements and results in motor incomplete (residual voluntary control of movement functions) or motor complete (no residual voluntary control) spinal cord injury classification. Of particular importance are intact functionally silent neural structures with residual brain influence but reduced state of excitability that inhibits execution of voluntary movements. The condition is described by the term discomplete spinal cord injury. There are strong evidences that artificial afferent input, e.g., by epidural or noninvasive electrical stimulation of the lumbar posterior roots, can elevate the state of excitability and thus re-enable or augment voluntary movement functions. This modality can serve as a powerful assessment technique for monitoring details of the residual function profile after spinal cord injury, as a therapeutic tool for support of restoration of movement programs and as a neuroprosthesis component augmenting and restoring movement functions, per se or in synergy with classical neuromuscular or muscular electrical stimulation.

Similar GABAergic inputs in dentate granule cells born during embryonic and adult neurogenesis.

PubMed

Laplagne, Diego A; Kamienkowski, Juan E; Espósito, M Soledad; Piatti, Verónica C; Zhao, Chunmei; Gage, Fred H; Schinder, Alejandro F

2007-05-01

Neurogenesis in the dentate gyrus of the hippocampus follows a unique temporal pattern that begins during embryonic development, peaks during the early postnatal stages and persists through adult life. We have recently shown that dentate granule cells born in early postnatal and adult mice acquire a remarkably similar afferent connectivity and firing behavior, suggesting that they constitute a homogeneous functional population [Laplagne et al. (2006)PLoS Biol., 4, e409]. Here we extend our previous study by comparing mature neurons born in the embryonic and adult hippocampus, with a focus on intrinsic membrane properties and gamma-aminobutyric acid (GABA)ergic synaptic inputs. For this purpose, dividing neuroblasts of the ventricular wall were retrovirally labeled with green fluorescent protein at embryonic day 15 (E15), and progenitor cells of the subgranular zone were labeled with red fluorescent protein in the same mice at postnatal day 42 (P42, adulthood). Electrophysiological properties of mature neurons born at either stage were then compared in the same brain slices. Evoked and spontaneous GABAergic postsynaptic responses of perisomatic and dendritic origin displayed similar characteristics in both neuronal populations. Miniature GABAergic inputs also showed similar functional properties and pharmacological profile. A comparative analysis of the present data with our previous observations rendered no significant differences among GABAergic inputs recorded from neurons born in the embryonic, early postnatal and adult mice. Yet, embryo-born neurons showed a reduced membrane excitability, suggesting a lower engagement in network activity. Our results demonstrate that granule cells of different age, location and degree of excitability receive GABAergic inputs of equivalent functional characteristics.

Rise Time Reduction of Thermal Actuators Operated in Air and Water through Optimized Pre-Shaped Open-Loop Driving.

PubMed

Larsen, T; Doll, J C; Loizeau, F; Hosseini, N; Peng, A W; Fantner, G; Ricci, A J; Pruitt, B L

2017-01-01

Electrothermal actuators have many advantages compared to other actuators used in Micro-Electro-Mechanical Systems (MEMS). They are simple to design, easy to fabricate and provide large displacements at low voltages. Low voltages enable less stringent passivation requirements for operation in liquid. Despite these advantages, thermal actuation is typically limited to a few kHz bandwidth when using step inputs due to its intrinsic thermal time constant. However, the use of pre-shaped input signals offers a route for reducing the rise time of these actuators by orders of magnitude. We started with an electrothermally actuated cantilever having an initial 10-90% rise time of 85 μs in air and 234 μs in water for a standard open-loop step input. We experimentally characterized the linearity and frequency response of the cantilever when operated in air and water, allowing us to obtain transfer functions for the two cases. We used these transfer functions, along with functions describing desired reduced rise-time system responses, to numerically simulate the required input signals. Using these pre-shaped input signals, we improved the open-loop 10-90% rise time from 85 μs to 3 μs in air and from 234 μs to 5 μs in water, an improvement by a factor of 28 and 47, respectively. Using this simple control strategy for MEMS electrothermal actuators makes them an attractive alternative to other high speed micromechanical actuators such as piezoelectric stacks or electrostatic comb structures which are more complex to design, fabricate, or operate.

Direct connections assist neurons to detect correlation in small amplitude noises

PubMed Central

Bolhasani, E.; Azizi, Y.; Valizadeh, A.

2013-01-01

We address a question on the effect of common stochastic inputs on the correlation of the spike trains of two neurons when they are coupled through direct connections. We show that the change in the correlation of small amplitude stochastic inputs can be better detected when the neurons are connected by direct excitatory couplings. Depending on whether intrinsic firing rate of the neurons is identical or slightly different, symmetric or asymmetric connections can increase the sensitivity of the system to the input correlation by changing the mean slope of the correlation transfer function over a given range of input correlation. In either case, there is also an optimum value for synaptic strength which maximizes the sensitivity of the system to the changes in input correlation. PMID:23966940

Measuring Input Thresholds on an Existing Board

NASA Technical Reports Server (NTRS)

Kuperman, Igor; Gutrich, Daniel G.; Berkun, Andrew C.

2011-01-01

A critical PECL (positive emitter-coupled logic) interface to Xilinx interface needed to be changed on an existing flight board. The new Xilinx input interface used a CMOS (complementary metal-oxide semiconductor) type of input, and the driver could meet its thresholds typically, but not in worst-case, according to the data sheet. The previous interface had been based on comparison with an external reference, but the CMOS input is based on comparison with an internal divider from the power supply. A way to measure what the exact input threshold was for this device for 64 inputs on a flight board was needed. The measurement technique allowed an accurate measurement of the voltage required to switch a Xilinx input from high to low for each of the 64 lines, while only probing two of them. Directly driving an external voltage was considered too risky, and tests done on any other unit could not be used to qualify the flight board. The two lines directly probed gave an absolute voltage threshold calibration, while data collected on the remaining 62 lines without probing gave relative measurements that could be used to identify any outliers. The PECL interface was forced to a long-period square wave by driving a saturated square wave into the ADC (analog to digital converter). The active pull-down circuit was turned off, causing each line to rise rapidly and fall slowly according to the input s weak pull-down circuitry. The fall time shows up as a change in the pulse width of the signal ready by the Xilinx. This change in pulse width is a function of capacitance, pulldown current, and input threshold. Capacitance was known from the different trace lengths, plus a gate input capacitance, which is the same for all inputs. The pull-down current is the same for all inputs including the two that are probed directly. The data was combined, and the Excel solver tool was used to find input thresholds for the 62 lines. This was repeated over different supply voltages and temperatures to show that the interface had voltage margin under all worst case conditions. Gate input thresholds are normally measured at the manufacturer when the device is on a chip tester. A key function of this machine was duplicated on an existing flight board with no modifications to the nets to be tested, with the exception of changes in the FPGA program.

Recovery of neuronal and network excitability after spinal cord injury and implications for spasticity

PubMed Central

D'Amico, Jessica M.; Condliffe, Elizabeth G.; Martins, Karen J. B.; Bennett, David J.; Gorassini, Monica A.

2014-01-01

The state of areflexia and muscle weakness that immediately follows a spinal cord injury (SCI) is gradually replaced by the recovery of neuronal and network excitability, leading to both improvements in residual motor function and the development of spasticity. In this review we summarize recent animal and human studies that describe how motoneurons and their activation by sensory pathways become hyperexcitable to compensate for the reduction of functional activation of the spinal cord and the eventual impact on the muscle. Specifically, decreases in the inhibitory control of sensory transmission and increases in intrinsic motoneuron excitability are described. We present the idea that replacing lost patterned activation of the spinal cord by activating synaptic inputs via assisted movements, pharmacology or electrical stimulation may help to recover lost spinal inhibition. This may lead to a reduction of uncontrolled activation of the spinal cord and thus, improve its controlled activation by synaptic inputs to ultimately normalize circuit function. Increasing the excitation of the spinal cord with spared descending and/or peripheral inputs by facilitating movement, instead of suppressing it pharmacologically, may provide the best avenue to improve residual motor function and manage spasticity after SCI. PMID:24860447

Target dependence of orientation and direction selectivity of corticocortical projection neurons in the mouse V1

PubMed Central

Matsui, Teppei; Ohki, Kenichi

2013-01-01

Higher order visual areas that receive input from the primary visual cortex (V1) are specialized for the processing of distinct features of visual information. However, it is still incompletely understood how this functional specialization is acquired. Here we used in vivo two photon calcium imaging in the mouse visual cortex to investigate whether this functional distinction exists at as early as the level of projections from V1 to two higher order visual areas, AL and LM. Specifically, we examined whether sharpness of orientation and direction selectivity and optimal spatial and temporal frequency of projection neurons from V1 to higher order visual areas match with that of target areas. We found that the V1 input to higher order visual areas were indeed functionally distinct: AL preferentially received inputs from V1 that were more orientation and direction selective and tuned for lower spatial frequency compared to projection of V1 to LM, consistent with functional differences between AL and LM. The present findings suggest that selective projections from V1 to higher order visual areas initiates parallel processing of sensory information in the visual cortical network. PMID:24068987

Recommended System Design for the Occupational Health Management Information System (OHMIS). Volume 1.

DTIC Science & Technology

1983-04-01

Management Information System (OHMIS). The system design includes: detailed function data flows for each of the core data processing functions of OHMIS, in the form of input/processing/output algorithms; detailed descriptions of the inputs and outputs; performance specifications of OHMIS; resources required to develop and operate OHMIS (Vol II). In addition, the report provides a summary of the rationale used to develop the recommended system design, a description of the methodology used to develop the recommended system design, and a review of existing

A technique for pole-zero placement for dual-input control systems. [computer simulation of CH-47 helicopter longitudinal dynamics

NASA Technical Reports Server (NTRS)

Reid, G. F.

1976-01-01

A technique is presented for determining state variable feedback gains that will place both the poles and zeros of a selected transfer function of a dual-input control system at pre-determined locations in the s-plane. Leverrier's algorithm is used to determine the numerator and denominator coefficients of the closed-loop transfer function as functions of the feedback gains. The values of gain that match these coefficients to those of a pre-selected model are found by solving two systems of linear simultaneous equations. The algorithm has been used in a computer simulation of the CH-47 helicopter to control longitudinal dynamics.

Desired Accuracy Estimation of Noise Function from ECG Signal by Fuzzy Approach

PubMed Central

Vahabi, Zahra; Kermani, Saeed

2012-01-01

Unknown noise and artifacts present in medical signals with non-linear fuzzy filter will be estimated and then removed. An adaptive neuro-fuzzy interference system which has a non-linear structure presented for the noise function prediction by before Samples. This paper is about a neuro-fuzzy method to estimate unknown noise of Electrocardiogram signal. Adaptive neural combined with Fuzzy System to construct a fuzzy Predictor. For this system setting parameters such as the number of Membership Functions for each input and output, training epochs, type of MFs for each input and output, learning algorithm and etc. is determined by learning data. At the end simulated experimental results are presented for proper validation. PMID:23717810

Multi-channel spatialization systems for audio signals

NASA Technical Reports Server (NTRS)

Begault, Durand R. (Inventor)

1993-01-01

Synthetic head related transfer functions (HRTF's) for imposing reprogrammable spatial cues to a plurality of audio input signals included, for example, in multiple narrow-band audio communications signals received simultaneously are generated and stored in interchangeable programmable read only memories (PROM's) which store both head related transfer function impulse response data and source positional information for a plurality of desired virtual source locations. The analog inputs of the audio signals are filtered and converted to digital signals from which synthetic head related transfer functions are generated in the form of linear phase finite impulse response filters. The outputs of the impulse response filters are subsequently reconverted to analog signals, filtered, mixed, and fed to a pair of headphones.

Multi-channel spatialization system for audio signals

NASA Technical Reports Server (NTRS)

Begault, Durand R. (Inventor)

1995-01-01

Synthetic head related transfer functions (HRTF's) for imposing reprogramable spatial cues to a plurality of audio input signals included, for example, in multiple narrow-band audio communications signals received simultaneously are generated and stored in interchangeable programmable read only memories (PROM's) which store both head related transfer function impulse response data and source positional information for a plurality of desired virtual source locations. The analog inputs of the audio signals are filtered and converted to digital signals from which synthetic head related transfer functions are generated in the form of linear phase finite impulse response filters. The outputs of the impulse response filters are subsequently reconverted to analog signals, filtered, mixed and fed to a pair of headphones.

An Automated Program Testing Methodology and its Implementation.

DTIC Science & Technology

1980-01-01

correctly on its input data; the number of for each software system. asse rtions violated defines an "error function"Itiimoan tocos ecsswhh over the Input...space of the program. ThisItiimoan tocos tecse whh remove@ the need to examine a program’s output uncover errors early in the development cycle, in

Economies of Scale and Scope in Australian Higher Education

ERIC Educational Resources Information Center

Worthington, A. C.; Higgs, H.

2011-01-01

This paper estimates economies of scale and scope for 36 Australian universities using a multiple-input, multiple-output cost function over the period 1998-2006. The three inputs included in the analysis are full-time equivalent academic and non-academic staff and physical capital. The five outputs are undergraduate, postgraduate and PhD…

Dendritic spines linearize the summation of excitatory potentials

PubMed Central

Araya, Roberto; Eisenthal, Kenneth B.; Yuste, Rafael

2006-01-01

In mammalian cortex, most excitatory inputs occur on dendritic spines, avoiding dendritic shafts. Although spines biochemically isolate inputs, nonspiny neurons can also implement biochemical compartmentalization; so, it is possible that spines have an additional function. We have recently shown that the spine neck can filter membrane potentials going into and out of the spine. To investigate the potential function of this electrical filtering, we used two-photon uncaging of glutamate and compared the integration of electrical signals in spines vs. dendritic shafts from basal dendrites of mouse layer 5 pyramidal neurons. Uncaging potentials onto spines summed linearly, whereas potentials on dendritic shafts reduced each other's effect. Linear integration of spines was maintained regardless of the amplitude of the response, distance between spines (as close as <2 μm), distance of the spines to the soma, dendritic diameter, or spine neck length. Our findings indicate that spines serve as electrical isolators to prevent input interaction, and thus generate a linear arithmetic of excitatory inputs. Linear integration could be an essential feature of cortical and other spine-laden circuits. PMID:17132736

Dendritic spines linearize the summation of excitatory potentials.

PubMed

Araya, Roberto; Eisenthal, Kenneth B; Yuste, Rafael

2006-12-05

In mammalian cortex, most excitatory inputs occur on dendritic spines, avoiding dendritic shafts. Although spines biochemically isolate inputs, nonspiny neurons can also implement biochemical compartmentalization; so, it is possible that spines have an additional function. We have recently shown that the spine neck can filter membrane potentials going into and out of the spine. To investigate the potential function of this electrical filtering, we used two-photon uncaging of glutamate and compared the integration of electrical signals in spines vs. dendritic shafts from basal dendrites of mouse layer 5 pyramidal neurons. Uncaging potentials onto spines summed linearly, whereas potentials on dendritic shafts reduced each other's effect. Linear integration of spines was maintained regardless of the amplitude of the response, distance between spines (as close as < 2 microm), distance of the spines to the soma, dendritic diameter, or spine neck length. Our findings indicate that spines serve as electrical isolators to prevent input interaction, and thus generate a linear arithmetic of excitatory inputs. Linear integration could be an essential feature of cortical and other spine-laden circuits.

Standardized residual as response function for order identification of multi input intervention analysis

NASA Astrophysics Data System (ADS)

Suhartono, Lee, Muhammad Hisyam; Rezeki, Sri

2017-05-01

Intervention analysis is a statistical model in the group of time series analysis which is widely used to describe the effect of an intervention caused by external or internal factors. An example of external factors that often occurs in Indonesia is a disaster, both natural or man-made disaster. The main purpose of this paper is to provide the results of theoretical studies on identification step for determining the order of multi inputs intervention analysis for evaluating the magnitude and duration of the impact of interventions on time series data. The theoretical result showed that the standardized residuals could be used properly as response function for determining the order of multi inputs intervention model. Then, these results are applied for evaluating the impact of a disaster on a real case in Indonesia, i.e. the magnitude and duration of the impact of the Lapindo mud on the volume of vehicles on the highway. Moreover, the empirical results showed that the multi inputs intervention model can describe and explain accurately the magnitude and duration of the impact of disasters on a time series data.

Multi-Response Optimization of WEDM Process Parameters Using Taguchi Based Desirability Function Analysis

NASA Astrophysics Data System (ADS)

Majumder, Himadri; Maity, Kalipada

2018-03-01

Shape memory alloy has a unique capability to return to its original shape after physical deformation by applying heat or thermo-mechanical or magnetic load. In this experimental investigation, desirability function analysis (DFA), a multi-attribute decision making was utilized to find out the optimum input parameter setting during wire electrical discharge machining (WEDM) of Ni-Ti shape memory alloy. Four critical machining parameters, namely pulse on time (TON), pulse off time (TOFF), wire feed (WF) and wire tension (WT) were taken as machining inputs for the experiments to optimize three interconnected responses like cutting speed, kerf width, and surface roughness. Input parameter combination TON = 120 μs., TOFF = 55 μs., WF = 3 m/min. and WT = 8 kg-F were found to produce the optimum results. The optimum process parameters for each desired response were also attained using Taguchi’s signal-to-noise ratio. Confirmation test has been done to validate the optimum machining parameter combination which affirmed DFA was a competent approach to select optimum input parameters for the ideal response quality for WEDM of Ni-Ti shape memory alloy.

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.

Further results on open-loop compensation of rate-dependent hysteresis in a magnetostrictive actuator with the Prandtl-Ishlinskii model

NASA Astrophysics Data System (ADS)

Al Janaideh, Mohammad; Aljanaideh, Omar

2018-05-01

Apart from the output-input hysteresis loops, the magnetostrictive actuators also exhibit asymmetry and saturation, particularly under moderate to large magnitude inputs and at relatively higher frequencies. Such nonlinear input-output characteristics could be effectively characterized by a rate-dependent Prandtl-Ishlinskii model in conjunction with a function of deadband operators. In this study, an inverse model is formulated to seek real-time compensation of rate-dependent and asymmetric hysteresis nonlinearities of a Terfenol-D magnetostrictive actuator. The inverse model is formulated with the inverse of the rate-dependent Prandtl-Ishlinskii model, satisfying the threshold dilation condition, with the inverse of the deadband function. The inverse model was subsequently applied to the hysteresis model as a feedforward compensator. The proposed compensator is applied as a feedforward compensator to the actuator hardware to study its potential for rate-dependent and asymmetric hysteresis loops. The experimental results are obtained under harmonic and complex harmonic inputs further revealed that the inverse compensator can substantially suppress the hysteresis and output asymmetry nonlinearities in the entire frequency range considered in the study.

Projected regression method for solving Fredholm integral equations arising in the analytic continuation problem of quantum physics

NASA Astrophysics Data System (ADS)

Arsenault, Louis-François; Neuberg, Richard; Hannah, Lauren A.; Millis, Andrew J.

2017-11-01

We present a supervised machine learning approach to the inversion of Fredholm integrals of the first kind as they arise, for example, in the analytic continuation problem of quantum many-body physics. The approach provides a natural regularization for the ill-conditioned inverse of the Fredholm kernel, as well as an efficient and stable treatment of constraints. The key observation is that the stability of the forward problem permits the construction of a large database of outputs for physically meaningful inputs. Applying machine learning to this database generates a regression function of controlled complexity, which returns approximate solutions for previously unseen inputs; the approximate solutions are then projected onto the subspace of functions satisfying relevant constraints. Under standard error metrics the method performs as well or better than the Maximum Entropy method for low input noise and is substantially more robust to increased input noise. We suggest that the methodology will be similarly effective for other problems involving a formally ill-conditioned inversion of an integral operator, provided that the forward problem can be efficiently solved.

Multisensory connections of monkey auditory cerebral cortex

PubMed Central

Smiley, John F.; Falchier, Arnaud

2009-01-01

Functional studies have demonstrated multisensory responses in auditory cortex, even in the primary and early auditory association areas. The features of somatosensory and visual responses in auditory cortex suggest that they are involved in multiple processes including spatial, temporal and object-related perception. Tract tracing studies in monkeys have demonstrated several potential sources of somatosensory and visual inputs to auditory cortex. These include potential somatosensory inputs from the retroinsular (RI) and granular insula (Ig) cortical areas, and from the thalamic posterior (PO) nucleus. Potential sources of visual responses include peripheral field representations of areas V2 and prostriata, as well as the superior temporal polysensory area (STP) in the superior temporal sulcus, and the magnocellular medial geniculate thalamic nucleus (MGm). Besides these sources, there are several other thalamic, limbic and cortical association structures that have multisensory responses and may contribute cross-modal inputs to auditory cortex. These connections demonstrated by tract tracing provide a list of potential inputs, but in most cases their significance has not been confirmed by functional experiments. It is possible that the somatosensory and visual modulation of auditory cortex are each mediated by multiple extrinsic sources. PMID:19619628

Distributed computing system with dual independent communications paths between computers and employing split tokens

NASA Technical Reports Server (NTRS)

Rasmussen, Robert D. (Inventor); Manning, Robert M. (Inventor); Lewis, Blair F. (Inventor); Bolotin, Gary S. (Inventor); Ward, Richard S. (Inventor)

1990-01-01

This is a distributed computing system providing flexible fault tolerance; ease of software design and concurrency specification; and dynamic balance of the loads. The system comprises a plurality of computers each having a first input/output interface and a second input/output interface for interfacing to communications networks each second input/output interface including a bypass for bypassing the associated computer. A global communications network interconnects the first input/output interfaces for providing each computer the ability to broadcast messages simultaneously to the remainder of the computers. A meshwork communications network interconnects the second input/output interfaces providing each computer with the ability to establish a communications link with another of the computers bypassing the remainder of computers. Each computer is controlled by a resident copy of a common operating system. Communications between respective ones of computers is by means of split tokens each having a moving first portion which is sent from computer to computer and a resident second portion which is disposed in the memory of at least one of computer and wherein the location of the second portion is part of the first portion. The split tokens represent both functions to be executed by the computers and data to be employed in the execution of the functions. The first input/output interfaces each include logic for detecting a collision between messages and for terminating the broadcasting of a message whereby collisions between messages are detected and avoided.

Replica symmetric evaluation of the information transfer in a two-layer network in the presence of continuous and discrete stimuli.

PubMed

Del Prete, Valeria; Treves, Alessandro

2002-04-01

In a previous paper we have evaluated analytically the mutual information between the firing rates of N independent units and a set of multidimensional continuous and discrete stimuli, for a finite population size and in the limit of large noise. Here, we extend the analysis to the case of two interconnected populations, where input units activate output ones via Gaussian weights and a threshold linear transfer function. We evaluate the information carried by a population of M output units, again about continuous and discrete correlates. The mutual information is evaluated solving saddle-point equations under the assumption of replica symmetry, a method that, by taking into account only the term linear in N of the input information, is equivalent to assuming the noise to be large. Within this limitation, we analyze the dependence of the information on the ratio M/N, on the selectivity of the input units and on the level of the output noise. We show analytically, and confirm numerically, that in the limit of a linear transfer function and of a small ratio between output and input noise, the output information approaches asymptotically the information carried in input. Finally, we show that the information loss in output does not depend much on the structure of the stimulus, whether purely continuous, purely discrete or mixed, but only on the position of the threshold nonlinearity, and on the ratio between input and output noise.

The Design of Feedback Control Systems Containing a Saturation Type Nonlinearity

NASA Technical Reports Server (NTRS)

Schmidt, Stanley F.; Harper, Eleanor V.

1960-01-01

A derivation of the optimum response for a step input for plant transfer functions which have an unstable pole and further data on plants with a single zero in the left half of the s plane. The calculated data are presented tabulated in normalized form. Optimum control systems are considered. The optimum system is defined as one which keeps the error as small as possible regardless of the input, under the constraint that the input to the plant (or controlled system) is limited. Intuitive arguments show that in the case where only the error can be sensed directly, the optimum system is obtained from the optimum relay or on-off solution. References to known solutions are presented. For the case when the system is of the sampled-data type, arguments are presented which indicate the optimum sampled-data system may be extremely difficult if not impossible to realize practically except for very simple plant transfer functions. Two examples of aircraft attitude autopilots are presented, one for a statically stable and the other for a statically unstable airframe. The rate of change of elevator motion is assumed limited for these examples. It is shown that by use of nonlinear design techniques described in NASA TN D-20 one can obtain near optimum response for step inputs and reason- able response to sine wave inputs for either case. Also, the nonlinear design prevents inputs from driving the system unstable for either case.

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.

An input-representing interneuron regulates spike timing and thereby phase switching in a motor network.

PubMed

Sasaki, Kosei; Jing, Jian; Due, Michael R; Weiss, Klaudiusz R

2008-02-20

Despite the importance of spike-timing regulation in network functioning, little is known about this regulation at the cellular level. In the Aplysia feeding network, we show that interneuron B65 regulates the timing of the spike initiation of phase-switch neurons B64 and cerebral-buccal interneuron-5/6 (CBI-5/6), and thereby determines the identity of the neuron that acts as a protraction terminator. Previous work showed that B64 begins to fire before the end of protraction phase and terminates protraction in CBI-2-elicited ingestive, but not in CBI-2-elicited egestive programs, thus indicating that the spike timing and phase-switching function of B64 depend on the type of the central pattern generator (CPG)-elicited response rather than on the input used to activate the CPG. Here, we find that CBI-5/6 is a protraction terminator in egestive programs elicited by the esophageal nerve (EN), but not by CBI-2, thus indicating that, in contrast to B64, the spike timing and protraction-terminating function of CBI-5/6 depends on the input to the CPG rather than the response type. Interestingly, B65 activity also depends on the input in that B65 is highly active in EN-elicited programs, but not in CBI-2-elicited programs independent of whether the programs are ingestive or egestive. Notably, during EN-elicited egestive programs, hyperpolarization of B65 delays the onset of CBI-5/6 firing, whereas in CBI-2-elicited ingestive programs, B65 stimulation simultaneously advances CBI-5/6 firing and delays B64 firing, thereby substituting CBI-5/6 for B64 as the protraction terminator. Thus, we identified a neural mechanism that, in an input-dependent manner, regulates spike timing and thereby the functional role of specific neurons.

Investigating the age distribution of fracture discharge using multiple environmental tracers, Bedrichov Tunnel, Czech Republic

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

Gardner, W. Payton; Hokr, Milan; Shao, Hua

We investigated the transit time distribution (TTD) of discharge collected from fractures in the Bedrichov Tunnel, Czech Republic, using lumped parameter models and multiple environmental tracers. We then utilize time series of δ 18O, δ 2H and 3H along with CFC measurements from individual fractures in the Bedrichov Tunnel of the Czech Republic to investigate the TTD, and the uncertainty in estimated mean travel time in several fracture networks of varying length and discharge. We also compare several TTDs, including the dispersion distribution, the exponential distribution, and a developed TTD which includes the effects of matrix diffusion. The effect ofmore » seasonal recharge is explored by comparing several seasonal weighting functions to derive the historical recharge concentration. We identify best fit mean ages for each TTD by minimizing the error-weighted, multi-tracer χ2 residual for each seasonal weighting function. We use this methodology to test the ability of each TTD and seasonal input function to fit the observed tracer concentrations, and the effect of choosing different TTD and seasonal recharge functions on the mean age estimation. We find that the estimated mean transit time is a function of both the assumed TTD and seasonal weighting function. Best fits as measured by the χ2 value were achieved for the dispersion model using the seasonal input function developed here for two of the three modeled sites, while at the third site, equally good fits were achieved with the exponential model and the dispersion model and our seasonal input function. The average mean transit time for all TTDs and seasonal input functions converged to similar values at each location. The sensitivity of the estimated mean transit time to the seasonal weighting function was equal to that of the TTD. These results indicated that understanding seasonality of recharge is at least as important as the uncertainty in the flow path distribution in fracture networks and that unique identification of the TTD and mean transit time is difficult given the uncertainty in the recharge function. But, the mean transit time appears to be relatively robust to the structural model uncertainty. The results presented here should be applicable to other studies using environmental tracers to constrain flow and transport properties in fractured rock systems.« less

Investigating the age distribution of fracture discharge using multiple environmental tracers, Bedrichov Tunnel, Czech Republic

DOE PAGES

Gardner, W. Payton; Hokr, Milan; Shao, Hua; ...

2016-10-19

We investigated the transit time distribution (TTD) of discharge collected from fractures in the Bedrichov Tunnel, Czech Republic, using lumped parameter models and multiple environmental tracers. We then utilize time series of δ 18O, δ 2H and 3H along with CFC measurements from individual fractures in the Bedrichov Tunnel of the Czech Republic to investigate the TTD, and the uncertainty in estimated mean travel time in several fracture networks of varying length and discharge. We also compare several TTDs, including the dispersion distribution, the exponential distribution, and a developed TTD which includes the effects of matrix diffusion. The effect ofmore » seasonal recharge is explored by comparing several seasonal weighting functions to derive the historical recharge concentration. We identify best fit mean ages for each TTD by minimizing the error-weighted, multi-tracer χ2 residual for each seasonal weighting function. We use this methodology to test the ability of each TTD and seasonal input function to fit the observed tracer concentrations, and the effect of choosing different TTD and seasonal recharge functions on the mean age estimation. We find that the estimated mean transit time is a function of both the assumed TTD and seasonal weighting function. Best fits as measured by the χ2 value were achieved for the dispersion model using the seasonal input function developed here for two of the three modeled sites, while at the third site, equally good fits were achieved with the exponential model and the dispersion model and our seasonal input function. The average mean transit time for all TTDs and seasonal input functions converged to similar values at each location. The sensitivity of the estimated mean transit time to the seasonal weighting function was equal to that of the TTD. These results indicated that understanding seasonality of recharge is at least as important as the uncertainty in the flow path distribution in fracture networks and that unique identification of the TTD and mean transit time is difficult given the uncertainty in the recharge function. But, the mean transit time appears to be relatively robust to the structural model uncertainty. The results presented here should be applicable to other studies using environmental tracers to constrain flow and transport properties in fractured rock systems.« less

[11C]Harmine Binding to Brain Monoamine Oxidase A: Test-Retest Properties and Noninvasive Quantification.

PubMed

Zanderigo, Francesca; D'Agostino, Alexandra E; Joshi, Nandita; Schain, Martin; Kumar, Dileep; Parsey, Ramin V; DeLorenzo, Christine; Mann, J John

2018-02-08

Inhibition of the isoform A of monoamine oxidase (MAO-A), a mitochondrial enzyme catalyzing deamination of monoamine neurotransmitters, is useful in treatment of depression and anxiety disorders. [ 11 C]harmine, a MAO-A PET radioligand, has been used to study mood disorders and antidepressant treatment. However, [ 11 C]harmine binding test-retest characteristics have to date only been partially investigated. Furthermore, since MAO-A is ubiquitously expressed, no reference region is available, thus requiring arterial blood sampling during PET scanning. Here, we investigate [ 11 C]harmine binding measurements test-retest properties; assess effects of using a minimally invasive input function estimation on binding quantification and repeatability; and explore binding potentials estimation using a reference region-free approach. Quantification of [ 11 C]harmine distribution volume (V T ) via kinetic models and graphical analyses was compared based on absolute test-retest percent difference (TRPD), intraclass correlation coefficient (ICC), and identifiability. The optimal procedure was also used with a simultaneously estimated input function in place of the measured curve. Lastly, an approach for binding potentials quantification in absence of a reference region was evaluated. [ 11 C]harmine V T estimates quantified using arterial blood and kinetic modeling showed average absolute TRPD values of 7.7 to 15.6 %, and ICC values between 0.56 and 0.86, across brain regions. Using simultaneous estimation (SIME) of input function resulted in V T estimates close to those obtained using arterial input function (r = 0.951, slope = 1.073, intercept = - 1.037), with numerically but not statistically higher test-retest difference (range 16.6 to 22.0 %), but with overall poor ICC values, between 0.30 and 0.57. Prospective studies using [ 11 C]harmine are possible given its test-retest repeatability when binding is quantified using arterial blood. Results with SIME of input function show potential for simplifying data acquisition by replacing arterial catheterization with one arterial blood sample at 20 min post-injection. Estimation of [ 11 C]harmine binding potentials remains a challenge that warrants further investigation.

Current Source Logic Gate

NASA Technical Reports Server (NTRS)

Krasowski, Michael J. (Inventor); Prokop, Norman F. (Inventor)

2017-01-01

A current source logic gate with depletion mode field effect transistor ("FET") transistors and resistors may include a current source, a current steering switch input stage, and a resistor divider level shifting output stage. The current source may include a transistor and a current source resistor. The current steering switch input stage may include a transistor to steer current to set an output stage bias point depending on an input logic signal state. The resistor divider level shifting output stage may include a first resistor and a second resistor to set the output stage point and produce valid output logic signal states. The transistor of the current steering switch input stage may function as a switch to provide at least two operating points.

Reconfigurable Drive Current System

NASA Technical Reports Server (NTRS)

Alhorn, Dean C. (Inventor); Dutton, Kenneth R. (Inventor); Howard, David E. (Inventor); Smith, Dennis A. (Inventor)

2017-01-01

A reconfigurable drive current system includes drive stages, each of which includes a high-side transistor and a low-side transistor in a totem pole configuration. A current monitor is coupled to an output of each drive stage. Input channels are provided to receive input signals. A processor is coupled to the input channels and to each current monitor for generating at least one drive signal using at least one of the input signals and current measured by at least one of the current monitors. A pulse width modulation generator is coupled to the processor and each drive stage for varying the drive signals as a function of time prior to being supplied to at least one of the drive stages.

Translating PI observing proposals into ALMA observing scripts

NASA Astrophysics Data System (ADS)

Liszt, Harvey S.

2014-08-01

The ALMA telescope is a complex 66-antenna array working in the specialized domain of mm- and sub-mm aperture synthesis imaging. To make ALMA accessible to technically inexperienced but scientifically expert users, the ALMA Observing Tool (OT) has been developed. Using the OT, scientifically oriented user input is formatted as observing proposals that are packaged for peer-review and assessment of technical feasibility. If accepted, the proposal's scientifically oriented inputs are translated by the OT into scheduling blocks, which function as input to observing scripts for the telescope's online control system. Here I describe the processes and practices by which this translation from PI scientific goals to online control input and schedule block execution actually occurs.

Optimization of a Thermodynamic Model Using a Dakota Toolbox Interface

NASA Astrophysics Data System (ADS)

Cyrus, J.; Jafarov, E. E.; Schaefer, K. M.; Wang, K.; Clow, G. D.; Piper, M.; Overeem, I.

2016-12-01

Scientific modeling of the Earth physical processes is an important driver of modern science. The behavior of these scientific models is governed by a set of input parameters. It is crucial to choose accurate input parameters that will also preserve the corresponding physics being simulated in the model. In order to effectively simulate real world processes the models output data must be close to the observed measurements. To achieve this optimal simulation, input parameters are tuned until we have minimized the objective function, which is the error between the simulation model outputs and the observed measurements. We developed an auxiliary package, which serves as a python interface between the user and DAKOTA. The package makes it easy for the user to conduct parameter space explorations, parameter optimizations, as well as sensitivity analysis while tracking and storing results in a database. The ability to perform these analyses via a Python library also allows the users to combine analysis techniques, for example finding an approximate equilibrium with optimization then immediately explore the space around it. We used the interface to calibrate input parameters for the heat flow model, which is commonly used in permafrost science. We performed optimization on the first three layers of the permafrost model, each with two thermal conductivity coefficients input parameters. Results of parameter space explorations indicate that the objective function not always has a unique minimal value. We found that gradient-based optimization works the best for the objective functions with one minimum. Otherwise, we employ more advanced Dakota methods such as genetic optimization and mesh based convergence in order to find the optimal input parameters. We were able to recover 6 initially unknown thermal conductivity parameters within 2% accuracy of their known values. Our initial tests indicate that the developed interface for the Dakota toolbox could be used to perform analysis and optimization on a `black box' scientific model more efficiently than using just Dakota.

SAMBA: Sparse Approximation of Moment-Based Arbitrary Polynomial Chaos

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

Ahlfeld, R., E-mail: r.ahlfeld14@imperial.ac.uk; Belkouchi, B.; Montomoli, F.

2016-09-01

A new arbitrary Polynomial Chaos (aPC) method is presented for moderately high-dimensional problems characterised by limited input data availability. The proposed methodology improves the algorithm of aPC and extends the method, that was previously only introduced as tensor product expansion, to moderately high-dimensional stochastic problems. The fundamental idea of aPC is to use the statistical moments of the input random variables to develop the polynomial chaos expansion. This approach provides the possibility to propagate continuous or discrete probability density functions and also histograms (data sets) as long as their moments exist, are finite and the determinant of the moment matrixmore » is strictly positive. For cases with limited data availability, this approach avoids bias and fitting errors caused by wrong assumptions. In this work, an alternative way to calculate the aPC is suggested, which provides the optimal polynomials, Gaussian quadrature collocation points and weights from the moments using only a handful of matrix operations on the Hankel matrix of moments. It can therefore be implemented without requiring prior knowledge about statistical data analysis or a detailed understanding of the mathematics of polynomial chaos expansions. The extension to more input variables suggested in this work, is an anisotropic and adaptive version of Smolyak's algorithm that is solely based on the moments of the input probability distributions. It is referred to as SAMBA (PC), which is short for Sparse Approximation of Moment-Based Arbitrary Polynomial Chaos. It is illustrated that for moderately high-dimensional problems (up to 20 different input variables or histograms) SAMBA can significantly simplify the calculation of sparse Gaussian quadrature rules. SAMBA's efficiency for multivariate functions with regard to data availability is further demonstrated by analysing higher order convergence and accuracy for a set of nonlinear test functions with 2, 5 and 10 different input distributions or histograms.« less

SAMBA: Sparse Approximation of Moment-Based Arbitrary Polynomial Chaos

NASA Astrophysics Data System (ADS)

Ahlfeld, R.; Belkouchi, B.; Montomoli, F.

2016-09-01

A new arbitrary Polynomial Chaos (aPC) method is presented for moderately high-dimensional problems characterised by limited input data availability. The proposed methodology improves the algorithm of aPC and extends the method, that was previously only introduced as tensor product expansion, to moderately high-dimensional stochastic problems. The fundamental idea of aPC is to use the statistical moments of the input random variables to develop the polynomial chaos expansion. This approach provides the possibility to propagate continuous or discrete probability density functions and also histograms (data sets) as long as their moments exist, are finite and the determinant of the moment matrix is strictly positive. For cases with limited data availability, this approach avoids bias and fitting errors caused by wrong assumptions. In this work, an alternative way to calculate the aPC is suggested, which provides the optimal polynomials, Gaussian quadrature collocation points and weights from the moments using only a handful of matrix operations on the Hankel matrix of moments. It can therefore be implemented without requiring prior knowledge about statistical data analysis or a detailed understanding of the mathematics of polynomial chaos expansions. The extension to more input variables suggested in this work, is an anisotropic and adaptive version of Smolyak's algorithm that is solely based on the moments of the input probability distributions. It is referred to as SAMBA (PC), which is short for Sparse Approximation of Moment-Based Arbitrary Polynomial Chaos. It is illustrated that for moderately high-dimensional problems (up to 20 different input variables or histograms) SAMBA can significantly simplify the calculation of sparse Gaussian quadrature rules. SAMBA's efficiency for multivariate functions with regard to data availability is further demonstrated by analysing higher order convergence and accuracy for a set of nonlinear test functions with 2, 5 and 10 different input distributions or histograms.

School Control--What, How and Why.

ERIC Educational Resources Information Center

Holmes, Mark

School administrators can get a better idea of what their purpose is by examining, first, what schools achieve; second, how schools function; and, third, why they function. A school's production function (what it achieves) involves many specific functions, but they all are a product of the relationship between school inputs and outputs. Inputs…

Cost function approach for estimating derived demand for composite wood products

Treesearch

T. C. Marcin

1991-01-01

A cost function approach was examined for using the concept of duality between production and input factor demands. A translog cost function was used to represent residential construction costs and derived conditional factor demand equations. Alternative models were derived from the translog cost function by imposing parameter restrictions.

Olfactory Bulb Deep Short-Axon Cells Mediate Widespread Inhibition of Tufted Cell Apical Dendrites

PubMed Central

LaRocca, Greg

2017-01-01

In the main olfactory bulb (MOB), the first station of sensory processing in the olfactory system, GABAergic interneuron signaling shapes principal neuron activity to regulate olfaction. However, a lack of known selective markers for MOB interneurons has strongly impeded cell-type-selective investigation of interneuron function. Here, we identify the first selective marker of glomerular layer-projecting deep short-axon cells (GL-dSACs) and investigate systematically the structure, abundance, intrinsic physiology, feedforward sensory input, neuromodulation, synaptic output, and functional role of GL-dSACs in the mouse MOB circuit. GL-dSACs are located in the internal plexiform layer, where they integrate centrifugal cholinergic input with highly convergent feedforward sensory input. GL-dSAC axons arborize extensively across the glomerular layer to provide highly divergent yet selective output onto interneurons and principal tufted cells. GL-dSACs are thus capable of shifting the balance of principal tufted versus mitral cell activity across large expanses of the MOB in response to diverse sensory and top-down neuromodulatory input. SIGNIFICANCE STATEMENT The identification of cell-type-selective molecular markers has fostered tremendous insight into how distinct interneurons shape sensory processing and behavior. In the main olfactory bulb (MOB), inhibitory circuits regulate the activity of principal cells precisely to drive olfactory-guided behavior. However, selective markers for MOB interneurons remain largely unknown, limiting mechanistic understanding of olfaction. Here, we identify the first selective marker of a novel population of deep short-axon cell interneurons with superficial axonal projections to the sensory input layer of the MOB. Using this marker, together with immunohistochemistry, acute slice electrophysiology, and optogenetic circuit mapping, we reveal that this novel interneuron population integrates centrifugal cholinergic input with broadly tuned feedforward sensory input to modulate principal cell activity selectively. PMID:28003347

Connections of cat auditory cortex: III. Corticocortical system.

PubMed

Lee, Charles C; Winer, Jeffery A

2008-04-20

The mammalian auditory cortex (AC) is essential for computing the source and decoding the information contained in sound. Knowledge of AC corticocortical connections is modest other than in the primary auditory regions, nor is there an anatomical framework in the cat for understanding the patterns of connections among the many auditory areas. To address this issue we investigated cat AC connectivity in 13 auditory regions. Retrograde tracers were injected in the same area or in different areas to reveal the areal and laminar sources of convergent input to each region. Architectonic borders were established in Nissl and SMI-32 immunostained material. We assessed the topography, convergence, and divergence of the labeling. Intrinsic input constituted >50% of the projection cells in each area, and extrinsic inputs were strongest from functionally related areas. Each area received significant convergent ipsilateral input from several fields (5 to 8; mean 6). These varied in their laminar origin and projection density. Major extrinsic projections were preferentially from areas of the same functional type (tonotopic to tonotopic, nontonotopic to nontonotopic, limbic-related to limbic-related, multisensory-to-multisensory), while smaller projections link areas belonging to different groups. Branched projections between areas were <2% with deposits of two tracers in an area or in different areas. All extrinsic projections to each area were highly and equally topographic and clustered. Intrinsic input arose from all layers except layer I, and extrinsic input had unique, area-specific infragranular and supragranular origins. The many areal and laminar sources of input may contribute to the complexity of physiological responses in AC and suggest that many projections of modest size converge within each area rather than a simpler area-to-area serial or hierarchical pattern of corticocortical connectivity. (c) 2008 Wiley-Liss, Inc.

ANL/RBC: A computer code for the analysis of Rankine bottoming cycles, including system cost evaluation and off-design performance

NASA Technical Reports Server (NTRS)

Mclennan, G. A.

1986-01-01

This report describes, and is a User's Manual for, a computer code (ANL/RBC) which calculates cycle performance for Rankine bottoming cycles extracting heat from a specified source gas stream. The code calculates cycle power and efficiency and the sizes for the heat exchangers, using tabular input of the properties of the cycle working fluid. An option is provided to calculate the costs of system components from user defined input cost functions. These cost functions may be defined in equation form or by numerical tabular data. A variety of functional forms have been included for these functions and they may be combined to create very general cost functions. An optional calculation mode can be used to determine the off-design performance of a system when operated away from the design-point, using the heat exchanger areas calculated for the design-point.

Inhibitory neurotransmission regulates vagal efferent activity and gastric motility

PubMed Central

McMenamin, Caitlin A; Travagli, R Alberto

2016-01-01

The gastrointestinal tract receives extrinsic innervation from both the sympathetic and parasympathetic nervous systems, which regulate and modulate the function of the intrinsic (enteric) nervous system. The stomach and upper gastrointestinal tract in particular are heavily influenced by the parasympathetic nervous system, supplied by the vagus nerve, and disruption of vagal sensory or motor functions results in disorganized motility patterns, disrupted receptive relaxation and accommodation, and delayed gastric emptying, amongst others. Studies from several laboratories have shown that the activity of vagal efferent motoneurons innervating the upper GI tract is inhibited tonically by GABAergic synaptic inputs from the adjacent nucleus tractus solitarius. Disruption of this influential central GABA input impacts vagal efferent output, hence gastric functions, significantly. The purpose of this review is to describe the development, physiology, and pathophysiology of this functionally dominant inhibitory synapse and its role in regulating vagally determined gastric functions. PMID:27302177

Multi-function all optical packet switch by periodic wavelength arrangement in an arrayed waveguide grating and wideband optical filters.

PubMed

Feng, Kai-Ming; Wu, Chung-Yu; Wen, Yu-Hsiang

2012-01-16

By utilizing the cyclic filtering function of an NxN arrayed waveguide grating (AWG), we propose and experimentally demonstrate a novel multi-function all optical packet switching (OPS) architecture by applying a periodical wavelength arrangement between the AWG in the optical routing/buffering unit and a set of wideband optical filters in the switched output ports to achieve the desired routing and buffering functions. The proposed OPS employs only one tunable wavelength converter at the input port to convert the input wavelength to a designated wavelength which reduces the number of active optical components and thus the complexity of the traffic control is simplified in the OPS. With the proposed OPS architecture, multiple optical packet switching functions, including arbitrary packet switching and buffering, first-in-first-out (FIFO) packet multiplexing, packet demultiplexing and packet add/drop multiplexing, have been successfully demonstrated.

The WORM site: worm.csirc.net

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

Jones, T.

2000-07-01

The Write One, Run Many (WORM) site (worm.csirc.net) is the on-line home of the WORM language and is hosted by the Criticality Safety Information Resource Center (CSIRC) (www.csirc.net). The purpose of this web site is to create an on-line community for WORM users to gather, share, and archive WORM-related information. WORM is an embedded, functional, programming language designed to facilitate the creation of input decks for computer codes that take standard ASCII text files as input. A functional programming language is one that emphasizes the evaluation of expressions, rather than execution of commands. The simplest and perhaps most common examplemore » of a functional language is a spreadsheet such as Microsoft Excel. The spreadsheet user specifies expressions to be evaluated, while the spreadsheet itself determines the commands to execute, as well as the order of execution/evaluation. WORM functions in a similar fashion and, as a result, is very simple to use and easy to learn. WORM improves the efficiency of today's criticality safety analyst by allowing: (1) input decks for parameter studies to be created quickly and easily; (2) calculations and variables to be embedded into any input deck, thus allowing for meaningful parameter specifications; (3) problems to be specified using any combination of units; and (4) complex mathematically defined models to be created. WORM is completely written in Perl. Running on all variants of UNIX, Windows, MS-DOS, MacOS, and many other operating systems, Perl is one of the most portable programming languages available. As such, WORM works on practically any computer platform.« less

Polarity-specific high-level information propagation in neural networks.

PubMed

Lin, Yen-Nan; Chang, Po-Yen; Hsiao, Pao-Yueh; Lo, Chung-Chuan

2014-01-01

Analyzing the connectome of a nervous system provides valuable information about the functions of its subsystems. Although much has been learned about the architectures of neural networks in various organisms by applying analytical tools developed for general networks, two distinct and functionally important properties of neural networks are often overlooked. First, neural networks are endowed with polarity at the circuit level: Information enters a neural network at input neurons, propagates through interneurons, and leaves via output neurons. Second, many functions of nervous systems are implemented by signal propagation through high-level pathways involving multiple and often recurrent connections rather than by the shortest paths between nodes. In the present study, we analyzed two neural networks: the somatic nervous system of Caenorhabditis elegans (C. elegans) and the partial central complex network of Drosophila, in light of these properties. Specifically, we quantified high-level propagation in the vertical and horizontal directions: the former characterizes how signals propagate from specific input nodes to specific output nodes and the latter characterizes how a signal from a specific input node is shared by all output nodes. We found that the two neural networks are characterized by very efficient vertical and horizontal propagation. In comparison, classic small-world networks show a trade-off between vertical and horizontal propagation; increasing the rewiring probability improves the efficiency of horizontal propagation but worsens the efficiency of vertical propagation. Our result provides insights into how the complex functions of natural neural networks may arise from a design that allows them to efficiently transform and combine input signals.

Polarity-specific high-level information propagation in neural networks

PubMed Central

Lin, Yen-Nan; Chang, Po-Yen; Hsiao, Pao-Yueh; Lo, Chung-Chuan

2014-01-01

Analyzing the connectome of a nervous system provides valuable information about the functions of its subsystems. Although much has been learned about the architectures of neural networks in various organisms by applying analytical tools developed for general networks, two distinct and functionally important properties of neural networks are often overlooked. First, neural networks are endowed with polarity at the circuit level: Information enters a neural network at input neurons, propagates through interneurons, and leaves via output neurons. Second, many functions of nervous systems are implemented by signal propagation through high-level pathways involving multiple and often recurrent connections rather than by the shortest paths between nodes. In the present study, we analyzed two neural networks: the somatic nervous system of Caenorhabditis elegans (C. elegans) and the partial central complex network of Drosophila, in light of these properties. Specifically, we quantified high-level propagation in the vertical and horizontal directions: the former characterizes how signals propagate from specific input nodes to specific output nodes and the latter characterizes how a signal from a specific input node is shared by all output nodes. We found that the two neural networks are characterized by very efficient vertical and horizontal propagation. In comparison, classic small-world networks show a trade-off between vertical and horizontal propagation; increasing the rewiring probability improves the efficiency of horizontal propagation but worsens the efficiency of vertical propagation. Our result provides insights into how the complex functions of natural neural networks may arise from a design that allows them to efficiently transform and combine input signals. PMID:24672472

Bilinearity in Spatiotemporal Integration of Synaptic Inputs

PubMed Central

Li, Songting; Liu, Nan; Zhang, Xiao-hui; Zhou, Douglas; Cai, David

2014-01-01

Neurons process information via integration of synaptic inputs from dendrites. Many experimental results demonstrate dendritic integration could be highly nonlinear, yet few theoretical analyses have been performed to obtain a precise quantitative characterization analytically. Based on asymptotic analysis of a two-compartment passive cable model, given a pair of time-dependent synaptic conductance inputs, we derive a bilinear spatiotemporal dendritic integration rule. The summed somatic potential can be well approximated by the linear summation of the two postsynaptic potentials elicited separately, plus a third additional bilinear term proportional to their product with a proportionality coefficient . The rule is valid for a pair of synaptic inputs of all types, including excitation-inhibition, excitation-excitation, and inhibition-inhibition. In addition, the rule is valid during the whole dendritic integration process for a pair of synaptic inputs with arbitrary input time differences and input locations. The coefficient is demonstrated to be nearly independent of the input strengths but is dependent on input times and input locations. This rule is then verified through simulation of a realistic pyramidal neuron model and in electrophysiological experiments of rat hippocampal CA1 neurons. The rule is further generalized to describe the spatiotemporal dendritic integration of multiple excitatory and inhibitory synaptic inputs. The integration of multiple inputs can be decomposed into the sum of all possible pairwise integration, where each paired integration obeys the bilinear rule. This decomposition leads to a graph representation of dendritic integration, which can be viewed as functionally sparse. PMID:25521832

FlaME: Flash Molecular Editor - a 2D structure input tool for the web.

PubMed

Dallakian, Pavel; Haider, Norbert

2011-02-01

So far, there have been no Flash-based web tools available for chemical structure input. The authors herein present a feasibility study, aiming at the development of a compact and easy-to-use 2D structure editor, using Adobe's Flash technology and its programming language, ActionScript. As a reference model application from the Java world, we selected the Java Molecular Editor (JME). In this feasibility study, we made an attempt to realize a subset of JME's functionality in the Flash Molecular Editor (FlaME) utility. These basic capabilities are: structure input, editing and depiction of single molecules, data import and export in molfile format. The result of molecular diagram sketching in FlaME is accessible in V2000 molfile format. By integrating the molecular editor into a web page, its communication with the HTML elements on this page is established using the two JavaScript functions, getMol() and setMol(). In addition, structures can be copied to the system clipboard. A first attempt was made to create a compact single-file application for 2D molecular structure input/editing on the web, based on Flash technology. With the application examples presented in this article, it could be demonstrated that the Flash methods are principally well-suited to provide the requisite communication between the Flash object (application) and the HTML elements on a web page, using JavaScript functions.

Early uneven ear input induces long-lasting differences in left-right motor function.

PubMed

Antoine, Michelle W; Zhu, Xiaoxia; Dieterich, Marianne; Brandt, Thomas; Vijayakumar, Sarath; McKeehan, Nicholas; Arezzo, Joseph C; Zukin, R Suzanne; Borkholder, David A; Jones, Sherri M; Frisina, Robert D; Hébert, Jean M

2018-03-01

How asymmetries in motor behavior become established normally or atypically in mammals remains unclear. An established model for motor asymmetry that is conserved across mammals can be obtained by experimentally inducing asymmetric striatal dopamine activity. However, the factors that can cause motor asymmetries in the absence of experimental manipulations to the brain remain unknown. Here, we show that mice with inner ear dysfunction display a robust left or right rotational preference, and this motor preference reflects an atypical asymmetry in cortico-striatal neurotransmission. By unilaterally targeting striatal activity with an antagonist of extracellular signal-regulated kinase (ERK), a downstream integrator of striatal neurotransmitter signaling, we can reverse or exaggerate rotational preference in these mice. By surgically biasing vestibular failure to one ear, we can dictate the direction of motor preference, illustrating the influence of uneven vestibular failure in establishing the outward asymmetries in motor preference. The inner ear-induced striatal asymmetries identified here intersect with non-ear-induced asymmetries previously linked to lateralized motor behavior across species and suggest that aspects of left-right brain function in mammals can be ontogenetically influenced by inner ear input. Consistent with inner ear input contributing to motor asymmetry, we also show that, in humans with normal ear function, the motor-dominant hemisphere, measured as handedness, is ipsilateral to the ear with weaker vestibular input.

Deep neural mapping support vector machines.

PubMed

Li, Yujian; Zhang, Ting

2017-09-01

The choice of kernel has an important effect on the performance of a support vector machine (SVM). The effect could be reduced by NEUROSVM, an architecture using multilayer perceptron for feature extraction and SVM for classification. In binary classification, a general linear kernel NEUROSVM can be theoretically simplified as an input layer, many hidden layers, and an SVM output layer. As a feature extractor, the sub-network composed of the input and hidden layers is first trained together with a virtual ordinary output layer by backpropagation, then with the output of its last hidden layer taken as input of the SVM classifier for further training separately. By taking the sub-network as a kernel mapping from the original input space into a feature space, we present a novel model, called deep neural mapping support vector machine (DNMSVM), from the viewpoint of deep learning. This model is also a new and general kernel learning method, where the kernel mapping is indeed an explicit function expressed as a sub-network, different from an implicit function induced by a kernel function traditionally. Moreover, we exploit a two-stage procedure of contrastive divergence learning and gradient descent for DNMSVM to jointly training an adaptive kernel mapping instead of a kernel function, without requirement of kernel tricks. As a whole of the sub-network and the SVM classifier, the joint training of DNMSVM is done by using gradient descent to optimize the objective function with the sub-network layer-wise pre-trained via contrastive divergence learning of restricted Boltzmann machines. Compared to the separate training of NEUROSVM, the joint training is a new algorithm for DNMSVM to have advantages over NEUROSVM. Experimental results show that DNMSVM can outperform NEUROSVM and RBFSVM (i.e., SVM with the kernel of radial basis function), demonstrating its effectiveness. Copyright © 2017 Elsevier Ltd. All rights reserved.

Additivity of nonsimultaneous masking for short Gaussian-shaped sinusoids.

PubMed

Laback, Bernhard; Balazs, Peter; Necciari, Thibaud; Savel, Sophie; Ystad, Solvi; Meunier, Sabine; Kronland-Martinet, Richard

2011-02-01

The additivity of nonsimultaneous masking was studied using Gaussian-shaped tone pulses (referred to as Gaussians) as masker and target stimuli. Combinations of up to four temporally separated Gaussian maskers with an equivalent rectangular bandwidth of 600 Hz and an equivalent rectangular duration of 1.7 ms were tested. Each masker was level-adjusted to produce approximately 8 dB of masking. Excess masking (exceeding linear additivity) was generally stronger than reported in the literature for longer maskers and comparable target levels. A model incorporating a compressive input/output function, followed by a linear summation stage, underestimated excess masking when using an input/output function derived from literature data for longer maskers and comparable target levels. The data could be predicted with a more compressive input/output function. Stronger compression may be explained by assuming that the Gaussian stimuli were too short to evoke the medial olivocochlear reflex (MOCR), whereas for longer maskers tested previously the MOCR caused reduced compression. Overall, the interpretation of the data suggests strong basilar membrane compression for very short stimuli.

Spinal microcircuits comprising dI3 interneurons are necessary for motor functional recovery following spinal cord transection

PubMed Central

Bui, Tuan V; Stifani, Nicolas; Akay, Turgay; Brownstone, Robert M

2016-01-01

The spinal cord has the capacity to coordinate motor activities such as locomotion. Following spinal transection, functional activity can be regained, to a degree, following motor training. To identify microcircuits involved in this recovery, we studied a population of mouse spinal interneurons known to receive direct afferent inputs and project to intermediate and ventral regions of the spinal cord. We demonstrate that while dI3 interneurons are not necessary for normal locomotor activity, locomotor circuits rhythmically inhibit them and dI3 interneurons can activate these circuits. Removing dI3 interneurons from spinal microcircuits by eliminating their synaptic transmission left locomotion more or less unchanged, but abolished functional recovery, indicating that dI3 interneurons are a necessary cellular substrate for motor system plasticity following transection. We suggest that dI3 interneurons compare inputs from locomotor circuits with sensory afferent inputs to compute sensory prediction errors that then modify locomotor circuits to effect motor recovery. DOI: http://dx.doi.org/10.7554/eLife.21715.001 PMID:27977000

Neural Network Optimization of Ligament Stiffnesses for the Enhanced Predictive Ability of a Patient-Specific, Computational Foot/Ankle Model.

PubMed

Chande, Ruchi D; Wayne, Jennifer S

2017-09-01

Computational models of diarthrodial joints serve to inform the biomechanical function of these structures, and as such, must be supplied appropriate inputs for performance that is representative of actual joint function. Inputs for these models are sourced from both imaging modalities as well as literature. The latter is often the source of mechanical properties for soft tissues, like ligament stiffnesses; however, such data are not always available for all the soft tissues nor is it known for patient-specific work. In the current research, a method to improve the ligament stiffness definition for a computational foot/ankle model was sought with the greater goal of improving the predictive ability of the computational model. Specifically, the stiffness values were optimized using artificial neural networks (ANNs); both feedforward and radial basis function networks (RBFNs) were considered. Optimal networks of each type were determined and subsequently used to predict stiffnesses for the foot/ankle model. Ultimately, the predicted stiffnesses were considered reasonable and resulted in enhanced performance of the computational model, suggesting that artificial neural networks can be used to optimize stiffness inputs.

Application of Model Based Parameter Estimation for Fast Frequency Response Calculations of Input Characteristics of Cavity-Backed Aperture Antennas Using Hybrid FEM/MoM Technique

NASA Technical Reports Server (NTRS)

Reddy C. J.

1998-01-01

Model Based Parameter Estimation (MBPE) is presented in conjunction with the hybrid Finite Element Method (FEM)/Method of Moments (MoM) technique for fast computation of the input characteristics of cavity-backed aperture antennas over a frequency range. The hybrid FENI/MoM technique is used to form an integro-partial- differential equation to compute the electric field distribution of a cavity-backed aperture antenna. In MBPE, the electric field is expanded in a rational function of two polynomials. The coefficients of the rational function are obtained using the frequency derivatives of the integro-partial-differential equation formed by the hybrid FEM/ MoM technique. Using the rational function approximation, the electric field is obtained over a frequency range. Using the electric field at different frequencies, the input characteristics of the antenna are obtained over a wide frequency range. Numerical results for an open coaxial line, probe-fed coaxial cavity and cavity-backed microstrip patch antennas are presented. Good agreement between MBPE and the solutions over individual frequencies is observed.

Computational models of O-LM cells are recruited by low or high theta frequency inputs depending on h-channel distributions

PubMed Central

Sekulić, Vladislav; Skinner, Frances K

2017-01-01

Although biophysical details of inhibitory neurons are becoming known, it is challenging to map these details onto function. Oriens-lacunosum/moleculare (O-LM) cells are inhibitory cells in the hippocampus that gate information flow, firing while phase-locked to theta rhythms. We build on our existing computational model database of O-LM cells to link model with function. We place our models in high-conductance states and modulate inhibitory inputs at a wide range of frequencies. We find preferred spiking recruitment of models at high (4–9 Hz) or low (2–5 Hz) theta depending on, respectively, the presence or absence of h-channels on their dendrites. This also depends on slow delayed-rectifier potassium channels, and preferred theta ranges shift when h-channels are potentiated by cyclic AMP. Our results suggest that O-LM cells can be differentially recruited by frequency-modulated inputs depending on specific channel types and distributions. This work exposes a strategy for understanding how biophysical characteristics contribute to function. DOI: http://dx.doi.org/10.7554/eLife.22962.001 PMID:28318488

Organization of Functional Long-Range Circuits Controlling the Activity of Serotonergic Neurons in the Dorsal Raphe Nucleus.

PubMed

Zhou, Li; Liu, Ming-Zhe; Li, Qing; Deng, Juan; Mu, Di; Sun, Yan-Gang

2017-03-21

Serotonergic neurons play key roles in various biological processes. However, circuit mechanisms underlying tight control of serotonergic neurons remain largely unknown. Here, we systematically investigated the organization of long-range synaptic inputs to serotonergic neurons and GABAergic neurons in the dorsal raphe nucleus (DRN) of mice with a combination of viral tracing, slice electrophysiological, and optogenetic techniques. We found that DRN serotonergic neurons and GABAergic neurons receive largely comparable synaptic inputs from six major upstream brain areas. Upon further analysis of the fine functional circuit structures, we found both bilateral and ipsilateral patterns of topographic connectivity in the DRN for the axons from different inputs. Moreover, the upstream brain areas were found to bidirectionally control the activity of DRN serotonergic neurons by recruiting feedforward inhibition or via a push-pull mechanism. Our study provides a framework for further deciphering the functional roles of long-range circuits controlling the activity of serotonergic neurons in the DRN. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Dual function conducting polymer diodes

DOEpatents

Heeger, Alan J.; Yu, Gang

1996-01-01

Dual function diodes based on conjugated organic polymer active layers are disclosed. When positively biased the diodes function as light emitters. When negatively biased they are highly efficient photodiodes. Methods of preparation and use of these diodes in displays and input/output devices are also disclosed.

Optical switches and switching methods

DOEpatents

Doty, Michael

2008-03-04

A device and method for collecting subject responses, particularly during magnetic imaging experiments and testing using a method such as functional MRI. The device comprises a non-metallic input device which is coupled via fiber optic cables to a computer or other data collection device. One or more optical switches transmit the subject's responses. The input device keeps the subject's fingers comfortably aligned with the switches by partially immobilizing the forearm, wrist, and/or hand of the subject. Also a robust nonmetallic switch, particularly for use with the input device and methods for optical switching.

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.

Network and neuronal membrane properties in hybrid networks reciprocally regulate selectivity to rapid thalamocortical inputs.

PubMed

Pesavento, Michael J; Pinto, David J

2012-11-01

Rapidly changing environments require rapid processing from sensory inputs. Varying deflection velocities of a rodent's primary facial vibrissa cause varying temporal neuronal activity profiles within the ventral posteromedial thalamic nucleus. Local neuron populations in a single somatosensory layer 4 barrel transform sparsely coded input into a spike count based on the input's temporal profile. We investigate this transformation by creating a barrel-like hybrid network with whole cell recordings of in vitro neurons from a cortical slice preparation, embedding the biological neuron in the simulated network by presenting virtual synaptic conductances via a conductance clamp. Utilizing the hybrid network, we examine the reciprocal network properties (local excitatory and inhibitory synaptic convergence) and neuronal membrane properties (input resistance) by altering the barrel population response to diverse thalamic input. In the presence of local network input, neurons are more selective to thalamic input timing; this arises from strong feedforward inhibition. Strongly inhibitory (damping) network regimes are more selective to timing and less selective to the magnitude of input but require stronger initial input. Input selectivity relies heavily on the different membrane properties of excitatory and inhibitory neurons. When inhibitory and excitatory neurons had identical membrane properties, the sensitivity of in vitro neurons to temporal vs. magnitude features of input was substantially reduced. Increasing the mean leak conductance of the inhibitory cells decreased the network's temporal sensitivity, whereas increasing excitatory leak conductance enhanced magnitude sensitivity. Local network synapses are essential in shaping thalamic input, and differing membrane properties of functional classes reciprocally modulate this effect.

Can Simulation Credibility Be Improved Using Sensitivity Analysis to Understand Input Data Effects on Model Outcome?

NASA Technical Reports Server (NTRS)

Myers, Jerry G.; Young, M.; Goodenow, Debra A.; Keenan, A.; Walton, M.; Boley, L.

2015-01-01

Model and simulation (MS) credibility is defined as, the quality to elicit belief or trust in MS results. NASA-STD-7009 [1] delineates eight components (Verification, Validation, Input Pedigree, Results Uncertainty, Results Robustness, Use History, MS Management, People Qualifications) that address quantifying model credibility, and provides guidance to the model developers, analysts, and end users for assessing the MS credibility. Of the eight characteristics, input pedigree, or the quality of the data used to develop model input parameters, governing functions, or initial conditions, can vary significantly. These data quality differences have varying consequences across the range of MS application. NASA-STD-7009 requires that the lowest input data quality be used to represent the entire set of input data when scoring the input pedigree credibility of the model. This requirement provides a conservative assessment of model inputs, and maximizes the communication of the potential level of risk of using model outputs. Unfortunately, in practice, this may result in overly pessimistic communication of the MS output, undermining the credibility of simulation predictions to decision makers. This presentation proposes an alternative assessment mechanism, utilizing results parameter robustness, also known as model input sensitivity, to improve the credibility scoring process for specific simulations.

Hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) and its application to predicting key process variables.

PubMed

He, Yan-Lin; Xu, Yuan; Geng, Zhi-Qiang; Zhu, Qun-Xiong

2016-03-01

In this paper, a hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) is proposed. Firstly, an improved functional link neural network with small norm of expanded weights and high input-output correlation (SNEWHIOC-FLNN) was proposed for enhancing the generalization performance of FLNN. Unlike the traditional FLNN, the expanded variables of the original inputs are not directly used as the inputs in the proposed SNEWHIOC-FLNN model. The original inputs are attached to some small norm of expanded weights. As a result, the correlation coefficient between some of the expanded variables and the outputs is enhanced. The larger the correlation coefficient is, the more relevant the expanded variables tend to be. In the end, the expanded variables with larger correlation coefficient are selected as the inputs to improve the performance of the traditional FLNN. In order to test the proposed SNEWHIOC-FLNN model, three UCI (University of California, Irvine) regression datasets named Housing, Concrete Compressive Strength (CCS), and Yacht Hydro Dynamics (YHD) are selected. Then a hybrid model based on the improved FLNN integrating with partial least square (IFLNN-PLS) was built. In IFLNN-PLS model, the connection weights are calculated using the partial least square method but not the error back propagation algorithm. Lastly, IFLNN-PLS was developed as an intelligent measurement model for accurately predicting the key variables in the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. Simulation results illustrated that the IFLNN-PLS could significant improve the prediction performance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Phonetic Category Cues in Adult-Directed Speech: Evidence from Three Languages with Distinct Vowel Characteristics

ERIC Educational Resources Information Center

Pons, Ferran; Biesanz, Jeremy C.; Kajikawa, Sachiyo; Fais, Laurel; Narayan, Chandan R.; Amano, Shigeaki; Werker, Janet F.

2012-01-01

Using an artificial language learning manipulation, Maye, Werker, and Gerken (2002) demonstrated that infants' speech sound categories change as a function of the distributional properties of the input. In a recent study, Werker et al. (2007) showed that Infant-directed Speech (IDS) input contains reliable acoustic cues that support distributional…

Transport and retention of multi-walled carbon nanotubes in saturated porous media: Effects of input concentration and grain size

USDA-ARS?s Scientific Manuscript database

Water-saturated column experiments were conducted to investigate the effect of input concentration (Co) and sand grain size on the transport and retention of low concentrations (1, 0.01, and 0.005 mg L/1) of functionalized 14C-labeled multi-walled carbon nanotubes (MWCNT) under repulsive electrostat...

School District Income Taxes and School Inputs: The Case of Ohio

ERIC Educational Resources Information Center

Nguyen-Hoang, Phuong

2014-01-01

This study is the first to explore the relationship between school district income taxes and school inputs (expenditures and student-teacher ratios) using Ohio as a case study. The study employed reduced-form expenditure functions on a data panel of 609 school districts between 1990 and 2010. Treating for the endogeneity of school district income…

Using a Polytope to Estimate Efficient Production Functions of Joint Product Processes.

ERIC Educational Resources Information Center

Simpson, William A.

In the last decade, a modeling technique has been developed to handle complex input/output analyses where outputs involve joint products and there are no known mathematical relationships linking the outputs or inputs. The technique uses the geometrical concept of a six-dimensional shape called a polytope to analyze the efficiency of each…

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.

Statistical linearization for multi-input/multi-output nonlinearities

NASA Technical Reports Server (NTRS)

Lin, Ching-An; Cheng, Victor H. L.

1991-01-01

Formulas are derived for the computation of the random input-describing functions for MIMO nonlinearities; these straightforward and rigorous derivations are based on the optimal mean square linear approximation. The computations involve evaluations of multiple integrals. It is shown that, for certain classes of nonlinearities, multiple-integral evaluations are obviated and the computations are significantly simplified.

The application of remote sensing to the development and formulation of hydrologic planning models

NASA Technical Reports Server (NTRS)

Castruccio, P. A.; Loats, H. L., Jr.; Fowler, T. R.

1976-01-01

A hydrologic planning model is developed based on remotely sensed inputs. Data from LANDSAT 1 are used to supply the model's quantitative parameters and coefficients. The use of LANDSAT data as information input to all categories of hydrologic models requiring quantitative surface parameters for their effects functioning is also investigated.

Listening to Another Sense: Somatosensory Integration in the Auditory System

PubMed Central

Wu, Calvin; Stefanescu, Roxana A.; Martel, David T.

2014-01-01

Conventionally, sensory systems are viewed as separate entities, each with its own physiological process serving a different purpose. However, many functions require integrative inputs from multiple sensory systems, and sensory intersection and convergence occur throughout the central nervous system. The neural processes for hearing perception undergo significant modulation by the two other major sensory systems, vision and somatosensation. This synthesis occurs at every level of the ascending auditory pathway: the cochlear nucleus, inferior colliculus, medial geniculate body, and the auditory cortex. In this review, we explore the process of multisensory integration from 1) anatomical (inputs and connections), 2) physiological (cellular responses), 3) functional, and 4) pathological aspects. We focus on the convergence between auditory and somatosensory inputs in each ascending auditory station. This review highlights the intricacy of sensory processing, and offers a multisensory perspective regarding the understanding of sensory disorders. PMID:25526698

Analog Computation by DNA Strand Displacement Circuits.

PubMed

Song, Tianqi; Garg, Sudhanshu; Mokhtar, Reem; Bui, Hieu; Reif, John

2016-08-19

DNA circuits have been widely used to develop biological computing devices because of their high programmability and versatility. Here, we propose an architecture for the systematic construction of DNA circuits for analog computation based on DNA strand displacement. The elementary gates in our architecture include addition, subtraction, and multiplication gates. The input and output of these gates are analog, which means that they are directly represented by the concentrations of the input and output DNA strands, respectively, without requiring a threshold for converting to Boolean signals. We provide detailed domain designs and kinetic simulations of the gates to demonstrate their expected performance. On the basis of these gates, we describe how DNA circuits to compute polynomial functions of inputs can be built. Using Taylor Series and Newton Iteration methods, functions beyond the scope of polynomials can also be computed by DNA circuits built upon our architecture.

An exact algebraic solution of the infimum in H-infinity optimization with output feedback

NASA Technical Reports Server (NTRS)

Chen, Ben M.; Saberi, Ali; Ly, Uy-Loi

1991-01-01

This paper presents a simple and noniterative procedure for the computation of the exact value of the infimum in the standard H-infinity-optimal control with output feedback. The problem formulation is general and does not place any restrictions on the direct feedthrough terms between the control input and the controlled output variables, and between the disturbance input and the measurement output variables. The method is applicable to systems that satisfy (1) the transfer function from the control input to the controlled output is right-invertible and has no invariant zeros on the j(w) axis and, (2) the transfer function from the disturbance to the measurement output is left-invertible and has no invariant zeros on the j(w) axis. A set of necessary and sufficient conditions for the solvability of H-infinity-almost disturbance decoupling problem via measurement feedback with internal stability is also given.

Electronic system for high power load control. [solar arrays

NASA Technical Reports Server (NTRS)

Miller, E. L. (Inventor)

1980-01-01

Parallel current paths are divided into two groups, with control devices in the current paths of one group each having a current limiting resistor, and the control devices in the other group each having no limiting resistor, so that when the control devices of the second group are turned fully on, a short circuit is achieved by the arrangement of parallel current paths. Separate but coordinated control signals are provided to turn on the control devices of the first group and increase their conduction toward saturation as a function of control input, and when fully on, or shortly before, to turn on the control devices of the second group and increase their conduction toward saturation as a function of the control input as that input continues to increase. Electronic means may be used to generate signals. The system may be used for 1-V characteristic measurements of solar arrays as well as for other load control purposes.

System/observer/controller identification toolbox

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Horta, Lucas G.; Phan, Minh

1992-01-01

System Identification is the process of constructing a mathematical model from input and output data for a system under testing, and characterizing the system uncertainties and measurement noises. The mathematical model structure can take various forms depending upon the intended use. The SYSTEM/OBSERVER/CONTROLLER IDENTIFICATION TOOLBOX (SOCIT) is a collection of functions, written in MATLAB language and expressed in M-files, that implements a variety of modern system identification techniques. For an open loop system, the central features of the SOCIT are functions for identification of a system model and its corresponding forward and backward observers directly from input and output data. The system and observers are represented by a discrete model. The identified model and observers may be used for controller design of linear systems as well as identification of modal parameters such as dampings, frequencies, and mode shapes. For a closed-loop system, an observer and its corresponding controller gain directly from input and output data.

A radiation model for calculating atmospheric corrections to remotely sensed infrared measurements, version 2

NASA Technical Reports Server (NTRS)

Boudreau, R. D.

1973-01-01

A numerical model is developed which calculates the atmospheric corrections to infrared radiometric measurements due to absorption and emission by water vapor, carbon dioxide, and ozone. The corrections due to aerosols are not accounted for. The transmissions functions for water vapor, carbon dioxide, and water are given. The model requires as input the vertical distribution of temperature and water vapor as determined by a standard radiosonde. The vertical distribution of carbon dioxide is assumed to be constant. The vertical distribution of ozone is an average of observed values. The model also requires as input the spectral response function of the radiometer and the nadir angle at which the measurements were made. A listing of the FORTRAN program is given with details for its use and examples of input and output listings. Calculations for four model atmospheres are presented.

Adaptive Neural Control of Uncertain MIMO Nonlinear Systems With State and Input Constraints.

PubMed

Chen, Ziting; Li, Zhijun; Chen, C L Philip

2017-06-01

An adaptive neural control strategy for multiple input multiple output nonlinear systems with various constraints is presented in this paper. To deal with the nonsymmetric input nonlinearity and the constrained states, the proposed adaptive neural control is combined with the backstepping method, radial basis function neural network, barrier Lyapunov function (BLF), and disturbance observer. By ensuring the boundedness of the BLF of the closed-loop system, it is demonstrated that the output tracking is achieved with all states remaining in the constraint sets and the general assumption on nonsingularity of unknown control coefficient matrices has been eliminated. The constructed adaptive neural control has been rigorously proved that it can guarantee the semiglobally uniformly ultimate boundedness of all signals in the closed-loop system. Finally, the simulation studies on a 2-DOF robotic manipulator system indicate that the designed adaptive control is effective.

Airflow and optic flow mediate antennal positioning in flying honeybees

PubMed Central

Roy Khurana, Taruni; Sane, Sanjay P

2016-01-01

To maintain their speeds during navigation, insects rely on feedback from their visual and mechanosensory modalities. Although optic flow plays an essential role in speed determination, it is less reliable under conditions of low light or sparse landmarks. Under such conditions, insects rely on feedback from antennal mechanosensors but it is not clear how these inputs combine to elicit flight-related antennal behaviours. We here show that antennal movements of the honeybee, Apis mellifera, are governed by combined visual and antennal mechanosensory inputs. Frontal airflow, as experienced during forward flight, causes antennae to actively move forward as a sigmoidal function of absolute airspeed values. However, corresponding front-to-back optic flow causes antennae to move backward, as a linear function of relative optic flow, opposite the airspeed response. When combined, these inputs maintain antennal position in a state of dynamic equilibrium. DOI: http://dx.doi.org/10.7554/eLife.14449.001 PMID:27097104

Refining Linear Fuzzy Rules by Reinforcement Learning

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.; Khedkar, Pratap S.; Malkani, Anil

1996-01-01

Linear fuzzy rules are increasingly being used in the development of fuzzy logic systems. Radial basis functions have also been used in the antecedents of the rules for clustering in product space which can automatically generate a set of linear fuzzy rules from an input/output data set. Manual methods are usually used in refining these rules. This paper presents a method for refining the parameters of these rules using reinforcement learning which can be applied in domains where supervised input-output data is not available and reinforcements are received only after a long sequence of actions. This is shown for a generalization of radial basis functions. The formation of fuzzy rules from data and their automatic refinement is an important step in closing the gap between the application of reinforcement learning methods in the domains where only some limited input-output data is available.

Six axis force feedback input device

NASA Technical Reports Server (NTRS)

Ohm, Timothy (Inventor)

1998-01-01

The present invention is a low friction, low inertia, six-axis force feedback input device comprising an arm with double-jointed, tendon-driven revolute joints, a decoupled tendon-driven wrist, and a base with encoders and motors. The input device functions as a master robot manipulator of a microsurgical teleoperated robot system including a slave robot manipulator coupled to an amplifier chassis, which is coupled to a control chassis, which is coupled to a workstation with a graphical user interface. The amplifier chassis is coupled to the motors of the master robot manipulator and the control chassis is coupled to the encoders of the master robot manipulator. A force feedback can be applied to the input device and can be generated from the slave robot to enable a user to operate the slave robot via the input device without physically viewing the slave robot. Also, the force feedback can be generated from the workstation to represent fictitious forces to constrain the input device's control of the slave robot to be within imaginary predetermined boundaries.

Fuzzy parametric uncertainty analysis of linear dynamical systems: A surrogate modeling approach

NASA Astrophysics Data System (ADS)

Chowdhury, R.; Adhikari, S.

2012-10-01

Uncertainty propagation engineering systems possess significant computational challenges. This paper explores the possibility of using correlated function expansion based metamodelling approach when uncertain system parameters are modeled using Fuzzy variables. In particular, the application of High-Dimensional Model Representation (HDMR) is proposed for fuzzy finite element analysis of dynamical systems. The HDMR expansion is a set of quantitative model assessment and analysis tools for capturing high-dimensional input-output system behavior based on a hierarchy of functions of increasing dimensions. The input variables may be either finite-dimensional (i.e., a vector of parameters chosen from the Euclidean space RM) or may be infinite-dimensional as in the function space CM[0,1]. The computational effort to determine the expansion functions using the alpha cut method scales polynomially with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is integrated with a commercial Finite Element software. Modal analysis of a simplified aircraft wing with Fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations.

Application of a water quality model in the White Cart water catchment, Glasgow, UK.

PubMed

Liu, S; Tucker, P; Mansell, M; Hursthouse, A

2003-03-01

Water quality models of urban systems have previously focused on point source (sewerage system) inputs. Little attention has been given to diffuse inputs and research into diffuse pollution has been largely confined to agriculture sources. This paper reports on new research that is aimed at integrating diffuse inputs into an urban water quality model. An integrated model is introduced that is made up of four modules: hydrology, contaminant point sources, nutrient cycling and leaching. The hydrology module, T&T consists of a TOPMODEL (a TOPography-based hydrological MODEL), which simulates runoff from pervious areas and a two-tank model, which simulates runoff from impervious urban areas. Linked into the two-tank model, the contaminant point source module simulates the overflow from the sewerage system in heavy rain. The widely known SOILN (SOIL Nitrate model) is the basis of nitrogen cycle module. Finally, the leaching module consists of two functions: the production function and the transfer function. The production function is based on SLIM (Solute Leaching Intermediate Model) while the transfer function is based on the 'flushing hypothesis' which postulates a relationship between contaminant concentrations in the receiving water course and the extent to which the catchment is saturated. This paper outlines the modelling methodology and the model structures that have been developed. An application of this model in the White Cart catchment (Glasgow) is also included.

Image classification at low light levels

NASA Astrophysics Data System (ADS)

Wernick, Miles N.; Morris, G. Michael

1986-12-01

An imaging photon-counting detector is used to achieve automatic sorting of two image classes. The classification decision is formed on the basis of the cross correlation between a photon-limited input image and a reference function stored in computer memory. Expressions for the statistical parameters of the low-light-level correlation signal are given and are verified experimentally. To obtain a correlation-based system for two-class sorting, it is necessary to construct a reference function that produces useful information for class discrimination. An expression for such a reference function is derived using maximum-likelihood decision theory. Theoretically predicted results are used to compare on the basis of performance the maximum-likelihood reference function with Fukunaga-Koontz basis vectors and average filters. For each method, good class discrimination is found to result in milliseconds from a sparse sampling of the input image.

In Search of a Visual-cortical Describing Function: a Summary of Work in Progress

NASA Technical Reports Server (NTRS)

Junker, A. M.; Peio, K. J.

1984-01-01

The thrust of the present work is to explore the utility of using a sum of sinusoids (seven or more) to obtain an evoked response and, furthermore, to see if the response is sensitive to changes in cognitive processing. Within the field of automatic control system technology, a mathematical input/output relationship for a sinusoidally stimulated nonlinear system is defined as describing function. Applying this technology, sum of sines inputs to yield describing functions for the visual-cortical response have been designed. What follows is a description of the method used to obtain visual-cortical describing functions. A number of measurement system redesigns were necessary to achieve the desired frequency resolution. Results that guided and came out of the redesigns are presented. Preliminary results of stimulus parameter effects (average intensity and depth of modulation) are also shown.

Round window closure affects cochlear responses to suprathreshold stimuli.

PubMed

Cai, Qunfeng; Whitcomb, Carolyn; Eggleston, Jessica; Sun, Wei; Salvi, Richard; Hu, Bo Hua

2013-12-01

The round window acts as a vent for releasing inner ear pressure and facilitating basilar membrane vibration. Loss of this venting function affects cochlear function, which leads to hearing impairment. In an effort to identify functional changes that might be used in clinical diagnosis of round window atresia, the current investigation was designed to examine how the cochlea responds to suprathreshold stimuli following round window closure. Prospective, controlled, animal study. A rat model of round window occlusion (RWO) was established. With this model, the thresholds of auditory brainstem responses (ABR) and the input/output (IO) functions of distortion product otoacoustic emissions (DPOAEs) and acoustic startle responses were examined. Round window closure caused a mild shift in the thresholds of the auditory brainstem response (13.5 ± 9.1 dB). It also reduced the amplitudes of the distortion product otoacoustic emissions and the slope of the input/output functions. This peripheral change was accompanied by a significant reduction in the amplitude, but not the threshold, of the acoustic startle reflex, a motor response to suprathreshold sounds. In addition to causing mild increase in the threshold of the auditory brainstem response, round window occlusion reduced the slopes of both distortion product otoacoustic emissions and startle reflex input/output functions. These changes differ from those observed for typical conductive or sensory hearing loss, and could be present in patients with round window atresia. However, future clinical observations in patients are needed to confirm these findings. Copyright © 2013 The American Laryngological, Rhinological and Otological Society, Inc.

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

Nishimura, Takahiro, E-mail: t-nishimura@ist.osaka-u.ac.jp; Fujii, Ryo; Ogura, Yusuke

Molecular logic circuits represent a promising technology for observation and manipulation of biological systems at the molecular level. However, the implementation of molecular logic circuits for temporal and programmable operation remains challenging. In this paper, we demonstrate an optically controllable logic circuit that uses fluorescence resonance energy transfer (FRET) for signaling. The FRET-based signaling process is modulated by both molecular and optical inputs. Based on the distance dependence of FRET, the FRET pathways required to execute molecular logic operations are formed on a DNA nanostructure as a circuit based on its molecular inputs. In addition, the FRET pathways on themore » DNA nanostructure are controlled optically, using photoswitching fluorescent molecules to instruct the execution of the desired operation and the related timings. The behavior of the circuit can thus be controlled using external optical signals. As an example, a molecular logic circuit capable of executing two different logic operations was studied. The circuit contains functional DNAs and a DNA scaffold to construct two FRET routes for executing Input 1 AND Input 2 and Input 1 AND NOT Input 3 operations on molecular inputs. The circuit produced the correct outputs with all possible combinations of the inputs by following the light signals. Moreover, the operation execution timings were controlled based on light irradiation and the circuit responded to time-dependent inputs. The experimental results demonstrate that the circuit changes the output for the required operations following the input of temporal light signals.« less

Experimental industrial signal acquisition board in a large scientific device

NASA Astrophysics Data System (ADS)

Zeng, Xiangzhen; Ren, Bin

2018-02-01

In order to measure the industrial signal of neutrino experiment, a set of general-purpose industrial data acquisition board has been designed. It includes the function of switch signal input and output, and the function of analog signal input. The main components are signal isolation amplifier and filter circuit, ADC circuit, microcomputer systems and isolated communication interface circuit. Through the practical experiments, it shows that the system is flexible, reliable, convenient and economical, and the system has characters of high definition and strong anti-interference ability. Thus, the system fully meets the design requirements.

Experimental evaluation of a unique radiometer for use in solar simulation testing

NASA Technical Reports Server (NTRS)

Richmond, R. G.

1978-01-01

The vane radiometer is designed to operate over the range 0-1 solar constant and is capable of withstanding temperatures over the range -200 to +175 C. Two of these radiometers, for use in the Johnson Space Center's largest space simulator, have been evaluated for: (1) thermal sensitivity with no solar input, (2) linearity as a function of solar simulation input, and (3) output drift as a function of time. The minimum sensitivity was measured to be approximately 25.5 mV/solar constant. An unusual effect in the pressure range 760 to 1.0 torr is discussed.

Constant-Elasticity-of-Substitution Simulation

NASA Technical Reports Server (NTRS)

Reiter, G.

1986-01-01

Program simulates constant elasticity-of-substitution (CES) production function. CES function used by economic analysts to examine production costs as well as uncertainties in production. User provides such input parameters as price of labor, price of capital, and dispersion levels. CES minimizes expected cost to produce capital-uncertainty pair. By varying capital-value input, one obtains series of capital-uncertainty pairs. Capital-uncertainty pairs then used to generate several cost curves. CES program menu driven and features specific print menu for examining selected output curves. Program written in BASIC for interactive execution and implemented on IBM PC-series computer.

Capability and Health Functioning in Ethiopian Households

ERIC Educational Resources Information Center

Mabsout, Ramzi

2011-01-01

From a recent Ethiopian representative household survey this paper empirically operationalizes concepts from the capability approach to shed light on the relationship between conversion factors, capability inputs and health functionings. The subjects of the study are women in partnership. The results suggest their health functionings are…

Generalized local emission tomography

DOEpatents

Katsevich, Alexander J.

1998-01-01

Emission tomography enables locations and values of internal isotope density distributions to be determined from radiation emitted from the whole object. In the method for locating the values of discontinuities, the intensities of radiation emitted from either the whole object or a region of the object containing the discontinuities are inputted to a local tomography function .function..sub..LAMBDA..sup.(.PHI.) to define the location S of the isotope density discontinuity. The asymptotic behavior of .function..sub..LAMBDA..sup.(.PHI.) is determined in a neighborhood of S, and the value for the discontinuity is estimated from the asymptotic behavior of .function..sub..LAMBDA..sup.(.PHI.) knowing pointwise values of the attenuation coefficient within the object. In the method for determining the location of the discontinuity, the intensities of radiation emitted from an object are inputted to a local tomography function .function..sub..LAMBDA..sup.(.PHI.) to define the location S of the density discontinuity and the location .GAMMA. of the attenuation coefficient discontinuity. Pointwise values of the attenuation coefficient within the object need not be known in this case.

Spike Triggered Covariance in Strongly Correlated Gaussian Stimuli

PubMed Central

Aljadeff, Johnatan; Segev, Ronen; Berry, Michael J.; Sharpee, Tatyana O.

2013-01-01

Many biological systems perform computations on inputs that have very large dimensionality. Determining the relevant input combinations for a particular computation is often key to understanding its function. A common way to find the relevant input dimensions is to examine the difference in variance between the input distribution and the distribution of inputs associated with certain outputs. In systems neuroscience, the corresponding method is known as spike-triggered covariance (STC). This method has been highly successful in characterizing relevant input dimensions for neurons in a variety of sensory systems. So far, most studies used the STC method with weakly correlated Gaussian inputs. However, it is also important to use this method with inputs that have long range correlations typical of the natural sensory environment. In such cases, the stimulus covariance matrix has one (or more) outstanding eigenvalues that cannot be easily equalized because of sampling variability. Such outstanding modes interfere with analyses of statistical significance of candidate input dimensions that modulate neuronal outputs. In many cases, these modes obscure the significant dimensions. We show that the sensitivity of the STC method in the regime of strongly correlated inputs can be improved by an order of magnitude or more. This can be done by evaluating the significance of dimensions in the subspace orthogonal to the outstanding mode(s). Analyzing the responses of retinal ganglion cells probed with Gaussian noise, we find that taking into account outstanding modes is crucial for recovering relevant input dimensions for these neurons. PMID:24039563

The Historical Role of the Production Function in Economics and Business

ERIC Educational Resources Information Center

Gordon, David; Vaughan, Richard

2011-01-01

The production function explains a basic technological relationship between scarce resources, or inputs, and output. This paper offers a brief overview of the historical significance and operational role of the production function in business and economics. The origin and development of this function over time is initially explored. Several…

Optimum free energy in the reference functional approach for the integral equations theory

NASA Astrophysics Data System (ADS)

Ayadim, A.; Oettel, M.; Amokrane, S.

2009-03-01

We investigate the question of determining the bulk properties of liquids, required as input for practical applications of the density functional theory of inhomogeneous systems, using density functional theory itself. By considering the reference functional approach in the test particle limit, we derive an expression of the bulk free energy that is consistent with the closure of the Ornstein-Zernike equations in which the bridge functions are obtained from the reference system bridge functional. By examining the connection between the free energy functional and the formally exact bulk free energy, we obtain an improved expression of the corresponding non-local term in the standard reference hypernetted chain theory derived by Lado. In this way, we also clarify the meaning of the recently proposed criterion for determining the optimum hard-sphere diameter in the reference system. This leads to a theory in which the sole input is the reference system bridge functional both for the homogeneous system and the inhomogeneous one. The accuracy of this method is illustrated with the standard case of the Lennard-Jones fluid and with a Yukawa fluid with very short range attraction.

Evolution of optimal Hill coefficients in nonlinear public goods games.

PubMed

Archetti, Marco; Scheuring, István

2016-10-07

In evolutionary game theory, the effect of public goods like diffusible molecules has been modelled using linear, concave, sigmoid and step functions. The observation that biological systems are often sigmoid input-output functions, as described by the Hill equation, suggests that a sigmoid function is more realistic. The Michaelis-Menten model of enzyme kinetics, however, predicts a concave function, and while mechanistic explanations of sigmoid kinetics exist, we lack an adaptive explanation: what is the evolutionary advantage of a sigmoid benefit function? We analyse public goods games in which the shape of the benefit function can evolve, in order to determine the optimal and evolutionarily stable Hill coefficients. We find that, while the dynamics depends on whether output is controlled at the level of the individual or the population, intermediate or high Hill coefficients often evolve, leading to sigmoid input-output functions that for some parameters are so steep to resemble a step function (an on-off switch). Our results suggest that, even when the shape of the benefit function is unknown, biological public goods should be modelled using a sigmoid or step function rather than a linear or concave function. Copyright © 2016 Elsevier Ltd. All rights reserved.

Measuring circadian and acute light responses in mice using wheel running activity.

PubMed

LeGates, Tara A; Altimus, Cara M

2011-02-04

Circadian rhythms are physiological functions that cycle over a period of approximately 24 hours (circadian- circa: approximate and diem: day). They are responsible for timing our sleep/wake cycles and hormone secretion. Since this timing is not precisely 24-hours, it is synchronized to the solar day by light input. This is accomplished via photic input from the retina to the suprachiasmatic nucleus (SCN) which serves as the master pacemaker synchronizing peripheral clocks in other regions of the brain and peripheral tissues to the environmental light dark cycle. The alignment of rhythms to this environmental light dark cycle organizes particular physiological events to the correct temporal niche, which is crucial for survival. For example, mice sleep during the day and are active at night. This ability to consolidate activity to either the light or dark portion of the day is referred to as circadian photoentrainment and requires light input to the circadian clock. Activity of mice at night is robust particularly in the presence of a running wheel. Measuring this behavior is a minimally invasive method that can be used to evaluate the functionality of the circadian system as well as light input to this system. Methods that will covered here are used to examine the circadian clock, light input to this system, as well as the direct influence of light on wheel running behavior.

Characteristic operator functions for quantum input-plant-output models and coherent control

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

Gough, John E.

We introduce the characteristic operator as the generalization of the usual concept of a transfer function of linear input-plant-output systems to arbitrary quantum nonlinear Markovian input-output models. This is intended as a tool in the characterization of quantum feedback control systems that fits in with the general theory of networks. The definition exploits the linearity of noise differentials in both the plant Heisenberg equations of motion and the differential form of the input-output relations. Mathematically, the characteristic operator is a matrix of dimension equal to the number of outputs times the number of inputs (which must coincide), but with entriesmore » that are operators of the plant system. In this sense, the characteristic operator retains details of the effective plant dynamical structure and is an essentially quantum object. We illustrate the relevance to model reduction and simplification definition by showing that the convergence of the characteristic operator in adiabatic elimination limit models requires the same conditions and assumptions appearing in the work on limit quantum stochastic differential theorems of Bouten and Silberfarb [Commun. Math. Phys. 283, 491-505 (2008)]. This approach also shows in a natural way that the limit coefficients of the quantum stochastic differential equations in adiabatic elimination problems arise algebraically as Schur complements and amounts to a model reduction where the fast degrees of freedom are decoupled from the slow ones and eliminated.« less

Connectivity in the human brain dissociates entropy and complexity of auditory inputs.

PubMed

Nastase, Samuel A; Iacovella, Vittorio; Davis, Ben; Hasson, Uri

2015-03-01

Complex systems are described according to two central dimensions: (a) the randomness of their output, quantified via entropy; and (b) their complexity, which reflects the organization of a system's generators. Whereas some approaches hold that complexity can be reduced to uncertainty or entropy, an axiom of complexity science is that signals with very high or very low entropy are generated by relatively non-complex systems, while complex systems typically generate outputs with entropy peaking between these two extremes. In understanding their environment, individuals would benefit from coding for both input entropy and complexity; entropy indexes uncertainty and can inform probabilistic coding strategies, whereas complexity reflects a concise and abstract representation of the underlying environmental configuration, which can serve independent purposes, e.g., as a template for generalization and rapid comparisons between environments. Using functional neuroimaging, we demonstrate that, in response to passively processed auditory inputs, functional integration patterns in the human brain track both the entropy and complexity of the auditory signal. Connectivity between several brain regions scaled monotonically with input entropy, suggesting sensitivity to uncertainty, whereas connectivity between other regions tracked entropy in a convex manner consistent with sensitivity to input complexity. These findings suggest that the human brain simultaneously tracks the uncertainty of sensory data and effectively models their environmental generators. Copyright © 2014. Published by Elsevier Inc.

Quality factor concept in piezoceramic transformer performance description.

PubMed

Mezheritsky, Alex V

2006-02-01

A new general approach based on the quality factor concept to piezoceramic transformer (PT) performance description is proposed. The system's quality factor, material elastic anisotropy, and coupling factors of the input and output sections of an electrically excited and electrically loaded PT fully characterize its resonance and near-resonance behavior. The PT efficiency, transformation ratio, and input and output power were analytically analyzed and simulated as functions of the load and frequency for the simplest classical Langevin-type and Rosen-type PT designs. A new formulation of the electrical input impedance allows one to separate the power consumed by PT from the power transferred into the load. The system's PT quality factor takes into account losses in each PT "input-output-load" functional components. The loading process is changing PT input electrical impedance on the way that under loading the minimum series impedance is increasing and the maximum parallel impedance is decreasing coincidentally. The quality-factors ratio, between the states of fully loaded and nonloaded PT, is one of the best measures of PTs dynamic performance--practically, the lower the ratio is, the better PT efficiency. A simple and effective method for the loaded PT quality factor determination is proposed. As was found, a piezoceramic with low piezoelectric anisotropy is required to provide maximum PT efficiency and higher corresponding voltage gain. Limitations on the PT output voltage and power, caused by nonlinear effects in piezoceramics, were established.

Deletion of Ten-m3 Induces the Formation of Eye Dominance Domains in Mouse Visual Cortex

PubMed Central

Merlin, Sam; Horng, Sam; Marotte, Lauren R.; Sur, Mriganka; Sawatari, Atomu

2013-01-01

The visual system is characterized by precise retinotopic mapping of each eye, together with exquisitely matched binocular projections. In many species, the inputs that represent the eyes are segregated into ocular dominance columns in primary visual cortex (V1), whereas in rodents, this does not occur. Ten-m3, a member of the Ten-m/Odz/Teneurin family, regulates axonal guidance in the retinogeniculate pathway. Significantly, ipsilateral projections are expanded in the dorsal lateral geniculate nucleus and are not aligned with contralateral projections in Ten-m3 knockout (KO) mice. Here, we demonstrate the impact of altered retinogeniculate mapping on the organization and function of V1. Transneuronal tracing and c-fos immunohistochemistry demonstrate that the subcortical expansion of ipsilateral input is conveyed to V1 in Ten-m3 KOs: Ipsilateral inputs are widely distributed across V1 and are interdigitated with contralateral inputs into eye dominance domains. Segregation is confirmed by optical imaging of intrinsic signals. Single-unit recording shows ipsilateral, and contralateral inputs are mismatched at the level of single V1 neurons, and binocular stimulation leads to functional suppression of these cells. These findings indicate that the medial expansion of the binocular zone together with an interocular mismatch is sufficient to induce novel structural features, such as eye dominance domains in rodent visual cortex. PMID:22499796

Chinchilla middle ear transmission matrix model and middle-ear flexibilitya)

PubMed Central

Ravicz, Michael E.; Rosowski, John J.

2017-01-01

The function of the middle ear (ME) in transforming ME acoustic inputs and outputs (sound pressures and volume velocities) can be described with an acoustic two-port transmission matrix. This description is independent of the load on the ME (cochlea or ear canal) and holds in either direction: forward (from ear canal to cochlea) or reverse (from cochlea to ear canal). A transmission matrix describing ME function in chinchilla, an animal commonly used in auditory research, is presented, computed from measurements of forward ME function: input admittance YTM, ME pressure gain GMEP, ME velocity transfer function HV, and cochlear input admittance YC, in the same set of ears [Ravicz and Rosowski (2012b). J. Acoust. Soc. Am. 132, 2437–2454; (2013a). J. Acoust. Soc. Am. 133, 2208–2223; (2013b). J. Acoust. Soc. Am. 134, 2852–2865]. Unlike previous estimates, these computations require no assumptions about the state of the inner ear, effectiveness of ME manipulations, or measurements of sound transmission in the reverse direction. These element values are generally consistent with physical constraints and the anatomical ME “transformer ratio.” Differences from a previous estimate in chinchilla [Songer and Rosowski (2007). J. Acoust. Soc. Am. 122, 932–942] may be due to a difference in ME flexibility between the two subject groups. PMID:28599566

Chinchilla middle ear transmission matrix model and middle-ear flexibility.

PubMed

Ravicz, Michael E; Rosowski, John J

2017-05-01

The function of the middle ear (ME) in transforming ME acoustic inputs and outputs (sound pressures and volume velocities) can be described with an acoustic two-port transmission matrix. This description is independent of the load on the ME (cochlea or ear canal) and holds in either direction: forward (from ear canal to cochlea) or reverse (from cochlea to ear canal). A transmission matrix describing ME function in chinchilla, an animal commonly used in auditory research, is presented, computed from measurements of forward ME function: input admittance Y TM , ME pressure gain G MEP , ME velocity transfer function H V , and cochlear input admittance Y C , in the same set of ears [Ravicz and Rosowski (2012b). J. Acoust. Soc. Am. 132, 2437-2454; (2013a). J. Acoust. Soc. Am. 133, 2208-2223; (2013b). J. Acoust. Soc. Am. 134, 2852-2865]. Unlike previous estimates, these computations require no assumptions about the state of the inner ear, effectiveness of ME manipulations, or measurements of sound transmission in the reverse direction. These element values are generally consistent with physical constraints and the anatomical ME "transformer ratio." Differences from a previous estimate in chinchilla [Songer and Rosowski (2007). J. Acoust. Soc. Am. 122, 932-942] may be due to a difference in ME flexibility between the two subject groups.

Constructing general partial differential equations using polynomial and neural networks.

PubMed

Zjavka, Ladislav; Pedrycz, Witold

2016-01-01

Sum fraction terms can approximate multi-variable functions on the basis of discrete observations, replacing a partial differential equation definition with polynomial elementary data relation descriptions. Artificial neural networks commonly transform the weighted sum of inputs to describe overall similarity relationships of trained and new testing input patterns. Differential polynomial neural networks form a new class of neural networks, which construct and solve an unknown general partial differential equation of a function of interest with selected substitution relative terms using non-linear multi-variable composite polynomials. The layers of the network generate simple and composite relative substitution terms whose convergent series combinations can describe partial dependent derivative changes of the input variables. This regression is based on trained generalized partial derivative data relations, decomposed into a multi-layer polynomial network structure. The sigmoidal function, commonly used as a nonlinear activation of artificial neurons, may transform some polynomial items together with the parameters with the aim to improve the polynomial derivative term series ability to approximate complicated periodic functions, as simple low order polynomials are not able to fully make up for the complete cycles. The similarity analysis facilitates substitutions for differential equations or can form dimensional units from data samples to describe real-world problems. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cognitive functions of intracellular mechanisms for contextual amplification.

PubMed

Phillips, William A

2017-03-01

Evidence for the hypothesis that input to the apical tufts of neocortical pyramidal cells plays a central role in cognition by amplifying their responses to feedforward input is reviewed. Apical tufts are electrically remote from the soma, and their inputs come from diverse sources including direct feedback from higher cortical regions, indirect feedback via the thalamus, and long-range lateral connections both within and between cortical regions. This suggests that input to tuft dendrites may amplify the cell's response to basal inputs that they receive via layer 4 and which have synapses closer to the soma. ERP data supporting this inference is noted. Intracellular studies of apical amplification (AA) and of disamplification by inhibitory interneurons targeted only at tufts are reviewed. Cognitive processes that have been related to them by computational, electrophysiological, and psychopathological studies are then outlined. These processes include: figure-ground segregation and Gestalt grouping; contextual disambiguation in perception and sentence comprehension; priming; winner-take-all competition; attention and working memory; setting the level of consciousness; cognitive control; and learning. It is argued that theories in cognitive neuroscience should not assume that all neurons function as integrate-and-fire point processors, but should use the capabilities of cells with distinct sites of integration for driving and modulatory inputs. Potentially 'unifying' theories that depend upon these capabilities are reviewed. It is concluded that evolution of the primitives of AA and disamplification in neocortex may have extended cognitive capabilities beyond those built from the long-established primitives of excitation, inhibition, and disinhibition. Copyright © 2015 Elsevier Inc. All rights reserved.

Stream-related preferences of inputs to the superior colliculus from areas of dorsal and ventral streams of mouse visual cortex.

PubMed

Wang, Quanxin; Burkhalter, Andreas

2013-01-23

Previous studies of intracortical connections in mouse visual cortex have revealed two subnetworks that resemble the dorsal and ventral streams in primates. Although calcium imaging studies have shown that many areas of the ventral stream have high spatial acuity whereas areas of the dorsal stream are highly sensitive for transient visual stimuli, there are some functional inconsistencies that challenge a simple grouping into "what/perception" and "where/action" streams known in primates. The superior colliculus (SC) is a major center for processing of multimodal sensory information and the motor control of orienting the eyes, head, and body. Visual processing is performed in superficial layers, whereas premotor activity is generated in deep layers of the SC. Because the SC is known to receive input from visual cortex, we asked whether the projections from 10 visual areas of the dorsal and ventral streams terminate in differential depth profiles within the SC. We found that inputs from primary visual cortex are by far the strongest. Projections from the ventral stream were substantially weaker, whereas the sparsest input originated from areas of the dorsal stream. Importantly, we found that ventral stream inputs terminated in superficial layers, whereas dorsal stream inputs tended to be patchy and either projected equally to superficial and deep layers or strongly preferred deep layers. The results suggest that the anatomically defined ventral and dorsal streams contain areas that belong to distinct functional systems, specialized for the processing of visual information and visually guided action, respectively.

Modeling development of natural multi-sensory integration using neural self-organisation and probabilistic population codes

NASA Astrophysics Data System (ADS)

Bauer, Johannes; Dávila-Chacón, Jorge; Wermter, Stefan

2015-10-01

Humans and other animals have been shown to perform near-optimally in multi-sensory integration tasks. Probabilistic population codes (PPCs) have been proposed as a mechanism by which optimal integration can be accomplished. Previous approaches have focussed on how neural networks might produce PPCs from sensory input or perform calculations using them, like combining multiple PPCs. Less attention has been given to the question of how the necessary organisation of neurons can arise and how the required knowledge about the input statistics can be learned. In this paper, we propose a model of learning multi-sensory integration based on an unsupervised learning algorithm in which an artificial neural network learns the noise characteristics of each of its sources of input. Our algorithm borrows from the self-organising map the ability to learn latent-variable models of the input and extends it to learning to produce a PPC approximating a probability density function over the latent variable behind its (noisy) input. The neurons in our network are only required to perform simple calculations and we make few assumptions about input noise properties and tuning functions. We report on a neurorobotic experiment in which we apply our algorithm to multi-sensory integration in a humanoid robot to demonstrate its effectiveness and compare it to human multi-sensory integration on the behavioural level. We also show in simulations that our algorithm performs near-optimally under certain plausible conditions, and that it reproduces important aspects of natural multi-sensory integration on the neural level.

Carbon and nitrogen inputs affect soil microbial community structure and function

NASA Astrophysics Data System (ADS)

Liu, X. J. A.; Mau, R. L.; Hayer, M.; Finley, B. K.; Schwartz, E.; Dijkstra, P.; Hungate, B. A.

2016-12-01

Climate change has been projected to increase energy and nutrient inputs to soils, affecting soil organic matter (SOM) decomposition (priming effect) and microbial communities. However, many important questions remain: how do labile C and/or N inputs affect priming and microbial communities? What is the relationship between them? To address these questions, we applied N (NH4NO3 ; 100 µg N g-1 wk-1), C (13C glucose; 1000 µg C g-1 wk-1), C+N to four different soils for five weeks. We found: 1) N showed no effect, whereas C induced the greatest priming, and C+N had significantly lower priming than C. 2) C and C+N additions increased the relative abundance of actinobacteria, proteobacteria, and firmicutes, but reduced relative abundance of acidobacteria, chloroflexi, verrucomicrobia, planctomycetes, and gemmatimonadetes. 3) Actinobacteria and proteobacteria increased relative abundance over time, but most others decreased over time. 4) substrate additions (N, C, C+N) significantly reduced microbial alpha diversity, which also decreased over time. 5) For beta diversity, C and C+N formed significantly different communities compare to the control and N treatments. Overtime, microbial community structure significantly altered. Four soils have drastically different community structures. These results indicate amounts of substrate C were determinant factors in modulating the rate of SOM decomposition and microbial communities. Variable responses of different microbial communities to labile C and N inputs indicate that complex relationships between priming and microbial functions. In general, we demonstrate that energy inputs can quickly accelerate SOM decomposition whereas extra N input can slow this process, though both had similar microbial community responses.

Quickbird Satellite in-orbit Modulation Transfer Function (MTF) Measurement Using Edge, Pulse and Impulse Methods for Summer 2003

NASA Technical Reports Server (NTRS)

Helder, Dennis; Choi, Taeyoung; Rangaswamy, Manjunath

2005-01-01

The spatial characteristics of an imaging system cannot be expressed by a single number or simple statement. However, the Modulation Transfer Function (MTF) is one approach to measure the spatial quality of an imaging system. Basically, MTF is the normalized spatial frequency response of an imaging system. The frequency response of the system can be evaluated by applying an impulse input. The resulting impulse response is termed the Point Spread function (PSF). This function is a measure of the amount of blurring present in the imaging system and is itself a useful measure of spatial quality. An underlying assumption is that the imaging system is linear and shift-independent. The Fourier transform of the PSF is called the Optical Transfer Function (OTF) and the normalized magnitude of the OTF is the MTF. In addition to using an impulse input, a knife-edge in technique has also been used in this project. The sharp edge exercises an imaging system at all spatial frequencies. The profile of an edge response from an imaging system is called an Edge Spread Function (ESF). Differentiation of the ESF results in a one-dimensional version of the Point Spread Function (PSF). Finally, MTF can be calculated through use of Fourier transform of the PSF as stated previously. Every image includes noise in some degree which makes MTF of PSF estimation more difficult. To avoid the noise effects, many MTF estimation approaches use smooth numerical models. Historically, Gaussian models and Fermi functions were applied to reduce the random noise in the output profiles. The pulse-input method was used to measure the MTF of the Landsat Thematic Mapper (TM) using 8th order even functions over the San Mateo Bridge in San Francisco, California. Because the bridge width was smaller than the 30-meter ground sample distance (GSD) of the TM, the Nyquist frequency was located before the first zero-crossing point of the sinc function from the Fourier transformation of the bridge pulse. To avoid the zero-crossing points in the frequency domain from a pulse, the pulse width should be less than the width of two pixels (or 2 GSD's), but the short extent of the pulse results in a poor signal-to-noise ratio. Similarly, for a high-resolution satellite imaging system such as Quickbird, the input pulse width was critical because of the zero crossing points and noise present in the background area. It is important, therefore, that the width of the input pulse be appropriately sized. Finally, the MTF was calculated by taking ratio between Fourier transform of output and Fourier transform of input. Regardless of whether the edge, pulse and impulse target method is used, the orientation of the targets is critical in order to obtain uniformly spaced sub-pixel data points. When the orientation is incorrect, sample data points tend to be located in clusters that result in poor reconstruction of the edge or pulse profiles. Thus, a compromise orientation must be selected so that all spectral bands can be accommodated. This report continues by outlining the objectives in Section 2, procedures followed in Section 3, descriptions of the field campaigns in Section 4, results in Section 5, and a brief summary in Section 6.

Modal analysis using a Fourier analyzer, curve-fitting, and modal tuning

NASA Technical Reports Server (NTRS)

Craig, R. R., Jr.; Chung, Y. T.

1981-01-01

The proposed modal test program differs from single-input methods in that preliminary data may be acquired using multiple inputs, and modal tuning procedures may be employed to define closely spaced frquency modes more accurately or to make use of frequency response functions (FRF's) which are based on several input locations. In some respects the proposed modal test proram resembles earlier sine-sweep and sine-dwell testing in that broadband FRF's are acquired using several input locations, and tuning is employed to refine the modal parameter estimates. The major tasks performed in the proposed modal test program are outlined. Data acquisition and FFT processing, curve fitting, and modal tuning phases are described and examples are given to illustrate and evaluate them.

Expanded all-optical programmable logic array based on multi-input/output canonical logic units.

PubMed

Lei, Lei; Dong, Jianji; Zou, Bingrong; Wu, Zhao; Dong, Wenchan; Zhang, Xinliang

2014-04-21

We present an expanded all-optical programmable logic array (O-PLA) using multi-input and multi-output canonical logic units (CLUs) generation. Based on four-wave mixing (FWM) in highly nonlinear fiber (HNLF), two-input and three-input CLUs are simultaneously achieved in five different channels with an operation speed of 40 Gb/s. Clear temporal waveforms and wide open eye diagrams are successfully observed. The effectiveness of the scheme is validated by extinction ratio and optical signal-to-noise ratio measurements. The computing capacity, defined as the total amount of logic functions achieved by the O-PLA, is discussed in detail. For a three-input O-PLA, the computing capacity of the expanded CLUs-PLA is more than two times as large as that of the standard CLUs-PLA, and this multiple will increase to more than three and a half as the idlers are individually independent.

Presynaptic Partners of Dorsal Raphe Serotonergic and GABAergic Neurons

PubMed Central

Weissbourd, Brandon; Ren, Jing; DeLoach, Katherine E.; Guenthner, Casey J.; Miyamichi, Kazunari; Luo, Liqun

2016-01-01

SUMMARY The serotonin system powerfully modulates physiology and behavior in health and disease, yet the circuit mechanisms underlying serotonin neuron activity are poorly understood. The major source of forebrain serotonergic innervation is from the dorsal raphe nucleus (DR), which contains both serotonin and GABA neurons. Using viral tracing combined with electrophysiology, we found that GABA and serotonin neurons in the DR receive excitatory, inhibitory, and peptidergic inputs from the same specific brain regions. Embedded in this overall similarity are important differences. Serotonin neurons are more likely to receive synaptic inputs from anterior neocortex while GABA neurons receive disproportionally higher input from the central amygdala. Local input mapping revealed extensive serotonin-serotonin as well as GABA-serotonin connectivity with a distinct spatial organization. Covariance analysis suggests heterogeneity of both serotonin and GABA neurons with respect to the inputs they receive. These analyses provide a foundation for further functional dissection of the serotonin system. PMID:25102560

Flexible Kernel Memory

PubMed Central

Nowicki, Dimitri; Siegelmann, Hava

2010-01-01

This paper introduces a new model of associative memory, capable of both binary and continuous-valued inputs. Based on kernel theory, the memory model is on one hand a generalization of Radial Basis Function networks and, on the other, is in feature space, analogous to a Hopfield network. Attractors can be added, deleted, and updated on-line simply, without harming existing memories, and the number of attractors is independent of input dimension. Input vectors do not have to adhere to a fixed or bounded dimensionality; they can increase and decrease it without relearning previous memories. A memory consolidation process enables the network to generalize concepts and form clusters of input data, which outperforms many unsupervised clustering techniques; this process is demonstrated on handwritten digits from MNIST. Another process, reminiscent of memory reconsolidation is introduced, in which existing memories are refreshed and tuned with new inputs; this process is demonstrated on series of morphed faces. PMID:20552013

Differential capacity of kaolinite and birnessite to protect surface associated proteins against thermal degradation [Fate of protein at mineral surfaces: influence of protein characteristics mineralogy, pH, and energy input

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

Chacon, Stephany S.; Garcia-Jaramillo, Manuel; Liu, Suet Yi

We report it is widely accepted that soil organic carbon cycling depends on the presence and catalytic functionality of extracellular enzymes. Recent reports suggest that combusted and autoclaved soils may have the capacity to degrade organic test substrates to a larger extent than the living, enzyme-bearing soils. In search of the underlying mechanisms, we adsorbed Beta-Glucosidase (BG) and Bovine Serum Albumin (BSA) on the phyllosilicate kaolinite and the manganese oxide birnessite at pH 5 and pH 7. The protein-mineral samples were then subjected to gradual energy inputs of a magnitude equivalent to naturally occurring wildfire events. The abundance and molecularmore » masses of desorbed organic compounds were recorded after ionization with tunable synchrotron vacuum ultraviolet radiation (VUV). The mechanisms controlling the fate of proteins varied with mineralogy. Kaolinite adsorbed protein largely through hydrophobic interactions and, even at large energy inputs, produced negligible amounts of desorption fragments compared to birnessite. Acid birnessite adsorbed protein through coulombic forces at low energy levels, became a hydrolyzing catalyst at low energies and low pH, and eventually turned into a reactant involving disintegration of both mineral and protein at higher energy inputs. Fragmentation of proteins was energy dependent and did not occur below an energy threshold of 0.20 MW cm -2 . Neither signal abundance nor signal intensity were a function of protein size. Above the energy threshold value, BG that had been adsorbed to birnessite at pH 7 showed an increase in signal abundance with increasing energy applications. Signal intensities differed with adsorption pH for BSA but only at the highest energy level applied. Our results indicate that proteins adsorbed to kaolinite may remain intact after exposure to such energy inputs as can be expected to occur in natural ecosystems. Protein fragmentation and concomitant loss of functionality must be expected in surface soils replete with pedogenic manganese oxides. Lastly, we conclude that minerals can do both: protect enzymes at high energy intensities in the case of kaolinite and, in the case of birnessite, substitute for and even exceed the oxidative functionality that may have been lost when unprotected oxidative enzymes were denatured at high energy inputs.« less

Inhibition of presynaptic calcium transients in cortical inputs to the dorsolateral striatum by metabotropic GABAB and mGlu2/3 receptors

PubMed Central

Kupferschmidt, David A; Lovinger, David M

2015-01-01

Cortical inputs to the dorsolateral striatum (DLS) are dynamically regulated during skill learning and habit formation, and are dysregulated in disorders characterized by impaired action control. Therefore, a mechanistic investigation of the processes regulating corticostriatal transmission is key to understanding DLS-associated circuit function, behaviour and pathology. Presynaptic GABAB and group II metabotropic glutamate (mGlu2/3) receptors exert marked inhibitory control over corticostriatal glutamate release in the DLS, yet the signalling pathways through which they do so are unclear. We developed a novel approach using the genetically encoded calcium (Ca2+) indicator GCaMP6 to assess presynaptic Ca2+ in corticostriatal projections to the DLS. Using simultaneous photometric presynaptic Ca2+ and striatal field potential recordings, we report that relative to P/Q-type Ca2+ channels, N-type channels preferentially contributed to evoked presynaptic Ca2+ influx in motor cortex projections to, and excitatory transmission in, the DLS. Activation of GABAB or mGlu2/3 receptors inhibited both evoked presynaptic Ca2+ transients and striatal field potentials. mGlu2/3 receptor-mediated depression did not require functional N-type Ca2+ channels, but was attenuated by blockade of P/Q-type channels. These findings reveal presynaptic mechanisms of inhibitory modulation of corticostriatal function that probably contribute to the selection and shaping of behavioural repertoires. Key points Plastic changes at cortical inputs to the dorsolateral striatum (DLS) underlie skill learning and habit formation, so characterizing the mechanisms by which these inputs are regulated is important for understanding the neural basis of action control. We developed a novel approach using the genetically encoded calcium (Ca2+) indicator GCaMP6 and brain slice photometry to assess evoked presynaptic Ca2+ transients in cortical inputs to the DLS and study their regulation by GABAB and mGlu2/3 receptors. GABAB and mGlu2/3 receptor activation caused clear reductions in electrical stimulus-evoked presynaptic Ca2+ transients in corticostriatal inputs to the DLS. Functional P/Q-type voltage-gated Ca2+ channels were required for the normal inhibitory action of corticostriatal mGlu2/3 receptors. We provide direct evidence of presynaptic Ca2+ inhibition by G protein-coupled receptors at corticostriatal projections. PMID:25781000

Observation-Based Dissipation and Input Terms for Spectral Wave Models, with End-User Testing

DTIC Science & Technology

2014-09-30

scale influence of the Great barrier reef matrix on wave attenuation, Coral Reefs [published, refereed] Ghantous, M., and A.V. Babanin, 2014: One...Observation-Based Dissipation and Input Terms for Spectral Wave Models...functions, based on advanced understanding of physics of air-sea interactions, wave breaking and swell attenuation, in wave - forecast models. OBJECTIVES The

The overlap between false belief and spatial reorientation in the temporo-parietal junction: The role of input modality and task.

PubMed

Özdem, Ceylan; Brass, Marcel; Van der Cruyssen, Laurens; Van Overwalle, Frank

2017-04-01

Neuroimaging research has demonstrated that the temporo-parietal junction (TPJ) is activated when unexpected stimuli appear in spatial reorientation tasks as well as during thinking about the beliefs of other people triggered by verbal scenarios. While the role of potential common component processes subserved by the TPJ has been extensively studied to explain this common activation, the potential confounding role of input modality (spatial vs. verbal) has been largely ignored. To investigate the role of input modality apart from task processes, we developed a novel spatial false belief task based on moving shapes. We explored the overlap in TPJ activation across this novel task and traditional tasks of spatial reorientation (Posner) and verbal belief (False Belief vs. Photo stories). The results show substantial overlap across the same spatial input modality (both reorientation and false belief) as well as across the common task process (verbal and spatial belief), but no triple overlap. This suggests the potential for an overarching function of the TPJ, with some degree of specialization in different subregions due to modality, function and connectivity. The results are discussed with respect to recent theoretical models of the TPJ.

Multilayer modal actuator-based piezoelectric transformers.

PubMed

Huang, Yao-Tien; Wu, Wen-Jong; Wang, Yen-Chieh; Lee, Chih-Kung

2007-02-01

An innovative, multilayer piezoelectric transformer equipped with a full modal filtering input electrode is reported herein. This modal-shaped electrode, based on the orthogonal property of structural vibration modes, is characterized by full modal filtering to ensure that only the desired vibration mode is excited during operation. The newly developed piezoelectric transformer is comprised of three layers: a multilayered input layer, an insulation layer, and a single output layer. The electrode shape of the input layer is derived from its structural vibration modal shape, which takes advantage of the orthogonal property of the vibration modes to achieve a full modal filtering effect. The insulation layer possesses two functions: first, to couple the mechanical vibration energy between the input and output, and second, to provide electrical insulation between the two layers. To meet the two functions, a low temperature, co-fired ceramic (LTCC) was used to provide the high mechanical rigidity and high electrical insulation. It can be shown that this newly developed piezoelectric transformer has the advantage of possessing a more efficient energy transfer and a wider optimal working frequency range when compared to traditional piezoelectric transformers. A multilayer piezoelectric, transformer-based inverter applicable for use in LCD monitors or portable displays is presented as well.

On the fusion of tuning parameters of fuzzy rules and neural network

NASA Astrophysics Data System (ADS)

Mamuda, Mamman; Sathasivam, Saratha

2017-08-01

Learning fuzzy rule-based system with neural network can lead to a precise valuable empathy of several problems. Fuzzy logic offers a simple way to reach at a definite conclusion based upon its vague, ambiguous, imprecise, noisy or missing input information. Conventional learning algorithm for tuning parameters of fuzzy rules using training input-output data usually end in a weak firing state, this certainly powers the fuzzy rule and makes it insecure for a multiple-input fuzzy system. In this paper, we introduce a new learning algorithm for tuning the parameters of the fuzzy rules alongside with radial basis function neural network (RBFNN) in training input-output data based on the gradient descent method. By the new learning algorithm, the problem of weak firing using the conventional method was addressed. We illustrated the efficiency of our new learning algorithm by means of numerical examples. MATLAB R2014(a) software was used in simulating our result The result shows that the new learning method has the best advantage of training the fuzzy rules without tempering with the fuzzy rule table which allowed a membership function of the rule to be used more than one time in the fuzzy rule base.

Distributed Optimal Consensus Control for Multiagent Systems With Input Delay.

PubMed

Zhang, Huaipin; Yue, Dong; Zhao, Wei; Hu, Songlin; Dou, Chunxia; Huaipin Zhang; Dong Yue; Wei Zhao; Songlin Hu; Chunxia Dou; Hu, Songlin; Zhang, Huaipin; Dou, Chunxia; Yue, Dong; Zhao, Wei

2018-06-01

This paper addresses the problem of distributed optimal consensus control for a continuous-time heterogeneous linear multiagent system subject to time varying input delays. First, by discretization and model transformation, the continuous-time input-delayed system is converted into a discrete-time delay-free system. Two delicate performance index functions are defined for these two systems. It is shown that the performance index functions are equivalent and the optimal consensus control problem of the input-delayed system can be cast into that of the delay-free system. Second, by virtue of the Hamilton-Jacobi-Bellman (HJB) equations, an optimal control policy for each agent is designed based on the delay-free system and a novel value iteration algorithm is proposed to learn the solutions to the HJB equations online. The proposed adaptive dynamic programming algorithm is implemented on the basis of a critic-action neural network (NN) structure. Third, it is proved that local consensus errors of the two systems and weight estimation errors of the critic-action NNs are uniformly ultimately bounded while the approximated control policies converge to their target values. Finally, two simulation examples are presented to illustrate the effectiveness of the developed method.

Functional Division of Hippocampal Area CA1 Via Modulatory Gating of Entorhinal Cortical Inputs

PubMed Central

Ito, Hiroshi T.; Schuman, Erin M.

2013-01-01

The hippocampus receives two streams of information, spatial and nonspatial, via major afferent inputs from the medial (MEC) and lateral entorhinal cortexes (LEC). The MEC and LEC projections in the temporoammonic pathway are topographically organized along the transverse-axis of area CA1. The potential for functional segregation of area CA1, however, remains relatively unexplored. Here, we demonstrated differential novelty-induced c-Fos expression along the transverse-axis of area CA1 corresponding to topographic projections of MEC and LEC inputs. We found that, while novel place exposure induced a uniform c-Fos expression along the transverse-axis of area CA1, novel object exposure primarily activated the distal half of CA1 neurons. In hippocampal slices, we observed distinct presynaptic properties between LEC and MEC terminals, and application of either DA or NE produced a largely selective influence on one set of inputs (LEC). Finally, we demonstrated that differential c-Fos expression along the transverse axis of area CA1 was largely abolished by an antagonist of neuromodulatory receptors, clozapine. Our results suggest that neuromodulators can control topographic TA projections allowing the hippocampus to differentially encode new information along the transverse axis of area CA1. PMID:21240920

Design of hybrid radial basis function neural networks (HRBFNNs) realized with the aid of hybridization of fuzzy clustering method (FCM) and polynomial neural networks (PNNs).

PubMed

Huang, Wei; Oh, Sung-Kwun; Pedrycz, Witold

2014-12-01

In this study, we propose Hybrid Radial Basis Function Neural Networks (HRBFNNs) realized with the aid of fuzzy clustering method (Fuzzy C-Means, FCM) and polynomial neural networks. Fuzzy clustering used to form information granulation is employed to overcome a possible curse of dimensionality, while the polynomial neural network is utilized to build local models. Furthermore, genetic algorithm (GA) is exploited here to optimize the essential design parameters of the model (including fuzzification coefficient, the number of input polynomial fuzzy neurons (PFNs), and a collection of the specific subset of input PFNs) of the network. To reduce dimensionality of the input space, principal component analysis (PCA) is considered as a sound preprocessing vehicle. The performance of the HRBFNNs is quantified through a series of experiments, in which we use several modeling benchmarks of different levels of complexity (different number of input variables and the number of available data). A comparative analysis reveals that the proposed HRBFNNs exhibit higher accuracy in comparison to the accuracy produced by some models reported previously in the literature. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Comprehensive Study of Gridding Methods for GPS Horizontal Velocity Fields

NASA Astrophysics Data System (ADS)

Wu, Yanqiang; Jiang, Zaisen; Liu, Xiaoxia; Wei, Wenxin; Zhu, Shuang; Zhang, Long; Zou, Zhenyu; Xiong, Xiaohui; Wang, Qixin; Du, Jiliang

2017-03-01

Four gridding methods for GPS velocities are compared in terms of their precision, applicability and robustness by analyzing simulated data with uncertainties from 0.0 to ±3.0 mm/a. When the input data are 1° × 1° grid sampled and the uncertainty of the additional error is greater than ±1.0 mm/a, the gridding results show that the least-squares collocation method is highly robust while the robustness of the Kriging method is low. In contrast, the spherical harmonics and the multi-surface function are moderately robust, and the regional singular values for the multi-surface function method and the edge effects for the spherical harmonics method become more significant with increasing uncertainty of the input data. When the input data (with additional errors of ±2.0 mm/a) are decimated by 50% from the 1° × 1° grid data and then erased in three 6° × 12° regions, the gridding results in these three regions indicate that the least-squares collocation and the spherical harmonics methods have good performances, while the multi-surface function and the Kriging methods may lead to singular values. The gridding techniques are also applied to GPS horizontal velocities with an average error of ±0.8 mm/a over the Chinese mainland and the surrounding areas, and the results show that the least-squares collocation method has the best performance, followed by the Kriging and multi-surface function methods. Furthermore, the edge effects of the spherical harmonics method are significantly affected by the sparseness and geometric distribution of the input data. In general, the least-squares collocation method is superior in terms of its robustness, edge effect, error distribution and stability, while the other methods have several positive features.

ANTONIA perfusion and stroke. A software tool for the multi-purpose analysis of MR perfusion-weighted datasets and quantitative ischemic stroke assessment.

PubMed

Forkert, N D; Cheng, B; Kemmling, A; Thomalla, G; Fiehler, J

2014-01-01

The objective of this work is to present the software tool ANTONIA, which has been developed to facilitate a quantitative analysis of perfusion-weighted MRI (PWI) datasets in general as well as the subsequent multi-parametric analysis of additional datasets for the specific purpose of acute ischemic stroke patient dataset evaluation. Three different methods for the analysis of DSC or DCE PWI datasets are currently implemented in ANTONIA, which can be case-specifically selected based on the study protocol. These methods comprise a curve fitting method as well as a deconvolution-based and deconvolution-free method integrating a previously defined arterial input function. The perfusion analysis is extended for the purpose of acute ischemic stroke analysis by additional methods that enable an automatic atlas-based selection of the arterial input function, an analysis of the perfusion-diffusion and DWI-FLAIR mismatch as well as segmentation-based volumetric analyses. For reliability evaluation, the described software tool was used by two observers for quantitative analysis of 15 datasets from acute ischemic stroke patients to extract the acute lesion core volume, FLAIR ratio, perfusion-diffusion mismatch volume with manually as well as automatically selected arterial input functions, and follow-up lesion volume. The results of this evaluation revealed that the described software tool leads to highly reproducible results for all parameters if the automatic arterial input function selection method is used. Due to the broad selection of processing methods that are available in the software tool, ANTONIA is especially helpful to support image-based perfusion and acute ischemic stroke research projects.

A hexagonal orthogonal-oriented pyramid as a model of image representation in visual cortex

NASA Technical Reports Server (NTRS)

Watson, Andrew B.; Ahumada, Albert J., Jr.

1989-01-01

Retinal ganglion cells represent the visual image with a spatial code, in which each cell conveys information about a small region in the image. In contrast, cells of the primary visual cortex use a hybrid space-frequency code in which each cell conveys information about a region that is local in space, spatial frequency, and orientation. A mathematical model for this transformation is described. The hexagonal orthogonal-oriented quadrature pyramid (HOP) transform, which operates on a hexagonal input lattice, uses basis functions that are orthogonal, self-similar, and localized in space, spatial frequency, orientation, and phase. The basis functions, which are generated from seven basic types through a recursive process, form an image code of the pyramid type. The seven basis functions, six bandpass and one low-pass, occupy a point and a hexagon of six nearest neighbors on a hexagonal lattice. The six bandpass basis functions consist of three with even symmetry, and three with odd symmetry. At the lowest level, the inputs are image samples. At each higher level, the input lattice is provided by the low-pass coefficients computed at the previous level. At each level, the output is subsampled in such a way as to yield a new hexagonal lattice with a spacing square root of 7 larger than the previous level, so that the number of coefficients is reduced by a factor of seven at each level. In the biological model, the input lattice is the retinal ganglion cell array. The resulting scheme provides a compact, efficient code of the image and generates receptive fields that resemble those of the primary visual cortex.

Generalized neurofuzzy network modeling algorithms using Bézier-Bernstein polynomial functions and additive decomposition.

PubMed

Hong, X; Harris, C J

2000-01-01

This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bézier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bézier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bézier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bézier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

Somatostatin-Expressing Inhibitory Interneurons in Cortical Circuits

PubMed Central

Yavorska, Iryna; Wehr, Michael

2016-01-01

Cortical inhibitory neurons exhibit remarkable diversity in their morphology, connectivity, and synaptic properties. Here, we review the function of somatostatin-expressing (SOM) inhibitory interneurons, focusing largely on sensory cortex. SOM neurons also comprise a number of subpopulations that can be distinguished by their morphology, input and output connectivity, laminar location, firing properties, and expression of molecular markers. Several of these classes of SOM neurons show unique dynamics and characteristics, such as facilitating synapses, specific axonal projections, intralaminar input, and top-down modulation, which suggest possible computational roles. SOM cells can be differentially modulated by behavioral state depending on their class, sensory system, and behavioral paradigm. The functional effects of such modulation have been studied with optogenetic manipulation of SOM cells, which produces effects on learning and memory, task performance, and the integration of cortical activity. Different classes of SOM cells participate in distinct disinhibitory circuits with different inhibitory partners and in different cortical layers. Through these disinhibitory circuits, SOM cells help encode the behavioral relevance of sensory stimuli by regulating the activity of cortical neurons based on subcortical and intracortical modulatory input. Associative learning leads to long-term changes in the strength of connectivity of SOM cells with other neurons, often influencing the strength of inhibitory input they receive. Thus despite their heterogeneity and variability across cortical areas, current evidence shows that SOM neurons perform unique neural computations, forming not only distinct molecular but also functional subclasses of cortical inhibitory interneurons. PMID:27746722

FlaME: Flash Molecular Editor - a 2D structure input tool for the web

PubMed Central

2011-01-01

Background So far, there have been no Flash-based web tools available for chemical structure input. The authors herein present a feasibility study, aiming at the development of a compact and easy-to-use 2D structure editor, using Adobe's Flash technology and its programming language, ActionScript. As a reference model application from the Java world, we selected the Java Molecular Editor (JME). In this feasibility study, we made an attempt to realize a subset of JME's functionality in the Flash Molecular Editor (FlaME) utility. These basic capabilities are: structure input, editing and depiction of single molecules, data import and export in molfile format. Implementation The result of molecular diagram sketching in FlaME is accessible in V2000 molfile format. By integrating the molecular editor into a web page, its communication with the HTML elements on this page is established using the two JavaScript functions, getMol() and setMol(). In addition, structures can be copied to the system clipboard. Conclusion A first attempt was made to create a compact single-file application for 2D molecular structure input/editing on the web, based on Flash technology. With the application examples presented in this article, it could be demonstrated that the Flash methods are principally well-suited to provide the requisite communication between the Flash object (application) and the HTML elements on a web page, using JavaScript functions. PMID:21284863

Thalamic projections to visual and visuomotor areas (V6 and V6A) in the Rostral Bank of the parieto-occipital sulcus of the Macaque.

PubMed

Gamberini, Michela; Bakola, Sophia; Passarelli, Lauretta; Burman, Kathleen J; Rosa, Marcello G P; Fattori, Patrizia; Galletti, Claudio

2016-04-01

The medial posterior parietal cortex of the primate brain includes different functional areas, which have been defined based on the functional properties, cyto- and myeloarchitectural criteria, and cortico-cortical connections. Here, we describe the thalamic projections to two of these areas (V6 and V6A), based on 14 retrograde neuronal tracer injections in 11 hemispheres of 9 Macaca fascicularis. The injections were placed either by direct visualisation or using electrophysiological guidance, and the location of injection sites was determined post mortem based on cyto- and myeloarchitectural criteria. We found that the majority of the thalamic afferents to the visual area V6 originate in subdivisions of the lateral and inferior pulvinar nuclei, with weaker inputs originating from the central densocellular, paracentral, lateral posterior, lateral geniculate, ventral anterior and mediodorsal nuclei. In contrast, injections in both the dorsal and ventral parts of the visuomotor area V6A revealed strong inputs from the lateral posterior and medial pulvinar nuclei, as well as smaller inputs from the ventrolateral complex and from the central densocellular, paracentral, and mediodorsal nuclei. These projection patterns are in line with the functional properties of injected areas: "dorsal stream" extrastriate area V6 receives information from visuotopically organised subdivisions of the thalamus; whereas visuomotor area V6A, which is involved in the sensory guidance of arm movement, receives its primary afferents from thalamic nuclei that provide high-order somatic and visual input.

Membrane voltage changes in passive dendritic trees: a tapering equivalent cylinder model.

PubMed

Poznański, R R

1988-01-01

An exponentially tapering equivalent cylinder model is employed in order to approximate the loss of the dendritic trunk parameter observed from anatomical data on apical and basilar dendrites of CA1 and CA3 hippocampal pyramidal neurons. This model allows dendritic trees with a relative paucity of branching to be treated. In particular, terminal branches are not required to end at the same electrotonic distance. The Laplace transform method is used to obtain analytic expressions for the Green's function corresponding to an instantaneous pulse of current injected at a single point along a tapering equivalent cylinder with sealed ends. The time course of the voltage in response to an arbitrary input is computed using the Green's function in a convolution integral. Examples of current input considered are (1) an infinitesimally brief (Dirac delta function) pulse and (2) a step pulse. It is demonstrated that inputs located on a tapering equivalent cylinder are more effective at the soma than identically placed inputs on a nontapering equivalent cylinder. Asymptotic solutions are derived to enable the voltage response behaviour over both relatively short and long time periods to be analysed. Semilogarithmic plots of these solutions provide a basis for estimating the membrane time constant tau m from experimental transients. Transient voltage decrement from a clamped soma reveals that tapering tends to reduce the error associated with inadequate voltage clamping of the dendritic membrane. A formula is derived which shows that tapering tends to increase the estimate of the electrotonic length parameter L.

Comparison and Enumeration of Chemical Graphs

PubMed Central

Akutsu, Tatsuya; Nagamochi, Hiroshi

2013-01-01

Chemical compounds are usually represented as graph structured data in computers. In this review article, we overview several graph classes relevant to chemical compounds and the computational complexities of several fundamental problems for these graph classes. In particular, we consider the following problems: determining whether two chemical graphs are identical, determining whether one input chemical graph is a part of the other input chemical graph, finding a maximum common part of two input graphs, finding a reaction atom mapping, enumerating possible chemical graphs, and enumerating stereoisomers. We also discuss the relationship between the fifth problem and kernel functions for chemical compounds. PMID:24688697

A uniform input data convention for the CALL 3-D crash victim simulation

NASA Astrophysics Data System (ADS)

Shaibani, S. J.

1982-07-01

Logical schemes for the labelling of planes (cards D) and functions (cards E) in the input decks used for the Calspan 3-D Crash Victim Simulation (CVS) program are proposed. One benefit of introducing such a standardized format for these inputs would be to facilitate greatly the interchange of data for different vehicles. A further advantage would be that the table of allowed contacts (cards F) could remain largely unaltered. It is hoped that the uniformity of the convention described by these schemes would help to promote the exchange of readily usable data between CVS users.

Command Filtering-Based Fuzzy Control for Nonlinear Systems With Saturation Input.

PubMed

Yu, Jinpeng; Shi, Peng; Dong, Wenjie; Lin, Chong

2017-09-01

In this paper, command filtering-based fuzzy control is designed for uncertain multi-input multioutput (MIMO) nonlinear systems with saturation nonlinearity input. First, the command filtering method is employed to deal with the explosion of complexity caused by the derivative of virtual controllers. Then, fuzzy logic systems are utilized to approximate the nonlinear functions of MIMO systems. Furthermore, error compensation mechanism is introduced to overcome the drawback of the dynamics surface approach. The developed method will guarantee all signals of the systems are bounded. The effectiveness and advantages of the theoretic result are obtained by a simulation example.

Developmental process emerges from extended brain-body-behavior networks

PubMed Central

Byrge, Lisa; Sporns, Olaf; Smith, Linda B.

2014-01-01

Studies of brain connectivity have focused on two modes of networks: structural networks describing neuroanatomy and the intrinsic and evoked dependencies of functional networks at rest and during tasks. Each mode constrains and shapes the other across multiple time scales, and each also shows age-related changes. Here we argue that understanding how brains change across development requires understanding the interplay between behavior and brain networks: changing bodies and activities modify the statistics of inputs to the brain; these changing inputs mold brain networks; these networks, in turn, promote further change in behavior and input. PMID:24862251

Motion planning for an adaptive wing structure with macro-fiber composite actuators

NASA Astrophysics Data System (ADS)

Schröck, J.; Meurer, T.; Kugi, A.

2009-05-01

A systematic approach for flatness-based motion planning and feedforward control is presented for the transient shaping of a piezo-actuated rectangular cantilevered plate modeling an adaptive wing. In the first step the consideration of an idealized infinite-dimensional input allows to determine the state and input parametrization in terms of a flat or basic output, which is used for a systematic motion planning approach. Subsequently, the obtained idealized input function is projected onto a finite number of suitably placed Macro-fiber Composite (MFC) patch actuators. The tracking performance of the proposed approach is evaluated in a simulation scenario.

High throughput reconfigurable data analysis system

NASA Technical Reports Server (NTRS)

Bearman, Greg (Inventor); Pelletier, Michael J. (Inventor); Seshadri, Suresh (Inventor); Pain, Bedabrata (Inventor)

2008-01-01

The present invention relates to a system and method for performing rapid and programmable analysis of data. The present invention relates to a reconfigurable detector comprising at least one array of a plurality of pixels, where each of the plurality of pixels can be selected to receive and read-out an input. The pixel array is divided into at least one pixel group for conducting a common predefined analysis. Each of the pixels has a programmable circuitry programmed with a dynamically configurable user-defined function to modify the input. The present detector also comprises a summing circuit designed to sum the modified input.

Supervised spike-timing-dependent plasticity: a spatiotemporal neuronal learning rule for function approximation and decisions.

PubMed

Franosch, Jan-Moritz P; Urban, Sebastian; van Hemmen, J Leo

2013-12-01

How can an animal learn from experience? How can it train sensors, such as the auditory or tactile system, based on other sensory input such as the visual system? Supervised spike-timing-dependent plasticity (supervised STDP) is a possible answer. Supervised STDP trains one modality using input from another one as "supervisor." Quite complex time-dependent relationships between the senses can be learned. Here we prove that under very general conditions, supervised STDP converges to a stable configuration of synaptic weights leading to a reconstruction of primary sensory input.

Mode-selective mapping and control of vectorial nonlinear-optical processes in multimode photonic-crystal fibers.

PubMed

Hu, Ming-Lie; Wang, Ching-Yue; Song, You-Jian; Li, Yan-Feng; Chai, Lu; Serebryannikov, Evgenii; Zheltikov, Aleksei

2006-02-06

We demonstrate an experimental technique that allows a mapping of vectorial nonlinear-optical processes in multimode photonic-crystal fibers (PCFs). Spatial and polarization modes of PCFs are selectively excited in this technique by varying the tilt angle of the input beam and rotating the polarization of the input field. Intensity spectra of the PCF output plotted as a function of the input field power and polarization then yield mode-resolved maps of nonlinear-optical interactions in multimode PCFs, facilitating the analysis and control of nonlinear-optical transformations of ultrashort laser pulses in such fibers.

Estimation of Psychophysical Thresholds Based on Neural Network Analysis of DPOAE Input/Output Functions

NASA Astrophysics Data System (ADS)

Naghibolhosseini, Maryam; Long, Glenis

2011-11-01

The distortion product otoacoustic emission (DPOAE) input/output (I/O) function may provide a potential tool for evaluating cochlear compression. Hearing loss causes an increase in the level of the sound that is just audible for the person, which affects the cochlea compression and thus the dynamic range of hearing. Although the slope of the I/O function is highly variable when the total DPOAE is used, separating the nonlinear-generator component from the reflection component reduces this variability. We separated the two components using least squares fit (LSF) analysis of logarithmic sweeping tones, and confirmed that the separated generator component provides more consistent I/O functions than the total DPOAE. In this paper we estimated the slope of the I/O functions of the generator components at different sound levels using LSF analysis. An artificial neural network (ANN) was used to estimate psychophysical thresholds using the estimated slopes of the I/O functions. DPOAE I/O functions determined in this way may help to estimate hearing thresholds and cochlear health.

Piezoelectric Actuator Modeling Using MSC/NASTRAN and MATLAB

NASA Technical Reports Server (NTRS)

Reaves, Mercedes C.; Horta, Lucas G.

2003-01-01

This paper presents a procedure for modeling structures containing piezoelectric actuators using MSCMASTRAN and MATLAB. The paper describes the utility and functionality of one set of validated modeling tools. The tools described herein use MSCMASTRAN to model the structure with piezoelectric actuators and a thermally induced strain to model straining of the actuators due to an applied voltage field. MATLAB scripts are used to assemble the dynamic equations and to generate frequency response functions. The application of these tools is discussed using a cantilever aluminum beam with a surface mounted piezoelectric actuator as a sample problem. Software in the form of MSCINASTRAN DMAP input commands, MATLAB scripts, and a step-by-step procedure to solve the example problem are provided. Analysis results are generated in terms of frequency response functions from deflection and strain data as a function of input voltage to the actuator.

The influences of metabotropic receptor activation on cellular signaling and synaptic function in amacrine cells.

PubMed

Gleason, Evanna

2012-01-01

Amacrine cells receive glutamatergic input from bipolar cells and GABAergic, glycinergic, cholinergic, and dopaminergic input from other amacrine cells. Glutamate, GABA, glycine, and acetylcholine (ACh) interact with ionotropic receptors and it is these interactions that form much of the functional circuitry in the inner retina. However, glutamate, GABA, ACh, and dopamine also activate metabotropic receptors linked to second messenger pathways that have the potential to modify the function of individual cells as well as retinal circuitry. Here, the physiological effects of activating dopamine receptors, metabotropic glutamate receptors, GABAB receptors, and muscarinic ACh receptors on amacrine cells will be discussed. The retina also expresses metabotropic receptors and the biochemical machinery associated with the synthesis and degradation of endocannabinoids and sphingosine-1-phosphate (S1P). The effects of activating cannabinoid receptors and S1P receptors on amacrine cell function will also be addressed. Copyright © Cambridge University Press, 2012

Sonic Hedgehog Expression in Corticofugal Projection Neurons Directs Cortical Microcircuit Formation

PubMed Central

Harwell, Corey C.; Parker, Philip R.L.; Gee, Steven M.; Okada, Ami; McConnell, Susan K.; Kreitzer, Anatol C.; Kriegstein, Arnold R.

2012-01-01

SUMMARY The precise connectivity of inputs and outputs is critical for cerebral cortex function; however, the cellular mechanisms that establish these connections are poorly understood. Here, we show that the secreted molecule Sonic Hedgehog (Shh) is involved in synapse formation of a specific cortical circuit. Shh is expressed in layer V corticofugal projection neurons and the Shh receptor, Brother of CDO (Boc), is expressed in local and callosal projection neurons of layer II/III that synapse onto the subcortical projection neurons. Layer V neurons of mice lacking functional Shh exhibit decreased synapses. Conversely, the loss of functional Boc leads to a reduction in the strength of synaptic connections onto layer Vb, but not layer II/III, pyramidal neurons. These results demonstrate that Shh is expressed in postsynaptic target cells while Boc is expressed in a complementary population of presynaptic input neurons, and they function to guide the formation of cortical microcircuitry. PMID:22445340

Human Systems Integration: Requirements and Functional Decomposition

NASA Technical Reports Server (NTRS)

Berson, Barry; Gershzohn, Gary; Boltz, Laura; Wolf, Russ; Schultz, Mike

2005-01-01

This deliverable was intended as an input to the Access 5 Policy and Simulation Integrated Product Teams. This document contains high-level pilot functionality for operations in the National Airspace System above FL430. Based on the derived pilot functions the associated pilot information and control requirements are given.

The Ph.D. Production Function: The Case at Berkeley.

ERIC Educational Resources Information Center

Breneman, David W.

This report analyzes departmental variations in time to degree and attrition in Ph.D. programs at Berkeley. An alternative hypothesis, the Ph.D. production function, is examined by cross-section econometric analysis of 28 departments. The inputs included in the production function were student variables--quality and percent males; faculty…

The production function

NASA Astrophysics Data System (ADS)

Fioretti, Guido

2007-02-01

The productions function maps the inputs of a firm or a productive system onto its outputs. This article expounds generalizations of the production function that include state variables, organizational structures and increasing returns to scale. These extensions are needed in order to explain the regularities of the empirical distributions of certain economic variables.

Versatile current-mode universal biquadratic filter using DO-CCIIs

NASA Astrophysics Data System (ADS)

Chen, Hua-Pin

2013-07-01

In this article, a new three-input and three-output versatile current-mode universal biquadratic filter is proposed. The circuit employs three dual-output current conveyors (DO-CCIIs) as active elements together with three grounded resistors and two grounded capacitors. The proposed configuration exhibits low-input impedance and high-output impedance which is important for easy cascading in the current-mode operations. It can be used as either a single-input and three-output or three-input and two-output circuit. In the operation of single-input and three-output circuit, the lowpass, bandpass and bandreject can be realised simultaneously, while the highpass filtering response can be easily obtained by connecting appropriated output current directly without using addition stages. In the operation of three-input and two-output circuit, all five generic filtering functions can be easily realised by selecting different three input current signals. The filter permits orthogonal controllability of the quality factor and resonance angular frequency, and no component matching conditions or inverting-type input current signals are imposed. All the passive and active sensitivities are low. HSPICE simulation results based on using TSMC 0.18 µm 1P6M CMOS process technology and supply voltages ±0.9 V to verify the theoretical analysis.

Entrainment and phase-shifting by centrifugation abolished in mice lacking functional vestibular input

NASA Astrophysics Data System (ADS)

Fuller, Charles; Ringgold, Kristyn

The circadian pacemaker can be phase shifted and entrained by appropriately timed locomotor activity, however the mechanism(s) involved remain poorly understood. Recent work in our lab has suggested the involvement of the vestibular otolith organs in activity-induced changes within the circadian timing system (CTS). For example, we have shown that changes in circa-dian period and phase in response to locomotion (wheel running) require functional macular gravity receptors. We believe the neurovestibular system is responsible for the transduction of gravitoinertial input associated with the types of locomotor activity that are known to af-fect the pacemaker. This study investigated the hypothesis that daily, timed gravitoinertial stimuli, as applied by centrifugation. would induce entrainment of circadian rhythms in only those animals with functional afferent vestibular input. To test this hypothesis, , chemically labyrinthectomized (Labx) mice, mice lacking macular vestibular input (head tilt or hets) and wildtype (WT) littermates were implanted i.p. with biotelemetry and individually housed in a 4-meter diameter centrifuge in constant darkness (DD). After 2 weeks in DD, the mice were exposed daily to 2G via centrifugation from 1000-1200 for 9 weeks. Only WT mice showed entrainment to the daily 2G pulse. The 2G pulse was then re-set to occur at 1200-1400 for 4 weeks. Only WT mice demonstrated a phase shift in response to the re-setting of the 2G pulse and subsequent re-entrainment to the new centrifugation schedule. These results provide further evidence that gravitoinertial stimuli require a functional vestibular system to both en-train and phase shift the CTS. Entrainment among only WT mice supports the role of macular gravity receptive cells in modulation of the CTS while also providing a functional mechanism by which gravitoinertial stimuli, including locomotor activity, may affect the pacemaker.

Prediction, scenarios and insight: The uses of an end-to-end model

NASA Astrophysics Data System (ADS)

Steele, John H.

2012-09-01

A major function of ecosystem models is to provide extrapolations from observed data in terms of predictions or scenarios or insight. These models can be at various levels of taxonomic resolution such as total community production, abundance of functional groups, or species composition, depending on the data input as drivers. A 40-year dynamic simulation of end-to-end processes in the Georges Bank food web is used to illustrate the input/output relations and the insights gained at the three levels of food web aggregation. The focus is on the intermediate level and the longer term changes in three functional fish guilds - planktivores, benthivores and piscivores - in terms of three ecosystem-based metrics - nutrient input, relative productivity of plankton and benthos, and food intake by juvenile fish. These simulations can describe the long term constraints imposed on guild structure and productivity by energy fluxes over the 40 years but cannot explain concurrent switches in abundance of individual species within guilds. Comparing time series data for individual species with model output provides insights; but including the data in the model would confer only limited extra information. The advantages and limitations of the three levels of resolution of models in relation to ecosystem-based management are: The correlations between primary production and total yield of fish imply a “bottom-up” constraint on end-to-end energy flow through the food web that can provide predictions of such yields. Functionally defined metrics such as nutrient input, relative productivity of plankton and benthos and food intake by juvenile fish, represent bottom-up, mid-level and top-down forcing of the food web. Model scenarios using these metrics can demonstrate constraints on the productivity of these functionally defined guilds within the limits set by (1). Comparisons of guild simulations with time series of fish species provide insight into the switches in species dominance that accompany changes in guild productivity and can illuminate the top-down aspects of regime shifts.

Effect of task demands on dual coding of pictorial stimuli.

PubMed

Babbitt, B C

1982-01-01

Recent studies have suggested that verbal labeling of a picture does not occur automatically. Although several experiments using paired-associate tasks produced little evidence indicating the use of a verbal code with picture stimuli, the tasks were probably not sensitive to whether the codes were activated initially. It is possible that verbal labels were activated at input, but not used later in performing the tasks. The present experiment used a color-naming interference task in order to assess, with a more sensitive measure, the amount of verbal coding occurring in response to word or picture input. Subjects named the color of ink in which words were printed following either word or picture input. If verbal labeling of the input occurs, then latency of color naming should increase when the input item and color-naming word are related. The results provided substantial evidence of such verbal activation when the input items were words. However, the presence of verbal activation with picture input was a function of task demands. Activation occurred when a recall memory test was used, but not when a recognition memory test was used. The results support the conclusion that name information (labels) need not be activated during presentation of visual stimuli.

Advanced information processing system: Input/output system services

NASA Technical Reports Server (NTRS)

Masotto, Tom; Alger, Linda

1989-01-01

The functional requirements and detailed specifications for the Input/Output (I/O) Systems Services of the Advanced Information Processing System (AIPS) are discussed. The introductory section is provided to outline the overall architecture and functional requirements of the AIPS system. Section 1.1 gives a brief overview of the AIPS architecture as well as a detailed description of the AIPS fault tolerant network architecture, while section 1.2 provides an introduction to the AIPS systems software. Sections 2 and 3 describe the functional requirements and design and detailed specifications of the I/O User Interface and Communications Management modules of the I/O System Services, respectively. Section 4 illustrates the use of the I/O System Services, while Section 5 concludes with a summary of results and suggestions for future work in this area.

Shear mode ER transfer function for robotic applications

NASA Astrophysics Data System (ADS)

Tan, K. P.; Stanway, R.; Bullough, W. A.

2005-06-01

Electro-rheological (ER) fluids are becoming popular in modern industrial applications. The advantage of employing ER devices is due to the ease of energizing the ER fluids at fast speeds of response. One innovation in ER applications could be in the positioning control of the robotic arm using an ER clutch. In order to actuate the manipulator, the ER output torque response is required. However, the behaviour of this ER torque response at different input conditions is not clearly understood. Therefore, in this paper, a sample study of the ER output torque is conducted. The ER output torque responses at different input parameters are studied carefully for the establishment of an appropriate ER transfer function in shear mode. This transfer function will serve as an important feature in future ER-actuated robot arm's control process.

Smooth function approximation using neural networks.

PubMed

Ferrari, Silvia; Stengel, Robert F

2005-01-01

An algebraic approach for representing multidimensional nonlinear functions by feedforward neural networks is presented. In this paper, the approach is implemented for the approximation of smooth batch data containing the function's input, output, and possibly, gradient information. The training set is associated to the network adjustable parameters by nonlinear weight equations. The cascade structure of these equations reveals that they can be treated as sets of linear systems. Hence, the training process and the network approximation properties can be investigated via linear algebra. Four algorithms are developed to achieve exact or approximate matching of input-output and/or gradient-based training sets. Their application to the design of forward and feedback neurocontrollers shows that algebraic training is characterized by faster execution speeds and better generalization properties than contemporary optimization techniques.

Realization of Minimum and Maximum Gate Function in Ta2O5-based Memristive Devices

NASA Astrophysics Data System (ADS)

Breuer, Thomas; Nielen, Lutz; Roesgen, Bernd; Waser, Rainer; Rana, Vikas; Linn, Eike

2016-04-01

Redox-based resistive switching devices (ReRAM) are considered key enablers for future non-volatile memory and logic applications. Functionally enhanced ReRAM devices could enable new hardware concepts, e.g. logic-in-memory or neuromorphic applications. In this work, we demonstrate the implementation of ReRAM-based fuzzy logic gates using Ta2O5 devices to enable analogous Minimum and Maximum operations. The realized gates consist of two anti-serially connected ReRAM cells offering two inputs and one output. The cells offer an endurance up to 106 cycles. By means of exemplary input signals, each gate functionality is verified and signal constraints are highlighted. This realization could improve the efficiency of analogous processing tasks such as sorting networks in the future.

Sound effects: Multimodal input helps infants find displaced objects.

PubMed

Shinskey, Jeanne L

2017-09-01

Before 9 months, infants use sound to retrieve a stationary object hidden by darkness but not one hidden by occlusion, suggesting auditory input is more salient in the absence of visual input. This article addresses how audiovisual input affects 10-month-olds' search for displaced objects. In AB tasks, infants who previously retrieved an object at A subsequently fail to find it after it is displaced to B, especially following a delay between hiding and retrieval. Experiment 1 manipulated auditory input by keeping the hidden object audible versus silent, and visual input by presenting the delay in the light versus dark. Infants succeeded more at B with audible than silent objects and, unexpectedly, more after delays in the light than dark. Experiment 2 presented both the delay and search phases in darkness. The unexpected light-dark difference disappeared. Across experiments, the presence of auditory input helped infants find displaced objects, whereas the absence of visual input did not. Sound might help by strengthening object representation, reducing memory load, or focusing attention. This work provides new evidence on when bimodal input aids object processing, corroborates claims that audiovisual processing improves over the first year of life, and contributes to multisensory approaches to studying cognition. Statement of contribution What is already known on this subject Before 9 months, infants use sound to retrieve a stationary object hidden by darkness but not one hidden by occlusion. This suggests they find auditory input more salient in the absence of visual input in simple search tasks. After 9 months, infants' object processing appears more sensitive to multimodal (e.g., audiovisual) input. What does this study add? This study tested how audiovisual input affects 10-month-olds' search for an object displaced in an AB task. Sound helped infants find displaced objects in both the presence and absence of visual input. Object processing becomes more sensitive to bimodal input as multisensory functions develop across the first year. © 2016 The British Psychological Society.

Smartphone Text Input Method Performance, Usability, and Preference With Younger and Older Adults.

PubMed

Smith, Amanda L; Chaparro, Barbara S

2015-09-01

User performance, perceived usability, and preference for five smartphone text input methods were compared with younger and older novice adults. Smartphones are used for a variety of functions other than phone calls, including text messaging, e-mail, and web browsing. Research comparing performance with methods of text input on smartphones reveals a high degree of variability in reported measures, procedures, and results. This study reports on a direct comparison of five of the most common input methods among a population of younger and older adults, who had no experience with any of the methods. Fifty adults (25 younger, 18-35 years; 25 older, 60-84 years) completed a text entry task using five text input methods (physical Qwerty, onscreen Qwerty, tracing, handwriting, and voice). Entry and error rates, perceived usability, and preference were recorded. Both age groups input text equally fast using voice input, but older adults were slower than younger adults using all other methods. Both age groups had low error rates when using physical Qwerty and voice, but older adults committed more errors with the other three methods. Both younger and older adults preferred voice and physical Qwerty input to the remaining methods. Handwriting consistently performed the worst and was rated lowest by both groups. Voice and physical Qwerty input methods proved to be the most effective for both younger and older adults, and handwriting input was the least effective overall. These findings have implications to the design of future smartphone text input methods and devices, particularly for older adults. © 2015, Human Factors and Ergonomics Society.

A FORTRAN program for the analysis of linear continuous and sample-data systems

NASA Technical Reports Server (NTRS)

Edwards, J. W.

1976-01-01

A FORTRAN digital computer program which performs the general analysis of linearized control systems is described. State variable techniques are used to analyze continuous, discrete, and sampled data systems. Analysis options include the calculation of system eigenvalues, transfer functions, root loci, root contours, frequency responses, power spectra, and transient responses for open- and closed-loop systems. A flexible data input format allows the user to define systems in a variety of representations. Data may be entered by inputing explicit data matrices or matrices constructed in user written subroutines, by specifying transfer function block diagrams, or by using a combination of these methods.

Attention enhances contrast appearance via increased input baseline of neural responses

PubMed Central

Cutrone, Elizabeth K.; Heeger, David J.; Carrasco, Marisa

2014-01-01

Covert spatial attention increases the perceived contrast of stimuli at attended locations, presumably via enhancement of visual neural responses. However, the relation between perceived contrast and the underlying neural responses has not been characterized. In this study, we systematically varied stimulus contrast, using a two-alternative, forced-choice comparison task to probe the effect of attention on appearance across the contrast range. We modeled performance in the task as a function of underlying neural contrast-response functions. Fitting this model to the observed data revealed that an increased input baseline in the neural responses accounted for the enhancement of apparent contrast with spatial attention. PMID:25549920

Ground Test of the Urine Processing Assembly for Accelerations and Transfer Functions

NASA Technical Reports Server (NTRS)

Houston, Janice; Almond, Deborah F. (Technical Monitor)

2001-01-01

This viewgraph presentation gives an overview of the ground test of the urine processing assembly for accelerations and transfer functions. Details are given on the test setup, test data, data analysis, analytical results, and microgravity assessment. The conclusions of the tests include the following: (1) the single input/multiple output method is useful if the data is acquired by tri-axial accelerometers and inputs can be considered uncorrelated; (2) tying coherence with the matrix yields higher confidence in results; (3) the WRS#2 rack ORUs need to be isolated; (4) and future work includes a plan for characterizing performance of isolation materials.

Phase Modulator with Terahertz Optical Bandwidth Formed by Multi-Layered Dielectric Stack

NASA Technical Reports Server (NTRS)

Keys, Andrew S. (Inventor); Fork, Richard L. (Inventor)

2005-01-01

An optical phase modulator includes a bandpass multilayer stack, formed by a plurality of dielectric layers, preferably of GaAs and AlAs, and having a transmission function related to the refractive index of the layers of the stack, for receiving an optical input signal to be phase modulated. A phase modulator device produces a nonmechanical change in the refractive index of each layer of the stack by, e.g., the injection of free carrier, to provide shifting of the transmission function so as to produce phase modulation of the optical input signal and to thereby produce a phase modulated output signal.

Convergent radial dispersion: A note on evaluation of the Laplace transform solution

USGS Publications Warehouse

Moench, Allen F.

1991-01-01

A numerical inversion algorithm for Laplace transforms that is capable of handling rapid changes in the computed function is applied to the Laplace transform solution to the problem of convergent radial dispersion in a homogeneous aquifer. Prior attempts by the author to invert this solution were unsuccessful for highly advective systems where the Peclet number was relatively large. The algorithm used in this note allows for rapid and accurate inversion of the solution for all Peclet numbers of practical interest, and beyond. Dimensionless breakthrough curves are illustrated for tracer input in the form of a step function, a Dirac impulse, or a rectangular input.

A BASIC program for the removal of noise from reaction traces using Fourier filtering.

PubMed

Brittain, T

1989-04-01

Software for the removal of noise from reaction curves using the principle of Fourier filtering has been written in BASIC to execute on a PC. The program inputs reaction traces which are subjected to a rotation-inversion process, to produce functions suitable for Fourier analysis. Fourier transformation into the frequency domain is followed by multiplication of the transform by a rectangular filter function, to remove the noise frequencies. Inverse transformation then yields a noise-reduced reaction trace suitable for further analysis. The program is interactive at each stage and could easily be modified to remove noise from a range of input data types.

Application of a rat hindlimb model: a prediction of force spaces reachable through stimulation of nerve fascicles.

PubMed

Johnson, Will L; Jindrich, Devin L; Zhong, Hui; Roy, Roland R; Edgerton, V Reggie

2011-12-01

A device to generate standing or locomotion through chronically placed electrodes has not been fully developed due in part to limitations of clinical experimentation and the high number of muscle activation inputs of the leg. We investigated the feasibility of functional electrical stimulation paradigms that minimize the input dimensions for controlling the limbs by stimulating at nerve fascicles, utilizing a model of the rat hindlimb, which combined previously collected morphological data with muscle physiological parameters presented herein. As validation of the model, we investigated the suitability of a lumped-parameter model for the prediction of muscle activation during dynamic tasks. Using the validated model, we found that the space of forces producible through activation of muscle groups sharing common nerve fascicles was nonlinearly dependent on the number of discrete muscle groups that could be individually activated (equivalently, the neuroanatomical level of activation). Seven commonly innervated muscle groups were sufficient to produce 78% of the force space producible through individual activation of the 42 modeled hindlimb muscles. This novel, neuroanatomically derived reduction in input dimension emphasizes the potential to simplify controllers for functional electrical stimulation to improve functional recovery after a neuromuscular injury.

Two- and three-input TALE-based AND logic computation in embryonic stem cells.

PubMed

Lienert, Florian; Torella, Joseph P; Chen, Jan-Hung; Norsworthy, Michael; Richardson, Ryan R; Silver, Pamela A

2013-11-01

Biological computing circuits can enhance our ability to control cellular functions and have potential applications in tissue engineering and medical treatments. Transcriptional activator-like effectors (TALEs) represent attractive components of synthetic gene regulatory circuits, as they can be designed de novo to target a given DNA sequence. We here demonstrate that TALEs can perform Boolean logic computation in mammalian cells. Using a split-intein protein-splicing strategy, we show that a functional TALE can be reconstituted from two inactive parts, thus generating two-input AND logic computation. We further demonstrate three-piece intein splicing in mammalian cells and use it to perform three-input AND computation. Using methods for random as well as targeted insertion of these relatively large genetic circuits, we show that TALE-based logic circuits are functional when integrated into the genome of mouse embryonic stem cells. Comparing construct variants in the same genomic context, we modulated the strength of the TALE-responsive promoter to improve the output of these circuits. Our work establishes split TALEs as a tool for building logic computation with the potential of controlling expression of endogenous genes or transgenes in response to a combination of cellular signals.

Application of a Rat Hindlimb Model: A Prediction of Force Spaces Reachable Through Stimulation of Nerve Fascicles

PubMed Central

Johnson, Will L.; Jindrich, Devin L.; Zhong, Hui; Roy, Roland R.

2011-01-01

A device to generate standing or locomotion through chronically placed electrodes has not been fully developed due in part to limitations of clinical experimentation and the high number of muscle activation inputs of the leg. We investigated the feasibility of functional electrical stimulation paradigms that minimize the input dimensions for controlling the limbs by stimulating at nerve fascicles, utilizing a model of the rat hindlimb which combined previously collected morphological data with muscle physiological parameters presented herein. As validation of the model we investigated the suitability of a lumped-parameter model for prediction of muscle activation during dynamic tasks. Using the validated model we found that the space of forces producible through activation of muscle groups sharing common nerve fascicles was nonlinearly dependent on the number of discrete muscle groups that could be individually activated (equivalently, the neuroanatomical level of activation). Seven commonly innervated muscle groups were sufficient to produce 78% of the force space producible through individual activation of the 42 modeled hindlimb muscles. This novel, neuroanatomically derived reduction in input dimension emphasizes the potential to simplify controllers for functional electrical stimulation to improve functional recovery after a neuromuscular injury. PMID:21244999

Optimal control of nonlinear continuous-time systems in strict-feedback form.

PubMed

Zargarzadeh, Hassan; Dierks, Travis; Jagannathan, Sarangapani

2015-10-01

This paper proposes a novel optimal tracking control scheme for nonlinear continuous-time systems in strict-feedback form with uncertain dynamics. The optimal tracking problem is transformed into an equivalent optimal regulation problem through a feedforward adaptive control input that is generated by modifying the standard backstepping technique. Subsequently, a neural network-based optimal control scheme is introduced to estimate the cost, or value function, over an infinite horizon for the resulting nonlinear continuous-time systems in affine form when the internal dynamics are unknown. The estimated cost function is then used to obtain the optimal feedback control input; therefore, the overall optimal control input for the nonlinear continuous-time system in strict-feedback form includes the feedforward plus the optimal feedback terms. It is shown that the estimated cost function minimizes the Hamilton-Jacobi-Bellman estimation error in a forward-in-time manner without using any value or policy iterations. Finally, optimal output feedback control is introduced through the design of a suitable observer. Lyapunov theory is utilized to show the overall stability of the proposed schemes without requiring an initial admissible controller. Simulation examples are provided to validate the theoretical results.

Impact angle constrained three-dimensional integrated guidance and control for STT missile in the presence of input saturation.

PubMed

Wang, Sen; Wang, Weihong; Xiong, Shaofeng

2016-09-01

Considering a class of skid-to-turn (STT) missile with fixed target and constrained terminal impact angles, a novel three-dimensional (3D) integrated guidance and control (IGC) scheme is proposed in this paper. Based on coriolis theorem, the fully nonlinear IGC model without the assumption that the missile flies heading to the target at initial time is established in the three-dimensional space. For this strict-feedback form of multi-variable system, dynamic surface control algorithm is implemented combining with extended observer (ESO) to complete the preliminary design. Then, in order to deal with the problems of the input constraints, a hyperbolic tangent function is introduced to approximate the saturation function and auxiliary system including a Nussbaum function established to compensate for the approximation error. The stability of the closed-loop system is proven based on Lyapunov theory. Numerical simulations results show that the proposed integrated guidance and control algorithm can ensure the accuracy of target interception with initial alignment angle deviation and the input saturation is suppressed with smooth deflection curves. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Studies of Transverse Momentum Dependent Parton Distributions and Bessel Weighting

NASA Astrophysics Data System (ADS)

Gamberg, Leonard

2015-04-01

We present a new technique for analysis of transverse momentum dependent parton distribution functions, based on the Bessel weighting formalism. Advantages of employing Bessel weighting are that transverse momentum weighted asymmetries provide a means to disentangle the convolutions in the cross section in a model independent way. The resulting compact expressions immediately connect to work on evolution equations for transverse momentum dependent parton distribution and fragmentation functions. As a test case, we apply the procedure to studies of the double longitudinal spin asymmetry in SIDIS using a dedicated Monte Carlo generator which includes quark intrinsic transverse momentum within the generalized parton model. Using a fully differential cross section for the process, the effect of four momentum conservation is analyzed using various input models for transverse momentum distributions and fragmentation functions. We observe a few percent systematic offset of the Bessel-weighted asymmetry obtained from Monte Carlo extraction compared to input model calculations. Bessel weighting provides a powerful and reliable tool to study the Fourier transform of TMDs with controlled systematics due to experimental acceptances and resolutions with different TMD model inputs. Work is supported by the U.S. Department of Energy under Contract No. DE-FG02-07ER41460.

Studies of Transverse Momentum Dependent Parton Distributions and Bessel Weighting

NASA Astrophysics Data System (ADS)

Gamberg, Leonard

2015-10-01

We present a new technique for analysis of transverse momentum dependent parton distribution functions, based on the Bessel weighting formalism. Advantages of employing Bessel weighting are that transverse momentum weighted asymmetries provide a means to disentangle the convolutions in the cross section in a model independent way. The resulting compact expressions immediately connect to work on evolution equations for transverse momentum dependent parton distribution and fragmentation functions. As a test case, we apply the procedure to studies of the double longitudinal spin asymmetry in SIDIS using a dedicated Monte Carlo generator which includes quark intrinsic transverse momentum within the generalized parton model. Using a fully differential cross section for the process, the effect of four momentum conservation is analyzed using various input models for transverse momentum distributions and fragmentation functions. We observe a few percent systematic offset of the Bessel-weighted asymmetry obtained from Monte Carlo extraction compared to input model calculations. Bessel weighting provides a powerful and reliable tool to study the Fourier transform of TMDs with controlled systematics due to experimental acceptances and resolutions with different TMD model inputs. Work is supported by the U.S. Department of Energy under Contract No. DE-FG02-07ER41460.

Global sensitivity analysis for fuzzy inputs based on the decomposition of fuzzy output entropy

NASA Astrophysics Data System (ADS)

Shi, Yan; Lu, Zhenzhou; Zhou, Yicheng

2018-06-01

To analyse the component of fuzzy output entropy, a decomposition method of fuzzy output entropy is first presented. After the decomposition of fuzzy output entropy, the total fuzzy output entropy can be expressed as the sum of the component fuzzy entropy contributed by fuzzy inputs. Based on the decomposition of fuzzy output entropy, a new global sensitivity analysis model is established for measuring the effects of uncertainties of fuzzy inputs on the output. The global sensitivity analysis model can not only tell the importance of fuzzy inputs but also simultaneously reflect the structural composition of the response function to a certain degree. Several examples illustrate the validity of the proposed global sensitivity analysis, which is a significant reference in engineering design and optimization of structural systems.

Method and apparatus for measuring response time

DOEpatents

Johanson, Edward W.; August, Charles

1985-01-01

A method of measuring the response time of an electrical instrument which generates an output signal in response to the application of a specified input, wherein the output signal varies as a function of time and when subjected to a step input approaches a steady-state value, comprises the steps of: (a) applying a step input of predetermined value to the electrical instrument to generate an output signal; (b) simultaneously starting a timer; (c) comparing the output signal to a reference signal to generate a stop signal when the output signal is substantially equal to the reference signal, the reference signal being a specified percentage of the steady-state value of the output signal corresponding to the predetermined value of the step input; and (d) applying the stop signal when generated to stop the timer.

Method and apparatus for measuring response time

DOEpatents

Johanson, E.W.; August, C.

1983-08-11

A method of measuring the response time of an electrical instrument which generates an output signal in response to the application of a specified input, wherein the output signal varies as a function of time and when subjected to a step input approaches a steady-state value, comprises the steps of: (a) applying a step input of predetermined value to the electrical instrument to generate an output signal; (b) simultaneously starting a timer; (c) comparing the output signal to a reference signal to generate a stop signal when the output signal is substantially equal to the reference signal, the reference signal being a specified percentage of the steady-state value of the output signal corresponding to the predetermined value of the step input; and (d) applying the stop signal when generated to stop the timer.

Coupling induced logical stochastic resonance

NASA Astrophysics Data System (ADS)

Aravind, Manaoj; Murali, K.; Sinha, Sudeshna

2018-06-01

In this work we will demonstrate the following result: when we have two coupled bistable sub-systems, each driven separately by an external logic input signal, the coupled system yields outputs that can be mapped to specific logic gate operations in a robust manner, in an optimal window of noise. So, though the individual systems receive only one logic input each, due to the interplay of coupling, nonlinearity and noise, they cooperatively respond to give a logic output that is a function of both inputs. Thus the emergent collective response of the system, due to the inherent coupling, in the presence of a noise floor, maps consistently to that of logic outputs of the two inputs, a phenomenon we term coupling induced Logical Stochastic Resonance. Lastly, we demonstrate our idea in proof of principle circuit experiments.

Nitrogen addition affects leaf nutrition and photosynthesis in sugar maple in a nutrient-poor northern Vermont forest

Treesearch

David S. Ellsworth

1999-01-01

Sugar maple-dominated forest ecosystems in the northeastern U.S. have been receiving precipitation nitrogen (N) inputs of 15 -20 kg N ha1 year1 since at least the mid 1980s sustained chronic N inputs of this magnitude into nutrient-poor forest ecosystems may cause eutrophication and affect ecosystem functioning as well as...

Fog and soil weathering as sources of nutrients in a California redwood forest

Treesearch

Holly A. Ewing; Kathleen C. Weathers; Amanda M. Lindsey; Pamela H. Templer; Todd E. Dawson; Damon C. Bradbury; Mary K. Firestone; Vanessa K.S. Boukili

2012-01-01

Fog water deposition is thought to influence the ecological function of many coastal ecosystems, including coast redwood forests. We examined cation and anion inputs from fog and rain, as well as the fate of these inputs, within a Sonoma County, California, coast redwood forest to elucidate the availability of these ions and some of the biotic and abiotic processes...

Lumped Nonlinear System Analysis with Volterra Series.

DTIC Science & Technology

1980-04-01

f h2 (t-=,t-r )x(r)x(t2)dl d 2 (4- 1 )O0 0 Consider the input signal comprising two unit sinusoidal signals at fre- quencies wa and wb. The input x... 1 - 2 . Nonlinear System Analysis Methods. .............. 2 1 -3. Objectives of the Investigation ....... ............... 6 1 -4. Organization of...the Report ..... ... ................. 9 CHAPTER 2 - VOLTERRA FUNCTIONAL SERIES ...... ............... 12 2 - 1 . Introduction

Electrical and Optical Activation of Mesoscale Neural Circuits with Implications for Coding.

PubMed

Millard, Daniel C; Whitmire, Clarissa J; Gollnick, Clare A; Rozell, Christopher J; Stanley, Garrett B

2015-11-25

Artificial activation of neural circuitry through electrical microstimulation and optogenetic techniques is important for both scientific discovery of circuit function and for engineered approaches to alleviate various disorders of the nervous system. However, evidence suggests that neural activity generated by artificial stimuli differs dramatically from normal circuit function, in terms of both the local neuronal population activity at the site of activation and the propagation to downstream brain structures. The precise nature of these differences and the implications for information processing remain unknown. Here, we used voltage-sensitive dye imaging of primary somatosensory cortex in the anesthetized rat in response to deflections of the facial vibrissae and electrical or optogenetic stimulation of thalamic neurons that project directly to the somatosensory cortex. Although the different inputs produced responses that were similar in terms of the average cortical activation, the variability of the cortical response was strikingly different for artificial versus sensory inputs. Furthermore, electrical microstimulation resulted in highly unnatural spatial activation of cortex, whereas optical input resulted in spatial cortical activation that was similar to that induced by sensory inputs. A thalamocortical network model suggested that observed differences could be explained by differences in the way in which artificial and natural inputs modulate the magnitude and synchrony of population activity. Finally, the variability structure in the response for each case strongly influenced the optimal inputs for driving the pathway from the perspective of an ideal observer of cortical activation when considered in the context of information transmission. Artificial activation of neural circuitry through electrical microstimulation and optogenetic techniques is important for both scientific discovery and clinical translation. However, neural activity generated by these artificial means differs dramatically from normal circuit function, both locally and in the propagation to downstream brain structures. The precise nature of these differences and the implications for information processing remain unknown. The significance of this work is in quantifying the differences, elucidating likely mechanisms underlying the differences, and determining the implications for information processing. Copyright © 2015 the authors 0270-6474/15/3515702-14$15.00/0.

Digital control algorithms for microgravity isolation systems

NASA Technical Reports Server (NTRS)

Sinha, Alok; Wang, Yung-Peng

1992-01-01

New digital control algorithms were developed to achieve the desired acceleration transmissibility function. The attractive electromagnets have been taken as actuators. The relative displacement and the acceleration of the mass were used as feedback signals. Two approaches were developed to find that controller transfer function in Z-domain, which yields the desired transmissibility at each frequency. In the first approach, the controller transfer function is obtained by assuming that the desired transmissibility is known in Z-domain. Since the desired transmissibility H sub d(S) = 1/(tauS+1)(exp 2) is given in S-domain, the first task is to obtain the desired transmissibility in Z-domain. There are three methods to perform this task: bilinear transformation, and backward and forward rectangular rules. The bilinear transformation and backward rectangular rule lead to improper controller transfer functions, which are physically not realizable. The forward rectangular rule does lead to a physically realizable controller. However, this controller is found to be marginally stable because of a pole at Z=1. In order to eliminate this pole, a hybrid control structure is proposed. Here the control input is composed of two parts: analog and digital. The analog input simply represents the velocity (or the integral of acceleration) feedback; and the digital controller which uses only relative displacement signal, is then obtained to achieve the desired closed-loop transfer function. The stability analysis indicates that the controller transfer function is stable for typical values of sampling period. In the second approach, the aforementioned hybrid control structure is again used. First, an analog controller transfer function corresponding to relative displacement feedback is obtained to achieve the transmissibility as 1/(tauS+1)(exp 2). Then the transfer function for the digital control input is obtained by discretizing this analog controller transfer function via bilinear transformation. The stability of the resulting Z-domain closed loop system is analyzed. Also, the frequency response of the Z-domain closed-loop transfer function is determined to evaluate the performance of the control system.

Identification of biomechanical nonlinearity in whole-body vibration using a reverse path multi-input-single-output method

NASA Astrophysics Data System (ADS)

Huang, Ya; Ferguson, Neil S.

2018-04-01

The study implements a classic signal analysis technique, typically applied to structural dynamics, to examine the nonlinear characteristics seen in the apparent mass of a recumbent person during whole-body horizontal random vibration. The nonlinearity in the present context refers to the amount of 'output' that is not correlated or coherent to the 'input', usually indicated by values of the coherence function that are less than unity. The analysis is based on the longitudinal horizontal inline and vertical cross-axis apparent mass of twelve human subjects exposed to 0.25-20 Hz random acceleration vibration at 0.125 and 1.0 ms-2 r.m.s. The conditioned reverse path frequency response functions (FRF) reveal that the uncorrelated 'linear' relationship between physical input (acceleration) and outputs (inline and cross-axis forces) has much greater variation around the primary resonance frequency between 0.5 and 5 Hz. By reversing the input and outputs of the physical system, it is possible to assemble additional mathematical inputs from the physical output forces and mathematical constructs (e.g. square root of inline force). Depending on the specific construct, this can improve the summed multiple coherence at frequencies where the response magnitude is low. In the present case this is between 6 and 20 Hz. The statistical measures of the response force time histories of each of the twelve subjects indicate that there are potential anatomical 'end-stops' for the sprung mass in the inline axis. No previous study has applied this reverse path multi-input-single-output approach to human vibration kinematic and kinetic data before. The implementation demonstrated in the present study will allow new and existing data to be examined using this different analytical tool.

CB1 Cannabinoid Receptor Expression in the Striatum: Association with Corticostriatal Circuits and Developmental Regulation

PubMed Central

Van Waes, Vincent; Beverley, Joel A.; Siman, Homayoun; Tseng, Kuei Y.; Steiner, Heinz

2012-01-01

Corticostriatal circuits mediate various aspects of goal-directed behavior and are critically important for basal ganglia-related disorders. Activity in these circuits is regulated by the endocannabinoid system via stimulation of CB1 cannabinoid receptors. CB1 receptors are highly expressed in projection neurons and select interneurons of the striatum, but expression levels vary considerably between different striatal regions (functional domains). We investigated CB1 receptor expression within specific corticostriatal circuits by mapping CB1 mRNA levels in striatal sectors defined by their cortical inputs in rats. We also assessed changes in CB1 expression in the striatum during development. Our results show that CB1 expression is highest in juveniles (P25) and then progressively decreases toward adolescent (P40) and adult (P70) levels. At every age, CB1 receptors are predominantly expressed in sensorimotor striatal sectors, with considerably lower expression in associative and limbic sectors. Moreover, for most corticostriatal circuits there is an inverse relationship between cortical and striatal expression levels. Thus, striatal sectors with high CB1 expression (sensorimotor sectors) tend to receive inputs from cortical areas with low expression, while striatal sectors with low expression (associative/limbic sectors) receive inputs from cortical regions with higher expression (medial prefrontal cortex). In so far as CB1 mRNA levels reflect receptor function, our findings suggest differential CB1 signaling between different developmental stages and between sensorimotor and associative/limbic circuits. The regional distribution of CB1 receptor expression in the striatum further suggests that, in sensorimotor sectors, CB1 receptors mostly regulate GABA inputs from local axon collaterals of projection neurons, whereas in associative/limbic sectors, CB1 regulation of GABA inputs from interneurons and glutamate inputs may be more important. PMID:22416230

Origin and function of short-latency inputs to the neural substrates underlying the acoustic startle reflex

PubMed Central

Gómez-Nieto, Ricardo; Horta-Júnior, José de Anchieta C.; Castellano, Orlando; Millian-Morell, Lymarie; Rubio, Maria E.; López, Dolores E.

2014-01-01

The acoustic startle reflex (ASR) is a survival mechanism of alarm, which rapidly alerts the organism to a sudden loud auditory stimulus. In rats, the primary ASR circuit encompasses three serially connected structures: cochlear root neurons (CRNs), neurons in the caudal pontine reticular nucleus (PnC), and motoneurons in the medulla and spinal cord. It is well-established that both CRNs and PnC neurons receive short-latency auditory inputs to mediate the ASR. Here, we investigated the anatomical origin and functional role of these inputs using a multidisciplinary approach that combines morphological, electrophysiological and behavioral techniques. Anterograde tracer injections into the cochlea suggest that CRNs somata and dendrites receive inputs depending, respectively, on their basal or apical cochlear origin. Confocal colocalization experiments demonstrated that these cochlear inputs are immunopositive for the vesicular glutamate transporter 1 (VGLUT1). Using extracellular recordings in vivo followed by subsequent tracer injections, we investigated the response of PnC neurons after contra-, ipsi-, and bilateral acoustic stimulation and identified the source of their auditory afferents. Our results showed that the binaural firing rate of PnC neurons was higher than the monaural, exhibiting higher spike discharges with contralateral than ipsilateral acoustic stimulations. Our histological analysis confirmed the CRNs as the principal source of short-latency acoustic inputs, and indicated that other areas of the cochlear nucleus complex are not likely to innervate PnC. Behaviorally, we observed a strong reduction of ASR amplitude in monaural earplugged rats that corresponds with the binaural summation process shown in our electrophysiological findings. Our study contributes to understand better the role of neuronal mechanisms in auditory alerting behaviors and provides strong evidence that the CRNs-PnC pathway mediates fast neurotransmission and binaural summation of the ASR. PMID:25120419

Assessment of input-output properties and control of neuroprosthetic hand grasp.

PubMed

Hines, A E; Owens, N E; Crago, P E

1992-06-01

Three tests have been developed to evaluate rapidly and quantitatively the input-output properties and patient control of neuroprosthetic hand grasp. Each test utilizes a visual pursuit tracking task during which the subject controls the grasp force and grasp opening (position) of the hand. The first test characterizes the static input-output properties of the hand grasp, where the input is a slowly changing patient generated command signal and the outputs are grasp force and grasp opening. Nonlinearities and inappropriate slopes have been documented in these relationships, and in some instances the need for system returning has been indicated. For each subject larger grasp forces were produced when grasping larger objects, and for some subjects the shapes of the relationships also varied with object size. The second test quantifies the ability of the subject to control the hand grasp outputs while tracking steps and ramps. Neuroprosthesis users had rms errors two to three times larger when tracking steps versus ramps, and had rms errors four to five times larger than normals when tracking ramps. The third test provides an estimate of the frequency response of the hand grasp system dynamics, from input and output data collected during a random tracking task. Transfer functions were estimated by spectral analysis after removal of the static input-output nonlinearities measured in the first test. The dynamics had low-pass filter characteristics with 3 dB cutoff frequencies from 1.0 to 1.4 Hz. The tests developed in this study provide a rapid evaluation of both the system and the user. They provide information to 1) help interpret subject performance of functional tasks, 2) evaluate the efficacy of system features such as closed-loop control, and 3) screen the neuroprosthesis to indicate the need for retuning.

Olfactory Bulb Deep Short-Axon Cells Mediate Widespread Inhibition of Tufted Cell Apical Dendrites.

PubMed

Burton, Shawn D; LaRocca, Greg; Liu, Annie; Cheetham, Claire E J; Urban, Nathaniel N

2017-02-01

In the main olfactory bulb (MOB), the first station of sensory processing in the olfactory system, GABAergic interneuron signaling shapes principal neuron activity to regulate olfaction. However, a lack of known selective markers for MOB interneurons has strongly impeded cell-type-selective investigation of interneuron function. Here, we identify the first selective marker of glomerular layer-projecting deep short-axon cells (GL-dSACs) and investigate systematically the structure, abundance, intrinsic physiology, feedforward sensory input, neuromodulation, synaptic output, and functional role of GL-dSACs in the mouse MOB circuit. GL-dSACs are located in the internal plexiform layer, where they integrate centrifugal cholinergic input with highly convergent feedforward sensory input. GL-dSAC axons arborize extensively across the glomerular layer to provide highly divergent yet selective output onto interneurons and principal tufted cells. GL-dSACs are thus capable of shifting the balance of principal tufted versus mitral cell activity across large expanses of the MOB in response to diverse sensory and top-down neuromodulatory input. The identification of cell-type-selective molecular markers has fostered tremendous insight into how distinct interneurons shape sensory processing and behavior. In the main olfactory bulb (MOB), inhibitory circuits regulate the activity of principal cells precisely to drive olfactory-guided behavior. However, selective markers for MOB interneurons remain largely unknown, limiting mechanistic understanding of olfaction. Here, we identify the first selective marker of a novel population of deep short-axon cell interneurons with superficial axonal projections to the sensory input layer of the MOB. Using this marker, together with immunohistochemistry, acute slice electrophysiology, and optogenetic circuit mapping, we reveal that this novel interneuron population integrates centrifugal cholinergic input with broadly tuned feedforward sensory input to modulate principal cell activity selectively. Copyright © 2017 the authors 0270-6474/17/371117-22$15.00/0.

Momentum distributions for H 2 ( e , e ' p )

DOE PAGES

Ford, William P.; Jeschonnek, Sabine; Van Orden, J. W.

2014-12-29

[Background] A primary goal of deuteron electrodisintegration is the possibility of extracting the deuteron momentum distribution. This extraction is inherently fraught with difficulty, as the momentum distribution is not an observable and the extraction relies on theoretical models dependent on other models as input. [Purpose] We present a new method for extracting the momentum distribution which takes into account a wide variety of model inputs thus providing a theoretical uncertainty due to the various model constituents. [Method] The calculations presented here are using a Bethe-Salpeter like formalism with a wide variety of bound state wave functions, form factors, and finalmore » state interactions. We present a method to extract the momentum distributions from experimental cross sections, which takes into account the theoretical uncertainty from the various model constituents entering the calculation. [Results] In order to test the extraction pseudo-data was generated, and the extracted "experimental'' distribution, which has theoretical uncertainty from the various model inputs, was compared with the theoretical distribution used to generate the pseudo-data. [Conclusions] In the examples we compared the original distribution was typically within the error band of the extracted distribution. The input wave functions do contain some outliers which are discussed in the text, but at least this process can provide an upper bound on the deuteron momentum distribution. Due to the reliance on the theoretical calculation to obtain this quantity any extraction method should account for the theoretical error inherent in these calculations due to model inputs.« less

An Integrated Circuit for Simultaneous Extracellular Electrophysiology Recording and Optogenetic Neural Manipulation

PubMed Central

Chen, Chang Hao; McCullagh, Elizabeth A.; Pun, Sio Hang; Mak, Peng Un; Vai, Mang I; Mak, Pui In; Klug, Achim; Lei, Tim C.

2017-01-01

The ability to record and to control action potential firing in neuronal circuits of the brain is critical to understand how the brain functions on the cellular and network levels. Recent development of optogenetic proteins allows direct stimulation or inhibition of action potential firing of neurons upon optical illumination. In this paper, we combined a low-noise and high input impedance (or low input capacitance) neural recording amplifier, and a high current laser/LED driver in a monolithic integrated circuit (IC) for simultaneous neural recording and optogenetic neural control. The low input capacitance of the amplifier (9.7 pF) was achieved through adding a dedicated unity gain input stage optimized for high impedance metal electrodes. The input referred noise of the amplifier was measured to be 4.57 µVrms, which is lower than the estimated thermal noise of the metal electrode. Thus, action potentials originating from a single neuron can be recorded with a signal-to-noise ratio of ~6.6. The LED/laser current driver delivers a maximum current of 330 mA to generate adequate light for optogenetic control. We experimentally tested the functionality of the IC with an anesthetized Mongolian gerbil and recorded auditory stimulated action potentials from the inferior colliculus. Furthermore, we showed that spontaneous firing of 5th (trigeminal) nerve fibers was inhibited using the optogenetic protein Halorhodopsin. A noise model was also derived including the equivalent electronic components of the metal electrode and the high current driver to guide the design. PMID:28221990

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.

Iterative pixelwise approach applied to computer-generated holograms and diffractive optical elements.

PubMed

Hsu, Wei-Feng; Lin, Shih-Chih

2018-01-01

This paper presents a novel approach to optimizing the design of phase-only computer-generated holograms (CGH) for the creation of binary images in an optical Fourier transform system. Optimization begins by selecting an image pixel with a temporal change in amplitude. The modulated image function undergoes an inverse Fourier transform followed by the imposition of a CGH constraint and the Fourier transform to yield an image function associated with the change in amplitude of the selected pixel. In iterations where the quality of the image is improved, that image function is adopted as the input for the next iteration. In cases where the image quality is not improved, the image function before the pixel changed is used as the input. Thus, the proposed approach is referred to as the pixelwise hybrid input-output (PHIO) algorithm. The PHIO algorithm was shown to achieve image quality far exceeding that of the Gerchberg-Saxton (GS) algorithm. The benefits were particularly evident when the PHIO algorithm was equipped with a dynamic range of image intensities equivalent to the amplitude freedom of the image signal. The signal variation of images reconstructed from the GS algorithm was 1.0223, but only 0.2537 when using PHIO, i.e., a 75% improvement. Nonetheless, the proposed scheme resulted in a 10% degradation in diffraction efficiency and signal-to-noise ratio.

Effect of basal forebrain stimulation on extracellular acetylcholine release and blood flow in the olfactory bulb.

PubMed

Uchida, Sae; Kagitani, Fusako

2017-05-12

The olfactory bulb receives cholinergic basal forebrain input, as does the neocortex; however, the in vivo physiological functions regarding the release of extracellular acetylcholine and regulation of regional blood flow in the olfactory bulb are unclear. We used in vivo microdialysis to measure the extracellular acetylcholine levels in the olfactory bulb of urethane-anesthetized rats. Focal chemical stimulation by microinjection of L-glutamate into the horizontal limb of the diagonal band of Broca (HDB) in the basal forebrain, which is the main source of cholinergic input to the olfactory bulb, increased extracellular acetylcholine release in the ipsilateral olfactory bulb. When the regional cerebral blood flow was measured using laser speckle contrast imaging, the focal chemical stimulation of the HDB did not significantly alter the blood flow in the olfactory bulb, while increases were observed in the neocortex. Our results suggest a functional difference between the olfactory bulb and neocortex regarding cerebral blood flow regulation through the release of acetylcholine by cholinergic basal forebrain input.

Input-output Transfer Function Analysis of a Photometer Circuit Based on an Operational Amplifier.

PubMed

Hernandez, Wilmar

2008-01-09

In this paper an input-output transfer function analysis based on the frequencyresponse of a photometer circuit based on operational amplifier (op amp) is carried out. Opamps are universally used in monitoring photodetectors and there are a variety of amplifierconnections for this purpose. However, the electronic circuits that are usually used to carryout the signal treatment in photometer circuits introduce some limitations in theperformance of the photometers that influence the selection of the op amps and otherelectronic devices. For example, the bandwidth, slew-rate, noise, input impedance and gain,among other characteristics of the op amp, are often the performance limiting factors ofphotometer circuits. For this reason, in this paper a comparative analysis between twophotodiode amplifier circuits is carried out. One circuit is based on a conventional currentto-voltage converter connection and the other circuit is based on a robust current-to-voltageconverter connection. The results are satisfactory and show that the photodiode amplifierperformance can be improved by using robust control techniques.

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.

Input-Specific NMDAR-Dependent Potentiation of Dendritic GABAergic Inhibition.

PubMed

Chiu, Chiayu Q; Martenson, James S; Yamazaki, Maya; Natsume, Rie; Sakimura, Kenji; Tomita, Susumu; Tavalin, Steven J; Higley, Michael J

2018-01-17

Preservation of a balance between synaptic excitation and inhibition is critical for normal brain function. A number of homeostatic cellular mechanisms have been suggested to play a role in maintaining this balance, including long-term plasticity of GABAergic inhibitory synapses. Many previous studies have demonstrated a coupling of postsynaptic spiking with modification of perisomatic inhibition. Here, we demonstrate that activation of NMDA-type glutamate receptors leads to input-specific long-term potentiation of dendritic inhibition mediated by somatostatin-expressing interneurons. This form of plasticity is expressed postsynaptically and requires both CaMKIIα and the β2 subunit of the GABA-A receptor. Importantly, this process may function to preserve dendritic inhibition, as genetic deletion of NMDAR signaling results in a selective weakening of dendritic inhibition. Overall, our results reveal a new mechanism for linking excitatory and inhibitory input in neuronal dendrites and provide novel insight into the homeostatic regulation of synaptic transmission in cortical circuits. Copyright © 2017 Elsevier Inc. All rights reserved.

Studies of transverse momentum dependent parton distributions and Bessel weighting

DOE PAGES

Aghasyan, M.; Avakian, H.; De Sanctis, E.; ...

2015-03-01

In this paper we present a new technique for analysis of transverse momentum dependent parton distribution functions, based on the Bessel weighting formalism. The procedure is applied to studies of the double longitudinal spin asymmetry in semi-inclusive deep inelastic scattering using a new dedicated Monte Carlo generator which includes quark intrinsic transverse momentum within the generalized parton model. Using a fully differential cross section for the process, the effect of four momentum conservation is analyzed using various input models for transverse momentum distributions and fragmentation functions. We observe a few percent systematic offset of the Bessel-weighted asymmetry obtained from Montemore » Carlo extraction compared to input model calculations, which is due to the limitations imposed by the energy and momentum conservation at the given energy/Q2. We find that the Bessel weighting technique provides a powerful and reliable tool to study the Fourier transform of TMDs with controlled systematics due to experimental acceptances and resolutions with different TMD model inputs.« less

Nonlinear channel equalization for QAM signal constellation using artificial neural networks.

PubMed

Patra, J C; Pal, R N; Baliarsingh, R; Panda, G

1999-01-01

Application of artificial neural networks (ANN's) to adaptive channel equalization in a digital communication system with 4-QAM signal constellation is reported in this paper. A novel computationally efficient single layer functional link ANN (FLANN) is proposed for this purpose. This network has a simple structure in which the nonlinearity is introduced by functional expansion of the input pattern by trigonometric polynomials. Because of input pattern enhancement, the FLANN is capable of forming arbitrarily nonlinear decision boundaries and can perform complex pattern classification tasks. Considering channel equalization as a nonlinear classification problem, the FLANN has been utilized for nonlinear channel equalization. The performance of the FLANN is compared with two other ANN structures [a multilayer perceptron (MLP) and a polynomial perceptron network (PPN)] along with a conventional linear LMS-based equalizer for different linear and nonlinear channel models. The effect of eigenvalue ratio (EVR) of input correlation matrix on the equalizer performance has been studied. The comparison of computational complexity involved for the three ANN structures is also provided.

Cross-entropy embedding of high-dimensional data using the neural gas model.

PubMed

Estévez, Pablo A; Figueroa, Cristián J; Saito, Kazumi

2005-01-01

A cross-entropy approach to mapping high-dimensional data into a low-dimensional space embedding is presented. The method allows to project simultaneously the input data and the codebook vectors, obtained with the Neural Gas (NG) quantizer algorithm, into a low-dimensional output space. The aim of this approach is to preserve the relationship defined by the NG neighborhood function for each pair of input and codebook vectors. A cost function based on the cross-entropy between input and output probabilities is minimized by using a Newton-Raphson method. The new approach is compared with Sammon's non-linear mapping (NLM) and the hierarchical approach of combining a vector quantizer such as the self-organizing feature map (SOM) or NG with the NLM recall algorithm. In comparison with these techniques, our method delivers a clear visualization of both data points and codebooks, and it achieves a better mapping quality in terms of the topology preservation measure q(m).

Studies of transverse momentum dependent parton distributions and Bessel weighting

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

Aghasyan, M.; Avakian, H.; De Sanctis, E.

In this paper we present a new technique for analysis of transverse momentum dependent parton distribution functions, based on the Bessel weighting formalism. The procedure is applied to studies of the double longitudinal spin asymmetry in semi-inclusive deep inelastic scattering using a new dedicated Monte Carlo generator which includes quark intrinsic transverse momentum within the generalized parton model. Using a fully differential cross section for the process, the effect of four momentum conservation is analyzed using various input models for transverse momentum distributions and fragmentation functions. We observe a few percent systematic offset of the Bessel-weighted asymmetry obtained from Montemore » Carlo extraction compared to input model calculations, which is due to the limitations imposed by the energy and momentum conservation at the given energy/Q2. We find that the Bessel weighting technique provides a powerful and reliable tool to study the Fourier transform of TMDs with controlled systematics due to experimental acceptances and resolutions with different TMD model inputs.« less

Acoustical transmission-line model of the middle-ear cavities and mastoid air cells.

PubMed

Keefe, Douglas H

2015-04-01

An acoustical transmission line model of the middle-ear cavities and mastoid air cell system (MACS) was constructed for the adult human middle ear with normal function. The air-filled cavities comprised the tympanic cavity, aditus, antrum, and MACS. A binary symmetrical airway branching model of the MACS was constructed using an optimization procedure to match the average total volume and surface area of human temporal bones. The acoustical input impedance of the MACS was calculated using a recursive procedure, and used to predict the input impedance of the middle-ear cavities at the location of the tympanic membrane. The model also calculated the ratio of the acoustical pressure in the antrum to the pressure in the middle-ear cavities at the location of the tympanic membrane. The predicted responses were sensitive to the magnitude of the viscothermal losses within the MACS. These predicted input impedance and pressure ratio functions explained the presence of multiple resonances reported in published data, which were not explained by existing MACS models.

Gaussian functional regression for output prediction: Model assimilation and experimental design

NASA Astrophysics Data System (ADS)

Nguyen, N. C.; Peraire, J.

2016-03-01

In this paper, we introduce a Gaussian functional regression (GFR) technique that integrates multi-fidelity models with model reduction to efficiently predict the input-output relationship of a high-fidelity model. The GFR method combines the high-fidelity model with a low-fidelity model to provide an estimate of the output of the high-fidelity model in the form of a posterior distribution that can characterize uncertainty in the prediction. A reduced basis approximation is constructed upon the low-fidelity model and incorporated into the GFR method to yield an inexpensive posterior distribution of the output estimate. As this posterior distribution depends crucially on a set of training inputs at which the high-fidelity models are simulated, we develop a greedy sampling algorithm to select the training inputs. Our approach results in an output prediction model that inherits the fidelity of the high-fidelity model and has the computational complexity of the reduced basis approximation. Numerical results are presented to demonstrate the proposed approach.

Polynomic nonlinear dynamical systems - A residual sensitivity method for model reduction

NASA Technical Reports Server (NTRS)

Yurkovich, S.; Bugajski, D.; Sain, M.

1985-01-01

The motivation for using polynomic combinations of system states and inputs to model nonlinear dynamics systems is founded upon the classical theories of analysis and function representation. A feature of such representations is the need to make available all possible monomials in these variables, up to the degree specified, so as to provide for the description of widely varying functions within a broad class. For a particular application, however, certain monomials may be quite superfluous. This paper examines the possibility of removing monomials from the model in accordance with the level of sensitivity displayed by the residuals to their absence. Critical in these studies is the effect of system input excitation, and the effect of discarding monomial terms, upon the model parameter set. Therefore, model reduction is approached iteratively, with inputs redesigned at each iteration to ensure sufficient excitation of remaining monomials for parameter approximation. Examples are reported to illustrate the performance of such model reduction approaches.

Training feed-forward neural networks with gain constraints

PubMed

Hartman

2000-04-01

Inaccurate input-output gains (partial derivatives of outputs with respect to inputs) are common in neural network models when input variables are correlated or when data are incomplete or inaccurate. Accurate gains are essential for optimization, control, and other purposes. We develop and explore a method for training feedforward neural networks subject to inequality or equality-bound constraints on the gains of the learned mapping. Gain constraints are implemented as penalty terms added to the objective function, and training is done using gradient descent. Adaptive and robust procedures are devised for balancing the relative strengths of the various terms in the objective function, which is essential when the constraints are inconsistent with the data. The approach has the virtue that the model domain of validity can be extended via extrapolation training, which can dramatically improve generalization. The algorithm is demonstrated here on artificial and real-world problems with very good results and has been advantageously applied to dozens of models currently in commercial use.

Method and apparatus for smart battery charging including a plurality of controllers each monitoring input variables

DOEpatents

Hammerstrom, Donald J.

2013-10-15

A method for managing the charging and discharging of batteries wherein at least one battery is connected to a battery charger, the battery charger is connected to a power supply. A plurality of controllers in communication with one and another are provided, each of the controllers monitoring a subset of input variables. A set of charging constraints may then generated for each controller as a function of the subset of input variables. A set of objectives for each controller may also be generated. A preferred charge rate for each controller is generated as a function of either the set of objectives, the charging constraints, or both, using an algorithm that accounts for each of the preferred charge rates for each of the controllers and/or that does not violate any of the charging constraints. A current flow between the battery and the battery charger is then provided at the actual charge rate.

Adaptive Backstepping-Based Neural Tracking Control for MIMO Nonlinear Switched Systems Subject to Input Delays.

PubMed

Niu, Ben; Li, Lu

2018-06-01

This brief proposes a new neural-network (NN)-based adaptive output tracking control scheme for a class of disturbed multiple-input multiple-output uncertain nonlinear switched systems with input delays. By combining the universal approximation ability of radial basis function NNs and adaptive backstepping recursive design with an improved multiple Lyapunov function (MLF) scheme, a novel adaptive neural output tracking controller design method is presented for the switched system. The feature of the developed design is that different coordinate transformations are adopted to overcome the conservativeness caused by adopting a common coordinate transformation for all subsystems. It is shown that all the variables of the resulting closed-loop system are semiglobally uniformly ultimately bounded under a class of switching signals in the presence of MLF and that the system output can follow the desired reference signal. To demonstrate the practicability of the obtained result, an adaptive neural output tracking controller is designed for a mass-spring-damper system.

Three Types of Cortical L5 Neurons that Differ in Brain-Wide Connectivity and Function

PubMed Central

Kim, Euiseok J.; Juavinett, Ashley L.; Kyubwa, Espoir M.; Jacobs, Matthew W.; Callaway, Edward M.

2015-01-01

SUMMARY Cortical layer 5 (L5) pyramidal neurons integrate inputs from many sources and distribute outputs to cortical and subcortical structures. Previous studies demonstrate two L5 pyramid types: cortico-cortical (CC) and cortico-subcortical (CS). We characterize connectivity and function of these cell types in mouse primary visual cortex and reveal a new subtype. Unlike previously described L5 CC and CS neurons, this new subtype does not project to striatum [cortico-cortical, non-striatal (CC-NS)] and has distinct morphology, physiology and visual responses. Monosynaptic rabies tracing reveals that CC neurons preferentially receive input from higher visual areas, while CS neurons receive more input from structures implicated in top-down modulation of brain states. CS neurons are also more direction-selective and prefer faster stimuli than CC neurons. These differences suggest distinct roles as specialized output channels, with CS neurons integrating information and generating responses more relevant to movement control and CC neurons being more important in visual perception. PMID:26671462

Three Types of Cortical Layer 5 Neurons That Differ in Brain-wide Connectivity and Function.

PubMed

Kim, Euiseok J; Juavinett, Ashley L; Kyubwa, Espoir M; Jacobs, Matthew W; Callaway, Edward M

2015-12-16

Cortical layer 5 (L5) pyramidal neurons integrate inputs from many sources and distribute outputs to cortical and subcortical structures. Previous studies demonstrate two L5 pyramid types: cortico-cortical (CC) and cortico-subcortical (CS). We characterize connectivity and function of these cell types in mouse primary visual cortex and reveal a new subtype. Unlike previously described L5 CC and CS neurons, this new subtype does not project to striatum [cortico-cortical, non-striatal (CC-NS)] and has distinct morphology, physiology, and visual responses. Monosynaptic rabies tracing reveals that CC neurons preferentially receive input from higher visual areas, while CS neurons receive more input from structures implicated in top-down modulation of brain states. CS neurons are also more direction-selective and prefer faster stimuli than CC neurons. These differences suggest distinct roles as specialized output channels, with CS neurons integrating information and generating responses more relevant to movement control and CC neurons being more important in visual perception. Copyright © 2015 Elsevier Inc. All rights reserved.

Otolith and Vertical Canal Contributions to Dynamic Postural Control

NASA Technical Reports Server (NTRS)

Black, F. Owen

1999-01-01

The objective of this project is to determine: 1) how do normal subjects adjust postural movements in response to changing or altered otolith input, for example, due to aging? and 2) how do patients adapt postural control after altered unilateral or bilateral vestibular sensory inputs such as ablative inner ear surgery or ototoxicity, respectively? The following hypotheses are under investigation: 1) selective alteration of otolith input or abnormalities of otolith receptor function will result in distinctive spatial, frequency, and temporal patterns of head movements and body postural sway dynamics. 2) subjects with reduced, altered, or absent vertical semicircular canal receptor sensitivity but normal otolith receptor function or vice versa, should show predictable alterations of body and head movement strategies essential for the control of postural sway and movement. The effect of altered postural movement control upon compensation and/or adaptation will be determined. These experiments provide data for the development of computational models of postural control in normals, vestibular deficient subjects and normal humans exposed to unusual force environments, including orbital space flight.

Heterogeneous firing responses predict diverse couplings to presynaptic activity in mice layer V pyramidal neurons

PubMed Central

2017-01-01

In this study, we present a theoretical framework combining experimental characterizations and analytical calculus to capture the firing rate input-output properties of single neurons in the fluctuation-driven regime. Our framework consists of a two-step procedure to treat independently how the dendritic input translates into somatic fluctuation variables, and how the latter determine action potential firing. We use this framework to investigate the functional impact of the heterogeneity in firing responses found experimentally in young mice layer V pyramidal cells. We first design and calibrate in vitro a simplified morphological model of layer V pyramidal neurons with a dendritic tree following Rall's branching rule. Then, we propose an analytical derivation for the membrane potential fluctuations at the soma as a function of the properties of the synaptic input in dendrites. This mathematical description allows us to easily emulate various forms of synaptic input: either balanced, unbalanced, synchronized, purely proximal or purely distal synaptic activity. We find that those different forms of dendritic input activity lead to various impact on the somatic membrane potential fluctuations properties, thus raising the possibility that individual neurons will differentially couple to specific forms of activity as a result of their different firing response. We indeed found such a heterogeneous coupling between synaptic input and firing response for all types of presynaptic activity. This heterogeneity can be explained by different levels of cellular excitability in the case of the balanced, unbalanced, synchronized and purely distal activity. A notable exception appears for proximal dendritic inputs: increasing the input level can either promote firing response in some cells, or suppress it in some other cells whatever their individual excitability. This behavior can be explained by different sensitivities to the speed of the fluctuations, which was previously associated to different levels of sodium channel inactivation and density. Because local network connectivity rather targets proximal dendrites, our results suggest that this aspect of biophysical heterogeneity might be relevant to neocortical processing by controlling how individual neurons couple to local network activity. PMID:28410418

Correlation between discharge timings of pairs of motor units reveals the presence but not the proportion of common synaptic input to motor neurons

PubMed Central

Negro, Francesco; Farina, Dario

2017-01-01

We investigated whether correlation measures derived from pairs of motor unit (MU) spike trains are reliable indicators of the degree of common synaptic input to motor neurons. Several 50-s isometric contractions of the biceps brachii muscle were performed at different target forces ranging from 10 to 30% of the maximal voluntary contraction relying on force feedback. Forty-eight pairs of MUs were examined at various force levels. Motor unit synchrony was assessed by cross-correlation analysis using three indexes: the output correlation as the peak of the cross-histogram (ρ) and the number of synchronous spikes per second (CIS) and per trigger (E). Individual analysis of MU pairs revealed that ρ, CIS, and E were most often positively associated with discharge rate (87, 85, and 76% of the MU pairs, respectively) and negatively with interspike interval variability (69, 65, and 62% of the MU pairs, respectively). Moreover, the behavior of synchronization indexes with discharge rate (and interspike interval variability) varied greatly among the MU pairs. These results were consistent with theoretical predictions, which showed that the output correlation between pairs of spike trains depends on the statistics of the input current and motor neuron intrinsic properties that differ for different motor neuron pairs. In conclusion, the synchronization between MU firing trains is necessarily caused by the (functional) common input to motor neurons, but it is not possible to infer the degree of shared common input to a pair of motor neurons on the basis of correlation measures of their output spike trains. NEW & NOTEWORTHY The strength of correlation between output spike trains is only poorly associated with the degree of common input to the population of motor neurons. The synchronization between motor unit firing trains is necessarily caused by the (functional) common input to motor neurons, but it is not possible to infer the degree of shared common input to a pair of motor neurons on the basis of correlation measures of their output spike trains. PMID:28100652

OCLC-MARC Tape Processing: A Functional Analysis.

ERIC Educational Resources Information Center

Miller, Bruce Cummings

1984-01-01

Analyzes structure of, and data in, the OCLC-MARC record in the form delivered via OCLC's Tape Subscription Service, and outlines important processing functions involved: "unreadable tapes," duplicate records and deduping, match processing, choice processing, locations processing, "automatic" and "input" stamps,…

Spatiotemporal coding of inputs for a system of globally coupled phase oscillators

NASA Astrophysics Data System (ADS)

Wordsworth, John; Ashwin, Peter

2008-12-01

We investigate the spatiotemporal coding of low amplitude inputs to a simple system of globally coupled phase oscillators with coupling function g(ϕ)=-sin(ϕ+α)+rsin(2ϕ+β) that has robust heteroclinic cycles (slow switching between cluster states). The inputs correspond to detuning of the oscillators. It was recently noted that globally coupled phase oscillators can encode their frequencies in the form of spatiotemporal codes of a sequence of cluster states [P. Ashwin, G. Orosz, J. Wordsworth, and S. Townley, SIAM J. Appl. Dyn. Syst. 6, 728 (2007)]. Concentrating on the case of N=5 oscillators we show in detail how the spatiotemporal coding can be used to resolve all of the information that relates the individual inputs to each other, providing that a long enough time series is considered. We investigate robustness to the addition of noise and find a remarkable stability, especially of the temporal coding, to the addition of noise even for noise of a comparable magnitude to the inputs.

Homeostatic plasticity shapes cell-type-specific wiring in the retina

PubMed Central

Tien, Nai-Wen; Soto, Florentina; Kerschensteiner, Daniel

2017-01-01

SUMMARY Convergent input from different presynaptic partners shapes the responses of postsynaptic neurons. Whether developing postsynaptic neurons establish connections with each presynaptic partner independently, or balance inputs to attain specific responses is unclear. Retinal ganglion cells (RGCs) receive convergent input from bipolar cell types with different contrast responses and temporal tuning. Here, using optogenetic activation and pharmacogenetic silencing, we found that type 6 bipolar cells (B6) dominate excitatory input to ONα-RGCs. We generated mice in which B6 cells were selectively removed from developing circuits (B6-DTA). In B6-DTA mice, ONα-RGCs adjusted connectivity with other bipolar cells in a cell-type-specific manner. They recruited new partners, increased synapses with some existing partners, and maintained constant input from others. Patch clamp recordings revealed that anatomical rewiring precisely preserved contrast- and temporal frequency response functions of ONα-RGCs, indicating that homeostatic plasticity shapes cell-type-specific wiring in the developing retina to stabilize visual information sent to the brain. PMID:28457596

Functional correlates of the lateral and medial entorhinal cortex: objects, path integration and local-global reference frames.

PubMed

Knierim, James J; Neunuebel, Joshua P; Deshmukh, Sachin S

2014-02-05

The hippocampus receives its major cortical input from the medial entorhinal cortex (MEC) and the lateral entorhinal cortex (LEC). It is commonly believed that the MEC provides spatial input to the hippocampus, whereas the LEC provides non-spatial input. We review new data which suggest that this simple dichotomy between 'where' versus 'what' needs revision. We propose a refinement of this model, which is more complex than the simple spatial-non-spatial dichotomy. MEC is proposed to be involved in path integration computations based on a global frame of reference, primarily using internally generated, self-motion cues and external input about environmental boundaries and scenes; it provides the hippocampus with a coordinate system that underlies the spatial context of an experience. LEC is proposed to process information about individual items and locations based on a local frame of reference, primarily using external sensory input; it provides the hippocampus with information about the content of an experience.

Neural network system for purposeful behavior based on foveal visual preprocessor

NASA Astrophysics Data System (ADS)

Golovan, Alexander V.; Shevtsova, Natalia A.; Klepatch, Arkadi A.

1996-10-01

Biologically plausible model of the system with an adaptive behavior in a priori environment and resistant to impairment has been developed. The system consists of input, learning, and output subsystems. The first subsystems classifies input patterns presented as n-dimensional vectors in accordance with some associative rule. The second one being a neural network determines adaptive responses of the system to input patterns. Arranged neural groups coding possible input patterns and appropriate output responses are formed during learning by means of negative reinforcement. Output subsystem maps a neural network activity into the system behavior in the environment. The system developed has been studied by computer simulation imitating a collision-free motion of a mobile robot. After some learning period the system 'moves' along a road without collisions. It is shown that in spite of impairment of some neural network elements the system functions reliably after relearning. Foveal visual preprocessor model developed earlier has been tested to form a kind of visual input to the system.

Functional correlates of the lateral and medial entorhinal cortex: objects, path integration and local–global reference frames

PubMed Central

Knierim, James J.; Neunuebel, Joshua P.; Deshmukh, Sachin S.

2014-01-01

The hippocampus receives its major cortical input from the medial entorhinal cortex (MEC) and the lateral entorhinal cortex (LEC). It is commonly believed that the MEC provides spatial input to the hippocampus, whereas the LEC provides non-spatial input. We review new data which suggest that this simple dichotomy between ‘where’ versus ‘what’ needs revision. We propose a refinement of this model, which is more complex than the simple spatial–non-spatial dichotomy. MEC is proposed to be involved in path integration computations based on a global frame of reference, primarily using internally generated, self-motion cues and external input about environmental boundaries and scenes; it provides the hippocampus with a coordinate system that underlies the spatial context of an experience. LEC is proposed to process information about individual items and locations based on a local frame of reference, primarily using external sensory input; it provides the hippocampus with information about the content of an experience. PMID:24366146

Joint analysis of input and parametric uncertainties in watershed water quality modeling: A formal Bayesian approach

NASA Astrophysics Data System (ADS)

Han, Feng; Zheng, Yi

2018-06-01

Significant Input uncertainty is a major source of error in watershed water quality (WWQ) modeling. It remains challenging to address the input uncertainty in a rigorous Bayesian framework. This study develops the Bayesian Analysis of Input and Parametric Uncertainties (BAIPU), an approach for the joint analysis of input and parametric uncertainties through a tight coupling of Markov Chain Monte Carlo (MCMC) analysis and Bayesian Model Averaging (BMA). The formal likelihood function for this approach is derived considering a lag-1 autocorrelated, heteroscedastic, and Skew Exponential Power (SEP) distributed error model. A series of numerical experiments were performed based on a synthetic nitrate pollution case and on a real study case in the Newport Bay Watershed, California. The Soil and Water Assessment Tool (SWAT) and Differential Evolution Adaptive Metropolis (DREAM(ZS)) were used as the representative WWQ model and MCMC algorithm, respectively. The major findings include the following: (1) the BAIPU can be implemented and used to appropriately identify the uncertain parameters and characterize the predictive uncertainty; (2) the compensation effect between the input and parametric uncertainties can seriously mislead the modeling based management decisions, if the input uncertainty is not explicitly accounted for; (3) the BAIPU accounts for the interaction between the input and parametric uncertainties and therefore provides more accurate calibration and uncertainty results than a sequential analysis of the uncertainties; and (4) the BAIPU quantifies the credibility of different input assumptions on a statistical basis and can be implemented as an effective inverse modeling approach to the joint inference of parameters and inputs.

Optimal discrete-time LQR problems for parabolic systems with unbounded input: Approximation and convergence

NASA Technical Reports Server (NTRS)

Rosen, I. G.

1988-01-01

An abstract approximation and convergence theory for the closed-loop solution of discrete-time linear-quadratic regulator problems for parabolic systems with unbounded input is developed. Under relatively mild stabilizability and detectability assumptions, functional analytic, operator techniques are used to demonstrate the norm convergence of Galerkin-based approximations to the optimal feedback control gains. The application of the general theory to a class of abstract boundary control systems is considered. Two examples, one involving the Neumann boundary control of a one-dimensional heat equation, and the other, the vibration control of a cantilevered viscoelastic beam via shear input at the free end, are discussed.

MIMO system identification using frequency response data

NASA Technical Reports Server (NTRS)

Medina, Enrique A.; Irwin, R. D.; Mitchell, Jerrel R.; Bukley, Angelia P.

1992-01-01

A solution to the problem of obtaining a multi-input, multi-output statespace model of a system from its individual input/output frequency responses is presented. The Residue Identification Algorithm (RID) identifies the system poles from a transfer function model of the determinant of the frequency response data matrix. Next, the residue matrices of the modes are computed guaranteeing that each input/output frequency response is fitted in the least squares sense. Finally, a realization of the system is computed. Results of the application of RID to experimental frequency responses of a large space structure ground test facility are presented and compared to those obtained via the Eigensystem Realization Algorithm.

Explicit least squares system parameter identification for exact differential input/output models

NASA Technical Reports Server (NTRS)

Pearson, A. E.

1993-01-01

The equation error for a class of systems modeled by input/output differential operator equations has the potential to be integrated exactly, given the input/output data on a finite time interval, thereby opening up the possibility of using an explicit least squares estimation technique for system parameter identification. The paper delineates the class of models for which this is possible and shows how the explicit least squares cost function can be obtained in a way that obviates dealing with unknown initial and boundary conditions. The approach is illustrated by two examples: a second order chemical kinetics model and a third order system of Lorenz equations.

Passive dendrites enable single neurons to compute linearly non-separable functions.

PubMed

Cazé, Romain Daniel; Humphries, Mark; Gutkin, Boris

2013-01-01

Local supra-linear summation of excitatory inputs occurring in pyramidal cell dendrites, the so-called dendritic spikes, results in independent spiking dendritic sub-units, which turn pyramidal neurons into two-layer neural networks capable of computing linearly non-separable functions, such as the exclusive OR. Other neuron classes, such as interneurons, may possess only a few independent dendritic sub-units, or only passive dendrites where input summation is purely sub-linear, and where dendritic sub-units are only saturating. To determine if such neurons can also compute linearly non-separable functions, we enumerate, for a given parameter range, the Boolean functions implementable by a binary neuron model with a linear sub-unit and either a single spiking or a saturating dendritic sub-unit. We then analytically generalize these numerical results to an arbitrary number of non-linear sub-units. First, we show that a single non-linear dendritic sub-unit, in addition to the somatic non-linearity, is sufficient to compute linearly non-separable functions. Second, we analytically prove that, with a sufficient number of saturating dendritic sub-units, a neuron can compute all functions computable with purely excitatory inputs. Third, we show that these linearly non-separable functions can be implemented with at least two strategies: one where a dendritic sub-unit is sufficient to trigger a somatic spike; another where somatic spiking requires the cooperation of multiple dendritic sub-units. We formally prove that implementing the latter architecture is possible with both types of dendritic sub-units whereas the former is only possible with spiking dendrites. Finally, we show how linearly non-separable functions can be computed by a generic two-compartment biophysical model and a realistic neuron model of the cerebellar stellate cell interneuron. Taken together our results demonstrate that passive dendrites are sufficient to enable neurons to compute linearly non-separable functions.

Passive Dendrites Enable Single Neurons to Compute Linearly Non-separable Functions

PubMed Central

Cazé, Romain Daniel; Humphries, Mark; Gutkin, Boris

2013-01-01

Local supra-linear summation of excitatory inputs occurring in pyramidal cell dendrites, the so-called dendritic spikes, results in independent spiking dendritic sub-units, which turn pyramidal neurons into two-layer neural networks capable of computing linearly non-separable functions, such as the exclusive OR. Other neuron classes, such as interneurons, may possess only a few independent dendritic sub-units, or only passive dendrites where input summation is purely sub-linear, and where dendritic sub-units are only saturating. To determine if such neurons can also compute linearly non-separable functions, we enumerate, for a given parameter range, the Boolean functions implementable by a binary neuron model with a linear sub-unit and either a single spiking or a saturating dendritic sub-unit. We then analytically generalize these numerical results to an arbitrary number of non-linear sub-units. First, we show that a single non-linear dendritic sub-unit, in addition to the somatic non-linearity, is sufficient to compute linearly non-separable functions. Second, we analytically prove that, with a sufficient number of saturating dendritic sub-units, a neuron can compute all functions computable with purely excitatory inputs. Third, we show that these linearly non-separable functions can be implemented with at least two strategies: one where a dendritic sub-unit is sufficient to trigger a somatic spike; another where somatic spiking requires the cooperation of multiple dendritic sub-units. We formally prove that implementing the latter architecture is possible with both types of dendritic sub-units whereas the former is only possible with spiking dendrites. Finally, we show how linearly non-separable functions can be computed by a generic two-compartment biophysical model and a realistic neuron model of the cerebellar stellate cell interneuron. Taken together our results demonstrate that passive dendrites are sufficient to enable neurons to compute linearly non-separable functions. PMID:23468600

Multiple-frequency acoustic wave devices for chemical sensing and materials characterization in both gas and liquid phase

DOEpatents

Martin, S.J.; Ricco, A.J.

1993-08-10

A chemical or intrinsic physical property sensor is described comprising: (a) a substrate; (b) an interaction region of said substrate where the presence of a chemical or physical stimulus causes a detectable change in the velocity and/or an attenuation of an acoustic wave traversing said region; and (c) a plurality of paired input and output interdigitated electrodes patterned on the surface of said substrate where each of said paired electrodes has a distinct periodicity, where each of said paired electrodes is comprised of an input and an output electrode; (d) an input signal generation means for transmitting an input signal having a distinct frequency to a specified input interdigitated electrode of said plurality so that each input electrode receives a unique input signal, whereby said electrode responds to said input signal by generating an acoustic wave of a specified frequency, thus, said plurality responds by generating a plurality of acoustic waves of different frequencies; (e) an output signal receiving means for determining an acoustic wave velocity and an amplitude of said acoustic waves at several frequencies after said waves transverses said interaction region and comparing these values to an input acoustic wave velocity and an input acoustic wave amplitude to produce values for perturbations in acoustic wave velocities and for acoustic wave attenuation as a function of frequency, where said output receiving means is individually coupled to each of said output interdigitated electrode; (f) a computer means for analyzing a data stream comprising information from said output receiving means and from said input signal generation means to differentiate a specified response due to a perturbation from a subsequent specified response due to a subsequent perturbation to determine the chemical or intrinsic physical properties desired.

Dynamics of infant cortical auditory evoked potentials (CAEPs) for tone and speech tokens.

PubMed

Cone, Barbara; Whitaker, Richard

2013-07-01

Cortical auditory evoked potentials (CAEPs) to tones and speech sounds were obtained in infants to: (1) further knowledge of auditory development above the level of the brainstem during the first year of life; (2) establish CAEP input-output functions for tonal and speech stimuli as a function of stimulus level and (3) elaborate the data-base that establishes CAEP in infants tested while awake using clinically relevant stimuli, thus providing methodology that would have translation to pediatric audiological assessment. Hypotheses concerning CAEP development were that the latency and amplitude input-output functions would reflect immaturity in encoding stimulus level. In a second experiment, infants were tested with the same stimuli used to evoke the CAEPs. Thresholds for these stimuli were determined using observer-based psychophysical techniques. The hypothesis was that the behavioral thresholds would be correlated with CAEP input-output functions because of shared cortical response areas known to be active in sound detection. 36 infants, between the ages of 4 and 12 months (mean=8 months, s.d.=1.8 months) and 9 young adults (mean age 21 years) with normal hearing were tested. First, CAEPs amplitude and latency input-output functions were obtained for 4 tone bursts and 7 speech tokens. The tone bursts stimuli were 50 ms tokens of pure tones at 0.5, 1.0, 2.0 and 4.0 kHz. The speech sound tokens, /a/, /i/, /o/, /u/, /m/, /s/, and /∫/, were created from natural speech samples and were also 50 ms in duration. CAEPs were obtained for tone burst and speech token stimuli at 10 dB level decrements in descending order from 70 dB SPL. All CAEP tests were completed while the infants were awake and engaged in quiet play. For the second experiment, observer-based psychophysical methods were used to establish perceptual threshold for the same speech sound and tone tokens. Infant CAEP component latencies were prolonged by 100-150 ms in comparison to adults. CAEP latency-intensity input output functions were steeper in infants compared to adults. CAEP amplitude growth functions with respect to stimulus SPL are adult-like at this age, particularly for the earliest component, P1-N1. Infant perceptual thresholds were elevated with respect to those found in adults. Furthermore, perceptual thresholds were higher, on average, than levels at which CAEPs could be obtained. When CAEP amplitudes were plotted with respect to perceptual threshold (dB SL), the infant CAEP amplitude growth slopes were steeper than in adults. Although CAEP latencies indicate immaturity in neural transmission at the level of the cortex, amplitude growth with respect to stimulus SPL is adult-like at this age, particularly for the earliest component, P1-N1. The latency and amplitude input-output functions may provide additional information as to how infants perceive stimulus level. The reasons for the discrepancy between electrophysiologic and perceptual threshold may be due to immaturity in perceptual temporal resolution abilities and the broad-band listening strategy employed by infants. The findings from the current study can be translated to the clinical setting. It is possible to use tonal or speech sound tokens to evoke CAEPs in an awake, passively alert infant, and thus determine whether these sounds activate the auditory cortex. This could be beneficial in the verification of hearing aid or cochlear implant benefit. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Homeostasis in a feed forward loop gene regulatory motif.

PubMed

Antoneli, Fernando; Golubitsky, Martin; Stewart, Ian

2018-05-14

The internal state of a cell is affected by inputs from the extra-cellular environment such as external temperature. If some output, such as the concentration of a target protein, remains approximately constant as inputs vary, the system exhibits homeostasis. Special sub-networks called motifs are unusually common in gene regulatory networks (GRNs), suggesting that they may have a significant biological function. Potentially, one such function is homeostasis. In support of this hypothesis, we show that the feed-forward loop GRN produces homeostasis. Here the inputs are subsumed into a single parameter that affects only the first node in the motif, and the output is the concentration of a target protein. The analysis uses the notion of infinitesimal homeostasis, which occurs when the input-output map has a critical point (zero derivative). In model equations such points can be located using implicit differentiation. If the second derivative of the input-output map also vanishes, the critical point is a chair: the output rises roughly linearly, then flattens out (the homeostasis region or plateau), and then starts to rise again. Chair points are a common cause of homeostasis. In more complicated equations or networks, numerical exploration would have to augment analysis. Thus, in terms of finding chairs, this paper presents a proof of concept. We apply this method to a standard family of differential equations modeling the feed-forward loop GRN, and deduce that chair points occur. This function determines the production of a particular mRNA and the resulting chair points are found analytically. The same method can potentially be used to find homeostasis regions in other GRNs. In the discussion and conclusion section, we also discuss why homeostasis in the motif may persist even when the rest of the network is taken into account. Copyright © 2018 Elsevier Ltd. All rights reserved.

Numerically accurate computational techniques for optimal estimator analyses of multi-parameter models

NASA Astrophysics Data System (ADS)

Berger, Lukas; Kleinheinz, Konstantin; Attili, Antonio; Bisetti, Fabrizio; Pitsch, Heinz; Mueller, Michael E.

2018-05-01

Modelling unclosed terms in partial differential equations typically involves two steps: First, a set of known quantities needs to be specified as input parameters for a model, and second, a specific functional form needs to be defined to model the unclosed terms by the input parameters. Both steps involve a certain modelling error, with the former known as the irreducible error and the latter referred to as the functional error. Typically, only the total modelling error, which is the sum of functional and irreducible error, is assessed, but the concept of the optimal estimator enables the separate analysis of the total and the irreducible errors, yielding a systematic modelling error decomposition. In this work, attention is paid to the techniques themselves required for the practical computation of irreducible errors. Typically, histograms are used for optimal estimator analyses, but this technique is found to add a non-negligible spurious contribution to the irreducible error if models with multiple input parameters are assessed. Thus, the error decomposition of an optimal estimator analysis becomes inaccurate, and misleading conclusions concerning modelling errors may be drawn. In this work, numerically accurate techniques for optimal estimator analyses are identified and a suitable evaluation of irreducible errors is presented. Four different computational techniques are considered: a histogram technique, artificial neural networks, multivariate adaptive regression splines, and an additive model based on a kernel method. For multiple input parameter models, only artificial neural networks and multivariate adaptive regression splines are found to yield satisfactorily accurate results. Beyond a certain number of input parameters, the assessment of models in an optimal estimator analysis even becomes practically infeasible if histograms are used. The optimal estimator analysis in this paper is applied to modelling the filtered soot intermittency in large eddy simulations using a dataset of a direct numerical simulation of a non-premixed sooting turbulent flame.

Synthesis of feedback systems with large plant ignorance for prescribed time domain tolerances

NASA Technical Reports Server (NTRS)

Horowitz, I. M.; Sidi, M.

1971-01-01

There is given a minimum-phase plant transfer function, with prescribed bounds on its parameter values. The plant is imbedded in a two-degree-of freedom feedback system, which is to be designed such that the system time response to a deterministic input lies within specified boundaries. Subject to the above, the design should be such as to minimize the effect of sensor noise at the input to the plant. This report presents a design procedure for this purpose, based on frequency response concepts. The time-domain tolerances are translated into equivalent frequency response tolerances. The latter lead to bounds on the loop transmission function in the form of continuous curves on the Nichols chart. The properties of the loop transmission function which satisfy these bounds with minimum effect of sensor noise, are derived.

Properties of Zero-Free Transfer Function Matrices

NASA Astrophysics Data System (ADS)

D. O. Anderson, Brian; Deistler, Manfred

Transfer functions of linear, time-invariant finite-dimensional systems with more outputs than inputs, as arise in factor analysis (for example in econometrics), have, for state-variable descriptions with generic entries in the relevant matrices, no finite zeros. This paper gives a number of characterizations of such systems (and indeed square discrete-time systems with no zeros), using state-variable, impulse response, and matrix-fraction descriptions. Key properties include the ability to recover the input values at any time from a bounded interval of output values, without any knowledge of an initial state, and an ability to verify the no-zero property in terms of a property of the impulse response coefficient matrices. Results are particularized to cases where the transfer function matrix in question may or may not have a zero at infinity or a zero at zero.

Ergonomic problems regarding the interactive touch input via screens in onboard and ground-based flight control

NASA Technical Reports Server (NTRS)

Holzhausen, K. P.; Gaertner, K. P.

1985-01-01

A significant problem concerning the integration of display and switching functions is related to the fact that numerous informative data which have to be processed by man must be read from only a few display devices. A satisfactory ergonomic design of integrated display devices and keyboards is in many cases difficult, because not all functions which can be displayed and selected are simultaneously available. A technical solution which provides an integration of display and functional elements on the basis of the highest flexibility is obtained by using a cathode ray tube with a touch-sensitive screen. The employment of an integrated data input/output system is demonstrated for the cases of onboard and ground-based flight control. Ergonomic studies conducted to investigate the suitability of an employment of touch-sensitive screens are also discussed.

A new approach of optimal control for a class of continuous-time chaotic systems by an online ADP algorithm

NASA Astrophysics Data System (ADS)

Song, Rui-Zhuo; Xiao, Wen-Dong; Wei, Qing-Lai

2014-05-01

We develop an online adaptive dynamic programming (ADP) based optimal control scheme for continuous-time chaotic systems. The idea is to use the ADP algorithm to obtain the optimal control input that makes the performance index function reach an optimum. The expression of the performance index function for the chaotic system is first presented. The online ADP algorithm is presented to achieve optimal control. In the ADP structure, neural networks are used to construct a critic network and an action network, which can obtain an approximate performance index function and the control input, respectively. It is proven that the critic parameter error dynamics and the closed-loop chaotic systems are uniformly ultimately bounded exponentially. Our simulation results illustrate the performance of the established optimal control method.

Visual Functions of the Thalamus

PubMed Central

Usrey, W. Martin; Alitto, Henry J.

2017-01-01

The thalamus is the heavily interconnected partner of the neocortex. All areas of the neocortex receive afferent input from and send efferent projections to specific thalamic nuclei. Through these connections, the thalamus serves to provide the cortex with sensory input, and to facilitate interareal cortical communication and motor and cognitive functions. In the visual system, the lateral geniculate nucleus (LGN) of the dorsal thalamus is the gateway through which visual information reaches the cerebral cortex. Visual processing in the LGN includes spatial and temporal influences on visual signals that serve to adjust response gain, transform the temporal structure of retinal activity patterns, and increase the signal-to-noise ratio of the retinal signal while preserving its basic content. This review examines recent advances in our understanding of LGN function and circuit organization and places these findings in a historical context. PMID:28217740

Inspection Methods in Programming.

DTIC Science & Technology

1981-06-01

Counting is a a specialization of Iterative-generation in which the generating function is Oneplus ) Waters’ second category of plan building method...is Oneplus and the initial input is 1. 0 I 180 CHAPTER NINE -ta a acio f igr9-.IeaieGnrtoPln 7 -7 STEADY STATE PLANS 181 TemporalPlan counting...specializalion iterative-generation roles .action(afu nction) ,tail(counting) conslraints .action.op = oneplus A .action.input = 1 The lItcrative-application

The Application of HOS to PLRS

DTIC Science & Technology

1977-11-01

of "older," more established fields, like philosophy or mathematics , and more recently, linguistics. But when working with large systems, there is...property of natural language, which is eliminated by using formal, mathematical specifications. 3.4.2.2 Network Management Processing: The Network...the format: y = f(x) That is, we must immediately begin thinking of the problem in terms of mathematical functions (mappings) acting on some input(s

The subcellular distribution of T-type Ca2+ channels in interneurons of the lateral geniculate nucleus.

PubMed

Allken, Vaneeda; Chepkoech, Joy-Loi; Einevoll, Gaute T; Halnes, Geir

2014-01-01

Inhibitory interneurons (INs) in the lateral geniculate nucleus (LGN) provide both axonal and dendritic GABA output to thalamocortical relay cells (TCs). Distal parts of the IN dendrites often enter into complex arrangements known as triadic synapses, where the IN dendrite plays a dual role as postsynaptic to retinal input and presynaptic to TC dendrites. Dendritic GABA release can be triggered by retinal input, in a highly localized process that is functionally isolated from the soma, but can also be triggered by somatically elicited Ca(2+)-spikes and possibly by backpropagating action potentials. Ca(2+)-spikes in INs are predominantly mediated by T-type Ca(2+)-channels (T-channels). Due to the complex nature of the dendritic signalling, the function of the IN is likely to depend critically on how T-channels are distributed over the somatodendritic membrane (T-distribution). To study the relationship between the T-distribution and several IN response properties, we here run a series of simulations where we vary the T-distribution in a multicompartmental IN model with a realistic morphology. We find that the somatic response to somatic current injection is facilitated by a high T-channel density in the soma-region. Conversely, a high T-channel density in the distal dendritic region is found to facilitate dendritic signalling in both the outward direction (increases the response in distal dendrites to somatic input) and the inward direction (the soma responds stronger to distal synaptic input). The real T-distribution is likely to reflect a compromise between several neural functions, involving somatic response patterns and dendritic signalling.

The Subcellular Distribution of T-Type Ca2+ Channels in Interneurons of the Lateral Geniculate Nucleus

PubMed Central

Allken, Vaneeda; Chepkoech, Joy-Loi; Einevoll, Gaute T.; Halnes, Geir

2014-01-01

Inhibitory interneurons (INs) in the lateral geniculate nucleus (LGN) provide both axonal and dendritic GABA output to thalamocortical relay cells (TCs). Distal parts of the IN dendrites often enter into complex arrangements known as triadic synapses, where the IN dendrite plays a dual role as postsynaptic to retinal input and presynaptic to TC dendrites. Dendritic GABA release can be triggered by retinal input, in a highly localized process that is functionally isolated from the soma, but can also be triggered by somatically elicited Ca2+-spikes and possibly by backpropagating action potentials. Ca2+-spikes in INs are predominantly mediated by T-type Ca2+-channels (T-channels). Due to the complex nature of the dendritic signalling, the function of the IN is likely to depend critically on how T-channels are distributed over the somatodendritic membrane (T-distribution). To study the relationship between the T-distribution and several IN response properties, we here run a series of simulations where we vary the T-distribution in a multicompartmental IN model with a realistic morphology. We find that the somatic response to somatic current injection is facilitated by a high T-channel density in the soma-region. Conversely, a high T-channel density in the distal dendritic region is found to facilitate dendritic signalling in both the outward direction (increases the response in distal dendrites to somatic input) and the inward direction (the soma responds stronger to distal synaptic input). The real T-distribution is likely to reflect a compromise between several neural functions, involving somatic response patterns and dendritic signalling. PMID:25268996

InterEvDock2: an expanded server for protein docking using evolutionary and biological information from homology models and multimeric inputs.

PubMed

Quignot, Chloé; Rey, Julien; Yu, Jinchao; Tufféry, Pierre; Guerois, Raphaël; Andreani, Jessica

2018-05-08

Computational protein docking is a powerful strategy to predict structures of protein-protein interactions and provides crucial insights for the functional characterization of macromolecular cross-talks. We previously developed InterEvDock, a server for ab initio protein docking based on rigid-body sampling followed by consensus scoring using physics-based and statistical potentials, including the InterEvScore function specifically developed to incorporate co-evolutionary information in docking. InterEvDock2 is a major evolution of InterEvDock which allows users to submit input sequences - not only structures - and multimeric inputs and to specify constraints for the pairwise docking process based on previous knowledge about the interaction. For this purpose, we added modules in InterEvDock2 for automatic template search and comparative modeling of the input proteins. The InterEvDock2 pipeline was benchmarked on 812 complexes for which unbound homology models of the two partners and co-evolutionary information are available in the PPI4DOCK database. InterEvDock2 identified a correct model among the top 10 consensus in 29% of these cases (compared to 15-24% for individual scoring functions) and at least one correct interface residue among 10 predicted in 91% of these cases. InterEvDock2 is thus a unique protein docking server, designed to be useful for the experimental biology community. The InterEvDock2 web interface is available at http://bioserv.rpbs.univ-paris-diderot.fr/services/InterEvDock2/.

Distributed approximating functional fit of the H{sub 3} {ital ab initio} potential-energy data of Liu and Siegbahn

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

Frishman, A.; Hoffman, D.K.; Kouri, D.J.

1997-07-01

We report a distributed approximating functional (DAF) fit of the {ital ab initio} potential-energy data of Liu [J. Chem. Phys. {bold 58}, 1925 (1973)] and Siegbahn and Liu [{ital ibid}. {bold 68}, 2457 (1978)]. The DAF-fit procedure is based on a variational principle, and is systematic and general. Only two adjustable parameters occur in the DAF leading to a fit which is both accurate (to the level inherent in the input data; RMS error of 0.2765 kcal/mol) and smooth ({open_quotes}well-tempered,{close_quotes} in DAF terminology). In addition, the LSTH surface of Truhlar and Horowitz based on this same data [J. Chem. Phys.more » {bold 68}, 2466 (1978)] is itself approximated using only the values of the LSTH surface on the same grid coordinate points as the {ital ab initio} data, and the same DAF parameters. The purpose of this exercise is to demonstrate that the DAF delivers a well-tempered approximation to a known function that closely mimics the true potential-energy surface. As is to be expected, since there is only roundoff error present in the LSTH input data, even more significant figures of fitting accuracy are obtained. The RMS error of the DAF fit, of the LSTH surface at the input points, is 0.0274 kcal/mol, and a smooth fit, accurate to better than 1cm{sup {minus}1}, can be obtained using more than 287 input data points. {copyright} {ital 1997 American Institute of Physics.}« less

Input transformation by dendritic spines of pyramidal neurons

PubMed Central

Araya, Roberto

2014-01-01

In the mammalian brain, most inputs received by a neuron are formed on the dendritic tree. In the neocortex, the dendrites of pyramidal neurons are covered by thousands of tiny protrusions known as dendritic spines, which are the major recipient sites for excitatory synaptic information in the brain. Their peculiar morphology, with a small head connected to the dendritic shaft by a slender neck, has inspired decades of theoretical and more recently experimental work in an attempt to understand how excitatory synaptic inputs are processed, stored and integrated in pyramidal neurons. Advances in electrophysiological, optical and genetic tools are now enabling us to unravel the biophysical and molecular mechanisms controlling spine function in health and disease. Here I highlight relevant findings, challenges and hypotheses on spine function, with an emphasis on the electrical properties of spines and on how these affect the storage and integration of excitatory synaptic inputs in pyramidal neurons. In an attempt to make sense of the published data, I propose that the raison d'etre for dendritic spines lies in their ability to undergo activity-dependent structural and molecular changes that can modify synaptic strength, and hence alter the gain of the linearly integrated sub-threshold depolarizations in pyramidal neuron dendrites before the generation of a dendritic spike. PMID:25520626

Uncertainty in Measurement: Procedures for Determining Uncertainty With Application to Clinical Laboratory Calculations.

PubMed

Frenkel, Robert B; Farrance, Ian

2018-01-01

The "Guide to the Expression of Uncertainty in Measurement" (GUM) is the foundational document of metrology. Its recommendations apply to all areas of metrology including metrology associated with the biomedical sciences. When the output of a measurement process depends on the measurement of several inputs through a measurement equation or functional relationship, the propagation of uncertainties in the inputs to the uncertainty in the output demands a level of understanding of the differential calculus. This review is intended as an elementary guide to the differential calculus and its application to uncertainty in measurement. The review is in two parts. In Part I, Section 3, we consider the case of a single input and introduce the concepts of error and uncertainty. Next we discuss, in the following sections in Part I, such notions as derivatives and differentials, and the sensitivity of an output to errors in the input. The derivatives of functions are obtained using very elementary mathematics. The overall purpose of this review, here in Part I and subsequently in Part II, is to present the differential calculus for those in the medical sciences who wish to gain a quick but accurate understanding of the propagation of uncertainties. © 2018 Elsevier Inc. All rights reserved.

Slow feature analysis: unsupervised learning of invariances.

PubMed

Wiskott, Laurenz; Sejnowski, Terrence J

2002-04-01

Invariant features of temporally varying signals are useful for analysis and classification. Slow feature analysis (SFA) is a new method for learning invariant or slowly varying features from a vectorial input signal. It is based on a nonlinear expansion of the input signal and application of principal component analysis to this expanded signal and its time derivative. It is guaranteed to find the optimal solution within a family of functions directly and can learn to extract a large number of decorrelated features, which are ordered by their degree of invariance. SFA can be applied hierarchically to process high-dimensional input signals and extract complex features. SFA is applied first to complex cell tuning properties based on simple cell output, including disparity and motion. Then more complicated input-output functions are learned by repeated application of SFA. Finally, a hierarchical network of SFA modules is presented as a simple model of the visual system. The same unstructured network can learn translation, size, rotation, contrast, or, to a lesser degree, illumination invariance for one-dimensional objects, depending on only the training stimulus. Surprisingly, only a few training objects suffice to achieve good generalization to new objects. The generated representation is suitable for object recognition. Performance degrades if the network is trained to learn multiple invariances simultaneously.

Feasibility study of parallel optical correlation-decoding analysis of lightning

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

Descour, M.R.; Sweatt, W.C.; Elliott, G.R.

The optical correlator described in this report is intended to serve as an attention-focusing processor. The objective is to narrowly bracket the range of a parameter value that characterizes the correlator input. The input is a waveform collected by a satellite-borne receiver. In the correlator, this waveform is simultaneously correlated with an ensemble of ionosphere impulse-response functions, each corresponding to a different total-electron-count (TEC) value. We have found that correlation is an effective method of bracketing the range of TEC values likely to be represented by the input waveform. High accuracy in a computational sense is not required of themore » correlator. Binarization of the impulse-response functions and the input waveforms prior to correlation results in a lower correlation-peak-to-background-fluctuation (signal-to-noise) ratio than the peak that is obtained when all waveforms retain their grayscale values. The results presented in this report were obtained by means of an acousto-optic correlator previously developed at SNL as well as by simulation. An optical-processor architecture optimized for 1D correlation of long waveforms characteristic of this application is described. Discussions of correlator components, such as optics, acousto-optic cells, digital micromirror devices, laser diodes, and VCSELs are included.« less

New generation of hydraulic pedotransfer functions for Europe

PubMed Central

Tóth, B; Weynants, M; Nemes, A; Makó, A; Bilas, G; Tóth, G

2015-01-01

A range of continental-scale soil datasets exists in Europe with different spatial representation and based on different principles. We developed comprehensive pedotransfer functions (PTFs) for applications principally on spatial datasets with continental coverage. The PTF development included the prediction of soil water retention at various matric potentials and prediction of parameters to characterize soil moisture retention and the hydraulic conductivity curve (MRC and HCC) of European soils. We developed PTFs with a hierarchical approach, determined by the input requirements. The PTFs were derived by using three statistical methods: (i) linear regression where there were quantitative input variables, (ii) a regression tree for qualitative, quantitative and mixed types of information and (iii) mean statistics of developer-defined soil groups (class PTF) when only qualitative input parameters were available. Data of the recently established European Hydropedological Data Inventory (EU-HYDI), which holds the most comprehensive geographical and thematic coverage of hydro-pedological data in Europe, were used to train and test the PTFs. The applied modelling techniques and the EU-HYDI allowed the development of hydraulic PTFs that are more reliable and applicable for a greater variety of input parameters than those previously available for Europe. Therefore the new set of PTFs offers tailored advanced tools for a wide range of applications in the continent. PMID:25866465

Adaptive Control via Neural Output Feedback for a Class of Nonlinear Discrete-Time Systems in a Nested Interconnected Form.

PubMed

Li, Dong-Juan; Li, Da-Peng

2017-09-14

In this paper, an adaptive output feedback control is framed for uncertain nonlinear discrete-time systems. The considered systems are a class of multi-input multioutput nonaffine nonlinear systems, and they are in the nested lower triangular form. Furthermore, the unknown dead-zone inputs are nonlinearly embedded into the systems. These properties of the systems will make it very difficult and challenging to construct a stable controller. By introducing a new diffeomorphism coordinate transformation, the controlled system is first transformed into a state-output model. By introducing a group of new variables, an input-output model is finally obtained. Based on the transformed model, the implicit function theorem is used to determine the existence of the ideal controllers and the approximators are employed to approximate the ideal controllers. By using the mean value theorem, the nonaffine functions of systems can become an affine structure but nonaffine terms still exist. The adaptation auxiliary terms are skillfully designed to cancel the effect of the dead-zone input. Based on the Lyapunov difference theorem, the boundedness of all the signals in the closed-loop system can be ensured and the tracking errors are kept in a bounded compact set. The effectiveness of the proposed technique is checked by a simulation study.

Connectivity in the human brain dissociates entropy and complexity of auditory inputs☆

PubMed Central

Nastase, Samuel A.; Iacovella, Vittorio; Davis, Ben; Hasson, Uri

2015-01-01

Complex systems are described according to two central dimensions: (a) the randomness of their output, quantified via entropy; and (b) their complexity, which reflects the organization of a system's generators. Whereas some approaches hold that complexity can be reduced to uncertainty or entropy, an axiom of complexity science is that signals with very high or very low entropy are generated by relatively non-complex systems, while complex systems typically generate outputs with entropy peaking between these two extremes. In understanding their environment, individuals would benefit from coding for both input entropy and complexity; entropy indexes uncertainty and can inform probabilistic coding strategies, whereas complexity reflects a concise and abstract representation of the underlying environmental configuration, which can serve independent purposes, e.g., as a template for generalization and rapid comparisons between environments. Using functional neuroimaging, we demonstrate that, in response to passively processed auditory inputs, functional integration patterns in the human brain track both the entropy and complexity of the auditory signal. Connectivity between several brain regions scaled monotonically with input entropy, suggesting sensitivity to uncertainty, whereas connectivity between other regions tracked entropy in a convex manner consistent with sensitivity to input complexity. These findings suggest that the human brain simultaneously tracks the uncertainty of sensory data and effectively models their environmental generators. PMID:25536493

Catalytic molecular logic devices by DNAzyme displacement.

PubMed

Brown, Carl W; Lakin, Matthew R; Stefanovic, Darko; Graves, Steven W

2014-05-05

Chemical reactions catalyzed by DNAzymes offer a route to programmable modification of biomolecules for therapeutic purposes. To this end, we have developed a new type of catalytic DNA-based logic gates in which DNAzyme catalysis is controlled via toehold-mediated strand displacement reactions. We refer to these as DNAzyme displacement gates. The use of toeholds to guide input binding provides a favorable pathway for input recognition, and the innate catalytic activity of DNAzymes allows amplification of nanomolar input concentrations. We demonstrate detection of arbitrary input sequences by rational introduction of mismatched bases into inhibitor strands. Furthermore, we illustrate the applicability of DNAzyme displacement to compute logic functions involving multiple logic gates. This work will enable sophisticated logical control of a range of biochemical modifications, with applications in pathogen detection and autonomous theranostics. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spatially Distributed Dendritic Resonance Selectively Filters Synaptic Input

PubMed Central

Segev, Idan; Shamma, Shihab

2014-01-01

An important task performed by a neuron is the selection of relevant inputs from among thousands of synapses impinging on the dendritic tree. Synaptic plasticity enables this by strenghtening a subset of synapses that are, presumably, functionally relevant to the neuron. A different selection mechanism exploits the resonance of the dendritic membranes to preferentially filter synaptic inputs based on their temporal rates. A widely held view is that a neuron has one resonant frequency and thus can pass through one rate. Here we demonstrate through mathematical analyses and numerical simulations that dendritic resonance is inevitably a spatially distributed property; and therefore the resonance frequency varies along the dendrites, and thus endows neurons with a powerful spatiotemporal selection mechanism that is sensitive both to the dendritic location and the temporal structure of the incoming synaptic inputs. PMID:25144440

Adaptive noise reduction circuit for a sound reproduction system

NASA Technical Reports Server (NTRS)

Engebretson, A. Maynard (Inventor); O'Connell, Michael P. (Inventor)

1995-01-01

A noise reduction circuit for a hearing aid having an adaptive filter for producing a signal which estimates the noise components present in an input signal. The circuit includes a second filter for receiving the noise-estimating signal and modifying it as a function of a user's preference or as a function of an expected noise environment. The circuit also includes a gain control for adjusting the magnitude of the modified noise-estimating signal, thereby allowing for the adjustment of the magnitude of the circuit response. The circuit also includes a signal combiner for combining the input signal with the adjusted noise-estimating signal to produce a noise reduced output signal.

A radial map of multi-whisker correlation selectivity in the rat barrel cortex

PubMed Central

Estebanez, Luc; Bertherat, Julien; Shulz, Daniel E.; Bourdieu, Laurent; Léger, Jean- François

2016-01-01

In the barrel cortex, several features of single-whisker stimuli are organized in functional maps. The barrel cortex also encodes spatio-temporal correlation patterns of multi-whisker inputs, but so far the cortical mapping of neurons tuned to such input statistics is unknown. Here we report that layer 2/3 of the rat barrel cortex contains an additional functional map based on neuronal tuning to correlated versus uncorrelated multi-whisker stimuli: neuron responses to uncorrelated multi-whisker stimulation are strongest above barrel centres, whereas neuron responses to correlated and anti-correlated multi-whisker stimulation peak above the barrel–septal borders, forming rings of multi-whisker synchrony-preferring cells. PMID:27869114

A radial map of multi-whisker correlation selectivity in the rat barrel cortex.

PubMed

Estebanez, Luc; Bertherat, Julien; Shulz, Daniel E; Bourdieu, Laurent; Léger, Jean-François

2016-11-21

In the barrel cortex, several features of single-whisker stimuli are organized in functional maps. The barrel cortex also encodes spatio-temporal correlation patterns of multi-whisker inputs, but so far the cortical mapping of neurons tuned to such input statistics is unknown. Here we report that layer 2/3 of the rat barrel cortex contains an additional functional map based on neuronal tuning to correlated versus uncorrelated multi-whisker stimuli: neuron responses to uncorrelated multi-whisker stimulation are strongest above barrel centres, whereas neuron responses to correlated and anti-correlated multi-whisker stimulation peak above the barrel-septal borders, forming rings of multi-whisker synchrony-preferring cells.

Electron transport in furfural: dependence of the electron ranges on the cross sections and the energy loss distribution functions

NASA Astrophysics Data System (ADS)

Ellis-Gibbings, L.; Krupa, K.; Colmenares, R.; Blanco, F.; Muńoz, A.; Mendes, M.; Ferreira da Silva, F.; Limá Vieira, P.; Jones, D. B.; Brunger, M. J.; García, G.

2016-09-01

Recent theoretical and experimental studies have provided a complete set of differential and integral electron scattering cross section data from furfural over a broad energy range. The energy loss distribution functions have been determined in this study by averaging electron energy loss spectra for different incident energies and scattering angles. All these data have been used as input parameters for an event by event Monte Carlo simulation procedure to obtain the electron energy deposition patterns and electron ranges in liquid furfural. The dependence of these results on the input cross sections is then analysed to determine the uncertainty of the simulated values.

Tactile Data Entry System

NASA Technical Reports Server (NTRS)

Adams, Richard J.

2015-01-01

The patent-pending Glove-Enabled Computer Operations (GECO) design leverages extravehicular activity (EVA) glove design features as platforms for instrumentation and tactile feedback, enabling the gloves to function as human-computer interface devices. Flexible sensors in each finger enable control inputs that can be mapped to any number of functions (e.g., a mouse click, a keyboard strike, or a button press). Tracking of hand motion is interpreted alternatively as movement of a mouse (change in cursor position on a graphical user interface) or a change in hand position on a virtual keyboard. Programmable vibro-tactile actuators aligned with each finger enrich the interface by creating the haptic sensations associated with control inputs, such as recoil of a button press.

Massive-scale gene co-expression network construction and robustness testing using random matrix theory.

PubMed

Gibson, Scott M; Ficklin, Stephen P; Isaacson, Sven; Luo, Feng; Feltus, Frank A; Smith, Melissa C

2013-01-01

The study of gene relationships and their effect on biological function and phenotype is a focal point in systems biology. Gene co-expression networks built using microarray expression profiles are one technique for discovering and interpreting gene relationships. A knowledge-independent thresholding technique, such as Random Matrix Theory (RMT), is useful for identifying meaningful relationships. Highly connected genes in the thresholded network are then grouped into modules that provide insight into their collective functionality. While it has been shown that co-expression networks are biologically relevant, it has not been determined to what extent any given network is functionally robust given perturbations in the input sample set. For such a test, hundreds of networks are needed and hence a tool to rapidly construct these networks. To examine functional robustness of networks with varying input, we enhanced an existing RMT implementation for improved scalability and tested functional robustness of human (Homo sapiens), rice (Oryza sativa) and budding yeast (Saccharomyces cerevisiae). We demonstrate dramatic decrease in network construction time and computational requirements and show that despite some variation in global properties between networks, functional similarity remains high. Moreover, the biological function captured by co-expression networks thresholded by RMT is highly robust.

The transfer functions of cardiac tissue during stochastic pacing.

PubMed

de Lange, Enno; Kucera, Jan P

2009-01-01

The restitution properties of cardiac action potential duration (APD) and conduction velocity (CV) are important factors in arrhythmogenesis. They determine alternans, wavebreak, and the patterns of reentrant arrhythmias. We developed a novel approach to characterize restitution using transfer functions. Transfer functions relate an input and an output quantity in terms of gain and phase shift in the complex frequency domain. We derived an analytical expression for the transfer function of interbeat intervals (IBIs) during conduction from one site (input) to another site downstream (output). Transfer functions can be efficiently obtained using a stochastic pacing protocol. Using simulations of conduction and extracellular mapping of strands of neonatal rat ventricular myocytes, we show that transfer functions permit the quantification of APD and CV restitution slopes when it is difficult to measure APD directly. We find that the normally positive CV restitution slope attenuates IBI variations. In contrast, a negative CV restitution slope (induced by decreasing extracellular [K(+)]) amplifies IBI variations with a maximum at the frequency of alternans. Hence, it potentiates alternans and renders conduction unstable, even in the absence of APD restitution. Thus, stochastic pacing and transfer function analysis represent a powerful strategy to evaluate restitution and the stability of conduction.

Characterization of Radar Signals Using Neural Networks

DTIC Science & Technology

1990-12-01

e***e*e*eeeeeeeeeeeesseeeeeese*eee*e*e************s /* Function Name: load.input.ptterns Number: 4.1 /* Description: This function determines wether ...XSE.last.layer Number: 8.5 */ /* Description: The function determines wether to backpropate the *f /* parameter by the sigmoidal or linear update...Sigmoidal Function," Mathematics of Control, Signals and Systems, 2:303-314 (March 1989). 6. Dayhoff, Judith E. Neural Network Architectures. New York: Van

Data Reduction Functions for the Langley 14- by 22-Foot Subsonic Tunnel

NASA Technical Reports Server (NTRS)

Boney, Andy D.

2014-01-01

The Langley 14- by 22-Foot Subsonic Tunnel's data reduction software utilizes six major functions to compute the acquired data. These functions calculate engineering units, tunnel parameters, flowmeters, jet exhaust measurements, balance loads/model attitudes, and model /wall pressures. The input (required) variables, the output (computed) variables, and the equations and/or subfunction(s) associated with each major function are discussed.

Optical Spatial integration methods for ambiguity function generation

NASA Technical Reports Server (NTRS)

Tamura, P. N.; Rebholz, J. J.; Daehlin, O. T.; Lee, T. C.

1981-01-01

A coherent optical spatial integration approach to ambiguity function generation is described. It uses one dimensional acousto-optic Bragg cells as input tranducers in conjunction with a space variant linear phase shifter, a passive optical element, to generate the two dimensional ambiguity function in one exposure. Results of a real time implementation of this system are shown.

A hardware-oriented algorithm for floating-point function generation

NASA Technical Reports Server (NTRS)

O'Grady, E. Pearse; Young, Baek-Kyu

1991-01-01

An algorithm is presented for performing accurate, high-speed, floating-point function generation for univariate functions defined at arbitrary breakpoints. Rapid identification of the breakpoint interval, which includes the input argument, is shown to be the key operation in the algorithm. A hardware implementation which makes extensive use of read/write memories is used to illustrate the algorithm.

Developing a 3D Gestural Interface for Anesthesia-Related Human-Computer Interaction Tasks Using Both Experts and Novices.

PubMed

Jurewicz, Katherina A; Neyens, David M; Catchpole, Ken; Reeves, Scott T

2018-06-01

The purpose of this research was to compare gesture-function mappings for experts and novices using a 3D, vision-based, gestural input system when exposed to the same context of anesthesia tasks in the operating room (OR). 3D, vision-based, gestural input systems can serve as a natural way to interact with computers and are potentially useful in sterile environments (e.g., ORs) to limit the spread of bacteria. Anesthesia providers' hands have been linked to bacterial transfer in the OR, but a gestural input system for anesthetic tasks has not been investigated. A repeated-measures study was conducted with two cohorts: anesthesia providers (i.e., experts) ( N = 16) and students (i.e., novices) ( N = 30). Participants chose gestures for 10 anesthetic functions across three blocks to determine intuitive gesture-function mappings. Reaction time was collected as a complementary measure for understanding the mappings. The two gesture-function mapping sets showed some similarities and differences. The gesture mappings of the anesthesia providers showed a relationship to physical components in the anesthesia environment that were not seen in the students' gestures. The students also exhibited evidence related to longer reaction times compared to the anesthesia providers. Domain expertise is influential when creating gesture-function mappings. However, both experts and novices should be able to use a gesture system intuitively, so development methods need to be refined for considering the needs of different user groups. The development of a touchless interface for perioperative anesthesia may reduce bacterial contamination and eventually offer a reduced risk of infection to patients.

AESOP- INTERACTIVE DESIGN OF LINEAR QUADRATIC REGULATORS AND KALMAN FILTERS

NASA Technical Reports Server (NTRS)

Lehtinen, B.

1994-01-01

AESOP was developed to solve a number of problems associated with the design of controls and state estimators for linear time-invariant systems. The systems considered are modeled in state-variable form by a set of linear differential and algebraic equations with constant coefficients. Two key problems solved by AESOP are the linear quadratic regulator (LQR) design problem and the steady-state Kalman filter design problem. AESOP is designed to be used in an interactive manner. The user can solve design problems and analyze the solutions in a single interactive session. Both numerical and graphical information are available to the user during the session. The AESOP program is structured around a list of predefined functions. Each function performs a single computation associated with control, estimation, or system response determination. AESOP contains over sixty functions and permits the easy inclusion of user defined functions. The user accesses these functions either by inputting a list of desired functions in the order they are to be performed, or by specifying a single function to be performed. The latter case is used when the choice of function and function order depends on the results of previous functions. The available AESOP functions are divided into several general areas including: 1) program control, 2) matrix input and revision, 3) matrix formation, 4) open-loop system analysis, 5) frequency response, 6) transient response, 7) transient function zeros, 8) LQR and Kalman filter design, 9) eigenvalues and eigenvectors, 10) covariances, and 11) user-defined functions. The most important functions are those that design linear quadratic regulators and Kalman filters. The user interacts with AESOP when using these functions by inputting design weighting parameters and by viewing displays of designed system response. Support functions obtain system transient and frequency responses, transfer functions, and covariance matrices. AESOP can also provide the user with open-loop system information including stability, controllability, and observability. The AESOP program is written in FORTRAN IV for interactive execution and has been implemented on an IBM 3033 computer using TSS 370. As currently configured, AESOP has a central memory requirement of approximately 2 Megs of 8 bit bytes. Memory requirements can be reduced by redimensioning arrays in the AESOP program. Graphical output requires adaptation of the AESOP plot routines to whatever device is available. The AESOP program was developed in 1984.

47 CFR 97.205 - Repeater station.

Code of Federal Regulations, 2013 CFR

2013-10-01

... case, the licensee of the non-coordinated repeater has primary responsibility to resolve the interference. (d) A repeater may be automatically controlled. (e) Ancillary functions of a repeater that are available to users on the input channel are not considered remotely controlled functions of the station...

47 CFR 97.205 - Repeater station.

Code of Federal Regulations, 2014 CFR

2014-10-01

... case, the licensee of the non-coordinated repeater has primary responsibility to resolve the interference. (d) A repeater may be automatically controlled. (e) Ancillary functions of a repeater that are available to users on the input channel are not considered remotely controlled functions of the station...

47 CFR 97.205 - Repeater station.

Code of Federal Regulations, 2012 CFR

2012-10-01

... case, the licensee of the non-coordinated repeater has primary responsibility to resolve the interference. (d) A repeater may be automatically controlled. (e) Ancillary functions of a repeater that are available to users on the input channel are not considered remotely controlled functions of the station...

47 CFR 97.205 - Repeater station.

Code of Federal Regulations, 2011 CFR

2011-10-01

... case, the licensee of the non-coordinated repeater has primary responsibility to resolve the interference. (d) A repeater may be automatically controlled. (e) Ancillary functions of a repeater that are available to users on the input channel are not considered remotely controlled functions of the station...

47 CFR 97.205 - Repeater station.

Code of Federal Regulations, 2010 CFR

2010-10-01

... case, the licensee of the non-coordinated repeater has primary responsibility to resolve the interference. (d) A repeater may be automatically controlled. (e) Ancillary functions of a repeater that are available to users on the input channel are not considered remotely controlled functions of the station...

Acute Fasting Regulates Retrograde Synaptic Enhancement through a 4E-BP-Dependent Mechanism.

PubMed

Kauwe, Grant; Tsurudome, Kazuya; Penney, Jay; Mori, Megumi; Gray, Lindsay; Calderon, Mario R; Elazouzzi, Fatima; Chicoine, Nicole; Sonenberg, Nahum; Haghighi, A Pejmun

2016-12-21

While beneficial effects of fasting on organismal function and health are well appreciated, we know little about the molecular details of how fasting influences synaptic function and plasticity. Our genetic and electrophysiological experiments demonstrate that acute fasting blocks retrograde synaptic enhancement that is normally triggered as a result of reduction in postsynaptic receptor function at the Drosophila larval neuromuscular junction (NMJ). This negative regulation critically depends on transcriptional enhancement of eukaryotic initiation factor 4E binding protein (4E-BP) under the control of the transcription factor Forkhead box O (Foxo). Furthermore, our findings indicate that postsynaptic 4E-BP exerts a constitutive negative input, which is counteracted by a positive regulatory input from the Target of Rapamycin (TOR). This combinatorial retrograde signaling plays a key role in regulating synaptic strength. Our results provide a mechanistic insight into how cellular stress and nutritional scarcity could acutely influence synaptic homeostasis and functional stability in neural circuits. Copyright © 2016 Elsevier Inc. All rights reserved.

Estimation of parameters in Shot-Noise-Driven Doubly Stochastic Poisson processes using the EM algorithm--modeling of pre- and postsynaptic spike trains.

PubMed

Mino, H

2007-01-01

To estimate the parameters, the impulse response (IR) functions of some linear time-invariant systems generating intensity processes, in Shot-Noise-Driven Doubly Stochastic Poisson Process (SND-DSPP) in which multivariate presynaptic spike trains and postsynaptic spike trains can be assumed to be modeled by the SND-DSPPs. An explicit formula for estimating the IR functions from observations of multivariate input processes of the linear systems and the corresponding counting process (output process) is derived utilizing the expectation maximization (EM) algorithm. The validity of the estimation formula was verified through Monte Carlo simulations in which two presynaptic spike trains and one postsynaptic spike train were assumed to be observable. The IR functions estimated on the basis of the proposed identification method were close to the true IR functions. The proposed method will play an important role in identifying the input-output relationship of pre- and postsynaptic neural spike trains in practical situations.

Complete Insecurity of Quantum Protocols for Classical Two-Party Computation

NASA Astrophysics Data System (ADS)

Buhrman, Harry; Christandl, Matthias; Schaffner, Christian

2012-10-01

A fundamental task in modern cryptography is the joint computation of a function which has two inputs, one from Alice and one from Bob, such that neither of the two can learn more about the other’s input than what is implied by the value of the function. In this Letter, we show that any quantum protocol for the computation of a classical deterministic function that outputs the result to both parties (two-sided computation) and that is secure against a cheating Bob can be completely broken by a cheating Alice. Whereas it is known that quantum protocols for this task cannot be completely secure, our result implies that security for one party implies complete insecurity for the other. Our findings stand in stark contrast to recent protocols for weak coin tossing and highlight the limits of cryptography within quantum mechanics. We remark that our conclusions remain valid, even if security is only required to be approximate and if the function that is computed for Bob is different from that of Alice.

Improving outcome of sensorimotor functions after traumatic spinal cord injury.

PubMed

Dietz, Volker

2016-01-01

In the rehabilitation of a patient suffering a spinal cord injury (SCI), the exploitation of neuroplasticity is well established. It can be facilitated through the training of functional movements with technical assistance as needed and can improve outcome after an SCI. The success of such training in individuals with incomplete SCI critically depends on the presence of physiological proprioceptive input to the spinal cord leading to meaningful muscle activations during movement performances. Some actual preclinical approaches to restore function by compensating for the loss of descending input to spinal networks following complete/incomplete SCI are critically discussed in this report. Electrical and pharmacological stimulation of spinal neural networks is still in the experimental stage, and despite promising repair studies in animal models, translations to humans up to now have not been convincing. It is possible that a combination of techniques targeting the promotion of axonal regeneration is necessary to advance the restoration of function. In the future, refinement of animal models according to clinical conditions and requirements may contribute to greater translational success.

Complete insecurity of quantum protocols for classical two-party computation.

PubMed

Buhrman, Harry; Christandl, Matthias; Schaffner, Christian

2012-10-19

A fundamental task in modern cryptography is the joint computation of a function which has two inputs, one from Alice and one from Bob, such that neither of the two can learn more about the other's input than what is implied by the value of the function. In this Letter, we show that any quantum protocol for the computation of a classical deterministic function that outputs the result to both parties (two-sided computation) and that is secure against a cheating Bob can be completely broken by a cheating Alice. Whereas it is known that quantum protocols for this task cannot be completely secure, our result implies that security for one party implies complete insecurity for the other. Our findings stand in stark contrast to recent protocols for weak coin tossing and highlight the limits of cryptography within quantum mechanics. We remark that our conclusions remain valid, even if security is only required to be approximate and if the function that is computed for Bob is different from that of Alice.

Sonic hedgehog expression in corticofugal projection neurons directs cortical microcircuit formation.

PubMed

Harwell, Corey C; Parker, Philip R L; Gee, Steven M; Okada, Ami; McConnell, Susan K; Kreitzer, Anatol C; Kriegstein, Arnold R

2012-03-22

The precise connectivity of inputs and outputs is critical for cerebral cortex function; however, the cellular mechanisms that establish these connections are poorly understood. Here, we show that the secreted molecule Sonic Hedgehog (Shh) is involved in synapse formation of a specific cortical circuit. Shh is expressed in layer V corticofugal projection neurons and the Shh receptor, Brother of CDO (Boc), is expressed in local and callosal projection neurons of layer II/III that synapse onto the subcortical projection neurons. Layer V neurons of mice lacking functional Shh exhibit decreased synapses. Conversely, the loss of functional Boc leads to a reduction in the strength of synaptic connections onto layer Vb, but not layer II/III, pyramidal neurons. These results demonstrate that Shh is expressed in postsynaptic target cells while Boc is expressed in a complementary population of presynaptic input neurons, and they function to guide the formation of cortical microcircuitry. Copyright © 2012 Elsevier Inc. All rights reserved.