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DFNA5 was first identified as a gene causing autosomal dominant hearing loss (HL). Different mutations have been found, all exerting a highly specific gain-of-function effect, in which skipping of exon 8 causes the HL. Later reports revealed the involvement of the gene in different types of cancer. Epigenetic silencing of DFNA5 in a large percentage of gastric, colorectal and breast tumors and p53-dependent transcriptional activity have been reported, concluding that DFNA5 acts as a tumor suppressor gene in different frequent types of cancer. Despite these data, the molecular function of DFNA5 has not been investigated properly. Previous transfection studies with mutant DFNA5 in yeast and in mammalian cells showed a toxic effect of the mutant protein, which was not seen after transfection ...

CERN Document Server

Methods and Procedures for the Verification and Validation of Artificial Neural Networks

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... A control design methodology enabling the adaptive neural augmentation. ... As an example, the problem of designing a neural augmentation system. ...

UK PubMed Central (United Kingdom)

The temporal synchrony of auditory and visual signals is known to affect the perception of an external event, yet it is unclear what neural mechanisms underlie the influence of temporal synchrony...Full Text Available

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Not Available

KoreaScience (Korea)

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DEFF Research Database (Denmark)

Udgivelsesdato: 2007/7

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Not Available

UK PubMed Central (United Kingdom)

Experience with visual objects leads to later improvements in identification speed and accuracy (“repetition priming”), but generally leads to reductions in neural activity in single-cell...Full Text Available

UK PubMed Central (United Kingdom)

Multiple stimuli present in the visual field at the same time compete for neural representation by mutually suppressing their evoked activity throughout visual cortex, providing a neural correlate...Full Text Available

UK PubMed Central (United Kingdom)

Several theories have proposed a functional role for synchronous neuronal firing in generating the neural code of a sensory perception. Synchronous neural activity develops during a critical...Full Text Available

International Nuclear Information System (INIS)

On the problem of alarm when parts are falling in nuclear power plant, the artificial neural network (ANN) alarm method based on the signal time-frequency characteristics was developed. The method was realized by the improved BP algorithm, and demonstrated with the data from simulation experiments

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No abstract prepared.

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CERN Document Server

Computing Networks (CNs) are defined. These are used to generalize neural and swarm architectures, namely artificial neural networks, ant colony optimization, and particle swarm optimization. The description of these architectures as CNs allows their comparison, distinguishing which properties enable them to perform complex computations and exhibit complex cognitive abilities. In this context, the most relevant characteristics of CNs are the existence multiple dynamical and functional scales.

British Library Electronic Table of Contents (United Kingdom)

Summary The effects of high-intensity pulsed electromagnetic stimulation (HIPEMS) on proliferation and differentiation of neonatal rat neural stem cells in vitro were investigated. Neural stem cells derived from neonatal rats were exposed to 0.1 Hz, 0.5-10 Tesla (T) [8 groups of B-I, respectively], 5 stimuli of HIPEMF. The sham exposure controls were correspondingly established. Inverted phase contrast microscope was used to observe the cultured cells, MTT assay to detect the viability of the cells as expressed by absorbance (A) value, and flow cytometry to measure differentiation of neural stem cells. The results showed that A values of neural stem cells in both 3.0 T and 4.0 T groups were significantly higher than the other groups 24 to 168 h post HPEMS, indicating a strong promotion of ...

International Nuclear Information System (INIS)

In this article, the ability of artificial neural networks in prediction of separation in steady two dimensional boundary layer flows is studied. Data for network training is extracted from numerical solution of an ODE obtained from Von Karman integral equation with approximate one parameter Pohlhousen velocity profile. As an appropriate neural network, a two layer radial basis generalized regression artificial neural network is used. The results shows good agreements between the overall behavior of the flow fields predicted by the artificial neural network and the actual flow fields for some cases. The method easily can be extended to unsteady separation and turbulent as well as compressible boundary layer flows. (author)

Science.gov (United States)

The effects of high-intensity pulsed electromagnetic stimulation (HIPEMS) on proliferation and differentiation of neonatal rat neural stem cells in vitro were investigated. Neural stem cells derived from neonatal rats were exposed to 0.1 Hz, 0.5-10 Tesla (T) [8 groups of B-I, respectively], 5 stimuli of HIPEMF. The sham exposure controls were correspondingly established. Inverted phase contrast microscope was used to observe the cultured cells, MTT assay to detect the viability of the cells as expressed by absorbance (A) value, and flow cytometry to measure differentiation of neural stem cells. The results showed that A values of neural stem cells in both 3.0 T and 4.0 T groups were significantly higher than the other groups 24 to 168 h post HPEMS, indicating a strong promotion of the growth of neural stem cells (PHPEMS groups was the same as that in control group (P>0.05). It ...

British Library Electronic Table of Contents (United Kingdom)

Time delay neural networks trained with the backpropagation algorithm are derived for the gun fire control system to correct the miss distance between a target and the projectiles from the gun. Its performance is compared to optimum linear filter based on minimum mean square error [R.E. Kalman, A new approach to linear filtering and prediction problems, J. Basic Eng. 82D (1960) 35-44.]. The structure of the proposed neural controller is described and performance results are shown.

Energy Technology Data Exchange (ETDEWEB)

As an application of ART2 neural networks, computer aided monitoring of pump efficiency is successfully examined for an industrial waste-liquid treatment process with measured data of valve openness and liquid flow rates. By running the neural networks in parallel, we confirm that accuracy to detect system changes is good, and the adjustment of classifier parameters is relatively easy. Investigating the resulting classes carefully, frequency of each class is correlated with pump efficiency. The relative amount of variables are also related to the classes. (author)

International Nuclear Information System (INIS)

Supplementing the collection of artificial neural network methodologies devised for monitoring energy producing installations, a general regression artificial neural network is proposed for the identification of the two-phase flow that occurs in the coolant channels of boiling water reactors. The utilization of a limited number of image features derived from radiography images affords the proposed approach with efficiency and non-invasiveness. Additionally, the application of counter-clustering to the input patterns prior to training accomplishes an 80% reduction in network size as well as in training and test time. Cross-validation tests confirm accurate on-line flow regime identification.

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A back-propagation neural network technique is used at JET to extract plasma parameters like ion temperature, rotation velocities or spectral line intensities from charge exchange (CX) spectra. It is shown that in the case of the C VI CX spectra, neural networks can give a good estimation (better than +-20% accuracy) for the main plasma parameters (Ti, V{sub rot}). Since the neural network approach involves no iterations or initial guesses the speed with which a spectrum is processed is so high (0.2 ms/spectrum) that real time analysis will be achieved in the near future. 4 refs., 8 figs.

British Library Electronic Table of Contents (United Kingdom)

Because the state of a free-floating space robot model is uncertain and sudden changes in the model parameters might undermine the stability of the system, this paper proposes a control strategy based on a variable structure neural integrated controller. This scheme does not need a precise space robot model, making use of the radial basis function neural network ability approach to learn about an uncertain model. The network weights are adjusted online in real-time. During the early period of the control phase and parameter changes, the variable structure controller compensates for the uncertain model which the neural network could not learn well. It also creates global asymptotic stability for the whole closed-loop system. Simulation results show that the controller can handle bad changea...

Science.gov (United States)

[9] Rysdyk, R. T., and Calise, A. J., Fault Tolerant Flight control via Adaptive Neural Augmentation, AIAA. Guidance, Navigation, and Control Conference, Aug. ...

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A new recurrent neural network power system stabilizer (RNNPSS) based on genetic algorithm (GA) was presented. It shows faster convergence than the linear quadratic regulator (LQR) stabilizer in a multi-machine power system, because the proposed GA based neural network was first trained off-line to determine the optimal values of the learning rates. Otherwise, the RNNPSS consists of just two layers. As such, the time consumption of the damping oscillations is lower than with conventional methods. In addition, the operating range of the RNNPSS is greater than that of the LQR and conventional three layer neural networks, since the RNNPSS can greatly reduce system complexity and effectively damp system oscillations. 9 refs., 7 figs.

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This paper presents the application of artificial neural networks to adiabatic flame temperature prediction of hydrocarbon fuels. The investigation was conducted over a wide range of operating conditions in terms of fuel composition, pressure and temperature of reactants, fuel-air equivalence ratio and fuel vapour fraction. Several neural network models for predicting the flame temperature for different applicable fuel ranges were built and examined. The proper preparation of network training data and the appropriate choice of network parameters for achieving better prediction accuracy are discussed. The neural network prediction results were compared with those calculated by a thermodynamic and chemical equilibrium-based computer code - the NASA program CET89. It was shown that trained neural network models can provide the adiabatic flame temperature prediction with a good level of accuracy over a wide ...

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This paper deals with the control of an electromechanical valves engine. The control uses neural networks in order to build a non-linear model of engine filing which depends on the driven inlets. The aim is to build this real-time model and to integrate this model to a control system which performs an iterative inversion. (J.S.)

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A novel approach is presented to extract relevant parameters associated with the energy loss of ejectiles from nuclear reactions obtained by digitizing the signals of a Bragg curve spectrometer. New and more powerful computational paradigms allow a more thorough pulse-shape analysis. This is fulfilled using a back-propagation artificial neural network as a pattern identifier. The known problem of over-training is discussed.

Science.gov (United States)

A voice-tracking algorithm was developed and tested for the purposes of electronically separating the voice signals of simultaneous talkers. Many individuals suffer from hearing disorders that often inhibit their ability to focus on a single speaker in a multiple speaker environment (the cocktail party effect). Digital hearing aid technology makes it possible to implement complex algorithms for speech processing in both the time and frequency domains. In this work, an average magnitude difference function (AMDF) was performed on mixed voice signals in order to determine the fundamental frequencies present in the signals. A time prediction neural network was trained to recognize normal human voice inflection patterns, including rising, falling, rising-falling, and falling-rising patterns. The neural network was designed to track the fundamental frequency of a single talker based on the training procedure. The output of the ...

British Library Electronic Table of Contents (United Kingdom)

The precedence effect (PE) is thought to be beneficial for proper localization and perception of sounds. The majority of recent physiological studies focus on the neural discharges correlated with PE in the inferior colliculus (IC). Pentobarbital anesthesia is widely used in physiological studies. However, little is known of the effect of pentobarbital on the discharge of neurons in PE. Neuronal responses in the IC from 23 male SD rats were recorded by standard extracellular recording techniques following presentation of 4ms white noise bursts, presented from either or both of two loud speakers, at different interstimulus delays (ISDs). The neural responses were recorded for off-line analysis before or after intraperitoneal administration of pentobarbital at a loading or maintenance dose. ...

British Library Electronic Table of Contents (United Kingdom)

Timely detection of the pneumatic system problems is important in industry. Many techniques have been employed to solve this problem. In this paper, Genetic Algorithm (GA) based optimal configuration of neural networks is proposed for fault diagnostic of bottle filling systems. Back-propagation is used for neural networks algorithm. The back-propagation algorithm had six inputs and one output. A fitness function was designed to the minimize execution time of ANN model by keeping the number of hidden layer(s) and nodes as low as possible while the mean square error of estimated output error is minimized. The designed GA-ANN combination and the graphical user interface (GUI) eliminate the trial and error process for selection of the fastest and most accurate configuration. The performance of...

CERN Document Server

We consider the effect of distributed delays in neural feedback systems. The avian optic tectum is reciprocally connected with the nucleus isthmi. Extracellular stimulation combined with intracellular recordings reveal a range of signal delays from 4 to 9 ms between isthmotectal elements. This observation together with prior mathematical analysis concerning the influence of a delay distribution on system dynamics raises the question whether a broad delay distribution can impact the dynamics of neural feedback loops. For a system of reciprocally connected model neurons, we found that distributed delays enhance system stability in the following sense. With increased distribution of delays, the system converges faster to a fixed point and converges slower toward a limit cycle. Further, the introduction of distributed delays leads to an increased range of the average delay value for which the system's equilibrium point is stable. The enhancement of ...

CERN Document Server

Recently, applying the novel data mining techniques for evaluating enterprise financial distress has received much research alternation. Support Vector Machine (SVM) and back propagation neural (BPN) network has been applied successfully in many areas with excellent generalization results, such as rule extraction, classification and evaluation. In this paper, a model based on SVM with Gaussian RBF kernel is proposed here for enterprise financial distress evaluation. BPN network is considered one of the simplest and are most general methods used for supervised training of multilayered neural network. The comparative results show that through the difference between the performance measures is marginal; SVM gives higher precision and lower error rates.

International Nuclear Information System (INIS)

In this paper, a neural networks (NN) based adaptive sliding mode controller (SMC) is introduced. The selection of SMC feedback gains is normally based on one operating point and thus the performance of the controller away from the design operating point is, of necessity, a compromise. The adaptive SMC is proposed to overcome the limitations imposed on the effectiveness of the SMC under different operating conditions. Neural networks are used for online prediction of the optimal SMC gains when the operating point changes. The proposed method has been applied to a power system stabilizer (PSS) of a single machine power system. Simulation results are included to demonstrate the performance of the proposed control scheme.

Science.gov (United States)

Using static Michelson interferometer to get the spectrum information of measurement targets for spectrum identification, under the condition that the interference length is constant, the system can be optimized by BP neural network algorithm for the mixed spectral separation process. Thereby it can realize improving the recognition probability of camouflage target. Collecting the spectrum information in field of view (FOV) by the interferometer and linear array CCD detector, composing the set of mixed spectrum data, with known absorption spectrum of the material as a hidden layer of rules, it used BP neural network to separate the mixed spectrum data. Experiment with different distances, different combinations of mixed background spectrum as the initial data, using steel target (size: 1.5 m x 1.5 m) made of four kinds, the recognition probability of non-camouflage target is about 90% by BP neural network algorithm or the ...

UK PubMed Central (United Kingdom)

Hypercapnia is often used as vasodilatory challenge in clinical applications and basic research. In functional magnetic resonance imaging (fMRI), elevated CO₂ is applied to derive stimulus-induced...Full Text Available

UK PubMed Central (United Kingdom)

In utero electroporation is widely used to study neuronal development and function by introducing plasmid DNA into neural progenitors during embryogenesis. This is an effective and...Full Text Available

Energy Technology Data Exchange (ETDEWEB)

In this paper, the combustible value (i.e. 100-Ash) and combustible recovery of coal flotation concentrate were predicted by regression and artificial neural network based on proximate and group macerals analysis. The regression method shows that the relationships between (a) in (ash), volatile matter and moisture (b) in (ash), in (liptinite), fusinite and vitrinite with combustible value can achieve the correlation coefficients (R{sup 2}) of 0.8 and 0.79, respectively. In addition, the input sets of (c) ash, volatile matter and moisture (d) ash, liptinite and fusinite can predict the combustible recovery with the correlation coefficients of 0.84 and 0.63, respectively. Feed-forward artificial neural network with 6-8-12-11-2-1 arrangement for moisture, ash and volatile matter input set was capable to estimate both combustible value and combustible recovery with correlation of 0.95. It was shown that the proposed neural ...

UK PubMed Central (United Kingdom)

Percutaneous radiofrequency ablation is the treatment of choice for osteoid osteoma of the appendicular skeleton. However, difficulties in localizing the lesion in the spine and its proximity to neural...Full Text Available

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Target recognition requires the ability to distinguish targets from non-targets, a capability called one-class generalization. To function as a one-class classifier, a neural network must have three types of generalization: within-class, between-class, and out-of-class. We discuss these three types of generalization and identify neural network architectures that meet these requirements. We have applied our one-class classifier ideas to the problem of automatic target recognition in synthetic aperture radar. We have compared three neural network algorithms: Carpenter and Grossberg`s algorithmic version of the Adaptive Resonance Theory (ART-2A), Kohonen`s Learning Vector Quantization (LVQ), and Reilly and Cooper`s Restricted Columb Energy network (RCE). The ART 2-A neural network has given the best results, with 100% within-class, and out-of-class generalization. Experiments show that the network`s ...

UK PubMed Central (United Kingdom)

The CNS can exhibit features of inflammation in response to injury, infection or disease, whereby resident cells generate inflammatory mediators, including cytokines, prostaglandins, free radicals and...Full Text Available

UK PubMed Central (United Kingdom)

An optical flow gradient algorithm was applied to spontaneously forming networks of neurons and glia in culture imaged by fluorescence optical microscopy in order to map functional calcium signaling...Full Text Available

UK PubMed Central (United Kingdom)

An influential neural model of face perception suggests that the posterior superior temporal sulcus (STS) is sensitive to those aspects of faces that produce transient visual changes, including facial...Full Text Available

UK PubMed Central (United Kingdom)

Synaptic gain control and information storage in neural networks are mediated by alterations in synaptic transmission, such as in long-term potentiation (LTP). Here, we show using both in...Full Text Available

UK PubMed Central (United Kingdom)

The destiny of the mitotically active cells of the subventricular zone (SVZ) in adult rodents is to migrate to the olfactory bulb, where they contribute to the replacement of granular and periglomerular...Full Text Available

UK PubMed Central (United Kingdom)

During asymmetric mitosis, both in male Drosophila germline stem cells and in mouse embryo neural progenitors, the mother centrosome is retained by the self-renewed cell; hence suggesting...Full Text Available

UK PubMed Central (United Kingdom)

A century ago, Cajal noted striking similarities between the neural circuits that underlie vision in vertebrates and flies. Over the past few decades, structural and functional studies have...Full Text Available

UK PubMed Central (United Kingdom)

Proprioceptive sensory signals inform the CNS of the consequences of motor acts, but effective motor planning involves internal neural systems capable of anticipating actual sensory feedback....Full Text Available

UK PubMed Central (United Kingdom)

Backgroundoscillatory activity, which can be separated in background and oscillatory burst pattern activities, is supposed to be representative of local synchronies of neural assemblies....Full Text Available

UK PubMed Central (United Kingdom)

The mammalian reoviruses have provided a valuable model for studying the pathogenesis of viral infections of the central nervous system (CNS). We have used this model to study the effect of antibody...Full Text Available

Energy Technology Data Exchange (ETDEWEB)

The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms), to some of the problems of complex engineering systems has the potential to enhance the safety, reliability, and operability of these systems. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network (e.g., a fast Fourier transformation of the time-series data to produce a spectral plot of the data). Specific applications described include: (1) Diagnostics: State of the Plant (2) Hybrid System for Transient Identification, (3) Sensor Validation, (4) Plant-Wide Monitoring, (5) Monitoring of Performance and Efficiency, and (6) Analysis of Vibrations. Although specific ...

UK PubMed Central (United Kingdom)

Even in healthy individuals, aging leads to deterioration in visual acuity, contrast sensitivity, visual field, and dark adaptation. Little is known about the neural mechanisms that drive the...Full Text Available

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We review visually guided behaviors in larval zebrafish and summarise what is known about the neural processing that results in these behaviors, paying particular attention to the progress made in the last 2 years. Using the examples of the optokinetic reflex, the optomotor response, prey tracking and the visual startle response, we illustrate how the larval zebrafish presents us with a very promising model vertebrate system that allows neurocientists to integrate functional and behavioral studies and from which we can expect illuminating insights in the near future.

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Artificial Neural Networks (ANNs) are parallel distributed processing machines. The unique characteristics of ANNs are: Fault tolerance, robustness, plasticity and generalization. These offer great potential in many AI applications such as character recognition. Handwritten character recognition is an intrinsically interesting problem, but the difficulties of this task are the many variations in the characters. A robust new incremental learning method, which combines supervised and unsupervised learning paradigms implemented by the Functional Link Net, is illustrated with experimental results. Clustering, based on unsupervised learning, classifies the input data into several categories. The supervised learning paradigm then further classifies the data in the clustered categories.

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In this paper an attempt is made to forecast load using fuzzy neural network (FNN) for an integrated power system. Here, the proposed system uses a two stage FNN for a short term peak and average load forecasting (STPALF). The first stage FNN deals with the load forecasting and the second stage algorithm can be worked independently for network security. This technique is used to forecast load accurately on week days as well as holidays, weekends and some special occasions considering historical data of load and weather information and also take necessary control action for network security.

International Nuclear Information System (INIS)

The paper provides a brief description of the fuel characterization for Fast Breeder Test Reactor (FBTR) and Prototype Fast Breeder Reactor (PFBR). The development and characterization of mechanical properties of Alloy D9 clad and wrapper tubes are discussed. The problems associated with fusion welding of Alloy D9 are outlined. Non-destructive characterization of cladding tubes by optimum encircling eddy current probes, on-line and off-line neural network methods is presented. Both the on-line and off-line neural network methods could readily detect and size defects specified by the designers

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Results from ultimate analysis, proximate and petrographic analyses of a wide range of Kentucky coal samples were used to predict coal rank parameters (vitrinite maximum reflectance (R{sub max}) and gross calorific value (GCV)) using multivariable regression and artificial neural network (ANN) methods. Volatile matter, carbon, total sulfur, hydrogen and oxygen were used to predict both R{sub max} and GCV by regression and ANN. Multivariable regression equations to predict R{sub max} and GCV showed R{sup 2} = 0.77 and 0.69, respectively. Results from the ANN method with a 2-5-4-2 arrangement that simultaneously predicts GCV and R{sub max} showed R{sup 2} values of 0.84 and 0.90, respectively, for an independent test data set. The artificial neural network method can be appropriately used to predict R{sub max} and GCV when regression results do not have high accuracy. (author)

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To determine if barbiturates would protect brain at high doses of radiation, survival rates in rats that received whole-brain x-irradiation during pentobarbital- or lidocaine-induced anesthesia were compared with those of control animals that received no medication and of animals anesthetized with ketamine. The animals were shielded so that respiratory and digestive tissues would not be damaged by the radiation. Survival rates in rats that received whole-brain irradiation as a single 7500-rad dose under pentobarbital- or lidocaine-induced anesthesia was increased from between from 0% and 20% to between 45% and 69% over the 40 days of observation compared with the other two groups (p less than 0.007). Ketamine anesthesia provided no protection. There were no notable differential effects upon non-neural tissues, suggesting that pentobarbital afforded protection through modulation of ambient neural activity during radiation exposure. ...

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Artificial neural network analysis is found to be far superior to multiple regression when applied to the evaluation of trap quality in the Northern Kuqa Depression, a gas-rich depression of Tarim Basin in western China. This is because this technique can correlate the complex and non-linear relationship between trap quality and related geological factors, whereas multiple regression can only describe a linear relationship. However, multiple regression can work as an auxiliary tool, as it is suited to high-speed calculations and can indicate the degree of dependence between the trap quality and its related geological factors which artificial neural network analysis cannot. For illustration, we have investigated 30 traps in the Northern Kuqa Depression. For each of the traps, the values of 14 selected geological factors were all known. While geologists were also able to assign individual trap quality values to 27 traps, they were less certain ...

Science.gov (United States)

In this paper, we introduce a new recursive neural network model able to process directed acyclic graphs with labelled edges. The model uses a state transition function which considers the edge labels and is independent both from the number and the order of the children of each node. The computational capabilities of the new recursive architecture are assessed. Moreover, in order to test the proposed architecture on a practical challenging application, the problem of object detection in images is also addressed. In fact, the localization of target objects is a preliminary step in any recognition system. The proposed technique is general and can be applied in different detection systems, since it does not exploit any a priori knowledge on the particular problem. Some experiments on face detection, carried out on scenes acquired by an indoor camera, are reported, showing very promising results. PMID:16181770

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The objective of this study is to develop an artificial neural network (ANN) model to predict the thermal conductivity of ethylene glycol-water solutions based on experimentally measured variables. The thermal conductivity of solutions at different concentrations and various temperatures was measured using the cylindrical cell method that physical properties of the solution are being determined fills the annular space between two concentric cylinders. During the experiment, heat flows in the radial direction outwards through the test liquid filled in the annual gap to cooling water. In the steady state, conduction inside the cell was described by the Fourier equation in cylindrical coordinates, with boundary conditions corresponding to heat transfer between the solution and cooling water. ...

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In vibration control field, magneto-rheological (MR) fluid dampers are semi-active control devices that have recently begun to receive more attention. This paper presents a nonlinear black-box model (BBM) and an inverse black-box model (IBBM) for the identification of a MR fluid damper and their application to design a novel force-sensorless control method for any damping system using that damper. The nonlinear model named 'black-box' is a simple direct modeling method which was designed based on fuzzy-neural technique. Characteristics of the damper in study are directly estimated through a fuzzy mapping system. In order to improve the model accuracy, neural network technique including back-propagation and gradient descent method were used to train the fuzzy parameters to minimize the mode...

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This study has been carried out in the framework of a collaboration between the laboratory of processes automation (LAP, Caen (France)), and Air Com, a monitoring network for the prevention of atmospheric pollution in Basse-Normandie. It aims at obtaining a medium and long term forecast of the ozone level above the Caen city. The expected goal is to foresee the pollution peaks exceeding the warning thresholds, but the rareness of such events make them more difficult to predict. In order to solve this kind of problem, a neural modeling method combined with a noise injection technique has been implemented in order to obtain a sufficiently performing model over the whole domain of operation. (J.S.)

British Library Electronic Table of Contents (United Kingdom)

A marine propulsion system is a very complicated system composed of many mechanical components. As a result, the vibration signal of a gearbox in the system is strongly coupled with the vibration signatures of other components including a diesel engine and main shaft. It is therefore imperative to assess the coupling effect on diagnostic reliability in the process of gear fault diagnosis. For this reason, a fault detection and diagnosis method based on bispectrum analysis and artificial neural networks (ANNs) was proposed for the gearbox with consideration given to the impact of the other components in marine propulsion systems. To monitor the gear conditions, the bispectrum analysis was first employed to detect gear faults. The amplitude-frequency plots containing gear characteristic sign...

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This article presents the micro-electro-mechanical systems (MEMS) microrobot which demonstrates locomotion controlled by hardware neural networks (HNN). The size of the microrobot fabricated by the MEMS technology is 4 ? 4 ? 3.5 mm. The frame of the robot is made of silicon wafer, and it is equipped with a rotary-type actuator, a link mechanism, and six legs. The rotary-type actuator generates rotational movement by applying an electrical current to artificial muscle wires. The locomotion of the microrobot is obtained by the rotation of the rotary-type actuator. As in a living organism, the HNN realized robot control without using any software programs, A/D converters, or additional driving circuits. A central pattern generator (CPG) model was implemented as an HNN system to emulate the lo...

British Library Electronic Table of Contents (United Kingdom)

Frozen boiled shrimp and dried shrimp are among the high-value fishery products of Thailand. During the production of these products boiling is one of the most important steps that affects significantly the product physicochemical properties, especially the quantity and quality of proteins, which in turn affect other apparent properties perceived by consumers. The protein changes are, however, difficult to evaluate comparing to other typical physical properties of shrimp. The objective of this study was therefore to develop an artificial neural network (ANN) model to predict the protein changes of shrimp in terms of protein loss and protein denaturation as a function of the boiling conditions, namely, concentration of salt solution and boiling time, as well as a rather easily determined ch...

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The aim of this study is to develop the methodology which enables to identify the mechanical properties of element such as stress intensity factor by using the AE parameters. Considering the multivariate and nonlinear properties of AE parameters such as ringdown count, rise time, energy, event duration and peak amplitude from fatigue cracks of machine element the principal component regression(PCR) and artificial neural network(ANN) models for the estimation of stress intensity factor were developed and validated. The AE parameters were found to be very significant to estimate the stress intensity factor. Since the statistical values including correlation coefficients, standard mr of calibration, standard error of prediction and bias were stable, the PCR and ANN models for stress intensity factor were very robust. The performance of ANN model for unknown data of stress intensity factor was better than that of PCR model

British Library Electronic Table of Contents (United Kingdom)

Several challenges currently exist for rational design of functional tissue engineering constructs within the host, which include appropriate cellular integration, avoidance of bacterial infections, and low inflammatory stimulation. This work describes a novel class of biodegradable, amphiphilic polyanhydrides with many desirable protein-material and cell-material attributes capable of confronting these challenges. The biocompatible amphiphilic polymer films were shown to release laminin in a stable and controlled manner, promote neural cell adhesion and differentiation, and evade inflammatory responses of the immune system. Using high-throughput approaches, it was shown that polymer chemistry plays an integral role in controlling cell?film interactions, which suggests that these polyanhyd...

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In the present scenario of market driven business, power supply has become more like a commodity. Reliable and quality power need to be ensured to meet customer requirements. In such a situation, it is extremely important that transmission line faults be identified accurately, reliably and in quick time. Advanced signal processing tools such as discrete wavelet transform (DWT) can be used very effectively for parameterisation and characterization of the fault signals. On the other hand, properly configured neural network (NN) can be utilized for classification of the faults based on the DWT signal. The present contribution uses electromagnetic transient program (EMTP) for modeling of a real transmission system and MATLAB for DWT and NN. Various types of faults have been simulated at different locations along the transmission line and an attempt has been made to correctly identify and locate the fault. (author)

Energy Technology Data Exchange (ETDEWEB)

A power system stabilizer based on GMV (Generalized Minimum Variance), one of the adaptive control techniques, is developed to enhance the dynamic performances of a power system using an Artificial Neural Network (ANN). The stabilizer consists of two parts. One part is Inverse Dynamics Neural Networks (IDNN), which is trained to identify the inverse dynamics of controlled plant and used as a one-step ahead controller, or inverse controller. The other part is Adaptive Reference Model (ARM), which prevents excessive controller output. The ARM produces the modified reference value by minimizing a cost function recursively on the assumption that the IDNN perfectly identifies the controlled plant. The IDNN is used in the minimization procedure to calculate the sensitivities. The proposed controller is simulated in a typical one-machine-infinite-bus power system to show its effectiveness to damp sustained low frequency oscillation. (author)

British Library Electronic Table of Contents (United Kingdom)

The paper describes two schemes that follow the model of Lamarckian evolution and combine differential evolution (DE), which is a population-based stochastic global search method, with the local optimization algorithm of conjugate gradients (CG). In the first, each offspring is fine-tuned by CG before competing with their parents. In the other CG is used to improve both parents and offspring in a manner that is completely seamless for individuals that survive more than one generation. Experiments involved training weights of feed-forward neural networks to solve three synthetic and four real-life problems. In six out of seven cases the DE?CG hybrid, which preserves and uses information on each solution?s local optimization process, outperformed two recent variants of DE.

Science.gov (United States)

Schizophrenia and bipolar disorder share genetic risk, brain vulnerability, and clinical symptoms. The ZNF804A risk variant, rs1344706, confers susceptibility for both disorders. This study aimed to identify neural mechanisms common to both schizophrenia and bipolar disorder through this variant's potential effects on cortical thickness, white matter tract integrity, and cognitive function. Imaging, genetics, and cognitive measures were ascertained in 62 healthy adults aged between 18 and 59 years. High-resolution multimodal MRI/DTI imaging was used to measure cortical thickness and major frontotemporal and interhemispheric white matter tracts. The general linear model was used to examine the influence of the ZNF804A rs1344706 risk variant on cortical thickness, white matter tract integrity, and cognitive measures. Individuals homozygous for the risk variant ('A' allele) demonstrated reduced cortical gray matter thickness in the superior temporal gyrus, and in the ...

Energy Technology Data Exchange (ETDEWEB)

The classical stochastic approximation methods are shown to yield algorithms to solve several formulations of the PAC learning problem defined on the domain [o,1]{sup d}. Under some assumptions on different ability of the probability measure functions, simple algorithms to solve some PAC learning problems are proposed based on networks of non-polynomial units (e.g. artificial neural networks). Conditions on the sizes of these samples required to ensure the error bounds are derived using martingale inequalities.

UK PubMed Central (United Kingdom)

In many rodent species, such as Syrian hamsters, reproductive behavior requires neural integration of chemosensory information and steroid hormone cues. The medial amygdala processes both of...Full Text Available

Energy Technology Data Exchange (ETDEWEB)

This paper presents general considerations concerning the application of artificial neural networks algorithms, more specifically the back-propagation learning algorithm and feed-forward multi-layer networks, to several problems in power system. The main application in power systems is the load forecasting, and two solution methods are used to solve it. (author). 45 figs., 32 tabs., 144 refs.

Energy Technology Data Exchange (ETDEWEB)

Interactive seismic processing systems for editing noisy seismic traces and picking the first-break refraction events have been developed using a neural network learning algorithm. The authors employ a back propagation neural network (BNN) paradigm modified to improve the convergence rate of the BNN. The BNN is interactively trained'' to edit seismic data or pick first breaks by a human processor who judiciously selects and presents to the network examples of trace edits or refraction picks. The network then iteratively adjusts a set of internal weights until it can accurately duplicate the examples provided by the user. After the training session is completed, the BNN system an then process new data sets in a manner that mimics the human processor. Synthetic modeling studies indicated that the BNN uses many of the same subjective criteria that humans employ in editing and picking seismic data sets. Automated trace editing and ...

International Nuclear Information System (INIS)

Besides differentiation and apoptosis, cell migration is a basic process in brain development in which neural cells migrate several centimeters within the developing brain before reaching their proper positions and forming the right connections. For identifying signaling events that control neural migration and are therefore potential targets of chemicals to disturb normal brain development, we developed a human neurosphere-based migration assay based on normal human neural progenitor (NHNP) cells, in which the distance is measured that cells wander over time. Applying this assay, we investigated the role of the extracellular signal-regulated kinases 1 and 2 (ERK1/2) in the regulation of NHNP cell migration. Exposure to model substances like ethanol or phorbol 12-myristate 13-acetate (PMA) revealed a correlation between ERK1/2 activation and cell migration. The participation of phospho-(P-) ERK1/2 was confirmed by exposure ...

Science.gov (United States)

Optogenetics, the ability to use light to activate and silence specific neuron types within neural networks in vivo and in vitro, is revolutionizing neuroscientists' capacity to understand how defined neural circuit elements contribute to normal and pathological brain functions. Typically, awake behaving experiments are conducted by inserting an optical fiber into the brain, tethered to a remote laser, or by utilizing an implanted light-emitting diode (LED), tethered to a remote power source. A fully wireless system would enable chronic or longitudinal experiments where long duration tethering is impractical, and would also support high-throughput experimentation. However, the high power requirements of light sources (LEDs, lasers), especially in the context of the extended illumination periods often desired in experiments, precludes battery-powered approaches from being widely applicable. We have developed a headborne device weighing 2 g ...

UK PubMed Central (United Kingdom)

AbstractT-box family transcription factors play many roles in Metazoan development. Here we characterise Tbx6r, a unique Tbx6 paralogue isolated from the amphibian Xenopus....Full Text Available

Energy Technology Data Exchange (ETDEWEB)

The topic of supervised learning within the conceptual framework of artificial neural network (ANN) models is addressed. An ANN is a parallel distributed processing system that consists of many computationally simple processing elements interconnected through uni-directional weighted connections. Such networks, which are roughly patterned after biological nervous systems, have been proposed for use in areas in which the traditional von Neumann computer architecture has been relatively unsuccessful. Learning in these networks is accomplished through the use of algorithms that adjust the values of the connection weights. The work presented here addresses the issue of improving the rate at which ANNs can learn to achieve the mapping of an input pattern to a desired output pattern. The most successful learning algorithms for accomplishing this task are based on gradient descent error minimization techniques. However, the large amount of training time that such ...

Energy Technology Data Exchange (ETDEWEB)

The generation of a defined swivel momentum in car door hinges depends on numerous constructional and technical manufacturing parameters. If these parameters and their influence are to be investigated, then in addition to detailed experiments with variations in the parameters, methods are also required which enable the measuring data produced to be assessed in such a way that, in general, the non-linear relationships between initial and target size can be described sufficiently accurately. This paper explains the parameter reduction necessary in the experimental investigation, gives the results of the data assessment with conventional statistical methods and describes in particular the use of artificial neural networks (ANN) to construct so-called 'neuro hinge models' on the basis of the data resulting from the experiments. Parameter variations can be simulated with the hinge models and in this way optimal constructional and technical ...

Energy Technology Data Exchange (ETDEWEB)

Gastric stromal tumors are an ill-defined group of lesions arising from muscle wall cells and characterized by extremely variable biological patterns. Thanks to modern immunohistochemical and ultrastructural techniques, four main classes of these lesions have been identified, namely: (1) tumors with differentiation toward smooth muscle cells; (2) tumors with differentiation toward neural elements; (3) tumors with differentiation toward neural elements; (3) tumors with dual differentiation toward either cell type. It was investigated the yield of CT in diagnosing and characterizing gastric stromal tumors. It was retrospectively reviewed the CT findings of 38 patients (15 men and 23 women; mean age 51 years) with pathologically proven gastric stromal tumors, namely 31 of myoid origin, 4 of neural origin, 2 with both muscle and neural differentiation, 1 lacking differentiation with either cell type. The ...

Energy Technology Data Exchange (ETDEWEB)

With using artificial neural networks (ANNs), an analytical study related to the heated length effect on critical heat flux (CHF) has been carried out to make an improvement of the CHF prediction accuracy based on local condition correlations or table. It has been carried out to suggest a feasible criterion of the threshold length-to-diameter (L/D) value in which heated length could affect CHF. And within the criterion, a L/D correction factor has been developed through conventional regression. In order to validate the developed L/D correction factor, CHF experiments for various heated lengths have been carried out under low and intermediate pressure conditions. The developed threshold L/D correlation provides a new feasible criterion of L/D threshold value. The developed correction factor gives a reasonable accuracy for the original database, showing the error of -2.18% for average and 27.75% for RMS, and promising results for new experimental data. 7 refs., 12 ...

Energy Technology Data Exchange (ETDEWEB)

Feed-forward (FF) artificial neural networks (ANN) and radial basis function (RBF) ANN methods were addressed for evaluating the lightning performance of high voltage transmission lines. Several structures, learning algorithms and transfer functions were tested in order to produce a model with the best generalizing ability. Actual input and output data, collected from operating Hellenic high voltage transmission lines, as well as simulated output data were used in the training, validation and testing process. The aims of the paper are to describe in detail and compare the proposed FF and RBF ANN models, to state their advantages and disadvantages and to present results obtained by their application on operating Hellenic transmission lines of 150kV and 400kV. The ANN results are also compared with results obtained using conventional methods and real records of outage rate showing a quite satisfactory agreement. The proposed ANN methods can be used by electric power ...

British Library Electronic Table of Contents (United Kingdom)

Innate immune responses are regulated by microorganisms and cell death, as well as by a third class of stress signal from the nervous and endocrine systems. The innate immune system also feeds back, through the production of cytokines, to regulate the function of the central nervous system (CNS), and this has effects on behaviour. These signals provide an extrinsic regulatory circuit that links physiological, social and environmental conditions, as perceived by the CNS, with transcriptional 'decision-making' in leukocytes. CNS-mediated regulation of innate immune responses optimizes total organism fitness and provides new opportunities for therapeutic control of chronic infectious, inflammatory and neuropsychiatric diseases.

Energy Technology Data Exchange (ETDEWEB)

The activities and results of a Small Business Innovation Research Phase II project entitled ''Rapid Tools for Joint Inversion and Imaging'' are presented. Research and development on three-dimensional methods to recover distributions of material property values from sparse data are reported. Innovations using artificial neural networks and extended Kalman filtering are described. The report also covers investigations on upscaling and downscaling, segmentation for data processing, and applications to ground penetrating radar and geohydraulic tomography.

British Library Electronic Table of Contents (United Kingdom)

Visceral hypersensitivity is currently considered a key pathophysiological mechanism involved in pain perception in large subgroups of patients with functional gastrointestinal disorders, including irritable bowel syndrome (IBS). In IBS, visceral hypersensitivity has been described in 20%?90% of patients. The contribution of the central nervous system and psychological factors to visceral hypersensitivity in patients with IBS may be significant, although still debated. Peripheral factors have gained increasing attention following the recognition that infectious enteritis may trigger the development of persistent IBS symptoms, and the identification of mucosal immune, neural, endocrine, microbiological, and intestinal permeability abnormalities. Growing evidence suggests that these factors ...

International Nuclear Information System (INIS)

Continuum events represent an eminent source of background in any e+e- experiment. As these have a higher branching ratio than BB-bar events (at BaBar this ratio is estimated to about 3.5) or ?+?- events, efficient continuum background suppression is essential in many analyses. Using Artificial Neural Networks and the Nearest Neighbor Method we developed several selectors which, based only on the global event shape variables, efficiently tag BB-bar events and ?+?- events against the continuum background. These selectors could then be combined with the channel specific information in various types of analyses. The study was done using a parametric Monte Carlo.

Energy Technology Data Exchange (ETDEWEB)

The effects of proximate and ultimate analysis, maceral content, and coal rank (R{sub max}) for a wide range of Kentucky coal samples from calorific value of 4320 to 14960 (BTU/lb) (10.05 to 34.80 MJ/kg) on Hardgrove Grindability Index (HGI) have been investigated by multivariable regression and artificial neural network methods (ANN). The stepwise least square mathematical method shows that the relationship between (a) Moisture, ash, volatile matter, and total sulfur; (b) ln (total sulfur), hydrogen, ash, ln ((oxygen + nitrogen)/carbon) and moisture; (c) ln (exinite), semifusinite, micrinite, macrinite, resinite, and R{sub max} input sets with HGI in linear condition can achieve the correlation coefficients (R{sup 2}) of 0.77, 0.75, and 0.81, respectively. The ANN, which adequately recognized the characteristics of the coal samples, can predict HGI with correlation coefficients of 0.89, 0.89 and 0.95 respectively in testing process. It was determined that ln ...

DEFF Research Database (Denmark)

The blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal response to neural stimulation is influenced by many factors that are unrelated to the stimulus. These factors are physiological, such as the resting venous cerebral blood volume (CBV(v)) and vessel size, as well as experimental, such as pulse sequence and static magnetic field strength (B(0)). Thus, it is difficult to compare task-induced fMRI signals across subjects, field strengths, and pulse sequences. This problem can be overcome by normalizing the neural activity-induced BOLD fMRI response by a global hypercapnia-induced BOLD signal. To demonstrate the effectiveness of the BOLD normalization approach, gradient-echo BOLD fMRI at 1.5, 4, and 7 T and spin-echo BOLD fMRI at 4 T were performed in human subjects. For neural stimulation, subjects performed sequential finger movements at 2 Hz, while for global stimulation, ...

British Library Electronic Table of Contents (United Kingdom)

Sphere-forming abilities in culture condition are considered a hallmark of cancer stem-like cells, which represents tumor cell invasiveness and stem-like characteristics. We aimed to show that the sphere-forming subpopulation of human malignant melanoma cell line WM-266-4 acts differently to zebrafish embryo extracts compared with their bulk counterpart. Spheres were maintained in neural stem cell culture conditions. The embryos of zebrafish at specific developmental stages were collected and the extracts were purified under 100 kDa. Spheres were treated with embyo extracts and proliferation assay and immunocytochemistry were conducted. Spheroid cells expressed nestin and epidermal growth factor receptor (EGFR) but not melanoma antigen recognized by T-cells (MART)1, indicating their stem-l...

British Library Electronic Table of Contents (United Kingdom)

There is evidence that aged normal subjects have more difficulty in achieving automaticity than young subjects. The underlying central neural mechanism for this phenomenon is unclear. In the present study, functional magnetic resonance imaging (fMRI) was used to investigate the effect of normal ageing on automaticity. Aged healthy subjects were asked to practice self-initiated, self-paced, memorized sequential finger movements with different complexity until they could perform the tasks automatically. Automaticity was evaluated by having subjects perform a secondary task simultaneously with the sequential movements. Although it took more time, most aged subjects eventually performed the tasks automatically at the same level as the young subjects. Functional MRI results showed that, for bot...

British Library Electronic Table of Contents (United Kingdom)

Testosterone influences various aspects of affective behavior, which is mediated by different brain regions within the emotion circuitry. Previous neuroimaging studies have demonstrated that testosterone increases neural activity in the amygdala. To investigate whether this could be due to altered regulation of amygdala functioning which is thought to be mediated by the prefrontal cortex, we studied the effects of exogenous testosterone on the interaction between the amygdala and other brain regions. Healthy middle-aged women received a single nasal testosterone dose in a randomized, placebo-controlled, crossover manner, and performed an emotional face matching task while their brain activity was measured with functional MRI. The results show that testosterone rapidly reduced functional co...

Energy Technology Data Exchange (ETDEWEB)

This study discusses and compares, from a practical point of view, three different approaches for permeability determination from logs. These are empirical, statistical, and the recently introduced virtual measurement methods. They respectively make use of empirically determined models, multiple variable regression, and artificial neural networks. All three methods are applied to well log data from a heterogeneous formation and the results are compared with core permeability, which is considered to be the standard. In this first part of the paper we present only the model development phase in which we are testing the capability of each method to match the presented data. Based on this, the best two methods are to be analyzed in terms of prediction performance in the second part of this paper.

International Nuclear Information System (INIS)

This paper is concerned with the real time automatic discriminating of flaws from two categories; i. cracks (planar defect) and ii. Non-cracks (volumetric defect such as cluster porosity and slag) using pulse-echo ultrasound. The raw ultrasonic flaws signal were collected from a computerized robotic plane scanning system over the whole of each reflector as the primary source of data. The signal is then filtered and the analysis in both time and frequency domain were executed to obtain the selected feature. The real time feature analysis techniques measured the number of peaks, maximum index, pulse duration, rise time and fall time. The obtained features could be used to distinguish between quantitatively classified flaws by using various tools in artificial intelligence such as neural networks. The proposed algorithm and complete system were implemented in a computer software developed using Microsoft Visual BASIC 6.0 (author)

Science.gov (United States)

Male meadow voles housed in a long photoperiod (14 h light/day, LP) preferred female to male odors, whereas males maintained in a short photoperiod (10 h light/day, SP) did not display preferences for odors of either sex. These odor-preference patterns matched those of free-living males during spring and autumn, respectively. The preference of LP male voles for female over male odors was eliminated by gonadectomy and reinstated by treatment with testosterone. In SP males, although gonadectomy did not affect odor choices, a preference for female odors was induced by testosterone treatment. Treatment with estradiol did not alter odor preferences of LP or SP males. In conjunction with previous result, the present findings suggest that hormonal responsiveness of neural substrates that control odor preferences are sexually dimorphic and may reflect sex differences in reproductive strategies. PMID:1615048

CERN Document Server

A recurrent idea in the study of complex systems is that optimal information processing is to be found near bifurcation points or phase transitions. However, this heuristic hypothesis has few (if any) concrete realizations where a standard and biologically relevant quantity is optimized at criticality. Here we give a clear example of such a phenomenon: a network of excitable elements has its sensitivity and dynamic range maximized at the critical point of a non-equilibrium phase transition. Our results are compatible with the essential role of gap junctions in olfactory glomeruli and retinal ganglionar cell output. Synchronization and global oscillations also appear in the network dynamics. We propose that the main functional role of electrical coupling is to provide an enhancement of dynamic range, therefore allowing the coding of information spanning several orders of magnitude. The mechanism could provide a microscopic neural basis for psychophysical laws.

CERN Document Server

We present a new modular traffic signs recognition system, successfully applied to both American and European speed limit signs. Our sign detection step is based only on shape-detection (rectangles or circles). This enables it to work on grayscale images, contrary to most European competitors, which eases robustness to illumination conditions (notably night operation). Speed sign candidates are classified (or rejected) by segmenting potential digits inside them (which is rather original and has several advantages), and then applying a neural digit recognition. The global detection rate is ~90% for both (standard) U.S. and E.U. speed signs, with a misclassification rate 150 minutes of video. The system processes in real-time ~20 frames/s on a standard high-end laptop.

British Library Electronic Table of Contents (United Kingdom)

Electric supply industry is facing deregulation all over the world. Under deregulated power supply scenario, power transmission congestion has become more intensified and recurrent, as compared to conventional regulated power system. Congestion may lead to violation of voltage or transmission capacity limits, thus threatens the power system security and reliability. Also the growing congestion may lead to unanticipated divergent electricity pricing. Owing to these facts congestion management has become a crucial issue in the deregulated power system scenario. Fast and precise prediction of nodal congestion prices in real time deregulated/spot power market may enable market participants and system operators to keep pace with the congestion by taking preventive measures like transaction resc...

British Library Electronic Table of Contents (United Kingdom)

ObjectiveTo address the characteristics of hearing loss in patients with Turner syndrome (TS), we evaluated hearing levels of patients with TS and analyzed causative factors.Study designThirty-three patients with TS (8 to 40 years of age) were studied through the use of audiological measurements, and causative factors were explored.ResultsTwenty cases (35 of 66 ears tested) showed high-frequency (8 kHz) sensory neural hearing loss (HFQ-SNHL). Fifteen cases (26 ears) and 15 cases (24 ears) of the impaired 20 cases were unresponsive to distortion-product otoacoustic emissions and transient-evoked otoacoustic emissions, respectively. HFQ-SNHL showed little relation to the history of middle ear infection and puberty, although middle ear infections were seen in 11 of the 20 cases. The hearing t...

Energy Technology Data Exchange (ETDEWEB)

By using the continuation theorem of coincidence degree theory and constructing suitable Lyapunov functions, we study the existence and stability of periodic solution for shunting inhibitory cellular neural networks (SICNNs) with delays x-bar {sub ij}(t)=-a{sub ij}(t)x{sub ij}(t)--bar B{sup kl}-bar Nr(i,j)B{sub ij}{sup kl}(t)f{sub ij}(x{sub kl}(t))x{sub ij}(t)--bar C{sup kl}-bar Nr(i,j)C{sub ij}{sup kl}(t)g{sub ij}(x{sub kl}(t-{tau}{sub kl}))x{sub ij}(t)+L{sub ij}(t)

Science.gov (United States)

Human embryonic stem (ES) cells can undergo spontaneously differentiation in standard culture conditions, demonstrating that the undifferentiated state is relatively unstable. The heterogeneous expression of SSEA3 observed within human ES colonies, provides a means to examine undifferentiated stem cell substates. Through functional testing of single cells we have shown that undifferentiated ES cells can be segregated into functionally discrete subpopulations on the basis of SSEA3 expression: SSEA3(High), SSEA(Low) and SSEA3(Negative). Human ES subpopulations were found to be interconvertible, but they possess distinct properties when challenged to differentiate along the neural lineage. These data suggest that ES cells with pluripotent/self-renewal capacities can exhibit different responses to induction of differentiation. PMID:21763622

British Library Electronic Table of Contents (United Kingdom)

The extended mind thesis (EM) asserts that some cognitive processes are (partially) composed of actions consisting of the manipulation and exploitation of environmental structures. Might some processes at the root of social cognition have a similarly extended structure? In this paper, I argue that social cognition is fundamentally an interactive form of space management-the negotiation and management of "we-space"-and that some of the expressive actions involved in the negotiation and management of we-space (gesture, touch, facial and whole-body expressions) drive basic processes of interpersonal understanding and thus do genuine social-cognitive work. Social interaction is a kind of extended social cognition, driven and at least partially constituted by environmental (non-neural) scaffold...

British Library Electronic Table of Contents (United Kingdom)

Mechanomyography (MMG) is the muscle surface oscillations that are generated by the dimensional change of the contracting muscle fibers. Because MMG reflects the number of recruited motor units and their firing rates, just as electromyography (EMG) is influenced by these two factors, it can be used to estimate the force exerted by skeletal muscles. The aim of this study was to demonstrate the feasibility of MMG for estimating the elbow flexion force at the wrist under an isometric contraction by using an artificial neural network in comparison with EMG. We performed experiments with five subjects, and the force at the wrist and the MMG from the contributing muscles were recorded. It was found that MMG could be utilized to accurately estimate the isometric elbow flexion force based on the v...

DEFF Research Database (Denmark)

A seasonal forecasting technique to produce probabilistic and deterministic streamflow forecasts for 23 basins in Norway and northern Sweden is developed in this work. Large scale circulation and moisture fields, forecasted by the ECHAM4.5 model 4 months in advance, are used to forecast spring flows. The technique includes model output statistics (MOS) based on a non-linear Neural Network (NN) approach. Results show that streamflow forecasts from Global Circulation Model (GCM) predictions, for the Scandinavia region are viable and highest skill values were found for basins located in south-western Norway. The physical interpretation of the forecasting skill is that stations close to the Norwegian coast are directly exposed to prevailing winds from the Atlantic ocean, which constitute the principal source of predictive information from the atmosphere on the seasonal timescale.

Energy Technology Data Exchange (ETDEWEB)

The analysis of transmission line faults is essential to the proper performance of the power system. It is required if protective relays are to take the appropriate action and in monitoring the performance of relays, circuit breakers, and other protective and control elements. The detection and classification of transmission line faults is a fundamental component of such fault analysis. Another application of fault analysis is in software packages for automated analysis of digital fault recorder (DFR) files. Recently, such a package, called DFR Assistant, was developed for substation applications. This program can be installed locally in a substation, in which case it is connected directly to the DFR via a high speed parallel link, or it can be installed at a central station, in which case it can be configured to automatically analyze events coming from all DFRs.

British Library Electronic Table of Contents (United Kingdom)

Glucose homeostasis requires the tight regulation of glucose utilization by liver, muscle and white or brown fat, and glucose production and release in the blood by liver. The major goal of maintaining glycemia at -5 mM is to ensure a sufficient flux of glucose to the brain, which depends mostly on this nutrient as a source of metabolic energy. This homeostatic process is controlled by hormones, mainly glucagon and insulin, and by autonomic nervous activities that control the metabolic state of liver, muscle and fat tissue but also the secretory activity of the endocrine pancreas. Activation or inhibition of the sympathetic or parasympathetic branches of the autonomic nervous systems are controlled by glucose-excited or glucose-inhibited neurons located at different anatomical sites, mainl...

Energy Technology Data Exchange (ETDEWEB)

This two-tomes book brings together the 108 presentations given at the first conference of the international institute of refrigeration (IIF/IIR) about air conditioning in high rise office buildings. The main themes are: general design and control systems, including split systems, radiant panels, fluctuating and gravity ventilation etc..; energy consumption, optimization and heat recovery; cold storage for peak shaving, including ice slurry circulation; indoor air quality; fire and smokes protection, protection against chimney effects and lighting spots; use of fuzzy logic and of neural networks. It includes also a description of the high rise building situation and works in progress in China, Japan and in some other countries. (J.S.)

British Library Electronic Table of Contents (United Kingdom)

Action potentials from the brain control the activity of spinal neural networks to produce, by as yet unknown mechanisms, a variety of motor behaviors. Particularly lacking are details on how identified descending neurons integrate diverse sensory inputs to generate specific locomotor patterns. We have examined the operations of the principal neurons in an intriguing midbrain nucleus, the nucleus of the medial longitudinal fasciculus (nMLF), in the larval zebrafish. The nMLF is the most rostral grouping of neurons that projects from the brain well into the spinal cord of teleost fishes, yet there is little direct physiological data available regarding its function. We report here that a distinct set of large, individually-identifiable neurons in nMLF (the MeL and MeM neurons) are activated...

International Nuclear Information System (INIS)

Growing of PV for electricity generation is one of the highest in the field of the renewable energies and this tendency is expected to continue in the next years. Due to the various seasonal, hourly and daily changes in climate, it is relatively difficult to find a suitable analytic model for predicting the performance of a grid-connected photovoltaic (GCPV) plant. In this paper, an artificial neural network is used for modelling and predicting the power produced by a 20 kWp GCPV plant installed on the roof top of the municipality of Trieste (latitude 45 deg. 40'N, longitude 13 deg. 46'E), Italy. An experimental database of climate (irradiance and air temperature) and electrical (power delivered to the grid) data from January 29th to May 25th 2009 has been used. Two ANN models have been developed and implemented on experimental climate and electrical data. The first one is a multivariate model based on the solar irradiance and the air temperature, while the second ...

International Nuclear Information System (INIS)

Cadmium is a non-essential heavy metal found abundantly in the environment. Children of women exposed to cadmium during pregnancy display lower motor and perceptual abilities. High cadmium body burden in children is also related to impaired intelligence and lowered school achievement. However, little is known about the molecular and cellular basis of developmental neurotoxicity in the sensitive early life stages of animals. In this study, we explore neurological deficits caused by cadmium during early embryonic stages in zebrafish by examining regionalization of the neural tube, pattern formation and cell fate determination, commitment of proneural genes and induction of neurogenesis. We show that cadmium-treated embryos developed a smaller head with unclear boundaries between the brain subdivisions, particularly in the mid-hindbrain region. Embryos display normal anterior to posterior regionalization; however, the commitment of neural ...

Energy Technology Data Exchange (ETDEWEB)

Validation of nuclear power reactor signals is often performed by comparing signal prototypes with the actual reactor signals. The signal prototypes are often computed based on empirical data. The implementation of an estimation algorithm which can make predictions on limited data is an important issue. A new machine learning algorithm called support vector machines (SVMS) recently developed by Vladimir Vapnik and his coworkers enables a high level of generalization with finite high-dimensional data. The improved generalization in comparison with standard methods like neural networks is due mainly to the following characteristics of the method. The input data space is transformed into a high-dimensional feature space using a kernel function, and the learning problem is formulated as a convex quadratic programming problem with a unique solution. In this paper the authors have applied the SVM method for data-based state estimation in nuclear power reactors. In ...

Energy Technology Data Exchange (ETDEWEB)

A method of kinetic analysis applicable to non-isothermal oxidation processes of ceramic nanocomposites is presented using Ti-Si-C-N powder as the substrate. The nanoparticle size and phase composition were determined using high-resolution transmission electron microscopy and X-ray diffraction (XRD). Thermogravimetric measurements were carried out for powder samples in dry air in the temperature range 298-1770 K. The following heating rates were applied: 3, 5, 10, 20 K min{sup -1}. Mass spectrometry was used to analyze gaseous oxidation products and solid products were identified by the XRD technique. The Coats-Redfern equation was applied for the kinetic analysis. For each stage of the oxidation kinetic models, the best accuracy was achieved using a series of criteria, and then the A and E parameters of the Arrhenius equations were estimated. Both linear regression and artificial neural networks were applied in testing kinetic models.

Energy Technology Data Exchange (ETDEWEB)

The use of electricity is indispensable to modern life. As Macao Special Administrative Region becomes a gaming and tourism center in Asia, modeling the consumption of electricity is critical to Macao's economic development. The purposes of this paper are to conduct an extensive literature review on modeling of electricity consumption, and to identify key climatic, demographic, economic and/or industrial factors that may affect the electricity consumption of a country/city. It was identified that the five factors, namely temperature, population, the number of tourists, hotel room occupancy and days per month, could be used to characterize Macao's monthly electricity consumption. Three selected approaches including multiple regression, artificial neural network (ANN) and wavelet ANN were used to derive mathematical models of the electricity consumption. The accuracy of these models was assessed by using the mean squared error (MSE), the mean ...

Energy Technology Data Exchange (ETDEWEB)

To keep up with the speeds of modern production lines, most machine vision applications require very powerful computers (often parallel-processing machines), which process millions of points of data in real time. The human brain performs approximately 100 billion logical floating-point operations each second. That is 400 times the speed of a Cray-1 supercomputer. The right software must be developed for parallel-processing computers. The NSF has awarded Rensselaer Polytechnic Institute (Troy, N.Y.) a $2 million grant for parallel- and image-processing software research. Over the last 15 years, Rensselaer has been conducting image-processing research, including work with high-definition TV (HDTV) and image coding and understanding. A similar NSF grant has been awarded to Michigan State University (East Lansing, Mich.) Neural networks are supposed to emulate human learning patterns. These networks and their hardware implementations (neurocomputers) show a great deal ...

Energy Technology Data Exchange (ETDEWEB)

Previous work shows the presence of scale invariance and long-range correlations in ongoing and spontaneous activity of large scale brain responses (i.e. EEG), and such scaling behavior can also be modulated by simple sensory stimulus. However, little is known whether such alteration but not destruction in scaling properties also occurs during complex cognitive processing and if neuroplasticity plays any role in mediating such changes. In this study, we addressed these issues by investigating scaling properties of multivariate EEG signals obtained from two broad groups - artists and non-artists - while they performed complex tasks of perception and mental imagery of visual art objects. We found that brain regions showing increased correlation properties from rest were similar for both tasks, suggesting that brain networks responsible for visual perception are reactivated for mental imagery. Further, we observed that the two groups could be differentiated by scaling exponents and an ...

International Nuclear Information System (INIS)

Aiming at the non-stationary characteristics of differential pressure fluctuation signals of gas-liquid two-phase flow, and the slow convergence of learning and liability of dropping into local minima for BP neural networks, flow regime identification method based on Singular Value Decomposition (SVD) and Least Square Support Vector Machine (LS-SVM) is presented. First of all, the Empirical Mode Decomposition (EMD) method is used to decompose the differential pressure fluctuation signals of gas-liquid two-phase flow into a number of stationary Intrinsic Mode Functions (IMFs) components from which the initial feature vector matrix is formed. By applying the singular vale decomposition technique to the initial feature vector matrixes, the singular values are obtained. Finally, the singular values serve as the flow regime characteristic vector to be LS-SVM classifier and flow regimes are identified by the output of the classifier. The identification result of four ...

DEFF Research Database (Denmark)

The volume of cortical activation as detected by functional magnetic resonance imaging (fMRI) in the visual cortex has previously been shown to be reduced following optic neuritis (ON). In order to understand the cause of this change, we studied the cortical activation, both the size of the activated area and the signal change following ON, and compared the results with results of neuroophthalmological testing. We studied nine patients with previous acute ON and 10 healthy persons served as controls using fMRI with visual stimulation. In addition to a reduced activated volume, patients showed a reduced blood oxygenation level dependent (BOLD) signal increase and a greater asymmetry in the visual cortex, compared with controls. The volume of visual cortical activation was significantly correlated to the result of the contrast sensitivity test. The BOLD signal increase correlated significantly to both the results of the contrast sensitivity test and to the Snellen visual acuity. Our ...

International Nuclear Information System (INIS)

Acetylcholine and other neurotransmitters play unique trophic roles in brain development. Accordingly, drugs and environmental toxicants that promote or interfere with neurotransmitter function evoke neurodevelopmental abnormalities by disrupting the timing or intensity of neurotrophic actions. The current review discusses three exposure scenarios involving acetylcholine systems: nicotine from maternal smoking during pregnancy, exposure to environmental tobacco smoke (ETS), and exposure to the organophosphate insecticide, chlorpyrifos (CPF). All three have long-term, adverse effects on specific processes involved in brain cell replication and differentiation, synaptic development and function, and ultimately behavioral performance. Many of these effects can be traced to the sequence of cellular events surrounding the trophic role of acetylcholine acting on its specific cellular receptors and associated signaling cascades. However, for chlorpyrifos, additional noncholinergic mechanisms ...

Science.gov (United States)

Cancer is a severe threat to human health. Early detection is considered the best way to increase the chance for survival. While the traditional cancer detection method, biopsy, is invasive, noninvasive optical diagnostic techniques are revolutionizing the way that cancer is diagnosed. Reflectance spectroscopy is one of these optical spectroscopy techniques showing promise as a diagnostic tool for pre-cancer detection. When a neoplasia occurs in tissue, morphologic and biochemical changes happen in the tissue, which in turn results in the change of optical properties and reflectance spectroscopy. Therefore, a pre-cancer can be detected by extracting optical properties from reflectance spectroscopy. This dissertation described the construction of a fiberoptic based reflectance system and the development of a series of modeling studies. This research is aimed at establishing an improved understanding of the optical properties of mucosal tissues by analyzing reflectance signals at ...

Energy Technology Data Exchange (ETDEWEB)

The growing concern of the population with regards to the problem of atmospheric pollution has induced a change in the role of air quality monitoring networks, especially those monitoring air pollution in large cities which suffer from summer smog. The population is no longer satisfied with real-time measurements but wants to be warmed of high pollutants concentrations in advance. Some countries have been forecasting air pollution, and especially ozone, for a large number of years. Although most of them use statistical models based on the analyses of past conditions which induced high pollution episodes, some predict ozone levels using only their knowledge of the meteorological situation. Nowadays two trends appear regarding ozone forecasting: either very basic statistical methods, such as regression, or more sophisticated ones, such as neural networks. The paper then reviews several behaviours common to most forecasting models: the uncertainly due to the great ...

Energy Technology Data Exchange (ETDEWEB)

Two geochemical surveys were conducted in 1992 and 2000 respectively in the Yimeng Uplift of the Ordos Basin, China. The earlier survey grid had 1 x 5km spacing and the later survey grid had 0.5 x 0.5km spacing. The acid-extractable hydrocarbons of both surveys show similar geochemical trends. However, the anomalies obtained with traditional statistical methods do not correlate with existing oil/gas fields. This study reveals two problems in the data and their processing. The first one is interference caused by the variation of soil composition. We applied a wavelet-analysis-based method to eliminate this interference in the data of the later survey. The second is that micro-seepage anomalies did not identify existing oil/gas fields and seepage anomalies related with faults had not been previously recognized. We modified the logic multiplication cluster analysis and applied a multi-fractal model and a back propagation artificial neural network to recognize these ...

Energy Technology Data Exchange (ETDEWEB)

The present invention is a fully connected feed forward network that includes at least one hidden layer 16. The hidden layer 16 includes nodes 20 in which the output of the node is fed back to that node as an input with a unit delay produced by a delay device 24 occurring in the feedback path 22 (local feedback). Each node within each layer also receives a delayed output (crosstalk) produced by a delay unit 36 from all the other nodes within the same layer 16. The node performs a transfer function operation based on the inputs from the previous layer and the delayed outputs. The network can be implemented as analog or digital or within a general purpose processor. Two teaching methods can be used: (1) back propagation of weight calculation that includes the local feedback and the crosstalk or (2) more preferably a feed forward gradient decent which immediately follows the output computations and which also includes the local feedback and the crosstalk. Subsequent to the gradient ...

International Nuclear Information System (INIS)

Computer programs have been written to allow the analysis of different types of eddy-current probes and their performance under different steam generators test conditions. The probe types include the differential bobbin probe, the absolute bobbin probe, the pancake probe and the reflection probe. The generator test conditions include tube supports, copper deposits, magnetite deposits, denting, wastage, pitting, cracking, and intergranular attack. These studies are based mostly on computed values, with the limited number of test specimens available used to verify the computed results. The instrument readings were computed for a complete matrix of the different test conditions, and then the test conditions determined as a function of the readings by a least-squares technique. A comparison was made of the errors in fit and instrument drift for the different probe types. The computations of the change in instrument reading due to the defects have led to an inversion technique in which the ...

International Nuclear Information System (INIS)

Full text: Disorders of brain development and phakomatosis are resulting from disturbed embryonic-foetal development One third of all major embryological anomalies involve CNS, and over 2000 different anomalies have been described. Anomalies of the brain often cause foetal and neonatal death, and mental and physical retardation in pediatric group. The majority of disorders of brain development and phakomatosis are idiopathic, and most of them are not hereditary or familial. Ultrasonography plays the important role in screening foetal and neonatal brain, but after closure of fontanels it is difficult to find the acoustic window. CT has limited contrast resolution, and disadvantage exposing infant to ionizing radiation. It is helpful to demonstrate the presence of calcifications. MR imaging has proved to be a diagnostic tool of major importance in children with disorders of brain development and phakomatosis. The excellent grey/white matter differentiation and multiplanar imaging ...

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The eastern oyster (Crassostrea virginica) developed neoplastic disorders when experimentally exposed both in the laboratory and field to chemically contaminated sediment from Black Rock Harbor (BRH), Bridgeport, Connecticut. Neoplasia was observed in oysters after 30 or 60 days of continuous exposure in a laboratory flow-through system to a 20 mg/L suspension of BRH sediment plus postexposure periods of 3, 30, or 60 days. Composite tumor incidence was 13.6% for both exposures. Tumor occurrence was highest in the renal excretory epithelium, followed in order by gill, gonad, gastrointestinal, heart, and embryonic neural tissue. Regression of experimental neoplasia was not observed when the stimulus was discontinued. In field experiments, gill neoplasms developed in oysters, deployed in cages for 30 days at BRH and 36 days at a BRH dredge material disposal area in Central Long Island Sound, and kidney and gastrointestinal neoplasms developed in caged oysters deployed ...

International Nuclear Information System (INIS)

The influence of carbon monoxide (CO) exposure on regional cerebral blood flow (r-CBF) in rat brain was studied using autoradiography and "1"2"5I-IMP. Fuji computed radiography (FCR) was used to obtain improved autoradiograms in this study. R-CBF was determined in a relative measure by calculating hippocampus/cortex and putamen/cortex ratios of RI accumulation from the autoradiogram using a densitometer. Comparison of autoradiograms with pathological findings in the area of the hippocampus and putamen yield the following results. In the animals that were exposed to 6400 ppm or 10000 ppm of CO for 30 minutes, and then were followed up for 2 weeks without further exposure, r-CBF was decreased but no pathological changes occurred. In the animals that were exposed to 6400 ppm or 10000 ppm of CO, and then were followed up for 4 weeks without further exposure, pathological changes appeared. In animals exposed to 3200 ppm of CO, the r-CBF tended to recover after 4 weeks. Furthermore, ...

Energy Technology Data Exchange (ETDEWEB)

The primary goal of this project is to increase the availability and ease of access to critical data on the Mesaverde and Dakota tight gas reservoirs of the San Juan Basin. Secondary goals include tuning well log interpretations through integration of core, water chemistry and production analysis data to help identify bypassed pay zones; increased knowledge of permeability ratios and how they affect well drainage and thus infill drilling plans; improved time-depth correlations through regional mapping of sonic logs; and improved understanding of the variability of formation waters within the basin through spatial analysis of water chemistry data. The project will collect, integrate, and analyze a variety of petrophysical and well data concerning the Mesaverde and Dakota reservoirs of the San Juan Basin, with particular emphasis on data available in the areas defined as tight gas areas for purpose of FERC. A relational, geo-referenced database (a geographic information system, or GIS) ...

Energy Technology Data Exchange (ETDEWEB)

This report describes the results made in fulfillment of contract DE-FG26-02NT15451, ''Multicomponent Seismic Analysis and Calibration to Improve Recovery from Algal Mounds: Application to the Roadrunner/Towaoc Area of the Paradox Basin, Ute Mountain Ute Reservation, Colorado''. Optimizing development of highly heterogeneous reservoirs where porosity and permeability vary in unpredictable ways due to facies variations can be challenging. An important example of this is in the algal mounds of the Lower and Upper Ismay reservoirs of the Paradox Basin in Utah and Colorado. It is nearly impossible to develop a forward predictive model to delineate regions of better reservoir development, and so enhanced recovery processes must be selected and designed based upon data that can quantitatively or qualitatively distinguish regions of good or bad reservoir permeability and porosity between existing well control. Recent advances in seismic acquisition and ...