Energy Technology Data Exchange (ETDEWEB)

By characterising the microstructure, quantitative image analysis allows to draw conclusions on the mechanical properties of materials. On fine microstructures with low contrast, e.g. of hardened steels, texture analysis has to be applied for quantification. Feeding texture parameters according to Haralick into a trained neural network, a correlation between the microstructure and the hardness of the steels C45 and 100Cr6 can be achieved. (orig.)

Science.gov (United States)

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KoreaScience (Korea)

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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

Energy Technology Data Exchange (ETDEWEB)

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)

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.

Energy Technology Data Exchange (ETDEWEB)

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 ...

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.

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 ...

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)

Energy Technology Data Exchange (ETDEWEB)

The detectors used in the TS93 balloon flight produced a large volume of information for each cosmic ray trigger. Some of the data was visual in nature, other portions contained energy deposition and timing information. The data sets are amenable to conventional analysis techniques but there is no assurance that conventional techniques make full use of subtle correlations and relations amongst the detector responses. With the advent of neural network technologies, particularly adept at classification of complex phenomena, it would seem appropriate to explore the utility of neural network techniques to classify particles observed with the instruments. In this paper neural network based methodology for signal/background discrimination in a cosmic ray space experiment is discussed. Results are presented for electron and positron classification in the TS93 flight ...

Energy Technology Data Exchange (ETDEWEB)

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.

Energy Technology Data Exchange (ETDEWEB)

This paper describes the structure of dynamic neuronal ensembles (DNEs). DNEs represent a new paradigm for learning, based on biological neural networks that use variable structures. We present a computational neural element that demonstrates biological neuron functionality such as neurotransmitter feedback absolute refractory period and multiple output potentials. More specifically, we will develop a network of neural elements that have the ability to dynamically strengthen, weaken, add and remove interconnections. We demonstrate that the DNE is capable of performing dynamic modifications to neuron connections and exhibiting biological neuron functionality. In addition to its applications for learning, DNEs provide an excellent environment for testing and analysis of biological neural systems. An example of habituation and hyper-sensitization in biological ...

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...

Energy Technology Data Exchange (ETDEWEB)

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.

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.

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...

Energy Technology Data Exchange (ETDEWEB)

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.

CERN Document Server

The Elman artificial neural network (ANN) (feedback connection) was used for seismic data filtering. The recurrent connection that characterizes this network offers the advantage of storing values from the previous time step to be used in the current time step. The proposed structure has the advantage of training simplicity by a back-propagation algorithm (steepest descent). Several trials were addressed on synthetic (with 10% and 50% of random and Gaussian noise) and real seismic data using respectively 10 to 30 neurons and a minimum of 60 neurons in the hidden layer. Both an iteration number up to 4000 and arrest criteria were used to obtain satisfactory performances. Application of such networks on real data shows that the filtered seismic section was efficient. Adequate cross-validation test is done to ensure the performance of network on new data sets.

Science.gov (United States)

In this paper we propose a method for construction of feed-forward neural classifiers based on regularization and adaptive architectures. Using a penalized maximum likelihood scheme, we derive a modified form of the entropic error measure and an algebraic estimate of the test error. In conjunction with optimal brain damage pruning, a test error estimate is used to select the network architecture. The scheme is evaluated on four classification problems. PMID:12662736

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 ...

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)

BackgroundWax esters are important ingredients in cosmetics, pharmaceuticals, lubricants and other chemical industries due to their excellent wetting property. Since the naturally...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 ...

Energy Technology Data Exchange (ETDEWEB)

A model-based technique incorporating neural networks has been developed for process monitoring. The technique is intended for processes where the uncertainty in the reference model is larger than desired but where process measurements providing additional information about the behavior of the system are available. This data is used to reduce the uncertainty of the model. The technique has been implemented in a real-time system for monitoring operational changes of mechanical equipment for use in predictive maintenance applications. Tests on a peristaltic pump were conducted and demonstrate the advantages of the proposed technique.

Energy Technology Data Exchange (ETDEWEB)

A novel way to extract relevant parameters associated with the outgoing ions from nuclear reactions, obtained by digitizing the signals provided by a Bragg curve spectrometer (BCS) is presented. This allowed the implementation of a more thorough pulse-shape analysis. Due to the complexity of this task, it was required to take advantage of new and more powerful computational paradigms. This was fulfilled using a back-propagation artificial neural network (ANN) as a pattern identifier. Over training of ANNs is a common problem during the training stage. In the performance of the ANN there is a compromise between its size and the size of the training set. Here, this effect will be illustrated in relation to the problem of Bragg Curve (BC) identification. (Author)

Energy Technology Data Exchange (ETDEWEB)

This paper deals with an artificial neural network (ANN) based adaptive conventional power system stabilizer (PSS). The ANN comprises an input layer, a hidden layer and an output layer. The input vector to the ANN comprises real power (P) and reactive power (Q), while the output vector comprises optimum PSS parameters. A systematic approach for generating training set covering wide range of operating conditions, is presented. The ANN has been trained using back-propagation training algorithm. Investigations reveal that the dynamic performance of ANN based adaptive conventional PSS is quite insensitive to wide variations in loading conditions.

Energy Technology Data Exchange (ETDEWEB)

Two classes of convergent algorithms for learning continuous functions (and also regression functions) that are represented by feedforward networks, are discussed. The first class of algorithms, applicable to networks with unknown weights located only in the output layer, is obtained by utilizing the potential function methods of Aizerman et al. The second class, applicable to general feedforward networks, is obtained by utilizing the classical Robbins-Monro style stochastic approximation methods. Conditions relating the sample sizes to the error bounds are derived for both classes of algorithms using martingale-type inequalities. For concreteness, the discussion is presented in terms of neural networks, but the results are applicable to general feedforward networks, in particular to wavelet networks. The algorithms can be directly adapted ...

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.

International Nuclear Information System (INIS)

The aim of the study was to assess the usefulness of artificial neural networks (ANN) application in evaluation of scintimammography in the context of clinical data in the diagnosis of breast cancer. The results produced by ANN were compared with the diagnosis of two independent observers, nuclear medicine specialists. Material and methods: The clinical data and the numerical values derived from scintimammograms of 103 patients were the material for the study. The reference method was the result of histopathology study (core biopsy and /or FNB). Results: The overall sensitivity of physician diagnosis was 78% with specificity of 72%. The ANN produced 71% sensitivity and specificity of 73%. The physicians and ANN results were not significantly different (p=0.4619). Conclusions: Artificial neutral networks are useful tool in clinical diagnosis of breast cancer. (authors)

UK PubMed Central (United Kingdom)

BackgroundSeveral fractal and non-fractal parameters have been considered for the quantitative assessment of the vascular architecture, using a variety of test specimens and of computational...Full Text Available

British Library Electronic Table of Contents (United Kingdom)

Entorhinal grid cells in mammals fire as a function of animal location, with spatially periodic response patterns. This nonlocal periodic representation of location, a local variable, is unlike other neural codes. There is no theoretical explanation for why such a code should exist. We examined how accurately the grid code with noisy neurons allows an ideal observer to estimate location and found this code to be a previously unknown type of population code with unprecedented robustness to noise. In particular, the representational accuracy attained by grid cells over the coding range was in a qualitatively different class from what is possible with observed sensory and motor population codes. We found that a simple neural network can effectively correct the grid code. To the best of our kn...

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 ...

Energy Technology Data Exchange (ETDEWEB)

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 ...

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

International Nuclear Information System (INIS)

In order to build the safety culture for nuclear power industry, it is important to evaluate the safety culture scientifically. Considering the traits of safety culture in the nuclear power industry, 24 safety culture assessment indexes are established from 4 aspects such as Safety consciousness, Safety attitude, Safety action and Safety actuality by using the SMART criteria. Safety culture star-class assessment criterion is presented and safety culture star-class assessment system is developed by using Visual Basic 6.0 and BP neural network. The system has a better generalization ability, and it can show exactly which phase the safety culture is in. Experimental results show that safety culture star-class assessment is practical and easy to perform. (authors)

Energy Technology Data Exchange (ETDEWEB)

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)

The ensemble empirical mode decomposition (EEMD) can overcome the mode mixing problem of the empirical mode decomposition (EMD) and therefore provide more precise decomposition results. Wavelet neural network (WNN) possesses the advantages of both wavelet transform and artificial neural networks. This paper combines the merits of EEMD and WNN to propose an automated and effective fault diagnosis method of locomotive roller bearings. First, the vibration signals captured from the locomotive roller bearings are preprocessed by EEMD method and intrinsic mode functions (IMFs) are produced. Second, a kurtosis based method is presented and used to select the sensitive IMF. Third, time- and frequency-domain features are extracted from the sensitive IMF, its frequency spectrum and its envelope spe...

Energy Technology Data Exchange (ETDEWEB)

Density is useful in deducing the spatial structure of coals. In this paper, nitrogen has been used instead of the commonly employed helium, for the gas displacement pycnometer based density determination of a number of coals of Indian origin. The results show that the nitrogen-based densities are always higher than the helium-based ones. Also, empirical relationships between the helium-based and nitrogen-based coal densities have been developed by two modeling methods, namely, multi-variable regression and artificial neural networks. Although the two models have fared well, the neural network model exhibits a relatively better prediction accuracy and generalization performance than the regression model. This study thus demonstrates that nitrogen, which is cheaper and easily available, can be used gainfully as the probe gas for estimating the true density of coals. 23 refs., 1 fig., 3 tabs.

Energy Technology Data Exchange (ETDEWEB)

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

Energy Technology Data Exchange (ETDEWEB)

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 ...

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 ...

Energy Technology Data Exchange (ETDEWEB)

Hybrid models for solving unit commitment problem have been proposed in this paper. To incorporate the changes due to the addition of new constraints automatically, an expert system (ES) has been proposed. The ES combines both schedules of units to be committed based on any classical or traditional algorithms and the knowledge of experienced power system operators. A solution database, i.e. information contained in the previous schedule is used to facilitate the current solution process. The proposed ES receives the input, i.e. the unit commitment solutions from a fuzzy-neural network. The unit commitment solutions from the artificial neural network cannot offer good performance if the load patterns are dissimilar to those of the trained data. Hence, the load demands, i.e. the input to the fuzzy-neural network is considered as fuzzy variables. To take into ...

Energy Technology Data Exchange (ETDEWEB)

Multiple linear regression, principal component analysis, partial least squares, polynomial regression and artificial neural networks are popular techniques for process modeling. An industrial case study illustrates some of these technologies, with an emphasis on artificial neural networks. Experience with this and other projects indicates that while neural network models, combined with partial least squares when necessary, are an excellent tool for modeling, linear techniques may also be appropriate in some cases. Regardless of the specific method used, software analyzers are an attractive lower-cost alterative to hardware options in some monitoring applications. From a fundamental point of view, the result of chemical analysis can be considered as the dependent variable(s) of a process system having a number of independent variables. The independent variables ...

Energy Technology Data Exchange (ETDEWEB)

A knowledge based system for pitting corrosion is presented. It can be used for material selection for specific pitting corrosion conditions or to check the suitability of a chosen material. The user can enter his own knowledge. The expert system is an integration of traditional expert system technology and neural networks. (orig.)

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 ...

Energy Technology Data Exchange (ETDEWEB)

Fractal dimensional analysis was employed to obtain a quantitative measure of the morphology of polymer networks formed by UV irradiation induced polymerization of photo-reactive mesogenic monomers dissolved in a liquid crystal host medium. The fractal dimensions obtained, may be interpreted by polymer network growth following a percolation-like model for monomer concentrations well below the solubility limit. On passing the solubility limit, the polymerization process changes from a (radical chain) solution polymerization to a dispersion polymerization, with fractal dimensions decreasing and suggesting a cluster-cluster aggregation process for monomer concentrations above the solubility limit, similar to the aggregation of colloidal particles.

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 ...

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 ...

Energy Technology Data Exchange (ETDEWEB)

Distance protection, differential protection and directional comparison schemes are presently used for protecting transmission lines. Directional comparison relays are set to respond to faults in the protection zone without intentional time delay and are, therefore, used where high-speed fault clearing is needed. Artificial Neural Networks (ANNs) can handle most situations which cannot be defined sufficiently for finding a deterministic solution. The design and testing of an ANN for directional comparison protection of transmission lines are presented in this paper. Training patterns were generated using voltage and current samples for faults at various locations along a transmission line. The faults were simulated using an electromagnetic transient program and a sample three-phase power system. The performance of the proposed discriminator was checked using data simulated for testing and the fault data recorded from 240 kV and 500 kV lines. ...

Science.gov (United States)

The removal of Reactive Black 5 dye in an aqueous solution by electrocoagulation (EC) as well as addition of flocculant was investigated. The effect of operational parameters, i.e. current density, treatment time, solution conductivity and polymer dosage, was investigated. Two models, namely the artificial neural network (ANN) and the response surface method (RSM), were used to model the effect of independent variables on percentage of dye removal. The findings of this work showed that current density, treatment time and dosage of polymer had the most significant effect on percentage of dye removal (p0.8). PMID:21411950

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 ...

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 ...

CERN Document Server

Because of the stochastic nature of traffic requirement matrix, it is very difficult to get the optimal traffic distribution to minimize the delay even with adaptive routing protocol in a fixed connection network where capacity already defined for each link. Hence there is a requirement to define such a method, which could generate the optimal solution very quickly and efficiently. This paper presenting a new concept to provide the adaptive optimal traffic distribution for dynamic condition of traffic matrix using nature based intelligence methods. With the defined load and fixed capacity of links, average delay for packet has minimized with various variations of evolutionary programming and particle swarm optimization. Comparative study has given over their performance in terms of converging speed. Universal approximation capability, the key feature of feed forward neural network has applied to predict the flow ...

Science.gov (United States)

Autism is a pervasive developmental condition, characterized by impairments in non-verbal communication, social relationships and stereotypical patterns of behavior. A large body of evidence suggests that several aspects of face processing are impaired in autism, including anomalies in gaze processing, memory for facial identity and recognition of facial expressions of emotion. In search of neural markers of anomalous face processing in autism, much interest has focused on a network of brain regions that are implicated in social cognition and face processing. In this review, we will focus on three such regions, namely the STS for its role in processing gaze and facial movements, the FFA in face detection and identification and the amygdala in processing facial expressions of emotion. Much evidence suggests that a better understanding of the normal development of these specialized regions is essential for discovering the ...

Science.gov (United States)

... Accession Number : ADA111683. Title : Coherency Effects on Retinal Neural Processes (ERG) of Pseudemys. Descriptive ...

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 ...

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.

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)

In the emerging restructured power system, the congestion management (CM) has become extremely important in order to ensure the security and reliability of the system. In addition to this, lack of CM can impose a hindrance in electricity trading. This paper presents a novel, growing radial basis function neural network (GRBFNN)-based approach for CM. For achieving CM, Nodal congestion price (NCP) forecasting is performed in real time competitive power market. NCP forecasting is an effective way of price-based preventive CM as it directly indicates the presence as well as the severity of the congestion in the system. In present paper, GRBFNN has been developed for NCP forecasting dividing the whole power system into various congestion zones. An unsupervised learning vector quantization (VQ)...

International Nuclear Information System (INIS)

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 _i_j(t)=-a_i_j(t)x_i_j(t)--bar B"k"l-bar Nr(i,j)B_i_j"k"l(t)f_i_j(x_k_l(t))x_i_j(t)--bar C"k"l-bar Nr(i,j)C_i_j"k"l(t)g_i_j(x_k_l(t-#tau#_k_l))x_i_j(t)+L_i_j(t).

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)

An artificial neural network (ANN), trained as an inverse of the controlled plant, to function as a power system stabilizer (PSS) is presented in this paper. In order to make the proposed ANN PSS work properly, it was trained over the full working range of the generating unit with a large variety of disturbances. Data used to train the ANN PSS consists of the control input and the synchronous machine response with an adaptive PSS (APSS) controlling the generator. During training, the ANN was required to memorize the reverse input/output mapping of the synchronous machine. After the training, the output of the synchronous machine was applied as the input of the ANN PSS and the output of the ANN PSS was used as the control signal. Simulation results show that the proposed ANN PSS can provide good damping of the power system over a wide operating range and significantly improve the system performance.

Science.gov (United States)

Readout integrated circuits (ROICs) for focal plane arrays (FPAs) have become increasingly complex to meet the needs of modern infrared systems. BAE Systems has pioneered a number of advanced signal processing architectures for FPA ROICs. Demonstrated signal processing capabilities of BAE Systems FPAs include analog-to-digital conversion, offset subtraction, individual pixel automatic gain compensation, transient noise suppression, on-FPA defect deselection, reconfigurable pixels, spatial neural network processing and subframe noise averaging. BAE Systems FPA advanced signal processing is not just for demonstrations, but is used in many of their deliverable FPAs, improving real system performance.

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Not Available

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Not Available

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 ...

International Nuclear Information System (INIS)

The aim of the study was the attempt to evaluate the influence of two different methods of cardiac perfusion SPECT reconstruction (FBP and ITW) on clinical efficacy in diagnosing the coronary artery disease as well as the cardiac ischemia detection in three areas of heart vascularized by main coronary arteries: LAD, LCX and RCA with the use of artificial neural networks (ANN). The study was performed retrospectively with the use of the diagnostic image records as well as clinical dataset of 43 patients. Myocardial perfusion stress/rest SPECT study and X-ray coronarography data were evaluated for each patient. The results of coronary angiography were considered the reference method. The cardiac SPECT data were reconstructed using the two different methods: filtered backprojection (FBP) and iterative Wallis method (ITW). The local perfusion deficits denominated in stress and rest study in three main vessel cardiac segments were the main input ...

International Nuclear Information System (INIS)

In the rural areas, especially those located far enough from infrastructure facilities (highways and national roads, electricity and gas networks, etc.), energy supply (both quantitatively and qualitatively) is scarcer than in the urban ones. The purpose of this paper is to analyse the use of renewable energy hybrid systems in order to increase the quality and the quantity of energy supplied to the rural settlements. The paper is thus a guide of how to choose the appropriate energy source with higher potential and efficiency, minimal capital and operational costs and better comfort. (authors)

Science.gov (United States)

... This paper presents our research in neural learning for predicting ... Denote this feature set as F4. ... can be observed that the SOC curves generated by ...

CERN Document Server

Office Moves Involving Network Equipment

Science.gov (United States)

PMID:17758994

Science.gov (United States)

PMID:15029781

International Nuclear Information System (INIS)

Research highlights: #-># The building occupancy affecting the cooling load prediction is studied. #-># PENN model is adopted in this study for predicting the building cooling load. #-># Statistical approach is adopted to result a less prejudice prediction performance. #-># Results show that occupancy data can significantly improve the prediction. -- Abstract: Building cooling load prediction is one of the key factors in the success of energy-saving measures. Many computational models available in the industry today have been developed from either forward or inverse modeling approaches. However, most of these models require extensive computer resources and involve lengthy computation. This paper discusses the use of data-driven intelligent approaches, a probabilistic entropy-based neural (PENN) model to predict the cooling load of a building. Although it is common knowledge that the presence and activity of building occupants have a significant impact ...

DEFF Research Database (Denmark)

Udgivelsesdato: 2007/7

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.

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 ...

Energy Technology Data Exchange (ETDEWEB)

The project aim is to model the hybrid plant at Vaesthamnsverket in Helsingborg using artificial neural networks (ANN) and integrating the ANN models, for online condition monitoring and thermoeconomic optimization, at Vaesthamnsverket. The definition of a hybrid plant is that it uses more than one fuel, in this case a natural gas fuelled gas turbine with heat recovery steam generator (HRSG) and a biomass fuelled steam boiler with steam turbine. The project is a continuation of previous projects where ANN training was done with operational data from the plant. The ANN models have, if required, been updated to better suit the purpose of this project. The thermoeconomic optimization takes into account current electricity prices, taxes, fuel prices etc. and calculates the current production cost along with the 'predicted' production cost. The tool also has a built in feature of predicting when a compressor wash is economically ...

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 ...

Energy Technology Data Exchange (ETDEWEB)

Through the dedicated collaborative efforts of many individuals interested in supporting local education, computer laboratories were established at two urban high schools. The purchasing and implementation of the project was handled by the Alliance for Education, a local non-profit education advocate. Funds were supplied by the Air Force as part of a 3-year research activity utilizing artificial intelligence technology to tutor 9th grade students. NCR (now AT7T Global Information Solutions) corporate leaders provided the computers and network equipment at a considerable savings to the project. Each lab is a state-of-the-art facility with air-conditioning, carpeting, special computer tables, computer projection screens, and on-site technical support. Student and teacher enthusiasm toward the project has been gratifying and quantitative results are currently being evaluated for both attitude, skills, and state proficiency tests.

British Library Electronic Table of Contents (United Kingdom)

Bacterial cellulose produced by the gram-negative bacterium Gluconacetobacter xylinum was found to be an excellent native starting material for preparing shaped ultra-lightweight cellulose aerogels. The procedure comprises thorough washing and sterilization of the aquogel, quantitative solvent exchange and subsequent drying with supercritical carbon dioxide at 40 degreeC and 100 bar. The average density of the obtained dry cellulose aerogels is only about 8 mg cm-3 which is comparable to the most lightweight silica aerogels and distinctly lower than all values for cellulosic aerogels obtained from plant cellulose so far. SEM, ESEM and nitrogen adsorption experiments at 77 K reveal an open-porous network structure that consists of a comparatively high percentage of large mesopores and small...

Science.gov (United States)

... ADVANCED NETWORK SECURITY PROJECT Indiana University ... 4. TITLE AND SUBTITLE ADVANCED NETWORK SECURITY PROJECT ...

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Not Available

Energy Technology Data Exchange (ETDEWEB)

No abstract prepared.

Science.gov (United States)

PMID:10175525

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

Science.gov (United States)

Adaptive Neural Augmentation , AIAA Guidance, Navigation, and. Control Conference, Aug. 1998. [2] J. T. Kaneshige, J. Bull, and J. J. Totah, Generic Neural ...

Science.gov (United States)

OF VOCALIZED SPEECH THROUGH. ANALYSIS OF NEURAL SIGNALS. " SYNTHETIC TELEPATHY- WIRELESS. TRANSMISSION OF DECODED. THOUGHTS. " IMPLANTABLE MEMORY-ELIMINATES ...

Science.gov (United States)

... strategies. Computer and network security deals with cryptography, authentication, and attacks on software. Information ...

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Not Available

International Nuclear Information System (INIS)

Purpose: The predictive potential of tumor cell kinetic parameters may be improved when they are studied in relation to other microenvironmental parameters. The purpose of this investigation was to quantitatively categorize human tumor samples according to proliferation patterns. Second, it was examined whether these characteristics are retained after xenotransplantation. Methods and Materials: Fifty tumor samples from head-and-neck cancer patients were immunohistochemically stained for Ki-67 and vessels. Also, parts of the samples were transplanted into nude mice. Tumors were categorized according to previously described patterns of proliferation. Vascular and proliferation patterns were analyzed using an image processing system. Results: The 50 tumors were categorized into four patterns of proliferation by visual assessment: marginal (6), intermediate (10), random (21), and mixed (12). One tumor could not be classified. These patterns were quantified by ...

International Nuclear Information System (INIS)

There are several concerns which bring to consider natural gas as a viable alternative to liquid fuels in transport. First, natural gas allows the curbing of global pollution in this steadily growing industry. Indeed, decoupling greenhouse gas emissions from transport growth has become a major issue in tackling climate change. Second, a more extensive use of natural gas would relieve city air quality, which is presently at levels harmful of human health. Nonetheless, this is just one side of the coin. The other side entails building a refuelling station network, and this carries financial requirements. The financing fraction holds a pivotal role in deciding whether natural gas for automotive purposes is an efficient solution. The final aim of this work is, therefore, to compare the natural gas advantages, stemming from avoided global and local emission, with the economic rationale of engaging in supplementary model network investments. A system ...

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 ...

UK PubMed Central (United Kingdom)

A technique for quantitative determination of cephalothin and desacetylcephalothin in serum using a method based on high-pressure liquid chromatography is described. Both compounds were quantitatively...Full Text Available

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 ...

Science.gov (United States)

... UNCLASSIFIED The 60 Minute Network Security Guide ... 15. SUBJECT TERMS IATAC Collection; information security; network security 16. ...

UK PubMed Central (United Kingdom)

This article is a story of networking of palliative care at the corporate level. This gives an insight that if you have will and dedication then you can imagine and make it true that networking can...Full Text Available

Science.gov (United States)

... TITLE (Indlude Security Classifkcation) Human Factors in Network Security 12. ... FIELD GROUP SUBGROUP Human Factors, Network, Security 19. ...

Energy Technology Data Exchange (ETDEWEB)

Thermo-hygro-rheology of wood-adhesive systems plays an important role during the hot pressing process of wood based composites. The principal objective of this research is to quantitatively study the thermo-hygro rheological characteristics of wood-adhesive systems used in such composites. This is with a view to providing material characteristics which may be used in simulation models of industrial hot-pressing operations. For this purpose, a specially designed miniature hot press system mounted on a servo-hydraulic testing machine was used to compress pre-formed fiber networks. The environment for each test was maintained uniform throughout the specimen by pre-treating it inside the system until the desired conditions of temperature and moisture were achieved. Experiments were conducted under a range of test conditions of load (1 to 6 MPa), temperature (25 to 150C) and moisture content (0 to 16%). A five-element rheological model was ...

Energy Technology Data Exchange (ETDEWEB)

This paper is a result of a research with the primary purpose of extending Probabilistic Risk Assessment (PRA) modeling frameworks to include the effects of organizational factors as the deeper, more fundamental causes of accidents and incidents. There have been significant improvements in the sophistication of quantitative methods of safety and risk assessment, but the progress on techniques most suitable for organizational safety risk frameworks has been limited. The focus of this paper is on the choice of 'representational schemes' and 'techniques.' A methodology for selecting appropriate candidate techniques and their integration in the form of a 'hybrid' approach is proposed. Then an example is given through an integration of System Dynamics (SD), Bayesian Belief Network (BBN), Event Sequence Diagram (ESD), and Fault Tree (FT) in order to demonstrate the feasibility and value of hybrid ...

Energy Technology Data Exchange (ETDEWEB)

To predict air quality properly at a given location, it is necessary to identify all emission sources that will have significant impact at that location. Furthermore, the atmospheric pollutants that are emitted by these sources must be identified and quantitatively characterized. Once the air-quality predictions have been made, it is desirable to have some historical air-quality data for comparison. An efficient means of obtaining this information is through the use of detailed emission inventories and an inventory of air-quality-monitoring stations. Therefore, as part of the Alberta Government/Industry Acid Deposition Research Program (ADRP), three comprehensive inventories have been developed, namely: a sulfur dioxide (SO/sub 2/) emission inventory, a nitrogen oxides (NOx) emission inventory, and an inventory of air-quality-monitoring stations. Volume 2, Design of the Emission Inventory, presents detailed information on the classification systems, source ...

British Library Electronic Table of Contents (United Kingdom)

Transforming growth factor beta (TGF-@b) has a crucial role in the differentiation of ectodermal cells to neural or epidermal precursors. TGF-@b and bone morphogenetic protein molecules (BMPs) are involved in many developmental processes, including cell proliferation and differentiation, apoptosis, mitotic arrest and intercellular interactions during morphogenesis. Additionally, the failure of central thymic tolerance mechanisms, leading to T cells with a skewed autoreactive response, is being described as a contributor in inflammatory processes in autoimmune diseases such as multiple sclerosis. Since TGF-@b and BMP proteins are crucial for the development of the neural system and the thymus, as well as for the differentiation of T cells, it is essential to further investigate their role i...

International Science & Technology Center (ISTC)

Morphological, Electrophysiological and Behavioral Investigations of the Nervous Tissue Developed from the Embryonic Matrix Zone Cells of the Dorsolateral Walls of Lateral Ventricles, Implanted into the Lesioned Regions of the Adult Rat's Brain

UK PubMed Central (United Kingdom)

The potential of radiolabelled phenylpiperazines as agents for the detection and therapy of tumours of neural crest origin was evaluated by in vitro pharmacological studies with human neuroblastoma...Full Text Available

Science.gov (United States)

No abstract prepared.

Energy Technology Data Exchange (ETDEWEB)

Short communication.

UK PubMed Central (United Kingdom)

We study the statistical properties of a variety of diverse real-world networks. We present evidence of the occurrence of three classes of small-world networks: (a) scale-free networks,...Full Text Available

Energy Technology Data Exchange (ETDEWEB)

There is a rapidly growing need to evaluate sensor network functionality and performance in the context of the larger environment of infrastructure and applications in which the sensor network is organically embedded. This need, which is motivated by complex applications related to national security operations, leads to a paradigm fundamentally different from that of traditional data networks. In the sensor networks of interest to us, the network dynamics depend strongly on sensor activity, which in turn is triggered by events in the environment. Because the behavior of sensor networks is sensitive to these driving phenomena, the integrity of the sensed observations, measurements and resource usage by the network can widely vary. It is therefore imperative to accurately capture the environmental phenomena, and drive the simulation of the ...

Science.gov (United States)

... MAGMA © : A LIQUID SOFTWARE APPROACH TO FAULT TOLERANCE, COMPUTER NETWORK SECURITY, AND SURVIVABLE NETWORKING ...

Science.gov (United States)

Computer And Network Security: Information For Everyone: This presentation was originally prepared as the 14th talk in a series known as "The Programmer's ...

Science.gov (United States)

... Accession Number : ADA326934. Title : Analyzing and Improving Stochastic Network Security: A Multicriteria Prescriptive Risk Analysis Model. ...

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) ...

CERN Document Server

Connectivity and capacity are two fundamental properties of wireless multi-hop networks. The scalability of these properties has been a primary concern for which asymptotic analysis is a useful tool. Three related but logically distinct network models are often considered in the asymptotic analysis, i.e. the dense network model, the extended network model and the infinite network model, which consider respectively a network deployed in a finite area with a sufficiently large node density, a network deployed in a sufficiently large area with a fixed node density, and a network deployed in $\\Re^{2}$ with a sufficiently large node density. The infinite network model originated from continuum percolation theory and asymptotic results obtained from the infinite network model have ...

British Library Electronic Table of Contents (United Kingdom)

Summary: Analysis of biological networks requires assessing the statistical significance of network-based predictions by using a realistic null model. However, the existing network null model, switch randomization, is unsuitable for metabolic networks, as it does not include physical constraints and generates unrealistic reactions. We present JMassBalance, a tool for mass-balanced randomization and analysis of metabolic networks. The tool allows efficient generation of large sets of randomized networks under the physical constraint of mass balance. In addition, various structural properties of the original and randomized networks can be calculated, facilitating the identification of the salient properties of metabolic networks with a biologically meaningful null model. Availability and Imp...

Science.gov (United States)

These are some interesting sites that will help you to understand networking and how it can benefit you. These sites contain sound so you may want to wear headphones if you are in a classroom. Learn how the internet began and the basics of the www. Learn why a network is useful. Jans network contains the important concepts of networking, Work through section 7 to learn about different types of connections, transmissions, media, and configurations. Then take the quiz at the end to see how ...

UK PubMed Central (United Kingdom)

Quantitative microscopy has been extensively used in biomedical research and has provided significant insights into structure and dynamics at the cell and tissue level. The entire procedure...Full Text Available

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 ...

UK PubMed Central (United Kingdom)

This paper describes how a computerized MIS is used to assist HMO management to conduct utilization and quality of care review activities in a prepaid medical care network. The HMO is a ‘network’...Full Text Available

Science.gov (United States)

Materials World Network: Cooperative Activity in Materials Research between US Investigators and ... Program Title: Materials World Network: Cooperative Activity in Materials Research between US ...

Science.gov (United States)

Cyber attacks on a hospital's computer network is a new crime to be reckoned with. Should your hospital consider internet insurance? The author explains this new phenomenon and presents a risk assessment for determining network vulnerabilities. PMID:11951384

CERN Document Server

Many mobile ad hoc network protocols use simple flooding, in order to adapt to changes in time varying network topology. Most of the times, a network-wide flood results in redundant packets and increases network congestion, probability of packet collision, low utilization of available bandwidth, and most important, higher power consumption. In this paper, we propose a new cross-layer broadcast scheme to minimize broadcast traffic in mobile ad hoc networks. Our scheme is based on use of received signal strength indicator, RSSI, value to reduce the number of broadcast packets. The effectiveness of the proposed technique is verified using simulations.

CERN Document Server

The capability of nodes to broadcast their message to the entire wireless network when nodes employ cooperation is considered. We employ an asymptotic analysis using an extended random network setting and show that the broadcast performance strongly depends on the path loss exponent of the medium. In particular, as the size of the random network grows, the probability of broadcast in a one-dimensional network goes to zero for path loss exponents larger than one, and goes to a nonzero value for path loss exponents less than one. In two-dimensional networks, the same behavior is observed for path loss exponents above and below two, respectively.

Science.gov (United States)

... VALIDATING NETWORK SECURITY POLICIES VIA STATIC ANALYSIS OF ROUTER ACL CONFIGURATION by Eric Gregory Wen Wei Wong ...

CERN Document Server

Understanding the dependence and interplay between architecture and function in biological networks has great relevance to disease progression, biological fabrication and biological systems in general. Recent research in complex systems and networks, presents methods to properly mine the architectural interdependence in networks. Guided by such work, we propose methods to associate organism characteristics with network topology by analyzing a large number of architectural patterns. We adopt an automated approach using 11 topological metrics from complex networks to characterize a collection of various kinds of biological networks. Principal component analysis and clustering allow us to extract the indispensable, independent and informative metrics. Using hierarchical linear modeling, we observe that organism characteristics associate with these metrics, ...

Science.gov (United States)

... LIFO queue descipline outperforms FIFO in ... We consider here the stochastic network system ... All-terminal Undirected Rational Network Reliability ...

Science.gov (United States)

Recently SSBRP network security planning was formalized with the production of several .... The SSBRP Network Security. Policy was written ...

Science.gov (United States)

voluntarily provided by you. Network Traffic Logs In the course of ensuring network security and consistent service for all users, the University employs software programs to...

International Nuclear Information System (INIS)

The Superconducting super Collider Laboratory is a complex of particle accelerators being built in Ellis County, Texas. It will have a dedicated global communications network that will deliver control messages and provide for general data acquisition. This network will connect thousands of computer nodes over a very large geographic area. In order to meet the demanding availability requirements being levied on the system, it will need comprehensive network management. A large number of the computer nodes are embedded systems that traditionally do not support network management services. This presents unique challenges to standard network management practices. The Simple Network Management Protocol, SNMP, is widely accepted by industry as a tool to manage network devices. In this paper the authors examine the performance characteristics and ...

Science.gov (United States)

... execute the samples The NSA's 60 Minute Network Security Guide [NSA02], part of the Supporting Document guides section ...

Science.gov (United States)

This paper proposes an approach that mitigates the problem of verification of network security system properties over concurrent processes.

Science.gov (United States)

of a stochastic network can be a. PERT-type network. After the terminal countdown, ...... pictorial representation of a single channel queueing system ...

CERN Document Server

Network tomography aims at inferring internal network characteristics based on measurements at the edge of the network. In loss tomography, in particular, the characteristic of interest is the loss rate of individual links. There is a significant body of work dedicated to this problem using multicast and/or unicast end-to-end probes. Independently, recent advances in network coding have shown that there are several advantages from allowing intermediate nodes to process and combine, in addition to just forward, packets. In this paper, we pose the problem of loss tomography in networks that have network coding capabilities. We design a framework for estimating link loss rates, which leverages network coding capabilities and we show that it improves several aspects of tomography, including the identifiability of links, the tradeoff between ...

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We advance a tentative composite model for computer security at JPL, together with inter and intra networking with other NASA centers and overseas clients.

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The central nervous system regulates peripheral immune responses via the vagus nerve, the primary neural component of the cholinergic anti-inflammatory pathway. Electrical stimulation of the...Full Text Available

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BackgroundThe variety of ways in which faces are categorized makes face recognition challenging for both synthetic and biological vision systems. Here we focus on two face processing...Full Text Available

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Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past...Full Text Available

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Background and purpose:The chicken anterior mesenteric artery contains an outer longitudinal smooth muscle layer, whose neural regulation remains to be elucidated. ATP evokes a depolarization...Full Text Available

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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

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Ten subjects balanced their own body or a mechanically equivalent unstable inverted pendulum by hand, through a compliant spring linkage. Their balancing process was always characterized by repeated...Full Text Available

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Blindness leads to a major reorganization of neural pathways associated with touch. Because incoming somatosensory information influences motor output, it is plausible that motor plasticity occurs in...Full Text Available

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A prevailing theory proposes that the brain's two visual pathways, the ventral and dorsal, lead to differing visual processing and world representations for conscious perception than those for action....Full Text Available

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Humans are remarkably adept at identifying individuals by the sound of their voice, a behavior supported by the nervous system’s ability to integrate information from voice and speech...Full Text Available

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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

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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

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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

International Nuclear Information System (INIS)

Published in summary form only.

Energy Technology Data Exchange (ETDEWEB)

Published in summary form only.

International Nuclear Information System (INIS)

Published in summary form only.

International Nuclear Information System (INIS)

Japanese (Jan 1986). Japan Taniguchi, Yoshiyuki Torizumi, Kazutami Katu,

Energy Technology Data Exchange (ETDEWEB)

In France, groundwater usage represents 40 per cent of volumetric use, outside of thermal power plants. Groundwater represents 60 per cent of domestic and public use, 40 per cent in the industrial sector, and is increasing in the agricultural sector where it accounts for 20 per cent. Groundwater withdrawal in France has slightly increased over the last twenty years and benefited the agricultural sector. Availability throughout the territory, the consistency of resupply and natural quality has rendered groundwater a prevailing source for drinking water. Water protection and management is important and led to the adoption of legislative and regulatory measures. The Mining Code (Code minier) allows for exploitation of underground resources starting at 10 metres. The Rural Code (Code rural) mandates the declaration of public utility for water collection for the public. Protection areas are to be provided under the Public Health Code (Code de sante publique). Proper permits and ...

Science.gov (United States)

The Soldier Information Requirements Technology Demonstration (SIREQ TD) project is an experimentation program to identify technologies that significantly enhance the performance of our future soldiers. One of the study series involved a 2 x 2 factorial comparison of the benefits of digital maps over paper maps, and the use of radios vs. no radios. Thirty-two Canadian regular force infantry soldiers performed force-on-force tactical assault missions in wooded terrain, with each soldier participating in all four test conditions. The radios were configured to operate in 4 subnets: 1 channel for each of the 2 Assault Groups (4 soldiers on a channel); a Section Commander/2IC channel; and an all-users channel. Note that in the no-radio conditions soldiers still operated the press-to-talk switch to allow recording of communications, but the speaker volume was set to zero. All communications were date/time stamped, identified as to the user and channel, and the audio was digitally recorded ...

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This report describes the results obtained during Stage 13 of a long-term research and development program concerning the development of diagnostics and monitoring methods for nuclear reactors. A brief proposal for the continuation of this program in Stage 14 is also given at the end of the report. The program executed in Stage 13 consists of three parts and the work performed in each part is summarized below. 1. Study of criticality, neutron kinetics and neutron noise in molten salt reactors (MSR). Although the original goal of the investigations of the MSR in Stage 13 was to calculate the neutron noise induced by the fluctuations of the fuel temperature, the study, solution and interpretation of the static problem, as well as to define an approximate version of the point kinetic approximation was necessary to perform. As it turned out, these tasks in themselves were more involved, and also very edifying, to solve. Hence, in this report, we confine the study of the reactor physics of ...

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PMID:21398174

Science.gov (United States)

PMID:12556767

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Not Available

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"Network Physics, the only provider of physics-based network management products, today announced an additional venture round of $6 million in funding, as well as the addition of David Jones as president and CEO and Tom Dunn as vice president of sales and business development" (1 page).

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Implementing a successful local area network for a publications work-group isn't as simple as the scarcity of information on the subject would suggest. Making a network work for your requires careful planning, developing and acquiring network expertise, transforming your group's patterns of working together, and carefully managing the human and technological resources.

ScienceCinema

...english uh ? that's quite motor ...

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Recent supply chain reengineering efforts have focused on integrating firms? production, inventory and replenishment activities with the help of communication networks. While communication networks and supply chain integration facilitate optimization of traditional supply chain functions, they also exacerbate the information security risk: communication networks propagate security breaches from one firm to another, and supply chain integration causes breach on one firm to affect other firms in the supply chain. We study the impact of network security vulnerability and supply chain integration on firms? incentives to invest in information security. We find that even though an increase in either the degree of network vulnerability or the degree of supply chain integration increases the secur...

CERN Document Server

Mobile entities with wireless links are able to form a mobile ad-hoc network. Such an infrastructureless network does not have to be administrated. However, self-organizing principles have to be applied to deal with upcoming problems, e.g. information dissemination. These kinds of problems are not easy to tackle, requiring complex algorithms. Moreover, the usefulness of pure ad-hoc networks is arguably limited. Hence, enthusiasm for mobile ad-hoc networks, which could eliminate the need for any fixed infrastructure, has been damped. The goal is to overcome the limitations of pure ad-hoc networks by augmenting them with instant Internet access, e.g. via integration of UMTS respectively GSM links. However, this raises multiple questions at the technical as well as the organizational level. Motivated by characteristics of small-world networks that describe an ...

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Information security involves many branches of effort, including information assurance, host level security, physical security, and network security. Computer network security methods and implementations are given a top-down description to permit a medically focused audience to anchor this information to their daily practice. The depth of detail of network functionality and security measures, like that of the study of human anatomy, can be highly involved. Presented at the level of major gross anatomical systems, this paper will focus on network backbone implementation and perimeter defenses, then diagnostic tools, and finally the user practices (the human element). Physical security measures, though significant, have been defined as beyond the scope of this presentation.

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Use of a broadband Local Area Network (LAN) for transmission of classified and secure unclassified information requires monitoring capabilities which are sensitive to discrete segments of the network frequency spectrum. A viable monitoring system must be capable of detecting possible intrusion attempts or network malfunctions and alerting operating and security personnel. This report documents the results of an evaluation of the Magnavox CATV Systems Inc. Digital System Sentry software for network monitoring. Recommendations are made on its possible future role in broadband LAN security monitoring throughout the Nuclear Weapons Complex.

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As network bandwidth continues to grow and longer paths are used to exchange large scientific data between storage systems and GRID computation, it has become increasingly obvious that there is a need to deploy a packet drop avoidance mechanism into network transmission protocols. Current end-to-end congestion avoidance mechanisms used in Transmission Control Protocol (TCP) have worked well on low bandwidth delay product networks, but with newer high-bandwidth delay networks they have shown to be inefficient and prone to unstable. This is largely due to increased network bandwidth coupled with changes in internet traffic patterns. These changes come from a variety of new network applications that are being developed to take advantage of the increased network bandwidth. This paper will examine the end-to-end congestion avoidance mechanism and ...

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A system and method for generating global asynchronous signals in a computing structure. Particularly, a global interrupt and barrier network is implemented that implements logic for generating global interrupt and barrier signals for controlling global asynchronous operations performed by processing elements at selected processing nodes of a computing structure in accordance with a processing algorithm; and includes the physical interconnecting of the processing nodes for communicating the global interrupt and barrier signals to the elements via low-latency paths. The global asynchronous signals respectively initiate interrupt and barrier operations at the processing nodes at times selected for optimizing performance of the processing algorithms. In one embodiment, the global interrupt and barrier network is implemented in a scalable, massively parallel supercomputing device structure comprising a plurality of processing nodes interconnected ...

CERN Document Server

We consider network coding for networks experiencing worst-case bit-flip errors, and argue that this is a reasonable model for highly dynamic wireless network transmissions. We demonstrate that in this setup prior network error-correcting schemes can be arbitrarily far from achieving the optimal network throughput. We propose a new metric for errors under this model. Using this metric, we prove a new Hamming-type upper bound on the network capacity. We also show a commensurate lower bound based on GV-type codes that can be used for error-correction. The codes used to attain the lower bound are non-coherent (do not require prior knowledge of network topology). The end-to-end nature of our design enables our codes to be overlaid on classical distributed random linear network codes. Further, we free internal nodes from ...

CERN Document Server

Tensor network states are used to approximate ground states of local Hamiltonians on a lattice in D spatial dimensions. Different types of tensor network states can be seen to generate different geometries. Matrix product states (MPS) in D=1 dimensions, as well as projected entangled pair states (PEPS) in D>1 dimensions, reproduce the D-dimensional physical geometry of the lattice model; in contrast, the multi-scale entanglement renormalization ansatz (MERA) generates a (D+1)-dimensional holographic geometry. Here we focus on homogeneous tensor networks, where all the tensors in the network are copies of the same tensor, and argue that certain structural properties of the resulting many-body states are preconditioned by the geometry of the tensor network and are therefore largely independent of the choice of variational parameters. Indeed, the asymptotic decay of correlations in ...

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The Advanced Networking Integration Department at Sandia National Laboratories has used the annual Supercomputing conference sponsored by the IEEE and ACM for the past three years as a forum to demonstrate and focus communication and networking developments. For Supercomputing `95, Sandia elected: to demonstrate the functionality and capability of an AT&T Globeview 20Gbps Asynchronous Transfer Mode (ATM) switch, which represents the core of Sandia`s corporate network, to build and utilize a three node 622 megabit per second Paragon network, and to extend the DOD`s ACTS ATM Internet from Sandia, New Mexico to the conference`s show floor in San Diego, California, for video demonstrations. This paper documents those accomplishments, discusses the details of their implementation, and describes how these demonstrations supports Sandia`s overall strategies in ATM networking.

CERN Document Server

We describe a large class of chemical reaction networks, those endowed with a subtle structural property called concordance. We show that the class of concordant networks coincides precisely with the class of networks which, when taken with any weakly monotonic kinetics, invariably give rise to kinetic systems that are injective --- a quality that, among other things, precludes the possibility of switch-like transitions between distinct positive steady states. We also provide persistence characteristics of concordant networks, instability implications of discordance, and consequences of stronger variants of concordance. Some of our results are in the spirit of recent ones by Banaji and Craciun, but here we do not require that every species suffer a degradation reaction. This is especially important in studying biochemical networks, for which it is rare to have all species degrade.

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Emphasis was put on the comparative quantitative structure-activity approaches to the exploration of action mechanisms of structurally different classes of compounds showing the same type of activity...Full Text Available

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A single radial hemolysis test was developed for quantitation of specific antibody to non-hemagglutinating viruses. With the human coronaviruses as models, this test utilizes the binding properties...Full Text Available

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Gene expression data has been used in lieu of phenotype in both classical and quantitative genetic settings. These two disciplines have separate approaches to measuring and interpreting epistasis, which...Full Text Available

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The Electronic REference To access In vivo Concentrations (ERETIC) method was applied to ¹H HR-MAS spectroscopy. The accuracy, precision, and stability of ERETIC as a quantitative...Full Text Available

International Nuclear Information System (INIS)

1986. p. 390-392. Germany Brecht-Krauss, D. Kusmierek, J. Adam, WE Ulm

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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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There is a thermal range for the operation of neural circuits beyond which nervous system function is compromised. Locusta migratoria is native to the semiarid regions of the world and provides an excellent model for studying neural phenomena. In this organism previous exposure to sublethal high temperatures (heat shock, HS) can protect neuronal function against future hyperthermia but, unlike many organisms, the profound physiological adaptations are not accompanied by a robust increase of Hsp70 transcript or protein in the nervous system. We compared Hsp70 increase following HS in the tissues of isolated and gregarious locusts to investigate the effect of population density. We also localized Hsp70 in the metathoracic ganglion (MTG) of gregarious locusts to determine if HS affects Hsp70 ...

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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...