Algorithm for Training a Recurrent Multilayer Perceptron
Parlos, Alexander G.; Rais, Omar T.; Menon, Sunil K.; Atiya, Amir F.
2004-01-01
An improved algorithm has been devised for training a recurrent multilayer perceptron (RMLP) for optimal performance in predicting the behavior of a complex, dynamic, and noisy system multiple time steps into the future. [An RMLP is a computational neural network with self-feedback and cross-talk (both delayed by one time step) among neurons in hidden layers]. Like other neural-network-training algorithms, this algorithm adjusts network biases and synaptic-connection weights according to a gradient-descent rule. The distinguishing feature of this algorithm is a combination of global feedback (the use of predictions as well as the current output value in computing the gradient at each time step) and recursiveness. The recursive aspect of the algorithm lies in the inclusion of the gradient of predictions at each time step with respect to the predictions at the preceding time step; this recursion enables the RMLP to learn the dynamics. It has been conjectured that carrying the recursion to even earlier time steps would enable the RMLP to represent a noisier, more complex system.
Modular, Multilayer Perceptron
Cheng, Li-Jen; Liu, Tsuen-Hsi
1991-01-01
Combination of proposed modular, multilayer perceptron and algorithm for its operation recognizes new objects after relatively brief retraining sessions. (Perceptron is multilayer, feedforward artificial neural network fully connected and trained via back-propagation learning algorithm.) Knowledge pertaining to each object to be recognized resides in subnetwork of full network, therefore not necessary to retrain full network to recognize each new object.
Multilayer perceptron for nonlinear programming
International Nuclear Information System (INIS)
A new method for solving nonlinear programming problems within the framework of a multilayer neural network perceptron is proposed. The method employs the Penalty Function method to transform a constrained optimization problem into a sequence of unconstrained optimization problems and then solves the sequence of unconstrained optimizations of the transformed problem by training a series of multilayer perceptrons. The neural network formulation is represented in such a way that the multilayer perceptron prediction error to be minimized mimics the objective function of the unconstrained problem, and therefore, the minimization of the objective function for each unconstrained optimization is attained by training a single perceptron. The multilayer perceptron allows for the transformation of problems with two-sided bounding constraints on the decision variables x, e.g., a?xn?b, into equivalent optimization problems in which these constraints do not explicitly appear. Hence, when these are the only constraints in the problem, the transformed problem is constraint free (i.e., the transformed objective function contains no penalty terms) and is solved by training a multilayer perceptron only once. In addition, we present a new Penalty Function method for solving nonlinear programming problems that is parameter free and guarantees that feasible solutions are obtained when the optimal solution is on the boundary of the feasible region. Simulation results, includble region. Simulation results, including an example from operations research, illustrate the proposed methods.
Multidimensional scaling using multilayer perceptron
Tuovinen, Tommi
2013-01-01
The objective of this thesis is to introduce the reader to the concepts of neural network and multidimensional scaling and to demonstrate how these two can be used together. The thesis introduces a construction in which a multilayer perceptron is trained by means of multidimensional scaling in order to perform dimensionality reduction. The algorithm is tested in four different test experiments.
Auto-kernel using multilayer perceptron
Directory of Open Access Journals (Sweden)
Wei-Chen Cheng
2012-06-01
Full Text Available This work presents a constructive method to train the multilayer perceptron layer after layer successively and to accomplish the kernel used in the support vector machine. Data in different classes will be trained to map to distant points in each layer. This will ease the mapping of the next layer. A perfect mapping kernel can be accomplished successively. Those distant mapped points can be discriminated easily by a single perceptron.
Auto-kernel using multilayer perceptron
Wei-Chen Cheng
2012-01-01
This work presents a constructive method to train the multilayer perceptron layer after layer successively and to accomplish the kernel used in the support vector machine. Data in different classes will be trained to map to distant points in each layer. This will ease the mapping of the next layer. A perfect mapping kernel can be accomplished successively. Those distant mapped points can be discriminated easily by a single perceptron.
Quaternionic Multilayer Perceptron with Local Analyticity
Directory of Open Access Journals (Sweden)
Nobuyuki Matsui
2012-11-01
Full Text Available A multi-layered perceptron type neural network is presented and analyzed in this paper. All neuronal parameters such as input, output, action potential and connection weight are encoded by quaternions, which are a class of hypercomplex number system. Local analytic condition is imposed on the activation function in updating neurons’ states in order to construct learning algorithm for this network. An error back-propagation algorithm is introduced for modifying the connection weights of the network.
Quaternionic Multilayer Perceptron with Local Analyticity
Nobuyuki Matsui; Haruhiko Nishimura; Teijiro Isokawa
2012-01-01
A multi-layered perceptron type neural network is presented and analyzed in this paper. All neuronal parameters such as input, output, action potential and connection weight are encoded by quaternions, which are a class of hypercomplex number system. Local analytic condition is imposed on the activation function in updating neurons’ states in order to construct learning algorithm for this network. An error back-propagation algorithm is introduced for modifying the connection weights...
Multilayer perceptron, fuzzy sets, and classification
Pal, Sankar K.; Mitra, Sushmita
1992-01-01
A fuzzy neural network model based on the multilayer perceptron, using the back-propagation algorithm, and capable of fuzzy classification of patterns is described. The input vector consists of membership values to linguistic properties while the output vector is defined in terms of fuzzy class membership values. This allows efficient modeling of fuzzy or uncertain patterns with appropriate weights being assigned to the backpropagated errors depending upon the membership values at the corresponding outputs. During training, the learning rate is gradually decreased in discrete steps until the network converges to a minimum error solution. The effectiveness of the algorithm is demonstrated on a speech recognition problem. The results are compared with those of the conventional MLP, the Bayes classifier, and the other related models.
Fourier-Lapped Multilayer Perceptron Method for Speech Quality Assessment
Amauri Lopes; Marcos Travassos Romano, Jo O.; Jayme Garcia Arnal Barbedo; Vidal Ribeiro, Mois S.
2005-01-01
The paper introduces a new objective method for speech quality assessment called Fourier-lapped multilayer perceptron (FLMLP). This method uses an overcomplete transform based on the discrete Fourier transform (DFT) and modulated lapped transform (MLT). This transform generates the DFT and the MLT speech spectral domains from which several relevant perceptual parameters are extracted. The proposed method also employs a multilayer perceptron neural network trained by a modified version of the...
Wind speed estimation using multilayer perceptron
International Nuclear Information System (INIS)
Highlights: • We present a method for determining the average wind speed using neural networks. • We use data from that site in the short term and data from other nearby stations. • The inputs used in the ANN were wind speed and direction data from a station. • The method allows knowing the wind speed without topographical data. - Abstract: Wind speed knowledge is prerequisite in the siting of wind turbines. In consequence the wind energy use requires meticulous and specified knowledge of the wind characteristics at a location. This paper presents a method for determining the annual average wind speed at a complex terrain site by using neural networks, when only short term data are available for that site. This information is useful for preliminary calculations of the wind resource at a remote area having only a short time period of wind measurements measurement in a site. Artificial neural networks are useful for implementing non-linear process variables over time, and therefore are a useful tool for estimating the wind speed. The neural network used is multilayer perceptron with three layers and the supervised learning algorithm used is backpropagation. The inputs used in the neural network were wind speed and direction data from a single station, and the training patterns used correspond to sixty days data. The results obtained by simulating the annual average wind speed at the selected site based on data from nearby stations with correlation coefficients above 0.5 were satisfactory, compared with actual values. Reliable estimations were obtained, with errors below 6%
Efficient Estimation of Multidimensional Regression Model with Multilayer Perceptron
Rynkiewicz, Joseph
2008-01-01
This work concerns estimation of multidimensional nonlinear regression models using multilayer perceptron (MLP). The main problem with such model is that we have to know the covariance matrix of the noise to get optimal estimator. however we show that, if we choose as cost function the logarithm of the determinant of the empirical error covariance matrix, we get an asymptotically optimal estimator.
Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics
Directory of Open Access Journals (Sweden)
N. Pedroni
2008-03-01
Full Text Available Artificial neural networks are powerful algorithms for constructing nonlinear empirical models from operational data. Their use is becoming increasingly popular in the complex modeling tasks required by diagnostic, safety, and control applications in complex technologies such as those employed in the nuclear industry. In this paper, the nonlinear modeling capabilities of an infinite impulse response multilayer perceptron (IIR-MLP for nuclear dynamics are considered in comparison to static modeling by a finite impulse response multilayer perceptron (FIR-MLP and a conventional static MLP. The comparison is made with respect to the nonlinear dynamics of a nuclear reactor as investigated by IIR-MLP in a previous paper. The superior performance of the locally recurrent scheme is demonstrated.
Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics
International Nuclear Information System (INIS)
Artificial neural networks are powerful algorithms for constructing nonlinear empirical models from operational data. Their use is becoming increasingly popular in the complex modeling tasks required by diagnostic, safety, and control applications in complex technologies such as those employed in the nuclear industry. In this paper, the nonlinear modeling capabilities of an infinite impulse response multilayer perceptron (IIR-MLP) for nuclear dynamics are considered in comparison to static modeling by a finite impulse response multilayer perceptron (FIR-MLP) and a conventional static MLP. The comparison is made with respect to the nonlinear dynamics of a nuclear reactor as investigated by IIR-MLP in a previous paper. The superior performance of the locally recurrent scheme is demonstrated
Asymptotic law of likelihood ratio for multilayer perceptron models.
Rynkiewicz, Joseph
2010-01-01
We consider regression models involving multilayer perceptrons (MLP) with one hidden layer and a Gaussian noise. The data are assumed to be generated by a true MLP model and the estimation of the parameters of the MLP is done by maximizing the likelihood of the model. When the number of hidden units of the true model is known, the asymptotic distribution of the maximum likelihood estimator (MLE) and the likelihood ratio (LR) statistic is easy to compute and converge to a $\\c...
Conventional modeling of the multilayer perceptron using polynomial basis functions
Chen, Mu-Song; Manry, Michael T.
1993-01-01
A technique for modeling the multilayer perceptron (MLP) neural network, in which input and hidden units are represented by polynomial basis functions (PBFs), is presented. The MLP output is expressed as a linear combination of the PBFs and can therefore be expressed as a polynomial function of its inputs. Thus, the MLP is isomorphic to conventional polynomial discriminant classifiers or Volterra filters. The modeling technique was successfully applied to several trained MLP networks.
A Parallel Framework for Multilayer Perceptron for Human Face Recognition
Bhowmik, M K; Nasipuri, M; Basu, D K; Kundu, M
2010-01-01
Artificial neural networks have already shown their success in face recognition and similar complex pattern recognition tasks. However, a major disadvantage of the technique is that it is extremely slow during training for larger classes and hence not suitable for real-time complex problems such as pattern recognition. This is an attempt to develop a parallel framework for the training algorithm of a perceptron. In this paper, two general architectures for a Multilayer Perceptron (MLP) have been demonstrated. The first architecture is All-Class-in-One-Network (ACON) where all the classes are placed in a single network and the second one is One-Class-in-One-Network (OCON) where an individual single network is responsible for each and every class. Capabilities of these two architectures were compared and verified in solving human face recognition, which is a complex pattern recognition task where several factors affect the recognition performance like pose variations, facial expression changes, occlusions, and ...
A Choice of Input Variables for a Multilayer Perceptron
International Nuclear Information System (INIS)
In the paper some aspects of multilayer perceptron (MLP) application to the problem of classifying the events presented by empirical samples of a finite volume are considered. The results of the MLP learning for various forms of the input data are analyzed and the reasons leading to the effect of an instantaneous learning of the MLP and rise of the neural network are investigated for the case when the input data are presented in a form of variational series. The problem of hidden layer neuron reduction without raising the recognition error is discussed. (author). 13 refs., 6 figs., 1 tab
Learning of Multilayer Perceptrons with Piecewise-Linear Activation Functions.
Czech Academy of Sciences Publication Activity Database
Kozub, P.; Hole?a, Martin
Praha : Matfyzpress, 2008 - (Obdržálek, D.; Štanclová, J.; Plátek, M.), s. 27-46 ISBN 978-80-7378-076-0. [MIS 2008. Malý informatický seminá? /25./. Josef?v d?l (CZ), 12.01.2008-19.01.2008] R&D Projects: GA ?R GA201/08/0802; GA ?R GA201/08/1744 Institutional research plan: CEZ:AV0Z10300504 Keywords : artificial neural networks * multilayer perceptrons * activation functions * function approximation * constrained optimization Subject RIV: IN - Informatics, Computer Science
Prediction of Parametric Roll Resonance by Multilayer Perceptron Neural Network
DEFF Research Database (Denmark)
Míguez González, M; López Peña, F.
2011-01-01
Parametric roll resonance is a ship stability related phenomenon that generates sudden large amplitude oscillations up to 30-40 degrees of roll. This can cause severe damage, and it can put the crew in serious danger. The need for a parametric rolling real time prediction system has been acknowledged in the last few years. This work proposes a prediction system based on a multilayer perceptron (MP) neural network. The training and testing of the MP network is accomplished by feeding it with simulated data of a three degrees-of-freedom nonlinear model of a fishing vessel. The neural network is shown to be capable of forecasting the ship’s roll motion in realistic scenarios.
Online learning dynamics of multilayer perceptrons with unidentifiable parameters
International Nuclear Information System (INIS)
In the over-realizable learning scenario of multilayer perceptrons, in which the student network has a larger number of hidden units than the true or optimal network, some of the weight parameters are unidentifiable. In this case, the teacher network consists of a union of optimal subspaces included in the parameter space. The optimal subspaces, which lead to singularities, are known to affect the estimation performance of neural networks. Using statistical mechanics, we investigate the online learning dynamics of two-layer neural networks in the over-realizable scenario with unidentifiable parameters. We show that the convergence speed strongly depends on the initial parameter conditions. We also show that there is a quasi-plateau around the optimal subspace, which differs from the well-known plateaus caused by permutation symmetry. In addition, we discuss the property of the final learning state, relating this to the singular structures
Classification of fused face images using multilayer perceptron neural network
Bhattacharjee, Debotosh; Nasipuri, Mita; Basu, Dipak Kumar; Kundu, Mahantapas
2010-01-01
This paper presents a concept of image pixel fusion of visual and thermal faces, which can significantly improve the overall performance of a face recognition system. Several factors affect face recognition performance including pose variations, facial expression changes, occlusions, and most importantly illumination changes. So, image pixel fusion of thermal and visual images is a solution to overcome the drawbacks present in the individual thermal and visual face images. Fused images are projected into eigenspace and finally classified using a multi-layer perceptron. In the experiments we have used Object Tracking and Classification Beyond Visible Spectrum (OTCBVS) database benchmark thermal and visual face images. Experimental results show that the proposed approach significantly improves the verification and identification performance and the success rate is 95.07%. The main objective of employing fusion is to produce a fused image that provides the most detailed and reliable information. Fusion of multip...
Inversion of Self Potential Anomalies with Multilayer Perceptron Neural Networks
Kaftan, Ilknur; S?nd?rg?, Petek; Akdemir, Özer
2014-08-01
This study investigates the inverse solution on a buried and polarized sphere-shaped body using the self-potential method via multilayer perceptron neural networks (MLPNN). The polarization angle ( ?), depth to the centre of sphere ( h), electrical dipole moment ( K) and the zero distance from the origin ( x 0) were estimated. For testing the success of the MLPNN for sphere model, parameters were also estimated by the traditional Damped Least Squares (Levenberg-Marquardt) inversion technique (DLS). The MLPNN was first tested on a synthetic example. The performance of method was also tested for two S/N ratios (5 % and 10 %) by adding noise to the same synthetic data, the estimated model parameters with MLPNN and DLS method are satisfactory. The MLPNN also applied for the field data example in ?zmir, Urla district, Turkey, with two cross-section data evaluated by MLPNN and DLS, and the two methods showed good agreement.
Optical proximity correction using a multilayer perceptron neural network
International Nuclear Information System (INIS)
Optical proximity correction (OPC) is one of the resolution enhancement techniques (RETs) in optical lithography, where the mask pattern is modified to improve the output pattern fidelity. Algorithms are needed to generate the modified mask pattern automatically and efficiently. In this paper, a multilayer perceptron (MLP) neural network (NN) is used to synthesize the mask pattern. We employ the pixel-based approach in this work. The MLP takes the pixel values of the desired output wafer pattern as input, and outputs the optimal mask pixel values. The MLP is trained with the backpropagation algorithm, with a training set retrieved from the desired output pattern, and the optimal mask pattern obtained by the model-based method. After training, the MLP is able to generate the optimal mask pattern non-iteratively with good pattern fidelity. (paper)
Dynamics of a multi-layered perceptron model : a rigorous result
Patrick, A. E.; Zagrebnov, V. A.
1990-01-01
We derive exactly and rigorously the system of dynamical equations for a multi-layered perceptron proposed by Domany, Meir and Kinzel (DMK-model). They describes both the main and the residual overlaps evolution.
Sarkar, Arindam; Mandal, J. K.
2012-01-01
In this paper, a multilayer perceptron guided key generation for encryption/decryption (MLPKG) has been proposed through recursive replacement using mutated character code generation for wireless communication of data/information. Multilayer perceptron transmitting systems at both ends accept an identical input vector, generate an output bit and the network are trained based on the output bit which is used to form a protected variable length secret-key. For each session, dif...
Multilayer perceptron in damage detection of bridge structures
Pandey, P. C.; Barai, S. V.
1995-02-01
Recent developments in artificial neural networks (ANN) have opened up new possibilities in the domain of structural engineering. For inverse problems like structural identification of large civil engineerlng structures such as bridges and buildings where the in situ measured data are expected to be imprecise and often incomplete, the ANN holds greater promise. The detection of structural damage and identification of damaged element in a large complex structure is a challenging task indeed. This paper presents an application of multilayer perceptron in the damage detection of steel bridge structures. The ssues relating to the design of network and learning paradigm are addressed and network architectures have been developed with reference to trussed bridge structures. The training patterns are generated for multiple damaged zones in a structure and performance of the networks with one and two hidden layers are examined. It has been observed that the performance of the network with two hidden layers was better than that of a single-layer architecture in general. The engineering importance of the whole exercise is demonstrated from the fact that measured input at only a few locations in the structure is needed in the identification process using the ANN.
Classification of Log-Polar-Visual Eigenfaces using Multilayer Perceptron
Bhowmik, Mrinal Kanti; Nasipuri, Mita; Kundu, Mahantapas; Basu, Dipak Kumar
2010-01-01
In this paper we present a simple novel approach to tackle the challenges of scaling and rotation of face images in face recognition. The proposed approach registers the training and testing visual face images by log-polar transformation, which is capable to handle complicacies introduced by scaling and rotation. Log-polar images are projected into eigenspace and finally classified using an improved multi-layer perceptron. In the experiments we have used ORL face database and Object Tracking and Classification Beyond Visible Spectrum (OTCBVS) database for visual face images. Experimental results show that the proposed approach significantly improves the recognition performances from visual to log-polar-visual face images. In case of ORL face database, recognition rate for visual face images is 89.5% and that is increased to 97.5% for log-polar-visual face images whereas for OTCBVS face database recognition rate for visual images is 87.84% and 96.36% for log-polar-visual face images.
Asymptotic law of likelihood ratio for multilayer perceptron models
Rynkiewicz, Joseph
2010-01-01
We consider regression models involving multilayer perceptrons (MLP) with one hidden layer and a Gaussian noise. The data are assumed to be generated by a true MLP model and the estimation of the parameters of the MLP is done by maximizing the likelihood of the model. When the number of hidden units of the true model is known, the asymptotic distribution of the maximum likelihood estimator (MLE) and the likelihood ratio (LR) statistic is easy to compute and converge to a $\\chi^2$ law. However, if the number of hidden unit is over-estimated the Fischer information matrix of the model is singular and the asymptotic behavior of the MLE is unknown. This paper deals with this case, and gives the exact asymptotic law of the LR statistics. Namely, if the parameters of the MLP lie in a suitable compact set, we show that the LR statistics is the supremum of the square of a Gaussian process indexed by a class of limit score functions.
International Nuclear Information System (INIS)
A nonlinear multivariable empirical model is developed for a U-tube steam generator using the recurrent multilayer perceptron network as the underlying model structure. The recurrent multilayer perceptron is a dynamic neural network, very effective in the input-output modeling of complex process systems. A dynamic gradient descent learning algorithm is used to train the recurrent multilayer perceptron, resulting in an order of magnitude improvement in convergence speed over static learning algorithms. In developing the U-tube steam generator empirical model, the effects of actuator, process,and sensor noise on the training and testing sets are investigated. Learning and prediction both appear very effective, despite the presence of training and testing set noise, respectively. The recurrent multilayer perceptron appears to learn the deterministic part of a stochastic training set, and it predicts approximately a moving average response. Extensive model validation studies indicate that the empirical model can substantially generalize (extrapolate), though online learning becomes necessary for tracking transients significantly different than the ones included in the training set and slowly varying U-tube steam generator dynamics. In view of the satisfactory modeling accuracy and the associated short development time, neural networks based empirical models in some cases appear to provide a serious alternative to first principles models. Caution, however, must be exercisemodels. Caution, however, must be exercised because extensive on-line validation of these models is still warranted
Multi-objective turbomachinery optimization using a gradient-enhanced multi-layer perceptron
Duta, Mc; Duta, Md
2009-01-01
Response surface models (RSMs) have found widespread use to reduce the overall computational cost of turbomachinery blading design optimization. Recent developments have seen the successful use of gradient information alongside sampled response values in building accurate response surfaces. This paper describes the use of gradients to enhance the performance of the RSM provided by a multi-layer perceptron. Gradient information is included in the perceptron by modifying the error function such...
DEFF Research Database (Denmark)
Proud, Simon Richard
2015-01-01
A multilayer perceptron neural network cloud mask for Meteosat Second Generation SEVIRI (Spinning Enhanced Visible and Infrared Imager) images is introduced and evaluated. The model is trained for cloud detection on MSG SEVIRI daytime data. It consists of a multi-layer perceptron with one hidden sigmoid layer, trained with the error back-propagation algorithm. The model is fed by six bands of MSG data (0.6, 0.8, 1.6, 3.9, 6.2 and 10.8 ?m) with 10 hidden nodes. The multiple-layer perceptrons lead to a cloud detection accuracy of 88.96%, when trained to map two predefined values that classify cloud and clear sky. The network was further evaluated using sixty MSG images taken at different dates. The network detected not only bright thick clouds but also thin or less bright clouds. The analysis demonstrated the feasibility of using machine learning models of cloud detection in MSG SEVIRI imagery.
Charniya, Nadir N.
2013-01-01
The Multi-layer Perceptron Neural Networks (MLP NN) are well known for their simplicity, ease of training for small-scale problems, and suitability for online implementation. This paper presents the methodology and challenges in the design of near-optimal MLP NN based classifier with maximize classification accuracy under the constraints of minimum network dimension for implementation intelligent sensors.
International Nuclear Information System (INIS)
In the thesis the results of verification of multilayer perceptron (MLP) {20–41–1} application with sigmoid activation function for prediction of lateral radionuclide migration are presented. The calculated values of Cs 137 and Sr 90 volumetric activity are close to experimental measurement limits, indicating the possibility of MLP application for the solving problem. (authors)
Evolutionary Learning of Multi-Layer Perceptron Neural Networks.
Czech Academy of Sciences Publication Activity Database
Neruda, Roman; Slušný, Stanislav
Košice : Prírodovedecká fakulta, Univerzita P. J. Šafárika, 2006 - (Vojtáš, P.), s. 125-130 ISBN 80-969184-4-3. [ITAT 2006. Workshop on Theory and Practice of Information Theory . Bystrá dolina (SK), 26.09.2006-01.10.2006] R&D Projects: GA AV ?R 1ET100300419 Institutional research plan: CEZ:AV0Z10300504 Keywords : perceptron networks * learning * evolutionary algorithms Subject RIV: IN - Informatics, Computer Science
Directory of Open Access Journals (Sweden)
Flávio Clésio Silva de Souza
2014-06-01
Full Text Available The purpose of the present research is to apply a Multilayer Perceptron (MLP neural network technique to create classification models from a portfolio of Non-Performing Loans (NPLs to classify this type of credit derivative. These credit derivatives are characterized as the amount of loans that were not paid and are already overdue more than 90 days. Since these titles are, because of legislative motives, moved by losses, Credit Rights Investment Funds (FDIC performs the purchase of these debts and the recovery of the credits. Using the Multilayer Perceptron (MLP architecture of Artificial Neural Network (ANN, classification models regarding the posterior recovery of these debts were created. To evaluate the performance of the models, evaluation metrics of classification relating to the neural networks with different architectures were presented. The results of the classifications were satisfactory, given the classification models were successful in the presented economics costs structure.
Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics
Pedroni, N.; Zio, E.; Cadini, F.
2008-01-01
Artificial neural networks are powerful algorithms for constructing nonlinear empirical models from operational data. Their use is becoming increasingly popular in the complex modeling tasks required by diagnostic, safety, and control applications in complex technologies such as those employed in the nuclear industry. In this paper, the nonlinear modeling capabilities of an infinite impulse response multilayer perceptron (IIR-MLP) for nuclear dynamics are considered in comparison to static mo...
Functional Multi-Layer Perceptron: a Nonlinear Tool for Functional Data Analysis
Rossi, Fabrice; Conan-guez, Brieuc
2004-01-01
This paper is an improved version of \\cit in which we study a natural extension of Multi-Layer Perceptrons (MLP) to functional inputs. We show that fundamental results for classical MLP can be extended to functional MLP. We obtain universal approximation results that show the expressive power of functional MLP is comparable to that of numerical MLP. We obtain consistency results which imply that the estimation of optimal parameters for functional MLP is statistically well defined. We finally ...
Experts Fusion and Multilayer Perceptron Based on Belief Learning for Sonar Image Classification
Martin, Arnaud; Osswald, Christophe
2008-01-01
The sonar images provide a rapid view of the seabed in order to characterize it. However, in such as uncertain environment, real seabed is unknown and the only information we can obtain, is the interpretation of different human experts, sometimes in conflict. In this paper, we propose to manage this conflict in order to provide a robust reality for the learning step of classification algorithms. The classification is conducted by a multilayer perceptron, taking into account ...
International Nuclear Information System (INIS)
This paper deals with the controversial topic of the selection of the parameters of a genetic algorithm, in this case hierarchical, used for training of multilayer perceptron neural networks for the binary classification. The parameters to select are the crossover and mutation probabilities of the control and parametric genes and the permanency percent. The results can be considered as a guide for using this kind of algorithm.
A New Approach to Predicting Bankruptcy: Combining DEA and Multi-Layer Perceptron
Ayan Mukhopadhyay; Suman Tiwari; Ankit Narsaria; Bhaskar Roy Karmaker
2012-01-01
The question of financial health and sustenance of a firm is so intriguing that it has spanned numerous studies. For investors,stakeholders and lenders, assessing the risk associated with an enterprise is vital. Several tools have been formulated to deal with predicting the solvency of a firm. This paper attempts to combine Data Envelopment Analysis and Multi-Layer Perceptron (MLP) to suggest a new method for prediction of bankruptcy that not only focusses on historical financial data of firm...
Sartori, Michael A.; Passino, Kevin M.; Antsaklis, Panos J.
1992-01-01
In rule-based AI planning, expert, and learning systems, it is often the case that the left-hand-sides of the rules must be repeatedly compared to the contents of some 'working memory'. The traditional approach to solve such a 'match phase problem' for production systems is to use the Rete Match Algorithm. Here, a new technique using a multilayer perceptron, a particular artificial neural network model, is presented to solve the match phase problem for rule-based AI systems. A syntax for premise formulas (i.e., the left-hand-sides of the rules) is defined, and working memory is specified. From this, it is shown how to construct a multilayer perceptron that finds all of the rules which can be executed for the current situation in working memory. The complexity of the constructed multilayer perceptron is derived in terms of the maximum number of nodes and the required number of layers. A method for reducing the number of layers to at most three is also presented.
Madyastha, Raghavendra K.; Aazhang, Behnaam; Henson, Troy F.; Huxhold, Wendy L.
1992-01-01
This paper addresses the issue of applying a globally convergent optimization algorithm to the training of multilayer perceptrons, a class of Artificial Neural Networks. The multilayer perceptrons are trained towards the solution of two highly nonlinear problems: (1) signal detection in a multi-user communication network, and (2) solving the inverse kinematics for a robotic manipulator. The research is motivated by the fact that a multilayer perceptron is theoretically capable of approximating any nonlinear function to within a specified accuracy. The algorithm that has been employed in this study combines the merits of two well known optimization algorithms, the Conjugate Gradients and the Trust Regions Algorithms. The performance is compared to a widely used algorithm, the Backpropagation Algorithm, that is basically a gradient-based algorithm, and hence, slow in converging. The performances of the two algorithms are compared with the convergence rate. Furthermore, in the case of the signal detection problem, performances are also benchmarked by the decision boundaries drawn as well as the probability of error obtained in either case.
Second-Order Learning Methods for a Multilayer Perceptron
International Nuclear Information System (INIS)
First- and second-order learning methods for feed-forward multilayer neural networks are studied. Newton-type and quasi-Newton algorithms are considered and compared with commonly used back-propagation algorithm. It is shown that, although second-order algorithms require enhanced computer facilities, they provide better convergence and simplicity in usage. 13 refs., 2 figs., 2 tabs
Directory of Open Access Journals (Sweden)
Alireza Taravat
2015-02-01
Full Text Available A multilayer perceptron neural network cloud mask for Meteosat Second Generation SEVIRI (Spinning Enhanced Visible and Infrared Imager images is introduced and evaluated. The model is trained for cloud detection on MSG SEVIRI daytime data. It consists of a multi-layer perceptron with one hidden sigmoid layer, trained with the error back-propagation algorithm. The model is fed by six bands of MSG data (0.6, 0.8, 1.6, 3.9, 6.2 and 10.8 ?m with 10 hidden nodes. The multiple-layer perceptrons lead to a cloud detection accuracy of 88.96%, when trained to map two predefined values that classify cloud and clear sky. The network was further evaluated using sixty MSG images taken at different dates. The network detected not only bright thick clouds but also thin or less bright clouds. The analysis demonstrated the feasibility of using machine learning models of cloud detection in MSG SEVIRI imagery.
Multilayered perceptron neural networks to compute energy losses in magnetic cores
Energy Technology Data Exchange (ETDEWEB)
Kucuk, Ilker [Physics Department, Faculty of Arts and Sciences, Uludag University, Gorukle Campus 16059, Bursa (Turkey)]. E-mail: ikucuk@uludag.edu.tr
2006-12-15
This paper presents a new approach based on multilayered perceptrons (MLPs) to compute the specific energy losses of toroidal wound cores built from 3% SiFe 0.27 mm thick M4, 0.1 and 0.08 mm thin gauge electrical steel strips. The MLP has been trained by a back-propagation and extended delta-bar-delta learning algorithm. The results obtained by using the MLP model were compared with a commonly used conventional method. The comparison has shown that the proposed model improved loss estimation with respect to the conventional method.
ECG biometric using multilayer perceptron and radial basis function neural networks.
Mai, Vu; Khalil, Ibrahim; Meli, Christopher
2011-01-01
This paper proposes a new method to identify people using Electrocardiogram (ECG), particularly the QRS complex which has been proven to be stable against heart rate variability and convenient to be used alone as a biometric feature. 324 QRS complexes are extracted from ECGs of 18 subjects in Physionet's MIT-BIH Normal Sinus Rhythm Database (NSRDB). Multilayer Perceptron (MLP) and Radial Basis Function (RBF) neural networks are used to classify those QRS complexes. If the training data are chosen carefully to cover a wide range of input values (i.e. QRS complexes), then the classification accuracy rates can reach above 98% using MLP and 97% using RBF. PMID:22254909
Apply Multi-Layer Perceptrons Neural Network for Off-Line Signature Verification and Recognition
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Suhail Odeh
2011-11-01
Full Text Available This paper discusses the applying of Multi-layer perceptrons for signature verification and recognition using a new approach enables the user to recognize whether a signature is original or a fraud. The approach starts by scanning images into the computer, then modifying their quality through image enhancement and noise reduction, followed by feature extraction and neural network training, and finally verifies the authenticity of the signature. The paper discusses the different stages of the process including: image pre-processing, feature extraction and pattern recognition through neural networks.
Mohammad Fathian; Kia, Arash N.
2012-01-01
In this paper, the problem of predicting the exchange rate time series in the foreign exchange rate market is going to be solved using a time-delayed multilayer perceptron neural network with gold price as external factor. The input for the learning phase of the artificial neural network are the exchange rate data of the last five days plus the gold price in two different currencies of the exchange rate as the external factor for helping the artificial neural network improving its forecast ac...
Multilayered perceptron neural networks to compute energy losses in magnetic cores
International Nuclear Information System (INIS)
This paper presents a new approach based on multilayered perceptrons (MLPs) to compute the specific energy losses of toroidal wound cores built from 3% SiFe 0.27 mm thick M4, 0.1 and 0.08 mm thin gauge electrical steel strips. The MLP has been trained by a back-propagation and extended delta-bar-delta learning algorithm. The results obtained by using the MLP model were compared with a commonly used conventional method. The comparison has shown that the proposed model improved loss estimation with respect to the conventional method
An Analog Multilayer Perceptron Neural Network for a Portable Electronic Nose
Chih-Heng Pan; Hung-Yi Hsieh; Kea-Tiong Tang
2012-01-01
This study examines an analog circuit comprising a multilayer perceptron neural network (MLPNN). This study proposes a low-power and small-area analog MLP circuit to implement in an E-nose as a classifier, such that the E-nose would be relatively small, power-efficient, and portable. The analog MLP circuit had only four input neurons, four hidden neurons, and one output neuron. The circuit was designed and fabricated using a 0.18 ?m standard CMOS process with a 1.8 V supply. The powe...
Belief Propagation for Error Correcting Codes and Lossy Compression Using Multilayer Perceptrons
Mimura, Kazushi; Okada, Masato
2011-01-01
The belief propagation (BP) based algorithm is investigated as a potential decoder for both of error correcting codes and lossy compression, which are based on non-monotonic tree-like multilayer perceptron encoders. We discuss that whether the BP can give practical algorithms or not in these schemes. The BP implementations in those kind of fully connected networks unfortunately shows strong limitation, while the theoretical results seems a bit promising. Instead, it reveals it might have a rich and complex structure of the solution space via the BP-based algorithms.
Kalamatianos, Dimitrios; Liatsis, Panos; Wellstead, Peter E
2006-01-01
Near-infrared (NIR) spectroscopy is being applied to the solution of problems in many areas of biomedical and pharmaceutical research. In this paper we investigate the use of NIR spectroscopy as an analytical tool to quantify concentrations of urea, creatinine, glucose and oxyhemoglobin (HbO2). Measurements have been made in vitro with a portable spectrometer developed in our labs that consists of a two beam interferometer operating in the range of 800-2300 nm. For the data analysis a pattern recognition philosophy was used with a preprocessing stage and a multi-layer perceptron (MLP) neural network for the measurement stage. Results show that the interferogram signatures of the above compounds are sufficiently strong in that spectral range. Measurements of three different concentrations were possible with mean squared error (MSE) of the order of 10(-6). PMID:17947035
Classification of Polar-Thermal Eigenfaces using Multilayer Perceptron for Human Face Recognition
Bhowmik, Mrinal Kanti; Nasipuri, Mita; Basu, Dipak Kumar; Kundu, Mahantapas
2010-01-01
This paper presents a novel approach to handle the challenges of face recognition. In this work thermal face images are considered, which minimizes the affect of illumination changes and occlusion due to moustache, beards, adornments etc. The proposed approach registers the training and testing thermal face images in polar coordinate, which is capable to handle complicacies introduced by scaling and rotation. Polar images are projected into eigenspace and finally classified using a multi-layer perceptron. In the experiments we have used Object Tracking and Classification Beyond Visible Spectrum (OTCBVS) database benchmark thermal face images. Experimental results show that the proposed approach significantly improves the verification and identification performance and the success rate is 97.05%.
Highly Accurate Multi-layer Perceptron Neural Network for Air Data System
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H. S. Krishna
2009-11-01
Full Text Available The error backpropagation multi-layer perceptron algorithm is revisited. This algorithm is used to train and validate two models of three-layer neural networks that can be used to calibrate a 5-hole pressure probe. This paper addresses Occam's Razor problem as it describes the adhoc training methodology applied to improve accuracy and sensitivity. The trained outputs from 5-4-3 feed-forward network architecture with jump connection are comparable to second decimal digit (~0.05 accuracy, hitherto unreported in literature.Defence Science Journal, 2009, 59(6, pp.670-674, DOI:http://dx.doi.org/10.14429/dsj.59.1574
An Analog Multilayer Perceptron Neural Network for a Portable Electronic Nose
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Chih-Heng Pan
2012-12-01
Full Text Available This study examines an analog circuit comprising a multilayer perceptron neural network (MLPNN. This study proposes a low-power and small-area analog MLP circuit to implement in an E-nose as a classifier, such that the E-nose would be relatively small, power-efficient, and portable. The analog MLP circuit had only four input neurons, four hidden neurons, and one output neuron. The circuit was designed and fabricated using a 0.18 ?m standard CMOS process with a 1.8 V supply. The power consumption was 0.553 mW, and the area was approximately 1.36 × 1.36 mm2. The chip measurements showed that this MLPNN successfully identified the fruit odors of bananas, lemons, and lychees with 91.7% accuracy.
A New Approach to Predicting Bankruptcy: Combining DEA and Multi-Layer Perceptron
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Ayan Mukhopadhyay
2012-07-01
Full Text Available The question of financial health and sustenance of a firm is so intriguing that it has spanned numerous studies. For investors,stakeholders and lenders, assessing the risk associated with an enterprise is vital. Several tools have been formulated to deal with predicting the solvency of a firm. This paper attempts to combine Data Envelopment Analysis and Multi-Layer Perceptron (MLP to suggest a new method for prediction of bankruptcy that not only focusses on historical financial data of firms that filed for bankruptcy like other past studies but also takes into account the data of those firms that were likely to do so. This method thus identifies firms that have a high chance of facing bankruptcy along with those that have filed for bankruptcy. The performance of this procedure is compared with MLP. The suggested method outperforms MLP in prediction of bankruptcy.
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Mohammad Fathian
2012-04-01
Full Text Available In this paper, the problem of predicting the exchange rate time series in the foreign exchange rate market is going to be solved using a time-delayed multilayer perceptron neural network with gold price as external factor. The input for the learning phase of the artificial neural network are the exchange rate data of the last five days plus the gold price in two different currencies of the exchange rate as the external factor for helping the artificial neural network improving its forecast accuracy. The five-day delay has been chosen because of the weekly cyclic behavior of the exchange rate time series with the consideration of two holidays in a week. The result of forecasts are then compared with using the multilayer peceptron neural network without gold price external factor by two most important evaluation techniques in the literature of exchange rate prediction. For the experimental analysis phase, the data of three important exchange rates of EUR/USD, GBP/USD, and USD/JPY are used.
Burger, Harold Christopher; Schuler, Christian J.; Harmeling, Stefan
2012-01-01
Image denoising can be described as the problem of mapping from a noisy image to a noise-free image. In another paper, we show that multi-layer perceptrons can achieve outstanding image denoising performance for various types of noise (additive white Gaussian noise, mixed Poisson-Gaussian noise, JPEG artifacts, salt-and-pepper noise and noise resembling stripes). In this work we discuss in detail which trade-offs have to be considered during the training procedure. We will s...
Sanong Amaroek; Nipon Theera-Umpon; Kittichai Wantanajittikul; Sansanee Auephanwiriyakul
2010-01-01
Problem statement: Estimation of moisture contents of dried food products from their dielectric constants was an important step in moisture measurement systems. The regression models that provide good prediction performance are desirable. Approach: The Multilayer Perceptrons (MLP) and Support Vector Regression (SVR) were applied in this research to predict the moisture contents of dried longan arils from their dielectric constants. The data set was collected from 1500 samp...
LALIT KUMAR BEHERA; MAYA NAYAK; SAREETA MOHANTY
2011-01-01
This paper presents discrete wavelet transform and the S-transform based neural classifier scheme used for time series data mining of power quality events occurring due to power signal disturbances. The DWT and the S –transform are used for feature extraction and then the extracted features are classified with neural classifiers such as multilayered perceptron network (MLP) for pattern classification, data mining and subsequent knowledge discovery.
Becerra, Roberto; Joya, Gonzalo; Garci?a, Rodolfo; Vela?zque, Luis; Rodri?guez, Roberto; Pino, Carmen
2013-01-01
In this paper, we compare the performance of two different methods for the task of electrooculogram saccadic points classification in Patients with Ataxia SCA2: Multilayer Perceptrons (MLP) and Random Forest. First we segment the recordings of 6 subjects into ranges of saccadic and non-saccadic points as the basis of supervised learning. Then, we randomly select a set of cases based on the velocity profile near each selected point for training and validation purposes using percent split schem...
An application of the multilayer perceptron: Solar radiation maps in Spain
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Hontoria, L.; Aguilera, J. [Grupo Investigacion y Desarrollo en Energia Solar y Automatica, Dpto. de Ingenieria Electronica, de Telecomunicaciones y Automatica, Escuela Politecnica Superior de Jaen, Campus de las Lagunillas, Universidad de Jaen, 23071 Jaen (Spain); Zufiria, P. [Grupo de Redes Neuronales, Dpto. de Matematica Aplicada a las Tecnologias de la Informacion, ETSI Telecomunicaciones, UPM Ciudad Universitaria s/n, 28040 Madrid (Spain)
2005-11-01
In this work an application of a methodology to obtain solar radiation maps is presented. This methodology is based on a neural network system [Lippmann, R.P., 1987. An introduction to computing with neural nets. IEEE ASSP Magazine, 4-22] called Multi-Layer Perceptron (MLP) [Haykin, S., 1994. Neural Networks. A Comprehensive Foundation. Macmillan Publishing Company; Hornik, K., Stinchcombe, M., White, H., 1989. Multilayer feedforward networks are universal approximators. Neural Networks, 2(5), 359-366]. To obtain a solar radiation map it is necessary to know the solar radiation of many points spread wide across the zone of the map where it is going to be drawn. For most of the locations all over the world the records of these data (solar radiation in whatever scale, daily or hourly values) are non-existent. Only very few locations have the privilege of having good meteorological stations where records of solar radiation have being registered. But even in those locations with historical records of solar data, the quality of these solar series is not as good as it should be for most purposes. In addition, to draw solar radiation maps the number of points on the maps (real sites) that it is necessary to work with makes this problem difficult to solve. Nevertheless, with the application of the methodology proposed in this paper, this problem has been solved and solar radiation maps have been obtained for a small region of Spain: Jaen province, a southern province of Spain between parallels 38{sup o}25' N and 37{sup o}25' N, and meridians 4{sup o}10' W and 2{sup o}10' W, and for a larger region: Andalucia, the most southern region of Spain situated between parallels 38{sup o}40' N and 36{sup o}00' N, and meridians 7{sup o}30' W and 1{sup o}40' W. (author)
Tfwala, Samkele S; Wang, Yu-Min; Lin, Yu-Chieh
2013-01-01
Hydrological data are often missing due to natural disasters, improper operation, limited equipment life, and other factors, which limit hydrological analysis. Therefore, missing data recovery is an essential process in hydrology. This paper investigates the accuracy of artificial neural networks (ANN) in estimating missing flow records. The purpose is to develop and apply neural networks models to estimate missing flow records in a station when data from adjacent stations is available. Multilayer perceptron neural networks model (MLP) and coactive neurofuzzy inference system model (CANFISM) are used to estimate daily flow records for Li-Lin station using daily flow data for the period 1997 to 2009 from three adjacent stations (Nan-Feng, Lao-Nung and San-Lin) in southern Taiwan. The performance of MLP is slightly better than CANFISM, having R (2) of 0.98 and 0.97, respectively. We conclude that accurate estimations of missing flow records under the complex hydrological conditions of Taiwan could be attained by intelligent methods such as MLP and CANFISM. PMID:24453876
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Alejandro J. Orozco-Naranjo
2013-11-01
Full Text Available This paper presents the results obtained by developing a methodology to detect 5 types of heartbeats (Normal (N, Right bundle branch block (RBBB, Left bundle branch block (LBBB, Premature atrial contraction (APC and Premature ventricular contraction (PVC, using Wavelet transform packets with non-adaptative mode applied on features extraction from heartbeats. It was used the Shannon function to calculate the entropy and It was added an identification nodes stage per every type of cardiac signal in the Wavelet tree. The using of Wavelet packets transform allows the access to information which results of decomposition of low and high frecuency, giving providing a more integral analysis than achieved by the discrete Wavelet transform. Three families of mother Wavelet were evaluated on transformation: Daubechies, Symlet and Reverse Biorthogonal, which were results from a previous research in that were identified the mother Wavelet that had higher entropy with the cardiac signals. With non-adaptive mode, the computational cost is reduced when Wavelet packets are used; this cost represents the most marked disadvantage from the transform. To classify the heartbeats were used Support Vector Machines and Multilayer Perceptron. The best classification error was achieved employing Support Vector Machine and a radial basis function; it was 2.57 %.
Estimate of significant wave height from non-coherent marine radar images by multilayer perceptrons
Vicen-Bueno, Raúl; Lido-Muela, Cristina; Nieto-Borge, José Carlos
2012-12-01
One of the most relevant parameters to characterize the severity of ocean waves is the significant wave height ( H s ). The estimate of H s from remotely sensed data acquired by non-coherent X-band marine radars is a problem not completely solved nowadays. A method commonly used in the literature (standard method) uses the square root of the signal-to-noise ratio (SNR) to linearly estimate H s . This method has been widely used during the last decade, but it presents some limitations, especially when swell-dominated sea states are present. To overcome these limitations, a new non-linear method incorporating additional sea state information is proposed in this article. This method is based on artificial neural networks (ANNs), specifically on multilayer perceptrons (MLPs). The information incorporated in the proposed MLP-based method is given by the wave monitoring system (WaMoS II) and concerns not only to the square root of the SNR, as in the standard method, but also to the peak wave length and mean wave period. Results for two different platforms (Ekofisk and FINO 1) placed in different locations of the North Sea are presented to analyze whether the proposed method works regardless of the sea states observed in each location or not. The obtained results empirically demonstrate how the proposed non-linear solution outperforms the standard method regardless of the environmental conditions (platform), maintaining real-time properties.
Face Recognition through Multilayer Perceptron (MLP and Learning Vector Quantization (LVQ
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Dr. Ikvinderpal Singh
2012-12-01
Full Text Available Face recognition is challenging problems and there is still a lot of work that needs to be done in this area. Over the past ten years, face recognition has received substantial attention from researchers in biometrics, pattern recognition, computer vision, and cognitive psychology communities. This common interest in facial recognition technology among researchers working in diverse fields is motivated both by the remarkable ability to recognize people and by the increased attention being devoted to security applications. Applications of face recognition can be found in security, tracking, multimedia, and entertainment domains.This paper presents a face recognition system using artificial neural network. Here, we have designed a neural network with some own set network parameters. The results presented here have been obtained using two basic methods: multilayer perceptron (MLP, and learning vector quantization (LVQ. In both cases, two kinds of data have been fed to the classifiers: reduced resolution images (gray level or segmented, and feature vectors. The experimental results also show that, for the approaches considered here, analyzing gray level images produced better results than analyzing geometrical features, either because of the errors introduced during their extraction or because the original images have a richer information content. Furthermore, training times were much shorter for LVQ than for MLP. On the other hand, MLP achieved lower error rates when dealing with geometrical features.
Using multilayer perceptron and a satellite image for the estimation of soil salinity
International Nuclear Information System (INIS)
Applying the model of the Perceptron multilayer with momentum of an artificial neural network particularly and a multispectral image of high resolution spatial and radiometric, for the first time estimated the salinity of the soil cultivated with sugar cane. The study area is the UBPC 'Lazaro Romero' of the sugar company 'Hector Molina' of the locality San Nicolas de Bari, Havana province, located at 22° 44' North latitude and 81 ° 56' longitude West. The experiments were made in the framework of the El-479 project funded by the Inter universities Council of Flanders, Belgium. 36 samples geo referenced of soils were taken at 3 depths in each of the 4 sugar cane selected blocks, which determined the electrical conductivity of the saturation extract; half of that amount of data was used for the training of the network and the other half for control in a computer program of the artificial neural network created to that effect, together with the reflectance of vegetation indexes for the image, which were maps of electrical conductivity of each block and bands. They were compared with those obtained by simple linear regression between the normalized difference vegetation index and electrical conductivity, Ndv with the approach of the neuronal network, the correlation coefficient was 0.78 to 0.83, while the linear regression was between 0.65 to 0.75
Geomagnetic Dst index forecast using a multilayer perceptrons artificial neural network
International Nuclear Information System (INIS)
Complete text of publication follows. The best known manifestations of the impact of solar wind on the magnetosphere are the geomagnetic storms. The prediction of geomagnetic field behavior allows the alert of geomagnetic storms occurrence, as those phenomena can cause many damages in the planet. The Artificial Intelligence tools have been applied in many multidisciplinary studies, covering several areas of knowledge, as a choice of approach to the solution of problems with characteristics like non-linearity, imprecision, and other features that can not be easily solved with conventional computational models. Techniques such as Artificial Neural Networks, Expert Systems and Decision Trees have been used in the Space Weather studies to perform tasks such as forecasting geomagnetic storms and the investigation of rules and parameters related on its occurrence. The main focus of this work is on forecasting the geomagnetic field behavior, represented this time by the Dst index, using for that task, mainly, the interplanetary magnetic field components and solar wind data. The tool chosen here to solve the non-linear problem was a Multi-layer Perceptrons Artificial Neural Network, trained with the backpropagation algorithm. Unlike what was done in other studies, we chose to predict calm and disturbed periods like, for example, a full month of data, for application in a real time forecasting system. It was possible to predict the geomagnetic Dst index one or two hours beforemagnetic Dst index one or two hours before with great percentage efficiency.
An Automated MR Image Segmentation System Using Multi-layer Perceptron Neural Network
Amiri, S; Movahedi, M M; Kazemi, K; Parsaei, H
2013-01-01
Background: Brain tissue segmentation for delineation of 3D anatomical structures from magnetic resonance (MR) images can be used for neuro-degenerative disorders, characterizing morphological differences between subjects based on volumetric analysis of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF), but only if the obtained segmentation results are correct. Due to image artifacts such as noise, low contrast and intensity non-uniformity, there are some classification errors in the results of image segmentation. Objective: An automated algorithm based on multi-layer perceptron neural networks (MLPNN) is presented for segmenting MR images. The system is to identify two tissues of WM and GM in human brain 2D structural MR images. A given 2D image is processed to enhance image intensity and to remove extra cerebral tissue. Thereafter, each pixel of the image under study is represented using 13 features (8 statistical and 5 non- statistical features) and is classified using a MLPNN into one of the three classes WM and GM or unknown. Results: The developed MR image segmentation algorithm was evaluated using 20 real images. Training using only one image, the system showed robust performance when tested using the remaining 19 images. The average Jaccard similarity index and Dice similarity metric for the GM and WM tissues were estimated to be 75.7 %, 86.0% for GM, and 67.8% and 80.7%for WM, respectively. Conclusion: The obtained performances are encouraging and show that the presented method may assist with segmentation of 2D MR images especially where categorizing WM and GM is of interest. PMID:25505757
Cross Validation Evaluation for Breast Cancer Prediction Using Multilayer Perceptron Neural Networks
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Shirin A. Mojarad
2011-01-01
Full Text Available Problem statement: The presence of metastasis in the regional lymph nodes is the most important factor in predicting prognosis in breast cancer. Many biomarkers have been identified that appear to relate to the aggressive behaviour of cancer. However, the nonlinear relation of these markers to nodal status and also the existence of complex interaction between markers have prohibited an accurate prognosis. Approach: The aim of this study is to investigate the effectiveness of a Multilayer Perceptron (MLP for predicting breast cancer progression using a set of four biomarkers of breast tumors. The biomarkers include DNA ploidy, cell cycle distribution (G0G1/G2M, steroid receptors (ER/PR and S-Phase Fraction (SPF. A further objective of the study is to explore the predictive potential of these markers in defining the state of nodal involvement in breast cancer. Two methods of outcome evaluation viz. stratified and simple k-fold Cross Validation (CV are studied in order to assess their accuracy and reliability for neural network validation. Criteria such as output accuracy, sensitivity and specificity are used for selecting the best validation technique besides evaluating the network outcome for different combinations of markers. Results: The results show that stratified 2-fold CV is more accurate and reliable compared to simple k-fold CV as it obtains a higher accuracy and specificity and also provides a more stable network validation in terms of sensitivity. Best prediction results are obtained by using an individual marker-SPF which obtains an accuracy of 65%. Conclusion/Recommendations: Our findings suggest that MLP-based analysis provides an accurate and reliable platform for breast cancer prediction given that an appropriate design and validation method is employed.
International Nuclear Information System (INIS)
The problem of pion-electron identification based on their energy losses in the TRD is considered in the frame of the CBM experiment. For particles identification an artificial neural network (ANN) was used, a multilayer perceptron realized in JETNET and ROOT packages. It is demonstrated that, in order to get correct and comparable results, it is important to define the network structure correctly. The recommendations for such a selection are given. In order to achieve an acceptable level of pions suppression, the energy losses need to be transformed to more 'effective' variables. The dependency of ANN output threshold for a fixed portion of electron loss on the particle momentum is presented
Fast accurate MEG source localization using a multilayer perceptron trained with real brain noise
International Nuclear Information System (INIS)
Iterative gradient methods such as Levenberg-Marquardt (LM) are in widespread use for source localization from electroencephalographic (EEG) and magnetoencephalographic (MEG) signals. Unfortunately, LM depends sensitively on the initial guess, necessitating repeated runs. This, combined with LM's high per-step cost, makes its computational burden quite high. To reduce this burden, we trained a multilayer perceptron (MLP) as a real-time localizer. We used an analytical model of quasistatic electromagnetic propagation through a spherical head to map randomly chosen dipoles to sensor activities according to the sensor geometry of a 4D Neuroimaging Neuromag-122 MEG system, and trained a MLP to invert this mapping in the absence of noise or in the presence of various sorts of noise such as white Gaussian noise, correlated noise, or real brain noise. A MLP structure was chosen to trade off computation and accuracy. This MLP was trained four times, with each type of noise. We measured the effects of initial guesses on LM performance, which motivated a hybrid MLP-start-LM method, in which the trained MLP initializes LM. We also compared the localization performance of LM, MLPs, and hybrid MLP-start-LMs for realistic brain signals. Trained MLPs are much faster than other methods, while the hybrid MLP-start-LMs are faster and more accurate than fixed-4-start-LM. In particular, the hybrid MLP-start-LM initialized by a MLP trained with the real brain noise dataset is 60 times fase real brain noise dataset is 60 times faster and is comparable in accuracy to random-20-start-LM, and this hybrid system (localization error: 0.28 cm, computation time: 36 ms) shows almost as good performance as optimal-1-start-LM (localization error: 0.23 cm, computation time: 22 ms), which initializes LM with the correct dipole location. MLPs trained with noise perform better than the MLP trained without noise, and the MLP trained with real brain noise is almost as good an initial guesser for LM as the correct dipole location. (author) )
An Optical Thresholding Perceptron
Saxena, Indu; Moerland, Perry; Fiesler, Emile; Pourzand, A. R.; Collings, N.
1997-01-01
An implementation of an optical perceptron with a soft optical threshold trained with an adapted BP algorithm is described as a precursor to an optical multilayer perceptron (MLP). It has 64 inputs and ten outputs. The soft threshold is implemented by a liquid crystal light valve. Experimental results on perceptron recall are also reported. The effect of a modified grey-scale to weight mapping for weight levels implemented by LCTVs is evaluated based on the results of handwritten digit recogn...
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Hadi Memarian
2012-10-01
Full Text Available Prediction of highly non-linear behavior of suspended sediment flow in rivers has prime importance in environmental studies and watershed management. In this study, the predictive performance of two Artificial Neural Networks (ANNs, namely Radial Basis Function (RBF and Multi-Layer Perceptron (MLP were compared. Time series data of daily suspended sediment discharge and water discharge at the Langat River, Malaysia were used for training and testing the networks. Mean Square Error (MSE, Normalized Mean Square Error (NMSE and correlation coefficient (r were used for performance evaluation of the models. Using the testing data set, both models produced a similar level of robustness in sediment load simulation. The MLP network model showed a slightly better output than the RBF network model in predicting suspended sediment discharge, especially in the training process. However, both ANNs showed a weak robustness in estimating large magnitudes of sediment load.
Burger, Harold Christopher; Schuler, Christian J.; Harmeling, Stefan
2012-01-01
Image denoising can be described as the problem of mapping from a noisy image to a noise-free image. The best currently available denoising methods approximate this mapping with cleverly engineered algorithms. In this work we attempt to learn this mapping directly with plain multi layer perceptrons (MLP) applied to image patches. We will show that by training on large image databases we are able to outperform the current state-of-the-art image denoising methods. In addition,...
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Alireza Taravat
2014-12-01
Full Text Available Oil spills represent a major threat to ocean ecosystems and their environmental status. Previous studies have shown that Synthetic Aperture Radar (SAR, as its recording is independent of clouds and weather, can be effectively used for the detection and classification of oil spills. Dark formation detection is the first and critical stage in oil-spill detection procedures. In this paper, a novel approach for automated dark-spot detection in SAR imagery is presented. A new approach from the combination of adaptive Weibull Multiplicative Model (WMM and MultiLayer Perceptron (MLP neural networks is proposed to differentiate between dark spots and the background. The results have been compared with the results of a model combining non-adaptive WMM and pulse coupled neural networks. The presented approach overcomes the non-adaptive WMM filter setting parameters by developing an adaptive WMM model which is a step ahead towards a full automatic dark spot detection. The proposed approach was tested on 60 ENVISAT and ERS2 images which contained dark spots. For the overall dataset, an average accuracy of 94.65% was obtained. Our experimental results demonstrate that the proposed approach is very robust and effective where the non-adaptive WMM & pulse coupled neural network (PCNN model generates poor accuracies.
Time series modeling with pruned multi-layer perceptron and 2-stage damped least-squares method
International Nuclear Information System (INIS)
A Multi-Layer Perceptron (MLP) defines a family of artificial neural networks often used in TS modeling and forecasting. Because of its ''black box'' aspect, many researchers refuse to use it. Moreover, the optimization (often based on the exhaustive approach where ''all'' configurations are tested) and learning phases of this artificial intelligence tool (often based on the Levenberg-Marquardt algorithm; LMA) are weaknesses of this approach (exhaustively and local minima). These two tasks must be repeated depending on the knowledge of each new problem studied, making the process, long, laborious and not systematically robust. In this paper a pruning process is proposed. This method allows, during the training phase, to carry out an inputs selecting method activating (or not) inter-nodes connections in order to verify if forecasting is improved. We propose to use iteratively the popular damped least-squares method to activate inputs and neurons. A first pass is applied to 10% of the learning sample to determine weights significantly different from 0 and delete other. Then a classical batch process based on LMA is used with the new MLP. The validation is done using 25 measured meteorological TS and cross-comparing the prediction results of the classical LMA and the 2-stage LMA
Taravat, Alireza; Oppelt, Natascha
2014-01-01
Oil spills represent a major threat to ocean ecosystems and their environmental status. Previous studies have shown that Synthetic Aperture Radar (SAR), as its recording is independent of clouds and weather, can be effectively used for the detection and classification of oil spills. Dark formation detection is the first and critical stage in oil-spill detection procedures. In this paper, a novel approach for automated dark-spot detection in SAR imagery is presented. A new approach from the combination of adaptive Weibull Multiplicative Model (WMM) and MultiLayer Perceptron (MLP) neural networks is proposed to differentiate between dark spots and the background. The results have been compared with the results of a model combining non-adaptive WMM and pulse coupled neural networks. The presented approach overcomes the non-adaptive WMM filter setting parameters by developing an adaptive WMM model which is a step ahead towards a full automatic dark spot detection. The proposed approach was tested on 60 ENVISAT and ERS2 images which contained dark spots. For the overall dataset, an average accuracy of 94.65% was obtained. Our experimental results demonstrate that the proposed approach is very robust and effective where the non-adaptive WMM & pulse coupled neural network (PCNN) model generates poor accuracies. PMID:25474376
International Nuclear Information System (INIS)
Critical heat flux (CHF) is an important parameter for the design of nuclear reactors. Although many experimental and theoretical researches have been performed, there is not a single correlation to predict CHF because it is influenced by many parameters. These parameters are based on fixed inlet, local and fixed outlet conditions. Artificial neural networks (ANNs) have been applied to a wide variety of different areas such as prediction, approximation, modeling and classification. In this study, two types of neural networks, radial basis function (RBF) and multilayer perceptron (MLP), are trained with the experimental CHF data and their performances are compared. RBF predicts CHF with root mean square (RMS) errors of 0.24%, 7.9%, 0.16% and MLP predicts CHF with RMS errors of 1.29%, 8.31% and 2.71%, in fixed inlet conditions, local conditions and fixed outlet conditions, respectively. The results show that neural networks with RBF structure have superior performance in CHF data prediction over MLP neural networks. The parametric trends of CHF obtained by the trained ANNs are also evaluated and results reported
Time series modeling with pruned multi-layer perceptron and 2-stage damped least-squares method
Voyant, Cyril; Tamas, Wani; Paoli, Christophe; Balu, Aurélia; Muselli, Marc; Nivet, Marie-Laure; Notton, Gilles
2014-03-01
A Multi-Layer Perceptron (MLP) defines a family of artificial neural networks often used in TS modeling and forecasting. Because of its "black box" aspect, many researchers refuse to use it. Moreover, the optimization (often based on the exhaustive approach where "all" configurations are tested) and learning phases of this artificial intelligence tool (often based on the Levenberg-Marquardt algorithm; LMA) are weaknesses of this approach (exhaustively and local minima). These two tasks must be repeated depending on the knowledge of each new problem studied, making the process, long, laborious and not systematically robust. In this paper a pruning process is proposed. This method allows, during the training phase, to carry out an inputs selecting method activating (or not) inter-nodes connections in order to verify if forecasting is improved. We propose to use iteratively the popular damped least-squares method to activate inputs and neurons. A first pass is applied to 10% of the learning sample to determine weights significantly different from 0 and delete other. Then a classical batch process based on LMA is used with the new MLP. The validation is done using 25 measured meteorological TS and cross-comparing the prediction results of the classical LMA and the 2-stage LMA.
International Nuclear Information System (INIS)
Highlights: • Multilayer perceptrons are used to simulate the I–V curve of thin-film PV modules. • APE from the spectral irradiance was added as an input variable to the network. • A self-organised map is used to select the curves used for training the network. • Curve error and maximum power error decrease when using this technique. • This method could provide accurate estimation of the output of a PV plant. - Abstract: In this paper, we propose the use of a methodology to characterise the electrical parameters of several thin-film photovoltaic module technologies. This methodology allows us to use not only solar irradiance and module temperature as classical models do, but also spectral distribution of solar radiation. The methodology is based on the use of neural network models. From all measured I–V curves of a module, a previous selection of them has been used in order to train the neural network model. This selection is performed using a Kohonen self-organising map fed with spectral data. This spectral information has been added as an input to the neural network itself. The results show that the incorporation of spectral measurements to simulate thin-film modules improves significantly both the fitting of the predicted I–V curve to the measured one and the peak power point estimation
Directory of Open Access Journals (Sweden)
Saleh Salimi
2013-10-01
Full Text Available In order to perceive of rainfall- runoff process, essential prediction for water surface source management has special importance. Thereby in this paper, Tang-e Karzin hydrometric station which is located in sub-domain of salman-farsi dam had been considered. By utilizing of weekly statistical discharge information related to past 36 years, multilayer perceptron neural network model was used to predict the average weekly discharge of Tang-e Karzin station through the discharge information of its two upside stations. In order to optimize the weights and biases of the MLP network, we tried to use Artificial Bee Colony (ABC algorithm within training phase of the ANN network. The results indicated that by changing of different parameters of hidden layer of perceptron model, ABC can well optimize ANN’s weights and biases. Among five activation function Log-sigmoid was performed better than others with 9 neurons in hidden layer
Directory of Open Access Journals (Sweden)
Sanong Amaroek
2010-01-01
Full Text Available Problem statement: Estimation of moisture contents of dried food products from their dielectric constants was an important step in moisture measurement systems. The regression models that provide good prediction performance are desirable. Approach: The Multilayer Perceptrons (MLP and Support Vector Regression (SVR were applied in this research to predict the moisture contents of dried longan arils from their dielectric constants. The data set was collected from 1500 samples of dried longan aril with five different moisture contents of 10, 14, 18, 22 and 25% Wet basis (Wb. Dielectric constant of dried longan aril was measured by using our previously proposed electrical capacitance-based system. The results from the MLP and SVR models were compared to that from the linear regression and polynomial regression models. To take into account the generalization of the models, the four-fold cross validation was applied. Results: For the training sets, the average mean absolute errors over three bulk densities of 1.30, 1.45 and 1.60 g cm-3 were 1.7578, 0.6157, 0.3812, 0.3113, 0.0103 and 0.0044% Wb for the linear regression, second-, third-, fourth-order polynomial regression, MLP and SVR models, respectively. For the validation sets, the average mean absolute errors over the three bulk densities were 1.7616, 0.6192, 0.3844, 0.3146, 0.0126 and 0.0093% Wb for the linear regression, 2nd, 3rd and 4th-order polynomial regression, MLP and SVR models, respectively. Conclusion: The regression models based on MLP and SVR yielded better performances than the models based on linear regression and polynomial regression on both training and validation sets. The models based on MLP and SVR also provided robustness to the variation of bulk density. Not only for dried longan aril, the proposed models can also be adapted and applied to other materials or dried food products.
Directory of Open Access Journals (Sweden)
A. Piotrowski
2007-12-01
Full Text Available The prediction of temporal concentration profiles of a transported pollutant in a river is still a subject of ongoing research efforts worldwide. The present paper is aimed at studying the possibility of using Multi-Layer Perceptron Neural Networks to evaluate the whole concentration versus time profile at several cross-sections of a river under various flow conditions, using as little information about the river system as possible. In contrast with the earlier neural networks based work on longitudinal dispersion coefficients, this new approach relies more heavily on measurements of concentration collected during tracer tests over a range of flow conditions, but fewer hydraulic and morphological data are needed. The study is based upon 26 tracer experiments performed in a small river in Edinburgh, UK (Murray Burn at various flow rates in a 540 m long reach. The only data used in this study were concentration measurements collected at 4 cross-sections, distances between the cross-sections and the injection site, time, as well as flow rate and water velocity, obtained according to the data measured at the 1st and 2nd cross-sections.
The four main features of concentration versus time profiles at a particular cross-section, namely the peak concentration, the arrival time of the peak at the cross-section, and the shapes of the rising and falling limbs of the profile are modeled, and for each of them a separately designed neural network was used. There was also a variant investigated in which the conservation of the injected mass was assured by adjusting the predicted peak concentration. The neural network methods were compared with the unit peak attenuation curve concept.
In general the neural networks predicted the main features of the concentration profiles satisfactorily. The predicted peak concentrations were generally better than those obtained using the unit peak attenuation method, and the method with mass-conservation assured generally performed better than the method that did not account for mass-conservation. Predictions of peak travel time were also better using the neural networks than the unit peak attenuation method. Including more data into the neural network training set clearly improved the prediction of the shapes of the concentration profiles. Similar improvements in peak concentration were less significant and the travel time prediction appeared to be largely unaffected.
Directory of Open Access Journals (Sweden)
A. Piotrowski
2007-08-01
Full Text Available The prediction of temporal concentration profiles of a transported pollutant in a river is still a subject of ongoing research efforts worldwide. The present paper is aimed at studying the possibility of using Multi-Layer Perceptron Neural Networks to evaluate the whole concentration versus time profile at several cross-sections of a river under various flow conditions, using as little information about the river system as possible. In contrast with the earlier neural networks based work on longitudinal dispersion coefficients, this new approach relies more heavily on measurements of concentration collected during tracer tests over a range of flow conditions, but fewer hydraulic and morphological data are needed. The study is based upon 26 tracer experiments performed in a small river in Edinburgh, UK (Murray Burn at various flow rates in a 540 m long reach. The only data used in this study were concentration measurements collected at 4 cross-sections, distances between the cross-sections and the injection site, time, as well as flow rate and water velocity, obtained according to the data measured at the 1st and 2nd cross-sections.
The four main features of concentration versus time profiles at a particular cross-section, namely the peak concentration, the arrival time of the peak at the cross-section, and the shapes of the rising and falling limbs of the profile are modeled, and for each of them a separately designed neural network was used. There was also a variant investigated in which the conservation of the injected mass was assured by adjusting the predicted peak concentration. The neural network methods were compared with the unit peak attenuation curve concept.
In general the neural networks predicted the main features of the concentration profiles satisfactorily. The predicted peak concentrations were generally better than those obtained using the unit peak attenuation method, and the method with mass-conservation assured generally performed better than the method that did not account for mass-conservation. Predictions of peak travel time were also better using the neural networks than the unit peak attenuation method. Including more data into the neural network training set clearly improved the prediction of the shapes of the concentration profiles. Similar improvements in peak concentration were less significant and the travel time prediction appeared to be largely unaffected.
Kallin Westin, Lena
2004-01-01
Reliable results are crucial when working with medical decision support systems. A decision support system should be reliable but also be interpretable, i.e. able to show how it has inferred its conclusions. In this thesis, the preprocessing perceptron is presented as a simple but effective and efficient analysis method to consider when creating medical decision support systems. The preprocessing perceptron has the simplicity of a perceptron combined with a performance comparable to the multi...
DEFF Research Database (Denmark)
Kucuk, Nil; Manohara, S.R.
2013-01-01
In this work, multilayered perceptron neural networks (MLPNNs) were presented for the computation of the gamma-ray energy absorption buildup factors (BA) of seven thermoluminescent dosimetric (TLD) materials [LiF, BeO, Na2B4O7, CaSO4, Li2B4O7, KMgF3, Ca3(PO4)2] in the energy region 0.015–15MeV, and for penetration depths up to 10 mfp (mean-free-path). The MLPNNs have been trained by a Levenberg–Marquardt learning algorithm. The developed model is in 99% agreement with the ANSI/ANS-6.4.3 standard data set. Furthermore, the model is fast and does not require tremendous computational efforts. The estimated BA data for TLD materials have been given with penetration depth and incident photon energy as comparative to the results of the interpolation method using the Geometrical Progression (G-P) fitting formula.
Scientific Electronic Library Online (English)
Héctor, Tabares; John, Branch; Jaime, Valencia.
2006-09-01
Full Text Available En este trabajo se aplica un método constructivo aproximado para encontrar arquitecturas de redes neuronales artificiales (RNA) de tipo perceptrón multicapa (PMC). El método se complementa con la técnica de la búsqueda forzada de mejores mínimos locales. El entrenamiento de la red se lleva a cabo a [...] través del algoritmo gradiente descendente básico (GDB); se aplican técnicas como la repetición del entrenamiento y la detención temprana (validación cruzada), para mejorar los resultados. El criterio de evaluación se basa en las habilidades de aprendizaje y de generalización de las arquitecturas generadas específicas de un dominio. Se presentan resultados experimentales con los cuales se demuestra la efectividad del método propuesto y comparan con las arquitecturas halladas por otros métodos. Abstract in english This paper deals with an approximate constructive method to find architectures of artificial neuronal network (ANN) of the type MultiLayer Percetron (MLP) which solves a particular problem. This method is supplemented with the technique of the Forced search of better local minima. The training of th [...] e net uses an algorithm basic descending gradient (BDG). Techniques such as repetition of the training and the early stopping (cross validation) are used to improve the results. The evaluation approach is based not only on the learning abilities but also on the generalization of the specific generated architectures of a domain. Experimental results are presented in order to prove the effectiveness of the proposed method. These are compared with architectures found by other methods.
Bachtiar, Luqman R; Unsworth, Charles P; Newcomb, Richard D
2014-08-01
Current electronic noses, or e-noses, that employ insect odorant receptors (Ors) as their sensory front end are potentially limited by the fact that the Ors come from a single species. In addition, a realistic e-nose also demands low numbers of Ors at its sensory front end due to the difficulties of receptor/sensor integration and functionalisation. In this work, we report the first investigations of a `Super E-Nose' that incorporates Ors from both the model organism Drosophila melanogaster fruit fly (DmOr) and the mosquito, Anopheles gambiae (AgOr). Furthermore, we report how an Artificial Neural Network (ANN), in the form of a hybrid double hidden layer Multi-Layer Perceptron (MLP), can be used to determine the optimal Ors that provide the best prediction performance in the classification of unknown odorants into their respective chemical class. Our findings demonstrate how 3-Or arrays consisting of DmOr only, AgOr only, or cross-species DmOr-AgOr combinations correctly classified all unknown odorants of the validation set. In addition, we report that all 3-Or combinations perform equally well as the complete 74 DmOr-AgOr array. Thus, the results of this work support further investigation into cross-species `Super E-noses' coupled with hybrid MLPs for the classification of unknown odorants. PMID:25570118
Bachtiar, Luqman R; Unsworth, Charles P; Newcomb, Richard D
2015-01-01
The model organism, Drosophila melanogaster, and the mosquito Anopheles gambiae use 60 and 79 odorant receptors, respectively, to sense their olfactory world. However, a commercial "electronic nose" in the form of an insect olfactory biosensor demands very low numbers of receptors at its front end of detection due to the difficulties of receptor/sensor integration and functionalization. In this letter, we demonstrate how computation via artificial neural networks (ANNs), in the form of multilayer perceptrons (MLPs), can be successfully incorporated as the signal processing back end of the biosensor to drastically reduce the number of receptors to three while still retaining 100% performance of odorant detection to that of a full complement of receptors. In addition, we provide a detailed performance comparison between D. melanogaster and A. gambiae odorant receptors and demonstrate that A. gambiae receptors provide superior olfaction detection performance over D. melanogaster for very low receptor numbers. The results from this study present the possibility of using the computation of MLPs to discover ideal biological olfactory receptors for an olfactory biosensor device to provide maximum classification performance of unknown odorants. PMID:25380337
International Nuclear Information System (INIS)
In this work, multilayered perceptron neural networks (MLPNNs) were presented for the computation of the gamma-ray energy absorption buildup factors (BA) of seven thermoluminescent dosimetric (TLD) materials [LiF, BeO, Na2B4O7, CaSO4, Li2B4O7, KMgF3, Ca3(PO4)2] in the energy region 0.015–15 MeV, and for penetration depths up to 10 mfp (mean-free-path). The MLPNNs have been trained by a Levenberg–Marquardt learning algorithm. The developed model is in 99% agreement with the ANSI/ANS-6.4.3 standard data set. Furthermore, the model is fast and does not require tremendous computational efforts. The estimated BA data for TLD materials have been given with penetration depth and incident photon energy as comparative to the results of the interpolation method using the Geometrical Progression (G-P) fitting formula. - Highlights: ? Gamma-ray energy absorption buildup factors estimation in TLD materials. ? The ANN approach can be alternative to G-P fitting method for BA calculations. ? The applied model is not time-consuming and easily predicted
Çaylak, Ça?r?; Kaftan, ?lknur
2014-12-01
This study proposes the use of multi-layer perceptron neural networks (MLPNN) to invert dispersion curves obtained via multi-channel analysis of surface waves (MASW) for shear S-wave velocity profile. The dispersion curve used in inversion includes the fundamental-mode dispersion data. In order to investigate the applicability and performance of the proposed MLPNN algorithm, test studies were performed using both synthetic and field examples. Gaussian random noise with a standard deviation of 4 and 8% was added to the noise-free test data to make the synthetic test more realistic. The model parameters, such as S-wave velocities and thicknesses of the synthetic layered-earth model, were obtained for different S/N ratios and noise-free data. The field survey was performed over the natural gas pipeline, located in the Germencik district of Ayd?n city, western Turkey. The results show that depth, velocity, and location of the embedded natural gas pipe are successfully estimated with reasonably good approximation.
Scientific Electronic Library Online (English)
Rodrigo Martins da, Silva; Luiza de Macedo, Mourelle; Nadia, Nedjah.
2011-12-01
Full Text Available Em termos computacionais, uma rede neural artificial (RNA) pode ser implementada em software ou em hardware, ou ainda de maneira híbrida, combinando ambos os recursos. O presente trabalho propõe uma arquitetura de hardware para a computação de uma rede neural do tipo perceptron com múltiplas camadas [...] (MLP). Soluções em hardware tendem a ser mais eficientes do que soluções em software. O projeto em questão, além de explorar fortemente o paralelismo das redes neurais, permite alterações do número de entradas, número de camadas e de neurônios por camada, de modo que diversas aplicações de RNAs possam ser executadas no hardware proposto. Visando a uma redução de tempo do processamento aritmético, um número real é aproximado por uma fração de inteiros. Dessa forma, as operações aritméticas limitam-se a operações inteiras, executadas por circuitos combinacionais. Uma simples máquina de estados é demandada para controlar somas e produtos de frações. A função de ativação usada neste projeto é a sigmóide. Essa função é aproximada mediante o uso de polinômios, cujas operações são regidas por somas e produtos. Um teorema é introduzido e provado, permitindo a fundamentação da estratégia de cálculo da função de ativação. Dessa forma, reaproveita-se o circuito aritmético da soma ponderada para também computar a sigmóide. Essa re-utilização dos recursos levou a uma redução drástica de área total de circuito. Após modelagem e simulação para validação do bom funcionamento, a arquitetura proposta foi sintetizada utilizando recursos reconfiguráveis, do tipo FPGA. Os resultados são promissores. Abstract in english There are several neural network implementations using either software, hardware-based or a hardware/software co-design. This work proposes a hardware architecture to implement an artificial neural network (ANN), whose topology is the multilayer perceptron (MLP). In this paper, we explore the parall [...] elism of neural networks and allow on-thefly changes of the number of inputs, number of layers and number of neurons per layer of the net. This reconfigurability characteristic permits that any application of ANNs may be implemented using the proposed hardware. In order to reduce the processing time that is spent in arithmetic computation, a real number is represented using a fraction of integers. In this way, the arithmetics is limited to integer operations, performed by fast combinational circuits. A simple state machine is required to control sums and products of fractions. Sigmoid is used as the activation function in the proposed implementation. It is approximated by polynomials, whose underlying computation requires only sums and products. A theorem is introduced and proven so as to cover the arithmetic strategy of the computation of the activation function. Thus, the arithmetic circuitry used to implement the neuron weighted sum is reused for computing the sigmoid. this resource sharing decreased drastically the total area of the system. After modeling and simulation for functionality validation, the proposed architecture synthesized using reconfigurable hardware. The results are promising.
Directory of Open Access Journals (Sweden)
Haydeé Elena Musso
2013-01-01
Full Text Available En este trabajo se realizó un estudio estadístico de variables físico químicas asociadas al fenómeno de contaminación ambiental, en particular concentración media mensual de SO2 , medidas en la ciudad Salta Capital, Argentina, simultáneamente a concentraciones de NO2 y O3 . Las series bajo estudio presentaban comportamientos dinámicos no lineales, datos atípicos y cambios estructurales, lo que hizo imposible modelarlas con tipologías econométricas tradiciones (AR, MA, ARMA, ARIMA, entre otras. Una solución eficiente que se encontró, hace uso de la teoría de los perceptrones multicapa. Mediante el modelo estructural de series de tiempo, esta solución se presenta como un proceso matemático iterativo que permite obtener un modelado final el cual tiene una muy alta confiabilidad (95%, para realizar pronoósticos a futuro sobre el comportamiento de la variable estudiada.In this paper a statistical study of phisical-chemistry variables connected with enviroment pollution, specifically SO2 monthly average concentration, measured in Salta Capital city, Argentina, together with NO2 and O3 concentrations, was made. Time series under study shown non linear dinamic behaviour, outliers and structural changes. Due to these it was impossible to use typical econometric typologies (AR, MA, ARMA, ARIMA, among others. An effective solution which uses multistep perceptrons theory was found. By using structural time series modelling, this solution is presented by an iterative mathematical process that allows us to obtain a final model with a high confidence level (95% in order to do the forecasting step on the studied variable.
Scientific Electronic Library Online (English)
Haydeé Elena, Musso; Orlando José, Ávila Blas.
2013-01-01
Full Text Available En este trabajo se realizó un estudio estadístico de variables físico químicas asociadas al fenómeno de contaminación ambiental, en particular concentración media mensual de SO2 , medidas en la ciudad Salta Capital, Argentina, simultáneamente a concentraciones de NO2 y O3 . Las series bajo estudio p [...] resentaban comportamientos dinámicos no lineales, datos atípicos y cambios estructurales, lo que hizo imposible modelarlas con tipologías econométricas tradiciones (AR, MA, ARMA, ARIMA, entre otras). Una solución eficiente que se encontró, hace uso de la teoría de los perceptrones multicapa. Mediante el modelo estructural de series de tiempo, esta solución se presenta como un proceso matemático iterativo que permite obtener un modelado final el cual tiene una muy alta confiabilidad (95%), para realizar pronoósticos a futuro sobre el comportamiento de la variable estudiada. Abstract in english In this paper a statistical study of phisical-chemistry variables connected with enviroment pollution, specifically SO2 monthly average concentration, measured in Salta Capital city, Argentina, together with NO2 and O3 concentrations, was made. Time series under study shown non linear dinamic behavi [...] our, outliers and structural changes. Due to these it was impossible to use typical econometric typologies (AR, MA, ARMA, ARIMA, among others). An effective solution which uses multistep perceptrons theory was found. By using structural time series modelling, this solution is presented by an iterative mathematical process that allows us to obtain a final model with a high confidence level (95%) in order to do the forecasting step on the studied variable.
Scientific Electronic Library Online (English)
Carlos A., de Luna-Ortega; Miguel, Mora-González; Julio C., Martínez-Romo; Francisco J., Luna-Rosas; Jesús, Muñoz-Maciel.
Full Text Available En el presente artículo se da a conocer una alternativa algorítimica a los sistemas actuales de reconocimiento automático del habla (ASR), mediante una propuesta en la forma de realizar la caracterización de las palabras basada en una aproximación que usa la extracción de coeficientes de la codifica [...] ción de predicción lineal (LPC) y la correlación cruzada. La implementación consiste en extraer las características fonéticas mediante los coeficientes LPC, después se forman vectores de patrones de la pronunciación conformados por el promedio de los coeficientes LPC de las muestras de las palabras obteniendo un vector característico de cada pronunciación mediante la autocorrelación de las secuencias de coeficientes LPC; estos vectores se utilizan para entrenar un clasificador de tipo perceptrón multicapa (MLP). Se realizaron pruebas de desempeño previo entrenamiento con los diferentes patrones de las palabras a reconocer. Se utilizó la fonética de los dígitos del cero al nueve como vocabulario objetivo, debido a su amplia aplicación, y para estimar el desempeño de este método se utilizaron dos corpus de pronunciaciones: el corpus UPA, que contempla en su base de datos la pronuncación de la región occidente de México, y el corpus Tlatoa, que hace lo propio para la región centro de México. Las señales en ambos corpus fueron adquiridas en el lenguaje español, y a una frecuencia de muestreo de 8kHz. Los porcentajes de reconocimiento obtenidos fueron del 96.7 y 93.3% para las modalidades de mono-locutor para el corpus UPA y múltiple-locutor para el corpus Tlatoa, respectivamente. Asimismo, se realizó una comparación contra dos métodos clásicos del reconocimiento de voz y del habla, Dynamic Time Warping (DTW) y Hidden Markov Models (HMM). Abstract in english It this paper we present an algorithmic alternative to the current Automatic Speech Recognition (ASR) systems by proposing a way to characterize words based on approximations that use an extracted coefficient from Linear Predictive Coding (LPC). The method consists in extracting phonetic characteris [...] tics through the use of LPC coefficients, after which pattern vectors are formed from the LPC coefficient averages taken from the word sampling, thus creating a unique vector for each pronunciation through the auto correlation of the LPC coefficient sequences. These vectors are used to train a Multilayer Perceptron (MLP) classifier. After training performance trials were executed. The sounds from the digits zero through nine where used as a target vocabulary, given its general use, and to estimate the performance of this method two corpus where used: the UPA corpus, which in its vocabulary uses a pronunciation familiar to the western part of Mexico, and the Tlatoa corpus, who's vocabulary presents a pronunciation typical of the central region of Mexico. The signals from both corpus where sampled in the Spanish language, and at a sampling frequency of 8kHz. The recognition rate for the mono-speaker from the UPA corpus and the multiple-speaker from the Tlatoa corpus were 96.7% and 93.3% respectively. Additionally, there where comparisons done against two classic methods used for speech recognition, Dynamic Time Warping (DTW) and Hidden Markov Models (HMM).
Pelossof, Raphael; Ying, Zhiliang
2010-01-01
We propose a focus of attention mechanism to speed up the Perceptron algorithm. Focus of attention speeds up the Perceptron algorithm by lowering the number of features evaluated throughout training and prediction. Whereas the traditional Perceptron evaluates all the features of each example, the Attentive Perceptron evaluates less features for easy to classify examples, thereby achieving significant speedups and small losses in prediction accuracy. Focus of attention allows...
Pelossof, Raphael
2010-01-01
We propose a focus of attention mechanism to speed up the Perceptron algorithm. Focus of attention speeds up the Perceptron algorithm by lowering the number of features evaluated throughout training and prediction. Whereas the traditional Perceptron evaluates all the features of each example, the Attentive Perceptron evaluates less features for easy to classify examples, thereby achieving significant speedups and small losses in prediction accuracy. Focus of attention allows the Attentive Perceptron to stop the evaluation of features at any interim point and filter the example. This creates an attentive filter which concentrates computation at examples that are hard to classify, and quickly filters examples that are easy to classify.
Scientific Electronic Library Online (English)
Yuleidys, Mejías César; Ramón, Carrasco Velar; Isbel, Ochoa Izquierdo; Edel, Moreno Lemus.
2013-12-01
Full Text Available El perceptrón multicapa (PMC) figura dentro de los tipos de redes neuronales artificiales (RNA) con resultados útiles en los estudios de relación estructura-actividad. Dado que los volúmenes de datos en proyectos de Bioinformática son eventualmente grandes, se propuso evaluar algoritmos para acortar [...] el tiempo de entrenamiento de la red sin afectar su eficiencia. Se desarrolló un algoritmo para el entrenamiento local y distribuido del PMC con la posibilidad de variar las funciones de transferencias para lo cual se utilizaron el Weka y la Plataforma de Tareas Distribuidas Tarenal para distribuir el entrenamiento del perceptrón multicapa. Se demostró que en dependencia de la muestra de entrenamiento, la variación de las funciones de transferencia pueden reportar resultados mucho más eficientes que los obtenidos con la clásica función Sigmoidal, con incremento de la g-media entre el 4.5 y el 17 %. Se encontró además que en los entrenamientos distribuidos es posible alcanzar eventualmente mejores resultados que los logrados en ambiente local. Abstract in english The multilayer perceptron (PMC) ranks among the types of artificial neural networks (ANN), which has provided better results in studies of structure-activity relationship. As the data volumes in Bioinformatics' projects are eventually big, it was proposed to evaluate algorithms to shorten the traini [...] ng time of the network without affecting its efficiency. There were evaluated different tools that work with ANN and were selected Weka algorithm for extracting the network and the Platform for Distributed Task Tarenal to distribute the training of multilayer perceptron. Finally, it was developed a training algorithm for local and distributed the MLP with the possibility of varying transfer functions. It was shown that depending on the training sample, the change of transfer functions can yield results much more efficient than those obtained with the classic sigmoid function with increased g-media between 4.5 and 17 %. Moreover, it was found that with distributed training can be achieved eventually, better results than those achieved in the local environment.
Introduction to Perceptron Networks
DEFF Research Database (Denmark)
Jantzen, Jan
1998-01-01
When it is time-consuming or expensive to model a plant using the basic laws of physics, a neural network approach can be an alternative. From a control engineer's viewpoint a two-layer perceptron network is sufficient. It is indicated how to model a dynamic plant using a perceptron network.
Mohri, Mehryar; Rostamizadeh, Afshin
2013-01-01
We present a brief survey of existing mistake bounds and introduce novel bounds for the Perceptron or the kernel Perceptron algorithm. Our novel bounds generalize beyond standard margin-loss type bounds, allow for any convex and Lipschitz loss function, and admit a very simple proof.
Generalization ability of a perceptron with non-monotonic transfer function
Inoue, Jun-ichi; Nishimori, Hidetoshi; Kabashima, Yoshiyuki
1997-01-01
We investigate the generalization ability of a perceptron with non-monotonic transfer function of a reversed-wedge type in on-line mode. This network is identical to a parity machine, a multilayer network. We consider several learning algorithms. By the perceptron algorithm the generalization error is shown to decrease by the ${\\alpha}^{-1/3}$-law similarly to the case of a simple perceptron in a restricted range of the parameter $a$ characterizing the non-monotonic transfer...
Scientific Electronic Library Online (English)
José C, Cúrvelo Santana; Sidnei A, de Araújo; Joana P, M. Biazus; Roberto R, de Souza.
2015-04-01
Full Text Available En este trabajo se propone utilizar una Red Neuronal Artificial (RNA) Perceptrón Multicapa (PMC) para simular la variación de la concentración de proteína de acuerdo con el tiempo y también para determinar la hora final del procedimiento, además de los parámetros óptimos del proceso de biodegradació [...] n de las proteínas de un efluente de matadero. Para eso, han sido utilizadas las papaínas, presentes en el látex de la papaya (Carica papaya) con el objetivo de disminuir la concentración de proteínas de un efluente de matadero a pH (5 y 7) con una temperatura de (25 y 30° C) controlada. Los resultados mostraron que las papaínas redujeron de 82% a 91% la concentración de proteína en 30 y 40 h de proceso. Las simulaciones con la RNA apuntaron que las condiciones perfectas fueron obtenidas a pH 5, con 30 °C y en 35 h, en el cual se ha alcanzado una reducción de 91% de la concentración de proteínas. Abstract in english In this paper, the use of a multilayer perceptron (MLP) artificial neural network (ANN) is proposed to simulate the variation of protein concentration according to the time and also to determine the end and optimal conditions of the biodegradation process of wastewater from meat industry. To reduce [...] the protein concentration, papains from Carica papaya latex have been used at controlled condition of pH (5 and 7) and temperature (25 and 30 °C). Results showed that a reduction of 82 to 91% of protein concentration by the action of papains for 30 to 40 h of process time. Simulations showed that the best condition of the process occurred at pH 5, 30 °C and 35 h, in which a maximum biodegradation of 91% was obtained.
Scientific Electronic Library Online (English)
Alejandro J., Orozco-Naranjo; Pablo A., Muñoz-Gutiérrez.
2013-12-30
Full Text Available Este artículo presenta los resultados obtenidos al desarrollar una metodología para la detección de 5 tipos de latidos cardiacos (Normal (N), Bloqueo de Rama Derecha (RBBB), Bloqueo de Rama Izquierda (LBBB), Contracción Auricular Prematura (APC) y Contracción Ventricular Prematura (PVC)) utilizando [...] la transformada por paquetes Wavelet de manera no adaptativa en la extracción de características de las señales cardiacas, empleando la función Shanon para cálculo de la entropía y adicionando una fase de identificación de nodos por cada tipo de señal cardiaca en el árbol Wavelet. La utilización de la transformada por paquetes Wavelet permite acceder a información obtenida de la descomposición tanto de baja como de alta frecuencia proporcionando un análisis más integral que el logrado con la transformada Wavelet discreta. Se evaluaron Wavelets madre de las familias Daubechies, Symlet 5 y Biortogonal inversa; que fueron resultado de una investigación previa en que se identificaron las Wavelet madre que mayor entropía presentaban con las señales cardiacas. Con la modalidad no adaptativa se reduce el costo computacional al utilizar los paquetes Wavelet, coste que representa la mayor desventaja de esta transformada, dando validez a la investigación realizada. Para la clasificación de los patrones cardiacos se emplearon las máquinas de soporte vectorial y el perceptrón multicapa. Con las máquinas de soporte vectorial empleando kernel de función de base radial, se logró un error de clasificación del 2,57 %. Abstract in english This paper presents the results obtained by developing a methodology to detect 5 types of heartbeats (Normal (N), Right bundle branch block (RBBB), Left bundle branch block (LBBB), Premature atrial contraction (APC) and Premature ventricular contraction (PVC)), using Wavelet transform packets with n [...] on-adaptative mode applied on features extraction from heartbeats. It was used the Shannon function to calculate the entropy and It was added an identification nodes stage per every type of cardiac signal in the Wavelet tree. The using of Wavelet packets transform allows the access to information which results of decomposition of low and high frecuency, giving providing a more integral analysis than achieved by the discrete Wavelet transform. Three families of mother Wavelet were evaluated on transformation: Daubechies, Symlet and Reverse Biorthogonal, which were results from a previous research in that were identified the mother Wavelet that had higher entropy with the cardiac signals. With non-adaptive mode, the computational cost is reduced when Wavelet packets are used; this cost represents the most marked disadvantage from the transform. To classify the heartbeats were used Support Vector Machines and Multilayer Perceptron. The best classification error was achieved employing Support Vector Machine and a radial basis function; it was 2.57 %.
The Perceptron with Dynamic Margin
Panagiotakopoulos, Constantinos; Tsampouka, Petroula
2011-01-01
The classical perceptron rule provides a varying upper bound on the maximum margin, namely the length of the current weight vector divided by the total number of updates up to that time. Requiring that the perceptron updates its internal state whenever the normalized margin of a pattern is found not to exceed a certain fraction of this dynamic upper bound we construct a new approximate maximum margin classifier called the perceptron with dynamic margin (PDM). We demonstrate ...
Fault characterization of a multilayered perceptron network
Tan, Chang H.; Iyer, Ravishankar K.
1990-01-01
The results of a set of simulation experiments conducted to quantify the effects of faults in a classification network implemented as a three-layered perception model are reported. The percentage of vectors misclassified by the classification network, the time taken for the network to stabilize, and the output values are measured. The results show that both transient and permanent faults have a significant impact on the performance of the network. Transient faults are also found to cause the network to be increasingly unstable as the duration of a transient is increased. The average percentage of the vectors misclassified is about 25 percent; after relearning, this is reduced to 10 percent. The impact of link faults is relatively insignificant in comparison with node faults (1 percent versus 19 percent misclassified after relearning). A study of the impact of hardware redundancy shows a linear increase in misclassifications with increasing hardware size.
The Perceptron with Dynamic Margin
Panagiotakopoulos, Constantinos
2011-01-01
The classical perceptron rule provides a varying upper bound on the maximum margin, namely the length of the current weight vector divided by the total number of updates up to that time. Requiring that the perceptron updates its internal state whenever the normalized margin of a pattern is found not to exceed a certain fraction of this dynamic upper bound we construct a new approximate maximum margin classifier called the perceptron with dynamic margin (PDM). We demonstrate that PDM converges in a finite number of steps and derive an upper bound on them. We also compare experimentally PDM with other perceptron-like algorithms and support vector machines on hard margin tasks involving linear kernels which are equivalent to 2-norm soft margin.
Finite Size Scaling of Perceptron
Korutcheva, Elka; Tonchev, N.
2000-01-01
We study the first-order transition in the model of a simple perceptron with continuous weights and large, bit finite value of the inputs. Making the analogy with the usual finite-size physical systems, we calculate the shift and the rounding exponents near the transition point. In the case of a general perceptron with larger variety of inputs, the analysis only gives bounds for the exponents.
Thomas, Philippe; Thomas, Andre?
2008-01-01
Simulation is often used to evaluate the relevance of a Directing Program of Production (PDP) or to evaluate its impact on detailed sc\\'enarii of scheduling. Within this framework, we propose to reduce the complexity of a model of simulation by exploiting a multilayer perceptron. A main phase of the modeling of one system using a multilayer perceptron remains the determination of the structure of the network. We propose to compare and use various pruning algorithms in order ...
Schroeder, M.; Kinzel, W.
1997-01-01
An artificial neural network can be used to generate a series of numbers. A boolean perceptron generates bit sequences with a periodic structure. The corresponding spectrum of cycle lengths is investigated analytically and numerically; it has similarities with properties of rational numbers.
Polyhedrons and Perceptrons Are Functionally Equivalent
Crespin, Daniel
2013-01-01
Mathematical definitions of polyhedrons and perceptron networks are discussed. The formalization of polyhedrons is done in a rather traditional way. For networks, previously proposed systems are developed. Perceptron networks in disjunctive normal form (DNF) and conjunctive normal forms (CNF) are introduced. The main theme is that single output perceptron neural networks and characteristic functions of polyhedrons are one and the same class of functions. A rigorous formulati...
Thomas, Philippe
2008-01-01
Simulation is often used to evaluate the relevance of a Directing Program of Production (PDP) or to evaluate its impact on detailed sc\\'enarii of scheduling. Within this framework, we propose to reduce the complexity of a model of simulation by exploiting a multilayer perceptron. A main phase of the modeling of one system using a multilayer perceptron remains the determination of the structure of the network. We propose to compare and use various pruning algorithms in order to determine the optimal structure of the network used to reduce the complexity of the model of simulation of our case of application: a sawmill.
Robust chaos generation by a perceptron
Priel, A.; Kanter, I.
2000-01-01
The properties of time series generated by a perceptron with monotonic and non-monotonic transfer function, where the next input vector is determined from past output values, are examined. Analysis of the parameter space reveals the following main finding: a perceptron with a monotonic function can produce fragile chaos only whereas a non-monotonic function can generate robust chaos as well. For non-monotonic functions, the dimension of the attractor can be controlled monoto...
The Margitron: A Generalised Perceptron with Margin
Panagiotakopoulos, Constantinos; Tsampouka, Petroula
2008-01-01
We identify the classical Perceptron algorithm with margin as a member of a broader family of large margin classifiers which we collectively call the Margitron. The Margitron, (despite its) sharing the same update rule with the Perceptron, is shown in an incremental setting to converge in a finite number of updates to solutions possessing any desirable fraction of the maximum margin. Experiments comparing the Margitron with decomposition SVMs on tasks involving linear kernel...
Classification of fuels using multilayer perceptron neural networks
International Nuclear Information System (INIS)
Electrical impedance data obtained with an array of conducting polymer chemical sensors was used by a neural network (ANN) to classify fuel adulteration. Real samples were classified with accuracy greater than 90% in two groups: approved and adulterated.
Hybrid Evolutionary Algorithm for Multilayer Perceptron Networks with Competetive Performance.
Czech Academy of Sciences Publication Activity Database
Neruda, Roman
Los Alamitos : IEEE, 2007, s. 1620-1627. ISBN 978-1-4244-1339-3. [CEC 2007. Congress on Evolutionary Computation. Singapore (SG), 25.09.2007-28.09.2007] R&D Projects: GA AV ?R 1ET100300419 Institutional research plan: CEZ:AV0Z10300504 Keywords : hybrid algorithm s * evolutionary learning * neural networks Subject RIV: IN - Informatics, Computer Science
FPGA Implementation of Multilayer Perceptron for Modeling of Photovoltaic panel
International Nuclear Information System (INIS)
The Number of electronic applications using artificial neural network-based solutions has increased considerably in the last few years. However, their applications in photovoltaic systems are very limited. This paper introduces the preliminary result of the modeling and simulation of photovoltaic panel based on neural network and VHDL-language. In fact, an experimental database of meteorological data (irradiation, temperature) and output electrical generation signals of the PV-panel (current and voltage) has been used in this study. The inputs of the ANN-PV-panel are the daily total irradiation and mean average temperature while the outputs are the current and voltage generated from the panel. Firstly, a dataset of 4x364 have been used for training the network. Subsequently, the neural network (MLP) corresponding to PV-panel is simulated using VHDL language based on the saved weights and bias of the network. Simulation results of the trained MLP-PV panel based on Matlab and VHDL are presented. The proposed PV-panel model based ANN and VHDL permit to evaluate the performance PV-panel using only the environmental factors and involves less computational efforts, and it can be used for predicting the output electrical energy from the PV-panel
Multilayer Perceptron with Functional Inputs: an Inverse Regression Approach
Ferre?, Louis; Villa, Nathalie
2006-01-01
Abstract. Functional data analysis is a growing research field as more and more practical applications involve functional data. In this paper, we focus on the problem of regression and classification with functional predictors: the model suggested combines an efficient dimension reduction procedure [functional sliced inverse regression, first introduced by Ferré & Yao (Statistics, 37, 2003, 475)], for which we give a regularized version, with the accuracy of a neural network. Some consistenc...
Classification of Parking Spots Using Multilayer Perceptron Networks
Directory of Open Access Journals (Sweden)
FALCAO, H. S.
2013-12-01
Full Text Available This project intends to develop a prototype for the identification of free spots in open air parking area where there is a good aerial view without obstacles, allowing for the identification of occupied and free spots. We used image processing techniques and pattern recognition using Artificial Neural Networks (ANN. In order to help implement the prototype, we used Matlab. In order to simulate the parking area, we created a model so that we could acquire the images using a webcam, process them, train the neural network, classify the spots and finally, show the results. The results show that it is viable to apply pattern recognition through image capture to classify parking spots
Perceptron beyond the limit of capacity
Del Giudice, P.; Franz, S.; Virasoro, M. A.
1989-01-01
An input-output map in which the patterns are divided into classes is considered for the perceptron. The statistical mechanical analysis with a finite number of classes turns out to give the same results as the case of only one class of patterns ; the limit of capacity and the relevant order parameters are calculated in a mean field approach. The analysis is then extended to the Derrida Gardner canonical ensemble in which the perceptron can be studied beyond the limit of capacity. We complete...
Chaotic diagonal recurrent neural network
International Nuclear Information System (INIS)
We propose a novel neural network based on a diagonal recurrent neural network and chaos, and its structure and learning algorithm are designed. The multilayer feedforward neural network, diagonal recurrent neural network, and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map. The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks. (interdisciplinary physics and related areas of science and technology)
Best Approximation by Heaviside Perceptron Networks.
Czech Academy of Sciences Publication Activity Database
Kainen, P.C.; K?rková, V?ra; Vogt, A.
2000-01-01
Ro?. 13, ?. 7 (2000), s. 695-697. ISSN 0893-6080 R&D Projects: GA ?R GA201/96/0917; GA AV ?R IAA2030602 Institutional research plan: AV0Z1030915 Keywords : one-hidden-layer networks * heaviside perceptrons * best approximation * metric projection * continuous selection * approximatively compact Subject RIV: BA - General Mathematics Impact factor: 1.221, year: 2000
A diluted version of the perceptron model
Marquez-Carreras, D; Tindel, S; Marquez-Carreras, David; Rovira, Carles; Tindel, Samy
2006-01-01
This note is concerned with a diluted version of the perceptron model. We establish a replica symmetric formula at high temperature, which is achieved by studying the asymptotic behavior of a given spin magnetization. Our main task will be to identify the order parameter of the system.
Minimization of Error Functionals over Perceptron Networks.
Czech Academy of Sciences Publication Activity Database
K?rková, V?ra
2008-01-01
Ro?. 20, ?. 1 (2008), s. 252-270. ISSN 0899-7667 R&D Projects: GA ?R GA201/05/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : model complexity of perceptron networks * minimization of error functionals Subject RIV: BA - General Mathematics Impact factor: 2.378, year: 2008
Landscape statistics of the binary perceptron
Fontanari, J. F.; Ko?berle, R.
1990-01-01
The landscape of the binary perceptron is studied by Simulated Annealing, exhaustive search and performing random walks on the landscape. We find that the number of local minima increases exponentially with the number of bonds, becoming deeper in the vicinity of a global minimum, but more and more shallow as we move away from it. The random walker detects a simple dependence on the size of the mapping, the architecture introducing a nontrivial dependence on the number of steps.
Simulating a perceptron on a quantum computer
Schuld, Maria; Sinayskiy, Ilya; Petruccione, Francesco
2014-01-01
Perceptrons are the basic computational unit of artificial neural networks, as they model the activation mechanism of an output neuron due to incoming signals from its neighbours. As linear classifiers, they play an important role in the foundations of machine learning. In the context of the emerging field of quantum machine learning, several attempts have been made to develop a corresponding unit using quantum information theory. Based on the quantum phase estimation algori...
Storage capacity of a Potts-perceptron
Nadal, Jean-pierre; Rau, Albrecht
1991-01-01
We consider the properties of “Potts” neural networks where each neuron can be in Q different states. For a “Potts-perceptron” with N Q-states input neurons and one Q' states output neutron, we compute the maximal storage capacity for unbiased patterns. In the large N limit the maximal number of patterns that can be stored is found to be proportional to N(Q-1)f(Q'), where f(Q') is of order 1.
Handwritten Digit Recognition with Binary Optical Perceptron
Saxena, Indu; Moerland, Perry; Fiesler, Emile; Pourzand, A. R.
1997-01-01
Binary weights are favored in electronic and optical hardware implementations of neural networks as they lead to improved system speeds. Optical neural networks based on fast ferroelectric liquid crystal binary level devices can benefit from the many orders of magnitudes improved liquid crystal response times. An optimized learning algorithm for all-positive perceptrons is simulated on a limited data set of hand-written digits and the resultant network implemented optically. First, gray-scale...
Storage of correlated patterns in a perceptron
Lopez, B.; Schroeder, M.; Opper, M.
1995-01-01
We calculate the storage capacity of a perceptron for correlated gaussian patterns. We find that the storage capacity $\\alpha_c$ can be less than 2 if similar patterns are mapped onto different outputs and vice versa. As long as the patterns are in general position we obtain, in contrast to previous works, that $\\alpha_c \\geq 1$ in agreement with Cover's theorem. Numerical simulations confirm the results.
Multifractal analysis of perceptron learning with errors
Weigt, M.
1997-01-01
Random input patterns induce a partition of the coupling space of a perceptron into cells labeled by their output sequences. Learning some data with a maximal error rate leads to clusters of neighboring cells. By analyzing the internal structure of these clusters with the formalism of multifractals, we can handle different storage and generalization tasks for lazy students and absent-minded teachers within one unified approach. The results also allow some conclusions on the ...
On-line learning through simple perceptron with a margin
Hara, Kazuyuki; Okada, Masato
2003-01-01
We analyze a learning method that uses a margin $\\kappa$ {\\it a la} Gardner for simple perceptron learning. This method corresponds to the perceptron learning when $\\kappa=0$, and to the Hebbian learning when $\\kappa \\to \\infty$. Nevertheless, we found that the generalization ability of the method was superior to that of the perceptron and the Hebbian methods at an early stage of learning. We analyzed the asymptotic property of the learning curve of this method through compu...
Jordan recurrent neural network versus IHACRES in modelling daily streamflows
Carcano, Elena Carla; Bartolini, Paolo; Muselli, Marco; Piroddi, Luigi
2008-12-01
SummaryA study of possible scenarios for modelling streamflow data from daily time series, using artificial neural networks (ANNs), is presented. Particular emphasis is devoted to the reconstruction of drought periods where water resource management and control are most critical. This paper considers two connectionist models: a feedforward multilayer perceptron (MLP) and a Jordan recurrent neural network (JNN), comparing network performance on real world data from two small catchments (192 and 69 km 2 in size) with irregular and torrential regimes. Several network configurations are tested to ensure a good combination of input features (rainfall and previous streamflow data) that capture the variability of the physical processes at work. Tapped delayed line (TDL) and memory effect techniques are introduced to recognize and reproduce temporal dependence. Results show a poor agreement when using TDL only, but a remarkable improvement can be obtained with JNN and its memory effect procedures, which are able to reproduce the system memory over a catchment in a more effective way. Furthermore, the IHACRES conceptual model, which relies on both rainfall and temperature input data, is introduced for comparative study. The results suggest that when good input data is unavailable, metric models perform better than conceptual ones and, in general, it is difficult to justify substantial conceptualization of complex processes.
Optimal Capacity of the Blume-Emery-Griffiths perceptron
Bolle, D.; Castillo, I. Perez; Shim, G. M.
2002-01-01
A Blume-Emery-Griffiths perceptron model is introduced and its optimal capacity is calculated within the replica-symmetric Gardner approach, as a function of the pattern activity and the imbedding stability parameter. The stability of the replica-symmetric approximation is studied via the analogue of the Almeida-Thouless line. A comparison is made with other three-state perceptrons.
Finite size scaling of the bayesian perceptron
Buhot, A; Gordon, M B
1997-01-01
We study numerically the properties of the bayesian perceptron through a gradient descent on the optimal cost function. The theoretical distribution of stabilities is deduced. It predicts that the optimal generalizer lies close to the boundary of the space of (error-free) solutions. The numerical simulations are in good agreement with the theoretical distribution. The extrapolation of the generalization error to infinite input space size agrees with the theoretical results. Finite size corrections are negative and exhibit two different scaling regimes, depending on the training set size. The variance of the generalization error vanishes for $N \\rightarrow \\infty$ confirming the property of self-averaging.
Representations of Boolean Functions by Perceptron Networks.
Czech Academy of Sciences Publication Activity Database
K?rková, V?ra
Prague : Institute of Computer Science AS CR, 2014 - (K?rková, V.; Bajer, L.; Peška, L.; Vojtáš, R.; Hole?a, M.; Nehéz, M.), s. 68-70 ISBN 978-80-87136-19-5. [ITAT 2014. European Conference on Information Technologies - Applications and Theory /14./. Demänovská dolina (SK), 25.09.2014-29.09.2014] R&D Projects: GA MŠk(CZ) LD13002 Institutional support: RVO:67985807 Keywords : perceptron network s * model complexity * Boolean functions Subject RIV: IN - Informatics, Computer Science
Finite size scaling of the Bayesian perceptron
Buhot, Arnaud; Torres Moreno, Juan-Manuel; Gordon, Mirta B.
1997-06-01
We study numerically the properties of the Bayesian perceptron through a gradient descent on the optimal cost function. The theoretical distribution of stabilities is deduced. It predicts that the optimal generalizer lies close to the boundary of the space of (error-free) solutions. The numerical simulations are in good agreement with the theoretical distribution. The extrapolation of the generalization error to infinite input space size agrees with the theoretical results. Finite size corrections are negative and exhibit two different scaling regimes, depending on the training set size. The variance of the generalization error vanishes for N-->? confirming the property of self-averaging.
Stochastic resonance in an intracellular genetic perceptron
Bates, Russell; Blyuss, Oleg; Zaikin, Alexey
2014-03-01
Intracellular genetic networks are more intelligent than was first assumed due to their ability to learn. One of the manifestations of this intelligence is the ability to learn associations of two stimuli within gene-regulating circuitry: Hebbian-type learning within the cellular life. However, gene expression is an intrinsically noisy process; hence, we investigate the effect of intrinsic and extrinsic noise on this kind of intracellular intelligence. We report a stochastic resonance in an intracellular associative genetic perceptron, a noise-induced phenomenon, which manifests itself in noise-induced increase of response in efficiency after the learning event under the conditions of optimal stochasticity.
Experimental characterization of the perceptron laser rangefinder
Kweon, I. S.; Hoffman, Regis; Krotkov, Eric
1991-01-01
In this report, we characterize experimentally a scanning laser rangefinder that employs active sensing to acquire three-dimensional images. We present experimental techniques applicable to a wide variety of laser scanners, and document the results of applying them to a device manufactured by Perceptron. Nominally, the sensor acquires data over a 60 deg x 60 deg field of view in 256 x 256 pixel images at 2 Hz. It digitizes both range and reflectance pixels to 12 bits, providing a maximum range of 40 m and a depth resolution of 1 cm. We present methods and results from experiments to measure geometric parameters including the field of view, angular scanning increments, and minimum sensing distance. We characterize qualitatively problems caused by implementation flaws, including internal reflections and range drift over time, and problems caused by inherent limitations of the rangefinding technology, including sensitivity to ambient light and surface material. We characterize statistically the precision and accuracy of the range measurements. We conclude that the performance of the Perceptron scanner does not compare favorably with the nominal performance, that scanner modifications are required, and that further experimentation must be conducted.
Vassiliadis, V S
2006-01-01
A novel algorithm for tunable compression to within the precision of reproduction targets, or storage, is proposed. The new algorithm is termed the `Perceptron Algorithm', which utilises simple existing concepts in a novel way, has multiple immediate commercial application aspects as well as it opens up a multitude of fronts in computational science and technology. The aims of this paper are to present the concepts underlying the algorithm, observations by its application to some example cases, and the identification of a multitude of potential areas of applications such as: image compression by orders of magnitude, signal compression including sound as well, image analysis in a multilayered detailed analysis, pattern recognition and matching and rapid database searching (e.g. face recognition), motion analysis, biomedical applications e.g. in MRI and CAT scan image analysis and compression, as well as hints on the link of these ideas to the way how biological memory might work leading to new points of view i...
Learning from correlated patterns by simple perceptrons
International Nuclear Information System (INIS)
Learning behavior of simple perceptrons is analyzed for a teacher-student scenario in which output labels are provided by a teacher network for a set of possibly correlated input patterns, and such that the teacher and student networks are of the same type. Our main concern is the effect of statistical correlations among the input patterns on learning performance. For this purpose, we extend to the teacher-student scenario a methodology for analyzing randomly labeled patterns recently developed in Shinzato and Kabashima 2008 J. Phys. A: Math. Theor. 41 324013. This methodology is used for analyzing situations in which orthogonality of the input patterns is enhanced in order to optimize the learning performance
A Simple Perceptron that Learns Non-Monotonic Rules
Inoue, Jun-ichi; Nishimori, Hidetoshi; Kabashima, Yoshiyuki
1997-01-01
We investigate the generalization ability of a simple perceptron trained in the off-line and on-line supervised modes. Examples are extracted from the teacher who is a non-monotonic perceptron. For this system, difficulties of training can be controlled continuously by changing a parameter of the teacher. We train the student by several learning strategies in order to obtain the theoretical lower bounds of generalization errors under various conditions. Asymptotic behavior o...
Stability of the replica symmetric solution in diluted perceptron learning
Lage-castellanos, Alejandro; Pagnani, Andrea; Angulo, Gretel Quintero
2012-01-01
We study the role played by the dilution in the average behavior of a perceptron model with continuous coupling with the replica method. We analyze the stability of the replica symmetric solution as a function of the dilution field for the generalization and memorization problems. Thanks to a Gardner like stability analysis we show that at any fixed ratio $\\alpha$ between the number of patterns M and the dimension N of the perceptron ($\\alpha=M/N$), there exists a critical d...
The Projectron: a Bounded Kernel-Based Perceptron
Orabona, Francesco; Keshet, Joseph; Caputo, Barbara
2008-01-01
We present a discriminative online algorithm with a bounded memory growth, which is based on the kernel-based Perceptron. Generally, the required memory of the kernel-based Perceptron for storing the online hypothesis is not bounded. Previous work has been focused on discarding part of the instances in order to keep the memory bounded. In the proposed algorithm the instances are not discarded, but projected onto the space spanned by the previous online hypothesis. We derive a relative mistake...
An Efficient Rescaled Perceptron Algorithm for Conic Systems
Vempala, Santosh; Belloni, Alexandre; Freund, Robert Michael
2009-01-01
The classical perceptron algorithm is an elementary row-action/relaxation algorithm for solving a homogeneous linear inequality system Ax > 0. A natural condition measure associated with this algorithm is the Euclidean width {tau} of the cone of feasible solutions, and the iteration complexity of the perceptron algorithm is bounded by 1/{tau}2 [see Rosenblatt, F. 1962. Principles of Neurodynamics. Spartan Books, Washington, DC]. Dunagan and Vempala [Dunagan, J., S. Vempala. 2007. A simple pol...
Stability of the replica symmetric solution in diluted perceptron learning
International Nuclear Information System (INIS)
We study the role played by dilution in the average behavior of a perceptron model with continuous coupling with the replica method. We analyze the stability of the replica symmetric solution as a function of the dilution field for the generalization and memorization problems. Thanks to a Gardner-like stability analysis we show that at any fixed ratio ? between the number of patterns M and the dimension N of the perceptron (? = M/N), there exists a critical dilution field hc above which the replica symmetric ansatz becomes unstable. (letter)
Training a perceptron by a bit sequence: Storage capacity
Schroeder, M.; Kinzel, W.; Kanter, I.
1996-01-01
A perceptron is trained by a random bit sequence. In comparison to the corresponding classification problem, the storage capacity decreases to alpha_c=1.70\\pm 0.02 due to correlations between input and output bits. The numerical results are supported by a signal to noise analysis of Hebbian weights.
Breaking a chaotic image encryption algorithm based on perceptron model
Zhang, Yu; Li, Chengqing; Li, Qin; Zhang, Dan; Shu, Shi
2011-01-01
Recently, a chaotic image encryption algorithm based on perceptron model was proposed. The present paper analyzes security of the algorithm and finds that the equivalent secret key can be reconstructed with only one pair of known-plaintext/ciphertext, which is supported by both mathematical proof and experiment results. In addition, some other security defects are also reported.
Scientific Electronic Library Online (English)
F., Dall Cortivo; E. S., Chalhoub; H. F., Campos Velho.
2012-12-01
Full Text Available Estimativa do perfil de concentração de clorofila, em águas naturais, a partir da radiação emergente na superfície de um corpo d'agua, com o uso de rede neural artificial do tipo Perceptron de Múltiplas Camadas. A concentração de clorofila está relacionada com os coeficientes de absorção e espalhame [...] nto via modelos bio-ópticos. O treinamento da rede é formulado como um problema de otimização, no qual a atualização das variáveis livres da rede (pesos, viés e parâmetros de cada função de ativação) é feita através do método quasi-Newton. Abstract in english In this work the average profile of chlorophyll concentration is estimated from the emitted radiation at the surface of natural waters. This is performed through the use an Artificial Neural Network of Multilayer Perceptron type to act as the inverse operator. Bio-optical models are used to correlat [...] e the chlorophyll concentration with the absorption and scattering coefficients. The network training is formulated as an optimization problem, in which the update of the free variables of network (weights, viéses and each slope of the activation functions) is performed through the quasi-Newton method.
The Role of Weight Shrinking in Large Margin Perceptron Learning
Panagiotakopoulos, Constantinos
2012-01-01
We introduce into the classical perceptron algorithm with margin a mechanism that shrinks the current weight vector as a first step of the update. If the shrinking factor is constant the resulting algorithm may be regarded as a margin-error-driven version of NORMA with constant learning rate. In this case we show that the allowed strength of shrinking depends on the value of the maximum margin. We also consider variable shrinking factors for which there is no such dependence. In both cases we obtain new generalizations of the perceptron with margin able to provably attain in a finite number of steps any desirable approximation of the maximal margin hyperplane. The new approximate maximum margin classifiers appear experimentally to be very competitive in 2-norm soft margin tasks involving linear kernels.
Higher-order probabilistic perceptrons as Bayesian inference engines
International Nuclear Information System (INIS)
This letter makes explicit a structural connection between the Bayes optimal classifier operating on K binary input variables and corresponding two-layer perceptron having normalized output activities and couplings from input to output units of all orders up to K. Given a large and unbiased training set and an effective learning algorithm, such a neural network should be able to learn the statistics of the classification problem and match the a posteriori probabilities given by the Bayes optimal classifier. (author). 18 refs
A Coherent Perceptron for All-Optical Learning
Tezak, Nikolas; Mabuchi, Hideo
2015-01-01
We present nonlinear photonic circuit models for constructing programmable linear transformations and use these to realize a coherent Perceptron, i.e., an all-optical linear classifier capable of learning the classification boundary iteratively from training data through a coherent feedback rule. Through extensive semi-classical stochastic simulations we demonstrate that the device nearly attains the theoretical error bound for a model classification problem.
PENGENALAN CITRA OBJEK SEDERHANA DENGAN JARINGAN SARAF TIRUAN METODE PERCEPTRON
Ardi Pujiyanta
2012-01-01
Konsep bangunan dan benda-benda yang ada di sekeliling didasarkan dan dipengaruhi oleh konsep objek sederhana atau sering disebut geometri ruang tiga dimensi, yaitu memiliki panjang, lebar dan tinggi. Namun, dalam rancangan dan penggambarannya menggunakan gambar berdimensi dua saja. Sehingga pada konsep penggambarannya membutuhkan visualisasi yang lebih detail. Diharapkan jaringan syaraf tiruan metode perceptron dapat mengenali gambar yang sesuai dengan bentuk aslinya. Pada penelitian ini met...
A fast method for calculating the perceptron with maximal stability
Ruja?n, Pa?l
1993-01-01
For the class of linearly separable two class (boolean) functions the Perceptron with maximal stability defines in the space of all possible input configurations the direction along which the gap between the two classes is maximal. This solution has several advantages: it is unique, it is robust, and has the best generalization probability among all known linear discriminants. present here an active set approach to the dual problem, finding the minimal connector between two disjoint convex hu...
Perceptron capacity revisited: classification ability for correlated patterns
Shinzato, Takashi; Kabashima, Yoshiyuki
2007-01-01
In this paper, we address the problem of how many randomly labeled patterns can be correctly classified by a single-layer perceptron when the patterns are correlated with each other. In order to solve this problem, two analytical schemes are developed based on the replica method and Thouless-Anderson-Palmer (TAP) approach by utilizing an integral formula concerning random rectangular matrices. The validity and relevance of the developed methodologies are shown for one known ...
Asymptotic behavior of the magnetization for the perceptron model
Marquez-carreras, David; Rovira, Carles; Tindel, Samy
2005-01-01
In this paper, we show that, in case of a perceptron model for which the number of outputs is a small proportion of the size of the system, the limiting behavior of the magnetization of a given spin, namely the random variable $\\langle\\si_k\\rangle$, can be identified. In fact, we prove a $L^2$ convergence for a collection of those random variables.
The Role of Weight Shrinking in Large Margin Perceptron Learning
Panagiotakopoulos, Constantinos; Tsampouka, Petroula
2012-01-01
We introduce into the classical perceptron algorithm with margin a mechanism that shrinks the current weight vector as a first step of the update. If the shrinking factor is constant the resulting algorithm may be regarded as a margin-error-driven version of NORMA with constant learning rate. In this case we show that the allowed strength of shrinking depends on the value of the maximum margin. We also consider variable shrinking factors for which there is no such dependence...
Use of the 'Perceptron' algorithm to distinguish translational initiation sites in E. coli.
Stormo, G. D.; Schneider, T. D.; Gold, L.; Ehrenfeucht, A.
1982-01-01
We have used a "Perceptron" algorithm to find a weighting function which distinguishes E. coli translational initiation sites from all other sites in a library of over 78,000 nucleotides of mRNA sequence. The "Perceptron" examined sequences as linear representations. The "Perceptron" is more successful at finding gene beginnings than our previous searches using "rules" (see previous paper). We note that the weighting function can find translational initiation sites within sequences that were ...
Hybrid Optimized Back propagation Learning Algorithm For Multi-layer Perceptron
Chakraborty, Mriganka; Ghosh, Arka
2012-01-01
Standard neural network based on general back propagation learning using delta method or gradient descent method has some great faults like poor optimization of error-weight objective function, low learning rate, instability .This paper introduces a hybrid supervised back propagation learning algorithm which uses trust-region method of unconstrained optimization of the error objective function by using quasi-newton method .This optimization leads to more accurate weight upda...
An Automated MR Image Segmentation System Using Multi-layer Perceptron Neural Network
Amiri, S; Movahedi, M M; Kazemi, K.; H. Parsaei+
2013-01-01
Background: Brain tissue segmentation for delineation of 3D anatomical structures from magnetic resonance (MR) images can be used for neuro-degenerative disorders, characterizing morphological differences between subjects based on volumetric analysis of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF), but only if the obtained segmentation results are correct. Due to image artifacts such as noise, low contrast and intensity non-uniformity, there are some classification errors...
Tfwala, Samkele S.; Yu-Min Wang; Yu-Chieh Lin
2013-01-01
Hydrological data are often missing due to natural disasters, improper operation, limited equipment life, and other factors, which limit hydrological analysis. Therefore, missing data recovery is an essential process in hydrology. This paper investigates the accuracy of artificial neural networks (ANN) in estimating missing flow records. The purpose is to develop and apply neural networks models to estimate missing flow records in a station when data from adjacent stations is available. Multi...
Chaudhuri, Sutapa; Das, Debanjana; Sarkar, Ishita; Goswami, Sayantika
2015-04-01
In order to meet the non-stationary characteristics of Magnetotelluric (MT) data series, a new method, which is called EMD-Teager, was proposed based on empirical mode decomposition (EMD) and Teager operator for the first time. With the EMD-Teager method, the amplitude of data series is expressed as a function of frequency and time, and then margin spectrum are calculated statistically from the time-frequency spectrum. This paper focuses on two aspects which are facilitated by applying the EMD-Teager. The first aspect is the time-frequency characteristics analysis of MT signal and using the time-frequency spectrum to do pretreatment for MT signal through piece-wise stationary analysis and MT data subsets selection; the other concerns the calculation of the Teager margin spectrum from the time-frequency spectrum. The conclusion reached through discussion of the first aspect is that EMD-Teager has a strong ability to describe the time-frequency characteristic of MT signal. Using the Teager spectrum, the better data section can be selected and the reliability of geological data is improved greatly. The conclusion draws from the second aspect is that Teager marginal spectrum, which is coming from the integral of Teager time-frequency spectrum along the time axis, overcomes the drawbacks of Fourier methods and minimizes the estimation bias brought about by the non-stationarity feature of MT signal. Therefore, EMD-Teager method is effective in analyzing the time-frequency characteristics and marginal spectrum estimation of MT signals, and it will have a wide application in processing of MT data.
Multilayer Perceptron for Robust Nonlinear Interval Regression Analysis Using Genetic Algorithms
Yi-Chung Hu
2014-01-01
On the basis of fuzzy regression, computational models in intelligence such as neural networks have the capability to be applied to nonlinear interval regression analysis for dealing with uncertain and imprecise data. When training data are not contaminated by outliers, computational models perform well by including almost all given training data in the data interval. Nevertheless, since training data are often corrupted by outliers, robust learning algorithms employed to resist outliers for ...
Application of artificial neural networks (multilayer perceptron) in reactor safety research
International Nuclear Information System (INIS)
One of the key areas of reactor safety research are studies of reliable and safe heat removal from the reactor core and the containment, respectively, of light water reactors. Leakage accidents could carry insulating material into the containment or the building sump of the containment and the associated post-decay heat removal systems. This could obstruct systems functions. In the study titled ''Knowledge-based Modeling of Transport Processes in BWR Coolant Flows Carrying Particle Loads after Loss-of-Coolant Accidents,'' a tool is being created for engineering application which allows the deposition and retention of insulating material in the sump of the reactor containment to be estimated. Potential plant conditions in accidents can be assessed in this way. The study serves the purpose of modeling by means of data-based and knowledge-based methods. In this way, the results of experimental investigations (such as differential pressure tests of retention systems) can be used for modeling purposes. (orig.)
Multilayer perceptron for simulation models reduction: application to a sawmill workshop
Thomas, Philippe; Thomas, Andre?
2011-01-01
Simulation is often used to evaluate supply chain or workshop management. This simulation task needs models, which are difficult to construct. The aim of this work is to reduce the complexity of a simulation model design. The proposed approach combines discrete and continuous approaches in order to construct speeder and simpler reduced model. The simulation model focuses on bottlenecks with a discrete approach according to the theory of constraints. The remaining of the workshop must be taken...
Electron/pion identification in the CBM TRD using a multilayer perceptron
International Nuclear Information System (INIS)
The problem of electron/pion identification in the CBM experiment based on the measurements of energy losses and transition radiation in the TRD detector is discussed. A possibility to solve such a problem by applying an artificial neural network (ANN) is considered. As input information for the network we used both the samples of energy losses of pions or electrons in the TRD absorbers and the 'clever' variable obtained on the basis of the original data. We show that usage of this new variable permits one to reach a reliable level of particle recognition no longer than after 10-20 training epochs; there are practically no fluctuations against the trend, and the needed level of pions suppression is obtained under the condition of a minimal loss of electrons
FORECASTING ON FOREX MARKET WITH RBF AND PERCEPTRON NEURAL NETWORKS
Directory of Open Access Journals (Sweden)
ALEXANDRA KOTTILOVÁ
2012-01-01
Full Text Available This work deals with an alternative approach in financial modelling -artificial neural networks approach. The aim of this paper is to show that this type oftime series modelling is an excellent alternative to classical econometric modelling. Atfirst, neural networks using methods of supervised machine learning are discussed.After explaining theoretical basis of ANN, these models are then applied to specificexchange rate (AUD/USD. Finally, the comparison between statistical models andRBF and perceptron neural networks is made to illustrate the sense of using ANNmodels
Representations of highly-varying functions by perceptron networks.
Czech Academy of Sciences Publication Activity Database
K?rková, V?ra
North Charleston : CreateSpace Independent Publishing Platform, 2013 - (Vina?, T.; Hole?a, M.; Lexa, M.; Peška, L.; Vojtáš, P.), s. 73-76 ISBN 978-1-4909-5208-6. [ITAT 2013. Conference on Theory and Practice of Information Technologies. Donovaly (SK), 11.09.2013-15.09.2013] R&D Projects: GA ?R GAP202/11/1368 Institutional support: RVO:67985807 Keywords : one-hidden-layer networks * perceptron s * Boolean functions * network complexity Subject RIV: IN - Informatics, Computer Science
Perceptron capacity revisited: classification ability for correlated patterns
International Nuclear Information System (INIS)
In this paper, we address the problem of how many randomly labeled patterns can be correctly classified by a single-layer perceptron when the patterns are correlated with each other. In order to solve this problem, two analytical schemes are developed based on the replica method and the Thouless-Anderson-Palmer (TAP) approach by utilizing an integral formula concerning random rectangular matrices. The validity and relevance of the developed methodologies are shown for one known result and two example problems. A message-passing algorithm to perform the TAP scheme is also presented
Entropy landscape of solutions in the binary perceptron problem
International Nuclear Information System (INIS)
The statistical picture of the solution space for a binary perceptron is studied. The binary perceptron learns a random classification of input random patterns by a set of binary synaptic weights. The learning of this network is difficult especially when the pattern (constraint) density is close to the capacity, which is supposed to be intimately related to the structure of the solution space. The geometrical organization is elucidated by the entropy landscape from a reference configuration and of solution-pairs separated by a given Hamming distance in the solution space. We evaluate the entropy at the annealed level as well as replica symmetric level and the mean field result is confirmed by the numerical simulations on single instances using the proposed message passing algorithms. From the first landscape (a random configuration as a reference), we see clearly how the solution space shrinks as more constraints are added. From the second landscape of solution-pairs, we deduce the coexistence of clustering and freezing in the solution space. (paper)
Generalization and capacity of extensively large two-layered perceptrons
International Nuclear Information System (INIS)
The generalization ability and storage capacity of a treelike two-layered neural network with a number of hidden units scaling as the input dimension is examined. The mapping from the input to the hidden layer is via Boolean functions; the mapping from the hidden layer to the output is done by a perceptron. The analysis is within the replica framework where an order parameter characterizing the overlap between two networks in the combined space of Boolean functions and hidden-to-output couplings is introduced. The maximal capacity of such networks is found to scale linearly with the logarithm of the number of Boolean functions per hidden unit. The generalization process exhibits a first-order phase transition from poor to perfect learning for the case of discrete hidden-to-output couplings. The critical number of examples per input dimension, ?c, at which the transition occurs, again scales linearly with the logarithm of the number of Boolean functions. In the case of continuous hidden-to-output couplings, the generalization error decreases according to the same power law as for the perceptron, with the prefactor being different
Handwritten Arabic Numeral Recognition using a Multi Layer Perceptron
Das, Nibaran; Saha, Sudip; Haque, Syed Sahidul
2010-01-01
Handwritten numeral recognition is in general a benchmark problem of Pattern Recognition and Artificial Intelligence. Compared to the problem of printed numeral recognition, the problem of handwritten numeral recognition is compounded due to variations in shapes and sizes of handwritten characters. Considering all these, the problem of handwritten numeral recognition is addressed under the present work in respect to handwritten Arabic numerals. Arabic is spoken throughout the Arab World and the fifth most popular language in the world slightly before Portuguese and Bengali. For the present work, we have developed a feature set of 88 features is designed to represent samples of handwritten Arabic numerals for this work. It includes 72 shadow and 16 octant features. A Multi Layer Perceptron (MLP) based classifier is used here for recognition handwritten Arabic digits represented with the said feature set. On experimentation with a database of 3000 samples, the technique yields an average recognition rate of 94....
Fernández-Delgado, Manuel; Cernadas, Eva; Barro, Senén; Ribeiro, Jorge; Neves, José
2014-02-01
The Direct Kernel Perceptron (DKP) (Fernández-Delgado et al., 2010) is a very simple and fast kernel-based classifier, related to the Support Vector Machine (SVM) and to the Extreme Learning Machine (ELM) (Huang, Wang, & Lan, 2011), whose ?-coefficients are calculated directly, without any iterative training, using an analytical closed-form expression which involves only the training patterns. The DKP, which is inspired by the Direct Parallel Perceptron, (Auer et al., 2008), uses a Gaussian kernel and a linear classifier (perceptron). The weight vector of this classifier in the feature space minimizes an error measure which combines the training error and the hyperplane margin, without any tunable regularization parameter. This weight vector can be translated, using a variable change, to the ?-coefficients, and both are determined without iterative calculations. We calculate solutions using several error functions, achieving the best trade-off between accuracy and efficiency with the linear function. These solutions for the ? coefficients can be considered alternatives to the ELM with a new physical meaning in terms of error and margin: in fact, the linear and quadratic DKP are special cases of the two-class ELM when the regularization parameter C takes the values C=0 and C=?. The linear DKP is extremely efficient and much faster (over a vast collection of 42 benchmark and real-life data sets) than 12 very popular and accurate classifiers including SVM, Multi-Layer Perceptron, Adaboost, Random Forest and Bagging of RPART decision trees, Linear Discriminant Analysis, K-Nearest Neighbors, ELM, Probabilistic Neural Networks, Radial Basis Function neural networks and Generalized ART. Besides, despite its simplicity and extreme efficiency, DKP achieves higher accuracies than 7 out of 12 classifiers, exhibiting small differences with respect to the best ones (SVM, ELM, Adaboost and Random Forest), which are much slower. Thus, the DKP provides an easy and fast way to achieve classification accuracies which are not too far from the best one for a given problem. The C and Matlab code of DKP are freely available. PMID:24287336
Duckitt, Kirsten; Qureshi, Aysha
1991-01-01
Recurrent miscarriage is the spontaneous loss of three or more consecutive pregnancies with the same biological father in the first trimester; it affects 1% to 2% of women, in half of whom there is no identifiable cause. Overall, 75% of affected women will have a successful subsequent pregnancy, but this rate falls for older mothers and with increasing number of miscarriages.Antiphospholipid syndrome, with anticardiolipin or lupus anticoagulant antibodies, is present in 15% of women with r...
Perceptron-like Algorithms and Generalization Bounds for Learning to Rank
Chaudhuri, Sougata; Tewari, Ambuj
2014-01-01
Learning to rank is a supervised learning problem where the output space is the space of rankings but the supervision space is the space of relevance scores. We make theoretical contributions to the learning to rank problem both in the online and batch settings. First, we propose a perceptron-like algorithm for learning a ranking function in an online setting. Our algorithm is an extension of the classic perceptron algorithm for the classification problem. Second, in the set...
A Novel Single Neuron Perceptron with Universal Approximation and XOR Computation Properties
Ehsan Lotfi; -r Akbarzadeh-t, M.
2014-01-01
We propose a biologically motivated brain-inspired single neuron perceptron (SNP) with universal approximation and XOR computation properties. This computational model extends the input pattern and is based on the excitatory and inhibitory learning rules inspired from neural connections in the human brain's nervous system. The resulting architecture of SNP can be trained by supervised excitatory and inhibitory online learning rules. The main features of proposed single layer perceptron are un...
On-line learning of non-monotonic rules by simple perceptron
Inoue, Jun-ichi; Nishimori, Hidetoshi; Kabashima, Yoshiyuki
1997-01-01
We study the generalization ability of a simple perceptron which learns unlearnable rules. The rules are presented by a teacher perceptron with a non-monotonic transfer function. The student is trained in the on-line mode. The asymptotic behaviour of the generalization error is estimated under various conditions. Several learning strategies are proposed and improved to obtain the theoretical lower bound of the generalization error.
Intelligent control of HVAC systems. Part II: perceptron performance analysis
Directory of Open Access Journals (Sweden)
Ioan URSU
2013-09-01
Full Text Available This is the second part of a paper on intelligent type control of Heating, Ventilating, and Air-Conditioning (HVAC systems. The whole study proposes a unified approach in the design of intelligent control for such systems, to ensure high energy efficiency and air quality improving. In the first part of the study it is considered as benchmark system a single thermal space HVAC system, for which it is assigned a mathematical model of the controlled system and a mathematical model(algorithm of intelligent control synthesis. The conception of the intelligent control is of switching type, between a simple neural network, a perceptron, which aims to decrease (optimize a cost index,and a fuzzy logic component, having supervisory antisaturating role for neuro-control. Based on numerical simulations, this Part II focuses on the analysis of system operation in the presence only ofthe neural control component. Working of the entire neuro-fuzzy system will be reported in a third part of the study.
30 years of adaptive neural networks - Perceptron, Madaline, and backpropagation
Widrow, Bernard; Lehr, Michael A.
1990-01-01
Fundamental developments in feedforward artificial neural networks from the past thirty years are reviewed. The history, origination, operating characteristics, and basic theory of several supervised neural-network training algorithms (including the perceptron rule, the least-mean-square algorithm, three Madaline rules, and the backpropagation technique) are described. The concept underlying these iterative adaptation algorithms is the minimal disturbance principle, which suggests that during training it is advisable to inject new information into a network in a manner that disturbs stored information to the smallest extent possible. The two principal kinds of online rules that have developed for altering the weights of a network are examined for both single-threshold elements and multielement networks. They are error-correction rules, which alter the weights of a network to correct error in the output response to the present input pattern, and gradient rules, which alter the weights of a network during each pattern presentation by gradient descent with the objective of reducing mean-square error (averaged over all training patterns).
Isomorphisms in Multilayer Networks
Kivelä, Mikko
2015-01-01
We extend the concept of graph isomorphisms to multilayer networks, and we identify multiple types of isomorphisms. For example, in multilayer networks with a single "aspect" (i.e., type of layering), permuting vertex labels, layer labels, and both of types of layers each yield a different type of isomorphism. We discuss how multilayer network isomorphisms naturally lead to defining isomorphisms in any type of network that can be represented as a multilayer network. This thereby yields isomorphisms for multiplex networks, temporal networks, networks with both such features, and more. We reduce each of the multilayer network isomorphism problems to a graph isomorphism problem, and we use this reduction to prove that the multilayer network isomorphism problem is computationally equally hard as the graph isomorphism problem. One can thus use software that has been developed to solve graph isomorphism problems as a practical means for solving multilayer network isomorphism problems.
Perceptron-like computation based on biologically-inspired neurons with heterosynaptic mechanisms
Kaluza, Pablo; Urdapilleta, Eugenio
2014-10-01
Perceptrons are one of the fundamental paradigms in artificial neural networks and a key processing scheme in supervised classification tasks. However, the algorithm they provide is given in terms of unrealistically simple processing units and connections and therefore, its implementation in real neural networks is hard to be fulfilled. In this work, we present a neural circuit able to perform perceptron's computation based on realistic models of neurons and synapses. The model uses Wang-Buzsáki neurons with coupling provided by axodendritic and axoaxonic synapses (heterosynapsis). The main characteristics of the feedforward perceptron operation are conserved, which allows to combine both approaches: whereas the classical artificial system can be used to learn a particular problem, its solution can be directly implemented in this neural circuit. As a result, we propose a biologically-inspired system able to work appropriately in a wide range of frequencies and system parameters, while keeping robust to noise and error.
Multilayer Insulation Material Guidelines
Finckenor, M. M.; Dooling, D.
1999-01-01
Multilayer Insulation Material Guidelines provides data on multilayer insulation materials used by previous spacecraft such as Spacelab and the Long-Duration Exposure Facility and outlines other concerns. The data presented in the document are presented for information only. They can be used as guidelines for multilayer insulation design for future spacecraft provided the thermal requirements of each new design and the environmental effects on these materials are taken into account.
Aksin, Devrim Y?lmaz; Aras, Sualp; Goknar, Izzet Cem
2011-01-01
The implementation of a perceptron that can classify data separable by two parallel hyper-planes or equivalentlyof a Single-Level TL-XOR gate is proposed using 10 MOS transistors and 2 capacitors. The functional subblockdecomposition of the Perceptron with two separating hyper-planes, its CMOS implementation explainingthe operation of each sub-block and simulation results, obtained using the SpectreS simulator and AMS 0.8mmCMOS double-poly double-metal technology parameters are presented. A b...
The Multidimensional Cube Recurrence
Henriques, Andre
2007-01-01
We introduce a recurrence which we term the multidimensional cube recurrence, generalizing the octahedron recurrence studied by Propp, Fomin and Zelevinsky, Speyer, and Fock and Goncharov and the three-dimensional cube recurrence studied by Fomin and Zelevinsky, and Carroll and Speyer. The states of this recurrence are indexed by tilings of a polygon with rhombi, and the variables in the recurrence are indexed by vertices of these tilings. We travel from one state of the recurrence to another by performing elementary flips. We show that the values of the recurrence are independent of the order in which we perform the flips; this proof involves nontrivial combinatorial results about rhombus tilings which may be of independent interest. We then show that the multidimensional cube recurrence exhibits the Laurent phenomenon -- any variable is given by a Laurent polynomial in the other variables. We recognize a special case of the multidimensional cube recurrence as giving explicit equations for the isotropic Gras...
A quenched large deviation principle and a Parisi formula for a Perceptron version of the GREM
Bolthausen, E.; Kistler, N.
2010-01-01
We introduce a perceptron version of the Generalized Random Energy Model, and prove a quenched Sanov type large deviation principle for the empirical distribution of the random energies. The dual of the rate function has a representation through a variational formula which is closely related to the Parisi variational formula for the SK-model.
How to guess the inter magnetic bubble potential by using a simple perceptron ?
Padovani, S.
2004-01-01
It is shown that magnetic bubble films behaviour can be described by using a 2D super-Ising hamiltonian. Calculated hysteresis curves and magnetic domain patterns are successfully compared with experimental results taken in literature. The reciprocal problem of finding paramaters of the super-Ising model to reproduce computed or experimental magnetic domain pictures is solved by using a perceptron neural network.
Full Text Available Resources Brochures & Videos Resource Links Books & Periodicals Cancer Centers print email Resources » Brochures & Videos Dealing with Recurrence We know that the topic of recurrence in cancer patients can be an overwhelming ...
Preeti, L; Magesh, KT; K. Rajkumar; Karthik, Raghavendhar
2011-01-01
Recurrent aphthous ulcers are common painful mucosal conditions affecting the oral cavity. Despite their high prevalence, etiopathogenesis remains unclear. This review article summarizes the clinical presentation, diagnostic criteria, and recent trends in the management of recurrent apthous stomatitis.
Full Text Available Resources Brochures & Videos Resource Links Books & Periodicals Cancer Centers print email Resources » Brochures & Videos Dealing with Recurrence We know that the topic of recurrence in cancer patients ...
Multilayer dielectric diffraction gratings
Perry, M.D.; Britten, J.A.; Nguyen, H.T.; Boyd, R.; Shore, B.W.
1999-05-25
The design and fabrication of dielectric grating structures with high diffraction efficiency used in reflection or transmission is described. By forming a multilayer structure of alternating index dielectric materials and placing a grating structure on top of the multilayer, a diffraction grating of adjustable efficiency, and variable optical bandwidth can be obtained. Diffraction efficiency into the first order in reflection varying between 1 and 98 percent has been achieved by controlling the design of the multilayer and the depth, shape, and material comprising the grooves of the grating structure. Methods for fabricating these gratings without the use of ion etching techniques are described. 7 figs.
Cox, P. J.; Leach, R. D.; Ellis, Harold
1981-01-01
One hundred consecutive recurrences following repair of inguinal hernias have been studied; 62 were direct, 30 indirect, 7 pantaloon and one a femoral hernia. Half the indirect recurrences occurred within a year of repair and probably represented failure to detect a small indirect sac. Later indirect recurrences probably represented failure to repair the internal ring. Nine of the direct hernias were medial funicular recurrences and represented failure to anchor the darn medially. The rest of...
Recurrent zosteriform herpes simplex
Inamadar Arun; Yatgiri R
1992-01-01
A 25-year-old man had recurrent zosteriform herpes simplex for past 6 years. The attacks were precipitated by prolonged exposure to sunlight. Pain was mild and lesions used to subside each time in about 7 days. Clinical features which help in differentiating recurrent herpes simplex from recurrent herpes zoster are summarized.
Recurrent zosteriform herpes simplex
Directory of Open Access Journals (Sweden)
Inamadar Arun
1992-01-01
Full Text Available A 25-year-old man had recurrent zosteriform herpes simplex for past 6 years. The attacks were precipitated by prolonged exposure to sunlight. Pain was mild and lesions used to subside each time in about 7 days. Clinical features which help in differentiating recurrent herpes simplex from recurrent herpes zoster are summarized.
Imaging recurrent parosteal osteosarcoma
International Nuclear Information System (INIS)
The aim of this study was to document the imaging features of recurrent parosteal osteosarcoma. The clinical and imaging records of 33 patients with a parosteal osteosarcoma referred to an orthopaedic oncology service over a 17-year period were retrospectively reviewed. The mode of identification of locally recurrent tumour was noted, together with the management and clinical outcome. Five patients developed a local recurrence of their parosteal osteosarcoma ranging from 6 months to 10 years after initial surgery. In 4 patients the recurrence was first suspected clinically due to the development of a mass. In the fifth patient recurrence was first detected on routine follow-up radiography. In 4 patients the recurrence could be identified on radiography as a mineralized mass. All the recurrences were readily identified on MR imaging, despite artefacts from prostheses. The recurrences were also evident in the 3 cases in which bone scintigraphy was performed. Local recurrence of parosteal osteosarcoma is adequately detected with a combination of clinical examination and conventional radiography. MR imaging is required to stage local recurrence or where radiography has failed to confirm clinically suspected recurrence. The routine use of MR imaging to follow-up patients is of doubtful value because of the frequently long time between initial surgery and relapse. (orig.)
Core reactivity estimation in space reactors using recurrent dynamic networks
International Nuclear Information System (INIS)
A recurrent Multi Layer Perceptron (MLP) network topology is used in the identification of nonlinear dynamic systems from only the input/output measurements. This effort is part of a research program devoted in developing real-time diagnostics and predictive control techniques for large-scale complex nonlinear dynamic systems. The identification is performed in the discrete time domain, with the learning algorithm being a modified form of the Back Propagation (BP) rule. The Recurrent Dynamic Network (RDN) developed is applied for the total core reactivity prediction of a spacecraft reactor from only neutronic power level measurements. Results indicate that the RDN can reproduce the nonlinear response of the reactor while keeping the number of nodes roughly equal to the relative order of the system. As accuracy requirements are increased, the number of required nodes also increases, however, the order of the RDN necessary to obtain such results is still in the same order of magnitude as the order of the matematical model of the system. There are a number of issues identified regarding the behavior of the RDN, which at this point are unresolved and require further research. Nevertheless, it is believed that use of the recurrent MLP structure with a variety of different learning algorithms may prove useful in utilizing artifical neural networks (ANNs) for recognition, classification and prediction of dynamic systems
TAG, dynamic programming, and the perceptron for efficient, feature-rich parsing
Carreras Pérez, Xavier; Collins, Michael; Koo, Terry
2008-01-01
We describe a parsing approach that makes use of the perceptron algorithm, in conjunction with dynamic programming methods, to recover full constituent-based parse trees. The formalism allows a rich set of parse-tree features, including PCFGbased features, bigram and trigram dependency features, and surface features. A severe challenge in applying such an approach to full syntactic parsing is the efficiency of the parsing algorithms involved. We show that efficient training is feasible, using...
On the Complexity of the Class of Regions Computable by a Two-Layered Perceptron
Mayoraz, Eddy
1996-01-01
This work is concerned with the computational complexity of the recognition of $\\mbox{LP}_2$, the class of regions of the Euclidian space that can be classified exactly by a two-layered perceptron. Several subclasses of $\\mbox{LP}_2$ of particular interest are also considered. We show that the recognition problems of $\\mbox{LP}_2$ and of other classes considered here are intractable, even in some favorable circumstances. We then identify special cases having polynomial time algorithms.
Learning rate and attractor size of the single-layer perceptron
International Nuclear Information System (INIS)
We study the simplest possible order one single-layer perceptron with two inputs, using the delta rule with online learning, in order to derive closed form expressions for the mean convergence rates. We investigate the rate of convergence in weight space of the weight vectors corresponding to each of the 14 out of 16 linearly separable rules. These vectors follow zigzagging lines through the piecewise constant vector field to their respective attractors. Based on our studies, we conclude that a single-layer perceptron with N inputs will converge in an average number of steps given by an Nth order polynomial in (t/l), where t is the threshold, and l is the size of the initial weight distribution. Exact values for these averages are provided for the five linearly separable classes with N=2. We also demonstrate that the learning rate is determined by the attractor size, and that the attractors of a single-layer perceptron with N inputs partition RN+RN
Advances in Artificial Neural Networks – Methodological Development and Application
Yanbo Huang
2009-01-01
Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other neural network training algorithms for other networks such as radial basis function, recurrent network, feedback network, and unsupervised Kohonen self-organizing network. These networks, especially the multilayer perceptron network with a back...
Control of Multilayer Networks
Menichetti, Giulia; Bianconi, Ginestra
2015-01-01
The controllability of a network is a theoretical problem of relevance in a variety of contexts ranging from financial markets to the brain. Until now, network controllability has been characterized only on isolated networks, while the vast majority of complex systems are formed by multilayer networks. Here we build a theoretical framework for the linear controllability of multilayer networks by mapping the problem into a combinatorial matching problem. We found that correlating the external signals in the different layers can significantly reduce the multiplex network robustness to node removal, as it can be seen in conjunction with a hybrid phase transition occurring in interacting Poisson networks. Moreover we observe that multilayer networks can stabilize the fully controllable multiplex network configuration that can be stable also when the full controllability of the single network is not stable.
Directory of Open Access Journals (Sweden)
Singh S
1998-01-01
Full Text Available A case of recurrent pityriasis rosea in a 25-year old man is reported. He had his first attack 4 years ago and new outbreaks followed every year in winter with last 2 episodes occurring in the same year. All investigations were normal and no explanation for recurrences was found.
Singh S; Singh Sanjay; Pandey S
1998-01-01
A case of recurrent pityriasis rosea in a 25-year old man is reported. He had his first attack 4 years ago and new outbreaks followed every year in winter with last 2 episodes occurring in the same year. All investigations were normal and no explanation for recurrences was found.
Neves, J C S
2015-01-01
In this work we have carried out an approach between the nonsingular scientific cosmologies (without the initial singularity, the big bang), specially the cyclic models, and the Nietzsche's thought of the eternal recurrence. Moreover, we have pointed out reasons for the Nietzsche's search for scientific proofs about the eternal recurrence in the decade of 1880's.
International Nuclear Information System (INIS)
Diffusion experiments are usually performed at macroscopic length scales, use of multilayers can lower these scale down to the nanometer range. This paper describes the main idea governing atomic transport at such short distance and in such inhomogeneous systems. The basic experimental methods involved are also discussed. Some representative recent works are shortly described
Energy Technology Data Exchange (ETDEWEB)
Piecuch, M.
1988-10-01
Diffusion experiments are usually performed at macroscopic length scales, use of multilayers can lower these scale down to the nanometer range. This paper describes the main idea governing atomic transport at such short distance and in such inhomogeneous systems. The basic experimental methods involved are also discussed. Some representative recent works are shortly described.
Investigation of periodic multilayers
Bodnarchuck, V.; Cser, L.; Ignatovich, V.; Veres, T.; Yaradaykin, S.
2009-01-01
Periodic multilayers of various periods were prepared according to an algorithm proposed by the authors. The reflectivity properties of these systems were investigated using neutron reflectometry.The obtained experimental results were compared with the theoretical expectations. In first approximation, the results proved the main features of the theoretical predictions. These promising results initiate further research of such systems.
Piecuch, M.
1988-01-01
Diffusion experiments are usually performed at macroscopic length scales, use of multilayers can lower these scale down to the nanometer range. This paper describes the main idea governing atomic transport at such short distance and in such inhomogeneous systems. The basic experimental methods involved are also discussed. Some representative recent works are shortly described.
Antimicrobial polypeptide multilayer nanocoatings.
Rudra, Jai S; Dave, Komal; Haynie, Donald T
2006-01-01
A multilayer coating (or film) of nanometer-thick layers can be made by sequential adsorption of oppositely charged polyelectrolytes on a solid support. The method is known as layer-by-layer assembly (LBL). No special apparatus is required for LBL and nanofilms can be prepared under mild, physiological conditions. A multilayer nanofilm in which at least one of the constituent species is a polypeptide is a polypeptide multilayer nanofilm. The present work was aimed at assessing whether polypeptide multilayer nanofilms with specific antimicrobial properties could be prepared by incorporation of a known antimicrobial agent in the film structure, in this case the edible protein hen egg white lysozyme (HEWL). The chicken enzyme is widely employed as a human food preservative. An advantage of LBL in this context is that the nanofilm is fabricated directly on the surface of interest, eliminating the need to incorporate the antimicrobial in other packaging materials. Here, nanofilms were made of poly(L-glutamic acid) (PLGA), which is highly negatively charged in the mildly acidic pH range, and HEWL, which has a high net positive charge at acidic pH. We show that PLGA/HEWL nanofilms inhibit growth of the model microbe Microccocus luteus in the surrounding liquid medium. The amount of HEWL released from PLGA/HEWL films depends on the number of HEWL layers and therefore on the total quantity of HEWL in the films. This initial study provides a sketch of the scope for further development of LBL in the area of antimicrobial polypeptide multilayer films. Potential applications of such films include strategies for food preservation and coatings for implant devices. PMID:17176751
On Concircularly Recurrent Finsler Manifolds
Youssef, Nabil L
2013-01-01
Two special Finsler spaces have been introduced and investigated, namely $R^h$-recurrent Finsler space and consircularly recurrent Finsler space. The defining properties of these spaces are formulated in terms of the first curvature tensor of Cartan connection. The following three results constitute the main object of the present paper: 1. A concircularly flat Finsler manifold is necessarily of constant curvature (Theorem A); 2. Every $R^h$-recurrent Finsler manifold is concirculaly recurrent with the same recurrence form (Theorem B); 3. Every horizontally integrable concircularly recurrent Finsler manifold is $R^h$-recurrent with the same recurrence form (Theorem C). The whole work is formulated in a coordinate-free form.
Perceptrons with Hebbian Learning Based on Wave Ensembles in Spatially Patterned Potentials
Espinosa-Ortega, T.; Liew, T. C. H.
2015-03-01
A general scheme to realize a perceptron for hardware neural networks is presented, where multiple interconnections are achieved by a superposition of Schrödinger waves. Spatially patterned potentials process information by coupling different points of reciprocal space. The necessary potential shape is obtained from the Hebbian learning rule, either through exact calculation or construction from a superposition of known optical inputs. This allows implementation in a wide range of compact optical systems, including (1) any nonlinear optical system, (2) optical systems patterned by optical lithography, and (3) exciton-polariton systems with phonon or nuclear spin interactions.
Multilayer graphene waveguides
Smirnova, Daria; Iorsh, Ivan; Shadrivov, Ilya; Kivshar, Yuri
2014-01-01
We study dispersion properties of TM-polarized electromagnetic waves guided by a multilayer graphene metamaterial. We demonstrate that both dispersion and localization of the guided modes can be efficiently controlled by changing the number of layers in the structure. Remarkably, we find that in the long wavelength limit, the dispersion of the fundamental mode of the N-layer graphene structure coincides with the dispersion of a plasmon mode supported by a single graphene lay...
Coherency stresses in multilayers
Saada, Georges
2008-01-01
Abstract The determination of the elastic state of coherently matched layers is of importance in a wide range of domains: epitaxial films on a substrate with different crystal structures, deformation of a lamella welded on a substrate, lamellar crystals. It is shown that the elastic state of coherently matched multilayers depends on two coupled field quantities: the stress (or equivalently the elastic strain), and the curvature. A general method, is derived to determine these f...
Recurrent herpes zoster myelitis.
Baik, J. S.; Kim, W. C.; Heo, J. H.; Zheng, H. Y.
1997-01-01
Recurrent zoster myelitis is quite rare. We present a previously healthy 27-year-old woman who developed recurrent attacks of myelopathy shortly after the characteristic skin rashes of herpes zoster. Magnetic resonance imaging studies demonstrated each lesion in the spinal cord at the same segments as the skin lesions. She had two attacks at opposite sites at the same spinal cord level and complete recovery after being treated with intravenous acyclovir. We suspect that direct invasion of var...
Microchimerism in recurrent miscarriage
Gammill, Hilary S.; Stephenson, Mary D.; Aydelotte, Tessa M.; Lee Nelson, J.
2014-01-01
Maternal–fetal cell exchange during pregnancy results in acquisition of microchimerism, which can durably persist in both recipients. Naturally acquired microchimerism may impact maternal–fetal interaction in pregnancy. We conducted studies to ask whether microchimerism that a woman acquired from her own mother is detectable before or during pregnancy in women with recurrent miscarriage. Fetal microchimerism was also assayed. Women with primary idiopathic recurrent miscarriage (n=23) and ...
Weight space structure and analysis using a finite replica number in the Ising perceptron
International Nuclear Information System (INIS)
The weight space of the Ising perceptron, in which a set of random patterns is stored, is examined using the generating function of the partition function ?(n) = (1/N)log[Zn] as the dimension of the weight vector N tends to infinity, where Z is the partition function and [c] represents the configurational average. We utilize ?(n) for two purposes, depending on the value of the ratio ? = M/N, where M is the number of random patterns. For ?s = 0.833..., we employ ?(n), in conjunction with Parisi's one-step replica symmetry breaking scheme in the limit of n?0, to evaluate the complexity that characterizes the number of disjoint clusters of weights that are compatible with a given set of random patterns, which indicates that, in typical cases, the weight space is equally dominated by a single large cluster of exponentially many weights and exponentially many small clusters of a single weight. For ?>?s, on the other hand, ?(n) is used to assess the rate function of a small probability that a given set of random patterns is atypically separable by the Ising perceptrons. We show that the analyticity of the rate function changes at ? = ?GD = 1.245..., which implies that the dominant configuration of the atypically separable patterns exhibits a phase transition at this critical ratio. Extensive numerical experiments are conducted to support the theoretical predictions
Learning by random walks in the weight space of the Ising perceptron
International Nuclear Information System (INIS)
Several variants of a stochastic local search process for constructing the synaptic weights of an Ising perceptron are studied. In this process, binary patterns are sequentially presented to the Ising perceptron and are then learned as the synaptic weight configuration is modified through a chain of single- or double-weight flips within the compatible weight configuration space of the earlier learned patterns. This process is able to reach a storage capacity of ??0.63 for pattern length N = 101 and ??0.41 for N = 1001. If in addition a relearning process is exploited, the learning performance is further improved to a storage capacity of ??0.80 for N = 101 and ??0.42 for N = 1001. We found that, for a given learning task, the solutions constructed by the random walk learning process are separated by a typical Hamming distance, which decreases with the constraint density ? of the learning task; at a fixed value of ?, the width of the Hamming distance distribution decreases with N
Beyond Bragg mirrors: the design of aperiodic omnidirectional multilayer reflectors
International Nuclear Information System (INIS)
A new method that enables omnidirectional reflectivity for all polarizations of incident light over a wide selectable range of wavelengths was used to design aperiodic multilayer mirrors. Choosing the materials, and with the desired threshold value of the reflection coefficient also being given, the resulting reflectors work for all polarizations in a predetermined range of incidence angles and wavelengths. They are 1D photonic aperiodic crystals composed of a stack of layers arranged according to a deterministic aperiodic substitutive sequence appropriately determined. In the calculation of the optical multilayer properties with the Rayleigh-Abeles matrices, the use of the computationally efficient building block recurrence or trace-antitrace map techniques avoids numerical instability and strongly reduces computational time. Experimental measurements of a prototype satisfying predetermined requirements fabricated after the sequence generated by ?:(a, b)?(bba, bbba) show excellent agreement.
Hyperhomocysteinemia in Recurrent Miscarriage
International Nuclear Information System (INIS)
Objective: An elevated total plasma homocysteine level has been suggested as a possible risk factor in women suffering from recurrent pregnancy loss. The current study was undertaken to assess the association between homocysteine, folate, cobalamin (vitamin B12) and the risk of recurrent pregnancy loss. Design: Case . control study Materials and Methods: The study included 57 non-pregnant Egyptian women. They were classified according to their obstetric history into 2 groups: 32 cases with at least two consecutive miscarriages (Study group), and 25 cases with normal obstetric history (Control group). All cases were tested for plasma total homocysteine, serum folate and cobalamin (vitamin B12). Results: The fasting total homocysteine was significantly higher in the study group as compared to the control group. While the median concentrations for the vitamins studied were significantly lower in women of the study group as compared to the controls. Elevated homocysteine and reduced vitamin B12 can be considered risk factors for recurrent miscarriage with odds ratio (OR) and 95% confidence intervals (95% CI) of 1.839 (1.286, 2.63) and 1.993 (1.346, 2.951) respectively in the group of recurrent miscarriages. The OR (95% CI) in the study population for low serum folate concentrations was 1.23 (0.776, 2.256). Conclusion: Elevated homocysteine and reduced serum vitamin B12 are risk factors for recurrent miscarriage. Low serum folate did not seem a risk factor for recurrent miscarriage. Testing for homocysteine levels in women suffering from unexplained recurrent miscarriage and pre-conceptional supplementation with vitamin B12 might be beneficial to improve pregnancy outcome
Process for manufacturing multilayer capacitors
Lauf, Robert J. (Oak Ridge, TN); Holcombe, Cressie E. (Knoxville, TN); Dykes, Norman L. (Oak Ridge, TN)
1996-01-01
The invention is directed to a method of manufacture of multilayer electrical components, especially capacitors, and components made by such a method. High capacitance dielectric materials and low cost metallizations layered with such dielectrics may be fabricated as multilayer electrical components by sintering the metallizations and the dielectrics during the fabrication process by application of microwave radiation.
International Nuclear Information System (INIS)
A set of projection images is acquired during longitudinal tomography with an image intensifier TV system. Reconstruction of tomograms in each desired plane is achieved by shifting and summing up to the digitalized projection images. Digital multilayer and conventional film tomograms mainly of the respiratory tract and skeleton have been compared in 100 patients. Image quality is comparable with both methods. Disadvantage of digital tomography is lower spatial resolution (512x512 matrix size); advantages include lower radiation dose, shorter study time, and facilities of digital imaging. (orig.)
J. Szajnar; P. Wróbel; T. Wróbel
2010-01-01
In paper is presented the possibility of making of multi-layers cast steel castings in result of connection of casting and welding coating technologies. First layer was composite surface layer on the basis of Fe-Cr-C alloy, which was put directly in founding process of cast carbon steel 200–450 with use of preparation of mould cavity method. Second layer were padding welds, which were put with use of TIG – Tungsten Inert Gas surfacing by welding technology with filler on Ni matrix, Ni and...
Recurrent Pneumonia in Children
Directory of Open Access Journals (Sweden)
Solmaz Çelebi
2010-06-01
Full Text Available Objective: The aim of this study was to determine the relative frequency and describe the predisposing causes of recurrent pneumonia in children. Material and methods: We retrospectively reviewed the medical records of patients with pneumonia at Uludag University Medical Faculty, Department of Pediatrics, between January 1998 and December 2007. Recurrent pneumonia was defined as at least two episodes in a 1 year period or at least three episodes over a lifetime. Patients with recurrent pneumonia were included in this study.Results: During the study period, 1617 children were admitted to hospital with a diagnosis of pneumonia, 185 (11.4% met the criteria for recurrent pneumonia. The mean age of patients was 16±32 months (3 months-14 years and 61% were male. An underlying cause was identified in 143 patients (77%. Of these, the underlying cause was diagnosed prior the pneumonia in 25 patients (17%, during the first episode in 30 (21%, and during recurrence in 88 (62%. Underlying causes included congenital cardiac defects in 32 patients (17.2%, gastroesophageal reflux in 31 patients (16.7%, aspiration syndrome in 27 patients (14.5%, asthma in 16 patients (8.6%, cystic fibrosis in 12 patients (6.4% immune disorders in 10 patients (5.4%, tuberculosis in 9 patients (4.8% and anomalies of the chest and lung in 6 patients (3.2%. No predisposing illness could be demonstrated in 42 patients (33%. Conclusion: Recurrent pneumonia occurred in 11.4% of all children hospitalized for pneumonia. The underlying cause was identified in 77% of the children. The most common causes were congenital cardiac defects, gastroesophageal reflux and aspiration syndrome.
Wild recurrent critical points
Rivera-Letelier, J
2004-01-01
It is conjectured that a rational map whose coefficients are algebraic over $\\Q_p$ has no wandering components of the Fatou set. R. Benedetto has shown that any counter example to this conjecture must have a wild recurrent critical point. We provide here the first examples of rational maps whose coefficients are algebraic over $\\Q_p$ and that have a (wild) recurrent critical point. In fact, we show that there is such a rational map in every one parameter family of rational maps that is defined over a finite extension of $\\Q_p$ and that has a Misiurewicz bifurcation.
Serially recurrent osteoid osteoma.
Sampath, Srihari C; Sampath, Srinath C; Rosenthal, Daniel I
2015-06-01
Osteoid osteoma is a relatively common, benign, painful tumor of bone. It is widely believed to run a course culminating in spontaneous regression. The tumor can usually be eliminated by excision or ablation, although it may recur locally. Although management has classically been surgical, thermocoagulation via percutaneously delivered radiofrequency energy has demonstrated excellent results, typically resulting in durable response following a single treatment. Here, we present an unusual case of serially recurrent pathologically proven pediatric osteoid osteoma, treated by radiofrequency ablation five times over the course of 11 years. Limitations of RF ablation of osteoid osteoma and possible factors predisposing to incomplete treatment or recurrence are discussed. PMID:25503857
Recurrent parotitis in children
Directory of Open Access Journals (Sweden)
Bhattarai M
2006-01-01
Full Text Available Recurrent parotitis is an uncommon condition in children. Its etiological factors have not been proved till date although causes due to genetic inheritance, local autoimmune manifestation, allergy, viral infection and immunodeficiency have been suggested. The exact management of this disorder is not yet standardized, but a conservative approach is preferred and all affected children should be screened for Sjogren?s syndrome and immune deficiency including human immunodeficiency virus. We report a 12 years female child who presented with 12 episodes of non-painful recurrent swellings of the bilateral parotid gland in the past 3 years.
International Nuclear Information System (INIS)
A framework to analyze inference performance in densely connected single-layer feed-forward networks is developed for situations where a given data set is composed of correlated patterns. The framework is based on the assumption that the left and right singular value bases of the given pattern matrix are generated independently and uniformly from Haar measures. This assumption makes it possible to characterize the objective system by a single function of two variables which is determined by the eigenvalue spectrum of the cross-correlation matrix of the pattern matrix. Links to existing methods for analysis of perceptron learning and Gaussian linear vector channels and an application to a simple but nontrivial problem are also shown
Energy Technology Data Exchange (ETDEWEB)
Hood, R.Q.
1994-04-01
Utilizing self-consistent Hartree-Fock calculations, several aspects of multilayers and interfaces are explored: enhancement and reduction of the local magnetic moments, magnetic coupling at the interfaces, magnetic arrangements within each film and among non-neighboring films, global symmetry of the systems, frustration, orientation of the various moments with respect to an outside applied field, and magnetic-field induced transitions. Magnetoresistance of ferromagnetic-normal-metal multilayers is found by solving the Boltzmann equation. Results explain the giant negative magnetoresistance encountered in these systems when an initial antiparallel arrangement is changed into a parallel configuration by an external magnetic field. The calculation depends on (1) geometric parameters (thicknesses of layers), (2) intrinsic metal parameters (number of conduction electrons, magnetization, and effective masses in layers), (3) bulk sample properties (conductivity relaxation times), (4) interface scattering properties (diffuse scattering versus potential scattering at the interfaces, and (5) outer surface scattering properties (specular versus diffuse surface scattering). It is found that a large negative magnetoresistance requires considerable asymmetry in interface scattering for the two spin orientations. Features of the interfaces that may produce an asymmetrical spin-dependent scattering are studied: varying interfacial geometric random roughness with no lateral coherence, correlated (quasi-periodic) roughness, and varying chemical composition of the interfaces. The interplay between these aspects of the interfaces may enhance or suppress the magnetoresistance, depending on whether it increases or decreases the asymmetry in the spin-dependent scattering of the conduction electrons.
Energy Technology Data Exchange (ETDEWEB)
Chrzan, D.C.; Dugger, M.; Follstaedt, D.M.; Friedman, Lawrence H.; Friedmann, T.A.; Knapp, J.A.; McCarty, K.F.; Medlin, D.L.; Mirkarimi, P.B.; Missert, N.; Newcomer, P.P.; Sullivan, J.P.; Tallant, D.R.
1999-05-01
We have developed a new multilayer a-tC material that is thick stress-free, adherent, low friction, and with hardness and stiffness near that of diamond. The new a-tC material is deposited by J pulsed-laser deposition (PLD) at room temperature, and fully stress-relieved by a short thermal anneal at 600°C. A thick multilayer is built up by repeated deposition and annealing steps. We measured 88 GPa hardness, 1100 GPa Young's modulus, and 0.1 friction coefficient (under high load). Significantly, these results are all well within the range reported for crystalline diamond. In fact, this material, if considered separate from crystalline diamond, is the 2nd hardest material known to man. Stress-free a-tC also has important advantages over thin film diamond; namely, it is smooth, processed at lower temperature, and can be grown on a much broader range of substrates. This breakthrough will enable a host of applications that we are actively pursuing in MEMs, sensors, LIGA, etc.
International Nuclear Information System (INIS)
Utilizing self-consistent Hartree-Fock calculations, several aspects of multilayers and interfaces are explored: enhancement and reduction of the local magnetic moments, magnetic coupling at the interfaces, magnetic arrangements within each film and among non-neighboring films, global symmetry of the systems, frustration, orientation of the various moments with respect to an outside applied field, and magnetic-field induced transitions. Magnetoresistance of ferromagnetic-normal-metal multilayers is found by solving the Boltzmann equation. Results explain the giant negative magnetoresistance encountered in these systems when an initial antiparallel arrangement is changed into a parallel configuration by an external magnetic field. The calculation depends on (1) geometric parameters (thicknesses of layers), (2) intrinsic metal parameters (number of conduction electrons, magnetization, and effective masses in layers), (3) bulk sample properties (conductivity relaxation times), (4) interface scattering properties (diffuse scattering versus potential scattering at the interfaces, and (5) outer surface scattering properties (specular versus diffuse surface scattering). It is found that a large negative magnetoresistance requires considerable asymmetry in interface scattering for the two spin orientations. Features of the interfaces that may produce an asymmetrical spin-dependent scattering are studied: varying interfacial geometric random roughness with no lateral coherence, correlated (quasi-periodic) roughness, and varying chemical composition of the interfaces. The interplay between these aspects of the interfaces may enhance or suppress the magnetoresistance, depending on whether it increases or decreases the asymmetry in the spin-dependent scattering of the conduction electrons
International Nuclear Information System (INIS)
We have developed a new multilayer a-tC material that is thick stress-free, adherent, low friction, and with hardness and stiffness near that of diamond. The new a-tC material is deposited by J pulsed-laser deposition (PLD) at room temperature, and fully stress-relieved by a short thermal anneal at 600 ampersand deg;C. A thick multilayer is built up by repeated deposition and annealing steps. We measured 88 GPa hardness, 1100 GPa Young's modulus, and 0.1 friction coefficient (under high load). Significantly, these results are all well within the range reported for crystalline diamond. In fact, this material, if considered separate from crystalline diamond, is the 2nd hardest material known to man. Stress-free a-tC also has important advantages over thin film diamond; namely, it is smooth, processed at lower temperature, and can be grown on a much broader range of substrates. This breakthrough will enable a host of applications that we are actively pursuing in MEMs, sensors, LIGA, etc
Full Text Available ... for any ovarian cancer survivor. In this video, Dr. John Comerci leads a discussion on recurrence and openly answered many questions from our survivor audience â€“ hopefully yours will be one of them. We appreciate Dr. Comerciâ€™s contribution of his time and Magee Womnens ...
Full Text Available ... cancer survivor. In this video, Dr. John Comerci leads a discussion on recurrence and openly answered many questions from our survivor audience â€“ hopefully yours will be one of them. We appreciate Dr. Comerciâ€™s contribution of his time and Magee Womnens Hospital of UPMC for providing ...
Ptychography with multilayer Laue lenses.
Kubec, Adam; Braun, Stefan; Niese, Sven; Krüger, Peter; Patommel, Jens; Hecker, Michael; Leson, Andreas; Schroer, Christian G
2014-09-01
Two different multilayer Laue lens designs were made with total deposition thicknesses of 48?µm and 53?µm, and focal lengths of 20.0?mm and 12.5?mm at 20.0?keV, respectively. From these two multilayer systems, several lenses were manufactured for one- and two-dimensional focusing. The latter is realised with a directly bonded assembly of two crossed lenses, that reduces the distance between the lenses in the beam direction to 30?µm and eliminates the necessity of producing different multilayer systems. Characterization of lens fabrication was performed using a laboratory X-ray microscope. Focusing properties have been investigated using ptychography. PMID:25178001
Diffusion Processes on Multilayer Networks
Salehi, Mostafa; Marzolla, Moreno; Montesi, Danilo; Siyari, Payam; Magnani, Matteo
2014-01-01
Several systems can be modelled as sets of interdependent networks or networks with multiple types of connections, here generally called multilayer networks. Diffusion processes like the propagation of information or the spreading of diseases are fundamental phenomena occurring in these networks. However, while the study of diffusion processes in single networks has received a great deal of interest from various disciplines for over a decade, diffusion on multilayer networks is still a young and promising research area presenting many challenging research issues. In this paper we review the main models, results and applications of multilayer diffusion and discuss some promising research directions.
Ruthenocuprates Intrinsic magnetic multilayers
Zivkovic, L; Prester, M; Drobac, D; Ariosa, D; Margaritondo, G; Felner, I; Frazer, B H; Onellion, M
2001-01-01
We report ac susceptibility measurements on polycrystalline samples of SrRuO_3 and three ruthenocuprates: superconducting RuSr_2GdCu_2O_8 (Ru-1212), superconducting RuSr_2Eu_(2-x)Ce_xCu_2O_y (Ru-1222, x=0.5) and nonsuperconducting, insulating RuSr_2Eu_(2-x)Ce_xCu_2O_z$ (Ru-1222, x=1.0). Ac susceptibility of both Ru-1222 compositions exhibit logarithmic time relaxation and `inverted' hysteresis loops. Ru-1212 samples exhibit none of these behaviors. We interpret the magnetic behavior of Ru-1222 in the framework of weakly coupled magnetic multilayers and argue that superconductivity coexists with qualitatively different magnetic behaviors.
International Nuclear Information System (INIS)
Digital multilayer tomography combines the principles of conventional tomography with digital techniques. The development of this method in addition to DSA and digital radiography is another step forward towards the achievement of digital radiology. Clinical application of the method for initial experience and results is done in the Institut fuer Klinische Strahlenkunde of the Johannes Gutenberg University in Mainz, and so far seventy patients have been examined with the new diagnostic tool, covering the following regions of interest: hilus/lungs (30 patients); skeleton (28 patients); middle part of the face (7 patients); kidneys (5 patients). In all cases, conventional tomograms have been available for comparison. Dose measurements for assessing the required dose and the dose to the patient have been made with a pelvic phantom. (orig./MG)
Directory of Open Access Journals (Sweden)
J. Szajnar
2010-01-01
Full Text Available In paper is presented the possibility of making of multi-layers cast steel castings in result of connection of casting and welding coating technologies. First layer was composite surface layer on the basis of Fe-Cr-C alloy, which was put directly in founding process of cast carbon steel 200–450 with use of preparation of mould cavity method. Second layer were padding welds, which were put with use of TIG – Tungsten Inert Gas surfacing by welding technology with filler on Ni matrix, Ni and Co matrix with wolfram carbides WC and on the basis on Fe-Cr-C alloy, which has the same chemical composition with alloy, which was used for making of composite surface layer. Usability for industrial applications of surface layers of castings were estimated by criterion of hardness and abrasive wear resistance of type metal-mineral.
Controlling light with plasmonic multilayers
Orlov, Alexey A.; Zhukovsky, Sergei V.; Iorsh, Ivan V.; Belov, Pavel A.
2014-06-01
Recent years have seen a new wave of interest in layered media - namely, plasmonic multilayers - in several emerging applications ranging from transparent metals to hyperbolic metamaterials. In this paper, we review the optical properties of such subwavelength metal-dielectric multilayered metamaterials and describe their use for light manipulation at the nanoscale. While demonstrating the recently emphasized hallmark effect of hyperbolic dispersion, we put special emphasis to the comparison between multilayered hyperbolic metamaterials and more broadly defined plasmonic-multilayer metamaterials A number of fundamental electromagnetic effects unique to the latter are identified and demonstrated. Examples include the evolution of isofrequency contour shape from elliptical to hyperbolic, all-angle negative refraction, and nonlocality-induced optical birefringence. Analysis of the underlying physical causes, which are spatial dispersion and optical nonlocality, is also reviewed. These recent results are extremely promising for a number of applications ranging from nanolithography to optical cloaking.
Controlling light with plasmonic multilayers
DEFF Research Database (Denmark)
Orlov, Alexey A.; Zhukovsky, Sergei
2014-01-01
Recent years have seen a new wave of interest in layered media - namely, plasmonic multilayers - in several emerging applications ranging from transparent metals to hyperbolic metamaterials. In this paper, we review the optical properties of such subwavelength metal-dielectric multilayered metamaterials and describe their use for light manipulation at the nanoscale. While demonstrating the recently emphasized hallmark effect of hyperbolic dispersion, we put special emphasis to the comparison between multilayered hyperbolic metamaterials and more broadly defined plasmonic-multilayer metamaterials A number of fundamental electromagnetic effects unique to the latter are identified and demonstrated. Examples include the evolution of isofrequency contour shape from elliptical to hyperbolic, all-angle negative refraction, and nonlocality-induced optical birefringence. Analysis of the underlying physical causes, which are spatial dispersion and optical nonlocality, is also reviewed. These recent results are extremely promising for a number of applications ranging from nanolithography to optical cloaking. © 2014 Elsevier B.V.
Multilayer high performance insulation materials
Stuckey, J. M.
1971-01-01
A number of tests are required to evaluate both multilayer high performance insulation samples and the materials that comprise them. Some of the techniques and tests being employed for these evaluations and some of the results obtained from thermal conductivity tests, outgassing studies, effect of pressure on layer density tests, hypervelocity impact tests, and a multilayer high performance insulation ambient storage program at the Kennedy Space Center are presented.
Anomalous Magnetoresistance in Fibonacci Multilayers
Machado, L. D.; Bezerra, C. G.; Correa, M. A.; Chesman, C.; Pearson, J E; Hoffmann, A.
2012-01-01
The present paper theoretically investigates magnetoresistance curves in quasiperiodic magnetic multilayers for two different growth directions, namely [110] and [100]. We considered identical ferromagnetic layers separated by non-magnetic layers with two different thicknesses chosen based on the Fibonacci sequence. Using parameters for Fe/Cr multilayers, four terms were included in our description of the magnetic energy: Zeeman, cubic anisotropy, bilinear and biquadratic co...
Multilayer thermal barrier coating systems
Vance, Steven J. (Orlando, FL); Goedjen, John G. (Oviedo, FL); Sabol, Stephen M. (Orlando, FL); Sloan, Kelly M. (Longwood, FL)
2000-01-01
The present invention generally describes multilayer thermal barrier coating systems and methods of making the multilayer thermal barrier coating systems. The thermal barrier coating systems comprise a first ceramic layer, a second ceramic layer, a thermally grown oxide layer, a metallic bond coating layer and a substrate. The thermal barrier coating systems have improved high temperature thermal and chemical stability for use in gas turbine applications.
Impact properties of multilayered materials
Vazquez Vaamonde, A.
1993-01-01
The possibilities of multilayered materials as high impact resistance materials are considered with reference to safety in transportation. The mechanism of fracture of the different layers of the material produces an enhancement of the impact resistance behavior and, as a consequence, a lower quantity of material is needed with the corresponding saving in weight of the transport vehicle. The reinforcing material of this multilayered composite are steel sheets. The sheets, two or more, are dip...
Recurrent parotitis in children
Bhattarai M; Wakode P
2006-01-01
Recurrent parotitis is an uncommon condition in children. Its etiological factors have not been proved till date although causes due to genetic inheritance, local autoimmune manifestation, allergy, viral infection and immunodeficiency have been suggested. The exact management of this disorder is not yet standardized, but a conservative approach is preferred and all affected children should be screened for Sjogren?s syndrome and immune deficiency including human immunodeficiency virus. ...
Pedersen, Morten With
1997-01-01
Training recurrent networks is generally believed to be a difficult task. Excessive training times and lack of convergence to an acceptable solution are frequently reported. In this paper we seek to explain the reason for this from a numerical point of view and show how to avoid problems when training. In particular we investigate ill-conditioning, the need for and effect of regularization and illustrate the superiority of second-order methods for training
Recurrent amiodarone pulmonary toxicity.
Chendrasekhar, A; Barke, R A; Druck, P
1996-01-01
Amiodarone, a widely used antiarrhythmic drug, is associated with pulmonary toxicity, with an estimated mortality of 1% to 33%. Standard treatment for amiodarone pulmonary toxicity (APT) has been discontinuance of the drug and steroid therapy. We report a case of APT that recurred after withdrawal of steroids and failed to respond to reinstatement of steroid therapy. Recurrent APT is a rare clinical entity that has been reported only twice in recent literature. PMID:8545700
International Nuclear Information System (INIS)
Neuroradiological techniques were used to elucidate pathophysiology of recurrent cerebral thrombosis. Twenty-two patients with cerebral thrombosis who suffered a second attack under stable conditions more than 22 days after the initial stroke were studied. Hypertension, diabetes mellitus, and hypercholesterolemia were also seen in 20, 8, and 12 patients, respectively. The patients were divided into three groups according to their symptoms: (I) symptoms differed between the first and second strokes (n=12); (II) initial symptoms were suddenly deteriorated (n=6); and (III) symptoms occurring in groups I and II were seen (n=4). In group I, contralateral hemiparesis or suprabulbar palsy was often associated with the initial hemiparesis. The time of recurrent stroke varied from 4 months to 9 years. CT and MRI showed not only lacunae in both hemispheres, but also deep white-matter ischemia of the centrum semi-ovale. In group II, hemiparesis or visual field defect was deteriorated early after the initial stroke. In addition, neuroimaging revealed that infarction in the posterior cerebral artery was progressed on the contralateral side, or that white matter lesion in the middle artery was enlarged in spite of small lesion in the left cerebral hemisphere. All patients in group III had deterioration of right hemiparesis associated with aphasia. CT, MRI, SPECT, and angiography indicated deep white-matter ischemia caused by main trunk lesions in the left hemisphere. Group III seemons in the left hemisphere. Group III seemed to be equivalent to group II, except for laterality of the lesion. Neuroradiological assessment of the initial stroke may help to predict the mode of recurrence, although pathophysiology of cerebral thrombosis is complicated and varies from patient to patient. (N.K.)
Recurrence Relations and Determinants
Janjic, Milan
2011-01-01
We examine relationships between two minors of order n of some matrices of n rows and n+r columns. This is done through a class of determinants, here called $n$-determinants, the investigation of which is our objective. We prove that 1-determinants are the upper Hessenberg determinants. In particular, we state several 1-determinants each of which equals a Fibonacci number. We also derive relationships among terms of sequences defined by the same recurrence equation independently of the initial conditions. A result generalizing the formula for the product of two determinants is obtained. Finally, we prove that the Schur functions may be expressed as $n$-determinants.
Equine recurrent airway obstruction
Directory of Open Access Journals (Sweden)
Artur Nied?wied?
2014-10-01
Full Text Available Equine Recurrent Airway Obstruction (RAO, also known as heaves or broken wind, is one of the most common disease in middle-aged horses. Inflammation of the airway is inducted by organic dust exposure. This disease is characterized by neutrophilic inflammation, bronchospasm, excessive mucus production and pathologic changes in the bronchiolar walls. Clinical signs are resolved in 3-4 weeks after environmental changes. Horses suffering from RAO are susceptible to allergens throughout their lives, therefore they should be properly managed. In therapy the most importanthing is to eliminate dustexposure, administration of corticosteroids and use bronchodilators to improve pulmonary function.
Zhao, Wenhua
2003-01-01
Let $F(z)=z-H(z)$ with $o(H(z))\\geq 2$ be a formal map from $\\bC^n$ to $\\bC^n$ and $G(z)$ the formal inverse of $F(z)$. In this paper, we fist study the deformation $F_t(z)=z-tH(z)$ and its formal inverse map $G_t(z)$. We then derive two recurrent formulas for the formal inverse $G(z)$. The first formula in certain situations provides a more efficient method for the calculation of $G(z)$ than other well known inversion formulas. The second one is differential free but only w...
On Concircularly Recurrent Finsler Manifolds
Youssef, Nabil. L.; Soleiman, A.
2012-01-01
Two special Finsler spaces have been introduced and investigated, namely $R^h$-recurrent Finsler space and consircularly recurrent Finsler space. The defining properties of these spaces are formulated in terms of the first curvature tensor of Cartan connection. The following three results constitute the main object of the present paper: 1. A concircularly flat Finsler manifold is necessarily of constant curvature (Theorem A); 2. Every $R^h$-recurrent Finsler manifold is conc...
Line Structures in Recurrence Plots
Marwan, N; Marwan, Norbert; Kurths, Juergen
2004-01-01
Recurrence plots exhibit line structures which represent typical behaviour of the investigated system. The local slope of these line structures is connected with a specific transformation of the time scales of different segments of the phase-space trajectory. This provides us a better understanding of the structures occuring in recurrence plots. The relationship between the time-scales and line structures are of practical importance in cross recurrence plots. Using this relationship within cross recurrence plots, the time-scales of differently sampled or time-transformed measurements can be adjusted. An application to geophysical measurements illustrates the capability of this method for the adjustment of time-scales in different measurements.
Epidemiology of recurrent venous thrombosis
Directory of Open Access Journals (Sweden)
D.D. Ribeiro
2012-01-01
Full Text Available Venous thrombosis, including deep vein thrombosis and pulmonary embolism, is a common disease that frequently recurs. Recurrence can be prevented by anticoagulants, but this comes at the risk of bleeding. Therefore, assessment of the risk of recurrence is important to balance the risks and benefits of anticoagulant treatment. This review briefly outlines what is currently known about the epidemiology of recurrent venous thrombosis, and focuses in more detail on potential new risk factors for venous recurrence. The general implications of these findings in patient management are discussed.
Epidemiology of recurrent venous thrombosis
Scientific Electronic Library Online (English)
D.D., Ribeiro; W.M., Lijfering; S.M., Barreto; F.R., Rosendaal; S.M., Rezende.
2012-01-01
Full Text Available Venous thrombosis, including deep vein thrombosis and pulmonary embolism, is a common disease that frequently recurs. Recurrence can be prevented by anticoagulants, but this comes at the risk of bleeding. Therefore, assessment of the risk of recurrence is important to balance the risks and benefits [...] of anticoagulant treatment. This review briefly outlines what is currently known about the epidemiology of recurrent venous thrombosis, and focuses in more detail on potential new risk factors for venous recurrence. The general implications of these findings in patient management are discussed.
Structural reducibility of multilayer networks
de Domenico, Manlio; Nicosia, Vincenzo; Arenas, Alexandre; Latora, Vito
2015-04-01
Many complex systems can be represented as networks consisting of distinct types of interactions, which can be categorized as links belonging to different layers. For example, a good description of the full protein-protein interactome requires, for some organisms, up to seven distinct network layers, accounting for different genetic and physical interactions, each containing thousands of protein-protein relationships. A fundamental open question is then how many layers are indeed necessary to accurately represent the structure of a multilayered complex system. Here we introduce a method based on quantum theory to reduce the number of layers to a minimum while maximizing the distinguishability between the multilayer network and the corresponding aggregated graph. We validate our approach on synthetic benchmarks and we show that the number of informative layers in some real multilayer networks of protein-genetic interactions, social, economical and transportation systems can be reduced by up to 75%.
Structural reducibility of multilayer networks.
De Domenico, Manlio; Nicosia, Vincenzo; Arenas, Alexandre; Latora, Vito
2015-01-01
Many complex systems can be represented as networks consisting of distinct types of interactions, which can be categorized as links belonging to different layers. For example, a good description of the full protein-protein interactome requires, for some organisms, up to seven distinct network layers, accounting for different genetic and physical interactions, each containing thousands of protein-protein relationships. A fundamental open question is then how many layers are indeed necessary to accurately represent the structure of a multilayered complex system. Here we introduce a method based on quantum theory to reduce the number of layers to a minimum while maximizing the distinguishability between the multilayer network and the corresponding aggregated graph. We validate our approach on synthetic benchmarks and we show that the number of informative layers in some real multilayer networks of protein-genetic interactions, social, economical and transportation systems can be reduced by up to 75%. PMID:25904309
Computing and fabricating multilayer models
Holroyd, Michael; Baran, Ilya; Lawrence, Jason; Matusik, Wojciech
2011-01-01
We present a method for automatically converting a digital 3D model into a multilayer model: a parallel stack of high-resolution 2D images embedded within a semi-transparent medium. Multilayer models can be produced quickly and cheaply and provide a strong sense of an object's 3D shape and texture over a wide range of viewing directions. Our method is designed to minimize visible cracks and other artifacts that can arise when projecting an input model onto a small number of parallel planes, a...
New developments in Ni/Ti multilayers
Energy Technology Data Exchange (ETDEWEB)
Anderson, I.; Hoghoj, P. [Institut Max von Laue - Paul Langevin (ILL), 38 - Grenoble (France)
1997-04-01
It is now 20 years since super-mirrors were first used as a neutron optical element. Since then the field of multilayer neutron-optics has matured with multilayers finding their way to application in many neutron scattering instruments. However, there is still room for progress in terms of multilayer quality, performance and application. Along with work on multilayers for neutron polarisation Ni/Ti super-mirrors have been optimised. The state-of-the-art Ni/Ti super-mirror performance and the results obtained in two neutron-optics applications of Ni/Ti multilayers are presented. (author).
Treatment possibilities of recurrent lymphogranulomatosis
International Nuclear Information System (INIS)
The authors present seven typical cases chosen from a group of thirty patients with recurrent Hodgkin's disease. One out of these patients suffered from two recurrences, five patients from three recurrences each, and one patient from six recurrences. The observation period, beginning with the primary treatment, was between five and 16 years. None of the patients was exclusively irradiated or only treated by cytostatic drugs. Therefore after primary radiotherapy in the stages I to III A, later recurrences could often be successfully treated by an alternating application of cytostatic drugs and repeated radiotherapy. After primary chemotherapy of the advanced primary stages III B to IV B, too, a remission of the second and third recurrence could often be achieved by radiotherapy. Futhermore, the application of alternative schemes such as Holoxan-Vepesid has to be taken into account in the treatment of recurrences. The repeated application of C-MOPP after an interval of at least twelve months also produces good rates of response. The present results allow to make the conlusion that a successful treatment of the second and third and even of further recurrences is possible by a combined application of irradiation and cytostatic therapy. (orig.)
[Recurrence: mechanisms and treatments].
Ghouzi, J
2000-01-01
An original analysis by computer has been imagined. Etiological diagnosis in recurrence's cases is based on asymmetry. Different levels were investigated: dental arch, ridge, basal bone and mandibular position. Dental shift, deformed bone, eccentric mandibular and occlusal distortion were found. Each molar is independently moving. Mandibular basal bone is stabilized in the transverse dimension. Mandibular deviation induces compression or stretching in temporo-mandibular articulation. Occlusal interferences involve distortion of cuspal plans. To reach stable objectives, molars require symmetrical position below one millimeter discrepancy, molar locking is to be had for the disto-vestibular cusp and ovoid arch. A special anchor apparatus allows to correct every wrong position of each individual molar, in each three-directional space. Mini-positioner or mini-splint perfect anterior misalignment. Sometimes, thermical memory archs are required. Ten fundamental rules that regulate occlusal and mandibular stability have been checked after treatment. PMID:10838865
Shortest Recurrence Periods of Novae
Kato, Mariko; Hachisu, Izumi; Nomoto, Ken'ichi
2014-01-01
Stimulated by the recent discovery of the 1 yr recurrence period nova M31N 2008-12a, we examined shortest recurrence periods of hydrogen shell flashes on mass-accreting white dwarfs (WDs). We discuss the mechanism that yields a finite minimum recurrence period for a given WD mass. Calculating unstable flashes for various WD masses and mass-accretion rates, we identified the shortest recurrence period of about two months for a non-rotating 1.38 M_\\sun WD with a mass-accretion rate of 3.6 \\times 10^{-7} M_\\sun yr^{-1}. One year recurrence period is realized for very massive (> 1.3 M_\\sun) WDs with very high accretion rates (>1.5 \\times 10^{-7} M_\\sun yr^{-1}). We also present a revised stability limit of hydrogen shell burning, which will be useful for binary evolution calculations toward Type Ia supernovae.
Stability of multilayered neural networks
International Nuclear Information System (INIS)
Stability of multilayered neural networks against synaptic changes has been studied numerically. The average maximum change goes to zero as the number N of input neurons is much greater than one. If a fixed fraction of output errors is allowed, then the synapses may be changed within some limits even for large N. (Author)
MAGNETIC MULTILAYERS : STATICS AND DYNAMICS
Fishman, F.; Schwabl, F.; Schwenk, D.
1988-01-01
In the framework of Ginzburg-Landay theory we calculate static and dynamical properties of ferromagnetic multilayers : Tc, mean magnetization and inelastic neutron scattering cross section. The magnon spectrum has a band structure, but the gaps vanish for certain values of k and ?. The cross section strongly increases at the points where gaps vanish.
Multilayer Controller for Outdoor Vehicle
DEFF Research Database (Denmark)
Reske-Nielsen, Anders; Mejnertsen, AsbjØrn
2006-01-01
A full software and hardware solution has been designed, implemented and tested for control of a small agricultural automatic tractor. The objective was to realise a user-friendly, multi-layer controller architecture for an outdoor platform. The collaborative research work was done as a part of a research project within the field of automated agriculture and precision farming.
Multilayer High-Gradient Insulators
Energy Technology Data Exchange (ETDEWEB)
Harris, J R
2006-08-16
Multilayer High-Gradient Insulators are vacuum insulating structures composed of thin, alternating layers of dielectric and metal. They are currently being developed for application to high-current accelerators and related pulsed power systems. This paper describes some of the High-Gradient Insulator research currently being conducted at Lawrence Livermore National Laboratory.
Mozumder, Chitrini; Tripathi, Nitin K.
2014-10-01
In recent decades, the world has experienced unprecedented urban growth which endangers the green environment in and around urban areas. In this work, an artificial neural network (ANN) based model is developed to predict future impacts of urban and agricultural expansion on the uplands of Deepor Beel, a Ramsar wetland in the city area of Guwahati, Assam, India, by 2025 and 2035 respectively. Simulations were carried out for three different transition rates as determined from the changes during 2001-2011, namely simple extrapolation, Markov Chain (MC), and system dynamic (SD) modelling, using projected population growth, which were further investigated based on three different zoning policies. The first zoning policy employed no restriction while the second conversion restriction zoning policy restricted urban-agricultural expansion in the Guwahati Municipal Development Authority (GMDA) proposed green belt, extending to a third zoning policy providing wetland restoration in the proposed green belt. The prediction maps were found to be greatly influenced by the transition rates and the allowed transitions from one class to another within each sub-model. The model outputs were compared with GMDA land demand as proposed for 2025 whereby the land demand as produced by MC was found to best match the projected demand. Regarding the conservation of Deepor Beel, the Landscape Development Intensity (LDI) Index revealed that wetland restoration zoning policies may reduce the impact of urban growth on a local scale, but none of the zoning policies was found to minimize the impact on a broader base. The results from this study may assist the planning and reviewing of land use allocation within Guwahati city to secure ecological sustainability of the wetlands.
Shafter, A W; Rector, T A; Schweizer, F; Hornoch, K; Orio, M; Pietsch, W; Darnley, M J; Williams, S C; Bode, M F; Bryan, J
2014-01-01
The reported positions of 964 suspected nova eruptions in M31 recorded through the end of calendar year 2013 have been compared in order to identify recurrent nova candidates. To pass the initial screen and qualify as a recurrent nova candidate two or more eruptions were required to be coincident within 0.1', although this criterion was relaxed to 0.15' for novae discovered on early photographic patrols. A total of 118 eruptions from 51 potential recurrent nova systems satisfied the screening criterion. To determine what fraction of these novae are indeed recurrent the original plates and published images of the relevant eruptions have been carefully compared. This procedure has resulted in the elimination of 27 of the 51 progenitor candidates (61 eruptions) from further consideration as recurrent novae, with another 8 systems (17 eruptions) deemed unlikely to be recurrent. Of the remaining 16 systems, 12 candidates (32 eruptions) were judged to be recurrent novae, with an additional 4 systems (8 eruptions) b...
STDP in recurrent neuronal networks
Directory of Open Access Journals (Sweden)
MatthieuGilson
2010-09-01
Full Text Available Recent results about spike-timing-dependent plasticity (STDP in recurrently connected neurons are reviewed, with a focus on the relationship between the weight dynamics and the emergence of network structure. In particular, the evolution of synaptic weights in the two cases of incoming connections for a single neuron and recurrent connections are compared and contrasted. A theoretical framework is used that is based upon Poisson neurons with a temporally inhomogeneous firing rate and the asymptotic distribution of weights generated by the learning dynamics. Different network configurations examined in recent studies are discussed and an overview of the current understanding of STDP in recurrently connected neuronal networks is presented.
Recurrent and weakly recurrent points in ÃŽÂ²G
Mostafa Nassar
1986-01-01
It is shown in this paper that if ÃŽÂ²G is the Stone-Ã„ÂŒech compactification of a group G, and G satisfying a certain condition, then there is a weakly recurrent point in ÃŽÂ²G which is not almost periodic, and if another condition will be added, then there is a recurrent point in ÃŽÂ²G which is not almost periodic point.
Giant recurrent retroperitoneal liposarcoma presenting as a recurrent inguinal hernia
Sameer Vora; Channabasappa G. Kori; Shenoy, Sachin S.; Borisa, Ashok D; Bakhshi, Girish D; Ajay H. Bhandarwar
2011-01-01
Retroperitoneal liposarcoma presenting as an inguinal hernia is a rare entity. We present the first case of Giant recurrent liposarcoma presenting as a recurrent inguinal hernia in a 40-year-old male. Physical examination showed an irreducible lump in the right inguinal region and a scar in the right lumbar and right inguinal region. Computed tomography (CT) scan of abdomen revealed it to be a retro peritoneal mass extending into the right inguinal region along and involving the cord structur...
Primary breast lymphoma; disease recurrence
Directory of Open Access Journals (Sweden)
Hüseyin KADIO?LU
2012-01-01
Full Text Available Primary breast lymphoma (PBL accounts 0.4-0.5% of all breast cancers. The aim is to present the patient diagnosed with recurrency of primary breast lymphoma treated six year ago without radiotherapy. A 63-years-old woman patient admitted to our hospital with a palpabl mass in her left breast. Six years ago she was treated with chemoterapy after local excision for primary left breast lymphoma. Imaging modalities showed multiple lesion in breast and confirmed with biopsy. Pathologic results were similar with first one and the case was accepted as PBL recurrence. Multipl metastases has been determined with staging modalities. Patient started to chemotherapy treatment. PBL is a rare cancer of breast and there is no consensus at the treatment of disease. In the literature addition of radiotherapy to the treatment prevents local recurrence. There were occured recurrence without radiotherapy, mimicked that radiotherapy is an essential modality in PBL treatment.
Recurrent ameloblastoma of the mandible
Joshi, C. P.; Vyas, K. C.; Deedwania, Seema; Jain, Sanjeev; Mangal, M. M.
1999-01-01
Ameloblastoma is an agressive locally recurring neoplasm of odentogenic epithelium. Here we describe a case of mandibular ameloblastoma with 12 yrs. history of local recurrences followed with history of excision twice (10 yrs. and 7 years back).
Recurrent networks for wave forecasting
Digital Repository Service at National Institute of Oceanography (India)
Mandal, S.; Prabaharan, N.
2002-01-01
, merchant vessel routing, nearshore construction, etc. more efficiently and safely. This paper presents an application of the Artificial Neural Network, namely Backpropagation Recurrent Neural Network (BRNN) with rprop update algorithm for wave forecasting...
Recurrent abdominal pain during childhood.
Scott, R. B.
1994-01-01
Recurrent abdominal pain is a common presenting complaint among children. A thorough history and physical examination and limited laboratory investigation should enable a physician to make a positive diagnosis of "functional" recurrent abdominal pain in 90% to 95% of cases; an organic cause is identified in only 5% to 10%. The care and thoroughness of the history and physical examination establish the physician's credibility; explaining the clinical basis for the diagnosis and educating the c...
Recurrence risks in mental retardation.
Crow, Y. J.; Tolmie, J. L.
1998-01-01
Despite improvements in diagnostic techniques and progress made in mapping genes associated with syndromal mental handicap, the estimation of recurrence risks in non-syndromal mental retardation is still dependent on empirical data. Unfortunately, few studies are available to guide the clinician and their results differ significantly. For example, recurrence risks to all sibs of a male index patient with severe mental retardation vary between 3.5% and 14% in commonly quoted series. The presen...
Multilayer weighted social network model
Murase, Yohsuke; Török, János; Jo, Hang-Hyun; Kaski, Kimmo; Kertész, János
2014-11-01
Recent empirical studies using large-scale data sets have validated the Granovetter hypothesis on the structure of the society in that there are strongly wired communities connected by weak ties. However, as interaction between individuals takes place in diverse contexts, these communities turn out to be overlapping. This implies that the society has a multilayered structure, where the layers represent the different contexts. To model this structure we begin with a single-layer weighted social network (WSN) model showing the Granovetterian structure. We find that when merging such WSN models, a sufficient amount of interlayer correlation is needed to maintain the relationship between topology and link weights, while these correlations destroy the enhancement in the community overlap due to multiple layers. To resolve this, we devise a geographic multilayer WSN model, where the indirect interlayer correlations due to the geographic constraints of individuals enhance the overlaps between the communities and, at the same time, the Granovetterian structure is preserved.
Curvature of multilayer epitaxial films
Marcus, P. M.
1996-06-01
An evaluation is made of the curvature produced by epitaxial strain on a multilayer structure formed by repetition of a film-substrate pair n times. When the substrate has thickness comparable to the film thickness, the curvature is increased by many orders of magnitude over the usual ultrathin film epitaxial on a much thicker crystalline substrate. Although the curvature is also shown to be reduced by a factor of n2 in the multilayer compared to a single film-substrate pair, a large net increase is possible. Explicit formulas are obtained for the dependence of the curvature on n, on the misfit, on the ratio of film to substrate thickness, and on the ratio of a modified Young's modulus for the film to that of the substrate. The curvature is calculated for a range of these parameters and asymptotic formulas for large n are given.
Anomalous magnetoresistance in Fibonacci multilayers
Machado, L. D.; Bezerra, C. G.; Correa, M. A.; Chesman, C.; Pearson, J. E.; Hoffmann, A.
2012-06-01
We theoretically investigated magnetoresistance curves in quasiperiodic magnetic multilayers for two different growth directions, namely, [110] and [100]. We considered identical ferromagnetic layers separated by nonmagnetic layers with two different thicknesses chosen based on the Fibonacci sequence. Using parameters for Fe/Cr multilayers, four terms were included in our description of the magnetic energy: Zeeman, cubic anisotropy, bilinear coupling, and biquadratic coupling. The minimum energy was determined by the gradient method and the equilibrium magnetization directions found were used to calculate magnetoresistance curves. By choosing spacers with a thickness such that biquadratic coupling is stronger than bilinear coupling, unusual behaviors for the magnetoresistance were observed: (i) for the [110] case, there is a different behavior for structures based on even and odd Fibonacci generations, and, more interesting, (ii) for the [100] case, we found magnetic field ranges for which the magnetoresistance increases with magnetic field.
Anomalous magnetoresistance in Fibonacci multilayers.
Energy Technology Data Exchange (ETDEWEB)
Machado, L. D.; Bezerra, C. G.; Correa, M. A.; Chesman, C.; Pearson, J. E.; Hoffmann, A. (Materials Science Division); (Universidade Federal do Rio Grande do Norte)
2012-01-01
We theoretically investigated magnetoresistance curves in quasiperiodic magnetic multilayers for two different growth directions, namely, [110] and [100]. We considered identical ferromagnetic layers separated by nonmagnetic layers with two different thicknesses chosen based on the Fibonacci sequence. Using parameters for Fe/Cr multilayers, four terms were included in our description of the magnetic energy: Zeeman, cubic anisotropy, bilinear coupling, and biquadratic coupling. The minimum energy was determined by the gradient method and the equilibrium magnetization directions found were used to calculate magnetoresistance curves. By choosing spacers with a thickness such that biquadratic coupling is stronger than bilinear coupling, unusual behaviors for the magnetoresistance were observed: (i) for the [110] case, there is a different behavior for structures based on even and odd Fibonacci generations, and, more interesting, (ii) for the [100] case, we found magnetic field ranges for which the magnetoresistance increases with magnetic field.
Polarizability and Screening in Chiral Multilayer Graphene
Min, Hongki; Hwang, E. H.; Sarma, S. Das
2012-01-01
We calculate the static polarizability of multilayer graphene and study the effect of stacking arrangement, carrier density, and onsite energy difference on graphene screening properties. At low densities, the energy spectrum of multilayer graphene is described by a set of chiral two-dimensional electron systems and the associated chiral nature determines the screening properties of multilayer graphene showing very different behavior depending on whether the chirality index ...
BESSY Bragg-Fresnel multilayer beam monitors
International Nuclear Information System (INIS)
X-ray optical systems based on Bragg-Fresnel multilayer components imaging an electron beam in a storage ring with microm resolution are presented. Design concepts are compared to alternative methods, and the aberrations and limits of Bragg-Fresnel multilayer optics are discussed. Experimental results of imaging the BESSY 1 source with sub 10 microm resolution are presented and the development of a compact Bragg-Fresnel multilayer telescope as a BESSY 2 standard beam monitor is described
Superconductivity in Multilayer Perovskite: Weak Coupling Analysis
Koikegami, Shigeru; Yanagisawa, Takashi
2008-01-01
We investigate the superconductivity of a three-dimensional d-p model with a multilayer perovskite structure on the basis of the second-order perturabation theory within the weak coupling framework. Our model has been designed with multilayer high-$T_c$ superconducting cuprates in mind. In our model, multiple Fermi surfaces appear, and the component of a superconducting gap function develops on each band. We have found that the multilayer structure can stabilize the supercon...
Magnetoelastic interactions in multilayer microwires
Vázquez, M.; Pirota, K.; Torrejón, J.; Badini, G.; Torcunov, A.
2006-09-01
Amorphous magnetic microwires exhibit outstanding magnetic characteristics as giant Barkhausen jump or nearly non-hysteretic behaviour that make them very suitable as sensing elements in various devices. In this article, we overview the different families of microwires and summarise most relevant results in connection with the magnetoelastic interlayer interactions in multilayer microwires. Improved magnetic behaviour can be observed in bi-layer microwires consisting of a magnetic nucleus coated by insulating cover. By employing combined sputtering and electroplating techniques, a novel series of multilayered magnetic microwires have been recently introduced. They consist typically of a magnetic nucleus and several shells having insulating and/or metallic nature, the latter magnetic or not. The magnetic character of the multilayer microwire will then depend on the magnetoelastic coupling between layers. External layers induce compressive stresses on the soft amorphous nucleus resulting in induced axial or circular anisotropies depending on magnetostriction sign. In a similar way, reduction of measuring temperature results in tensile stress as a consequence of different thermal expansion coefficients of various layers.
Magnetoelastic interactions in multilayer microwires
International Nuclear Information System (INIS)
Amorphous magnetic microwires exhibit outstanding magnetic characteristics as giant Barkhausen jump or nearly non-hysteretic behaviour that make them very suitable as sensing elements in various devices. In this article, we overview the different families of microwires and summarise most relevant results in connection with the magnetoelastic interlayer interactions in multilayer microwires. Improved magnetic behaviour can be observed in bi-layer microwires consisting of a magnetic nucleus coated by insulating cover. By employing combined sputtering and electroplating techniques, a novel series of multilayered magnetic microwires have been recently introduced. They consist typically of a magnetic nucleus and several shells having insulating and/or metallic nature, the latter magnetic or not. The magnetic character of the multilayer microwire will then depend on the magnetoelastic coupling between layers. External layers induce compressive stresses on the soft amorphous nucleus resulting in induced axial or circular anisotropies depending on magnetostriction sign. In a similar way, reduction of measuring temperature results in tensile stress as a consequence of different thermal expansion coefficients of various layers
Magnetoresistive multilayers deposited on the AAO membranes
International Nuclear Information System (INIS)
Silicon and GaAs wafers are the most commonly used substrates for deposition of giant magnetoresistive (GMR) multilayers. We explored a new type of a substrate, prepared electrochemically by anodization of aluminum sheets, for deposition of GMR multilayers. The surface of this AAO substrate consists of nanosized hemispheres organized in a regular hexagonal array. The current applied along the substrate surface intersects many magnetic layers in the multilayered structure, which results in enhancement of giant magnetoresistance effect. The GMR effect in uncoupled Co/Cu multilayers was significantly larger than the magnetoresistance of similar structures deposited on Si
Energy Technology Data Exchange (ETDEWEB)
Shafter, A. W. [Department of Astronomy, San Diego State University, San Diego, CA 92182 (United States); Henze, M. [European Space Astronomy Centre, P.O. Box 78, E-28692 Villanueva de la Cañada, Madrid (Spain); Rector, T. A. [Department of Physics and Astronomy, University of Alaska Anchorage, 3211 Providence Dr., Anchorage, AK 99508 (United States); Schweizer, F. [Carnegie Observatories, 813 Santa Barbara St., Pasadena, CA 91101 (United States); Hornoch, K. [Astronomical Institute, Academy of Sciences, CZ-251 65 Ond?ejov (Czech Republic); Orio, M. [Astronomical Observatory of Padova (INAF), I-35122 Padova (Italy); Pietsch, W. [Max Planck Institute for Extraterrestrial Physics, P.O. Box 1312, Giessenbachstr., D-85741, Garching (Germany); Darnley, M. J.; Williams, S. C.; Bode, M. F. [Astrophysics Research Institute, Liverpool John Moores University, Liverpool L3 5RF (United Kingdom); Bryan, J., E-mail: aws@nova.sdsu.edu [McDonald Observatory, Austin, TX 78712 (United States)
2015-02-01
The reported positions of 964 suspected nova eruptions in M31 recorded through the end of calendar year 2013 have been compared in order to identify recurrent nova (RN) candidates. To pass the initial screen and qualify as a RN candidate, two or more eruptions were required to be coincident within 0.?1, although this criterion was relaxed to 0.?15 for novae discovered on early photographic patrols. A total of 118 eruptions from 51 potential RN systems satisfied the screening criterion. To determine what fraction of these novae are indeed recurrent, the original plates and published images of the relevant eruptions have been carefully compared. This procedure has resulted in the elimination of 27 of the 51 progenitor candidates (61 eruptions) from further consideration as RNe, with another 8 systems (17 eruptions) deemed unlikely to be recurrent. Of the remaining 16 systems, 12 candidates (32 eruptions) were judged to be RNe, with an additional 4 systems (8 eruptions) being possibly recurrent. It is estimated that ?4% of the nova eruptions seen in M31 over the past century are associated with RNe. A Monte Carlo analysis shows that the discovery efficiency for RNe may be as low as 10% that for novae in general, suggesting that as many as one in three nova eruptions observed in M31 arise from progenitor systems having recurrence times ?100 yr. For plausible system parameters, it appears unlikely that RNe can provide a significant channel for the production of Type Ia supernovae.
Multilayer Graphene for Waveguide Terahertz Modulator
DEFF Research Database (Denmark)
Khromova, I.; Andryieuski, Andrei
2014-01-01
We study terahertz to infrared electromagnetic properties of multilayer graphene/dielectric artificial medium and present a novel concept of terahertz modulation at midinfrared wavelengths. This approach allows the realization of high-speed electrically controllable terahertz modulators based on hollow waveguide sections filled with multilayer graphene.
Multi-Layer E-Textile Circuits
Dunne, Lucy E.; Bibeau, Kaila; Mulligan, Lucie; Frith, Ashton; Simon, Cory
2012-01-01
Stitched e-textile circuits facilitate wearable, flexible, comfortable wearable technology. However, while stitched methods of e-textile circuits are common, multi-layer circuit creation remains a challenge. Here, we present methods of stitched multi-layer circuit creation using accessible tools and techniques.
Pigmented villonodular synovitis: extrasynovial recurrence.
Jobe, Christopher M; Raza, Anwar; Zuckerman, Lee
2011-10-01
A 32-year-old female athlete underwent arthroscopy for a second recurrence of pigmented villonodular synovitis (PVNS), which was extrasynovial, seen on magnetic resonance imaging. It was noted on arthroscopy that (1) the nodules moved medially with joint insufflation, (2) the nodules were less prominent than on magnetic resonance imaging, and (3) more than 95% of the recurrent tumor was hidden by neosynovium. We believe that the extrasynovial location is because of the more rapid proliferation of the neosynovium relative to the growth of the remaining tumor cells after the previous resection. In resecting pigmented villonodular synovitis with a high risk of recurrence, a layer of periarticular fat should be removed and the surgeon should be wary of change in position with insufflation. PMID:21889289
[Sclerotherapy for recurrent glomus tumors].
Benchakroun, M; Zaddoug, O; Boussouga, M; Boukhris, J; Jaafar, A
2013-05-01
We report the cases of two women aged 28 and 34 years who presented recurrent glomus tumors of the hand after surgery for marginal resection of the tumor mass. The pathological study of the surgical specimen confirmed the diagnosis of recurrent glomus tumor. Due to the vascular origin of this tumor, sclerotherapy was delivered. The functional outcomes were good with dramatic pain relief within a few days. At 3-year mean follow-up, the cosmetic and functional results were very satisfactory. PMID:23660495
First realization and characterization of multilayer EUV reflective coatings
Nicolosi, Piergiorgio; Patelli, Alessandro; Pelizzo, Maria-Guglielmina; Rigato, Valentino; Maggioni, Gianluigi; Depero, L.; Bontempi, E.; Mattei, G.; Poletto, Luca; Mazzoldi, Paolo; Tondello, Giuseppe
2001-12-01
Experimental results on the realization of Mo/Si multilayer mirrors for EUV applications are presented. The multilayers have been deposited using RF-magnetron sputtering. The characterization of single layers and multilayers has been performed using different physical techniques. The reflectivity of multilayer mirrors optimised for 13 and 19 nm radiation has been measured and compared to simulation.
Recent advances in etched multilayer X-ray optics
André, J.; Sammar, A.; Bac, S.; Ouahabi, M.; Idir, M.; Soullié, G.; Barchewitz, R.
1994-01-01
We present the recent advances achieved in the Laboratoire de Chimie Physique of Université Paris 6, in the field of the soft X-ray etched multilayer optics. Modellings and characterizations are given for the laminar multilayer amplitude gratings, the highly resolutive X-ray multilayer monochromators, the X-ray polychromators and the Bragg-Fresnel multilayer linear lenses.?
Ovarian irradiation in recurrent endometriosis
International Nuclear Information System (INIS)
We describe a case of a young woman with a history of an aplastic anaemia in which pelvic radiotherapy was used successfully in the management of a recurrent and inoperable endometriosis. The use of therapeutic pelvic or ovarian irradiation in endometriosis may be considered, when surgical and medical treatments have been exhausted and have failed. (authors)
Coping with Fear of Recurrence
... Fear of Recurrence Having a Baby After Cancer: Pregnancy Having a Baby After Cancer: Fertility Assistance and Other Options Recognizing and Celebrating Milestones Going Back to Work After Cancer Cancer and Workplace Discrimination Finding a Job After Cancer Stopping Work After ...
Recurrence Formulas for Fibonacci Sums
Brandao, Adilson J V
2008-01-01
In this article we present a new recurrence formula for a finite sum involving the Fibonacci sequence. Furthermore, we state an algorithm to compute the sum of a power series related to Fibonacci series, without the use of term-by-term differentiation theorem
Hyperthermia of recurrent breast sarcoma
International Nuclear Information System (INIS)
Full text: Breast sarcomas comprise approximately 3 % of all malignant breast tumors. The efficacy of adjuvant chemotherapy, hormone therapy or radiotherapy has not been proven. Recently, hyperthermia (HT) has been recognized as an effective adjuvant in treatment of locally advanced recurrent breast cancer. A 72-year-old female patient was admitted to our breast unit. In her history she had 10 resections for recurrent liposarcoma of the left breast over a period of 14 years, comprising resection of the infiltrated axillary vein. After a new wide resection and implantation of two interstitial devices HT was performed with a total number of 6 sessions over 3 weeks. The time for each session was 60 minutes. Temperature was exactly calibrated between 40 and 43 degrees Celsius. No notable complications were observed. The patient is free of local recurrence for a follow up period of 49 months. Our results suggest that local hyperthermia may be useful to prevent local recurrence in liposarcoma of the breast. The data should encourage further clinical studies. (author)
14 CFR 121.427 - Recurrent training.
2010-01-01
...respectively. (4) Approved recurrent CRM training. For flight crewmembers, this...training (LOFT) session. The recurrent CRM training requirement does not apply until a person has completed the applicable initial CRM training required by §§ 121.419,...
Evidence-based management of recurrent miscarriages
Jeve, Yadava B.; Davies, William
2014-01-01
Recurrent miscarriages are postimplantation failures in natural conception; they are also termed as habitual abortions or recurrent pregnancy losses. Recurrent pregnancy loss is disheartening to the couple and to the treating clinician. There has been a wide range of research from aetiology to management of recurrent pregnancy loss. It is one of the most debated topic among clinicians and academics. The ideal management is unanswered. This review is aimed to produce an evidence-based guidance...
2015-06-02
Anxiety Disorder; Depression; Fatigue; Leydig Cell Tumor; Ovarian Sarcoma; Ovarian Stromal Cancer; Pain; Peritoneal Carcinomatosis; Pseudomyxoma Peritonei; Recurrent Breast Cancer; Recurrent Cervical Cancer; Recurrent Endometrial Carcinoma; Recurrent Fallopian Tube Cancer; Recurrent Gestational Trophoblastic Tumor; Recurrent Ovarian Epithelial Cancer; Recurrent Ovarian Germ Cell Tumor; Recurrent Primary Peritoneal Cavity Cancer; Recurrent Uterine Sarcoma; Recurrent Vaginal Cancer; Recurrent Vulvar Cancer
2014-05-20
Anxiety Disorder; Depression; Fatigue; Leydig Cell Tumor; Ovarian Sarcoma; Ovarian Stromal Cancer; Pain; Peritoneal Carcinomatosis; Pseudomyxoma Peritonei; Recurrent Breast Cancer; Recurrent Cervical Cancer; Recurrent Endometrial Carcinoma; Recurrent Fallopian Tube Cancer; Recurrent Gestational Trophoblastic Tumor; Recurrent Ovarian Epithelial Cancer; Recurrent Ovarian Germ Cell Tumor; Recurrent Primary Peritoneal Cavity Cancer; Recurrent Uterine Sarcoma; Recurrent Vaginal Cancer; Recurrent Vulvar Cancer
On generalized M-projectively recurrent manifolds
Directory of Open Access Journals (Sweden)
Uday Chand De
2014-04-01
Full Text Available The purpose of the present paper is to study generalized M-projectively recurrent manifolds. Some geometric properties of generalized M-projectively recurrent manifolds have been studied under certain curvature conditions. An application of such a manifold in the theory of relativity has also been shown. Finally, we give an example of a generalized M-projectively recurrent manifold.
Learning temporal dependencies in connectionist speech recognition
Renals, Steve; Hochberg, Mike; Robinson, Tony
1994-01-01
Hybrid connectionist/HMM systems model time using both a Markov chain and through properties of a connectionist network. In this paper, we discuss the nature of the time dependence currently employed in our systems using recurrent networks (RNs) and feed-forward multi-layer perceptrons (MLPs). In particular, we introduce local recurrences into an MLP to produce an enhanced input representation. This is in the form of an adaptive gamma filter and incorporates an automatic approach for learning...
Multilayer networks: metrics and spectral properties
Cozzo, Emanuele; Rodrigues, Francisco A; Moreno, Yamir
2015-01-01
Multilayer networks represent systems in which there are several topological levels each one representing one kind of interaction or interdependency between the systems' elements. These networks have attracted a lot of attention recently because their study allows considering different dynamical modes concurrently. Here, we revise the main concepts and tools developed up to date. Specifically, we focus on several metrics for multilayer network characterization as well as on the spectral properties of the system, which ultimately enable for the dynamical characterization of several critical phenomena. The theoretical framework is also applied for description of real-world multilayer systems.
BESSY Bragg-Fresnel multilayer beam monitors
International Nuclear Information System (INIS)
X-ray optical systems based on Bragg-Fresnel multilayer components imaging an electron beam in a storage ring with ?m resolution are presented. Design concepts are compared to alternative methods, and the aberrations and limits of Bragg-Fresnel multilayer optics are discussed. Experimental results of imaging the BESSY I source with sub-10-?m resolution are presented, and the development of a compact Bragg-Fresnel multilayer telescope as a BESSY II standard beam monitor is described. copyright 1996 American Institute of Physics
Tunable optical properties of multilayers black phosphorus
Low, Tony; Carvalho, A; Jiang, Yongjin; Wang, Han; Xia, Fengnian; Neto, A H Castro
2014-01-01
We calculated the optical conductivity tensor of multilayers black phosphorus using the Kubo formula within an effective low-energy Hamiltonian. The optical absorption spectra of multilayers black phosphorus are shown to vary sensitively with thickness, doping, and light polarization. In conjunction with experimental spectra obtained from infrared absorption spectroscopy, we discuss the role of interband coupling and disorder on the observed anisotropic absorption spectra. Multilayers black phosphorus might offer attractive alternatives to narrow gap compound semiconductors for optoelectronics across mid- to near-infrared frequencies.
Giant recurrent retroperitoneal liposarcoma presenting as a recurrent inguinal hernia
Directory of Open Access Journals (Sweden)
Sameer Vora
2011-09-01
Full Text Available Retroperitoneal liposarcoma presenting as an inguinal hernia is a rare entity. We present the first case of Giant recurrent liposarcoma presenting as a recurrent inguinal hernia in a 40-year-old male. Physical examination showed an irreducible lump in the right inguinal region and a scar in the right lumbar and right inguinal region. Computed tomography (CT scan of abdomen revealed it to be a retro peritoneal mass extending into the right inguinal region along and involving the cord structures. Wide local excision of the tumour with right orchidectomy and inguinal hernioplasty was performed. Histo-pathology confirmed it to be a liposarcoma. Patient received postoperative radio therapy. Follow up of two years has shown him to be disease free. Retroperitoneal liposarcoma can grow along cord structures into the inguinal canal and mimic an irreducible indirect inguinal hernia.
Giant recurrent retroperitoneal liposarcoma presenting as a recurrent inguinal hernia
Bhandarwar, Ajay H.; Bakhshi, Girish D.; Borisa, Ashok D.; Shenoy, Sachin S.; Kori, Channabasappa G.; Vora, Sameer
2011-01-01
Retroperitoneal liposarcoma presenting as an inguinal hernia is a rare entity. We present the first case of Giant recurrent liposarcoma presenting as a recurrent inguinal hernia in a 40-year-old male. Physical examination showed an irreducible lump in the right inguinal region and a scar in the right lumbar and right inguinal region. Computed tomography (CT) scan of abdomen revealed it to be a retro peritoneal mass extending into the right inguinal region along and involving the cord structures. Wide local excision of the tumour with right orchidectomy and inguinal hernioplasty was performed. Histo-pathology confirmed it to be a liposarcoma. Patient received postoperative radio therapy. Follow up of two years has shown him to be disease free. Retroperitoneal liposarcoma can grow along cord structures into the inguinal canal and mimic an irreducible indirect inguinal hernia. PMID:24765371
Recurrent and non-recurrent trajectories in a chaotic system
Directory of Open Access Journals (Sweden)
A. O. Akala
2010-09-01
Full Text Available The dynamics of a system subjected to a potential equal to the sum of the Henon-Heiles potential and that of thehydrogen atom in a uniform magnetic field has been studied. Depending on the energy of the system, the Poincaresurface is characterised by regions of regular motion, appearing and disappearing regions of regular motion, regions ofrecurrent (regular and chaotic trajectories and those of non-recurrent trajectories.
Magnetic quantization in multilayer graphenes
Lin, Chiun-Yan; Ou, Yih-Jon; Chiu, Yu-Huang; Lin, Ming-Fa
2015-01-01
Essential properties of multilayer graphenes are diversified by the number of layers and the stacking configurations. For an $N$-layer system, Landau levels are divided into $N$ groups, with each identified by a dominant sublattice associated with the stacking configuration. We focus on the main characteristics of Landau levels, including the degeneracy, wave functions, quantum numbers, onset energies, field-dependent energy spectra, semiconductor-metal transitions, and crossing patterns, which are reflected in the magneto-optical spectroscopy, scanning tunneling spectroscopy, and quantum transport experiments. The Landau levels in AA-stacked graphene are responsible for multiple Dirac cones, while in AB-stacked graphene the Dirac properties depend on the number of graphene layers, and in ABC-stacked graphene the low-lying levels are related to surface states. The Landau-level mixing leads to anticrossings patterns in energy spectra, which are seen for intergroup Landau levels in AB-stacked graphene, while in...
Electronic properties of graphene multilayers
Nilsson, J; Guinea, F; Peres, N M R; Nilsson, Johan
2006-01-01
We study the effects of disorder in the electronic properties of graphene multilayers, with special focus on the bilayer and the infinite stack. At low energies and long wavelengths, the electronic self-energies and density of states exhibit behavior with divergences near half-filling. As a consequence, the spectral functions and conductivities do not follow Landau's Fermi liquid theory. In particular, we show that the quasiparticle decay rate has a minimum as a function of energy, there is a universal minimum value for the in-plane conductivity of order e^2/h per plane and, unexpectedly, the c-axis conductivity is enhanced by disorder at low doping, leading to an enormous conductivity anisotropy at low temperatures.
Centrality in Interconnected Multilayer Networks
De Domenico, Manlio; Omodei, Elisa; Gómez, Sergio; Arenas, Alex
2013-01-01
Real-world complex systems exhibit multiple levels of relationships. In many cases, they require to be modeled by interconnected multilayer networks, characterizing interactions on several levels simultaneously. It is of crucial importance in many fields, from economics to biology, from urban planning to social sciences, to identify the most (or the less) influent nodes in a network. However, defining the centrality of actors in an interconnected structure is not trivial. In this paper, we capitalize on the tensorial formalism, recently proposed to characterize and investigate this kind of complex topologies, to show how several centrality measures -- well-known in the case of standard ("monoplex") networks -- can be extended naturally to the realm of interconnected multiplexes. We consider diagnostics widely used in different fields, e.g., computer science, biology, communication and social sciences, to cite only some of them. We show, both theoretically and numerically, that using the weighted monoplex obta...
Phrenic-Recurrent Nerve Anastomosis in Animal Models with Unilateral Cutting of the Recurrent Nerve
Engin, Omer; Ipekci, Fuat; Yildirim, Mehmet; Kulan, Ahmet; Yagci, Ayse; Dalgic, Abdullah; Calik, Bulent
2010-01-01
In our experimental study, the aim was to recover vocal cord physiology in cutting of recurrent laryngeal nerve, thus phrenic-recurrent nerve transposition was planned in rabbits. Experiments were performed on 10 experimental and 10 control rabbits. The right recurrent nerve was cut in the control group, while in the experiment group, the right recurrent nerve was cut. Then, a right phrenic-recurrent nerve end-to-end anastomosis was performed and the results were evaluated. After the 3rd post...
Recurrent gossypiboma in the thigh
International Nuclear Information System (INIS)
Gossypiboma, an iatrogenic mass lesion caused by a retained surgical sponge is an extremely rare event following musculoskeletal procedures. This entity is therefore a very unusual experience and can create considerable confusion. Unsuspecting surgeons may thus be caught out by this unlikely presentation. We present our experience with a recurrent gossypiboma in the thigh occurring several years after surgical evacuation of a similar gossypiboma from the same anatomic location with interval resolution of symptoms. The purpose of this case report is to highlight the possibility of a ''recurrent'' soft tissue mass occurring for reasons other than a neoplasm. In the absence of a definitive biopsy diagnosis of tumor in patients who have undergone prior surgical procedures in that area, it may be more prudent to adopt a conservative surgical resection rather than a conventional radical resection as warranted by the dramatic clinical presentation mimicking a soft tissue sarcoma. (orig.)
Recurrent gossypiboma in the thigh
Energy Technology Data Exchange (ETDEWEB)
Puri, Ajay; Anchan, Chetan; Agarwal, Manish G. [Tata Memorial Hospital, Department of Orthopaedic Oncology, Mumbai (India); Jambhekar, Nirmala A. [Tata Memorial Hospital, Department of Pathology, Mumbai (India); Badwe, Rajendra A. [Tata Memorial Hospital, Department of Surgical Oncology, Mumbai (India)
2007-06-15
Gossypiboma, an iatrogenic mass lesion caused by a retained surgical sponge is an extremely rare event following musculoskeletal procedures. This entity is therefore a very unusual experience and can create considerable confusion. Unsuspecting surgeons may thus be caught out by this unlikely presentation. We present our experience with a recurrent gossypiboma in the thigh occurring several years after surgical evacuation of a similar gossypiboma from the same anatomic location with interval resolution of symptoms. The purpose of this case report is to highlight the possibility of a ''recurrent'' soft tissue mass occurring for reasons other than a neoplasm. In the absence of a definitive biopsy diagnosis of tumor in patients who have undergone prior surgical procedures in that area, it may be more prudent to adopt a conservative surgical resection rather than a conventional radical resection as warranted by the dramatic clinical presentation mimicking a soft tissue sarcoma. (orig.)
Multilayered Josephson junction logic and memory devices
International Nuclear Information System (INIS)
Flux quantum logic and memory circuits using superconducting Josephson tunnel junctions have high-speed switching times (? 1 ps), low power dissipation (< 1 microW per circuit) and low levels of thermally induced electrical noise. Current designs of such circuits employ single trilayer junctions, which impose circuit size and logic threshold limitations. A new design component, the multilayered tunnel junction, consists of a vertically stacked array (a one dimensional superlattice) of Josephson tunnel junctions. The introduction of multilayered junctions into superconducting electronic circuitry offers a reduction in current device size, fault tolerances, and new device applications. The authors present numerical simulations of simple circuits employing multilayered Josephson junctions as design components. Comparison with conventional single flux quantum (SFQ) circuitry is discussed. They also present preliminary measurements of multilayered Josephson junctions fabricated for use in flux quantum devices
Review of the multilayer coating model
Kubo, Takayuki; Saeki, Takayuki
2014-01-01
The recent theoretical study on the multilayer-coating model published in Applied Physics Letters [1] is reviewed. Magnetic-field attenuation behavior in a multilayer coating model is different from a semi-infinite superconductor and a superconducting thin film. This difference causes that of the vortex-penetration field at which the Bean-Livingston surface barrier disappears. A material with smaller penetration depth, such as a pure Nb, is preferable as the substrate for pushing up the vortex-penetration field of the superconductor layer. The field limit of the whole structure of the multilayer coating model is limited not only by the vortex-penetration field of the superconductor layer, but also by that of the substrate. Appropriate thicknesses of superconductor and insulator layers can be extracted from contour plots of the field limit of the multilayer coating model given in Ref.[1].
Irradiated multilayer film for primal meat packaging
International Nuclear Information System (INIS)
This patent deals with a heat-shrinkable, multilayer film suitable for use in fabricating bags for packaging primal and sub-primal meat cuts and processed meats. The multilayer film has a first outer layer of a first ethylene-vinyl acetate copolymer, a core layer of a polyvinylidene chloride-vinyl chloride copolymer containing between about 70 weight percent and about 90 weight percent vinylidene chloride as a barrier film, and a second outer layer of a second ethylene-vinyl acetate copolymer. The multilayer film is preferably made by co-extrusion of the layers, and then it is biaxially stretched. After biaxial stretching, the entire multilayer film is substantially uniformly irradiated to a dosage level of between about 2 megarads and about 3 megarads and heat-sealed in the form of a bag. The film is not significantly discoloured by the irradiation and the bag has improved toughness properties and heat-sealing characteristics
Irradiated multilayer film for primal meat packaging
International Nuclear Information System (INIS)
This patent deals with a heat-shrinkable, multilayer film suitable for use in fabricating bags for packaging primal and sub-primal meat cuts and processed meats. The multilayer film has a first outer layer of an ethylene-vinyl acetate copolymer, a core layer of a barrier film comprising vinylidene chloride-methyl acrylate copolymer, and a second outer layer of an ethylene-vinyl acetate copolymer. The multilayer film is preferably made by co-extrusion of the layers, and then it is biaxially stretched. After biaxial stretching, the multilayer film is irradiated to a dosage level of between 1 megarad and 5 megarads and heat-sealed in the form of a bag. The bag has improved storage stability characteristics
Sliced multilayer grating x-ray spectroscopy
Wilson, Michele M.; Zukic, Muamer; Kim, Jongmin; Torr, Douglas G.; Fennelly, Alphonsus J.; Fry, Edward L.
1994-11-01
Low energy monochromatic x rays can be ]used to detect the attenuation differences between fibrous, fat, and cancerous tissues in mammography, evaluation of computer processor chips, as well as quality control for micro components. At 17 keV, carcinomas, fibrous and fatty tissues attenuate incident radiation to different degrees which permits non invasive detection of cancerous tissue. A sliced transmission multilayer grating is presented that produces monochromatic x-ray radiation at 17 keV. The sliced multilayer utilizes the coincidence of Bragg and diffraction orders to achieve higher efficiency and resolution than a conventional grating. A classical multilayer consisting of low and high atomic number materials along with a monomaterial multilayer in which the density of the material is varied to simulate two different layers are presented.
Treatment of Recurrent Ovarian Cancer.
Hacker, Neville F.; Michael Friedlander
2004-01-01
Recurrent ovarian cancer is a common clinical problem and the management of eachpatient must be individualized. Diagnosis is usually based on a progressively rising CA-125titre, and a CT scan of the pelvis and abdomen, together with a chest X-ray should be performed.Although there is no study to support immediate treatment in the asymptomaticpatient, our approach is to commence such patients on Tamoxifen. Chemotherapy isreserved for asymptomatic patients or those who progress on Tamoxifen. Th...
Visualizing and Understanding Recurrent Networks
Karpathy, Andrej; Johnson, Justin; Li, Fei-Fei
2015-01-01
Recurrent Neural Networks (RNNs), and specifically a variant with Long Short-Term Memory (LSTM), are enjoying renewed interest as a result of successful applications in a wide range of machine learning problems that involve sequential data. However, while LSTMs provide exceptional results in practice, the source of their performance and their limitations remain rather poorly understood. Using character-level language models as an interpretable testbed, we aim to bridge this ...
Recurrent Pregnancy Loss and Thrombophilia
D’uva, Maristella; Micco, Pierpaolo Di; Strina, Ida; Placido, Giuseppe
2010-01-01
Emerging data seem to be available also on the role of active thromboprophylaxis with heparin and pregnancy outcome. In the last decades we found many data concerning the association between a hypercoagulable state and its causes and adverse pregnancy outcome, in particular recurrent pregnancy loss (RPL). First studies which focused on the association between thrombophilia and RPL underlined the role of reduced clotting inhibitors and RPL, and subsequent studies underlined a pathogenetic role...
[Suicidal risk in recurrent depression].
Courtet, P
2010-12-01
Recurrent depression represents a major target of suicide prevention, due to its high prevalence and its strong association to Suicidal Behaviour (SB). In France, every year, nearly 11,000 persons dye from completed suicide and 200,000 attempt suicide. It has been recently shown that the adjusted population attributable fraction of the time spent depressed for suicide attempts was 78%. Thus, suicidal risk in recurrent depression being related to severity, partial response to treatment, chronicity and recurrences, the expectancies of treatment should be elevated. The assessment of the suicidal risk should involve psychiatric comorbidities that facilitate the act, particularly alcohol misuse, and also the lack of social support. The current conceptualisation of SB allows considering them as psychiatric entities per se. Consequently, the evaluation will be focused on the specific suicidal vulnerability: personal and family history of SB, hopelessness and impulsive aggression, and childhood maltreatment. The existence of this vulnerability would help to detect very high-risk patients, in order to deliver the necessary protections. Current advances provided by the use of neuroscientific tools open the way to improve our understanding of the pathophysiology of SB. Based on this multifocal evaluation, the clinician would identify potential therapeutic targets. Indeed, the priority is first to treat adequately recurrent depression, as it is clear that too many patients do not receive such a treatment. Next steps would be related to the efforts allowing obtaining complete remission. Comorbid disorders would need specific care. This is the case for the suicidal comorbidity that may justify implementing specific treatments such as lithium or focused psychotherapies. Finally, innovative care management need to be developed, as they are likely to be helpful to provide continuously assistance to people who are suffering in order to avoid a suicidal act. PMID:21211632
Pinealitis accompanying equine recurrent uveitis.
Kalsow, C. M.; Dwyer, A. E.; Smith, A. W.; Nifong, T. P.
1993-01-01
There is no direct verification of pineal gland involvement in human uveitis. Specimens of pineal tissue are not available during active uveitis in human patients. Naturally occurring uveitis in horses gives us an opportunity to examine tissues during active ocular inflammation. We examined the pineal gland of a horse that was killed because it had become blind during an episode of uveitis. The clinical history and histopathology of the eyes were consistent with post-leptospiral equine recurr...
Review of the multilayer coating model
Kubo, Takayuki; Iwashita, Yoshihisa; Saeki, Takayuki
2014-01-01
The recent theoretical study on the multilayer-coating model published in Applied Physics Letters [1] is reviewed. Magnetic-field attenuation behavior in a multilayer coating model is different from a semi-infinite superconductor and a superconducting thin film. This difference causes that of the vortex-penetration field at which the Bean-Livingston surface barrier disappears. A material with smaller penetration depth, such as a pure Nb, is preferable as the substrate for pu...
Multi-Layer Microbubbles by Microfluidics
Hongbo Zhang; Haosu Meng; Qian Sun; Jianpu Liu; Zhang, W. J.
2013-01-01
Multi-layer microbubble has great potential in enabling the corporation of medical imaging with tumor therapy such as drug and gene delivery of therapeutics or other functional materials in medical applications. Microfluidic technique has advanced over the last decade and showed great promise in replacing traditional microbubble generating method. In this paper, a multi-layer microbubble structure was produced with the aspect as potentially used for drug loaded microbub...
Multilayer Nanofilms as Substrates for Hepatocellular Applications
Wittmer, Corinne R.; Phelps, Jennifer A.; Lepus, Christin M.; Saltzman, W. Mark; Harding, Martha J.; Tassel, Paul R.
2008-01-01
Multilayer nanofilms, formed by the layer-by-layer (LbL) adsorption of positively and negatively charged polyelectrolytes, are promising substrates for tissue engineering. We investigate here the attachmemt and function of hepatic cells on multilayer films in terms of film composition, terminal layer, rigidity, charge, and presence of biofunctional species. Human hepatocellular carcinoma cells (HepG2), adult rat hepatocytes (ARH), and human fetal hepatoblasts (HFHb) are studied on films compo...
Fretting wear of metallic multilayer films
International Nuclear Information System (INIS)
Fretting wear behaviour of electrodeposited Cu/Ni multilayer films with 10 and 5 nm thick sublayers has been investigated against a hardened steel ball as the counter body and compared with that of the constituents, Cu and Ni. The wear tests were carried out by using a ball-on-flat geometry at a translation frequency of 8 Hz and slip amplitude of 100 ?m. Friction force was recorded on line during the tests. At the end of the tests, the wear scars were examined by laser surface profilometry, scanning electron microscopy and energy dispersive X-ray microanalysis. It has been observed that the frictional and wear mechanisms are very different for copper, nickel and Cu/Ni multilayers. Fretting of copper creates a relatively smooth wear scar mainly by mechanical ploughing of the asperities on steel counterbody (abrasive wear) and shows a very little third body interaction. Fretting of nickel involves adhesive wear resulting in a large transfer of steel to nickel, which is attributed to the strong chemical interaction between nickel and the steel counterbody. Fretting on multilayers involves a strong third body interaction resulting in ploughing mainly by debris (abrasive wear). The coefficient of friction is approximately 0.45 for copper, and approximately 0.8 for nickel as well as for multilayers. The values of the coefficient of friction for nickel and Cu/Ni multilayers found under the present fretting conditions are approximately double the corresponding values reportey double the corresponding values reported earlier for sliding wear conditions. It has been found that Cu/Ni multilayer is more resistance to fretting wear than the constituents, copper and nickel. Furthermore, the fretting wear resistance of Cu/Ni multilayers with 5 nm thick sublayer is better than that of the multilayers with 10 nm thick sublayers
Ordered organic-organic multilayer growth
Energy Technology Data Exchange (ETDEWEB)
Forrest, Stephen R; Lunt, Richard R
2015-01-13
An ordered multilayer crystalline organic thin film structure is formed by depositing at least two layers of thin film crystalline organic materials successively wherein the at least two thin film layers are selected to have their surface energies within .+-.50% of each other, and preferably within .+-.15% of each other, whereby every thin film layer within the multilayer crystalline organic thin film structure exhibit a quasi-epitaxial relationship with the adjacent crystalline organic thin film.
Interactions in bonded soft magnetic particle multilayers
International Nuclear Information System (INIS)
Magnetisation measurements have been made on a polymer-bonded NiFe/CoFe multilayered structure. Changes in the magnetisation loop in relation to the direction of the applied field have been attributed to associated demagnetisation factors. Computation has also been performed, using a finite element package to calculate the levels of induction within the multilayered sample, as a function of magnitude and orientation of the applied field
Recurrent frequency-size distribution
Abaimov, S G
2008-01-01
Many complex systems, including a sand-pile model, a slider-block model, and actual earthquakes, have been discussed whether they obey the principles of self-organized criticality. Behavior of these systems can be investigated from two different points of view: interoccurrent behavior in a region and recurrent behavior at a given point on a fault or at a given fault. The interoccurrent frequency-size statistics are known to be scale-invariant and obey the power-law Gutenberg-Richter distribution. This paper investigates the recurrent frequency-size behavior at a given point on a fault or at a given fault. For this purpose sequences of creep events at a creeping section of the San Andreas fault are investigated. The applicability of Brownian passage-time, lognormal, and Weibull distributions to the recurrent frequency-size statistics of slip events is tested and the Weibull distribution is found to be a best-fit distribution. To verify this result the behavior of the numerical slider-block and sand-pile models...
Locoregional recurrence after management of carcinoma breast
International Nuclear Information System (INIS)
Objective: To determine the rate of locoregional recurrence, disease-free interval, site and pattern of locoregional recurrence and the significance of different factors for predicting locoregional recurrence in patients with stage II and III carcinoma breast. Patients and Methods: Criteria for including patients in this study was female patients with stage II and III carcinoma breast who presented in our unit from 1995-2002 and underwent surgical (modified radical mastectomy, simple mastectomy with axillary sampling) and non-surgical (chemotherapy, radiotherapy, hormonal therapy) treatment of carcinoma breast. Record of 98 patients was evaluated for rate of locoregional recurrence, disease-free interval, site and pattern of locoregional recurrence and different clinical factors like stage of carcinoma, tumour size, lymph node status and histopathology were assessed for association with locoregional recurrence. Results: After a mean follow-up of 3.5 years, 17 patients developed locoregional recurrence. Mean disease free interval in stage II was 30 months and only 9.5 months in stage III. Lymph node positivity was associated with locoregional recurrence (p-value is less than 0.05). Chest wall was commonest site of recurrence (73%). Single spot recurrence was common in stage II whereas multiple spot recurrence and field change was more common in stage III. Addition of radiotherapy to surgery decreased the locoregional recurrence but chemotherapy had no significant effec but chemotherapy had no significant effect on prevention of locoregional recurrence. Conclusion: In this series 17.34 % patients developed locoregional recurrence for mean follow-up duration of 3.5 years. Mean disease-free interval was 20.52 months. Lymph node involvement had significant correlation with LRR. (author)
Capability of etched multilayer EUV mask fabrication
Takai, Kosuke; Murano, Koji; Kamo, Takashi; Morikawa, Yasutaka; Hayashi, Naoya
2014-09-01
Recently, development of next generation extremely ultraviolet lithography (EUVL) equipment with high-NA (Numerical Aperture) optics for less than hp10nm node is accelerated. Increasing magnification of projection optics or mask size using conventional mask structure has been studied, but these methods make lithography cost high because of low through put and preparing new large mask infrastructures. To avoid these issues, etched multilayer EUV mask has been proposed. As a result of improvement of binary etched multilayer mask process, hp40nm line and space pattern on mask (hp10nm on wafer using 4x optics) has been demonstrated. However, mask patterns are easily collapsed by wet cleaning process due to their low durability caused by high aspect ratio. We propose reducing the number of multilayer pairs from 40 to 20 in order to increase durability against multilayer pattern collapse. With 20pair multilayer blank, durable minimum feature size of isolated line is extended from 80nm to 56nm. CD uniformity and linearity of 20pair etched multilayer pattern are catching up EUV mask requirement of 2014.
2015-02-19
Childhood Choroid Plexus Tumor; Childhood Ependymoblastoma; Childhood Grade III Meningioma; Childhood High-grade Cerebellar Astrocytoma; Childhood High-grade Cerebral Astrocytoma; Childhood Medulloepithelioma; Recurrent Childhood Anaplastic Astrocytoma; Recurrent Childhood Anaplastic Oligoastrocytoma; Recurrent Childhood Anaplastic Oligodendroglioma; Recurrent Childhood Brain Stem Glioma; Recurrent Childhood Cerebellar Astrocytoma; Recurrent Childhood Cerebral Astrocytoma; Recurrent Childhood Giant Cell Glioblastoma; Recurrent Childhood Glioblastoma; Recurrent Childhood Gliomatosis Cerebri; Recurrent Childhood Gliosarcoma; Recurrent Childhood Medulloblastoma; Recurrent Childhood Pineoblastoma; Recurrent Childhood Supratentorial Primitive Neuroectodermal Tumor
Sperm DNA fragmentation, recurrent implantation failure and recurrent miscarriage
Directory of Open Access Journals (Sweden)
Carol Coughlan
2015-01-01
Full Text Available Evidence is increasing that the integrity of sperm DNA may also be related to implantation failure and recurrent miscarriage (RM. To investigate this, the sperm DNA fragmentation in partners of 35 women with recurrent implantation failure (RIF following in vitro fertilization, 16 women diagnosed with RM and seven recent fathers (control were examined. Sperm were examined pre- and post-density centrifugation by the sperm chromatin dispersion (SCD test and the terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL assay. There were no significant differences in the age of either partner or sperm concentration, motility or morphology between three groups. Moreover, there were no obvious differences in sperm DNA fragmentation measured by either test. However, whilst on average sperm DNA fragmentation in all groups was statistically lower in prepared sperm when measured by the SCD test, this was not seen with the results from the TUNEL assay. These results do not support the hypothesis that sperm DNA fragmentation is an important cause of RIF or RM, or that sperm DNA integrity testing has value in such patients. It also highlights significant differences between test methodologies and sperm preparation methods in interpreting the data from sperm DNA fragmentation tests.
Multilayer Piezoelectric Stack Actuator Characterization
Sherrit, Stewart; Jones, Christopher M.; Aldrich, Jack B.; Blodget, Chad; Bao, Xioaqi; Badescu, Mircea; Bar-Cohen, Yoseph
2008-01-01
Future NASA missions are increasingly seeking to use actuators for precision positioning to accuracies of the order of fractions of a nanometer. For this purpose, multilayer piezoelectric stacks are being considered as actuators for driving these precision mechanisms. In this study, sets of commercial PZT stacks were tested in various AC and DC conditions at both nominal and extreme temperatures and voltages. AC signal testing included impedance, capacitance and dielectric loss factor of each actuator as a function of the small-signal driving sinusoidal frequency, and the ambient temperature. DC signal testing includes leakage current and displacement as a function of the applied DC voltage. The applied DC voltage was increased to over eight times the manufacturers' specifications to investigate the correlation between leakage current and breakdown voltage. Resonance characterization as a function of temperature was done over a temperature range of -180C to +200C which generally exceeded the manufacturers' specifications. In order to study the lifetime performance of these stacks, five actuators from one manufacturer were driven by a 60volt, 2 kHz sine-wave for ten billion cycles. The tests were performed using a Lab-View controlled automated data acquisition system that monitored the waveform of the stack electrical current and voltage. The measurements included the displacement, impedance, capacitance and leakage current and the analysis of the experimental results will be presented.
Multilayer transducer transfer matrix formalism.
Bloomfield, Philip E
2002-09-01
A complete formulation of direct and inverse 4 x 4 transfer matrices for parallel and series, electrically connected, mechanically stacked, 1-D thickness mode multilayer piezoelectric transducers is presented. Complex coefficients account for the mechanical, dielectric, and piezoelectric losses. The direct or inverse 4 x 4 transfer matrix transfers quantities at the top surface into their values at the bottom surface or vice versa, respectively. The 4 x 4 transfer matrices derive from the 3 x 3 transfer matrices, which follow from the 3 x 3 matrix for the general three-port. For both parallel and series connections, the 3 x 3 and 4 x 4 direct and inverse transfer matrices are interrelated through transformation symmetries; also, the inverse matrix can be obtained from the direct matrix by changing the sign of both the piezoelectric coefficient and the explicitly occurring complex variable, j. For the electrically parallel-connected case, explicit voltage orientation reversals occur at successive piezoelectric layers. Cascading the 4 x 4 matrices yields the sum of the currents through the piezoelectric layers for the electrically parallel-connected case and the sum of the voltage differences across the layers for the electrically series-connected case. The resultant matrices are calculated for the cascading of n identical piezoelectric layers connected in parallel and series. PMID:12243581
Optical properties of multilayer structures
Lebedev, M. S.; Ayupov, B. M.; Smirnova, T. P.
2009-01-01
The possibility of using the ellipsometry method for investigation of the optical properties of multilayer films and structures is shown. The optical properties of structures HfO2/SiO2/Si, HfO2/Si, ZrO2/Si, Ta2O5/Si, and Al2O3/Si are studied. It is found that a layer of hafnium silicate is formed at the interface between the HfO2 film and Si. Annealing of the structures in oxygen shows that oxides studied are oxygen-permeable and that the thickness of SiO2 at the film-substrate interface increases. The growth rate of SiO2 layers depends on the chemical nature of an oxide. Al2O3 films are impermeable for oxygen diffusion. The production of layers of alloys (Al2O3) x (HfO2)1 - x is optimized, which allows one to obtain layers with a homogeneous distribution of elements over the thickness.
Multilayer contactless dielectrophoresis: theoretical considerations.
Sano, Michael B; Salmanzadeh, Alireza; Davalos, Rafael V
2012-07-01
Dielectrophoresis (DEP), the movement of dielectric particles in a nonuniform electric field, is of particular interest due to its ability to manipulate particles based on their unique electrical properties. Contactless DEP (cDEP) is an extension of traditional and insulator-based DEP topologies. The devices consist of a sample channel and fluid electrode channels filled with a highly conductive media. A thin insulating membrane between the sample channel and the fluid electrode channels serves to isolate the sample from direct contact with metal electrodes. Here we investigate, for the first time, the properties of multilayer devices in which the sample and electrode channels occupy distinct layers. Simulations are conducted using commercially available finite element software and a less computationally demanding numerical approximation is presented and validated. We show that devices can be created that achieve a similar level of electrical performance to other cDEP devices presented in the literature while increasing fluid throughput. We conclude, based on these models, that the ultimate limiting factors in device performance resides in breakdown voltage of the barrier material and the ability to generate high-voltage, high-frequency signals. Finally, we demonstrate trapping of MDA-MB-231 breast cancer cells in a prototype device at a flow rate of 1.0 mL/h when 250 V(RMS) at 600 kHz is applied. PMID:22806458
Moisture in multilayer ceramic capacitors
Donahoe, Daniel Noel
When both precious metal electrode and base metal electrode (BME) capacitors were subjected to autoclave (120°C/100% RH) testing, it was found that the precious metal capacitors aged according to a well known aging mechanism (less than 3% from their starting values), but the BME capacitors degraded to below the -30% criterion at 500 hours of exposure. The reasons for this new failure mechanism are complex, and there were two theories that were hypothesized. The first was that there could be oxidation or corrosion of the nickel plates. The other hypothesis was that the loss of capacitance was due to molecular changes in the barium titanate. This thesis presents the evaluation of these hypotheses and the physics of the degradation mechanism. It is concluded by proof by elimination that there are molecular changes in the barium titanate. Furthermore, the continuous reduction in capacitor size makes the newer base metal electrode capacitors more vulnerable to moisture degradation than the older generation precious metal capacitors. In addition, standard humidity life testing, such as JESD-22 THB and HAST, will likely not uncover this problem. Therefore, poor reliability due to degradation of base metal electrode multilayer ceramic capacitors may catch manufacturers and consumers by surprise.
Recurrent priapism from therapeutic quetiapine.
Saghafi, Omeed; Kao, Amanda; Druck, Jeffrey
2014-02-01
Priapism is rarely related to use of non-erectile related medications. The objective was to educate about the multiple possible causes of priapism and to provide treatment recommendations for the different types of priapism. We present the case of a 43-year-old African American male with a history of schizoaffective disorder who presented to our emergency department multiple times over a three year period with priapism, each episode related to the ingestion of quetiapine. Following penile aspiration and intercavernosal injection of phenylephrine, this patient had resolution of his priapism. This case demonstrates an unusual case of recurrent priapism. PMID:24578777
MR imaging of recurrent medullary thyroid carcinoma
International Nuclear Information System (INIS)
This study used MR imaging for the evaluation of recurrent medulla thyroid carcinoma. A total of 38 MR images were obtained in 20 patients with elevated calcitonin levels to check for recurrent medullary thyroid carcinoma. Surgical follow-up was obtained in 11 patients. In eight of 11 cases, surgery confirmed recurrence detected on MR images. In one case, MR imaging failed to demonstrate metastatic mediastinal nodes seen at surgery. In the remaining two cases, surgery confirmed the MR finding of no recurrence. The other nine patients were followed with serial MR images for an average of 26 months postoperatively without evidence of recurrence. This preliminary study has indicate that MR imaging might be a useful alternative to routine surgical exploration in patients with possible recurrent medullary thyroid carcinoma
2013-06-04
Childhood Central Nervous System Germ Cell Tumor; Childhood Extragonadal Germ Cell Tumor; Childhood Hepatoblastoma; Childhood Hepatocellular Carcinoma; Childhood High-grade Cerebral Astrocytoma; Childhood Low-grade Cerebral Astrocytoma; Childhood Malignant Ovarian Germ Cell Tumor; Childhood Malignant Testicular Germ Cell Tumor; Childhood Teratoma; Recurrent Adrenocortical Carcinoma; Recurrent Childhood Brain Stem Glioma; Recurrent Childhood Cerebellar Astrocytoma; Recurrent Childhood Cerebral Astrocytoma; Recurrent Childhood Ependymoma; Recurrent Childhood Liver Cancer; Recurrent Childhood Malignant Germ Cell Tumor; Recurrent Childhood Rhabdomyosarcoma; Recurrent Childhood Soft Tissue Sarcoma; Recurrent Childhood Visual Pathway and Hypothalamic Glioma; Recurrent Colon Cancer; Recurrent Ewing Sarcoma/Peripheral Primitive Neuroectodermal Tumor; Recurrent Nasopharyngeal Cancer; Recurrent Neuroblastoma; Recurrent Osteosarcoma; Recurrent Rectal Cancer; Recurrent Renal Cell Cancer
Interpersonal mechanisms in recurrence of depression
Bos, Elisabeth Henrie?tte
2005-01-01
Depression is serious disease, also because of its recurrent nature. Many people who have become depressed once, will become depressed more often. Moreover, the risk of depression seems to increase with every further episode. These observations underline the importance of gaining a better understanding of the mechanisms behind recurrence of depression. The present multidisciplinary project investigates 5 different types of risk factors for recurrence of depression (factors from the fields of ...
High-resolution X-ray Multilayers
International Nuclear Information System (INIS)
Two new approaches are taken in multilayer fabrication to help bridge the gap in bandwidth between traditional multilayers (1 to 2%) and perfect crystals (0.01%). The first approach is based on creating many layers of low-contrast Al2O3/ B4C materials. The second approach is based on using multilayer structures with a small d-spacing using traditional W/B4C and Mo/B4C materials. With 8 keV x-rays on the Chess A2 beamline, we measured a bandwidth of 0.27% with a reflectivity of 40% and a Darwin width of 17 arc seconds from a 26 A d-spacing multilayer with 800 bi-layers of Al2O3/B4C using the low-contrast approach. On the other hand, the short period approach with a W/B4C multilayer and a 14.8 A d-spacing showed a resolution of 0.5 % and a reflectivity of 58.5%. Two more Mo/B4C samples with d-spacings of 15 A and 20 A showed energy resolutions of 0.25% and 0.52% with corresponding reflectivities of 39% and 66%. Thus we observe that both methods can produce useful x-ray optical components
Multilayer PVD coatings for wear protection
Energy Technology Data Exchange (ETDEWEB)
Holleck, H. [Forschungszentrum Karlsruhe GmbH Technik und Umwelt (Germany). Inst. fuer Materialforschung; Schier, V. [Forschungszentrum Karlsruhe GmbH Technik und Umwelt (Germany). Inst. fuer Materialforschung
1995-11-01
The PVD technology is well suited to realize new and advanced coating concepts like gradient coatings, metastable coatings, multicomponent coatings, multilayer or superlattice coatings. Among these coating concepts the multilayer coatings seem to be the most promising concept because it meets many requirements (e.g. multifunctional character, moderate residual stresses, good adherence to metallic substrates, proper hardness to toughness ratio and low friction coefficients) for a composite exposed to complex wear conditions. Further the concept allows metastable and multicomponent materials to be introduced in a graded multilayer arrangement. By this way different layer concepts can be realized simultaneously. A functional and a structural design, taking into account the material selection for the individual layers, the adjustment of the interface volume and constitution and the optimization of the individual layer sequence and thickness, allows a tailoring of properties and performance. Covalent or ionic materials like B{sub 4}C, SiC, Si{sub 3}N{sub 4} or Al{sub 2}O{sub 3} can be introduced as intermediate layers in the multilayer arrangement, raising hardness and high temperature strength without reducing adherence or toughness of the coating. New results concerning constitution, properties and application characteristics for multilayer coatings mainly based on TiC/TiN are presented. (orig.)
Recurrence and Relapse in Bipolar Mood Disorder
Directory of Open Access Journals (Sweden)
S Gh Mousavi
2004-06-01
Full Text Available Background: Despite the effectiveness of pharmacotherapy in acute phase of bipolar mood disorder, patients often experience relapses or recurrent episodes. Hospitalization of patients need a great deal of financial and humanistic resources which can be saved through understanding more about the rate of relapse and factors affecting this rate. Methods: In a descriptive analytical study, 380 patients with bipolar disorder who were hospitalized in psychiatric emergency ward of Noor hospital, Isfahan, Iran, were followed. Each patient was considered for; the frequency of relapse and recurrence, kind of pharmachotherapy, presence of psychotherapeutic treatments, frequency of visits by psychiatrist and the rank of present episode. Results: The overall prevalence of recurrence was 42.2%. Recurrence was lower in patients using lithium carbonate or sodium valproate or combined therapy (about 40%, compared to those using carbamazepine (80%. Recurrence was higher in patients treated with only pharmacotherapy (44.5% compared to those treated with both pharmacotherapy and psychotherapy (22.2%. Patients who were visited monthy by psychiatrist had lower rate of recurrence compared to those who had irregular visits. Conclusion: The higher rate of recurrence observed in carbamazepine therapy may be due to its adverse reactions and consequently poor compliance to this drug. Lower rates of recurrence with psychotherapy and regular visits may be related to the preventive effects of these procedures and especially to the effective management of stress. Keywords: Bipolar Mood Disorder, Recurrence, Relapse.
Radiotherapy for postoperative recurrent uterine cervical carcinoma
International Nuclear Information System (INIS)
From January 1980 to December 1985, a total of 110 patients with postoperative recurrent uterine cervical carcinoma were treated with radiotherapy. The mean age was 53 years. Ten patients were excluded due to incomplete treatment. The population was grouped according to the classification by Ciatto et al. into patients with central recurrence (n=48), with peripheral limited recurrence (n=43), and with peripheral massive recurrence (n=9). The midpelvic dose given to patients with central recurrence was 40 to 45 Gy, followed by a boost given either by perineal teletherapy with 30 Gy or brachytherapy with 30 Gy at 0.5 cm beneath the vaginal mucosa. For the peripheral group, the midpelvic dose was 50 Gy followed by a boost of 10 Gy through reduced portals. Further boost to the vaginal mucosa was given by either of the two methods mentioned above. The overall 5-year survival rate was 28%. In the group with central recurrence, it was 42% and in the group with peripheral recurrence 15%. Sixteen patients had persistent local tumor and 15 patients developed distant metastasis. Complications noted were proctitis (5%), cystitis (2%), vesicovaginal fistula (2%) and rectovaginal fistula (2%). Our data clearly indicate that radiotherapy was effective in controlling central recurrence, but for peripheral recurrence, control rate and prognosis were less favorable. (orig.)
Recurrent odontogenic keratocyst within the masticatory space
International Nuclear Information System (INIS)
The odontogenic keratocyst (OKC) is a developmental odontogenic cyst typically occurring in the jaws. Since the first description of OKC was published in 1956, the lesion has been of particular interest because of its specific histopathologic features, high recurrence rate, and aggressive behavior. Recurrences most commonly arise within bone at the site of the original cyst. However, as lining cells may find their way into surrounding tissues either from implantation during surgery or from cortical perforation recurrences may arise at a distance from the original cyst. Here, we report a rare case of recurrent OKC which was first developed in mandible and recurred within the masticatory space.
Ultrahydrophobicity of Polydimethylsiloxanes-Based Multilayered Thin Films
Hongyan Gao; Karen Xiaohe Xu; Bin Chen; Li-Zhu Wu; Chen-Ho Tung; Hai-Feng Ji
2009-01-01
The formation of polydimethylsiloxanes (PDMSs)-based layer-by-layer multilayer ultrathin films on charged surfaces prepared from water and phosphate buffer solutions has been investigated. The multilayer films prepared under these conditions showed different surface roughness. Nanoscale islands and network structures were observed homogeneously on the multilayer film prepared from pure water solutions, which is attributing to the ultrahydrobic property of the multilayer film. The formation of...
Interlayer exchange coupling in (Ga,Mn)As based multilayers
Giddings, A D; Gallagher, B L
2006-01-01
Exhibiting antiferromagnetic interlayer coupling in dilute magnetic semiconductor multilayers is essential for the realisation of magnetoresistances analogous to giant magnetoresistance in metallic multilayer structures. In this work we use a mean-field theory of carrier induced ferromagnetism to explore possible (Ga,Mn)As based multilayer structures that might yield antiferromagnetic coupling.
EUV Polarimetry with single multilayer optical element
Zuccon, Sara; Pelizzo, Maria-Guglielmina; Nicolosi, P.; Giglia, A.; Mahne, N.; Nannarone, S.
2008-08-01
A polarimetric measurement technique based on the analysis of the reflection data given by a single mirror rotated around the incidence beam axis is presented. In the extreme ultraviolet spectral region, a multilayer coated mirror must be used. The multilayer mirror must be fully characterized before the experiment. Theory demonstrates how this method allows complete determination of Stoke's parameters in case of a totally polarized beam. A simulation code has been developed in order to model the experiment in case of synchrotron radiation propagating in a bending magnet beamline and impinging a multilayer mirror. The simulation is useful to verify each time the effectiveness of the method in the different experimental conditions considered. Finally an experimental application is presented.
Long Range Surface Plasmons in Multilayer Structures
Delfan, Aida
2013-01-01
We present a new strategy, based on a Fresnel coefficient pole analysis, for designing an asymmetric multilayer structure that supports long range surface plasmons (LRSP). We find that the electric field intensity in the metal layer of a multilayer LRSP structure can be even slightly smaller than in the metal layer of the corresponding symmetric LRSP structure, minimizing absorption losses and resulting in LRSP propagation lengths up to 2mm. With a view towards biosensing applications, we also present semi-analytic expressions for a standard surface sensing parameter in arbitrary planar resonant structures, and in particular show that for an asymmetric structure consisting of a gold film deposited on a multilayer of SiO2 and TiO2 a surface sensing parameter G = 1.28(1/nm) can be achieved.
Multilayer neural networks a generalized net perspective
Krawczak, Maciej
2013-01-01
The primary purpose of this book is to show that a multilayer neural network can be considered as a multistage system, and then that the learning of this class of neural networks can be treated as a special sort of the optimal control problem. In this way, the optimal control problem methodology, like dynamic programming, with modifications, can yield a new class of learning algorithms for multilayer neural networks. Another purpose of this book is to show that the generalized net theory can be successfully used as a new description of multilayer neural networks. Several generalized net descriptions of neural networks functioning processes are considered, namely: the simulation process of networks, a system of neural networks and the learning algorithms developed in this book. The generalized net approach to modelling of real systems may be used successfully for the description of a variety of technological and intellectual problems, it can be used not only for representing the parallel functioning of homogen...
Magnetic studies of Fe/Cu multilayers
International Nuclear Information System (INIS)
The structural and magnetic properties of sputtered Fe/Cu multilayers are examined as a function of Fe layer thickness tFe by means of X-ray diffraction, Moessbauer spectrometry and superconducting quantum interference magnetometer. The temperature dependence of the spontaneous magnetization M(T) is well described by a T3/2 law in all multilayers in the temperature range 5-300 K. The interface anisotropy constant of Fe/Cu multilayers, Ks, is found to be 0.31 and 0.45 erg/cm2 at 5 and 300 K, respectively. A spin-wave theory has been used to explain the temperature dependence of the magnetization and the approximate values for the bulk exchange interaction Jb, surface exchange interaction Js and the interlayer coupling strength JI for various Fe layer thicknesses have been obtained
Multilayer fuel assemblies for SCWR reactor cores
International Nuclear Information System (INIS)
In this paper, a new type of fuel assembly - multilayer fuel assembly is proposed with the main purpose to reduce the hot channel factor. The main idea is to axially divide the active zone into several sub-layers, between which inactive layers are introduced, where fluid from the previous active layer mixes well with each other and enters the next active layer with a wall homogenous distribution of fluid temperature. A coupled method using 3-D neutron-physical code and sub-channel analysis code is applied to assess the performance of the multi-layer FAs. Computational Fluid-Dynamics (CFD) method is used to study the fluid mixing behavior in the mixing layer. The preliminary results show promising feasibility of the multi-layer concepts and emphasize at the same time the necessity of further detailed studies. (author)
Evolutionary games on multilayer networks: A colloquium
Wang, Zhen; Szolnoki, Attila; Perc, Matjaz
2015-01-01
Networks form the backbone of many complex systems, ranging from the Internet to human societies. Accordingly, not only is the range of our interactions limited and thus best described and modeled by networks, it is also a fact that the networks that are an integral part of such models are often interdependent or even interconnected. Networks of networks or multilayer networks are therefore a more apt description of social systems. This colloquium is devoted to evolutionary games on multilayer networks, and in particular to the evolution of cooperation as one of the main pillars of modern human societies. We first give an overview of the most significant conceptual differences between single-layer and multilayer networks, and we provide basic definitions and a classification of the most commonly used terms. Subsequently, we review fascinating and counterintuitive evolutionary outcomes that emerge due to different types of interdependencies between otherwise independent populations. The focus is on coupling th...
Treatment of locally recurrent rectal cancer
International Nuclear Information System (INIS)
The suggested classifications of locally recurrent rectal cancer are based on the presence of symptoms and the degree of tumour fixation to the pelvic wall, or, otherwise, account for factor T in the TMN system. Although the results of rectal cancer treatment have improved, which may be attributed to total meso rectal excision and application of perioperative radiotherapy and radiochemotherapy, the ratio of cases of locally recurrent rectal cancer still amount from several to over a dozen percent. Among the available diagnostic methods for detecting locally recurrent rectal cancer after anterior rectal resection, endorectal sonography is of special importance. In the estimation of prognostic factors the lack of vascular invasion in recurrent cancer and the long period between the treatment of primary rectal cancer and the development of recurrence are a sign of good prognosis, while pain prior to recurrence treatment and male sex diminish the chances for cure. Locally recurrent rectal cancer impairs the patient's quality of life in all measurable aspects, but even after complete recovery we observe severe disturbances of sexual activity in most patients, and a number of patients require hygiene pads or suffer from chronic pain. Local recurrence of rectal cancer is more commonly qualified for excision after surgical treatment only, than after preoperative radiotherapy. The probability of total recurrent rectal cancer excision increases when the patient is younger, the ncreases when the patient is younger, the primary tumours was less advanced and the first operation was sphincter-sparing surgery. Progress in the surgical treatment of recurrent rectal cancer was brought on by the introduction of the composite musculocutaneous flap to compensate the loss of perineal tissue. The application of intraoperative radiotherapy improves treatment results of recurrent rectal cancer, however at the cost of more frequent, serious postoperative complications and intense pain. In inoperable cases high dose regional chemotherapy accounts for some 30% of responses which last for several months. After RO resections of locally recurrent rectal cancer combined with intraoperative radiotherapy and chemotherapy 5-year survival periods are obtained in approx. 35 % of cases. If complete response (pTO) is observed within the excised tissues after preoperative radio- or chemotherapy the likelihood of curability is significantly higher. Recurrence after local excision or electrocoagulation of rectal cancer can be efficiently treated with abdomino-perneal resection. According to various sources, perioperative mortality in patients with locally recurrent rectal cancer ranges from null to 30%. Local recurrence of rectal cancer should be treated in well equipped institutions with a high reference status.(author)
Current management options for recurrent adrenocortical carcinoma
Directory of Open Access Journals (Sweden)
Glover AR
2013-06-01
Full Text Available Anthony R Glover,1 Julian C Y Ip,1 Jing Ting Zhao,1 Patsy S H Soon,1,4 Bruce G Robinson,1,3 Stan B Sidhu1,2 1Kolling Institute of Medical Research, Cancer Genetics Laboratory, 2Endocrine Surgical Unit, 3Department of Endocrinology, Royal North Shore Hospital and University of Sydney, St Leonards, 4Department of Surgery, Bankstown Hospital and University of New South Wales, Bankstown, NSW, Australia Abstract: Adrenal cortical carcinoma (ACC is a rare cancer that poses a number of management challenges due to the limited number of effective systemic treatments. Complete surgical resection offers the best chance of long-term survival. However, despite complete resection, ACC is associated with high recurrence rates. This review will discuss the management of recurrent ACC in adults following complete surgical resection. Management should take place in a specialist center and treatment decisions must consider the individual tumor biology of each case of recurrence. Given the fact that ACC commonly recurs, management to prevent recurrence should be considered from initial diagnosis with the use of adjuvant mitotane. Close follow up with clinical examination and imaging is important for early detection of recurrent disease. Locoregional recurrence may be isolated, and repeat surgical resection should be considered along with mitotane. The use of radiotherapy in ACC remains controversial. Systemic recurrence most often involves liver, pulmonary, and bone metastasis and is usually managed with mitotane, with or without combination chemotherapy. There is a limited role for surgical resection in systemic recurrence in selected patients. In all patients with recurrent disease, control of excessive hormone production is an important part of management. Despite intensive management of recurrent ACC, treatment failure is common and the use of clinical trials and novel treatment is an important part of management. Keywords: recurrence, surgery, chemotherapy, mitotane, treatment
Chemoradiotherapy response in recurrent rectal cancer
International Nuclear Information System (INIS)
The efficacy of response to preoperative chemoradiotherapy (CRT) in recurrent versus primary rectal cancer has not been investigated. We compared radiological downsizing between primary and recurrent rectal cancers following CRT and determined the optimal size reduction threshold for response validated by survival outcomes. The proportional change in tumor length for primary and recurrent rectal cancers following CRT was compared using the independent sample t-test. Overall survival (OS) was calculated using the Kaplan–Meier product limit method and differences between survival for tumor size reduction thresholds of 30% (response evaluation criteria in solid tumors [RECIST]), 40%, and 50% after CRT in primary and recurrent rectal cancer groups. A total of 385 patients undergoing CRT were analyzed, 99 with recurrent rectal cancer and 286 with primary rectal cancer. The mean proportional reduction in maximum craniocaudal length was significantly higher for primary rectal tumors (33%) compared with recurrent rectal cancer (11%) (P < 0.01). There was no difference in OS for either primary or recurrent rectal cancer when ?30% or ?40% definitions were used. However, for both primary and recurrent tumors, significant differences in median 3-year OS were observed when a RECIST cut-off of 50% was used. OS was 99% versus 77% in primary and 100% versus 42% in recurrent rectal cancer (P = 0.002 and P = 0.03, respectively). Only patients that demonstrated >50% size reduction showed a survival benefit. Recurrent rectal cancer appears radioresistant compared with primary tumors for tumor size after CRT. Further investigation into improving/intensifying chemotherapy and radiotherapy for locally recurrent rectal cancer is justified
Synthesis and electrical conductivity of multilayer silicene
Energy Technology Data Exchange (ETDEWEB)
Vogt, P., E-mail: patrick.vogt@tu-berlin.de, E-mail: bruno.grandidier@isen.iemn.univ-lille1.fr; Bruhn, T. [Technische Universität Berlin, Hardenbergstraße 36, 10623 Berlin (Germany); Capiod, P.; Berthe, M.; Grandidier, B., E-mail: patrick.vogt@tu-berlin.de, E-mail: bruno.grandidier@isen.iemn.univ-lille1.fr [Institut d' Electronique, de Microélectronique et de Nanotechnologies (IEMN), CNRS, UMR 8520 Département ISEN, 41 bd Vauban, 59046 Lille Cedex (France); Resta, A. [Aix-Marseille University, CNRS-CINaM, Campus de Luminy, Case 913, F-13288 Marseille Cedex 09 (France); De Padova, P. [Instituto di Struttura della Materia, Consiglio Nazionale delle Ricerche - ISM, via Fosso del Cavaliere, 00133 Roma (Italy); Le Lay, G. [Aix-Marseille University, CNRS-CINaM, Campus de Luminy, Case 913, F-13288 Marseille Cedex 09 (France); Instituto di Struttura della Materia, Consiglio Nazionale delle Ricerche - ISM, via Fosso del Cavaliere, 00133 Roma (Italy)
2014-01-13
The epitaxial growth and the electrical resistance of multilayer silicene on the Ag(111) surface has been investigated. We show that the atomic structure of the first silicene layer differs from the next layers and that the adsorption of Si induces the formation of extended silicene terraces surrounded by step bunching. Thanks to the controlled contact formation between the tips of a multiple probe scanning tunneling microscope and these extended terraces, a low sheet resistance, albeit much higher than the electrical resistance of the underlying silver substrate, has been measured, advocating for the electrical viability of multilayer silicene.
Magnetic multilayers : fundamental and practical aspects
Krishnan, R.
1992-01-01
After a brief introduction we describe the preparation of the multilayers by evaporation under ultra high vacuum conditions and their characterisation. We then discuss the magnetic and magneto-optical properties of some multilayer systems such as, Ni/Ag, Fe/Ag, Co/Ag and Co/Pt. The last one is quite interesting and is a potential candidate for magneto-optical information storage, particularly capable of working in the shorter wave length of light. We describe particularly the various anisotro...
Exchange interactions in Fe/Y multilayers
International Nuclear Information System (INIS)
The magnetization of Fe/Y multilayers has been measured as a function of temperature. A bulk-like T 3/2 temperature dependence of the magnetization is observed for all multilayers in the temperature range 5-300 K. The spin-wave constant B is found to decrease inversely with t Fe. A simple theoretical model with exchange interactions only, and with non-interacting magnons, has been used to explain the temperature dependence of the magnetization and the approximate values for the bulk exchange interaction J b, surface exchange interaction J s and the interlayer exchange interaction J I for various Fe layer thicknesses have been obtained
Reverse engineering of multi-layer films
Directory of Open Access Journals (Sweden)
Effendi Widjaja
2011-03-01
Full Text Available This contribution introduces the combined application of Raman microscopy and band-target entropy minimization (BTEM in order to successfully reverse-engineer a multi-layer packaging material. Three layers are identified, namely, polyethylene, a paper and talc layer (with two distinct cellulose forms, and a poly-styrene co-polymer composite containing anatase and calcite. This rapid and non-destructive approach provides a unique opportunity for the assessment of multi-layer composites, including the constitution of the additives present.
Multilayer recording in microholographic data storage
International Nuclear Information System (INIS)
The potential of multilayer recording in microholographic data storage is investigated. Micrometer-scaled depth localization of resolution-limited microgratings is achieved in photopolymers sensitized to green and violet light. Confocal readout results in an optical depth of approximately 2 ?m. The spatial Bragg selectivity of resolution-limited micrograting structures allows reducing their longitudinal depth spacing down to 4 ?m. Multilayer recording is demonstrated as depth multiplexing of microgratings written in 50 layer locations within a 300 ?m thick photopolymer. (fast track communication)
Physical and chemical characterization of multilayered structures
International Nuclear Information System (INIS)
It is important to know the physical and chemical properties of a multilayer if its performance is to be compared to theoretical predictions, or if guidance is needed for the production of superior multilayers. Accurate, nondestructive analytical methods, such as neutron activation analysis, are restricted to certain elements. Certain destructive methods, such as total carbon analysis by combustion, can be sensitive enough for use with very small samples. The method of choice depends upon sensitivity and specificity, both of which are discussed in this paper. 6 refs., 3 figs., 2 tabs
Synthesis and electrical conductivity of multilayer silicene
International Nuclear Information System (INIS)
The epitaxial growth and the electrical resistance of multilayer silicene on the Ag(111) surface has been investigated. We show that the atomic structure of the first silicene layer differs from the next layers and that the adsorption of Si induces the formation of extended silicene terraces surrounded by step bunching. Thanks to the controlled contact formation between the tips of a multiple probe scanning tunneling microscope and these extended terraces, a low sheet resistance, albeit much higher than the electrical resistance of the underlying silver substrate, has been measured, advocating for the electrical viability of multilayer silicene
2015-06-12
Endometrial Clear Cell Adenocarcinoma; Estrogen Receptor Negative; Ovarian Clear Cell Cystadenocarcinoma; Recurrent Fallopian Tube Carcinoma; Recurrent Ovarian Carcinoma; Recurrent Primary Peritoneal Carcinoma; Recurrent Uterine Corpus Carcinoma
Energy Technology Data Exchange (ETDEWEB)
Caujolle, Jean-Pierre, E-mail: ncaujolle@aol.com [Department of Ophthalmology, Saint Roch Hospital, Nice Teaching Hospital, Nice (France); Paoli, Vincent [Department of Ophthalmology, Saint Roch Hospital, Nice Teaching Hospital, Nice (France); Chamorey, Emmanuel [Department of Radiation Oncology, Protontherapy Center, Centre Antoine Lacassagne, Nice (France); Department of Biostatistics and Epidemiology, Centre Antoine Lacassagne, Nice (France); Maschi, Celia; Baillif, Stéphanie [Department of Ophthalmology, Saint Roch Hospital, Nice Teaching Hospital, Nice (France); Herault, Joël [Department of Radiation Oncology, Protontherapy Center, Centre Antoine Lacassagne, Nice (France); Gastaud, Pierre [Department of Ophthalmology, Saint Roch Hospital, Nice Teaching Hospital, Nice (France); Hannoun-Levi, Jean Michel [Department of Radiation Oncology, Protontherapy Center, Centre Antoine Lacassagne, Nice (France)
2013-04-01
Purpose: To study the prognosis of the different types of uveal melanoma recurrences treated by proton beam therapy (PBT). Methods and Materials: This retrospective study analyzed 61 cases of uveal melanoma local recurrences on a total of 1102 patients treated by PBT between June 1991 and December 2010. Survival rates have been determined by using Kaplan-Meier curves. Prognostic factors have been evaluated by using log-rank test or Cox model. Results: Our local recurrence rate was 6.1% at 5 years. These recurrences were divided into 25 patients with marginal recurrences, 18 global recurrences, 12 distant recurrences, and 6 extrascleral extensions. Five factors have been identified as statistically significant risk factors of local recurrence in the univariate analysis: large tumoral diameter, small tumoral volume, low ratio of tumoral volume over eyeball volume, iris root involvement, and safety margin inferior to 1 mm. In the local recurrence-free population, the overall survival rate was 68.7% at 10 years and the specific survival rate was 83.6% at 10 years. In the local recurrence population, the overall survival rate was 43.1% at 10 years and the specific survival rate was 55% at 10 years. The multivariate analysis of death risk factors has shown a better prognosis for marginal recurrences. Conclusion: Survival rate of marginal recurrences is superior to that of the other recurrences. The type of recurrence is a clinical prognostic value to take into account. The influence of local recurrence retreatment by proton beam therapy should be evaluated by novel studies.
International Nuclear Information System (INIS)
Purpose: To study the prognosis of the different types of uveal melanoma recurrences treated by proton beam therapy (PBT). Methods and Materials: This retrospective study analyzed 61 cases of uveal melanoma local recurrences on a total of 1102 patients treated by PBT between June 1991 and December 2010. Survival rates have been determined by using Kaplan-Meier curves. Prognostic factors have been evaluated by using log-rank test or Cox model. Results: Our local recurrence rate was 6.1% at 5 years. These recurrences were divided into 25 patients with marginal recurrences, 18 global recurrences, 12 distant recurrences, and 6 extrascleral extensions. Five factors have been identified as statistically significant risk factors of local recurrence in the univariate analysis: large tumoral diameter, small tumoral volume, low ratio of tumoral volume over eyeball volume, iris root involvement, and safety margin inferior to 1 mm. In the local recurrence-free population, the overall survival rate was 68.7% at 10 years and the specific survival rate was 83.6% at 10 years. In the local recurrence population, the overall survival rate was 43.1% at 10 years and the specific survival rate was 55% at 10 years. The multivariate analysis of death risk factors has shown a better prognosis for marginal recurrences. Conclusion: Survival rate of marginal recurrences is superior to that of the other recurrences. The type of recurrence is a clinical prognostic value to take into account. The influence of local recurrence retreatment by proton beam therapy should be evaluated by novel studies
Alternative therapy for recurrent Hodgkin's disease
International Nuclear Information System (INIS)
Eleven patients with recurrent Hodgkin's disease have returned to apparent normality after simple treatment regimes with radiotherapy and hyperthermia from 434 MHz electromagnetic radiation. None have experienced any complication or sequelae from this treatment. All the patients with recurrent active Hodgkin's disease who attended the author's practice since February 1976 have been treated with this combined treatment and are reported here. (author)
Decomposable spaces of recurrent conformal curvature
International Nuclear Information System (INIS)
Definitions of a decomposable space, decomposition spaces and a space of recurrent conformal curvature are given. A decomposable space of recurrent conformal curvature Vn, (shortly CKn) is looked upon as decomposition spaces Vr and Vn-r. With this concept some results on decomposable CKn are derived. (author). 5 refs
On Large Deviation Property of Recurrence Times
Jain, Siddharth; Bansal, Rakesh Kumar
2013-01-01
We extend the study by Ornstein and Weiss on the asymptotic behavior of the normalized version of recurrence times and establish the large deviation property for a certain class of mixing processes. Further, an estimator for entropy based on recurrence times is proposed for which large deviation behavior is proved for stationary and ergodic sources satisfying similar mixing conditions.
Late breast recurrence after lumpectomy and irradiation
Energy Technology Data Exchange (ETDEWEB)
Kurtz, J.M. (Swedish Hospital Tumor Inst., Seattle, WA); Spitalier, J.M.; Amalric, R.
1983-08-01
For 276 patients with early breast cancer followed from 10 to 21 years after lumpectomy and radiotherapy, the recurrence rate in the treated breast was 15.6%, and 7.2% developed contralateral breast cancer. Only 63% of breast recurrences occurred within 5 years, and the remainder were late failures, with 5 of the 43 recurrences observed after 10 years. The proportion of failures occurring late was greater for T/sub 1/ than for T/sub 2/ tumors (53% vs 25%). Twenty-six percent of early recurrences were inoperable, and an adverse impact of early recurrence on 10-year survival was clearly demonstrable. Late recurrences were all operable and did not appear to be associated with decreased survival. Only 16 of the 36 patients (44%) with operable breast recurrence ever developed metastatic disease, and 5 year survival following salvage therapy was 62%. Although the treated breast remains at continuous cancer risk even beyond 5 years, the prognosis of late recurrence appears quite similar to that of contralateral breast cancer.
Late breast recurrence after lumpectomy and irradiation
International Nuclear Information System (INIS)
For 276 patients with early breast cancer followed from 10 to 21 years after lumpectomy and radiotherapy, the recurrence rate in the treated breast was 15.6%, and 7.2% developed contralateral breast cancer. Only 63% of breast recurrences occurred within 5 years, and the remainder were late failures, with 5 of the 43 recurrences observed after 10 years. The proportion of failures occurring late was greater for T1 than for T2 tumors (53% vs 25%). Twenty-six percent of early recurrences were inoperable, and an adverse impact of early recurrence on 10-year survival was clearly demonstrable. Late recurrences were all operable and did not appear to be associated with decreased survival. Only 16 of the 36 patients (44%) with operable breast recurrence ever developed metastatic disease, and 5 year survival following salvage therapy was 62%. Although the treated breast remains at continuous cancer risk even beyond 5 years, the prognosis of late recurrence appears quite similar to that of contralateral breast cancer
A case of seven recurrent ectopic pregnancies.
Faiz, Shakeel A.; Sporrong, Bengt G.; Al-meshari, Abdulaziz A.
2003-01-01
ABSTRACT If a woman with previous ectopic pregnancy ever gets pregnant again, the risk of a repeat ectopic pregnancy is said to be 4-fold. We present a rare case of 7 recurrent ectopic pregnancies in a 39-year-old Saudi woman, together with a literature review of the reproductive performance after recurrent ectopic pregnancy.
Lesson learned from (some) recurrent novae
Mason, Elena; Walters, Frederick M.
2013-01-01
In this talk we present early decline and nebular spectra of the recurrent novae YY Dor and nova LMC 2009. These and a few other recurrent novae of the same type, share similar spectral characteristics and evolution. We will critically discuss those common features suggesting same white dwarf progenitor and post outburst phases for all of them.
Atypical recurrence of rheumatic chorea
Directory of Open Access Journals (Sweden)
Gunjan Pankaj Kumar
2015-05-01
Full Text Available Syndenhams Chorea in acute rheumatic fever is reported to occur in 20-30% of patients. It is usually late onset, occurring upto 6 months after acute infection but may occasionally be present as presenting symptom of rheumatic fever. It is a self-limiting condition with spontaneous remission lasting from 1 week to 6 months. The risk of recurrence is present in 1st 1-2 years in about 20% of cases. Most of children (two thirds with rheumatic fever are of school age (5-15 years of age. It is common in India and the incidence has not shown the declining trends seen in the developing countries. We report the clinical findings, investigations and the course of clinical development of a 14-year-old girl, who presented with Rheumatic chorea which recurred 3 years after the initial episode. [Int J Res Med Sci 2015; 3(5.000: 1272-1273
Poincare recurrences and topological diversity
International Nuclear Information System (INIS)
Finite entropy thermal systems undergo Poincare recurrences. In the context of field theory, this implies that at finite temperature, timelike two-point functions will be quasi-periodic. In this note we attempt to reproduce this behavior using the AdS/CFT correspondence by studying the correlator of a massive scalar field in the bulk. We evaluate the correlator by summing over all the SL(2,Z) images of the BTZ spacetime. We show that all the terms in this sum receive large corrections after at certain critical time, and that the result, even if convergent, is not quasi-periodic. We present several arguments indicating that the periodicity will be very difficult to recover without an exact re-summation, and discuss several toy models which illustrate this. Finally, we consider the consequences for the information paradox. (author)
International Nuclear Information System (INIS)
Highlights: ? A method is presented to improve power system stability using IPFC. ? Recurrent neural network controllers damp oscillations in a power system. ? Training is based on back propagation with adaptive training parameters. ? Selection of effectiveness damping control signal carried out using SVD method. -- Abstract: This paper presents a method to improve power system stability using IPFC based damping online learning recurrent neural network controllers for damping oscillations in a power system. Parameters of equipped controllers for enhancing dynamical stability at the IPFC are tuned using mathematical methods. Therefore these control parameters are often fixed and are set for particular system configurations or operating points. Multilayer recurrent neural network, which can be tuned for changing system conditions, is used in this paper for effectively damp the oscillations. Training is based on back propagation with adaptive training parameters. This controller is tested to variations in system loading and fault in the power system and its performance is compared with performance of a controller that the phase compensation method is used to set its parameters. Selection of effectiveness damping control signal for the design of robust IPFC damping controller carried out through singular value decomposition (SVD) method. Simulation studies show the superior robustness and stabilizing effect of the proposed controller in comparison with phase compeler in comparison with phase compensation method.
Endoscopic Therapy for Chronic Recurrent Pancreatitis
Directory of Open Access Journals (Sweden)
Yoshiaki Kawaguchi
2012-12-01
Full Text Available Chronic recurrent pancreatitis develops as a result of pancreaticoutflow disturbance associated with pancreatic duct stenosis orpancreatic stones in most cases. Therefore it is rational to reduceintrapancreatic ductal pressure by removing pancreatic outflowdisturbance for treatment of chronic recurrent pancreatitis. Surgicalprocedures and endoscopic pancreatic stenting are available fordecompression of the pancreatic duct. As endoscopic pancreaticstenting is less invasive, safe and effective method, this approachhas spread rapidly. Comorbid pancreatic cancer should never beoverlooked before stenting for chronic recurrent pancreatitis, becausechronic recurrent pancreatitis carries a high risk of progressingto pancreatic cancer. In cases with a stone in the pancreatic duct,extracorporeal shock wave lithotripsy (ESWL should be performedin combination with endoscopic pancreatic stenting. In this reviewwe discuss the current status of endoscopic pancreatic stenting in thetreatment of chronic recurrent pancreatitis.
Thermal Transport in Graphene and Graphene Multilayers
Balandin, Alexander A.; Nika, Denis L.
2015-01-01
In this paper we review thermal properties of graphene and multilayer graphene and discuss the optothermal technique developed for the thermal conductivity measurements. We also outline different theoretical approaches used for the description of phonon transport in graphene and provide comparison with available experimental thermal conductivity data.
Optical and structural study of BST multilayers.
Czech Academy of Sciences Publication Activity Database
Železný, Vladimír; Chvostová, Dagmar; Pajasová, Libuše; Jelínek, Miroslav; Kocourek, Tomáš; Daniš, S.; Valvoda, V.
2010-01-01
Ro?. 12, ?. 3 (2010), 538-541. ISSN 1454-4164 R&D Projects: GA ?R GA202/07/0591 Institutional research plan: CEZ:AV0Z10100522; CEZ:AV0Z10100520 Keywords : ellipsometry * structure * ferroelectric multilayers Subject RIV: BH - Optics, Masers, Lasers Impact factor: 0.412, year: 2010
Thermal mixing of Al-Fe multilayers
International Nuclear Information System (INIS)
Al-Fe multilayers have been mixed by thermal treatment and their evolution followed by conversion electron Moessbauer spectroscopy. The initial and final states have been characterized by Rutherford backscattering spectrometry. The results are compared with those previously obtained in the ion beam mixing of similar systems. (orig.)
Analysis of Fracture Behaviour of Multilayer Pipes.
Czech Academy of Sciences Publication Activity Database
Nezbedová, E.; Knésl, Zden?k; Vlach, B.
2007-01-01
Ro?. 36, ?. 5 (2007), s. 207-212. ISSN 1465-8011. [Plastic Pipes /13./. Washington , D. C., 02.10.2006-05.10.2006] R&D Projects: GA ?R GA106/07/1284 Institutional research plan: CEZ:AV0Z20410507 Keywords : multi-layer pipes Subject RIV: JL - Materials Fatigue, Friction Mechanics Impact factor: 0.431, year: 2007
EduXs: Multilayer Educational Services Platforms
Chang, Li-Jie; Yang, Jie-Chi; Deng, Yi-Chan; Chan, Tak-Wai
2003-01-01
How to use the online social learning communities to improve quality and quantity of interactions in physical social learning communities is an important issue. This work describes the design and implementation of multilayer educational services platforms that enable learners to establish their own online social learning communities and integrate…
Diffraction Gratings Based on Multilayer Structures
International Science & Technology Center (ISTC)
Development of High Efficiency Diffraction Gratings on the Basis of Multilayer Structures for Monochromators and Polychromators of X-Ray Synchrotron Radiation and for Ultra-High Spectral Resolution X-Ray Diagnostics in the 0.1 – 10 Kev Energy Range
Transmission fingerprints in quasiperiodic magnonic multilayers
International Nuclear Information System (INIS)
In this paper we investigated the influence of mirror symmetry on the transmission spectra of quasiperiodic magnonic multilayers arranged according to Fibonacci, Thue-Morse and double period quasiperiodic sequences. We consider that the multilayers composed of two simple cubic Heisenberg ferromagnets with bulk exchange constants JA and JB and spin quantum numbers SA and SB, respectively. The multilayer structure is surrounded by two semi-infinite slabs of a third Heisenberg ferromagnetic material with exchange constant JC and spin quantum number SC. For simplicity, the lattice constant has the same value a in each material, corresponding to epitaxial growth at the interfaces. The transfer matrix treatment was used for the exchange-dominated regime, taking into account the random phase approximation (RPA). Our numerical results illustrate the effects of mirror symmetry on (i) transmission spectra and (ii) transmission fingerprints. - Highlights: ? We model quasiperiodic magnetic multilayers presenting mirror symmetry. ? We investigated the allowed and forbidden bands of magnonic transmission. ? Transmission return maps show the influence of mirror symmetry. ? Mirror symmetry has no effect on the Fibonacci case. ? Mirror symmetry does have effect on the Thue-Morse and double period cases.
Multi-layer film neutron interferometers
International Nuclear Information System (INIS)
Since the first success by H. Rauch et al. using a silicon complete crystal, neutron interferometers have been utilized for the research on the basic physics of neutrons and the precision measurement of neutron refractive index, and the spectacular results have been obtained. Also for the verification on neutron waves of Berry phase, it is expected to become a powerful weapon. However in the interferometers of silicon single crystals, the applicable neutron wavelength is limited to below 6A, and there are the problems of dimensional restraint and others. Recently in USSR, by utilizing the diffraction grating arranged regularly on a glass surface, the interferometer which can be applied to long wavelength neutrons was successfully developed. The authors have developed various multi-layer film neutron mirrors which utilize the Bragg's reflection, and can make the mirrors with arbitrary reflectivity. The multi-layer film neutron interferometers are those of Mach-Zehnder type similar to silicon interferometers, and are composed of a half mirror as the beam splitter, two reflection mirrors and a half mirror for phase analysis. For the purpose of verifying that multi-layer film neutron interferometers can be manufactured, the authors developed that with neutron wavelength of 22A using Ni-Ti multi-layer film. Its principle, the problems in the manufacture, the features and the application to physical experimental are reported. (K.I.)
Growth and structure of metallic multilayer system
International Nuclear Information System (INIS)
The multichamber ultrahigh vacuum system which has been built for surface and interface studies in thin magnetic films in the Institute of Nuclear Physics in Cracow has been performed. The design and performance of this setup, together with a description of other analytical techniques used for studying the structural and magnetotransport properties of thin multilayered systems has been presented
Inguinal hernia recurrence: Classification and approach
Directory of Open Access Journals (Sweden)
Campanelli Giampiero
2006-01-01
Full Text Available The authors reviewed the records of 2,468 operations of groin hernia in 2,350 patients, including 277 recurrent hernias updated to January 2005. The data obtained - evaluating technique, results and complications - were used to propose a simple anatomo-clinical classification into three types which could be used to plan the surgical strategy:Type R1: first recurrence ?high,? oblique external, reducible hernia with small (< 2 cm defect in non-obese patients, after pure tissue or mesh repairType R2: first recurrence ?low,? direct, reducible hernia with small (< 2 cm defect in non-obese patients, after pure tissue or mesh repairType R3: all the other recurrences - including femoral recurrences; recurrent groin hernia with big defect (inguinal eventration; multirecurrent hernias; nonreducible, linked with a controlateral primitive or recurrent hernia; and situations compromised from aggravating factors (for example obesity or anyway not easily included in R1 or R2, after pure tissue or mesh repair.
Generalised Recurrence Plot Analysis for Spatial Data
Marwan, N; Saparin, P; Marwan, Norbert; Kurths, Juergen; Saparin, Peter
2006-01-01
Recurrence plot based methods are highly efficient and widely accepted tools for the investigation of time series or one-dimensional data. We present an extension of the recurrence plots and their quantifications in order to study recurrent structures in higher-dimensional spatial data. The capability of this extension is illustrated on prototypical 2D models. Next, the tested and proved approach is applied to assess the bone structure from CT images of human proximal tibia. We find that the spatial structures in trabecular bone become more self-similar during the bone loss in osteoporosis.
Recurrences of transient synovitis of the hip.
Illingworth, C. M.
1983-01-01
Thirty six children with transient synovitis of the hip had a total of 80 recurrences, 69 of them personally observed, and 11 described by the mother. No features distinguished the initial attack of those who had a recurrence from that of the 18 children who have not so far had a recurrence. We analysed the total of 126 episodes. In 72 there was evidence of an associated infection from the history, clinical signs, and a raised antistreptolysin O titre or isolation of a pathogen from a throat ...
What Is an Earthquake?: Recurrence Interval
This activity consists of two exercises on determining recurrence interval; one, a hypothetical example, and the other, using real data from the San Andreas Fault. They provide the learner with a good idea of how valuable the concept can be in assessing earthquake hazards, and of a few of the problems associated with determining and correctly applying recurrence intervals in fault studies. The learner is familiarized with the concept of recurrence interval, and several different ways to determine this value for a given fault. There is also a graphing exercise that looks at real-world data from studies made on the San Andreas fault.
Treatment of Recurrent Ovarian Cancer.
Directory of Open Access Journals (Sweden)
Neville F. Hacker
2004-08-01
Full Text Available Recurrent ovarian cancer is a common clinical problem and the management of eachpatient must be individualized. Diagnosis is usually based on a progressively rising CA-125titre, and a CT scan of the pelvis and abdomen, together with a chest X-ray should be performed.Although there is no study to support immediate treatment in the asymptomaticpatient, our approach is to commence such patients on Tamoxifen. Chemotherapy isreserved for asymptomatic patients or those who progress on Tamoxifen. The longer thetreatment-free interval of 18-24 months. The choice of non-platinum second or subsequentline chemotherapy is based on many factors including likelihood of benefit, potential toxicity,schedule and convenience to the patient, as well as organ function and residual toxicityfrom prior treatment. Aggressive secondary cytoreductive surgery can significantly prolongsurvival in those with a disease-free interval of 24 months or more and in those in whom allmacroscopic disease can be removed. Radiation therapy to the tumour bed following resectionof localized disease may be beneficial in selected patients. Quality of life issues are particularlyimportant for this group of patients and have not been adequately studies.Communication regarding the objectives of therapy is important, and the multidisciplinaryapproach should include palliative care and psycho-social support, in addition to the moretraditional medical options.
Polyelectrolyte multilayers: An odyssey through interdisciplinary science
Jaber, Jad A.
This dissertation provides an overview of a self assembled multilayer technique based on the alternating deposition of oppositely charged polyelectrolytes onto charged solid supports. The basic principles and methodologies governing this technique are laid down, and new strategies are built upon the latter, in an effort to develop innovative technologies that would be beneficial for making new products or improving the quality of existing ones. Fundamental studies to characterize the water content, efficiency of ion-pairing, differential strength of electrostatic interactions, topology, and viscoelastic properties of polyelectrolyte multilayers, PEMUs, are illustrated and conducted. In addition, polyelectrolyte multilayers that are stimulus responsive, or support active and controlled bio-motor protein interactions are described. Attenuated total reflectance Fourier transform infrared, (ATR), spectroscopy was used to compare the extent of swelling and doping within PAH/PSS and PDADMA/PSS polyelectrolyte multilayers. Unlike PDADMA/PSS, whose water content depended on the solution ionic strength, PAH/PSS was resistant to swelling by salt. It was stable up to 4.0 M sodium chloride, with 6 water molecules per ion-pair. Using the infrared active perchlorate sodium salt, the amount of residual persistent extrinsic sites in both PDADMA/PSS and PAH/PSS was determined to be 3% and 6%, respectively. The free energy of association between the polymer segments, in the presence of sodium perchlorate, was in the order of 4.5 kJ mol-1 and -9.5 kJ mol-1 for PDADMA/PSS and PAH/PSS correspondingly. Thus, indicating the relatively strong electrostatic association between the polymer segments in a PAH/PSS relative to PDADMA/PSS multilayer. Adjusting the pH of the solution in contact with the PAH/PSS multilayer to 11.5 resulted in a first order discontinuous dissociation of the Pol+Pol- bonds. Techniques used to study the mechanical properties of single muscle fiber were adapted to characterize the topology, viscoelastic behavior, complex modulus and loss factor of PDADMA/PSS multilayers, over a range of frequencies and strain amplitudes. Tensile mode (transient uniaxial stretching) of a PEMU microcoupon using a capacitative-type force transducer located on a modified stage of inverted microscope revealed evidence on the viscous-like behavior of polymer chains within PEMU. Dependence of viscosity was primarily on the ionic strength of the bathing solution, with appreciable stress relaxation occurring at high salt concentrations. Dynamic mechanical analysis was then used to determine the damping properties of PEMU where the length was oscillated sinusoidally, and the resulting force, amplitude and phase shift were observed. Compared to other commercially available polymer damping materials such as acrylic and rubber adhesives, PEMU demonstrated up to 250% enhancement in damping properties over the frequency range of 0.3-10 Hz. This was obtained while the multilayer dry thickness was 3000% less then that of the conventional adhesives. The synthesis of charged copolymers of poly(N-isopropylacrylamide), (PNIPAM), and their use in constructing thermally responsive PEMU were demonstrated. The temperature dependent water content of the thin film, studied in situ using ATR-FTIR spectroscopy, revealed microscopic and macroscopic transitions at 33 and 45°C, respectively. About 7 water molecules per NIPAM repeat unit were found to be reversibly lost from, or recovered by, the film upon cycling over a temperature range of 10 to 55°C. Assuming that each ion-pair represents a crosslink, swelling theory was used to translate these results into polymer-solvent interaction parameters and enthalpies of mixing for the various polymer components. In addition, the flux of a charged probe molecule, potassium ferricyanide, through the NIPAM-rich multilayer was assessed with rotating disk electrode voltammetry. Thermally reversible modulation of ion transport was demonstrated. Positive polyelectrolytes were investigated as new surface coatings for promoting in vi
Heterogeneous recurrence monitoring and control of nonlinear stochastic processes
International Nuclear Information System (INIS)
Recurrence is one of the most common phenomena in natural and engineering systems. Process monitoring of dynamic transitions in nonlinear and nonstationary systems is more concerned with aperiodic recurrences and recurrence variations. However, little has been done to investigate the heterogeneous recurrence variations and link with the objectives of process monitoring and anomaly detection. Notably, nonlinear recurrence methodologies are based on homogeneous recurrences, which treat all recurrence states in the same way as black dots, and non-recurrence is white in recurrence plots. Heterogeneous recurrences are more concerned about the variations of recurrence states in terms of state properties (e.g., values and relative locations) and the evolving dynamics (e.g., sequential state transitions). This paper presents a novel approach of heterogeneous recurrence analysis that utilizes a new fractal representation to delineate heterogeneous recurrence states in multiple scales, including the recurrences of both single states and multi-state sequences. Further, we developed a new set of heterogeneous recurrence quantifiers that are extracted from fractal representation in the transformed space. To that end, we integrated multivariate statistical control charts with heterogeneous recurrence analysis to simultaneously monitor two or more related quantifiers. Experimental results on nonlinear stochastic processes show that the proposed approach not only captures heterogeneous recurrence patterns in the fractal representation but also effectively monitors the changes in the dynamics of a complex system
Design and development of multilayer vascular graft
Madhavan, Krishna
2011-07-01
Vascular graft is a widely-used medical device for the treatment of vascular diseases such as atherosclerosis and aneurysm as well as for the use of vascular access and pediatric shunt, which are major causes of mortality and morbidity in this world. Dysfunction of vascular grafts often occurs, particularly for grafts with diameter less than 6mm, and is associated with the design of graft materials. Mechanical strength, compliance, permeability, endothelialization and availability are issues of most concern for vascular graft materials. To address these issues, we have designed a biodegradable, compliant graft made of hybrid multilayer by combining an intimal equivalent, electrospun heparin-impregnated poly-epsilon-caprolactone nanofibers, with a medial equivalent, a crosslinked collagen-chitosan-based gel scaffold. The intimal equivalent is designed to build mechanical strength and stability suitable for in vivo grafting and to prevent thrombosis. The medial equivalent is designed to serve as a scaffold for the activity of the smooth muscle cells important for vascular healing and regeneration. Our results have shown that genipin is a biocompatible crosslinker to enhance the mechanical properties of collagen-chitosan based scaffolds, and the degradation time and the activity of smooth muscle cells in the scaffold can be modulated by the crosslinking degree. For vascular grafting and regeneration in vivo, an important design parameter of the hybrid multilayer is the interface adhesion between the intimal and medial equivalents. With diametrically opposite affinities to water, delamination of the two layers occurs. Physical or chemical modification techniques were thus used to enhance the adhesion. Microscopic examination and graft-relevant functional characterizations have been performed to evaluate these techniques. Results from characterization of microstructure and functional properties, including burst strength, compliance, water permeability and suture strength, showed that the multilayer graft possessed properties mimicking those of native vessels. Achieving these FDA-required functional properties is essential because they play critical roles in graft performances in vivo such as thrombus formation, occlusion, healing, and bleeding. In addition, cell studies and animal studies have been performed on the multilayer graft. Our results show that the multilayer graft support mimetic vascular culture of cells and the acellular graft serves as an artery equivalent in vivo to sustain the physiological conditions and promote appropriate cellular activity. In conclusion, the newly-developed hybrid multilayer graft provides a proper balance of biomechanical and biochemical properties and demonstrates the potential for the use of vascular tissue engineering and regeneration.
Recurrent IVF failure and hereditary thrombophilia
Safdarian, Leila; Najmi, Zahra; Aleyasin, Ashraf; Aghahosseini, Marzieh; Rashidi, Mandana; Asadollah, Sara
2014-01-01
Background: The largest percentage of failed invitro fertilization (IVF (cycles, are due to lack of implantation. As hereditary thrombophilia can cause in placentation failure, it may have a role in recurrent IVF failure.
A Case of Recurrent Silent Thyroiditis
Suleyman Ipekci; Mehtap Çak?r
2011-01-01
Silent thyroiditis constitutes approximately 1% all of thyroiditis. Rarely, silent thyroiditis can present with recurrent attacks. Here, we present the case of a patient who had four episodes of painless (silent) thyroiditis. Turk Jem 2011; 15: 47-9
Postoperative recurrence after VATS for spontaneous pneumothorax
International Nuclear Information System (INIS)
A total of 88 cases of 81 patients with spontaneous pneumothorax treated at the hospital from March 1992 to August 2001 were subjected to a study of examining preoperative chest CT and thoracographic findings from the standpoint of postoperative recurrence. Preoperative chest CT and thoracography were conducted in 82 cases and 41 cases (including 25 cases with continuous air leakage), respectively. Eight (9.1%) patients developed recurrence of pneumothorax, and three patients of them underwent reoperation. Considering the intraoperative findings, newly formed bullae appeared to be a cause of recurrence. Resulting from these examinations, we conclude that it is difficult to predict the risk factor for postoperative recurrence at this time, in addition, it is important that the area of air leakage can be confirmed by thoracoscopic findings. (author)
Surgical treatment for residual or recurrent strabismus
Directory of Open Access Journals (Sweden)
Tao Wang
2014-12-01
Full Text Available Although the surgical treatment is a relatively effective and predictable method for correcting residual or recurrent strabismus, such as posterior fixation sutures, medial rectus marginal myotomy, unilateral or bilateral rectus re-recession and resection, unilateral lateral rectus recession and adjustable suture, no standard protocol is established for the surgical style. Different surgical approaches have been recommended for correcting residual or recurrent strabismus. The choice of the surgical procedure depends on the former operation pattern and the surgical dosages applied on the patients, residual or recurrent angle of deviation and the operator''s preference and experience. This review attempts to outline recent publications and current opinion in the management of residual or recurrent esotropia and exotropia.
Genetic considerations in recurrent pregnancy loss.
Hyde, Kassie J; Schust, Danny J
2015-03-01
Human reproduction is remarkably inefficient; nearly 70% of human conceptions do not survive to live birth. Spontaneous fetal aneuploidy is the most common cause for spontaneous loss, particularly in the first trimester of pregnancy. Although losses owing to de novo fetal aneuploidy occur at similar frequencies among women with sporadic and recurrent losses, some couples with recurrent pregnancy loss have additional associated genetic factors and some have nongenetic etiologies. Genetic testing of the products of conception from couples experiencing two or more losses may aid in defining the underlying etiology and in counseling patients about prognosis in a subsequent pregnancy. Parental karyotyping of couples who have experienced recurrent pregnancy loss (RPL) will detect some couples with an increased likelihood of recurrent fetal aneuploidy; this may direct interventions. The utility of preimplantation genetic analysis in couples with RPL is unproven, but new approaches to this testing show great promise. PMID:25659378
RECURRENT TRICHOBEZOAR IN A CASE OF TRICHOTILLOMANIA
Chaudhury, S.; John, T. R.; Ghosh, S. R.; Mishra, G. S.
2001-01-01
A rare case of 13 years old female child with recurrent trichobezoar stomach which needed reoperation for its removal is reported. Patient also had trichotillomania and mental retardation. She showed satisfactory response to therapy with fluoxetine.
Recurrence quantification analysis theory and best practices
Jr, Jr; Marwan, Norbert
2015-01-01
The analysis of recurrences in dynamical systems by using recurrence plots and their quantification is still an emerging field. Over the past decades recurrence plots have proven to be valuable data visualization and analysis tools in the theoretical study of complex, time-varying dynamical systems as well as in various applications in biology, neuroscience, kinesiology, psychology, physiology, engineering, physics, geosciences, linguistics, finance, economics, and other disciplines. This multi-authored book intends to comprehensively introduce and showcase recent advances as well as established best practices concerning both theoretical and practical aspects of recurrence plot based analysis. Edited and authored by leading researcher in the field, the various chapters address an interdisciplinary readership, ranging from theoretical physicists to application-oriented scientists in all data-providing disciplines.
Recurrent encephalic hemorrhage associated with cocaine abuse
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We report a case of recurrent intracerebral hemorrhage secondary to cocaine abuse in a patient with no other predisposing factors. The hemorrhages were located both supra- and infratentorially. (orig.)
Endoscopic retreatment of recurrent choledocholithiasis after sphincterotomy
Sugiyama, M.; Y. Suzuki; Abe, N.; Masaki, T; T. Mori; Atomi, Y
2004-01-01
Background: Endoscopic sphincterotomy (ES) carries a substantial risk of recurrent choledocholithiasis but retreatment with endoscopic retrograde cholangiopancreatography (ERCP) is safe and feasible. However, long term results of repeat ERCP and risk factors for late complications are largely unknown.
Familial recurrence of congenital heart diseases.
Thammineni, K; Lohr, J; Trefz, M; Sivanandam, S
2011-11-01
Familial recurrence of congenital heart disease (CHD), in particular, d-transposition of great arteries (d-TGA) is rare. However, there have been several reports in the literature of sibling recurrence of total anomalous pulmonary venous return (TAPVR). This is the first case report in the literature, describing mother to offspring recurrence of d-TGA. We describe two cases of non-syndromic CHD with mother to offspring and sibling recurrence. The first case is an antenatally diagnosed d-TGA on fetal echocardiogram at 25 weeks of gestational age in the offspring of a 30-year-old mother with d-TGA. The second case is a sibling reoccurrence of TAPVR diagnosed antenatally at 30 weeks of gestational age, with supradiaphragmatic TAPVR on fetal echocardiogram in a mother, whose first child was diagnosed with infradiaphragmatic TAPVR in infancy. PMID:22037157
Risk factors that affect recurrence in strokes
Directory of Open Access Journals (Sweden)
Sevim Bayba?
2010-01-01
Full Text Available Introduction: Recurrent stroke is defined as a new cerebrovascular event which occurs after the stabilization of the previous stroke. Recurrence of stroke increases likelihood of disability-mortality associated with stroke. Systematic evaluation of stroke cases can help to reduce the risk of recurrence. Objective: In order to predict strokes which carry the risk of recurrence, we aimed to compare data related to risk factors, stroke type, etiology and disability-mortality rates associated with stroke. Material And Method: Patients with stroke who referred to Bak?rkoy Neurological and Psychiatric Diseases Training and Research State Hospital between June 1, 2002 and February 28, 2003 were recorded into the stroke database in a consecutive and prospective manner. Strokes were classified as ischemic/hemorrhagic and first/recurrent. For recurrent strokes, information about previous strokes was also recorded. Risk factors were classified as hypertension (HT, diabetes mellitus (DM, hyperlipidemia, atrial fibrillation (AF, coronary artery disease (CAD, migraine, transient ischemic accident (TIA, family history of cerebrovascular accident (CVA, oral contraceptive use, PAD, congestive heart failure (CHF, other heart diseases, smoking cigarette and alcohol consumption. Disability-mortality rates associated with stroke were evaluated. All data were compared for first and recurrent strokes. Results: In our study, 631 patients were evaluated, 52.3% of whom were female and 47.7% male. Frequency of stroke was statistically high (p<0.001 in females over 70 years old. Recurrent strokes were of the same type. For the first and recurrent strokes, HT was the highest risk factor. AF frequency increased with age (p<0.001. The rate of disability-mortality was found high in strokes of undetermined and cardioembolic origin. Conclusion: Knowledge of etiologic group can help to predict recurrence of stroke and prevent death. We think that effective treatment of modifiable risk factors identified in stroke groups where recurrence is the highest, and prioritising the investigation of cardioembolic risk factors in elderly women are significant in terms of primary and secondary stroke prevention.
Energy Technology Data Exchange (ETDEWEB)
Nishimura, Reiki; Nagao, Kazuharu; Miyayama, Haruhiko [Kumamoto City Hospital (Japan)] (and others)
2001-06-01
Recurrence of cancer in the breast is an important problem in breast-conserving therapy. We evaluated risk factors for recurrence from the viewpoint of recurrence type and outcome after recurrence. Of 533 cases of breast cancer treated with breast-conserving surgery from April 1989 through July 2000, disease in 66 recurred (12.4%) and were classified as 23 cases of breast recurrence only, 16 cases of both breast recurrence and distant metastasis, and 27 cases of distant metastasis only. The clinical factors examined included age, lymphatic invasion, nodal status, extensive intraductal component (EIC), proliferative activity, and estrogen receptor (ER) status. Of the 39 cases of breast recurrence, 19 had intramammary tumors and 20 had extramammary tumors of the skin, subcutaneous tissue, or muscle, including 8 cases with inflammatory breast recurrence. Multivariate analysis showed that factors correlated with breast recurrence were age, ER status, proliferative activity, and surgical margin. EIC-comedo was related to intramammary recurrence, whereas lymphatic invasion and nodal status were related to extramammary recurrence. Postoperative irradiation was an effective treatment for tumors in young women and tumors with positive margins or a comedo component. Outcome after breast recurrence depended on nodal status at primary operation, and survival rates were worst in patients with inflammatory breast recurrence. In conclusion, age, EIC-comedo status, the surgical margin, and negative ER status were correlated with breast recurrence. Countermeasures against these factors should be investigated. (author)
International Nuclear Information System (INIS)
Recurrence of cancer in the breast is an important problem in breast-conserving therapy. We evaluated risk factors for recurrence from the viewpoint of recurrence type and outcome after recurrence. Of 533 cases of breast cancer treated with breast-conserving surgery from April 1989 through July 2000, disease in 66 recurred (12.4%) and were classified as 23 cases of breast recurrence only, 16 cases of both breast recurrence and distant metastasis, and 27 cases of distant metastasis only. The clinical factors examined included age, lymphatic invasion, nodal status, extensive intraductal component (EIC), proliferative activity, and estrogen receptor (ER) status. Of the 39 cases of breast recurrence, 19 had intramammary tumors and 20 had extramammary tumors of the skin, subcutaneous tissue, or muscle, including 8 cases with inflammatory breast recurrence. Multivariate analysis showed that factors correlated with breast recurrence were age, ER status, proliferative activity, and surgical margin. EIC-comedo was related to intramammary recurrence, whereas lymphatic invasion and nodal status were related to extramammary recurrence. Postoperative irradiation was an effective treatment for tumors in young women and tumors with positive margins or a comedo component. Outcome after breast recurrence depended on nodal status at primary operation, and survival rates were worst in patients with inflammatory breast recurrence. In conclusion, age, EIC-comedo status, the surgical margiage, EIC-comedo status, the surgical margin, and negative ER status were correlated with breast recurrence. Countermeasures against these factors should be investigated. (author)
Sequence Modeling using Gated Recurrent Neural Networks
Pezeshki, Mohammad
2015-01-01
In this paper, we have used Recurrent Neural Networks to capture and model human motion data and generate motions by prediction of the next immediate data point at each time-step. Our RNN is armed with recently proposed Gated Recurrent Units which has shown promising results in some sequence modeling problems such as Machine Translation and Speech Synthesis. We demonstrate that this model is able to capture long-term dependencies in data and generate realistic motions.
International Nuclear Information System (INIS)
On the example of a hard-disk system the non-recurrence problem have been investigated. Some of the properties of differential equation for the motion of hard-disk system have been analyzed. Using the suggestions of all disk pairs occur simultaneously within a rather small period ?, asymptotic properties of the non-equilibrium hard-disk system when t?? have been studied. The explanation of non-recurrence nature have been submitted. (author)
Recurrence of hepatitis C after liver transplantation
Vinaixa, Carmen; Rubi?n, Angel; Aguilera, Victoria; Berenguer, Marina
2013-01-01
Recurrence of hepatitis C virus (HCV) infection following liver transplantation is a major source of morbidity and mortality. The natural history of hepatitis C in the transplant setting is shortened. Overall, one third of HCV-infected recipients have developed allograft cirrhosis due to HCV recurrence by the 5th-7th year post-transplantation. The most significant variables which determine disease progression are the use of organs from old donors, the use of an inadequate immunosuppression (t...
Oxidative stress in recurrent pregnancy loss women.
Baban, Rayah S.
2010-01-01
OBJECTIVES To investigate biochemical changes in lipid peroxidation, nitric oxide, and vitamin E in recurrent pregnancy loss women, and compare these with healthy pregnant, and non-pregnant women. METHODS A case control study was conducted from September 2008 to December 2009 at Al-Khadimiya Teaching Hospital, Baghdad, Iraq. Ninety-six subjects were included in the study, 32 were patients with recurrent pregnancy loss (RPL), and 32 pregnant women in their third trimester, and another...
Recurrence of Autoimmunity Following Pancreas Transplantation
Burke, George W.; Vendrame, Francesco; Pileggi, Antonello; Ciancio, Gaetano; Reijonen, Helena; Pugliese, Alberto
2011-01-01
Pancreas transplantation is a therapeutic option for patients with type 1 diabetes. Advances in immunosuppression have reduced immunological failures, and these are usually categorized as chronic rejection. Yet studies in our cohort of pancreas transplant recipients identified several patients in whom chronic islet autoimmunity led to recurrent diabetes, despite immunosuppression that prevented rejection. Recurrent diabetes in our cohort is as frequent as chronic rejection, and thus is a sign...
Surgical treatment for residual or recurrent strabismus
Wang, Tao; Wang, Li-hua
2014-01-01
Although the surgical treatment is a relatively effective and predictable method for correcting residual or recurrent strabismus, such as posterior fixation sutures, medial rectus marginal myotomy, unilateral or bilateral rectus re-recession and resection, unilateral lateral rectus recession and adjustable suture, no standard protocol is established for the surgical style. Different surgical approaches have been recommended for correcting residual or recurrent strabismus. The choice of the su...
Pathogenesis and treatment of recurrent erosion.
Williams, R.; Buckley, R. J.
1985-01-01
A series of recurrent corneal erosions secondary to map-dot-fingerprint dystrophy is presented. Erosions were closely related to the Hudson-Stahli line, and this may be a factor in pathogenesis. Traumatic abrasions did not demonstrate such localisation, evidence that trauma is not a primary cause. A trial of management with therapeutic contact lenses versus topical medication was performed. Therapeutic contact lenses were shown to be inferior and had a high complication rate. Recurrent erosio...
Myeloablative chemotherapy for recurrent aggressive oligodendroglioma.
Cairncross, G.; Swinnen, L; Bayer, R.; Rosenfeld, S.; Salzman, D.; Paleologos, N.; Kaminer, L.; Forsyth, P.; Stewart, D.; Peterson, K.; Hu, W; MACDONALD, D; Ramsay, D; SMITH, A.
2000-01-01
The objective of this study was to ascertain the duration of tumor control and the toxicities of dose-intense myeloablative chemotherapy for patients with recurrent oligodendrogliomas. Patients with previously irradiated oligodendrogliomas, either pure or mixed, that were contrast enhancing, measurable, and behaving aggressively at recurrence were eligible for this study. Only complete responders or major partial responders (75 % reduction in tumor size) to induction chemotherapy--either inte...
Laboratory constraints on models of earthquake recurrence
Beeler, N. M.; Tullis, Terry; Junger, Jenni; Kilgore, Brian; Goldsby, David
2014-12-01
In this study, rock friction "stick-slip" experiments are used to develop constraints on models of earthquake recurrence. Constant rate loading of bare rock surfaces in high-quality experiments produces stick-slip recurrence that is periodic at least to second order. When the loading rate is varied, recurrence is approximately inversely proportional to loading rate. These laboratory events initiate due to a slip-rate-dependent process that also determines the size of the stress drop and, as a consequence, stress drop varies weakly but systematically with loading rate. This is especially evident in experiments where the loading rate is changed by orders of magnitude, as is thought to be the loading condition of naturally occurring, small repeating earthquakes driven by afterslip, or low-frequency earthquakes loaded by episodic slip. The experimentally observed stress drops are well described by a logarithmic dependence on recurrence interval that can be cast as a nonlinear slip predictable model. The fault's rate dependence of strength is the key physical parameter. Additionally, even at constant loading rate the most reproducible laboratory recurrence is not exactly periodic, unlike existing friction recurrence models. We present example laboratory catalogs that document the variance and show that in large catalogs, even at constant loading rate, stress drop and recurrence covary systematically. The origin of this covariance is largely consistent with variability of the dependence of fault strength on slip rate. Laboratory catalogs show aspects of both slip and time predictability, and successive stress drops are strongly correlated indicating a "memory" of prior slip history that extends over at least one recurrence cycle.
PET Imaging in Recurrent Medullary Thyroid Carcinoma
Giorgio Treglia; Vittoria Rufini; Massimo Salvatori; Alessandro Giordano; Luca Giovanella
2012-01-01
Purpose. To perform an overview about the role of positron emission tomography (PET) or PET/computed tomography (PET/CT) using different radiopharmaceuticals in recurrent medullary thyroid carcinoma (MTC) based on biochemical findings (increased tumor marker levels after primary surgery). Methods. A comprehensive literature search of studies published in PubMed/MEDLINE, Scopus, and Embase databases through February 2012 regarding PET or PET/CT in patients with recurrent MTC was performed. Res...
Regional phlebography in patients with varicocele recurrences
International Nuclear Information System (INIS)
Diagnostic potentialities of phlebography were studies in 50 patients with varicocele recurrences. Two methods of phlebography: transfemoral renospermaticography and transscrotal orthograde testiculophlebography - were employed. The main cause of recurrence development was shown to be the abnormality of venous outflow from the testicle in the region of the left renal vein, testicular vein and in the pelvic veins. The effectiveness of both methods was 71.9 and 94.4%, respectively, their combined use provided additional information
Recurrence of adrenal aldosterone-producing adenoma
Calvo-romero, J. M.; Ramos-salado, J. L.
2000-01-01
Conn's syndrome (adrenal aldosterone-producing adenoma) and bilateral adrenal hyperplasia are the most common causes of primary aldosteronism. The treatment of choice for patients with aldosterone-producing adenoma is unilateral total adrenalectomy. Recurrence after adequate surgery is exceptional. We present a patient with recurrence of an aldosterone-producing adenoma in the right adrenal gland 9 years after adenomectomy of a aldosterone-producing adenoma in the same adrenal gland. We conc...
Recurrent Respiratory Papillomatosis: an Extensive Review
Angelou Valerie; Kalodimou E. Vasiliki
2012-01-01
Recurrent respiratory papillomatosis (RRP) is characterized by the recurrence of benign tumors (papillomata) in the aero digestive tract caused by Human Papilloma Virus. The burden for the patient and the society is non negligible, due to the high frequency of repetitive surgeries. The disease follows a bimodal age distribution. Usually the very first manifestation is hoarseness or voice changes but if negligee it can cause airway obstruction resulting in respiratorystridor or acute resp...
Recurrent erysipelas - risk factors and clinical presentation
2014-01-01
Background Erysipelas is a common infection that often recurs, but the impact of specific risk factors for reoccurrence remains elusive. In the present study we aimed at clarifying predisposing conditions for reoccurrence. Methods Medical records were reviewed from all patients ?18 years of age diagnosed with erysipelas at the Department of Infectious Diseases at Skåne University Hospital, Sweden, from January 2007 to February 2011. 502 patients were included, of which 357 were single episode erysipelas and 145 had recurrent erysipelas. These two groups were compared regarding underlying conditions and clinical presentation. Results Erysipelas in the lower limbs had the greatest propensity of recurrence. The associations between underlying conditions and recurrence were largely depending on the site of erysipelas. Overall, the most prominent risk factor for recurrence was lymphedema and other conditions causing a chronic impairment of the defence against microbes. Conditions temporarily disrupting the skin barrier (e.g. a local wound or toe web intertrigo), although likely being risk factors for erysipelas per se, did not seem to predispose to repeated episodes. Individuals with recurrent erysipelas tended to seek medical attention earlier, and were less likely to be hospitalized or receive intravenous antibiotics, but there was no evidence of any difference in inflammatory reaction when taking confounding factors into account. Conclusions In this large cross-sectional study of over 500 patients with erysipelas, lymphedema was the most prominent risk factors for recurrence although the distribution of predisposing conditions varies depending on the site of erysipelas. PMID:24884840
An ensemble perspective on multi-layer networks
Wider, Nicolas; Scholtes, Ingo; Schweitzer, Frank
2015-01-01
We study properties of multi-layered, interconnected networks from an ensemble perspective, i.e. we analyze ensembles of multi-layer networks that share similar aggregate characteristics. Using a diffusive process that evolves on a multi-layer network, we analyze how the speed of diffusion depends on the aggregate characteristics of both intra- and inter-layer connectivity. Through a block-matrix model representing the distinct layers, we construct transition matrices of random walkers on multi-layer networks, and estimate expected properties of multi-layer networks using a mean-field approach. In addition, we quantify and explore conditions on the link topology that allow to estimate the ensemble average by only considering aggregate statistics of the layers. Our approach can be used when only partial information is available, like it is usually the case for real-world multi-layer complex systems.
Growth and characterisation on giant magnetoresistance property of metallic multilayers
International Nuclear Information System (INIS)
Metallic multilayers with specific materials configurations have been shown to exhibit giant magnetoresistance effect at room temperature. In this study, microstructural analysis was carried out on magnetron sputtered Co/Cu multilayers using various diffraction and imaging techniques. Dominant characteristic features associated with the multilayers, such as lateral and vertical columnar grain orientations as well as layer undulation and regularity were identified. By deliberately introducing microstructural changes using a buffer layer and via heat treatment, detailed microstructural analysis carried out on the multilayers has provided an insight into the dependence of giant magnetoresistance on the observed microstructures. Our study shows that high giant magnetoresistance effect of the multilayers was associated with highly correlated interfacial profiles, sharp columnar grain boundaries and high degree of lateral coherency in columnar grain growth. While the introduction of iron buffer layer favored the growth of these structural features that were responsible for large giant magnetoresistance effect, annealing led to deterioration of giant magnetoresistance property of the multilayers. (Author)
Multi-layer weighted social network model
Murase, Yohsuke; Jo, Hang-Hyun; Kaski, Kimmo; Kertész, János
2014-01-01
Recent empirical studies using large-scale datasets have validated the Granovetter hypothesis on the structure of the society in that there are strongly wired communities connected by weak ties. However, as interaction between individuals takes place in diverse contexts, these communities turn out to be overlapping. This implies that the society has a multi-layered structure, where the layers represent the different contexts. To model this structure we begin with a single-layer weighted social network (WSN) model showing the Granovetterian structure. We find that when merging such WSN models, sufficient amount of inter-layer correlation is needed to maintain the relationship between topology and link weights but these correlations destroy the enhancement in the community overlap due to multiple layers. To resolve this, we devise a geographic multi-layer WSN model, where the indirect inter-layer correlations due to the geographic constraints of individuals enhance the overlaps between the communities and, at t...
EUV Ellipsometry on Mo/Si Multilayers
Uschakow, S.; Gaupp, A.; MacDonald, M.; Schäfers, F.
2013-03-01
We investigate polarisation properties of a reflective Mo/Si multilayer system in the EUV range using polarized synchrotron radiation at BESSY-II. The characterization involves reflectivity measurements with s- and p-polarized light as a function of the wavelength for three different angles near normal incidence. The phase retardance is determined near normal incidence for one fixed angle of incidence as a function of the wavelength. As an additional spin-off of the polarimetry measurement the Stokes parameters of the beamline could be determined. With the 8-axis UHV-polarimeter we have measured the complex reflection coefficients for the first time and establish this ellipsometry technique as an additional sensitive probe to characterize and model multilayer optical elements.
Theory of superconductivity in multilayer systems
International Nuclear Information System (INIS)
Superconducting properties of artificial multilayer superconductors and layered cuprate-oxide superconductors are studied on a unified basis of the proximity effect. In multilayers composed of two superconductors with different Hc2, an anomaly in the temperature dependence of Hc2 is predicted in relation to a transition between the two different vortex states. For the cuprate oxides we take a model in which superconductivity is generated in the CuO2 layers and superconductivity in the other layers is induced by the proximity effect. On a basis of this model, anomalous behavior of the tunneling conductance, the optical conductivity, the critical fields, the critical current, etc. observed in the superconducting state of the oxides is explained. (orig.)
The structure and dynamics of multilayer networks
Boccaletti, S.; Bianconi, G.; Criado, R.; del Genio, C. I.; Gómez-Gardeñes, J.; Romance, M.; Sendiña-Nadal, I.; Wang, Z.; Zanin, M.
2014-11-01
In the past years, network theory has successfully characterized the interaction among the constituents of a variety of complex systems, ranging from biological to technological, and social systems. However, up until recently, attention was almost exclusively given to networks in which all components were treated on equivalent footing, while neglecting all the extra information about the temporal- or context-related properties of the interactions under study. Only in the last years, taking advantage of the enhanced resolution in real data sets, network scientists have directed their interest to the multiplex character of real-world systems, and explicitly considered the time-varying and multilayer nature of networks. We offer here a comprehensive review on both structural and dynamical organization of graphs made of diverse relationships (layers) between its constituents, and cover several relevant issues, from a full redefinition of the basic structural measures, to understanding how the multilayer nature of the network affects processes and dynamics.
The structure and dynamics of multilayer networks
Boccaletti, S; Criado, R; del Genio, C I; Gómez-Gardeñes, J; Romance, M; Sendiña-Nadal, I; Wang, Z; Zanin, M
2014-01-01
In the past years, network theory has successfully characterized the interaction among the constituents of a variety of complex systems, ranging from biological to technological, and social systems. However, up until recently, attention was almost exclusively given to networks in which all components were treated on equivalent footing, while neglecting all the extra information about the temporal- or context-related properties of the interactions under study. Only in the last years, taking advantage of the enhanced resolution in real data sets, network scientists have directed their interest to the multiplex character of real-world systems, and explicitly considered the time-varying and multilayer nature of networks. We offer here a comprehensive review on both structural and dynamical organization of graphs made of diverse relationships (layers) between its constituents, and cover several relevant issues, from a full redefinition of the basic structural measures, to understanding how the multilayer nature of...
Mathematical Formulation of Multi-Layer Networks
De Domenico, Manlio; Cozzo, Emanuele; Kivelä, Mikko; Moreno, Yamir; Porter, Mason A; Gòmez, Sergio; Arenas, Alex
2013-01-01
A network representation is useful for describing the structure of a large variety of complex systems. However, most real and engineered systems have multiple subsystems and layers of connectivity, and the data produced by such systems is very rich. Achieving a deep understanding of such systems necessitates generalizing "traditional" network theory, and the newfound deluge of data now makes it possible to test increasingly general frameworks for the study of networks. In particular, although adjacency matrices are useful to describe traditional single-layer networks, such a representation is insufficient for the analysis and description of multiplex and time-dependent networks. One must therefore develop a more general mathematical framework to cope with the challenges posed by multi-layer complex systems. In this paper, we introduce a tensorial framework to study multi-layer networks, and we discuss the generalization of several important network descriptors and dynamical processes ---including degree centr...
Optics in magnetic multilayers and nanostructures
Visnovsky, Stefan
2006-01-01
In the continuing push toward optical computing, the focus remains on finding and developing the right materials. Characterizing materials, understanding the behavior of light in these materials, and being able to control the light are key players in the search for suitable optical materials. Optics in Magnetic Multilayers and Nanostructures presents an accessible introduction to optics in anisotropic magnetic media.While most of the literature presents only final results of the complicated formulae for the optics in anisotropic media, this book provides detailed explanations and full step-by-step derivations that offer insight into the procedure and reveal any approximations. Based on more than three decades of experimental research on the subject, the author explains the basic concepts of magnetooptics; nonreciprocal wave propagation; the simultaneous effect of crystalline symmetry and arbitrarily oriented magnetization on the form of permittivity tensors; spectral dependence of permittivity; multilayers at...
Magnetic nanodiscs fabricated from multilayered nanowires.
Min, Ji Hyun; Cho, Ji Ung; An, Boo Hyun; Choi, Daniel S; Kimlr, Young Keun
2014-10-01
We report a simple, high throughput synthesis method of producing magnetic nanodiscs, in which the diameter and thickness are easily controlled. This method consists of two steps: (1) Electrodeposition for growing multilayered nanowires and (2) Selective etching of sacrificial layers. The electrodeposition step results in a bundle of multilayered nanowires. The nanowires consist of alternating layers of magnetic (e.g., Co) and sacrificial materials (e.g., Cu) inside the nanometer-sized pores of an anodized aluminum oxide (AAO) template. The diameter of each layer is determined by pore size, while the thickness is controlled by electrodeposition time. The selective wet etching step removes sacrificial layers, leaving the magnetic nanodiscs. Through this process, the magnetic nanodiscs are fabricated with aspect ratios ranging from 0.25 to 2.0. PMID:25942895
Mo-C Multilayered CVD Coatings
Directory of Open Access Journals (Sweden)
A. Sagalovych
2013-12-01
Full Text Available Production processes of multi-layered Mo-C coatings by the method of chemical vapor deposition (CVD with the use of organometallic compounds were developed. Coatings are applied on technical purpose steel DIN 1.2379 (H12F1 and DIN 1.7709 (25H2MF (ÉI10 heat-treated ball with the high class of surface roughness (> 10. The average deposition rate was 50 ?m / h. The optimal conditions of deposition coatings for different technological schemas were defined. Metallographic investigations of the obtained coatings were carried out. Tribological studies of the friction and wear characteristics of sliding friction in conditions of boundary lubrication of Ï-S multilayered CVD coatings shows, that coatings have low friction coefficients (0075-0095 at loads up to 2.0 kN, showed high resistance to wear and are effective in increasing the stability of the pair for precision friction pairs of hydraulical units.
Random walk centrality in interconnected multilayer networks
Solé-Ribalta, Albert; Gómez, Sergio; Arenas, Alex
2015-01-01
Real-world complex systems exhibit multiple levels of relationships. In many cases they require to be modeled as interconnected multilayer networks, characterizing interactions of several types simultaneously. It is of crucial importance in many fields, from economics to biology and from urban planning to social sciences, to identify the most (or the less) influential nodes in a network using centrality measures. However, defining the centrality of actors in interconnected complex networks is not trivial. In this paper, we rely on the tensorial formalism recently proposed to characterize and investigate this kind of complex topologies, and extend two well known random walk centrality measures, the random walk betweenness and closeness centrality, to interconnected multilayer networks. For each of the measures we provide analytical expressions that completely agree with numerically results.
Diffuse photon propagation in multilayered geometries
Energy Technology Data Exchange (ETDEWEB)
Sikora, Jan [Institute of the Theory of Electrical Engineering, Measurement and Information Systems, Warsaw University of Technology, Koszykowa 75, 00-661 Warsaw (Poland); Zacharopoulos, Athanasios [Department of Computer Science, University College London, Gower Street, London, WC1E 6BT (United Kingdom); Douiri, Abdel [Department of Computer Science, University College London, Gower Street, London, WC1E 6BT (United Kingdom); Schweiger, Martin [Department of Computer Science, University College London, Gower Street, London, WC1E 6BT (United Kingdom); Horesh, Lior [Department of Medical Physics and BioEngineering, University College London, Gower Street, London, WC1E 6BT (United Kingdom); Arridge, Simon R [Department of Computer Science, University College London, Gower Street, London, WC1E 6BT (United Kingdom); Ripoll, Jorge [Institute of Electronic Structure and Laser, FORTH, PO Box 1527, Vassilika Vouton, 71110 Heraklion, Crete (Greece)
2006-02-07
Diffuse optical tomography (DOT) is an emerging functional medical imaging modality which aims to recover the optical properties of biological tissue. The forward problem of the light propagation of DOT can be modelled in the frequency domain as a diffusion equation with Robin boundary conditions. In the case of multilayered geometries with piecewise constant parameters, the forward problem is equivalent to a set of coupled Helmholtz equations. In this paper, we present solutions for the multilayered diffuse light propagation for a three-layer concentric sphere model using a series expansion method and for a general layered geometry using the boundary element method (BEM). Results are presented comparing these solutions to an independent Monte Carlo model, and for an example three layered head model.
Methodology for determining multilayered temperature inversions
Fochesatto, G.J.
2015-01-01
Temperature sounding of the atmospheric boundary layer (ABL) and lower troposphere exhibits multilayered temperature inversions specially in high latitudes during extreme winters. These temperature inversion layers are originated based on the combined forcing of local- and large-scale synoptic meteorology. At the local scale, the thermal inversion layer forms near the surface and plays a central role in controlling the surface radiative cooling and air pollution dispersion; ...
Development of multilayered chitosan-based nanofibers
Croisier, Florence; Aqil, Abdelhafid; Detrembleur, Christophe; Je?ro?me, Christine
2009-01-01
By combining electrospinning and layer-by-layer deposition techniques, new porous material scaffolds of multilayered, chitosan-based nanofibers were produced. Layer-by-layer (LBL) is a well-known method for surface coating, based on electrostatic interactions. It enables the controllable deposition of a variety of polyelectrolytes including synthetic and natural materials, with designable layer structure, defined layer thickness and size. Electrospinning (ESP) allows the fabrication of po...
Fracture mechanics parameters of multilayer pipes
Šestáková L.; Náhlík L.; Huta? P.; Knésl Z.
2007-01-01
Multilayer pipes consisting of different materials are frequently used in praxis because of partial improvement of the properties of pipe systems. To estimate lifetime of these pipes the basic fracture parameters have to be determined. In this work finite element calculations are applied in order to estimate the stress intensity factor K and T-stress values for a new type of non-homogenous C-shape specimen. The application of calculated K and T values to laboratory estimation of fracture toug...
Layer-resolved conductivities in multilayer graphenes
Wakutsu, Takeo; Nakamura, Masaaki; Do?ra, Bala?zs
2011-01-01
We study interlayer transport of multilayer graphenes in magnetic field with various stacking structures (AB, ABC, and AA types) by calculating the Hall and longitudinal conductivities as functions of Fermi energy. Their behavior depends strongly on the stacking structures and selection of the layers. The Hall conductivity between different layers is no longer quantized. Moreover, for AB stacking, the interlayer conductivity vanishes around zero energy with increasing layer ...
Planar multilayer structure analysis: an educational approach
Scientific Electronic Library Online (English)
D.B., Ferreira; A.F., Tinoco Salazar; I., Bianchi; J.C. da S., Lacava.
2012-06-01
Full Text Available This paper discusses how symbolic computation combined with a circuit model can be used for analyzing planar multilayer structures, in a manner suitable for educational approach. Working in the Fourier domain, expressions for the transversal spectral Green’s functions are evaluated in compact, close [...] d form using the symbolic computation capability of the Mathematica package. Printed antennas were analyzed through the method of moments. Further validation was achieved with the IE3D and HFSS packages.
Novel multilayer structure CWDM demultiplexer in silica
Atieh, Ahmad; Mansour, Ibrahim; Dalala, Zakariya
2011-12-01
Novel CWDM multilayer structure demultiplexer in silica is proposed and investigated. The refractive index of each layer in the structure follows fiber graded index profile with ?-parameter less than one. The demultiplexer structure depends on the refractive index profile parameter, thickness, incidence angle, number of layers and channel's spacing. The effect of all of these parameters on the amount of spatial shift and the separation between adjacent channels is investigated.
Ultrapure Multilayer Graphene in Bromine Intercalated Graphite
Hwang, J.; Carbotte, J. P.; Tongay, S.; Hebard, A. F.; Tanner, D.B.
2011-01-01
We investigate the optical properties of bromine intercalated highly orientated pyrolytic graphite (Br-HOPG) and provide a novel interpretation of the data. We observe new absorption features below 620 meV which are absent in the absorption spectrum of graphite. Comparing our results with those of theoretical studies on graphite, single and bilayer graphene as well as recent optical studies of multilayer graphene, we conclude that Br-HOPG contains the signatures of ultrapure...
Specific heat of niobium-zirconium multilayers
International Nuclear Information System (INIS)
We present the first specific-heat measurements of artificially layered superconducting structures. Using small sample calorimetry, we have measured the specific heat of Nb-Zr multilayers. Samples with ?, the bilayer period, varying from 32.8 to 429 A (with total sample thickness of 1.5 ?m were studied in a temperature range 1.5--20 K. We obtained the effective theta/sub D/ and ? for the samples as well as ?C/?T/sub c/. .AE
Critical fields of Nb-Ta multilayers
International Nuclear Information System (INIS)
Nb-Ta multilayered films prepared by magnetron sputtering have been studied by critical-field measurements. We have examined the effects of substrate orientation and deposition temperature on the properties of the films. Three-dimensional to two-dimensional crossover is observed. For films with larger Nb layer thicknesses an additional transition in H/sub c/2/sub X/ at lower temperatures is observed which cannot be accounted for by the interfacial regions
Multilayer relaxation of clean Ag\\{001\\}
Li, H.; Quinn, J.; Li, Y. S.; Tian, D.; Jona, F.; Marcus, P. M.
1991-03-01
A low-energy electron-diffraction intensity analysis of data from a clean Ag\\{001\\} surface finds no multilayer relaxation, i.e., with ?dik being the change in spacing between layer i and layer k, ?d12=0+/-0.03 Å and ?d23=0+/-0.03 Å. These results are compared with the results of first-principles total-energy calculations and with other recent relaxation determinations on fcc \\{001\\} surfaces.
Tensor damping in metallic magnetic multilayers
Smith, Neil
2009-01-01
The mechanism of spin-pumping, described by Tserkovnyak et al., is formally analyzed in the general case of a magnetic multilayer consisting of two or more metallic ferromagnetic (FM) films separated by normal metal (NM) layers. It is shown that the spin-pumping-induced dynamic coupling between FM layers modifies the linearized Gilbert equations in a way that replaces the scalar Gilbert damping constant with a nonlocal matrix of Cartesian damping tensors. The latter are show...
Ballistic properties of multilayered concrete shields
International Nuclear Information System (INIS)
We investigate theoretically the effect of layering of concrete shields using a wide class of semi-empirical models. We have found that (i) the ballistic limit velocity (BLV) of the multilayered shield does not depend on the order of the plates in the shield, (ii) monolithic shield is superior to any layered shield with the same thickness, and (iii) the largest decrease of the BLV occurs when a shield is divided into a number of plates having the same thickness.
Flint, Alex; Blaschko, Matthew
2012-01-01
Boolean satisfiability (SAT) as a canonical NP-complete decision problem is one of the most important problems in computer science. In practice, real-world SAT sentences are drawn from a distribution that may result in efficient algorithms for their solution. Such SAT instances are likely to have shared characteristics and substructures. This work approaches the exploration of a family of SAT solvers as a learning problem. In particular, we relate polynomial time solvability of a SAT subset t...
Stress in tungsten carbide-diamond like carbon multilayer coatings:
Pujada, B.R.; Tichelaar, F.D.; Janssen, G.C.A.M.
2007-01-01
Tungsten carbide-diamond like carbon (WC-DLC) multilayer coatings have been prepared by sputter deposition from a tungsten-carbide target and periodic switching on and off of the reactive acetylene gas flow. The stress in the resulting WC-DLC multilayers has been studied by substrate curvature. Periodicity and microstructure have been studied by transmission electron microscopy. It has been observed that compressive stress in the multilayers decreases when the bilayer thickness is reduced. Re...
Etched-multilayer phase shifting masks for EUV lithography
Chapman, Henry N.; Taylor, John S.
2005-04-05
A method is disclosed for the implementation of phase shifting masks for EUV lithography. The method involves directly etching material away from the multilayer coating of the mask, to cause a refractive phase shift in the mask. By etching into the multilayer (for example, by reactive ion etching), rather than depositing extra material on the top of the multilayer, there will be minimal absorption loss associated with the phase shift.
Multilayered Polymer Coated Carbon Nanotubes to Deliver Dasatinib
Moore, Thomas L.; Grimes, Stuart W.; Lewis, Robert L.; Alexis, Frank
2013-01-01
Multilayered, multifunctional polymer coatings were grafted onto carbon nanotubes (CNT) using a one-pot, ring-opening polymerization in order to control the release kinetic and therapeutic efficacy of dasatinib. Biocompatible, biodegradable multilayered coatings composed of poly(glycolide) (PGA), and poly(lactide) (PLA) were polymerized directly onto hydroxyl-functionalized CNT surfaces. Sequential addition of monomers into the reaction vessel enabled multilayered coatings of PLA-PGA, or PGA-...
Model calculations of the proximity effect in finite multilayers
Ciuhu, C.; Lodder, A.
2000-01-01
The proximity-effect theory developed by Takahashi and Tachiki for infinite multilayers is applied to multilayer systems with a finite number of layers in the growth direction. The purpose is to investigate why previous applications to infinite multilayers fail to describe the measured data satisfactorily. Surface superconductivity may appear, depending on the thickness of the covering normal metallic N layers on both the top and the bottom. The parameters used are character...
Multiperiodicity in plasmonic multilayers: General description and diversity of topologies
DEFF Research Database (Denmark)
Orlov, Alexey A.; Krylova, Anastasia K.
2014-01-01
We introduce multiperiodicity in periodicmetal-dielectric multilayers by stacking more than two types of metal and/or dielectric layers into the unit cell. A simple way to characterize arbitrary multiperiodic multilayers using permutation vectors is suggested and employed. Effects of multiperiodicity up to its fourth order are investigated. We demonstrate that various topologies of multiple-sheet isofrequency and dispersion surfaces exist for such plasmonic multilayers, including a photonic realization of nontrivial isolated Dirac cones.
Multilayer modal actuator-based piezoelectric transformers.
Huang, Yao-Tien; Wu, Wen-Jong; Wang, Yen-Chieh; Lee, Chih-Kung
2007-02-01
An innovative, multilayer piezoelectric transformer equipped with a full modal filtering input electrode is reported herein. This modal-shaped electrode, based on the orthogonal property of structural vibration modes, is characterized by full modal filtering to ensure that only the desired vibration mode is excited during operation. The newly developed piezoelectric transformer is comprised of three layers: a multilayered input layer, an insulation layer, and a single output layer. The electrode shape of the input layer is derived from its structural vibration modal shape, which takes advantage of the orthogonal property of the vibration modes to achieve a full modal filtering effect. The insulation layer possesses two functions: first, to couple the mechanical vibration energy between the input and output, and second, to provide electrical insulation between the two layers. To meet the two functions, a low temperature, co-fired ceramic (LTCC) was used to provide the high mechanical rigidity and high electrical insulation. It can be shown that this newly developed piezoelectric transformer has the advantage of possessing a more efficient energy transfer and a wider optimal working frequency range when compared to traditional piezoelectric transformers. A multilayer piezoelectric, transformer-based inverter applicable for use in LCD monitors or portable displays is presented as well. PMID:17328332
Heat Transfer in High Temperature Multilayer Insulation
Daryabeigi, Kamran; Miller, Steve D.; Cunnington, George R.
2007-01-01
High temperature multilayer insulations have been investigated as an effective component of thermal-protection systems for atmospheric re-entry of reusable launch vehicles. Heat transfer in multilayer insulations consisting of thin, gold-coated, ceramic reflective foils and Saffil(TradeMark) fibrous insulation spacers was studied both numerically and experimentally. A finite volume numerical thermal model using combined conduction (gaseous and solid) and radiation in porous media was developed. A two-flux model with anisotropic scattering was used for radiation heat transfer in the fibrous insulation spacers between the reflective foils. The thermal model was validated by comparison with effective thermal conductivity measurements in an apparatus based on ASTM standard C201. Measurements were performed at environmental pressures in the range from 1x10(exp -4) to 760 torr over the temperature range from 300 to 1300 K. Four multilayer samples with nominal densities of 48 kg/cu m were tested. The first sample was 13.3 mm thick and had four evenly spaced reflective foils. The other three samples were 26.6 mm thick and utilized either one, two, or four reflective foils, located near the hot boundary with nominal foil spacing of 1.7 mm. The validated thermal model was then used to study relevant design parameters, such as reflective foil spacing and location in the stack-up and coating of one or both sides of foils.
Automation Enhancement of Multilayer Laue Lenses
Energy Technology Data Exchange (ETDEWEB)
Lauer K. R.; Conley R.
2010-12-01
X-ray optics fabrication at Brookhaven National Laboratory has been facilitated by a new, state of the art magnetron sputtering physical deposition system. With its nine magnetron sputtering cathodes and substrate carrier that moves on a linear rail via a UHV brushless linear servo motor, the system is capable of accurately depositing the many thousands of layers necessary for multilayer Laue lenses. I have engineered a versatile and automated control program from scratch for the base system and many subsystems. Its main features include a custom scripting language, a fully customizable graphical user interface, wireless and remote control, and a terminal-based interface. This control system has already been successfully used in the creation of many types of x-ray optics, including several thousand layer multilayer Laue lenses.Before reaching the point at which a deposition can be run, stencil-like masks for the sputtering cathodes must be created to ensure the proper distribution of sputtered atoms. Quality of multilayer Laue lenses can also be difficult to measure, given the size of the thin film layers. I employ my knowledge of software and algorithms to further ease these previously painstaking processes with custom programs. Additionally, I will give an overview of an x-ray optic simulator package I helped develop during the summer of 2010. In the interest of keeping my software free and open, I have worked mostly with the multiplatform Python and the PyQt application framework, utilizing C and C++ where necessary.
Performance of multilayer coated silicon pore optics
DEFF Research Database (Denmark)
Ackermann, M. D.; Collon, M. J.
2010-01-01
The requirements for the IXO (International X-ray Observatory) telescope are very challenging in respect of angular resolution and effective area. Within a clear aperture with 1.7 m > R > 0.25 m that is dictated by the spacecraft envelope, the optics technology must be developed to satisfy simultaneously requirements for effective area of 2.5 m2 at 1.25 keV, 0.65 m2 at 6 keV and 150 cm2 at 30 keV. The reflectivity of the bare mirror substrate materials does not allow these requirements to be met. As such the IXO baseline design contains a coating layout that varies as a function of mirror radius and in accordance with the variation in grazing incidence angle. The higher energy photon response is enhanced through the use of depth-graded multilayer coatings on the inner radii mirror modules. In this paper we report on the first reflectivity measurements of wedged ribbed silicon pore optics mirror plates coated with a depth graded W/Si multilayer. The measurements demonstrate that the deposition and performance of the multilayer coatings is compatible with the SPO production process.
Physical Properties of PC-PMMA Multilayers
Rahman, Arifur; Baer, Eric; Chipara, Alin Cristian; Vajtai, Robert; Ajayan, Pullickel M.; Hinthorne, James; Elamin, Ibrahim; Chipara, Mircea; Eric Baer Collaboration; Pullickel Ajayan Collaboration; Mircea Chipara Collaboration
2015-03-01
Multilayers of polycarbonate (PC) and polymethylmethacrylate (PMMA) have been obtained by the layer multiplying coextrusion method. Each sample (1024 layers, of equal thickness, with individual thickness between 10 and 200 nm) has been investigated at room temperature by Wide Angle X-Ray Scattering (WAXS) using a Bruker Discovery 8 spectrometer (Cu K ? radiation), Raman spectroscopy (Bruker Senterra confocal Raman spectrometer operating at 785 nm), FTIR spectroscopy (Tensor 27 Bruker), and UV-Vis spectroscopy. Further details about the glass transition temperature in these samples have been obtained by Dynamical Mechanical Analysis, DMA, (TA Instruments Q800) at various frequencies in the range 1 to 100 Hz. Isothermal Differential Scanning Calorimetry, DSC, (TA Instruments Q200) was used to investigate the effect of the thickness of the polymeric film on the crystallization processes. Non-isothermal DSC measurements aimed at the identification and location of the main phase transitions (glass, crystallization, and melting) occurring in these multilayers. The effects of confinement on the phase transitions occurring in these multilayers are discussed in detail.
Quantum Spin Hall phase in multilayer graphene
Garcia, Noel; Lado, Jose Luis; Fernandez-Rossier, Joaquin; Theory of Nanostructures Team
2015-03-01
We address the question of whether multilayer graphene systems are Quantum Spin Hall (QSH) insulators. Since interlayer coupling coples pz orbitals to s orbitals of different layers and Spin-Orbit (SO) couples pz orbitals with px and py of opposite spins, new spins mixing channels appear in the multilayer scenario that were not present in the monolayer. These new spin-mixing channels cast a doubt on the validity of the spin-conserving Kane-Mele model for multilayers and motivates our choice of a four orbital tight-binding model in the Slater-Koster approximation with intrinsic Spin-Orbit interaction. To completely determine if the QSH phase is present we calculate for different number of layers both the Z2 invariant for different stackings (only for inversion symmetric systems), and the density of states at the edge of semi-infinite graphene ribbon with armchair termination. We find that systems with even number of layers are normal insulators while systems with odd number of layers are QSH insulators, regardless of the stacking. We acknowledge financial support by Marie-Curie-ITN 607904-SPINOGRAPH.
Evolutionary games on multilayer networks: a colloquium
Wang, Zhen; Wang, Lin; Szolnoki, Attila; Perc, Matjaž
2015-05-01
Networks form the backbone of many complex systems, ranging from the Internet to human societies. Accordingly, not only is the range of our interactions limited and thus best described and modeled by networks, it is also a fact that the networks that are an integral part of such models are often interdependent or even interconnected. Networks of networks or multilayer networks are therefore a more apt description of social systems. This colloquium is devoted to evolutionary games on multilayer networks, and in particular to the evolution of cooperation as one of the main pillars of modern human societies. We first give an overview of the most significant conceptual differences between single-layer and multilayer networks, and we provide basic definitions and a classification of the most commonly used terms. Subsequently, we review fascinating and counterintuitive evolutionary outcomes that emerge due to different types of interdependencies between otherwise independent populations. The focus is on coupling through the utilities of players, through the flow of information, as well as through the popularity of different strategies on different network layers. The colloquium highlights the importance of pattern formation and collective behavior for the promotion of cooperation under adverse conditions, as well as the synergies between network science and evolutionary game theory.
Building a Chaotic Proved Neural Network
Bahi, Jacques M; Salomon, Michel
2011-01-01
Chaotic neural networks have received a great deal of attention these last years. In this paper we establish a precise correspondence between the so-called chaotic iterations and a particular class of artificial neural networks: global recurrent multi-layer perceptrons. We show formally that it is possible to make these iterations behave chaotically, as defined by Devaney, and thus we obtain the first neural networks proven chaotic. Several neural networks with different architectures are trained to exhibit a chaotical behavior.
Building a Chaotic Proved Neural Network
Bahi, Jacques M.; Guyeux, Christophe; Salomon, Michel
2011-01-01
Chaotic neural networks have received a great deal of attention these last years. In this paper we establish a precise correspondence between the so-called chaotic iterations and a particular class of artificial neural networks: global recurrent multi-layer perceptrons. We show formally that it is possible to make these iterations behave chaotically, as defined by Devaney, and thus we obtain the first neural networks proven chaotic. Several neural networks with different arc...
Neutron reflectivity studies from a platinum/carbon multilayer
International Nuclear Information System (INIS)
The neutron reflectivity from 30 Pt/C bilayers on an Si substrate has been measured using the time-of-flight (TOF) technique. The thickness of the bilayers, the total thickness of the multilayer structure and the density of the carbon and platinum layers are determined. The influence on the reflectivity curve of different types of multilayer-substrate and air-multilayer interfaces are examined. The experimental data are fitted with a reflectivity curve calculated by using a smoothly varying density profile between the multilayer structure and the substrate. (author)
A degree centrality in multi-layered social network
Bródka, Piotr; Kazienko, Przemys?aw; Musia?, Katarzyna
2012-01-01
Multi-layered social networks reflect complex relationships existing in modern interconnected IT systems. In such a network each pair of nodes may be linked by many edges that correspond to different communication or collaboration user activities. Multi-layered degree centrality for multi-layered social networks is presented in the paper. Experimental studies were carried out on data collected from the real Web 2.0 site. The multi-layered social network extracted from this data consists of ten distinct layers and the network analysis was performed for different degree centralities measures.
Multi-Periodicity Induces Prominent Optical Phenomena in Plasmonic Multilayers
DEFF Research Database (Denmark)
Orlov, Alexey A.; Krylova, A. K.
2014-01-01
We introduce multi-periodicity in plasmonic multilayers and develop a general theory for the description of their eigenwaves. We define the order of multi-periodicity as the number of different kinds of plasmonic interfaces present in the multilayer, and investigate the optical effects that arise as this order increases from one (simple periodic multilayers) to two (bi- periodic multilayers) and beyond. For example, we show the formation of additional photonic bands, multi-refringence of p -polarized light, Dirac and mixed states.
Detection of recurrent rectal carcinoma with computed tomography
International Nuclear Information System (INIS)
In patients with abdominoperineal resection CT is the only effective radiological method for demonstrating the recurrence of rectal carcinomas. Our series consists of 20 patients examined with CT (38 examinations) because of suspected recurrent rectal carcinoma. Three patients had no recurrence. 13 recurrences were definitely diagnosed. In 2 cases the possibility of an abscess was considered. One recurrent tumour was misdiagnosed as postoperative fibrosis and one as a uterine fibroid. (orig.)
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
Chung, Junyoung; Gulcehre, Caglar; Cho, Kyunghyun; Bengio, Yoshua
2014-01-01
In this paper we compare different types of recurrent units in recurrent neural networks (RNNs). Especially, we focus on more sophisticated units that implement a gating mechanism, such as a long short-term memory (LSTM) unit and a recently proposed gated recurrent unit (GRU). We evaluate these recurrent units on the tasks of polyphonic music modeling and speech signal modeling. Our experiments revealed that these advanced recurrent units are indeed better than more traditio...
Aggressive angiomyxoma: irradiation for recurrent disease
International Nuclear Information System (INIS)
Background: Aggressive angiomyxoma (AAM) is a tumor of the soft tissues predominantly occurring in the genital and pelvic area with a strong propensity to local recurrences. The entity was first described in 1983. The tumor is regarded as low-grade sarcoma by some authors; its cause and pathogenesis are presently unknown. Patient and method: This is a case report on a 27-year-old man who underwent 4 surgical procedures of the left lower extremity because of a recurrent soft tissue neoplasm, initially (August 1993) diagnosed as a myxolipoma. The patient suffered from recurrences in February 1995, September 1996 and February 1998. The diagnosis was revised at the time of the latest recurrence. A palliative resection with macroscopic residuals left was performed in February 1998, followed by a radiation therapy with 56 Gy total dose and a concomitant administration of the radiosensitizer razoxane per os. The single radiation doses were 200 cGy 5 times a week. Results: The small residuals of the tumor obviously regressed although an objective response could not be shown because the lesion was not clearly measurable. A follow-up 2 years after the radiation treatment revealed no recurrence. The time of the local control achieved as yet is already longer than any former time to regrowth between the surgical procedures. This is, to our knowledge, the first description of a therapeutic irradiation of a recurrent aggressive angiomyxoma. Conclusion: Radiation therapy combined wi Conclusion: Radiation therapy combined with the sensitizer razoxane is able to control a recurrent AAM for an unknown time. It remains open whether a radiation treatment alone would have had a similar effect. (orig.)
FEBRILE SEIZURE: RECURRENCE AND RISK FACTORS
Directory of Open Access Journals (Sweden)
A. TALEBIAN
2006-06-01
Full Text Available Background:Febrile Convulsion is the most common convulsive disorder in children,occurring in 2 to 4% of the pediatric population and recurring in 30-50% of cases. Considering the varying recurrence rates reported, thisstudy was conducted at the pediatric ward of the Shaheed BeheshtiGeneral Hospital, between 2000-2001 to determine the frequencyof recurrence and related risk factors in children presenting with theirfirst episode of febrile convulsionMaterials & Methods:A two–year cohort study was performed on 50 children presentingwith the first attack of febrile convulsion. Patient demographic dataincluding age, sex, type and duration of seizure, family history offebrile seizure or epilepsy and the interval between fever onset andoccurrence of seizure were recorded in questionnaires. Those patients,for whom prophylactic medication was not administered, werefollowed at three–month intervals for up to one year. Findings werestatistically analyzed using Fisher’s exact testResults:Recurrence was observed in twelve children (24% out of the fifty,being most common in patients aged less than one year (54.4%.Recurrence rates among children with a positive family history offebrile convulsion, presence of complex febrile seizure and positivefamily history of epilepsy were 42.1%, 42.8% and 25% respectively.From among those children with a “less than one hour” intervalbetween fever onset and occurrence of seizure, recurrence occurredin 43-7% of cases, while in those with a “more than one hourinterval”, 14.7% experienced recurrence.Conclusion:Recurrence rates are increased by certain factors including age-belowone year-, positive family history of febrile convulsion, and a “lessthan one hour” interval between time of fever onset and seizureoccurrence.
Reactive Functionalized Multilayer Polymers in Coextrusion Process
Lamnawar, Khalid; Maazouz, Abderrahim
2007-04-01
Coextrusion technologies are commonly used to produce multilayered composite sheets or films with a large range of applications. The contrast of rheological properties between layers can lead to interfacial instabilities during flow. Important theoretical and experimental advances have been made during the last decades on the stability of compatible and incompatible polymers using a mechanical approach. The present study deals with the influence of this affinity on interfacial instabilities for functionalized incompatible polymers between the neighboring layers. Polyamide (PA6)/Polyethylene-grafted (GMA) or pure PE were studied with different viscosity and elasticity ratios. We have experimentally confirmed, in this case, that the weak disturbance can be predicted by considering an interphase of non-zero thickness (corresponding to interdiffusion/reaction zone) instead of a purely geometrical interface between the two reactive layers. As a first step, rheological behavior of multilayer coextruded cast films was investigated to probe: (i) the competition between polymer/polymer interdiffusion and the interfacial reaction and (ii) the influence of the interphase. The contribution of this one effect has been studied along with the increase of the number of layers. The results show that the variation in dynamic modulus of the multilayer system reflects both diffusion and chemical reaction. Finally, and in order to quantify the contribution of the effect of the interface/interphase with a specific interfacial area, an expression was developed to take into account the interphase triggered between the neighboring layers and allowed us to estimate its thickness at a specific welding time and shear rate. As the second step, we formulate an experimental strategy to optimize the process by listing the different parameters controlling the stability of the reactive multilayer flows. The plastic films of two, three and five layers were coextruded in symmetrical and asymmetrical configurations in which PA6 is a middle layer. Indeed, for reactive multilayered system, the interfacial flow instability can be reduced or eliminated, for example, by (i) increasing the residence time or temperature in the coextrusion feed block (for T over reaction temperature) and (ii) reducing the total extrusion flow rate. Hence, based on this analysis guide-lines for stable Coextrusion of reactive functionalized polymers can be provided.
Recurrent Laryngeal Nerve Injury in Thyroid Surgery
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Hazem M. Zakaria
2011-01-01
Full Text Available AbstractObjectives: Vocal cord paresis or paralysis due to iatrogenic injury of the recurrent laryngeal nerve (RLNI is one of the main problems in thyroid surgery. Although many procedures have been introduced to prevent the nerve injury, still the incidence of recurrent laryngeal nerve palsy varies between 1.5-14?20The aim of the present study is to assess the risk factors of recurrent laryngeal nerve injury during thyroid surgery.Methods: Patients who had thyroid surgery between 1990 and 2005 and were admitted to the surgical department of King Fahd hospital of the University, Al-Khobar, Saudi Arabia were enrolled for this retrospective review, Factors predisposing to recurrent laryngeal nerve injury were evaluated such as pathology of the lesions and the type of operations and identification of recurrent laryngeal nerve intra-operatively. Preoperative and postoperative indirect laryngoscopic examinations were performed for all patients.Results: 340 patients were included in this study. Transient unilateral vocal cord problems occurred in 11 (3.2?20cases, and in 1 (0.3?20case, it became permanent (post Rt. Hemithyroidectomy. Bilateral vocal cord problems occurred in 2 cases (0.58? but none became permanent. There were significant increases in the incidence of recurrent laryngeal nerve injury in secondary operation (21.7?0in secondary vs. 2.8?0in primary, p=0.001, total/near total thyroidectomy (7.2?0in total vs. 1.9?0in subtotal, p=0.024, non-identification of RLN during surgery (7.6?0in non-identification vs. 2.6?0in identification, p=0.039 and in malignant disease (12.8?0in malignant vs. 2.9?0in benign, p=0.004. However, there was no significant difference in the incidence of recurrent laryngeal nerve injury with regards to gender (4.1?0in male vs 3.8?0in female, p=0.849.Conclusion: The present study showed that thyroid carcinoma, re-operation for recurrent goiter, non-identification of RLN and total thyroidectomy were associated with a significantly increased risk of operative recurrent laryngeal nerve injury.
2015-05-28
Estrogen Receptor Negative; HER2/Neu Negative; Ovarian Endometrioid Adenocarcinoma; Ovarian Serous Cystadenocarcinoma; Ovarian Serous Surface Papillary Adenocarcinoma; Progesterone Receptor Negative; Recurrent Breast Carcinoma; Recurrent Fallopian Tube Carcinoma; Recurrent Ovarian Carcinoma; Recurrent Primary Peritoneal Carcinoma; Triple-Negative Breast Carcinoma
Use of bevacizumab in recurrent glioblastoma.
Ghiaseddin, Ashley; Peters, Katherine B
2015-05-01
SUMMARY? Glioblastoma (GBM) is the most common adult primary brain neoplasm. Despite advances in treatment, GBM continues to be associated with considerable morbidity and mortality as compared with other malignancies. Standard treatment for GBM results in survival of 12.9 months (95% CI: 12.3-13.7 months) with a median progression-free survival of 7.2 months (95% CI: 6.4-8.2 months) in a modern GBM cohort. These aggressive tumors recur and treatment for recurrent GBM continues to have very poor outcomes. Prior to the use of bevacizumab, monoclonal antibody to VEGF, 6-month progression-free survival in clinical trials for recurrent GBM ranged from 9 to 15%. Trials utilizing bevacizumab and its subsequent US FDA approval have given more hope to recurrent GBM and this concise review discusses bevacizumab in recurrent GBM. This review focuses on time-to-event outcomes (overall survival, progression-free survival and 6-month progression-free survival) in clinical trials utilizing bevacizumab for the treatment of recurrent GBM. For this review, we have chosen to focus primarily on Phase II clinical trials that have been published and available in the literature (PubMed). While we focused primarily on time-to-event variables, toxicity and safety of bevacizumab is very important and this agent can be associated with serious life-threatening toxicities. We have included a general section of toxicities but for a more lengthy review please see the excellent study by Odia and colleagues. PMID:25906439
Cytogenetic Study in Couples with Recurrent Miscarriage
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Tarek A. Atia, **Salah E. Mourad*** Salem H
2007-03-01
Full Text Available Introduction: Recurrent miscarriage (RM is a mysterious reproductive problem affecting a proportion of couples trying to conceive. Although spontaneous abortion occurs in approximately 15 to 20% of clinically diagnosed pregnancies of reproductive-aged women, recurrent miscarriage occurs in approximately 1 to 2% of these women. Many syndromes are involved in the aetiology of RM, where genetic factors appear to be highly associated. Indeed, chromosomal anomaly constitutes the single most common cause. About 7% of couples with RM have one partner with balanced chromosomal rearrangement. Aim of the study: This study is a prospective study carried out to evaluate the incidence of chromosomal abnormalities in couples suffering recurrent miscarriage. Patient and methods: The present study included one hundred couples attending the antenatal clinic. They have been divided into two groups; the first, is a study group, included 50 couples with recurrent miscarriage. And the second, is a control group, included 50 couples with normal reproductive history. Conventional cytogenetic analysis was done for both groups. Result: We have found four cases (8% carrying chromosomal rearrangements (two reciprocal translocations, one Robertsonian translocation, and one with duplicated chromosome segment among RM group, and no cases of chromosomal rearrangement among those with normal reproductive history. Statistically, there was a significant association between recurrent miscarriage and chromosomal rearrangement. Conclusion: We have concluded that chromosome analysis is highly important to evaluate such cases with RM
Photodynamic therapy of recurrent cerebral glioma
Zhu, Shu-Gan; Wu, Si-En; Chen, Zong-Qian; Sun, Wei
1993-03-01
Photodynamic therapy (PDT) was performed on 11 cases of recurrent cerebral glioma, including 3 cases of recurrent glioblastoma, 7 of recurrent anaplastic astrocytoma, and 1 recurrent ependymoma. Hematoporphyrin derivative (HPD) was administered intravenously at a dose of 4 - 7 mg/kg 5 - 24 hours before the operation. All patients underwent a craniotomy with a nearly radical excision of the tumor following which the tumor bed was irradiated with 630 nm laser light emitting either an argon pumped dye laser or frequency double YAG pumped dye laser for 30 to 80 minutes with a total dose of 50 J/cm2 (n equals 1), 100 J/cm2 (n equals 2), 200 J/cm2 (n equals 7), and 300 J/cm2 (n equals 1). The temperature was kept below 37 degree(s)C by irrigation. Two patients underwent postoperative radiotherapy. There was no evidence of increased cerebral edema, and no other toxicity by the therapy. All patients were discharged from the hospital within 15 days after surgery. We conclude that PDT using 4 - 7 mg/kg of HPD and 630 nm light with a dose of up to 300 J/cm2 can be used as an adjuvant therapy with no additional complications. Adjuvant PDT in the treatment of recurrent glioma is better than simple surgery.
[Analysis of axillary recurrence after breast reconstruction].
Okishiro, Masatsugu; Egawa, Chiyomi; Ishida, Tomo; Sato, Yasufumi; Morimoto, Yoshihiro; Kusama, Hiroki; Matsushita, Katsunori; Hashimoto, Tadayoshi; Kimura, Kei; Katsura, Yoshiteru; Nitta, Kanae; Kagawa, Yoshinori; Takeno, Atsushi; Sakisaka, Hideki; Nakahira, Shin; Taniguchi, Kazuhiro; Takeda, Yutaka; Kato, Takeshi; Tamura, Shigeyuki; Takatsuka, Yuichi; Asada, Yuji
2014-11-01
In recent years, breast reconstruction is being increasingly performed. Axillary resection is the standard treatment for axillary recurrence after a negative sentinel node (SN) biopsy. Appropriate treatment in the event of a negative SN artifact poses a problem. Case 1: A3 9-year-old woman with right breast cancer underwent Bt+SN (negative)+TE, IMP. Approximately 8 years postoperatively, axillary lymph node recurrence was diagnosed. Axillary resection was performed, and the reconstructed breast was preserved. Case 2: A4 0-year-old woman with right breast cancer underwent Bt+SN (negative)+TE, IMP. Approximately 8 years postoperatively, axillary lymph node recurrence was diagnosed. Axillary resection was performed, and the reconstructed breast was preserved. Case 3: A5 7-year-old woman with right breast cancer underwent Bt+SN (negative)+ TE, IMP. Because the metastatic lymph node was near the reconstructed breast, axillary resection and removal of the reconstructed breast was performed. It is expected that the incidence of axillary lymph node recurrence after breast reconstruction will increase in the future. For axillary lymph node recurrence, surgical resection needs to be performed to achieve a complete recovery. Therefore, it may be necessary to perform surgery without preserving the reconstructed breast. PMID:25731375
Recurrent glomerular disease in the kidney allograft.
Menn-Josephy, Hanni; Beck, Laurence H
2015-01-01
Glomerulonephritis is responsible for nearly 15% of prevalent end-stage renal disease, and many of these patients will receive kidney transplants with the potential for a long duration of allograft survival. Recurrent glomerular disease, however, is not uncommon and can lead to both substantial morbidity and/or loss of the kidney allograft. The timing of recurrence after transplantation as well as the prevalence of recurrent disease vary by study, especially accounting for differences in protocol versus clinically-indicated biopsies, the use of immunofluorescence or electron microscopy in histopathological evaluation, and length of follow-up. Transplant immunosuppression alone may be sufficient to keep some recurrent disease in a subclinical form, whereas other recurrent glomerular diseases may be clinically evident and progress to threaten the allograft. This review highlights the epidemiology, diagnosis, and treatment of five common glomerular diseases that may recur in the transplant: focal and segmental glomerulosclerosis (FSGS), membranous nephropathy (MN), membranoproliferative glomerulonephritis (MPGN), immunoglobulin A nephropathy (IgAN), and lupus nephritis (LN). PMID:25553369
Pain recurrence after shaving of rectovaginal endometriosis
DEFF Research Database (Denmark)
Heide, Mathias Gottschalck; Forman, Axel
Background: Surgical treatment of rectovaginal endometriosis varies from shaving of the nodule off the rectal wall without perforation, over discoid excision to routine rectal resection. Of these methods, shaving involves the lowest rate of serious complications but leaves endometriosis tissue on the bowel with risk of recurrence. This could motivate a change into more radical surgery. In the present study we therefore assessed recurrence of pain after shaving of rectovaginal endometriosis performed 2001-2009. Methods: Retrospective follow-up study. Questionnaires were sent to 212 women of whom 174 women (82%) responded. Outcomes were correlated to the involvement of the anterior rectal wall and postoperative hormonal treatment. Results: Recurrence (pain unchanged or worse) of menstrual pain was found in 26 %, intermenstrual pain in 29 %, dyspareunia in 42 % and dyschezia in 41 %. Postoperative OCs and gestagen IUD showed a trend towards a protective effect against menstrual pain (p=0.06). There was foundno significant association between recurrence of pain and anterior rectal wall involvement. Conclusion: Shaving of rectovaginal endometriosis shows a high risk of postoperative pain recurrence, especially for dyspareunia and dyschezia. Routine postoperative hormonal treatment seems of value. Research into new surgical methods is motivated.
Recurrence quantification analysis of global stock markets
Bastos, João A.; Caiado, Jorge
2011-04-01
This study investigates the presence of deterministic dependencies in international stock markets using recurrence plots and recurrence quantification analysis (RQA). The results are based on a large set of free float-adjusted market capitalization stock indices, covering a period of 15 years. The statistical tests suggest that the dynamics of stock prices in emerging markets is characterized by higher values of RQA measures when compared to their developed counterparts. The behavior of stock markets during critical financial events, such as the burst of the technology bubble, the Asian currency crisis, and the recent subprime mortgage crisis, is analyzed by performing RQA in sliding windows. It is shown that during these events stock markets exhibit a distinctive behavior that is characterized by temporary decreases in the fraction of recurrence points contained in diagonal and vertical structures.
RECURRENT SUBCLITORAL ABSCESS TREATED BY MARSUPIALIZATION
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HORMOZ DABIRASHRAFI
1986-05-01
Full Text Available This is a report of a very rare case of recurrent subclitoral abscess. Its etiology and the best treatment of the disease is here in discussed. We, the same as Sur, believe that marsupialization is the most promising treatment. Recurrent periclitoral abscess has been described previously5. s ome of the authors believe that it is part of the pilonidal disease. The first pilonidal cyst in 7 the clitoral region was introduced by Palmer (1957."nAnother case of pilonidal sinus of clitoris was repor-2 ted by Betson . All of the researchers are not in this opinion that the disease is necessarily a pilonidal sinus 1 3,and, sometimes, there is not any hair in the epithelium lining of the cyst. One case of recurrent subclitoral abscess treated by marsupialization is presented here.
CHROMOSOMAL ABNORMALITIES IN PATIENTS WITH RECURRENT MISCARRIAGE
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Veronica Stoian
2012-06-01
Full Text Available Chromosomal abnormalities are involved in the etiology of recurrent spontaneous pregnancy loss and sub-fertility. The purpose of this study was to determine the frequency and contribution of chromosomal abnormalities in recurrent miscarriages. The results obtained and literature review are helpful in understanding the importance of cytogenetics analysis of female infertility. To investigate the distribution of chromosomal abnormalities in the Romanian population with recurrent miscarriage, karyotype analysis by G-banding was performed from peripheral blood in 967 women infertility. Results: Chromosomal abnormalities were found to 79 women (8,17%. The percentage of chromosomal abnormalities in the studied population correlates with the data in the literature. Chromosomal abnormalities could play the important role in etiology of infertility and are more frequently detected in this group of patients compared to general population. In the infertile couples balanced chromosomal abnormalities are the main cause of spontaneous abortions.
Recurrent intramedullary epidermoid cyst of conus medullaris.
LENUS (Irish Health Repository)
Fleming, Christina
2011-01-01
Spinal intramedullary epidermoid cyst is a rare condition. Recurrent epidermoid cyst in the spine cord is known to occur. The authors describe a case of recurrent conus medullaris epidermoid cyst in a 24-year-old female. She initially presented at 7 years of age with bladder disturbance in the form of diurnal enuresis and recurrent urinary tract infection. MRI lumbar spine revealed a 4 cm conus medullaris epidermoid cyst. Since the initial presentation, the cyst had recurred seven times in the same location and she underwent surgical intervention in the form of exploration and debulking. This benign condition, owing to its anatomical location, has posed a surgical and overall management challenge. This occurrence is better managed in a tertiary-care centre requiring multi-disciplinary treatment approach.
Acute recurrent pancreatitis: An autoimmune disease?
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Raffaele Pezzilli
2008-02-01
Full Text Available In this review article, we will briefly describe the main characteristics of autoimmune pancreatitis and then we will concentrate on our aim, namely, evaluating the clinical characteristics of patients having recurrence of pain from the disease. In fact, the open question is to evaluate the possible presence of autoimmune pancreatitis in patients with an undefined etiology of acute pancreatitis and for this reason we carried out a search in the literature in order to explore this issue. In cases of recurrent attacks of pain in patients with “diopathic”pancreatitis, we need to keep in mind the possibility that our patients may have autoimmune pancreatitis. Even though the frequency of this disease seems to be quite low, we believe that in the future, by increasing our knowledge on the subject, we will be able to diagnose an ever-increasing number of patients having acute recurrence of pain from autoimmune pancreatitis.
High-Density Stretchable Electronics: Toward an Integrated Multilayer Composite
Guo, Liang; Deweerth, Stephen P.
2010-01-01
High-density stretchable electronics is achieved using multilayer interconnects on an elastomeric substrate. Two major challenges associated with stretchable electronics—increasing integration density and improving electrical bonding—have been addressed by our innovative multilayer via-bonding technology. The resulting multichip-module architecture provides an elastic, high-density solution for numerous potential applications.
Heat stability evaluations of Co/SiO2 multilayers
International Nuclear Information System (INIS)
The heat stability of Co/SiO2 multilayers was evaluated. Co/SiO2 multilayer samples were deposited on Si substrate by means of an ion beam sputtering method, and annealed at temperatures from 100degC to 600degC in a vacuum furnace. For the structural and optical evaluations, small angle x-ray diffraction (XRD) measurements, soft x-ray reflectivity measurements, and transmission electron microscopy (TEM) observations were carried out. As the results, the Co/SiO2 multilayer samples annealed up to 400degC maintained the initial multilayer structures, and kept almost the same soft x-ray reflectivities as that of the as-deposited Co/SiO2 multilayer sample. A deterioration of the multilayer structure caused by the growth of Co grains was found on the Co/SiO2 multilayer samples annealed over 500degC, and the soft x-ray reflectivity dropped in accordance with the deterioration of the multilayer structure. (author)
Multilayer, Front-Contact Grid for Solar Cells
Milnes, A. G.; Flat, A.
1982-01-01
Proposed multilayer, front-contact grid structure for solar cells optimizes collection of photogenerated current with minimum power losses. It is constructed of several layers of conducting grids. With multilayer concept, peak efficiency can occur at higher output-power levels. Because of this, higher solar concentrations can be applied to solar-cell arrays.
A refined model for characterizing x-ray multilayers
International Nuclear Information System (INIS)
The ability to quickly and accurately characterize arbitrary multilayers is very valuable for not only can we use the characterizations to predict the reflectivity of a multilayer for any soft x-ray wavelength, we also can generalize the results to apply to other multilayers of the same type. In addition, we can use the characterizations as a means of evaluating various sputtering environments and refining sputtering techniques to obtain better multilayers. In this report we have obtained improved characterizations for sample molybdenum-silicon and vanadium-silicon multilayers. However, we only examined five crystals overall, so the conclusions that we could draw about the structure of general multilayers is limited. Research involving many multilayers manufactured under the same sputtering conditions is clearly in order. In order to best understand multilayer structures it may be necessary to further refine our model, e.g., adopting a Gaussian form for the interface regions. With such improvements we can expect even better agreement with experimental values and continued concurrence with other characterization techniques. 18 refs., 30 figs., 7 tabs
On the periods of generalized Fibonacci recurrences
Brent, Richard P
2010-01-01
We give a simple condition for a linear recurrence (mod 2^w) of degree r to have the maximal possible period 2^(w-1).(2^r-1). It follows that the period is maximal in the cases of interest for pseudo-random number generation, i.e. for 3-term linear recurrences defined by trinomials which are primitive (mod 2) and of degree r > 2. We consider the enumeration of certain exceptional polynomials which do not give maximal period, and list all such polynomials of degree less than 15.
RECURRENT SUBCLITORAL ABSCESS TREATED BY MARSUPIALIZATION
HORMOZ DABIRASHRAFI; SIMIN KAMYAB TEHRANY
1986-01-01
This is a report of a very rare case of recurrent subclitoral abscess. Its etiology and the best treatment of the disease is here in discussed. We, the same as Sur, believe that marsupialization is the most promising treatment. Recurrent periclitoral abscess has been described previously5. s ome of the authors believe that it is part of the pilonidal disease. The first pilonidal cyst in 7 the clitoral region was introduced by Palmer (1957)."nAnother case of pilonidal sinus of clitoris wa...
Mining Recurrent Pattern Identification on Large Database
Shivangi Srivastava; Ganesh Khadanga; Divya Gupta
2014-01-01
Recurrent pattern mining is an important problem in the context of data mining. In this paper data mining algorithms have been discussed and compared. Recurrent pattern mining has been an important area in data mining research and it is the first step in the analysis of data rising in a broad range of applications. The algorithms are compared with respect to the items like methodology and its basic principles in terms of the elements user like support, and scan of the database (full or parti...
Recurrent pregnancy loss: evaluation and treatment.
Shahine, Lora; Lathi, Ruth
2015-03-01
Recurrent pregnancy loss (RPL) is a multifactorial condition. Approximately half of patients with RPL will have no explanation for their miscarriages. De novo chromosome abnormalities are common in sporadic and recurrent pregnancy loss. Testing for embryonic abnormalities can provide an explanation for the miscarriage in many cases and prognostic information. Regardless of the cause of RPL, patients should be reassured that the prognosis for live birth with an evidence-based approach is excellent for most patients. The authors review current evidence for the evaluation and treatment of RPL and explore the proposed use of newer technology for patients with RPL. PMID:25681844
Mining Recurrent Pattern Identification on Large Database
Directory of Open Access Journals (Sweden)
Shivangi Srivastava
2014-04-01
Full Text Available Recurrent pattern mining is an important problem in the context of data mining. In this paper data mining algorithms have been discussed and compared. Recurrent pattern mining has been an important area in data mining research and it is the first step in the analysis of data rising in a broad range of applications. The algorithms are compared with respect to the items like methodology and its basic principles in terms of the elements user like support, and scan of the database (full or partial.
Dipole radiation in a multilayer geometry
International Nuclear Information System (INIS)
There are several kinds of experiments that can be done with multilayer stacks of dielectric media which require an understanding of light emission by sources within the stack for their analysis. These experiments may involve, for example, light-emitting tunnel junctions, Raman scattering in Kretschmann and other multilayered geometries, and Rayleigh scattering by small amounts of surface or interface roughness, either alone or in combination with other processes. A set of electromagnetic Green's functions for a multilayer stack of isotropic dielectric media [D. L. Mills and A. A. Maradudin, Phys. Rev. B 12, 2943 (1975)] gives the electric fields produced everywhere by a point source of current oscillating at a frequency f. These Green's functions can thus be used to solve this type of problem. In this paper we show how these Green's functions can be written in terms of 2 x 2 transfer matrices of the type commonly used to find the fields in a dielectric stack due to an incident plane wave. With this simplification we can easily evaluate the Green's functions for a stack with an arbitrary number of layers. We further show that, when the electric fields generated by a point source within the stack are evaluated far away, they can be written directly in terms of the electric fields that would be generated at the location of the current source by plane waves incident from the direction of the observation point. We show that this follows from the Lorentz reciprocity theoreollows from the Lorentz reciprocity theorem. Thus, in this case the formalism of Green's functions is not needed
Tactile display with dielectric multilayer elastomer actuatorsq
Matysek, Marc; Lotz, Peter; Schlaak, Helmut F.
2009-03-01
Tactile perception is the human sensation of surface textures through the vibrations generated by stroking a finger over the surface. The skin responds to several distributed physical quantities. Perhaps the most important are high-frequency vibrations, pressure distributions (static shape) and thermal properties. The integration of tactile displays in man-machine interfaces promises a more intuitive handling. For this reason many tactile displays are developed using different technologies. We present several state-of-the-art tactile displays based on different types of dielectric elastomer actuators to clarify the advantages of our matrix display based on multilayer technology. Using this technology perpendicular and hexagonal arrays of actuator elements (tactile stimulators) can be integrated into a PDMS substrate. Element diameters down to 1 mm allow stimuli at the range of the human two-point-discrimination threshold. Driving the elements by column and row addressing enables various stimulation patterns with a reduced number of feeding lines. The transient analysis determines charging times of the capacitive actuators depending on actuator geometry and material parameters. This is very important to ensure an adequate dynamic characteristic of the actuators to stimulate the human skin by vibrations. The suitability of multilayer dielectric elastomer actuators for actuation in tactile displays has been determined. Beside the realization of a static tactile display - where multilayer DEA are integrated as drives for movable contact pins - we focus on the direct use of DEA as a vibrotactile display. Finally, we present the scenario and achieved results of a recognition threshold test. Even relative low voltages in the range of 800 V generate vibrations with 100% recognition ratio within the group of participants. Furthermore, the frequency dependent characteristic of the determined recognition threshold confirms with established literature.
Clustering Network Layers With the Strata Multilayer Stochastic Block Model
Stanley, Natalie; Taylor, Dane; Mucha, Peter J
2015-01-01
Multilayer networks are a useful data structure for simultaneously capturing multiple types of relationships between a set of nodes. In such networks, each relational definition gives rise to a layer. While each layer provides its own set of information, community structure can be collectively utilized to discover and quantify underlying relational patterns. To most concisely extract information from a multilayer network, we propose to identify and combine sets of layers with meaningful similarities in community structure. In this paper, we describe the strata multilayer stochastic block model (sMLSBM), a probabilistic model for multilayer community structure. The assumption of the model is that there exist groups of layers, that we call strata, with community structure described by a common stochastic block model (SBM). That is, layers in a stratum exhibit similar node-to-community assignments as well as SBM probability parameters. Fitting the sMLSBM to a multilayer network provides a joint clustering of nod...
Simulation of X-ray scattering from multilayers
International Nuclear Information System (INIS)
This paper describes basic methods for the simulation of X-ray scattering from ideal and non-ideal multilayers. In the 1 D model the kinematical and dynamical calculation is made with several kinds of disturbances of the ideal structure of the multilayers. We shall discuss the influence of surface roughness, interdiffusion between layers and fluctuation of thickness in the multilayer. In the second part some ideas are given to get non-specular scattering simulations of disturbed multilayer structures in a 2 D model. Although this is a well-known subject and has been treated several times in the last years, it is really fruitful to do the basic steps for this topic, because it can give you a deep insight into the physics of a travelling wave inside a multilayer. (author) 26 figs., 1 tab., 4 refs
Swift ion irradiation of magnetostrictive multilayers
International Nuclear Information System (INIS)
The modification of the magnetic and magnetostrictive properties of TbFe2/Co exchange-coupled multilayers irradiated with 700 MeV Pb ions was investigated as a function of ion fluence. After irradiation, the magnetostrictive properties of the sample are first strongly improved up to a fluence of 1 x 1012 ions cm-2 where the magnetoelastic susceptibility is six times higher than for the as-deposited sample. This effect is ascribed to stress relaxation and Fe-Co intermixing at the interfaces. For higher fluences, the magnetostrictive properties do not vary further, indicating a stationary state of mixing