HybridGO-Loc: mining hybrid features on gene ontology for predicting subcellular localization of multi-location proteins.

PubMed

Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

2014-01-01

Protein subcellular localization prediction, as an essential step to elucidate the functions in vivo of proteins and identify drugs targets, has been extensively studied in previous decades. Instead of only determining subcellular localization of single-label proteins, recent studies have focused on predicting both single- and multi-location proteins. Computational methods based on Gene Ontology (GO) have been demonstrated to be superior to methods based on other features. However, existing GO-based methods focus on the occurrences of GO terms and disregard their relationships. This paper proposes a multi-label subcellular-localization predictor, namely HybridGO-Loc, that leverages not only the GO term occurrences but also the inter-term relationships. This is achieved by hybridizing the GO frequencies of occurrences and the semantic similarity between GO terms. Given a protein, a set of GO terms are retrieved by searching against the gene ontology database, using the accession numbers of homologous proteins obtained via BLAST search as the keys. The frequency of GO occurrences and semantic similarity (SS) between GO terms are used to formulate frequency vectors and semantic similarity vectors, respectively, which are subsequently hybridized to construct fusion vectors. An adaptive-decision based multi-label support vector machine (SVM) classifier is proposed to classify the fusion vectors. Experimental results based on recent benchmark datasets and a new dataset containing novel proteins show that the proposed hybrid-feature predictor significantly outperforms predictors based on individual GO features as well as other state-of-the-art predictors. For readers' convenience, the HybridGO-Loc server, which is for predicting virus or plant proteins, is available online at http://bioinfo.eie.polyu.edu.hk/HybridGoServer/.

A Hybrid RANS/LES Approach for Predicting Jet Noise

NASA Technical Reports Server (NTRS)

Goldstein, Marvin E.

2006-01-01

Hybrid acoustic prediction methods have an important advantage over the current Reynolds averaged Navier-Stokes (RANS) based methods in that they only involve modeling of the relatively universal subscale motion and not the configuration dependent larger scale turbulence. Unfortunately, they are unable to account for the high frequency sound generated by the turbulence in the initial mixing layers. This paper introduces an alternative approach that directly calculates the sound from a hybrid RANS/LES flow model (which can resolve the steep gradients in the initial mixing layers near the nozzle lip) and adopts modeling techniques similar to those used in current RANS based noise prediction methods to determine the unknown sources in the equations for the remaining unresolved components of the sound field. The resulting prediction method would then be intermediate between the current noise prediction codes and previously proposed hybrid noise prediction methods.

General hybrid projective complete dislocated synchronization with non-derivative and derivative coupling based on parameter identification in several chaotic and hyperchaotic systems

NASA Astrophysics Data System (ADS)

Sun, Jun-Wei; Shen, Yi; Zhang, Guo-Dong; Wang, Yan-Feng; Cui, Guang-Zhao

2013-04-01

According to the Lyapunov stability theorem, a new general hybrid projective complete dislocated synchronization scheme with non-derivative and derivative coupling based on parameter identification is proposed under the framework of drive-response systems. Every state variable of the response system equals the summation of the hybrid drive systems in the previous hybrid synchronization. However, every state variable of the drive system equals the summation of the hybrid response systems while evolving with time in our method. Complete synchronization, hybrid dislocated synchronization, projective synchronization, non-derivative and derivative coupling, and parameter identification are included as its special item. The Lorenz chaotic system, Rössler chaotic system, memristor chaotic oscillator system, and hyperchaotic Lü system are discussed to show the effectiveness of the proposed methods.

Health Monitoring of a Planetary Rover Using Hybrid Particle Petri Nets

NASA Technical Reports Server (NTRS)

Gaudel, Quentin; Ribot, Pauline; Chanthery, Elodie; Daigle, Matthew J.

2016-01-01

This paper focuses on the application of a Petri Net-based diagnosis method on a planetary rover prototype.The diagnosis is performed by using a model-based method in the context of health management of hybrid systems.In system health management, the diagnosis task aims at determining the current health state of a system and the fault occurrences that lead to this state. The Hybrid Particle Petri Nets (HPPN) formalism is used to model hybrid systems behavior and degradation, and to define the generation of diagnosers to monitor the health states of such systems under uncertainty. At any time, the HPPN-based diagnoser provides the current diagnosis represented by a distribution of beliefs over the health states. The health monitoring methodology is demonstrated on the K11 rover. A hybrid model of the K11 is proposed and experimental results show that the approach is robust to real system data and constraints.

Hybrid Evidence Theory-based Finite Element/Statistical Energy Analysis method for mid-frequency analysis of built-up systems with epistemic uncertainties

NASA Astrophysics Data System (ADS)

Yin, Shengwen; Yu, Dejie; Yin, Hui; Lü, Hui; Xia, Baizhan

2017-09-01

Considering the epistemic uncertainties within the hybrid Finite Element/Statistical Energy Analysis (FE/SEA) model when it is used for the response analysis of built-up systems in the mid-frequency range, the hybrid Evidence Theory-based Finite Element/Statistical Energy Analysis (ETFE/SEA) model is established by introducing the evidence theory. Based on the hybrid ETFE/SEA model and the sub-interval perturbation technique, the hybrid Sub-interval Perturbation and Evidence Theory-based Finite Element/Statistical Energy Analysis (SIP-ETFE/SEA) approach is proposed. In the hybrid ETFE/SEA model, the uncertainty in the SEA subsystem is modeled by a non-parametric ensemble, while the uncertainty in the FE subsystem is described by the focal element and basic probability assignment (BPA), and dealt with evidence theory. Within the hybrid SIP-ETFE/SEA approach, the mid-frequency response of interest, such as the ensemble average of the energy response and the cross-spectrum response, is calculated analytically by using the conventional hybrid FE/SEA method. Inspired by the probability theory, the intervals of the mean value, variance and cumulative distribution are used to describe the distribution characteristics of mid-frequency responses of built-up systems with epistemic uncertainties. In order to alleviate the computational burdens for the extreme value analysis, the sub-interval perturbation technique based on the first-order Taylor series expansion is used in ETFE/SEA model to acquire the lower and upper bounds of the mid-frequency responses over each focal element. Three numerical examples are given to illustrate the feasibility and effectiveness of the proposed method.

Nanoscale hybrid systems based on carbon nanotubes for biological sensing and control

PubMed Central

Cho, Youngtak; Shin, Narae; Kim, Daesan; Park, Jae Yeol

2017-01-01

This paper provides a concise review on the recent development of nanoscale hybrid systems based on carbon nanotubes (CNTs) for biological sensing and control. CNT-based hybrid systems have been intensively studied for versatile applications of biological interfaces such as sensing, cell therapy and tissue regeneration. Recent advances in nanobiotechnology not only enable the fabrication of highly sensitive biosensors at nanoscale but also allow the applications in the controls of cell growth and differentiation. This review describes the fabrication methods of such CNT-based hybrid systems and their applications in biosensing and cell controls. PMID:28188158

An Ellipsoidal Particle-Finite Element Method for Hypervelocity Impact Simulation. Chapter 1

NASA Technical Reports Server (NTRS)

Shivarama, Ravishankar; Fahrenthold, Eric P.

2004-01-01

A number of coupled particle-element and hybrid particle-element methods have been developed for the simulation of hypervelocity impact problems, to avoid certain disadvantages associated with the use of pure continuum based or pure particle based methods. To date these methods have employed spherical particles. In recent work a hybrid formulation has been extended to the ellipsoidal particle case. A model formulation approach based on Lagrange's equations, with particles entropies serving as generalized coordinates, avoids the angular momentum conservation problems which have been reported with ellipsoidal smooth particle hydrodynamics models.

Efficient parameter estimation in longitudinal data analysis using a hybrid GEE method.

PubMed

Leung, Denis H Y; Wang, You-Gan; Zhu, Min

2009-07-01

The method of generalized estimating equations (GEEs) provides consistent estimates of the regression parameters in a marginal regression model for longitudinal data, even when the working correlation model is misspecified (Liang and Zeger, 1986). However, the efficiency of a GEE estimate can be seriously affected by the choice of the working correlation model. This study addresses this problem by proposing a hybrid method that combines multiple GEEs based on different working correlation models, using the empirical likelihood method (Qin and Lawless, 1994). Analyses show that this hybrid method is more efficient than a GEE using a misspecified working correlation model. Furthermore, if one of the working correlation structures correctly models the within-subject correlations, then this hybrid method provides the most efficient parameter estimates. In simulations, the hybrid method's finite-sample performance is superior to a GEE under any of the commonly used working correlation models and is almost fully efficient in all scenarios studied. The hybrid method is illustrated using data from a longitudinal study of the respiratory infection rates in 275 Indonesian children.

Ultrasensitive Hybridization-Based ELISA Method for the Determination of Phosphorodiamidate Morpholino Oligonucleotides in Biological samples.

PubMed

Burki, Umar; Straub, Volker

2017-01-01

Determining the concentration of oligonucleotide in biological samples such as tissue lysate and serum is essential for determining the biodistribution and pharmacokinetic profile, respectively. ELISA-based assays have shown far greater sensitivities compared to other methods such as HPLC and LC/MS. Here, we describe a novel ultrasensitive hybridization-based ELISA method for quantitating morpholino oligonucleotides in mouse tissue lysate and serum samples. The assay has a linear detection range of 5-250 pM (R2 > 0.99).

Assessing the impact of lyophilization process in production of implants based on the bacterial cellulose using Raman spectroscopy method

NASA Astrophysics Data System (ADS)

Timchenko, E. V.; Timchenko, P. E.; Pisareva, E. V.; Vlasov, M. Yu; Revin, V. V.; Klenova, N. A.; Asadova, A. A.

2017-01-01

In this article we present the research results of lyophilization process influence on the composition of hybrid materials based on the bacterial cellulose (BC) using Raman spectroscopy method. As an object of research was used BC, as well as hybrids based on it, comprising the various combinations of hydroxyapatite (HAP) and collagen. Our studies showed that during the lyophilization process changes the ratio of the individual components. It was found that for samples hybrid based on BC with addition of HAP occurs increase of PO4 3- peak intensity in the region 956 cm-1 with decreasing width, which indicates a change in the degree of HAP crystallinity.

Accurate modeling of switched reluctance machine based on hybrid trained WNN

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

Song, Shoujun, E-mail: sunnyway@nwpu.edu.cn; Ge, Lefei; Ma, Shaojie

2014-04-15

According to the strong nonlinear electromagnetic characteristics of switched reluctance machine (SRM), a novel accurate modeling method is proposed based on hybrid trained wavelet neural network (WNN) which combines improved genetic algorithm (GA) with gradient descent (GD) method to train the network. In the novel method, WNN is trained by GD method based on the initial weights obtained per improved GA optimization, and the global parallel searching capability of stochastic algorithm and local convergence speed of deterministic algorithm are combined to enhance the training accuracy, stability and speed. Based on the measured electromagnetic characteristics of a 3-phase 12/8-pole SRM, themore » nonlinear simulation model is built by hybrid trained WNN in Matlab. The phase current and mechanical characteristics from simulation under different working conditions meet well with those from experiments, which indicates the accuracy of the model for dynamic and static performance evaluation of SRM and verifies the effectiveness of the proposed modeling method.« less

A modified hybrid uncertain analysis method for dynamic response field of the LSOAAC with random and interval parameters

NASA Astrophysics Data System (ADS)

Zi, Bin; Zhou, Bin

2016-07-01

For the prediction of dynamic response field of the luffing system of an automobile crane (LSOAAC) with random and interval parameters, a hybrid uncertain model is introduced. In the hybrid uncertain model, the parameters with certain probability distribution are modeled as random variables, whereas, the parameters with lower and upper bounds are modeled as interval variables instead of given precise values. Based on the hybrid uncertain model, the hybrid uncertain dynamic response equilibrium equation, in which different random and interval parameters are simultaneously included in input and output terms, is constructed. Then a modified hybrid uncertain analysis method (MHUAM) is proposed. In the MHUAM, based on random interval perturbation method, the first-order Taylor series expansion and the first-order Neumann series, the dynamic response expression of the LSOAAC is developed. Moreover, the mathematical characteristics of extrema of bounds of dynamic response are determined by random interval moment method and monotonic analysis technique. Compared with the hybrid Monte Carlo method (HMCM) and interval perturbation method (IPM), numerical results show the feasibility and efficiency of the MHUAM for solving the hybrid LSOAAC problems. The effects of different uncertain models and parameters on the LSOAAC response field are also investigated deeply, and numerical results indicate that the impact made by the randomness in the thrust of the luffing cylinder F is larger than that made by the gravity of the weight in suspension Q . In addition, the impact made by the uncertainty in the displacement between the lower end of the lifting arm and the luffing cylinder a is larger than that made by the length of the lifting arm L .

Methods of DNA sequencing by hybridization based on optimizing concentration of matrix-bound oligonucleotide and device for carrying out same

DOEpatents

Khrapko, Konstantin R [Moscow, RU; Khorlin, Alexandr A [Moscow, RU; Ivanov, Igor B [Moskovskaya, RU; Ershov, Gennady M [Moscow, RU; Lysov, Jury P [Moscow, RU; Florentiev, Vladimir L [Moscow, RU; Mirzabekov, Andrei D [Moscow, RU

1996-09-03

A method for sequencing DNA by hybridization that includes the following steps: forming an array of oligonucleotides at such concentrations that either ensure the same dissociation temperature for all fully complementary duplexes or allows hybridization and washing of such duplexes to be conducted at the same temperature; hybridizing said oligonucleotide array with labeled test DNA; washing in duplex dissociation conditions; identifying single-base substitutions in the test DNA by analyzing the distribution of the dissociation temperatures and reconstructing the DNA nucleotide sequence based on the above analysis. A device for carrying out the method comprises a solid substrate and a matrix rigidly bound to the substrate. The matrix contains the oligonucleotide array and consists of a multiplicity of gel portions. Each gel portion contains one oligonucleotide of desired length. The gel portions are separated from one another by interstices and have a thickness not exceeding 30 .mu.m.

Conceptual design of distillation-based hybrid separation processes.

PubMed

Skiborowski, Mirko; Harwardt, Andreas; Marquardt, Wolfgang

2013-01-01

Hybrid separation processes combine different separation principles and constitute a promising design option for the separation of complex mixtures. Particularly, the integration of distillation with other unit operations can significantly improve the separation of close-boiling or azeotropic mixtures. Although the design of single-unit operations is well understood and supported by computational methods, the optimal design of flowsheets of hybrid separation processes is still a challenging task. The large number of operational and design degrees of freedom requires a systematic and optimization-based design approach. To this end, a structured approach, the so-called process synthesis framework, is proposed. This article reviews available computational methods for the conceptual design of distillation-based hybrid processes for the separation of liquid mixtures. Open problems are identified that must be addressed to finally establish a structured process synthesis framework for such processes.

A hybrid neural learning algorithm using evolutionary learning and derivative free local search method.

PubMed

Ghosh, Ranadhir; Yearwood, John; Ghosh, Moumita; Bagirov, Adil

2006-06-01

In this paper we investigate a hybrid model based on the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. Also we discuss different variants for hybrid models using the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. The Discrete Gradient method has the advantage of being able to jump over many local minima and find very deep local minima. However, earlier research has shown that a good starting point for the discrete gradient method can improve the quality of the solution point. Evolutionary algorithms are best suited for global optimisation problems. Nevertheless they are cursed with longer training times and often unsuitable for real world application. For optimisation problems such as weight optimisation for ANNs in real world applications the dimensions are large and time complexity is critical. Hence the idea of a hybrid model can be a suitable option. In this paper we propose different fusion strategies for hybrid models combining the evolutionary strategy with the discrete gradient method to obtain an optimal solution much quicker. Three different fusion strategies are discussed: a linear hybrid model, an iterative hybrid model and a restricted local search hybrid model. Comparative results on a range of standard datasets are provided for different fusion hybrid models.

A hybrid filtering method based on a novel empirical mode decomposition for friction signals

NASA Astrophysics Data System (ADS)

Li, Chengwei; Zhan, Liwei

2015-12-01

During a measurement, the measured signal usually contains noise. To remove the noise and preserve the important feature of the signal, we introduce a hybrid filtering method that uses a new intrinsic mode function (NIMF) and a modified Hausdorff distance. The NIMF is defined as the difference between the noisy signal and each intrinsic mode function (IMF), which is obtained by empirical mode decomposition (EMD), ensemble EMD, complementary ensemble EMD, or complete ensemble EMD with adaptive noise (CEEMDAN). The relevant mode selecting is based on the similarity between the first NIMF and the rest of the NIMFs. With this filtering method, the EMD and improved versions are used to filter the simulation and friction signals. The friction signal between an airplane tire and the runaway is recorded during a simulated airplane touchdown and features spikes of various amplitudes and noise. The filtering effectiveness of the four hybrid filtering methods are compared and discussed. The results show that the filtering method based on CEEMDAN outperforms other signal filtering methods.

Development of computer informational system of diagnostics integrated optical materials, elements, and devices

NASA Astrophysics Data System (ADS)

Volosovitch, Anatoly E.; Konopaltseva, Lyudmila I.

1995-11-01

Well-known methods of optical diagnostics, database for their storage, as well as expert system (ES) for their development are analyzed. A computer informational system is developed, which is based on a hybrid ES built on modern DBMS. As an example, the structural and constructive circuits of the hybrid integrated-optical devices based on laser diodes, diffusion waveguides, geodetic lenses, package-free linear photodiode arrays, etc. are presented. The features of methods and test results as well as the advanced directions of works related to the hybrid integrated-optical devices in the field of metrology are discussed.

Sensitive fluorescence detection of nucleic acids based on isothermal circular strand-displacement polymerization reaction.

PubMed

Guo, Qiuping; Yang, Xiaohai; Wang, Kemin; Tan, Weihong; Li, Wei; Tang, Hongxing; Li, Huimin

2009-02-01

Here we have developed a sensitive DNA amplified detection method based on isothermal strand-displacement polymerization reaction. This method takes advantage of both the hybridization property of DNA and the strand-displacement property of polymerase. Importantly, we demonstrate that our method produces a circular polymerization reaction activated by the target, which essentially allows it to self-detect. Functionally, this DNA system consists of a hairpin fluorescence probe, a short primer and polymerase. Upon recognition and hybridization with the target ssDNA, the stem of the hairpin probe is opened, after which the opened probe anneals with the primer and triggers the polymerization reaction. During this process of the polymerization reaction, a complementary DNA is synthesized and the hybridized target is displaced. Finally, the displaced target recognizes and hybridizes with another probe, triggering the next round of polymerization reaction, reaching a target detection limit of 6.4 x 10(-15) M.

Carbon nanotube TiO2 hybrid films for detecting traces of O2

NASA Astrophysics Data System (ADS)

Llobet, E.; Espinosa, E. H.; Sotter, E.; Ionescu, R.; Vilanova, X.; Torres, J.; Felten, A.; Pireaux, J. J.; Ke, X.; Van Tendeloo, G.; Renaux, F.; Paint, Y.; Hecq, M.; Bittencourt, C.

2008-09-01

Hybrid titania films have been prepared using an adapted sol-gel method for obtaining well-dispersed hydrogen plasma-treated multiwall carbon nanotubes in either pure titania or Nb-doped titania. The drop-coating method has been used to fabricate resistive oxygen sensors based on titania or on titania and carbon nanotube hybrids. Morphology and composition studies have revealed that the dispersion of low amounts of carbon nanotubes within the titania matrix does not significantly alter its crystallization behaviour. The gas sensitivity studies performed on the different samples have shown that the hybrid layers based on titania and carbon nanotubes possess an unprecedented responsiveness towards oxygen (i.e. more than four times higher than that shown by optimized Nb-doped TiO2 films). Furthermore, hybrid sensors containing carbon nanotubes respond at significantly lower operating temperatures than their non-hybrid counterparts. These new hybrid sensors show a strong potential for monitoring traces of oxygen (i.e. <=10 ppm) in a flow of CO2, which is of interest for the beverage industry.

Allele-specific HLA-DR typing by mass spectrometry: an alternative to hybridization-based typing methods.

PubMed

Worrall, T A; Schmeckpeper, B J; Corvera, J S; Cotter, R J

2000-11-01

The primer oligomer base extension (PROBE) reaction, combined with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, is used to characterize HLA-DR2 polymorphism. Alleles are distinguished rapidly and accurately by measuring the mass of primer extension products at every known variable region of HLA-DR2 alleles. Since differentiation of alleles by PROBE relies on measuring differences in extension product mass rather than differences in hybridization properties, mistyped alleles resulting from nonspecific hybridization are absent. The method shows considerable potential for high-throughput screening of HLA-DR polymorphism in a chip-based format, including rapid tissue typing of unrelated volunteer donors.

Hybrid Polyvinyl Alcohol and Cellulose Fiber Pulp Instead of Asbestos Fibers in Cement-Based Composites

NASA Astrophysics Data System (ADS)

Shokrieh, M. M.; Mahmoudi, A.; Shadkam, H. R.

2015-05-01

The Taguchi method was used to determine the optimum content of a four-parameters cellulose fiber pulp, polyvinyl alcohol (PVA) fibers, a silica fume, and bentonite for cement-based composite sheets. Then cement composite sheets from the hybrid of PVA and the cellulose fiber pulp were manufactured, and their moduli of rapture were determined experimentally. The result obtained showed that cement composites with a hybrid of PVA and cellulose fiber pulp had a higher flexural strength than cellulose-fiber- reinforced cement ones, but this strength was rather similar to that of asbestos-fiber-reinforced cement composites. Also, using the results of flexural tests and an analytical method, the tensile and compressive moduli of the hybrid of PVA and cement sheet were calculated. The hybrid of PVA and cellulose fiber pulp is proposed as an appropriate alternative for substituting asbestos in the Hatschek process.

Hybrid grammar-based approach to nonlinear dynamical system identification from biological time series

NASA Astrophysics Data System (ADS)

McKinney, B. A.; Crowe, J. E., Jr.; Voss, H. U.; Crooke, P. S.; Barney, N.; Moore, J. H.

2006-02-01

We introduce a grammar-based hybrid approach to reverse engineering nonlinear ordinary differential equation models from observed time series. This hybrid approach combines a genetic algorithm to search the space of model architectures with a Kalman filter to estimate the model parameters. Domain-specific knowledge is used in a context-free grammar to restrict the search space for the functional form of the target model. We find that the hybrid approach outperforms a pure evolutionary algorithm method, and we observe features in the evolution of the dynamical models that correspond with the emergence of favorable model components. We apply the hybrid method to both artificially generated time series and experimentally observed protein levels from subjects who received the smallpox vaccine. From the observed data, we infer a cytokine protein interaction network for an individual’s response to the smallpox vaccine.

Study on Hybrid Image Search Technology Based on Texts and Contents

NASA Astrophysics Data System (ADS)

Wang, H. T.; Ma, F. L.; Yan, C.; Pan, H.

2018-05-01

Image search was studied first here based on texts and contents, respectively. The text-based image feature extraction was put forward by integrating the statistical and topic features in view of the limitation of extraction of keywords only by means of statistical features of words. On the other hand, a search-by-image method was put forward based on multi-feature fusion in view of the imprecision of the content-based image search by means of a single feature. The layered-searching method depended on primarily the text-based image search method and additionally the content-based image search was then put forward in view of differences between the text-based and content-based methods and their difficult direct fusion. The feasibility and effectiveness of the hybrid search algorithm were experimentally verified.

A survey on evolutionary algorithm based hybrid intelligence in bioinformatics.

PubMed

Li, Shan; Kang, Liying; Zhao, Xing-Ming

2014-01-01

With the rapid advance in genomics, proteomics, metabolomics, and other types of omics technologies during the past decades, a tremendous amount of data related to molecular biology has been produced. It is becoming a big challenge for the bioinformatists to analyze and interpret these data with conventional intelligent techniques, for example, support vector machines. Recently, the hybrid intelligent methods, which integrate several standard intelligent approaches, are becoming more and more popular due to their robustness and efficiency. Specifically, the hybrid intelligent approaches based on evolutionary algorithms (EAs) are widely used in various fields due to the efficiency and robustness of EAs. In this review, we give an introduction about the applications of hybrid intelligent methods, in particular those based on evolutionary algorithm, in bioinformatics. In particular, we focus on their applications to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and reconstruction of biological networks.

A Hybrid Method for Opinion Finding Task (KUNLP at TREC 2008 Blog Track)

DTIC Science & Technology

2008-11-01

retrieve relevant documents. For the Opinion Retrieval subtask, we propose a hybrid model of lexicon-based approach and machine learning approach for...estimating and ranking the opinionated documents. For the Polarized Opinion Retrieval subtask, we employ machine learning for predicting the polarity...and linear combination technique for ranking polar documents. The hybrid model which utilize both lexicon-based approach and machine learning approach

An Improved Fast Self-Calibration Method for Hybrid Inertial Navigation System under Stationary Condition

PubMed Central

Liu, Bingqi; Wei, Shihui; Su, Guohua; Wang, Jiping; Lu, Jiazhen

2018-01-01

The navigation accuracy of the inertial navigation system (INS) can be greatly improved when the inertial measurement unit (IMU) is effectively calibrated and compensated, such as gyro drifts and accelerometer biases. To reduce the requirement for turntable precision in the classical calibration method, a continuous dynamic self-calibration method based on a three-axis rotating frame for the hybrid inertial navigation system is presented. First, by selecting a suitable IMU frame, the error models of accelerometers and gyros are established. Then, by taking the navigation errors during rolling as the observations, the overall twenty-one error parameters of hybrid inertial navigation system (HINS) are identified based on the calculation of the intermediate parameter. The actual experiment verifies that the method can identify all error parameters of HINS and this method has equivalent accuracy to the classical calibration on a high-precision turntable. In addition, this method is rapid, simple and feasible. PMID:29695041

An Improved Fast Self-Calibration Method for Hybrid Inertial Navigation System under Stationary Condition.

PubMed

Liu, Bingqi; Wei, Shihui; Su, Guohua; Wang, Jiping; Lu, Jiazhen

2018-04-24

The navigation accuracy of the inertial navigation system (INS) can be greatly improved when the inertial measurement unit (IMU) is effectively calibrated and compensated, such as gyro drifts and accelerometer biases. To reduce the requirement for turntable precision in the classical calibration method, a continuous dynamic self-calibration method based on a three-axis rotating frame for the hybrid inertial navigation system is presented. First, by selecting a suitable IMU frame, the error models of accelerometers and gyros are established. Then, by taking the navigation errors during rolling as the observations, the overall twenty-one error parameters of hybrid inertial navigation system (HINS) are identified based on the calculation of the intermediate parameter. The actual experiment verifies that the method can identify all error parameters of HINS and this method has equivalent accuracy to the classical calibration on a high-precision turntable. In addition, this method is rapid, simple and feasible.

An efficient method for hybrid density functional calculation with spin-orbit coupling

NASA Astrophysics Data System (ADS)

Wang, Maoyuan; Liu, Gui-Bin; Guo, Hong; Yao, Yugui

2018-03-01

In first-principles calculations, hybrid functional is often used to improve accuracy from local exchange correlation functionals. A drawback is that evaluating the hybrid functional needs significantly more computing effort. When spin-orbit coupling (SOC) is taken into account, the non-collinear spin structure increases computing effort by at least eight times. As a result, hybrid functional calculations with SOC are intractable in most cases. In this paper, we present an approximate solution to this problem by developing an efficient method based on a mixed linear combination of atomic orbital (LCAO) scheme. We demonstrate the power of this method using several examples and we show that the results compare very well with those of direct hybrid functional calculations with SOC, yet the method only requires a computing effort similar to that without SOC. The presented technique provides a good balance between computing efficiency and accuracy, and it can be extended to magnetic materials.

Effective coupled optoelectrical design method for fully infiltrated semiconductor nanowires based hybrid solar cells.

PubMed

Wu, Dan; Tang, Xiaohong; Wang, Kai; Li, Xianqiang

2016-10-31

We present a novel coupled design method that both optimizes light absorption and predicts electrical performance of fully infiltrated inorganic semiconductor nanowires (NWs) based hybrid solar cells (HSC). This method provides a thorough insight of hybrid photovoltaic process as a function of geometrical parameters of NWs. An active layer consisting of GaAs NWs as acceptor and poly(3-hexylthiophene-2,5-diyl) (P3HT) as donor were used as a design example. Absorption spectra features were studied by the evolution of the leaky modes and Fabry-Perot resonance with wavelength focusing firstly on the GaAs/air layer before extending to GaAs/P3HT hybrid active layer. The highest absorption efficiency reached 39% for the hybrid active layer of 2 μm thickness under AM 1.5G illumination. Combined with the optical absorption analysis, our method further codesigns the energy harvesting to predict electrical performance of HSC considering exciton dissociation efficiencies within both inorganic NWs and a polymeric shell of 20 nm thickness. The validity of the simulation model was also proved by the well agreement of the simulation results with the published experimental work indicating an effective guidance for future high performance HSC design.

Identification of a novel interspecific hybrid yeast from a metagenomic spontaneously inoculated beer sample using Hi-C.

PubMed

Smukowski Heil, Caiti; Burton, Joshua N; Liachko, Ivan; Friedrich, Anne; Hanson, Noah A; Morris, Cody L; Schacherer, Joseph; Shendure, Jay; Thomas, James H; Dunham, Maitreya J

2018-01-01

Interspecific hybridization is a common mechanism enabling genetic diversification and adaptation; however, the detection of hybrid species has been quite difficult. The identification of microbial hybrids is made even more complicated, as most environmental microbes are resistant to culturing and must be studied in their native mixed communities. We have previously adapted the chromosome conformation capture method Hi-C to the assembly of genomes from mixed populations. Here, we show the method's application in assembling genomes directly from an uncultured, mixed population from a spontaneously inoculated beer sample. Our assembly method has enabled us to de-convolute four bacterial and four yeast genomes from this sample, including a putative yeast hybrid. Downstream isolation and analysis of this hybrid confirmed its genome to consist of Pichia membranifaciens and that of another related, but undescribed, yeast. Our work shows that Hi-C-based metagenomic methods can overcome the limitation of traditional sequencing methods in studying complex mixtures of genomes. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Preparation and properties of recycled HDPE/clay hybrids

Treesearch

Yong Lei; Qinglin Wu; Craig M. Clemons

2007-01-01

Hybrids based on recycled high density polyethylene (RHDPE) and organic clay were made by melt compounding. The influence of blending method, compatibilizers, and clay content on clay intercalation and exfoliation, RHDPE crystallization behavior, and the mechanical properties of RHDPE/clay hybrids were investigated. Both maleated polyethylene (MAPE) and titanate could...

Examining the Implementation of a Problem-Based Learning and Traditional Hybrid Model of Instruction in Remedial Mathematics Classes Designed for State Testing Preparation of Eleventh Grade Students

ERIC Educational Resources Information Center

Rodgers, Lindsay D.

2011-01-01

The following paper examined the effects of a new method of teaching for remedial mathematics, named the hybrid model of instruction. Due to increasing importance of high stakes testing, the study sought to determine if this method of instruction, that blends traditional teaching and problem-based learning, had different learning effects on…

Nucleic acid in-situ hybridization detection of infectious agents

NASA Astrophysics Data System (ADS)

Thompson, Curtis T.

2000-04-01

Limitations of traditional culture methods and newer polymerase chain reaction (PCR)-based methods for detection and speciation of infectious agents demonstrate the need for more rapid and better diagnostics. Nucleic acid hybridization is a detection technology that has gained wide acceptance in cancer and prenatal cytogenetics. Using a modification of the nucleic acid hybridization technique known as fluorescence in-situ hybridization, infectious agents can be detected in a variety of specimens with high sensitivity and specificity. The specimens derive from all types of human and animal sources including body fluids, tissue aspirates and biopsy material. Nucleic acid hybridization can be performed in less than one hour. The result can be interpreted either using traditional fluorescence microscopy or automated platforms such as micro arrays. This paper demonstrates proof of concept for nucleic acid hybridization detection of different infectious agents. Interpretation within a cytologic and histologic context is possible with fluorescence microscopic analysis, thereby providing confirmatory evidence of hybridization. With careful probe selection, nucleic acid hybridization promises to be a highly sensitive and specific practical diagnostic alternative to culture, traditional staining methods, immunohistochemistry and complicated nucleic acid amplification tests.

Hybrid 3D-2D printing of bone scaffolds Hybrid 3D-2D printing methods for bone scaffolds fabrication.

PubMed

Prinz, V Ya; Seleznev, Vladimir

2016-12-13

It is a well-known fact that bone scaffold topography on micro- and nanometer scale influences the cellular behavior. Nano-scale surface modification of scaffolds allows the modulation of biological activity for enhanced cell differentiation. To date, there has been only a limited success in printing scaffolds with micro- and nano-scale features exposed on the surface. To improve on the currently available imperfect technologies, in our paper we introduce new hybrid technologies based on a combination of 2D (nano imprint) and 3D printing methods. The first method is based on using light projection 3D printing and simultaneous 2D nanostructuring of each of the layers during the formation of the 3D structure. The second method is based on the sequential integration of preliminarily created 2D nanostructured films into a 3D printed structure. The capabilities of the developed hybrid technologies are demonstrated with the example of forming 3D bone scaffolds. The proposed technologies can be used to fabricate complex 3D micro- and nanostructured products for various fields. Copyright 2016 IOP Publishing Ltd.

Superpixel-based segmentation of glottal area from videolaryngoscopy images

NASA Astrophysics Data System (ADS)

Turkmen, H. Irem; Albayrak, Abdulkadir; Karsligil, M. Elif; Kocak, Ismail

2017-11-01

Segmentation of the glottal area with high accuracy is one of the major challenges for the development of systems for computer-aided diagnosis of vocal-fold disorders. We propose a hybrid model combining conventional methods with a superpixel-based segmentation approach. We first employed a superpixel algorithm to reveal the glottal area by eliminating the local variances of pixels caused by bleedings, blood vessels, and light reflections from mucosa. Then, the glottal area was detected by exploiting a seeded region-growing algorithm in a fully automatic manner. The experiments were conducted on videolaryngoscopy images obtained from both patients having pathologic vocal folds as well as healthy subjects. Finally, the proposed hybrid approach was compared with conventional region-growing and active-contour model-based glottal area segmentation algorithms. The performance of the proposed method was evaluated in terms of segmentation accuracy and elapsed time. The F-measure, true negative rate, and dice coefficients of the hybrid method were calculated as 82%, 93%, and 82%, respectively, which are superior to the state-of-art glottal-area segmentation methods. The proposed hybrid model achieved high success rates and robustness, making it suitable for developing a computer-aided diagnosis system that can be used in clinical routines.

Edge gradients evaluation for 2D hybrid finite volume method model

USDA-ARS?s Scientific Manuscript database

In this study, a two-dimensional depth-integrated hydrodynamic model was developed using FVM on a hybrid unstructured collocated mesh system. To alleviate the negative effects of mesh irregularity and non-uniformity, a conservative evaluation method for edge gradients based on the second-order Tayl...

Preparation and optical characteristics of layered perovskite-type lead-bromide-incorporated azobenzene chromophores

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

Sasai, Ryo, E-mail: rsasai@riko.shimane-u.ac.jp; Shinomura, Hisashi

Lead bromide-based layered perovskite powders with azobenzene derivatives were prepared by a homogeneous precipitation method. From the diffuse reflectance (DR) and photoluminescence (PL) spectra of the hybrid powder materials, the present hybrids exhibited sharp absorption and PL peaks originating from excitons produced in the PbBr{sub 4}{sup 2-} layer. When the present hybrid powder was irradiated with UV light at 350 nm, the absorption band from the trans-azobenzene chromophore, observed around 350 nm, decreased, while the absorption band from the cis-azobenzene chromophore, observed around 450 nm, increased. These results indicate that azobenzene chromophores in the present hybrid materials exhibit reversible photoisomerization.more » Moreover, it was found that the PL intensity from the exciton also varied due to photoisomerization of the azobenzene chromophores in the present hybrid. Thus, for the first time we succeeded in preparing the azobenzene derivative lead-bromide-based layered perovskite with photochromism before and after UV light irradiation. - Graphical abstract: For the first time, we succeeded in preparing the azobenzene derivative lead-bromide-based layered perovskite with photochromism before and after UV light irradiation. Highlights: Black-Right-Pointing-Pointer PbBr-based layered perovskite with azobenezene derivatives could be synthesized by a homogeneous precipitation method. Black-Right-Pointing-Pointer Azobenzene derivatives incorporated the present hybrid that exhibited reversible photoisomerization under UV and/or visible light irradiation. Black-Right-Pointing-Pointer PL property of the present hybrid could also be varied by photoisomerization.« less

Novel hybrid linear stochastic with non-linear extreme learning machine methods for forecasting monthly rainfall a tropical climate.

PubMed

Zeynoddin, Mohammad; Bonakdari, Hossein; Azari, Arash; Ebtehaj, Isa; Gharabaghi, Bahram; Riahi Madavar, Hossein

2018-09-15

A novel hybrid approach is presented that can more accurately predict monthly rainfall in a tropical climate by integrating a linear stochastic model with a powerful non-linear extreme learning machine method. This new hybrid method was then evaluated by considering four general scenarios. In the first scenario, the modeling process is initiated without preprocessing input data as a base case. While in other three scenarios, the one-step and two-step procedures are utilized to make the model predictions more precise. The mentioned scenarios are based on a combination of stationarization techniques (i.e., differencing, seasonal and non-seasonal standardization and spectral analysis), and normality transforms (i.e., Box-Cox, John and Draper, Yeo and Johnson, Johnson, Box-Cox-Mod, log, log standard, and Manly). In scenario 2, which is a one-step scenario, the stationarization methods are employed as preprocessing approaches. In scenario 3 and 4, different combinations of normality transform, and stationarization methods are considered as preprocessing techniques. In total, 61 sub-scenarios are evaluated resulting 11013 models (10785 linear methods, 4 nonlinear models, and 224 hybrid models are evaluated). The uncertainty of the linear, nonlinear and hybrid models are examined by Monte Carlo technique. The best preprocessing technique is the utilization of Johnson normality transform and seasonal standardization (respectively) (R 2  = 0.99; RMSE = 0.6; MAE = 0.38; RMSRE = 0.1, MARE = 0.06, UI = 0.03 &UII = 0.05). The results of uncertainty analysis indicated the good performance of proposed technique (d-factor = 0.27; 95PPU = 83.57). Moreover, the results of the proposed methodology in this study were compared with an evolutionary hybrid of adaptive neuro fuzzy inference system (ANFIS) with firefly algorithm (ANFIS-FFA) demonstrating that the new hybrid methods outperformed ANFIS-FFA method. Copyright © 2018 Elsevier Ltd. All rights reserved.

Carbon nanotube based hybrid nanostructures: Synthesis and applications

NASA Astrophysics Data System (ADS)

Ou, Fung Suong

Hybrid nanostructures are fascinating materials for their promising applications in future nanoelectronics, electrical interconnects and energy storage devices. Practical ways of connecting individual carbon nanotubes to metal contacts for their use as interconnects and in electronic devices have been challenging. In this thesis, carbon nanotube based hybrids that combine the best properties of carbon nanotubes and metal nanowires have been fabricated. The electrical properties and Raman spectra of the hybrid nanowires are also studied. This thesis will focus on our recent results in the development of carbon nanotube hybrids for various applications. Various hybrid structures of multiwalled carbon nanotubes and metal nanowires can be fabricated using a combination of electrodeposition and chemical vapor deposition techniques. Controlled fabrication of multi-segmented structures will be studied. Several novel applications of these structures, for example, as electrodes in ultra-high power supercapacitors, multi-functional smart materials are also studied. The thesis will also highlight the development of carbon nanotube hybrids based smart materials. Hybrid nanowires with hydrophobic carbon nanotube tails and hydrophilic metal nanowire heads, allows for the assembly of spheres in solution. The design and manipulation of these carbon nanotube hybrids based smart structures for various novel applications will be discussed. Such new class of carbon nanotube hybrids surfactants are likely to lead as new tools in various fields such as microfluidics or water purification. In addition, we will also look at other variations of hybrid nanostructures fabricated from our method.

Hybrid Filtering in Semantic Query Processing

ERIC Educational Resources Information Center

Jeong, Hanjo

2011-01-01

This dissertation presents a hybrid filtering method and a case-based reasoning framework for enhancing the effectiveness of Web search. Web search may not reflect user needs, intent, context, and preferences, because today's keyword-based search is lacking semantic information to capture the user's context and intent in posing the search query.…

Information filtering via a scaling-based function.

PubMed

Qiu, Tian; Zhang, Zi-Ke; Chen, Guang

2013-01-01

Finding a universal description of the algorithm optimization is one of the key challenges in personalized recommendation. In this article, for the first time, we introduce a scaling-based algorithm (SCL) independent of recommendation list length based on a hybrid algorithm of heat conduction and mass diffusion, by finding out the scaling function for the tunable parameter and object average degree. The optimal value of the tunable parameter can be abstracted from the scaling function, which is heterogeneous for the individual object. Experimental results obtained from three real datasets, Netflix, MovieLens and RYM, show that the SCL is highly accurate in recommendation. More importantly, compared with a number of excellent algorithms, including the mass diffusion method, the original hybrid method, and even an improved version of the hybrid method, the SCL algorithm remarkably promotes the personalized recommendation in three other aspects: solving the accuracy-diversity dilemma, presenting a high novelty, and solving the key challenge of cold start problem.

Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

PubMed Central

Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.

2015-01-01

Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

Graph Structure-Based Simultaneous Localization and Mapping Using a Hybrid Method of 2D Laser Scan and Monocular Camera Image in Environments with Laser Scan Ambiguity

PubMed Central

Oh, Taekjun; Lee, Donghwa; Kim, Hyungjin; Myung, Hyun

2015-01-01

Localization is an essential issue for robot navigation, allowing the robot to perform tasks autonomously. However, in environments with laser scan ambiguity, such as long corridors, the conventional SLAM (simultaneous localization and mapping) algorithms exploiting a laser scanner may not estimate the robot pose robustly. To resolve this problem, we propose a novel localization approach based on a hybrid method incorporating a 2D laser scanner and a monocular camera in the framework of a graph structure-based SLAM. 3D coordinates of image feature points are acquired through the hybrid method, with the assumption that the wall is normal to the ground and vertically flat. However, this assumption can be relieved, because the subsequent feature matching process rejects the outliers on an inclined or non-flat wall. Through graph optimization with constraints generated by the hybrid method, the final robot pose is estimated. To verify the effectiveness of the proposed method, real experiments were conducted in an indoor environment with a long corridor. The experimental results were compared with those of the conventional GMappingapproach. The results demonstrate that it is possible to localize the robot in environments with laser scan ambiguity in real time, and the performance of the proposed method is superior to that of the conventional approach. PMID:26151203

A general strategy for hybrid thin film fabrication and transfer onto arbitrary substrates.

PubMed

Zhang, Yong; Magan, John J; Blau, Werner J

2014-04-28

The development of thin film-based structures/devices often requires thin films to be transferred onto arbitrary substrates/surfaces. Controllable and non-destructive transfer method, although highly desired, remains quite challenging. Here we report a general method for fabrication and transfer of hybrid (ultra)thin films. The proposed solution-based in-situ transfer method shows not only its robust ability for thin film transfer onto arbitrary substrates but also its highly controlled and non-destructive characteristic. With a hole structure as the support, fully-stretched free-standing thin film is prepared. The successful transfer to a curved surface demonstrates the possibility for production of thin film-coated complex optical components. Ultrathin (35 nm) hybrid film transferred onto PET (50 μm thick) shows high transparency (>90% in visible range), conductivity (1.54 × 10(4) S/m), and flexibility (radius of curvature down to mm scale). The reported transfer method would provide a powerful route towards complex thin film-based structures/devices.

A General Strategy for Hybrid Thin Film Fabrication and Transfer onto Arbitrary Substrates

PubMed Central

Zhang, Yong; Magan, John J.; Blau, Werner J.

2014-01-01

The development of thin film-based structures/devices often requires thin films to be transferred onto arbitrary substrates/surfaces. Controllable and non-destructive transfer method, although highly desired, remains quite challenging. Here we report a general method for fabrication and transfer of hybrid (ultra)thin films. The proposed solution-based in-situ transfer method shows not only its robust ability for thin film transfer onto arbitrary substrates but also its highly controlled and non-destructive characteristic. With a hole structure as the support, fully-stretched free-standing thin film is prepared. The successful transfer to a curved surface demonstrates the possibility for production of thin film-coated complex optical components. Ultrathin (35 nm) hybrid film transferred onto PET (50 μm thick) shows high transparency (>90% in visible range), conductivity (1.54 × 104 S/m), and flexibility (radius of curvature down to mm scale). The reported transfer method would provide a powerful route towards complex thin film-based structures/devices. PMID:24769689

A Hybrid Method to Estimate Specific Differential Phase and Rainfall With Linear Programming and Physics Constraints

DOE PAGES

Huang, Hao; Zhang, Guifu; Zhao, Kun; ...

2016-10-20

A hybrid method of combining linear programming (LP) and physical constraints is developed to estimate specific differential phase (K DP) and to improve rain estimation. Moreover, the hybrid K DP estimator and the existing estimators of LP, least squares fitting, and a self-consistent relation of polarimetric radar variables are evaluated and compared using simulated data. Our simulation results indicate the new estimator's superiority, particularly in regions where backscattering phase (δ hv) dominates. Further, a quantitative comparison between auto-weather-station rain-gauge observations and K DP-based radar rain estimates for a Meiyu event also demonstrate the superiority of the hybrid K DP estimatormore » over existing methods.« less

Carbon and metal nanotube hybrid structures on graphene as efficient electron field emitters

NASA Astrophysics Data System (ADS)

Heo, Kwang; Lee, Byung Yang; Lee, Hyungwoo; Cho, Dong-guk; Arif, Muhammad; Kim, Kyu Young; Choi, Young Jin; Hong, Seunghun

2016-07-01

We report a facile and efficient method for the fabrication of highly-flexible field emission devices by forming tubular hybrid structures based on carbon nanotubes (CNTs) and nickel nanotubes (Ni NTs) on graphene-based flexible substrates. By employing an infiltration process in anodic alumina oxide (AAO) templates followed by Ni electrodeposition, we could fabricate CNT-wrapped Ni NT/graphene hybrid structures. During the electrodeposition process, the CNTs served as Ni nucleation sites, resulting in a large-area array of high aspect-ratio field emitters composed of CNT-wrapped Ni NT hybrid structures. As a proof of concepts, we demonstrate that high-quality flexible field emission devices can be simply fabricated using our method. Remarkably, our proto-type field emission devices exhibited a current density higher by two orders of magnitude compared to other devices fabricated by previous methods, while maintaining its structural integrity in various bending deformations. This novel fabrication strategy can be utilized in various applications such as optoelectronic devices, sensors and energy storage devices.

Carbon and metal nanotube hybrid structures on graphene as efficient electron field emitters.

PubMed

Heo, Kwang; Lee, Byung Yang; Lee, Hyungwoo; Cho, Dong-Guk; Arif, Muhammad; Kim, Kyu Young; Choi, Young Jin; Hong, Seunghun

2016-07-08

We report a facile and efficient method for the fabrication of highly-flexible field emission devices by forming tubular hybrid structures based on carbon nanotubes (CNTs) and nickel nanotubes (Ni NTs) on graphene-based flexible substrates. By employing an infiltration process in anodic alumina oxide (AAO) templates followed by Ni electrodeposition, we could fabricate CNT-wrapped Ni NT/graphene hybrid structures. During the electrodeposition process, the CNTs served as Ni nucleation sites, resulting in a large-area array of high aspect-ratio field emitters composed of CNT-wrapped Ni NT hybrid structures. As a proof of concepts, we demonstrate that high-quality flexible field emission devices can be simply fabricated using our method. Remarkably, our proto-type field emission devices exhibited a current density higher by two orders of magnitude compared to other devices fabricated by previous methods, while maintaining its structural integrity in various bending deformations. This novel fabrication strategy can be utilized in various applications such as optoelectronic devices, sensors and energy storage devices.

A hybrid PSO-SVM-based method for predicting the friction coefficient between aircraft tire and coating

NASA Astrophysics Data System (ADS)

Zhan, Liwei; Li, Chengwei

2017-02-01

A hybrid PSO-SVM-based model is proposed to predict the friction coefficient between aircraft tire and coating. The presented hybrid model combines a support vector machine (SVM) with particle swarm optimization (PSO) technique. SVM has been adopted to solve regression problems successfully. Its regression accuracy is greatly related to optimizing parameters such as the regularization constant C , the parameter gamma γ corresponding to RBF kernel and the epsilon parameter \\varepsilon in the SVM training procedure. However, the friction coefficient which is predicted based on SVM has yet to be explored between aircraft tire and coating. The experiment reveals that drop height and tire rotational speed are the factors affecting friction coefficient. Bearing in mind, the friction coefficient can been predicted using the hybrid PSO-SVM-based model by the measured friction coefficient between aircraft tire and coating. To compare regression accuracy, a grid search (GS) method and a genetic algorithm (GA) are used to optimize the relevant parameters (C , γ and \\varepsilon ), respectively. The regression accuracy could be reflected by the coefficient of determination ({{R}2} ). The result shows that the hybrid PSO-RBF-SVM-based model has better accuracy compared with the GS-RBF-SVM- and GA-RBF-SVM-based models. The agreement of this model (PSO-RBF-SVM) with experiment data confirms its good performance.

A hybrid method for flood simulation in small catchments combining hydrodynamic and hydrological techniques

NASA Astrophysics Data System (ADS)

Bellos, Vasilis; Tsakiris, George

2016-09-01

The study presents a new hybrid method for the simulation of flood events in small catchments. It combines a physically-based two-dimensional hydrodynamic model and the hydrological unit hydrograph theory. Unit hydrographs are derived using the FLOW-R2D model which is based on the full form of two-dimensional Shallow Water Equations, solved by a modified McCormack numerical scheme. The method is tested at a small catchment in a suburb of Athens-Greece for a storm event which occurred in February 2013. The catchment is divided into three friction zones and unit hydrographs of 15 and 30 min are produced. The infiltration process is simulated by the empirical Kostiakov equation and the Green-Ampt model. The results from the implementation of the proposed hybrid method are compared with recorded data at the hydrometric station at the outlet of the catchment and the results derived from the fully hydrodynamic model FLOW-R2D. It is concluded that for the case studied, the proposed hybrid method produces results close to those of the fully hydrodynamic simulation at substantially shorter computational time. This finding, if further verified in a variety of case studies, can be useful in devising effective hybrid tools for the two-dimensional flood simulations, which are lead to accurate and considerably faster results than those achieved by the fully hydrodynamic simulations.

A hybrid method for solutes in complex solvents: Density functional theory combined with empirical force fields

NASA Astrophysics Data System (ADS)

Eichinger, M.; Tavan, P.; Hutter, J.; Parrinello, M.

1999-06-01

We present a hybrid method for molecular dynamics simulations of solutes in complex solvents as represented, for example, by substrates within enzymes. The method combines a quantum mechanical (QM) description of the solute with a molecular mechanics (MM) approach for the solvent. The QM fragment of a simulation system is treated by ab initio density functional theory (DFT) based on plane-wave expansions. Long-range Coulomb interactions within the MM fragment and between the QM and the MM fragment are treated by a computationally efficient fast multipole method. For the description of covalent bonds between the two fragments, we introduce the scaled position link atom method (SPLAM), which removes the shortcomings of related procedures. The various aspects of the hybrid method are scrutinized through test calculations on liquid water, the water dimer, ethane and a small molecule related to the retinal Schiff base. In particular, the extent to which vibrational spectra obtained by DFT for the solute can be spoiled by the lower quality force field of the solvent is checked, including cases in which the two fragments are covalently joined. The results demonstrate that our QM/MM hybrid method is especially well suited for the vibrational analysis of molecules in condensed phase.

Hybrid DFP-CG method for solving unconstrained optimization problems

NASA Astrophysics Data System (ADS)

Osman, Wan Farah Hanan Wan; Asrul Hery Ibrahim, Mohd; Mamat, Mustafa

2017-09-01

The conjugate gradient (CG) method and quasi-Newton method are both well known method for solving unconstrained optimization method. In this paper, we proposed a new method by combining the search direction between conjugate gradient method and quasi-Newton method based on BFGS-CG method developed by Ibrahim et al. The Davidon-Fletcher-Powell (DFP) update formula is used as an approximation of Hessian for this new hybrid algorithm. Numerical result showed that the new algorithm perform well than the ordinary DFP method and proven to posses both sufficient descent and global convergence properties.

A hybrid method with deviational particles for spatial inhomogeneous plasma

NASA Astrophysics Data System (ADS)

Yan, Bokai

2016-03-01

In this work we propose a Hybrid method with Deviational Particles (HDP) for a plasma modeled by the inhomogeneous Vlasov-Poisson-Landau system. We split the distribution into a Maxwellian part evolved by a grid based fluid solver and a deviation part simulated by numerical particles. These particles, named deviational particles, could be both positive and negative. We combine the Monte Carlo method proposed in [31], a Particle in Cell method and a Macro-Micro decomposition method [3] to design an efficient hybrid method. Furthermore, coarse particles are employed to accelerate the simulation. A particle resampling technique on both deviational particles and coarse particles is also investigated and improved. This method is applicable in all regimes and significantly more efficient compared to a PIC-DSMC method near the fluid regime.

A Novel Hybrid Error Criterion-Based Active Control Method for on-Line Milling Vibration Suppression with Piezoelectric Actuators and Sensors

PubMed Central

Zhang, Xingwu; Wang, Chenxi; Gao, Robert X.; Yan, Ruqiang; Chen, Xuefeng; Wang, Shibin

2016-01-01

Milling vibration is one of the most serious factors affecting machining quality and precision. In this paper a novel hybrid error criterion-based frequency-domain LMS active control method is constructed and used for vibration suppression of milling processes by piezoelectric actuators and sensors, in which only one Fast Fourier Transform (FFT) is used and no Inverse Fast Fourier Transform (IFFT) is involved. The correction formulas are derived by a steepest descent procedure and the control parameters are analyzed and optimized. Then, a novel hybrid error criterion is constructed to improve the adaptability, reliability and anti-interference ability of the constructed control algorithm. Finally, based on piezoelectric actuators and acceleration sensors, a simulation of a spindle and a milling process experiment are presented to verify the proposed method. Besides, a protection program is added in the control flow to enhance the reliability of the control method in applications. The simulation and experiment results indicate that the proposed method is an effective and reliable way for on-line vibration suppression, and the machining quality can be obviously improved. PMID:26751448

Instructional Strategies for Face-to-Face, Internet-Based, and Hybrid Education: An Action Oriented Case Study

ERIC Educational Resources Information Center

Naffziger, Loren Benjamin

2012-01-01

With the advent of the Internet and the rapid growth of educational software, high schools are applying new instructional strategies with their students, including online and hybrid education. Hybrid education combines face-to-face encounters with online methods; students attend classroom sessions with their teachers and peers, and they engage…

A hybrid method for accurate star tracking using star sensor and gyros.

PubMed

Lu, Jiazhen; Yang, Lie; Zhang, Hao

2017-10-01

Star tracking is the primary operating mode of star sensors. To improve tracking accuracy and efficiency, a hybrid method using a star sensor and gyroscopes is proposed in this study. In this method, the dynamic conditions of an aircraft are determined first by the estimated angular acceleration. Under low dynamic conditions, the star sensor is used to measure the star vector and the vector difference method is adopted to estimate the current angular velocity. Under high dynamic conditions, the angular velocity is obtained by the calibrated gyros. The star position is predicted based on the estimated angular velocity and calibrated gyros using the star vector measurements. The results of the semi-physical experiment show that this hybrid method is accurate and feasible. In contrast with the star vector difference and gyro-assisted methods, the star position prediction result of the hybrid method is verified to be more accurate in two different cases under the given random noise of the star centroid.

Swarm intelligence-based approach for optimal design of CMOS differential amplifier and comparator circuit using a hybrid salp swarm algorithm

NASA Astrophysics Data System (ADS)

Asaithambi, Sasikumar; Rajappa, Muthaiah

2018-05-01

In this paper, an automatic design method based on a swarm intelligence approach for CMOS analog integrated circuit (IC) design is presented. The hybrid meta-heuristics optimization technique, namely, the salp swarm algorithm (SSA), is applied to the optimal sizing of a CMOS differential amplifier and the comparator circuit. SSA is a nature-inspired optimization algorithm which mimics the navigating and hunting behavior of salp. The hybrid SSA is applied to optimize the circuit design parameters and to minimize the MOS transistor sizes. The proposed swarm intelligence approach was successfully implemented for an automatic design and optimization of CMOS analog ICs using Generic Process Design Kit (GPDK) 180 nm technology. The circuit design parameters and design specifications are validated through a simulation program for integrated circuit emphasis simulator. To investigate the efficiency of the proposed approach, comparisons have been carried out with other simulation-based circuit design methods. The performances of hybrid SSA based CMOS analog IC designs are better than the previously reported studies.

Swarm intelligence-based approach for optimal design of CMOS differential amplifier and comparator circuit using a hybrid salp swarm algorithm.

PubMed

Asaithambi, Sasikumar; Rajappa, Muthaiah

2018-05-01

In this paper, an automatic design method based on a swarm intelligence approach for CMOS analog integrated circuit (IC) design is presented. The hybrid meta-heuristics optimization technique, namely, the salp swarm algorithm (SSA), is applied to the optimal sizing of a CMOS differential amplifier and the comparator circuit. SSA is a nature-inspired optimization algorithm which mimics the navigating and hunting behavior of salp. The hybrid SSA is applied to optimize the circuit design parameters and to minimize the MOS transistor sizes. The proposed swarm intelligence approach was successfully implemented for an automatic design and optimization of CMOS analog ICs using Generic Process Design Kit (GPDK) 180 nm technology. The circuit design parameters and design specifications are validated through a simulation program for integrated circuit emphasis simulator. To investigate the efficiency of the proposed approach, comparisons have been carried out with other simulation-based circuit design methods. The performances of hybrid SSA based CMOS analog IC designs are better than the previously reported studies.

A Circuit-Based Neural Network with Hybrid Learning of Backpropagation and Random Weight Change Algorithms

PubMed Central

Yang, Changju; Kim, Hyongsuk; Adhikari, Shyam Prasad; Chua, Leon O.

2016-01-01

A hybrid learning method of a software-based backpropagation learning and a hardware-based RWC learning is proposed for the development of circuit-based neural networks. The backpropagation is known as one of the most efficient learning algorithms. A weak point is that its hardware implementation is extremely difficult. The RWC algorithm, which is very easy to implement with respect to its hardware circuits, takes too many iterations for learning. The proposed learning algorithm is a hybrid one of these two. The main learning is performed with a software version of the BP algorithm, firstly, and then, learned weights are transplanted on a hardware version of a neural circuit. At the time of the weight transplantation, a significant amount of output error would occur due to the characteristic difference between the software and the hardware. In the proposed method, such error is reduced via a complementary learning of the RWC algorithm, which is implemented in a simple hardware. The usefulness of the proposed hybrid learning system is verified via simulations upon several classical learning problems. PMID:28025566

An agent-based method for simulating porous fluid-saturated structures with indistinguishable components

NASA Astrophysics Data System (ADS)

Kashani, Jamal; Pettet, Graeme John; Gu, YuanTong; Zhang, Lihai; Oloyede, Adekunle

2017-10-01

Single-phase porous materials contain multiple components that intermingle up to the ultramicroscopic level. Although the structures of the porous materials have been simulated with agent-based methods, the results of the available methods continue to provide patterns of distinguishable solid and fluid agents which do not represent materials with indistinguishable phases. This paper introduces a new agent (hybrid agent) and category of rules (intra-agent rule) that can be used to create emergent structures that would more accurately represent single-phase structures and materials. The novel hybrid agent carries the characteristics of system's elements and it is capable of changing within itself, while also responding to its neighbours as they also change. As an example, the hybrid agent under one-dimensional cellular automata formalism in a two-dimensional domain is used to generate patterns that demonstrate the striking morphological and characteristic similarities with the porous saturated single-phase structures where each agent of the ;structure; carries semi-permeability property and consists of both fluid and solid in space and at all times. We conclude that the ability of the hybrid agent to change locally provides an enhanced protocol to simulate complex porous structures such as biological tissues which could facilitate models for agent-based techniques and numerical methods.

Hybrid approach to structure modeling of the histamine H3 receptor: Multi-level assessment as a tool for model verification.

PubMed

Jończyk, Jakub; Malawska, Barbara; Bajda, Marek

2017-01-01

The crucial role of G-protein coupled receptors and the significant achievements associated with a better understanding of the spatial structure of known receptors in this family encouraged us to undertake a study on the histamine H3 receptor, whose crystal structure is still unresolved. The latest literature data and availability of different software enabled us to build homology models of higher accuracy than previously published ones. The new models are expected to be closer to crystal structures; and therefore, they are much more helpful in the design of potential ligands. In this article, we describe the generation of homology models with the use of diverse tools and a hybrid assessment. Our study incorporates a hybrid assessment connecting knowledge-based scoring algorithms with a two-step ligand-based docking procedure. Knowledge-based scoring employs probability theory for global energy minimum determination based on information about native amino acid conformation from a dataset of experimentally determined protein structures. For a two-step docking procedure two programs were applied: GOLD was used in the first step and Glide in the second. Hybrid approaches offer advantages by combining various theoretical methods in one modeling algorithm. The biggest advantage of hybrid methods is their intrinsic ability to self-update and self-refine when additional structural data are acquired. Moreover, the diversity of computational methods and structural data used in hybrid approaches for structure prediction limit inaccuracies resulting from theoretical approximations or fuzziness of experimental data. The results of docking to the new H3 receptor model allowed us to analyze ligand-receptor interactions for reference compounds.

SU-E-T-226: Correction of a Standard Model-Based Dose Calculator Using Measurement Data

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

Chen, M; Jiang, S; Lu, W

Purpose: To propose a hybrid method that combines advantages of the model-based and measurement-based method for independent dose calculation. Modeled-based dose calculation, such as collapsed-cone-convolution/superposition (CCCS) or the Monte-Carlo method, models dose deposition in the patient body accurately; however, due to lack of detail knowledge about the linear accelerator (LINAC) head, commissioning for an arbitrary machine is tedious and challenging in case of hardware changes. On the contrary, the measurement-based method characterizes the beam property accurately but lacks the capability of dose disposition modeling in heterogeneous media. Methods: We used a standard CCCS calculator, which is commissioned by published data,more » as the standard model calculator. For a given machine, water phantom measurements were acquired. A set of dose distributions were also calculated using the CCCS for the same setup. The difference between the measurements and the CCCS results were tabulated and used as the commissioning data for a measurement based calculator. Here we used a direct-ray-tracing calculator (ΔDRT). The proposed independent dose calculation consists of the following steps: 1. calculate D-model using CCCS. 2. calculate D-ΔDRT using ΔDRT. 3. combine Results: D=D-model+D-ΔDRT. Results: The hybrid dose calculation was tested on digital phantoms and patient CT data for standard fields and IMRT plan. The results were compared to dose calculated by the treatment planning system (TPS). The agreement of the hybrid and the TPS was within 3%, 3 mm for over 98% of the volume for phantom studies and lung patients. Conclusion: The proposed hybrid method uses the same commissioning data as those for the measurement-based method and can be easily extended to any non-standard LINAC. The results met the accuracy, independence, and simple commissioning criteria for an independent dose calculator.« less

Substituent-Modulated Assembly Formation: An Approach to Enhancing the Photostability of Photoelectric-Sensitive Chalcogenide-Based Ion-Pair Hybrids.

PubMed

Lin, Jian; Fu, Zhixing; Zhang, Jiaxu; Zhu, Yujia; Hu, Dandan; Li, Dongsheng; Wu, Tao

2017-03-20

A series of electronically active viologen dications (RV) with tunable substituent groups were utilized to hybridize with [Ge 4 S 10 ] 4- (T2 cluster) to form the hybrids of T2@RV. These hybrids exhibited variable supermolecular assembly formation, tunable optical absorption properties, and different photoelectric response under the influence of different RV dications. Raman testing and time-dependent photocurrent response indicated that the photosensitivity and photostability of T2@RV could be integrated while choosing suitable RV dications. Current research provides a general method to build a tunable hybrid system based on crystalline metal chalcogenide compounds through the replacement of photoinactive cationic organic templates with photoactive ones with different substituent groups.

Texton-based super-resolution for achieving high spatiotemporal resolution in hybrid camera system

NASA Astrophysics Data System (ADS)

Kamimura, Kenji; Tsumura, Norimichi; Nakaguchi, Toshiya; Miyake, Yoichi

2010-05-01

Many super-resolution methods have been proposed to enhance the spatial resolution of images by using iteration and multiple input images. In a previous paper, we proposed the example-based super-resolution method to enhance an image through pixel-based texton substitution to reduce the computational cost. In this method, however, we only considered the enhancement of a texture image. In this study, we modified this texton substitution method for a hybrid camera to reduce the required bandwidth of a high-resolution video camera. We applied our algorithm to pairs of high- and low-spatiotemporal-resolution videos, which were synthesized to simulate a hybrid camera. The result showed that the fine detail of the low-resolution video can be reproduced compared with bicubic interpolation and the required bandwidth could be reduced to about 1/5 in a video camera. It was also shown that the peak signal-to-noise ratios (PSNRs) of the images improved by about 6 dB in a trained frame and by 1.0-1.5 dB in a test frame, as determined by comparison with the processed image using bicubic interpolation, and the average PSNRs were higher than those obtained by the well-known Freeman’s patch-based super-resolution method. Compared with that of the Freeman’s patch-based super-resolution method, the computational time of our method was reduced to almost 1/10.

A rapid and efficient branched DNA hybridization assay to titer lentiviral vectors.

PubMed

Nair, Ayyappan; Xie, Jinger; Joshi, Sarasijam; Harden, Paul; Davies, Joan; Hermiston, Terry

2008-11-01

A robust assay to titer lentiviral vectors is imperative to qualifying their use in drug discovery, target validation and clinical applications. In this study, a novel branched DNA based hybridization assay was developed to titer lentiviral vectors by quantifying viral RNA genome copy numbers from viral lysates without having to purify viral RNA, and this approach was compared with other non-functional (p24 protein ELISA and viral RT-qPCR) and a functional method (reporter gene expression) used commonly. The RT-qPCR method requires purification of viral RNA and the accuracy of titration therefore depends on the efficiency of purification; this requirement is ameliorated in the hybridization assay as RNA is measured directly in viral lysates. The present study indicates that the hybridization based titration assay performed on viral lysates was more accurate and has additional advantages of being rapid, robust and not dependent on transduction efficiency in different cell types.

Hybrid breeding in wheat: technologies to improve hybrid wheat seed production.

PubMed

Whitford, Ryan; Fleury, Delphine; Reif, Jochen C; Garcia, Melissa; Okada, Takashi; Korzun, Viktor; Langridge, Peter

2013-12-01

Global food security demands the development and delivery of new technologies to increase and secure cereal production on finite arable land without increasing water and fertilizer use. There are several options for boosting wheat yields, but most offer only small yield increases. Wheat is an inbred plant, and hybrids hold the potential to deliver a major lift in yield and will open a wide range of new breeding opportunities. A series of technological advances are needed as a base for hybrid wheat programmes. These start with major changes in floral development and architecture to separate the sexes and force outcrossing. Male sterility provides the best method to block self-fertilization, and modifying the flower structure will enhance pollen access. The recent explosion in genomic resources and technologies provides new opportunities to overcome these limitations. This review outlines the problems with existing hybrid wheat breeding systems and explores molecular-based technologies that could improve the hybrid production system to reduce hybrid seed production costs, a prerequisite for a commercial hybrid wheat system.

Numerical Approach to Spatial Deterministic-Stochastic Models Arising in Cell Biology.

PubMed

Schaff, James C; Gao, Fei; Li, Ye; Novak, Igor L; Slepchenko, Boris M

2016-12-01

Hybrid deterministic-stochastic methods provide an efficient alternative to a fully stochastic treatment of models which include components with disparate levels of stochasticity. However, general-purpose hybrid solvers for spatially resolved simulations of reaction-diffusion systems are not widely available. Here we describe fundamentals of a general-purpose spatial hybrid method. The method generates realizations of a spatially inhomogeneous hybrid system by appropriately integrating capabilities of a deterministic partial differential equation solver with a popular particle-based stochastic simulator, Smoldyn. Rigorous validation of the algorithm is detailed, using a simple model of calcium 'sparks' as a testbed. The solver is then applied to a deterministic-stochastic model of spontaneous emergence of cell polarity. The approach is general enough to be implemented within biologist-friendly software frameworks such as Virtual Cell.

N-S/DSMC hybrid simulation of hypersonic flow over blunt body including wakes

NASA Astrophysics Data System (ADS)

Li, Zhonghua; Li, Zhihui; Li, Haiyan; Yang, Yanguang; Jiang, Xinyu

2014-12-01

A hybrid N-S/DSMC method is presented and applied to solve the three-dimensional hypersonic transitional flows by employing the MPC (modular Particle-Continuum) technique based on the N-S and the DSMC method. A sub-relax technique is adopted to deal with information transfer between the N-S and the DSMC. The hypersonic flows over a 70-deg spherically blunted cone under different Kn numbers are simulated using the CFD, DSMC and hybrid N-S/DSMC method. The present computations are found in good agreement with DSMC and experimental results. The present method provides an efficient way to predict the hypersonic aerodynamics in near-continuum transitional flow regime.

Hybrid-DFT  +  V w method for band structure calculation of semiconducting transition metal compounds: the case of cerium dioxide.

PubMed

Ivády, Viktor; Gali, Adam; Abrikosov, Igor A

2017-11-15

Hybrid functionals' non-local exchange-correlation potential contains a derivative discontinuity that improves on standard semi-local density functional theory (DFT) band gaps. Moreover, by careful parameterization, hybrid functionals can provide self-interaction reduced description of selected states. On the other hand, the uniform description of all the electronic states of a given system is a known drawback of these functionals that causes varying accuracy in the description of states with different degrees of localization. This limitation can be remedied by the orbital dependent exact exchange extension of hybrid functionals; the hybrid-DFT  +  V w method (Ivády et al 2014 Phys. Rev. B 90 035146). Based on the analogy of quasi-particle equations and hybrid-DFT single particle equations, here we demonstrate that parameters of hybrid-DFT  +  V w functional can be determined from approximate theoretical quasi-particle spectra without any fitting to experiment. The proposed method is illustrated on the charge self-consistent electronic structure calculation for cerium dioxide where itinerant valence states interact with well-localized 4f atomic like states, making this system challenging for conventional methods, either hybrid-DFT or LDA  +  U, and therefore allowing for a demonstration of the advantages of the proposed scheme.

Preparation and properties of CVD-graphene/AgNWs hybrid transparent electrodes for the application of flexible optoelectronic devices

NASA Astrophysics Data System (ADS)

Wang, Xue-yan; Bao, Jun; Li, Lu; Cui, Shao-li; Du, Xiao-qing

2017-10-01

The flexible electrodes based on CVD-graphene/ AgNWs hybrid transparent films were prepared by the vacuum filtration and substrate transferring method, and several performances of the films including sheet resistance, optical transmittance, work function, surface roughness and flexibility were further researched. The results suggested that the hybrid films which were obtained by vacuum filtration and substrate transferring method have the advantages such as uniform distribution of AgNWs, high work function, low roughness and small sheet resistance and good flexibility. The sheet resistance of the hybrid films would decrease with the increasing of the concentration of AgNWs, while the surface roughness would increase and the optical transmittance at 550nm of the films decrease linearly. Organic light emitting devices (OLED) devices based on CVD-graphene/AgNWs hybrid films were fabricated, and characteristics of voltage-current density, luminance, current efficiency were tested. It's found that CVD-graphene/AgNWs hybrid films were better than CVD-graphene films when they were used as anodes for organic light emitting devices. It can be seen that CVD-graphene/AgNWs hybrid transparent films have great potential in applications of flexible electrodes, and are of great significance for promoting the development of organic light emitting devices.

Design and synthesis of organic-inorganic hybrid capsules for biotechnological applications.

PubMed

Shi, Jiafu; Jiang, Yanjun; Wang, Xiaoli; Wu, Hong; Yang, Dong; Pan, Fusheng; Su, Yanlei; Jiang, Zhongyi

2014-08-07

Organic-inorganic hybrid capsules, which typically possess a hollow lumen and a hybrid wall, have emerged as a novel and promising class of hybrid materials and have attracted enormous attention. In comparison to polymeric capsules or inorganic capsules, the hybrid capsules combine the intrinsic physical/chemical properties of the organic and inorganic moieties, acquire more degrees of freedom to manipulate multiple interactions, create hierarchical structures and integrate multiple functionalities. Thus, the hybrid capsules exhibit superior mechanical strength (vs. polymeric capsules) and diverse functionalities (vs. inorganic capsules), which may give new opportunities to produce high-performance materials. Much effort has been devoted to exploring innovative and effective methods for the synthesis of hybrid capsules that exhibit desirable performance in target applications. This tutorial review firstly presents a brief description of the capsular structure and hybrid materials in nature, then classifies the hybrid capsules into molecule-hybrid capsules and nano-hybrid capsules based upon the size of the organic and inorganic moieties in the capsule wall, followed by a detailed discussion of the design and synthesis of the hybrid capsules. For each kind of hybrid capsule, the state-of-the-art synthesis methods are described in detail and a critical comment is embedded. The applications of these hybrid capsules in biotechnological areas (biocatalysis, drug delivery, etc.) have also been summarized. Hopefully, this review will offer a perspective and guidelines for the future research and development of hybrid capsules.

Optimization of the hybridization-based method for purification of thermostable tRNAs in the presence of tetraalkylammonium salts

PubMed Central

Yokogawa, Takashi; Kitamura, Yusuke; Nakamura, Daigo; Ohno, Satoshi; Nishikawa, Kazuya

2010-01-01

We found that both tetramethylammonium chloride (TMA-Cl) and tetra-ethylammonium chloride (TEA-Cl), which are used as monovalent cations for northern hybridization, drastically destabilized the tertiary structures of tRNAs and enhanced the formation of tRNA•oligoDNA hybrids. These effects are of great advantage for the hybridization-based method for purification of specific tRNAs from unfractionated tRNA mixtures through the use of an immobilized oligoDNA complementary to the target tRNA. Replacement of NaCl by TMA-Cl or TEA-Cl in the hybridization buffer greatly improved the recovery of a specific tRNA, even from unfractionated tRNAs derived from a thermophile. Since TEA-Cl destabilized tRNAs more strongly than TMA-Cl, it was necessary to lower the hybridization temperature at the sacrifice of the purity of the recovered tRNA when using TEA-Cl. Therefore, we propose two alternative protocols, depending on the desired properties of the tRNA to be purified. When the total recovery of the tRNA is important, hybridization should be carried out in the presence of TEA-Cl. However, if the purity of the recovered tRNA is important, TMA-Cl should be used for the hybridization. In principle, this procedure for tRNA purification should be applicable to any small-size RNA whose gene sequence is already known. PMID:20040572

Novel Hybrid Virtual Screening Protocol Based on Molecular Docking and Structure-Based Pharmacophore for Discovery of Methionyl-tRNA Synthetase Inhibitors as Antibacterial Agents

PubMed Central

Liu, Chi; He, Gu; Jiang, Qinglin; Han, Bo; Peng, Cheng

2013-01-01

Methione tRNA synthetase (MetRS) is an essential enzyme involved in protein biosynthesis in all living organisms and is a potential antibacterial target. In the current study, the structure-based pharmacophore (SBP)-guided method has been suggested to generate a comprehensive pharmacophore of MetRS based on fourteen crystal structures of MetRS-inhibitor complexes. In this investigation, a hybrid protocol of a virtual screening method, comprised of pharmacophore model-based virtual screening (PBVS), rigid and flexible docking-based virtual screenings (DBVS), is used for retrieving new MetRS inhibitors from commercially available chemical databases. This hybrid virtual screening approach was then applied to screen the Specs (202,408 compounds) database, a structurally diverse chemical database. Fifteen hit compounds were selected from the final hits and shifted to experimental studies. These results may provide important information for further research of novel MetRS inhibitors as antibacterial agents. PMID:23839093

Impervious surface mapping with Quickbird imagery

PubMed Central

Lu, Dengsheng; Hetrick, Scott; Moran, Emilio

2010-01-01

This research selects two study areas with different urban developments, sizes, and spatial patterns to explore the suitable methods for mapping impervious surface distribution using Quickbird imagery. The selected methods include per-pixel based supervised classification, segmentation-based classification, and a hybrid method. A comparative analysis of the results indicates that per-pixel based supervised classification produces a large number of “salt-and-pepper” pixels, and segmentation based methods can significantly reduce this problem. However, neither method can effectively solve the spectral confusion of impervious surfaces with water/wetland and bare soils and the impacts of shadows. In order to accurately map impervious surface distribution from Quickbird images, manual editing is necessary and may be the only way to extract impervious surfaces from the confused land covers and the shadow problem. This research indicates that the hybrid method consisting of thresholding techniques, unsupervised classification and limited manual editing provides the best performance. PMID:21643434

Electrically heated particulate filter regeneration methods and systems for hybrid vehicles

DOEpatents

Gonze, Eugene V.; Paratore, Jr., Michael J.

2010-10-12

A control system for controlling regeneration of a particulate filter for a hybrid vehicle is provided. The system generally includes a regeneration module that controls current to the particulate filter to initiate regeneration. An engine control module controls operation of an engine of the hybrid vehicle based on the control of the current to the particulate filter.

Transfer matrix method for dynamics modeling and independent modal space vibration control design of linear hybrid multibody system

NASA Astrophysics Data System (ADS)

Rong, Bao; Rui, Xiaoting; Lu, Kun; Tao, Ling; Wang, Guoping; Ni, Xiaojun

2018-05-01

In this paper, an efficient method of dynamics modeling and vibration control design of a linear hybrid multibody system (MS) is studied based on the transfer matrix method. The natural vibration characteristics of a linear hybrid MS are solved by using low-order transfer equations. Then, by constructing the brand-new body dynamics equation, augmented operator and augmented eigenvector, the orthogonality of augmented eigenvector of a linear hybrid MS is satisfied, and its state space model expressed in each independent model space is obtained easily. According to this dynamics model, a robust independent modal space-fuzzy controller is designed for vibration control of a general MS, and the genetic optimization of some critical control parameters of fuzzy tuners is also presented. Two illustrative examples are performed, which results show that this method is computationally efficient and with perfect control performance.

HPV Genotyping of Modified General Primer-Amplicons Is More Analytically Sensitive and Specific by Sequencing than by Hybridization

PubMed Central

Meisal, Roger; Rounge, Trine Ballestad; Christiansen, Irene Kraus; Eieland, Alexander Kirkeby; Worren, Merete Molton; Molden, Tor Faksvaag; Kommedal, Øyvind; Hovig, Eivind; Leegaard, Truls Michael

2017-01-01

Sensitive and specific genotyping of human papillomaviruses (HPVs) is important for population-based surveillance of carcinogenic HPV types and for monitoring vaccine effectiveness. Here we compare HPV genotyping by Next Generation Sequencing (NGS) to an established DNA hybridization method. In DNA isolated from urine, the overall analytical sensitivity of NGS was found to be 22% higher than that of hybridization. NGS was also found to be the most specific method and expanded the detection repertoire beyond the 37 types of the DNA hybridization assay. Furthermore, NGS provided an increased resolution by identifying genetic variants of individual HPV types. The same Modified General Primers (MGP)-amplicon was used in both methods. The NGS method is described in detail to facilitate implementation in the clinical microbiology laboratory and includes suggestions for new standards for detection and calling of types and variants with improved resolution. PMID:28045981

HPV Genotyping of Modified General Primer-Amplicons Is More Analytically Sensitive and Specific by Sequencing than by Hybridization.

PubMed

Meisal, Roger; Rounge, Trine Ballestad; Christiansen, Irene Kraus; Eieland, Alexander Kirkeby; Worren, Merete Molton; Molden, Tor Faksvaag; Kommedal, Øyvind; Hovig, Eivind; Leegaard, Truls Michael; Ambur, Ole Herman

2017-01-01

Sensitive and specific genotyping of human papillomaviruses (HPVs) is important for population-based surveillance of carcinogenic HPV types and for monitoring vaccine effectiveness. Here we compare HPV genotyping by Next Generation Sequencing (NGS) to an established DNA hybridization method. In DNA isolated from urine, the overall analytical sensitivity of NGS was found to be 22% higher than that of hybridization. NGS was also found to be the most specific method and expanded the detection repertoire beyond the 37 types of the DNA hybridization assay. Furthermore, NGS provided an increased resolution by identifying genetic variants of individual HPV types. The same Modified General Primers (MGP)-amplicon was used in both methods. The NGS method is described in detail to facilitate implementation in the clinical microbiology laboratory and includes suggestions for new standards for detection and calling of types and variants with improved resolution.

Solution of the nonlinear mixed Volterra-Fredholm integral equations by hybrid of block-pulse functions and Bernoulli polynomials.

PubMed

Mashayekhi, S; Razzaghi, M; Tripak, O

2014-01-01

A new numerical method for solving the nonlinear mixed Volterra-Fredholm integral equations is presented. This method is based upon hybrid functions approximation. The properties of hybrid functions consisting of block-pulse functions and Bernoulli polynomials are presented. The operational matrices of integration and product are given. These matrices are then utilized to reduce the nonlinear mixed Volterra-Fredholm integral equations to the solution of algebraic equations. Illustrative examples are included to demonstrate the validity and applicability of the technique.

Solution of the Nonlinear Mixed Volterra-Fredholm Integral Equations by Hybrid of Block-Pulse Functions and Bernoulli Polynomials

PubMed Central

Mashayekhi, S.; Razzaghi, M.; Tripak, O.

2014-01-01

A new numerical method for solving the nonlinear mixed Volterra-Fredholm integral equations is presented. This method is based upon hybrid functions approximation. The properties of hybrid functions consisting of block-pulse functions and Bernoulli polynomials are presented. The operational matrices of integration and product are given. These matrices are then utilized to reduce the nonlinear mixed Volterra-Fredholm integral equations to the solution of algebraic equations. Illustrative examples are included to demonstrate the validity and applicability of the technique. PMID:24523638

A highly oriented hybrid microarray modified electrode fabricated by a template-free method for ultrasensitive electrochemical DNA recognition

NASA Astrophysics Data System (ADS)

Shi, Lei; Chu, Zhenyu; Dong, Xueliang; Jin, Wanqin; Dempsey, Eithne

2013-10-01

Highly oriented growth of a hybrid microarray was realized by a facile template-free method on gold substrates for the first time. The proposed formation mechanism involves an interfacial structure-directing force arising from self-assembled monolayers (SAMs) between gold substrates and hybrid crystals. Different SAMs and variable surface coverage of the assembled molecules play a critical role in the interfacial directing forces and influence the morphologies of hybrid films. A highly oriented hybrid microarray was formed on the highly aligned and vertical SAMs of 1,4-benzenedithiol molecules with rigid backbones, which afforded an intense structure-directing power for the oriented growth of hybrid crystals. Additionally, the density of the microarray could be adjusted by controlling the surface coverage of assembled molecules. Based on the hybrid microarray modified electrode with a large specific area (ca. 10 times its geometrical area), a label-free electrochemical DNA biosensor was constructed for the detection of an oligonucleotide fragment of the avian flu virus H5N1. The DNA biosensor displayed a significantly low detection limit of 5 pM (S/N = 3), a wide linear response from 10 pM to 10 nM, as well as excellent selectivity, good regeneration and high stability. We expect that the proposed template-free method can provide a new reference for the fabrication of a highly oriented hybrid array and the as-prepared microarray modified electrode will be a promising paradigm in constructing highly sensitive and selective biosensors.Highly oriented growth of a hybrid microarray was realized by a facile template-free method on gold substrates for the first time. The proposed formation mechanism involves an interfacial structure-directing force arising from self-assembled monolayers (SAMs) between gold substrates and hybrid crystals. Different SAMs and variable surface coverage of the assembled molecules play a critical role in the interfacial directing forces and influence the morphologies of hybrid films. A highly oriented hybrid microarray was formed on the highly aligned and vertical SAMs of 1,4-benzenedithiol molecules with rigid backbones, which afforded an intense structure-directing power for the oriented growth of hybrid crystals. Additionally, the density of the microarray could be adjusted by controlling the surface coverage of assembled molecules. Based on the hybrid microarray modified electrode with a large specific area (ca. 10 times its geometrical area), a label-free electrochemical DNA biosensor was constructed for the detection of an oligonucleotide fragment of the avian flu virus H5N1. The DNA biosensor displayed a significantly low detection limit of 5 pM (S/N = 3), a wide linear response from 10 pM to 10 nM, as well as excellent selectivity, good regeneration and high stability. We expect that the proposed template-free method can provide a new reference for the fabrication of a highly oriented hybrid array and the as-prepared microarray modified electrode will be a promising paradigm in constructing highly sensitive and selective biosensors. Electronic supplementary information (ESI) available: Four-probe method for determining the conductivity of the hybrid crystal (Fig. S1); stability comparisons of the hybrid films (Fig. S2); FESEM images of the hybrid microarray (Fig. S3); electrochemical characterizations of the hybrid films (Fig. S4); DFT simulations (Fig. S5); cross-sectional FESEM image of the hybrid microarray (Fig. S6); regeneration and stability tests of the DNA biosensor (Fig. S7). See DOI: 10.1039/c3nr03097k

New hybrid frequency reuse method for packet loss minimization in LTE network.

PubMed

Ali, Nora A; El-Dakroury, Mohamed A; El-Soudani, Magdi; ElSayed, Hany M; Daoud, Ramez M; Amer, Hassanein H

2015-11-01

This paper investigates the problem of inter-cell interference (ICI) in Long Term Evolution (LTE) mobile systems, which is one of the main problems that causes loss of packets between the base station and the mobile station. Recently, different frequency reuse methods, such as soft and fractional frequency reuse, have been introduced in order to mitigate this type of interference. In this paper, minimizing the packet loss between the base station and the mobile station is the main concern. Soft Frequency Reuse (SFR), which is the most popular frequency reuse method, is examined and the amount of packet loss is measured. In order to reduce packet loss, a new hybrid frequency reuse method is implemented. In this method, each cell occupies the same bandwidth of the SFR, but the total system bandwidth is greater than in SFR. This will provide the new method with a lot of new sub-carriers from the neighboring cells to reduce the ICI which represents a big problem in many applications and causes a lot of packets loss. It is found that the new hybrid frequency reuse method has noticeable improvement in the amount of packet loss compared to SFR method in the different frequency bands. Traffic congestion management in Intelligent Transportation system (ITS) is one of the important applications that is affected by the packet loss due to the large amount of traffic that is exchanged between the base station and the mobile node. Therefore, it is used as a studied application for the proposed frequency reuse method and the improvement in the amount of packet loss reached 49.4% in some frequency bands using the new hybrid frequency reuse method.

An Integrated In Silico Method to Discover Novel Rock1 Inhibitors: Multi- Complex-Based Pharmacophore, Molecular Dynamics Simulation and Hybrid Protocol Virtual Screening.

PubMed

Chen, Haining; Li, Sijia; Hu, Yajiao; Chen, Guo; Jiang, Qinglin; Tong, Rongsheng; Zang, Zhihe; Cai, Lulu

2016-01-01

Rho-associated, coiled-coil containing protein kinase 1 (ROCK1) is an important regulator of focal adhesion, actomyosin contraction and cell motility. In this manuscript, a combination of the multi-complex-based pharmacophore (MCBP), molecular dynamics simulation and a hybrid protocol of a virtual screening method, comprised of multipharmacophore- based virtual screening (PBVS) and ensemble docking-based virtual screening (DBVS) methods were used for retrieving novel ROCK1 inhibitors from the natural products database embedded in the ZINC database. Ten hit compounds were selected from the hit compounds, and five compounds were tested experimentally. Thus, these results may provide valuable information for further discovery of more novel ROCK1 inhibitors.

Two molecular markers based on mitochondrial genomes for varieties identification of the northern snakehead (Channa argus) and blotched snakehead (Channa maculata) and their reciprocal hybrids.

PubMed

Xincheng, Zhang; Kunci, Chen; Xinping, Zhu; Jian, Zhao; Qing, Luo; Xiaoyou, Hong; Wei, Li; Fengfang, Xiao

2015-08-01

The northern snakehead (Channa argus) and blotched snakehead (Channa maculata) and their reciprocal hybrids have played important roles in the Chinese freshwater aquaculture industry, with an annual production in China exceeding 400 thousand tons. While these are popular aquaculture breeds in China, it is not easy to identify northern snakehead, blotched snakehead, and their hybrids. Thus, a method should be developed to identify these varieties. To distinguish between the reciprocal hybrids (C. argus ♀ × C. maculata ♂ and C. maculata ♀ × C. argus ♂), the mitochondrial genome sequences of northern snakehead and blotched snakehead and their reciprocal hybrids were compared. Following the alignment and analysis of mtDNA sequences of northern snakehead, blotched snakehead and their hybrids, two pairs of specific primers were designed based on identified differences ranging from 12S rRNA to 16S rRNA gene. The BY1 primers amplified the same bands in the blotched snakehead and the hybrid (C. maculata ♀ × C. argus ♂), while producing no products in northern snakehead and the hybrid (C. argus ♀ × C. maculata ♂). Amplification with WY1 yielded the opposite results. Then, 30 individuals per fish were randomized to verify the primers, and the results showed that the primers were specific for breeds, as intended. The specific primers can not only simply distinguish between two kinds of hybrids, but also rapidly identify the two parents. This study provides a method of molecular marker identification to identify reciprocal hybrids.

PCR-free quantitative detection of genetically modified organism from raw materials – A novel electrochemiluminescence-based bio-barcode method

PubMed Central

Zhu, Debin; Tang, Yabing; Xing, Da; Chen, Wei R.

2018-01-01

Bio-barcode assay based on oligonucleotide-modified gold nanoparticles (Au-NPs) provides a PCR-free method for quantitative detection of nucleic acid targets. However, the current bio-barcode assay requires lengthy experimental procedures including the preparation and release of barcode DNA probes from the target-nanoparticle complex, and immobilization and hybridization of the probes for quantification. Herein, we report a novel PCR-free electrochemiluminescence (ECL)-based bio-barcode assay for the quantitative detection of genetically modified organism (GMO) from raw materials. It consists of tris-(2’2’-bipyridyl) ruthenium (TBR)-labele barcode DNA, nucleic acid hybridization using Au-NPs and biotin-labeled probes, and selective capture of the hybridization complex by streptavidin-coated paramagnetic beads. The detection of target DNA is realized by direct measurement of ECL emission of TBR. It can quantitatively detect target nucleic acids with high speed and sensitivity. This method can be used to quantitatively detect GMO fragments from real GMO products. PMID:18386909

PCR-free quantitative detection of genetically modified organism from raw materials. An electrochemiluminescence-based bio bar code method.

PubMed

Zhu, Debin; Tang, Yabing; Xing, Da; Chen, Wei R

2008-05-15

A bio bar code assay based on oligonucleotide-modified gold nanoparticles (Au-NPs) provides a PCR-free method for quantitative detection of nucleic acid targets. However, the current bio bar code assay requires lengthy experimental procedures including the preparation and release of bar code DNA probes from the target-nanoparticle complex and immobilization and hybridization of the probes for quantification. Herein, we report a novel PCR-free electrochemiluminescence (ECL)-based bio bar code assay for the quantitative detection of genetically modified organism (GMO) from raw materials. It consists of tris-(2,2'-bipyridyl) ruthenium (TBR)-labeled bar code DNA, nucleic acid hybridization using Au-NPs and biotin-labeled probes, and selective capture of the hybridization complex by streptavidin-coated paramagnetic beads. The detection of target DNA is realized by direct measurement of ECL emission of TBR. It can quantitatively detect target nucleic acids with high speed and sensitivity. This method can be used to quantitatively detect GMO fragments from real GMO products.

A Biogeography-Based Optimization Algorithm Hybridized with Tabu Search for the Quadratic Assignment Problem

PubMed Central

Lim, Wee Loon; Wibowo, Antoni; Desa, Mohammad Ishak; Haron, Habibollah

2016-01-01

The quadratic assignment problem (QAP) is an NP-hard combinatorial optimization problem with a wide variety of applications. Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems. It has been shown that BBO provides performance on a par with other optimization methods. A classical BBO algorithm employs the mutation operator as its diversification strategy. However, this process will often ruin the quality of solutions in QAP. In this paper, we propose a hybrid technique to overcome the weakness of classical BBO algorithm to solve QAP, by replacing the mutation operator with a tabu search procedure. Our experiments using the benchmark instances from QAPLIB show that the proposed hybrid method is able to find good solutions for them within reasonable computational times. Out of 61 benchmark instances tested, the proposed method is able to obtain the best known solutions for 57 of them. PMID:26819585

A Biogeography-Based Optimization Algorithm Hybridized with Tabu Search for the Quadratic Assignment Problem.

PubMed

Lim, Wee Loon; Wibowo, Antoni; Desa, Mohammad Ishak; Haron, Habibollah

2016-01-01

The quadratic assignment problem (QAP) is an NP-hard combinatorial optimization problem with a wide variety of applications. Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems. It has been shown that BBO provides performance on a par with other optimization methods. A classical BBO algorithm employs the mutation operator as its diversification strategy. However, this process will often ruin the quality of solutions in QAP. In this paper, we propose a hybrid technique to overcome the weakness of classical BBO algorithm to solve QAP, by replacing the mutation operator with a tabu search procedure. Our experiments using the benchmark instances from QAPLIB show that the proposed hybrid method is able to find good solutions for them within reasonable computational times. Out of 61 benchmark instances tested, the proposed method is able to obtain the best known solutions for 57 of them.

Information Filtering via a Scaling-Based Function

PubMed Central

Qiu, Tian; Zhang, Zi-Ke; Chen, Guang

2013-01-01

Finding a universal description of the algorithm optimization is one of the key challenges in personalized recommendation. In this article, for the first time, we introduce a scaling-based algorithm (SCL) independent of recommendation list length based on a hybrid algorithm of heat conduction and mass diffusion, by finding out the scaling function for the tunable parameter and object average degree. The optimal value of the tunable parameter can be abstracted from the scaling function, which is heterogeneous for the individual object. Experimental results obtained from three real datasets, Netflix, MovieLens and RYM, show that the SCL is highly accurate in recommendation. More importantly, compared with a number of excellent algorithms, including the mass diffusion method, the original hybrid method, and even an improved version of the hybrid method, the SCL algorithm remarkably promotes the personalized recommendation in three other aspects: solving the accuracy-diversity dilemma, presenting a high novelty, and solving the key challenge of cold start problem. PMID:23696829

The Diagnostic Yield of Array Comparative Genomic Hybridization Is High Regardless of Severity of Intellectual Disability/Developmental Delay in Children.

PubMed

D'Arrigo, Stefano; Gavazzi, Francesco; Alfei, Enrico; Zuffardi, Orsetta; Montomoli, Cristina; Corso, Barbara; Buzzi, Erika; Sciacca, Francesca L; Bulgheroni, Sara; Riva, Daria; Pantaleoni, Chiara

2016-05-01

Microarray-based comparative genomic hybridization is a method of molecular analysis that identifies chromosomal anomalies (or copy number variants) that correlate with clinical phenotypes. The aim of the present study was to apply a clinical score previously designated by de Vries to 329 patients with intellectual disability/developmental disorder (intellectual disability/developmental delay) referred to our tertiary center and to see whether the clinical factors are associated with a positive outcome of aCGH analyses. Another goal was to test the association between a positive microarray-based comparative genomic hybridization result and the severity of intellectual disability/developmental delay. Microarray-based comparative genomic hybridization identified structural chromosomal alterations responsible for the intellectual disability/developmental delay phenotype in 16% of our sample. Our study showed that causative copy number variants are frequently found even in cases of mild intellectual disability (30.77%). We want to emphasize the need to conduct microarray-based comparative genomic hybridization on all individuals with intellectual disability/developmental delay, regardless of the severity, because the degree of intellectual disability/developmental delay does not predict the diagnostic yield of microarray-based comparative genomic hybridization. © The Author(s) 2015.

Hybrid Method for Power Control Simulation of a Single Fluid Plasma Thruster

NASA Astrophysics Data System (ADS)

Jaisankar, S.; Sheshadri, T. S.

2018-05-01

Propulsive plasma flow through a cylindrical-conical diverging thruster is simulated by a power controlled hybrid method to obtain the basic flow, thermodynamic and electromagnetic variables. Simulation is based on a single fluid model with electromagnetics being described by the equations of potential Poisson, Maxwell and the Ohm's law while the compressible fluid dynamics by the Navier Stokes in cylindrical form. The proposed method solved the electromagnetics and fluid dynamics separately, both to segregate the two prominent scales for an efficient computation and for the delivery of voltage controlled rated power. The magnetic transport is solved for steady state while fluid dynamics is allowed to evolve in time along with an electromagnetic source using schemes based on generalized finite difference discretization. The multistep methodology with power control is employed for simulating fully ionized propulsive flow of argon plasma through the thruster. Numerical solution shows convergence of every part of the solver including grid stability causing the multistep hybrid method to converge for a rated power delivery. Simulation results are reasonably in agreement with the reported physics of plasma flow in the thruster thus indicating the potential utility of this hybrid computational framework, especially when single fluid approximation of plasma is relevant.

Improvements to direct quantitative analysis of multiple microRNAs facilitating faster analysis.

PubMed

Ghasemi, Farhad; Wegman, David W; Kanoatov, Mirzo; Yang, Burton B; Liu, Stanley K; Yousef, George M; Krylov, Sergey N

2013-11-05

Studies suggest that patterns of deregulation in sets of microRNA (miRNA) can be used as cancer diagnostic and prognostic biomarkers. Establishing a "miRNA fingerprint"-based diagnostic technique requires a suitable miRNA quantitation method. The appropriate method must be direct, sensitive, capable of simultaneous analysis of multiple miRNAs, rapid, and robust. Direct quantitative analysis of multiple microRNAs (DQAMmiR) is a recently introduced capillary electrophoresis-based hybridization assay that satisfies most of these criteria. Previous implementations of the method suffered, however, from slow analysis time and required lengthy and stringent purification of hybridization probes. Here, we introduce a set of critical improvements to DQAMmiR that address these technical limitations. First, we have devised an efficient purification procedure that achieves the required purity of the hybridization probe in a fast and simple fashion. Second, we have optimized the concentrations of the DNA probe to decrease the hybridization time to 10 min. Lastly, we have demonstrated that the increased probe concentrations and decreased incubation time removed the need for masking DNA, further simplifying the method and increasing its robustness. The presented improvements bring DQAMmiR closer to use in a clinical setting.

Random walk and graph cut based active contour model for three-dimension interactive pituitary adenoma segmentation from MR images

NASA Astrophysics Data System (ADS)

Sun, Min; Chen, Xinjian; Zhang, Zhiqiang; Ma, Chiyuan

2017-02-01

Accurate volume measurements of pituitary adenoma are important to the diagnosis and treatment for this kind of sellar tumor. The pituitary adenomas have different pathological representations and various shapes. Particularly, in the case of infiltrating to surrounding soft tissues, they present similar intensities and indistinct boundary in T1-weighted (T1W) magnetic resonance (MR) images. Then the extraction of pituitary adenoma from MR images is still a challenging task. In this paper, we propose an interactive method to segment the pituitary adenoma from brain MR data, by combining graph cuts based active contour model (GCACM) and random walk algorithm. By using the GCACM method, the segmentation task is formulated as an energy minimization problem by a hybrid active contour model (ACM), and then the problem is solved by the graph cuts method. The region-based term in the hybrid ACM considers the local image intensities as described by Gaussian distributions with different means and variances, expressed as maximum a posteriori probability (MAP). Random walk is utilized as an initialization tool to provide initialized surface for GCACM. The proposed method is evaluated on the three-dimensional (3-D) T1W MR data of 23 patients and compared with the standard graph cuts method, the random walk method, the hybrid ACM method, a GCACM method which considers global mean intensity in region forces, and a competitive region-growing based GrowCut method planted in 3D Slicer. Based on the experimental results, the proposed method is superior to those methods.

Kalman Filtered Bio Heat Transfer Model Based Self-adaptive Hybrid Magnetic Resonance Thermometry.

PubMed

Zhang, Yuxin; Chen, Shuo; Deng, Kexin; Chen, Bingyao; Wei, Xing; Yang, Jiafei; Wang, Shi; Ying, Kui

2017-01-01

To develop a self-adaptive and fast thermometry method by combining the original hybrid magnetic resonance thermometry method and the bio heat transfer equation (BHTE) model. The proposed Kalman filtered Bio Heat Transfer Model Based Self-adaptive Hybrid Magnetic Resonance Thermometry, abbreviated as KalBHT hybrid method, introduced the BHTE model to synthesize a window on the regularization term of the hybrid algorithm, which leads to a self-adaptive regularization both spatially and temporally with change of temperature. Further, to decrease the sensitivity to accuracy of the BHTE model, Kalman filter is utilized to update the window at each iteration time. To investigate the effect of the proposed model, computer heating simulation, phantom microwave heating experiment and dynamic in-vivo model validation of liver and thoracic tumor were conducted in this study. The heating simulation indicates that the KalBHT hybrid algorithm achieves more accurate results without adjusting λ to a proper value in comparison to the hybrid algorithm. The results of the phantom heating experiment illustrate that the proposed model is able to follow temperature changes in the presence of motion and the temperature estimated also shows less noise in the background and surrounding the hot spot. The dynamic in-vivo model validation with heating simulation demonstrates that the proposed model has a higher convergence rate, more robustness to susceptibility problem surrounding the hot spot and more accuracy of temperature estimation. In the healthy liver experiment with heating simulation, the RMSE of the hot spot of the proposed model is reduced to about 50% compared to the RMSE of the original hybrid model and the convergence time becomes only about one fifth of the hybrid model. The proposed model is able to improve the accuracy of the original hybrid algorithm and accelerate the convergence rate of MR temperature estimation.

Møller-Plesset perturbation theory gradient in the generalized hybrid orbital quantum mechanical and molecular mechanical method

NASA Astrophysics Data System (ADS)

Jung, Jaewoon; Sugita, Yuji; Ten-no, S.

2010-02-01

An analytic gradient expression is formulated and implemented for the second-order Møller-Plesset perturbation theory (MP2) based on the generalized hybrid orbital QM/MM method. The method enables us to obtain an accurate geometry at a reasonable computational cost. The performance of the method is assessed for various isomers of alanine dipepetide. We also compare the optimized structures of fumaramide-derived [2]rotaxane and cAMP-dependent protein kinase with experiment.

Optimized Vertex Method and Hybrid Reliability

NASA Technical Reports Server (NTRS)

Smith, Steven A.; Krishnamurthy, T.; Mason, B. H.

2002-01-01

A method of calculating the fuzzy response of a system is presented. This method, called the Optimized Vertex Method (OVM), is based upon the vertex method but requires considerably fewer function evaluations. The method is demonstrated by calculating the response membership function of strain-energy release rate for a bonded joint with a crack. The possibility of failure of the bonded joint was determined over a range of loads. After completing the possibilistic analysis, the possibilistic (fuzzy) membership functions were transformed to probability density functions and the probability of failure of the bonded joint was calculated. This approach is called a possibility-based hybrid reliability assessment. The possibility and probability of failure are presented and compared to a Monte Carlo Simulation (MCS) of the bonded joint.

Production and molecular characterization of somatic hybrids between Pleurotus florida and Lentinula edodes.

PubMed

Mallick, Pijush; Sikdar, Samir Ranjan

2014-08-01

Nine inter-generic somatic hybrids named as pfle were produced through PEG-mediated protoplast fusion between Pleurotus florida and Lentinula edodes using double selection method. Hybridity of the newly developed strains was established on the basis of colony morphology, mycelial growth, hyphal traits, fruit-body productivity and inter single sequence repeat (ISSR) marker profiling. Hybrid population was assessed with different phenotypic variables by one-way analysis of variance. Principal component matrices were analyzed for the six phenotypic variables in scatter plot showing maximum positive correlation between each variable for all strains examined. Six ISSR primers generated 66 reproducible fragments with 98.48 % polymorphism. The dendrogram thus created based on unweighted pair-group method with mathematic averages method of clustering and Euclidean distance which exhibited three major groups between the parents and pfle hybrids. Though P. florida parent remained in one group but it showed different degrees of genetic distance with all the hybrid lines belonging to the other two groups while L. edodes was most distantly related to all the hybrid lines. L. edodes specific sequence-rich ISSR amplicon was recorded in all the hybrid lines and in L. edodes but not in P. florida. All the fruit body generating pfle hybrid lines could produce basidiocarp on paddy straw in sub-tropical climate and showed phenotypic resemblance to the P. florida parent.

25th anniversary article: hybrid nanostructures based on two-dimensional nanomaterials.

PubMed

Huang, Xiao; Tan, Chaoliang; Yin, Zongyou; Zhang, Hua

2014-04-09

Two-dimensional (2D) nanomaterials, such as graphene and transition metal dichalcogenides (TMDs), receive a lot of attention, because of their intriguing properties and wide applications in catalysis, energy-storage devices, electronics, optoelectronics, and so on. To further enhance the performance of their application, these 2D nanomaterials are hybridized with other functional nanostructures. In this review, the latest studies of 2D nanomaterial-based hybrid nanostructures are discussed, focusing on their preparation methods, properties, and applications. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Numerical Approach to Spatial Deterministic-Stochastic Models Arising in Cell Biology

PubMed Central

Gao, Fei; Li, Ye; Novak, Igor L.; Slepchenko, Boris M.

2016-01-01

Hybrid deterministic-stochastic methods provide an efficient alternative to a fully stochastic treatment of models which include components with disparate levels of stochasticity. However, general-purpose hybrid solvers for spatially resolved simulations of reaction-diffusion systems are not widely available. Here we describe fundamentals of a general-purpose spatial hybrid method. The method generates realizations of a spatially inhomogeneous hybrid system by appropriately integrating capabilities of a deterministic partial differential equation solver with a popular particle-based stochastic simulator, Smoldyn. Rigorous validation of the algorithm is detailed, using a simple model of calcium ‘sparks’ as a testbed. The solver is then applied to a deterministic-stochastic model of spontaneous emergence of cell polarity. The approach is general enough to be implemented within biologist-friendly software frameworks such as Virtual Cell. PMID:27959915

Human exposure assessment in the near field of GSM base-station antennas using a hybrid finite element/method of moments technique.

PubMed

Meyer, Frans J C; Davidson, David B; Jakobus, Ulrich; Stuchly, Maria A

2003-02-01

A hybrid finite-element method (FEM)/method of moments (MoM) technique is employed for specific absorption rate (SAR) calculations in a human phantom in the near field of a typical group special mobile (GSM) base-station antenna. The MoM is used to model the metallic surfaces and wires of the base-station antenna, and the FEM is used to model the heterogeneous human phantom. The advantages of each of these frequency domain techniques are, thus, exploited, leading to a highly efficient and robust numerical method for addressing this type of bioelectromagnetic problem. The basic mathematical formulation of the hybrid technique is presented. This is followed by a discussion of important implementation details-in particular, the linear algebra routines for sparse, complex FEM matrices combined with dense MoM matrices. The implementation is validated by comparing results to MoM (surface equivalence principle implementation) and finite-difference time-domain (FDTD) solutions of human exposure problems. A comparison of the computational efficiency of the different techniques is presented. The FEM/MoM implementation is then used for whole-body and critical-organ SAR calculations in a phantom at different positions in the near field of a base-station antenna. This problem cannot, in general, be solved using the MoM or FDTD due to computational limitations. This paper shows that the specific hybrid FEM/MoM implementation is an efficient numerical tool for accurate assessment of human exposure in the near field of base-station antennas.

Conditional Random Field (CRF)-Boosting: Constructing a Robust Online Hybrid Boosting Multiple Object Tracker Facilitated by CRF Learning

PubMed Central

Yang, Ehwa; Gwak, Jeonghwan; Jeon, Moongu

2017-01-01

Due to the reasonably acceptable performance of state-of-the-art object detectors, tracking-by-detection is a standard strategy for visual multi-object tracking (MOT). In particular, online MOT is more demanding due to its diverse applications in time-critical situations. A main issue of realizing online MOT is how to associate noisy object detection results on a new frame with previously being tracked objects. In this work, we propose a multi-object tracker method called CRF-boosting which utilizes a hybrid data association method based on online hybrid boosting facilitated by a conditional random field (CRF) for establishing online MOT. For data association, learned CRF is used to generate reliable low-level tracklets and then these are used as the input of the hybrid boosting. To do so, while existing data association methods based on boosting algorithms have the necessity of training data having ground truth information to improve robustness, CRF-boosting ensures sufficient robustness without such information due to the synergetic cascaded learning procedure. Further, a hierarchical feature association framework is adopted to further improve MOT accuracy. From experimental results on public datasets, we could conclude that the benefit of proposed hybrid approach compared to the other competitive MOT systems is noticeable. PMID:28304366

Hybrid LES/RANS simulation of a turbulent boundary layer over a rectangular cavity

NASA Astrophysics Data System (ADS)

Zhang, Qi; Haering, Sigfried; Oliver, Todd; Moser, Robert

2016-11-01

We report numerical investigations of a turbulent boundary layer over a rectangular cavity using a new hybrid RANS/LES model and the traditional Detached Eddy Simulation (DES). Our new hybrid method aims to address many of the shortcomings from the traditional DES. In the new method, RANS/LES blending controlled by a parameter that measures the ratio of the modeled subgrid kinetic energy to an estimate of the subgrid energy based on the resolved scales. The result is a hybrid method automatically resolves as much turbulence as can be supported by the grid and transitions appropriately from RANS to LES without the need for ad hoc delaying functions that are often required for DES. Further, the new model is designed to improve upon DES by accounting for the effects of grid anisotropy and inhomogeneity in the LES region. We present comparisons of the flow features inside the cavity and the pressure time history and spectra as computed using the new hybrid model and DES.

Application of Islanding Detection and Classification of Power Quality Disturbance in Hybrid Energy System

NASA Astrophysics Data System (ADS)

Sun, L. B.; Wu, Z. S.; Yang, K. K.

2018-04-01

Islanding and power quality (PQ) disturbances in hybrid energy system become more serious with the application of renewable energy sources. In this paper, a novel method based on wavelet transform (WT) and modified feed forward neural network (FNN) is proposed to detect islanding and classify PQ problems. First, the performance indices, i.e., the energy content and SD of the transformed signal are extracted from the negative sequence component of the voltage signal at PCC using WT. Afterward, WT indices are fed to train FNNs midfield by Particle Swarm Optimization (PSO) which is a novel heuristic optimization method. Then, the results of simulation based on WT-PSOFNN are discussed in MATLAB/SIMULINK. Simulations on the hybrid power system show that the accuracy can be significantly improved by the proposed method in detecting and classifying of different disturbances connected to multiple distributed generations.

Fabrication of organic-inorganic perovskite thin films for planar solar cells via pulsed laser deposition

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

Liang, Yangang; Zhang, Xiaohang; Gong, Yunhui

2016-01-15

We report on fabrication of organic-inorganic perovskite thin films using a hybrid method consisting of pulsed laser deposition (PLD) of lead iodide and spin-coating of methylammonium iodide. Smooth and highly crystalline CH{sub 3}NH{sub 3}PbI{sub 3} thin films have been fabricated on silicon and glass coated substrates with fluorine doped tin oxide using this PLD-based hybrid method. Planar perovskite solar cells with an inverted structure have been successfully fabricated using the perovskite films. Because of its versatility, the PLD-based hybrid fabrication method not only provides an easy and precise control of the thickness of the perovskite thin films, but also offersmore » a straightforward platform for studying the potential feasibility in using other metal halides and organic salts for formation of the organic-inorganic perovskite structure.« less

Differentiation of respiratory syncytial virus subgroups with cDNA probes in a nucleic acid hybridization assay.

PubMed Central

Sullender, W M; Anderson, L J; Anderson, K; Wertz, G W

1990-01-01

A new approach to respiratory syncytial (RS) virus subgroup determination was developed by using a simple nucleic acid filter hybridization technique. By this method, virus-infected cells are bound and fixed in a single step, and the viral RNA in the fixed-cell preparation is characterized directly by its ability to hybridize to cDNA probes specific for either the A or B subgroups of RS virus. The subgroup-specific probes were constructed from cDNA clones that corresponded to a portion of the extracellular domain of the RS virus G protein of either a subgroup B RS virus (8/60) or a subgroup A RS virus (A2). The cDNA probes were labeled with 32P and used to analyze RS virus isolates collected over a period of three decades. Replicate templates of infected cell preparations were hybridized with either the subgroup A or B probe. The subgroup assignments of 40 viruses tested by nucleic acid hybridization were in agreement with the results of subgroup determinations based on their reactivities with monoclonal antibodies, which previously has been the only method available for determining the subgroup classification of RS virus isolates. The nucleic acid hybridization assay has the advantage of providing broad-based discrimination of the two subgroups on the basis of nucleic acid homology, irrespective of minor antigenic differences that are detected in assays in which monoclonal antibodies are used. The nucleic acid hybridization technique provides a reliable method for RS virus subgroup characterization. Images PMID:2118548

Comparison of dkgB-linked intergenic sequence ribotyping to DNA microarray hybridization for assigning serotype to Salmonella enterica

PubMed Central

Guard, Jean; Sanchez-Ingunza, Roxana; Morales, Cesar; Stewart, Tod; Liljebjelke, Karen; Kessel, JoAnn; Ingram, Kim; Jones, Deana; Jackson, Charlene; Fedorka-Cray, Paula; Frye, Jonathan; Gast, Richard; Hinton, Arthur

2012-01-01

Two DNA-based methods were compared for the ability to assign serotype to 139 isolates of Salmonella enterica ssp. I. Intergenic sequence ribotyping (ISR) evaluated single nucleotide polymorphisms occurring in a 5S ribosomal gene region and flanking sequences bordering the gene dkgB. A DNA microarray hybridization method that assessed the presence and the absence of sets of genes was the second method. Serotype was assigned for 128 (92.1%) of submissions by the two DNA methods. ISR detected mixtures of serotypes within single colonies and it cost substantially less than Kauffmann–White serotyping and DNA microarray hybridization. Decreasing the cost of serotyping S. enterica while maintaining reliability may encourage routine testing and research. PMID:22998607

HOPIS: hybrid omnidirectional and perspective imaging system for mobile robots.

PubMed

Lin, Huei-Yung; Wang, Min-Liang

2014-09-04

In this paper, we present a framework for the hybrid omnidirectional and perspective robot vision system. Based on the hybrid imaging geometry, a generalized stereo approach is developed via the construction of virtual cameras. It is then used to rectify the hybrid image pair using the perspective projection model. The proposed method not only simplifies the computation of epipolar geometry for the hybrid imaging system, but also facilitates the stereo matching between the heterogeneous image formation. Experimental results for both the synthetic data and real scene images have demonstrated the feasibility of our approach.

HOPIS: Hybrid Omnidirectional and Perspective Imaging System for Mobile Robots

PubMed Central

Lin, Huei-Yung.; Wang, Min-Liang.

2014-01-01

In this paper, we present a framework for the hybrid omnidirectional and perspective robot vision system. Based on the hybrid imaging geometry, a generalized stereo approach is developed via the construction of virtual cameras. It is then used to rectify the hybrid image pair using the perspective projection model. The proposed method not only simplifies the computation of epipolar geometry for the hybrid imaging system, but also facilitates the stereo matching between the heterogeneous image formation. Experimental results for both the synthetic data and real scene images have demonstrated the feasibility of our approach. PMID:25192317

A hybrid feature selection method using multiclass SVM for diagnosis of erythemato-squamous disease

NASA Astrophysics Data System (ADS)

Maryam, Setiawan, Noor Akhmad; Wahyunggoro, Oyas

2017-08-01

The diagnosis of erythemato-squamous disease is a complex problem and difficult to detect in dermatology. Besides that, it is a major cause of skin cancer. Data mining implementation in the medical field helps expert to diagnose precisely, accurately, and inexpensively. In this research, we use data mining technique to developed a diagnosis model based on multiclass SVM with a novel hybrid feature selection method to diagnose erythemato-squamous disease. Our hybrid feature selection method, named ChiGA (Chi Square and Genetic Algorithm), uses the advantages from filter and wrapper methods to select the optimal feature subset from original feature. Chi square used as filter method to remove redundant features and GA as wrapper method to select the ideal feature subset with SVM used as classifier. Experiment performed with 10 fold cross validation on erythemato-squamous diseases dataset taken from University of California Irvine (UCI) machine learning database. The experimental result shows that the proposed model based multiclass SVM with Chi Square and GA can give an optimum feature subset. There are 18 optimum features with 99.18% accuracy.

Assessment of a hybrid finite element-transfer matrix model for flat structures with homogeneous acoustic treatments.

PubMed

Alimonti, Luca; Atalla, Noureddine; Berry, Alain; Sgard, Franck

2014-05-01

Modeling complex vibroacoustic systems including poroelastic materials using finite element based methods can be unfeasible for practical applications. For this reason, analytical approaches such as the transfer matrix method are often preferred to obtain a quick estimation of the vibroacoustic parameters. However, the strong assumptions inherent within the transfer matrix method lead to a lack of accuracy in the description of the geometry of the system. As a result, the transfer matrix method is inherently limited to the high frequency range. Nowadays, hybrid substructuring procedures have become quite popular. Indeed, different modeling techniques are typically sought to describe complex vibroacoustic systems over the widest possible frequency range. As a result, the flexibility and accuracy of the finite element method and the efficiency of the transfer matrix method could be coupled in a hybrid technique to obtain a reduction of the computational burden. In this work, a hybrid methodology is proposed. The performances of the method in predicting the vibroacoutic indicators of flat structures with attached homogeneous acoustic treatments are assessed. The results prove that, under certain conditions, the hybrid model allows for a reduction of the computational effort while preserving enough accuracy with respect to the full finite element solution.

A hybrid learning method for constructing compact rule-based fuzzy models.

PubMed

Zhao, Wanqing; Niu, Qun; Li, Kang; Irwin, George W

2013-12-01

The Takagi–Sugeno–Kang-type rule-based fuzzy model has found many applications in different fields; a major challenge is, however, to build a compact model with optimized model parameters which leads to satisfactory model performance. To produce a compact model, most existing approaches mainly focus on selecting an appropriate number of fuzzy rules. In contrast, this paper considers not only the selection of fuzzy rules but also the structure of each rule premise and consequent, leading to the development of a novel compact rule-based fuzzy model. Here, each fuzzy rule is associated with two sets of input attributes, in which the first is used for constructing the rule premise and the other is employed in the rule consequent. A new hybrid learning method combining the modified harmony search method with a fast recursive algorithm is hereby proposed to determine the structure and the parameters for the rule premises and consequents. This is a hard mixed-integer nonlinear optimization problem, and the proposed hybrid method solves the problem by employing an embedded framework, leading to a significantly reduced number of model parameters and a small number of fuzzy rules with each being as simple as possible. Results from three examples are presented to demonstrate the compactness (in terms of the number of model parameters and the number of rules) and the performance of the fuzzy models obtained by the proposed hybrid learning method, in comparison with other techniques from the literature.

Performance evaluations of hybrid modulation with different optical labels over PDQ in high bit-rate OLS network systems.

PubMed

Xu, M; Li, Y; Kang, T Z; Zhang, T S; Ji, J H; Yang, S W

2016-11-14

Two orthogonal modulation optical label switching(OLS) schemes, which are based on payload of polarization multiplexing-differential quadrature phase shift keying(POLMUX-DQPSK or PDQ) modulated with identifications of duobinary (DB) label and pulse position modulation(PPM) label, are researched in high bit-rate OLS network. The BER performance of hybrid modulation with payload and label signals are discussed and evaluated in theory and simulation. The theoretical BER expressions of PDQ, PDQ-DB and PDQ-PPM are given with analysis method of hybrid modulation encoding in different the bit-rate ratios of payload and label. Theoretical derivation results are shown that the payload of hybrid modulation has a certain gain of receiver sensitivity than payload without label. The sizes of payload BER gain obtained from hybrid modulation are related to the different types of label. The simulation results are consistent with that of theoretical conclusions. The extinction ratio (ER) conflicting between hybrid encoding of intensity and phase types can be compromised and optimized in OLS system of hybrid modulation. The BER analysis method of hybrid modulation encoding in OLS system can be applied to other n-ary hybrid modulation or combination modulation systems.

Fuzzy control based engine sizing optimization for a fuel cell/battery hybrid mini-bus

NASA Astrophysics Data System (ADS)

Kim, Minjin; Sohn, Young-Jun; Lee, Won-Yong; Kim, Chang-Soo

The fuel cell/battery hybrid vehicle has been focused for the alternative engine of the existing internal-combustion engine due to the following advantages of the fuel cell and the battery. Firstly, the fuel cell is highly efficient and eco-friendly. Secondly, the battery has the fast response for the changeable power demand. However, the competitive efficiency of the hybrid fuel cell vehicle is necessary to successfully alternate the conventional vehicles with the fuel cell hybrid vehicle. The most relevant factor which affects the overall efficiency of the hybrid fuel cell vehicle is the relative engine sizing between the fuel cell and the battery. Therefore the design method to optimize the engine sizing of the fuel cell hybrid vehicle has been proposed. The target system is the fuel cell/battery hybrid mini-bus and its power distribution is controlled based on the fuzzy logic. The optimal engine sizes are determined based on the simulator developed in this paper. The simulator includes the several models for the fuel cell, the battery, and the major balance of plants. After the engine sizing, the system efficiency and the stability of the power distribution are verified based on the well-known driving schedule. Consequently, the optimally designed mini-bus shows good performance.

A Four-Stage Hybrid Model for Hydrological Time Series Forecasting

PubMed Central

Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

2014-01-01

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of ‘denoising, decomposition and ensemble’. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models. PMID:25111782

A four-stage hybrid model for hydrological time series forecasting.

PubMed

Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

2014-01-01

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of 'denoising, decomposition and ensemble'. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models.

Electrochemical DNA hybridization sensors based on conducting polymers.

PubMed

Rahman, Md Mahbubur; Li, Xiao-Bo; Lopa, Nasrin Siraj; Ahn, Sang Jung; Lee, Jae-Joon

2015-02-05

Conducting polymers (CPs) are a group of polymeric materials that have attracted considerable attention because of their unique electronic, chemical, and biochemical properties. This is reflected in their use in a wide range of potential applications, including light-emitting diodes, anti-static coating, electrochromic materials, solar cells, chemical sensors, biosensors, and drug-release systems. Electrochemical DNA sensors based on CPs can be used in numerous areas related to human health. This review summarizes the recent progress made in the development and use of CP-based electrochemical DNA hybridization sensors. We discuss the distinct properties of CPs with respect to their use in the immobilization of probe DNA on electrode surfaces, and we describe the immobilization techniques used for developing DNA hybridization sensors together with the various transduction methods employed. In the concluding part of this review, we present some of the challenges faced in the use of CP-based DNA hybridization sensors, as well as a future perspective.

Investigating the ability of shunt hybrid power filter based on SRF method under non-ideal supply voltage

NASA Astrophysics Data System (ADS)

Omran, Mohamed A.; Mohd, Izzeldin I.; Almelian, Mohamad M.; Ullah Sheikh, Usman; Bofares, Mustafa E. A. A.

2018-04-01

This study presents the capacity of a self-tuning filter based on the synchronous reference frame method with a fuzzy logic controller for the improvement of the efficiency of harmonic suppression of a shunt hybrid active power filter in an unbalanced distorted and un-distorted voltage supply conditions. The simulation results indicated that the filter with a fuzzy logic controller had a good filtering performance in steady and transient states, irrespective of whether the voltage supply is distorted or unbalanced.

Battery control system for hybrid vehicle and method for controlling a hybrid vehicle battery

DOEpatents

Bockelmann, Thomas R [Battle Creek, MI; Beaty, Kevin D [Kalamazoo, MI; Zou, Zhanijang [Battle Creek, MI; Kang, Xiaosong [Battle Creek, MI

2009-07-21

A battery control system for controlling a state of charge of a hybrid vehicle battery includes a detecting arrangement for determining a vehicle operating state or an intended vehicle operating state and a controller for setting a target state of charge level of the battery based on the vehicle operating state or the intended vehicle operating state. The controller is operable to set a target state of charge level at a first level during a mobile vehicle operating state and at a second level during a stationary vehicle operating state or in anticipation of the vehicle operating in the stationary vehicle operating state. The invention further includes a method for controlling a state of charge of a hybrid vehicle battery.

Distinguishing between incomplete lineage sorting and genomic introgressions: complete fixation of allospecific mitochondrial DNA in a sexually reproducing fish (Cobitis; Teleostei), despite clonal reproduction of hybrids.

PubMed

Choleva, Lukas; Musilova, Zuzana; Kohoutova-Sediva, Alena; Paces, Jan; Rab, Petr; Janko, Karel

2014-01-01

Distinguishing between hybrid introgression and incomplete lineage sorting causing incongruence among gene trees in that they exhibit topological differences requires application of statistical approaches that are based on biologically relevant models. Such study is especially challenging in hybrid systems, where usual vectors mediating interspecific gene transfers--hybrids with Mendelian heredity--are absent or unknown. Here we study a complex of hybridizing species, which are known to produce clonal hybrids, to discover how one of the species, Cobitis tanaitica, has achieved a pattern of mito-nuclear mosaic genome over the whole geographic range. We appplied three distinct methods, including the method using solely the information on gene tree topologies, and found that the contrasting mito-nuclear signal might not have resulted from the retention of ancestral polymorphism. Instead, we found two signs of hybridization events related to C. tanaitica; one concerning nuclear gene flow and the other suggested mitochondrial capture. Interestingly, clonal inheritance (gynogenesis) of contemporary hybrids prevents genomic introgressions and non-clonal hybrids are either absent or too rare to be detected among European Cobitis. Our analyses therefore suggest that introgressive hybridizations are rather old episodes, mediated by previously existing hybrids whose inheritance was not entirely clonal. Cobitis complex thus supports the view that the type of resulting hybrids depends on a level of genomic divergence between sexual species.

Bio-inspired Hybrid Carbon Nanotube Muscles

NASA Astrophysics Data System (ADS)

Kim, Tae Hyeob; Kwon, Cheong Hoon; Lee, Changsun; An, Jieun; Phuong, Tam Thi Thanh; Park, Sun Hwa; Lima, Márcio D.; Baughman, Ray H.; Kang, Tong Mook; Kim, Seon Jeong

2016-05-01

There has been continuous progress in the development for biomedical engineering systems of hybrid muscle generated by combining skeletal muscle and artificial structure. The main factor affecting the actuation performance of hybrid muscle relies on the compatibility between living cells and their muscle scaffolds during cell culture. Here, we developed a hybrid muscle powered by C2C12 skeletal muscle cells based on the functionalized multi-walled carbon nanotubes (MWCNT) sheets coated with poly(3,4-ethylenedioxythiophene) (PEDOT) to achieve biomimetic actuation. This hydrophilic hybrid muscle is physically durable in solution and responds to electric field stimulation with flexible movement. Furthermore, the biomimetic actuation when controlled by electric field stimulation results in movement similar to that of the hornworm by patterned cell culture method. The contraction and relaxation behavior of the PEDOT/MWCNT-based hybrid muscle is similar to that of the single myotube movement, but has faster relaxation kinetics because of the shape-maintenance properties of the freestanding PEDOT/MWCNT sheets in solution. Our development provides the potential possibility for substantial innovation in the next generation of cell-based biohybrid microsystems.

A hybrid neurogenetic approach for stock forecasting.

PubMed

Kwon, Yung-Keun; Moon, Byung-Ro

2007-05-01

In this paper, we propose a hybrid neurogenetic system for stock trading. A recurrent neural network (NN) having one hidden layer is used for the prediction model. The input features are generated from a number of technical indicators being used by financial experts. The genetic algorithm (GA) optimizes the NN's weights under a 2-D encoding and crossover. We devised a context-based ensemble method of NNs which dynamically changes on the basis of the test day's context. To reduce the time in processing mass data, we parallelized the GA on a Linux cluster system using message passing interface. We tested the proposed method with 36 companies in NYSE and NASDAQ for 13 years from 1992 to 2004. The neurogenetic hybrid showed notable improvement on the average over the buy-and-hold strategy and the context-based ensemble further improved the results. We also observed that some companies were more predictable than others, which implies that the proposed neurogenetic hybrid can be used for financial portfolio construction.

Fuel cell-gas turbine hybrid system design part II: Dynamics and control

NASA Astrophysics Data System (ADS)

McLarty, Dustin; Brouwer, Jack; Samuelsen, Scott

2014-05-01

Fuel cell gas turbine hybrid systems have achieved ultra-high efficiency and ultra-low emissions at small scales, but have yet to demonstrate effective dynamic responsiveness or base-load cost savings. Fuel cell systems and hybrid prototypes have not utilized controls to address thermal cycling during load following operation, and have thus been relegated to the less valuable base-load and peak shaving power market. Additionally, pressurized hybrid topping cycles have exhibited increased stall/surge characteristics particularly during off-design operation. This paper evaluates additional control actuators with simple control methods capable of mitigating spatial temperature variation and stall/surge risk during load following operation of hybrid fuel cell systems. The novel use of detailed, spatially resolved, physical fuel cell and turbine models in an integrated system simulation enables the development and evaluation of these additional control methods. It is shown that the hybrid system can achieve greater dynamic response over a larger operating envelope than either individual sub-system; the fuel cell or gas turbine. Results indicate that a combined feed-forward, P-I and cascade control strategy is capable of handling moderate perturbations and achieving a 2:1 (MCFC) or 4:1 (SOFC) turndown ratio while retaining >65% fuel-to-electricity efficiency, while maintaining an acceptable stack temperature profile and stall/surge margin.

Robust backstepping control of an interlink converter in a hybrid AC/DC microgrid based on feedback linearisation method

NASA Astrophysics Data System (ADS)

Dehkordi, N. Mahdian; Sadati, N.; Hamzeh, M.

2017-09-01

This paper presents a robust dc-link voltage as well as a current control strategy for a bidirectional interlink converter (BIC) in a hybrid ac/dc microgrid. To enhance the dc-bus voltage control, conventional methods strive to measure and feedforward the load or source power in the dc-bus control scheme. However, the conventional feedforward-based approaches require remote measurement with communications. Moreover, conventional methods suffer from stability and performance issues, mainly due to the use of the small-signal-based control design method. To overcome these issues, in this paper, the power from DG units of the dc subgrid imposed on the BIC is considered an unmeasurable disturbance signal. In the proposed method, in contrast to existing methods, using the nonlinear model of BIC, a robust controller that does not need the remote measurement with communications effectively rejects the impact of the disturbance signal imposed on the BIC's dc-link voltage. To avoid communication links, the robust controller has a plug-and-play feature that makes it possible to add a DG/load to or remove it from the dc subgrid without distorting the hybrid microgrid stability. Finally, Monte Carlo simulations are conducted to confirm the effectiveness of the proposed control strategy in MATLAB/SimPowerSystems software environment.

A hybrid method for provincial scale energy-related carbon emission allocation in China.

PubMed

Bai, Hongtao; Zhang, Yingxuan; Wang, Huizhi; Huang, Yanying; Xu, He

2014-01-01

Achievement of carbon emission reduction targets proposed by national governments relies on provincial/state allocations. In this study, a hybrid method for provincial energy-related carbon emissions allocation in China was developed to provide a good balance between production- and consumption-based approaches. In this method, provincial energy-related carbon emissions are decomposed into direct emissions of local activities other than thermal power generation and indirect emissions as a result of electricity consumption. Based on the carbon reduction efficiency principle, the responsibility for embodied emissions of provincial product transactions is assigned entirely to the production area. The responsibility for carbon generation during the production of thermal power is borne by the electricity consumption area, which ensures that different regions with resource endowments have rational development space. Empirical studies were conducted to examine the hybrid method and three indices, per capita GDP, resource endowment index and the proportion of energy-intensive industries, were screened to preliminarily interpret the differences among China's regional carbon emissions. Uncertainty analysis and a discussion of this method are also provided herein.

Generalized type II hybrid ARQ scheme using punctured convolutional coding

NASA Astrophysics Data System (ADS)

Kallel, Samir; Haccoun, David

1990-11-01

A method is presented to construct rate-compatible convolutional (RCC) codes from known high-rate punctured convolutional codes, obtained from best-rate 1/2 codes. The construction method is rather simple and straightforward, and still yields good codes. Moreover, low-rate codes can be obtained without any limit on the lowest achievable code rate. Based on the RCC codes, a generalized type-II hybrid ARQ scheme, which combines the benefits of the modified type-II hybrid ARQ strategy of Hagenauer (1988) with the code-combining ARQ strategy of Chase (1985), is proposed and analyzed. With the proposed generalized type-II hybrid ARQ strategy, the throughput increases as the starting coding rate increases, and as the channel degrades, it tends to merge with the throughput of rate 1/2 type-II hybrid ARQ schemes with code combining, thus allowing the system to be flexible and adaptive to channel conditions, even under wide noise variations and severe degradations.

NEMA image quality phantom measurements and attenuation correction in integrated PET/MR hybrid imaging.

PubMed

Ziegler, Susanne; Jakoby, Bjoern W; Braun, Harald; Paulus, Daniel H; Quick, Harald H

2015-12-01

In integrated PET/MR hybrid imaging the evaluation of PET performance characteristics according to the NEMA standard NU 2-2007 is challenging because of incomplete MR-based attenuation correction (AC) for phantom imaging. In this study, a strategy for CT-based AC of the NEMA image quality (IQ) phantom is assessed. The method is systematically evaluated in NEMA IQ phantom measurements on an integrated PET/MR system. NEMA IQ measurements were performed on the integrated 3.0 Tesla PET/MR hybrid system (Biograph mMR, Siemens Healthcare). AC of the NEMA IQ phantom was realized by an MR-based and by a CT-based method. The suggested CT-based AC uses a template μ-map of the NEMA IQ phantom and a phantom holder for exact repositioning of the phantom on the systems patient table. The PET image quality parameters contrast recovery, background variability, and signal-to-noise ratio (SNR) were determined and compared for both phantom AC methods. Reconstruction parameters of an iterative 3D OP-OSEM reconstruction were optimized for highest lesion SNR in NEMA IQ phantom imaging. Using a CT-based NEMA IQ phantom μ-map on the PET/MR system is straightforward and allowed performing accurate NEMA IQ measurements on the hybrid system. MR-based AC was determined to be insufficient for PET quantification in the tested NEMA IQ phantom because only photon attenuation caused by the MR-visible phantom filling but not the phantom housing is considered. Using the suggested CT-based AC, the highest SNR in this phantom experiment for small lesions (<= 13 mm) was obtained with 3 iterations, 21 subsets and 4 mm Gaussian filtering. This study suggests CT-based AC for the NEMA IQ phantom when performing PET NEMA IQ measurements on an integrated PET/MR hybrid system. The superiority of CT-based AC for this phantom is demonstrated by comparison to measurements using MR-based AC. Furthermore, optimized PET image reconstruction parameters are provided for the highest lesion SNR in NEMA IQ phantom measurements.

Finite-time hybrid projective synchronization of the drive-response complex networks with distributed-delay via adaptive intermittent control

NASA Astrophysics Data System (ADS)

Cheng, Lin; Yang, Yongqing; Li, Li; Sui, Xin

2018-06-01

This paper studies the finite-time hybrid projective synchronization of the drive-response complex networks. In the model, general transmission delays and distributed delays are also considered. By designing the adaptive intermittent controllers, the response network can achieve hybrid projective synchronization with the drive system in finite time. Based on finite-time stability theory and several differential inequalities, some simple finite-time hybrid projective synchronization criteria are derived. Two numerical examples are given to illustrate the effectiveness of the proposed method.

A Novel Interfacing Technique for Distributed Hybrid Simulations Combining EMT and Transient Stability Models

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

Shu, Dewu; Xie, Xiaorong; Jiang, Qirong

With steady increase of power electronic devices and nonlinear dynamic loads in large scale AC/DC systems, the traditional hybrid simulation method, which incorporates these components into a single EMT subsystem and hence causes great difficulty for network partitioning and significant deterioration in simulation efficiency. To resolve these issues, a novel distributed hybrid simulation method is proposed in this paper. The key to realize this method is a distinct interfacing technique, which includes: i) a new approach based on the two-level Schur complement to update the interfaces by taking full consideration of the couplings between different EMT subsystems; and ii) amore » combined interaction protocol to further improve the efficiency while guaranteeing the simulation accuracy. The advantages of the proposed method in terms of both efficiency and accuracy have been verified by using it for the simulation study of an AC/DC hybrid system including a two-terminal VSC-HVDC and nonlinear dynamic loads.« less

Time-series-based hybrid mathematical modelling method adapted to forecast automotive and medical waste generation: Case study of Lithuania.

PubMed

Karpušenkaitė, Aistė; Ruzgas, Tomas; Denafas, Gintaras

2018-05-01

The aim of the study was to create a hybrid forecasting method that could produce higher accuracy forecasts than previously used 'pure' time series methods. Mentioned methods were already tested with total automotive waste, hazardous automotive waste, and total medical waste generation, but demonstrated at least a 6% error rate in different cases and efforts were made to decrease it even more. Newly developed hybrid models used a random start generation method to incorporate different time-series advantages and it helped to increase the accuracy of forecasts by 3%-4% in hazardous automotive waste and total medical waste generation cases; the new model did not increase the accuracy of total automotive waste generation forecasts. Developed models' abilities to forecast short- and mid-term forecasts were tested using prediction horizon.

Improvements to image quality using hybrid and model-based iterative reconstructions: a phantom study.

PubMed

Aurumskjöld, Marie-Louise; Ydström, Kristina; Tingberg, Anders; Söderberg, Marcus

2017-01-01

The number of computed tomography (CT) examinations is increasing and leading to an increase in total patient exposure. It is therefore important to optimize CT scan imaging conditions in order to reduce the radiation dose. The introduction of iterative reconstruction methods has enabled an improvement in image quality and a reduction in radiation dose. To investigate how image quality depends on reconstruction method and to discuss patient dose reduction resulting from the use of hybrid and model-based iterative reconstruction. An image quality phantom (Catphan® 600) and an anthropomorphic torso phantom were examined on a Philips Brilliance iCT. The image quality was evaluated in terms of CT numbers, noise, noise power spectra (NPS), contrast-to-noise ratio (CNR), low-contrast resolution, and spatial resolution for different scan parameters and dose levels. The images were reconstructed using filtered back projection (FBP) and different settings of hybrid (iDose 4 ) and model-based (IMR) iterative reconstruction methods. iDose 4 decreased the noise by 15-45% compared with FBP depending on the level of iDose 4 . The IMR reduced the noise even further, by 60-75% compared to FBP. The results are independent of dose. The NPS showed changes in the noise distribution for different reconstruction methods. The low-contrast resolution and CNR were improved with iDose 4 , and the improvement was even greater with IMR. There is great potential to reduce noise and thereby improve image quality by using hybrid or, in particular, model-based iterative reconstruction methods, or to lower radiation dose and maintain image quality. © The Foundation Acta Radiologica 2016.

Fast mean and variance computation of the diffuse sound transmission through finite-sized thick and layered wall and floor systems

NASA Astrophysics Data System (ADS)

Decraene, Carolina; Dijckmans, Arne; Reynders, Edwin P. B.

2018-05-01

A method is developed for computing the mean and variance of the diffuse field sound transmission loss of finite-sized layered wall and floor systems that consist of solid, fluid and/or poroelastic layers. This is achieved by coupling a transfer matrix model of the wall or floor to statistical energy analysis subsystem models of the adjacent room volumes. The modal behavior of the wall is approximately accounted for by projecting the wall displacement onto a set of sinusoidal lateral basis functions. This hybrid modal transfer matrix-statistical energy analysis method is validated on multiple wall systems: a thin steel plate, a polymethyl methacrylate panel, a thick brick wall, a sandwich panel, a double-leaf wall with poro-elastic material in the cavity, and a double glazing. The predictions are compared with experimental data and with results obtained using alternative prediction methods such as the transfer matrix method with spatial windowing, the hybrid wave based-transfer matrix method, and the hybrid finite element-statistical energy analysis method. These comparisons confirm the prediction accuracy of the proposed method and the computational efficiency against the conventional hybrid finite element-statistical energy analysis method.

Detection of Protein Interactions in T3S Systems Using Yeast Two-Hybrid Analysis.

PubMed

Nilles, Matthew L

2017-01-01

Two-hybrid systems, sometimes termed interaction traps, are genetic systems designed to find and analyze interactions between proteins. The most common systems are yeast based (commonly Saccharomyces cerevisae) and rely on the functional reconstitution of the GAL4 transcriptional activator. Reporter genes, such as the lacZ gene of Escherichia coli (encodes β-galactosidase), are placed under GAL4-dependent transcriptional control to provide quick and reliable detection of protein interactions. In this method the use of a yeast-based two-hybrid system is described to study protein interactions between components of type III secretion systems.

Advancing renal education: hybrid simulation, using simulated patients to enhance realism in haemodialysis education.

PubMed

Dunbar-Reid, Kylie; Sinclair, Peter M; Hudson, Denis

2015-06-01

Simulation is a well-established and proven teaching method, yet its use in renal education is not widely reported. Criticisms of simulation-based teaching include limited realism and a lack of authentic patient interaction. This paper discusses the benefits and challenges of high-fidelity simulation and suggests hybrid simulation as a complementary model to existing simulation programmes. Through the use of a simulated patient, hybrid simulation can improve the authenticity of renal simulation-based education while simultaneously teaching and assessing technologically enframed caring. © 2015 European Dialysis and Transplant Nurses Association/European Renal Care Association.

Safety Verification of a Fault Tolerant Reconfigurable Autonomous Goal-Based Robotic Control System

NASA Technical Reports Server (NTRS)

Braman, Julia M. B.; Murray, Richard M; Wagner, David A.

2007-01-01

Fault tolerance and safety verification of control systems are essential for the success of autonomous robotic systems. A control architecture called Mission Data System (MDS), developed at the Jet Propulsion Laboratory, takes a goal-based control approach. In this paper, a method for converting goal network control programs into linear hybrid systems is developed. The linear hybrid system can then be verified for safety in the presence of failures using existing symbolic model checkers. An example task is simulated in MDS and successfully verified using HyTech, a symbolic model checking software for linear hybrid systems.

Carbon-based hybrid nanogels: a synergistic nanoplatform for combined biosensing, bioimaging, and responsive drug delivery.

PubMed

Wang, Hui; Chen, Qianwang; Zhou, Shuiqin

2018-06-05

Nanosized crosslinked polymer networks, named as nanogels, are playing an increasingly important role in a diverse range of applications by virtue of their porous structures, large surface area, good biocompatibility and responsiveness to internal and/or external chemico-physical stimuli. Recently, a variety of carbon nanomaterials, such as carbon quantum dots, graphene/graphene oxide nanosheets, fullerenes, carbon nanotubes, and nanodiamonds, have been embedded into responsive polymer nanogels, in order to integrate the unique electro-optical properties of carbon nanomaterials with the merits of nanogels into a single hybrid nanogel system for improvement of their applications in nanomedicine. A vast number of studies have been pursued to explore the applications of carbon-based hybrid nanogels in biomedical areas for biosensing, bioimaging, and smart drug carriers with combinatorial therapies and/or theranostic ability. New synthetic methods and structures have been developed to prepare carbon-based hybrid nanogels with versatile properties and functions. In this review, we summarize the latest developments and applications and address the future perspectives of these carbon-based hybrid nanogels in the biomedical field.

Hybridization in the section Mentha (Lamiaceae) inferred from AFLP markers.

PubMed

Gobert, V; Moja, S; Colson, M; Taberlet, P

2002-12-01

The amplified fragment length polymorphism (AFLP) method was used to evaluate genetic diversity and to assess genetic relationships within the section Mentha in order to clarify the taxonomy of several interspecific mint hybrids with molecular markers. To this end, genetic diversity of 62 Mentha accessions from different geographic origins, representing five species and three hybrids, was assessed. Three EcoRI/MseI AFLP primer combinations generated an average of 40 AFLP markers per primer combination, ranging in size from 50 to 500 base pairs (bp). The percentage of markers polymorphic ranged from 50% to 60% across all accessions studied. According to phenetic and cladistic analysis, the 62 mint accessions were grouped into two major clusters. Principal coordinates analysis separated species into well-defined groups, and clear relationships between species and hybrids could be described. Our AFLP analysis supports taxonomic classification established among Mentha species by conventional (morphological, cytological, and chemical) methods. It allows the assessment of phenetic relationships between species and the hybrids M. spicata and M. × piperita, largely cultivated all over the world for their menthol source, and provides new insights into the subdivision of M. spicata, based for the first time on molecular markers.

Sample size for post-marketing safety studies based on historical controls.

PubMed

Wu, Yu-te; Makuch, Robert W

2010-08-01

As part of a drug's entire life cycle, post-marketing studies are an important part in the identification of rare, serious adverse events. Recently, the US Food and Drug Administration (FDA) has begun to implement new post-marketing safety mandates as a consequence of increased emphasis on safety. The purpose of this research is to provide exact sample size formula for the proposed hybrid design, based on a two-group cohort study with incorporation of historical external data. Exact sample size formula based on the Poisson distribution is developed, because the detection of rare events is our outcome of interest. Performance of exact method is compared to its approximate large-sample theory counterpart. The proposed hybrid design requires a smaller sample size compared to the standard, two-group prospective study design. In addition, the exact method reduces the number of subjects required in the treatment group by up to 30% compared to the approximate method for the study scenarios examined. The proposed hybrid design satisfies the advantages and rationale of the two-group design with smaller sample sizes generally required. 2010 John Wiley & Sons, Ltd.

Hybrid 3D-2D printing for bone scaffolds fabrication

NASA Astrophysics Data System (ADS)

Seleznev, V. A.; Prinz, V. Ya

2017-02-01

It is a well-known fact that bone scaffold topography on micro- and nanometer scale influences the cellular behavior. Nano-scale surface modification of scaffolds allows the modulation of biological activity for enhanced cell differentiation. To date, there has been only a limited success in printing scaffolds with micro- and nano-scale features exposed on the surface. To improve on the currently available imperfect technologies, in our paper we introduce new hybrid technologies based on a combination of 2D (nano imprint) and 3D printing methods. The first method is based on using light projection 3D printing and simultaneous 2D nanostructuring of each of the layers during the formation of the 3D structure. The second method is based on the sequential integration of preliminarily created 2D nanostructured films into a 3D printed structure. The capabilities of the developed hybrid technologies are demonstrated with the example of forming 3D bone scaffolds. The proposed technologies can be used to fabricate complex 3D micro- and nanostructured products for various fields.

A novel hybrid decomposition-and-ensemble model based on CEEMD and GWO for short-term PM2.5 concentration forecasting

NASA Astrophysics Data System (ADS)

Niu, Mingfei; Wang, Yufang; Sun, Shaolong; Li, Yongwu

2016-06-01

To enhance prediction reliability and accuracy, a hybrid model based on the promising principle of "decomposition and ensemble" and a recently proposed meta-heuristic called grey wolf optimizer (GWO) is introduced for daily PM2.5 concentration forecasting. Compared with existing PM2.5 forecasting methods, this proposed model has improved the prediction accuracy and hit rates of directional prediction. The proposed model involves three main steps, i.e., decomposing the original PM2.5 series into several intrinsic mode functions (IMFs) via complementary ensemble empirical mode decomposition (CEEMD) for simplifying the complex data; individually predicting each IMF with support vector regression (SVR) optimized by GWO; integrating all predicted IMFs for the ensemble result as the final prediction by another SVR optimized by GWO. Seven benchmark models, including single artificial intelligence (AI) models, other decomposition-ensemble models with different decomposition methods and models with the same decomposition-ensemble method but optimized by different algorithms, are considered to verify the superiority of the proposed hybrid model. The empirical study indicates that the proposed hybrid decomposition-ensemble model is remarkably superior to all considered benchmark models for its higher prediction accuracy and hit rates of directional prediction.

FPGA Techniques Based New Hybrid Modulation Strategies for Voltage Source Inverters

PubMed Central

Sudha, L. U.; Baskaran, J.; Elankurisil, S. A.

2015-01-01

This paper corroborates three different hybrid modulation strategies suitable for single-phase voltage source inverter. The proposed method is formulated using fundamental switching and carrier based pulse width modulation methods. The main tale of this proposed method is to optimize a specific performance criterion, such as minimization of the total harmonic distortion (THD), lower order harmonics, switching losses, and heat losses. The proposed method is articulated using fundamental switching and carrier based pulse width modulation methods. Thus, the harmonic pollution in the power system will be reduced and the power quality will be augmented with better harmonic profile for a target fundamental output voltage. The proposed modulation strategies are simulated in MATLAB r2010a and implemented in a Xilinx spartan 3E-500 FG 320 FPGA processor. The feasibility of these modulation strategies is authenticated through simulation and experimental results. PMID:25821852

Optimal clustering of MGs based on droop controller for improving reliability using a hybrid of harmony search and genetic algorithms.

PubMed

Abedini, Mohammad; Moradi, Mohammad H; Hosseinian, S M

2016-03-01

This paper proposes a novel method to address reliability and technical problems of microgrids (MGs) based on designing a number of self-adequate autonomous sub-MGs via adopting MGs clustering thinking. In doing so, a multi-objective optimization problem is developed where power losses reduction, voltage profile improvement and reliability enhancement are considered as the objective functions. To solve the optimization problem a hybrid algorithm, named HS-GA, is provided, based on genetic and harmony search algorithms, and a load flow method is given to model different types of DGs as droop controller. The performance of the proposed method is evaluated in two case studies. The results provide support for the performance of the proposed method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

A hybrid NIRS-EEG system for self-paced brain computer interface with online motor imagery.

PubMed

Koo, Bonkon; Lee, Hwan-Gon; Nam, Yunjun; Kang, Hyohyeong; Koh, Chin Su; Shin, Hyung-Cheul; Choi, Seungjin

2015-04-15

For a self-paced motor imagery based brain-computer interface (BCI), the system should be able to recognize the occurrence of a motor imagery, as well as the type of the motor imagery. However, because of the difficulty of detecting the occurrence of a motor imagery, general motor imagery based BCI studies have been focusing on the cued motor imagery paradigm. In this paper, we present a novel hybrid BCI system that uses near infrared spectroscopy (NIRS) and electroencephalography (EEG) systems together to achieve online self-paced motor imagery based BCI. We designed a unique sensor frame that records NIRS and EEG simultaneously for the realization of our system. Based on this hybrid system, we proposed a novel analysis method that detects the occurrence of a motor imagery with the NIRS system, and classifies its type with the EEG system. An online experiment demonstrated that our hybrid system had a true positive rate of about 88%, a false positive rate of 7% with an average response time of 10.36 s. As far as we know, there is no report that explored hemodynamic brain switch for self-paced motor imagery based BCI with hybrid EEG and NIRS system. From our experimental results, our hybrid system showed enough reliability for using in a practical self-paced motor imagery based BCI. Copyright © 2014 Elsevier B.V. All rights reserved.

A Hybrid Approach to Clinical Question Answering

DTIC Science & Technology

2014-11-01

participation in TREC, we submitted a single run using a hybrid Natural Language Processing ( NLP )-driven approach to accomplish the given task. Evaluation re...for the CDS track uses a variety of NLP - based techniques to address the clinical questions provided. We present a description of our approach, and...discuss our experimental setup, results and eval- uation in the subsequent sections. 2 Description of Our Approach Our hybrid NLP -driven method presents a

Development of a time-resolved fluorometric method for observing hybridization in living cells using fluorescence resonance energy transfer.

PubMed Central

Tsuji, A; Sato, Y; Hirano, M; Suga, T; Koshimoto, H; Taguchi, T; Ohsuka, S

2001-01-01

We previously showed that a specific kind of mRNA (c-fos) was detected in a living cell under a microscope by introducing two fluorescently labeled oligodeoxynucleotides, each labeled with donor or acceptor, into the cytoplasm, making them hybridize to adjacent locations on c-fos mRNA, and taking images of fluorescence resonance energy transfer (FRET) (A. Tsuji, H. Koshimoto, Y. Sato, M. Hirano. Y. Sei-Iida, S. Kondo, and K. Ishibashi, 2000, Biophys. J. 78:3260-3274). On the formed hybrid, the distance between donor and acceptor becomes close and FRET occurs. To observe small numbers of mRNA in living cells using this method, it is required that FRET fluorescence of hybrid must be distinguished from fluorescence of excess amounts of non-hybridizing probes and from cell autofluorescence. To meet these requirements, we developed a time-resolved method using acceptor fluorescence decays. When a combination of a donor having longer fluorescence lifetime and an acceptor having shorter lifetime is used, the measured fluorescence decays of acceptors under FRET becomes slower than the acceptor fluorescence decay with direct excitation. A combination of Bodipy493/503 and Cy5 was selected as donor and acceptor. When the formed hybrid had a configuration where the target RNA has no single-strand part between the two fluorophores, the acceptor fluorescence of hybrid had a sufficiently longer delay to detect fluorescence of hybrid in the presence of excess amounts of non-hybridizing probes. Spatial separation of 10-12 bases between two fluorophores on the hybrid is also required. The decay is also much slower than cell autofluorescence, and smaller numbers of hybrid were detected with less interference of cell autofluorescence in the cytoplasm of living cells under a time-resolved fluorescence microscope with a time-gated function equipped camera. The present method will be useful when observing induced expressions of mRNA in living cells. PMID:11423432

Study on optimal configuration of the grid-connected wind-solar-battery hybrid power system

NASA Astrophysics Data System (ADS)

Ma, Gang; Xu, Guchao; Ju, Rong; Wu, Tiantian

2017-08-01

The capacity allocation of each energy unit in the grid-connected wind-solar-battery hybrid power system is a significant segment in system design. In this paper, taking power grid dispatching into account, the research priorities are as follows: (1) We establish the mathematic models of each energy unit in the hybrid power system. (2) Based on dispatching of the power grid, energy surplus rate, system energy volatility and total cost, we establish the evaluation system for the wind-solar-battery power system and use a number of different devices as the constraint condition. (3) Based on an improved Genetic algorithm, we put forward a multi-objective optimisation algorithm to solve the optimal configuration problem in the hybrid power system, so we can achieve the high efficiency and economy of the grid-connected hybrid power system. The simulation result shows that the grid-connected wind-solar-battery hybrid power system has a higher comprehensive performance; the method of optimal configuration in this paper is useful and reasonable.

Comparative analysis of nonlinear dimensionality reduction techniques for breast MRI segmentation

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

Akhbardeh, Alireza; Jacobs, Michael A.; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205

2012-04-15

Purpose: Visualization of anatomical structures using radiological imaging methods is an important tool in medicine to differentiate normal from pathological tissue and can generate large amounts of data for a radiologist to read. Integrating these large data sets is difficult and time-consuming. A new approach uses both supervised and unsupervised advanced machine learning techniques to visualize and segment radiological data. This study describes the application of a novel hybrid scheme, based on combining wavelet transform and nonlinear dimensionality reduction (NLDR) methods, to breast magnetic resonance imaging (MRI) data using three well-established NLDR techniques, namely, ISOMAP, local linear embedding (LLE), andmore » diffusion maps (DfM), to perform a comparative performance analysis. Methods: Twenty-five breast lesion subjects were scanned using a 3T scanner. MRI sequences used were T1-weighted, T2-weighted, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging. The hybrid scheme consisted of two steps: preprocessing and postprocessing of the data. The preprocessing step was applied for B{sub 1} inhomogeneity correction, image registration, and wavelet-based image compression to match and denoise the data. In the postprocessing step, MRI parameters were considered data dimensions and the NLDR-based hybrid approach was applied to integrate the MRI parameters into a single image, termed the embedded image. This was achieved by mapping all pixel intensities from the higher dimension to a lower dimensional (embedded) space. For validation, the authors compared the hybrid NLDR with linear methods of principal component analysis (PCA) and multidimensional scaling (MDS) using synthetic data. For the clinical application, the authors used breast MRI data, comparison was performed using the postcontrast DCE MRI image and evaluating the congruence of the segmented lesions. Results: The NLDR-based hybrid approach was able to define and segment both synthetic and clinical data. In the synthetic data, the authors demonstrated the performance of the NLDR method compared with conventional linear DR methods. The NLDR approach enabled successful segmentation of the structures, whereas, in most cases, PCA and MDS failed. The NLDR approach was able to segment different breast tissue types with a high accuracy and the embedded image of the breast MRI data demonstrated fuzzy boundaries between the different types of breast tissue, i.e., fatty, glandular, and tissue with lesions (>86%). Conclusions: The proposed hybrid NLDR methods were able to segment clinical breast data with a high accuracy and construct an embedded image that visualized the contribution of different radiological parameters.« less

Hybrid plasma modeling.

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

Hopkins, Matthew Morgan; DeChant, Lawrence Justin.; Piekos, Edward Stanley

2009-02-01

This report summarizes the work completed during FY2007 and FY2008 for the LDRD project ''Hybrid Plasma Modeling''. The goal of this project was to develop hybrid methods to model plasmas across the non-continuum-to-continuum collisionality spectrum. The primary methodology to span these regimes was to couple a kinetic method (e.g., Particle-In-Cell) in the non-continuum regions to a continuum PDE-based method (e.g., finite differences) in continuum regions. The interface between the two would be adjusted dynamically ased on statistical sampling of the kinetic results. Although originally a three-year project, it became clear during the second year (FY2008) that there were not sufficientmore » resources to complete the project and it was terminated mid-year.« less

Functionalized graphene oxide/Fe3O4 hybrids for cellular magnetic resonance imaging and fluorescence labeling.

PubMed

Zhou, Chaohui; Wu, Hui; Wang, Mingliang; Huang, Chusen; Yang, Dapeng; Jia, Nengqin

2017-09-01

In this work, we developed a T 2 -weighted contrast agent based on graphene oxide (GO)/Fe 3 O 4 hybrids for efficient cellular magnetic resonance imaging (MRI). The GO/Fe 3 O 4 hybrids were obtained by combining with co-precipitation method and pyrolysis method. The structural, surface and magnetic characteristics of the hybrids were systematically characterized by transmission electron microscopy (TEM), vibrating sample magnetometer (VSM), AFM, Raman, FT-IR and XRD. The GO/Fe 3 O 4 hybrids were functionalized by modifying with anionic and cationic polyelectrolyte through layer-by-layer assembling. The fluorescence probe fluorescein isothiocyanate (FITC) was further loaded on the surface of functionalized GO/Fe 3 O 4 hybrids to trace the location of GO/Fe 3 O 4 hybrids in cells. Functionalized GO/Fe 3 O 4 hybrids possess good hydrophilicity, less cytotoxicity, high MRI enhancement with the relaxivity (r 2 ) of 493mM -1 s -1 as well as cellular MRI contrast effect. These obtained results indicated that the functionalized GO/Fe 3 O 4 hybrids could have great potential to be utilized as cellular MRI contrast agents for tumor early diagnosis and monitoring. Copyright © 2017 Elsevier B.V. All rights reserved.

Preparation and optical characteristics of layered perovskite-type lead-bromide-incorporated azobenzene chromophores

NASA Astrophysics Data System (ADS)

Sasai, Ryo; Shinomura, Hisashi

2013-02-01

Lead bromide-based layered perovskite powders with azobenzene derivatives were prepared by a homogeneous precipitation method. From the diffuse reflectance (DR) and photoluminescence (PL) spectra of the hybrid powder materials, the present hybrids exhibited sharp absorption and PL peaks originating from excitons produced in the PbBr42- layer. When the present hybrid powder was irradiated with UV light at 350 nm, the absorption band from the trans-azobenzene chromophore, observed around 350 nm, decreased, while the absorption band from the cis-azobenzene chromophore, observed around 450 nm, increased. These results indicate that azobenzene chromophores in the present hybrid materials exhibit reversible photoisomerization. Moreover, it was found that the PL intensity from the exciton also varied due to photoisomerization of the azobenzene chromophores in the present hybrid. Thus, for the first time we succeeded in preparing the azobenzene derivative lead-bromide-based layered perovskite with photochromism before and after UV light irradiation.

On-chip multiplexed solid-phase nucleic acid hybridization assay using spatial profiles of immobilized quantum dots and fluorescence resonance energy transfer.

PubMed

Noor, M Omair; Tavares, Anthony J; Krull, Ulrich J

2013-07-25

A microfluidic based solid-phase assay for the multiplexed detection of nucleic acid hybridization using quantum dot (QD) mediated fluorescence resonance energy transfer (FRET) is described herein. The glass surface of hybrid glass-polydimethylsiloxane (PDMS) microfluidic channels was chemically modified to assemble the biorecognition interface. Multiplexing was demonstrated using a detection system that was comprised of two colors of immobilized semi-conductor QDs and two different oligonucleotide probe sequences. Green-emitting and red-emitting QDs were paired with Cy3 and Alexa Fluor 647 (A647) labeled oligonucleotides, respectively. The QDs served as energy donors for the transduction of dye labeled oligonucleotide targets. The in-channel assembly of the biorecognition interface and the subsequent introduction of oligonucleotide targets was accomplished within minutes using a combination of electroosmotic flow and electrophoretic force. The concurrent quantification of femtomole quantities of two target sequences was possible by measuring the spatial coverage of FRET sensitized emission along the length of the channel. In previous reports, multiplexed QD-FRET hybridization assays that employed a ratiometric method for quantification had challenges associated with lower analytical sensitivity arising from both donor and acceptor dilution that resulted in reduced energy transfer pathways as compared to single-color hybridization assays. Herein, a spatial method for quantification that is based on in-channel QD-FRET profiles provided higher analytical sensitivity in the multiplexed assay format as compared to single-color hybridization assays. The selectivity of the multiplexed hybridization assays was demonstrated by discrimination between a fully-complementary sequence and a 3 base pair sequence at a contrast ratio of 8 to 1. Copyright © 2013 Elsevier B.V. All rights reserved.

Ultrashort hybrid metal-insulator plasmonic directional coupler.

PubMed

Noghani, Mahmoud Talafi; Samiei, Mohammad Hashem Vadjed

2013-11-01

An ultrashort plasmonic directional coupler based on the hybrid metal-insulator slab waveguide is proposed and analyzed at the telecommunication wavelength of 1550 nm. It is first analyzed using the supermode theory based on mode analysis via the transfer matrix method in the interaction region. Then the 2D model of the coupler, including transition arms, is analyzed using a commercial finite-element method simulator. The hybrid slab waveguide is composed of a metallic layer of silver and two dielectric layers of silica (SiO2) and silicon (Si). The coupler is optimized to have a minimum coupling length and to transfer maximum power considering the layer thicknesses as optimization variables. The resulting coupling length in the submicrometer region along with a noticeable power transfer efficiency are advantages of the proposed coupler compared to previously reported plasmonic couplers.

Method for performing site-specific affinity fractionation for use in DNA sequencing

DOEpatents

Mirzabekov, Andrei Darievich; Lysov, Yuri Petrovich; Dubley, Svetlana A.

1999-01-01

A method for fractionating and sequencing DNA via affinity interaction is provided comprising contacting cleaved DNA to a first array of oligonucleotide molecules to facilitate hybridization between said cleaved DNA and the molecules; extracting the hybridized DNA from the molecules; contacting said extracted hybridized DNA with a second array of oligonucleotide molecules, wherein the oligonucleotide molecules in the second array have specified base sequences that are complementary to said extracted hybridized DNA; and attaching labeled DNA to the second array of oligonucleotide molecules, wherein the labeled re-hybridized DNA have sequences that are complementary to the oligomers. The invention further provides a method for performing multi-step conversions of the chemical structure of compounds comprising supplying an array of polyacrylamide vessels separated by hydrophobic surfaces; immobilizing a plurality of reactants, such as enzymes, in the vessels so that each vessel contains one reactant; contacting the compounds to each of the vessels in a predetermined sequence and for a sufficient time to convert the compounds to a desired state; and isolating the converted compounds from said array.

Miniaturized reaction vessel system, method for performing site-specific biochemical reactions and affinity fractionation for use in DNA sequencing

DOEpatents

Mirzabekov, Andrei Darievich; Lysov, Yuri Petrovich; Dubley, Svetlana A.

2000-01-01

A method for fractionating and sequencing DNA via affinity interaction is provided comprising contacting cleaved DNA to a first array of oligonucleotide molecules to facilitate hybridization between said cleaved DNA and the molecules; extracting the hybridized DNA from the molecules; contacting said extracted hybridized DNA with a second array of oligonucleotide molecules, wherein the oligonucleotide molecules in the second array have specified base sequences that are complementary to said extracted hybridized DNA; and attaching labeled DNA to the second array of oligonucleotide molecules, wherein the labeled re-hybridized DNA have sequences that are complementary to the oligomers. The invention further provides a method for performing multi-step conversions of the chemical structure of compounds comprising supplying an array of polyacrylamide vessels separated by hydrophobic surfaces; immobilizing a plurality of reactants, such as enzymes, in the vessels so that each vessel contains one reactant; contacting the compounds to each of the vessels in a predetermined sequence and for a sufficient time to convert the compounds to a desired state; and isolating the converted compounds from said array.

Method for performing site-specific affinity fractionation for use in DNA sequencing

DOEpatents

Mirzabekov, A.D.; Lysov, Y.P.; Dubley, S.A.

1999-05-18

A method for fractionating and sequencing DNA via affinity interaction is provided comprising contacting cleaved DNA to a first array of oligonucleotide molecules to facilitate hybridization between the cleaved DNA and the molecules; extracting the hybridized DNA from the molecules; contacting the extracted hybridized DNA with a second array of oligonucleotide molecules, wherein the oligonucleotide molecules in the second array have specified base sequences that are complementary to the extracted hybridized DNA; and attaching labeled DNA to the second array of oligonucleotide molecules, wherein the labeled re-hybridized DNA have sequences that are complementary to the oligomers. The invention further provides a method for performing multi-step conversions of the chemical structure of compounds comprising supplying an array of polyacrylamide vessels separated by hydrophobic surfaces; immobilizing a plurality of reactants, such as enzymes, in the vessels so that each vessel contains one reactant; contacting the compounds to each of the vessels in a predetermined sequence and for a sufficient time to convert the compounds to a desired state; and isolating the converted compounds from the array. 14 figs.

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

Huang, Hao; Zhang, Guifu; Zhao, Kun

A hybrid method of combining linear programming (LP) and physical constraints is developed to estimate specific differential phase (K DP) and to improve rain estimation. Moreover, the hybrid K DP estimator and the existing estimators of LP, least squares fitting, and a self-consistent relation of polarimetric radar variables are evaluated and compared using simulated data. Our simulation results indicate the new estimator's superiority, particularly in regions where backscattering phase (δ hv) dominates. Further, a quantitative comparison between auto-weather-station rain-gauge observations and K DP-based radar rain estimates for a Meiyu event also demonstrate the superiority of the hybrid K DP estimatormore » over existing methods.« less

Improved detection of genetic markers of antimicrobial resistance by hybridization probe-based melting curve analysis using primers to mask proximal mutations: examples include the influenza H275Y substitution.

PubMed

Whiley, David M; Jacob, Kevin; Nakos, Jennifer; Bletchly, Cheryl; Nimmo, Graeme R; Nissen, Michael D; Sloots, Theo P

2012-06-01

Numerous real-time PCR assays have been described for detection of the influenza A H275Y alteration. However, the performance of these methods can be undermined by sequence variation in the regions flanking the codon of interest. This is a problem encountered more broadly in microbial diagnostics. In this study, we developed a modification of hybridization probe-based melting curve analysis, whereby primers are used to mask proximal mutations in the sequence targets of hybridization probes, so as to limit the potential for sequence variation to interfere with typing. The approach was applied to the H275Y alteration of the influenza A (H1N1) 2009 strain, as well as a Neisseria gonorrhoeae mutation associated with antimicrobial resistance. Assay performances were assessed using influenza A and N. gonorrhoeae strains characterized by DNA sequencing. The modified hybridization probe-based approach proved successful in limiting the effects of proximal mutations, with the results of melting curve analyses being 100% consistent with the results of DNA sequencing for all influenza A and N. gonorrhoeae strains tested. Notably, these included influenza A and N. gonorrhoeae strains exhibiting additional mutations in hybridization probe targets. Of particular interest was that the H275Y assay correctly typed influenza A strains harbouring a T822C nucleotide substitution, previously shown to interfere with H275Y typing methods. Overall our modified hybridization probe-based approach provides a simple means of circumventing problems caused by sequence variation, and offers improved detection of the influenza A H275Y alteration and potentially other resistance mechanisms.

Hybrid Imaging Labels: Providing the Link Between Mass Spectrometry-Based Molecular Pathology and Theranostics

PubMed Central

Buckle, Tessa; van der Wal, Steffen; van Malderen, Stijn J.M.; Müller, Larissa; Kuil, Joeri; van Unen, Vincent; Peters, Ruud J.B.; van Bemmel, Margaretha E.M.; McDonnell, Liam A.; Velders, Aldrik H.; Koning, Frits; Vanhaeke, Frank; van Leeuwen, Fijs W. B.

2017-01-01

Background: Development of theranostic concepts that include inductively coupled plasma mass spectrometry (ICP-MS) and laser ablation ICP-MS (LA-ICP-MS) imaging can be hindered by the lack of a direct comparison to more standardly used methods for in vitro and in vivo evaluation; e.g. fluorescence or nuclear medicine. In this study a bimodal (or rather, hybrid) tracer that contains both a fluorescent dye and a chelate was used to evaluate the existence of a direct link between mass spectrometry (MS) and in vitro and in vivo molecular imaging findings using fluorescence and radioisotopes. At the same time, the hybrid label was used to determine whether the use of a single isotope label would allow for MS-based diagnostics. Methods: A hybrid label that contained both a DTPA chelate (that was coordinated with either 165Ho or 111In) and a Cy5 fluorescent dye was coupled to the chemokine receptor 4 (CXCR4) targeting peptide Ac-TZ14011 (hybrid-Cy5-Ac-TZ4011). This receptor targeting tracer was used to 1) validate the efficacy of (165Ho-based) mass-cytometry in determining the receptor affinity via comparison with fluorescence-based flow cytometry (Cy5), 2) evaluate the microscopic binding pattern of the tracer in tumor cells using both fluorescence confocal imaging (Cy5) and LA-ICP-MS-imaging (165Ho), 3) compare in vivo biodistribution patterns obtained with ICP-MS (165Ho) and radiodetection (111In) after intravenous administration of hybrid-Cy5-Ac-TZ4011 in tumor-bearing mice. Finally, LA-ICP-MS-imaging (165Ho) was linked to fluorescence-based analysis of excised tissue samples (Cy5). Results: Analysis with both mass-cytometry and flow cytometry revealed a similar receptor affinity, respectively 352 ± 141 nM and 245 ± 65 nM (p = 0.08), but with a much lower detection sensitivity for the first modality. In vitro LA-ICP-MS imaging (165Ho) enabled clear discrimination between CXCR4 positive and negative cells, but fluorescence microscopy was required to determine the intracellular distribution. In vivo biodistribution patterns obtained with ICP-MS (165Ho) and radiodetection (111In) of the hybrid peptide were shown to be similar. Assessment of tracer distribution in excised tissues revealed the location of tracer uptake with both LA-ICP-MS-imaging and fluorescence imaging. Conclusion: Lanthanide-isotope chelation expands the scope of fluorescent/radioactive hybrid tracers to include MS-based analytical tools such as mass-cytometry, ICP-MS and LA-ICP-MS imaging in molecular pathology. In contradiction to common expectations, MS detection using a single chelate imaging agent was shown to be feasible, enabling a direct link between nuclear medicine-based imaging and theranostic methods. PMID:28255355

Conjugated polymers/semiconductor nanocrystals hybrid materials--preparation, electrical transport properties and applications.

PubMed

Reiss, Peter; Couderc, Elsa; De Girolamo, Julia; Pron, Adam

2011-02-01

This critical review discusses specific preparation and characterization methods applied to hybrid materials consisting of π-conjugated polymers (or oligomers) and semiconductor nanocrystals. These materials are of great importance in the quickly growing field of hybrid organic/inorganic electronics since they can serve as active components of photovoltaic cells, light emitting diodes, photodetectors and other devices. The electronic energy levels of the organic and inorganic components of the hybrid can be tuned individually and thin hybrid films can be processed using low cost solution based techniques. However, the interface between the hybrid components and the morphology of the hybrid directly influences the generation, separation and transport of charge carriers and those parameters are not easy to control. Therefore a large variety of different approaches for assembling the building blocks--conjugated polymers and semiconductor nanocrystals--has been developed. They range from their simple blending through various grafting procedures to methods exploiting specific non-covalent interactions between both components, induced by their tailor-made functionalization. In the first part of this review, we discuss the preparation of the building blocks (nanocrystals and polymers) and the strategies for their assembly into hybrid materials' thin films. In the second part, we focus on the charge carriers' generation and their transport within the hybrids. Finally, we summarize the performances of solar cells using conjugated polymer/semiconductor nanocrystals hybrids and give perspectives for future developments.

Scheduled power tracking control of the wind-storage hybrid system based on the reinforcement learning theory

NASA Astrophysics Data System (ADS)

Li, Ze

2017-09-01

In allusion to the intermittency and uncertainty of the wind electricity, energy storage and wind generator are combined into a hybrid system to improve the controllability of the output power. A scheduled power tracking control method is proposed based on the reinforcement learning theory and Q-learning algorithm. In this method, the state space of the environment is formed with two key factors, i.e. the state of charge of the energy storage and the difference value between the actual wind power and scheduled power, the feasible action is the output power of the energy storage, and the corresponding immediate rewarding function is designed to reflect the rationality of the control action. By interacting with the environment and learning from the immediate reward, the optimal control strategy is gradually formed. After that, it could be applied to the scheduled power tracking control of the hybrid system. Finally, the rationality and validity of the method are verified through simulation examples.

Development of novel biocompatible hybrid nanocomposites based on polyurethane-silica prepared by sol gel process.

PubMed

Rashti, Ali; Yahyaei, Hossein; Firoozi, Saman; Ramezani, Sara; Rahiminejad, Ali; Karimi, Roya; Farzaneh, Khadijeh; Mohseni, Mohsen; Ghanbari, Hossein

2016-12-01

Due to high biocompatibility, polyurethane has found many applications, particularly in development of biomedical devices. A new nanocomposite based on thermoset polyurethane and silica nanoparticles was synthesized using sol-gel method. Sol-gel process was fulfilled in two acidic and basic conditions by using tetraethylorthosilicate (TEOS) and trimethoxyisocyanatesilane as precursors. The hybrid films characterized for mechanical and surface properties using tensile strength, contact angle, ATR-FTIR and scanning electron microscopy. Biocompatibility and cytotoxicity of the hybrids were assessed using standard MTT, LDH and TUNEL assays. The results revealed that incorporation of silica nanoparticles was significantly improved tensile strength and mechanical properties of the hybrids. Based on the contact angle results, silica nanoparticles increased hydrophilicity of the hybrids. Biocompatibility by using human lung epithelial cell line (MRC-5) demonstrated that the hybrids were significantly less cytotoxic compared to pristine polymer as tested by MTT and LDH assays. TUNEL assay revealed no signs of apoptosis in all tested samples. The results of this study demonstrated that incorporation of silica nanoparticles into polyurethane lead to the enhancement of biocompatibility, indicating that these hybrids could potentially be used in biomedical field in particular as a new coating for medical implants. Copyright © 2016 Elsevier B.V. All rights reserved.

Overview of existing algorithms for emotion classification. Uncertainties in evaluations of accuracies.

NASA Astrophysics Data System (ADS)

Avetisyan, H.; Bruna, O.; Holub, J.

2016-11-01

A numerous techniques and algorithms are dedicated to extract emotions from input data. In our investigation it was stated that emotion-detection approaches can be classified into 3 following types: Keyword based / lexical-based, learning based, and hybrid. The most commonly used techniques, such as keyword-spotting method, Support Vector Machines, Naïve Bayes Classifier, Hidden Markov Model and hybrid algorithms, have impressive results in this sphere and can reach more than 90% determining accuracy.

Dynamics and Control of Flexible Space Vehicles

NASA Technical Reports Server (NTRS)

Likins, P. W.

1970-01-01

The purpose of this report is twofold: (1) to survey the established analytic procedures for the simulation of controlled flexible space vehicles, and (2) to develop in detail methods that employ a combination of discrete and distributed ("modal") coordinates, i.e., the hybrid-coordinate methods. Analytic procedures are described in three categories: (1) discrete-coordinate methods, (2) hybrid-coordinate methods, and (3) vehicle normal-coordinate methods. Each of these approaches is described and analyzed for its advantages and disadvantages, and each is found to have an area of applicability. The hybrid-coordinate method combines the efficiency of the vehicle normal-coordinate method with the versatility of the discrete-coordinate method, and appears to have the widest range of practical application. The results in this report have practical utility in two areas: (1) complex digital computer simulation of flexible space vehicles of arbitrary configuration subject to realistic control laws, and (2) preliminary control system design based on transfer functions for linearized models of dynamics and control laws.

Development of pyrene-stacked carbon nanotube-based hybrid: measurement of NO3- ions using fluorescence spectroscopy.

PubMed

Billing, Beant Kaur; Mayank; Agnihotri, Prabhat K; Singh, Narinder

2018-06-08

Non-covalent bonding via π-π stacking is in demand these days because it does not affect the structure of the carbon nanotube (CNT). Herein, a hybrid material was fabricated via π-π stacking between the aromatic rings of carbon nanotubes and a dihydropyrimidone-based pyrene derivative. The developed CNT@pyrene hybrid material was fully characterized using SEM, EDX, TEM, XRD, and FTIR techniques. The hybrid was developed to improve the heat transport in the hybrid solution by anion addition. The emission profile of the developed hybrid was screened against TBA salts of different anions in EtOH-H2O (10-90% v/v) solvent system to identify the anion that can interact with the hybrid. The hybrid exhibited high sensitivity and selectivity towards NO3- ions with 1.5-fold enhancement in fluorescence intensity, while other anions neither showed significant responses nor interfered in the sensor's response. The limit of NO3- ions detection was found to be 8.1 nM, calculated using the 3-sigma method. It was observed that the proposed hybrid sensor showed stable response at different pH and diverse salt concentrations. The binding mechanism was elucidated by DFT-based theoretical calculations. Real sample analysis was performed for the detection of NO3- concentrations in local water bodies with accuracy as high as 95%. Viscosity and thermal conductivity experiments were performed to measure the effect of concentration, temperature, and pH on the NO3- response.

A Hybrid Acoustic and Pronunciation Model Adaptation Approach for Non-native Speech Recognition

NASA Astrophysics Data System (ADS)

Oh, Yoo Rhee; Kim, Hong Kook

In this paper, we propose a hybrid model adaptation approach in which pronunciation and acoustic models are adapted by incorporating the pronunciation and acoustic variabilities of non-native speech in order to improve the performance of non-native automatic speech recognition (ASR). Specifically, the proposed hybrid model adaptation can be performed at either the state-tying or triphone-modeling level, depending at which acoustic model adaptation is performed. In both methods, we first analyze the pronunciation variant rules of non-native speakers and then classify each rule as either a pronunciation variant or an acoustic variant. The state-tying level hybrid method then adapts pronunciation models and acoustic models by accommodating the pronunciation variants in the pronunciation dictionary and by clustering the states of triphone acoustic models using the acoustic variants, respectively. On the other hand, the triphone-modeling level hybrid method initially adapts pronunciation models in the same way as in the state-tying level hybrid method; however, for the acoustic model adaptation, the triphone acoustic models are then re-estimated based on the adapted pronunciation models and the states of the re-estimated triphone acoustic models are clustered using the acoustic variants. From the Korean-spoken English speech recognition experiments, it is shown that ASR systems employing the state-tying and triphone-modeling level adaptation methods can relatively reduce the average word error rates (WERs) by 17.1% and 22.1% for non-native speech, respectively, when compared to a baseline ASR system.

Regional gene mapping using mixed radiation hybrids and reverse chromosome painting.

PubMed

Lin, J Y; Bedford, J S

1997-11-01

We describe a new approach for low-resolution physical mapping using pooled DNA probe from mixed (non-clonal) populations of human-CHO cell hybrids and reverse chromosome painting. This mapping method is based on a process in which the human chromosome fragments bearing a complementing gene were selectively retained in a large non-clonal population of CHO-human hybrid cells during a series of 12- to 15-Gy gamma irradiations each followed by continuous growth selection. The location of the gene could then be identified by reverse chromosome painting on normal human metaphase spreads using biotinylated DNA from this population of "enriched" hybrid cells. We tested the validity of this method by correctly mapping the complementing human HPRT gene, whose location is well established. We then demonstrated the method's usefulness by mapping the chromosome location of a human gene which complemented the defect responsible for the hypersensitivity to ionizing radiation in CHO irs-20 cells. This method represents an efficient alternative to conventional concordance analysis in somatic cell hybrids where detailed chromosome analysis of numerous hybrid clones is necessary. Using this approach, it is possible to localize a gene for which there is no prior sequence or linkage information to a subchromosomal region, thus facilitating association with known mapping landmarks (e.g. RFLP, YAC or STS contigs) for higher-resolution mapping.

A hybrid multimodal non-rigid registration of MR images based on diffeomorphic demons.

PubMed

Lu, Huanxiang; Cattin, Philippe C; Reyes, Mauricio

2010-01-01

In this paper we present a novel hybrid approach for multimodal medical image registration based on diffeomorphic demons. Diffeomorphic demons have proven to be a robust and efficient way for intensity-based image registration. A very recent extension even allows to use mutual information (MI) as a similarity measure to registration multimodal images. However, due to the intensity correspondence uncertainty existing in some anatomical parts, it is difficult for a purely intensity-based algorithm to solve the registration problem. Therefore, we propose to combine the resulting transformations from both intensity-based and landmark-based methods for multimodal non-rigid registration based on diffeomorphic demons. Several experiments on different types of MR images were conducted, for which we show that a better anatomical correspondence between the images can be obtained using the hybrid approach than using either intensity information or landmarks alone.

Protein-precipitable tannin in wines from Vitis vinifera and interspecific hybrid grapes (Vitis ssp.): differences in concentration, extractability, and cell wall binding.

PubMed

Springer, Lindsay F; Sacks, Gavin L

2014-07-30

Although they possess significant viticultural advantages, interspecific hybrid grapes (Vitis spp.) are reported to produce wine with lower tannin concentrations than European wine varieties (Vitis vinifera). However, extensive quantitative data on this phenomenon as well as mechanistic explanations for these differences are lacking. A survey of primarily commercial wines from the Finger Lakes American Viticultural Area (New York) using a protein precipitation method determined that hybrid-based wines had >4-fold lower tannin concentrations than vinifera wines. To elucidate factors responsible for differences in wine tannin, 24 wines were produced from both red hybrid and vinifera cultivars under identical conditions. Lower wine tannin in French-American hybrid- than vinifera-based wines could be partially explained by lower grape tannin. However, experiments in which cell wall material was incubated with tannin indicated that cell wall binding may be of equal or greater importance in explaining lower wine tannin concentrations in hybrid-based wines. Subsequent characterization of cell wall material revealed that protein in flesh cell walls and, to a lesser extent, pectin in skin cell walls were correlated with cell wall binding.

Characterization of coronary plaque regions in intravascular ultrasound images using a hybrid ensemble classifier.

PubMed

Hwang, Yoo Na; Lee, Ju Hwan; Kim, Ga Young; Shin, Eun Seok; Kim, Sung Min

2018-01-01

The purpose of this study was to propose a hybrid ensemble classifier to characterize coronary plaque regions in intravascular ultrasound (IVUS) images. Pixels were allocated to one of four tissues (fibrous tissue (FT), fibro-fatty tissue (FFT), necrotic core (NC), and dense calcium (DC)) through processes of border segmentation, feature extraction, feature selection, and classification. Grayscale IVUS images and their corresponding virtual histology images were acquired from 11 patients with known or suspected coronary artery disease using 20 MHz catheter. A total of 102 hybrid textural features including first order statistics (FOS), gray level co-occurrence matrix (GLCM), extended gray level run-length matrix (GLRLM), Laws, local binary pattern (LBP), intensity, and discrete wavelet features (DWF) were extracted from IVUS images. To select optimal feature sets, genetic algorithm was implemented. A hybrid ensemble classifier based on histogram and texture information was then used for plaque characterization in this study. The optimal feature set was used as input of this ensemble classifier. After tissue characterization, parameters including sensitivity, specificity, and accuracy were calculated to validate the proposed approach. A ten-fold cross validation approach was used to determine the statistical significance of the proposed method. Our experimental results showed that the proposed method had reliable performance for tissue characterization in IVUS images. The hybrid ensemble classification method outperformed other existing methods by achieving characterization accuracy of 81% for FFT and 75% for NC. In addition, this study showed that Laws features (SSV and SAV) were key indicators for coronary tissue characterization. The proposed method had high clinical applicability for image-based tissue characterization. Copyright © 2017 Elsevier B.V. All rights reserved.

Electrochemical DNA Hybridization Sensors Based on Conducting Polymers

PubMed Central

Rahman, Md. Mahbubur; Li, Xiao-Bo; Lopa, Nasrin Siraj; Ahn, Sang Jung; Lee, Jae-Joon

2015-01-01

Conducting polymers (CPs) are a group of polymeric materials that have attracted considerable attention because of their unique electronic, chemical, and biochemical properties. This is reflected in their use in a wide range of potential applications, including light-emitting diodes, anti-static coating, electrochromic materials, solar cells, chemical sensors, biosensors, and drug-release systems. Electrochemical DNA sensors based on CPs can be used in numerous areas related to human health. This review summarizes the recent progress made in the development and use of CP-based electrochemical DNA hybridization sensors. We discuss the distinct properties of CPs with respect to their use in the immobilization of probe DNA on electrode surfaces, and we describe the immobilization techniques used for developing DNA hybridization sensors together with the various transduction methods employed. In the concluding part of this review, we present some of the challenges faced in the use of CP-based DNA hybridization sensors, as well as a future perspective. PMID:25664436

Recent advances in the fabrication and structure-specific applications of graphene-based inorganic hybrid membranes.

PubMed

Zhao, Xinne; Zhang, Panpan; Chen, Yuting; Su, Zhiqiang; Wei, Gang

2015-03-12

The preparation and applications of graphene (G)-based materials are attracting increasing interests due to their unique electronic, optical, magnetic, thermal, and mechanical properties. Compared to G-based hybrid and composite materials, G-based inorganic hybrid membrane (GIHM) offers enormous advantages ascribed to their facile synthesis, planar two-dimensional multilayer structure, high specific surface area, and mechanical stability, as well as their unique optical and mechanical properties. In this review, we report the recent advances in the technical fabrication and structure-specific applications of GIHMs with desirable thickness and compositions. In addition, the advantages and disadvantages of the methods utilized for creating GIHMs are discussed in detail. Finally, the potential applications and key challenges of GIHMs for future technical applications are mentioned.

Resin infusion of layered metal/composite hybrid and resulting metal/composite hybrid laminate

NASA Technical Reports Server (NTRS)

Cano, Roberto J. (Inventor); Grimsley, Brian W. (Inventor); Weiser, Erik S. (Inventor); Jensen, Brian J. (Inventor)

2009-01-01

A method of fabricating a metal/composite hybrid laminate is provided. One or more layered arrangements are stacked on a solid base to form a layered structure. Each layered arrangement is defined by a fibrous material and a perforated metal sheet. A resin in its liquid state is introduced along a portion of the layered structure while a differential pressure is applied across the laminate structure until the resin permeates the fibrous material of each layered arrangement and fills perforations in each perforated metal sheet. The resin is cured thereby yielding a metal/composite hybrid laminate.

Monitoring technique for a hybrid PS/WDM-PON by using a tunable OTDR and FBGs

NASA Astrophysics Data System (ADS)

Hann, Swook; Yoo, Jun-sang; Park, Chang-Soo

2006-05-01

A monitoring technique for hybrid passive optical networks (PON) is presented. The technique is based on the remote sensing of fibre Bragg gratings (FBGs) using a tunable optical time domain reflectometer (OTDR). The FBG would help discern an individual event during the monitoring of the hybrid PON in collaboration with the information provided by the Rayleigh backscattered power. The hybrid architecture of passive splitter-PON and WDM-PON can be analysed by the monitoring method by using the tunable OTDR and FBGs at the central office under the in-service state of PON.

Resolution-improved in situ DNA hybridization detection based on microwave photonic interrogation.

PubMed

Cao, Yuan; Guo, Tuan; Wang, Xudong; Sun, Dandan; Ran, Yang; Feng, Xinhuan; Guan, Bai-ou

2015-10-19

In situ bio-sensing system based on microwave photonics filter (MPF) interrogation method with improved resolution is proposed and experimentally demonstrated. A microfiber Bragg grating (mFBG) is used as sensing probe for DNA hybridization detection. Different from the traditional wavelength monitoring technique, we use the frequency interrogation scheme for resolution-improved bio-sensing detection. Experimental results show that the frequency shift of MPF notch presents a linear response to the surrounding refractive index (SRI) change over the range of 1.33 to 1.38, with a SRI resolution up to 2.6 × 10(-5) RIU, which has been increased for almost two orders of magnitude compared with the traditional fundamental mode monitoring technique (~3.6 × 10(-3) RIU). Due to the high Q value (about 27), the whole process of DNA hybridization can be in situ monitored. The proposed MPF-based bio-sensing system provides a new interrogation method over the frequency domain with improved sensing resolution and rapid interrogation rate for biochemical and environmental measurement.

Nondestructive assessment of pore size in foam-based hybrid composite materials

NASA Astrophysics Data System (ADS)

Chen, M. Y.; Ko, R. T.

2012-05-01

In-situ non-destructive evaluation (NDE) during processing of high temperature polymer based hybrids offers great potential to gain close control and achieve the desired level of pore size, with low overall development cost. During the polymer curing cycle, close control over the evolution of volatiles would be beneficial to avoid the presence of pores or at least control their sizes. Traditional NDE methods cannot realistically be expected to evaluate individual pores in such components, as each pore evolves and grows during curing. However, NDE techniques offer the potential to detect and quantify the macroscopic response of many pores that are undesirable or intentionally introduced into these advanced materials. In this paper, preliminary results will be presented for nondestructive assessment of pore size in foam-based hybrid composite materials using ultrasonic techniques. Pore size was evaluated through the frequency content of the ultrasonic signal. The effects of pore size on the attenuation of ultrasound were studied. Feasibility of this method was demonstrated on two types of foams with various pore sizes.

New hybrid conjugate gradient methods with the generalized Wolfe line search.

PubMed

Xu, Xiao; Kong, Fan-Yu

2016-01-01

The conjugate gradient method was an efficient technique for solving the unconstrained optimization problem. In this paper, we made a linear combination with parameters β k of the DY method and the HS method, and putted forward the hybrid method of DY and HS. We also proposed the hybrid of FR and PRP by the same mean. Additionally, to present the two hybrid methods, we promoted the Wolfe line search respectively to compute the step size α k of the two hybrid methods. With the new Wolfe line search, the two hybrid methods had descent property and global convergence property of the two hybrid methods that can also be proved.

Surveillance technique for hybrid WDM/PS-PON using a tunable OTDR

NASA Astrophysics Data System (ADS)

Hann, Swook; Yoo, Jun-sang; Park, Chang-soo

2005-05-01

A surveillance technique for passive optical networks (PON) is presented. The technique is based on the remote sensing of fiber Bragg grating using a tunable OTDR. Hybrid architecture of WDM and passive splitter-PON can be analyzed by the surveillance method at the central office under in-service state of PON.

Fluorescence in-situ hybridization (FISH) as a tool for visualization and enumeration of Campylobacter in broiler ceca

USDA-ARS?s Scientific Manuscript database

Food-borne human pathogens are typically detected and enumerated by either cultural methods or PCR-based approaches. Fluorescence in-situ hybridization (FISH) is a standard microscopy tool for microbial ecology but has not been widely used for food safety applications despite important advantages o...

The Integration of Psychomotor Skills in a Hybrid-PBL Dental Curriculum: The Clinical Clerkships.

ERIC Educational Resources Information Center

Walton, Joanne N.; MacNeil, M. A. J.; Harrison, Rosamund L.; Clark, D. Christopher

1998-01-01

Describes the restructuring of clinical clerkships at the University of British Columbia (Canada) dental school as part of a new, hybrid, problem-based learning (PBL) curriculum, focusing on strategies for integrating development of psychomotor skills. Methods of achieving both horizontal and vertical integration of competencies through grouping…

Recent progress in design and hybridization of planar grating-based transceivers

NASA Astrophysics Data System (ADS)

Bidnyk, S.; Pearson, M.; Balakrishnan, A.; Gao, M.

2007-06-01

We report on recent progress in simulations, physical layout, fabrication and hybridization of planar grating-based transceivers for passive optical networks (PONs). Until recently, PON transceivers have been manufactured using bulk micro-optical components. Today, advancements in modeling and simulation techniques has made it possible to design complex elements in the same silica-on silicon PLC platform and create an alternative platform for manufacturing of bi-directional transceivers. In our chips we simulated an integrated chip that monolithically combined planar reflective gratings and cascaded Mach-Zehnder interferometers. We used a combination of the finite element method and beam propagation method to model cascaded interferometers with enhanced coupling coefficients. Our simulations show that low-diffraction order planar reflective gratings, designed for small incidence and reflection angles, possess the required dispersion strength to meet the PON specifications. Subsequently, we created structures for passive alignment and hybridized photodetectors and lasers. We believe that advancements in simulation of planar lightwave circuits with embedded planar reflective gratings will result in displacement of the thin-film filters (TFFs) technology in many applications that require a high degree of monolithic and hybrid integration.

High- and Reproducible-Performance Graphene/II-VI Semiconductor Film Hybrid Photodetectors

PubMed Central

Huang, Fan; Jia, Feixiang; Cai, Caoyuan; Xu, Zhihao; Wu, Congjun; Ma, Yang; Fei, Guangtao; Wang, Min

2016-01-01

High- and reproducible-performance photodetectors are critical to the development of many technologies, which mainly include one-dimensional (1D) nanostructure based and film based photodetectors. The former suffer from a huge performance variation because the performance is quite sensitive to the synthesis microenvironment of 1D nanostructure. Herein, we show that the graphene/semiconductor film hybrid photodetectors not only possess a high performance but also have a reproducible performance. As a demo, the as-produced graphene/ZnS film hybrid photodetector shows a high responsivity of 1.7 × 107 A/W and a fast response speed of 50 ms, and shows a highly reproducible performance, in terms of narrow distribution of photocurrent (38–65 μA) and response speed (40–60 ms) for 20 devices. Graphene/ZnSe film and graphene/CdSe film hybrid photodetectors fabricated by this method also show a high and reproducible performance. The general method is compatible with the conventional planar process, and would be easily standardized and thus pay a way for the photodetector applications. PMID:27349692

Application of Model Based Parameter Estimation for Fast Frequency Response Calculations of Input Characteristics of Cavity-Backed Aperture Antennas Using Hybrid FEM/MoM Technique

NASA Technical Reports Server (NTRS)

Reddy C. J.

1998-01-01

Model Based Parameter Estimation (MBPE) is presented in conjunction with the hybrid Finite Element Method (FEM)/Method of Moments (MoM) technique for fast computation of the input characteristics of cavity-backed aperture antennas over a frequency range. The hybrid FENI/MoM technique is used to form an integro-partial- differential equation to compute the electric field distribution of a cavity-backed aperture antenna. In MBPE, the electric field is expanded in a rational function of two polynomials. The coefficients of the rational function are obtained using the frequency derivatives of the integro-partial-differential equation formed by the hybrid FEM/ MoM technique. Using the rational function approximation, the electric field is obtained over a frequency range. Using the electric field at different frequencies, the input characteristics of the antenna are obtained over a wide frequency range. Numerical results for an open coaxial line, probe-fed coaxial cavity and cavity-backed microstrip patch antennas are presented. Good agreement between MBPE and the solutions over individual frequencies is observed.

Surface Modifier-Free Organic-Inorganic Hybridization To Produce Optically Transparent and Highly Refractive Bulk Materials Composed of Epoxy Resins and ZrO2 Nanoparticles.

PubMed

Enomoto, Kazushi; Kikuchi, Moriya; Narumi, Atsushi; Kawaguchi, Seigou

2018-04-25

Surface modifier-free hybridization of ZrO 2 nanoparticles (NPs) with epoxy-based polymers is demonstrated for the first time to afford highly transparent and refractive bulk materials. This is achieved by a unique and versatile hybridization via the one-pot direct phase transfer of ZrO 2 NPs from water to epoxy monomers without any aggregation followed by curing with anhydride. Three types of representative epoxy monomers, bisphenol A diglycidyl ether (BADGE), 3,4-epoxycyclohexylmethyl-3',4'-epoxycyclohexane carboxylate (CEL), and 1,3,5-tris(3-(oxiran-2-yl)propyl)-1,3,5-triazinane-2,4,6-trione (TEPIC), are used to produce transparent viscous dispersions. The resulting ZrO 2 NPs are thoroughly characterized using dynamic light scattering (DLS), transmission electron microscopy (TEM), Fourier transform infrared (FT-IR), and solid-state 13 C CP/MAS NMR measurements. The results from DLS and TEM analyses indicate nanodispersion of ZrO 2 into epoxy monomers as a continuous medium. A surface modification mechanism and the binding fashion during phase transfer are proposed based on the FT-IR and solid-state 13 C CP/MAS NMR measurements. Epoxy-based hybrid materials with high transparency and refractive index are successfully fabricated by heat curing or polymerizing a mixture of monomers containing epoxy-functionalized ZrO 2 NPs and methylhexahydrophthalic anhydride in the presence of a phosphoric catalyst. The TEM and small-angle X-ray scattering measurements of the hybrids show a nanodispersion of ZrO 2 in the epoxy networks. The refractive index at 594 nm ( n 594 ) increases up to 1.765 for BADGE-based hybrids, 1.667 for CEL-based hybrids, and 1.693 for TEPIC-based hybrids. Their refractive indices and Abbe's numbers are quantitatively described by the Lorentz-Lorenz effective medium expansion theory. Their transmissivity is also reasonably explained using Fresnel refraction, Rayleigh scattering, and the Lambert-Beer theories. This surface modifier-free hybridization provides a versatile, fascinating, and promising method for synthesizing a variety of epoxy-based hybrid materials.

A Hybrid Maximum Power Point Tracking Method for Automobile Exhaust Thermoelectric Generator

NASA Astrophysics Data System (ADS)

Quan, Rui; Zhou, Wei; Yang, Guangyou; Quan, Shuhai

2017-05-01

To make full use of the maximum output power of automobile exhaust thermoelectric generator (AETEG) based on Bi2Te3 thermoelectric modules (TEMs), taking into account the advantages and disadvantages of existing maximum power point tracking methods, and according to the output characteristics of TEMs, a hybrid maximum power point tracking method combining perturb and observe (P&O) algorithm, quadratic interpolation and constant voltage tracking method was put forward in this paper. Firstly, it searched the maximum power point with P&O algorithms and a quadratic interpolation method, then, it forced the AETEG to work at its maximum power point with constant voltage tracking. A synchronous buck converter and controller were implemented in the electric bus of the AETEG applied in a military sports utility vehicle, and the whole system was modeled and simulated with a MATLAB/Simulink environment. Simulation results demonstrate that the maximum output power of the AETEG based on the proposed hybrid method is increased by about 3.0% and 3.7% compared with that using only the P&O algorithm and the quadratic interpolation method, respectively. The shorter tracking time is only 1.4 s, which is reduced by half compared with that of the P&O algorithm and quadratic interpolation method, respectively. The experimental results demonstrate that the tracked maximum power is approximately equal to the real value using the proposed hybrid method,and it can preferentially deal with the voltage fluctuation of the AETEG with only P&O algorithm, and resolve the issue that its working point can barely be adjusted only with constant voltage tracking when the operation conditions change.

Plasmon-enhanced versatile optical nonlinearities in a Au-Ag-Au multi-segmental hybrid structure.

PubMed

Yao, Lin-Hua; Zhang, Jun-Pei; Dai, Hong-Wei; Wang, Ming-Shan; Zhang, Lu-Man; Wang, Xia; Han, Jun-Bo

2018-06-27

A Au-Ag-Au multi-segmental hybrid structure has been synthesized by using an electrodeposition method based on an anodic aluminum oxide (AAO) membrane. The third-order optical nonlinearities, second harmonic generation (SHG) and photoluminescence (PL) properties containing ultrafast supercontinuum generation and plasmon mediated thermal emission have been investigated. Significant optical enhancements have been obtained near surface plasmon resonance wavelength in all the abovementioned nonlinear processes. Comparative studies between the Au-Ag-Au multi-segmental hybrid structure and the corresponding single-component Au and Ag hybrid structures demonstrate that the Au-Ag-Au multi-segmental hybrid structure has much larger optical nonlinearities than its counterparts. These results demonstrate that the Au-Ag-Au hybrid structure is a promising candidate for applications in plasmonic devices and enhancement substrates.

Modeling level change in Lake Urmia using hybrid artificial intelligence approaches

NASA Astrophysics Data System (ADS)

Esbati, M.; Ahmadieh Khanesar, M.; Shahzadi, Ali

2017-06-01

The investigation of water level fluctuations in lakes for protecting them regarding the importance of these water complexes in national and regional scales has found a special place among countries in recent years. The importance of the prediction of water level balance in Lake Urmia is necessary due to several-meter fluctuations in the last decade which help the prevention from possible future losses. For this purpose, in this paper, the performance of adaptive neuro-fuzzy inference system (ANFIS) for predicting the lake water level balance has been studied. In addition, for the training of the adaptive neuro-fuzzy inference system, particle swarm optimization (PSO) and hybrid backpropagation-recursive least square method algorithm have been used. Moreover, a hybrid method based on particle swarm optimization and recursive least square (PSO-RLS) training algorithm for the training of ANFIS structure is introduced. In order to have a more fare comparison, hybrid particle swarm optimization and gradient descent are also applied. The models have been trained, tested, and validated based on lake level data between 1991 and 2014. For performance evaluation, a comparison is made between these methods. Numerical results obtained show that the proposed methods with a reasonable error have a good performance in water level balance prediction. It is also clear that with continuing the current trend, Lake Urmia will experience more drop in the water level balance in the upcoming years.

Analysis and Assessment of Operation Risk for Hybrid AC/DC Power System based on the Monte Carlo Method

NASA Astrophysics Data System (ADS)

Hu, Xiaojing; Li, Qiang; Zhang, Hao; Guo, Ziming; Zhao, Kun; Li, Xinpeng

2018-06-01

Based on the Monte Carlo method, an improved risk assessment method for hybrid AC/DC power system with VSC station considering the operation status of generators, converter stations, AC lines and DC lines is proposed. According to the sequential AC/DC power flow algorithm, node voltage and line active power are solved, and then the operation risk indices of node voltage over-limit and line active power over-limit are calculated. Finally, an improved two-area IEEE RTS-96 system is taken as a case to analyze and assessment its operation risk. The results show that the proposed model and method can intuitively and directly reflect the weak nodes and weak lines of the system, which can provide some reference for the dispatching department.

Utilizing Intrinsic Properties of Polyaniline to Detect Nucleic Acid Hybridization through UV-Enhanced Electrostatic Interaction.

PubMed

Sengupta, Partha Pratim; Gloria, Jared N; Amato, Dahlia N; Amato, Douglas V; Patton, Derek L; Murali, Beddhu; Flynt, Alex S

2015-10-12

Detection of specific RNA or DNA molecules by hybridization to "probe" nucleic acids via complementary base-pairing is a powerful method for analysis of biological systems. Here we describe a strategy for transducing hybridization events through modulating intrinsic properties of the electroconductive polymer polyaniline (PANI). When DNA-based probes electrostatically interact with PANI, its fluorescence properties are increased, a phenomenon that can be enhanced by UV irradiation. Hybridization of target nucleic acids results in dissociation of probes causing PANI fluorescence to return to basal levels. By monitoring restoration of base PANI fluorescence as little as 10(-11) M (10 pM) of target oligonucleotides could be detected within 15 min of hybridization. Detection of complementary oligos was specific, with introduction of a single mismatch failing to form a target-probe duplex that would dissociate from PANI. Furthermore, this approach is robust and is capable of detecting specific RNAs in extracts from animals. This sensor system improves on previously reported strategies by transducing highly specific probe dissociation events through intrinsic properties of a conducting polymer without the need for additional labels.

Fast Computation of Frequency Response of Cavity-Backed Apertures Using MBPE in Conjunction with Hybrid FEM/MoM Technique

NASA Technical Reports Server (NTRS)

Reddy, C. J.; Deshpande, M. D.; Cockrell, C. R.; Beck, F. B.

2004-01-01

The hybrid Finite Element Method(FEM)/Method of Moments(MoM) technique has become popular over the last few years due to its flexibility to handle arbitrarily shaped objects with complex materials. One of the disadvantages of this technique, however, is the computational cost involved in obtaining solutions over a frequency range as computations are repeated for each frequency. In this paper, the application of Model Based Parameter Estimation (MBPE) method[1] with the hybrid FEM/MoM technique is presented for fast computation of frequency response of cavity-backed apertures[2,3]. In MBPE, the electric field is expanded in a rational function of two polynomials. The coefficients of the rational function are obtained using the frequency-derivatives of the integro-differential equation formed by the hybrid FEM/MoM technique. Using the rational function approximation, the electric field is calculated at different frequencies from which the frequency response is obtained.

A hybrid method in combining treatment effects from matched and unmatched studies.

PubMed

Byun, Jinyoung; Lai, Dejian; Luo, Sheng; Risser, Jan; Tung, Betty; Hardy, Robert J

2013-12-10

The most common data structures in the biomedical studies have been matched or unmatched designs. Data structures resulting from a hybrid of the two may create challenges for statistical inferences. The question may arise whether to use parametric or nonparametric methods on the hybrid data structure. The Early Treatment for Retinopathy of Prematurity study was a multicenter clinical trial sponsored by the National Eye Institute. The design produced data requiring a statistical method of a hybrid nature. An infant in this multicenter randomized clinical trial had high-risk prethreshold retinopathy of prematurity that was eligible for treatment in one or both eyes at entry into the trial. During follow-up, recognition visual acuity was accessed for both eyes. Data from both eyes (matched) and from only one eye (unmatched) were eligible to be used in the trial. The new hybrid nonparametric method is a meta-analysis based on combining the Hodges-Lehmann estimates of treatment effects from the Wilcoxon signed rank and rank sum tests. To compare the new method, we used the classic meta-analysis with the t-test method to combine estimates of treatment effects from the paired and two sample t-tests. We used simulations to calculate the empirical size and power of the test statistics, as well as the bias, mean square and confidence interval width of the corresponding estimators. The proposed method provides an effective tool to evaluate data from clinical trials and similar comparative studies. Copyright © 2013 John Wiley & Sons, Ltd.

Synthesis of porous NiO/CeO2 hybrid nanoflake arrays as a platform for electrochemical biosensing

NASA Astrophysics Data System (ADS)

Cui, Jiewu; Luo, Jinbao; Peng, Bangguo; Zhang, Xinyi; Zhang, Yong; Wang, Yan; Qin, Yongqiang; Zheng, Hongmei; Shu, Xia; Wu, Yucheng

2015-12-01

Porous NiO/CeO2 hybrid nanoflake arrays fabricated by a facile hydrothermal method were employed as substrates for electrochemical biosensors. The resulting NiO/CeO2 hybrid nanoflake arrays with a large specific surface area and good biocompatibility presented an excellent platform for electrochemical biosensing.Porous NiO/CeO2 hybrid nanoflake arrays fabricated by a facile hydrothermal method were employed as substrates for electrochemical biosensors. The resulting NiO/CeO2 hybrid nanoflake arrays with a large specific surface area and good biocompatibility presented an excellent platform for electrochemical biosensing. Electronic supplementary information (ESI) available: Optical photographs of the as-prepared samples, SEM, TEM, EDS, XRD and BET data of the samples are presented, I-t curves of glucose biosensors based on NiO and NiO/CeO2 NFAs, EIS results of different electrodes. See DOI: 10.1039/c5nr05924k

[Hybrid 3-D rendering of the thorax and surface-based virtual bronchoscopy in surgical and interventional therapy control].

PubMed

Seemann, M D; Gebicke, K; Luboldt, W; Albes, J M; Vollmar, J; Schäfer, J F; Beinert, T; Englmeier, K H; Bitzer, M; Claussen, C D

2001-07-01

The aim of this study was to demonstrate the possibilities of a hybrid rendering method, the combination of a color-coded surface and volume rendering method, with the feasibility of performing surface-based virtual endoscopy with different representation models in the operative and interventional therapy control of the chest. In 6 consecutive patients with partial lung resection (n = 2) and lung transplantation (n = 4) a thin-section spiral computed tomography of the chest was performed. The tracheobronchial system and the introduced metallic stents were visualized using a color-coded surface rendering method. The remaining thoracic structures were visualized using a volume rendering method. For virtual bronchoscopy, the tracheobronchial system was visualized using a triangle surface model, a shaded-surface model and a transparent shaded-surface model. The hybrid 3D visualization uses the advantages of both the color-coded surface and volume rendering methods and facilitates a clear representation of the tracheobronchial system and the complex topographical relationship of morphological and pathological changes without loss of diagnostic information. Performing virtual bronchoscopy with the transparent shaded-surface model facilitates a reasonable to optimal, simultaneous visualization and assessment of the surface structure of the tracheobronchial system and the surrounding mediastinal structures and lesions. Hybrid rendering relieve the morphological assessment of anatomical and pathological changes without the need for time-consuming detailed analysis and presentation of source images. Performing virtual bronchoscopy with a transparent shaded-surface model offers a promising alternative to flexible fiberoptic bronchoscopy.

In Situ Synthesis of Metal Nanoparticle Embedded Hybrid Soft Nanomaterials.

PubMed

Divya, Kizhmuri P; Miroshnikov, Mikhail; Dutta, Debjit; Vemula, Praveen Kumar; Ajayan, Pulickel M; John, George

2016-09-20

The allure of integrating the tunable properties of soft nanomaterials with the unique optical and electronic properties of metal nanoparticles has led to the development of organic-inorganic hybrid nanomaterials. A promising method for the synthesis of such organic-inorganic hybrid nanomaterials is afforded by the in situ generation of metal nanoparticles within a host organic template. Due to their tunable surface morphology and porosity, soft organic materials such as gels, liquid crystals, and polymers that are derived from various synthetic or natural compounds can act as templates for the synthesis of metal nanoparticles of different shapes and sizes. This method provides stabilization to the metal nanoparticles by the organic soft material and advantageously precludes the use of external reducing or capping agents in many instances. In this Account, we exemplify the green chemistry approach for synthesizing these materials, both in the choice of gelators as soft material frameworks and in the reduction mechanisms that generate the metal nanoparticles. Established herein is the core design principle centered on conceiving multifaceted amphiphilic soft materials that possess the ability to self-assemble and reduce metal ions into nanoparticles. Furthermore, these soft materials stabilize the in situ generated metal nanoparticles and retain their self-assembly ability to generate metal nanoparticle embedded homogeneous organic-inorganic hybrid materials. We discuss a remarkable example of vegetable-based drying oils as host templates for metal ions, resulting in the synthesis of novel hybrid nanomaterials. The synthesis of metal nanoparticles via polymers and self-assembled materials fabricated via cardanol (a bioorganic monomer derived from cashew nut shell liquid) are also explored in this Account. The organic-inorganic hybrid structures were characterized by several techniques such as UV-visible spectroscopy, scanning electron microscopy (SEM), and transmission electron microscopy (TEM). Utilization of silver nanoparticle-based hybrid nanomaterials as an antimicrobial material is another illustration of the advantage of hybrid nanomaterials. We envision that the results summarized in this Account will help the scientific community to design and develop diverse organic-inorganic hybrid materials using environmentally benign methods and that these materials will yield advanced properties that have multifaceted applications in various research fields.

Simultaneous measurement of cerebral blood flow and mRNA signals: pixel-based inter-modality correlational analysis.

PubMed

Zhao, W; Busto, R; Truettner, J; Ginsberg, M D

2001-07-30

The analysis of pixel-based relationships between local cerebral blood flow (LCBF) and mRNA expression can reveal important insights into brain function. Traditionally, LCBF and in situ hybridization studies for genes of interest have been analyzed in separate series. To overcome this limitation and to increase the power of statistical analysis, this study focused on developing a double-label method to measure local cerebral blood flow (LCBF) and gene expressions simultaneously by means of a dual-autoradiography procedure. A 14C-iodoantipyrine autoradiographic LCBF study was first performed. Serial brain sections (12 in this study) were obtained at multiple coronal levels and were processed in the conventional manner to yield quantitative LCBF images. Two replicate sections at each bregma level were then used for in situ hybridization. To eliminate the 14C-iodoantipyrine from these sections, a chloroform-washout procedure was first performed. The sections were then processed for in situ hybridization autoradiography for the probes of interest. This method was tested in Wistar rats subjected to 12 min of global forebrain ischemia by two-vessel occlusion plus hypotension, followed by 2 or 6 h of reperfusion (n=4-6 per group). LCBF and in situ hybridization images for heat shock protein 70 (HSP70) were generated for each rat, aligned by disparity analysis, and analyzed on a pixel-by-pixel basis. This method yielded detailed inter-modality correlation between LCBF and HSP70 mRNA expressions. The advantages of this method include reducing the number of experimental animals by one-half; and providing accurate pixel-based correlations between different modalities in the same animals, thus enabling paired statistical analyses. This method can be extended to permit correlation of LCBF with the expression of multiple genes of interest.

Horseradish peroxidase-labeled oligonucleotides and fluorescent tyramides for rapid detection of chromosome-specific repeat sequences.

PubMed

van Gijlswijk, R P; Wiegant, J; Vervenne, R; Lasan, R; Tanke, H J; Raap, A K

1996-01-01

We present a sensitive and rapid fluorescence in situ hybridization (FISH) strategy for detecting chromosome-specific repeat sequences. It uses horseradish peroxidase (HRP)-labeled oligonucleotide sequences in combination with fluorescent tyramide-based detection. After in situ hybridization, the HRP conjugated to the oligonucleotide probe is used to deposit fluorescently labeled tyramide molecules at the site of hybridization. The method features full chemical synthesis of probes, strong FISH signals, and short processing periods, as well as multicolor capabilities.

Development of a DNA-Based Method for Distinguishing the Malaria Vectors, Anopheles Gambiae from Anopheles Arabiensis.

DTIC Science & Technology

1987-11-15

analysis. However, in our preliminary studies, hybridization with the DPro.5ohil actin probe required such low stringency conditions that the signal to...rDNA genes and could therefore contain seOuencec tjhich, under normal DNA hybridization conditions , behave in a species-specific mrnner. We theref’-e...pAGr23B) behave as species-specific probes under the conditions normally used for DNA hybridization. These sequences could be used to design specific

Construction of optical glucose nanobiosensor with high sensitivity and selectivity at physiological pH on the basis of organic-inorganic hybrid microgels.

PubMed

Wu, Weitai; Zhou, Ting; Aiello, Michael; Zhou, Shuiqin

2010-08-15

A new class of optical glucose nanobiosensors with high sensitivity and selectivity at physiological pH is described. To construct these glucose nanobiosensors, the fluorescent CdS quantum dots (QDs), serving as the optical code, were incorporated into the glucose-sensitive poly(N-isopropylacrylamide-acrylamide-2-acrylamidomethyl-5-fluorophenylboronic acid) copolymer microgels, via both in situ growth method and "breathing in" method, respectively. The polymeric gel can adapt to surrounding glucose concentrations, and regulate the fluorescence of the embedded QDs, converting biochemical signals into optical signals. The gradual swelling of the gel would lead to the quenching of the fluorescence at the elevated glucose concentrations. The hybrid microgels displayed high selectivity to glucose over the potential primary interferents of lactate and human serum albumin in the physiologically important glucose concentration range. The stability, reversibility, and sensitivity of the organic-inorganic hybrid microgel-based biosensors were also systematically studied. These general properties of our nanobiosensors are well tunable under appropriate tailor on the hybrid microgels, in particular, simply through the change in the crosslinking degree of the microgels. The optical glucose nanobiosensors based on the organic-inorganic hybrid microgels have shown the potential for a third generation fluorescent biosensor. Copyright 2010 Elsevier B.V. All rights reserved.

Hybrid stochastic simulation of reaction-diffusion systems with slow and fast dynamics.

PubMed

Strehl, Robert; Ilie, Silvana

2015-12-21

In this paper, we present a novel hybrid method to simulate discrete stochastic reaction-diffusion models arising in biochemical signaling pathways. We study moderately stiff systems, for which we can partition each reaction or diffusion channel into either a slow or fast subset, based on its propensity. Numerical approaches missing this distinction are often limited with respect to computational run time or approximation quality. We design an approximate scheme that remedies these pitfalls by using a new blending strategy of the well-established inhomogeneous stochastic simulation algorithm and the tau-leaping simulation method. The advantages of our hybrid simulation algorithm are demonstrated on three benchmarking systems, with special focus on approximation accuracy and efficiency.

An Application of CFD to Guide Forced Boundary-Layer Transition for Low-Speed Tests of a Hybrid Wing-Body Configuration

NASA Technical Reports Server (NTRS)

Luckring, James M.; Deere, Karen A.; Childs, Robert E.; Stremel, Paul M.; Long, Kurtis R.

2016-01-01

A hybrid transition trip-dot sizing and placement test technique was developed in support of recent experimental research on a hybrid wing-body configuration under study for the NASA Environmentally Responsible Aviation project. The approach combines traditional methods with Computational Fluid Dynamics. The application had three-dimensional boundary layers that were simulated with either fully turbulent or transitional flow models using established Reynolds-Averaged Navier-Stokes methods. Trip strip effectiveness was verified experimentally using infrared thermography during a low-speed wind tunnel test. Although the work was performed on one specific configuration, the process was based on fundamental flow physics and could be applicable to other configurations.

Very-short-term wind power prediction by a hybrid model with single- and multi-step approaches

NASA Astrophysics Data System (ADS)

Mohammed, E.; Wang, S.; Yu, J.

2017-05-01

Very-short-term wind power prediction (VSTWPP) has played an essential role for the operation of electric power systems. This paper aims at improving and applying a hybrid method of VSTWPP based on historical data. The hybrid method is combined by multiple linear regressions and least square (MLR&LS), which is intended for reducing prediction errors. The predicted values are obtained through two sub-processes:1) transform the time-series data of actual wind power into the power ratio, and then predict the power ratio;2) use the predicted power ratio to predict the wind power. Besides, the proposed method can include two prediction approaches: single-step prediction (SSP) and multi-step prediction (MSP). WPP is tested comparatively by auto-regressive moving average (ARMA) model from the predicted values and errors. The validity of the proposed hybrid method is confirmed in terms of error analysis by using probability density function (PDF), mean absolute percent error (MAPE) and means square error (MSE). Meanwhile, comparison of the correlation coefficients between the actual values and the predicted values for different prediction times and window has confirmed that MSP approach by using the hybrid model is the most accurate while comparing to SSP approach and ARMA. The MLR&LS is accurate and promising for solving problems in WPP.

Diversity in Genetic In Vivo Methods for Protein-Protein Interaction Studies: from the Yeast Two-Hybrid System to the Mammalian Split-Luciferase System

PubMed Central

Stynen, Bram; Tournu, Hélène; Tavernier, Jan

2012-01-01

Summary: The yeast two-hybrid system pioneered the field of in vivo protein-protein interaction methods and undisputedly gave rise to a palette of ingenious techniques that are constantly pushing further the limits of the original method. Sensitivity and selectivity have improved because of various technical tricks and experimental designs. Here we present an exhaustive overview of the genetic approaches available to study in vivo binary protein interactions, based on two-hybrid and protein fragment complementation assays. These methods have been engineered and employed successfully in microorganisms such as Saccharomyces cerevisiae and Escherichia coli, but also in higher eukaryotes. From single binary pairwise interactions to whole-genome interactome mapping, the self-reassembly concept has been employed widely. Innovative studies report the use of proteins such as ubiquitin, dihydrofolate reductase, and adenylate cyclase as reconstituted reporters. Protein fragment complementation assays have extended the possibilities in protein-protein interaction studies, with technologies that enable spatial and temporal analyses of protein complexes. In addition, one-hybrid and three-hybrid systems have broadened the types of interactions that can be studied and the findings that can be obtained. Applications of these technologies are discussed, together with the advantages and limitations of the available assays. PMID:22688816

Analysis of the solar/wind resources in Southern Spain for optimal sizing of hybrid solar-wind power generation systems

NASA Astrophysics Data System (ADS)

Quesada-Ruiz, S.; Pozo-Vazquez, D.; Santos-Alamillos, F. J.; Lara-Fanego, V.; Ruiz-Arias, J. A.; Tovar-Pescador, J.

2010-09-01

A drawback common to the solar and wind energy systems is their unpredictable nature and dependence on weather and climate on a wide range of time scales. In addition, the variation of the energy output may not match with the time distribution of the load demand. This can partially be solved by the use of batteries for energy storage in stand-alone systems. The problem caused by the variable nature of the solar and wind resources can be partially overcome by the use of energy systems that uses both renewable resources in a combined manner, that is, hybrid wind-solar systems. Since both resources can show complementary characteristics in certain location, the independent use of solar or wind systems results in considerable over sizing of the batteries system compared to the use of hybrid solar-wind systems. Nevertheless, to the day, there is no single recognized method for properly sizing these hybrid wind-solar systems. In this work, we present a method for sizing wind-solar hybrid systems in southern Spain. The method is based on the analysis of the wind and solar resources on daily scale, particularly, its temporal complementary characteristics. The method aims to minimize the size of the energy storage systems, trying to provide the most reliable supply.

Orthogonal test design for optimization of synthesis of MTX/LDHs hybrids by ion-exchange method

NASA Astrophysics Data System (ADS)

Liu, Su-Qing; Dai, Chao-Fan; Wang, Lin; Li, Shu-Ping; Li, Xiao-Dong

2015-04-01

Based on orthogonal test design, the factors influencing the synthesis of methotrexate intercalated magnesium-aluminum layered double hydroxides (MTX/LDHs for short) by ion-exchange method, such as weight ratio of pristine LDHs to MTX (R for short), exchange temperature, time and pH value were investigated. Of the four controllable independent variables, R had the strongest effect on the crystallinity and the drug-loading capacity and the optimum synthesis conditions considered from the crystallinity and the drug-loading capacity both pointed to the same values, i.e., R=2:1, pH=9.5, temperature of 80 °C and exchange time of 3 day. The XRD diffractions indicated that high MTX content was in favor of the formation of intercalated hybrids, while low content lead to the failure of it. TEM photos indicated that the intercalated hybrids all exhibited aggregated hexagonal plates. In order to improve the morphology, two different states of pristine LDHs, i.e., powder and colloid, were chosen to prepare MTX/LDHs hybrids and the results indicated that colloid state of pristine was advantageous to obtain regular particles. The study also revealed that the properties of hybrids obtained at optimum conditions by ion-exchange were superior to that obtained from standard methods, such as co-precipitation method.

A hybrid approach for efficient anomaly detection using metaheuristic methods

PubMed Central

Ghanem, Tamer F.; Elkilani, Wail S.; Abdul-kader, Hatem M.

2014-01-01

Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms. PMID:26199752

A hybrid approach for efficient anomaly detection using metaheuristic methods.

PubMed

Ghanem, Tamer F; Elkilani, Wail S; Abdul-Kader, Hatem M

2015-07-01

Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms.

Sensitive DNA detection and SNP discrimination using ultrabright SERS nanorattles and magnetic beads for malaria diagnostics.

PubMed

Ngo, Hoan T; Gandra, Naveen; Fales, Andrew M; Taylor, Steve M; Vo-Dinh, Tuan

2016-07-15

One of the major obstacles to implement nucleic acid-based molecular diagnostics at the point-of-care (POC) and in resource-limited settings is the lack of sensitive and practical DNA detection methods that can be seamlessly integrated into portable platforms. Herein we present a sensitive yet simple DNA detection method using a surface-enhanced Raman scattering (SERS) nanoplatform: the ultrabright SERS nanorattle. The method, referred to as the nanorattle-based method, involves sandwich hybridization of magnetic beads that are loaded with capture probes, target sequences, and ultrabright SERS nanorattles that are loaded with reporter probes. Upon hybridization, a magnet was applied to concentrate the hybridization sandwiches at a detection spot for SERS measurements. The ultrabright SERS nanorattles, composed of a core and a shell with resonance Raman reporters loaded in the gap space between the core and the shell, serve as SERS tags for signal detection. Using this method, a specific DNA sequence of the malaria parasite Plasmodium falciparum could be detected with a detection limit of approximately 100 attomoles. Single nucleotide polymorphism (SNP) discrimination of wild type malaria DNA and mutant malaria DNA, which confers resistance to artemisinin drugs, was also demonstrated. These test models demonstrate the molecular diagnostic potential of the nanorattle-based method to both detect and genotype infectious pathogens. Furthermore, the method's simplicity makes it a suitable candidate for integration into portable platforms for POC and in resource-limited settings applications. Copyright © 2016. Published by Elsevier B.V.

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

Miyasaka, Y; Kadoya, N; Ito, K

Purpose: Accurate deformable image registration (DIR) between external beam radiotherapy (EBRT) and HDR brachytherapy (BT) CT images in cervical cancer is challenging. DSC has been evaluated only on the basis of the consistency of the structure, and its use does not guarantee an anatomically reasonable deformation. We evaluate the DIR accuracy for cervical cancer with DSC and anatomical landmarks using a 3D-printed pelvis phantom. Methods: A 3D-printed, deformable female pelvis phantom was created on the basis of the patient’s CT image. Urethane and silicon were used as materials for creating the uterus and bladder, respectively, in the phantom. We performedmore » DIR in two cases: case-A with a full bladder (170 ml) in both the EBRT and BT images and case-B with a full bladder in the BT image and a half bladder (100 ml) in the EBRT image. DIR was evaluated using DSCs and 70 uterus and bladder landmarks. A Hybrid intensity and structure DIR algorithm with two settings (RayStation) was used. Results: In the case-A, DSCs of the intensity-based DIR were 0.93 and 0.85 for the bladder and uterus, respectively, whereas those of hybrid-DIR were 0.98 and 0.96, respectively. The mean landmark error values of intensity-based DIR were 0.73±0.29 and 1.70±0.19 cm for the bladder and uterus, respectively, whereas those of Hybrid-DIR were 0.43±0.33 and 1.23±0.25 cm, respectively. In both cases, the Hybrid-DIR accuracy was better than the intensity-based DIR accuracy for both evaluation methods. However, for several bladder landmarks, the Hybrid-DIR landmark errors were larger than the corresponding intensity-based DIR errors (e.g., 2.26 vs 1.25 cm). Conclusion: Our results demonstrate that Hybrid-DIR can perform with a better accuracy than the intensity-based DIR for both DSC and landmark errors; however, Hybrid-DIR shows a larger landmark error for some landmarks because the technique focuses on both the structure and intensity.« less

Heat engine and electric motor torque distribution strategy for a hybrid electric vehicle

DOEpatents

Boberg, Evan S.; Gebby, Brian P.

1999-09-28

A method is provided for controlling a power train system for a hybrid electric vehicle. The method includes a torque distribution strategy for controlling the engine and the electric motor. The engine and motor commands are determined based upon the accelerator position, the battery state of charge and the amount of engine and motor torque available. The amount of torque requested for the engine is restricted by a limited rate of rise in order to reduce the emissions from the engine. The limited engine torque is supplemented by motor torque in order to meet a torque request determined based upon the accelerator position.

Colorimetric Detection of Ehrlichia Canis via Nucleic Acid Hybridization in Gold Nano-Colloids

PubMed Central

Muangchuen, Ajima; Chaumpluk, Piyasak; Suriyasomboon, Annop; Ekgasit, Sanong

2014-01-01

Canine monocytic ehrlichiosis (CME) is a major thick-bone disease of dog caused by Ehrlichia canis. Detection of this causal agent outside the laboratory using conventional methods is not effective enough. Thus an assay for E. canis detection based on the p30 outer membrane protein gene was developed. It was based on the p30 gene amplification using loop-mediated isothermal DNA amplification (LAMP). The primer set specific to six areas within the target gene were designed and tested for their sensitivity and specificity. Detection of DNA signals was based on modulation of gold nanoparticles' surface properties and performing DNA/DNA hybridization using an oligonucleotide probe. Presence of target DNA affected the gold colloid nanoparticles in terms of particle aggregation with a plasmonic color change of the gold colloids from ruby red to purple, visible by the naked eye. All the assay steps were completed within 90 min including DNA extraction without relying on standard laboratory facilities. This method was very specific to target bacteria. Its sensitivity with probe hybridization was sufficient to detect 50 copies of target DNA. This method should provide an alternative choice for point of care control and management of the disease. PMID:25111239

Colorimetric detection of Ehrlichia canis via nucleic acid hybridization in gold nano-colloids.

PubMed

Muangchuen, Ajima; Chaumpluk, Piyasak; Suriyasomboon, Annop; Ekgasit, Sanong

2014-08-08

Canine monocytic ehrlichiosis (CME) is a major thick-bone disease of dog caused by Ehrlichia canis. Detection of this causal agent outside the laboratory using conventional methods is not effective enough. Thus an assay for E. canis detection based on the p30 outer membrane protein gene was developed. It was based on the p30 gene amplification using loop-mediated isothermal DNA amplification (LAMP). The primer set specific to six areas within the target gene were designed and tested for their sensitivity and specificity. Detection of DNA signals was based on modulation of gold nanoparticles' surface properties and performing DNA/DNA hybridization using an oligonucleotide probe. Presence of target DNA affected the gold colloid nanoparticles in terms of particle aggregation with a plasmonic color change of the gold colloids from ruby red to purple, visible by the naked eye. All the assay steps were completed within 90 min including DNA extraction without relying on standard laboratory facilities. This method was very specific to target bacteria. Its sensitivity with probe hybridization was sufficient to detect 50 copies of target DNA. This method should provide an alternative choice for point of care control and management of the disease.

Hybrid Power Management for Office Equipment

NASA Astrophysics Data System (ADS)

Gingade, Ganesh P.

Office machines (such as printers, scanners, fax, and copiers) can consume significant amounts of power. Few studies have been devoted to power management of office equipment. Most office machines have sleep modes to save power. Power management of these machines are usually timeout-based: a machine sleeps after being idle long enough. Setting the timeout duration can be difficult: if it is too long, the machine wastes power during idleness. If it is too short, the machine sleeps too soon and too often--the wakeup delay can significantly degrade productivity. Thus, power management is a tradeoff between saving energy and keeping short response time. Many power management policies have been published and one policy may outperform another in some scenarios. There is no definite conclusion which policy is always better. This thesis describes two methods for office equipment power management. The first method adaptively reduces power based on a constraint of the wakeup delay. The second method is a hybrid with multiple candidate policies and it selects the most appropriate power management policy. Using six months of request traces from 18 different offices, we demonstrate that the hybrid policy outperforms individual policies. We also discover that power management based on business hours does not produce consistent energy savings.

3D magnetospheric parallel hybrid multi-grid method applied to planet–plasma interactions

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

Leclercq, L., E-mail: ludivine.leclercq@latmos.ipsl.fr; Modolo, R., E-mail: ronan.modolo@latmos.ipsl.fr; Leblanc, F.

2016-03-15

We present a new method to exploit multiple refinement levels within a 3D parallel hybrid model, developed to study planet–plasma interactions. This model is based on the hybrid formalism: ions are kinetically treated whereas electrons are considered as a inertia-less fluid. Generally, ions are represented by numerical particles whose size equals the volume of the cells. Particles that leave a coarse grid subsequently entering a refined region are split into particles whose volume corresponds to the volume of the refined cells. The number of refined particles created from a coarse particle depends on the grid refinement rate. In order tomore » conserve velocity distribution functions and to avoid calculations of average velocities, particles are not coalesced. Moreover, to ensure the constancy of particles' shape function sizes, the hybrid method is adapted to allow refined particles to move within a coarse region. Another innovation of this approach is the method developed to compute grid moments at interfaces between two refinement levels. Indeed, the hybrid method is adapted to accurately account for the special grid structure at the interfaces, avoiding any overlapping grid considerations. Some fundamental test runs were performed to validate our approach (e.g. quiet plasma flow, Alfven wave propagation). Lastly, we also show a planetary application of the model, simulating the interaction between Jupiter's moon Ganymede and the Jovian plasma.« less

Effect of Manufacturing Method to Tensile Properties of Hybrid Composite Reinforced by Natural (Agel Leaf Fiber) and Glass Fibers

NASA Astrophysics Data System (ADS)

Nugroho, A.; Abdurohman, K.; Kusmono; Hestiawan, H.; Jamasri

2018-04-01

This paper described the effect of different type of manufacturing method to tensile properties of hybrid composite woven agel leaf fiber and glass fiber as an alternative of LSU structure material. The research was done by using 3 ply of woven agel leaf fiber (ALF) and 3 ply of glass fiber (wr200) while the matrix was using unsaturated polyester. Composite manufacturing method used hand lay-up and vacuum bagging. Tensile test conducted with Tensilon universal testing machine, specimen shape and size according to standard size ASTM D 638. Based on tensile test result showed that the tensile strength of agel leaf fiber composite with unsaturated polyester matrix is 54.5 MPa by hand lay-up and 84.6 MPa with vacuum bagging method. From result of tensile test, hybrid fiber agel composite and glass fiber with unsaturated polyester matrix have potential as LSU structure.

Hybrid detection of lung nodules on CT scan images

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

Lu, Lin; Tan, Yongqiang; Schwartz, Lawrence H.

Purpose: The diversity of lung nodules poses difficulty for the current computer-aided diagnostic (CAD) schemes for lung nodule detection on computed tomography (CT) scan images, especially in large-scale CT screening studies. We proposed a novel CAD scheme based on a hybrid method to address the challenges of detection in diverse lung nodules. Methods: The hybrid method proposed in this paper integrates several existing and widely used algorithms in the field of nodule detection, including morphological operation, dot-enhancement based on Hessian matrix, fuzzy connectedness segmentation, local density maximum algorithm, geodesic distance map, and regression tree classification. All of the adopted algorithmsmore » were organized into tree structures with multi-nodes. Each node in the tree structure aimed to deal with one type of lung nodule. Results: The method has been evaluated on 294 CT scans from the Lung Image Database Consortium (LIDC) dataset. The CT scans were randomly divided into two independent subsets: a training set (196 scans) and a test set (98 scans). In total, the 294 CT scans contained 631 lung nodules, which were annotated by at least two radiologists participating in the LIDC project. The sensitivity and false positive per scan for the training set were 87% and 2.61%. The sensitivity and false positive per scan for the testing set were 85.2% and 3.13%. Conclusions: The proposed hybrid method yielded high performance on the evaluation dataset and exhibits advantages over existing CAD schemes. We believe that the present method would be useful for a wide variety of CT imaging protocols used in both routine diagnosis and screening studies.« less

Study on Multi-stage Logistics System Design Problem with Inventory Considering Demand Change by Hybrid Genetic Algorithm

NASA Astrophysics Data System (ADS)

Inoue, Hisaki; Gen, Mitsuo

The logistics model used in this study is 3-stage model employed by an automobile company, which aims to solve traffic problems at a total minimum cost. Recently, research on the metaheuristics method has advanced as an approximate means for solving optimization problems like this model. These problems can be solved using various methods such as the genetic algorithm (GA), simulated annealing, and tabu search. GA is superior in robustness and adjustability toward a change in the structure of these problems. However, GA has a disadvantage in that it has a slightly inefficient search performance because it carries out a multi-point search. A hybrid GA that combines another method is attracting considerable attention since it can compensate for a fault to a partial solution that early convergence gives a bad influence on a result. In this study, we propose a novel hybrid random key-based GA(h-rkGA) that combines local search and parameter tuning of crossover rate and mutation rate; h-rkGA is an improved version of the random key-based GA (rk-GA). We attempted comparative experiments with spanning tree-based GA, priority based GA and random key-based GA. Further, we attempted comparative experiments with “h-GA by only local search” and “h-GA by only parameter tuning”. We reported the effectiveness of the proposed method on the basis of the results of these experiments.

Luminescence resonance energy transfer-based nucleic acid hybridization assay on cellulose paper with upconverting phosphor as donors.

PubMed

Zhou, Feng; Noor, M Omair; Krull, Ulrich J

2014-03-04

A bioassay based on DNA hybridization on cellulose paper is a promising format for gene fragment detection that may be suited for in-field and rapid diagnostic applications. We demonstrate for the first time that luminescence resonance energy transfer (LRET) associated with upconverting phosphors (UCPs) can be used to develop a paper-based DNA hybridization assay with high sensitivity, selectivity and fast response. UCPs with strong green emission were synthesized and subsequently functionalized with streptavidin (UCP-strep). UCP-strep particles were immobilized on cellulose paper, and then biotinylated single-stranded oligonucleotide probes were conjugated onto the UCPs via streptavidin-biotin linkage. The UCPs served as donors that were LRET-paired with Cy3-labeled target DNA. Selective DNA hybridization enabled the proximity required for LRET-sensitized emission from Cy3, which was used as the detection signal. Hybridization was complete within 2 min, and the limit of detection of the method was 34 fmol, which is a significant improvement in comparison to an analogous fluorescence resonance energy transfer (FRET) assay based on quantum dots. The assay exhibited excellent resistance to nonspecific adsorption of noncomplementary short/long DNA and protein. The selectivity of the assay was further evaluated by one base pair mismatched (1BPM) DNA detection, where a maximum signal ratio of 3.1:1 was achieved between fully complementary and 1BPM samples. This work represents a preliminary but significant step for the development of paper-based UCP-LRET nucleic acid hybridization assays, which offer potential for lowering the limit of detection of luminescent hybridization assays due to the negligible background signal associated with optical excitation by near-infrared (NIR) light.

Efficient 3D porous microstructure reconstruction via Gaussian random field and hybrid optimization.

PubMed

Jiang, Z; Chen, W; Burkhart, C

2013-11-01

Obtaining an accurate three-dimensional (3D) structure of a porous microstructure is important for assessing the material properties based on finite element analysis. Whereas directly obtaining 3D images of the microstructure is impractical under many circumstances, two sets of methods have been developed in literature to generate (reconstruct) 3D microstructure from its 2D images: one characterizes the microstructure based on certain statistical descriptors, typically two-point correlation function and cluster correlation function, and then performs an optimization process to build a 3D structure that matches those statistical descriptors; the other method models the microstructure using stochastic models like a Gaussian random field and generates a 3D structure directly from the function. The former obtains a relatively accurate 3D microstructure, but computationally the optimization process can be very intensive, especially for problems with large image size; the latter generates a 3D microstructure quickly but sacrifices the accuracy due to issues in numerical implementations. A hybrid optimization approach of modelling the 3D porous microstructure of random isotropic two-phase materials is proposed in this paper, which combines the two sets of methods and hence maintains the accuracy of the correlation-based method with improved efficiency. The proposed technique is verified for 3D reconstructions based on silica polymer composite images with different volume fractions. A comparison of the reconstructed microstructures and the optimization histories for both the original correlation-based method and our hybrid approach demonstrates the improved efficiency of the approach. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

A study on optimization of hybrid drive train using Advanced Vehicle Simulator (ADVISOR)

NASA Astrophysics Data System (ADS)

Same, Adam; Stipe, Alex; Grossman, David; Park, Jae Wan

This study investigates the advantages and disadvantages of three hybrid drive train configurations: series, parallel, and "through-the-ground" parallel. Power flow simulations are conducted with the MATLAB/Simulink-based software ADVISOR. These simulations are then applied in an application for the UC Davis SAE Formula Hybrid vehicle. ADVISOR performs simulation calculations for vehicle position using a combined backward/forward method. These simulations are used to study how efficiency and agility are affected by the motor, fuel converter, and hybrid configuration. Three different vehicle models are developed to optimize the drive train of a vehicle for three stages of the SAE Formula Hybrid competition: autocross, endurance, and acceleration. Input cycles are created based on rough estimates of track geometry. The output from these ADVISOR simulations is a series of plots of velocity profile and energy storage State of Charge that provide a good estimate of how the Formula Hybrid vehicle will perform on the given course. The most noticeable discrepancy between the input cycle and the actual velocity profile of the vehicle occurs during deceleration. A weighted ranking system is developed to organize the simulation results and to determine the best drive train configuration for the Formula Hybrid vehicle. Results show that the through-the-ground parallel configuration with front-mounted motors achieves an optimal balance of efficiency, simplicity, and cost. ADVISOR is proven to be a useful tool for vehicle power train design for the SAE Formula Hybrid competition. This vehicle model based on ADVISOR simulation is applicable to various studies concerning performance and efficiency of hybrid drive trains.

Heterogeneous Catalysis of Polyoxometalate Based Organic–Inorganic Hybrids

PubMed Central

Ren, Yuanhang; Wang, Meiyin; Chen, Xueying; Yue, Bin; He, Heyong

2015-01-01

Organic–inorganic hybrid polyoxometalate (POM) compounds are a subset of materials with unique structures and physical/chemical properties. The combination of metal-organic coordination complexes with classical POMs not only provides a powerful way to gain multifarious new compounds but also affords a new method to modify and functionalize POMs. In parallel with the many reports on the synthesis and structure of new hybrid POM compounds, the application of these compounds for heterogeneous catalysis has also attracted considerable attention. The hybrid POM compounds show noteworthy catalytic performance in acid, oxidation, and even in asymmetric catalytic reactions. This review summarizes the design and synthesis of organic–inorganic hybrid POM compounds and particularly highlights their recent progress in heterogeneous catalysis. PMID:28788017

Polymerase chain reaction-hybridization method using urease gene sequences for high-throughput Ureaplasma urealyticum and Ureaplasma parvum detection and differentiation.

PubMed

Xu, Chen; Zhang, Nan; Huo, Qianyu; Chen, Minghui; Wang, Rengfeng; Liu, Zhili; Li, Xue; Liu, Yunde; Bao, Huijing

2016-04-15

In this article, we discuss the polymerase chain reaction (PCR)-hybridization assay that we developed for high-throughput simultaneous detection and differentiation of Ureaplasma urealyticum and Ureaplasma parvum using one set of primers and two specific DNA probes based on urease gene nucleotide sequence differences. First, U. urealyticum and U. parvum DNA samples were specifically amplified using one set of biotin-labeled primers. Furthermore, amine-modified DNA probes, which can specifically react with U. urealyticum or U. parvum DNA, were covalently immobilized to a DNA-BIND plate surface. The plate was then incubated with the PCR products to facilitate sequence-specific DNA binding. Horseradish peroxidase-streptavidin conjugation and a colorimetric assay were used. Based on the results, the PCR-hybridization assay we developed can specifically differentiate U. urealyticum and U. parvum with high sensitivity (95%) compared with cultivation (72.5%). Hence, this study demonstrates a new method for high-throughput simultaneous differentiation and detection of U. urealyticum and U. parvum with high sensitivity. Based on these observations, the PCR-hybridization assay developed in this study is ideal for detecting and discriminating U. urealyticum and U. parvum in clinical applications. Copyright © 2016 Elsevier Inc. All rights reserved.

Face recognition system using multiple face model of hybrid Fourier feature under uncontrolled illumination variation.

PubMed

Hwang, Wonjun; Wang, Haitao; Kim, Hyunwoo; Kee, Seok-Cheol; Kim, Junmo

2011-04-01

The authors present a robust face recognition system for large-scale data sets taken under uncontrolled illumination variations. The proposed face recognition system consists of a novel illumination-insensitive preprocessing method, a hybrid Fourier-based facial feature extraction, and a score fusion scheme. First, in the preprocessing stage, a face image is transformed into an illumination-insensitive image, called an "integral normalized gradient image," by normalizing and integrating the smoothed gradients of a facial image. Then, for feature extraction of complementary classifiers, multiple face models based upon hybrid Fourier features are applied. The hybrid Fourier features are extracted from different Fourier domains in different frequency bandwidths, and then each feature is individually classified by linear discriminant analysis. In addition, multiple face models are generated by plural normalized face images that have different eye distances. Finally, to combine scores from multiple complementary classifiers, a log likelihood ratio-based score fusion scheme is applied. The proposed system using the face recognition grand challenge (FRGC) experimental protocols is evaluated; FRGC is a large available data set. Experimental results on the FRGC version 2.0 data sets have shown that the proposed method shows an average of 81.49% verification rate on 2-D face images under various environmental variations such as illumination changes, expression changes, and time elapses.

Skull defect reconstruction based on a new hybrid level set.

PubMed

Zhang, Ziqun; Zhang, Ran; Song, Zhijian

2014-01-01

Skull defect reconstruction is an important aspect of surgical repair. Historically, a skull defect prosthesis was created by the mirroring technique, surface fitting, or formed templates. These methods are not based on the anatomy of the individual patient's skull, and therefore, the prosthesis cannot precisely correct the defect. This study presented a new hybrid level set model, taking into account both the global optimization region information and the local accuracy edge information, while avoiding re-initialization during the evolution of the level set function. Based on the new method, a skull defect was reconstructed, and the skull prosthesis was produced by rapid prototyping technology. This resulted in a skull defect prosthesis that well matched the skull defect with excellent individual adaptation.

Teachers and Students' Perceptions of a Hybrid Sport Education and Teaching for Personal and Social Responsibility Learning Unit

ERIC Educational Resources Information Center

Fernandez-Rio, Javier; Menendez-Santurio, Jose Ignacio

2017-01-01

Purpose: The purpose of this study was to assess students and teachers' perceptions concerning their participation in an educational kickboxing learning unit based on a hybridization of two pedagogical models: Sport Education and Teaching for Personal and Social Responsibility. Method: Seventy-one students and three physical education teachers…

Hybrid Fourier pseudospectral/discontinuous Galerkin time-domain method for wave propagation

NASA Astrophysics Data System (ADS)

Pagán Muñoz, Raúl; Hornikx, Maarten

2017-11-01

The Fourier Pseudospectral time-domain (Fourier PSTD) method was shown to be an efficient way of modelling acoustic propagation problems as described by the linearized Euler equations (LEE), but is limited to real-valued frequency independent boundary conditions and predominantly staircase-like boundary shapes. This paper presents a hybrid approach to solve the LEE, coupling Fourier PSTD with a nodal Discontinuous Galerkin (DG) method. DG exhibits almost no restrictions with respect to geometrical complexity or boundary conditions. The aim of this novel method is to allow the computation of complex geometries and to be a step towards the implementation of frequency dependent boundary conditions by using the benefits of DG at the boundaries, while keeping the efficient Fourier PSTD in the bulk of the domain. The hybridization approach is based on conformal meshes to avoid spatial interpolation of the DG solutions when transferring values from DG to Fourier PSTD, while the data transfer from Fourier PSTD to DG is done utilizing spectral interpolation of the Fourier PSTD solutions. The accuracy of the hybrid approach is presented for one- and two-dimensional acoustic problems and the main sources of error are investigated. It is concluded that the hybrid methodology does not introduce significant errors compared to the Fourier PSTD stand-alone solver. An example of a cylinder scattering problem is presented and accurate results have been obtained when using the proposed approach. Finally, no instabilities were found during long-time calculation using the current hybrid methodology on a two-dimensional domain.

Novel RNA hybridization method for the in situ detection of ETV1, ETV4, and ETV5 gene fusions in prostate cancer.

PubMed

Kunju, Lakshmi P; Carskadon, Shannon; Siddiqui, Javed; Tomlins, Scott A; Chinnaiyan, Arul M; Palanisamy, Nallasivam

2014-09-01

The genetic basis of 50% to 60% of prostate cancer (PCa) is attributable to rearrangements in E26 transformation-specific (ETS) (ERG, ETV1, ETV4, and ETV5), BRAF, and RAF1 genes and overexpression of SPINK1. The development and validation of reliable detection methods are warranted to classify various molecular subtypes of PCa for diagnostic and prognostic purposes. ETS gene rearrangements are typically detected by fluorescence in situ hybridization and reverse-transcription polymerase chain reaction methods. Recently, monoclonal antibodies against ERG have been developed that detect the truncated ERG protein in immunohistochemical assays where staining levels are strongly correlated with ERG rearrangement status by fluorescence in situ hybridization. However, specific antibodies for ETV1, ETV4, and ETV5 are unavailable, challenging their clinical use. We developed a novel RNA in situ hybridization-based assay for the in situ detection of ETV1, ETV4, and ETV5 in formalin-fixed paraffin-embedded tissues from prostate needle biopsies, prostatectomy, and metastatic PCa specimens using RNA probes. Further, with combined RNA in situ hybridization and immunohistochemistry we identified a rare subset of PCa with dual ETS gene rearrangements in collisions of independent tumor foci. The high specificity and sensitivity of RNA in situ hybridization provides an alternate method enabling bright-field in situ detection of ETS gene aberrations in routine clinically available PCa specimens.

Homogenous assay for protein detection based on proximity DNA hybridization and isothermal circular strand displacement amplification reaction.

PubMed

Zhang, Manjun; Li, Ruimin; Ling, Liansheng

2017-06-01

This work proposed a homogenous fluorescence assay for proteins, based on the target-triggered proximity DNA hybridization in combination with strand displacement amplification (SDA). It benefited from target-triggered proximity DNA hybridization to specifically recognize the target and SDA making recycling signal amplification. The system included a molecular beacon (MB), an extended probe (EP), and an assistant probe (AP), which were not self-assembly in the absence of target proteins, due to the short length of the designed complementary sequence among MB, EP, and AP. Upon addition of the target proteins, EP and AP are bound to the target proteins, which induced the occurrence of proximity hybridization between MB, EP, and AP and followed by strand displacement amplification. Through the primer extension, a tripartite complex of probes and target was displaced and recycled to hybridize with another MB, and the more opened MB enabled the detection signal to amplify. Under optimum conditions, it was used for the detection of streptavidin and thrombin. Fluorescence intensity was proportional to the concentration of streptavidin and thrombin in the range of 0.2-30 and 0.2-35 nmol/L, respectively. Furthermore, this fluorescent method has a good selectivity, in which the fluorescence intensity of thrombin was ~37-fold or even larger than that of the other proteins at the same concentration. It is a new and simple method for SDA-involved target protein detection and possesses a great potential for other protein detection in the future. Graphical abstract A homogenous assay for protein detection is based on proximity DNA hybridization and strand displacement amplification reaction.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

NASA Astrophysics Data System (ADS)

Yeganeh, B.; Motlagh, M. Shafie Pour; Rashidi, Y.; Kamalan, H.

2012-08-01

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS-SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS-SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65-85% for hybrid PLS-SVM model respectively. Also it was found that the hybrid PLS-SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS-SVM model.

Azurin/CdSe-ZnS-Based Bio-Nano Hybrid Structure for Nanoscale Resistive Memory Device.

PubMed

Yagati, Ajay Kumar; Lee, Taek; Choi, Jeong-Woo

2017-07-15

In the present study, we propose a method for bio-nano hybrid formation by coupling a redox metalloprotein, Azurin, with CdSe-ZnS quantum dot for the development of a nanoscale resistive memory device. The covalent interaction between the two nanomaterials enables a strong and effective binding to form an azurin/CdSe-ZnS hybrid, and also enabled better controllability to couple with electrodes to examine the memory function properties. Morphological and optical properties were performed to confirm both hybrid formations and also their individual components. Current-Voltage (I-V) measurements on the hybrid nanostructures exhibited bistable current levels towards the memory function device, that and those characteristics were unnoticeable on individual nanomaterials. The hybrids showed good retention characteristics with high stability and durability, which is a promising feature for future nanoscale memory devices.

Nonlinear analysis for dual-frequency concurrent energy harvesting

NASA Astrophysics Data System (ADS)

Yan, Zhimiao; Lei, Hong; Tan, Ting; Sun, Weipeng; Huang, Wenhu

2018-05-01

The dual-frequency responses of the hybrid energy harvester undergoing the base excitation and galloping were analyzed numerically. In this work, an approximate dual-frequency analytical method is proposed for the nonlinear analysis of such a system. To obtain the approximate analytical solutions of the full coupled distributed-parameter model, the forcing interactions is first neglected. Then, the electromechanical decoupled governing equation is developed using the equivalent structure method. The hybrid mechanical response is finally separated to be the self-excited and forced responses for deriving the analytical solutions, which are confirmed by the numerical simulations of the full coupled model. The forced response has great impacts on the self-excited response. The boundary of Hopf bifurcation is analytically determined by the onset wind speed to galloping, which is linearly increased by the electrical damping. Quenching phenomenon appears when the increasing base excitation suppresses the galloping. The theoretical quenching boundary depends on the forced mode velocity. The quenching region increases with the base acceleration and electrical damping, but decreases with the wind speed. Superior to the base-excitation-alone case, the existence of the aerodynamic force protects the hybrid energy harvester at resonance from damages caused by the excessive large displacement. From the view of the harvested power, the hybrid system surpasses the base-excitation-alone system or the galloping-alone system. This study advances our knowledge on intrinsic nonlinear dynamics of the dual-frequency energy harvesting system by taking advantage of the analytical solutions.

High accuracy demodulation for twin-grating based sensor network with hybrid TDM/FDM

NASA Astrophysics Data System (ADS)

Ai, Fan; Sun, Qizhen; Cheng, Jianwei; Luo, Yiyang; Yan, Zhijun; Liu, Deming

2017-04-01

We demonstrate a high accuracy demodulation platform with a tunable Fabry-Perot filter (TFF) for twin-grating based fiber optic sensing network with hybrid TDM/FDM. The hybrid TDM/FDM scheme can improve the spatial resolution to centimeter but increases the requirement of high spectrum resolution. To realize the demodulation of the complex twin-grating spectrum, we adopt the TFF demodulation method and compensate the environmental temperature change and nonlinear effect through calibration FBGs. The performance of the demodulation module is tested by a temperature experiment. Spectrum resolution of 1pm is realized with precision of 2.5pm while the environmental temperature of TFF changes 9.3°C.

Localization for robotic capsule looped by axially magnetized permanent-magnet ring based on hybrid strategy.

PubMed

Yang, Wanan; Li, Yan; Qin, Fengqing

2015-01-01

To actively maneuver a robotic capsule for interactive diagnosis in the gastrointestinal tract, visualizing accurate position and orientation of the capsule when it moves in the gastrointestinal tract is essential. A possible method that encloses the circuits, batteries, imaging device, etc into the capsule looped by an axially magnetized permanent-magnet ring is proposed. Based on expression of the axially magnetized permanent-magnet ring's magnetic fields, a localization and orientation model was established. An improved hybrid strategy that combines the advantages of particle-swarm optimization, clone algorithm, and the Levenberg-Marquardt algorithm was found to solve the model. Experiments showed that the hybrid strategy has good accuracy, convergence, and real time performance.

The two-dimensional hybrid surface plasma micro-cavity

NASA Astrophysics Data System (ADS)

Kai, Tong; Mei-yu, Wang; Fu-cheng, Wang; Jia, Guo

2018-07-01

A hybrid surface plasma micro-cavity structure with a defect cavity is formed based on the two-dimensional surface plasmon resonance photonic crystal waveguide structure. A cell defect is introduced in the centre of the photonic crystal layer to build the hybrid surface plasma micro-cavity structure. This work is numerical based on the finite-difference time-domain method. The photon energy is confined to the micro-cavity and the photon energy is strongest at the interface between the insulating layer and the metal layer. The micro-cavity structure has a very small mode volume of sub-wavelength scale in the 1550 nm communication band. The value of Q/V is up to 7132.08 λ/n-3.

Protein loop modeling using a new hybrid energy function and its application to modeling in inaccurate structural environments.

PubMed

Park, Hahnbeom; Lee, Gyu Rie; Heo, Lim; Seok, Chaok

2014-01-01

Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function.

Microwave-Induced Inactivation of DNA-Based Hybrid Catalyst in Asymmetric Catalysis

PubMed Central

Zhao, Hua; Shen, Kai

2015-01-01

DNA-based hybrid catalysts have gained strong interests in asymmetric reactions. However, to maintain the high enantioselectivity, these reactions are usually conducted at relatively low temperatures (e.g. < 5 °C) for 2–3 days. Aiming to improve the reaction’s turnover rate, we evaluated microwave irradiation with simultaneous cooling as potential energy source since this method has been widely used to accelerate various chemical and enzymatic reactions. However, our data indicated that microwave irradiation induced an inactivation of DNA-based hybrid catalyst even at low temperatures (such as 5 °C). Circular dichroism (CD) spectra and gel electrophoresis of DNA suggest that microwave exposure degrades DNA molecules and disrupts DNA double-stranded structures, causing changes of DNA–metal ligand binding properties and thus poor DNA catalytic performance. PMID:26712696

Design of Hybrid Mobile Communication Networks for Planetary Exploration

NASA Technical Reports Server (NTRS)

Alena, Richard L.; Ossenfort, John; Lee, Charles; Walker, Edward; Stone, Thom

2004-01-01

The Mobile Exploration System Project (MEX) at NASA Ames Research Center has been conducting studies into hybrid communication networks for future planetary missions. These networks consist of space-based communication assets connected to ground-based Internets and planetary surface-based mobile wireless networks. These hybrid mobile networks have been deployed in rugged field locations in the American desert and the Canadian arctic for support of science and simulation activities on at least six occasions. This work has been conducted over the past five years resulting in evolving architectural complexity, improved component characteristics and better analysis and test methods. A rich set of data and techniques have resulted from the development and field testing of the communication network during field expeditions such as the Haughton Mars Project and NASA Mobile Agents Project.

Hybrid multiscale modeling and prediction of cancer cell behavior

PubMed Central

Habibi, Jafar

2017-01-01

Background Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. Methods In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for prediction of cell phenotypes. By using a proposed Q-learning based on SVR-NSGA-II method, the cells have the capability to predict their phenotypes autonomously that is, to act on its own without external direction in response to situations it encounters. Results Computational simulations of the model were performed in order to analyze its performance. The most striking feature of our results is that each cell can select its phenotype at each time step according to its condition. We provide evidence that the prediction of cell phenotypes is reliable. Conclusion Our proposed model, which we term a hybrid multiscale modeling of cancer cell behavior, has the potential to combine the best features of both continuum and discrete models. The in silico results indicate that the 3D model can represent key features of cancer growth, angiogenesis, and its related micro-environment and show that the findings are in good agreement with biological tumor behavior. To the best of our knowledge, this paper is the first hybrid vascular multiscale modeling of cancer cell behavior that has the capability to predict cell phenotypes individually by a self-generated dataset. PMID:28846712

Hybrid thermal link-wise artificial compressibility method

NASA Astrophysics Data System (ADS)

Obrecht, Christian; Kuznik, Frédéric

2015-10-01

Thermal flow prediction is a subject of interest from a scientific and engineering points of view. Our motivation is to develop an accurate, easy to implement and highly scalable method for convective flows simulation. To this end, we present an extension to the link-wise artificial compressibility method (LW-ACM) for thermal simulation of weakly compressible flows. The novel hybrid formulation uses second-order finite difference operators of the energy equation based on the same stencils as the LW-ACM. For validation purposes, the differentially heated cubic cavity was simulated. The simulations remained stable for Rayleigh numbers up to Ra =108. The Nusselt numbers at isothermal walls and dynamics quantities are in good agreement with reference values from the literature. Our results show that the hybrid thermal LW-ACM is an effective and easy-to-use solution to solve convective flows.

A Hybrid 3D Indoor Space Model

NASA Astrophysics Data System (ADS)

Jamali, Ali; Rahman, Alias Abdul; Boguslawski, Pawel

2016-10-01

GIS integrates spatial information and spatial analysis. An important example of such integration is for emergency response which requires route planning inside and outside of a building. Route planning requires detailed information related to indoor and outdoor environment. Indoor navigation network models including Geometric Network Model (GNM), Navigable Space Model, sub-division model and regular-grid model lack indoor data sources and abstraction methods. In this paper, a hybrid indoor space model is proposed. In the proposed method, 3D modeling of indoor navigation network is based on surveying control points and it is less dependent on the 3D geometrical building model. This research proposes a method of indoor space modeling for the buildings which do not have proper 2D/3D geometrical models or they lack semantic or topological information. The proposed hybrid model consists of topological, geometrical and semantical space.

A Hybrid Key Management Scheme for WSNs Based on PPBR and a Tree-Based Path Key Establishment Method

PubMed Central

Zhang, Ying; Liang, Jixing; Zheng, Bingxin; Chen, Wei

2016-01-01

With the development of wireless sensor networks (WSNs), in most application scenarios traditional WSNs with static sink nodes will be gradually replaced by Mobile Sinks (MSs), and the corresponding application requires a secure communication environment. Current key management researches pay less attention to the security of sensor networks with MS. This paper proposes a hybrid key management schemes based on a Polynomial Pool-based key pre-distribution and Basic Random key pre-distribution (PPBR) to be used in WSNs with MS. The scheme takes full advantages of these two kinds of methods to improve the cracking difficulty of the key system. The storage effectiveness and the network resilience can be significantly enhanced as well. The tree-based path key establishment method is introduced to effectively solve the problem of communication link connectivity. Simulation clearly shows that the proposed scheme performs better in terms of network resilience, connectivity and storage effectiveness compared to other widely used schemes. PMID:27070624

Bio-Based Artificial Nacre with Excellent Mechanical and Barrier Properties Realized by a Facile In Situ Reduction and Cross-Linking Reaction.

PubMed

Shahzadi, Kiran; Mohsin, Imran; Wu, Lin; Ge, Xuesong; Jiang, Yijun; Li, Hui; Mu, Xindong

2017-01-24

Demands for high strength integrated materials have substantially increased across various kinds of industries. Inspired by the relationship of excellent integration of mechanical properties and hierarchical nano/microscale structure of the natural nacre, a simple and facile method to fabricate high strength integrated artificial nacre based on sodium carboxymethylcellulose (CMC) and borate cross-linked graphene oxide (GO) sheets has been developed. The tensile strength and toughness of cellulose-based hybrid material reached 480.5 ± 13.1 MPa and 11.8 ± 0.4 MJm -3 by a facile in situ reduction and cross-linking reaction between CMC and GO (0.7%), which are 3.55 and 6.55 times that of natural nacre. This hybrid film exhibits better thermal stability and flame retardancy. More interestingly, the hybrid material showed good water stability compared to that in the original water-soluble CMC. This type of hybrid has great potential applications in aerospace, artificial muscle, and tissue engineering.

Exact Hybrid Particle/Population Simulation of Rule-Based Models of Biochemical Systems

PubMed Central

Stover, Lori J.; Nair, Niketh S.; Faeder, James R.

2014-01-01

Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This “network-free” approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of “partial network expansion” into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings can be achieved using the new approach and a monetary cost analysis provides a practical measure of its utility. PMID:24699269

Exact hybrid particle/population simulation of rule-based models of biochemical systems.

PubMed

Hogg, Justin S; Harris, Leonard A; Stover, Lori J; Nair, Niketh S; Faeder, James R

2014-04-01

Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This "network-free" approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of "partial network expansion" into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings can be achieved using the new approach and a monetary cost analysis provides a practical measure of its utility.

Efficient quantitative assessment of facial paralysis using iris segmentation and active contour-based key points detection with hybrid classifier.

PubMed

Barbosa, Jocelyn; Lee, Kyubum; Lee, Sunwon; Lodhi, Bilal; Cho, Jae-Gu; Seo, Woo-Keun; Kang, Jaewoo

2016-03-12

Facial palsy or paralysis (FP) is a symptom that loses voluntary muscles movement in one side of the human face, which could be very devastating in the part of the patients. Traditional methods are solely dependent to clinician's judgment and therefore time consuming and subjective in nature. Hence, a quantitative assessment system becomes apparently invaluable for physicians to begin the rehabilitation process; and to produce a reliable and robust method is challenging and still underway. We introduce a novel approach for a quantitative assessment of facial paralysis that tackles classification problem for FP type and degree of severity. Specifically, a novel method of quantitative assessment is presented: an algorithm that extracts the human iris and detects facial landmarks; and a hybrid approach combining the rule-based and machine learning algorithm to analyze and prognosticate facial paralysis using the captured images. A method combining the optimized Daugman's algorithm and Localized Active Contour (LAC) model is proposed to efficiently extract the iris and facial landmark or key points. To improve the performance of LAC, appropriate parameters of initial evolving curve for facial features' segmentation are automatically selected. The symmetry score is measured by the ratio between features extracted from the two sides of the face. Hybrid classifiers (i.e. rule-based with regularized logistic regression) were employed for discriminating healthy and unhealthy subjects, FP type classification, and for facial paralysis grading based on House-Brackmann (H-B) scale. Quantitative analysis was performed to evaluate the performance of the proposed approach. Experiments show that the proposed method demonstrates its efficiency. Facial movement feature extraction on facial images based on iris segmentation and LAC-based key point detection along with a hybrid classifier provides a more efficient way of addressing classification problem on facial palsy type and degree of severity. Combining iris segmentation and key point-based method has several merits that are essential for our real application. Aside from the facial key points, iris segmentation provides significant contribution as it describes the changes of the iris exposure while performing some facial expressions. It reveals the significant difference between the healthy side and the severe palsy side when raising eyebrows with both eyes directed upward, and can model the typical changes in the iris region.

Biochemical simulations: stochastic, approximate stochastic and hybrid approaches.

PubMed

Pahle, Jürgen

2009-01-01

Computer simulations have become an invaluable tool to study the sometimes counterintuitive temporal dynamics of (bio-)chemical systems. In particular, stochastic simulation methods have attracted increasing interest recently. In contrast to the well-known deterministic approach based on ordinary differential equations, they can capture effects that occur due to the underlying discreteness of the systems and random fluctuations in molecular numbers. Numerous stochastic, approximate stochastic and hybrid simulation methods have been proposed in the literature. In this article, they are systematically reviewed in order to guide the researcher and help her find the appropriate method for a specific problem.

Biochemical simulations: stochastic, approximate stochastic and hybrid approaches

PubMed Central

2009-01-01

Computer simulations have become an invaluable tool to study the sometimes counterintuitive temporal dynamics of (bio-)chemical systems. In particular, stochastic simulation methods have attracted increasing interest recently. In contrast to the well-known deterministic approach based on ordinary differential equations, they can capture effects that occur due to the underlying discreteness of the systems and random fluctuations in molecular numbers. Numerous stochastic, approximate stochastic and hybrid simulation methods have been proposed in the literature. In this article, they are systematically reviewed in order to guide the researcher and help her find the appropriate method for a specific problem. PMID:19151097

A FINITE-DIFFERENCE, DISCRETE-WAVENUMBER METHOD FOR CALCULATING RADAR TRACES

EPA Science Inventory

A hybrid of the finite-difference method and the discrete-wavenumber method is developed to calculate radar traces. The method is based on a three-dimensional model defined in the Cartesian coordinate system; the electromagnetic properties of the model are symmetric with respect ...

Hybrid surrogate-model-based multi-fidelity efficient global optimization applied to helicopter blade design

NASA Astrophysics Data System (ADS)

Ariyarit, Atthaphon; Sugiura, Masahiko; Tanabe, Yasutada; Kanazaki, Masahiro

2018-06-01

A multi-fidelity optimization technique by an efficient global optimization process using a hybrid surrogate model is investigated for solving real-world design problems. The model constructs the local deviation using the kriging method and the global model using a radial basis function. The expected improvement is computed to decide additional samples that can improve the model. The approach was first investigated by solving mathematical test problems. The results were compared with optimization results from an ordinary kriging method and a co-kriging method, and the proposed method produced the best solution. The proposed method was also applied to aerodynamic design optimization of helicopter blades to obtain the maximum blade efficiency. The optimal shape obtained by the proposed method achieved performance almost equivalent to that obtained using the high-fidelity, evaluation-based single-fidelity optimization. Comparing all three methods, the proposed method required the lowest total number of high-fidelity evaluation runs to obtain a converged solution.

SNBRFinder: A Sequence-Based Hybrid Algorithm for Enhanced Prediction of Nucleic Acid-Binding Residues.

PubMed

Yang, Xiaoxia; Wang, Jia; Sun, Jun; Liu, Rong

2015-01-01

Protein-nucleic acid interactions are central to various fundamental biological processes. Automated methods capable of reliably identifying DNA- and RNA-binding residues in protein sequence are assuming ever-increasing importance. The majority of current algorithms rely on feature-based prediction, but their accuracy remains to be further improved. Here we propose a sequence-based hybrid algorithm SNBRFinder (Sequence-based Nucleic acid-Binding Residue Finder) by merging a feature predictor SNBRFinderF and a template predictor SNBRFinderT. SNBRFinderF was established using the support vector machine whose inputs include sequence profile and other complementary sequence descriptors, while SNBRFinderT was implemented with the sequence alignment algorithm based on profile hidden Markov models to capture the weakly homologous template of query sequence. Experimental results show that SNBRFinderF was clearly superior to the commonly used sequence profile-based predictor and SNBRFinderT can achieve comparable performance to the structure-based template methods. Leveraging the complementary relationship between these two predictors, SNBRFinder reasonably improved the performance of both DNA- and RNA-binding residue predictions. More importantly, the sequence-based hybrid prediction reached competitive performance relative to our previous structure-based counterpart. Our extensive and stringent comparisons show that SNBRFinder has obvious advantages over the existing sequence-based prediction algorithms. The value of our algorithm is highlighted by establishing an easy-to-use web server that is freely accessible at http://ibi.hzau.edu.cn/SNBRFinder.

Hybrid dose calculation: a dose calculation algorithm for microbeam radiation therapy

NASA Astrophysics Data System (ADS)

Donzelli, Mattia; Bräuer-Krisch, Elke; Oelfke, Uwe; Wilkens, Jan J.; Bartzsch, Stefan

2018-02-01

Microbeam radiation therapy (MRT) is still a preclinical approach in radiation oncology that uses planar micrometre wide beamlets with extremely high peak doses, separated by a few hundred micrometre wide low dose regions. Abundant preclinical evidence demonstrates that MRT spares normal tissue more effectively than conventional radiation therapy, at equivalent tumour control. In order to launch first clinical trials, accurate and efficient dose calculation methods are an inevitable prerequisite. In this work a hybrid dose calculation approach is presented that is based on a combination of Monte Carlo and kernel based dose calculation. In various examples the performance of the algorithm is compared to purely Monte Carlo and purely kernel based dose calculations. The accuracy of the developed algorithm is comparable to conventional pure Monte Carlo calculations. In particular for inhomogeneous materials the hybrid dose calculation algorithm out-performs purely convolution based dose calculation approaches. It is demonstrated that the hybrid algorithm can efficiently calculate even complicated pencil beam and cross firing beam geometries. The required calculation times are substantially lower than for pure Monte Carlo calculations.

A new modal superposition method for nonlinear vibration analysis of structures using hybrid mode shapes

NASA Astrophysics Data System (ADS)

Ferhatoglu, Erhan; Cigeroglu, Ender; Özgüven, H. Nevzat

2018-07-01

In this paper, a new modal superposition method based on a hybrid mode shape concept is developed for the determination of steady state vibration response of nonlinear structures. The method is developed specifically for systems having nonlinearities where the stiffness of the system may take different limiting values. Stiffness variation of these nonlinear systems enables one to define different linear systems corresponding to each value of the limiting equivalent stiffness. Moreover, the response of the nonlinear system is bounded by the confinement of these linear systems. In this study, a modal superposition method utilizing novel hybrid mode shapes which are defined as linear combinations of the modal vectors of the limiting linear systems is proposed to determine periodic response of nonlinear systems. In this method the response of the nonlinear system is written in terms of hybrid modes instead of the modes of the underlying linear system. This provides decrease of the number of modes that should be retained for an accurate solution, which in turn reduces the number of nonlinear equations to be solved. In this way, computational time for response calculation is directly curtailed. In the solution, the equations of motion are converted to a set of nonlinear algebraic equations by using describing function approach, and the numerical solution is obtained by using Newton's method with arc-length continuation. The method developed is applied on two different systems: a lumped parameter model and a finite element model. Several case studies are performed and the accuracy and computational efficiency of the proposed modal superposition method with hybrid mode shapes are compared with those of the classical modal superposition method which utilizes the mode shapes of the underlying linear system.

Hybrid stochastic simulation of reaction-diffusion systems with slow and fast dynamics

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

Strehl, Robert; Ilie, Silvana, E-mail: silvana@ryerson.ca

2015-12-21

In this paper, we present a novel hybrid method to simulate discrete stochastic reaction-diffusion models arising in biochemical signaling pathways. We study moderately stiff systems, for which we can partition each reaction or diffusion channel into either a slow or fast subset, based on its propensity. Numerical approaches missing this distinction are often limited with respect to computational run time or approximation quality. We design an approximate scheme that remedies these pitfalls by using a new blending strategy of the well-established inhomogeneous stochastic simulation algorithm and the tau-leaping simulation method. The advantages of our hybrid simulation algorithm are demonstrated onmore » three benchmarking systems, with special focus on approximation accuracy and efficiency.« less

Direct Detection of OXA-48 Carbapenemase Gene in Lysate Samples through Changes in Mechanical Properties of DNA Monolayers upon Hybridization.

PubMed

Domínguez, Carmen M; Ramos, Daniel; Mingorance, Jesús; Fierro, José L G; Tamayo, Javier; Calleja, Montserrat

2018-01-02

Carbapenem-resistant Enterobacteriaceae have recently become an important cause of morbidity and mortality due to healthcare-associated infections. Most commonly used diagnostic methods are incompatible with fast and accurate directed therapy. We report here the direct identification of the bla OXA48 gene, which codes for the carbapenemase OXA-48, in lysate samples from Klebsiella pneumoniae. The method is PCR-free and label-free. It is based on the measurement of changes in the stiffness of DNA self-assembled monolayers anchored to microcantilevers that occur as a consequence of the hybridization. The stiffness of the DNA layer is measured through changes of the sensor resonance frequency upon hybridization and at varying relative humidity.

Optimal Power Scheduling for a Medium Voltage AC/DC Hybrid Distribution Network

DOE PAGES

Zhu, Zhenshan; Liu, Dichen; Liao, Qingfen; ...

2018-01-26

With the great increase of renewable generation as well as the DC loads in the distribution network; DC distribution technology is receiving more attention; since the DC distribution network can improve operating efficiency and power quality by reducing the energy conversion stages. This paper presents a new architecture for the medium voltage AC/DC hybrid distribution network; where the AC and DC subgrids are looped by normally closed AC soft open point (ACSOP) and DC soft open point (DCSOP); respectively. The proposed AC/DC hybrid distribution systems contain renewable generation (i.e., wind power and photovoltaic (PV) generation); energy storage systems (ESSs); softmore » open points (SOPs); and both AC and DC flexible demands. An energy management strategy for the hybrid system is presented based on the dynamic optimal power flow (DOPF) method. The main objective of the proposed power scheduling strategy is to minimize the operating cost and reduce the curtailment of renewable generation while meeting operational and technical constraints. The proposed approach is verified in five scenarios. The five scenarios are classified as pure AC system; hybrid AC/DC system; hybrid system with interlinking converter; hybrid system with DC flexible demand; and hybrid system with SOPs. Results show that the proposed scheduling method can successfully dispatch the controllable elements; and that the presented architecture for the AC/DC hybrid distribution system is beneficial for reducing operating cost and renewable generation curtailment.« less

Sorting through the chaff, nDNA gene trees for phylogenetic inference and hybrid identification of annual sunflowers (Helianthus sect. Helianthus).

PubMed

Moody, Michael L; Rieseberg, Loren H

2012-07-01

The annual sunflowers (Helianthus sect. Helianthus) present a formidable challenge for phylogenetic inference because of ancient hybrid speciation, recent introgression, and suspected issues with deep coalescence. Here we analyze sequence data from 11 nuclear DNA (nDNA) genes for multiple genotypes of species within the section to (1) reconstruct the phylogeny of this group, (2) explore the utility of nDNA gene trees for detecting hybrid speciation and introgression; and (3) test an empirical method of hybrid identification based on the phylogenetic congruence of nDNA gene trees from tightly linked genes. We uncovered considerable topological heterogeneity among gene trees with or without three previously identified hybrid species included in the analyses, as well as a general lack of reciprocal monophyly of species. Nonetheless, partitioned Bayesian analyses provided strong support for the reciprocal monophyly of all species except H. annuus (0.89 PP), the most widespread and abundant annual sunflower. Previous hypotheses of relationships among taxa were generally strongly supported (1.0 PP), except among taxa typically associated with H. annuus, apparently due to the paraphyly of the latter in all gene trees. While the individual nDNA gene trees provided a useful means for detecting recent hybridization, identification of ancient hybridization was problematic for all ancient hybrid species, even when linkage was considered. We discuss biological factors that affect the efficacy of phylogenetic methods for hybrid identification.

Optimal Power Scheduling for a Medium Voltage AC/DC Hybrid Distribution Network

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

Zhu, Zhenshan; Liu, Dichen; Liao, Qingfen

With the great increase of renewable generation as well as the DC loads in the distribution network; DC distribution technology is receiving more attention; since the DC distribution network can improve operating efficiency and power quality by reducing the energy conversion stages. This paper presents a new architecture for the medium voltage AC/DC hybrid distribution network; where the AC and DC subgrids are looped by normally closed AC soft open point (ACSOP) and DC soft open point (DCSOP); respectively. The proposed AC/DC hybrid distribution systems contain renewable generation (i.e., wind power and photovoltaic (PV) generation); energy storage systems (ESSs); softmore » open points (SOPs); and both AC and DC flexible demands. An energy management strategy for the hybrid system is presented based on the dynamic optimal power flow (DOPF) method. The main objective of the proposed power scheduling strategy is to minimize the operating cost and reduce the curtailment of renewable generation while meeting operational and technical constraints. The proposed approach is verified in five scenarios. The five scenarios are classified as pure AC system; hybrid AC/DC system; hybrid system with interlinking converter; hybrid system with DC flexible demand; and hybrid system with SOPs. Results show that the proposed scheduling method can successfully dispatch the controllable elements; and that the presented architecture for the AC/DC hybrid distribution system is beneficial for reducing operating cost and renewable generation curtailment.« less

Manipulation of oligonucleotides immobilized on solid supports - DNA computations on surfaces

NASA Astrophysics Data System (ADS)

Liu, Qinghua

The manipulation of DNA oligonucleotides immobilized on various solid supports has been studied intensively, especially in the area of surface hybridization. Recently, surface-based biotechnology has been applied to the area of molecular computing. These surface-based methods have advantages with regard to ease of handling, facile purification, and less interference when compared to solution methodologies. This dissertation describes the investigation of molecular approaches to DNA computing. The feasibility of encoding a bit (0 or 1) of information for DNA-based computations at the single nucleotide level was studied, particularly with regard to the efficiency and specificity of hybridization discrimination. Both gold and glass surfaces, with addressed arrays of 32 oligonucleotides, were employed with similar hybridization results. Although single-base discrimination may be achieved in the system, it is at the cost of a severe decrease in the efficiency of hybridization to perfectly matched sequences. This compromises the utility of single nucleotide encoding for DNA computing applications in the absence of some additional mechanism for increasing specificity. Several methods are suggested including a multiple-base encoding strategy. The multiple-base encoding strategy was employed to develop a prototype DNA computer. The approach was demonstrated by solving a small example of the Satisfiability (SAT) problem, an NP-complete problem in Boolean logic. 16 distinct DNA oligonucleotides, encoding all candidate solutions to the 4-variable-4-clause-3-SAT problem, were immobilized on a gold surface in the non-addressed format. Four cycles of MARK (hybridization), DESTROY (enzymatic destruction) and UNMARK (denaturation) were performed, which identified and eliminated members of the set which were not solutions to the problem. Determination of the answer was accomplished in the READOUT (sequence identification) operation by PCR amplification of the remaining molecules and hybridization to an addressed array. Four answers were determined and the S/N ratio between correct and incorrect solutions ranged from 10 to 777, making discrimination between correct and incorrect solutions to the problem straightforward. Additionally, studies of enzymatic manipulations of DNA molecules on surfaces suggested the use of E. coli Exonuclease I (Exo I) and perhaps EarI in the DESTROY operation.

Hybrid Automatic Building Interpretation System

NASA Astrophysics Data System (ADS)

Pakzad, K.; Klink, A.; Müterthies, A.; Gröger, G.; Stroh, V.; Plümer, L.

2011-09-01

HABIS (Hybrid Automatic Building Interpretation System) is a system for an automatic reconstruction of building roofs used in virtual 3D building models. Unlike most of the commercially available systems, HABIS is able to work to a high degree automatically. The hybrid method uses different sources intending to exploit the advantages of the particular sources. 3D point clouds usually provide good height and surface data, whereas spatial high resolution aerial images provide important information for edges and detail information for roof objects like dormers or chimneys. The cadastral data provide important basis information about the building ground plans. The approach used in HABIS works with a multi-stage-process, which starts with a coarse roof classification based on 3D point clouds. After that it continues with an image based verification of these predicted roofs. In a further step a final classification and adjustment of the roofs is done. In addition some roof objects like dormers and chimneys are also extracted based on aerial images and added to the models. In this paper the used methods are described and some results are presented.

Synthesis of nanostructured bio-related materials by hybridization of synthetic polymers with polysaccharides or saccharide residues.

PubMed

Kaneko, Yoshiro; Kadokawa, Jun-Ichi

2006-01-01

In the first part of this review, we describe the synthesis of nanostructured hybrid materials composed of polysaccharides and synthetic polymers. Amylose-synthetic polymer inclusion complexes were synthesized by amylose-forming polymerization using phosphorylase enzyme in the presence of synthetic polymers such as polyethers and polyesters. Alginate-polymethacrylate hybrid materials were prepared by free-radical polymerization of cationic methacrylate in the presence of sodium alginate. These methods allow the simultaneous control of the nanostructure with polymerization, giving well-defined hybrid materials. In the second part of this review, we describe the synthesis of novel glycopolymers with rigid structures. Polyaniline-based glycopolymers were synthesized by means of oxidative polymerization of N-glycosylaniline. Polysiloxane-based glycopolymers were prepared by means of introduction of sugar-lactone to the rodlike polysiloxane. These glycopolymers had regular higher-ordered structures due to their rigid polymer backbones, resulting in control of the three-dimensional array of sugar-residues.

Efficient and Robust Optimization for Building Energy Simulation

PubMed Central

Pourarian, Shokouh; Kearsley, Anthony; Wen, Jin; Pertzborn, Amanda

2016-01-01

Efficiently, robustly and accurately solving large sets of structured, non-linear algebraic and differential equations is one of the most computationally expensive steps in the dynamic simulation of building energy systems. Here, the efficiency, robustness and accuracy of two commonly employed solution methods are compared. The comparison is conducted using the HVACSIM+ software package, a component based building system simulation tool. The HVACSIM+ software presently employs Powell’s Hybrid method to solve systems of nonlinear algebraic equations that model the dynamics of energy states and interactions within buildings. It is shown here that the Powell’s method does not always converge to a solution. Since a myriad of other numerical methods are available, the question arises as to which method is most appropriate for building energy simulation. This paper finds considerable computational benefits result from replacing the Powell’s Hybrid method solver in HVACSIM+ with a solver more appropriate for the challenges particular to numerical simulations of buildings. Evidence is provided that a variant of the Levenberg-Marquardt solver has superior accuracy and robustness compared to the Powell’s Hybrid method presently used in HVACSIM+. PMID:27325907

Efficient and Robust Optimization for Building Energy Simulation.

PubMed

Pourarian, Shokouh; Kearsley, Anthony; Wen, Jin; Pertzborn, Amanda

2016-06-15

Efficiently, robustly and accurately solving large sets of structured, non-linear algebraic and differential equations is one of the most computationally expensive steps in the dynamic simulation of building energy systems. Here, the efficiency, robustness and accuracy of two commonly employed solution methods are compared. The comparison is conducted using the HVACSIM+ software package, a component based building system simulation tool. The HVACSIM+ software presently employs Powell's Hybrid method to solve systems of nonlinear algebraic equations that model the dynamics of energy states and interactions within buildings. It is shown here that the Powell's method does not always converge to a solution. Since a myriad of other numerical methods are available, the question arises as to which method is most appropriate for building energy simulation. This paper finds considerable computational benefits result from replacing the Powell's Hybrid method solver in HVACSIM+ with a solver more appropriate for the challenges particular to numerical simulations of buildings. Evidence is provided that a variant of the Levenberg-Marquardt solver has superior accuracy and robustness compared to the Powell's Hybrid method presently used in HVACSIM+.

A Hybrid Template-Based Composite Classification System

DTIC Science & Technology

2009-02-01

Hybrid Classifier: Forced Decision . . . . 116 5.3.2 Forced Decision Experimental Results . . . . . 119 5.3.3 Test for Statistical Significance ...Results . . . . . . . . . . 127 5.4.2 Test for Statistical Significance : NDEC Option 129 5.5 Implementing the Hyrid Classifier with OOL Targets . 130...comple- mentary in nature . Complementary classifiers are observed by finding an optimal method for partitioning the problem space. For example, the

Durable Hybrid Coatings. Annual Performance Report (2008)

DTIC Science & Technology

2008-09-01

points 162ensuring stabilization of the reading before moving to the next point. 163Two different thermogravimetric analysis (TGA) methods were...aluminum alloy (Al 2024). Mg-rich primers based on a hybrid organic-inorganic binder derived from silica nanoparticles and...phenethyltrimethoxysilane gave excellent corrosion protection of Al 2024-T3. Work has continued on these coatings with particular emphasis on the silica nanoparticle

Highly sensitive DNA detection using cascade amplification strategy based on hybridization chain reaction and enzyme-induced metallization

PubMed Central

Yu, Xu; Zhang, Zhi-Ling; Zheng, Si-Yang

2014-01-01

A novel highly sensitive colorimetric assay for DNA detection using cascade amplification strategy based on hybridization chain reaction and enzyme-induced metallization was established. The DNA modified superparamagnetic beads were demonstrated to capture and enrich the target DNA in the hybridization buffer or human plasma. The hybridization chain reaction and enzyme-induced silver metallization on the gold nanoparticles were used as cascade signal amplification for the detection of target DNA. The metalization of silver on the gold nanoparticles induced a significant colour change from red to yellow until black depending on the concentration of the target DNA, which could be recognized by naked eyes. This method showed a good specificity for the target DNA detection, with the capabilty to discriminate single-base-pair mismatched DNA mutation (single nucleotide polymorphism). Meanwhile, this approach exhibited an excellent anti-interference capability with the convenience of the magentic seperation and washing, which enabled its usage in complex biological systems such as human blood plasma. As an added benefit, the utilization of hybridization chain reaction and enzyme-induced metallization improved detection sensitivity down to 10 pM, which is about 100-fold lower than that of traditional unamplified homogeneous assays. PMID:25500528

A FINITE-DIFFERENCE, DISCRETE-WAVENUMBER METHOD FOR CALCULATING RADAR TRACES

EPA Science Inventory

A hybrid of the finite-difference method and the discrete-wavenumber method is developed to calculate radar traces. The method is based on a three-dimensional model defined in the Cartesian coordinate system; the electromag-netic properties of the model are symmetric with respect...

A Hybrid Approach to Protect Palmprint Templates

PubMed Central

Sun, Dongmei; Xiong, Ke; Qiu, Zhengding

2014-01-01

Biometric template protection is indispensable to protect personal privacy in large-scale deployment of biometric systems. Accuracy, changeability, and security are three critical requirements for template protection algorithms. However, existing template protection algorithms cannot satisfy all these requirements well. In this paper, we propose a hybrid approach that combines random projection and fuzzy vault to improve the performances at these three points. Heterogeneous space is designed for combining random projection and fuzzy vault properly in the hybrid scheme. New chaff point generation method is also proposed to enhance the security of the heterogeneous vault. Theoretical analyses of proposed hybrid approach in terms of accuracy, changeability, and security are given in this paper. Palmprint database based experimental results well support the theoretical analyses and demonstrate the effectiveness of proposed hybrid approach. PMID:24982977

A hybrid approach to protect palmprint templates.

PubMed

Liu, Hailun; Sun, Dongmei; Xiong, Ke; Qiu, Zhengding

2014-01-01

Biometric template protection is indispensable to protect personal privacy in large-scale deployment of biometric systems. Accuracy, changeability, and security are three critical requirements for template protection algorithms. However, existing template protection algorithms cannot satisfy all these requirements well. In this paper, we propose a hybrid approach that combines random projection and fuzzy vault to improve the performances at these three points. Heterogeneous space is designed for combining random projection and fuzzy vault properly in the hybrid scheme. New chaff point generation method is also proposed to enhance the security of the heterogeneous vault. Theoretical analyses of proposed hybrid approach in terms of accuracy, changeability, and security are given in this paper. Palmprint database based experimental results well support the theoretical analyses and demonstrate the effectiveness of proposed hybrid approach.

Synthesis of a hybrid model of the VSC FACTS devices and HVDC technologies

NASA Astrophysics Data System (ADS)

Borovikov, Yu S.; Gusev, A. S.; Sulaymanov, A. O.; Ufa, R. A.

2014-10-01

The motivation of the presented research is based on the need for development of new methods and tools for adequate simulation of FACTS devices and HVDC systems as part of real electric power systems (EPS). The Research object: An alternative hybrid approach for synthesizing VSC-FACTS and -HVDC hybrid model is proposed. The results: the VSC- FACTS and -HVDC hybrid model is designed in accordance with the presented concepts of hybrid simulation. The developed model allows us to carry out adequate simulation in real time of all the processes in HVDC, FACTS devices and EPS as a whole without any decomposition and limitation on their duration, and also use the developed tool for effective solution of a design, operational and research tasks of EPS containing such devices.

Cellular morphology of organic-inorganic hybrid foams based on alkali alumino-silicate matrix

NASA Astrophysics Data System (ADS)

Verdolotti, Letizia; Liguori, Barbara; Capasso, Ilaria; Caputo, Domenico; Lavorgna, Marino; Iannace, Salvatore

2014-05-01

Organic-inorganic hybrid foams based on an alkali alumino-silicate matrix were prepared by using different foaming methods. Initially, the synthesis of an inorganic matrix by using aluminosilicate particles, activated through a sodium silicate solution, was performed at room temperature. Subsequently the viscous paste was foamed by using three different methods. In the first method, gaseous hydrogen produced by the oxidization of Si powder in an alkaline media, was used as blowing agent to generate gas bubbles in the paste. In the second method, the porous structure was generated by mixing the paste with a "meringue" type of foam previously prepared by whipping, under vigorous stirring, a water solution containing vegetal proteins as surfactants. In the third method, a combination of these two methods was employed. The foamed systems were consolidated for 24 hours at 40°C and then characterized by FTIR, X-Ray diffraction, scanning electron microscopy (SEM) and compression tests. Low density foams (˜500 Kg/m3) with good cellular structure and mechanical properties were obtained by combining the "meringue" approach with the use of the chemical blowing agent based on Si.

Supervised segmentation of phenotype descriptions for the human skeletal phenome using hybrid methods.

PubMed

Groza, Tudor; Hunter, Jane; Zankl, Andreas

2012-10-15

Over the course of the last few years there has been a significant amount of research performed on ontology-based formalization of phenotype descriptions. In order to fully capture the intrinsic value and knowledge expressed within them, we need to take advantage of their inner structure, which implicitly combines qualities and anatomical entities. The first step in this process is the segmentation of the phenotype descriptions into their atomic elements. We present a two-phase hybrid segmentation method that combines a series individual classifiers using different aggregation schemes (set operations and simple majority voting). The approach is tested on a corpus comprised of skeletal phenotype descriptions emerged from the Human Phenotype Ontology. Experimental results show that the best hybrid method achieves an F-Score of 97.05% in the first phase and F-Scores of 97.16% / 94.50% in the second phase. The performance of the initial segmentation of anatomical entities and qualities (phase I) is not affected by the presence / absence of external resources, such as domain dictionaries. From a generic perspective, hybrid methods may not always improve the segmentation accuracy as they are heavily dependent on the goal and data characteristics.

Hybrid MCDA Methods to Integrate Multiple Ecosystem Services in Forest Management Planning: A Critical Review

NASA Astrophysics Data System (ADS)

Uhde, Britta; Andreas Hahn, W.; Griess, Verena C.; Knoke, Thomas

2015-08-01

Multi-criteria decision analysis (MCDA) is a decision aid frequently used in the field of forest management planning. It includes the evaluation of multiple criteria such as the production of timber and non-timber forest products and tangible as well as intangible values of ecosystem services (ES). Hence, it is beneficial compared to those methods that take a purely financial perspective. Accordingly, MCDA methods are increasingly popular in the wide field of sustainability assessment. Hybrid approaches allow aggregating MCDA and, potentially, other decision-making techniques to make use of their individual benefits and leading to a more holistic view of the actual consequences that come with certain decisions. This review is providing a comprehensive overview of hybrid approaches that are used in forest management planning. Today, the scientific world is facing increasing challenges regarding the evaluation of ES and the trade-offs between them, for example between provisioning and regulating services. As the preferences of multiple stakeholders are essential to improve the decision process in multi-purpose forestry, participatory and hybrid approaches turn out to be of particular importance. Accordingly, hybrid methods show great potential for becoming most relevant in future decision making. Based on the review presented here, the development of models for the use in planning processes should focus on participatory modeling and the consideration of uncertainty regarding available information.

Hybrid MCDA Methods to Integrate Multiple Ecosystem Services in Forest Management Planning: A Critical Review.

PubMed

Uhde, Britta; Hahn, W Andreas; Griess, Verena C; Knoke, Thomas

2015-08-01

Multi-criteria decision analysis (MCDA) is a decision aid frequently used in the field of forest management planning. It includes the evaluation of multiple criteria such as the production of timber and non-timber forest products and tangible as well as intangible values of ecosystem services (ES). Hence, it is beneficial compared to those methods that take a purely financial perspective. Accordingly, MCDA methods are increasingly popular in the wide field of sustainability assessment. Hybrid approaches allow aggregating MCDA and, potentially, other decision-making techniques to make use of their individual benefits and leading to a more holistic view of the actual consequences that come with certain decisions. This review is providing a comprehensive overview of hybrid approaches that are used in forest management planning. Today, the scientific world is facing increasing challenges regarding the evaluation of ES and the trade-offs between them, for example between provisioning and regulating services. As the preferences of multiple stakeholders are essential to improve the decision process in multi-purpose forestry, participatory and hybrid approaches turn out to be of particular importance. Accordingly, hybrid methods show great potential for becoming most relevant in future decision making. Based on the review presented here, the development of models for the use in planning processes should focus on participatory modeling and the consideration of uncertainty regarding available information.

Wire connector classification with machine vision and a novel hybrid SVM

NASA Astrophysics Data System (ADS)

Chauhan, Vedang; Joshi, Keyur D.; Surgenor, Brian W.

2018-04-01

A machine vision-based system has been developed and tested that uses a novel hybrid Support Vector Machine (SVM) in a part inspection application with clear plastic wire connectors. The application required the system to differentiate between 4 different known styles of connectors plus one unknown style, for a total of 5 classes. The requirement to handle an unknown class is what necessitated the hybrid approach. The system was trained with the 4 known classes and tested with 5 classes (the 4 known plus the 1 unknown). The hybrid classification approach used two layers of SVMs: one layer was semi-supervised and the other layer was supervised. The semi-supervised SVM was a special case of unsupervised machine learning that classified test images as one of the 4 known classes (to accept) or as the unknown class (to reject). The supervised SVM classified test images as one of the 4 known classes and consequently would give false positives (FPs). Two methods were tested. The difference between the methods was that the order of the layers was switched. The method with the semi-supervised layer first gave an accuracy of 80% with 20% FPs. The method with the supervised layer first gave an accuracy of 98% with 0% FPs. Further work is being conducted to see if the hybrid approach works with other applications that have an unknown class requirement.

Hybrid organic-inorganic sol-gel materials and components for integrated optoelectronics

NASA Astrophysics Data System (ADS)

Lu, Dong

On the technical platform of hybrid organic-inorganic sol-gel, the integrated optoelectronics in the forms of heterogeneous integration between the hybrid sol-gel waveguide and the high refractive index semiconductors and the nonlinear functional doping of disperse red chromophore into hybrid sol-gel is developed. The structure of hybrid sol-gel waveguide on high index semiconductor substrate is designed with BPM-CAD software. A hybrid sol-gel based on MAPTMS and TEOS suitable for lower cladding for the waveguide is developed. The multi-layer hybrid sol-gel waveguide with good mode confinement and low polarization dependence is fabricated on Si and InP. As proof of concept, a 1 x 12 beam splitter based on multimode interference is fabricated on silicon substrate. The device shows excess loss below 0.65 dB and imbalance below 0.28 dB for both TE and TM polarization. A nonlinear active hybrid sol-gel doped with disperse red 13 has been developed by simple co-solvent method. It permits high loading concentration and has low optical loss at 1550 nm. The second-order nonlinear property of the active sol-gel is induced with corona poling and studied with second harmonic generation. A 3-fold of enhancement in the poling efficiency is achieved by blue light assisted corona poling. The chromophore alignment stability is improved by reducing the free volume of the formed inorganic network from the sol-gel condensation reaction. An active sol-gel channel waveguide has been fabricated using active and passive hybrid sol-gel materials by only photopatterning and spin-coating. An amplitude modulator based on the active sol-gel containing 30 wt.% of DR13 shows an electro-optic coefficient of 14 pm/V at 1550 nm and stable operation within the observation time of 24 days.

The application of hybrid artificial intelligence systems for forecasting

NASA Astrophysics Data System (ADS)

Lees, Brian; Corchado, Juan

1999-03-01

The results to date are presented from an ongoing investigation, in which the aim is to combine the strengths of different artificial intelligence methods into a single problem solving system. The premise underlying this research is that a system which embodies several cooperating problem solving methods will be capable of achieving better performance than if only a single method were employed. The work has so far concentrated on the combination of case-based reasoning and artificial neural networks. The relative merits of artificial neural networks and case-based reasoning problem solving paradigms, and their combination are discussed. The integration of these two AI problem solving methods in a hybrid systems architecture, such that the neural network provides support for learning from past experience in the case-based reasoning cycle, is then presented. The approach has been applied to the task of forecasting the variation of physical parameters of the ocean. Results obtained so far from tests carried out in the dynamic oceanic environment are presented.

Adaptable gene-specific dye bias correction for two-channel DNA microarrays.

PubMed

Margaritis, Thanasis; Lijnzaad, Philip; van Leenen, Dik; Bouwmeester, Diane; Kemmeren, Patrick; van Hooff, Sander R; Holstege, Frank C P

2009-01-01

DNA microarray technology is a powerful tool for monitoring gene expression or for finding the location of DNA-bound proteins. DNA microarrays can suffer from gene-specific dye bias (GSDB), causing some probes to be affected more by the dye than by the sample. This results in large measurement errors, which vary considerably for different probes and also across different hybridizations. GSDB is not corrected by conventional normalization and has been difficult to address systematically because of its variance. We show that GSDB is influenced by label incorporation efficiency, explaining the variation of GSDB across different hybridizations. A correction method (Gene- And Slide-Specific Correction, GASSCO) is presented, whereby sequence-specific corrections are modulated by the overall bias of individual hybridizations. GASSCO outperforms earlier methods and works well on a variety of publically available datasets covering a range of platforms, organisms and applications, including ChIP on chip. A sequence-based model is also presented, which predicts which probes will suffer most from GSDB, useful for microarray probe design and correction of individual hybridizations. Software implementing the method is publicly available.

Adaptable gene-specific dye bias correction for two-channel DNA microarrays

PubMed Central

Margaritis, Thanasis; Lijnzaad, Philip; van Leenen, Dik; Bouwmeester, Diane; Kemmeren, Patrick; van Hooff, Sander R; Holstege, Frank CP

2009-01-01

DNA microarray technology is a powerful tool for monitoring gene expression or for finding the location of DNA-bound proteins. DNA microarrays can suffer from gene-specific dye bias (GSDB), causing some probes to be affected more by the dye than by the sample. This results in large measurement errors, which vary considerably for different probes and also across different hybridizations. GSDB is not corrected by conventional normalization and has been difficult to address systematically because of its variance. We show that GSDB is influenced by label incorporation efficiency, explaining the variation of GSDB across different hybridizations. A correction method (Gene- And Slide-Specific Correction, GASSCO) is presented, whereby sequence-specific corrections are modulated by the overall bias of individual hybridizations. GASSCO outperforms earlier methods and works well on a variety of publically available datasets covering a range of platforms, organisms and applications, including ChIP on chip. A sequence-based model is also presented, which predicts which probes will suffer most from GSDB, useful for microarray probe design and correction of individual hybridizations. Software implementing the method is publicly available. PMID:19401678

Bio-hybrid cell-based actuators for microsystems.

PubMed

Carlsen, Rika Wright; Sitti, Metin

2014-10-15

As we move towards the miniaturization of devices to perform tasks at the nano and microscale, it has become increasingly important to develop new methods for actuation, sensing, and control. Over the past decade, bio-hybrid methods have been investigated as a promising new approach to overcome the challenges of scaling down robotic and other functional devices. These methods integrate biological cells with artificial components and therefore, can take advantage of the intrinsic actuation and sensing functionalities of biological cells. Here, the recent advancements in bio-hybrid actuation are reviewed, and the challenges associated with the design, fabrication, and control of bio-hybrid microsystems are discussed. As a case study, focus is put on the development of bacteria-driven microswimmers, which has been investigated as a targeted drug delivery carrier. Finally, a future outlook for the development of these systems is provided. The continued integration of biological and artificial components is envisioned to enable the performance of tasks at a smaller and smaller scale in the future, leading to the parallel and distributed operation of functional systems at the microscale. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A low density microarray method for the identification of human papillomavirus type 18 variants.

PubMed

Meza-Menchaca, Thuluz; Williams, John; Rodríguez-Estrada, Rocío B; García-Bravo, Aracely; Ramos-Ligonio, Ángel; López-Monteon, Aracely; Zepeda, Rossana C

2013-09-26

We describe a novel microarray based-method for the screening of oncogenic human papillomavirus 18 (HPV-18) molecular variants. Due to the fact that sequencing methodology may underestimate samples containing more than one variant we designed a specific and sensitive stacking DNA hybridization assay. This technology can be used to discriminate between three possible phylogenetic branches of HPV-18. Probes were attached covalently on glass slides and hybridized with single-stranded DNA targets. Prior to hybridization with the probes, the target strands were pre-annealed with the three auxiliary contiguous oligonucleotides flanking the target sequences. Screening HPV-18 positive cell lines and cervical samples were used to evaluate the performance of this HPV DNA microarray. Our results demonstrate that the HPV-18's variants hybridized specifically to probes, with no detection of unspecific signals. Specific probes successfully reveal detectable point mutations in these variants. The present DNA oligoarray system can be used as a reliable, sensitive and specific method for HPV-18 variant screening. Furthermore, this simple assay allows the use of inexpensive equipment, making it accessible in resource-poor settings.

A Low Density Microarray Method for the Identification of Human Papillomavirus Type 18 Variants

PubMed Central

Meza-Menchaca, Thuluz; Williams, John; Rodríguez-Estrada, Rocío B.; García-Bravo, Aracely; Ramos-Ligonio, Ángel; López-Monteon, Aracely; Zepeda, Rossana C.

2013-01-01

We describe a novel microarray based-method for the screening of oncogenic human papillomavirus 18 (HPV-18) molecular variants. Due to the fact that sequencing methodology may underestimate samples containing more than one variant we designed a specific and sensitive stacking DNA hybridization assay. This technology can be used to discriminate between three possible phylogenetic branches of HPV-18. Probes were attached covalently on glass slides and hybridized with single-stranded DNA targets. Prior to hybridization with the probes, the target strands were pre-annealed with the three auxiliary contiguous oligonucleotides flanking the target sequences. Screening HPV-18 positive cell lines and cervical samples were used to evaluate the performance of this HPV DNA microarray. Our results demonstrate that the HPV-18's variants hybridized specifically to probes, with no detection of unspecific signals. Specific probes successfully reveal detectable point mutations in these variants. The present DNA oligoarray system can be used as a reliable, sensitive and specific method for HPV-18 variant screening. Furthermore, this simple assay allows the use of inexpensive equipment, making it accessible in resource-poor settings. PMID:24077317

Semi-active control of tracked vehicle suspension incorporating magnetorheological dampers

NASA Astrophysics Data System (ADS)

Ata, W. G.; Salem, A. M.

2017-05-01

In past years, the application of magnetorheological (MR) and electrorheological dampers in vehicle suspension has been widely studied, mainly for the purpose of vibration control. This paper presents theoretical study to identify an appropriate semi-active control method for MR-tracked vehicle suspension. Three representative control algorithms are simulated including the skyhook, hybrid and fuzzy-hybrid controllers. A seven degrees-of-freedom tracked vehicle suspension model incorporating MR dampers has been adopted for comparison between the performance of the three controllers. The model differential equations are derived based on Newton's second law of motion and the proposed control methods are developed. The performance of each control method under bump and sinusoidal road profiles for different vehicle speeds is simulated and compared with the performance of the conventional suspension system in time and frequency domains. The results show that the performance of tracked vehicle suspension with MR dampers is substantially improved. Moreover, the fuzzy-hybrid controller offers an excellent integrated performance in reducing the body accelerations as well as wheel bounce responses compared with the classical skyhook and hybrid controllers.

Highly specific detection of genetic modification events using an enzyme-linked probe hybridization chip.

PubMed

Zhang, M Z; Zhang, X F; Chen, X M; Chen, X; Wu, S; Xu, L L

2015-08-10

The enzyme-linked probe hybridization chip utilizes a method based on ligase-hybridizing probe chip technology, with the principle of using thio-primers for protection against enzyme digestion, and using lambda DNA exonuclease to cut multiple PCR products obtained from the sample being tested into single-strand chains for hybridization. The 5'-end amino-labeled probe was fixed onto the aldehyde chip, and hybridized with the single-stranded PCR product, followed by addition of a fluorescent-modified probe that was then enzymatically linked with the adjacent, substrate-bound probe in order to achieve highly specific, parallel, and high-throughput detection. Specificity and sensitivity testing demonstrated that enzyme-linked probe hybridization technology could be applied to the specific detection of eight genetic modification events at the same time, with a sensitivity reaching 0.1% and the achievement of accurate, efficient, and stable results.

Hybrid real-code ant colony optimisation for constrained mechanical design

NASA Astrophysics Data System (ADS)

Pholdee, Nantiwat; Bureerat, Sujin

2016-01-01

This paper proposes a hybrid meta-heuristic based on integrating a local search simplex downhill (SDH) method into the search procedure of real-code ant colony optimisation (ACOR). This hybridisation leads to five hybrid algorithms where a Monte Carlo technique, a Latin hypercube sampling technique (LHS) and a translational propagation Latin hypercube design (TPLHD) algorithm are used to generate an initial population. Also, two numerical schemes for selecting an initial simplex are investigated. The original ACOR and its hybrid versions along with a variety of established meta-heuristics are implemented to solve 17 constrained test problems where a fuzzy set theory penalty function technique is used to handle design constraints. The comparative results show that the hybrid algorithms are the top performers. Using the TPLHD technique gives better results than the other sampling techniques. The hybrid optimisers are a powerful design tool for constrained mechanical design problems.

A New Control Method to Mitigate Power Fluctuations for Grid Integrated PV/Wind Hybrid Power System Using Ultracapacitors

NASA Astrophysics Data System (ADS)

Jayalakshmi, N. S.; Gaonkar, D. N.

2016-08-01

The output power obtained from solar-wind hybrid system fluctuates with changes in weather conditions. These power fluctuations cause adverse effects on the voltage, frequency and transient stability of the utility grid. In this paper, a control method is presented for power smoothing of grid integrated PV/wind hybrid system using ultracapacitors in a DC coupled structure. The power fluctuations of hybrid system are mitigated and smoothed power is supplied to the utility grid. In this work both photovoltaic (PV) panels and the wind generator are controlled to operate at their maximum power point. The grid side inverter control strategy presented in this paper maintains DC link voltage constant while injecting power to the grid at unity power factor considering different operating conditions. Actual solar irradiation and wind speed data are used in this study to evaluate the performance of the developed system using MATLAB/Simulink software. The simulation results show that output power fluctuations of solar-wind hybrid system can be significantly mitigated using the ultracapacitor based storage system.

Invasive pulmonary aspergillosis: current diagnostic methodologies and a new molecular approach.

PubMed

Moura, S; Cerqueira, L; Almeida, A

2018-05-13

The fungus Aspergillus fumigatus is the main pathogenic agent responsible for invasive pulmonary aspergillosis. Immunocompromised patients are more likely to develop this pathology due to a decrease in the immune system's defense capacity. Despite of the low occurrence of invasive pulmonary aspergillosis, this pathology presents high rates of mortality, mostly due to late and unspecific diagnosis. Currently, the diagnostic methods used to detect this fungal infection are conventional mycological examination (direct microscopic examination, histological examination, and culture), imaging, non-culture-based tests for the detection of galactomannan, β(1,3)-glucan and an extracellular glycoprotein, and molecular tests based on PCR. However, most of these methods do not detect the species A. fumigatus; they only allow the identification of genus Aspergillus. The development of more specific detection methods is of extreme importance. Fluorescent in situ hybridization-based molecular methods can be a good alternative to achieve this purpose. In this review, it is intended to point out that most of the methods used for the diagnosis of invasive pulmonary aspergillosis do not allow to detect the fungus at the species level and that fluorescence in situ hybridization-based molecular method will be a promising approach in the A. fumigatus detection.

Preparation and characterization of flexible asymmetric supercapacitors based on transition-metal-oxide nanowire/single-walled carbon nanotube hybrid thin-film electrodes.

PubMed

Chen, Po-Chiang; Shen, Guozhen; Shi, Yi; Chen, Haitian; Zhou, Chongwu

2010-08-24

In the work described in this paper, we have successfully fabricated flexible asymmetric supercapacitors (ASCs) based on transition-metal-oxide nanowire/single-walled carbon nanotube (SWNT) hybrid thin-film electrodes. These hybrid nanostructured films, with advantages of mechanical flexibility, uniform layered structures, and mesoporous surface morphology, were produced by using a filtration method. Here, manganese dioxide nanowire/SWNT hybrid films worked as the positive electrode, and indium oxide nanowire/SWNT hybrid films served as the negative electrode in a designed ASC. In our design, charges can be stored not only via electrochemical double-layer capacitance from SWNT films but also through a reversible faradic process from transition-metal-oxide nanowires. In addition, to obtain stable electrochemical behavior during charging/discharging cycles in a 2 V potential window, the mass balance between two electrodes has been optimized. Our optimized hybrid nanostructured ASCs exhibited a superior device performance with specific capacitance of 184 F/g, energy density of 25.5 Wh/kg, and columbic efficiency of approximately 90%. In addition, our ASCs exhibited a power density of 50.3 kW/kg, which is 10-fold higher than obtained in early reported ASC work. The high-performance hybrid nanostructured ASCs can find applications in conformal electrics, portable electronics, and electrical vehicles.

Nonlinear optical properties of metal alkanoate composites with hybrid core/shell nanoparticles

NASA Astrophysics Data System (ADS)

Rudenko, V.; Tolochko, A.; Zhulai, D.; Klimusheva, G.; Mirnaya, T.; Yaremchuk, G.; Asaula, V.

2018-02-01

New composites with hybrid CdSe/ZnS and Au/CdSe nanoparticles (NPs) were chemically synthesized in the thermotropic liquid crystalline phase (smectic A) of cadmium octanoate. Features of structure and nonlinear optical properties of glassy cadmium octanoate composites with hybrid core/shell NPs were studied using small-angle X-ray scattering method and Z-scan technique. Experimental optical setup (Z-scan) is based on a Nd: YAG laser, generating 9 ns pulses with a repetition rate of 0,5 Hz on a wavelength of 532 nm. The effects of the influence of hybrid NPs on the nonlinear optical properties of nanocomposites are considered in this study.

Development of the hard and soft constraints based optimisation model for unit sizing of the hybrid renewable energy system designed for microgrid applications

NASA Astrophysics Data System (ADS)

Sundaramoorthy, Kumaravel

2017-02-01

The hybrid energy systems (HESs) based electricity generation system has become a more attractive solution for rural electrification nowadays. Economically feasible and technically reliable HESs are solidly based on an optimisation stage. This article discusses about the optimal unit sizing model with the objective function to minimise the total cost of the HES. Three typical rural sites from southern part of India have been selected for the application of the developed optimisation methodology. Feasibility studies and sensitivity analysis on the optimal HES are discussed elaborately in this article. A comparison has been carried out with the Hybrid Optimization Model for Electric Renewable optimisation model for three sites. The optimal HES is found with less total net present rate and rate of energy compared with the existing method

Sentaurus® based modeling and simulation for GFET's characteristic for ssDNA immobilization and hybridization

NASA Astrophysics Data System (ADS)

Yunfang, Jia; Cheng, Ju

2016-01-01

The graphene field effect transistor (GFET) has been widely studied and developed as sensors and functional devices. The first report about GFET sensing simulation on the device level is proposed. The GFET's characteristics, its responding for single strand DNA (ssDNA) and hybridization with the complimentary DNA (cDNA) are simulated based on Sentaurus, a popular CAD tool for electronic devices. The agreement between the simulated blank GFET feature and the reported experimental data suggests the feasibility of the presented simulation method. Then the simulations of ssDNA immobilization on GFET and hybridization with its cDNA are performed, the results are discussed based on the electron transfer (ET) mechanism between DNA and graphene. Project supported by the National Natural Science Foundation of China (No. 61371028) and the Tianjin Natural Science Foundation (No. 12JCZDJC22400).

A hybrid brain-computer interface-based mail client.

PubMed

Yu, Tianyou; Li, Yuanqing; Long, Jinyi; Li, Feng

2013-01-01

Brain-computer interface-based communication plays an important role in brain-computer interface (BCI) applications; electronic mail is one of the most common communication tools. In this study, we propose a hybrid BCI-based mail client that implements electronic mail communication by means of real-time classification of multimodal features extracted from scalp electroencephalography (EEG). With this BCI mail client, users can receive, read, write, and attach files to their mail. Using a BCI mouse that utilizes hybrid brain signals, that is, motor imagery and P300 potential, the user can select and activate the function keys and links on the mail client graphical user interface (GUI). An adaptive P300 speller is employed for text input. The system has been tested with 6 subjects, and the experimental results validate the efficacy of the proposed method.

A Hybrid Brain-Computer Interface-Based Mail Client

PubMed Central

Yu, Tianyou; Li, Yuanqing; Long, Jinyi; Li, Feng

2013-01-01

Brain-computer interface-based communication plays an important role in brain-computer interface (BCI) applications; electronic mail is one of the most common communication tools. In this study, we propose a hybrid BCI-based mail client that implements electronic mail communication by means of real-time classification of multimodal features extracted from scalp electroencephalography (EEG). With this BCI mail client, users can receive, read, write, and attach files to their mail. Using a BCI mouse that utilizes hybrid brain signals, that is, motor imagery and P300 potential, the user can select and activate the function keys and links on the mail client graphical user interface (GUI). An adaptive P300 speller is employed for text input. The system has been tested with 6 subjects, and the experimental results validate the efficacy of the proposed method. PMID:23690880

Diversified models for portfolio selection based on uncertain semivariance

NASA Astrophysics Data System (ADS)

Chen, Lin; Peng, Jin; Zhang, Bo; Rosyida, Isnaini

2017-02-01

Since the financial markets are complex, sometimes the future security returns are represented mainly based on experts' estimations due to lack of historical data. This paper proposes a semivariance method for diversified portfolio selection, in which the security returns are given subjective to experts' estimations and depicted as uncertain variables. In the paper, three properties of the semivariance of uncertain variables are verified. Based on the concept of semivariance of uncertain variables, two types of mean-semivariance diversified models for uncertain portfolio selection are proposed. Since the models are complex, a hybrid intelligent algorithm which is based on 99-method and genetic algorithm is designed to solve the models. In this hybrid intelligent algorithm, 99-method is applied to compute the expected value and semivariance of uncertain variables, and genetic algorithm is employed to seek the best allocation plan for portfolio selection. At last, several numerical examples are presented to illustrate the modelling idea and the effectiveness of the algorithm.

Development of quadruped walking locomotion gait generator using a hybrid method

NASA Astrophysics Data System (ADS)

Jasni, F.; Shafie, A. A.

2013-12-01

The earth, in many areas is hardly reachable by the wheeled or tracked locomotion system. Thus, walking locomotion system is becoming a favourite option for mobile robot these days. This is because of the ability of walking locomotion to move on the rugged and unlevel terrains. However, to develop a walking locomotion gait for a robot is not a simple task. Central Pattern Generator (CPGs) method is a biological inspired method that is introduced as a method to develop the gait for the walking robot recently to tackle the issue faced by the conventional method of pre-designed trajectory based method. However, research shows that even the CPG method do have some limitations. Thus, in this paper, a hybrid method that combines CPG and the pre-designed trajectory based method is introduced to develop a walking gait for quadruped walking robot. The 3-D foot trajectories and the joint angle trajectories developed using the proposed method are compared with the data obtained via the conventional method of pre-designed trajectory to confirm the performance.

Product demand forecasts using wavelet kernel support vector machine and particle swarm optimization in manufacture system

NASA Astrophysics Data System (ADS)

Wu, Qi

2010-03-01

Demand forecasts play a crucial role in supply chain management. The future demand for a certain product is the basis for the respective replenishment systems. Aiming at demand series with small samples, seasonal character, nonlinearity, randomicity and fuzziness, the existing support vector kernel does not approach the random curve of the sales time series in the space (quadratic continuous integral space). In this paper, we present a hybrid intelligent system combining the wavelet kernel support vector machine and particle swarm optimization for demand forecasting. The results of application in car sale series forecasting show that the forecasting approach based on the hybrid PSOWv-SVM model is effective and feasible, the comparison between the method proposed in this paper and other ones is also given, which proves that this method is, for the discussed example, better than hybrid PSOv-SVM and other traditional methods.

Development of Single-Channel Hybrid BCI System Using Motor Imagery and SSVEP.

PubMed

Ko, Li-Wei; Ranga, S S K; Komarov, Oleksii; Chen, Chung-Chiang

2017-01-01

Numerous EEG-based brain-computer interface (BCI) systems that are being developed focus on novel feature extraction algorithms, classification methods and combining existing approaches to create hybrid BCIs. Several recent studies demonstrated various advantages of hybrid BCI systems in terms of an improved accuracy or number of commands available for the user. But still, BCI systems are far from realization for daily use. Having high performance with less number of channels is one of the challenging issues that persists, especially with hybrid BCI systems, where multiple channels are necessary to record information from two or more EEG signal components. Therefore, this work proposes a single-channel (C3 or C4) hybrid BCI system that combines motor imagery (MI) and steady-state visually evoked potential (SSVEP) approaches. This study demonstrates that besides MI features, SSVEP features can also be captured from C3 or C4 channel. The results show that due to rich feature information (MI and SSVEP) at these channels, the proposed hybrid BCI system outperforms both MI- and SSVEP-based systems having an average classification accuracy of 85.6 ± 7.7% in a two-class task.

Electroencephalography epilepsy classifications using hybrid cuckoo search and neural network

NASA Astrophysics Data System (ADS)

Pratiwi, A. B.; Damayanti, A.; Miswanto

2017-07-01

Epilepsy is a condition that affects the brain and causes repeated seizures. This seizure is episodes that can vary and nearly undetectable to long periods of vigorous shaking or brain contractions. Epilepsy often can be confirmed with an electrocephalography (EEG). Neural Networks has been used in biomedic signal analysis, it has successfully classified the biomedic signal, such as EEG signal. In this paper, a hybrid cuckoo search and neural network are used to recognize EEG signal for epilepsy classifications. The weight of the multilayer perceptron is optimized by the cuckoo search algorithm based on its error. The aim of this methods is making the network faster to obtained the local or global optimal then the process of classification become more accurate. Based on the comparison results with the traditional multilayer perceptron, the hybrid cuckoo search and multilayer perceptron provides better performance in term of error convergence and accuracy. The purpose methods give MSE 0.001 and accuracy 90.0 %.

An Efficient Recommendation Filter Model on Smart Home Big Data Analytics for Enhanced Living Environments.

PubMed

Chen, Hao; Xie, Xiaoyun; Shu, Wanneng; Xiong, Naixue

2016-10-15

With the rapid growth of wireless sensor applications, the user interfaces and configurations of smart homes have become so complicated and inflexible that users usually have to spend a great amount of time studying them and adapting to their expected operation. In order to improve user experience, a weighted hybrid recommender system based on a Kalman Filter model is proposed to predict what users might want to do next, especially when users are located in a smart home with an enhanced living environment. Specifically, a weight hybridization method was introduced, which combines contextual collaborative filter and the contextual content-based recommendations. This method inherits the advantages of the optimum regression and the stability features of the proposed adaptive Kalman Filter model, and it can predict and revise the weight of each system component dynamically. Experimental results show that the hybrid recommender system can optimize the distribution of weights of each component, and achieve more reasonable recall and precision rates.

An Efficient Recommendation Filter Model on Smart Home Big Data Analytics for Enhanced Living Environments

PubMed Central

Chen, Hao; Xie, Xiaoyun; Shu, Wanneng; Xiong, Naixue

2016-01-01

With the rapid growth of wireless sensor applications, the user interfaces and configurations of smart homes have become so complicated and inflexible that users usually have to spend a great amount of time studying them and adapting to their expected operation. In order to improve user experience, a weighted hybrid recommender system based on a Kalman Filter model is proposed to predict what users might want to do next, especially when users are located in a smart home with an enhanced living environment. Specifically, a weight hybridization method was introduced, which combines contextual collaborative filter and the contextual content-based recommendations. This method inherits the advantages of the optimum regression and the stability features of the proposed adaptive Kalman Filter model, and it can predict and revise the weight of each system component dynamically. Experimental results show that the hybrid recommender system can optimize the distribution of weights of each component, and achieve more reasonable recall and precision rates. PMID:27754456

Sexual Satisfaction Concept Analysis in Iranian Married Women: A Hybrid Model Study

PubMed Central

Yekta, Zohre Parsa; Raisi, Firoozeh; Ebadi, Abbas; Shahvari, Zahra

2015-01-01

Background: Sexual satisfaction is considered to be a sexual right and an important component of sexual health. The purpose of this qualitative study was to clarify the meaning and the nature of sexual satisfaction in Iranian married women, and to provide a cultural-based definition of it. Method: Sexual satisfaction was examined in three phases by the Hybrid Model of concept analysis: (1) the theoretical phase; (2) the fieldwork phase and (3) the analytical phase. Hybrid concept analysis method was chosen because its inclusion of married women’s perspectives enriches the limits of sexual health search literature. Result: The critical attributes of sexual satisfaction were investigated. They included ‘two-dimensional structure’, ‘an affective response’, ‘a means to achieve marital satisfaction’, ‘unique’, ‘a concept based on expectations’ and ‘a concept on shadow of values’. Conclusion: The concept analysis of sexual satisfaction showed some of the attributes and antecedents for this concept that, have not been mentioned in the literature. PMID:26153166

Biodegradable and adjustable sol-gel glass based hybrid scaffolds from multi-armed oligomeric building blocks.

PubMed

Kascholke, Christian; Hendrikx, Stephan; Flath, Tobias; Kuzmenka, Dzmitry; Dörfler, Hans-Martin; Schumann, Dirk; Gressenbuch, Mathias; Schulze, F Peter; Schulz-Siegmund, Michaela; Hacker, Michael C

2017-11-01

Biodegradability is a crucial characteristic to improve the clinical potential of sol-gel-derived glass materials. To this end, a set of degradable organic/inorganic class II hybrids from a tetraethoxysilane(TEOS)-derived silica sol and oligovalent cross-linker oligomers containing oligo(d,l-lactide) domains was developed and characterized. A series of 18 oligomers (Mn: 1100-3200Da) with different degrees of ethoxylation and varying length of oligoester units was established and chemical composition was determined. Applicability of an established indirect rapid prototyping method enabled fabrication of a total of 85 different hybrid scaffold formulations from 3-isocyanatopropyltriethoxysilane-functionalized macromers. In vitro degradation was analyzed over 12months and a continuous linear weight loss (0.2-0.5wt%/d) combined with only moderate material swelling was detected which was controlled by oligo(lactide) content and matrix hydrophilicity. Compressive strength (2-30MPa) and compressive modulus (44-716MPa) were determined and total content, oligo(ethylene oxide) content, oligo(lactide) content and molecular weight of the oligomeric cross-linkers as well as material porosity were identified as the main factors determining hybrid mechanics. Cytocompatibility was assessed by cell culture experiments with human adipose tissue-derived stem cells (hASC). Cell migration into the entire scaffold pore network was indicated and continuous proliferation over 14days was found. ALP activity linearly increased over 2weeks indicating osteogenic differentiation. The presented glass-based hybrid concept with precisely adjustable material properties holds promise for regenerative purposes. Adaption of degradation kinetics toward physiological relevance is still an unmet challenge of (bio-)glass engineering. We therefore present a glass-derived hybrid material with adjustable degradation. A flexible design concept based on degradable multi-armed oligomers was combined with an established indirect rapid prototyping method to produce a systematic set of porous sol-gel-derived class II hybrid scaffolds. Mechanical properties in the range of cancellous bone were narrowly controlled by hybrid composition. The oligoester introduction resulted in significantly increased compressive moduli. Cytocompatible hybrids degraded in physiologically relevant time frames and a promising linear and controllable weight loss profile was found. To our knowledge, our degradation study represents the most extensive long-term investigation of sol-gel-derived class II hybrids. Due to the broad adjustability of material properties, our concept offers potential for engineering of biodegradable hybrid materials for versatile applications. Copyright © 2017. Published by Elsevier Ltd.

Design of time interval generator based on hybrid counting method

NASA Astrophysics Data System (ADS)

Yao, Yuan; Wang, Zhaoqi; Lu, Houbing; Chen, Lian; Jin, Ge

2016-10-01

Time Interval Generators (TIGs) are frequently used for the characterizations or timing operations of instruments in particle physics experiments. Though some "off-the-shelf" TIGs can be employed, the necessity of a custom test system or control system makes the TIGs, being implemented in a programmable device desirable. Nowadays, the feasibility of using Field Programmable Gate Arrays (FPGAs) to implement particle physics instrumentation has been validated in the design of Time-to-Digital Converters (TDCs) for precise time measurement. The FPGA-TDC technique is based on the architectures of Tapped Delay Line (TDL), whose delay cells are down to few tens of picosecond. In this case, FPGA-based TIGs with high delay step are preferable allowing the implementation of customized particle physics instrumentations and other utilities on the same FPGA device. A hybrid counting method for designing TIGs with both high resolution and wide range is presented in this paper. The combination of two different counting methods realizing an integratable TIG is described in detail. A specially designed multiplexer for tap selection is emphatically introduced. The special structure of the multiplexer is devised for minimizing the different additional delays caused by the unpredictable routings from different taps to the output. A Kintex-7 FPGA is used for the hybrid counting-based implementation of a TIG, providing a resolution up to 11 ps and an interval range up to 8 s.

Brain tissue segmentation in MR images based on a hybrid of MRF and social algorithms.

PubMed

Yousefi, Sahar; Azmi, Reza; Zahedi, Morteza

2012-05-01

Effective abnormality detection and diagnosis in Magnetic Resonance Images (MRIs) requires a robust segmentation strategy. Since manual segmentation is a time-consuming task which engages valuable human resources, automatic MRI segmentations received an enormous amount of attention. For this goal, various techniques have been applied. However, Markov Random Field (MRF) based algorithms have produced reasonable results in noisy images compared to other methods. MRF seeks a label field which minimizes an energy function. The traditional minimization method, simulated annealing (SA), uses Monte Carlo simulation to access the minimum solution with heavy computation burden. For this reason, MRFs are rarely used in real time processing environments. This paper proposed a novel method based on MRF and a hybrid of social algorithms that contain an ant colony optimization (ACO) and a Gossiping algorithm which can be used for segmenting single and multispectral MRIs in real time environments. Combining ACO with the Gossiping algorithm helps find the better path using neighborhood information. Therefore, this interaction causes the algorithm to converge to an optimum solution faster. Several experiments on phantom and real images were performed. Results indicate that the proposed algorithm outperforms the traditional MRF and hybrid of MRF-ACO in speed and accuracy. Copyright © 2012 Elsevier B.V. All rights reserved.

Transparent anti-stain coatings with good thermal and mechanical properties based on polyimide-silica nanohybrids.

PubMed

Choi, Myeon-Cheon; Sung, Giju; Nagappan, Saravanan; Han, Mi-Jeong; Ha, Chang-Sik

2012-07-01

In this work, we synthesized polyimide/silica hybrid materials via sol-gel method using a fluorinated poly(amic acid) silane precursor and a variety of perfluorosilane contents. We studied the influence of a hybrid coating film with the following characteristics; hydrophobicity, oleophobicity, optical transparency, and surface hardness of the coating films. The hybrid coatings with the fluorosilane contents up to 10 wt% are optically transparent and present good thermal stability with a degradation temperature of > 500 degrees C as well as a glass transition of > 300 degrees C. Both water contact angle and oil contact angle increase rapidly with introducing small amount of the fluorosilane in the hybrids and reaches the maximum of 115 degrees and 61 degrees, respectively. The hardness of the hybrid coatings increases up to 5H with an increase of the FTES content in the hybrids. These colorless, transparent, and thermally stable hybrid materials could be suitable for applications as anti-stain coatings.

A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI

PubMed Central

Stawicki, Piotr; Gembler, Felix; Rezeika, Aya; Volosyak, Ivan

2017-01-01

Steady state visual evoked potentials (SSVEPs)-based Brain-Computer interfaces (BCIs), as well as eyetracking devices, provide a pathway for re-establishing communication for people with severe disabilities. We fused these control techniques into a novel eyetracking/SSVEP hybrid system, which utilizes eye tracking for initial rough selection and the SSVEP technology for fine target activation. Based on our previous studies, only four stimuli were used for the SSVEP aspect, granting sufficient control for most BCI users. As Eye tracking data is not used for activation of letters, false positives due to inappropriate dwell times are avoided. This novel approach combines the high speed of eye tracking systems and the high classification accuracies of low target SSVEP-based BCIs, leading to an optimal combination of both methods. We evaluated accuracy and speed of the proposed hybrid system with a 30-target spelling application implementing all three control approaches (pure eye tracking, SSVEP and the hybrid system) with 32 participants. Although the highest information transfer rates (ITRs) were achieved with pure eye tracking, a considerable amount of subjects was not able to gain sufficient control over the stand-alone eye-tracking device or the pure SSVEP system (78.13% and 75% of the participants reached reliable control, respectively). In this respect, the proposed hybrid was most universal (over 90% of users achieved reliable control), and outperformed the pure SSVEP system in terms of speed and user friendliness. The presented hybrid system might offer communication to a wider range of users in comparison to the standard techniques. PMID:28379187

A multi-domain spectral method for time-fractional differential equations

NASA Astrophysics Data System (ADS)

Chen, Feng; Xu, Qinwu; Hesthaven, Jan S.

2015-07-01

This paper proposes an approach for high-order time integration within a multi-domain setting for time-fractional differential equations. Since the kernel is singular or nearly singular, two main difficulties arise after the domain decomposition: how to properly account for the history/memory part and how to perform the integration accurately. To address these issues, we propose a novel hybrid approach for the numerical integration based on the combination of three-term-recurrence relations of Jacobi polynomials and high-order Gauss quadrature. The different approximations used in the hybrid approach are justified theoretically and through numerical examples. Based on this, we propose a new multi-domain spectral method for high-order accurate time integrations and study its stability properties by identifying the method as a generalized linear method. Numerical experiments confirm hp-convergence for both time-fractional differential equations and time-fractional partial differential equations.

Evaluation and application of an innovative method based on various chitosan composites and Lemna gibba for boron removal from drinking water.

PubMed

Türker, Onur Can; Baran, Talat

2017-06-15

Boron exists in various types of water environments, and it is difficult and costly to remove B with conventional treatment methods from drinking water. Clearly, alternative and cost effective treatment techniques are imperative. In the present study, an innovative and environment friendly method based on hybrid systems consisting of various chitosan composite beads and Lemna gibba were evaluated for removal of B from drinking water. Our results from batch adsorption experiment indicated that a plant-based chitosan composite bead has a higher capacity of B removal than mineral-based chitosan composite beads. Almost 50% of total B removal was achieved using the hybrid system based on dried Lemna-chitosan composite beads and Lemna gibba combination in 4 days. Even at the high B concentration (8mgBL -1 ), B in drinking water could be reduced to less than 2.4mgL -1 when 0.05g plant-based chitosan composite beads and 12 Lemna fronds were used for 50mL test solution. Copyright © 2017 Elsevier Ltd. All rights reserved.

System equivalent model mixing

NASA Astrophysics Data System (ADS)

Klaassen, Steven W. B.; van der Seijs, Maarten V.; de Klerk, Dennis

2018-05-01

This paper introduces SEMM: a method based on Frequency Based Substructuring (FBS) techniques that enables the construction of hybrid dynamic models. With System Equivalent Model Mixing (SEMM) frequency based models, either of numerical or experimental nature, can be mixed to form a hybrid model. This model follows the dynamic behaviour of a predefined weighted master model. A large variety of applications can be thought of, such as the DoF-space expansion of relatively small experimental models using numerical models, or the blending of different models in the frequency spectrum. SEMM is outlined, both mathematically and conceptually, based on a notation commonly used in FBS. A critical physical interpretation of the theory is provided next, along with a comparison to similar techniques; namely DoF expansion techniques. SEMM's concept is further illustrated by means of a numerical example. It will become apparent that the basic method of SEMM has some shortcomings which warrant a few extensions to the method. One of the main applications is tested in a practical case, performed on a validated benchmark structure; it will emphasize the practicality of the method.

Simplified Microarray Technique for Identifying mRNA in Rare Samples

NASA Technical Reports Server (NTRS)

Almeida, Eduardo; Kadambi, Geeta

2007-01-01

Two simplified methods of identifying messenger ribonucleic acid (mRNA), and compact, low-power apparatuses to implement the methods, are at the proof-of-concept stage of development. These methods are related to traditional methods based on hybridization of nucleic acid, but whereas the traditional methods must be practiced in laboratory settings, these methods could be practiced in field settings. Hybridization of nucleic acid is a powerful technique for detection of specific complementary nucleic acid sequences, and is increasingly being used for detection of changes in gene expression in microarrays containing thousands of gene probes. A traditional microarray study entails at least the following six steps: 1. Purification of cellular RNA, 2. Amplification of complementary deoxyribonucleic acid [cDNA] by polymerase chain reaction (PCR), 3. Labeling of cDNA with fluorophores of Cy3 (a green cyanine dye) and Cy5 (a red cyanine dye), 4. Hybridization to a microarray chip, 5. Fluorescence scanning the array(s) with dual excitation wavelengths, and 6. Analysis of the resulting images. This six-step procedure must be performed in a laboratory because it requires bulky equipment.

Identification of piecewise affine systems based on fuzzy PCA-guided robust clustering technique

NASA Astrophysics Data System (ADS)

Khanmirza, Esmaeel; Nazarahari, Milad; Mousavi, Alireza

2016-12-01

Hybrid systems are a class of dynamical systems whose behaviors are based on the interaction between discrete and continuous dynamical behaviors. Since a general method for the analysis of hybrid systems is not available, some researchers have focused on specific types of hybrid systems. Piecewise affine (PWA) systems are one of the subsets of hybrid systems. The identification of PWA systems includes the estimation of the parameters of affine subsystems and the coefficients of the hyperplanes defining the partition of the state-input domain. In this paper, we have proposed a PWA identification approach based on a modified clustering technique. By using a fuzzy PCA-guided robust k-means clustering algorithm along with neighborhood outlier detection, the two main drawbacks of the well-known clustering algorithms, i.e., the poor initialization and the presence of outliers, are eliminated. Furthermore, this modified clustering technique enables us to determine the number of subsystems without any prior knowledge about system. In addition, applying the structure of the state-input domain, that is, considering the time sequence of input-output pairs, provides a more efficient clustering algorithm, which is the other novelty of this work. Finally, the proposed algorithm has been evaluated by parameter identification of an IGV servo actuator. Simulation together with experiment analysis has proved the effectiveness of the proposed method.

A study of speech emotion recognition based on hybrid algorithm

NASA Astrophysics Data System (ADS)

Zhu, Ju-xia; Zhang, Chao; Lv, Zhao; Rao, Yao-quan; Wu, Xiao-pei

2011-10-01

To effectively improve the recognition accuracy of the speech emotion recognition system, a hybrid algorithm which combines Continuous Hidden Markov Model (CHMM), All-Class-in-One Neural Network (ACON) and Support Vector Machine (SVM) is proposed. In SVM and ACON methods, some global statistics are used as emotional features, while in CHMM method, instantaneous features are employed. The recognition rate by the proposed method is 92.25%, with the rejection rate to be 0.78%. Furthermore, it obtains the relative increasing of 8.53%, 4.69% and 0.78% compared with ACON, CHMM and SVM methods respectively. The experiment result confirms the efficiency of distinguishing anger, happiness, neutral and sadness emotional states.

Estimation of interfacial heat transfer coefficient in inverse heat conduction problems based on artificial fish swarm algorithm

NASA Astrophysics Data System (ADS)

Wang, Xiaowei; Li, Huiping; Li, Zhichao

2018-04-01

The interfacial heat transfer coefficient (IHTC) is one of the most important thermal physical parameters which have significant effects on the calculation accuracy of physical fields in the numerical simulation. In this study, the artificial fish swarm algorithm (AFSA) was used to evaluate the IHTC between the heated sample and the quenchant in a one-dimensional heat conduction problem. AFSA is a global optimization method. In order to speed up the convergence speed, a hybrid method which is the combination of AFSA and normal distribution method (ZAFSA) was presented. The IHTC evaluated by ZAFSA were compared with those attained by AFSA and the advanced-retreat method and golden section method. The results show that the reasonable IHTC is obtained by using ZAFSA, the convergence of hybrid method is well. The algorithm based on ZAFSA can not only accelerate the convergence speed, but also reduce the numerical oscillation in the evaluation of IHTC.

A set of parallel, implicit methods for a reconstructed discontinuous Galerkin method for compressible flows on 3D hybrid grids

DOE PAGES

Xia, Yidong; Luo, Hong; Frisbey, Megan; ...

2014-07-01

A set of implicit methods are proposed for a third-order hierarchical WENO reconstructed discontinuous Galerkin method for compressible flows on 3D hybrid grids. An attractive feature in these methods are the application of the Jacobian matrix based on the P1 element approximation, resulting in a huge reduction of memory requirement compared with DG (P2). Also, three approaches -- analytical derivation, divided differencing, and automatic differentiation (AD) are presented to construct the Jacobian matrix respectively, where the AD approach shows the best robustness. A variety of compressible flow problems are computed to demonstrate the fast convergence property of the implemented flowmore » solver. Furthermore, an SPMD (single program, multiple data) programming paradigm based on MPI is proposed to achieve parallelism. The numerical results on complex geometries indicate that this low-storage implicit method can provide a viable and attractive DG solution for complicated flows of practical importance.« less

Identification and handling of artifactual gene expression profiles emerging in microarray hybridization experiments

PubMed Central

Brodsky, Leonid; Leontovich, Andrei; Shtutman, Michael; Feinstein, Elena

2004-01-01

Mathematical methods of analysis of microarray hybridizations deal with gene expression profiles as elementary units. However, some of these profiles do not reflect a biologically relevant transcriptional response, but rather stem from technical artifacts. Here, we describe two technically independent but rationally interconnected methods for identification of such artifactual profiles. Our diagnostics are based on detection of deviations from uniformity, which is assumed as the main underlying principle of microarray design. Method 1 is based on detection of non-uniformity of microarray distribution of printed genes that are clustered based on the similarity of their expression profiles. Method 2 is based on evaluation of the presence of gene-specific microarray spots within the slides’ areas characterized by an abnormal concentration of low/high differential expression values, which we define as ‘patterns of differentials’. Applying two novel algorithms, for nested clustering (method 1) and for pattern detection (method 2), we can make a dual estimation of the profile’s quality for almost every printed gene. Genes with artifactual profiles detected by method 1 may then be removed from further analysis. Suspicious differential expression values detected by method 2 may be either removed or weighted according to the probabilities of patterns that cover them, thus diminishing their input in any further data analysis. PMID:14999086

Application of a hybrid model to reduce bias and improve precision in population estimates for elk (Cervus elaphus) inhabiting a cold desert ecosystem

USGS Publications Warehouse

Schoenecker, Kathryn A.; Lubow, Bruce C.

2016-01-01

Accurately estimating the size of wildlife populations is critical to wildlife management and conservation of species. Raw counts or “minimum counts” are still used as a basis for wildlife management decisions. Uncorrected raw counts are not only negatively biased due to failure to account for undetected animals, but also provide no estimate of precision on which to judge the utility of counts. We applied a hybrid population estimation technique that combined sightability modeling, radio collar-based mark-resight, and simultaneous double count (double-observer) modeling to estimate the population size of elk in a high elevation desert ecosystem. Combining several models maximizes the strengths of each individual model while minimizing their singular weaknesses. We collected data with aerial helicopter surveys of the elk population in the San Luis Valley and adjacent mountains in Colorado State, USA in 2005 and 2007. We present estimates from 7 alternative analyses: 3 based on different methods for obtaining a raw count and 4 based on different statistical models to correct for sighting probability bias. The most reliable of these approaches is a hybrid double-observer sightability model (model MH), which uses detection patterns of 2 independent observers in a helicopter plus telemetry-based detections of radio collared elk groups. Data were fit to customized mark-resight models with individual sighting covariates. Error estimates were obtained by a bootstrapping procedure. The hybrid method was an improvement over commonly used alternatives, with improved precision compared to sightability modeling and reduced bias compared to double-observer modeling. The resulting population estimate corrected for multiple sources of undercount bias that, if left uncorrected, would have underestimated the true population size by as much as 22.9%. Our comparison of these alternative methods demonstrates how various components of our method contribute to improving the final estimate and demonstrates why each is necessary.

Identifying Important Attributes for Prognostic Prediction in Traumatic Brain Injury Patients. A Hybrid Method of Decision Tree and Neural Network.

PubMed

Pourahmad, Saeedeh; Hafizi-Rastani, Iman; Khalili, Hosseinali; Paydar, Shahram

2016-10-17

Generally, traumatic brain injury (TBI) patients do not have a stable condition, particularly after the first week of TBI. Hence, indicating the attributes in prognosis through a prediction model is of utmost importance since it helps caregivers with treatment-decision options, or prepares the relatives for the most-likely outcome. This study attempted to determine and order the attributes in prognostic prediction in TBI patients, based on early clinical findings. A hybrid method was employed, which combines a decision tree (DT) and an artificial neural network (ANN) in order to improve the modeling process. The DT approach was applied as the initial analysis of the network architecture to increase accuracy in prediction. Afterwards, the ANN structure was mapped from the initial DT based on a part of the data. Subsequently, the designed network was trained and validated by the remaining data. 5-fold cross-validation method was applied to train the network. The area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, and accuracy rate were utilized as performance measures. The important attributes were then determined from the trained network using two methods: change of mean squared error (MSE), and sensitivity analysis (SA). The hybrid method offered better results compared to the DT method. The accuracy rate of 86.3 % vs. 82.2 %, sensitivity value of 55.1 % vs. 47.6 %, specificity value of 93.6 % vs. 91.1 %, and the area under the ROC curve of 0.705 vs. 0.695 were achieved for the hybrid method and DT, respectively. However, the attributes' order by DT method was more consistent with the clinical literature. The combination of different modeling methods can enhance their performance. However, it may create some complexities in computations and interpretations. The outcome of the present study could deliver some useful hints in prognostic prediction on the basis of early clinical findings for TBI patients.

Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets.

PubMed

Zhang, Jian-Hua; Xia, Jia-Jun; Garibaldi, Jonathan M; Groumpos, Petros P; Wang, Ru-Bin

2017-06-01

In human-machine (HM) hybrid control systems, human operator and machine cooperate to achieve the control objectives. To enhance the overall HM system performance, the discrete manual control task-load by the operator must be dynamically allocated in accordance with continuous-time fluctuation of psychophysiological functional status of the operator, so-called operator functional state (OFS). The behavior of the HM system is hybrid in nature due to the co-existence of discrete task-load (control) variable and continuous operator performance (system output) variable. Petri net is an effective tool for modeling discrete event systems, but for hybrid system involving discrete dynamics, generally Petri net model has to be extended. Instead of using different tools to represent continuous and discrete components of a hybrid system, this paper proposed a method of fuzzy inference Petri nets (FIPN) to represent the HM hybrid system comprising a Mamdani-type fuzzy model of OFS and a logical switching controller in a unified framework, in which the task-load level is dynamically reallocated between the operator and machine based on the model-predicted OFS. Furthermore, this paper used a multi-model approach to predict the operator performance based on three electroencephalographic (EEG) input variables (features) via the Wang-Mendel (WM) fuzzy modeling method. The membership function parameters of fuzzy OFS model for each experimental participant were optimized using artificial bee colony (ABC) evolutionary algorithm. Three performance indices, RMSE, MRE, and EPR, were computed to evaluate the overall modeling accuracy. Experiment data from six participants are analyzed. The results show that the proposed method (FIPN with adaptive task allocation) yields lower breakdown rate (from 14.8% to 3.27%) and higher human performance (from 90.30% to 91.99%). The simulation results of the FIPN-based adaptive HM (AHM) system on six experimental participants demonstrate that the FIPN framework provides an effective way to model and regulate/optimize the OFS in HM hybrid systems composed of continuous-time OFS model and discrete-event switching controller. Copyright © 2017 Elsevier B.V. All rights reserved.

Application of a hybrid method combining grey model and back propagation artificial neural networks to forecast hepatitis B in china.

PubMed

Gan, Ruijing; Chen, Xiaojun; Yan, Yu; Huang, Daizheng

2015-01-01

Accurate incidence forecasting of infectious disease provides potentially valuable insights in its own right. It is critical for early prevention and may contribute to health services management and syndrome surveillance. This study investigates the use of a hybrid algorithm combining grey model (GM) and back propagation artificial neural networks (BP-ANN) to forecast hepatitis B in China based on the yearly numbers of hepatitis B and to evaluate the method's feasibility. The results showed that the proposal method has advantages over GM (1, 1) and GM (2, 1) in all the evaluation indexes.

Ultra-tough and strong, hybrid thin films based on ionically crosslinked polymers and 2D inorganic platelets

NASA Astrophysics Data System (ADS)

Ji, Dong Hwan; Choi, Suji; Kim, Jaeyun; nanobiomaterials lab Team

Integration of high strength and toughness tend to be mutually exclusive and synthesized hybrid films with superior mechanical properties have been difficult to fabricate controllable shapes and various scales. Although diverse synthesized hybrid films consisting of organic matrix and inorganic materials with brick-and-mortar structure, show improved mechanical properties, these films are still limited in toughness and fabrication methods. Herein, we report ultra-tough and strong hybrid thin films with self-assembled uniform microstructures with controllable shapes and various scale based on hydrogel-mediated process. Ca2+-crosslinking in alginate chains and well-aligned alumina platelets in alginate matrix lead to a synergistic enhancement of strength and toughness in the resulting film. Consequentially, Ca2+-crosslinked Alg/Alu films showed outstanding toughness of 29 MJ m-3 and tensile strength of 160 MPa. Furthermore, modifying Alu surface with polyvinylpyrrolidone (PVP), tensile strength was further improved up to 200 MPa. Our results suggest an alternative approach to design and processing of self-assembled hydrogel-mediated hybrid films with outstanding mechanical properties.

Multi-component lanthanide hybrids based on zeolite A/L and zeolite A/L-polymers for tunable luminescence.

PubMed

Chen, Lei; Yan, Bing

2015-02-01

Some multi-component hybrids based on zeolite L/A are prepared. Firstly, zeolite A/L is loaded with lanthanide complexes (Eu-DBM or Tb-AA (acetylacetone = AA, dibenzoylmethane = DBM)) into its channels. Secondly, 3-methacryloyloxypropyltrimethoxysilane (γ-MPS) is used to covalently graft onto the surface of functionalized zeolite A/L (Si-[ZA/L⊃Eu-DBM(Tb-AA)]). Thirdly, lanthanide ions (Eu(3+)/Tb(3+)) are coordinated to the functionalized zeolite A/L and ligands (phen(1,10-phenanthroline) or bipy (2,2'-bipyridyl)) are introduced by a ship-in-bottle method. The inside-outside double modifications of ZA/L with lanthanide complexes afford the final hybrids and these are characterized by means of XRD, FT-IR, UV-vis DRS, SEM and luminescence spectroscopy, some of which display white or near-white light emission. Furthermore, selected above-mentioned hybrids are incorporated into PEMA/PMMA (poly ethyl methylacryate/poly methyl methacrylate) hosts to prepare luminescent polymer films. These results provide abundant data that these hybrid materials can be expected to have potential application in various practical fields.

Intercomparison of Multiscale Modeling Approaches in Simulating Subsurface Flow and Transport

NASA Astrophysics Data System (ADS)

Yang, X.; Mehmani, Y.; Barajas-Solano, D. A.; Song, H. S.; Balhoff, M.; Tartakovsky, A. M.; Scheibe, T. D.

2016-12-01

Hybrid multiscale simulations that couple models across scales are critical to advance predictions of the larger system behavior using understanding of fundamental processes. In the current study, three hybrid multiscale methods are intercompared: multiscale loose-coupling method, multiscale finite volume (MsFV) method and multiscale mortar method. The loose-coupling method enables a parallel workflow structure based on the Swift scripting environment that manages the complex process of executing coupled micro- and macro-scale models without being intrusive to the at-scale simulators. The MsFV method applies microscale and macroscale models over overlapping subdomains of the modeling domain and enforces continuity of concentration and transport fluxes between models via restriction and prolongation operators. The mortar method is a non-overlapping domain decomposition approach capable of coupling all permutations of pore- and continuum-scale models with each other. In doing so, Lagrange multipliers are used at interfaces shared between the subdomains so as to establish continuity of species/fluid mass flux. Subdomain computations can be performed either concurrently or non-concurrently depending on the algorithm used. All the above methods have been proven to be accurate and efficient in studying flow and transport in porous media. However, there has not been any field-scale applications and benchmarking among various hybrid multiscale approaches. To address this challenge, we apply all three hybrid multiscale methods to simulate water flow and transport in a conceptualized 2D modeling domain of the hyporheic zone, where strong interactions between groundwater and surface water exist across multiple scales. In all three multiscale methods, fine-scale simulations are applied to a thin layer of riverbed alluvial sediments while the macroscopic simulations are used for the larger subsurface aquifer domain. Different numerical coupling methods are then applied between scales and inter-compared. Comparisons are drawn in terms of velocity distributions, solute transport behavior, algorithm-induced numerical error and computing cost. The intercomparison work provides support for confidence in a variety of hybrid multiscale methods and motivates further development and applications.

Development of performance specifications for hybrid modeling of floating wind turbines in wave basin tests

DOE PAGES

Hall, Matthew; Goupee, Andrew; Jonkman, Jason

2017-08-24

Hybrid modeling—combining physical testing and numerical simulation in real time$-$opens new opportunities in floating wind turbine research. Wave basin testing is an important validation step for floating support structure design, but the conventional approaches that use physical wind above the basin are limited by scaling problems in the aerodynamics. Applying wind turbine loads with an actuation system that is controlled by a simulation responding to the basin test in real time offers a way to avoid scaling problems and reduce cost barriers for floating wind turbine design validation in realistic coupled wind and wave conditions. This paper demonstrates the developmentmore » of performance specifications for a system that couples a wave basin experiment with a wind turbine simulation. Two different points for the hybrid coupling are considered: the tower-base interface and the aero-rotor interface (the boundary between aerodynamics and the rotor structure). Analyzing simulations of three floating wind turbine designs across seven load cases reveals the motion and force requirements of the coupling system. By simulating errors in the hybrid coupling system, the sensitivity of the floating wind turbine response to coupling quality can be quantified. The sensitivity results can then be used to determine tolerances for motion tracking errors, force actuation errors, bandwidth limitations, and latency in the hybrid coupling system. These tolerances can guide the design of hybrid coupling systems to achieve desired levels of accuracy. An example demonstrates how the developed methods can be used to generate performance specifications for a system at 1:50 scale. Results show that sensitivities vary significantly between support structure designs and that coupling at the aero-rotor interface has less stringent requirements than those for coupling at the tower base. As a result, the methods and results presented here can inform design of future hybrid coupling systems and enhance understanding of how test results are affected by hybrid coupling quality.« less

Development of performance specifications for hybrid modeling of floating wind turbines in wave basin tests

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

Hall, Matthew; Goupee, Andrew; Jonkman, Jason

Hybrid modeling—combining physical testing and numerical simulation in real time$-$opens new opportunities in floating wind turbine research. Wave basin testing is an important validation step for floating support structure design, but the conventional approaches that use physical wind above the basin are limited by scaling problems in the aerodynamics. Applying wind turbine loads with an actuation system that is controlled by a simulation responding to the basin test in real time offers a way to avoid scaling problems and reduce cost barriers for floating wind turbine design validation in realistic coupled wind and wave conditions. This paper demonstrates the developmentmore » of performance specifications for a system that couples a wave basin experiment with a wind turbine simulation. Two different points for the hybrid coupling are considered: the tower-base interface and the aero-rotor interface (the boundary between aerodynamics and the rotor structure). Analyzing simulations of three floating wind turbine designs across seven load cases reveals the motion and force requirements of the coupling system. By simulating errors in the hybrid coupling system, the sensitivity of the floating wind turbine response to coupling quality can be quantified. The sensitivity results can then be used to determine tolerances for motion tracking errors, force actuation errors, bandwidth limitations, and latency in the hybrid coupling system. These tolerances can guide the design of hybrid coupling systems to achieve desired levels of accuracy. An example demonstrates how the developed methods can be used to generate performance specifications for a system at 1:50 scale. Results show that sensitivities vary significantly between support structure designs and that coupling at the aero-rotor interface has less stringent requirements than those for coupling at the tower base. As a result, the methods and results presented here can inform design of future hybrid coupling systems and enhance understanding of how test results are affected by hybrid coupling quality.« less

Automated hybridization/imaging device for fluorescent multiplex DNA sequencing

DOEpatents

Weiss, R.B.; Kimball, A.W.; Gesteland, R.F.; Ferguson, F.M.; Dunn, D.M.; Di Sera, L.J.; Cherry, J.L.

1995-11-28

A method is disclosed for automated multiplex sequencing of DNA with an integrated automated imaging hybridization chamber system. This system comprises an hybridization chamber device for mounting a membrane containing size-fractionated multiplex sequencing reaction products, apparatus for fluid delivery to the chamber device, imaging apparatus for light delivery to the membrane and image recording of fluorescence emanating from the membrane while in the chamber device, and programmable controller apparatus for controlling operation of the system. The multiplex reaction products are hybridized with a probe, the enzyme (such as alkaline phosphatase) is bound to a binding moiety on the probe, and a fluorogenic substrate (such as a benzothiazole derivative) is introduced into the chamber device by the fluid delivery apparatus. The enzyme converts the fluorogenic substrate into a fluorescent product which, when illuminated in the chamber device with a beam of light from the imaging apparatus, excites fluorescence of the fluorescent product to produce a pattern of hybridization. The pattern of hybridization is imaged by a CCD camera component of the imaging apparatus to obtain a series of digital signals. These signals are converted by the controller apparatus into a string of nucleotides corresponding to the nucleotide sequence an automated sequence reader. The method and apparatus are also applicable to other membrane-based applications such as colony and plaque hybridization and Southern, Northern, and Western blots. 9 figs.

Automated hybridization/imaging device for fluorescent multiplex DNA sequencing

DOEpatents

Weiss, Robert B.; Kimball, Alvin W.; Gesteland, Raymond F.; Ferguson, F. Mark; Dunn, Diane M.; Di Sera, Leonard J.; Cherry, Joshua L.

1995-01-01

A method is disclosed for automated multiplex sequencing of DNA with an integrated automated imaging hybridization chamber system. This system comprises an hybridization chamber device for mounting a membrane containing size-fractionated multiplex sequencing reaction products, apparatus for fluid delivery to the chamber device, imaging apparatus for light delivery to the membrane and image recording of fluorescence emanating from the membrane while in the chamber device, and programmable controller apparatus for controlling operation of the system. The multiplex reaction products are hybridized with a probe, then an enzyme (such as alkaline phosphatase) is bound to a binding moiety on the probe, and a fluorogenic substrate (such as a benzothiazole derivative) is introduced into the chamber device by the fluid delivery apparatus. The enzyme converts the fluorogenic substrate into a fluorescent product which, when illuminated in the chamber device with a beam of light from the imaging apparatus, excites fluorescence of the fluorescent product to produce a pattern of hybridization. The pattern of hybridization is imaged by a CCD camera component of the imaging apparatus to obtain a series of digital signals. These signals are converted by the controller apparatus into a string of nucleotides corresponding to the nucleotide sequence an automated sequence reader. The method and apparatus are also applicable to other membrane-based applications such as colony and plaque hybridization and Southern, Northern, and Western blots.

Highly sensitive electrochemical detection of human telomerase activity based on bio-barcode method.

PubMed

Li, Ying; Liu, Bangwei; Li, Xia; Wei, Qingli

2010-07-15

In the present study, an electrochemical method for highly sensitive detection of human telomerase activity was developed based on bio-barcode amplification assay. Telomerase was extracted from HeLa cells, then the extract was mixed with telomerase substrate (TS) primer to perform extension reaction. The extension product was hybridized with the capture DNA immobilized on the Au electrode and then reacted with the signal DNA on Au nanoparticles to form a sandwich hybridization mode. Electrochemical signals were generated by chronocoulometric interrogation of [Ru(NH(3))(6)](3+) that quantitatively binds to the DNA on Au nanoparticles via electrostatic interaction. This method can detect the telomerase activity from as little as 10 cultured cancer cells without the polymerase chain reaction (PCR) amplification of telomerase extension product. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Hybrid Differential Dynamic Programming with Stochastic Search

NASA Technical Reports Server (NTRS)

Aziz, Jonathan; Parker, Jeffrey; Englander, Jacob

2016-01-01

Differential dynamic programming (DDP) has been demonstrated as a viable approach to low-thrust trajectory optimization, namely with the recent success of NASAs Dawn mission. The Dawn trajectory was designed with the DDP-based Static Dynamic Optimal Control algorithm used in the Mystic software. Another recently developed method, Hybrid Differential Dynamic Programming (HDDP) is a variant of the standard DDP formulation that leverages both first-order and second-order state transition matrices in addition to nonlinear programming (NLP) techniques. Areas of improvement over standard DDP include constraint handling, convergence properties, continuous dynamics, and multi-phase capability. DDP is a gradient based method and will converge to a solution nearby an initial guess. In this study, monotonic basin hopping (MBH) is employed as a stochastic search method to overcome this limitation, by augmenting the HDDP algorithm for a wider search of the solution space.

A survey of hybrid Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Saeed, Adnan S.; Younes, Ahmad Bani; Cai, Chenxiao; Cai, Guowei

2018-04-01

This article presents a comprehensive overview on the recent advances of miniature hybrid Unmanned Aerial Vehicles (UAVs). For now, two conventional types, i.e., fixed-wing UAV and Vertical Takeoff and Landing (VTOL) UAV, dominate the miniature UAVs. Each type has its own inherent limitations on flexibility, payload, flight range, cruising speed, takeoff and landing requirements and endurance. Enhanced popularity and interest are recently gained by the newer type, named hybrid UAV, that integrates the beneficial features of both conventional ones. In this survey paper, a systematic categorization method for the hybrid UAV's platform designs is introduced, first presenting the technical features and representative examples. Next, the hybrid UAV's flight dynamics model and flight control strategies are explained addressing several representative modeling and control work. In addition, key observations, existing challenges and conclusive remarks based on the conducted review are discussed accordingly.

Discrete stochastic simulation methods for chemically reacting systems.

PubMed

Cao, Yang; Samuels, David C

2009-01-01

Discrete stochastic chemical kinetics describe the time evolution of a chemically reacting system by taking into account the fact that, in reality, chemical species are present with integer populations and exhibit some degree of randomness in their dynamical behavior. In recent years, with the development of new techniques to study biochemistry dynamics in a single cell, there are increasing studies using this approach to chemical kinetics in cellular systems, where the small copy number of some reactant species in the cell may lead to deviations from the predictions of the deterministic differential equations of classical chemical kinetics. This chapter reviews the fundamental theory related to stochastic chemical kinetics and several simulation methods based on that theory. We focus on nonstiff biochemical systems and the two most important discrete stochastic simulation methods: Gillespie's stochastic simulation algorithm (SSA) and the tau-leaping method. Different implementation strategies of these two methods are discussed. Then we recommend a relatively simple and efficient strategy that combines the strengths of the two methods: the hybrid SSA/tau-leaping method. The implementation details of the hybrid strategy are given here and a related software package is introduced. Finally, the hybrid method is applied to simple biochemical systems as a demonstration of its application.

Degradation of ciprofloxacin antibiotic by Homogeneous Fenton oxidation: Hybrid AHP-PROMETHEE method, optimization, biodegradability improvement and identification of oxidized by-products.

PubMed

Salari, Marjan; Rakhshandehroo, Gholam Reza; Nikoo, Mohammad Reza

2018-09-01

The main purpose of this experimental study was to optimize Homogeneous Fenton oxidation (HFO) and identification of oxidized by-products from degradation of Ciprofloxacin (CIP) using hybrid AHP-PROMETHEE, Response Surface Methodology (RSM) and High Performance Liquid Chromatography coupled with Mass Spectrometry (HPLC-MS). At the first step, an assessment was made for performances of two catalysts (FeSO 4 ·7H 2 O and FeCl 2 ·4H 2 O) based on hybrid AHP-PROMETHEE decision making method. Then, RSM was utilized to examine and optimize the influence of different variables including initial CIP concentration, Fe 2+ concentration, [H 2 O 2 ]/[ Fe 2+ ] mole ratio and initial pH as independent variables on CIP removal, COD removal, and sludge to iron (SIR) as the response functions in a reaction time of 25 min. Weights of the mentioned responses as well as cost criteria were determined by AHP model based on pairwise comparison and then used as inputs to PROMETHEE method to develop hybrid AHP-PROMETHEE. Based on net flow results of this hybrid model, FeCl 2 ·4H 2 O was more efficient because of its less environmental stability as well as lower SIR production. Then, optimization of experiments using Central Composite Design (CCD) under RSM was performed with the FeCl 2 ·4H 2 O catalyst. Biodegradability of wastewater was determined in terms of BOD 5 /COD ratio, showing that HFO process is able to improve wastewater biodegradability from zero to 0.42. Finally, the main intermediaries of degradation and degradation pathways of CIP were investigated with (HPLC-MS). Major degradation pathways from hydroxylation of both piperazine and quinolonic rings, oxidation and cleavage of the piperazine ring, and defluorination (OH/F substitution) were suggested. Copyright © 2018 Elsevier Ltd. All rights reserved.

Assignment of Alzheimer's presenilin-2 (PS-2) gene to 1q42.1 by fluorescence in situ hybridization.

PubMed

Takano, T; Sahara, N; Yamanouchi, Y; Mori, H

1997-01-17

Presenilin-2 (PS-2) was suggested to be localized on 1q31-42 based on linkage analysis and cDNA cloning. The final identification of PS-2 as the causal gene for early-onset familial Alzheimer's disease in Voga-German pedigrees was concluded based on the point mutation found in the candidate cDNA isolated from this familial AD. We present evidence of its physical genome mapping of PS-2 on chromosome 1q42.1 by fluorescence in situ hybridization method.

The system design and performance test of hybrid vertical axis wind turbine

NASA Astrophysics Data System (ADS)

Dwiyantoro, Bambang Arip; Suphandani, Vivien

2017-04-01

Vertical axis wind turbine is a tool that is being developed to generate energy from wind. One cause is still little use of wind energy is the design of wind turbines that are less precise. Therefore in this study will be developed the system design of hybrid vertical axis wind turbine and tested performance with experimental methods. The design of hybrid turbine based on a straight bladed Darrieus turbine along with a double step Savonius turbine. The method used to design wind turbines is by studying literature, analyzing the critical parts of a wind turbine and the structure of the optimal design. Wind turbine prototype of the optimal design characteristic tests in the wind tunnel experimentally by varying the speed of the wind. From the experimental results show that the greater the wind speed, the greater the wind turbine rotation and torque is raised. The hybrid vertical axis wind turbine has much better self-starting and better conversion efficiency.

Pose Invariant Face Recognition Based on Hybrid Dominant Frequency Features

NASA Astrophysics Data System (ADS)

Wijaya, I. Gede Pasek Suta; Uchimura, Keiichi; Hu, Zhencheng

Face recognition is one of the most active research areas in pattern recognition, not only because the face is a human biometric characteristics of human being but also because there are many potential applications of the face recognition which range from human-computer interactions to authentication, security, and surveillance. This paper presents an approach to pose invariant human face image recognition. The proposed scheme is based on the analysis of discrete cosine transforms (DCT) and discrete wavelet transforms (DWT) of face images. From both the DCT and DWT domain coefficients, which describe the facial information, we build compact and meaningful features vector, using simple statistical measures and quantization. This feature vector is called as the hybrid dominant frequency features. Then, we apply a combination of the L2 and Lq metric to classify the hybrid dominant frequency features to a person's class. The aim of the proposed system is to overcome the high memory space requirement, the high computational load, and the retraining problems of previous methods. The proposed system is tested using several face databases and the experimental results are compared to a well-known Eigenface method. The proposed method shows good performance, robustness, stability, and accuracy without requiring geometrical normalization. Furthermore, the purposed method has low computational cost, requires little memory space, and can overcome retraining problem.

Hybrid Adaptive Flight Control with Model Inversion Adaptation

NASA Technical Reports Server (NTRS)

Nguyen, Nhan

2011-01-01

This study investigates a hybrid adaptive flight control method as a design possibility for a flight control system that can enable an effective adaptation strategy to deal with off-nominal flight conditions. The hybrid adaptive control blends both direct and indirect adaptive control in a model inversion flight control architecture. The blending of both direct and indirect adaptive control provides a much more flexible and effective adaptive flight control architecture than that with either direct or indirect adaptive control alone. The indirect adaptive control is used to update the model inversion controller by an on-line parameter estimation of uncertain plant dynamics based on two methods. The first parameter estimation method is an indirect adaptive law based on the Lyapunov theory, and the second method is a recursive least-squares indirect adaptive law. The model inversion controller is therefore made to adapt to changes in the plant dynamics due to uncertainty. As a result, the modeling error is reduced that directly leads to a decrease in the tracking error. In conjunction with the indirect adaptive control that updates the model inversion controller, a direct adaptive control is implemented as an augmented command to further reduce any residual tracking error that is not entirely eliminated by the indirect adaptive control.

Characterization of the complete mitochondrial genome of the hybrid Epinephelus moara♀ × Epinephelus lanceolatus♂, and phylogenetic analysis in subfamily epinephelinae

NASA Astrophysics Data System (ADS)

Gao, Fengtao; Wei, Min; Zhu, Ying; Guo, Hua; Chen, Songlin; Yang, Guanpin

2017-06-01

This study presents the complete mitochondrial genome of the hybrid Epinephelus moara♀× Epinephelus lanceolatus♂. The genome is 16886 bp in length, and contains 13 protein-coding genes, 2 rRNA genes, 22 tRNA genes, a light-strand replication origin and a control region. Additionally, phylogenetic analysis based on the nucleotide sequences of 13 conserved protein-coding genes using the maximum likelihood method indicated that the mitochondrial genome is maternally inherited. This study presents genomic data for studying phylogenetic relationships and breeding of hybrid Epinephelinae.

Spin-polarized electron transport in hybrid graphene-BN nanoribbons

NASA Astrophysics Data System (ADS)

Gao, Song; Lu, Wei; Zheng, Guo-Hui; Jia, Yalei; Ke, San-Huang

2017-05-01

The experimental realization of hybrid graphene and h-BN provides a new way to modify the electronic and transport properties of graphene-based materials. In this work, we investigate the spin-polarized electron transport in hybrid graphene-BN zigzag nanoribbons by performing first-principles nonequilibrium Green’s function method calculations. A 100% spin-polarized electron transport in a large energy window around the Fermi level is found and this behavior is independent of the ribbon width as long as there contain 3 zigzag carbon chains. This behavior may be useful in making perfect spin filters.

Modeling and control of a hybrid-electric vehicle for drivability and fuel economy improvements

NASA Astrophysics Data System (ADS)

Koprubasi, Kerem

The gradual decline of oil reserves and the increasing demand for energy over the past decades has resulted in automotive manufacturers seeking alternative solutions to reduce the dependency on fossil-based fuels for transportation. A viable technology that enables significant improvements in the overall tank-to-wheel vehicle energy conversion efficiencies is the hybridization of electrical and conventional drive systems. Sophisticated hybrid powertrain configurations require careful coordination of the actuators and the onboard energy sources for optimum use of the energy saving benefits. The term optimality is often associated with fuel economy, although other measures such as drivability and exhaust emissions are also equally important. This dissertation focuses on the design of hybrid-electric vehicle (HEV) control strategies that aim to minimize fuel consumption while maintaining good vehicle drivability. In order to facilitate the design of controllers based on mathematical models of the HEV system, a dynamic model that is capable of predicting longitudinal vehicle responses in the low-to-mid frequency region (up to 10 Hz) is developed for a parallel HEV configuration. The model is validated using experimental data from various driving modes including electric only, engine only and hybrid. The high fidelity of the model makes it possible to accurately identify critical drivability issues such as time lags, shunt, shuffle, torque holes and hesitation. Using the information derived from the vehicle model, an energy management strategy is developed and implemented on a test vehicle. The resulting control strategy has a hybrid structure in the sense that the main mode of operation (the hybrid mode) is occasionally interrupted by event-based rules to enable the use of the engine start-stop function. The changes in the driveline dynamics during this transition further contribute to the hybrid nature of the system. To address the unique characteristics of the HEV drivetrain and to ensure smooth vehicle operation during mode changes, a special control method is developed. This method is generalized to a broad class of switched systems in which the switching conditions are state dependent or are supervised. The control approach involves partitioning the state-space such that the control law is modified as the state trajectory approaches a switching set and the state is steered to a location within the partition with low transitioning cost. Away from the partitions that contain switching sets, the controller is designed to achieve any suitable control objective. In the case of the HEV control problem, this objective generally involves minimizing fuel consumption. Finally, the experimental verification of this control method is illustrated using the application that originally motivated the development of this approach: the control of a HEV driveline during the transition from electric only to hybrid mode.

Hybrid multiscale modeling and prediction of cancer cell behavior.

PubMed

Zangooei, Mohammad Hossein; Habibi, Jafar

2017-01-01

Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems. In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for prediction of cell phenotypes. By using a proposed Q-learning based on SVR-NSGA-II method, the cells have the capability to predict their phenotypes autonomously that is, to act on its own without external direction in response to situations it encounters. Computational simulations of the model were performed in order to analyze its performance. The most striking feature of our results is that each cell can select its phenotype at each time step according to its condition. We provide evidence that the prediction of cell phenotypes is reliable. Our proposed model, which we term a hybrid multiscale modeling of cancer cell behavior, has the potential to combine the best features of both continuum and discrete models. The in silico results indicate that the 3D model can represent key features of cancer growth, angiogenesis, and its related micro-environment and show that the findings are in good agreement with biological tumor behavior. To the best of our knowledge, this paper is the first hybrid vascular multiscale modeling of cancer cell behavior that has the capability to predict cell phenotypes individually by a self-generated dataset.

Visual discrimination of dihydroxybenzene isomers based on a nitrogen-doped graphene quantum dot-silver nanoparticle hybrid

NASA Astrophysics Data System (ADS)

Shi, Bingfang; Su, Yubin; Zhao, Jingjin; Liu, Rongjun; Zhao, Yan; Zhao, Shulin

2015-10-01

A room temperature reducing agent-free strategy for the synthesis of a nitrogen-doped graphene quantum dot-silver nanoparticle (N-GQD/AgNP) hybrid was presented. In this strategy, N-GQDs were used as a reducing agent and stabilizer for the formation of the N-GQD/AgNP hybrid, and the formation of the N-GQD/AgNP hybrid may result from the extraordinary reduction properties of N-GQDs, which are attributed to the nature of the surface oxygen-containing functional groups. The N-GQD/AgNP hybrid exhibits good dispersity and outstanding catalytic ability toward the oxidation of catechol (CC) and hydroquinone (HQ) by Ag+. In the presence of the N-GQD/AgNP hybrid, the reduction of Ag+ by CC and HQ was improved. CC enhanced the absorbance of the N-GQD/AgNP-Ag+ system the most, and HQ followed, while resorcinol (RC) had only a little effect on the absorption intensity of the system. Thus, a sensitive and selective colorimetric sensing method based on the N-GQD/AgNP-Ag+ system was developed for the discrimination of CC, HQ and RC. A good linear relationship was obtained from 0.1 to 15.0 μM for CC and from 0.3 to 20.0 μM for HQ. The detection limits of CC and HQ were 0.03 and 0.1 μM, respectively. In addition, the proposed method also shows a high selectivity for the detection of CC and HQ, and appreciable changes in color of the N-GQD/AgNP-Ag+ system toward CC, RC and HQ were observed.A room temperature reducing agent-free strategy for the synthesis of a nitrogen-doped graphene quantum dot-silver nanoparticle (N-GQD/AgNP) hybrid was presented. In this strategy, N-GQDs were used as a reducing agent and stabilizer for the formation of the N-GQD/AgNP hybrid, and the formation of the N-GQD/AgNP hybrid may result from the extraordinary reduction properties of N-GQDs, which are attributed to the nature of the surface oxygen-containing functional groups. The N-GQD/AgNP hybrid exhibits good dispersity and outstanding catalytic ability toward the oxidation of catechol (CC) and hydroquinone (HQ) by Ag+. In the presence of the N-GQD/AgNP hybrid, the reduction of Ag+ by CC and HQ was improved. CC enhanced the absorbance of the N-GQD/AgNP-Ag+ system the most, and HQ followed, while resorcinol (RC) had only a little effect on the absorption intensity of the system. Thus, a sensitive and selective colorimetric sensing method based on the N-GQD/AgNP-Ag+ system was developed for the discrimination of CC, HQ and RC. A good linear relationship was obtained from 0.1 to 15.0 μM for CC and from 0.3 to 20.0 μM for HQ. The detection limits of CC and HQ were 0.03 and 0.1 μM, respectively. In addition, the proposed method also shows a high selectivity for the detection of CC and HQ, and appreciable changes in color of the N-GQD/AgNP-Ag+ system toward CC, RC and HQ were observed. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr04659a

Solid-phase supports for the in situ assembly of quantum dot-FRET hybridization assays in channel microfluidics.

PubMed

Tavares, Anthony J; Noor, M Omair; Uddayasankar, Uvaraj; Krull, Ulrich J; Vannoy, Charles H

2014-01-01

Semiconductor quantum dots (QDs) have long served as integral components in signal transduction modalities such as Förster resonance energy transfer (FRET). The majority of bioanalytical methods using QDs for FRET-based techniques simply monitor binding-induced conformational changes. In more recent work, QDs have been incorporated into solid-phase support systems, such as microfluidic chips, to serve as physical platforms in the development of functional biosensors and bioprobes. Herein, we describe a simple strategy for the transduction of nucleic acid hybridization that combines a novel design method based on FRET with an electrokinetically controlled microfluidic technology, and that offers further potential for amelioration of sample-handling issues and for simplification of dynamic stringency control.

Transfer of a Mycobacterium tuberculosis genotyping method, Spoligotyping, from a reverse line-blot hybridization, membrane-based assay to the Luminex multianalyte profiling system.

PubMed

Cowan, Lauren S; Diem, Lois; Brake, Mary Catherine; Crawford, Jack T

2004-01-01

Spoligotyping using Luminex technology was shown to be a highly reproducible method suitable for high-throughput analysis. Spoligotyping of 48 isolates using the traditional membrane-based assay and the Luminex assay yielded concordant results for all isolates. The Luminex platform provides greater flexibility and cost effectiveness than the membrane-based assay.

Hybrid modeling method for a DEP based particle manipulation.

PubMed

Miled, Mohamed Amine; Gagne, Antoine; Sawan, Mohamad

2013-01-30

In this paper, a new modeling approach for Dielectrophoresis (DEP) based particle manipulation is presented. The proposed method fulfills missing links in finite element modeling between the multiphysic simulation and the biological behavior. This technique is amongst the first steps to develop a more complex platform covering several types of manipulations such as magnetophoresis and optics. The modeling approach is based on a hybrid interface using both ANSYS and MATLAB to link the propagation of the electrical field in the micro-channel to the particle motion. ANSYS is used to simulate the electrical propagation while MATLAB interprets the results to calculate cell displacement and send the new information to ANSYS for another turn. The beta version of the proposed technique takes into account particle shape, weight and its electrical properties. First obtained results are coherent with experimental results.

Hybrid Modeling Method for a DEP Based Particle Manipulation

PubMed Central

Miled, Mohamed Amine; Gagne, Antoine; Sawan, Mohamad

2013-01-01

In this paper, a new modeling approach for Dielectrophoresis (DEP) based particle manipulation is presented. The proposed method fulfills missing links in finite element modeling between the multiphysic simulation and the biological behavior. This technique is amongst the first steps to develop a more complex platform covering several types of manipulations such as magnetophoresis and optics. The modeling approach is based on a hybrid interface using both ANSYS and MATLAB to link the propagation of the electrical field in the micro-channel to the particle motion. ANSYS is used to simulate the electrical propagation while MATLAB interprets the results to calculate cell displacement and send the new information to ANSYS for another turn. The beta version of the proposed technique takes into account particle shape, weight and its electrical properties. First obtained results are coherent with experimental results. PMID:23364197

A hybrid robust fault tolerant control based on adaptive joint unscented Kalman filter.

PubMed

Shabbouei Hagh, Yashar; Mohammadi Asl, Reza; Cocquempot, Vincent

2017-01-01

In this paper, a new hybrid robust fault tolerant control scheme is proposed. A robust H ∞ control law is used in non-faulty situation, while a Non-Singular Terminal Sliding Mode (NTSM) controller is activated as soon as an actuator fault is detected. Since a linear robust controller is designed, the system is first linearized through the feedback linearization method. To switch from one controller to the other, a fuzzy based switching system is used. An Adaptive Joint Unscented Kalman Filter (AJUKF) is used for fault detection and diagnosis. The proposed method is based on the simultaneous estimation of the system states and parameters. In order to show the efficiency of the proposed scheme, a simulated 3-DOF robotic manipulator is used. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Identification of inelastic parameters based on deep drawing forming operations using a global-local hybrid Particle Swarm approach

NASA Astrophysics Data System (ADS)

Vaz, Miguel; Luersen, Marco A.; Muñoz-Rojas, Pablo A.; Trentin, Robson G.

2016-04-01

Application of optimization techniques to the identification of inelastic material parameters has substantially increased in recent years. The complex stress-strain paths and high nonlinearity, typical of this class of problems, require the development of robust and efficient techniques for inverse problems able to account for an irregular topography of the fitness surface. Within this framework, this work investigates the application of the gradient-based Sequential Quadratic Programming method, of the Nelder-Mead downhill simplex algorithm, of Particle Swarm Optimization (PSO), and of a global-local PSO-Nelder-Mead hybrid scheme to the identification of inelastic parameters based on a deep drawing operation. The hybrid technique has shown to be the best strategy by combining the good PSO performance to approach the global minimum basin of attraction with the efficiency demonstrated by the Nelder-Mead algorithm to obtain the minimum itself.

Combining the Best of Two Standard Setting Methods: The Ordered Item Booklet Angoff

ERIC Educational Resources Information Center

Smith, Russell W.; Davis-Becker, Susan L.; O'Leary, Lisa S.

2014-01-01

This article describes a hybrid standard setting method that combines characteristics of the Angoff (1971) and Bookmark (Mitzel, Lewis, Patz & Green, 2001) methods. The proposed approach utilizes strengths of each method while addressing weaknesses. An ordered item booklet, with items sorted based on item difficulty, is used in combination…

Hybrid finite element method for describing the electrical response of biological cells to applied fields.

PubMed

Ying, Wenjun; Henriquez, Craig S

2007-04-01

A novel hybrid finite element method (FEM) for modeling the response of passive and active biological membranes to external stimuli is presented. The method is based on the differential equations that describe the conservation of electric flux and membrane currents. By introducing the electric flux through the cell membrane as an additional variable, the algorithm decouples the linear partial differential equation part from the nonlinear ordinary differential equation part that defines the membrane dynamics of interest. This conveniently results in two subproblems: a linear interface problem and a nonlinear initial value problem. The linear interface problem is solved with a hybrid FEM. The initial value problem is integrated by a standard ordinary differential equation solver such as the Euler and Runge-Kutta methods. During time integration, these two subproblems are solved alternatively. The algorithm can be used to model the interaction of stimuli with multiple cells of almost arbitrary geometries and complex ion-channel gating at the plasma membrane. Numerical experiments are presented demonstrating the uses of the method for modeling field stimulation and action potential propagation.

Preparation of SnS2 colloidal quantum dots and their application in organic/inorganic hybrid solar cells

PubMed Central

2011-01-01

Dispersive SnS2 colloidal quantum dots have been synthesized via hot-injection method. Hybrid photovoltaic devices based on blends of a conjugated polymer poly[2-methoxy-5-(3",7"dimethyloctyloxy)-1,4-phenylenevinylene] (MDMO-PPV) as electron donor and crystalline SnS2 quantum dots as electron acceptor have been studied. Photoluminescence measurement has been performed to study the surfactant effect on the excitons splitting process. The photocurrent of solar cells with the hybrid depends greatly on the ligands exchange as well as the device heat treatment. AFM characterization has demonstrated morphology changes happening upon surfactant replacement and annealing, which can explain the performance variation of hybrid solar cells. PMID:21711811

Applications of Synthetic Microchannel and Nanopore Systems

NASA Astrophysics Data System (ADS)

Hinkle, Thomas Preston

This thesis describes research conducted on the physics and applications of micro- and nanoscale ion-conducting channels. Making use of the nanoscale physics that takes place in the vicinity of charged surfaces, there is the possibility that nanopores, holes on the order of 1 nm in size, could be used to make complex integrated ionic circuits. For inspiration on what such circuits could achieve we only need to look to biology systems, immensely complex machines that at their most basic level require precise control of ions and intercellular electric potentials to function. In order to contribute to the ever expanding field of nanopore research, we engineered novel hybrid insulator-conductor nanopores that behave analagously to ionic diodes, which allow passage of current flow in one direction but severely limit the current in the opposite direction. The experiments revealed that surface polarization of the conducting material can induce the formation of an electrical double layer in the same way static surface charges can. Furthermore, we showed that the hybrid device behaved similar to an ionic diode, and could see potential use as a standard rectifying element in ionic circuits. Another application based on ion conducting channels is resistive pulse sensing, a single particle detection and characterization method. We present three main experiments that expand the capacity of resistive pulse sensing for particle characterization. First, we demonstrate how resistive pulse sensing in pores with longitudinal irregularities can be used to measure the lengths of individual nanoparticles. Then, we describe an entirely new hybrid approach to resistive pulse sensing, whereby the electrical measurements are combined with simultaneous optical imaging. The hybrid method allows for validation of the resistive pulse signals and will greatly contribute to their interpretability. We present experiments that explore some of the possibilities of the hybrid method. Then, building off the hybrid method we present experiments performed to measure single particle deformability with resistive pulse sensing. Using a novel microfluidic channel design, we were able to reproducibily induce bidirectional deformation of cells. We describe how these deformations could be detected with the resistive pulse signal alone, paving the way for resistive pulse sensing based cell deformability cytometers.

Facile preparation of well-combined lignin-based carbon/ZnO hybrid composite with excellent photocatalytic activity

NASA Astrophysics Data System (ADS)

Wang, Huan; Qiu, Xueqing; Liu, Weifeng; Yang, Dongjie

2017-12-01

In this work, a novel lignin-based carbon/ZnO (LC/ZnO) hybrid composite with excellent photocatalytic performance was prepared through a convenient and environment friendly method using alkali lignin (AL) as carbon source. The morphological, microstructure and optical properties of the as-prepared LC/ZnO hybrid composite was characterized with scanning electron microscope (SEM), X-ray diffraction (XRD), Raman and UV-vis. The resulting LC/ZnO hybrid is composed of highly dispersed ZnO nanoparticles embedded on a lignin-based carbon nanosheet, showing excellent photogenerated electrons and holes separation and migration efficiency. The photocatalytic activity of LC/ZnO was much higher than the pure ZnO. The LC/ZnO hybrid composite showed different photocatalytic mechanism for degradation of negative methyl orange (MO) and positive Rhodamine B (RhB). It showed that h+ was the main photocatalytic active group during the degradation of MO, ·O2- and ·OH were the photocatalytic active groups during degradation of RhB. This reported photocatalyst with selective degradation of positive and negative organic dyes may have a great application prospect for photoelectric conversion and catalytic materials. Results of this work were of practical importance for high-valued utilization of lignin for carbon materials.

Synthesis, spectroscopic and catalytic properties of some new boron hybrid molecule derivatives by BF2 and BPh2 chelation

NASA Astrophysics Data System (ADS)

Kilic, Ahmet; Alcay, Ferhat; Aydemir, Murat; Durgun, Mustafa; Keles, Armagan; Baysal, Akın

2015-05-01

A new series of Schiff base ligands (L1-L3) and their corresponding fluorine/phenyl boron hybrid complexes [LnBF2] and [LnBPh2] (n = 1, 2 or 3) have been synthesized and well characterized by both analytical and spectroscopic methods. The Schiff base ligands and their corresponding fluorine/phenyl boron hybrid complexes have been characterized by NMR (1H, 13C and 19F), FT-IR, UV-Vis, LC-MS, and fluorescence spectroscopy as well as melting point and elemental analysis. The fluorescence efficiencies of phenyl chelate complexes are greatly red-shifted compared to those of the fluorine chelate analogs based on the same ligands, presumably due to the large steric hindrance and hard π → π∗ transition of the diphenyl boron chelation, which can effectively prevent molecular aggregation. The boron hybrid complexes were applied to the transfer hydrogenation of acetophenone derivatives to 1-phenylethanol derivatives in the presence of 2-propanol as the hydrogen source. The catalytic studies showed that boron hybrid complexes are good catalytic precursors for transfer hydrogenation of aromatic ketones in 0.1 M iso-PrOH solution. Also, we have found that both steric and electronic factors have a significant impact on the catalytic properties of this class of molecules.

Ultra-Small Dualband Dualmode Microstrip Antenna Based on Novel Hybrid Resonator

NASA Astrophysics Data System (ADS)

Zhu, Ji-Xu; Bai, Peng; Zheng, Hao-Zhong

2016-11-01

A novel hybrid resonator consists of right handed patch+composite right and left handed transmission line (RH+CRLH) is proposed for the first time aiming at both compactness and frequency manipulation. A demonstration with theoretical dispersion relations and EM simulation is provided for the correctness and efficiency. According to the new method, an ultra-small and dualband antenna operating around 2.4 GHz (n=0, Bluetooth band) and 3.5 GHz (n=+1, Wimax band) is designed, fabricated and measured, whose occupied area is only of 0.158 λ_0. Numerical and experimental results indicate that the antenna exhibits a good impendence match, low cross-polarization and comparable radiation gains in both bands. Excellent performances of the antennas based on hybrid resonators predict promising applications in multifunction wireless communication systems.

A hybrid method for evaluating enterprise architecture implementation.

PubMed

Nikpay, Fatemeh; Ahmad, Rodina; Yin Kia, Chiam

2017-02-01

Enterprise Architecture (EA) implementation evaluation provides a set of methods and practices for evaluating the EA implementation artefacts within an EA implementation project. There are insufficient practices in existing EA evaluation models in terms of considering all EA functions and processes, using structured methods in developing EA implementation, employing matured practices, and using appropriate metrics to achieve proper evaluation. The aim of this research is to develop a hybrid evaluation method that supports achieving the objectives of EA implementation. To attain this aim, the first step is to identify EA implementation evaluation practices. To this end, a Systematic Literature Review (SLR) was conducted. Second, the proposed hybrid method was developed based on the foundation and information extracted from the SLR, semi-structured interviews with EA practitioners, program theory evaluation and Information Systems (ISs) evaluation. Finally, the proposed method was validated by means of a case study and expert reviews. This research provides a suitable foundation for researchers who wish to extend and continue this research topic with further analysis and exploration, and for practitioners who would like to employ an effective and lightweight evaluation method for EA projects. Copyright © 2016 Elsevier Ltd. All rights reserved.

Design of Passive Power Filter for Hybrid Series Active Power Filter using Estimation, Detection and Classification Method

NASA Astrophysics Data System (ADS)

Swain, Sushree Diptimayee; Ray, Pravat Kumar; Mohanty, K. B.

2016-06-01

This research paper discover the design of a shunt Passive Power Filter (PPF) in Hybrid Series Active Power Filter (HSAPF) that employs a novel analytic methodology which is superior than FFT analysis. This novel approach consists of the estimation, detection and classification of the signals. The proposed method is applied to estimate, detect and classify the power quality (PQ) disturbance such as harmonics. This proposed work deals with three methods: the harmonic detection through wavelet transform method, the harmonic estimation by Kalman Filter algorithm and harmonic classification by decision tree method. From different type of mother wavelets in wavelet transform method, the db8 is selected as suitable mother wavelet because of its potency on transient response and crouched oscillation at frequency domain. In harmonic compensation process, the detected harmonic is compensated through Hybrid Series Active Power Filter (HSAPF) based on Instantaneous Reactive Power Theory (IRPT). The efficacy of the proposed method is verified in MATLAB/SIMULINK domain and as well as with an experimental set up. The obtained results confirm the superiority of the proposed methodology than FFT analysis. This newly proposed PPF is used to make the conventional HSAPF more robust and stable.

Feedforward-Feedback Hybrid Control for Magnetic Shape Memory Alloy Actuators Based on the Krasnosel'skii-Pokrovskii Model

PubMed Central

Zhou, Miaolei; Zhang, Qi; Wang, Jingyuan

2014-01-01

As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system. PMID:24828010

Feedforward-feedback hybrid control for magnetic shape memory alloy actuators based on the Krasnosel'skii-Pokrovskii model.

PubMed

Zhou, Miaolei; Zhang, Qi; Wang, Jingyuan

2014-01-01

As a new type of smart material, magnetic shape memory alloy has the advantages of a fast response frequency and outstanding strain capability in the field of microdrive and microposition actuators. The hysteresis nonlinearity in magnetic shape memory alloy actuators, however, limits system performance and further application. Here we propose a feedforward-feedback hybrid control method to improve control precision and mitigate the effects of the hysteresis nonlinearity of magnetic shape memory alloy actuators. First, hysteresis nonlinearity compensation for the magnetic shape memory alloy actuator is implemented by establishing a feedforward controller which is an inverse hysteresis model based on Krasnosel'skii-Pokrovskii operator. Secondly, the paper employs the classical Proportion Integration Differentiation feedback control with feedforward control to comprise the hybrid control system, and for further enhancing the adaptive performance of the system and improving the control accuracy, the Radial Basis Function neural network self-tuning Proportion Integration Differentiation feedback control replaces the classical Proportion Integration Differentiation feedback control. Utilizing self-learning ability of the Radial Basis Function neural network obtains Jacobian information of magnetic shape memory alloy actuator for the on-line adjustment of parameters in Proportion Integration Differentiation controller. Finally, simulation results show that the hybrid control method proposed in this paper can greatly improve the control precision of magnetic shape memory alloy actuator and the maximum tracking error is reduced from 1.1% in the open-loop system to 0.43% in the hybrid control system.

Method of Identifying a Base in a Nucleic Acid

DOEpatents

Fodor, Stephen P. A.; Lipshutz, Robert J.; Huang, Xiaohua

1999-01-01

Devices and techniques for hybridization of nucleic acids and for determining the sequence of nucleic acids. Arrays of nucleic acids are formed by techniques, preferably high resolution, light-directed techniques. Positions of hybridization of a target nucleic acid are determined by, e.g., epifluorescence microscopy. Devices and techniques are proposed to determine the sequence of a target nucleic acid more efficiently and more quickly through such synthesis and detection techniques.

Assessing the performance of self-consistent hybrid functional for band gap calculation in oxide semiconductors

NASA Astrophysics Data System (ADS)

He, Jiangang; Franchini, Cesare

2017-11-01

In this paper we assess the predictive power of the self-consistent hybrid functional scPBE0 in calculating the band gap of oxide semiconductors. The computational procedure is based on the self-consistent evaluation of the mixing parameter α by means of an iterative calculation of the static dielectric constant using the perturbation expansion after discretization method and making use of the relation \

3D-2D registration in endovascular image-guided surgery: evaluation of state-of-the-art methods on cerebral angiograms.

PubMed

Mitrović, Uroš; Likar, Boštjan; Pernuš, Franjo; Špiclin, Žiga

2018-02-01

Image guidance for minimally invasive surgery is based on spatial co-registration and fusion of 3D pre-interventional images and treatment plans with the 2D live intra-interventional images. The spatial co-registration or 3D-2D registration is the key enabling technology; however, the performance of state-of-the-art automated methods is rather unclear as they have not been assessed under the same test conditions. Herein we perform a quantitative and comparative evaluation of ten state-of-the-art methods for 3D-2D registration on a public dataset of clinical angiograms. Image database consisted of 3D and 2D angiograms of 25 patients undergoing treatment for cerebral aneurysms or arteriovenous malformations. On each of the datasets, highly accurate "gold-standard" registrations of 3D and 2D images were established based on patient-attached fiducial markers. The database was used to rigorously evaluate ten state-of-the-art 3D-2D registration methods, namely two intensity-, two gradient-, three feature-based and three hybrid methods, both for registration of 3D pre-interventional image to monoplane or biplane 2D images. Intensity-based methods were most accurate in all tests (0.3 mm). One of the hybrid methods was most robust with 98.75% of successful registrations (SR) and capture range of 18 mm for registrations of 3D to biplane 2D angiograms. In general, registration accuracy was similar whether registration of 3D image was performed onto mono- or biplanar 2D images; however, the SR was substantially lower in case of 3D to monoplane 2D registration. Two feature-based and two hybrid methods had clinically feasible execution times in the order of a second. Performance of methods seems to fall below expectations in terms of robustness in case of registration of 3D to monoplane 2D images, while translation into clinical image guidance systems seems readily feasible for methods that perform registration of the 3D pre-interventional image onto biplanar intra-interventional 2D images.

Hybrid Optimal Design of the Eco-Hydrological Wireless Sensor Network in the Middle Reach of the Heihe River Basin, China

PubMed Central

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-01-01

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables. PMID:25317762

A short-term and high-resolution distribution system load forecasting approach using support vector regression with hybrid parameters optimization

DOE PAGES

Jiang, Huaiguang; Zhang, Yingchen; Muljadi, Eduard; ...

2016-01-01

This paper proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of themore » hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system. The performance of the proposed approach is compared to some classic methods in later sections of the paper.« less

Hybrid optimal design of the eco-hydrological wireless sensor network in the middle reach of the Heihe River Basin, China.

PubMed

Kang, Jian; Li, Xin; Jin, Rui; Ge, Yong; Wang, Jinfeng; Wang, Jianghao

2014-10-14

The eco-hydrological wireless sensor network (EHWSN) in the middle reaches of the Heihe River Basin in China is designed to capture the spatial and temporal variability and to estimate the ground truth for validating the remote sensing productions. However, there is no available prior information about a target variable. To meet both requirements, a hybrid model-based sampling method without any spatial autocorrelation assumptions is developed to optimize the distribution of EHWSN nodes based on geostatistics. This hybrid model incorporates two sub-criteria: one for the variogram modeling to represent the variability, another for improving the spatial prediction to evaluate remote sensing productions. The reasonability of the optimized EHWSN is validated from representativeness, the variogram modeling and the spatial accuracy through using 15 types of simulation fields generated with the unconditional geostatistical stochastic simulation. The sampling design shows good representativeness; variograms estimated by samples have less than 3% mean error relative to true variograms. Then, fields at multiple scales are predicted. As the scale increases, estimated fields have higher similarities to simulation fields at block sizes exceeding 240 m. The validations prove that this hybrid sampling method is effective for both objectives when we do not know the characteristics of an optimized variables.

A Hybrid Numerical Method for Turbulent Mixing Layers. Degree awarded by Case Western Reserve Univ.

NASA Technical Reports Server (NTRS)

Georgiadis, Nicholas J.

2001-01-01

A hybrid method has been developed for simulations of compressible turbulent mixing layers. Such mixing layers dominate the flows in exhaust systems of modern day aircraft and also those of hypersonic vehicles currently under development. The method configurations in which a dominant structural feature provides an unsteady mechanism to drive the turbulent development in the mixing layer. The hybrid method uses a Reynolds-averaged Navier-Stokes (RANS) procedure to calculate wall bounded regions entering a mixing section, and a Large Eddy Simulation (LES) procedure to calculate the mixing dominated regions. A numerical technique was developed to enable the use of the hybrid RANS-LES method on stretched, non-Cartesian grids. Closure for the RANS equations was obtained using the Cebeci-Smith algebraic turbulence model in conjunction with the wall-function approach of Ota and Goldberg. The wall-function approach enabled a continuous computational grid from the RANS regions to the LES region. The LES equations were closed using the Smagorinsky subgrid scale model. The hybrid RANS-LES method is applied to a benchmark compressible mixing layer experiment. Preliminary two dimensional calculations are used to investigate the effects of axial grid density and boundary conditions. Vortex shedding from the base region of a splitter plate separating the upstream flows was observed to eventually transition to turbulence. The location of the transition, however, was much further downstream than indicated by experiments. Actual LES calculations, performed in three spatial directions, also indicated vortex shedding, but the transition to turbulence was found to occur much closer to the beginning of the mixing section. which is in agreement with experimental observations. These calculations demonstrated that LES simulations must be performed in three dimensions. Comparisons of time-averaged axial velocities and turbulence intensities indicated reasonable agreement with experimental data.

A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data.

PubMed

Song, Hongchao; Jiang, Zhuqing; Men, Aidong; Yang, Bo

2017-01-01

Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE) and an ensemble k -nearest neighbor graphs- ( K -NNG-) based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity.

A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data

PubMed Central

Jiang, Zhuqing; Men, Aidong; Yang, Bo

2017-01-01

Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE) and an ensemble k-nearest neighbor graphs- (K-NNG-) based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity. PMID:29270197

An electrochemical genosensor for Salmonella typhi on gold nanoparticles-mercaptosilane modified screen printed electrode.

PubMed

Das, Ritu; Sharma, Mukesh K; Rao, Vepa K; Bhattacharya, B K; Garg, Iti; Venkatesh, V; Upadhyay, Sanjay

2014-10-20

In this work, we fabricated a system of integrated self-assembled layer of organosilane 3-mercaptopropyltrimethoxy silane (MPTS) on the screen printed electrode (SPE) and electrochemically deposited gold nanoparticle for Salmonella typhi detection employing Vi gene as a molecular marker. Thiolated DNA probe was immobilized on a gold nanoparticle (AuNP) modified SPE for DNA hybridization assay using methylene blue as redox (electroactive) hybridization indicator, and signal was monitored by differential pulse voltammetry (DPV) method. The modified SPE was characterized by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and atomic force microscopy (AFM) method. The DNA biosensor showed excellent performances with high sensitivity and good selectivity. The current response was linear with the target sequence concentrations ranging from 1.0 × 10(-11) to 0.5 × 10(-8)M and the detection limit was found to be 50 (± 2.1)pM. The DNA biosensor showed good discrimination ability to the one-base, two-base and three-base mismatched sequences. The fabricated genosensor could also be regenerated easily and reused for three to four times for further hybridization studies. Copyright © 2014 Elsevier B.V. All rights reserved.

Hybrid perturbation methods based on statistical time series models

NASA Astrophysics Data System (ADS)

San-Juan, Juan Félix; San-Martín, Montserrat; Pérez, Iván; López, Rosario

2016-04-01

In this work we present a new methodology for orbit propagation, the hybrid perturbation theory, based on the combination of an integration method and a prediction technique. The former, which can be a numerical, analytical or semianalytical theory, generates an initial approximation that contains some inaccuracies derived from the fact that, in order to simplify the expressions and subsequent computations, not all the involved forces are taken into account and only low-order terms are considered, not to mention the fact that mathematical models of perturbations not always reproduce physical phenomena with absolute precision. The prediction technique, which can be based on either statistical time series models or computational intelligence methods, is aimed at modelling and reproducing missing dynamics in the previously integrated approximation. This combination results in the precision improvement of conventional numerical, analytical and semianalytical theories for determining the position and velocity of any artificial satellite or space debris object. In order to validate this methodology, we present a family of three hybrid orbit propagators formed by the combination of three different orders of approximation of an analytical theory and a statistical time series model, and analyse their capability to process the effect produced by the flattening of the Earth. The three considered analytical components are the integration of the Kepler problem, a first-order and a second-order analytical theories, whereas the prediction technique is the same in the three cases, namely an additive Holt-Winters method.

Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model

NASA Astrophysics Data System (ADS)

Pathak, Jaideep; Wikner, Alexander; Fussell, Rebeckah; Chandra, Sarthak; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

2018-04-01

A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training data), without prior knowledge of the system dynamics. The motivation for this paper is the potential of machine learning for filling in the gaps in our underlying mechanistic knowledge that cause widely-used knowledge-based models to be inaccurate. Thus, we here propose a general method that leverages the advantages of these two approaches by combining a knowledge-based model and a machine learning technique to build a hybrid forecasting scheme. Potential applications for such an approach are numerous (e.g., improving weather forecasting). We demonstrate and test the utility of this approach using a particular illustrative version of a machine learning known as reservoir computing, and we apply the resulting hybrid forecaster to a low-dimensional chaotic system, as well as to a high-dimensional spatiotemporal chaotic system. These tests yield extremely promising results in that our hybrid technique is able to accurately predict for a much longer period of time than either its machine-learning component or its model-based component alone.

A hybrid hydrologically complemented warning model for shallow landslides induced by extreme rainfall in Korean Mountain

NASA Astrophysics Data System (ADS)

Singh Pradhan, Ananta Man; Kang, Hyo-Sub; Kim, Yun-Tae

2016-04-01

This study uses a physically based approach to evaluate the factor of safety of the hillslope for different hydrological conditions, in Mt Umyeon, south of Seoul. The hydrological conditions were determined using intensity and duration of whole Korea of known landslide inventory data. Quantile regression statistical method was used to ascertain different probability warning levels on the basis of rainfall thresholds. Physically based models are easily interpreted and have high predictive capabilities but rely on spatially explicit and accurate parameterization, which is commonly not possible. Statistical probabilistic methods can include other causative factors which influence the slope stability such as forest, soil and geology, but rely on good landslide inventories of the site. In this study a hybrid approach has described that combines the physically-based landslide susceptibility for different hydrological conditions. A presence-only based maximum entropy model was used to hybrid and analyze relation of landslide with conditioning factors. About 80% of the landslides were listed among the unstable sites identified in the proposed model, thereby presenting its effectiveness and accuracy in determining unstable areas and areas that require evacuation. These cumulative rainfall thresholds provide a valuable reference to guide disaster prevention authorities in the issuance of warning levels with the ability to reduce losses and save lives.

Occasional hybridization between a native and invasive Senecio species in Australia is unlikely to contribute to invasive success.

PubMed

Dormontt, Eleanor E; Prentis, Peter J; Gardner, Michael G; Lowe, Andrew J

2017-01-01

Hybridization between native and invasive species can facilitate introgression of native genes that increase invasive potential by providing exotic species with pre-adapted genes suitable for new environments. In this study we assessed the outcome of hybridization between native Senecio pinnatifolius var. pinnatifolius A.Rich. (dune ecotype) and invasive Senecio madagascariensis Poir. to investigate the potential for introgression of adaptive genes to have facilitated S. madagascariensis spread in Australia. We used amplified fragment length polymorphisms (141 loci) and nuclear microsatellites (2 loci) to genotype a total of 118 adults and 223 seeds from S. pinnatifolius var. pinnatifolius and S. madagascariensis at one allopatric and two shared sites. We used model based clustering and assignment methods to establish whether hybrid seed set and mature hybrids occur in the field. We detected no adult hybrids in any population. Low incidence of hybrid seed set was found at Lennox Head where the contact zone overlapped for 20 m (6% and 22% of total seeds sampled for S. pinnatifolius var. pinnatifolius and S. madagascariensis respectively). One hybrid seed was detected at Ballina where a gap of approximately 150 m was present between species (2% of total seeds sampled for S. madagascariensis ). We found no evidence of adult hybrid plants at two shared sites. Hybrid seed set from both species was identified at low levels. Based on these findings we conclude that introgression of adaptive genes from S. pinnatifolius var. pinnatifolius is unlikely to have facilitated S. madagascariensis invasions in Australia. Revisitation of one site after two years could find no remaining S. pinnatifolius var.  pinnatifolius , suggesting that contact zones between these species are dynamic and that S. pinnatifolius var.  pinnatifolius may be at risk of displacement by S. madagascariensis in coastal areas.

The electronic structure of Au25 clusters: between discrete and continuous

NASA Astrophysics Data System (ADS)

Katsiev, Khabiboulakh; Lozova, Nataliya; Wang, Lu; Sai Krishna, Katla; Li, Ruipeng; Mei, Wai-Ning; Skrabalak, Sara E.; Kumar, Challa S. S. R.; Losovyj, Yaroslav

2016-08-01

Here, an approach based on synchrotron resonant photoemission is employed to explore the transition between quantization and hybridization of the electronic structure in atomically precise ligand-stabilized nanoparticles. While the presence of ligands maintains quantization in Au25 clusters, their removal renders increased hybridization of the electronic states in the vicinity of the Fermi level. These observations are supported by DFT studies.Here, an approach based on synchrotron resonant photoemission is employed to explore the transition between quantization and hybridization of the electronic structure in atomically precise ligand-stabilized nanoparticles. While the presence of ligands maintains quantization in Au25 clusters, their removal renders increased hybridization of the electronic states in the vicinity of the Fermi level. These observations are supported by DFT studies. Electronic supplementary information (ESI) available: Experimental details including chemicals, sample preparation, and characterization methods. Computation techniques, SV-AUC, GIWAXS, XPS, UPS, MALDI-TOF, ESI data of Au25 clusters. See DOI: 10.1039/c6nr02374f

A hybrid degradation tendency measurement method for mechanical equipment based on moving window and Grey-Markov model

NASA Astrophysics Data System (ADS)

Jiang, Wei; Zhou, Jianzhong; Zheng, Yang; Liu, Han

2017-11-01

Accurate degradation tendency measurement is vital for the secure operation of mechanical equipment. However, the existing techniques and methodologies for degradation measurement still face challenges, such as lack of appropriate degradation indicator, insufficient accuracy, and poor capability to track the data fluctuation. To solve these problems, a hybrid degradation tendency measurement method for mechanical equipment based on a moving window and Grey-Markov model is proposed in this paper. In the proposed method, a 1D normalized degradation index based on multi-feature fusion is designed to assess the extent of degradation. Subsequently, the moving window algorithm is integrated with the Grey-Markov model for the dynamic update of the model. Two key parameters, namely the step size and the number of states, contribute to the adaptive modeling and multi-step prediction. Finally, three types of combination prediction models are established to measure the degradation trend of equipment. The effectiveness of the proposed method is validated with a case study on the health monitoring of turbine engines. Experimental results show that the proposed method has better performance, in terms of both measuring accuracy and data fluctuation tracing, in comparison with other conventional methods.

De-optical-line-terminal hybrid access-aggregation optical network for time-sensitive services based on software-defined networking orchestration

NASA Astrophysics Data System (ADS)

Bai, Wei; Yang, Hui; Xiao, Hongyun; Yu, Ao; He, Linkuan; Zhang, Jie; Li, Zhen; Du, Yi

2017-11-01

With the increase in varieties of services in network, time-sensitive services (TSSs) appear and bring forward an impending need for delay performance. Ultralow-latency communication has become one of the important development goals for many scenarios in the coming 5G era (e.g., robotics and driverless cars). However, the conventional methods, which decrease delay by promoting the available resources and the network transmission speed, have limited effect; a new breakthrough for ultralow-latency communication is necessary. We propose a de-optical-line-terminal (De-OLT) hybrid access-aggregation optical network (DAON) for TSS based on software-defined networking (SDN) orchestration. In this network, low-latency all-optical communication based on optical burst switching can be achieved by removing OLT. For supporting this network and guaranteeing the quality of service for TSSs, we design SDN-driven control method and service provision method. Numerical results demonstrate the proposed DAON promotes network service efficiency and avoids traffic congestion.

Identifying Degenerative Brain Disease Using Rough Set Classifier Based on Wavelet Packet Method.

PubMed

Cheng, Ching-Hsue; Liu, Wei-Xiang

2018-05-28

Population aging has become a worldwide phenomenon, which causes many serious problems. The medical issues related to degenerative brain disease have gradually become a concern. Magnetic Resonance Imaging is one of the most advanced methods for medical imaging and is especially suitable for brain scans. From the literature, although the automatic segmentation method is less laborious and time-consuming, it is restricted in several specific types of images. In addition, hybrid techniques segmentation improves the shortcomings of the single segmentation method. Therefore, this study proposed a hybrid segmentation combined with rough set classifier and wavelet packet method to identify degenerative brain disease. The proposed method is a three-stage image process method to enhance accuracy of brain disease classification. In the first stage, this study used the proposed hybrid segmentation algorithms to segment the brain ROI (region of interest). In the second stage, wavelet packet was used to conduct the image decomposition and calculate the feature values. In the final stage, the rough set classifier was utilized to identify the degenerative brain disease. In verification and comparison, two experiments were employed to verify the effectiveness of the proposed method and compare with the TV-seg (total variation segmentation) algorithm, Discrete Cosine Transform, and the listing classifiers. Overall, the results indicated that the proposed method outperforms the listing methods.

Enhancing the Performance of Perovskite Solar Cells by Hybridizing SnS Quantum Dots with CH3 NH3 PbI3.

PubMed

Han, Jianhua; Yin, Xuewen; Nan, Hui; Zhou, Yu; Yao, Zhibo; Li, Jianbao; Oron, Dan; Lin, Hong

2017-08-01

The combination of perovskite solar cells and quantum dot solar cells has significant potential due to the complementary nature of the two constituent materials. In this study, solar cells (SCs) with a hybrid CH 3 NH 3 PbI 3 /SnS quantum dots (QDs) absorber layer are fabricated by a facile and universal in situ crystallization method, enabling easy embedding of the QDs in perovskite layer. Compared with SCs based on CH 3 NH 3 PbI 3 , SCs using CH 3 NH 3 PbI 3 /SnS QDs hybrid films as absorber achieves a 25% enhancement in efficiency, giving rise to an efficiency of 16.8%. The performance improvement can be attributed to the improved crystallinity of the absorber, enhanced photo-induced carriers' separation and transport within the absorber layer, and improved incident light utilization. The generality of the methods used in this work paves a universal pathway for preparing other perovskite/QDs hybrid materials and the synthesis of entire nontoxic perovskite/QDs hybrid structure. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of an optimized protocol for the detection of classical swine fever virus in formalin-fixed, paraffin-embedded tissues by seminested reverse transcription-polymerase chain reaction and comparison with in situ hybridization.

PubMed

Ha, S-K; Choi, C; Chae, C

2004-10-01

An optimized protocol was developed for the detection of classical swine fever virus (CSFV) in formalin-fixed, paraffin-embedded tissues obtained from experimentally and naturally infected pigs by seminested reverse transcription-polymerase chain reaction (RT-PCR). The results for seminested RT-PCR were compared with those determined by in situ hybridization. The results obtained show that the use of deparaffinization with xylene, digestion with proteinase K, extraction with Trizol LS, followed by seminested RT-PCR is a reliable detection method. An increase in sensitivity was observed as amplicon size decreased. The highest sensitivity for RT-PCR on formalin-fixed, paraffin-embedded tissues RNA was obtained with amplicon sizes less than approximately 200 base pairs. An hybridization signal for CSFV was detected in lymph nodes from 12 experimentally and 12 naturally infected pigs. The sensitivity of seminested RT-PCR compared with in situ hybridization was 100% for CSFV. When only formalin-fixed tissues are available, seminested RT-PCR and in situ hybridization would be useful diagnostic methods for the detection of CSFV nucleic acid.

EMSE at TREC 2015 Clinical Decision Support Track

DTIC Science & Technology

2015-11-20

pseudo relevant documents, semantic ressources of UMLS , and a hybrid approach called SMERA that combines LSI and UMLS based approaches. Only three of...approach to query expansion uses ontologies ( UMLS ) and a lo- cal approach based on pseudo relevant feedback documents using LSI. A brief description of...pseudo relevance feedback documents, and a semantic method based on UMLS concepts. The LSI-based method was used only to expand summary terms that can’t

Hybrid microfluidics combined with active and passive approaches for continuous cell separation.

PubMed

Yan, Sheng; Zhang, Jun; Yuan, Dan; Li, Weihua

2017-01-01

Microfluidics, which is classified as either active or passive, is capable of separating cells of interest from a complex and heterogeneous sample. Active methods utilise external fields such as electric, magnetic, acoustic, and optical to drive cells for separation, while passive methods utilise channel structures, intrinsic hydrodynamic forces, and steric hindrances to manipulate cells. However, when processing complex biological samples such as whole blood with rare cells, separation with a single module microfluidic device is difficult. Hybrid microfluidics is an emerging technique, which utilises active and passive methods whilst fulfilling higher requirements for stable performance, versatility, and convenience, including (i) the ability to process multi-target cells, (ii) enhanced ability for multiplexed separation, (iii) higher sensitivity, and (iv) tunability for a wider operational range. This review introduces the fundamental physics and typical formats for subclasses of hybrid microfluidic devices based on their different physical fields; presents current examples of cell sorting to highlight the advantage and usefulness of hybrid microfluidics on biomedicine, and then discusses the challenges and perspective of future development and the promising direction of research in this field. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Overcoming the errors of in-house PCR used in the clinical laboratory for the diagnosis of extrapulmonary tuberculosis.

PubMed

Kunakorn, M; Raksakai, K; Pracharktam, R; Sattaudom, C

1999-03-01

Our experiences from 1993 to 1997 in the development and use of IS6110 base PCR for the diagnosis of extrapulmonary tuberculosis in a routine clinical setting revealed that error-correcting processes can improve existing diagnostic methodology. The reamplification method initially used had a sensitivity of 90.91% and a specificity of 93.75%. The concern was focused on the false positive results of this method caused by product-carryover contamination. This method was changed to single round PCR with carryover prevention by uracil DNA glycosylase (UDG), resulting in a 100% specificity but only 63% sensitivity. Dot blot hybridization was added after the single round PCR, increasing the sensitivity to 87.50%. However, false positivity resulted from the nonspecific dot blot hybridization signal, reducing the specificity to 89.47%. The hybridization of PCR was changed to a Southern blot with a new oligonucleotide probe giving the sensitivity of 85.71% and raising the specificity to 99.52%. We conclude that the PCR protocol for routine clinical use should include UDG for carryover prevention and hybridization with specific probes to optimize diagnostic sensitivity and specificity in extrapulmonary tuberculosis testing.

Fast and Non-Toxic In Situ Hybridization without Blocking of Repetitive Sequences

PubMed Central

Matthiesen, Steen H.; Hansen, Charles M.

2012-01-01

Formamide is the preferred solvent to lower the melting point and annealing temperature of nucleic acid strands in in situ hybridization (ISH). A key benefit of formamide is better preservation of morphology due to a lower incubation temperature. However, in fluorescence in situ hybridization (FISH), against unique DNA targets in tissue sections, an overnight hybridization is required to obtain sufficient signal intensity. Here, we identified alternative solvents and developed a new hybridization buffer that reduces the required hybridization time to one hour (IQFISH method). Remarkably, denaturation and blocking against repetitive DNA sequences to prevent non-specific binding is not required. Furthermore, the new hybridization buffer is less hazardous than formamide containing buffers. The results demonstrate a significant increased hybridization rate at a lowered denaturation and hybridization temperature for both DNA and PNA (peptide nucleic acid) probes. We anticipate that these formamide substituting solvents will become the foundation for changes in the understanding and performance of denaturation and hybridization of nucleic acids. For example, the process time for tissue-based ISH for gene aberration tests in cancer diagnostics can be reduced from days to a few hours. Furthermore, the understanding of the interactions and duplex formation of nucleic acid strands may benefit from the properties of these solvents. PMID:22911704

Myocardial matrix-polyethylene glycol hybrid hydrogels for tissue engineering

NASA Astrophysics Data System (ADS)

Grover, Gregory N.; Rao, Nikhil; Christman, Karen L.

2014-01-01

Similar to other protein-based hydrogels, extracellular matrix (ECM) based hydrogels, derived from decellularized tissues, have a narrow range of mechanical properties and are rapidly degraded. These hydrogels contain natural cellular adhesion sites, form nanofibrous networks similar to native ECM, and are biodegradable. In this study, we expand the properties of these types of materials by incorporating poly(ethylene glycol) (PEG) into the ECM network. We use decellularized myocardial matrix as an example of a tissue specific ECM derived hydrogel. Myocardial matrix-PEG hybrids were synthesized by two different methods, cross-linking the proteins with an amine-reactive PEG-star and photo-induced radical polymerization of two different multi-armed PEG-acrylates. We show that both methods allow for conjugation of PEG to the myocardial matrix by gel electrophoresis and infrared spectroscopy. Scanning electron microscopy demonstrated that the hybrid materials still contain a nanofibrous network similar to unmodified myocardial matrix and that the fiber diameter is changed by the method of PEG incorporation and PEG molecular weight. PEG conjugation also decreased the rate of enzymatic degradation in vitro, and increased material stiffness. Hybrids synthesized with amine-reactive PEG had gelation rates of 30 min, similar to the unmodified myocardial matrix, and incorporation of PEG did not prevent cell adhesion and migration through the hydrogels, thus offering the possibility to have an injectable ECM hydrogel that degrades more slowly in vivo. The photo-polymerized radical systems gelled in 4 min upon irradiation, allowing 3D encapsulation and culture of cells, unlike the soft unmodified myocardial matrix. This work demonstrates that PEG incorporation into ECM-based hydrogels can expand material properties, thereby opening up new possibilities for in vitro and in vivo applications.

Polymer-lipid hybrid nanoparticles as enhanced indomethacin delivery systems.

PubMed

Dalmoro, Annalisa; Bochicchio, Sabrina; Nasibullin, Shamil F; Bertoncin, Paolo; Lamberti, Gaetano; Barba, Anna Angela; Moustafine, Rouslan I

2018-05-17

Non-steroidal anti-inflammatory drugs (NSAIDs), i.e. indomethacin used for rheumatoid arthritis and non-rheumatoid inflammatory diseases, are known for their injurious actions on the gastrointestinal (GI) tract. Mucosal damage can be avoided by using nanoscale systems composed by a combination of liposomes and biodegradable natural polymer, i.e. chitosan, for enhancing drug activity. Aim of this study was to prepare chitosan-lipid hybrid delivery systems for indomethacin dosage through a novel continuous method based on microfluidic principles. The drop-wise conventional method was also applied in order to investigate the effect of the two polymeric coverage processes on the nanostructures features and their interactions with indomethacin. Thermal-physical properties, mucoadhesiveness, drug entrapment efficiency, in vitro release behavior in simulated GI fluids and stability in stocking conditions were assayed and compared, respectively, for the uncoated and chitosan-coated nanoliposomes prepared by the two introduced methods. The prepared chitosan-lipid hybrid structures, with nanometric size, have shown high indomethacin loading (about 10%) and drug encapsulation efficiency up to 99%. TEM investigation has highlighted that the developed novel simil-microfluidic method is able to put a polymeric layer, surrounding indomethacin loaded nanoliposomes, thicker and smoother than that achievable by the drop-wise method, improving their storage stability. Finally, double pH tests have confirmed that the chitosan-lipid hybrid nanostructures have a gastro retentive behavior in simulated gastric and intestinal fluids thus can be used as delivery systems for the oral-controlled release of indomethacin. Based on the present results, the simil-microfluidic method, working with large volumes, in a rapid manner, without the use of drastic conditions and with a precise control over the covering process, seems to be the most promising method for the production of suitable indomethacin delivery system, with a great potential in industrial manufacturing. Copyright © 2018 Elsevier B.V. All rights reserved.

Enzyme-free and isothermal detection of microRNA based on click-chemical ligation-assisted hybridization coupled with hybridization chain reaction signal amplification.

PubMed

Oishi, Motoi

2015-05-01

An enzyme-free and isothermal microRNA (miRNA) detection method has been developed based on click-chemical ligation-assisted hybridization coupled with hybridization chain reaction (HCR) on magnetic beads (MBs). The click-chemical ligation between an azide-modified probe DNA and a dibenzocyclooctyne-modified probe DNA occurred through the hybridization of target miRNA (miR-141). HCR on MBs was performed by the addition of DNA hairpin monomers (H1 and H2). After magnetic separation and denaturation/rehybridization of HCR products ([H1/H2] n ), the resulting HCR products were analyzed by the fluorescence emitted from an intercalative dye, allowing amplification of the fluorescent signal. The proposed assay had a limit of detection of 0.55 fmol, which was 230-fold more sensitive than that of the HCR on the MBs coupled with a conventional sandwich hybridization assay (without click-chemical ligation) (limit of detection 127 fmol). Additionally, the proposed assay could discriminate between miR-141 and other miR-200 family members. In contrast to quantitative reverse transcription polymerase chain reaction techniques using enzymes and thermal cycling, this is an enzyme-free assay that can be conducted under isothermal conditions and can specifically detect miR-141 in fetal bovine serum.

Ultrafast web inspection with hybrid dispersion laser scanner.

PubMed

Chen, Hongwei; Wang, Chao; Yazaki, Akio; Kim, Chanju; Goda, Keisuke; Jalali, Bahram

2013-06-10

We report an ultrafast web inspector that operates at a 1000 times higher scan rate than conventional methods. This system is based on a hybrid dispersion laser scanner that performs line scans at nearly 100 MHz. Specifically, we demonstrate web inspection with detectable resolution of 48.6 μm/pixel (scan direction) × 23 μm (web flow direction) within a width of view of 6 mm at a record high scan rate of 90.9 MHz. We demonstrate the identification and evaluation of particles on silicon wafers. This method holds great promise for speeding up quality control and hence reducing manufacturing costs.

A hybrid monkey search algorithm for clustering analysis.

PubMed

Chen, Xin; Zhou, Yongquan; Luo, Qifang

2014-01-01

Clustering is a popular data analysis and data mining technique. The k-means clustering algorithm is one of the most commonly used methods. However, it highly depends on the initial solution and is easy to fall into local optimum solution. In view of the disadvantages of the k-means method, this paper proposed a hybrid monkey algorithm based on search operator of artificial bee colony algorithm for clustering analysis and experiment on synthetic and real life datasets to show that the algorithm has a good performance than that of the basic monkey algorithm for clustering analysis.

Classification of Medical Datasets Using SVMs with Hybrid Evolutionary Algorithms Based on Endocrine-Based Particle Swarm Optimization and Artificial Bee Colony Algorithms.

PubMed

Lin, Kuan-Cheng; Hsieh, Yi-Hsiu

2015-10-01

The classification and analysis of data is an important issue in today's research. Selecting a suitable set of features makes it possible to classify an enormous quantity of data quickly and efficiently. Feature selection is generally viewed as a problem of feature subset selection, such as combination optimization problems. Evolutionary algorithms using random search methods have proven highly effective in obtaining solutions to problems of optimization in a diversity of applications. In this study, we developed a hybrid evolutionary algorithm based on endocrine-based particle swarm optimization (EPSO) and artificial bee colony (ABC) algorithms in conjunction with a support vector machine (SVM) for the selection of optimal feature subsets for the classification of datasets. The results of experiments using specific UCI medical datasets demonstrate that the accuracy of the proposed hybrid evolutionary algorithm is superior to that of basic PSO, EPSO and ABC algorithms, with regard to classification accuracy using subsets with a reduced number of features.

Three-dimensional noninvasive monitoring iodine-131 uptake in the thyroid using a modified Cerenkov luminescence tomography approach.

PubMed

Hu, Zhenhua; Ma, Xiaowei; Qu, Xiaochao; Yang, Weidong; Liang, Jimin; Wang, Jing; Tian, Jie

2012-01-01

Cerenkov luminescence tomography (CLT) provides the three-dimensional (3D) radiopharmaceutical biodistribution in small living animals, which is vital to biomedical imaging. However, existing single-spectral and multispectral methods are not very efficient and effective at reconstructing the distribution of the radionuclide tracer. In this paper, we present a semi-quantitative Cerenkov radiation spectral characteristic-based source reconstruction method named the hybrid spectral CLT, to efficiently reconstruct the radionuclide tracer with both encouraging reconstruction results and less acquisition and image reconstruction time. We constructed the implantation mouse model implanted with a 400 µCi Na(131)I radioactive source and the physiological mouse model received an intravenous tail injection of 400 µCi radiopharmaceutical Iodine-131 (I-131) to validate the performance of the hybrid spectral CLT and compared the reconstruction results, acquisition, and image reconstruction time with that of single-spectral and multispectral CLT. Furthermore, we performed 3D noninvasive monitoring of I-131 uptake in the thyroid and quantified I-131 uptake in vivo using hybrid spectral CLT. Results showed that the reconstruction based on the hybrid spectral CLT was more accurate in localization and quantification than using single-spectral CLT, and was more efficient in the in vivo experiment compared with multispectral CLT. Additionally, 3D visualization of longitudinal observations suggested that the reconstructed energy of I-131 uptake in the thyroid increased with acquisition time and there was a robust correlation between the reconstructed energy versus the gamma ray counts of I-131 (r(2) = 0.8240). The ex vivo biodistribution experiment further confirmed the I-131 uptake in the thyroid for hybrid spectral CLT. Results indicated that hybrid spectral CLT could be potentially used for thyroid imaging to evaluate its function and monitor its treatment for thyroid cancer.

Measuring DNA hybridization using fluorescent DNA-stabilized silver clusters to investigate mismatch effects on therapeutic oligonucleotides.

PubMed

de Bruin, Donny; Bossert, Nelli; Aartsma-Rus, Annemieke; Bouwmeester, Dirk

2018-04-06

Short nucleic acid oligomers have found a wide range of applications in experimental physics, biology and medicine, and show potential for the treatment of acquired and genetic diseases. These applications rely heavily on the predictability of hybridization through Watson-Crick base pairing to allow positioning on a nanometer scale, as well as binding to the target transcripts, but also off-target binding to transcripts with partial homology. These effects are of particular importance in the development of therapeutic oligonucleotides, where off-target effects caused by the binding of mismatched sequences need to be avoided. We employ a novel method of probing DNA hybridization using optically active DNA-stabilized silver clusters (Ag-DNA) to measure binding efficiencies through a change in fluorescence intensity. In this way we can determine their location-specific sensitivity to individual mismatches in the sequence. The results reveal a strong dependence of the hybridization on the location of the mismatch, whereby mismatches close to the edges and center show a relatively minor impact. In parallel, we propose a simple model for calculating the annealing ratios of mismatched DNA sequences, which supports our experimental results. The primary result shown in this work is a demonstration of a novel technique to measure DNA hybridization using fluorescent Ag-DNA. With this technique, we investigated the effect of mismatches on the hybridization efficiency, and found a significant dependence on the location of individual mismatches. These effects are strongly influenced by the length of the used oligonucleotides. The novel probe method based on fluorescent Ag-DNA functions as a reliable tool in measuring this behavior. As a secondary result, we formulated a simple model that is consistent with the experimental data.

Rapid and Simple Detection of Hot Spot Point Mutations of Epidermal Growth Factor Receptor, BRAF, and NRAS in Cancers Using the Loop-Hybrid Mobility Shift Assay

PubMed Central

Matsukuma, Shoichi; Yoshihara, Mitsuyo; Kasai, Fumio; Kato, Akinori; Yoshida, Akira; Akaike, Makoto; Kobayashi, Osamu; Nakayama, Haruhiko; Sakuma, Yuji; Yoshida, Tsutomu; Kameda, Yoichi; Tsuchiya, Eiju; Miyagi, Yohei

2006-01-01

A simple and rapid method to detect the epidermal growth factor receptor hot spot mutation L858R in lung adenocarcinoma was developed based on principles similar to the universal heteroduplex generator technology. A single-stranded oligonucleotide with an internal deletion was used to generate heteroduplexes (loop-hybrids) bearing a loop in the complementary strand derived from the polymerase chain reaction product of the normal or mutant allele. By placing deletion in the oligonucleotide adjacent to the mutational site, difference in electrophoretic mobility between loop-hybrids with normal and mutated DNA was distinguishable in a native polyacrylamide gel. The method was also modified to detect in-frame deletion mutations of epidermal growth factor receptor in lung adenocarcinomas. In addition, the method was adapted to detect hot spot mutations in the B-type Raf kinase (BRAF) at V600 and in a Ras-oncogene (NRAS) at Q61, the mutations commonly found in thyroid carcinomas. Our mutation detection system, designated the loop-hybrid mobility shift assay was sensitive enough to detect mutant DNA comprising 7.5% of the total DNA. As a simple and straightforward mutation detection technique, loop-hybrid mobility shift assay may be useful for the molecular diagnosis of certain types of clinical cancers. Other applications are also discussed. PMID:16931592

Joint Chroma Subsampling and Distortion-Minimization-Based Luma Modification for RGB Color Images With Application.

PubMed

Chung, Kuo-Liang; Hsu, Tsu-Chun; Huang, Chi-Chao

2017-10-01

In this paper, we propose a novel and effective hybrid method, which joins the conventional chroma subsampling and the distortion-minimization-based luma modification together, to improve the quality of the reconstructed RGB full-color image. Assume the input RGB full-color image has been transformed to a YUV image, prior to compression. For each 2×2 UV block, one 4:2:0 subsampling is applied to determine the one subsampled U and V components, U s and V s . Based on U s , V s , and the corresponding 2×2 original RGB block, a main theorem is provided to determine the ideally modified 2×2 luma block in constant time such that the color peak signal-to-noise ratio (CPSNR) quality distortion between the original 2×2 RGB block and the reconstructed 2×2 RGB block can be minimized in a globally optimal sense. Furthermore, the proposed hybrid method and the delivered theorem are adjusted to tackle the digital time delay integration images and the Bayer mosaic images whose Bayer CFA structure has been widely used in modern commercial digital cameras. Based on the IMAX, Kodak, and screen content test image sets, the experimental results demonstrate that in high efficiency video coding, the proposed hybrid method has substantial quality improvement, in terms of the CPSNR quality, visual effect, CPSNR-bitrate trade-off, and Bjøntegaard delta PSNR performance, of the reconstructed RGB images when compared with existing chroma subsampling schemes.

An efficient fast response and high-gain solar-blind flexible ultraviolet photodetector employing hybrid geometry

NASA Astrophysics Data System (ADS)

Hussain, Amreen A.; Pal, Arup R.; Patil, Dinkar S.

2014-05-01

We report high performance flexible hybrid ultraviolet photodetector with solar-blind sensitivity using nanocomposite film of plasma polymerized aniline-titanium dioxide. A facile solvent-free plasma technique is used to synthesize superior quality hybrid material with high yield. The hybrid photodetector exhibited high photoconductive gain of the order of ˜105 and fast speed with response and recovery time of 22.87 ms and 34.23 ms. This is an excellent result towards getting a balance in the response speed and photoconductive gain trade-off of the photodetectors reported so far. In addition, the device has the advantages of enhanced photosensitivity ((Ilight - Idark)/Idark) of the order of ˜102 and high responsivity of ˜104 AW-1. All the merits substantiates that, to prepare hybrid material, plasma based method holds potential to be an easy way for realizing large scale nanostructured photodetectors for practical applications.

Magnetite nanoparticles conjugated with lignin: A physicochemical and magnetic study

NASA Astrophysics Data System (ADS)

Klapiszewski, Łukasz; Zdarta, Jakub; Antecka, Katarzyna; Synoradzki, Karol; Siwińska-Stefańska, Katarzyna; Moszyński, Dariusz; Jesionowski, Teofil

2017-11-01

Using the by-product biopolymer lignin and nanoparticles of magnetite, well-known for its nontoxicity and magnetic properties, novel nanomagnetite-lignin hybrid materials were synthesized. In the first step, magnetite was produced via a co-precipitation method with hydrothermal treatment, and was found to have a particle size of around 20 nm. Nano-Fe3O4 was then combined with pre-activated lignin to obtain hybrids with various magnetite-lignin ratios, whose physicochemical and magnetic properties were thoroughly analyzed. Thermal analysis showed the hybrids to have higher thermal stability than pure lignin. Based on Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy it was demonstrated that the Fe3O4 and lignin are connected via Fesbnd Osbnd C bonds. Further measurements showed the nanomagnetite-lignin hybrid materials to have good magnetic properties. The results of this study suggest that the synthesized hybrids may find practical applications in many fields of science and industry.

Development of a PCR/LDR/flow-through hybridization assay using a capillary tube, probe DNA-immobilized magnetic beads and chemiluminescence detection.

PubMed

Hommatsu, Manami; Okahashi, Hisamitsu; Ohta, Keisuke; Tamai, Yusuke; Tsukagoshi, Kazuhiko; Hashimoto, Masahiko

2013-01-01

A polymerase chain reaction (PCR)/ligase detection reaction (LDR)/flow-through hybridization assay using chemiluminescence (CL) detection was developed for analyzing point mutations in gene fragments with high diagnostic value for colorectal cancers. A flow-through hybridization format using a capillary tube, in which probe DNA-immobilized magnetic beads were packed, provided accelerated hybridization kinetics of target DNA (i.e. LDR product) to the probe DNA. Simple fluid manipulations enabled both allele-specific hybridization and the removal of non-specifically bound DNA in the wash step. Furthermore, the use of CL detection greatly simplified the detection scheme, since CL does not require a light source for excitation of the fluorescent dye tags on the LDR products. Preliminary results demonstrated that this analytical system could detect both homozygous and heterozygous mutations, without the expensive instrumentation and cumbersome procedures required by conventional DNA microarray-based methods.

Photofunctional Eu3+/Tb3+ hybrids through sulfoxide linkages: coordination bonds construction, characterization and luminescence.

PubMed

Guo, Lei; Yan, Bing; Liu, Jin-Liang

2011-05-14

New kinds of organic-inorganic hybrid materials consisting of rare earth (Eu(3+), Tb(3+)) complexes covalently bonded to a silica-based network have been obtained by a sol-gel approach. Three novel versatile molecular building blocks containing sulfoxide organic units have been synthesized by methylene modification reaction, which are used as the ligands of rare earth ions and also as siloxane network precursors. The obtained hybrids are characterized by chemical analysis and spectroscopic methods such as FTIR and UV; XRD and SEM. Photoluminescence measurements on the prepared hybrids were performed showing the intra-4f(n) emission in the visible (Eu(3+), Tb(3+)) region and in all the cases being sensitized by the sulfoxide ligands. The emission quantum efficiency and the Judd-Ofelt intensity parameters of Eu(3+) hybrid materials were also investigated in detail.

Reduction hybrid artifacts of EMG-EOG in electroencephalography evoked by prefrontal transcranial magnetic stimulation

NASA Astrophysics Data System (ADS)

Bai, Yang; Wan, Xiaohong; Zeng, Ke; Ni, Yinmei; Qiu, Lirong; Li, Xiaoli

2016-12-01

Objective. When prefrontal-transcranial magnetic stimulation (p-TMS) performed, it may evoke hybrid artifact mixed with muscle activity and blink activity in EEG recordings. Reducing this kind of hybrid artifact challenges the traditional preprocessing methods. We aim to explore method for the p-TMS evoked hybrid artifact removal. Approach. We propose a novel method used as independent component analysis (ICA) post processing to reduce the p-TMS evoked hybrid artifact. Ensemble empirical mode decomposition (EEMD) was used to decompose signal into multi-components, then the components were separated with artifact reduced by blind source separation (BSS) method. Three standard BSS methods, ICA, independent vector analysis, and canonical correlation analysis (CCA) were tested. Main results. Synthetic results showed that EEMD-CCA outperformed others as ICA post processing step in hybrid artifacts reduction. Its superiority was clearer when signal to noise ratio (SNR) was lower. In application to real experiment, SNR can be significantly increased and the p-TMS evoked potential could be recovered from hybrid artifact contaminated signal. Our proposed method can effectively reduce the p-TMS evoked hybrid artifacts. Significance. Our proposed method may facilitate future prefrontal TMS-EEG researches.

TU-AB-202-07: A Novel Method for Registration of Mid-Treatment PET/CT Images Under Conditions of Tumor Regression for Patients with Locally Advanced Lung Cancers

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

Sharifi, Hoda; Department of Physics, Oakland University, Rochester, MI; Zhang, Hong

Purpose: In PET-guided adaptive radiotherapy (RT), changes in the metabolic activity at individual voxels cannot be derived until the duringtreatment CT images are appropriately registered to pre-treatment CT images. However, deformable image registration (DIR) usually does not preserve tumor volume. This may induce errors when comparing to the target. The aim of this study was to develop a DIR-integrated mechanical modeling technique to track radiation-induced metabolic changes on PET images. Methods: Three patients with non-small cell lung cancer (NSCLC) were treated with adaptive radiotherapy under RTOG 1106. Two PET/CT image sets were acquired 2 weeks before RT and 18 fractionsmore » after the start of treatment. DIR was performed to register the during-RT CT to the pre-RT CT using a B-spline algorithm and the resultant displacements in the region of tumor were remodeled using a hybrid finite element method (FEM). Gross tumor volume (GTV) was delineated on the during-RT PET/CT image sets and deformed using the 3D deformation vector fields generated by the CT-based registrations. Metabolic tumor volume (MTV) was calculated using the pre- and during–RT image set. The quality of the PET mapping was evaluated based on the constancy of the mapped MTV and landmark comparison. Results: The B-spline-based registrations changed MTVs by 7.3%, 4.6% and −5.9% for the 3 patients and the correspondent changes for the hybrid FEM method −2.9%, 1% and 6.3%, respectively. Landmark comparisons were used to evaluate the Rigid, B-Spline, and hybrid FEM registrations with the mean errors of 10.1 ± 1.6 mm, 4.4 ± 0.4 mm, and 3.6 ± 0.4 mm for three patients. The hybrid FEM method outperforms the B-Spline-only registration for patients with tumor regression Conclusion: The hybrid FEM modeling technique improves the B-Spline registrations in tumor regions. This technique may help compare metabolic activities between two PET/CT images with regressing tumors. The author gratefully acknowledges the financial support from the National Institutes of Health Grant.« less

Lipase-inorganic hybrid nanoflower constructed through biomimetic mineralization: A new support for biodiesel synthesis.

PubMed

Jiang, Wei; Wang, Xinghuo; Yang, Jiebing; Han, Haobo; Li, Quanshun; Tang, Jun

2018-03-15

We reported a facile, economic and green method based on biomimetic mineralization to acquire lipase-inorganic hybrid nanoflower, which was then employed as a biocatalyst for biodiesel production. In the hybrid nanoflower, enzyme molecules and Cu 2+ ions were utilized as the organic and inorganic components, respectively. The morphology of nanoflower and the distribution and loading of proteins were systematically characterized by scanning electron microscopy, confocal laser scanning microscopy and ultraviolet-visible spectroscopy, which indicated the successful encapsulation of lipase in the hybrid nanoflower. Using the hydrolysis of p-nitrophenyl caprylate as a model, lipase-inorganic hybrid nanoflower was observed to possess favorable catalytic activity and stability in the ester hydrolysis. Further, the hybrid nanoflower was used as a catalyst for biodiesel production, in which it could convert sunflower oil to biodiesel with 96.5% conversion and remain 72.5% conversion after being used for 5 cycles. Thus, the lipase-inorganic hybrid nanoflower is potential to be used as an economically viable biocatalyst for the production of biofuel as the future petrol-fuel replacement. Copyright © 2017 Elsevier Inc. All rights reserved.

Variational method based on Retinex with double-norm hybrid constraints for uneven illumination correction

NASA Astrophysics Data System (ADS)

Li, Shuo; Wang, Hui; Wang, Liyong; Yu, Xiangzhou; Yang, Le

2018-01-01

The uneven illumination phenomenon reduces the quality of remote sensing image and causes interference in the subsequent processing and applications. A variational method based on Retinex with double-norm hybrid constraints for uneven illumination correction is proposed. The L1 norm and the L2 norm are adopted to constrain the textures and details of reflectance image and the smoothness of the illumination image, respectively. The problem of separating the illumination image from the reflectance image is transformed into the optimal solution of the variational model. In order to accelerate the solution, the split Bregman method is used to decompose the variational model into three subproblems, which are calculated by alternate iteration. Two groups of experiments are implemented on two synthetic images and three real remote sensing images. Compared with the variational Retinex method with single-norm constraint and the Mask method, the proposed method performs better in both visual evaluation and quantitative measurements. The proposed method can effectively eliminate the uneven illumination while maintaining the textures and details of the remote sensing image. Moreover, the proposed method using split Bregman method is more than 10 times faster than the method with the steepest descent method.

Hybrid Differential Dynamic Programming with Stochastic Search

NASA Technical Reports Server (NTRS)

Aziz, Jonathan; Parker, Jeffrey; Englander, Jacob A.

2016-01-01

Differential dynamic programming (DDP) has been demonstrated as a viable approach to low-thrust trajectory optimization, namely with the recent success of NASA's Dawn mission. The Dawn trajectory was designed with the DDP-based Static/Dynamic Optimal Control algorithm used in the Mystic software.1 Another recently developed method, Hybrid Differential Dynamic Programming (HDDP),2, 3 is a variant of the standard DDP formulation that leverages both first-order and second-order state transition matrices in addition to nonlinear programming (NLP) techniques. Areas of improvement over standard DDP include constraint handling, convergence properties, continuous dynamics, and multi-phase capability. DDP is a gradient based method and will converge to a solution nearby an initial guess. In this study, monotonic basin hopping (MBH) is employed as a stochastic search method to overcome this limitation, by augmenting the HDDP algorithm for a wider search of the solution space.

Microbial-enzymatic-hybrid biological fuel cell with optimized growth conditions for Shewanella oneidensis DSP-10.

PubMed

Roy, Jared N; Luckarift, Heather R; Sizemore, Susan R; Farrington, Karen E; Lau, Carolin; Johnson, Glenn R; Atanassov, Plamen

2013-07-10

In this work we present a biological fuel cell fabricated by combining a Shewanella oneidensis microbial anode and a laccase-modified air-breathing cathode. This concept is devised as an extension to traditional biochemical methods by incorporating diverse biological catalysts with the aim of powering small devices. In preparing the biological fuel cell anode, novel hierarchical-structured architectures and biofilm configurations were investigated. A method for creating an artificial biofilm based on encapsulating microorganisms in a porous, thin film of silica was compared with S. oneidensis biofilms that were allowed to colonize naturally. Results indicate comparable current and power densities for artificial and natural biofilm formations, based on growth characteristics. As a result, this work describes methods for creating controllable and reproducible bio-anodes and demonstrates the versatility of hybrid biological fuel cells. Copyright © 2013 Elsevier Inc. All rights reserved.

Liquid contrabands classification based on energy dispersive X-ray diffraction and hybrid discriminant analysis

NASA Astrophysics Data System (ADS)

YangDai, Tianyi; Zhang, Li

2016-02-01

Energy dispersive X-ray diffraction (EDXRD) combined with hybrid discriminant analysis (HDA) has been utilized for classifying the liquid materials for the first time. The XRD spectra of 37 kinds of liquid contrabands and daily supplies were obtained using an EDXRD test bed facility. The unique spectra of different samples reveal XRD's capability to distinguish liquid contrabands from daily supplies. In order to create a system to detect liquid contrabands, the diffraction spectra were subjected to HDA which is the combination of principal components analysis (PCA) and linear discriminant analysis (LDA). Experiments based on the leave-one-out method demonstrate that HDA is a practical method with higher classification accuracy and lower noise sensitivity than the other methods in this application. The study shows the great capability and potential of the combination of XRD and HDA for liquid contrabands classification.

Active semi-supervised learning method with hybrid deep belief networks.

PubMed

Zhou, Shusen; Chen, Qingcai; Wang, Xiaolong

2014-01-01

In this paper, we develop a novel semi-supervised learning algorithm called active hybrid deep belief networks (AHD), to address the semi-supervised sentiment classification problem with deep learning. First, we construct the previous several hidden layers using restricted Boltzmann machines (RBM), which can reduce the dimension and abstract the information of the reviews quickly. Second, we construct the following hidden layers using convolutional restricted Boltzmann machines (CRBM), which can abstract the information of reviews effectively. Third, the constructed deep architecture is fine-tuned by gradient-descent based supervised learning with an exponential loss function. Finally, active learning method is combined based on the proposed deep architecture. We did several experiments on five sentiment classification datasets, and show that AHD is competitive with previous semi-supervised learning algorithm. Experiments are also conducted to verify the effectiveness of our proposed method with different number of labeled reviews and unlabeled reviews respectively.

A New Stochastic Technique for Painlevé Equation-I Using Neural Network Optimized with Swarm Intelligence

PubMed Central

Raja, Muhammad Asif Zahoor; Khan, Junaid Ali; Ahmad, Siraj-ul-Islam; Qureshi, Ijaz Mansoor

2012-01-01

A methodology for solution of Painlevé equation-I is presented using computational intelligence technique based on neural networks and particle swarm optimization hybridized with active set algorithm. The mathematical model of the equation is developed with the help of linear combination of feed-forward artificial neural networks that define the unsupervised error of the model. This error is minimized subject to the availability of appropriate weights of the networks. The learning of the weights is carried out using particle swarm optimization algorithm used as a tool for viable global search method, hybridized with active set algorithm for rapid local convergence. The accuracy, convergence rate, and computational complexity of the scheme are analyzed based on large number of independents runs and their comprehensive statistical analysis. The comparative studies of the results obtained are made with MATHEMATICA solutions, as well as, with variational iteration method and homotopy perturbation method. PMID:22919371

Transfer of a Mycobacterium tuberculosis Genotyping Method, Spoligotyping, from a Reverse Line-Blot Hybridization, Membrane-Based Assay to the Luminex Multianalyte Profiling System

PubMed Central

Cowan, Lauren S.; Diem, Lois; Brake, Mary Catherine; Crawford, Jack T.

2004-01-01

Spoligotyping using Luminex technology was shown to be a highly reproducible method suitable for high-throughput analysis. Spoligotyping of 48 isolates using the traditional membrane-based assay and the Luminex assay yielded concordant results for all isolates. The Luminex platform provides greater flexibility and cost effectiveness than the membrane-based assay. PMID:14715809

Hybrid charge division multiplexing method for silicon photomultiplier based PET detectors

NASA Astrophysics Data System (ADS)

Park, Haewook; Ko, Guen Bae; Lee, Jae Sung

2017-06-01

Silicon photomultiplier (SiPM) is widely utilized in various positron emission tomography (PET) detectors and systems. However, the individual recording of SiPM output signals is still challenging owing to the high granularity of the SiPM; thus, charge division multiplexing is commonly used in PET detectors. Resistive charge division method is well established for reducing the number of output channels in conventional multi-channel photosensors, but it degrades the timing performance of SiPM-based PET detectors by yielding a large resistor-capacitor (RC) constant. Capacitive charge division method, on the other hand, yields a small RC constant and provides a faster timing response than the resistive method, but it suffers from an output signal undershoot. Therefore, in this study, we propose a hybrid charge division method which can be implemented by cascading the parallel combination of a resistor and a capacitor throughout the multiplexing network. In order to compare the performance of the proposed method with the conventional methods, a 16-channel Hamamatsu SiPM (S11064-050P) was coupled with a 4  ×  4 LGSO crystal block (3  ×  3  ×  20 mm3) and a 9  ×  9 LYSO crystal block (1.2  ×  1.2  ×  10 mm3). In addition, we tested a time-over-threshold (TOT) readout using the digitized position signals to further demonstrate the feasibility of the time-based readout of multiplexed signals based on the proposed method. The results indicated that the proposed method exhibited good energy and timing performance, thus inheriting only the advantages of conventional resistive and capacitive methods. Moreover, the proposed method showed excellent pulse shape uniformity that does not depend on the position of the interacted crystal. Accordingly, we can conclude that the hybrid charge division method is useful for effectively reducing the number of output channels of the SiPM array.

Morphological Variation among Betula nana (diploid), B. pubescens (tetraploid) and their Triploid Hybrids in Iceland

PubMed Central

Thórsson, Æ. Th.; Pálsson, S.; Sigurgeirsson, A.; Anamthawat-Jónsson, K.

2007-01-01

Background and Aims Introgressive hybridization between two co-existing Betula species in Iceland, diploid dwarf birch B. nana and tetraploid downy birch B. pubescens, has been well documented. The two species are highly variable morphologically, making taxonomic delineation difficult despite stable ploidy levels. Here an analysis is made of morphological variation within each ploidy group with an aim to establishing a reliable means to distinguish the species. Methods Plant materials were collected from 14 woodlands in Iceland. The plants were identified based on 2n chromosome numbers. Morphological variation in species-specific characters within each ploidy group was analysed qualitatively and quantitatively. The morphological index was based on eight discrete characters, whereas the multivariate analysis was based on nine leaf variables. Key Results Of the 461 plants examined, 9·5 % were found to be triploid hybrids. The three ploidy groups were morphologically distinguishable but their variation overlapped. The diploid, triploid and tetraploid groups had average scores of 1·3, 4·1 and 8·3, respectively, in the morphology index scale from 0 (B. nana) to 13 (B. pubescens). A linear discriminant analysis also revealed significant separation among the three ploidy groups and the model assigned 96 % and 97 % of the B. nana and B. pubescens individuals correctly. The triploid hybrids were difficult to predict since only half of them could be assigned correctly. Leaf length was the most useful variable identifying triploid hybrids. Geographical patterns within the ploidy groups could partly be explained by differences in mean July temperature. Conclusions Hybridization between B. nana and B. pubescens is widespread in Iceland. The species can be distinguished from each other morphologically, and from the triploid hybrids. The overlapping morphological variation indicates bidirectional introgression between the two species via triploid hybrids. Iceland could be considered a birch hybrid zone, harbouring genetic variation which may be advantageous in subarctic regions. PMID:17495985

A Hybrid Forward-Adjoint Data Assimilation Method for Reconstructing the Temporal Evolution of Mantle Dynamics

NASA Astrophysics Data System (ADS)

Zhou, Q.; Liu, L.

2017-12-01

Quantifying past mantle dynamic processes represents a major challenge in understanding the temporal evolution of the solid earth. Mantle convection modeling with data assimilation is one of the most powerful tools to investigate the dynamics of plate subduction and mantle convection. Although various data assimilation methods, both forward and inverse, have been created, these methods all have limitations in their capabilities to represent the real earth. Pure forward models tend to miss important mantle structures due to the incorrect initial condition and thus may lead to incorrect mantle evolution. In contrast, pure tomography-based models cannot effectively resolve the fine slab structure and would fail to predict important subduction-zone dynamic processes. Here we propose a hybrid data assimilation method that combines the unique power of the sequential and adjoint algorithms, which can properly capture the detailed evolution of the downgoing slab and the tomographically constrained mantle structures, respectively. We apply this new method to reconstructing mantle dynamics below the western U.S. while considering large lateral viscosity variations. By comparing this result with those from several existing data assimilation methods, we demonstrate that the hybrid modeling approach recovers the realistic 4-D mantle dynamics to the best.

Hybrid-Based Dense Stereo Matching

NASA Astrophysics Data System (ADS)

Chuang, T. Y.; Ting, H. W.; Jaw, J. J.

2016-06-01

Stereo matching generating accurate and dense disparity maps is an indispensable technique for 3D exploitation of imagery in the fields of Computer vision and Photogrammetry. Although numerous solutions and advances have been proposed in the literature, occlusions, disparity discontinuities, sparse texture, image distortion, and illumination changes still lead to problematic issues and await better treatment. In this paper, a hybrid-based method based on semi-global matching is presented to tackle the challenges on dense stereo matching. To ease the sensitiveness of SGM cost aggregation towards penalty parameters, a formal way to provide proper penalty estimates is proposed. To this end, the study manipulates a shape-adaptive cross-based matching with an edge constraint to generate an initial disparity map for penalty estimation. Image edges, indicating the potential locations of occlusions as well as disparity discontinuities, are approved by the edge drawing algorithm to ensure the local support regions not to cover significant disparity changes. Besides, an additional penalty parameter 𝑃𝑒 is imposed onto the energy function of SGM cost aggregation to specifically handle edge pixels. Furthermore, the final disparities of edge pixels are found by weighting both values derived from the SGM cost aggregation and the U-SURF matching, providing more reliable estimates at disparity discontinuity areas. Evaluations on Middlebury stereo benchmarks demonstrate satisfactory performance and reveal the potency of the hybrid-based dense stereo matching method.

Parameter estimation methods for gene circuit modeling from time-series mRNA data: a comparative study.

PubMed

Fan, Ming; Kuwahara, Hiroyuki; Wang, Xiaolei; Wang, Suojin; Gao, Xin

2015-11-01

Parameter estimation is a challenging computational problem in the reverse engineering of biological systems. Because advances in biotechnology have facilitated wide availability of time-series gene expression data, systematic parameter estimation of gene circuit models from such time-series mRNA data has become an important method for quantitatively dissecting the regulation of gene expression. By focusing on the modeling of gene circuits, we examine here the performance of three types of state-of-the-art parameter estimation methods: population-based methods, online methods and model-decomposition-based methods. Our results show that certain population-based methods are able to generate high-quality parameter solutions. The performance of these methods, however, is heavily dependent on the size of the parameter search space, and their computational requirements substantially increase as the size of the search space increases. In comparison, online methods and model decomposition-based methods are computationally faster alternatives and are less dependent on the size of the search space. Among other things, our results show that a hybrid approach that augments computationally fast methods with local search as a subsequent refinement procedure can substantially increase the quality of their parameter estimates to the level on par with the best solution obtained from the population-based methods while maintaining high computational speed. These suggest that such hybrid methods can be a promising alternative to the more commonly used population-based methods for parameter estimation of gene circuit models when limited prior knowledge about the underlying regulatory mechanisms makes the size of the parameter search space vastly large. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Bands selection and classification of hyperspectral images based on hybrid kernels SVM by evolutionary algorithm

NASA Astrophysics Data System (ADS)

Hu, Yan-Yan; Li, Dong-Sheng

2016-01-01

The hyperspectral images(HSI) consist of many closely spaced bands carrying the most object information. While due to its high dimensionality and high volume nature, it is hard to get satisfactory classification performance. In order to reduce HSI data dimensionality preparation for high classification accuracy, it is proposed to combine a band selection method of artificial immune systems (AIS) with a hybrid kernels support vector machine (SVM-HK) algorithm. In fact, after comparing different kernels for hyperspectral analysis, the approach mixed radial basis function kernel (RBF-K) with sigmoid kernel (Sig-K) and applied the optimized hybrid kernels in SVM classifiers. Then the SVM-HK algorithm used to induce the bands selection of an improved version of AIS. The AIS was composed of clonal selection and elite antibody mutation, including evaluation process with optional index factor (OIF). Experimental classification performance was on a San Diego Naval Base acquired by AVIRIS, the HRS dataset shows that the method is able to efficiently achieve bands redundancy removal while outperforming the traditional SVM classifier.

An Improved Hybrid Encoding Cuckoo Search Algorithm for 0-1 Knapsack Problems

PubMed Central

Feng, Yanhong; Jia, Ke; He, Yichao

2014-01-01

Cuckoo search (CS) is a new robust swarm intelligence method that is based on the brood parasitism of some cuckoo species. In this paper, an improved hybrid encoding cuckoo search algorithm (ICS) with greedy strategy is put forward for solving 0-1 knapsack problems. First of all, for solving binary optimization problem with ICS, based on the idea of individual hybrid encoding, the cuckoo search over a continuous space is transformed into the synchronous evolution search over discrete space. Subsequently, the concept of confidence interval (CI) is introduced; hence, the new position updating is designed and genetic mutation with a small probability is introduced. The former enables the population to move towards the global best solution rapidly in every generation, and the latter can effectively prevent the ICS from trapping into the local optimum. Furthermore, the greedy transform method is used to repair the infeasible solution and optimize the feasible solution. Experiments with a large number of KP instances show the effectiveness of the proposed algorithm and its ability to achieve good quality solutions. PMID:24527026

Detection and isolation of nucleic acid sequences using competitive hybridization probes

DOEpatents

Lucas, Joe N.; Straume, Tore; Bogen, Kenneth T.

1997-01-01

A method for detecting a target nucleic acid sequence in a sample is provided using hybridization probes which competitively hybridize to a target nucleic acid. According to the method, a target nucleic acid sequence is hybridized to first and second hybridization probes which are complementary to overlapping portions of the target nucleic acid sequence, the first hybridization probe including a first complexing agent capable of forming a binding pair with a second complexing agent and the second hybridization probe including a detectable marker. The first complexing agent attached to the first hybridization probe is contacted with a second complexing agent, the second complexing agent being attached to a solid support such that when the first and second complexing agents are attached, target nucleic acid sequences hybridized to the first hybridization probe become immobilized on to the solid support. The immobilized target nucleic acids are then separated and detected by detecting the detectable marker attached to the second hybridization probe. A kit for performing the method is also provided.

Detection and isolation of nucleic acid sequences using competitive hybridization probes

DOEpatents

Lucas, J.N.; Straume, T.; Bogen, K.T.

1997-04-01

A method for detecting a target nucleic acid sequence in a sample is provided using hybridization probes which competitively hybridize to a target nucleic acid. According to the method, a target nucleic acid sequence is hybridized to first and second hybridization probes which are complementary to overlapping portions of the target nucleic acid sequence, the first hybridization probe including a first complexing agent capable of forming a binding pair with a second complexing agent and the second hybridization probe including a detectable marker. The first complexing agent attached to the first hybridization probe is contacted with a second complexing agent, the second complexing agent being attached to a solid support such that when the first and second complexing agents are attached, target nucleic acid sequences hybridized to the first hybridization probe become immobilized on to the solid support. The immobilized target nucleic acids are then separated and detected by detecting the detectable marker attached to the second hybridization probe. A kit for performing the method is also provided. 7 figs.

Validation of columnar CsI x-ray detector responses obtained with hybridMANTIS, a CPU-GPU Monte Carlo code for coupled x-ray, electron, and optical transport

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

Sharma, Diksha; Badano, Aldo

2013-03-15

Purpose: hybridMANTIS is a Monte Carlo package for modeling indirect x-ray imagers using columnar geometry based on a hybrid concept that maximizes the utilization of available CPU and graphics processing unit processors in a workstation. Methods: The authors compare hybridMANTIS x-ray response simulations to previously published MANTIS and experimental data for four cesium iodide scintillator screens. These screens have a variety of reflective and absorptive surfaces with different thicknesses. The authors analyze hybridMANTIS results in terms of modulation transfer function and calculate the root mean square difference and Swank factors from simulated and experimental results. Results: The comparison suggests thatmore » hybridMANTIS better matches the experimental data as compared to MANTIS, especially at high spatial frequencies and for the thicker screens. hybridMANTIS simulations are much faster than MANTIS with speed-ups up to 5260. Conclusions: hybridMANTIS is a useful tool for improved description and optimization of image acquisition stages in medical imaging systems and for modeling the forward problem in iterative reconstruction algorithms.« less

A hybrid 3D region growing and 4D curvature analysis-based automatic abdominal blood vessel segmentation through contrast enhanced CT

NASA Astrophysics Data System (ADS)

Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Shimada, Mitsuo; Iinuma, Gen

2017-03-01

In abdominal disease diagnosis and various abdominal surgeries planning, segmentation of abdominal blood vessel (ABVs) is a very imperative task. Automatic segmentation enables fast and accurate processing of ABVs. We proposed a fully automatic approach for segmenting ABVs through contrast enhanced CT images by a hybrid of 3D region growing and 4D curvature analysis. The proposed method comprises three stages. First, candidates of bone, kidneys, ABVs and heart are segmented by an auto-adapted threshold. Second, bone is auto-segmented and classified into spine, ribs and pelvis. Third, ABVs are automatically segmented in two sub-steps: (1) kidneys and abdominal part of the heart are segmented, (2) ABVs are segmented by a hybrid approach that integrates a 3D region growing and 4D curvature analysis. Results are compared with two conventional methods. Results show that the proposed method is very promising in segmenting and classifying bone, segmenting whole ABVs and may have potential utility in clinical use.

Adaptive positive position feedback control with a feedforward compensator of a magnetostrictive beam for vibration suppression

NASA Astrophysics Data System (ADS)

Bian, Leixiang; Zhu, Wei

2018-07-01

In this paper, a Fe–Ga alloy magnetostrictive beam is designed as an actuator to restrain the vibration of a supported mass. Dynamic modeling of the system based on the transfer matrix method of multibody system is first shown, and then a hybrid controller is developed to achieve vibration control. The proposed vibration controller combines a multi-mode adaptive positive position feedback (APPF) with a feedforward compensator. In the APPF control, an adaptive natural frequency estimator based on the recursive least-square method is developed to be used. In the feedforward compensator, the hysteresis of the magnetostrictive beam is linearized based on a Bouc–Wen model. The further remarkable vibration suppression capability of the proposed hybrid controller is demonstrated experimentally and compared with the positive position feedback controller. Experiment results show that the proposed controller is applicable to the magnetostrictive beam for improving vibration control effectiveness.

Hybrid Integrated Label-Free Chemical and Biological Sensors

PubMed Central

Mehrabani, Simin; Maker, Ashley J.; Armani, Andrea M.

2014-01-01

Label-free sensors based on electrical, mechanical and optical transduction methods have potential applications in numerous areas of society, ranging from healthcare to environmental monitoring. Initial research in the field focused on the development and optimization of various sensor platforms fabricated from a single material system, such as fiber-based optical sensors and silicon nanowire-based electrical sensors. However, more recent research efforts have explored designing sensors fabricated from multiple materials. For example, synthetic materials and/or biomaterials can also be added to the sensor to improve its response toward analytes of interest. By leveraging the properties of the different material systems, these hybrid sensing devices can have significantly improved performance over their single-material counterparts (better sensitivity, specificity, signal to noise, and/or detection limits). This review will briefly discuss some of the methods for creating these multi-material sensor platforms and the advances enabled by this design approach. PMID:24675757

A hybrid skull-stripping algorithm based on adaptive balloon snake models

NASA Astrophysics Data System (ADS)

Liu, Hung-Ting; Sheu, Tony W. H.; Chang, Herng-Hua

2013-02-01

Skull-stripping is one of the most important preprocessing steps in neuroimage analysis. We proposed a hybrid algorithm based on an adaptive balloon snake model to handle this challenging task. The proposed framework consists of two stages: first, the fuzzy possibilistic c-means (FPCM) is used for voxel clustering, which provides a labeled image for the snake contour initialization. In the second stage, the contour is initialized outside the brain surface based on the FPCM result and evolves under the guidance of the balloon snake model, which drives the contour with an adaptive inward normal force to capture the boundary of the brain. The similarity indices indicate that our method outperformed the BSE and BET methods in skull-stripping the MR image volumes in the IBSR data set. Experimental results show the effectiveness of this new scheme and potential applications in a wide variety of skull-stripping applications.

Hybrid integrated label-free chemical and biological sensors.

PubMed

Mehrabani, Simin; Maker, Ashley J; Armani, Andrea M

2014-03-26

Label-free sensors based on electrical, mechanical and optical transduction methods have potential applications in numerous areas of society, ranging from healthcare to environmental monitoring. Initial research in the field focused on the development and optimization of various sensor platforms fabricated from a single material system, such as fiber-based optical sensors and silicon nanowire-based electrical sensors. However, more recent research efforts have explored designing sensors fabricated from multiple materials. For example, synthetic materials and/or biomaterials can also be added to the sensor to improve its response toward analytes of interest. By leveraging the properties of the different material systems, these hybrid sensing devices can have significantly improved performance over their single-material counterparts (better sensitivity, specificity, signal to noise, and/or detection limits). This review will briefly discuss some of the methods for creating these multi-material sensor platforms and the advances enabled by this design approach.

Symmetric and asymmetric hybrid cryptosystem based on compressive sensing and computer generated holography

NASA Astrophysics Data System (ADS)

Ma, Lihong; Jin, Weimin

2018-01-01

A novel symmetric and asymmetric hybrid optical cryptosystem is proposed based on compressive sensing combined with computer generated holography. In this method there are six encryption keys, among which two decryption phase masks are different from the two random phase masks used in the encryption process. Therefore, the encryption system has the feature of both symmetric and asymmetric cryptography. On the other hand, because computer generated holography can flexibly digitalize the encrypted information and compressive sensing can significantly reduce data volume, what is more, the final encryption image is real function by phase truncation, the method favors the storage and transmission of the encryption data. The experimental results demonstrate that the proposed encryption scheme boosts the security and has high robustness against noise and occlusion attacks.

A hybrid CS-SA intelligent approach to solve uncertain dynamic facility layout problems considering dependency of demands

NASA Astrophysics Data System (ADS)

Moslemipour, Ghorbanali

2018-07-01

This paper aims at proposing a quadratic assignment-based mathematical model to deal with the stochastic dynamic facility layout problem. In this problem, product demands are assumed to be dependent normally distributed random variables with known probability density function and covariance that change from period to period at random. To solve the proposed model, a novel hybrid intelligent algorithm is proposed by combining the simulated annealing and clonal selection algorithms. The proposed model and the hybrid algorithm are verified and validated using design of experiment and benchmark methods. The results show that the hybrid algorithm has an outstanding performance from both solution quality and computational time points of view. Besides, the proposed model can be used in both of the stochastic and deterministic situations.

Formal methods for modeling and analysis of hybrid systems

NASA Technical Reports Server (NTRS)

Tiwari, Ashish (Inventor); Lincoln, Patrick D. (Inventor)

2009-01-01

A technique based on the use of a quantifier elimination decision procedure for real closed fields and simple theorem proving to construct a series of successively finer qualitative abstractions of hybrid automata is taught. The resulting abstractions are always discrete transition systems which can then be used by any traditional analysis tool. The constructed abstractions are conservative and can be used to establish safety properties of the original system. The technique works on linear and non-linear polynomial hybrid systems: the guards on discrete transitions and the continuous flows in all modes can be specified using arbitrary polynomial expressions over the continuous variables. An exemplar tool in the SAL environment built over the theorem prover PVS is detailed. The technique scales well to large and complex hybrid systems.

New porphyrin-polyoxometalate hybrid materials: synthesis, characterization and investigation of catalytic activity in acetylation reactions.

PubMed

Araghi, Mehdi; Mirkhani, Valiollah; Moghadam, Majid; Tangestaninejad, Shahram; Mohammdpoor-Baltork, Iraj

2012-10-14

New hybrid complexes based on covalent interaction between 5,10,15,20-tetrakis(4-aminophenyl)porphyrinatozinc(II) and 5,10,15,20-tetrakis(4-aminophenyl)porphyrinatotin(IV) chloride, and a Lindqvist-type polyoxometalate, Mo(6)O(19)(2-), were prepared. These new porphyrin-polyoxometalate hybrid materials were characterized by (1)H NMR, FT IR and UV-Vis spectroscopic methods and cyclic voltammetry. These spectro- and electrochemical studies provided several spectral data for synthesis of these compounds. Cyclic voltammetry showed the influence of the polyoxometalate on the redox process of the porphyrin ring. The catalytic activity of tin(IV)porphyrin-hexamolybdate hybrid material was investigated in the acetylation of alcohols and phenols with acetic anhydride. The reusability of this catalyst was also investigated.

A Hybrid Neural Network-Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2001-01-01

In this paper, a model-based diagnostic method, which utilizes Neural Networks and Genetic Algorithms, is investigated. Neural networks are applied to estimate the engine internal health, and Genetic Algorithms are applied for sensor bias detection and estimation. This hybrid approach takes advantage of the nonlinear estimation capability provided by neural networks while improving the robustness to measurement uncertainty through the application of Genetic Algorithms. The hybrid diagnostic technique also has the ability to rank multiple potential solutions for a given set of anomalous sensor measurements in order to reduce false alarms and missed detections. The performance of the hybrid diagnostic technique is evaluated through some case studies derived from a turbofan engine simulation. The results show this approach is promising for reliable diagnostics of aircraft engines.

Stiffness Customization and Patterning for Property Modulation of Silicone-Based Soft Pneumatic Actuators.

PubMed

Sun, Yi; Yap, Hong Kai; Liang, Xinquan; Guo, Jin; Qi, Peng; Ang, Marcelo H; Yeow, Chen-Hua

2017-09-01

Soft pneumatic actuators (SPAs), as novel types of motion drivers for robotic devices, excel in many applications, such as rehabilitation and biomimicry, which demand compliance and softness. To further expand their scope of utilization, the SPAs should be customizable to meet the distinctive requirements of different applications. This article proposes a novel perspective on the SPA working mechanism based on stiffness distribution and then presents a versatile method called stiffness customization and patterning (SCP) for SPA body stiffness layout as a novel attempt to customize SPAs with distinctive properties. We fabricated a hybrid type of material combining unstretchable material and silicone with customizable aggregated elasticity. The tensile results showed that embedding unstretchable material directly increases the stiffness of the hybrid material sample, and our stress-strain model for SCP is able to adequately predict the elasticity of hybrid samples with specific material ratios. By applying this approach to bending-type SPAs, we are able to mitigate SPA buckling, a main failure mode of SPAs, and improve the SPA tip force by using hybrid material with globally increased stiffness. We also diversify bending modalities with different stiffness configurations in the hybrid material. SCP offers numerous ways to engineer SPAs for more applications.

Mathematical-Artificial Neural Network Hybrid Model to Predict Roll Force during Hot Rolling of Steel

NASA Astrophysics Data System (ADS)

Rath, S.; Sengupta, P. P.; Singh, A. P.; Marik, A. K.; Talukdar, P.

2013-07-01

Accurate prediction of roll force during hot strip rolling is essential for model based operation of hot strip mills. Traditionally, mathematical models based on theory of plastic deformation have been used for prediction of roll force. In the last decade, data driven models like artificial neural network have been tried for prediction of roll force. Pure mathematical models have accuracy limitations whereas data driven models have difficulty in convergence when applied to industrial conditions. Hybrid models by integrating the traditional mathematical formulations and data driven methods are being developed in different parts of world. This paper discusses the methodology of development of an innovative hybrid mathematical-artificial neural network model. In mathematical model, the most important factor influencing accuracy is flow stress of steel. Coefficients of standard flow stress equation, calculated by parameter estimation technique, have been used in the model. The hybrid model has been trained and validated with input and output data collected from finishing stands of Hot Strip Mill, Bokaro Steel Plant, India. It has been found that the model accuracy has been improved with use of hybrid model, over the traditional mathematical model.

Model predictive control of an air suspension system with damping multi-mode switching damper based on hybrid model

NASA Astrophysics Data System (ADS)

Sun, Xiaoqiang; Yuan, Chaochun; Cai, Yingfeng; Wang, Shaohua; Chen, Long

2017-09-01

This paper presents the hybrid modeling and the model predictive control of an air suspension system with damping multi-mode switching damper. Unlike traditional damper with continuously adjustable damping, in this study, a new damper with four discrete damping modes is applied to vehicle semi-active air suspension. The new damper can achieve different damping modes by just controlling the on-off statuses of two solenoid valves, which makes its damping adjustment more efficient and more reliable. However, since the damping mode switching induces different modes of operation, the air suspension system with the new damper poses challenging hybrid control problem. To model both the continuous/discrete dynamics and the switching between different damping modes, the framework of mixed logical dynamical (MLD) systems is used to establish the system hybrid model. Based on the resulting hybrid dynamical model, the system control problem is recast as a model predictive control (MPC) problem, which allows us to optimize the switching sequences of the damping modes by taking into account the suspension performance requirements. Numerical simulations results demonstrate the efficacy of the proposed control method finally.

Enhanced optical gain clamping for upstream packet based traffic on hybrid WDM/TDM-PON using fiber Bragg grating

NASA Astrophysics Data System (ADS)

Neto, B.; Klingler, A.; Reis, C.; Dionísio, R. P.; Nogueira, R. N.; Teixeira, A. L. J.; André, P. S.

2011-03-01

In this paper, we propose a method to mitigate the temporal power transients arising from Erbium doped fiber amplifiers (EDFAs) on packeted/bursty scenario. The technique, applicable on hybrid WDM/TDM-PON for extended reach, is based on a low power clamping provided by a distributed feedback (DFB) laser and a fiber Bragg grating (FBG). An improvement in the data signal Q factor was achieved keeping the clamping control signal with a low power, accompanied by a maximum reduction in the gain excursion of 1.12 dB.

ATLAS: An advanced PCR-method for routine visualization of telomere length in Saccharomyces cerevisiae.

PubMed

Zubko, Elena I; Shackleton, Jennifer L; Zubko, Mikhajlo K

2016-12-01

Measuring telomere length is essential in telomere biology. Southern blot hybridization is the predominant method for measuring telomere length in the genetic model Saccharomyces cerevisiae. We have further developed and refined a telomere PCR approach, which was rarely used previously (mainly in specific telomeric projects), into a robust method allowing direct visualisation of telomere length differences in routine experiments with S. cerevisiae, and showing a strong correlation of results with data obtained by Southern blot hybridization. In this expanded method denoted as ATLAS (A-dvanced T-elomere L-ength A-nalysis in S. cerevisiae), we have introduced: 1) set of new primers annealing with high specificity to telomeric regions on five different chromosomes; 2) new approach for designing reverse telomere primers that is based on the ligation of an adaptor of a fixed size to telomeric ends. ATLAS can be used at the scale of individual assays and high-throughput approaches. This simple, time/cost-effective and reproducible methodology will complement Southern blot hybridization and facilitate further progress in telomere research. Copyright © 2016 Elsevier B.V. All rights reserved.

Hybrid Upwind Splitting (HUS) by a Field-by-Field Decomposition

NASA Technical Reports Server (NTRS)

Coquel, Frederic; Liou, Meng-Sing

1995-01-01

We introduce and develop a new approach for upwind biasing: the hybrid upwind splitting (HUS) method. This original procedure is based on a suitable hybridization of current prominent flux vector splitting (FVS) and flux difference splitting (FDS) methods. The HUS method is designed to naturally combine the respective strengths of the above methods while excluding their main deficiencies. Specifically, the HUS strategy yields a family of upwind methods that exhibit the robustness of FVS schemes in the capture of nonlinear waves and the accuracy of some FDS schemes in the resolution of linear waves. We give a detailed construction of the HUS methods following a general and systematic procedure directly performed at the basic level of the field by field (i.e. waves) decomposition involved in FDS methods. For such a given decomposition, each field is endowed either with FVS or FDS numerical fluxes, depending on the nonlinear nature of the field under consideration. Such a design principle is made possible thanks to the introduction of a convenient formalism that provides us with a unified framework for upwind methods. The HUS methods we propose bring significant improvements over current methods in terms of accuracy and robustness. They yield entropy-satisfying approximate solutions as they are strongly supported in numerical experiments. Field by field hybrid numerical fluxes also achieve fairly simple and explicit expressions and hence require a computational effort between that of the FVS and FDS. Several numerical experiments ranging from stiff 1D shock-tube to high speed viscous flows problems are displayed, intending to illustrate the benefits of the present approach. We assess in particular the relevance of our HUS schemes to viscous flow calculations.

A rapid method for detection of genetically modified organisms based on magnetic separation and surface-enhanced Raman scattering.

PubMed

Guven, Burcu; Boyacı, İsmail Hakkı; Tamer, Ugur; Çalık, Pınar

2012-01-07

In this study, a new method combining magnetic separation (MS) and surface-enhanced Raman scattering (SERS) was developed to detect genetically modified organisms (GMOs). An oligonucleotide probe which is specific for 35 S DNA target was immobilized onto gold coated magnetic nanospheres to form oligonucleotide-coated nanoparticles. A self assembled monolayer was formed on gold nanorods using 5,5'-dithiobis (2-nitrobenzoic acid) (DTNB) and the second probe of the 35 S DNA target was immobilized on the activated nanorod surfaces. Probes on the nanoparticles were hybridized with the target oligonucleotide. Optimization parameters for hybridization were investigated by high performance liquid chromatography. Optimum hybridization parameters were determined as: 4 μM probe concentration, 20 min immobilization time, 30 min hybridization time, 55 °C hybridization temperature, 750 mM buffer salt concentration and pH: 7.4. Quantification of the target concentration was performed via SERS spectra of DTNB on the nanorods. The correlation between the target concentration and the SERS signal was found to be linear within the range of 25-100 nM. The analyses were performed with only one hybridization step in 40 min. Real sample analysis was conducted using Bt-176 maize sample. The results showed that the developed MS-SERS assay is capable of detecting GMOs in a rapid and selective manner. This journal is © The Royal Society of Chemistry 2012

a Hybrid Method in Vegetation Height Estimation Using Polinsar Images of Campaign Biosar

NASA Astrophysics Data System (ADS)

Dehnavi, S.; Maghsoudi, Y.

2015-12-01

Recently, there have been plenty of researches on the retrieval of forest height by PolInSAR data. This paper aims at the evaluation of a hybrid method in vegetation height estimation based on L-band multi-polarized air-borne SAR images. The SAR data used in this paper were collected by the airborne E-SAR system. The objective of this research is firstly to describe each interferometry cross correlation as a sum of contributions corresponding to single bounce, double bounce and volume scattering processes. Then, an ESPIRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm is implemented, to determine the interferometric phase of each local scatterer (ground and canopy). Secondly, the canopy height is estimated by phase differencing method, according to the RVOG (Random Volume Over Ground) concept. The applied model-based decomposition method is unrivaled, as it is not limited to specific type of vegetation, unlike the previous decomposition techniques. In fact, the usage of generalized probability density function based on the nth power of a cosine-squared function, which is characterized by two parameters, makes this method useful for different vegetation types. Experimental results show the efficiency of the approach for vegetation height estimation in the test site.

A mesoscale hybrid data assimilation system based on the JMA nonhydrostatic model

NASA Astrophysics Data System (ADS)

Ito, K.; Kunii, M.; Kawabata, T. T.; Saito, K. K.; Duc, L. L.

2015-12-01

This work evaluates the potential of a hybrid ensemble Kalman filter and four-dimensional variational (4D-Var) data assimilation system for predicting severe weather events from a deterministic point of view. This hybrid system is an adjoint-based 4D-Var system using a background error covariance matrix constructed from the mixture of a so-called NMC method and perturbations in a local ensemble transform Kalman filter data assimilation system, both of which are based on the Japan Meteorological Agency nonhydrostatic model. To construct the background error covariance matrix, we investigated two types of schemes. One is a spatial localization scheme and the other is neighboring ensemble approach, which regards the result at a horizontally spatially shifted point in each ensemble member as that obtained from a different realization of ensemble simulation. An assimilation of a pseudo single-observation located to the north of a tropical cyclone (TC) yielded an analysis increment of wind and temperature physically consistent with what is expected for a mature TC in both hybrid systems, whereas an analysis increment in a 4D-Var system using a static background error covariance distorted a structure of the mature TC. Real data assimilation experiments applied to 4 TCs and 3 local heavy rainfall events showed that hybrid systems and EnKF provided better initial conditions than the NMC-based 4D-Var, both for predicting the intensity and track forecast of TCs and for the location and amount of local heavy rainfall events.

Significance of DNA bond strength in programmable nanoparticle thermodynamics and dynamics.

PubMed

Yu, Qiuyan; Hu, Jinglei; Hu, Yi; Wang, Rong

2018-04-04

Assembly of nanoparticles (NPs) coated with complementary DNA strands leads to novel crystals with nanosized basic units rather than classic atoms, ions or molecules. The assembly process is mediated by hybridization of DNA via specific base pairing interaction, and is kinetically linked to the disassociation of DNA duplexes. DNA-level physiochemical quantities, both thermodynamic and kinetic, are key to understanding this process and essential for the design of DNA-NP crystals. The melting transition properties are helpful to judge the thermostability and sensitivity of relative DNA probes or other applications. Three different cases are investigated by changing the linker length and the spacer length on which the melting properties depend using the molecular dynamics method. Melting temperature is determined by sigmoidal melting curves based on hybridization percentage versus temperature and the Lindemann melting rule simultaneously. We provide a computational strategy based on a coarse-grained model to estimate the hybridization enthalpy, entropy and free energy from percentages of hybridizations which are readily accessible in experiments. Importantly, the lifetime of DNA bond dehybridization based on temperature and the activation energy depending on DNA bond strength are also calculated. The simulation results are in good agreement with the theoretical analysis and the present experimental data. Our study provides a good strategy to predict the melting temperature which is important for the DNA-directed nanoparticle system, and bridges the dynamics and thermodynamics of DNA-directed nanoparticle systems by estimating the equilibrium constant from the hybridization of DNA bonds quantitatively.

Hybrid Drug Delivery Patches Based on Spherical Cellulose Nanocrystals and Colloid Titania—Synthesis and Antibacterial Properties

PubMed Central

Svensson, Fredric G.; Agafonov, Alexander V.; Håkansson, Sebastian; Seisenbaeva, Gulaim A.

2018-01-01

Spherical cellulose nanocrystal-based hybrids grafted with titania nanoparticles were successfully produced for topical drug delivery. The conventional analytical filter paper was used as a precursor material for cellulose nanocrystals (CNC) production. Cellulose nanocrystals were extracted via a simple and quick two-step process based on first the complexation with Cu(II) solution in aqueous ammonia followed by acid hydrolysis with diluted H2SO4. Triclosan was selected as a model drug for complexation with titania and further introduction into the nanocellulose based composite. Obtained materials were characterized by a broad variety of microscopic, spectroscopic, and thermal analysis methods. The drug release studies showed long-term release profiles of triclosan from the titania based nanocomposite that agreed with Higuchi model. The bacterial susceptibility tests demonstrated that released triclosan retained its antibacterial activity against Escherichia coli and Staphylococcus aureus. It was found that a small amount of titania significantly improved the antibacterial activity of obtained nanocomposites, even without immobilization of model drug. Thus, the developed hybrid patches are highly promising candidates for potential application as antibacterial agents. PMID:29642486

Hybrid Drug Delivery Patches Based on Spherical Cellulose Nanocrystals and Colloid Titania-Synthesis and Antibacterial Properties.

PubMed

Evdokimova, Olga L; Svensson, Fredric G; Agafonov, Alexander V; Håkansson, Sebastian; Seisenbaeva, Gulaim A; Kessler, Vadim G

2018-04-08

Spherical cellulose nanocrystal-based hybrids grafted with titania nanoparticles were successfully produced for topical drug delivery. The conventional analytical filter paper was used as a precursor material for cellulose nanocrystals (CNC) production. Cellulose nanocrystals were extracted via a simple and quick two-step process based on first the complexation with Cu(II) solution in aqueous ammonia followed by acid hydrolysis with diluted H₂SO₄. Triclosan was selected as a model drug for complexation with titania and further introduction into the nanocellulose based composite. Obtained materials were characterized by a broad variety of microscopic, spectroscopic, and thermal analysis methods. The drug release studies showed long-term release profiles of triclosan from the titania based nanocomposite that agreed with Higuchi model. The bacterial susceptibility tests demonstrated that released triclosan retained its antibacterial activity against Escherichia coli and Staphylococcus aureus . It was found that a small amount of titania significantly improved the antibacterial activity of obtained nanocomposites, even without immobilization of model drug. Thus, the developed hybrid patches are highly promising candidates for potential application as antibacterial agents.

High-resolution multi-code implementation of unsteady Navier-Stokes flow solver based on paralleled overset adaptive mesh refinement and high-order low-dissipation hybrid schemes

NASA Astrophysics Data System (ADS)

Li, Gaohua; Fu, Xiang; Wang, Fuxin

2017-10-01

The low-dissipation high-order accurate hybrid up-winding/central scheme based on fifth-order weighted essentially non-oscillatory (WENO) and sixth-order central schemes, along with the Spalart-Allmaras (SA)-based delayed detached eddy simulation (DDES) turbulence model, and the flow feature-based adaptive mesh refinement (AMR), are implemented into a dual-mesh overset grid infrastructure with parallel computing capabilities, for the purpose of simulating vortex-dominated unsteady detached wake flows with high spatial resolutions. The overset grid assembly (OGA) process based on collection detection theory and implicit hole-cutting algorithm achieves an automatic coupling for the near-body and off-body solvers, and the error-and-try method is used for obtaining a globally balanced load distribution among the composed multiple codes. The results of flows over high Reynolds cylinder and two-bladed helicopter rotor show that the combination of high-order hybrid scheme, advanced turbulence model, and overset adaptive mesh refinement can effectively enhance the spatial resolution for the simulation of turbulent wake eddies.

EEG-based driver fatigue detection using hybrid deep generic model.

PubMed

Phyo Phyo San; Sai Ho Ling; Rifai Chai; Tran, Yvonne; Craig, Ashley; Hung Nguyen

2016-08-01

Classification of electroencephalography (EEG)-based application is one of the important process for biomedical engineering. Driver fatigue is a major case of traffic accidents worldwide and considered as a significant problem in recent decades. In this paper, a hybrid deep generic model (DGM)-based support vector machine is proposed for accurate detection of driver fatigue. Traditionally, a probabilistic DGM with deep architecture is quite good at learning invariant features, but it is not always optimal for classification due to its trainable parameters are in the middle layer. Alternatively, Support Vector Machine (SVM) itself is unable to learn complicated invariance, but produces good decision surface when applied to well-behaved features. Consolidating unsupervised high-level feature extraction techniques, DGM and SVM classification makes the integrated framework stronger and enhance mutually in feature extraction and classification. The experimental results showed that the proposed DBN-based driver fatigue monitoring system achieves better testing accuracy of 73.29 % with 91.10 % sensitivity and 55.48 % specificity. In short, the proposed hybrid DGM-based SVM is an effective method for the detection of driver fatigue in EEG.

System-wide hybrid MPC-PID control of a continuous pharmaceutical tablet manufacturing process via direct compaction.

PubMed

Singh, Ravendra; Ierapetritou, Marianthi; Ramachandran, Rohit

2013-11-01

The next generation of QbD based pharmaceutical products will be manufactured through continuous processing. This will allow the integration of online/inline monitoring tools, coupled with an efficient advanced model-based feedback control systems, to achieve precise control of process variables, so that the predefined product quality can be achieved consistently. The direct compaction process considered in this study is highly interactive and involves time delays for a number of process variables due to sensor placements, process equipment dimensions, and the flow characteristics of the solid material. A simple feedback regulatory control system (e.g., PI(D)) by itself may not be sufficient to achieve the tight process control that is mandated by regulatory authorities. The process presented herein comprises of coupled dynamics involving slow and fast responses, indicating the requirement of a hybrid control scheme such as a combined MPC-PID control scheme. In this manuscript, an efficient system-wide hybrid control strategy for an integrated continuous pharmaceutical tablet manufacturing process via direct compaction has been designed. The designed control system is a hybrid scheme of MPC-PID control. An effective controller parameter tuning strategy involving an ITAE method coupled with an optimization strategy has been used for tuning of both MPC and PID parameters. The designed hybrid control system has been implemented in a first-principles model-based flowsheet that was simulated in gPROMS (Process System Enterprise). Results demonstrate enhanced performance of critical quality attributes (CQAs) under the hybrid control scheme compared to only PID or MPC control schemes, illustrating the potential of a hybrid control scheme in improving pharmaceutical manufacturing operations. Copyright © 2013 Elsevier B.V. All rights reserved.

Interfacial transduction of nucleic acid hybridization using immobilized quantum dots as donors in fluorescence resonance energy transfer.

PubMed

Algar, W Russ; Krull, Ulrich J

2009-01-06

Fluorescence resonance energy transfer (FRET) using immobilized quantum dots (QDs) as energy donors was explored as a transduction method for the detection of nucleic acid hybridization at an interface. This research was motivated by the success of the QD-FRET-based transduction of nucleic acid hybridization in solution-phase assays. This new work represents a fundamental step toward the assembly of a biosensor, where immobilization of the selective chemistry on a surface is desired. After immobilizing QD-probe oligonucleotide conjugates on optical fibers, a demonstration of the retention of selectivity was achieved by the introduction of acceptor (Cy3)-labeled single-stranded target oligonucleotides. Hybridization generated the proximity required for FRET, and the resulting fluorescence spectra provided an analytical signal proportional to the amount of target. This research provides an important framework for the future development of nucleic acid biosensors based on QDs and FRET. The most important findings of this work are that (1) a QD-FRET solid-phase hybridization assay is viable and (2) a passivating layer of denatured bovine serum albumin alleviates nonspecific adsorption, ultimately resulting in (3) the potential for a reusable assay format and mismatch discrimination. In this, the first incarnation of a solid-phase QD-FRET hybridization assay, the limit of detection was found to be 5 nM, and the dynamic range was almost 2 orders of magnitude. Selective discrimination of the target was shown using a three-base-pairs mismatch from a fully complementary sequence. Despite a gradual loss of signal, reuse of the optical fibers over multiple cycles of hybridization and dehybridization was possible. Directions for further improvement of the analytical performance by optimizing the design of the QD-probe oligonucleotide interface are identified.

Detection of pulmonary nodules in CT images based on fuzzy integrated active contour model and hybrid parametric mixture model.

PubMed

Li, Bin; Chen, Kan; Tian, Lianfang; Yeboah, Yao; Ou, Shanxing

2013-01-01

The segmentation and detection of various types of nodules in a Computer-aided detection (CAD) system present various challenges, especially when (1) the nodule is connected to a vessel and they have very similar intensities; (2) the nodule with ground-glass opacity (GGO) characteristic possesses typical weak edges and intensity inhomogeneity, and hence it is difficult to define the boundaries. Traditional segmentation methods may cause problems of boundary leakage and "weak" local minima. This paper deals with the above mentioned problems. An improved detection method which combines a fuzzy integrated active contour model (FIACM)-based segmentation method, a segmentation refinement method based on Parametric Mixture Model (PMM) of juxta-vascular nodules, and a knowledge-based C-SVM (Cost-sensitive Support Vector Machines) classifier, is proposed for detecting various types of pulmonary nodules in computerized tomography (CT) images. Our approach has several novel aspects: (1) In the proposed FIACM model, edge and local region information is incorporated. The fuzzy energy is used as the motivation power for the evolution of the active contour. (2) A hybrid PMM Model of juxta-vascular nodules combining appearance and geometric information is constructed for segmentation refinement of juxta-vascular nodules. Experimental results of detection for pulmonary nodules show desirable performances of the proposed method.

Combinatorial high-throughput optical screening of high performance Pd alloy cathode for hybrid Li-air battery.

PubMed

Jun, Young Jin; Park, Sung Hyeon; Woo, Seong Ihl

2014-12-08

Combinatorial high-throughput optical screening method was developed to find the optimum composition of highly active Pd-based catalysts at the cathode of the hybrid Li-air battery. Pd alone, which is one-third the cost of Pt, has difficulty in replacing Pt; therefore, the integration of other metals was investigated to improve its performance toward oxygen reduction reaction (ORR). Among the binary Pd-based catalysts, the composition of Pd-Ir derived catalysts had higher performance toward ORR compared to other Pd-based binary combinations. The composition at 88:12 at. % (Pd: Ir) showed the highest activity toward ORR at the cathode of the hybrid Li-air battery. The prepared Pd(88)Ir(12)/C catalyst showed a current density of -2.58 mA cm(-2) at 0.8 V (vs RHE), which was around 30% higher compared to that of Pd/C (-1.97 mA cm(-2)). When the prepared Pd(88)Ir(12)/C catalyst was applied to the hybrid Li-air battery, the polarization of the cell was reduced and the energy efficiency of the cell was about 30% higher than that of the cell with Pd/C.

TEMPTING system: a hybrid method of rule and machine learning for temporal relation extraction in patient discharge summaries.

PubMed

Chang, Yung-Chun; Dai, Hong-Jie; Wu, Johnny Chi-Yang; Chen, Jian-Ming; Tsai, Richard Tzong-Han; Hsu, Wen-Lian

2013-12-01

Patient discharge summaries provide detailed medical information about individuals who have been hospitalized. To make a precise and legitimate assessment of the abundant data, a proper time layout of the sequence of relevant events should be compiled and used to drive a patient-specific timeline, which could further assist medical personnel in making clinical decisions. The process of identifying the chronological order of entities is called temporal relation extraction. In this paper, we propose a hybrid method to identify appropriate temporal links between a pair of entities. The method combines two approaches: one is rule-based and the other is based on the maximum entropy model. We develop an integration algorithm to fuse the results of the two approaches. All rules and the integration algorithm are formally stated so that one can easily reproduce the system and results. To optimize the system's configuration, we used the 2012 i2b2 challenge TLINK track dataset and applied threefold cross validation to the training set. Then, we evaluated its performance on the training and test datasets. The experiment results show that the proposed TEMPTING (TEMPoral relaTion extractING) system (ranked seventh) achieved an F-score of 0.563, which was at least 30% better than that of the baseline system, which randomly selects TLINK candidates from all pairs and assigns the TLINK types. The TEMPTING system using the hybrid method also outperformed the stage-based TEMPTING system. Its F-scores were 3.51% and 0.97% better than those of the stage-based system on the training set and test set, respectively. Copyright © 2013 Elsevier Inc. All rights reserved.

Power Source Status Estimation and Drive Control Method for Autonomous Decentralized Hybrid Train

NASA Astrophysics Data System (ADS)

Furuya, Takemasa; Ogawa, Kenichi; Yamamoto, Takamitsu; Hasegawa, Hitoshi

A hybrid control system has two main functions: power sharing and equipment protection. In this paper, we discuss the design, construction and testing of a drive control method for an autonomous decentralized hybrid train with 100-kW-class fuel cells (FC) and 36-kWh lithium-ion batteries (Li-Batt). The main objectives of this study are to identify the operation status of the power sources on the basis of the input voltage of the traction inverter and to estimate the maximum traction power control basis of the power-source status. The proposed control method is useful in preventing overload operation of the onboard power sources in an autonomous decentralized hybrid system that has a flexible main circuit configuration and a few control signal lines. Further, with this method, the initial cost of a hybrid system can be reduced and the retrofit design of the hybrid system can be simplified. The effectiveness of the proposed method is experimentally confirmed by using a real-scale hybrid train system.

Magnetic steering control of multi-cellular bio-hybrid microswimmers.

PubMed

Carlsen, Rika Wright; Edwards, Matthew R; Zhuang, Jiang; Pacoret, Cecile; Sitti, Metin

2014-10-07

Bio-hybrid devices, which integrate biological cells with synthetic components, have opened a new path in miniaturized systems with the potential to provide actuation and control for systems down to a few microns in size. Here, we address the challenge of remotely controlling bio-hybrid microswimmers propelled by multiple bacterial cells. These devices have been proposed as a viable method for targeted drug delivery but have also been shown to exhibit stochastic motion. We demonstrate a method of remote magnetic control that significantly reduces the stochasticity of the motion, enabling steering control. The demonstrated microswimmers consist of multiple Serratia marcescens (S. marcescens) bacteria attached to a 6 μm-diameter superparamagnetic bead. We characterize their motion and define the parameters governing their controllability. We show that the microswimmers can be controlled along two-dimensional (2-D) trajectories using weak magnetic fields (≤10 mT) and can achieve 2-D swimming speeds up to 7.3 μm s(-1). This magnetic steering approach can be integrated with sensory-based steering in future work, enabling new control strategies for bio-hybrid microsystems.

New t-gap insertion-deletion-like metrics for DNA hybridization thermodynamic modeling.

PubMed

D'yachkov, Arkadii G; Macula, Anthony J; Pogozelski, Wendy K; Renz, Thomas E; Rykov, Vyacheslav V; Torney, David C

2006-05-01

We discuss the concept of t-gap block isomorphic subsequences and use it to describe new abstract string metrics that are similar to the Levenshtein insertion-deletion metric. Some of the metrics that we define can be used to model a thermodynamic distance function on single-stranded DNA sequences. Our model captures a key aspect of the nearest neighbor thermodynamic model for hybridized DNA duplexes. One version of our metric gives the maximum number of stacked pairs of hydrogen bonded nucleotide base pairs that can be present in any secondary structure in a hybridized DNA duplex without pseudoknots. Thermodynamic distance functions are important components in the construction of DNA codes, and DNA codes are important components in biomolecular computing, nanotechnology, and other biotechnical applications that employ DNA hybridization assays. We show how our new distances can be calculated by using a dynamic programming method, and we derive a Varshamov-Gilbert-like lower bound on the size of some of codes using these distance functions as constraints. We also discuss software implementation of our DNA code design methods.

Robust Power Management Control for Stand-Alone Hybrid Power Generation System

NASA Astrophysics Data System (ADS)

Kamal, Elkhatib; Adouane, Lounis; Aitouche, Abdel; Mohammed, Walaa

2017-01-01

This paper presents a new robust fuzzy control of energy management strategy for the stand-alone hybrid power systems. It consists of two levels named centralized fuzzy supervisory control which generates the power references for each decentralized robust fuzzy control. Hybrid power systems comprises: a photovoltaic panel and wind turbine as renewable sources, a micro turbine generator and a battery storage system. The proposed control strategy is able to satisfy the load requirements based on a fuzzy supervisor controller and manage power flows between the different energy sources and the storage unit by respecting the state of charge and the variation of wind speed and irradiance. Centralized controller is designed based on If-Then fuzzy rules to manage and optimize the hybrid power system production by generating the reference power for photovoltaic panel and wind turbine. Decentralized controller is based on the Takagi-Sugeno fuzzy model and permits us to stabilize each photovoltaic panel and wind turbine in presence of disturbances and parametric uncertainties and to optimize the tracking reference which is given by the centralized controller level. The sufficient conditions stability are formulated in the format of linear matrix inequalities using the Lyapunov stability theory. The effectiveness of the proposed Strategy is finally demonstrated through a SAHPS (stand-alone hybrid power systems) to illustrate the effectiveness of the overall proposed method.

On the integration of reinforcement learning and approximate reasoning for control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

The author discusses the importance of strengthening the knowledge representation characteristic of reinforcement learning techniques using methods such as approximate reasoning. The ARIC (approximate reasoning-based intelligent control) architecture is an example of such a hybrid approach in which the fuzzy control rules are modified (fine-tuned) using reinforcement learning. ARIC also demonstrates that it is possible to start with an approximately correct control knowledge base and learn to refine this knowledge through further experience. On the other hand, techniques such as the TD (temporal difference) algorithm and Q-learning establish stronger theoretical foundations for their use in adaptive control and also in stability analysis of hybrid reinforcement learning and approximate reasoning-based controllers.

Practical state of health estimation of power batteries based on Delphi method and grey relational grade analysis

NASA Astrophysics Data System (ADS)

Sun, Bingxiang; Jiang, Jiuchun; Zheng, Fangdan; Zhao, Wei; Liaw, Bor Yann; Ruan, Haijun; Han, Zhiqiang; Zhang, Weige

2015-05-01

The state of health (SOH) estimation is very critical to battery management system to ensure the safety and reliability of EV battery operation. Here, we used a unique hybrid approach to enable complex SOH estimations. The approach hybridizes the Delphi method known for its simplicity and effectiveness in applying weighting factors for complicated decision-making and the grey relational grade analysis (GRGA) for multi-factor optimization. Six critical factors were used in the consideration for SOH estimation: peak power at 30% state-of-charge (SOC), capacity, the voltage drop at 30% SOC with a C/3 pulse, the temperature rises at the end of discharge and charge at 1C; respectively, and the open circuit voltage at the end of charge after 1-h rest. The weighting of these factors for SOH estimation was scored by the 'experts' in the Delphi method, indicating the influencing power of each factor on SOH. The parameters for these factors expressing the battery state variations are optimized by GRGA. Eight battery cells were used to illustrate the principle and methodology to estimate the SOH by this hybrid approach, and the results were compared with those based on capacity and power capability. The contrast among different SOH estimations is discussed.

A hybrid method based on Band Pass Filter and Correlation Algorithm to improve debris sensor capacity

NASA Astrophysics Data System (ADS)

Hong, Wei; Wang, Shaoping; Liu, Haokuo; Tomovic, Mileta M.; Chao, Zhang

2017-01-01

The inductive debris detection is an effective method for monitoring mechanical wear, and could be used to prevent serious accidents. However, debris detection during early phase of mechanical wear, when small debris (<100 um) is generated, requires that the sensor has high sensitivity with respect to background noise. In order to detect smaller debris by existing sensors, this paper presents a hybrid method which combines Band Pass Filter and Correlation Algorithm to improve sensor signal-to-noise ratio (SNR). The simulation results indicate that the SNR will be improved at least 2.67 times after signal processing. In other words, this method ensures debris identification when the sensor's SNR is bigger than -3 dB. Thus, smaller debris will be detected in the same SNR. Finally, effectiveness of the proposed method is experimentally validated.

A robust hybrid fuzzy-simulated annealing-intelligent water drops approach for tuning a distribution static compensator nonlinear controller in a distribution system

NASA Astrophysics Data System (ADS)

Bagheri Tolabi, Hajar; Hosseini, Rahil; Shakarami, Mahmoud Reza

2016-06-01

This article presents a novel hybrid optimization approach for a nonlinear controller of a distribution static compensator (DSTATCOM). The DSTATCOM is connected to a distribution system with the distributed generation units. The nonlinear control is based on partial feedback linearization. Two proportional-integral-derivative (PID) controllers regulate the voltage and track the output in this control system. In the conventional scheme, the trial-and-error method is used to determine the PID controller coefficients. This article uses a combination of a fuzzy system, simulated annealing (SA) and intelligent water drops (IWD) algorithms to optimize the parameters of the controllers. The obtained results reveal that the response of the optimized controlled system is effectively improved by finding a high-quality solution. The results confirm that using the tuning method based on the fuzzy-SA-IWD can significantly decrease the settling and rising times, the maximum overshoot and the steady-state error of the voltage step response of the DSTATCOM. The proposed hybrid tuning method for the partial feedback linearizing (PFL) controller achieved better regulation of the direct current voltage for the capacitor within the DSTATCOM. Furthermore, in the event of a fault the proposed controller tuned by the fuzzy-SA-IWD method showed better performance than the conventional controller or the PFL controller without optimization by the fuzzy-SA-IWD method with regard to both fault duration and clearing times.

Detection and identification of intestinal pathogenic bacteria by hybridization to oligonucleotide microarrays

PubMed Central

Jin, Lian-Qun; Li, Jun-Wen; Wang, Sheng-Qi; Chao, Fu-Huan; Wang, Xin-Wei; Yuan, Zheng-Quan

2005-01-01

AIM: To detect the common intestinal pathogenic bacteria quickly and accurately. METHODS: A rapid (<3 h) experimental procedure was set up based upon the gene chip technology. Target genes were amplified and hybridized by oligonucleotide microarrays. RESULTS: One hundred and seventy strains of bacteria in pure culture belonging to 11 genera were successfully discriminated under comparatively same conditions, and a series of specific hybridization maps corresponding to each kind of bacteria were obtained. When this method was applied to 26 divided cultures, 25 (96.2%) were identified. CONCLUSION: Salmonella sp., Escherichia coli, Shigella sp., Listeria monocytogenes, Vibrio parahaemolyticus, Staphylococcus aureus, Proteus sp., Bacillus cereus, Vibrio cholerae, Enterococcus faecalis, Yersinia enterocolitica, and Campylobacter jejuni can be detected and identified by our microarrays. The accuracy, range, and discrimination power of this assay can be continually improved by adding further oligonucleotides to the arrays without any significant increase of complexity or cost. PMID:16437687

Continuously tunable nucleic acid hybridization probes.

PubMed

Wu, Lucia R; Wang, Juexiao Sherry; Fang, John Z; Evans, Emily R; Pinto, Alessandro; Pekker, Irena; Boykin, Richard; Ngouenet, Celine; Webster, Philippa J; Beechem, Joseph; Zhang, David Yu

2015-12-01

In silico-designed nucleic acid probes and primers often do not achieve favorable specificity and sensitivity tradeoffs on the first try, and iterative empirical sequence-based optimization is needed, particularly in multiplexed assays. We present a novel, on-the-fly method of tuning probe affinity and selectivity by adjusting the stoichiometry of auxiliary species, which allows for independent and decoupled adjustment of the hybridization yield for different probes in multiplexed assays. Using this method, we achieved near-continuous tuning of probe effective free energy. To demonstrate our approach, we enforced uniform capture efficiency of 31 DNA molecules (GC content, 0-100%), maximized the signal difference for 11 pairs of single-nucleotide variants and performed tunable hybrid capture of mRNA from total RNA. Using the Nanostring nCounter platform, we applied stoichiometric tuning to simultaneously adjust yields for a 24-plex assay, and we show multiplexed quantitation of RNA sequences and variants from formalin-fixed, paraffin-embedded samples.

New Avenue for Limiting Degradation in NanoLi4Ti5O12 for Ultrafast-Charge Lithium-Ion Batteries: Hybrid Polymer-Inorganic Particles.

PubMed

Daigle, Jean-Christophe; Asakawa, Yuichiro; Beaupré, Mélanie; Vieillette, René; Laul, Dharminder; Trudeau, Michel; Zaghib, Karim

2017-12-13

Lithium titanium oxide (Li 4 Ti 5 O 12 )-based cells are a very promising battery technology for ultrafast-charge-discharge and long-cycle-life batteries. However, the surface reactivity of lithium titanium oxide in the presence of organic electrolytes continues to be a problem that may cause expansion of pouch cells. In this study, we report on the development of a simple and economical grafting method for forming hybrid polymer-Li 4 Ti 15 O 12 nanoparticles, which can be successfully applied in lithium-ion batteries. This method utilizes a low-cost and scalable hydrophobic polymer that is applicable in industrial processes. The hybrid materials demonstrated exceptional capability for preventing the degradation of cells in accelerated aging and operating over 150 cycles at 1C and 45 °C.

Analysis/design of strip reinforced random composites (strip hybrids)

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Sinclair, J. H.

1978-01-01

Advanced analysis methods and composite mechanics were applied to a strip-reinforced random composite square panel with fixed ends to illustrate the use of these methods for the a priori assessment of the composite panel when subjected to complex loading conditions. The panel was assumed to be of E-glass random composite. The strips were assumed to be of three advanced unidirectional composites to cover a range of low, intermediate, and high modulus stiffness. The panels were assumed to be subjected to complex loadings to assess their adequacy as load-carrying members in auto body, aircraft engine nacelle and windmill blade applications. The results show that strip hybrid panels can be several times more structurally efficient than the random composite base materials. Some of the results are presented in graphical form and procedures are described for use of these graphs as guides for preliminary design of strip hybrids.

pmx: Automated protein structure and topology generation for alchemical perturbations

PubMed Central

Gapsys, Vytautas; Michielssens, Servaas; Seeliger, Daniel; de Groot, Bert L

2015-01-01

Computational protein design requires methods to accurately estimate free energy changes in protein stability or binding upon an amino acid mutation. From the different approaches available, molecular dynamics-based alchemical free energy calculations are unique in their accuracy and solid theoretical basis. The challenge in using these methods lies in the need to generate hybrid structures and topologies representing two physical states of a system. A custom made hybrid topology may prove useful for a particular mutation of interest, however, a high throughput mutation analysis calls for a more general approach. In this work, we present an automated procedure to generate hybrid structures and topologies for the amino acid mutations in all commonly used force fields. The described software is compatible with the Gromacs simulation package. The mutation libraries are readily supported for five force fields, namely Amber99SB, Amber99SB*-ILDN, OPLS-AA/L, Charmm22*, and Charmm36. PMID:25487359

Comprehensive Genomic Profiling Identifies a Subset of Crizotinib-Responsive ALK-Rearranged Non-Small Cell Lung Cancer Not Detected by Fluorescence In Situ Hybridization

PubMed Central

Hensing, Thomas; Schrock, Alexa B.; Allen, Justin; Sanford, Eric; Gowen, Kyle; Kulkarni, Atul; He, Jie; Suh, James H.; Lipson, Doron; Elvin, Julia A.; Yelensky, Roman; Chalmers, Zachary; Chmielecki, Juliann; Peled, Nir; Klempner, Samuel J.; Firozvi, Kashif; Frampton, Garrett M.; Molina, Julian R.; Menon, Smitha; Brahmer, Julie R.; MacMahon, Heber; Nowak, Jan; Ou, Sai-Hong Ignatius; Zauderer, Marjorie; Ladanyi, Marc; Zakowski, Maureen; Fischbach, Neil; Ross, Jeffrey S.; Stephens, Phil J.; Miller, Vincent A.; Wakelee, Heather

2016-01-01

Introduction. For patients with non-small cell lung cancer (NSCLC) to benefit from ALK inhibitors, sensitive and specific detection of ALK genomic rearrangements is needed. ALK break-apart fluorescence in situ hybridization (FISH) is the U.S. Food and Drug Administration approved and standard-of-care diagnostic assay, but identification of ALK rearrangements by other methods reported in NSCLC cases that tested negative for ALK rearrangements by FISH suggests a significant false-negative rate. We report here a large series of NSCLC cases assayed by hybrid-capture-based comprehensive genomic profiling (CGP) in the course of clinical care. Materials and Methods. Hybrid-capture-based CGP using next-generation sequencing was performed in the course of clinical care of 1,070 patients with advanced lung cancer. Each tumor sample was evaluated for all classes of genomic alterations, including base-pair substitutions, insertions/deletions, copy number alterations and rearrangements, as well as fusions/rearrangements. Results. A total of 47 patients (4.4%) were found to harbor ALK rearrangements, of whom 41 had an EML4-ALK fusion, and 6 had other fusion partners, including 3 previously unreported rearrangement events: EIF2AK-ALK, PPM1B-ALK, and PRKAR1A-ALK. Of 41 patients harboring ALK rearrangements, 31 had prior FISH testing results available. Of these, 20 were ALK FISH positive, and 11 (35%) were ALK FISH negative. Of the latter 11 patients, 9 received crizotinib based on the CGP results, and 7 achieved a response with median duration of 17 months. Conclusion. Comprehensive genomic profiling detected canonical ALK rearrangements and ALK rearrangements with noncanonical fusion partners in a subset of patients with NSCLC with previously negative ALK FISH results. In this series, such patients had durable responses to ALK inhibitors, comparable to historical response rates for ALK FISH-positive cases. Implications for Practice: Comprehensive genomic profiling (CGP) that includes hybrid capture and specific baiting of intron 19 of ALK is a highly sensitive, alternative method for identification of drug-sensitive ALK fusions in patients with non-small cell lung cancer (NSCLC) who had previously tested negative using standard ALK fluorescence in situ hybridization (FISH) diagnostic assays. Given the proven benefit of treatment with crizotinib and second-generation ALK inhibitors in patients with ALK fusions, CGP should be considered in patients with NSCLC, including those who have tested negative for other alterations, including negative results using ALK FISH testing. PMID:27245569

An enhanced security solution for electronic medical records based on AES hybrid technique with SOAP/XML and SHA-1.

PubMed

Kiah, M L Mat; Nabi, Mohamed S; Zaidan, B B; Zaidan, A A

2013-10-01

This study aims to provide security solutions for implementing electronic medical records (EMRs). E-Health organizations could utilize the proposed method and implement recommended solutions in medical/health systems. Majority of the required security features of EMRs were noted. The methods used were tested against each of these security features. In implementing the system, the combination that satisfied all of the security features of EMRs was selected. Secure implementation and management of EMRs facilitate the safeguarding of the confidentiality, integrity, and availability of e-health organization systems. Health practitioners, patients, and visitors can use the information system facilities safely and with confidence anytime and anywhere. After critically reviewing security and data transmission methods, a new hybrid method was proposed to be implemented on EMR systems. This method will enhance the robustness, security, and integration of EMR systems. The hybrid of simple object access protocol/extensible markup language (XML) with advanced encryption standard and secure hash algorithm version 1 has achieved the security requirements of an EMR system with the capability of integrating with other systems through the design of XML messages.

Three-Dimensional Printing Based Hybrid Manufacturing of Microfluidic Devices.

PubMed

Alapan, Yunus; Hasan, Muhammad Noman; Shen, Richang; Gurkan, Umut A

2015-05-01

Microfluidic platforms offer revolutionary and practical solutions to challenging problems in biology and medicine. Even though traditional micro/nanofabrication technologies expedited the emergence of the microfluidics field, recent advances in advanced additive manufacturing hold significant potential for single-step, stand-alone microfluidic device fabrication. One such technology, which holds a significant promise for next generation microsystem fabrication is three-dimensional (3D) printing. Presently, building 3D printed stand-alone microfluidic devices with fully embedded microchannels for applications in biology and medicine has the following challenges: (i) limitations in achievable design complexity, (ii) need for a wider variety of transparent materials, (iii) limited z-resolution, (iv) absence of extremely smooth surface finish, and (v) limitations in precision fabrication of hollow and void sections with extremely high surface area to volume ratio. We developed a new way to fabricate stand-alone microfluidic devices with integrated manifolds and embedded microchannels by utilizing a 3D printing and laser micromachined lamination based hybrid manufacturing approach. In this new fabrication method, we exploit the minimized fabrication steps enabled by 3D printing, and reduced assembly complexities facilitated by laser micromachined lamination method. The new hybrid fabrication method enables key features for advanced microfluidic system architecture: (i) increased design complexity in 3D, (ii) improved control over microflow behavior in all three directions and in multiple layers, (iii) transverse multilayer flow and precisely integrated flow distribution, and (iv) enhanced transparency for high resolution imaging and analysis. Hybrid manufacturing approaches hold great potential in advancing microfluidic device fabrication in terms of standardization, fast production, and user-independent manufacturing.

Lateral flow nucleic acid biosensor for sensitive detection of microRNAs based on the dual amplification strategy of duplex-specific nuclease and hybridization chain reaction.

PubMed

Ying, Na; Ju, Chuanjing; Sun, Xiuwei; Li, Letian; Chang, Hongbiao; Song, Guangping; Li, Zhongyi; Wan, Jiayu; Dai, Enyong

2017-01-01

MicroRNAs (miRNAs) constitute novel biomarkers for various diseases. Accurate and quantitative analysis of miRNA expression is critical for biomedical research and clinical theranostics. In this study, a method was developed for sensitive and specific detection of miRNAs via dual signal amplification based on duplex specific nuclease (DSN) and hybridization chain reaction (HCR). A reporter probe (RP), comprising recognition sequence (3' end modified with biotin) for a target miRNA of miR-21 and capture sequence (5' end modified with Fam) for HCR product, was designed and synthesized. HCR was initiated by partial sequence of initiator probe (IP), the other part of which can hybridize with capture sequence of RP, and was assembled by hairpin probes modified with biotin (H1-bio and H2-bio). A miR-21 triggered cyclical DSN cleavage of RP, which was immobilized to a streptavidin (SA) coated magnetic bead (MB). The released Fam labeled capture sequence then hybridized with the HCR product to generate a detectable dsDNA. This polymer was then dropped on lateral flow strip and positive result was observed. The proposed method allowed quantitative sequence-specific detection of miR-21 (with a detection limit of 2.1 fM, S/N = 3) in a dynamic range from 100 fM to 100 pM, with an excellent ability to discriminate differences in miRNAs. The method showed acceptable testing recoveries for the determination of miRNAs in serum.

Three-Dimensional Printing Based Hybrid Manufacturing of Microfluidic Devices

PubMed Central

Shen, Richang; Gurkan, Umut A.

2016-01-01

Microfluidic platforms offer revolutionary and practical solutions to challenging problems in biology and medicine. Even though traditional micro/nanofabrication technologies expedited the emergence of the microfluidics field, recent advances in advanced additive manufacturing hold significant potential for single-step, stand-alone microfluidic device fabrication. One such technology, which holds a significant promise for next generation microsystem fabrication is three-dimensional (3D) printing. Presently, building 3D printed stand-alone microfluidic devices with fully embedded microchannels for applications in biology and medicine has the following challenges: (i) limitations in achievable design complexity, (ii) need for a wider variety of transparent materials, (iii) limited z-resolution, (iv) absence of extremely smooth surface finish, and (v) limitations in precision fabrication of hollow and void sections with extremely high surface area to volume ratio. We developed a new way to fabricate stand-alone microfluidic devices with integrated manifolds and embedded microchannels by utilizing a 3D printing and laser micromachined lamination based hybrid manufacturing approach. In this new fabrication method, we exploit the minimized fabrication steps enabled by 3D printing, and reduced assembly complexities facilitated by laser micromachined lamination method. The new hybrid fabrication method enables key features for advanced microfluidic system architecture: (i) increased design complexity in 3D, (ii) improved control over microflow behavior in all three directions and in multiple layers, (iii) transverse multilayer flow and precisely integrated flow distribution, and (iv) enhanced transparency for high resolution imaging and analysis. Hybrid manufacturing approaches hold great potential in advancing microfluidic device fabrication in terms of standardization, fast production, and user-independent manufacturing. PMID:27512530

Hybrid optimization and Bayesian inference techniques for a non-smooth radiation detection problem

DOE PAGES

Stefanescu, Razvan; Schmidt, Kathleen; Hite, Jason; ...

2016-12-12

In this paper, we propose several algorithms to recover the location and intensity of a radiation source located in a simulated 250 × 180 m block of an urban center based on synthetic measurements. Radioactive decay and detection are Poisson random processes, so we employ likelihood functions based on this distribution. Owing to the domain geometry and the proposed response model, the negative logarithm of the likelihood is only piecewise continuous differentiable, and it has multiple local minima. To address these difficulties, we investigate three hybrid algorithms composed of mixed optimization techniques. For global optimization, we consider simulated annealing, particlemore » swarm, and genetic algorithm, which rely solely on objective function evaluations; that is, they do not evaluate the gradient in the objective function. By employing early stopping criteria for the global optimization methods, a pseudo-optimum point is obtained. This is subsequently utilized as the initial value by the deterministic implicit filtering method, which is able to find local extrema in non-smooth functions, to finish the search in a narrow domain. These new hybrid techniques, combining global optimization and implicit filtering address, difficulties associated with the non-smooth response, and their performances, are shown to significantly decrease the computational time over the global optimization methods. To quantify uncertainties associated with the source location and intensity, we employ the delayed rejection adaptive Metropolis and DiffeRential Evolution Adaptive Metropolis algorithms. Finally, marginal densities of the source properties are obtained, and the means of the chains compare accurately with the estimates produced by the hybrid algorithms.« less

Direct fluorescence in situ hybridization on human metaphase chromosomes using quantum dot-platinum labeled DNA probes

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

Hwang, Gyoyeon; Biological Chemistry, Korea University of Science and Technology, 217, Gajeong-ro, Yuseong-gu, Deajeon; Lee, Hansol

The telomere shortening in chromosomes implies the senescence, apoptosis, or oncogenic transformation of cells. Since detecting telomeres in aging and diseases like cancer, is important, the direct detection of telomeres has been a very useful biomarker. We propose a telomere detection method using a newly synthesized quantum dot (QD) based probe with oligonucleotide conjugation and direct fluorescence in situ hybridization (FISH). QD-oligonucleotides were prepared with metal coordination bonding based on platinum-guanine binding reported in our previous work. The QD-oligonucleotide conjugation method has an advantage where any sequence containing guanine at the end can be easily bound to the starting QD-Ptmore » conjugate. A synthesized telomeric oligonucleotide was bound to the QD-Pt conjugate successfully and this probe hybridized specifically on the telomere of fabricated MV-4-11 and MOLT-4 chromosomes. Additionally, the QD-telomeric oligonucleotide probe successfully detected the telomeres on the CGH metaphase slide. Due to the excellent photostability and high quantum yield of QDs, the QD-oligonucleotide probe has high fluorescence intensity when compared to the organic dye-oligonucleotide probe. Our QD-oligonucleotide probe, conjugation method of this QD probe, and hybridization protocol with the chromosomes can be a useful tool for chromosome painting and FISH. - Highlights: • We prepared a probe linked between QD and telomeric oligonucleotide with platinum-guanine bonding. • Telomeres were detected by our new telomere probes successfully in three different human metaphase chromosomes. • QDPt-DNA probe has high fluorescence intensity in comparison with organic dye-DNA probe.« less

Adaptive sensor-based ultra-high accuracy solar concentrator tracker

NASA Astrophysics Data System (ADS)

Brinkley, Jordyn; Hassanzadeh, Ali

2017-09-01

Conventional solar trackers use information of the sun's position, either by direct sensing or by GPS. Our method uses the shading of the receiver. This, coupled with nonimaging optics design allows us to achieve ultra-high concentration. Incorporating a sensor based shadow tracking method with a two stage concentration solar hybrid parabolic trough allows the system to maintain high concentration with acute accuracy.

Prospective technologies for using biohydrogen in power installations on the basis of fuel cells (a review)

NASA Astrophysics Data System (ADS)

Dunikov, D. O.; Borzenko, V. I.; Malyshenko, S. P.; Blinov, D. V.; Kazakov, A. N.

2013-03-01

The present state of technology for obtaining hydrogen by biological methods and for purifying it is reviewed from the viewpoint of its possible use in kilowatt-class power installations. Hybrid membranesorption biohydrogen purification methods combining membrane-based pretreatment and sorption-based final treatment, also with the use of metal hydrides, should be regarded as the most efficient ones.

Bridging paradigms: hybrid mechanistic-discriminative predictive models.

PubMed

Doyle, Orla M; Tsaneva-Atansaova, Krasimira; Harte, James; Tiffin, Paul A; Tino, Peter; Díaz-Zuccarini, Vanessa

2013-03-01

Many disease processes are extremely complex and characterized by multiple stochastic processes interacting simultaneously. Current analytical approaches have included mechanistic models and machine learning (ML), which are often treated as orthogonal viewpoints. However, to facilitate truly personalized medicine, new perspectives may be required. This paper reviews the use of both mechanistic models and ML in healthcare as well as emerging hybrid methods, which are an exciting and promising approach for biologically based, yet data-driven advanced intelligent systems.

Non-centrosymmetric Au-SnO2 hybrid nanostructures with strong localization of plasmonic for enhanced photocatalysis application

NASA Astrophysics Data System (ADS)

Wu, Wei; Liao, Lei; Zhang, Shaofeng; Zhou, Juan; Xiao, Xiangheng; Ren, Feng; Sun, Lingling; Dai, Zhigao; Jiang, Changzhong

2013-05-01

We present an innovative approach to the production of sub-100 nm hollow Au-SnO2 hybrid nanospheres, employing a low-cost, surfactant-free and environmentally friendly solution-based route. The hollow hybrid nanostructures were synthesized using a seed-mediated hydrothermal method, which can be divided into two stages: (1) formation of multicore-shell Au@SnO2 nanoparticles (NPs) and (2) thermal diffusion and ripening to form hollow Au-SnO2 hybrid NPs. The morphology, optical properties and formation mechanism were determined by a collection of joint techniques. Photocatalytic degradation of Rhodamine B (RhB) in the liquid phase served as a probe reaction to evaluate the activity of the as-prepared hollow hybrid Au-SnO2 NPs under the irradiation of both visible light and ultraviolet light. Significantly, the as-obtained Au-SnO2 hybrid nanostructures exhibited enhanced visible light or UV photocatalytic abilities, remarkably superior to commercial pure SnO2 products and P25 TiO2, mainly owing to the effective electron hole separation at the SnO2-Au interfaces and strong localization of plasmonic near-fields effects.We present an innovative approach to the production of sub-100 nm hollow Au-SnO2 hybrid nanospheres, employing a low-cost, surfactant-free and environmentally friendly solution-based route. The hollow hybrid nanostructures were synthesized using a seed-mediated hydrothermal method, which can be divided into two stages: (1) formation of multicore-shell Au@SnO2 nanoparticles (NPs) and (2) thermal diffusion and ripening to form hollow Au-SnO2 hybrid NPs. The morphology, optical properties and formation mechanism were determined by a collection of joint techniques. Photocatalytic degradation of Rhodamine B (RhB) in the liquid phase served as a probe reaction to evaluate the activity of the as-prepared hollow hybrid Au-SnO2 NPs under the irradiation of both visible light and ultraviolet light. Significantly, the as-obtained Au-SnO2 hybrid nanostructures exhibited enhanced visible light or UV photocatalytic abilities, remarkably superior to commercial pure SnO2 products and P25 TiO2, mainly owing to the effective electron hole separation at the SnO2-Au interfaces and strong localization of plasmonic near-fields effects. Electronic supplementary information (ESI) available: The EDX of Au-SnO2 samples (reaction time = 12 h) and plasmonic near-field maps simulated using 3D-FDTD for Au seeds. See DOI: 10.1039/c3nr00985h

Analysis and optimization of hybrid excitation permanent magnet synchronous generator for stand-alone power system

NASA Astrophysics Data System (ADS)

Wang, Huijun; Qu, Zheng; Tang, Shaofei; Pang, Mingqi; Zhang, Mingju

2017-08-01

In this paper, electromagnetic design and permanent magnet shape optimization for permanent magnet synchronous generator with hybrid excitation are investigated. Based on generator structure and principle, design outline is presented for obtaining high efficiency and low voltage fluctuation. In order to realize rapid design, equivalent magnetic circuits for permanent magnet and iron poles are developed. At the same time, finite element analysis is employed. Furthermore, by means of design of experiment (DOE) method, permanent magnet is optimized to reduce voltage waveform distortion. Finally, the validity of proposed design methods is validated by the analytical and experimental results.

Improved Fractal Space Filling Curves Hybrid Optimization Algorithm for Vehicle Routing Problem.

PubMed

Yue, Yi-xiang; Zhang, Tong; Yue, Qun-xing

2015-01-01

Vehicle Routing Problem (VRP) is one of the key issues in optimization of modern logistics system. In this paper, a modified VRP model with hard time window is established and a Hybrid Optimization Algorithm (HOA) based on Fractal Space Filling Curves (SFC) method and Genetic Algorithm (GA) is introduced. By incorporating the proposed algorithm, SFC method can find an initial and feasible solution very fast; GA is used to improve the initial solution. Thereafter, experimental software was developed and a large number of experimental computations from Solomon's benchmark have been studied. The experimental results demonstrate the feasibility and effectiveness of the HOA.

Improved Fractal Space Filling Curves Hybrid Optimization Algorithm for Vehicle Routing Problem

PubMed Central

Yue, Yi-xiang; Zhang, Tong; Yue, Qun-xing

2015-01-01

Vehicle Routing Problem (VRP) is one of the key issues in optimization of modern logistics system. In this paper, a modified VRP model with hard time window is established and a Hybrid Optimization Algorithm (HOA) based on Fractal Space Filling Curves (SFC) method and Genetic Algorithm (GA) is introduced. By incorporating the proposed algorithm, SFC method can find an initial and feasible solution very fast; GA is used to improve the initial solution. Thereafter, experimental software was developed and a large number of experimental computations from Solomon's benchmark have been studied. The experimental results demonstrate the feasibility and effectiveness of the HOA. PMID:26167171

Facile synthesis of hybrid nanorods with the Sb2Se3/AgSbSe2 heterojunction structure for high performance photodetectors.

PubMed

Chen, Shuo; Qiao, Xvsheng; Wang, Fengxia; Luo, Qun; Zhang, Xianghua; Wan, Xia; Xu, Yang; Fan, Xianping

2016-01-28

An effective colloidal process involving the hot-injection method is developed to synthesize uniform single-crystalline Sb2Se3 nanorods in high yields. The photoconductive characteristics of the as-synthesized Sb2Se3 nanorods are investigated by developing a film-based photodetector and this device displays a remarkable response to visible light with an "ON/OFF" ratio as high as 50 (with an incident light density of 12.05 mW cm(-2)), short response/recovery times and long-term durability. To overcome the challenge of the intrinsic low electrical conductivity of Sb2Se3, hybrid nanorods with the Sb2Se3/AgSbSe2 heterojunction structure having a type-II band alignment are firstly prepared. The electric current of the photodetector based on the Sb2Se3/AgSbSe2 hybrid nanorod film has been significantly increased both in the dark and under light illumination. The responsivity of the photodetector based on the Sb2Se3/AgSbSe2 hybrid nanorod film is about 4.2 times as much as that of the photodetector based on the Sb2Se3 nanorod film. This improvement can be considered as an important step to promote Sb2Se3 based semiconductors for applications in high performance photodetectors.

A hybrid symplectic principal component analysis and central tendency measure method for detection of determinism in noisy time series with application to mechanomyography

NASA Astrophysics Data System (ADS)

Xie, Hong-Bo; Dokos, Socrates

2013-06-01

We present a hybrid symplectic geometry and central tendency measure (CTM) method for detection of determinism in noisy time series. CTM is effective for detecting determinism in short time series and has been applied in many areas of nonlinear analysis. However, its performance significantly degrades in the presence of strong noise. In order to circumvent this difficulty, we propose to use symplectic principal component analysis (SPCA), a new chaotic signal de-noising method, as the first step to recover the system dynamics. CTM is then applied to determine whether the time series arises from a stochastic process or has a deterministic component. Results from numerical experiments, ranging from six benchmark deterministic models to 1/f noise, suggest that the hybrid method can significantly improve detection of determinism in noisy time series by about 20 dB when the data are contaminated by Gaussian noise. Furthermore, we apply our algorithm to study the mechanomyographic (MMG) signals arising from contraction of human skeletal muscle. Results obtained from the hybrid symplectic principal component analysis and central tendency measure demonstrate that the skeletal muscle motor unit dynamics can indeed be deterministic, in agreement with previous studies. However, the conventional CTM method was not able to definitely detect the underlying deterministic dynamics. This result on MMG signal analysis is helpful in understanding neuromuscular control mechanisms and developing MMG-based engineering control applications.

A hybrid symplectic principal component analysis and central tendency measure method for detection of determinism in noisy time series with application to mechanomyography.

PubMed

Xie, Hong-Bo; Dokos, Socrates

2013-06-01

We present a hybrid symplectic geometry and central tendency measure (CTM) method for detection of determinism in noisy time series. CTM is effective for detecting determinism in short time series and has been applied in many areas of nonlinear analysis. However, its performance significantly degrades in the presence of strong noise. In order to circumvent this difficulty, we propose to use symplectic principal component analysis (SPCA), a new chaotic signal de-noising method, as the first step to recover the system dynamics. CTM is then applied to determine whether the time series arises from a stochastic process or has a deterministic component. Results from numerical experiments, ranging from six benchmark deterministic models to 1/f noise, suggest that the hybrid method can significantly improve detection of determinism in noisy time series by about 20 dB when the data are contaminated by Gaussian noise. Furthermore, we apply our algorithm to study the mechanomyographic (MMG) signals arising from contraction of human skeletal muscle. Results obtained from the hybrid symplectic principal component analysis and central tendency measure demonstrate that the skeletal muscle motor unit dynamics can indeed be deterministic, in agreement with previous studies. However, the conventional CTM method was not able to definitely detect the underlying deterministic dynamics. This result on MMG signal analysis is helpful in understanding neuromuscular control mechanisms and developing MMG-based engineering control applications.

A numerical algorithm for optimal feedback gains in high dimensional linear quadratic regulator problems

NASA Technical Reports Server (NTRS)

Banks, H. T.; Ito, K.

1991-01-01

A hybrid method for computing the feedback gains in linear quadratic regulator problem is proposed. The method, which combines use of a Chandrasekhar type system with an iteration of the Newton-Kleinman form with variable acceleration parameter Smith schemes, is formulated to efficiently compute directly the feedback gains rather than solutions of an associated Riccati equation. The hybrid method is particularly appropriate when used with large dimensional systems such as those arising in approximating infinite-dimensional (distributed parameter) control systems (e.g., those governed by delay-differential and partial differential equations). Computational advantages of the proposed algorithm over the standard eigenvector (Potter, Laub-Schur) based techniques are discussed, and numerical evidence of the efficacy of these ideas is presented.

A numerical algorithm for optimal feedback gains in high dimensional LQR problems

NASA Technical Reports Server (NTRS)

Banks, H. T.; Ito, K.

1986-01-01

A hybrid method for computing the feedback gains in linear quadratic regulator problems is proposed. The method, which combines the use of a Chandrasekhar type system with an iteration of the Newton-Kleinman form with variable acceleration parameter Smith schemes, is formulated so as to efficiently compute directly the feedback gains rather than solutions of an associated Riccati equation. The hybrid method is particularly appropriate when used with large dimensional systems such as those arising in approximating infinite dimensional (distributed parameter) control systems (e.g., those governed by delay-differential and partial differential equations). Computational advantage of the proposed algorithm over the standard eigenvector (Potter, Laub-Schur) based techniques are discussed and numerical evidence of the efficacy of our ideas presented.

Component-Based Approach for Educating Students in Bioinformatics

ERIC Educational Resources Information Center

Poe, D.; Venkatraman, N.; Hansen, C.; Singh, G.

2009-01-01

There is an increasing need for an effective method of teaching bioinformatics. Increased progress and availability of computer-based tools for educating students have led to the implementation of a computer-based system for teaching bioinformatics as described in this paper. Bioinformatics is a recent, hybrid field of study combining elements of…

On Hybrid and mixed finite element methods

NASA Technical Reports Server (NTRS)

Pian, T. H. H.

1981-01-01

Three versions of the assumed stress hybrid model in finite element methods and the corresponding variational principles for the formulation are presented. Examples of rank deficiency for stiffness matrices by the hybrid stress model are given and their corresponding kinematic deformation modes are identified. A discussion of the derivation of general semi-Loof elements for plates and shells by the hybrid stress method is given. It is shown that the equilibrium model by Fraeijs de Veubeke can be derived by the approach of the hybrid stress model as a special case of semi-Loof elements.

Engineering of high performance supercapacitor electrode based on Fe-Ni/Fe{sub 2}O{sub 3}-NiO core/shell hybrid nanostructures

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

Singh, Ashutosh K., E-mail: ashuvishen@gmail.com, E-mail: aksingh@bose.res.in; Mandal, Kalyan

The present work reports on fabrication and supercapacitor applications of a core/shell Fe-Ni/Fe{sub 2}O{sub 3}-NiO hybrid nanostructures (HNs) electrode. The core/shell Fe-Ni/Fe{sub 2}O{sub 3}-NiO hybrid nanostructures have been fabricated through a two step method (nanowire fabrication and their controlled oxidation). The 1D hybrid nanostructure consists of highly porous shell layer (redox active materials NiO and Fe{sub 2}O{sub 3}) and the conductive core (FeNi nanowire). Thus, the highly porous shell layer allows facile electrolyte diffusion as well as faster redox reaction kinetics; whereas the conductive FeNi nanowire core provides the proficient express way for electrons to travel to the current collector,more » which helps in the superior electrochemical performance. The core/shell Fe-Ni/Fe{sub 2}O{sub 3}-NiO hybrid nanostructures electrode based supercapacitor shows very good electrochemical performances in terms of high specific capacitance nearly 1415 F g{sup −1} at a current density of 2.5 A g{sup −1}, excellent cycling stability and rate capability. The high quality electrochemical performance of core/shell hybrid nanostructures electrode shows its potential as an alternative electrode for forthcoming supercapacitor devices.« less

Evaluating team-based, lecture-based, and hybrid learning methods for neurology clerkship in China: a method-comparison study

PubMed Central

2014-01-01

Background Neurology is complex, abstract, and difficult for students to learn. However, a good learning method for neurology clerkship training is required to help students quickly develop strong clinical thinking as well as problem-solving skills. Both the traditional lecture-based learning (LBL) and the relatively new team-based learning (TBL) methods have inherent strengths and weaknesses when applied to neurology clerkship education. However, the strengths of each method may complement the weaknesses of the other. Combining TBL with LBL may produce better learning outcomes than TBL or LBL alone. We propose a hybrid method (TBL + LBL) and designed an experiment to compare the learning outcomes with those of pure LBL and pure TBL. Methods One hundred twenty-seven fourth-year medical students attended a two-week neurology clerkship program organized by the Department of Neurology, Sun Yat-Sen Memorial Hospital. All of the students were from Grade 2007, Department of Clinical Medicine, Zhongshan School of Medicine, Sun Yat-Sen University. These students were assigned to one of three groups randomly: Group A (TBL + LBL, with 41 students), Group B (LBL, with 43 students), and Group C (TBL, with 43 students). The learning outcomes were evaluated by a questionnaire and two tests covering basic knowledge of neurology and clinical practice. Results The practice test scores of Group A were similar to those of Group B, but significantly higher than those of Group C. The theoretical test scores and the total scores of Group A were significantly higher than those of Groups B and C. In addition, 100% of the students in Group A were satisfied with the combination of TBL + LBL. Conclusions Our results support our proposal that the combination of TBL + LBL is acceptable to students and produces better learning outcomes than either method alone in neurology clerkships. In addition, the proposed hybrid method may also be suited for other medical clerkships that require students to absorb a large amount of abstract and complex course materials in a short period, such as pediatrics and internal medicine clerkships. PMID:24884854

Silicone-containing aqueous polymer dispersions with hybrid particle structure.

PubMed

Kozakiewicz, Janusz; Ofat, Izabela; Trzaskowska, Joanna

2015-09-01

In this paper the synthesis, characterization and application of silicone-containing aqueous polymer dispersions (APD) with hybrid particle structure are reviewed based on available literature data. Advantages of synthesis of dispersions with hybrid particle structure over blending of individual dispersions are pointed out. Three main processes leading to silicone-containing hybrid APD are identified and described in detail: (1) emulsion polymerization of organic unsaturated monomers in aqueous dispersions of silicone polymers or copolymers, (2) emulsion copolymerization of unsaturated organic monomers with alkoxysilanes or polysiloxanes with unsaturated functionality and (3) emulsion polymerization of alkoxysilanes (in particular with unsaturated functionality) and/or cyclic siloxanes in organic polymer dispersions. The effect of various factors on the properties of such hybrid APD and films as well as on hybrid particles composition and morphology is presented. It is shown that core-shell morphology where silicones constitute either the core or the shell is predominant in hybrid particles. Main applications of silicone-containing hybrid APD and related hybrid particles are reviewed including (1) coatings which show specific surface properties such as enhanced water repellency or antisoiling or antigraffiti properties due to migration of silicone to the surface, and (2) impact modifiers for thermoplastics and thermosets. Other processes in which silicone-containing particles with hybrid structure can be obtained (miniemulsion polymerization, polymerization in non-aqueous media, hybridization of organic polymer and polysiloxane, emulsion polymerization of silicone monomers in silicone polymer dispersions and physical methods) are also discussed. Prospects for further developments in the area of silicone-containing hybrid APD and related hybrid particles are presented. Copyright © 2015. Published by Elsevier B.V.

Using multiple classifiers for predicting the risk of endovascular aortic aneurysm repair re-intervention through hybrid feature selection.

PubMed

Attallah, Omneya; Karthikesalingam, Alan; Holt, Peter Je; Thompson, Matthew M; Sayers, Rob; Bown, Matthew J; Choke, Eddie C; Ma, Xianghong

2017-11-01

Feature selection is essential in medical area; however, its process becomes complicated with the presence of censoring which is the unique character of survival analysis. Most survival feature selection methods are based on Cox's proportional hazard model, though machine learning classifiers are preferred. They are less employed in survival analysis due to censoring which prevents them from directly being used to survival data. Among the few work that employed machine learning classifiers, partial logistic artificial neural network with auto-relevance determination is a well-known method that deals with censoring and perform feature selection for survival data. However, it depends on data replication to handle censoring which leads to unbalanced and biased prediction results especially in highly censored data. Other methods cannot deal with high censoring. Therefore, in this article, a new hybrid feature selection method is proposed which presents a solution to high level censoring. It combines support vector machine, neural network, and K-nearest neighbor classifiers using simple majority voting and a new weighted majority voting method based on survival metric to construct a multiple classifier system. The new hybrid feature selection process uses multiple classifier system as a wrapper method and merges it with iterated feature ranking filter method to further reduce features. Two endovascular aortic repair datasets containing 91% censored patients collected from two centers were used to construct a multicenter study to evaluate the performance of the proposed approach. The results showed the proposed technique outperformed individual classifiers and variable selection methods based on Cox's model such as Akaike and Bayesian information criterions and least absolute shrinkage and selector operator in p values of the log-rank test, sensitivity, and concordance index. This indicates that the proposed classifier is more powerful in correctly predicting the risk of re-intervention enabling doctor in selecting patients' future follow-up plan.

Coupling discrete and continuum concentration particle models for multiscale and hybrid molecular-continuum simulations

NASA Astrophysics Data System (ADS)

Petsev, Nikolai D.; Leal, L. Gary; Shell, M. Scott

2017-12-01

Hybrid molecular-continuum simulation techniques afford a number of advantages for problems in the rapidly burgeoning area of nanoscale engineering and technology, though they are typically quite complex to implement and limited to single-component fluid systems. We describe an approach for modeling multicomponent hydrodynamic problems spanning multiple length scales when using particle-based descriptions for both the finely resolved (e.g., molecular dynamics) and coarse-grained (e.g., continuum) subregions within an overall simulation domain. This technique is based on the multiscale methodology previously developed for mesoscale binary fluids [N. D. Petsev, L. G. Leal, and M. S. Shell, J. Chem. Phys. 144, 084115 (2016)], simulated using a particle-based continuum method known as smoothed dissipative particle dynamics. An important application of this approach is the ability to perform coupled molecular dynamics (MD) and continuum modeling of molecularly miscible binary mixtures. In order to validate this technique, we investigate multicomponent hybrid MD-continuum simulations at equilibrium, as well as non-equilibrium cases featuring concentration gradients.

Shape-controlled fabrication of magnetite silver hybrid nanoparticles with high performance magnetic hyperthermia.

PubMed

Ding, Qi; Liu, Dongfang; Guo, Dawei; Yang, Fang; Pang, Xingyun; Che, Renchao; Zhou, Naizhen; Xie, Jun; Sun, Jianfei; Huang, Zhihai; Gu, Ning

2017-04-01

Superparamagnetic Fe 3 O 4 nanoparticles (NPs)-based hyperthermia is a promising non-invasive approach for cancer therapy. However, the heat transfer efficiency of Fe 3 O 4 NPs is relative low, which hinders their practical clinical applications. Therefore, it is promising to improve the magnetic hyperthermia efficiency by exploring the higher performance magnetic NPs-based hybrid nanostructures. In the current study, it presents a straightforward in situ reduction method for the shape-controlled preparation of magnetite (Fe 3 O 4 ) silver (Ag) hybrid NPs designed as magnetic hyperthermia heat mediators. The magnetite silver hybrid NPs with core-shell (Fe 3 O 4 @Ag) or heteromer (Fe 3 O 4 -Ag) structures exhibited a higher biocompatibility with SMMC-7721 cells and L02 cells than the individual Ag NPs. Importantly, in the magnetic hyperthermia, with the exposure to alternating current magnetic field, the Fe 3 O 4 @Ag and Fe 3 O 4 -Ag hybrid NPs indicated much better tumor suppression effect against SMMC-7721 cells than the individual Fe 3 O 4 NPs in vitro and in vivo. These results demonstrate that the hybridisation of Fe 3 O 4 and Ag NPs could greatly enhance the magnetic hyperthermia efficiency of Fe 3 O 4 NPs. Therefore, the Fe 3 O 4 @Ag and Fe 3 O 4 -Ag hybrid NPs can be used to be as high performance magnetic hyperthermia mediators based on a simple and effective preparation approach. Copyright © 2017 Elsevier Ltd. All rights reserved.