Classification VIA Information-Theoretic Fusion of Vector-Magnetic and Acoustic Sensor Data
2007-04-01
10) where tBsBtBsBtBsBtsB zzyyxx, . (11) The operation in (10) may be viewed as a vector matched- filter on to estimate )(tB CPARv . In summary...choosing to maximize the classification information in Y are described in Section 3.2. A 3.2. Maximum mutual information ( MMI ) features We begin with a...review of several desirable properties of features that maximize a mutual information ( MMI ) criterion. Then we review a particular algorithm [2
Holographic mutual information of two disjoint spheres
NASA Astrophysics Data System (ADS)
Chen, Bin; Fan, Zhong-Ying; Li, Wen-Ming; Zhang, Cheng-Yong
2018-04-01
We study quantum corrections to holographic mutual information for two disjoint spheres at a large separation by using the operator product expansion of the twist field. In the large separation limit, the holographic mutual information is vanishing at the semiclassical order, but receive quantum corrections from the fluctuations. We show that the leading contributions from the quantum fluctuations take universal forms as suggested from the boundary CFT. We find the universal behavior for the scalar, the vector, the tensor and the fermionic fields by treating these fields as free fields propagating in the fixed background and by using the 1 /n prescription. In particular, for the fields with gauge symmetries, including the massless vector boson and massless graviton, we find that the gauge parts in the propagators play an indispensable role in reading the leading order corrections to the bulk mutual information.
NASA Astrophysics Data System (ADS)
Xiangfeng, Zhang; Hong, Jiang
2018-03-01
In this paper, the full vector LCD method is proposed to solve the misjudgment problem caused by the change of the working condition. First, the signal from different working condition is decomposed by LCD, to obtain the Intrinsic Scale Component (ISC)whose instantaneous frequency with physical significance. Then, calculate of the cross correlation coefficient between ISC and the original signal, signal denoising based on the principle of mutual information minimum. At last, calculate the sum of absolute Vector mutual information of the sample under different working condition and the denoised ISC as the characteristics to classify by use of Support vector machine (SVM). The wind turbines vibration platform gear box experiment proves that this method can identify fault characteristics under different working conditions. The advantage of this method is that it reduce dependence of man’s subjective experience, identify fault directly from the original data of vibration signal. It will has high engineering value.
Spatial Mutual Information Based Hyperspectral Band Selection for Classification
2015-01-01
The amount of information involved in hyperspectral imaging is large. Hyperspectral band selection is a popular method for reducing dimensionality. Several information based measures such as mutual information have been proposed to reduce information redundancy among spectral bands. Unfortunately, mutual information does not take into account the spatial dependency between adjacent pixels in images thus reducing its robustness as a similarity measure. In this paper, we propose a new band selection method based on spatial mutual information. As validation criteria, a supervised classification method using support vector machine (SVM) is used. Experimental results of the classification of hyperspectral datasets show that the proposed method can achieve more accurate results. PMID:25918742
Mutually orthogonal Latin squares from the inner products of vectors in mutually unbiased bases
NASA Astrophysics Data System (ADS)
Hall, Joanne L.; Rao, Asha
2010-04-01
Mutually unbiased bases (MUBs) are important in quantum information theory. While constructions of complete sets of d + 1 MUBs in {\\bb C}^d are known when d is a prime power, it is unknown if such complete sets exist in non-prime power dimensions. It has been conjectured that complete sets of MUBs only exist in {\\bb C}^d if a maximal set of mutually orthogonal Latin squares (MOLS) of side length d also exists. There are several constructions (Roy and Scott 2007 J. Math. Phys. 48 072110; Paterek, Dakić and Brukner 2009 Phys. Rev. A 79 012109) of complete sets of MUBs from specific types of MOLS, which use Galois fields to construct the vectors of the MUBs. In this paper, two known constructions of MUBs (Alltop 1980 IEEE Trans. Inf. Theory 26 350-354 Wootters and Fields 1989 Ann. Phys. 191 363-381), both of which use polynomials over a Galois field, are used to construct complete sets of MOLS in the odd prime case. The MOLS come from the inner products of pairs of vectors in the MUBs.
Learning dependence from samples.
Seth, Sohan; Príncipe, José C
2014-01-01
Mutual information, conditional mutual information and interaction information have been widely used in scientific literature as measures of dependence, conditional dependence and mutual dependence. However, these concepts suffer from several computational issues; they are difficult to estimate in continuous domain, the existing regularised estimators are almost always defined only for real or vector-valued random variables, and these measures address what dependence, conditional dependence and mutual dependence imply in terms of the random variables but not finite realisations. In this paper, we address the issue that given a set of realisations in an arbitrary metric space, what characteristic makes them dependent, conditionally dependent or mutually dependent. With this novel understanding, we develop new estimators of association, conditional association and interaction association. Some attractive properties of these estimators are that they do not require choosing free parameter(s), they are computationally simpler, and they can be applied to arbitrary metric spaces.
A Search for Strange Attractors in the Saturation of Middle Atmosphere Gravity Waves
1990-09-01
Fraser, A. M. and H. L. Swinney, 1986: Independent coordinates for strange attractors from mutual information . Phvs. Rev. A, 33, 1134-1140. Fraser...vectors implies that the two are linearly independent . However, data characterized by a strange attractor are usually highly nonlinear, thus making...noise in this data set. The degree of autocorrelation and the lack of general independence as determined from the mutual information also reduces the
DOE Office of Scientific and Technical Information (OSTI.GOV)
Alpatov, A. V.; Vikhrov, S. P.; Rybina, N. V., E-mail: pgnv@mail.ru
The processes of self-organization of the surface structure of hydrogenated amorphous silicon are studied by the methods of fluctuation analysis and average mutual information on the basis of atomic-force-microscopy images of the surface. It is found that all of the structures can be characterized by a correlation vector and represented as a superposition of harmonic components and noise. It is shown that, under variations in the technological parameters of the production of a-Si:H films, the correlation properties of their structure vary as well. As the substrate temperature is increased, the formation of structural irregularities becomes less efficient; in this case,more » the length of the correlation vector and the degree of structural ordering increase. It is shown that the procedure based on the method of fluctuation analysis in combination with the method of average mutual information provides a means for studying the self-organization processes in any structures on different length scales.« less
NASA Astrophysics Data System (ADS)
Pahlavani, Parham; Bigdeli, Behnaz
2017-12-01
Hyperspectral images contain extremely rich spectral information that offer great potential to discriminate between various land cover classes. However, these images are usually composed of tens or hundreds of spectrally close bands, which result in high redundancy and great amount of computation time in hyperspectral classification. Furthermore, in the presence of mixed coverage pixels, crisp classifiers produced errors, omission and commission. This paper presents a mutual information-Dempster-Shafer system through an ensemble classification approach for classification of hyperspectral data. First, mutual information is applied to split data into a few independent partitions to overcome high dimensionality. Then, a fuzzy maximum likelihood classifies each band subset. Finally, Dempster-Shafer is applied to fuse the results of the fuzzy classifiers. In order to assess the proposed method, a crisp ensemble system based on a support vector machine as the crisp classifier and weighted majority voting as the crisp fusion method are applied on hyperspectral data. Furthermore, a dimension reduction system is utilized to assess the effectiveness of mutual information band splitting of the proposed method. The proposed methodology provides interesting conclusions on the effectiveness and potentiality of mutual information-Dempster-Shafer based classification of hyperspectral data.
Elman RNN based classification of proteins sequences on account of their mutual information.
Mishra, Pooja; Nath Pandey, Paras
2012-10-21
In the present work we have employed the method of estimating residue correlation within the protein sequences, by using the mutual information (MI) of adjacent residues, based on structural and solvent accessibility properties of amino acids. The long range correlation between nonadjacent residues is improved by constructing a mutual information vector (MIV) for a single protein sequence, like this each protein sequence is associated with its corresponding MIVs. These MIVs are given to Elman RNN to obtain the classification of protein sequences. The modeling power of MIV was shown to be significantly better, giving a new approach towards alignment free classification of protein sequences. We also conclude that sequence structural and solvent accessible property based MIVs are better predictor. Copyright © 2012 Elsevier Ltd. All rights reserved.
Estimation and classification by sigmoids based on mutual information
NASA Technical Reports Server (NTRS)
Baram, Yoram
1994-01-01
An estimate of the probability density function of a random vector is obtained by maximizing the mutual information between the input and the output of a feedforward network of sigmoidal units with respect to the input weights. Classification problems can be solved by selecting the class associated with the maximal estimated density. Newton's s method, applied to an estimated density, yields a recursive maximum likelihood estimator, consisting of a single internal layer of sigmoids, for a random variable or a random sequence. Applications to the diamond classification and to the prediction of a sun-spot process are demonstrated.
Aspects of mutually unbiased bases in odd-prime-power dimensions
NASA Astrophysics Data System (ADS)
Chaturvedi, S.
2002-04-01
We rephrase the Wootters-Fields construction [W. K. Wootters and B. C. Fields, Ann. Phys. 191, 363 (1989)] of a full set of mutually unbiased bases in a complex vector space of dimensions N=pr, where p is an odd prime, in terms of the character vectors of the cyclic group G of order p. This form may be useful in explicitly writing down mutually unbiased bases for N=pr.
SIC-POVMS and MUBS: Geometrical Relationships in Prime Dimension
NASA Astrophysics Data System (ADS)
Appleby, D. M.
2009-03-01
The paper concerns Weyl-Heisenberg covariant SIC-POVMs (symmetric informationally complete positive operator valued measures) and full sets of MUBs (mutually unbiased bases) in prime dimension. When represented as vectors in generalized Bloch space a SIC-POVM forms a d2-1 dimensional regular simplex (d being the Hilbert space dimension). By contrast, the generalized Bloch vectors representing a full set of MUBs form d+1 mutually orthogonal d-1 dimensional regular simplices. In this paper we show that, in the Weyl-Heisenberg case, there are some simple geometrical relationships between the single SIC-POVM simplex and the d+1 MUB simplices. We go on to give geometrical interpretations of the minimum uncertainty states introduced by Wootters and Sussman, and by Appleby, Dang and Fuchs, and of the fiduciality condition given by Appleby, Dang and Fuchs.
NASA Astrophysics Data System (ADS)
Klappenecker, Andreas; Rötteler, Martin; Shparlinski, Igor E.; Winterhof, Arne
2005-08-01
We address the problem of constructing positive operator-valued measures (POVMs) in finite dimension n consisting of n2 operators of rank one which have an inner product close to uniform. This is motivated by the related question of constructing symmetric informationally complete POVMs (SIC-POVMs) for which the inner products are perfectly uniform. However, SIC-POVMs are notoriously hard to construct and, despite some success of constructing them numerically, there is no analytic construction known. We present two constructions of approximate versions of SIC-POVMs, where a small deviation from uniformity of the inner products is allowed. The first construction is based on selecting vectors from a maximal collection of mutually unbiased bases and works whenever the dimension of the system is a prime power. The second construction is based on perturbing the matrix elements of a subset of mutually unbiased bases. Moreover, we construct vector systems in Cn which are almost orthogonal and which might turn out to be useful for quantum computation. Our constructions are based on results of analytic number theory.
Katz, Matthew L.; Viney, Tim J.; Nikolic, Konstantin
2016-01-01
Sensory stimuli are encoded by diverse kinds of neurons but the identities of the recorded neurons that are studied are often unknown. We explored in detail the firing patterns of eight previously defined genetically-identified retinal ganglion cell (RGC) types from a single transgenic mouse line. We first introduce a new technique of deriving receptive field vectors (RFVs) which utilises a modified form of mutual information (“Quadratic Mutual Information”). We analysed the firing patterns of RGCs during presentation of short duration (~10 second) complex visual scenes (natural movies). We probed the high dimensional space formed by the visual input for a much smaller dimensional subspace of RFVs that give the most information about the response of each cell. The new technique is very efficient and fast and the derivation of novel types of RFVs formed by the natural scene visual input was possible even with limited numbers of spikes per cell. This approach enabled us to estimate the 'visual memory' of each cell type and the corresponding receptive field area by calculating Mutual Information as a function of the number of frames and radius. Finally, we made predictions of biologically relevant functions based on the RFVs of each cell type. RGC class analysis was complemented with results for the cells’ response to simple visual input in the form of black and white spot stimulation, and their classification on several key physiological metrics. Thus RFVs lead to predictions of biological roles based on limited data and facilitate analysis of sensory-evoked spiking data from defined cell types. PMID:26845435
Misra, Sanchit; Pamnany, Kiran; Aluru, Srinivas
2015-01-01
Construction of whole-genome networks from large-scale gene expression data is an important problem in systems biology. While several techniques have been developed, most cannot handle network reconstruction at the whole-genome scale, and the few that can, require large clusters. In this paper, we present a solution on the Intel Xeon Phi coprocessor, taking advantage of its multi-level parallelism including many x86-based cores, multiple threads per core, and vector processing units. We also present a solution on the Intel® Xeon® processor. Our solution is based on TINGe, a fast parallel network reconstruction technique that uses mutual information and permutation testing for assessing statistical significance. We demonstrate the first ever inference of a plant whole genome regulatory network on a single chip by constructing a 15,575 gene network of the plant Arabidopsis thaliana from 3,137 microarray experiments in only 22 minutes. In addition, our optimization for parallelizing mutual information computation on the Intel Xeon Phi coprocessor holds out lessons that are applicable to other domains.
Feature Selection for Chemical Sensor Arrays Using Mutual Information
Wang, X. Rosalind; Lizier, Joseph T.; Nowotny, Thomas; Berna, Amalia Z.; Prokopenko, Mikhail; Trowell, Stephen C.
2014-01-01
We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays. PMID:24595058
Mutual information-based facial expression recognition
NASA Astrophysics Data System (ADS)
Hazar, Mliki; Hammami, Mohamed; Hanêne, Ben-Abdallah
2013-12-01
This paper introduces a novel low-computation discriminative regions representation for expression analysis task. The proposed approach relies on interesting studies in psychology which show that most of the descriptive and responsible regions for facial expression are located around some face parts. The contributions of this work lie in the proposition of new approach which supports automatic facial expression recognition based on automatic regions selection. The regions selection step aims to select the descriptive regions responsible or facial expression and was performed using Mutual Information (MI) technique. For facial feature extraction, we have applied Local Binary Patterns Pattern (LBP) on Gradient image to encode salient micro-patterns of facial expressions. Experimental studies have shown that using discriminative regions provide better results than using the whole face regions whilst reducing features vector dimension.
Kumar, Shiu; Sharma, Alok; Tsunoda, Tatsuhiko
2017-12-28
Common spatial pattern (CSP) has been an effective technique for feature extraction in electroencephalography (EEG) based brain computer interfaces (BCIs). However, motor imagery EEG signal feature extraction using CSP generally depends on the selection of the frequency bands to a great extent. In this study, we propose a mutual information based frequency band selection approach. The idea of the proposed method is to utilize the information from all the available channels for effectively selecting the most discriminative filter banks. CSP features are extracted from multiple overlapping sub-bands. An additional sub-band has been introduced that cover the wide frequency band (7-30 Hz) and two different types of features are extracted using CSP and common spatio-spectral pattern techniques, respectively. Mutual information is then computed from the extracted features of each of these bands and the top filter banks are selected for further processing. Linear discriminant analysis is applied to the features extracted from each of the filter banks. The scores are fused together, and classification is done using support vector machine. The proposed method is evaluated using BCI Competition III dataset IVa, BCI Competition IV dataset I and BCI Competition IV dataset IIb, and it outperformed all other competing methods achieving the lowest misclassification rate and the highest kappa coefficient on all three datasets. Introducing a wide sub-band and using mutual information for selecting the most discriminative sub-bands, the proposed method shows improvement in motor imagery EEG signal classification.
Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification
1999-05-17
Experimental Results In this section, we compare kNN -mut which uses the weight vector obtained using mutual information as the fi- nal weight vector and...WAKNN against kNN , C4.5 [Qui93], RIPPER [Coh95], PEBLS [CS93], Rainbow [McC96], VSM [Low95] on several synthetic and real data sets. VSM is another k...obtained without this option. 3 C4.5 RIPPER PEBLS Rainbow kNN WAKNN Syn-1 100.0 100.0 100.0 100.0 77.3 100.0 Syn-2 67.5 69.5 62.0 50.0 66.0 68.8 Syn
Li, Ran; Weldegergis, Berhane T.; Li, Jie; Jung, Choonkyun; Qu, Jing; Sun, Yanwei; Qian, Hongmei; Tee, ChuanSia; van Loon, Joop J.A.; Dicke, Marcel; Chua, Nam-Hai; Liu, Shu-Sheng
2014-01-01
A pathogen may cause infected plants to promote the performance of its transmitting vector, which accelerates the spread of the pathogen. This positive effect of a pathogen on its vector via their shared host plant is termed indirect mutualism. For example, terpene biosynthesis is suppressed in begomovirus-infected plants, leading to reduced plant resistance and enhanced performance of the whiteflies (Bemisia tabaci) that transmit these viruses. Although begomovirus-whitefly mutualism has been known, the underlying mechanism is still elusive. Here, we identified βC1 of Tomato yellow leaf curl China virus, a monopartite begomovirus, as the viral genetic factor that suppresses plant terpene biosynthesis. βC1 directly interacts with the basic helix-loop-helix transcription factor MYC2 to compromise the activation of MYC2-regulated terpene synthase genes, thereby reducing whitefly resistance. MYC2 associates with the bipartite begomoviral protein BV1, suggesting that MYC2 is an evolutionarily conserved target of begomoviruses for the suppression of terpene-based resistance and the promotion of vector performance. Our findings describe how this viral pathogen regulates host plant metabolism to establish mutualism with its insect vector. PMID:25490915
Orbits of Two-Body Problem From the Lenz Vector
ERIC Educational Resources Information Center
Caplan, S.; And Others
1978-01-01
Obtains the orbits with reference to the center of mass of two bodies under mutual universe square law interaction by use of the eccentricity vector which is equivalent to the Lenz vector within a numerical factor. (Author/SL)
Graph-state formalism for mutually unbiased bases
NASA Astrophysics Data System (ADS)
Spengler, Christoph; Kraus, Barbara
2013-11-01
A pair of orthonormal bases is called mutually unbiased if all mutual overlaps between any element of one basis and an arbitrary element of the other basis coincide. In case the dimension, d, of the considered Hilbert space is a power of a prime number, complete sets of d+1 mutually unbiased bases (MUBs) exist. Here we present a method based on the graph-state formalism to construct such sets of MUBs. We show that for n p-level systems, with p being prime, one particular graph suffices to easily construct a set of pn+1 MUBs. In fact, we show that a single n-dimensional vector, which is associated with this graph, can be used to generate a complete set of MUBs and demonstrate that this vector can be easily determined. Finally, we discuss some advantages of our formalism regarding the analysis of entanglement structures in MUBs, as well as experimental realizations.
Feature and Intensity Based Medical Image Registration Using Particle Swarm Optimization.
Abdel-Basset, Mohamed; Fakhry, Ahmed E; El-Henawy, Ibrahim; Qiu, Tie; Sangaiah, Arun Kumar
2017-11-03
Image registration is an important aspect in medical image analysis, and kinds use in a variety of medical applications. Examples include diagnosis, pre/post surgery guidance, comparing/merging/integrating images from multi-modal like Magnetic Resonance Imaging (MRI), and Computed Tomography (CT). Whether registering images across modalities for a single patient or registering across patients for a single modality, registration is an effective way to combine information from different images into a normalized frame for reference. Registered datasets can be used for providing information relating to the structure, function, and pathology of the organ or individual being imaged. In this paper a hybrid approach for medical images registration has been developed. It employs a modified Mutual Information (MI) as a similarity metric and Particle Swarm Optimization (PSO) method. Computation of mutual information is modified using a weighted linear combination of image intensity and image gradient vector flow (GVF) intensity. In this manner, statistical as well as spatial image information is included into the image registration process. Maximization of the modified mutual information is effected using the versatile Particle Swarm Optimization which is developed easily with adjusted less parameter. The developed approach has been tested and verified successfully on a number of medical image data sets that include images with missing parts, noise contamination, and/or of different modalities (CT, MRI). The registration results indicate the proposed model as accurate and effective, and show the posture contribution in inclusion of both statistical and spatial image data to the developed approach.
Bipartite entangled stabilizer mutually unbiased bases as maximum cliques of Cayley graphs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dam, Wim van; Howard, Mark; Department of Physics, University of California, Santa Barbara, California 93106
2011-07-15
We examine the existence and structure of particular sets of mutually unbiased bases (MUBs) in bipartite qudit systems. In contrast to well-known power-of-prime MUB constructions, we restrict ourselves to using maximally entangled stabilizer states as MUB vectors. Consequently, these bipartite entangled stabilizer MUBs (BES MUBs) provide no local information, but are sufficient and minimal for decomposing a wide variety of interesting operators including (mixtures of) Jamiolkowski states, entanglement witnesses, and more. The problem of finding such BES MUBs can be mapped, in a natural way, to that of finding maximum cliques in a family of Cayley graphs. Some relationships withmore » known power-of-prime MUB constructions are discussed, and observables for BES MUBs are given explicitly in terms of Pauli operators.« less
Bipartite entangled stabilizer mutually unbiased bases as maximum cliques of Cayley graphs
NASA Astrophysics Data System (ADS)
van Dam, Wim; Howard, Mark
2011-07-01
We examine the existence and structure of particular sets of mutually unbiased bases (MUBs) in bipartite qudit systems. In contrast to well-known power-of-prime MUB constructions, we restrict ourselves to using maximally entangled stabilizer states as MUB vectors. Consequently, these bipartite entangled stabilizer MUBs (BES MUBs) provide no local information, but are sufficient and minimal for decomposing a wide variety of interesting operators including (mixtures of) Jamiołkowski states, entanglement witnesses, and more. The problem of finding such BES MUBs can be mapped, in a natural way, to that of finding maximum cliques in a family of Cayley graphs. Some relationships with known power-of-prime MUB constructions are discussed, and observables for BES MUBs are given explicitly in terms of Pauli operators.
NASA Technical Reports Server (NTRS)
Fichtl, G. H.; Holland, R. L.
1978-01-01
A stochastic model of spacecraft motion was developed based on the assumption that the net torque vector due to crew activity and rocket thruster firings is a statistically stationary Gaussian vector process. The process had zero ensemble mean value, and the components of the torque vector were mutually stochastically independent. The linearized rigid-body equations of motion were used to derive the autospectral density functions of the components of the spacecraft rotation vector. The cross-spectral density functions of the components of the rotation vector vanish for all frequencies so that the components of rotation were mutually stochastically independent. The autospectral and cross-spectral density functions of the induced gravity environment imparted to scientific apparatus rigidly attached to the spacecraft were calculated from the rotation rate spectral density functions via linearized inertial frame to body-fixed principal axis frame transformation formulae. The induced gravity process was a Gaussian one with zero mean value. Transformation formulae were used to rotate the principal axis body-fixed frame to which the rotation rate and induced gravity vector were referred to a body-fixed frame in which the components of the induced gravity vector were stochastically independent. Rice's theory of exceedances was used to calculate expected exceedance rates of the components of the rotation and induced gravity vector processes.
Mutualism and Antagonism: Ecological Interactions Among Bark Beetles, Mite and Fungi
K.D. Klepzig; J.C. Moser; M.J. Lombardero; M.P. Ayres; R.W. Hofstetter; C.J. Walkinshaw
2001-01-01
Insect-fungal complexes provide challenging and fascinating systems for the study of biotic interactions between plants. plant pathogens, insect vectors and other associated organisms. The types of interactions among these organisms (mutualism. antagonism. parasitism. phoresy. etc.) are as variable as the range of organisms involved (plants, fungi, insects. mites. etc...
Lee, David; Park, Sang-Hoon; Lee, Sang-Goog
2017-10-07
In this paper, we propose a set of wavelet-based combined feature vectors and a Gaussian mixture model (GMM)-supervector to enhance training speed and classification accuracy in motor imagery brain-computer interfaces. The proposed method is configured as follows: first, wavelet transforms are applied to extract the feature vectors for identification of motor imagery electroencephalography (EEG) and principal component analyses are used to reduce the dimensionality of the feature vectors and linearly combine them. Subsequently, the GMM universal background model is trained by the expectation-maximization (EM) algorithm to purify the training data and reduce its size. Finally, a purified and reduced GMM-supervector is used to train the support vector machine classifier. The performance of the proposed method was evaluated for three different motor imagery datasets in terms of accuracy, kappa, mutual information, and computation time, and compared with the state-of-the-art algorithms. The results from the study indicate that the proposed method achieves high accuracy with a small amount of training data compared with the state-of-the-art algorithms in motor imagery EEG classification.
Quantum speed limit time in a magnetic resonance
NASA Astrophysics Data System (ADS)
Ivanchenko, E. A.
2017-12-01
A visualization for dynamics of a qudit spin vector in a time-dependent magnetic field is realized by means of mapping a solution for a spin vector on the three-dimensional spherical curve (vector hodograph). The obtained results obviously display the quantum interference of precessional and nutational effects on the spin vector in the magnetic resonance. For any spin the bottom bounds of the quantum speed limit time (QSL) are found. It is shown that the bottom bound goes down when using multilevel spin systems. Under certain conditions the non-nil minimal time, which is necessary to achieve the orthogonal state from the initial one, is attained at spin S = 2. An estimation of the product of two and three standard deviations of the spin components are presented. We discuss the dynamics of the mutual uncertainty, conditional uncertainty and conditional variance in terms of spin standard deviations. The study can find practical applications in the magnetic resonance, 3D visualization of computational data and in designing of optimized information processing devices for quantum computation and communication.
2014-01-01
Background Leptotrombidium pallidum and Leptotrombidium scutellare are the major vector mites for Orientia tsutsugamushi, the causative agent of scrub typhus. Before these organisms can be subjected to whole-genome sequencing, it is necessary to estimate their genome sizes to obtain basic information for establishing the strategies that should be used for genome sequencing and assembly. Method The genome sizes of L. pallidum and L. scutellare were estimated by a method based on quantitative real-time PCR. In addition, a k-mer analysis of the whole-genome sequences obtained through Illumina sequencing was conducted to verify the mutual compatibility and reliability of the results. Results The genome sizes estimated using qPCR were 191 ± 7 Mb for L. pallidum and 262 ± 13 Mb for L. scutellare. The k-mer analysis-based genome lengths were estimated to be 175 Mb for L. pallidum and 286 Mb for L. scutellare. The estimates from these two independent methods were mutually complementary and within a similar range to those of other Acariform mites. Conclusions The estimation method based on qPCR appears to be a useful alternative when the standard methods, such as flow cytometry, are impractical. The relatively small estimated genome sizes should facilitate whole-genome analysis, which could contribute to our understanding of Arachnida genome evolution and provide key information for scrub typhus prevention and mite vector competence. PMID:24947244
Mutually unbiased phase states, phase uncertainties, and Gauss sums
NASA Astrophysics Data System (ADS)
Planat, M.; Rosu, H.
2005-10-01
Mutually unbiased bases (MUBs), which are such that the inner product between two vectors in different orthogonal bases is a constant equal to 1/sqrt{d}, with d the dimension of the finite Hilbert space, are becoming more and more studied for applications such as quantum tomography and cryptography, and in relation to entangled states and to the Heisenberg-Weil group of quantum optics. Complete sets of MUBs of cardinality d+1 have been derived for prime power dimensions d=pm using the tools of abstract algebra. Presumably, for non prime dimensions the cardinality is much less. Here we reinterpret MUBs as quantum phase states, i.e. as eigenvectors of Hermitian phase operators generalizing those introduced by Pegg and Barnett in 1989. We relate MUB states to additive characters of Galois fields (in odd characteristic p) and to Galois rings (in characteristic 2). Quantum Fourier transforms of the components in vectors of the bases define a more general class of MUBs with multiplicative characters and additive ones altogether. We investigate the complementary properties of the above phase operator with respect to the number operator. We also study the phase probability distribution and variance for general pure quantum electromagnetic states and find them to be related to the Gauss sums, which are sums over all elements of the field (or of the ring) of the product of multiplicative and additive characters. Finally, we relate the concepts of mutual unbiasedness and maximal entanglement. This allows to use well studied algebraic concepts as efficient tools in the study of entanglement and its information aspects.
Kilosanidze, Barbara
2010-06-01
Generalization of the Jones vector for partially polarized radiation carried out by Kakichashvili is given. Partially polarized light is presented as two noncoherent components of mutually orthogonal polarization. The formal operation of amplitude summation of mutually noncoherent components and the symbol of this operation are introduced. The rules of operating with this symbol are determined. The regularity of the Weigert effect is modified for partial polarization of the inducing light. On this basis the modification of the Jones matrix for partially polarized light is made. The rules for the formation of the resulting matrix from the Jones matrices corresponding to the noncoherent components of partially polarized light are determined.
Spatial Lattice Modulation for MIMO Systems
NASA Astrophysics Data System (ADS)
Choi, Jiwook; Nam, Yunseo; Lee, Namyoon
2018-06-01
This paper proposes spatial lattice modulation (SLM), a spatial modulation method for multipleinput-multiple-output (MIMO) systems. The key idea of SLM is to jointly exploit spatial, in-phase, and quadrature dimensions to modulate information bits into a multi-dimensional signal set that consists oflattice points. One major finding is that SLM achieves a higher spectral efficiency than the existing spatial modulation and spatial multiplexing methods for the MIMO channel under the constraint ofM-ary pulseamplitude-modulation (PAM) input signaling per dimension. In particular, it is shown that when the SLM signal set is constructed by using dense lattices, a significant signal-to-noise-ratio (SNR) gain, i.e., a nominal coding gain, is attainable compared to the existing methods. In addition, closed-form expressions for both the average mutual information and average symbol-vector-error-probability (ASVEP) of generic SLM are derived under Rayleigh-fading environments. To reduce detection complexity, a low-complexity detection method for SLM, which is referred to as lattice sphere decoding, is developed by exploiting lattice theory. Simulation results verify the accuracy of the conducted analysis and demonstrate that the proposed SLM techniques achieve higher average mutual information and lower ASVEP than do existing methods.
NASA Astrophysics Data System (ADS)
Otake, Y.; Murphy, R. J.; Grupp, R. B.; Sato, Y.; Taylor, R. H.; Armand, M.
2015-03-01
A robust atlas-to-subject registration using a statistical deformation model (SDM) is presented. The SDM uses statistics of voxel-wise displacement learned from pre-computed deformation vectors of a training dataset. This allows an atlas instance to be directly translated into an intensity volume and compared with a patient's intensity volume. Rigid and nonrigid transformation parameters were simultaneously optimized via the Covariance Matrix Adaptation - Evolutionary Strategy (CMA-ES), with image similarity used as the objective function. The algorithm was tested on CT volumes of the pelvis from 55 female subjects. A performance comparison of the CMA-ES and Nelder-Mead downhill simplex optimization algorithms with the mutual information and normalized cross correlation similarity metrics was conducted. Simulation studies using synthetic subjects were performed, as well as leave-one-out cross validation studies. Both studies suggested that mutual information and CMA-ES achieved the best performance. The leave-one-out test demonstrated 4.13 mm error with respect to the true displacement field, and 26,102 function evaluations in 180 seconds, on average.
Frances, Stephen P; Edstein, Michael D; Debboun, Mustapha; Shanks, G Dennis
2016-01-01
Australian and US military medical services have collaborated since World War II to minimize vector-borne diseases such as malaria, dengue, and scrub typhus. In this review, collaboration over the last 30 years is discussed. The collaborative projects and exchange scientist programs have resulted in mutually beneficial outcomes in the fields of drug development and personal protection measures against vector-borne diseases.
On the Partitioning of Squared Euclidean Distance and Its Applications in Cluster Analysis.
ERIC Educational Resources Information Center
Carter, Randy L.; And Others
1989-01-01
The partitioning of squared Euclidean--E(sup 2)--distance between two vectors in M-dimensional space into the sum of squared lengths of vectors in mutually orthogonal subspaces is discussed. Applications to specific cluster analysis problems are provided (i.e., to design Monte Carlo studies for performance comparisons of several clustering methods…
Si, Weijian; Zhao, Pinjiao; Qu, Zhiyu
2016-01-01
This paper presents an L-shaped sparsely-distributed vector sensor (SD-VS) array with four different antenna compositions. With the proposed SD-VS array, a novel two-dimensional (2-D) direction of arrival (DOA) and polarization estimation method is proposed to handle the scenario where uncorrelated and coherent sources coexist. The uncorrelated and coherent sources are separated based on the moduli of the eigenvalues. For the uncorrelated sources, coarse estimates are acquired by extracting the DOA information embedded in the steering vectors from estimated array response matrix of the uncorrelated sources, and they serve as coarse references to disambiguate fine estimates with cyclical ambiguity obtained from the spatial phase factors. For the coherent sources, four Hankel matrices are constructed, with which the coherent sources are resolved in a similar way as for the uncorrelated sources. The proposed SD-VS array requires only two collocated antennas for each vector sensor, thus the mutual coupling effects across the collocated antennas are reduced greatly. Moreover, the inter-sensor spacings are allowed beyond a half-wavelength, which results in an extended array aperture. Simulation results demonstrate the effectiveness and favorable performance of the proposed method. PMID:27258271
Hamelin, Frédéric M; Hilker, Frank M; Sun, T Anthony; Jeger, Michael J; Hajimorad, M Reza; Allen, Linda J S; Prendeville, Holly R
2017-09-15
Virus-plant interactions range from parasitism to mutualism. Viruses have been shown to increase fecundity of infected plants in comparison with uninfected plants under certain environmental conditions. Increased fecundity of infected plants may benefit both the plant and the virus as seed transmission is one of the main virus transmission pathways, in addition to vector transmission. Trade-offs between vertical (seed) and horizontal (vector) transmission pathways may involve virulence, defined here as decreased fecundity in infected plants. To better understand plant-virus symbiosis evolution, we explore the ecological and evolutionary interplay of virus transmission modes when infection can lead to an increase in plant fecundity. We consider two possible trade-offs: vertical seed transmission vs infected plant fecundity, and horizontal vector transmission vs infected plant fecundity (virulence). Through mathematical models and numerical simulations, we show (1) that a trade-off between virulence and vertical transmission can lead to virus extinction during the course of evolution, (2) that evolutionary branching can occur with subsequent coexistence of mutualistic and parasitic virus strains, and (3) that mutualism can out-compete parasitism in the long-run. In passing, we show that ecological bi-stability is possible in a very simple discrete-time epidemic model. Possible extensions of this study include the evolution of conditional (environment-dependent) mutualism in plant viruses. Copyright © 2017 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Paul, Subir; Nagesh Kumar, D.
2018-04-01
Hyperspectral (HS) data comprises of continuous spectral responses of hundreds of narrow spectral bands with very fine spectral resolution or bandwidth, which offer feature identification and classification with high accuracy. In the present study, Mutual Information (MI) based Segmented Stacked Autoencoder (S-SAE) approach for spectral-spatial classification of the HS data is proposed to reduce the complexity and computational time compared to Stacked Autoencoder (SAE) based feature extraction. A non-parametric dependency measure (MI) based spectral segmentation is proposed instead of linear and parametric dependency measure to take care of both linear and nonlinear inter-band dependency for spectral segmentation of the HS bands. Then morphological profiles are created corresponding to segmented spectral features to assimilate the spatial information in the spectral-spatial classification approach. Two non-parametric classifiers, Support Vector Machine (SVM) with Gaussian kernel and Random Forest (RF) are used for classification of the three most popularly used HS datasets. Results of the numerical experiments carried out in this study have shown that SVM with a Gaussian kernel is providing better results for the Pavia University and Botswana datasets whereas RF is performing better for Indian Pines dataset. The experiments performed with the proposed methodology provide encouraging results compared to numerous existing approaches.
Oppenheim, Sara J; Rosenfeld, Jeffrey A; DeSalle, Rob
2017-02-27
The persistent and growing gap between the availability of sequenced genomes and the ability to assign functions to sequenced genes led us to explore ways to maximize the information content of automated annotation for studies of anopheline mosquitos. Specifically, we use genome content analysis of a large number of previously sequenced anopheline mosquitos to follow the loss and gain of protein families over the evolutionary history of this group. The importance of this endeavor lies in the potential for comparative genomic studies between Anopheles and closely related non-vector species to reveal ancestral genome content dynamics involved in vector competence. In addition, comparisons within Anopheles could identify genome content changes responsible for variation in the vectorial capacity of this family of important parasite vectors. The competence and capacity of P. falciparum vectors do not appear to be phylogenetically constrained within the Anophelinae. Instead, using ancestral reconstruction methods, we suggest that a previously unexamined component of vector biology, anopheline nucleotide metabolism, may contribute to the unique status of anophelines as P. falciparum vectors. While the fitness effects of nucleotide co-option by P. falciparum parasites on their anopheline hosts are not yet known, our results suggest that anopheline genome content may be responding to selection pressure from P. falciparum. Whether this response is defensive, in an attempt to redress improper nucleotide balance resulting from P. falciparum infection, or perhaps symbiotic, resulting from an as-yet-unknown mutualism between anophelines and P. falciparum, is an open question that deserves further study. Clearly, there is a wealth of functional information to be gained from detailed manual genome annotation, yet the rapid increase in the number of available sequences means that most researchers will not have the time or resources to manually annotate all the sequence data they generate. We believe that efforts to maximize the amount of information obtained from automated annotation can help address the functional annotation deficit that most evolutionary biologists now face, and here demonstrate the value of such an approach.
where C is the storm motion vector, and k is the unit vector in the vertical (Davies-Jones et al. 1990 mutually interacting perspectives, each addressing different aspects of the supercell storms most directly marked by low clouds, extending to the left. Photograph © 2005 C. Doswell 4. Developing a conceptual
Meyer, C R; Boes, J L; Kim, B; Bland, P H; Zasadny, K R; Kison, P V; Koral, K; Frey, K A; Wahl, R L
1997-04-01
This paper applies and evaluates an automatic mutual information-based registration algorithm across a broad spectrum of multimodal volume data sets. The algorithm requires little or no pre-processing, minimal user input and easily implements either affine, i.e. linear or thin-plate spline (TPS) warped registrations. We have evaluated the algorithm in phantom studies as well as in selected cases where few other algorithms could perform as well, if at all, to demonstrate the value of this new method. Pairs of multimodal gray-scale volume data sets were registered by iteratively changing registration parameters to maximize mutual information. Quantitative registration errors were assessed in registrations of a thorax phantom using PET/CT and in the National Library of Medicine's Visible Male using MRI T2-/T1-weighted acquisitions. Registrations of diverse clinical data sets were demonstrated including rotate-translate mapping of PET/MRI brain scans with significant missing data, full affine mapping of thoracic PET/CT and rotate-translate mapping of abdominal SPECT/CT. A five-point thin-plate spline (TPS) warped registration of thoracic PET/CT is also demonstrated. The registration algorithm converged in times ranging between 3.5 and 31 min for affine clinical registrations and 57 min for TPS warping. Mean error vector lengths for rotate-translate registrations were measured to be subvoxel in phantoms. More importantly the rotate-translate algorithm performs well even with missing data. The demonstrated clinical fusions are qualitatively excellent at all levels. We conclude that such automatic, rapid, robust algorithms significantly increase the likelihood that multimodality registrations will be routinely used to aid clinical diagnoses and post-therapeutic assessment in the near future.
Mutual information in the evolution of trajectories in discrete aiming movements.
Lai, Shih-Chiung; Mayer-Kress, Gottfried; Newell, Karl M
2008-07-01
This study investigated the mutual information in the trajectories of discrete aiming movements on a computer controlled graphics tablet where movement time ( 300 - 2050 ms) was manipulated in a given distance (100 mm) and movement distance (15-240 mm) in 2 given movement times (300 ms and 800 ms ). For the distance-fixed conditions, there was higher mutual information in the slower movements in the 0 vs. 80-100% trajectory point comparisons, whereas the mutual information was higher for the faster movements when comparing within the 80 and 100% points of the movement trajectory. For the time-fixed conditions, the spatial constraints led to a decreasing pattern of the mutual information throughout the points of the trajectory, with the highest mutual information found in the 80 vs. 100% comparison. Overall, the pattern of mutual information reveals systematic modulation of the trajectories between the attractive fixed point of the target as a function of movement condition. These mutual information patterns are postulated to be the consequence of the different relative contributions of feedforward and feedback control processes in trajectory formation as a function of task constraints.
Mutual coupling effects in antenna arrays, volume 1
NASA Technical Reports Server (NTRS)
Collin, R. E.
1986-01-01
Mutual coupling between rectangular apertures in a finite antenna array, in an infinite ground plane, is analyzed using the vector potential approach. The method of moments is used to solve the equations that result from setting the tangential magnetic fields across each aperture equal. The approximation uses a set of vector potential model functions to solve for equivalent magnetic currents. A computer program was written to carry out this analysis and the resulting currents were used to determine the co- and cross-polarized far zone radiation patterns. Numerical results for various arrays using several modes in the approximation are presented. Results for one and two aperture arrays are compared against published data to check on the agreement of this model with previous work. Computer derived results are also compared against experimental results to test the accuracy of the model. These tests of the accuracy of the program showed that it yields valid data.
Conditions for success of engineered underdominance gene drive systems.
Edgington, Matthew P; Alphey, Luke S
2017-10-07
Engineered underdominance is one of a number of different gene drive strategies that have been proposed for the genetic control of insect vectors of disease. Here we model a two-locus engineered underdominance based gene drive system that is based on the concept of mutually suppressing lethals. In such a system two genetic constructs are introduced, each possessing a lethal element and a suppressor of the lethal at the other locus. Specifically, we formulate and analyse a population genetics model of this system to assess when different combinations of release strategies (i.e. single or multiple releases of both sexes or males only) and genetic systems (i.e. bisex lethal or female-specific lethal elements and different strengths of suppressors) will give population replacement or fail to do so. We anticipate that results presented here will inform the future design of engineered underdominance gene drive systems as well as providing a point of reference regarding release strategies for those looking to test such a system. Our discussion is framed in the context of genetic control of insect vectors of disease. One of several serious threats in this context are Aedes aegypti mosquitoes as they are the primary vectors of dengue viruses. However, results are also applicable to Ae. aegypti as vectors of Zika, yellow fever and chikungunya viruses and also to the control of a number of other insect species and thereby of insect-vectored pathogens. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Lafuente, Victoria; Herrera, Luis J; Pérez, María del Mar; Val, Jesús; Negueruela, Ignacio
2015-08-15
In this work, near infrared spectroscopy (NIR) and an acoustic measure (AWETA) (two non-destructive methods) were applied in Prunus persica fruit 'Calrico' (n = 260) to predict Magness-Taylor (MT) firmness. Separate and combined use of these measures was evaluated and compared using partial least squares (PLS) and least squares support vector machine (LS-SVM) regression methods. Also, a mutual-information-based variable selection method, seeking to find the most significant variables to produce optimal accuracy of the regression models, was applied to a joint set of variables (NIR wavelengths and AWETA measure). The newly proposed combined NIR-AWETA model gave good values of the determination coefficient (R(2)) for PLS and LS-SVM methods (0.77 and 0.78, respectively), improving the reliability of MT firmness prediction in comparison with separate NIR and AWETA predictions. The three variables selected by the variable selection method (AWETA measure plus NIR wavelengths 675 and 697 nm) achieved R(2) values 0.76 and 0.77, PLS and LS-SVM. These results indicated that the proposed mutual-information-based variable selection algorithm was a powerful tool for the selection of the most relevant variables. © 2014 Society of Chemical Industry.
Islam, Md Rabiul; Tanaka, Toshihisa; Molla, Md Khademul Islam
2018-05-08
When designing multiclass motor imagery-based brain-computer interface (MI-BCI), a so-called tangent space mapping (TSM) method utilizing the geometric structure of covariance matrices is an effective technique. This paper aims to introduce a method using TSM for finding accurate operational frequency bands related brain activities associated with MI tasks. A multichannel electroencephalogram (EEG) signal is decomposed into multiple subbands, and tangent features are then estimated on each subband. A mutual information analysis-based effective algorithm is implemented to select subbands containing features capable of improving motor imagery classification accuracy. Thus obtained features of selected subbands are combined to get feature space. A principal component analysis-based approach is employed to reduce the features dimension and then the classification is accomplished by a support vector machine (SVM). Offline analysis demonstrates the proposed multiband tangent space mapping with subband selection (MTSMS) approach outperforms state-of-the-art methods. It acheives the highest average classification accuracy for all datasets (BCI competition dataset 2a, IIIa, IIIb, and dataset JK-HH1). The increased classification accuracy of MI tasks with the proposed MTSMS approach can yield effective implementation of BCI. The mutual information-based subband selection method is implemented to tune operation frequency bands to represent actual motor imagery tasks.
Albers, D. J.; Hripcsak, George
2012-01-01
A method to estimate the time-dependent correlation via an empirical bias estimate of the time-delayed mutual information for a time-series is proposed. In particular, the bias of the time-delayed mutual information is shown to often be equivalent to the mutual information between two distributions of points from the same system separated by infinite time. Thus intuitively, estimation of the bias is reduced to estimation of the mutual information between distributions of data points separated by large time intervals. The proposed bias estimation techniques are shown to work for Lorenz equations data and glucose time series data of three patients from the Columbia University Medical Center database. PMID:22536009
Cannon, Jonathan
2017-01-01
Mutual information is a commonly used measure of communication between neurons, but little theory exists describing the relationship between mutual information and the parameters of the underlying neuronal interaction. Such a theory could help us understand how specific physiological changes affect the capacity of neurons to synaptically communicate, and, in particular, they could help us characterize the mechanisms by which neuronal dynamics gate the flow of information in the brain. Here we study a pair of linear-nonlinear-Poisson neurons coupled by a weak synapse. We derive an analytical expression describing the mutual information between their spike trains in terms of synapse strength, neuronal activation function, the time course of postsynaptic currents, and the time course of the background input received by the two neurons. This expression allows mutual information calculations that would otherwise be computationally intractable. We use this expression to analytically explore the interaction of excitation, information transmission, and the convexity of the activation function. Then, using this expression to quantify mutual information in simulations, we illustrate the information-gating effects of neural oscillations and oscillatory coherence, which may either increase or decrease the mutual information across the synapse depending on parameters. Finally, we show analytically that our results can quantitatively describe the selection of one information pathway over another when multiple sending neurons project weakly to a single receiving neuron.
NASA Astrophysics Data System (ADS)
Perotti, Juan Ignacio; Tessone, Claudio Juan; Caldarelli, Guido
2015-12-01
The quest for a quantitative characterization of community and modular structure of complex networks produced a variety of methods and algorithms to classify different networks. However, it is not clear if such methods provide consistent, robust, and meaningful results when considering hierarchies as a whole. Part of the problem is the lack of a similarity measure for the comparison of hierarchical community structures. In this work we give a contribution by introducing the hierarchical mutual information, which is a generalization of the traditional mutual information and makes it possible to compare hierarchical partitions and hierarchical community structures. The normalized version of the hierarchical mutual information should behave analogously to the traditional normalized mutual information. Here the correct behavior of the hierarchical mutual information is corroborated on an extensive battery of numerical experiments. The experiments are performed on artificial hierarchies and on the hierarchical community structure of artificial and empirical networks. Furthermore, the experiments illustrate some of the practical applications of the hierarchical mutual information, namely the comparison of different community detection methods and the study of the consistency, robustness, and temporal evolution of the hierarchical modular structure of networks.
Martin, James E.; Solis, Kyle Jameson
2015-11-09
It has recently been reported that two types of triaxial electric or magnetic fields can drive vorticity in dielectric or magnetic particle suspensions, respectively. The first type-symmetry -- breaking rational fields -- consists of three mutually orthogonal fields, two alternating and one dc, and the second type -- rational triads -- consists of three mutually orthogonal alternating fields. In each case it can be shown through experiment and theory that the fluid vorticity vector is parallel to one of the three field components. For any given set of field frequencies this axis is invariant, but the sign and magnitude ofmore » the vorticity (at constant field strength) can be controlled by the phase angles of the alternating components and, at least for some symmetry-breaking rational fields, the direction of the dc field. In short, the locus of possible vorticity vectors is a 1-d set that is symmetric about zero and is along a field direction. In this paper we show that continuous, 3-d control of the vorticity vector is possible by progressively transitioning the field symmetry by applying a dc bias along one of the principal axes. Such biased rational triads are a combination of symmetry-breaking rational fields and rational triads. A surprising aspect of these transitions is that the locus of possible vorticity vectors for any given field bias is extremely complex, encompassing all three spatial dimensions. As a result, the evolution of a vorticity vector as the dc bias is increased is complex, with large components occurring along unexpected directions. More remarkable are the elaborate vorticity vector orbits that occur when one or more of the field frequencies are detuned. As a result, these orbits provide the basis for highly effective mixing strategies wherein the vorticity axis periodically explores a range of orientations and magnitudes.« less
Generalized mutual information and Tsirelson's bound
NASA Astrophysics Data System (ADS)
Wakakuwa, Eyuri; Murao, Mio
2014-12-01
We introduce a generalization of the quantum mutual information between a classical system and a quantum system into the mutual information between a classical system and a system described by general probabilistic theories. We apply this generalized mutual information (GMI) to a derivation of Tsirelson's bound from information causality, and prove that Tsirelson's bound can be derived from the chain rule of the GMI. By using the GMI, we formulate the "no-supersignalling condition" (NSS), that the assistance of correlations does not enhance the capability of classical communication. We prove that NSS is never violated in any no-signalling theory.
Generalized mutual information and Tsirelson's bound
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wakakuwa, Eyuri; Murao, Mio
2014-12-04
We introduce a generalization of the quantum mutual information between a classical system and a quantum system into the mutual information between a classical system and a system described by general probabilistic theories. We apply this generalized mutual information (GMI) to a derivation of Tsirelson's bound from information causality, and prove that Tsirelson's bound can be derived from the chain rule of the GMI. By using the GMI, we formulate the 'no-supersignalling condition' (NSS), that the assistance of correlations does not enhance the capability of classical communication. We prove that NSS is never violated in any no-signalling theory.
Mutual information and the fidelity of response of gene regulatory models
NASA Astrophysics Data System (ADS)
Tabbaa, Omar P.; Jayaprakash, C.
2014-08-01
We investigate cellular response to extracellular signals by using information theory techniques motivated by recent experiments. We present results for the steady state of the following gene regulatory models found in both prokaryotic and eukaryotic cells: a linear transcription-translation model and a positive or negative auto-regulatory model. We calculate both the information capacity and the mutual information exactly for simple models and approximately for the full model. We find that (1) small changes in mutual information can lead to potentially important changes in cellular response and (2) there are diminishing returns in the fidelity of response as the mutual information increases. We calculate the information capacity using Gillespie simulations of a model for the TNF-α-NF-κ B network and find good agreement with the measured value for an experimental realization of this network. Our results provide a quantitative understanding of the differences in cellular response when comparing experimentally measured mutual information values of different gene regulatory models. Our calculations demonstrate that Gillespie simulations can be used to compute the mutual information of more complex gene regulatory models, providing a potentially useful tool in synthetic biology.
Virus infection of a weed increases vector attraction to and vector fitness on the weed.
Chen, Gong; Pan, Huipeng; Xie, Wen; Wang, Shaoli; Wu, Qingjun; Fang, Yong; Shi, Xiaobin; Zhang, Youjun
2013-01-01
Weeds are important in the ecology of field crops, and when crops are harvested, weeds often become the main hosts for plant viruses and their insect vectors. Few studies, however, have examined the relationships between plant viruses, vectors, and weeds. Here, we investigated how infection of the weed Datura stramonium L. by tomato yellow leaf curl virus (TYLCV) affects the host preference and performance of the TYLCV vector, Bemisia tabaci (Gennadius) Q. The results of a choice experiment indicated that B. tabaci Q preferentially settled and oviposited on TYLCV-infected plants rather than on healthy plants. In addition, B. tabaci Q performed better on TYLCV-infected plants than on healthy plants. These results demonstrate that TYLCV is indirectly mutualistic to B. tabaci Q. The mutually beneficial interaction between TYLCV and B. tabaci Q may help explain the concurrent outbreaks of TYLCV and B. tabaci Q in China.
Zhang, Yongshun; Zheng, Guimei; Feng, Cunqian; Tang, Jun
2017-01-01
In this paper, we focus on the problem of two-dimensional direction of arrival (2D-DOA) estimation for monostatic MIMO Radar with electromagnetic vector received sensors (MIMO-EMVSs) under the condition of gain and phase uncertainties (GPU) and mutual coupling (MC). GPU would spoil the invariance property of the EMVSs in MIMO-EMVSs, thus the effective ESPRIT algorithm unable to be used directly. Then we put forward a C-SPD ESPRIT-like algorithm. It estimates the 2D-DOA and polarization station angle (PSA) based on the instrumental sensors method (ISM). The C-SPD ESPRIT-like algorithm can obtain good angle estimation accuracy without knowing the GPU. Furthermore, it can be applied to arbitrary array configuration and has low complexity for avoiding the angle searching procedure. When MC and GPU exist together between the elements of EMVSs, in order to make our algorithm feasible, we derive a class of separated electromagnetic vector receiver and give the S-SPD ESPRIT-like algorithm. It can solve the problem of GPU and MC efficiently. And the array configuration can be arbitrary. The effectiveness of our proposed algorithms is verified by the simulation result. PMID:29072588
Zhang, Dong; Zhang, Yongshun; Zheng, Guimei; Feng, Cunqian; Tang, Jun
2017-10-26
In this paper, we focus on the problem of two-dimensional direction of arrival (2D-DOA) estimation for monostatic MIMO Radar with electromagnetic vector received sensors (MIMO-EMVSs) under the condition of gain and phase uncertainties (GPU) and mutual coupling (MC). GPU would spoil the invariance property of the EMVSs in MIMO-EMVSs, thus the effective ESPRIT algorithm unable to be used directly. Then we put forward a C-SPD ESPRIT-like algorithm. It estimates the 2D-DOA and polarization station angle (PSA) based on the instrumental sensors method (ISM). The C-SPD ESPRIT-like algorithm can obtain good angle estimation accuracy without knowing the GPU. Furthermore, it can be applied to arbitrary array configuration and has low complexity for avoiding the angle searching procedure. When MC and GPU exist together between the elements of EMVSs, in order to make our algorithm feasible, we derive a class of separated electromagnetic vector receiver and give the S-SPD ESPRIT-like algorithm. It can solve the problem of GPU and MC efficiently. And the array configuration can be arbitrary. The effectiveness of our proposed algorithms is verified by the simulation result.
NASA Astrophysics Data System (ADS)
Shi, Jing; Shi, Yunli; Tan, Jian; Zhu, Lei; Li, Hu
2018-02-01
Traditional power forecasting models cannot efficiently take various factors into account, neither to identify the relation factors. In this paper, the mutual information in information theory and the artificial intelligence random forests algorithm are introduced into the medium and long-term electricity demand prediction. Mutual information can identify the high relation factors based on the value of average mutual information between a variety of variables and electricity demand, different industries may be highly associated with different variables. The random forests algorithm was used for building the different industries forecasting models according to the different correlation factors. The data of electricity consumption in Jiangsu Province is taken as a practical example, and the above methods are compared with the methods without regard to mutual information and the industries. The simulation results show that the above method is scientific, effective, and can provide higher prediction accuracy.
Method for multi-axis, non-contact mixing of magnetic particle suspensions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Martin, James E.; Solis, Kyle J.
Continuous, three-dimensional control of the vorticity vector is possible by progressively transitioning the field symmetry by applying or removing a dc bias along one of the principal axes of mutually orthogonal alternating fields. By exploiting this transition, the vorticity vector can be oriented in a wide range of directions that comprise all three spatial dimensions. Detuning one or more field components to create phase modulation causes the vorticity vector to trace out complex orbits of a wide variety, creating very robust multiaxial stirring. This multiaxial, non-contact stirring is particularly attractive for applications where the fluid volume has complex boundaries, ormore » is congested.« less
Nonlinear pattern analysis of ventricular premature beats by mutual information
NASA Technical Reports Server (NTRS)
Osaka, M.; Saitoh, H.; Yokoshima, T.; Kishida, H.; Hayakawa, H.; Cohen, R. J.
1997-01-01
The frequency of ventricular premature beats (VPBs) has been related to the risk of mortality. However, little is known about the temporal pattern of occurrence of VPBs and its relationship to autonomic activity. Hence, we applied a general correlation measure, mutual information, to quantify how VPBs are generated over time. We also used mutual information to determine the correlation between VPB production and heart rate in order to evaluate effects of autonomic activity on VPB production. We examined twenty subjects with more than 3000 VPBs/day and simulated random time series of VPB occurrence. We found that mutual information values could be used to characterize quantitatively the temporal patterns of VPB generation. Our data suggest that VPB production is not random and VPBs generated with a higher value of mutual information may be more greatly affected by autonomic activity.
JRSP of three-particle state via three tripartite GHZ class in quantum noisy channels
NASA Astrophysics Data System (ADS)
Falaye, Babatunde James; Sun, Guo-Hua; Camacho-Nieto, Oscar; Dong, Shi-Hai
2016-10-01
We present a scheme for joint remote state preparation (JRSP) of three-particle state via three tripartite Greenberger-Horne-Zeilinger (GHZ) entangled states as the quantum channel linking the parties. We use eight-qubit mutually orthogonal basis vector as measurement point of departure. The likelihood of success for this scheme has been found to be 1/8. However, by putting some special cases into consideration, the chances can be ameliorated to 1/4 and 1. The effects of amplitude-damping noise, phase-damping noise and depolarizing noise on this scheme have been scrutinized and the analytical derivations of fidelities for the quantum noisy channels have been presented. We found that for 0.55≤η≤1, the states conveyed through depolarizing channel lose more information than phase-damping channel while the information loss through amplitude damping channel is most minimal.
Equitability, mutual information, and the maximal information coefficient.
Kinney, Justin B; Atwal, Gurinder S
2014-03-04
How should one quantify the strength of association between two random variables without bias for relationships of a specific form? Despite its conceptual simplicity, this notion of statistical "equitability" has yet to receive a definitive mathematical formalization. Here we argue that equitability is properly formalized by a self-consistency condition closely related to Data Processing Inequality. Mutual information, a fundamental quantity in information theory, is shown to satisfy this equitability criterion. These findings are at odds with the recent work of Reshef et al. [Reshef DN, et al. (2011) Science 334(6062):1518-1524], which proposed an alternative definition of equitability and introduced a new statistic, the "maximal information coefficient" (MIC), said to satisfy equitability in contradistinction to mutual information. These conclusions, however, were supported only with limited simulation evidence, not with mathematical arguments. Upon revisiting these claims, we prove that the mathematical definition of equitability proposed by Reshef et al. cannot be satisfied by any (nontrivial) dependence measure. We also identify artifacts in the reported simulation evidence. When these artifacts are removed, estimates of mutual information are found to be more equitable than estimates of MIC. Mutual information is also observed to have consistently higher statistical power than MIC. We conclude that estimating mutual information provides a natural (and often practical) way to equitably quantify statistical associations in large datasets.
Stable Transmission in the Time-Varying MIMO Broadcast Channel
2008-01-01
jth received vector in (6) given knowledge at the receiver of bothH j(n) and H j(n0) is IDPC [ x j(n); y j ( n0,n ) | H j(n),H j ( n0 )] = h[y j ( n0...erroneous CSI from [4] are equivalent and reduce to IDPC [ x j(n); y j ( n0,n ) | H j(n),H j ( n0 )] = log ∣∣Z j + H j(n)Q j ( n0 ) HHj (n) ∣∣ ∣∣Z j ∣∣ , Z j...input covariance matrix calculated at sample n0. After computing (8) for each user, the sum mutual information becomes CDPC ( n0,n ) = K∑ j=1 IDPC [ x
Mutual information against correlations in binary communication channels.
Pregowska, Agnieszka; Szczepanski, Janusz; Wajnryb, Eligiusz
2015-05-19
Explaining how the brain processing is so fast remains an open problem (van Hemmen JL, Sejnowski T., 2004). Thus, the analysis of neural transmission (Shannon CE, Weaver W., 1963) processes basically focuses on searching for effective encoding and decoding schemes. According to the Shannon fundamental theorem, mutual information plays a crucial role in characterizing the efficiency of communication channels. It is well known that this efficiency is determined by the channel capacity that is already the maximal mutual information between input and output signals. On the other hand, intuitively speaking, when input and output signals are more correlated, the transmission should be more efficient. A natural question arises about the relation between mutual information and correlation. We analyze the relation between these quantities using the binary representation of signals, which is the most common approach taken in studying neuronal processes of the brain. We present binary communication channels for which mutual information and correlation coefficients behave differently both quantitatively and qualitatively. Despite this difference in behavior, we show that the noncorrelation of binary signals implies their independence, in contrast to the case for general types of signals. Our research shows that the mutual information cannot be replaced by sheer correlations. Our results indicate that neuronal encoding has more complicated nature which cannot be captured by straightforward correlations between input and output signals once the mutual information takes into account the structure and patterns of the signals.
NASA Astrophysics Data System (ADS)
Hasanian, Mostafa; Lissenden, Cliff J.
2017-08-01
The extraordinary sensitivity of nonlinear ultrasonic waves to the early stages of material degradation makes them excellent candidates for nondestructive material characterization. However, distinguishing weak material nonlinearity from instrumentation nonlinearity remains problematic for second harmonic generation approaches. A solution to this problem is to mix waves having different frequencies and to let their mutual interaction generate sum and difference harmonics at frequencies far from those of the instrumentation. Mixing of bulk waves and surface waves has been researched for some time, but mixing of guided waves has not yet been investigated in depth. A unique aspect of guided waves is their dispersive nature, which means we need to assure that a wave can propagate at the sum or difference frequency. A wave vector analysis is conducted that enables selection of primary waves traveling in any direction that generate phase matched secondary waves. We have tabulated many sets of primary waves and phase matched sum and difference harmonics. An example wave mode triplet of two counter-propagating collinear shear horizontal waves that interact to generate a symmetric Lamb wave at the sum frequency is simulated using finite element analysis and then laboratory experiments are conducted. The finite element simulation eliminates issues associated with instrumentation nonlinearities and signal-to-noise ratio. A straightforward subtraction method is used in the experiments to identify the material nonlinearity induced mutual interaction and show that the generated Lamb wave propagates on its own and is large enough to measure. Since the Lamb wave has different polarity than the shear horizontal waves the material nonlinearity is clearly identifiable. Thus, the mutual interactions of shear horizontal waves in plates could enable volumetric characterization of material in remote regions from transducers mounted on just one side of the plate.
A Minimum Spanning Forest Based Method for Noninvasive Cancer Detection with Hyperspectral Imaging
Pike, Robert; Lu, Guolan; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei
2016-01-01
Goal The purpose of this paper is to develop a classification method that combines both spectral and spatial information for distinguishing cancer from healthy tissue on hyperspectral images in an animal model. Methods An automated algorithm based on a minimum spanning forest (MSF) and optimal band selection has been proposed to classify healthy and cancerous tissue on hyperspectral images. A support vector machine (SVM) classifier is trained to create a pixel-wise classification probability map of cancerous and healthy tissue. This map is then used to identify markers that are used to compute mutual information for a range of bands in the hyperspectral image and thus select the optimal bands. An MSF is finally grown to segment the image using spatial and spectral information. Conclusion The MSF based method with automatically selected bands proved to be accurate in determining the tumor boundary on hyperspectral images. Significance Hyperspectral imaging combined with the proposed classification technique has the potential to provide a noninvasive tool for cancer detection. PMID:26285052
USDA-ARS?s Scientific Manuscript database
The presence of multiple enhancers and promoters within a single vector often provokes complicated mutual interaction and crosstalk, thereby, altering promoter specificity, which causes serious problems for precisely engineering gene function and agronomic traits in transgenic plants. Enhancer elem...
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The Impact of Different Sources of Fluctuations on Mutual Information in Biochemical Networks
Chevalier, Michael; Venturelli, Ophelia; El-Samad, Hana
2015-01-01
Stochastic fluctuations in signaling and gene expression limit the ability of cells to sense the state of their environment, transfer this information along cellular pathways, and respond to it with high precision. Mutual information is now often used to quantify the fidelity with which information is transmitted along a cellular pathway. Mutual information calculations from experimental data have mostly generated low values, suggesting that cells might have relatively low signal transmission fidelity. In this work, we demonstrate that mutual information calculations might be artificially lowered by cell-to-cell variability in both initial conditions and slowly fluctuating global factors across the population. We carry out our analysis computationally using a simple signaling pathway and demonstrate that in the presence of slow global fluctuations, every cell might have its own high information transmission capacity but that population averaging underestimates this value. We also construct a simple synthetic transcriptional network and demonstrate using experimental measurements coupled to computational modeling that its operation is dominated by slow global variability, and hence that its mutual information is underestimated by a population averaged calculation. PMID:26484538
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Tolmachov, Oleg E
2012-05-01
The cell-specific and long-term expression of therapeutic transgenes often requires a full array of native gene control elements including distal enhancers, regulatory introns and chromatin organisation sequences. The delivery of such extended gene expression modules to human cells can be accomplished with non-viral high-molecular-weight DNA vectors, in particular with several classes of linear DNA vectors. All high-molecular-weight DNA vectors are susceptible to damage by shear stress, and while for some of the vectors the harmful impact of shear stress can be minimised through the transformation of the vectors to compact topological configurations by supercoiling and/or knotting, linear DNA vectors with terminal loops or covalently attached terminal proteins cannot be self-compacted in this way. In this case, the only available self-compacting option is self-entangling, which can be defined as the folding of single DNA molecules into a configuration with mutual restriction of molecular motion by the individual segments of bent DNA. A negatively charged phosphate backbone makes DNA self-repulsive, so it is reasonable to assume that a certain number of 'sticky points' dispersed within DNA could facilitate the entangling by bringing DNA segments into proximity and by interfering with the DNA slipping away from the entanglement. I propose that the spontaneous entanglement of vector DNA can be enhanced by the interlacing of the DNA with sites capable of mutual transient attachment through the formation of non-B-DNA forms, such as interacting cruciform structures, inter-segment triplexes, slipped-strand DNA, left-handed duplexes (Z-forms) or G-quadruplexes. It is expected that the non-B-DNA based entanglement of the linear DNA vectors would consist of the initial transient and co-operative non-B-DNA mediated binding events followed by tight self-ensnarement of the vector DNA. Once in the nucleoplasm of the target human cells, the DNA can be disentangled by type II topoisomerases. The technology for such self-entanglement can be an avenue for the improvement of gene delivery with high-molecular-weight naked DNA using therapeutically important methods associated with considerable shear stress. Priority applications include in vivo muscle electroporation and sonoporation for Duchenne muscular dystrophy patients, aerosol inhalation to reach the target lung cells of cystic fibrosis patients and bio-ballistic delivery to skin melanomas with the vector DNA adsorbed on gold or tungsten projectiles. Copyright © 2012 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
James, Ryan G.; Mahoney, John R.; Crutchfield, James P.
2017-06-01
One of the most basic characterizations of the relationship between two random variables, X and Y , is the value of their mutual information. Unfortunately, calculating it analytically and estimating it empirically are often stymied by the extremely large dimension of the variables. One might hope to replace such a high-dimensional variable by a smaller one that preserves its relationship with the other. It is well known that either X (or Y ) can be replaced by its minimal sufficient statistic about Y (or X ) while preserving the mutual information. While intuitively reasonable, it is not obvious or straightforward that both variables can be replaced simultaneously. We demonstrate that this is in fact possible: the information X 's minimal sufficient statistic preserves about Y is exactly the information that Y 's minimal sufficient statistic preserves about X . We call this procedure information trimming. As an important corollary, we consider the case where one variable is a stochastic process' past and the other its future. In this case, the mutual information is the channel transmission rate between the channel's effective states. That is, the past-future mutual information (the excess entropy) is the amount of information about the future that can be predicted using the past. Translating our result about minimal sufficient statistics, this is equivalent to the mutual information between the forward- and reverse-time causal states of computational mechanics. We close by discussing multivariate extensions to this use of minimal sufficient statistics.
Behura, Susanta K.; Severson, David W.
2014-01-01
The mosquito Aedes aegypti is the primary vector of dengue virus (DENV) infection in most of the subtropical and tropical countries. Besides DENV, yellow fever virus (YFV) is also transmitted by A. aegypti. Susceptibility of A. aegypti to West Nile virus (WNV) has also been confirmed. Although studies have indicated correlation of codon bias between flaviviridae and their animal/insect hosts, it is not clear if codon sequences have any relation to susceptibility of A. aegypti to DENV, YFV and WNV. In the current study, usages of codon context sequences (codon pairs for neighboring amino acids) of the vector (A. aegypti) genome as well as the flaviviral genomes are investigated. We used bioinformatics methods to quantify codon context bias in a genome-wide manner of A. aegypti as well as DENV, WNV and YFV sequences. Mutual information statistics was applied to perform bicluster analysis of codon context bias between vector and flaviviral sequences. Functional relevance of the bicluster pattern was inferred from published microarray data. Our study shows that codon context bias of DENV, WNV and YFV sequences varies in a bicluster manner with that of specific sets of genes of A. aegypti. Many of these mosquito genes are known to be differentially expressed in response to flaviviral infection suggesting that codon context sequences of A. aegypti and the flaviviruses may play a role in the susceptible interaction between flaviviruses and this mosquito. The bias inusages of codon context sequences likely has a functional association with susceptibility of A. aegypti to flaviviral infection. The results from this study will allow us to conduct hypothesis driven tests to examine the role of codon contexts bias in evolution of vector-virus interactions at the molecular level. PMID:24838953
Multiparty quantum mutual information: An alternative definition
NASA Astrophysics Data System (ADS)
Kumar, Asutosh
2017-07-01
Mutual information is the reciprocal information that is common to or shared by two or more parties. Quantum mutual information for bipartite quantum systems is non-negative, and bears the interpretation of total correlation between the two subsystems. This may, however, no longer be true for three or more party quantum systems. In this paper, we propose an alternative definition of multipartite information, taking into account the shared information between two and more parties. It is non-negative, observes monotonicity under partial trace as well as completely positive maps, and equals the multipartite information measure in literature for pure states. We then define multiparty quantum discord, and give some examples. Interestingly, we observe that quantum discord increases when a measurement is performed on a large number of subsystems. Consequently, the symmetric quantum discord, which involves a measurement on all parties, reveals the maximal quantumness. This raises a question on the interpretation of measured mutual information as a classical correlation.
Electric fields and vector potentials of thin cylindrical antennas
NASA Astrophysics Data System (ADS)
King, Ronold W. P.
1990-09-01
The vector potential and electric field generated by the current in a center-driven or parasitic dipole antenna that extends from z = -h to z = h are investigated for each of the several components of the current. These include sin k(h - absolute value of z), sin k (absolute value of z) - sin kh, cos kz - cos kh, and cos kz/2 - cos kh/2. Of special interest are the interactions among the variously spaced elements in parallel nonstaggered arrays. These depend on the mutual vector potentials. It is shown that at a radial distance rho approximately = h and in the range z = -h to h, the vector potentials due to all four components become alike and have an approximately plane-wave form. Simple approximate formulas for the electric fields and vector potentials generated by each of the four distributions are derived and compared with the exact results. The application of the new formulas to large arrays is discussed.
Multimodal registration via spatial-context mutual information.
Yi, Zhao; Soatto, Stefano
2011-01-01
We propose a method to efficiently compute mutual information between high-dimensional distributions of image patches. This in turn is used to perform accurate registration of images captured under different modalities, while exploiting their local structure otherwise missed in traditional mutual information definition. We achieve this by organizing the space of image patches into orbits under the action of Euclidean transformations of the image plane, and estimating the modes of a distribution in such an orbit space using affinity propagation. This way, large collections of patches that are equivalent up to translations and rotations are mapped to the same representative, or "dictionary element". We then show analytically that computing mutual information for a joint distribution in this space reduces to computing mutual information between the (scalar) label maps, and between the transformations mapping each patch into its closest dictionary element. We show that our approach improves registration performance compared with the state of the art in multimodal registration, using both synthetic and real images with quantitative ground truth.
Seok, Junhee; Seon Kang, Yeong
2015-01-01
Mutual information, a general measure of the relatedness between two random variables, has been actively used in the analysis of biomedical data. The mutual information between two discrete variables is conventionally calculated by their joint probabilities estimated from the frequency of observed samples in each combination of variable categories. However, this conventional approach is no longer efficient for discrete variables with many categories, which can be easily found in large-scale biomedical data such as diagnosis codes, drug compounds, and genotypes. Here, we propose a method to provide stable estimations for the mutual information between discrete variables with many categories. Simulation studies showed that the proposed method reduced the estimation errors by 45 folds and improved the correlation coefficients with true values by 99 folds, compared with the conventional calculation of mutual information. The proposed method was also demonstrated through a case study for diagnostic data in electronic health records. This method is expected to be useful in the analysis of various biomedical data with discrete variables. PMID:26046461
75 FR 33319 - Agency Information Collection Activities: New Information Collection; Comment Request
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2010-06-11
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Reducing Interpolation Artifacts for Mutual Information Based Image Registration
Soleimani, H.; Khosravifard, M.A.
2011-01-01
Medical image registration methods which use mutual information as similarity measure have been improved in recent decades. Mutual Information is a basic concept of Information theory which indicates the dependency of two random variables (or two images). In order to evaluate the mutual information of two images their joint probability distribution is required. Several interpolation methods, such as Partial Volume (PV) and bilinear, are used to estimate joint probability distribution. Both of these two methods yield some artifacts on mutual information function. Partial Volume-Hanning window (PVH) and Generalized Partial Volume (GPV) methods are introduced to remove such artifacts. In this paper we show that the acceptable performance of these methods is not due to their kernel function. It's because of the number of pixels which incorporate in interpolation. Since using more pixels requires more complex and time consuming interpolation process, we propose a new interpolation method which uses only four pixels (the same as PV and bilinear interpolations) and removes most of the artifacts. Experimental results of the registration of Computed Tomography (CT) images show superiority of the proposed scheme. PMID:22606673
NASA Astrophysics Data System (ADS)
Albers, D. J.; Hripcsak, George
2012-03-01
This paper addresses how to calculate and interpret the time-delayed mutual information (TDMI) for a complex, diversely and sparsely measured, possibly non-stationary population of time-series of unknown composition and origin. The primary vehicle used for this analysis is a comparison between the time-delayed mutual information averaged over the population and the time-delayed mutual information of an aggregated population (here, aggregation implies the population is conjoined before any statistical estimates are implemented). Through the use of information theoretic tools, a sequence of practically implementable calculations are detailed that allow for the average and aggregate time-delayed mutual information to be interpreted. Moreover, these calculations can also be used to understand the degree of homo or heterogeneity present in the population. To demonstrate that the proposed methods can be used in nearly any situation, the methods are applied and demonstrated on the time series of glucose measurements from two different subpopulations of individuals from the Columbia University Medical Center electronic health record repository, revealing a picture of the composition of the population as well as physiological features.
Rényi and Tsallis formulations of separability conditions in finite dimensions
NASA Astrophysics Data System (ADS)
Rastegin, Alexey E.
2017-12-01
Separability conditions for a bipartite quantum system of finite-dimensional subsystems are formulated in terms of Rényi and Tsallis entropies. Entropic uncertainty relations often lead to entanglement criteria. We propose new approach based on the convolution of discrete probability distributions. Measurements on a total system are constructed of local ones according to the convolution scheme. Separability conditions are derived on the base of uncertainty relations of the Maassen-Uffink type as well as majorization relations. On each of subsystems, we use a pair of sets of subnormalized vectors that form rank-one POVMs. We also obtain entropic separability conditions for local measurements with a special structure, such as mutually unbiased bases and symmetric informationally complete measurements. The relevance of the derived separability conditions is demonstrated with several examples.
NASA Astrophysics Data System (ADS)
Bhardwaj, Kaushal; Patra, Swarnajyoti
2018-04-01
Inclusion of spatial information along with spectral features play a significant role in classification of remote sensing images. Attribute profiles have already proved their ability to represent spatial information. In order to incorporate proper spatial information, multiple attributes are required and for each attribute large profiles need to be constructed by varying the filter parameter values within a wide range. Thus, the constructed profiles that represent spectral-spatial information of an hyperspectral image have huge dimension which leads to Hughes phenomenon and increases computational burden. To mitigate these problems, this work presents an unsupervised feature selection technique that selects a subset of filtered image from the constructed high dimensional multi-attribute profile which are sufficiently informative to discriminate well among classes. In this regard the proposed technique exploits genetic algorithms (GAs). The fitness function of GAs are defined in an unsupervised way with the help of mutual information. The effectiveness of the proposed technique is assessed using one-against-all support vector machine classifier. The experiments conducted on three hyperspectral data sets show the robustness of the proposed method in terms of computation time and classification accuracy.
NASA Astrophysics Data System (ADS)
Zhao, Bei; Zhong, Yanfei; Zhang, Liangpei
2016-06-01
Land-use classification of very high spatial resolution remote sensing (VHSR) imagery is one of the most challenging tasks in the field of remote sensing image processing. However, the land-use classification is hard to be addressed by the land-cover classification techniques, due to the complexity of the land-use scenes. Scene classification is considered to be one of the expected ways to address the land-use classification issue. The commonly used scene classification methods of VHSR imagery are all derived from the computer vision community that mainly deal with terrestrial image recognition. Differing from terrestrial images, VHSR images are taken by looking down with airborne and spaceborne sensors, which leads to the distinct light conditions and spatial configuration of land cover in VHSR imagery. Considering the distinct characteristics, two questions should be answered: (1) Which type or combination of information is suitable for the VHSR imagery scene classification? (2) Which scene classification algorithm is best for VHSR imagery? In this paper, an efficient spectral-structural bag-of-features scene classifier (SSBFC) is proposed to combine the spectral and structural information of VHSR imagery. SSBFC utilizes the first- and second-order statistics (the mean and standard deviation values, MeanStd) as the statistical spectral descriptor for the spectral information of the VHSR imagery, and uses dense scale-invariant feature transform (SIFT) as the structural feature descriptor. From the experimental results, the spectral information works better than the structural information, while the combination of the spectral and structural information is better than any single type of information. Taking the characteristic of the spatial configuration into consideration, SSBFC uses the whole image scene as the scope of the pooling operator, instead of the scope generated by a spatial pyramid (SP) commonly used in terrestrial image classification. The experimental results show that the whole image as the scope of the pooling operator performs better than the scope generated by SP. In addition, SSBFC codes and pools the spectral and structural features separately to avoid mutual interruption between the spectral and structural features. The coding vectors of spectral and structural features are then concatenated into a final coding vector. Finally, SSBFC classifies the final coding vector by support vector machine (SVM) with a histogram intersection kernel (HIK). Compared with the latest scene classification methods, the experimental results with three VHSR datasets demonstrate that the proposed SSBFC performs better than the other classification methods for VHSR image scenes.
Rényi generalizations of the conditional quantum mutual information
NASA Astrophysics Data System (ADS)
Berta, Mario; Seshadreesan, Kaushik P.; Wilde, Mark M.
2015-02-01
The conditional quantum mutual information I(A; B|C) of a tripartite state ρABC is an information quantity which lies at the center of many problems in quantum information theory. Three of its main properties are that it is non-negative for any tripartite state, that it decreases under local operations applied to systems A and B, and that it obeys the duality relation I(A; B|C) = I(A; B|D) for a four-party pure state on systems ABCD. The conditional mutual information also underlies the squashed entanglement, an entanglement measure that satisfies all of the axioms desired for an entanglement measure. As such, it has been an open question to find Rényi generalizations of the conditional mutual information, that would allow for a deeper understanding of the original quantity and find applications beyond the traditional memoryless setting of quantum information theory. The present paper addresses this question, by defining different α-Rényi generalizations Iα(A; B|C) of the conditional mutual information, some of which we can prove converge to the conditional mutual information in the limit α → 1. Furthermore, we prove that many of these generalizations satisfy non-negativity, duality, and monotonicity with respect to local operations on one of the systems A or B (with it being left as an open question to prove that monotonicity holds with respect to local operations on both systems). The quantities defined here should find applications in quantum information theory and perhaps even in other areas of physics, but we leave this for future work. We also state a conjecture regarding the monotonicity of the Rényi conditional mutual informations defined here with respect to the Rényi parameter α. We prove that this conjecture is true in some special cases and when α is in a neighborhood of one.
Rényi generalizations of the conditional quantum mutual information
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berta, Mario; Seshadreesan, Kaushik P.; Wilde, Mark M.
2015-02-15
The conditional quantum mutual information I(A; B|C) of a tripartite state ρ{sub ABC} is an information quantity which lies at the center of many problems in quantum information theory. Three of its main properties are that it is non-negative for any tripartite state, that it decreases under local operations applied to systems A and B, and that it obeys the duality relation I(A; B|C) = I(A; B|D) for a four-party pure state on systems ABCD. The conditional mutual information also underlies the squashed entanglement, an entanglement measure that satisfies all of the axioms desired for an entanglement measure. As such,more » it has been an open question to find Rényi generalizations of the conditional mutual information, that would allow for a deeper understanding of the original quantity and find applications beyond the traditional memoryless setting of quantum information theory. The present paper addresses this question, by defining different α-Rényi generalizations I{sub α}(A; B|C) of the conditional mutual information, some of which we can prove converge to the conditional mutual information in the limit α → 1. Furthermore, we prove that many of these generalizations satisfy non-negativity, duality, and monotonicity with respect to local operations on one of the systems A or B (with it being left as an open question to prove that monotonicity holds with respect to local operations on both systems). The quantities defined here should find applications in quantum information theory and perhaps even in other areas of physics, but we leave this for future work. We also state a conjecture regarding the monotonicity of the Rényi conditional mutual informations defined here with respect to the Rényi parameter α. We prove that this conjecture is true in some special cases and when α is in a neighborhood of one.« less
[What makes an insect a vector?].
Kampen, Helge
2009-01-01
Blood-feeding insects transmit numerous viruses, bacteria, protozoans and helminths to vertebrates. The developmental cycles of the microorganisms in their vectors and the mechanisms of transmission are generally extremely complex and the result of a long-lasting coevolution of vector and vectored pathogen based on mutual adaptation. The conditions necessary for an insect to become a vector are multiple but require an innate vector competence as a genetic basis. Next to the vector competence plenty of entomological, ecological and pathogen-related factors are decisive, given the availability of infection sources. The various modes of pathogen transmission by vectors are connected to the developmental routes of the microorganisms in their vectors. In particular, pathogens transmitted by saliva encounter a lot of cellular and acellular barriers during their migration from the insect's midgut through the hemocele into the salivary fluid, including components of the insect's immune system. With regard to intracellular development, receptor-mediated invasion mechanisms are of relevance. As an environmental factor, the temperature has a paramount impact on the vectorial roles of hematophagous insects. Not only has it a considerable influence on the duration of a pathogen's development in its vector (extrinsic incubation period) but it can render putatively vector-incompetent insects to vectors ("leaky gut" phenomenon). Equally crucial are behavioural aspects of both the insect and the pathogen such as blood host preferences, seasonal appearance and circadian biting activity on the vector's side and diurnal/nocturnal periodicity on the pathogen's side which facilitate a contact in the first place.
Bleul, Christiane; Baumann-Klausener, Franziska; Labhart, Thomas; Dickinson, Michael H.
2016-01-01
Many insects exploit skylight polarization as a compass cue for orientation and navigation. In the fruit fly, Drosophila melanogaster, photoreceptors R7 and R8 in the dorsal rim area (DRA) of the compound eye are specialized to detect the electric vector (e-vector) of linearly polarized light. These photoreceptors are arranged in stacked pairs with identical fields of view and spectral sensitivities, but mutually orthogonal microvillar orientations. As in larger flies, we found that the microvillar orientation of the distal photoreceptor R7 changes in a fan-like fashion along the DRA. This anatomical arrangement suggests that the DRA constitutes a detector for skylight polarization, in which different e-vectors maximally excite different positions in the array. To test our hypothesis, we measured responses to polarized light of varying e-vector angles in the terminals of R7/8 cells using genetically encoded calcium indicators. Our data confirm a progression of preferred e-vector angles from anterior to posterior in the DRA, and a strict orthogonality between the e-vector preferences of paired R7/8 cells. We observed decreased activity in photoreceptors in response to flashes of light polarized orthogonally to their preferred e-vector angle, suggesting reciprocal inhibition between photoreceptors in the same medullar column, which may serve to increase polarization contrast. Together, our results indicate that the polarization-vision system relies on a spatial map of preferred e-vector angles at the earliest stage of sensory processing. SIGNIFICANCE STATEMENT The fly's visual system is an influential model system for studying neural computation, and much is known about its anatomy, physiology, and development. The circuits underlying motion processing have received the most attention, but researchers are increasingly investigating other functions, such as color perception and object recognition. In this work, we investigate the early neural processing of a somewhat exotic sense, called polarization vision. Because skylight is polarized in an orientation that is rigidly determined by the position of the sun, this cue provides compass information. Behavioral experiments have shown that many species use the polarization pattern in the sky to direct locomotion. Here we describe the input stage of the fly's polarization-vision system. PMID:27170135
Principal Components of Recurrence Quantification Analysis of EMG
2001-10-25
Springer, 1981, pp. 366-381. 4. M. Fraser and H. L. Swinney, “ Independent coordinates for strange attractors from mutual information ,” Phys. Rev. A...autocorrelation function of s(n), although it has also been argued that the first local minimum of the auto mutual information function is more appropriate [4...recordings from a given subject. T was taken as the lag corresponding to the first minimum of the auto mutual information function, calculated as
NASA Astrophysics Data System (ADS)
Nourani, Vahid; Andalib, Gholamreza; Dąbrowska, Dominika
2017-05-01
Accurate nitrate load predictions can elevate decision management of water quality of watersheds which affects to environment and drinking water. In this paper, two scenarios were considered for Multi-Station (MS) nitrate load modeling of the Little River watershed. In the first scenario, Markovian characteristics of streamflow-nitrate time series were proposed for the MS modeling. For this purpose, feature extraction criterion of Mutual Information (MI) was employed for input selection of artificial intelligence models (Feed Forward Neural Network, FFNN and least square support vector machine). In the second scenario for considering seasonality-based characteristics of the time series, wavelet transform was used to extract multi-scale features of streamflow-nitrate time series of the watershed's sub-basins to model MS nitrate loads. Self-Organizing Map (SOM) clustering technique which finds homogeneous sub-series clusters was also linked to MI for proper cluster agent choice to be imposed into the models for predicting the nitrate loads of the watershed's sub-basins. The proposed MS method not only considers the prediction of the outlet nitrate but also covers predictions of interior sub-basins nitrate load values. The results indicated that the proposed FFNN model coupled with the SOM-MI improved the performance of MS nitrate predictions compared to the Markovian-based models up to 39%. Overall, accurate selection of dominant inputs which consider seasonality-based characteristics of streamflow-nitrate process could enhance the efficiency of nitrate load predictions.
Code of Federal Regulations, 2011 CFR
2011-07-01
... to deter money laundering and terrorist activity for mutual funds. 1024.520 Section 1024.520 Money... ENFORCEMENT NETWORK, DEPARTMENT OF THE TREASURY RULES FOR MUTUAL FUNDS Special Information Sharing Procedures... deter money laundering and terrorist activity for mutual funds. (a) Refer to § 1010.520 of this chapter...
Mutual Information Rate and Bounds for It
Baptista, Murilo S.; Rubinger, Rero M.; Viana, Emilson R.; Sartorelli, José C.; Parlitz, Ulrich; Grebogi, Celso
2012-01-01
The amount of information exchanged per unit of time between two nodes in a dynamical network or between two data sets is a powerful concept for analysing complex systems. This quantity, known as the mutual information rate (MIR), is calculated from the mutual information, which is rigorously defined only for random systems. Moreover, the definition of mutual information is based on probabilities of significant events. This work offers a simple alternative way to calculate the MIR in dynamical (deterministic) networks or between two time series (not fully deterministic), and to calculate its upper and lower bounds without having to calculate probabilities, but rather in terms of well known and well defined quantities in dynamical systems. As possible applications of our bounds, we study the relationship between synchronisation and the exchange of information in a system of two coupled maps and in experimental networks of coupled oscillators. PMID:23112809
LDA boost classification: boosting by topics
NASA Astrophysics Data System (ADS)
Lei, La; Qiao, Guo; Qimin, Cao; Qitao, Li
2012-12-01
AdaBoost is an efficacious classification algorithm especially in text categorization (TC) tasks. The methodology of setting up a classifier committee and voting on the documents for classification can achieve high categorization precision. However, traditional Vector Space Model can easily lead to the curse of dimensionality and feature sparsity problems; so it affects classification performance seriously. This article proposed a novel classification algorithm called LDABoost based on boosting ideology which uses Latent Dirichlet Allocation (LDA) to modeling the feature space. Instead of using words or phrase, LDABoost use latent topics as the features. In this way, the feature dimension is significantly reduced. Improved Naïve Bayes (NB) is designed as the weaker classifier which keeps the efficiency advantage of classic NB algorithm and has higher precision. Moreover, a two-stage iterative weighted method called Cute Integration in this article is proposed for improving the accuracy by integrating weak classifiers into strong classifier in a more rational way. Mutual Information is used as metrics of weights allocation. The voting information and the categorization decision made by basis classifiers are fully utilized for generating the strong classifier. Experimental results reveals LDABoost making categorization in a low-dimensional space, it has higher accuracy than traditional AdaBoost algorithms and many other classic classification algorithms. Moreover, its runtime consumption is lower than different versions of AdaBoost, TC algorithms based on support vector machine and Neural Networks.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Popple, R; Bredel, M; Brezovich, I
Purpose: To compare the accuracy of CT-MR registration using a mutual information method with registration using a frame-based localizer box. Methods: Ten patients having the Leksell head frame and scanned with a modality specific localizer box were imported into the treatment planning system. The fiducial rods of the localizer box were contoured on both the MR and CT scans. The skull was contoured on the CT images. The MR and CT images were registered by two methods. The frame-based method used the transformation that minimized the mean square distance of the centroids of the contours of the fiducial rods frommore » a mathematical model of the localizer. The mutual information method used automated image registration tools in the TPS and was restricted to a volume-of-interest defined by the skull contours with a 5 mm margin. For each case, the two registrations were adjusted by two evaluation teams, each comprised of an experienced radiation oncologist and neurosurgeon, to optimize alignment in the region of the brainstem. The teams were blinded to the registration method. Results: The mean adjustment was 0.4 mm (range 0 to 2 mm) and 0.2 mm (range 0 to 1 mm) for the frame and mutual information methods, respectively. The median difference between the frame and mutual information registrations was 0.3 mm, but was not statistically significant using the Wilcoxon signed rank test (p=0.37). Conclusion: The difference between frame and mutual information registration techniques was neither statistically significant nor, for most applications, clinically important. These results suggest that mutual information is equivalent to frame-based image registration for radiosurgery. Work is ongoing to add additional evaluators and to assess the differences between evaluators.« less
Quantum Darwinism for mixed-state environment
NASA Astrophysics Data System (ADS)
Quan, Haitao; Zwolak, Michael; Zurek, Wojciech
2009-03-01
We exam quantum darwinism when a system is in the presence of a mixed environment, and we find a general relation between the mutual information for the mixed-state environment and the change of the entropy of the fraction of the environment. We then look at a particular solvable model, and we numerically exam the time evolution of the ``mutual information" for large environment. Finally we discuss about the exact expressions for all entropies and the mutual information at special time.
Entanglement entropy and mutual information production rates in acoustic black holes.
Giovanazzi, Stefano
2011-01-07
A method to investigate acoustic Hawking radiation is proposed, where entanglement entropy and mutual information are measured from the fluctuations of the number of particles. The rate of entropy radiated per one-dimensional (1D) channel is given by S=κ/12, where κ is the sound acceleration on the sonic horizon. This entropy production is accompanied by a corresponding formation of mutual information to ensure the overall conservation of information. The predictions are confirmed using an ab initio analytical approach in transonic flows of 1D degenerate ideal Fermi fluids.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Riyahi, S; Choi, W; Bhooshan, N
2016-06-15
Purpose: To compare linear and deformable registration methods for evaluation of tumor response to Chemoradiation therapy (CRT) in patients with esophageal cancer. Methods: Linear and multi-resolution BSpline deformable registration were performed on Pre-Post-CRT CT/PET images of 20 patients with esophageal cancer. For both registration methods, we registered CT using Mean Square Error (MSE) metric, however to register PET we used transformation obtained using Mutual Information (MI) from the same CT due to being multi-modality. Similarity of Warped-CT/PET was quantitatively evaluated using Normalized Mutual Information and plausibility of DF was assessed using inverse consistency Error. To evaluate tumor response four groupsmore » of tumor features were examined: (1) Conventional PET/CT e.g. SUV, diameter (2) Clinical parameters e.g. TNM stage, histology (3)spatial-temporal PET features that describe intensity, texture and geometry of tumor (4)all features combined. Dominant features were identified using 10-fold cross-validation and Support Vector Machine (SVM) was deployed for tumor response prediction while the accuracy was evaluated by ROC Area Under Curve (AUC). Results: Average and standard deviation of Normalized mutual information for deformable registration using MSE was 0.2±0.054 and for linear registration was 0.1±0.026, showing higher NMI for deformable registration. Likewise for MI metric, deformable registration had 0.13±0.035 comparing to linear counterpart with 0.12±0.037. Inverse consistency error for deformable registration for MSE metric was 4.65±2.49 and for linear was 1.32±2.3 showing smaller value for linear registration. The same conclusion was obtained for MI in terms of inverse consistency error. AUC for both linear and deformable registration was 1 showing no absolute difference in terms of response evaluation. Conclusion: Deformable registration showed better NMI comparing to linear registration, however inverse consistency of transformation was lower in linear registration. We do not expect to see significant difference when warping PET images using deformable or linear registration. This work was supported in part by the National Cancer Institute Grants R01CA172638.« less
Exploring Proxy Measures of Mutuality for Strategic Partnership Development: A Case Study.
Mayo-Gamble, Tilicia L; Barnes, Priscilla A; Sherwood-Laughlin, Catherine M; Reece, Michael; DeWeese, Sandy; Kennedy, Carol Weiss; Valenta, Mary Ann
2017-07-01
Partnerships between academic and clinical-based health organizations are becoming increasingly important in improving health outcomes. Mutuality is recognized as a vital component of these partnerships. If partnerships are to achieve mutuality, there is a need to define what it means to partnering organizations. Few studies have described the elements contributing to mutuality, particularly in new relationships between academic and clinical partners. This study seeks to identify how mutuality is expressed and to explore potential proxy measures of mutuality for an alliance consisting of a hospital system and a School of Public Health. Key informant interviews were conducted with faculty and hospital representatives serving on the partnership steering committee. Key informants were asked about perceived events that led to the development of the Alliance; perceived goals, expectations, and outcomes; and current/future roles with the Alliance. Four proxy measures of mutuality for an academic-clinical partnership were identified: policy directives, community beneficence, procurement of human capital, and partnership longevity. Findings can inform the development of tools for assisting in strengthening relationships and ensuring stakeholders' interests align with the mission and goal of the partnership by operationalizing elements necessary to evaluate the progress of the partnership.
75 FR 53322 - Agency Information Collection Activities: New Information Collection; Comment Request
Federal Register 2010, 2011, 2012, 2013, 2014
2010-08-31
... Information Collection for Review; ICE Mutual Agreement between Government and Employers (IMAGE), OMB No. 1653...) Title of the Form/Collection: IMAGE Information Request and Membership Application/ICE Mutual Agreement between Government and Employers (IMAGE) (3) Agency form number, if any, and the applicable component of...
A Feature Selection Method Based on Fisher's Discriminant Ratio for Text Sentiment Classification
NASA Astrophysics Data System (ADS)
Wang, Suge; Li, Deyu; Wei, Yingjie; Li, Hongxia
With the rapid growth of e-commerce, product reviews on the Web have become an important information source for customers' decision making when they intend to buy some product. As the reviews are often too many for customers to go through, how to automatically classify them into different sentiment orientation categories (i.e. positive/negative) has become a research problem. In this paper, based on Fisher's discriminant ratio, an effective feature selection method is proposed for product review text sentiment classification. In order to validate the validity of the proposed method, we compared it with other methods respectively based on information gain and mutual information while support vector machine is adopted as the classifier. In this paper, 6 subexperiments are conducted by combining different feature selection methods with 2 kinds of candidate feature sets. Under 1006 review documents of cars, the experimental results indicate that the Fisher's discriminant ratio based on word frequency estimation has the best performance with F value 83.3% while the candidate features are the words which appear in both positive and negative texts.
Electron in higher-dimensional weakly charged rotating black hole spacetimes
NASA Astrophysics Data System (ADS)
Cariglia, Marco; Frolov, Valeri P.; Krtouš, Pavel; Kubizňák, David
2013-03-01
We demonstrate separability of the Dirac equation in weakly charged rotating black hole spacetimes in all dimensions. The electromagnetic field of the black hole is described by a test field approximation, with the vector potential proportional to the primary Killing vector field. It is shown that the demonstrated separability can be intrinsically characterized by the existence of a complete set of mutually commuting first-order symmetry operators generated from the principal Killing-Yano tensor. The presented results generalize the results on integrability of charged particle motion and separability of charged scalar field studied in V. P. Frolov and P. Krtous [Phys. Rev. D 83, 024016 (2011)].
12 CFR 12.101 - National bank disclosure of remuneration for mutual fund transactions.
Code of Federal Regulations, 2011 CFR
2011-01-01
... mutual fund transactions. 12.101 Section 12.101 Banks and Banking COMPTROLLER OF THE CURRENCY, DEPARTMENT... Interpretations § 12.101 National bank disclosure of remuneration for mutual fund transactions. A national bank... by § 12.4, for mutual fund transactions by providing this information to the customer in a current...
12 CFR 12.101 - National bank disclosure of remuneration for mutual fund transactions.
Code of Federal Regulations, 2010 CFR
2010-01-01
... mutual fund transactions. 12.101 Section 12.101 Banks and Banking COMPTROLLER OF THE CURRENCY, DEPARTMENT... Interpretations § 12.101 National bank disclosure of remuneration for mutual fund transactions. A national bank... by § 12.4, for mutual fund transactions by providing this information to the customer in a current...
Attractor reconstruction for non-linear systems: a methodological note
Nichols, J.M.; Nichols, J.D.
2001-01-01
Attractor reconstruction is an important step in the process of making predictions for non-linear time-series and in the computation of certain invariant quantities used to characterize the dynamics of such series. The utility of computed predictions and invariant quantities is dependent on the accuracy of attractor reconstruction, which in turn is determined by the methods used in the reconstruction process. This paper suggests methods by which the delay and embedding dimension may be selected for a typical delay coordinate reconstruction. A comparison is drawn between the use of the autocorrelation function and mutual information in quantifying the delay. In addition, a false nearest neighbor (FNN) approach is used in minimizing the number of delay vectors needed. Results highlight the need for an accurate reconstruction in the computation of the Lyapunov spectrum and in prediction algorithms.
Savel'ev, Sergey E; Zagoskin, Alexandre M
2018-06-25
A popular interpretation of the "collapse" of the wave function is as being the result of a local interaction ("measurement") of the quantum system with a macroscopic system ("detector"), with the ensuing loss of phase coherence between macroscopically distinct components of its quantum state vector. Nevetheless as early as in 1953 Renninger suggested a Gedankenexperiment, in which the collapse is triggered by non-observation of one of two mutually exclusive outcomes of the measurement, i.e., in the absence of interaction of the quantum system with the detector. This provided a powerful argument in favour of "physical reality" of (nonlocal) quantum state vector. In this paper we consider a possible version of Renninger's experiment using the light propagation through a birefringent quantum metamaterial. Its realization would provide a clear visualization of a wave function collapse produced by a "non-measurement", and make the concept of a physically real quantum state vector more acceptable.
Invasive mutualisms between a plant pathogen and insect vectors in the Middle East and Brazil
Queiroz, Renan Batista; Silva, Fábio Nascimento; Al-Mahmmoli, Issa Hashil; Al-Sadi, Abdullah Mohammed; Carvalho, Claudine Márcia; Elliot, Simon L.
2016-01-01
Complex multi-trophic interactions in vectorborne diseases limit our understanding and ability to predict outbreaks. Arthropod-vectored pathogens are especially problematic, with the potential for novel interspecific interactions during invasions. Variations and novelties in plant–arthropod–pathogen triumvirates present significant threats to global food security. We examined aspects of a phytoplasma pathogen of citrus across two continents. ‘Candidatus Phytoplasma aurantifolia’ causes Witches' Broom Disease of Lime (WBDL) and has devastated citrus production in the Middle East. A variant of this phytoplasma currently displays asymptomatic or ‘silent’ infections in Brazil. We first studied vector capacity and fitness impacts of the pathogen on its vectors. The potential for co-occurring weed species to act as pathogen reservoirs was analysed and key transmission periods in the year were also studied. We demonstrate that two invasive hemipteran insects—Diaphorina citri and Hishimonus phycitis—can vector the phytoplasma. Feeding on phytoplasma-infected hosts greatly increased reproduction of its invasive vector D. citri both in Oman and Brazil; suggesting that increased fitness of invasive insect vectors thereby further increases the pathogen's capacity to spread. Based on our findings, this is a robust system for studying the effects of invasions on vectorborne diseases and highlights concerns about its spread to warmer, drier regions of Brazil. PMID:28083099
Enhancement of plant metabolite fingerprinting by machine learning.
Scott, Ian M; Vermeer, Cornelia P; Liakata, Maria; Corol, Delia I; Ward, Jane L; Lin, Wanchang; Johnson, Helen E; Whitehead, Lynne; Kular, Baldeep; Baker, John M; Walsh, Sean; Dave, Anuja; Larson, Tony R; Graham, Ian A; Wang, Trevor L; King, Ross D; Draper, John; Beale, Michael H
2010-08-01
Metabolite fingerprinting of Arabidopsis (Arabidopsis thaliana) mutants with known or predicted metabolic lesions was performed by (1)H-nuclear magnetic resonance, Fourier transform infrared, and flow injection electrospray-mass spectrometry. Fingerprinting enabled processing of five times more plants than conventional chromatographic profiling and was competitive for discriminating mutants, other than those affected in only low-abundance metabolites. Despite their rapidity and complexity, fingerprints yielded metabolomic insights (e.g. that effects of single lesions were usually not confined to individual pathways). Among fingerprint techniques, (1)H-nuclear magnetic resonance discriminated the most mutant phenotypes from the wild type and Fourier transform infrared discriminated the fewest. To maximize information from fingerprints, data analysis was crucial. One-third of distinctive phenotypes might have been overlooked had data models been confined to principal component analysis score plots. Among several methods tested, machine learning (ML) algorithms, namely support vector machine or random forest (RF) classifiers, were unsurpassed for phenotype discrimination. Support vector machines were often the best performing classifiers, but RFs yielded some particularly informative measures. First, RFs estimated margins between mutant phenotypes, whose relations could then be visualized by Sammon mapping or hierarchical clustering. Second, RFs provided importance scores for the features within fingerprints that discriminated mutants. These scores correlated with analysis of variance F values (as did Kruskal-Wallis tests, true- and false-positive measures, mutual information, and the Relief feature selection algorithm). ML classifiers, as models trained on one data set to predict another, were ideal for focused metabolomic queries, such as the distinctiveness and consistency of mutant phenotypes. Accessible software for use of ML in plant physiology is highlighted.
Development of stock correlation networks using mutual information and financial big data.
Guo, Xue; Zhang, Hu; Tian, Tianhai
2018-01-01
Stock correlation networks use stock price data to explore the relationship between different stocks listed in the stock market. Currently this relationship is dominantly measured by the Pearson correlation coefficient. However, financial data suggest that nonlinear relationships may exist in the stock prices of different shares. To address this issue, this work uses mutual information to characterize the nonlinear relationship between stocks. Using 280 stocks traded at the Shanghai Stocks Exchange in China during the period of 2014-2016, we first compare the effectiveness of the correlation coefficient and mutual information for measuring stock relationships. Based on these two measures, we then develop two stock networks using the Minimum Spanning Tree method and study the topological properties of these networks, including degree, path length and the power-law distribution. The relationship network based on mutual information has a better distribution of the degree and larger value of the power-law distribution than those using the correlation coefficient. Numerical results show that mutual information is a more effective approach than the correlation coefficient to measure the stock relationship in a stock market that may undergo large fluctuations of stock prices.
Development of stock correlation networks using mutual information and financial big data
Guo, Xue; Zhang, Hu
2018-01-01
Stock correlation networks use stock price data to explore the relationship between different stocks listed in the stock market. Currently this relationship is dominantly measured by the Pearson correlation coefficient. However, financial data suggest that nonlinear relationships may exist in the stock prices of different shares. To address this issue, this work uses mutual information to characterize the nonlinear relationship between stocks. Using 280 stocks traded at the Shanghai Stocks Exchange in China during the period of 2014-2016, we first compare the effectiveness of the correlation coefficient and mutual information for measuring stock relationships. Based on these two measures, we then develop two stock networks using the Minimum Spanning Tree method and study the topological properties of these networks, including degree, path length and the power-law distribution. The relationship network based on mutual information has a better distribution of the degree and larger value of the power-law distribution than those using the correlation coefficient. Numerical results show that mutual information is a more effective approach than the correlation coefficient to measure the stock relationship in a stock market that may undergo large fluctuations of stock prices. PMID:29668715
Cross Correlation versus Normalized Mutual Information on Image Registration
NASA Technical Reports Server (NTRS)
Tan, Bin; Tilton, James C.; Lin, Guoqing
2016-01-01
This is the first study to quantitatively assess and compare cross correlation and normalized mutual information methods used to register images in subpixel scale. The study shows that the normalized mutual information method is less sensitive to unaligned edges due to the spectral response differences than is cross correlation. This characteristic makes the normalized image resolution a better candidate for band to band registration. Improved band-to-band registration in the data from satellite-borne instruments will result in improved retrievals of key science measurements such as cloud properties, vegetation, snow and fire.
Faghihi, Faramarz; Kolodziejski, Christoph; Fiala, André; Wörgötter, Florentin; Tetzlaff, Christian
2013-12-20
Fruit flies (Drosophila melanogaster) rely on their olfactory system to process environmental information. This information has to be transmitted without system-relevant loss by the olfactory system to deeper brain areas for learning. Here we study the role of several parameters of the fly's olfactory system and the environment and how they influence olfactory information transmission. We have designed an abstract model of the antennal lobe, the mushroom body and the inhibitory circuitry. Mutual information between the olfactory environment, simulated in terms of different odor concentrations, and a sub-population of intrinsic mushroom body neurons (Kenyon cells) was calculated to quantify the efficiency of information transmission. With this method we study, on the one hand, the effect of different connectivity rates between olfactory projection neurons and firing thresholds of Kenyon cells. On the other hand, we analyze the influence of inhibition on mutual information between environment and mushroom body. Our simulations show an expected linear relation between the connectivity rate between the antennal lobe and the mushroom body and firing threshold of the Kenyon cells to obtain maximum mutual information for both low and high odor concentrations. However, contradicting all-day experiences, high odor concentrations cause a drastic, and unrealistic, decrease in mutual information for all connectivity rates compared to low concentration. But when inhibition on the mushroom body is included, mutual information remains at high levels independent of other system parameters. This finding points to a pivotal role of inhibition in fly information processing without which the system efficiency will be substantially reduced.
Sea Ice Detection Based on an Improved Similarity Measurement Method Using Hyperspectral Data.
Han, Yanling; Li, Jue; Zhang, Yun; Hong, Zhonghua; Wang, Jing
2017-05-15
Hyperspectral remote sensing technology can acquire nearly continuous spectrum information and rich sea ice image information, thus providing an important means of sea ice detection. However, the correlation and redundancy among hyperspectral bands reduce the accuracy of traditional sea ice detection methods. Based on the spectral characteristics of sea ice, this study presents an improved similarity measurement method based on linear prediction (ISMLP) to detect sea ice. First, the first original band with a large amount of information is determined based on mutual information theory. Subsequently, a second original band with the least similarity is chosen by the spectral correlation measuring method. Finally, subsequent bands are selected through the linear prediction method, and a support vector machine classifier model is applied to classify sea ice. In experiments performed on images of Baffin Bay and Bohai Bay, comparative analyses were conducted to compare the proposed method and traditional sea ice detection methods. Our proposed ISMLP method achieved the highest classification accuracies (91.18% and 94.22%) in both experiments. From these results the ISMLP method exhibits better performance overall than other methods and can be effectively applied to hyperspectral sea ice detection.
Sea Ice Detection Based on an Improved Similarity Measurement Method Using Hyperspectral Data
Han, Yanling; Li, Jue; Zhang, Yun; Hong, Zhonghua; Wang, Jing
2017-01-01
Hyperspectral remote sensing technology can acquire nearly continuous spectrum information and rich sea ice image information, thus providing an important means of sea ice detection. However, the correlation and redundancy among hyperspectral bands reduce the accuracy of traditional sea ice detection methods. Based on the spectral characteristics of sea ice, this study presents an improved similarity measurement method based on linear prediction (ISMLP) to detect sea ice. First, the first original band with a large amount of information is determined based on mutual information theory. Subsequently, a second original band with the least similarity is chosen by the spectral correlation measuring method. Finally, subsequent bands are selected through the linear prediction method, and a support vector machine classifier model is applied to classify sea ice. In experiments performed on images of Baffin Bay and Bohai Bay, comparative analyses were conducted to compare the proposed method and traditional sea ice detection methods. Our proposed ISMLP method achieved the highest classification accuracies (91.18% and 94.22%) in both experiments. From these results the ISMLP method exhibits better performance overall than other methods and can be effectively applied to hyperspectral sea ice detection. PMID:28505135
Federal Register 2010, 2011, 2012, 2013, 2014
2013-06-12
...-end investment company (mutual fund) when a fiduciary with respect to the plan is also the investment advisor for the mutual fund. There are three basic disclosure requirements incorporated within PTE 77-4... mutual fund. The second requirement is that, at the time of the purchase or sale of such mutual fund...
Mutual information and spontaneous symmetry breaking
NASA Astrophysics Data System (ADS)
Hamma, A.; Giampaolo, S. M.; Illuminati, F.
2016-01-01
We show that the metastable, symmetry-breaking ground states of quantum many-body Hamiltonians have vanishing quantum mutual information between macroscopically separated regions and are thus the most classical ones among all possible quantum ground states. This statement is obvious only when the symmetry-breaking ground states are simple product states, e.g., at the factorization point. On the other hand, symmetry-breaking states are in general entangled along the entire ordered phase, and to show that they actually feature the least macroscopic correlations compared to their symmetric superpositions is highly nontrivial. We prove this result in general, by considering the quantum mutual information based on the two-Rényi entanglement entropy and using a locality result stemming from quasiadiabatic continuation. Moreover, in the paradigmatic case of the exactly solvable one-dimensional quantum X Y model, we further verify the general result by considering also the quantum mutual information based on the von Neumann entanglement entropy.
[Non-rigid medical image registration based on mutual information and thin-plate spline].
Cao, Guo-gang; Luo, Li-min
2009-01-01
To get precise and complete details, the contrast in different images is needed in medical diagnosis and computer assisted treatment. The image registration is the basis of contrast, but the regular rigid registration does not satisfy the clinic requirements. A non-rigid medical image registration method based on mutual information and thin-plate spline was present. Firstly, registering two images globally based on mutual information; secondly, dividing reference image and global-registered image into blocks and registering them; then getting the thin-plate spline transformation according to the shift of blocks' center; finally, applying the transformation to the global-registered image. The results show that the method is more precise than the global rigid registration based on mutual information and it reduces the complexity of getting control points and satisfy the clinic requirements better by getting control points of the thin-plate transformation automatically.
Hierarchical clustering using mutual information
NASA Astrophysics Data System (ADS)
Kraskov, A.; Stögbauer, H.; Andrzejak, R. G.; Grassberger, P.
2005-04-01
We present a conceptually simple method for hierarchical clustering of data called mutual information clustering (MIC) algorithm. It uses mutual information (MI) as a similarity measure and exploits its grouping property: The MI between three objects X, Y, and Z is equal to the sum of the MI between X and Y, plus the MI between Z and the combined object (XY). We use this both in the Shannon (probabilistic) version of information theory and in the Kolmogorov (algorithmic) version. We apply our method to the construction of phylogenetic trees from mitochondrial DNA sequences and to the output of independent components analysis (ICA) as illustrated with the ECG of a pregnant woman.
Developmental Experience Alters Information Coding in Auditory Midbrain and Forebrain Neurons
Woolley, Sarah M. N.; Hauber, Mark E.; Theunissen, Frederic E.
2010-01-01
In songbirds, species identity and developmental experience shape vocal behavior and behavioral responses to vocalizations. The interaction of species identity and developmental experience may also shape the coding properties of sensory neurons. We tested whether responses of auditory midbrain and forebrain neurons to songs differed between species and between groups of conspecific birds with different developmental exposure to song. We also compared responses of individual neurons to conspecific and heterospecific songs. Zebra and Bengalese finches that were raised and tutored by conspecific birds, and zebra finches that were cross-tutored by Bengalese finches were studied. Single-unit responses to zebra and Bengalese finch songs were recorded and analyzed by calculating mutual information, response reliability, mean spike rate, fluctuations in time-varying spike rate, distributions of time-varying spike rates, and neural discrimination of individual songs. Mutual information quantifies a response’s capacity to encode information about a stimulus. In midbrain and forebrain neurons, mutual information was significantly higher in normal zebra finch neurons than in Bengalese finch and cross-tutored zebra finch neurons, but not between Bengalese finch and cross-tutored zebra finch neurons. Information rate differences were largely due to spike rate differences. Mutual information did not differ between responses to conspecific and heterospecific songs. Therefore, neurons from normal zebra finches encoded more information about songs than did neurons from other birds, but conspecific and heterospecific songs were encoded equally. Neural discrimination of songs and mutual information were highly correlated. Results demonstrate that developmental exposure to vocalizations shapes the information coding properties of songbird auditory neurons. PMID:20039264
Finite Geometries in Quantum Theory:. from Galois (fields) to Hjelmslev (rings)
NASA Astrophysics Data System (ADS)
Saniga, Metod; Planat, Michel
Geometries over Galois fields (and related finite combinatorial structures/algebras) have recently been recognized to play an ever-increasing role in quantum theory, especially when addressing properties of mutually unbiased bases (MUBs). The purpose of this contribution is to show that completely new vistas open up if we consider a generalized class of finite (projective) geometries, viz. those defined over Galois rings and/or other finite Hjelmslev rings. The case is illustrated by demonstrating that the basic combinatorial properties of a complete set of MUBs of a q-dimensional Hilbert space { H}q, q = pr with p being a prime and r a positive integer, are qualitatively mimicked by the configuration of points lying on a proper conic in a projective Hjelmslev plane defined over a Galois ring of characteristic p2 and rank r. The q vectors of a basis of { H}q correspond to the q points of a (so-called) neighbour class and the q + 1 MUBs answer to the total number of (pairwise disjoint) neighbour classes on the conic. Although this remarkable analogy is still established at the level of cardinalities only, we currently work on constructing an explicit mapping by associating a MUB to each neighbour class of the points of the conic and a state vector of this MUB to a particular point of the class. Further research in this direction may prove to be of great relevance for many areas of quantum information theory, in particular for quantum information processing.
Problem decomposition by mutual information and force-based clustering
NASA Astrophysics Data System (ADS)
Otero, Richard Edward
The scale of engineering problems has sharply increased over the last twenty years. Larger coupled systems, increasing complexity, and limited resources create a need for methods that automatically decompose problems into manageable sub-problems by discovering and leveraging problem structure. The ability to learn the coupling (inter-dependence) structure and reorganize the original problem could lead to large reductions in the time to analyze complex problems. Such decomposition methods could also provide engineering insight on the fundamental physics driving problem solution. This work forwards the current state of the art in engineering decomposition through the application of techniques originally developed within computer science and information theory. The work describes the current state of automatic problem decomposition in engineering and utilizes several promising ideas to advance the state of the practice. Mutual information is a novel metric for data dependence and works on both continuous and discrete data. Mutual information can measure both the linear and non-linear dependence between variables without the limitations of linear dependence measured through covariance. Mutual information is also able to handle data that does not have derivative information, unlike other metrics that require it. The value of mutual information to engineering design work is demonstrated on a planetary entry problem. This study utilizes a novel tool developed in this work for planetary entry system synthesis. A graphical method, force-based clustering, is used to discover related sub-graph structure as a function of problem structure and links ranked by their mutual information. This method does not require the stochastic use of neural networks and could be used with any link ranking method currently utilized in the field. Application of this method is demonstrated on a large, coupled low-thrust trajectory problem. Mutual information also serves as the basis for an alternative global optimizer, called MIMIC, which is unrelated to Genetic Algorithms. Advancement to the current practice demonstrates the use of MIMIC as a global method that explicitly models problem structure with mutual information, providing an alternate method for globally searching multi-modal domains. By leveraging discovered problem inter- dependencies, MIMIC may be appropriate for highly coupled problems or those with large function evaluation cost. This work introduces a useful addition to the MIMIC algorithm that enables its use on continuous input variables. By leveraging automatic decision tree generation methods from Machine Learning and a set of randomly generated test problems, decision trees for which method to apply are also created, quantifying decomposition performance over a large region of the design space.
Poynting Vector in High-Temperature Superconducting Transformers with a Separate Excitation Winding
NASA Astrophysics Data System (ADS)
Volkov, E. P.; Dzhafarov, E. A.
2017-12-01
The HTSC transformer with a separate winding for excitation of the mutual magnetic flux is considered; the windings of the transformer are performed of first- or second-generation HTSC wires. The article presents the design and the electrical circuit of the transformer, the equations of electromagnetic balance, and the total resistance of the primary and secondary power windings and the separate excitation winding. The transfer of the electromagnetic field energy is considered in a single-phase HTSC transformer with the separate excitation winding using the Poynting vector. The temporal change in the reactive and active components of the Poynting vector and the decrease in the leakage energy flux of the separate excitation winding are shown, which causes an increase in the critical current density of the HTSC power windings, a decrease in the energy losses in the latter, and an increase the in the specific power of the HTSC transformer.
Weir, Peter T; Henze, Miriam J; Bleul, Christiane; Baumann-Klausener, Franziska; Labhart, Thomas; Dickinson, Michael H
2016-05-11
Many insects exploit skylight polarization as a compass cue for orientation and navigation. In the fruit fly, Drosophila melanogaster, photoreceptors R7 and R8 in the dorsal rim area (DRA) of the compound eye are specialized to detect the electric vector (e-vector) of linearly polarized light. These photoreceptors are arranged in stacked pairs with identical fields of view and spectral sensitivities, but mutually orthogonal microvillar orientations. As in larger flies, we found that the microvillar orientation of the distal photoreceptor R7 changes in a fan-like fashion along the DRA. This anatomical arrangement suggests that the DRA constitutes a detector for skylight polarization, in which different e-vectors maximally excite different positions in the array. To test our hypothesis, we measured responses to polarized light of varying e-vector angles in the terminals of R7/8 cells using genetically encoded calcium indicators. Our data confirm a progression of preferred e-vector angles from anterior to posterior in the DRA, and a strict orthogonality between the e-vector preferences of paired R7/8 cells. We observed decreased activity in photoreceptors in response to flashes of light polarized orthogonally to their preferred e-vector angle, suggesting reciprocal inhibition between photoreceptors in the same medullar column, which may serve to increase polarization contrast. Together, our results indicate that the polarization-vision system relies on a spatial map of preferred e-vector angles at the earliest stage of sensory processing. The fly's visual system is an influential model system for studying neural computation, and much is known about its anatomy, physiology, and development. The circuits underlying motion processing have received the most attention, but researchers are increasingly investigating other functions, such as color perception and object recognition. In this work, we investigate the early neural processing of a somewhat exotic sense, called polarization vision. Because skylight is polarized in an orientation that is rigidly determined by the position of the sun, this cue provides compass information. Behavioral experiments have shown that many species use the polarization pattern in the sky to direct locomotion. Here we describe the input stage of the fly's polarization-vision system. Copyright © 2016 the authors 0270-6474/16/365397-08$15.00/0.
Waking and scrambling in holographic heating up
NASA Astrophysics Data System (ADS)
Ageev, D. S.; Aref'eva, I. Ya.
2017-10-01
Using holographic methods, we study the heating up process in quantum field theory. As a holographic dual of this process, we use absorption of a thin shell on a black brane. We find the explicit form of the time evolution of the quantum mutual information during heating up from the temperature Ti to the temperature T f in a system of two intervals in two-dimensional space-time. We determine the geometric characteristics of the system under which the time dependence of the mutual information has a bell shape: it is equal to zero at the initial instant, becomes positive at some subsequent instant, further attains its maximum, and again decreases to zero. Such a behavior of the mutual information occurs in the process of photosynthesis. We show that if the distance x between the intervals is less than log 2/2π T i, then the evolution of the holographic mutual information has a bell shape only for intervals whose lengths are bounded from above and below. For sufficiently large x, i.e., for x < log 2/2π T i, the bell-like shape of the time dependence of the quantum mutual information is present only for sufficiently large intervals. Moreover, the zone narrows as T i increases and widens as T f increases.
Hoyer, Dirk; Leder, Uwe; Hoyer, Heike; Pompe, Bernd; Sommer, Michael; Zwiener, Ulrich
2002-01-01
The heart rate variability (HRV) is related to several mechanisms of the complex autonomic functioning such as respiratory heart rate modulation and phase dependencies between heart beat cycles and breathing cycles. The underlying processes are basically nonlinear. In order to understand and quantitatively assess those physiological interactions an adequate coupling analysis is necessary. We hypothesized that nonlinear measures of HRV and cardiorespiratory interdependencies are superior to the standard HRV measures in classifying patients after acute myocardial infarction. We introduced mutual information measures which provide access to nonlinear interdependencies as counterpart to the classically linear correlation analysis. The nonlinear statistical autodependencies of HRV were quantified by auto mutual information, the respiratory heart rate modulation by cardiorespiratory cross mutual information, respectively. The phase interdependencies between heart beat cycles and breathing cycles were assessed basing on the histograms of the frequency ratios of the instantaneous heart beat and respiratory cycles. Furthermore, the relative duration of phase synchronized intervals was acquired. We investigated 39 patients after acute myocardial infarction versus 24 controls. The discrimination of these groups was improved by cardiorespiratory cross mutual information measures and phase interdependencies measures in comparison to the linear standard HRV measures. This result was statistically confirmed by means of logistic regression models of particular variable subsets and their receiver operating characteristics.
Mutual information identifies spurious Hurst phenomena in resting state EEG and fMRI data
NASA Astrophysics Data System (ADS)
von Wegner, Frederic; Laufs, Helmut; Tagliazucchi, Enzo
2018-02-01
Long-range memory in time series is often quantified by the Hurst exponent H , a measure of the signal's variance across several time scales. We analyze neurophysiological time series from electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) resting state experiments with two standard Hurst exponent estimators and with the time-lagged mutual information function applied to discretized versions of the signals. A confidence interval for the mutual information function is obtained from surrogate Markov processes with equilibrium distribution and transition matrix identical to the underlying signal. For EEG signals, we construct an additional mutual information confidence interval from a short-range correlated, tenth-order autoregressive model. We reproduce the previously described Hurst phenomenon (H >0.5 ) in the analytical amplitude of alpha frequency band oscillations, in EEG microstate sequences, and in fMRI signals, but we show that the Hurst phenomenon occurs without long-range memory in the information-theoretical sense. We find that the mutual information function of neurophysiological data behaves differently from fractional Gaussian noise (fGn), for which the Hurst phenomenon is a sufficient condition to prove long-range memory. Two other well-characterized, short-range correlated stochastic processes (Ornstein-Uhlenbeck, Cox-Ingersoll-Ross) also yield H >0.5 , whereas their mutual information functions lie within the Markovian confidence intervals, similar to neural signals. In these processes, which do not have long-range memory by construction, a spurious Hurst phenomenon occurs due to slow relaxation times and heteroscedasticity (time-varying conditional variance). In summary, we find that mutual information correctly distinguishes long-range from short-range dependence in the theoretical and experimental cases discussed. Our results also suggest that the stationary fGn process is not sufficient to describe neural data, which seem to belong to a more general class of stochastic processes, in which multiscale variance effects produce Hurst phenomena without long-range dependence. In our experimental data, the Hurst phenomenon and long-range memory appear as different system properties that should be estimated and interpreted independently.
Daub, Carsten O; Steuer, Ralf; Selbig, Joachim; Kloska, Sebastian
2004-01-01
Background The information theoretic concept of mutual information provides a general framework to evaluate dependencies between variables. In the context of the clustering of genes with similar patterns of expression it has been suggested as a general quantity of similarity to extend commonly used linear measures. Since mutual information is defined in terms of discrete variables, its application to continuous data requires the use of binning procedures, which can lead to significant numerical errors for datasets of small or moderate size. Results In this work, we propose a method for the numerical estimation of mutual information from continuous data. We investigate the characteristic properties arising from the application of our algorithm and show that our approach outperforms commonly used algorithms: The significance, as a measure of the power of distinction from random correlation, is significantly increased. This concept is subsequently illustrated on two large-scale gene expression datasets and the results are compared to those obtained using other similarity measures. A C++ source code of our algorithm is available for non-commercial use from kloska@scienion.de upon request. Conclusion The utilisation of mutual information as similarity measure enables the detection of non-linear correlations in gene expression datasets. Frequently applied linear correlation measures, which are often used on an ad-hoc basis without further justification, are thereby extended. PMID:15339346
Medical image registration based on normalized multidimensional mutual information
NASA Astrophysics Data System (ADS)
Li, Qi; Ji, Hongbing; Tong, Ming
2009-10-01
Registration of medical images is an essential research topic in medical image processing and applications, and especially a preliminary and key step for multimodality image fusion. This paper offers a solution to medical image registration based on normalized multi-dimensional mutual information. Firstly, affine transformation with translational and rotational parameters is applied to the floating image. Then ordinal features are extracted by ordinal filters with different orientations to represent spatial information in medical images. Integrating ordinal features with pixel intensities, the normalized multi-dimensional mutual information is defined as similarity criterion to register multimodality images. Finally the immune algorithm is used to search registration parameters. The experimental results demonstrate the effectiveness of the proposed registration scheme.
Equity trees and graphs via information theory
NASA Astrophysics Data System (ADS)
Harré, M.; Bossomaier, T.
2010-01-01
We investigate the similarities and differences between two measures of the relationship between equities traded in financial markets. Our measures are the correlation coefficients and the mutual information. In the context of financial markets correlation coefficients are well established whereas mutual information has not previously been as well studied despite its theoretically appealing properties. We show that asset trees which are derived from either the correlation coefficients or the mutual information have a mixture of both similarities and differences at the individual equity level and at the macroscopic level. We then extend our consideration from trees to graphs using the "genus 0" condition recently introduced in order to study the networks of equities.
Validation of a method to measure the vector fidelity of triaxial vector sensors
NASA Astrophysics Data System (ADS)
De Freitas, J. M.
2018-06-01
A method to measure the misalignment angles and vector fidelity of a mutually orthogonal arrangement of triaxial accelerometers has been validated by introducing known misalignments into the measurement procedure. The method is based on the excitation of all three accelerometers in equal measure and the determination of the second order responsivity tensor as a metric. The sensor axis misalignment angles measured using a sensor rotation technique as a reference were 1.49° ± 0.05°, 0.63° ± 0.02°, and 0.78° ± 0.04°. The resolution of the new approach against the reference was 0.03° with an accuracy of 0.2° and maximum deviation of 0.4°. An ellipticity tensor β that characterises the extent to which a triaxial system preserves the input polarisation state purity was introduced. In a careful laboratory arrangement, up to 98% input polarisation state purity was shown to be maintained. It is recommended that documentation on commercial and research grade high-precision triaxial sensor systems should give the responsivity matrix . This technique will improve the range of vector fidelity measurement tools for triaxial accelerometers and other vector sensors such as magnetometers, gyroscopes and acoustic vector sensors.
Tsetse flies: genetics, evolution, and role as vectors.
Krafsur, E S
2009-01-01
Tsetse flies (Diptera: Glossinidae) are an ancient taxon of one genus, Glossina, and limited species diversity. All are exclusively haematophagous and confined to sub-Saharan Africa. The Glossina are the principal vectors of African trypanosomes Trypanosoma sp. (Kinetoplastida: Trypanosomatidae) and as such, are of great medical and economic importance. Clearly tsetse flies and trypanosomes are coadapted and evolutionary interactions between them are manifest. Numerous clonally reproducing strains of Trypanosoma sp. exist and their genetic diversities and spatial distributions are inadequately known. Here I review the breeding structures of the principle trypanosome vectors, G. morsitans s.l., G. pallidipes, G. palpalis s.l. and G. fuscipes fuscipes. All show highly structured populations among which there is surprisingly little detectable gene flow. Rather less is known of the breeding structure of T. brucei sensu lato vis à vis their vector tsetse flies but many genetically differentiated strains exist in nature. Genetic recombination in Trypanosoma via meiosis has recently been demonstrated in the laboratory thereby furnishing a mechanism of strain differentiation in addition to that of simple mutation. Spatially and genetically representative sampling of both trypanosome species and strains and their Glossina vectors is a major barrier to a comprehensive understanding of their mutual relationships.
Tsetse flies: Genetics, evolution, and role as vectors
Krafsur, E. S.
2009-01-01
Tsetse flies (Diptera: Glossinidae) are an ancient taxon of one genus, Glossina, and limited species diversity. All are exclusively haematophagous and confined to sub-Saharan Africa. The Glossina are the principal vectors of African trypanosomes Trypanosoma sp (Kinetoplastida: Trypanosomatidae) and as such, are of great medical and economic importance. Clearly tsetse flies and trypanosomes are coadapted and evolutionary interactions between them are manifest. Numerous clonally reproducing strains of Trypanosoma sp exist and their genetic diversities and spatial distributions are inadequately known. Here I review the breeding structures of the principle trypanosome vectors, G. morsitans s.l., G. pallidipes, G. palpalis s.l. and G. fuscipes fuscipes. All show highly structured populations among which there is surprisingly little detectable gene flow. Rather less is known of the breeding structure of T. brucei sensu lato vis à vis their vector tsetse flies but many genetically differentiated strains exist in nature. Genetic recombination in Trypanosoma via meiosis has recently been demonstrated in the laboratory thereby furnishing a mechanism of strain differentiation in addition to that of simple mutation. Spatially and genetically representative sampling of both trypanosome species and strains and their Glossina vectors is a major barrier to a comprehensive understanding of their mutual relationships. PMID:18992846
A new implementation of the CMRH method for solving dense linear systems
NASA Astrophysics Data System (ADS)
Heyouni, M.; Sadok, H.
2008-04-01
The CMRH method [H. Sadok, Methodes de projections pour les systemes lineaires et non lineaires, Habilitation thesis, University of Lille1, Lille, France, 1994; H. Sadok, CMRH: A new method for solving nonsymmetric linear systems based on the Hessenberg reduction algorithm, Numer. Algorithms 20 (1999) 303-321] is an algorithm for solving nonsymmetric linear systems in which the Arnoldi component of GMRES is replaced by the Hessenberg process, which generates Krylov basis vectors which are orthogonal to standard unit basis vectors rather than mutually orthogonal. The iterate is formed from these vectors by solving a small least squares problem involving a Hessenberg matrix. Like GMRES, this method requires one matrix-vector product per iteration. However, it can be implemented to require half as much arithmetic work and less storage. Moreover, numerical experiments show that this method performs accurately and reduces the residual about as fast as GMRES. With this new implementation, we show that the CMRH method is the only method with long-term recurrence which requires not storing at the same time the entire Krylov vectors basis and the original matrix as in the GMRES algorithmE A comparison with Gaussian elimination is provided.
TOF-SIMS imaging technique with information entropy
NASA Astrophysics Data System (ADS)
Aoyagi, Satoka; Kawashima, Y.; Kudo, Masahiro
2005-05-01
Time-of-flight secondary ion mass spectrometry (TOF-SIMS) is capable of chemical imaging of proteins on insulated samples in principal. However, selection of specific peaks related to a particular protein, which are necessary for chemical imaging, out of numerous candidates had been difficult without an appropriate spectrum analysis technique. Therefore multivariate analysis techniques, such as principal component analysis (PCA), and analysis with mutual information defined by information theory, have been applied to interpret SIMS spectra of protein samples. In this study mutual information was applied to select specific peaks related to proteins in order to obtain chemical images. Proteins on insulated materials were measured with TOF-SIMS and then SIMS spectra were analyzed by means of the analysis method based on the comparison using mutual information. Chemical mapping of each protein was obtained using specific peaks related to each protein selected based on values of mutual information. The results of TOF-SIMS images of proteins on the materials provide some useful information on properties of protein adsorption, optimality of immobilization processes and reaction between proteins. Thus chemical images of proteins by TOF-SIMS contribute to understand interactions between material surfaces and proteins and to develop sophisticated biomaterials.
Terahertz Magnetoelectric Resonance Enhanced by Mutual Coupling of Electromagnons
NASA Astrophysics Data System (ADS)
Takahashi, Y.; Yamasaki, Y.; Tokura, Y.
2013-07-01
Both electric- and magnetic-dipole active spin excitations, i.e., electromagnons, which mediate the dynamical magnetoelectric effect, have been investigated for a multiferroic perovskite of manganite by optical spectroscopy at terahertz frequencies. Upon the magnetoelectric resonance at 1 meV in the multiferroic phase with the bc-plane spin cycloidal order, a gigantic dynamical magnetoelectric effect has been observed as a nonreciprocal directional dichroism or birefringence. The light k-vector-dependent difference (Δκ=κ+-κ-) of the extinction coefficient (κ±) is as large as Δκ˜1 or 2Δκ/(κ++κ-)˜0.7 at the lowest-lying electromagnon energy. We clarified the mutual coupling of the Eω∥a-polarized electromagnons of the different origins, leading to the enhancement of the magnetoelectric resonance.
Ground states of partially connected binary neural networks
NASA Technical Reports Server (NTRS)
Baram, Yoram
1990-01-01
Neural networks defined by outer products of vectors over (-1, 0, 1) are considered. Patterns over (-1, 0, 1) define by their outer products partially connected neural networks consisting of internally strongly connected, externally weakly connected subnetworks. Subpatterns over (-1, 1) define subnetworks, and their combinations that agree in the common bits define permissible words. It is shown that the permissible words are locally stable states of the network, provided that each of the subnetworks stores mutually orthogonal subwords, or, at most, two subwords. It is also shown that when each of the subnetworks stores two mutually orthogonal binary subwords at most, the permissible words, defined as the combinations of the subwords (one corresponding to each subnetwork), that agree in their common bits are the unique ground states of the associated energy function.
Competitive learning with pairwise constraints.
Covões, Thiago F; Hruschka, Eduardo R; Ghosh, Joydeep
2013-01-01
Constrained clustering has been an active research topic since the last decade. Most studies focus on batch-mode algorithms. This brief introduces two algorithms for on-line constrained learning, named on-line linear constrained vector quantization error (O-LCVQE) and constrained rival penalized competitive learning (C-RPCL). The former is a variant of the LCVQE algorithm for on-line settings, whereas the latter is an adaptation of the (on-line) RPCL algorithm to deal with constrained clustering. The accuracy results--in terms of the normalized mutual information (NMI)--from experiments with nine datasets show that the partitions induced by O-LCVQE are competitive with those found by the (batch-mode) LCVQE. Compared with this formidable baseline algorithm, it is surprising that C-RPCL can provide better partitions (in terms of the NMI) for most of the datasets. Also, experiments on a large dataset show that on-line algorithms for constrained clustering can significantly reduce the computational time.
Code of Federal Regulations, 2011 CFR
2011-07-01
... ENFORCEMENT NETWORK, DEPARTMENT OF THE TREASURY RULES FOR MUTUAL FUNDS Special Information Sharing Procedures To Deter Money Laundering and Terrorist Activity § 1024.500 General. Mutual funds are subject to the... forth and cross referenced in this subpart. Mutual funds should also refer to subpart E of part 1010 of...
Cui, Dong; Pu, Weiting; Liu, Jing; Bian, Zhijie; Li, Qiuli; Wang, Lei; Gu, Guanghua
2016-10-01
Synchronization is an important mechanism for understanding information processing in normal or abnormal brains. In this paper, we propose a new method called normalized weighted-permutation mutual information (NWPMI) for double variable signal synchronization analysis and combine NWPMI with S-estimator measure to generate a new method named S-estimator based normalized weighted-permutation mutual information (SNWPMI) for analyzing multi-channel electroencephalographic (EEG) synchronization strength. The performances including the effects of time delay, embedding dimension, coupling coefficients, signal to noise ratios (SNRs) and data length of the NWPMI are evaluated by using Coupled Henon mapping model. The results show that the NWPMI is superior in describing the synchronization compared with the normalized permutation mutual information (NPMI). Furthermore, the proposed SNWPMI method is applied to analyze scalp EEG data from 26 amnestic mild cognitive impairment (aMCI) subjects and 20 age-matched controls with normal cognitive function, who both suffer from type 2 diabetes mellitus (T2DM). The proposed methods NWPMI and SNWPMI are suggested to be an effective index to estimate the synchronization strength. Copyright © 2016 Elsevier Ltd. All rights reserved.
Enhancement of Plant Metabolite Fingerprinting by Machine Learning1[W
Scott, Ian M.; Vermeer, Cornelia P.; Liakata, Maria; Corol, Delia I.; Ward, Jane L.; Lin, Wanchang; Johnson, Helen E.; Whitehead, Lynne; Kular, Baldeep; Baker, John M.; Walsh, Sean; Dave, Anuja; Larson, Tony R.; Graham, Ian A.; Wang, Trevor L.; King, Ross D.; Draper, John; Beale, Michael H.
2010-01-01
Metabolite fingerprinting of Arabidopsis (Arabidopsis thaliana) mutants with known or predicted metabolic lesions was performed by 1H-nuclear magnetic resonance, Fourier transform infrared, and flow injection electrospray-mass spectrometry. Fingerprinting enabled processing of five times more plants than conventional chromatographic profiling and was competitive for discriminating mutants, other than those affected in only low-abundance metabolites. Despite their rapidity and complexity, fingerprints yielded metabolomic insights (e.g. that effects of single lesions were usually not confined to individual pathways). Among fingerprint techniques, 1H-nuclear magnetic resonance discriminated the most mutant phenotypes from the wild type and Fourier transform infrared discriminated the fewest. To maximize information from fingerprints, data analysis was crucial. One-third of distinctive phenotypes might have been overlooked had data models been confined to principal component analysis score plots. Among several methods tested, machine learning (ML) algorithms, namely support vector machine or random forest (RF) classifiers, were unsurpassed for phenotype discrimination. Support vector machines were often the best performing classifiers, but RFs yielded some particularly informative measures. First, RFs estimated margins between mutant phenotypes, whose relations could then be visualized by Sammon mapping or hierarchical clustering. Second, RFs provided importance scores for the features within fingerprints that discriminated mutants. These scores correlated with analysis of variance F values (as did Kruskal-Wallis tests, true- and false-positive measures, mutual information, and the Relief feature selection algorithm). ML classifiers, as models trained on one data set to predict another, were ideal for focused metabolomic queries, such as the distinctiveness and consistency of mutant phenotypes. Accessible software for use of ML in plant physiology is highlighted. PMID:20566707
Iskarous, Khalil; Mooshammer, Christine; Hoole, Phil; Recasens, Daniel; Shadle, Christine H.; Saltzman, Elliot; Whalen, D. H.
2013-01-01
Coarticulation and invariance are two topics at the center of theorizing about speech production and speech perception. In this paper, a quantitative scale is proposed that places coarticulation and invariance at the two ends of the scale. This scale is based on physical information flow in the articulatory signal, and uses Information Theory, especially the concept of mutual information, to quantify these central concepts of speech research. Mutual Information measures the amount of physical information shared across phonological units. In the proposed quantitative scale, coarticulation corresponds to greater and invariance to lesser information sharing. The measurement scale is tested by data from three languages: German, Catalan, and English. The relation between the proposed scale and several existing theories of coarticulation is discussed, and implications for existing theories of speech production and perception are presented. PMID:23927125
Using Mutual Information for Adaptive Item Comparison and Student Assessment
ERIC Educational Resources Information Center
Liu, Chao-Lin
2005-01-01
The author analyzes properties of mutual information between dichotomous concepts and test items. The properties generalize some common intuitions about item comparison, and provide principled foundations for designing item-selection heuristics for student assessment in computer-assisted educational systems. The proposed item-selection strategies…
Applications of statistical physics and information theory to the analysis of DNA sequences
NASA Astrophysics Data System (ADS)
Grosse, Ivo
2000-10-01
DNA carries the genetic information of most living organisms, and the of genome projects is to uncover that genetic information. One basic task in the analysis of DNA sequences is the recognition of protein coding genes. Powerful computer programs for gene recognition have been developed, but most of them are based on statistical patterns that vary from species to species. In this thesis I address the question if there exist universal statistical patterns that are different in coding and noncoding DNA of all living species, regardless of their phylogenetic origin. In search for such species-independent patterns I study the mutual information function of genomic DNA sequences, and find that it shows persistent period-three oscillations. To understand the biological origin of the observed period-three oscillations, I compare the mutual information function of genomic DNA sequences to the mutual information function of stochastic model sequences. I find that the pseudo-exon model is able to reproduce the mutual information function of genomic DNA sequences. Moreover, I find that a generalization of the pseudo-exon model can connect the existence and the functional form of long-range correlations to the presence and the length distributions of coding and noncoding regions. Based on these theoretical studies I am able to find an information-theoretical quantity, the average mutual information (AMI), whose probability distributions are significantly different in coding and noncoding DNA, while they are almost identical in all studied species. These findings show that there exist universal statistical patterns that are different in coding and noncoding DNA of all studied species, and they suggest that the AMI may be used to identify genes in different living species, irrespective of their taxonomic origin.
Feature Selection Methods for Robust Decoding of Finger Movements in a Non-human Primate
Padmanaban, Subash; Baker, Justin; Greger, Bradley
2018-01-01
Objective: The performance of machine learning algorithms used for neural decoding of dexterous tasks may be impeded due to problems arising when dealing with high-dimensional data. The objective of feature selection algorithms is to choose a near-optimal subset of features from the original feature space to improve the performance of the decoding algorithm. The aim of our study was to compare the effects of four feature selection techniques, Wilcoxon signed-rank test, Relative Importance, Principal Component Analysis (PCA), and Mutual Information Maximization on SVM classification performance for a dexterous decoding task. Approach: A nonhuman primate (NHP) was trained to perform small coordinated movements—similar to typing. An array of microelectrodes was implanted in the hand area of the motor cortex of the NHP and used to record action potentials (AP) during finger movements. A Support Vector Machine (SVM) was used to classify which finger movement the NHP was making based upon AP firing rates. We used the SVM classification to examine the functional parameters of (i) robustness to simulated failure and (ii) longevity of classification. We also compared the effect of using isolated-neuron and multi-unit firing rates as the feature vector supplied to the SVM. Main results: The average decoding accuracy for multi-unit features and single-unit features using Mutual Information Maximization (MIM) across 47 sessions was 96.74 ± 3.5% and 97.65 ± 3.36% respectively. The reduction in decoding accuracy between using 100% of the features and 10% of features based on MIM was 45.56% (from 93.7 to 51.09%) and 4.75% (from 95.32 to 90.79%) for multi-unit and single-unit features respectively. MIM had best performance compared to other feature selection methods. Significance: These results suggest improved decoding performance can be achieved by using optimally selected features. The results based on clinically relevant performance metrics also suggest that the decoding algorithm can be made robust by using optimal features and feature selection algorithms. We believe that even a few percent increase in performance is important and improves the decoding accuracy of the machine learning algorithm potentially increasing the ease of use of a brain machine interface. PMID:29467602
Field Day: A Case Study examining scientists’ oral performance skills
USDA-ARS?s Scientific Manuscript database
Communication is a complex cyclic process wherein senders and receivers encode and decode information in an effort to reach a state of mutuality or mutual understanding. When the communication of scientific or technical information occurs in a public space, effective speakers follow a formula for co...
Mutual Information Item Selection in Adaptive Classification Testing
ERIC Educational Resources Information Center
Weissman, Alexander
2007-01-01
A general approach for item selection in adaptive multiple-category classification tests is provided. The approach uses mutual information (MI), a special case of the Kullback-Leibler distance, or relative entropy. MI works efficiently with the sequential probability ratio test and alleviates the difficulties encountered with using other local-…
Mathematical Theory of Generalized Duality Quantum Computers Acting on Vector-States
NASA Astrophysics Data System (ADS)
Cao, Huai-Xin; Long, Gui-Lu; Guo, Zhi-Hua; Chen, Zheng-Li
2013-06-01
Following the idea of duality quantum computation, a generalized duality quantum computer (GDQC) acting on vector-states is defined as a tuple consisting of a generalized quantum wave divider (GQWD) and a finite number of unitary operators as well as a generalized quantum wave combiner (GQWC). It is proved that the GQWD and GQWC of a GDQC are an isometry and a co-isometry, respectively, and mutually dual. It is also proved that every GDQC gives a contraction, called a generalized duality quantum gate (GDQG). A classification of GDQCs is given and the properties of GDQGs are discussed. Some applications are obtained, including two orthogonal duality quantum computer algorithms for unsorted database search and an understanding of the Mach-Zehnder interferometer.
Federal Register 2010, 2011, 2012, 2013, 2014
2010-01-29
... activity.\\5\\ There will also be an increase in the monthly fee for the mutual fund Profile Phase II Service.... Profile Phase I transmits mutual fund price and rate information. Profile Phase II stores data elements such as accumulation, breakpoints, and commission eligibility that relate to mutual fund processing...
Information-theoretical noninvasive damage detection in bridge structures
NASA Astrophysics Data System (ADS)
Sudu Ambegedara, Amila; Sun, Jie; Janoyan, Kerop; Bollt, Erik
2016-11-01
Damage detection of mechanical structures such as bridges is an important research problem in civil engineering. Using spatially distributed sensor time series data collected from a recent experiment on a local bridge in Upper State New York, we study noninvasive damage detection using information-theoretical methods. Several findings are in order. First, the time series data, which represent accelerations measured at the sensors, more closely follow Laplace distribution than normal distribution, allowing us to develop parameter estimators for various information-theoretic measures such as entropy and mutual information. Second, as damage is introduced by the removal of bolts of the first diaphragm connection, the interaction between spatially nearby sensors as measured by mutual information becomes weaker, suggesting that the bridge is "loosened." Finally, using a proposed optimal mutual information interaction procedure to prune away indirect interactions, we found that the primary direction of interaction or influence aligns with the traffic direction on the bridge even after damaging the bridge.
Information Theoretic Approaches to Rapid Discovery of Relationships in Large Climate Data Sets
NASA Technical Reports Server (NTRS)
Knuth, Kevin H.; Rossow, William B.; Clancy, Daniel (Technical Monitor)
2002-01-01
Mutual information as the asymptotic Bayesian measure of independence is an excellent starting point for investigating the existence of possible relationships among climate-relevant variables in large data sets, As mutual information is a nonlinear function of of its arguments, it is not beholden to the assumption of a linear relationship between the variables in question and can reveal features missed in linear correlation analyses. However, as mutual information is symmetric in its arguments, it only has the ability to reveal the probability that two variables are related. it provides no information as to how they are related; specifically, causal interactions or a relation based on a common cause cannot be detected. For this reason we also investigate the utility of a related quantity called the transfer entropy. The transfer entropy can be written as a difference between mutual informations and has the capability to reveal whether and how the variables are causally related. The application of these information theoretic measures is rested on some familiar examples using data from the International Satellite Cloud Climatology Project (ISCCP) to identify relation between global cloud cover and other variables, including equatorial pacific sea surface temperature (SST), over seasonal and El Nino Southern Oscillation (ENSO) cycles.
Agnihotri, Deepak; Verma, Kesari; Tripathi, Priyanka
2016-01-01
The contiguous sequences of the terms (N-grams) in the documents are symmetrically distributed among different classes. The symmetrical distribution of the N-Grams raises uncertainty in the belongings of the N-Grams towards the class. In this paper, we focused on the selection of most discriminating N-Grams by reducing the effects of symmetrical distribution. In this context, a new text feature selection method named as the symmetrical strength of the N-Grams (SSNG) is proposed using a two pass filtering based feature selection (TPF) approach. Initially, in the first pass of the TPF, the SSNG method chooses various informative N-Grams from the entire extracted N-Grams of the corpus. Subsequently, in the second pass the well-known Chi Square (χ(2)) method is being used to select few most informative N-Grams. Further, to classify the documents the two standard classifiers Multinomial Naive Bayes and Linear Support Vector Machine have been applied on the ten standard text data sets. In most of the datasets, the experimental results state the performance and success rate of SSNG method using TPF approach is superior to the state-of-the-art methods viz. Mutual Information, Information Gain, Odds Ratio, Discriminating Feature Selection and χ(2).
Entanglement entropy of dispersive media from thermodynamic entropy in one higher dimension.
Maghrebi, M F; Reid, M T H
2015-04-17
A dispersive medium becomes entangled with zero-point fluctuations in the vacuum. We consider an arbitrary array of material bodies weakly interacting with a quantum field and compute the quantum mutual information between them. It is shown that the mutual information in D dimensions can be mapped to classical thermodynamic entropy in D+1 dimensions. As a specific example, we compute the mutual information both analytically and numerically for a range of separation distances between two bodies in D=2 dimensions and find a logarithmic correction to the area law at short separations. A key advantage of our method is that it allows the strong subadditivity property to be easily verified.
Nikitin, E E; Troe, J
2010-09-16
Approximate analytical expressions are derived for the low-energy rate coefficients of capture of two identical dipolar polarizable rigid rotors in their lowest nonresonant (j(1) = 0 and j(2) = 0) and resonant (j(1) = 0,1 and j(2) = 1,0) states. The considered range extends from the quantum, ultralow energy regime, characterized by s-wave capture, to the classical regime described within fly wheel and adiabatic channel approaches, respectively. This is illustrated by the table of contents graphic (available on the Web) that shows the scaled rate coefficients for the mutual capture of rotors in the resonant state versus the reduced wave vector between the Bethe zero-energy (left arrows) and classical high-energy (right arrow) limits for different ratios δ of the dipole-dipole to dispersion interaction.
Propagation and scattering of vector light beam in turbid scattering medium
NASA Astrophysics Data System (ADS)
Doronin, Alexander; Milione, Giovanni; Meglinski, Igor; Alfano, Robert R.
2014-03-01
Due to its high sensitivity to subtle alterations in medium morphology the vector light beams have recently gained much attention in the area of photonics. This leads to development of a new non-invasive optical technique for tissue diagnostics. Conceptual design of the particular experimental systems requires careful selection of various technical parameters, including beam structure, polarization, coherence, wavelength of incident optical radiation, as well as an estimation of how the spatial and temporal structural alterations in biological tissues can be distinguished by variations of these parameters. Therefore, an accurate realistic description of vector light beams propagation within tissue-like media is required. To simulate and mimic the propagation of vector light beams within the turbid scattering media the stochastic Monte Carlo (MC) technique has been used. In current report we present the developed MC model and the results of simulation of different vector light beams propagation in turbid tissue-like scattering media. The developed MC model takes into account the coherent properties of light, the influence of reflection and refraction at the medium boundary, helicity flip of vortexes and their mutual interference. Finally, similar to the concept of higher order Poincaŕe sphere (HOPS), to link the spatial distribution of the intensity of the backscattered vector light beam and its state of polarization on the medium surface we introduced the color-coded HOPS.
Higher-Order Statistical Correlations and Mutual Information Among Particles in a Quantum Well
NASA Astrophysics Data System (ADS)
Yépez, V. S.; Sagar, R. P.; Laguna, H. G.
2017-12-01
The influence of wave function symmetry on statistical correlation is studied for the case of three non-interacting spin-free quantum particles in a unidimensional box, in position and in momentum space. Higher-order statistical correlations occurring among the three particles in this quantum system is quantified via higher-order mutual information and compared to the correlation between pairs of variables in this model, and to the correlation in the two-particle system. The results for the higher-order mutual information show that there are states where the symmetric wave functions are more correlated than the antisymmetric ones with same quantum numbers. This holds in position as well as in momentum space. This behavior is opposite to that observed for the correlation between pairs of variables in this model, and the two-particle system, where the antisymmetric wave functions are in general more correlated. These results are also consistent with those observed in a system of three uncoupled oscillators. The use of higher-order mutual information as a correlation measure, is monitored and examined by considering a superposition of states or systems with two Slater determinants.
Lin, Fen-Fang; Wang, Ke; Yang, Ning; Yan, Shi-Guang; Zheng, Xin-Yu
2012-02-01
In this paper, some main factors such as soil type, land use pattern, lithology type, topography, road, and industry type that affect soil quality were used to precisely obtain the spatial distribution characteristics of regional soil quality, mutual information theory was adopted to select the main environmental factors, and decision tree algorithm See 5.0 was applied to predict the grade of regional soil quality. The main factors affecting regional soil quality were soil type, land use, lithology type, distance to town, distance to water area, altitude, distance to road, and distance to industrial land. The prediction accuracy of the decision tree model with the variables selected by mutual information was obviously higher than that of the model with all variables, and, for the former model, whether of decision tree or of decision rule, its prediction accuracy was all higher than 80%. Based on the continuous and categorical data, the method of mutual information theory integrated with decision tree could not only reduce the number of input parameters for decision tree algorithm, but also predict and assess regional soil quality effectively.
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2010-11-10
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Parallel mutual information estimation for inferring gene regulatory networks on GPUs
2011-01-01
Background Mutual information is a measure of similarity between two variables. It has been widely used in various application domains including computational biology, machine learning, statistics, image processing, and financial computing. Previously used simple histogram based mutual information estimators lack the precision in quality compared to kernel based methods. The recently introduced B-spline function based mutual information estimation method is competitive to the kernel based methods in terms of quality but at a lower computational complexity. Results We present a new approach to accelerate the B-spline function based mutual information estimation algorithm with commodity graphics hardware. To derive an efficient mapping onto this type of architecture, we have used the Compute Unified Device Architecture (CUDA) programming model to design and implement a new parallel algorithm. Our implementation, called CUDA-MI, can achieve speedups of up to 82 using double precision on a single GPU compared to a multi-threaded implementation on a quad-core CPU for large microarray datasets. We have used the results obtained by CUDA-MI to infer gene regulatory networks (GRNs) from microarray data. The comparisons to existing methods including ARACNE and TINGe show that CUDA-MI produces GRNs of higher quality in less time. Conclusions CUDA-MI is publicly available open-source software, written in CUDA and C++ programming languages. It obtains significant speedup over sequential multi-threaded implementation by fully exploiting the compute capability of commonly used CUDA-enabled low-cost GPUs. PMID:21672264
On Information Metrics for Spatial Coding.
Souza, Bryan C; Pavão, Rodrigo; Belchior, Hindiael; Tort, Adriano B L
2018-04-01
The hippocampal formation is involved in navigation, and its neuronal activity exhibits a variety of spatial correlates (e.g., place cells, grid cells). The quantification of the information encoded by spikes has been standard procedure to identify which cells have spatial correlates. For place cells, most of the established metrics derive from Shannon's mutual information (Shannon, 1948), and convey information rate in bits/s or bits/spike (Skaggs et al., 1993, 1996). Despite their widespread use, the performance of these metrics in relation to the original mutual information metric has never been investigated. In this work, using simulated and real data, we find that the current information metrics correlate less with the accuracy of spatial decoding than the original mutual information metric. We also find that the top informative cells may differ among metrics, and show a surrogate-based normalization that yields comparable spatial information estimates. Since different information metrics may identify different neuronal populations, we discuss current and alternative definitions of spatially informative cells, which affect the metric choice. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.
Inglis, Stephen; Melko, Roger G
2013-01-01
We implement a Wang-Landau sampling technique in quantum Monte Carlo (QMC) simulations for the purpose of calculating the Rényi entanglement entropies and associated mutual information. The algorithm converges an estimate for an analog to the density of states for stochastic series expansion QMC, allowing a direct calculation of Rényi entropies without explicit thermodynamic integration. We benchmark results for the mutual information on two-dimensional (2D) isotropic and anisotropic Heisenberg models, a 2D transverse field Ising model, and a three-dimensional Heisenberg model, confirming a critical scaling of the mutual information in cases with a finite-temperature transition. We discuss the benefits and limitations of broad sampling techniques compared to standard importance sampling methods.
Entanglement of purification in free scalar field theories
NASA Astrophysics Data System (ADS)
Bhattacharyya, Arpan; Takayanagi, Tadashi; Umemoto, Koji
2018-04-01
We compute the entanglement of purification (EoP) in a 2d free scalar field theory with various masses. This quantity measures correlations between two subsystems and is reduced to the entanglement entropy when the total system is pure. We obtain explicit numerical values by assuming minimal gaussian wave functionals for the purified states. We find that when the distance between the subsystems is large, the EoP behaves like the mutual information. However, when the distance is small, the EoP shows a characteristic behavior which qualitatively agrees with the conjectured holographic computation and which is different from that of the mutual information. We also study behaviors of mutual information in purified spaces and violations of monogamy/strong superadditivity.
Federal Register 2010, 2011, 2012, 2013, 2014
2011-04-08
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NASA Technical Reports Server (NTRS)
Wolf, David R.
2004-01-01
The topic of this paper is a hierarchy of information-like functions, here named the information correlation functions, where each function of the hierarchy may be thought of as the information between the variables it depends upon. The information correlation functions are particularly suited to the description of the emergence of complex behaviors due to many- body or many-agent processes. They are particularly well suited to the quantification of the decomposition of the information carried among a set of variables or agents, and its subsets. In more graphical language, they provide the information theoretic basis for understanding the synergistic and non-synergistic components of a system, and as such should serve as a forceful toolkit for the analysis of the complexity structure of complex many agent systems. The information correlation functions are the natural generalization to an arbitrary number of sets of variables of the sequence starting with the entropy function (one set of variables) and the mutual information function (two sets). We start by describing the traditional measures of information (entropy) and mutual information.
1985-07-01
Datatape Division 4-1 5.0 REFERENCES Acuna, M.H. et. al., The MAGSAT Vector Magnetometer - A Precision Fluxgate Magnetometer for the Measurement of the...charting would consist of a triaxial, mutually orthogonal fluxgate magnetometer and an absolute scalar magnetometer to check the flux- gates drift...While space-ready, triaxial fluxgate magnetometers are not an off-the-shelf item, their design concepts are well understood. Their resolution of less
Photoelectrochemical etching measurement of defect density in GaN grown by nanoheteroepitaxy
NASA Astrophysics Data System (ADS)
Ferdous, M. S.; Sun, X. Y.; Wang, X.; Fairchild, M. N.; Hersee, S. D.
2006-05-01
The density of dislocations in n-type GaN was measured by photoelectrochemical etching. A 10× reduction in dislocation density was observed compared to planar GaN grown at the same time. Cross-sectional transmission electron microscopy studies indicate that defect reduction is due to the mutual cancellation of dislocations with equal and opposite Burger's vectors. The nanoheteroepitaxy sample exhibited significantly higher photoluminescence intensity and higher electron mobility than the planar reference sample.
Mutually unbiased coarse-grained measurements of two or more phase-space variables
NASA Astrophysics Data System (ADS)
Paul, E. C.; Walborn, S. P.; Tasca, D. S.; Rudnicki, Łukasz
2018-05-01
Mutual unbiasedness of the eigenstates of phase-space operators—such as position and momentum, or their standard coarse-grained versions—exists only in the limiting case of infinite squeezing. In Phys. Rev. Lett. 120, 040403 (2018), 10.1103/PhysRevLett.120.040403, it was shown that mutual unbiasedness can be recovered for periodic coarse graining of these two operators. Here we investigate mutual unbiasedness of coarse-grained measurements for more than two phase-space variables. We show that mutual unbiasedness can be recovered between periodic coarse graining of any two nonparallel phase-space operators. We illustrate these results through optics experiments, using the fractional Fourier transform to prepare and measure mutually unbiased phase-space variables. The differences between two and three mutually unbiased measurements is discussed. Our results contribute to bridging the gap between continuous and discrete quantum mechanics, and they could be useful in quantum-information protocols.
NASA Astrophysics Data System (ADS)
Pachinger, Dietmar; De Huu, Marc; Mueller, Harald; Care, Isabelle; Frederiksen, John; Piccato, Aline; Bertasiene, Agne
2017-01-01
For the first time a EURAMET comparison of standard facilities in the field of low air speed is presented. The air velocities range from 0.05 m/s up to 1 m/s. Two different thermal anemometers are used as Transfer Standards (TS), namely a ball-type and a planar-type anemometer. Due to their construction it is possible to analyze different components of the flow vector. Orientation-dependent measurements which are investigated in addition might also deliver information concerning the components of the flow vector. A Comparison Reference Value (CRV) is calculated with the help of the chi-squared test according to the procedure A presented by Cox [1] [2] and the degree of equivalence of the laboratory data to the CRV is determined. Both TS show reasonable results and a high degree of equivalence. Furthermore the degree of equivalence of the laboratory data to each other is investigated in detail. Main text To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by the CCM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
2D-3D registration using gradient-based MI for image guided surgery systems
NASA Astrophysics Data System (ADS)
Yim, Yeny; Chen, Xuanyi; Wakid, Mike; Bielamowicz, Steve; Hahn, James
2011-03-01
Registration of preoperative CT data to intra-operative video images is necessary not only to compare the outcome of the vocal fold after surgery with the preplanned shape but also to provide the image guidance for fusion of all imaging modalities. We propose a 2D-3D registration method using gradient-based mutual information. The 3D CT scan is aligned to 2D endoscopic images by finding the corresponding viewpoint between the real camera for endoscopic images and the virtual camera for CT scans. Even though mutual information has been successfully used to register different imaging modalities, it is difficult to robustly register the CT rendered image to the endoscopic image due to varying light patterns and shape of the vocal fold. The proposed method calculates the mutual information in the gradient images as well as original images, assigning more weight to the high gradient regions. The proposed method can emphasize the effect of vocal fold and allow a robust matching regardless of the surface illumination. To find the viewpoint with maximum mutual information, a downhill simplex method is applied in a conditional multi-resolution scheme which leads to a less-sensitive result to local maxima. To validate the registration accuracy, we evaluated the sensitivity to initial viewpoint of preoperative CT. Experimental results showed that gradient-based mutual information provided robust matching not only for two identical images with different viewpoints but also for different images acquired before and after surgery. The results also showed that conditional multi-resolution scheme led to a more accurate registration than single-resolution.
Schalk, Stefan G; Demi, Libertario; Bouhouch, Nabil; Kuenen, Maarten P J; Postema, Arnoud W; de la Rosette, Jean J M C H; Wijkstra, Hessel; Tjalkens, Tjalling J; Mischi, Massimo
2017-03-01
The role of angiogenesis in cancer growth has stimulated research aimed at noninvasive cancer detection by blood perfusion imaging. Recently, contrast ultrasound dispersion imaging was proposed as an alternative method for angiogenesis imaging. After the intravenous injection of an ultrasound-contrast-agent bolus, dispersion can be indirectly estimated from the local similarity between neighboring time-intensity curves (TICs) measured by ultrasound imaging. Up until now, only linear similarity measures have been investigated. Motivated by the promising results of this approach in prostate cancer (PCa), we developed a novel dispersion estimation method based on mutual information, thus including nonlinear similarity, to further improve its ability to localize PCa. First, a simulation study was performed to establish the theoretical link between dispersion and mutual information. Next, the method's ability to localize PCa was validated in vivo in 23 patients (58 datasets) referred for radical prostatectomy by comparison with histology. A monotonic relationship between dispersion and mutual information was demonstrated. The in vivo study resulted in a receiver operating characteristic (ROC) curve area equal to 0.77, which was superior (p = 0.21-0.24) to that obtained by linear similarity measures (0.74-0.75) and (p <; 0.05) to that by conventional perfusion parameters (≤0.70). Mutual information between neighboring time-intensity curves can be used to indirectly estimate contrast dispersion and can lead to more accurate PCa localization. An improved PCa localization method can possibly lead to better grading and staging of tumors, and support focal-treatment guidance. Moreover, future employment of the method in other types of angiogenic cancer can be considered.
Nonrigid mammogram registration using mutual information
NASA Astrophysics Data System (ADS)
Wirth, Michael A.; Narhan, Jay; Gray, Derek W. S.
2002-05-01
Of the papers dealing with the task of mammogram registration, the majority deal with the task by matching corresponding control-points derived from anatomical landmark points. One of the caveats encountered when using pure point-matching techniques is their reliance on accurately extracted anatomical features-points. This paper proposes an innovative approach to matching mammograms which combines the use of a similarity-measure and a point-based spatial transformation. Mutual information is a cost-function used to determine the degree of similarity between the two mammograms. An initial rigid registration is performed to remove global differences and bring the mammograms into approximate alignment. The mammograms are then subdivided into smaller regions and each of the corresponding subimages is matched independently using mutual information. The centroids of each of the matched subimages are then used as corresponding control-point pairs in association with the Thin-Plate Spline radial basis function. The resulting spatial transformation generates a nonrigid match of the mammograms. The technique is illustrated by matching mammograms from the MIAS mammogram database. An experimental comparison is made between mutual information incorporating purely rigid behavior, and that incorporating a more nonrigid behavior. The effectiveness of the registration process is evaluated using image differences.
VectorBase: a home for invertebrate vectors of human pathogens
Lawson, Daniel; Arensburger, Peter; Atkinson, Peter; Besansky, Nora J.; Bruggner, Robert V.; Butler, Ryan; Campbell, Kathryn S.; Christophides, George K.; Christley, Scott; Dialynas, Emmanuel; Emmert, David; Hammond, Martin; Hill, Catherine A.; Kennedy, Ryan C.; Lobo, Neil F.; MacCallum, M. Robert; Madey, Greg; Megy, Karine; Redmond, Seth; Russo, Susan; Severson, David W.; Stinson, Eric O.; Topalis, Pantelis; Zdobnov, Evgeny M.; Birney, Ewan; Gelbart, William M.; Kafatos, Fotis C.; Louis, Christos; Collins, Frank H.
2007-01-01
VectorBase () is a web-accessible data repository for information about invertebrate vectors of human pathogens. VectorBase annotates and maintains vector genomes providing an integrated resource for the research community. Currently, VectorBase contains genome information for two organisms: Anopheles gambiae, a vector for the Plasmodium protozoan agent causing malaria, and Aedes aegypti, a vector for the flaviviral agents causing Yellow fever and Dengue fever. PMID:17145709
Adaptive DSPI phase denoising using mutual information and 2D variational mode decomposition
NASA Astrophysics Data System (ADS)
Xiao, Qiyang; Li, Jian; Wu, Sijin; Li, Weixian; Yang, Lianxiang; Dong, Mingli; Zeng, Zhoumo
2018-04-01
In digital speckle pattern interferometry (DSPI), noise interference leads to a low peak signal-to-noise ratio (PSNR) and measurement errors in the phase map. This paper proposes an adaptive DSPI phase denoising method based on two-dimensional variational mode decomposition (2D-VMD) and mutual information. Firstly, the DSPI phase map is subjected to 2D-VMD in order to obtain a series of band-limited intrinsic mode functions (BLIMFs). Then, on the basis of characteristics of the BLIMFs and in combination with mutual information, a self-adaptive denoising method is proposed to obtain noise-free components containing the primary phase information. The noise-free components are reconstructed to obtain the denoising DSPI phase map. Simulation and experimental results show that the proposed method can effectively reduce noise interference, giving a PSNR that is higher than that of two-dimensional empirical mode decomposition methods.
Holographic control of information and dynamical topology change for composite open quantum systems
NASA Astrophysics Data System (ADS)
Aref'eva, I. Ya.; Volovich, I. V.; Inozemcev, O. V.
2017-12-01
We analyze how the compositeness of a system affects the characteristic time of equilibration. We study the dynamics of open composite quantum systems strongly coupled to the environment after a quantum perturbation accompanied by nonequilibrium heating. We use a holographic description of the evolution of entanglement entropy. The nonsmooth character of the evolution with holographic entanglement is a general feature of composite systems, which demonstrate a dynamical change of topology in the bulk space and a jumplike velocity change of entanglement entropy propagation. Moreover, the number of jumps depends on the system configuration and especially on the number of composite parts. The evolution of the mutual information of two composite systems inherits these jumps. We present a detailed study of the mutual information for two subsystems with one of them being bipartite. We find five qualitatively different types of behavior of the mutual information dynamics and indicate the corresponding regions of the system parameters.
Pelz-Stelinski, K S; Killiny, N
2016-05-01
The duration of the evolutionary association between a pathogen and vector can be inferred based on the strength of their mutualistic interactions. A well-adapted pathogen is likely to confer some benefit or, at a minimum, exhibit low pathogenicity toward its host vector. Coevolution of the two toward a mutually beneficial association appears to have occurred between the citrus greening disease pathogen, Candidatus Liberibacter asiaticus (Las), and its insect vector, the Asian citrus psyllid, Diaphorina citri (Kuwayama). To better understand the dynamics facilitating transmission, we evaluated the effects of Las infection on the fitness of its vector. Diaphorina citri harboring Las were more fecund than their uninfected counterparts; however, their nymphal development rate and adult survival were comparatively reduced. The finite rate of population increase and net reproductive rate were both greater among Las-infected D. citri as compared with uninfected counterparts, indicating that overall population fitness of infected psyllids was improved given the greater number of offspring produced. Previous reports of transovarial transmission, in conjunction with increased fecundity and population growth rates of Las-positive D. citri found in the current investigation, suggest a long evolutionary relationship between pathogen and vector. The survival of Las-infected adult D. citri was lower compared with uninfected D. citri , which suggests that there may be a fitness trade-off in response to Las infection. A beneficial effect of a plant pathogen on vector fitness may indicate that the pathogen developed a relationship with the insect before secondarily moving to plants.
Pelz-Stelinski, K. S.; Killiny, N.
2016-01-01
The duration of the evolutionary association between a pathogen and vector can be inferred based on the strength of their mutualistic interactions. A well-adapted pathogen is likely to confer some benefit or, at a minimum, exhibit low pathogenicity toward its host vector. Coevolution of the two toward a mutually beneficial association appears to have occurred between the citrus greening disease pathogen, Candidatus Liberibacter asiaticus (Las), and its insect vector, the Asian citrus psyllid, Diaphorina citri (Kuwayama). To better understand the dynamics facilitating transmission, we evaluated the effects of Las infection on the fitness of its vector. Diaphorina citri harboring Las were more fecund than their uninfected counterparts; however, their nymphal development rate and adult survival were comparatively reduced. The finite rate of population increase and net reproductive rate were both greater among Las-infected D. citri as compared with uninfected counterparts, indicating that overall population fitness of infected psyllids was improved given the greater number of offspring produced. Previous reports of transovarial transmission, in conjunction with increased fecundity and population growth rates of Las-positive D. citri found in the current investigation, suggest a long evolutionary relationship between pathogen and vector. The survival of Las-infected adult D. citri was lower compared with uninfected D. citri, which suggests that there may be a fitness trade-off in response to Las infection. A beneficial effect of a plant pathogen on vector fitness may indicate that the pathogen developed a relationship with the insect before secondarily moving to plants. PMID:27418697
An emergence of coordinated communication in populations of agents.
Kvasnicka, V; Pospichal, J
1999-01-01
The purpose of this article is to demonstrate that coordinated communication spontaneously emerges in a population composed of agents that are capable of specific cognitive activities. Internal states of agents are characterized by meaning vectors. Simple neural networks composed of one layer of hidden neurons perform cognitive activities of agents. An elementary communication act consists of the following: (a) two agents are selected, where one of them is declared the speaker and the other the listener; (b) the speaker codes a selected meaning vector onto a sequence of symbols and sends it to the listener as a message; and finally, (c) the listener decodes this message into a meaning vector and adapts his or her neural network such that the differences between speaker and listener meaning vectors are decreased. A Darwinian evolution enlarged by ideas from the Baldwin effect and Dawkins' memes is simulated by a simple version of an evolutionary algorithm without crossover. The agent fitness is determined by success of the mutual pairwise communications. It is demonstrated that agents in the course of evolution gradually do a better job of decoding received messages (they are closer to meaning vectors of speakers) and all agents gradually start to use the same vocabulary for the common communication. Moreover, if agent meaning vectors contain regularities, then these regularities are manifested also in messages created by agent speakers, that is, similar parts of meaning vectors are coded by similar symbol substrings. This observation is considered a manifestation of the emergence of a grammar system in the common coordinated communication.
Approximated mutual information training for speech recognition using myoelectric signals.
Guo, Hua J; Chan, A D C
2006-01-01
A new training algorithm called the approximated maximum mutual information (AMMI) is proposed to improve the accuracy of myoelectric speech recognition using hidden Markov models (HMMs). Previous studies have demonstrated that automatic speech recognition can be performed using myoelectric signals from articulatory muscles of the face. Classification of facial myoelectric signals can be performed using HMMs that are trained using the maximum likelihood (ML) algorithm; however, this algorithm maximizes the likelihood of the observations in the training sequence, which is not directly associated with optimal classification accuracy. The AMMI training algorithm attempts to maximize the mutual information, thereby training the HMMs to optimize their parameters for discrimination. Our results show that AMMI training consistently reduces the error rates compared to these by the ML training, increasing the accuracy by approximately 3% on average.
Mutual information as an order parameter for quantum synchronization
NASA Astrophysics Data System (ADS)
Ameri, V.; Eghbali-Arani, M.; Mari, A.; Farace, A.; Kheirandish, F.; Giovannetti, V.; Fazio, R.
2015-01-01
Spontaneous synchronization is a fundamental phenomenon, important in many theoretical studies and applications. Recently, this effect has been analyzed and observed in a number of physical systems close to the quantum-mechanical regime. In this work we propose mutual information as a useful order parameter which can capture the emergence of synchronization in very different contexts, ranging from semiclassical to intrinsically quantum-mechanical systems. Specifically, we first study the synchronization of two coupled Van der Pol oscillators in both classical and quantum regimes and later we consider the synchronization of two qubits inside two coupled optical cavities. In all these contexts, we find that mutual information can be used as an appropriate figure of merit for determining the synchronization phases independently of the specific details of the system.
Couceiro, R; Carvalho, P; Paiva, R P; Henriques, J; Muehlsteff, J
2014-12-01
The presence of motion artifacts in photoplethysmographic (PPG) signals is one of the major obstacles in the extraction of reliable cardiovascular parameters in continuous monitoring applications. In the current paper we present an algorithm for motion artifact detection based on the analysis of the variations in the time and the period domain characteristics of the PPG signal. The extracted features are ranked using a normalized mutual information feature selection algorithm and the best features are used in a support vector machine classification model to distinguish between clean and corrupted sections of the PPG signal. The proposed method has been tested in healthy and cardiovascular diseased volunteers, considering 11 different motion artifact sources. The results achieved by the current algorithm (sensitivity--SE: 84.3%, specificity--SP: 91.5% and accuracy--ACC: 88.5%) show that the current methodology is able to identify both corrupted and clean PPG sections with high accuracy in both healthy (ACC: 87.5%) and cardiovascular diseases (ACC: 89.5%) context.
Bullinaria, John A; Levy, Joseph P
2012-09-01
In a previous article, we presented a systematic computational study of the extraction of semantic representations from the word-word co-occurrence statistics of large text corpora. The conclusion was that semantic vectors of pointwise mutual information values from very small co-occurrence windows, together with a cosine distance measure, consistently resulted in the best representations across a range of psychologically relevant semantic tasks. This article extends that study by investigating the use of three further factors--namely, the application of stop-lists, word stemming, and dimensionality reduction using singular value decomposition (SVD)--that have been used to provide improved performance elsewhere. It also introduces an additional semantic task and explores the advantages of using a much larger corpus. This leads to the discovery and analysis of improved SVD-based methods for generating semantic representations (that provide new state-of-the-art performance on a standard TOEFL task) and the identification and discussion of problems and misleading results that can arise without a full systematic study.
Precoded spatial multiplexing MIMO system with spatial component interleaver.
Gao, Xiang; Wu, Zhanji
In this paper, the performance of precoded bit-interleaved coded modulation (BICM) spatial multiplexing multiple-input multiple-output (MIMO) system with spatial component interleaver is investigated. For the ideal precoded spatial multiplexing MIMO system with spatial component interleaver based on singular value decomposition (SVD) of the MIMO channel, the average pairwise error probability (PEP) of coded bits is derived. Based on the PEP analysis, the optimum spatial Q-component interleaver design criterion is provided to achieve the minimum error probability. For the limited feedback precoded proposed scheme with linear zero forcing (ZF) receiver, in order to minimize a bound on the average probability of a symbol vector error, a novel effective signal-to-noise ratio (SNR)-based precoding matrix selection criterion and a simplified criterion are proposed. Based on the average mutual information (AMI)-maximization criterion, the optimal constellation rotation angles are investigated. Simulation results indicate that the optimized spatial multiplexing MIMO system with spatial component interleaver can achieve significant performance advantages compared to the conventional spatial multiplexing MIMO system.
Gkigkitzis, Ioannis
2013-01-01
The aim of this report is to provide a mathematical model of the mechanism for making binary fate decisions about cell death or survival, during and after Photodynamic Therapy (PDT) treatment, and to supply the logical design for this decision mechanism as an application of rate distortion theory to the biochemical processing of information by the physical system of a cell. Based on system biology models of the molecular interactions involved in the PDT processes previously established, and regarding a cellular decision-making system as a noisy communication channel, we use rate distortion theory to design a time dependent Blahut-Arimoto algorithm where the input is a stimulus vector composed of the time dependent concentrations of three PDT related cell death signaling molecules and the output is a cell fate decision. The molecular concentrations are determined by a group of rate equations. The basic steps are: initialize the probability of the cell fate decision, compute the conditional probability distribution that minimizes the mutual information between input and output, compute the cell probability of cell fate decision that minimizes the mutual information and repeat the last two steps until the probabilities converge. Advance to the next discrete time point and repeat the process. Based on the model from communication theory described in this work, and assuming that the activation of the death signal processing occurs when any of the molecular stimulants increases higher than a predefined threshold (50% of the maximum concentrations), for 1800s of treatment, the cell undergoes necrosis within the first 30 minutes with probability range 90.0%-99.99% and in the case of repair/survival, it goes through apoptosis within 3-4 hours with probability range 90.00%-99.00%. Although, there is no experimental validation of the model at this moment, it reproduces some patterns of survival ratios of predicted experimental data. Analytical modeling based on cell death signaling molecules has been shown to be an independent and useful tool for prediction of cell surviving response to PDT. The model can be adjusted to provide important insights for cellular response to other treatments such as hyperthermia, and diseases such as neurodegeneration.
2007-04-16
velocity of the fluid mesh, P is the relative pressure, xr is the position vector, τ is the deviatoric stress tensor, D is the rate of deformation...corresponds to a slip factor of zero. The slip factor determines how much of the fluid and structure forces are mutually exchanged. Equations 22 and 23...updated from last to first. viii.Average the fluid pressure (This step eliminates the pressure checker-boarding effect and allows use of equal
Entropic uncertainty relations and locking: Tight bounds for mutually unbiased bases
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ballester, Manuel A.; Wehner, Stephanie
We prove tight entropic uncertainty relations for a large number of mutually unbiased measurements. In particular, we show that a bound derived from the result by Maassen and Uffink [Phys. Rev. Lett. 60, 1103 (1988)] for two such measurements can in fact be tight for up to {radical}(d) measurements in mutually unbiased bases. We then show that using more mutually unbiased bases does not always lead to a better locking effect. We prove that the optimal bound for the accessible information using up to {radical}(d) specific mutually unbiased bases is log d/2, which is the same as can be achievedmore » by using only two bases. Our result indicates that merely using mutually unbiased bases is not sufficient to achieve a strong locking effect and we need to look for additional properties.« less
Ellis Cowling; KaDonna Randolph
2013-01-01
The purpose of this article is to encourage development of an enduring mutually beneficial collaboration between data and information analysts in the US Forest Serviceâs "Enhanced Forest Inventory and Analysis (FIA) Program" and forest pathologists and geneticists in the information exchange group (IEG) titled "Genetics and Breeding of Southern Forest...
Earthquake Damage Assessment over Port-au-Prince (Haiti) by Fusing Optical and SAR Data
NASA Astrophysics Data System (ADS)
Romaniello, V.; Piscini, A.; Bignami, C.; Anniballe, R.; Pierdicca, N.; Stramondo, S.
2016-08-01
This work proposes methodologies aiming at evaluating the sensitivity of optical and SAR change features obtained from satellite images with respect to the damage grade. The proposed methods are derived from the literature ([1], [2], [3], [4]) and the main novelty concerns the estimation of these change features at object scale.The test case is the Mw 7.0 earthquake that hit Haiti on January 12, 2010.The analysis of change detection indicators is based on ground truth information collected during a post- earthquake survey. We have generated the damage map of Port-au-Prince by considering a set of polygons extracted from the open source Open Street Map geo- database. The resulting damage map was calculated in terms of collapse ratio [5].We selected some features having a good sensitivity with damage at object scale [6]: the Normalised Difference Index, the Kullback-Libler Divergence, the Mutual Information and the Intensity Correlation Difference.The Naive Bayes and the Support Vector Machine classifiers were used to evaluate the goodness of these features. The classification results demonstrate that the simultaneous use of several change features from EO observations can improve the damage estimation at object scale.
An online sleep apnea detection method based on recurrence quantification analysis.
Nguyen, Hoa Dinh; Wilkins, Brek A; Cheng, Qi; Benjamin, Bruce Allen
2014-07-01
This paper introduces an online sleep apnea detection method based on heart rate complexity as measured by recurrence quantification analysis (RQA) statistics of heart rate variability (HRV) data. RQA statistics can capture nonlinear dynamics of a complex cardiorespiratory system during obstructive sleep apnea. In order to obtain a more robust measurement of the nonstationarity of the cardiorespiratory system, we use different fixed amount of neighbor thresholdings for recurrence plot calculation. We integrate a feature selection algorithm based on conditional mutual information to select the most informative RQA features for classification, and hence, to speed up the real-time classification process without degrading the performance of the system. Two types of binary classifiers, i.e., support vector machine and neural network, are used to differentiate apnea from normal sleep. A soft decision fusion rule is developed to combine the results of these classifiers in order to improve the classification performance of the whole system. Experimental results show that our proposed method achieves better classification results compared with the previous recurrence analysis-based approach. We also show that our method is flexible and a strong candidate for a real efficient sleep apnea detection system.
Mapping of Malaria Vectors at District Level in India: Changing Scenario and Identified Gaps.
Singh, Poonam; Lingala, Mercy Aparna L; Sarkar, Soma; Dhiman, Ramesh C
2017-02-01
Malaria is one of the six major vector-borne diseases in India, the endemicity of which changes with changes in ecological, climatic, and sociodevelopmental conditions. The anopheline vectors are greatly affected by ecological conditions such as deforestation, urbanization, climate and lifestyle. Despite the advent of tools such as Geographic Information System (GIS), the updated information on the distribution of anopheline vectors of malaria is not available. In India, the plan for vector control is organized at subcentral level but information about vectors is unavailable even at the district level. Therefore, a systematic presentation of vector distribution has been made to provide maps in respect of major vector species. A search of the literature for major vector species, that is, Anopheles culicifacies, Anopheles fluviatilis, Anopheles stephensi, Anopheles minimus, and Anopheles dirus sensu lato, since 1927 till 2015 was carried out. Data have been presented as present, absent, and no information about vector species during pre-eradication (1927-1958), posteradication (1959-1999), and current scenario (2000-2015). Vectors' distribution and malaria endemicity were mapped using Arc GIS. Of 630 districts of India, major vectors An. culicifacies, An. fluviatilis, and An. stephensi were present in 420, 241, and 243 districts, respectively. In 183 districts, there is no information on any major malaria vector species although 27 of them from the states of Arunachal Pradesh, Jharkhand, Manipur, and Mizoram are highly endemic for malaria, having incidences of 2-40 cases/1000/year. The identified gaps in vector distribution, particularly in malaria endemic areas, necessitate further surveys so as to generate the missing information.
Okariz, Ana; Guraya, Teresa; Iturrondobeitia, Maider; Ibarretxe, Julen
2017-12-01
A method is proposed and verified for selecting the optimum segmentation of a TEM reconstruction among the results of several segmentation algorithms. The selection criterion is the accuracy of the segmentation. To do this selection, a parameter for the comparison of the accuracies of the different segmentations has been defined. It consists of the mutual information value between the acquired TEM images of the sample and the Radon projections of the segmented volumes. In this work, it has been proved that this new mutual information parameter and the Jaccard coefficient between the segmented volume and the ideal one are correlated. In addition, the results of the new parameter are compared to the results obtained from another validated method to select the optimum segmentation. Copyright © 2017 Elsevier Ltd. All rights reserved.
Kaneko, Hidekazu; Tamura, Hiroshi; Tate, Shunta; Kawashima, Takahiro; Suzuki, Shinya S; Fujita, Ichiro
2010-08-01
In order for patients with disabilities to control assistive devices with their own neural activity, multineuronal spike trains must be efficiently decoded because only limited computational resources can be used to generate prosthetic control signals in portable real-time applications. In this study, we compare the abilities of two vectorizing procedures (multineuronal and time-segmental) to extract information from spike trains during the same total neuron-seconds. In the multineuronal vectorizing procedure, we defined a response vector whose components represented the spike counts of one to five neurons. In the time-segmental vectorizing procedure, a response vector consisted of components representing a neuron's spike counts for one to five time-segment(s) of a response period of 1 s. Spike trains were recorded from neurons in the inferior temporal cortex of monkeys presented with visual stimuli. We examined whether the amount of information of the visual stimuli carried by these neurons differed between the two vectorizing procedures. The amount of information calculated with the multineuronal vectorizing procedure, but not the time-segmental vectorizing procedure, significantly increased with the dimensions of the response vector. We conclude that the multineuronal vectorizing procedure is superior to the time-segmental vectorizing procedure in efficiently extracting information from neuronal signals. Copyright (c) 2010 Elsevier Ltd. All rights reserved.
How much a galaxy knows about its large-scale environment?: An information theoretic perspective
NASA Astrophysics Data System (ADS)
Pandey, Biswajit; Sarkar, Suman
2017-05-01
The small-scale environment characterized by the local density is known to play a crucial role in deciding the galaxy properties but the role of large-scale environment on galaxy formation and evolution still remain a less clear issue. We propose an information theoretic framework to investigate the influence of large-scale environment on galaxy properties and apply it to the data from the Galaxy Zoo project that provides the visual morphological classifications of ˜1 million galaxies from the Sloan Digital Sky Survey. We find a non-zero mutual information between morphology and environment that decreases with increasing length-scales but persists throughout the entire length-scales probed. We estimate the conditional mutual information and the interaction information between morphology and environment by conditioning the environment on different length-scales and find a synergic interaction between them that operates up to at least a length-scales of ˜30 h-1 Mpc. Our analysis indicates that these interactions largely arise due to the mutual information shared between the environments on different length-scales.
Federal Register 2010, 2011, 2012, 2013, 2014
2010-12-28
... of most mutual funds. Current Actions: On October 14, 2010, the Federal Reserve published a notice in... margin stock, and (3) shares of most mutual funds. Lenders other than brokers and dealers and banks must...
Renyi generalizations of the conditional quantum mutual information
2015-02-23
D) for a four-party pure state on systems ABCD. The conditional mutual information also underlies the squashed entanglement , an entanglement measure...that satisfies all of the axioms desired for an entanglement measure. As such, it has been an open question to find Rényi generalizations of the...possessing the C systems, and the sender and receiver sharing noiseless entanglement before communication begins, the optimal rate of quantum communication
Part mutual information for quantifying direct associations in networks.
Zhao, Juan; Zhou, Yiwei; Zhang, Xiujun; Chen, Luonan
2016-05-03
Quantitatively identifying direct dependencies between variables is an important task in data analysis, in particular for reconstructing various types of networks and causal relations in science and engineering. One of the most widely used criteria is partial correlation, but it can only measure linearly direct association and miss nonlinear associations. However, based on conditional independence, conditional mutual information (CMI) is able to quantify nonlinearly direct relationships among variables from the observed data, superior to linear measures, but suffers from a serious problem of underestimation, in particular for those variables with tight associations in a network, which severely limits its applications. In this work, we propose a new concept, "partial independence," with a new measure, "part mutual information" (PMI), which not only can overcome the problem of CMI but also retains the quantification properties of both mutual information (MI) and CMI. Specifically, we first defined PMI to measure nonlinearly direct dependencies between variables and then derived its relations with MI and CMI. Finally, we used a number of simulated data as benchmark examples to numerically demonstrate PMI features and further real gene expression data from Escherichia coli and yeast to reconstruct gene regulatory networks, which all validated the advantages of PMI for accurately quantifying nonlinearly direct associations in networks.
Mutual information-based analysis of JPEG2000 contexts.
Liu, Zhen; Karam, Lina J
2005-04-01
Context-based arithmetic coding has been widely adopted in image and video compression and is a key component of the new JPEG2000 image compression standard. In this paper, the contexts used in JPEG2000 are analyzed using the mutual information, which is closely related to the compression performance. We first show that, when combining the contexts, the mutual information between the contexts and the encoded data will decrease unless the conditional probability distributions of the combined contexts are the same. Given I, the initial number of contexts, and F, the final desired number of contexts, there are S(I, F) possible context classification schemes where S(I, F) is called the Stirling number of the second kind. The optimal classification scheme is the one that gives the maximum mutual information. Instead of using an exhaustive search, the optimal classification scheme can be obtained through a modified generalized Lloyd algorithm with the relative entropy as the distortion metric. For binary arithmetic coding, the search complexity can be reduced by using dynamic programming. Our experimental results show that the JPEG2000 contexts capture the correlations among the wavelet coefficients very well. At the same time, the number of contexts used as part of the standard can be reduced without loss in the coding performance.
Mutual Information in Frequency and Its Application to Measure Cross-Frequency Coupling in Epilepsy
NASA Astrophysics Data System (ADS)
Malladi, Rakesh; Johnson, Don H.; Kalamangalam, Giridhar P.; Tandon, Nitin; Aazhang, Behnaam
2018-06-01
We define a metric, mutual information in frequency (MI-in-frequency), to detect and quantify the statistical dependence between different frequency components in the data, referred to as cross-frequency coupling and apply it to electrophysiological recordings from the brain to infer cross-frequency coupling. The current metrics used to quantify the cross-frequency coupling in neuroscience cannot detect if two frequency components in non-Gaussian brain recordings are statistically independent or not. Our MI-in-frequency metric, based on Shannon's mutual information between the Cramer's representation of stochastic processes, overcomes this shortcoming and can detect statistical dependence in frequency between non-Gaussian signals. We then describe two data-driven estimators of MI-in-frequency: one based on kernel density estimation and the other based on the nearest neighbor algorithm and validate their performance on simulated data. We then use MI-in-frequency to estimate mutual information between two data streams that are dependent across time, without making any parametric model assumptions. Finally, we use the MI-in- frequency metric to investigate the cross-frequency coupling in seizure onset zone from electrocorticographic recordings during seizures. The inferred cross-frequency coupling characteristics are essential to optimize the spatial and spectral parameters of electrical stimulation based treatments of epilepsy.
The Vector Electric Field Instrument on the C/NOFS Satellite
NASA Technical Reports Server (NTRS)
Pfaff, R.; Kujawski, J.; Uribe, P.; Bromund, K.; Fourre, R.; Acuna, M.; Le, G.; Farrell, W.; Holzworth, R.; McCarthy, M.;
2008-01-01
We provide an overview of the Vector Electric Field Instrument (VEFI) on the Air Force Communication/Navigation Outage Forecasting System (C/NOFS) satellite, a mission designed to understand, model, and forecast the presence of equatorial ionospheric irregularities. VEFI is a NASA GSFC instrument designed 1) to investigate the role of the ambient electric fields in initiating nighttime ionospheric density depletions and turbulence; 2) to determine the electric fields associated with abrupt, large amplitude, density depletions and 3) to quantify the spectrum of the wave electric fields and plasma densities (irregularities) associated with density depletions or Equatorial Spread-F. The VEFI instrument includes a vector electric field double probe detector, a Langmuir trigger probe, a flux gate magnetometer, a lightning detector and associated electronics. The heart of the instrument is the set of double probe detectors designed to measure DC and AC electric fields using 6 identical, mutually orthogonal, deployable 9.5 m booms tipped with 10 cm diameter spheres containing embedded preamplifiers. A description of the instrument and its sensors will be presented. If available, representative measurements will be provided.
Electromagnetically induced transparency in the case of elliptic polarization of interacting fields
NASA Astrophysics Data System (ADS)
Parshkov, Oleg M.
2018-04-01
The theoretical investigation results of disintegration effect of elliptic polarized shot probe pulses of electromagnetically induced transparency in the counterintuitive superposed elliptic polarized control field and in weak probe field approximation are presented. It is shown that this disintegration occurs because the probe field in the medium is the sum of two normal modes, which correspond to elliptic polarized pulses with different speeds of propagation. The polarization ellipses of normal modes have equal eccentricities and mutually perpendicular major axes. Major axis of polarization ellipse of one normal mode is parallel to polarization ellipse major axis of control field, and electric vector of this mode rotates in the opposite direction, than electric vector of the control field. The electric vector other normal mode rotates in the same direction that the control field electric vector. The normal mode speed of the first type aforementioned is less than that of the second type. The polarization characteristics of the normal mode depend uniquely on the polarization characteristics of elliptic polarized control field and remain changeless in the propagation process. The theoretical investigation is performed for Λ-scheme of degenerated quantum transitions between 3P0, 3P10 and 3P2 energy levels of 208Pb isotope.
Comparison of co-expression measures: mutual information, correlation, and model based indices.
Song, Lin; Langfelder, Peter; Horvath, Steve
2012-12-09
Co-expression measures are often used to define networks among genes. Mutual information (MI) is often used as a generalized correlation measure. It is not clear how much MI adds beyond standard (robust) correlation measures or regression model based association measures. Further, it is important to assess what transformations of these and other co-expression measures lead to biologically meaningful modules (clusters of genes). We provide a comprehensive comparison between mutual information and several correlation measures in 8 empirical data sets and in simulations. We also study different approaches for transforming an adjacency matrix, e.g. using the topological overlap measure. Overall, we confirm close relationships between MI and correlation in all data sets which reflects the fact that most gene pairs satisfy linear or monotonic relationships. We discuss rare situations when the two measures disagree. We also compare correlation and MI based approaches when it comes to defining co-expression network modules. We show that a robust measure of correlation (the biweight midcorrelation transformed via the topological overlap transformation) leads to modules that are superior to MI based modules and maximal information coefficient (MIC) based modules in terms of gene ontology enrichment. We present a function that relates correlation to mutual information which can be used to approximate the mutual information from the corresponding correlation coefficient. We propose the use of polynomial or spline regression models as an alternative to MI for capturing non-linear relationships between quantitative variables. The biweight midcorrelation outperforms MI in terms of elucidating gene pairwise relationships. Coupled with the topological overlap matrix transformation, it often leads to more significantly enriched co-expression modules. Spline and polynomial networks form attractive alternatives to MI in case of non-linear relationships. Our results indicate that MI networks can safely be replaced by correlation networks when it comes to measuring co-expression relationships in stationary data.
A Discriminant Distance Based Composite Vector Selection Method for Odor Classification
Choi, Sang-Il; Jeong, Gu-Min
2014-01-01
We present a composite vector selection method for an effective electronic nose system that performs well even in noisy environments. Each composite vector generated from a electronic nose data sample is evaluated by computing the discriminant distance. By quantitatively measuring the amount of discriminative information in each composite vector, composite vectors containing informative variables can be distinguished and the final composite features for odor classification are extracted using the selected composite vectors. Using the only informative composite vectors can be also helpful to extract better composite features instead of using all the generated composite vectors. Experimental results with different volatile organic compound data show that the proposed system has good classification performance even in a noisy environment compared to other methods. PMID:24747735
Large distance expansion of mutual information for disjoint disks in a free scalar theory
Agón, Cesar A.; Cohen-Abbo, Isaac; Schnitzer, Howard J.
2016-11-11
We compute the next-to-leading order term in the long-distance expansion of the mutual information for free scalars in three space-time dimensions. The geometry considered is two disjoint disks separated by a distance r between their centers. No evidence for non-analyticity in the Rényi parameter n for the continuation n → 1 in the next-to-leading order term is found.
Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale
Kobourov, Stephen; Gallant, Mike; Börner, Katy
2016-01-01
Overview Notions of community quality underlie the clustering of networks. While studies surrounding network clustering are increasingly common, a precise understanding of the realtionship between different cluster quality metrics is unknown. In this paper, we examine the relationship between stand-alone cluster quality metrics and information recovery metrics through a rigorous analysis of four widely-used network clustering algorithms—Louvain, Infomap, label propagation, and smart local moving. We consider the stand-alone quality metrics of modularity, conductance, and coverage, and we consider the information recovery metrics of adjusted Rand score, normalized mutual information, and a variant of normalized mutual information used in previous work. Our study includes both synthetic graphs and empirical data sets of sizes varying from 1,000 to 1,000,000 nodes. Cluster Quality Metrics We find significant differences among the results of the different cluster quality metrics. For example, clustering algorithms can return a value of 0.4 out of 1 on modularity but score 0 out of 1 on information recovery. We find conductance, though imperfect, to be the stand-alone quality metric that best indicates performance on the information recovery metrics. Additionally, our study shows that the variant of normalized mutual information used in previous work cannot be assumed to differ only slightly from traditional normalized mutual information. Network Clustering Algorithms Smart local moving is the overall best performing algorithm in our study, but discrepancies between cluster evaluation metrics prevent us from declaring it an absolutely superior algorithm. Interestingly, Louvain performed better than Infomap in nearly all the tests in our study, contradicting the results of previous work in which Infomap was superior to Louvain. We find that although label propagation performs poorly when clusters are less clearly defined, it scales efficiently and accurately to large graphs with well-defined clusters. PMID:27391786
Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale.
Emmons, Scott; Kobourov, Stephen; Gallant, Mike; Börner, Katy
2016-01-01
Notions of community quality underlie the clustering of networks. While studies surrounding network clustering are increasingly common, a precise understanding of the realtionship between different cluster quality metrics is unknown. In this paper, we examine the relationship between stand-alone cluster quality metrics and information recovery metrics through a rigorous analysis of four widely-used network clustering algorithms-Louvain, Infomap, label propagation, and smart local moving. We consider the stand-alone quality metrics of modularity, conductance, and coverage, and we consider the information recovery metrics of adjusted Rand score, normalized mutual information, and a variant of normalized mutual information used in previous work. Our study includes both synthetic graphs and empirical data sets of sizes varying from 1,000 to 1,000,000 nodes. We find significant differences among the results of the different cluster quality metrics. For example, clustering algorithms can return a value of 0.4 out of 1 on modularity but score 0 out of 1 on information recovery. We find conductance, though imperfect, to be the stand-alone quality metric that best indicates performance on the information recovery metrics. Additionally, our study shows that the variant of normalized mutual information used in previous work cannot be assumed to differ only slightly from traditional normalized mutual information. Smart local moving is the overall best performing algorithm in our study, but discrepancies between cluster evaluation metrics prevent us from declaring it an absolutely superior algorithm. Interestingly, Louvain performed better than Infomap in nearly all the tests in our study, contradicting the results of previous work in which Infomap was superior to Louvain. We find that although label propagation performs poorly when clusters are less clearly defined, it scales efficiently and accurately to large graphs with well-defined clusters.
Whitney, Jon; Corredor, German; Janowczyk, Andrew; Ganesan, Shridar; Doyle, Scott; Tomaszewski, John; Feldman, Michael; Gilmore, Hannah; Madabhushi, Anant
2018-05-30
Gene-expression companion diagnostic tests, such as the Oncotype DX test, assess the risk of early stage Estrogen receptor (ER) positive (+) breast cancers, and guide clinicians in the decision of whether or not to use chemotherapy. However, these tests are typically expensive, time consuming, and tissue-destructive. In this paper, we evaluate the ability of computer-extracted nuclear morphology features from routine hematoxylin and eosin (H&E) stained images of 178 early stage ER+ breast cancer patients to predict corresponding risk categories derived using the Oncotype DX test. A total of 216 features corresponding to the nuclear shape and architecture categories from each of the pathologic images were extracted and four feature selection schemes: Ranksum, Principal Component Analysis with Variable Importance on Projection (PCA-VIP), Maximum-Relevance, Minimum Redundancy Mutual Information Difference (MRMR MID), and Maximum-Relevance, Minimum Redundancy - Mutual Information Quotient (MRMR MIQ), were employed to identify the most discriminating features. These features were employed to train 4 machine learning classifiers: Random Forest, Neural Network, Support Vector Machine, and Linear Discriminant Analysis, via 3-fold cross validation. The four sets of risk categories, and the top Area Under the receiver operating characteristic Curve (AUC) machine classifier performances were: 1) Low ODx and Low mBR grade vs. High ODx and High mBR grade (Low-Low vs. High-High) (AUC = 0.83), 2) Low ODx vs. High ODx (AUC = 0.72), 3) Low ODx vs. Intermediate and High ODx (AUC = 0.58), and 4) Low and Intermediate ODx vs. High ODx (AUC = 0.65). Trained models were tested independent validation set of 53 cases which comprised of Low and High ODx risk, and demonstrated per-patient accuracies ranging from 75 to 86%. Our results suggest that computerized image analysis of digitized H&E pathology images of early stage ER+ breast cancer might be able predict the corresponding Oncotype DX risk categories.
Computing the Energy Cost of the Information Transmitted by Model Biological Neurons
NASA Astrophysics Data System (ADS)
Torrealdea, F. J.; Sarasola, C.; d'Anjou, A.; Moujahid, A.
2009-08-01
We assign an energy function to a Hindmarsh-Rose model of a neuron and use it to compute values of average energy consumption during its signalling activity. We also compute values of information entropy of an isolated neuron and of mutual information between two electrically coupled neurons. We find that for the isolated neuron the chaotic signaling regime is the one with the biggest ratio of information entropy to energy consumption. We also find that in the case of electrically coupled neurons there are values of the coupling strength at which the mutual information to energy consumption ratio is maximum, that is, that transmitting at that coupling conditions is energetically less expensive.
Parallel scheduling of recursively defined arrays
NASA Technical Reports Server (NTRS)
Myers, T. J.; Gokhale, M. B.
1986-01-01
A new method of automatic generation of concurrent programs which constructs arrays defined by sets of recursive equations is described. It is assumed that the time of computation of an array element is a linear combination of its indices, and integer programming is used to seek a succession of hyperplanes along which array elements can be computed concurrently. The method can be used to schedule equations involving variable length dependency vectors and mutually recursive arrays. Portions of the work reported here have been implemented in the PS automatic program generation system.
Optimization of stable quadruped locomotion using mutual information
NASA Astrophysics Data System (ADS)
Silva, Pedro; Santos, Cristina P.; Polani, Daniel
2013-10-01
Central Pattern Generators (CPG)s have been widely used in the field of robotics to address the task of legged locomotion generation. The adequate configuration of these structures for a given platform can be accessed through evolutionary strategies, according to task dependent selection pressures. Information driven evolution, accounts for information theoretical measures as selection pressures, as an alternative to a fully task dependent selection pressure. In this work we exploit this concept and evaluate the use of mean Mutual Information, as a selection pressure towards a CPG configuration capable of faster, yet more coordinated and stabler locomotion than when only a task dependent selection pressure is used.
An incompressible fluid flow model with mutual information for MR image registration
NASA Astrophysics Data System (ADS)
Tsai, Leo; Chang, Herng-Hua
2013-03-01
Image registration is one of the fundamental and essential tasks within image processing. It is a process of determining the correspondence between structures in two images, which are called the template image and the reference image, respectively. The challenge of registration is to find an optimal geometric transformation between corresponding image data. This paper develops a new MR image registration algorithm that uses a closed incompressible viscous fluid model associated with mutual information. In our approach, we treat the image pixels as the fluid elements of a viscous fluid flow governed by the nonlinear Navier-Stokes partial differential equation (PDE). We replace the pressure term with the body force mainly used to guide the transformation with a weighting coefficient, which is expressed by the mutual information between the template and reference images. To solve this modified Navier-Stokes PDE, we adopted the fast numerical techniques proposed by Seibold1. The registration process of updating the body force, the velocity and deformation fields is repeated until the mutual information weight reaches a prescribed threshold. We applied our approach to the BrainWeb and real MR images. As consistent with the theory of the proposed fluid model, we found that our method accurately transformed the template images into the reference images based on the intensity flow. Experimental results indicate that our method is of potential in a wide variety of medical image registration applications.
47 CFR 25.263 - Information sharing requirements for SDARS terrestrial repeater operators.
Code of Federal Regulations, 2011 CFR
2011-10-01
... SDARS licensee and all potentially affected WCS licensees reach a mutual agreement to provide... SDARS licensee and all potentially affected WCS licensees reach a mutual agreement to provide... notice period. (e) Duty to cooperate. SDARS licensees must cooperate in good faith in the selection and...
47 CFR 27.72 - Information sharing requirements.
Code of Federal Regulations, 2011 CFR
2011-10-01
... WCS licensees in the 2305-2320 MHz and 2345-2360 MHz bands. (a) Sites and frequency selections. WCS..., unless the SDARS licensee and all potentially affected WCS licensees reach a mutual agreement to provide... affected WCS licensees reach a mutual agreement to provide notification by some other means, that agreement...
75 FR 9453 - Submission for OMB Review; Comment Request
Federal Register 2010, 2011, 2012, 2013, 2014
2010-03-02
... certain investment advisory programs. These programs, which include ``wrap fee'' and ``mutual fund wrap... size of most mutual funds. Under wrap fee and similar programs, a client's account is typically managed... securities and funds in the account. The requirement that the sponsor (or its designee) obtain information...
Code of Federal Regulations, 2010 CFR
2010-07-01
... purposes only. 2. This information shall be accorded substantially the same degree of security protection... 413(a) of the Mutual Security Act of 1954, as amended (22 U.S.C. 1933(a)), and pursuant to the... the Mutual Security Program, to relieve the Department of Defense of administrative burdens, and to...
Palaniyandi, M
2012-12-01
There have been several attempts made to the appreciation of remote sensing and GIS for the study of vectors, biodiversity, vector presence, vector abundance and the vector-borne diseases with respect to space and time. This study was made for reviewing and appraising the potential use of remote sensing and GIS applications for spatial prediction of vector-borne diseases transmission. The nature of the presence and the abundance of vectors and vector-borne diseases, disease infection and the disease transmission are not ubiquitous and are confined with geographical, environmental and climatic factors, and are localized. The presence of vectors and vector-borne diseases is most complex in nature, however, it is confined and fueled by the geographical, climatic and environmental factors including man-made factors. The usefulness of the present day availability of the information derived from the satellite data including vegetation indices of canopy cover and its density, soil types, soil moisture, soil texture, soil depth, etc. is integrating the information in the expert GIS engine for the spatial analysis of other geoclimatic and geoenvironmental variables. The present study gives the detailed information on the classical studies of the past and present, and the future role of remote sensing and GIS for the vector-borne diseases control. The ecological modeling directly gives us the relevant information to understand the spatial variation of the vector biodiversity, vector presence, vector abundance and the vector-borne diseases in association with geoclimatic and the environmental variables. The probability map of the geographical distribution and seasonal variations of horizontal and vertical distribution of vector abundance and its association with vector -borne diseases can be obtained with low cost remote sensing and GIS tool with reliable data and speed.
Automatic indexing of compound words based on mutual information for Korean text retrieval
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pan Koo Kim; Yoo Kun Cho
In this paper, we present an automatic indexing technique for compound words suitable to an aggulutinative language, specifically Korean. Firstly, we present the construction conditions to compose compound words as indexing terms. Also we present the decomposition rules applicable to consecutive nouns to extract all contents of text. Finally we propose a measure to estimate the usefulness of a term, mutual information, to calculate the degree of word association of compound words, based on the information theoretic notion. By applying this method, our system has raised the precision rate of compound words from 72% to 87%.
Giordano, Bruno L.; Kayser, Christoph; Rousselet, Guillaume A.; Gross, Joachim; Schyns, Philippe G.
2016-01-01
Abstract We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open‐source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541–1573, 2017. © 2016 Wiley Periodicals, Inc. PMID:27860095
Quantum dynamics of a two-atom-qubit system
NASA Astrophysics Data System (ADS)
Van Hieu, Nguyen; Bich Ha, Nguyen; Linh, Le Thi Ha
2009-09-01
A physical model of the quantum information exchange between two qubits is studied theoretically. The qubits are two identical two-level atoms, the physical mechanism of the quantum information exchange is the mutual dependence of the reduced density matrices of two qubits generated by their couplings with a multimode radiation field. The Lehmberg-Agarwal master equation is exactly solved. The explicit form of the mutual dependence of two reduced density matrices is established. The application to study the entanglement of two qubits is discussed.
Entanglement and purity of two-mode Gaussian states in noisy channels
DOE Office of Scientific and Technical Information (OSTI.GOV)
Serafini, Alessio; Illuminati, Fabrizio; De Siena, Silvio
2004-02-01
We study the evolution of purity, entanglement, and total correlations of general two-mode continuous variable Gaussian states in arbitrary uncorrelated Gaussian environments. The time evolution of purity, von Neumann entropy, logarithmic negativity, and mutual information is analyzed for a wide range of initial conditions. In general, we find that a local squeezing of the bath leads to a faster degradation of purity and entanglement, while it can help to preserve the mutual information between the modes.
Mutual information based feature selection for medical image retrieval
NASA Astrophysics Data System (ADS)
Zhi, Lijia; Zhang, Shaomin; Li, Yan
2018-04-01
In this paper, authors propose a mutual information based method for lung CT image retrieval. This method is designed to adapt to different datasets and different retrieval task. For practical applying consideration, this method avoids using a large amount of training data. Instead, with a well-designed training process and robust fundamental features and measurements, the method in this paper can get promising performance and maintain economic training computation. Experimental results show that the method has potential practical values for clinical routine application.
A Synchronous Digital Duplexing Technique for OFDMA-Based Indoor Communications
NASA Astrophysics Data System (ADS)
Park, Chang-Hwan; Ko, Yo-Han; Kim, Yeong-Jun; Park, Kyung-Won; Jeon, Won-Gi; Paik, Jong-Ho; Lee, Seok-Pil; Cho, Yong-Soo
In this paper, we propose a new digital duplexing scheme, called synchronous digital duplexing (SDD), which can increase data efficiency and flexibility of resource by transmitting uplink signal and downlink signal simultaneously in wireless communication. In order to transmit uplink and downlink signals simultaneously, the proposed SDD obtains mutual information among subscriber stations (SSs) with a mutual ranging symbol. This information is used for selection of transmission time, decision on cyclic suffix (CS) insertion, determination of CS length, and re-establishment of FFT starting point.
NASA Technical Reports Server (NTRS)
Wiswell, E. R.; Cooper, G. R. (Principal Investigator)
1978-01-01
The author has identified the following significant results. The concept of average mutual information in the received spectral random process about the spectral scene was developed. Techniques amenable to implementation on a digital computer were also developed to make the required average mutual information calculations. These techniques required identification of models for the spectral response process of scenes. Stochastic modeling techniques were adapted for use. These techniques were demonstrated on empirical data from wheat and vegetation scenes.
Secure anonymous mutual authentication for star two-tier wireless body area networks.
Ibrahim, Maged Hamada; Kumari, Saru; Das, Ashok Kumar; Wazid, Mohammad; Odelu, Vanga
2016-10-01
Mutual authentication is a very important service that must be established between sensor nodes in wireless body area network (WBAN) to ensure the originality and integrity of the patient's data sent by sensors distributed on different parts of the body. However, mutual authentication service is not enough. An adversary can benefit from monitoring the traffic and knowing which sensor is in transmission of patient's data. Observing the traffic (even without disclosing the context) and knowing its origin, it can reveal to the adversary information about the patient's medical conditions. Therefore, anonymity of the communicating sensors is an important service as well. Few works have been conducted in the area of mutual authentication among sensor nodes in WBAN. However, none of them has considered anonymity among body sensor nodes. Up to our knowledge, our protocol is the first attempt to consider this service in a two-tier WBAN. We propose a new secure protocol to realize anonymous mutual authentication and confidential transmission for star two-tier WBAN topology. The proposed protocol uses simple cryptographic primitives. We prove the security of the proposed protocol using the widely-accepted Burrows-Abadi-Needham (BAN) logic, and also through rigorous informal security analysis. In addition, to demonstrate the practicality of our protocol, we evaluate it using NS-2 simulator. BAN logic and informal security analysis prove that our proposed protocol achieves the necessary security requirements and goals of an authentication service. The simulation results show the impact on the various network parameters, such as end-to-end delay and throughput. The nodes in the network require to store few hundred bits. Nodes require to perform very few hash invocations, which are computationally very efficient. The communication cost of the proposed protocol is few hundred bits in one round of communication. Due to the low computation cost, the energy consumed by the nodes is also low. Our proposed protocol is a lightweight anonymous mutually authentication protocol to mutually authenticate the sensor nodes with the controller node (hub) in a star two-tier WBAN topology. Results show that our protocol proves efficiency over previously proposed protocols and at the same time, achieves the necessary security requirements for a secure anonymous mutual authentication scheme. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Prediction of microsleeps using pairwise joint entropy and mutual information between EEG channels.
Baseer, Abdul; Weddell, Stephen J; Jones, Richard D
2017-07-01
Microsleeps are involuntary and brief instances of complete loss of responsiveness, typically of 0.5-15 s duration. They adversely affect performance in extended attention-driven jobs and can be fatal. Our aim was to predict microsleeps from 16 channel EEG signals. Two information theoretic concepts - pairwise joint entropy and mutual information - were independently used to continuously extract features from EEG signals. k-nearest neighbor (kNN) with k = 3 was used to calculate both joint entropy and mutual information. Highly correlated features were discarded and the rest were ranked using Fisher score followed by an average of 3-fold cross-validation area under the curve of the receiver operating characteristic (AUC ROC ). Leave-one-out method (LOOM) was performed to test the performance of microsleep prediction system on independent data. The best prediction for 0.25 s ahead was AUCROC, sensitivity, precision, geometric mean (GM), and φ of 0.93, 0.68, 0.33, 0.75, and 0.38 respectively with joint entropy using single linear discriminant analysis (LDA) classifier.
A multistage motion vector processing method for motion-compensated frame interpolation.
Huang, Ai- Mei; Nguyen, Truong Q
2008-05-01
In this paper, a novel, low-complexity motion vector processing algorithm at the decoder is proposed for motion-compensated frame interpolation or frame rate up-conversion. We address the problems of having broken edges and deformed structures in an interpolated frame by hierarchically refining motion vectors on different block sizes. Our method explicitly considers the reliability of each received motion vector and has the capability of preserving the structure information. This is achieved by analyzing the distribution of residual energies and effectively merging blocks that have unreliable motion vectors. The motion vector reliability information is also used as a prior knowledge in motion vector refinement using a constrained vector median filter to avoid choosing identical unreliable one. We also propose using chrominance information in our method. Experimental results show that the proposed scheme has better visual quality and is also robust, even in video sequences with complex scenes and fast motion.
Modelling nutritional mutualisms: challenges and opportunities for data integration.
Clark, Teresa J; Friel, Colleen A; Grman, Emily; Shachar-Hill, Yair; Friesen, Maren L
2017-09-01
Nutritional mutualisms are ancient, widespread, and profoundly influential in biological communities and ecosystems. Although much is known about these interactions, comprehensive answers to fundamental questions, such as how resource availability and structured interactions influence mutualism persistence, are still lacking. Mathematical modelling of nutritional mutualisms has great potential to facilitate the search for comprehensive answers to these and other fundamental questions by connecting the physiological and genomic underpinnings of mutualisms with ecological and evolutionary processes. In particular, when integrated with empirical data, models enable understanding of underlying mechanisms and generalisation of principles beyond the particulars of a given system. Here, we demonstrate how mathematical models can be integrated with data to address questions of mutualism persistence at four biological scales: cell, individual, population, and community. We highlight select studies where data has been or could be integrated with models to either inform model structure or test model predictions. We also point out opportunities to increase model rigour through tighter integration with data, and describe areas in which data is urgently needed. We focus on plant-microbe systems, for which a wealth of empirical data is available, but the principles and approaches can be generally applied to any nutritional mutualism. © 2017 John Wiley & Sons Ltd/CNRS.
Community structure detection based on the neighbor node degree information
NASA Astrophysics Data System (ADS)
Tang, Li-Ying; Li, Sheng-Nan; Lin, Jian-Hong; Guo, Qiang; Liu, Jian-Guo
2016-11-01
Community structure detection is of great significance for better understanding the network topology property. By taking into account the neighbor degree information of the topological network as the link weight, we present an improved Nonnegative Matrix Factorization (NMF) method for detecting community structure. The results for empirical networks show that the largest improved ratio of the Normalized Mutual Information value could reach 63.21%. Meanwhile, for synthetic networks, the highest Normalized Mutual Information value could closely reach 1, which suggests that the improved method with the optimal λ can detect the community structure more accurately. This work is helpful for understanding the interplay between the link weight and the community structure detection.
ERIC Educational Resources Information Center
Bui, Diana D.; And Others
The results of an informal survey of the characteristics, composition, capacity building needs and future directions of sixty Cambodian, Laotian and Vietnamese Mutual Assistance Associations (MAAs) are documented in this report. Included among the survey findings are the purposes, current achievements, and future goals of the associations,…
School/Business Partnerships: We Expanded the Idea into a Mutual-Benefit Plan.
ERIC Educational Resources Information Center
Cameron, S. L.
1987-01-01
Describes a "mutual benefit" arrangement that expanded the school-business partnership model. Westfall Secondary School and an industrial operation in Owen Sound Ontario, Canada, linked their strengths and needs to offer students actual work and project experiences and to give the company useful information, services, and adult basic…
Dipole interaction of the Quincke rotating particles.
Dolinsky, Yu; Elperin, T
2012-02-01
We study the behavior of particles having a finite electric permittivity and conductivity in a weakly conducting fluid under the action of the external electric field. We consider the case when the strength of the external electric field is above the threshold, and particles rotate due to the Quincke effect. We determine the magnitude of the dipole interaction of the Quincke rotating particles and the shift of frequency of the Quincke rotation caused by the dipole interaction between the particles. It is demonstrated that depending on the mutual orientation of the vectors of angular velocities of particles, vector-directed along the straight line between the centers of the particles and the external electric field strength vector, particles can attract or repel each other. In contrast to the case of nonrotating particles when the magnitude of the dipole interaction increases with the increase of the strength of the external electric field, the magnitude of the dipole interaction of the Quincke rotating particles either does not change or decreases with the increase of the strength of the external electric field depending on the strength of the external electric field and electrodynamic parameters of the particles.
Dipole interaction of the Quincke rotating particles
NASA Astrophysics Data System (ADS)
Dolinsky, Yu.; Elperin, T.
2012-02-01
We study the behavior of particles having a finite electric permittivity and conductivity in a weakly conducting fluid under the action of the external electric field. We consider the case when the strength of the external electric field is above the threshold, and particles rotate due to the Quincke effect. We determine the magnitude of the dipole interaction of the Quincke rotating particles and the shift of frequency of the Quincke rotation caused by the dipole interaction between the particles. It is demonstrated that depending on the mutual orientation of the vectors of angular velocities of particles, vector-directed along the straight line between the centers of the particles and the external electric field strength vector, particles can attract or repel each other. In contrast to the case of nonrotating particles when the magnitude of the dipole interaction increases with the increase of the strength of the external electric field, the magnitude of the dipole interaction of the Quincke rotating particles either does not change or decreases with the increase of the strength of the external electric field depending on the strength of the external electric field and electrodynamic parameters of the particles.
Isoflurane and Ketamine Anesthesia have Different Effects on Ventilatory Pattern Variability in Rats
Chung, Augustine; Fishman, Mikkel; Dasenbrook, Elliot C.; Loparo, Kenneth A.; Dick, Thomas E.; Jacono, Frank J.
2013-01-01
We hypothesize that isoflurane and ketamine impact ventilatory pattern variability (VPV) differently. Adult Sprague-Dawley rats were recorded in a whole-body plethysmograph before, during and after deep anesthesia. VPV was quantified from 60-s epochs using a complementary set of analytic techniques that included constructing surrogate data sets that preserved the linear structure but disrupted nonlinear deterministic properties of the original data. Even though isoflurane decreased and ketamine increased respiratory rate, VPV as quantified by the coefficient of variation decreased for both anesthetics. Further, mutual information increased and sample entropy decreased and the nonlinear complexity index (NLCI) increased during anesthesia despite qualitative differences in the shape and period of the waveform. Surprisingly mutual information and sample entropy did not change in the surrogate sets constructed from isoflurane data, but in those constructed from ketamine data, mutual information increased and sample entropy decreased significantly in the surrogate segments constructed from anesthetized relative to unanesthetized epochs. These data suggest that separate mechanisms modulate linear and nonlinear variability of breathing. PMID:23246800
Maximally Informative Stimuli and Tuning Curves for Sigmoidal Rate-Coding Neurons and Populations
NASA Astrophysics Data System (ADS)
McDonnell, Mark D.; Stocks, Nigel G.
2008-08-01
A general method for deriving maximally informative sigmoidal tuning curves for neural systems with small normalized variability is presented. The optimal tuning curve is a nonlinear function of the cumulative distribution function of the stimulus and depends on the mean-variance relationship of the neural system. The derivation is based on a known relationship between Shannon’s mutual information and Fisher information, and the optimality of Jeffrey’s prior. It relies on the existence of closed-form solutions to the converse problem of optimizing the stimulus distribution for a given tuning curve. It is shown that maximum mutual information corresponds to constant Fisher information only if the stimulus is uniformly distributed. As an example, the case of sub-Poisson binomial firing statistics is analyzed in detail.
Electromagnetic Charge Radius of the Pion at High Precision
NASA Astrophysics Data System (ADS)
Ananthanarayan, B.; Caprini, Irinel; Das, Diganta
2017-09-01
We present a determination of the pion charge radius from high precision data on the pion vector form factor from both timelike and spacelike regions, using a novel formalism based on analyticity and unitarity. At low energies, instead of the poorly known modulus of the form factor, we use its phase, known with high accuracy from Roy equations for π π elastic scattering via the Fermi-Watson theorem. We use also the values of the modulus at several higher timelike energies, where the data from e+e- annihilation and τ decay are mutually consistent, as well as the most recent measurements at spacelike momenta. The experimental uncertainties are implemented by Monte Carlo simulations. The results, which do not rely on a specific parametrization, are optimal for the given input information and do not depend on the unknown phase of the form factor above the first inelastic threshold. Our prediction for the charge radius of the pion is rπ=(0.657 ±0.003 ) fm , which amounts to an increase in precision by a factor of about 2.7 compared to the Particle Data Group average.
Lin, Tungyou; Guyader, Carole Le; Dinov, Ivo; Thompson, Paul; Toga, Arthur; Vese, Luminita
2013-01-01
This paper proposes a numerical algorithm for image registration using energy minimization and nonlinear elasticity regularization. Application to the registration of gene expression data to a neuroanatomical mouse atlas in two dimensions is shown. We apply a nonlinear elasticity regularization to allow larger and smoother deformations, and further enforce optimality constraints on the landmark points distance for better feature matching. To overcome the difficulty of minimizing the nonlinear elasticity functional due to the nonlinearity in the derivatives of the displacement vector field, we introduce a matrix variable to approximate the Jacobian matrix and solve for the simplified Euler-Lagrange equations. By comparison with image registration using linear regularization, experimental results show that the proposed nonlinear elasticity model also needs fewer numerical corrections such as regridding steps for binary image registration, it renders better ground truth, and produces larger mutual information; most importantly, the landmark points distance and L2 dissimilarity measure between the gene expression data and corresponding mouse atlas are smaller compared with the registration model with biharmonic regularization. PMID:24273381
Spatially weighted mutual information image registration for image guided radiation therapy.
Park, Samuel B; Rhee, Frank C; Monroe, James I; Sohn, Jason W
2010-09-01
To develop a new metric for image registration that incorporates the (sub)pixelwise differential importance along spatial location and to demonstrate its application for image guided radiation therapy (IGRT). It is well known that rigid-body image registration with mutual information is dependent on the size and location of the image subset on which the alignment analysis is based [the designated region of interest (ROI)]. Therefore, careful review and manual adjustments of the resulting registration are frequently necessary. Although there were some investigations of weighted mutual information (WMI), these efforts could not apply the differential importance to a particular spatial location since WMI only applies the weight to the joint histogram space. The authors developed the spatially weighted mutual information (SWMI) metric by incorporating an adaptable weight function with spatial localization into mutual information. SWMI enables the user to apply the selected transform to medically "important" areas such as tumors and critical structures, so SWMI is neither dominated by, nor neglects the neighboring structures. Since SWMI can be utilized with any weight function form, the authors presented two examples of weight functions for IGRT application: A Gaussian-shaped weight function (GW) applied to a user-defined location and a structures-of-interest (SOI) based weight function. An image registration example using a synthesized 2D image is presented to illustrate the efficacy of SWMI. The convergence and feasibility of the registration method as applied to clinical imaging is illustrated by fusing a prostate treatment planning CT with a clinical cone beam CT (CBCT) image set acquired for patient alignment. Forty-one trials are run to test the speed of convergence. The authors also applied SWMI registration using two types of weight functions to two head and neck cases and a prostate case with clinically acquired CBCT/ MVCT image sets. The SWMI registration with a Gaussian weight function (SWMI-GW) was tested between two different imaging modalities: CT and MRI image sets. SWMI-GW converges 10% faster than registration using mutual information with an ROI. SWMI-GW as well as SWMI with SOI-based weight function (SWMI-SOI) shows better compensation of the target organ's deformation and neighboring critical organs' deformation. SWMI-GW was also used to successfully fuse MRI and CT images. Rigid-body image registration using our SWMI-GW and SWMI-SOI as cost functions can achieve better registration results in (a) designated image region(s) as well as faster convergence. With the theoretical foundation established, we believe SWMI could be extended to larger clinical testing.
Entanglement measures based on observable correlations
NASA Astrophysics Data System (ADS)
Luo, Shunlong
2008-06-01
By regarding quantum states as communication channels and using observable correlations quantitatively expressed by mutual information, we introduce a hierarchy of entanglement measures that includes the entanglement of formation as a particular instance. We compare the maximal and minimal measures and indicate the conceptual advantages of the minimal measure over the entanglement of formation. We reveal a curious feature of the entanglement of formation by showing that it can exceed the quantum mutual information, which is usually regarded as a theoretical measure of total correlations. This places the entanglement of formation in a broader scenario, highlights its peculiarity in relation to pure-state ensembles, and introduces a competing definition with intrinsic informational significance.
Chinese and American Women: Issues of Mutual Concern. Wingspread Brief.
ERIC Educational Resources Information Center
Johnson Foundation, Inc., Racine, WI.
This article briefly describes a conference of Chinese and American women held to discuss womens' issues and promote mutual understanding between the two groups. The cultural exchange of information at the conference focused on discussion of the All China Womens' Federation (ACWF); the roles of women in China and the United States in the areas of…
Children's Use of Mutual Exclusivity to Learn Labels for Parts of Objects
ERIC Educational Resources Information Center
Hansen, Mikkel B.; Markman, Ellen M.
2009-01-01
When teaching children part terms, adults frequently outline the relevant part rather than simply point. This pragmatic information very likely helps children interpret the label correctly. But the importance of gestures may not negate the need for default lexical biases such as the whole object assumption and mutual exclusivity. On this view,…
A feature selection approach towards progressive vector transmission over the Internet
NASA Astrophysics Data System (ADS)
Miao, Ru; Song, Jia; Feng, Min
2017-09-01
WebGIS has been applied for visualizing and sharing geospatial information popularly over the Internet. In order to improve the efficiency of the client applications, the web-based progressive vector transmission approach is proposed. Important features should be selected and transferred firstly, and the methods for measuring the importance of features should be further considered in the progressive transmission. However, studies on progressive transmission for large-volume vector data have mostly focused on map generalization in the field of cartography, but rarely discussed on the selection of geographic features quantitatively. This paper applies information theory for measuring the feature importance of vector maps. A measurement model for the amount of information of vector features is defined based upon the amount of information for dealing with feature selection issues. The measurement model involves geometry factor, spatial distribution factor and thematic attribute factor. Moreover, a real-time transport protocol (RTP)-based progressive transmission method is then presented to improve the transmission of vector data. To clearly demonstrate the essential methodology and key techniques, a prototype for web-based progressive vector transmission is presented, and an experiment of progressive selection and transmission for vector features is conducted. The experimental results indicate that our approach clearly improves the performance and end-user experience of delivering and manipulating large vector data over the Internet.
NASA Astrophysics Data System (ADS)
Quian Quiroga, R.; Kraskov, A.; Kreuz, T.; Grassberger, P.
2003-06-01
We agree with the Comment by Duckrow and Albano [Phys. Rev. E 67, 063901 (2003)] that mutual information, estimated with an optimized algorithm, can be a useful tool for studying synchronization in real data. However, we point out that the improvement they found is mainly due to an interesting but nonstandard embedding technique used, and not so much due to the algorithm used for the estimation of mutual information itself. We also address the issue of stationarity of electroencephalographic (EEG) data.
NASA Astrophysics Data System (ADS)
Gurevich, Boris M.; Tempel'man, Arcady A.
2010-05-01
For a dynamical system \\tau with 'time' \\mathbb Z^d and compact phase space X, we introduce three subsets of the space \\mathbb R^m related to a continuous function f\\colon X\\to\\mathbb R^m: the set of time means of f and two sets of space means of f, namely those corresponding to all \\tau-invariant probability measures and those corresponding to some equilibrium measures on X. The main results concern topological properties of these sets of means and their mutual position. Bibliography: 18 titles.
Computation of convex bounds for present value functions with random payments
NASA Astrophysics Data System (ADS)
Ahcan, Ales; Darkiewicz, Grzegorz; Goovaerts, Marc; Hoedemakers, Tom
2006-02-01
In this contribution we study the distribution of the present value function of a series of random payments in a stochastic financial environment. Such distributions occur naturally in a wide range of applications within fields of insurance and finance. We obtain accurate approximations by developing upper and lower bounds in the convex-order sense for present value functions. Technically speaking, our methodology is an extension of the results of Dhaene et al. [Insur. Math. Econom. 31(1) (2002) 3-33, Insur. Math. Econom. 31(2) (2002) 133-161] to the case of scalar products of mutually independent random vectors.
Optimum Multisensor, Multitarget Localization and Tracking.
1983-06-07
parameter vector t is given by (see Equation (3.5.1-7)’ the simul- taneous solution of A(e) N B G --1 ae &j’ -4n-in (fk’ ijn k3jn ~ k )kjn kjn - knn =1 k...the coefficient of mutual dependence given by M = 12 -(K-2) 121M12 :(3l 11J12 ) (K-2 and Jij is given by (see Equation (6.4.1-2)) - - (_ I R knN kn K...Transactions on Acoustic, Speech and Signal Processing, Vol ASSP-29, No. 3, June 1981. 17. B. Friedlander, "An ARMA Modeling Approach to Multitarget Tracking
Heat engine driven by purely quantum information.
Park, Jung Jun; Kim, Kang-Hwan; Sagawa, Takahiro; Kim, Sang Wook
2013-12-06
The key question of this Letter is whether work can be extracted from a heat engine by using purely quantum mechanical information. If the answer is yes, what is its mathematical formula? First, by using a bipartite memory we show that the work extractable from a heat engine is bounded not only by the free energy change and the sum of the entropy change of an individual memory but also by the change of quantum mutual information contained inside the memory. We then find that the engine can be driven by purely quantum information, expressed as the so-called quantum discord, forming a part of the quantum mutual information. To confirm it, as a physical example we present the Szilard engine containing a diatomic molecule with a semipermeable wall.
Universal recovery map for approximate Markov chains.
Sutter, David; Fawzi, Omar; Renner, Renato
2016-02-01
A central question in quantum information theory is to determine how well lost information can be reconstructed. Crucially, the corresponding recovery operation should perform well without knowing the information to be reconstructed. In this work, we show that the quantum conditional mutual information measures the performance of such recovery operations. More precisely, we prove that the conditional mutual information I ( A : C | B ) of a tripartite quantum state ρ ABC can be bounded from below by its distance to the closest recovered state [Formula: see text], where the C -part is reconstructed from the B -part only and the recovery map [Formula: see text] merely depends on ρ BC . One particular application of this result implies the equivalence between two different approaches to define topological order in quantum systems.
Universal recovery map for approximate Markov chains
Sutter, David; Fawzi, Omar; Renner, Renato
2016-01-01
A central question in quantum information theory is to determine how well lost information can be reconstructed. Crucially, the corresponding recovery operation should perform well without knowing the information to be reconstructed. In this work, we show that the quantum conditional mutual information measures the performance of such recovery operations. More precisely, we prove that the conditional mutual information I(A:C|B) of a tripartite quantum state ρABC can be bounded from below by its distance to the closest recovered state RB→BC(ρAB), where the C-part is reconstructed from the B-part only and the recovery map RB→BC merely depends on ρBC. One particular application of this result implies the equivalence between two different approaches to define topological order in quantum systems. PMID:27118889
Han, Fang; Wang, Zhijie; Fan, Hong
2017-01-01
This paper proposed a new method to determine the neuronal tuning curves for maximum information efficiency by computing the optimum firing rate distribution. Firstly, we proposed a general definition for the information efficiency, which is relevant to mutual information and neuronal energy consumption. The energy consumption is composed of two parts: neuronal basic energy consumption and neuronal spike emission energy consumption. A parameter to model the relative importance of energy consumption is introduced in the definition of the information efficiency. Then, we designed a combination of exponential functions to describe the optimum firing rate distribution based on the analysis of the dependency of the mutual information and the energy consumption on the shape of the functions of the firing rate distributions. Furthermore, we developed a rapid algorithm to search the parameter values of the optimum firing rate distribution function. Finally, we found with the rapid algorithm that a combination of two different exponential functions with two free parameters can describe the optimum firing rate distribution accurately. We also found that if the energy consumption is relatively unimportant (important) compared to the mutual information or the neuronal basic energy consumption is relatively large (small), the curve of the optimum firing rate distribution will be relatively flat (steep), and the corresponding optimum tuning curve exhibits a form of sigmoid if the stimuli distribution is normal. PMID:28270760
Quantization of Gaussian samples at very low SNR regime in continuous variable QKD applications
NASA Astrophysics Data System (ADS)
Daneshgaran, Fred; Mondin, Marina
2016-09-01
The main problem for information reconciliation in continuous variable Quantum Key Distribution (QKD) at low Signal to Noise Ratio (SNR) is quantization and assignment of labels to the samples of the Gaussian Random Variables (RVs) observed at Alice and Bob. Trouble is that most of the samples, assuming that the Gaussian variable is zero mean which is de-facto the case, tend to have small magnitudes and are easily disturbed by noise. Transmission over longer and longer distances increases the losses corresponding to a lower effective SNR exasperating the problem. This paper looks at the quantization problem of the Gaussian samples at very low SNR regime from an information theoretic point of view. We look at the problem of two bit per sample quantization of the Gaussian RVs at Alice and Bob and derive expressions for the mutual information between the bit strings as a result of this quantization. The quantization threshold for the Most Significant Bit (MSB) should be chosen based on the maximization of the mutual information between the quantized bit strings. Furthermore, while the LSB string at Alice and Bob are balanced in a sense that their entropy is close to maximum, this is not the case for the second most significant bit even under optimal threshold. We show that with two bit quantization at SNR of -3 dB we achieve 75.8% of maximal achievable mutual information between Alice and Bob, hence, as the number of quantization bits increases beyond 2-bits, the number of additional useful bits that can be extracted for secret key generation decreases rapidly. Furthermore, the error rates between the bit strings at Alice and Bob at the same significant bit level are rather high demanding very powerful error correcting codes. While our calculations and simulation shows that the mutual information between the LSB at Alice and Bob is 0.1044 bits, that at the MSB level is only 0.035 bits. Hence, it is only by looking at the bits jointly that we are able to achieve a mutual information of 0.2217 bits which is 75.8% of maximum achievable. The implication is that only by coding both MSB and LSB jointly can we hope to get close to this 75.8% limit. Hence, non-binary codes are essential to achieve acceptable performance.
Optimal protocol for maximum work extraction in a feedback process with a time-varying potential
NASA Astrophysics Data System (ADS)
Kwon, Chulan
2017-12-01
The nonequilibrium nature of information thermodynamics is characterized by the inequality or non-negativity of the total entropy change of the system, memory, and reservoir. Mutual information change plays a crucial role in the inequality, in particular if work is extracted and the paradox of Maxwell's demon is raised. We consider the Brownian information engine where the protocol set of the harmonic potential is initially chosen by the measurement and varies in time. We confirm the inequality of the total entropy change by calculating, in detail, the entropic terms including the mutual information change. We rigorously find the optimal values of the time-dependent protocol for maximum extraction of work both for the finite-time and the quasi-static process.
NASA Astrophysics Data System (ADS)
Tezuka, Miwa; Kanno, Kazutaka; Bunsen, Masatoshi
2016-08-01
Reservoir computing is a machine-learning paradigm based on information processing in the human brain. We numerically demonstrate reservoir computing with a slowly modulated mask signal for preprocessing by using a mutually coupled optoelectronic system. The performance of our system is quantitatively evaluated by a chaotic time series prediction task. Our system can produce comparable performance with reservoir computing with a single feedback system and a fast modulated mask signal. We showed that it is possible to slow down the modulation speed of the mask signal by using the mutually coupled system in reservoir computing.
Vector and Raster Data Storage Based on Morton Code
NASA Astrophysics Data System (ADS)
Zhou, G.; Pan, Q.; Yue, T.; Wang, Q.; Sha, H.; Huang, S.; Liu, X.
2018-05-01
Even though geomatique is so developed nowadays, the integration of spatial data in vector and raster formats is still a very tricky problem in geographic information system environment. And there is still not a proper way to solve the problem. This article proposes a method to interpret vector data and raster data. In this paper, we saved the image data and building vector data of Guilin University of Technology to Oracle database. Then we use ADO interface to connect database to Visual C++ and convert row and column numbers of raster data and X Y of vector data to Morton code in Visual C++ environment. This method stores vector and raster data to Oracle Database and uses Morton code instead of row and column and X Y to mark the position information of vector and raster data. Using Morton code to mark geographic information enables storage of data make full use of storage space, simultaneous analysis of vector and raster data more efficient and visualization of vector and raster more intuitive. This method is very helpful for some situations that need to analyse or display vector data and raster data at the same time.
Taghva, Alexander; Song, Dong; Hampson, Robert E.; Deadwyler, Sam A.; Berger, Theodore W.
2013-01-01
BACKGROUND Identification of functional dependence among neurons is a necessary component in both the rational design of neural prostheses as well as in the characterization of network physiology. The objective of this article is to provide a tutorial for neurosurgeons regarding information theory, specifically time-delayed mutual information, and to compare time-delayed mutual information, an information theoretic quantity based on statistical dependence, with cross-correlation, a commonly used metric for this task in a preliminary analysis of rat hippocampal neurons. METHODS Spike trains were recorded from rats performing delayed nonmatch-to-sample task using an array of electrodes surgically implanted into the hippocampus of each hemisphere of the brain. In addition, spike train simulations of positively correlated neurons, negatively correlated neurons, and neurons correlated by nonlinear functions were generated. These were evaluated by time-delayed mutual information (MI) and cross-correlation. RESULTS Application of time-delayed MI to experimental data indicated the optimal bin size for information capture in the CA3-CA1 system was 40 ms, which may provide some insight into the spatiotemporal nature of encoding in the rat hippocampus. On simulated data, time-delayed MI showed peak values at appropriate time lags in positively correlated, negatively correlated, and complexly correlated data. Cross-correlation showed peak and troughs with positively correlated and negatively correlated data, but failed to capture some higher order correlations. CONCLUSIONS Comparison of time-delayed MI to cross-correlation in identification of functionally dependent neurons indicates that the methods are not equivalent. Time-delayed MI appeared to capture some interactions between CA3-CA1 neurons at physiologically plausible time delays missed by cross-correlation. It should be considered as a method for identification of functional dependence between neurons and may be useful in the development of neural prosthetics. PMID:22120279
Taghva, Alexander; Song, Dong; Hampson, Robert E; Deadwyler, Sam A; Berger, Theodore W
2012-12-01
Identification of functional dependence among neurons is a necessary component in both the rational design of neural prostheses as well as in the characterization of network physiology. The objective of this article is to provide a tutorial for neurosurgeons regarding information theory, specifically time-delayed mutual information, and to compare time-delayed mutual information, an information theoretic quantity based on statistical dependence, with cross-correlation, a commonly used metric for this task in a preliminary analysis of rat hippocampal neurons. Spike trains were recorded from rats performing delayed nonmatch-to-sample task using an array of electrodes surgically implanted into the hippocampus of each hemisphere of the brain. In addition, spike train simulations of positively correlated neurons, negatively correlated neurons, and neurons correlated by nonlinear functions were generated. These were evaluated by time-delayed mutual information (MI) and cross-correlation. Application of time-delayed MI to experimental data indicated the optimal bin size for information capture in the CA3-CA1 system was 40 ms, which may provide some insight into the spatiotemporal nature of encoding in the rat hippocampus. On simulated data, time-delayed MI showed peak values at appropriate time lags in positively correlated, negatively correlated, and complexly correlated data. Cross-correlation showed peak and troughs with positively correlated and negatively correlated data, but failed to capture some higher order correlations. Comparison of time-delayed MI to cross-correlation in identification of functionally dependent neurons indicates that the methods are not equivalent. Time-delayed MI appeared to capture some interactions between CA3-CA1 neurons at physiologically plausible time delays missed by cross-correlation. It should be considered as a method for identification of functional dependence between neurons and may be useful in the development of neural prosthetics. Copyright © 2012 Elsevier Inc. All rights reserved.
Mutual information as a measure of image quality for 3D dynamic lung imaging with EIT
Crabb, M G; Davidson, J L; Little, R; Wright, P; Morgan, A R; Miller, C A; Naish, J H; Parker, G J M; Kikinis, R; McCann, H; Lionheart, W R B
2014-01-01
We report on a pilot study of dynamic lung electrical impedance tomography (EIT) at the University of Manchester. Low-noise EIT data at 100 frames per second (fps) were obtained from healthy male subjects during controlled breathing, followed by magnetic resonance imaging (MRI) subsequently used for spatial validation of the EIT reconstruction. The torso surface in the MR image and electrode positions obtained using MRI fiducial markers informed the construction of a 3D finite element model extruded along the caudal-distal axis of the subject. Small changes in the boundary that occur during respiration were accounted for by incorporating the sensitivity with respect to boundary shape into a robust temporal difference reconstruction algorithm. EIT and MRI images were co-registered using the open source medical imaging software, 3D Slicer. A quantitative comparison of quality of different EIT reconstructions was achieved through calculation of the mutual information with a lung-segmented MR image. EIT reconstructions using a linear shape correction algorithm reduced boundary image artefacts, yielding better contrast of the lungs, and had 10% greater mutual information compared with a standard linear EIT reconstruction. PMID:24710978
Computing algebraic transfer entropy and coupling directions via transcripts
NASA Astrophysics Data System (ADS)
Amigó, José M.; Monetti, Roberto; Graff, Beata; Graff, Grzegorz
2016-11-01
Most random processes studied in nonlinear time series analysis take values on sets endowed with a group structure, e.g., the real and rational numbers, and the integers. This fact allows to associate with each pair of group elements a third element, called their transcript, which is defined as the product of the second element in the pair times the first one. The transfer entropy of two such processes is called algebraic transfer entropy. It measures the information transferred between two coupled processes whose values belong to a group. In this paper, we show that, subject to one constraint, the algebraic transfer entropy matches the (in general, conditional) mutual information of certain transcripts with one variable less. This property has interesting practical applications, especially to the analysis of short time series. We also derive weak conditions for the 3-dimensional algebraic transfer entropy to yield the same coupling direction as the corresponding mutual information of transcripts. A related issue concerns the use of mutual information of transcripts to determine coupling directions in cases where the conditions just mentioned are not fulfilled. We checked the latter possibility in the lowest dimensional case with numerical simulations and cardiovascular data, and obtained positive results.
Mutual information as a measure of image quality for 3D dynamic lung imaging with EIT.
Crabb, M G; Davidson, J L; Little, R; Wright, P; Morgan, A R; Miller, C A; Naish, J H; Parker, G J M; Kikinis, R; McCann, H; Lionheart, W R B
2014-05-01
We report on a pilot study of dynamic lung electrical impedance tomography (EIT) at the University of Manchester. Low-noise EIT data at 100 frames per second were obtained from healthy male subjects during controlled breathing, followed by magnetic resonance imaging (MRI) subsequently used for spatial validation of the EIT reconstruction. The torso surface in the MR image and electrode positions obtained using MRI fiducial markers informed the construction of a 3D finite element model extruded along the caudal-distal axis of the subject. Small changes in the boundary that occur during respiration were accounted for by incorporating the sensitivity with respect to boundary shape into a robust temporal difference reconstruction algorithm. EIT and MRI images were co-registered using the open source medical imaging software, 3D Slicer. A quantitative comparison of quality of different EIT reconstructions was achieved through calculation of the mutual information with a lung-segmented MR image. EIT reconstructions using a linear shape correction algorithm reduced boundary image artefacts, yielding better contrast of the lungs, and had 10% greater mutual information compared with a standard linear EIT reconstruction.
Permutation auto-mutual information of electroencephalogram in anesthesia
NASA Astrophysics Data System (ADS)
Liang, Zhenhu; Wang, Yinghua; Ouyang, Gaoxiang; Voss, Logan J.; Sleigh, Jamie W.; Li, Xiaoli
2013-04-01
Objective. The dynamic change of brain activity in anesthesia is an interesting topic for clinical doctors and drug designers. To explore the dynamical features of brain activity in anesthesia, a permutation auto-mutual information (PAMI) method is proposed to measure the information coupling of electroencephalogram (EEG) time series obtained in anesthesia. Approach. The PAMI is developed and applied on EEG data collected from 19 patients under sevoflurane anesthesia. The results are compared with the traditional auto-mutual information (AMI), SynchFastSlow (SFS, derived from the BIS index), permutation entropy (PE), composite PE (CPE), response entropy (RE) and state entropy (SE). Performance of all indices is assessed by pharmacokinetic/pharmacodynamic (PK/PD) modeling and prediction probability. Main results. The PK/PD modeling and prediction probability analysis show that the PAMI index correlates closely with the anesthetic effect. The coefficient of determination R2 between PAMI values and the sevoflurane effect site concentrations, and the prediction probability Pk are higher in comparison with other indices. The information coupling in EEG series can be applied to indicate the effect of the anesthetic drug sevoflurane on the brain activity as well as other indices. The PAMI of the EEG signals is suggested as a new index to track drug concentration change. Significance. The PAMI is a useful index for analyzing the EEG dynamics during general anesthesia.
Optimal reconstruction of the states in qutrit systems
NASA Astrophysics Data System (ADS)
Yan, Fei; Yang, Ming; Cao, Zhuo-Liang
2010-10-01
Based on mutually unbiased measurements, an optimal tomographic scheme for the multiqutrit states is presented explicitly. Because the reconstruction process of states based on mutually unbiased states is free of information waste, we refer to our scheme as the optimal scheme. By optimal we mean that the number of the required conditional operations reaches the minimum in this tomographic scheme for the states of qutrit systems. Special attention will be paid to how those different mutually unbiased measurements are realized; that is, how to decompose each transformation that connects each mutually unbiased basis with the standard computational basis. It is found that all those transformations can be decomposed into several basic implementable single- and two-qutrit unitary operations. For the three-qutrit system, there exist five different mutually unbiased-bases structures with different entanglement properties, so we introduce the concept of physical complexity to minimize the number of nonlocal operations needed over the five different structures. This scheme is helpful for experimental scientists to realize the most economical reconstruction of quantum states in qutrit systems.
Dendritic excitability modulates dendritic information processing in a purkinje cell model.
Coop, Allan D; Cornelis, Hugo; Santamaria, Fidel
2010-01-01
Using an electrophysiological compartmental model of a Purkinje cell we quantified the contribution of individual active dendritic currents to processing of synaptic activity from granule cells. We used mutual information as a measure to quantify the information from the total excitatory input current (I(Glu)) encoded in each dendritic current. In this context, each active current was considered an information channel. Our analyses showed that most of the information was encoded by the calcium (I(CaP)) and calcium activated potassium (I(Kc)) currents. Mutual information between I(Glu) and I(CaP) and I(Kc) was sensitive to different levels of excitatory and inhibitory synaptic activity that, at the same time, resulted in the same firing rate at the soma. Since dendritic excitability could be a mechanism to regulate information processing in neurons we quantified the changes in mutual information between I(Glu) and all Purkinje cell currents as a function of the density of dendritic Ca (g(CaP)) and Kca (g(Kc)) conductances. We extended our analysis to determine the window of temporal integration of I(Glu) by I(CaP) and I(Kc) as a function of channel density and synaptic activity. The window of information integration has a stronger dependence on increasing values of g(Kc) than on g(CaP), but at high levels of synaptic stimulation information integration is reduced to a few milliseconds. Overall, our results show that different dendritic conductances differentially encode synaptic activity and that dendritic excitability and the level of synaptic activity regulate the flow of information in dendrites.
Non-Mutually Exclusive Deep Neural Network Classifier for Combined Modes of Bearing Fault Diagnosis.
Duong, Bach Phi; Kim, Jong-Myon
2018-04-07
The simultaneous occurrence of various types of defects in bearings makes their diagnosis more challenging owing to the resultant complexity of the constituent parts of the acoustic emission (AE) signals. To address this issue, a new approach is proposed in this paper for the detection of multiple combined faults in bearings. The proposed methodology uses a deep neural network (DNN) architecture to effectively diagnose the combined defects. The DNN structure is based on the stacked denoising autoencoder non-mutually exclusive classifier (NMEC) method for combined modes. The NMEC-DNN is trained using data for a single fault and it classifies both single faults and multiple combined faults. The results of experiments conducted on AE data collected through an experimental test-bed demonstrate that the DNN achieves good classification performance with a maximum accuracy of 95%. The proposed method is compared with a multi-class classifier based on support vector machines (SVMs). The NMEC-DNN yields better diagnostic performance in comparison to the multi-class classifier based on SVM. The NMEC-DNN reduces the number of necessary data collections and improves the bearing fault diagnosis performance.
ERIC Educational Resources Information Center
Denissen, Jaap J. A.; van Aken, Marcel A. G.; Dubas, Judith S.
2009-01-01
According to J. Belsky's (1984) process model of parenting, both adolescents' and parents' personality should exert a significant impact on the quality of their mutual relationship. Using multi-informant, symmetric data on the Big Five personality traits and the relationship quality of mothers, fathers, and two adolescent children, the current…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Carle, S F
Compositional data are represented as vector variables with individual vector components ranging between zero and a positive maximum value representing a constant sum constraint, usually unity (or 100 percent). The earth sciences are flooded with spatial distributions of compositional data, such as concentrations of major ion constituents in natural waters (e.g. mole, mass, or volume fractions), mineral percentages, ore grades, or proportions of mutually exclusive categories (e.g. a water-oil-rock system). While geostatistical techniques have become popular in earth science applications since the 1970s, very little attention has been paid to the unique mathematical properties of geostatistical formulations involving compositional variables.more » The book 'Geostatistical Analysis of Compositional Data' by Vera Pawlowsky-Glahn and Ricardo Olea (Oxford University Press, 2004), unlike any previous book on geostatistics, directly confronts the mathematical difficulties inherent to applying geostatistics to compositional variables. The book righteously justifies itself with prodigious referencing to previous work addressing nonsensical ranges of estimated values and error, spurious correlation, and singular cross-covariance matrices.« less
Novel Rickettsiella Bacterium in the Leafhopper Orosius albicinctus (Hemiptera: Cicadellidae)
Iasur-Kruh, Lilach; Weintraub, Phyllis G.; Mozes-Daube, Netta; Robinson, Wyatt E.; Perlman, Steve J.
2013-01-01
Bacteria in the genus Rickettsiella (Coxiellaceae), which are mainly known as arthropod pathogens, are emerging as excellent models to study transitions between mutualism and pathogenicity. The current report characterizes a novel Rickettsiella found in the leafhopper Orosius albicinctus (Hemiptera: Cicadellidae), a major vector of phytoplasma diseases in Europe and Asia. Denaturing gradient gel electrophoresis (DGGE) and pyrosequencing were used to survey the main symbionts of O. albicinctus, revealing the obligate symbionts Sulcia and Nasuia, and the facultative symbionts Arsenophonus and Wolbachia, in addition to Rickettsiella. The leafhopper Rickettsiella is allied with bacteria found in ticks. Screening O. albicinctus from the field showed that Rickettsiella is highly prevalent, with over 60% of individuals infected. A stable Rickettsiella infection was maintained in a leafhopper laboratory colony for at least 10 generations, and fluorescence microscopy localized bacteria to accessory glands of the female reproductive tract, suggesting that the bacterium is vertically transmitted. Future studies will be needed to examine how Rickettsiella affects host fitess and its ability to vector phytopathogens. PMID:23645190
The fungal aroma gene ATF1 promotes dispersal of yeast cells through insect vectors.
Christiaens, Joaquin F; Franco, Luis M; Cools, Tanne L; De Meester, Luc; Michiels, Jan; Wenseleers, Tom; Hassan, Bassem A; Yaksi, Emre; Verstrepen, Kevin J
2014-10-23
Yeast cells produce various volatile metabolites that are key contributors to the pleasing fruity and flowery aroma of fermented beverages. Several of these fruity metabolites, including isoamyl acetate and ethyl acetate, are produced by a dedicated enzyme, the alcohol acetyl transferase Atf1. However, despite much research, the physiological role of acetate ester formation in yeast remains unknown. Using a combination of molecular biology, neurobiology, and behavioral tests, we demonstrate that deletion of ATF1 alters the olfactory response in the antennal lobe of fruit flies that feed on yeast cells. The flies are much less attracted to the mutant yeast cells, and this in turn results in reduced dispersal of the mutant yeast cells by the flies. Together, our results uncover the molecular details of an intriguing aroma-based communication and mutualism between microbes and their insect vectors. Similar mechanisms may exist in other microbes, including microbes on flowering plants and pathogens. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
Cycle/Cocycle Oblique Projections on Oriented Graphs
NASA Astrophysics Data System (ADS)
Polettini, Matteo
2015-01-01
It is well known that the edge vector space of an oriented graph can be decomposed in terms of cycles and cocycles (alias cuts, or bonds), and that a basis for the cycle and the cocycle spaces can be generated by adding and removing edges to an arbitrarily chosen spanning tree. In this paper, we show that the edge vector space can also be decomposed in terms of cycles and the generating edges of cocycles (called cochords), or of cocycles and the generating edges of cycles (called chords). From this observation follows a construction in terms of oblique complementary projection operators. We employ this algebraic construction to prove several properties of unweighted Kirchhoff-Symanzik matrices, encoding the mutual superposition between cycles and cocycles. In particular, we prove that dual matrices of planar graphs have the same spectrum (up to multiplicities). We briefly comment on how this construction provides a refined formalization of Kirchhoff's mesh analysis of electrical circuits, which has lately been applied to generic thermodynamic networks.
Host influence in the genomic composition of flaviviruses: A multivariate approach.
Simón, Diego; Fajardo, Alvaro; Sóñora, Martín; Delfraro, Adriana; Musto, Héctor
2017-10-28
Flaviviruses present substantial differences in their host range and transmissibility. We studied the evolution of base composition, dinucleotide biases, codon usage and amino acid frequencies in the genus Flavivirus within a phylogenetic framework by principal components analysis. There is a mutual interplay between the evolutionary history of flaviviruses and their respective vectors and/or hosts. Hosts associated to distinct phylogenetic groups may be driving flaviviruses at different pace and through various sequence landscapes, as can be seen for viruses associated with Aedes or Culex spp., although phylogenetic inertia cannot be ruled out. In some cases, viruses face even opposite forces. For instance, in tick-borne flaviviruses, while vertebrate hosts exert pressure to deplete their CpG, tick vectors drive them to exhibit GC-rich codons. Within a vertebrate environment, natural selection appears to be acting on the viral genome to overcome the immune system. On the other side, within an arthropod environment, mutational biases seem to be the dominant forces. Copyright © 2017 Elsevier Inc. All rights reserved.
Critical scaling of the mutual information in two-dimensional disordered Ising models
NASA Astrophysics Data System (ADS)
Sriluckshmy, P. V.; Mandal, Ipsita
2018-04-01
Rényi mutual information, computed from second Rényi entropies, can identify classical phase transitions from their finite-size scaling at critical points. We apply this technique to examine the presence or absence of finite temperature phase transitions in various two-dimensional models on a square lattice, which are extensions of the conventional Ising model by adding a quenched disorder. When the quenched disorder causes the nearest neighbor bonds to be both ferromagnetic and antiferromagnetic, (a) a spin glass phase exists only at zero temperature, and (b) a ferromagnetic phase exists at a finite temperature when the antiferromagnetic bond distributions are sufficiently dilute. Furthermore, finite temperature paramagnetic-ferromagnetic transitions can also occur when the disordered bonds involve only ferromagnetic couplings of random strengths. In our numerical simulations, the ‘zero temperature only’ phase transitions are identified when there is no consistent finite-size scaling of the Rényi mutual information curves, while for finite temperature critical points, the curves can identify the critical temperature T c by their crossings at T c and 2 Tc .
Least-dependent-component analysis based on mutual information
NASA Astrophysics Data System (ADS)
Stögbauer, Harald; Kraskov, Alexander; Astakhov, Sergey A.; Grassberger, Peter
2004-12-01
We propose to use precise estimators of mutual information (MI) to find the least dependent components in a linearly mixed signal. On the one hand, this seems to lead to better blind source separation than with any other presently available algorithm. On the other hand, it has the advantage, compared to other implementations of “independent” component analysis (ICA), some of which are based on crude approximations for MI, that the numerical values of the MI can be used for (i) estimating residual dependencies between the output components; (ii) estimating the reliability of the output by comparing the pairwise MIs with those of remixed components; and (iii) clustering the output according to the residual interdependencies. For the MI estimator, we use a recently proposed k -nearest-neighbor-based algorithm. For time sequences, we combine this with delay embedding, in order to take into account nontrivial time correlations. After several tests with artificial data, we apply the resulting MILCA (mutual-information-based least dependent component analysis) algorithm to a real-world dataset, the ECG of a pregnant woman.
Effect of age on changes in motor units functional connectivity.
Arjunan, Sridhar P; Kumar, Dinesh
2015-08-01
With age, there is a change in functional connectivity of motor units in muscle. This leads to reduced muscle strength. This study has investigated the effect of age on the changes in the motor unit recruitment by measuring the mutual information between multiple channels of surface electromyogram (sEMG) of biceps brachii muscle. It is hypothesised that with ageing, there is a reduction in number of motor units, which can lead to an increase in the dependency of remaining motor units. This increase can be observed in the mutual information between the multiple channels of the muscle activity. Two channels of sEMG were recorded during the maximum level of isometric contraction. 28 healthy subjects (Young: age range 20-35years and Old: age range - 60-70years) participated in the experiments. The normalized mutual information (NMI), a measure of dependency factor, was computed for the sEMG recordings. Statistical analysis was performed to test the effect of age on NMI. The results show that the NMI among the older cohort was significantly higher when compared with the young adults.
Effect of acculturation and mutuality on family loyalty among Mexican American caregivers of elders.
Kao, Hsueh-Fen S; An, Kyungeh
2012-06-01
Informal family care for elders is conventional in Mexican American communities despite increasing intergenerational gaps in filial values. In our study, we explored whether acculturation and dyadic mutuality, as perceived by Mexican American family caregivers, explain the caregivers' expectations of family loyalty toward elderly relatives. A nonexperimental, correlational design with convenience sampling was used in El Paso, Texas, from October 2007 to January 2008. Three bilingual promotoras collected data from 193 Mexican American adult caregivers of community-dwelling elders using three scales designed for Mexican Americans: the Acculturation Rating Scale for Mexican Americans II-Short Form, the Mutuality Scale, and the Expectations of Family Loyalty of Children Toward Elderly Relatives Scale. Confirmatory factor analysis was used to analyze the data. Acculturation had a marginal effect (r = .21, p < .05), but mutuality presented a strong correlation (r = .45, p < .001) with the expectations of family loyalty toward elderly relatives. There was no significant correlation between acculturation and mutuality (r = .05). Although Mexican American caregivers with strong Mexican orientation may have high expectations of family loyalty toward elderly relatives, mutuality exhibits more significant effects on expectations. Among Mexican Americans, mutuality between the caregiving dyad, as perceived by caregivers, may be a better predictor of filial values than caregivers' acculturation alone. It may be useful to incorporate the dual paradigm of acculturation and mutuality into immigrant family care for elderly relatives. © 2012 Sigma Theta Tau International.
Altschuler, Andrea; Liljestrand, Petra; Grant, Marcia; Hornbrook, Mark C; Krouse, Robert S; McMullen, Carmit K
2018-02-01
The cancer caregiving literature focuses on the early phases of survivorship, but caregiving can continue for decades when cancer creates disability. Survivors with an ostomy following colorectal cancer (CRC) have caregiving needs that may last decades. Mutuality has been identified as a relationship component that can affect caregiving. This paper discusses how mutuality may affect long-term ostomy caregiving. We conducted semi-structured, in-depth interviews with 31 long-term CRC survivors with ostomies and their primary informal caregivers. Interviewees were members of an integrated health care delivery system in the USA. We used inductive theme analysis techniques to analyze the interviews. Most survivors were 71 years of age or older (67%), female (55%), and with some college education (54%). Two thirds lived with and received care from spouses. Caregiving ranged from minimal support to intimate assistance with daily ostomy care. While some survivors received caregiving far beyond what was needed, others did not receive adequate caregiving for their health care needs. Low mutuality created challenges for ostomy caregiving. Mutuality impacts the quality of caregiving, and this quality may change over time, depending on various factors. Emotional feedback and amplification is the proposed mechanism by which mutuality may shift over time. Survivorship care should include assessment and support of mutuality as a resource to enhance health outcomes and quality of life for survivors with long-term caregiving needs and their caregivers. Appropriate questionnaires can be identified or developed to assess mutuality over the survivorship trajectory.
Resolution of Probabilistic Weather Forecasts with Application in Disease Management.
Hughes, G; McRoberts, N; Burnett, F J
2017-02-01
Predictive systems in disease management often incorporate weather data among the disease risk factors, and sometimes this comes in the form of forecast weather data rather than observed weather data. In such cases, it is useful to have an evaluation of the operational weather forecast, in addition to the evaluation of the disease forecasts provided by the predictive system. Typically, weather forecasts and disease forecasts are evaluated using different methodologies. However, the information theoretic quantity expected mutual information provides a basis for evaluating both kinds of forecast. Expected mutual information is an appropriate metric for the average performance of a predictive system over a set of forecasts. Both relative entropy (a divergence, measuring information gain) and specific information (an entropy difference, measuring change in uncertainty) provide a basis for the assessment of individual forecasts.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tziotziou, Kostas; Georgoulis, Manolis K.; Liu Yang
In previous works, we introduced a nonlinear force-free method that self-consistently calculates the instantaneous budgets of free magnetic energy and relative magnetic helicity in solar active regions (ARs). Calculation is expedient and practical, using only a single vector magnetogram per computation. We apply this method to a time series of 600 high-cadence vector magnetograms of the eruptive NOAA AR 11158 acquired by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory over a five-day observing interval. Besides testing our method extensively, we use it to interpret the dynamical evolution in the AR, including eruptions. We find that themore » AR builds large budgets of both free magnetic energy and relative magnetic helicity, sufficient to power many more eruptions than the ones it gave within the interval of interest. For each of these major eruptions, we find eruption-related decreases and subsequent free-energy and helicity budgets that are consistent with the observed eruption (flare and coronal mass ejection (CME)) sizes. In addition, we find that (1) evolution in the AR is consistent with the recently proposed (free) energy-(relative) helicity diagram of solar ARs, (2) eruption-related decreases occur before the flare and the projected CME-launch times, suggesting that CME progenitors precede flares, and (3) self terms of free energy and relative helicity most likely originate from respective mutual terms, following a progressive mutual-to-self conversion pattern that most likely stems from magnetic reconnection. This results in the non-ideal formation of increasingly helical pre-eruption structures and instigates further research on the triggering of solar eruptions with magnetic helicity firmly placed in the eruption cadre.« less
Ince, Robin A A; Giordano, Bruno L; Kayser, Christoph; Rousselet, Guillaume A; Gross, Joachim; Schyns, Philippe G
2017-03-01
We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open-source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541-1573, 2017. © 2016 Wiley Periodicals, Inc. 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Information flow to assess cardiorespiratory interactions in patients on weaning trials.
Vallverdú, M; Tibaduisa, O; Clariá, F; Hoyer, D; Giraldo, B; Benito, S; Caminal, P
2006-01-01
Nonlinear processes of the autonomic nervous system (ANS) can produce breath-to-breath variability in the pattern of breathing. In order to provide assess to these nonlinear processes, nonlinear statistical dependencies between heart rate variability and respiratory pattern variability are analyzed. In this way, auto-mutual information and cross-mutual information concepts are applied. This information flow analysis is presented as a short-term non linear analysis method to investigate the information flow interactions in patients on weaning trials. 78 patients from mechanical ventilation were studied: Group A of 28 patients that failed to maintain spontaneous breathing and were reconnected; Group B of 50 patients with successful trials. The results show lower complexity with an increase of information flow in group A than in group B. Furthermore, a more (weakly) coupled nonlinear oscillator behavior is observed in the series of group A than in B.
Vaxvec: The first web-based recombinant vaccine vector database and its data analysis
Deng, Shunzhou; Martin, Carly; Patil, Rasika; Zhu, Felix; Zhao, Bin; Xiang, Zuoshuang; He, Yongqun
2015-01-01
A recombinant vector vaccine uses an attenuated virus, bacterium, or parasite as the carrier to express a heterologous antigen(s). Many recombinant vaccine vectors and related vaccines have been developed and extensively investigated. To compare and better understand recombinant vectors and vaccines, we have generated Vaxvec (http://www.violinet.org/vaxvec), the first web-based database that stores various recombinant vaccine vectors and those experimentally verified vaccines that use these vectors. Vaxvec has now included 59 vaccine vectors that have been used in 196 recombinant vector vaccines against 66 pathogens and cancers. These vectors are classified to 41 viral vectors, 15 bacterial vectors, 1 parasitic vector, and 1 fungal vector. The most commonly used viral vaccine vectors are double-stranded DNA viruses, including herpesviruses, adenoviruses, and poxviruses. For example, Vaxvec includes 63 poxvirus-based recombinant vaccines for over 20 pathogens and cancers. Vaxvec collects 30 recombinant vector influenza vaccines that use 17 recombinant vectors and were experimentally tested in 7 animal models. In addition, over 60 protective antigens used in recombinant vector vaccines are annotated and analyzed. User-friendly web-interfaces are available for querying various data in Vaxvec. To support data exchange, the information of vaccine vectors, vaccines, and related information is stored in the Vaccine Ontology (VO). Vaxvec is a timely and vital source of vaccine vector database and facilitates efficient vaccine vector research and development. PMID:26403370
Signal processing in local neuronal circuits based on activity-dependent noise and competition
NASA Astrophysics Data System (ADS)
Volman, Vladislav; Levine, Herbert
2009-09-01
We study the characteristics of weak signal detection by a recurrent neuronal network with plastic synaptic coupling. It is shown that in the presence of an asynchronous component in synaptic transmission, the network acquires selectivity with respect to the frequency of weak periodic stimuli. For nonperiodic frequency-modulated stimuli, the response is quantified by the mutual information between input (signal) and output (network's activity) and is optimized by synaptic depression. Introducing correlations in signal structure resulted in the decrease in input-output mutual information. Our results suggest that in neural systems with plastic connectivity, information is not merely carried passively by the signal; rather, the information content of the signal itself might determine the mode of its processing by a local neuronal circuit.
A Method for Evaluating Tuning Functions of Single Neurons based on Mutual Information Maximization
NASA Astrophysics Data System (ADS)
Brostek, Lukas; Eggert, Thomas; Ono, Seiji; Mustari, Michael J.; Büttner, Ulrich; Glasauer, Stefan
2011-03-01
We introduce a novel approach for evaluation of neuronal tuning functions, which can be expressed by the conditional probability of observing a spike given any combination of independent variables. This probability can be estimated out of experimentally available data. By maximizing the mutual information between the probability distribution of the spike occurrence and that of the variables, the dependence of the spike on the input variables is maximized as well. We used this method to analyze the dependence of neuronal activity in cortical area MSTd on signals related to movement of the eye and retinal image movement.
Cross-Service Investigation of Geographical Information Systems
2004-03-01
Figure 8 illustrates the combined layers. Information for the layers is stored in a database format. The two types of storage are vector and...raster models. In a vector model, the image and information are stored as geometric objects such as points, lines, or polygons. In a raster model...DNCs are a vector -based digital database with selected maritime significant physical features from hydrographic charts. Layers within the DNC are data
NASA Astrophysics Data System (ADS)
Tuttle, S. E.; Salvucci, G.
2013-12-01
Validation of remotely sensed soil moisture is complicated by the difference in scale between remote sensing footprints and traditional ground-based soil moisture measurements. To address this issue, a new method was developed to evaluate the useful information content of remotely sensed soil moisture data using only large-scale precipitation (i.e. without modeling). Under statistically stationary conditions [Salvucci, 2001], precipitation conditionally averaged according to soil moisture (denoted E[P|S]) results in a sigmoidal shape in a manner that reflects the dependence of drainage, runoff, and evapotranspiration on soil moisture. However, errors in satellite measurement and algorithmic conversion of satellite data to soil moisture can degrade this relationship. Thus, remotely sensed soil moisture products can be assessed by the degree to which the natural sigmoidal relationship is preserved. The metric of mutual information was used as an error-dependent measure of the strength of the sigmoidal relationship, calculated from a two-dimensional histogram of soil moisture versus precipitation estimated using Gaussian mixture models. Three AMSR-E algorithms (VUA-NASA [Owe et al., 2001], NASA [Njoku et al., 2003], and U. Montana [Jones & Kimball, 2010]) were evaluated with the method for a nine-year period (2002-2011) over the contiguous United States at ¼° latitude-longitude resolution, using precipitation from the North American Land Data Assimilation System (NLDAS). The U. Montana product resulted in the highest mutual information for 57% of the region, followed by VUA-NASA and NASA at 40% and 3%, respectively. Areas where the U. Montana product yielded the maximum mutual information generally coincided with low vegetation biomass and flatter terrain, while the VUA-NASA product contained more useful information in more rugged and highly vegetated areas. Additionally, E[P|S] curves resulting from the Gaussian mixture method can potentially be decomposed into their conditional evapotranspiration and drainage plus runoff components using matrix factorization methods, allowing for time-averaged mapping of these fluxes over the study area.
Stochastic information transfer from cochlear implant electrodes to auditory nerve fibers
NASA Astrophysics Data System (ADS)
Gao, Xiao; Grayden, David B.; McDonnell, Mark D.
2014-08-01
Cochlear implants, also called bionic ears, are implanted neural prostheses that can restore lost human hearing function by direct electrical stimulation of auditory nerve fibers. Previously, an information-theoretic framework for numerically estimating the optimal number of electrodes in cochlear implants has been devised. This approach relies on a model of stochastic action potential generation and a discrete memoryless channel model of the interface between the array of electrodes and the auditory nerve fibers. Using these models, the stochastic information transfer from cochlear implant electrodes to auditory nerve fibers is estimated from the mutual information between channel inputs (the locations of electrodes) and channel outputs (the set of electrode-activated nerve fibers). Here we describe a revised model of the channel output in the framework that avoids the side effects caused by an "ambiguity state" in the original model and also makes fewer assumptions about perceptual processing in the brain. A detailed comparison of how different assumptions on fibers and current spread modes impact on the information transfer in the original model and in the revised model is presented. We also mathematically derive an upper bound on the mutual information in the revised model, which becomes tighter as the number of electrodes increases. We found that the revised model leads to a significantly larger maximum mutual information and corresponding number of electrodes compared with the original model and conclude that the assumptions made in this part of the modeling framework are crucial to the model's overall utility.
Benefit and cost curves for typical pollination mutualisms.
Morris, William F; Vázquez, Diego P; Chacoff, Natacha P
2010-05-01
Mutualisms provide benefits to interacting species, but they also involve costs. If costs come to exceed benefits as population density or the frequency of encounters between species increases, the interaction will no longer be mutualistic. Thus curves that represent benefits and costs as functions of interaction frequency are important tools for predicting when a mutualism will tip over into antagonism. Currently, most of what we know about benefit and cost curves in pollination mutualisms comes from highly specialized pollinating seed-consumer mutualisms, such as the yucca moth-yucca interaction. There, benefits to female reproduction saturate as the number of visits to a flower increases (because the amount of pollen needed to fertilize all the flower's ovules is finite), but costs continue to increase (because pollinator offspring consume developing seeds), leading to a peak in seed production at an intermediate number of visits. But for most plant-pollinator mutualisms, costs to the plant are more subtle than consumption of seeds, and how such costs scale with interaction frequency remains largely unknown. Here, we present reasonable benefit and cost curves that are appropriate for typical pollinator-plant interactions, and we show how they can result in a wide diversity of relationships between net benefit (benefit minus cost) and interaction frequency. We then use maximum-likelihood methods to fit net-benefit curves to measures of female reproductive success for three typical pollination mutualisms from two continents, and for each system we chose the most parsimonious model using information-criterion statistics. We discuss the implications of the shape of the net-benefit curve for the ecology and evolution of plant-pollinator mutualisms, as well as the challenges that lie ahead for disentangling the underlying benefit and cost curves for typical pollination mutualisms.
The Philosophy of Information as an Underlying and Unifying Theory of Information Science
ERIC Educational Resources Information Center
Tomic, Taeda
2010-01-01
Introduction: Philosophical analyses of theoretical principles underlying these sub-domains reveal philosophy of information as underlying meta-theory of information science. Method: Conceptual research on the knowledge sub-domains in information science and philosophy and analysis of their mutual connection. Analysis: Similarities between…
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NASA Astrophysics Data System (ADS)
Wang, Lijuan; Yan, Yong; Wang, Xue; Wang, Tao
2017-03-01
Input variable selection is an essential step in the development of data-driven models for environmental, biological and industrial applications. Through input variable selection to eliminate the irrelevant or redundant variables, a suitable subset of variables is identified as the input of a model. Meanwhile, through input variable selection the complexity of the model structure is simplified and the computational efficiency is improved. This paper describes the procedures of the input variable selection for the data-driven models for the measurement of liquid mass flowrate and gas volume fraction under two-phase flow conditions using Coriolis flowmeters. Three advanced input variable selection methods, including partial mutual information (PMI), genetic algorithm-artificial neural network (GA-ANN) and tree-based iterative input selection (IIS) are applied in this study. Typical data-driven models incorporating support vector machine (SVM) are established individually based on the input candidates resulting from the selection methods. The validity of the selection outcomes is assessed through an output performance comparison of the SVM based data-driven models and sensitivity analysis. The validation and analysis results suggest that the input variables selected from the PMI algorithm provide more effective information for the models to measure liquid mass flowrate while the IIS algorithm provides a fewer but more effective variables for the models to predict gas volume fraction.
An affine projection algorithm using grouping selection of input vectors
NASA Astrophysics Data System (ADS)
Shin, JaeWook; Kong, NamWoong; Park, PooGyeon
2011-10-01
This paper present an affine projection algorithm (APA) using grouping selection of input vectors. To improve the performance of conventional APA, the proposed algorithm adjusts the number of the input vectors using two procedures: grouping procedure and selection procedure. In grouping procedure, the some input vectors that have overlapping information for update is grouped using normalized inner product. Then, few input vectors that have enough information for for coefficient update is selected using steady-state mean square error (MSE) in selection procedure. Finally, the filter coefficients update using selected input vectors. The experimental results show that the proposed algorithm has small steady-state estimation errors comparing with the existing algorithms.
Iso-vector form factors of the delta and nucleon in QCD sum rules
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ozpineci, A.
Form factors are important non-perturbative properties of hadrons. They give information about the internal structure of the hadrons. In this work, iso-vector axial-vector and iso-vector tensor form factors of the nucleon and the iso-vector axial-vector {Delta}{yields}N transition form factor calculations in QCD Sum Rules are presented.
>From naive to sophisticated behavior in multiagents-based financial market models
NASA Astrophysics Data System (ADS)
Mansilla, R.
2000-09-01
The behavior of physical complexity and mutual information function of the outcome of a model of heterogeneous, inductive rational agents inspired by the El Farol Bar problem and the Minority Game is studied. The first magnitude is a measure rooted in the Kolmogorov-Chaitin theory and the second a measure related to Shannon's information entropy. Extensive computer simulations were done, as a result of which, is proposed an ansatz for physical complexity of the type C(l)=lα and the dependence of the exponent α from the parameters of the model is established. The accuracy of our results and the relationship with the behavior of mutual information function as a measure of time correlation of agents choice are discussed.
Vaxvec: The first web-based recombinant vaccine vector database and its data analysis.
Deng, Shunzhou; Martin, Carly; Patil, Rasika; Zhu, Felix; Zhao, Bin; Xiang, Zuoshuang; He, Yongqun
2015-11-27
A recombinant vector vaccine uses an attenuated virus, bacterium, or parasite as the carrier to express a heterologous antigen(s). Many recombinant vaccine vectors and related vaccines have been developed and extensively investigated. To compare and better understand recombinant vectors and vaccines, we have generated Vaxvec (http://www.violinet.org/vaxvec), the first web-based database that stores various recombinant vaccine vectors and those experimentally verified vaccines that use these vectors. Vaxvec has now included 59 vaccine vectors that have been used in 196 recombinant vector vaccines against 66 pathogens and cancers. These vectors are classified to 41 viral vectors, 15 bacterial vectors, 1 parasitic vector, and 1 fungal vector. The most commonly used viral vaccine vectors are double-stranded DNA viruses, including herpesviruses, adenoviruses, and poxviruses. For example, Vaxvec includes 63 poxvirus-based recombinant vaccines for over 20 pathogens and cancers. Vaxvec collects 30 recombinant vector influenza vaccines that use 17 recombinant vectors and were experimentally tested in 7 animal models. In addition, over 60 protective antigens used in recombinant vector vaccines are annotated and analyzed. User-friendly web-interfaces are available for querying various data in Vaxvec. To support data exchange, the information of vaccine vectors, vaccines, and related information is stored in the Vaccine Ontology (VO). Vaxvec is a timely and vital source of vaccine vector database and facilitates efficient vaccine vector research and development. Copyright © 2015 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Snyder
1998-04-01
It has been shown by Einstein, Podolsky, and Rosen that in quantum mechanics two different wave functions can simultaneously characterize the same physical existent. This result means that one can make predictions regarding simultaneous, mutually exclusive features of a physical existent. It is important to ask whether people have the capacity to make observations of mutually exclusive phenomena simultaneously? Our everyday experience informs us that a human observer is capable of observing only one set of physical circumstances at a time. Evidence from psychology, though, indicates that people indeed have the capacity to make observations of mutually exclusive phenomena simultaneously, even though this capacity is not generally recognized. Working independently, Sigmund Freud and William James provided some of this evidence. How the nature of the quantum mechanical wave function is associated with the problem posed by Einstein, Podolsky, and Rosen, is addressed at the end of the paper.
Send-side matching of data communications messages
Archer, Charles J.; Blocksome, Michael A.; Ratterman, Joseph D.; Smith, Brian E.
2014-07-01
Send-side matching of data communications messages includes a plurality of compute nodes organized for collective operations, including: issuing by a receiving node to source nodes a receive message that specifies receipt of a single message to be sent from any source node, the receive message including message matching information, a specification of a hardware-level mutual exclusion device, and an identification of a receive buffer; matching by two or more of the source nodes the receive message with pending send messages in the two or more source nodes; operating by one of the source nodes having a matching send message the mutual exclusion device, excluding messages from other source nodes with matching send messages and identifying to the receiving node the source node operating the mutual exclusion device; and sending to the receiving node from the source node operating the mutual exclusion device a matched pending message.
Send-side matching of data communications messages
Archer, Charles J.; Blocksome, Michael A.; Ratterman, Joseph D.; Smith, Brian E.
2014-06-17
Send-side matching of data communications messages in a distributed computing system comprising a plurality of compute nodes, including: issuing by a receiving node to source nodes a receive message that specifies receipt of a single message to be sent from any source node, the receive message including message matching information, a specification of a hardware-level mutual exclusion device, and an identification of a receive buffer; matching by two or more of the source nodes the receive message with pending send messages in the two or more source nodes; operating by one of the source nodes having a matching send message the mutual exclusion device, excluding messages from other source nodes with matching send messages and identifying to the receiving node the source node operating the mutual exclusion device; and sending to the receiving node from the source node operating the mutual exclusion device a matched pending message.
Semi-automatic feedback using concurrence between mixture vectors for general databases
NASA Astrophysics Data System (ADS)
Larabi, Mohamed-Chaker; Richard, Noel; Colot, Olivier; Fernandez-Maloigne, Christine
2001-12-01
This paper describes how a query system can exploit the basic knowledge by employing semi-automatic relevance feedback to refine queries and runtimes. For general databases, it is often useless to call complex attributes, because we have not sufficient information about images in the database. Moreover, these images can be topologically very different from one to each other and an attribute that is powerful for a database category may be very powerless for the other categories. The idea is to use very simple features, such as color histogram, correlograms, Color Coherence Vectors (CCV), to fill out the signature vector. Then, a number of mixture vectors is prepared depending on the number of very distinctive categories in the database. Knowing that a mixture vector is a vector containing the weight of each attribute that will be used to compute a similarity distance. We post a query in the database using successively all the mixture vectors defined previously. We retain then the N first images for each vector in order to make a mapping using the following information: Is image I present in several mixture vectors results? What is its rank in the results? These informations allow us to switch the system on an unsupervised relevance feedback or user's feedback (supervised feedback).
48 CFR 952.204-72 - Disclosure of information.
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2013-10-01
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48 CFR 952.204-72 - Disclosure of information.
Code of Federal Regulations, 2014 CFR
2014-10-01
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48 CFR 952.204-72 - Disclosure of information.
Code of Federal Regulations, 2012 CFR
2012-10-01
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Redundant imprinting of information in nonideal environments: Objective reality via a noisy channel
NASA Astrophysics Data System (ADS)
Zwolak, Michael; Quan, H. T.; Zurek, Wojciech H.
2010-06-01
Quantum Darwinism provides an information-theoretic framework for the emergence of the objective, classical world from the quantum substrate. The key to this emergence is the proliferation of redundant information throughout the environment where observers can then intercept it. We study this process for a purely decohering interaction when the environment, E, is in a nonideal (e.g., mixed) initial state. In the case of good decoherence, that is, after the pointer states have been unambiguously selected, the mutual information between the system, S, and an environment fragment, F, is given solely by F’s entropy increase. This demonstrates that the environment’s capacity for recording the state of S is directly related to its ability to increase its entropy. Environments that remain nearly invariant under the interaction with S, either because they have a large initial entropy or a misaligned initial state, therefore have a diminished ability to acquire information. To elucidate the concept of good decoherence, we show that, when decoherence is not complete, the deviation of the mutual information from F’s entropy change is quantified by the quantum discord, i.e., the excess mutual information between S and F is information regarding the initial coherence between pointer states of S. In addition to illustrating these results with a single-qubit system interacting with a multiqubit environment, we find scaling relations for the redundancy of information acquired by the environment that display a universal behavior independent of the initial state of S. Our results demonstrate that Quantum Darwinism is robust with respect to nonideal initial states of the environment: the environment almost always acquires redundant information about the system but its rate of acquisition can be reduced.
Fluctuation sensitivity of a transcriptional signaling cascade
NASA Astrophysics Data System (ADS)
Pilkiewicz, Kevin R.; Mayo, Michael L.
2016-09-01
The internal biochemical state of a cell is regulated by a vast transcriptional network that kinetically correlates the concentrations of numerous proteins. Fluctuations in protein concentration that encode crucial information about this changing state must compete with fluctuations caused by the noisy cellular environment in order to successfully transmit information across the network. Oftentimes, one protein must regulate another through a sequence of intermediaries, and conventional wisdom, derived from the data processing inequality of information theory, leads us to expect that longer sequences should lose more information to noise. Using the metric of mutual information to characterize the fluctuation sensitivity of transcriptional signaling cascades, we find, counter to this expectation, that longer chains of regulatory interactions can instead lead to enhanced informational efficiency. We derive an analytic expression for the mutual information from a generalized chemical kinetics model that we reduce to simple, mass-action kinetics by linearizing for small fluctuations about the basal biological steady state, and we find that at long times this expression depends only on a simple ratio of protein production to destruction rates and the length of the cascade. We place bounds on the values of these parameters by requiring that the mutual information be at least one bit—otherwise, any received signal would be indistinguishable from noise—and we find not only that nature has devised a way to circumvent the data processing inequality, but that it must be circumvented to attain this one-bit threshold. We demonstrate how this result places informational and biochemical efficiency at odds with one another by correlating high transcription factor binding affinities with low informational output, and we conclude with an analysis of the validity of our assumptions and propose how they might be tested experimentally.
Lu, Songjian; Lu, Kevin N.; Cheng, Shi-Yuan; Hu, Bo; Ma, Xiaojun; Nystrom, Nicholas; Lu, Xinghua
2015-01-01
An important goal of cancer genomic research is to identify the driving pathways underlying disease mechanisms and the heterogeneity of cancers. It is well known that somatic genome alterations (SGAs) affecting the genes that encode the proteins within a common signaling pathway exhibit mutual exclusivity, in which these SGAs usually do not co-occur in a tumor. With some success, this characteristic has been utilized as an objective function to guide the search for driver mutations within a pathway. However, mutual exclusivity alone is not sufficient to indicate that genes affected by such SGAs are in common pathways. Here, we propose a novel, signal-oriented framework for identifying driver SGAs. First, we identify the perturbed cellular signals by mining the gene expression data. Next, we search for a set of SGA events that carries strong information with respect to such perturbed signals while exhibiting mutual exclusivity. Finally, we design and implement an efficient exact algorithm to solve an NP-hard problem encountered in our approach. We apply this framework to the ovarian and glioblastoma tumor data available at the TCGA database, and perform systematic evaluations. Our results indicate that the signal-oriented approach enhances the ability to find informative sets of driver SGAs that likely constitute signaling pathways. PMID:26317392
Automatic detection of atrial fibrillation in cardiac vibration signals.
Brueser, C; Diesel, J; Zink, M D H; Winter, S; Schauerte, P; Leonhardt, S
2013-01-01
We present a study on the feasibility of the automatic detection of atrial fibrillation (AF) from cardiac vibration signals (ballistocardiograms/BCGs) recorded by unobtrusive bedmounted sensors. The proposed system is intended as a screening and monitoring tool in home-healthcare applications and not as a replacement for ECG-based methods used in clinical environments. Based on BCG data recorded in a study with 10 AF patients, we evaluate and rank seven popular machine learning algorithms (naive Bayes, linear and quadratic discriminant analysis, support vector machines, random forests as well as bagged and boosted trees) for their performance in separating 30 s long BCG epochs into one of three classes: sinus rhythm, atrial fibrillation, and artifact. For each algorithm, feature subsets of a set of statistical time-frequency-domain and time-domain features were selected based on the mutual information between features and class labels as well as first- and second-order interactions among features. The classifiers were evaluated on a set of 856 epochs by means of 10-fold cross-validation. The best algorithm (random forests) achieved a Matthews correlation coefficient, mean sensitivity, and mean specificity of 0.921, 0.938, and 0.982, respectively.
Comparison of six methods for the detection of causality in a bivariate time series
NASA Astrophysics Data System (ADS)
Krakovská, Anna; Jakubík, Jozef; Chvosteková, Martina; Coufal, David; Jajcay, Nikola; Paluš, Milan
2018-04-01
In this comparative study, six causality detection methods were compared, namely, the Granger vector autoregressive test, the extended Granger test, the kernel version of the Granger test, the conditional mutual information (transfer entropy), the evaluation of cross mappings between state spaces, and an assessment of predictability improvement due to the use of mixed predictions. Seven test data sets were analyzed: linear coupling of autoregressive models, a unidirectional connection of two Hénon systems, a unidirectional connection of chaotic systems of Rössler and Lorenz type and of two different Rössler systems, an example of bidirectionally connected two-species systems, a fishery model as an example of two correlated observables without a causal relationship, and an example of mediated causality. We tested not only 20 000 points long clean time series but also noisy and short variants of the data. The standard and the extended Granger tests worked only for the autoregressive models. The remaining methods were more successful with the more complex test examples, although they differed considerably in their capability to reveal the presence and the direction of coupling and to distinguish causality from mere correlation.
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2013-05-16
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NASA Astrophysics Data System (ADS)
Diamant, Idit; Shalhon, Moran; Goldberger, Jacob; Greenspan, Hayit
2016-03-01
Classification of clustered breast microcalcifications into benign and malignant categories is an extremely challenging task for computerized algorithms and expert radiologists alike. In this paper we present a novel method for feature selection based on mutual information (MI) criterion for automatic classification of microcalcifications. We explored the MI based feature selection for various texture features. The proposed method was evaluated on a standardized digital database for screening mammography (DDSM). Experimental results demonstrate the effectiveness and the advantage of using the MI-based feature selection to obtain the most relevant features for the task and thus to provide for improved performance as compared to using all features.
Quantifying Complexity in Quantum Phase Transitions via Mutual Information Complex Networks
NASA Astrophysics Data System (ADS)
Valdez, Marc Andrew; Jaschke, Daniel; Vargas, David L.; Carr, Lincoln D.
2017-12-01
We quantify the emergent complexity of quantum states near quantum critical points on regular 1D lattices, via complex network measures based on quantum mutual information as the adjacency matrix, in direct analogy to quantifying the complexity of electroencephalogram or functional magnetic resonance imaging measurements of the brain. Using matrix product state methods, we show that network density, clustering, disparity, and Pearson's correlation obtain the critical point for both quantum Ising and Bose-Hubbard models to a high degree of accuracy in finite-size scaling for three classes of quantum phase transitions, Z2, mean field superfluid to Mott insulator, and a Berzinskii-Kosterlitz-Thouless crossover.
Timing the state of light with anomalous dispersion and a gradient echo memory
NASA Astrophysics Data System (ADS)
Clark, Jeremy B.
We study the effects of anomalous dispersion on the continuous-variable entanglement of EPR states (generated using four-wave mixing in 85 Rb) by sending one part of the state through a fast-light medium and measuring the state's quantum mutual information. We observe an advance in the maximum of the quantum mutual information between modes. In contrast, due to uncorrelated noise added by a small phase-insensitive gain, we do not observe any statistically significant advance in the leading edge of the mutual information. We also study the storage and retrieval of multiplexed optical signals in a Gradient Echo Memory (GEM) at relevant four-wave mixing frequencies in 85Rb. Temporal multiplexing capabilities are demonstrated by storing multiple classical images in the memory simultaneously and observing the expected first-in last-out order of recall without obvious cross-talk. We also develop a technique wherein selected portions of an image written into the memory can be spatially targeted for readout and erasure on demand. The effect of diffusion on the quality of the recalled images is characterized. Our results indicate that Raman-based atomic memories may serve as a flexible platform for the storage and retrieval of multiplexed optical signals.
Wang, Jianxin; Chen, Bo; Wang, Yaqun; Wang, Ningtao; Garbey, Marc; Tran-Son-Tay, Roger; Berceli, Scott A.; Wu, Rongling
2013-01-01
The capacity of an organism to respond to its environment is facilitated by the environmentally induced alteration of gene and protein expression, i.e. expression plasticity. The reconstruction of gene regulatory networks based on expression plasticity can gain not only new insights into the causality of transcriptional and cellular processes but also the complex regulatory mechanisms that underlie biological function and adaptation. We describe an approach for network inference by integrating expression plasticity into Shannon’s mutual information. Beyond Pearson correlation, mutual information can capture non-linear dependencies and topology sparseness. The approach measures the network of dependencies of genes expressed in different environments, allowing the environment-induced plasticity of gene dependencies to be tested in unprecedented details. The approach is also able to characterize the extent to which the same genes trigger different amounts of expression in response to environmental changes. We demonstrated the usefulness of this approach through analysing gene expression data from a rabbit vein graft study that includes two distinct blood flow environments. The proposed approach provides a powerful tool for the modelling and analysis of dynamic regulatory networks using gene expression data from distinct environments. PMID:23470995
Escudero, Javier; Hornero, Roberto; Abásolo, Daniel
2009-02-01
The mutual information (MI) is a measure of both linear and nonlinear dependences. It can be applied to a time series and a time-delayed version of the same sequence to compute the auto-mutual information function (AMIF). Moreover, the AMIF rate of decrease (AMIFRD) with increasing time delay in a signal is correlated with its entropy and has been used to characterize biomedical data. In this paper, we aimed at gaining insight into the dependence of the AMIFRD on several signal processing concepts and at illustrating its application to biomedical time series analysis. Thus, we have analysed a set of synthetic sequences with the AMIFRD. The results show that the AMIF decreases more quickly as bandwidth increases and that the AMIFRD becomes more negative as there is more white noise contaminating the time series. Additionally, this metric detected changes in the nonlinear dynamics of a signal. Finally, in order to illustrate the analysis of real biomedical signals with the AMIFRD, this metric was applied to electroencephalogram (EEG) signals acquired with eyes open and closed and to ictal and non-ictal intracranial EEG recordings.
NASA Astrophysics Data System (ADS)
DSouza, Adora M.; Abidin, Anas Z.; Chockanathan, Udaysankar; Wismüller, Axel
2018-03-01
In this study, we investigate whether there are discernable changes in influence that brain regions have on themselves once patients show symptoms of HIV Associated Neurocognitive Disorder (HAND) using functional MRI (fMRI). Simple functional connectivity measures, such as correlation cannot reveal such information. To this end, we use mutual connectivity analysis (MCA) with Local Models (LM), which reveals a measure of influence in terms of predictability. Once such measures of interaction are obtained, we train two classifiers to characterize difference in patterns of regional self-influence between healthy subjects and subjects presenting with HAND symptoms. The two classifiers we use are Support Vector Machines (SVM) and Localized Generalized Matrix Learning Vector Quantization (LGMLVQ). Performing machine learning on fMRI connectivity measures is popularly known as multi-voxel pattern analysis (MVPA). By performing such an analysis, we are interested in studying the impact HIV infection has on an individual's brain. The high area under receiver operating curve (AUC) and accuracy values for 100 different train/test separations using MCA-LM self-influence measures (SVM: mean AUC=0.86, LGMLVQ: mean AUC=0.88, SVM and LGMLVQ: mean accuracy=0.78) compared with standard MVPA analysis using cross-correlation between fMRI time-series (SVM: mean AUC=0.58, LGMLVQ: mean AUC=0.57), demonstrates that self-influence features can be more discriminative than measures of interaction between time-series pairs. Furthermore, our results suggest that incorporating measures of self-influence in MVPA analysis used commonly in fMRI analysis has the potential to provide a performance boost and indicate important changes in dynamics of regions in the brain as a consequence of HIV infection.
Rényi squashed entanglement, discord, and relative entropy differences
NASA Astrophysics Data System (ADS)
Seshadreesan, Kaushik P.; Berta, Mario; Wilde, Mark M.
2015-10-01
The squashed entanglement quantifies the amount of entanglement in a bipartite quantum state, and it satisfies all of the axioms desired for an entanglement measure. The quantum discord is a measure of quantum correlations that are different from those due to entanglement. What these two measures have in common is that they are both based upon the conditional quantum mutual information. In Berta et al (2015 J. Math. Phys. 56 022205), we recently proposed Rényi generalizations of the conditional quantum mutual information of a tripartite state on ABC (with C being the conditioning system), which were shown to satisfy some properties that hold for the original quantity, such as non-negativity, duality, and monotonicity with respect to local operations on the system B (with it being left open to show that the Rényi quantity is monotone with respect to local operations on system A). Here we define a Rényi squashed entanglement and a Rényi quantum discord based on a Rényi conditional quantum mutual information and investigate these quantities in detail. Taking as a conjecture that the Rényi conditional quantum mutual information is monotone with respect to local operations on both systems A and B, we prove that the Rényi squashed entanglement and the Rényi quantum discord satisfy many of the properties of the respective original von Neumann entropy based quantities. In our prior work (Berta et al 2015 Phys. Rev. A 91 022333), we also detailed a procedure to obtain Rényi generalizations of any quantum information measure that is equal to a linear combination of von Neumann entropies with coefficients chosen from the set \\{-1,0,1\\}. Here, we extend this procedure to include differences of relative entropies. Using the extended procedure and a conjectured monotonicity of the Rényi generalizations in the Rényi parameter, we discuss potential remainder terms for well known inequalities such as monotonicity of the relative entropy, joint convexity of the relative entropy, and the Holevo bound.
Mutual information estimation for irregularly sampled time series
NASA Astrophysics Data System (ADS)
Rehfeld, K.; Marwan, N.; Heitzig, J.; Kurths, J.
2012-04-01
For the automated, objective and joint analysis of time series, similarity measures are crucial. Used in the analysis of climate records, they allow for a complimentary, unbiased view onto sparse datasets. The irregular sampling of many of these time series, however, makes it necessary to either perform signal reconstruction (e.g. interpolation) or to develop and use adapted measures. Standard linear interpolation comes with an inevitable loss of information and bias effects. We have recently developed a Gaussian kernel-based correlation algorithm with which the interpolation error can be substantially lowered, but this would not work should the functional relationship in a bivariate setting be non-linear. We therefore propose an algorithm to estimate lagged auto and cross mutual information from irregularly sampled time series. We have extended the standard and adaptive binning histogram estimators and use Gaussian distributed weights in the estimation of the (joint) probabilities. To test our method we have simulated linear and nonlinear auto-regressive processes with Gamma-distributed inter-sampling intervals. We have then performed a sensitivity analysis for the estimation of actual coupling length, the lag of coupling and the decorrelation time in the synthetic time series and contrast our results to the performance of a signal reconstruction scheme. Finally we applied our estimator to speleothem records. We compare the estimated memory (or decorrelation time) to that from a least-squares estimator based on fitting an auto-regressive process of order 1. The calculated (cross) mutual information results are compared for the different estimators (standard or adaptive binning) and contrasted with results from signal reconstruction. We find that the kernel-based estimator has a significantly lower root mean square error and less systematic sampling bias than the interpolation-based method. It is possible that these encouraging results could be further improved by using non-histogram mutual information estimators, like k-Nearest Neighbor or Kernel-Density estimators, but for short (<1000 points) and irregularly sampled datasets the proposed algorithm is already a great improvement.
Margin based ontology sparse vector learning algorithm and applied in biology science.
Gao, Wei; Qudair Baig, Abdul; Ali, Haidar; Sajjad, Wasim; Reza Farahani, Mohammad
2017-01-01
In biology field, the ontology application relates to a large amount of genetic information and chemical information of molecular structure, which makes knowledge of ontology concepts convey much information. Therefore, in mathematical notation, the dimension of vector which corresponds to the ontology concept is often very large, and thus improves the higher requirements of ontology algorithm. Under this background, we consider the designing of ontology sparse vector algorithm and application in biology. In this paper, using knowledge of marginal likelihood and marginal distribution, the optimized strategy of marginal based ontology sparse vector learning algorithm is presented. Finally, the new algorithm is applied to gene ontology and plant ontology to verify its efficiency.
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Finding Useful Questions: On Bayesian Diagnosticity, Probability, Impact, and Information Gain
ERIC Educational Resources Information Center
Nelson, Jonathan D.
2005-01-01
Several norms for how people should assess a question's usefulness have been proposed, notably Bayesian diagnosticity, information gain (mutual information), Kullback-Liebler distance, probability gain (error minimization), and impact (absolute change). Several probabilistic models of previous experiments on categorization, covariation assessment,…
Optimal averaging of soil moisture predictions from ensemble land surface model simulations
USDA-ARS?s Scientific Manuscript database
The correct interpretation of ensemble information obtained from the parallel implementation of multiple land surface models (LSMs) requires information concerning the LSM ensemble’s mutual error covariance. Here we propose a new technique for obtaining such information using an instrumental variabl...
GeneGuard: A modular plasmid system designed for biosafety.
Wright, Oliver; Delmans, Mihails; Stan, Guy-Bart; Ellis, Tom
2015-03-20
Synthetic biology applications in biosensing, bioremediation, and biomining envision the use of engineered microbes beyond a contained laboratory. Deployment of such microbes in the environment raises concerns of unchecked cellular proliferation or unwanted spread of synthetic genes. While antibiotic-resistant plasmids are the most utilized vectors for introducing synthetic genes into bacteria, they are also inherently insecure, acting naturally to propagate DNA from one cell to another. To introduce security into bacterial synthetic biology, we here took on the task of completely reformatting plasmids to be dependent on their intended host strain and inherently disadvantageous for others. Using conditional origins of replication, rich-media compatible auxotrophies, and toxin-antitoxin pairs we constructed a mutually dependent host-plasmid platform, called GeneGuard. In this, replication initiators for the R6K or ColE2-P9 origins are provided in trans by a specified host, whose essential thyA or dapA gene is translocated from a genomic to a plasmid location. This reciprocal arrangement is stable for at least 100 generations without antibiotic selection and is compatible for use in LB medium and soil. Toxin genes ζ or Kid are also employed in an auxiliary manner to make the vector disadvantageous for strains not expressing their antitoxins. These devices, in isolation and in concert, severely reduce unintentional plasmid propagation in E. coli and B. subtilis and do not disrupt the intended E. coli host's growth dynamics. Our GeneGuard system comprises several versions of modular cargo-ready vectors, along with their requisite genomic integration cassettes, and is demonstrated here as an efficient vector for heavy-metal biosensors.
Whitmore, Rebecca; Crooks, Valorie A; Snyder, Jeremy
2015-09-01
This study examines the experiences of informal caregivers in medical tourism through an ethics of care lens. We conducted semi-structured interviews with 20 Canadians who had accompanied their friends or family members abroad for surgery, asking questions that dealt with their experiences prior to, during and after travel. Thematic analysis revealed three themes central to an ethics of care: responsibility, vulnerability and mutuality. Ethics of care theorists have highlighted how care has been historically devalued. We posit that medical tourism reproduces dominant narratives about care in a novel care landscape. Informal care goes unaccounted for by the industry, as it occurs in largely private spaces at a geographic distance from the home countries of medical tourists. Copyright © 2015 Elsevier Ltd. All rights reserved.
Sagna, O; Seck, I; Dia, A T; Sall, F L; Diouf, S; Mendy, J; Ka, O; Kassoka, B
2016-08-01
In Senegal, the informal and rural sector that accounts for over 80% of the population is covered only up to 7% by a health insurance system. That is why, for the implementation of development strategy of the universal health coverage (UHC) through mutual health insurance providers, the Government of Senegal has focused on this sector. The objective of this study was to assess the consumer's preference on the UHC development strategies through mutual health insurance providers. This was a qualitative and exploratory study based on a literature review, and indepth interview with the heads of households. It was also based on focus groups of people with and without health mutual membership, and the Expert Committee meetings. The results showed that the most critical attributes in the decision-making of consumers to join the health mutual in Ziguinchor were the membership units; the content of the benefit package, the payment modalities of the premium, the premium amount, the availability of transportation, the co-payment level, convention arrangement with health facilities, and health mutual governance. For a successful implementation of the UHC development strategy through health mutual organizations, policymakers should explore the possibility of introducing the modality of payment in kind, the revision of the co-payment amount, and the promotion of equity through the introduction of a differentiated premium contribution by income. They should also establish a crossborder strategy with The Gambia and Guinea-Bissau to improve health care access to people living in the borders. The promotion of innovative funding and risk equalization between health insurance schemes is also recommended. In areas where the microfinance institutions are well organized and structured their substitution to health mutuals should be an option the decision-makers have to explore.
Vector assembly of colloids on monolayer substrates
NASA Astrophysics Data System (ADS)
Jiang, Lingxiang; Yang, Shenyu; Tsang, Boyce; Tu, Mei; Granick, Steve
2017-06-01
The key to spontaneous and directed assembly is to encode the desired assembly information to building blocks in a programmable and efficient way. In computer graphics, raster graphics encodes images on a single-pixel level, conferring fine details at the expense of large file sizes, whereas vector graphics encrypts shape information into vectors that allow small file sizes and operational transformations. Here, we adapt this raster/vector concept to a 2D colloidal system and realize `vector assembly' by manipulating particles on a colloidal monolayer substrate with optical tweezers. In contrast to raster assembly that assigns optical tweezers to each particle, vector assembly requires a minimal number of optical tweezers that allow operations like chain elongation and shortening. This vector approach enables simple uniform particles to form a vast collection of colloidal arenes and colloidenes, the spontaneous dissociation of which is achieved with precision and stage-by-stage complexity by simply removing the optical tweezers.
New Term Weighting Formulas for the Vector Space Method in Information Retrieval
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chisholm, E.; Kolda, T.G.
The goal in information retrieval is to enable users to automatically and accurately find data relevant to their queries. One possible approach to this problem i use the vector space model, which models documents and queries as vectors in the term space. The components of the vectors are determined by the term weighting scheme, a function of the frequencies of the terms in the document or query as well as throughout the collection. We discuss popular term weighting schemes and present several new schemes that offer improved performance.
Reliable estimation of orbit errors in spaceborne SAR interferometry. The network approach
NASA Astrophysics Data System (ADS)
Bähr, Hermann; Hanssen, Ramon F.
2012-12-01
An approach to improve orbital state vectors by orbit error estimates derived from residual phase patterns in synthetic aperture radar interferograms is presented. For individual interferograms, an error representation by two parameters is motivated: the baseline error in cross-range and the rate of change of the baseline error in range. For their estimation, two alternatives are proposed: a least squares approach that requires prior unwrapping and a less reliable gridsearch method handling the wrapped phase. In both cases, reliability is enhanced by mutual control of error estimates in an overdetermined network of linearly dependent interferometric combinations of images. Thus, systematic biases, e.g., due to unwrapping errors, can be detected and iteratively eliminated. Regularising the solution by a minimum-norm condition results in quasi-absolute orbit errors that refer to particular images. For the 31 images of a sample ENVISAT dataset, orbit corrections with a mutual consistency on the millimetre level have been inferred from 163 interferograms. The method itself qualifies by reliability and rigorous geometric modelling of the orbital error signal but does not consider interfering large scale deformation effects. However, a separation may be feasible in a combined processing with persistent scatterer approaches or by temporal filtering of the estimates.
NASA Astrophysics Data System (ADS)
Baltz, Anthony J.
2002-10-01
Theoretical predictions for a number of electromagnetically induced reactions have been compared with available ultrarelativistic heavy ion data. Calculations for three atomic process have been confronted with CERN SPS data. Theoretically predicted rates are in good agreement with data[1] for bound-electron positron pairs and ionization of single electron heavy ions. Furthermore, the exact solution of the semi-classical Dirac equation in the ultrarelativistic limit reproduces the perturbative scaling result seen in data[2] for continuum pairs (i.e. cross sections go as Z_1^2 Z_2^2). In the area of electromagnetically induced nuclear and hadronic physics, mutual Coulomb dissociation predictions are in good agreement with RHIC Zero Degree Calorimeter measurements[3], and calculations of coherent vector meson production accompanied by mutual Coulomb dissociation[4] are in good agreement with RHIC STAR data[5]. [1] H. F. Krause et al., Phys. Rev. Lett., 80, 1190 (1998). [2] C. R. Vane et al., Phys. Rev. A 56, 3682 (1997). [3] Mickey Chiu et al., Phys. Rev. Lett. 89, 012302 (2002). [4] Anthony J. Baltz, Spencer R. Klein, and Joakim Nystrand, Phys. Rev. Lett. 89, 012301 (2002). [5] C. Adler et al., STAR Collaboration, arXiv:nucl-ex/206004.
Non-Mutually Exclusive Deep Neural Network Classifier for Combined Modes of Bearing Fault Diagnosis
Kim, Jong-Myon
2018-01-01
The simultaneous occurrence of various types of defects in bearings makes their diagnosis more challenging owing to the resultant complexity of the constituent parts of the acoustic emission (AE) signals. To address this issue, a new approach is proposed in this paper for the detection of multiple combined faults in bearings. The proposed methodology uses a deep neural network (DNN) architecture to effectively diagnose the combined defects. The DNN structure is based on the stacked denoising autoencoder non-mutually exclusive classifier (NMEC) method for combined modes. The NMEC-DNN is trained using data for a single fault and it classifies both single faults and multiple combined faults. The results of experiments conducted on AE data collected through an experimental test-bed demonstrate that the DNN achieves good classification performance with a maximum accuracy of 95%. The proposed method is compared with a multi-class classifier based on support vector machines (SVMs). The NMEC-DNN yields better diagnostic performance in comparison to the multi-class classifier based on SVM. The NMEC-DNN reduces the number of necessary data collections and improves the bearing fault diagnosis performance. PMID:29642466
Prostate Cancer Rates by Race and Ethnicity
... P25–1130). For more information, see the USCS technical notes. † Race categories are not mutually exclusive from ... with caution. For more information, see the USCS technical notes. ¶ Data are compiled from cancer registries that ...
2010-01-01
Background Mosquitoes are important vectors of diseases but, in spite of various mosquito faunistic surveys globally, there is a need for a spatial online database of mosquito collection data and distribution summaries. Such a resource could provide entomologists with the results of previous mosquito surveys, and vector disease control workers, preventative medicine practitioners, and health planners with information relating mosquito distribution to vector-borne disease risk. Results A web application called MosquitoMap was constructed comprising mosquito collection point data stored in an ArcGIS 9.3 Server/SQL geodatabase that includes administrative area and vector species x country lookup tables. In addition to the layer containing mosquito collection points, other map layers were made available including environmental, and vector and pathogen/disease distribution layers. An application within MosquitoMap called the Mal-area calculator (MAC) was constructed to quantify the area of overlap, for any area of interest, of vector, human, and disease distribution models. Data standards for mosquito records were developed for MosquitoMap. Conclusion MosquitoMap is a public domain web resource that maps and compares georeferenced mosquito collection points to other spatial information, in a geographical information system setting. The MAC quantifies the Mal-area, i.e. the area where it is theoretically possible for vector-borne disease transmission to occur, thus providing a useful decision tool where other disease information is limited. The Mal-area approach emphasizes the independent but cumulative contribution to disease risk of the vector species predicted present. MosquitoMap adds value to, and makes accessible, the results of past collecting efforts, as well as providing a template for other arthropod spatial databases. PMID:20167090
Foley, Desmond H; Wilkerson, Richard C; Birney, Ian; Harrison, Stanley; Christensen, Jamie; Rueda, Leopoldo M
2010-02-18
Mosquitoes are important vectors of diseases but, in spite of various mosquito faunistic surveys globally, there is a need for a spatial online database of mosquito collection data and distribution summaries. Such a resource could provide entomologists with the results of previous mosquito surveys, and vector disease control workers, preventative medicine practitioners, and health planners with information relating mosquito distribution to vector-borne disease risk. A web application called MosquitoMap was constructed comprising mosquito collection point data stored in an ArcGIS 9.3 Server/SQL geodatabase that includes administrative area and vector species x country lookup tables. In addition to the layer containing mosquito collection points, other map layers were made available including environmental, and vector and pathogen/disease distribution layers. An application within MosquitoMap called the Mal-area calculator (MAC) was constructed to quantify the area of overlap, for any area of interest, of vector, human, and disease distribution models. Data standards for mosquito records were developed for MosquitoMap. MosquitoMap is a public domain web resource that maps and compares georeferenced mosquito collection points to other spatial information, in a geographical information system setting. The MAC quantifies the Mal-area, i.e. the area where it is theoretically possible for vector-borne disease transmission to occur, thus providing a useful decision tool where other disease information is limited. The Mal-area approach emphasizes the independent but cumulative contribution to disease risk of the vector species predicted present. MosquitoMap adds value to, and makes accessible, the results of past collecting efforts, as well as providing a template for other arthropod spatial databases.
Multisource image fusion method using support value transform.
Zheng, Sheng; Shi, Wen-Zhong; Liu, Jian; Zhu, Guang-Xi; Tian, Jin-Wen
2007-07-01
With the development of numerous imaging sensors, many images can be simultaneously pictured by various sensors. However, there are many scenarios where no one sensor can give the complete picture. Image fusion is an important approach to solve this problem and produces a single image which preserves all relevant information from a set of different sensors. In this paper, we proposed a new image fusion method using the support value transform, which uses the support value to represent the salient features of image. This is based on the fact that, in support vector machines (SVMs), the data with larger support values have a physical meaning in the sense that they reveal relative more importance of the data points for contributing to the SVM model. The mapped least squares SVM (mapped LS-SVM) is used to efficiently compute the support values of image. The support value analysis is developed by using a series of multiscale support value filters, which are obtained by filling zeros in the basic support value filter deduced from the mapped LS-SVM to match the resolution of the desired level. Compared with the widely used image fusion methods, such as the Laplacian pyramid, discrete wavelet transform methods, the proposed method is an undecimated transform-based approach. The fusion experiments are undertaken on multisource images. The results demonstrate that the proposed approach is effective and is superior to the conventional image fusion methods in terms of the pertained quantitative fusion evaluation indexes, such as quality of visual information (Q(AB/F)), the mutual information, etc.
21 CFR 26.19 - Information relating to quality aspects.
Code of Federal Regulations, 2013 CFR
2013-04-01
... 21 Food and Drugs 1 2013-04-01 2013-04-01 false Information relating to quality aspects. 26.19... relating to quality aspects. The authorities will establish an appropriate means of exchanging information... MUTUAL RECOGNITION OF PHARMACEUTICAL GOOD MANUFACTURING PRACTICE REPORTS, MEDICAL DEVICE QUALITY SYSTEM...
21 CFR 26.19 - Information relating to quality aspects.
Code of Federal Regulations, 2012 CFR
2012-04-01
... 21 Food and Drugs 1 2012-04-01 2012-04-01 false Information relating to quality aspects. 26.19... relating to quality aspects. The authorities will establish an appropriate means of exchanging information... MUTUAL RECOGNITION OF PHARMACEUTICAL GOOD MANUFACTURING PRACTICE REPORTS, MEDICAL DEVICE QUALITY SYSTEM...
21 CFR 26.19 - Information relating to quality aspects.
Code of Federal Regulations, 2011 CFR
2011-04-01
... 21 Food and Drugs 1 2011-04-01 2011-04-01 false Information relating to quality aspects. 26.19... relating to quality aspects. The authorities will establish an appropriate means of exchanging information... MUTUAL RECOGNITION OF PHARMACEUTICAL GOOD MANUFACTURING PRACTICE REPORTS, MEDICAL DEVICE QUALITY SYSTEM...
21 CFR 26.19 - Information relating to quality aspects.
Code of Federal Regulations, 2014 CFR
2014-04-01
... 21 Food and Drugs 1 2014-04-01 2014-04-01 false Information relating to quality aspects. 26.19... relating to quality aspects. The authorities will establish an appropriate means of exchanging information... MUTUAL RECOGNITION OF PHARMACEUTICAL GOOD MANUFACTURING PRACTICE REPORTS, MEDICAL DEVICE QUALITY SYSTEM...
Joint Attention Enhances Visual Working Memory
ERIC Educational Resources Information Center
Gregory, Samantha E. A.; Jackson, Margaret C.
2017-01-01
Joint attention--the mutual focus of 2 individuals on an item--speeds detection and discrimination of target information. However, what happens to that information beyond the initial perceptual episode? To fully comprehend and engage with our immediate environment also requires working memory (WM), which integrates information from second to…
Optimal averaging of soil moisture predictions from ensemble land surface model simulations
USDA-ARS?s Scientific Manuscript database
The correct interpretation of ensemble 3 soil moisture information obtained from the parallel implementation of multiple land surface models (LSMs) requires information concerning the LSM ensemble’s mutual error covariance. Here we propose a new technique for obtaining such information using an inst...
Application of information-retrieval methods to the classification of physical data
NASA Technical Reports Server (NTRS)
Mamotko, Z. N.; Khorolskaya, S. K.; Shatrovskiy, L. I.
1975-01-01
Scientific data received from satellites are characterized as a multi-dimensional time series, whose terms are vector functions of a vector of measurement conditions. Information retrieval methods are used to construct lower dimensional samples on the basis of the condition vector, in order to obtain these data and to construct partial relations. The methods are applied to the joint Soviet-French Arkad project.
Classical emergence of intrinsic spin-orbit interaction of light at the nanoscale
NASA Astrophysics Data System (ADS)
Vázquez-Lozano, J. Enrique; Martínez, Alejandro
2018-03-01
Traditionally, in macroscopic geometrical optics intrinsic polarization and spatial degrees of freedom of light can be treated independently. However, at the subwavelength scale these properties appear to be coupled together, giving rise to the spin-orbit interaction (SOI) of light. In this work we address theoretically the classical emergence of the optical SOI at the nanoscale. By means of a full-vector analysis involving spherical vector waves we show that the spin-orbit factorizability condition, accounting for the mutual influence between the amplitude (spin) and phase (orbit), is fulfilled only in the far-field limit. On the other side, in the near-field region, an additional relative phase introduces an extra term that hinders the factorization and reveals an intricate dynamical behavior according to the SOI regime. As a result, we find a suitable theoretical framework able to capture analytically the main features of intrinsic SOI of light. Besides allowing for a better understanding into the mechanism leading to its classical emergence at the nanoscale, our approach may be useful to design experimental setups that enhance the response of SOI-based effects.
EEG-based driver fatigue detection using hybrid deep generic model.
Phyo Phyo San; Sai Ho Ling; Rifai Chai; Tran, Yvonne; Craig, Ashley; Hung Nguyen
2016-08-01
Classification of electroencephalography (EEG)-based application is one of the important process for biomedical engineering. Driver fatigue is a major case of traffic accidents worldwide and considered as a significant problem in recent decades. In this paper, a hybrid deep generic model (DGM)-based support vector machine is proposed for accurate detection of driver fatigue. Traditionally, a probabilistic DGM with deep architecture is quite good at learning invariant features, but it is not always optimal for classification due to its trainable parameters are in the middle layer. Alternatively, Support Vector Machine (SVM) itself is unable to learn complicated invariance, but produces good decision surface when applied to well-behaved features. Consolidating unsupervised high-level feature extraction techniques, DGM and SVM classification makes the integrated framework stronger and enhance mutually in feature extraction and classification. The experimental results showed that the proposed DBN-based driver fatigue monitoring system achieves better testing accuracy of 73.29 % with 91.10 % sensitivity and 55.48 % specificity. In short, the proposed hybrid DGM-based SVM is an effective method for the detection of driver fatigue in EEG.
Bases for qudits from a nonstandard approach to SU(2)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kibler, M. R., E-mail: kibler@ipnl.in2p3.fr
2011-06-15
Bases of finite-dimensional Hilbert spaces (in dimension d) of relevance for quantum information and quantum computation are constructed from angular momentum theory and su(2) Lie algebraic methods. We report on a formula for deriving in one step the (1 + p)p qupits (i.e., qudits with d = p a prime integer) of a complete set of 1 + p mutually unbiased bases in C{sup p}. Repeated application of the formula can be used for generating mutually unbiased bases in C{sup d} with d = p{sup e} (e {>=} 2) a power of a prime integer. A connection between mutually unbiasedmore » bases and the unitary group SU(d) is briefly discussed in the case d = p{sup e}.« less
Quantum corrections to holographic mutual information
Agon, Cesar A.; Faulkner, Thomas
2016-08-22
We compute the leading contribution to the mutual information (MI) of two disjoint spheres in the large distance regime for arbitrary conformal field theories (CFT) in any dimension. This is achieved by refining the operator product expansion method introduced by Cardy [1]. For CFTs with holographic duals the leading contribution to the MI at long distances comes from bulk quantum corrections to the Ryu-Takayanagi area formula. According to the FLM proposal [2] this equals the bulk MI between the two disjoint regions spanned by the boundary spheres and their corresponding minimal area surfaces. We compute this quantum correction and providemore » in this way a non-trivial check of the FLM proposal.« less
Delocalizing entanglement of anisotropic black branes
NASA Astrophysics Data System (ADS)
Jahnke, Viktor
2018-01-01
We study the mutual information between pairs of regions on the two asymptotic boundaries of maximally extended anisotropic black branes. This quantity characterizes the local pattern of entanglement of the thermofield double states which are dual to these geometries. We analyze the disruption of the mutual information in anisotropic shock wave geometries and show that the entanglement velocity plays an important role in this phenomenon. Moreover, we compute several chaos-related properties of this system, such as the entanglement velocity, the butterfly velocity, and the scrambling time. We find that the butterfly velocity and the entanglement velocity violate the upper bounds proposed in [1-3], but remain bounded by their corresponding values in the infrared effective theory.
Item Selection Criteria with Practical Constraints for Computerized Classification Testing
ERIC Educational Resources Information Center
Lin, Chuan-Ju
2011-01-01
This study compares four item selection criteria for a two-category computerized classification testing: (1) Fisher information (FI), (2) Kullback-Leibler information (KLI), (3) weighted log-odds ratio (WLOR), and (4) mutual information (MI), with respect to the efficiency and accuracy of classification decision using the sequential probability…
Federal Register 2010, 2011, 2012, 2013, 2014
2012-06-14
... Proposed Information Collection to OMB Request for Termination of Multifamily Mortgage Insurance AGENCY... mutually agree to terminate the HUD multifamily mortgage insurance. DATES: Comments Due Date: July 16, 2012... following information: Title of Proposal: Request for Termination of Multifamily Mortgage Insurance. OMB...
32 CFR 700.334 - The Chief of Information.
Code of Federal Regulations, 2010 CFR
2010-07-01
...) The Chief of Information is the direct representative of the Secretary of the Navy in all public affairs and internal relations matters. The Chief of Information is authorized to implement Navy public affairs and internal relations policies and to coordinate those Navy and Marine Corps activities of mutual...
[Vision-astigmatometer and methods of its use].
Dashevskiĭ, A I; Kirrilov, Iu A
1991-01-01
A combination of astigmatic figures with black strips in different directions every 45 degrees and of two mutually perpendicular figures combined with an angle on a rotating disk on the front side of the astigmatometer and a combination of an angle and visometric cross of Landolt's optotypes on its back side with the similar disk, and a table of optotypes on the same side is suggested, that was tried in clinic. The directions of optotype ring ruptures are situated in 8 meridians. The front side of the astigmatometer shows a scheme for vector analysis of lenticular astigmatism. The method employed by the authors simplifies and accelerates the investigation, making unnecessary clouding and use of cross cylinders.
Canard configured aircraft with 2-D nozzle
NASA Technical Reports Server (NTRS)
Child, R. D.; Henderson, W. P.
1978-01-01
A closely-coupled canard fighter with vectorable two-dimensional nozzle was designed for enhanced transonic maneuvering. The HiMAT maneuver goal of a sustained 8g turn at a free-stream Mach number of 0.9 and 30,000 feet was the primary design consideration. The aerodynamic design process was initiated with a linear theory optimization minimizing the zero percent suction drag including jet effects and refined with three-dimensional nonlinear potential flow techniques. Allowances were made for mutual interference and viscous effects. The design process to arrive at the resultant configuration is described, and the design of a powered 2-D nozzle model to be tested in the LRC 16-foot Propulsion Wind Tunnel is shown.
NASA Astrophysics Data System (ADS)
Warchoł, Piotr
2018-06-01
The public transportation system of Cuernavaca, Mexico, exhibits random matrix theory statistics. In particular, the fluctuation of times between the arrival of buses on a given bus stop, follows the Wigner surmise for the Gaussian unitary ensemble. To model this, we propose an agent-based approach in which each bus driver tries to optimize his arrival time to the next stop with respect to an estimated arrival time of his predecessor. We choose a particular form of the associated utility function and recover the appropriate distribution in numerical experiments for a certain value of the only parameter of the model. We then investigate whether this value of the parameter is otherwise distinguished within an information theoretic approach and give numerical evidence that indeed it is associated with a minimum of averaged pairwise mutual information.
Measuring the usefulness of hidden units in Boltzmann machines with mutual information.
Berglund, Mathias; Raiko, Tapani; Cho, Kyunghyun
2015-04-01
Restricted Boltzmann machines (RBMs) and deep Boltzmann machines (DBMs) are important models in deep learning, but it is often difficult to measure their performance in general, or measure the importance of individual hidden units in specific. We propose to use mutual information to measure the usefulness of individual hidden units in Boltzmann machines. The measure is fast to compute, and serves as an upper bound for the information the neuron can pass on, enabling detection of a particular kind of poor training results. We confirm experimentally that the proposed measure indicates how much the performance of the model drops when some of the units of an RBM are pruned away. We demonstrate the usefulness of the measure for early detection of poor training in DBMs. Copyright © 2014 Elsevier Ltd. All rights reserved.
Recurrence plot statistics and the effect of embedding
NASA Astrophysics Data System (ADS)
March, T. K.; Chapman, S. C.; Dendy, R. O.
2005-01-01
Recurrence plots provide a graphical representation of the recurrent patterns in a timeseries, the quantification of which is a relatively new field. Here we derive analytical expressions which relate the values of key statistics, notably determinism and entropy of line length distribution, to the correlation sum as a function of embedding dimension. These expressions are obtained by deriving the transformation which generates an embedded recurrence plot from an unembedded plot. A single unembedded recurrence plot thus provides the statistics of all possible embedded recurrence plots. If the correlation sum scales exponentially with embedding dimension, we show that these statistics are determined entirely by the exponent of the exponential. This explains the results of Iwanski and Bradley [J.S. Iwanski, E. Bradley, Recurrence plots of experimental data: to embed or not to embed? Chaos 8 (1998) 861-871] who found that certain recurrence plot statistics are apparently invariant to embedding dimension for certain low-dimensional systems. We also examine the relationship between the mutual information content of two timeseries and the common recurrent structure seen in their recurrence plots. This allows time-localized contributions to mutual information to be visualized. This technique is demonstrated using geomagnetic index data; we show that the AU and AL geomagnetic indices share half their information, and find the timescale on which mutual features appear.
Cancer cell redirection biomarker discovery using a mutual information approach.
Roche, Kimberly; Feltus, F Alex; Park, Jang Pyo; Coissieux, Marie-May; Chang, Chenyan; Chan, Vera B S; Bentires-Alj, Mohamed; Booth, Brian W
2017-01-01
Introducing tumor-derived cells into normal mammary stem cell niches at a sufficiently high ratio of normal to tumorous cells causes those tumor cells to undergo a change to normal mammary phenotype and yield normal mammary progeny. This phenomenon has been termed cancer cell redirection. We have developed an in vitro model that mimics in vivo redirection of cancer cells by the normal mammary microenvironment. Using the RNA profiling data from this cellular model, we examined high-level characteristics of the normal, redirected, and tumor transcriptomes and found the global expression profiles clearly distinguish the three expression states. To identify potential redirection biomarkers that cause the redirected state to shift toward the normal expression pattern, we used mutual information relationships between normal, redirected, and tumor cell groups. Mutual information relationship analysis reduced a dataset of over 35,000 gene expression measurements spread over 13,000 curated gene sets to a set of 20 significant molecular signatures totaling 906 unique loci. Several of these molecular signatures are hallmark drivers of the tumor state. Using differential expression as a guide, we further refined the gene set to 120 core redirection biomarker genes. The expression levels of these core biomarkers are sufficient to make the normal and redirected gene expression states indistinguishable from each other but radically different from the tumor state.
Cancer cell redirection biomarker discovery using a mutual information approach
Roche, Kimberly; Feltus, F. Alex; Park, Jang Pyo; Coissieux, Marie-May; Chang, Chenyan; Chan, Vera B. S.; Bentires-Alj, Mohamed
2017-01-01
Introducing tumor-derived cells into normal mammary stem cell niches at a sufficiently high ratio of normal to tumorous cells causes those tumor cells to undergo a change to normal mammary phenotype and yield normal mammary progeny. This phenomenon has been termed cancer cell redirection. We have developed an in vitro model that mimics in vivo redirection of cancer cells by the normal mammary microenvironment. Using the RNA profiling data from this cellular model, we examined high-level characteristics of the normal, redirected, and tumor transcriptomes and found the global expression profiles clearly distinguish the three expression states. To identify potential redirection biomarkers that cause the redirected state to shift toward the normal expression pattern, we used mutual information relationships between normal, redirected, and tumor cell groups. Mutual information relationship analysis reduced a dataset of over 35,000 gene expression measurements spread over 13,000 curated gene sets to a set of 20 significant molecular signatures totaling 906 unique loci. Several of these molecular signatures are hallmark drivers of the tumor state. Using differential expression as a guide, we further refined the gene set to 120 core redirection biomarker genes. The expression levels of these core biomarkers are sufficient to make the normal and redirected gene expression states indistinguishable from each other but radically different from the tumor state. PMID:28594912
Mutual information estimation reveals global associations between stimuli and biological processes
Suzuki, Taiji; Sugiyama, Masashi; Kanamori, Takafumi; Sese, Jun
2009-01-01
Background Although microarray gene expression analysis has become popular, it remains difficult to interpret the biological changes caused by stimuli or variation of conditions. Clustering of genes and associating each group with biological functions are often used methods. However, such methods only detect partial changes within cell processes. Herein, we propose a method for discovering global changes within a cell by associating observed conditions of gene expression with gene functions. Results To elucidate the association, we introduce a novel feature selection method called Least-Squares Mutual Information (LSMI), which computes mutual information without density estimaion, and therefore LSMI can detect nonlinear associations within a cell. We demonstrate the effectiveness of LSMI through comparison with existing methods. The results of the application to yeast microarray datasets reveal that non-natural stimuli affect various biological processes, whereas others are no significant relation to specific cell processes. Furthermore, we discover that biological processes can be categorized into four types according to the responses of various stimuli: DNA/RNA metabolism, gene expression, protein metabolism, and protein localization. Conclusion We proposed a novel feature selection method called LSMI, and applied LSMI to mining the association between conditions of yeast and biological processes through microarray datasets. In fact, LSMI allows us to elucidate the global organization of cellular process control. PMID:19208155
Independent EEG Sources Are Dipolar
Delorme, Arnaud; Palmer, Jason; Onton, Julie; Oostenveld, Robert; Makeig, Scott
2012-01-01
Independent component analysis (ICA) and blind source separation (BSS) methods are increasingly used to separate individual brain and non-brain source signals mixed by volume conduction in electroencephalographic (EEG) and other electrophysiological recordings. We compared results of decomposing thirteen 71-channel human scalp EEG datasets by 22 ICA and BSS algorithms, assessing the pairwise mutual information (PMI) in scalp channel pairs, the remaining PMI in component pairs, the overall mutual information reduction (MIR) effected by each decomposition, and decomposition ‘dipolarity’ defined as the number of component scalp maps matching the projection of a single equivalent dipole with less than a given residual variance. The least well-performing algorithm was principal component analysis (PCA); best performing were AMICA and other likelihood/mutual information based ICA methods. Though these and other commonly-used decomposition methods returned many similar components, across 18 ICA/BSS algorithms mean dipolarity varied linearly with both MIR and with PMI remaining between the resulting component time courses, a result compatible with an interpretation of many maximally independent EEG components as being volume-conducted projections of partially-synchronous local cortical field activity within single compact cortical domains. To encourage further method comparisons, the data and software used to prepare the results have been made available (http://sccn.ucsd.edu/wiki/BSSComparison). PMID:22355308
International Librarianship: Developing Professional, Intercultural, and Educational Leadership
ERIC Educational Resources Information Center
Constantinou, Constantia, Ed.; Miller, Michael J., Ed.; Schlesinger, Kenneth, Ed.
2017-01-01
International librarianship stems from a desire to bring about political change, transcultural understanding, collaboration, and mutual respect. Historically, librarians have been deeply involved with challenging issues of information sharing, equity in information access, and bridging the digital divide between different socioeconomic…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jani, S; Kishan, A; O'Connell, D
2014-06-01
Purpose: To investigate if pelvic nodal coverage for prostate patients undergoing intensity modulated radiotherapy (IMRT) can be predicted using mutual image information computed between planning and cone-beam CTs (CBCTs). Methods: Four patients with high-risk prostate adenocarcinoma were treated with IMRT on a Varian TrueBeam. Plans were designed such that 95% of the nodal planning target volume (PTV) received the prescription dose of 45 Gy (N=1) or 50.4 Gy (N=3). Weekly CBCTs (N=25) were acquired and the nodal clinical target volumes and organs at risk were contoured by a physician. The percent nodal volume receiving prescription dose was recorded as amore » ground truth. Using the recorded shifts performed by the radiation therapists at the time of image acquisition, CBCTs were aligned with the planning kVCT. Mutual image information (MI) was calculated between the CBCT and the aligned planning CT within the contour of the nodal PTV. Due to variable CBCT fields-of-view, CBCT images covering less than 90% of the nodal volume were excluded from the analysis, resulting in the removal of eight CBCTs. Results: A correlation coefficient of 0.40 was observed between the MI metric and the percent of the nodal target volume receiving the prescription dose. One patient's CBCTs had clear outliers from the rest of the patients. Upon further investigation, we discovered image artifacts that were present only in that patient's images. When those four images were excluded, the correlation improved to 0.81. Conclusion: This pilot study shows the potential of predicting pelvic nodal dosimetry by computing the mutual image information between planning CTs and patient setup CBCTs. Importantly, this technique does not involve manual or automatic contouring of the CBCT images. Additional patients and more robust exclusion criteria will help validate our findings.« less
The Anopheles gambiae transcriptome - a turning point for malaria control.
Domingos, A; Pinheiro-Silva, R; Couto, J; do Rosário, V; de la Fuente, J
2017-04-01
Mosquitoes are important vectors of several pathogens and thereby contribute to the spread of diseases, with social, economic and public health impacts. Amongst the approximately 450 species of Anopheles, about 60 are recognized as vectors of human malaria, the most important parasitic disease. In Africa, Anopheles gambiae is the main malaria vector mosquito. Current malaria control strategies are largely focused on drugs and vector control measures such as insecticides and bed-nets. Improvement of current, and the development of new, mosquito-targeted malaria control methods rely on a better understanding of mosquito vector biology. An organism's transcriptome is a reflection of its physiological state and transcriptomic analyses of different conditions that are relevant to mosquito vector competence can therefore yield important information. Transcriptomic analyses have contributed significant information on processes such as blood-feeding parasite-vector interaction, insecticide resistance, and tissue- and stage-specific gene regulation, thereby facilitating the path towards the development of new malaria control methods. Here, we discuss the main applications of transcriptomic analyses in An. gambiae that have led to a better understanding of mosquito vector competence. © 2017 The Royal Entomological Society.
Can invertebrates see the e-vector of polarization as a separate modality of light?
Labhart, Thomas
2016-12-15
The visual world is rich in linearly polarized light stimuli, which are hidden from the human eye. But many invertebrate species make use of polarized light as a source of valuable visual information. However, exploiting light polarization does not necessarily imply that the electric (e)-vector orientation of polarized light can be perceived as a separate modality of light. In this Review, I address the question of whether invertebrates can detect specific e-vector orientations in a manner similar to that of humans perceiving spectral stimuli as specific hues. To analyze e-vector orientation, the signals of at least three polarization-sensitive sensors (analyzer channels) with different e-vector tuning axes must be compared. The object-based, imaging polarization vision systems of cephalopods and crustaceans, as well as the water-surface detectors of flying backswimmers, use just two analyzer channels. Although this excludes the perception of specific e-vector orientations, a two-channel system does provide a coarse, categoric analysis of polarized light stimuli, comparable to the limited color sense of dichromatic, 'color-blind' humans. The celestial compass of insects employs three or more analyzer channels. However, that compass is multimodal, i.e. e-vector information merges with directional information from other celestial cues, such as the solar azimuth and the spectral gradient in the sky, masking e-vector information. It seems that invertebrate organisms take no interest in the polarization details of visual stimuli, but polarization vision grants more practical benefits, such as improved object detection and visual communication for cephalopods and crustaceans, compass readings to traveling insects, or the alert 'water below!' to water-seeking bugs. © 2016. Published by The Company of Biologists Ltd.
Can invertebrates see the e-vector of polarization as a separate modality of light?
2016-01-01
ABSTRACT The visual world is rich in linearly polarized light stimuli, which are hidden from the human eye. But many invertebrate species make use of polarized light as a source of valuable visual information. However, exploiting light polarization does not necessarily imply that the electric (e)-vector orientation of polarized light can be perceived as a separate modality of light. In this Review, I address the question of whether invertebrates can detect specific e-vector orientations in a manner similar to that of humans perceiving spectral stimuli as specific hues. To analyze e-vector orientation, the signals of at least three polarization-sensitive sensors (analyzer channels) with different e-vector tuning axes must be compared. The object-based, imaging polarization vision systems of cephalopods and crustaceans, as well as the water-surface detectors of flying backswimmers, use just two analyzer channels. Although this excludes the perception of specific e-vector orientations, a two-channel system does provide a coarse, categoric analysis of polarized light stimuli, comparable to the limited color sense of dichromatic, ‘color-blind’ humans. The celestial compass of insects employs three or more analyzer channels. However, that compass is multimodal, i.e. e-vector information merges with directional information from other celestial cues, such as the solar azimuth and the spectral gradient in the sky, masking e-vector information. It seems that invertebrate organisms take no interest in the polarization details of visual stimuli, but polarization vision grants more practical benefits, such as improved object detection and visual communication for cephalopods and crustaceans, compass readings to traveling insects, or the alert ‘water below!’ to water-seeking bugs. PMID:27974532
Vector systems for prenatal gene therapy: principles of retrovirus vector design and production.
Howe, Steven J; Chandrashekran, Anil
2012-01-01
Vectors derived from the Retroviridae family have several attributes required for successful gene delivery. Retroviral vectors have an adequate payload size for the coding regions of most genes; they are safe to handle and simple to produce. These vectors can be manipulated to target different cell types with low immunogenicity and can permanently insert genetic information into the host cells' genome. Retroviral vectors have been used in gene therapy clinical trials and successfully applied experimentally in vitro, in vivo, and in utero.
The PHESAT95 catalogue of observations of the mutual events of the Saturnian satellites
NASA Astrophysics Data System (ADS)
Thuillot, W.; Arlot, J.-E.; Ruatti, C.; Berthier, J.; Blanco, C.; Colas, F.; Czech, W.; Damani, M.; D'Ambrosio, V.; Descamps, P.; Dourneau, G.; Emelianov, N.; Foglia, S.; Helmer, G.; Irsmambetova, T. R.; James, N.; Laques, P.; Lecacheux, J.; Le Campion, J.-F.; Ledoux, C.; Le Floch, J.-C.; Oprescu, G.; Rapaport, M.; Riccioli, R.; Starosta, B.; Tejfel, V. G.; Trunkovsky, E. M.; Viateau, B.; Veiga, C. H.; Vu, D. T.
2001-05-01
In 1994-1996 the Sun and the Earth passed through the equatorial plane of Saturn and therefore through the orbital planes of its main satellites. During this period, phenomena involving seven of these satellites were observed. Light curves of eclipses by Saturn and of mutual eclipses and occultations were recorded by the observers of the international campaign PHESAT95 organized by the Institut de mécanique céleste, Paris, France. Herein, we report 66 observations of 43 mutual events from 16 sites. For each observation, information is given about the telescope, the receptor, the site and the observational conditions. This paper gathers together all these data and gives a first estimate of the precision providing accurate astrometric data useful for the development of dynamical models.
What Makes Informal Mentorship in the Medical Realm Effective?
ERIC Educational Resources Information Center
Mohtady, Heba A.; Könings, Karen D.; van Merriënboer, Jeroen J. G.
2016-01-01
Informal mentoring is based on a natural match between a junior individual and a senior one who share mutual interests. It usually aids in the professional and personal development of both parties involved. We reviewed the literature regarding factors that make informal mentoring effective within the medical realm, by searching a major academic…
ERIC Educational Resources Information Center
Dobozy, Eva; Gross, Julia
2010-01-01
The authors contend that better information literacy and library skills development practice is needed for students entering university. This paper presents a case study of how a teacher education (TE) lecturer and a faculty librarian collaborated in an Australian university to provide information literacy practice. A mutual interest in…
Inference of topology and the nature of synapses, and the flow of information in neuronal networks
NASA Astrophysics Data System (ADS)
Borges, F. S.; Lameu, E. L.; Iarosz, K. C.; Protachevicz, P. R.; Caldas, I. L.; Viana, R. L.; Macau, E. E. N.; Batista, A. M.; Baptista, M. S.
2018-02-01
The characterization of neuronal connectivity is one of the most important matters in neuroscience. In this work, we show that a recently proposed informational quantity, the causal mutual information, employed with an appropriate methodology, can be used not only to correctly infer the direction of the underlying physical synapses, but also to identify their excitatory or inhibitory nature, considering easy to handle and measure bivariate time series. The success of our approach relies on a surprising property found in neuronal networks by which nonadjacent neurons do "understand" each other (positive mutual information), however, this exchange of information is not capable of causing effect (zero transfer entropy). Remarkably, inhibitory connections, responsible for enhancing synchronization, transfer more information than excitatory connections, known to enhance entropy in the network. We also demonstrate that our methodology can be used to correctly infer directionality of synapses even in the presence of dynamic and observational Gaussian noise, and is also successful in providing the effective directionality of intermodular connectivity, when only mean fields can be measured.
Beheshti, Iman; Demirel, Hasan; Farokhian, Farnaz; Yang, Chunlan; Matsuda, Hiroshi
2016-12-01
This paper presents an automatic computer-aided diagnosis (CAD) system based on feature ranking for detection of Alzheimer's disease (AD) using structural magnetic resonance imaging (sMRI) data. The proposed CAD system is composed of four systematic stages. First, global and local differences in the gray matter (GM) of AD patients compared to the GM of healthy controls (HCs) are analyzed using a voxel-based morphometry technique. The aim is to identify significant local differences in the volume of GM as volumes of interests (VOIs). Second, the voxel intensity values of the VOIs are extracted as raw features. Third, the raw features are ranked using a seven-feature ranking method, namely, statistical dependency (SD), mutual information (MI), information gain (IG), Pearson's correlation coefficient (PCC), t-test score (TS), Fisher's criterion (FC), and the Gini index (GI). The features with higher scores are more discriminative. To determine the number of top features, the estimated classification error based on training set made up of the AD and HC groups is calculated, with the vector size that minimized this error selected as the top discriminative feature. Fourth, the classification is performed using a support vector machine (SVM). In addition, a data fusion approach among feature ranking methods is introduced to improve the classification performance. The proposed method is evaluated using a data-set from ADNI (130 AD and 130 HC) with 10-fold cross-validation. The classification accuracy of the proposed automatic system for the diagnosis of AD is up to 92.48% using the sMRI data. An automatic CAD system for the classification of AD based on feature-ranking method and classification errors is proposed. In this regard, seven-feature ranking methods (i.e., SD, MI, IG, PCC, TS, FC, and GI) are evaluated. The optimal size of top discriminative features is determined by the classification error estimation in the training phase. The experimental results indicate that the performance of the proposed system is comparative to that of state-of-the-art classification models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Chen, Yongren; Li, Yueqing; Qi, Dongmei
2018-04-01
Based on a variety of ground-based and satellite-derived observational data, we studied a flood-rainstorm event that occurred over northeastern Sichuan, China, from the 8th to the 14th of September 2014. Four periods of mesoscale convective system (MCS) activity were found during a mutual evolution process of an 850-hPa basin inverted trough (BIT) and 850-hPa basin low vortex (BLV). Among them, the first three periods occurred in an alternating evolution of the BIT and BLV (called the first stage), and then, the fourth period was stimulated by continuous activity of the BLV (called the second stage). During the first stage, MCSs enhanced (weakened) under the situation of the BIT (BLV), and then during the second stage MCSs developed to their strongest levels. Further analysis of the reasons behind the enhancement and weakening of MCSs revealed an obvious characteristic of upper level (lower level) positive (negative) divergence in the BIT situation of the first stage and BLV situation of the second stage. By comparison, under the BLV situation of the first stage, the vertical helicity was larger in the upward airflow of the zonal circulation, and the direction of the wet Q-vector was toward the ascending airflow in the vertical direction. In the horizontal direction, the negative divergence of the wet Q-vector corresponded to the position of water vapor flux convergence. In addition, in the early development of convection, sounding data showed a humidity profile of dry upper and wet lower levels, as well as a larger value of convective available potential energy, which triggered convective activity under the favorable dynamic conditions of atmosphere. When the above characteristics weakened, the convective activity also weakened. Therefore, the formation of multiple convective systems was closely related to the adjustment in atmospheric conditions around the BIT and BLV.
NASA Astrophysics Data System (ADS)
Kuznetsova, Tamara; Laptukhov, Alexej; Petrov, Valery
Causes of the geomagnetic activity (GA) in the report are divided into temporal changes of the solar wind parameters and the changes of the geomagnetic moment orientation relative directions of the solar wind electric and magnetic fields. Based on our previous study we concluded that a reconnection based on determining role of mutual orientation of the solar wind electric field and geomagnetic moment taking into account effects of the Earth's orbital and daily motions is the most effective compared with existing mechanisms. At present a reconnection as paradigma that has applications in broad fields of physics needs analysis of experimental facts to be developed. In terms of reconnection it is important not only mutual orientation of vectors describing physics of interaction region but and reconnection rate which depends from rate of energy flux to those regions where the reconnection is permitted. Applied to magnetosphere these regions first of all are dayside magnetopause and polar caps. Influence of rate of the energy flux to the lobe magnetopause (based on calculations of the Poyting electromagnetic flux component controlling the reconnection rate along the solar wind velocity Pv) on planetary GA (Dst, Kp indices) is investigated at different phases of geomagnetic storms. We study also the rate of energy flux to the polar caps during storms (based on calculations of the Poyting flux vector component along the geomagnetic moment Pm) and its influence on magnetic activity in the polar ionosphere: at the auroral zone (AU,AL indices). Results allow to evaluate contributions of high and low latitude sources of electromagnetic energy to the storm development and also to clear mechanism of the electromagnetic energy transmission from the solar wind to the magnetosphere. We evaluate too power of the solar wind electromagnetic energy during well-known large storms and compare result with power of the energy sources of other geophysical processes (atmosphere, ocean, earthquakes and etc). The study was supported by a grant of RFBR, n 06-05-64998.
Empirical mode decomposition-based facial pose estimation inside video sequences
NASA Astrophysics Data System (ADS)
Qing, Chunmei; Jiang, Jianmin; Yang, Zhijing
2010-03-01
We describe a new pose-estimation algorithm via integration of the strength in both empirical mode decomposition (EMD) and mutual information. While mutual information is exploited to measure the similarity between facial images to estimate poses, EMD is exploited to decompose input facial images into a number of intrinsic mode function (IMF) components, which redistribute the effect of noise, expression changes, and illumination variations as such that, when the input facial image is described by the selected IMF components, all the negative effects can be minimized. Extensive experiments were carried out in comparisons to existing representative techniques, and the results show that the proposed algorithm achieves better pose-estimation performances with robustness to noise corruption, illumination variation, and facial expressions.
Compressed Secret Key Agreement:Maximizing Multivariate Mutual Information per Bit
NASA Astrophysics Data System (ADS)
Chan, Chung
2017-10-01
The multiterminal secret key agreement problem by public discussion is formulated with an additional source compression step where, prior to the public discussion phase, users independently compress their private sources to filter out strongly correlated components for generating a common secret key. The objective is to maximize the achievable key rate as a function of the joint entropy of the compressed sources. Since the maximum achievable key rate captures the total amount of information mutual to the compressed sources, an optimal compression scheme essentially maximizes the multivariate mutual information per bit of randomness of the private sources, and can therefore be viewed more generally as a dimension reduction technique. Single-letter lower and upper bounds on the maximum achievable key rate are derived for the general source model, and an explicit polynomial-time computable formula is obtained for the pairwise independent network model. In particular, the converse results and the upper bounds are obtained from those of the related secret key agreement problem with rate-limited discussion. A precise duality is shown for the two-user case with one-way discussion, and such duality is extended to obtain the desired converse results in the multi-user case. In addition to posing new challenges in information processing and dimension reduction, the compressed secret key agreement problem helps shed new light on resolving the difficult problem of secret key agreement with rate-limited discussion, by offering a more structured achieving scheme and some simpler conjectures to prove.
Neighboring block based disparity vector derivation for multiview compatible 3D-AVC
NASA Astrophysics Data System (ADS)
Kang, Jewon; Chen, Ying; Zhang, Li; Zhao, Xin; Karczewicz, Marta
2013-09-01
3D-AVC being developed under Joint Collaborative Team on 3D Video Coding (JCT-3V) significantly outperforms the Multiview Video Coding plus Depth (MVC+D) which simultaneously encodes texture views and depth views with the multiview extension of H.264/AVC (MVC). However, when the 3D-AVC is configured to support multiview compatibility in which texture views are decoded without depth information, the coding performance becomes significantly degraded. The reason is that advanced coding tools incorporated into the 3D-AVC do not perform well due to the lack of a disparity vector converted from the depth information. In this paper, we propose a disparity vector derivation method utilizing only the information of texture views. Motion information of neighboring blocks is used to determine a disparity vector for a macroblock, so that the derived disparity vector is efficiently used for the coding tools in 3D-AVC. The proposed method significantly improves a coding gain of the 3D-AVC in the multiview compatible mode about 20% BD-rate saving in the coded views and 26% BD-rate saving in the synthesized views on average.
VectorBase: a data resource for invertebrate vector genomics
Lawson, Daniel; Arensburger, Peter; Atkinson, Peter; Besansky, Nora J.; Bruggner, Robert V.; Butler, Ryan; Campbell, Kathryn S.; Christophides, George K.; Christley, Scott; Dialynas, Emmanuel; Hammond, Martin; Hill, Catherine A.; Konopinski, Nathan; Lobo, Neil F.; MacCallum, Robert M.; Madey, Greg; Megy, Karine; Meyer, Jason; Redmond, Seth; Severson, David W.; Stinson, Eric O.; Topalis, Pantelis; Birney, Ewan; Gelbart, William M.; Kafatos, Fotis C.; Louis, Christos; Collins, Frank H.
2009-01-01
VectorBase (http://www.vectorbase.org) is an NIAID-funded Bioinformatic Resource Center focused on invertebrate vectors of human pathogens. VectorBase annotates and curates vector genomes providing a web accessible integrated resource for the research community. Currently, VectorBase contains genome information for three mosquito species: Aedes aegypti, Anopheles gambiae and Culex quinquefasciatus, a body louse Pediculus humanus and a tick species Ixodes scapularis. Since our last report VectorBase has initiated a community annotation system, a microarray and gene expression repository and controlled vocabularies for anatomy and insecticide resistance. We have continued to develop both the software infrastructure and tools for interrogating the stored data. PMID:19028744
Thepsoonthorn, C.; Yokozuka, T.; Miura, S.; Ogawa, K.; Miyake, Y.
2016-01-01
As prior knowledge is claimed to be an essential key to achieve effective education, we are interested in exploring whether prior knowledge enhances communication effectiveness. To demonstrate the effects of prior knowledge, mutual gaze convergence and head nodding synchrony are observed as indicators of communication effectiveness. We conducted an experiment on lecture task between lecturer and student under 2 conditions: prior knowledge and non-prior knowledge. The students in prior knowledge condition were provided the basic information about the lecture content and were assessed their understanding by the experimenter before starting the lecture while the students in non-prior knowledge had none. The result shows that the interaction in prior knowledge condition establishes significantly higher mutual gaze convergence (t(15.03) = 6.72, p < 0.0001; α = 0.05, n = 20) and head nodding synchrony (t(16.67) = 1.83, p = 0.04; α = 0.05, n = 19) compared to non-prior knowledge condition. This study reveals that prior knowledge facilitates mutual gaze convergence and head nodding synchrony. Furthermore, the interaction with and without prior knowledge can be evaluated by measuring or observing mutual gaze convergence and head nodding synchrony. PMID:27910902
Thepsoonthorn, C; Yokozuka, T; Miura, S; Ogawa, K; Miyake, Y
2016-12-02
As prior knowledge is claimed to be an essential key to achieve effective education, we are interested in exploring whether prior knowledge enhances communication effectiveness. To demonstrate the effects of prior knowledge, mutual gaze convergence and head nodding synchrony are observed as indicators of communication effectiveness. We conducted an experiment on lecture task between lecturer and student under 2 conditions: prior knowledge and non-prior knowledge. The students in prior knowledge condition were provided the basic information about the lecture content and were assessed their understanding by the experimenter before starting the lecture while the students in non-prior knowledge had none. The result shows that the interaction in prior knowledge condition establishes significantly higher mutual gaze convergence (t(15.03) = 6.72, p < 0.0001; α = 0.05, n = 20) and head nodding synchrony (t(16.67) = 1.83, p = 0.04; α = 0.05, n = 19) compared to non-prior knowledge condition. This study reveals that prior knowledge facilitates mutual gaze convergence and head nodding synchrony. Furthermore, the interaction with and without prior knowledge can be evaluated by measuring or observing mutual gaze convergence and head nodding synchrony.
Mutual Information and Information Gating in Synfire Chains
Xiao, Zhuocheng; Wang, Binxu; Sornborger, Andrew Tyler; ...
2018-02-01
Here, coherent neuronal activity is believed to underlie the transfer and processing of information in the brain. Coherent activity in the form of synchronous firing and oscillations has been measured in many brain regions and has been correlated with enhanced feature processing and other sensory and cognitive functions. In the theoretical context, synfire chains and the transfer of transient activity packets in feedforward networks have been appealed to in order to describe coherent spiking and information transfer. Recently, it has been demonstrated that the classical synfire chain architecture, with the addition of suitably timed gating currents, can support the gradedmore » transfer of mean firing rates in feedforward networks (called synfire-gated synfire chains—SGSCs). Here we study information propagation in SGSCs by examining mutual information as a function of layer number in a feedforward network. We explore the effects of gating and noise on information transfer in synfire chains and demonstrate that asymptotically, two main regions exist in parameter space where information may be propagated and its propagation is controlled by pulse-gating: a large region where binary codes may be propagated, and a smaller region near a cusp in parameter space that supports graded propagation across many layers.« less
Mutual Information and Information Gating in Synfire Chains
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xiao, Zhuocheng; Wang, Binxu; Sornborger, Andrew Tyler
Here, coherent neuronal activity is believed to underlie the transfer and processing of information in the brain. Coherent activity in the form of synchronous firing and oscillations has been measured in many brain regions and has been correlated with enhanced feature processing and other sensory and cognitive functions. In the theoretical context, synfire chains and the transfer of transient activity packets in feedforward networks have been appealed to in order to describe coherent spiking and information transfer. Recently, it has been demonstrated that the classical synfire chain architecture, with the addition of suitably timed gating currents, can support the gradedmore » transfer of mean firing rates in feedforward networks (called synfire-gated synfire chains—SGSCs). Here we study information propagation in SGSCs by examining mutual information as a function of layer number in a feedforward network. We explore the effects of gating and noise on information transfer in synfire chains and demonstrate that asymptotically, two main regions exist in parameter space where information may be propagated and its propagation is controlled by pulse-gating: a large region where binary codes may be propagated, and a smaller region near a cusp in parameter space that supports graded propagation across many layers.« less
Statistics of optimal information flow in ensembles of regulatory motifs
NASA Astrophysics Data System (ADS)
Crisanti, Andrea; De Martino, Andrea; Fiorentino, Jonathan
2018-02-01
Genetic regulatory circuits universally cope with different sources of noise that limit their ability to coordinate input and output signals. In many cases, optimal regulatory performance can be thought to correspond to configurations of variables and parameters that maximize the mutual information between inputs and outputs. Since the mid-2000s, such optima have been well characterized in several biologically relevant cases. Here we use methods of statistical field theory to calculate the statistics of the maximal mutual information (the "capacity") achievable by tuning the input variable only in an ensemble of regulatory motifs, such that a single controller regulates N targets. Assuming (i) sufficiently large N , (ii) quenched random kinetic parameters, and (iii) small noise affecting the input-output channels, we can accurately reproduce numerical simulations both for the mean capacity and for the whole distribution. Our results provide insight into the inherent variability in effectiveness occurring in regulatory systems with heterogeneous kinetic parameters.
Mutuality and solidarity: assessing risks and sharing losses.
Wilkie, D
1997-01-01
Mutuality is the principle of private, commercial insurance; individuals enter the pool for sharing losses, and pay according to the best estimate of the risk they bring with them. Solidarity is the sharing of losses with payment according to some other scheme; this is the principle of state social insurance; essential features of solidarity are comprehensiveness and compulsion. Private insurance is subject to the uberrima fides principle, or utmost good faith; each side declares all it knows about the risk. The Disability Discrimination Act requires insurers to justify disability discrimination on the basis of relevant information, acturial, statistical or medical, on which it is reasonable to rely. It could be very damaging to private insurance to abandon uberrima fides. However, although some genetic information is clearly useful to underwriters, other information may be so general as to be of little use. The way in which mortality rates are assessed is also explained. PMID:9304668
McGrath, Pam; Holewa, Hamish; Koilparampil, Thomas; Koshy, Cherian; George, Shobha
2009-10-01
This article presents the findings of a cross-cultural research project that explored similarities and differences between palliative care service provision in Kerala, India and South-East Queensland, Australia, to inform a process of mutual learning for service development. Three major points of difference that can inform this process of mutual learning were identified: 1) an understanding of the significance of honesty in information-giving to the patient, 2) recognition of the importance of palliative care specialists providing education to mainstream health professionals, and 3) appreciation of the need for palliative care to be cognizant of the socio-economic impact of dying-especially for families experiencing poverty-by embracing strategies for financial and material support. The findings highlight the effectiveness of a cross-cultural collaboration between health professionals and researchers in South-East Queensland, Australia and Kerala, India.
Estimating Mutual Information for High-to-Low Calibration
DOE Office of Scientific and Technical Information (OSTI.GOV)
Michaud, Isaac James; Williams, Brian J.; Weaver, Brian Phillip
Presentation shows that KSG 2 is superior to KSG 1 because it scales locally automatically; KSG estimators are limited to a maximum MI due to sample size; LNC extends the capability of KSG without onerous assumptions; iLNC allows LNC to estimate information gain.
43 CFR 17.333 - Investigation.
Code of Federal Regulations, 2010 CFR
2010-10-01
..., Conciliation, and Enforcement Procedures § 17.333 Investigation. (a) Informal investigation. (1) DOI will... mediation agreement. (2) As part of the initial investigation, DOI will use informal fact finding methods... possible, settle the complaint on terms that are mutually agreeable to the parties. DOI may seek the...
A Menagerie of Tracks at Maryland: HARD, Enterprise, QA, and Genomics, Oh My!
2006-01-01
mutually agreeable search strategy for acquiring the desired information. Like information need negotiation in a reference interview, clarification...answer key to identify relevant nuggets in system responses. The obvious downside of this approach is that the process requires human intervention
43 CFR 17.333 - Investigation.
Code of Federal Regulations, 2011 CFR
2011-10-01
..., Conciliation, and Enforcement Procedures § 17.333 Investigation. (a) Informal investigation. (1) DOI will... mediation agreement. (2) As part of the initial investigation, DOI will use informal fact finding methods... possible, settle the complaint on terms that are mutually agreeable to the parties. DOI may seek the...
Implementation of mutual information and bayes theorem for classification microarray data
NASA Astrophysics Data System (ADS)
Dwifebri Purbolaksono, Mahendra; Widiastuti, Kurnia C.; Syahrul Mubarok, Mohamad; Adiwijaya; Aminy Ma’ruf, Firda
2018-03-01
Microarray Technology is one of technology which able to read the structure of gen. The analysis is important for this technology. It is for deciding which attribute is more important than the others. Microarray technology is able to get cancer information to diagnose a person’s gen. Preparation of microarray data is a huge problem and takes a long time. That is because microarray data contains high number of insignificant and irrelevant attributes. So, it needs a method to reduce the dimension of microarray data without eliminating important information in every attribute. This research uses Mutual Information to reduce dimension. System is built with Machine Learning approach specifically Bayes Theorem. This theorem uses a statistical and probability approach. By combining both methods, it will be powerful for Microarray Data Classification. The experiment results show that system is good to classify Microarray data with highest F1-score using Bayesian Network by 91.06%, and Naïve Bayes by 88.85%.
Traditional risk-sharing arrangements and informal social insurance in Eritrea.
Habtom, GebreMichael Kibreab; Ruys, Pieter
2007-01-01
In Eritrea neither the state nor the market is effective in providing health insurance to low-income people (in rural and informal job sector). Schemes intended for the informal sector are confronted with low and irregular incomes of target populations and consequently negligible potential for profit making. Because of this there, are no formal health insurance systems in Eritrea that cover people in the traditional (or informal) sector of the economy. In the absence of formal safety nets traditional Eritrean societies use their local social capital to alleviate unexpected social costs. In Eritrea traditional risk-sharing arrangements are made within extended families and mutual aid community associations. This study reveals that in a situation where the state no longer provides free public health services any more and access to private insurance is denied, the extension of the voluntary mutual aid community associations to Mahber-based health insurance schemes at the local level is a viable way for providing modern health services.
Information-theoretic approach to lead-lag effect on financial markets
NASA Astrophysics Data System (ADS)
Fiedor, Paweł
2014-08-01
Recently the interest of researchers has shifted from the analysis of synchronous relationships of financial instruments to the analysis of more meaningful asynchronous relationships. Both types of analysis are concentrated mostly on Pearson's correlation coefficient and consequently intraday lead-lag relationships (where one of the variables in a pair is time-lagged) are also associated with them. Under the Efficient-Market Hypothesis such relationships are not possible as all information is embedded in the prices, but in real markets we find such dependencies. In this paper we analyse lead-lag relationships of financial instruments and extend known methodology by using mutual information instead of Pearson's correlation coefficient. Mutual information is not only a more general measure, sensitive to non-linear dependencies, but also can lead to a simpler procedure of statistical validation of links between financial instruments. We analyse lagged relationships using New York Stock Exchange 100 data not only on an intraday level, but also for daily stock returns, which have usually been ignored.
NASA Astrophysics Data System (ADS)
Xiong, Yan; Reichenbach, Stephen E.
1999-01-01
Understanding of hand-written Chinese characters is at such a primitive stage that models include some assumptions about hand-written Chinese characters that are simply false. So Maximum Likelihood Estimation (MLE) may not be an optimal method for hand-written Chinese characters recognition. This concern motivates the research effort to consider alternative criteria. Maximum Mutual Information Estimation (MMIE) is an alternative method for parameter estimation that does not derive its rationale from presumed model correctness, but instead examines the pattern-modeling problem in automatic recognition system from an information- theoretic point of view. The objective of MMIE is to find a set of parameters in such that the resultant model allows the system to derive from the observed data as much information as possible about the class. We consider MMIE for recognition of hand-written Chinese characters using on a simplified hidden Markov Random Field. MMIE provides improved performance improvement over MLE in this application.
NASA Astrophysics Data System (ADS)
Beck, L.; Wood, B.; Whitney, S.; Rossi, R.; Spanner, M.; Rodriguez, M.; Rodriguez-Ramirez, A.; Salute, J.; Legters, L.; Roberts, D.; Rejmankova, E.; Washino, R.
1993-08-01
This paper describes a procedure whereby remote sensing and geographic information system (GIS) technologies are used in a sample design to study the habitat of Anopheles albimanus, one of the principle vectors of malaria in Central America. This procedure incorporates Landsat-derived land cover maps with digital elevation and road network data to identify a random selection of larval habitats accessible for field sampling. At the conclusion of the sampling season, the larval counts will be used to determine habitat productivity, and then integrated with information on human settlement to assess where people are at high risk of malaria. This aproach would be appropriate in areas where land cover information is lacking and problems of access constrain field sampling. The use of a GIS also permits other data (such as insecticide spraying data) to the incorporated in the sample design as they arise. This approach would also be pertinent for other tropical vector-borne diseases, particularly where human activities impact disease vector habitat.
DOE Office of Scientific and Technical Information (OSTI.GOV)
O'Donnell, T.J.; Olson, A.J.
1981-08-01
GRAMPS, a graphics language interpreter has been developed in FORTRAN 77 to be used in conjunction with an interactive vector display list processor (Evans and Sutherland Multi-Picture-System). Several of the features of the language make it very useful and convenient for real-time scene construction, manipulation and animation. The GRAMPS language syntax allows natural interaction with scene elements as well as easy, interactive assignment of graphics input devices. GRAMPS facilitates the creation, manipulation and copying of complex nested picture structures. The language has a powerful macro feature that enables new graphics commands to be developed and incorporated interactively. Animation may bemore » achieved in GRAMPS by two different, yet mutually compatible means. Picture structures may contain framed data, which consist of a sequence of fixed objects. These structures may be displayed sequentially to give a traditional frame animation effect. In addition, transformation information on picture structures may be saved at any time in the form of new macro commands that will transform these structures from one saved state to another in a specified number of steps, yielding an interpolated transformation animation effect. An overview of the GRAMPS command structure is given and several examples of application of the language to molecular modeling and animation are presented.« less
Code of Federal Regulations, 2011 CFR
2011-01-01
... agencies, assisted by outside experts, may cooperatively study mutual problems, exchange information, and develop recommendations for action by proper authorities to the end that private rights may be fully...
African American women describe support processes during high-risk pregnancy and postpartum.
Coffman, Sherrilyn; Ray, Marilyn A
2002-01-01
To explore social support processes in low-income African American women during high-risk pregnancy and postpartum. A qualitative grounded theory approach. Interview was the primary data collection technique and was combined with observation, medical chart review, and literature review. A high-risk pregnancy clinic and participants' homes. Ten pregnant women, 3 social network members, and 11 health care providers. Four of the women at high risk tell their in-depth stories in this article: Yolanda, coping with gestational diabetes; Frances, participating in drug rehabilitation; Trista, waiting to deliver a fetus with severe congenital anomalies; and Beatrice, HIV positive and carrying her seventh child. The substantive theory of support developed in the study was termed mutual intentionality. Narratives illustrate the mutual roles that women at high risk and support givers played in the helping process. Support themes included being there, caring, respecting, sharing information, knowing, believing in, and doing for the other. The theorsy of mutual intentionality suggests that social support is a process or transaction involving intentionality. For support to happen, the therapeutic relationship must be valued as a mutual resource.
Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae
2014-01-01
Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications. PMID:24521942
Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae
2014-02-11
Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications.
Research on the Factors Influencing the Measurement Errors of the Discrete Rogowski Coil †
Xu, Mengyuan; Yan, Jing; Geng, Yingsan; Zhang, Kun; Sun, Chao
2018-01-01
An innovative array of magnetic coils (the discrete Rogowski coil—RC) with the advantages of flexible structure, miniaturization and mass producibility is investigated. First, the mutual inductance between the discrete RC and circular and rectangular conductors are calculated using the magnetic vector potential (MVP) method. The results are found to be consistent with those calculated using the finite element method, but the MVP method is simpler and more practical. Then, the influence of conductor section parameters, inclination, and eccentricity on the accuracy of the discrete RC is calculated to provide a reference. Studying the influence of an external current on the discrete RC’s interference error reveals optimal values for length, winding density, and position arrangement of the solenoids. It has also found that eccentricity and interference errors decreasing with increasing number of solenoids. Finally, a discrete RC prototype is devised and manufactured. The experimental results show consistent output characteristics, with the calculated sensitivity and mutual inductance of the discrete RC being very close to the experimental results. The influence of an external conductor on the measurement of the discrete RC is analyzed experimentally, and the results show that interference from an external current decreases with increasing distance between the external and measured conductors. PMID:29534006
Research on the Factors Influencing the Measurement Errors of the Discrete Rogowski Coil.
Xu, Mengyuan; Yan, Jing; Geng, Yingsan; Zhang, Kun; Sun, Chao
2018-03-13
An innovative array of magnetic coils (the discrete Rogowski coil-RC) with the advantages of flexible structure, miniaturization and mass producibility is investigated. First, the mutual inductance between the discrete RC and circular and rectangular conductors are calculated using the magnetic vector potential (MVP) method. The results are found to be consistent with those calculated using the finite element method, but the MVP method is simpler and more practical. Then, the influence of conductor section parameters, inclination, and eccentricity on the accuracy of the discrete RC is calculated to provide a reference. Studying the influence of an external current on the discrete RC's interference error reveals optimal values for length, winding density, and position arrangement of the solenoids. It has also found that eccentricity and interference errors decreasing with increasing number of solenoids. Finally, a discrete RC prototype is devised and manufactured. The experimental results show consistent output characteristics, with the calculated sensitivity and mutual inductance of the discrete RC being very close to the experimental results. The influence of an external conductor on the measurement of the discrete RC is analyzed experimentally, and the results show that interference from an external current decreases with increasing distance between the external and measured conductors.
The use of information theory for the evaluation of biomarkers of aging and physiological age.
Blokh, David; Stambler, Ilia
2017-04-01
The present work explores the application of information theoretical measures, such as entropy and normalized mutual information, for research of biomarkers of aging. The use of information theory affords unique methodological advantages for the study of aging processes, as it allows evaluating non-linear relations between biological parameters, providing the precise quantitative strength of those relations, both for individual and multiple parameters, showing cumulative or synergistic effect. Here we illustrate those capabilities utilizing a dataset on heart disease, including diagnostic parameters routinely available to physicians. The use of information-theoretical methods, utilizing normalized mutual information, revealed the exact amount of information that various diagnostic parameters or their combinations contained about the persons' age. Based on those exact informative values for the correlation of measured parameters with age, we constructed a diagnostic rule (a decision tree) to evaluate physiological age, as compared to chronological age. The present data illustrated that younger subjects suffering from heart disease showed characteristics of people of higher age (higher physiological age). Utilizing information-theoretical measures, with additional data, it may be possible to create further clinically applicable information-theory-based markers and models for the evaluation of physiological age, its relation to age-related diseases and its potential modifications by therapeutic interventions. Copyright © 2017 Elsevier B.V. All rights reserved.
Bacteriophages encode factors required for protection in a symbiotic mutualism.
Oliver, Kerry M; Degnan, Patrick H; Hunter, Martha S; Moran, Nancy A
2009-08-21
Bacteriophages are known to carry key virulence factors for pathogenic bacteria, but their roles in symbiotic bacteria are less well understood. The heritable symbiont Hamiltonella defensa protects the aphid Acyrthosiphon pisum from attack by the parasitoid Aphidius ervi by killing developing wasp larvae. In a controlled genetic background, we show that a toxin-encoding bacteriophage is required to produce the protective phenotype. Phage loss occurs repeatedly in laboratory-held H. defensa-infected aphid clonal lines, resulting in increased susceptibility to parasitism in each instance. Our results show that these mobile genetic elements can endow a bacterial symbiont with benefits that extend to the animal host. Thus, phages vector ecologically important traits, such as defense against parasitoids, within and among symbiont and animal host lineages.
Impedance of curved rectangular spiral coils around a conductive cylinder
NASA Astrophysics Data System (ADS)
Burke, S. K.; Ditchburn, R. J.; Theodoulidis, T. P.
2008-07-01
Eddy-current induction due to a thin conformable coil wrapped around a long conductive cylinder is examined using a second-order vector potential formalism. Compact closed-form expressions are derived for the self- and mutual impedances of curved rectangular spiral coils (i) in free space and (ii) when wrapped around the surface of the cylindrical rod. The validity of these expressions was tested against the results of a systematic series of experiments using a cylindrical Al-alloy rod and conformable coils manufactured using flexible printed-circuit-board technology. The theoretical expressions were in very good agreement with the experimental measurements. The significance of the results for eddy-current nondestructive inspection using flexible coils and flexible coil arrays is discussed.
Strategic Information Systems Planning in Malaysian Public Universities
ERIC Educational Resources Information Center
Ismail, Noor Azizi; Raja Mohd Ali, Raja Haslinda; Mat Saat, Rafeah; Hsbollah, Hafizah Mohamad
2007-01-01
Purpose: The paper's purpose is to investigate the current status, problems and benefits of strategic information systems planning implementation in Malaysian public universities. Design/methodology/approach: The study uses dual but mutually supportive strands of investigation, i.e. a questionnaire survey and interviews. Findings: Malaysian public…
21 CFR 26.71 - Exchange of information.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 21 Food and Drugs 1 2010-04-01 2010-04-01 false Exchange of information. 26.71 Section 26.71 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL MUTUAL RECOGNITION OF PHARMACEUTICAL GOOD MANUFACTURING PRACTICE REPORTS, MEDICAL DEVICE QUALITY SYSTEM AUDIT REPORTS...
Memarian, Negar; Kim, Sally; Dewar, Sandra; Engel, Jerome; Staba, Richard J
2015-09-01
This study sought to predict postsurgical seizure freedom from pre-operative diagnostic test results and clinical information using a rapid automated approach, based on supervised learning methods in patients with drug-resistant focal seizures suspected to begin in temporal lobe. We applied machine learning, specifically a combination of mutual information-based feature selection and supervised learning classifiers on multimodal data, to predict surgery outcome retrospectively in 20 presurgical patients (13 female; mean age±SD, in years 33±9.7 for females, and 35.3±9.4 for males) who were diagnosed with mesial temporal lobe epilepsy (MTLE) and subsequently underwent standard anteromesial temporal lobectomy. The main advantage of the present work over previous studies is the inclusion of the extent of ipsilateral neocortical gray matter atrophy and spatiotemporal properties of depth electrode-recorded seizures as training features for individual patient surgery planning. A maximum relevance minimum redundancy (mRMR) feature selector identified the following features as the most informative predictors of postsurgical seizure freedom in this study's sample of patients: family history of epilepsy, ictal EEG onset pattern (positive correlation with seizure freedom), MRI-based gray matter thickness reduction in the hemisphere ipsilateral to seizure onset, proportion of seizures that first appeared in ipsilateral amygdala to total seizures, age, epilepsy duration, delay in the spread of ipsilateral ictal discharges from site of onset, gender, and number of electrode contacts at seizure onset (negative correlation with seizure freedom). Using these features in combination with a least square support vector machine (LS-SVM) classifier compared to other commonly used classifiers resulted in very high surgical outcome prediction accuracy (95%). Supervised machine learning using multimodal compared to unimodal data accurately predicted postsurgical outcome in patients with atypical MTLE. Published by Elsevier Ltd.
NASA Astrophysics Data System (ADS)
Kurihara, Yosuke; Watanabe, Kajiro; Kobayashi, Kazuyuki; Tanaka, Tanaka
Sleep disorders disturb the recovery from mental and physical fatigues, one of the functions of the sleep. The majority of those who with the disorders are suffering from Sleep Apnea Syndrome (SAS). Continuous Hypoxia during sleep due to SAS cause Circulatory Disturbances, such as hypertension and ischemic heart disease, and Malfunction of Autonomic Nervous System, and other severe complications, often times bringing the suffers to death. In order to prevent these from happening, it is important to detect the SAS in its early stage by monitoring the daily respirations during sleep, and to provide appropriate treatments at medical institutions. In this paper, the Pneumatic Method to detect the Apnea period during sleep is proposed. Pneumatic method can measure heartbeat and respiration signal. Respiration signal can be considered as noise against heartbeat signal, and the decrease in the respiration signal due to Apnea increases the Average Mutual Information of heartbeat. The result of scaling analysis of the average mutual information is defined as threshold to detect the apnea period. The root mean square error between the lengths of Apnea measured by Strain Gauge using for reference and those measured by using the proposed method was 3.1 seconds. And, error of the number of apnea times judged by doctor and proposal method in OSAS patients was 3.3 times.
Automatic registration of ICG images using mutual information and perfusion analysis
NASA Astrophysics Data System (ADS)
Kim, Namkug; Seo, Jong-Mo; Lee, June-goo; Kim, Jong Hyo; Park, Kwangsuk; Yu, Hyeong-Gon; Yu, Young Suk; Chung, Hum
2005-04-01
Introduction: Indocyanin green fundus angiographic images (ICGA) of the eyes is useful method in detecting and characterizing the choroidal neovascularization (CNV), which is the major cause of the blindness over 65 years of age. To investigate the quantitative analysis of the blood flow on ICGA, systematic approach for automatic registration of using mutual information and a quantitative analysis was developed. Methods: Intermittent sequential images of indocyanin green angiography were acquired by Heidelberg retinal angiography that uses the laser scanning system for the image acquisition. Misalignment of the each image generated by the minute eye movement of the patients was corrected by the mutual information method because the distribution of the contrast media on image is changing throughout the time sequences. Several region of interest (ROI) were selected by a physician and the intensities of the selected region were plotted according to the time sequences. Results: The registration of ICGA time sequential images is required not only translate transform but also rotational transform. Signal intensities showed variation based on gamma-variate function depending on ROIs and capillary vessels show more variance of signal intensity than major vessels. CNV showed intermediate variance of signal intensity and prolonged transit time. Conclusion: The resulting registered images can be used not only for quantitative analysis, but also for perfusion analysis. Various investigative approached on CNV using this method will be helpful in the characterization of the lesion and follow-up.
Classical mutual information in mean-field spin glass models
NASA Astrophysics Data System (ADS)
Alba, Vincenzo; Inglis, Stephen; Pollet, Lode
2016-03-01
We investigate the classical Rényi entropy Sn and the associated mutual information In in the Sherrington-Kirkpatrick (S-K) model, which is the paradigm model of mean-field spin glasses. Using classical Monte Carlo simulations and analytical tools we investigate the S-K model in the n -sheet booklet. This is achieved by gluing together n independent copies of the model, and it is the main ingredient for constructing the Rényi entanglement-related quantities. We find a glassy phase at low temperatures, whereas at high temperatures the model exhibits paramagnetic behavior, consistent with the regular S-K model. The temperature of the paramagnetic-glassy transition depends nontrivially on the geometry of the booklet. At high temperatures we provide the exact solution of the model by exploiting the replica symmetry. This is the permutation symmetry among the fictitious replicas that are used to perform disorder averages (via the replica trick). In the glassy phase the replica symmetry has to be broken. Using a generalization of the Parisi solution, we provide analytical results for Sn and In and for standard thermodynamic quantities. Both Sn and In exhibit a volume law in the whole phase diagram. We characterize the behavior of the corresponding densities, Sn/N and In/N , in the thermodynamic limit. Interestingly, at the critical point the mutual information does not exhibit any crossing for different system sizes, in contrast with local spin models.
21 CFR 26.19 - Information relating to quality aspects.
Code of Federal Regulations, 2010 CFR
2010-04-01
... MUTUAL RECOGNITION OF PHARMACEUTICAL GOOD MANUFACTURING PRACTICE REPORTS, MEDICAL DEVICE QUALITY SYSTEM AUDIT REPORTS, AND CERTAIN MEDICAL DEVICE PRODUCT EVALUATION REPORTS: UNITED STATES AND THE EUROPEAN...
Multi-pulse frequency shifted (MPFS) multiple access modulation for ultra wideband
Nekoogar, Faranak [San Ramon, CA; Dowla, Farid U [Castro Valley, CA
2012-01-24
The multi-pulse frequency shifted technique uses mutually orthogonal short duration pulses o transmit and receive information in a UWB multiuser communication system. The multiuser system uses the same pulse shape with different frequencies for the reference and data for each user. Different users have a different pulse shape (mutually orthogonal to each other) and different transmit and reference frequencies. At the receiver, the reference pulse is frequency shifted to match the data pulse and a correlation scheme followed by a hard decision block detects the data.
Let the right one in: a microeconomic approach to partner choice in mutualisms.
Archetti, Marco; Ubeda, Francisco; Fudenberg, Drew; Green, Jerry; Pierce, Naomi E; Yu, Douglas W
2011-01-01
One of the main problems impeding the evolution of cooperation is partner choice. When information is asymmetric (the quality of a potential partner is known only to himself), it may seem that partner choice is not possible without signaling. Many mutualisms, however, exist without signaling, and the mechanisms by which hosts might select the right partners are unclear. Here we propose a general mechanism of partner choice, "screening," that is similar to the economic theory of mechanism design. Imposing the appropriate costs and rewards may induce the informed individuals to screen themselves according to their types and therefore allow a noninformed individual to establish associations with the correct partners in the absence of signaling. Several types of biological symbioses are good candidates for screening, including bobtail squid, ant-plants, gut microbiomes, and many animal and plant species that produce reactive oxygen species. We describe a series of diagnostic tests for screening. Screening games can apply to the cases where by-products, partner fidelity feedback, or host sanctions do not apply, therefore explaining the evolution of mutualism in systems where it is impossible for potential symbionts to signal their cooperativeness beforehand and where the host does not punish symbiont misbehavior.
Visual navigation in insects: coupling of egocentric and geocentric information
Wehner; Michel; Antonsen
1996-01-01
Social hymenopterans such as bees and ants are central-place foragers; they regularly depart from and return to fixed positions in their environment. In returning to the starting point of their foraging excursion or to any other point, they could resort to two fundamentally different ways of navigation by using either egocentric or geocentric systems of reference. In the first case, they would rely on information continuously collected en route (path integration, dead reckoning), i.e. integrate all angles steered and all distances covered into a mean home vector. In the second case, they are expected, at least by some authors, to use a map-based system of navigation, i.e. to obtain positional information by virtue of the spatial position they occupy within a larger environmental framework. In bees and ants, path integration employing a skylight compass is the predominant mechanism of navigation, but geocentred landmark-based information is used as well. This information is obtained while the animal is dead-reckoning and, hence, added to the vector course. For example, the image of the horizon skyline surrounding the nest entrance is retinotopically stored while the animal approaches the goal along its vector course. As shown in desert ants (genus Cataglyphis), there is neither interocular nor intraocular transfer of landmark information. Furthermore, this retinotopically fixed, and hence egocentred, neural snapshot is linked to an external (geocentred) system of reference. In this way, geocentred information might more and more complement and potentially even supersede the egocentred information provided by the path-integration system. In competition experiments, however, Cataglyphis never frees itself of its homeward-bound vector - its safety-line, so to speak - by which it is always linked to home. Vector information can also be transferred to a longer-lasting (higher-order) memory. There is no need to invoke the concept of the mental analogue of a topographic map - a metric map - assembled by the insect navigator. The flexible use of vectors, snapshots and landmark-based routes suffices to interpret the insect's behaviour. The cognitive-map approach in particular, and the representational paradigm in general, are discussed.
Zhu, Yu; Lu, Gui-Hua; Bian, Zhuo-Wu; Wu, Feng-Yao; Pang, Yan-Jun; Wang, Xiao-Ming; Yang, Rong-Wu; Tang, Cheng-Yi; Qi, Jin-Liang; Yang, Yong-Hua
2017-11-13
Shikonin is a naphthoquinone secondary metabolite with important medicinal value and is found in Lithospermum erythrorhizon. Considering the limited knowledge on the membrane transport mechanism of shikonin, this study investigated such molecular mechanism. We successfully isolated an ATP-binding cassette protein gene, LeMDR, from L. erythrorhizon. LeMDR is predominantly expressed in L. erythrorhizon roots, where shikonin accumulated. Functional analysis of LeMDR by using the yeast cell expression system revealed that LeMDR is possibly involved in the shikonin efflux transport. The accumulation of shikonin is lower in yeast cells transformed with LeMDR-overexpressing vector than that with empty vector. The transgenic hairy roots of L. erythrorhizon overexpressing LeMDR (MDRO) significantly enhanced shikonin production, whereas the RNA interference of LeMDR (MDRi) displayed a reverse trend. Moreover, the mRNA expression level of LeMDR was up-regulated by treatment with shikonin and shikonin-positive regulators, methyl jasmonate and indole-3-acetic acid. There might be a relationship of mutual regulation between the expression level of LeMDR and shikonin biosynthesis. Our findings demonstrated the important role of LeMDR in transmembrane transport and biosynthesis of shikonin.
Woo, Ha-Na; Lee, Won Il; Kim, Ji Hyun; Ahn, Jeonghyun; Han, Jeong Hee; Lim, Sue Yeon; Lee, Won Woo; Lee, Heuiran
2015-12-01
A proof-of-concept study is presented using dual gene therapy that employed a small hairpin RNA (shRNA) specific for mammalian target of rapamycin (mTOR) and a herpes simplex virus-thymidine kinase (HSV-TK) gene to inhibit the growth of tumors. Recombinant adeno-associated virus (rAAV) vectors containing a mutant TK gene (sc39TK) were transduced into HeLa cells, and the prodrug ganciclovir (GCV) was administered to establish a suicide gene-therapy strategy. Additionally, rAAV vectors expressing an mTOR-targeted shRNA were employed to suppress mTOR-dependent tumor growth. GCV selectively induced death in tumor cells expressing TK, and the mTOR-targeted shRNA altered the cell cycle to impair tumor growth. Combining the TK-GCV system with mTOR inhibition suppressed tumor growth to a greater extent than that achieved with either treatment alone. Furthermore, HSV-TK expression and mTOR inhibition did not mutually interfere with each other. In conclusion, gene therapy that combines the TK-GCV system and mTOR inhibition shows promise as a novel strategy for cancer therapy.
Velocimetry using scintillation of a laser beam for a laser-based gas-flux monitor
NASA Astrophysics Data System (ADS)
Kagawa, Naoki; Wada, Osami; Koga, Ryuji
1999-05-01
This paper describes a velocimetry system using scintillation of a laser-beam with spatial filters based on sensor arrays for a laser- based gas flux monitor. In the eddy correlation method, gas flux is obtained by mutual relation between the gas density and the flow velocity. The velocimetry system is developed to support the flow velocity monitor portion of the laser-based gas flux monitor with a long span for measurement. In order to sense not only the flow velocity but also the flow direction, two photo diode arrays are arranged with difference of a quarter period of the weighting function between them; the two output signals from the sensor arrays have phase difference of either (pi) /2 or -(pi) /2 depending on the sense of flow direction. In order to obtain the flow velocity and the flow direction instantly, an electronic apparatus built by the authors extracts frequency and phase from crude outputs of the pair of sensors. A feasibility of the velocimetry was confirmed indoors by measurement of the flow- velocity vector of the convection. Measured flow-velocity vector of the upward flow agreed comparatively with results of an ultrasonic anemometer.
NASA Astrophysics Data System (ADS)
Kaporin, I. E.
2012-02-01
In order to precondition a sparse symmetric positive definite matrix, its approximate inverse is examined, which is represented as the product of two sparse mutually adjoint triangular matrices. In this way, the solution of the corresponding system of linear algebraic equations (SLAE) by applying the preconditioned conjugate gradient method (CGM) is reduced to performing only elementary vector operations and calculating sparse matrix-vector products. A method for constructing the above preconditioner is described and analyzed. The triangular factor has a fixed sparsity pattern and is optimal in the sense that the preconditioned matrix has a minimum K-condition number. The use of polynomial preconditioning based on Chebyshev polynomials makes it possible to considerably reduce the amount of scalar product operations (at the cost of an insignificant increase in the total number of arithmetic operations). The possibility of an efficient massively parallel implementation of the resulting method for solving SLAEs is discussed. For a sequential version of this method, the results obtained by solving 56 test problems from the Florida sparse matrix collection (which are large-scale and ill-conditioned) are presented. These results show that the method is highly reliable and has low computational costs.
Mutual information and redundancy in spontaneous communication between cortical neurons.
Szczepanski, J; Arnold, M; Wajnryb, E; Amigó, J M; Sanchez-Vives, M V
2011-03-01
An important question in neural information processing is how neurons cooperate to transmit information. To study this question, we resort to the concept of redundancy in the information transmitted by a group of neurons and, at the same time, we introduce a novel concept for measuring cooperation between pairs of neurons called relative mutual information (RMI). Specifically, we studied these two parameters for spike trains generated by neighboring neurons from the primary visual cortex in the awake, freely moving rat. The spike trains studied here were spontaneously generated in the cortical network, in the absence of visual stimulation. Under these conditions, our analysis revealed that while the value of RMI oscillated slightly around an average value, the redundancy exhibited a behavior characterized by a higher variability. We conjecture that this combination of approximately constant RMI and greater variable redundancy makes information transmission more resistant to noise disturbances. Furthermore, the redundancy values suggest that neurons can cooperate in a flexible way during information transmission. This mostly occurs via a leading neuron with higher transmission rate or, less frequently, through the information rate of the whole group being higher than the sum of the individual information rates-in other words in a synergetic manner. The proposed method applies not only to the stationary, but also to locally stationary neural signals.
Low-dimensional approximation searching strategy for transfer entropy from non-uniform embedding
2018-01-01
Transfer entropy from non-uniform embedding is a popular tool for the inference of causal relationships among dynamical subsystems. In this study we present an approach that makes use of low-dimensional conditional mutual information quantities to decompose the original high-dimensional conditional mutual information in the searching procedure of non-uniform embedding for significant variables at different lags. We perform a series of simulation experiments to assess the sensitivity and specificity of our proposed method to demonstrate its advantage compared to previous algorithms. The results provide concrete evidence that low-dimensional approximations can help to improve the statistical accuracy of transfer entropy in multivariate causality analysis and yield a better performance over other methods. The proposed method is especially efficient as the data length grows. PMID:29547669
NASA Astrophysics Data System (ADS)
Quian Quiroga, R.; Kraskov, A.; Kreuz, T.; Grassberger, P.
2002-04-01
We study the synchronization between left and right hemisphere rat electroencephalographic (EEG) channels by using various synchronization measures, namely nonlinear interdependences, phase synchronizations, mutual information, cross correlation, and the coherence function. In passing we show a close relation between two recently proposed phase synchronization measures and we extend the definition of one of them. In three typical examples we observe that except mutual information, all these measures give a useful quantification that is hard to be guessed beforehand from the raw data. Despite their differences, results are qualitatively the same. Therefore, we claim that the applied measures are valuable for the study of synchronization in real data. Moreover, in the particular case of EEG signals their use as complementary variables could be of clinical relevance.
Entropy, energy, and entanglement of localized states in bent triatomic molecules
NASA Astrophysics Data System (ADS)
Yuan, Qiang; Hou, Xi-Wen
2017-05-01
The dynamics of quantum entropy, energy, and entanglement is studied for various initial states in an important spectroscopic Hamiltonian of bent triatomic molecules H2O, D2O, and H2S. The total quantum correlation is quantified in terms of the mutual information and the entanglement by the concurrence borrowed from the theory of quantum information. The Pauli entropy and the intramolecular energy usually used in the theory of molecules are calculated to establish a possible relationship between both theories. Sections of two quantities among these four quantities are introduced to visualize such relationship. Analytic and numerical simulations demonstrate that if an initial state is taken to be the stretch- or the bend-vibrationally localized state, the mutual information, the Pauli entropy, and the concurrence are dominant-positively correlated while they are dominantly anti-correlated with the interacting energy among three anharmonic vibrational modes. In particular, such correlation is more distinct for the localized state with high excitations in the bending mode. The nice quasi-periodicity of those quantities in D2O molecule reveals that this molecule prepared in the localized state in the stretching or the bending mode can be more appreciated for molecular quantum computation. However, the dynamical correlations of those quantities behave irregularly for the dislocalized states. Moreover, the hierarchy of the mutual information and the Pauli entropy is explicitly proved. Quantum entropy and energy in every vibrational mode are investigated. Thereby, the relation between bipartite and tripartite entanglements is discussed as well. Those are useful for the understanding of quantum correlations in high-dimensional states in polyatomic molecules from quantum information and intramolecular dynamics.
Network model of human aging: Frailty limits and information measures
NASA Astrophysics Data System (ADS)
Farrell, Spencer G.; Mitnitski, Arnold B.; Rockwood, Kenneth; Rutenberg, Andrew D.
2016-11-01
Aging is associated with the accumulation of damage throughout a persons life. Individual health can be assessed by the Frailty Index (FI). The FI is calculated simply as the proportion f of accumulated age-related deficits relative to the total, leading to a theoretical maximum of f ≤1 . Observational studies have generally reported a much more stringent bound, with f ≤fmax<1 . The value of fmax in observational studies appears to be nonuniversal, but fmax≈0.7 is often reported. A previously developed network model of individual aging was unable to recover fmax<1 while retaining the other observed phenomenology of increasing f and mortality rates with age. We have developed a computationally accelerated network model that also allows us to tune the scale-free network exponent α . The network exponent α significantly affects the growth of mortality rates with age. However, we are only able to recover fmax by also introducing a deficit sensitivity parameter 1 -q , which is equivalent to a false-negative rate q . Our value of q =0.3 is comparable to finite sensitivities of age-related deficits with respect to mortality that are often reported in the literature. In light of nonzero q , we use mutual information I to provide a nonparametric measure of the predictive value of the FI with respect to individual mortality. We find that I is only modestly degraded by q <1 , and this degradation is mitigated when increasing number of deficits are included in the FI. We also find that the information spectrum, i.e., the mutual information of individual deficits versus connectivity, has an approximately power-law dependence that depends on the network exponent α . Mutual information I is therefore a useful tool for characterizing the network topology of aging populations.
Multipass Target Search in Natural Environments
Otte, Michael W.; Sofge, Donald; Gupta, Satyandra K.
2017-01-01
Consider a disaster scenario where search and rescue workers must search difficult to access buildings during an earthquake or flood. Often, finding survivors a few hours sooner results in a dramatic increase in saved lives, suggesting the use of drones for expedient rescue operations. Entropy can be used to quantify the generation and resolution of uncertainty. When searching for targets, maximizing mutual information of future sensor observations will minimize expected target location uncertainty by minimizing the entropy of the future estimate. Motion planning for multi-target autonomous search requires planning over an area with an imperfect sensor and may require multiple passes, which is hindered by the submodularity property of mutual information. Further, mission duration constraints must be handled accordingly, requiring consideration of the vehicle’s dynamics to generate feasible trajectories and must plan trajectories spanning the entire mission duration, something which most information gathering algorithms are incapable of doing. If unanticipated changes occur in an uncertain environment, new plans must be generated quickly. In addition, planning multipass trajectories requires evaluating path dependent rewards, requiring planning in the space of all previously selected actions, compounding the problem. We present an anytime algorithm for autonomous multipass target search in natural environments. The algorithm is capable of generating long duration dynamically feasible multipass coverage plans that maximize mutual information using a variety of techniques such as ϵ-admissible heuristics to speed up the search. To the authors’ knowledge this is the first attempt at efficiently solving multipass target search problems of such long duration. The proposed algorithm is based on best first branch and bound and is benchmarked against state of the art algorithms adapted to the problem in natural Simplex environments, gathering the most information in the given search time. PMID:29099087
Aggression and Moral Development: Integrating Social Information Processing and Moral Domain Models
ERIC Educational Resources Information Center
Arsenio, William F.; Lemerise, Elizabeth A.
2004-01-01
Social information processing and moral domain theories have developed in relative isolation from each other despite their common focus on intentional harm and victimization, and mutual emphasis on social cognitive processes in explaining aggressive, morally relevant behaviors. This article presents a selective summary of these literatures with…
Federal Register 2010, 2011, 2012, 2013, 2014
2012-08-22
.... Type of Request: New Collection. Originating Office: Bureau of Educational and Cultural Affairs, ECA/EC... of technology. Abstract of proposed collection: This collection of information is under the provisions of the Mutual Educational and Cultural Exchange Act, as amended, and its implementing regulations...
78 FR 15800 - 30-Day Notice of Proposed Information Collection: Exchange Student Survey
Federal Register 2010, 2011, 2012, 2013, 2014
2013-03-12
... Collection. Originating Office: Educational and Cultural Affairs (ECA/ PE/C/PY). Form Number: SV2012-0007... automated collection techniques or other forms of information technology. Please note that comments... provisions of the Mutual Educational and Cultural Exchange Act, as amended, and the Exchange Visitor Program...
Information Seeking and Avoidance Behavior in School Library Distance Learning
ERIC Educational Resources Information Center
Du, Yunfei
2010-01-01
Library science students in school librarianship were surveyed to determine their information seeking and avoidance behaviors in Web-based online environments. Two coping styles were identified among students. Barriers to student online collaboration, such as individual preferences, concerns on efficiency, and lack of mutual trust, were observed.…
The Information Ambassadors: The 1990-91 Library/Book Fellows.
ERIC Educational Resources Information Center
American Library Association, Chicago, IL.
The American Library Association (ALA) Library/Book Fellows program began in 1986 with a grant from the U.S. Information Agency. The program's purpose is threefold: (1) to increase international understanding through the establishment of professional and personal relationships and the accomplishment of mutual goals; (2) to promote international…
ERIC Educational Resources Information Center
2003
This publication describes efforts in the United Kingdom (UK) to develop mutually beneficial, collaborative partnerships between businesses and communities that promote digital inclusion (access to information and communication technologies). Case studies of different kinds of relationships are listed, including UK online centers, schools, events…
Term Dependence: A Basis for Luhn and Zipf Models.
ERIC Educational Resources Information Center
Losee, Robert M.
2001-01-01
Discusses relationships between the frequency-based characteristics of neighboring terms in natural language and the rank or frequency of the terms. Topics include information theory measures, including expected mutual information measure (EMIM); entropy and rank; Luhn's model of term aboutness; Zipf's law; and implications for indexing and…
Ontology for Vector Surveillance and Management
LOZANO-FUENTES, SAUL; BANDYOPADHYAY, ARITRA; COWELL, LINDSAY G.; GOLDFAIN, ALBERT; EISEN, LARS
2013-01-01
Ontologies, which are made up by standardized and defined controlled vocabulary terms and their interrelationships, are comprehensive and readily searchable repositories for knowledge in a given domain. The Open Biomedical Ontologies (OBO) Foundry was initiated in 2001 with the aims of becoming an “umbrella” for life-science ontologies and promoting the use of ontology development best practices. A software application (OBO-Edit; *.obo file format) was developed to facilitate ontology development and editing. The OBO Foundry now comprises over 100 ontologies and candidate ontologies, including the NCBI organismal classification ontology (NCBITaxon), the Mosquito Insecticide Resistance Ontology (MIRO), the Infectious Disease Ontology (IDO), the IDOMAL malaria ontology, and ontologies for mosquito gross anatomy and tick gross anatomy. We previously developed a disease data management system for dengue and malaria control programs, which incorporated a set of information trees built upon ontological principles, including a “term tree” to promote the use of standardized terms. In the course of doing so, we realized that there were substantial gaps in existing ontologies with regards to concepts, processes, and, especially, physical entities (e.g., vector species, pathogen species, and vector surveillance and management equipment) in the domain of surveillance and management of vectors and vector-borne pathogens. We therefore produced an ontology for vector surveillance and management, focusing on arthropod vectors and vector-borne pathogens with relevance to humans or domestic animals, and with special emphasis on content to support operational activities through inclusion in databases, data management systems, or decision support systems. The Vector Surveillance and Management Ontology (VSMO) includes >2,200 unique terms, of which the vast majority (>80%) were newly generated during the development of this ontology. One core feature of the VSMO is the linkage, through the has_vector relation, of arthropod species to the pathogenic microorganisms for which they serve as biological vectors. We also recognized and addressed a potential roadblock for use of the VSMO by the vector-borne disease community: the difficulty in extracting information from OBO-Edit ontology files (*.obo files) and exporting the information to other file formats. A novel ontology explorer tool was developed to facilitate extraction and export of information from the VSMO *.obo file into lists of terms and their associated unique IDs in *.txt or *.csv file formats. These lists can then be imported into a database or data management system for use as select lists with predefined terms. This is an important step to ensure that the knowledge contained in our ontology can be put into practical use. PMID:23427646
Ontology for vector surveillance and management.
Lozano-Fuentes, Saul; Bandyopadhyay, Aritra; Cowell, Lindsay G; Goldfain, Albert; Eisen, Lars
2013-01-01
Ontologies, which are made up by standardized and defined controlled vocabulary terms and their interrelationships, are comprehensive and readily searchable repositories for knowledge in a given domain. The Open Biomedical Ontologies (OBO) Foundry was initiated in 2001 with the aims of becoming an "umbrella" for life-science ontologies and promoting the use of ontology development best practices. A software application (OBO-Edit; *.obo file format) was developed to facilitate ontology development and editing. The OBO Foundry now comprises over 100 ontologies and candidate ontologies, including the NCBI organismal classification ontology (NCBITaxon), the Mosquito Insecticide Resistance Ontology (MIRO), the Infectious Disease Ontology (IDO), the IDOMAL malaria ontology, and ontologies for mosquito gross anatomy and tick gross anatomy. We previously developed a disease data management system for dengue and malaria control programs, which incorporated a set of information trees built upon ontological principles, including a "term tree" to promote the use of standardized terms. In the course of doing so, we realized that there were substantial gaps in existing ontologies with regards to concepts, processes, and, especially, physical entities (e.g., vector species, pathogen species, and vector surveillance and management equipment) in the domain of surveillance and management of vectors and vector-borne pathogens. We therefore produced an ontology for vector surveillance and management, focusing on arthropod vectors and vector-borne pathogens with relevance to humans or domestic animals, and with special emphasis on content to support operational activities through inclusion in databases, data management systems, or decision support systems. The Vector Surveillance and Management Ontology (VSMO) includes >2,200 unique terms, of which the vast majority (>80%) were newly generated during the development of this ontology. One core feature of the VSMO is the linkage, through the has vector relation, of arthropod species to the pathogenic microorganisms for which they serve as biological vectors. We also recognized and addressed a potential roadblock for use of the VSMO by the vector-borne disease community: the difficulty in extracting information from OBO-Edit ontology files (*.obo files) and exporting the information to other file formats. A novel ontology explorer tool was developed to facilitate extraction and export of information from the VSMO*.obo file into lists of terms and their associated unique IDs in *.txt or *.csv file formats. These lists can then be imported into a database or data management system for use as select lists with predefined terms. This is an important step to ensure that the knowledge contained in our ontology can be put into practical use.
Power, Sinead; Hegarty, Josephine
2010-01-01
Peer support programs are associated with the provision of emotional, informational, and appraisal support. The benefits of peer support for women with breast cancer include reduced social isolation, enhanced coping, and access to information. The aim of this study was to conduct a pre- and post-program evaluation of a 7-week facilitated breast cancer peer support program in a cancer support house. Women with primary breast cancer (n = 8) participated in pre- and post-program focus groups. The interviews were recorded and were transcribed verbatim by the researcher. The data were analyzed using content analysis. Eight themes were identified. The key themes emerging from the pre and post programme focus groups included: The need for mutual identification; Post-treatment isolation; Help with moving on; The impact of hair loss; Consolidation of information; Enablement/empowerment; The importance of the cancer survivor; Mutual sharing. It is essential that facilitated peer support programs are tailored to meet the support needs of women with breast cancer. There is a particular need to facilitate mutual sharing and support for hair loss within these programs. Implications for practice emerging from this study include the importance of pre- and post-program evaluations in identifying whether peer support programs meet the expectations of women with breast cancer, the need for peer/professional programs to support women with treatment-induced hair loss, the importance of including cancer survivors in support programs, and the need to allow more informal sharing to occur in facilitated peer support programs.
A multivariate extension of mutual information for growing neural networks.
Ball, Kenneth R; Grant, Christopher; Mundy, William R; Shafer, Timothy J
2017-11-01
Recordings of neural network activity in vitro are increasingly being used to assess the development of neural network activity and the effects of drugs, chemicals and disease states on neural network function. The high-content nature of the data derived from such recordings can be used to infer effects of compounds or disease states on a variety of important neural functions, including network synchrony. Historically, synchrony of networks in vitro has been assessed either by determination of correlation coefficients (e.g. Pearson's correlation), by statistics estimated from cross-correlation histograms between pairs of active electrodes, and/or by pairwise mutual information and related measures. The present study examines the application of Normalized Multiinformation (NMI) as a scalar measure of shared information content in a multivariate network that is robust with respect to changes in network size. Theoretical simulations are designed to investigate NMI as a measure of complexity and synchrony in a developing network relative to several alternative approaches. The NMI approach is applied to these simulations and also to data collected during exposure of in vitro neural networks to neuroactive compounds during the first 12 days in vitro, and compared to other common measures, including correlation coefficients and mean firing rates of neurons. NMI is shown to be more sensitive to developmental effects than first order synchronous and nonsynchronous measures of network complexity. Finally, NMI is a scalar measure of global (rather than pairwise) mutual information in a multivariate network, and hence relies on less assumptions for cross-network comparisons than historical approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.
A Lightweight RFID Mutual Authentication Protocol Based on Physical Unclonable Function.
Xu, He; Ding, Jie; Li, Peng; Zhu, Feng; Wang, Ruchuan
2018-03-02
With the fast development of the Internet of Things, Radio Frequency Identification (RFID) has been widely applied into many areas. Nevertheless, security problems of the RFID technology are also gradually exposed, when it provides life convenience. In particular, the appearance of a large number of fake and counterfeit goods has caused massive loss for both producers and customers, for which the clone tag is a serious security threat. If attackers acquire the complete information of a tag, they can then obtain the unique identifier of the tag by some technological means. In general, because there is no extra identifier of a tag, it is difficult to distinguish an original tag and its clone one. Once the legal tag data is obtained, attackers can be able to clone this tag. Therefore, this paper shows an efficient RFID mutual verification protocol. This protocol is based on the Physical Unclonable Function (PUF) and the lightweight cryptography to achieve efficient verification of a single tag. The protocol includes three process: tag recognition, mutual verification and update. The tag recognition is that the reader recognizes the tag; mutual verification is that the reader and tag mutually verify the authenticity of each other; update is supposed to maintain the latest secret key for the following verification. Analysis results show that this protocol has a good balance between performance and security.
A Lightweight RFID Mutual Authentication Protocol Based on Physical Unclonable Function
Ding, Jie; Zhu, Feng; Wang, Ruchuan
2018-01-01
With the fast development of the Internet of Things, Radio Frequency Identification (RFID) has been widely applied into many areas. Nevertheless, security problems of the RFID technology are also gradually exposed, when it provides life convenience. In particular, the appearance of a large number of fake and counterfeit goods has caused massive loss for both producers and customers, for which the clone tag is a serious security threat. If attackers acquire the complete information of a tag, they can then obtain the unique identifier of the tag by some technological means. In general, because there is no extra identifier of a tag, it is difficult to distinguish an original tag and its clone one. Once the legal tag data is obtained, attackers can be able to clone this tag. Therefore, this paper shows an efficient RFID mutual verification protocol. This protocol is based on the Physical Unclonable Function (PUF) and the lightweight cryptography to achieve efficient verification of a single tag. The protocol includes three process: tag recognition, mutual verification and update. The tag recognition is that the reader recognizes the tag; mutual verification is that the reader and tag mutually verify the authenticity of each other; update is supposed to maintain the latest secret key for the following verification. Analysis results show that this protocol has a good balance between performance and security. PMID:29498684
Adding localization information in a fingerprint binary feature vector representation
NASA Astrophysics Data System (ADS)
Bringer, Julien; Despiegel, Vincent; Favre, Mélanie
2011-06-01
At BTAS'10, a new framework to transform a fingerprint minutiae template into a binary feature vector of fixed length is described. A fingerprint is characterized by its similarity with a fixed number set of representative local minutiae vicinities. This approach by representative leads to a fixed length binary representation, and, as the approach is local, it enables to deal with local distortions that may occur between two acquisitions. We extend this construction to incorporate additional information in the binary vector, in particular on localization of the vicinities. We explore the use of position and orientation information. The performance improvement is promising for utilization into fast identification algorithms or into privacy protection algorithms.
Road Damage Extraction from Post-Earthquake Uav Images Assisted by Vector Data
NASA Astrophysics Data System (ADS)
Chen, Z.; Dou, A.
2018-04-01
Extraction of road damage information after earthquake has been regarded as urgent mission. To collect information about stricken areas, Unmanned Aerial Vehicle can be used to obtain images rapidly. This paper put forward a novel method to detect road damage and bring forward a coefficient to assess road accessibility. With the assistance of vector road data, image data of the Jiuzhaigou Ms7.0 Earthquake is tested. In the first, the image is clipped according to vector buffer. Then a large-scale segmentation is applied to remove irrelevant objects. Thirdly, statistics of road features are analysed, and damage information is extracted. Combining with the on-filed investigation, the extraction result is effective.
Information and communication technology in cross-industry glossaries
NASA Astrophysics Data System (ADS)
Pronichev, A. N.; Polyakov, E. V.; Nikitaev, V. G.; Vasilyev, N. P.; Dmitrieva, V. V.; Ulina, I. V.
2017-01-01
Interdisciplinary glossary is proposed to ensure mutual understanding of specialists from various fields of science and technology. Glossary is designed with application of information technologies. The field of information technologies is considered. It is necessary for the understanding and cooperation of specialists in various areas. The technological solutions and applications for multi-disciplinary areas, results of testing of the developed techniques are presented.
A Reward-Maximizing Spiking Neuron as a Bounded Rational Decision Maker.
Leibfried, Felix; Braun, Daniel A
2015-08-01
Rate distortion theory describes how to communicate relevant information most efficiently over a channel with limited capacity. One of the many applications of rate distortion theory is bounded rational decision making, where decision makers are modeled as information channels that transform sensory input into motor output under the constraint that their channel capacity is limited. Such a bounded rational decision maker can be thought to optimize an objective function that trades off the decision maker's utility or cumulative reward against the information processing cost measured by the mutual information between sensory input and motor output. In this study, we interpret a spiking neuron as a bounded rational decision maker that aims to maximize its expected reward under the computational constraint that the mutual information between the neuron's input and output is upper bounded. This abstract computational constraint translates into a penalization of the deviation between the neuron's instantaneous and average firing behavior. We derive a synaptic weight update rule for such a rate distortion optimizing neuron and show in simulations that the neuron efficiently extracts reward-relevant information from the input by trading off its synaptic strengths against the collected reward.
The locking-decoding frontier for generic dynamics.
Dupuis, Frédéric; Florjanczyk, Jan; Hayden, Patrick; Leung, Debbie
2013-11-08
It is known that the maximum classical mutual information, which can be achieved between measurements on pairs of quantum systems, can drastically underestimate the quantum mutual information between them. In this article, we quantify this distinction between classical and quantum information by demonstrating that after removing a logarithmic-sized quantum system from one half of a pair of perfectly correlated bitstrings, even the most sensitive pair of measurements might yield only outcomes essentially independent of each other. This effect is a form of information locking but the definition we use is strictly stronger than those used previously. Moreover, we find that this property is generic, in the sense that it occurs when removing a random subsystem. As such, the effect might be relevant to statistical mechanics or black hole physics. While previous works had always assumed a uniform message, we assume only a min-entropy bound and also explore the effect of entanglement. We find that classical information is strongly locked almost until it can be completely decoded. Finally, we exhibit a quantum key distribution protocol that is 'secure' in the sense of accessible information but in which leakage of even a logarithmic number of bits compromises the secrecy of all others.
Activity Recognition on Streaming Sensor Data.
Krishnan, Narayanan C; Cook, Diane J
2014-02-01
Many real-world applications that focus on addressing needs of a human, require information about the activities being performed by the human in real-time. While advances in pervasive computing have lead to the development of wireless and non-intrusive sensors that can capture the necessary activity information, current activity recognition approaches have so far experimented on either a scripted or pre-segmented sequence of sensor events related to activities. In this paper we propose and evaluate a sliding window based approach to perform activity recognition in an on line or streaming fashion; recognizing activities as and when new sensor events are recorded. To account for the fact that different activities can be best characterized by different window lengths of sensor events, we incorporate the time decay and mutual information based weighting of sensor events within a window. Additional contextual information in the form of the previous activity and the activity of the previous window is also appended to the feature describing a sensor window. The experiments conducted to evaluate these techniques on real-world smart home datasets suggests that combining mutual information based weighting of sensor events and adding past contextual information into the feature leads to best performance for streaming activity recognition.
The locking-decoding frontier for generic dynamics
Dupuis, Frédéric; Florjanczyk, Jan; Hayden, Patrick; Leung, Debbie
2013-01-01
It is known that the maximum classical mutual information, which can be achieved between measurements on pairs of quantum systems, can drastically underestimate the quantum mutual information between them. In this article, we quantify this distinction between classical and quantum information by demonstrating that after removing a logarithmic-sized quantum system from one half of a pair of perfectly correlated bitstrings, even the most sensitive pair of measurements might yield only outcomes essentially independent of each other. This effect is a form of information locking but the definition we use is strictly stronger than those used previously. Moreover, we find that this property is generic, in the sense that it occurs when removing a random subsystem. As such, the effect might be relevant to statistical mechanics or black hole physics. While previous works had always assumed a uniform message, we assume only a min-entropy bound and also explore the effect of entanglement. We find that classical information is strongly locked almost until it can be completely decoded. Finally, we exhibit a quantum key distribution protocol that is ‘secure’ in the sense of accessible information but in which leakage of even a logarithmic number of bits compromises the secrecy of all others. PMID:24204183
MIDER: network inference with mutual information distance and entropy reduction.
Villaverde, Alejandro F; Ross, John; Morán, Federico; Banga, Julio R
2014-01-01
The prediction of links among variables from a given dataset is a task referred to as network inference or reverse engineering. It is an open problem in bioinformatics and systems biology, as well as in other areas of science. Information theory, which uses concepts such as mutual information, provides a rigorous framework for addressing it. While a number of information-theoretic methods are already available, most of them focus on a particular type of problem, introducing assumptions that limit their generality. Furthermore, many of these methods lack a publicly available implementation. Here we present MIDER, a method for inferring network structures with information theoretic concepts. It consists of two steps: first, it provides a representation of the network in which the distance among nodes indicates their statistical closeness. Second, it refines the prediction of the existing links to distinguish between direct and indirect interactions and to assign directionality. The method accepts as input time-series data related to some quantitative features of the network nodes (such as e.g. concentrations, if the nodes are chemical species). It takes into account time delays between variables, and allows choosing among several definitions and normalizations of mutual information. It is general purpose: it may be applied to any type of network, cellular or otherwise. A Matlab implementation including source code and data is freely available (http://www.iim.csic.es/~gingproc/mider.html). The performance of MIDER has been evaluated on seven different benchmark problems that cover the main types of cellular networks, including metabolic, gene regulatory, and signaling. Comparisons with state of the art information-theoretic methods have demonstrated the competitive performance of MIDER, as well as its versatility. Its use does not demand any a priori knowledge from the user; the default settings and the adaptive nature of the method provide good results for a wide range of problems without requiring tuning.
40 CFR 503.27 - Recordkeeping.
Code of Federal Regulations, 2010 CFR
2010-07-01
... penalty of law, that the information that will be used to determine compliance with the pathogen... requirements is met) and the vector attraction reduction requirement in (insert one of the vector attraction... met. (iv) A description of how one of the vector attraction reduction requirements in § 503.33 (b)(1...
40 CFR 503.27 - Recordkeeping.
Code of Federal Regulations, 2014 CFR
2014-07-01
... penalty of law, that the information that will be used to determine compliance with the pathogen... requirements is met) and the vector attraction reduction requirement in (insert one of the vector attraction... met. (iv) A description of how one of the vector attraction reduction requirements in § 503.33 (b)(1...
40 CFR 503.27 - Recordkeeping.
Code of Federal Regulations, 2012 CFR
2012-07-01
... penalty of law, that the information that will be used to determine compliance with the pathogen... requirements is met) and the vector attraction reduction requirement in (insert one of the vector attraction... met. (iv) A description of how one of the vector attraction reduction requirements in § 503.33 (b)(1...
40 CFR 503.27 - Recordkeeping.
Code of Federal Regulations, 2013 CFR
2013-07-01
... penalty of law, that the information that will be used to determine compliance with the pathogen... requirements is met) and the vector attraction reduction requirement in (insert one of the vector attraction... met. (iv) A description of how one of the vector attraction reduction requirements in § 503.33 (b)(1...
A SWOT Analysis of the Various Backup Scenarios Used in Electronic Medical Record Systems.
Seo, Hwa Jeong; Kim, Hye Hyeon; Kim, Ju Han
2011-09-01
Electronic medical records (EMRs) are increasingly being used by health care services. Currently, if an EMR shutdown occurs, even for a moment, patient safety and care can be seriously impacted. Our goal was to determine the methodology needed to develop an effective and reliable EMR backup system. Our "independent backup system by medical organizations" paradigm implies that individual medical organizations develop their own EMR backup systems within their organizations. A "personal independent backup system" is defined as an individual privately managing his/her own medical records, whereas in a "central backup system by the government" the government controls all the data. A "central backup system by private enterprises" implies that individual companies retain control over their own data. A "cooperative backup system among medical organizations" refers to a networked system established through mutual agreement. The "backup system based on mutual trust between an individual and an organization" means that the medical information backup system at the organizational level is established through mutual trust. Through the use of SWOT analysis it can be shown that cooperative backup among medical organizations is possible to be established through a network composed of various medical agencies and that it can be managed systematically. An owner of medical information only grants data access to the specific person who gave the authorization for backup based on the mutual trust between an individual and an organization. By employing SWOT analysis, we concluded that a linkage among medical organizations or between an individual and an organization can provide an efficient backup system.
A SWOT Analysis of the Various Backup Scenarios Used in Electronic Medical Record Systems
Seo, Hwa Jeong; Kim, Hye Hyeon
2011-01-01
Objectives Electronic medical records (EMRs) are increasingly being used by health care services. Currently, if an EMR shutdown occurs, even for a moment, patient safety and care can be seriously impacted. Our goal was to determine the methodology needed to develop an effective and reliable EMR backup system. Methods Our "independent backup system by medical organizations" paradigm implies that individual medical organizations develop their own EMR backup systems within their organizations. A "personal independent backup system" is defined as an individual privately managing his/her own medical records, whereas in a "central backup system by the government" the government controls all the data. A "central backup system by private enterprises" implies that individual companies retain control over their own data. A "cooperative backup system among medical organizations" refers to a networked system established through mutual agreement. The "backup system based on mutual trust between an individual and an organization" means that the medical information backup system at the organizational level is established through mutual trust. Results Through the use of SWOT analysis it can be shown that cooperative backup among medical organizations is possible to be established through a network composed of various medical agencies and that it can be managed systematically. An owner of medical information only grants data access to the specific person who gave the authorization for backup based on the mutual trust between an individual and an organization. Conclusions By employing SWOT analysis, we concluded that a linkage among medical organizations or between an individual and an organization can provide an efficient backup system. PMID:22084811
NASA Astrophysics Data System (ADS)
Watanabe, Jobu
2009-09-01
Mutual information can be given a directional sense by introducing a time lag in one of the variables. In an author's previous study, to investigate the network dynamics of human brain regions, lagged transinformation (LTI) was introduced using time delayed mutual information. The LTI makes it possible to quantify the time course of dynamic information transfer between regions in the temporal domain. The LTI was applied to functional magnetic resonance imaging (fMRI) data involved in neural processing of the transformation and comparison from three-dimensional (3D) visual information to a two-dimensional (2D) location to calculate directed information flows between the activated brain regions. In the present study, for more precise estimation of LTI, Kalman filter smoothing was applied to the same fMRI data. Because the smoothing method exploits the full length of the time series data for the estimation, its application increases the precision. Large information flows were found from the bilateral prefrontal cortices to the parietal cortices. The results suggest that information of the 3D images stored as working memory was retrieved and transferred from the prefrontal cortices to the parietal cortices for comparison with information of the 2D images.
NASA Technical Reports Server (NTRS)
Imhoff, M. L.; Vermillion, C. H.; Khan, F. A.
1984-01-01
An investigation to examine the utility of spaceborne radar image data to malaria vector control programs is described. Specific tasks involve an analysis of radar illumination geometry vs information content, the synergy of radar and multispectral data mergers, and automated information extraction techniques.
Cyber Mutual Assistance Workshop Report
2018-02-01
Information Technology, Nuclear Reactors, Materials/Waste, Defense Industrial Base, Critical Manufacturing, Food/ Agriculture Government Facilities and...Manufacturing, Food/ Agriculture Government Facilities and Chemical, Commercial Facilities [DHS 2017c]. Distributed Energy Resources (DER) are
Sigstad, Hanne Marie Høybråten
2017-03-01
This study examined how adolescents with mild intellectual disabilities define qualities of friendship and discussed the extent to which these definitions adhere to established definitions of close friendship. The study was based on qualitative interviews with 11 adolescents in secondary school. The interviews were supplemented with information from six parents. A thematic structural analysis was used to identify themes. Qualities of friendship were categorized as mutual preference, mutual enjoyment, shared interactions, care, mutual trust and bonding. The criteria for close friendship seem to be fulfilled, albeit to a moderate degree. Closeness and reciprocity appear to be significant in this study, although these features have been considered less relevant within this target group in previous research. Differences in definitions may explain divergent results compared with other studies, and the need to achieve equivalence in friendship may be another.
12-Step Interventions and Mutual Support Programs for Substance Use Disorders: An Overview
Donovan, Dennis M.; Ingalsbe, Michelle H.; Benbow, James; Daley, Dennis C.
2013-01-01
Social workers and other behavioral health professionals are likely to encounter individuals with substance use disorders in a variety of practice settings outside of specialty treatment. 12-Step mutual support programs represent readily available, no cost community-based resources for such individuals; however, practitioners are often unfamiliar with such programs. The present article provides a brief overview of 12-Step programs, the positive substance use and psychosocial outcomes associated with active 12-Step involvement, and approaches ranging from ones that can be utilized by social workers in any practice setting to those developed for specialty treatment programs to facilitate engagement in 12-Step meetings and recovery activities. The goal is to familiarize social workers with 12-Step approaches so that they are better able to make informed referrals that match clients to mutual support groups that best meet the individual’s needs and maximize the likelihood of engagement and positive outcomes. PMID:23731422
Conditional Tests for Localizing Trait Genes
Di, Yanming; Thompson, Elizabeth A.
2009-01-01
Background/Aims With pedigree data, genetic linkage can be detected using inheritance vector tests, which explore the discrepancy between the posterior distribution of the inheritance vectors given observed trait values and the prior distribution of the inheritance vectors. In this paper, we propose conditional inheritance vector tests for linkage localization. These conditional tests can also be used to detect additional linkage signals in the presence of previously detected causal genes. Methods For linkage localization, we propose to perform inheritance vector tests conditioning on the inheritance vectors at two positions bounding a test region. We can detect additional linkage signals by conducting a further conditional test in a region with no previously detected genes. We use randomized p values to extend the marginal and conditional tests when the inheritance vectors cannot be completely determined from genetic marker data. Results We conduct simulation studies to compare and contrast the marginal and the conditional tests and to demonstrate that randomized p values can capture both the significance and the uncertainty in the test results. Conclusions The simulation results demonstrate that the proposed conditional tests provide useful localization information, and with informative marker data, the uncertainty in randomized marginal and conditional test results is small. PMID:19439976
Vontas, John; Mitsakakis, Konstantinos; Zengerle, Roland; Yewhalaw, Delenasaw; Sikaala, Chadwick Haadezu; Etang, Josiane; Fallani, Matteo; Carman, Bill; Müller, Pie; Chouaïbou, Mouhamadou; Coleman, Marlize; Coleman, Michael
2016-01-01
Malaria is a life-threatening disease that caused more than 400,000 deaths in sub-Saharan Africa in 2015. Mass prevention of the disease is best achieved by vector control which heavily relies on the use of insecticides. Monitoring mosquito vector populations is an integral component of control programs and a prerequisite for effective interventions. Several individual methods are used for this task; however, there are obstacles to their uptake, as well as challenges in organizing, interpreting and communicating vector population data. The Horizon 2020 project "DMC-MALVEC" consortium will develop a fully integrated and automated multiplex vector-diagnostic platform (LabDisk) for characterizing mosquito populations in terms of species composition, Plasmodium infections and biochemical insecticide resistance markers. The LabDisk will be interfaced with a Disease Data Management System (DDMS), a custom made data management software which will collate and manage data from routine entomological monitoring activities providing information in a timely fashion based on user needs and in a standardized way. The ResistanceSim, a serious game, a modern ICT platform that uses interactive ways of communicating guidelines and exemplifying good practices of optimal use of interventions in the health sector will also be a key element. The use of the tool will teach operational end users the value of quality data (relevant, timely and accurate) to make informed decisions. The integrated system (LabDisk, DDMS & ResistanceSim) will be evaluated in four malaria endemic countries, representative of the vector control challenges in sub-Saharan Africa, (Cameroon, Ivory Coast, Ethiopia and Zambia), highly representative of malaria settings with different levels of endemicity and vector control challenges, to support informed decision-making in vector control and disease management.
Liu, Ying; Ciliax, Brian J; Borges, Karin; Dasigi, Venu; Ram, Ashwin; Navathe, Shamkant B; Dingledine, Ray
2004-01-01
One of the key challenges of microarray studies is to derive biological insights from the unprecedented quatities of data on gene-expression patterns. Clustering genes by functional keyword association can provide direct information about the nature of the functional links among genes within the derived clusters. However, the quality of the keyword lists extracted from biomedical literature for each gene significantly affects the clustering results. We extracted keywords from MEDLINE that describes the most prominent functions of the genes, and used the resulting weights of the keywords as feature vectors for gene clustering. By analyzing the resulting cluster quality, we compared two keyword weighting schemes: normalized z-score and term frequency-inverse document frequency (TFIDF). The best combination of background comparison set, stop list and stemming algorithm was selected based on precision and recall metrics. In a test set of four known gene groups, a hierarchical algorithm correctly assigned 25 of 26 genes to the appropriate clusters based on keywords extracted by the TDFIDF weighting scheme, but only 23 og 26 with the z-score method. To evaluate the effectiveness of the weighting schemes for keyword extraction for gene clusters from microarray profiles, 44 yeast genes that are differentially expressed during the cell cycle were used as a second test set. Using established measures of cluster quality, the results produced from TFIDF-weighted keywords had higher purity, lower entropy, and higher mutual information than those produced from normalized z-score weighted keywords. The optimized algorithms should be useful for sorting genes from microarray lists into functionally discrete clusters.
U.S. Information Policy and Cultural Diplomacy. Headline Series No. 308.
ERIC Educational Resources Information Center
Ninkovich, Frank
This booklet examines U.S. involvement with cultural diplomacy, emphasizing exchanges of persons and ideas that have lasting effects on relatively small numbers of people and information programs using the mass media to influence large numbers of people. Whereas the cultural exchange programs are internationalist in nature, promoting mutual and…
ERIC Educational Resources Information Center
Budde, Stephen; Schene, Patricia
2004-01-01
There is increasing interest among policymakers and practitioners in tapping the potential of family, friends, volunteers, peer support groups, and mutual aid organizations to help prevent violence. The popularity of these informal social support (ISS) interventions stems, in part, from their flexibility, responsiveness to individual needs, and…
Internet Resources for Reference: Finance and Investment.
ERIC Educational Resources Information Center
Mai, Brent Alan
1997-01-01
When called upon to aid in filtering through finance and investment information on the Internet, the business librarian is also faced with knowing what is available and how to find it. Web sites are identified that provide information about stocks and their exchanges, mutual funds, bonds, company annual reports, and taxes. (Author/AEF)
78 FR 64197 - Renewable Energy Policy Business Roundtable in Livermore, CA
Federal Register 2010, 2011, 2012, 2013, 2014
2013-10-28
... allowed the private sector to explore areas of mutual concern and share with government officials their... rolling basis in the order they are received. Selected companies will be contacted with information about... send an email to [email protected] with the following information. Name of Applicant Company Name Company...
U.S. Information Ambassadors: The 1991-92 Library Fellows and Debriefing Report.
ERIC Educational Resources Information Center
Doyle, Robert P.
The American Library Association (ALA) Library Fellows program began in 1986 with a grant from the U.S. Information Agency. The program's purpose is threefold: (1) to increase international understanding through the establishment of professional and personal relationships and the accomplishment of mutual goals; (2) to promote international sharing…
An information theory framework for dynamic functional domain connectivity.
Vergara, Victor M; Miller, Robyn; Calhoun, Vince
2017-06-01
Dynamic functional network connectivity (dFNC) analyzes time evolution of coherent activity in the brain. In this technique dynamic changes are considered for the whole brain. This paper proposes an information theory framework to measure information flowing among subsets of functional networks call functional domains. Our method aims at estimating bits of information contained and shared among domains. The succession of dynamic functional states is estimated at the domain level. Information quantity is based on the probabilities of observing each dynamic state. Mutual information measurement is then obtained from probabilities across domains. Thus, we named this value the cross domain mutual information (CDMI). Strong CDMIs were observed in relation to the subcortical domain. Domains related to sensorial input, motor control and cerebellum form another CDMI cluster. Information flow among other domains was seldom found. Other methods of dynamic connectivity focus on whole brain dFNC matrices. In the current framework, information theory is applied to states estimated from pairs of multi-network functional domains. In this context, we apply information theory to measure information flow across functional domains. Identified CDMI clusters point to known information pathways in the basal ganglia and also among areas of sensorial input, patterns found in static functional connectivity. In contrast, CDMI across brain areas of higher level cognitive processing follow a different pattern that indicates scarce information sharing. These findings show that employing information theory to formally measured information flow through brain domains reveals additional features of functional connectivity. Copyright © 2017 Elsevier B.V. All rights reserved.
Chen, Yun; Yang, Hui
2016-01-01
In the era of big data, there are increasing interests on clustering variables for the minimization of data redundancy and the maximization of variable relevancy. Existing clustering methods, however, depend on nontrivial assumptions about the data structure. Note that nonlinear interdependence among variables poses significant challenges on the traditional framework of predictive modeling. In the present work, we reformulate the problem of variable clustering from an information theoretic perspective that does not require the assumption of data structure for the identification of nonlinear interdependence among variables. Specifically, we propose the use of mutual information to characterize and measure nonlinear correlation structures among variables. Further, we develop Dirichlet process (DP) models to cluster variables based on the mutual-information measures among variables. Finally, orthonormalized variables in each cluster are integrated with group elastic-net model to improve the performance of predictive modeling. Both simulation and real-world case studies showed that the proposed methodology not only effectively reveals the nonlinear interdependence structures among variables but also outperforms traditional variable clustering algorithms such as hierarchical clustering. PMID:27966581
Chen, Yun; Yang, Hui
2016-12-14
In the era of big data, there are increasing interests on clustering variables for the minimization of data redundancy and the maximization of variable relevancy. Existing clustering methods, however, depend on nontrivial assumptions about the data structure. Note that nonlinear interdependence among variables poses significant challenges on the traditional framework of predictive modeling. In the present work, we reformulate the problem of variable clustering from an information theoretic perspective that does not require the assumption of data structure for the identification of nonlinear interdependence among variables. Specifically, we propose the use of mutual information to characterize and measure nonlinear correlation structures among variables. Further, we develop Dirichlet process (DP) models to cluster variables based on the mutual-information measures among variables. Finally, orthonormalized variables in each cluster are integrated with group elastic-net model to improve the performance of predictive modeling. Both simulation and real-world case studies showed that the proposed methodology not only effectively reveals the nonlinear interdependence structures among variables but also outperforms traditional variable clustering algorithms such as hierarchical clustering.
Identifying functionally informative evolutionary sequence profiles.
Gil, Nelson; Fiser, Andras
2018-04-15
Multiple sequence alignments (MSAs) can provide essential input to many bioinformatics applications, including protein structure prediction and functional annotation. However, the optimal selection of sequences to obtain biologically informative MSAs for such purposes is poorly explored, and has traditionally been performed manually. We present Selection of Alignment by Maximal Mutual Information (SAMMI), an automated, sequence-based approach to objectively select an optimal MSA from a large set of alternatives sampled from a general sequence database search. The hypothesis of this approach is that the mutual information among MSA columns will be maximal for those MSAs that contain the most diverse set possible of the most structurally and functionally homogeneous protein sequences. SAMMI was tested to select MSAs for functional site residue prediction by analysis of conservation patterns on a set of 435 proteins obtained from protein-ligand (peptides, nucleic acids and small substrates) and protein-protein interaction databases. Availability and implementation: A freely accessible program, including source code, implementing SAMMI is available at https://github.com/nelsongil92/SAMMI.git. andras.fiser@einstein.yu.edu. Supplementary data are available at Bioinformatics online.
Tightening the entropic uncertainty bound in the presence of quantum memory
NASA Astrophysics Data System (ADS)
Adabi, F.; Salimi, S.; Haseli, S.
2016-06-01
The uncertainty principle is a fundamental principle in quantum physics. It implies that the measurement outcomes of two incompatible observables cannot be predicted simultaneously. In quantum information theory, this principle can be expressed in terms of entropic measures. M. Berta et al. [Nat. Phys. 6, 659 (2010), 10.1038/nphys1734] have indicated that uncertainty bound can be altered by considering a particle as a quantum memory correlating with the primary particle. In this article, we obtain a lower bound for entropic uncertainty in the presence of a quantum memory by adding an additional term depending on the Holevo quantity and mutual information. We conclude that our lower bound will be tightened with respect to that of Berta et al. when the accessible information about measurements outcomes is less than the mutual information about the joint state. Some examples have been investigated for which our lower bound is tighter than Berta et al.'s lower bound. Using our lower bound, a lower bound for the entanglement of formation of bipartite quantum states has been obtained, as well as an upper bound for the regularized distillable common randomness.
Electromagnetic potential vectors and the Lagrangian of a charged particle
NASA Technical Reports Server (NTRS)
Shebalin, John V.
1992-01-01
Maxwell's equations can be shown to imply the existence of two independent three-dimensional potential vectors. A comparison between the potential vectors and the electric and magnetic field vectors, using a spatial Fourier transformation, reveals six independent potential components but only four independent electromagnetic field components for each mode. Although the electromagnetic fields determined by Maxwell's equations give a complete description of all possible classical electromagnetic phenomena, potential vectors contains more information and allow for a description of such quantum mechanical phenomena as the Aharonov-Bohm effect. A new result is that a charged particle Lagrangian written in terms of potential vectors automatically contains a 'spontaneous symmetry breaking' potential.
Effects of OCR Errors on Ranking and Feedback Using the Vector Space Model.
ERIC Educational Resources Information Center
Taghva, Kazem; And Others
1996-01-01
Reports on the performance of the vector space model in the presence of OCR (optical character recognition) errors in information retrieval. Highlights include precision and recall, a full-text test collection, smart vector representation, impact of weighting parameters, ranking variability, and the effect of relevance feedback. (Author/LRW)
Mosquito distribution in a saltmarsh: determinants of eggs in a variable environment.
Rowbottom, Raylea; Carver, Scott; Barmuta, Leon A; Weinstein, Philip; Allen, Geoff R
2017-06-01
Two saltmarsh mosquitoes dominate the transmission of Ross River virus (RRV, Togoviridae: Alphavirus), one of Australia's most prominent mosquito-borne diseases. Ecologically, saltmarshes vary in their structure, including habitat types, hydrological regimes, and diversity of aquatic fauna, all of which drive mosquito oviposition behavior. Understanding the distribution of vector mosquitoes within saltmarshes can inform early warning systems, surveillance, and management of vector populations. The aim of this study was to identify the distribution of Ae. camptorhynchus, a known vector for RRV, across a saltmarsh and investigate the influence that other invertebrate assemblage might have on Ae. camptorhynchus egg dispersal. We demonstrate that vegetation is a strong indicator for Ae. camptorhynchus egg distribution, and this was not correlated with elevation or other invertebrates located at this saltmarsh. Also, habitats within this marsh are less frequently inundated, resulting in dryer conditions. We conclude that this information can be applied in vector surveillance and monitoring of temperate saltmarsh environments and also provides a baseline for future investigations into understanding mosquito vector habitat requirements. © 2017 The Society for Vector Ecology.
Alternate entropy measure for assessing volatility in financial markets.
Bose, Ranjan; Hamacher, Kay
2012-11-01
We propose two alternate information theoretical approaches to assess non-Gaussian fluctuations in the return dynamics of financial markets. Specifically, we use superinformation, which is a measure of the disorder of the entropy of time series. We argue on theoretical grounds on its usefulness and show that it can be applied effectively for analyzing returns. A study of stock market data for over five years has been carried out using this approach. We show how superinformation helps to identify and classify important signals in the time series. The financial crisis of 2008 comes out very clearly in the superinformation plots. In addition, we introduce the super mutual information. Distinct super mutual information signatures are observed that might be used to mitigate idiosyncratic risk. The universality of our approach has been tested by carrying out the analysis for the 100 stocks listed in S&P100 index. The average superinformation values for the S&P100 stocks correlates very well with the VIX.
Alternate entropy measure for assessing volatility in financial markets
NASA Astrophysics Data System (ADS)
Bose, Ranjan; Hamacher, Kay
2012-11-01
We propose two alternate information theoretical approaches to assess non-Gaussian fluctuations in the return dynamics of financial markets. Specifically, we use superinformation, which is a measure of the disorder of the entropy of time series. We argue on theoretical grounds on its usefulness and show that it can be applied effectively for analyzing returns. A study of stock market data for over five years has been carried out using this approach. We show how superinformation helps to identify and classify important signals in the time series. The financial crisis of 2008 comes out very clearly in the superinformation plots. In addition, we introduce the super mutual information. Distinct super mutual information signatures are observed that might be used to mitigate idiosyncratic risk. The universality of our approach has been tested by carrying out the analysis for the 100 stocks listed in S&P100 index. The average superinformation values for the S&P100 stocks correlates very well with the VIX.
Mutual information-based LPI optimisation for radar network
NASA Astrophysics Data System (ADS)
Shi, Chenguang; Zhou, Jianjiang; Wang, Fei; Chen, Jun
2015-07-01
Radar network can offer significant performance improvement for target detection and information extraction employing spatial diversity. For a fixed number of radars, the achievable mutual information (MI) for estimating the target parameters may extend beyond a predefined threshold with full power transmission. In this paper, an effective low probability of intercept (LPI) optimisation algorithm is presented to improve LPI performance for radar network. Based on radar network system model, we first provide Schleher intercept factor for radar network as an optimisation metric for LPI performance. Then, a novel LPI optimisation algorithm is presented, where for a predefined MI threshold, Schleher intercept factor for radar network is minimised by optimising the transmission power allocation among radars in the network such that the enhanced LPI performance for radar network can be achieved. The genetic algorithm based on nonlinear programming (GA-NP) is employed to solve the resulting nonconvex and nonlinear optimisation problem. Some simulations demonstrate that the proposed algorithm is valuable and effective to improve the LPI performance for radar network.
Computing quantum discord is NP-complete
NASA Astrophysics Data System (ADS)
Huang, Yichen
2014-03-01
We study the computational complexity of quantum discord (a measure of quantum correlation beyond entanglement), and prove that computing quantum discord is NP-complete. Therefore, quantum discord is computationally intractable: the running time of any algorithm for computing quantum discord is believed to grow exponentially with the dimension of the Hilbert space so that computing quantum discord in a quantum system of moderate size is not possible in practice. As by-products, some entanglement measures (namely entanglement cost, entanglement of formation, relative entropy of entanglement, squashed entanglement, classical squashed entanglement, conditional entanglement of mutual information, and broadcast regularization of mutual information) and constrained Holevo capacity are NP-hard/NP-complete to compute. These complexity-theoretic results are directly applicable in common randomness distillation, quantum state merging, entanglement distillation, superdense coding, and quantum teleportation; they may offer significant insights into quantum information processing. Moreover, we prove the NP-completeness of two typical problems: linear optimization over classical states and detecting classical states in a convex set, providing evidence that working with classical states is generically computationally intractable.
Women's experiences of social support during the first year following primary breast cancer surgery.
Drageset, Sigrunn; Lindstrøm, Torill Christine; Giske, Tove; Underlid, Kjell
2016-06-01
The aim of this qualitative follow-up study was to describe women's individual experiences of social support during their first year after primary breast cancer surgery. Individual semi-structured interviews with 10 women 1 year after surgery analysed by Kvales' meaning condensation method. Sharing experiences, being understood as an individual, continuity, and information and explanations were themes identified. Sharing mutual experiences increased the women's knowledge regarding cancer, increased experience of support and minimised rumination. After 1 year, the women felt that the network around them had 'normalised' and was less supportive. Being seen as a person, not as 'a diagnosis being treated', and continuity of professional support were important, giving feelings of security and trust. The women felt uncertainty after loss of professional support post-treatment. Information and explanations regarding treatment and treatment-related problems were essential. Mutual sharing of experiences is an important part of social support. Continuity, availability, information and respect were essential aspects of experienced professional support. © 2015 Nordic College of Caring Science.
Tripartite counterfactual quantum cryptography
NASA Astrophysics Data System (ADS)
Salih, Hatim
2014-07-01
We show how two distrustful parties, "Bob" and "Charlie," can share a secret key with the help of a mutually trusted "Alice" counterfactually; that is, with no information-carrying particles traveling between any of the three.
Raimondi, G; Chillemi, S; Michelassi, C; Di Garbo, A; Varanini, M; Legramante, J; Balocchi, R
2002-07-01
Orthostatic intolerance is the most serious symptom of cardiovascular deconditioning induced by microgravity. However, the exact mechanisms underlying these alterations have not been completely clarified. Several methods for studying the time series of systolic arterial pressure and RR interval have been proposed both in the time and in the frequency domain. However, these methods did not produce definitive results. In fact heart rate and arterial pressure show a complex pattern of global variability which is likely due to non linear feedback which involves the autonomic nervous system and to "stochastic" influences. Aim of this study was to evaluate the degree of interdependence between the mechanisms responsible for the variability of SAP and RR signals in subjects exposed to head down (HD). This quantification was achieved by using Mutual Information (MI).
Mutual information measures applied to EEG signals for sleepiness characterization.
Melia, Umberto; Guaita, Marc; Vallverdú, Montserrat; Embid, Cristina; Vilaseca, Isabel; Salamero, Manel; Santamaria, Joan
2015-03-01
Excessive daytime sleepiness (EDS) is one of the main symptoms of several sleep related disorders with a great impact on the patient lives. While many studies have been carried out in order to assess daytime sleepiness, the automatic EDS detection still remains an open problem. In this work, a novel approach to this issue based on non-linear dynamical analysis of EEG signal was proposed. Multichannel EEG signals were recorded during five maintenance of wakefulness (MWT) and multiple sleep latency (MSLT) tests alternated throughout the day from patients suffering from sleep disordered breathing. A group of 20 patients with excessive daytime sleepiness (EDS) was compared with a group of 20 patients without daytime sleepiness (WDS), by analyzing 60-s EEG windows in waking state. Measures obtained from cross-mutual information function (CMIF) and auto-mutual-information function (AMIF) were calculated in the EEG. These functions permitted a quantification of the complexity properties of the EEG signal and the non-linear couplings between different zones of the scalp. Statistical differences between EDS and WDS groups were found in β band during MSLT events (p-value < 0.0001). WDS group presented more complexity than EDS in the occipital zone, while a stronger nonlinear coupling between occipital and frontal zones was detected in EDS patients than in WDS. The AMIF and CMIF measures yielded sensitivity and specificity above 80% and AUC of ROC above 0.85 in classifying EDS and WDS patients. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.
Geometric k-nearest neighbor estimation of entropy and mutual information
NASA Astrophysics Data System (ADS)
Lord, Warren M.; Sun, Jie; Bollt, Erik M.
2018-03-01
Nonparametric estimation of mutual information is used in a wide range of scientific problems to quantify dependence between variables. The k-nearest neighbor (knn) methods are consistent, and therefore expected to work well for a large sample size. These methods use geometrically regular local volume elements. This practice allows maximum localization of the volume elements, but can also induce a bias due to a poor description of the local geometry of the underlying probability measure. We introduce a new class of knn estimators that we call geometric knn estimators (g-knn), which use more complex local volume elements to better model the local geometry of the probability measures. As an example of this class of estimators, we develop a g-knn estimator of entropy and mutual information based on elliptical volume elements, capturing the local stretching and compression common to a wide range of dynamical system attractors. A series of numerical examples in which the thickness of the underlying distribution and the sample sizes are varied suggest that local geometry is a source of problems for knn methods such as the Kraskov-Stögbauer-Grassberger estimator when local geometric effects cannot be removed by global preprocessing of the data. The g-knn method performs well despite the manipulation of the local geometry. In addition, the examples suggest that the g-knn estimators can be of particular relevance to applications in which the system is large, but the data size is limited.
Improving semi-text-independent method of writer verification using difference vector
NASA Astrophysics Data System (ADS)
Li, Xin; Ding, Xiaoqing
2009-01-01
The semi-text-independent method of writer verification based on the linear framework is a method that can use all characters of two handwritings to discriminate the writers in the condition of knowing the text contents. The handwritings are allowed to just have small numbers of even totally different characters. This fills the vacancy of the classical text-dependent methods and the text-independent methods of writer verification. Moreover, the information, what every character is, is used for the semi-text-independent method in this paper. Two types of standard templates, generated from many writer-unknown handwritten samples and printed samples of each character, are introduced to represent the content information of each character. The difference vectors of the character samples are gotten by subtracting the standard templates from the original feature vectors and used to replace the original vectors in the process of writer verification. By removing a large amount of content information and remaining the style information, the verification accuracy of the semi-text-independent method is improved. On a handwriting database involving 30 writers, when the query handwriting and the reference handwriting are composed of 30 distinct characters respectively, the average equal error rate (EER) of writer verification reaches 9.96%. And when the handwritings contain 50 characters, the average EER falls to 6.34%, which is 23.9% lower than the EER of not using the difference vectors.
Support Vector Machines: Relevance Feedback and Information Retrieval.
ERIC Educational Resources Information Center
Drucker, Harris; Shahrary, Behzad; Gibbon, David C.
2002-01-01
Compares support vector machines (SVMs) to Rocchio, Ide regular and Ide dec-hi algorithms in information retrieval (IR) of text documents using relevancy feedback. If the preliminary search is so poor that one has to search through many documents to find at least one relevant document, then SVM is preferred. Includes nine tables. (Contains 24…
Optimized scalable network switch
Blumrich, Matthias A [Ridgefield, CT; Chen, Dong [Croton On Hudson, NY; Coteus, Paul W [Yorktown Heights, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Takken, Todd E [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY
2007-12-04
In a massively parallel computing system having a plurality of nodes configured in m multi-dimensions, each node including a computing device, a method for routing packets towards their destination nodes is provided which includes generating at least one of a 2m plurality of compact bit vectors containing information derived from downstream nodes. A multilevel arbitration process in which downstream information stored in the compact vectors, such as link status information and fullness of downstream buffers, is used to determine a preferred direction and virtual channel for packet transmission. Preferred direction ranges are encoded and virtual channels are selected by examining the plurality of compact bit vectors. This dynamic routing method eliminates the necessity of routing tables, thus enhancing scalability of the switch.
Optimized scalable network switch
Blumrich, Matthias A.; Chen, Dong; Coteus, Paul W.
2010-02-23
In a massively parallel computing system having a plurality of nodes configured in m multi-dimensions, each node including a computing device, a method for routing packets towards their destination nodes is provided which includes generating at least one of a 2m plurality of compact bit vectors containing information derived from downstream nodes. A multilevel arbitration process in which downstream information stored in the compact vectors, such as link status information and fullness of downstream buffers, is used to determine a preferred direction and virtual channel for packet transmission. Preferred direction ranges are encoded and virtual channels are selected by examining the plurality of compact bit vectors. This dynamic routing method eliminates the necessity of routing tables, thus enhancing scalability of the switch.
2015-01-07
DOCUMENTATION PAGE Form Approved OMB No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour per...reviewing this collection of information . Send comments regarding this burden estimate or any other aspect of this collection of information , including...suggestions for reducing this burden to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports
Handheld Synthetic Array Final Report, Part B
2014-12-01
Multiple Model IMU Inertial Measurement Unit 4/154 IEEE Institute of Electrical and Electronics Engineers KF Kalman Filter KL Kullback - Leibler LAMBDA...important metric in information theory is the input–output mutual information (MI) that is used as an indicator of how much coded information can be...tracking using best- fitting Gaussian distributions,” Proc. Int. Conf. Inform . Fusion, pp. 1–8, 2005. [liv] L. Svensson, “On the Bayesian Cramér-Rao
MIDER: Network Inference with Mutual Information Distance and Entropy Reduction
Villaverde, Alejandro F.; Ross, John; Morán, Federico; Banga, Julio R.
2014-01-01
The prediction of links among variables from a given dataset is a task referred to as network inference or reverse engineering. It is an open problem in bioinformatics and systems biology, as well as in other areas of science. Information theory, which uses concepts such as mutual information, provides a rigorous framework for addressing it. While a number of information-theoretic methods are already available, most of them focus on a particular type of problem, introducing assumptions that limit their generality. Furthermore, many of these methods lack a publicly available implementation. Here we present MIDER, a method for inferring network structures with information theoretic concepts. It consists of two steps: first, it provides a representation of the network in which the distance among nodes indicates their statistical closeness. Second, it refines the prediction of the existing links to distinguish between direct and indirect interactions and to assign directionality. The method accepts as input time-series data related to some quantitative features of the network nodes (such as e.g. concentrations, if the nodes are chemical species). It takes into account time delays between variables, and allows choosing among several definitions and normalizations of mutual information. It is general purpose: it may be applied to any type of network, cellular or otherwise. A Matlab implementation including source code and data is freely available (http://www.iim.csic.es/~gingproc/mider.html). The performance of MIDER has been evaluated on seven different benchmark problems that cover the main types of cellular networks, including metabolic, gene regulatory, and signaling. Comparisons with state of the art information–theoretic methods have demonstrated the competitive performance of MIDER, as well as its versatility. Its use does not demand any a priori knowledge from the user; the default settings and the adaptive nature of the method provide good results for a wide range of problems without requiring tuning. PMID:24806471
Hessen, Dag O; Tombre, Ingunn M; van Geest, Gerben; Alfsnes, Kristian
2017-02-01
Migratory connectivity by birds may mutually affect different ecosystems over large distances. Populations of geese overwintering in southern areas while breeding in high-latitude ecosystems have increased strongly over the past decades. The increase is likely due to positive feedbacks caused by climate change at both wintering, stopover sites and breeding grounds, land-use practices at the overwintering grounds and protection from hunting. Here we show how increasing goose populations in temperate regions, and increased breeding success in the Arctic, entail a positive feedback with strong impacts on Arctic freshwater ecosystems in the form of eutrophication. This may again strongly affect community composition and productivity of the ponds, due to increased nutrient loadings or birds serving as vectors for new species.
Electromagnetic gauge as an integration condition: De Broglie's argument revisited and expanded
NASA Astrophysics Data System (ADS)
Costa de Beauregard, O.
1992-12-01
Einstein's mass-energy equivalence law, argues de Broglie, by fixing the zero of the potential energy of a system, ipso facto selects a gauge in electromagnetism. We examine how this works in electrostatics and in magnetostatics and bring in, as a “trump card,” the familiar, but highly peculiar, system consisting of a toroidal magnet m and a current coil c, where none of the mutual energy W resides in the vacuum. We propose the principle of a crucial test for measuring the fractions of W residing in m and in c; if the latter is nonzero, the (fieldless) vector potential has physicality. Also, using induction for transferring energy from the magnet to a superconducting current, we prove that W is equipartitioned between m and c.
Numerically Integrated Orbits of the Major Saturnian Satellites fit to Earthbased Observations
NASA Technical Reports Server (NTRS)
Jacobson, R. A.; Vaughan, R. M.
1993-01-01
We have fit numerically integrated orbits of the eight major satellites of Saturn to all available astrometric and meridian circle observations for the period of 1971 to 1992. The integration was carried out in cartesian coordinates in the J2000 system. The force model included the gravitational effects of the oblate primary, the mutual perturbations of the satellites, and perturbations due to Jupiter and the Sun. Values of the gravitational parameters of the Saturnian system, e.g. planet and satellite masses, were taken from Campbell, et. al., 1989, only the epoch state vectors of the satellites were adjusted to obtain orbits which fit the observations. All astrometric data was processed in the form of satellite relative positions which were weighted according to observer and opposition to reflect the varying data quality...
NASA Technical Reports Server (NTRS)
Muellerschoen, R. J.
1988-01-01
A unified method to permute vector-stored upper-triangular diagonal factorized covariance (UD) and vector stored upper-triangular square-root information filter (SRIF) arrays is presented. The method involves cyclical permutation of the rows and columns of the arrays and retriangularization with appropriate square-root-free fast Givens rotations or elementary slow Givens reflections. A minimal amount of computation is performed and only one scratch vector of size N is required, where N is the column dimension of the arrays. To make the method efficient for large SRIF arrays on a virtual memory machine, three additional scratch vectors each of size N are used to avoid expensive paging faults. The method discussed is compared with the methods and routines of Bierman's Estimation Subroutine Library (ESL).
NASA Astrophysics Data System (ADS)
Bhaskar, Ankush; Ramesh, Durbha Sai; Vichare, Geeta; Koganti, Triven; Gurubaran, S.
2017-12-01
Identification and quantification of possible drivers of recent global temperature variability remains a challenging task. This important issue is addressed adopting a non-parametric information theory technique, the Transfer Entropy and its normalized variant. It distinctly quantifies actual information exchanged along with the directional flow of information between any two variables with no bearing on their common history or inputs, unlike correlation, mutual information etc. Measurements of greenhouse gases: CO2, CH4 and N2O; volcanic aerosols; solar activity: UV radiation, total solar irradiance ( TSI) and cosmic ray flux ( CR); El Niño Southern Oscillation ( ENSO) and Global Mean Temperature Anomaly ( GMTA) made during 1984-2005 are utilized to distinguish driving and responding signals of global temperature variability. Estimates of their relative contributions reveal that CO2 ({˜ } 24 %), CH4 ({˜ } 19 %) and volcanic aerosols ({˜ }23 %) are the primary contributors to the observed variations in GMTA. While, UV ({˜ } 9 %) and ENSO ({˜ } 12 %) act as secondary drivers of variations in the GMTA, the remaining play a marginal role in the observed recent global temperature variability. Interestingly, ENSO and GMTA mutually drive each other at varied time lags. This study assists future modelling efforts in climate science.
Improved 2D/3D registration robustness using local spatial information
NASA Astrophysics Data System (ADS)
De Momi, Elena; Eckman, Kort; Jaramaz, Branislav; DiGioia, Anthony, III
2006-03-01
Xalign is a tool designed to measure implant orientation after joint arthroplasty by co-registering a projection of an implant model and a digitally reconstructed radiograph of the patient's anatomy with a post operative x-ray. A mutual information based registration method is used to automate alignment. When using basic mutual information, the presence of local maxima can result in misregistration. To increase robustness of registration, our research is aimed at improving the similarity function by modifying the information measure and incorporating local spatial information. A test dataset with known groundtruth parameters was created to evaluate the performance of this measure. A synthetic radiograph was generated first from a preoperative pelvic CT scan to act as the gold standard. The voxel weights used to generate the image were then modified and new images were generated with the CT rigidly transformed. The roll, pitch and yaw angles span a range of -10/+10 degrees, while x, y and z translations range from -10mm to +10mm. These images were compared with the reference image. The proposed cost function correctly identified the correct pose in all tests and did not exhibit any local maxima which would slow or prevent locating the global maximum.
Kabula, Bilali; Derua, Yahya A; Tungui, Patrick; Massue, Dennis J; Sambu, Edward; Stanley, Grades; Mosha, Franklin W; Kisinza, William N
2011-12-01
In Sub Saharan Africa where most of the malaria cases and deaths occur, members of the Anopheles gambiae species complex and Anophelesfunestus species group are the important malaria vectors. Control efforts against these vectors in Tanzania like in most other Sub Saharan countries have failed to achieve the set objectives of eliminating transmission due to scarcity of information about the enormous diversity of Anopheles mosquito species and their susceptibility status to insecticides used for malaria vector control. Understanding the diversity and insecticide susceptibility status of these vectors and other factors relating to their importance as vectors (such as malaria transmission dynamics, vector biology, ecology, behaviour and population genetics) is crucial to developing a better and sound intervention strategies that will reduce man-vector contact and also manage the emergency of insecticide resistance early and hence .a success in malaria control. The objective of this review was therefore to obtain the information from published and unpublished documents on spatial distribution and composition of malaria vectors, key features of their behaviour, transmission indices and susceptibility status to insecticides in Tanzania. All data available were collated into a database. Details recorded for each data source were the locality, latitude/longitude, time/period of study, species, abundance, sampling/collection methods, species identification methods, insecticide resistance status, including evidence of the kdr allele, and Plasmodium falciparum sporozoite rate. This collation resulted in a total of 368 publications, encompassing 806,273 Anopheles mosquitoes from 157 georeferenced locations being collected and identified across Tanzania from 1950s to 2010. Overall, the vector species most often reported included An. gambiae complex (66.8%), An. funestus complex (21.8%), An. gambiae s.s. (2.1%) and An. arabiensis (9%). A variety of sampling/ collection and species identification methods were used with an increase in molecular techniques in recent decades. Only 32.2% and 8.4% of the data sets reported on sporozoite analysis and entomological inoculation rate (EIR), respectively which highlights the paucity of such important information in the country. Studies demonstrated efficacy of all four major classes of insecticides against malaria vectors in Tanzania with focal points showing phenotypic resistance. About 95% of malaria entomological data was obtained from northeastern Tanzania. This shows the disproportionate nature of the available information with the western part of the country having none. Therefore it is important for the country to establish entomological surveillance system with state of the art to capture all vitally important entomological indices including vector bionomics in areas of Tanzania where very few or no studies have been done. This is vital in planning and implementing evidence based malaria vector control programmes as well as in monitoring the current malaria control interventions.
Zamanzadeh, Vahid; Rahmani, Azad; Valizadeh, Leila; Ferguson, Caleb; Hassankhani, Hadi; Nikanfar, Ali-Reza; Howard, Fuchsia
2013-02-01
The objective of this study is to describe the experiences of cancer disclosure by Iranian cancer patients, their family members and physicians. Twenty cancer patients, ten family members and eight physicians participated in this study. Data were collected via semi-structured, in-depth interviews and analyzed using qualitative content analysis. Three categories were identified: cancer avoidance, a climate of non-disclosure and mutual concern. The findings demonstrated that cancer is a taboo subject and the word cancer, as well as other indicative terms, was rarely used in daily communication. A climate of non-disclosure predominated because patients were the last to know their diagnosis, they were unaware of their prognosis, and family members and physicians employed strategies to conceal this information. The mutual concern of patients, family members and physicians was the main reason that cancer was not discussed. Cancer is a taboo subject in Iran that is maintained and reinforced primarily because of the mutual concern of patients, family members and physicians. The first step to address this taboo and inform cancer patients of their diagnosis would be to understand and help mitigate the individual, family and social consequences of disclosure. Copyright © 2011 John Wiley & Sons, Ltd.
Improvement on `structure of weakly 2-dependent siphons'
NASA Astrophysics Data System (ADS)
Chao, Daniel Y.
2015-01-01
Li and Zhou propose simpler Petri net controllers based on the concept of elementary siphons (generally much smaller than the set of all strict minimum siphons (SMSs) in large Petri nets) to minimise the addition of control places. SMSs can be divided into two groups: elementary and dependant; characteristic T-vectors of the latter are linear combinations of that of the former. A T-vector η is associated with each siphon S such that η(i) is the number of tokens gained in or lost from S by firing transition ti once. A dependent siphon S0 strongly depends on elementary siphons S1, S2, … , Sk if η0 = a1η1 + a2η2 + ṡṡṡ + akηk with all ai (i = 1, 2, 3, … , k) positive. S0 is a weakly dependent siphon if some ai is negative. The T-vectors (resp. number) for elementary siphons are mutually independent (linear to the size of the net). In an earlier paper, we show that there exists a third siphon S3 such that ηβ = η1 + η2 - η3. This equation (called η relationship) plays an important role for optimal control of weakly dependent siphons. However, it assumes that all above S span between exactly two processes. For a well-known benchmark, however, most dependent siphons span more than two processes. This paper improves by removing this restriction and shows that ηβ = η1 + η2 - η3 holds as long as S1∩S2 is another emptiable siphon.
Faithful Squashed Entanglement
NASA Astrophysics Data System (ADS)
Brandão, Fernando G. S. L.; Christandl, Matthias; Yard, Jon
2011-09-01
Squashed entanglement is a measure for the entanglement of bipartite quantum states. In this paper we present a lower bound for squashed entanglement in terms of a distance to the set of separable states. This implies that squashed entanglement is faithful, that is, it is strictly positive if and only if the state is entangled. We derive the lower bound on squashed entanglement from a lower bound on the quantum conditional mutual information which is used to define squashed entanglement. The quantum conditional mutual information corresponds to the amount by which strong subadditivity of von Neumann entropy fails to be saturated. Our result therefore sheds light on the structure of states that almost satisfy strong subadditivity with equality. The proof is based on two recent results from quantum information theory: the operational interpretation of the quantum mutual information as the optimal rate for state redistribution and the interpretation of the regularised relative entropy of entanglement as an error exponent in hypothesis testing. The distance to the set of separable states is measured in terms of the LOCC norm, an operationally motivated norm giving the optimal probability of distinguishing two bipartite quantum states, each shared by two parties, using any protocol formed by local quantum operations and classical communication (LOCC) between the parties. A similar result for the Frobenius or Euclidean norm follows as an immediate consequence. The result has two applications in complexity theory. The first application is a quasipolynomial-time algorithm solving the weak membership problem for the set of separable states in LOCC or Euclidean norm. The second application concerns quantum Merlin-Arthur games. Here we show that multiple provers are not more powerful than a single prover when the verifier is restricted to LOCC operations thereby providing a new characterisation of the complexity class QMA.
ERIC Educational Resources Information Center
Von Bergen, C. W.; Soper, Barlow; Licata, Jane W.
2002-01-01
Explains why effective teachers need relationships of mutual respect and understanding with their supervisors. Makes suggestions for building relationships: understand administrators' objectives, pressures, strengths, weaknesses, and preferred styles; communicate needs clearly; and keep administrators informed. Describes incompetent types of…
Virus Database and Online Inquiry System Based on Natural Vectors.
Dong, Rui; Zheng, Hui; Tian, Kun; Yau, Shek-Chung; Mao, Weiguang; Yu, Wenping; Yin, Changchuan; Yu, Chenglong; He, Rong Lucy; Yang, Jie; Yau, Stephen St
2017-01-01
We construct a virus database called VirusDB (http://yaulab.math.tsinghua.edu.cn/VirusDB/) and an online inquiry system to serve people who are interested in viral classification and prediction. The database stores all viral genomes, their corresponding natural vectors, and the classification information of the single/multiple-segmented viral reference sequences downloaded from National Center for Biotechnology Information. The online inquiry system serves the purpose of computing natural vectors and their distances based on submitted genomes, providing an online interface for accessing and using the database for viral classification and prediction, and back-end processes for automatic and manual updating of database content to synchronize with GenBank. Submitted genomes data in FASTA format will be carried out and the prediction results with 5 closest neighbors and their classifications will be returned by email. Considering the one-to-one correspondence between sequence and natural vector, time efficiency, and high accuracy, natural vector is a significant advance compared with alignment methods, which makes VirusDB a useful database in further research.
National Center for Biotechnology Information
... Splign Vector Alignment Search Tool (VAST) All Data & Software Resources... Domains & Structures BioSystems Cn3D Conserved Domain Database (CDD) Conserved Domain Search Service (CD Search) Structure (Molecular Modeling Database) Vector Alignment ...
Dynamic Substrate for the Physical Encoding of Sensory Information in Bat Biosonar
NASA Astrophysics Data System (ADS)
Müller, Rolf; Gupta, Anupam K.; Zhu, Hongxiao; Pannala, Mittu; Gillani, Uzair S.; Fu, Yanqing; Caspers, Philip; Buck, John R.
2017-04-01
Horseshoe bats have dynamic biosonar systems with interfaces for ultrasonic emission (reception) that change shape while diffracting the outgoing (incoming) sound waves. An information-theoretic analysis based on numerical and physical prototypes shows that these shape changes add sensory information (mutual information between distant shape conformations <20 %), increase the number of resolvable directions of sound incidence, and improve the accuracy of direction finding. These results demonstrate that horseshoe bats have a highly effective substrate for dynamic encoding of sensory information.
Dynamic Substrate for the Physical Encoding of Sensory Information in Bat Biosonar.
Müller, Rolf; Gupta, Anupam K; Zhu, Hongxiao; Pannala, Mittu; Gillani, Uzair S; Fu, Yanqing; Caspers, Philip; Buck, John R
2017-04-14
Horseshoe bats have dynamic biosonar systems with interfaces for ultrasonic emission (reception) that change shape while diffracting the outgoing (incoming) sound waves. An information-theoretic analysis based on numerical and physical prototypes shows that these shape changes add sensory information (mutual information between distant shape conformations <20%), increase the number of resolvable directions of sound incidence, and improve the accuracy of direction finding. These results demonstrate that horseshoe bats have a highly effective substrate for dynamic encoding of sensory information.
A quasi-current representation for information needs inspired by Two-State Vector Formalism
NASA Astrophysics Data System (ADS)
Wang, Panpan; Hou, Yuexian; Li, Jingfei; Zhang, Yazhou; Song, Dawei; Li, Wenjie
2017-09-01
Recently, a number of quantum theory (QT)-based information retrieval (IR) models have been proposed for modeling session search task that users issue queries continuously in order to describe their evolving information needs (IN). However, the standard formalism of QT cannot provide a complete description for users' current IN in a sense that it does not take the 'future' information into consideration. Therefore, to seek a more proper and complete representation for users' IN, we construct a representation of quasi-current IN inspired by an emerging Two-State Vector Formalism (TSVF). With the enlightenment of the completeness of TSVF, a "two-state vector" derived from the 'future' (the current query) and the 'history' (the previous query) is employed to describe users' quasi-current IN in a more complete way. Extensive experiments are conducted on the session tracks of TREC 2013 & 2014, and show that our model outperforms a series of compared IR models.
Evidence for instantaneous e-vector detection in the honeybee using an associative learning paradigm
Sakura, Midori; Okada, Ryuichi; Aonuma, Hitoshi
2012-01-01
Many insects use the polarization pattern of the sky for obtaining compass information during orientation or navigation. E-vector information is collected by a specialized area in the dorsal-most part of the compound eye, the dorsal rim area (DRA). We tested honeybees' capability of learning certain e-vector orientations by using a classical conditioning paradigm with the proboscis extension reflex. When one e-vector orientation (CS+) was associated with sugar water, while another orientation (CS−) was not rewarded, the honeybees could discriminate CS+ from CS−. Bees whose DRA was inactivated by painting did not learn CS+. When ultraviolet (UV) polarized light (350 nm) was used for CS, the bees discriminated CS+ from CS−, but no discrimination was observed in blue (442 nm) or green light (546 nm). Our data indicate that honeybees can learn and discriminate between different e-vector orientations, sensed by the UV receptors of the DRA, suggesting that bees can determine their flight direction from polarized UV skylight during foraging. Fixing the bees' heads during the experiments did not prevent learning, indicating that they use an ‘instantaneous’ algorithm of e-vector detection; that is, the bees do not need to actively scan the sky with their DRAs (‘sequential’ method) to determine e-vector orientation. PMID:21733901
Severson, David W.; Behura, Susanta K.
2016-01-01
Dengue (DENV), yellow fever, chikungunya, and Zika virus transmission to humans by a mosquito host is confounded by both intrinsic and extrinsic variables. Besides virulence factors of the individual arboviruses, likelihood of virus transmission is subject to variability in the genome of the primary mosquito vector, Aedes aegypti. The “vectorial capacity” of A. aegypti varies depending upon its density, biting rate, and survival rate, as well as its intrinsic ability to acquire, host and transmit a given arbovirus. This intrinsic ability is known as “vector competence”. Based on whole transcriptome analysis, several genes and pathways have been predicated to have an association with a susceptible or refractory response in A. aegypti to DENV infection. However, the functional genomics of vector competence of A. aegypti is not well understood, primarily due to lack of integrative approaches in genomic or transcriptomic studies. In this review, we focus on the present status of genomics studies of DENV vector competence in A. aegypti as limited information is available relative to the other arboviruses. We propose future areas of research needed to facilitate the integration of vector and virus genomics and environmental factors to work towards better understanding of vector competence and vectorial capacity in natural conditions. PMID:27809220
Peng, Hui; Lan, Chaowang; Liu, Yuansheng; Liu, Tao; Blumenstein, Michael; Li, Jinyan
2017-10-03
Disease-related protein-coding genes have been widely studied, but disease-related non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the state-of-the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long non-coding genes.
Peng, Hui; Lan, Chaowang; Liu, Yuansheng; Liu, Tao; Blumenstein, Michael; Li, Jinyan
2017-01-01
Disease-related protein-coding genes have been widely studied, but disease-related non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the state-of-the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long non-coding genes. PMID:29108274
Sex-oriented stable matchings of the marriage problem with correlated and incomplete information
NASA Astrophysics Data System (ADS)
Caldarelli, Guido; Capocci, Andrea; Laureti, Paolo
2001-10-01
In the stable marriage problem two sets of agents must be paired according to mutual preferences, which may happen to conflict. We present two generalizations of its sex-oriented version, aiming to take into account correlations between the preferences of agents and costly information. Their effects are investigated both numerically and analytically.
"We Got to Figure It out": Information-Sharing and Siblings' Negotiations of Conflicts of Interests
ERIC Educational Resources Information Center
Ram, Avigail; Ross, Hildy
2008-01-01
Given the importance of mutual understanding for constructive conflict resolution, this study investigated the influence of information-sharing on siblings faced with conflicts of interests. Thirty-two sibling dyads (ages 4.5 to 8) participated. Siblings were asked to negotiate the division of five toys between themselves. Half of the pairs first…
Estimating Mutual Information by Local Gaussian Approximation
2015-07-13
suggesstions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway...following conditions: lim N→∞ hi = 0 , lim N→∞ Nhi =∞, i = 1, 2, . . . , d. (9) Then the following holds: lim N→∞ E|f̂ (x)− f (x)| = 0 (10) lim N→∞ E|f̂ (x
Okia, Michael; Okui, Peter; Lugemwa, Myers; Govere, John M; Katamba, Vincent; Rwakimari, John B; Mpeka, Betty; Chanda, Emmanuel
2016-04-14
Integrated vector management (IVM) is the recommended approach for controlling some vector-borne diseases (VBD). In the face of current challenges to disease vector control, IVM is vital to achieve national targets set for VBD control. Though global efforts, especially for combating malaria, now focus on elimination and eradication, IVM remains useful for Uganda which is principally still in the control phase of the malaria continuum. This paper outlines the processes undertaken to consolidate tactical planning and implementation frameworks for IVM in Uganda. The Uganda National Malaria Control Programme with its efforts to implement an IVM approach to vector control was the 'case' for this study. Integrated management of malaria vectors in Uganda remained an underdeveloped component of malaria control policy. In 2012, knowledge and perceptions of malaria vector control policy and IVM were assessed, and recommendations for a specific IVM policy were made. In 2014, a thorough vector control needs assessment (VCNA) was conducted according to WHO recommendations. The findings of the VCNA informed the development of the national IVM strategic guidelines. Information sources for this study included all available data and accessible archived documentary records on VBD control in Uganda. The literature was reviewed and adapted to the local context and translated into the consolidated tactical framework. WHO recommends implementation of IVM as the main strategy to vector control and has encouraged member states to adopt the approach. However, many VBD-endemic countries lack IVM policy frameworks to guide implementation of the approach. In Uganda most VBD coexists and could be managed more effectively if done in tandem. In order to successfully control malaria and other VBD and move towards their elimination, the country needs to scale up proven and effective vector control interventions and also learn from the experience of other countries. The IVM strategy is important in consolidating inter-sectoral collaboration and coordination and providing the tactical direction for effective deployment of vector control interventions along the five key elements of the approach and to align them with contemporary epidemiology of VBD in the country. Uganda has successfully established an evidence-based IVM approach and consolidated strategic planning and operational frameworks for VBD control. However, operating implementation arrangements as outlined in the national strategic guidelines for IVM and managing insecticide resistance, as well as improving vector surveillance, are imperative. In addition, strengthened information, education and communication/behaviour change and communication, collaboration and coordination will be crucial in scaling up and using vector control interventions.