Integration of Error Compensation of Coordinate Measuring Machines into Feature Measurement: Part II—Experimental Implementation

PubMed Central

Calvo, Roque; D’Amato, Roberto; Gómez, Emilio; Domingo, Rosario

2016-01-01

Coordinate measuring machines (CMM) are main instruments of measurement in laboratories and in industrial quality control. A compensation error model has been formulated (Part I). It integrates error and uncertainty in the feature measurement model. Experimental implementation for the verification of this model is carried out based on the direct testing on a moving bridge CMM. The regression results by axis are quantified and compared to CMM indication with respect to the assigned values of the measurand. Next, testing of selected measurements of length, flatness, dihedral angle, and roundness features are accomplished. The measurement of calibrated gauge blocks for length or angle, flatness verification of the CMM granite table and roundness of a precision glass hemisphere are presented under a setup of repeatability conditions. The results are analysed and compared with alternative methods of estimation. The overall performance of the model is endorsed through experimental verification, as well as the practical use and the model capability to contribute in the improvement of current standard CMM measuring capabilities. PMID:27754441

Extraction of latent images from printed media

NASA Astrophysics Data System (ADS)

Sergeyev, Vladislav; Fedoseev, Victor

2015-12-01

In this paper we propose an automatic technology for extraction of latent images from printed media such as documents, banknotes, financial securities, etc. This technology includes image processing by adaptively constructed Gabor filter bank for obtaining feature images, as well as subsequent stages of feature selection, grouping and multicomponent segmentation. The main advantage of the proposed technique is versatility: it allows to extract latent images made by different texture variations. Experimental results showing performance of the method over another known system for latent image extraction are given.

A 62-MeV Proton Beam for the Treatment of Ocular Melanoma at Laboratori Nazionali del Sud-INFN

NASA Astrophysics Data System (ADS)

Cirrone, G. A. P.; Cuttone, G.; Lojacono, P. A.; Lo Nigro, S.; Mongelli, V.; Patti, I. V.; Privitera, G.; Raffaele, L.; Rifuggiato, D.; Sabini, M. G.; Salamone, V.; Spatola, C.; Valastro, L. M.

2004-06-01

At the Istituto Nazionale di Fisica Nucleare-Laboratori Nazionali del Sud (INFN-LNS) in Catania, Italy, the first Italian protontherapy facility, named Centro di AdroTerapia e Applicazioni Nucleari Avanzate (CATANA) has been built in collaboration with the University of Catania. It is based on the use of the 62-MeV proton beam delivered by the K=800 Superconducting Cyclotron installed and working at INFN-LNS since 1995. The facility is mainly devoted to the treatment of ocular diseases like uveal melanoma. A beam treatment line in air has been assembled together with a dedicated positioning patient system. The facility has been in operation since the beginning of 2002 and 66 patients have been successfully treated up to now. The main features of CATANA together with the clinical and dosimetric features will be extensively described; particularly, the proton beam line, that has been entirely built at LNS, with all its elements, the experimental transversal and depth dose distributions of the 62-MeV proton beam obtained for a final collimator of 25-mm diameter and the experimental depth dose distributions of a modulated proton beam obtained for the same final collimator. Finally, the clinical results over 1 yr of treatments, describing the features of the treated diseases will be reported.

Early stages of the oxidation of metal surfaces. [photoelectron spectroscopy of zinc oxide

NASA Technical Reports Server (NTRS)

Gatos, H. C.; Johnson, K. H.

1978-01-01

Photoemission cross sections were calculated for the ZnO4(-6) cluster using the self consistent-chi alpha- scattered wave theory to display the main features of the ultraviolet and X-ray photoemission data from ZnO. A solid model is suggested for an absolute photoemission intensity comparison resulting in chi alpha intensities which are roughly 70% of the experimental values. Together with the experimental data, the calculations allow a complete determination of the electronic structure of a ZnO surface.

A harmonic linear dynamical system for prominent ECG feature extraction.

PubMed

Thi, Ngoc Anh Nguyen; Yang, Hyung-Jeong; Kim, SunHee; Do, Luu Ngoc

2014-01-01

Unsupervised mining of electrocardiography (ECG) time series is a crucial task in biomedical applications. To have efficiency of the clustering results, the prominent features extracted from preprocessing analysis on multiple ECG time series need to be investigated. In this paper, a Harmonic Linear Dynamical System is applied to discover vital prominent features via mining the evolving hidden dynamics and correlations in ECG time series. The discovery of the comprehensible and interpretable features of the proposed feature extraction methodology effectively represents the accuracy and the reliability of clustering results. Particularly, the empirical evaluation results of the proposed method demonstrate the improved performance of clustering compared to the previous main stream feature extraction approaches for ECG time series clustering tasks. Furthermore, the experimental results on real-world datasets show scalability with linear computation time to the duration of the time series.

Duct flow nonuniformities study for space shuttle main engine

NASA Technical Reports Server (NTRS)

Thoenes, J.

1985-01-01

To improve the Space Shuttle Main Engine (SSME) design and for future use in the development of generation rocket engines, a combined experimental/analytical study was undertaken with the goals of first, establishing an experimental data base for the flow conditions in the SSME high pressure fuel turbopump (HPFTP) hot gas manifold (HGM) and, second, setting up a computer model of the SSME HGM flow field. Using the test data to verify the computer model it should be possible in the future to computationally scan contemplated advanced design configurations and limit costly testing to the most promising design. The effort of establishing and using the computer model is detailed. The comparison of computational results and experimental data observed clearly demonstrate that computational fluid mechanics (CFD) techniques can be used successfully to predict the gross features of three dimensional fluid flow through configurations as intricate as the SSME turbopump hot gas manifold.

Experimental study of isolas in nonlinear systems featuring modal interactions

PubMed Central

Noël, Jean-Philippe; Virgin, Lawrence N.; Kerschen, Gaëtan

2018-01-01

The objective of the present paper is to provide experimental evidence of isolated resonances in the frequency response of nonlinear mechanical systems. More specifically, this work explores the presence of isolas, which are periodic solutions detached from the main frequency response, in the case of a nonlinear set-up consisting of two masses sliding on a horizontal guide. A careful experimental investigation of isolas is carried out using responses to swept-sine and stepped-sine excitations. The experimental findings are validated with advanced numerical simulations combining nonlinear modal analysis and bifurcation monitoring. In particular, the interactions between two nonlinear normal modes are shown to be responsible for the creation of the isolas. PMID:29584758

Alcohol and the developing fetus--a review.

PubMed

Chaudhuri, J D

2000-01-01

Fetal alcohol syndrome (FAS) is a collection of signs and symptoms seen in some children exposed to alcohol in the prenatal period. It is characterized mainly by physical and mental retardation, craniofacial anomalies and minor joint abnormalities. However, with the increasing incidence of FAS, there is a great variation in the clinical features of FAS. This article describes in detail these clinical features. Due to ethical reasons it is not possible to perform experiments on pregnant women. Hence to study the effects of alcohol, various animal and avian experimental models have been chosen. The various experimental findings and human correlation are described. The exact mechanism by which alcohol induces its teratogenic effects is not known. The possible mechanisms are discussed. Measures to prevent the occurrence of FAS have been suggested.

Change Detection of High-Resolution Remote Sensing Images Based on Adaptive Fusion of Multiple Features

NASA Astrophysics Data System (ADS)

Wang, G. H.; Wang, H. B.; Fan, W. F.; Liu, Y.; Chen, C.

2018-04-01

In view of the traditional change detection algorithm mainly depends on the spectral information image spot, failed to effectively mining and fusion of multi-image feature detection advantage, the article borrows the ideas of object oriented analysis proposed a multi feature fusion of remote sensing image change detection algorithm. First by the multi-scale segmentation of image objects based; then calculate the various objects of color histogram and linear gradient histogram; utilizes the color distance and edge line feature distance between EMD statistical operator in different periods of the object, using the adaptive weighted method, the color feature distance and edge in a straight line distance of combination is constructed object heterogeneity. Finally, the curvature histogram analysis image spot change detection results. The experimental results show that the method can fully fuse the color and edge line features, thus improving the accuracy of the change detection.

Numerical-experimental investigation of resonance characteristics of a sounding board

NASA Astrophysics Data System (ADS)

Shlychkov, S. V.

2007-05-01

The paper presents results of numerical and experimental investigations into the vibrations of thin-walled structures, considering such their features as the complexity of geometry, the laminated structure of walls, the anisotropy of materials, the presence of stiffeners, and the initial stresses. The object of the study is the sounding board of an acoustic guitar, the main structural material of which is a three-layer birch veneer. Based on the finite-element method, a corresponding calculation model is created, and the steady-state regimes of forced vibrations of the sounding board are investigated. A good correspondence between calculation results and experimental data is found to exist.

Bringing Together Reading and Writing: An Experimental Study of Writing Intensive Reading Comprehension in Low-Performing Urban Elementary Schools

ERIC Educational Resources Information Center

Collins, James L.; Lee, Jaekyung; Fox, Jeffery D.; Madigan, Timothy P.

2017-01-01

This study examined the hypothesis that assisted writing during reading improves reading comprehension. The hypothesis was derived from sociocognitive and constructivist theory and research and implemented in the form of a curricular intervention called Writing Intensive Reading Comprehension after its main feature of bringing together reading…

Discovering semantic features in the literature: a foundation for building functional associations

PubMed Central

Chagoyen, Monica; Carmona-Saez, Pedro; Shatkay, Hagit; Carazo, Jose M; Pascual-Montano, Alberto

2006-01-01

Background Experimental techniques such as DNA microarray, serial analysis of gene expression (SAGE) and mass spectrometry proteomics, among others, are generating large amounts of data related to genes and proteins at different levels. As in any other experimental approach, it is necessary to analyze these data in the context of previously known information about the biological entities under study. The literature is a particularly valuable source of information for experiment validation and interpretation. Therefore, the development of automated text mining tools to assist in such interpretation is one of the main challenges in current bioinformatics research. Results We present a method to create literature profiles for large sets of genes or proteins based on common semantic features extracted from a corpus of relevant documents. These profiles can be used to establish pair-wise similarities among genes, utilized in gene/protein classification or can be even combined with experimental measurements. Semantic features can be used by researchers to facilitate the understanding of the commonalities indicated by experimental results. Our approach is based on non-negative matrix factorization (NMF), a machine-learning algorithm for data analysis, capable of identifying local patterns that characterize a subset of the data. The literature is thus used to establish putative relationships among subsets of genes or proteins and to provide coherent justification for this clustering into subsets. We demonstrate the utility of the method by applying it to two independent and vastly different sets of genes. Conclusion The presented method can create literature profiles from documents relevant to sets of genes. The representation of genes as additive linear combinations of semantic features allows for the exploration of functional associations as well as for clustering, suggesting a valuable methodology for the validation and interpretation of high-throughput experimental data. PMID:16438716

Off-lexicon online Arabic handwriting recognition using neural network

NASA Astrophysics Data System (ADS)

Yahia, Hamdi; Chaabouni, Aymen; Boubaker, Houcine; Alimi, Adel M.

2017-03-01

This paper highlights a new method for online Arabic handwriting recognition based on graphemes segmentation. The main contribution of our work is to explore the utility of Beta-elliptic model in segmentation and features extraction for online handwriting recognition. Indeed, our method consists in decomposing the input signal into continuous part called graphemes based on Beta-Elliptical model, and classify them according to their position in the pseudo-word. The segmented graphemes are then described by the combination of geometric features and trajectory shape modeling. The efficiency of the considered features has been evaluated using feed forward neural network classifier. Experimental results using the benchmarking ADAB Database show the performance of the proposed method.

Dynamic properties of ionospheric plasma turbulence driven by high-power high-frequency radiowaves

NASA Astrophysics Data System (ADS)

Grach, S. M.; Sergeev, E. N.; Mishin, E. V.; Shindin, A. V.

2016-11-01

A review is given of the current state-of-the-art of experimental studies and the theoretical understanding of nonlinear phenomena that occur in the ionospheric F-layer irradiated by high-power high-frequency ground-based transmitters. The main focus is on the dynamic features of high-frequency turbulence (plasma waves) and low-frequency turbulence (density irregularities of various scales) that have been studied in experiments at the Sura and HAARP heating facilities operated in temporal and frequency regimes specially designed with consideration of the characteristic properties of nonlinear processes in the perturbed ionosphere using modern radio receivers and optical instruments. Experimental results are compared with theoretical turbulence models for a magnetized collisional plasma in a high-frequency electromagnetic field, allowing the identification of the processes responsible for the observed features of artificial ionospheric turbulence.

Neutron cross section measurements at n-TOF for ADS related studies

NASA Astrophysics Data System (ADS)

Mastinu, P. F.; Abbondanno, U.; Aerts, G.; Álvarez, H.; Alvarez-Velarde, F.; Andriamonje, S.; Andrzejewski, J.; Assimakopoulos, P.; Audouin, L.; Badurek, G.; Bustreo, N.; aumann, P.; vá, F. Be; Berthoumieux, E.; Calviño, F.; Cano-Ott, D.; Capote, R.; Carrillo de Albornoz, A.; Cennini, P.; Chepel, V.; Chiaveri, E.; Colonna, N.; Cortes, G.; Couture, A.; Cox, J.; Dahlfors, M.; David, S.; Dillmann, I.; Dolfini, R.; Domingo-Pardo, C.; Dridi, W.; Duran, I.; Eleftheriadis, C.; Embid-Segura, M.; Ferrant, L.; Ferrari, A.; Ferreira-Marques, R.; itzpatrick, L.; Frais-Kölbl, H.; Fujii, K.; Furman, W.; Guerrero, C.; Goncalves, I.; Gallino, R.; Gonzalez-Romero, E.; Goverdovski, A.; Gramegna, F.; Griesmayer, E.; Gunsing, F.; Haas, B.; Haight, R.; Heil, M.; Herrera-Martinez, A.; Igashira, M.; Isaev, S.; Jericha, E.; Kadi, Y.; Käppeler, F.; Karamanis, D.; Karadimos, D.; Kerveno, M.; Ketlerov, V.; Koehler, P.; Konovalov, V.; Kossionides, E.; Krti ka, M.; Lamboudis, C.; Leeb, H.; Lindote, A.; Lopes, I.; Lozano, M.; Lukic, S.; Marganiec, J.; Marques, L.; Marrone, S.; Massimi, C.; Mengoni, A.; Milazzo, P. M.; Moreau, C.; Mosconi, M.; Neves, F.; Oberhummer, H.; O'Brien, S.; Oshima, M.; Pancin, J.; Papachristodoulou, C.; Papadopoulos, C.; Paradela, C.; Patronis, N.; Pavlik, A.; Pavlopoulos, P.; Perrot, L.; Plag, R.; Plompen, A.; Plukis, A.; Poch, A.; Pretel, C.; Quesada, J.; Rauscher, T.; Reifarth, R.; Rosetti, M.; Rubbia, C.; Rudolf, G.; Rullhusen, P.; Salgado, J.; Sarchiapone, L.; Savvidis, I.; Stephan, C.; Tagliente, G.; Tain, J. L.; Tassan-Got, L.; Tavora, L.; Terlizzi, R.; Vannini, G.; Vaz, P.; Ventura, A.; Villamarin, D.; Vincente, M. C.; Vlachoudis, V.; Vlastou, R.; Voss, F.; Walter, S.; Wendler, H.; Wiescherand, M.; Wisshak, K.

2006-05-01

A neutron Time-of-Flight facility (n_TOF) is available at CERN since 2001. The innovative features of the neutron beam, in particular the high instantaneous flux, the wide energy range, the high resolution and the low background, make this facility unique for measurements of neutron induced reactions relevant to the field of Emerging Nuclear Technologies, as well as to Nuclear Astrophysics and Fundamental Nuclear Physics. The scientific motivations that have led to the construction of this new facility are here presented. The main characteristics of the n_TOF neutron beam are described, together with the features of the experimental apparata used for cross-section measurements. The main results of the first measurement campaigns are presented. Preliminary results of capture cross-section measurements of minor actinides, important to ADS project for nuclear waste transmutation, are finally discussed.

Experimental study of the novel tuned mass damper with inerter which enables changes of inertance

NASA Astrophysics Data System (ADS)

Brzeski, P.; Lazarek, M.; Perlikowski, P.

2017-09-01

In this paper we present the experimental verification of the novel tuned mass damper which enables changes of inertance. Characteristic feature of the proposed device is the presence of special type of inerter. This inerter incorporates a continuously variable transmission that enables stepless changes of inertance. Thus, it enables to adjust the parameters of the damping device to the current forcing characteristic. In the paper we present and describe the experimental rig that consists of the massive main oscillator forced kinematically and the prototype of the investigated damper. We perform a series of dedicated experiments to characterize the device and asses its damping efficiency. Moreover, we perform numerical simulations using the simple mathematical model of investigated system. Comparing the numerical results and the experimental data we legitimize the model and demonstrate the capabilities of the investigated tuned mass damper. Presented results prove that the concept of the novel type of tuned mass damper can be realized and enable to confirm its main advantages. Investigated prototype device offers excellent damping efficiency in a wide range of forcing frequencies.

Simulation and observation of line-slip structures in columnar structures of soft spheres

NASA Astrophysics Data System (ADS)

Winkelmann, J.; Haffner, B.; Weaire, D.; Mughal, A.; Hutzler, S.

2017-07-01

We present the computed phase diagram of columnar structures of soft spheres under pressure, of which the main feature is the appearance and disappearance of line slips, the shearing of adjacent spirals, as pressure is increased. A comparable experimental observation is made on a column of bubbles under forced drainage, clearly exhibiting the expected line slip.

Simulation and observation of line-slip structures in columnar structures of soft spheres.

PubMed

Winkelmann, J; Haffner, B; Weaire, D; Mughal, A; Hutzler, S

2017-07-01

We present the computed phase diagram of columnar structures of soft spheres under pressure, of which the main feature is the appearance and disappearance of line slips, the shearing of adjacent spirals, as pressure is increased. A comparable experimental observation is made on a column of bubbles under forced drainage, clearly exhibiting the expected line slip.

A model for 3-D sonic/supersonic transverse fuel injection into a supersonic air stream

NASA Technical Reports Server (NTRS)

Bussing, Thomas R. A.; Lidstone, Gary L.

1989-01-01

A model for sonic/supersonic transverse fuel injection into a supersonic airstream is proposed. The model replaces the hydrogen jet up to the Mach disk plane and the elliptic parts of the air flow field around the jet by an equivalent body. The main features of the model were validated on the basis of experimental data.

Whatever Happened to School-Based Assessment in England's GCSEs and A Levels?

ERIC Educational Resources Information Center

Opposs, Dennis

2016-01-01

For the past 30 years, school-based assessment (SBA) has been a major feature of GCSEs and A levels, the main school examinations in England. SBA has allowed teachers to allocate marks to their students for the level of skills that they show in their work. Such skills include for example, experimental techniques in science, performance in drama…

High-resolution stress measurements for microsystem and semiconductor applications

NASA Astrophysics Data System (ADS)

Vogel, Dietmar; Keller, Juergen; Michel, Bernd

2006-04-01

Research results obtained for local stress determination on micro and nanotechnology components are summarized. It meets the concern of controlling stresses introduced to sensors, MEMS and electronics devices during different micromachining processes. The method bases on deformation measurement options made available inside focused ion beam equipment. Removing locally material by ion beam milling existing stresses / residual stresses lead to deformation fields around the milled feature. Digital image correlation techniques are used to extract deformation values from micrographs captured before and after milling. In the paper, two main milling features have been analyzed - through hole and through slit milling. Analytical solutions for stress release fields of in-plane stresses have been derived and compared to respective experimental findings. Their good agreement allows to settle a method for determination of residual stress values, which is demonstrated for thin membranes manufactured by silicon micro technology. Some emphasis is made on the elimination of main error sources for stress determination, like rigid body object displacements and rotations due to drifts of experimental conditions under FIB imaging. In order to illustrate potential application areas of the method residual stress suppression by ion implantation is evaluated by the method and reported here.

FIB-based measurement of local residual stresses on microsystems

NASA Astrophysics Data System (ADS)

Vogel, Dietmar; Sabate, Neus; Gollhardt, Astrid; Keller, Juergen; Auersperg, Juergen; Michel, Bernd

2006-03-01

The paper comprises research results obtained for stress determination on micro and nanotechnology components. It meets the concern of controlling stresses introduced to sensors, MEMS and electronics devices during different micromachining processes. The method bases on deformation measurement options made available inside focused ion beam equipment. Removing locally material by ion beam milling existing stresses / residual stresses lead to deformation fields around the milled feature. Digital image correlation techniques are used to extract deformation values from micrographs captured before and after milling. In the paper, two main milling features have been analyzed - through hole and through slit milling. Analytical solutions for stress release fields of in-plane stresses have been derived and compared to respective experimental findings. Their good agreement allows to settle a method for determination of residual stress values, which is demonstrated for thin membranes manufactured by silicon micro technology. Some emphasis is made on the elimination of main error sources for stress determination, like rigid body object displacements and rotations due to drifts of experimental conditions under FIB imaging. In order to illustrate potential application areas of the method residual stress suppression by ion implantation is evaluated by the method and reported here.

GIFAD for He/KCl(001). Structure in the pattern for 〈 110 〉 incidence as a measure of the projectile-cation interaction

NASA Astrophysics Data System (ADS)

Bocan, G. A.; Gravielle, M. S.

2018-04-01

In this article we address grazing incidence fast atom diffraction (GIFAD) for the He/KCl(001) system, for which a systematic experimental study was recently reported [E. Meyer, Ph.D dissertation, Humboldt-Universität, Berlin, Germany, 2015]. Our theoretical model is built from a projectile-surface interaction obtained from Density Functional Theory (DFT) calculations and the Surface Initial-Value Representation (SIVR), which is a semi-quantum approach to describe the scattering process. For incidence along the 〈 100 〉 and 〈 110 〉 directions, we present and discuss the main features of our interaction potential, the dependence of the rainbow angle with the impact energy normal to the surface, and the simulated GIFAD patterns, which reproduce the main aspects of the reported experimental charts. The features of the diffraction charts for He/KCl(001) are related to the averaged equipotential curves of the system and a comparison is established with the case of He/LiF(001). The marked differences observed for 〈 110 〉 incidence are explained as due to the much larger size of the K+ ion relative to that of Li+.

Motor Fault Diagnosis Based on Short-time Fourier Transform and Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Wang, Li-Hua; Zhao, Xiao-Ping; Wu, Jia-Xin; Xie, Yang-Yang; Zhang, Yong-Hong

2017-11-01

With the rapid development of mechanical equipment, the mechanical health monitoring field has entered the era of big data. However, the method of manual feature extraction has the disadvantages of low efficiency and poor accuracy, when handling big data. In this study, the research object was the asynchronous motor in the drivetrain diagnostics simulator system. The vibration signals of different fault motors were collected. The raw signal was pretreated using short time Fourier transform (STFT) to obtain the corresponding time-frequency map. Then, the feature of the time-frequency map was adaptively extracted by using a convolutional neural network (CNN). The effects of the pretreatment method, and the hyper parameters of network diagnostic accuracy, were investigated experimentally. The experimental results showed that the influence of the preprocessing method is small, and that the batch-size is the main factor affecting accuracy and training efficiency. By investigating feature visualization, it was shown that, in the case of big data, the extracted CNN features can represent complex mapping relationships between signal and health status, and can also overcome the prior knowledge and engineering experience requirement for feature extraction, which is used by traditional diagnosis methods. This paper proposes a new method, based on STFT and CNN, which can complete motor fault diagnosis tasks more intelligently and accurately.

A method for real-time implementation of HOG feature extraction

NASA Astrophysics Data System (ADS)

Luo, Hai-bo; Yu, Xin-rong; Liu, Hong-mei; Ding, Qing-hai

2011-08-01

Histogram of oriented gradient (HOG) is an efficient feature extraction scheme, and HOG descriptors are feature descriptors which is widely used in computer vision and image processing for the purpose of biometrics, target tracking, automatic target detection(ATD) and automatic target recognition(ATR) etc. However, computation of HOG feature extraction is unsuitable for hardware implementation since it includes complicated operations. In this paper, the optimal design method and theory frame for real-time HOG feature extraction based on FPGA were proposed. The main principle is as follows: firstly, the parallel gradient computing unit circuit based on parallel pipeline structure was designed. Secondly, the calculation of arctangent and square root operation was simplified. Finally, a histogram generator based on parallel pipeline structure was designed to calculate the histogram of each sub-region. Experimental results showed that the HOG extraction can be implemented in a pixel period by these computing units.

Vibrations of bioionic liquids by ab initio molecular dynamics and vibrational spectroscopy.

PubMed

Tanzi, Luana; Benassi, Paola; Nardone, Michele; Ramondo, Fabio

2014-12-26

Density functional theory and vibrational spectroscopy are used to investigate a class of bioionic liquids consisting of a choline cation and carboxylate anions. Through quantum mechanical studies of motionless ion pairs and molecular dynamics of small portions of the liquid, we have characterized important structural features of the ionic liquid. Hydrogen bonding produces stable ion pairs in the liquid and induces vibrational features of the carboxylate groups comparable with experimental results. Infrared and Raman spectra of liquids have been measured, and main bands have been assigned on the basis of theoretical spectra.

The IVTANTHERMO-Online database for thermodynamic properties of individual substances with web interface

NASA Astrophysics Data System (ADS)

Belov, G. V.; Dyachkov, S. A.; Levashov, P. R.; Lomonosov, I. V.; Minakov, D. V.; Morozov, I. V.; Sineva, M. A.; Smirnov, V. N.

2018-01-01

The database structure, main features and user interface of an IVTANTHERMO-Online system are reviewed. This system continues the series of the IVTANTHERMO packages developed in JIHT RAS. It includes the database for thermodynamic properties of individual substances and related software for analysis of experimental results, data fitting, calculation and estimation of thermodynamical functions and thermochemistry quantities. In contrast to the previous IVTANTHERMO versions it has a new extensible database design, the client-server architecture, a user-friendly web interface with a number of new features for online and offline data processing.

Unravelling Some of the Key Transformations in the Hydrothermal Liquefaction of Lignin.

PubMed

Lui, Matthew Y; Chan, Bun; Yuen, Alexander K L; Masters, Anthony F; Montoya, Alejandro; Maschmeyer, Thomas

2017-05-22

Using both experimental and computational methods, focusing on intermediates and model compounds, some of the main features of the reaction mechanisms that operate during the hydrothermal processing of lignin were elucidated. Key reaction pathways and their connection to different structural features of lignin were proposed. Under neutral conditions, subcritical water was demonstrated to act as a bifunctional acid/base catalyst for the dissection of lignin structures. In a complex web of mutually dependent interactions, guaiacyl units within lignin were shown to significantly affect overall lignin reactivity. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Novel Multi-Class Ensemble Model for Classifying Imbalanced Biomedical Datasets

NASA Astrophysics Data System (ADS)

Bikku, Thulasi; Sambasiva Rao, N., Dr; Rao, Akepogu Ananda, Dr

2017-08-01

This paper mainly focuseson developing aHadoop based framework for feature selection and classification models to classify high dimensionality data in heterogeneous biomedical databases. Wide research has been performing in the fields of Machine learning, Big data and Data mining for identifying patterns. The main challenge is extracting useful features generated from diverse biological systems. The proposed model can be used for predicting diseases in various applications and identifying the features relevant to particular diseases. There is an exponential growth of biomedical repositories such as PubMed and Medline, an accurate predictive model is essential for knowledge discovery in Hadoop environment. Extracting key features from unstructured documents often lead to uncertain results due to outliers and missing values. In this paper, we proposed a two phase map-reduce framework with text preprocessor and classification model. In the first phase, mapper based preprocessing method was designed to eliminate irrelevant features, missing values and outliers from the biomedical data. In the second phase, a Map-Reduce based multi-class ensemble decision tree model was designed and implemented in the preprocessed mapper data to improve the true positive rate and computational time. The experimental results on the complex biomedical datasets show that the performance of our proposed Hadoop based multi-class ensemble model significantly outperforms state-of-the-art baselines.

Deep visual-semantic for crowded video understanding

NASA Astrophysics Data System (ADS)

Deng, Chunhua; Zhang, Junwen

2018-03-01

Visual-semantic features play a vital role for crowded video understanding. Convolutional Neural Networks (CNNs) have experienced a significant breakthrough in learning representations from images. However, the learning of visualsemantic features, and how it can be effectively extracted for video analysis, still remains a challenging task. In this study, we propose a novel visual-semantic method to capture both appearance and dynamic representations. In particular, we propose a spatial context method, based on the fractional Fisher vector (FV) encoding on CNN features, which can be regarded as our main contribution. In addition, to capture temporal context information, we also applied fractional encoding method on dynamic images. Experimental results on the WWW crowed video dataset demonstrate that the proposed method outperform the state of the art.

Overview of C-2U FRC Experimental Program and Plans for C-2W

NASA Astrophysics Data System (ADS)

Gota, H.; Binderbauer, M. W.; Tajima, T.; Putvinski, S.; Tuszewski, M.; Dettrick, S.; Korepanov, S.; Smirnov, A.; Thompson, M. C.; Yang, X.; Cappello, M.; Ivanov, A. A.; TAE Team

2016-10-01

Tri Alpha Energy's experimental program has been focused on a demonstration of reliable field-reversed configuration (FRC) formation and sustainment, driven by fast ions via high-power neutral-beam (NB) injection. The world's largest compact-toroid experimental devices, C-2 and C-2U, have successfully produced a well-stabilized, sustainable FRC plasma state with NB injection (input power, PNB 10 + MW; 15 keV hydrogen) and end-on coaxial plasma guns. Remarkable improvements in confinement and stability of FRC plasmas have led to further improved fast-ion build up; thereby, an advanced beam-driven FRC state has been produced and sustained for up to 5 + ms (longer than all characteristic system time scales), only limited by hardware and electric supply constraints such as NB and plasma-gun power supplies. To further improve the FRC performance the C-2U device is being replaced by C-2W featuring higher injected NB power, longer pulse duration as well as enhanced edge-biasing systems and substantially upgraded divertors. Main C-2U experimental results and key features of C-2W will be presented. Tri Alpha Energy, Inc.

LSAH: a fast and efficient local surface feature for point cloud registration

NASA Astrophysics Data System (ADS)

Lu, Rongrong; Zhu, Feng; Wu, Qingxiao; Kong, Yanzi

2018-04-01

Point cloud registration is a fundamental task in high level three dimensional applications. Noise, uneven point density and varying point cloud resolutions are the three main challenges for point cloud registration. In this paper, we design a robust and compact local surface descriptor called Local Surface Angles Histogram (LSAH) and propose an effectively coarse to fine algorithm for point cloud registration. The LSAH descriptor is formed by concatenating five normalized sub-histograms into one histogram. The five sub-histograms are created by accumulating a different type of angle from a local surface patch respectively. The experimental results show that our LSAH is more robust to uneven point density and point cloud resolutions than four state-of-the-art local descriptors in terms of feature matching. Moreover, we tested our LSAH based coarse to fine algorithm for point cloud registration. The experimental results demonstrate that our algorithm is robust and efficient as well.

[Practice of the use of remote telemedical consultations in "experimental area of work"].

PubMed

Kalachev, O V; Plakhov, A N; Pershin, I V; Agapitov, A A; Andreev, A I; Yakovlev, A E

2016-02-01

The article presents experimental results of telehealth technology of "medical company--military hospital--central military hospital". Requirements for the equipment, which is used for telehealth consultations and software are specified. Throughout the test were practiced emergency consultations of "physician-physician" interface, including the use of mobile video call and portable terminals of videoconference, remote diagnosis with the use of medical equipment and devices. Data transmission features and video definition are received. The authors determined main types of telecommunication equipment, which are supposed to prospective for the Armed Forces. Prospects of implementation of telecommunication technologies are shown.

30 cm Engineering Model thruster design and qualification tests

NASA Technical Reports Server (NTRS)

Schnelker, D. E.; Collett, C. R.

1975-01-01

Development of a 30-cm mercury electron bombardment Engineering Model ion thruster has successfully brought the thruster from the status of a laboratory experimental device to a point approaching flight readiness. This paper describes the development progress of the Engineering Model (EM) thruster in four areas: (1) design features and fabrication approaches, (2) performance verification and thruster to thruster variations, (3) structural integrity, and (4) interface definition. The design of major subassemblies, including the cathode-isolator-vaporizer (CIV), main isolator-vaporizer (MIV), neutralizer isolator-vaporizer (NIV), ion optical system, and discharge chamber/outer housing is discussed along with experimental results.

Theory of the Trojan-Horse Method - From the Original Idea to Actual Applications

NASA Astrophysics Data System (ADS)

Typel, Stefan

2018-01-01

The origin and the main features of the Trojan-horse (TH) method are delineated starting with the original idea of Gerhard Baur. Basic theoretical considerations, general experimental conditions and possible problems are discussed. Significant steps in experimental studies towards the implementation of the TH method and the development of the theoretical description are presented. This lead to the successful application of the TH approach by Claudio Spitaleri and his group to determine low-energy cross section that are relevant for astrophysics. An outlook with possible developments in the future are given.

Self-injection-locking linewidth narrowing in a semiconductor laser coupled to an external fiber-optic ring resonator

NASA Astrophysics Data System (ADS)

Korobko, Dmitry A.; Zolotovskii, Igor O.; Panajotov, Krassimir; Spirin, Vasily V.; Fotiadi, Andrei A.

2017-12-01

We develop a theoretical framework for modeling of semiconductor laser coupled to an external fiber-optic ring resonator. The developed approach has shown good qualitative agreement between theoretical predictions and experimental results for particular configuration of a self-injection locked DFB laser delivering narrow-band radiation. The model is capable of describing the main features of the experimentally measured laser outputs such as laser line narrowing, spectral shape of generated radiation, mode-hoping instabilities and makes possible exploring the key physical mechanisms responsible for the laser operation stability.

Using Activity-Related Behavioural Features towards More Effective Automatic Stress Detection

PubMed Central

Giakoumis, Dimitris; Drosou, Anastasios; Cipresso, Pietro; Tzovaras, Dimitrios; Hassapis, George; Gaggioli, Andrea; Riva, Giuseppe

2012-01-01

This paper introduces activity-related behavioural features that can be automatically extracted from a computer system, with the aim to increase the effectiveness of automatic stress detection. The proposed features are based on processing of appropriate video and accelerometer recordings taken from the monitored subjects. For the purposes of the present study, an experiment was conducted that utilized a stress-induction protocol based on the stroop colour word test. Video, accelerometer and biosignal (Electrocardiogram and Galvanic Skin Response) recordings were collected from nineteen participants. Then, an explorative study was conducted by following a methodology mainly based on spatiotemporal descriptors (Motion History Images) that are extracted from video sequences. A large set of activity-related behavioural features, potentially useful for automatic stress detection, were proposed and examined. Experimental evaluation showed that several of these behavioural features significantly correlate to self-reported stress. Moreover, it was found that the use of the proposed features can significantly enhance the performance of typical automatic stress detection systems, commonly based on biosignal processing. PMID:23028461

Application of a three-feature dispersed-barrier hardening model to neutron-irradiated Fe-Cr model alloys

NASA Astrophysics Data System (ADS)

Bergner, F.; Pareige, C.; Hernández-Mayoral, M.; Malerba, L.; Heintze, C.

2014-05-01

An attempt is made to quantify the contributions of different types of defect-solute clusters to the total irradiation-induced yield stress increase in neutron-irradiated (300 °C, 0.6 dpa), industrial-purity Fe-Cr model alloys (target Cr contents of 2.5, 5, 9 and 12 at.% Cr). Former work based on the application of transmission electron microscopy, atom probe tomography, and small-angle neutron scattering revealed the formation of dislocation loops, NiSiPCr-enriched clusters and α‧-phase particles, which act as obstacles to dislocation glide. The values of the dimensionless obstacle strength are estimated in the framework of a three-feature dispersed-barrier hardening model. Special attention is paid to the effect of measuring errors, experimental details and model details on the estimates. The three families of obstacles and the hardening model are well capable of reproducing the observed yield stress increase as a function of Cr content, suggesting that the nanostructural features identified experimentally are the main, if not the only, causes of irradiation hardening in these model alloys.

Fault diagnosis method based on FFT-RPCA-SVM for Cascaded-Multilevel Inverter.

PubMed

Wang, Tianzhen; Qi, Jie; Xu, Hao; Wang, Yide; Liu, Lei; Gao, Diju

2016-01-01

Thanks to reduced switch stress, high quality of load wave, easy packaging and good extensibility, the cascaded H-bridge multilevel inverter is widely used in wind power system. To guarantee stable operation of system, a new fault diagnosis method, based on Fast Fourier Transform (FFT), Relative Principle Component Analysis (RPCA) and Support Vector Machine (SVM), is proposed for H-bridge multilevel inverter. To avoid the influence of load variation on fault diagnosis, the output voltages of the inverter is chosen as the fault characteristic signals. To shorten the time of diagnosis and improve the diagnostic accuracy, the main features of the fault characteristic signals are extracted by FFT. To further reduce the training time of SVM, the feature vector is reduced based on RPCA that can get a lower dimensional feature space. The fault classifier is constructed via SVM. An experimental prototype of the inverter is built to test the proposed method. Compared to other fault diagnosis methods, the experimental results demonstrate the high accuracy and efficiency of the proposed method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Shape Distributions of Nonlinear Dynamical Systems for Video-Based Inference.

PubMed

Venkataraman, Vinay; Turaga, Pavan

2016-12-01

This paper presents a shape-theoretic framework for dynamical analysis of nonlinear dynamical systems which appear frequently in several video-based inference tasks. Traditional approaches to dynamical modeling have included linear and nonlinear methods with their respective drawbacks. A novel approach we propose is the use of descriptors of the shape of the dynamical attractor as a feature representation of nature of dynamics. The proposed framework has two main advantages over traditional approaches: a) representation of the dynamical system is derived directly from the observational data, without any inherent assumptions, and b) the proposed features show stability under different time-series lengths where traditional dynamical invariants fail. We illustrate our idea using nonlinear dynamical models such as Lorenz and Rossler systems, where our feature representations (shape distribution) support our hypothesis that the local shape of the reconstructed phase space can be used as a discriminative feature. Our experimental analyses on these models also indicate that the proposed framework show stability for different time-series lengths, which is useful when the available number of samples are small/variable. The specific applications of interest in this paper are: 1) activity recognition using motion capture and RGBD sensors, 2) activity quality assessment for applications in stroke rehabilitation, and 3) dynamical scene classification. We provide experimental validation through action and gesture recognition experiments on motion capture and Kinect datasets. In all these scenarios, we show experimental evidence of the favorable properties of the proposed representation.

Hybrid feature selection for supporting lightweight intrusion detection systems

NASA Astrophysics Data System (ADS)

Song, Jianglong; Zhao, Wentao; Liu, Qiang; Wang, Xin

2017-08-01

Redundant and irrelevant features not only cause high resource consumption but also degrade the performance of Intrusion Detection Systems (IDS), especially when coping with big data. These features slow down the process of training and testing in network traffic classification. Therefore, a hybrid feature selection approach in combination with wrapper and filter selection is designed in this paper to build a lightweight intrusion detection system. Two main phases are involved in this method. The first phase conducts a preliminary search for an optimal subset of features, in which the chi-square feature selection is utilized. The selected set of features from the previous phase is further refined in the second phase in a wrapper manner, in which the Random Forest(RF) is used to guide the selection process and retain an optimized set of features. After that, we build an RF-based detection model and make a fair comparison with other approaches. The experimental results on NSL-KDD datasets show that our approach results are in higher detection accuracy as well as faster training and testing processes.

Reliability of numerical wind tunnels for VAWT simulation

NASA Astrophysics Data System (ADS)

Raciti Castelli, M.; Masi, M.; Battisti, L.; Benini, E.; Brighenti, A.; Dossena, V.; Persico, G.

2016-09-01

Computational Fluid Dynamics (CFD) based on the Unsteady Reynolds Averaged Navier Stokes (URANS) equations have long been widely used to study vertical axis wind turbines (VAWTs). Following a comprehensive experimental survey on the wakes downwind of a troposkien-shaped rotor, a campaign of bi-dimensional simulations is presented here, with the aim of assessing its reliability in reproducing the main features of the flow, also identifying areas needing additional research. Starting from both a well consolidated turbulence model (k-ω SST) and an unstructured grid typology, the main simulation settings are here manipulated in a convenient form to tackle rotating grids reproducing a VAWT operating in an open jet wind tunnel. The dependence of the numerical predictions from the selected grid spacing is investigated, thus establishing the less refined grid size that is still capable of capturing some relevant flow features such as integral quantities (rotor torque) and local ones (wake velocities).

Middle Atmosphere Program. Handbook for MAP, volume 22

NASA Technical Reports Server (NTRS)

Russell, James M., III (Editor)

1986-01-01

A series of plots are presented that describe the state of the stratosphere and to some degree, the mesosphere as revealed by satellite observations. The pertinent instrument features, spatial and temporal coverage, and details of accuracy and precision for the experiments providing the data are described. The main features of zonal mean cross sections and polar stereographic projections are noted and intercomparisons are discussed where a parameter was measured by more than one experiment. It was not the attempt to be exhaustive in this or to present detailed results of scientific investigations. The main purpose was to collect the available data in one place and provide enough information on limitations or cautions about the data so that they could be used in model comparisons and science studies. Without a doubt, when these are used, numerous questions will arise that were not addressed here. In such cases, the reader is encouraged to contact the experimenters for proper clarification.

Terahertz spectra of L-phenylalanine and its monohydrate

NASA Astrophysics Data System (ADS)

Pan, Tingting; Li, Shaoping; Zou, Tao; Yu, Zheng; Zhang, Bo; Wang, Chenyang; Zhang, Jianbing; He, Mingxia; Zhao, Hongwei

2017-05-01

The low-frequency vibrational property of L-phenylalanine (L-Phe) and L-phenylalanine monohydrate (L-Phe·H2O) has been investigated by terahertz time-domain spectroscopy (THz-TDS) at room and low temperature ranging from 0.5 to 4.5 THz. Distinctive THz absorption spectra of the two compounds were observed. Density functional theory (DFT) calculations based on the crystal structures have been performed to simulate the vibrational modes of L-Phe and L-Phe·H2O and the results agree well with the experimental observations. The study indicates that the characterized features of L-Phe mainly originate from the collective vibration of molecules. And the characterized features of L-Phe·H2O mainly come from hydrogen bond interactions between L-Phe and water molecules. L-Phe and L-Phe·H2O were also verified by differential scanning calorimetry and thermogravimetry (DSC-TG) and powder X-ray diffraction (PXRD) examinations.

Carrier recombination dynamics in anatase TiO 2 nanoparticles

NASA Astrophysics Data System (ADS)

Cavigli, Lucia; Bogani, Franco; Vinattieri, Anna; Cortese, Lorenzo; Colocci, Marcello; Faso, Valentina; Baldi, Giovanni

2010-11-01

We present an experimental study of the radiative recombination dynamics in size-controlled TiO 2 nanoparticles in the range 20-130 nm. Time-integrated photoluminescence spectra clearly show a dominance of self-trapped exciton (STE) emission, with main features not dependent on the nanoparticle size and on its environment. From picosecond time-resolved experiments as a function of the excitation density and the nanoparticle size we address the STE recombination dynamics as the result of two main processes related to the direct STE formation and to the indirect STE formation mediated by non-radiative surface states.

Unsupervised Pattern Classifier for Abnormality-Scaling of Vibration Features for Helicopter Gearbox Fault Diagnosis

NASA Technical Reports Server (NTRS)

Jammu, Vinay B.; Danai, Kourosh; Lewicki, David G.

1996-01-01

A new unsupervised pattern classifier is introduced for on-line detection of abnormality in features of vibration that are used for fault diagnosis of helicopter gearboxes. This classifier compares vibration features with their respective normal values and assigns them a value in (0, 1) to reflect their degree of abnormality. Therefore, the salient feature of this classifier is that it does not require feature values associated with faulty cases to identify abnormality. In order to cope with noise and changes in the operating conditions, an adaptation algorithm is incorporated that continually updates the normal values of the features. The proposed classifier is tested using experimental vibration features obtained from an OH-58A main rotor gearbox. The overall performance of this classifier is then evaluated by integrating the abnormality-scaled features for detection of faults. The fault detection results indicate that the performance of this classifier is comparable to the leading unsupervised neural networks: Kohonen's Feature Mapping and Adaptive Resonance Theory (AR72). This is significant considering that the independence of this classifier from fault-related features makes it uniquely suited to abnormality-scaling of vibration features for fault diagnosis.

Some peculiarities of interactions of weakly bound lithium nuclei at near-barrier energies

NASA Astrophysics Data System (ADS)

Kabyshev, A. M.; Kuterbekov, K. A.; Sobolev, Yu G.; Penionzhkevich, Yu E.; Kubenova, M. M.; Azhibekov, A. K.; Mukhambetzhan, A. M.; Lukyanov, S. M.; Maslov, V. A.; Kabdrakhimova, G. D.

2018-02-01

This paper presents new experimental data on the total cross sections of 9Li + 28Si reactions at low energies as well as the analysis of previously obtained data for 6,7Li. Based on a large collection of data (authors’ and literature data) we carried out a comparative analysis of the two main experimental interaction cross sections (angular distributions of the differential cross sections and total reaction cross sections) for weakly bound lithium (6-9Li, 11Li) nuclei in the framework of Kox parameterization and the macroscopic optical model. We identified specific features of these interactions and predicted the experimental trend in the total reaction cross sections for Li isotopes at energies close to the Coulomb barrier.

Computational fluid dynamics analysis of a maglev centrifugal left ventricular assist device.

PubMed

Burgreen, Greg W; Loree, Howard M; Bourque, Kevin; Dague, Charles; Poirier, Victor L; Farrar, David; Hampton, Edward; Wu, Z Jon; Gempp, Thomas M; Schöb, Reto

2004-10-01

The fluid dynamics of the Thoratec HeartMate III (Thoratec Corp., Pleasanton, CA, U.S.A.) left ventricular assist device are analyzed over a range of physiological operating conditions. The HeartMate III is a centrifugal flow pump with a magnetically suspended rotor. The complete pump was analyzed using computational fluid dynamics (CFD) analysis and experimental particle imaging flow visualization (PIFV). A comparison of CFD predictions to experimental imaging shows good agreement. Both CFD and experimental PIFV confirmed well-behaved flow fields in the main components of the HeartMate III pump: inlet, volute, and outlet. The HeartMate III is shown to exhibit clean flow features and good surface washing across its entire operating range.

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

Derbenev, Yaroslav S.; Morozov, Vasiliy; Lin, Fanglei

We present a complete scheme for managing the polarization of ion beams in Jefferson Lab's proposed Medium-energy Electron-Ion Collider (MEIC). It provides preservation of the ion polarization during all stages of beam acceleration and polarization control in the collider's experimental straights. We discuss characteristic features of the spin motion in accelerators with Siberian snakes and in accelerators of figure-8 shape. We propose 3D spin rotators for polarization control in the MEIC ion collider ring. We provide polarization calculations in the collider with the 3D rotator for deuteron and proton beams. The main polarization control features of the figure-8 design aremore » summarized.« less

Kernel-aligned multi-view canonical correlation analysis for image recognition

NASA Astrophysics Data System (ADS)

Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

2016-09-01

Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

The morphing of geographical features by Fourier transformation.

PubMed

Li, Jingzhong; Liu, Pengcheng; Yu, Wenhao; Cheng, Xiaoqiang

2018-01-01

This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features' continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable.

Corrected Article: Simulation and observation of line-slip structures in columnar structures of soft spheres [Phys. Rev. E 96, 012610 (2017)

NASA Astrophysics Data System (ADS)

Winkelmann, J.; Haffner, B.; Weaire, D.; Mughal, A.; Hutzler, S.

2017-07-01

We present the computed phase diagram of columnar structures of soft spheres under pressure, of which the main feature is the appearance and disappearance of line slips, the shearing of adjacent spirals, as pressure is increased. A comparable experimental observation is made on a column of bubbles under forced drainage, clearly exhibiting the expected line slip.

Feature and Region Selection for Visual Learning.

PubMed

Zhao, Ji; Wang, Liantao; Cabral, Ricardo; De la Torre, Fernando

2016-03-01

Visual learning problems, such as object classification and action recognition, are typically approached using extensions of the popular bag-of-words (BoWs) model. Despite its great success, it is unclear what visual features the BoW model is learning. Which regions in the image or video are used to discriminate among classes? Which are the most discriminative visual words? Answering these questions is fundamental for understanding existing BoW models and inspiring better models for visual recognition. To answer these questions, this paper presents a method for feature selection and region selection in the visual BoW model. This allows for an intermediate visualization of the features and regions that are important for visual learning. The main idea is to assign latent weights to the features or regions, and jointly optimize these latent variables with the parameters of a classifier (e.g., support vector machine). There are four main benefits of our approach: 1) our approach accommodates non-linear additive kernels, such as the popular χ(2) and intersection kernel; 2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; 3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; and 4) we point out strong connections with multiple kernel learning and multiple instance learning approaches. Experimental results in the PASCAL VOC 2007, MSR Action Dataset II and YouTube illustrate the benefits of our approach.

Stacked sparse autoencoder in hyperspectral data classification using spectral-spatial, higher order statistics and multifractal spectrum features

NASA Astrophysics Data System (ADS)

Wan, Xiaoqing; Zhao, Chunhui; Wang, Yanchun; Liu, Wu

2017-11-01

This paper proposes a novel classification paradigm for hyperspectral image (HSI) using feature-level fusion and deep learning-based methodologies. Operation is carried out in three main steps. First, during a pre-processing stage, wave atoms are introduced into bilateral filter to smooth HSI, and this strategy can effectively attenuate noise and restore texture information. Meanwhile, high quality spectral-spatial features can be extracted from HSI by taking geometric closeness and photometric similarity among pixels into consideration simultaneously. Second, higher order statistics techniques are firstly introduced into hyperspectral data classification to characterize the phase correlations of spectral curves. Third, multifractal spectrum features are extracted to characterize the singularities and self-similarities of spectra shapes. To this end, a feature-level fusion is applied to the extracted spectral-spatial features along with higher order statistics and multifractal spectrum features. Finally, stacked sparse autoencoder is utilized to learn more abstract and invariant high-level features from the multiple feature sets, and then random forest classifier is employed to perform supervised fine-tuning and classification. Experimental results on two real hyperspectral data sets demonstrate that the proposed method outperforms some traditional alternatives.

EEG Sleep Stages Classification Based on Time Domain Features and Structural Graph Similarity.

PubMed

Diykh, Mohammed; Li, Yan; Wen, Peng

2016-11-01

The electroencephalogram (EEG) signals are commonly used in diagnosing and treating sleep disorders. Many existing methods for sleep stages classification mainly depend on the analysis of EEG signals in time or frequency domain to obtain a high classification accuracy. In this paper, the statistical features in time domain, the structural graph similarity and the K-means (SGSKM) are combined to identify six sleep stages using single channel EEG signals. Firstly, each EEG segment is partitioned into sub-segments. The size of a sub-segment is determined empirically. Secondly, statistical features are extracted, sorted into different sets of features and forwarded to the SGSKM to classify EEG sleep stages. We have also investigated the relationships between sleep stages and the time domain features of the EEG data used in this paper. The experimental results show that the proposed method yields better classification results than other four existing methods and the support vector machine (SVM) classifier. A 95.93% average classification accuracy is achieved by using the proposed method.

Gaussian mixture models-based ship target recognition algorithm in remote sensing infrared images

NASA Astrophysics Data System (ADS)

Yao, Shoukui; Qin, Xiaojuan

2018-02-01

Since the resolution of remote sensing infrared images is low, the features of ship targets become unstable. The issue of how to recognize ships with fuzzy features is an open problem. In this paper, we propose a novel ship target recognition algorithm based on Gaussian mixture models (GMMs). In the proposed algorithm, there are mainly two steps. At the first step, the Hu moments of these ship target images are calculated, and the GMMs are trained on the moment features of ships. At the second step, the moment feature of each ship image is assigned to the trained GMMs for recognition. Because of the scale, rotation, translation invariance property of Hu moments and the power feature-space description ability of GMMs, the GMMs-based ship target recognition algorithm can recognize ship reliably. Experimental results of a large simulating image set show that our approach is effective in distinguishing different ship types, and obtains a satisfactory ship recognition performance.

Revisiting Shock Initiation Modeling of Homogeneous Explosives

NASA Astrophysics Data System (ADS)

Partom, Yehuda

2013-04-01

Shock initiation of homogeneous explosives has been a subject of research since the 1960s, with neat and sensitized nitromethane as the main materials for experiments. A shock initiation model of homogeneous explosives was established in the early 1960s. It involves a thermal explosion event at the shock entrance boundary, which develops into a superdetonation that overtakes the initial shock. In recent years, Sheffield and his group, using accurate experimental tools, were able to observe details of buildup of the superdetonation. There are many papers on modeling shock initiation of heterogeneous explosives, but there are only a few papers on modeling shock initiation of homogeneous explosives. In this article, bulk reaction reactive flow equations are used to model homogeneous shock initiation in an attempt to reproduce experimental data of Sheffield and his group. It was possible to reproduce the main features of the shock initiation process, including thermal explosion, superdetonation, input shock overtake, overdriven detonation after overtake, and the beginning of decay toward Chapman-Jouget (CJ) detonation. The time to overtake (TTO) as function of input pressure was also calculated and compared to the experimental TTO.

New ab initio potential surfaces and three-dimensional quantum dynamics for transition state spectroscopy in ozone photodissociation

NASA Astrophysics Data System (ADS)

Yamashita, Koichi; Morokuma, Keiji; Le Quéré, Frederic; Leforestier, Claude

1992-04-01

New ab initio potential energy surfaces (PESs) of the ground and B ( 1B 2) states of ozone have been calculated with the CASSCF-SECI/DZP method to describe the three-dimensional photodissociation process. The dissociation energy of the ground state and the vertical barrier height of the B PES are obtained to be 0.88 and 1.34 eV, respectively, in better agreement with the experimental values than the previous calculation. The photodissociation autocorrelation function, calculated on the new B PES, based on exact three-dimensional quantum dynamics, reproduces well the main recurrence feature extracted from the experimental spectra.

Experimental demonstration of an optical phased array antenna for laser space communications.

PubMed

Neubert, W M; Kudielka, K H; Leeb, W R; Scholtz, A L

1994-06-20

The feasibility of an optical phased array antenna applicable for spaceborne laser communications was experimentally demonstrated. Heterodyne optical phase-locked loops provide for a defined phase relationship between the collimated output beams of three single-mode fibers. In the far field the beams interfere with a measured efficiency of 99%. The main lobe of the interference pattern can be moved by phase shifting the subaperture output beams. The setup permitted agile beam steering within an angular range of 1 mr and a response time of 0.7 ms. We propose an operational optical phased array antenna fed by seven lasers, featuring high transmit power and redundance.

Portraits of self-organization in fish schools interacting with robots

NASA Astrophysics Data System (ADS)

Aureli, M.; Fiorilli, F.; Porfiri, M.

2012-05-01

In this paper, we propose an enabling computational and theoretical framework for the analysis of experimental instances of collective behavior in response to external stimuli. In particular, this work addresses the characterization of aggregation and interaction phenomena in robot-animal groups through the exemplary analysis of fish schooling in the vicinity of a biomimetic robot. We adapt global observables from statistical mechanics to capture the main features of the shoal collective motion and its response to the robot from experimental observations. We investigate the shoal behavior by using a diffusion mapping analysis performed on these global observables that also informs the definition of relevant portraits of self-organization.

[Safety evaluation and risk control measures of Cassiae Semen].

PubMed

Zhao, Yi-Meng; Wu, Li; Zhang, Shuo; Zhang, Li; Gao, Xue-Min; Sun, Xiao-Bo; Wang, Chun

2017-11-01

In this study, the authors reviewed domestic and foreign literatures, conducted the textual research on origin and development of Cassia Semen, studied records in ancient books and ancient and modern literatures, clinical adverse reactions and relevant experimental studies in recent years, and summarized the clinical features and influencing factors related to the safety of Cassiae Semen. According to the findings,Cassia Semen's safety risks are mainly liver and kidney system damages, with the main clinical features of fatigue, anorexia, disgusting of oil, yellow urine and gray stool; digestive system injury, with the main clinical features of diarrhea, abdominal distension, nausea and loose stool; reproductive system damage, with the main clinical features of vaginal bleeding. Allergic reactions and clinical adverse events, with the main clinical features for numb mouth, itching skin, nausea and vomiting, diarrhea, wheezing and lip cyanosis were also reported. The toxicological studies on toxic components of Cassiae Semen obtusifolia were carried out through acute toxicity test, subacute toxicity test, subchronic toxicity test and chronic toxicity test. Risk factors might include patients, compatibility and physicians. Physicians should strictly abide by the medication requirements in the Pharmacopoeia, pay attention to rational compatibility, appropriate dosage,correct usage and appropriate processing, control the dosage below 15 g to avoid excessive intake, strictly control the course of treatment to avoid accumulated poisoning caused by long-term administration. At the same time, clinicians should pay attention to the latest research progress, update the knowledge structure, quickly find the latest and useful materials from clinical practice, scientific research and drug information and other literatures, make evaluation and judgment for the materials, establish a traditional Chinese medicine intelligence information library, and strengthen the control over adverse effects with a pre-warning consciousness. The authors suggested standardizing clinical medication of Cassiae Semen, and avoiding misuse or excessive use; clinicians should prescribe it in strict accordance with there commended usage and dosage in the Pharmacopoeia, and focus on the safety signal accumulation in clinic, while strengthening studies for toxic substance basis and toxicity mechanism, in order to give full play to Cassiae Semen's clinical efficacy and reduce its adverse reactions. Copyright© by the Chinese Pharmaceutical Association.

Double beta decay: yesterday, today, tomorrow

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

Fiorini, Ettore

2011-12-16

After a brief introduction on the main features of Double Beta Decay (DBD) and on its origin, its importance is stressed in view of the recent results of experiments on neutrino oscillations. The present experimental situation is reported with special reference to direct experiments and to the comparison of their results with theory. The expectations of the future experiments aiming to reach the sensitivity indicated by neutrino oscillations in the inverse hierarchy hypothesis are discussed.

Muon background studies for shallow depth Double - Chooz near detector

NASA Astrophysics Data System (ADS)

Gómez, H.

2015-08-01

Muon events are one of the main concerns regarding background in neutrino experiments. The placement of experimental set-ups in deep underground facilities reduce considerably their impact on the research of the expected signals. But in the cases where the detector is installed on surface or at shallow depth, muon flux remains high, being necessary their precise identification for further rejection. Total flux, mean energy or angular distributions are some of the parameters that can help to characterize the muons. Empirically, the muon rate can be measured in an experiment by a number of methods. Nevertheless, the capability to determine the muons angular distribution strongly depends on the detector features, while the measurement of the muon energy is quite difficult. Also considering that on-site measurements can not be extrapolated to other sites due to the difference on the overburden and its profile, it is necessary to find an adequate solution to perform the muon characterization. The method described in this work to obtain the main features of the muons reaching the experimental set-up, is based on the muon transport simulation by the MUSIC software, combined with a dedicated sampling algorithm for shallow depth installations based on a modified Gaisser parametrization. This method provides all the required information about the muons for any shallow depth installation if the corresponding overburden profile is implemented. In this work, the method has been applied for the recently commissioned Double - Chooz near detector, which will allow the cross-check between the simulation and the experimental data, as it has been done for the far detector.

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

Gómez, H.

Muon events are one of the main concerns regarding background in neutrino experiments. The placement of experimental set-ups in deep underground facilities reduce considerably their impact on the research of the expected signals. But in the cases where the detector is installed on surface or at shallow depth, muon flux remains high, being necessary their precise identification for further rejection. Total flux, mean energy or angular distributions are some of the parameters that can help to characterize the muons. Empirically, the muon rate can be measured in an experiment by a number of methods. Nevertheless, the capability to determine themore » muons angular distribution strongly depends on the detector features, while the measurement of the muon energy is quite difficult. Also considering that on-site measurements can not be extrapolated to other sites due to the difference on the overburden and its profile, it is necessary to find an adequate solution to perform the muon characterization. The method described in this work to obtain the main features of the muons reaching the experimental set-up, is based on the muon transport simulation by the MUSIC software, combined with a dedicated sampling algorithm for shallow depth installations based on a modified Gaisser parametrization. This method provides all the required information about the muons for any shallow depth installation if the corresponding overburden profile is implemented. In this work, the method has been applied for the recently commissioned Double - Chooz near detector, which will allow the cross-check between the simulation and the experimental data, as it has been done for the far detector.« less

On the use of multiple-point statistics to improve groundwater flow modeling in karst aquifers: A case study from the Hydrogeological Experimental Site of Poitiers, France

NASA Astrophysics Data System (ADS)

Le Coz, Mathieu; Bodin, Jacques; Renard, Philippe

2017-02-01

Limestone aquifers often exhibit complex groundwater flow behaviors resulting from depositional heterogeneities and post-lithification fracturing and karstification. In this study, multiple-point statistics (MPS) was applied to reproduce karst features and to improve groundwater flow modeling. For this purpose, MPS realizations were used in a numerical flow model to simulate the responses to pumping test experiments observed at the Hydrogeological Experimental Site of Poitiers, France. The main flow behaviors evident in the field data were simulated, particularly (i) the early-time inflection of the drawdown signal at certain observation wells and (ii) the convex behavior of the drawdown curves at intermediate times. In addition, it was shown that the spatial structure of the karst features at various scales is critical with regard to the propagation of the depletion wave induced by pumping. Indeed, (i) the spatial shape of the cone of depression is significantly affected by the karst proportion in the vicinity of the pumping well, and (ii) early-time inflection of the drawdown signal occurs only at observation wells crossing locally well-developed karst features.

Fast and effective characterization of 3D region of interest in medical image data

NASA Astrophysics Data System (ADS)

Kontos, Despina; Megalooikonomou, Vasileios

2004-05-01

We propose a framework for detecting, characterizing and classifying spatial Regions of Interest (ROIs) in medical images, such as tumors and lesions in MRI or activation regions in fMRI. A necessary step prior to classification is efficient extraction of discriminative features. For this purpose, we apply a characterization technique especially designed for spatial ROIs. The main idea of this technique is to extract a k-dimensional feature vector using concentric spheres in 3D (or circles in 2D) radiating out of the ROI's center of mass. These vectors form characterization signatures that can be used to represent the initial ROIs. We focus on classifying fMRI ROIs obtained from a study that explores neuroanatomical correlates of semantic processing in Alzheimer's disease (AD). We detect a ROI highly associated with AD and apply the feature extraction technique with different experimental settings. We seek to distinguish control from patient samples. We study how classification can be performed using the extracted signatures as well as how different experimental parameters affect classification accuracy. The obtained classification accuracy ranged from 82% to 87% (based on the selected ROI) suggesting that the proposed classification framework can be potentially useful in supporting medical decision-making.

Research on driver fatigue detection

NASA Astrophysics Data System (ADS)

Zhang, Ting; Chen, Zhong; Ouyang, Chao

2018-03-01

Driver fatigue is one of the main causes of frequent traffic accidents. In this case, driver fatigue detection system has very important significance in avoiding traffic accidents. This paper presents a real-time method based on fusion of multiple facial features, including eye closure, yawn and head movement. The eye state is classified as being open or closed by a linear SVM classifier trained using HOG features of the detected eye. The mouth state is determined according to the width-height ratio of the mouth. The head movement is detected by head pitch angle calculated by facial landmark. The driver's fatigue state can be reasoned by the model trained by above features. According to experimental results, drive fatigue detection obtains an excellent performance. It indicates that the developed method is valuable for the application of avoiding traffic accidents caused by driver's fatigue.

Design, manufacturing and characterization of aero-elastically scaled wind turbine blades for testing active and passive load alleviation techniques within a ABL wind tunnel

NASA Astrophysics Data System (ADS)

Campagnolo, Filippo; Bottasso, Carlo L.; Bettini, Paolo

2014-06-01

In the research described in this paper, a scaled wind turbine model featuring individual pitch control (IPC) capabilities, and equipped with aero-elastically scaled blades featuring passive load reduction capabilities (bend-twist coupling, BTC), was constructed to investigate, by means of wind tunnel testing, the load alleviation potential of BTC and its synergy with active load reduction techniques. The paper mainly focus on the design of the aero-elastic blades and their dynamic and static structural characterization. The experimental results highlight that manufactured blades show desired bend-twist coupling behavior and are a first milestone toward their testing in the wind tunnel.

Laser-induced asymmetric faceting and growth of a nano-protrusion on a tungsten tip

NASA Astrophysics Data System (ADS)

Yanagisawa, Hirofumi; Zadin, Vahur; Kunze, Karsten; Hafner, Christian; Aabloo, Alvo; Kim, Dong Eon; Kling, Matthias F.; Djurabekova, Flyura; Osterwalder, Jürg; Wuensch, Walter

2016-12-01

Irradiation of a sharp tungsten tip by a femtosecond laser and exposed to a strong DC electric field led to reproducible surface modifications. By a combination of field emission microscopy and scanning electron microscopy, we observed asymmetric surface faceting with sub-ten nanometer high steps. The presence of faceted features mainly on the laser-exposed side implies that the surface modification was driven by a laser-induced transient temperature rise on a scale of a couple of picoseconds in the tungsten tip apex. Moreover, we identified the formation of a nano-tip a few nanometers high located at one of the corners of a faceted plateau. The results of simulations emulating the experimental conditions are consistent with the experimental observations. The presented technique would be a new method to fabricate a nano-tip especially for generating coherent electron pulses. The features may also help to explain the origin of enhanced field emission, which leads to vacuum arcs, in high electric field devices such as radio-frequency particle accelerators.

Mechanism of voltage-gated channel formation in lipid membranes.

PubMed

Guidelli, Rolando; Becucci, Lucia

2016-04-01

Although several molecular models for voltage-gated ion channels in lipid membranes have been proposed, a detailed mechanism accounting for the salient features of experimental data is lacking. A general treatment accounting for peptide dipole orientation in the electric field and their nucleation and growth kinetics with ion channel formation is provided. This is the first treatment that explains all the main features of the experimental current-voltage curves of peptides forming voltage-gated channels available in the literature. It predicts a regime of weakly voltage-dependent conductance, followed by one of strong voltage-dependent conductance at higher voltages. It also predicts values of the parameters expressing the exponential dependence of conductance upon voltage and peptide bulk concentration for both regimes, in good agreement with those reported in the literature. Most importantly, the only two adjustable parameters involved in the kinetics of nucleation and growth of ion channels can be varied over broad ranges without affecting the above predictions to a significant extent. Thus, the fitting of experimental current-voltage curves stems naturally from the treatment and depends only slightly upon the choice of the kinetic parameters. Copyright © 2015 Elsevier B.V. All rights reserved.

Mining the key predictors for event outbreaks in social networks

NASA Astrophysics Data System (ADS)

Yi, Chengqi; Bao, Yuanyuan; Xue, Yibo

2016-04-01

It will be beneficial to devise a method to predict a so-called event outbreak. Existing works mainly focus on exploring effective methods for improving the accuracy of predictions, while ignoring the underlying causes: What makes event go viral? What factors that significantly influence the prediction of an event outbreak in social networks? In this paper, we proposed a novel definition for an event outbreak, taking into account the structural changes to a network during the propagation of content. In addition, we investigated features that were sensitive to predicting an event outbreak. In order to investigate the universality of these features at different stages of an event, we split the entire lifecycle of an event into 20 equal segments according to the proportion of the propagation time. We extracted 44 features, including features related to content, users, structure, and time, from each segment of the event. Based on these features, we proposed a prediction method using supervised classification algorithms to predict event outbreaks. Experimental results indicate that, as time goes by, our method is highly accurate, with a precision rate ranging from 79% to 97% and a recall rate ranging from 74% to 97%. In addition, after applying a feature-selection algorithm, the top five selected features can considerably improve the accuracy of the prediction. Data-driven experimental results show that the entropy of the eigenvector centrality, the entropy of the PageRank, the standard deviation of the betweenness centrality, the proportion of re-shares without content, and the average path length are the key predictors for an event outbreak. Our findings are especially useful for further exploring the intrinsic characteristics of outbreak prediction.

Terahertz spectra of l-phenylalanine and its monohydrate.

PubMed

Pan, Tingting; Li, Shaoping; Zou, Tao; Yu, Zheng; Zhang, Bo; Wang, Chenyang; Zhang, Jianbing; He, Mingxia; Zhao, Hongwei

2017-05-05

The low-frequency vibrational property of l-phenylalanine (l-Phe) and l-phenylalanine monohydrate (l-Phe·H 2 O) has been investigated by terahertz time-domain spectroscopy (THz-TDS) at room and low temperature ranging from 0.5 to 4.5THz. Distinctive THz absorption spectra of the two compounds were observed. Density functional theory (DFT) calculations based on the crystal structures have been performed to simulate the vibrational modes of l-Phe and l-Phe·H 2 O and the results agree well with the experimental observations. The study indicates that the characterized features of l-Phe mainly originate from the collective vibration of molecules. And the characterized features of l-Phe·H 2 O mainly come from hydrogen bond interactions between l-Phe and water molecules. l-Phe and l-Phe·H 2 O were also verified by differential scanning calorimetry and thermogravimetry (DSC-TG) and powder X-ray diffraction (PXRD) examinations. Copyright © 2017. Published by Elsevier B.V.

Hyperspectral remote sensing image retrieval system using spectral and texture features.

PubMed

Zhang, Jing; Geng, Wenhao; Liang, Xi; Li, Jiafeng; Zhuo, Li; Zhou, Qianlan

2017-06-01

Although many content-based image retrieval systems have been developed, few studies have focused on hyperspectral remote sensing images. In this paper, a hyperspectral remote sensing image retrieval system based on spectral and texture features is proposed. The main contributions are fourfold: (1) considering the "mixed pixel" in the hyperspectral image, endmembers as spectral features are extracted by an improved automatic pixel purity index algorithm, then the texture features are extracted with the gray level co-occurrence matrix; (2) similarity measurement is designed for the hyperspectral remote sensing image retrieval system, in which the similarity of spectral features is measured with the spectral information divergence and spectral angle match mixed measurement and in which the similarity of textural features is measured with Euclidean distance; (3) considering the limited ability of the human visual system, the retrieval results are returned after synthesizing true color images based on the hyperspectral image characteristics; (4) the retrieval results are optimized by adjusting the feature weights of similarity measurements according to the user's relevance feedback. The experimental results on NASA data sets can show that our system can achieve comparable superior retrieval performance to existing hyperspectral analysis schemes.

Impact of experimental design on PET radiomics in predicting somatic mutation status.

PubMed

Yip, Stephen S F; Parmar, Chintan; Kim, John; Huynh, Elizabeth; Mak, Raymond H; Aerts, Hugo J W L

2017-12-01

PET-based radiomic features have demonstrated great promises in predicting genetic data. However, various experimental parameters can influence the feature extraction pipeline, and hence, Here, we investigated how experimental settings affect the performance of radiomic features in predicting somatic mutation status in non-small cell lung cancer (NSCLC) patients. 348 NSCLC patients with somatic mutation testing and diagnostic PET images were included in our analysis. Radiomic feature extractions were analyzed for varying voxel sizes, filters and bin widths. 66 radiomic features were evaluated. The performance of features in predicting mutations status was assessed using the area under the receiver-operating-characteristic curve (AUC). The influence of experimental parameters on feature predictability was quantified as the relative difference between the minimum and maximum AUC (δ). The large majority of features (n=56, 85%) were significantly predictive for EGFR mutation status (AUC≥0.61). 29 radiomic features significantly predicted EGFR mutations and were robust to experimental settings with δ Overall <5%. The overall influence (δ Overall ) of the voxel size, filter and bin width for all features ranged from 5% to 15%, respectively. For all features, none of the experimental designs was predictive of KRAS+ from KRAS- (AUC≤0.56). The predictability of 29 radiomic features was robust to the choice of experimental settings; however, these settings need to be carefully chosen for all other features. The combined effect of the investigated processing methods could be substantial and must be considered. Optimized settings that will maximize the predictive performance of individual radiomic features should be investigated in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

Design and Application of a Collocated Capacitance Sensor for Magnetic Bearing Spindle

NASA Technical Reports Server (NTRS)

Shin, Dongwon; Liu, Seon-Jung; Kim, Jongwon

1996-01-01

This paper presents a collocated capacitance sensor for magnetic bearings. The main feature of the sensor is that it is made of a specific compact printed circuit board (PCB). The signal processing unit has been also developed. The results of the experimental performance evaluation on the sensitivity, resolution and frequency response of the sensor are presented. Finally, an application example of the sensor to the active control of a magnetic bearing is described.

Two-dimensional electronic spectra of the photosynthetic apparatus of green sulfur bacteria

NASA Astrophysics Data System (ADS)

Kramer, Tobias; Rodriguez, Mirta

2017-03-01

Advances in time resolved spectroscopy have provided new insight into the energy transmission in natural photosynthetic complexes. Novel theoretical tools and models are being developed in order to explain the experimental results. We provide a model calculation for the two-dimensional electronic spectra of Cholorobaculum tepidum which correctly describes the main features and transfer time scales found in recent experiments. From our calculation one can infer the coupling of the antenna chlorosome with the environment and the coupling between the chlorosome and the Fenna-Matthews-Olson complex. We show that environment assisted transport between the subunits is the required mechanism to reproduce the experimental two-dimensional electronic spectra.

Statistical process control using optimized neural networks: a case study.

PubMed

Addeh, Jalil; Ebrahimzadeh, Ata; Azarbad, Milad; Ranaee, Vahid

2014-09-01

The most common statistical process control (SPC) tools employed for monitoring process changes are control charts. A control chart demonstrates that the process has altered by generating an out-of-control signal. This study investigates the design of an accurate system for the control chart patterns (CCPs) recognition in two aspects. First, an efficient system is introduced that includes two main modules: feature extraction module and classifier module. In the feature extraction module, a proper set of shape features and statistical feature are proposed as the efficient characteristics of the patterns. In the classifier module, several neural networks, such as multilayer perceptron, probabilistic neural network and radial basis function are investigated. Based on an experimental study, the best classifier is chosen in order to recognize the CCPs. Second, a hybrid heuristic recognition system is introduced based on cuckoo optimization algorithm (COA) algorithm to improve the generalization performance of the classifier. The simulation results show that the proposed algorithm has high recognition accuracy. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Feature hashing for fast image retrieval

NASA Astrophysics Data System (ADS)

Yan, Lingyu; Fu, Jiarun; Zhang, Hongxin; Yuan, Lu; Xu, Hui

2018-03-01

Currently, researches on content based image retrieval mainly focus on robust feature extraction. However, due to the exponential growth of online images, it is necessary to consider searching among large scale images, which is very timeconsuming and unscalable. Hence, we need to pay much attention to the efficiency of image retrieval. In this paper, we propose a feature hashing method for image retrieval which not only generates compact fingerprint for image representation, but also prevents huge semantic loss during the process of hashing. To generate the fingerprint, an objective function of semantic loss is constructed and minimized, which combine the influence of both the neighborhood structure of feature data and mapping error. Since the machine learning based hashing effectively preserves neighborhood structure of data, it yields visual words with strong discriminability. Furthermore, the generated binary codes leads image representation building to be of low-complexity, making it efficient and scalable to large scale databases. Experimental results show good performance of our approach.

Fast large-scale object retrieval with binary quantization

NASA Astrophysics Data System (ADS)

Zhou, Shifu; Zeng, Dan; Shen, Wei; Zhang, Zhijiang; Tian, Qi

2015-11-01

The objective of large-scale object retrieval systems is to search for images that contain the target object in an image database. Where state-of-the-art approaches rely on global image representations to conduct searches, we consider many boxes per image as candidates to search locally in a picture. In this paper, a feature quantization algorithm called binary quantization is proposed. In binary quantization, a scale-invariant feature transform (SIFT) feature is quantized into a descriptive and discriminative bit-vector, which allows itself to adapt to the classic inverted file structure for box indexing. The inverted file, which stores the bit-vector and box ID where the SIFT feature is located inside, is compact and can be loaded into the main memory for efficient box indexing. We evaluate our approach on available object retrieval datasets. Experimental results demonstrate that the proposed approach is fast and achieves excellent search quality. Therefore, the proposed approach is an improvement over state-of-the-art approaches for object retrieval.

Multi-label learning with fuzzy hypergraph regularization for protein subcellular location prediction.

PubMed

Chen, Jing; Tang, Yuan Yan; Chen, C L Philip; Fang, Bin; Lin, Yuewei; Shang, Zhaowei

2014-12-01

Protein subcellular location prediction aims to predict the location where a protein resides within a cell using computational methods. Considering the main limitations of the existing methods, we propose a hierarchical multi-label learning model FHML for both single-location proteins and multi-location proteins. The latent concepts are extracted through feature space decomposition and label space decomposition under the nonnegative data factorization framework. The extracted latent concepts are used as the codebook to indirectly connect the protein features to their annotations. We construct dual fuzzy hypergraphs to capture the intrinsic high-order relations embedded in not only feature space, but also label space. Finally, the subcellular location annotation information is propagated from the labeled proteins to the unlabeled proteins by performing dual fuzzy hypergraph Laplacian regularization. The experimental results on the six protein benchmark datasets demonstrate the superiority of our proposed method by comparing it with the state-of-the-art methods, and illustrate the benefit of exploiting both feature correlations and label correlations.

Study on ancient Chinese imitated GE ware by INAA and WDXRF

NASA Astrophysics Data System (ADS)

Xie, Guoxi; Feng, Songlin; Feng, Xiangqian; Wang, Yanqing; Zhu, Jihao; Yan, Lingtong; Li, Yongqiang; Han, Hongye

2007-11-01

Imitated GE ware was one of the most famous products of Jingdezhen porcelain field in Ming dynasty (AD 1368-1644). The exterior features of its body and glaze are very marvelous. Black foot, purple mouth and crazing glaze are the main features of imitated GE ware. Until now, the key conditions of resulting these features are not clearly identified. In order to find the critical elements for firing these features, instrumental neutron activation analysis (INAA) and wavelength-dispersive X-ray fluorescence (WDXRF) were used to determine the element abundance patterns of imitated GE ware body and glaze. The experimental data was compared with that of imitated Longquan celadon and of Longquan celadon. The analytical results indicated that Fe, Ti and Na were the critical elements. The body of imitated GE ware which contains high Fe and Ti are the basic conditions of firing its black body, black foot and purple mouth. The glaze of imitated GE ware which contains high Na is the main condition of producing its crazing glaze. Na is the critical element which enlarges the difference in expansion coefficients between the glaze and body of imitated GE ware. Furthermore, Zijin soil was added into kaolin to make the body rich in Fe and Ti. And something which was rich in Na was used to produce crazing glaze in the manufacturing process of imitated GE ware.

Adversarial Feature Selection Against Evasion Attacks.

PubMed

Zhang, Fei; Chan, Patrick P K; Biggio, Battista; Yeung, Daniel S; Roli, Fabio

2016-03-01

Pattern recognition and machine learning techniques have been increasingly adopted in adversarial settings such as spam, intrusion, and malware detection, although their security against well-crafted attacks that aim to evade detection by manipulating data at test time has not yet been thoroughly assessed. While previous work has been mainly focused on devising adversary-aware classification algorithms to counter evasion attempts, only few authors have considered the impact of using reduced feature sets on classifier security against the same attacks. An interesting, preliminary result is that classifier security to evasion may be even worsened by the application of feature selection. In this paper, we provide a more detailed investigation of this aspect, shedding some light on the security properties of feature selection against evasion attacks. Inspired by previous work on adversary-aware classifiers, we propose a novel adversary-aware feature selection model that can improve classifier security against evasion attacks, by incorporating specific assumptions on the adversary's data manipulation strategy. We focus on an efficient, wrapper-based implementation of our approach, and experimentally validate its soundness on different application examples, including spam and malware detection.

Experimental and theoretical description of the optical properties of Myrcia sylvatica essential oil.

PubMed

Silva Prado, Andriele da; Leal, Luciano Almeida; de Brito, Patrick Pascoal; de Almeida Fonseca, Antonio Luciano; Blawid, Stefan; Ceschin, Artemis Marti; Veras Mourão, Rosa Helena; da Silva Júnior, Antônio Quaresma; Antonio da Silva Filho, Demétrio; Ribeiro Junior, Luiz Antonio; Ferreira da Cunha, Wiliam

2017-07-01

We present an extensive study of the optical properties of Myrcia sylvatica essential oil with the goal of investigating the suitability of its material system for uses in organic photovoltaics. The methods of extraction, experimental analysis, and theoretical modeling are described in detail. The precise composition of the oil in our samples is determined via gas chromatography, mass spectrometry, and X-ray scattering techniques. The measurements indicate that, indeed, the material system of Myrcia sylvatica essential oil may be successfully employed for the design of organic photovoltaic devices. The optical absorption of the molecules that compose the oil are calculated using time-dependent density functional theory and used to explain the measured UV-Vis spectra of the oil. We show that it is sufficient to consider the α-bisabolol/cadalene pair, two of the main constituents of the oil, to obtain the main features of the UV-Vis spectra. This finding is of importance for future works that aim to use Myrcia sylvatica essential oil as a photovoltaic material.

Functional feature embedded space mapping of fMRI data.

PubMed

Hu, Jin; Tian, Jie; Yang, Lei

2006-01-01

We have proposed a new method for fMRI data analysis which is called Functional Feature Embedded Space Mapping (FFESM). Our work mainly focuses on the experimental design with periodic stimuli which can be described by a number of Fourier coefficients in the frequency domain. A nonlinear dimension reduction technique Isomap is applied to the high dimensional features obtained from frequency domain of the fMRI data for the first time. Finally, the presence of activated time series is identified by the clustering method in which the information theoretic criterion of minimum description length (MDL) is used to estimate the number of clusters. The feasibility of our algorithm is demonstrated by real human experiments. Although we focus on analyzing periodic fMRI data, the approach can be extended to analyze non-periodic fMRI data (event-related fMRI) by replacing the Fourier analysis with a wavelet analysis.

Iterative feature refinement for accurate undersampled MR image reconstruction

NASA Astrophysics Data System (ADS)

Wang, Shanshan; Liu, Jianbo; Liu, Qiegen; Ying, Leslie; Liu, Xin; Zheng, Hairong; Liang, Dong

2016-05-01

Accelerating MR scan is of great significance for clinical, research and advanced applications, and one main effort to achieve this is the utilization of compressed sensing (CS) theory. Nevertheless, the existing CSMRI approaches still have limitations such as fine structure loss or high computational complexity. This paper proposes a novel iterative feature refinement (IFR) module for accurate MR image reconstruction from undersampled K-space data. Integrating IFR with CSMRI which is equipped with fixed transforms, we develop an IFR-CS method to restore meaningful structures and details that are originally discarded without introducing too much additional complexity. Specifically, the proposed IFR-CS is realized with three iterative steps, namely sparsity-promoting denoising, feature refinement and Tikhonov regularization. Experimental results on both simulated and in vivo MR datasets have shown that the proposed module has a strong capability to capture image details, and that IFR-CS is comparable and even superior to other state-of-the-art reconstruction approaches.

Unsteady Analysis of Turbine Main Flow Coupled with Secondary Air Flow

NASA Technical Reports Server (NTRS)

Hah, Chunill

2006-01-01

Two numerical approaches are used to model the interaction between the turbine main gas flow and the wheelspace cavity seal flow. The 3-D, unsteady Reynolds-averaged Navier-Stokes equations are solved with a CFD code based on a structured grid to study the interaction between the turbine main gas flow and the wheelspace cavity seal flow. A CFD code based on an unstructured grid is used to solve detailed flow feature in the cavity seal which has a complex geometry. The numerical results confirm various observations from earlier experimental studies under similar flow conditions. When the flow rate through the rim cavity seal is increased, the ingestion of the main turbine flow into the rim seal area decreases drastically. However, a small amount of main gas flow is ingested to the rim seal area even with very high level of seal flow rate. This is due to the complex nature of 3-D, unsteady flow interaction near the hub of the turbine stage.

Biological and functional relevance of CASP predictions

PubMed Central

Liu, Tianyun; Ish‐Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D.

2017-01-01

Abstract Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo‐sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo‐sites), and Ten sites containing important motifs, loops, or key residues with important disease‐associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best‐ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand‐binding sites, most prediction methods have higher performance on apo‐sites than holo‐sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein‐protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein‐protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. PMID:28975675

[THE FEATURES OF PHARMACOKINETICS ANTIBIOTIC CEFTRIAXONE WITH INTRAVENOUS WAY THAT ARE DEPOSITED IN AUTOLOGOUS ERYTHROCYTES AND LEUKOCYTES OF RABBIT].

PubMed

Yussifov, Z; Lokhvitskii, S; Gulyaev, A

2016-11-01

In the experiment on 18 rabbits Сeftriaxone pharmacokinetics after intravenous injection of the medication deposited in autologous erythrocytes and leukocytes were studied. The features of the pharmacokinetics when administered Сeftriaxone in erythrocytes ghost and leukocytes as compared to traditional intravenous drug administration have been determined.It is discussed the possibility of antibiotics transport in the surgical site of infection via cellular carriers in the article. We do the comparative analysis of the main pharmacokinetic parameters of Ceftriaxone in experimental conditions of leukocyte, erythrocyte transport and intravenous way. Based on these results the authors come to the conclusion about the benefits of leukocyte antibiotic transport to the site of surgical infection.

Integrated studies into characteristics of physical fields using discontinuous geomedium models under external loading

NASA Astrophysics Data System (ADS)

Usoltseva Vostrikov, OM, VI; Tsoy, PA; Semenov, VN

2018-03-01

The article presents the laboratory study of deformation in artificial layered geomaterial samples down to failure with the simultaneous measurement of stresses, strains, micro-strains and signals of microseismic emission. The analysis of the synchronized experimental data made it possible to determine features of change in the microseismicity parameters and micro-strain fields in the samples depending on the deformation stage, and also to reveal the dynamics of evolution of microfailures and the main fracture zone.

CompHEP: developments and applications

NASA Astrophysics Data System (ADS)

Boos, E. E.; Bunichev, V. E.; Dubinin, M. N.; Ilyin, V. A.; Savrin, V. I.; CompHEP Collaboration

2017-11-01

New developments of the CompHEP package and its applications to the top quark and the Higgs boson physics at the LHC collider are reviewed. These developments were motivated mainly by the needs of experimental searches of DO (Tevatron) and CMS (LHC) collaborations where identification of the top quark and the Higgs boson in the framework of the Standard Model (SM) or possible extensions of the SM played an important role. New useful features of the CompHEP Graphics User Interface (GUI) are described.

Recent advances in Oral Oncology 2008; squamous cell carcinoma aetiopathogenesis and experimental studies.

PubMed

Bagan, Jose V; Scully, Crispian

2009-07-01

This paper provides a synopsis of the main papers related to the aetiopathogenesis of oral and oropharyngeal squamous cell carcinoma (OSCC) and head and neck SCC (HNSCC) published in 2008 in Oral Oncology - an international interdisciplinary journal which publishes high quality original research, clinical trials and review articles, and all other scientific articles relating to the aetiopathogenesis, epidemiology, prevention, clinical features, diagnosis, treatment, and management of patients with neoplasms in the head and neck, and orofacial disease in patients with malignant disease.

Polymorphism at the ref(2)P locus in Drosophila melanogaster: preliminary experiments concerning the selection mechanisms involved in its maintenance.

PubMed

Fleuriet, A

1981-02-01

It has been shown previously that a polymorphism for two alleles of the ref(2)P locus is a regular feature of French natural populations of Drosophila melanogaster and that this is maintained in laboratory populations raised in cages. In this paper, an experimental population and egg-collection experiments are reported. Differential survival of the three genotypes would be the main factor leading to the equilibrium frequencies, working only in drastic conditions of larval competition.

"Anti-Michael addition" of Grignard reagents to sulfonylacetylenes: synthesis of alkynes.

PubMed

Esteban, Francisco; Boughani, Lazhar; García Ruano, José L; Fraile, Alberto; Alemán, José

2017-05-10

In this work, the addition of Grignard reagents to arylsulfonylacetylenes, which undergoes an "anti-Michael addition", resulting in their alkynylation under very mild conditions is described. The simplicity of the experimental procedure and the functional group tolerance are the main features of this methodology. This is an important advantage over the use of organolithium at -78 °C that we previously reported. Moreover, the synthesis of diynes and other examples showing functional group tolerance in this anti-Michael reaction is also presented.

Chinese character recognition based on Gabor feature extraction and CNN

NASA Astrophysics Data System (ADS)

Xiong, Yudian; Lu, Tongwei; Jiang, Yongyuan

2018-03-01

As an important application in the field of text line recognition and office automation, Chinese character recognition has become an important subject of pattern recognition. However, due to the large number of Chinese characters and the complexity of its structure, there is a great difficulty in the Chinese character recognition. In order to solve this problem, this paper proposes a method of printed Chinese character recognition based on Gabor feature extraction and Convolution Neural Network(CNN). The main steps are preprocessing, feature extraction, training classification. First, the gray-scale Chinese character image is binarized and normalized to reduce the redundancy of the image data. Second, each image is convoluted with Gabor filter with different orientations, and the feature map of the eight orientations of Chinese characters is extracted. Third, the feature map through Gabor filters and the original image are convoluted with learning kernels, and the results of the convolution is the input of pooling layer. Finally, the feature vector is used to classify and recognition. In addition, the generalization capacity of the network is improved by Dropout technology. The experimental results show that this method can effectively extract the characteristics of Chinese characters and recognize Chinese characters.

Mouse epileptic seizure detection with multiple EEG features and simple thresholding technique

NASA Astrophysics Data System (ADS)

Tieng, Quang M.; Anbazhagan, Ashwin; Chen, Min; Reutens, David C.

2017-12-01

Objective. Epilepsy is a common neurological disorder characterized by recurrent, unprovoked seizures. The search for new treatments for seizures and epilepsy relies upon studies in animal models of epilepsy. To capture data on seizures, many applications require prolonged electroencephalography (EEG) with recordings that generate voluminous data. The desire for efficient evaluation of these recordings motivates the development of automated seizure detection algorithms. Approach. A new seizure detection method is proposed, based on multiple features and a simple thresholding technique. The features are derived from chaos theory, information theory and the power spectrum of EEG recordings and optimally exploit both linear and nonlinear characteristics of EEG data. Main result. The proposed method was tested with real EEG data from an experimental mouse model of epilepsy and distinguished seizures from other patterns with high sensitivity and specificity. Significance. The proposed approach introduces two new features: negative logarithm of adaptive correlation integral and power spectral coherence ratio. The combination of these new features with two previously described features, entropy and phase coherence, improved seizure detection accuracy significantly. Negative logarithm of adaptive correlation integral can also be used to compute the duration of automatically detected seizures.

Internal Gravity Waves: Generation and Breaking Mechanisms by Laboratory Experiments

NASA Astrophysics Data System (ADS)

la Forgia, Giovanni; Adduce, Claudia; Falcini, Federico

2016-04-01

Internal gravity waves (IGWs), occurring within estuaries and the coastal oceans, are manifest as large amplitude undulations of the pycnocline. IGWs propagating horizontally in a two layer stratified fluid are studied. The breaking of an IGW of depression shoaling upon a uniformly sloping boundary is investigated experimentally. Breaking dynamics beneath the shoaling waves causes both mixing and wave-induced near-bottom vortices suspending and redistributing the bed material. Laboratory experiments are conducted in a Perspex tank through the standard lock-release method, following the technique described in Sutherland et al. (2013). Each experiment is analysed and the instantaneous pycnocline position is measured, in order to obtain both geometric and kinematic features of the IGW: amplitude, wavelength and celerity. IGWs main features depend on the geometrical parameters that define the initial experimental setting: the density difference between the layers, the total depth, the layers depth ratio, the aspect ratio, and the displacement between the pycnoclines. Relations between IGWs geometric and kinematic features and the initial setting parameters are analysed. The approach of the IGWs toward a uniform slope is investigated in the present experiments. Depending on wave and slope characteristics, different breaking and mixing processes are observed. Sediments are sprinkled on the slope to visualize boundary layer separation in order to analyze the suspension e redistribution mechanisms due to the wave breaking.

ValWorkBench: an open source Java library for cluster validation, with applications to microarray data analysis.

PubMed

Giancarlo, R; Scaturro, D; Utro, F

2015-02-01

The prediction of the number of clusters in a dataset, in particular microarrays, is a fundamental task in biological data analysis, usually performed via validation measures. Unfortunately, it has received very little attention and in fact there is a growing need for software tools/libraries dedicated to it. Here we present ValWorkBench, a software library consisting of eleven well known validation measures, together with novel heuristic approximations for some of them. The main objective of this paper is to provide the interested researcher with the full software documentation of an open source cluster validation platform having the main features of being easily extendible in a homogeneous way and of offering software components that can be readily re-used. Consequently, the focus of the presentation is on the architecture of the library, since it provides an essential map that can be used to access the full software documentation, which is available at the supplementary material website [1]. The mentioned main features of ValWorkBench are also discussed and exemplified, with emphasis on software abstraction design and re-usability. A comparison with existing cluster validation software libraries, mainly in terms of the mentioned features, is also offered. It suggests that ValWorkBench is a much needed contribution to the microarray software development/algorithm engineering community. For completeness, it is important to mention that previous accurate algorithmic experimental analysis of the relative merits of each of the implemented measures [19,23,25], carried out specifically on microarray data, gives useful insights on the effectiveness of ValWorkBench for cluster validation to researchers in the microarray community interested in its use for the mentioned task. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Experimental and theoretical studies of vibrational density of states in Fe3O4 single-crystalline thin films

NASA Astrophysics Data System (ADS)

Handke, B.; Kozłowski, A.; Parliński, K.; Przewoźnik, J.; Ślęzak, T.; Chumakov, A. I.; Niesen, L.; Kąkol, Z.; Korecki, J.

2005-04-01

This paper presents experimental and theoretical studies of lattice vibrations in a single-crystalline Fe3O4(001) thin film. The investigations were carried out in order to see how the lattice dynamics changes at the Verwey transition. Vibrational densities of states (DOS) were obtained from nuclear inelastic scattering (NIS) of synchrotron radiation in the temperature range 25 to 296 K, while theoretical DOS were calculated ab initio within density functional theory. Experimental phonon density of states shows good agreement with calculated DOS, reproducing both the general features of main line groups as well as the groups’ structure. This is also in qualitative accord with heat capacity data, provided that experimental DOS is augmented with that calculated for oxygen atoms. We have observed a gradual change in the NIS raw data as well as the relevant DOS while lowering the temperature. In particular, the main peak in the energy region 15-25 meV shows increasing splitting on cooling. The Lamb-Mössbauer factor calculated in the course of DOS evaluation shows a pronounced drop in the vicinity of the Verwey transition that may be partly connected to the observed abrupt lowering of the count rate at approximately 7 meV for T

Tracking prominent points in image sequences

NASA Astrophysics Data System (ADS)

Hahn, Michael

1994-03-01

Measuring image motion and inferring scene geometry and camera motion are main aspects of image sequence analysis. The determination of image motion and the structure-from-motion problem are tasks that can be addressed independently or in cooperative processes. In this paper we focus on tracking prominent points. High stability, reliability, and accuracy are criteria for the extraction of prominent points. This implies that tracking should work quite well with those features; unfortunately, the reality looks quite different. In the experimental investigations we processed a long sequence of 128 images. This mono sequence is taken in an outdoor environment at the experimental field of Mercedes Benz in Rastatt. Different tracking schemes are explored and the results with respect to stability and quality are reported.

Velocity Measurements in Nasal Cavities by Means of Stereoscopic Piv - Preliminary Tests

NASA Astrophysics Data System (ADS)

Cozzi, Fabio; Felisati, Giovanni; Quadrio, Maurizio

2017-08-01

The prediction of detailed flow patterns in human nasal cavities using computational fluid dynamics (CFD) can provide essential information on the potential relationship between patient-specific geometrical characteristics of the nasal anatomy and health problems, and ultimately led to improved surgery. The complex flow structure and the intricate geometry of the nasal cavities make achieving such goals a challenge for CFD specialists. The need for experimental data to validate and improve the numerical simulations is particularly crucial. To this aim an experimental set-up based on Stereo PIV and a silicon phantom of nasal cavities have been designed and realized at Politecnico di Milano. This work describes the main features and challenges of the set-up along with some preliminary results.

A Preliminary Investigation of Hall Thruster Technology

NASA Technical Reports Server (NTRS)

Gallimore, Alec D.

1997-01-01

A three-year, NASA/BMDO-sponsored experimental program to conduct performance and plume plasma property measurements on two Russian Stationary Plasma Thrusters (SPTs) has been completed. The program utilized experimental facilitates at the University of Michigan's Plasmadynamics and Electric Propulsion Laboratory (PEPL). The main features of the proposed effort were as follows: We Characterized Hall thruster [and arcjet] performance by measuring ion exhaust velocity with probes at various thruster conditions. Used a variety of probe diagnostics in the thruster plume to measure plasma properties and flow properties including T(sub e) and n(sub e), ion current density and ion energy distribution, and electric fields by mapping plasma potential. Used emission spectroscopy to identify species within the plume and to measure electron temperatures.

Modeling of atomization and distribution of drop-liquid fuel in unsteady swirling flows in a combustion chamber and free space

NASA Astrophysics Data System (ADS)

Sviridenkov, A. A.; Toktaliev, P. D.; Tretyakov, V. V.

2018-03-01

Numerical and experimental research of atomization and propagation of drop-liquid phase in swirling flow behind the frontal device of combustion chamber was performed. Numerical procedure was based on steady and unsteady Reynolds equations solution. It's shown that better agreement with experimental data could be obtained with unsteady approach. Fractional time step method was implemented to solve Reynolds equations. Models of primary and secondary breakup of liquid fuel jet in swirling flows are formulated and tested. Typical mean sizes of fuel droplets for base operational regime of swirling device and combustion chamber were calculated. Comparison of main features of internal swirling flow in combustion chamber with unbounded swirling flow was made.

Dynamics of alkali ions-neutral molecules reactions: Radio frequency-guided beam experimental cross-sections and direct quasiclassical trajectory studies

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

Aguilar, J.; Andres, J. de; Lucas, J. M.

2012-11-27

Different reactive processes taking place in collisions between alkali ions and neutral i-C{sub 3}H{sub 7}Cl molecules in the low (center of mass frame) energy range have been studied using an octopole radiofrequency guided-ion-beam apparatus developed in our laboratory. Cross-section energy dependences for all these reactions have been obtained in absolute units. Ab initio electronic structure calculations for those colliding systems evolving on the ground single potential surface have given relevant information on the main topological features of the surfaces. For some of the reactions a dynamic study by 'on the fly' trajectories has complemented the available experimental and electronic structuremore » information.« less

Rhabdomyosarcomas: an overview on the experimental animal models.

PubMed

Zanola, Alessandra; Rossi, Stefania; Faggi, Fiorella; Monti, Eugenio; Fanzani, Alessandro

2012-07-01

Rhabdomyosarcomas (RMS) are aggressive childhood soft-tissue malignancies deriving from mesenchymal progenitors that are committed to muscle-specific lineages. Despite the histopathological signatures associated with three main histological variants, termed embryonal, alveolar and pleomorphic, a plethora of genetic and molecular changes are recognized in RMS. Over the years, exposure to carcinogens or ionizing radiations and gene-targeting approaches in vivo have greatly contributed to disclose some of the mechanisms underlying RMS onset. In this review, we describe the principal distinct features associated with RMS variants and focus on the current available experimental animal models to point out the molecular determinants cooperating with RMS development and progression. © 2012 The Authors Journal of Cellular and Molecular Medicine © 2012 Foundation for Cellular and Molecular Medicine/Blackwell Publishing Ltd.

Feature Selection Has a Large Impact on One-Class Classification Accuracy for MicroRNAs in Plants.

PubMed

Yousef, Malik; Saçar Demirci, Müşerref Duygu; Khalifa, Waleed; Allmer, Jens

2016-01-01

MicroRNAs (miRNAs) are short RNA sequences involved in posttranscriptional gene regulation. Their experimental analysis is complicated and, therefore, needs to be supplemented with computational miRNA detection. Currently computational miRNA detection is mainly performed using machine learning and in particular two-class classification. For machine learning, the miRNAs need to be parametrized and more than 700 features have been described. Positive training examples for machine learning are readily available, but negative data is hard to come by. Therefore, it seems prerogative to use one-class classification instead of two-class classification. Previously, we were able to almost reach two-class classification accuracy using one-class classifiers. In this work, we employ feature selection procedures in conjunction with one-class classification and show that there is up to 36% difference in accuracy among these feature selection methods. The best feature set allowed the training of a one-class classifier which achieved an average accuracy of ~95.6% thereby outperforming previous two-class-based plant miRNA detection approaches by about 0.5%. We believe that this can be improved upon in the future by rigorous filtering of the positive training examples and by improving current feature clustering algorithms to better target pre-miRNA feature selection.

Salient object detection based on multi-scale contrast.

PubMed

Wang, Hai; Dai, Lei; Cai, Yingfeng; Sun, Xiaoqiang; Chen, Long

2018-05-01

Due to the development of deep learning networks, a salient object detection based on deep learning networks, which are used to extract the features, has made a great breakthrough compared to the traditional methods. At present, the salient object detection mainly relies on very deep convolutional network, which is used to extract the features. In deep learning networks, an dramatic increase of network depth may cause more training errors instead. In this paper, we use the residual network to increase network depth and to mitigate the errors caused by depth increase simultaneously. Inspired by image simplification, we use color and texture features to obtain simplified image with multiple scales by means of region assimilation on the basis of super-pixels in order to reduce the complexity of images and to improve the accuracy of salient target detection. We refine the feature on pixel level by the multi-scale feature correction method to avoid the feature error when the image is simplified at the above-mentioned region level. The final full connection layer not only integrates features of multi-scale and multi-level but also works as classifier of salient targets. The experimental results show that proposed model achieves better results than other salient object detection models based on original deep learning networks. Copyright © 2018 Elsevier Ltd. All rights reserved.

Modeling the nonlinear hysteretic response in DAE experiments of Berea sandstone: A case-study

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

Pecorari, Claudio, E-mail: claudio.pecorari@hotmail.com

2015-03-31

Dynamic acousto-elasticity (DAE) allows probing the instantaneous state of a material while the latter slowly and periodically is changed by an external, dynamic source. In DAE investigations of geo-materials, hysteresis of the material's modulus defect displays intriguing features which have not yet been interpreted in terms of any specific mechanism occurring at atomic or mesoscale. Here, experimental results on dry Berea sandstone, which is the rock type best investigated by means of a DAE technique, are analyzed in terms of three rheological models providing simplified representations of mechanisms involving dislocations interacting with point defects which are distributed along the dislocations'more » core or glide planes, and microcracks with finite stiffness in compression. Constitutive relations linking macroscopic strain and stress are derived. From the latter, the modulus defect associated to each mechanism is recovered. These models are employed to construct a composite one which is capable of reproducing several of the main features observed in the experimental data. The limitations of the present approach and, possibly, of the current implementation of DAE are discussed.« less

X-ray and 1H-NMR spectroscopic studies of the structures and conformations of the new nootropic agents RU-35929, RU-47010 and RU-35965

NASA Astrophysics Data System (ADS)

Amato, Maria E.; Bandoli, Giuliano; Casellato, Umberto; Pappalardo, Giuseppe C.; Toja, Emilio

1990-10-01

The crystal and molecular structures of the nootropics (±)1-benzenesulphonyl-2-oxo-5-ethoxypyrrolidine ( 1), (±)1-(3-pyridinylsulphonyl)-2-oxo-5-ethoxypyrrolidine ( 2) and (±)1-benzenesulphonyl-2-oxo-5-isopropyloxypyrrolidine ( 3) have been determined by X-ray analysis. The solution conformation of 1, 2 and 3 has been investigated by 1H NMR spectroscopy. In the solid state, the main feature consists of the similar structural parameters and conformations, with the exception of the conformation adopted by the 5-ethoxy moiety which changes on passing from 1 to 2. The solid state overall enveloped conformation of the 2-pyrrolidinone ring for the three nootropics is found to be retained in solution on the basis of NMR evidence. Comparison between calculated and experimental coupling constant values shows that one of the two possible puckered opposite conformational isomers (half-chair shapes) occurs in solution. The relative pharmacological potencies of 1, 2 and 3 cannot therefore be interpreted in terms of the different conformation features presently detectable by available experimental methods.

Modeling place field activity with hierarchical slow feature analysis

PubMed Central

Schönfeld, Fabian; Wiskott, Laurenz

2015-01-01

What are the computational laws of hippocampal activity? In this paper we argue for the slowness principle as a fundamental processing paradigm behind hippocampal place cell firing. We present six different studies from the experimental literature, performed with real-life rats, that we replicated in computer simulations. Each of the chosen studies allows rodents to develop stable place fields and then examines a distinct property of the established spatial encoding: adaptation to cue relocation and removal; directional dependent firing in the linear track and open field; and morphing and scaling the environment itself. Simulations are based on a hierarchical Slow Feature Analysis (SFA) network topped by a principal component analysis (ICA) output layer. The slowness principle is shown to account for the main findings of the presented experimental studies. The SFA network generates its responses using raw visual input only, which adds to its biological plausibility but requires experiments performed in light conditions. Future iterations of the model will thus have to incorporate additional information, such as path integration and grid cell activity, in order to be able to also replicate studies that take place during darkness. PMID:26052279

Experimental and theoretical study of the structural environment of magnesium in minerals and silicate glasses using X-ray absorption near-edge structure

NASA Astrophysics Data System (ADS)

Trcera, Nicolas; Cabaret, Delphine; Rossano, Stéphanie; Farges, François; Flank, Anne-Marie; Lagarde, Pierre

2009-05-01

X-ray absorption spectroscopy at the Mg K-edge is used to obtain information on magnesium environment in minerals, silicate and alumino-silicate glasses. First-principles XANES calculations are performed for minerals using a plane-wave density functional formalism with core-hole effects treated in a supercell approach. The good agreement obtained between experimental and theoretical spectra provides useful information to interpret the spectral features. With the help of calculation, the position of the first peak of XANES spectra is related to both coordination and polyhedron distortion changes. In alumino-silicate glasses, magnesium is found to be mainly 5-fold coordinated to oxygen whatever the aluminum saturation index value. In silicate glasses, magnesium coordination increases from 4 in Cs-, Rb- and K-bearing glasses to 5 in Na- and Li-bearing glasses but remains equal as the polymerization degree of the glass varies. The variation of the C feature (position and intensity) is strongly related to the alkali type providing information on the medium range order.

A Preliminary Investigation of Hall Thruster Technology

NASA Technical Reports Server (NTRS)

Gallimore, Alec D.

1997-01-01

A three-year NASA/BMDO-sponsored experimental program to conduct performance and plume plasma property measurements on two Russian Stationary Plasma Thrusters (SPTs) has been completed. The program utilized experimental facilitates at the University of Michigan's Plasmadynamics and Electric Propulsion Laboratory (PEPL). The main features of the proposed effort were as follows: (1) Characterized Hall thruster (and arcjet) performance by measuring ion exhaust velocity with probes at various thruster conditions; (2) Used a variety of probe diagnostics in the thruster plume to measure plasma properties and flow properties including T(sub e) and n(sub e) ion current density and ion energy distribution, and electric fields by mapping plasma potential; (3) Used emission spectroscopy to identify species within the plume and to measure electron temperatures. A key and unique feature of our research was our collaboration with Russian Hall thruster researcher Dr. Sergey A Khartov, Deputy Dean of International Relations at the Moscow Aviation Institute (MAI). His activities in this program included consulting on and participation in research at PEPL through use of a MAI-built SPT and ion energy probe.

Combined measurement system for double shield tunnel boring machine guidance based on optical and visual methods.

PubMed

Lin, Jiarui; Gao, Kai; Gao, Yang; Wang, Zheng

2017-10-01

In order to detect the position of the cutting shield at the head of a double shield tunnel boring machine (TBM) during the excavation, this paper develops a combined measurement system which is mainly composed of several optical feature points, a monocular vision sensor, a laser target sensor, and a total station. The different elements of the combined system are mounted on the TBM in suitable sequence, and the position of the cutting shield in the reference total station frame is determined by coordinate transformations. Subsequently, the structure of the feature points and matching technique for them are expounded, the position measurement method based on monocular vision is presented, and the calibration methods for the unknown relationships among different parts of the system are proposed. Finally, a set of experimental platforms to simulate the double shield TBM is established, and accuracy verification experiments are conducted. Experimental results show that the mean deviation of the system is 6.8 mm, which satisfies the requirements of double shield TBM guidance.

The Quantum Cheshire Cat effect: Theoretical basis and observational implications

NASA Astrophysics Data System (ADS)

Duprey, Q.; Kanjilal, S.; Sinha, U.; Home, D.; Matzkin, A.

2018-04-01

The Quantum Cheshire Cat (QCC) is an effect introduced recently within the Weak Measurements framework. The main feature of the QCC effect is that a property of a quantum particle appears to be spatially separated from its position. The status of this effect has however remained unclear, as claims of experimental observation of the QCC have been disputed by strong criticism of the experimental as well as the theoretical aspects of the effect. In this paper we clarify in what precise sense the QCC can be regarded as an unambiguous consequence of the standard quantum mechanical formalism applied to describe quantum pointers weakly coupled to a system. In light of this clarification, the raised criticisms of the QCC effect are rebutted. We further point out that the limitations of the experiments performed to date imply that a loophole-free experimental demonstration of the QCC has not yet been achieved.

An experimental and theoretical model of children’s search behavior in relation to target conspicuity and spatial distribution

NASA Astrophysics Data System (ADS)

Rosetti, Marcos Francisco; Pacheco-Cobos, Luis; Larralde, Hernán; Hudson, Robyn

2010-11-01

This work explores search trajectories of children attempting to find targets distributed on a playing field. This task, of ludic nature, was developed to test the effect of conspicuity and spatial distribution of targets on the searcher’s performance. The searcher’s path was recorded by a Global Positioning System (GPS) device attached to the child’s waist. Participants were not rewarded nor their performance rated. Variation in the conspicuity of the targets influenced search performance as expected; cryptic targets resulted in slower searches and longer, more tortuous paths. Extracting the main features of the paths showed that the children: (1) paid little attention to the spatial distribution and at least in the conspicuous condition approximately followed a nearest neighbor pattern of target collection, (2) were strongly influenced by the conspicuity of the targets. We implemented a simple statistical model for the search rules mimicking the children’s behavior at the level of individual (coarsened) steps. The model reproduced the main features of the children’s paths without the participation of memory or planning.

Chaotic behaviour of Zeeman machines at introductory course of mechanics

NASA Astrophysics Data System (ADS)

Nagy, Péter; Tasnádi, Péter

2016-05-01

Investigation of chaotic motions and cooperative systems offers a magnificent opportunity to involve modern physics into the basic course of mechanics taught to engineering students. In the present paper it will be demonstrated that Zeeman Machine can be a versatile and motivating tool for students to get introductory knowledge about chaotic motion via interactive simulations. It works in a relatively simple way and its properties can be understood very easily. Since the machine can be built easily and the simulation of its movement is also simple the experimental investigation and the theoretical description can be connected intuitively. Although Zeeman Machine is known mainly for its quasi-static and catastrophic behaviour, its dynamic properties are also of interest with its typical chaotic features. By means of a periodically driven Zeeman Machine a wide range of chaotic properties of the simple systems can be demonstrated such as bifurcation diagrams, chaotic attractors, transient chaos and so on. The main goal of this paper is the presentation of an interactive learning material for teaching the basic features of the chaotic systems through the investigation of the Zeeman Machine.

“Feature Detection” vs. “Predictive Coding” Models of Plant Behavior

PubMed Central

Calvo, Paco; Baluška, František; Sims, Andrew

2016-01-01

In this article we consider the possibility that plants exhibit anticipatory behavior, a mark of intelligence. If plants are able to anticipate and respond accordingly to varying states of their surroundings, as opposed to merely responding online to environmental contingencies, then such capacity may be in principle testable, and subject to empirical scrutiny. Our main thesis is that adaptive behavior can only take place by way of a mechanism that predicts the environmental sources of sensory stimulation. We propose to test for anticipation in plants experimentally by contrasting two empirical hypotheses: “feature detection” and “predictive coding.” We spell out what these contrasting hypotheses consist of by way of illustration from the animal literature, and consider how to transfer the rationale involved to the plant literature. PMID:27757094

Comparison of multiobjective evolutionary algorithms: empirical results.

PubMed

Zitzler, E; Deb, K; Thiele, L

2000-01-01

In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly in converging to the Pareto-optimal front (e.g., multimodality and deception). By investigating these different problem features separately, it is possible to predict the kind of problems to which a certain technique is or is not well suited. However, in contrast to what was suspected beforehand, the experimental results indicate a hierarchy of the algorithms under consideration. Furthermore, the emerging effects are evidence that the suggested test functions provide sufficient complexity to compare multiobjective optimizers. Finally, elitism is shown to be an important factor for improving evolutionary multiobjective search.

Placenta and Placental Derivatives in Regenerative Therapies: Experimental Studies, History, and Prospects

PubMed Central

Prokopyuk, Volodymyr; Pogozhykh, Denys

2018-01-01

Placental structures, capable to persist in a genetically foreign organism, are a natural model of allogeneic engraftment carrying a number of distinctive properties. In this review, the main features of the placenta and its derivatives such as structure, cellular composition, immunological and endocrine aspects, and the ability to invasion and deportation are discussed. These features are considered from a perspective that determines the placental material as a unique source for regenerative cell therapies and a lesson for immunological tolerance. A historical overview of clinical applications of placental extracts, cells, and tissue components is described. Empirically accumulated data are summarized and compared with modern research. Furthermore, we define scopes and outlooks of application of placental cells and tissues in the rapidly progressing field of regenerative medicine. PMID:29535770

Computational model for vocal tract dynamics in a suboscine bird.

PubMed

Assaneo, M F; Trevisan, M A

2010-09-01

In a recent work, active use of the vocal tract has been reported for singing oscines. The reconfiguration of the vocal tract during song serves to match its resonances to the syringeal fundamental frequency, demonstrating a precise coordination of the two main pieces of the avian vocal system for songbirds characterized by tonal songs. In this work we investigated the Great Kiskadee (Pitangus sulfuratus), a suboscine bird whose calls display a rich harmonic content. Using a recently developed mathematical model for the syrinx and a mobile vocal tract, we set up a computational model that provides a plausible reconstruction of the vocal tract movement using a few spectral features taken from the utterances. Moreover, synthetic calls were generated using the articulated vocal tract that accounts for all the acoustical features observed experimentally.

Exploiting Information Diffusion Feature for Link Prediction in Sina Weibo

NASA Astrophysics Data System (ADS)

Li, Dong; Zhang, Yongchao; Xu, Zhiming; Chu, Dianhui; Li, Sheng

2016-01-01

The rapid development of online social networks (e.g., Twitter and Facebook) has promoted research related to social networks in which link prediction is a key problem. Although numerous attempts have been made for link prediction based on network structure, node attribute and so on, few of the current studies have considered the impact of information diffusion on link creation and prediction. This paper mainly addresses Sina Weibo, which is the largest microblog platform with Chinese characteristics, and proposes the hypothesis that information diffusion influences link creation and verifies the hypothesis based on real data analysis. We also detect an important feature from the information diffusion process, which is used to promote link prediction performance. Finally, the experimental results on Sina Weibo dataset have demonstrated the effectiveness of our methods.

Exploiting Information Diffusion Feature for Link Prediction in Sina Weibo.

PubMed

Li, Dong; Zhang, Yongchao; Xu, Zhiming; Chu, Dianhui; Li, Sheng

2016-01-28

The rapid development of online social networks (e.g., Twitter and Facebook) has promoted research related to social networks in which link prediction is a key problem. Although numerous attempts have been made for link prediction based on network structure, node attribute and so on, few of the current studies have considered the impact of information diffusion on link creation and prediction. This paper mainly addresses Sina Weibo, which is the largest microblog platform with Chinese characteristics, and proposes the hypothesis that information diffusion influences link creation and verifies the hypothesis based on real data analysis. We also detect an important feature from the information diffusion process, which is used to promote link prediction performance. Finally, the experimental results on Sina Weibo dataset have demonstrated the effectiveness of our methods.

Image processing based detection of lung cancer on CT scan images

NASA Astrophysics Data System (ADS)

Abdillah, Bariqi; Bustamam, Alhadi; Sarwinda, Devvi

2017-10-01

In this paper, we implement and analyze the image processing method for detection of lung cancer. Image processing techniques are widely used in several medical problems for picture enhancement in the detection phase to support the early medical treatment. In this research we proposed a detection method of lung cancer based on image segmentation. Image segmentation is one of intermediate level in image processing. Marker control watershed and region growing approach are used to segment of CT scan image. Detection phases are followed by image enhancement using Gabor filter, image segmentation, and features extraction. From the experimental results, we found the effectiveness of our approach. The results show that the best approach for main features detection is watershed with masking method which has high accuracy and robust.

Distributed cable sensors with memory feature for post-disaster damage assessment

NASA Astrophysics Data System (ADS)

Chen, Genda; McDaniel, Ryan D.; Pommerenke, David J.; Sun, Shishuang

2005-05-01

A new design of distributed crack sensors is presented for the condition assessment of reinforced concrete (RC) structures during and immediately after an earthquake event. This study is mainly focused on the performance of cable sensors under dynamic loading, particularly their ability to memorize the crack history of an RC member. This unique memory feature enables the post-earthquake condition assessment of structural members such as RC columns, in which the earthquake-induced cracks are closed immediately after an earthquake event due to gravity loads and they are visually undetectable. Factors affecting the onset of the memory feature were investigated experimentally with small-scale RC beams under cyclic loading. Test results indicated that both crack width and the number of loading cycles were instrumental in the onset of the memory feature of cable sensors. Practical issues related to dynamic acquisition with the sensors were discussed. The sensors were proven to be fatigue resistant from the shake table tests of RC columns. They continued to show useful signal after the columns can no longer support additional loads.

Real-Time Tracking by Double Templates Matching Based on Timed Motion History Image with HSV Feature

PubMed Central

Li, Zhiyong; Li, Pengfei; Yu, Xiaoping; Hashem, Mervat

2014-01-01

It is a challenge to represent the target appearance model for moving object tracking under complex environment. This study presents a novel method with appearance model described by double templates based on timed motion history image with HSV color histogram feature (tMHI-HSV). The main components include offline template and online template initialization, tMHI-HSV-based candidate patches feature histograms calculation, double templates matching (DTM) for object location, and templates updating. Firstly, we initialize the target object region and calculate its HSV color histogram feature as offline template and online template. Secondly, the tMHI-HSV is used to segment the motion region and calculate these candidate object patches' color histograms to represent their appearance models. Finally, we utilize the DTM method to trace the target and update the offline template and online template real-timely. The experimental results show that the proposed method can efficiently handle the scale variation and pose change of the rigid and nonrigid objects, even in illumination change and occlusion visual environment. PMID:24592185

Biological and functional relevance of CASP predictions.

PubMed

Liu, Tianyun; Ish-Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D; Altman, Russ B

2018-03-01

Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo-sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo-sites), and Ten sites containing important motifs, loops, or key residues with important disease-associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best-ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand-binding sites, most prediction methods have higher performance on apo-sites than holo-sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein-protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein-protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. © 2017 The Authors Proteins: Structure, Function and Bioinformatics Published by Wiley Periodicals, Inc.

Feature Extraction for Track Section Status Classification Based on UGW Signals

PubMed Central

Yang, Yuan; Shi, Lin

2018-01-01

Track status classification is essential for the stability and safety of railway operations nowadays, when railway networks are becoming more and more complex and broad. In this situation, monitoring systems are already a key element in applications dedicated to evaluating the status of a certain track section, often determining whether it is free or occupied by a train. Different technologies have already been involved in the design of monitoring systems, including ultrasonic guided waves (UGW). This work proposes the use of the UGW signals captured by a track monitoring system to extract the features that are relevant for determining the corresponding track section status. For that purpose, three features of UGW signals have been considered: the root mean square value, the energy, and the main frequency components. Experimental results successfully validated how these features can be used to classify the track section status into free, occupied and broken. Furthermore, spatial and temporal dependencies among these features were analysed in order to show how they can improve the final classification performance. Finally, a preliminary high-level classification system based on deep learning networks has been envisaged for future works. PMID:29673156

Simultenious binary hash and features learning for image retrieval

NASA Astrophysics Data System (ADS)

Frantc, V. A.; Makov, S. V.; Voronin, V. V.; Marchuk, V. I.; Semenishchev, E. A.; Egiazarian, K. O.; Agaian, S.

2016-05-01

Content-based image retrieval systems have plenty of applications in modern world. The most important one is the image search by query image or by semantic description. Approaches to this problem are employed in personal photo-collection management systems, web-scale image search engines, medical systems, etc. Automatic analysis of large unlabeled image datasets is virtually impossible without satisfactory image-retrieval technique. It's the main reason why this kind of automatic image processing has attracted so much attention during recent years. Despite rather huge progress in the field, semantically meaningful image retrieval still remains a challenging task. The main issue here is the demand to provide reliable results in short amount of time. This paper addresses the problem by novel technique for simultaneous learning of global image features and binary hash codes. Our approach provide mapping of pixel-based image representation to hash-value space simultaneously trying to save as much of semantic image content as possible. We use deep learning methodology to generate image description with properties of similarity preservation and statistical independence. The main advantage of our approach in contrast to existing is ability to fine-tune retrieval procedure for very specific application which allow us to provide better results in comparison to general techniques. Presented in the paper framework for data- dependent image hashing is based on use two different kinds of neural networks: convolutional neural networks for image description and autoencoder for feature to hash space mapping. Experimental results confirmed that our approach has shown promising results in compare to other state-of-the-art methods.

Present status of numerical modeling of hydrogen negative ion source plasmas and its comparison with experiments: Japanese activities and their collaboration with experimental groups

NASA Astrophysics Data System (ADS)

Hatayama, A.; Nishioka, S.; Nishida, K.; Mattei, S.; Lettry, J.; Miyamoto, K.; Shibata, T.; Onai, M.; Abe, S.; Fujita, S.; Yamada, S.; Fukano, A.

2018-06-01

The present status of kinetic modeling of particle dynamics in hydrogen negative ion (H‑) source plasmas and their comparisons with experiments are reviewed and discussed with some new results. The main focus is placed on the following topics, which are important for the research and development of H‑ sources for intense and high-quality H‑ ion beams: (i) effects of non-equilibrium features of electron energy distribution function on volume and surface H‑ production, (ii) the origin of the spatial non-uniformity in giant multi-cusp arc-discharge H‑ sources, (iii) capacitive to inductive (E to H) mode transition in radio frequency-inductively coupled plasma H‑ sources and (iv) extraction physics of H‑ ions and beam optics, especially the present understanding of the meniscus formation in strongly electronegative plasmas (so-called ion–ion plasmas) and its effect on beam optics. For these topics, mainly Japanese modeling activities, and their domestic and international collaborations with experimental studies, are introduced with some examples showing how models have been improved and to what extent the modeling studies can presently contribute to improving the source performance. Close collaboration between experimental and modeling activities is indispensable for the validation/improvement of the modeling and its contribution to the source design/development.

Multi-Temporal Classification and Change Detection Using Uav Images

NASA Astrophysics Data System (ADS)

Makuti, S.; Nex, F.; Yang, M. Y.

2018-05-01

In this paper different methodologies for the classification and change detection of UAV image blocks are explored. UAV is not only the cheapest platform for image acquisition but it is also the easiest platform to operate in repeated data collections over a changing area like a building construction site. Two change detection techniques have been evaluated in this study: the pre-classification and the post-classification algorithms. These methods are based on three main steps: feature extraction, classification and change detection. A set of state of the art features have been used in the tests: colour features (HSV), textural features (GLCM) and 3D geometric features. For classification purposes Conditional Random Field (CRF) has been used: the unary potential was determined using the Random Forest algorithm while the pairwise potential was defined by the fully connected CRF. In the performed tests, different feature configurations and settings have been considered to assess the performance of these methods in such challenging task. Experimental results showed that the post-classification approach outperforms the pre-classification change detection method. This was analysed using the overall accuracy, where by post classification have an accuracy of up to 62.6 % and the pre classification change detection have an accuracy of 46.5 %. These results represent a first useful indication for future works and developments.

The very low angle detector for high-energy inelastic neutron scattering on the VESUVIO spectrometer

NASA Astrophysics Data System (ADS)

Perelli Cippo, E.; Gorini, G.; Tardocchi, M.; Pietropaolo, A.; Andreani, C.; Senesi, R.; Rhodes, N. J.; Schooneveld, E. M.

2008-05-01

The Very Low Angle Detector (VLAD) bank has been installed on the VESUVIO spectrometer at the ISIS spallation neutron source. The new device allows for high-energy inelastic neutron scattering measurements, at energies above 1 eV, maintaining the wave vector transfer lower than 10Å-1. This opens a still unexplored region of the kinematical (q, ω) space, enabling new and challenging experimental investigations in condensed matter. This paper describes the main instrumental features of the VLAD device, including instrument design, detector response, and calibration procedure.

Polymorphism at the REF(2)P Locus in DROSOPHILA MELANOGASTER: Preliminary Experiments concerning the Selection Mechanisms Involved in Its Maintenance

PubMed Central

Fleuriet, Annie

1981-01-01

It has been shown previously that a polymorphism for two alleles of the ref(2)P locus is a regular feature of French natural populations of Drosophila melanogaster and that this is maintained in laboratory populations raised in cages. In this paper, an experimental population and egg-collection experiments are reported. Differential survival of the three genotypes would be the main factor leading to the equilibrium frequencies, working only in drastic conditions of larval competition. PMID:6791986

Mesh refinement in a two-dimensional large eddy simulation of a forced shear layer

NASA Technical Reports Server (NTRS)

Claus, R. W.; Huang, P. G.; Macinnes, J. M.

1989-01-01

A series of large eddy simulations are made of a forced shear layer and compared with experimental data. Several mesh densities were examined to separate the effect of numerical inaccuracy from modeling deficiencies. The turbulence model that was used to represent small scale, 3-D motions correctly predicted some gross features of the flow field, but appears to be structurally incorrect. The main effect of mesh refinement was to act as a filter on the scale of vortices that developed from the inflow boundary conditions.

Electronic states with nontrivial topology in Dirac materials

NASA Astrophysics Data System (ADS)

Turkevich, R. V.; Perov, A. A.; Protogenov, A. P.; Chulkov, E. V.

2017-08-01

The theoretical studies of phase states with a linear dispersion of the spectrum of low-energy electron excitations have been reviewed. Some main properties and methods of experimental study of these states in socalled Dirac materials have been discussed in detail. The results of modern studies of symmetry-protected electronic states with nontrivial topology have been reported. Combination of approaches based on geometry with homotopic topology methods and results of condensed matter physics makes it possible to clarify new features of topological insulators, as well as Dirac and Weyl semimetals.

Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching

PubMed Central

Guo, Yanrong; Gao, Yaozong

2016-01-01

Automatic and reliable segmentation of the prostate is an important but difficult task for various clinical applications such as prostate cancer radiotherapy. The main challenges for accurate MR prostate localization lie in two aspects: (1) inhomogeneous and inconsistent appearance around prostate boundary, and (2) the large shape variation across different patients. To tackle these two problems, we propose a new deformable MR prostate segmentation method by unifying deep feature learning with the sparse patch matching. First, instead of directly using handcrafted features, we propose to learn the latent feature representation from prostate MR images by the stacked sparse auto-encoder (SSAE). Since the deep learning algorithm learns the feature hierarchy from the data, the learned features are often more concise and effective than the handcrafted features in describing the underlying data. To improve the discriminability of learned features, we further refine the feature representation in a supervised fashion. Second, based on the learned features, a sparse patch matching method is proposed to infer a prostate likelihood map by transferring the prostate labels from multiple atlases to the new prostate MR image. Finally, a deformable segmentation is used to integrate a sparse shape model with the prostate likelihood map for achieving the final segmentation. The proposed method has been extensively evaluated on the dataset that contains 66 T2-wighted prostate MR images. Experimental results show that the deep-learned features are more effective than the handcrafted features in guiding MR prostate segmentation. Moreover, our method shows superior performance than other state-of-the-art segmentation methods. PMID:26685226

Automated analysis and classification of melanocytic tumor on skin whole slide images.

PubMed

Xu, Hongming; Lu, Cheng; Berendt, Richard; Jha, Naresh; Mandal, Mrinal

2018-06-01

This paper presents a computer-aided technique for automated analysis and classification of melanocytic tumor on skin whole slide biopsy images. The proposed technique consists of four main modules. First, skin epidermis and dermis regions are segmented by a multi-resolution framework. Next, epidermis analysis is performed, where a set of epidermis features reflecting nuclear morphologies and spatial distributions is computed. In parallel with epidermis analysis, dermis analysis is also performed, where dermal cell nuclei are segmented and a set of textural and cytological features are computed. Finally, the skin melanocytic image is classified into different categories such as melanoma, nevus or normal tissue by using a multi-class support vector machine (mSVM) with extracted epidermis and dermis features. Experimental results on 66 skin whole slide images indicate that the proposed technique achieves more than 95% classification accuracy, which suggests that the technique has the potential to be used for assisting pathologists on skin biopsy image analysis and classification. Copyright © 2018 Elsevier Ltd. All rights reserved.

JANIS: NEA JAva-based Nuclear Data Information System

NASA Astrophysics Data System (ADS)

Soppera, Nicolas; Bossant, Manuel; Cabellos, Oscar; Dupont, Emmeric; Díez, Carlos J.

2017-09-01

JANIS (JAva-based Nuclear Data Information System) software is developed by the OECD Nuclear Energy Agency (NEA) Data Bank to facilitate the visualization and manipulation of nuclear data, giving access to evaluated nuclear data libraries, such as ENDF, JEFF, JENDL, TENDL etc., and also to experimental nuclear data (EXFOR) and bibliographical references (CINDA). It is available as a standalone Java program, downloadable and distributed on DVD and also a web application available on the NEA website. One of the main new features in JANIS is the scripting capability via command line, which notably automatizes plots generation and permits automatically extracting data from the JANIS database. Recent NEA software developments rely on these JANIS features to access nuclear data, for example the Nuclear Data Sensitivity Tool (NDaST) makes use of covariance data in BOXER and COVERX formats, which are retrieved from the JANIS database. New features added in this version of the JANIS software are described along this paper with some examples.

Gamma-ray Signal from Dark Matter Annihilation Mediated by Mixing Slepton

NASA Astrophysics Data System (ADS)

Teng, Fei

2016-03-01

In order to reconcile the tension between the collider SUSY particle search and the dark matter relic density constraint, we free ourselves from the simplest CMSSM model and find a large parameter space in which a sub-TeV bino dark matter may comply with all the current experimental constraints. In this so-called incredible bulk region, dark matter mainly annihilates through the t channel exchange of a mixing slepton into a leptonic final state. We have explored this proposal and studied the resultant spectrum feature. We are going to show that the line signal produced by the γγ and γZ final state will give some indications to the mixing angle and CP-violation phase of the slepton sector. On the other hand, internal bremsstrahlung (IB) feature will be easier to get observed by future experiments, with sensitivity around 10-29cm3 /s . Unlike some other models, our IB signal is dominated by the collinear limit of the final state radiation amplitude and shows a bump-like feature.

Pollen Image Recognition Based on DGDB-LBP Descriptor

NASA Astrophysics Data System (ADS)

Han, L. P.; Xie, Y. H.

2018-01-01

In this paper, we propose DGDB-LBP, a local binary pattern descriptor based on the pixel blocks in the dominant gradient direction. Differing from traditional LBP and its variants, DGDB-LBP encodes by comparing the main gradient magnitude of each block rather than the single pixel value or the average of pixel blocks, in doing so, it reduces the influence of noise on pollen images and eliminates redundant and non-informative features. In order to fully describe the texture features of pollen images and analyze it under multi-scales, we propose a new sampling strategy, which uses three types of operators to extract the radial, angular and multiple texture features under different scales. Considering that the pollen images have some degree of rotation under the microscope, we propose the adaptive encoding direction, which is determined by the texture distribution of local region. Experimental results on the Pollenmonitor dataset show that the average correct recognition rate of our method is superior to other pollen recognition methods in recent years.

Real-time skin feature identification in a time-sequential video stream

NASA Astrophysics Data System (ADS)

Kramberger, Iztok

2005-04-01

Skin color can be an important feature when tracking skin-colored objects. Particularly this is the case for computer-vision-based human-computer interfaces (HCI). Humans have a highly developed feeling of space and, therefore, it is reasonable to support this within intelligent HCI, where the importance of augmented reality can be foreseen. Joining human-like interaction techniques within multimodal HCI could, or will, gain a feature for modern mobile telecommunication devices. On the other hand, real-time processing plays an important role in achieving more natural and physically intuitive ways of human-machine interaction. The main scope of this work is the development of a stereoscopic computer-vision hardware-accelerated framework for real-time skin feature identification in the sense of a single-pass image segmentation process. The hardware-accelerated preprocessing stage is presented with the purpose of color and spatial filtering, where the skin color model within the hue-saturation-value (HSV) color space is given with a polyhedron of threshold values representing the basis of the filter model. An adaptive filter management unit is suggested to achieve better segmentation results. This enables the adoption of filter parameters to the current scene conditions in an adaptive way. Implementation of the suggested hardware structure is given at the level of filed programmable system level integrated circuit (FPSLIC) devices using an embedded microcontroller as their main feature. A stereoscopic clue is achieved using a time-sequential video stream, but this shows no difference for real-time processing requirements in terms of hardware complexity. The experimental results for the hardware-accelerated preprocessing stage are given by efficiency estimation of the presented hardware structure using a simple motion-detection algorithm based on a binary function.

Simulation and performance analysis of a novel high-accuracy sheathless microfluidic impedance cytometer with coplanar electrode layout.

PubMed

Caselli, Federica; Bisegna, Paolo

2017-10-01

The performance of a novel microfluidic impedance cytometer (MIC) with coplanar configuration is investigated in silico. The main feature of the device is the ability to provide accurate particle-sizing despite the well-known measurement sensitivity to particle trajectory. The working principle of the device is presented and validated by means of an original virtual laboratory providing close-to-experimental synthetic data streams. It is shown that a metric correlating with particle trajectory can be extracted from the signal traces and used to compensate the trajectory-induced error in the estimated particle size, thus reaching high-accuracy. An analysis of relevant parameters of the experimental setup is also presented. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Dynamics of short-pulse generation via spectral filtering from intensely excited gain-switched 1.55-μm distributed-feedback laser diodes.

PubMed

Chen, Shaoqiang; Yoshita, Masahiro; Sato, Aya; Ito, Takashi; Akiyama, Hidefumi; Yokoyama, Hiroyuki

2013-05-06

Picosecond-pulse-generation dynamics and pulse-width limiting factors via spectral filtering from intensely pulse-excited gain-switched 1.55-μm distributed-feedback laser diodes were studied. The spectral and temporal characteristics of the spectrally filtered pulses indicated that the short-wavelength component stems from the initial part of the gain-switched main pulse and has a nearly linear down-chirp of 5.2 ps/nm, whereas long-wavelength components include chirped pulse-lasing components and steady-state-lasing components. Rate-equation calculations with a model of linear change in refractive index with carrier density explained the major features of the experimental results. The analysis of the expected pulse widths with optimum spectral widths was also consistent with the experimental data.

First principles molecular dynamics of molten NaCl

NASA Astrophysics Data System (ADS)

Galamba, N.; Costa Cabral, B. J.

2007-03-01

First principles Hellmann-Feynman molecular dynamics (HFMD) results for molten NaCl at a single state point are reported. The effect of induction forces on the structure and dynamics of the system is studied by comparison of the partial radial distribution functions and the velocity and force autocorrelation functions with those calculated from classical MD based on rigid-ion and shell-model potentials. The first principles results reproduce the main structural features of the molten salt observed experimentally, whereas they are incorrectly described by both rigid-ion and shell-model potentials. Moreover, HFMD Green-Kubo self-diffusion coefficients are in closer agreement with experimental data than those predicted by classical MD. A comprehensive discussion of MD results for molten NaCl based on different ab initio parametrized polarizable interionic potentials is also given.

Pedestrian Detection in Far-Infrared Daytime Images Using a Hierarchical Codebook of SURF

PubMed Central

Besbes, Bassem; Rogozan, Alexandrina; Rus, Adela-Maria; Bensrhair, Abdelaziz; Broggi, Alberto

2015-01-01

One of the main challenges in intelligent vehicles concerns pedestrian detection for driving assistance. Recent experiments have showed that state-of-the-art descriptors provide better performances on the far-infrared (FIR) spectrum than on the visible one, even in daytime conditions, for pedestrian classification. In this paper, we propose a pedestrian detector with on-board FIR camera. Our main contribution is the exploitation of the specific characteristics of FIR images to design a fast, scale-invariant and robust pedestrian detector. Our system consists of three modules, each based on speeded-up robust feature (SURF) matching. The first module allows generating regions-of-interest (ROI), since in FIR images of the pedestrian shapes may vary in large scales, but heads appear usually as light regions. ROI are detected with a high recall rate with the hierarchical codebook of SURF features located in head regions. The second module consists of pedestrian full-body classification by using SVM. This module allows one to enhance the precision with low computational cost. In the third module, we combine the mean shift algorithm with inter-frame scale-invariant SURF feature tracking to enhance the robustness of our system. The experimental evaluation shows that our system outperforms, in the FIR domain, the state-of-the-art Haar-like Adaboost-cascade, histogram of oriented gradients (HOG)/linear SVM (linSVM) and MultiFtrpedestrian detectors, trained on the FIR images. PMID:25871724

Distribution of genotype network sizes in sequence-to-structure genotype-phenotype maps.

PubMed

Manrubia, Susanna; Cuesta, José A

2017-04-01

An essential quantity to ensure evolvability of populations is the navigability of the genotype space. Navigability, understood as the ease with which alternative phenotypes are reached, relies on the existence of sufficiently large and mutually attainable genotype networks. The size of genotype networks (e.g. the number of RNA sequences folding into a particular secondary structure or the number of DNA sequences coding for the same protein structure) is astronomically large in all functional molecules investigated: an exhaustive experimental or computational study of all RNA folds or all protein structures becomes impossible even for moderately long sequences. Here, we analytically derive the distribution of genotype network sizes for a hierarchy of models which successively incorporate features of increasingly realistic sequence-to-structure genotype-phenotype maps. The main feature of these models relies on the characterization of each phenotype through a prototypical sequence whose sites admit a variable fraction of letters of the alphabet. Our models interpolate between two limit distributions: a power-law distribution, when the ordering of sites in the prototypical sequence is strongly constrained, and a lognormal distribution, as suggested for RNA, when different orderings of the same set of sites yield different phenotypes. Our main result is the qualitative and quantitative identification of those features of sequence-to-structure maps that lead to different distributions of genotype network sizes. © 2017 The Author(s).

Sawja: Static Analysis Workshop for Java

NASA Astrophysics Data System (ADS)

Hubert, Laurent; Barré, Nicolas; Besson, Frédéric; Demange, Delphine; Jensen, Thomas; Monfort, Vincent; Pichardie, David; Turpin, Tiphaine

Static analysis is a powerful technique for automatic verification of programs but raises major engineering challenges when developing a full-fledged analyzer for a realistic language such as Java. Efficiency and precision of such a tool rely partly on low level components which only depend on the syntactic structure of the language and therefore should not be redesigned for each implementation of a new static analysis. This paper describes the Sawja library: a static analysis workshop fully compliant with Java 6 which provides OCaml modules for efficiently manipulating Java bytecode programs. We present the main features of the library, including i) efficient functional data-structures for representing a program with implicit sharing and lazy parsing, ii) an intermediate stack-less representation, and iii) fast computation and manipulation of complete programs. We provide experimental evaluations of the different features with respect to time, memory and precision.

The morphing of geographical features by Fourier transformation

PubMed Central

Liu, Pengcheng; Yu, Wenhao; Cheng, Xiaoqiang

2018-01-01

This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features’ continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable. PMID:29351344

Radiation effects in advanced microelectronics technologies

NASA Astrophysics Data System (ADS)

Johnston, A. H.

1998-06-01

The pace of device scaling has increased rapidly in recent years. Experimental CMOS devices have been produced with feature sizes below 0.1 /spl mu/m, demonstrating that devices with feature sizes between 0.1 and 0.25 /spl mu/m will likely be available in mainstream technologies after the year 2000. This paper discusses how the anticipated changes in device dimensions and design are likely to affect their radiation response in space environments. Traditional problems, such as total dose effects, SEU and latchup are discussed, along with new phenomena. The latter include hard errors from heavy ions (microdose and gate-rupture errors), and complex failure modes related to advanced circuit architecture. The main focus of the paper is on commercial devices, which are displacing hardened device technologies in many space applications. However, the impact of device scaling on hardened devices is also discussed.

Recognition of Simple 3D Geometrical Objects under Partial Occlusion

NASA Astrophysics Data System (ADS)

Barchunova, Alexandra; Sommer, Gerald

In this paper we present a novel procedure for contour-based recognition of partially occluded three-dimensional objects. In our approach we use images of real and rendered objects whose contours have been deformed by a restricted change of the viewpoint. The preparatory part consists of contour extraction, preprocessing, local structure analysis and feature extraction. The main part deals with an extended construction and functionality of the classifier ensemble Adaptive Occlusion Classifier (AOC). It relies on a hierarchical fragmenting algorithm to perform a local structure analysis which is essential when dealing with occlusions. In the experimental part of this paper we present classification results for five classes of simple geometrical figures: prism, cylinder, half cylinder, a cube, and a bridge. We compare classification results for three classical feature extractors: Fourier descriptors, pseudo Zernike and Zernike moments.

Usage monitoring of electrical devices in a smart home.

PubMed

Rahimi, Saba; Chan, Adrian D C; Goubran, Rafik A

2011-01-01

Profiling the usage of electrical devices within a smart home can be used as a method for determining an occupant's activities of daily living. A nonintrusive load monitoring system monitors the electrical consumption at a single electrical source (e.g., main electric utility service entry) and the operating schedules of individual devices are determined by disaggregating the composite electrical consumption waveforms. An electrical device's load signature plays a key role in nonintrusive load monitoring systems. A load signature is the unique electrical behaviour of an individual device when it is in operation. This paper proposes a feature-based model, using the real power and reactive power as features for describing the load signatures of individual devices. Experimental results for single device recognition for 7 devices show that the proposed approach can achieve 100% classification accuracy with discriminant analysis using Mahalanobis distances.

Check the Lambert-Beer-Bouguer law: a simple trick to boost the confidence of students toward both exponential laws and the discrete approach to experimental physics

NASA Astrophysics Data System (ADS)

Di Capua, R.; Offi, F.; Fontana, F.

2014-07-01

Exponential decay is a prototypical functional behaviour for many physical phenomena, and therefore it deserves great attention in physics courses at an academic level. The absorption of the electromagnetic radiation that propagates in a dissipative medium provides an example of the decay of light intensity, as stated by the law of Lambert-Beer-Bourguer. We devised a very simple experiment to check this law. The experimental setup, its realization, and the data analysis of the experiment are definitely simple. Our main goal was to create an experiment that is accessible to all students, including those in their first year of academic courses and those with poorly equipped laboratories. As illustrated in this paper, our proposal allowed us to develop a deep discussion about some general mathematical and numerical features of exponential decay. Furthermore, the special setup of the absorbing medium (sliced in finite thickness slabs) and the experimental outcomes allow students to understand the transition from the discrete to the continuum approach in experimental physics.

Centrifugal compressor surge detecting method based on wavelet analysis of unsteady pressure fluctuations in typical stages

NASA Astrophysics Data System (ADS)

Izmaylov, R.; Lebedev, A.

2015-08-01

Centrifugal compressors are complex energy equipment. Automotive control and protection system should meet the requirements: of operation reliability and durability. In turbocompressors there are at least two dangerous areas: surge and rotating stall. Antisurge protecting systems usually use parametric or feature methods. As a rule industrial system are parametric. The main disadvantages of anti-surge parametric systems are difficulties in mass flow measurements in natural gas pipeline compressor. The principal idea of feature method is based on the experimental fact: as a rule just before the onset of surge rotating or precursor stall established in compressor. In this case the problem consists in detecting of unsteady pressure or velocity fluctuations characteristic signals. Wavelet analysis is the best method for detecting onset of rotating stall in spite of high level of spurious signals (rotating wakes, turbulence, etc.). This method is compatible with state of the art DSP systems of industrial control. Examples of wavelet analysis application for detecting onset of rotating stall in typical stages centrifugal compressor are presented. Experimental investigations include unsteady pressure measurement and sophisticated data acquisition system. Wavelet transforms used biorthogonal wavelets in Mathlab systems.

Investigation of features in radon soil dynamics and search for influencing factors

NASA Astrophysics Data System (ADS)

Yakovlev, Grigorii; Cherepnev, Maxim; Nagorskiy, Petr; Yakovleva, Valentina

2018-03-01

The features in radon soil dynamics at two depths were investigated and the main influencing factors were revealed. The monitoring of radon volumetric activity in soil air was performed at experimental site of Tomsk Observatory of Radioactivity and Ionizing Radiation with using radon radiometers and scintillation detectors of alpha-radiation with 10 min sampling frequency. The detectors were installed into boreholes of 0.5 and 1 m depths. The analysis of the soil radon monitoring data has allowed revealing some dependencies at daily and annual scales and main influencing factors. In periods with clearly defined daily radon variations in the soil were revealed the next: 1) amplitude of the daily variations of the soil radon volumetric activity damps with the depth, that is related with the influence of convective fluxes in the soil; 2) temporal shift between times of occurrence of radon volumetric activity maximum (or minimum) values at 0.5 m and 1 m depths can reach 3 hours. In seasonal dynamics of the soil radon the following dependences were found: 1) maximal values are observed in winter, but minimal - in summer; 2) spring periods of snow melting are accompanied by anomaly increasing of radon volumetric activity in the soil up to about 3 times. The main influencing factors are atmospheric precipitations, temperature gradient in the soil and the state of upper soil layer.

Visual Odometry Based on Structural Matching of Local Invariant Features Using Stereo Camera Sensor

PubMed Central

Núñez, Pedro; Vázquez-Martín, Ricardo; Bandera, Antonio

2011-01-01

This paper describes a novel sensor system to estimate the motion of a stereo camera. Local invariant image features are matched between pairs of frames and linked into image trajectories at video rate, providing the so-called visual odometry, i.e., motion estimates from visual input alone. Our proposal conducts two matching sessions: the first one between sets of features associated to the images of the stereo pairs and the second one between sets of features associated to consecutive frames. With respect to previously proposed approaches, the main novelty of this proposal is that both matching algorithms are conducted by means of a fast matching algorithm which combines absolute and relative feature constraints. Finding the largest-valued set of mutually consistent matches is equivalent to finding the maximum-weighted clique on a graph. The stereo matching allows to represent the scene view as a graph which emerge from the features of the accepted clique. On the other hand, the frame-to-frame matching defines a graph whose vertices are features in 3D space. The efficiency of the approach is increased by minimizing the geometric and algebraic errors to estimate the final displacement of the stereo camera between consecutive acquired frames. The proposed approach has been tested for mobile robotics navigation purposes in real environments and using different features. Experimental results demonstrate the performance of the proposal, which could be applied in both industrial and service robot fields. PMID:22164016

Experimental Methodology in English Teaching and Learning: Method Features, Validity Issues, and Embedded Experimental Design

ERIC Educational Resources Information Center

Lee, Jang Ho

2012-01-01

Experimental methods have played a significant role in the growth of English teaching and learning studies. The paper presented here outlines basic features of experimental design, including the manipulation of independent variables, the role and practicality of randomised controlled trials (RCTs) in educational research, and alternative methods…

IUPAC-NIST Solubility Data Series. 100. Rare Earth Metal Fluorides in Water and Aqueous Systems. Part 2. Light Lanthanides (Ce-Eu)

NASA Astrophysics Data System (ADS)

Mioduski, Tomasz; Gumiński, Cezary; Zeng, Dewen

2015-03-01

This is the second part of the volume devoted to the evaluation of experimental solubility data for rare earth metal (REM) fluorides in water as well as in aqueous ternary and multicomponent systems. Fluorides of Ce, Pr, Nd, Pm, Sm, and Eu (so-called light lanthanides), as the main solutes, are covered in the present part, which has thorough coverage of the experimental literature through the end of 2012. The experimentally unknown solubility value for PmF3 in water was predicted by an interpolation of the solubility values for NdF3 and SmF3 at 298 K. General features of the systems, such as the nature of the equilibrium solid phases, solubility as a function of temperature, influence of ionic strength, pH, mixed solvent medium on the solubility, quality of the solubility results, and solubility as a function of REM atomic number, have already been presented in Part 1 of the volume.

Absorption and Emission of the Apigenin and Luteolin Flavonoids: A TDDFT Investigation

NASA Astrophysics Data System (ADS)

Amat, Anna; Clementi, Catia; de Angelis, Filippo; Sgamellotti, Antonio; Fantacci, Simona

2009-09-01

The absorption and emission properties of the two components of the yellow color extracted from weld (Reseda luteola L.), apigenin and luteolin, have been extensively investigated by means of DFT and TDDFT calculations. Our calculations reproduce the absorption spectra of both flavonoids in good agreement with the experimental data and allow us to assign the transitions giving rise to the main spectral features. For apigenin, we have also computed the electronic spectrum of the monodeprotonated species, providing a rationale for the red-shift of the experimental spectrum with increasing pH. The fluorescence emission of both apigenin and luteolin has then been investigated. Excited-state TDDFT geometry optimizations have highlighted an excited-state intramolecular proton transfer (ESIPT) from the 5-hydroxyl to the 4-carbonyl oxygen of the substituted benzopyrone moiety. By computing the potential energy curves at the ground and excited states as a function of an approximate proton transfer coordinate for apigenin, we have been able to trace an ESIPT pathway and thus explain the double emission observed experimentally.

Quantitative Comparisons of a Coarse-Grid LES with Experimental Data for Backward-Facing Step Flow

NASA Astrophysics Data System (ADS)

McDonough, J. M.

1999-11-01

A novel approach to LES employing an additive decomposition of both solutions and governing equations (similar to ``multi-level'' approaches of Dubois et al.,Dynamic Multilevel Methods and the Simulation of Turbulence, Cambridge University Press, 1999) is presented; its main structural features are lack of filtering of governing equations (instead, solutions are filtered to remove aliasing due to under resolution) and direct modeling of subgrid-scale primitive variables (rather than modeling their correlations) in the manner proposed by Hylin and McDonough (Int. J. Fluid Mech. Res. 26, 228-256, 1999). A 2-D implementation of this formalism is applied to the backward-facing step flow studied experimentally by Driver and Seegmiller (AIAA J. 23, 163-171, 1985) and Driver et al. (AIAA J. 25, 914-919, 1987), and run on grids sufficiently coarse to permit easy extension to 3-D, industrially-realistic problems. Comparisons of computed and experimental mean quantities (velocity profiles, turbulence kinetic energy, reattachment lengths, etc.) and effects of grid refinement will be presented.

Application of texture analysis method for mammogram density classification

NASA Astrophysics Data System (ADS)

Nithya, R.; Santhi, B.

2017-07-01

Mammographic density is considered a major risk factor for developing breast cancer. This paper proposes an automated approach to classify breast tissue types in digital mammogram. The main objective of the proposed Computer-Aided Diagnosis (CAD) system is to investigate various feature extraction methods and classifiers to improve the diagnostic accuracy in mammogram density classification. Texture analysis methods are used to extract the features from the mammogram. Texture features are extracted by using histogram, Gray Level Co-Occurrence Matrix (GLCM), Gray Level Run Length Matrix (GLRLM), Gray Level Difference Matrix (GLDM), Local Binary Pattern (LBP), Entropy, Discrete Wavelet Transform (DWT), Wavelet Packet Transform (WPT), Gabor transform and trace transform. These extracted features are selected using Analysis of Variance (ANOVA). The features selected by ANOVA are fed into the classifiers to characterize the mammogram into two-class (fatty/dense) and three-class (fatty/glandular/dense) breast density classification. This work has been carried out by using the mini-Mammographic Image Analysis Society (MIAS) database. Five classifiers are employed namely, Artificial Neural Network (ANN), Linear Discriminant Analysis (LDA), Naive Bayes (NB), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). Experimental results show that ANN provides better performance than LDA, NB, KNN and SVM classifiers. The proposed methodology has achieved 97.5% accuracy for three-class and 99.37% for two-class density classification.

Latent fingerprint matching.

PubMed

Jain, Anil K; Feng, Jianjiang

2011-01-01

Latent fingerprint identification is of critical importance to law enforcement agencies in identifying suspects: Latent fingerprints are inadvertent impressions left by fingers on surfaces of objects. While tremendous progress has been made in plain and rolled fingerprint matching, latent fingerprint matching continues to be a difficult problem. Poor quality of ridge impressions, small finger area, and large nonlinear distortion are the main difficulties in latent fingerprint matching compared to plain or rolled fingerprint matching. We propose a system for matching latent fingerprints found at crime scenes to rolled fingerprints enrolled in law enforcement databases. In addition to minutiae, we also use extended features, including singularity, ridge quality map, ridge flow map, ridge wavelength map, and skeleton. We tested our system by matching 258 latents in the NIST SD27 database against a background database of 29,257 rolled fingerprints obtained by combining the NIST SD4, SD14, and SD27 databases. The minutiae-based baseline rank-1 identification rate of 34.9 percent was improved to 74 percent when extended features were used. In order to evaluate the relative importance of each extended feature, these features were incrementally used in the order of their cost in marking by latent experts. The experimental results indicate that singularity, ridge quality map, and ridge flow map are the most effective features in improving the matching accuracy.

A concept of highly maneuverable experimental space (HIMES) vehicle

NASA Astrophysics Data System (ADS)

Nagatomo, M.; Naruo, Y.; Inatani, Y.

1985-10-01

The development of a highly maneuverable experimental space (HIMES) vehicle is proposed. This reusable sounding rocket is to be propelled by a liquid hydrogen/LOX engine, and have a maximum payload mass of 500 kg at an altitude of 300 km. The main subsystems of HIMES, the fuselage and wing structure, propulsion, and navigation, guidance, and control system, are described and a diagram is provided. The operational features of HIMES are defined by three mission models. In the first model the vehicle is used as a stable platform of low velocity relative to the environment; model two represents the suborbital flight of sounding rockets, and model three is used for orbital reentry experiments and the testing of a new system of winged space vehicles. Typical mission profiles for the three models are presented. A cost estimation of the HIMES vehicle is given.

Time-domain reflectance diffuse optical tomography with Mellin-Laplace transform for experimental detection and depth localization of a single absorbing inclusion

PubMed Central

Puszka, Agathe; Hervé, Lionel; Planat-Chrétien, Anne; Koenig, Anne; Derouard, Jacques; Dinten, Jean-Marc

2013-01-01

We show how to apply the Mellin-Laplace transform to process time-resolved reflectance measurements for diffuse optical tomography. We illustrate this method on simulated signals incorporating the main sources of experimental noise and suggest how to fine-tune the method in order to detect the deepest absorbing inclusions and optimize their localization in depth, depending on the dynamic range of the measurement. To finish, we apply this method to measurements acquired with a setup including a femtosecond laser, photomultipliers and a time-correlated single photon counting board. Simulations and experiments are illustrated for a probe featuring the interfiber distance of 1.5 cm and show the potential of time-resolved techniques for imaging absorption contrast in depth with this geometry. PMID:23577292

Experimental infection of bovine mammary gland with prototheca zopfii genotype 1.

PubMed

Ito, Takaaki; Kano, Rui; Sobukawa, Hideto; Ogawa, Jin; Honda, Yayoi; Hosoi, Yoshihiro; Shibuya, Hisashi; Sato, Tsuneo; Hasegawa, Atsuhiko; Kamata, Hiroshi

2011-01-01

Prototheca zopfii is divided into three genotypes, one of which, P. zopfii genotype 2, appears to be the main causative agent of bovine protothecal mastitis. However, the difference in pathogenicity between genotypes 1 and 2 has not been well investigated. In the present study, we experimentally infected normal bovine mammary gland with P. zopfii genotype 1 to investigate its pathogenicity. The mammary gland infected with P. zopfii genotype 1 showed no clinical signs. However, the histopathologic features of the infected mammary gland consisted of interstitial infiltrates of macrophages, plasma cells, lymphocytes, and fibroblasts with neutrophils in acinar lumens. Algae were present in macrophages and free in the alveolar lumens and the interstitium. Histopathology of the resultant tissue samples revealed that genotype 1 also induced a granulomatous lesion in the cow teat, similar to the mastitis lesion due to genotype 2.

Wireless sensor network for wide-area high-mobility applications

NASA Astrophysics Data System (ADS)

del Castillo, Ignacio; Esper-Chaín, Roberto; Tobajas, Félix; de Armas, Valentín.

2013-05-01

In recent years, IEEE 802.15.4-based Wireless Sensor Networks (WSN) have experienced significant growth, mainly motivated by the standard features, such as small size oriented devices, low power consumption nodes, wireless communication links, and sensing and data processing capabilities. In this paper, the development, implementation and deployment of a novel fully compatible IEEE 802.15.4-based WSN architecture for applications operating over extended geographic regions with high node mobility support, is described. In addition, a practical system implementation of the proposed WSN architecture is presented and described for experimental validation and characterization purposes.

A hybrid metaheuristic for closest string problem.

PubMed

Mousavi, Sayyed Rasoul

2011-01-01

The Closest String Problem (CSP) is an optimisation problem, which is to obtain a string with the minimum distance from a number of given strings. In this paper, a new metaheuristic algorithm is investigated for the problem, whose main feature is relatively high speed in obtaining good solutions, which is essential when the input size is large. The proposed algorithm is compared with four recent algorithms suggested for the problem, outperforming them in more than 98% of the cases. It is also remarkably faster than all of them, running within 1 s in most of the experimental cases.

The 13C nuclear magnetic resonance in graphite intercalation compounds

NASA Technical Reports Server (NTRS)

Tsang, T.; Resing, H. A.

1985-01-01

The (13)C NMR chemical shifts of graphite intercalation compounds were calculated. For acceptor types, the shifts come mainly from the paramagnetic (Ramsey) intra-atomic terms. They are related to the gross features of the two-dimensional band structures. The calculated anisotropy is about -140 ppm and is independent of the finer details such as charge transfer. For donor types, the carbon 2p pi orbitals are spin-polarized because of mixing with metal conduction electrons, thus there is an additional dipolar contribution which may be correlated with the electronic specific heat. The general agreement with experimental data is satisfactory.

C-13 nuclear magnetic resonance in graphite intercalation compounds

NASA Technical Reports Server (NTRS)

Tsang, T.; Resing, H. A.

1985-01-01

The C-13 NMR chemical shifts of graphite intercalation compounds have been calculated. For acceptor types, the shifts come mainly from the paramagnetic (Ramsey) intra-atomic terms. They are related to the gross features of the two-dimensional band structures. The calculated anisotropy is about - 140 ppm and is independent of the finer details such as charge transfer. For donor types, the carbon 2p pi orbitals are spin-polarized because of mixing with metal-conduction electrons, thus there is an additional dipolar contribution which may be correlated with the electronic specific heat. The general agreement with experimental data is satisfactory.

Droplet Epitaxy Image Contrast in Mirror Electron Microscopy

NASA Astrophysics Data System (ADS)

Kennedy, S. M.; Zheng, C. X.; Jesson, D. E.

2017-01-01

Image simulation methods are applied to interpret mirror electron microscopy (MEM) images obtained from a movie of GaAs droplet epitaxy. Cylindrical symmetry of structures grown by droplet epitaxy is assumed in the simulations which reproduce the main features of the experimental MEM image contrast, demonstrating that droplet epitaxy can be studied in real-time. It is therefore confirmed that an inner ring forms at the droplet contact line and an outer ring (or skirt) occurs outside the droplet periphery. We believe that MEM combined with image simulations will be increasingly used to study the formation and growth of quantum structures.

Atorvastatin effect evaluation based on feature combination of three-dimension ultrasound images

NASA Astrophysics Data System (ADS)

Luo, Yongkang; Ding, Mingyue

2016-03-01

In the past decades, stroke has become the worldwide common cause of death and disability. It is well known that ischemic stroke is mainly caused by carotid atherosclerosis. As an inexpensive, convenient and fast means of detection, ultrasound technology is applied widely in the prevention and treatment of carotid atherosclerosis. Recently, many studies have focused on how to quantitatively evaluate local arterial effects of medicine treatment for carotid diseases. So the evaluation method based on feature combination was proposed to detect potential changes in the carotid arteries after atorvastatin treatment. And the support vector machine (SVM) and 10-fold cross-validation protocol were utilized on a database of 5533 carotid ultrasound images of 38 patients (17 atorvastatin groups and 21 placebo groups) at baseline and after 3 months of the treatment. With combination optimization of many features (including morphological and texture features), the evaluation results of single feature and different combined features were compared. The experimental results showed that the performance of single feature is poor and the best feature combination have good recognition ability, with the accuracy 92.81%, sensitivity 80.95%, specificity 95.52%, positive predictive value 80.47%, negative predictive value 95.65%, Matthew's correlation coefficient 76.27%, and Youden's index 76.48%. And the receiver operating characteristic (ROC) curve was also performed well with 0.9663 of the area under the ROC curve (AUC), which is better than all the features with 0.9423 of the AUC. Thus, it is proved that this novel method can reliably and accurately evaluate the effect of atorvastatin treatment.

Long-term information and distributed neural activation are relevant for the "internal features advantage" in face processing: electrophysiological and source reconstruction evidence.

PubMed

Olivares, Ela I; Saavedra, Cristina; Trujillo-Barreto, Nelson J; Iglesias, Jaime

2013-01-01

In face processing tasks, prior presentation of internal facial features, when compared with external ones, facilitates the recognition of subsequently displayed familiar faces. In a previous ERP study (Olivares & Iglesias, 2010) we found a visibly larger N400-like effect when identity mismatch familiar faces were preceded by internal features, as compared to prior presentation of external ones. In the present study we contrasted the processing of familiar and unfamiliar faces in the face-feature matching task to assess whether the so-called "internal features advantage" relies mainly on the use of stored face-identity-related information or if it might operate independently from stimulus familiarity. Our participants (N = 24) achieved better performance with internal features as primes and, significantly, with familiar faces. Importantly, ERPs elicited by identity mismatch complete faces displayed a negativity around 300-600 msec which was clearly enhanced for familiar faces primed by internal features when compared with the other experimental conditions. Source reconstruction showed incremented activity elicited by familiar stimuli in both posterior (ventral occipitotemporal) and more anterior (parahippocampal (ParaHIP) and orbitofrontal) brain regions. The activity elicited by unfamiliar stimuli was, in general, located in more posterior regions. Our findings suggest that the activation of multiple neural codes is required for optimal individuation in face-feature matching and that a cortical network related to long-term information for face-identity processing seems to support the internal feature effect. Copyright © 2013 Elsevier Ltd. All rights reserved.

A spectral-structural bag-of-features scene classifier for very high spatial resolution remote sensing imagery

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.

Compressed learning and its applications to subcellular localization.

PubMed

Zheng, Zhong-Long; Guo, Li; Jia, Jiong; Xie, Chen-Mao; Zeng, Wen-Cai; Yang, Jie

2011-09-01

One of the main challenges faced by biological applications is to predict protein subcellular localization in automatic fashion accurately. To achieve this in these applications, a wide variety of machine learning methods have been proposed in recent years. Most of them focus on finding the optimal classification scheme and less of them take the simplifying the complexity of biological systems into account. Traditionally, such bio-data are analyzed by first performing a feature selection before classification. Motivated by CS (Compressed Sensing) theory, we propose the methodology which performs compressed learning with a sparseness criterion such that feature selection and dimension reduction are merged into one analysis. The proposed methodology decreases the complexity of biological system, while increases protein subcellular localization accuracy. Experimental results are quite encouraging, indicating that the aforementioned sparse methods are quite promising in dealing with complicated biological problems, such as predicting the subcellular localization of Gram-negative bacterial proteins.

Self-Oscillating Josephson Quantum Heat Engine

NASA Astrophysics Data System (ADS)

Marchegiani, G.; Virtanen, P.; Giazotto, F.; Campisi, M.

2016-11-01

The design of a mesoscopic self-oscillating heat engine that works thanks to purely quantum effects is presented. The proposed scheme is amenable to experimental implementation with current state-of-the-art nanotechnology and materials. One of the main features of the structure is its versatility: The engine can deliver work to a generic load without galvanic contact. This versatility makes it a promising building block for low-temperature on-chip energy-management applications. The heat engine consists of a circuit featuring a thermoelectric element based on a ferromagnetic insulator-superconductor tunnel junction and a Josephson weak link that realizes a purely quantum dc-ac converter. This makeup enables the contactless transfer of work to the load (a generic RL circuit). The performance of the heat engine is investigated as a function of the thermal gradient applied to the thermoelectric junction. Power up to 1 pW can be delivered to a load RL=10 Ω .

Static and dynamic friction in sliding colloidal monolayers

PubMed Central

Vanossi, Andrea; Manini, Nicola; Tosatti, Erio

2012-01-01

In a pioneer experiment, Bohlein et al. realized the controlled sliding of two-dimensional colloidal crystals over laser-generated periodic or quasi-periodic potentials. Here we present realistic simulations and arguments that besides reproducing the main experimentally observed features give a first theoretical demonstration of the potential impact of colloid sliding in nanotribology. The free motion of solitons and antisolitons in the sliding of hard incommensurate crystals is contrasted with the soliton–antisoliton pair nucleation at the large static friction threshold Fs when the two lattices are commensurate and pinned. The frictional work directly extracted from particles’ velocities can be analyzed as a function of classic tribological parameters, including speed, spacing, and amplitude of the periodic potential (representing, respectively, the mismatch of the sliding interface and the corrugation, or “load”). These and other features suggestive of further experiments and insights promote colloid sliding to a unique friction study instrument. PMID:23019582

Brain modularity controls the critical behavior of spontaneous activity.

PubMed

Russo, R; Herrmann, H J; de Arcangelis, L

2014-03-13

The human brain exhibits a complex structure made of scale-free highly connected modules loosely interconnected by weaker links to form a small-world network. These features appear in healthy patients whereas neurological diseases often modify this structure. An important open question concerns the role of brain modularity in sustaining the critical behaviour of spontaneous activity. Here we analyse the neuronal activity of a model, successful in reproducing on non-modular networks the scaling behaviour observed in experimental data, on a modular network implementing the main statistical features measured in human brain. We show that on a modular network, regardless the strength of the synaptic connections or the modular size and number, activity is never fully scale-free. Neuronal avalanches can invade different modules which results in an activity depression, hindering further avalanche propagation. Critical behaviour is solely recovered if inter-module connections are added, modifying the modular into a more random structure.

Comparative genomics of Paracoccus sp. SM22M-07 isolated from coral mucus: insights into bacteria-host interactions.

PubMed

Carlos, Camila; Pereira, Letícia Bianca; Ottoboni, Laura Maria Mariscal

2017-06-01

One of the main goals of coral microbiology is to understand the ways in which coral-bacteria associations are established and maintained. This work describes the sequencing of the genome of Paracoccus sp. SM22M-07 isolated from the mucus of the endemic Brazilian coral species Mussismilia hispida. Comparative analysis was used to identify unique genomic features of SM22M-07 that might be involved in its adaptation to the marine ecosystem and the nutrient-rich environment provided by coral mucus, as well as in the establishment and strengthening of the interaction with the host. These features included genes related to the type IV protein secretion system, erythritol catabolism, and succinoglycan biosynthesis. We experimentally confirmed the production of succinoglycan by Paracoccus sp. SM22M-07 and we hypothesize that it may be involved in the association of the bacterium with coral surfaces.

Quasiparticle interference of Fermi arc states in the type-II Weyl semimetal candidate WT e2

NASA Astrophysics Data System (ADS)

Yuan, Yuan; Yang, Xing; Peng, Lang; Wang, Zhi-Jun; Li, Jian; Yi, Chang-Jiang; Xian, Jing-Jing; Shi, You-Guo; Fu, Ying-Shuang

2018-04-01

Weyl semimetals possess linear dispersions through pairs of Weyl nodes in three-dimensional momentum spaces, whose hallmark arclike surface states are connected to Weyl nodes with different chirality. WT e2 was recently predicted to be a new type of Weyl semimetal. Here, we study the quasiparticle interference (QPI) of its Fermi arc surface states by combined spectroscopic-imaging scanning tunneling spectroscopy and density functional theory calculations. We observed the electron scattering on two types of WT e2 surfaces unambiguously. Its scattering signal can be ascribed mainly to trivial surface states. We also address the QPI feature of nontrivial surface states from theoretical calculations. The experimental QPI patterns show some features that are likely related to the nontrivial Fermi arc states, whose existence is, however, not conclusive. Our study provides an indispensable clue for studying the Weyl semimetal phase in WT e2 .

Flow Structures within a Helicopter Rotor Hub Wake

NASA Astrophysics Data System (ADS)

Elbing, Brian; Reich, David; Schmitz, Sven

2015-11-01

A scaled model of a notional helicopter rotor hub was tested in the 48'' Garfield Thomas Water Tunnel at the Applied Research Laboratory Penn State. The measurement suite included total hub drag and wake velocity measurements (LDV, PIV, stereo-PIV) at three downstream locations. The main objective was to understand the spatiotemporal evolution of the unsteady wake between the rotor hub and the nominal location of the empennage (tail). Initial analysis of the data revealed prominent two- and four-per-revolution fluid structures linked to geometric hub features persisting into the wake far-field. In addition, a six-per-revolution fluid structure was observed in the far-field, which is unexpected due to the lack of any hub feature with the corresponding symmetry. This suggests a nonlinear interaction is occurring within the wake to generate these structures. This presentation will provide an overview of the experimental data and analysis with particular emphasis on these six-per-revolution structures.

Multifeature-based high-resolution palmprint recognition.

PubMed

Dai, Jifeng; Zhou, Jie

2011-05-01

Palmprint is a promising biometric feature for use in access control and forensic applications. Previous research on palmprint recognition mainly concentrates on low-resolution (about 100 ppi) palmprints. But for high-security applications (e.g., forensic usage), high-resolution palmprints (500 ppi or higher) are required from which more useful information can be extracted. In this paper, we propose a novel recognition algorithm for high-resolution palmprint. The main contributions of the proposed algorithm include the following: 1) use of multiple features, namely, minutiae, density, orientation, and principal lines, for palmprint recognition to significantly improve the matching performance of the conventional algorithm. 2) Design of a quality-based and adaptive orientation field estimation algorithm which performs better than the existing algorithm in case of regions with a large number of creases. 3) Use of a novel fusion scheme for an identification application which performs better than conventional fusion methods, e.g., weighted sum rule, SVMs, or Neyman-Pearson rule. Besides, we analyze the discriminative power of different feature combinations and find that density is very useful for palmprint recognition. Experimental results on the database containing 14,576 full palmprints show that the proposed algorithm has achieved a good performance. In the case of verification, the recognition system's False Rejection Rate (FRR) is 16 percent, which is 17 percent lower than the best existing algorithm at a False Acceptance Rate (FAR) of 10(-5), while in the identification experiment, the rank-1 live-scan partial palmprint recognition rate is improved from 82.0 to 91.7 percent.

Increasing dimension of structures by 4D printing shape memory polymers via fused deposition modeling

NASA Astrophysics Data System (ADS)

Hu, G. F.; Damanpack, A. R.; Bodaghi, M.; Liao, W. H.

2017-12-01

The main objective of this paper is to introduce a 4D printing method to program shape memory polymers (SMPs) during fabrication process. Fused deposition modeling (FDM) as a filament-based printing method is employed to program SMPs during depositing the material. This method is implemented to fabricate complicated polymeric structures by self-bending features without need of any post-programming. Experiments are conducted to demonstrate feasibility of one-dimensional (1D)-to 2D and 2D-to-3D self-bending. It is shown that 3D printed plate structures can transform into masonry-inspired 3D curved shell structures by simply heating. Good reliability of SMP programming during printing process is also demonstrated. A 3D macroscopic constitutive model is established to simulate thermo-mechanical features of the printed SMPs. Governing equations are also derived to simulate programming mechanism during printing process and shape change of self-bending structures. In this respect, a finite element formulation is developed considering von-Kármán geometric nonlinearity and solved by implementing iterative Newton-Raphson scheme. The accuracy of the computational approach is checked with experimental results. It is demonstrated that the theoretical model is able to replicate the main characteristics observed in the experiments. This research is likely to advance the state of the art FDM 4D printing, and provide pertinent results and computational tool that are instrumental in design of smart materials and structures with self-bending features.

Multi-label spacecraft electrical signal classification method based on DBN and random forest

PubMed Central

Li, Ke; Yu, Nan; Li, Pengfei; Song, Shimin; Wu, Yalei; Li, Yang; Liu, Meng

2017-01-01

In spacecraft electrical signal characteristic data, there exists a large amount of data with high-dimensional features, a high computational complexity degree, and a low rate of identification problems, which causes great difficulty in fault diagnosis of spacecraft electronic load systems. This paper proposes a feature extraction method that is based on deep belief networks (DBN) and a classification method that is based on the random forest (RF) algorithm; The proposed algorithm mainly employs a multi-layer neural network to reduce the dimension of the original data, and then, classification is applied. Firstly, we use the method of wavelet denoising, which was used to pre-process the data. Secondly, the deep belief network is used to reduce the feature dimension and improve the rate of classification for the electrical characteristics data. Finally, we used the random forest algorithm to classify the data and comparing it with other algorithms. The experimental results show that compared with other algorithms, the proposed method shows excellent performance in terms of accuracy, computational efficiency, and stability in addressing spacecraft electrical signal data. PMID:28486479

Multi-label spacecraft electrical signal classification method based on DBN and random forest.

PubMed

Li, Ke; Yu, Nan; Li, Pengfei; Song, Shimin; Wu, Yalei; Li, Yang; Liu, Meng

2017-01-01

In spacecraft electrical signal characteristic data, there exists a large amount of data with high-dimensional features, a high computational complexity degree, and a low rate of identification problems, which causes great difficulty in fault diagnosis of spacecraft electronic load systems. This paper proposes a feature extraction method that is based on deep belief networks (DBN) and a classification method that is based on the random forest (RF) algorithm; The proposed algorithm mainly employs a multi-layer neural network to reduce the dimension of the original data, and then, classification is applied. Firstly, we use the method of wavelet denoising, which was used to pre-process the data. Secondly, the deep belief network is used to reduce the feature dimension and improve the rate of classification for the electrical characteristics data. Finally, we used the random forest algorithm to classify the data and comparing it with other algorithms. The experimental results show that compared with other algorithms, the proposed method shows excellent performance in terms of accuracy, computational efficiency, and stability in addressing spacecraft electrical signal data.

Localizing text in scene images by boundary clustering, stroke segmentation, and string fragment classification.

PubMed

Yi, Chucai; Tian, Yingli

2012-09-01

In this paper, we propose a novel framework to extract text regions from scene images with complex backgrounds and multiple text appearances. This framework consists of three main steps: boundary clustering (BC), stroke segmentation, and string fragment classification. In BC, we propose a new bigram-color-uniformity-based method to model both text and attachment surface, and cluster edge pixels based on color pairs and spatial positions into boundary layers. Then, stroke segmentation is performed at each boundary layer by color assignment to extract character candidates. We propose two algorithms to combine the structural analysis of text stroke with color assignment and filter out background interferences. Further, we design a robust string fragment classification based on Gabor-based text features. The features are obtained from feature maps of gradient, stroke distribution, and stroke width. The proposed framework of text localization is evaluated on scene images, born-digital images, broadcast video images, and images of handheld objects captured by blind persons. Experimental results on respective datasets demonstrate that the framework outperforms state-of-the-art localization algorithms.

Collision-induced evaporation of water clusters and contribution of momentum transfer

NASA Astrophysics Data System (ADS)

Calvo, Florent; Berthias, Francis; Feketeová, Linda; Abdoul-Carime, Hassan; Farizon, Bernadette; Farizon, Michel

2017-05-01

The evaporation of water molecules from high-velocity argon atoms impinging on protonated water clusters has been computationally investigated using molecular dynamics simulations with the reactive OSS2 potential to model water clusters and the ZBL pair potential to represent their interaction with the projectile. Swarms of trajectories and an event-by-event analysis reveal the conditions under which a specific number of molecular evaporation events is found one nanosecond after impact, thereby excluding direct knockout events from the analysis. These simulations provide velocity distributions that exhibit two main features, with a major statistical component arising from a global redistribution of the collision energy into intermolecular degrees of freedom, and another minor but non-ergodic feature at high velocities. The latter feature is produced by direct impacts on the peripheral water molecules and reflects a more complete momentum transfer. These two components are consistent with recent experimental measurements and confirm that electronic processes are not explicitly needed to explain the observed non-ergodic behavior. Contribution to the Topical Issue "Dynamics of Systems at the Nanoscale", edited by Andrey Solov'yov and Andrei Korol.

Mind-body relationships in elite apnea divers during breath holding: a study of autonomic responses to acute hypoxemia

PubMed Central

Laurino, Marco; Menicucci, Danilo; Mastorci, Francesca; Allegrini, Paolo; Piarulli, Andrea; Scilingo, Enzo P.; Bedini, Remo; Pingitore, Alessandro; Passera, Mirko; L'Abbate, Antonio; Gemignani, Angelo

2011-01-01

The mental control of ventilation with all associated phenomena, from relaxation to modulation of emotions, from cardiovascular to metabolic adaptations, constitutes a psychophysiological condition characterizing voluntary breath-holding (BH). BH induces several autonomic responses, involving both autonomic cardiovascular and cutaneous pathways, whose characterization is the main aim of this study. Electrocardiogram and skin conductance (SC) recordings were collected from 14 elite divers during three conditions: free breathing (FB), normoxic phase of BH (NPBH) and hypoxic phase of BH (HPBH). Thus, we compared a set of features describing signal dynamics between the three experimental conditions: from heart rate variability (HRV) features (in time and frequency-domains and by using nonlinear methods) to rate and shape of spontaneous SC responses (SCRs). The main result of the study rises by applying a Factor Analysis to the subset of features significantly changed in the two BH phases. Indeed, the Factor Analysis allowed to uncover the structure of latent factors which modeled the autonomic response: a factor describing the autonomic balance (AB), one the information increase rate (IIR), and a latter the central nervous system driver (CNSD). The BH did not disrupt the FB factorial structure, and only few features moved among factors. Factor Analysis indicates that during BH (1) only the SC described the emotional output, (2) the sympathetic tone on heart did not change, (3) the dynamics of interbeats intervals showed an increase of long-range correlation that anticipates the HPBH, followed by a drop to a random behavior. In conclusion, data show that the autonomic control on heart rate and SC are differentially modulated during BH, which could be related to a more pronounced effect on emotional control induced by the mental training to BH. PMID:22461774

Prevention of pulmonary hypoplasia and pulmonary vascular remodeling by antenatal simvastatin treatment in nitrofen-induced congenital diaphragmatic hernia.

PubMed

Makanga, Martine; Maruyama, Hidekazu; Dewachter, Celine; Da Costa, Agnès Mendes; Hupkens, Emeline; de Medina, Geoffrey; Naeije, Robert; Dewachter, Laurence

2015-04-01

Congenital diaphragmatic hernia (CDH) has a high mortality rate mainly due to lung hypoplasia and persistent pulmonary hypertension of the newborn (PPHN). Simvastatin has been shown to prevent the development of pulmonary hypertension (PH) in experimental models of PH. We, therefore, hypothesized that antenatal simvastatin would attenuate PPHN in nitrofen-induced CDH in rats. The efficacy of antenatal simvastatin was compared with antenatal sildenafil, which has already been shown to improve pathological features of PPHN in nitrofen-induced CDH. On embryonic day (E) 9.5, nitrofen or vehicle was administered to pregnant Sprague-Dawley rats. On E11, nitrofen-treated rats were randomly assigned to antenatal simvastatin (20 mg·kg(-1)·day(-1) orally), antenatal sildenafil (100 mg·kg(-1)·day(-1) orally), or placebo administration from E11 to E21. On E21, fetuses were delivered by cesarean section, killed, and checked for left-sided CDH. Lung tissue was then harvested for further pathobiological evaluation. In nitrofen-induced CDH, simvastatin failed to reduce the incidence of nitrofen-induced CDH in the offspring and to increase the body weight, but improved the lung-to-body weight ratio and lung parenchyma structure. Antenatal simvastatin restored the pulmonary vessel density and external diameter, and reduced the pulmonary arteriolar remodeling compared with nitrofen-induced CDH. This was associated with decreased lung expression of endothelin precursor, endothelin type A and B receptors, endothelial and inducible nitric oxide synthase, together with restored lung activation of apoptotic processes mainly in the epithelium. Antenatal simvastatin presented similar effects as antenatal therapy with sildenafil on nitrofen-induced CDH. Antenatal simvastatin improves pathological features of lung hypoplasia and PPHN in experimental nitrofen-induced CDH. Copyright © 2015 the American Physiological Society.

Prevention of pulmonary hypoplasia and pulmonary vascular remodeling by antenatal simvastatin treatment in nitrofen-induced congenital diaphragmatic hernia

PubMed Central

Makanga, Martine; Maruyama, Hidekazu; Dewachter, Celine; Da Costa, Agnès Mendes; Hupkens, Emeline; de Medina, Geoffrey; Naeije, Robert

2015-01-01

Congenital diaphragmatic hernia (CDH) has a high mortality rate mainly due to lung hypoplasia and persistent pulmonary hypertension of the newborn (PPHN). Simvastatin has been shown to prevent the development of pulmonary hypertension (PH) in experimental models of PH. We, therefore, hypothesized that antenatal simvastatin would attenuate PPHN in nitrofen-induced CDH in rats. The efficacy of antenatal simvastatin was compared with antenatal sildenafil, which has already been shown to improve pathological features of PPHN in nitrofen-induced CDH. On embryonic day (E) 9.5, nitrofen or vehicle was administered to pregnant Sprague-Dawley rats. On E11, nitrofen-treated rats were randomly assigned to antenatal simvastatin (20 mg·kg−1·day−1 orally), antenatal sildenafil (100 mg·kg−1·day−1 orally), or placebo administration from E11 to E21. On E21, fetuses were delivered by cesarean section, killed, and checked for left-sided CDH. Lung tissue was then harvested for further pathobiological evaluation. In nitrofen-induced CDH, simvastatin failed to reduce the incidence of nitrofen-induced CDH in the offspring and to increase the body weight, but improved the lung-to-body weight ratio and lung parenchyma structure. Antenatal simvastatin restored the pulmonary vessel density and external diameter, and reduced the pulmonary arteriolar remodeling compared with nitrofen-induced CDH. This was associated with decreased lung expression of endothelin precursor, endothelin type A and B receptors, endothelial and inducible nitric oxide synthase, together with restored lung activation of apoptotic processes mainly in the epithelium. Antenatal simvastatin presented similar effects as antenatal therapy with sildenafil on nitrofen-induced CDH. Antenatal simvastatin improves pathological features of lung hypoplasia and PPHN in experimental nitrofen-induced CDH. PMID:25617377

The bioimpedance analysis of a parenchyma of a liver in the conditions of its extensive resection in experiment

NASA Astrophysics Data System (ADS)

Agibalov, D. Y.; Panchenkov, D. N.; Chertyuk, V. B.; Leonov, S. D.; Astakhov, D. A.

2017-01-01

The liver failure which is result of disharmony of functionality of a liver to requirements of an organism is the main reason for unsatisfactory results of an extensive resection of a liver. However, uniform effective criterion of definition of degree of a liver failure it isn’t developed now. One of data acquisition methods about a morfo-functional condition of internals is the bioimpedance analysis (BIA) based on impedance assessment (full electric resistance) of a biological tissue. Measurements of an impedance are used in medicine and biology for the characteristic of physical properties of living tissue, studying of the changes bound to a functional state and its structural features. In experimental conditions we carried out an extensive resection of a liver on 27 white laboratory rats of the Vistar line. The comparative characteristic of data of a bioimpedansometriya in intraoperative and after the operational period with the main existing methods of assessment of a functional condition of a liver was carried out. By results of the work performed by us it is possible to claim that the bioimpedance analysis of a liver on the basis of an invasive bioimpedansometriya allows to estimate morphological features and functional activity of a liver before performance of an extensive resection of a liver. The data obtained during scientific work are experimental justification for use of an impedansometriya during complex assessment of functional reserves of a liver. Preliminary data of clinical approbation at a stage of introduction of a technique speak about rather high informational content of a bioimpedansometriya. The subsequent analysis of efficiency of the invasive bioimpedance analysis of a liver requires further accumulation of clinical data. However even at this stage the method showed the prospect for further use in clinical surgical hepathology.

An improved approach for the segmentation of starch granules in microscopic images

PubMed Central

2010-01-01

Background Starches are the main storage polysaccharides in plants and are distributed widely throughout plants including seeds, roots, tubers, leaves, stems and so on. Currently, microscopic observation is one of the most important ways to investigate and analyze the structure of starches. The position, shape, and size of the starch granules are the main measurements for quantitative analysis. In order to obtain these measurements, segmentation of starch granules from the background is very important. However, automatic segmentation of starch granules is still a challenging task because of the limitation of imaging condition and the complex scenarios of overlapping granules. Results We propose a novel method to segment starch granules in microscopic images. In the proposed method, we first separate starch granules from background using automatic thresholding and then roughly segment the image using watershed algorithm. In order to reduce the oversegmentation in watershed algorithm, we use the roundness of each segment, and analyze the gradient vector field to find the critical points so as to identify oversegments. After oversegments are found, we extract the features, such as the position and intensity of the oversegments, and use fuzzy c-means clustering to merge the oversegments to the objects with similar features. Experimental results demonstrate that the proposed method can alleviate oversegmentation of watershed segmentation algorithm successfully. Conclusions We present a new scheme for starch granules segmentation. The proposed scheme aims to alleviate the oversegmentation in watershed algorithm. We use the shape information and critical points of gradient vector flow (GVF) of starch granules to identify oversegments, and use fuzzy c-mean clustering based on prior knowledge to merge these oversegments to the objects. Experimental results on twenty microscopic starch images demonstrate the effectiveness of the proposed scheme. PMID:21047380

A novel content-based medical image retrieval method based on query topic dependent image features (QTDIF)

NASA Astrophysics Data System (ADS)

Xiong, Wei; Qiu, Bo; Tian, Qi; Mueller, Henning; Xu, Changsheng

2005-04-01

Medical image retrieval is still mainly a research domain with a large variety of applications and techniques. With the ImageCLEF 2004 benchmark, an evaluation framework has been created that includes a database, query topics and ground truth data. Eleven systems (with a total of more than 50 runs) compared their performance in various configurations. The results show that there is not any one feature that performs well on all query tasks. Key to successful retrieval is rather the selection of features and feature weights based on a specific set of input features, thus on the query task. In this paper we propose a novel method based on query topic dependent image features (QTDIF) for content-based medical image retrieval. These feature sets are designed to capture both inter-category and intra-category statistical variations to achieve good retrieval performance in terms of recall and precision. We have used Gaussian Mixture Models (GMM) and blob representation to model medical images and construct the proposed novel QTDIF for CBIR. Finally, trained multi-class support vector machines (SVM) are used for image similarity ranking. The proposed methods have been tested over the Casimage database with around 9000 images, for the given 26 image topics, used for imageCLEF 2004. The retrieval performance has been compared with the medGIFT system, which is based on the GNU Image Finding Tool (GIFT). The experimental results show that the proposed QTDIF-based CBIR can provide significantly better performance than systems based general features only.

DrugE-Rank: improving drug–target interaction prediction of new candidate drugs or targets by ensemble learning to rank

PubMed Central

Yuan, Qingjun; Gao, Junning; Wu, Dongliang; Zhang, Shihua; Mamitsuka, Hiroshi; Zhu, Shanfeng

2016-01-01

Motivation: Identifying drug–target interactions is an important task in drug discovery. To reduce heavy time and financial cost in experimental way, many computational approaches have been proposed. Although these approaches have used many different principles, their performance is far from satisfactory, especially in predicting drug–target interactions of new candidate drugs or targets. Methods: Approaches based on machine learning for this problem can be divided into two types: feature-based and similarity-based methods. Learning to rank is the most powerful technique in the feature-based methods. Similarity-based methods are well accepted, due to their idea of connecting the chemical and genomic spaces, represented by drug and target similarities, respectively. We propose a new method, DrugE-Rank, to improve the prediction performance by nicely combining the advantages of the two different types of methods. That is, DrugE-Rank uses LTR, for which multiple well-known similarity-based methods can be used as components of ensemble learning. Results: The performance of DrugE-Rank is thoroughly examined by three main experiments using data from DrugBank: (i) cross-validation on FDA (US Food and Drug Administration) approved drugs before March 2014; (ii) independent test on FDA approved drugs after March 2014; and (iii) independent test on FDA experimental drugs. Experimental results show that DrugE-Rank outperforms competing methods significantly, especially achieving more than 30% improvement in Area under Prediction Recall curve for FDA approved new drugs and FDA experimental drugs. Availability: http://datamining-iip.fudan.edu.cn/service/DrugE-Rank Contact: zhusf@fudan.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307615

DrugE-Rank: improving drug-target interaction prediction of new candidate drugs or targets by ensemble learning to rank.

PubMed

Yuan, Qingjun; Gao, Junning; Wu, Dongliang; Zhang, Shihua; Mamitsuka, Hiroshi; Zhu, Shanfeng

2016-06-15

Identifying drug-target interactions is an important task in drug discovery. To reduce heavy time and financial cost in experimental way, many computational approaches have been proposed. Although these approaches have used many different principles, their performance is far from satisfactory, especially in predicting drug-target interactions of new candidate drugs or targets. Approaches based on machine learning for this problem can be divided into two types: feature-based and similarity-based methods. Learning to rank is the most powerful technique in the feature-based methods. Similarity-based methods are well accepted, due to their idea of connecting the chemical and genomic spaces, represented by drug and target similarities, respectively. We propose a new method, DrugE-Rank, to improve the prediction performance by nicely combining the advantages of the two different types of methods. That is, DrugE-Rank uses LTR, for which multiple well-known similarity-based methods can be used as components of ensemble learning. The performance of DrugE-Rank is thoroughly examined by three main experiments using data from DrugBank: (i) cross-validation on FDA (US Food and Drug Administration) approved drugs before March 2014; (ii) independent test on FDA approved drugs after March 2014; and (iii) independent test on FDA experimental drugs. Experimental results show that DrugE-Rank outperforms competing methods significantly, especially achieving more than 30% improvement in Area under Prediction Recall curve for FDA approved new drugs and FDA experimental drugs. http://datamining-iip.fudan.edu.cn/service/DrugE-Rank zhusf@fudan.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Ephus: Multipurpose Data Acquisition Software for Neuroscience Experiments

PubMed Central

Suter, Benjamin A.; O'Connor, Timothy; Iyer, Vijay; Petreanu, Leopoldo T.; Hooks, Bryan M.; Kiritani, Taro; Svoboda, Karel; Shepherd, Gordon M. G.

2010-01-01

Physiological measurements in neuroscience experiments often involve complex stimulus paradigms and multiple data channels. Ephus (http://www.ephus.org) is an open-source software package designed for general-purpose data acquisition and instrument control. Ephus operates as a collection of modular programs, including an ephys program for standard whole-cell recording with single or multiple electrodes in typical electrophysiological experiments, and a mapper program for synaptic circuit mapping experiments involving laser scanning photostimulation based on glutamate uncaging or channelrhodopsin-2 excitation. Custom user functions allow user-extensibility at multiple levels, including on-line analysis and closed-loop experiments, where experimental parameters can be changed based on recently acquired data, such as during in vivo behavioral experiments. Ephus is compatible with a variety of data acquisition and imaging hardware. This paper describes the main features and modules of Ephus and their use in representative experimental applications. PMID:21960959

Phase-insensitive storage of coherences by reversible mapping onto long-lived populations

NASA Astrophysics Data System (ADS)

Mieth, Simon; Genov, Genko T.; Yatsenko, Leonid P.; Vitanov, Nikolay V.; Halfmann, Thomas

2016-01-01

We theoretically develop and experimentally demonstrate a coherence population mapping (CPM) protocol to store atomic coherences in long-lived populations, enabling storage times far beyond the typically very short decoherence times of quantum systems. The amplitude and phase of an atomic coherence is written onto the populations of a three-state system by specifically designed sequences of radiation pulses from two coupling fields. As an important feature, the CPM sequences enable a retrieval efficiency, which is insensitive to the phase of the initial coherence. The information is preserved in every individual atom of the medium, enabling applications in purely homogeneously or inhomogeneously broadened ensembles even when stochastic phase jumps are the main source of decoherence. We experimentally confirm the theoretical predictions by applying CPM for storage of atomic coherences in a doped solid, reaching storage times in the regime of 1 min.

Ultrafast spectral dynamics of dual-color-soliton intracavity collision in a mode-locked fiber laser

NASA Astrophysics Data System (ADS)

Wei, Yuan; Li, Bowen; Wei, Xiaoming; Yu, Ying; Wong, Kenneth K. Y.

2018-02-01

The single-shot spectral dynamics of dual-color-soliton collisions inside a mode-locked laser is experimentally and numerically investigated. By using the all-optically dispersive Fourier transform, we spectrally unveil the collision-induced soliton self-reshaping process, which features dynamic spectral fringes over the soliton main lobe, and the rebuilding of Kelly sidebands with wavelength drifting. Meanwhile, the numerical simulations validate the experimental observation and provide additional insights into the physical mechanism of the collision-induced spectral dynamics from the temporal domain perspective. It is verified that the dynamic interference between the soliton and the dispersive waves is responsible for the observed collision-induced spectral evolution. These dynamic phenomena not only demonstrate the role of dispersive waves in the sophisticated soliton interaction inside the laser cavity, but also facilitate a deeper understanding of the soliton's inherent stability.

[Radiotherapy phase I trials' methodology: Features].

PubMed

Rivoirard, R; Vallard, A; Langrand-Escure, J; Guy, J-B; Ben Mrad, M; Yaoxiong, X; Diao, P; Méry, B; Pigne, G; Rancoule, C; Magné, N

2016-12-01

In clinical research, biostatistical methods allow the rigorous analysis of data collection and should be defined from the trial design to obtain the appropriate experimental approach. Thus, if the main purpose of phase I is to determine the dose to use during phase II, methodology should be finely adjusted to experimental treatment(s). Today, the methodology for chemotherapy and targeted therapy is well known. For radiotherapy and chemoradiotherapy phase I trials, the primary endpoint must reflect both effectiveness and potential treatment toxicities. Methodology should probably be complex to limit failures in the following phases. However, there are very few data about methodology design in the literature. The present study focuses on these particular trials and their characteristics. It should help to raise existing methodological patterns shortcomings in order to propose new and better-suited designs. Copyright © 2016 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

Improved Intrapulse Raman Scattering Control via Asymmetric Airy Pulses

NASA Astrophysics Data System (ADS)

Hu, Yi; Tehranchi, Amirhossein; Wabnitz, Stefan; Kashyap, Raman; Chen, Zhigang; Morandotti, Roberto

2015-02-01

We experimentally demonstrate the possibility of tuning the frequency of a laser pulse via the use of an Airy pulse-seeded soliton self-frequency shift. The intrinsically asymmetric nature of Airy pulses, typically featured by either leading or trailing oscillatory tails (relatively to the main lobe), is revealed through the nonlinear generation of both a primary and a secondary Raman soliton self-frequency shift, a phenomenon which is driven by the soliton fission processes. The resulting frequency shift can be carefully controlled by using time-reversed Airy pulses or, alternatively, by applying an offset to the cubic phase modulation used to generate the pulses. When compared with the use of conventional chirped Gaussian pulses, our technique brings about unique advantages in terms of both efficient frequency tuning and feasibility, along with the generation and control of multicolor Raman solitons with enhanced tunability. Our theoretical analysis agrees well with our experimental observations.

A New Virtual and Remote Experimental Environment for Teaching and Learning Science

NASA Astrophysics Data System (ADS)

Lustigova, Zdena; Lustig, Frantisek

This paper describes how a scientifically exact and problem-solving-oriented remote and virtual science experimental environment might help to build a new strategy for science education. The main features are: the remote observations and control of real world phenomena, their processing and evaluation, verification of hypotheses combined with the development of critical thinking, supported by sophisticated relevant information search, classification and storing tools and collaborative environment, supporting argumentative writing and teamwork, public presentations and defense of achieved results, all either in real presence, in telepresence or in combination of both. Only then real understanding of generalized science laws and their consequences can be developed. This science learning and teaching environment (called ROL - Remote and Open Laboratory), has been developed and used by Charles University in Prague since 1996, offered to science students in both formal and informal learning, and also to science teachers within their professional development studies, since 2003.

Non-classical photon correlation in a two-dimensional photonic lattice.

PubMed

Gao, Jun; Qiao, Lu-Feng; Lin, Xiao-Feng; Jiao, Zhi-Qiang; Feng, Zhen; Zhou, Zheng; Gao, Zhen-Wei; Xu, Xiao-Yun; Chen, Yuan; Tang, Hao; Jin, Xian-Min

2016-06-13

Quantum interference and quantum correlation, as two main features of quantum optics, play an essential role in quantum information applications, such as multi-particle quantum walk and boson sampling. While many experimental demonstrations have been done in one-dimensional waveguide arrays, it remains unexplored in higher dimensions due to tight requirement of manipulating and detecting photons in large-scale. Here, we experimentally observe non-classical correlation of two identical photons in a fully coupled two-dimensional structure, i.e. photonic lattice manufactured by three-dimensional femtosecond laser writing. Photon interference consists of 36 Hong-Ou-Mandel interference and 9 bunching. The overlap between measured and simulated distribution is up to 0.890 ± 0.001. Clear photon correlation is observed in the two-dimensional photonic lattice. Combining with controllably engineered disorder, our results open new perspectives towards large-scale implementation of quantum simulation on integrated photonic chips.

Vanadium supersaturated silicon system: a theoretical and experimental approach

NASA Astrophysics Data System (ADS)

Garcia-Hemme, Eric; García, Gregorio; Palacios, Pablo; Montero, Daniel; García-Hernansanz, Rodrigo; Gonzalez-Diaz, Germán; Wahnon, Perla

2017-12-01

The effect of high dose vanadium ion implantation and pulsed laser annealing on the crystal structure and sub-bandgap optical absorption features of V-supersaturated silicon samples has been studied through the combination of experimental and theoretical approaches. Interest in V-supersaturated Si focusses on its potential as a material having a new band within the Si bandgap. Rutherford backscattering spectrometry measurements and formation energies computed through quantum calculations provide evidence that V atoms are mainly located at interstitial positions. The response of sub-bandgap spectral photoconductance is extended far into the infrared region of the spectrum. Theoretical simulations (based on density functional theory and many-body perturbation in GW approximation) bring to light that, in addition to V atoms at interstitial positions, Si defects should also be taken into account in explaining the experimental profile of the spectral photoconductance. The combination of experimental and theoretical methods provides evidence that the improved spectral photoconductance up to 6.2 µm (0.2 eV) is due to new sub-bandgap transitions, for which the new band due to V atoms within the Si bandgap plays an essential role. This enables the use of V-supersaturated silicon in the third generation of photovoltaic devices.

Drug-target interaction prediction from PSSM based evolutionary information.

PubMed

Mousavian, Zaynab; Khakabimamaghani, Sahand; Kavousi, Kaveh; Masoudi-Nejad, Ali

2016-01-01

The labor-intensive and expensive experimental process of drug-target interaction prediction has motivated many researchers to focus on in silico prediction, which leads to the helpful information in supporting the experimental interaction data. Therefore, they have proposed several computational approaches for discovering new drug-target interactions. Several learning-based methods have been increasingly developed which can be categorized into two main groups: similarity-based and feature-based. In this paper, we firstly use the bi-gram features extracted from the Position Specific Scoring Matrix (PSSM) of proteins in predicting drug-target interactions. Our results demonstrate the high-confidence prediction ability of the Bigram-PSSM model in terms of several performance indicators specifically for enzymes and ion channels. Moreover, we investigate the impact of negative selection strategy on the performance of the prediction, which is not widely taken into account in the other relevant studies. This is important, as the number of non-interacting drug-target pairs are usually extremely large in comparison with the number of interacting ones in existing drug-target interaction data. An interesting observation is that different levels of performance reduction have been attained for four datasets when we change the sampling method from the random sampling to the balanced sampling. Copyright © 2015 Elsevier Inc. All rights reserved.

Procedure Enabling Simulation and In-Depth Analysis of Optical Effects in Camera-Based Time-Of Sensors

NASA Astrophysics Data System (ADS)

Baumgart, M.; Druml, N.; Consani, M.

2018-05-01

This paper presents a simulation approach for Time-of-Flight cameras to estimate sensor performance and accuracy, as well as to help understanding experimentally discovered effects. The main scope is the detailed simulation of the optical signals. We use a raytracing-based approach and use the optical path length as the master parameter for depth calculations. The procedure is described in detail with references to our implementation in Zemax OpticStudio and Python. Our simulation approach supports multiple and extended light sources and allows accounting for all effects within the geometrical optics model. Especially multi-object reflection/scattering ray-paths, translucent objects, and aberration effects (e.g. distortion caused by the ToF lens) are supported. The optical path length approach also enables the implementation of different ToF senor types and transient imaging evaluations. The main features are demonstrated on a simple 3D test scene.

A Module for Adaptive Course Configuration and Assessment in Moodle

NASA Astrophysics Data System (ADS)

Limongelli, Carla; Sciarrone, Filippo; Temperini, Marco; Vaste, Giulia

Personalization and Adaptation are among the main challenges in the field of e-learning, where currently just few Learning Management Systems, mostly experimental ones, support such features. In this work we present an architecture that allows Moodle to interact with the Lecomps system, an adaptive learning system developed earlier by our research group, that has been working in a stand-alone modality so far. In particular, the Lecomps responsibilities are circumscribed to the sole production of personalized learning objects sequences and to the management of the student model, leaving to Moodle all the rest of the activities for course delivery. The Lecomps system supports the "dynamic" adaptation of learning objects sequences, basing on the student model, i.e., learner's Cognitive State and Learning Style. Basically, this work integrates two main Lecomps tasks into Moodle, to be directly managed by it: Authentication and Quizzes.

Singularities in the lineshape of a second-order perturbed quadrupolar nucleus. The magic-angle spinning case.

PubMed

Field, Timothy R; Bain, Alex D

2014-01-01

For a nucleus with a half-integral spin and a strong quadrupole coupling, the central transition (from magnetic quantum number -1/2 to +1/2) in the spectrum shows a characteristic lineshape. By strong coupling, we mean an interaction strong enough so that second-order perturbation theory is needed, yet still sufficient. The spectrum of a static sample is well-known and the magic-angle-spinning (MAS spectrum) is different, but still can be calculated. The important features of both these spectra are singularities and steps in the lineshape, since these are the main tools in fitting the calculated spectrum to experimental data. A useful tool in this investigation is a plot of the frequency as a function of orientation over the surface of the unit sphere. These plots have maxima, minima and saddle points, and these correspond to the features of the spectrum. We used these plots to define both the positions and derive new formulae for the heights of the features and we now extend this to the magic-angle spinning case. For the first time, we identify the orientations corresponding to the features of the MAS spectra and derive formulae for the heights. We then compare the static and MAS cases and show the relationships between the features in the two spectra. Copyright © 2014 Elsevier Inc. All rights reserved.

Visual Cortex Inspired CNN Model for Feature Construction in Text Analysis

PubMed Central

Fu, Hongping; Niu, Zhendong; Zhang, Chunxia; Ma, Jing; Chen, Jie

2016-01-01

Recently, biologically inspired models are gradually proposed to solve the problem in text analysis. Convolutional neural networks (CNN) are hierarchical artificial neural networks, which include a various of multilayer perceptrons. According to biological research, CNN can be improved by bringing in the attention modulation and memory processing of primate visual cortex. In this paper, we employ the above properties of primate visual cortex to improve CNN and propose a biological-mechanism-driven-feature-construction based answer recommendation method (BMFC-ARM), which is used to recommend the best answer for the corresponding given questions in community question answering. BMFC-ARM is an improved CNN with four channels respectively representing questions, answers, asker information and answerer information, and mainly contains two stages: biological mechanism driven feature construction (BMFC) and answer ranking. BMFC imitates the attention modulation property by introducing the asker information and answerer information of given questions and the similarity between them, and imitates the memory processing property through bringing in the user reputation information for answerers. Then the feature vector for answer ranking is constructed by fusing the asker-answerer similarities, answerer's reputation and the corresponding vectors of question, answer, asker, and answerer. Finally, the Softmax is used at the stage of answer ranking to get best answers by the feature vector. The experimental results of answer recommendation on the Stackexchange dataset show that BMFC-ARM exhibits better performance. PMID:27471460

Visual Cortex Inspired CNN Model for Feature Construction in Text Analysis.

PubMed

Fu, Hongping; Niu, Zhendong; Zhang, Chunxia; Ma, Jing; Chen, Jie

2016-01-01

Recently, biologically inspired models are gradually proposed to solve the problem in text analysis. Convolutional neural networks (CNN) are hierarchical artificial neural networks, which include a various of multilayer perceptrons. According to biological research, CNN can be improved by bringing in the attention modulation and memory processing of primate visual cortex. In this paper, we employ the above properties of primate visual cortex to improve CNN and propose a biological-mechanism-driven-feature-construction based answer recommendation method (BMFC-ARM), which is used to recommend the best answer for the corresponding given questions in community question answering. BMFC-ARM is an improved CNN with four channels respectively representing questions, answers, asker information and answerer information, and mainly contains two stages: biological mechanism driven feature construction (BMFC) and answer ranking. BMFC imitates the attention modulation property by introducing the asker information and answerer information of given questions and the similarity between them, and imitates the memory processing property through bringing in the user reputation information for answerers. Then the feature vector for answer ranking is constructed by fusing the asker-answerer similarities, answerer's reputation and the corresponding vectors of question, answer, asker, and answerer. Finally, the Softmax is used at the stage of answer ranking to get best answers by the feature vector. The experimental results of answer recommendation on the Stackexchange dataset show that BMFC-ARM exhibits better performance.

True-Triaxial Experimental Study of the Evolutionary Features of the Acoustic Emissions and Sounds of Rockburst Processes

NASA Astrophysics Data System (ADS)

Su, Guoshao; Shi, Yanjiong; Feng, Xiating; Jiang, Jianqing; Zhang, Jie; Jiang, Quan

2018-02-01

Rockbursts are markedly characterized by the ejection of rock fragments from host rocks at certain speeds. The rockburst process is always accompanied by acoustic signals that include acoustic emissions (AE) and sounds. A deep insight into the evolutionary features of AE and sound signals is important to improve the accuracy of rockburst prediction. To investigate the evolutionary features of AE and sound signals, rockburst tests on granite rock specimens under true-triaxial loading conditions were performed using an improved rockburst testing system, and the AE and sounds during rockburst development were recorded and analyzed. The results show that the evolutionary features of the AE and sound signals were obvious and similar. On the eve of a rockburst, a `quiescent period' could be observed in both the evolutionary process of the AE hits and the sound waveform. Furthermore, the time-dependent fractal dimensions of the AE hits and sound amplitude both showed a tendency to continuously decrease on the eve of the rockbursts. In addition, on the eve of the rockbursts, the main frequency of the AE and sound signals both showed decreasing trends, and the frequency spectrum distributions were both characterized by low amplitudes, wide frequency bands and multiple peak shapes. Thus, the evolutionary features of sound signals on the eve of rockbursts, as well as that of AE signals, can be used as beneficial information for rockburst prediction.

Enhancement of the Feature Extraction Capability in Global Damage Detection Using Wavelet Theory

NASA Technical Reports Server (NTRS)

Saleeb, Atef F.; Ponnaluru, Gopi Krishna

2006-01-01

The main objective of this study is to assess the specific capabilities of the defect energy parameter technique for global damage detection developed by Saleeb and coworkers. The feature extraction is the most important capability in any damage-detection technique. Features are any parameters extracted from the processed measurement data in order to enhance damage detection. The damage feature extraction capability was studied extensively by analyzing various simulation results. The practical significance in structural health monitoring is that the detection at early stages of small-size defects is always desirable. The amount of changes in the structure's response due to these small defects was determined to show the needed level of accuracy in the experimental methods. The arrangement of fine/extensive sensor network to measure required data for the detection is an "unlimited" ability, but there is a difficulty to place extensive number of sensors on a structure. Therefore, an investigation was conducted using the measurements of coarse sensor network. The white and the pink noises, which cover most of the frequency ranges that are typically encountered in the many measuring devices used (e.g., accelerometers, strain gauges, etc.) are added to the displacements to investigate the effect of noisy measurements in the detection technique. The noisy displacements and the noisy damage parameter values are used to study the signal feature reconstruction using wavelets. The enhancement of the feature extraction capability was successfully achieved by the wavelet theory.

A statics-dynamics equivalence through the fluctuation–dissipation ratio provides a window into the spin-glass phase from nonequilibrium measurements

PubMed Central

Baity-Jesi, Marco; Calore, Enrico; Cruz, Andres; Fernandez, Luis Antonio; Gil-Narvión, José Miguel; Gordillo-Guerrero, Antonio; Iñiguez, David; Maiorano, Andrea; Marinari, Enzo; Martin-Mayor, Victor; Monforte-Garcia, Jorge; Muñoz Sudupe, Antonio; Navarro, Denis; Parisi, Giorgio; Perez-Gaviro, Sergio; Ricci-Tersenghi, Federico; Ruiz-Lorenzo, Juan Jesus; Schifano, Sebastiano Fabio; Tarancón, Alfonso; Tripiccione, Raffaele; Yllanes, David

2017-01-01

We have performed a very accurate computation of the nonequilibrium fluctuation–dissipation ratio for the 3D Edwards–Anderson Ising spin glass, by means of large-scale simulations on the special-purpose computers Janus and Janus II. This ratio (computed for finite times on very large, effectively infinite, systems) is compared with the equilibrium probability distribution of the spin overlap for finite sizes. Our main result is a quantitative statics-dynamics dictionary, which could allow the experimental exploration of important features of the spin-glass phase without requiring uncontrollable extrapolations to infinite times or system sizes. PMID:28174274

Physical Regulation of the Self-Assembly of Tobacco Mosaic Virus Coat Protein

PubMed Central

Kegel, Willem K.; van der Schoot, Paul

2006-01-01

We present a statistical mechanical model based on the principle of mass action that explains the main features of the in vitro aggregation behavior of the coat protein of tobacco mosaic virus (TMV). By comparing our model to experimentally obtained stability diagrams, titration experiments, and calorimetric data, we pin down three competing factors that regulate the transitions between the different kinds of aggregated state of the coat protein. These are hydrophobic interactions, electrostatic interactions, and the formation of so-called “Caspar” carboxylate pairs. We suggest that these factors could be universal and relevant to a large class of virus coat proteins. PMID:16731551

A survey of keystroke dynamics biometrics.

PubMed

Teh, Pin Shen; Teoh, Andrew Beng Jin; Yue, Shigang

2013-01-01

Research on keystroke dynamics biometrics has been increasing, especially in the last decade. The main motivation behind this effort is due to the fact that keystroke dynamics biometrics is economical and can be easily integrated into the existing computer security systems with minimal alteration and user intervention. Numerous studies have been conducted in terms of data acquisition devices, feature representations, classification methods, experimental protocols, and evaluations. However, an up-to-date extensive survey and evaluation is not yet available. The objective of this paper is to provide an insightful survey and comparison on keystroke dynamics biometrics research performed throughout the last three decades, as well as offering suggestions and possible future research directions.

[Vaccination with Mycobacterium: can it cure allergies?].

PubMed

Louis, R

2003-06-01

In developed countries, the prevalence of tuberculosis has evolved in an opposite direction as to the one of allergy over the last century. The immunological response is mainly Th1 in tuberculosis while it features a Th2 pattern in allergy. Vaccination with BCG in early life is associated with a reduction in the prevalence of allergy later in childhood. In an experimental mouse model of asthma, administration of BCG or killed Mycobacterium vaccae inhibits the sensitisation process as well as the bronchial inflammation and hyperresponsiveness that follows allergen exposure. In children and adolescents suffering from atopic dermatitis, subcutaneous injection of killed Mycobacterium vaccae attenuates the severity of skin lesions.

Data mining in bioinformatics using Weka.

PubMed

Frank, Eibe; Hall, Mark; Trigg, Len; Holmes, Geoffrey; Witten, Ian H

2004-10-12

The Weka machine learning workbench provides a general-purpose environment for automatic classification, regression, clustering and feature selection-common data mining problems in bioinformatics research. It contains an extensive collection of machine learning algorithms and data pre-processing methods complemented by graphical user interfaces for data exploration and the experimental comparison of different machine learning techniques on the same problem. Weka can process data given in the form of a single relational table. Its main objectives are to (a) assist users in extracting useful information from data and (b) enable them to easily identify a suitable algorithm for generating an accurate predictive model from it. http://www.cs.waikato.ac.nz/ml/weka.

Anisotropic failure and size effects in periodic honeycomb materials: A gradient-elasticity approach

NASA Astrophysics Data System (ADS)

Réthoré, Julien; Dang, Thi Bach Tuyet; Kaltenbrunner, Christine

2017-02-01

This paper proposes a fracture mechanics model for the analysis of crack propagation in periodic honeycomb materials. The model is based on gradient-elasticity which enables us to account for the effect of the material structure at the macroscopic scale. For simulating the propagation of cracks along an arbitrary path, the numerical implementation is elaborated based on an extended finite element method with the required level of continuity. The two main features captured by the model are directionality and size effect. The numerical predictions are consistent with experimental results on honeycomb materials but also with results reported in the literature for microstructurally short cracks in metals.

The Crystal Structures of Potentially Tautomeric Compounds

NASA Astrophysics Data System (ADS)

Furmanova, Nina G.

1981-08-01

Data on the structures of potentially proto-, metallo-, and carbono-tropic compounds, obtained mainly by X-ray diffraction, are surveyed. The results of neutron and electron diffraction studies have also been partly used. It is shown that a characteristic feature of all the systems considered is the formation of hydrogen or secondary bonds ensuring the contribution of both possible tautomeric forms to the structure. Systematic consideration of the experimental data leads to the conclusion that there is a close relation between the crystal structure and the dynamic behaviour of the molecules in solution and that secondary and hydrogen bonds play a significant role in the tautomeric transition. The bibliography includes 152 references.

On the efficient and reliable numerical solution of rate-and-state friction problems

NASA Astrophysics Data System (ADS)

Pipping, Elias; Kornhuber, Ralf; Rosenau, Matthias; Oncken, Onno

2016-03-01

We present a mathematically consistent numerical algorithm for the simulation of earthquake rupture with rate-and-state friction. Its main features are adaptive time stepping, a novel algebraic solution algorithm involving nonlinear multigrid and a fixed point iteration for the rate-and-state decoupling. The algorithm is applied to a laboratory scale subduction zone which allows us to compare our simulations with experimental results. Using physical parameters from the experiment, we find a good fit of recurrence time of slip events as well as their rupture width and peak slip. Computations in 3-D confirm efficiency and robustness of our algorithm.

An effective method for cirrhosis recognition based on multi-feature fusion

NASA Astrophysics Data System (ADS)

Chen, Yameng; Sun, Gengxin; Lei, Yiming; Zhang, Jinpeng

2018-04-01

Liver disease is one of the main causes of human healthy problem. Cirrhosis, of course, is the critical phase during the development of liver lesion, especially the hepatoma. Many clinical cases are still influenced by the subjectivity of physicians in some degree, and some objective factors such as illumination, scale, edge blurring will affect the judgment of clinicians. Then the subjectivity will affect the accuracy of diagnosis and the treatment of patients. In order to solve the difficulty above and improve the recognition rate of liver cirrhosis, we propose a method of multi-feature fusion to obtain more robust representations of texture in ultrasound liver images, the texture features we extract include local binary pattern(LBP), gray level co-occurrence matrix(GLCM) and histogram of oriented gradient(HOG). In this paper, we firstly make a fusion of multi-feature to recognize cirrhosis and normal liver based on parallel combination concept, and the experimental results shows that the classifier is effective for cirrhosis recognition which is evaluated by the satisfying classification rate, sensitivity and specificity of receiver operating characteristic(ROC), and cost time. Through the method we proposed, it will be helpful to improve the accuracy of diagnosis of cirrhosis and prevent the development of liver lesion towards hepatoma.

A multi-feature integration method for fatigue crack detection and crack length estimation in riveted lap joints using Lamb waves

NASA Astrophysics Data System (ADS)

He, Jingjing; Guan, Xuefei; Peng, Tishun; Liu, Yongming; Saxena, Abhinav; Celaya, Jose; Goebel, Kai

2013-10-01

This paper presents an experimental study of damage detection and quantification in riveted lap joints. Embedded lead zirconate titanate piezoelectric (PZT) ceramic wafer-type sensors are employed to perform in situ non-destructive evaluation (NDE) during fatigue cyclical loading. PZT wafers are used to monitor the wave reflection from the boundaries of the fatigue crack at the edge of bolt joints. The group velocity of the guided wave is calculated to select a proper time window in which the received signal contains the damage information. It is found that the fatigue crack lengths are correlated with three main features of the signal, i.e., correlation coefficient, amplitude change, and phase change. It was also observed that a single feature cannot be used to quantify the damage among different specimens since a considerable variability was observed in the response from different specimens. A multi-feature integration method based on a second-order multivariate regression analysis is proposed for the prediction of fatigue crack lengths using sensor measurements. The model parameters are obtained using training datasets from five specimens. The effectiveness of the proposed methodology is demonstrated using several lap joint specimens from different manufactures and under different loading conditions.

Recycling Old PCC Pavement - Performance Evaluation of FAI 57 Inlays

DOT National Transportation Integrated Search

1993-02-01

This report details the construction and performance monitoring efforts of two demonstration projects proposed in an experimental features work plan entitled Recycling Old PCC Pavement". The objectives of this experimental feature were to evaluate th...

Direct measurement of nuclear cross-section of astrophysical interest: Results and perspectives

NASA Astrophysics Data System (ADS)

Cavanna, Francesca; Prati, Paolo

2018-03-01

Stellar evolution and nucleosynthesis are interconnected by a wide network of nuclear reactions: the study of such connection is usually known as nuclear astrophysics. The main task of this discipline is the determination of nuclear cross-section and hence of the reaction rate in different scenarios, i.e. from the synthesis of a few very light isotopes just after the Big Bang to the heavy element production in the violent explosive end of massive stars. The experimental determination of reaction cross-section at the astrophysical relevant energies is extremely difficult, sometime impossible, due to the Coulomb repulsion between the interacting nuclei which turns out in cross-section values down to the fbar level. To overcome these obstacles, several experimental approaches have been developed and the adopted techniques can be roughly divided into two categories, i.e. direct and indirect methods. In this review paper, the general problem of nuclear astrophysics is introduced and discussed from the point of view of experimental approach. We focus on direct methods and in particular on the features of low-background experiments performed at underground laboratory facilities. The present knowledge of reactions involved in the Big Bang and stellar hydrogen-burning scenarios is discussed as well as the ongoing projects aiming to investigate mainly the helium- and carbon-burning phases. Worldwide, a new generation of experiment in the MeV range is in the design phase or at the very first steps and decisive progresses are expected to come in the next years.

Experimental Estimation Of Energy Damping During Free Rocking Of Unreinforced Masonry Walls. First Results

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

Sorrentino, Luigi; Masiani, Renato; Benedetti, Stefano

2008-07-08

This paper presents an ongoing experimental program on unreinforced masonry walls undergoing free rocking. Aim of the laboratory campaign is the estimation of kinetic energy damping exhibited by walls released with non-zero initial conditions of motion. Such energy damping is necessary for dynamic modelling of unreinforced masonry local mechanisms. After a brief review of the literature on this topic, the main features of the laboratory tests are presented. The program involves the experimental investigation of several parameters: 1) unit material (brick or tuff), 2) wall aspect ratio (ranging between 14.5 and 7.1), 3) restraint condition (two-sided or one-sided rocking), andmore » 4) depth of the contact surface between facade and transverse walls (one-sided rocking only). All walls are single wythe and the mortar is pozzuolanic. The campaign is still in progress. However, it is possible to present the results on most of the mechanical properties of mortar and bricks. Moreover, a few time histories are reported, already indicating the need to correct some of the assumptions frequent in the literature.« less

Counter-Flow Cooling Tower Test Cell

NASA Astrophysics Data System (ADS)

Dvořák, Lukáš; Nožička, Jiří

2014-03-01

The article contains a design of a functional experimental model of a cross-flow mechanical draft cooling tower and the results and outcomes of measurements. This device is primarily used for measuring performance characteristics of cooling fills, but with a simple rebuild, it can be used for measuring other thermodynamic processes that take part in so-called wet cooling. The main advantages of the particular test cell lie in the accuracy, size, and the possibility of changing the water distribution level. This feature is very useful for measurements of fills of different heights without the influence of the spray and rain zone. The functionality of this test cell has been verified experimentally during assembly, and data from the measurement of common film cooling fills have been compared against the results taken from another experimental line. For the purpose of evaluating the data gathered, computational scripts were created in the MATLAB numerical computing environment. The first script is for exact calculation of the thermal balance of the model, and the second is for determining Merkel's number via Chebyshev's method.

IUPAC-NIST Solubility Data Series. 100. Rare Earth Metal Fluorides in Water and Aqueous Systems. Part 2. Light Lanthanides (Ce–Eu)

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

Mioduski, Tomasz; Gumiński, Cezary, E-mail: cegie@chem.uw.edu.pl; Zeng, Dewen, E-mail: dewen-zeng@hotmail.com

This is the second part of the volume devoted to the evaluation of experimental solubility data for rare earth metal (REM) fluorides in water as well as in aqueous ternary and multicomponent systems. Fluorides of Ce, Pr, Nd, Pm, Sm, and Eu (so-called light lanthanides), as the main solutes, are covered in the present part, which has thorough coverage of the experimental literature through the end of 2012. The experimentally unknown solubility value for PmF{sub 3} in water was predicted by an interpolation of the solubility values for NdF{sub 3} and SmF{sub 3} at 298 K. General features of themore » systems, such as the nature of the equilibrium solid phases, solubility as a function of temperature, influence of ionic strength, pH, mixed solvent medium on the solubility, quality of the solubility results, and solubility as a function of REM atomic number, have already been presented in Part 1 of the volume.« less

Acoustic Features Influence Musical Choices Across Multiple Genres.

PubMed

Barone, Michael D; Bansal, Jotthi; Woolhouse, Matthew H

2017-01-01

Based on a large behavioral dataset of music downloads, two analyses investigate whether the acoustic features of listeners' preferred musical genres influence their choice of tracks within non-preferred, secondary musical styles. Analysis 1 identifies feature distributions for pairs of genre-defined subgroups that are distinct. Using correlation analysis, these distributions are used to test the degree of similarity between subgroups' main genres and the other music within their download collections. Analysis 2 explores the issue of main-to-secondary genre influence through the production of 10 feature-influence matrices, one per acoustic feature, in which cell values indicate the percentage change in features for genres and subgroups compared to overall population averages. In total, 10 acoustic features and 10 genre-defined subgroups are explored within the two analyses. Results strongly indicate that the acoustic features of people's main genres influence the tracks they download within non-preferred, secondary musical styles. The nature of this influence and its possible actuating mechanisms are discussed with respect to research on musical preference, personality, and statistical learning.

Analysis of a Split-Plot Experimental Design Applied to a Low-Speed Wind Tunnel Investigation

NASA Technical Reports Server (NTRS)

Erickson, Gary E.

2013-01-01

A procedure to analyze a split-plot experimental design featuring two input factors, two levels of randomization, and two error structures in a low-speed wind tunnel investigation of a small-scale model of a fighter airplane configuration is described in this report. Standard commercially-available statistical software was used to analyze the test results obtained in a randomization-restricted environment often encountered in wind tunnel testing. The input factors were differential horizontal stabilizer incidence and the angle of attack. The response variables were the aerodynamic coefficients of lift, drag, and pitching moment. Using split-plot terminology, the whole plot, or difficult-to-change, factor was the differential horizontal stabilizer incidence, and the subplot, or easy-to-change, factor was the angle of attack. The whole plot and subplot factors were both tested at three levels. Degrees of freedom for the whole plot error were provided by replication in the form of three blocks, or replicates, which were intended to simulate three consecutive days of wind tunnel facility operation. The analysis was conducted in three stages, which yielded the estimated mean squares, multiple regression function coefficients, and corresponding tests of significance for all individual terms at the whole plot and subplot levels for the three aerodynamic response variables. The estimated regression functions included main effects and two-factor interaction for the lift coefficient, main effects, two-factor interaction, and quadratic effects for the drag coefficient, and only main effects for the pitching moment coefficient.

ADHD classification using bag of words approach on network features

NASA Astrophysics Data System (ADS)

Solmaz, Berkan; Dey, Soumyabrata; Rao, A. Ravishankar; Shah, Mubarak

2012-02-01

Attention Deficit Hyperactivity Disorder (ADHD) is receiving lots of attention nowadays mainly because it is one of the common brain disorders among children and not much information is known about the cause of this disorder. In this study, we propose to use a novel approach for automatic classification of ADHD conditioned subjects and control subjects using functional Magnetic Resonance Imaging (fMRI) data of resting state brains. For this purpose, we compute the correlation between every possible voxel pairs within a subject and over the time frame of the experimental protocol. A network of voxels is constructed by representing a high correlation value between any two voxels as an edge. A Bag-of-Words (BoW) approach is used to represent each subject as a histogram of network features; such as the number of degrees per voxel. The classification is done using a Support Vector Machine (SVM). We also investigate the use of raw intensity values in the time series for each voxel. Here, every subject is represented as a combined histogram of network and raw intensity features. Experimental results verified that the classification accuracy improves when the combined histogram is used. We tested our approach on a highly challenging dataset released by NITRC for ADHD-200 competition and obtained promising results. The dataset not only has a large size but also includes subjects from different demography and edge groups. To the best of our knowledge, this is the first paper to propose BoW approach in any functional brain disorder classification and we believe that this approach will be useful in analysis of many brain related conditions.

True Triaxial Experimental Study of Rockbursts Induced By Ramp and Cyclic Dynamic Disturbances

NASA Astrophysics Data System (ADS)

Su, Guoshao; Hu, Lihua; Feng, Xiating; Yan, Liubin; Zhang, Gangliang; Yan, Sizhou; Zhao, Bin; Yan, Zhaofu

2018-04-01

A modified rockburst testing system was utilized to reproduce rockbursts induced by ramp and cyclic dynamic disturbances with a low-intermediate strain rate of 2 × 10-3-5 × 10-3 s-1 in the laboratory. The experimental results show that both the ramp and cyclic dynamic disturbances play a significant role in inducing rockbursts. In the tests of rockbursts induced by a ramp dynamic disturbance, as the static stress before the dynamic disturbance increases, both the strength of specimens and the kinetic energy of the ejected fragments first increase and then decrease. In the tests of rockbursts induced by a cyclic dynamic disturbance, there exists a rockburst threshold of the static stress and the dynamic disturbance amplitude, and the kinetic energy of the ejected fragments first increases and then decreases as the cyclic dynamic disturbance frequency increases. The main differences between rockbursts induced by ramp dynamic disturbances and those induced by cyclic dynamic disturbances are as follows: the rockburst development process of the former is characterized by an impact failure feature, while that of the latter is characterized by a fatigue failure feature; the damage evolution curve of the specimen of the former has a leap-developing form with a significant catastrophic feature, while that of the latter has an inverted S-shape with a remarkable fatigue damage characteristic; the energy mechanism of the former involves the ramp dynamic disturbance giving extra elastic strain energy to rocks, while that of the latter involves the cyclic dynamic disturbance decreasing the ultimate energy storage capacity of rocks.

Neuronal avalanches and learning

NASA Astrophysics Data System (ADS)

de Arcangelis, Lucilla

2011-05-01

Networks of living neurons represent one of the most fascinating systems of biology. If the physical and chemical mechanisms at the basis of the functioning of a single neuron are quite well understood, the collective behaviour of a system of many neurons is an extremely intriguing subject. Crucial ingredient of this complex behaviour is the plasticity property of the network, namely the capacity to adapt and evolve depending on the level of activity. This plastic ability is believed, nowadays, to be at the basis of learning and memory in real brains. Spontaneous neuronal activity has recently shown features in common to other complex systems. Experimental data have, in fact, shown that electrical information propagates in a cortex slice via an avalanche mode. These avalanches are characterized by a power law distribution for the size and duration, features found in other problems in the context of the physics of complex systems and successful models have been developed to describe their behaviour. In this contribution we discuss a statistical mechanical model for the complex activity in a neuronal network. The model implements the main physiological properties of living neurons and is able to reproduce recent experimental results. Then, we discuss the learning abilities of this neuronal network. Learning occurs via plastic adaptation of synaptic strengths by a non-uniform negative feedback mechanism. The system is able to learn all the tested rules, in particular the exclusive OR (XOR) and a random rule with three inputs. The learning dynamics exhibits universal features as function of the strength of plastic adaptation. Any rule could be learned provided that the plastic adaptation is sufficiently slow.

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

Lin, Jiusheng; van den Bedem, Henry; Brunger, Axel T.

Calmodulin (CaM) is the primary calcium signaling protein in eukaryotes and has been extensively studied using various biophysical techniques. Prior crystal structures have noted the presence of ambiguous electron density in both hydrophobic binding pockets of Ca 2+-CaM, but no assignment of these features has been made. In addition, Ca 2+-CaM samples many conformational substates in the crystal and accurately modeling the full range of this functionally important disorder is challenging. In order to characterize these features in a minimally biased manner, a 1.0 Å resolution single-wavelength anomalous diffraction data set was measured for selenomethionine-substituted Ca 2+-CaM. Density-modified electron-density mapsmore » enabled the accurate assignment of Ca 2+-CaM main-chain and side-chain disorder. These experimental maps also substantiate complex disorder models that were automatically built using low-contour features of model-phased electron density. Furthermore, experimental electron-density maps reveal that 2-methyl-2,4-pentanediol (MPD) is present in the C-terminal domain, mediates a lattice contact between N-terminal domains and may occupy the N-terminal binding pocket. The majority of the crystal structures of target-free Ca 2+-CaM have been derived from crystals grown using MPD as a precipitant, and thus MPD is likely to be bound in functionally critical regions of Ca 2+-CaM in most of these structures. The adventitious binding of MPD helps to explain differences between the Ca 2+-CaM crystal and solution structures and is likely to favor more open conformations of the EF-hands in the crystal.« less

Dynamic Socialized Gaussian Process Models for Human Behavior Prediction in a Health Social Network

PubMed Central

Shen, Yelong; Phan, NhatHai; Xiao, Xiao; Jin, Ruoming; Sun, Junfeng; Piniewski, Brigitte; Kil, David; Dou, Dejing

2016-01-01

Modeling and predicting human behaviors, such as the level and intensity of physical activity, is a key to preventing the cascade of obesity and helping spread healthy behaviors in a social network. In our conference paper, we have developed a social influence model, named Socialized Gaussian Process (SGP), for socialized human behavior modeling. Instead of explicitly modeling social influence as individuals' behaviors influenced by their friends' previous behaviors, SGP models the dynamic social correlation as the result of social influence. The SGP model naturally incorporates personal behavior factor and social correlation factor (i.e., the homophily principle: Friends tend to perform similar behaviors) into a unified model. And it models the social influence factor (i.e., an individual's behavior can be affected by his/her friends) implicitly in dynamic social correlation schemes. The detailed experimental evaluation has shown the SGP model achieves better prediction accuracy compared with most of baseline methods. However, a Socialized Random Forest model may perform better at the beginning compared with the SGP model. One of the main reasons is the dynamic social correlation function is purely based on the users' sequential behaviors without considering other physical activity-related features. To address this issue, we further propose a novel “multi-feature SGP model” (mfSGP) which improves the SGP model by using multiple physical activity-related features in the dynamic social correlation learning. Extensive experimental results illustrate that the mfSGP model clearly outperforms all other models in terms of prediction accuracy and running time. PMID:27746515

Shale embankment construction criteria : experimental feature interim report.

DOT National Transportation Integrated Search

1985-06-01

The research was conducted in the summer of 1983 during the realignment construction of the Mystic Creek - Camas Valley section on the Coos Bay - Roseburg Highway. Construction is still in progress. As outlined in the experimental features work plan ...

Present status, future prospects of domestic acoustical instruments

NASA Astrophysics Data System (ADS)

Guibin, L.

1984-01-01

The product lines, specifications, and special features of China's main acoustical instrument products are described. The methods of operation nd the main problems associated with these products are discussed. Examples of the application of acoustical instruments are given. The main features of a digital signal analyzer are enumerated.

Secure UNIX socket-based controlling system for high-throughput protein crystallography experiments.

PubMed

Gaponov, Yurii; Igarashi, Noriyuki; Hiraki, Masahiko; Sasajima, Kumiko; Matsugaki, Naohiro; Suzuki, Mamoru; Kosuge, Takashi; Wakatsuki, Soichi

2004-01-01

A control system for high-throughput protein crystallography experiments has been developed based on a multilevel secure (SSL v2/v3) UNIX socket under the Linux operating system. Main features of protein crystallography experiments (purification, crystallization, loop preparation, data collecting, data processing) are dealt with by the software. All information necessary to perform protein crystallography experiments is stored (except raw X-ray data, that are stored in Network File Server) in a relational database (MySQL). The system consists of several servers and clients. TCP/IP secure UNIX sockets with four predefined behaviors [(a) listening to a request followed by a reply, (b) sending a request and waiting for a reply, (c) listening to a broadcast message, and (d) sending a broadcast message] support communications between all servers and clients allowing one to control experiments, view data, edit experimental conditions and perform data processing remotely. The usage of the interface software is well suited for developing well organized control software with a hierarchical structure of different software units (Gaponov et al., 1998), which will pass and receive different types of information. All communication is divided into two parts: low and top levels. Large and complicated control tasks are split into several smaller ones, which can be processed by control clients independently. For communicating with experimental equipment (beamline optical elements, robots, and specialized experimental equipment etc.), the STARS server, developed at the Photon Factory, is used (Kosuge et al., 2002). The STARS server allows any application with an open socket to be connected with any other clients that control experimental equipment. Majority of the source code is written in C/C++. GUI modules of the system were built mainly using Glade user interface builder for GTK+ and Gnome under Red Hat Linux 7.1 operating system.

Automatic brain MR image denoising based on texture feature-based artificial neural networks.

PubMed

Chang, Yu-Ning; Chang, Herng-Hua

2015-01-01

Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

Severity of clinical disease and pathology in ferrets experimentally infected with influenza viruses is influenced by inoculum volume.

PubMed

Moore, Ian N; Lamirande, Elaine W; Paskel, Myeisha; Donahue, Danielle; Kenney, Heather; Qin, Jing; Subbarao, Kanta

2014-12-01

Ferrets are a valuable model for influenza virus pathogenesis, virus transmission, and antiviral therapy studies. However, the contributions of the volume of inoculum administered and the ferret's respiratory tract anatomy to disease outcome have not been explored. We noted variations in clinical disease outcomes and the volume of inoculum administered and investigated these differences by administering two influenza viruses (A/California/07/2009 [H1N1 pandemic] and A/Minnesota/11/2010 [H3N2 variant]) to ferrets intranasally at a dose of 10(6) 50% tissue culture infective doses in a range of inoculum volumes (0.2, 0.5, or 1.0 ml) and followed viral replication, clinical disease, and pathology over 6 days. Clinical illness and respiratory tract pathology were the most severe and most consistent when the viruses were administered in a volume of 1.0 ml. Using a modified micro-computed tomography imaging method and examining gross specimens, we found that the right main-stem bronchus was consistently larger in diameter than the left main-stem bronchus, though the latter was longer and straighter. These anatomic features likely influence the distribution of the inoculum in the lower respiratory tract. A 1.0-ml volume of inoculum is optimal for delivery of virus to the lower respiratory tract of ferrets, particularly when evaluation of clinical disease is desired. Furthermore, we highlight important anatomical features of the ferret lung that influence the kinetics of viral replication, clinical disease severity, and lung pathology. Ferrets are a valuable model for influenza virus pathogenesis, virus transmission, and antiviral therapy studies. Clinical disease in ferrets is an important parameter in evaluating the virulence of novel influenza viruses, and findings are extrapolated to virulence in humans. Therefore, it is highly desirable that the data from different laboratories be accurate and reproducible. We have found that, even when the same virus was administered at similar doses, different investigators reported a range of clinical disease outcomes, from asymptomatic infection to severe weight loss, ocular and nasal discharge, sneezing, and lethargy. We found that a wide range of inoculum volumes was used to experimentally infect ferrets, and we sought to determine whether the variations in disease outcome were the result of the volume of inoculum administered. These data highlight some less explored features of the model, methods of experimental infection, and clinical disease outcomes in a research setting. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Severity of Clinical Disease and Pathology in Ferrets Experimentally Infected with Influenza Viruses Is Influenced by Inoculum Volume

PubMed Central

Moore, Ian N.; Lamirande, Elaine W.; Paskel, Myeisha; Donahue, Danielle; Qin, Jing

2014-01-01

ABSTRACT Ferrets are a valuable model for influenza virus pathogenesis, virus transmission, and antiviral therapy studies. However, the contributions of the volume of inoculum administered and the ferret's respiratory tract anatomy to disease outcome have not been explored. We noted variations in clinical disease outcomes and the volume of inoculum administered and investigated these differences by administering two influenza viruses (A/California/07/2009 [H1N1 pandemic] and A/Minnesota/11/2010 [H3N2 variant]) to ferrets intranasally at a dose of 106 50% tissue culture infective doses in a range of inoculum volumes (0.2, 0.5, or 1.0 ml) and followed viral replication, clinical disease, and pathology over 6 days. Clinical illness and respiratory tract pathology were the most severe and most consistent when the viruses were administered in a volume of 1.0 ml. Using a modified micro-computed tomography imaging method and examining gross specimens, we found that the right main-stem bronchus was consistently larger in diameter than the left main-stem bronchus, though the latter was longer and straighter. These anatomic features likely influence the distribution of the inoculum in the lower respiratory tract. A 1.0-ml volume of inoculum is optimal for delivery of virus to the lower respiratory tract of ferrets, particularly when evaluation of clinical disease is desired. Furthermore, we highlight important anatomical features of the ferret lung that influence the kinetics of viral replication, clinical disease severity, and lung pathology. IMPORTANCE Ferrets are a valuable model for influenza virus pathogenesis, virus transmission, and antiviral therapy studies. Clinical disease in ferrets is an important parameter in evaluating the virulence of novel influenza viruses, and findings are extrapolated to virulence in humans. Therefore, it is highly desirable that the data from different laboratories be accurate and reproducible. We have found that, even when the same virus was administered at similar doses, different investigators reported a range of clinical disease outcomes, from asymptomatic infection to severe weight loss, ocular and nasal discharge, sneezing, and lethargy. We found that a wide range of inoculum volumes was used to experimentally infect ferrets, and we sought to determine whether the variations in disease outcome were the result of the volume of inoculum administered. These data highlight some less explored features of the model, methods of experimental infection, and clinical disease outcomes in a research setting. PMID:25187553

A liver cirrhosis classification on B-mode ultrasound images by the use of higher order local autocorrelation features

NASA Astrophysics Data System (ADS)

Sasaki, Kenya; Mitani, Yoshihiro; Fujita, Yusuke; Hamamoto, Yoshihiko; Sakaida, Isao

2017-02-01

In this paper, in order to classify liver cirrhosis on regions of interest (ROIs) images from B-mode ultrasound images, we have proposed to use the higher order local autocorrelation (HLAC) features. In a previous study, we tried to classify liver cirrhosis by using a Gabor filter based approach. However, the classification performance of the Gabor feature was poor from our preliminary experimental results. In order accurately to classify liver cirrhosis, we examined to use the HLAC features for liver cirrhosis classification. The experimental results show the effectiveness of HLAC features compared with the Gabor feature. Furthermore, by using a binary image made by an adaptive thresholding method, the classification performance of HLAC features has improved.

Preparation of TPP-crosslinked chitosan microparticles by spray drying for the controlled delivery of progesterone intended for estrus synchronization in cattle.

PubMed

Helbling, Ignacio M; Busatto, Carlos A; Fioramonti, Silvana A; Pesoa, Juan I; Santiago, Liliana; Estenoz, Diana A; Luna, Julio A

2018-02-20

Planned reproduction in cattle involves regulation of estrous cycle and the use of artificial insemination. Cycle control includes the administration of exogenous progesterone during 5-8 days in a controlled manner allowing females to synchronize their ovulation. Several progesterone delivery systems are commercially available but they have several drawbacks. The aim of the present contribution was to evaluate chitosan microparticles entrapping progesterone as an alternative system. Microparticles were prepared by spray drying. The effect of formulation parameters and experimental conditions on particle features and delivery was studied. A mathematical model to predict progesterone plasma concentration in animals was developed and validated with experimental data. Microparticle size was not affected by formulation parameters but sphericity enhances as Tween 80 content increases and it impairs as TPP content rises. Z potential decreases as phosphate content rises. Particles remain stable in acidic solution but the addition of surfactant is required to stabilize dispersions in neutral medium. Encapsulation efficiencies was 69-75%. In vitro delivery studies showed burst and diffusion-controlled phases, being progesterone released faster at low pH. In addition, delivery extend in cows was affected mainly by particle size and hormone initial content, while the amount injected altered plasma concentration. Theoretical predictions with excellent accuracy were obtained. The mathematical model developed can help to find proper particle features to reach specific delivery rates in the animals. This not only save time, money and effort but also minimized experimentation with animals which is desired from an ethical point of view.

A magneto-rheological fluid mount featuring squeeze mode: analysis and testing

NASA Astrophysics Data System (ADS)

Chen, Peng; Bai, Xian-Xu; Qian, Li-Jun; Choi, Seung-Bok

2016-05-01

This paper presents a mathematical model for a new semi-active vehicle engine mount utilizing magneto-rheological (MR) fluids in squeeze mode (MR mount in short) and validates the model by comparing analysis results with experimental tests. The proposed MR mount is mainly comprised of a frame for installation, a main rubber, a squeeze plate and a bobbin for coil winding. When the magnetic fields on, MR effect occurs in the upper gap between the squeeze plate and the bobbin, and the dynamic stiffness can be controlled by tuning the applied currents. Employing Bingham model and flow properties between parallel plates of MR fluids, a mathematical model for the squeeze type of MR mount is formulated with consideration of the fluid inertia, MR effect and hysteresis property. The field-dependent dynamic stiffness of the MR mount is then analyzed using the established mathematical model. Subsequently, in order to validate the mathematical model, an appropriate size of MR mount is fabricated and tested. The field-dependent force and dynamic stiffness of the proposed MR mount are evaluated and compared between the model and experimental tests in both time and frequency domains to verify the model efficiency. In addition, it is shown that both the damping property and the stiffness property of the proposed MR mount can be simultaneously controlled.

[The morphometric characteristics of the main structural components of renal nephrons in the white rats with experimentally induced acute and chronic alcohol intoxication].

PubMed

Shcherbakova, V M

2016-01-01

The objective of the present work was to study the morphometric characteristics of the main structural components of renal nephrons in the white rats with the experimentally induced acute and chronic alcohol intoxication. We undertook the morphometric examination of the structural elements of rat kidneys with the subsequent statistical analysis of the data obtained. The results of the study give evidence of the toxic action of ethanol on all structural components of the nephron in the case of both acute and chronic alcohol intoxication. The study revealed some specific features of the development of pathological process in the renal tissue structures at different stages of alcohol intoxication. The most pronounced morphological changes were observed in the renal proximal tubules and the least pronounced ones in the structure of the renal glomeruli. The earliest morphological changes become apparent in distal convoluted tubules of the nephron; in the case of persistent alcoholemia, they first develop in the renal corpuscles and thereafter in the distal proximal tubules. The maximum changes occur in the case of acute alcohol intoxication and between 2 weeks and 2 months of chronic intoxication; they become less conspicuous during a later period.

Registration algorithm of point clouds based on multiscale normal features

NASA Astrophysics Data System (ADS)

Lu, Jun; Peng, Zhongtao; Su, Hang; Xia, GuiHua

2015-01-01

The point cloud registration technology for obtaining a three-dimensional digital model is widely applied in many areas. To improve the accuracy and speed of point cloud registration, a registration method based on multiscale normal vectors is proposed. The proposed registration method mainly includes three parts: the selection of key points, the calculation of feature descriptors, and the determining and optimization of correspondences. First, key points are selected from the point cloud based on the changes of magnitude of multiscale curvatures obtained by using principal components analysis. Then the feature descriptor of each key point is proposed, which consists of 21 elements based on multiscale normal vectors and curvatures. The correspondences in a pair of two point clouds are determined according to the descriptor's similarity of key points in the source point cloud and target point cloud. Correspondences are optimized by using a random sampling consistency algorithm and clustering technology. Finally, singular value decomposition is applied to optimized correspondences so that the rigid transformation matrix between two point clouds is obtained. Experimental results show that the proposed point cloud registration algorithm has a faster calculation speed, higher registration accuracy, and better antinoise performance.

Predicting clinical outcome of neuroblastoma patients using an integrative network-based approach.

PubMed

Tranchevent, Léon-Charles; Nazarov, Petr V; Kaoma, Tony; Schmartz, Georges P; Muller, Arnaud; Kim, Sang-Yoon; Rajapakse, Jagath C; Azuaje, Francisco

2018-06-07

One of the main current challenges in computational biology is to make sense of the huge amounts of multidimensional experimental data that are being produced. For instance, large cohorts of patients are often screened using different high-throughput technologies, effectively producing multiple patient-specific molecular profiles for hundreds or thousands of patients. We propose and implement a network-based method that integrates such patient omics data into Patient Similarity Networks. Topological features derived from these networks were then used to predict relevant clinical features. As part of the 2017 CAMDA challenge, we have successfully applied this strategy to a neuroblastoma dataset, consisting of genomic and transcriptomic data. In particular, we observe that models built on our network-based approach perform at least as well as state of the art models. We furthermore explore the effectiveness of various topological features and observe, for instance, that redundant centrality metrics can be combined to build more powerful models. We demonstrate that the networks inferred from omics data contain clinically relevant information and that patient clinical outcomes can be predicted using only network topological data. This article was reviewed by Yang-Yu Liu, Tomislav Smuc and Isabel Nepomuceno.

Multi-focus image fusion using a guided-filter-based difference image.

PubMed

Yan, Xiang; Qin, Hanlin; Li, Jia; Zhou, Huixin; Yang, Tingwu

2016-03-20

The aim of multi-focus image fusion technology is to integrate different partially focused images into one all-focused image. To realize this goal, a new multi-focus image fusion method based on a guided filter is proposed and an efficient salient feature extraction method is presented in this paper. Furthermore, feature extraction is primarily the main objective of the present work. Based on salient feature extraction, the guided filter is first used to acquire the smoothing image containing the most sharpness regions. To obtain the initial fusion map, we compose a mixed focus measure by combining the variance of image intensities and the energy of the image gradient together. Then, the initial fusion map is further processed by a morphological filter to obtain a good reprocessed fusion map. Lastly, the final fusion map is determined via the reprocessed fusion map and is optimized by a guided filter. Experimental results demonstrate that the proposed method does markedly improve the fusion performance compared to previous fusion methods and can be competitive with or even outperform state-of-the-art fusion methods in terms of both subjective visual effects and objective quality metrics.

Wavelet-based study of valence-arousal model of emotions on EEG signals with LabVIEW.

PubMed

Guzel Aydin, Seda; Kaya, Turgay; Guler, Hasan

2016-06-01

This paper illustrates the wavelet-based feature extraction for emotion assessment using electroencephalogram (EEG) signal through graphical coding design. Two-dimensional (valence-arousal) emotion model was studied. Different emotions (happy, joy, melancholy, and disgust) were studied for assessment. These emotions were stimulated by video clips. EEG signals obtained from four subjects were decomposed into five frequency bands (gamma, beta, alpha, theta, and delta) using "db5" wavelet function. Relative features were calculated to obtain further information. Impact of the emotions according to valence value was observed to be optimal on power spectral density of gamma band. The main objective of this work is not only to investigate the influence of the emotions on different frequency bands but also to overcome the difficulties in the text-based program. This work offers an alternative approach for emotion evaluation through EEG processing. There are a number of methods for emotion recognition such as wavelet transform-based, Fourier transform-based, and Hilbert-Huang transform-based methods. However, the majority of these methods have been applied with the text-based programming languages. In this study, we proposed and implemented an experimental feature extraction with graphics-based language, which provides great convenience in bioelectrical signal processing.

Systematic review of the information and communication technology features of web- and mobile-based psychoeducational interventions for depression.

PubMed

Zhao, Danyang; Lustria, Mia Liza A; Hendrickse, Joshua

2017-06-01

To examine the information and communication technology (ICT) features of psychoeducational interventions for depression delivered via the Internet or via mobile technology. Web- and mobile-based psychoeducational intervention studies published from 2004 to 2014 were selected and reviewed by two independent coders. A total of 55 unique studies satisfied the selection criteria. The review revealed a diverse range of ICTs used to support the psychoeducational programs. Most interventions used websites as their main mode of delivery and reported greater use of communication tools compared to effective approaches like tailoring or interactive technologies games, videos, and self-monitoring tools. Many of the studies relied on medium levels of clinician involvement and only a few were entirely self-guided. Programs that reported higher levels of clinician involvement also reported using more communication tools, and reported greater compliance to treatment. Future experimental studies may help unpack the effects of technology features and reveal new ways to automate aspects of clinician input. There is a need to further examine ways ICTs can be optimized to reduce the burden on clinicians whilst enhancing the delivery of proven effective therapeutic approaches. Copyright © 2017 Elsevier B.V. All rights reserved.

Using Saliency-Weighted Disparity Statistics for Objective Visual Comfort Assessment of Stereoscopic Images

NASA Astrophysics Data System (ADS)

Zhang, Wenlan; Luo, Ting; Jiang, Gangyi; Jiang, Qiuping; Ying, Hongwei; Lu, Jing

2016-06-01

Visual comfort assessment (VCA) for stereoscopic images is a particularly significant yet challenging task in 3D quality of experience research field. Although the subjective assessment given by human observers is known as the most reliable way to evaluate the experienced visual discomfort, it is time-consuming and non-systematic. Therefore, it is of great importance to develop objective VCA approaches that can faithfully predict the degree of visual discomfort as human beings do. In this paper, a novel two-stage objective VCA framework is proposed. The main contribution of this study is that the important visual attention mechanism of human visual system is incorporated for visual comfort-aware feature extraction. Specifically, in the first stage, we first construct an adaptive 3D visual saliency detection model to derive saliency map of a stereoscopic image, and then a set of saliency-weighted disparity statistics are computed and combined to form a single feature vector to represent a stereoscopic image in terms of visual comfort. In the second stage, a high dimensional feature vector is fused into a single visual comfort score by performing random forest algorithm. Experimental results on two benchmark databases confirm the superior performance of the proposed approach.

Acoustic Features Influence Musical Choices Across Multiple Genres

PubMed Central

Barone, Michael D.; Bansal, Jotthi; Woolhouse, Matthew H.

2017-01-01

Based on a large behavioral dataset of music downloads, two analyses investigate whether the acoustic features of listeners' preferred musical genres influence their choice of tracks within non-preferred, secondary musical styles. Analysis 1 identifies feature distributions for pairs of genre-defined subgroups that are distinct. Using correlation analysis, these distributions are used to test the degree of similarity between subgroups' main genres and the other music within their download collections. Analysis 2 explores the issue of main-to-secondary genre influence through the production of 10 feature-influence matrices, one per acoustic feature, in which cell values indicate the percentage change in features for genres and subgroups compared to overall population averages. In total, 10 acoustic features and 10 genre-defined subgroups are explored within the two analyses. Results strongly indicate that the acoustic features of people's main genres influence the tracks they download within non-preferred, secondary musical styles. The nature of this influence and its possible actuating mechanisms are discussed with respect to research on musical preference, personality, and statistical learning. PMID:28725200

Robust infrared targets tracking with covariance matrix representation

NASA Astrophysics Data System (ADS)

Cheng, Jian

2009-07-01

Robust infrared target tracking is an important and challenging research topic in many military and security applications, such as infrared imaging guidance, infrared reconnaissance, scene surveillance, etc. To effectively tackle the nonlinear and non-Gaussian state estimation problems, particle filtering is introduced to construct the theory framework of infrared target tracking. Under this framework, the observation probabilistic model is one of main factors for infrared targets tracking performance. In order to improve the tracking performance, covariance matrices are introduced to represent infrared targets with the multi-features. The observation probabilistic model can be constructed by computing the distance between the reference target's and the target samples' covariance matrix. Because the covariance matrix provides a natural tool for integrating multiple features, and is scale and illumination independent, target representation with covariance matrices can hold strong discriminating ability and robustness. Two experimental results demonstrate the proposed method is effective and robust for different infrared target tracking, such as the sensor ego-motion scene, and the sea-clutter scene.

Uncertain decision tree inductive inference

NASA Astrophysics Data System (ADS)

Zarban, L.; Jafari, S.; Fakhrahmad, S. M.

2011-10-01

Induction is the process of reasoning in which general rules are formulated based on limited observations of recurring phenomenal patterns. Decision tree learning is one of the most widely used and practical inductive methods, which represents the results in a tree scheme. Various decision tree algorithms have already been proposed such as CLS, ID3, Assistant C4.5, REPTree and Random Tree. These algorithms suffer from some major shortcomings. In this article, after discussing the main limitations of the existing methods, we introduce a new decision tree induction algorithm, which overcomes all the problems existing in its counterparts. The new method uses bit strings and maintains important information on them. This use of bit strings and logical operation on them causes high speed during the induction process. Therefore, it has several important features: it deals with inconsistencies in data, avoids overfitting and handles uncertainty. We also illustrate more advantages and the new features of the proposed method. The experimental results show the effectiveness of the method in comparison with other methods existing in the literature.

Age group classification and gender detection based on forced expiratory spirometry.

PubMed

Cosgun, Sema; Ozbek, I Yucel

2015-08-01

This paper investigates the utility of forced expiratory spirometry (FES) test with efficient machine learning algorithms for the purpose of gender detection and age group classification. The proposed method has three main stages: feature extraction, training of the models and detection. In the first stage, some features are extracted from volume-time curve and expiratory flow-volume loop obtained from FES test. In the second stage, the probabilistic models for each gender and age group are constructed by training Gaussian mixture models (GMMs) and Support vector machine (SVM) algorithm. In the final stage, the gender (or age group) of test subject is estimated by using the trained GMM (or SVM) model. Experiments have been evaluated on a large database from 4571 subjects. The experimental results show that average correct classification rate performance of both GMM and SVM methods based on the FES test is more than 99.3 % and 96.8 % for gender and age group classification, respectively.

Fusion of LBP and SWLD using spatio-spectral information for hyperspectral face recognition

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Jiang, Peng; Zhang, Shuai; Xiong, Jinquan

2018-01-01

Hyperspectral imaging, recording intrinsic spectral information of the skin cross different spectral bands, become an important issue for robust face recognition. However, the main challenges for hyperspectral face recognition are high data dimensionality, low signal to noise ratio and inter band misalignment. In this paper, hyperspectral face recognition based on LBP (Local binary pattern) and SWLD (Simplified Weber local descriptor) is proposed to extract discriminative local features from spatio-spectral fusion information. Firstly, the spatio-spectral fusion strategy based on statistical information is used to attain discriminative features of hyperspectral face images. Secondly, LBP is applied to extract the orientation of the fusion face edges. Thirdly, SWLD is proposed to encode the intensity information in hyperspectral images. Finally, we adopt a symmetric Kullback-Leibler distance to compute the encoded face images. The hyperspectral face recognition is tested on Hong Kong Polytechnic University Hyperspectral Face database (PolyUHSFD). Experimental results show that the proposed method has higher recognition rate (92.8%) than the state of the art hyperspectral face recognition algorithms.

Local coding based matching kernel method for image classification.

PubMed

Song, Yan; McLoughlin, Ian Vince; Dai, Li-Rong

2014-01-01

This paper mainly focuses on how to effectively and efficiently measure visual similarity for local feature based representation. Among existing methods, metrics based on Bag of Visual Word (BoV) techniques are efficient and conceptually simple, at the expense of effectiveness. By contrast, kernel based metrics are more effective, but at the cost of greater computational complexity and increased storage requirements. We show that a unified visual matching framework can be developed to encompass both BoV and kernel based metrics, in which local kernel plays an important role between feature pairs or between features and their reconstruction. Generally, local kernels are defined using Euclidean distance or its derivatives, based either explicitly or implicitly on an assumption of Gaussian noise. However, local features such as SIFT and HoG often follow a heavy-tailed distribution which tends to undermine the motivation behind Euclidean metrics. Motivated by recent advances in feature coding techniques, a novel efficient local coding based matching kernel (LCMK) method is proposed. This exploits the manifold structures in Hilbert space derived from local kernels. The proposed method combines advantages of both BoV and kernel based metrics, and achieves a linear computational complexity. This enables efficient and scalable visual matching to be performed on large scale image sets. To evaluate the effectiveness of the proposed LCMK method, we conduct extensive experiments with widely used benchmark datasets, including 15-Scenes, Caltech101/256, PASCAL VOC 2007 and 2011 datasets. Experimental results confirm the effectiveness of the relatively efficient LCMK method.

Gyrokinetic modeling of impurity peaking in JET H-mode plasmas

NASA Astrophysics Data System (ADS)

Manas, P.; Camenen, Y.; Benkadda, S.; Weisen, H.; Angioni, C.; Casson, F. J.; Giroud, C.; Gelfusa, M.; Maslov, M.

2017-06-01

Quantitative comparisons are presented between gyrokinetic simulations and experimental values of the carbon impurity peaking factor in a database of JET H-modes during the carbon wall era. These plasmas feature strong NBI heating and hence high values of toroidal rotation and corresponding gradient. Furthermore, the carbon profiles present particularly interesting shapes for fusion devices, i.e., hollow in the core and peaked near the edge. Dependencies of the experimental carbon peaking factor ( R / L nC ) on plasma parameters are investigated via multilinear regressions. A marked correlation between R / L nC and the normalised toroidal rotation gradient is observed in the core, which suggests an important role of the rotation in establishing hollow carbon profiles. The carbon peaking factor is then computed with the gyrokinetic code GKW, using a quasi-linear approach, supported by a few non-linear simulations. The comparison of the quasi-linear predictions to the experimental values at mid-radius reveals two main regimes. At low normalised collisionality, ν * , and T e / T i < 1 , the gyrokinetic simulations quantitatively recover experimental carbon density profiles, provided that rotodiffusion is taken into account. In contrast, at higher ν * and T e / T i > 1 , the very hollow experimental carbon density profiles are never predicted by the simulations and the carbon density peaking is systematically over estimated. This points to a possible missing ingredient in this regime.

Optimal subsystem approach to multi-qubit quantum state discrimination and experimental investigation

NASA Astrophysics Data System (ADS)

Xue, ShiChuan; Wu, JunJie; Xu, Ping; Yang, XueJun

2018-02-01

Quantum computing is a significant computing capability which is superior to classical computing because of its superposition feature. Distinguishing several quantum states from quantum algorithm outputs is often a vital computational task. In most cases, the quantum states tend to be non-orthogonal due to superposition; quantum mechanics has proved that perfect outcomes could not be achieved by measurements, forcing repetitive measurement. Hence, it is important to determine the optimum measuring method which requires fewer repetitions and a lower error rate. However, extending current measurement approaches mainly aiming at quantum cryptography to multi-qubit situations for quantum computing confronts challenges, such as conducting global operations which has considerable costs in the experimental realm. Therefore, in this study, we have proposed an optimum subsystem method to avoid these difficulties. We have provided an analysis of the comparison between the reduced subsystem method and the global minimum error method for two-qubit problems; the conclusions have been verified experimentally. The results showed that the subsystem method could effectively discriminate non-orthogonal two-qubit states, such as separable states, entangled pure states, and mixed states; the cost of the experimental process had been significantly reduced, in most circumstances, with acceptable error rate. We believe the optimal subsystem method is the most valuable and promising approach for multi-qubit quantum computing applications.

NiTi Alloy Negator Springs for Long-Stroke Constant-Force Shape Memory Actuators: Modeling, Simulation and Testing

NASA Astrophysics Data System (ADS)

Spaggiari, Andrea; Dragoni, Eugenio; Tuissi, Ausonio

2014-07-01

This work aims at the experimental characterization and modeling validation of shape memory alloy (SMA) Negator springs. According to the classic engineering books on springs, a Negator spring is a spiral spring made of strip of metal wound on the flat with an inherent curvature such that, in repose, each coil wraps tightly on its inner neighbor. The main feature of a Negator springs is the nearly constant force displacement behavior in the unwinding of the strip. Moreover the stroke is very long, theoretically infinite, as it depends only on the length of the initial strip. A Negator spring made in SMA is built and experimentally tested to demonstrate the feasibility of this actuator. The shape memory Negator spring behavior can be modeled with an analytical procedure, which is in good agreement with the experimental test and can be used for design purposes. In both cases, the material is modeled as elastic in austenitic range, while an exponential continuum law is used to describe the martensitic behavior. The experimental results confirms the applicability of this kind of geometry to the shape memory alloy actuators, and the analytical model is confirmed to be a powerful design tool to dimension and predict the spring behavior both in martensitic and austenitic range.

Experimental Characterization of Cryogenic Helium Pulsating Heat Pipes

NASA Astrophysics Data System (ADS)

Fonseca Flores, Luis Diego

This study was inspired to investigate an alternative cooling system using a helium-based pulsating heat pipes (PHP), for low temperature superconducting magnets in MRI systems. In addition, the same approach can be used for exploring other low temperature applications such as cooling space instrumentation. The advantages of PHP for transferring heat and smoothing temperature profiles in various room temperature applications have been explored for the past 20 years. An experimental apparatus has been designed, fabricated and operated and is primarily composed of an evaporator and a condenser; in which both are thermally connected by a closed loop capillary tubing. The main goal is to measure the heat transfer properties of this device using helium as the working fluid. The evaporator end of the PHP is comprised of a copper winding in which heat loads up to 10 watts are generated, while the condenser is isothermal and can reach 4.2 K at 1 W via a two stage Sumitomo RDK408A2 GM cryocooler. Various experimental design features are highlighted. Additionally, the thermal performance for the presented design remained unchanged when increasing the adiabatic length from 300 mm to 1000 mm. Finally a spring mass damper model has been developed and proven to predict well the experimental data, such models should be used as tool to design and manufacturer PHP prototypes.

Numerical and experimental study of expiratory flow in the case of major upper airway obstructions with fluid structure interaction

NASA Astrophysics Data System (ADS)

Chouly, F.; van Hirtum, A.; Lagrée, P.-Y.; Pelorson, X.; Payan, Y.

2008-02-01

This study deals with the numerical prediction and experimental description of the flow-induced deformation in a rapidly convergent divergent geometry which stands for a simplified tongue, in interaction with an expiratory airflow. An original in vitro experimental model is proposed, which allows measurement of the deformation of the artificial tongue, in condition of major initial airway obstruction. The experimental model accounts for asymmetries in geometry and tissue properties which are two major physiological upper airway characteristics. The numerical method for prediction of the fluid structure interaction is described. The theory of linear elasticity in small deformations has been chosen to compute the mechanical behaviour of the tongue. The main features of the flow are taken into account using a boundary layer theory. The overall numerical method entails finite element solving of the solid problem and finite differences solving of the fluid problem. First, the numerical method predicts the deformation of the tongue with an overall error of the order of 20%, which can be seen as a preliminary successful validation of the theory and simulations. Moreover, expiratory flow limitation is predicted in this configuration. As a result, both the physical and numerical models could be useful to understand this phenomenon reported in heavy snorers and apneic patients during sleep.

The QSPR-THESAURUS: the online platform of the CADASTER project.

PubMed

Brandmaier, Stefan; Peijnenburg, Willie; Durjava, Mojca K; Kolar, Boris; Gramatica, Paola; Papa, Ester; Bhhatarai, Barun; Kovarich, Simona; Cassani, Stefano; Roy, Partha Pratim; Rahmberg, Magnus; Öberg, Tomas; Jeliazkova, Nina; Golsteijn, Laura; Comber, Mike; Charochkina, Larisa; Novotarskyi, Sergii; Sushko, Iurii; Abdelaziz, Ahmed; D'Onofrio, Elisa; Kunwar, Prakash; Ruggiu, Fiorella; Tetko, Igor V

2014-03-01

The aim of the CADASTER project (CAse Studies on the Development and Application of in Silico Techniques for Environmental Hazard and Risk Assessment) was to exemplify REACH-related hazard assessments for four classes of chemical compound, namely, polybrominated diphenylethers, per and polyfluorinated compounds, (benzo)triazoles, and musks and fragrances. The QSPR-THESAURUS website (http: / /qspr-thesaurus.eu) was established as the project's online platform to upload, store, apply, and also create, models within the project. We overview the main features of the website, such as model upload, experimental design and hazard assessment to support risk assessment, and integration with other web tools, all of which are essential parts of the QSPR-THESAURUS. 2014 FRAME.

A Survey of Keystroke Dynamics Biometrics

PubMed Central

Yue, Shigang

2013-01-01

Research on keystroke dynamics biometrics has been increasing, especially in the last decade. The main motivation behind this effort is due to the fact that keystroke dynamics biometrics is economical and can be easily integrated into the existing computer security systems with minimal alteration and user intervention. Numerous studies have been conducted in terms of data acquisition devices, feature representations, classification methods, experimental protocols, and evaluations. However, an up-to-date extensive survey and evaluation is not yet available. The objective of this paper is to provide an insightful survey and comparison on keystroke dynamics biometrics research performed throughout the last three decades, as well as offering suggestions and possible future research directions. PMID:24298216

Computational prediction of hemolysis in a centrifugal ventricular assist device.

PubMed

Pinotti, M; Rosa, E S

1995-03-01

This paper describes the use of computational fluid dynamics (CFD) to predict numerically the hemolysis in centrifugal pumps. A numerical hydrodynamical model, based on the full Navier-Stokes equation, was used to obtain the flow in a vaneless centrifugal pump (of corotating disks type). After proper postprocessing, critical zones in the channel were identified by means of two-dimensional color-coded maps of %Hb release. Simulation of different conditions revealed that flow behavior at the entrance region of the channel is the main cause of blood trauma in such devices. A useful feature resulting from the CFD simulation is the visualization of critical flow zones that are impossible to determine experimentally with in vitro hemolysis tests.

Tight-binding model of the photosystem II reaction center: application to two-dimensional electronic spectroscopy

NASA Astrophysics Data System (ADS)

Gelzinis, Andrius; Valkunas, Leonas; Fuller, Franklin D.; Ogilvie, Jennifer P.; Mukamel, Shaul; Abramavicius, Darius

2013-07-01

We propose an optimized tight-binding electron-hole model of the photosystem II (PSII) reaction center (RC). Our model incorporates two charge separation pathways and spatial correlations of both static disorder and fast fluctuations of energy levels. It captures the main experimental features observed in time-resolved two-dimensional (2D) optical spectra at 77 K: peak pattern, lineshapes and time traces. Analysis of 2D spectra kinetics reveals that specific regions of the 2D spectra of the PSII RC are sensitive to the charge transfer states. We find that the energy disorder of two peripheral chlorophylls is four times larger than the other RC pigments.

Modeling no-jam traffic in ant trails: a pheromone-controlled approach

NASA Astrophysics Data System (ADS)

Guo, Ning; Hu, Mao-Bin; Jiang, Rui; Ding, Jianxun; Ling, Xiang

2018-05-01

The experiment in John et al (2009 Phys. Rev. Lett. 102 108001) shows that when ants move in a single-file trail, no jam emerges even at very high densities. We propose a self-propelled model of ant traffic to reproduce the fundamental diagram without a jammed branch. In this model, ants can adjust their desired velocities actively by perceiving pheromone concentration near the front of the trail. Moreover, ants will bear the repulsive force when they have physical contact with neighbors. The velocity in the simulation decreases slightly with increasing density, which captures the main feature observed in the experiment. Distributions of velocity and distance headway basically also conform to the experimental ones.

Evidence for a shear horizontal resonance in supported thin films

NASA Astrophysics Data System (ADS)

Zhang, X.; Manghnani, M. H.; Every, A. G.

2000-07-01

We report evidence for a different type of acoustic film excitation, identified as a shear horizontal resonance, in amorphous silicon oxynitride films on GaAs substrate. Observation of this excitation has been carried out using surface Brillouin scattering of light. A Green's function formalism is used for analyzing the experimental spectra, and successfully simulates the spectral features associated with this mode. The attributes of this mode are described; these include its phase velocity which is nearly equal to that of a bulk shear wave propagating parallel to the surface and is almost independent of film thickness and scattering angle, its localization mainly in the film, and its polarization in the shear horizontal direction.

Fidelity for kicked atoms with gravity near a quantum resonance.

PubMed

Dubertrand, Rémy; Guarneri, Italo; Wimberger, Sandro

2012-03-01

Kicked atoms under a constant Stark or gravity field are investigated for experimental setups with cold and ultracold atoms. The parametric stability of the quantum dynamics is studied using the fidelity. In the case of a quantum resonance, it is shown that the behavior of the fidelity depends on arithmetic properties of the gravity parameter. Close to a quantum resonance, the long-time asymptotics of the fidelity is studied by means of a pseudoclassical approximation introduced by Fishman et al. [J. Stat. Phys. 110, 911 (2003)]. The long-time decay of fidelity arises from the tunneling out of pseudoclassical stable islands, and a simple ansatz is proposed which satisfactorily reproduces the main features observed in numerical simulations.

Effects of charge symmetry on heavy ion reaction mechanisms

NASA Astrophysics Data System (ADS)

Colonna, M.; di Toro, M.; Fabbri, G.; Maccarone, S.

1998-03-01

We suggest several possibilities to study the properties of the symmetry term in the nuclear equation of state from radioactive beam experiments. Collision simulations with a stochastic transport approach, where asymmetry effects are suitably introduced, are presented. The dynamical response of an interacting highly asymmetric nuclear matter can be studied, taking advantage of the neutron skin structure. The main reaction mechanisms, from fusion to deep inelastic and fragmentation, appear quite sensitive to the form of the symmetry term of the effective force used, opening some new appealing experimental perspectives. Finally new features of fragment production are presented, due to the onset of chemical plus mechanical instabilities in dilute asymmetric nuclear matter.

Broken SU(3) x SU(3) x SU(3) x SU(3) Symmetry

DOE R&D Accomplishments Database

Freund, P. G. O.; Nambu, Y.

1964-10-01

We argue that the "Eight-fold Way" version of the SU(3) symmetry should be extended to a product of up to four separate and badly broken SU(3) groups, including the gamma{sub 5} type SU(3) symmetry. A hierarchy of subgroups (or subalgebras) are considered within this framework, and two candidates are found to be interesting in view of experimental evidence. Main features of the theory are: 1) the baryons belong to a nonet; 2) there is an octet of axial vector gauge mesons in addition to one or two octets of vector mesons; 3) pseudoscalar and scalar mesons exist as "incomplete" multiplets arising from spontaneous breakdown of symmetry.

Effect of bromine deficiency on the lattice dynamics and dielectric properties of alpha-phase diisopropylammonium bromide molecular crystals

NASA Astrophysics Data System (ADS)

Alsaad, Ahmad; Marin, Chris M.; Alaqtash, Nabil; Chao, Hsien-Wen; Chang, Tsun-Hsu; Cheung, Chin Li; Ahmad, A.; Qattan, I. A.; Sabirianov, Renat F.

2018-02-01

Diisopropylammonium bromide (DIPAB) molecular ferroelectric crystals were synthesized and examined to exhibit a large electric polarization (∼23μC/cm2), a large dielectric constant in the α-phase. Although the PXRD pattern indicates that the α-DIPAB sample has an overall excellent crystallinity, our analysis of its FT-IR and Raman vibrational spectra suggests the presence of disorder in the synthesized crystals as indicated by the presence of broad features in the Raman spectrum. Using vdW+DF2 calculations, we identified the majority of vibrational modes in the experimental spectra and analyzed the ones due to Br-disorder. We found that the bromine (Br) deficiency strongly affects the electric properties of α-DIPAB. Particularly, the experimentally measured dielectric constant of α-DIPAB is large (∼20), whereas the DFT-based calculations of the ideal DIPAB give much smaller values (∼2-3). We find that Br-deficiency is responsible for large dielectric constant of the DIPAB crystal with calculated value of ∼15-20. Furthermore, we showed that the van der Waals forces have a slight effect on the structural parameters, only causing a small shift in the vibrational frequencies. The main vibrational features of the DIPAB crystal in the Raman spectrum were shown to be driven by covalent bonding in the DIPA molecules and hydrogen bonds between the molecules with Br.

DFT/TD-DFT study of solvent effect as well the substituents influence on the different features of TPP derivatives for PDT application

NASA Astrophysics Data System (ADS)

Dulski, Mateusz; Kempa, Marta; Kozub, Patrycja; Wójcik, Justyna; Rojkiewicz, Marcin; Kuś, Piotr; Szurko, Agnieszka; Ratuszna, Alicja; Wrzalik, Roman

2013-03-01

Spectral characteristics study of meso-tetraphenylporphyrin derivatives (TPP1 and TPP2) used as photosensitizers for utilization in photodynamic therapy (PDT) has been performed by density functional theory (DFT) and time dependent DFT (TD-DFT) calculations at B3LYP/6-31G(d) level of theory using PCM solvation model. The geometrical parameters of porphyrins have been studied for ground and excited-state geometry to deduce the influence of various substituents as well as solvent effect on the deformation of porphyrin ring. Two theoretical approaches - linear response (LR) and external iteration (EI) - have been performed to replicate absorption and fluorescence emission spectra. Experimental and theoretical investigations have shown that EI method reproduces the absorption energies very well for both singlet-singlet and triplet-triplet transitions, whereas the LR approach is more coherent with experimental fluorescence emission spectra. Spectral features and HOMO-LUMO band gap analysis have shown that TPP1 can be more useful in PDT. Calculations have revealed that two the highest occupied and two the lowest unoccupied molecular orbitals are responsible for the Q-band absorption and are located mainly on the porphyrin ring. In order to verify the substituent effect on the activity of tested compounds in their ground and excited states, the molecular electrostatic potential surfaces have been analyzed.

Stress Dependence of Microstructures in Experimentally Deformed Calcite

NASA Astrophysics Data System (ADS)

Platt, J. P.; De Bresser, J. H. P.

2017-12-01

Measurements of dynamically recrystallized grain size (Dr), subgrain size (Sg), minimum bulge size (Blg), and the maximum scale length for surface-energy driven grain-boundary migration (γGBM) in experimentally deformed Cararra marble help define the dependence of these microstructural features on stress and temperature. Measurements were made optically on ultra-thin sections in order to allow these features to be defined during measurement on the basis of microstructural setting and geometry. Taken together with previously published data Dr defines a paleopiezometer with a stress exponent of -1.09. There is no discernible temperature dependence over the 500°C temperature range of the experiments. Recrystallization occured mainly by bulging and subgrain rotation, and the two processes operated together, so that it is not possible to separate grains nucleated by the two mechanisms. Sg and Dr measured in the same samples are closely similar in size, suggesting that new grains do not grow significantly after nucleation, and that subgrain size is likely to be the primary control on recrystallized grain size. Blg and γGBM measured on each sample define a relationship to stress with an exponent of approximately -1.6, which helps define the boundary in stress - grain-size space between a region of dominant strain-energy-driven grain-boundary migration at high stress, from a region of dominant surface-energy-driven grain-boundary migration at low stress.

Hydrogen bond dynamics of superheated water and methanol by ultrafast IR-pump and EUV-photoelectron probe spectroscopy.

PubMed

Vöhringer-Martinez, E; Link, O; Lugovoy, E; Siefermann, K R; Wiederschein, F; Grubmüller, H; Abel, B

2014-09-28

Supercritical water and methanol have recently drawn much attention in the field of green chemistry. It is crucial to an understanding of supercritical solvents to know their dynamics and to what extent hydrogen (H) bonds persist in these fluids. Here, we show that with femtosecond infrared (IR) laser pulses water and methanol can be heated to temperatures near and above their critical temperature Tc and their molecular dynamics can be studied via ultrafast photoelectron spectroscopy at liquid jet interfaces with high harmonics radiation. As opposed to previous studies, the main focus here is the comparison between the hydrogen bonded systems of methanol and water and their interpretation by theory. Superheated water initially forms a dense hot phase with spectral features resembling those of monomers in gas phase water. On longer timescales, this phase was found to build hot aggregates, whose size increases as a function of time. In contrast, methanol heated to temperatures near Tc initially forms a broad distribution of aggregate sizes and some gas. These experimental features are also found and analyzed in extended molecular dynamics simulations. Additionally, the simulations enabled us to relate the origin of the different behavior of these two hydrogen-bonded liquids to the nature of the intermolecular potentials. The combined experimental and theoretical approach delivers new insights into both superheated phases and may contribute to understand their different chemical reactivities.

Object-based selection from spatially-invariant representations: evidence from a feature-report task.

PubMed

Matsukura, Michi; Vecera, Shaun P

2011-02-01

Attention selects objects as well as locations. When attention selects an object's features, observers identify two features from a single object more accurately than two features from two different objects (object-based effect of attention; e.g., Duncan, Journal of Experimental Psychology: General, 113, 501-517, 1984). Several studies have demonstrated that object-based attention can operate at a late visual processing stage that is independent of objects' spatial information (Awh, Dhaliwal, Christensen, & Matsukura, Psychological Science, 12, 329-334, 2001; Matsukura & Vecera, Psychonomic Bulletin & Review, 16, 529-536, 2009; Vecera, Journal of Experimental Psychology: General, 126, 14-18, 1997; Vecera & Farah, Journal of Experimental Psychology: General, 123, 146-160, 1994). In the present study, we asked two questions regarding this late object-based selection mechanism. In Part I, we investigated how observers' foreknowledge of to-be-reported features allows attention to select objects, as opposed to individual features. Using a feature-report task, a significant object-based effect was observed when to-be-reported features were known in advance but not when this advance knowledge was absent. In Part II, we examined what drives attention to select objects rather than individual features in the absence of observers' foreknowledge of to-be-reported features. Results suggested that, when there was no opportunity for observers to direct their attention to objects that possess to-be-reported features at the time of stimulus presentation, these stimuli must retain strong perceptual cues to establish themselves as separate objects.

Experimental investigation of fluvial dike breaching due to flow overtopping

NASA Astrophysics Data System (ADS)

El Kadi Abderrezzak, K.; Rifai, I.; Erpicum, S.; Archambeau, P.; Violeau, D.; Pirotton, M.; Dewals, B.

2017-12-01

The failure of fluvial dikes (levees) often leads to devastating floods that cause loss of life and damages to public infrastructure. Overtopping flows have been recognized as one of the most frequent cause of dike erosion and breaching. Fluvial dike breaching is different from frontal dike (embankments) breaching, because of specific geometry and boundary conditions. The current knowledge on the physical processes underpinning fluvial dike failure due to overtopping remains limited. In addition, there is a lack of a continuous monitoring of the 3D breach formation, limiting the analysis of the key mechanisms governing the breach development and the validation of conceptual or physically-based models. Laboratory tests on breach growth in homogeneous, non-cohesive sandy fluvial dikes due to flow overtopping have been performed. Two experimental setups have been constructed, permitting the investigation of various hydraulic and geometric parameters. Each experimental setup includes a main channel, separated from a floodplain by a dike. A rectangular initial notch is cut in the crest to initiate dike breaching. The breach development is monitored continuously using a specific developed laser profilometry technique. The observations have shown that the breach develops in two stages: first the breach deepens and widens with the breach centerline being gradually shifted toward the downstream side of the main channel. This behavior underlines the influence of the flow momentum component parallel to the dike crest. Second, the dike geometry upstream of the breach stops evolving and the breach widening continues only toward the downstream side of the main channel. The breach evolution has been found strongly affected by the flow conditions (i.e. inflow discharge in the main channel, downstream boundary condition) and floodplain confinement. The findings of this work shed light on key mechanisms of fluvial dike breaching, which differ substantially from those of dam breaching. These specific features need to be incorporated in flood risk analyses involving fluvial dike breach and failure. In addition, a well-documented, reliable data set, with a continuous high resolution monitoring of the 3D breach evolution under various flow conditions, has been gathered, which can be used for validating numerical models.

Detail view to show the stylized "dragon" bracket feature that ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Detail view to show the stylized "dragon" bracket feature that stands guard by the outside door to the kitchen (north elevation of the main house) - Death Valley Ranch, Main House, Death Valley Junction, Inyo County, CA

Topological data analysis: A promising big data exploration tool in biology, analytical chemistry and physical chemistry.

PubMed

Offroy, Marc; Duponchel, Ludovic

2016-03-03

An important feature of experimental science is that data of various kinds is being produced at an unprecedented rate. This is mainly due to the development of new instrumental concepts and experimental methodologies. It is also clear that the nature of acquired data is significantly different. Indeed in every areas of science, data take the form of always bigger tables, where all but a few of the columns (i.e. variables) turn out to be irrelevant to the questions of interest, and further that we do not necessary know which coordinates are the interesting ones. Big data in our lab of biology, analytical chemistry or physical chemistry is a future that might be closer than any of us suppose. It is in this sense that new tools have to be developed in order to explore and valorize such data sets. Topological data analysis (TDA) is one of these. It was developed recently by topologists who discovered that topological concept could be useful for data analysis. The main objective of this paper is to answer the question why topology is well suited for the analysis of big data set in many areas and even more efficient than conventional data analysis methods. Raman analysis of single bacteria should be providing a good opportunity to demonstrate the potential of TDA for the exploration of various spectroscopic data sets considering different experimental conditions (with high noise level, with/without spectral preprocessing, with wavelength shift, with different spectral resolution, with missing data). Copyright © 2016 Elsevier B.V. All rights reserved.

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

Eads, Damian Ryan; Rosten, Edward; Helmbold, David

The authors present BEAMER: a new spatially exploitative approach to learning object detectors which shows excellent results when applied to the task of detecting objects in greyscale aerial imagery in the presence of ambiguous and noisy data. There are four main contributions used to produce these results. First, they introduce a grammar-guided feature extraction system, enabling the exploration of a richer feature space while constraining the features to a useful subset. This is specified with a rule-based generative grammer crafted by a human expert. Second, they learn a classifier on this data using a newly proposed variant of AdaBoost whichmore » takes into account the spatially correlated nature of the data. Third, they perform another round of training to optimize the method of converting the pixel classifications generated by boosting into a high quality set of (x,y) locations. lastly, they carefully define three common problems in object detection and define two evaluation criteria that are tightly matched to these problems. Major strengths of this approach are: (1) a way of randomly searching a broad feature space, (2) its performance when evaluated on well-matched evaluation criteria, and (3) its use of the location prediction domain to learn object detectors as well as to generate detections that perform well on several tasks: object counting, tracking, and target detection. They demonstrate the efficacy of BEAMER with a comprehensive experimental evaluation on a challenging data set.« less

Cross-Domain Multi-View Object Retrieval via Multi-Scale Topic Models.

PubMed

Hong, Richang; Hu, Zhenzhen; Wang, Ruxin; Wang, Meng; Tao, Dacheng

2016-09-27

The increasing number of 3D objects in various applications has increased the requirement for effective and efficient 3D object retrieval methods, which attracted extensive research efforts in recent years. Existing works mainly focus on how to extract features and conduct object matching. With the increasing applications, 3D objects come from different areas. In such circumstances, how to conduct object retrieval becomes more important. To address this issue, we propose a multi-view object retrieval method using multi-scale topic models in this paper. In our method, multiple views are first extracted from each object, and then the dense visual features are extracted to represent each view. To represent the 3D object, multi-scale topic models are employed to extract the hidden relationship among these features with respected to varied topic numbers in the topic model. In this way, each object can be represented by a set of bag of topics. To compare the objects, we first conduct topic clustering for the basic topics from two datasets, and then generate the common topic dictionary for new representation. Then, the two objects can be aligned to the same common feature space for comparison. To evaluate the performance of the proposed method, experiments are conducted on two datasets. The 3D object retrieval experimental results and comparison with existing methods demonstrate the effectiveness of the proposed method.

Merging physical parameters and laboratory subjective ratings for the soundscape assessment of urban squares.

PubMed

Brambilla, Giovanni; Maffei, Luigi; Di Gabriele, Maria; Gallo, Veronica

2013-07-01

An experimental study was carried out in 20 squares in the center of Rome, covering a wide range of different uses, sonic environments, geometry, and architectural styles. Soundwalks along the perimeter of each square were performed during daylight and weekdays taking binaural and video recordings, as well as spot measurements of illuminance. The cluster analysis performed on the physical parameters, not only acoustic, provided two clusters that are in satisfactory agreement with the "a priori" classification. Applying the principal component analysis (PCA) to five physical parameters, two main components were obtained which might be associated to two environmental features, namely, "chaotic/calm" and "open/enclosed." On the basis of these two features, six squares were selected for the laboratory audio-video tests where 32 subjects took part filling in a questionnaire. The PCA performed on the subjective ratings on the sonic environment showed two main components which might be associated to two emotional meanings, namely, "calmness" and "vibrancy." The linear regression modeling between five objective parameters and the mean value of subjective ratings on chaotic/calm and enclosed/open attributes showed a good correlation. Notwithstanding these interesting results being limited to the specific data set, it is worth pointing out that the complexity of the soundscape quality assessment can be more comprehensively examined merging the field measurements of physical parameters with the subjective ratings provided by field and/or laboratory tests.

Comparative modeling without implicit sequence alignments.

PubMed

Kolinski, Andrzej; Gront, Dominik

2007-10-01

The number of known protein sequences is about thousand times larger than the number of experimentally solved 3D structures. For more than half of the protein sequences a close or distant structural analog could be identified. The key starting point in a classical comparative modeling is to generate the best possible sequence alignment with a template or templates. With decreasing sequence similarity, the number of errors in the alignments increases and these errors are the main causes of the decreasing accuracy of the molecular models generated. Here we propose a new approach to comparative modeling, which does not require the implicit alignment - the model building phase explores geometric, evolutionary and physical properties of a template (or templates). The proposed method requires prior identification of a template, although the initial sequence alignment is ignored. The model is built using a very efficient reduced representation search engine CABS to find the best possible superposition of the query protein onto the template represented as a 3D multi-featured scaffold. The criteria used include: sequence similarity, predicted secondary structure consistency, local geometric features and hydrophobicity profile. For more difficult cases, the new method qualitatively outperforms existing schemes of comparative modeling. The algorithm unifies de novo modeling, 3D threading and sequence-based methods. The main idea is general and could be easily combined with other efficient modeling tools as Rosetta, UNRES and others.

Numerical modeling of a glow discharge through a supersonic bow shock in air

NASA Astrophysics Data System (ADS)

Rassou, S.; Packan, D.; Elias, P.-Q.; Tholin, F.; Chemartin, L.; Labaune, J.

2017-03-01

The interaction between a glow discharge and the bow shock of a Mach 3 air flow around a truncated conical model with a central spike is modeled, and comparison is made with prior experimental results. The KRONOS workflow for plasma modeling in flow fields, which has recently been developed at ONERA, was used for the modeling. Based on the quasi-neutral approximation, it couples hypersonic and reactive flow fields with electron chemistry, including the effect of non-Maxwellian electron energy distribution function. The model used for the discharge involves 12 species and 82 reactions, including ionization, electronic and vibrational excitation, and attachment. The simulations reproduce the main features of the discharge observed experimentally well, in particular, the very recognizable topology of the discharge. It was found from the simulations that behind the bow shock, in the afterglow, the negative ion flow ensures the electrical conduction and the establishment of the glow discharge. The influence of kinetic rates on the voltage-current characteristics is discussed.

An investigation of the self-heating phenomenon in viscoelastic materials subjected to cyclic loadings accounting for prestress

NASA Astrophysics Data System (ADS)

de Lima, A. M. G.; Rade, D. A.; Lacerda, H. B.; Araújo, C. A.

2015-06-01

It has been demonstrated by many authors that the internal damping mechanism of the viscoelastic materials offers many possibilities for practical engineering applications. However, in traditional procedures of analysis and design of viscoelastic dampers subjected to cyclic loadings, uniform, constant temperature is generally assumed and do not take into account the self-heating phenomenon. Moreover, for viscoelastic materials subjected to dynamic loadings superimposed on static preloads, such as engine mounts, these procedures can lead to poor designs or even severe failures since the energy dissipated within the volume of the material leads to temperature rises. In this paper, a hybrid numerical-experimental investigation of effects of the static preloads on the self-heating phenomenon in viscoelastic dampers subjected to harmonic loadings is reported. After presenting the theoretical foundations, the numerical and experimental results obtained in terms of the temperature evolutions at different points within the volume of the viscoelastic material for various static preloads are compared, and the main features of the methodology are discussed.

Theory of electronic and spin-orbit proximity effects in graphene on Cu(111)

NASA Astrophysics Data System (ADS)

Frank, Tobias; Gmitra, Martin; Fabian, Jaroslav

2016-04-01

We study orbital and spin-orbit proximity effects in graphene adsorbed to the Cu(111) surface by means of density functional theory (DFT). The proximity effects are caused mainly by the hybridization of graphene π and copper d orbitals. Our electronic structure calculations agree well with the experimentally observed features. We carry out a graphene-Cu(111) distance dependent study to obtain proximity orbital and spin-orbit coupling parameters, by fitting the DFT results to a robust low energy model Hamiltonian. We find a strong distance dependence of the Rashba and intrinsic proximity induced spin-orbit coupling parameters, which are in the meV and hundreds of μ eV range, respectively, for experimentally relevant distances. The Dirac spectrum of graphene also exhibits a proximity orbital gap, of about 20 meV. Furthermore, we find a band inversion within the graphene states accompanied by a reordering of spin and pseudospin states, when graphene is pressed towards copper.

Experimental research control software system

NASA Astrophysics Data System (ADS)

Cohn, I. A.; Kovalenko, A. G.; Vystavkin, A. N.

2014-05-01

A software system, intended for automation of a small scale research, has been developed. The software allows one to control equipment, acquire and process data by means of simple scripts. The main purpose of that development is to increase experiment automation easiness, thus significantly reducing experimental setup automation efforts. In particular, minimal programming skills are required and supervisors have no reviewing troubles. Interactions between scripts and equipment are managed automatically, thus allowing to run multiple scripts simultaneously. Unlike well-known data acquisition commercial software systems, the control is performed by an imperative scripting language. This approach eases complex control and data acquisition algorithms implementation. A modular interface library performs interaction with external interfaces. While most widely used interfaces are already implemented, a simple framework is developed for fast implementations of new software and hardware interfaces. While the software is in continuous development with new features being implemented, it is already used in our laboratory for automation of a helium-3 cryostat control and data acquisition. The software is open source and distributed under Gnu Public License.

Origin of subgap states in amorphous In-Ga-Zn-O

NASA Astrophysics Data System (ADS)

Körner, Wolfgang; Urban, Daniel F.; Elsässer, Christian

2013-10-01

We present a density functional theory analysis of stoichiometric and nonstoichiometric, crystalline and amorphous In-Ga-Zn-O (c-IGZO, a-IGZO), which connects the recently experimentally discovered electronic subgap states to structural features of a-IGZO. In particular, we show that undercoordinated oxygen atoms create electronic defect levels in the lower half of the band gap up to about 1.5 eV above the valence band edge. As a second class of fundamental defects that appear in a-IGZO, we identify mainly pairs of metal atoms which are not separated by oxygen atoms in between. These defects cause electronic defect levels in the upper part of the band gap. Furthermore, we show that hydrogen doping can suppress the deep levels due to undercoordinated oxygen atoms while those of metal defects just undergo a shift within the band gap. Altogether our results provide an explanation for the experimentally observed effect that hydrogen doping increases the transparency and improves the conductivity of a-IGZO.

Sequence of Tissue Responses in the Early Stages of Experimental Allergic Encephalomyelitis (EAE): Immunohistochemical, Light Microscopic, and Ultrastructural Observations in the Spinal Cord

NASA Technical Reports Server (NTRS)

DAmelio, Fernando E.; Smith, Marion E.; Eng, Lawrence F.

1990-01-01

Experimental allergic encephalomyelitis (EAE) was induced in adult Lewis rats with purified guinea pig CNS myelin and Freund's adjuvant. As soon as the very earliest clinical signs appeared the animals were perfused with fixatives and the spinal cord analyzed by electron microscopy, silver methods, and immunocytochemistry. Our findings suggest that in the early stages of EAE a sequence of events can be traced, although these events frequently overlap. The earliest morphological change appears to be astrocytic edema in both the cell body and processes. Increased amounts of glycogen particles and dispersion of glial filaments are prominent. These changes seem to occur just prior to the time when inflammatory cells begin to penetrate the capillary walls. Invasion of the neuropil mainly by macrophages and lymphocytes closely follows. Both macrophages and microglia seem to participate in phagocytosis of oligodendrocytes and myelin. Demyelination, however, is not a prominent feature at this early stage.

Phyllosilicate absorption features in main-belt and outer-belt asteroid reflectance spectra.

PubMed

Vilas, F; Gaffey, M J

1989-11-10

Absorption features having depths up to 5% are identified in high-quality, high-resolution reflectance spectra of 16 dark asteroids in the main belt and in the Cybele and Hilda groups. Analogs among the CM2 carbonaceous chondrite meteorites exist for some of these asteroids, suggesting that these absorptions are due to iron oxides in phyllosilicates formed on the asteroidal surfaces by aqueous alteration processes. Spectra of ten additional asteroids, located beyond the outer edge of the main belt, show no discernible absorption features, suggesting that aqueous alteration did not always operate at these heliocentric distances.

Phyllosilicate absorption features in main-belt and outer-belt asteroid reflectance spectra

NASA Technical Reports Server (NTRS)

Vilas, Faith; Gaffey, Michael J.

1989-01-01

Absorption features having depths up to 5 percent are identified in high-quality, high-resolution reflectance spectra of 16 dark asteroids in the main belt and in the Cybele and Hilda groups. Analogs among the CM2 carbonaceous chondrite meteorites exist for some of these asteroids, suggesting that these absorptions are due to iron oxides in phyllosilicates formed on the asteroidal surfaces by aqueous alteration processes. Spectra of ten additional asteroids, located beyond the outer edge of the main belt, show no discernible absorption features, suggesting that aqueous alteration did not always operate at these heliocentric distances.

A PCA aided cross-covariance scheme for discriminative feature extraction from EEG signals.

PubMed

Zarei, Roozbeh; He, Jing; Siuly, Siuly; Zhang, Yanchun

2017-07-01

Feature extraction of EEG signals plays a significant role in Brain-computer interface (BCI) as it can significantly affect the performance and the computational time of the system. The main aim of the current work is to introduce an innovative algorithm for acquiring reliable discriminating features from EEG signals to improve classification performances and to reduce the time complexity. This study develops a robust feature extraction method combining the principal component analysis (PCA) and the cross-covariance technique (CCOV) for the extraction of discriminatory information from the mental states based on EEG signals in BCI applications. We apply the correlation based variable selection method with the best first search on the extracted features to identify the best feature set for characterizing the distribution of mental state signals. To verify the robustness of the proposed feature extraction method, three machine learning techniques: multilayer perceptron neural networks (MLP), least square support vector machine (LS-SVM), and logistic regression (LR) are employed on the obtained features. The proposed methods are evaluated on two publicly available datasets. Furthermore, we evaluate the performance of the proposed methods by comparing it with some recently reported algorithms. The experimental results show that all three classifiers achieve high performance (above 99% overall classification accuracy) for the proposed feature set. Among these classifiers, the MLP and LS-SVM methods yield the best performance for the obtained feature. The average sensitivity, specificity and classification accuracy for these two classifiers are same, which are 99.32%, 100%, and 99.66%, respectively for the BCI competition dataset IVa and 100%, 100%, and 100%, for the BCI competition dataset IVb. The results also indicate the proposed methods outperform the most recently reported methods by at least 0.25% average accuracy improvement in dataset IVa. The execution time results show that the proposed method has less time complexity after feature selection. The proposed feature extraction method is very effective for getting representatives information from mental states EEG signals in BCI applications and reducing the computational complexity of classifiers by reducing the number of extracted features. Copyright © 2017 Elsevier B.V. All rights reserved.

Automatic plankton image classification combining multiple view features via multiple kernel learning.

PubMed

Zheng, Haiyong; Wang, Ruchen; Yu, Zhibin; Wang, Nan; Gu, Zhaorui; Zheng, Bing

2017-12-28

Plankton, including phytoplankton and zooplankton, are the main source of food for organisms in the ocean and form the base of marine food chain. As the fundamental components of marine ecosystems, plankton is very sensitive to environment changes, and the study of plankton abundance and distribution is crucial, in order to understand environment changes and protect marine ecosystems. This study was carried out to develop an extensive applicable plankton classification system with high accuracy for the increasing number of various imaging devices. Literature shows that most plankton image classification systems were limited to only one specific imaging device and a relatively narrow taxonomic scope. The real practical system for automatic plankton classification is even non-existent and this study is partly to fill this gap. Inspired by the analysis of literature and development of technology, we focused on the requirements of practical application and proposed an automatic system for plankton image classification combining multiple view features via multiple kernel learning (MKL). For one thing, in order to describe the biomorphic characteristics of plankton more completely and comprehensively, we combined general features with robust features, especially by adding features like Inner-Distance Shape Context for morphological representation. For another, we divided all the features into different types from multiple views and feed them to multiple classifiers instead of only one by combining different kernel matrices computed from different types of features optimally via multiple kernel learning. Moreover, we also applied feature selection method to choose the optimal feature subsets from redundant features for satisfying different datasets from different imaging devices. We implemented our proposed classification system on three different datasets across more than 20 categories from phytoplankton to zooplankton. The experimental results validated that our system outperforms state-of-the-art plankton image classification systems in terms of accuracy and robustness. This study demonstrated automatic plankton image classification system combining multiple view features using multiple kernel learning. The results indicated that multiple view features combined by NLMKL using three kernel functions (linear, polynomial and Gaussian kernel functions) can describe and use information of features better so that achieve a higher classification accuracy.

Experimental models of tracheobronchial stenoses: a useful tool for evaluating airway stents.

PubMed

Marquette, C H; Mensier, E; Copin, M C; Desmidt, A; Freitag, L; Witt, C; Petyt, L; Ramon, P

1995-09-01

Stent implantation is a conservative alternative to open operation for treating benign tracheobronchial strictures. Most of the presently available stents were primarily designed for endovascular use. Their respiratory use entails a risk of iatrogenic complications. From a scientific and from an ethical point of view these risks justify preclinical evaluation of new respiratory stents in experimental models of central airway stenoses. Therefore, an attempt was made to develop such models in piglets and adult minipigs. Tracheal stenoses were obtained by creating first a segmental tracheomalacia through extramucosal resection of cartilaginous arches. The fibrous component of the stenoses was then obtained through bronchoscopic application of a caustic agent causing progressive deep mucosal and submucosal injury. Stenoses of the main bronchi were created by topical application of the caustic agent only. These models demonstrated the typical features of benign fibromalacic tracheobronchial stenoses with constant recurrence after mechanical dilation. Preliminary experiments showed that short-term problems of tolerance of stent prototypes are easily demonstrable in these models. These experimental models, which simulate quite realistically human diseases, offer the opportunity to perfect new tracheobronchial stents specifically designed for respiratory use and to evaluate their long-term tolerance before their use in humans.

Copper-Substituted Lead Perovskite Materials Constructed with Different Halides for Working (CH3NH3)2CuX4-Based Perovskite Solar Cells from Experimental and Theoretical View.

PubMed

Elseman, Ahmed Mourtada; Shalan, Ahmed Esmail; Sajid, Sajid; Rashad, Mohamed Mohamed; Hassan, Ali Mostafa; Li, Meicheng

2018-04-11

Toxicity and chemical instability issues of halide perovskites based on organic-inorganic lead-containing materials still remain as the main drawbacks for perovskite solar cells (PSCs). Herein, we discuss the preparation of copper (Cu)-based hybrid materials, where we replace lead (Pb) with nontoxic Cu metal for lead-free PSCs, and investigate their potential toward solar cell applications based on experimental and theoretical studies. The formation of (CH 3 NH 3 ) 2 CuX 4 [(CH 3 NH 3 ) 2 CuCl 4 , (CH 3 NH 3 ) 2 CuCl 2 I 2 , and (CH 3 NH 3 ) 2 CuCl 2 Br 2 ] was discussed in details. Furthermore, it was found that chlorine (Cl - ) in the structure is critical for the stabilization of the formed compounds. Cu-based perovskite-like materials showed attractive absorbance features extended to the near-infrared range, with appropriate band gaps. Green photoluminescence of these materials was obtained because of Cu + ions. The power conversion efficiency was measured experimentally and estimated theoretically for different architectures of solar cell devices.

Role of prion protein aggregation in neurotoxicity.

PubMed

Corsaro, Alessandro; Thellung, Stefano; Villa, Valentina; Nizzari, Mario; Florio, Tullio

2012-01-01

In several neurodegenerative diseases, such as Parkinson, Alzheimer's, Huntington, and prion diseases, the deposition of aggregated misfolded proteins is believed to be responsible for the neurotoxicity that characterizes these diseases. Prion protein (PrP), the protein responsible of prion diseases, has been deeply studied for the peculiar feature of its misfolded oligomers that are able to propagate within affected brains, inducing the conversion of the natively folded PrP into the pathological conformation. In this review, we summarize the available experimental evidence concerning the relationship between aggregation status of misfolded PrP and neuronal death in the course of prion diseases. In particular, we describe the main findings resulting from the use of different synthetic (mainly PrP106-126) and recombinant PrP-derived peptides, as far as mechanisms of aggregation and amyloid formation, and how these different spatial conformations can affect neuronal death. In particular, most data support the involvement of non-fibrillar oligomers rather than actual amyloid fibers as the determinant of neuronal death.

Role of Prion Protein Aggregation in Neurotoxicity

PubMed Central

Corsaro, Alessandro; Thellung, Stefano; Villa, Valentina; Nizzari, Mario; Florio, Tullio

2012-01-01

In several neurodegenerative diseases, such as Parkinson, Alzheimer’s, Huntington, and prion diseases, the deposition of aggregated misfolded proteins is believed to be responsible for the neurotoxicity that characterizes these diseases. Prion protein (PrP), the protein responsible of prion diseases, has been deeply studied for the peculiar feature of its misfolded oligomers that are able to propagate within affected brains, inducing the conversion of the natively folded PrP into the pathological conformation. In this review, we summarize the available experimental evidence concerning the relationship between aggregation status of misfolded PrP and neuronal death in the course of prion diseases. In particular, we describe the main findings resulting from the use of different synthetic (mainly PrP106-126) and recombinant PrP-derived peptides, as far as mechanisms of aggregation and amyloid formation, and how these different spatial conformations can affect neuronal death. In particular, most data support the involvement of non-fibrillar oligomers rather than actual amyloid fibers as the determinant of neuronal death. PMID:22942726

An experimental investigation of the chopping of helicopter main rotor tip vortices by the tail rotor. Part 2: High speed photographic study

NASA Technical Reports Server (NTRS)

Cary, Charles M.

1987-01-01

The interaction of a free vortex and a rotor was recorded photographically using oil smoke and stroboscopic illumination. The incident vortex is normal to the plane of the rotor and crosses the rotor plane. This idealized aerodynamic experiment most nearly corresponds to helicopter flight conditions in which a tip vortex from the main rotor is incident upon the tail rotor while hovering. The high speed photographs reveal important features not observed using conventional photography where the image is the time average of varying instantaneous images. Most prominent is the strong interaction between the rotor tip vortex system and the incident vortex, resulting in the roll-up of the incident vortex around the (stronger) tip vortices and the resulting rapid destabilization of the deformed incident vortex. The viscous interaction is clearly shown also. Other forms of instabilities or wave-like behavior may be apparent from further analysis of the photographs.

Hydrodynamic Trapping of Swimming Bacteria by Convex Walls

NASA Astrophysics Data System (ADS)

Sipos, O.; Nagy, K.; Di Leonardo, R.; Galajda, P.

2015-06-01

Swimming bacteria display a remarkable tendency to move along flat surfaces for prolonged times. This behavior may have a biological importance but can also be exploited by using microfabricated structures to manipulate bacteria. The main physical mechanism behind the surface entrapment of swimming bacteria is, however, still an open question. By studying the swimming motion of Escherichia coli cells near microfabricated pillars of variable size, we show that cell entrapment is also present for convex walls of sufficiently low curvature. Entrapment is, however, markedly reduced below a characteristic radius. Using a simple hydrodynamic model, we predict that trapped cells swim at a finite angle with the wall and a precise relation exists between the swimming angle at a flat wall and the critical radius of curvature for entrapment. Both predictions are quantitatively verified by experimental data. Our results demonstrate that the main mechanism for wall entrapment is hydrodynamic in nature and show the possibility of inhibiting cell adhesion, and thus biofilm formation, using convex features of appropriate curvature.

Hydroxytyrosol in the Prevention of the Metabolic Syndrome and Related Disorders.

PubMed

Peyrol, Julien; Riva, Catherine; Amiot, Marie Josèphe

2017-03-20

Virgin olive oil (VOO) constitutes the main source of fat in the Mediterranean diet. VOO is rich in oleic acid, displaying health-promoting properties, but also contains minor bioactive components, especially phenolic compounds. Hydroxytyrosol (HT), the main polyphenol of olive oil, has been reported to be the most bioactive component. This review aims to compile the results of clinical, animal and cell culture studies evaluating the effects of HT on the features of Metabolic Syndrome (MetS) (body weight/adiposity, dyslipidemia, hypertension, and hyperglycemia/insulin resistance) and associated complications (oxidative stress and inflammation). HT was able to improve the lipid profile, glycaemia, and insulin sensitivity, and counteract oxidative and inflammatory processes. Experimental studies identified multiple molecular targets for HT conferring its beneficial effect on health in spite of its low bioavailability. However, rodent experiments and clinical trials with pure HT at biologically relevant concentrations are still lacking. Moreover, the roles of intestine and its gut microbiota have not been elucidated.

Hydroxytyrosol in the Prevention of the Metabolic Syndrome and Related Disorders

PubMed Central

Peyrol, Julien; Riva, Catherine; Amiot, Marie Josèphe

2017-01-01

Virgin olive oil (VOO) constitutes the main source of fat in the Mediterranean diet. VOO is rich in oleic acid, displaying health-promoting properties, but also contains minor bioactive components, especially phenolic compounds. Hydroxytyrosol (HT), the main polyphenol of olive oil, has been reported to be the most bioactive component. This review aims to compile the results of clinical, animal and cell culture studies evaluating the effects of HT on the features of Metabolic Syndrome (MetS) (body weight/adiposity, dyslipidemia, hypertension, and hyperglycemia/insulin resistance) and associated complications (oxidative stress and inflammation). HT was able to improve the lipid profile, glycaemia, and insulin sensitivity, and counteract oxidative and inflammatory processes. Experimental studies identified multiple molecular targets for HT conferring its beneficial effect on health in spite of its low bioavailability. However, rodent experiments and clinical trials with pure HT at biologically relevant concentrations are still lacking. Moreover, the roles of intestine and its gut microbiota have not been elucidated. PMID:28335507

Semi-regular remeshing based trust region spherical geometry image for 3D deformed mesh used MLWNN

NASA Astrophysics Data System (ADS)

Dhibi, Naziha; Elkefi, Akram; Bellil, Wajdi; Ben Amar, Chokri

2017-03-01

Triangular surface are now widely used for modeling three-dimensional object, since these models are very high resolution and the geometry of the mesh is often very dense, it is then necessary to remesh this object to reduce their complexity, the mesh quality (connectivity regularity) must be ameliorated. In this paper, we review the main methods of semi-regular remeshing of the state of the art, given the semi-regular remeshing is mainly relevant for wavelet-based compression, then we present our method for re-meshing based trust region spherical geometry image to have good scheme of 3d mesh compression used to deform 3D meh based on Multi library Wavelet Neural Network structure (MLWNN). Experimental results show that the progressive re-meshing algorithm capable of obtaining more compact representations and semi-regular objects and yield an efficient compression capabilities with minimal set of features used to have good 3D deformation scheme.

Modeling birds on wires.

PubMed

Aydoğdu, A; Frasca, P; D'Apice, C; Manzo, R; Thornton, J M; Gachomo, B; Wilson, T; Cheung, B; Tariq, U; Saidel, W; Piccoli, B

2017-02-21

In this paper we introduce a mathematical model to study the group dynamics of birds resting on wires. The model is agent-based and postulates attraction-repulsion forces between the interacting birds: the interactions are "topological", in the sense that they involve a given number of neighbors irrespective of their distance. The model is first mathematically analyzed and then simulated to study its main properties: we observe that the model predicts birds to be more widely spaced near the borders of each group. We compare the results from the model with experimental data, derived from the analysis of pictures of pigeons and starlings taken in New Jersey: two different image elaboration protocols allow us to establish a good agreement with the model and to quantify its main parameters. We also discuss the potential handedness of the birds, by analyzing the group organization features and the group dynamics at the arrival of new birds. Finally, we propose a more refined mathematical model that describes landing and departing birds by suitable stochastic processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Experimental Investigation of a Helicopter Rotor Hub Wake

NASA Astrophysics Data System (ADS)

Reich, David; Elbing, Brian; Schmitz, Sven

2013-11-01

A scaled model of a notional helicopter rotor hub was tested in the 48'' Garfield Thomas Water Tunnel at the Applied Research Laboratory Penn State. The main objectives of the experiment were to understand the spatial- and temporal content of the unsteady wake downstream of a rotor hub up to a distance corresponding to the empennage. Primary measurements were the total hub drag and velocity measurements at three nominal downstream locations. Various flow structures were identified and linked to geometric features of the hub model. The most prominent structures were two-per-revolution (hub component: scissors) and four-per-revolution (hub component: main hub arms) vortices shed by the hub. Both the two-per-revolution and four-per-revolution structures persisted far downstream of the hub, but the rate of dissipation was greater for the four-per-rev structures. This work provides a dataset for enhanced understanding of the fundamental physics underlying rotor hub flows and serves as validation data for future CFD analyses.

An experimental approach to free vibration analysis of smart composite beam

NASA Astrophysics Data System (ADS)

Yashavantha Kumar, G. A.; Sathish Kumar, K. M.

2018-02-01

Experimental vibration analysis is a main concern of this study. In designing any structural component the important parameter that has to be considered is vibration. The present work involves the experimental investigation of free vibration analysis of a smart beam. Smart beam consists of glass/epoxy composite as a main substrate and two PZT patches. The PZT patches are glued above and below the main beam. By experimentation the natural frequencies and mode shapes are obtained for both with and without PZT patches of a beam. Finally through experimentation the response of the smart beam is recorded.

Assessing postural stability via the correlation patterns of vertical ground reaction force components.

PubMed

Hong, Chih-Yuan; Guo, Lan-Yuen; Song, Rong; Nagurka, Mark L; Sung, Jia-Li; Yen, Chen-Wen

2016-08-02

Many methods have been proposed to assess the stability of human postural balance by using a force plate. While most of these approaches characterize postural stability by extracting features from the trajectory of the center of pressure (COP), this work develops stability measures derived from components of the ground reaction force (GRF). In comparison with previous GRF-based approaches that extract stability features from the GRF resultant force, this study proposes three feature sets derived from the correlation patterns among the vertical GRF (VGRF) components. The first and second feature sets quantitatively assess the strength and changing speed of the correlation patterns, respectively. The third feature set is used to quantify the stabilizing effect of the GRF coordination patterns on the COP. In addition to experimentally demonstrating the reliability of the proposed features, the efficacy of the proposed features has also been tested by using them to classify two age groups (18-24 and 65-73 years) in quiet standing. The experimental results show that the proposed features are considerably more sensitive to aging than one of the most effective conventional COP features and two recently proposed COM features. By extracting information from the correlation patterns of the VGRF components, this study proposes three sets of features to assess human postural stability during quiet standing. As demonstrated by the experimental results, the proposed features are not only robust to inter-trial variability but also more accurate than the tested COP and COM features in classifying the older and younger age groups. An additional advantage of the proposed approach is that it reduces the force sensing requirement from 3D to 1D, substantially reducing the cost of the force plate measurement system.

Involvement of autophagy and apoptosis and lipid accumulation in sclerotial morphogenesis of Morchella importuna.

PubMed

He, Peixin; Wang, Ke; Cai, Yingli; Hu, Xiaolong; Zheng, Yan; Zhang, Junjie; Liu, Wei

2018-06-01

Sclerotial formation is a key phase of the morel life cycle and lipids have been recorded as the main cytoplasmic reserves in sclerotia of Morchella fungi without any experimental verification. In this study, the ultrastructural features of the undifferentiated mycelia stage (MS) and three main sclerotial differentiation states (sclerotial initial [SI], sclerotial development [SD] and sclerotial maturation [SM]) were compared by transmission electron microscopy. The nature of the energy-rich substance in hypha and sclerotium of Morchella importuna was qualitatively investigated by confocal laser scanning microscopy and quantitatively studied by extraction of lipids. Sclerotia were observed to form from the repeated branching and enlargement of either terminal hyphae or subordinate hyphal branches, indicating a complex type of sclerotial development. Autophagy and apoptosis were involved in the sclerotial metamorphosis of the cultivated strain of M. importuna. During the SI phase, the characteristic features of autophagy (vacuolation, coalescence of small vacuoles, existence of autophagosomes and engulfment of autophagosomes by vacuoles) were observed. At the SD phase, apoptotic characteristics (condensation of the cytoplasm and nucleus, shrinkage of plasma membrane, extensive plasma membrane blebbing and existence of phagosomes) could be seen in some developing sclerotial cells. In the final stage of sclerotial morphogensis, the sclerotial cells showed a necrotic mode of cell death. In addition, confocal laser imaging studies of live cells indicated that the energy-rich substance in morel hyphae and sclerotia was lipid. The lipid content in sclerotia was significantly more than that in hyphal cells. To the best of our knowledge, this is the first detailed ultrastructural description highlighting the involvement of autophagy and apoptosis in sclerotial metamorphosis of Morchella species and lipid accumulation during morel sclerotial development was also first experimentally verified. This work will promote a better understanding of the mechanism of morel sclerotial metamorphosis. Copyright © 2018 Elsevier Ltd. All rights reserved.

Stochastic modeling for neural spiking events based on fractional superstatistical Poisson process

NASA Astrophysics Data System (ADS)

Konno, Hidetoshi; Tamura, Yoshiyasu

2018-01-01

In neural spike counting experiments, it is known that there are two main features: (i) the counting number has a fractional power-law growth with time and (ii) the waiting time (i.e., the inter-spike-interval) distribution has a heavy tail. The method of superstatistical Poisson processes (SSPPs) is examined whether these main features are properly modeled. Although various mixed/compound Poisson processes are generated with selecting a suitable distribution of the birth-rate of spiking neurons, only the second feature (ii) can be modeled by the method of SSPPs. Namely, the first one (i) associated with the effect of long-memory cannot be modeled properly. Then, it is shown that the two main features can be modeled successfully by a class of fractional SSPP (FSSPP).

Experimental study of performance degradation of a model helicopter main rotor with simulated ice shapes

NASA Technical Reports Server (NTRS)

Korkan, K. D.; Cross, E. J., Jr.; Cornell, C. C.

1984-01-01

An experimental study utilizing a remote controlled model helicopter has been conducted to measure the performance degradation due to simulated ice accretion on the leading edge of the main rotor for hover and forward flight. The 53.375 inch diameter main rotor incorporates a NACA 0012 airfoil with a generic ice shape corresponding to a specified natural ice condition. Thrust coefficients and torque coefficients about the main rotor were measured as a function of velocity, main rotor RPM, angle-of-incidence of the fuselage, collective pitch angle, and extent of spanwise ice accretion. An experimental airfoil data bank has been determined using a two-dimensional twenty-one inch NACA 0012 airfoil with scaled ice accretion shapes identical to that used on the model helicopter main rotor. The corresponding experimental data are discussed with emphasis on Reynolds number effects and ice accretion scale model testing.

Features and characterization needs of rubber composite structures

NASA Technical Reports Server (NTRS)

Tabaddor, Farhad

1989-01-01

Some of the major unique features of rubber composite structures are outlined. The features covered are those related to the material properties, but the analytical features are also briefly discussed. It is essential to recognize these features at the planning stage of any long-range analytical, experimental, or application program. The development of a general and comprehensive program which fully accounts for all the important characteristics of tires, under all the relevant modes of operation, may present a prohibitively expensive and impractical task at the near future. There is therefore a need to develop application methodologies which can utilize the less general models, beyond their theoretical limitations and yet with reasonable reliability, by proper mix of analytical, experimental, and testing activities.

Thermo-electric analysis of the interconnection of the LHC main superconducting bus bars

NASA Astrophysics Data System (ADS)

Granieri, P. P.; Breschi, M.; Casali, M.; Bottura, L.; Siemko, A.

2013-01-01

Spurred by the question of the maximum allowable energy for the operation of the Large Hadron Collider (LHC), we have progressed in the understanding of the thermo-electric behavior of the 13 kA superconducting bus bars interconnecting its main magnets. A deep insight of the underlying mechanisms is required to ensure the protection of the accelerator against undesired effects of resistive transitions. This is especially important in case of defective interconnections which can jeopardize the operation of the whole LHC. In this paper we present a numerical model of the interconnections between the main dipole and quadrupole magnets, validated against experimental tests of an interconnection sample with a purposely built-in defect. We consider defective interconnections featuring a lack of bonding among the superconducting cables and the copper stabilizer components, such as those that could be present in the machine. We evaluate the critical defect length limiting the maximum allowable current for powering the magnets. We determine the dependence of the critical defect length on different parameters as the heat transfer towards the cooling helium bath, the quality of manufacturing, the operating conditions and the protection system parameters, and discuss the relevant mechanisms.

A New, Scalable and Low Cost Multi-Channel Monitoring System for Polymer Electrolyte Fuel Cells.

PubMed

Calderón, Antonio José; González, Isaías; Calderón, Manuel; Segura, Francisca; Andújar, José Manuel

2016-03-09

In this work a new, scalable and low cost multi-channel monitoring system for Polymer Electrolyte Fuel Cells (PEFCs) has been designed, constructed and experimentally validated. This developed monitoring system performs non-intrusive voltage measurement of each individual cell of a PEFC stack and it is scalable, in the sense that it is capable to carry out measurements in stacks from 1 to 120 cells (from watts to kilowatts). The developed system comprises two main subsystems: hardware devoted to data acquisition (DAQ) and software devoted to real-time monitoring. The DAQ subsystem is based on the low-cost open-source platform Arduino and the real-time monitoring subsystem has been developed using the high-level graphical language NI LabVIEW. Such integration can be considered a novelty in scientific literature for PEFC monitoring systems. An original amplifying and multiplexing board has been designed to increase the Arduino input port availability. Data storage and real-time monitoring have been performed with an easy-to-use interface. Graphical and numerical visualization allows a continuous tracking of cell voltage. Scalability, flexibility, easy-to-use, versatility and low cost are the main features of the proposed approach. The system is described and experimental results are presented. These results demonstrate its suitability to monitor the voltage in a PEFC at cell level.

A New, Scalable and Low Cost Multi-Channel Monitoring System for Polymer Electrolyte Fuel Cells

PubMed Central

Calderón, Antonio José; González, Isaías; Calderón, Manuel; Segura, Francisca; Andújar, José Manuel

2016-01-01

In this work a new, scalable and low cost multi-channel monitoring system for Polymer Electrolyte Fuel Cells (PEFCs) has been designed, constructed and experimentally validated. This developed monitoring system performs non-intrusive voltage measurement of each individual cell of a PEFC stack and it is scalable, in the sense that it is capable to carry out measurements in stacks from 1 to 120 cells (from watts to kilowatts). The developed system comprises two main subsystems: hardware devoted to data acquisition (DAQ) and software devoted to real-time monitoring. The DAQ subsystem is based on the low-cost open-source platform Arduino and the real-time monitoring subsystem has been developed using the high-level graphical language NI LabVIEW. Such integration can be considered a novelty in scientific literature for PEFC monitoring systems. An original amplifying and multiplexing board has been designed to increase the Arduino input port availability. Data storage and real-time monitoring have been performed with an easy-to-use interface. Graphical and numerical visualization allows a continuous tracking of cell voltage. Scalability, flexibility, easy-to-use, versatility and low cost are the main features of the proposed approach. The system is described and experimental results are presented. These results demonstrate its suitability to monitor the voltage in a PEFC at cell level. PMID:27005630

Closing in on the Mechanisms of Pulsatile Insulin Secretion.

PubMed

Bertram, Richard; Satin, Leslie S; Sherman, Arthur S

2018-03-01

Insulin secretion from pancreatic islet β-cells occurs in a pulsatile fashion, with a typical period of ∼5 min. The basis of this pulsatility in mouse islets has been investigated for more than four decades, and the various theories have been described as either qualitative or mathematical models. In many cases the models differ in their mechanisms for rhythmogenesis, as well as other less important details. In this Perspective, we describe two main classes of models: those in which oscillations in the intracellular Ca 2+ concentration drive oscillations in metabolism, and those in which intrinsic metabolic oscillations drive oscillations in Ca 2+ concentration and electrical activity. We then discuss nine canonical experimental findings that provide key insights into the mechanism of islet oscillations and list the models that can account for each finding. Finally, we describe a new model that integrates features from multiple earlier models and is thus called the Integrated Oscillator Model. In this model, intracellular Ca 2+ acts on the glycolytic pathway in the generation of oscillations, and it is thus a hybrid of the two main classes of models. It alone among models proposed to date can explain all nine key experimental findings, and it serves as a good starting point for future studies of pulsatile insulin secretion from human islets. © 2018 by the American Diabetes Association.

Use of sEMG in identification of low level muscle activities: features based on ICA and fractal dimension.

PubMed

Naik, Ganesh R; Kumar, Dinesh K; Arjunan, Sridhar

2009-01-01

This paper has experimentally verified and compared features of sEMG (Surface Electromyogram) such as ICA (Independent Component Analysis) and Fractal Dimension (FD) for identification of low level forearm muscle activities. The fractal dimension was used as a feature as reported in the literature. The normalized feature values were used as training and testing vectors for an Artificial neural network (ANN), in order to reduce inter-experimental variations. The identification accuracy using FD of four channels sEMG was 58%, and increased to 96% when the signals are separated to their independent components using ICA.

Borderline Personality Features, Anger, and Intimate Partner Violence: An Experimental Manipulation of Rejection.

PubMed

Armenti, Nicholas A; Babcock, Julia C

2018-04-01

Individuals with borderline personality features may be susceptible to react to situational stressors with negative and interpersonally maladaptive emotionality (e.g., anger) and aggression. The current study attempted to test two moderated mediation models to investigate dispositional risk factors associated with borderline personality features and intimate partner violence (IPV). Results from an experimental rejection induction paradigm were examined using moderated regression to observe contextual reactions to imagined romantic rejection from a current romantic partner among individuals with borderline personality features. An ethnically diverse sample of 218 undergraduates at a large public university in the southwestern United States was recruited. Participants responded to demographic questions and self-report measures, and engaged in an experimental rejection induction paradigm. Borderline personality features was positively associated with rejection sensitivity, physical assault, and psychological aggression. Contrary to initial hypotheses, rejection sensitivity did not serve as a mediator of the relations between borderline personality features and physical assault and psychological aggression. However, trait anger mediated the relation between borderline personality features and psychological aggression. As such, trait anger may be an important explanatory variable in the relation between borderline personality features and psychological aggression specifically. Results of the rejection induction paradigm indicated that, for individuals who were asked to imagine an ambiguous rejection, the relation between borderline personality features and state anger post-rejection was strengthened. For individuals who imagined a critical rejection, there was no significant relation between borderline personality features and state anger post-rejection. Findings suggest that trait anger may be an important dispositional factor in the link between borderline personality features and IPV. In addition, contextual factors, such as ambiguous rejection by an intimate partner, may be especially relevant in activating anger or aggression in individuals with borderline personality features.

Conceptual design of the beam source for the DEMO Neutral Beam Injectors

NASA Astrophysics Data System (ADS)

Sonato, P.; Agostinetti, P.; Fantz, U.; Franke, T.; Furno, I.; Simonin, A.; Tran, M. Q.

2016-12-01

DEMO (DEMOnstration Fusion Power Plant) is a proposed nuclear fusion power plant that is intended to follow the ITER experimental reactor. The main goal of DEMO will be to demonstrate the possibility to produce electric energy from the fusion reaction. The injection of high energy neutral beams is one of the main tools to heat the plasma up to fusion conditions. A conceptual design of the Neutral Beam Injector (NBI) for the DEMO fusion reactor, is currently being developed by Consorzio RFX in collaboration with other European research institutes. High efficiency and low recirculating power, which are fundamental requirements for the success of DEMO, have been taken into special consideration for the DEMO NBI. Moreover, particular attention has been paid to the issues related to reliability, availability, maintainability and inspectability. A conceptual design of the beam source for the DEMO NBI is here presented featuring 20 sub-sources (two adjacent columns of 10 sub-sources each), following a modular design concept, with each sub-source featuring its radio frequency driver, capable of increasing the reliability and availability of the DEMO NBI. Copper grids with increasing size of the apertures have been adopted in the accelerator, with three main layouts of the apertures (circular apertures, slotted apertures and frame-like apertures for each sub-source). This design, permitting to significantly decrease the stripping losses in the accelerator without spoiling the beam optics, has been investigated with a self-consistent model able to study at the same time the magnetic field, the electrostatic field and the trajectory of the negative ions. Moreover, the status on the R&D carried out in Europe on the ion sources is presented.

Design, installation, commissioning and operation of a beamlet monitor in the negative ion beam test stand at NIFS

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

Antoni, V.; Agostinetti, P.; Brombin, M.

2015-04-08

In the framework of the accompanying activity for the development of the two neutral beam injectors for the ITER fusion experiment, an instrumented beam calorimeter is being designed at Consorzio RFX, to be used in the SPIDER test facility (particle energy 100keV; beam current 50A), with the aim of testing beam characteristics and to verify the source proper operation. The main components of the instrumented calorimeter are one-directional carbon-fibre-carbon composite tiles. Some prototype tiles have been used as a small-scale version of the entire calorimeter in the test stand of the neutral beam injectors of the LHD experiment, with themore » aim of characterising the beam features in various operating conditions. The extraction system of the NIFS test stand source was modified, by applying a mask to the first gridded electrode, in order to isolate only a subset of the beamlets, arranged in two 3×5 matrices, resembling the beamlet groups of the ITER beam sources. The present contribution gives a description of the design of the diagnostic system, including the numerical simulations of the expected thermal pattern. Moreover the dedicated thermocouple measurement system is presented. The beamlet monitor was successfully used for a full experimental campaign, during which the main parameters of the source, mainly the arc power and the grid voltages, were varied. This contribution describes the methods of fitting and data analysis applied to the infrared images of the camera to recover the beamlet optics characteristics, in order to quantify the response of the system to different operational conditions. Some results concerning the beamlet features are presented as a function of the source parameters.« less

Combining Feature Selection and Integration—A Neural Model for MT Motion Selectivity

PubMed Central

Beck, Cornelia; Neumann, Heiko

2011-01-01

Background The computation of pattern motion in visual area MT based on motion input from area V1 has been investigated in many experiments and models attempting to replicate the main mechanisms. Two different core conceptual approaches were developed to explain the findings. In integrationist models the key mechanism to achieve pattern selectivity is the nonlinear integration of V1 motion activity. In contrast, selectionist models focus on the motion computation at positions with 2D features. Methodology/Principal Findings Recent experiments revealed that neither of the two concepts alone is sufficient to explain all experimental data and that most of the existing models cannot account for the complex behaviour found. MT pattern selectivity changes over time for stimuli like type II plaids from vector average to the direction computed with an intersection of constraint rule or by feature tracking. Also, the spatial arrangement of the stimulus within the receptive field of a MT cell plays a crucial role. We propose a recurrent neural model showing how feature integration and selection can be combined into one common architecture to explain these findings. The key features of the model are the computation of 1D and 2D motion in model area V1 subpopulations that are integrated in model MT cells using feedforward and feedback processing. Our results are also in line with findings concerning the solution of the aperture problem. Conclusions/Significance We propose a new neural model for MT pattern computation and motion disambiguation that is based on a combination of feature selection and integration. The model can explain a range of recent neurophysiological findings including temporally dynamic behaviour. PMID:21814543

Main Road Extraction from ZY-3 Grayscale Imagery Based on Directional Mathematical Morphology and VGI Prior Knowledge in Urban Areas

PubMed Central

Liu, Bo; Wu, Huayi; Wang, Yandong; Liu, Wenming

2015-01-01

Main road features extracted from remotely sensed imagery play an important role in many civilian and military applications, such as updating Geographic Information System (GIS) databases, urban structure analysis, spatial data matching and road navigation. Current methods for road feature extraction from high-resolution imagery are typically based on threshold value segmentation. It is difficult however, to completely separate road features from the background. We present a new method for extracting main roads from high-resolution grayscale imagery based on directional mathematical morphology and prior knowledge obtained from the Volunteered Geographic Information found in the OpenStreetMap. The two salient steps in this strategy are: (1) using directional mathematical morphology to enhance the contrast between roads and non-roads; (2) using OpenStreetMap roads as prior knowledge to segment the remotely sensed imagery. Experiments were conducted on two ZiYuan-3 images and one QuickBird high-resolution grayscale image to compare our proposed method to other commonly used techniques for road feature extraction. The results demonstrated the validity and better performance of the proposed method for urban main road feature extraction. PMID:26397832

A comprehensive study on rotation reversal in KSTAR: experimental observations and modelling

NASA Astrophysics Data System (ADS)

Na, D. H.; Na, Yong-Su; Angioni, C.; Yang, S. M.; Kwon, J. M.; Jhang, Hogun; Camenen, Y.; Lee, S. G.; Shi, Y. J.; Ko, W. H.; Lee, J. A.; Hahm, T. S.; KSTAR Team

2017-12-01

Dedicated experiments have been performed in KSTAR Ohmic plasmas to investigate the detailed physics of the rotation reversal phenomena. Here we adapt the more general definition of rotation reversal, a large change of the intrinsic toroidal rotation gradient produced by minor changes in the control parameters (Camenen et al 2017 Plasma Phys. Control. Fusion 59 034001), which is commonly observed in KSTAR regardless of the operating conditions. The two main phenomenological features of the rotation reversal are the normalized toroidal rotation gradient ({{u}\\prime} ) change in the gradient region and the existence of an anchor point. For the KSTAR Ohmic plasma database including the experiment results up to the 2016 experimental campaign, both features were investigated. First, the observations show that the locations of the gradient and the anchor point region are dependent on {{q}95} . Second, a strong dependence of {{u}\\prime} on {νeff} is clearly observed in the gradient region, whereas the dependence on R/{{L}{{Ti}}} , R/{{L}{{Te}}} , and R/{{L}{{ne}}} is unclear considering the usual variation of the normalized gradient length in KSTAR. The experimental observations were compared against several theoretical models. The rotation reversal might not occur due to the transition of the dominant turbulence from the trapped electron mode to the ion temperature gradient mode or the neoclassical equilibrium effect in KSTAR. Instead, it seems that the profile shearing effects associated with a finite ballooning tilting well reproduce the experimental observations of both the gradient region and the anchor point; the difference seems to be related to the magnetic shear and the q value. Further analysis implies that the increase of {{u}\\prime} in the gradient region with the increase of the collisionality would occur when the reduction of the momentum diffusivity is comparatively larger than the reduction of the residual stress. It is supported by the perturbative analysis of the experiments and the nonlinear gyrokinetic simulations. The absence of the sign change of {{u}\\prime} even when a much lower collisionality is produced by additional electron cyclotron heating brings further experimental support to this interpretation.

Quantum irreversible decoherence behaviour in open quantum systems with few degrees of freedom: Application to 1H NMR reversion experiments in nematic liquid crystals

NASA Astrophysics Data System (ADS)

Segnorile, H. H.; Zamar, R. C.

2013-10-01

An experimental study of NMR spin decoherence in nematic liquid crystals is presented. Decoherence dynamics can be put in evidence by means of refocusing experiments of the dipolar interactions. The experimental technique used in this work is based on the MREV8 pulse sequence. The aim of the work is to detect the main features of the irreversible quantum decoherence in liquid crystals, on the basis of the theory presented by the authors recently. The focus is laid on experimentally probing the eigen-selection process in the intermediate time scale, between quantum interference of a closed system and thermalization, as a signature of the quantum spin decoherence of the open quantum system, as well as on quantifying the effects of non-idealities as possible sources of signal decays which could mask the intrinsic decoherence. In order to contrast experiment and theory, the theory was adapted to obtain the decoherence function corresponding to the MREV8 reversion experiments. Non-idealities of the experimental setting, like external field inhomogeneity, pulse misadjustments, and the presence of non-reverted spin interaction terms are analysed in detail within this framework, and their effects on the observed signal decay are numerically estimated. It is found that though all these non-idealities could in principle affect the evolution of the spin dynamics, their influence can be mitigated and they do not present the characteristic behaviour of the irreversible spin decoherence. As unique characteristic of decoherence, the experimental results clearly show the occurrence of eigen-selectivity in the intermediate timescale, in complete agreement with the theoretical predictions. We conclude that the eigen-selection effect is the fingerprint of decoherence associated with a quantum open spin system in liquid crystals. Besides, these features of the results account for the quasi-equilibrium states of the spin system, which were observed previously in these mesophases, and lead to conclude that the quasi-equilibrium is a definite stage of the spin dynamics during its evolution towards equilibrium.

Study of reflection and transport in the microwave photo-excited GaAs/AlGaAs two dimensional electron system

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

Ye, Tianyu; Mani, Ramesh G.; Wegscheider, Werner

2013-12-04

We present the results of a concurrent experimental study of microwave reflection and transport in the GaAs/AlGaAs two dimensional electron gas system and correlate observed features in the reflection with the observed transport features. The experimental results are compared with expectations based on theory.

Categorizing biomedicine images using novel image features and sparse coding representation

PubMed Central

2013-01-01

Background Images embedded in biomedical publications carry rich information that often concisely summarize key hypotheses adopted, methods employed, or results obtained in a published study. Therefore, they offer valuable clues for understanding main content in a biomedical publication. Prior studies have pointed out the potential of mining images embedded in biomedical publications for automatically understanding and retrieving such images' associated source documents. Within the broad area of biomedical image processing, categorizing biomedical images is a fundamental step for building many advanced image analysis, retrieval, and mining applications. Similar to any automatic categorization effort, discriminative image features can provide the most crucial aid in the process. Method We observe that many images embedded in biomedical publications carry versatile annotation text. Based on the locations of and the spatial relationships between these text elements in an image, we thus propose some novel image features for image categorization purpose, which quantitatively characterize the spatial positions and distributions of text elements inside a biomedical image. We further adopt a sparse coding representation (SCR) based technique to categorize images embedded in biomedical publications by leveraging our newly proposed image features. Results we randomly selected 990 images of the JPG format for use in our experiments where 310 images were used as training samples and the rest were used as the testing cases. We first segmented 310 sample images following the our proposed procedure. This step produced a total of 1035 sub-images. We then manually labeled all these sub-images according to the two-level hierarchical image taxonomy proposed by [1]. Among our annotation results, 316 are microscopy images, 126 are gel electrophoresis images, 135 are line charts, 156 are bar charts, 52 are spot charts, 25 are tables, 70 are flow charts, and the remaining 155 images are of the type "others". A serial of experimental results are obtained. Firstly, each image categorizing results is presented, and next image categorizing performance indexes such as precision, recall, F-score, are all listed. Different features which include conventional image features and our proposed novel features indicate different categorizing performance, and the results are demonstrated. Thirdly, we conduct an accuracy comparison between support vector machine classification method and our proposed sparse representation classification method. At last, our proposed approach is compared with three peer classification method and experimental results verify our impressively improved performance. Conclusions Compared with conventional image features that do not exploit characteristics regarding text positions and distributions inside images embedded in biomedical publications, our proposed image features coupled with the SR based representation model exhibit superior performance for classifying biomedical images as demonstrated in our comparative benchmark study. PMID:24565470

Distant failure prediction for early stage NSCLC by analyzing PET with sparse representation

NASA Astrophysics Data System (ADS)

Hao, Hongxia; Zhou, Zhiguo; Wang, Jing

2017-03-01

Positron emission tomography (PET) imaging has been widely explored for treatment outcome prediction. Radiomicsdriven methods provide a new insight to quantitatively explore underlying information from PET images. However, it is still a challenging problem to automatically extract clinically meaningful features for prognosis. In this work, we develop a PET-guided distant failure predictive model for early stage non-small cell lung cancer (NSCLC) patients after stereotactic ablative radiotherapy (SABR) by using sparse representation. The proposed method does not need precalculated features and can learn intrinsically distinctive features contributing to classification of patients with distant failure. The proposed framework includes two main parts: 1) intra-tumor heterogeneity description; and 2) dictionary pair learning based sparse representation. Tumor heterogeneity is initially captured through anisotropic kernel and represented as a set of concatenated vectors, which forms the sample gallery. Then, given a test tumor image, its identity (i.e., distant failure or not) is classified by applying the dictionary pair learning based sparse representation. We evaluate the proposed approach on 48 NSCLC patients treated by SABR at our institute. Experimental results show that the proposed approach can achieve an area under the characteristic curve (AUC) of 0.70 with a sensitivity of 69.87% and a specificity of 69.51% using a five-fold cross validation.

Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System.

PubMed

Li, Hongqiang; Yuan, Danyang; Wang, Youxi; Cui, Dianyin; Cao, Lu

2016-10-20

Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG) recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias.

Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System

PubMed Central

Li, Hongqiang; Yuan, Danyang; Wang, Youxi; Cui, Dianyin; Cao, Lu

2016-01-01

Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG) recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias. PMID:27775596

ENVIRONMENT: a computational platform to stochastically simulate reacting and self-reproducing lipid compartments

NASA Astrophysics Data System (ADS)

Mavelli, Fabio; Ruiz-Mirazo, Kepa

2010-09-01

'ENVIRONMENT' is a computational platform that has been developed in the last few years with the aim to simulate stochastically the dynamics and stability of chemically reacting protocellular systems. Here we present and describe some of its main features, showing how the stochastic kinetics approach can be applied to study the time evolution of reaction networks in heterogeneous conditions, particularly when supramolecular lipid structures (micelles, vesicles, etc) coexist with aqueous domains. These conditions are of special relevance to understand the origins of cellular, self-reproducing compartments, in the context of prebiotic chemistry and evolution. We contrast our simulation results with real lab experiments, with the aim to bring together theoretical and experimental research on protocell and minimal artificial cell systems.

Improving human activity recognition and its application in early stroke diagnosis.

PubMed

Villar, José R; González, Silvia; Sedano, Javier; Chira, Camelia; Trejo-Gabriel-Galan, Jose M

2015-06-01

The development of efficient stroke-detection methods is of significant importance in today's society due to the effects and impact of stroke on health and economy worldwide. This study focuses on Human Activity Recognition (HAR), which is a key component in developing an early stroke-diagnosis tool. An overview of the proposed global approach able to discriminate normal resting from stroke-related paralysis is detailed. The main contributions include an extension of the Genetic Fuzzy Finite State Machine (GFFSM) method and a new hybrid feature selection (FS) algorithm involving Principal Component Analysis (PCA) and a voting scheme putting the cross-validation results together. Experimental results show that the proposed approach is a well-performing HAR tool that can be successfully embedded in devices.

Computer Design Technology of the Small Thrust Rocket Engines Using CAE / CAD Systems

NASA Astrophysics Data System (ADS)

Ryzhkov, V.; Lapshin, E.

2018-01-01

The paper presents an algorithm for designing liquid small thrust rocket engine, the process of which consists of five aggregated stages with feedback. Three stages of the algorithm provide engineering support for design, and two stages - the actual engine design. A distinctive feature of the proposed approach is a deep study of the main technical solutions at the stage of engineering analysis and interaction with the created knowledge (data) base, which accelerates the process and provides enhanced design quality. The using multifunctional graphic package Siemens NX allows to obtain the final product -rocket engine and a set of design documentation in a fairly short time; the engine design does not require a long experimental development.

Spin glass model for dynamics of cell reprogramming

NASA Astrophysics Data System (ADS)

Pusuluri, Sai Teja; Lang, Alex H.; Mehta, Pankaj; Castillo, Horacio E.

2015-03-01

Recent experiments show that differentiated cells can be reprogrammed to become pluripotent stem cells. The possible cell fates can be modeled as attractors in a dynamical system, the ``epigenetic landscape.'' Both cellular differentiation and reprogramming can be described in the landscape picture as motion from one attractor to another attractor. We perform Monte Carlo simulations in a simple model of the landscape. This model is based on spin glass theory and it can be used to construct a simulated epigenetic landscape starting from the experimental genomic data. We re-analyse data from several cell reprogramming experiments and compare with our simulation results. We find that the model can reproduce some of the main features of the dynamics of cell reprogramming.

Structural evolution of 2D microporous covalent triazine-based framework toward the study of high-performance supercapacitors.

PubMed

Hao, Long; Ning, Jing; Luo, Bin; Wang, Bin; Zhang, Yunbo; Tang, Zhihong; Yang, Junhe; Thomas, Arne; Zhi, Linjie

2015-01-14

A series of nitrogen-containing micropore-donimated materials, porous triazine-based frameworks (PTFs), are constructed through the structural evolution of a 2D microporous covalent triazine-based framework. The PTFs feature predictable and controllable nitrogen doping and pore structures, which serve as a model-like system to more deeply understand the heteroatom effect and micropore effect in ionic liquid-based supercapacitors. The experimental results reveal that the nitrogen doping can enhance the supercapacitor performance mainly through affecting the relative permittivity of the electrode materials. Although microspores' contribution is not as obvious as the doped nitrogen, the great performances of the micropore-dominated PTF suggest that micropore-dominated materials still have great potential in ionic liquid-based supercapacitors.

Broadband spectral analysis of non-Debye dielectric relaxation in percolating heterostructures

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

Tuncer, Enis; Bellatar, J; Achour, M E

2011-01-01

In this study, the main features of dielectric relaxation in carbon black epoxy composites are discussed using several types of complementary modelling (i.e., the Cole-Cole phenomenological equation, Jonscher s universal dielectric response, and an approach that relies on a continuous distribution of relaxation times). These methods of characterizing the relaxation were conducted below Tg. Through the numerical model we can obtain the characteristic effective relaxation time and exponents straightforwardly. However, the true relaxation spectrum can be obtained from the distribution of relaxation times calculated from the complex dielectric permittivity. Over the compositional range explored, relaxation occurs by a Vogel-Tammam-Fulcher-like temperaturemore » dependence within the limits of experimental accuracy.« less

BX90: A new diamond anvil cell design for X-ray diffraction and optical measurements

NASA Astrophysics Data System (ADS)

Kantor, I.; Prakapenka, V.; Kantor, A.; Dera, P.; Kurnosov, A.; Sinogeikin, S.; Dubrovinskaia, N.; Dubrovinsky, L.

2012-12-01

We present a new design of a universal diamond anvil cell, suitable for different kinds of experimental studies under high pressures. Main features of the cell are an ultimate 90-degrees symmetrical axial opening and high stability, making the presented cell design suitable for a whole range of techniques from optical absorption to single-crystal X-ray diffraction studies, also in combination with external resistive or double-side laser heating. Three examples of the cell applications are provided: a Brillouin scattering of neon, single-crystal X-ray diffraction of α-Cr2O3, and resistivity measurements on the (Mg0.60Fe0.40)(Si0.63Al0.37)O3 silicate perovskite.

Correlation between Charge Contrast Imaging and the Distribution of Some Trace Level Impurities in Gibbsite

NASA Astrophysics Data System (ADS)

Baroni, Travis C.; Griffin, Brendan J.; Browne, James R.; Lincoln, Frank J.

2000-01-01

Charge contrast images (CCI) of synthetic gibbsite obtained on an environmental scanning electron microscope gives information on the crystallization process. Furthermore, X-ray mapping of the same grains shows that impurities are localized during the initial stages of growth and that the resulting composition images have features similar to these observed in CCI. This suggests a possible correlation between impurity distributions and the emission detected during CCI. X-ray line profiles, simulating the spatial distribution of impurities derived from the Monte Carlo program CASINO, have been compared with experimental line profiles and give an estimate of the localization. The model suggests that a main impurity, Ca, is depleted from the solution within approximately 3 4 [mu]m of growth.

Specific Features of Pressure-Fluctuation Fields in the Vicinity of a Forward-Facing Step-Backward-Facing Step Configuration

NASA Astrophysics Data System (ADS)

Golubev, A. Yu.

2018-01-01

A computational model of inhomogeneous pressure-fluctuation fields in the vicinity of a forward-facing step-backward-facing step configuration taking into account the high degree of their mutual correlation (global correlation) is generalized from experimental data. It is shown that when determining the characteristics of pressure fluctuations that act on an elastic structure, the global correlation is represented by an additional inhomogeneous field. It is demonstrated that a high degree of correlation may lead to a significant change in the main characteristics of the pressure-fluctuation field in the wake behind the configuration. This is taken into consideration in the model by correcting the local properties of this field.

Evolutionary Approach for Relative Gene Expression Algorithms

PubMed Central

Czajkowski, Marcin

2014-01-01

A Relative Expression Analysis (RXA) uses ordering relationships in a small collection of genes and is successfully applied to classiffication using microarray data. As checking all possible subsets of genes is computationally infeasible, the RXA algorithms require feature selection and multiple restrictive assumptions. Our main contribution is a specialized evolutionary algorithm (EA) for top-scoring pairs called EvoTSP which allows finding more advanced gene relations. We managed to unify the major variants of relative expression algorithms through EA and introduce weights to the top-scoring pairs. Experimental validation of EvoTSP on public available microarray datasets showed that the proposed solution significantly outperforms in terms of accuracy other relative expression algorithms and allows exploring much larger solution space. PMID:24790574

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

Esposito, A.; Pilloni, A.; Polosa, Antonio D.

Multiquark resonances are undoubtedly experimentally observed. The number of states and the amount of details on their properties have been growing over the years. It is very recent the discovery of two pentaquarks and the confirmation of four tetraquarks, two of which had not been observed before. We mainly review the theoretical understanding of this sector of particle physics phenomenology and present some considerations attempting a coherent description of the so called X and Z resonances. The prominent problems plaguing theoretical models, like the absence of selection rules limiting the number of states predicted, motivate new directions in model building.more » Lastly, data are reviewed going through all of the observed resonances with particular attention to their common features and the purpose of providing a starting point to further research.« less

Selection method of terrain matching area for TERCOM algorithm

NASA Astrophysics Data System (ADS)

Zhang, Qieqie; Zhao, Long

2017-10-01

The performance of terrain aided navigation is closely related to the selection of terrain matching area. The different matching algorithms have different adaptability to terrain. This paper mainly studies the adaptability to terrain of TERCOM algorithm, analyze the relation between terrain feature and terrain characteristic parameters by qualitative and quantitative methods, and then research the relation between matching probability and terrain characteristic parameters by the Monte Carlo method. After that, we propose a selection method of terrain matching area for TERCOM algorithm, and verify the method correctness with real terrain data by simulation experiment. Experimental results show that the matching area obtained by the method in this paper has the good navigation performance and the matching probability of TERCOM algorithm is great than 90%

Coherent optimal control of photosynthetic molecules

NASA Astrophysics Data System (ADS)

Caruso, F.; Montangero, S.; Calarco, T.; Huelga, S. F.; Plenio, M. B.

2012-04-01

We demonstrate theoretically that open-loop quantum optimal control techniques can provide efficient tools for the verification of various quantum coherent transport mechanisms in natural and artificial light-harvesting complexes under realistic experimental conditions. To assess the feasibility of possible biocontrol experiments, we introduce the main settings and derive optimally shaped and robust laser pulses that allow for the faithful preparation of specified initial states (such as localized excitation or coherent superposition, i.e., propagating and nonpropagating states) of the photosystem and probe efficiently the subsequent dynamics. With these tools, different transport pathways can be discriminated, which should facilitate the elucidation of genuine quantum dynamical features of photosystems and therefore enhance our understanding of the role that coherent processes may play in actual biological complexes.

Effective Thermal Conductivity of Spherical Particulate Nanocomposites: Comparison with Theoretical Models, Monte Carlo Simulations and Experiments

NASA Astrophysics Data System (ADS)

Machrafi, Hatim; Lebon, Georgy

2014-11-01

The purpose of this work is to study heat conduction in systems that are composed out of spherical micro-and nanoparticles dispersed in a bulk matrix. Special emphasis will be put on the dependence of the effective heat conductivity on various selected parameters as dimension and density of particles, interface interaction with the matrix. This is achieved by combining the effective medium approximation and extended irreversible thermodynamics, whose main feature is to elevate the heat flux vector to the status of independent variable. The model is illustrated by three examples: Silicium-Germanium, Silica-epoxy-resin and Copper-Silicium systems. Predictions of our model are in good agreement with other theoretical models, Monte-Carlo simulations and experimental data.

A comprehensive experimental characterization of the iPIX gamma imager

NASA Astrophysics Data System (ADS)

Amgarou, K.; Paradiso, V.; Patoz, A.; Bonnet, F.; Handley, J.; Couturier, P.; Becker, F.; Menaa, N.

2016-08-01

The results of more than 280 different experiments aimed at exploring the main features and performances of a newly developed gamma imager, called iPIX, are summarized in this paper. iPIX is designed to quickly localize radioactive sources while estimating the ambient dose equivalent rate at the measurement point. It integrates a 1 mm thick CdTe detector directly bump-bonded to a Timepix chip, a tungsten coded-aperture mask, and a mini RGB camera. It also represents a major technological breakthrough in terms of lightness, compactness, usability, response sensitivity, and angular resolution. As an example of its key strengths, an 241Am source with a dose rate of only few nSv/h can be localized in less than one minute.

Nuclear mass formula with the shell energies obtained by a new method

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

Koura, H.; Tachibana, T.; Yamada, M.

1998-12-21

Nuclear shapes and masses are estimated by a new method. The main feature of this method lies in estimating shell energies of deformed nuclei from spherical shell energies by mixing them with appropriate weights. The spherical shell energies are calculated from single-particle potentials, and, till now, two mass formulas have been constructed from two different sets of potential parameters. The standard deviation of the calculated masses from all the experimental masses of the 1995 Mass Evaluation is about 760 keV. Contrary to the mass formula by Tachibana, Uno, Yamada and Yamada in the 1987-1988 Atomic Mass Predictions, the present formulasmore » can give nuclear shapes and predict on super-heavy elements.« less

High-Pressure Geoscience Special Feature: Dynamical stability of Fe-H in the Earth's mantle and core regions

NASA Astrophysics Data System (ADS)

Isaev, Eyvaz I.; Skorodumova, Natalia V.; Ahuja, Rajeev; Vekilov, Yuri K.; Johansson, Börje

2007-05-01

The core extends from the depth of 2,900 km to the center of the Earth and is composed mainly of an iron-rich alloy with nickel, with 10% of the mass comprised of lighter elements like hydrogen, but the exact composition is uncertain. We present a quantum mechanical first-principles study of the dynamical stability of FeH phases and their phonon densities of states at high pressure. Our free-energy calculations reveal a phonon-driven stabilization of dhcp FeH at low pressures, thus resolving the present contradiction between experimental observations and theoretical predictions. Calculations reveal a complex phase diagram for FeH under pressure with a dhcp → hcp → fcc sequence of structural transitions.

Face liveness detection for face recognition based on cardiac features of skin color image

NASA Astrophysics Data System (ADS)

Suh, Kun Ha; Lee, Eui Chul

2016-07-01

With the growth of biometric technology, spoofing attacks have been emerged a threat to the security of the system. Main spoofing scenarios in the face recognition system include the printing attack, replay attack, and 3D mask attack. To prevent such attacks, techniques that evaluating liveness of the biometric data can be considered as a solution. In this paper, a novel face liveness detection method based on cardiac signal extracted from face is presented. The key point of proposed method is that the cardiac characteristic is detected in live faces but not detected in non-live faces. Experimental results showed that the proposed method can be effective way for determining printing attack or 3D mask attack.

Turbulence Investigations With High-Resolution Simulations of Dilute Suspension Particle-Laden Gravity Currents

NASA Astrophysics Data System (ADS)

Espath, L.; Pinto, L.; Laizet, S.; Silvestrini, J.; Scientific Team of DNS on Gravity Currents

2013-05-01

Gravity currents are very common in nature, either in atmosphere (due to sea-breeze fronts), in mountain avalanches (in airborne snow or debris flow), or in the ocean due to turbidity currents or river plumes (Simpson, 1982). In this numerical study, we focus on particle-laden hyperpycnal flows (negative-buoyancy), where the dynamics play a central role in the formation of hydrocarbon reservoirs (Meiburg & Kneller, 2009). Moreover, these particle-driven gravity currents are often extremely dangerous for the stability of submarine structures placed near the sea-floor (like pipelines or submarines cables). It is clear that the understanding of the physical mechanism associated with these currents and the correct prediction of their main features are of great importance for practical as well as theoretical purposes. For this numerical work, we are interested in the prediction of a mono-disperse dilute suspension particle-laden flow in the typical lock-exchange configuration. We consider only flat surfaces using DNS (Direct Numerical Simulation). Our approach takes into account the possibility of particles deposition but ignores erosion and/or re-suspension. Previous results for this kind of flows were obtained in laboratory experiments with Reynolds numbers up to 10400 (De Rooij & Dalziel, 2001), or by numerical simulations at moderate Reynolds numbers, up to 5000 for a 2D case (Nasr-Azadani, Hall & Meiburg, 2011) and up to 2236 for a 3D (Necker, Härtel, Kleiser & Meiburg, 2002) case with a Reynolds number based on the buoyancy velocity. It was shown that boundary conditions, initial lock configuration and different particle sizes can have a strong influence on the main characteristics of this kind of flows. The main objective of this numerical study is to undertake unprecedented simulations in order to focus on the turbulence and to investigate the effect of the Reynolds number in such flows. We want to investigate the turbulent mechanism in gravity currents such as local production and dissipation and their relationships with the main features of the flow for different Reynolds numbers, ranging from 2236 to 10000 for 2D and 3D cases. The main features of the flow will be related to the temporal evolution of the front location, sedimentation rate and the resulting streamwise deposit profiles. In particular, we will investigate the flow energy budget where the balance between kinetic and potential energy with dissipation (due to convective fluid motion and Stokes flow around particles) will be analysed in detail, using comparisons with previous experimental and numerical works.

Online Feature Transformation Learning for Cross-Domain Object Category Recognition.

PubMed

Zhang, Xuesong; Zhuang, Yan; Wang, Wei; Pedrycz, Witold

2017-06-09

In this paper, we introduce a new research problem termed online feature transformation learning in the context of multiclass object category recognition. The learning of a feature transformation is viewed as learning a global similarity metric function in an online manner. We first consider the problem of online learning a feature transformation matrix expressed in the original feature space and propose an online passive aggressive feature transformation algorithm. Then these original features are mapped to kernel space and an online single kernel feature transformation (OSKFT) algorithm is developed to learn a nonlinear feature transformation. Based on the OSKFT and the existing Hedge algorithm, a novel online multiple kernel feature transformation algorithm is also proposed, which can further improve the performance of online feature transformation learning in large-scale application. The classifier is trained with k nearest neighbor algorithm together with the learned similarity metric function. Finally, we experimentally examined the effect of setting different parameter values in the proposed algorithms and evaluate the model performance on several multiclass object recognition data sets. The experimental results demonstrate the validity and good performance of our methods on cross-domain and multiclass object recognition application.

Morphological and immunobiochemical analysis of the liver in L-arginine induced experimental chronic pancreatitis.

PubMed

Hu, Na; Shen, Yicong; Liu, Fengyu; Wu, Jiuping; Yuan, Feng; Tian, Liwei; Wu, Bo; Chen, Guoqing; Zhang, Jianming; Wang, Jun

Clinical evidence indicates that hepatic abnormalities in patients with chronic pancreatitis are not uncommon. Here we aimed to study the possible association between liver and pancreatic damage in a recently described experimental mouse model of CP. The severity of the damage to pancreas, liver and other organs was assessed by biochemical markers and histopathology. The methods applied included Hematoxylin Eosin staining, electron microscope examination, biochemical measurements, RT-PCR, ELISA, and the correlations among some of the parameters contributing to these changes were statistically analyzed. The hepatic aberrations were mainly represented by mild infiltration of inflammatory cells in portal triad and congestion of central vein of liver, and the main features of drug-induced hepatotoxicity could not be observed. Severe fibrosis of pancreatic tissue was noticed in experimental group, and the existence of multiple organ injuries was also seen under the microscope. Hepatic pathologic scores were positively correlated with those from the corresponding pancreatic specimens (r = 0.72, P < 0.01). TGF-β1 protein levels significantly elevated both in the test pancreas and liver (P < 0.05) and these values were positively correlated (r = 0.86, P < 0.01). The level of interleukin-1β was increased in the serum and tissue of the liver. In addition, cardiac troponin (Tn-I) level not only significantly increased in myocardial homogenates (P < 0.05) but also was positively correlated with the corresponding pathologic score of the liver (r = 0.88, P < 0.01). The liver aberrations might be associated with L-arginine induced chronic pancreatitis. Copyright © 2017 IAP and EPC. Published by Elsevier B.V. All rights reserved.

Stochastic mechanical model of vocal folds for producing jitter and for identifying pathologies through real voices.

PubMed

Cataldo, E; Soize, C

2018-06-06

Jitter, in voice production applications, is a random phenomenon characterized by the deviation of the glottal cycle length with respect to a mean value. Its study can help in identifying pathologies related to the vocal folds according to the values obtained through the different ways to measure it. This paper aims to propose a stochastic model, considering three control parameters, to generate jitter based on a deterministic one-mass model for the dynamics of the vocal folds and to identify parameters from the stochastic model taking into account real voice signals experimentally obtained. To solve the corresponding stochastic inverse problem, the cost function used is based on the distance between probability density functions of the random variables associated with the fundamental frequencies obtained by the experimental voices and the simulated ones, and also on the distance between features extracted from the voice signals, simulated and experimental, to calculate jitter. The results obtained show that the model proposed is valid and some samples of voices are synthesized considering the identified parameters for normal and pathological cases. The strategy adopted is also a novelty and mainly because a solution was obtained. In addition to the use of three parameters to construct the model of jitter, it is the discussion of a parameter related to the bandwidth of the power spectral density function of the stochastic process to measure the quality of the signal generated. A study about the influence of all the main parameters is also performed. The identification of the parameters of the model considering pathological cases is maybe of all novelties introduced by the paper the most interesting. Copyright © 2018 Elsevier Ltd. All rights reserved.

Analysis of stimulated Raman backscatter and stimulated Brillouin backscatter in experiments performed on SG-III prototype facility with a spectral analysis code

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

Hao, Liang; Zhao, Yiqing; Hu, Xiaoyan

2014-07-15

Experiments about the observations of stimulated Raman backscatter (SRS) and stimulated Brillouin backscatter (SBS) in Hohlraum were performed on Shenguang-III (SG-III) prototype facility for the first time in 2011. In this paper, relevant experimental results are analyzed for the first time with a one-dimension spectral analysis code, which is developed to study the coexistent process of SRS and SBS in Hohlraum plasma condition. Spectral features of the backscattered light are discussed with different plasma parameters. In the case of empty Hohlraum experiments, simulation results indicate that SBS, which grows fast at the energy deposition region near the Hohlraum wall, ismore » the dominant instability process. The time resolved spectra of SRS and SBS are numerically obtained, which agree with the experimental observations. For the gas-filled Hohlraum experiments, simulation results show that SBS grows fastest in Au plasma and amplifies convectively in C{sub 5}H{sub 12} gas, whereas SRS mainly grows in the high density region of the C{sub 5}H{sub 12} gas. Gain spectra and the spectra of backscattered light are simulated along the ray path, which clearly show the location where the intensity of scattered light with a certain wavelength increases. This work is helpful to comprehend the observed spectral features of SRS and SBS. The experiments and relevant analysis provide references for the ignition target design in future.« less

Improving Speaker Recognition by Biometric Voice Deconstruction

PubMed Central

Mazaira-Fernandez, Luis Miguel; Álvarez-Marquina, Agustín; Gómez-Vilda, Pedro

2015-01-01

Person identification, especially in critical environments, has always been a subject of great interest. However, it has gained a new dimension in a world threatened by a new kind of terrorism that uses social networks (e.g., YouTube) to broadcast its message. In this new scenario, classical identification methods (such as fingerprints or face recognition) have been forcedly replaced by alternative biometric characteristics such as voice, as sometimes this is the only feature available. The present study benefits from the advances achieved during last years in understanding and modeling voice production. The paper hypothesizes that a gender-dependent characterization of speakers combined with the use of a set of features derived from the components, resulting from the deconstruction of the voice into its glottal source and vocal tract estimates, will enhance recognition rates when compared to classical approaches. A general description about the main hypothesis and the methodology followed to extract the gender-dependent extended biometric parameters is given. Experimental validation is carried out both on a highly controlled acoustic condition database, and on a mobile phone network recorded under non-controlled acoustic conditions. PMID:26442245

What does the cryopreserved oocyte look like? A fresh look at the characteristic oocyte features following cryopreservation.

PubMed

Hosseini, Sayyed Morteza; Nasr-Esfahani, Mohammad Hossein

2016-04-01

In October 2012, the American Society for Reproductive Medicine (ASRM) and, in March 2012, the European Society of Human Reproduction and Embryology (ESHRE), lifted the categorization of oocyte cryopreservation as being "experimental" and endorsed its entrance into the mainstream of assisted reproductive techniques. This change in policy, with the considerable advantages that oocytes offer over embryos for cryopreservation, has increased applications of oocyte cryopreservation in assisted reproduction techniques. A deep understanding of oocyte cryobiology, however, is lagging behind the forces propelling the clinical application of oocyte cryopreservation. We have drawn attention to this shortcoming by initiating a debate on whether a vitrified-warmed oocyte has the same characteristics as its fresh sibling. The answer to this question may explain why the oocyte cryopreservation success rate is as yet far from satisfactory and why cryopreserved oocytes should be treated differently from their fresh siblings. A fresh look at the characteristic features of oocytes after cryopreservation is the main scope of this review as a stimulus to further improvement of oocyte cryopreservation. Copyright © 2016. Published by Elsevier Ltd.

On the influence of additive and multiplicative noise on holes in dissipative systems.

PubMed

Descalzi, Orazio; Cartes, Carlos; Brand, Helmut R

2017-05-01

We investigate the influence of noise on deterministically stable holes in the cubic-quintic complex Ginzburg-Landau equation. Inspired by experimental possibilities, we specifically study two types of noise: additive noise delta-correlated in space and spatially homogeneous multiplicative noise on the formation of π-holes and 2π-holes. Our results include the following main features. For large enough additive noise, we always find a transition to the noisy version of the spatially homogeneous finite amplitude solution, while for sufficiently large multiplicative noise, a collapse occurs to the zero amplitude solution. The latter type of behavior, while unexpected deterministically, can be traced back to a characteristic feature of multiplicative noise; the zero solution acts as the analogue of an absorbing boundary: once trapped at zero, the system cannot escape. For 2π-holes, which exist deterministically over a fairly small range of values of subcriticality, one can induce a transition to a π-hole (for additive noise) or to a noise-sustained pulse (for multiplicative noise). This observation opens the possibility of noise-induced switching back and forth from and to 2π-holes.

Investigation of soft component in cosmic ray detection

NASA Astrophysics Data System (ADS)

Oláh, László; Varga, Dezső

2017-07-01

Cosmic ray detection is a research area which finds various applications in tomographic imaging of large size objects. In such applications, the background sources which contaminate cosmic muon signal require a good understanding of the creation processes, as well as reliable simulation frameworks with high predictive power are needed. One of the main background source is the ;soft component;, that is electrons and positrons. In this paper a simulation framework based on GEANT4 has been established to pin down the key features of the soft component. We have found that the electron and positron flux shows a remarkable invariance against various model parameters including the muon emission altitude or primary particle energy distribution. The correlation between simultaneously arriving particles have been quantitatively investigated, demonstrating that electrons and positrons tend to arrive within a close distance and with low relative angle. This feature, which is highly relevant for counting detectors, has been experimentally verified under open sky and at shallow depth underground. The simulation results have been compared to existing other measurements as well as other simulation programs.

Man-Made Object Extraction from Remote Sensing Imagery by Graph-Based Manifold Ranking

NASA Astrophysics Data System (ADS)

He, Y.; Wang, X.; Hu, X. Y.; Liu, S. H.

2018-04-01

The automatic extraction of man-made objects from remote sensing imagery is useful in many applications. This paper proposes an algorithm for extracting man-made objects automatically by integrating a graph model with the manifold ranking algorithm. Initially, we estimate a priori value of the man-made objects with the use of symmetric and contrast features. The graph model is established to represent the spatial relationships among pre-segmented superpixels, which are used as the graph nodes. Multiple characteristics, namely colour, texture and main direction, are used to compute the weights of the adjacent nodes. Manifold ranking effectively explores the relationships among all the nodes in the feature space as well as initial query assignment; thus, it is applied to generate a ranking map, which indicates the scores of the man-made objects. The man-made objects are then segmented on the basis of the ranking map. Two typical segmentation algorithms are compared with the proposed algorithm. Experimental results show that the proposed algorithm can extract man-made objects with high recognition rate and low omission rate.

Hydrogen Embrittlement of Automotive Advanced High-Strength Steels

NASA Astrophysics Data System (ADS)

Lovicu, Gianfranco; Bottazzi, Mauro; D'Aiuto, Fabio; De Sanctis, Massimo; Dimatteo, Antonella; Santus, Ciro; Valentini, Renzo

2012-11-01

Advanced high-strength steels (AHSS) have a better combination between strength and ductility than conventional HSS, and higher crash resistances are obtained in concomitance with weight reduction of car structural components. These steels have been developed in the last few decades, and their use is rapidly increasing. Notwithstanding, some of their important features have to be still understood and studied in order to completely characterize their service behavior. In particular, the high mechanical resistance of AHSS makes hydrogen-related problems a great concern for this steel grade. This article investigates the hydrogen embrittlement (HE) of four AHSS steels. The behavior of one transformation induced plasticity (TRIP), two martensitic with different strength levels, and one hot-stamping steels has been studied using slow strain rate tensile (SSRT) tests on electrochemically hydrogenated notched samples. The embrittlement susceptibility of these AHSS steels has been correlated mainly to their strength level and to their microstructural features. Finally, the hydrogen critical concentrations for HE, established by SSRT tests, have been compared to hydrogen contents absorbed during the painting process of a body in white (BIW) structure, experimentally determined during a real cycle in an industrial plant.

HEp-2 cell image classification method based on very deep convolutional networks with small datasets

NASA Astrophysics Data System (ADS)

Lu, Mengchi; Gao, Long; Guo, Xifeng; Liu, Qiang; Yin, Jianping

2017-07-01

Human Epithelial-2 (HEp-2) cell images staining patterns classification have been widely used to identify autoimmune diseases by the anti-Nuclear antibodies (ANA) test in the Indirect Immunofluorescence (IIF) protocol. Because manual test is time consuming, subjective and labor intensive, image-based Computer Aided Diagnosis (CAD) systems for HEp-2 cell classification are developing. However, methods proposed recently are mostly manual features extraction with low accuracy. Besides, the scale of available benchmark datasets is small, which does not exactly suitable for using deep learning methods. This issue will influence the accuracy of cell classification directly even after data augmentation. To address these issues, this paper presents a high accuracy automatic HEp-2 cell classification method with small datasets, by utilizing very deep convolutional networks (VGGNet). Specifically, the proposed method consists of three main phases, namely image preprocessing, feature extraction and classification. Moreover, an improved VGGNet is presented to address the challenges of small-scale datasets. Experimental results over two benchmark datasets demonstrate that the proposed method achieves superior performance in terms of accuracy compared with existing methods.

Biomass saccharification is largely enhanced by altering wall polymer features and reducing silicon accumulation in rice cultivars harvested from nitrogen fertilizer supply.

PubMed

Zahoor; Sun, Dan; Li, Ying; Wang, Jing; Tu, Yuanyuan; Wang, Yanting; Hu, Zhen; Zhou, Shiguang; Wang, Lingqiang; Xie, Guosheng; Huang, Jianliang; Alam, Aftab; Peng, Liangcai

2017-11-01

In this study, two rice cultivars were collected from experimental fields with seven nitrogen fertilizer treatments. All biomass samples contained significantly increased cellulose contents and reduced silica levels, with variable amounts of hemicellulose and lignin from different nitrogen treatments. Under chemical (NaOH, CaO, H 2 SO 4 ) and physical (hot water) pretreatments, biomass samples exhibited much enhanced hexoses yields from enzymatic hydrolysis, with high bioethanol production from yeast fermentation. Notably, both degree of polymerization (DP) of cellulose and xylose/arabinose (Xyl/Ara) ratio of hemicellulose were reduced in biomass residues, whereas other wall polymer features (cellulose crystallinity and monolignol proportion) were variable. Integrative analysis indicated that cellulose DP, hemicellulosic Xyl/Ara and silica are the major factors that significantly affect cellulose crystallinity and biomass saccharification. Hence, this study has demonstrated that nitrogen fertilizer supply could largely enhance biomass saccharification in rice cultivars, mainly by reducing cellulose DP, hemicellulosic Xyl/Ara and silica in cell walls. Copyright © 2017 Elsevier Ltd. All rights reserved.

Finger vein recognition based on personalized weight maps.

PubMed

Yang, Gongping; Xiao, Rongyang; Yin, Yilong; Yang, Lu

2013-09-10

Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs). The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition.

Finger Vein Recognition Based on Personalized Weight Maps

PubMed Central

Yang, Gongping; Xiao, Rongyang; Yin, Yilong; Yang, Lu

2013-01-01

Finger vein recognition is a promising biometric recognition technology, which verifies identities via the vein patterns in the fingers. Binary pattern based methods were thoroughly studied in order to cope with the difficulties of extracting the blood vessel network. However, current binary pattern based finger vein matching methods treat every bit of feature codes derived from different image of various individuals as equally important and assign the same weight value to them. In this paper, we propose a finger vein recognition method based on personalized weight maps (PWMs). The different bits have different weight values according to their stabilities in a certain number of training samples from an individual. Firstly we present the concept of PWM, and then propose the finger vein recognition framework, which mainly consists of preprocessing, feature extraction, and matching. Finally, we design extensive experiments to evaluate the effectiveness of our proposal. Experimental results show that PWM achieves not only better performance, but also high robustness and reliability. In addition, PWM can be used as a general framework for binary pattern based recognition. PMID:24025556

Improving Speaker Recognition by Biometric Voice Deconstruction.

PubMed

Mazaira-Fernandez, Luis Miguel; Álvarez-Marquina, Agustín; Gómez-Vilda, Pedro

2015-01-01

Person identification, especially in critical environments, has always been a subject of great interest. However, it has gained a new dimension in a world threatened by a new kind of terrorism that uses social networks (e.g., YouTube) to broadcast its message. In this new scenario, classical identification methods (such as fingerprints or face recognition) have been forcedly replaced by alternative biometric characteristics such as voice, as sometimes this is the only feature available. The present study benefits from the advances achieved during last years in understanding and modeling voice production. The paper hypothesizes that a gender-dependent characterization of speakers combined with the use of a set of features derived from the components, resulting from the deconstruction of the voice into its glottal source and vocal tract estimates, will enhance recognition rates when compared to classical approaches. A general description about the main hypothesis and the methodology followed to extract the gender-dependent extended biometric parameters is given. Experimental validation is carried out both on a highly controlled acoustic condition database, and on a mobile phone network recorded under non-controlled acoustic conditions.

Modelling multi-rotor UAVs swarm deployment using virtual pheromones

PubMed Central

Pujol, Mar; Rizo, Ramón; Rizo, Carlos

2018-01-01

In this work, a swarm behaviour for multi-rotor Unmanned Aerial Vehicles (UAVs) deployment will be presented. The main contribution of this behaviour is the use of a virtual device for quantitative sematectonic stigmergy providing more adaptable behaviours in complex environments. It is a fault tolerant highly robust behaviour that does not require prior information of the area to be covered, or to assume the existence of any kind of information signals (GPS, mobile communication networks …), taking into account the specific features of UAVs. This behaviour will be oriented towards emergency tasks. Their main goal will be to cover an area of the environment for later creating an ad-hoc communication network, that can be used to establish communications inside this zone. Although there are several papers on robotic deployment it is more difficult to find applications with UAV systems, mainly because of the existence of various problems that must be overcome including limitations in available sensory and on-board processing capabilities and low flight endurance. In addition, those behaviours designed for UAVs often have significant limitations on their ability to be used in real tasks, because they assume specific features, not easily applicable in a general way. Firstly, in this article the characteristics of the simulation environment will be presented. Secondly, a microscopic model for deployment and creation of ad-hoc networks, that implicitly includes stigmergy features, will be shown. Then, the overall swarm behaviour will be modeled, providing a macroscopic model of this behaviour. This model can accurately predict the number of agents needed to cover an area as well as the time required for the deployment process. An experimental analysis through simulation will be carried out in order to verify our models. In this analysis the influence of both the complexity of the environment and the stigmergy system will be discussed, given the data obtained in the simulation. In addition, the macroscopic and microscopic models will be compared verifying the number of predicted individuals for each state regarding the simulation. PMID:29370203

Context-specific selection of algorithms for recursive feature tracking in endoscopic image using a new methodology.

PubMed

Selka, F; Nicolau, S; Agnus, V; Bessaid, A; Marescaux, J; Soler, L

2015-03-01

In minimally invasive surgery, the tracking of deformable tissue is a critical component for image-guided applications. Deformation of the tissue can be recovered by tracking features using tissue surface information (texture, color,...). Recent work in this field has shown success in acquiring tissue motion. However, the performance evaluation of detection and tracking algorithms on such images are still difficult and are not standardized. This is mainly due to the lack of ground truth data on real data. Moreover, in order to avoid supplementary techniques to remove outliers, no quantitative work has been undertaken to evaluate the benefit of a pre-process based on image filtering, which can improve feature tracking robustness. In this paper, we propose a methodology to validate detection and feature tracking algorithms, using a trick based on forward-backward tracking that provides an artificial ground truth data. We describe a clear and complete methodology to evaluate and compare different detection and tracking algorithms. In addition, we extend our framework to propose a strategy to identify the best combinations from a set of detector, tracker and pre-process algorithms, according to the live intra-operative data. Experimental results have been performed on in vivo datasets and show that pre-process can have a strong influence on tracking performance and that our strategy to find the best combinations is relevant for a reasonable computation cost. Copyright © 2014 Elsevier Ltd. All rights reserved.

3D variational brain tumor segmentation on a clustered feature set

NASA Astrophysics Data System (ADS)

Popuri, Karteek; Cobzas, Dana; Jagersand, Martin; Shah, Sirish L.; Murtha, Albert

2009-02-01

Tumor segmentation from MRI data is a particularly challenging and time consuming task. Tumors have a large diversity in shape and appearance with intensities overlapping the normal brain tissues. In addition, an expanding tumor can also deflect and deform nearby tissue. Our work addresses these last two difficult problems. We use the available MRI modalities (T1, T1c, T2) and their texture characteristics to construct a multi-dimensional feature set. Further, we extract clusters which provide a compact representation of the essential information in these features. The main idea in this paper is to incorporate these clustered features into the 3D variational segmentation framework. In contrast to the previous variational approaches, we propose a segmentation method that evolves the contour in a supervised fashion. The segmentation boundary is driven by the learned inside and outside region voxel probabilities in the cluster space. We incorporate prior knowledge about the normal brain tissue appearance, during the estimation of these region statistics. In particular, we use a Dirichlet prior that discourages the clusters in the ventricles to be in the tumor and hence better disambiguate the tumor from brain tissue. We show the performance of our method on real MRI scans. The experimental dataset includes MRI scans, from patients with difficult instances, with tumors that are inhomogeneous in appearance, small in size and in proximity to the major structures in the brain. Our method shows good results on these test cases.

Automatic segmentation of solitary pulmonary nodules based on local intensity structure analysis and 3D neighborhood features in 3D chest CT images

NASA Astrophysics Data System (ADS)

Chen, Bin; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku

2012-03-01

This paper presents a solitary pulmonary nodule (SPN) segmentation method based on local intensity structure analysis and neighborhood feature analysis in chest CT images. Automated segmentation of SPNs is desirable for a chest computer-aided detection/diagnosis (CAS) system since a SPN may indicate early stage of lung cancer. Due to the similar intensities of SPNs and other chest structures such as blood vessels, many false positives (FPs) are generated by nodule detection methods. To reduce such FPs, we introduce two features that analyze the relation between each segmented nodule candidate and it neighborhood region. The proposed method utilizes a blob-like structure enhancement (BSE) filter based on Hessian analysis to augment the blob-like structures as initial nodule candidates. Then a fine segmentation is performed to segment much more accurate region of each nodule candidate. FP reduction is mainly addressed by investigating two neighborhood features based on volume ratio and eigenvector of Hessian that are calculates from the neighborhood region of each nodule candidate. We evaluated the proposed method by using 40 chest CT images, include 20 standard-dose CT images that we randomly chosen from a local database and 20 low-dose CT images that were randomly chosen from a public database: LIDC. The experimental results revealed that the average TP rate of proposed method was 93.6% with 12.3 FPs/case.

YamiPred: A Novel Evolutionary Method for Predicting Pre-miRNAs and Selecting Relevant Features.

PubMed

Kleftogiannis, Dimitrios; Theofilatos, Konstantinos; Likothanassis, Spiros; Mavroudi, Seferina

2015-01-01

MicroRNAs (miRNAs) are small non-coding RNAs, which play a significant role in gene regulation. Predicting miRNA genes is a challenging bioinformatics problem and existing experimental and computational methods fail to deal with it effectively. We developed YamiPred, an embedded classification method that combines the efficiency and robustness of support vector machines (SVM) with genetic algorithms (GA) for feature selection and parameters optimization. YamiPred was tested in a new and realistic human dataset and was compared with state-of-the-art computational intelligence approaches and the prevalent SVM-based tools for miRNA prediction. Experimental results indicate that YamiPred outperforms existing approaches in terms of accuracy and of geometric mean of sensitivity and specificity. The embedded feature selection component selects a compact feature subset that contributes to the performance optimization. Further experimentation with this minimal feature subset has achieved very high classification performance and revealed the minimum number of samples required for developing a robust predictor. YamiPred also confirmed the important role of commonly used features such as entropy and enthalpy, and uncovered the significance of newly introduced features, such as %A-U aggregate nucleotide frequency and positional entropy. The best model trained on human data has successfully predicted pre-miRNAs to other organisms including the category of viruses.

Computational Model of the Insect Pheromone Transduction Cascade

PubMed Central

Gu, Yuqiao; Lucas, Philippe; Rospars, Jean-Pierre

2009-01-01

A biophysical model of receptor potential generation in the male moth olfactory receptor neuron is presented. It takes into account all pre-effector processes—the translocation of pheromone molecules from air to sensillum lymph, their deactivation and interaction with the receptors, and the G-protein and effector enzyme activation—and focuses on the main post-effector processes. These processes involve the production and degradation of second messengers (IP3 and DAG), the opening and closing of a series of ionic channels (IP3-gated Ca2+ channel, DAG-gated cationic channel, Ca2+-gated Cl− channel, and Ca2+- and voltage-gated K+ channel), and Ca2+ extrusion mechanisms. The whole network is regulated by modulators (protein kinase C and Ca2+-calmodulin) that exert feedback inhibition on the effector and channels. The evolution in time of these linked chemical species and currents and the resulting membrane potentials in response to single pulse stimulation of various intensities were simulated. The unknown parameter values were fitted by comparison to the amplitude and temporal characteristics (rising and falling times) of the experimentally measured receptor potential at various pheromone doses. The model obtained captures the main features of the dose–response curves: the wide dynamic range of six decades with the same amplitudes as the experimental data, the short rising time, and the long falling time. It also reproduces the second messenger kinetics. It suggests that the two main types of depolarizing ionic channels play different roles at low and high pheromone concentrations; the DAG-gated cationic channel plays the major role for depolarization at low concentrations, and the Ca2+-gated Cl− channel plays the major role for depolarization at middle and high concentrations. Several testable predictions are proposed, and future developments are discussed. PMID:19300479

Layout optimization with assist features placement by model based rule tables for 2x node random contact

NASA Astrophysics Data System (ADS)

Jun, Jinhyuck; Park, Minwoo; Park, Chanha; Yang, Hyunjo; Yim, Donggyu; Do, Munhoe; Lee, Dongchan; Kim, Taehoon; Choi, Junghoe; Luk-Pat, Gerard; Miloslavsky, Alex

2015-03-01

As the industry pushes to ever more complex illumination schemes to increase resolution for next generation memory and logic circuits, sub-resolution assist feature (SRAF) placement requirements become increasingly severe. Therefore device manufacturers are evaluating improvements in SRAF placement algorithms which do not sacrifice main feature (MF) patterning capability. There are known-well several methods to generate SRAF such as Rule based Assist Features (RBAF), Model Based Assist Features (MBAF) and Hybrid Assisted Features combining features of the different algorithms using both RBAF and MBAF. Rule Based Assist Features (RBAF) continue to be deployed, even with the availability of Model Based Assist Features (MBAF) and Inverse Lithography Technology (ILT). Certainly for the 3x nm node, and even at the 2x nm nodes and lower, RBAF is used because it demands less run time and provides better consistency. Since RBAF is needed now and in the future, what is also needed is a faster method to create the AF rule tables. The current method typically involves making masks and printing wafers that contain several experiments, varying the main feature configurations, AF configurations, dose conditions, and defocus conditions - this is a time consuming and expensive process. In addition, as the technology node shrinks, wafer process changes and source shape redesigns occur more frequently, escalating the cost of rule table creation. Furthermore, as the demand on process margin escalates, there is a greater need for multiple rule tables: each tailored to a specific set of main-feature configurations. Model Assisted Rule Tables(MART) creates a set of test patterns, and evaluates the simulated CD at nominal conditions, defocused conditions and off-dose conditions. It also uses lithographic simulation to evaluate the likelihood of AF printing. It then analyzes the simulation data to automatically create AF rule tables. It means that analysis results display the cost of different AF configurations as the space grows between a pair of main features. In summary, model based rule tables method is able to make it much easier to create rule tables, leading to faster rule-table creation and a lower barrier to the creation of more rule tables.

The Main Features and the Key Challenges of the Education System in Taiwan

ERIC Educational Resources Information Center

Chien, Chiu-Kuei Chang; Lin, Lung-Chi; Chen, Chun-Fu

2013-01-01

Taiwan has undergone radical innovation of its educational system in the wake of political liberalization and democratization, with a request for a change in the idea which diverts from "de-centralization" to "individualization." The reforms have led to two main features of pluralism and generalization of education in our…

Prediction of enhancer-promoter interactions via natural language processing.

PubMed

Zeng, Wanwen; Wu, Mengmeng; Jiang, Rui

2018-05-09

Precise identification of three-dimensional genome organization, especially enhancer-promoter interactions (EPIs), is important to deciphering gene regulation, cell differentiation and disease mechanisms. Currently, it is a challenging task to distinguish true interactions from other nearby non-interacting ones since the power of traditional experimental methods is limited due to low resolution or low throughput. We propose a novel computational framework EP2vec to assay three-dimensional genomic interactions. We first extract sequence embedding features, defined as fixed-length vector representations learned from variable-length sequences using an unsupervised deep learning method in natural language processing. Then, we train a classifier to predict EPIs using the learned representations in supervised way. Experimental results demonstrate that EP2vec obtains F1 scores ranging from 0.841~ 0.933 on different datasets, which outperforms existing methods. We prove the robustness of sequence embedding features by carrying out sensitivity analysis. Besides, we identify motifs that represent cell line-specific information through analysis of the learned sequence embedding features by adopting attention mechanism. Last, we show that even superior performance with F1 scores 0.889~ 0.940 can be achieved by combining sequence embedding features and experimental features. EP2vec sheds light on feature extraction for DNA sequences of arbitrary lengths and provides a powerful approach for EPIs identification.

Squared ligament of the elbow: anatomy and contribution to forearm stability.

PubMed

Otayek, Salma; Tayeb, Abd-el-Kader Ait; Assabah, Bouchra; Viard, Brice; Dayan, Romain; Lazure, Thierry; Soubeyrand, Marc

2016-03-01

The present study describes the macroscopic and microscopic features of the squared ligament of the elbow (SLE). In addition, the SLE biomechanical behavior and contribution to the forearm stability were also examined. Ten forearms from freshly frozen cadavers were used for this work. Each forearm was mounted in an experimental frame for quantification of longitudinal and transverse stability. Macroscopic features and biomechanical behavior were analyzed on dynamic videos obtained during forearm rotation. Then, the SLE was harvested from the 10 forearms for microscopic analysis on histological slices stained with hematoxylin-eosin-saffron. Two main SLE configurations were identified. One in which the SLE had three distinct bundles (anterior, middle, posterior) and another in which it was homogeneous. The anterior part of the SLE had a mean length of 11.2 mm (±2.4 mm) and a mean width of 1.2 mm (±0.2 mm) while the posterior part had a mean length of 9.9 mm (±2.2 mm) and a mean width of 1 mm (±0.2 mm). Microscopic examination showed that the SLE is composed of a thin layer of arranged collagen fibers. During forearm rotation, the SLE progressively tightens upon pronation and supination by wrapping around the radial neck. Tightening of the SLE during forearm rotation provides transverse and longitudinal stability to the forearm, mainly in maximal pronation and supination. The SLE is a true ligament and provides forearm stability when it is stretched in pronation and supination.

Structural, electronic, and optical properties of representative Cu-flavonoid complexes.

PubMed

Lekka, Ch E; Ren, Jun; Meng, Sheng; Kaxiras, Efthimios

2009-05-07

We present density functional theory (DFT) results on the structural, electronic, and optical properties of Cu-flavonoid complexes for molar ratios 1:1, 1:2, and 1:3. We find that the preferred chelating site is close to the 4-oxo group and in particular the 3-4 site followed by the 3'-4' dihydroxy group in ring B. For the Cu-quercetin complexes, the large bathochromic shift of the first absorbance band upon complexation, which is in good agreement with experimental UV-vis spectra, results from the reduction of the electronic energy gap. The HOMO states for these complexes are characterized by pi-bonding between the Cu d orbitals and the C, O p orbitals except for the case of 1:1 complex (spin minority), which corresponds to sigma-type bonds. The LUMO states are attributed to the contribution of Cu p(z) orbitals. Consequently, the main features of the first optical absorption maxima are essentially due to pi --> pi transitions, while the 1:1 complex exhibits also sigma --> pi transitions. Our optical absorption calculations based on time-dependent DFT demonstrate that the 1:1 complex is responsible for the spectroscopic features at pH 5.5, whereas the 1:2 complex is mainly the one responsible for the characteristic spectra at pH 7.4. These theoretical predictions explain in detail the behavior of the optical absorption for the Cu-flavonoid complexes observed in experiments and are thus useful in elucidating the complexation mechanism and antioxidant activity of flavonoids.

Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods.

PubMed

Qu, Kaiyang; Han, Ke; Wu, Song; Wang, Guohua; Wei, Leyi

2017-09-22

DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF), is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.

Feature Selection and Pedestrian Detection Based on Sparse Representation.

PubMed

Yao, Shihong; Wang, Tao; Shen, Weiming; Pan, Shaoming; Chong, Yanwen; Ding, Fei

2015-01-01

Pedestrian detection have been currently devoted to the extraction of effective pedestrian features, which has become one of the obstacles in pedestrian detection application according to the variety of pedestrian features and their large dimension. Based on the theoretical analysis of six frequently-used features, SIFT, SURF, Haar, HOG, LBP and LSS, and their comparison with experimental results, this paper screens out the sparse feature subsets via sparse representation to investigate whether the sparse subsets have the same description abilities and the most stable features. When any two of the six features are fused, the fusion feature is sparsely represented to obtain its important components. Sparse subsets of the fusion features can be rapidly generated by avoiding calculation of the corresponding index of dimension numbers of these feature descriptors; thus, the calculation speed of the feature dimension reduction is improved and the pedestrian detection time is reduced. Experimental results show that sparse feature subsets are capable of keeping the important components of these six feature descriptors. The sparse features of HOG and LSS possess the same description ability and consume less time compared with their full features. The ratios of the sparse feature subsets of HOG and LSS to their full sets are the highest among the six, and thus these two features can be used to best describe the characteristics of the pedestrian and the sparse feature subsets of the combination of HOG-LSS show better distinguishing ability and parsimony.

Application of machine learning on brain cancer multiclass classification

NASA Astrophysics Data System (ADS)

Panca, V.; Rustam, Z.

2017-07-01

Classification of brain cancer is a problem of multiclass classification. One approach to solve this problem is by first transforming it into several binary problems. The microarray gene expression dataset has the two main characteristics of medical data: extremely many features (genes) and only a few number of samples. The application of machine learning on microarray gene expression dataset mainly consists of two steps: feature selection and classification. In this paper, the features are selected using a method based on support vector machine recursive feature elimination (SVM-RFE) principle which is improved to solve multiclass classification, called multiple multiclass SVM-RFE. Instead of using only the selected features on a single classifier, this method combines the result of multiple classifiers. The features are divided into subsets and SVM-RFE is used on each subset. Then, the selected features on each subset are put on separate classifiers. This method enhances the feature selection ability of each single SVM-RFE. Twin support vector machine (TWSVM) is used as the method of the classifier to reduce computational complexity. While ordinary SVM finds single optimum hyperplane, the main objective Twin SVM is to find two non-parallel optimum hyperplanes. The experiment on the brain cancer microarray gene expression dataset shows this method could classify 71,4% of the overall test data correctly, using 100 and 1000 genes selected from multiple multiclass SVM-RFE feature selection method. Furthermore, the per class results show that this method could classify data of normal and MD class with 100% accuracy.

Embedded feature ranking for ensemble MLP classifiers.

PubMed

Windeatt, Terry; Duangsoithong, Rakkrit; Smith, Raymond

2011-06-01

A feature ranking scheme for multilayer perceptron (MLP) ensembles is proposed, along with a stopping criterion based upon the out-of-bootstrap estimate. To solve multi-class problems feature ranking is combined with modified error-correcting output coding. Experimental results on benchmark data demonstrate the versatility of the MLP base classifier in removing irrelevant features.

Effects of Normal Aging on Memory for Multiple Contextual Features

ERIC Educational Resources Information Center

Gagnon, Sylvain; Soulard, Kathleen; Brasgold, Melissa; Kreller, Joshua

2007-01-01

Twenty-four younger (18-35 years) and 24 older adult participants (65 or older) were exposed to three experimental conditions involving the memorization words and their associated contextual features, with contextual feature complexity increasing from Conditions 1 to 3. In Condition 1, words presented varied only on one binary feature (color,…

Experimental pragmatics: a Gricean turn in the study of language.

PubMed

Noveck, Ira A; Reboul, Anne

2008-11-01

Discerning the meaning of an utterance requires not only mastering grammar and knowing the meanings of words but also understanding the communicative (i.e., pragmatic) features of language. Although it has been an ever present aspect of linguistic analyses and discussions, it is only over the last ten years or so that cognitive scientists have been investigating--in a concerted fashion--the pragmatic features of language experimentally. We begin by highlighting Paul Grice's contributions to ordinary language philosophy and show how it has led to this active area of experimental investigation. We then focus on two exemplary phenomena--'scalar inference' and 'reference resolution'--before considering other topics that fit into the paradigm known as 'experimental pragmatics'.

Deep Correlated Holistic Metric Learning for Sketch-Based 3D Shape Retrieval.

PubMed

Dai, Guoxian; Xie, Jin; Fang, Yi

2018-07-01

How to effectively retrieve desired 3D models with simple queries is a long-standing problem in computer vision community. The model-based approach is quite straightforward but nontrivial, since people could not always have the desired 3D query model available by side. Recently, large amounts of wide-screen electronic devices are prevail in our daily lives, which makes the sketch-based 3D shape retrieval a promising candidate due to its simpleness and efficiency. The main challenge of sketch-based approach is the huge modality gap between sketch and 3D shape. In this paper, we proposed a novel deep correlated holistic metric learning (DCHML) method to mitigate the discrepancy between sketch and 3D shape domains. The proposed DCHML trains two distinct deep neural networks (one for each domain) jointly, which learns two deep nonlinear transformations to map features from both domains into a new feature space. The proposed loss, including discriminative loss and correlation loss, aims to increase the discrimination of features within each domain as well as the correlation between different domains. In the new feature space, the discriminative loss minimizes the intra-class distance of the deep transformed features and maximizes the inter-class distance of the deep transformed features to a large margin within each domain, while the correlation loss focused on mitigating the distribution discrepancy across different domains. Different from existing deep metric learning methods only with loss at the output layer, our proposed DCHML is trained with loss at both hidden layer and output layer to further improve the performance by encouraging features in the hidden layer also with desired properties. Our proposed method is evaluated on three benchmarks, including 3D Shape Retrieval Contest 2013, 2014, and 2016 benchmarks, and the experimental results demonstrate the superiority of our proposed method over the state-of-the-art methods.

Experimental and theoretical studies of dipole and quadrupole contributions to the vanadium K-edge XANES for VOPO4.2H2O xerogel

NASA Astrophysics Data System (ADS)

Poumellec, B.; Kraizman, V.; Aifa, Y.; Cortès, R.; Novakovich, A.; Vedrinskii, R.

1998-09-01

Angular dependence of the vanadium K-edge x-ray appearance near-edge structure (XANES) for the VOPO4.2H2O xerogel is thoroughly studied both experimentally and theoretically. The main attention is paid to the pre-edge fine structure (PEFS) of the spectra which was shown earlier to be a useful tool for the atomic short order investigations. Good quantitative agreement between theory and experiment obtained for both dipole and quadrupole contributions to the spectra proves validity of the calculation method developed and enables us to ascertain the nature of all the features in the PEFS's. The p-d mixture effect due to distortion of the central coordination octahedron and the quadrupole transitions are proved to be the only mechanisms responsible for the PEFS formation in the case considered. We show that in order to achieve quantitative agreement between experimental and theoretical spectra, it is necessary to include the effect of atomic vibrations, which makes the forbidden transitions to molecular orbitals of the central octahedron (MOCO's) dipole allowed, and to take into account deviation of the crystal layers from the substrate plane, which is not a single crystal but a texture.

ICG: a wiki-driven knowledgebase of internal control genes for RT-qPCR normalization.

PubMed

Sang, Jian; Wang, Zhennan; Li, Man; Cao, Jiabao; Niu, Guangyi; Xia, Lin; Zou, Dong; Wang, Fan; Xu, Xingjian; Han, Xiaojiao; Fan, Jinqi; Yang, Ye; Zuo, Wanzhu; Zhang, Yang; Zhao, Wenming; Bao, Yiming; Xiao, Jingfa; Hu, Songnian; Hao, Lili; Zhang, Zhang

2018-01-04

Real-time quantitative PCR (RT-qPCR) has become a widely used method for accurate expression profiling of targeted mRNA and ncRNA. Selection of appropriate internal control genes for RT-qPCR normalization is an elementary prerequisite for reliable expression measurement. Here, we present ICG (http://icg.big.ac.cn), a wiki-driven knowledgebase for community curation of experimentally validated internal control genes as well as their associated experimental conditions. Unlike extant related databases that focus on qPCR primers in model organisms (mainly human and mouse), ICG features harnessing collective intelligence in community integration of internal control genes for a variety of species. Specifically, it integrates a comprehensive collection of more than 750 internal control genes for 73 animals, 115 plants, 12 fungi and 9 bacteria, and incorporates detailed information on recommended application scenarios corresponding to specific experimental conditions, which, collectively, are of great help for researchers to adopt appropriate internal control genes for their own experiments. Taken together, ICG serves as a publicly editable and open-content encyclopaedia of internal control genes and accordingly bears broad utility for reliable RT-qPCR normalization and gene expression characterization in both model and non-model organisms. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Piezoelectric Driving of Vibration Conveyors: An Experimental Assessment

PubMed Central

Rade, Domingos Alves; de Albuquerque, Emerson Bastos; Figueira, Leandro Chaves; Carvalho, João Carlos Mendes

2013-01-01

Vibratory feeders or vibratory conveyors have been widely used for the transport and orientation of individual parts and bulk materials in many branches of industrial activity. From the designer's standpoint, the current endeavor is to conceive efficient vibratory feeders, satisfying constraints of power consumption, vibration transmission and noise emission. Moreover, the interest in the reduction of maintenance cost is always present. In this context, this paper investigates experimentally the concept of vibratory conveying based on the use of piezoelectric materials for motion generation. A small-size prototype of a linear conveyor, in which lead-zirconate-titanate (PZT) patches are bonded to the resilient elements, is described. One of the main design goals is that the prototype is intended to be fed directly from the electric network, aiming at avoiding the use of electronic equipment for driving. To comply with this feature and, at the same time, enable to adjust the transport velocity, a mechanical device has been conceived in such a way that the first natural frequency of the conveyor can be changed. It is shown that the transport velocity is determined by the proximity between the excitation frequency and the first natural frequency of the conveyor. The experimental tests performed to characterize the dynamic behavior of the prototype are described and the range of transport velocities is determined. PMID:23867743

Continuous Beam Steering Through Broadside Using Asymmetrically Modulated Goubau Line Leaky-Wave Antennas.

PubMed

Tang, Xiao-Lan; Zhang, Qingfeng; Hu, Sanming; Zhuang, Yaqiang; Kandwal, Abhishek; Zhang, Ge; Chen, Yifan

2017-09-15

Goubau line is a single-conductor transmission line, featuring easy integration and low-loss transmission properties. Here, we propose a periodic leaky-wave antenna (LWA) based on planar Goubau transmission line on a thin dielectric substrate. The leaky-wave radiations are generated by introducing periodic modulations along the Goubau line. In this way, the surface wave, which is slow-wave mode supported by the Goubau line, achieves an additional momentum and hence enters the fast-wave region for radiations. By employing the periodic modulations, the proposed Goubau line LWAs are able to continuously steer the main beam from backward to forward within the operational frequency range. However, the LWAs usually suffer from a low radiation efficiency at the broadside direction. To overcome this drawback, we explore both transversally and longitudinally asymmetrical modulations to the Goubau line. Theoretical analysis, numerical simulations and experimental results are given in comparison with the symmetrical LWAs. It is demonstrated that the asymmetrical modulations significantly improve the radiation efficiency of LWAs at the broadside. Furthermore, the measurement results agree well with the numerical ones, which experimentally validates the proposed LWA structures. These novel Goubau line LWAs, experimentally demonstrated and validated at microwave frequencies, show also great potential for millimeter-wave and terahertz systems.

Optimization of a miniature Maglev ventricular assist device for pediatric circulatory support.

PubMed

Zhang, Juntao; Koert, Andrew; Gellman, Barry; Gempp, Thomas M; Dasse, Kurt A; Gilbert, Richard J; Griffith, Bartley P; Wu, Zhongjun J

2007-01-01

A miniature Maglev blood pump based on magnetically levitated bearingless technology is being developed and optimized for pediatric patients. We performed impeller optimization by characterizing the hemodynamic and hemocompatibility performances using a combined computational and experimental approach. Both three-dimensional flow features and hemolytic characteristics were analyzed using computational fluid dynamics (CFD) modeling. Hydraulic pump performances and hemolysis levels of three different impeller designs were quantified and compared numerically. Two pump prototypes were constructed from the two impeller designs and experimentally tested. Comparison of CFD predictions with experimental results showed good agreement. The optimized impeller remarkably increased overall pump hydraulic output by more than 50% over the initial design. The CFD simulation demonstrated a clean and streamlined flow field in the main flow path. The numerical results by hemolysis model indicated no significant high shear stress regions. Through the use of CFD analysis and bench-top testing, the small pediatric pump was optimized to achieve a low level of blood damage and improved hydraulic performance and efficiency. The Maglev pediatric blood pump is innovative due to its small size, very low priming volume, excellent hemodynamic and hematologic performance, and elimination of seal-related and bearing-related failures due to adoption of magnetically levitated bearingless motor technology, making it ideal for pediatric applications.

Remote synchronization of amplitudes across an experimental ring of non-linear oscillators

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

Minati, Ludovico, E-mail: lminati@ieee.org, E-mail: ludovico.minati@unitn.it, E-mail: lminati@istituto-besta.it

In this paper, the emergence of remote synchronization in a ring of 32 unidirectionally coupled non-linear oscillators is reported. Each oscillator consists of 3 negative voltage gain stages connected in a loop to which two integrators are superimposed and receives input from its preceding neighbour via a “mixing” stage whose gains form the main system control parameters. Collective behaviour of the network is investigated numerically and experimentally, based on a custom-designed circuit board featuring 32 field-programmable analog arrays. A diverse set of synchronization patterns is observed depending on the control parameters. While phase synchronization ensues globally, albeit imperfectly, for certainmore » control parameter values, amplitudes delineate subsets of non-adjacent but preferentially synchronized nodes; this cannot be trivially explained by synchronization paths along sequences of structurally connected nodes and is therefore interpreted as representing a form of remote synchronization. Complex topology of functional synchronization thus emerges from underlying elementary structural connectivity. In addition to the Kuramoto order parameter and cross-correlation coefficient, other synchronization measures are considered, and preliminary findings suggest that generalized synchronization may identify functional relationships across nodes otherwise not visible. Further work elucidating the mechanism underlying this observation of remote synchronization is necessary, to support which experimental data and board design materials have been made freely downloadable.« less

Remote synchronization of amplitudes across an experimental ring of non-linear oscillators.

PubMed

Minati, Ludovico

2015-12-01

In this paper, the emergence of remote synchronization in a ring of 32 unidirectionally coupled non-linear oscillators is reported. Each oscillator consists of 3 negative voltage gain stages connected in a loop to which two integrators are superimposed and receives input from its preceding neighbour via a "mixing" stage whose gains form the main system control parameters. Collective behaviour of the network is investigated numerically and experimentally, based on a custom-designed circuit board featuring 32 field-programmable analog arrays. A diverse set of synchronization patterns is observed depending on the control parameters. While phase synchronization ensues globally, albeit imperfectly, for certain control parameter values, amplitudes delineate subsets of non-adjacent but preferentially synchronized nodes; this cannot be trivially explained by synchronization paths along sequences of structurally connected nodes and is therefore interpreted as representing a form of remote synchronization. Complex topology of functional synchronization thus emerges from underlying elementary structural connectivity. In addition to the Kuramoto order parameter and cross-correlation coefficient, other synchronization measures are considered, and preliminary findings suggest that generalized synchronization may identify functional relationships across nodes otherwise not visible. Further work elucidating the mechanism underlying this observation of remote synchronization is necessary, to support which experimental data and board design materials have been made freely downloadable.

A cytological and experimental study of the neuropil and primary olfactory afferences to the piriform cortex.

PubMed

Vargas-Barroso, Víctor; Larriva-Sahd, Jorge

2013-09-01

The microscopic organization of the piriform cortex (PC) was studied in normal and experimental material from adult albino rats. In rapid-Golgi specimens a set of collaterals from the lateral olfactory tract (i.e., sublayer Ia) to the neuropil of the Layer II (LII) was identified. Specimens from experimental animals that received electrolytic lesion of the main olfactory bulb three days before sacrificing, were further processed for pre-embedding immunocytochemistry to the enzyme glutamic acid decarboxylase 67 (GAD 67). This novel approach permitted a simultaneous visualization at electron microscopy of both synaptic degeneration and GAD67-immunoreactive (GAD-I) sites. Degenerating and GAD-I synapses were separately found in the neuropil of Layers I and II of the PC. Previously overlooked patches of neuropil were featured in sublayer Ia. These areas consisted of dendritic and axonal processes including four synaptic types. Tridimensional reconstructions from serial thin sections from LI revealed the external appearance of the varicose and tubular dendrites as well as the synaptic terminals therein. The putative source(s) of processes to the neuropil of sublayer Ia is discussed in the context of the internal circuitry of the PC and an alternative model is introduced. Copyright © 2013 Wiley Periodicals, Inc.

On-line experimental validation of a model-based diagnostic algorithm dedicated to a solid oxide fuel cell system

NASA Astrophysics Data System (ADS)

Polverino, Pierpaolo; Esposito, Angelo; Pianese, Cesare; Ludwig, Bastian; Iwanschitz, Boris; Mai, Andreas

2016-02-01

In the current energetic scenario, Solid Oxide Fuel Cells (SOFCs) exhibit appealing features which make them suitable for environmental-friendly power production, especially for stationary applications. An example is represented by micro-combined heat and power (μ-CHP) generation units based on SOFC stacks, which are able to produce electric and thermal power with high efficiency and low pollutant and greenhouse gases emissions. However, the main limitations to their diffusion into the mass market consist in high maintenance and production costs and short lifetime. To improve these aspects, the current research activity focuses on the development of robust and generalizable diagnostic techniques, aimed at detecting and isolating faults within the entire system (i.e. SOFC stack and balance of plant). Coupled with appropriate recovery strategies, diagnosis can prevent undesired system shutdowns during faulty conditions, with consequent lifetime increase and maintenance costs reduction. This paper deals with the on-line experimental validation of a model-based diagnostic algorithm applied to a pre-commercial SOFC system. The proposed algorithm exploits a Fault Signature Matrix based on a Fault Tree Analysis and improved through fault simulations. The algorithm is characterized on the considered system and it is validated by means of experimental induction of faulty states in controlled conditions.

Influence of surface roughness on the elastic-light scattering patterns of micron-sized aerosol particles

NASA Astrophysics Data System (ADS)

Auger, J.-C.; Fernandes, G. E.; Aptowicz, K. B.; Pan, Y.-L.; Chang, R. K.

2010-04-01

The relation between the surface roughness of aerosol particles and the appearance of island-like features in their angle-resolved elastic-light scattering patterns is investigated both experimentally and with numerical simulation. Elastic scattering patterns of polystyrene spheres, Bacillus subtilis spores and cells, and NaCl crystals are measured and statistical properties of the island-like intensity features in their patterns are presented. The island-like features for each class of particle are found to be similar; however, principal-component analysis applied to extracted features is able to differentiate between some of the particle classes. Numerically calculated scattering patterns of Chebyshev particles and aggregates of spheres are analyzed and show qualitative agreement with experimental results.

Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences.

PubMed

An, Ji-Yong; Meng, Fan-Rong; You, Zhu-Hong; Fang, Yu-Hong; Zhao, Yu-Jun; Zhang, Ming

2016-01-01

We propose a novel computational method known as RVM-LPQ that combines the Relevance Vector Machine (RVM) model and Local Phase Quantization (LPQ) to predict PPIs from protein sequences. The main improvements are the results of representing protein sequences using the LPQ feature representation on a Position Specific Scoring Matrix (PSSM), reducing the influence of noise using a Principal Component Analysis (PCA), and using a Relevance Vector Machine (RVM) based classifier. We perform 5-fold cross-validation experiments on Yeast and Human datasets, and we achieve very high accuracies of 92.65% and 97.62%, respectively, which is significantly better than previous works. To further evaluate the proposed method, we compare it with the state-of-the-art support vector machine (SVM) classifier on the Yeast dataset. The experimental results demonstrate that our RVM-LPQ method is obviously better than the SVM-based method. The promising experimental results show the efficiency and simplicity of the proposed method, which can be an automatic decision support tool for future proteomics research.

KEWPIE2: A cascade code for the study of dynamical decay of excited nuclei

NASA Astrophysics Data System (ADS)

Lü, Hongliang; Marchix, Anthony; Abe, Yasuhisa; Boilley, David

2016-03-01

KEWPIE-a cascade code devoted to investigating the dynamical decay of excited nuclei, specially designed for treating very low probability events related to the synthesis of super-heavy nuclei formed in fusion-evaporation reactions-has been improved and rewritten in C++ programming language to become KEWPIE2. The current version of the code comprises various nuclear models concerning the light-particle emission, fission process and statistical properties of excited nuclei. General features of the code, such as the numerical scheme and the main physical ingredients, are described in detail. Some typical calculations having been performed in the present paper clearly show that theoretical predictions are generally in accordance with experimental data. Furthermore, since the values of some input parameters cannot be determined neither theoretically nor experimentally, a sensibility analysis is presented. To this end, we systematically investigate the effects of using different parameter values and reaction models on the final results. As expected, in the case of heavy nuclei, the fission process has the most crucial role to play in theoretical predictions. This work would be essential for numerical modeling of fusion-evaporation reactions.

Physics of protein folding

NASA Astrophysics Data System (ADS)

Finkelstein, A. V.; Galzitskaya, O. V.

2004-04-01

Protein physics is grounded on three fundamental experimental facts: protein, this long heteropolymer, has a well defined compact three-dimensional structure; this structure can spontaneously arise from the unfolded protein chain in appropriate environment; and this structure is separated from the unfolded state of the chain by the “all-or-none” phase transition, which ensures robustness of protein structure and therefore of its action. The aim of this review is to consider modern understanding of physical principles of self-organization of protein structures and to overview such important features of this process, as finding out the unique protein structure among zillions alternatives, nucleation of the folding process and metastable folding intermediates. Towards this end we will consider the main experimental facts and simple, mostly phenomenological theoretical models. We will concentrate on relatively small (single-domain) water-soluble globular proteins (whose structure and especially folding are much better studied and understood than those of large or membrane and fibrous proteins) and consider kinetic and structural aspects of transition of initially unfolded protein chains into their final solid (“native”) 3D structures.

Role of JNK isoforms in the kainic acid experimental model of epilepsy and neurodegeneration.

PubMed

Auladell, Carme; de Lemos, Luisa; Verdaguer, Ester; Ettcheto, Miren; Busquets, Oriol; Lazarowski, Alberto; Beas-Zarate, Carlos; Olloquequi, Jordi; Folch, Jaume; Camins, Antoni

2017-01-01

Chemoconvulsants that induce status epilepticus in rodents have been widely used over the past decades due to their capacity to reproduce with high similarity neuropathological and electroencephalographic features observed in patients with temporal lobe epilepsy (TLE). Kainic acid  is one of the most used chemoconvulsants in experimental models. KA administration mainly induces neuronal loss in the hippocampus. We focused the present review inthe c-Jun N-terminal kinase-signaling pathway (JNK), since it has been shown to play a key role in the process of neuronal death following KA activation. Among the three isoforms of JNK (JNK1, JNK2, JNK3), JNK3 is widely localized in the majority of areas of the hippocampus, whereas JNK1 levels are located exclusively in the CA3 and CA4 areas and in dentate gyrus. Disruption of the gene encoding JNK3 in mice renders neuroprotection to KA, since these animals showed a reduction in seizure activity and a diminution in hippocampal neuronal apoptosis. In light of this, JNK3 could be a promising subcellular target for future therapeutic interventions in epilepsy.

Results of studying creep and long-term strength of metals at the Institute of Mechanics at the Lomonosov Moscow State University (To Yu. N. Rabotnov's Anniversary)

NASA Astrophysics Data System (ADS)

Lokoshchenko, A. M.

2014-01-01

Basic results of experimental and theoretical research of creep processes and long-term strength of metals obtained by researchers of the Institute of Mechanics at the Lomonosov Moscow State University are presented. These results further develop and refine the kinetic theory of creep and long-duration strength proposed by Yu. N. Rabotnov. Some problems arising in formulating various types of kinetic equations and describing experimental data for materials that can be considered as statically homogeneous materials (in studying the process of deformation and rupture of such materials, there is no need to study the evolution of individual cracks) are considered. The main specific features of metal creep models at constant and variable stresses, in uniaxial and complex stress states, and with allowance for one or two damage parameters are described. Criterial and kinetic approaches used to determine long-term strength under conditions of a complex stress state are considered. Methods of modeling the metal behavior in an aggressive medium are described. A possibility of using these models for solving engineering problems is demonstrated.

Effect of the size of experimental channels of the lead slowing-down spectrometer SVZ-100 (Institute for Nuclear Research, Moscow) on the moderation constant

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

Latysheva, L. N.; Bergman, A. A.; Sobolevsky, N. M., E-mail: sobolevs@inr.ru

Lead slowing-down (LSD) spectrometers have a low energy resolution (about 30%), but their luminosity is 10{sup 3} to 10{sup 4} times higher than that of time-of-flight (TOF) spectrometers. A high luminosity of LSD spectrometers makes it possible to use them to measure neutron cross section for samples of mass about several micrograms. These features specify a niche for the application of LSD spectrometers in measuring neutron cross sections for elements hardly available in macroscopic amounts-in particular, for actinides. A mathematical simulation of the parameters of SVZ-100 LSD spectrometer of the Institute for Nuclear Research (INR, Moscow) is performed in themore » present study on the basis of the MCNPX code. It is found that the moderation constant, which is the main parameter of LSD spectrometers, is highly sensitive to the size and shape of detecting volumes in calculations and, hence, to the real size of experimental channels of the LSD spectrometer.« less

Photonic surface waves on metamaterial interfaces

NASA Astrophysics Data System (ADS)

Takayama, O.; Bogdanov, A. A.; Lavrinenko, A. V.

2017-11-01

A surface wave (SW) in optics is a light wave, which is supported at an interface of two dissimilar media and propagates along the interface with its field amplitude exponentially decaying away from the boundary. Research on surface waves has been flourishing in the last few decades due to their unique properties of surface sensitivity and field localization. These features have resulted in applications in nano-guiding, sensing, light-trapping and imaging based on near-field techniques, contributing to the establishment of nanophotonics as a field of research. Up to now, a wide variety of surface waves has been investigated in numerous material and structure settings. This article reviews the recent progress and development in the physics of SWs localized at metamaterial interfaces, as well as bulk media in order to provide broader perspectives on optical surface waves in general. For each type of surface wave, we discuss the material and structural platforms. We mainly focus on experimental realizations in the visible and near-infrared wavelength ranges. We also address existing and potential application of SWs in chemical and biological sensing, and experimental excitation and characterization methods.

Mineralogical, Spectral, and Compositional Changes During Heating of Hydrous Carbonaceous Chondrites

NASA Technical Reports Server (NTRS)

Nakamura, T.; Matsuoka, M.; Yamashita, S.; Sato, Y.; Mogi, K.; Enokido, Y.; Nakata, A.; Okumura, S.; Furukawa, Y.; Zolensky, M.

2017-01-01

Hydrous carbonaceous chondrites experienced hydration and subsequent dehydration by heating, which resulted in a variety of mineralogical and spectral features [e. g., 1-6]. The degree of heating is classified according to heating stage (HS) II to IV based on mineralogy of phyllosilicates [2], because they change, with elevating temperature, to poorly crystal-line phases and subsequently to aggregates of small secondary anhydrous silicates of mainly olivine. Heating of hydrous carbonaceous chondrites also causes spectral changes and volatile loss [3-6]. Experimental heating of Murchison CM chondrite showed flattening of whole visible-near infrared spectra, especially weakening of the 3µm band strength [1, 4, 7]. In order to understand mineralogical, spectral, and compositional changes during heating of hydrous carbonaceous chondrites, we have carried out systematic investigation of mineralogy, reflectance spectra, and volatile composition of hydrated and dehydrated carbonaceous chondrites as well as experimentally-heated hydrous carbonaceous chondrites. In addition, we investigated reflectance spectra of tochilinite that is a major phase of CM chondrites and has a low dehydration temperature (250degC).

Robust tracking control of an IPMC actuator using nonsingular terminal sliding mode

NASA Astrophysics Data System (ADS)

Khawwaf, Jasim; Zheng, Jinchuan; Lu, Renquan; Al-Ghanimi, Ali; Kazem, Bahaa I.; Man, Zhihong

2017-09-01

Ionic polymer metal composite (IPMC) is a highly innovative material that has recently gained attention in many fields such as medical, biomimetic, and micro/nano underwater applications. The main characteristic of IPMC lies in its ability to achieve a large deflection under a fairly low driving voltage. Moreover, its agile, light weight, noiseless and flexible features render it well suited for certain specific applications. Like other smart materials, such as piezoelectric ceramics, IPMC could be used in actuators or sensors. In this paper, we study the application of IPMC as an actuator for underwater use. The goal is to develop a robust feedback controller for the IPMC actuator to track a desired reference whilst dealing with the uncertainties due to the inherent actuator nonlinearity, external disturbance or the variations of working environment. To this end, we first present a nominal model of the IPMC actuator through experimental identification. Next, a nonsingular terminal sliding mode controller is proposed. Lastly, experimental studies are conducted to verify the tracking accuracy and robustness of the designed controller.

Observation of optical domino modes in arrays of non-resonant plasmonic nanoantennas

NASA Astrophysics Data System (ADS)

Sinev, Ivan S.; Samusev, Anton K.; Voroshilov, Pavel M.; Mukhin, Ivan S.; Denisyuk, Andrey I.; Guzhva, Mikhail E.; Belov, Pavel A.; Simovski, Constantin R.

2014-09-01

Domino modes are highly-confined collectivemodes that were first predicted for a periodic arrangement of metallic parallelepipeds in far-infrared region. The main feature of domino modes is the advantageous distribution of the local electric field, which is concentrated between metallic elements (hot spots), while its penetration depth in metal is much smaller than the skin-depth. Therefore, arrays of non-resonant plasmonic nanoantennas exhibiting domino modes can be employed as broadband light trapping coatings for thin-film solar cells. However, until now in the excitation of such modes was demonstrated only in numerical simulations. Here, we for the first time demonstrate experimentally the excitation of optical domino modes in arrays of non-resonant plasmonic nanoantennas. We characterize the nanoantenna arrays produced by means of electron beam lithography both experimentally using an aperture-type near-field scanning optical microscope and numerically. The proof of domino modes concept for plasmonic arrays of nanoantennas in the visible spectral region opens new pathways for development of low-absorptive structures for effective focusing of light at the nanoscale.

Ground state, collective mode, phase soliton and vortex in multiband superconductors.

PubMed

Lin, Shi-Zeng

2014-12-10

This article reviews theoretical and experimental work on the novel physics in multiband superconductors. Multiband superconductors are characterized by multiple superconducting energy gaps in different bands with interaction between Cooper pairs in these bands. The discovery of prominent multiband superconductors MgB2 and later iron-based superconductors, has triggered enormous interest in multiband superconductors. The most recently discovered superconductors exhibit multiband features. The multiband superconductors possess novel properties that are not shared with their single-band counterpart. Examples include: the time-reversal symmetry broken state in multiband superconductors with frustrated interband couplings; the collective oscillation of number of Cooper pairs between different bands, known as the Leggett mode; and the phase soliton and fractional vortex, which are the main focus of this review. This review presents a survey of a wide range of theoretical exploratory and experimental investigations of novel physics in multiband superconductors. A vast amount of information derived from these studies is shown to highlight unusual and unique properties of multiband superconductors and to reveal the challenges and opportunities in the research on the multiband superconductivity.

Were komatiites wet?

NASA Astrophysics Data System (ADS)

Arndt, N.; Ginibre, C.; Chauvel, C.; Albarède, F.; Cheadle, M.; Herzberg, C.; Jenner, G.; Lahaye, Y.

1998-08-01

The main arguments used to support the concept that komatiites form by melting of hydrous mantle are as follows: (1) Water reduces liquidus temperatures from extreme values to lower, more “normal” temperatures. (2) Some komatiites are pyroclastic and some contain vesicles, features that have been attributed to magmatic volatiles. (3) It is claimed from experimental studies of peridotite melting that the chemical composition of komatiite requires the presence of water, as does their characteristic spinifex textures. Counterarguments are the following: (1) Loss of volatiles as hydrous komatiite approaches the surface should produce degassing textures and structures, which, though not unknown, are rare in komatiites. Degassing should produce a highly supercooled liquid that partially crystallizes to porphyritic magma; komatiites commonly erupt as phenocryst-poor, highly magnesian lavas. (2) Chemical and isotopic compositions of most komatiites indicate that their mantle source became depleted in incompatible elements soon before magma formation. Such depletion removes water, leaving a dry source. (3) The experimental data are at best ambiguous; neither the chemical composition of komatiites, nor the crystallization of spinifex, requires the presence of water. We conclude that although some rare komatiites may be hydrous, most are dry.

Experimental investigation on the miniature mixed refrigerant cooler driven by a mini-compressor

NASA Astrophysics Data System (ADS)

Chen, Gaofei; Gong, Maoqiong; Wu, Yinong

2018-05-01

Three miniature Joule-Thomson cryogenic coolers and a testing set up were built to investigate the cooling performance in this work. Shell-and-tube heat exchanger and plate fin heat exchangers with rectangular micro channels were designed to achieve high specific surface area. The main processing technology of micro mixed refrigerant cooler (MMRC) was described. The design and fabrication processing of the plate fin heat exchangers were also described. The new developed micro plate-fin type heat exchanger shows high compactness with the specific heat surface larger than 1.0x104 m2/m3. The results of experimental investigations on miniature mixed refrigerant J-T cryogenic coolers driven by a Mini-Compressor were discussed. The performance evaluation and comparison of the three coolers was made to find out the features for each type of cooler. Expressions of refrigeration coefficient and exergy efficiency were pointed out. No-load temperature of about 112 K, and the cooling power of 4.0W at 118K with the input power of 120W is achieved. The exergy efficiency of the SJTC is 5.14%.

Density and magnetic fluctuations in type III-ELM pedestal evolution in JET: experimental and numerical characterization

NASA Astrophysics Data System (ADS)

De Masi, G.; Predebon, I.; Spagnolo, S.; Meneses, L.; Delabie, E.; Lupelli, I.; Hillesheim, J. C.; Maggi, C.; Contributors, JET

2018-04-01

Density and magnetic fluctuation measurements in low-β type-III ELM discharges are obtained in the Joint European Torus (JET). They are observed during the inter-ELM pedestal evolution, after the LH transition phase, at about 60-70 kHz. Density fluctuations are measured with a correlation reflectometer system installed on the low-field side and they are localized at the pedestal top. Magnetic fluctuations with a spatial scale k_yρ_i˜ 0.1 are measured through a high resolution coil array. The main features and the relations with local plasma parameters are presented. The nature of these fluctuations is discussed along with linear gyrokinetic simulations. Ion temperature gradient (ITG) modes are the dominant instabilities in the frequency range of interest. In terms of radial localization, typical oscillation frequency and qualitative relation with the possible linear drive, ITG modes are consistent with the experimental density fluctuations measurements. Micro-tearing modes (MTMs), found unstable with a lower growth rate, appear a possible explanation for magnetic fluctuations in terms of typical wavenumbers and direction of propagation.

Characterization of origami shape memory metamaterials (SMMM) made of bio-polymer blends

NASA Astrophysics Data System (ADS)

Kshad, Mohamed Ali E.; Naguib, Hani E.

2016-04-01

Shape memory materials (SMMs) are materials that can return to their virgin state and release mechanically induced strains by external stimuli. Shape memory polymers (SMPs) are a class of SMMs that show a high shape recoverability and which have attractive potential for structural applications. In this paper, we experimentally study the shape memory effect of origami based metamaterials. The main focus is on the Muira origami metamaterials. The fabrication technique used to produce origami structure is direct molding where all the geometrical features are molded from thermally virgin polymers without post folding of flat sheets. The study shows experimental investigations of shape memory metamaterials (SMMMs) made of SMPs that can be used in different applications such as medicine, robotics, and lightweight structures. The origami structure made from SMP blends, activated with uniform heating. The effect of blend composition on the shape memory behavior was studied. Also the influence of the thermomechanical and the viscoelastic properties of origami unit cell on the activation process have been discussed, and stress relaxation and shape recovery were investigated. Activation process of the unit cell has been demonstrated.

Theoretical investigations of the role played by quercetinase enzymes upon the flavonoids oxygenolysis mechanism.

PubMed

Antonczak, Serge; Fiorucci, Sébastien; Golebiowski, Jérôme; Cabrol-Bass, Daniel

2009-03-14

Quercetinase enzymatic activity consists in the addition of dioxygen onto flavonoids, some natural polyphenol compounds, leading to the production of both molecular carbon monoxide and to the structurally related depside compound. Experimental studies have reported degradation rates of various flavonoids by such enzymes that can not be directly correlated neither to the number nor to the place of the hydroxyl groups. In order to decipher the role of these functions, we have theoretically characterised the stationary points of various flavonoids oxygenolysis mechanisms by density functional quantum methods. Thus in the present study are reported the main energetic, structural and electronic features that drive this degradation. Together with previous analysis from MD simulations taking into account the dynamic behaviour of the substrate embedded in the enzyme cavity, the present results show that the role of the enzyme, in terms of structural and electronic effects, can not be neglected. Thus, we propose here that deformations of the substrate induced by the enzyme could originate the differences in the degradation rates experimentally observed.

Mixing characterisation of full-scale membrane bioreactors: CFD modelling with experimental validation.

PubMed

Brannock, M; Wang, Y; Leslie, G

2010-05-01

Membrane Bioreactors (MBRs) have been successfully used in aerobic biological wastewater treatment to solve the perennial problem of effective solids-liquid separation. The optimisation of MBRs requires knowledge of the membrane fouling, biokinetics and mixing. However, research has mainly concentrated on the fouling and biokinetics (Ng and Kim, 2007). Current methods of design for a desired flow regime within MBRs are largely based on assumptions (e.g. complete mixing of tanks) and empirical techniques (e.g. specific mixing energy). However, it is difficult to predict how sludge rheology and vessel design in full-scale installations affects hydrodynamics, hence overall performance. Computational Fluid Dynamics (CFD) provides a method for prediction of how vessel features and mixing energy usage affect the hydrodynamics. In this study, a CFD model was developed which accounts for aeration, sludge rheology and geometry (i.e. bioreactor and membrane module). This MBR CFD model was then applied to two full-scale MBRs and was successfully validated against experimental results. The effect of sludge settling and rheology was found to have a minimal impact on the bulk mixing (i.e. the residence time distribution).

Detecting experimental techniques and selecting relevant documents for protein-protein interactions from biomedical literature.

PubMed

Wang, Xinglong; Rak, Rafal; Restificar, Angelo; Nobata, Chikashi; Rupp, C J; Batista-Navarro, Riza Theresa B; Nawaz, Raheel; Ananiadou, Sophia

2011-10-03

The selection of relevant articles for curation, and linking those articles to experimental techniques confirming the findings became one of the primary subjects of the recent BioCreative III contest. The contest's Protein-Protein Interaction (PPI) task consisted of two sub-tasks: Article Classification Task (ACT) and Interaction Method Task (IMT). ACT aimed to automatically select relevant documents for PPI curation, whereas the goal of IMT was to recognise the methods used in experiments for identifying the interactions in full-text articles. We proposed and compared several classification-based methods for both tasks, employing rich contextual features as well as features extracted from external knowledge sources. For IMT, a new method that classifies pair-wise relations between every text phrase and candidate interaction method obtained promising results with an F1 score of 64.49%, as tested on the task's development dataset. We also explored ways to combine this new approach and more conventional, multi-label document classification methods. For ACT, our classifiers exploited automatically detected named entities and other linguistic information. The evaluation results on the BioCreative III PPI test datasets showed that our systems were very competitive: one of our IMT methods yielded the best performance among all participants, as measured by F1 score, Matthew's Correlation Coefficient and AUC iP/R; whereas for ACT, our best classifier was ranked second as measured by AUC iP/R, and also competitive according to other metrics. Our novel approach that converts the multi-class, multi-label classification problem to a binary classification problem showed much promise in IMT. Nevertheless, on the test dataset the best performance was achieved by taking the union of the output of this method and that of a multi-class, multi-label document classifier, which indicates that the two types of systems complement each other in terms of recall. For ACT, our system exploited a rich set of features and also obtained encouraging results. We examined the features with respect to their contributions to the classification results, and concluded that contextual words surrounding named entities, as well as the MeSH headings associated with the documents were among the main contributors to the performance.

Advanced quantitative magnetic nondestructive evaluation methods - Theory and experiment

NASA Technical Reports Server (NTRS)

Barton, J. R.; Kusenberger, F. N.; Beissner, R. E.; Matzkanin, G. A.

1979-01-01

The paper reviews the scale of fatigue crack phenomena in relation to the size detection capabilities of nondestructive evaluation methods. An assessment of several features of fatigue in relation to the inspection of ball and roller bearings suggested the use of magnetic methods; magnetic domain phenomena including the interaction of domains and inclusions, and the influence of stress and magnetic field on domains are discussed. Experimental results indicate that simplified calculations can be used to predict many features of these results; the data predicted by analytic models which use finite element computer analysis predictions do not agree with respect to certain features. Experimental analyses obtained on rod-type fatigue specimens which show experimental magnetic measurements in relation to the crack opening displacement and volume and crack depth should provide methods for improved crack characterization in relation to fracture mechanics and life prediction.

Spectral Regression Based Fault Feature Extraction for Bearing Accelerometer Sensor Signals

PubMed Central

Xia, Zhanguo; Xia, Shixiong; Wan, Ling; Cai, Shiyu

2012-01-01

Bearings are not only the most important element but also a common source of failures in rotary machinery. Bearing fault prognosis technology has been receiving more and more attention recently, in particular because it plays an increasingly important role in avoiding the occurrence of accidents. Therein, fault feature extraction (FFE) of bearing accelerometer sensor signals is essential to highlight representative features of bearing conditions for machinery fault diagnosis and prognosis. This paper proposes a spectral regression (SR)-based approach for fault feature extraction from original features including time, frequency and time-frequency domain features of bearing accelerometer sensor signals. SR is a novel regression framework for efficient regularized subspace learning and feature extraction technology, and it uses the least squares method to obtain the best projection direction, rather than computing the density matrix of features, so it also has the advantage in dimensionality reduction. The effectiveness of the SR-based method is validated experimentally by applying the acquired vibration signals data to bearings. The experimental results indicate that SR can reduce the computation cost and preserve more structure information about different bearing faults and severities, and it is demonstrated that the proposed feature extraction scheme has an advantage over other similar approaches. PMID:23202017

Automatic sleep stage classification of single-channel EEG by using complex-valued convolutional neural network.

PubMed

Zhang, Junming; Wu, Yan

2018-03-28

Many systems are developed for automatic sleep stage classification. However, nearly all models are based on handcrafted features. Because of the large feature space, there are so many features that feature selection should be used. Meanwhile, designing handcrafted features is a difficult and time-consuming task because the feature designing needs domain knowledge of experienced experts. Results vary when different sets of features are chosen to identify sleep stages. Additionally, many features that we may be unaware of exist. However, these features may be important for sleep stage classification. Therefore, a new sleep stage classification system, which is based on the complex-valued convolutional neural network (CCNN), is proposed in this study. Unlike the existing sleep stage methods, our method can automatically extract features from raw electroencephalography data and then classify sleep stage based on the learned features. Additionally, we also prove that the decision boundaries for the real and imaginary parts of a complex-valued convolutional neuron intersect orthogonally. The classification performances of handcrafted features are compared with those of learned features via CCNN. Experimental results show that the proposed method is comparable to the existing methods. CCNN obtains a better classification performance and considerably faster convergence speed than convolutional neural network. Experimental results also show that the proposed method is a useful decision-support tool for automatic sleep stage classification.

Electronic structure of atoms: atomic spectroscopy information system

NASA Astrophysics Data System (ADS)

Kazakov, V. V.; Kazakov, V. G.; Kovalev, V. S.; Meshkov, O. I.; Yatsenko, A. S.

2017-10-01

The article presents a Russian atomic spectroscopy, information system electronic structure of atoms (IS ESA) (http://grotrian.nsu.ru), and describes its main features and options to support research and training. The database contains over 234 000 records, great attention paid to experimental data and uniform filling of the database for all atomic numbers Z, including classified levels and transitions of rare earth and transuranic elements and their ions. Original means of visualization of scientific data in the form of spectrograms and Grotrian diagrams have been proposed. Presentation of spectral data in the form of interactive color charts facilitates understanding and analysis of properties of atomic systems. The use of the spectral data of the IS ESA together with its functionality is effective for solving various scientific problems and training of specialists.

Nondestructive Superresolution Imaging of Defects and Nonuniformities in Metals, Semiconductors, Dielectrics, Composites, and Plants Using Evanescent Microwaves

NASA Technical Reports Server (NTRS)

Tabib-Azar, M.; Pathak, P. S.; Ponchak, G.; LeClair, S.

1999-01-01

We have imaged and mapped material nonuniformities and defects using microwaves generated at the end of a microstripline resonator with 0.4 micrometer lateral spatial resolution at 1 GHz. Here we experimentally examine the effect of microstripline substrate permittivity, the feedline-to-resonator coupling strength, and probe tip geometry on the spatial resolution of the probe. Carbon composites, dielectrics, semiconductors, metals, and botanical samples were scanned for defects, residual stresses, subsurface features, areas of different film thickness, and moisture content. The resulting evanescent microwave probe (EMP) images are discussed. The main objective of this work is to demonstrate the overall capabilities of the EMP imaging technique as well as to discuss various probe parameters that can be used to design EMPs for different applications.

Space structures insulating material's thermophysical and radiation properties estimation

NASA Astrophysics Data System (ADS)

Nenarokomov, A. V.; Alifanov, O. M.; Titov, D. M.

2007-11-01

In many practical situations in aerospace technology it is impossible to measure directly such properties of analyzed materials (for example, composites) as thermal and radiation characteristics. The only way that can often be used to overcome these difficulties is indirect measurements. This type of measurement is usually formulated as the solution of inverse heat transfer problems. Such problems are ill-posed in mathematical sense and their main feature shows itself in the solution instabilities. That is why special regularizing methods are needed to solve them. The experimental methods of identification of the mathematical models of heat transfer based on solving the inverse problems are one of the modern effective solving manners. The objective of this paper is to estimate thermal and radiation properties of advanced materials using the approach based on inverse methods.

An efficient cloud detection method for high resolution remote sensing panchromatic imagery

NASA Astrophysics Data System (ADS)

Li, Chaowei; Lin, Zaiping; Deng, Xinpu

2018-04-01

In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.

Best Merge Region Growing with Integrated Probabilistic Classification for Hyperspectral Imagery

NASA Technical Reports Server (NTRS)

Tarabalka, Yuliya; Tilton, James C.

2011-01-01

A new method for spectral-spatial classification of hyperspectral images is proposed. The method is based on the integration of probabilistic classification within the hierarchical best merge region growing algorithm. For this purpose, preliminary probabilistic support vector machines classification is performed. Then, hierarchical step-wise optimization algorithm is applied, by iteratively merging regions with the smallest Dissimilarity Criterion (DC). The main novelty of this method consists in defining a DC between regions as a function of region statistical and geometrical features along with classification probabilities. Experimental results are presented on a 200-band AVIRIS image of the Northwestern Indiana s vegetation area and compared with those obtained by recently proposed spectral-spatial classification techniques. The proposed method improves classification accuracies when compared to other classification approaches.

An analysis of the specificity of defects embedded into (1 0 0) and (1 1 1) faceted CVD diamond microcrystals grown on Si and Mo substrates by using E/H field discharge

NASA Astrophysics Data System (ADS)

Nasieka, Iurii; Strelchuk, Victor; Naseka, Victor; Stubrov, Yuriy; Dudnik, Stanislav; Gritsina, Vasiliy; Opalev, Oleg; Koshevoy, Konstantin; Strel'nitskij, Vladimir; Tkach, Vasyl; Boyko, Mykola; Antypov, Ievgen

2018-06-01

The PE CVD method with magnetic field discharge stabilization was applied for the growth of arrays of freestanding diamond grains (island films) as well as continuous films on Mo and Si substrates with (1 1 1) and (1 0 0) faceted microcrystals, respectively. Raman, SEM, XRD and PL methods were used for search of the specific features of defects embedded into (1 0 0) and (1 1 1) faceted grains. The main characteristic differences in the defect states of the diamond island films grown on Si and Mo substrates with (1 0 0) and (1 1 1) faceted diamond microcrystals were discussed on the base of the experimental data.

Explosive attractor solutions to a universal cubic delay equation

NASA Astrophysics Data System (ADS)

Sanz-Orozco, D.; Berk, H. L.

2017-05-01

New explosive attractor solutions have been found in a universal cubic delay equation that has been studied in both the plasma and the fluid mechanics literature. Through computational simulations and analytic approximations, it is found that the oscillatory component of the explosive mode amplitude solutions are described through multi-frequency Fourier expansions with respect to a pseudo-time variable. The spectral dependence of these solutions as a function of a system parameter, ϕ , is studied. The mode amplitude that is described in the explosive regime has two main features: a well-known envelope ( t 0 - t ) - 5 / 2 , with t0 the blow-up time of the amplitude, and a spectrum of discrete oscillations with ever-increasing frequencies, which may give experimental information about the properties of a system's equilibrium.

An experimental sample of the field gamma-spectrometer based on solid state Si-photomultiplier

NASA Astrophysics Data System (ADS)

Denisov, Viktor; Korotaev, Valery; Titov, Aleksandr; Blokhina, Anastasia; Kleshchenok, Maksim

2017-05-01

Design of optical-electronic devices and systems involves the selection of such technical patterns that under given initial requirements and conditions are optimal according to certain criteria. The original characteristic of the OES for any purpose, defining its most important feature ability is a threshold detection. Based on this property, will be achieved the required functional quality of the device or system. Therefore, the original criteria and optimization methods have to subordinate to the idea of a better detectability. Generally reduces to the problem of optimal selection of the expected (predetermined) signals in the predetermined observation conditions. Thus the main purpose of optimization of the system when calculating its detectability is the choice of circuits and components that provide the most effective selection of a target.

Magnetic effect for electrochemically driven cellular convection.

PubMed

Nakabayashi, S; Inokuma, K; Karantonis, A

1999-06-01

Hydrodynamic instability analogous to Rayleigh-Bénard convection is observed in an electrolytic solution between two parallel copper wire electrodes. The laser interferometric technique can reveal the dissipation structure created by the motion of the fluid, which is controlled electrochemically. It is shown that under the presence of horizontal magnetic field the roll cells move horizontally along the electrodes. The electrochemically driven convection is simply controlled and monitored by setting and measuring the electrochemical parameters and forms many kinds of spatiotemporal patterns, especially under the magnetic field. The phenomenon is modeled by considering a Boussinesq fluid under a concentration gradient. The stability of the resulting equations is studied by linear stability analysis. The time dependent nonlinear system is investigated numerically and the main features of the experimental response are reproduced.

Experimental Research on Creep Characteristics of Nansha Soft Soil

PubMed Central

Luo, Qingzi; Chen, Xiaoping

2014-01-01

A series of tests were performed to investigate the creep characteristics of soil in interactive marine and terrestrial deposit of Pearl River Delta. The secondary consolidation test results show that the influence of consolidation pressure on coefficient of secondary consolidation is conditional, which is decided by the consolidation state. The ratio of coefficient of secondary consolidation and coefficient of compressibility C a/C c is almost a constant, and the value is 0.03. In the shear-box test, the direct sheer creep failure of soil is mainly controlled by shear stress rather than the accumulation of shear strain. The triaxial creep features are closely associated with the drainage conditions, and consolidation can weaken the effect of creep. When the soft soil has triaxial creep damage, the strain rate will increase sharply. PMID:24526925

Experimental research on creep characteristics of Nansha soft soil.

PubMed

Luo, Qingzi; Chen, Xiaoping

2014-01-01

A series of tests were performed to investigate the creep characteristics of soil in interactive marine and terrestrial deposit of Pearl River Delta. The secondary consolidation test results show that the influence of consolidation pressure on coefficient of secondary consolidation is conditional, which is decided by the consolidation state. The ratio of coefficient of secondary consolidation and coefficient of compressibility (Ca/Cc) is almost a constant, and the value is 0.03. In the shear-box test, the direct sheer creep failure of soil is mainly controlled by shear stress rather than the accumulation of shear strain. The triaxial creep features are closely associated with the drainage conditions, and consolidation can weaken the effect of creep. When the soft soil has triaxial creep damage, the strain rate will increase sharply.

Modeling study of polychlorinated dibenzo-p-dioxins and dibenzofurans behavior in flue gases under electron beam irradiation.

PubMed

Gerasimov, Gennady

2016-09-01

The efficiency of the electron beam treatment of industrial flue gases for the removal of sulfur and nitrogen oxides was investigated as applied to polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) using methods of mathematical modeling. The proposed kinetic model of the process includes mechanism of PCDD/Fs decomposition caused by their interaction with OH radicals generated in the flue gases under the electron beam (EB) irradiation as well as PCDD/Fs formation from unburned aromatic compounds. The model allows to predict the main features of the process, which are observed in pilot plant installations, as well as to evaluate the process efficiency. The results of calculations are compared with the available experimental data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multiquark resonances

DOE PAGES

Esposito, A.; Pilloni, A.; Polosa, Antonio D.

2016-12-02

Multiquark resonances are undoubtedly experimentally observed. The number of states and the amount of details on their properties have been growing over the years. It is very recent the discovery of two pentaquarks and the confirmation of four tetraquarks, two of which had not been observed before. We mainly review the theoretical understanding of this sector of particle physics phenomenology and present some considerations attempting a coherent description of the so called X and Z resonances. The prominent problems plaguing theoretical models, like the absence of selection rules limiting the number of states predicted, motivate new directions in model building.more » Lastly, data are reviewed going through all of the observed resonances with particular attention to their common features and the purpose of providing a starting point to further research.« less

Model-based document categorization employing semantic pattern analysis and local structure clustering

NASA Astrophysics Data System (ADS)

Fume, Kosei; Ishitani, Yasuto

2008-01-01

We propose a document categorization method based on a document model that can be defined externally for each task and that categorizes Web content or business documents into a target category in accordance with the similarity of the model. The main feature of the proposed method consists of two aspects of semantics extraction from an input document. The semantics of terms are extracted by the semantic pattern analysis and implicit meanings of document substructure are specified by a bottom-up text clustering technique focusing on the similarity of text line attributes. We have constructed a system based on the proposed method for trial purposes. The experimental results show that the system achieves more than 80% classification accuracy in categorizing Web content and business documents into 15 or 70 categories.

SUMCOR: Cascade summing correction for volumetric sources applying MCNP6.

PubMed

Dias, M S; Semmler, R; Moreira, D S; de Menezes, M O; Barros, L F; Ribeiro, R V; Koskinas, M F

2018-04-01

The main features of code SUMCOR developed for cascade summing correction for volumetric sources are described. MCNP6 is used to track histories starting from individual points inside the volumetric source, for each set of cascade transitions from the radionuclide. Total and FEP efficiencies are calculated for all gamma-rays and X-rays involved in the cascade. Cascade summing correction is based on the matrix formalism developed by Semkow et al. (1990). Results are presented applying the experimental data sent to the participants of two intercomparisons organized by the ICRM-GSWG and coordinated by Dr. Marie-Cristine Lépy from the Laboratoire National Henri Becquerel (LNE-LNHB), CEA, in 2008 and 2010, respectively and compared to the other participants in the intercomparisons. Copyright © 2017 Elsevier Ltd. All rights reserved.

Macroscopic and mesoscopic approach to the alkali-silica reaction in concrete

NASA Astrophysics Data System (ADS)

Grymin, Witold; Koniorczyk, Marcin; Pesavento, Francesco; Gawin, Dariusz

2018-01-01

A model of the alkali-silica reaction, which takes into account couplings between thermal, hygral, mechanical and chemical phenomena in concrete, has been discussed. The ASR may be considered at macroscopic or mesoscopic scale. The main features of each approach have been summarized and development of the model for both scales has been briefly described. Application of the model to experimental results for both scales has been presented. Even though good accordance of the model has been obtained for both approaches, consideration of the model at the mesoscopic scale allows to model different mortar mixes, prepared with the same aggregate, but of different grain size, using the same set of parameters. It enables also to predict reaction development assuming different alkali sources, such as de-icing salts or alkali leaching.

NeedATool: A Needlet Analysis Tool for Cosmological Data Processing

NASA Astrophysics Data System (ADS)

Pietrobon, Davide; Balbi, Amedeo; Cabella, Paolo; Gorski, Krzysztof M.

2010-11-01

We introduce NeedATool (Needlet Analysis Tool), a software for data analysis based on needlets, a wavelet rendition which is powerful for the analysis of fields defined on a sphere. Needlets have been applied successfully to the treatment of astrophysical and cosmological observations, and in particular to the analysis of cosmic microwave background (CMB) data. Usually, such analyses are performed in real space as well as in its dual domain, the harmonic one. Both spaces have advantages and disadvantages: for example, in pixel space it is easier to deal with partial sky coverage and experimental noise; in the harmonic domain, beam treatment and comparison with theoretical predictions are more effective. During the last decade, however, wavelets have emerged as a useful tool for CMB data analysis, since they allow us to combine most of the advantages of the two spaces, one of the main reasons being their sharp localization. In this paper, we outline the analytical properties of needlets and discuss the main features of the numerical code, which should be a valuable addition to the CMB analyst's toolbox.

Overview and Evaluation of Bluetooth Low Energy: An Emerging Low-Power Wireless Technology

PubMed Central

Gomez, Carles; Oller, Joaquim; Paradells, Josep

2012-01-01

Bluetooth Low Energy (BLE) is an emerging low-power wireless technology developed for short-range control and monitoring applications that is expected to be incorporated into billions of devices in the next few years. This paper describes the main features of BLE, explores its potential applications, and investigates the impact of various critical parameters on its performance. BLE represents a trade-off between energy consumption, latency, piconet size, and throughput that mainly depends on parameters such as connInterval and connSlaveLatency. According to theoretical results, the lifetime of a BLE device powered by a coin cell battery ranges between 2.0 days and 14.1 years. The number of simultaneous slaves per master ranges between 2 and 5,917. The minimum latency for a master to obtain a sensor reading is 676 μs, although simulation results show that, under high bit error rate, average latency increases by up to three orders of magnitude. The paper provides experimental results that complement the theoretical and simulation findings, and indicates implementation constraints that may reduce BLE performance.

Dependence with the oxidation state of X-ray transition energies, intensities and natural line widths of CrKβ spectra

NASA Astrophysics Data System (ADS)

Torres Deluigi, M.; Tirao, G.; Stutz, G.; Cusatis, C.; Riveros, J. A.

2006-06-01

The Kβ emission spectrum of chromium was experimentally analyzed in different compounds and compared with previous data. Measurements of whole Kβ spectra were performed with a wavelength dispersive commercial XRF equipment. To study possible effects of the chemical state in the width and position of the main Kβ 1,3 line, high resolution measurements were also performed. In the latter measurements, a spectrometer based on a backdiffracting crystal analyzer with spherical focalization and synchrotron radiation monochromatic excitation was used. Kβ 1,3 line shifts in relation to metallic Cr were observed, both to higher energies (≅+1 eV) for Cr III and to lower energies (≅-0.5 eV) for Cr VI. It was also found that the natural width of CrKβ 1,3 line, the ionization energy of the 3p orbital of Cr, and the relative intensities of Kβ″ and Kβ 2,5 lines with respect to the main Kβ 1,3 line increase as the oxidation state increases. The use of these features as an index for chemical state analysis is discussed.

Guided filter-based fusion method for multiexposure images

NASA Astrophysics Data System (ADS)

Hou, Xinglin; Luo, Haibo; Qi, Feng; Zhou, Peipei

2016-11-01

It is challenging to capture a high-dynamic range (HDR) scene using a low-dynamic range camera. A weighted sum-based image fusion (IF) algorithm is proposed so as to express an HDR scene with a high-quality image. This method mainly includes three parts. First, two image features, i.e., gradients and well-exposedness are measured to estimate the initial weight maps. Second, the initial weight maps are refined by a guided filter, in which the source image is considered as the guidance image. This process could reduce the noise in initial weight maps and preserve more texture consistent with the original images. Finally, the fused image is constructed by a weighted sum of source images in the spatial domain. The main contributions of this method are the estimation of the initial weight maps and the appropriate use of the guided filter-based weight maps refinement. It provides accurate weight maps for IF. Compared to traditional IF methods, this algorithm avoids image segmentation, combination, and the camera response curve calibration. Furthermore, experimental results demonstrate the superiority of the proposed method in both subjective and objective evaluations.

Contribution of Large Animals to Translational Research on Prenatal Programming of Obesity and Associated Diseases.

PubMed

Gonzalez-Bulnes, Antonio; Chavatte-Palmer, Pascale

2017-01-01

The awareness of factors causing obesity and associated disorders has grown up in the last years from genome to a more complicated concept (developmental programming) in which prenatal and early-postnatal conditions markedly modify the phenotype and homeostasis of the individuals and determine juvenile growth, life-time fitness/obesity and disease risks. Experimentation in human beings is impeded by ethical issues plus inherent high variability and confounding factors (genetics, lifestyle and socioeconomic heterogeneity) and preclinical studies in adequate translational animal models are therefore decisive. Most of the studies have been performed in rodents, whilst the use of large animals is scarce. Having in mind body-size, handlingeasiness and cost-efficiency, the main large animal species for use in biomedical research are rabbits, sheep and swine. The choice of the model depends on the research objectives. To outline the main features of the use of rabbits, sheep and swine and their contributions as translational models in prenatal programming of obesity and associated disorders. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

The monitoring of transient regimes on machine tools based on speed, acceleration and active electric power absorbed by motors

NASA Astrophysics Data System (ADS)

Horodinca, M.

2016-08-01

This paper intend to propose some new results related with computer aided monitoring of transient regimes on machine-tools based on the evolution of active electrical power absorbed by the electric motor used to drive the main kinematic chains and the evolution of rotational speed and acceleration of the main shaft. The active power is calculated in numerical format using the evolution of instantaneous voltage and current delivered by electrical power system to the electric motor. The rotational speed and acceleration of the main shaft are calculated based on the signal delivered by a sensor. Three real-time analogic signals are acquired with a very simple computer assisted setup which contains a voltage transformer, a current transformer, an AC generator as rotational speed sensor, a data acquisition system and a personal computer. The data processing and analysis was done using Matlab software. Some different transient regimes were investigated; several important conclusions related with the advantages of this monitoring technique were formulated. Many others features of the experimental setup are also available: to supervise the mechanical loading of machine-tools during cutting processes or for diagnosis of machine-tools condition by active electrical power signal analysis in frequency domain.

Penobscot Experimental Forest: resources, administration, and mission

Treesearch

Alan J. Kimball

2014-01-01

The Penobscot Experimental Forest (PEF) was established more than 60 years ago as a result of private forest landowners' interest in supporting forest research in Maine. In 1950, nine pulp and paper and land-holding companies pooled resources and purchased almost 4,000 acres of land in east-central Maine. The property was named the Penobscot Experimental Forest...

Penobscot Experimental Forest: 60 years of research and demonstration in Maine, 1950-2010

Treesearch

Laura S. Kenefic; John C. Brissette

2014-01-01

The Penobscot Experimental Forest (PEF) in Maine has been the site of U.S. Department of Agriculture, Forest Service, Northern Research Station (previously Northeastern Forest Experiment Station) research on northern conifer silviculture and ecology since 1950. Purchased by forest industry and leased to the Forest Service for long-term experimentation, the PEF was...

[Results of testing of MINISKAN mobile gamma-ray camera and specific features of its design].

PubMed

Utkin, V M; Kumakhov, M A; Blinov, N N; Korsunskiĭ, V N; Fomin, D K; Kolesnikova, N V; Tultaev, A V; Nazarov, A A; Tararukhina, O B

2007-01-01

The main results of engineering, biomedical, and clinical testing of MINISKAN mobile gamma-ray camera are presented. Specific features of the camera hardware and software, as well as the main technical specifications, are described. The gamma-ray camera implements a new technology based on reconstructive tomography, aperture encoding, and digital processing of signals.

Structural organization of G-protein-coupled receptors

NASA Astrophysics Data System (ADS)

Lomize, Andrei L.; Pogozheva, Irina D.; Mosberg, Henry I.

1999-07-01

Atomic-resolution structures of the transmembrane 7-α-helical domains of 26 G-protein-coupled receptors (GPCRs) (including opsins, cationic amine, melatonin, purine, chemokine, opioid, and glycoprotein hormone receptors and two related proteins, retinochrome and Duffy erythrocyte antigen) were calculated by distance geometry using interhelical hydrogen bonds formed by various proteins from the family and collectively applied as distance constraints, as described previously [Pogozheva et al., Biophys. J., 70 (1997) 1963]. The main structural features of the calculated GPCR models are described and illustrated by examples. Some of the features reflect physical interactions that are responsible for the structural stability of the transmembrane α-bundle: the formation of extensive networks of interhelical H-bonds and sulfur-aromatic clusters that are spatially organized as 'polarity gradients' the close packing of side-chains throughout the transmembrane domain; and the formation of interhelical disulfide bonds in some receptors and a plausible Zn2+ binding center in retinochrome. Other features of the models are related to biological function and evolution of GPCRs: the formation of a common 'minicore' of 43 evolutionarily conserved residues; a multitude of correlated replacements throughout the transmembrane domain; an Na+-binding site in some receptors, and excellent complementarity of receptor binding pockets to many structurally dissimilar, conformationally constrained ligands, such as retinal, cyclic opioid peptides, and cationic amine ligands. The calculated models are in good agreement with numerous experimental data.

Hidden pattern discovery on epileptic EEG with 1-D local binary patterns and epileptic seizures detection by grey relational analysis.

PubMed

Kaya, Yılmaz

2015-09-01

This paper proposes a novel approach to detect epilepsy seizures by using Electroencephalography (EEG), which is one of the most common methods for the diagnosis of epilepsy, based on 1-Dimension Local Binary Pattern (1D-LBP) and grey relational analysis (GRA) methods. The main aim of this paper is to evaluate and validate a novel approach, which is a computer-based quantitative EEG analyzing method and based on grey systems, aimed to help decision-maker. In this study, 1D-LBP, which utilizes all data points, was employed for extracting features in raw EEG signals, Fisher score (FS) was employed to select the representative features, which can also be determined as hidden patterns. Additionally, GRA is performed to classify EEG signals through these Fisher scored features. The experimental results of the proposed approach, which was employed in a public dataset for validation, showed that it has a high accuracy in identifying epileptic EEG signals. For various combinations of epileptic EEG, such as A-E, B-E, C-E, D-E, and A-D clusters, 100, 96, 100, 99.00 and 100% were achieved, respectively. Also, this work presents an attempt to develop a new general-purpose hidden pattern determination scheme, which can be utilized for different categories of time-varying signals.

Feature-Motivated Simplified Adaptive PCNN-Based Medical Image Fusion Algorithm in NSST Domain.

PubMed

Ganasala, Padma; Kumar, Vinod

2016-02-01

Multimodality medical image fusion plays a vital role in diagnosis, treatment planning, and follow-up studies of various diseases. It provides a composite image containing critical information of source images required for better localization and definition of different organs and lesions. In the state-of-the-art image fusion methods based on nonsubsampled shearlet transform (NSST) and pulse-coupled neural network (PCNN), authors have used normalized coefficient value to motivate the PCNN-processing both low-frequency (LF) and high-frequency (HF) sub-bands. This makes the fused image blurred and decreases its contrast. The main objective of this work is to design an image fusion method that gives the fused image with better contrast, more detail information, and suitable for clinical use. We propose a novel image fusion method utilizing feature-motivated adaptive PCNN in NSST domain for fusion of anatomical images. The basic PCNN model is simplified, and adaptive-linking strength is used. Different features are used to motivate the PCNN-processing LF and HF sub-bands. The proposed method is extended for fusion of functional image with an anatomical image in improved nonlinear intensity hue and saturation (INIHS) color model. Extensive fusion experiments have been performed on CT-MRI and SPECT-MRI datasets. Visual and quantitative analysis of experimental results proved that the proposed method provides satisfactory fusion outcome compared to other image fusion methods.

A thermodynamic framework for the study of crystallization in polymers

NASA Astrophysics Data System (ADS)

Rao, I. J.; Rajagopal, K. R.

In this paper, we present a new thermodynamic framework within the context of continuum mechanics, to predict the behavior of crystallizing polymers. The constitutive models that are developed within this thermodynamic setting are able to describe the main features of the crystallization process. The model is capable of capturing the transition from a fluid like behavior to a solid like behavior in a rational manner without appealing to any adhoc transition criterion. The anisotropy of the crystalline phase is built into the model and the specific anisotropy of the crystalline phase depends on the deformation in the melt. These features are incorporated into a recent framework that associates different natural configurations and material symmetries with distinct microstructural features within the body that arise during the process under consideration. Specific models are generated by choosing particular forms for the internal energy, entropy and the rate of dissipation. Equations governing the evolution of the natural configurations and the rate of crystallization are obtained by maximizing the rate of dissipation, subject to appropriate constraints. The initiation criterion, marking the onset of crystallization, arises naturally in this setting in terms of the thermodynamic functions. The model generated within such a framework is used to simulate bi-axial extension of a polymer film that is undergoing crystallization. The predictions of the theory that has been proposed are consistent with the experimental results (see [28] and [7]).

Coarse-to-fine wavelet-based airport detection

NASA Astrophysics Data System (ADS)

Li, Cheng; Wang, Shuigen; Pang, Zhaofeng; Zhao, Baojun

2015-10-01

Airport detection on optical remote sensing images has attracted great interest in the applications of military optics scout and traffic control. However, most of the popular techniques for airport detection from optical remote sensing images have three weaknesses: 1) Due to the characteristics of optical images, the detection results are often affected by imaging conditions, like weather situation and imaging distortion; and 2) optical images contain comprehensive information of targets, so that it is difficult for extracting robust features (e.g., intensity and textural information) to represent airport area; 3) the high resolution results in large data volume, which makes real-time processing limited. Most of the previous works mainly focus on solving one of those problems, and thus, the previous methods cannot achieve the balance of performance and complexity. In this paper, we propose a novel coarse-to-fine airport detection framework to solve aforementioned three issues using wavelet coefficients. The framework includes two stages: 1) an efficient wavelet-based feature extraction is adopted for multi-scale textural feature representation, and support vector machine(SVM) is exploited for classifying and coarsely deciding airport candidate region; and then 2) refined line segment detection is used to obtain runway and landing field of airport. Finally, airport recognition is achieved by applying the fine runway positioning to the candidate regions. Experimental results show that the proposed approach outperforms the existing algorithms in terms of detection accuracy and processing efficiency.

Prediction of Peptide and Protein Propensity for Amyloid Formation

PubMed Central

Família, Carlos; Dennison, Sarah R.; Quintas, Alexandre; Phoenix, David A.

2015-01-01

Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo structural changes, which lead to amyloid formation, are quite diverse and share no obvious sequence or structural homology, despite the structural similarity found in the fibrils. To address these issues, a novel approach based on recursive feature selection and feed-forward neural networks was undertaken to identify key features highly correlated with the self-assembly problem. This approach allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔG° values for peptides extrapolated in 0 M urea). Moreover, these features enabled the development of a new predictor (available at http://cran.r-project.org/web/packages/appnn/index.html) capable of accurately and reliably predicting the amyloidogenic propensity from the polypeptide sequence alone with a prediction accuracy of 84.9 % against an external validation dataset of sequences with experimental in vitro, evidence of amyloid formation. PMID:26241652

Correspondence effects with torches: grasping affordance or visual feature asymmetry?

PubMed

Song, Xiaolei; Chen, Jing; Proctor, Robert W

2014-01-01

Three experiments were conducted to determine whether an object-based correspondence effect for torch (flashlight) stimuli reported by Pellicano et al. [( 2010 ). Simon-like and functional affordance effects with tools: The effects of object perceptual discrimination and object action state. Quarterly Journal of Experimental Psychology, 63, 2190-2201] is due to a grasping affordance provided by the handle or asymmetry of feature markings on the torch. In Experiment 1 the stimuli were the same as those from Pellicano et al.'s Experiment 2, whereas in Experiments 2 and 3 the stimuli were modified versions with the graspable handle removed. Participants in all experiments performed upright/inverted orientation judgements on the torch stimuli. The results of Experiment 1 replicated those of Pellicano et al.: A small but significant object-based correspondence effect was evident, mainly when the torch was in an active state. With the handle of the torch removed in Experiment 2, making the barrel markings more asymmetric in the display, the correspondence effect was larger. Experiment 3 directly demonstrated an effect of barrel-marking asymmetry on the correspondence effect: When only the half of the markings nearest the light end of the torch was included, the correspondence effect reversed to favour the light end. The results are in agreement with a visual feature-asymmetry account and are difficult to reconcile with a grasping-affordance account.

Image preprocessing study on KPCA-based face recognition

NASA Astrophysics Data System (ADS)

Li, Xuan; Li, Dehua

2015-12-01

Face recognition as an important biometric identification method, with its friendly, natural, convenient advantages, has obtained more and more attention. This paper intends to research a face recognition system including face detection, feature extraction and face recognition, mainly through researching on related theory and the key technology of various preprocessing methods in face detection process, using KPCA method, focuses on the different recognition results in different preprocessing methods. In this paper, we choose YCbCr color space for skin segmentation and choose integral projection for face location. We use erosion and dilation of the opening and closing operation and illumination compensation method to preprocess face images, and then use the face recognition method based on kernel principal component analysis method for analysis and research, and the experiments were carried out using the typical face database. The algorithms experiment on MATLAB platform. Experimental results show that integration of the kernel method based on PCA algorithm under certain conditions make the extracted features represent the original image information better for using nonlinear feature extraction method, which can obtain higher recognition rate. In the image preprocessing stage, we found that images under various operations may appear different results, so as to obtain different recognition rate in recognition stage. At the same time, in the process of the kernel principal component analysis, the value of the power of the polynomial function can affect the recognition result.

The extraction and use of facial features in low bit-rate visual communication.

PubMed

Pearson, D

1992-01-29

A review is given of experimental investigations by the author and his collaborators into methods of extracting binary features from images of the face and hands. The aim of the research has been to enable deaf people to communicate by sign language over the telephone network. Other applications include model-based image coding and facial-recognition systems. The paper deals with the theoretical postulates underlying the successful experimental extraction of facial features. The basic philosophy has been to treat the face as an illuminated three-dimensional object and to identify features from characteristics of their Gaussian maps. It can be shown that in general a composite image operator linked to a directional-illumination estimator is required to accomplish this, although the latter can often be omitted in practice.

Classification Influence of Features on Given Emotions and Its Application in Feature Selection

NASA Astrophysics Data System (ADS)

Xing, Yin; Chen, Chuang; Liu, Li-Long

2018-04-01

In order to solve the problem that there is a large amount of redundant data in high-dimensional speech emotion features, we analyze deeply the extracted speech emotion features and select better features. Firstly, a given emotion is classified by each feature. Secondly, the recognition rate is ranked in descending order. Then, the optimal threshold of features is determined by rate criterion. Finally, the better features are obtained. When applied in Berlin and Chinese emotional data set, the experimental results show that the feature selection method outperforms the other traditional methods.

Wire rope tension control of hoisting systems using a robust nonlinear adaptive backstepping control scheme.

PubMed

Zhu, Zhen-Cai; Li, Xiang; Shen, Gang; Zhu, Wei-Dong

2018-01-01

This paper concerns wire rope tension control of a double-rope winding hoisting system (DRWHS), which consists of a hoisting system employed to realize a transportation function and an electro-hydraulic servo system utilized to adjust wire rope tensions. A dynamic model of the DRWHS is developed in which parameter uncertainties and external disturbances are considered. A comparison between simulation results using the dynamic model and experimental results using a double-rope winding hoisting experimental system is given in order to demonstrate accuracy of the dynamic model. In order to improve the wire rope tension coordination control performance of the DRWHS, a robust nonlinear adaptive backstepping controller (RNABC) combined with a nonlinear disturbance observer (NDO) is proposed. Main features of the proposed combined controller are: (1) using the RNABC to adjust wire rope tensions with consideration of parameter uncertainties, whose parameters are designed online by adaptive laws derived from Lyapunov stability theory to guarantee the control performance and stability of the closed-loop system; and (2) introducing the NDO to deal with uncertain external disturbances. In order to demonstrate feasibility and effectiveness of the proposed controller, experimental studies have been conducted on the DRWHS controlled by an xPC rapid prototyping system. Experimental results verify that the proposed controller exhibits excellent performance on wire rope tension coordination control compared with a conventional proportional-integral (PI) controller and adaptive backstepping controller. Copyright © 2017 ISA. All rights reserved.

Computational/experimental studies of isolated, single component droplet combustion

NASA Technical Reports Server (NTRS)

Dryer, Frederick L.

1993-01-01

Isolated droplet combustion processes have been the subject of extensive experimental and theoretical investigations for nearly 40 years. The gross features of droplet burning are qualitatively embodied by simple theories and are relatively well understood. However, there remain significant aspects of droplet burning, particularly its dynamics, for which additional basic knowledge is needed for thorough interpretations and quantitative explanations of transient phenomena. Spherically-symmetric droplet combustion, which can only be approximated under conditions of both low Reynolds and Grashof numbers, represents the simplest geometrical configuration in which to study the coupled chemical/transport processes inherent within non-premixed flames. The research summarized here, concerns recent results on isolated, single component, droplet combustion under microgravity conditions, a program pursued jointly with F.A. Williams of the University of California, San Diego. The overall program involves developing and applying experimental methods to study the burning of isolated, single component droplets, in various atmospheres, primarily at atmospheric pressure and below, in both drop towers and aboard space-based platforms such as the Space Shuttle or Space Station. Both computational methods and asymptotic methods, the latter pursued mainly at UCSD, are used in developing the experimental test matrix, in analyzing results, and for extending theoretical understanding. Methanol, and the normal alkanes, n-heptane, and n-decane, have been selected as test fuels to study time-dependent droplet burning phenomena. The following sections summarizes the Princeton efforts on this program, describe work in progress, and briefly delineate future research directions.

Identifying Bottom-Up and Top-Down Components of Attentional Weight by Experimental Analysis and Computational Modeling

ERIC Educational Resources Information Center

Nordfang, Maria; Dyrholm, Mads; Bundesen, Claus

2013-01-01

The attentional weight of a visual object depends on the contrast of the features of the object to its local surroundings (feature contrast) and the relevance of the features to one's goals (feature relevance). We investigated the dependency in partial report experiments with briefly presented stimuli but unspeeded responses. The task was to…

Red to Green or Fast to Slow? Infants' Visual Working Memory for "Just Salient Differences"

ERIC Educational Resources Information Center

Kaldy, Zsuzsa; Blaser, Erik

2013-01-01

In this study, 6-month-old infants' visual working memory for a static feature (color) and a dynamic feature (rotational motion) was compared. Comparing infants' use of different features can only be done properly if experimental manipulations to those features are equally salient (Kaldy & Blaser, 2009; Kaldy, Blaser, & Leslie,…

Experimental signatures of direct-laser-acceleration-assisted laser wakefield acceleration

NASA Astrophysics Data System (ADS)

Shaw, J. L.; Lemos, N.; Marsh, K. A.; Froula, D. H.; Joshi, C.

2018-04-01

The direct laser acceleration (DLA) of electrons in a laser wakefield accelerator (LWFA) operating in the forced or quasi-blowout regimes has been investigated through experiment and simulation. When there is a significant overlap between the trapped electrons and the drive laser in a LWFA cavity, the resulting electrons can gain energy from both the LWFA and the DLA mechanisms. Experimental work investigates the properties of the electron beams produced in a LWFA with ionization injection by dispersing those beams in the direction perpendicular to the laser polarization. These electron beams show certain spectral features that are characteristic of DLA. These characteristic features are reproduced using particle-in-cell simulations, where particle tracking was used to elucidate the roles of LWFA and DLA to the energy gain of the electrons in this experimental regime and to demonstrate that such spectral features are definitive signatures of the presence of DLA in LWFA.

Quantitative 3-D Imaging, Segmentation and Feature Extraction of the Respiratory System in Small Mammals for Computational Biophysics Simulations

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

Trease, Lynn L.; Trease, Harold E.; Fowler, John

2007-03-15

One of the critical steps toward performing computational biology simulations, using mesh based integration methods, is in using topologically faithful geometry derived from experimental digital image data as the basis for generating the computational meshes. Digital image data representations contain both the topology of the geometric features and experimental field data distributions. The geometric features that need to be captured from the digital image data are three-dimensional, therefore the process and tools we have developed work with volumetric image data represented as data-cubes. This allows us to take advantage of 2D curvature information during the segmentation and feature extraction process.more » The process is basically: 1) segmenting to isolate and enhance the contrast of the features that we wish to extract and reconstruct, 2) extracting the geometry of the features in an isosurfacing technique, and 3) building the computational mesh using the extracted feature geometry. “Quantitative” image reconstruction and feature extraction is done for the purpose of generating computational meshes, not just for producing graphics "screen" quality images. For example, the surface geometry that we extract must represent a closed water-tight surface.« less

Asymmetric bagging and feature selection for activities prediction of drug molecules.

PubMed

Li, Guo-Zheng; Meng, Hao-Hua; Lu, Wen-Cong; Yang, Jack Y; Yang, Mary Qu

2008-05-28

Activities of drug molecules can be predicted by QSAR (quantitative structure activity relationship) models, which overcomes the disadvantages of high cost and long cycle by employing the traditional experimental method. With the fact that the number of drug molecules with positive activity is rather fewer than that of negatives, it is important to predict molecular activities considering such an unbalanced situation. Here, asymmetric bagging and feature selection are introduced into the problem and asymmetric bagging of support vector machines (asBagging) is proposed on predicting drug activities to treat the unbalanced problem. At the same time, the features extracted from the structures of drug molecules affect prediction accuracy of QSAR models. Therefore, a novel algorithm named PRIFEAB is proposed, which applies an embedded feature selection method to remove redundant and irrelevant features for asBagging. Numerical experimental results on a data set of molecular activities show that asBagging improve the AUC and sensitivity values of molecular activities and PRIFEAB with feature selection further helps to improve the prediction ability. Asymmetric bagging can help to improve prediction accuracy of activities of drug molecules, which can be furthermore improved by performing feature selection to select relevant features from the drug molecules data sets.

Conformational diversity analysis reveals three functional mechanisms in proteins

PubMed Central

Fornasari, María Silvina

2017-01-01

Protein motions are a key feature to understand biological function. Recently, a large-scale analysis of protein conformational diversity showed a positively skewed distribution with a peak at 0.5 Å C-alpha root-mean-square-deviation (RMSD). To understand this distribution in terms of structure-function relationships, we studied a well curated and large dataset of ~5,000 proteins with experimentally determined conformational diversity. We searched for global behaviour patterns studying how structure-based features change among the available conformer population for each protein. This procedure allowed us to describe the RMSD distribution in terms of three main protein classes sharing given properties. The largest of these protein subsets (~60%), which we call “rigid” (average RMSD = 0.83 Å), has no disordered regions, shows low conformational diversity, the largest tunnels and smaller and buried cavities. The two additional subsets contain disordered regions, but with differential sequence composition and behaviour. Partially disordered proteins have on average 67% of their conformers with disordered regions, average RMSD = 1.1 Å, the highest number of hinges and the longest disordered regions. In contrast, malleable proteins have on average only 25% of disordered conformers and average RMSD = 1.3 Å, flexible cavities affected in size by the presence of disordered regions and show the highest diversity of cognate ligands. Proteins in each set are mostly non-homologous to each other, share no given fold class, nor functional similarity but do share features derived from their conformer population. These shared features could represent conformational mechanisms related with biological functions. PMID:28192432

High-order above-threshold photoemission from nanotips controlled with two-color laser fields

NASA Astrophysics Data System (ADS)

Seiffert, Lennart; Paschen, Timo; Hommelhoff, Peter; Fennel, Thomas

2018-07-01

We investigate the process of phase-controlled high-order above-threshold photoemission from metallic nanotips under bichromatic laser fields. Experimental photoelectron spectra resulting from two-color excitation with a moderately intense near-infrared fundamental field (1560 nm) and its weak second harmonic show a strong sensitivity on the relative phase and clear indications for a plateau-like structure that is attributed to elastic backscattering. To explore the relevant control mechanisms, characteristic features, and particular signatures from the near-field inhomogeneity, we performed systematic quantum simulations employing a one-dimensional nanotip model. Besides rich phase-dependent structures in the simulated above-threshold ionization photoelectron spectra we find ponderomotive shifts as well as substantial modifications of the rescattering cutoff as function of the decay length of the near-field. To explore the quantum or classical nature of the observed features and to discriminate the two-color effects stemming from electron propagation and from the ionization rate we compare the quantum results to classical trajectory simulations. We show that signatures from direct electrons as well as the modulations in the plateau region mainly stem from control of the ionization probability, while the modulation in the cutoff region can only be explained by the impact of the two-color field on the electron trajectory. Despite the complexity of the phase-dependent features that render two-color strong-field photoemission from nanotips intriguing for sub-cycle strong-field control, our findings support that the recollision features in the cutoff region provide a robust and reliable method to calibrate the relative two-color phase.

Signatures of nonlinearity in single cell noise-induced oscillations.

PubMed

Thomas, Philipp; Straube, Arthur V; Timmer, Jens; Fleck, Christian; Grima, Ramon

2013-10-21

A class of theoretical models seeks to explain rhythmic single cell data by postulating that they are generated by intrinsic noise in biochemical systems whose deterministic models exhibit only damped oscillations. The main features of such noise-induced oscillations are quantified by the power spectrum which measures the dependence of the oscillatory signal's power with frequency. In this paper we derive an approximate closed-form expression for the power spectrum of any monostable biochemical system close to a Hopf bifurcation, where noise-induced oscillations are most pronounced. Unlike the commonly used linear noise approximation which is valid in the macroscopic limit of large volumes, our theory is valid over a wide range of volumes and hence affords a more suitable description of single cell noise-induced oscillations. Our theory predicts that the spectra have three universal features: (i) a dominant peak at some frequency, (ii) a smaller peak at twice the frequency of the dominant peak and (iii) a peak at zero frequency. Of these, the linear noise approximation predicts only the first feature while the remaining two stem from the combination of intrinsic noise and nonlinearity in the law of mass action. The theoretical expressions are shown to accurately match the power spectra determined from stochastic simulations of mitotic and circadian oscillators. Furthermore it is shown how recently acquired single cell rhythmic fibroblast data displays all the features predicted by our theory and that the experimental spectrum is well described by our theory but not by the conventional linear noise approximation. © 2013 Elsevier Ltd. All rights reserved.

NASA catalogue of lunar nomenclature

NASA Technical Reports Server (NTRS)

Andersson, L. A.; Whitaker, E. A.

1982-01-01

Lunar nomenclature is cataloged. It includes letter designations for subsidiary craters, and uses a more familiar spelling from eight names. The listed features are divided into three main groups for cataloging purposes, namely: (1) craters, (2) noncrater features; and (3) minor and miscellaneous features.

Applying a nonlinear, pitch-catch, ultrasonic technique for the detection of kissing bonds in friction stir welds.

PubMed

Delrue, Steven; Tabatabaeipour, Morteza; Hettler, Jan; Van Den Abeele, Koen

2016-05-01

Friction stir welding (FSW) is a promising technology for the joining of aluminum alloys and other metallic admixtures that are hard to weld by conventional fusion welding. Although FSW generally provides better fatigue properties than traditional fusion welding methods, fatigue properties are still significantly lower than for the base material. Apart from voids, kissing bonds for instance, in the form of closed cracks propagating along the interface of the stirred and heat affected zone, are inherent features of the weld and can be considered as one of the main causes of a reduced fatigue life of FSW in comparison to the base material. The main problem with kissing bond defects in FSW, is that they currently are very difficult to detect using existing NDT methods. Besides, in most cases, the defects are not directly accessible from the exposed surface. Therefore, new techniques capable of detecting small kissing bond flaws need to be introduced. In the present paper, a novel and practical approach is introduced based on a nonlinear, single-sided, ultrasonic technique. The proposed inspection technique uses two single element transducers, with the first transducer transmitting an ultrasonic signal that focuses the ultrasonic waves at the bottom side of the sample where cracks are most likely to occur. The large amount of energy at the focus activates the kissing bond, resulting in the generation of nonlinear features in the wave propagation. These nonlinear features are then captured by the second transducer operating in pitch-catch mode, and are analyzed, using pulse inversion, to reveal the presence of a defect. The performance of the proposed nonlinear, pitch-catch technique, is first illustrated using a numerical study of an aluminum sample containing simple, vertically oriented, incipient cracks. Later, the proposed technique is also applied experimentally on a real-life friction stir welded butt joint containing a kissing bond flaw. Copyright © 2016 Elsevier B.V. All rights reserved.

Nucleic Acid Database (NDB)

Science.gov Websites

the NDB archive or in the Non-Redundant list Advanced Search Search for structures based on structural features, chemical features, binding modes, citation and experimental information Featured Tools RNA 3D Motif Atlas, a representative collection of RNA 3D internal and hairpin loop motifs Non-redundant Lists

Variogram-based feature extraction for neural network recognition of logos

NASA Astrophysics Data System (ADS)

Pham, Tuan D.

2003-03-01

This paper presents a new approach for extracting spatial features of images based on the theory of regionalized variables. These features can be effectively used for automatic recognition of logo images using neural networks. Experimental results on a public-domain logo database show the effectiveness of the proposed approach.

Observation of Weyl points

Science.gov Websites

copolymers, liquid crystals. Experimental observation of Weyl points First public annoucement on 11 Feburary Vishwanath from University of California, Berkeley. "Experimental Observation of Weyl Semimetals" ; Published by Science on 16 July, 2015. "Experimental observation of Weyl points" Featured on the

Seminal quality prediction using data mining methods.

PubMed

Sahoo, Anoop J; Kumar, Yugal

2014-01-01

Now-a-days, some new classes of diseases have come into existences which are known as lifestyle diseases. The main reasons behind these diseases are changes in the lifestyle of people such as alcohol drinking, smoking, food habits etc. After going through the various lifestyle diseases, it has been found that the fertility rates (sperm quantity) in men has considerably been decreasing in last two decades. Lifestyle factors as well as environmental factors are mainly responsible for the change in the semen quality. The objective of this paper is to identify the lifestyle and environmental features that affects the seminal quality and also fertility rate in man using data mining methods. The five artificial intelligence techniques such as Multilayer perceptron (MLP), Decision Tree (DT), Navie Bayes (Kernel), Support vector machine+Particle swarm optimization (SVM+PSO) and Support vector machine (SVM) have been applied on fertility dataset to evaluate the seminal quality and also to predict the person is either normal or having altered fertility rate. While the eight feature selection techniques such as support vector machine (SVM), neural network (NN), evolutionary logistic regression (LR), support vector machine plus particle swarm optimization (SVM+PSO), principle component analysis (PCA), chi-square test, correlation and T-test methods have been used to identify more relevant features which affect the seminal quality. These techniques are applied on fertility dataset which contains 100 instances with nine attribute with two classes. The experimental result shows that SVM+PSO provides higher accuracy and area under curve (AUC) rate (94% & 0.932) among multi-layer perceptron (MLP) (92% & 0.728), Support Vector Machines (91% & 0.758), Navie Bayes (Kernel) (89% & 0.850) and Decision Tree (89% & 0.735) for some of the seminal parameters. This paper also focuses on the feature selection process i.e. how to select the features which are more important for prediction of fertility rate. In this paper, eight feature selection methods are applied on fertility dataset to find out a set of good features. The investigational results shows that childish diseases (0.079) and high fever features (0.057) has less impact on fertility rate while age (0.8685), season (0.843), surgical intervention (0.7683), alcohol consumption (0.5992), smoking habit (0.575), number of hours spent on setting (0.4366) and accident (0.5973) features have more impact. It is also observed that feature selection methods increase the accuracy of above mentioned techniques (multilayer perceptron 92%, support vector machine 91%, SVM+PSO 94%, Navie Bayes (Kernel) 89% and decision tree 89%) as compared to without feature selection methods (multilayer perceptron 86%, support vector machine 86%, SVM+PSO 85%, Navie Bayes (Kernel) 83% and decision tree 84%) which shows the applicability of feature selection methods in prediction. This paper lightens the application of artificial techniques in medical domain. From this paper, it can be concluded that data mining methods can be used to predict a person with or without disease based on environmental and lifestyle parameters/features rather than undergoing various medical test. In this paper, five data mining techniques are used to predict the fertility rate and among which SVM+PSO provide more accurate results than support vector machine and decision tree.

Experimental and numerical investigation of the turbulent wake flow of a generic space launcher configuration

NASA Astrophysics Data System (ADS)

Statnikov, V.; Saile, D.; Meiß, J.-H.; Henckels, A.; Meinke, M.; Gülhan, A.; Schröder, W.

2015-06-01

The turbulent wake of a generic space launcher at cold hypersonic freestream conditions is investigated experimentally and numerically to gain detailed insight into the intricate base flow phenomena of space vehicles at upper stages of the flight trajectory. The experiments are done at Ma∞ = 6 and ReD = 1.7 · 106 m-1 by the German Aerospace Center (DLR) and the corresponding computations are performed by the Institute of Aerodynamics Aachen using a zonal Reynolds-averaged Navier-Stokes / Large-Eddy Simulation (RANS/LES) approach. Two different aft-body geometries consisting of a blunt base and an attached cylindrical nozzle dummy are considered. It is found that the wind tunnel model support attached to the upper side of the main body has a nonnegligible impact on the wake along the whole circumference, albeit on the opposite side, the effects are minimal compared to an axisymmetric configuration. In the blunt-base case, the turbulent supersonic boundary layer undergoes a strong aftexpansion on the model shoulder leading to the formation of a confined low-pressure (p/p∞ ≈ 0.2) recirculation region. Adding a nozzle dummy causes the shear layer to reattach on the its wall at x/D ˜ 0.6 and the base pressure level to increase (p/p∞ ≈ 0.25) compared to the blunt-base case. For both configurations, the pressure fluctuations on the base wall feature dominant frequencies at SrD ≈ 0.05 and SrD ≈ 0.2-0.27, but are of small amplitudes (prms/p∞ = 0.02-0.025) compared to the main body boundary layer. For the nozzle dummy configuration, when moving downstream along the nozzle extension, the wall pressure is increasingly influenced by the reattaching shear layer and the periodic low-frequency behavior becomes less pronounced. Directly behind the reattachment point, the wall pressure reaches maximum mean and root-mean-square (rms) values of about p/p∞ = 1 and p'rms/p∞ = 0.1 and features a broadband specrms trum without distinct frequencies determined by the incoming turbulent supersonic boundary layer.

Functional magnetic resonance imaging activation detection: fuzzy cluster analysis in wavelet and multiwavelet domains.

PubMed

Jahanian, Hesamoddin; Soltanian-Zadeh, Hamid; Hossein-Zadeh, Gholam-Ali

2005-09-01

To present novel feature spaces, based on multiscale decompositions obtained by scalar wavelet and multiwavelet transforms, to remedy problems associated with high dimension of functional magnetic resonance imaging (fMRI) time series (when they are used directly in clustering algorithms) and their poor signal-to-noise ratio (SNR) that limits accurate classification of fMRI time series according to their activation contents. Using randomization, the proposed method finds wavelet/multiwavelet coefficients that represent the activation content of fMRI time series and combines them to define new feature spaces. Using simulated and experimental fMRI data sets, the proposed feature spaces are compared to the cross-correlation (CC) feature space and their performances are evaluated. In these studies, the false positive detection rate is controlled using randomization. To compare different methods, several points of the receiver operating characteristics (ROC) curves, using simulated data, are estimated and compared. The proposed features suppress the effects of confounding signals and improve activation detection sensitivity. Experimental results show improved sensitivity and robustness of the proposed method compared to the conventional CC analysis. More accurate and sensitive activation detection can be achieved using the proposed feature spaces compared to CC feature space. Multiwavelet features show superior detection sensitivity compared to the scalar wavelet features. (c) 2005 Wiley-Liss, Inc.

Selective Laser Treatment on Cold-Sprayed Titanium Coatings: Numerical Modeling and Experimental Analysis

NASA Astrophysics Data System (ADS)

Carlone, Pierpaolo; Astarita, Antonello; Rubino, Felice; Pasquino, Nicola; Aprea, Paolo

2016-12-01

In this paper, a selective laser post-deposition on pure grade II titanium coatings, cold-sprayed on AA2024-T3 sheets, was experimentally and numerically investigated. Morphological features, microstructure, and chemical composition of the treated zone were assessed by means of optical microscopy, scanning electron microscopy, and energy dispersive X-ray spectrometry. Microhardness measurements were also carried out to evaluate the mechanical properties of the coating. A numerical model of the laser treatment was implemented and solved to simulate the process and discuss the experimental outcomes. Obtained results highlighted the key role played by heat input and dimensional features on the effectiveness of the treatment.

Edge Length and Surface Area of a Blank: Experimental Assessment of Measures, Size Predictions and Utility

PubMed Central

Dogandžić, Tamara; Braun, David R.; McPherron, Shannon P.

2015-01-01

Blank size and form represent one of the main sources of variation in lithic assemblages. They reflect economic properties of blanks and factors such as efficiency and use life. These properties require reliable measures of size, namely edge length and surface area. These measures, however, are not easily captured with calipers. Most attempts to quantify these features employ estimates; however, the efficacy of these estimations for measuring critical features such as blank surface area and edge length has never been properly evaluated. In addition, these parameters are even more difficult to acquire for retouched implements as their original size and hence indication of their previous utility have been lost. It has been suggested, in controlled experimental conditions, that two platform variables, platform thickness and exterior platform angle, are crucial in determining blank size and shape meaning that knappers can control the interaction between size and efficiency by selecting specific core angles and controlling where fracture is initiated. The robustness of these models has rarely been tested and confirmed in context other than controlled experiments. In this paper, we evaluate which currently employed caliper measurement methods result in the highest accuracy of size estimations of blanks, and we evaluate how platform variables can be used to indirectly infer aspects of size on retouched artifacts. Furthermore, we investigate measures of different platform management strategies that control the shape and size of artifacts. To investigate these questions, we created an experimental lithic assemblage, we digitized images to calculate 2D surface area and edge length, which are used as a point of comparison for the caliper measurements and additional analyses. The analysis of aspects of size determinations and the utility of blanks contributes to our understanding of the technological strategies of prehistoric knappers and what economic decisions they made during process of blank production. PMID:26332773

Methodological standards and interpretation of video-electroencephalography in adult control rodents. A TASK1-WG1 report of the AES/ILAE Translational Task Force of the ILAE.

PubMed

Kadam, Shilpa D; D'Ambrosio, Raimondo; Duveau, Venceslas; Roucard, Corinne; Garcia-Cairasco, Norberto; Ikeda, Akio; de Curtis, Marco; Galanopoulou, Aristea S; Kelly, Kevin M

2017-11-01

In vivo electrophysiological recordings are widely used in neuroscience research, and video-electroencephalography (vEEG) has become a mainstay of preclinical neuroscience research, including studies of epilepsy and cognition. Studies utilizing vEEG typically involve comparison of measurements obtained from different experimental groups, or from the same experimental group at different times, in which one set of measurements serves as "control" and the others as "test" of the variables of interest. Thus, controls provide mainly a reference measurement for the experimental test. Control rodents represent an undiagnosed population, and cannot be assumed to be "normal" in the sense of being "healthy." Certain physiological EEG patterns seen in humans are also seen in control rodents. However, interpretation of rodent vEEG studies relies on documented differences in frequency, morphology, type, location, behavioral state dependence, reactivity, and functional or structural correlates of specific EEG patterns and features between control and test groups. This paper will focus on the vEEG of standard laboratory rodent strains with the aim of developing a small set of practical guidelines that can assist researchers in the design, reporting, and interpretation of future vEEG studies. To this end, we will: (1) discuss advantages and pitfalls of common vEEG techniques in rodents and propose a set of recommended practices and (2) present EEG patterns and associated behaviors recorded from adult rats of a variety of strains. We will describe the defining features of selected vEEG patterns (brain-generated or artifactual) and note similarities to vEEG patterns seen in adult humans. We will note similarities to normal variants or pathological human EEG patterns and defer their interpretation to a future report focusing on rodent seizure patterns. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Main trends in experimental morphological research in angiology and outlook for its development

NASA Technical Reports Server (NTRS)

Dzhavakhishvili, N. A.; Melman, Y. P.

1980-01-01

The main prospective trends in the problem of collateral circulation and new trends in experimental angiology with respect to the effect of gravitational forces, hypodynamia and hypokinesia on the vascular bed are discussed.

Detection of silicate emission features in the 8- to 13-micron spectra of main belt asteroids

NASA Technical Reports Server (NTRS)

Feierberg, M. A.; Witteborn, F. C.; Lebofsky, L. A.

1983-01-01

A presentation is given of 8.0-13.0 micron spectra (Delta lambda/lambda = 0.02-0.03) for six main belt asteroids, which range from 58 to 220 km in diameter and sample the five principal taxonomic classes (C, S, M, R and E). Narrow, well-defined silicate emission features are present on two of the asteroids, the C-type 19 Fortuna and the M-type 21 Lutetia. No comparable emission features are observed on the S-types 11 Parthenope and 14 Irene, the R-type 349 Dembowska or the E-type 64 Angelina.

Multi-task linear programming discriminant analysis for the identification of progressive MCI individuals.

PubMed

Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

2014-01-01

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images). Experimental results show very promising performance of our proposed MLPD method.

Specific excitatory connectivity for feature integration in mouse primary visual cortex

PubMed Central

Molina-Luna, Patricia; Roth, Morgane M.

2017-01-01

Local excitatory connections in mouse primary visual cortex (V1) are stronger and more prevalent between neurons that share similar functional response features. However, the details of how functional rules for local connectivity shape neuronal responses in V1 remain unknown. We hypothesised that complex responses to visual stimuli may arise as a consequence of rules for selective excitatory connectivity within the local network in the superficial layers of mouse V1. In mouse V1 many neurons respond to overlapping grating stimuli (plaid stimuli) with highly selective and facilitatory responses, which are not simply predicted by responses to single gratings presented alone. This complexity is surprising, since excitatory neurons in V1 are considered to be mainly tuned to single preferred orientations. Here we examined the consequences for visual processing of two alternative connectivity schemes: in the first case, local connections are aligned with visual properties inherited from feedforward input (a ‘like-to-like’ scheme specifically connecting neurons that share similar preferred orientations); in the second case, local connections group neurons into excitatory subnetworks that combine and amplify multiple feedforward visual properties (a ‘feature binding’ scheme). By comparing predictions from large scale computational models with in vivo recordings of visual representations in mouse V1, we found that responses to plaid stimuli were best explained by assuming feature binding connectivity. Unlike under the like-to-like scheme, selective amplification within feature-binding excitatory subnetworks replicated experimentally observed facilitatory responses to plaid stimuli; explained selective plaid responses not predicted by grating selectivity; and was consistent with broad anatomical selectivity observed in mouse V1. Our results show that visual feature binding can occur through local recurrent mechanisms without requiring feedforward convergence, and that such a mechanism is consistent with visual responses and cortical anatomy in mouse V1. PMID:29240769

Multi-Task Linear Programming Discriminant Analysis for the Identification of Progressive MCI Individuals

PubMed Central

Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

2014-01-01

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images). Experimental results show very promising performance of our proposed MLPD method. PMID:24820966

78 FR 56227 - Issuance of an Experimental Use Permit

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-12

... experimental use permit (EUP) to the pesticide applicant, Robert I. Rose, Ph.D., on behalf of James Mains, Ph.D.... Issuance. Robert I. Rose, Ph.D., on behalf of James Mains, Ph.D., Mosquito Mate, Inc., 1122 Oak Hill Drive...

Experimental placement of stone matrix asphalt : project STP-8724 (00) X South Portland.

DOT National Transportation Integrated Search

2004-01-01

In September 2003 the Maine Department of Transportation used stone matrix asphalt and Superpave to : renovate two intersections in South Portland, Maine. The experimental placement of stone matrix asphalt : (SMA) and Superpave with modified binder w...

Wavelet decomposition based principal component analysis for face recognition using MATLAB

NASA Astrophysics Data System (ADS)

Sharma, Mahesh Kumar; Sharma, Shashikant; Leeprechanon, Nopbhorn; Ranjan, Aashish

2016-03-01

For the realization of face recognition systems in the static as well as in the real time frame, algorithms such as principal component analysis, independent component analysis, linear discriminate analysis, neural networks and genetic algorithms are used for decades. This paper discusses an approach which is a wavelet decomposition based principal component analysis for face recognition. Principal component analysis is chosen over other algorithms due to its relative simplicity, efficiency, and robustness features. The term face recognition stands for identifying a person from his facial gestures and having resemblance with factor analysis in some sense, i.e. extraction of the principal component of an image. Principal component analysis is subjected to some drawbacks, mainly the poor discriminatory power and the large computational load in finding eigenvectors, in particular. These drawbacks can be greatly reduced by combining both wavelet transform decomposition for feature extraction and principal component analysis for pattern representation and classification together, by analyzing the facial gestures into space and time domain, where, frequency and time are used interchangeably. From the experimental results, it is envisaged that this face recognition method has made a significant percentage improvement in recognition rate as well as having a better computational efficiency.

Monte Carlo modeling of single-molecule cytoplasmic dynein.

PubMed

Singh, Manoranjan P; Mallik, Roop; Gross, Steven P; Yu, Clare C

2005-08-23

Molecular motors are responsible for active transport and organization in the cell, underlying an enormous number of crucial biological processes. Dynein is more complicated in its structure and function than other motors. Recent experiments have found that, unlike other motors, dynein can take different size steps along microtubules depending on load and ATP concentration. We use Monte Carlo simulations to model the molecular motor function of cytoplasmic dynein at the single-molecule level. The theory relates dynein's enzymatic properties to its mechanical force production. Our simulations reproduce the main features of recent single-molecule experiments that found a discrete distribution of dynein step sizes, depending on load and ATP concentration. The model reproduces the large steps found experimentally under high ATP and no load by assuming that the ATP binding affinities at the secondary sites decrease as the number of ATP bound to these sites increases. Additionally, to capture the essential features of the step-size distribution at very low ATP concentration and no load, the ATP hydrolysis of the primary site must be dramatically reduced when none of the secondary sites have ATP bound to them. We make testable predictions that should guide future experiments related to dynein function.

Enhancing business intelligence by means of suggestive reviews.

PubMed

Qazi, Atika; Raj, Ram Gopal; Tahir, Muhammad; Cambria, Erik; Syed, Karim Bux Shah

2014-01-01

Appropriate identification and classification of online reviews to satisfy the needs of current and potential users pose a critical challenge for the business environment. This paper focuses on a specific kind of reviews: the suggestive type. Suggestions have a significant influence on both consumers' choices and designers' understanding and, hence, they are key for tasks such as brand positioning and social media marketing. The proposed approach consists of three main steps: (1) classify comparative and suggestive sentences; (2) categorize suggestive sentences into different types, either explicit or implicit locutions; (3) perform sentiment analysis on the classified reviews. A range of supervised machine learning approaches and feature sets are evaluated to tackle the problem of suggestive opinion mining. Experimental results for all three tasks are obtained on a dataset of mobile phone reviews and demonstrate that extending a bag-of-words representation with suggestive and comparative patterns is ideal for distinguishing suggestive sentences. In particular, it is observed that classifying suggestive sentences into implicit and explicit locutions works best when using a mixed sequential rule feature representation. Sentiment analysis achieves maximum performance when employing additional preprocessing in the form of negation handling and target masking, combined with sentiment lexicons.

Firefly Mating Algorithm for Continuous Optimization Problems

PubMed Central

Ritthipakdee, Amarita; Premasathian, Nol; Jitkongchuen, Duangjai

2017-01-01

This paper proposes a swarm intelligence algorithm, called firefly mating algorithm (FMA), for solving continuous optimization problems. FMA uses genetic algorithm as the core of the algorithm. The main feature of the algorithm is a novel mating pair selection method which is inspired by the following 2 mating behaviors of fireflies in nature: (i) the mutual attraction between males and females causes them to mate and (ii) fireflies of both sexes are of the multiple-mating type, mating with multiple opposite sex partners. A female continues mating until her spermatheca becomes full, and, in the same vein, a male can provide sperms for several females until his sperm reservoir is depleted. This new feature enhances the global convergence capability of the algorithm. The performance of FMA was tested with 20 benchmark functions (sixteen 30-dimensional functions and four 2-dimensional ones) against FA, ALC-PSO, COA, MCPSO, LWGSODE, MPSODDS, DFOA, SHPSOS, LSA, MPDPGA, DE, and GABC algorithms. The experimental results showed that the success rates of our proposed algorithm with these functions were higher than those of other algorithms and the proposed algorithm also required fewer numbers of iterations to reach the global optima. PMID:28808442

An Experimental Study of Droplets Produced by a Plunging Breakers

NASA Astrophysics Data System (ADS)

Erinin, Martin; Wang, Dan; Towle, David; Liu, Xinan; Duncan, James

2016-11-01

In this study, the production of droplets by a mechanically generated plunging breaking water wave is investigated in a wave tank. The breaker, with an amplitude of 0.070 m, is generated repeatedly with a programmable wave maker by using a dispersively focused wave packet (average frequency 1.15 Hz). The profile histories of the breaking wave crests along the center plane of the tank are measured using cinematic laser-induced fluorescence. The droplets are measured using a cinematic digital in-line holographic system positioned at 30 locations along a horizontal plane that is 1 cm above the maximum wave crest height. This measurement plane covers the entire region in the tank where the wave breaks. The holographic system is used to obtain the droplet diameters (d, for d >100 microns) and the three components of the droplet velocities. From these measurements and counting only the droplets that are moving up, the spatio-temporal distribution of droplet generation by the breaking wave is obtained. The main features of the droplet generation are correlated with the features and phases of the breaking process. The support of the National Science Foundation under Grant OCE0751853 from the Division of Ocean Sciences is gratefully acknowledged.

Cluster Headache: Epidemiology, Pathophysiology, Clinical Features, and Diagnosis

PubMed Central

Wei, Diana Yi-Ting; Yuan Ong, Jonathan Jia; Goadsby, Peter James

2018-01-01

Cluster headache is a primary headache disorder affecting up to 0.1% of the population. Patients suffer from cluster headache attacks lasting from 15 to 180 min up to 8 times a day. The attacks are characterized by the severe unilateral pain mainly in the first division of the trigeminal nerve, with associated prominent unilateral cranial autonomic symptoms and a sense of agitation and restlessness during the attacks. The male-to-female ratio is approximately 2.5:1. Experimental, clinical, and neuroimaging studies have advanced our understanding of the pathogenesis of cluster headache. The pathophysiology involves activation of the trigeminovascular complex and the trigeminal-autonomic reflex and accounts for the unilateral severe headache, the prominent ipsilateral cranial autonomic symptoms. In addition, the circadian and circannual rhythmicity unique to this condition is postulated to involve the hypothalamus and suprachiasmatic nucleus. Although the clinical features are distinct, it may be misdiagnosed, with patients often presenting to the otolaryngologist or dentist with symptoms. The prognosis of cluster headache remains difficult to predict. Patients with episodic cluster headache can shift to chronic cluster headache and vice versa. Longitudinally, cluster headache tends to remit with age with less frequent bouts and more prolonged periods of remission in between bouts. PMID:29720812

Cluster Headache: Epidemiology, Pathophysiology, Clinical Features, and Diagnosis.

PubMed

Wei, Diana Yi-Ting; Yuan Ong, Jonathan Jia; Goadsby, Peter James

2018-04-01

Cluster headache is a primary headache disorder affecting up to 0.1% of the population. Patients suffer from cluster headache attacks lasting from 15 to 180 min up to 8 times a day. The attacks are characterized by the severe unilateral pain mainly in the first division of the trigeminal nerve, with associated prominent unilateral cranial autonomic symptoms and a sense of agitation and restlessness during the attacks. The male-to-female ratio is approximately 2.5:1. Experimental, clinical, and neuroimaging studies have advanced our understanding of the pathogenesis of cluster headache. The pathophysiology involves activation of the trigeminovascular complex and the trigeminal-autonomic reflex and accounts for the unilateral severe headache, the prominent ipsilateral cranial autonomic symptoms. In addition, the circadian and circannual rhythmicity unique to this condition is postulated to involve the hypothalamus and suprachiasmatic nucleus. Although the clinical features are distinct, it may be misdiagnosed, with patients often presenting to the otolaryngologist or dentist with symptoms. The prognosis of cluster headache remains difficult to predict. Patients with episodic cluster headache can shift to chronic cluster headache and vice versa. Longitudinally, cluster headache tends to remit with age with less frequent bouts and more prolonged periods of remission in between bouts.

Structural analysis of online handwritten mathematical symbols based on support vector machines

NASA Astrophysics Data System (ADS)

Simistira, Foteini; Papavassiliou, Vassilis; Katsouros, Vassilis; Carayannis, George

2013-01-01

Mathematical expression recognition is still a very challenging task for the research community mainly because of the two-dimensional (2d) structure of mathematical expressions (MEs). In this paper, we present a novel approach for the structural analysis between two on-line handwritten mathematical symbols of a ME, based on spatial features of the symbols. We introduce six features to represent the spatial affinity of the symbols and compare two multi-class classification methods that employ support vector machines (SVMs): one based on the "one-against-one" technique and one based on the "one-against-all", in identifying the relation between a pair of symbols (i.e. subscript, numerator, etc). A dataset containing 1906 spatial relations derived from the Competition on Recognition of Online Handwritten Mathematical Expressions (CROHME) 2012 training dataset is constructed to evaluate the classifiers and compare them with the rule-based classifier of the ILSP-1 system participated in the contest. The experimental results give an overall mean error rate of 2.61% for the "one-against-one" SVM approach, 6.57% for the "one-against-all" SVM technique and 12.31% error rate for the ILSP-1 classifier.

Unified framework for triaxial accelerometer-based fall event detection and classification using cumulants and hierarchical decision tree classifier.

PubMed

Kambhampati, Satya Samyukta; Singh, Vishal; Manikandan, M Sabarimalai; Ramkumar, Barathram

2015-08-01

In this Letter, the authors present a unified framework for fall event detection and classification using the cumulants extracted from the acceleration (ACC) signals acquired using a single waist-mounted triaxial accelerometer. The main objective of this Letter is to find suitable representative cumulants and classifiers in effectively detecting and classifying different types of fall and non-fall events. It was discovered that the first level of the proposed hierarchical decision tree algorithm implements fall detection using fifth-order cumulants and support vector machine (SVM) classifier. In the second level, the fall event classification algorithm uses the fifth-order cumulants and SVM. Finally, human activity classification is performed using the second-order cumulants and SVM. The detection and classification results are compared with those of the decision tree, naive Bayes, multilayer perceptron and SVM classifiers with different types of time-domain features including the second-, third-, fourth- and fifth-order cumulants and the signal magnitude vector and signal magnitude area. The experimental results demonstrate that the second- and fifth-order cumulant features and SVM classifier can achieve optimal detection and classification rates of above 95%, as well as the lowest false alarm rate of 1.03%.

X-ray Absorption and Emission Spectroscopy of CrIII (Hydr)Oxides: Analysis of the K-Pre-Edge Region

NASA Astrophysics Data System (ADS)

Frommer, Jakob; Nachtegaal, Maarten; Czekaj, Izabela; Weng, Tsu-Chien; Kretzschmar, Ruben

2009-10-01

Pre-edge spectral features below the main X-ray absorption K-edge of transition metals show a pronounced chemical sensitivity and are promising sources of structural information. Nevertheless, the use of pre-edge analysis in applied research is limited because of the lack of definite theoretical peak-assignments. The aim of this study was to determine the factors affecting the chromium K-pre-edge features in trivalent chromium-bearing oxides and oxyhydroxides. The selected phases varied in the degree of octahedral polymerization and the degree of iron-for-chromium substitution in the crystal structure. We investigated the pre-edge fine structure by means of high-energy-resolution fluorescence detected X-ray absorption spectroscopy and by 1s2p resonant X-ray emission spectroscopy. Multiplet theory and full multiple-scattering calculations were used to analyze the experimental data. We show that the chromium K-pre-edge contains localized and nonlocalized transitions. Contributions arising from nonlocalized metal-metal transitions are sensitive to the nearest metal type and to the linkage mode between neighboring metal octahedra. Analyzing these transitions opens up new opportunities for investigating the local coordination environment of chromium in poorly ordered solids of environmental relevance.

A Michelson Interferometer for Electron Cyclotron Emission Measurements on EAST

NASA Astrophysics Data System (ADS)

Liu, Yong; Stefan, Schmuck; Zhao, Hailin; John, Fessey; Paul, Trimble; Liu, Xiang; Zhu, Zeying; Zang, Qing; Hu, Liqun

2016-12-01

A Michelson interferometer, on loan from EFDA-JET (Culham, United Kingdom) has recently been commissioned on the experimental advanced superconducting tokamak (EAST, ASIPP, Hefei, China). Following a successful in-situ absolute calibration the instrument is able to measure the electron cyclotron emission (ECE) spectrum, from 80 GHz to 350 GHz in extraordinary mode (X-mode) polarization, with high accuracy. This allows the independent determination of the electron temperature profile from observation of the second harmonic ECE and the possible identification of non-Maxwellian features by comparing higher harmonic emission with numerical simulations. The in-situ calibration results are presented together with the initial measured temperature profiles. These measurements are then discussed and compared with other independent temperature profile measurements. This paper also describes the main hardware features of the diagnostic and the associated commissioning test results. supported by National Natural Science Foundation of China (Nos. 11405211, 11275233), and the National Magnetic Confinement Fusion Science Program of China (Nos. 2013GB106002, 2015GB101000), and the RCUK Energy Programme (No. EP/I501045), partly supported by the JSPS-NRF-NSFC A3 Foresight Program in the Field of Plasma Physics (NSFC: No. 11261140328)

Firefly Mating Algorithm for Continuous Optimization Problems.

PubMed

Ritthipakdee, Amarita; Thammano, Arit; Premasathian, Nol; Jitkongchuen, Duangjai

2017-01-01

This paper proposes a swarm intelligence algorithm, called firefly mating algorithm (FMA), for solving continuous optimization problems. FMA uses genetic algorithm as the core of the algorithm. The main feature of the algorithm is a novel mating pair selection method which is inspired by the following 2 mating behaviors of fireflies in nature: (i) the mutual attraction between males and females causes them to mate and (ii) fireflies of both sexes are of the multiple-mating type, mating with multiple opposite sex partners. A female continues mating until her spermatheca becomes full, and, in the same vein, a male can provide sperms for several females until his sperm reservoir is depleted. This new feature enhances the global convergence capability of the algorithm. The performance of FMA was tested with 20 benchmark functions (sixteen 30-dimensional functions and four 2-dimensional ones) against FA, ALC-PSO, COA, MCPSO, LWGSODE, MPSODDS, DFOA, SHPSOS, LSA, MPDPGA, DE, and GABC algorithms. The experimental results showed that the success rates of our proposed algorithm with these functions were higher than those of other algorithms and the proposed algorithm also required fewer numbers of iterations to reach the global optima.

Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network.

PubMed

Li, Yuexiang; Shen, Linlin

2018-02-11

Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging due to the following reasons: low contrast between lesions and skin, visual similarity between melanoma and non-melanoma lesions, etc. Hence, reliable automatic detection of skin tumors is very useful to increase the accuracy and efficiency of pathologists. In this paper, we proposed two deep learning methods to address three main tasks emerging in the area of skin lesion image processing, i.e., lesion segmentation (task 1), lesion dermoscopic feature extraction (task 2) and lesion classification (task 3). A deep learning framework consisting of two fully convolutional residual networks (FCRN) is proposed to simultaneously produce the segmentation result and the coarse classification result. A lesion index calculation unit (LICU) is developed to refine the coarse classification results by calculating the distance heat-map. A straight-forward CNN is proposed for the dermoscopic feature extraction task. The proposed deep learning frameworks were evaluated on the ISIC 2017 dataset. Experimental results show the promising accuracies of our frameworks, i.e., 0.753 for task 1, 0.848 for task 2 and 0.912 for task 3 were achieved.