SVM-based feature extraction and classification of aflatoxin contaminated corn using fluorescence hyperspectral data

USDA-ARS?s Scientific Manuscript database

Support Vector Machine (SVM) was used in the Genetic Algorithms (GA) process to select and classify a subset of hyperspectral image bands. The method was applied to fluorescence hyperspectral data for the detection of aflatoxin contamination in Aspergillus flavus infected single corn kernels. In the...

Research on intrusion detection based on Kohonen network and support vector machine

NASA Astrophysics Data System (ADS)

Shuai, Chunyan; Yang, Hengcheng; Gong, Zeweiyi

2018-05-01

In view of the problem of low detection accuracy and the long detection time of support vector machine, which directly applied to the network intrusion detection system. Optimization of SVM parameters can greatly improve the detection accuracy, but it can not be applied to high-speed network because of the long detection time. a method based on Kohonen neural network feature selection is proposed to reduce the optimization time of support vector machine parameters. Firstly, this paper is to calculate the weights of the KDD99 network intrusion data by Kohonen network and select feature by weight. Then, after the feature selection is completed, genetic algorithm (GA) and grid search method are used for parameter optimization to find the appropriate parameters and classify them by support vector machines. By comparing experiments, it is concluded that feature selection can reduce the time of parameter optimization, which has little influence on the accuracy of classification. The experiments suggest that the support vector machine can be used in the network intrusion detection system and reduce the missing rate.

Structure-based predictions of 13C-NMR chemical shifts for a series of 2-functionalized 5-(methylsulfonyl)-1-phenyl-1H-indoles derivatives using GA-based MLR method

NASA Astrophysics Data System (ADS)

Ghavami, Raouf; Sadeghi, Faridoon; Rasouli, Zolikha; Djannati, Farhad

2012-12-01

Experimental values for the 13C NMR chemical shifts (ppm, TMS = 0) at 300 K ranging from 96.28 ppm (C4' of indole derivative 17) to 159.93 ppm (C4' of indole derivative 23) relative to deuteride chloroform (CDCl3, 77.0 ppm) or dimethylsulfoxide (DMSO, 39.50 ppm) as internal reference in CDCl3 or DMSO-d6 solutions have been collected from literature for thirty 2-functionalized 5-(methylsulfonyl)-1-phenyl-1H-indole derivatives containing different substituted groups. An effective quantitative structure-property relationship (QSPR) models were built using hybrid method combining genetic algorithm (GA) based on stepwise selection multiple linear regression (SWS-MLR) as feature-selection tools and correlation models between each carbon atom of indole derivative and calculated descriptors. Each compound was depicted by molecular structural descriptors that encode constitutional, topological, geometrical, electrostatic, and quantum chemical features. The accuracy of all developed models were confirmed using different types of internal and external procedures and various statistical tests. Furthermore, the domain of applicability for each model which indicates the area of reliable predictions was defined.

Fuel spill identification using solid-phase extraction and solid-phase microextraction. 1. Aviation turbine fuels.

PubMed

Lavine, B K; Brzozowski, D M; Ritter, J; Moores, A J; Mayfield, H T

2001-12-01

The water-soluble fraction of aviation jet fuels is examined using solid-phase extraction and solid-phase microextraction. Gas chromatographic profiles of solid-phase extracts and solid-phase microextracts of the water-soluble fraction of kerosene- and nonkerosene-based jet fuels reveal that each jet fuel possesses a unique profile. Pattern recognition analysis reveals fingerprint patterns within the data characteristic of fuel type. By using a novel genetic algorithm (GA) that emulates human pattern recognition through machine learning, it is possible to identify features characteristic of the chromatographic profile of each fuel class. The pattern recognition GA identifies a set of features that optimize the separation of the fuel classes in a plot of the two largest principal components of the data. Because principal components maximize variance, the bulk of the information encoded by the selected features is primarily about the differences between the fuel classes.

A Genetic Algorithm Based Support Vector Machine Model for Blood-Brain Barrier Penetration Prediction

PubMed Central

Zhang, Daqing; Xiao, Jianfeng; Zhou, Nannan; Luo, Xiaomin; Jiang, Hualiang; Chen, Kaixian

2015-01-01

Blood-brain barrier (BBB) is a highly complex physical barrier determining what substances are allowed to enter the brain. Support vector machine (SVM) is a kernel-based machine learning method that is widely used in QSAR study. For a successful SVM model, the kernel parameters for SVM and feature subset selection are the most important factors affecting prediction accuracy. In most studies, they are treated as two independent problems, but it has been proven that they could affect each other. We designed and implemented genetic algorithm (GA) to optimize kernel parameters and feature subset selection for SVM regression and applied it to the BBB penetration prediction. The results show that our GA/SVM model is more accurate than other currently available log BB models. Therefore, to optimize both SVM parameters and feature subset simultaneously with genetic algorithm is a better approach than other methods that treat the two problems separately. Analysis of our log BB model suggests that carboxylic acid group, polar surface area (PSA)/hydrogen-bonding ability, lipophilicity, and molecular charge play important role in BBB penetration. Among those properties relevant to BBB penetration, lipophilicity could enhance the BBB penetration while all the others are negatively correlated with BBB penetration. PMID:26504797

Genetic Algorithms and Classification Trees in Feature Discovery: Diabetes and the NHANES database

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

Heredia-Langner, Alejandro; Jarman, Kristin H.; Amidan, Brett G.

2013-09-01

This paper presents a feature selection methodology that can be applied to datasets containing a mixture of continuous and categorical variables. Using a Genetic Algorithm (GA), this method explores a dataset and selects a small set of features relevant for the prediction of a binary (1/0) response. Binary classification trees and an objective function based on conditional probabilities are used to measure the fitness of a given subset of features. The method is applied to health data in order to find factors useful for the prediction of diabetes. Results show that our algorithm is capable of narrowing down the setmore » of predictors to around 8 factors that can be validated using reputable medical and public health resources.« less

Statistical analysis for validating ACO-KNN algorithm as feature selection in sentiment analysis

NASA Astrophysics Data System (ADS)

Ahmad, Siti Rohaidah; Yusop, Nurhafizah Moziyana Mohd; Bakar, Azuraliza Abu; Yaakub, Mohd Ridzwan

2017-10-01

This research paper aims to propose a hybrid of ant colony optimization (ACO) and k-nearest neighbor (KNN) algorithms as feature selections for selecting and choosing relevant features from customer review datasets. Information gain (IG), genetic algorithm (GA), and rough set attribute reduction (RSAR) were used as baseline algorithms in a performance comparison with the proposed algorithm. This paper will also discuss the significance test, which was used to evaluate the performance differences between the ACO-KNN, IG-GA, and IG-RSAR algorithms. This study evaluated the performance of the ACO-KNN algorithm using precision, recall, and F-score, which were validated using the parametric statistical significance tests. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. In addition, the experimental results have proven that the ACO-KNN can be used as a feature selection technique in sentiment analysis to obtain quality, optimal feature subset that can represent the actual data in customer review data.

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

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

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

2013-12-04

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

Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering.

PubMed

Suraj; Tiwari, Purnendu; Ghosh, Subhojit; Sinha, Rakesh Kumar

2015-01-01

Transferring the brain computer interface (BCI) from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG) signal reasons us to look toward evolutionary algorithm (EA). Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI) tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA) and particle swarm optimization (PSO) based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR) techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD) and desynchronization (ERD) feature vector is formed.

Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering

PubMed Central

Suraj; Tiwari, Purnendu; Ghosh, Subhojit; Sinha, Rakesh Kumar

2015-01-01

Transferring the brain computer interface (BCI) from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG) signal reasons us to look toward evolutionary algorithm (EA). Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI) tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA) and particle swarm optimization (PSO) based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR) techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD) and desynchronization (ERD) feature vector is formed. PMID:25972896

Heterogeneous Ensemble Combination Search Using Genetic Algorithm for Class Imbalanced Data Classification.

PubMed

Haque, Mohammad Nazmul; Noman, Nasimul; Berretta, Regina; Moscato, Pablo

2016-01-01

Classification of datasets with imbalanced sample distributions has always been a challenge. In general, a popular approach for enhancing classification performance is the construction of an ensemble of classifiers. However, the performance of an ensemble is dependent on the choice of constituent base classifiers. Therefore, we propose a genetic algorithm-based search method for finding the optimum combination from a pool of base classifiers to form a heterogeneous ensemble. The algorithm, called GA-EoC, utilises 10 fold-cross validation on training data for evaluating the quality of each candidate ensembles. In order to combine the base classifiers decision into ensemble's output, we used the simple and widely used majority voting approach. The proposed algorithm, along with the random sub-sampling approach to balance the class distribution, has been used for classifying class-imbalanced datasets. Additionally, if a feature set was not available, we used the (α, β) - k Feature Set method to select a better subset of features for classification. We have tested GA-EoC with three benchmarking datasets from the UCI-Machine Learning repository, one Alzheimer's disease dataset and a subset of the PubFig database of Columbia University. In general, the performance of the proposed method on the chosen datasets is robust and better than that of the constituent base classifiers and many other well-known ensembles. Based on our empirical study we claim that a genetic algorithm is a superior and reliable approach to heterogeneous ensemble construction and we expect that the proposed GA-EoC would perform consistently in other cases.

Heterogeneous Ensemble Combination Search Using Genetic Algorithm for Class Imbalanced Data Classification

PubMed Central

Haque, Mohammad Nazmul; Noman, Nasimul; Berretta, Regina; Moscato, Pablo

2016-01-01

Classification of datasets with imbalanced sample distributions has always been a challenge. In general, a popular approach for enhancing classification performance is the construction of an ensemble of classifiers. However, the performance of an ensemble is dependent on the choice of constituent base classifiers. Therefore, we propose a genetic algorithm-based search method for finding the optimum combination from a pool of base classifiers to form a heterogeneous ensemble. The algorithm, called GA-EoC, utilises 10 fold-cross validation on training data for evaluating the quality of each candidate ensembles. In order to combine the base classifiers decision into ensemble’s output, we used the simple and widely used majority voting approach. The proposed algorithm, along with the random sub-sampling approach to balance the class distribution, has been used for classifying class-imbalanced datasets. Additionally, if a feature set was not available, we used the (α, β) − k Feature Set method to select a better subset of features for classification. We have tested GA-EoC with three benchmarking datasets from the UCI-Machine Learning repository, one Alzheimer’s disease dataset and a subset of the PubFig database of Columbia University. In general, the performance of the proposed method on the chosen datasets is robust and better than that of the constituent base classifiers and many other well-known ensembles. Based on our empirical study we claim that a genetic algorithm is a superior and reliable approach to heterogeneous ensemble construction and we expect that the proposed GA-EoC would perform consistently in other cases. PMID:26764911

Automatic variable selection method and a comparison for quantitative analysis in laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Duan, Fajie; Fu, Xiao; Jiang, Jiajia; Huang, Tingting; Ma, Ling; Zhang, Cong

2018-05-01

In this work, an automatic variable selection method for quantitative analysis of soil samples using laser-induced breakdown spectroscopy (LIBS) is proposed, which is based on full spectrum correction (FSC) and modified iterative predictor weighting-partial least squares (mIPW-PLS). The method features automatic selection without artificial processes. To illustrate the feasibility and effectiveness of the method, a comparison with genetic algorithm (GA) and successive projections algorithm (SPA) for different elements (copper, barium and chromium) detection in soil was implemented. The experimental results showed that all the three methods could accomplish variable selection effectively, among which FSC-mIPW-PLS required significantly shorter computation time (12 s approximately for 40,000 initial variables) than the others. Moreover, improved quantification models were got with variable selection approaches. The root mean square errors of prediction (RMSEP) of models utilizing the new method were 27.47 (copper), 37.15 (barium) and 39.70 (chromium) mg/kg, which showed comparable prediction effect with GA and SPA.

Selective epitaxial growth of monolithically integrated GaN-based light emitting diodes with AlGaN/GaN driving transistors

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

Liu, Zhaojun; Ma, Jun; Huang, Tongde

2014-03-03

In this Letter, we report selective epitaxial growth of monolithically integrated GaN-based light emitting diodes (LEDs) with AlGaN/GaN high-electron-mobility transistor (HEMT) drivers. A comparison of two integration schemes, selective epitaxial removal (SER), and selective epitaxial growth (SEG) was made. We found the SER resulted in serious degradation of the underlying LEDs in a HEMT-on-LED structure due to damage of the p-GaN surface. The problem was circumvented using the SEG that avoided plasma etching and minimized device degradation. The integrated HEMT-LEDs by SEG exhibited comparable characteristics as unintegrated devices and emitted modulated blue light by gate biasing.

Magnetic field feature extraction and selection for indoor location estimation.

PubMed

Galván-Tejada, Carlos E; García-Vázquez, Juan Pablo; Brena, Ramon F

2014-06-20

User indoor positioning has been under constant improvement especially with the availability of new sensors integrated into the modern mobile devices, which allows us to exploit not only infrastructures made for everyday use, such as WiFi, but also natural infrastructure, as is the case of natural magnetic field. In this paper we present an extension and improvement of our current indoor localization model based on the feature extraction of 46 magnetic field signal features. The extension adds a feature selection phase to our methodology, which is performed through Genetic Algorithm (GA) with the aim of optimizing the fitness of our current model. In addition, we present an evaluation of the final model in two different scenarios: home and office building. The results indicate that performing a feature selection process allows us to reduce the number of signal features of the model from 46 to 5 regardless the scenario and room location distribution. Further, we verified that reducing the number of features increases the probability of our estimator correctly detecting the user's location (sensitivity) and its capacity to detect false positives (specificity) in both scenarios.

Design of Clinical Support Systems Using Integrated Genetic Algorithm and Support Vector Machine

NASA Astrophysics Data System (ADS)

Chen, Yung-Fu; Huang, Yung-Fa; Jiang, Xiaoyi; Hsu, Yuan-Nian; Lin, Hsuan-Hung

Clinical decision support system (CDSS) provides knowledge and specific information for clinicians to enhance diagnostic efficiency and improving healthcare quality. An appropriate CDSS can highly elevate patient safety, improve healthcare quality, and increase cost-effectiveness. Support vector machine (SVM) is believed to be superior to traditional statistical and neural network classifiers. However, it is critical to determine suitable combination of SVM parameters regarding classification performance. Genetic algorithm (GA) can find optimal solution within an acceptable time, and is faster than greedy algorithm with exhaustive searching strategy. By taking the advantage of GA in quickly selecting the salient features and adjusting SVM parameters, a method using integrated GA and SVM (IGS), which is different from the traditional method with GA used for feature selection and SVM for classification, was used to design CDSSs for prediction of successful ventilation weaning, diagnosis of patients with severe obstructive sleep apnea, and discrimination of different cell types form Pap smear. The results show that IGS is better than methods using SVM alone or linear discriminator.

White emission from non-planar InGaN/GaN MQW LEDs grown on GaN template with truncated hexagonal pyramids.

PubMed

Lee, Ming-Lun; Yeh, Yu-Hsiang; Tu, Shang-Ju; Chen, P C; Lai, Wei-Chih; Sheu, Jinn-Kong

2015-04-06

Non-planar InGaN/GaN multiple quantum well (MQW) structures are grown on a GaN template with truncated hexagonal pyramids (THPs) featuring c-plane and r-plane surfaces. The THP array is formed by the regrowth of the GaN layer on a selective-area Si-implanted GaN template. Transmission electron microscopy shows that the InGaN/GaN epitaxial layers regrown on the THPs exhibit different growth rates and indium compositions of the InGaN layer between the c-plane and r-plane surfaces. Consequently, InGaN/GaN MQW light-emitting diodes grown on the GaN THP array emit multiple wavelengths approaching near white light.

Oral cancer prognosis based on clinicopathologic and genomic markers using a hybrid of feature selection and machine learning methods

PubMed Central

2013-01-01

Background Machine learning techniques are becoming useful as an alternative approach to conventional medical diagnosis or prognosis as they are good for handling noisy and incomplete data, and significant results can be attained despite a small sample size. Traditionally, clinicians make prognostic decisions based on clinicopathologic markers. However, it is not easy for the most skilful clinician to come out with an accurate prognosis by using these markers alone. Thus, there is a need to use genomic markers to improve the accuracy of prognosis. The main aim of this research is to apply a hybrid of feature selection and machine learning methods in oral cancer prognosis based on the parameters of the correlation of clinicopathologic and genomic markers. Results In the first stage of this research, five feature selection methods have been proposed and experimented on the oral cancer prognosis dataset. In the second stage, the model with the features selected from each feature selection methods are tested on the proposed classifiers. Four types of classifiers are chosen; these are namely, ANFIS, artificial neural network, support vector machine and logistic regression. A k-fold cross-validation is implemented on all types of classifiers due to the small sample size. The hybrid model of ReliefF-GA-ANFIS with 3-input features of drink, invasion and p63 achieved the best accuracy (accuracy = 93.81%; AUC = 0.90) for the oral cancer prognosis. Conclusions The results revealed that the prognosis is superior with the presence of both clinicopathologic and genomic markers. The selected features can be investigated further to validate the potential of becoming as significant prognostic signature in the oral cancer studies. PMID:23725313

Enhanced light extraction from free-standing InGaN/GaN light emitters using bio-inspired backside surface structuring.

PubMed

Pynn, Christopher D; Chan, Lesley; Lora Gonzalez, Federico; Berry, Alex; Hwang, David; Wu, Haoyang; Margalith, Tal; Morse, Daniel E; DenBaars, Steven P; Gordon, Michael J

2017-07-10

Light extraction from InGaN/GaN-based multiple-quantum-well (MQW) light emitters is enhanced using a simple, scalable, and reproducible method to create hexagonally close-packed conical nano- and micro-scale features on the backside outcoupling surface. Colloidal lithography via Langmuir-Blodgett dip-coating using silica masks (d = 170-2530 nm) and Cl 2 /N 2 -based plasma etching produced features with aspect ratios of 3:1 on devices grown on semipolar GaN substrates. InGaN/GaN MQW structures were optically pumped at 266 nm and light extraction enhancement was quantified using angle-resolved photoluminescence. A 4.8-fold overall enhancement in light extraction (9-fold at normal incidence) relative to a flat outcoupling surface was achieved using a feature pitch of 2530 nm. This performance is on par with current photoelectrochemical (PEC) nitrogen-face roughening methods, which positions the technique as a strong alternative for backside structuring of c-plane devices. Also, because colloidal lithography functions independently of GaN crystal orientation, it is applicable to semipolar and nonpolar GaN devices, for which PEC roughening is ineffective.

Phosphinic acid functionalized polyazacycloalkane chelators for radiodiagnostics and radiotherapeutics: unique characteristics and applications.

PubMed

Notni, Johannes; Šimeček, Jakub; Wester, Hans-Jürgen

2014-06-01

Given the wide application of positron emission tomography (PET), positron-emitting metal radionuclides have received much attention recently. Of these, gallium-68 has become particularly popular, as it is the only PET nuclide commercially available from radionuclide generators, therefore allowing local production of PET radiotracers independent of an on-site cyclotron. Hence, interest in optimized bifunctional chelators for the elaboration of (68) Ga-labeled bioconjugates has been rekindled as well, resulting in the development of improved triazacyclononane-triphosphinate (TRAP) ligand structures. The most remarkable features of these ligands are unparalleled selectivity for Ga(III) , rapid Ga(III) complexation kinetics, extraordinarily high thermodynamic stability, and kinetic inertness of the respective Ga(III) chelates. As a result, TRAP chelators exhibit very favorable (68) Ga-labeling properties. Based on the scaffolds NOPO (1,4,7-triazacyclononane-1,4-bis[methylene(hydroxymethyl)phosphinic acid]-7-[methylene(2-carboxyethyl)phosphinic acid]) and TRAP-Pr, tailored for convenient preparation of (68) Ga-labeled monomeric and multimeric bioconjugates, a variety of novel (68) Ga radiopharmaceuticals have been synthesized. These include bisphosphonates, somatostatin receptor ligands, prostate-specific membrane antigen (PSMA)-targeting peptides, and cyclic RGD pentapeptides, for in vivo PET imaging of bone, neuroendocrine tumors, prostate cancer, and integrin expression, respectively. Furthermore, TRAP-based (68) Ga-labeled gadolinium(III) complexes have been proposed as bimodal probes for PET/MRI, and a cyclen-based analogue of TRAP-Pr has been suggested for the elaboration of targeted radiotherapeutics comprising radiolanthanide ions. Thus, polyazacycloalkane-based polyphosphinic acid chelators are a powerful toolbox for pharmaceutical research, particularly for the development of (68) Ga radiopharmaceuticals. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The influence of surfaces on the transient terahertz conductivity and electron mobility of GaAs nanowires

NASA Astrophysics Data System (ADS)

Joyce, Hannah J.; Baig, Sarwat A.; Parkinson, Patrick; Davies, Christopher L.; Boland, Jessica L.; Tan, H. Hoe; Jagadish, Chennupati; Herz, Laura M.; Johnston, Michael B.

2017-06-01

Bare unpassivated GaAs nanowires feature relatively high electron mobilities (400-2100 cm2 V-1 s-1) and ultrashort charge carrier lifetimes (1-5 ps) at room temperature. These two properties are highly desirable for high speed optoelectronic devices, including photoreceivers, modulators and switches operating at microwave and terahertz frequencies. When engineering these GaAs nanowire-based devices, it is important to have a quantitative understanding of how the charge carrier mobility and lifetime can be tuned. Here we use optical-pump-terahertz-probe spectroscopy to quantify how mobility and lifetime depend on the nanowire surfaces and on carrier density in unpassivated GaAs nanowires. We also present two alternative frameworks for the analysis of nanowire photoconductivity: one based on plasmon resonance and the other based on Maxwell-Garnett effective medium theory with the nanowires modelled as prolate ellipsoids. We find the electron mobility decreases significantly with decreasing nanowire diameter, as charge carriers experience increased scattering at nanowire surfaces. Reducing the diameter from 50 nm to 30 nm degrades the electron mobility by up to 47%. Photoconductivity dynamics were dominated by trapping at saturable states existing at the nanowire surface, and the trapping rate was highest for the nanowires of narrowest diameter. The maximum surface recombination velocity, which occurs in the limit of all traps being empty, was calculated as 1.3  ×  106 cm s-1. We note that when selecting the optimum nanowire diameter for an ultrafast device, there is a trade-off between achieving a short lifetime and a high carrier mobility. To achieve high speed GaAs nanowire devices featuring the highest charge carrier mobilities and shortest lifetimes, we recommend operating the devices at low charge carrier densities.

Morphological evolution and characterization of GaN pyramid arrays fabricated by photo-assisted chemical etching

NASA Astrophysics Data System (ADS)

Zhang, Shiying; Xiu, Xiangqian; Xu, Qingjun; Li, Yuewen; Hua, Xuemei; Chen, Peng; Xie, Zili; Liu, Bin; Zhou, Yugang; Han, Ping; Zhang, Rong; Zheng, Youdou

2016-12-01

GaN pyramid arrays have been successfully synthesized by selective photo-assisted chemical etching in a K2S2O8/KOH solution. A detailed analysis of time evolution of surface morphology has been conducted, which describes an etching process of GaN pyramids. Room temperature cathodoluminescence images indicate that these pyramids are composed of crystalline GaN surrounding dislocations, which is caused by the greater recombination rate of electrons and holes at dislocation than that of crystalline GaN. The Raman results show a stress relaxation in GaN pyramids compared with unetched GaN. The optical property of both unetched GaN and GaN pyramids has been studied by photoluminescence. The formation mechanism and feature of GaN pyramids are also rationally explained.

GENIE: a hybrid genetic algorithm for feature classification in multispectral images

NASA Astrophysics Data System (ADS)

Perkins, Simon J.; Theiler, James P.; Brumby, Steven P.; Harvey, Neal R.; Porter, Reid B.; Szymanski, John J.; Bloch, Jeffrey J.

2000-10-01

We consider the problem of pixel-by-pixel classification of a multi- spectral image using supervised learning. Conventional spuervised classification techniques such as maximum likelihood classification and less conventional ones s uch as neural networks, typically base such classifications solely on the spectral components of each pixel. It is easy to see why: the color of a pixel provides a nice, bounded, fixed dimensional space in which these classifiers work well. It is often the case however, that spectral information alone is not sufficient to correctly classify a pixel. Maybe spatial neighborhood information is required as well. Or maybe the raw spectral components do not themselves make for easy classification, but some arithmetic combination of them would. In either of these cases we have the problem of selecting suitable spatial, spectral or spatio-spectral features that allow the classifier to do its job well. The number of all possible such features is extremely large. How can we select a suitable subset? We have developed GENIE, a hybrid learning system that combines a genetic algorithm that searches a space of image processing operations for a set that can produce suitable feature planes, and a more conventional classifier which uses those feature planes to output a final classification. In this paper we show that the use of a hybrid GA provides significant advantages over using either a GA alone or more conventional classification methods alone. We present results using high-resolution IKONOS data, looking for regions of burned forest and for roads.

Selective Area Sublimation: A Simple Top-down Route for GaN-Based Nanowire Fabrication.

PubMed

Damilano, B; Vézian, S; Brault, J; Alloing, B; Massies, J

2016-03-09

Post-growth in situ partial SiNx masking of GaN-based epitaxial layers grown in a molecular beam epitaxy reactor is used to get GaN selective area sublimation (SAS) by high temperature annealing. Using this top-down approach, nanowires (NWs) with nanometer scale diameter are obtained from GaN and InxGa1-xN/GaN quantum well epitaxial structures. After GaN regrowth on InxGa1-xN/GaN NWs resulting from SAS, InxGa1-xN quantum disks (QDisks) with nanometer sizes in the three dimensions are formed. Low temperature microphotoluminescence experiments demonstrate QDisk multilines photon emission around 3 eV with individual line widths of 1-2 meV.

Multi-probe-based resonance-frequency electrical impedance spectroscopy for detection of suspicious breast lesions: improving performance using partial ROC optimization

NASA Astrophysics Data System (ADS)

Lederman, Dror; Zheng, Bin; Wang, Xingwei; Wang, Xiao Hui; Gur, David

2011-03-01

We have developed a multi-probe resonance-frequency electrical impedance spectroscope (REIS) system to detect breast abnormalities. Based on assessing asymmetry in REIS signals acquired between left and right breasts, we developed several machine learning classifiers to classify younger women (i.e., under 50YO) into two groups of having high and low risk for developing breast cancer. In this study, we investigated a new method to optimize performance based on the area under a selected partial receiver operating characteristic (ROC) curve when optimizing an artificial neural network (ANN), and tested whether it could improve classification performance. From an ongoing prospective study, we selected a dataset of 174 cases for whom we have both REIS signals and diagnostic status verification. The dataset includes 66 "positive" cases recommended for biopsy due to detection of highly suspicious breast lesions and 108 "negative" cases determined by imaging based examinations. A set of REIS-based feature differences, extracted from the two breasts using a mirror-matched approach, was computed and constituted an initial feature pool. Using a leave-one-case-out cross-validation method, we applied a genetic algorithm (GA) to train the ANN with an optimal subset of features. Two optimization criteria were separately used in GA optimization, namely the area under the entire ROC curve (AUC) and the partial area under the ROC curve, up to a predetermined threshold (i.e., 90% specificity). The results showed that although the ANN optimized using the entire AUC yielded higher overall performance (AUC = 0.83 versus 0.76), the ANN optimized using the partial ROC area criterion achieved substantially higher operational performance (i.e., increasing sensitivity level from 28% to 48% at 95% specificity and/ or from 48% to 58% at 90% specificity).

Organometallic model complexes elucidate the active gallium species in alkane dehydrogenation catalysts based on ligand effects in Ga K-edge XANES

DOE PAGES

Getsoian, Andrew "Bean"; Das, Ujjal; Camacho-Bunquin, Jeffrey; ...

2016-06-13

Gallium-modified zeolites are known catalysts for the dehydrogenation of alkanes, reactivity that finds industrial application in the aromatization of light alkanes by Ga-ZSM5. While the role of gallium cations in alkane activation is well known, the oxidation state and coordination environment of gallium under reaction conditions has been the subject of debate. Edge shifts in Ga K-edge XANES spectra acquired under reaction conditions have long been interpreted as evidence for reduction of Ga(III) to Ga(I). However, a change in oxidation state is not the only factor that can give rise to a change in the XANES spectrum. In order tomore » better understand the XANES spectra of working catalysts, we have synthesized a series of molecular model compounds and grafted surface organometallic Ga species and compared their XANES spectra to those of gallium-based catalysts acquired under reducing conditions. We demonstrate that changes in the identity and number of gallium nearest neighbors can give rise to changes in XANES spectra similar to those attributed in literature to changes in oxidation state. Specifically, spectral features previously attributed to Ga(I) may be equally well interpreted as evidence for low-coordinate Ga(III) alkyl or hydride species. Furthermore, these findings apply both to gallium-impregnated zeolite catalysts and to silica-supported single site gallium catalysts, the latter of which is found to be active and selective for dehydrogenation of propane and hydrogenation of propylene.« less

A multistage approach to improve performance of computer-aided detection of pulmonary embolisms depicted on CT images: preliminary investigation.

PubMed

Park, Sang Cheol; Chapman, Brian E; Zheng, Bin

2011-06-01

This study developed a computer-aided detection (CAD) scheme for pulmonary embolism (PE) detection and investigated several approaches to improve CAD performance. In the study, 20 computed tomography examinations with various lung diseases were selected, which include 44 verified PE lesions. The proposed CAD scheme consists of five basic steps: 1) lung segmentation; 2) PE candidate extraction using an intensity mask and tobogganing region growing; 3) PE candidate feature extraction; 4) false-positive (FP) reduction using an artificial neural network (ANN); and 5) a multifeature-based k-nearest neighbor for positive/negative classification. In this study, we also investigated the following additional methods to improve CAD performance: 1) grouping 2-D detected features into a single 3-D object; 2) selecting features with a genetic algorithm (GA); and 3) limiting the number of allowed suspicious lesions to be cued in one examination. The results showed that 1) CAD scheme using tobogganing, an ANN, and grouping method achieved the maximum detection sensitivity of 79.2%; 2) the maximum scoring method achieved the superior performance over other scoring fusion methods; 3) GA was able to delete "redundant" features and further improve CAD performance; and 4) limiting the maximum number of cued lesions in an examination reduced FP rate by 5.3 times. Combining these approaches, CAD scheme achieved 63.2% detection sensitivity with 18.4 FP lesions per examination. The study suggested that performance of CAD schemes for PE detection depends on many factors that include 1) optimizing the 2-D region grouping and scoring methods; 2) selecting the optimal feature set; and 3) limiting the number of allowed cueing lesions per examination.

Intraband magneto-optical absorption in InAs/GaAs quantum dots: Orbital Zeeman splitting and the Thomas-Reiche-Kuhn sum rule

NASA Astrophysics Data System (ADS)

Zhang, J.-Z.; Galbraith, I.

2008-05-01

Using perturbation theory, intraband magneto-optical absorption is calculated for InAs/GaAs truncated pyramidal quantum dots in a magnetic field applied parallel to the growth direction z . The effects of the magnetic field on the electronic states as well as the intraband transitions are systematically studied. Selection rules governing the intraband transitions are discussed based on the symmetry properties of the electronic states. While the broadband z -polarized absorption is almost insensitive to the magnetic field, the orbital Zeeman splitting is the dominant feature in the in-plane polarized spectrum. Strong in-plane polarized magneto-absorption features are located in the far-infrared region, while z -polarized absorption occurs at higher frequencies. This is due to the dot geometry (the base length is much larger than the height) yielding different quantum confinement in the vertical and lateral directions. The Thomas-Reiche-Kuhn sum rule, including the magnetic field effect, is applied together with the selection rules to the absorption spectra. The orbital Zeeman splitting depends on both the dot size and the confining potential—the splitting decreases as the dot size or the confining potential decreases. Our calculated Zeeman splittings are in agreement with experimental data.

Feature Selection in Order to Extract Multiple Sclerosis Lesions Automatically in 3D Brain Magnetic Resonance Images Using Combination of Support Vector Machine and Genetic Algorithm.

PubMed

Khotanlou, Hassan; Afrasiabi, Mahlagha

2012-10-01

This paper presents a new feature selection approach for automatically extracting multiple sclerosis (MS) lesions in three-dimensional (3D) magnetic resonance (MR) images. Presented method is applicable to different types of MS lesions. In this method, T1, T2, and fluid attenuated inversion recovery (FLAIR) images are firstly preprocessed. In the next phase, effective features to extract MS lesions are selected by using a genetic algorithm (GA). The fitness function of the GA is the Similarity Index (SI) of a support vector machine (SVM) classifier. The results obtained on different types of lesions have been evaluated by comparison with manual segmentations. This algorithm is evaluated on 15 real 3D MR images using several measures. As a result, the SI between MS regions determined by the proposed method and radiologists was 87% on average. Experiments and comparisons with other methods show the effectiveness and the efficiency of the proposed approach.

Gallium nitride based logpile photonic crystals.

PubMed

Subramania, Ganapathi; Li, Qiming; Lee, Yun-Ju; Figiel, Jeffrey J; Wang, George T; Fischer, Arthur J

2011-11-09

We demonstrate a nine-layer logpile three-dimensional photonic crystal (3DPC) composed of single crystalline gallium nitride (GaN) nanorods, ∼100 nm in size with lattice constants of 260, 280, and 300 nm with photonic band gap in the visible region. This unique GaN structure is created through a combined approach of a layer-by-layer template fabrication technique and selective metal organic chemical vapor deposition (MOCVD). These GaN 3DPC exhibit a stacking direction band gap characterized by strong optical reflectance between 380 and 500 nm. By introducing a "line-defect" cavity in the fifth (middle) layer of the 3DPC, a localized transmission mode with a quality factor of 25-30 is also observed within the photonic band gap. The realization of a group III nitride 3DPC with uniform features and a band gap at wavelengths in the visible region is an important step toward realizing complete control of the electromagnetic environment for group III nitride based optoelectronic devices.

Application of quantum-behaved particle swarm optimization to motor imagery EEG classification.

PubMed

Hsu, Wei-Yen

2013-12-01

In this study, we propose a recognition system for single-trial analysis of motor imagery (MI) electroencephalogram (EEG) data. Applying event-related brain potential (ERP) data acquired from the sensorimotor cortices, the system chiefly consists of automatic artifact elimination, feature extraction, feature selection and classification. In addition to the use of independent component analysis, a similarity measure is proposed to further remove the electrooculographic (EOG) artifacts automatically. Several potential features, such as wavelet-fractal features, are then extracted for subsequent classification. Next, quantum-behaved particle swarm optimization (QPSO) is used to select features from the feature combination. Finally, selected sub-features are classified by support vector machine (SVM). Compared with without artifact elimination, feature selection using a genetic algorithm (GA) and feature classification with Fisher's linear discriminant (FLD) on MI data from two data sets for eight subjects, the results indicate that the proposed method is promising in brain-computer interface (BCI) applications.

Optimal subset selection of primary sequence features using the genetic algorithm for thermophilic proteins identification.

PubMed

Wang, LiQiang; Li, CuiFeng

2014-10-01

A genetic algorithm (GA) coupled with multiple linear regression (MLR) was used to extract useful features from amino acids and g-gap dipeptides for distinguishing between thermophilic and non-thermophilic proteins. The method was trained by a benchmark dataset of 915 thermophilic and 793 non-thermophilic proteins. The method reached an overall accuracy of 95.4 % in a Jackknife test using nine amino acids, 38 0-gap dipeptides and 29 1-gap dipeptides. The accuracy as a function of protein size ranged between 85.8 and 96.9 %. The overall accuracies of three independent tests were 93, 93.4 and 91.8 %. The observed results of detecting thermophilic proteins suggest that the GA-MLR approach described herein should be a powerful method for selecting features that describe thermostabile machines and be an aid in the design of more stable proteins.

Simultaneous determination of indoor ammonia pollution and its biological metabolite in the human body with a recyclable nanocrystalline lanthanide-functionalized MOF

NASA Astrophysics Data System (ADS)

Hao, Ji-Na; Yan, Bing

2016-01-01

A Eu3+ post-functionalized metal-organic framework of nanosized Ga(OH)bpydc(Eu3+@Ga(OH)bpydc, 1a) with intense luminescence is synthesized and characterized. Luminescence measurements reveal that 1a can detect ammonia gas selectively and sensitively among various indoor air pollutants. 1a can simultaneously determine a biological ammonia metabolite (urinary urea) in the human body, which is a rare example of a luminescent sensor that can monitor pollutants in the environment and also detect their biological markers. Furthermore, 1a exhibits appealing features including high selectivity and sensitivity, fast response, simple and quick regeneration, and excellent recyclability.A Eu3+ post-functionalized metal-organic framework of nanosized Ga(OH)bpydc(Eu3+@Ga(OH)bpydc, 1a) with intense luminescence is synthesized and characterized. Luminescence measurements reveal that 1a can detect ammonia gas selectively and sensitively among various indoor air pollutants. 1a can simultaneously determine a biological ammonia metabolite (urinary urea) in the human body, which is a rare example of a luminescent sensor that can monitor pollutants in the environment and also detect their biological markers. Furthermore, 1a exhibits appealing features including high selectivity and sensitivity, fast response, simple and quick regeneration, and excellent recyclability. Electronic supplementary information (ESI) available: Experimental section; XPS spectra; N2 adsorption-desorption isotherms; ICP data; SEM image; PXRD patterns and other luminescence data. See DOI: 10.1039/c5nr06066d

Novel Mahalanobis-based feature selection improves one-class classification of early hepatocellular carcinoma.

PubMed

Thomaz, Ricardo de Lima; Carneiro, Pedro Cunha; Bonin, João Eliton; Macedo, Túlio Augusto Alves; Patrocinio, Ana Claudia; Soares, Alcimar Barbosa

2018-05-01

Detection of early hepatocellular carcinoma (HCC) is responsible for increasing survival rates in up to 40%. One-class classifiers can be used for modeling early HCC in multidetector computed tomography (MDCT), but demand the specific knowledge pertaining to the set of features that best describes the target class. Although the literature outlines several features for characterizing liver lesions, it is unclear which is most relevant for describing early HCC. In this paper, we introduce an unconstrained GA feature selection algorithm based on a multi-objective Mahalanobis fitness function to improve the classification performance for early HCC. We compared our approach to a constrained Mahalanobis function and two other unconstrained functions using Welch's t-test and Gaussian Data Descriptors. The performance of each fitness function was evaluated by cross-validating a one-class SVM. The results show that the proposed multi-objective Mahalanobis fitness function is capable of significantly reducing data dimensionality (96.4%) and improving one-class classification of early HCC (0.84 AUC). Furthermore, the results provide strong evidence that intensity features extracted at the arterial to portal and arterial to equilibrium phases are important for classifying early HCC.

Functionalized vertical GaN micro pillar arrays with high signal-to-background ratio for detection and analysis of proteins secreted from breast tumor cells.

PubMed

Choi, Mun-Ki; Kim, Gil-Sung; Jeong, Jin-Tak; Lim, Jung-Taek; Lee, Won-Yong; Umar, Ahmad; Lee, Sang-Kwon

2017-11-02

The detection of cancer biomarkers has recently attracted significant attention as a means of determining the correct course of treatment with targeted therapeutics. However, because the concentration of these biomarkers in blood is usually relatively low, highly sensitive biosensors for fluorescence imaging and precise detection are needed. In this study, we have successfully developed vertical GaN micropillar (MP) based biosensors for fluorescence sensing and quantitative measurement of CA15-3 antigens. The highly ordered vertical GaN MP arrays result in the successful immobilization of CA15-3 antigens on each feature of the arrays, thereby allowing the detection of an individual fluorescence signal from the top surface of the arrays owing to the high regularity of fluorophore-tagged MP spots and relatively low background signal. Therefore, our fluorescence-labeled and CA15-3 functionalized vertical GaN-MP-based biosensor is suitable for the selective quantitative analysis of secreted CA15-3 antigens from MCF-7 cell lines, and helps in the early diagnosis and prognosis of serious diseases as well as the monitoring of the therapeutic response of breast cancer patients.

Dual Tracer PET Imaging (68Ga-DOTATATE and 18F-FDG) Features in Pulmonary Carcinoid: Correlation with Tumor Proliferation Index.

PubMed

Bhatkar, Dhiraj; Utpat, Ketaki; Basu, Sandip; Joshi, Jyotsna M

2017-01-01

Pulmonary carcinoid tumors are rare group of lung neoplasms representing 1% of all the lung tumors. The typical bronchial carcinoids showed higher and more selective uptake of 68 Ga-DOTATATE than of 18 F-FDG on PET-CT. The Ki-67(MIB-1), a tumor proliferation index is a prognostic marker in neuroendocrine tumors for estimating tumor progression. Atypical carcinoids have higher Ki-67 index and have an increased propensity to metastasize as compared to typical ones. 68 Ga-DOTATATE PET imaging along with Ki-67 can be correlated for better management of patients with neuroendocrine tumors. We describe the dual tracer imaging features in a patient of pulmonary carcinoid with avid 68 Ga-DOTATATE and minimal 18 FDG ( 18 Flurodeoxyglucose) uptake diagnosed on the basis of imaging and bronchoscopic biopsy and its correlation with tumor proliferation index.

Genetic algorithm for the optimization of features and neural networks in ECG signals classification

NASA Astrophysics Data System (ADS)

Li, Hongqiang; Yuan, Danyang; Ma, Xiangdong; Cui, Dianyin; Cao, Lu

2017-01-01

Feature extraction and classification of electrocardiogram (ECG) signals are necessary for the automatic diagnosis of cardiac diseases. In this study, a novel method based on genetic algorithm-back propagation neural network (GA-BPNN) for classifying ECG signals with feature extraction using wavelet packet decomposition (WPD) is proposed. WPD combined with the statistical method is utilized to extract the effective features of ECG signals. The statistical features of the wavelet packet coefficients are calculated as the feature sets. GA is employed to decrease the dimensions of the feature sets and to optimize the weights and biases of the back propagation neural network (BPNN). Thereafter, the optimized BPNN classifier is applied to classify six types of ECG signals. In addition, an experimental platform is constructed for ECG signal acquisition to supply the ECG data for verifying the effectiveness of the proposed method. The GA-BPNN method with the MIT-BIH arrhythmia database achieved a dimension reduction of nearly 50% and produced good classification results with an accuracy of 97.78%. The experimental results based on the established acquisition platform indicated that the GA-BPNN method achieved a high classification accuracy of 99.33% and could be efficiently applied in the automatic identification of cardiac arrhythmias.

YamiPred: A Novel Evolutionary Method for Predicting Pre-miRNAs and Selecting Relevant Features.

PubMed

Kleftogiannis, Dimitrios; Theofilatos, Konstantinos; Likothanassis, Spiros; Mavroudi, Seferina

2015-01-01

MicroRNAs (miRNAs) are small non-coding RNAs, which play a significant role in gene regulation. Predicting miRNA genes is a challenging bioinformatics problem and existing experimental and computational methods fail to deal with it effectively. We developed YamiPred, an embedded classification method that combines the efficiency and robustness of support vector machines (SVM) with genetic algorithms (GA) for feature selection and parameters optimization. YamiPred was tested in a new and realistic human dataset and was compared with state-of-the-art computational intelligence approaches and the prevalent SVM-based tools for miRNA prediction. Experimental results indicate that YamiPred outperforms existing approaches in terms of accuracy and of geometric mean of sensitivity and specificity. The embedded feature selection component selects a compact feature subset that contributes to the performance optimization. Further experimentation with this minimal feature subset has achieved very high classification performance and revealed the minimum number of samples required for developing a robust predictor. YamiPred also confirmed the important role of commonly used features such as entropy and enthalpy, and uncovered the significance of newly introduced features, such as %A-U aggregate nucleotide frequency and positional entropy. The best model trained on human data has successfully predicted pre-miRNAs to other organisms including the category of viruses.

GA(M)E-QSAR: a novel, fully automatic genetic-algorithm-(meta)-ensembles approach for binary classification in ligand-based drug design.

PubMed

Pérez-Castillo, Yunierkis; Lazar, Cosmin; Taminau, Jonatan; Froeyen, Mathy; Cabrera-Pérez, Miguel Ángel; Nowé, Ann

2012-09-24

Computer-aided drug design has become an important component of the drug discovery process. Despite the advances in this field, there is not a unique modeling approach that can be successfully applied to solve the whole range of problems faced during QSAR modeling. Feature selection and ensemble modeling are active areas of research in ligand-based drug design. Here we introduce the GA(M)E-QSAR algorithm that combines the search and optimization capabilities of Genetic Algorithms with the simplicity of the Adaboost ensemble-based classification algorithm to solve binary classification problems. We also explore the usefulness of Meta-Ensembles trained with Adaboost and Voting schemes to further improve the accuracy, generalization, and robustness of the optimal Adaboost Single Ensemble derived from the Genetic Algorithm optimization. We evaluated the performance of our algorithm using five data sets from the literature and found that it is capable of yielding similar or better classification results to what has been reported for these data sets with a higher enrichment of active compounds relative to the whole actives subset when only the most active chemicals are considered. More important, we compared our methodology with state of the art feature selection and classification approaches and found that it can provide highly accurate, robust, and generalizable models. In the case of the Adaboost Ensembles derived from the Genetic Algorithm search, the final models are quite simple since they consist of a weighted sum of the output of single feature classifiers. Furthermore, the Adaboost scores can be used as ranking criterion to prioritize chemicals for synthesis and biological evaluation after virtual screening experiments.

Prediction of apoptosis protein locations with genetic algorithms and support vector machines through a new mode of pseudo amino acid composition.

PubMed

Kandaswamy, Krishna Kumar; Pugalenthi, Ganesan; Möller, Steffen; Hartmann, Enno; Kalies, Kai-Uwe; Suganthan, P N; Martinetz, Thomas

2010-12-01

Apoptosis is an essential process for controlling tissue homeostasis by regulating a physiological balance between cell proliferation and cell death. The subcellular locations of proteins performing the cell death are determined by mostly independent cellular mechanisms. The regular bioinformatics tools to predict the subcellular locations of such apoptotic proteins do often fail. This work proposes a model for the sorting of proteins that are involved in apoptosis, allowing us to both the prediction of their subcellular locations as well as the molecular properties that contributed to it. We report a novel hybrid Genetic Algorithm (GA)/Support Vector Machine (SVM) approach to predict apoptotic protein sequences using 119 sequence derived properties like frequency of amino acid groups, secondary structure, and physicochemical properties. GA is used for selecting a near-optimal subset of informative features that is most relevant for the classification. Jackknife cross-validation is applied to test the predictive capability of the proposed method on 317 apoptosis proteins. Our method achieved 85.80% accuracy using all 119 features and 89.91% accuracy for 25 features selected by GA. Our models were examined by a test dataset of 98 apoptosis proteins and obtained an overall accuracy of 90.34%. The results show that the proposed approach is promising; it is able to select small subsets of features and still improves the classification accuracy. Our model can contribute to the understanding of programmed cell death and drug discovery. The software and dataset are available at http://www.inb.uni-luebeck.de/tools-demos/apoptosis/GASVM.

Influence of vacancy defect on surface feature and adsorption of Cs on GaN(0001) surface.

PubMed

Ji, Yanjun; Du, Yujie; Wang, Meishan

2014-01-01

The effects of Ga and N vacancy defect on the change in surface feature, work function, and characteristic of Cs adsorption on a (2 × 2) GaN(0001) surface have been investigated using density functional theory with a plane-wave ultrasoft pseudopotential method based on first-principles calculations. The covalent bonds gain strength for Ga vacancy defect, whereas they grow weak for N vacancy defect. The lower work function is achieved for Ga and N vacancy defect surfaces than intact surface. The most stable position of Cs adatom on Ga vacancy defect surface is at T1 site, whereas it is at B(Ga) site on N vacancy defect surface. The E(ads) of Cs on GaN(0001) vacancy defect surface increases compared with that of intact surface; this illustrates that the adsorption of Cs on intact surface is more stable.

Paroxysmal atrial fibrillation prediction method with shorter HRV sequences.

PubMed

Boon, K H; Khalil-Hani, M; Malarvili, M B; Sia, C W

2016-10-01

This paper proposes a method that predicts the onset of paroxysmal atrial fibrillation (PAF), using heart rate variability (HRV) segments that are shorter than those applied in existing methods, while maintaining good prediction accuracy. PAF is a common cardiac arrhythmia that increases the health risk of a patient, and the development of an accurate predictor of the onset of PAF is clinical important because it increases the possibility to stabilize (electrically) and prevent the onset of atrial arrhythmias with different pacing techniques. We investigate the effect of HRV features extracted from different lengths of HRV segments prior to PAF onset with the proposed PAF prediction method. The pre-processing stage of the predictor includes QRS detection, HRV quantification and ectopic beat correction. Time-domain, frequency-domain, non-linear and bispectrum features are then extracted from the quantified HRV. In the feature selection, the HRV feature set and classifier parameters are optimized simultaneously using an optimization procedure based on genetic algorithm (GA). Both full feature set and statistically significant feature subset are optimized by GA respectively. For the statistically significant feature subset, Mann-Whitney U test is used to filter non-statistical significance features that cannot pass the statistical test at 20% significant level. The final stage of our predictor is the classifier that is based on support vector machine (SVM). A 10-fold cross-validation is applied in performance evaluation, and the proposed method achieves 79.3% prediction accuracy using 15-minutes HRV segment. This accuracy is comparable to that achieved by existing methods that use 30-minutes HRV segments, most of which achieves accuracy of around 80%. More importantly, our method significantly outperforms those that applied segments shorter than 30 minutes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

GaSb-based single-mode distributed feedback lasers for sensing (Conference Presentation)

NASA Astrophysics Data System (ADS)

Gupta, James A.; Bezinger, Andrew; Lapointe, Jean; Poitras, Daniel; Aers, Geof C.

2017-02-01

GaSb-based tunable single-mode diode lasers can enable rapid, highly-selective and highly-sensitive absorption spectroscopy systems for gas sensing. In this work, single-mode distributed feedback (DFB) laser diodes were developed for the detection of various trace gases in the 2-3.3um range, including CO2, CO, HF, H2S, H2O and CH4. The lasers were fabricated using an index-coupled grating process without epitaxial regrowth, making the process significantly less expensive than conventional DFB fabrication. The devices are based on InGaAsSb/AlGaAsSb separate confinement heterostructures grown on GaSb by molecular beam epitaxy. DFB lasers were produced using a two step etch process. Narrow ridge waveguides were first defined by optical lithography and etched into the semiconductor. Lateral gratings were then defined on both sides of the ridge using electron-beam lithography and etched to produce the index-grating. Effective index modeling was used to optimize the ridge width, etch depths and the grating pitch to ensure single-lateral-mode operation and adequate coupling strength. The effective index method was further used to simulate the DFB laser emission spectrum, based on a transfer matrix model for light transmission through the periodic structure. The fabricated lasers exhibit single-mode operation which is tunable through the absorption features of the various target gases by adjustment of the drive current. In addition to the established open-path sensing applications, these devices have great potential for optoelectronic integrated gas sensors, making use of integrated photodetectors and possibly on-chip Si photonics waveguide structures.

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

Getsoian, Andrew "Bean"; Das, Ujjal; Camacho-Bunquin, Jeffrey

Gallium-modified zeolites are known catalysts for the dehydrogenation of alkanes, reactivity that finds industrial application in the aromatization of light alkanes by Ga-ZSM5. While the role of gallium cations in alkane activation is well known, the oxidation state and coordination environment of gallium under reaction conditions has been the subject of debate. Edge shifts in Ga K-edge XANES spectra acquired under reaction conditions have long been interpreted as evidence for reduction of Ga(III) to Ga(I). However, a change in oxidation state is not the only factor that can give rise to a change in the XANES spectrum. In order tomore » better understand the XANES spectra of working catalysts, we have synthesized a series of molecular model compounds and grafted surface organometallic Ga species and compared their XANES spectra to those of gallium-based catalysts acquired under reducing conditions. We demonstrate that changes in the identity and number of gallium nearest neighbors can give rise to changes in XANES spectra similar to those attributed in literature to changes in oxidation state. Specifically, spectral features previously attributed to Ga(I) may be equally well interpreted as evidence for low-coordinate Ga(III) alkyl or hydride species. Furthermore, these findings apply both to gallium-impregnated zeolite catalysts and to silica-supported single site gallium catalysts, the latter of which is found to be active and selective for dehydrogenation of propane and hydrogenation of propylene.« less

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

Getsoian, Andrew “Bean”; Das, Ujjal; Camacho-Bunquin, Jeffrey

Gallium-modified zeolites are known catalysts for the dehydrogenation of alkanes, reactivity that finds industrial application in the aromatization of light alkanes by Ga-ZSM5. While the role of gallium cations in alkane activation is well known, the oxidation state and coordination environment of gallium under reaction conditions has been the subject of debate. Edge shifts in Ga K-edge XANES spectra acquired under reaction conditions have long been interpreted as evidence for reduction of Ga(III) to Ga(I). However, a change in oxidation state is not the only factor that can give rise to a change in the XANES spectrum. In order tomore » better understand the XANES spectra of working catalysts, we have synthesized a series of molecular model compounds and grafted surface organometallic Ga species and compared their XANES spectra to those of gallium-based catalysts acquired under reducing conditions. We demonstrate that changes in the identity and number of gallium nearest neighbors can give rise to changes in XANES spectra similar to those attributed in literature to changes in oxidation state. Specifically, spectral features previously attributed to Ga(I) may be equally well interpreted as evidence for low-coordinate Ga(III) alkyl or hydride species. These findings apply both to gallium-impregnated zeolite catalysts and to silica-supported single site gallium catalysts, the latter of which is found to be active and selective for dehydrogenation of propane and hydrogenation of propylene.« less

Comprehensive Genomic Profiling of Esthesioneuroblastoma Reveals Additional Treatment Options.

PubMed

Gay, Laurie M; Kim, Sungeun; Fedorchak, Kyle; Kundranda, Madappa; Odia, Yazmin; Nangia, Chaitali; Battiste, James; Colon-Otero, Gerardo; Powell, Steven; Russell, Jeffery; Elvin, Julia A; Vergilio, Jo-Anne; Suh, James; Ali, Siraj M; Stephens, Philip J; Miller, Vincent A; Ross, Jeffrey S

2017-07-01

Esthesioneuroblastoma (ENB), also known as olfactory neuroblastoma, is a rare malignant neoplasm of the olfactory mucosa. Despite surgical resection combined with radiotherapy and adjuvant chemotherapy, ENB often relapses with rapid progression. Current multimodality, nontargeted therapy for relapsed ENB is of limited clinical benefit. We queried whether comprehensive genomic profiling (CGP) of relapsed or refractory ENB can uncover genomic alterations (GA) that could identify potential targeted therapies for these patients. CGP was performed on formalin-fixed, paraffin-embedded sections from 41 consecutive clinical cases of ENBs using a hybrid-capture, adaptor ligation based next-generation sequencing assay to a mean coverage depth of 593X. The results were analyzed for base substitutions, insertions and deletions, select rearrangements, and copy number changes (amplifications and homozygous deletions). Clinically relevant GA (CRGA) were defined as GA linked to drugs on the market or under evaluation in clinical trials. A total of 28 ENBs harbored GA, with a mean of 1.5 GA per sample. Approximately half of the ENBs (21, 51%) featured at least one CRGA, with an average of 1 CRGA per sample. The most commonly altered gene was TP53 (17%), with GA in PIK3CA , NF1 , CDKN2A , and CDKN2C occurring in 7% of samples. We report comprehensive genomic profiles for 41 ENB tumors. CGP revealed potential new therapeutic targets, including targetable GA in the mTOR, CDK and growth factor signaling pathways, highlighting the clinical value of genomic profiling in ENB. Comprehensive genomic profiling of 41 relapsed or refractory ENBs reveals recurrent alterations or classes of mutation, including amplification of tyrosine kinases encoded on chromosome 5q and mutations affecting genes in the mTOR/PI3K pathway. Approximately half of the ENBs (21, 51%) featured at least one clinically relevant genomic alteration (CRGA), with an average of 1 CRGA per sample. The most commonly altered gene was TP53 (17%), and alterations in PIK3CA , NF1 , CDKN2A , or CDKN2C were identified in 7% of samples. Responses to treatment with the kinase inhibitors sunitinib, everolimus, and pazopanib are presented in conjunction with tumor genomics. © AlphaMed Press 2017.

Mining Feature of Data Fusion in the Classification of Beer Flavor Information Using E-Tongue and E-Nose

PubMed Central

Men, Hong; Shi, Yan; Fu, Songlin; Jiao, Yanan; Qiao, Yu; Liu, Jingjing

2017-01-01

Multi-sensor data fusion can provide more comprehensive and more accurate analysis results. However, it also brings some redundant information, which is an important issue with respect to finding a feature-mining method for intuitive and efficient analysis. This paper demonstrates a feature-mining method based on variable accumulation to find the best expression form and variables’ behavior affecting beer flavor. First, e-tongue and e-nose were used to gather the taste and olfactory information of beer, respectively. Second, principal component analysis (PCA), genetic algorithm-partial least squares (GA-PLS), and variable importance of projection (VIP) scores were applied to select feature variables of the original fusion set. Finally, the classification models based on support vector machine (SVM), random forests (RF), and extreme learning machine (ELM) were established to evaluate the efficiency of the feature-mining method. The result shows that the feature-mining method based on variable accumulation obtains the main feature affecting beer flavor information, and the best classification performance for the SVM, RF, and ELM models with 96.67%, 94.44%, and 98.33% prediction accuracy, respectively. PMID:28753917

Influence of Vacancy Defect on Surface Feature and Adsorption of Cs on GaN(0001) Surface

PubMed Central

Ji, Yanjun; Du, Yujie; Wang, Meishan

2014-01-01

The effects of Ga and N vacancy defect on the change in surface feature, work function, and characteristic of Cs adsorption on a (2 × 2) GaN(0001) surface have been investigated using density functional theory with a plane-wave ultrasoft pseudopotential method based on first-principles calculations. The covalent bonds gain strength for Ga vacancy defect, whereas they grow weak for N vacancy defect. The lower work function is achieved for Ga and N vacancy defect surfaces than intact surface. The most stable position of Cs adatom on Ga vacancy defect surface is at T1 site, whereas it is at BGa site on N vacancy defect surface. The E ads of Cs on GaN(0001) vacancy defect surface increases compared with that of intact surface; this illustrates that the adsorption of Cs on intact surface is more stable. PMID:25126599

Polarization-Engineered Ga-Face GaN-Based Heterostructures for Normally-Off Heterostructure Field-Effect Transistors

NASA Astrophysics Data System (ADS)

Kim, Hyeongnam; Nath, Digbijoy; Rajan, Siddharth; Lu, Wu

2013-01-01

Polarization-engineered Ga-face GaN-based heterostructures with a GaN cap layer and an AlGaN/ p-GaN back barrier have been designed for normally-off field-effect transistors (FETs). The simulation results show that an unintentionally doped GaN cap and p-GaN layer in the buffer primarily deplete electrons in the channel and the Al0.2Ga0.8N back barrier helps to pinch off the channel. Experimentally, we have demonstrated a normally-off GaN-based field-effect transistor on the designed GaN cap/Al0.3Ga0.7N/GaN channel/Al0.2Ga0.8N/ p-GaN/GaN heterostructure. A positive threshold voltage of 0.2 V and maximum transconductance of 2.6 mS/mm were achieved for 80- μm-long gate devices. The device fabrication process does not require a dry etching process for gate recessing, while highly selective etching of the GaN cap against a very thin Al0.3GaN0.7N top barrier has to be performed to create a two-dimensional electron gas for both the ohmic and access regions. A self-aligned, selective etch of the GaN cap in the access region is introduced, using the gate metal as an etch mask. The absence of gate recess etching is promising for uniform and repeatable threshold voltage control in normally-off AlGaN/GaN heterostructure FETs for power switching applications.

An ensemble of SVM classifiers based on gene pairs.

PubMed

Tong, Muchenxuan; Liu, Kun-Hong; Xu, Chungui; Ju, Wenbin

2013-07-01

In this paper, a genetic algorithm (GA) based ensemble support vector machine (SVM) classifier built on gene pairs (GA-ESP) is proposed. The SVMs (base classifiers of the ensemble system) are trained on different informative gene pairs. These gene pairs are selected by the top scoring pair (TSP) criterion. Each of these pairs projects the original microarray expression onto a 2-D space. Extensive permutation of gene pairs may reveal more useful information and potentially lead to an ensemble classifier with satisfactory accuracy and interpretability. GA is further applied to select an optimized combination of base classifiers. The effectiveness of the GA-ESP classifier is evaluated on both binary-class and multi-class datasets. Copyright © 2013 Elsevier Ltd. All rights reserved.

A novel approach for dimension reduction of microarray.

PubMed

Aziz, Rabia; Verma, C K; Srivastava, Namita

2017-12-01

This paper proposes a new hybrid search technique for feature (gene) selection (FS) using Independent component analysis (ICA) and Artificial Bee Colony (ABC) called ICA+ABC, to select informative genes based on a Naïve Bayes (NB) algorithm. An important trait of this technique is the optimization of ICA feature vector using ABC. ICA+ABC is a hybrid search algorithm that combines the benefits of extraction approach, to reduce the size of data and wrapper approach, to optimize the reduced feature vectors. This hybrid search technique is facilitated by evaluating the performance of ICA+ABC on six standard gene expression datasets of classification. Extensive experiments were conducted to compare the performance of ICA+ABC with the results obtained from recently published Minimum Redundancy Maximum Relevance (mRMR) +ABC algorithm for NB classifier. Also to check the performance that how ICA+ABC works as feature selection with NB classifier, compared the combination of ICA with popular filter techniques and with other similar bio inspired algorithm such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The result shows that ICA+ABC has a significant ability to generate small subsets of genes from the ICA feature vector, that significantly improve the classification accuracy of NB classifier compared to other previously suggested methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Lamb Wave Damage Quantification Using GA-Based LS-SVM.

PubMed

Sun, Fuqiang; Wang, Ning; He, Jingjing; Guan, Xuefei; Yang, Jinsong

2017-06-12

Lamb waves have been reported to be an efficient tool for non-destructive evaluations (NDE) for various application scenarios. However, accurate and reliable damage quantification using the Lamb wave method is still a practical challenge, due to the complex underlying mechanism of Lamb wave propagation and damage detection. This paper presents a Lamb wave damage quantification method using a least square support vector machine (LS-SVM) and a genetic algorithm (GA). Three damage sensitive features, namely, normalized amplitude, phase change, and correlation coefficient, were proposed to describe changes of Lamb wave characteristics caused by damage. In view of commonly used data-driven methods, the GA-based LS-SVM model using the proposed three damage sensitive features was implemented to evaluate the crack size. The GA method was adopted to optimize the model parameters. The results of GA-based LS-SVM were validated using coupon test data and lap joint component test data with naturally developed fatigue cracks. Cases of different loading and manufacturer were also included to further verify the robustness of the proposed method for crack quantification.

Lamb Wave Damage Quantification Using GA-Based LS-SVM

PubMed Central

Sun, Fuqiang; Wang, Ning; He, Jingjing; Guan, Xuefei; Yang, Jinsong

2017-01-01

Lamb waves have been reported to be an efficient tool for non-destructive evaluations (NDE) for various application scenarios. However, accurate and reliable damage quantification using the Lamb wave method is still a practical challenge, due to the complex underlying mechanism of Lamb wave propagation and damage detection. This paper presents a Lamb wave damage quantification method using a least square support vector machine (LS-SVM) and a genetic algorithm (GA). Three damage sensitive features, namely, normalized amplitude, phase change, and correlation coefficient, were proposed to describe changes of Lamb wave characteristics caused by damage. In view of commonly used data-driven methods, the GA-based LS-SVM model using the proposed three damage sensitive features was implemented to evaluate the crack size. The GA method was adopted to optimize the model parameters. The results of GA-based LS-SVM were validated using coupon test data and lap joint component test data with naturally developed fatigue cracks. Cases of different loading and manufacturer were also included to further verify the robustness of the proposed method for crack quantification. PMID:28773003

Learning-based prediction of gestational age from ultrasound images of the fetal brain.

PubMed

Namburete, Ana I L; Stebbing, Richard V; Kemp, Bryn; Yaqub, Mohammad; Papageorghiou, Aris T; Alison Noble, J

2015-04-01

We propose an automated framework for predicting gestational age (GA) and neurodevelopmental maturation of a fetus based on 3D ultrasound (US) brain image appearance. Our method capitalizes on age-related sonographic image patterns in conjunction with clinical measurements to develop, for the first time, a predictive age model which improves on the GA-prediction potential of US images. The framework benefits from a manifold surface representation of the fetal head which delineates the inner skull boundary and serves as a common coordinate system based on cranial position. This allows for fast and efficient sampling of anatomically-corresponding brain regions to achieve like-for-like structural comparison of different developmental stages. We develop bespoke features which capture neurosonographic patterns in 3D images, and using a regression forest classifier, we characterize structural brain development both spatially and temporally to capture the natural variation existing in a healthy population (N=447) over an age range of active brain maturation (18-34weeks). On a routine clinical dataset (N=187) our age prediction results strongly correlate with true GA (r=0.98,accurate within±6.10days), confirming the link between maturational progression and neurosonographic activity observable across gestation. Our model also outperforms current clinical methods by ±4.57 days in the third trimester-a period complicated by biological variations in the fetal population. Through feature selection, the model successfully identified the most age-discriminating anatomies over this age range as being the Sylvian fissure, cingulate, and callosal sulci. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

The K 2S 2O 8-KOH photoetching system for GaN

NASA Astrophysics Data System (ADS)

Weyher, J. L.; Tichelaar, F. D.; van Dorp, D. H.; Kelly, J. J.; Khachapuridze, A.

2010-09-01

A recently developed photoetching system for n-type GaN, a KOH solution containing the strong oxidizing agent potassium peroxydisulphate (K 2S 2O 8), was studied in detail. By careful selection of the etching parameters, such as the ratio of components and the hydrodynamics, two distinct modes were defined: defect-selective etching (denoted by KSO-D) and polishing (KSO-P). Both photoetching methods can be used under open-circuit (electroless) conditions. Well-defined dislocation-related etch whiskers are formed during KSO-D etching. All types of dislocations are revealed, and this was confirmed by cross-sectional TEM examination of the etched samples. Extended electrically active defects are also clearly revealed. The known relationship between etch rate and carrier concentration for photoetching of GaN in KOH solutions was confirmed for KSO-D etch using Raman measurements. It is shown that during KSO-P etching diffusion is the rate-limiting step, i.e. this etch is suitable for polishing of GaN. Some constraints of the KSO etching system for GaN are discussed and peculiar etch features, so far not understood, are described.

An Extended Spectral-Spatial Classification Approach for Hyperspectral Data

NASA Astrophysics Data System (ADS)

Akbari, D.

2017-11-01

In this paper an extended classification approach for hyperspectral imagery based on both spectral and spatial information is proposed. The spatial information is obtained by an enhanced marker-based minimum spanning forest (MSF) algorithm. Three different methods of dimension reduction are first used to obtain the subspace of hyperspectral data: (1) unsupervised feature extraction methods including principal component analysis (PCA), independent component analysis (ICA), and minimum noise fraction (MNF); (2) supervised feature extraction including decision boundary feature extraction (DBFE), discriminate analysis feature extraction (DAFE), and nonparametric weighted feature extraction (NWFE); (3) genetic algorithm (GA). The spectral features obtained are then fed into the enhanced marker-based MSF classification algorithm. In the enhanced MSF algorithm, the markers are extracted from the classification maps obtained by both SVM and watershed segmentation algorithm. To evaluate the proposed approach, the Pavia University hyperspectral data is tested. Experimental results show that the proposed approach using GA achieves an approximately 8 % overall accuracy higher than the original MSF-based algorithm.

Conductivity based on selective etch for GaN devices and applications thereof

DOEpatents

Zhang, Yu; Sun, Qian; Han, Jung

2015-12-08

This invention relates to methods of generating NP gallium nitride (GaN) across large areas (>1 cm.sup.2) with controlled pore diameters, pore density, and porosity. Also disclosed are methods of generating novel optoelectronic devices based on porous GaN. Additionally a layer transfer scheme to separate and create free-standing crystalline GaN thin layers is disclosed that enables a new device manufacturing paradigm involving substrate recycling. Other disclosed embodiments of this invention relate to fabrication of GaN based nanocrystals and the use of NP GaN electrodes for electrolysis, water splitting, or photosynthetic process applications.

Automatic epileptic seizure detection in EEGs using MF-DFA, SVM based on cloud computing.

PubMed

Zhang, Zhongnan; Wen, Tingxi; Huang, Wei; Wang, Meihong; Li, Chunfeng

2017-01-01

Epilepsy is a chronic disease with transient brain dysfunction that results from the sudden abnormal discharge of neurons in the brain. Since electroencephalogram (EEG) is a harmless and noninvasive detection method, it plays an important role in the detection of neurological diseases. However, the process of analyzing EEG to detect neurological diseases is often difficult because the brain electrical signals are random, non-stationary and nonlinear. In order to overcome such difficulty, this study aims to develop a new computer-aided scheme for automatic epileptic seizure detection in EEGs based on multi-fractal detrended fluctuation analysis (MF-DFA) and support vector machine (SVM). New scheme first extracts features from EEG by MF-DFA during the first stage. Then, the scheme applies a genetic algorithm (GA) to calculate parameters used in SVM and classify the training data according to the selected features using SVM. Finally, the trained SVM classifier is exploited to detect neurological diseases. The algorithm utilizes MLlib from library of SPARK and runs on cloud platform. Applying to a public dataset for experiment, the study results show that the new feature extraction method and scheme can detect signals with less features and the accuracy of the classification reached up to 99%. MF-DFA is a promising approach to extract features for analyzing EEG, because of its simple algorithm procedure and less parameters. The features obtained by MF-DFA can represent samples as well as traditional wavelet transform and Lyapunov exponents. GA can always find useful parameters for SVM with enough execution time. The results illustrate that the classification model can achieve comparable accuracy, which means that it is effective in epileptic seizure detection.

Selective dry etching of III-V nitrides in Cl{sub 2}/Ar, CH{sub 4}/H{sub 2}/Ar, ICi/Ar, and IBr/Ar

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

Vartuli, C.B.; Pearton, S.J.; MacKenzie, J.D.

1996-10-01

The selectivity for etching the binary (GaN, AlN, and InN) and ternary nitrides (InGaN and InAlN) relative to each other in Cl{sub 2}/Ar, CH{sub 4}/H{sub 2}/Ar, ICl/Ar, or IBr/Ar electron cyclotron resonance (ECR) plasmas, and Cl{sub 2}/Ar or CH{sub 4}/H{sub 2}/Ar reactive ion (RIE) plasmas was investigated. Cl-based etches appear to be the best choice for maximizing the selectivity of GaN over the other nitrides. GaN/AlN and GaN/InGaN etch rate ratios of {approximately} 10 were achieved at low RF power in Cl{sub 2}/Ar under ECR and RIE conditions, respectively. GaN/InN selectivity of 10 was found in ICl under ECR conditions.more » A relatively high selectivity (> 6) of InN/GaN was achieved in CH{sub 4}/H{sub 2}/Ar under ECR conditions at low RF powers (50 W). Since the high bond strengths of the nitrides require either high ion energies or densities to achieve practical etch rates it is difficult to achieve high selectivities.« less

Atmospheric pressure-MOVPE growth of GaSb/GaAs quantum dots

NASA Astrophysics Data System (ADS)

Tile, Ngcali; Ahia, Chinedu C.; Olivier, Jaco; Botha, Johannes Reinhardt

2018-04-01

This study focuses on the growth of GaSb/GaAs quantum dots (QD) using an atmospheric pressure MOVPE system. For the best uncapped dots, the average dot height, base diameter and density are 5 nm, 45 nm and 4.5×1010 cm-2, respectively. Capping of GaSb QDs at high temperatures caused flattening and formation of thin inhomogeneous GaSb layer inside GaAs resulting in no obvious QD PL peak. Capping at low temperatures lead to the formation of dot-like features and a wetting layer (WL) with distinct PL peaks for QD and WL at 1097 nm and 983 nm respectively. Some of the dot-like features had voids. An increase in excitation power caused the QD and WL peaks to shift to higher energies. This is attributed to electrostatic band bending leading to triangular potential wells, typical of type-II alignment between GaAs and strained GaSb. Variable temperature PL measurements of the QD sample showed the decrease in the intensity of the WL peak to be faster than that of the QD peak as the temperature increased.

Structural basis of DNA folding and recognition in an AMP-DNA aptamer complex: distinct architectures but common recognition motifs for DNA and RNA aptamers complexed to AMP.

PubMed

Lin, C H; Patel, D J

1997-11-01

Structural studies by nuclear magnetic resonance (NMR) of RNA and DNA aptamer complexes identified through in vitro selection and amplification have provided a wealth of information on RNA and DNA tertiary structure and molecular recognition in solution. The RNA and DNA aptamers that target ATP (and AMP) with micromolar affinity exhibit distinct binding site sequences and secondary structures. We report below on the tertiary structure of the AMP-DNA aptamer complex in solution and compare it with the previously reported tertiary structure of the AMP-RNA aptamer complex in solution. The solution structure of the AMP-DNA aptamer complex shows, surprisingly, that two AMP molecules are intercalated at adjacent sites within a rectangular widened minor groove. Complex formation involves adaptive binding where the asymmetric internal bubble of the free DNA aptamer zippers up through formation of a continuous six-base mismatch segment which includes a pair of adjacent three-base platforms. The AMP molecules pair through their Watson-Crick edges with the minor groove edges of guanine residues. These recognition G.A mismatches are flanked by sheared G.A and reversed Hoogsteen G.G mismatch pairs. The AMP-DNA aptamer and AMP-RNA aptamer complexes have distinct tertiary structures and binding stoichiometries. Nevertheless, both complexes have similar structural features and recognition alignments in their binding pockets. Specifically, AMP targets both DNA and RNA aptamers by intercalating between purine bases and through identical G.A mismatch formation. The recognition G.A mismatch stacks with a reversed Hoogsteen G.G mismatch in one direction and with an adenine base in the other direction in both complexes. It is striking that DNA and RNA aptamers selected independently from libraries of 10(14) molecules in each case utilize identical mismatch alignments for molecular recognition with micromolar affinity within binding-site pockets containing common structural elements.

An automatic optimum number of well-distributed ground control lines selection procedure based on genetic algorithm

NASA Astrophysics Data System (ADS)

Yavari, Somayeh; Valadan Zoej, Mohammad Javad; Salehi, Bahram

2018-05-01

The procedure of selecting an optimum number and best distribution of ground control information is important in order to reach accurate and robust registration results. This paper proposes a new general procedure based on Genetic Algorithm (GA) which is applicable for all kinds of features (point, line, and areal features). However, linear features due to their unique characteristics are of interest in this investigation. This method is called Optimum number of Well-Distributed ground control Information Selection (OWDIS) procedure. Using this method, a population of binary chromosomes is randomly initialized. The ones indicate the presence of a pair of conjugate lines as a GCL and zeros specify the absence. The chromosome length is considered equal to the number of all conjugate lines. For each chromosome, the unknown parameters of a proper mathematical model can be calculated using the selected GCLs (ones in each chromosome). Then, a limited number of Check Points (CPs) are used to evaluate the Root Mean Square Error (RMSE) of each chromosome as its fitness value. The procedure continues until reaching a stopping criterion. The number and position of ones in the best chromosome indicate the selected GCLs among all conjugate lines. To evaluate the proposed method, a GeoEye and an Ikonos Images are used over different areas of Iran. Comparing the obtained results by the proposed method in a traditional RFM with conventional methods that use all conjugate lines as GCLs shows five times the accuracy improvement (pixel level accuracy) as well as the strength of the proposed method. To prevent an over-parametrization error in a traditional RFM due to the selection of a high number of improper correlated terms, an optimized line-based RFM is also proposed. The results show the superiority of the combination of the proposed OWDIS method with an optimized line-based RFM in terms of increasing the accuracy to better than 0.7 pixel, reliability, and reducing systematic errors. These results also demonstrate the high potential of linear features as reliable control features to reach sub-pixel accuracy in registration applications.

Selective-area catalyst-free MBE growth of GaN nanowires using a patterned oxide layer.

PubMed

Schumann, T; Gotschke, T; Limbach, F; Stoica, T; Calarco, R

2011-03-04

GaN nanowires (NWs) were grown selectively in holes of a patterned silicon oxide mask, by rf-plasma-assisted molecular beam epitaxy (PAMBE), without any metal catalyst. The oxide was deposited on a thin AlN buffer layer previously grown on a Si(111) substrate. Regular arrays of holes in the oxide layer were obtained using standard e-beam lithography. The selectivity of growth has been studied varying the substrate temperature, gallium beam equivalent pressure and patterning layout. Adjusting the growth parameters, GaN NWs can be selectively grown in the holes of the patterned oxide with complete suppression of the parasitic growth in between the holes. The occupation probability of a hole with a single or multiple NWs depends strongly on its diameter. The selectively grown GaN NWs have one common crystallographic orientation with respect to the Si(111) substrate via the AlN buffer layer, as proven by x-ray diffraction (XRD) measurements. Based on the experimental data, we present a schematic model of the GaN NW formation in which a GaN pedestal is initially grown in the hole.

Growth optimization toward low angle incidence microchannel epitaxy of GaN using ammonia-based metal-organic molecular beam epitaxy

NASA Astrophysics Data System (ADS)

Lin, Chia-Hung; Abe, Ryota; Uchiyama, Shota; Maruyama, Takahiro; Naritsuka, Shigeya

2012-08-01

Growth optimization toward low angle incidence microchannel epitaxy (LAIMCE) of GaN was accomplished using ammonia-based metal-organic molecular beam epitaxy (NH3-based MOMBE). Firstly, the [NH3]/[trimethylgallium (TMG)] ratio (R) dependence of selective GaN growth was studied. The growth temperature was set at 860 °C while R was varied from 5 to 200 with precursors being supplied parallel to the openings cut in the SiO2 mask. The selectivity of the growth was superior for all R, because TMG and NH3 preferably decompose on the GaN film. The formation of {112¯0}GaN or {112¯2}GaN sidewalls and (0001)GaN surface were observed by the change in R. The intersurface diffusion of Ga adatoms was also changed by a change in R. Ga adatoms migrate from the sidewalls to the top at R lower than 50, whereas the migration weakened with R greater than 100. Secondly, LAIMCE was optimized by changing the growth temperature. Consequently, 6 μm wide lateral overgrowth in the direction of precursor incidence was achieved with no pit after etching by H3PO4, which was six times wider than that in the opposite direction.

Fabrication and characterization of GaN-based light-emitting diodes without pre-activation of p-type GaN.

PubMed

Hu, Xiao-Long; Wang, Hong; Zhang, Xi-Chun

2015-01-01

We fabricated GaN-based light-emitting diodes (LEDs) without pre-activation of p-type GaN. During the fabrication process, a 100-nm-thick indium tin oxide film was served as the p-type contact layer and annealed at 500°C in N2 ambient for 20 min to increase its transparency as well as to activate the p-type GaN. The electrical measurements showed that the LEDs were featured by a lower forward voltage and higher wall-plug efficiency in comparison with LEDs using pre-activation of p-type GaN. We discussed the mechanism of activation of p-type GaN at 500°C in N2 ambient. Furthermore, x-ray photoemission spectroscopy examinations were carried out to study the improved electrical performances of the LEDs without pre-activation of p-type GaN.

[Application of characteristic NIR variables selection in portable detection of soluble solids content of apple by near infrared spectroscopy].

PubMed

Fan, Shu-Xiang; Huang, Wen-Qian; Li, Jiang-Bo; Guo, Zhi-Ming; Zhaq, Chun-Jiang

2014-10-01

In order to detect the soluble solids content(SSC)of apple conveniently and rapidly, a ring fiber probe and a portable spectrometer were applied to obtain the spectroscopy of apple. Different wavelength variable selection methods, including unin- formative variable elimination (UVE), competitive adaptive reweighted sampling (CARS) and genetic algorithm (GA) were pro- posed to select effective wavelength variables of the NIR spectroscopy of the SSC in apple based on PLS. The back interval LS- SVM (BiLS-SVM) and GA were used to select effective wavelength variables based on LS-SVM. Selected wavelength variables and full wavelength range were set as input variables of PLS model and LS-SVM model, respectively. The results indicated that PLS model built using GA-CARS on 50 characteristic variables selected from full-spectrum which had 1512 wavelengths achieved the optimal performance. The correlation coefficient (Rp) and root mean square error of prediction (RMSEP) for prediction sets were 0.962, 0.403°Brix respectively for SSC. The proposed method of GA-CARS could effectively simplify the portable detection model of SSC in apple based on near infrared spectroscopy and enhance the predictive precision. The study can provide a reference for the development of portable apple soluble solids content spectrometer.

A correlation between the defect states and yellow luminescence in AlGaN/GaN heterostructures

NASA Astrophysics Data System (ADS)

Jana, Dipankar; Sharma, T. K.

2017-07-01

AlGaN/GaN heterostructures are investigated by performing complementary spectroscopic measurements under novel experimental configurations. Distinct features related to the band edge of AlGaN and GaN layers are clearly observed in surface photovoltage spectroscopy (SPS) spectra. A few more SPS features, which are associated with defects in GaN, are also identified by performing the pump-probe SPS measurements. SPS results are strongly corroborated by the complementary photoluminescence and photoluminescence excitation (PLE) measurements. A correlation between the defect assisted SPS features and yellow luminescence (YL) peak is established by performing pump-probe SPS and PLE measurements. It is found that CN-ON donor complex is responsible for the generation of YL peak in our sample. Further, the deep trap states are found to be present throughout the entire GaN epilayer. It is also noticed that the deep trap states lying at the GaN/Fe-GaN interface make a strong contribution to the YL feature. A phenomenological model is proposed to explain the intensity dependence of the YL feature and the corresponding SPS features in a pump-probe configuration, where a reasonable agreement between the numerical simulations and experimental results is achieved.

Simultaneous determination of indoor ammonia pollution and its biological metabolite in the human body with a recyclable nanocrystalline lanthanide-functionalized MOF.

PubMed

Hao, Ji-Na; Yan, Bing

2016-02-07

A Eu(3+) post-functionalized metal-organic framework of nanosized Ga(OH)bpydc(Eu(3+)@Ga(OH)bpydc, 1a) with intense luminescence is synthesized and characterized. Luminescence measurements reveal that 1a can detect ammonia gas selectively and sensitively among various indoor air pollutants. 1a can simultaneously determine a biological ammonia metabolite (urinary urea) in the human body, which is a rare example of a luminescent sensor that can monitor pollutants in the environment and also detect their biological markers. Furthermore, 1a exhibits appealing features including high selectivity and sensitivity, fast response, simple and quick regeneration, and excellent recyclability.

Emission Characteristics of InGaN/GaN Core-Shell Nanorods Embedded in a 3D Light-Emitting Diode.

PubMed

Jung, Byung Oh; Bae, Si-Young; Lee, Seunga; Kim, Sang Yun; Lee, Jeong Yong; Honda, Yoshio; Amano, Hiroshi

2016-12-01

We report the selective-area growth of a gallium nitride (GaN)-nanorod-based InGaN/GaN multiple-quantum-well (MQW) core-shell structure embedded in a three-dimensional (3D) light-emitting diode (LED) grown by metalorganic chemical vapor deposition (MOCVD) and its optical analysis. High-resolution transmission electron microscopy (HR-TEM) observation revealed the high quality of the GaN nanorods and the position dependence of the structural properties of the InGaN/GaN MQWs on multiple facets. The excitation and temperature dependences of photoluminescence (PL) revealed the m-plane emission behaviors of the InGaN/GaN core-shell nanorods. The electroluminescence (EL) of the InGaN/GaN core-shell-nanorod-embedded 3D LED changed color from green to blue with increasing injection current. This phenomenon was mainly due to the energy gradient and deep localization of the indium in the selectively grown InGaN/GaN core-shell MQWs on the 3D architecture.

EOL performance comparison of GaAs/Ge and Si BSF/R solar arrays

NASA Technical Reports Server (NTRS)

Woike, Thomas J.

1993-01-01

EOL power estimates for solar array designs are significantly influenced by the predicted degradation due to charged particle radiation. New radiation-induced power degradation data for GaAs/Ge solar arrays applicable to missions ranging from low earth orbit (LEO) to geosynchronous earth orbit (GEO) and compares these results to silicon BSF/R arrays. These results are based on recently published radiation damage coefficients for GaAs/Ge cells. The power density ratio (GaAs/Ge to Si BSF/R) was found to be as high as 1.83 for the proton-dominated worst-case altitude of 7408 km medium Earth orbit (MEO). Based on the EOL GaAs/Ge solar array power density results for MEO, missions which were previously considered infeasible may be reviewed based on these more favorable results. The additional life afforded by using GaAs/Ge cells is an important factor in system-level trade studies when selecting a solar cell technology for a mission and needs to be considered. The data presented supports this decision since the selected orbits have characteristics similar to most orbits of interest.

Photoluminescence spectroscopy and the effective mass theory of strained (In,Ga)As/GaAs heterostructures grown on (112)B GaAs substrates

NASA Technical Reports Server (NTRS)

Henderson, R. H.; Sun, D.; Towe, E.

1995-01-01

The photoluminescence characteristics of pseudomorphic In(0.19)Ga(0.81)As/GaAs quantum well structures grown on both the conventional (001) and the unconventional (112)B GaAs substrate are investigated. It is found that the emission spectra of the structures grown on the (112)B surface exhibit some spectral characteristics not observed on similar structures grown on the (001) surface. A spectral blue shift of the e yields hh1 transition with increasing optical pump intensity is observed for the quantum wells on the (112) surface. This shift is interpreted to be evidence of a strain-induced piezoelectric field. A second spectral feature located within the band gap of the In(0.19)Ga(0.81)As layer is also observed for the (112) structure; this feature is thought to be an impurity-related emission. The expected transition energies of the quantum well structures are calculated using the effective mass theory based on the 4 x 4 Luttinger valence band Hamiltonian, and related strain Hamiltonian.

Combinatorial Multiobjective Optimization Using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Crossley, William A.; Martin. Eric T.

2002-01-01

The research proposed in this document investigated multiobjective optimization approaches based upon the Genetic Algorithm (GA). Several versions of the GA have been adopted for multiobjective design, but, prior to this research, there had not been significant comparisons of the most popular strategies. The research effort first generalized the two-branch tournament genetic algorithm in to an N-branch genetic algorithm, then the N-branch GA was compared with a version of the popular Multi-Objective Genetic Algorithm (MOGA). Because the genetic algorithm is well suited to combinatorial (mixed discrete / continuous) optimization problems, the GA can be used in the conceptual phase of design to combine selection (discrete variable) and sizing (continuous variable) tasks. Using a multiobjective formulation for the design of a 50-passenger aircraft to meet the competing objectives of minimizing takeoff gross weight and minimizing trip time, the GA generated a range of tradeoff designs that illustrate which aircraft features change from a low-weight, slow trip-time aircraft design to a heavy-weight, short trip-time aircraft design. Given the objective formulation and analysis methods used, the results of this study identify where turboprop-powered aircraft and turbofan-powered aircraft become more desirable for the 50 seat passenger application. This aircraft design application also begins to suggest how a combinatorial multiobjective optimization technique could be used to assist in the design of morphing aircraft.

A Wavelet-Based Methodology for Grinding Wheel Condition Monitoring

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

Liao, T. W.; Ting, C.F.; Qu, Jun

2007-01-01

Grinding wheel surface condition changes as more material is removed. This paper presents a wavelet-based methodology for grinding wheel condition monitoring based on acoustic emission (AE) signals. Grinding experiments in creep feed mode were conducted to grind alumina specimens with a resinoid-bonded diamond wheel using two different conditions. During the experiments, AE signals were collected when the wheel was 'sharp' and when the wheel was 'dull'. Discriminant features were then extracted from each raw AE signal segment using the discrete wavelet decomposition procedure. An adaptive genetic clustering algorithm was finally applied to the extracted features in order to distinguish differentmore » states of grinding wheel condition. The test results indicate that the proposed methodology can achieve 97% clustering accuracy for the high material removal rate condition, 86.7% for the low material removal rate condition, and 76.7% for the combined grinding conditions if the base wavelet, the decomposition level, and the GA parameters are properly selected.« less

A surface-potential-based drain current compact model for a-InGaZnO thin-film transistors in Non-Degenerate conduction regime

NASA Astrophysics Data System (ADS)

Yu, Fei; Ma, Xiaoyu; Deng, Wanling; Liou, Juin J.; Huang, Junkai

2017-11-01

A physics-based drain current compact model for amorphous InGaZnO (a-InGaZnO) thin-film transistors (TFTs) is proposed. As a key feature, the surface potential model accounts for both exponential tail and deep trap densities of states, which are essential to describe a-InGaZnO TFT electrical characteristics. The surface potential is solved explicitly without the process of amendment and suitable for circuit simulations. Furthermore, based on the surface potential, an explicit closed-form expression of the drain current is developed. For the cases of the different operational voltages, surface potential and drain current are verified by numerical results and experimental data, respectively. As a result, our model can predict DC characteristics of a-InGaZnO TFTs.

Automatic Detection of Galaxy Type From Datasets of Galaxies Image Based on Image Retrieval Approach.

PubMed

Abd El Aziz, Mohamed; Selim, I M; Xiong, Shengwu

2017-06-30

This paper presents a new approach for the automatic detection of galaxy morphology from datasets based on an image-retrieval approach. Currently, there are several classification methods proposed to detect galaxy types within an image. However, in some situations, the aim is not only to determine the type of galaxy within the queried image, but also to determine the most similar images for query image. Therefore, this paper proposes an image-retrieval method to detect the type of galaxies within an image and return with the most similar image. The proposed method consists of two stages, in the first stage, a set of features is extracted based on shape, color and texture descriptors, then a binary sine cosine algorithm selects the most relevant features. In the second stage, the similarity between the features of the queried galaxy image and the features of other galaxy images is computed. Our experiments were performed using the EFIGI catalogue, which contains about 5000 galaxies images with different types (edge-on spiral, spiral, elliptical and irregular). We demonstrate that our proposed approach has better performance compared with the particle swarm optimization (PSO) and genetic algorithm (GA) methods.

Fabrication of a terahertz quantum-cascade laser with a double metal waveguide based on multilayer GaAs/AlGaAs heterostructures

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

Khabibullin, R. A., E-mail: khabibullin@isvch.ru; Shchavruk, N. V.; Pavlov, A. Yu.

2016-10-15

The Postgrowth processing of GaAs/AlGaAs multilayer heterostructures for terahertz quantumcascade lasers (QCLs) are studied. This procedure includes the thermocompression bonding of In–Au multilayer heterostructures with a doped n{sup +}-GaAs substrate, mechanical grinding, and selective wet etching of the substrate, and dry etching of QCL ridge mesastripes through a Ti/Au metallization mask 50 and 100 μm wide. Reactive-ion-etching modes with an inductively coupled plasma source in a BCl{sub 3}/Ar gas mixture are selected to obtain vertical walls of the QCL ridge mesastripes with minimum Ti/Au mask sputtering.

A Darwinian approach to control-structure design

NASA Technical Reports Server (NTRS)

Zimmerman, David C.

1993-01-01

Genetic algorithms (GA's), as introduced by Holland (1975), are one form of directed random search. The form of direction is based on Darwin's 'survival of the fittest' theories. GA's are radically different from the more traditional design optimization techniques. GA's work with a coding of the design variables, as opposed to working with the design variables directly. The search is conducted from a population of designs (i.e., from a large number of points in the design space), unlike the traditional algorithms which search from a single design point. The GA requires only objective function information, as opposed to gradient or other auxiliary information. Finally, the GA is based on probabilistic transition rules, as opposed to deterministic rules. These features allow the GA to attack problems with local-global minima, discontinuous design spaces and mixed variable problems, all in a single, consistent framework.

Hybrid genetic algorithm-neural network: feature extraction for unpreprocessed microarray data.

PubMed

Tong, Dong Ling; Schierz, Amanda C

2011-09-01

Suitable techniques for microarray analysis have been widely researched, particularly for the study of marker genes expressed to a specific type of cancer. Most of the machine learning methods that have been applied to significant gene selection focus on the classification ability rather than the selection ability of the method. These methods also require the microarray data to be preprocessed before analysis takes place. The objective of this study is to develop a hybrid genetic algorithm-neural network (GANN) model that emphasises feature selection and can operate on unpreprocessed microarray data. The GANN is a hybrid model where the fitness value of the genetic algorithm (GA) is based upon the number of samples correctly labelled by a standard feedforward artificial neural network (ANN). The model is evaluated by using two benchmark microarray datasets with different array platforms and differing number of classes (a 2-class oligonucleotide microarray data for acute leukaemia and a 4-class complementary DNA (cDNA) microarray dataset for SRBCTs (small round blue cell tumours)). The underlying concept of the GANN algorithm is to select highly informative genes by co-evolving both the GA fitness function and the ANN weights at the same time. The novel GANN selected approximately 50% of the same genes as the original studies. This may indicate that these common genes are more biologically significant than other genes in the datasets. The remaining 50% of the significant genes identified were used to build predictive models and for both datasets, the models based on the set of genes extracted by the GANN method produced more accurate results. The results also suggest that the GANN method not only can detect genes that are exclusively associated with a single cancer type but can also explore the genes that are differentially expressed in multiple cancer types. The results show that the GANN model has successfully extracted statistically significant genes from the unpreprocessed microarray data as well as extracting known biologically significant genes. We also show that assessing the biological significance of genes based on classification accuracy may be misleading and though the GANN's set of extra genes prove to be more statistically significant than those selected by other methods, a biological assessment of these genes is highly recommended to confirm their functionality. Copyright © 2011 Elsevier B.V. All rights reserved.

Dislocation gliding and cross-hatch morphology formation in AIII-BV epitaxial heterostructures

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

Kovalskiy, V. A., E-mail: kovalva@iptm.ru; Vergeles, P. S.; Eremenko, V. G.

2014-12-08

An approach for understanding the origin of cross-hatch pattern (CHP) on the surface of lattice mismatched GaMnAs/InGaAs samples grown on GaAs (001) substrates is developed. It is argued that the motion of threading dislocations in the (111) slip planes during the relaxation of InGaAs buffer layer is more complicated process and its features are similar to the ones of dislocation half-loops gliding in plastically deformed crystals. The heterostructures were characterized by atomic force microscopy and electron beam induced current (EBIC). Detailed EBIC experiments revealed contrast features, which cannot be accounted for by the electrical activity of misfit dislocations at themore » buffer/substrate interface. We attribute these features to specific extended defects (EDs) generated by moving threading dislocations in the partially relaxed InGaAs layers. We believe that the core topology, surface reconstruction, and elastic strains from these EDs accommodated in slip planes play an important role in the CHP formation. The study of such electrically active EDs will allow further understanding of degradation and changes in characteristics of quantum devices based on strained heterostructures.« less

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

Arutyunyan, S. S., E-mail: spartakmain@gmail.com; Pavlov, A. Yu.; Pavlov, B. Yu.

The fabrication of a two-layer Si{sub 3}N{sub 4}/SiO{sub 2} dielectric mask and features of its application in the technology of non-fired epitaxially grown ohmic contacts for high-power HEMTs on AlGaN/GaN heterostructures are described. The proposed Si{sub 3}N{sub 4}/SiO{sub 2} mask allows the selective epitaxial growth of heavily doped ohmic contacts by nitride molecular-beam epitaxy and the fabrication of non-fired ohmic contacts with a resistance of 0.15–0.2 Ω mm and a smooth surface and edge morphology.

Electroencephalogram Signal Classification for Automated Epileptic Seizure Detection Using Genetic Algorithm

PubMed Central

Nanthini, B. Suguna; Santhi, B.

2017-01-01

Background: Epilepsy causes when the repeated seizure occurs in the brain. Electroencephalogram (EEG) test provides valuable information about the brain functions and can be useful to detect brain disorder, especially for epilepsy. In this study, application for an automated seizure detection model has been introduced successfully. Materials and Methods: The EEG signals are decomposed into sub-bands by discrete wavelet transform using db2 (daubechies) wavelet. The eight statistical features, the four gray level co-occurrence matrix and Renyi entropy estimation with four different degrees of order, are extracted from the raw EEG and its sub-bands. Genetic algorithm (GA) is used to select eight relevant features from the 16 dimension features. The model has been trained and tested using support vector machine (SVM) classifier successfully for EEG signals. The performance of the SVM classifier is evaluated for two different databases. Results: The study has been experimented through two different analyses and achieved satisfactory performance for automated seizure detection using relevant features as the input to the SVM classifier. Conclusion: Relevant features using GA give better accuracy performance for seizure detection. PMID:28781480

Development of Coatings for Radar Absorbing Materials at X-band

NASA Astrophysics Data System (ADS)

Kumar, Abhishek; Singh, Samarjit

2018-03-01

The present review gives a brief account on some of the technical features of radar absorbing materials (RAMs). The paper has been presented with a concentrated approach towards the material aspects for achieving enhanced radar absorption characteristics for its application as a promising candidate in stealth technology and electromagnetic interference (EMI) minimization problems. The effect of metal particles doping/dispersion in the ferrites and dielectrics has been discussed for obtaining tunable radar absorbing characteristics. A short theoretical overview on the development of absorber materials, implementation of genetic algorithm (GA) in multi-layering and frequency selective surfaces (FSSs) based multi-layer has also been presented for the development of radar absorbing coatings for achieving better absorption augmented with broadband features in order to counter the radar detection systems.

Patients classification on weaning trials using neural networks and wavelet transform.

PubMed

Arizmendi, Carlos; Viviescas, Juan; González, Hernando; Giraldo, Beatriz

2014-01-01

The determination of the optimal time of the patients in weaning trial process from mechanical ventilation, between patients capable of maintaining spontaneous breathing and patients that fail to maintain spontaneous breathing, is a very important task in intensive care unit. Wavelet Transform (WT) and Neural Networks (NN) techniques were applied in order to develop a classifier for the study of patients on weaning trial process. The respiratory pattern of each patient was characterized through different time series. Genetic Algorithms (GA) and Forward Selection were used as feature selection techniques. A classification performance of 77.00±0.06% of well classified patients, was obtained using a NN and GA combination, with only 6 variables of the 14 initials.

Growth of AlGaN under the conditions of significant gallium evaporation: Phase separation and enhanced lateral growth

NASA Astrophysics Data System (ADS)

Mayboroda, I. O.; Knizhnik, A. A.; Grishchenko, Yu. V.; Ezubchenko, I. S.; Zanaveskin, Maxim L.; Kondratev, O. A.; Presniakov, M. Yu.; Potapkin, B. V.; Ilyin, V. A.

2017-09-01

The growth kinetics of AlGaN in NH3 MBE under significant Ga desorption was studied. It was found that the addition of gallium stimulates 2D growth and provides better morphology of films compared to pure AlN. The effect was experimentally observed at up to 98% desorption of the impinging gallium. We found that under the conditions of significant thermal desorption, larger amounts of gallium were retained at lateral boundaries of 3D surface features than at flat terraces because of the higher binding energy of Ga atoms at specific surface defects. The selective accumulation of gallium resulted in an increase in the lateral growth component through the formation of the Ga-enriched AlGaN phase at boundaries of 3D surface features. We studied the temperature dependence of AlGaN growth rate and developed a kinetic model analytically describing this dependence. As the model was in good agreement with the experimental data, we used it to estimate the increase in the binding energy of Ga atoms at surface defects compared to terrace surface sites using data on the Ga content in different AlGaN phases. We also applied first-principles calculations to the thermodynamic analysis of stable configurations on the AlN surface and then used these surface configurations to compare the binding energy of Ga atoms at terraces and steps. Both first-principles calculations and analytical estimations of the experimental results gave similar values of difference in binding energies; this value is 0.3 eV. Finally, it was studied experimentally whether gallium can act as a surfactant in AlN growth by NH3 MBE at elevated temperatures. Gallium application has allowed us to grow a 300 nm thick AlN film with a RMS surface roughness of 2.2 Å over an area of 10 × 10 μm and a reduced density of screw dislocations.

MOVPE growth of violet GaN LEDs on β-Ga2O3 substrates

NASA Astrophysics Data System (ADS)

Li, Ding; Hoffmann, Veit; Richter, Eberhard; Tessaro, Thomas; Galazka, Zbigniew; Weyers, Markus; Tränkle, Günther

2017-11-01

We report that a H2-free atmosphere is essential for the initial stage of metalorganic vapour phase epitaxy (MOVPE) growth of GaN on β-Ga2O3 to prevent the surface from damage. A simple growth method is proposed that can easily transfer established GaN growth recipes from sapphire to β-Ga2O3 with both (-2 0 1) and (1 0 0) orientations. This method features a thin AlN nucleation layer grown below 900 °C in N2 atmosphere to protect the surface of β-Ga2O3 from deterioration during further growth under the H2 atmosphere. Based on this, we demonstrate working violet vertical light emitting diodes (VLEDs) on n-conductive β-Ga2O3 substrates.

In-plane InSb nanowires grown by selective area molecular beam epitaxy on semi-insulating substrate.

PubMed

Desplanque, L; Bucamp, A; Troadec, D; Patriarche, G; Wallart, X

2018-07-27

In-plane InSb nanostructures are grown on a semi-insulating GaAs substrate using an AlGaSb buffer layer covered with a patterned SiO 2 mask and selective area molecular beam epitaxy. The shape of these nanostructures is defined by the aperture in the silicon dioxide layer used as a selective mask thanks to the use of an atomic hydrogen flux during the growth. Transmission electron microscopy reveals that the mismatch accommodation between InSb and GaAs is obtained in two steps via the formation of an array of misfit dislocations both at the AlGaSb buffer layer/GaAs and at the InSb nanostructures/AlGaSb interfaces. Several micron long in-plane nanowires (NWs) can be achieved as well as more complex nanostructures such as branched NWs. The electrical properties of the material are investigated by the characterization of an InSb NW MOSFET down to 77 K. The resulting room temperature field effect mobility values are comparable with those reported on back-gated MOSFETs based on InSb NWs obtained by vapor liquid solid growth or electrodeposition. This growth method paves the way to the fabrication of complex InSb-based nanostructures.

Genetic algorithms applied to the scheduling of the Hubble Space Telescope

NASA Technical Reports Server (NTRS)

Sponsler, Jeffrey L.

1989-01-01

A prototype system employing a genetic algorithm (GA) has been developed to support the scheduling of the Hubble Space Telescope. A non-standard knowledge structure is used and appropriate genetic operators have been created. Several different crossover styles (random point selection, evolving points, and smart point selection) are tested and the best GA is compared with a neural network (NN) based optimizer. The smart crossover operator produces the best results and the GA system is able to evolve complete schedules using it. The GA is not as time-efficient as the NN system and the NN solutions tend to be better.

Study on high breakdown voltage GaN-based vertical field effect transistor with interfacial charge engineering for power applications

NASA Astrophysics Data System (ADS)

Du, Jiangfeng; Liu, Dong; Liu, Yong; Bai, Zhiyuan; Jiang, Zhiguang; Liu, Yang; Yu, Qi

2017-11-01

A high voltage GaN-based vertical field effect transistor with interfacial charge engineering (GaN ICE-VFET) is proposed and its breakdown mechanism is presented. This vertical FET features oxide trenches which show a fixed negative charge at the oxide/GaN interface. In the off-state, firstly, the trench oxide layer acts as a field plate; secondly, the n-GaN buffer layer is inverted along the oxide/GaN interface and thus a vertical hole layer is formed, which acts as a virtual p-pillar and laterally depletes the n-buffer pillar. Both of them modulate electric field distribution in the device and significantly increase the breakdown voltage (BV). Compared with a conventional GaN vertical FET, the BV of GaN ICE-VFET is increased from 1148 V to 4153 V with the same buffer thickness of 20 μm. Furthermore, the proposed device achieves a great improvement in the tradeoff between BV and on-resistance; and its figure of merit even exceeds the GaN one-dimensional limit.

Ni2+-binding RNA motifs with an asymmetric purine-rich internal loop and a G-A base pair.

PubMed Central

Hofmann, H P; Limmer, S; Hornung, V; Sprinzl, M

1997-01-01

RNA molecules with high affinity for immobilized Ni2+ were isolated from an RNA pool with 50 randomized positions by in vitro selection-amplification. The selected RNAs preferentially bind Ni2+ and Co2+ over other cations from first series transition metals. Conserved structure motifs, comprising about 15 nt, were identified that are likely to represent the Ni2+ binding sites. Two conserved motifs contain an asymmetric purine-rich internal loop and probably a mismatch G-A base pair. The structure of one of these motifs was studied with proton NMR spectroscopy and formation of the G-A pair at the junction of helix and internal loop was demonstrated. Using Ni2+ as a paramagnetic probe, a divalent metal ion binding site near this G-A base pair was identified. Ni2+ ions bound to this motif exert a specific stabilization effect. We propose that small asymmetric purine-rich loops that contain a G-A interaction may represent a divalent metal ion binding site in RNA. PMID:9409620

Human emotion detector based on genetic algorithm using lip features

NASA Astrophysics Data System (ADS)

Brown, Terrence; Fetanat, Gholamreza; Homaifar, Abdollah; Tsou, Brian; Mendoza-Schrock, Olga

2010-04-01

We predicted human emotion using a Genetic Algorithm (GA) based lip feature extractor from facial images to classify all seven universal emotions of fear, happiness, dislike, surprise, anger, sadness and neutrality. First, we isolated the mouth from the input images using special methods, such as Region of Interest (ROI) acquisition, grayscaling, histogram equalization, filtering, and edge detection. Next, the GA determined the optimal or near optimal ellipse parameters that circumvent and separate the mouth into upper and lower lips. The two ellipses then went through fitness calculation and were followed by training using a database of Japanese women's faces expressing all seven emotions. Finally, our proposed algorithm was tested using a published database consisting of emotions from several persons. The final results were then presented in confusion matrices. Our results showed an accuracy that varies from 20% to 60% for each of the seven emotions. The errors were mainly due to inaccuracies in the classification, and also due to the different expressions in the given emotion database. Detailed analysis of these errors pointed to the limitation of detecting emotion based on the lip features alone. Similar work [1] has been done in the literature for emotion detection in only one person, we have successfully extended our GA based solution to include several subjects.

GaAs/AlGaAs core multishell nanowire-based light-emitting diodes on Si.

PubMed

Tomioka, Katsuhiro; Motohisa, Junichi; Hara, Shinjiroh; Hiruma, Kenji; Fukui, Takashi

2010-05-12

We report on integration of GaAs nanowire-based light-emitting-diodes (NW-LEDs) on Si substrate by selective-area metalorganic vapor phase epitaxy. The vertically aligned GaAs/AlGaAs core-multishell nanowires with radial p-n junction and NW-LED array were directly fabricated on Si. The threshold current for electroluminescence (EL) was 0.5 mA (current density was approximately 0.4 A/cm(2)), and the EL intensity superlinearly increased with increasing current injections indicating superluminescence behavior. The technology described in this letter could help open new possibilities for monolithic- and on-chip integration of III-V NWs on Si.

Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

PubMed Central

Boonjing, Veera; Intakosum, Sarun

2016-01-01

This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid's prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span. PMID:27974883

Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend.

PubMed

Inthachot, Montri; Boonjing, Veera; Intakosum, Sarun

2016-01-01

This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid's prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span.

Scanning tunneling microscopy studies of Si donors (Si[sub Ga]) in GaAs

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

Zheng, J.F.; Liu, X.; Newman, N.

1994-03-07

We report scanning tunneling microscopy (STM) studies of Si substitutional donors (Si[sub Ga]) in GaAs that reveal delocalized and localized electronic features corresponding to Si[sub Ga] in the top few layers of the (110) cleavage surface. The delocalized features appear as protrusions a few nm in size, superimposed on the background lattice. These features are attributed to enhanced tunneling due to the local perturbation of the band bending by the Coulomb potential of subsurface Si[sub Ga]. In contrast, STM images of surface Si[sub Ga] show very localized electronic structures, in good agreement with a recent theoretical prediction [J. Wang [italmore » et] [ital al]., Phys. Rev. B 47, 10 329 (1993)].« less

Nanoheteroepitaxy of gallium arsenide on strain-compliant silicon-germanium nanowires

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

Chin, Hock-Chun; Gong, Xiao; Yeo, Yee-Chia

Heterogeneous integration of high-quality GaAs on Si-based substrates using a selective migration-enhanced epitaxy (MEE) of GaAs on strain-compliant SiGe nanowires was demonstrated for the first time. The physics of compliance in nanoscale heterostructures was captured and studied using finite-element simulation. It is shown that nanostructures can provide additional substrate compliance for strain relief and therefore contribute to the formation of defect-free GaAs on SiGe. Extensive characterization using scanning electron microscopy and cross-sectional transmission electron microscopy was performed to illustrate the successful growth of GaAs on SiGe nanowire. Raman and Auger electron spectroscopy measurements further confirmed the quality of the GaAsmore » grown and the high growth selectivity of the MEE process.« less

Atomic structure of the GaAs(001)-c(4x4) surface: first-principles evidence for diversity of heterodimer motifs.

PubMed

Penev, E; Kratzer, P; Scheffler, M

2004-10-01

The GaAs(001)-c(4x4) surface was studied using ab initio atomistic thermodynamics based on density-functional theory calculations. We demonstrate that in a range of stoichiometries, between those of the conventional three As-dimer and the new three Ga-As-dimer models, there exists a diversity of atomic structures featuring Ga-As heterodimers. These results fully explain the experimental scanning tunneling microscopy images and are likely to be relevant also to the c(4x4)-reconstructed (001) surfaces of other III-V semiconductors.

Polarity Control of Heteroepitaxial GaN Nanowires on Diamond.

PubMed

Hetzl, Martin; Kraut, Max; Hoffmann, Theresa; Stutzmann, Martin

2017-06-14

Group III-nitride materials such as GaN nanowires are characterized by a spontaneous polarization within the crystal. The sign of the resulting sheet charge at the top and bottom facet of a GaN nanowire is determined by the orientation of the wurtzite bilayer of the different atomic species, called N and Ga polarity. We investigate the polarity distribution of heteroepitaxial GaN nanowires on different substrates and demonstrate polarity control of GaN nanowires on diamond. Kelvin Probe Force Microscopy is used to determine the polarity of individual selective area-grown and self-assembled nanowires over a large scale. At standard growth conditions, mixed polarity occurs for selective GaN nanowires on various substrates, namely on silicon, on sapphire and on diamond. To obtain control over the growth orientation on diamond, the substrate surface is modified by nitrogen and oxygen plasma exposure prior to growth, and the growth parameters are adjusted simultaneously. We find that the surface chemistry and the substrate temperature are the decisive factors for obtaining control of up to 93% for both polarity types, whereas the growth mode, namely selective area or self-assembled growth, does not influence the polarity distribution significantly. The experimental results are discussed by a model based on the interfacial bonds between the GaN nanowires, the termination layer, and the substrate.

Methanol, ethanol and hydrogen sensing using metal oxide and metal (TiO(2)-Pt) composite nanoclusters on GaN nanowires: a new route towards tailoring the selectivity of nanowire/nanocluster chemical sensors.

PubMed

Aluri, Geetha S; Motayed, Abhishek; Davydov, Albert V; Oleshko, Vladimir P; Bertness, Kris A; Sanford, Norman A; Mulpuri, Rao V

2012-05-04

We demonstrate a new method for tailoring the selectivity of chemical sensors using semiconductor nanowires (NWs) decorated with metal and metal oxide multicomponent nanoclusters (NCs). Here we present the change of selectivity of titanium dioxide (TiO(2)) nanocluster-coated gallium nitride (GaN) nanowire sensor devices on the addition of platinum (Pt) nanoclusters. The hybrid sensor devices were developed by fabricating two-terminal devices using individual GaN NWs followed by the deposition of TiO(2) and/or Pt nanoclusters (NCs) using the sputtering technique. This paper present the sensing characteristics of GaN/(TiO(2)-Pt) nanowire-nanocluster (NWNC) hybrids and GaN/(Pt) NWNC hybrids, and compare their selectivity with that of the previously reported GaN/TiO(2) sensors. The GaN/TiO(2) NWNC hybrids showed remarkable selectivity to benzene and related aromatic compounds, with no measurable response for other analytes. Addition of Pt NCs to GaN/TiO(2) sensors dramatically altered their sensing behavior, making them sensitive only to methanol, ethanol and hydrogen, but not to any other chemicals we tested. The GaN/(TiO(2)-Pt) hybrids were able to detect ethanol and methanol concentrations as low as 100 nmol mol(-1) (ppb) in air in approximately 100 s, and hydrogen concentrations from 1 µmol mol(-1) (ppm) to 1% in nitrogen in less than 60 s. However, GaN/Pt NWNC hybrids showed limited sensitivity only towards hydrogen and not towards any alcohols. All these hybrid sensors worked at room temperature and are photomodulated, i.e. they responded to analytes only in the presence of ultraviolet (UV) light. We propose a qualitative explanation based on the heat of adsorption, ionization energy and solvent polarity to explain the observed selectivity of the different hybrids. These results are significant from the standpoint of applications requiring room-temperature hydrogen sensing and sensitive alcohol monitoring. These results demonstrate the tremendous potential for tailoring the selectivity of the hybrid nanosensors for a multitude of environmental and industrial sensing applications.

A study of GaN-based LED structure etching using inductively coupled plasma

NASA Astrophysics Data System (ADS)

Wang, Pei; Cao, Bin; Gan, Zhiyin; Liu, Sheng

2011-02-01

GaN as a wide band gap semiconductor has been employed to fabricate optoelectronic devices such as light-emitting diodes (LEDs) and laser diodes (LDs). Recently several different dry etching techniques for GaN-based materials have been developed. ICP etching is attractive because of its superior plasma uniformity and strong controllability. Most previous reports emphasized on the ICP etching characteristics of single GaN film. In this study dry etching of GaN-based LED structure was performed by inductively coupled plasmas (ICP) etching with Cl2 as the base gas and BCl3 as the additive gas. The effects of the key process parameters such as etching gases flow rate, ICP power, RF power and chamber pressure on the etching properties of GaN-based LED structure including etching rate, selectivity, etched surface morphology and sidewall was investigated. Etch depths were measured using a depth profilometer and used to calculate the etch rates. The etch profiles were observed with a scanning electron microscope (SEM).

Alkali-templated surface nanopatterning of chalcogenide thin films: a novel approach toward solar cells with enhanced efficiency.

PubMed

Reinhard, Patrick; Bissig, Benjamin; Pianezzi, Fabian; Hagendorfer, Harald; Sozzi, Giovanna; Menozzi, Roberto; Gretener, Christina; Nishiwaki, Shiro; Buecheler, Stephan; Tiwari, Ayodhya N

2015-05-13

Concepts of localized contacts and junctions through surface passivation layers are already advantageously applied in Si wafer-based photovoltaic technologies. For Cu(In,Ga)Se2 thin film solar cells, such concepts are generally not applied, especially at the heterojunction, because of the lack of a simple method yielding features with the required size and distribution. Here, we show a novel, innovative surface nanopatterning approach to form homogeneously distributed nanostructures (<30 nm) on the faceted, rough surface of polycrystalline chalcogenide thin films. The method, based on selective dissolution of self-assembled and well-defined alkali condensates in water, opens up new research opportunities toward development of thin film solar cells with enhanced efficiency.

Metallurgical characterization of experimental Ag-based soldering alloys.

PubMed

Ntasi, Argyro; Al Jabbari, Youssef S; Silikas, Nick; Al Taweel, Sara M; Zinelis, Spiros

2014-10-01

To characterize microstructure, hardness and thermal properties of experimental Ag-based soldering alloys for dental applications. Ag12Ga (AgGa) and Ag10Ga5Sn (AgGaSn) were fabricated by induction melting. Six samples were prepared for each alloy and microstructure, hardness and their melting range were determined by, scanning electron microscopy, energy dispersive X-ray (EDX) microanalysis, X-ray diffraction (XRD), Vickers hardness testing and differential scanning calorimetry (DSC). Both alloys demonstrated a gross dendritic microstructure while according to XRD results both materials consisted predominately of a Ag-rich face centered cubic phase The hardness of AgGa (61 ± 2) was statistically lower than that of AgGaSn (84 ± 2) while the alloys tested showed similar melting range of 627-762 °C for AgGa and 631-756 °C for AgGaSn. The experimental alloys tested demonstrated similar microstructures and melting ranges. Ga and Sn might be used as alternative to Cu and Zn to modify the selected properties of Ag based soldering alloys.

Metallurgical characterization of experimental Ag-based soldering alloys

PubMed Central

Ntasi, Argyro; Al Jabbari, Youssef S.; Silikas, Nick; Al Taweel, Sara M.; Zinelis, Spiros

2014-01-01

Aim To characterize microstructure, hardness and thermal properties of experimental Ag-based soldering alloys for dental applications. Materials and methods Ag12Ga (AgGa) and Ag10Ga5Sn (AgGaSn) were fabricated by induction melting. Six samples were prepared for each alloy and microstructure, hardness and their melting range were determined by, scanning electron microscopy, energy dispersive X-ray (EDX) microanalysis, X-ray diffraction (XRD), Vickers hardness testing and differential scanning calorimetry (DSC). Results Both alloys demonstrated a gross dendritic microstructure while according to XRD results both materials consisted predominately of a Ag-rich face centered cubic phase The hardness of AgGa (61 ± 2) was statistically lower than that of AgGaSn (84 ± 2) while the alloys tested showed similar melting range of 627–762 °C for AgGa and 631–756 °C for AgGaSn. Conclusion The experimental alloys tested demonstrated similar microstructures and melting ranges. Ga and Sn might be used as alternative to Cu and Zn to modify the selected properties of Ag based soldering alloys. PMID:25382945

Selectively Enhanced UV-A Photoresponsivity of a GaN MSM UV Photodetector with a Step-Graded AlxGa1-xN Buffer Layer.

PubMed

Lee, Chang-Ju; Won, Chul-Ho; Lee, Jung-Hee; Hahm, Sung-Ho; Park, Hongsik

2017-07-21

The UV-to-visible rejection ratio is one of the important figure of merits of GaN-based UV photodetectors. For cost-effectiveness and large-scale fabrication of GaN devices, we tried to grow a GaN epitaxial layer on silicon substrate with complicated buffer layers for a stress-release. It is known that the structure of the buffer layers affects the performance of devices fabricated on the GaN epitaxial layers. In this study, we show that the design of a buffer layer structure can make effect on the UV-to-visible rejection ratio of GaN UV photodetectors. The GaN photodetector fabricated on GaN-on-silicon substrate with a step-graded Al x Ga -x N buffer layer has a highly-selective photoresponse at 365-nm wavelength. The UV-to-visible rejection ratio of the GaN UV photodetector with the step-graded Al x Ga 1-x N buffer layer was an order-of-magnitude higher than that of a photodetector with a conventional GaN/AlN multi buffer layer. The maximum photoresponsivity was as high as 5 × 10 - ² A/W. This result implies that the design of buffer layer is important for photoresponse characteristics of GaN UV photodetectors as well as the crystal quality of the GaN epitaxial layers.

Development of a stacked ensemble model for forecasting and analyzing daily average PM2.5 concentrations in Beijing, China.

PubMed

Zhai, Binxu; Chen, Jianguo

2018-04-18

A stacked ensemble model is developed for forecasting and analyzing the daily average concentrations of fine particulate matter (PM 2.5 ) in Beijing, China. Special feature extraction procedures, including those of simplification, polynomial, transformation and combination, are conducted before modeling to identify potentially significant features based on an exploratory data analysis. Stability feature selection and tree-based feature selection methods are applied to select important variables and evaluate the degrees of feature importance. Single models including LASSO, Adaboost, XGBoost and multi-layer perceptron optimized by the genetic algorithm (GA-MLP) are established in the level 0 space and are then integrated by support vector regression (SVR) in the level 1 space via stacked generalization. A feature importance analysis reveals that nitrogen dioxide (NO 2 ) and carbon monoxide (CO) concentrations measured from the city of Zhangjiakou are taken as the most important elements of pollution factors for forecasting PM 2.5 concentrations. Local extreme wind speeds and maximal wind speeds are considered to extend the most effects of meteorological factors to the cross-regional transportation of contaminants. Pollutants found in the cities of Zhangjiakou and Chengde have a stronger impact on air quality in Beijing than other surrounding factors. Our model evaluation shows that the ensemble model generally performs better than a single nonlinear forecasting model when applied to new data with a coefficient of determination (R 2 ) of 0.90 and a root mean squared error (RMSE) of 23.69μg/m 3 . For single pollutant grade recognition, the proposed model performs better when applied to days characterized by good air quality than when applied to days registering high levels of pollution. The overall classification accuracy level is 73.93%, with most misclassifications made among adjacent categories. The results demonstrate the interpretability and generalizability of the stacked ensemble model. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Room Temperature Sensing Achieved by GaAs Nanowires and oCVD Polymer Coating.

PubMed

Wang, Xiaoxue; Ermez, Sema; Goktas, Hilal; Gradečak, Silvija; Gleason, Karen

2017-06-01

Novel structures comprised of GaAs nanowire arrays conformally coated with conducting polymers (poly(3,4-ethylenedioxythiophene) (PEDOT) or poly(3,4-ethylenedioxythiophene-co-3-thiophene acetic acid) display both sensitivity and selectivity to a variety of volatile organic chemicals. A key feature is room temperature operation, so that neither a heater nor the power it would consume, is required. It is a distinct difference from traditional metal oxide sensors, which typically require elevated operational temperature. The GaAs nanowires are prepared directly via self-seeded metal-organic chemical deposition, and conducting polymers are deposited on GaAs nanowires using oxidative chemical vapor deposition (oCVD). The range of thickness for the oCVD layer is between 100 and 200 nm, which is controlled by changing the deposition time. X-ray diffraction analysis indicates an edge-on alignment of the crystalline structure of the PEDOT coating layer on GaAs nanowires. In addition, the positive correlation between the improvement of sensitivity and the increasing nanowire density is demonstrated. Furthermore, the effect of different oCVD coating materials is studied. The sensing mechanism is also discussed with studies considering both nanowire density and polymer types. Overall, the novel structure exhibits good sensitivity and selectivity in gas sensing, and provides a promising platform for future sensor design. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Glycyrrhetinic Acid-Poly(ethylene glycol)-glycyrrhetinic Acid Tri-Block Conjugates Based Self-Assembled Micelles for Hepatic Targeted Delivery of Poorly Water Soluble Drug

PubMed Central

Xu, Ting; Liu, Chi; Chen, Can; Song, Xiangrong; Zheng, Yu

2013-01-01

The triblock 18β-glycyrrhetinic acid-poly(ethylene glycol)-18β-glycyrrhetinic acid conjugates (GA-PEG-GA) based self-assembled micelles were synthesized and characterized by FTIR, NMR, transmission electron microscopy, and particle size analysis. The GA-PEG-GA conjugates having the critical micelle concentration of 6 × 10−5 M were used to form nanosized micelles, with mean diameters of 159.21 ± 2.2 nm, and then paclitaxel (PTX) was incorporated into GA-PEG-GA micelles by self-assembly method. The physicochemical properties of the PTX loaded GA-PEG-GA micelles were evaluated including in vitro cellular uptake, cytotoxicity, drug release profile, and in vivo tissue distribution. The results demonstrate that the GA-PEG-GA micelles had low cytotoxicity and good ability of selectively delivering drug to hepatic cells in vitro and in vivo by the targeting moiety glycyrrhetinic acid. In conclusion, the GA-PEG-GA conjugates have potential medical applications for targeted delivery of poor soluble drug delivery. PMID:24376388

A global optimization approach to multi-polarity sentiment analysis.

PubMed

Li, Xinmiao; Li, Jing; Wu, Yukeng

2015-01-01

Following the rapid development of social media, sentiment analysis has become an important social media mining technique. The performance of automatic sentiment analysis primarily depends on feature selection and sentiment classification. While information gain (IG) and support vector machines (SVM) are two important techniques, few studies have optimized both approaches in sentiment analysis. The effectiveness of applying a global optimization approach to sentiment analysis remains unclear. We propose a global optimization-based sentiment analysis (PSOGO-Senti) approach to improve sentiment analysis with IG for feature selection and SVM as the learning engine. The PSOGO-Senti approach utilizes a particle swarm optimization algorithm to obtain a global optimal combination of feature dimensions and parameters in the SVM. We evaluate the PSOGO-Senti model on two datasets from different fields. The experimental results showed that the PSOGO-Senti model can improve binary and multi-polarity Chinese sentiment analysis. We compared the optimal feature subset selected by PSOGO-Senti with the features in the sentiment dictionary. The results of this comparison indicated that PSOGO-Senti can effectively remove redundant and noisy features and can select a domain-specific feature subset with a higher-explanatory power for a particular sentiment analysis task. The experimental results showed that the PSOGO-Senti approach is effective and robust for sentiment analysis tasks in different domains. By comparing the improvements of two-polarity, three-polarity and five-polarity sentiment analysis results, we found that the five-polarity sentiment analysis delivered the largest improvement. The improvement of the two-polarity sentiment analysis was the smallest. We conclude that the PSOGO-Senti achieves higher improvement for a more complicated sentiment analysis task. We also compared the results of PSOGO-Senti with those of the genetic algorithm (GA) and grid search method. From the results of this comparison, we found that PSOGO-Senti is more suitable for improving a difficult multi-polarity sentiment analysis problem.

InGaAs/GaAsSb Type-II superlattice based photodiodes for short wave infrared detection

NASA Astrophysics Data System (ADS)

Uliel, Y.; Cohen-Elias, D.; Sicron, N.; Grimberg, I.; Snapi, N.; Paltiel, Y.; Katz, M.

2017-08-01

Short Wave Infra-Red (SWIR) photodetectors operating above the response cutoff of InGaAs- based detectors (1.7-2.5 μm) are required for both defense and civil applications. Type II Super-Lattices (T2SL) were recently proposed For near- room temperature SWIR detection as a possible system enabling bandgap adjustment in the required range. The work presented here focuses on a T2SL with alternating nano-layers of InGaAs and GaAsSb lattice-matched to an InP substrate. A near room temperature SWIR cutoff of 2.4 μm was measured. Electrical junctions were realized using Zn diffusion p-doping process. We realized and studied both mesa- and selective diffusion- based p-i-n photodiodes. Dark currents of mesa-based devices were 1.5 mA/cm2 and 32 μA/cm2 at 300 and 230 K respectively. Dark currents were reduced to 1.2 mA/cm2 and 12 μA/cm2 respectively by utilizing the selective diffusion process. The effect of operating voltage is discussed. At 300 K the quantum efficiency was up to 40% at 2.18 μm in mesa devices. D∗ was 1.7 ×1010cm ·√{Hz } /W at 2 μm.

Using GA-Ridge regression to select hydro-geological parameters influencing groundwater pollution vulnerability.

PubMed

Ahn, Jae Joon; Kim, Young Min; Yoo, Keunje; Park, Joonhong; Oh, Kyong Joo

2012-11-01

For groundwater conservation and management, it is important to accurately assess groundwater pollution vulnerability. This study proposed an integrated model using ridge regression and a genetic algorithm (GA) to effectively select the major hydro-geological parameters influencing groundwater pollution vulnerability in an aquifer. The GA-Ridge regression method determined that depth to water, net recharge, topography, and the impact of vadose zone media were the hydro-geological parameters that influenced trichloroethene pollution vulnerability in a Korean aquifer. When using these selected hydro-geological parameters, the accuracy was improved for various statistical nonlinear and artificial intelligence (AI) techniques, such as multinomial logistic regression, decision trees, artificial neural networks, and case-based reasoning. These results provide a proof of concept that the GA-Ridge regression is effective at determining influential hydro-geological parameters for the pollution vulnerability of an aquifer, and in turn, improves the AI performance in assessing groundwater pollution vulnerability.

Genetics algorithm optimization of DWT-DCT based image Watermarking

NASA Astrophysics Data System (ADS)

Budiman, Gelar; Novamizanti, Ledya; Iwut, Iwan

2017-01-01

Data hiding in an image content is mandatory for setting the ownership of the image. Two dimensions discrete wavelet transform (DWT) and discrete cosine transform (DCT) are proposed as transform method in this paper. First, the host image in RGB color space is converted to selected color space. We also can select the layer where the watermark is embedded. Next, 2D-DWT transforms the selected layer obtaining 4 subband. We select only one subband. And then block-based 2D-DCT transforms the selected subband. Binary-based watermark is embedded on the AC coefficients of each block after zigzag movement and range based pixel selection. Delta parameter replacing pixels in each range represents embedded bit. +Delta represents bit “1” and -delta represents bit “0”. Several parameters to be optimized by Genetics Algorithm (GA) are selected color space, layer, selected subband of DWT decomposition, block size, embedding range, and delta. The result of simulation performs that GA is able to determine the exact parameters obtaining optimum imperceptibility and robustness, in any watermarked image condition, either it is not attacked or attacked. DWT process in DCT based image watermarking optimized by GA has improved the performance of image watermarking. By five attacks: JPEG 50%, resize 50%, histogram equalization, salt-pepper and additive noise with variance 0.01, robustness in the proposed method has reached perfect watermark quality with BER=0. And the watermarked image quality by PSNR parameter is also increased about 5 dB than the watermarked image quality from previous method.

An ab initio study of Cu-based delafossites as an alternative to nickel oxide in photocathodes: effects of Mg-doping and surface electronic features.

PubMed

Schiavo, Eduardo; Latouche, Camille; Barone, Vincenzo; Crescenzi, Orlando; Muñoz-García, Ana B; Pavone, Michele

2018-05-23

CuMO2 delafossites (M = Al, Ga, and Cr) are p-type semiconductor oxides that have been recently proposed as the electrode in p-type dye-sensitized solar cells (p-DSSC) which is an alternative to the standard, low-performing nickel oxide. To assess this potential application of delafossites, we report here a DFT-based investigation of the structural and electronic properties of CuAlO2, CuGaO2 and CuCrO2. In particular, we address the role of Mg doping to obtain the p-type semiconducting character: the substitution of an M3+ cation with Mg2+ is easier with Ga than with Al and Cr, and, in all cases, the hole introduced by Mg2+ leads to the formation of Cu2+ species. Moreover, we address surface electronic features in order to characterize the most exposed delafossite surface termination and, more importantly, to predict the valence band maximum energy value, which determines the p-DSSC open circuit potential. From analysis of all our results, CuGaO2 emerges as the most promising system that can boost the development of new photocathodes for p-DSSCs.

A genetic algorithm-based framework for wavelength selection on sample categorization.

PubMed

Anzanello, Michel J; Yamashita, Gabrielli; Marcelo, Marcelo; Fogliatto, Flávio S; Ortiz, Rafael S; Mariotti, Kristiane; Ferrão, Marco F

2017-08-01

In forensic and pharmaceutical scenarios, the application of chemometrics and optimization techniques has unveiled common and peculiar features of seized medicine and drug samples, helping investigative forces to track illegal operations. This paper proposes a novel framework aimed at identifying relevant subsets of attenuated total reflectance Fourier transform infrared (ATR-FTIR) wavelengths for classifying samples into two classes, for example authentic or forged categories in case of medicines, or salt or base form in cocaine analysis. In the first step of the framework, the ATR-FTIR spectra were partitioned into equidistant intervals and the k-nearest neighbour (KNN) classification technique was applied to each interval to insert samples into proper classes. In the next step, selected intervals were refined through the genetic algorithm (GA) by identifying a limited number of wavelengths from the intervals previously selected aimed at maximizing classification accuracy. When applied to Cialis®, Viagra®, and cocaine ATR-FTIR datasets, the proposed method substantially decreased the number of wavelengths needed to categorize, and increased the classification accuracy. From a practical perspective, the proposed method provides investigative forces with valuable information towards monitoring illegal production of drugs and medicines. In addition, focusing on a reduced subset of wavelengths allows the development of portable devices capable of testing the authenticity of samples during police checking events, avoiding the need for later laboratorial analyses and reducing equipment expenses. Theoretically, the proposed GA-based approach yields more refined solutions than the current methods relying on interval approaches, which tend to insert irrelevant wavelengths in the retained intervals. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Determination of gallium at trace levels using a spectrofluorimetric method in synthetic U-Ga and Ga-As solutions.

PubMed

Kara, Derya; Fisher, Andrew; Foulkes, Mike; Hill, Steve J

2010-01-01

A simple, easy to use and selective spectrofluorimetric method for the determination of trace levels of gallium has been developed. A new Schiff base, N-o-vanillidine-2-amino-p-cresol (OVAC) was synthesized and its fluorescence activity with gallium investigated. Based on this chelation reaction, a spectrofluorimetric method has been developed for the determination of gallium in synthetically prepared Ga-U and Ga-As samples buffered at pH 4.0 using acetic acid-sodium acetate. The chelation reaction between Ga(III) and N-o-vanillidine-2-amino-p-cresol was very fast, requiring only 30min at room temperature to complex completely. The limit of detection (LOD) (3sigma) for Ga(III) was 7.17 nM (0.50 microgL(-1)), determined from the analysis of 11 different solutions of 20 microg L(-1) Ga(III). Copyright 2009 Elsevier B.V. All rights reserved.

AlGaN-Cladding-Free m-Plane InGaN/GaN Laser Diodes with p-Type AlGaN Etch Stop Layers

NASA Astrophysics Data System (ADS)

Farrell, Robert M.; Haeger, Daniel A.; Hsu, Po Shan; Hardy, Matthew T.; Kelchner, Kathryn M.; Fujito, Kenji; Feezell, Daniel F.; Mishra, Umesh K.; DenBaars, Steven P.; Speck, James S.; Nakamura, Shuji

2011-09-01

We present a new method of improving the accuracy and reproducibility of dry etching processes for ridge waveguide InGaN/GaN laser diodes (LDs). A GaN:Al0.09Ga0.91N etch rate selectivity of 11:1 was demonstrated for an m-plane LD with a 40 nm p-Al0.09Ga0.91N etch stop layer (ESL) surrounded by Al-free cladding layers, establishing the effectiveness of AlGaN-based ESLs for controlling etch depth in ridge waveguide InGaN/GaN LDs. These results demonstrate the potential for integrating AlGaN ESLs into commercial device designs where accurate control of the etch depth of the ridge waveguide is necessary for stable, kink-free operation at high output powers.

Inverted Al0.25Ga0.75N/GaN ultraviolet p-i-n photodiodes formed on p-GaN template layer grown by metalorganic vapor phase epitaxy

NASA Astrophysics Data System (ADS)

Chang, Kuo-Hua; Sheu, Jinn-Kong; Lee, Ming-Lun; Tu, Shang-Ju; Yang, Chih-Ciao; Kuo, Huan-Shao; Yang, J. H.; Lai, Wei-Chih

2010-07-01

Inverted Al0.25Ga0.75N/GaN ultraviolet (UV) p-i-n photodiodes (PDs) were grown by selective-area regrowth on p-GaN template. The inverted devices with low-resistivity n-type AlGaN top-contact layers exhibited a typical zero-bias peak responsivity of 66.7 mA/W at 310 nm corresponding to the external quantum efficiency of 26.6%. The typical UV-to-visible (310/400 nm) spectral rejection ratio at zero-bias was over three orders of magnitude. The differential resistance and detectivity were obtained at approximately 6.2×1012 Ω and 3.4×1013 cm Hz1/2 W-1, respectively. Compared with conventional AlGaN/GaN-based UV p-i-n PDs, the proposed device structure can potentially achieve solar-blind AlGaN/GaN-based p-i-n PDs with low-aluminum content or aluminum-free p-contact layer and reduce excessive tensile strain due to the lattice mismatch between AlGaN and GaN layers.

Accuracy of whole-genome prediction using a genetic architecture-enhanced variance-covariance matrix.

PubMed

Zhang, Zhe; Erbe, Malena; He, Jinlong; Ober, Ulrike; Gao, Ning; Zhang, Hao; Simianer, Henner; Li, Jiaqi

2015-02-09

Obtaining accurate predictions of unobserved genetic or phenotypic values for complex traits in animal, plant, and human populations is possible through whole-genome prediction (WGP), a combined analysis of genotypic and phenotypic data. Because the underlying genetic architecture of the trait of interest is an important factor affecting model selection, we propose a new strategy, termed BLUP|GA (BLUP-given genetic architecture), which can use genetic architecture information within the dataset at hand rather than from public sources. This is achieved by using a trait-specific covariance matrix ( T: ), which is a weighted sum of a genetic architecture part ( S: matrix) and the realized relationship matrix ( G: ). The algorithm of BLUP|GA (BLUP-given genetic architecture) is provided and illustrated with real and simulated datasets. Predictive ability of BLUP|GA was validated with three model traits in a dairy cattle dataset and 11 traits in three public datasets with a variety of genetic architectures and compared with GBLUP and other approaches. Results show that BLUP|GA outperformed GBLUP in 20 of 21 scenarios in the dairy cattle dataset and outperformed GBLUP, BayesA, and BayesB in 12 of 13 traits in the analyzed public datasets. Further analyses showed that the difference of accuracies for BLUP|GA and GBLUP significantly correlate with the distance between the T: and G: matrices. The new strategy applied in BLUP|GA is a favorable and flexible alternative to the standard GBLUP model, allowing to account for the genetic architecture of the quantitative trait under consideration when necessary. This feature is mainly due to the increased similarity between the trait-specific relationship matrix ( T: matrix) and the genetic relationship matrix at unobserved causal loci. Applying BLUP|GA in WGP would ease the burden of model selection. Copyright © 2015 Zhang et al.

GaN-based photon-recycling green light-emitting diodes with vertical-conduction structure.

PubMed

Sheu, Jinn-Kong; Chen, Fu-Bang; Yen, Wei-Yu; Wang, Yen-Chin; Liu, Chun-Nan; Yeh, Yu-Hsiang; Lee, Ming-Lun

2015-04-06

A p-i-n structure with near-UV(n-UV) emitting InGaN/GaN multiple quantum well(MQW) structure stacked on a green unipolar InGaN/GaN MQW was epitaxially grown at the same sapphire substrate. Photon recycling green light-emitting diodes(LEDs) with vertical-conduction feature on silicon substrates were then fabricated by wafer bonding and laser lift-off techniques. The green InGaN/GaN QWs were pumped with n-UV light to reemit low-energy photons when the LEDs were electrically driven with a forward current. Efficiency droop is potentially insignificant compared with the direct green LEDs due to the increase of effective volume of active layer in the optically pumped green LEDs, i.e., light emitting no longer limited in the QWs nearest to the p-type region to cause severe Auger recombination and carrier overflow losses.

GaN based nanorods for solid state lighting

NASA Astrophysics Data System (ADS)

Li, Shunfeng; Waag, Andreas

2012-04-01

In recent years, GaN nanorods are emerging as a very promising novel route toward devices for nano-optoelectronics and nano-photonics. In particular, core-shell light emitting devices are thought to be a breakthrough development in solid state lighting, nanorod based LEDs have many potential advantages as compared to their 2 D thin film counterparts. In this paper, we review the recent developments of GaN nanorod growth, characterization, and related device applications based on GaN nanorods. The initial work on GaN nanorod growth focused on catalyst-assisted and catalyst-free statistical growth. The growth condition and growth mechanisms were extensively investigated and discussed. Doping of GaN nanorods, especially p-doping, was found to significantly influence the morphology of GaN nanorods. The large surface of 3 D GaN nanorods induces new optical and electrical properties, which normally can be neglected in layered structures. Recently, more controlled selective area growth of GaN nanorods was realized using patterned substrates both by metalorganic chemical vapor deposition (MOCVD) and by molecular beam epitaxy (MBE). Advanced structures, for example, photonic crystals and DBRs are meanwhile integrated in GaN nanorod structures. Based on the work of growth and characterization of GaN nanorods, GaN nanoLEDs were reported by several groups with different growth and processing methods. Core/shell nanoLED structures were also demonstrated, which could be potentially useful for future high efficient LED structures. In this paper, we will discuss recent developments in GaN nanorod technology, focusing on the potential advantages, but also discussing problems and open questions, which may impose obstacles during the future development of a GaN nanorod based LED technology.

A comparative study of thermal characteristics of GaN-based VCSELs with three different typical structures

NASA Astrophysics Data System (ADS)

Mei, Yang; Xu, Rong-Bin; Xu, Huan; Ying, Lei-Ying; Zheng, Zhi-Wei; Zhang, Bao-Ping; Li, Mo; Zhang, Jian

2018-01-01

Thermal characteristics of GaN-based vertical cavity surface emitting lasers (VCSELs) with three typical structures were investigated both theoretically and experimentally. The simulation results based on a steady state quasi three-dimensional cylindrical model show that the thermal resistance (R th) is affected by cavity length, mesa size, as well as the bottom distributed Bragg reflector (DBR) size, and the detail further depends on different structures. Among different devices, GaN VCSEL with a hybrid cavity formed by one nitride bottom DBR and another dielectric top DBR is featured with lower R th, which is meanwhile affected strongly by the materials of the epitaxial bottom DBR. The main issues affecting the thermal dissipation in VCSELs with double dielectric DBRs are the bottom dielectric DBR and the dielectric current-confinement layer. To validate the simulation results, GaN-based VCSEL bonded on a copper plate was fabricated. R th of this device was measured and the results agreed well with the simulation. This work provides a better understanding of the thermal characteristics of GaN-based VCSELs and is useful in optimizing the structure design and improving the device performance.

The use of a genetic algorithm-based search strategy in geostatistics: application to a set of anisotropic piezometric head data

NASA Astrophysics Data System (ADS)

Abedini, M. J.; Nasseri, M.; Burn, D. H.

2012-04-01

In any geostatistical study, an important consideration is the choice of an appropriate, repeatable, and objective search strategy that controls the nearby samples to be included in the location-specific estimation procedure. Almost all geostatistical software available in the market puts the onus on the user to supply search strategy parameters in a heuristic manner. These parameters are solely controlled by geographical coordinates that are defined for the entire area under study, and the user has no guidance as to how to choose these parameters. The main thesis of the current study is that the selection of search strategy parameters has to be driven by data—both the spatial coordinates and the sample values—and cannot be chosen beforehand. For this purpose, a genetic-algorithm-based ordinary kriging with moving neighborhood technique is proposed. The search capability of a genetic algorithm is exploited to search the feature space for appropriate, either local or global, search strategy parameters. Radius of circle/sphere and/or radii of standard or rotated ellipse/ellipsoid are considered as the decision variables to be optimized by GA. The superiority of GA-based ordinary kriging is demonstrated through application to the Wolfcamp Aquifer piezometric head data. Assessment of numerical results showed that definition of search strategy parameters based on both geographical coordinates and sample values improves cross-validation statistics when compared with that based on geographical coordinates alone. In the case of a variable search neighborhood for each estimation point, optimization of local search strategy parameters for an elliptical support domain—the orientation of which is dictated by anisotropic axes—via GA was able to capture the dynamics of piezometric head in west Texas/New Mexico in an efficient way.

[Study on Application of NIR Spectral Information Screening in Identification of Maca Origin].

PubMed

Wang, Yuan-zhong; Zhao, Yan-li; Zhang, Ji; Jin, Hang

2016-02-01

Medicinal and edible plant Maca is rich in various nutrients and owns great medicinal value. Based on near infrared diffuse reflectance spectra, 139 Maca samples collected from Peru and Yunnan were used to identify their geographical origins. Multiplication signal correction (MSC) coupled with second derivative (SD) and Norris derivative filter (ND) was employed in spectral pretreatment. Spectrum range (7,500-4,061 cm⁻¹) was chosen by spectrum standard deviation. Combined with principal component analysis-mahalanobis distance (PCA-MD), the appropriate number of principal components was selected as 5. Based on the spectrum range and the number of principal components selected, two abnormal samples were eliminated by modular group iterative singular sample diagnosis method. Then, four methods were used to filter spectral variable information, competitive adaptive reweighted sampling (CARS), monte carlo-uninformative variable elimination (MC-UVE), genetic algorithm (GA) and subwindow permutation analysis (SPA). The spectral variable information filtered was evaluated by model population analysis (MPA). The results showed that RMSECV(SPA) > RMSECV(CARS) > RMSECV(MC-UVE) > RMSECV(GA), were 2. 14, 2. 05, 2. 02, and 1. 98, and the spectral variables were 250, 240, 250 and 70, respectively. According to the spectral variable filtered, partial least squares discriminant analysis (PLS-DA) was used to build the model, with random selection of 97 samples as training set, and the other 40 samples as validation set. The results showed that, R²: GA > MC-UVE > CARS > SPA, RMSEC and RMSEP: GA < MC-UVE < CARS

Ultrafast third-harmonic spectroscopy of single nanoantennas fabricated using helium-ion beam lithography

NASA Astrophysics Data System (ADS)

Kollmann, H.; Esmann, M.; Becker, S. F.; Piao, X.; Huynh, C.; Kautschor, L.-O.; Bösker, G.; Vieker, H.; Beyer, A.; Gölzhäuser, A.; Park, N.; Silies, M.; Lienau, C.

2016-03-01

Metallic nanoantennas are able to spatially localize far-field electromagnetic waves on a few nanometer length scale in the form of surface plasmon excitations 1-3. Standard tools for fabricating bowtie and rod antennas with sub-20 nm feature sizes are Electron Beam Lithography or Ga-based Focused Ion Beam (FIB) Milling. These structures, however, often suffer from surface roughness and hence show only a limited optical polarization contrast and therefore a limited electric field localization. Here, we combine Ga- and He-ion based milling (HIM) for the fabrication of gold bowtie and rod antennas with gap sizes of less than 6 nm combined with a high aspect ratio. Using polarization-sensitive Third-Harmonic (TH) spectroscopy, we compare the nonlinear optical properties of single HIM-antennas with sub-6-nm gaps with those produced by standard Ga-based FIB. We find a pronounced enhancement of the total TH intensity of more than three in comparison to Ga-FIB antennas and a highly improved polarization contrast of the TH intensity of 250:1 for Heion produced antennas 4. These findings combined with Finite-Element Method calculations demonstrate a field enhancement of up to one hundred in the few-nanometer gap of the antenna. This makes He-ion beam milling a highly attractive and promising new tool for the fabrication of plasmonic nanoantennas with few-nanometer feature sizes.

Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

PubMed

Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

2015-06-01

Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

Selective layer disordering in intersubband Al 0.028Ga 0.972 N/AlN superlattices with silicon nitride capping layer

DOE PAGES

Wierer, Jonathan J.; Allerman, Andrew A.; Skogen, Erik J.; ...

2015-06-01

We demonstrate the selective layer disordering in intersubband Al 0.028Ga 0.972 N/AlN superlattices using a silicon nitride (SiN x) capping layer. The (SiN x) capped superlattice exhibits suppressed layer disordering under high-temperature annealing. In addition, the rate of layer disordering is reduced with increased SiN x thickness. The layer disordering is caused by Si diffusion, and the SiN x layer inhibits vacancy formation at the crystal surface and ultimately, the movement of Al and Ga atoms across the heterointerfaces. In conclusion, patterning of the SiN x layer results in selective layer disordering, an attractive method to integrate active and passivemore » III–nitride-based intersubband devices.« less

Characterization of GaAs:Cr-based Timepix detector using synchrotron radiation and charged particles

NASA Astrophysics Data System (ADS)

Smolyanskiy, P.; Chelkov, G.; Guskov, A.; Dedovich, D.; Kozhevnikov, D.; Kruchonak, U.; Leyva Fabelo, A.; Zhemchugov, A.

2016-12-01

The interest in the use of high resistivity gallium arsenide compensated by chromium (GaAs:Cr) for photon detection has been growing steadily due to its numerous advantages over silicon. At the same time, the prospects of this material as a sensor for pixel detectors in nuclear and high energy physics are much less studied. In this paper we report the results of characterization of the Timepix detectors hybridized with GaAs:Cr sensors of various thickness using synchrotron radiation and various charged particles, including alphas and heavy ions. The energy and spatial resolution have been determined. Interesting features of GaAs:Cr specific to the detector response to an extremely dense energy deposit by heavy ions have been observed for the first time. The long-term stability of the detector has been evaluated based on the measurements performed over one year. Possible limitation of GaAs:Cr as a sensor for high flux X-ray imaging is discussed.

Fabrication of Very High Efficiency 5.8 GHz Power Amplifiers using AlGaN HFETs on SiC Substrates for Wireless Power Transmission

NASA Technical Reports Server (NTRS)

Sullivan, Gerry

2001-01-01

For wireless power transmission using microwave energy, very efficient conversion of the DC power into microwave power is extremely important. Class E amplifiers have the attractive feature that they can, in theory, be 100% efficient at converting, DC power to RF power. Aluminum gallium nitride (AlGaN) semiconductor material has many advantageous properties, relative to silicon (Si), gallium arsenide (GaAs), and silicon carbide (SiC), such as a much larger bandgap, and the ability to form AlGaN/GaN heterojunctions. The large bandgap of AlGaN also allows for device operation at higher temperatures than could be tolerated by a smaller bandgap transistor. This could reduce the cooling requirements. While it is unlikely that the AlGaN transistors in a 5.8 GHz class E amplifier can operate efficiently at temperatures in excess of 300 or 400 C, AlGaN based amplifiers could operate at temperatures that are higher than a GaAs or Si based amplifier could tolerate. Under this program, AlGaN microwave power HFETs have been fabricated and characterized. Hybrid class E amplifiers were designed and modeled. Unfortunately, within the time frame of this program, good quality HFETs were not available from either the RSC laboratories or commercially, and so the class E amplifiers were not constructed.

Interface dynamics and crystal phase switching in GaAs nanowires

NASA Astrophysics Data System (ADS)

Jacobsson, Daniel; Panciera, Federico; Tersoff, Jerry; Reuter, Mark C.; Lehmann, Sebastian; Hofmann, Stephan; Dick, Kimberly A.; Ross, Frances M.

2016-03-01

Controlled formation of non-equilibrium crystal structures is one of the most important challenges in crystal growth. Catalytically grown nanowires are ideal systems for studying the fundamental physics of phase selection, and could lead to new electronic applications based on the engineering of crystal phases. Here we image gallium arsenide (GaAs) nanowires during growth as they switch between phases as a result of varying growth conditions. We find clear differences between the growth dynamics of the phases, including differences in interface morphology, step flow and catalyst geometry. We explain these differences, and the phase selection, using a model that relates the catalyst volume, the contact angle at the trijunction (the point at which solid, liquid and vapour meet) and the nucleation site of each new layer of GaAs. This model allows us to predict the conditions under which each phase should be observed, and use these predictions to design GaAs heterostructures. These results could apply to phase selection in other nanowire systems.

Interface dynamics and crystal phase switching in GaAs nanowires.

PubMed

Jacobsson, Daniel; Panciera, Federico; Tersoff, Jerry; Reuter, Mark C; Lehmann, Sebastian; Hofmann, Stephan; Dick, Kimberly A; Ross, Frances M

2016-03-17

Controlled formation of non-equilibrium crystal structures is one of the most important challenges in crystal growth. Catalytically grown nanowires are ideal systems for studying the fundamental physics of phase selection, and could lead to new electronic applications based on the engineering of crystal phases. Here we image gallium arsenide (GaAs) nanowires during growth as they switch between phases as a result of varying growth conditions. We find clear differences between the growth dynamics of the phases, including differences in interface morphology, step flow and catalyst geometry. We explain these differences, and the phase selection, using a model that relates the catalyst volume, the contact angle at the trijunction (the point at which solid, liquid and vapour meet) and the nucleation site of each new layer of GaAs. This model allows us to predict the conditions under which each phase should be observed, and use these predictions to design GaAs heterostructures. These results could apply to phase selection in other nanowire systems.

n-ZnO/p-GaN heterojunction light-emitting diodes featuring a buried polarization-induced tunneling junction

NASA Astrophysics Data System (ADS)

Li, Ling; Zhang, Yuantao; Yan, Long; Jiang, Junyan; Han, Xu; Deng, Gaoqiang; Chi, Chen; Song, Junfeng

2016-12-01

n-ZnO/p-GaN heterojunction light-emitting diodes with a p-GaN/Al0.1Ga0.9N/n+-GaN polarization-induced tunneling junction (PITJ) were fabricated by metal-organic chemical vapor deposition. An intense and sharp ultraviolet emission centered at ˜396 nm was observed under forward bias. Compared with the n-ZnO/p-GaN reference diode without PITJ, the light intensity of the proposed diode is increased by ˜1.4-folds due to the improved current spreading. More importantly, the studied diode operates continuously for eight hours with the decay of only ˜3.5% under 20 mA, suggesting a remarkable operating stability. The results demonstrate the feasibility of using PITJ as hole injection layer for high-performance ZnO-based light-emitting devices.

Structural dependences of localization and recombination of photogenerated carriers in the top GaInP Subcells of GaInP/GaAs double-junction tandem solar cells.

PubMed

Deng, Zhuo; Ning, Jiqiang; Su, Zhicheng; Xu, Shijie; Xing, Zheng; Wang, Rongxin; Lu, Shulong; Dong, Jianrong; Zhang, Baoshun; Yang, Hui

2015-01-14

In high-efficiency GaInP/GaAs double-junction tandem solar cells, GaInP layers play a central role in determining the performance of the solar cells. Therefore, gaining a deeper understanding of the optoelectronic processes in GaInP layers is crucial for improving the energy conversion efficiency of GaInP-based photovoltaic devices. In this work, we firmly show strong dependences of localization and recombination of photogenerated carriers in the top GaInP subcells in the GaInP/GaAs double-junction tandem solar cells on the substrate misorientation angle with excitation intensity- and temperature-dependent photoluminescence (PL). The entire solar cell structures including GaInP layers were grown with metalorganic chemical vapor deposition on GaAs substrates with misorientation angles of 2° (denoted as Sample 2°) and 7° (Sample 7°) off (100) toward (111)B. The PL spectral features of the two top GaInP subcells, as well as their excitation-power and temperature dependences exhibit remarkable variation on the misorientation angle. In Sample 2°, the dominant localization mechanism and luminescence channels are due to the energy potential minima caused by highly ordered atomic domains; In Sample 7°, the main localization and radiative recombination of photogenerated carriers occur in the atomically disordered regions. Our results reveal a more precise picture on the localization and recombination mechanisms of photogenerated carriers in the top GaInP subcells, which could be the crucial factors in controlling the optoelectronic efficiency of the GaInP-based multijunction photovoltaic devices.

Loss of G-A base pairs is insufficient for achieving a large opening of U4 snRNA K-turn motif.

PubMed

Cojocaru, Vlad; Klement, Reinhard; Jovin, Thomas M

2005-01-01

Upon binding to the 15.5K protein, two tandem-sheared G-A base pairs are formed in the internal loop of the kink-turn motif of U4 snRNA (Kt-U4). We have reported that the folding of Kt-U4 is assisted by protein binding. Unstable interactions that contribute to a large opening of the free RNA ('k-e motion') were identified using locally enhanced sampling molecular dynamics simulations, results that agree with experiments. A detailed analysis of the simulations reveals that the k-e motion in Kt-U4 is triggered both by loss of G-A base pairs in the internal loop and backbone flexibility in the stems. Essential dynamics show that the loss of G-A base pairs is correlated along the first mode but anti-correlated along the third mode with the k-e motion. Moreover, when enhanced sampling was confined to the internal loop, the RNA adopted an alternative conformation characterized by a sharper kink, opening of G-A base pairs and modified stacking interactions. Thus, loss of G-A base pairs is insufficient for achieving a large opening of the free RNA. These findings, supported by previously published RNA structure probing experiments, suggest that G-A base pair formation occurs upon protein binding, thereby stabilizing a selective orientation of the stems.

Exciton localization and ultralow onset ultraviolet emission in ZnO nanopencils-based heterojunction diodes.

PubMed

Jiang, Junyan; Zhang, Yuantao; Chi, Chen; Long, Yan; Han, Xu; Wu, Bin; Zhang, Baolin; Du, Guotong

2016-09-05

n-GaN/i-ZnO/p-GaN double heterojunction diodes were constructed by vertically binding p-GaN wafer on the tip of ZnO nanopencil arrays grown on n-GaN/sapphire substrates. An increased quantum confinement in the tip of ZnO nanopencils has been verified by photoluminescence measurements combined with quantitative analyses. Under forward bias, a sharp ultraviolet emission at ~375 nm due to localized excitons recombination can be observed in ZnO. The electroluminescence mechanism of the studied diode is tentatively elucidated using a simplified quantum confinement model. Additionally, the improved performance of the studied diode featuring an ultralow emission onset, a good operation stability and an enhanced ultraviolet emission shows the potential of our approach. This work provides a new route for the design and development of ZnO-based excitonic optoelectronic devices.

Identification of the spatial location of deep trap states in AlGaN/GaN heterostructures by surface photovoltage spectroscopy

NASA Astrophysics Data System (ADS)

Jana, Dipankar; Porwal, S.; Sharma, T. K.

2017-12-01

Spatial and spectral origin of deep level defects in molecular beam epitaxy grown AlGaN/GaN heterostructures are investigated by using surface photovoltage spectroscopy (SPS) and pump-probe SPS techniques. A deep trap center ∼1 eV above the valence band is observed in SPS measurements which is correlated with the yellow luminescence feature in GaN. Capture of electrons and holes is resolved by performing temperature dependent SPS and pump-probe SPS measurements. It is found that the deep trap states are distributed throughout the sample while their dominance in SPS spectra depends on the density, occupation probability of deep trap states and the background electron density of GaN channel layer. Dynamics of deep trap states associated with GaN channel layer is investigated by performing frequency dependent photoluminescence (PL) and SPS measurements. A time constant of few millisecond is estimated for the deep defects which might limit the dynamic performance of AlGaN/GaN based devices.

Experimental and simulation studies on the effect of suction opening orientation on solar vertical chimney

NASA Astrophysics Data System (ADS)

Kumar, L. Madan Ananda; Sivaramakrishnan, V.; Premalatha, M.; Vivekanandan, M.

2017-07-01

The zero energy building considered is a single storey building in Tiruchirappalli city retrofitted with various green features. This study investigated the effect of a suction opening orientation on a vertical solar chimney (VSC), integrated into a one-storey building. It was designed, manufactured and tested through selection of different suction openings for the entry of air, including right, left, front, back, both right and left and both front and back sides. Genetic algorithm (GA) calculates maximum air flow rate for a building with VSC for better suction opening, in Tiruchirappalli's dry, environmental conditions. GA is a useful technique for finding an improved suction opening specifically in the presence of a host of independent parameters which are large. The obtained results are related to fluid flow temperature distribution along the chimney, mass flow rate and air change per hour. The findings between the GA and the experimental results show sound agreement.

Selective heteroepitaxy on deeply grooved substrate: A route to low cost semipolar GaN platforms of bulk quality

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

Tendille, Florian, E-mail: florian.tendille@crhea.cnrs.fr; Vennéguès, Philippe; De Mierry, Philippe

2016-08-22

Semipolar GaN crystal stripes larger than 100 μm with dislocation densities below 5 × 10{sup 6} cm{sup −2} are achieved using a low cost fabrication process. An original sapphire patterning procedure is proposed, enabling selective growth of semipolar oriented GaN stripes while confining the defects to specific areas. Radiative and non-radiative crystalline defects are investigated by cathodoluminescence and can be correlated to the development of crystal microstructure during the growth process. A dislocation reduction mechanism, supported by transmission electron microscopy, is proposed. This method represents a step forward toward low-cost quasi-bulk semipolar GaN epitaxial platforms with an excellent structural quality which will allowmore » for even more efficient III-nitride based devices.« less

The controlled growth of GaN nanowires.

PubMed

Hersee, Stephen D; Sun, Xinyu; Wang, Xin

2006-08-01

This paper reports a scalable process for the growth of high-quality GaN nanowires and uniform nanowire arrays in which the position and diameter of each nanowire is precisely controlled. The approach is based on conventional metalorganic chemical vapor deposition using regular precursors and requires no additional metal catalyst. The location, orientation, and diameter of each GaN nanowire are controlled using a thin, selective growth mask that is patterned by interferometric lithography. It was found that use of a pulsed MOCVD process allowed the nanowire diameter to remain constant after the nanowires had emerged from the selective growth mask. Vertical GaN nanowire growth rates in excess of 2 mum/h were measured, while remarkably the diameter of each nanowire remained constant over the entire (micrometer) length of the nanowires. The paper reports transmission electron microscopy and photoluminescence data.

New strategy for determination of anthocyanins, polyphenols and antioxidant capacity of Brassica oleracea liquid extract using infrared spectroscopies and multivariate regression

NASA Astrophysics Data System (ADS)

de Oliveira, Isadora R. N.; Roque, Jussara V.; Maia, Mariza P.; Stringheta, Paulo C.; Teófilo, Reinaldo F.

2018-04-01

A new method was developed to determine the antioxidant properties of red cabbage extract (Brassica oleracea) by mid (MID) and near (NIR) infrared spectroscopies and partial least squares (PLS) regression. A 70% (v/v) ethanolic extract of red cabbage was concentrated to 9° Brix and further diluted (12 to 100%) in water. The dilutions were used as external standards for the building of PLS models. For the first time, this strategy was applied for building multivariate regression models. Reference analyses and spectral data were obtained from diluted extracts. The determinate properties were total and monomeric anthocyanins, total polyphenols and antioxidant capacity by ABTS (2,2-azino-bis(3-ethyl-benzothiazoline-6-sulfonate)) and DPPH (2,2-diphenyl-1-picrylhydrazyl) methods. Ordered predictors selection (OPS) and genetic algorithm (GA) were used for feature selection before PLS regression (PLS-1). In addition, a PLS-2 regression was applied to all properties simultaneously. PLS-1 models provided more predictive models than did PLS-2 regression. PLS-OPS and PLS-GA models presented excellent prediction results with a correlation coefficient higher than 0.98. However, the best models were obtained using PLS and variable selection with the OPS algorithm and the models based on NIR spectra were considered more predictive for all properties. Then, these models provided a simple, rapid and accurate method for determination of red cabbage extract antioxidant properties and its suitability for use in the food industry.

Biomedical named entity extraction: some issues of corpus compatibilities.

PubMed

Ekbal, Asif; Saha, Sriparna; Sikdar, Utpal Kumar

2013-01-01

Named Entity (NE) extraction is one of the most fundamental and important tasks in biomedical information extraction. It involves identification of certain entities from text and their classification into some predefined categories. In the biomedical community, there is yet no general consensus regarding named entity (NE) annotation; thus, it is very difficult to compare the existing systems due to corpus incompatibilities. Due to this problem we can not also exploit the advantages of using different corpora together. In our present work we address the issues of corpus compatibilities, and use a single objective optimization (SOO) based classifier ensemble technique that uses the search capability of genetic algorithm (GA) for NE extraction in biomedicine. We hypothesize that the reliability of predictions of each classifier differs among the various output classes. We use Conditional Random Field (CRF) and Support Vector Machine (SVM) frameworks to build a number of models depending upon the various representations of the set of features and/or feature templates. It is to be noted that we tried to extract the features without using any deep domain knowledge and/or resources. In order to assess the challenges of corpus compatibilities, we experiment with the different benchmark datasets and their various combinations. Comparison results with the existing approaches prove the efficacy of the used technique. GA based ensemble achieves around 2% performance improvements over the individual classifiers. Degradation in performance on the integrated corpus clearly shows the difficulties of the task. In summary, our used ensemble based approach attains the state-of-the-art performance levels for entity extraction in three different kinds of biomedical datasets. The possible reasons behind the better performance in our used approach are the (i). use of variety and rich features as described in Subsection "Features for named entity extraction"; (ii) use of GA based classifier ensemble technique to combine the outputs of multiple classifiers.

EEG feature selection method based on decision tree.

PubMed

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

Application of genetic algorithm in integrated setup planning and operation sequencing

NASA Astrophysics Data System (ADS)

Kafashi, Sajad; Shakeri, Mohsen

2011-01-01

Process planning is an essential component for linking design and manufacturing process. Setup planning and operation sequencing is two main tasks in process planning. Many researches solved these two problems separately. Considering the fact that the two functions are complementary, it is necessary to integrate them more tightly so that performance of a manufacturing system can be improved economically and competitively. This paper present a generative system and genetic algorithm (GA) approach to process plan the given part. The proposed approach and optimization methodology analyses the TAD (tool approach direction), tolerance relation between features and feature precedence relations to generate all possible setups and operations using workshop resource database. Based on these technological constraints the GA algorithm approach, which adopts the feature-based representation, optimizes the setup plan and sequence of operations using cost indices. Case study show that the developed system can generate satisfactory results in optimizing the setup planning and operation sequencing simultaneously in feasible condition.

Terahertz spectroscopic investigation of gallic acid and its monohydrate

NASA Astrophysics Data System (ADS)

Zhang, Bo; Li, Shaoping; Wang, Chenyang; Zou, Tao; Pan, Tingting; Zhang, Jianbing; Xu, Zhou; Ren, Guanhua; Zhao, Hongwei

2018-02-01

The low-frequency spectra of gallic acid (GA) and its monohydrate were investigated by terahertz time-domain spectroscopy (THz-TDS) in the range of 0.5 to 4.5 THz. The dehydration process of GA monohydrate was monitored on-line. The kinetic mechanism of the dehydration process was analyzed depending on the THz spectral change at different temperatures. The results indicate that the diffusion of water molecule dominates the speed of the entire dehydration process. Solid-state density functional theory (DFT) calculations of the vibrational modes of both GA and its monohydrate were performed based on their crystalline structures for better interpreting the experimental THz spectra. The results demonstrate that the characterized features of GA mainly originate from the collective vibrations of molecules. And the interactions between GA and water molecules are responsible for THz fingerprint of GA monohydrate. Multi-techniques including differential scanning calorimetry and thermogravimetry (DSC-TG) and powder X-ray diffraction (PXRD) were also carried out to further investigate GA and its monohydrate.

Bias Selectable Dual Band AlGaN Ultra-violet Detectors

NASA Technical Reports Server (NTRS)

Yan, Feng; Miko, Laddawan; Franz, David; Guan, Bing; Stahle, Carl M.

2007-01-01

Bias selectable dual band AlGaN ultra-violet (UV) detectors, which can separate UV-A and UV-B using one detector in the same pixel by bias switching, have been designed, fabricated and characterized. A two-terminal n-p-n photo-transistor-like structure was used. When a forward bias is applied between the top electrode and the bottom electrode, the detectors can successfully detect W-A and reject UV-B. Under reverse bias, they can detect UV-B and reject UV-A. The proof of concept design shows that it is feasible to fabricate high performance dual-band UV detectors based on the current AlGaN material growth and fabrication technologies.

Quantitative Characteristics of Spectral-Domain Optical Coherence Tomography in Corresponding Areas of Increased Autofluorescence at the Margin of Geographic Atrophy in Patients With Age-Related Macular Degeneration.

PubMed

Hariri, Amir H; Nittala, Muneeswar G; Sadda, SriniVas R

2016-06-01

To evaluate the spectral-domain optical coherence tomography (SD-OCT) characteristics of the junctional zone corresponding to areas of increased autofluorescence (IAF) at the margin of geographic atrophy (GA) in patients with age-related macular degeneration (AMD). SD-OCT and fundus autofluorescence (FAF) images from untreated eyes with GA available from archived studies at Doheny Image Reading Center were evaluated. Areas of definite decreased autofluorescence (DDAF) corresponding to GA, and areas of IAF at the margins of the GA were manually segmented. Eyes with evidence of IAF were selected. Following manual registration of FAF and OCT data, areas of IAF and normal fluorescence were correlated with OCT features at these locations. Thirty eyes were included. The mean retinal pigment epithelium (RPE) thickness in areas of IAF was 40.6 µm ± 7.69 µm, compared to 28.8 µm ± 7.09 µm in normal adjacent areas (P < .001). Regions of IAF at the junctional zone of GA lesions appear to correspond to thickening of the presumed RPE band on OCT. [Ophthalmic Surg Lasers Imaging Retina. 2016;47:523-527.]. Copyright 2016, SLACK Incorporated.

An improved genetic algorithm for multidimensional optimization of precedence-constrained production planning and scheduling

NASA Astrophysics Data System (ADS)

Dao, Son Duy; Abhary, Kazem; Marian, Romeo

2017-06-01

Integration of production planning and scheduling is a class of problems commonly found in manufacturing industry. This class of problems associated with precedence constraint has been previously modeled and optimized by the authors, in which, it requires a multidimensional optimization at the same time: what to make, how many to make, where to make and the order to make. It is a combinatorial, NP-hard problem, for which no polynomial time algorithm is known to produce an optimal result on a random graph. In this paper, the further development of Genetic Algorithm (GA) for this integrated optimization is presented. Because of the dynamic nature of the problem, the size of its solution is variable. To deal with this variability and find an optimal solution to the problem, GA with new features in chromosome encoding, crossover, mutation, selection as well as algorithm structure is developed herein. With the proposed structure, the proposed GA is able to "learn" from its experience. Robustness of the proposed GA is demonstrated by a complex numerical example in which performance of the proposed GA is compared with those of three commercial optimization solvers.

Method of plasma etching Ga-based compound semiconductors

DOEpatents

Qiu, Weibin; Goddard, Lynford L.

2012-12-25

A method of plasma etching Ga-based compound semiconductors includes providing a process chamber and a source electrode adjacent to the process chamber. The process chamber contains a sample comprising a Ga-based compound semiconductor. The sample is in contact with a platen which is electrically connected to a first power supply, and the source electrode is electrically connected to a second power supply. The method includes flowing SiCl.sub.4 gas into the chamber, flowing Ar gas into the chamber, and flowing H.sub.2 gas into the chamber. RF power is supplied independently to the source electrode and the platen. A plasma is generated based on the gases in the process chamber, and regions of a surface of the sample adjacent to one or more masked portions of the surface are etched to create a substantially smooth etched surface including features having substantially vertical walls beneath the masked portions.

Lateral terahertz hot-electron bolometer based on an array of Sn nanothreads in GaAs

NASA Astrophysics Data System (ADS)

Ponomarev, D. S.; Lavrukhin, D. V.; Yachmenev, A. E.; Khabibullin, R. A.; Semenikhin, I. E.; Vyurkov, V. V.; Ryzhii, M.; Otsuji, T.; Ryzhii, V.

2018-04-01

We report on the proposal and the theoretical and experimental studies of the terahertz hot-electron bolometer (THz HEB) based on a gated GaAs structure like the field-effect transistor with the array of parallel Sn nanothreads (Sn-NTs). The operation of the HEB is associated with an increase in the density of the delocalized electrons due to their heating by the incoming THz radiation. The quantum and the classical device models were developed, the quantum one was based on the self-consistent solution of the Poisson and Schrödinger equations, the classical model involved the Poisson equation and density of states omitting quantization. We calculated the electron energy distributions in the channels formed around the Sn-NTs for different gate voltages and found the fraction of the delocalized electrons propagating across the energy barriers between the NTs. Since the fraction of the delocalized electrons strongly depends on the average electron energy (effective temperature), the proposed THz HEB can exhibit an elevated responsivity compared with the HEBs based on more standard heterostructures. Due to a substantial anisotropy of the device structure, the THz HEB may demonstrate a noticeable polarization selectivity of the response to the in-plane polarized THz radiation. The features of the THz HEB might be useful in their practical applications in biology, medicine and material science.

Investigation of abrupt degradation of drain current caused by under-gate crack in AlGaN/GaN high electron mobility transistors during high temperature operation stress

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

Zeng, Chang; Liao, XueYang; Li, RuGuan

2015-09-28

In this paper, we investigate the degradation mode and mechanism of AlGaN/GaN based high electron mobility transistors (HEMTs) during high temperature operation (HTO) stress. It demonstrates that there was abrupt degradation mode of drain current during HTO stress. The abrupt degradation is ascribed to the formation of crack under the gate which was the result of the brittle fracture of epilayer based on failure analysis. The origin of the mechanical damage under the gate is further investigated and discussed based on top-down scanning electron microscope, cross section transmission electron microscope and energy dispersive x-ray spectroscopy analysis, and stress simulation. Basedmore » on the coupled analysis of the failure physical feature and stress simulation considering the coefficient of thermal expansion (CTE) mismatch in different materials in gate metals/semiconductor system, the mechanical damage under the gate is related to mechanical stress induced by CTE mismatch in Au/Ti/Mo/GaN system and stress concentration caused by the localized structural damage at the drain side of the gate edge. These results indicate that mechanical stress induced by CTE mismatch of materials inside the device plays great important role on the reliability of AlGaN/GaN HEMTs during HTO stress.« less

Ring resonator optical modes in InGaN/GaN structures grown on micro-cone-patterned sapphire substrates

NASA Astrophysics Data System (ADS)

Kazanov, D. R.; Pozina, G.; Jmerik, V. N.; Shubina, T. V.

2018-03-01

Molecular beam epitaxy (MBE) of III-nitride compounds on specially prepared cone-shaped patterned substrates is being actively developed nowadays, especially for nanophotonic applications. This type of substrates enables the successful growth of hexagonal nanorods (NRs). The insertion of an active quantum-sized region of InGaN inside a GaN NR allows us to enhance the rate of optical transitions by coupling them with resonant optical modes in the NR. However, we have observed the enhancement of emission not only from the NR but also around the circumference region of the cone-shaped base. We have studied this specific feature and demonstrated its impact on the output signal.

Laser generation in microdisc resonators with InAs/GaAs quantum dots transferred on a silicon substrate

NASA Astrophysics Data System (ADS)

Nadtochiy, A. M.; Kryzhanovskaya, N. V.; Maximov, M. V.; Zhukov, A. E.; Moiseev, E. I.; Kulagina, M. M.; Vashanova, K. A.; Zadiranov, Yu. M.; Mukhin, I. S.; Arakcheeva, E. M.; Livshits, D.; Lipovskii, A. A.

2013-09-01

Microdisc resonators based on InAs/GaAs quantum dots separated from a GaAs substrate by selective etching and fixed to a silicon substrate by epoxy glue are studied using luminescence spectroscopy. A disc resonator 6 μm in diameter exhibits quasi-single-mode laser generation at a temperature of 78 K with a threshold power of 320 μW and λ/Δλ ˜ 27000.

SiNOI and AlGaAs-on-SOI nonlinear circuits for continuum generation in Si photonics

NASA Astrophysics Data System (ADS)

El Dirani, Houssein; Monat, Christelle; Brision, Stéphane; Olivier, Nicolas; Jany, Christophe; Letartre, Xavier; Pu, Minhao; Girouard, Peter D.; Hagedorn Frandsen, Lars; Semenova, Elizaveta; Katsuo Oxenløwe, Leif; Yvind, Kresten; Sciancalepore, Corrado

2018-02-01

In this communication, we report on the design, fabrication, and testing of Silicon Nitride on Insulator (SiNOI) and Aluminum-Gallium-Arsenide (AlGaAs) on silicon-on-insulator (SOI) nonlinear photonic circuits for continuum generation in Silicon (Si) photonics. As recently demonstrated, the generation of frequency continua and supercontinua can be used to overcome the intrinsic limitations of nowadays silicon photonics notably concerning the heterogeneous integration of III-V on SOI lasers for datacom and telecom applications. By using the Kerr nonlinearity of monolithic silicon nitride and heterointegrated GaAs-based alloys on SOI, the generation of tens or even hundreds of new optical frequencies can be obtained in dispersion tailored waveguides, thus providing an all-optical alternative to the heterointegration of hundreds of standalone III-V on Si lasers. In our work, we present paths to energy-efficient continua generation on silicon photonics circuits. Notably, we demonstrate spectral broadening covering the full C-band via Kerrbased self-phase modulation in SiNOI nanowires featuring full process compatibility with Si photonic devices. Moreover, AlGaAs waveguides are heterointegrated on SOI in order to dramatically reduce (x1/10) thresholds in optical parametric oscillation and in the power required for supercontinuum generation under pulsed pumping. The manufacturing techniques allowing the monolithic co-integration of nonlinear functionalities on existing CMOS-compatible Si photonics for both active and passive components will be shown. Experimental evidence based on self-phase modulation show SiNOI and AlGaAs nanowires capable of generating wide-spanning frequency continua in the C-Band. This will pave the way for low-threshold power-efficient Kerr-based comb- and continuum- sources featuring compatibility with Si photonic integrated circuits (Si-PICs).

Lattice constant changes leading to significant changes of the spin-gapless features and physical nature in a inverse Heusler compound Zr2MnGa

NASA Astrophysics Data System (ADS)

Wang, Xiaotian; Cheng, Zhenxiang; Khenata, Rabah; Wu, Yang; Wang, Liying; Liu, Guodong

2017-12-01

The spin-gapless semiconductors with parabolic energy dispersions [1-3] have been recently proposed as a new class of materials for potential applications in spintronic devices. In this work, according to the Slater-Pauling rule, we report the fully-compensated ferrimagnetic (FCF) behavior and spin-gapless semiconducting (SGS) properties for a new inverse Heusler compound Zr2MnGa by means of the plane-wave pseudo-potential method based on density functional theory. With the help of GGA-PBE, the electronic structures and the magnetism of Zr2MnGa compound at its equilibrium and strained lattice constants are systematically studied. The calculated results show that the Zr2MnGa is a new SGS at its equilibrium lattice constant: there is an energy gap between the conduction and valence bands for both the majority and minority electrons, while there is no gap between the majority electrons in the valence band and the minority electrons in the conduction band. Remarkably, not only a diverse physical nature transition, but also different types of spin-gapless features can be observed with the change of the lattice constants. Our calculated results of Zr2MnGa compound indicate that this material has great application potential in spintronic devices.

Probing collective oscillation of d-orbital electrons at the nanoscale

NASA Astrophysics Data System (ADS)

Dhall, Rohan; Vigil-Fowler, Derek; Houston Dycus, J.; Kirste, Ronny; Mita, Seiji; Sitar, Zlatko; Collazo, Ramon; LeBeau, James M.

2018-02-01

Here, we demonstrate that high energy electrons can be used to explore the collective oscillation of s, p, and d orbital electrons at the nanometer length scale. Using epitaxial AlGaN/AlN quantum wells as a test system, we observe the emergence of additional features in the loss spectrum with the increasing Ga content. A comparison of the observed spectra with ab-initio theory reveals that the origin of these spectral features lies in excitations of 3d-electrons contributed by Ga. We find that these modes differ in energy from the valence electron plasmons in Al1-xGaxN due to the different polarizabilities of the d electrons. Finally, we study the dependence of observed spectral features on the Ga content, lending insights into the origin of these spectral features, and their coupling with electron-hole excitations.

The controlled growth of GaN microrods on Si(111) substrates by MOCVD

NASA Astrophysics Data System (ADS)

Foltynski, Bartosz; Garro, Nuria; Vallo, Martin; Finken, Matthias; Giesen, Christoph; Kalisch, Holger; Vescan, Andrei; Cantarero, Andrés; Heuken, Michael

2015-03-01

In this paper, a selective area growth (SAG) approach for growing GaN microrods on patterned SiNx/Si(111) substrates by metal-organic chemical vapor deposition (MOCVD) is studied. The surface morphology, optical and structural properties of vertical GaN microrods terminated by pyramidal shaped facets (six { 10 1 bar 1} planes) were characterized using scanning electron microscopy (SEM), room temperature photoluminescence (PL) and Raman spectroscopy, respectively. Measurements revealed high-quality GaN microcolumns grown with silane support. Characterized structures were grown nearly strain-free (central frequency of Raman peak of 567±1 cm-1) with crystal quality comparable to bulk crystals (FWHM=4.2±1 cm-1). Such GaN microrods might be used as a next-generation device concept for solid-state lighting (SSL) applications by realizing core-shell InGaN/GaN multi-quantum wells (MQWs) on the n-GaN rod base.

Integrated feature extraction and selection for neuroimage classification

NASA Astrophysics Data System (ADS)

Fan, Yong; Shen, Dinggang

2009-02-01

Feature extraction and selection are of great importance in neuroimage classification for identifying informative features and reducing feature dimensionality, which are generally implemented as two separate steps. This paper presents an integrated feature extraction and selection algorithm with two iterative steps: constrained subspace learning based feature extraction and support vector machine (SVM) based feature selection. The subspace learning based feature extraction focuses on the brain regions with higher possibility of being affected by the disease under study, while the possibility of brain regions being affected by disease is estimated by the SVM based feature selection, in conjunction with SVM classification. This algorithm can not only take into account the inter-correlation among different brain regions, but also overcome the limitation of traditional subspace learning based feature extraction methods. To achieve robust performance and optimal selection of parameters involved in feature extraction, selection, and classification, a bootstrapping strategy is used to generate multiple versions of training and testing sets for parameter optimization, according to the classification performance measured by the area under the ROC (receiver operating characteristic) curve. The integrated feature extraction and selection method is applied to a structural MR image based Alzheimer's disease (AD) study with 98 non-demented and 100 demented subjects. Cross-validation results indicate that the proposed algorithm can improve performance of the traditional subspace learning based classification.

Design of Low Inductance Switching Power Cell for GaN HEMT Based Inverter

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

Gurpinar, Emre; Iannuzzo, Francesco; Yang, Yongheng

Here in this paper, an ultra-low inductance power cell is designed for a three-Level Active Neutral Point Clamped (3LANPC) based on 650 V gallium nitride (GaN) HEMT devices. The 3L-ANPC topology with GaN HEMT devices and the selected modulation scheme suitable for wide-bandgap (WBG) devices are presented. The commutation loops, which mainly contribute to voltage overshoots and increase of switching losses, are discussed. The ultra-low inductance power cell design based on a fourlayer Printed Circuit Board (PCB) with the aim to maximize the switching performance of GaN HEMTs is explained. The design of gate drivers for the GaN HEMT devicesmore » is presented. Parasitic inductance and resistance of the proposed design are extracted with finite element analysis and discussed. Common mode behaviours based on the SPICE model of the converter are analyzed. Experimental results on the designed 3L-ANPC with the output power of up to 1 kW are presented, which verifies the performance of the proposed design in terms of ultra-low inductance.« less

InGaAs/InP SPAD photon-counting module with auto-calibrated gate-width generation and remote control

NASA Astrophysics Data System (ADS)

Tosi, Alberto; Ruggeri, Alessandro; Bahgat Shehata, Andrea; Della Frera, Adriano; Scarcella, Carmelo; Tisa, Simone; Giudice, Andrea

2013-01-01

We present a photon-counting module based on InGaAs/InP SPAD (Single-Photon Avalanche Diode) for detecting single photons up to 1.7 μm. The module exploits a novel architecture for generating and calibrating the gate width, along with other functions (such as module supervision, counting and processing of detected photons, etc.). The gate width, i.e. the time interval when the SPAD is ON, is user-programmable in the range from 500 ps to 1.5 μs, by means of two different delay generation methods implemented with an FPGA (Field-Programmable Gate Array). In order to compensate chip-to-chip delay variation, an auto-calibration circuit picks out a combination of delays in order to match at best the selected gate width. The InGaAs/InP module accepts asynchronous and aperiodic signals and introduces very low timing jitter. Moreover the photon counting module provides other new features like a microprocessor for system supervision, a touch-screen for local user interface, and an Ethernet link for smart remote control. Thanks to the fullyprogrammable and configurable architecture, the overall instrument provides high system flexibility and can easily match all requirements set by many different applications requiring single photon-level sensitivity in the near infrared with very low photon timing jitter.

Photodynamic therapy with redaporfin targets the endoplasmic reticulum and Golgi apparatus.

PubMed

Gomes-da-Silva, Lígia C; Zhao, Liwei; Bezu, Lucillia; Zhou, Heng; Sauvat, Allan; Liu, Peng; Durand, Sylvère; Leduc, Marion; Souquere, Sylvie; Loos, Friedemann; Mondragón, Laura; Sveinbjørnsson, Baldur; Rekdal, Øystein; Boncompain, Gaelle; Perez, Franck; Arnaut, Luis G; Kepp, Oliver; Kroemer, Guido

2018-05-28

Preclinical evidence depicts the capacity of redaporfin (Redp) to act as potent photosensitizer, causing direct antineoplastic effects as well as indirect immune-dependent destruction of malignant lesions. Here, we investigated the mechanisms through which photodynamic therapy (PDT) with redaporfin kills cancer cells. Subcellular localization and fractionation studies based on the physicochemical properties of redaporfin revealed its selective tropism for the endoplasmic reticulum (ER) and the Golgi apparatus (GA). When activated, redaporfin caused rapid reactive oxygen species-dependent perturbation of ER/GA compartments, coupled to ER stress and an inhibition of the GA-dependent secretory pathway. This led to a general inhibition of protein secretion by PDT-treated cancer cells. The ER/GA play a role upstream of mitochondria in the lethal signaling pathway triggered by redaporfin-based PDT Pharmacological perturbation of GA function or homeostasis reduces mitochondrial permeabilization. In contrast, removal of the pro-apoptotic multidomain proteins BAX and BAK or pretreatment with protease inhibitors reduced cell killing, yet left the GA perturbation unaffected. Altogether, these results point to the capacity of redaporfin to kill tumor cells via destroying ER/GA function. © 2018 The Authors.

MOVPE of GaSb/InGaAsSb Multilayers and Fabrication of Dual Band Photodetectors

NASA Technical Reports Server (NTRS)

Xiao, Ye-Gao; Bhat, Ishwara; Refaat, Tamer F.; Abedin, M. Nurul; Shao, Qing-Hui

2005-01-01

Metalorganic vapor phase epitaxy (MOVPE) of GaSb/InGaAsSb multilayer thin films and fabrication of bias-selectable dual band photodetectors are reported. For the dual band photodetectors the short wavelength detector, or the upper p- GaSb/n-GaSb junction photodiode, is placed optically ahead of the long wavelength one, or the lower photodiode. The latter is based on latticed-matched In0.13Ga0.87As0.11Sb0.89 with bandgap near 0.6 eV. Specifically, high quality multilayer thin films are grown sequentially from top to bottom as p+-GaSb/p-GaSb/n-GaSb/n-InGaAsSb/p-InGaAsSb/p-GaSb on undoped p-type GaSb substrate, and as n-GaSb/p-GaSb/p-InGaAsSb/n-InGaAsSb/n-GaSb on Te-doped n-type GaSb substrate respectively. The multilayer thin films are characterized by optical microscope, atomic force microscope (AFM), electron microprobe analyses etc. The photodiode mesa steps are patterned by photolithography with wet chemical etching and the front metallization is carried out by e-beam evaporation with Pd/Ge/Au/Ti/Au to give ohmic contact on both n- and p-type Sb based layer surfaces. Dark I-V measurements show typical diode behavior for both the upper and lower photodiodes. The photoresponsivity measurements indicate that both the upper and lower photodiodes can sense the infrared illumination corresponding to their cutoff wavelengths respectively, comparable with the simulation results. More work is underway to bring the long wavelength band to the medium infrared wavelength region near 4 micrometers.

Train axle bearing fault detection using a feature selection scheme based multi-scale morphological filter

NASA Astrophysics Data System (ADS)

Li, Yifan; Liang, Xihui; Lin, Jianhui; Chen, Yuejian; Liu, Jianxin

2018-02-01

This paper presents a novel signal processing scheme, feature selection based multi-scale morphological filter (MMF), for train axle bearing fault detection. In this scheme, more than 30 feature indicators of vibration signals are calculated for axle bearings with different conditions and the features which can reflect fault characteristics more effectively and representatively are selected using the max-relevance and min-redundancy principle. Then, a filtering scale selection approach for MMF based on feature selection and grey relational analysis is proposed. The feature selection based MMF method is tested on diagnosis of artificially created damages of rolling bearings of railway trains. Experimental results show that the proposed method has a superior performance in extracting fault features of defective train axle bearings. In addition, comparisons are performed with the kurtosis criterion based MMF and the spectral kurtosis criterion based MMF. The proposed feature selection based MMF method outperforms these two methods in detection of train axle bearing faults.

A flow method based on solvent extraction coupled on-line to a reversed micellar mediated chemiluminescence detection for selective determination of gold(III) and gallium(III) in water and industrial samples.

PubMed

Hasanin, Tamer H A; Okamoto, Yasuaki; Fujiwara, Terufumi

2016-02-01

A rapid and sensitive flow method, based on the combination of on-line solvent extraction with reversed micellar mediated chemiluminescence (CL) detection using rhodamine B (RB), was investigated for the selective determination of Au(III) and Ga(III) in aqueous solutions. 2.0 M HCl was the optimum for extracting Au(III) while a 5.0M HCl solution containing 2.5M LiCl was selected as an optimum acidic medium for extraction of Ga(III). The Au(III) and Ga(III) chloro-complex anions were extracted from the above aqueous acidic solutions into toluene as their ion-pair complexes with the protonated RBH(+) ion followed by membrane phase separation in a flow system. In a flow cell of a detector, the extract was mixed with the reversed micellar solution of cetyltrimethylammonium chloride (CTAC) in 1-hexanol-cyclohexane/water (1.0M HCl) containing 0.10 M cerium(IV) and 0.05 M lithium sulfate. Then uptake of the ion-pair by the CTAC reversed micelles and the subsequent CL oxidation of RB with Ce(IV) occurred easily and the CL signals produced were recorded. Using a flow injection system, a detection limit (DL) of 0.4 μM Au(III) and 0.6 μM Ga(III), and linear calibration graphs with dynamic ranges from the respective DLs to 10 μM for Au(III) and Ga(III) were obtained under the optimized experimental conditions. The relative standard deviations (n=6) obtained at 2.0 µM Au(III) and 4.0 µM Ga(III) were 3.0% and 2.4%, respectively. The presented CL methodology has been applied for the determination of Au(III) and Ga(III) in water and industrial samples with satisfactory results. Copyright © 2015 Elsevier B.V. All rights reserved.

Growth behavior and growth rate dependency in LEDs performance for Mg-doped a-plane GaN

NASA Astrophysics Data System (ADS)

Song, Keun-Man; Kim, Jong-Min; Lee, Dong-Hun; Shin, Chan-Soo; Ko, Chul-Gi; Kong, Bo-Hyun; Cho, Hyung-Koun; Yoon, Dae-Ho

2011-07-01

We investigated the influence of growth rate of Mg-doped a-plane GaN on the surface morphological and electrical properties, and the characteristics of InGaN-based nonpolar LEDs. Mg-doped a-plane GaN layers were grown on r-plane sapphire substrate by metalorganic chemical vapor deposition (MOCVD). Scanning electron microscopy (SEM), transmission electron microscopy (TEM) and cathode luminescence (CL) analysis exhibited that the surface morphology changed from stripe features with large triangular pits to rough and rugged surface with small asymmetric V-shape pits, as the growth rate increased. The Mg incorporation into a-plane GaN layers increased with increasing growth rate of Mg-doped a-plane GaN, while the activation efficiency of Mg dopants decreased in a-plane GaN. Additionally, it was found that operation voltage at 20 mA decreased in characteristics of LEDs, as the growth rate of Mg-doped a-plane GaN decreased. Meanwhile, the EL intensity of LEDs with p-GaN layers grown at higher growth rate was improved compared to that of LEDs with p-GaN layers grown at lower growth rate. Such an increase of EL intensity is attributed to the rougher surface morphology with increasing growth rate of Mg-doped a-plane GaN.

Design Optimization of Ge/GaAs-Based Heterojunction Gate-All-Around (GAA) Arch-Shaped Tunneling Field-Effect Transistor (A-TFET).

PubMed

Seo, Jae Hwa; Yoon, Young Jun; Kang, In Man

2018-09-01

The Ge/GaAs-based heterojunction gate-all-around (GAA) arch-shaped tunneling field-effect transistor (A-TFET) have been designed and optimized using technology computer-aided design (TCAD) simulations. In our previous work, the silicon-based A-TFET was designed and demonstrated. However, to progress the electrical characteristics of A-TFET, the III-V compound heterojunction structures which has enhanced electrical properties must be adopted. Thus, the germanium with gallium arsenide (Ge/GaAs) is considered as key materials of A-TFET. The proposed device has a Ge-based p-doped source, GaAs-based i-doped channel and GaAs-based n-doped drain. Due to the critical issues of device performances, the doping concentration of source and channel region (Dsource, Dchannel), height of source region (Hsource) and epitaxially grown thickness of channel (tepi) was selected as design optimization variables of Ge/GaAs-based GAA A-TFET. The DC characteristics such as on-state current (ion), off-state current (ioff), subthreshold-swing (S) were of extracted and analyzed. Finally, the proposed device has a gate length (LG) of 90 nm, Dsource 5 × 1019 cm-3, Dchannel of 1018 cm-3, tepi of 4 nm, Hsource of 90 nm, R of 10 nm and demonstrate an ion of 2 mA/μm, S of 12.9 mV/dec.

Light extraction efficiency of GaN-based LED with pyramid texture by using ray path analysis.

PubMed

Pan, Jui-Wen; Wang, Chia-Shen

2012-09-10

We study three different gallium-nitride (GaN) based light emitting diode (LED) cases based on the different locations of the pyramid textures. In case 1, the pyramid texture is located on the sapphire top surface, in case 2, the pyramid texture is locate on the P-GaN top surface, while in case 3, the pyramid texture is located on both the sapphire and P-GaN top surfaces. We study the relationship between the light extraction efficiency (LEE) and angle of slant of the pyramid texture. The optimization of total LEE was highest for case 3 among the three cases. Moreover, the seven escape paths along which most of the escaped photon flux propagated were selected in a simulation of the LEDs. The seven escape paths were used to estimate the slant angle for the optimization of LEE and to precisely analyze the photon escape path.

Improved Ohmic-contact to AlGaN/GaN using Ohmic region recesses by self-terminating thermal oxidation assisted wet etching technique

NASA Astrophysics Data System (ADS)

Liu, J.; Wang, J.; Wang, H.; Zhu, L.; Wu, W.

2017-06-01

Lower Ti/Al/Ni/Au Ohmic contact resistance on AlGaN/GaN with wider rapid thermal annealing (RTA) temperature window was achieved using recessed Ohmic contact structure based on self-terminating thermal oxidation assisted wet etching technique (STOAWET), in comparison with conventional Ohmic contacts. Even at lower temperature such as 650°C, recessed structure by STOAWET could still obtain Ohmic contact with contact resistance of 1.97Ω·mm, while conventional Ohmic structure mainly featured as Schottky contact. Actually, both Ohmic contact recess and mesa isolation processes could be accomplished by STOAWET in one process step and the process window of STOAWET is wide, simplifying AlGaN/GaN HEMT device process. Our experiment shows that the isolation leakage current by STOAWET is about one order of magnitude lower than that by inductivity coupled plasma (ICP) performed on the same wafer.

Large area ultraviolet photodetector on surface modified Si:GaN layers

NASA Astrophysics Data System (ADS)

Anitha, R.; R., Ramesh; Loganathan, R.; Vavilapalli, Durga Sankar; Baskar, K.; Singh, Shubra

2018-03-01

Unique features of semiconductor based heterostructured photoelectric devices have drawn considerable attention in the recent past. In the present work, large area UV photodetector has been fabricated utilizing interesting Zinc oxide microstructures on etched Si:GaN layers. The surface of Si:GaN layer grown by metal organic chemical vapor deposition method on sapphire has been modified by chemical etching to control the microstructure. The photodetector exhibits response to Ultraviolet light only. Optimum etching of Si:GaN was required to exhibit higher responsivity (0.96 A/W) and detectivity (∼4.87 × 109 Jones), the two important parameters for a photodetector. Present method offers a tunable functionality of photodetector through modification of top layer microstructure. A comparison with state of art materials has also been presented.

Primary central nervous system lymphoma and glioblastoma differentiation based on conventional magnetic resonance imaging by high-throughput SIFT features.

PubMed

Chen, Yinsheng; Li, Zeju; Wu, Guoqing; Yu, Jinhua; Wang, Yuanyuan; Lv, Xiaofei; Ju, Xue; Chen, Zhongping

2018-07-01

Due to the totally different therapeutic regimens needed for primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM), accurate differentiation of the two diseases by noninvasive imaging techniques is important for clinical decision-making. Thirty cases of PCNSL and 66 cases of GBM with conventional T1-contrast magnetic resonance imaging (MRI) were analyzed in this study. Convolutional neural networks was used to segment tumor automatically. A modified scale invariant feature transform (SIFT) method was utilized to extract three-dimensional local voxel arrangement information from segmented tumors. Fisher vector was proposed to normalize the dimension of SIFT features. An improved genetic algorithm (GA) was used to extract SIFT features with PCNSL and GBM discrimination ability. The data-set was divided into a cross-validation cohort and an independent validation cohort by the ratio of 2:1. Support vector machine with the leave-one-out cross-validation based on 20 cases of PCNSL and 44 cases of GBM was employed to build and validate the differentiation model. Among 16,384 high-throughput features, 1356 features show significant differences between PCNSL and GBM with p < 0.05 and 420 features with p < 0.001. A total of 496 features were finally chosen by improved GA algorithm. The proposed method produces PCNSL vs. GBM differentiation with an area under the curve (AUC) curve of 99.1% (98.2%), accuracy 95.3% (90.6%), sensitivity 85.0% (80.0%) and specificity 100% (95.5%) on the cross-validation cohort (and independent validation cohort). Since the local voxel arrangement characterization provided by SIFT features, proposed method produced more competitive PCNSL and GBM differentiation performance by using conventional MRI than methods based on advanced MRI.

Integrating AlGaN/GaN high electron mobility transistor with Si: A comparative study of integration schemes

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

Mohan, Nagaboopathy; Raghavan, Srinivasan; Centre for Nano Science and Engineering, Indian Institute of Science, Bangalore 560012

2015-10-07

AlGaN/GaN high electron mobility transistor stacks deposited on a single growth platform are used to compare the most common transition, AlN to GaN, schemes used for integrating GaN with Si. The efficiency of these transitions based on linearly graded, step graded, interlayer, and superlattice schemes on dislocation density reduction, stress management, surface roughness, and eventually mobility of the 2D-gas are evaluated. In a 500 nm GaN probe layer deposited, all of these transitions result in total transmission electron microscopy measured dislocations densities of 1 to 3 × 10{sup 9}/cm{sup 2} and <1 nm surface roughness. The 2-D electron gas channels formed atmore » an AlGaN-1 nm AlN/GaN interface deposited on this GaN probe layer all have mobilities of 1600–1900 cm{sup 2}/V s at a carrier concentration of 0.7–0.9 × 10{sup 13}/cm{sup 2}. Compressive stress and changes in composition in GaN rich regions of the AlN-GaN transition are the most effective at reducing dislocation density. Amongst all the transitions studied the step graded transition is the one that helps to implement this feature of GaN integration in the simplest and most consistent manner.« less

Probing collective oscillation of d -orbital electrons at the nanoscale

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

Dhall, Rohan; Vigil-Fowler, Derek; Houston Dycus, J.

Here, we demonstrate that high energy electrons can be used to explore the collective oscillation of s, p, and d orbital electrons at the nanometer length scale. Using epitaxial AlGaN/AlN quantum wells as a test system, we observe the emergence of additional features in the loss spectrum with the increasing Ga content. A comparison of the observed spectra with ab-initio theory reveals that the origin of these spectral features lies in excitations of 3d-electrons contributed by Ga. We find that these modes differ in energy from the valence electron plasmons in Al1-xGaxN due to the different polarizabilities of the dmore » electrons. Finally, we study the dependence of observed spectral features on the Ga content, lending insights into the origin of these spectral features, and their coupling with electron-hole excitations.« less

Analysis of GaN Damage Induced by Cl2/SiCl4/Ar Plasma

NASA Astrophysics Data System (ADS)

Minami, Masaki; Tomiya, Shigetaka; Ishikawa, Kenji; Matsumoto, Ryosuke; Chen, Shang; Fukasawa, Masanaga; Uesawa, Fumikatsu; Sekine, Makoto; Hori, Masaru; Tatsumi, Tetsuya

2011-08-01

GaN-based optical devices are fabricated using a GaN/InGaN/GaN sandwiched structure. The effect of radicals, ions, and UV light on the GaN optical properties during Cl2/SiCl4/Ar plasma etching was evaluated using photoluminescence (PL) analysis. The samples were exposed to plasma (radicals, ions, and UV light) using an inductively coupled plasma (ICP) etching system and a plasma ion beam apparatus that can separate the effects of UV and ions both with and without covering the SiO2 window on the surface. Etching damage in an InGaN single quantum well (SQW) was formed by exposing the sample to plasma. The damage, which decreases PL emission intensity, was generated not only by ion beam irradiation but also by UV light irradiation. PL intensity decreased when the thickness of the upper GaN layer was etched to less than 60 nm. In addition, simultaneous irradiation of UV light and ions slightly increased the degree of damage. There seems to be a synergistic effect between the UV light and the ions. For high-quality GaN-based optoelectronics and power devices, UV light must be controlled during etching processes in addition to the etching profile, selectivity, and ion bombardment damage.

Clavulanic acid production estimation based on color and structural features of Streptomyces clavuligerus bacteria using self-organizing map and genetic algorithm.

PubMed

Nurmohamadi, Maryam; Pourghassem, Hossein

2014-05-01

The utilization of antibiotics produced by Clavulanic acid (CA) is an increasing need in medicine and industry. Usually, the CA is created from the fermentation of Streptomycen Clavuligerus (SC) bacteria. Analysis of visual and morphological features of SC bacteria is an appropriate measure to estimate the growth of CA. In this paper, an automatic and fast CA production level estimation algorithm based on visual and structural features of SC bacteria instead of statistical methods and experimental evaluation by microbiologist is proposed. In this algorithm, structural features such as the number of newborn branches, thickness of hyphal and bacterial density and also color features such as acceptance color levels are extracted from the SC bacteria. Moreover, PH and biomass of the medium provided by microbiologists are considered as specified features. The level of CA production is estimated by using a new application of Self-Organizing Map (SOM), and a hybrid model of genetic algorithm with back propagation network (GA-BPN). The proposed algorithm is evaluated on four carbonic resources including malt, starch, wheat flour and glycerol that had used as different mediums of bacterial growth. Then, the obtained results are compared and evaluated with observation of specialist. Finally, the Relative Error (RE) for the SOM and GA-BPN are achieved 14.97% and 16.63%, respectively. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Isolating GaSb membranes grown metamorphically on GaAs substrates using highly selective substrate removal etch processes

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

Lavrova, Olga; Balakrishnan, Ganesh

2017-02-24

The etch rates of NH 4OH:H 2O 2 and C 6H 8O 7:H 2O 2 for GaAs and GaSb have been investigated to develop a selective etch for GaAs substrates and to isolate GaSb epilayers grown on GaAs. The NH 4OH:H 2O 2 solution has a greater etch rate differential for the GaSb/GaAs material system than C 6H 8O 7:H 2O 2 solution. The selectivity of NH 4OH:H 2O 2 for GaAs/GaSb under optimized etch conditions has been observed to be as high as 11471 ± 1691 whereas that of C 6H 8O 7:H 2O 2 has been measured upmore » to 143 ± 2. The etch contrast has been verified by isolating 2 μm thick GaSb epi-layers that were grown on GaAs substrates. GaSb membranes were tested and characterized with high-resolution X-Ray diffraction (HR-XRD) and atomic force microscopy (AFM).« less

Quantum-enhanced feature selection with forward selection and backward elimination

NASA Astrophysics Data System (ADS)

He, Zhimin; Li, Lvzhou; Huang, Zhiming; Situ, Haozhen

2018-07-01

Feature selection is a well-known preprocessing technique in machine learning, which can remove irrelevant features to improve the generalization capability of a classifier and reduce training and inference time. However, feature selection is time-consuming, particularly for the applications those have thousands of features, such as image retrieval, text mining and microarray data analysis. It is crucial to accelerate the feature selection process. We propose a quantum version of wrapper-based feature selection, which converts a classical feature selection to its quantum counterpart. It is valuable for machine learning on quantum computer. In this paper, we focus on two popular kinds of feature selection methods, i.e., wrapper-based forward selection and backward elimination. The proposed feature selection algorithm can quadratically accelerate the classical one.

Knowledge and intelligent computing system in medicine.

PubMed

Pandey, Babita; Mishra, R B

2009-03-01

Knowledge-based systems (KBS) and intelligent computing systems have been used in the medical planning, diagnosis and treatment. The KBS consists of rule-based reasoning (RBR), case-based reasoning (CBR) and model-based reasoning (MBR) whereas intelligent computing method (ICM) encompasses genetic algorithm (GA), artificial neural network (ANN), fuzzy logic (FL) and others. The combination of methods in KBS such as CBR-RBR, CBR-MBR and RBR-CBR-MBR and the combination of methods in ICM is ANN-GA, fuzzy-ANN, fuzzy-GA and fuzzy-ANN-GA. The combination of methods from KBS to ICM is RBR-ANN, CBR-ANN, RBR-CBR-ANN, fuzzy-RBR, fuzzy-CBR and fuzzy-CBR-ANN. In this paper, we have made a study of different singular and combined methods (185 in number) applicable to medical domain from mid 1970s to 2008. The study is presented in tabular form, showing the methods and its salient features, processes and application areas in medical domain (diagnosis, treatment and planning). It is observed that most of the methods are used in medical diagnosis very few are used for planning and moderate number in treatment. The study and its presentation in this context would be helpful for novice researchers in the area of medical expert system.

Cell division inhibitors with efficacy equivalent to isoniazid in the acute murine Mycobacterium tuberculosis infection model

PubMed Central

Knudson, Susan E.; Awasthi, Divya; Kumar, Kunal; Carreau, Alexandra; Goullieux, Laurent; Lagrange, Sophie; Vermet, Hélène; Ojima, Iwao; Slayden, Richard A.

2015-01-01

Objectives The increasing number of clinical strains resistant to one or more of the front-line TB drugs complicates the management of this disease. To develop next-generation benzimidazole-based FtsZ inhibitors with improved efficacy, we employed iterative optimization strategies based on whole bacteria potency, bactericidal activity, plasma and metabolic stability and in vivo efficacy studies. Methods Candidate benzimidazoles were evaluated for potency against Mycobacterium tuberculosis H37Rv and select clinical strains, toxicity against Vero cells and compound stability in plasma and liver microsomes. The efficacy of lead compounds was assessed in the acute murine M. tuberculosis infection model via intraperitoneal and oral routes. Results MICs of SB-P17G-A33, SB-P17G-A38 and SB-P17G-A42 for M. tuberculosis H37Rv and select clinical strains were 0.18–0.39 mg/L. SB-P17G-A38 and SB-P17G-A42 delivered at 50 mg/kg twice daily intraperitoneally or orally demonstrated efficacy in reducing the bacterial load by 5.7–6.3 log10 cfu in the lungs and 3.9–5.0 log10 cfu in the spleen. SB-P17G-A33 delivered at 50 mg/kg twice daily intraperitoneally or orally also reduced the bacterial load by 1.7–2.1 log10 cfu in the lungs and 2.5–3.4 log10 cfu in the spleen. Conclusions Next-generation benzimidazoles with excellent potency and efficacy against M. tuberculosis have been developed. This is the first report on benzimidazole-based FtsZ inhibitors showing an equivalent level of efficacy to isoniazid in an acute murine M. tuberculosis infection model. PMID:26245639

Colloidal nickel/gallium nanoalloys obtained from organometallic precursors in conventional organic solvents and in ionic liquids: noble-metal-free alkyne semihydrogenation catalysts

NASA Astrophysics Data System (ADS)

Schütte, Kai; Doddi, Adinarayana; Kroll, Clarissa; Meyer, Hajo; Wiktor, Christian; Gemel, Christian; van Tendeloo, Gustaaf; Fischer, Roland A.; Janiak, Christoph

2014-04-01

Efforts to replace noble-metal catalysts by low-cost alternatives are of constant interest. The organometallic, non-aqueous wet-chemical synthesis of various hitherto unknown nanocrystalline Ni/Ga intermetallic materials and the use of NiGa for the selective semihydrogenation of alkynes to alkenes are reported. Thermal co-hydrogenolysis of the all-hydrocarbon precursors [Ni(COD)2] (COD = 1,5-cyclooctadiene) and GaCp* (Cp* = pentamethylcyclopentadienyl) in high-boiling organic solvents mesitylene and n-decane in molar ratios of 1 : 1, 2 : 3 and 3 : 1 yields the nano-crystalline powder materials of the over-all compositions NiGa, Ni2Ga3 and Ni3Ga, respectively. Microwave induced co-pyrolysis of the same precursors without additional hydrogen in the ionic liquid [BMIm][BF4] (BMIm = 1-butyl-3-methyl-imidazolium) selectively yields the intermetallic phases NiGa and Ni3Ga from the respective 1 : 1 and 3 : 1 molar ratios of the precursors. The obtained materials are characterized by transmission electron microscopy (TEM), energy dispersive X-ray spectroscopy (EDX), IR, powder X-ray diffraction (PXRD) and atomic absorption spectroscopy (AAS). The single-source precursor [Ni(GaCp*)(PMe3)3] with a fixed Ni : Ga stoichiometry of 1 : 1 was employed as well. In comparison with the co-hydrogenolytic dual precursor source approach it turned out to be less practical due to inefficient nickel incorporation caused by the parasitic formation of stable [Ni(PMe3)4]. The use of ionic liquid [BMIm][BF4] as a non-conventional solvent to control the reaction and stabilize the nanoparticles proved to be particularly advantageous and stable colloids of the nanoalloys NiGa and Ni3Ga were obtained. A phase-selective Ni/Ga colloid synthesis in conventional solvents and in the presence of surfactants such as hexadecylamine (HDA) was not feasible due to the undesired reactivity of HDA with GaCp* leading to inefficient gallium incorporation. Recyclable NiGa nanoparticles selectively semihydrogenate 1-octyne and diphenylacetylene (tolan) to 1-octene and diphenylethylene, respectively, with a yield of about 90% and selectivities of up to 94 and 87%. Ni-NPs yield alkanes with a selectivity of 97 or 78%, respectively, under the same conditions.Efforts to replace noble-metal catalysts by low-cost alternatives are of constant interest. The organometallic, non-aqueous wet-chemical synthesis of various hitherto unknown nanocrystalline Ni/Ga intermetallic materials and the use of NiGa for the selective semihydrogenation of alkynes to alkenes are reported. Thermal co-hydrogenolysis of the all-hydrocarbon precursors [Ni(COD)2] (COD = 1,5-cyclooctadiene) and GaCp* (Cp* = pentamethylcyclopentadienyl) in high-boiling organic solvents mesitylene and n-decane in molar ratios of 1 : 1, 2 : 3 and 3 : 1 yields the nano-crystalline powder materials of the over-all compositions NiGa, Ni2Ga3 and Ni3Ga, respectively. Microwave induced co-pyrolysis of the same precursors without additional hydrogen in the ionic liquid [BMIm][BF4] (BMIm = 1-butyl-3-methyl-imidazolium) selectively yields the intermetallic phases NiGa and Ni3Ga from the respective 1 : 1 and 3 : 1 molar ratios of the precursors. The obtained materials are characterized by transmission electron microscopy (TEM), energy dispersive X-ray spectroscopy (EDX), IR, powder X-ray diffraction (PXRD) and atomic absorption spectroscopy (AAS). The single-source precursor [Ni(GaCp*)(PMe3)3] with a fixed Ni : Ga stoichiometry of 1 : 1 was employed as well. In comparison with the co-hydrogenolytic dual precursor source approach it turned out to be less practical due to inefficient nickel incorporation caused by the parasitic formation of stable [Ni(PMe3)4]. The use of ionic liquid [BMIm][BF4] as a non-conventional solvent to control the reaction and stabilize the nanoparticles proved to be particularly advantageous and stable colloids of the nanoalloys NiGa and Ni3Ga were obtained. A phase-selective Ni/Ga colloid synthesis in conventional solvents and in the presence of surfactants such as hexadecylamine (HDA) was not feasible due to the undesired reactivity of HDA with GaCp* leading to inefficient gallium incorporation. Recyclable NiGa nanoparticles selectively semihydrogenate 1-octyne and diphenylacetylene (tolan) to 1-octene and diphenylethylene, respectively, with a yield of about 90% and selectivities of up to 94 and 87%. Ni-NPs yield alkanes with a selectivity of 97 or 78%, respectively, under the same conditions. Electronic supplementary information (ESI) available: Ni-Ga phase diagrams, EDX (XPS) of NP1-NP8, table of Ni : Ga ratios, TG of Ni-Ga SSPs, analysis of NP4, dec. of [Ni(GaCp*)3(PCy3)] with characterization, local resolution EDX of NP3-IL, Ni-NP characterization from Ni(COD)2 and details of (semi-)hydrogenation catalysis. See DOI: 10.1039/c4nr00111g

Molecular descriptor subset selection in theoretical peptide quantitative structure-retention relationship model development using nature-inspired optimization algorithms.

PubMed

Žuvela, Petar; Liu, J Jay; Macur, Katarzyna; Bączek, Tomasz

2015-10-06

In this work, performance of five nature-inspired optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), firefly algorithm (FA), and flower pollination algorithm (FPA), was compared in molecular descriptor selection for development of quantitative structure-retention relationship (QSRR) models for 83 peptides that originate from eight model proteins. The matrix with 423 descriptors was used as input, and QSRR models based on selected descriptors were built using partial least squares (PLS), whereas root mean square error of prediction (RMSEP) was used as a fitness function for their selection. Three performance criteria, prediction accuracy, computational cost, and the number of selected descriptors, were used to evaluate the developed QSRR models. The results show that all five variable selection methods outperform interval PLS (iPLS), sparse PLS (sPLS), and the full PLS model, whereas GA is superior because of its lowest computational cost and higher accuracy (RMSEP of 5.534%) with a smaller number of variables (nine descriptors). The GA-QSRR model was validated initially through Y-randomization. In addition, it was successfully validated with an external testing set out of 102 peptides originating from Bacillus subtilis proteomes (RMSEP of 22.030%). Its applicability domain was defined, from which it was evident that the developed GA-QSRR exhibited strong robustness. All the sources of the model's error were identified, thus allowing for further application of the developed methodology in proteomics.

Genetic Particle Swarm Optimization-Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection.

PubMed

Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

2016-07-30

In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm.

The selectivity of water-based pyrophosphate recognition is tuned by metal substitution in dimetallic receptors.

PubMed

Svane, Simon; Kjeldsen, Frank; McKee, Vickie; McKenzie, Christine J

2015-07-14

The three dimetallic compounds [Ga2(bpbp)(OH)2(H2O)2](ClO4)3, [In2(bpbp)(CH3CO2)2](ClO4)3 and [Zn2(bpbp)(HCO2)2](ClO4) (bpbp(-) = 2,6-bis((N,N'-bis(2-picolyl)amino)methyl)-4-tertbutylphenolate) were evaluated as stable solid state precursors for reactive solution state receptors to use for the recognition of the biologically important anion pyrophosphate in water at neutral pH. Indicator displacement assays using in situ generated complex-pyrocatechol violet adducts, {M2(bpbp)(HxPV)}(n+) M = Ga(3+), In(3+), Zn(2+), were tested for selectivity in their reactions with a series of common anions: pyrophosphate, phosphate, ATP, arsenate, nitrate, perchlorate, chloride, sulfate, formate, carbonate and acetate. The receptor employing Ga(3+) showed a slow but visually detectable response (blue to yellow) in the presence of one equivalent of pyrophosphate but no response to any other anion, even when they were present in much higher concentrations. The systems based on In(3+) or Zn(2+) show less selectivity in accord with visibly discernible responses to several of the anions. These results demonstrate a facile method for increasing anion selectivity without modification of an organic dinucleating ligand scaffold. The comfortable supramolecular recognition of pyrophosphate by the dimetallic complexes is demonstrated by the single crystal X-ray structure of [Ga2(bpbp)(HP2O7)](ClO4)2 in which the pyrophosphate is coordinated to the two gallium ions via four of its oxygen atoms.

Doping concentration effect on performance of single QW double-heterostructure InGaN/AlGaN light emitting diode

NASA Astrophysics Data System (ADS)

Halim, N. Syafira Abdul; Wahid, M. Halim A.; Hambali, N. Azura M. Ahmad; Rashid, Shanise; Shahimin, Mukhzeer M.

2017-11-01

Light emitting diode (LED) employed a numerous applications such as displaying information, communication, sensing, illumination and lighting. In this paper, InGaN/AlGaN based on one quantum well (1QW) light emitting diode (LED) is modeled and studied numerically by using COMSOL Multiphysics 5.1 version. We have selected In0.06Ga0.94N as the active layer with thickness 50nm sandwiched between 0.15μm thick layers of p and n-type Al0.15Ga0.85N of cladding layers. We investigated an effect of doping concentration on InGaN/AlGaN double heterostructure of light-emitting diode (LED). Thus, energy levels, carrier concentration, electron concentration and forward voltage (IV) are extracted from the simulation results. As the doping concentration is increasing, the performance of threshold voltage, Vth on one quantum well (1QW) is also increases from 2.8V to 3.1V.

The role of titanium aluminide in n-gallium nitride ohmic contact technology

NASA Astrophysics Data System (ADS)

Pelto, Christopher M.

Ohmic contacts are essential to the realization of efficient and affordable nitride-based electronic and optoelectronic devices. Currently, the most successful ohmic contact schemes to n-GaN are based on the Al/Ti bilayer structure, although the mechanism responsible for the low resistance in these contacts is not sufficiently understood. In this work, the intermetallic TiAl3 has been employed both as a model ohmic contact system to help understand the essential features of the Al/Ti standard contact, as well as a thermally stable oxidation cap for the bilayer structure. A quaternary isotherm of the Al-Ti-Ga-N system was calculated at 600°C, which showed that a sufficient phase topology was present to apply the exchange mechanism to the TiAl 3/GaN couple. The exchange mechanism rationalized the selection of the TiAl3 intermetallic by predicting that an Al-rich AlGaN layer will form at the metal/semiconductor interface. As part of the investigation of these novel contact systems, a thorough characterization was undertaken on both a standard Al/Ti and Au/Ni/Al/Ti contact to n-GaN in which the essential processing parameters and metallurgical properties were identified. The TiAl 3 contact was found to exhibit inferior electrical behavior compared to the Al/Ti bilayer, requiring significantly higher annealing temperatures to achieve comparable specific contact resistance. It is conjectured that this is due to the early formation of a TiN layer at the metal/semiconductor interface of the bilayer contact, even though both contacts are suspected to form the Al-rich nitride layer at higher temperature. As an oxidation cap, the TiAl3 metallization was found to provide much improved performance characteristics compared to the four-layer Au/Al/Ni/Ti standard. The TiAl 3/Al/Ti contact proved to achieve optimal performance at a much lower temperature than the standard, and furthermore showed complete insensitivity to the oxidation content of the annealing ambient. Reaction mechanisms for the TiAl3-capped and the four-layer contact metallizations are suggested that account for both the morphology and the expected interfacial phases of each system.

Band engineered epitaxial 3D GaN-InGaN core-shell rod arrays as an advanced photoanode for visible-light-driven water splitting.

PubMed

Caccamo, Lorenzo; Hartmann, Jana; Fàbrega, Cristian; Estradé, Sonia; Lilienkamp, Gerhard; Prades, Joan Daniel; Hoffmann, Martin W G; Ledig, Johannes; Wagner, Alexander; Wang, Xue; Lopez-Conesa, Lluis; Peiró, Francesca; Rebled, José Manuel; Wehmann, Hergo-Heinrich; Daum, Winfried; Shen, Hao; Waag, Andreas

2014-02-26

3D single-crystalline, well-aligned GaN-InGaN rod arrays are fabricated by selective area growth (SAG) metal-organic vapor phase epitaxy (MOVPE) for visible-light water splitting. Epitaxial InGaN layer grows successfully on 3D GaN rods to minimize defects within the GaN-InGaN heterojunctions. The indium concentration (In ∼ 0.30 ± 0.04) is rather homogeneous in InGaN shells along the radial and longitudinal directions. The growing strategy allows us to tune the band gap of the InGaN layer in order to match the visible absorption with the solar spectrum as well as to align the semiconductor bands close to the water redox potentials to achieve high efficiency. The relation between structure, surface, and photoelectrochemical property of GaN-InGaN is explored by transmission electron microscopy (TEM), electron energy loss spectroscopy (EELS), Auger electron spectroscopy (AES), current-voltage, and open circuit potential (OCP) measurements. The epitaxial GaN-InGaN interface, pseudomorphic InGaN thin films, homogeneous and suitable indium concentration and defined surface orientation are properties demanded for systematic study and efficient photoanodes based on III-nitride heterojunctions.

Semiconductor CdF2:Ga and CdF2:In Crystals as Media for Real-Time Holography

PubMed Central

Ryskin, Alexander I.; Shcheulin, Alexander S.; Angervaks, Alexander E.

2012-01-01

Monocrystalline cadmium fluoride is a dielectric solid that can be converted into a semiconductor by doping with donor impurities and subsequent heating in the reduction atmosphere. For two donor elements, Ga and In, the donor (“shallow”) state is a metastable one separated from the ground (“deep”) state by a barrier. Photoinduced deep-to-shallow state transition underlies the photochromism of CdF2:Ga and CdF2:In. Real-time phase holograms are recorded in these crystals capable of following up optical processes in a wide frequency range. The features of photochromic transformations in CdF2:Ga and CdF2:In crystals as well as holographic characteristics of these media are discussed. Exemplary applications of CdF2-based holographic elements are given. PMID:28817009

Sensitivity of Fermi level position at Ga-polar, N-polar, and nonpolar m-plane GaN surfaces to vacuum and air ambient

NASA Astrophysics Data System (ADS)

Janicki, Łukasz; Ramírez-López, Manolo; Misiewicz, Jan; Cywiński, Grzegorz; Boćkowski, Michał; Muzioł, Grzegorz; Chèze, Caroline; Sawicka, Marta; Skierbiszewski, Czesław; Kudrawiec, Robert

2016-05-01

Ga-polar, N-polar, and nonpolar m-plane GaN UN+ structures have been examined in air and vacuum ambient by contactless electroreflectance (CER). This technique is very sensitive to the surface electric field that varies with the Fermi level position at the surface. For UN+ GaN structures [i.e., GaN (undoped)/GaN (n-type)/substrate], a homogeneous built-in electric field is expected in the undoped GaN layer that is manifested by Franz-Keldysh oscillation (FKO) in CER spectra. A clear change in FKO has been observed in CER spectra for N-polar and nonpolar m-plane structures when changing from air to vacuum ambient. This means that those surfaces are very sensitive to ambient atmosphere. In contrast to that, only a small change in FKO can be seen in the Ga-polar structure. This clearly shows that the ambient sensitivity of the Fermi level position at the GaN surface varies with the crystallographic orientation and is very high for N-polar and nonpolar m-plane surfaces. This feature of the N-polar and nonpolar m-plane surfaces can be very important for GaN-based devices grown on these crystallographic orientations and can be utilized in some of the devices, e.g., sensors.

QSAR modeling for anti-human African trypanosomiasis activity of substituted 2-Phenylimidazopyridines

NASA Astrophysics Data System (ADS)

Masand, Vijay H.; El-Sayed, Nahed N. E.; Mahajan, Devidas T.; Mercader, Andrew G.; Alafeefy, Ahmed M.; Shibi, I. G.

2017-02-01

In the present work, sixty substituted 2-Phenylimidazopyridines previously reported with potent anti-human African trypanosomiasis (HAT) activity were selected to build genetic algorithm (GA) based QSAR models to determine the structural features that have significant correlation with the activity. Multiple QSAR models were built using easily interpretable descriptors that are directly associated with the presence or the absence of a structural scaffold, or a specific atom. All the QSAR models have been thoroughly validated according to the OECD principles. All the QSAR models are statistically very robust (R2 = 0.80-0.87) with high external predictive ability (CCCex = 0.81-0.92). The QSAR analysis reveals that the HAT activity has good correlation with the presence of five membered rings in the molecule.

L2₁ and XA Ordering Competition in Hafnium-Based Full-Heusler Alloys Hf₂VZ (Z = Al, Ga, In, Tl, Si, Ge, Sn, Pb).

PubMed

Wang, Xiaotian; Cheng, Zhenxiang; Wang, Wenhong

2017-10-20

For theoretical designing of full-Heusler based spintroinc materials, people have long believed in the so-called Site Preference Rule (SPR). Very recently, according to the SPR, there are several studies on XA-type Hafnium-based Heusler alloys X₂YZ, i.e., Hf₂VAl, Hf₂CoZ (Z = Ga, In) and Hf₂CrZ (Z = Al, Ga, In). In this work, a series of Hf₂-based Heusler alloys, Hf₂VZ (Z = Al, Ga, In, Tl, Si, Ge, Sn, Pb), were selected as targets to study the site preferences of their atoms by first-principle calculations. It has been found that all of them are likely to exhibit the L2₁-type structure instead of the XA one. Furthermore, we reveal that the high values of spin-polarization of XA-type Hf₂VZ (Z = Al, Ga, In, Tl, Si, Ge, Sn, Pb) alloys have dropped dramatically when they form the L2₁-type structure. Also, we prove that the electronic, magnetic, and physics nature of these alloys are quite different, depending on the L2₁-type or XA-type structures.

Calculation of Electronic and Optical Properties of AgGaO2 Polymorphs Using Many-Body Approaches

NASA Astrophysics Data System (ADS)

Dadsetani, Mehrdad; Nejatipour, Reihan

2018-02-01

Ab initio calculations based on many-body perturbation theory have been used to study the electronic and optical properties of AgGaO2 in rhombohedral, hexagonal, and orthorhombic phases. GW calculations showed that AgGaO2 is an indirect-bandgap semiconductor in all three phases with energy bandgap of 2.35 eV, 2.23 eV, and 2.07 eV, in good agreement with available experimental values. By solving the Bethe-Salpeter equation (BSE) using the full potential linearized augmented plane wave basis, optical properties of the AgGaO2 polymorphs were calculated and compared with those obtained using the GW-corrected random phase approximation (RPA) and with existing experimental data. Strong anisotropy in the optical absorption spectra was observed, and the excitonic structures which were absent in the RPA calculations were reproduced in GWBSE calculations, in good agreement with the optical absorption spectrum of the rhombohedral phase. While modifying peak positions and intensities of the absorption spectra, the GWBSE gave rise to the redistribution of oscillator strengths. In comparison with the z-polarized response, excitonic effects in the x-polarized response were dominant. In the x- (and y-) polarized responses of r- and h-AgGaO2, spectral features and excitonic effects occur at the lower energies, but in the case of o-AgGaO2, the spectral structures of the z-polarized response occur at lower energies. In addition, the low-energy loss functions of AgGaO2 were calculated and compared using the GWBSE approach. Spectral features in the energy loss function components near the bandgap region were attributed to corresponding excitonic structures in the imaginary part of the dielectric function.

Variable selection based near infrared spectroscopy quantitative and qualitative analysis on wheat wet gluten

NASA Astrophysics Data System (ADS)

Lü, Chengxu; Jiang, Xunpeng; Zhou, Xingfan; Zhang, Yinqiao; Zhang, Naiqian; Wei, Chongfeng; Mao, Wenhua

2017-10-01

Wet gluten is a useful quality indicator for wheat, and short wave near infrared spectroscopy (NIRS) is a high performance technique with the advantage of economic rapid and nondestructive test. To study the feasibility of short wave NIRS analyzing wet gluten directly from wheat seed, 54 representative wheat seed samples were collected and scanned by spectrometer. 8 spectral pretreatment method and genetic algorithm (GA) variable selection method were used to optimize analysis. Both quantitative and qualitative model of wet gluten were built by partial least squares regression and discriminate analysis. For quantitative analysis, normalization is the optimized pretreatment method, 17 wet gluten sensitive variables are selected by GA, and GA model performs a better result than that of all variable model, with R2V=0.88, and RMSEV=1.47. For qualitative analysis, automatic weighted least squares baseline is the optimized pretreatment method, all variable models perform better results than those of GA models. The correct classification rates of 3 class of <24%, 24-30%, >30% wet gluten content are 95.45, 84.52, and 90.00%, respectively. The short wave NIRS technique shows potential for both quantitative and qualitative analysis of wet gluten for wheat seed.

Kernel-based Joint Feature Selection and Max-Margin Classification for Early Diagnosis of Parkinson’s Disease

NASA Astrophysics Data System (ADS)

Adeli, Ehsan; Wu, Guorong; Saghafi, Behrouz; An, Le; Shi, Feng; Shen, Dinggang

2017-01-01

Feature selection methods usually select the most compact and relevant set of features based on their contribution to a linear regression model. Thus, these features might not be the best for a non-linear classifier. This is especially crucial for the tasks, in which the performance is heavily dependent on the feature selection techniques, like the diagnosis of neurodegenerative diseases. Parkinson’s disease (PD) is one of the most common neurodegenerative disorders, which progresses slowly while affects the quality of life dramatically. In this paper, we use the data acquired from multi-modal neuroimaging data to diagnose PD by investigating the brain regions, known to be affected at the early stages. We propose a joint kernel-based feature selection and classification framework. Unlike conventional feature selection techniques that select features based on their performance in the original input feature space, we select features that best benefit the classification scheme in the kernel space. We further propose kernel functions, specifically designed for our non-negative feature types. We use MRI and SPECT data of 538 subjects from the PPMI database, and obtain a diagnosis accuracy of 97.5%, which outperforms all baseline and state-of-the-art methods.

Kernel-based Joint Feature Selection and Max-Margin Classification for Early Diagnosis of Parkinson’s Disease

PubMed Central

Adeli, Ehsan; Wu, Guorong; Saghafi, Behrouz; An, Le; Shi, Feng; Shen, Dinggang

2017-01-01

Feature selection methods usually select the most compact and relevant set of features based on their contribution to a linear regression model. Thus, these features might not be the best for a non-linear classifier. This is especially crucial for the tasks, in which the performance is heavily dependent on the feature selection techniques, like the diagnosis of neurodegenerative diseases. Parkinson’s disease (PD) is one of the most common neurodegenerative disorders, which progresses slowly while affects the quality of life dramatically. In this paper, we use the data acquired from multi-modal neuroimaging data to diagnose PD by investigating the brain regions, known to be affected at the early stages. We propose a joint kernel-based feature selection and classification framework. Unlike conventional feature selection techniques that select features based on their performance in the original input feature space, we select features that best benefit the classification scheme in the kernel space. We further propose kernel functions, specifically designed for our non-negative feature types. We use MRI and SPECT data of 538 subjects from the PPMI database, and obtain a diagnosis accuracy of 97.5%, which outperforms all baseline and state-of-the-art methods. PMID:28120883

Computerized decision support system for mass identification in breast using digital mammogram: a study on GA-based neuro-fuzzy approaches.

PubMed

Das, Arpita; Bhattacharya, Mahua

2011-01-01

In the present work, authors have developed a treatment planning system implementing genetic based neuro-fuzzy approaches for accurate analysis of shape and margin of tumor masses appearing in breast using digital mammogram. It is obvious that a complicated structure invites the problem of over learning and misclassification. In proposed methodology, genetic algorithm (GA) has been used for searching of effective input feature vectors combined with adaptive neuro-fuzzy model for final classification of different boundaries of tumor masses. The study involves 200 digitized mammograms from MIAS and other databases and has shown 86% correct classification rate.

Kinetics and docking studies of a COX-2 inhibitor isolated from Terminalia bellerica fruits.

PubMed

Reddy, Tamatam Chandramohan; Aparoy, Polamarasetty; Babu, Neela Kishore; Kumar, Kotha Anil; Kalangi, Suresh Kumar; Reddanna, Pallu

2010-10-01

Triphala is an Ayurvedic herbal formulation consisting of equal parts of three myrobalans: Terminalia chebula, Terminalia bellerica and Emblica officinalis. We recently reported that chebulagic acid (CA) isolated from Terminalia chebula is a potent COX-2/5-LOX dual inhibitor. In this study, compounds isolated from Terminalia bellerica were tested for inhibition against COX and 5-LOX. One of the fractionated compounds showed potent inhibition against COX enzymes with no inhibition against 5-LOX. It was identified as gallic acid (GA) by LC-MS, NMR and IR analyses. We report here the inhibitory effects of GA, with an IC(50) value of 74 nM against COX-2 and 1500 nM for COX-1, showing ≈20 fold preference towards COX-2. Further docking studies revealed that GA binds in the active site of COX-2 at the non-steroidal anti-inflammatory drug (NSAID) binding site. The carboxylate moiety of GA interacts with Arg120 and Glu524. Based on substrate dependent kinetics, GA was found to be a competitive inhibitor of both COX-1 and COX-2, with more affinity towards COX-2. Taken together, our studies indicate that GA is a selective inhibitor of COX-2. Being a small natural product with selective and reversible inhibition of COX-2, GA would form a lead molecule for developing potent anti-inflammatory drug candidates.

Attentional Selection Can Be Predicted by Reinforcement Learning of Task-relevant Stimulus Features Weighted by Value-independent Stickiness.

PubMed

Balcarras, Matthew; Ardid, Salva; Kaping, Daniel; Everling, Stefan; Womelsdorf, Thilo

2016-02-01

Attention includes processes that evaluate stimuli relevance, select the most relevant stimulus against less relevant stimuli, and bias choice behavior toward the selected information. It is not clear how these processes interact. Here, we captured these processes in a reinforcement learning framework applied to a feature-based attention task that required macaques to learn and update the value of stimulus features while ignoring nonrelevant sensory features, locations, and action plans. We found that value-based reinforcement learning mechanisms could account for feature-based attentional selection and choice behavior but required a value-independent stickiness selection process to explain selection errors while at asymptotic behavior. By comparing different reinforcement learning schemes, we found that trial-by-trial selections were best predicted by a model that only represents expected values for the task-relevant feature dimension, with nonrelevant stimulus features and action plans having only a marginal influence on covert selections. These findings show that attentional control subprocesses can be described by (1) the reinforcement learning of feature values within a restricted feature space that excludes irrelevant feature dimensions, (2) a stochastic selection process on feature-specific value representations, and (3) value-independent stickiness toward previous feature selections akin to perseveration in the motor domain. We speculate that these three mechanisms are implemented by distinct but interacting brain circuits and that the proposed formal account of feature-based stimulus selection will be important to understand how attentional subprocesses are implemented in primate brain networks.

Inclusion complex from cyclodextrin-grafted hyaluronic acid and pseudo protein as biodegradable nano-delivery vehicle for gambogic acid.

PubMed

Ji, Ying; Shan, Shuo; He, Mingyu; Chu, Chih-Chang

2017-10-15

β-Cyclodextrin can form inclusion complex with a series of guest molecules including phenyl moieties, and has gained considerable popularity in the study of supramolecular nanostructure. In this study, a biodegradable nanocomplex (HA(CD)-4Phe4 nanocomplex) was developed from β-cyclodextrin grafted hyaluronic acid (HA) and phenylalanine based poly(ester amide). The phenylalanine based poly(ester amide) is a biodegradable pseudo protein which provides the encapsulation capacity for gambogic acid (GA), a naturally-derived chemotherapeutic which has been effectively employed to treat multidrug resistant tumor. The therapeutic potency of free GA is limited due to its poor solubility in water and the lack of tumor-selective toxicity. The nanocomplex carrier enhanced the solubility and availability of GA in aqueous media, and the HA component enabled the targeted delivery to tumor cells with overexpression of CD44 receptors. In the presence of hyaluronidase, the release of GA from the nanocomplex was significantly accelerated, due to the enzymatic biodegradation of the carrier. Compared to free GA, GA-loaded nanocomplex exhibited improved cytotoxicity in MDA-MB-435/MDR multidrug resistant melanoma cells, and induced enhanced level of apoptosis and mitochondrial depolarization, at low concentration of GA (1-2µM). The nanocomplex enhanced the therapeutic potency of GA, especially when diluted in physiological environment. In addition, suppressed matrix metalloproteinase activity was also detected in MDA-MB-435/MDR cells treated by GA-loaded nanocomplex, which demonstrated its potency in the inhibition of tumor metastasis. The in vitro data suggested that HA(CD)-4Phe4 nanocomplex could provide a promising alternative in the treatment of multidrug resistant tumor cells. Gambogic acid (GA), naturally derived from genus Garcinia trees, exhibited significant cytotoxic activity against multiple types of tumors with resistance to traditional chemotherapeutics. Unfortunately, the poor solubility of GA in conventional pharmaceutical solvents and non-targeted distribution in normal tissues greatly limited its therapeutic potency. To overcome the challenges, we develop a nanoplatform from the supramolecular assembly of β-cyclodextrin grafted hyaluronic acid (HA) and phenylalanine based pseudo protein. The pseudo protein in the nanocomplex provided the hydrophobic interaction and loading capacity for GA, while the HA component targeted the overexpressed CD44 receptor and improved the selective endocytosis in multidrug resistant melanoma cells. The supramolecular nanocomplex provide a promising platform for the delivery of hydrophobic chemotherapeutics to improve the bioavailability and efficiency. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Mononuclear salen-gallium complexes for iso-selective ring-opening polymerization (ROP) of rac-lactide.

PubMed

Specklin, David; Fliedel, Christophe; Hild, Frédéric; Mameri, Samir; Karmazin, Lydia; Bailly, Corinne; Dagorne, Samuel

2017-10-03

A series of mononuclear salen-supported gallium amido/alkoxide derivatives were prepared and structurally characterized and subsequently used as initiators in rac-lactide ring-opening polymerisation (ROP). The reaction of variously substituted salen ligands (1a-1f) with 0.5 equiv. of Ga 2 (NMe 2 ) 6 allowed the isolation of the corresponding (salen)Ga-NMe 2 chelates (2b-2d, 2f) via an amine elimination route, as poorly soluble compounds in common solvents. The (salen)Ga-OBn derivatives (3a-3e) may be readily accessed by an amine-elimination/alcoholysis sequence and the molecular structures of 3a, 3d and 3e were confirmed through X-ray crystallography diffraction analysis. The present (salen)Ga-X species may effectively mediate the iso-selective ROP of rac-LA in a controlled manner (P m up to 0.77 using a 1/1 2f/BnOH mixture as ROP initiator), with a ROP activity greatly dependent upon steric hindrance and geometrical constraints imposed by the variously substituted salen ligands. Based on the present study, salen ligands with limited steric hindrance and a certain degree of flexibility appear best suited for iso-selective ROP by (salen)Ga chelates. The salen-gallium complex 3a is also effective for the controlled ROP of ε-caprolactone (CL) and the production of PCL-b-PLA copolymers.

Features of the Percolation Scheme of Vibrational Spectrum Reconstruction in the Ga1 - x Al x P Alloy

NASA Astrophysics Data System (ADS)

Kozyrev, S. P.

2018-04-01

Specific features of the properties of Ga-P lattice vibrations have been investigated using the percolation model of a mixed Ga1 - x Al x P crystal (alloy) with zero lattice mismatch between binary components of the alloy. In contrast to other two-mode alloy systems, in Ga1 - x Al x P a percolation splitting of δ 13 cm-1 is observed for the low-frequency mode of GaP-like vibrations. An additional GaP mode (one of the percolation doublet components) split from the fundamental mode is observed for the GaP-rich alloy, which coincides in frequency with the gap corresponding to the zero density of one-phonon states of the GaP crystal. The vibrational spectrum of impurity Al in the GaP crystal has been calculated using the theory of crystal lattice dynamics. Upon substitution of lighter Al for the Ga atom, the calculated spectrum includes, along with the local mode, a singularity near the gap with the zero density of phonon states of the GaP crystal, which coincides with the mode observed experimentally at a frequency of 378 cm-1 in the Ga1 - x Al x P ( x < 0.4) alloy.

Layered Structures and Disordered Polyanionic Nets in the Cation-Poor Polar Intermetallics CsAu 1.4 Ga 2.8 and CsAu 2 Ga 2.6

DOE PAGES

Smetana, Volodymyr; Steinberg, Simon; Mudring, Anja-Verena

2016-12-27

Gold intermetallics are known for their unusual structures and bonding patterns. Two new compounds have been discovered in the cation-poor part of the Cs–Au–Ga system. We obtained both compounds directly by heating the elements at elevated temperatures. Structure determinations based on single-crystal X-ray diffraction analyses revealed two structurally and compositionally related formations: CsAu 1.4Ga 2.8 (I) and CsAu 2Ga 2.6 (II) crystallize in their own structure types (I: Rmore » $$\\bar{3}$$, a = 11.160(2) Å, c = 21.706(4) Å, Z = 18; II: R$$\\bar{3}$$, a = 11.106(1) Å, Å, c = 77.243(9) Å, Z = 54) and contain hexagonal cationic layers of cesium. Furthermore, this is a unique structural motif, which has never been observed for the other (lighter) alkali metals in combination with Au and post transition elements. The polyanionic part is characterized in contrast by Au/Ga tetrahedral stars, a structural feature that is characteristic for light alkali metal representatives, and disordered sites with mixed Au/Ga occupancies that occur in both structures with a more significant disorder in the polyanionic component of CsAu 2Ga 2.6. Examinations of the electronic band structure for a model approximating the composition of CsAu 1.4Ga 2.8 have been completed using density-functional-theory-based methods and reveal a deep pseudogap at E F. Bonding analysis by evaluating the crystal orbital Hamilton populations show dominant heteroatomic Au–Ga bonds and only a negligible contribution from Cs pairs.« less

Ground Vibration Test Planning and Pre-Test Analysis for the X-33 Vehicle

NASA Technical Reports Server (NTRS)

Bedrossian, Herand; Tinker, Michael L.; Hidalgo, Homero

2000-01-01

This paper describes the results of the modal test planning and the pre-test analysis for the X-33 vehicle. The pre-test analysis included the selection of the target modes, selection of the sensor and shaker locations and the development of an accurate Test Analysis Model (TAM). For target mode selection, four techniques were considered, one based on the Modal Cost technique, one based on Balanced Singular Value technique, a technique known as the Root Sum Squared (RSS) method, and a Modal Kinetic Energy (MKE) approach. For selecting sensor locations, four techniques were also considered; one based on the Weighted Average Kinetic Energy (WAKE), one based on Guyan Reduction (GR), one emphasizing engineering judgment, and one based on an optimum sensor selection technique using Genetic Algorithm (GA) search technique combined with a criteria based on Hankel Singular Values (HSV's). For selecting shaker locations, four techniques were also considered; one based on the Weighted Average Driving Point Residue (WADPR), one based on engineering judgment and accessibility considerations, a frequency response method, and an optimum shaker location selection based on a GA search technique combined with a criteria based on HSV's. To evaluate the effectiveness of the proposed sensor and shaker locations for exciting the target modes, extensive numerical simulations were performed. Multivariate Mode Indicator Function (MMIF) was used to evaluate the effectiveness of each sensor & shaker set with respect to modal parameter identification. Several TAM reduction techniques were considered including, Guyan, IRS, Modal, and Hybrid. Based on a pre-test cross-orthogonality checks using various reduction techniques, a Hybrid TAM reduction technique was selected and was used for all three vehicle fuel level configurations.

Genetic Particle Swarm Optimization–Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection

PubMed Central

Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

2016-01-01

In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm. PMID:27483285

Development of GaAs/Si and GaAs/Si monolithic structures for future space solar cells

NASA Technical Reports Server (NTRS)

Spitzer, M. B.; Vernon, S. M.; Wolfson, R. G.; Tobin, S. P.

1984-01-01

The results of heteroepitaxial growth of GaAs and GaAlAs directly on Si are presented, and applications to new cell structures are suggested. The novel feature is the elimination of a Ge lattice transition region. This feature not only reduces the cost of substrate preparation, but also makes possible the fabrication of high efficiency monolithic cascade structures. All films to be discussed were grown by organometallic chemical vapor deposition at atmospheric pressure. This process yielded reproducible, large-area films of GaAs, grown directly on Si, that are tightly adherent and smooth, and are characterized by a defect density of 5 x 10(6) power/sq cm. Preliminary studies indicate that GaAlAs can also be grown in this way. A number of promising applications are suggested. Certainly these substrates are ideal for low-weight GaAs space solar ells. For very high efficiency, the absence of Ge makes the technology attractive for GaAlAs/Si monolithic cascades, in which the Si substrates would first be provided with a suitable p/n junction. An evaluation of a three bandgap cascade consisting of appropriately designed GaAlAs/GaAs/Si layers is also presented.

1550-nm Driven ErAs:In(Al)GaAs Photoconductor-Based Terahertz Time Domain System with 6.5 THz Bandwidth

NASA Astrophysics Data System (ADS)

Nandi, U.; Norman, J. C.; Gossard, A. C.; Lu, H.; Preu, S.

2018-04-01

ErAs:In(Al)GaAs superlattice photoconductors are grown using molecular beam epitaxy (MBE) with excellent material characteristics for terahertz time-domain spectroscopy (TDS) systems operating at 1550 nm. The transmitter material (Tx) features a record resistivity of 3.85 kΩcm and record breakdown field strength of 170 ± 40 kV/cm (dark) and 130 ± 20 kV/cm (illuminated with 45 mW laser power). Receivers (Rx) with different superlattice structures were fabricated showing very high mobility (775 cm2/Vs). The TDS system using these photoconductors features a bandwidth larger than 6.5 THz with a laser power of 45 mW at Tx and 16 mW at Rx.

Variable selection in near-infrared spectroscopy: benchmarking of feature selection methods on biodiesel data.

PubMed

Balabin, Roman M; Smirnov, Sergey V

2011-04-29

During the past several years, near-infrared (near-IR/NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields from petroleum to biomedical sectors. The NIR spectrum (above 4000 cm(-1)) of a sample is typically measured by modern instruments at a few hundred of wavelengths. Recently, considerable effort has been directed towards developing procedures to identify variables (wavelengths) that contribute useful information. Variable selection (VS) or feature selection, also called frequency selection or wavelength selection, is a critical step in data analysis for vibrational spectroscopy (infrared, Raman, or NIRS). In this paper, we compare the performance of 16 different feature selection methods for the prediction of properties of biodiesel fuel, including density, viscosity, methanol content, and water concentration. The feature selection algorithms tested include stepwise multiple linear regression (MLR-step), interval partial least squares regression (iPLS), backward iPLS (BiPLS), forward iPLS (FiPLS), moving window partial least squares regression (MWPLS), (modified) changeable size moving window partial least squares (CSMWPLS/MCSMWPLSR), searching combination moving window partial least squares (SCMWPLS), successive projections algorithm (SPA), uninformative variable elimination (UVE, including UVE-SPA), simulated annealing (SA), back-propagation artificial neural networks (BP-ANN), Kohonen artificial neural network (K-ANN), and genetic algorithms (GAs, including GA-iPLS). Two linear techniques for calibration model building, namely multiple linear regression (MLR) and partial least squares regression/projection to latent structures (PLS/PLSR), are used for the evaluation of biofuel properties. A comparison with a non-linear calibration model, artificial neural networks (ANN-MLP), is also provided. Discussion of gasoline, ethanol-gasoline (bioethanol), and diesel fuel data is presented. The results of other spectroscopic techniques application, such as Raman, ultraviolet-visible (UV-vis), or nuclear magnetic resonance (NMR) spectroscopies, can be greatly improved by an appropriate feature selection choice. Copyright © 2011 Elsevier B.V. All rights reserved.

Selectivity of the gas sensor based on the 50%In2O3-50%Ga2O3 thin film in dynamic mode of operation

NASA Astrophysics Data System (ADS)

Demin, I. E.; Kozlov, A. G.

2018-01-01

The article considers the gas sensor with the sensitive layer based on the 50%In2O3 -50%Ga2O3 thin film. The temperature and concentration dependencies of gas-induced resistance response of this sensor and the dynamical dependencies of its resistance response on the test gases in air are investigated. The test gases were ethanol, acetone, ammonia and liquefied petroleum gas. The information parameters of the sensor in the dynamical mode of operation were considered to improve its selectivity. The presented results show that the selectivity of the sensor in this mode may be improved by using the following information parameters: gas-induced resistance response in steady state, activation energy of the response and pre-exponential factor of the temperature dependence of the response time constant.

Optical properties of beryllium-doped GaSb epilayers grown on GaAs substrate

NASA Astrophysics Data System (ADS)

Deng, Zhuo; Chen, Baile; Chen, Xiren; Shao, Jun; Gong, Qian; Liu, Huiyun; Wu, Jiang

2018-05-01

In this work, the effects of p-type beryllium (Be) doping on the optical properties of GaSb epilayers grown on GaAs substrate by Molecular Beam Epitaxy (MBE) have been studied. Temperature- and excitation power-dependent photoluminescence (PL) measurements were performed on both nominally undoped and intentionally Be-doped GaSb layers. Clear PL emissions are observable even at the temperature of 270 K from both layers, indicating the high material quality. In the Be-doped GaSb layer, the transition energies of main PL features exhibit red-shift up to ∼7 meV, and the peak widths characterized by Full-Width-at-Half-Maximum (FWHM) also decrease. In addition, analysis on the PL integrated intensity in the Be-doped sample reveals a gain of emission signal, as well as a larger carrier thermal activation energy. These distinctive PL behaviors identified in the Be-doped GaSb layer suggest that the residual compressive strain is effectively relaxed in the epilayer, due possibly to the reduction of dislocation density in the GaSb layer with the intentional incorporation of Be dopants. Our results confirm the role of Be as a promising dopant in the improvement of crystalline quality in GaSb, which is a crucial factor for growth and fabrication of high quality strain-free GaSb-based devices on foreign substrates.

Absorption enhancement in type-II coupled quantum rings due to existence of quasi-bound states

NASA Astrophysics Data System (ADS)

Hsieh, Chi-Ti; Lin, Shih-Yen; Chang, Shu-Wei

2018-02-01

The absorption of type-II nanostructures is often weaker than type-I counterpart due to spatially separated electrons and holes. We model the bound-to-continuum absorption of type-II quantum rings (QRs) using a multiband source-radiation approach using the retarded Green function in the cylindrical coordinate system. The selection rules due to the circular symmetry for allowed transitions of absorption are utilized. The bound-tocontinuum absorptions of type-II GaSb coupled and uncoupled QRs embedded in GaAs matrix are compared here. The GaSb QRs act as energy barriers for electrons but potential wells for holes. For the coupled QR structure, the region sandwiched between two QRs forms a potential reservoir of quasi-bound electrons. Electrons in these states, though look like bound ones, would ultimately tunnel out of the reservoir through barriers. Multiband perfectly-matched layers are introduced to model the tunneling of quasi-bound states into open space. Resonance peaks are observed on the absorption spectra of type-II coupled QRs due to the formation of quasi-bound states in conduction bands, but no resonance exist in the uncoupled QR. The tunneling time of these metastable states can be extracted from the resonance and is in the order of ten femtoseconds. Absorption of coupled QRs is significantly enhanced as compared to that of uncoupled ones in certain spectral windows of interest. These features may improve the performance of photon detectors and photovoltaic devices based on type-II semiconductor nanostructures.

InGaN based micro light emitting diodes featuring a buried GaN tunnel junction

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

Malinverni, M., E-mail: marco.malinverni@epfl.ch; Martin, D.; Grandjean, N.

GaN tunnel junctions (TJs) are grown by ammonia molecular beam epitaxy. High doping levels are achieved with a net acceptor concentration close to ∼10{sup 20 }cm{sup −3}, thanks to the low growth temperature. This allows for the realization of p-n junctions with ultrathin depletion width enabling efficient interband tunneling. n-p-n structures featuring such a TJ exhibit low leakage current densities, e.g., <5 × 10{sup −5} A cm{sup −2} at reverse bias of 10 V. Under forward bias, the voltage is 3.3 V and 4.8 V for current densities of 20 A cm{sup −2} and 2000 A cm{sup −2}, respectively. The specific series resistance of the whole device ismore » 3.7 × 10{sup −4} Ω cm{sup 2}. Then micro-light emitting diodes (μ-LEDs) featuring buried TJs are fabricated. Excellent current confinement is demonstrated together with homogeneous electrical injection, as seen on electroluminescence mapping. Finally, the I-V characteristics of μ-LEDs with various diameters point out the role of the access resistance at the current aperture edge.« less

Selective-area growth of GaN nanocolumns on Si(111) substrates for application to nanocolumn emitters with systematic analysis of dislocation filtering effect of nanocolumns

NASA Astrophysics Data System (ADS)

Kishino, Katsumi; Ishizawa, Shunsuke

2015-06-01

The growth of highly uniform arrays of GaN nanocolumns with diameters from 122 to 430 nm on Si (111) substrates was demonstrated. The employment of GaN film templates with flat surfaces (root mean square surface roughness of 0.84 nm), which were obtained using an AlN/GaN superlattice (SL) buffer on Si, contributed to the high-quality selective-area growth of nanocolumns using a thin Ti mask of 5 nm thickness by rf-plasma-assisted molecular beam epitaxy. Although the GaN template included a large number of dislocations (dislocation density ˜1011 cm-2), the dislocation filtering effect of nanocolumns was enhanced with decreasing nanocolumn diameters (D). Systematic transmission electron microscopy (TEM) observation enabled us to explain the dependence of the dislocation propagation behavior in nanocolumns on the nanocolumn diameter for the first time. Plan-view TEM analysis was performed for nanocolumns with D = 120-324 nm by slicing the nanocolumns horizontally at a height of ˜300 nm above their bottoms and dislocation propagation through the nanocolumns was analyzed by the cross-sectional TEM observation of nanocolumns with D ˜ 200 nm. It was clarified that dislocations were effectively filtered in the bottom 300 nm region of the nanocolumns, the dislocation density of the nanocolumns decreased with decreasing D, and for narrow nanocolumns with D < 200 nm, dislocation-free crystals were obtained in the upper part of the nanocolumns. The dramatic improvement in the emission properties of GaN nanocolumns observed with decreasing diameter is discussed in relation to the decreased dislocation density. The laser action of InGaN/GaN-based nanocolumn arrays with a nanocolumn diameter of 170 nm and a period of 200 nm on Si under optical excitation was obtained with an emission wavelength of 407 nm. We also fabricated red-emitting InGaN-based nanocolumn light-emitting diodes on Si that operated at a wavelength of 652 nm, demonstrating vertical conduction through the AlN/GaN SL buffer to the Si substrate.

Gallium based low-interaction anions

DOEpatents

King, Wayne A.; Kubas, Gregory J.

2000-01-01

The present invention provides: a composition of the formula M.sup.+x (Ga(Y).sub.4.sup.-).sub.x where M is a metal selected from the group consisting of lithium, sodium, potassium, cesium, calcium, strontium, thallium, and silver, x is an integer selected from the group consisting of 1 or 2, each Y is a ligand selected from the group consisting of aryl, alkyl, hydride and halide with the proviso that at least one Y is a ligand selected from the group consisting of aryl, alkyl and halide; a composition of the formula (R).sub.x Q.sup.+ Ga(Y).sub.4.sup.- where Q is selected from the group consisting of carbon, nitrogen, sulfur, phosphorus and oxygen, each R is a ligand selected from the group consisting of alkyl, aryl, and hydrogen, x is an integer selected from the group consisting of 3 and 4 depending upon Q, and each Y is a ligand selected from the group consisting of aryl, alkyl, hydride and halide with the proviso that at least one Y is a ligand selected from the group consisting of aryl, alkyl and halide; an ionic polymerization catalyst composition including an active cationic portion and a gallium based weakly coordinating anion; and bridged anion species of the formula M.sup.+x.sub.y [X(Ga(Y.sub.3).sub.z ].sup.-y.sub.x where M is a metal selected from the group consisting of lithium, sodium, potassium, magnesium, cesium, calcium, strontium, thallium, and silver, x is an integer selected from the group consisting of 1 or 2, X is a bridging group between two gallium atoms, y is an integer selected from the group consisting 1 and 2, z is an integer of at least 2, each Y is a ligand selected from the group consisting of aryl, alkyl, hydride and halide with the proviso that at least one Y is a ligand selected from the group consisting of aryl, alkyl and halide.

The fate of task-irrelevant visual motion: perceptual load versus feature-based attention.

PubMed

Taya, Shuichiro; Adams, Wendy J; Graf, Erich W; Lavie, Nilli

2009-11-18

We tested contrasting predictions derived from perceptual load theory and from recent feature-based selection accounts. Observers viewed moving, colored stimuli and performed low or high load tasks associated with one stimulus feature, either color or motion. The resultant motion aftereffect (MAE) was used to evaluate attentional allocation. We found that task-irrelevant visual features received less attention than co-localized task-relevant features of the same objects. Moreover, when color and motion features were co-localized yet perceived to belong to two distinct surfaces, feature-based selection was further increased at the expense of object-based co-selection. Load theory predicts that the MAE for task-irrelevant motion would be reduced with a higher load color task. However, this was not seen for co-localized features; perceptual load only modulated the MAE for task-irrelevant motion when this was spatially separated from the attended color location. Our results suggest that perceptual load effects are mediated by spatial selection and do not generalize to the feature domain. Feature-based selection operates to suppress processing of task-irrelevant, co-localized features, irrespective of perceptual load.

Piezo-Phototronic Effect in a Quantum Well Structure.

PubMed

Huang, Xin; Du, Chunhua; Zhou, Yongli; Jiang, Chunyan; Pu, Xiong; Liu, Wei; Hu, Weiguo; Chen, Hong; Wang, Zhong Lin

2016-05-24

With enhancements in the performance of optoelectronic devices, the field of piezo-phototronics has attracted much attention, and several theoretical works have been reported based on semiclassical models. At present, the feature size of optoelectronic devices are rapidly shrinking toward several tens of nanometers, which results in the quantum confinement effect. Starting from the basic piezoelectricity equation, Schrödinger equation, Poisson equation, and Fermi's golden rule, a self-consistent theoretical model is proposed to study the piezo-phototronic effect in the framework of perturbation theory in quantum mechanics. The validity and universality of this model are well-proven with photoluminescence measurements in a single GaN/InGaN quantum well and multiple GaN/InGaN quantum wells. This study provides important insight into the working principle of nanoscale piezo-phototronic devices as well as guidance for the future device design.

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

Guo, Wei, E-mail: wguo2@ncsu.edu; Kirste, Ronny; Bryan, Zachary

Enhanced light extraction efficiency was demonstrated on nanostructure patterned GaN and AlGaN/AlN Multiple-Quantum-Well (MQW) structures using mass production techniques including natural lithography and interference lithography with feature size as small as 100 nm. Periodic nanostructures showed higher light extraction efficiency and modified emission profile compared to non-periodic structures based on integral reflection and angular-resolved transmission measurement. Light extraction mechanism of macroscopic and microscopic nanopatterning is discussed, and the advantage of using periodic nanostructure patterning is provided. An enhanced photoluminescence emission intensity was observed on nanostructure patterned AlGaN/AlN MQW compared to as-grown structure, demonstrating a large-scale and mass-producible pathway to higher lightmore » extraction efficiency in deep-ultra-violet light-emitting diodes.« less

Feature Selection Using Information Gain for Improved Structural-Based Alert Correlation

PubMed Central

Siraj, Maheyzah Md; Zainal, Anazida; Elshoush, Huwaida Tagelsir; Elhaj, Fatin

2016-01-01

Grouping and clustering alerts for intrusion detection based on the similarity of features is referred to as structurally base alert correlation and can discover a list of attack steps. Previous researchers selected different features and data sources manually based on their knowledge and experience, which lead to the less accurate identification of attack steps and inconsistent performance of clustering accuracy. Furthermore, the existing alert correlation systems deal with a huge amount of data that contains null values, incomplete information, and irrelevant features causing the analysis of the alerts to be tedious, time-consuming and error-prone. Therefore, this paper focuses on selecting accurate and significant features of alerts that are appropriate to represent the attack steps, thus, enhancing the structural-based alert correlation model. A two-tier feature selection method is proposed to obtain the significant features. The first tier aims at ranking the subset of features based on high information gain entropy in decreasing order. The‏ second tier extends additional features with a better discriminative ability than the initially ranked features. Performance analysis results show the significance of the selected features in terms of the clustering accuracy using 2000 DARPA intrusion detection scenario-specific dataset. PMID:27893821

Temperature sensing using a Cr:ZnGa2O4 new phosphor

NASA Astrophysics Data System (ADS)

Sharma, S. K.; Glais, E.; Pellerin, M.; Chaneac, C.; Viana, B.

2016-02-01

The luminescence emission of a thermographic phosphor based on trivalent chromium doped ZGO (ZnGa2O4) bulk as well as nanoparticles is here reported. This material has a strong temperature dependence on the optical features such as ratio of their emission bands, bandwidths, bands position as well as the lifetime decay of the Cr3+. This makes this material well suitable as temperature sensor. ZnGa2O4 (ZGO), a normal spinel, exhibits a high brightness persistent luminescence, when doped with Cr3+ ions and shows an emission spectrum centered at 695 nm. At the nanometric scale, ZGO is used for in vivo imaging with a better signal to background ratio than classical fluorescent NIR probes. In this work we investigate the ability of the host to be a new thermographic phosphor. Several optical features are investigated in a broad temperature range (10 K-700 K). A comparison between bulk material and nanoparticles is introduced. The obtained results could be used to determine the optimal design parameters for sensor development.

Mutual information criterion for feature selection with application to classification of breast microcalcifications

NASA Astrophysics Data System (ADS)

Diamant, Idit; Shalhon, Moran; Goldberger, Jacob; Greenspan, Hayit

2016-03-01

Classification of clustered breast microcalcifications into benign and malignant categories is an extremely challenging task for computerized algorithms and expert radiologists alike. In this paper we present a novel method for feature selection based on mutual information (MI) criterion for automatic classification of microcalcifications. We explored the MI based feature selection for various texture features. The proposed method was evaluated on a standardized digital database for screening mammography (DDSM). Experimental results demonstrate the effectiveness and the advantage of using the MI-based feature selection to obtain the most relevant features for the task and thus to provide for improved performance as compared to using all features.

McTwo: a two-step feature selection algorithm based on maximal information coefficient.

PubMed

Ge, Ruiquan; Zhou, Manli; Luo, Youxi; Meng, Qinghan; Mai, Guoqin; Ma, Dongli; Wang, Guoqing; Zhou, Fengfeng

2016-03-23

High-throughput bio-OMIC technologies are producing high-dimension data from bio-samples at an ever increasing rate, whereas the training sample number in a traditional experiment remains small due to various difficulties. This "large p, small n" paradigm in the area of biomedical "big data" may be at least partly solved by feature selection algorithms, which select only features significantly associated with phenotypes. Feature selection is an NP-hard problem. Due to the exponentially increased time requirement for finding the globally optimal solution, all the existing feature selection algorithms employ heuristic rules to find locally optimal solutions, and their solutions achieve different performances on different datasets. This work describes a feature selection algorithm based on a recently published correlation measurement, Maximal Information Coefficient (MIC). The proposed algorithm, McTwo, aims to select features associated with phenotypes, independently of each other, and achieving high classification performance of the nearest neighbor algorithm. Based on the comparative study of 17 datasets, McTwo performs about as well as or better than existing algorithms, with significantly reduced numbers of selected features. The features selected by McTwo also appear to have particular biomedical relevance to the phenotypes from the literature. McTwo selects a feature subset with very good classification performance, as well as a small feature number. So McTwo may represent a complementary feature selection algorithm for the high-dimensional biomedical datasets.

Max-AUC Feature Selection in Computer-Aided Detection of Polyps in CT Colonography

PubMed Central

Xu, Jian-Wu; Suzuki, Kenji

2014-01-01

We propose a feature selection method based on a sequential forward floating selection (SFFS) procedure to improve the performance of a classifier in computerized detection of polyps in CT colonography (CTC). The feature selection method is coupled with a nonlinear support vector machine (SVM) classifier. Unlike the conventional linear method based on Wilks' lambda, the proposed method selected the most relevant features that would maximize the area under the receiver operating characteristic curve (AUC), which directly maximizes classification performance, evaluated based on AUC value, in the computer-aided detection (CADe) scheme. We presented two variants of the proposed method with different stopping criteria used in the SFFS procedure. The first variant searched all feature combinations allowed in the SFFS procedure and selected the subsets that maximize the AUC values. The second variant performed a statistical test at each step during the SFFS procedure, and it was terminated if the increase in the AUC value was not statistically significant. The advantage of the second variant is its lower computational cost. To test the performance of the proposed method, we compared it against the popular stepwise feature selection method based on Wilks' lambda for a colonic-polyp database (25 polyps and 2624 nonpolyps). We extracted 75 morphologic, gray-level-based, and texture features from the segmented lesion candidate regions. The two variants of the proposed feature selection method chose 29 and 7 features, respectively. Two SVM classifiers trained with these selected features yielded a 96% by-polyp sensitivity at false-positive (FP) rates of 4.1 and 6.5 per patient, respectively. Experiments showed a significant improvement in the performance of the classifier with the proposed feature selection method over that with the popular stepwise feature selection based on Wilks' lambda that yielded 18.0 FPs per patient at the same sensitivity level. PMID:24608058

Max-AUC feature selection in computer-aided detection of polyps in CT colonography.

PubMed

Xu, Jian-Wu; Suzuki, Kenji

2014-03-01

We propose a feature selection method based on a sequential forward floating selection (SFFS) procedure to improve the performance of a classifier in computerized detection of polyps in CT colonography (CTC). The feature selection method is coupled with a nonlinear support vector machine (SVM) classifier. Unlike the conventional linear method based on Wilks' lambda, the proposed method selected the most relevant features that would maximize the area under the receiver operating characteristic curve (AUC), which directly maximizes classification performance, evaluated based on AUC value, in the computer-aided detection (CADe) scheme. We presented two variants of the proposed method with different stopping criteria used in the SFFS procedure. The first variant searched all feature combinations allowed in the SFFS procedure and selected the subsets that maximize the AUC values. The second variant performed a statistical test at each step during the SFFS procedure, and it was terminated if the increase in the AUC value was not statistically significant. The advantage of the second variant is its lower computational cost. To test the performance of the proposed method, we compared it against the popular stepwise feature selection method based on Wilks' lambda for a colonic-polyp database (25 polyps and 2624 nonpolyps). We extracted 75 morphologic, gray-level-based, and texture features from the segmented lesion candidate regions. The two variants of the proposed feature selection method chose 29 and 7 features, respectively. Two SVM classifiers trained with these selected features yielded a 96% by-polyp sensitivity at false-positive (FP) rates of 4.1 and 6.5 per patient, respectively. Experiments showed a significant improvement in the performance of the classifier with the proposed feature selection method over that with the popular stepwise feature selection based on Wilks' lambda that yielded 18.0 FPs per patient at the same sensitivity level.

Inductively Coupled Plasma and Electron Cyclotron Resonance Plasma Etching of InGaAlP Compound Semiconductor System

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

Abernathy, C.R.; Hobson, W.S.; Hong, J.

1998-11-04

Current and future generations of sophisticated compound semiconductor devices require the ability for submicron scale patterning. The situation is being complicated since some of the new devices are based on a wider diversity of materials to be etched. Conventional IUE (Reactive Ion Etching) has been prevalent across the industry so far, but has limitations for materials with high bond strengths or multiple elements. IrI this paper, we suggest high density plasmas such as ECR (Electron Cyclotron Resonance) and ICP (Inductively Coupled Plasma), for the etching of ternary compound semiconductors (InGaP, AIInP, AlGaP) which are employed for electronic devices like heterojunctionmore » bipolar transistors (HBTs) or high electron mobility transistors (HEMTs), and photonic devices such as light-emitting diodes (LEDs) and lasers. High density plasma sources, opeiating at lower pressure, are expected to meet target goals determined in terms of etch rate, surface morphology, surface stoichiometry, selectivity, etc. The etching mechanisms, which are described in this paper, can also be applied to other III-V (GaAs-based, InP-based) as well as III-Nitride since the InGaAIP system shares many of the same properties.« less

Dynamical scattering in coherent hard x-ray nanobeam Bragg diffraction

NASA Astrophysics Data System (ADS)

Pateras, A.; Park, J.; Ahn, Y.; Tilka, J. A.; Holt, M. V.; Kim, H.; Mawst, L. J.; Evans, P. G.

2018-06-01

Unique intensity features arising from dynamical diffraction arise in coherent x-ray nanobeam diffraction patterns of crystals having thicknesses larger than the x-ray extinction depth or exhibiting combinations of nanoscale and mesoscale features. We demonstrate that dynamical scattering effects can be accurately predicted using an optical model combined with the Darwin theory of dynamical x-ray diffraction. The model includes the highly divergent coherent x-ray nanobeams produced by Fresnel zone plate focusing optics and accounts for primary extinction, multiple scattering, and absorption. The simulation accurately reproduces the dynamical scattering features of experimental diffraction patterns acquired from a GaAs/AlGaAs epitaxial heterostructure on a GaAs (001) substrate.

Computational intelligence-based polymerase chain reaction primer selection based on a novel teaching-learning-based optimisation.

PubMed

Cheng, Yu-Huei

2014-12-01

Specific primers play an important role in polymerase chain reaction (PCR) experiments, and therefore it is essential to find specific primers of outstanding quality. Unfortunately, many PCR constraints must be simultaneously inspected which makes specific primer selection difficult and time-consuming. This paper introduces a novel computational intelligence-based method, Teaching-Learning-Based Optimisation, to select the specific and feasible primers. The specified PCR product lengths of 150-300 bp and 500-800 bp with three melting temperature formulae of Wallace's formula, Bolton and McCarthy's formula and SantaLucia's formula were performed. The authors calculate optimal frequency to estimate the quality of primer selection based on a total of 500 runs for 50 random nucleotide sequences of 'Homo species' retrieved from the National Center for Biotechnology Information. The method was then fairly compared with the genetic algorithm (GA) and memetic algorithm (MA) for primer selection in the literature. The results show that the method easily found suitable primers corresponding with the setting primer constraints and had preferable performance than the GA and the MA. Furthermore, the method was also compared with the common method Primer3 according to their method type, primers presentation, parameters setting, speed and memory usage. In conclusion, it is an interesting primer selection method and a valuable tool for automatic high-throughput analysis. In the future, the usage of the primers in the wet lab needs to be validated carefully to increase the reliability of the method.

Spectra of Earth-like Planets through Geological Evolution around FGKM Stars

NASA Astrophysics Data System (ADS)

Rugheimer, S.; Kaltenegger, L.

2018-02-01

Future observations of terrestrial exoplanet atmospheres will occur for planets at different stages of geological evolution. We expect to observe a wide variety of atmospheres and planets with alternative evolutionary paths, with some planets resembling Earth at different epochs. For an Earth-like atmospheric time trajectory, we simulate planets from the prebiotic to the current atmosphere based on geological data. We use a stellar grid F0V to M8V ({T}{eff}=7000–2400 K) to model four geological epochs of Earth's history corresponding to a prebiotic world (3.9 Ga), the rise of oxygen at 2.0 Ga and at 0.8 Ga, and the modern Earth. We show the VIS–IR spectral features, with a focus on biosignatures through geological time for this grid of Sun-like host stars and the effect of clouds on their spectra. We find that the observability of biosignature gases reduces with increasing cloud cover and increases with planetary age. The observability of the visible O2 feature for lower concentrations will partly depend on clouds, which, while slightly reducing the feature, increase the overall reflectivity, and thus the detectable flux of a planet. The depth of the IR ozone feature contributes substantially to the opacity at lower oxygen concentrations, especially for the high near-UV stellar environments around F stars. Our results are a grid of model spectra for atmospheres representative of Earth's geological history to inform future observations and instrument design and are available online at http://carlsaganinstitute.org/data/.

Rough sets and Laplacian score based cost-sensitive feature selection

PubMed Central

Yu, Shenglong

2018-01-01

Cost-sensitive feature selection learning is an important preprocessing step in machine learning and data mining. Recently, most existing cost-sensitive feature selection algorithms are heuristic algorithms, which evaluate the importance of each feature individually and select features one by one. Obviously, these algorithms do not consider the relationship among features. In this paper, we propose a new algorithm for minimal cost feature selection called the rough sets and Laplacian score based cost-sensitive feature selection. The importance of each feature is evaluated by both rough sets and Laplacian score. Compared with heuristic algorithms, the proposed algorithm takes into consideration the relationship among features with locality preservation of Laplacian score. We select a feature subset with maximal feature importance and minimal cost when cost is undertaken in parallel, where the cost is given by three different distributions to simulate different applications. Different from existing cost-sensitive feature selection algorithms, our algorithm simultaneously selects out a predetermined number of “good” features. Extensive experimental results show that the approach is efficient and able to effectively obtain the minimum cost subset. In addition, the results of our method are more promising than the results of other cost-sensitive feature selection algorithms. PMID:29912884

Rough sets and Laplacian score based cost-sensitive feature selection.

PubMed

Yu, Shenglong; Zhao, Hong

2018-01-01

Cost-sensitive feature selection learning is an important preprocessing step in machine learning and data mining. Recently, most existing cost-sensitive feature selection algorithms are heuristic algorithms, which evaluate the importance of each feature individually and select features one by one. Obviously, these algorithms do not consider the relationship among features. In this paper, we propose a new algorithm for minimal cost feature selection called the rough sets and Laplacian score based cost-sensitive feature selection. The importance of each feature is evaluated by both rough sets and Laplacian score. Compared with heuristic algorithms, the proposed algorithm takes into consideration the relationship among features with locality preservation of Laplacian score. We select a feature subset with maximal feature importance and minimal cost when cost is undertaken in parallel, where the cost is given by three different distributions to simulate different applications. Different from existing cost-sensitive feature selection algorithms, our algorithm simultaneously selects out a predetermined number of "good" features. Extensive experimental results show that the approach is efficient and able to effectively obtain the minimum cost subset. In addition, the results of our method are more promising than the results of other cost-sensitive feature selection algorithms.

Processing of AlGaAs/GaAs quantum-cascade structures for terahertz laser

NASA Astrophysics Data System (ADS)

Szerling, Anna; Kosiel, Kamil; Szymański, Michał; Wasilewski, Zbig; Gołaszewska, Krystyna; Łaszcz, Adam; Płuska, Mariusz; Trajnerowicz, Artur; Sakowicz, Maciej; Walczakowski, Michał; Pałka, Norbert; Jakieła, Rafał; Piotrowska, Anna

2015-01-01

We report research results with regard to AlGaAs/GaAs structure processing for THz quantum-cascade lasers (QCLs). We focus on the processes of Ti/Au cladding fabrication for metal-metal waveguides and wafer bonding with indium solder. Particular emphasis is placed on optimization of technological parameters for the said processes that result in working devices. A wide range of technological parameters was studied using test structures and the analysis of their electrical, optical, chemical, and mechanical properties performed by electron microscopic techniques, energy dispersive x-ray spectrometry, secondary ion mass spectroscopy, atomic force microscopy, Fourier-transform infrared spectroscopy, and circular transmission line method. On that basis, a set of technological parameters was selected for the fabrication of devices lasing at a maximum temperature of 130 K from AlGaAs/GaAs structures grown by means of molecular beam epitaxy. Their resulting threshold-current densities were on a level of 1.5 kA/cm2. Furthermore, initial stage research regarding fabrication of Cu-based claddings is reported as these are theoretically more promising than the Au-based ones with regard to low-loss waveguide fabrication for THz QCLs.

The effect of Ga pre-deposition on Si (111) surface for InAs nanowire selective area hetero-epitaxy

NASA Astrophysics Data System (ADS)

Liu, Ziyang; Merckling, Clement; Rooyackers, Rita; Franquet, Alexis; Richard, Olivier; Bender, Hugo; Vila, María; Rubio-Zuazo, Juan; Castro, Germán R.; Collaert, Nadine; Thean, Aaron; Vandervorst, Wilfried; Heyns, Marc

2018-04-01

Vertical InAs nanowires (NWs) grown on a Si substrate are promising building-blocks for next generation vertical gate-all-around transistor fabrication. We investigate the initial stage of InAs NW selective area epitaxy (SAE) on a patterned Si (111) substrate with a focus on the interfacial structures. The direct epitaxy of InAs NWs on a clean Si (111) surface is found to be challenging. The yield of vertical InAs NWs is low, as the SAE is accompanied by high proportions of empty holes, inclined NWs, and irregular blocks. In contrast, it is improved when the NW contains gallium, and the yield of vertical InxGa1-xAs NWs increased with higher Ga content. Meanwhile, unintentional Ga surface contamination on a patterned Si substrate induces high yield vertical InAs NW SAE, which is attributed to a GaAs-like seeding layer formed at the InAs/Si interface. The role of Ga played in the III-V NW nucleation on Si is further discussed. It stabilizes the B-polarity on a non-polar Si (111) surface and enhances the nucleation. Therefore, gallium incorporation on a Si surface is identified as an important enabler for vertical InAs NW growth. A new method for high yield (>99%) vertical InAs NW SAE on Si using an InGaAs nucleation layer is proposed based on this study.

Selective etching of InGaAs/GaAs(100) multilayers of quantum-dot chains

NASA Astrophysics Data System (ADS)

Wang, Zh. M.; Zhang, L.; Holmes, K.; Salamo, G. J.

2005-04-01

We report selective chemical etching as a promising procedure to study the buried quantum dots in multiple InGaAs/GaAs layers. The dot layer-by-dot layer etching is demonstrated using a mixed solution of NH4OH:H2O2:H2O. Regular plan-view atomic force microscopy reveals that all of the exposed InGaAs layers have a chain-like lateral ordering despite the potential of significant In-Ga intermixing during capping. The vertical self-correlation of quantum dots in the chains is observed.

Selective area growth and characterization of GaN nanocolumns, with and without an InGaN insertion, on semi-polar (11–22) GaN templates

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

Bengoechea-Encabo, A.; Albert, S.; Barbagini, F.

The aim of this work is the selective area growth (SAG) of GaN nanocolumns, with and without an InGaN insertion, by molecular beam epitaxyon semi-polar (11–22) GaN templates. The high density of stacking faults present in the template is strongly reduced after SAG. A dominant sharp photoluminescence emission at 3.473 eV points to high quality strain-free material. When embedding an InGaN insertion into the ordered GaN nanostructures, very homogeneous optical properties are observed, with two emissions originating from different regions of each nanostructure, most likely related to different In contents on different crystallographic planes.

Speech Emotion Feature Selection Method Based on Contribution Analysis Algorithm of Neural Network

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

Wang Xiaojia; Mao Qirong; Zhan Yongzhao

There are many emotion features. If all these features are employed to recognize emotions, redundant features may be existed. Furthermore, recognition result is unsatisfying and the cost of feature extraction is high. In this paper, a method to select speech emotion features based on contribution analysis algorithm of NN is presented. The emotion features are selected by using contribution analysis algorithm of NN from the 95 extracted features. Cluster analysis is applied to analyze the effectiveness for the features selected, and the time of feature extraction is evaluated. Finally, 24 emotion features selected are used to recognize six speech emotions.more » The experiments show that this method can improve the recognition rate and the time of feature extraction.« less

Microwave synthesis of gibberellin acid 3 magnetic molecularly imprinted polymer beads for the trace analysis of gibberellin acids in plant samples by liquid chromatography-mass spectrometry detection.

PubMed

Zhang, Zhuomin; Tan, Wei; Hu, Yuling; Li, Gongke; Zan, Song

2012-02-21

In this study, novel GA3 magnetic molecularly imprinted polymer (mag-MIP) beads were synthesized by a microwave irradiation method, and the beads were applied for the trace analysis of gibberellin acids (GAs) in plant samples including rice and cucumber coupled with high performance liquid chromatography-mass spectrometry (HPLC-MS). The microwave synthetic procedure was optimized in detail. In particular, the interaction between GA3 and functional monomers was further studied for the selection of the optimal functional monomers during synthesis. It can be seen that the interaction between GA3 and acrylamide (AM) finally selected was stronger than that between GA3 and other functional monomers. GA3 mag-MIP beads were characterized by a series of physical tests. GA3 mag-MIP beads had a porous and homogeneous surface morphology with stable chemical, thermal and magnetic properties. Moreover, GA3 mag-MIP beads demonstrated selective and specific absorption behavior for the target compounds during unsaturated extraction, which resulted in a higher extraction capacity (∼708.4 pmol for GA3) and selectivity than GA3 mag-non-imprinted polymer beads. Finally, an analytical method of GA3 mag-AM-MIP bead extraction coupled with HPLC-MS detection was established and applied for the determination of trace GA1, GA3, GA4 and GA7 in rice and cucumber samples. It was satisfactory that GA4 could be actually found to be 121.5 ± 1.4 μg kg(-1) in real rice samples by this novel analytical method. The recoveries of spiked rice and cucumber samples were found to be 76.0-109.1% and 79.9-93.6% with RSDs of 2.8-8.8% and 3.1-7.7% (n = 3), respectively. The proposed method is efficient and applicable for the trace analysis of GAs in complicated plant samples.

Improving Classification of Protein Interaction Articles Using Context Similarity-Based Feature Selection.

PubMed

Chen, Yifei; Sun, Yuxing; Han, Bing-Qing

2015-01-01

Protein interaction article classification is a text classification task in the biological domain to determine which articles describe protein-protein interactions. Since the feature space in text classification is high-dimensional, feature selection is widely used for reducing the dimensionality of features to speed up computation without sacrificing classification performance. Many existing feature selection methods are based on the statistical measure of document frequency and term frequency. One potential drawback of these methods is that they treat features separately. Hence, first we design a similarity measure between the context information to take word cooccurrences and phrase chunks around the features into account. Then we introduce the similarity of context information to the importance measure of the features to substitute the document and term frequency. Hence we propose new context similarity-based feature selection methods. Their performance is evaluated on two protein interaction article collections and compared against the frequency-based methods. The experimental results reveal that the context similarity-based methods perform better in terms of the F1 measure and the dimension reduction rate. Benefiting from the context information surrounding the features, the proposed methods can select distinctive features effectively for protein interaction article classification.

GaN and ZnO nanostructures

NASA Astrophysics Data System (ADS)

Fündling, Sönke; Sökmen, Ünsal; Behrends, Arne; Al-Suleiman, Mohamed Aid Mansur; Merzsch, Stephan; Li, Shunfeng; Bakin, Andrey; Wehmann, Hergo-Heinrich; Waag, Andreas; Lähnemann, Jonas; Jahn, Uwe; Trampert, Achim; Riechert, Henning

2010-07-01

GaN and ZnO are both wide band gap semiconductors with interesting properties concerning optoelectronic and sensor device applications. Due to the lack or the high costs of native substrates, alternatives like sapphire, silicon, or silicon carbide are taken, but the resulting lattice and thermal mismatches lead to increased defect densities which reduce the material quality. In contrast, nanostructures with high aspect ratio have lower defect densities as compared to layers. In this work, we give an overview on our results achieved on both ZnO as well as GaN based nanorods. ZnO nanostructures were grown by a wet chemical approach as well as by VPT on different substrates - even on flexible polymers. To compare the growth results we analyzed the structures by XRD and PL and show possible device applications. The GaN nano- and microstructures were grown by metal organic vapor phase epitaxy either in a self- organized process or by selective area growth for a better control of shape and material composition. Finally we take a look onto possible device applications, presenting our attempts, e.g., to build LEDs based on GaN nanostructures.

Facial Emotion Recognition System – A Machine Learning Approach

NASA Astrophysics Data System (ADS)

Ramalingam, V. V.; Pandian, A.; Jayakumar, Lavanya

2018-04-01

Frown is a medium for people correlation and it could be exercised in multiple real systems. Single crucial stage for frown realizing is to exactly select hysterical aspects. This journal proposed a frown realization scheme applying transformative Particle Swarm Optimization (PSO) based aspect accumulation. This entity initially employs changed LVP, handles crisscross adjacent picture element contrast, for achieving the selective first frown portrayal. Then the PSO entity inserted with a concept of micro Genetic Algorithm (mGA) called mGA-embedded PSO designed for achieving aspect accumulation. This study, the technique subsumes no disposable memory, a little-populace insignificant flock, a latest acceleration that amends with the approach and a sub dimension-based in-depth local frown aspect examines. Assistance of provincial utilization and comprehensive inspection examine structure of alleviating of an immature concurrence complication of conventional PSO. Numerous identifiers are used to diagnose different frown expositions. Stationed on extensive study within and other-sphere pictures from the continued Cohn Kanade and MMI benchmark directory appropriately. Determination of the application exceeds most advanced level PSO variants, conventional PSO, classical GA and alternate relevant frown realization structures is described with powerful limit. Extending our accession to a motion based FER application for connecting patch-based Gabor aspects with continuous data in multi-frames.

Highly selective dry etching of GaP in the presence of AlxGa1–xP with a SiCl4/SF6 plasma

NASA Astrophysics Data System (ADS)

Hönl, Simon; Hahn, Herwig; Baumgartner, Yannick; Czornomaz, Lukas; Seidler, Paul

2018-05-01

We present an inductively coupled-plasma reactive-ion etching process that simultaneously provides both a high etch rate and unprecedented selectivity for gallium phosphide (GaP) in the presence of aluminum gallium phosphide (AlxGa1–xP). Utilizing mixtures of silicon tetrachloride (SiCl4) and sulfur hexafluoride (SF6), selectivities exceeding 2700:1 are achieved at GaP etch rates above 3000 nm min‑1. A design of experiments has been employed to investigate the influence of the inductively coupled-plasma power, the chamber pressure, the DC bias and the ratio of SiCl4 to SF6. The process enables the use of thin AlxGa1–xP stop layers even at aluminum contents of a few percent.

Detection of nicotine content impact in tobacco manufacturing using computational intelligence.

PubMed

Begic Fazlic, Lejla; Avdagic, Zikrija

2011-01-01

A study is presented for the detection of nicotine impact in different cigarette type, using recorded data and Computational Intelligence techniques. Recorded puffs are processed using Continuous Wavelet Transform and used to extract time-frequency features for normal and abnormal puffs conditions. The wavelet energy distributions are used as inputs to classifiers based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Genetic Algorithms (GAs). The number and the parameters of Membership Functions are used in ANFIS along with the features from wavelet energy distributionare selected using GAs, maximising the diagnosis success. GA with ANFIS (GANFIS) are trained with a subset of data with known nicotine conditions. The trained GANFIS are tested using the other set of data (testing data). A classical method by High-Performance Liquid Chromatography is also introduced to solve this problem, respectively. The results as well as the performances of these two approaches are compared. A combination of these two algorithms is also suggested to improve the efficiency of this solution procedure. Computational results show that this combined algorithm is promising.

Design and development of short- and long-wavelength MQW infrared vertical cavity surface emitting lasers

NASA Astrophysics Data System (ADS)

Iliadis, Agisilaos A.; Christou, Aristos

2003-07-01

The design, fabrication and performance of low threshold selectively oxidized infrared vertical cavity surface emitting lasers (VCSELs) for operation at 0.89μm and 1.55μm wavelengths using optimized graded Bragg mirrors, is reported. The devices are based on III-V ternary (AlGaAs/GaAs) and quaternary (AlInGaAs/GaInAsP/InP) graded semiconductor alloys and quantum wells and are grown by Molecular Beam Epitaxy. The VCSEL arrays are processed using inductively coupled plasma (ICP) etching with BCl3 gas mixtures to achieve vertical walls and small geometries, and the fabrication of the devices proceeds by using conventional Ohmic contacts (Ti-Pt-Au and Ni-Au-Ge-Ni) and indium tin oxide (ITO) transparent contacts. The theoretical investigation of the optical properties of the quaternary compound semiconductor alloys allows us to select the optimum materials for highly reflective Bragg mirrors with less periods. The simulation of the designed VCSEL performance has been carried out by evaluation of the important laser characteristics such as threshold gain, threshold current density and external quantum efficiency.

Feature Selection in Classification of Eye Movements Using Electrooculography for Activity Recognition

PubMed Central

Mala, S.; Latha, K.

2014-01-01

Activity recognition is needed in different requisition, for example, reconnaissance system, patient monitoring, and human-computer interfaces. Feature selection plays an important role in activity recognition, data mining, and machine learning. In selecting subset of features, an efficient evolutionary algorithm Differential Evolution (DE), a very efficient optimizer, is used for finding informative features from eye movements using electrooculography (EOG). Many researchers use EOG signals in human-computer interactions with various computational intelligence methods to analyze eye movements. The proposed system involves analysis of EOG signals using clearness based features, minimum redundancy maximum relevance features, and Differential Evolution based features. This work concentrates more on the feature selection algorithm based on DE in order to improve the classification for faultless activity recognition. PMID:25574185

Feature selection in classification of eye movements using electrooculography for activity recognition.

PubMed

Mala, S; Latha, K

2014-01-01

Activity recognition is needed in different requisition, for example, reconnaissance system, patient monitoring, and human-computer interfaces. Feature selection plays an important role in activity recognition, data mining, and machine learning. In selecting subset of features, an efficient evolutionary algorithm Differential Evolution (DE), a very efficient optimizer, is used for finding informative features from eye movements using electrooculography (EOG). Many researchers use EOG signals in human-computer interactions with various computational intelligence methods to analyze eye movements. The proposed system involves analysis of EOG signals using clearness based features, minimum redundancy maximum relevance features, and Differential Evolution based features. This work concentrates more on the feature selection algorithm based on DE in order to improve the classification for faultless activity recognition.

Metal-interconnection-free integration of InGaN/GaN light emitting diodes with AlGaN/GaN high electron mobility transistors

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

Liu, Chao; Cai, Yuefei; Liu, Zhaojun

2015-05-04

We report a metal-interconnection-free integration scheme for InGaN/GaN light emitting diodes (LEDs) and AlGaN/GaN high electron mobility transistors (HEMTs) by combining selective epi removal (SER) and selective epitaxial growth (SEG) techniques. SER of HEMT epi was carried out first to expose the bottom unintentionally doped GaN buffer and the sidewall GaN channel. A LED structure was regrown in the SER region with the bottom n-type GaN layer (n-electrode of the LED) connected to the HEMTs laterally, enabling monolithic integration of the HEMTs and LEDs (HEMT-LED) without metal-interconnection. In addition to saving substrate real estate, minimal interface resistance between the regrownmore » n-type GaN and the HEMT channel is a significant improvement over metal-interconnection. Furthermore, excellent off-state leakage characteristics of the driving transistor can also be guaranteed in such an integration scheme.« less

Large-Format AlGaN PIN Photodiode Arrays for UV Images

NASA Technical Reports Server (NTRS)

Aslam, Shahid; Franz, David

2010-01-01

A large-format hybridized AlGaN photodiode array with an adjustable bandwidth features stray-light control, ultralow dark-current noise to reduce cooling requirements, and much higher radiation tolerance than previous technologies. This technology reduces the size, mass, power, and cost of future ultraviolet (UV) detection instruments by using lightweight, low-voltage AlGaN detectors in a hybrid detector/multiplexer configuration. The solar-blind feature eliminates the need for additional visible light rejection and reduces the sensitivity of the system to stray light that can contaminate observations.

Growth and characterization of sol-gel derived CuGaO2 semiconductor thin films for UV photodetector application

NASA Astrophysics Data System (ADS)

Tsay, Chien-Yie; Chen, Ching-Lien

2017-06-01

In this study, a p-type wide-bandgap oxide semiconductor CuGaO2 thin film was grown on quartz substrate by sol-gel method. The authors report the influence of annealing temperature on the phase transformation, structural features, and electrical properties of sol-gel derived Cu-Ga-O thin films. At relatively low annealing temperatures (≤900 °C), the films are a mixture of CuGa2O4, CuGaO2, and CuO phases. At relatively high annealing temperatures (≥925 °C), the majority phase in the films is delafossite CuGaO2. All as-prepared Cu-Ga-O thin films exhibited p-type conductivity, as confirmed by Hall measurements. The mean electrical resistivity of the Cu-Ga-O films decreased from 3.54×104 Ω-cm to 1.35×102 Ω-cm and then increased slightly to 3.51×102 Ω-cm when the annealing temperature was increased from 850 °C to 950 °C. We found that annealing the Cu-based oxide thin films at 925 °C produced nearly phase-pure CuGaO2 thin films with good densification. Such thin films exhibited the best electrical properties: a mean electrical resistivity of 1.35×102 Ω-cm, and a mean hole concentration of 1.60×1016 cm-3. In addition, we also fabricated and characterized MSM-type CuGaO2 UV photodetectors on quartz substrates.

Enhanced characteristics of blue InGaN /GaN light-emitting diodes by using selective activation to modulate the lateral current spreading length

NASA Astrophysics Data System (ADS)

Lin, Ray-Ming; Lu, Yuan-Chieh; Chou, Yi-Lun; Chen, Guo-Hsing; Lin, Yung-Hsiang; Wu, Meng-Chyi

2008-06-01

We have studied the characteristics of blue InGaN /GaN multiquantum-well light-emitting diodes (LEDs) after reducing the length of the lateral current path through the transparent layer through formation of a peripheral high-resistance current-blocking region in the Mg-doped GaN layer. To study the mechanism of selective activation in the Mg-doped GaN layer, we deposited titanium (Ti), gold (Au), Ti /Au, silver, and copper individually onto the Mg-doped GaN layer and investigated their effects on the hole concentration in the p-GaN layer. The Mg-doped GaN layer capped with Ti effectively depressed the hole concentration in the p-GaN layer by over one order of magnitude relative to that of the as-grown layer. This may suggest that high resistive regions are formed by diffusion of Ti and depth of high resistive region from the p-GaN surface depends on the capped Ti film thickness. Selective activation of the Mg-doped GaN layer could be used to modulate the length of the lateral current path. Furthermore, the external quantum efficiency of the LEDs was improved significantly after reducing the lateral current spreading length. In our best result, the external quantum efficiency was 52.3% higher (at 100mA) than that of the as-grown blue LEDs.

Process Development of Gallium Nitride Phosphide Core-Shell Nanowire Array Solar Cell

NASA Astrophysics Data System (ADS)

Chuang, Chen

Dilute Nitride GaNP is a promising materials for opto-electronic applications due to its band gap tunability. The efficiency of GaNxP1-x /GaNyP1-y core-shell nanowire solar cell (NWSC) is expected to reach as high as 44% by 1% N and 9% N in the core and shell, respectively. By developing such high efficiency NWSCs on silicon substrate, a further reduction of the cost of solar photovoltaic can be further reduced to 61$/MWh, which is competitive to levelized cost of electricity (LCOE) of fossil fuels. Therefore, a suitable NWSC structure and fabrication process need to be developed to achieve this promising NWSC. This thesis is devoted to the study on the development of fabrication process of GaNxP 1-x/GaNyP1-y core-shell Nanowire solar cell. The thesis is divided into two major parts. In the first parts, previously grown GaP/GaNyP1-y core-shell nanowire samples are used to develop the fabrication process of Gallium Nitride Phosphide nanowire solar cell. The design for nanowire arrays, passivation layer, polymeric filler spacer, transparent col- lecting layer and metal contact are discussed and fabricated. The property of these NWSCs are also characterized to point out the future development of Gal- lium Nitride Phosphide NWSC. In the second part, a nano-hole template made by nanosphere lithography is studied for selective area growth of nanowires to improve the structure of core-shell NWSC. The fabrication process of nano-hole templates and the results are presented. To have a consistent features of nano-hole tem- plate, the Taguchi Method is used to optimize the fabrication process of nano-hole templates.

Retrieval of Dry Snow Parameters from Radiometric Data Using a Dense Medium Model and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Tedesco, Marco; Kim, Edward J.

2005-01-01

In this paper, GA-based techniques are used to invert the equations of an electromagnetic model based on Dense Medium Radiative Transfer Theory (DMRT) under the Quasi Crystalline Approximation with Coherent Potential to retrieve snow depth, mean grain size and fractional volume from microwave brightness temperatures. The technique is initially tested on both noisy and not-noisy simulated data. During this phase, different configurations of genetic algorithm parameters are considered to quantify how their change can affect the algorithm performance. A configuration of GA parameters is then selected and the algorithm is applied to experimental data acquired during the NASA Cold Land Process Experiment. Snow parameters retrieved with the GA-DMRT technique are then compared with snow parameters measured on field.

Feature selection method based on multi-fractal dimension and harmony search algorithm and its application

NASA Astrophysics Data System (ADS)

Zhang, Chen; Ni, Zhiwei; Ni, Liping; Tang, Na

2016-10-01

Feature selection is an important method of data preprocessing in data mining. In this paper, a novel feature selection method based on multi-fractal dimension and harmony search algorithm is proposed. Multi-fractal dimension is adopted as the evaluation criterion of feature subset, which can determine the number of selected features. An improved harmony search algorithm is used as the search strategy to improve the efficiency of feature selection. The performance of the proposed method is compared with that of other feature selection algorithms on UCI data-sets. Besides, the proposed method is also used to predict the daily average concentration of PM2.5 in China. Experimental results show that the proposed method can obtain competitive results in terms of both prediction accuracy and the number of selected features.

A New Selective Area Lateral Epitaxy Approach for Depositing a-Plane GaN over r-Plane Sapphire

NASA Astrophysics Data System (ADS)

Chen, Changqing; Zhang, Jianping; Yang, Jinwei; Adivarahan, Vinod; Rai, Shiva; Wu, Shuai; Wang, Hongmei; Sun, Wenhong; Su, Ming; Gong, Zheng; Kuokstis, Edmundas; Gaevski, Mikhail; Khan, Muhammad Asif

2003-07-01

We report a new epitaxy procedure for growing extremely low defect density a-plane GaN films over r-plane sapphire. By combining selective area growth through a SiO2 mask opening to produce high height to width aspect ratio a-plane GaN pillars and lateral epitaxy from their c-plane facets, we obtained fully coalesced a-plane GaN films. The excellent structural, optical and electrical characteristics of these selective area lateral epitaxy (SALE) deposited films make them ideal for high efficiency III-N electronic and optoelectronic devices.

Fabrication and characterization of zinc oxide and gallium nitride based sensors

NASA Astrophysics Data System (ADS)

Wang, Hung-Ta

Pt-coated ZnO nanorods show a decrease of 8% resistance upon exposure to 500 ppm hydrogen in room temperature. This is a factor of two larger than that obtained with Pd; approximately 95% of the initial ZnO conductance was recovered within 20 s by exposing the nanorods to O2. This rapid and easy recoverability makes the ZnO nanorods suitable for ppm-level sensing at room temperature with low power consumption. Pt-gated AlGaN/GaN based high electron mobility transistors (HEMTs) showed that Schottky diode operation provides large relative sensitivity over a narrow range around turn-on voltage; the differential designed Schottky diodes with AlGaN/GaN hetero-structure was shown to provide robust detection of 1% H 2 in air at 25°C, which remove false alarms from ambient temperature variations; moreover, the use of TiB2-based Ohmic contacts on Pt-Schottky contacted AlGaN/GaN based hydrogen sensing diodes was shown to provide more stable operation. Thioglycolic acid functionalized Au-gated AlGaN/GaN based HEMTs were used to detect mercury (II) ions. A fast detection (>5 seconds) was achieved. This is the shortest response ever reported. The sensors were able to detect mercury (II) ion concentration as low as 10-7 M. The sensors showed an excellent sensing selectivity of more than 100 of detecting mercury ions over sodium, magnesium, and lead ions, but not copper. AlGaN/GaN based HEMTs were used to detect kidney injury molecule-1 (KIM-1), an important biomarker for early kidney injury detection. The HEMT gate region was coated with KIM-1 antibodies and the HEMT source-drain current showed a clear dependence on the KIM-1 concentration in phosphate-buffered saline (PBS) solution. The limit of detection (LOD) was 1ng/ml using a 20 mum x50 mum gate sensing area. This approach shows a potential for both preclinical and clinical disease diagnosis with accurate, rapid, noninvasive, and high throughput capabilities. The rest of this dissertation includes ZnO band edge electroluminescence from N+-implanted ZnO bulk, and the investigation of cryogenic gold Schottky contact on GaAs for enhancing device thermal stability.

Improvements of electronic and optical characteristics of n-GaN-based structures by photoelectrochemical oxidation in glycol solution

NASA Astrophysics Data System (ADS)

Shiozaki, Nanako; Hashizume, Tamotsu

2009-03-01

Surface control of n-GaN was performed by applying a photoelectrochemical oxidation method in a glycol solution to improve the optical and electronic characteristics. The fundamental properties of the oxidation were investigated. The oxidation, chemical composition, and bonding states were analyzed by x-ray photoelectron spectroscopy and micro-Auger electron spectroscopy, in which confirmed the formation of gallium oxide on the surface. The oxide formation rate was about 8 nm/min under UV illumination of 4 mW/cm2. After establishing the basic properties for control of n-GaN oxidation, the surface control technique was applied to achieve low-damage etching, enhancement of the photoluminescence intensity, and selective passivation of the air-exposed sidewalls in an AlGaN/GaN high electron mobility transistor wire structure. The capacitance-voltage measurement revealed the minimum interface-state density between GaN and anodic oxide to be about 5×1011 cm-2 eV-1, which is rather low value for compound semiconductors.

Effect of arsenic on the optical properties of GaSb-based type II quantum wells with quaternary GaInAsSb layers

NASA Astrophysics Data System (ADS)

Janiak, F.; Motyka, M.; Sek, G.; Dyksik, M.; Ryczko, K.; Misiewicz, J.; Weih, R.; Höfling, S.; Kamp, M.; Patriarche, G.

2013-12-01

Optical properties of molecular beam epitaxially grown type II "W" shaped GaSb/AlSb/InAs/GaIn(As)Sb/InAs/AlSb/GaSb quantum wells (QWs) designed for the active region of interband cascade lasers have been investigated. Temperature dependence of Fourier-transformed photoluminescence and photoreflectance was employed to probe the effects of addition of arsenic into the original ternary valence band well of GaInSb. It is revealed that adding arsenic provides an additional degree of freedom in terms of band alignment and strain tailoring and allows enhancing the oscillator strength of the active type II transition. On the other hand, however, arsenic incorporation apparently also affects the structural and optical material quality via generating carrier trapping states at the interfaces, which can deteriorate the radiative efficiency. These have been evidenced in several spectroscopic features and are also confirmed by cross-sectional transmission electron microscopy images. While arsenic incorporation into type II QWs is a powerful heterostructure engineering tool for optoelectronic devices, a compromise has to be found between ideal band structure properties and high quality morphological properties.

Design and analysis of 30 nm T-gate InAlN/GaN HEMT with AlGaN back-barrier for high power microwave applications

NASA Astrophysics Data System (ADS)

Murugapandiyan, P.; Ravimaran, S.; William, J.; Meenakshi Sundaram, K.

2017-11-01

In this article, we present the DC and microwave characteristics of a novel 30 nm T-gate InAlN/AlN/GaN HEMT with AlGaN back-barrier. The device structure is simulated by using Synopsys Sentaurus TCAD Drift-Diffusion transport model at room temperature. The device features are heavily doped (n++ GaN) source/drain regions with Si3N4 passivated device surface for reducing the contact resistances and gate capacitances of the device, which uplift the microwave characteristics of the HEMTs. 30 nm gate length D-mode (E-mode) HEMT exhibited a peak drain current density Idmax of 2.3 (2.42) A/mm, transconductance gm of 1.24(1.65) S/mm, current gain cut-off frequency ft of 262 (246) GHz, power gain cut-off frequency fmax of 246(290) GHz and the three terminal off-state breakdown voltage VBR of 40(38) V. The preeminent microwave characteristics with the higher breakdown voltage of the proposed GaN-based HEMT are the expected to be the most optimistic applicant for future high power millimeter wave applications.

Micro and nano-structured green gallium indium nitride/gallium nitride light-emitting diodes

NASA Astrophysics Data System (ADS)

Stark, Christoph J. M.

Light-emitting diodes (LEDs) are commonly designed and studied based on bulk material properties. In this thesis different approaches based on patterns in the nano and micrometer length scale range are used to tackle low efficiency in the green spectral region, which is known as “green gap”. Since light generation and extraction are governed by microscopic processes, it is instructive to study LEDs with lateral mesa sizes scaled to the nanometer range. Besides the well-known case of the quantum size effect along the growth direction, a continuous lateral scaling could reveal the mechanisms behind the purported absence of a green gap in nanowire LEDs and the role of their extraction enhancement. Furthermore the possibility to modulate strain and piezoelectric polarization by post growth patterning is of practical interest, because the internal electric fields in conventional wurtzite GaN LEDs cause performance problems. A possible alternative is cubic phase GaN, which is free of built-in polarization fields. LEDs on cubic GaN could show the link between strong polarization fields and efficiency roll-off at high current densities, also known as droop. An additional problem for all nitride-based LEDs is efficient light extraction. For a planar GaN LED only roughly 8% of the generated light can be extracted. Novel lightextraction structures with extraction-favoring geometry can yield significant increase in light output power. To investigate the effect of scaling the mesa dimension, micro and nano-sized LED arrays of variable structure size were fabricated. The nano-LEDs were patterned by electron beam lithography and dry etching. They contained up to 100 parallel nano-stripe LEDs connected to one common contact area. The mesa width was varied over 1 μm, 200 nm, and 50 nm. These LEDs were characterized electrically and optically, and the peak emission wavelength was found to depend on the lateral structure size. An electroluminescence (EL) wavelength shift of 3 nm towards smaller values was observed when the stripe width was reduced from 1 μm to 50 nm. At the same time a strong fourfold enhancement of the light emission from the patterned region over the unpatterned area was observed. Micro-patterned LEDs showed non-linear scaling of the light output power, and an enhancement of 39 % was achieved for structures with an area fill ratio of 0.5 over an LED with square mesa. Growth of cubic GaN and cubic GaInN/GaN LEDs was shown by M-OVPE in Vshaped grooves formed by the {111} planes of etched silicon. SEM images of the GaN layer in small ( 0.5 μm) regions show a contrast change where the phase boundary between cubic and wurtzite GaN is expected to occur. The growth parameter space is explored for optimal conditions while minimizing the alloying problem for GaN growth on Si. The cubic GaN phase is confirmed by electron back-scatter diffraction (EBSD) in the V-groove center, whereas wurtzite GaN is found near the groove edges. Luminescence of undoped GaN and GaInN/GaN multi-quantum well structures was studied by cathodoluminescence (CL). The undoped cubic GaN structure showed strong band-edge luminescence at 385 nm (3.22 eV) at 78 K, whereas for the MQW device strong emission at 498 nm is observed, even at room temperature. Full cubic LED structures were grown, and wavelength-stable electroluminescence at 489 nm was demonstrated. LEDs with integrated light extraction structures are grown on free-standing GaN substrates with different off-cut angles. The devices with different off-cut show pronounced features at the top surface that also penetrate the active region. For a 2.24° off-cut, these features resemble fish scales, where the feature sizes are in the μm-range. The 2.24° off-cut LED shows a 3.6-fold increased light output power compared to a LED on virtually on-axis substrate with 0.06° off-cut. The enhancement found in the fish scale LEDs is attributed to increased light scattering, effectively reducing the fraction of trapped light. These results show the potential of structures on the micro and nanometer scale for LED device performance and the progress on cubic GaN could open alternative ways to understand the droop problem.

Origin of positive fixed charge at insulator/AlGaN interfaces and its control by AlGaN composition

NASA Astrophysics Data System (ADS)

Matys, M.; Stoklas, R.; Blaho, M.; Adamowicz, B.

2017-06-01

The key feature for the precise tuning of Vth in GaN-based metal-insulator-semiconductor (MIS) high electron mobility transistors is the control of the positive fixed charge (Qf) at the insulator/III-N interfaces, whose amount is often comparable to the negative surface polarization charge ( Qp o l -). In order to clarify the origin of Qf, we carried out a comprehensive capacitance-voltage (C-V) characterization of SiO2/AlxGa1-xN/GaN and SiN/AlxGa1-xN/GaN structures with Al composition (x) varying from 0.15 to 0.4. For both types of structures, we observed a significant Vth shift in C-V curves towards the positive gate voltage with increasing x. On the contrary, the Schottky gate structures exhibited Vth shift towards the more negative biases. From the numerical simulations of C-V curves using the Poisson's equation supported by the analytical calculations of Vth, we showed that the Vth shift in the examined MIS structures is due to a significant decrease in the positive Qf with rising x. Finally, we examined this result with respect to various hypotheses developed in the literature to explain the origin of the positive Qf at insulator/III-N interfaces.

Developing a NIR multispectral imaging for prediction and visualization of peanut protein content using variable selection algorithms

NASA Astrophysics Data System (ADS)

Cheng, Jun-Hu; Jin, Huali; Liu, Zhiwei

2018-01-01

The feasibility of developing a multispectral imaging method using important wavelengths from hyperspectral images selected by genetic algorithm (GA), successive projection algorithm (SPA) and regression coefficient (RC) methods for modeling and predicting protein content in peanut kernel was investigated for the first time. Partial least squares regression (PLSR) calibration model was established between the spectral data from the selected optimal wavelengths and the reference measured protein content ranged from 23.46% to 28.43%. The RC-PLSR model established using eight key wavelengths (1153, 1567, 1972, 2143, 2288, 2339, 2389 and 2446 nm) showed the best predictive results with the coefficient of determination of prediction (R2P) of 0.901, and root mean square error of prediction (RMSEP) of 0.108 and residual predictive deviation (RPD) of 2.32. Based on the obtained best model and image processing algorithms, the distribution maps of protein content were generated. The overall results of this study indicated that developing a rapid and online multispectral imaging system using the feature wavelengths and PLSR analysis is potential and feasible for determination of the protein content in peanut kernels.

Multi-wavelength VCSEL arrays using high-contrast gratings

NASA Astrophysics Data System (ADS)

Haglund, Erik; Gustavsson, Johan S.; Sorin, Wayne V.; Bengtsson, Jörgen; Fattal, David; Haglund, Àsa; Tan, Michael; Larsson, Anders

2017-02-01

The use of a high-contrast grating (HCG) as the top mirror in a vertical-cavity surface-emitting laser (VCSEL) allows for setting the resonance wavelength by the grating parameters in a post-epitaxial growth fabrication process. Using this technique, we demonstrate electrically driven multi-wavelength VCSEL arrays at 980 nm wavelength. The VCSELs are GaAs-based and the suspended GaAs HCGs were fabricated using electron-beam lithography, dry etching and selective removal of an InGaP sacrificial layer. The air-coupled cavity design enabled 4-channel arrays with 5 nm wavelength spacing and sub-mA threshold currents thanks to the high HCG reflectance.

The Secondary Development of ABAQUS by using Python and the Application of the Advanced GA

NASA Astrophysics Data System (ADS)

Luo, Lilong; Zhao, Meiying

Realizing the secondary development of the ABAQUS based on the manual of ABAQUS. In order to overcome the prematurity and the worse convergence of the Simple Genetic Algorithm (SGA), a new strategy how to improve the efficiency of the SGA has been put forward. In the new GA, the selection probability and the mutation probability are self-adaptive. Taking the stability of the composite laminates as the target, the optimized laminates sequences and radius of the hatch are analyzed with the help of ABAQUS. Compared with the SGA, the new GA method shows a good consistency, fast convergence and practical feasibility.

Improved interpretation of satellite altimeter data using genetic algorithms

NASA Technical Reports Server (NTRS)

Messa, Kenneth; Lybanon, Matthew

1992-01-01

Genetic algorithms (GA) are optimization techniques that are based on the mechanics of evolution and natural selection. They take advantage of the power of cumulative selection, in which successive incremental improvements in a solution structure become the basis for continued development. A GA is an iterative procedure that maintains a 'population' of 'organisms' (candidate solutions). Through successive 'generations' (iterations) the population as a whole improves in simulation of Darwin's 'survival of the fittest'. GA's have been shown to be successful where noise significantly reduces the ability of other search techniques to work effectively. Satellite altimetry provides useful information about oceanographic phenomena. It provides rapid global coverage of the oceans and is not as severely hampered by cloud cover as infrared imagery. Despite these and other benefits, several factors lead to significant difficulty in interpretation. The GA approach to the improved interpretation of satellite data involves the representation of the ocean surface model as a string of parameters or coefficients from the model. The GA searches in parallel, a population of such representations (organisms) to obtain the individual that is best suited to 'survive', that is, the fittest as measured with respect to some 'fitness' function. The fittest organism is the one that best represents the ocean surface model with respect to the altimeter data.

Tandem Solar Cells Using GaAs Nanowires on Si: Design, Fabrication, and Observation of Voltage Addition.

PubMed

Yao, Maoqing; Cong, Sen; Arab, Shermin; Huang, Ningfeng; Povinelli, Michelle L; Cronin, Stephen B; Dapkus, P Daniel; Zhou, Chongwu

2015-11-11

Multijunction solar cells provide us a viable approach to achieve efficiencies higher than the Shockley-Queisser limit. Due to their unique optical, electrical, and crystallographic features, semiconductor nanowires are good candidates to achieve monolithic integration of solar cell materials that are not lattice-matched. Here, we report the first realization of nanowire-on-Si tandem cells with the observation of voltage addition of the GaAs nanowire top cell and the Si bottom cell with an open circuit voltage of 0.956 V and an efficiency of 11.4%. Our simulation showed that the current-matching condition plays an important role in the overall efficiency. Furthermore, we characterized GaAs nanowire arrays grown on lattice-mismatched Si substrates and estimated the carrier density using photoluminescence. A low-resistance connecting junction was obtained using n(+)-GaAs/p(+)-Si heterojunction. Finally, we demonstrated tandem solar cells based on top GaAs nanowire array solar cells grown on bottom planar Si solar cells. The reported nanowire-on-Si tandem cell opens up great opportunities for high-efficiency, low-cost multijunction solar cells.

Quantum chemical density functional theory studies on the molecular structure and vibrational spectra of Gallic acid imprinted polymers

NASA Astrophysics Data System (ADS)

Pardeshi, Sushma; Dhodapkar, Rita; Kumar, Anupama

2013-12-01

Gallic acid (GA) is known by its antioxidant, anticarcinogenic properties and scavenger activity against several types of harmful free radicals. Molecularly imprinted polymers (MIPs) are used in separation of a pure compound from complex matrices. A stable template-monomer complex generates the MIPs with the highest affinity and selectivity for the template. The quantum chemical computations based on density functional theory (DFT) was used on the template Gallic acid (GA), monomer acrylic acid (AA) and GA-AA complex to study the nature of interactions involved in the GA-AA complex. B3LYP/6-31+G(2d,2p) model chemistry was used to optimize their structures and frequency calculations. The effect of porogen acetonitrile (ACN) on complex formation was included by using polarizable continuum model (PCM). The results demonstrated the formation of a stable GA-AA complex through the intermolecular hydrogen bonding between carboxylic acid groups of GA and AA. The Mulliken atomic charge analysis and simulated vibrational spectra also supported the stable hydrogen bonding interaction between the carboxylic acid groups of GA and AA with minimal interference of porogen ACN. Further, simulations on GA-AA mole ratio revealed that 1:4 GA-AA was optimum for synthesis of MIP for GA.

Assessment of gene order computing methods for Alzheimer's disease

PubMed Central

2013-01-01

Background Computational genomics of Alzheimer disease (AD), the most common form of senile dementia, is a nascent field in AD research. The field includes AD gene clustering by computing gene order which generates higher quality gene clustering patterns than most other clustering methods. However, there are few available gene order computing methods such as Genetic Algorithm (GA) and Ant Colony Optimization (ACO). Further, their performance in gene order computation using AD microarray data is not known. We thus set forth to evaluate the performances of current gene order computing methods with different distance formulas, and to identify additional features associated with gene order computation. Methods Using different distance formulas- Pearson distance and Euclidean distance, the squared Euclidean distance, and other conditions, gene orders were calculated by ACO and GA (including standard GA and improved GA) methods, respectively. The qualities of the gene orders were compared, and new features from the calculated gene orders were identified. Results Compared to the GA methods tested in this study, ACO fits the AD microarray data the best when calculating gene order. In addition, the following features were revealed: different distance formulas generated a different quality of gene order, and the commonly used Pearson distance was not the best distance formula when used with both GA and ACO methods for AD microarray data. Conclusion Compared with Pearson distance and Euclidean distance, the squared Euclidean distance generated the best quality gene order computed by GA and ACO methods. PMID:23369541

Towards automated spectroscopic tissue classification in thyroid and parathyroid surgery.

PubMed

Schols, Rutger M; Alic, Lejla; Wieringa, Fokko P; Bouvy, Nicole D; Stassen, Laurents P S

2017-03-01

In (para-)thyroid surgery iatrogenic parathyroid injury should be prevented. To aid the surgeons' eye, a camera system enabling parathyroid-specific image enhancement would be useful. Hyperspectral camera technology might work, provided that the spectral signature of parathyroid tissue offers enough specific features to be reliably and automatically distinguished from surrounding tissues. As a first step to investigate this, we examined the feasibility of wide band diffuse reflectance spectroscopy (DRS) for automated spectroscopic tissue classification, using silicon (Si) and indium-gallium-arsenide (InGaAs) sensors. DRS (350-1830 nm) was performed during (para-)thyroid resections. From the acquired spectra 36 features at predefined wavelengths were extracted. The best features for classification of parathyroid from adipose or thyroid were assessed by binary logistic regression for Si- and InGaAs-sensor ranges. Classification performance was evaluated by leave-one-out cross-validation. In 19 patients 299 spectra were recorded (62 tissue sites: thyroid = 23, parathyroid = 21, adipose = 18). Classification accuracy of parathyroid-adipose was, respectively, 79% (Si), 82% (InGaAs) and 97% (Si/InGaAs combined). Parathyroid-thyroid classification accuracies were 80% (Si), 75% (InGaAs), 82% (Si/InGaAs combined). Si and InGaAs sensors are fairly accurate for automated spectroscopic classification of parathyroid, adipose and thyroid tissues. Combination of both sensor technologies improves accuracy. Follow-up research, aimed towards hyperspectral imaging seems justified. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Skin lesion computational diagnosis of dermoscopic images: Ensemble models based on input feature manipulation.

PubMed

Oliveira, Roberta B; Pereira, Aledir S; Tavares, João Manuel R S

2017-10-01

The number of deaths worldwide due to melanoma has risen in recent times, in part because melanoma is the most aggressive type of skin cancer. Computational systems have been developed to assist dermatologists in early diagnosis of skin cancer, or even to monitor skin lesions. However, there still remains a challenge to improve classifiers for the diagnosis of such skin lesions. The main objective of this article is to evaluate different ensemble classification models based on input feature manipulation to diagnose skin lesions. Input feature manipulation processes are based on feature subset selections from shape properties, colour variation and texture analysis to generate diversity for the ensemble models. Three subset selection models are presented here: (1) a subset selection model based on specific feature groups, (2) a correlation-based subset selection model, and (3) a subset selection model based on feature selection algorithms. Each ensemble classification model is generated using an optimum-path forest classifier and integrated with a majority voting strategy. The proposed models were applied on a set of 1104 dermoscopic images using a cross-validation procedure. The best results were obtained by the first ensemble classification model that generates a feature subset ensemble based on specific feature groups. The skin lesion diagnosis computational system achieved 94.3% accuracy, 91.8% sensitivity and 96.7% specificity. The input feature manipulation process based on specific feature subsets generated the greatest diversity for the ensemble classification model with very promising results. Copyright © 2017 Elsevier B.V. All rights reserved.

Fabrication of current confinement aperture structure by transforming a conductive GaN:Si epitaxial layer into an insulating GaOx layer.

PubMed

Lin, Chia-Feng; Lee, Wen-Che; Shieh, Bing-Cheng; Chen, Danti; Wang, Dili; Han, Jung

2014-12-24

We report here a simple and robust process to convert embedded conductive GaN epilayers into insulating GaOx and demonstrate its efficacy in vertical current blocking and lateral current steering in a working LED device. The fabrication processes consist of laser scribing, electrochemical (EC) wet-etching, photoelectrochemical (PEC) oxidation, and thermal oxidization of a sacrificial n(+)-GaN:Si layer. The conversion of GaN is made possible through an intermediate stage of porosification where the standard n-type GaN epilayers can be laterally and selectively anodized into a nanoporous (NP) texture while keeping the rest of the layers intact. The fibrous texture of NP GaN with an average wall thickness of less than 100 nm dramatically increases the surface-to-volume ratio and facilitates a rapid oxidation process of GaN into GaOX. The GaOX aperture was formed on the n-side of the LED between the active region and the n-type GaN layer. The wavelength blueshift phenomena of electroluminescence spectra is observed in the treated aperture-emission LED structure (441.5 nm) when compared to nontreated LED structure (443.7 nm) at 0.1 mA. The observation of aperture-confined electroluminescence from an InGaN LED structure suggests that the NP GaN based oxidation will play an enabling role in the design and fabrication of III-nitride photonic devices.

Monolithically integrated bacteriorhodopsin-GaAs/GaAlAs phototransceiver.

PubMed

Shin, Jonghyun; Bhattacharya, Pallab; Xu, Jian; Váró, György

2004-10-01

A monolithically integrated bacteriorhodopsin-semiconductor phototransceiver is demonstrated for the first time to the authors' knowledge. In this novel biophotonic optical interconnect, the input photoexcitation is detected by bacteriorhodopsin (bR) that has been selectively deposited onto the gate of a GaAs-based field-effect transistor. The photovoltage developed across the bR is converted by the transistor into an amplified photocurrent, which drives an integrated light-emitting diode with a Ga0.37Al0.63As active region. Advantage is taken of the high-input impedance of the field-effect transistor, which matches the high internal resistance of bR. The input and output wavelengths are 594 and 655 nm, respectively. The transient response of the optoelectronic circuit to modulated input light has also been studied.

InGaP/InGaAs field-effect transistor typed hydrogen sensor

NASA Astrophysics Data System (ADS)

Tsai, Jung-Hui; Liou, Syuan-Hao; Lin, Pao-Sheng; Chen, Yu-Chi

2018-02-01

In this article, the Pd-based mixture comprising silicon dioxide (SiO2) is applied as sensing material for the InGaP/InGaAs field-effect transistor typed hydrogen sensor. After wet selectively etching the SiO2, the mixture is turned into Pd nanoparticles on an interlayer. Experimental results depict that hydrogen atoms trapped inside the mixture could effectively decrease the gate barrier height and increase the drain current due to the improved sensing properties when Pd nanoparticles were formed by wet etching method. The sensitivity of the gate forward current from air (the reference) to 9800 ppm hydrogen/air environment approaches the high value of 1674. Thus, the studied device shows a good potential for hydrogen sensor and integrated circuit applications.

Attentional Selection of Feature Conjunctions Is Accomplished by Parallel and Independent Selection of Single Features.

PubMed

Andersen, Søren K; Müller, Matthias M; Hillyard, Steven A

2015-07-08

Experiments that study feature-based attention have often examined situations in which selection is based on a single feature (e.g., the color red). However, in more complex situations relevant stimuli may not be set apart from other stimuli by a single defining property but by a specific combination of features. Here, we examined sustained attentional selection of stimuli defined by conjunctions of color and orientation. Human observers attended to one out of four concurrently presented superimposed fields of randomly moving horizontal or vertical bars of red or blue color to detect brief intervals of coherent motion. Selective stimulus processing in early visual cortex was assessed by recordings of steady-state visual evoked potentials (SSVEPs) elicited by each of the flickering fields of stimuli. We directly contrasted attentional selection of single features and feature conjunctions and found that SSVEP amplitudes on conditions in which selection was based on a single feature only (color or orientation) exactly predicted the magnitude of attentional enhancement of SSVEPs when attending to a conjunction of both features. Furthermore, enhanced SSVEP amplitudes elicited by attended stimuli were accompanied by equivalent reductions of SSVEP amplitudes elicited by unattended stimuli in all cases. We conclude that attentional selection of a feature-conjunction stimulus is accomplished by the parallel and independent facilitation of its constituent feature dimensions in early visual cortex. The ability to perceive the world is limited by the brain's processing capacity. Attention affords adaptive behavior by selectively prioritizing processing of relevant stimuli based on their features (location, color, orientation, etc.). We found that attentional mechanisms for selection of different features belonging to the same object operate independently and in parallel: concurrent attentional selection of two stimulus features is simply the sum of attending to each of those features separately. This result is key to understanding attentional selection in complex (natural) scenes, where relevant stimuli are likely to be defined by a combination of stimulus features. Copyright © 2015 the authors 0270-6474/15/359912-08$15.00/0.

The barrier to misfit dislocation glide in continuous, strained, epitaxial layers on patterned substrates

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

Watson, G.P.; Ast, D.G.; Anderson, T.J.

1993-09-01

In a previous report [G. P. Watson, D. G. Ast, T. J. Anderson, and Y. Hayakawa, Appl. Phys. Lett. [bold 58], 2517 (1991)] we demonstrated that the motion of misfit dislocations in InGaAs, grown by organometallic vapor phase epitaxy on patterned GaAs substrates, can be impeded even if the strained epitaxial layer is continuous. Trenches etched into GaAs before growth are known to act as a barrier to misfit dislocation propagation [E. A. Fitzgerald, G. P. Watson, R. E. Proano, D. G. Ast, P. D. Kirchner, G. D. Pettit, and J. M. Woodall, J. Appl. Phys. [bold 65], 2220 (1989)]more » when those trenches create discontinuities in the epitaxial layers; but even shallow trenches, with continuous strained layers following the surface features, can act as barriers. By considering the strain energy required to change the length of the dislocation glide segments that stretch from the interface to the free surface, a simple model is developed that explains the major features of the unique blocking action observed at the trench edges. The trench wall angle is found to be an important parameter in determining whether or not a trench will block dislocation glide. The predicted blocking angles are consistent with observations made on continuous 300 and 600 nm thick In[sub 0.04]Ga[sub 0.96]As films on patterned GaAs. Based on the model, a structure is proposed that may be used as a filter to yield misfit dislocations with identical Burgers vectors or dislocations which slip in only one glide plane.« less

Multisensor-based real-time quality monitoring by means of feature extraction, selection and modeling for Al alloy in arc welding

NASA Astrophysics Data System (ADS)

Zhang, Zhifen; Chen, Huabin; Xu, Yanling; Zhong, Jiyong; Lv, Na; Chen, Shanben

2015-08-01

Multisensory data fusion-based online welding quality monitoring has gained increasing attention in intelligent welding process. This paper mainly focuses on the automatic detection of typical welding defect for Al alloy in gas tungsten arc welding (GTAW) by means of analzing arc spectrum, sound and voltage signal. Based on the developed algorithms in time and frequency domain, 41 feature parameters were successively extracted from these signals to characterize the welding process and seam quality. Then, the proposed feature selection approach, i.e., hybrid fisher-based filter and wrapper was successfully utilized to evaluate the sensitivity of each feature and reduce the feature dimensions. Finally, the optimal feature subset with 19 features was selected to obtain the highest accuracy, i.e., 94.72% using established classification model. This study provides a guideline for feature extraction, selection and dynamic modeling based on heterogeneous multisensory data to achieve a reliable online defect detection system in arc welding.

Geographic atrophy phenotype identification by cluster analysis.

PubMed

Monés, Jordi; Biarnés, Marc

2018-03-01

To identify ocular phenotypes in patients with geographic atrophy secondary to age-related macular degeneration (GA) using a data-driven cluster analysis. This was a retrospective analysis of data from a prospective, natural history study of patients with GA who were followed for ≥6 months. Cluster analysis was used to identify subgroups within the population based on the presence of several phenotypic features: soft drusen, reticular pseudodrusen (RPD), primary foveal atrophy, increased fundus autofluorescence (FAF), greyish FAF appearance and subfoveal choroidal thickness (SFCT). A comparison of features between the subgroups was conducted, and a qualitative description of the new phenotypes was proposed. The atrophy growth rate between phenotypes was then compared. Data were analysed from 77 eyes of 77 patients with GA. Cluster analysis identified three groups: phenotype 1 was characterised by high soft drusen load, foveal atrophy and slow growth; phenotype 3 showed high RPD load, extrafoveal and greyish FAF appearance and thin SFCT; the characteristics of phenotype 2 were midway between phenotypes 1 and 3. Phenotypes differed in all measured features (p≤0.013), with decreases in the presence of soft drusen, foveal atrophy and SFCT seen from phenotypes 1 to 3 and corresponding increases in high RPD load, high FAF and greyish FAF appearance. Atrophy growth rate differed between phenotypes 1, 2 and 3 (0.63, 1.91 and 1.73 mm 2 /year, respectively, p=0.0005). Cluster analysis identified three distinct phenotypes in GA. One of them showed a particularly slow growth pattern. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Enhancing the Discrimination Ability of a Gas Sensor Array Based on a Novel Feature Selection and Fusion Framework.

PubMed

Deng, Changjian; Lv, Kun; Shi, Debo; Yang, Bo; Yu, Song; He, Zhiyi; Yan, Jia

2018-06-12

In this paper, a novel feature selection and fusion framework is proposed to enhance the discrimination ability of gas sensor arrays for odor identification. Firstly, we put forward an efficient feature selection method based on the separability and the dissimilarity to determine the feature selection order for each type of feature when increasing the dimension of selected feature subsets. Secondly, the K-nearest neighbor (KNN) classifier is applied to determine the dimensions of the optimal feature subsets for different types of features. Finally, in the process of establishing features fusion, we come up with a classification dominance feature fusion strategy which conducts an effective basic feature. Experimental results on two datasets show that the recognition rates of Database I and Database II achieve 97.5% and 80.11%, respectively, when k = 1 for KNN classifier and the distance metric is correlation distance (COR), which demonstrates the superiority of the proposed feature selection and fusion framework in representing signal features. The novel feature selection method proposed in this paper can effectively select feature subsets that are conducive to the classification, while the feature fusion framework can fuse various features which describe the different characteristics of sensor signals, for enhancing the discrimination ability of gas sensors and, to a certain extent, suppressing drift effect.

Optimisation of GaN LEDs and the reduction of efficiency droop using active machine learning

DOE PAGES

Rouet-Leduc, Bertrand; Barros, Kipton Marcos; Lookman, Turab; ...

2016-04-26

A fundamental challenge in the design of LEDs is to maximise electro-luminescence efficiency at high current densities. We simulate GaN-based LED structures that delay the onset of efficiency droop by spreading carrier concentrations evenly across the active region. Statistical analysis and machine learning effectively guide the selection of the next LED structure to be examined based upon its expected efficiency as well as model uncertainty. This active learning strategy rapidly constructs a model that predicts Poisson-Schrödinger simulations of devices, and that simultaneously produces structures with higher simulated efficiencies.

Enzymatic glucose detection using ZnO nanorods on the gate region of AlGaN /GaN high electron mobility transistors

NASA Astrophysics Data System (ADS)

Kang, B. S.; Wang, H. T.; Ren, F.; Pearton, S. J.; Morey, T. E.; Dennis, D. M.; Johnson, J. W.; Rajagopal, P.; Roberts, J. C.; Piner, E. L.; Linthicum, K. J.

2007-12-01

ZnO nanorod-gated AlGaN /GaN high electron mobility transistors (HEMTs) are demonstrated for the detection of glucose. A ZnO nanorod array was selectively grown on the gate area using low temperature hydrothermal decomposition to immobilize glucose oxidase (GOx). The one-dimensional ZnO nanorods provide a large effective surface area with high surface-to-volume ratio and provide a favorable environment for the immobilization of GOx. The AlGaN /GaN HEMT drain-source current showed a rapid response of less than 5s when target glucose in a buffer with a pH value of 7.4 was added to the GOx immobilized on the ZnO nanorod surface. We could detect a wide range of concentrations from 0.5nMto125μM. The sensor exhibited a linear range from 0.5nMto14.5μM and an experiment limit of detection of 0.5nM. This demonstrates the possibility of using AlGaN /GaN HEMTs for noninvasive exhaled breath condensate based glucose detection of diabetic application.

Determination of 200 °C Isothermal Section of Al-Ag-Ga Phase Diagram by Microanalysis, X-ray Diffraction, Hardness and Electrical Conductivity Measurements

NASA Astrophysics Data System (ADS)

Premović, Milena; Tomović, Milica; Minić, Duško; Manasijević, Dragan; Živković, Dragana; Ćosović, Vladan; Grković, Vladan; Đorđević, Aleksandar

2017-04-01

Ternary Al-Ag-Ga system at 200 °C was experimentally and thermodynamically assessed. Isothermal section was extrapolated using optimized thermodynamic parameters for constitutive binary systems. Microstructure and phase composition of the selected alloy samples were analyzed using light microscopy, scanning electron microscopy combined with energy-dispersive spectrometry and x-ray powder diffraction technique. The obtained experimental results were found to be in a close agreement with the predicted phase equilibria. Hardness and electrical conductivity of the alloy samples from four vertical sections Al-Ag80Ga20, Al-Ag60Ga40, Ag-Al80Ga20 and Ag-Al60Ga40 of the ternary Al-Ag-Ga system at 200 °C were experimentally determined using Brinell method and eddy current measurements. Additionally, hardness of the individual phases present in the microstructure of the studied alloy samples was determined using Vickers microhardness test. Based on experimentally obtained results, isolines of Brinell hardness and electrical conductivity were calculated for the alloys from isothermal section of the ternary Al-Ag-Ga system at 200 °C.

A Comparative Study of Probability Collectives Based Multi-agent Systems and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Huang, Chien-Feng; Wolpert, David H.; Bieniawski, Stefan; Strauss, Charles E. M.

2005-01-01

We compare Genetic Algorithms (GA's) with Probability Collectives (PC), a new framework for distributed optimization and control. In contrast to GA's, PC-based methods do not update populations of solutions. Instead they update an explicitly parameterized probability distribution p over the space of solutions. That updating of p arises as the optimization of a functional of p. The functional is chosen so that any p that optimizes it should be p peaked about good solutions. The PC approach works in both continuous and discrete problems. It does not suffer from the resolution limitation of the finite bit length encoding of parameters into GA alleles. It also has deep connections with both game theory and statistical physics. We review the PC approach using its motivation as the information theoretic formulation of bounded rationality for multi-agent systems. It is then compared with GA's on a diverse set of problems. To handle high dimensional surfaces, in the PC method investigated here p is restricted to a product distribution. Each distribution in that product is controlled by a separate agent. The test functions were selected for their difficulty using either traditional gradient descent or genetic algorithms. On those functions the PC-based approach significantly outperforms traditional GA's in both rate of descent, trapping in false minima, and long term optimization.

LMD Based Features for the Automatic Seizure Detection of EEG Signals Using SVM.

PubMed

Zhang, Tao; Chen, Wanzhong

2017-08-01

Achieving the goal of detecting seizure activity automatically using electroencephalogram (EEG) signals is of great importance and significance for the treatment of epileptic seizures. To realize this aim, a newly-developed time-frequency analytical algorithm, namely local mean decomposition (LMD), is employed in the presented study. LMD is able to decompose an arbitrary signal into a series of product functions (PFs). Primarily, the raw EEG signal is decomposed into several PFs, and then the temporal statistical and non-linear features of the first five PFs are calculated. The features of each PF are fed into five classifiers, including back propagation neural network (BPNN), K-nearest neighbor (KNN), linear discriminant analysis (LDA), un-optimized support vector machine (SVM) and SVM optimized by genetic algorithm (GA-SVM), for five classification cases, respectively. Confluent features of all PFs and raw EEG are further passed into the high-performance GA-SVM for the same classification tasks. Experimental results on the international public Bonn epilepsy EEG dataset show that the average classification accuracy of the presented approach are equal to or higher than 98.10% in all the five cases, and this indicates the effectiveness of the proposed approach for automated seizure detection.

Numerical analysis of light extraction enhancement of GaN-based thin-film flip-chip light-emitting diodes with high-refractive-index buckling nanostructures

NASA Astrophysics Data System (ADS)

Yue, Qing-Yang; Yang, Yang; Cheng, Zhen-Jia; Guo, Cheng-Shan

2018-06-01

In this work, the light extraction efficiency enhancement of GaN-based thin-film flip-chip (TFFC) light-emitting diodes (LEDs) with high-refractive-index (TiO2) buckling nanostructures was studied using the three-dimensional finite difference time domain method. Compared with 2-D photonic crystals, the buckling structures have the advantages of a random directionality and a broad distribution in periodicity, which can effectively extract the guided light propagating in all azimuthal directions over a wide spectrum. Numerical studies revealed that the light extraction efficiency of buckling-structured LEDs reaches 1.1 times that of triangular lattice photonic crystals. The effects of the buckling structure feature sizes and the thickness of the N-GaN layer on the light extraction efficiency for TFFC LEDs were also investigated systematically. With optimized structural parameters, a significant light extraction enhancement of about 2.6 times was achieved for TiO2 buckling-structured TFFC LEDs compared with planar LEDs.

Ultradeep electron cyclotron resonance plasma etching of GaN

DOE PAGES

Harrison, Sara E.; Voss, Lars F.; Torres, Andrea M.; ...

2017-07-25

Here, ultradeep (≥5 μm) electron cyclotron resonance plasma etching of GaN micropillars was investigated. Parametric studies on the influence of the applied radio-frequency power, chlorine content in a Cl 2/Ar etch plasma, and operating pressure on the etch depth, GaN-to-SiO 2 selectivity, and surface morphology were performed. Etch depths of >10 μm were achieved over a wide range of parameters. Etch rates and sidewall roughness were found to be most sensitive to variations in RF power and % Cl 2 in the etch plasma. Selectivities of >20:1 GaN:SiO 2 were achieved under several chemically driven etch conditions where a maximummore » selectivity of ~39:1 was obtained using a 100% Cl 2 plasma. The etch profile and (0001) surface morphology were significantly influenced by operating pressure and the chlorine content in the plasma. Optimized etch conditions yielded >10 μm tall micropillars with nanometer-scale sidewall roughness, high GaN:SiO 2 selectivity, and nearly vertical etch profiles. These results provide a promising route for the fabrication of ultradeep GaN microstructures for use in electronic and optoelectronic device applications. In addition, dry etch induced preferential crystallographic etching in GaN microstructures is also demonstrated, which may be of great interest for applications requiring access to non- or semipolar GaN surfaces.« less

Modelling Aṣṭādhyāyī: An Approach Based on the Methodology of Ancillary Disciplines (Vedāṅga)

NASA Astrophysics Data System (ADS)

Mishra, Anand

This article proposes a general model based on the common methodological approach of the ancillary disciplines (Vedāṅga) associated with the Vedas taking examples from Śikṣā, Chandas, Vyākaraṇa and Prātiśā khya texts. It develops and elaborates this model further to represent the contents and processes of Aṣṭādhyāyī. Certain key features are added to my earlier modelling of Pāṇinian system of Sanskrit grammar. This includes broader coverage of the Pāṇinian meta-language, mechanism for automatic application of rules and positioning the grammatical system within the procedural complexes of ancillary disciplines.

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities.

PubMed

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities

NASA Astrophysics Data System (ADS)

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

Quantitative strain and compositional studies of InxGa1-xAs Epilayer in a GaAs-based pHEMT device structure by TEM techniques.

PubMed

Sridhara Rao, Duggi V; Sankarasubramanian, Ramachandran; Muraleedharan, Kuttanellore; Mehrtens, Thorsten; Rosenauer, Andreas; Banerjee, Dipankar

2014-08-01

In GaAs-based pseudomorphic high-electron mobility transistor device structures, strain and composition of the In x Ga1-x As channel layer are very important as they influence the electronic properties of these devices. In this context, transmission electron microscopy techniques such as (002) dark-field imaging, high-resolution transmission electron microscopy (HRTEM) imaging, scanning transmission electron microscopy-high angle annular dark field (STEM-HAADF) imaging and selected area diffraction, are useful. A quantitative comparative study using these techniques is relevant for assessing the merits and limitations of the respective techniques. In this article, we have investigated strain and composition of the In x Ga1-x As layer with the mentioned techniques and compared the results. The HRTEM images were investigated with strain state analysis. The indium content in this layer was quantified by HAADF imaging and correlated with STEM simulations. The studies showed that the In x Ga1-x As channel layer was pseudomorphically grown leading to tetragonal strain along the [001] growth direction and that the average indium content (x) in the epilayer is ~0.12. We found consistency in the results obtained using various methods of analysis.

Preparation and composition of superconducting copper oxides based on Ga-O layers

DOEpatents

Dabrowski, Bogdan; Vaughey, J. T.; Poeppelmeier, Kenneth R.

1994-01-01

A high temperature superconducting material with the general formula GaSr.sub.2 Ln.sub.1-x MxCu.sub.2 O.sub.7.+-.w wherein Ln is selected from the group consisting of La, Ce, Pt, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb and Y and M is selected from the group consisting of Ca and Sr, 0.2.ltoreq.x.ltoreq.0.4 and w is a small fraction of one. A method of preparing this high temperature superconducting material is provided which includes heating and cooling a mixture to produce a crystalline material which is subsequently fired, ground and annealed at high pressure and temperature in oxygen to establish superconductivity.

Composition controllability of InGaAs nanowire arrays in selective area growth with controlled pitches on Si platform

NASA Astrophysics Data System (ADS)

Chiba, Kohei; Tomioka, Katsuhiro; Yoshida, Akinobu; Motohisa, Junichi

2017-12-01

Composition controllability of vertical InGaAs nanowires (NWs) on Si integrated by selective area growth was characterized for Si photonics in the optical telecommunication bands. The pitch of pre-patterned holes (NW sites) changed to an In/Ga alloy-composition in the solid phase during the NW growth. The In composition with a nanometer-scaled pitch differed completely from that with a μm-scaled pitch. Accordingly, the growth morphologies of InGaAs NWs show different behavior with respect to the In/Ga ratio.

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

PubMed

Matsukura, Michi; Vecera, Shaun P

2011-02-01

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

Fabrication of high reflectivity nanoporous distributed Bragg reflectors by controlled electrochemical etching of GaN

NASA Astrophysics Data System (ADS)

Lee, Seung-Min; Kang, Jin-Ho; Lee, June Key; Ryu, Sang-Wan

2016-09-01

The nanoporous medium is a valuable feature of optical devices because of its variable optical refractive index with porosity. One important application is in a GaN-based vertical cavity surface emitting laser having a distributed Bragg reflector (DBR) composed of alternating nanoporous and bulk GaNs. However, optimization of the fabrication process for high reflectivity DBRs having wellcontrolled high reflection bands has not been studied yet. We used electrochemical etching to study the fabrication process of a nanoporous GaN DBR and analyzed the relationship between the morphology and optical reflectivity. Several electrolytes were examined for the formation of the optimized nanoporous structure. A highly reflective DBRs having reflectivity of ~100% were obtained over a wide wavelength range of 450-750 nm. Porosification of semiconductors into nanoporous layers could provide a high reflectivity DBR due to controlled index-contrast, which would be advantages for the construction of a high-Q optical cavity.

MOMBE selective infill growth of InP:Si and InGaAs:Si and large area MOMBE regrowth

NASA Astrophysics Data System (ADS)

Schelhase, S.; Böttcher, J.; Gibis, R.; Künzel, H.; Paraskevopoulos, A.

1996-07-01

MOMBE selective infill growth (SIG) of silicon-doped InP and InGaAs was investigated by variation of the principal growth parameters, i.e. temperature, {V}/{III}- ratio and rate. Excellent surface morphology in conjunction with perfect selectivity and defect-free vertical interfaces between the grown layer and the etched substrate sidewall was achieved by an appropriate optimization of the selective growth conditions for InP as well as, for the first time, InGaAs. In the case of SIG of InP, smooth growth boundaries were obtained in the [01¯1] direction, whereas in the [01¯1¯] direction minor growth perturbations occur, which are related to a strong orientation dependent diffusion behavior of the growth species on the growth front. In the case of SIG of InGaAs, slight perturbations accompanied by facet formation at the edges of the selectively grown windows were observed. In the perspective of device application, homogeneous large area MOMBE InGaAs regrowth of the embedded structures was successfully achieved.

Gallium Phosphide Integrated with Silicon Heterojunction Solar Cells

NASA Astrophysics Data System (ADS)

Zhang, Chaomin

It has been a long-standing goal to epitaxially integrate III-V alloys with Si substrates which can enable low-cost microelectronic and optoelectronic systems. Among the III-V alloys, gallium phosphide (GaP) is a strong candidate, especially for solar cells applications. Gallium phosphide with small lattice mismatch ( 0.4%) to Si enables coherent/pseudomorphic epitaxial growth with little crystalline defect creation. The band offset between Si and GaP suggests that GaP can function as an electron-selective contact, and it has been theoretically shown that GaP/Si integrated solar cells have the potential to overcome the limitations of common a-Si based heterojunction (SHJ) solar cells. Despite the promising potential of GaP/Si heterojunction solar cells, there are two main obstacles to realize high performance photovoltaic devices from this structure. First, the growth of the polar material (GaP) on the non-polar material (Si) is a challenge in how to suppress the formation of structural defects, such as anti-phase domains (APD). Further, it is widely observed that the minority-carrier lifetime of the Si substrates is significantly decreased during epitaxially growth of GaP on Si. In this dissertation, two different GaP growth methods were compared and analyzed, including migration-enhanced epitaxy (MEE) and traditional molecular beam epitaxy (MBE). High quality GaP can be realized on precisely oriented (001) Si substrates by MBE growth, and the investigation of structural defect creation in the GaP/Si epitaxial structures was conducted using high resolution X-ray diffraction (HRXRD) and high resolution transmission electron microscopy (HRTEM). The mechanisms responsible for lifetime degradation were further investigated, and it was found that external fast diffusors are the origin for the degradation. Two practical approaches including the use of both a SiNx diffusion barrier layer and P-diffused layers, to suppress the Si minority-carrier lifetime degradation during GaP epitaxial growth on Si by MBE were proposed. To achieve high performance of GaP/Si solar cells, different GaP/Si structures were designed, fabricated and compared, including GaP as a hetero-emitter, GaP as a heterojunction on the rear side, inserting passivation membrane layers at the GaP/Si interface, and GaP/wet-oxide functioning as a passivation contact. A designed of a-Si free carrier-selective contact MoOx/Si/GaP solar cells demonstrated 14.1% power conversion efficiency.

Radial tunnel diodes based on InP/InGaAs core-shell nanowires

NASA Astrophysics Data System (ADS)

Tizno, Ofogh; Ganjipour, Bahram; Heurlin, Magnus; Thelander, Claes; Borgström, Magnus T.; Samuelson, Lars

2017-03-01

We report on the fabrication and characterization of radial tunnel diodes based on InP(n+)/InGaAs(p+) core-shell nanowires, where the effect of Zn-dopant precursor flow on the electrical properties of the devices is evaluated. Selective and local etching of the InGaAs shell is employed to access the nanowire core in the contact process. Devices with an n+-p doping profile show normal diode rectification, whereas n+-p+ junctions exhibit typical tunnel diode characteristics with peak-to-valley current ratios up to 14 at room temperature and 100 at 4.2 K. A maximum peak current density of 28 A/cm2 and a reverse current density of 7.3 kA/cm2 at VSD = -0.5 V are extracted at room temperature after normalization with the effective junction area.

Cl 2-based dry etching of the AlGaInN system in inductively coupled plasmas

NASA Astrophysics Data System (ADS)

Cho, Hyun; Vartuli, C. B.; Abernathy, C. R.; Donovan, S. M.; Pearton, S. J.; Shul, R. J.; Han, J.

1998-12-01

Cl 2-Based inductively coupled plasmas with low additional d.c. self-biases (-100 V) produce convenient etch rates (500-1500 Å·min -1) for GaN, AlN, InN, InAlN and InGaN. A systematic study of the effects of additive gas (Ar, N 2, H 2), discharge composition and ICP source power and chuck power on etch rate and surface morphology has been performed. The general trends are to go through a maximum in etch rate with percent Cl 2 in the discharge for all three mixtures and to have an increase (decrease) in etch rate with source power (pressure). Since the etching is strongly ion-assisted, anisotropic pattern transfer is readily achieved. Maximum etch selectivities of approximately 6 for InN over the other nitrides were obtained.

Platinum-Promoted Ga/Al2O3 as Highly Active, Selective, and Stable Catalyst for the Dehydrogenation of Propane**

PubMed Central

Sattler, Jesper J H B; Gonzalez-Jimenez, Ines D; Luo, Lin; Stears, Brien A; Malek, Andrzej; Barton, David G; Kilos, Beata A; Kaminsky, Mark P; Verhoeven, Tiny W G M; Koers, Eline J; Baldus, Marc; Weckhuysen, Bert M

2014-01-01

A novel catalyst material for the selective dehydrogenation of propane is presented. The catalyst consists of 1000 ppm Pt, 3 wt % Ga, and 0.25 wt % K supported on alumina. We observed a synergy between Ga and Pt, resulting in a highly active and stable catalyst. Additionally, we propose a bifunctional active phase, in which coordinately unsaturated Ga3+ species are the active species and where Pt functions as a promoter. PMID:24989975

AlGaN/GaN high electron mobility transistors with selective area grown p-GaN gates

NASA Astrophysics Data System (ADS)

Yuliang, Huang; Lian, Zhang; Zhe, Cheng; Yun, Zhang; Yujie, Ai; Yongbing, Zhao; Hongxi, Lu; Junxi, Wang; Jinmin, Li

2016-11-01

We report a selective area growth (SAG) method to define the p-GaN gate of AlGaN/GaN high electron mobility transistors (HEMTs) by metal-organic chemical vapor deposition. Compared with Schottky gate HEMTs, the SAG p-GaN gate HEMTs show more positive threshold voltage (V th) and better gate control ability. The influence of Cp2Mg flux of SAG p-GaN gate on the AlGaN/GaN HEMTs has also been studied. With the increasing Cp2Mg from 0.16 μmol/min to 0.20 μmol/min, the V th raises from -0.67 V to -0.37 V. The maximum transconductance of the SAG HEMT at a drain voltage of 10 V is 113.9 mS/mm while that value of the Schottky HEMT is 51.6 mS/mm. The SAG method paves a promising way for achieving p-GaN gate normally-off AlGaN/GaN HEMTs without dry etching damage. Project supported by the National Natural Sciences Foundation of China (Nos. 61376090, 61306008) and the National High Technology Program of China (No. 2014AA032606).

Stress management on underlying GaN-based epitaxial films: A new vision for achieving high-performance LEDs on Si substrates

NASA Astrophysics Data System (ADS)

Lin, Zhiting; Wang, Haiyan; Lin, Yunhao; Wang, Wenliang; Li, Guoqiang

2017-11-01

High-performance blue GaN-based light-emitting diodes (LEDs) on Si substrates have been achieved by applying a suitable tensile stress in the underlying n-GaN. It is demonstrated by simulation that tensile stress in the underlying n-GaN alleviates the negative effect from polarization electric fields on multiple quantum wells but an excessively large tensile stress severely bends the band profile of the electron blocking layer, resulting in carrier loss and large electric resistance. A medium level of tensile stress, which ranges from 4 to 5 GPa, can maximally improve the luminous intensity and decrease forward voltage of LEDs on Si substrates. The LED with the optimal tensile stress shows the largest simulated luminous intensity and the smallest simulated voltage at 35 A/cm2. Compared to the LEDs with a compressive stress of -3 GPa and a large tensile stress of 8 GPa, the improvement of luminous intensity can reach 102% and 28.34%, respectively. Subsequent experimental results provide evidence of the superiority of applying tensile stress in n-GaN. The experimental light output power of the LEDs with a tensile stress of 1.03 GPa is 528 mW, achieving a significant improvement of 19.4% at 35 A/cm2 in comparison to the reference LED with a compressive stress of -0.63 GPa. The forward voltage of this LED is 3.08 V, which is smaller than 3.11 V for the reference LED. This methodology of stress management on underlying GaN-based epitaxial films shows a bright feature for achieving high-performance LED devices on Si substrates.

Mapping QTL for popping expansion volume in popcorn with simple sequence repeat markers.

PubMed

Lu, H-J; Bernardo, R; Ohm, H W

2003-02-01

Popping expansion volume is the most important quality trait in popcorn ( Zea mays L.), but its genetics is not well understood. The objectives of this study were to map quantitative trait loci (QTLs) responsible for popping expansion volume in a popcorn x dent corn cross, and to compare the predicted efficiencies of phenotypic selection, marker-based selection, and marker-assisted selection for popping expansion volume. Of 259 simple sequence repeat (SSR) primer pairs screened, 83 pairs were polymorphic between the H123 (dent corn) and AG19 (popcorn) parental inbreds. Popping test data were obtained for 160 S(1) families developed from the [AG19(H123 x AG19)] BC(1) population. The heritability ( h(2)) for popping expansion volume on an S(1) family mean basis was 0.73. The presence of the gametophyte factor Ga1(s) in popcorn complicates the analysis of popcorn x dent corn crosses. But, from a practical perspective, the linkage between a favorable QTL allele and Ga1(s) in popcorn will lead to selection for the favorable QTL allele. Four QTLs, on chromosomes 1S, 3S, 5S and 5L, jointly explained 45% of the phenotypic variation. Marker-based selection for popping expansion volume would require less time and work than phenotypic selection. But due to the high h(2) of popping expansion volume, marker-based selection was predicted to be only 92% as efficient as phenotypic selection. Marker-assisted selection, which comprises index selection on phenotypic and marker scores, was predicted to be 106% as efficient as phenotypic selection. Overall, our results suggest that phenotypic selection will remain the preferred method for selection in popcorn x dent corn crosses.

Relevance popularity: A term event model based feature selection scheme for text classification.

PubMed

Feng, Guozhong; An, Baiguo; Yang, Fengqin; Wang, Han; Zhang, Libiao

2017-01-01

Feature selection is a practical approach for improving the performance of text classification methods by optimizing the feature subsets input to classifiers. In traditional feature selection methods such as information gain and chi-square, the number of documents that contain a particular term (i.e. the document frequency) is often used. However, the frequency of a given term appearing in each document has not been fully investigated, even though it is a promising feature to produce accurate classifications. In this paper, we propose a new feature selection scheme based on a term event Multinomial naive Bayes probabilistic model. According to the model assumptions, the matching score function, which is based on the prediction probability ratio, can be factorized. Finally, we derive a feature selection measurement for each term after replacing inner parameters by their estimators. On a benchmark English text datasets (20 Newsgroups) and a Chinese text dataset (MPH-20), our numerical experiment results obtained from using two widely used text classifiers (naive Bayes and support vector machine) demonstrate that our method outperformed the representative feature selection methods.

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

PubMed Central

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems. PMID:25961028

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

PubMed

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

Design Issues of GaAs and AlGaAs Delta-Doped p-i-n Quantum-Well APD's

NASA Technical Reports Server (NTRS)

Wang, Yang

1994-01-01

We examine the basic design issues in the optimization of GaAs delta-doped and AlGAs delta-doped quantum-well avalanche photodiode (APD) structures using a theoretical analysis based on an ensemble Monte Carlo simulation. The devices are variations of the p-i-n doped quantum-well structure previously described in the literature. They have the same low-noise, high-gain and high-bandwidth features as the p-i-n doped quantum-well device. However, the use of delta doping provides far greater control or the doping concentrations within each stage possibly enhancing the extent to which the device can be depleted. As a result, it is expected that the proposed devices will operate at higher gain levels (at very low noise) than devices previously developed.

Development of B2 Shape Memory Intermetallics Beyond NiAl, CoNiAl and CoNiGa

NASA Astrophysics Data System (ADS)

Gerstein, G.; Firstov, G. S.; Kosorukova, T. A.; Koval, Yu. N.; Maier, H. J.

2018-06-01

The present study describes the development of shape memory alloys based on NiAl. Initially, this system was considered a promising but unsuccessful neighbour of NiTi. Later, however, shape memory alloys like CoNiAl or CoNiGa were developed that can be considered as NiAl derivatives and already demonstrated good mechanical properties. Yet, these alloys were still inferior to NiTi in most respects. Lately, using a multi-component approach, a CoNiCuAlGaIn high entropy intermetallic compound was developed from the NiAl prototype. This new alloy featured a B2 phase and a martensitic transformation along with a remarkable strength in the as-cast state. In the long-term, this new approach might led to a breakthrough for shape memory alloys in general.

Demonstration of a Retrofit Corrosion-Resistant Fire Hydrant Which Also Protects Against Deliberate Contamination of Critical Army Water Supplies

DTIC Science & Technology

2010-02-01

0.4 Sodium Cyanide 3.7 Fast acting, readily available Sodium Fluoroacetate 1.7 Tasteless, Colorless, Odorless Thallium Nitrate 3.4 Sarin 1 VX 0.15 L iq...TurbChlor TOC 1080 Aflatoxin Cyanide "VX" BUILDING STRONG®27 Beijing Olympics  GuardianBlue Systems selected for securing drinking water during the...Closed BUILDING STRONG®54 Features 304 Stainless Replacement Stem, Tensile Strength 80 Ksi E Coated Sleeve/Seat 11 ga, A-569 Hot Rolled Steel

Data driven analysis of rain events: feature extraction, clustering, microphysical /macro physical relationship

NASA Astrophysics Data System (ADS)

Djallel Dilmi, Mohamed; Mallet, Cécile; Barthes, Laurent; Chazottes, Aymeric

2017-04-01

The study of rain time series records is mainly carried out using rainfall rate or rain accumulation parameters estimated on a fixed integration time (typically 1 min, 1 hour or 1 day). In this study we used the concept of rain event. In fact, the discrete and intermittent natures of rain processes make the definition of some features inadequate when defined on a fixed duration. Long integration times (hour, day) lead to mix rainy and clear air periods in the same sample. Small integration time (seconds, minutes) will lead to noisy data with a great sensibility to detector characteristics. The analysis on the whole rain event instead of individual short duration samples of a fixed duration allows to clarify relationships between features, in particular between macro physical and microphysical ones. This approach allows suppressing the intra-event variability partly due to measurement uncertainties and allows focusing on physical processes. An algorithm based on Genetic Algorithm (GA) and Self Organising Maps (SOM) is developed to obtain a parsimonious characterisation of rain events using a minimal set of variables. The use of self-organizing map (SOM) is justified by the fact that it allows to map a high dimensional data space in a two-dimensional space while preserving as much as possible the initial space topology in an unsupervised way. The obtained SOM allows providing the dependencies between variables and consequently removing redundant variables leading to a minimal subset of only five features (the event duration, the rain rate peak, the rain event depth, the event rain rate standard deviation and the absolute rain rate variation of order 0.5). To confirm relevance of the five selected features the corresponding SOM is analyzed. This analysis shows clearly the existence of relationships between features. It also shows the independence of the inter-event time (IETp) feature or the weak dependence of the Dry percentage in event (Dd%e) feature. This confirms that a rain time series can be considered by an alternation of independent rain event and no rain period. The five selected feature are used to perform a hierarchical clustering of the events. The well-known division between stratiform and convective events appears clearly. This classification into two classes is then refined in 5 fairly homogeneous subclasses. The data driven analysis performed on whole rain events instead of fixed length samples allows identifying strong relationships between macrophysics (based on rain rate) and microphysics (based on raindrops) features. We show that among the 5 identified subclasses some of them have specific microphysics characteristics. Obtaining information on microphysical characteristics of rainfall events from rain gauges measurement suggests many implications in development of the quantitative precipitation estimation (QPE), for the improvement of rain rate retrieval algorithm in remote sensing context.

Toward optimal feature and time segment selection by divergence method for EEG signals classification.

PubMed

Wang, Jie; Feng, Zuren; Lu, Na; Luo, Jing

2018-06-01

Feature selection plays an important role in the field of EEG signals based motor imagery pattern classification. It is a process that aims to select an optimal feature subset from the original set. Two significant advantages involved are: lowering the computational burden so as to speed up the learning procedure and removing redundant and irrelevant features so as to improve the classification performance. Therefore, feature selection is widely employed in the classification of EEG signals in practical brain-computer interface systems. In this paper, we present a novel statistical model to select the optimal feature subset based on the Kullback-Leibler divergence measure, and automatically select the optimal subject-specific time segment. The proposed method comprises four successive stages: a broad frequency band filtering and common spatial pattern enhancement as preprocessing, features extraction by autoregressive model and log-variance, the Kullback-Leibler divergence based optimal feature and time segment selection and linear discriminate analysis classification. More importantly, this paper provides a potential framework for combining other feature extraction models and classification algorithms with the proposed method for EEG signals classification. Experiments on single-trial EEG signals from two public competition datasets not only demonstrate that the proposed method is effective in selecting discriminative features and time segment, but also show that the proposed method yields relatively better classification results in comparison with other competitive methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

Terahertz response in the quantum-Hall-effect regime of a quantum-well-based charge-sensitive infrared phototransistor

NASA Astrophysics Data System (ADS)

Nakagawa, Daisuke; Takizawa, Kazuhiro; Ikushima, Kenji; Kim, Sunmi; Patrashin, Mikhail; Hosako, Iwao; Komiyama, Susumu

2018-04-01

The characteristics of a charge-sensitive infrared phototransistor (CSIP) based on a GaAs/AlGaAs multiple quantum-well (QW) structure are studied under a magnetic field. In the CSIP, the upper QWs serve as a floating gate that is charged by photoexcitation. The photoinduced charges are detected using the resistance of the lowest QW conducting channel. The conducting channel exhibits the integer quantum Hall effect (QHE) in a perpendicular high magnetic field, yielding the magnetic field dependence of the terahertz (THz) response ΔR. We found two different features of ΔR. One is that ΔR switches sign across the QHE plateau, which is explained simply by an increased electron density in the conducting channel. The other feature is observed as an enhanced positive ΔR when a potential barrier is formed in the conducting channel. The latter mechanism can be interpreted as the promotion of edge/bulk scattering due to photoinduced charges. These findings suggest ways to enhance the THz response by using magnetic fields and potential barriers.

Multi-stack InAs/InGaAs Sub-monolayer Quantum Dots Infrared Photodetectors

DTIC Science & Technology

2013-01-01

013110 (2013) Demonstration of high performance bias-selectable dual- band short-/mid-wavelength infrared photodetectors based on type-II InAs/ GaSb ...been used for the growth of QD structures . These include the formation of self-assembled QD, for example, Stranski-Krastanov (SK) growth mode,8,9 atomic...confinement in SML-QD and the reduction in the amount of InAs used per layer of QD can help stack more layers in a 3-dimensional QD structure . Several

MBE System for Antimonide Based Semiconductor Lasers

DTIC Science & Technology

1999-01-31

selectivity are reported as a function of plasma chemistry and DC self-bias. Experiment The samples used in this study are undoped bulk GaSb, InSb...Phys. Lett. 64(13), 1673-1675 (1994). 8. J. W. Lee, J. Hong, E. S. Lambers, C. R. Abernathy, S. J. Pearton, W. S. Hobson, and F. Ren, Plasma Chemistry and...AlGaAsSb are reported as functions of plasma chemistry , ICP power, RF self-bias, and chamber pressure. It is found that physical sputtering desorption of

Modeling the Non-Equilibrium Process of the Chemical Adsorption of Ammonia on GaN(0001) Reconstructed Surfaces Based on Steepest-Entropy-Ascent Quantum Thermodynamics.

PubMed

Kusaba, Akira; Li, Guanchen; von Spakovsky, Michael R; Kangawa, Yoshihiro; Kakimoto, Koichi

2017-08-15

Clearly understanding elementary growth processes that depend on surface reconstruction is essential to controlling vapor-phase epitaxy more precisely. In this study, ammonia chemical adsorption on GaN(0001) reconstructed surfaces under metalorganic vapor phase epitaxy (MOVPE) conditions (3Ga-H and N ad -H + Ga-H on a 2 × 2 unit cell) is investigated using steepest-entropy-ascent quantum thermodynamics (SEAQT). SEAQT is a thermodynamic-ensemble based, first-principles framework that can predict the behavior of non-equilibrium processes, even those far from equilibrium where the state evolution is a combination of reversible and irreversible dynamics. SEAQT is an ideal choice to handle this problem on a first-principles basis since the chemical adsorption process starts from a highly non-equilibrium state. A result of the analysis shows that the probability of adsorption on 3Ga-H is significantly higher than that on N ad -H + Ga-H. Additionally, the growth temperature dependence of these adsorption probabilities and the temperature increase due to the heat of reaction is determined. The non-equilibrium thermodynamic modeling applied can lead to better control of the MOVPE process through the selection of preferable reconstructed surfaces. The modeling also demonstrates the efficacy of DFT-SEAQT coupling for determining detailed non-equilibrium process characteristics with a much smaller computational burden than would be entailed with mechanics-based, microscopic-mesoscopic approaches.

Modeling the Non-Equilibrium Process of the Chemical Adsorption of Ammonia on GaN(0001) Reconstructed Surfaces Based on Steepest-Entropy-Ascent Quantum Thermodynamics

PubMed Central

Kusaba, Akira; von Spakovsky, Michael R.; Kangawa, Yoshihiro; Kakimoto, Koichi

2017-01-01

Clearly understanding elementary growth processes that depend on surface reconstruction is essential to controlling vapor-phase epitaxy more precisely. In this study, ammonia chemical adsorption on GaN(0001) reconstructed surfaces under metalorganic vapor phase epitaxy (MOVPE) conditions (3Ga-H and Nad-H + Ga-H on a 2 × 2 unit cell) is investigated using steepest-entropy-ascent quantum thermodynamics (SEAQT). SEAQT is a thermodynamic-ensemble based, first-principles framework that can predict the behavior of non-equilibrium processes, even those far from equilibrium where the state evolution is a combination of reversible and irreversible dynamics. SEAQT is an ideal choice to handle this problem on a first-principles basis since the chemical adsorption process starts from a highly non-equilibrium state. A result of the analysis shows that the probability of adsorption on 3Ga-H is significantly higher than that on Nad-H + Ga-H. Additionally, the growth temperature dependence of these adsorption probabilities and the temperature increase due to the heat of reaction is determined. The non-equilibrium thermodynamic modeling applied can lead to better control of the MOVPE process through the selection of preferable reconstructed surfaces. The modeling also demonstrates the efficacy of DFT-SEAQT coupling for determining detailed non-equilibrium process characteristics with a much smaller computational burden than would be entailed with mechanics-based, microscopic-mesoscopic approaches. PMID:28809816

High-Performance Schottky Diode Gas Sensor Based on the Heterojunction of Three-Dimensional Nanohybrids of Reduced Graphene Oxide-Vertical ZnO Nanorods on an AlGaN/GaN Layer.

PubMed

Minh Triet, Nguyen; Thai Duy, Le; Hwang, Byeong-Ung; Hanif, Adeela; Siddiqui, Saqib; Park, Kyung-Ho; Cho, Chu-Young; Lee, Nae-Eung

2017-09-13

A Schottky diode based on a heterojunction of three-dimensional (3D) nanohybrid materials, formed by hybridizing reduced graphene oxide (RGO) with epitaxial vertical zinc oxide nanorods (ZnO NRs) and Al 0.27 GaN 0.73 (∼25 nm)/GaN is presented as a new class of high-performance chemical sensors. The RGO nanosheet layer coated on the ZnO NRs enables the formation of a direct Schottky contact with the AlGaN layer. The sensing results of the Schottky diode with respect to NO 2 , SO 2 , and HCHO gases exhibit high sensitivity (0.88-1.88 ppm -1 ), fast response (∼2 min), and good reproducibility down to 120 ppb concentration levels at room temperature. The sensing mechanism of the Schottky diode can be explained by the effective modulation of the reverse saturation current due to the change in thermionic emission carrier transport caused by ultrasensitive changes in the Schottky barrier of a van der Waals heterostructure between RGO and AlGaN layers upon interaction with gas molecules. Advances in the design of a Schottky diode gas sensor based on the heterojunction of high-mobility two-dimensional electron gas channel and highly responsive 3D-engineered sensing nanomaterials have potential not only for the enhancement of sensitivity and selectivity but also for improving operation capability at room temperature.

Bias Selective Operation of Sb-Based Two-Color Photodetectors

NASA Technical Reports Server (NTRS)

Abedin, M. N.; Refaat, Tamer F.; Bhat, Ishwara B.; Xiao, Yegao; Johnson, David G.

2006-01-01

Multicolor detectors have a strong potential to replace conventional single-color detectors in application dealing with the simultaneous detection of more than one wavelength. This will lead to the reduction of heavy and complex optical components now required for spectral discrimination for multi-wavelengths applications. This multicolor technology is simpler, lighter, compact and cheaper with respect to the single-color ones. In this paper, Sb-based two-color detectors fabrication and characterization are presented. The color separation is achieved by fabricating dual band pn junction on a GaSb substrate. The first band consists of an InGaAsSb pn junction for long wavelength detection, while the second band consists of a GaSb pn junction for shorter wavelength detection. Three metal contacts were deposited to access the individual junctions. Surface morphology of multi-layer thin films and also device characteristics of quasi-dual band photodetector were characterized using standard optical microscope and electro-optic techniques respectively. Dark current measurements illustrated the diode behavior of both lattice-matched detector bands. Spectral response measurements indicated either independent operation of both detectors simultaneously, or selective operation of one detector, by the polarity of the bias voltage, while serially accessing both devices.

Defect-Induced Nucleation and Epitaxy: A New Strategy toward the Rational Synthesis of WZ-GaN/3C-SiC Core-Shell Heterostructures.

PubMed

Liu, Baodan; Yang, Bing; Yuan, Fang; Liu, Qingyun; Shi, Dan; Jiang, Chunhai; Zhang, Jinsong; Staedler, Thorsten; Jiang, Xin

2015-12-09

In this work, we demonstrate a new strategy to create WZ-GaN/3C-SiC heterostructure nanowires, which feature controllable morphologies. The latter is realized by exploiting the stacking faults in 3C-SiC as preferential nucleation sites for the growth of WZ-GaN. Initially, cubic SiC nanowires with an average diameter of ∼100 nm, which display periodic stacking fault sections, are synthesized in a chemical vapor deposition (CVD) process to serve as the core of the heterostructure. Subsequently, hexagonal wurtzite-type GaN shells with different shapes are grown on the surface of 3C-SiC wire core. In this context, it is possible to obtain two types of WZ-GaN/3C-SiC heterostructure nanowires by means of carefully controlling the corresponding CVD reactions. Here, the stacking faults, initially formed in 3C-SiC nanowires, play a key role in guiding the epitaxial growth of WZ-GaN as they represent surface areas of the 3C-SiC nanowires that feature a higher surface energy. A dedicated structural analysis of the interfacial region by means of high-resolution transmission electron microscopy (HRTEM) revealed that the disordering of the atom arrangements in the SiC defect area promotes a lattice-matching with respect to the WZ-GaN phase, which results in a preferential nucleation. All WZ-GaN crystal domains exhibit an epitaxial growth on 3C-SiC featuring a crystallographic relationship of [12̅10](WZ-GaN) //[011̅](3C-SiC), (0001)(WZ-GaN)//(111)(3C-SiC), and d(WZ-GaN(0001)) ≈ 2d(3C-SiC(111)). The approach to utilize structural defects of a nanowire core to induce a preferential nucleation of foreign shells generally opens up a number of opportunities for the epitaxial growth of a wide range of semiconductor nanostructures which are otherwise impossible to acquire. Consequently, this concept possesses tremendous potential for the applications of semiconductor heterostructures in various fields such as optics, electrics, electronics, and photocatalysis for energy harvesting and environment processing.

In situ XPS study of methanol reforming on PdGa near-surface intermetallic phases

PubMed Central

Rameshan, Christoph; Stadlmayr, Werner; Penner, Simon; Lorenz, Harald; Mayr, Lukas; Hävecker, Michael; Blume, Raoul; Rocha, Tulio; Teschner, Detre; Knop-Gericke, Axel; Schlögl, Robert; Zemlyanov, Dmitry; Memmel, Norbert; Klötzer, Bernhard

2012-01-01

In situ X-ray photoelectron spectroscopy and low-energy ion scattering were used to study the preparation, (thermo)chemical and catalytic properties of 1:1 PdGa intermetallic near-surface phases. Deposition of several multilayers of Ga metal and subsequent annealing to 503–523 K led to the formation of a multi-layered 1:1 PdGa near-surface state without desorption of excess Ga to the gas phase. In general, the composition of the PdGa model system is much more variable than that of its PdZn counterpart, which results in gradual changes of the near-surface composition with increasing annealing or reaction temperature. In contrast to near-surface PdZn, in methanol steam reforming, no temperature region with pronounced CO2 selectivity was observed, which is due to the inability of purely intermetallic PdGa to efficiently activate water. This allows to pinpoint the water-activating role of the intermetallic/support interface and/or of the oxide support in the related supported PdxGa/Ga2O3 systems, which exhibit high CO2 selectivity in a broad temperature range. In contrast, corresponding experiments starting on the purely bimetallic model surface in oxidative methanol reforming yielded high CO2 selectivity already at low temperatures (∼460 K), which is due to efficient O2 activation on PdGa. In situ detected partial and reversible oxidative Ga segregation on intermetallic PdGa is associated with total oxidation of intermediate C1 oxygenates to CO2. PMID:22875996

Effect of the deposition of cobalt on the optoelectronic properties of quantum-confined In(Ga)As/GaAs heteronanostructures

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

Volkova, N. S., E-mail: volkovans88@mail.ru; Gorshkov, A. P.; Zdoroveyshchev, A. V.

2015-12-15

The systematic features of the inf luence of defect formation during the deposition of a cobalt contact on the optoelectronic characteristics of structures containing InAs/GaAs quantum dots and In{sub x}Ga{sub 1–x}As/GaAs quantum wells are studied. From analysis of the temperature dependences of the photosensitivity of the InAs/GaAs quantum-dot structures, the values of the resultant recombination lifetime of photoexcited charge carriers in quantum dots at different conditions of Co deposition and at different structural parameters are determined.

Selective area growth of N-polar GaN nanorods by plasma-assisted MBE on micro-cone-patterned c-sapphire substrates

NASA Astrophysics Data System (ADS)

Jmerik, V. N.; Kuznetsova, N. V.; Nechaev, D. V.; Shubina, T. V.; Kirilenko, D. A.; Troshkov, S. I.; Davydov, V. Yu.; Smirnov, A. N.; Ivanov, S. V.

2017-11-01

The site-controlled selective area growth of N-polar GaN nanorods (NR) was developed by plasma-assisted MBE (PA MBE) on micro-cone-patterned sapphire substrates (μ-CPSS) by using a two-stage growth process. A GaN nucleation layer grown by migration enhanced epitaxy provides the best selectivity for nucleation of NRs on the apexes of 3.5-μm-diameter cones, whereas the subsequent growth of 1-μm-high NRs with a constant diameter of about 100 nm proceeds by standard high-temperature PA MBE at nitrogen-rich conditions. These results are explained by anisotropy of the surface energy for GaN of different polarity and crystal orientation. The InGaN single quantum wells inserted in the GaN NRs grown on the μ-CPSS demonstrate photoluminescence at 510 nm with a spatially periodic variation of its intensity with a period of ∼6 μm equal to that of the substrate patterning profile.

Comparison of Feature Selection Techniques in Machine Learning for Anatomical Brain MRI in Dementia.

PubMed

Tohka, Jussi; Moradi, Elaheh; Huttunen, Heikki

2016-07-01

We present a comparative split-half resampling analysis of various data driven feature selection and classification methods for the whole brain voxel-based classification analysis of anatomical magnetic resonance images. We compared support vector machines (SVMs), with or without filter based feature selection, several embedded feature selection methods and stability selection. While comparisons of the accuracy of various classification methods have been reported previously, the variability of the out-of-training sample classification accuracy and the set of selected features due to independent training and test sets have not been previously addressed in a brain imaging context. We studied two classification problems: 1) Alzheimer's disease (AD) vs. normal control (NC) and 2) mild cognitive impairment (MCI) vs. NC classification. In AD vs. NC classification, the variability in the test accuracy due to the subject sample did not vary between different methods and exceeded the variability due to different classifiers. In MCI vs. NC classification, particularly with a large training set, embedded feature selection methods outperformed SVM-based ones with the difference in the test accuracy exceeding the test accuracy variability due to the subject sample. The filter and embedded methods produced divergent feature patterns for MCI vs. NC classification that suggests the utility of the embedded feature selection for this problem when linked with the good generalization performance. The stability of the feature sets was strongly correlated with the number of features selected, weakly correlated with the stability of classification accuracy, and uncorrelated with the average classification accuracy.

Glutaric aciduria type I: A treatable neurometabolic disorder.

PubMed

Kamate, Mahesh; Patil, Vishwanath; Chetal, Vivek; Darak, Pavan; Hattiholi, Virupaxi

2012-01-01

Glutaric aciduria Type-I (GA-I) has characteristic clinical and neuroimaging features, which clinches the diagnosis in a majority of patients. However, there have been few case reports on GA-I from India. This study was undertaken to study the clinical presentations, metabolic profile, neuroimaging findings and outcome of patients with GA-I. The present study was a retrospective study. Retrospective review of charts of patients with a diagnosis of GA-I was carried out from March 2008 to April 2010. The clinical, laboratory and neuroimaging findings were extracted in a predesigned proforma and the data was analyzed. Eleven cases were found to have GA-1. Clinical presentation was quite varied. Follow-up of patients revealed that one patient with macrocephaly as the only clinical finding was developmentally normal. One patient with encephalitis-like illness steadily improved and started walking at 2 years. Two patients were bed ridden and had severe dystonia. One patient died during follow-up. The remaining six patients had dystonia and other abnormal movements, but had attained sitting without support and were not ambulatory. GA-I is not an uncommon disorder and diagnosis can be made easily based on clinical, laboratory investigations and neuroimaging findings. It is one of the treatable metabolic disorders and, if managed appropriately, favorable prognosis can be given.

Surface passivation and self-regulated shell growth in selective area-grown GaN-(Al,Ga)N core-shell nanowires.

PubMed

Hetzl, Martin; Winnerl, Julia; Francaviglia, Luca; Kraut, Max; Döblinger, Markus; Matich, Sonja; Fontcuberta I Morral, Anna; Stutzmann, Martin

2017-06-01

The large surface-to-volume ratio of GaN nanowires implicates sensitivity of the optical and electrical properties of the nanowires to their surroundings. The implementation of an (Al,Ga)N shell with a larger band gap around the GaN nanowire core is a promising geometry to seal the GaN surface. We investigate the luminescence and structural properties of selective area-grown GaN-(Al,Ga)N core-shell nanowires grown on Si and diamond substrates. While the (Al,Ga)N shell allows a suppression of yellow defect luminescence from the GaN core, an overall intensity loss due to Si-related defects at the GaN/(Al,Ga)N interface has been observed in the case of Si substrates. Scanning transmission electron microscopy measurements indicate a superior crystal quality of the (Al,Ga)N shell along the nanowire side facets compared to the (Al,Ga)N cap at the top facet. A nucleation study of the (Al,Ga)N shell reveals a pronounced bowing of the nanowires along the c-direction after a short deposition time which disappears for longer growth times. This is assigned to an initially inhomogeneous shell nucleation. A detailed study of the proceeding shell growth allows the formulation of a strain-driven self-regulating (Al,Ga)N shell nucleation model.

Temporal Correlation Mechanisms and Their Role in Feature Selection: A Single-Unit Study in Primate Somatosensory Cortex

PubMed Central

Gomez-Ramirez, Manuel; Trzcinski, Natalie K.; Mihalas, Stefan; Niebur, Ernst

2014-01-01

Studies in vision show that attention enhances the firing rates of cells when it is directed towards their preferred stimulus feature. However, it is unknown whether other sensory systems employ this mechanism to mediate feature selection within their modalities. Moreover, whether feature-based attention modulates the correlated activity of a population is unclear. Indeed, temporal correlation codes such as spike-synchrony and spike-count correlations (rsc) are believed to play a role in stimulus selection by increasing the signal and reducing the noise in a population, respectively. Here, we investigate (1) whether feature-based attention biases the correlated activity between neurons when attention is directed towards their common preferred feature, (2) the interplay between spike-synchrony and rsc during feature selection, and (3) whether feature attention effects are common across the visual and tactile systems. Single-unit recordings were made in secondary somatosensory cortex of three non-human primates while animals engaged in tactile feature (orientation and frequency) and visual discrimination tasks. We found that both firing rate and spike-synchrony between neurons with similar feature selectivity were enhanced when attention was directed towards their preferred feature. However, attention effects on spike-synchrony were twice as large as those on firing rate, and had a tighter relationship with behavioral performance. Further, we observed increased rsc when attention was directed towards the visual modality (i.e., away from touch). These data suggest that similar feature selection mechanisms are employed in vision and touch, and that temporal correlation codes such as spike-synchrony play a role in mediating feature selection. We posit that feature-based selection operates by implementing multiple mechanisms that reduce the overall noise levels in the neural population and synchronize activity across subpopulations that encode the relevant features of sensory stimuli. PMID:25423284

Synthesis of Ga 2O 3 chains with closely spaced knots connected by nanowires

NASA Astrophysics Data System (ADS)

Dai, L.; You, L. P.; Duan, X. F.; Lian, W. C.; Qin, G. G.

2004-07-01

Chains of closely spaced metal or semiconductor particles have potential applications in optoelectronics and single electron devices. We report, for the first time, the synthesis of Ga 2O 3 chains with closely spaced knots connected by nanowires using the thermal evaporation method with a specially designed quartz boat. The Ga 2O 3 chains grew only on the Si substrates where Au catalyst or Ga droplets were coated. The average diameter of the knots is about 450 nm and that of the nanowires is about 50 nm. The selected area electron diffraction of either a knot or a connecting nanowire includes two sets of overlapped single crystal electron diffraction patterns which belong to the [1 0 2] and [1 0 1¯] crystal zone axes of the monoclinic β-Ga 2O 3 phase, respectively. The knot and its neighbor nanowire have the common ( 2¯ 0 1) growth planes at their interface. A mechanism model for the Ga 2O 3 chains synthesis based on the vapor-liquid-solid mechanism is discussed.

Selective formation of GaN-based nanorod heterostructures on soda-lime glass substrates by a local heating method.

PubMed

Hong, Young Joon; Kim, Yong-Jin; Jeon, Jong-Myeong; Kim, Miyoung; Choi, Jun Hee; Baik, Chan Wook; Kim, Sun Il; Park, Sung Soo; Kim, Jong Min; Yi, Gyu-Chul

2011-05-20

We report on the fabrication of high-quality GaN on soda-lime glass substrates, heretofore precluded by both the intolerance of soda-lime glass to the high temperatures required for III-nitride growth and the lack of an epitaxial relationship with amorphous glass. The difficulties were circumvented by heteroepitaxial coating of GaN on ZnO nanorods via a local microheating method. Metal-organic chemical vapor deposition of ZnO nanorods and GaN layers using the microheater arrays produced high-quality GaN/ZnO coaxial nanorod heterostructures at only the desired regions on the soda-lime glass substrates. High-resolution transmission electron microscopy examination of the coaxial nanorod heterostructures indicated the formation of an abrupt, semicoherent interface. Photoluminescence and cathodoluminescence spectroscopy was also applied to confirm the high optical quality of the coaxial nanorod heterostructures. Mg-doped GaN/ZnO coaxial nanorod heterostructure arrays, whose GaN shell layers were grown with various different magnesocene flow rates, were further investigated by using photoluminescence spectroscopy for the p-type doping characteristics. The suggested method for fabrication of III-nitrides on glass substrates signifies potentials for low-cost and large-size optoelectronic device applications.

Gradual tilting of crystallographic orientation and configuration of dislocations in GaN selectively grown by vapour phase epitaxy methods

PubMed

Kuwan; Tsukamoto; Taki; Horibuchi; Oki; Kawaguchi; Shibata; Sawaki; Hiramatsu

2000-01-01

Cross-sectional transmission electron microscope (TEM) observation was performed for selectively grown gallium nitride (GaN) in order to examine the dependence of GaN microstructure on the growth conditions. The GaN films were grown by hydride vapour phase epitaxy (HVPE) or metalorganic vapour phase epitaxy (MOVPE) on GaN covered with a patterned mask. Thin foil specimens for TEM observation were prepared with focused ion beam (FIB) machining apparatus. It was demonstrated that the c-axis of GaN grown over the terrace of the mask tilts towards the centre of the terrace when the GaN is grown in a carrier gas of N2. The wider terrace results in a larger tilting angle if other growth conditions are identical. The tilting is attributed to 'horizontal dislocations' (HDs) generated during the overgrowth of GaN on the mask terrace. The HDs in HVPE-GaN have a semi-loop shape and are tangled with one another, while those in MOVPE-GaN are straight and lined up to form low-angle grain boundaries.

Self-terminated etching of GaN with a high selectivity over AlGaN under inductively coupled Cl2/N2/O2 plasma with a low-energy ion bombardment

NASA Astrophysics Data System (ADS)

Zhong, Yaozong; Zhou, Yu; Gao, Hongwei; Dai, Shujun; He, Junlei; Feng, Meixin; Sun, Qian; Zhang, Jijun; Zhao, Yanfei; DingSun, An; Yang, Hui

2017-10-01

Etching of GaN/AlGaN heterostructure by O-containing inductively coupled Cl2/N2 plasma with a low-energy ion bombardment can be self-terminated at the surface of the AlGaN layer. The estimated etching rates of GaN and AlGaN were 42 and 0.6 nm/min, respectively, giving a selective etching ratio of 70:1. To study the mechanism of the etching self-termination, detailed characterization and analyses were carried out, including X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectroscopy (TOF-SIMS). It was found that in the presence of oxygen, the top surface of the AlGaN layer was converted into a thin film of (Al,Ga)Ox with a high bonding energy, which effectively prevented the underlying atoms from a further etching, resulting in a nearly self-terminated etching. This technique enables a uniform and reproducible fabrication process for enhancement-mode high electron mobility transistors with a p-GaN gate.

Feature selection methods for object-based classification of sub-decimeter resolution digital aerial imagery

USDA-ARS?s Scientific Manuscript database

Due to the availability of numerous spectral, spatial, and contextual features, the determination of optimal features and class separabilities can be a time consuming process in object-based image analysis (OBIA). While several feature selection methods have been developed to assist OBIA, a robust c...

GaAs MOEMS Technology

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

SPAHN, OLGA B.; GROSSETETE, GRANT D.; CICH, MICHAEL J.

2003-03-01

Many MEMS-based components require optical monitoring techniques using optoelectronic devices for converting mechanical position information into useful electronic signals. While the constituent piece-parts of such hybrid opto-MEMS components can be separately optimized, the resulting component performance, size, ruggedness and cost are substantially compromised due to assembly and packaging limitations. GaAs MOEMS offers the possibility of monolithically integrating high-performance optoelectronics with simple mechanical structures built in very low-stress epitaxial layers with a resulting component performance determined only by GaAs microfabrication technology limitations. GaAs MOEMS implicitly integrates the capability for radiation-hardened optical communications into the MEMS sensor or actuator component, a vitalmore » step towards rugged integrated autonomous microsystems that sense, act, and communicate. This project establishes a new foundational technology that monolithically combines GaAs optoelectronics with simple mechanics. Critical process issues addressed include selectivity, electrochemical characteristics, and anisotropy of the release chemistry, and post-release drying and coating processes. Several types of devices incorporating this novel technology are demonstrated.« less

Improved GaSb-based quantum well laser performance through metamorphic growth on GaAs substrates

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

Richardson, Christopher J. K., E-mail: richardson@lps.umd.edu; He, Lei; Apiratikul, Paveen

The promise of the metamorphic growth paradigm is to enable design freedom of the substrate selection criteria beyond current choices that are limited by lattice matching requirements. A demonstration of this emerging degree of freedom is reported here by directly comparing identical laser structures grown both pseudomorphically on a GaSb substrate and metamorphically on a GaAs substrate. Improved thermal performance of the metamorphic laser material enables a higher output power before thermal roll-over begins. These performance gains are demonstrated in minimally processed gain-guided broad-area type-I lasers emitting close to 2-μm wavelengths and mounted p-side up. Continuous wave measurements at roommore » temperature yield a T{sub 0} of 145 K and peak output power of 192 mW from metamorphic lasers, compared to a T{sub 0} of 96 K and peak output power of 164 mW from identical lasers grown pseudomorphically on GaSb.« less

Specific peptide for functionalization of GaN

NASA Astrophysics Data System (ADS)

Estephan, E.; Larroque, C.; Cloitre, T.; Cuisinier, F. J. G.; Gergely, C.

2008-04-01

Nanobiotechnology aims to exploit biomolecular recognition and self-assembly capabilities for integrating advanced materials into medicine and biology. However frequent problems are encountered at the interface of substrate-biological molecule, as the direct physical adsorption of biological molecules is dependent of unpredictable non-specific interactions with the surface, often causing their denaturation. Therefore, a proper functionalization of the substrate should avoid a loss of biological activity. In this work we address the functionalization of the semiconductor GaN (0001) for biosensing applications. The basic interest of using III-V class semiconductors is their good light emitting properties and a fair chemical stability that allows various applications of these materials. The technology chosen to elaborate GaN-specific peptides is the combinatorial phage-display method, a biological screening procedure based on affinity selection. An M13 bacteriophage library has been used to screen 10 10 different peptides against the GaN (0001) surface to finally isolate one specific peptide. The preferential attachment of the biotinylated selected peptide onto the GaN (0001), in close proximity to a surface of different chemical and structural composition has been demonstrated by fluorescence microscopy. Further physicochemical studies have been initiated to evaluate the semiconductor-peptide interface and understand the details in the specific recognition of peptides for semiconductor substrates. Fourier Transform Infrared spectroscopy in Attenuated Total Reflection mode (FTIR-ATR) has been employed to prove the presence of peptides on the surface. Our Atomic Force Microscopy (AFM) studies on the morphology of the GaN surface after functionalization revealed a total surface coverage by a very thin, homogeneous peptide layer. Due to its good biocompatibility, functionalized GaN devices might evolve in a new class of implantable biosensors for medical applications.

QSAR analysis for nano-sized layered manganese-calcium oxide in water oxidation: An application of chemometric methods in artificial photosynthesis.

PubMed

Shahbazy, Mohammad; Kompany-Zareh, Mohsen; Najafpour, Mohammad Mahdi

2015-11-01

Water oxidation is among the most important reactions in artificial photosynthesis, and nano-sized layered manganese-calcium oxides are efficient catalysts toward this reaction. Herein, a quantitative structure-activity relationship (QSAR) model was constructed to predict the catalytic activities of twenty manganese-calcium oxides toward water oxidation using multiple linear regression (MLR) and genetic algorithm (GA) for multivariate calibration and feature selection, respectively. Although there are eight controlled parameters during synthesizing of the desired catalysts including ripening time, temperature, manganese content, calcium content, potassium content, the ratio of calcium:manganese, the average manganese oxidation state and the surface of catalyst, by using GA only three of them (potassium content, the ratio of calcium:manganese and the average manganese oxidation state) were selected as the most effective parameters on catalytic activities of these compounds. The model's accuracy criteria such as R(2)test and Q(2)test in order to predict catalytic rate for external test set experiments; were equal to 0.941 and 0.906, respectively. Therefore, model reveals acceptable capability to anticipate the catalytic activity. Copyright © 2015 Elsevier B.V. All rights reserved.

Photocurrent characteristics of metal–AlGaN/GaN Schottky-on-heterojunction diodes induced by GaN interband excitation

NASA Astrophysics Data System (ADS)

Tang, Xi; Li, Baikui; Chen, Kevin J.; Wang, Jiannong

2018-05-01

The photocurrent characteristics of metal–AlGaN/GaN Schottky-on-heterojunction diodes were investigated. When the photon energy of incident light was larger than the bandgap of GaN but smaller than that of AlGaN, the alternating-current (ac) photocurrent measured using lock-in techniques increased with the chopper frequency. Analyzing the generation and flow processes of photocarriers revealed that the photocurrent induced by GaN interband excitation featured a transient behavior, and its direction reversed when the light excitation was removed. The abnormal dependence of the measured ac photocurrent magnitude on the chopper frequency was explained considering the detection principles of a lock-in amplifier.

Constraint programming based biomarker optimization.

PubMed

Zhou, Manli; Luo, Youxi; Sun, Guoquan; Mai, Guoqin; Zhou, Fengfeng

2015-01-01

Efficient and intuitive characterization of biological big data is becoming a major challenge for modern bio-OMIC based scientists. Interactive visualization and exploration of big data is proven to be one of the successful solutions. Most of the existing feature selection algorithms do not allow the interactive inputs from users in the optimizing process of feature selection. This study investigates this question as fixing a few user-input features in the finally selected feature subset and formulates these user-input features as constraints for a programming model. The proposed algorithm, fsCoP (feature selection based on constrained programming), performs well similar to or much better than the existing feature selection algorithms, even with the constraints from both literature and the existing algorithms. An fsCoP biomarker may be intriguing for further wet lab validation, since it satisfies both the classification optimization function and the biomedical knowledge. fsCoP may also be used for the interactive exploration of bio-OMIC big data by interactively adding user-defined constraints for modeling.

In vivo diagnosis of cervical precancer using Raman spectroscopy and genetic algorithm techniques.

PubMed

Duraipandian, Shiyamala; Zheng, Wei; Ng, Joseph; Low, Jeffrey J H; Ilancheran, A; Huang, Zhiwei

2011-10-21

This study aimed to evaluate the clinical utility of applying near-infrared (NIR) Raman spectroscopy and genetic algorithm-partial least squares-discriminant analysis (GA-PLS-DA) to identify biomolecular changes of cervical tissues associated with dysplastic transformation during colposcopic examination. A total of 105 in vivo Raman spectra were measured from 57 cervical sites (35 normal and 22 precancer sites) of 29 patients recruited, in which 65 spectra were from normal sites, while 40 spectra were from cervical precancerous lesions (i.e., 7 low-grade CIN and 33 high-grade CIN). The GA feature selection technique incorporated with PLS was utilized to study the significant biochemical Raman bands for differentiation between normal and precancer cervical tissues. The GA-PLS-DA algorithm with double cross-validation (dCV) identified seven diagnostically significant Raman bands in the ranges of 925-935, 979-999, 1080-1090, 1240-1260, 1320-1340, 1400-1420, and 1625-1645 cm(-1) related to proteins, nucleic acids and lipids in tissue, and yielded a diagnostic accuracy of 82.9% (sensitivity of 72.5% (29/40) and specificity of 89.2% (58/65)) for precancer detection. The results of this exploratory study suggest that Raman spectroscopy in conjunction with GA-PLS-DA and dCV methods has the potential to provide clinically significant discrimination between normal and precancer cervical tissues at the molecular level.

Excited states of neutral donor bound excitons in GaN

NASA Astrophysics Data System (ADS)

Callsen, G.; Kure, T.; Wagner, M. R.; Butté, R.; Grandjean, N.

2018-06-01

We investigate the excited states of a neutral donor bound exciton (D0X) in bulk GaN by means of high-resolution, polychromatic photoluminescence excitation (PLE) spectroscopy. The optically most prominent donor in our sample is silicon accompanied by only a minor contribution of oxygen—the key for an unambiguous assignment of excited states. Consequently, we can observe a multitude of Si0X-related excitation channels with linewidths down to 200 μeV. Two groups of excitation channels are identified, belonging either to rotational-vibrational or electronic excited states of the hole in the Si0X complex. Such identification is achieved by modeling the excited states based on the equations of motion for a Kratzer potential, taking into account the particularly large anisotropy of effective hole masses in GaN. Furthermore, several ground- and excited states of the exciton-polaritons and the dominant bound exciton are observed in the photoluminescence (PL) and PLE spectra, facilitating an estimate of the associated complex binding energies. Our data clearly show that great care must be taken if only PL spectra of D0X centers in GaN are analyzed. Every PL feature we observe at higher emission energies with regard to the Si0X ground state corresponds to an excited state. Hence, any unambiguous peak identification renders PLE spectra highly valuable, as important spectral features are obscured in common PL spectra. Here, GaN represents a particular case among the wide-bandgap, wurtzite semiconductors, as comparably low localization energies for common D0X centers are usually paired with large emission linewidths and the prominent optical signature of exciton-polaritons, making the sole analysis of PL spectra a challenging task.

Hierarchical Gene Selection and Genetic Fuzzy System for Cancer Microarray Data Classification

PubMed Central

Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

2015-01-01

This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice. PMID:25823003

Hierarchical gene selection and genetic fuzzy system for cancer microarray data classification.

PubMed

Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

2015-01-01

This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice.

Synthesis and Raman scattering of GaN nanorings, nanoribbons and nanowires

NASA Astrophysics Data System (ADS)

Li, Z. J.; Chen, X. L.; Li, H. J.; Tu, Q. Y.; Yang, Z.; Xu, Y. P.; Hu, B. Q.

Low-dimensional GaN materials, including nanorings, nanoribbons and smooth nanowires have been synthesized by reacting gallium and ammonia using Ag particles as a catalyst on the substrate of MgO single crystals. They were characterized by field emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDX) and X-ray diffraction (XRD). EDX, XRD indicated that the low-dimensional nanomaterials were wurtzite GaN. New features are found in Raman scatterings for these low-dimensional GaN materials, which are different from the previous observations of GaN materials.

Effect of screw threading dislocations and inverse domain boundaries in GaN on the shape of reciprocal-space maps.

PubMed

Barchuk, Mykhailo; Motylenko, Mykhaylo; Lukin, Gleb; Pätzold, Olf; Rafaja, David

2017-04-01

The microstructure of polar GaN layers, grown by upgraded high-temperature vapour phase epitaxy on [001]-oriented sapphire substrates, was studied by means of high-resolution X-ray diffraction and transmission electron microscopy. Systematic differences between reciprocal-space maps measured by X-ray diffraction and those which were simulated for different densities of threading dislocations revealed that threading dislocations are not the only microstructure defect in these GaN layers. Conventional dark-field transmission electron microscopy and convergent-beam electron diffraction detected vertical inversion domains as an additional microstructure feature. On a series of polar GaN layers with different proportions of threading dislocations and inversion domain boundaries, this contribution illustrates the capability and limitations of coplanar reciprocal-space mapping by X-ray diffraction to distinguish between these microstructure features.

MADS-Box Genes and Gibberellins Regulate Bolting in Lettuce (Lactuca sativa L.)

PubMed Central

Han, Yingyan; Chen, Zijing; Lv, Shanshan; Ning, Kang; Ji, Xueliang; Liu, Xueying; Wang, Qian; Liu, Renyi; Fan, Shuangxi; Zhang, Xiaolan

2016-01-01

Bolting in lettuce is promoted by high temperature and bolting resistance is of great economic importance for lettuce production. But how bolting is regulated at the molecular level remains elusive. Here, a bolting resistant line S24 and a bolting sensitive line S39 were selected for morphological, physiological, transcriptomic and proteomic comparisons. A total of 12204 genes were differentially expressed in S39 vs. S24. Line S39 was featured with larger leaves, higher levels of chlorophyll, soluble sugar, anthocyanin and auxin, consistent with its up-regulation of genes implicated in photosynthesis, oxidation-reduction and auxin actions. Proteomic analysis identified 30 differentially accumulated proteins in lines S39 and S24 upon heat treatment, and 19 out of the 30 genes showed differential expression in the RNA-Seq data. Exogenous gibberellins (GA) treatment promoted bolting in both S39 and S24, while 12 flowering promoting MADS-box genes were specifically induced in line S39, suggesting that although GA regulates bolting in lettuce, it may be the MADS-box genes, not GA, that plays a major role in differing the bolting resistance between these two lettuce lines. PMID:28018414

Selective principal component regression analysis of fluorescence hyperspectral image to assess aflatoxin contamination in corn

USDA-ARS?s Scientific Manuscript database

Selective principal component regression analysis (SPCR) uses a subset of the original image bands for principal component transformation and regression. For optimal band selection before the transformation, this paper used genetic algorithms (GA). In this case, the GA process used the regression co...

Natural image classification driven by human brain activity

NASA Astrophysics Data System (ADS)

Zhang, Dai; Peng, Hanyang; Wang, Jinqiao; Tang, Ming; Xue, Rong; Zuo, Zhentao

2016-03-01

Natural image classification has been a hot topic in computer vision and pattern recognition research field. Since the performance of an image classification system can be improved by feature selection, many image feature selection methods have been developed. However, the existing supervised feature selection methods are typically driven by the class label information that are identical for different samples from the same class, ignoring with-in class image variability and therefore degrading the feature selection performance. In this study, we propose a novel feature selection method, driven by human brain activity signals collected using fMRI technique when human subjects were viewing natural images of different categories. The fMRI signals associated with subjects viewing different images encode the human perception of natural images, and therefore may capture image variability within- and cross- categories. We then select image features with the guidance of fMRI signals from brain regions with active response to image viewing. Particularly, bag of words features based on GIST descriptor are extracted from natural images for classification, and a sparse regression base feature selection method is adapted to select image features that can best predict fMRI signals. Finally, a classification model is built on the select image features to classify images without fMRI signals. The validation experiments for classifying images from 4 categories of two subjects have demonstrated that our method could achieve much better classification performance than the classifiers built on image feature selected by traditional feature selection methods.

Preparation and composition of superconducting copper oxides based on Ga-O layers

DOEpatents

Dabrowski, B.; Vaughey, J.T.; Poeppelmeier, K.R.

1994-12-20

A high temperature superconducting material with the general formula GaSr[sub 2]Ln[sub 1[minus]x]M[sub x]Cu[sub 2]O[sub 7[+-]w] wherein Ln is selected from the group consisting of La, Ce, Pt, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb and Y and M is selected from the group consisting of C and Sr, 0.2[<=]x[<=]0.4 and w is a small fraction of one. A method of preparing this high temperature superconducting material is provided which includes heating and cooling a mixture to produce a crystalline material which is subsequently fired, ground and annealed at high pressure and temperature in oxygen to establish superconductivity. 14 figures.

A Study of Penalty Function Methods for Constraint Handling with Genetic Algorithm

NASA Technical Reports Server (NTRS)

Ortiz, Francisco

2004-01-01

COMETBOARDS (Comparative Evaluation Testbed of Optimization and Analysis Routines for Design of Structures) is a design optimization test bed that can evaluate the performance of several different optimization algorithms. A few of these optimization algorithms are the sequence of unconstrained minimization techniques (SUMT), sequential linear programming (SLP) and the sequential quadratic programming techniques (SQP). A genetic algorithm (GA) is a search technique that is based on the principles of natural selection or "survival of the fittest". Instead of using gradient information, the GA uses the objective function directly in the search. The GA searches the solution space by maintaining a population of potential solutions. Then, using evolving operations such as recombination, mutation and selection, the GA creates successive generations of solutions that will evolve and take on the positive characteristics of their parents and thus gradually approach optimal or near-optimal solutions. By using the objective function directly in the search, genetic algorithms can be effectively applied in non-convex, highly nonlinear, complex problems. The genetic algorithm is not guaranteed to find the global optimum, but it is less likely to get trapped at a local optimum than traditional gradient-based search methods when the objective function is not smooth and generally well behaved. The purpose of this research is to assist in the integration of genetic algorithm (GA) into COMETBOARDS. COMETBOARDS cast the design of structures as a constrained nonlinear optimization problem. One method used to solve constrained optimization problem with a GA to convert the constrained optimization problem into an unconstrained optimization problem by developing a penalty function that penalizes infeasible solutions. There have been several suggested penalty function in the literature each with there own strengths and weaknesses. A statistical analysis of some suggested penalty functions is performed in this study. Also, a response surface approach to robust design is used to develop a new penalty function approach. This new penalty function approach is then compared with the other existing penalty functions.

A Filter Feature Selection Method Based on MFA Score and Redundancy Excluding and It's Application to Tumor Gene Expression Data Analysis.

PubMed

Li, Jiangeng; Su, Lei; Pang, Zenan

2015-12-01

Feature selection techniques have been widely applied to tumor gene expression data analysis in recent years. A filter feature selection method named marginal Fisher analysis score (MFA score) which is based on graph embedding has been proposed, and it has been widely used mainly because it is superior to Fisher score. Considering the heavy redundancy in gene expression data, we proposed a new filter feature selection technique in this paper. It is named MFA score+ and is based on MFA score and redundancy excluding. We applied it to an artificial dataset and eight tumor gene expression datasets to select important features and then used support vector machine as the classifier to classify the samples. Compared with MFA score, t test and Fisher score, it achieved higher classification accuracy.

Aptasensor based optical detection of glycated albumin for diabetes mellitus diagnosis

NASA Astrophysics Data System (ADS)

Ghosh, Shreya; Datta, Debopam; Cheema, Mehar; Dutta, Mitra; Stroscio, Michael A.

2017-10-01

Glycated albumin (GA) has been reported as an important biomarker for diabetes mellitus. This study investigates an optical sensor comprised of deoxyribonucleic acid (DNA) aptamer, semiconductor quantum dot and gold (Au) nanoparticle for the detection of GA. The system functions as a ‘turn on’ sensor because an increase in photoluminescence intensity is observed upon the addition of GA to the sensor. This is possibly because of the structure of the DNA aptamer, which folds to form a large hairpin loop before the addition of the analyte and is assumed to open up after the addition of target to the sensor in order to bind to GA. This pushes the quantum dot and the Au nanoparticle away causing an increase in photoluminescence. A linear increase in photoluminescence intensity and quenching efficiency of the sensor is observed as the GA concentration is varied between 0-14 500 nM. Time based photoluminescence studies with the sensor show the decrease in binding rate of the aptamer to the target within a specific time period. The sensor was found to have a higher selectivity towards GA than other control proteins. Further investigation of this simple sensor with greater number of clinical samples can open up avenues for an efficient diagnosis and monitoring of diabetes mellitus when used in conjunction with the traditional method of glucose level monitoring.

Centrosymmetry vs noncentrosymmetry in La2Ga0.33SbS5 and Ce4GaSbS9 based on the interesting size effects of lanthanides: Syntheses, crystal structures, and optical properties

NASA Astrophysics Data System (ADS)

Zhao, Hua-Jun

2016-05-01

Two new quaternary sulfides La2Ga0.33SbS5 and Ce4GaSbS9 have been prepared from stoichiometric elements at 1223 K in an evacuated silica tube. Interestingly, La2Ga0.33SbS5 crystallizes in the centrosymmetric structure, while Ce4GaSbS9 crystallizes in the noncentrosymmetric structure, which show obvious size effects of lanthanides on the crystal structures of these two compounds. Ce4GaSbS9 belongs to RE4GaSbS9 (RE=Pr, Nd, Sm, Gd-Ho) structure type with a=13.8834(9) Å, b=14.3004(11) Å, c=14.4102(13) Å, V=2861.0(4) Å3. The structure features infinite chains of [Ga2Sb2S1110-]∞ propagating along a direction separated by Ce3+ cations and S2- anions. La2Ga0.33SbS5 adopts the family of La4FeSb2S10-related structure with a=7.5193(6) Å, c=13.4126(17) Å, V=758.35(13) Å3. Its structure is built up from the alternate stacking of La/Sb/S and La/Ga/S 2D building blocks. The La/Sb/S slabs consist of teeter-totter chains of Sb1S4 seesaws, which are connected via sharing the apexes of μ4-S1. Moreover, La1 is positionally disordered with Sb1 and stabilized in a bicapped trigonal prismatic coordination sphere. Between these La/Sb/S slabs, La2S8 square antiprisms are connected via edge-sharing into 2D building blocks, creating tetrahedral sites partially occupied by the Ga1 atoms. UV/Vis diffuse reflectance spectroscopy study shows that the optical gap of La2Ga0.33SbS5 is about 1.76 eV.

Structural features of the DNA hairpin d(ATCCTA-GTTA-TAGGAT): formation of a G-A base pair in the loop.

PubMed Central

van Dongen, M J; Mooren, M M; Willems, E F; van der Marel, G A; van Boom, J H; Wijmenga, S S; Hilbers, C W

1997-01-01

The three-dimensional structure of the hairpin formed by d(ATCCTA-GTTA-TAGGAT) has been determined by means of two-dimensional NMR studies, distance geometry and molecular dynamics calculations. The first and the last residues of the tetraloop of this hairpin form a sheared G-A base pair on top of the six Watson-Crick base pairs in the stem. The glycosidic torsion angles of the guanine and adenine residues in the G-A base pair reside in the anti and high- anti domain ( approximately -60 degrees ) respectively. Several dihedral angles in the loop adopt non-standard values to accommodate this base pair. The first and second residue in the loop are stacked in a more or less normal helical fashion; the fourth loop residue also stacks upon the stem, while the third residue is directed away from the loop region. The loop structure can be classified as a so-called type-I loop, in which the bases at the 5'-end of the loop stack in a continuous fashion. In this situation, loop stability is unlikely to depend heavily on the nature of the unpaired bases in the loop. Moreover, the present study indicates that the influence of the polarity of a closing A.T pair is much less significant than that of a closing C.G base pair. PMID:9092659

Photo-excited zero-resistance states in quasi-two-dimensional GaAs / Al xGa 1- xAs devices

NASA Astrophysics Data System (ADS)

Mani, R. G.

2007-12-01

We illustrate some experimental features of the recently discovered radiation-induced zero-resistance states in the high-mobility GaAs/AlGaAs system, with a special emphasis on the interplay between the radiation-induced changes in the diagonal resistance and the Hall effect. We show that, quantum Hall effects, i.e., quantum Hall plateaus, disappear under photoexcitation, at the minima of the radiation-induced magnetoresistance oscillations.

Optical Coherence Tomography Reflective Drusen Substructures Predict Progression to Geographic Atrophy in Age-related Macular Degeneration.

PubMed

Veerappan, Malini; El-Hage-Sleiman, Abdul-Karim M; Tai, Vincent; Chiu, Stephanie J; Winter, Katrina P; Stinnett, Sandra S; Hwang, Thomas S; Hubbard, G Baker; Michelson, Michelle; Gunther, Randall; Wong, Wai T; Chew, Emily Y; Toth, Cynthia A

2016-12-01

Structural and compositional heterogeneity within drusen comprising lipids, carbohydrates, and proteins have been previously described. We sought to detect and define phenotypic patterns of drusen heterogeneity in the form of optical coherence tomography-reflective drusen substructures (ODS) and examine their associations with age-related macular degeneration (AMD)-related features and AMD progression. Retrospective analysis in a prospective study. Patients with intermediate AMD (n = 349) enrolled in the multicenter Age-Related Eye Disease Study 2 (AREDS2) ancillary spectral-domain optical coherence tomography (SD OCT) study. Baseline SD OCT scans of 1 eye per patient were analyzed for the presence of ODS. Cross-sectional and longitudinal associations of ODS presence with AMD-related features visible on SD OCT and color photographs, including drusen volume, geographic atrophy (GA), and preatrophic features, were evaluated for the entire macular region. Similar associations were also made locally within a 0.5-mm-diameter region around individual ODS and corresponding control region without ODS in the same eye. Preatrophy SD OCT changes and GA, central GA, and choroidal neovascularization (CNV) from color photographs. Four phenotypic subtypes of ODS were defined: low reflective cores, high reflective cores, conical debris, and split drusen. Among the 349 participants, there were 307 eligible eyes and 74 (24%) had at least 1 ODS. The ODS at baseline were associated with (1) greater macular drusen volume at baseline (P < 0.001), (2) development of preatrophic changes at year 2 (P = 0.001-0.01), and (3) development of macular GA (P = 0.005) and preatrophic changes at year 3 (P = 0.002-0.008), but not development of CNV. The ODS at baseline in a local region were associated with (1) presence of preatrophy changes at baseline (P = 0.02-0.03) and (2) development of preatrophy changes at years 2 and 3 within the region (P = 0.008-0.05). Optical coherence tomography-reflective drusen substructures are optical coherence tomography-based biomarkers of progression to GA, but not to CNV, in eyes with intermediate AMD. Optical coherence tomography-reflective drusen substructures may be a clinical entity helpful in monitoring AMD progression and informing mechanisms in GA pathogenesis. Copyright © 2016 American Academy of Ophthalmology. All rights reserved.

Optical Coherence Tomography Reflective Drusen Substructures Predict Progression to Geographic Atrophy in Non-neovascular Age-related Macular Degeneration

PubMed Central

Veerappan, Malini; El-Hage Sleiman, Abdul-Karim M.; Tai, Vincent; Chiu, Stephanie J.; Winter, Katrina P.; Stinnett, Sandra S.; Hwang, Thomas S.; Hubbard, G. Baker; Michelson, Michelle; Gunther, Randall; Wong, Wai T.; Chew, Emily Y.; Toth, Cynthia A.

2016-01-01

Purpose Structural and compositional heterogeneity within drusen, composed of lipid, carbohydrates, and proteins, have been previously described. We sought to detect and define phenotypic patterns of drusen heterogeneity in the form of optical coherence tomography–reflective drusen substructures (ODS) and examine their associations with age-related macular degeneration (AMD)-related features and AMD progression. Design Retrospective analysis in a prospective study. Participants Patients with intermediate AMD (n = 349) enrolled in the multicenter Age-Related Eye Disease Study 2 (AREDS2) ancillary spectral domain optical coherence tomography (SD OCT) study. Methods Baseline SD OCT scans of 1 eye per patient were analyzed for presence of ODS. Cross-sectional and longitudinal associations of ODS presence with AMD-related features visible on SD OCT and color photographs, including drusen volume, geographic atrophy (GA), and preatrophic features, were evaluated for the entire macular region. Similar associations were also made locally within a 0.5-mm diameter region around individual ODS and corresponding control region without ODS in the same eye. Main Outcome Measures Preatrophy SD OCT changes and GA, central GA, and choroidal neovascularization (CNV) from color photographs. Results Four phenotypic subtypes of ODS were defined: low reflective cores, high reflective cores, conical debris, and split drusen. Of the 349 participants, there were 307 eligible eyes and 74 (24%) had at least 1 ODS. The ODS at baseline were associated with (1) greater macular drusen volume at baseline (P < 0.001), (2) development of preatrophic changes at year 2 (P = 0.001–0.01), and (3) development of macular GA (P = 0.005) and preatrophic changes at year 3 (P = 0.002–0.008), but not development of CNV. The ODS at baseline in a local region were associated with (1) presence of preatrophy changes at baseline (P = 0.02-0.03) and (2) development of preatrophy changes at years 2 and 3 within the region (P = 0.008-0.05). Conclusions Optical coherence tomography–reflective drusen substructures are optical coherence tomography–based biomarkers of progression to GA, but not to CNV, in eyes with intermediate AMD. Optical coherence tomography–reflective drusen substructures may be a clinical entity helpful in monitoring AMD progression and informing mechanisms in GA pathogenesis. PMID:27793356

Nonlinear absorption in AlGaAs/GaAs multiple quantum well structures grown by metalorganic chemical vapor deposition

NASA Technical Reports Server (NTRS)

Lee, H. C.; Hariz, A.; Dapkus, P. D.; Kost, A.; Kawase, M.

1987-01-01

This paper reports the study of growth conditions for achieving the sharp exciton resonances and low-intensity saturation of these resonances in AlGaAs-GaAs multiple quantum well structures grown by metalorganic chemical vapor deposition. Low growth temperature is necessary to observe this sharp resonance feature at room temperature. The optimal growth conditions are a tradeoff between the high temperatures required for high quality AlGaAs and low temperatures required for high-purity GaAs. A strong optical saturation of the excitonic absorption has been observed. A saturation density as low as 250 W/sq cm is reported.

CL-imaging and ion microprobe dating of single zircons from a high-grade rock from the Central Zone, Limpopo Belt, South Africa: Evidence for a single metamorphic event at ˜2.0 Ga

NASA Astrophysics Data System (ADS)

Mouri, H.; Brandl, G.; Whitehouse, M.; de Waal, S.; Guiraud, M.

2008-02-01

The combination of ion microprobe dating and cathodoluminescence (CL) imaging of zircons from a high-grade rock from the Central Zone of the Limpopo Belt were used to constrain the age of metamorphic events in the area. Zircon grains extracted from an orthopyroxene-gedrite-bearing granulite were prepared for single crystal CL-imaging and ion microprobe dating. The grains display complex zoning when using SEM-based CL-imaging. A common feature in most grains is the presence of a distinct core with a broken oscillatory zoned structure, which clearly appears to be the remnant of an original grain of igneous origin. This core is overgrown by an unzoned thin rim measuring about 10-30 μm in diameter, which is considered as new zircon growth during a single metamorphic event. Selected domains of the zircon grains were analysed for U, Pb and Th isotopic composition using a CAMECA IMS 1270 ion microprobe (Nordsim facility). Most of the grains define a near-concordant cluster with some evidence of Pb loss. The most concordant ages of the cores yielded a weighted mean 207Pb/ 206Pb age of 2689 ± 15 (2 σ) Ma, interpreted as the age of the protolith of an igneous origin. The unzoned overgrowths of the zircon grains yielded a considerably younger weighted mean 207Pb/ 206Pb age of ˜2006.5 ± 8.0 Ma (2 σ), and these data are interpreted to reflect closely the age of the ubiquitous high-grade metamorphic event in the Central Zone. This study shows clearly, based on both the internal structure of the zircons and the data obtained by ion microprobe dating, that only a single metamorphic event is recorded by the studied 2.69 Ga old rocks, and we found no evidence of an earlier metamorphic event at ˜2.5 Ga as postulated earlier by some workers.

A comparison of three feature selection methods for object-based classification of sub-decimeter resolution UltraCam-L imagery

USDA-ARS?s Scientific Manuscript database

The availability of numerous spectral, spatial, and contextual features with object-based image analysis (OBIA) renders the selection of optimal features a time consuming and subjective process. While several feature election methods have been used in conjunction with OBIA, a robust comparison of th...

Multi-level gene/MiRNA feature selection using deep belief nets and active learning.

PubMed

Ibrahim, Rania; Yousri, Noha A; Ismail, Mohamed A; El-Makky, Nagwa M

2014-01-01

Selecting the most discriminative genes/miRNAs has been raised as an important task in bioinformatics to enhance disease classifiers and to mitigate the dimensionality curse problem. Original feature selection methods choose genes/miRNAs based on their individual features regardless of how they perform together. Considering group features instead of individual ones provides a better view for selecting the most informative genes/miRNAs. Recently, deep learning has proven its ability in representing the data in multiple levels of abstraction, allowing for better discrimination between different classes. However, the idea of using deep learning for feature selection is not widely used in the bioinformatics field yet. In this paper, a novel multi-level feature selection approach named MLFS is proposed for selecting genes/miRNAs based on expression profiles. The approach is based on both deep and active learning. Moreover, an extension to use the technique for miRNAs is presented by considering the biological relation between miRNAs and genes. Experimental results show that the approach was able to outperform classical feature selection methods in hepatocellular carcinoma (HCC) by 9%, lung cancer by 6% and breast cancer by around 10% in F1-measure. Results also show the enhancement in F1-measure of our approach over recently related work in [1] and [2].

Feature engineering for drug name recognition in biomedical texts: feature conjunction and feature selection.

PubMed

Liu, Shengyu; Tang, Buzhou; Chen, Qingcai; Wang, Xiaolong; Fan, Xiaoming

2015-01-01

Drug name recognition (DNR) is a critical step for drug information extraction. Machine learning-based methods have been widely used for DNR with various types of features such as part-of-speech, word shape, and dictionary feature. Features used in current machine learning-based methods are usually singleton features which may be due to explosive features and a large number of noisy features when singleton features are combined into conjunction features. However, singleton features that can only capture one linguistic characteristic of a word are not sufficient to describe the information for DNR when multiple characteristics should be considered. In this study, we explore feature conjunction and feature selection for DNR, which have never been reported. We intuitively select 8 types of singleton features and combine them into conjunction features in two ways. Then, Chi-square, mutual information, and information gain are used to mine effective features. Experimental results show that feature conjunction and feature selection can improve the performance of the DNR system with a moderate number of features and our DNR system significantly outperforms the best system in the DDIExtraction 2013 challenge.

The role of proline-containing peptide triads in β-sheet formation: A kinetic study.

PubMed

Takor, Gaius A; Higashiya, Seiichiro; Sikirzhytski, Vitali K; Seeley, Jason P; Lednev, Igor K; Welch, John T

2015-06-01

The design of biomimetic materials through molecular self-assembly is a growing area of modern nanotechnology. With problems of protein folding, self-assembly, and sequence-structure relationships as essential in nanotechnology as in biology, the effect of the nucleation of β-hairpin formation by proline on the folding process has been investigated in model studies. Previously such studies were limited to investigations of the influence of proline on the formation of turns in short peptide sequences. The effect of proline-based triads on the folding of an 11-kDa amyloidogenic peptide GH6[(GA)3GY(GA)3GE]8 GAH6 (YE8) was investigated by selective substitution of the proline-substituted triads at the γ-turn sites. The folding and fibrillation of the singly proline-substituted polypeptides, e.g., GH6-[(GA)3GY(GA)3GE]7(GA)3GY(GA)3PD-GAH6 (8PD), and doubly proline-substituted polypeptides, e.g., GH6-[(GA)3GY(GA)3GE]3(GA)3GY(GA)3PD[(GA)3GY(GA)3GE]3(GA)3GY(GA)3PD-GAH6 (4,8PD), were directly monitored by circular dichroism and deep UV resonance Raman and fluorescence spectroscopies. These findings were used to identify the essential folding domains, i.e., the minimum number of β-strands necessary for stable folding. These experimental findings may be especially useful in the design and construction of peptidic materials for a wide range of applications as well as in understanding the mechanisms of folding critical to fibril formation. © 2015 Wiley Periodicals, Inc.

Study to determine the IFR operational profile and problems to the general aviation pilot

NASA Technical Reports Server (NTRS)

Weislogel, S.

1983-01-01

A study of the general aviation single pilot operating under instrument flight rules (GA SPIFR) has been conducted for NASA Langley Research Center. The objectives of the study were to (1) develop a GA SPIFR operational profile, (2) identify problems experienced by the GA SPIFR pilot, and (3) identify research tasks which have the potential for eliminating or reducing the severity of the problems. To obtain the information necessary to accomplish these objectives, a mail questionnaire survey of instrument rated pilots was conducted. Complete questionnaire data is reported in NASA CR-165805, "Statistical Summary: Study to Determine the IFR Operational Profile and Problems of the General Aviation Single Pilot'-Based upon the results of the GA SPIFR survey, this final report presents the general aviation IFR single pilot operational profile, illustrates selected data analysis, examples, identifies the problems which he is experiencing, and recommends further research.

Alternating evolutionary pressure in a genetic algorithm facilitates protein model selection

PubMed Central

Offman, Marc N; Tournier, Alexander L; Bates, Paul A

2008-01-01

Background Automatic protein modelling pipelines are becoming ever more accurate; this has come hand in hand with an increasingly complicated interplay between all components involved. Nevertheless, there are still potential improvements to be made in template selection, refinement and protein model selection. Results In the context of an automatic modelling pipeline, we analysed each step separately, revealing several non-intuitive trends and explored a new strategy for protein conformation sampling using Genetic Algorithms (GA). We apply the concept of alternating evolutionary pressure (AEP), i.e. intermediate rounds within the GA runs where unrestrained, linear growth of the model populations is allowed. Conclusion This approach improves the overall performance of the GA by allowing models to overcome local energy barriers. AEP enabled the selection of the best models in 40% of all targets; compared to 25% for a normal GA. PMID:18673557

Classification of motor imagery tasks for BCI with multiresolution analysis and multiobjective feature selection.

PubMed

Ortega, Julio; Asensio-Cubero, Javier; Gan, John Q; Ortiz, Andrés

2016-07-15

Brain-computer interfacing (BCI) applications based on the classification of electroencephalographic (EEG) signals require solving high-dimensional pattern classification problems with such a relatively small number of training patterns that curse of dimensionality problems usually arise. Multiresolution analysis (MRA) has useful properties for signal analysis in both temporal and spectral analysis, and has been broadly used in the BCI field. However, MRA usually increases the dimensionality of the input data. Therefore, some approaches to feature selection or feature dimensionality reduction should be considered for improving the performance of the MRA based BCI. This paper investigates feature selection in the MRA-based frameworks for BCI. Several wrapper approaches to evolutionary multiobjective feature selection are proposed with different structures of classifiers. They are evaluated by comparing with baseline methods using sparse representation of features or without feature selection. The statistical analysis, by applying the Kolmogorov-Smirnoff and Kruskal-Wallis tests to the means of the Kappa values evaluated by using the test patterns in each approach, has demonstrated some advantages of the proposed approaches. In comparison with the baseline MRA approach used in previous studies, the proposed evolutionary multiobjective feature selection approaches provide similar or even better classification performances, with significant reduction in the number of features that need to be computed.

Feature Selection for Speech Emotion Recognition in Spanish and Basque: On the Use of Machine Learning to Improve Human-Computer Interaction

PubMed Central

Arruti, Andoni; Cearreta, Idoia; Álvarez, Aitor; Lazkano, Elena; Sierra, Basilio

2014-01-01

Study of emotions in human–computer interaction is a growing research area. This paper shows an attempt to select the most significant features for emotion recognition in spoken Basque and Spanish Languages using different methods for feature selection. RekEmozio database was used as the experimental data set. Several Machine Learning paradigms were used for the emotion classification task. Experiments were executed in three phases, using different sets of features as classification variables in each phase. Moreover, feature subset selection was applied at each phase in order to seek for the most relevant feature subset. The three phases approach was selected to check the validity of the proposed approach. Achieved results show that an instance-based learning algorithm using feature subset selection techniques based on evolutionary algorithms is the best Machine Learning paradigm in automatic emotion recognition, with all different feature sets, obtaining a mean of 80,05% emotion recognition rate in Basque and a 74,82% in Spanish. In order to check the goodness of the proposed process, a greedy searching approach (FSS-Forward) has been applied and a comparison between them is provided. Based on achieved results, a set of most relevant non-speaker dependent features is proposed for both languages and new perspectives are suggested. PMID:25279686

Development of highly durable deep-ultraviolet AlGaN-based LED multichip array with hemispherical encapsulated structures using a selected resin through a detailed feasibility study

NASA Astrophysics Data System (ADS)

Nagai, Shoko; Yamada, Kiho; Hirano, Akira; Ippommatsu, Masamichi; Ito, Masahiro; Morishima, Naoki; Aosaki, Ko; Honda, Yoshio; Amano, Hiroshi; Akasaki, Isamu

2016-08-01

To replace mercury lamps with AlGaN-based deep-ultraviolet (DUV) LEDs, a simple and low-cost package with increased light extraction efficiency (LEE) is indispensable. Therefore, resin encapsulation is considered to be a key technology. However, the photochemical reactions induced by DUV light cause serious problems, and conventional resins cannot be used. In the former part of this study, a comparison of a silicone resin and fluorine polymers was carried out in terms of their suitability for encapsulation, and we concluded that only one of the fluorine polymers can be used for encapsulation. In the latter part, the endurance of encapsulation using the selected fluorine polymer was investigated, and we confirmed that the selected fluorine polymer can guarantee a lifetime of over 6,000 h at a wavelength of 265 nm. Furthermore, a 3 × 4 array module of encapsulated dies on a simple AlN submount was fabricated, demonstrating the possibility of W/cm2-class lighting.

Statistical optimisation techniques in fatigue signal editing problem

NASA Astrophysics Data System (ADS)

Nopiah, Z. M.; Osman, M. H.; Baharin, N.; Abdullah, S.

2015-02-01

Success in fatigue signal editing is determined by the level of length reduction without compromising statistical constraints. A great reduction rate can be achieved by removing small amplitude cycles from the recorded signal. The long recorded signal sometimes renders the cycle-to-cycle editing process daunting. This has encouraged researchers to focus on the segment-based approach. This paper discusses joint application of the Running Damage Extraction (RDE) technique and single constrained Genetic Algorithm (GA) in fatigue signal editing optimisation.. In the first section, the RDE technique is used to restructure and summarise the fatigue strain. This technique combines the overlapping window and fatigue strain-life models. It is designed to identify and isolate the fatigue events that exist in the variable amplitude strain data into different segments whereby the retention of statistical parameters and the vibration energy are considered. In the second section, the fatigue data editing problem is formulated as a constrained single optimisation problem that can be solved using GA method. The GA produces the shortest edited fatigue signal by selecting appropriate segments from a pool of labelling segments. Challenges arise due to constraints on the segment selection by deviation level over three signal properties, namely cumulative fatigue damage, root mean square and kurtosis values. Experimental results over several case studies show that the idea of solving fatigue signal editing within a framework of optimisation is effective and automatic, and that the GA is robust for constrained segment selection.

Statistical optimisation techniques in fatigue signal editing problem

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

Nopiah, Z. M.; Osman, M. H.; Baharin, N.

Success in fatigue signal editing is determined by the level of length reduction without compromising statistical constraints. A great reduction rate can be achieved by removing small amplitude cycles from the recorded signal. The long recorded signal sometimes renders the cycle-to-cycle editing process daunting. This has encouraged researchers to focus on the segment-based approach. This paper discusses joint application of the Running Damage Extraction (RDE) technique and single constrained Genetic Algorithm (GA) in fatigue signal editing optimisation.. In the first section, the RDE technique is used to restructure and summarise the fatigue strain. This technique combines the overlapping window andmore » fatigue strain-life models. It is designed to identify and isolate the fatigue events that exist in the variable amplitude strain data into different segments whereby the retention of statistical parameters and the vibration energy are considered. In the second section, the fatigue data editing problem is formulated as a constrained single optimisation problem that can be solved using GA method. The GA produces the shortest edited fatigue signal by selecting appropriate segments from a pool of labelling segments. Challenges arise due to constraints on the segment selection by deviation level over three signal properties, namely cumulative fatigue damage, root mean square and kurtosis values. Experimental results over several case studies show that the idea of solving fatigue signal editing within a framework of optimisation is effective and automatic, and that the GA is robust for constrained segment selection.« less

Fetal biometric parameters: Reference charts for a non-selected risk population from Uberaba, Brazil

PubMed Central

Peixoto, Alberto Borges; da Cunha Caldas, Taciana Mara Rodrigues; Dulgheroff, Fernando Felix; Martins, Wellington P.

2017-01-01

Objective To establish reference charts for fetal biometric parameters in a non-selected risk population from Uberaba, Southeast of Brazil. Methods A retrospective cross-sectional study was performed among 5656 non-selected risk singleton pregnant women between 14 and 41 weeks of gestation. The ultrasound exams were performed during routine visits of second and third trimesters. Biparietal diameter (BPD) was measured at the level of the thalami and cavum septi pellucidi. Head circumference (HC) was calculated by the following formula: HC = 1.62*(BPD + occipital frontal diameter, OFD). Abdominal circumference (AC) was measured using the following formula: AC = (anteroposterior diameter + transverse abdominal diameter) × 1.57. Femur diaphysis length (FDL) was obtained in the longest axis of femur without including the distal femoral epiphysis. The estimated fetal weight (EFW) was obtained by the Hadlock formula. Polynomial regressions were performed to obtain the best-fit model for each fetal biometric parameter as the function of gestational age (GA). Results The mean, standard deviations (SD), minimum and maximum of BPD (cm), HC (cm), AC (cm), FDL (cm) and EFW (g) were 6.9 ± 1.9 (2.3 – 10.5), 24.51 ± 6.61 (9.1 – 36.4), 22.8 ± 7.3 (7.5 – 41.1), 4.9 ± 1.6 (1.2 – 8.1) and 1365 ± 1019 (103 – 4777), respectively. Second-degree polynomial regressions between the evaluated parameters and GA resulted in the following formulas: BPD = –4.044 + 0.540 × GA – 0.0049 × GA2 (R2 = 0.97); HC= –15.420 + 2.024 GA – 0.0199 × GA2 (R2 = 0.98); AC = –9.579 + 1.329 × GA – 0.0055 × GA2 (R2 = 0.97); FDL = –3.778 + 0.416 × GA – 0.0035 × GA2 (R2 = 0.98) and EFW = 916 – 123 × GA + 4.70 × GA2 (R2 = 0.96); respectively. Conclusion Reference charts for the fetal biometric parameters in a non-selected risk population from Uberaba, Southeast of Brazil, were established. PMID:28439425

Fetal biometric parameters: Reference charts for a non-selected risk population from Uberaba, Brazil.

PubMed

Peixoto, Alberto Borges; da Cunha Caldas, Taciana Mara Rodrigues; Dulgheroff, Fernando Felix; Martins, Wellington P; Araujo Júnior, Edward

2017-03-01

To establish reference charts for fetal biometric parameters in a non-selected risk population from Uberaba, Southeast of Brazil. A retrospective cross-sectional study was performed among 5656 non-selected risk singleton pregnant women between 14 and 41 weeks of gestation. The ultrasound exams were performed during routine visits of second and third trimesters. Biparietal diameter (BPD) was measured at the level of the thalami and cavum septi pellucidi. Head circumference (HC) was calculated by the following formula: HC = 1.62*(BPD + occipital frontal diameter, OFD). Abdominal circumference (AC) was measured using the following formula: AC = (anteroposterior diameter + transverse abdominal diameter) × 1.57. Femur diaphysis length (FDL) was obtained in the longest axis of femur without including the distal femoral epiphysis. The estimated fetal weight (EFW) was obtained by the Hadlock formula. Polynomial regressions were performed to obtain the best-fit model for each fetal biometric parameter as the function of gestational age (GA). The mean, standard deviations ( SD ), minimum and maximum of BPD (cm), HC (cm), AC (cm), FDL (cm) and EFW (g) were 6.9 ± 1.9 (2.3 - 10.5), 24.51 ± 6.61 (9.1 - 36.4), 22.8 ± 7.3 (7.5 - 41.1), 4.9 ± 1.6 (1.2 - 8.1) and 1365 ± 1019 (103 - 4777), respectively. Second-degree polynomial regressions between the evaluated parameters and GA resulted in the following formulas: BPD = -4.044 + 0.540 × GA - 0.0049 × GA 2 ( R 2 = 0.97); HC= -15.420 + 2.024 GA - 0.0199 × GA 2 ( R 2 = 0.98); AC = -9.579 + 1.329 × GA - 0.0055 × GA 2 ( R 2 = 0.97); FDL = -3.778 + 0.416 × GA - 0.0035 × GA 2 ( R 2 = 0.98) and EFW = 916 - 123 × GA + 4.70 × GA 2 ( R 2 = 0.96); respectively. Reference charts for the fetal biometric parameters in a non-selected risk population from Uberaba, Southeast of Brazil, were established.

Adaptive runtime for a multiprocessing API

DOEpatents

Antao, Samuel F.; Bertolli, Carlo; Eichenberger, Alexandre E.; O'Brien, John K.

2016-11-15

A computer-implemented method includes selecting a runtime for executing a program. The runtime includes a first combination of feature implementations, where each feature implementation implements a feature of an application programming interface (API). Execution of the program is monitored, and the execution uses the runtime. Monitor data is generated based on the monitoring. A second combination of feature implementations are selected, by a computer processor, where the selection is based at least in part on the monitor data. The runtime is modified by activating the second combination of feature implementations to replace the first combination of feature implementations.

Adaptive runtime for a multiprocessing API

DOEpatents

Antao, Samuel F.; Bertolli, Carlo; Eichenberger, Alexandre E.; O'Brien, John K.

2016-10-11

A computer-implemented method includes selecting a runtime for executing a program. The runtime includes a first combination of feature implementations, where each feature implementation implements a feature of an application programming interface (API). Execution of the program is monitored, and the execution uses the runtime. Monitor data is generated based on the monitoring. A second combination of feature implementations are selected, by a computer processor, where the selection is based at least in part on the monitor data. The runtime is modified by activating the second combination of feature implementations to replace the first combination of feature implementations.

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

King, W.A.; Kubas, G.J.

The present invention provides: a composition of the formula M{sup +x}(Ga(Y){sub 4}{sup {minus}}){sub x} where M is a metal selected from the group consisting of lithium, sodium, potassium, cesium, calcium, strontium, thallium, and silver, x is an integer selected from the group consisting of 1 or 2, each Y is a ligand selected from the group consisting of aryl, alkyl, hydride and halide with the proviso that at least one Y is a ligand selected from the group consisting of aryl, alkyl and halide; a composition of the formula (R){sub x}Q{sup +}Ga(Y){sub 4}{sup {minus}} where Q is selected from themore » group consisting of carbon, nitrogen, sulfur, phosphorus and oxygen, each R is a ligand selected from the group consisting of alkyl, aryl, and hydrogen, x is an integer selected from the group consisting of 3 and 4 depending upon Q, and each Y is a ligand selected from the group consisting of aryl, alkyl, hydride and halide with the proviso that at least one Y is a ligand selected from the group consisting of aryl, alkyl and halide; an ionic polymerization catalyst composition including an active cationic portion and a gallium based weakly coordinating anion; and bridged anion species of the formula M{sup +x}{sub y}[X(GaY{sub 3}){sub z}]{sup {minus}y}{sub x} where M is a metal selected from the group consisting of lithium, sodium, potassium, magnesium, cesium, calcium, strontium, thallium, and silver, x is an integer selected from the group consisting of 1 or 2, X is a bridging group between two gallium atoms, y is an integer selected from the group consisting 1 and 2, z is an integer of at least 2, each Y is a ligand selected from the group consisting of aryl, alkyl, hydride and halide with the proviso that at least one Y is a ligand selected from the group consisting of aryl, alkyl and halide.« less

Properties of transparent (Gd,Lu)3(Al,Ga)5O12:Ce ceramic with Mg, Ca and Ce co-dopants

NASA Astrophysics Data System (ADS)

Wang, Yimin; Baldoni, Gary; Brecher, Charles; Rhodes, William H.; Shirwadkar, Urmila; Glodo, Jarek; Shah, Ishaan; Ji, Chuncheng

2015-08-01

Cerium activated mixed lutetium/gadolinium- and aluminum/gallium-based garnets have great potential as host scintillators for medical imaging applications. (Gd,Lu)3(Al,Ga)5O12:Ce and denoted as GLuGAG feature high effective atomic number and good light yield, which make it particularly attractive for Positron Emission Tomography (PET) and other γ-ray detection applications. For PET application, rapid decay and good timing resolution are extremely important. Most Ce-doped mixed garnet materials such as GLuGAG:Ce, have their main decay component at around 80 ns. However, it has been reported that the decays of some single crystal scintillators (e.g., LSO and GGAG) can be effectively accelerated by codoping with selected additives such as Ca, Mg and B. In this study, transparent polycrystalline (Gd,Lu)3(Al,Ga)5O12:Ce ceramics codoped with Ca or Mg or additional Ce, were fabricated by the sinter-HIP approach. It was found the transmission of the ceramics are closely related to the microstructure of the ceramics. As the co-dopant levels increase, 2nd phase occurs in the ceramic and thus transparency of the ceramic decreases. Ca and Mg co-doping in GLuGAG:Ce ceramic effectively accelerate decays of GLuGAG:Ce ceramics at a cost of light output. However, additional Ce doping in the GLuGAG:Ce has no benefit on improving decay time but, on the other hand, reduces transmission, light output. The mechanism under the different scintillation behaviors with Mg, Ca and Ce dopants are discussed. The results suggest that decay time of GLuGAG:Ce ceramics can be effectively tailored by co-doping GLuGAG:Ce ceramic with Mg and Ca for applications with optimal timing resolution.

III-nitride nanopyramid light emitting diodes grown by organometallic vapor phase epitaxy

NASA Astrophysics Data System (ADS)

Wildeson, Isaac H.; Colby, Robert; Ewoldt, David A.; Liang, Zhiwen; Zakharov, Dmitri N.; Zaluzec, Nestor J.; García, R. Edwin; Stach, Eric A.; Sands, Timothy D.

2010-08-01

Nanopyramid light emitting diodes (LEDs) have been synthesized by selective area organometallic vapor phase epitaxy. Self-organized porous anodic alumina is used to pattern the dielectric growth templates via reactive ion etching, eliminating the need for lithographic processes. (In,Ga)N quantum well growth occurs primarily on the six {11¯01} semipolar facets of each of the nanopyramids, while coherent (In,Ga)N quantum dots with heights of up to ˜20 nm are incorporated at the apex by controlling growth conditions. Transmission electron microscopy (TEM) indicates that the (In,Ga)N active regions of the nanopyramid heterostructures are completely dislocation-free. Temperature-dependent continuous-wave photoluminescence of nanopyramid heterostructures yields a peak emission wavelength of 617 nm and 605 nm at 300 K and 4 K, respectively. The peak emission energy varies with increasing temperature with a double S-shaped profile, which is attributed to either the presence of two types of InN-rich features within the nanopyramids or a contribution from the commonly observed yellow defect luminescence close to 300 K. TEM cross-sections reveal continuous planar defects in the (In,Ga)N quantum wells and GaN cladding layers grown at 650-780 °C, present in 38% of the nanopyramid heterostructures. Plan-view TEM of the planar defects confirms that these defects do not terminate within the nanopyramids. During the growth of p-GaN, the structure of the nanopyramid LEDs changed from pyramidal to a partially coalesced film as the thickness requirements for an undepleted p-GaN layer result in nanopyramid impingement. Continuous-wave electroluminescence of nanopyramid LEDs reveals a 45 nm redshift in comparison to a thin-film LED, suggesting higher InN incorporation in the nanopyramid LEDs. These results strongly encourage future investigations of III-nitride nanoheteroepitaxy as an approach for creating efficient long wavelength LEDs.

Modeling of THz Lasers Based on Intersubband Transitions in Semiconductor Quantum Wells

NASA Technical Reports Server (NTRS)

Liu, Ansheng; Woo, Alex C. (Technical Monitor)

1999-01-01

In semiconductor quantum well structures, the intersubband energy separation can be adjusted to the terahertz (THz) frequency range by changing the well width and material combinations. The electronic and optical properties of these nanostructures can also be controlled by an applied dc electric field. These unique features lead to a large frequency tunability of the quantum well devices. In the on-going project of modeling of the THz lasers, we investigate the possibility of using optical pumping to generate THz radiation based on intersubband transitions in semiconductor quantum wells. We choose the optical pumping because in the electric current injection it is difficult to realize population inversion in the THz frequency range due to the small intersubband separation (4-40 meV). We considered both small conduction band offset (GaAs/AlGaAs) and large band offset (InGaAs/AlAsSb) quantum well structures. For GaAs/AlGaAs quantum wells, mid-infrared C02 lasers are used as pumping sources. For InGaAs/AlAsSb quantum wells, the resonant intersubband transitions can be excited by the near-infrared diode lasers. For three- and four-subband quantum wells, we solve the pumpfield-induced nonequilibrium distribution function for each subband of the quantum well system from a set of rate equations that include both intrasubband and intersubband relaxation processes. Taking into account the coherent interactions between pump and THz (signal) waves, we calculate the optical gain for the THz field. The gain arising from population inversion and stimulated Raman processes is calculated in a unified manner. A graph shows the calculated THz gain spectra for three-subband GaAs/AlGaAs quantum wells. We see that the coherent pump and signal wave interactions contribute significantly to the gain. The pump intensity dependence of the THz gain is also studied. The calculated results are shown. Because of the optical Stark effect and pump-induced population redistribution, the maximum THz gain saturates at larger pump intensities.

Thermal stability of implanted dopants in GaN

NASA Astrophysics Data System (ADS)

Wilson, R. G.; Pearton, S. J.; Abernathy, C. R.; Zavada, J. M.

1995-04-01

Results are reported of measurements of depth profiles and stability against redistribution with annealing up to 800 or 900 °C, for implanted Be, C, Mg, Si, S, Zn, Ge, and Se as dopants in GaN. The results confirm the high-temperature stability of dopants in this material up to temperatures that vary from 600 to 900 °C. S redistributes for temperatures above 600 °C, and Zn and Se, for temperatures above 800 °C. All of the other elements are stable to 900 °C. These results indicate that direct implantation of dopants rather than masked diffusion will probably be necessary to define selective area doping of III-V nitride device structures based on these results for GaN.

Technologies for thermal management of mid-IR Sb-based surface emitting lasers

NASA Astrophysics Data System (ADS)

Perez, J.-P.; Laurain, A.; Cerutti, L.; Sagnes, I.; Garnache, A.

2010-04-01

In this paper, for the first time to our knowledge, we report and demonstrate the technological steps dedicated to thermal management of antimonide-based surface emitting laser devices grown by molecular beam epitaxy. Key points of the technological process are firstly the bonding of the structure on the SiC host substrate and secondly the GaSb substrate removal to leave the Sb-based membrane. The structure design (etch stop layer, metallic mirror, etc), bonding process (metallic bonding via solid-liquid interdiffusion) and GaSb substrate removal process (selective wet-chemical etchants, etc) are presented. Optical characterizations together with external-cavity VCSEL laser emission at 2.3 µm at room temperature in continuous wave are presented.

Infrared face recognition based on LBP histogram and KW feature selection

NASA Astrophysics Data System (ADS)

Xie, Zhihua

2014-07-01

The conventional LBP-based feature as represented by the local binary pattern (LBP) histogram still has room for performance improvements. This paper focuses on the dimension reduction of LBP micro-patterns and proposes an improved infrared face recognition method based on LBP histogram representation. To extract the local robust features in infrared face images, LBP is chosen to get the composition of micro-patterns of sub-blocks. Based on statistical test theory, Kruskal-Wallis (KW) feature selection method is proposed to get the LBP patterns which are suitable for infrared face recognition. The experimental results show combination of LBP and KW features selection improves the performance of infrared face recognition, the proposed method outperforms the traditional methods based on LBP histogram, discrete cosine transform(DCT) or principal component analysis(PCA).

[Feature extraction for breast cancer data based on geometric algebra theory and feature selection using differential evolution].

PubMed

Li, Jing; Hong, Wenxue

2014-12-01

The feature extraction and feature selection are the important issues in pattern recognition. Based on the geometric algebra representation of vector, a new feature extraction method using blade coefficient of geometric algebra was proposed in this study. At the same time, an improved differential evolution (DE) feature selection method was proposed to solve the elevated high dimension issue. The simple linear discriminant analysis was used as the classifier. The result of the 10-fold cross-validation (10 CV) classification of public breast cancer biomedical dataset was more than 96% and proved superior to that of the original features and traditional feature extraction method.

Determination of a Two-Phase Structure of Nanocrystals: GaN and SiC

NASA Technical Reports Server (NTRS)

Palosz, W.; Grzanka, E.; Gierlotka, S.; Stelmakh, S.; Pielaszek, R.; Lojkowski, W.; Bismayer, U.; Neuefeind, J.; Weber, H.-P.; Janik, J. F.;

Optical emission of GaN/AlN quantum-wires - the role of charge transfer from a nanowire template.

PubMed

Müßener, Jan; Greif, Ludwig A Th; Kalinowski, Stefan; Callsen, Gordon; Hille, Pascal; Schörmann, Jörg; Wagner, Markus R; Schliwa, Andrei; Martí-Sánchez, Sara; Arbiol, Jordi; Hoffmann, Axel; Eickhoff, Martin

2018-03-28

We show that one-dimensional (1d) GaN quantum-wires (QWRs) exhibit intense and spectrally sharp emission lines. These QWRs are realized in an entirely self-assembled growth process by molecular beam epitaxy (MBE) on the side facets of GaN/AlN nanowire (NW) heterostructures. Time-integrated and time-resolved photoluminescence (PL) data in combination with numerical calculations allow the identification and assignment of the manifold emission features to three different spatial recombination centers within the NWs. The recombination processes in the QWRs are driven by efficient charge carrier transfer effects between the different optically active regions, providing high intense QWR luminescence despite their small volume. This is deduced by a fast rise time of the QWR PL, which is similar to the fast decay-time of adjacent carrier reservoirs. Such processes, feeding the ultra-narrow QWRs with carriers from the relatively large NWs, can be the key feature towards the realization of future QWR-based devices. While processing of single quantum structures with diameters in the nm range presents a serious obstacle with respect to their integration into electronic or photonic devices, the QWRs presented here can be analyzed and processed using existing techniques developed for single NWs.

AVC: Selecting discriminative features on basis of AUC by maximizing variable complementarity.

PubMed

Sun, Lei; Wang, Jun; Wei, Jinmao

2017-03-14

The Receiver Operator Characteristic (ROC) curve is well-known in evaluating classification performance in biomedical field. Owing to its superiority in dealing with imbalanced and cost-sensitive data, the ROC curve has been exploited as a popular metric to evaluate and find out disease-related genes (features). The existing ROC-based feature selection approaches are simple and effective in evaluating individual features. However, these approaches may fail to find real target feature subset due to their lack of effective means to reduce the redundancy between features, which is essential in machine learning. In this paper, we propose to assess feature complementarity by a trick of measuring the distances between the misclassified instances and their nearest misses on the dimensions of pairwise features. If a misclassified instance and its nearest miss on one feature dimension are far apart on another feature dimension, the two features are regarded as complementary to each other. Subsequently, we propose a novel filter feature selection approach on the basis of the ROC analysis. The new approach employs an efficient heuristic search strategy to select optimal features with highest complementarities. The experimental results on a broad range of microarray data sets validate that the classifiers built on the feature subset selected by our approach can get the minimal balanced error rate with a small amount of significant features. Compared with other ROC-based feature selection approaches, our new approach can select fewer features and effectively improve the classification performance.

Orbitally driven low thermal conductivity of monolayer gallium nitride (GaN) with planar honeycomb structure: a comparative study.

PubMed

Qin, Zhenzhen; Qin, Guangzhao; Zuo, Xu; Xiong, Zhihua; Hu, Ming

2017-03-23

Two-dimensional (2D) materials with graphene as a representative have been intensively studied for a long time. Recently, monolayer gallium nitride (ML GaN) with honeycomb structure was successfully fabricated in experiments, generating enormous research interest for its promising applications in nano- and opto-electronics. Considering all these applications are inevitably involved with thermal transport, systematic investigation of the phonon transport properties of 2D GaN is in demand. In this paper, by solving the Boltzmann transport equation (BTE) based on first-principles calculations, we performed a comprehensive study of the phonon transport properties of ML GaN, with detailed comparison to bulk GaN, 2D graphene, silicene and ML BN with similar honeycomb structure. Considering the similar planar structure of ML GaN to graphene, it is quite intriguing to find that the thermal conductivity (κ) of ML GaN (14.93 W mK -1 ) is more than two orders of magnitude lower than that of graphene and is even lower than that of silicene with a buckled structure. Systematic analysis is performed based on the study of the contribution from phonon branches, comparison among the mode level phonon group velocity and lifetime, the detailed process and channels of phonon-phonon scattering, and phonon anharmonicity with potential energy well. We found that, different from graphene and ML BN, the phonon-phonon scattering selection rule in 2D GaN is slightly broken by the lowered symmetry due to the large difference in the atomic radius and mass between Ga and N atoms. Further deep insight is gained from the electronic structure. Resulting from the special sp orbital hybridization mediated by the Ga-d orbital in ML GaN, the strongly polarized Ga-N bond, localized charge density, and its inhomogeneous distribution induce large phonon anharmonicity and lead to the intrinsic low κ of ML GaN. The orbitally driven low κ of ML GaN unraveled in this work would make 2D GaN prospective for applications in energy conversion such as thermoelectrics. Our study offers fundamental understanding of phonon transport in ML GaN within the framework of BTE and further electronic structure, which will enrich the studies of nanoscale phonon transport in 2D materials and shed light on further studies.

Emotional textile image classification based on cross-domain convolutional sparse autoencoders with feature selection

NASA Astrophysics Data System (ADS)

Li, Zuhe; Fan, Yangyu; Liu, Weihua; Yu, Zeqi; Wang, Fengqin

2017-01-01

We aim to apply sparse autoencoder-based unsupervised feature learning to emotional semantic analysis for textile images. To tackle the problem of limited training data, we present a cross-domain feature learning scheme for emotional textile image classification using convolutional autoencoders. We further propose a correlation-analysis-based feature selection method for the weights learned by sparse autoencoders to reduce the number of features extracted from large size images. First, we randomly collect image patches on an unlabeled image dataset in the source domain and learn local features with a sparse autoencoder. We then conduct feature selection according to the correlation between different weight vectors corresponding to the autoencoder's hidden units. We finally adopt a convolutional neural network including a pooling layer to obtain global feature activations of textile images in the target domain and send these global feature vectors into logistic regression models for emotional image classification. The cross-domain unsupervised feature learning method achieves 65% to 78% average accuracy in the cross-validation experiments corresponding to eight emotional categories and performs better than conventional methods. Feature selection can reduce the computational cost of global feature extraction by about 50% while improving classification performance.

A feature selection approach towards progressive vector transmission over the Internet

NASA Astrophysics Data System (ADS)

Miao, Ru; Song, Jia; Feng, Min

2017-09-01

WebGIS has been applied for visualizing and sharing geospatial information popularly over the Internet. In order to improve the efficiency of the client applications, the web-based progressive vector transmission approach is proposed. Important features should be selected and transferred firstly, and the methods for measuring the importance of features should be further considered in the progressive transmission. However, studies on progressive transmission for large-volume vector data have mostly focused on map generalization in the field of cartography, but rarely discussed on the selection of geographic features quantitatively. This paper applies information theory for measuring the feature importance of vector maps. A measurement model for the amount of information of vector features is defined based upon the amount of information for dealing with feature selection issues. The measurement model involves geometry factor, spatial distribution factor and thematic attribute factor. Moreover, a real-time transport protocol (RTP)-based progressive transmission method is then presented to improve the transmission of vector data. To clearly demonstrate the essential methodology and key techniques, a prototype for web-based progressive vector transmission is presented, and an experiment of progressive selection and transmission for vector features is conducted. The experimental results indicate that our approach clearly improves the performance and end-user experience of delivering and manipulating large vector data over the Internet.

Note: All solid-state high repetitive sub-nanosecond risetime pulse generator based on bulk gallium arsenide avalanche semiconductor switches.

PubMed

Hu, Long; Su, Jiancang; Ding, Zhenjie; Hao, Qingsong; Fan, Yajun; Liu, Chunliang

2016-08-01

An all solid-state high repetitive sub-nanosecond risetime pulse generator featuring low-energy-triggered bulk gallium arsenide (GaAs) avalanche semiconductor switches and a step-type transmission line is presented. The step-type transmission line with two stages is charged to a potential of 5.0 kV also biasing at the switches. The bulk GaAs avalanche semiconductor switch closes within sub-nanosecond range when illuminated with approximately 87 nJ of laser energy at 905 nm in a single pulse. An asymmetric dipolar pulse with peak-to-peak amplitude of 9.6 kV and risetime of 0.65 ns is produced on a resistive load of 50 Ω. A technique that allows for repetition-rate multiplication of pulse trains experimentally demonstrated that the parallel-connected bulk GaAs avalanche semiconductor switches are triggered in sequence. The highest repetition rate is decided by recovery time of the bulk GaAs avalanche semiconductor switch, and the operating result of 100 kHz of the generator is discussed.

Concentration and structure inhomogeneities in GaSb(Si) single crystals grown at different heat and mass transfer conditions

NASA Astrophysics Data System (ADS)

Serebryakov, Yu. A.; Prokhorov, I. A.; Vlasov, V. N.; Korobeynikova, E. N.; Zakharov, B. G.; Shul'pina, I. L.; Marchenko, M. P.; Fryazinov, I. V.

2007-06-01

Results of ground-based experiments on crystallization of gallium antimonide on the POLIZON facility carried out within the framework of space experiment preparation aboard FOTON satellite are submitted. Technical and technological opportunities of suppression of disturbing factors for improvement of quality of grown crystals in space are substantiated. Features of formation of concentration and structure inhomogeneities in GaSb:Si crystals grown under non-stationary and stationary convection conditions are investigated. Experimental data about structure and dopant distribution inhomogeneities are discussed taking into account results of numerical researches of GaSb:Si crystallization. Also earlier received results of modeling of GaSb:Te crystallization under close temperature conditions are used. Correlation between computational and experimental data is shown. The data on intensity of flows close to crystallization front are received at which non-stationary or stationary conditions of crystallization are realized. The forecast for space conditions is made. The influence of a rotating magnetic field on convection in melt for application in space experiment projected is investigated.

Nanoporous Gallium Nitride Through Anisotropic Metal-Assisted Electroless Photochemical Wet Etching Technique

NASA Astrophysics Data System (ADS)

Perumal, R.; Hassan, Z.

2016-12-01

Nanoporous gallium nitride (GaN) has many potential applications in light-emitting diodes (LEDs), photovoltaics, templates and chemical sensors. This article reports the porosification of GaN through UV enhanced metal-assisted electroless photochemical wet etching technique using three different acid-based etchants and platinum served as catalyst for porosification. The etching process was conducted at room temperature for a duration of 90min. The morphological, structural, spectral and optical features of the developed porous GaN were studied with appropriate characterization techniques and the obtained results were presented. Field emission scanning electron micrographs exhibited the porosity nature along with excellent porous network of the etched samples. Structural studies confirmed the mono crystalline quality of the porous nanostructures. Raman spectral analyzes inferred the presenting phonon modes such as E2 (TO) and A1 (LO) in fabricated nanoporous structures. The resulted porous nanostructures hold the substantially enhanced photoluminescence intensity compared with the pristine GaN epitaxial film that is interesting and desirable for several advances in the applications of Nano-optoelectronic devices.

Additional compound semiconductor nanowires for photonics

NASA Astrophysics Data System (ADS)

Ishikawa, F.

2016-02-01

GaAs related compound semiconductor heterostructures are one of the most developed materials for photonics. Those have realized various photonic devices with high efficiency, e. g., lasers, electro-optical modulators, and solar cells. To extend the functions of the materials system, diluted nitride and bismide has been paid attention over the past decade. They can largely decrease the band gap of the alloys, providing the greater tunability of band gap and strain status, eventually suppressing the non-radiative Auger recombinations. On the other hand, selective oxidation for AlGaAs is a vital technique for vertical surface emitting lasers. That enables precisely controlled oxides in the system, enabling the optical and electrical confinement, heat transfer, and mechanical robustness. We introduce the above functions into GaAs nanowires. GaAs/GaAsN core-shell nanowires showed clear redshift of the emitting wavelength toward infrared regime. Further, the introduction of N elongated the carrier lifetime at room temperature indicating the passivation of non-radiative surface recombinations. GaAs/GaAsBi nanowire shows the redshift with metamorphic surface morphology. Selective and whole oxidations of GaAs/AlGaAs core-shell nanowires produce semiconductor/oxide composite GaAs/AlGaOx and oxide GaOx/AlGaOx core-shell nanowires, respectively. Possibly sourced from nano-particle species, the oxide shell shows white luminescence. Those property should extend the functions of the nanowires for their application to photonics.

HIV-1 protease cleavage site prediction based on two-stage feature selection method.

PubMed

Niu, Bing; Yuan, Xiao-Cheng; Roeper, Preston; Su, Qiang; Peng, Chun-Rong; Yin, Jing-Yuan; Ding, Juan; Li, HaiPeng; Lu, Wen-Cong

2013-03-01

Knowledge of the mechanism of HIV protease cleavage specificity is critical to the design of specific and effective HIV inhibitors. Searching for an accurate, robust, and rapid method to correctly predict the cleavage sites in proteins is crucial when searching for possible HIV inhibitors. In this article, HIV-1 protease specificity was studied using the correlation-based feature subset (CfsSubset) selection method combined with Genetic Algorithms method. Thirty important biochemical features were found based on a jackknife test from the original data set containing 4,248 features. By using the AdaBoost method with the thirty selected features the prediction model yields an accuracy of 96.7% for the jackknife test and 92.1% for an independent set test, with increased accuracy over the original dataset by 6.7% and 77.4%, respectively. Our feature selection scheme could be a useful technique for finding effective competitive inhibitors of HIV protease.

Comparison of estimated human dose of (68)Ga-MAA with (99m)Tc-MAA based on rat data.

PubMed

Shanehsazzadeh, Saeed; Lahooti, Afsaneh; Yousefnia, Hassan; Geramifar, Parham; Jalilian, Amir Reza

2015-10-01

(99m)Tc macroaggregated albumin ((99m)Tc-MAA) that had been used as a perfusion agent has been evaluated. In this study, we tried to estimate human absorbed dose of ⁶⁸Ga-MAA via commercially available kit from Pars-Isotopes, based on biodistribution data in wild-type rats, and compare our estimation with the available absorbed dose data from (99m)Tc-MAA. For biodistribution of ⁶⁸Ga-MAA, three rats were sacrificed at each selected times after injection (15, 30, 45, 60, and 120 min) and the percentage of injected dose per gram of each organ was measured by direct counting from rats data from 11 harvested organs. The medical internal radiation dose formulation was applied to extrapolate from rats to human and to project the absorbed radiation dose for various organs in humans. The biodistribution data for ⁶⁸Ga-MAA showed that the most of the activity was taken up by the lung (more than 97 %) in no time. Our dose prediction shows that a 185-MBq injection of ⁶⁸Ga-MAA into humans might result in an estimated absorbed dose of 4.31 mGy in the whole body. The highest absorbed doses are observed in the adrenals, spleen, pancreas, and red marrow with 0.36, 0.34, 0.26, and 0.19 mGy, respectively. Since the (99m)Tc-MAA remains longer than ⁶⁸Ga-MAA in the lung and ⁶⁸Ga-MAA has good image qualities and results in lower amounts of dose delivery to the critical organs such as gonads, red marrow, and adrenals, the use of ⁶⁸Ga-MAA is recommended.

The Epigenetic Clock at Birth: Associations With Maternal Antenatal Depression and Child Psychiatric Problems.

PubMed

Suarez, Anna; Lahti, Jari; Czamara, Darina; Lahti-Pulkkinen, Marius; Knight, Anna K; Girchenko, Polina; Hämäläinen, Esa; Kajantie, Eero; Lipsanen, Jari; Laivuori, Hannele; Villa, Pia M; Reynolds, Rebecca M; Smith, Alicia K; Binder, Elisabeth B; Räikkönen, Katri

2018-05-01

Maternal antenatal depression may compromise the fetal developmental milieu and contribute to individual differences in aging and disease trajectories in later life. We evaluated the association between maternal antenatal depression and a novel biomarker of aging at birth, namely epigenetic gestational age (GA) based on fetal cord blood methylation data. We also examined whether this biomarker prospectively predicts and mediates maternal effects on early childhood psychiatric problems. A total of 694 mothers from the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) Study provided information on history of depression diagnosed before pregnancy; 581 completed the Center for Epidemiological Studies Depression Scale throughout pregnancy, and 407 completed the Child Behavior Checklist at child's age 3.7 years (SD = 0.75 year). DNA methylation (DNAm) GA of fetal cord blood DNA was based on the methylation profile of 148 selected cytosine linked to guanine by phosphate (CpG) sites. Epigenetic GA was calculated as the arithmetic difference between DNAm GA and chronological GA and adjusted for chronological GA. Maternal history of depression diagnosed before pregnancy (mean difference = -0.25 SD units, 95% CI = -0.46 to -0.03) and greater antenatal depressive symptoms (-0.08 SD unit per 1-SD unit increase, 95% CI = -0.16 to -0.004) were associated with child's lower epigenetic GA. Child's lower epigenetic GA, in turn, prospectively predicted total and internalizing problems and partially mediated the effects of maternal antenatal depression on internalizing problems in boys. Maternal antenatal depression is associated with lower epigenetic GA in offspring. This lower epigenetic GA seems to be associated with a developmental disadvantage for boys, who, in early childhood, show greater psychiatric problems. Copyright © 2018 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Gallic Acid Ameliorated Impaired Glucose and Lipid Homeostasis in High Fat Diet-Induced NAFLD Mice

PubMed Central

Chao, Jung; Huo, Teh-Ia; Cheng, Hao-Yuan; Tsai, Jen-Chieh; Liao, Jiunn-Wang; Lee, Meng-Shiou; Qin, Xue-Mei; Hsieh, Ming-Tsuen; Pao, Li-Heng; Peng, Wen-Huang

2014-01-01

Gallic acid (GA), a naturally abundant plant phenolic compound in vegetables and fruits, has been shown to have potent anti-oxidative and anti-obesity activity. However, the effects of GA on nonalcoholic fatty liver disease (NAFLD) are poorly understood. In this study, we investigated the beneficial effects of GA administration on nutritional hepatosteatosis model by a more “holistic view” approach, namely 1H NMR-based metabolomics, in order to prove efficacy and to obtain information that might lead to a better understanding of the mode of action of GA. Male C57BL/6 mice were placed for 16 weeks on either a normal chow diet, a high fat diet (HFD, 60%), or a high fat diet supplemented with GA (50 and 100 mg/kg/day, orally). Liver histopathology and serum biochemical examinations indicated that the daily administration of GA protects against hepatic steatosis, obesity, hypercholesterolemia, and insulin resistance among the HFD-induced NAFLD mice. In addition, partial least squares discriminant analysis scores plots demonstrated that the cluster of HFD fed mice is clearly separated from the normal group mice plots, indicating that the metabolic characteristics of these two groups are distinctively different. Specifically, the GA-treated mice are located closer to the normal group of mice, indicating that the HFD-induced disturbances to the metabolic profile were partially reversed by GA treatment. Our results show that the hepatoprotective effect of GA occurs in part through a reversing of the HFD caused disturbances to a range of metabolic pathways, including lipid metabolism, glucose metabolism (glycolysis and gluconeogenesis), amino acids metabolism, choline metabolism and gut-microbiota-associated metabolism. Taken together, this study suggested that a 1H NMR-based metabolomics approach is a useful platform for natural product functional evaluation. The selected metabolites are potentially useful as preventive action biomarkers and could also be used to help our further understanding of the effect of GA in hepatosteatosis mice. PMID:24918580

Pure wurtzite GaP nanowires grown on zincblende GaP substrates by selective area vapor liquid solid epitaxy

NASA Astrophysics Data System (ADS)

Halder, Nripendra N.; Kelrich, Alexander; Cohen, Shimon; Ritter, Dan

2017-11-01

We report on the growth of single phase wurtzite (WZ) GaP nanowires (NWs) on GaP (111) B substrates by metal organic molecular beam epitaxy following the selective area vapor-liquid-solid (SA-VLS) approach. During the SA-VLS process, precursors are supplied directly to the NW sidewalls, and the short diffusion length of gallium (or its precursors) does not significantly limit axial growth. Transmission electron microscopy (TEM) images reveal that no stacking faults are present along a 600 nm long NW. The lattice constants of the pure WZ GaP obtained from the TEM images agree with values determined previously by x-ray diffraction from non-pure NW ensembles.

Pure wurtzite GaP nanowires grown on zincblende GaP substrates by selective area vapor liquid solid epitaxy.

PubMed

Halder, Nripendra N; Kelrich, Alexander; Cohen, Shimon; Ritter, Dan

2017-11-17

We report on the growth of single phase wurtzite (WZ) GaP nanowires (NWs) on GaP (111) B substrates by metal organic molecular beam epitaxy following the selective area vapor-liquid-solid (SA-VLS) approach. During the SA-VLS process, precursors are supplied directly to the NW sidewalls, and the short diffusion length of gallium (or its precursors) does not significantly limit axial growth. Transmission electron microscopy (TEM) images reveal that no stacking faults are present along a 600 nm long NW. The lattice constants of the pure WZ GaP obtained from the TEM images agree with values determined previously by x-ray diffraction from non-pure NW ensembles.

Transport, Thermal, and Magnetic Properties of YbNi3X9 (X = Al, Ga): A Newly Synthesized Yb-Based Kondo Lattice System

NASA Astrophysics Data System (ADS)

Yamashita, Tetsuro; Miyazaki, Ryoichi; Aoki, Yuji; Ohara, Shigeo

2012-03-01

We have succeeded in synthesizing a new Yb-based Kondo lattice system, YbNi3X9 (X = Al, Ga). Our study reveals that YbNi3Al9 shows typical features of a heavy-fermion antiferromagnet with a Néel temperature of TN = 3.4 K. All of the properties reflect a competition between the Kondo effect and the crystalline electric field (CEF) effect. The moderate heavy-fermion state leads to an enhanced Sommerfeld coefficient of 100 mJ/(mol\\cdotK2), even if ordered antiferromagnetically. On the other hand, the isostructural gallide YbNi3Ga9 is an intermediate-valence system with a Kondo temperature of TK = 570 K. A large hybridization scale can overcome the CEF splitting energy, and a moderately heavy Fermi-liquid ground state with high local moment degeneracy should form at low temperatures. Note that the quality of single-crystalline YbNi3X9 is extremely high compared with those of other Yb-based Kondo lattice compounds. We conclude that YbNi3X9 is a suitable system for investigating the electronic structure of Yb-based Kondo lattice systems from a heavy-fermion system with an antiferromagnetically ordered ground state to an intermediate-valence system.

Optimal sensor placement for time-domain identification using a wavelet-based genetic algorithm

NASA Astrophysics Data System (ADS)

Mahdavi, Seyed Hossein; Razak, Hashim Abdul

2016-06-01

This paper presents a wavelet-based genetic algorithm strategy for optimal sensor placement (OSP) effective for time-domain structural identification. Initially, the GA-based fitness evaluation is significantly improved by using adaptive wavelet functions. Later, a multi-species decimal GA coding system is modified to be suitable for an efficient search around the local optima. In this regard, a local operation of mutation is introduced in addition with regeneration and reintroduction operators. It is concluded that different characteristics of applied force influence the features of structural responses, and therefore the accuracy of time-domain structural identification is directly affected. Thus, the reliable OSP strategy prior to the time-domain identification will be achieved by those methods dealing with minimizing the distance of simulated responses for the entire system and condensed system considering the force effects. The numerical and experimental verification on the effectiveness of the proposed strategy demonstrates the considerably high computational performance of the proposed OSP strategy, in terms of computational cost and the accuracy of identification. It is deduced that the robustness of the proposed OSP algorithm lies in the precise and fast fitness evaluation at larger sampling rates which result in the optimum evaluation of the GA-based exploration and exploitation phases towards the global optimum solution.

Photochemical Modification of Single Crystalline GaN Film Using n-Alkene with Different Carbon Chain Lengths as Biolinker.

PubMed

Wang, Chun; Zhuang, Hao; Huang, Nan; Heuser, Steffen; Schlemper, Christoph; Zhai, Zhaofeng; Liu, Baodan; Staedler, Thorsten; Jiang, Xin

2016-06-14

As a potential material for biosensing applications, gallium nitride (GaN) films have attracted remarkable attention. In order to construct GaN biosensors, a corresponding immobilization of biolinkers is of great importance in order to render a surface bioactive. In this work, two kinds of n-alkenes with different carbon chain lengths, namely allylamine protected with trifluoroacetamide (TFAAA) and 10-aminodec-1-ene protected with trifluoroacetamide (TFAAD), were used to photochemically functionalize single crystalline GaN films. The successful linkage of both TFAAA and TFAAD to the GaN films is confirmed by time-of-flight secondary ion mass spectrometry (ToF-SIMS) measurement. With increased UV illumination time, the intensity of the secondary ions corresponding to the linker molecules initially increases and subsequently decreases in both cases. Based on the SIMS measurements, the maximum coverage of TFAAA is achieved after 14 h of UV illumination, while only 2 h is required in the case of TFAAD to reach the situation of a fully covered GaN surface. This finding leads to the conclusion that the reaction rate of TFAAD is significantly higher compared to TFAAA. Measurements by atomic force microscopy (AFM) indicate that the coverage of GaN films by a TFAAA layer leads to an increased surface roughness. The atomic terraces, which are clearly observable for the pristine GaN films, disappear once the surface is fully covered by a TFAAA layer. Such TFAAA layers will feature a homogeneous surface topography even for reaction times of 24 h. In contrast to this, TFAAD shows strong cross-polymerization on the surface, this is confirmed by optical microscopy. These results demonstrate that TFAAA is a more suitable candidate as biolinker in context of the GaN surfaces due to its improved controllability.

A possible radiation-resistant solar cell geometry using superlattices

NASA Technical Reports Server (NTRS)

Goradia, C.; Clark, R.; Brinker, D.

1985-01-01

A solar cell structure is proposed which uses a GaAs nipi doping superlattice. An important feature of this structure is that photogenerated minority carriers are very quickly collected in a time shorter than bulk lifetime in the fairly heavily doped n and p layers and these carriers are then transported parallel to the superlattice layers to selective ohmic contacts. Assuming that these already-separated carriers have very long recombination lifetimes, due to their across an indirect bandgap in real space, it is argued that the proposed structure may exhibit superior radiation tolerance along with reasonably high beginning-of-life efficiency.

Molecular Beam Epitaxial Growth of GaAs on (631) Oriented Substrates

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

Cruz Hernandez, Esteban; Rojas Ramirez, Juan-Salvador; Contreras Hernandez, Rocio

2007-02-09

In this work, we report the study of the homoepitaxial growth of GaAs on (631) oriented substrates by molecular beam epitaxy (MBE). We observed the spontaneous formation of a high density of large scale features on the surface. The hilly like features are elongated towards the [-5, 9, 3] direction. We show the dependence of these structures with the growth conditions and we present the possibility of to create quantum wires structures on this surface.

Resonant cavity light-emitting diodes based on dielectric passive cavity structures

NASA Astrophysics Data System (ADS)

Ledentsov, N.; Shchukin, V. A.; Kropp, J.-R.; Zschiedrich, L.; Schmidt, F.; Ledentsov, N. N.

2017-02-01

A novel design for high brightness planar technology light-emitting diodes (LEDs) and LED on-wafer arrays on absorbing substrates is proposed. The design integrates features of passive dielectric cavity deposited on top of an oxide- semiconductor distributed Bragg reflector (DBR), the p-n junction with a light emitting region is introduced into the top semiconductor λ/4 DBR period. A multilayer dielectric structure containing a cavity layer and dielectric DBRs is further processed by etching into a micrometer-scale pattern. An oxide-confined aperture is further amended for current and light confinement. We study the impact of the placement of the active region into the maximum or minimum of the optical field intensity and study an impact of the active region positioning on light extraction efficiency. We also study an etching profile composed of symmetric rings in the etched passive cavity over the light emitting area. The bottom semiconductor is an AlGaAs-AlAs multilayer DBR selectively oxidized with the conversion of the AlAs layers into AlOx to increase the stopband width preventing the light from entering the semiconductor substrate. The approach allows to achieve very high light extraction efficiency in a narrow vertical angle keeping the reasonable thermal and current conductivity properties. As an example, a micro-LED structure has been modeled with AlGaAs-AlAs or AlGaAs-AlOx DBRs and an active region based on InGaAlP quantum well(s) emitting in the orange spectral range at 610 nm. A passive dielectric SiO2 cavity is confined by dielectric Ta2O5/SiO2 and AlGaAs-AlOx DBRs. Cylindrically-symmetric structures with multiple ring patterns are modeled. It is demonstrated that the extraction coefficient of light to the air can be increased from 1.3% up to above 90% in a narrow vertical angle (full width at half maximum (FWHM) below 20°). For very small oxide-confined apertures 100nm the narrowing of the FWHM for light extraction can be reduced down to 5°. Consequently high efficiency high brightness arrays of micro-LEDs becomes possible. For single emitters the approach is particularly interesting for oscillator strength engineering allowing high speed data transmission and for single photonics applying single quantum dot (QD) emitters and allowing >90% coupling of the emission into single mode fiber. We also note that for longer wavelength ( 1300nm) QDs the thickness of the layers and surface patterns significantly increase allowing greatly reduced processing tolerances and applying further simplifications due to the possibility of using high contrast GaAs-AlOx DBRs.

Glutaric aciduria type I: A treatable neurometabolic disorder

PubMed Central

Kamate, Mahesh; Patil, Vishwanath; Chetal, Vivek; Darak, Pavan; Hattiholi, Virupaxi

2012-01-01

Background and Objectives: Glutaric aciduria Type-I (GA-I) has characteristic clinical and neuroimaging features, which clinches the diagnosis in a majority of patients. However, there have been few case reports on GA-I from India. This study was undertaken to study the clinical presentations, metabolic profile, neuroimaging findings and outcome of patients with GA-I. Study Design: The present study was a retrospective study. Materials and Methods: Retrospective review of charts of patients with a diagnosis of GA-I was carried out from March 2008 to April 2010. The clinical, laboratory and neuroimaging findings were extracted in a predesigned proforma and the data was analyzed. Results: Eleven cases were found to have GA-1. Clinical presentation was quite varied. Follow-up of patients revealed that one patient with macrocephaly as the only clinical finding was developmentally normal. One patient with encephalitis-like illness steadily improved and started walking at 2 years. Two patients were bed ridden and had severe dystonia. One patient died during follow-up. The remaining six patients had dystonia and other abnormal movements, but had attained sitting without support and were not ambulatory. Conclusion: GA-I is not an uncommon disorder and diagnosis can be made easily based on clinical, laboratory investigations and neuroimaging findings. It is one of the treatable metabolic disorders and, if managed appropriately, favorable prognosis can be given. PMID:22412270

Maskless micro/nanofabrication on GaAs surface by friction-induced selective etching

PubMed Central

2014-01-01

In the present study, a friction-induced selective etching method was developed to produce nanostructures on GaAs surface. Without any resist mask, the nanofabrication can be achieved by scratching and post-etching in sulfuric acid solution. The effects of the applied normal load and etching period on the formation of the nanostructure were studied. Results showed that the height of the nanostructure increased with the normal load or the etching period. XPS and Raman detection demonstrated that residual compressive stress and lattice densification were probably the main reason for selective etching, which eventually led to the protrusive nanostructures from the scratched area on the GaAs surface. Through a homemade multi-probe instrument, the capability of this fabrication method was demonstrated by producing various nanostructures on the GaAs surface, such as linear array, intersecting parallel, surface mesas, and special letters. In summary, the proposed method provided a straightforward and more maneuverable micro/nanofabrication method on the GaAs surface. PMID:24495647

Reverse-bias-driven dichromatic electroluminescence of n-ZnO wire arrays/p-GaN film heterojunction light-emitting diodes

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

Jeong, Junseok; Choi, Ji Eun; Hong, Young Joon, E-mail: yjhong@sejong.ac.kr

Position-controlled n-ZnO microwire (MW) and nanowire-bundle (NW-B) arrays were fabricated using hydrothermal growth of ZnO on a patterned p-GaN film. Both the wire/film p–n heterojunctions showed electrical rectification features at reverse-bias (rb) voltages, analogous to backward diodes. Dichromatic electroluminescence (EL) emissions with 445- and 560-nm-wavelength peaks displayed whitish-blue and greenish-yellow light from MW- and NW-B-based heterojunctions at rb voltages, respectively. The different dichromatic EL emission colors were studied based on photoluminescence spectra and the dichromatic EL peak intensity ratios as a function of the rb voltage. The different EL colors are discussed with respect to depletion thickness and electron tunnelingmore » probability determined by wire/film junction geometry and size.« less

Reverse-bias-driven dichromatic electroluminescence of n-ZnO wire arrays/p-GaN film heterojunction light-emitting diodes

NASA Astrophysics Data System (ADS)

Jeong, Junseok; Choi, Ji Eun; Kim, Yong-Jin; Hwang, Sunyong; Kim, Sung Kyu; Kim, Jong Kyu; Jeong, Hu Young; Hong, Young Joon

2016-09-01

Position-controlled n-ZnO microwire (MW) and nanowire-bundle (NW-B) arrays were fabricated using hydrothermal growth of ZnO on a patterned p-GaN film. Both the wire/film p-n heterojunctions showed electrical rectification features at reverse-bias (rb) voltages, analogous to backward diodes. Dichromatic electroluminescence (EL) emissions with 445- and 560-nm-wavelength peaks displayed whitish-blue and greenish-yellow light from MW- and NW-B-based heterojunctions at rb voltages, respectively. The different dichromatic EL emission colors were studied based on photoluminescence spectra and the dichromatic EL peak intensity ratios as a function of the rb voltage. The different EL colors are discussed with respect to depletion thickness and electron tunneling probability determined by wire/film junction geometry and size.

A novel feature extraction approach for microarray data based on multi-algorithm fusion

PubMed Central

Jiang, Zhu; Xu, Rong

2015-01-01

Feature extraction is one of the most important and effective method to reduce dimension in data mining, with emerging of high dimensional data such as microarray gene expression data. Feature extraction for gene selection, mainly serves two purposes. One is to identify certain disease-related genes. The other is to find a compact set of discriminative genes to build a pattern classifier with reduced complexity and improved generalization capabilities. Depending on the purpose of gene selection, two types of feature extraction algorithms including ranking-based feature extraction and set-based feature extraction are employed in microarray gene expression data analysis. In ranking-based feature extraction, features are evaluated on an individual basis, without considering inter-relationship between features in general, while set-based feature extraction evaluates features based on their role in a feature set by taking into account dependency between features. Just as learning methods, feature extraction has a problem in its generalization ability, which is robustness. However, the issue of robustness is often overlooked in feature extraction. In order to improve the accuracy and robustness of feature extraction for microarray data, a novel approach based on multi-algorithm fusion is proposed. By fusing different types of feature extraction algorithms to select the feature from the samples set, the proposed approach is able to improve feature extraction performance. The new approach is tested against gene expression dataset including Colon cancer data, CNS data, DLBCL data, and Leukemia data. The testing results show that the performance of this algorithm is better than existing solutions. PMID:25780277

A novel feature extraction approach for microarray data based on multi-algorithm fusion.

PubMed

Jiang, Zhu; Xu, Rong

2015-01-01

Feature extraction is one of the most important and effective method to reduce dimension in data mining, with emerging of high dimensional data such as microarray gene expression data. Feature extraction for gene selection, mainly serves two purposes. One is to identify certain disease-related genes. The other is to find a compact set of discriminative genes to build a pattern classifier with reduced complexity and improved generalization capabilities. Depending on the purpose of gene selection, two types of feature extraction algorithms including ranking-based feature extraction and set-based feature extraction are employed in microarray gene expression data analysis. In ranking-based feature extraction, features are evaluated on an individual basis, without considering inter-relationship between features in general, while set-based feature extraction evaluates features based on their role in a feature set by taking into account dependency between features. Just as learning methods, feature extraction has a problem in its generalization ability, which is robustness. However, the issue of robustness is often overlooked in feature extraction. In order to improve the accuracy and robustness of feature extraction for microarray data, a novel approach based on multi-algorithm fusion is proposed. By fusing different types of feature extraction algorithms to select the feature from the samples set, the proposed approach is able to improve feature extraction performance. The new approach is tested against gene expression dataset including Colon cancer data, CNS data, DLBCL data, and Leukemia data. The testing results show that the performance of this algorithm is better than existing solutions.

Low defect InGaAs quantum well selectively grown by metal organic chemical vapor deposition on Si(100) 300 mm wafers for next generation non planar devices

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

Cipro, R.; Gorbenko, V.; Univ. Grenoble Alpes, F-38000, France CEA-LETI, MINATEC Campus, F-38054 Grenoble

2014-06-30

Metal organic chemical vapor deposition of GaAs, InGaAs, and AlGaAs on nominal 300 mm Si(100) at temperatures below 550 °C was studied using the selective aspect ratio trapping method. We clearly show that growing directly GaAs on a flat Si surface in a SiO{sub 2} cavity with an aspect ratio as low as 1.3 is efficient to completely annihilate the anti-phase boundary domains. InGaAs quantum wells were grown on a GaAs buffer and exhibit room temperature micro-photoluminescence. Cathodoluminescence reveals the presence of dark spots which could be associated with the presence of emerging dislocation in a direction parallel to the cavity. Themore » InGaAs layers obtained with no antiphase boundaries are perfect candidates for being integrated as channels in n-type metal oxide semiconductor field effect transistor (MOSFET), while the low temperatures used allow the co-integration of p-type MOSFET.« less

Fabrication of an electrochemical sensor based on computationally designed molecularly imprinted polymer for the determination of mesalamine in real samples.

PubMed

Torkashvand, M; Gholivand, M B; Taherkhani, F

2015-10-01

A novel electrochemical sensor based on mesalamine molecularly imprinted polymer (MIP) film on a glassy carbon electrode was fabricated. Density functional theory (DFT) in gas and solution phases was developed to study the intermolecular interactions in the pre-polymerization mixture and to find the suitable functional monomers in MIP preparation. On the basis of computational results, o-phenylenediamine (OP), gallic acid (GA) and p-aminobenzoic acid (ABA) were selected as functional monomers. The MIP film was cast on glassy carbon electrode by electropolymerization of solution containing ternary monomers and then followed by Ag dendrites (AgDs) with nanobranch deposition. The surface feature of the modified electrode (AgDs/MIP/GCE) was characterized by scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS). Under the optimal experimental conditions, the peak current was proportional to the concentration of mesalamine ranging from 0.05 to 100 μM, with the detection limit of 0.015 μM. The proposed sensor was applied successfully for mesalamine determination in real samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Validation of a [Al18F]PSMA-11 preparation for clinical applications.

PubMed

Al-Momani, Ehab; Israel, Ina; Samnick, Samuel

2017-12-01

Imaging prostate-specific membrane antigen (PSMA) using positron emission tomography (PET) has been presented so far as the most sensitive and specific with regard to prostate cancer detection, in particular in high-risk prostate cancer patients. Currently, it mainly features Gallium-68 ( 68 Ga) labeled PSMA ligands, notably [ 68 Ga]Glu-urea-Lys(Ahx)-HBED-CC ([ 68 Ga]-PSMA-11) and [ 68 Ga]DOTAGA-FFK (Sub-KuE termed ([ 68 Ga]PSMA-I&T). However, 68 Ga has several shortcomings as radionuclide including a short half-life and non-ideal energies. This has motivated consideration of 18 F-labeled analogues for PET imaging of prostate cancer. Here, we describe a simple synthesis and validation of a fluorine-18 labeled Glu-urea-Lys(Ahx)-HBED-CC ([Al 18 F]PSMA-11) for nuclear medicine applications. An efficient method for preparation of [Al 18 F]PSMA-11 was developed and validated (according to Pharm Eur) for routinely clinical applications. [Al 18 F]PSMA-11 was reproducibly obtained in radiochemical yields of 84 ± 6% (n = 15) and > 98% radiochemical purity using an improved one-step radiofluorination in aqueous solution. The total (production/preparation) time, including purification, pharmacological formulation of the isolated product and the quality control of the injectable solution was less than 60min. The [Al 18 F]PSMA-11 was stable over 4h in 1% EtOH/saline selected as injection solution. The solution was sterile, non-pyrogenic and ready for clinical applications after sterile filtration through a 0.22µm membrane filter under sterile conditions. In addition, [Al 18 F]PSMA-11 exhibited higher uptake and retention in PMSA-expressing LNCap prostate cells as compared to its clinically established 68 Ga-labeled analogues [ 68 Ga]PSMA-11 and [ 68 Ga]PSMA-I&T as well as to [ 68 Ga]NOTA-Bn-PSMA. The simple and fast preparation of [Al 18 F]PSMA-11 combined with its favorable pharmacological properties warrant its translation to a clinical setting. The facile and high-yielding radiosynthesis of [Al 18 F]PSMA-11as well as its promising in vitro and in-vivo characteristics makes it worthy of clinical development for PET imaging of prostate cancer. Copyright © 2017. Published by Elsevier Ltd.

System Complexity Reduction via Feature Selection

ERIC Educational Resources Information Center

Deng, Houtao

2011-01-01

This dissertation transforms a set of system complexity reduction problems to feature selection problems. Three systems are considered: classification based on association rules, network structure learning, and time series classification. Furthermore, two variable importance measures are proposed to reduce the feature selection bias in tree…

IMMAN: free software for information theory-based chemometric analysis.

PubMed

Urias, Ricardo W Pino; Barigye, Stephen J; Marrero-Ponce, Yovani; García-Jacas, César R; Valdes-Martiní, José R; Perez-Gimenez, Facundo

2015-05-01

The features and theoretical background of a new and free computational program for chemometric analysis denominated IMMAN (acronym for Information theory-based CheMoMetrics ANalysis) are presented. This is multi-platform software developed in the Java programming language, designed with a remarkably user-friendly graphical interface for the computation of a collection of information-theoretic functions adapted for rank-based unsupervised and supervised feature selection tasks. A total of 20 feature selection parameters are presented, with the unsupervised and supervised frameworks represented by 10 approaches in each case. Several information-theoretic parameters traditionally used as molecular descriptors (MDs) are adapted for use as unsupervised rank-based feature selection methods. On the other hand, a generalization scheme for the previously defined differential Shannon's entropy is discussed, as well as the introduction of Jeffreys information measure for supervised feature selection. Moreover, well-known information-theoretic feature selection parameters, such as information gain, gain ratio, and symmetrical uncertainty are incorporated to the IMMAN software ( http://mobiosd-hub.com/imman-soft/ ), following an equal-interval discretization approach. IMMAN offers data pre-processing functionalities, such as missing values processing, dataset partitioning, and browsing. Moreover, single parameter or ensemble (multi-criteria) ranking options are provided. Consequently, this software is suitable for tasks like dimensionality reduction, feature ranking, as well as comparative diversity analysis of data matrices. Simple examples of applications performed with this program are presented. A comparative study between IMMAN and WEKA feature selection tools using the Arcene dataset was performed, demonstrating similar behavior. In addition, it is revealed that the use of IMMAN unsupervised feature selection methods improves the performance of both IMMAN and WEKA supervised algorithms. Graphic representation for Shannon's distribution of MD calculating software.

Comparative analysis of high-performance infrared avalanche InxGa1-xAsyP1-y and Hg1-xCdxTe heterophotodiodes

NASA Astrophysics Data System (ADS)

Kholodnov, Viacheslav; Drugova, Albina; Nikitin, Mikhail; Chekanova, Galina

2012-10-01

Technology of infrared (IR) avalanche photodiodes (APDs) gradually moves from simple single element APD to 2D focal plane arrays (FPA). Spectral covering of APDs is expanded continuously from classic 1.3 μm to longer wavelengths due to using of narrow-gap semiconductor materials like Hg1-xCdxTe. APDs are of great interest to developers and manufacturers of different optical communication, measuring and 3D reconstruction thermal imaging systems. Major IR detector materials for manufacturing of high-performance APDs became heteroepitaxial structures InxGa1-xAsyP1-y and Hg1-xCdxTe. Progress in IR APD technology was achieved through serious improvement in material growing techniques enabling forming of multilayer heterostuctures with separate absorption and multiplication regions (SAM). Today SAM-APD design can be implemented both on InxGa1-xAsyP1-y and Hg1-xCdxTe multilayer heteroepitaxial structures. To create the best performance optimal design avalanche heterophotodiode (AHPD) it is necessary to carry out a detailed theoretical analysis of basic features of generation, avalanche breakdown and multiplication of charge carriers in proper heterostructure. Optimization of AHPD properties requires comprehensive estimation of AHPD's pixel performance depending on pixel's multi-layer structure design, layers doping, distribution of electric field in the structure and operating temperature. Objective of the present article is to compare some features of 1.55 μm SAM-AHPDs based on InxGa1-xAsyP1-y and Hg1-xCdxTe.

Design, synthesis, and structure-activity relationship study of glycyrrhetinic acid derivatives as potent and selective inhibitors against human carboxylesterase 2.

PubMed

Zou, Li-Wei; Li, Yao-Guang; Wang, Ping; Zhou, Kun; Hou, Jie; Jin, Qiang; Hao, Da-Cheng; Ge, Guang-Bo; Yang, Ling

2016-04-13

Human carboxylesterase 2 (hCE2), one of the major carboxylesterases in the human intestine and various tumour tissues, plays important roles in the oral bioavailability and treatment outcomes of ester- or amide-containing drugs or prodrugs, such as anticancer agents CPT-11 (irinotecan) and LY2334737 (gemcitabine). In this study, 18β-glycyrrhetinic acid (GA), the most abundant pentacyclic triterpenoid from natural source, was selected as a reference compound for the development of potent and specific inhibitors against hCE2. Simple semi-synthetic modulation on GA was performed to obtain a series of GA derivatives. Structure-activity relationship analysis brought novel insights into the structure modification of GA. Converting the 11-oxo-12-ene of GA to 12-diene moiety, and C-3 hydroxyl and C-30 carboxyl group to 3-O-β-carboxypropionyl and ethyl ester respectively, led to a significant enhancement of the inhibitory effect on hCE2 and the selectivity over hCE1. These exciting findings inspired us to design and synthesize the more potent compound 15 (IC50 0.02 μM) as a novel and highly selective inhibitor against hCE2, which was 3463-fold more potent than the parent compound GA and demonstrated excellent selectivity (>1000-fold over hCE1). The molecular docking study of compound 15 and the active site of hCE1 and hCE2 demonstrated that the potent and selective inhibition of compound 15 toward hCE2 could partially be attributed to its relatively stronger interactions with hCE2 than with hCE1. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Design a software real-time operation platform for wave piercing catamarans motion control using linear quadratic regulator based genetic algorithm.

PubMed

Liang, Lihua; Yuan, Jia; Zhang, Songtao; Zhao, Peng

2018-01-01

This work presents optimal linear quadratic regulator (LQR) based on genetic algorithm (GA) to solve the two degrees of freedom (2 DoF) motion control problem in head seas for wave piercing catamarans (WPC). The proposed LQR based GA control strategy is to select optimal weighting matrices (Q and R). The seakeeping performance of WPC based on proposed algorithm is challenged because of multi-input multi-output (MIMO) system of uncertain coefficient problems. Besides the kinematical constraint problems of WPC, the external conditions must be considered, like the sea disturbance and the actuators (a T-foil and two flaps) control. Moreover, this paper describes the MATLAB and LabVIEW software plats to simulate the reduction effects of WPC. Finally, the real-time (RT) NI CompactRIO embedded controller is selected to test the effectiveness of the actuators based on proposed techniques. In conclusion, simulation and experimental results prove the correctness of the proposed algorithm. The percentage of heave and pitch reductions are more than 18% in different high speeds and bad sea conditions. And the results also verify the feasibility of NI CompactRIO embedded controller.

Design a software real-time operation platform for wave piercing catamarans motion control using linear quadratic regulator based genetic algorithm

PubMed Central

Liang, Lihua; Zhang, Songtao; Zhao, Peng

2018-01-01

This work presents optimal linear quadratic regulator (LQR) based on genetic algorithm (GA) to solve the two degrees of freedom (2 DoF) motion control problem in head seas for wave piercing catamarans (WPC). The proposed LQR based GA control strategy is to select optimal weighting matrices (Q and R). The seakeeping performance of WPC based on proposed algorithm is challenged because of multi-input multi-output (MIMO) system of uncertain coefficient problems. Besides the kinematical constraint problems of WPC, the external conditions must be considered, like the sea disturbance and the actuators (a T-foil and two flaps) control. Moreover, this paper describes the MATLAB and LabVIEW software plats to simulate the reduction effects of WPC. Finally, the real-time (RT) NI CompactRIO embedded controller is selected to test the effectiveness of the actuators based on proposed techniques. In conclusion, simulation and experimental results prove the correctness of the proposed algorithm. The percentage of heave and pitch reductions are more than 18% in different high speeds and bad sea conditions. And the results also verify the feasibility of NI CompactRIO embedded controller. PMID:29709008

One-Pot Green Synthesis of Graphene Nanosheets Encapsulated Gold Nanoparticles for Sensitive and Selective Detection of Dopamine

PubMed Central

Thirumalraj, Balamurugan; Rajkumar, Chellakannu; Chen, Shen-Ming; Palanisamy, Selvakumar

2017-01-01

We report a simple new approach for green preparation of gallic acid supported reduced graphene oxide encapsulated gold nanoparticles (GA-RGO/AuNPs) via one-pot hydrothermal method. The as-prepared composites were successfully characterized by using Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, X-ray powder diffraction techniques (XRD), scanning electron microscope (SEM), high resolution transmission electron microscopy (HRTEM) and elemental analysis. The GA-RGO/AuNPs modified electrode behaves as a hybrid electrode material for sensitive and selective detection of dopamine (DA) in presence of ascorbic acid (AA) and uric acid (UA). The GA-RGO/AuNPs modified electrode displays an excellent electrocatalytic activity towards the oxidation of DA and exhibits a wide linear response range over the DA concentrations from 0.01–100.3 μM with a detection limit (LOD) of 2.6 nM based on S/N = 3. In addition, the proposed sensor could be applied for the determination of DA in human serum and urine samples for practical analysis. PMID:28128225

One-Pot Green Synthesis of Graphene Nanosheets Encapsulated Gold Nanoparticles for Sensitive and Selective Detection of Dopamine

NASA Astrophysics Data System (ADS)

Thirumalraj, Balamurugan; Rajkumar, Chellakannu; Chen, Shen-Ming; Palanisamy, Selvakumar

2017-01-01

We report a simple new approach for green preparation of gallic acid supported reduced graphene oxide encapsulated gold nanoparticles (GA-RGO/AuNPs) via one-pot hydrothermal method. The as-prepared composites were successfully characterized by using Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, X-ray powder diffraction techniques (XRD), scanning electron microscope (SEM), high resolution transmission electron microscopy (HRTEM) and elemental analysis. The GA-RGO/AuNPs modified electrode behaves as a hybrid electrode material for sensitive and selective detection of dopamine (DA) in presence of ascorbic acid (AA) and uric acid (UA). The GA-RGO/AuNPs modified electrode displays an excellent electrocatalytic activity towards the oxidation of DA and exhibits a wide linear response range over the DA concentrations from 0.01-100.3 μM with a detection limit (LOD) of 2.6 nM based on S/N = 3. In addition, the proposed sensor could be applied for the determination of DA in human serum and urine samples for practical analysis.

Dislocation filtering in GaN nanostructures.

PubMed

Colby, Robert; Liang, Zhiwen; Wildeson, Isaac H; Ewoldt, David A; Sands, Timothy D; García, R Edwin; Stach, Eric A

2010-05-12

Dislocation filtering in GaN by selective area growth through a nanoporous template is examined both by transmission electron microscopy and numerical modeling. These nanorods grow epitaxially from the (0001)-oriented GaN underlayer through the approximately 100 nm thick template and naturally terminate with hexagonal pyramid-shaped caps. It is demonstrated that for a certain window of geometric parameters a threading dislocation growing within a GaN nanorod is likely to be excluded by the strong image forces of the nearby free surfaces. Approximately 3000 nanorods were examined in cross-section, including growth through 50 and 80 nm diameter pores. The very few threading dislocations not filtered by the template turn toward a free surface within the nanorod, exiting less than 50 nm past the base of the template. The potential active region for light-emitting diode devices based on these nanorods would have been entirely free of threading dislocations for all samples examined. A greater than 2 orders of magnitude reduction in threading dislocation density can be surmised from a data set of this size. A finite element-based implementation of the eigenstrain model was employed to corroborate the experimentally observed data and examine a larger range of potential nanorod geometries, providing a simple map of the different regimes of dislocation filtering for this class of GaN nanorods. These results indicate that nanostructured semiconductor materials are effective at eliminating deleterious extended defects, as necessary to enhance the optoelectronic performance and device lifetimes compared to conventional planar heterostructures.

Feature selection for elderly faller classification based on wearable sensors.

PubMed

Howcroft, Jennifer; Kofman, Jonathan; Lemaire, Edward D

2017-05-30

Wearable sensors can be used to derive numerous gait pattern features for elderly fall risk and faller classification; however, an appropriate feature set is required to avoid high computational costs and the inclusion of irrelevant features. The objectives of this study were to identify and evaluate smaller feature sets for faller classification from large feature sets derived from wearable accelerometer and pressure-sensing insole gait data. A convenience sample of 100 older adults (75.5 ± 6.7 years; 76 non-fallers, 24 fallers based on 6 month retrospective fall occurrence) walked 7.62 m while wearing pressure-sensing insoles and tri-axial accelerometers at the head, pelvis, left and right shanks. Feature selection was performed using correlation-based feature selection (CFS), fast correlation based filter (FCBF), and Relief-F algorithms. Faller classification was performed using multi-layer perceptron neural network, naïve Bayesian, and support vector machine classifiers, with 75:25 single stratified holdout and repeated random sampling. The best performing model was a support vector machine with 78% accuracy, 26% sensitivity, 95% specificity, 0.36 F1 score, and 0.31 MCC and one posterior pelvis accelerometer input feature (left acceleration standard deviation). The second best model achieved better sensitivity (44%) and used a support vector machine with 74% accuracy, 83% specificity, 0.44 F1 score, and 0.29 MCC. This model had ten input features: maximum, mean and standard deviation posterior acceleration; maximum, mean and standard deviation anterior acceleration; mean superior acceleration; and three impulse features. The best multi-sensor model sensitivity (56%) was achieved using posterior pelvis and both shank accelerometers and a naïve Bayesian classifier. The best single-sensor model sensitivity (41%) was achieved using the posterior pelvis accelerometer and a naïve Bayesian classifier. Feature selection provided models with smaller feature sets and improved faller classification compared to faller classification without feature selection. CFS and FCBF provided the best feature subset (one posterior pelvis accelerometer feature) for faller classification. However, better sensitivity was achieved by the second best model based on a Relief-F feature subset with three pressure-sensing insole features and seven head accelerometer features. Feature selection should be considered as an important step in faller classification using wearable sensors.

Green-Ampt approximations: A comprehensive analysis

NASA Astrophysics Data System (ADS)

Ali, Shakir; Islam, Adlul; Mishra, P. K.; Sikka, Alok K.

2016-04-01

Green-Ampt (GA) model and its modifications are widely used for simulating infiltration process. Several explicit approximate solutions to the implicit GA model have been developed with varying degree of accuracy. In this study, performance of nine explicit approximations to the GA model is compared with the implicit GA model using the published data for broad range of soil classes and infiltration time. The explicit GA models considered are Li et al. (1976) (LI), Stone et al. (1994) (ST), Salvucci and Entekhabi (1994) (SE), Parlange et al. (2002) (PA), Barry et al. (2005) (BA), Swamee et al. (2012) (SW), Ali et al. (2013) (AL), Almedeij and Esen (2014) (AE), and Vatankhah (2015) (VA). Six statistical indicators (e.g., percent relative error, maximum absolute percent relative error, average absolute percent relative errors, percent bias, index of agreement, and Nash-Sutcliffe efficiency) and relative computer computation time are used for assessing the model performance. Models are ranked based on the overall performance index (OPI). The BA model is found to be the most accurate followed by the PA and VA models for variety of soil classes and infiltration periods. The AE, SW, SE, and LI model also performed comparatively better. Based on the overall performance index, the explicit models are ranked as BA > PA > VA > LI > AE > SE > SW > ST > AL. Results of this study will be helpful in selection of accurate and simple explicit approximate GA models for solving variety of hydrological problems.

Multi-period project portfolio selection under risk considerations and stochastic income

NASA Astrophysics Data System (ADS)

Tofighian, Ali Asghar; Moezzi, Hamid; Khakzar Barfuei, Morteza; Shafiee, Mahmood

2018-02-01

This paper deals with multi-period project portfolio selection problem. In this problem, the available budget is invested on the best portfolio of projects in each period such that the net profit is maximized. We also consider more realistic assumptions to cover wider range of applications than those reported in previous studies. A novel mathematical model is presented to solve the problem, considering risks, stochastic incomes, and possibility of investing extra budget in each time period. Due to the complexity of the problem, an effective meta-heuristic method hybridized with a local search procedure is presented to solve the problem. The algorithm is based on genetic algorithm (GA), which is a prominent method to solve this type of problems. The GA is enhanced by a new solution representation and well selected operators. It also is hybridized with a local search mechanism to gain better solution in shorter time. The performance of the proposed algorithm is then compared with well-known algorithms, like basic genetic algorithm (GA), particle swarm optimization (PSO), and electromagnetism-like algorithm (EM-like) by means of some prominent indicators. The computation results show the superiority of the proposed algorithm in terms of accuracy, robustness and computation time. At last, the proposed algorithm is wisely combined with PSO to improve the computing time considerably.

Improvements of the Vis-NIRS Model in the Prediction of Soil Organic Matter Content Using Spectral Pretreatments, Sample Selection, and Wavelength Optimization

NASA Astrophysics Data System (ADS)

Lin, Z. D.; Wang, Y. B.; Wang, R. J.; Wang, L. S.; Lu, C. P.; Zhang, Z. Y.; Song, L. T.; Liu, Y.

2017-07-01

A total of 130 topsoil samples collected from Guoyang County, Anhui Province, China, were used to establish a Vis-NIR model for the prediction of organic matter content (OMC) in lime concretion black soils. Different spectral pretreatments were applied for minimizing the irrelevant and useless information of the spectra and increasing the spectra correlation with the measured values. Subsequently, the Kennard-Stone (KS) method and sample set partitioning based on joint x-y distances (SPXY) were used to select the training set. Successive projection algorithm (SPA) and genetic algorithm (GA) were then applied for wavelength optimization. Finally, the principal component regression (PCR) model was constructed, in which the optimal number of principal components was determined using the leave-one-out cross validation technique. The results show that the combination of the Savitzky-Golay (SG) filter for smoothing and multiplicative scatter correction (MSC) can eliminate the effect of noise and baseline drift; the SPXY method is preferable to KS in the sample selection; both the SPA and the GA can significantly reduce the number of wavelength variables and favorably increase the accuracy, especially GA, which greatly improved the prediction accuracy of soil OMC with Rcc, RMSEP, and RPD up to 0.9316, 0.2142, and 2.3195, respectively.

A predictive machine learning approach for microstructure optimization and materials design

NASA Astrophysics Data System (ADS)

Liu, Ruoqian; Kumar, Abhishek; Chen, Zhengzhang; Agrawal, Ankit; Sundararaghavan, Veera; Choudhary, Alok

2015-06-01

This paper addresses an important materials engineering question: How can one identify the complete space (or as much of it as possible) of microstructures that are theoretically predicted to yield the desired combination of properties demanded by a selected application? We present a problem involving design of magnetoelastic Fe-Ga alloy microstructure for enhanced elastic, plastic and magnetostrictive properties. While theoretical models for computing properties given the microstructure are known for this alloy, inversion of these relationships to obtain microstructures that lead to desired properties is challenging, primarily due to the high dimensionality of microstructure space, multi-objective design requirement and non-uniqueness of solutions. These challenges render traditional search-based optimization methods incompetent in terms of both searching efficiency and result optimality. In this paper, a route to address these challenges using a machine learning methodology is proposed. A systematic framework consisting of random data generation, feature selection and classification algorithms is developed. Experiments with five design problems that involve identification of microstructures that satisfy both linear and nonlinear property constraints show that our framework outperforms traditional optimization methods with the average running time reduced by as much as 80% and with optimality that would not be achieved otherwise.

Structural modifications of silicon-implanted GaAs induced by the athermal annealing technique

NASA Astrophysics Data System (ADS)

Qadri, S. B.; Yousuf, M.; Kendziora, C. A.; Nachumi, B.; Fischer, R.; Grun, J.; Rao, M. V.; Tucker, J.; Siddiqui, S.; Ridgway, M. C.

2004-12-01

We have used high-resolution X-ray diffraction and Raman spectroscopy to investigate structural modifications inside and outside the focal region of Si-implanted GaAs samples that have been irradiated at high power by a focused short-pulse laser. Si atoms implanted into the GaAs matrix generate exciton-induced local lattice expansion, resulting in a satellite on the lower-angle side of the Bragg peak. After the laser pulse irradiation, surface features inside and outside the focal spot suggest the presence of Bernard convection cells, indicating that a rapid melting and re-crystallization has taken place. Moreover, the laser irradiation induces a compressive strain inside the focal spot, since the satellite appears on the higher-angle side of the Bragg peak. The stress maximizes at the center of the focal spot and extends far outside the irradiated area (approximately 2.5-mm away from the bull’s eye), suggesting the propagation of a laser-induced mechanical wave. The maximum compressive stress inside the focal spot corresponds to 2.7 GPa. Raman spectra inside the focal spot resemble that of pristine GaAs, indicating that rapid melting has introduced significant heterogeneity, with zones of high and low Si concentration. X-ray measurements indicate that areas inside the focal spot and annealed areas outside of the focal spot contain overtones of a minor tetragonal distortion of the lattice, consistent with the observed relaxation of Raman selection rules when compared with the parent zinc-blende structure.

Ridge InGaAs/InP multi-quantum-well selective growth in nanoscale trenches on Si (001) substrate

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

Li, S.; Zhou, X.; Li, M.

Metal organic chemical vapor deposition of InGaAs/InP multi-quantum-well in nanoscale V-grooved trenches on Si (001) substrate was studied using the aspect ratio trapping method. A high quality GaAs/InP buffer layer with two convex (111) B facets was selectively grown to promote the highly uniform, single-crystal ridge InP/InGaAs multi-quantum-well structure growth. Material quality was confirmed by transmission electron microscopy and room temperature micro-photoluminescence measurements. This approach shows great promise for the fabrication of photonics devices and nanolasers on Si substrate.

QWIP from 4μm up to 18μm

NASA Astrophysics Data System (ADS)

Costard, Eric; Truffer, Jean P.; Huet, Odile; Dua, Lydie; Nedelcu, Alexandre; Robo, J. A.; Marcadet, Xavier; Brèire de l'Isle, Nadia; Bois, Philippe

2006-09-01

Standard GaAs/AlGaAs Quantum Well Infrared Photodetectors (QWIP) are considered as a technological choice for 3 rdgeneration thermal imagers [1], [2]. Since 2001, the THALES Group has been manufacturing sensitive arrays using AsGa based QWIP technology at THALES Research and Technology Laboratory. This QWIP technology allows the realization of large staring arrays for Thermal Imagers (TI) working in the Infrared region of the spectrum. The main advantage of this GaAs detector technology is that it is also used for other commercial devices. The GaAs industry has lead to important improvements over the last ten years and it reaches now an undeniable level of maturity. As a result the key parameters to reach high production yield: large substrate and good uniformity characteristics, have already been achieved. Considering defective pixels, the main usual features are a high operability (> 99.9%) and a low number of clusters having a maximum of 4 dead pixels. Another advantage of this III-V technology is the versatility of the design and processing phases. It allows customizing both the quantum structure and the pixel architecture in order to fulfill the requirements of any specific applications. The spectral response of QWIPs is intrinsically resonant but the quantum structure can be designed for a given detection wavelength window ranging from MWIR, LWIR to VLWIR.

Dense Plasma Focus-Based Nanofabrication of III–V Semiconductors: Unique Features and Recent Advances

PubMed Central

Mangla, Onkar; Roy, Savita; Ostrikov, Kostya (Ken)

2015-01-01

The hot and dense plasma formed in modified dense plasma focus (DPF) device has been used worldwide for the nanofabrication of several materials. In this paper, we summarize the fabrication of III–V semiconductor nanostructures using the high fluence material ions produced by hot, dense and extremely non-equilibrium plasma generated in a modified DPF device. In addition, we present the recent results on the fabrication of porous nano-gallium arsenide (GaAs). The details of morphological, structural and optical properties of the fabricated nano-GaAs are provided. The effect of rapid thermal annealing on the above properties of porous nano-GaAs is studied. The study reveals that it is possible to tailor the size of pores with annealing temperature. The optical properties of these porous nano-GaAs also confirm the possibility to tailor the pore sizes upon annealing. Possible applications of the fabricated and subsequently annealed porous nano-GaAs in transmission-type photo-cathodes and visible optoelectronic devices are discussed. These results suggest that the modified DPF is an effective tool for nanofabrication of continuous and porous III–V semiconductor nanomaterials. Further opportunities for using the modified DPF device for the fabrication of novel nanostructures are discussed as well. PMID:28344261

GaN/NbN epitaxial semiconductor/superconductor heterostructures

NASA Astrophysics Data System (ADS)

Yan, Rusen; Khalsa, Guru; Vishwanath, Suresh; Han, Yimo; Wright, John; Rouvimov, Sergei; Katzer, D. Scott; Nepal, Neeraj; Downey, Brian P.; Muller, David A.; Xing, Huili G.; Meyer, David J.; Jena, Debdeep

2018-03-01

Epitaxy is a process by which a thin layer of one crystal is deposited in an ordered fashion onto a substrate crystal. The direct epitaxial growth of semiconductor heterostructures on top of crystalline superconductors has proved challenging. Here, however, we report the successful use of molecular beam epitaxy to grow and integrate niobium nitride (NbN)-based superconductors with the wide-bandgap family of semiconductors—silicon carbide, gallium nitride (GaN) and aluminium gallium nitride (AlGaN). We apply molecular beam epitaxy to grow an AlGaN/GaN quantum-well heterostructure directly on top of an ultrathin crystalline NbN superconductor. The resulting high-mobility, two-dimensional electron gas in the semiconductor exhibits quantum oscillations, and thus enables a semiconductor transistor—an electronic gain element—to be grown and fabricated directly on a crystalline superconductor. Using the epitaxial superconductor as the source load of the transistor, we observe in the transistor output characteristics a negative differential resistance—a feature often used in amplifiers and oscillators. Our demonstration of the direct epitaxial growth of high-quality semiconductor heterostructures and devices on crystalline nitride superconductors opens up the possibility of combining the macroscopic quantum effects of superconductors with the electronic, photonic and piezoelectric properties of the group III/nitride semiconductor family.

GaN/NbN epitaxial semiconductor/superconductor heterostructures.

PubMed

Yan, Rusen; Khalsa, Guru; Vishwanath, Suresh; Han, Yimo; Wright, John; Rouvimov, Sergei; Katzer, D Scott; Nepal, Neeraj; Downey, Brian P; Muller, David A; Xing, Huili G; Meyer, David J; Jena, Debdeep

2018-03-07

Epitaxy is a process by which a thin layer of one crystal is deposited in an ordered fashion onto a substrate crystal. The direct epitaxial growth of semiconductor heterostructures on top of crystalline superconductors has proved challenging. Here, however, we report the successful use of molecular beam epitaxy to grow and integrate niobium nitride (NbN)-based superconductors with the wide-bandgap family of semiconductors-silicon carbide, gallium nitride (GaN) and aluminium gallium nitride (AlGaN). We apply molecular beam epitaxy to grow an AlGaN/GaN quantum-well heterostructure directly on top of an ultrathin crystalline NbN superconductor. The resulting high-mobility, two-dimensional electron gas in the semiconductor exhibits quantum oscillations, and thus enables a semiconductor transistor-an electronic gain element-to be grown and fabricated directly on a crystalline superconductor. Using the epitaxial superconductor as the source load of the transistor, we observe in the transistor output characteristics a negative differential resistance-a feature often used in amplifiers and oscillators. Our demonstration of the direct epitaxial growth of high-quality semiconductor heterostructures and devices on crystalline nitride superconductors opens up the possibility of combining the macroscopic quantum effects of superconductors with the electronic, photonic and piezoelectric properties of the group III/nitride semiconductor family.

Insight into the Near-Conduction Band States at the Crystallized Interface between GaN and SiN x Grown by Low-Pressure Chemical Vapor Deposition.

PubMed

Liu, Xinyu; Wang, Xinhua; Zhang, Yange; Wei, Ke; Zheng, Yingkui; Kang, Xuanwu; Jiang, Haojie; Li, Junfeng; Wang, Wenwu; Wu, Xuebang; Wang, Xianping; Huang, Sen

2018-06-12

Constant-capacitance deep-level transient Fourier spectroscopy is utilized to characterize the interface between a GaN epitaxial layer and a SiN x passivation layer grown by low-pressure chemical vapor deposition (LPCVD). A near-conduction band (NCB) state E LP ( E C - E T = 60 meV) featuring a very small capture cross section of 1.5 × 10 -20 cm -2 was detected at 70 K at the LPCVD-SiN x /GaN interface. A partially crystallized Si 2 N 2 O thin layer was detected at the interface by high-resolution transmission electron microscopy. Based on first-principles calculations of crystallized Si 2 N 2 O/GaN slabs, it was confirmed that the NCB state E LP mainly originates from the strong interactions between the dangling bonds of gallium and its vicinal atoms near the interface. The partially crystallized Si 2 N 2 O interfacial layer might also give rise to the very small capture cross section of the E LP owing to the smaller lattice mismatch between the Si 2 N 2 O and GaN epitaxial layer and a larger mean free path of the electron in the crystallized portion compared with an amorphous interfacial layer.

Dense Plasma Focus-Based Nanofabrication of III-V Semiconductors: Unique Features and Recent Advances.

PubMed

Mangla, Onkar; Roy, Savita; Ostrikov, Kostya Ken

2015-12-29

The hot and dense plasma formed in modified dense plasma focus (DPF) device has been used worldwide for the nanofabrication of several materials. In this paper, we summarize the fabrication of III-V semiconductor nanostructures using the high fluence material ions produced by hot, dense and extremely non-equilibrium plasma generated in a modified DPF device. In addition, we present the recent results on the fabrication of porous nano-gallium arsenide (GaAs). The details of morphological, structural and optical properties of the fabricated nano-GaAs are provided. The effect of rapid thermal annealing on the above properties of porous nano-GaAs is studied. The study reveals that it is possible to tailor the size of pores with annealing temperature. The optical properties of these porous nano-GaAs also confirm the possibility to tailor the pore sizes upon annealing. Possible applications of the fabricated and subsequently annealed porous nano-GaAs in transmission-type photo-cathodes and visible optoelectronic devices are discussed. These results suggest that the modified DPF is an effective tool for nanofabrication of continuous and porous III-V semiconductor nanomaterials. Further opportunities for using the modified DPF device for the fabrication of novel nanostructures are discussed as well.

Isolation and characterization of gallium resistant Pseudomonas aeruginosa mutants.

PubMed

García-Contreras, Rodolfo; Lira-Silva, Elizabeth; Jasso-Chávez, Ricardo; Hernández-González, Ismael L; Maeda, Toshinari; Hashimoto, Takahiro; Boogerd, Fred C; Sheng, Lili; Wood, Thomas K; Moreno-Sánchez, Rafael

2013-12-01

Pseudomonas aeruginosa PA14 cells resistant to the novel antimicrobial gallium nitrate (Ga) were developed using transposon mutagenesis and by selecting spontaneous mutants. The mutants showing the highest growth in the presence of Ga were selected for further characterization. These mutants showed 4- to 12-fold higher Ga minimal inhibitory growth concentrations and a greater than 8-fold increase in the minimum biofilm eliminating Ga concentration. Both types of mutants produced Ga resistant biofilms whereas the formation of wild-type biofilms was strongly inhibited by Ga. The gene interrupted in the transposon mutant was hitA, which encodes a periplasmic iron binding protein that delivers Fe³⁺ to the HitB iron permease; complementation of the mutant with the hitA gene restored the Ga sensitivity. This hitA mutant showed a 14-fold decrease in Ga internalization versus the wild-type strain, indicating that the HitAB system is also involved in the Ga uptake. Ga uptake in the spontaneous mutant was also lower, although no mutations were found in the hitAB genes. Instead, this mutant harbored 64 non-silent mutations in several genes including those of the phenazine pyocyanin biosynthesis. The spontaneous mutant produced 2-fold higher pyocyanin basal levels than the wild-type; the addition of this phenazine to wild-type cultures protected them from the Ga bacteriostatic effect. The present data indicate that mutations affecting Ga transport and probably pyocyanin biosynthesis enable cells to develop resistance to Ga. Copyright © 2013 Elsevier GmbH. All rights reserved.

Isothermal sections of the quasi-ternary systems Ag{sub 2}S(Se)–Ga{sub 2}S(Se){sub 3}–In{sub 2}S(Se){sub 3} at 820 K and the physical properties of the ternary phases Ga{sub 5.5}In{sub 4.5}S{sub 15}, Ga{sub 6}In{sub 4}Se{sub 15} and Ga{sub 5.5}In{sub 4.5}S{sub 15}:Er{sup 3+}, Ga{sub 6}In{sub 4}Se{sub 15}:Er{sup 3+}

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

Ivashchenko, I.A., E-mail: Ivashchenko.Inna@eenu.edu.ua; Danyliuk, I.V.; Gulay, L.D.

Isothermal sections of the quasi-ternary systems Ag{sub 2}S(Se)–Ga{sub 2}S(Se){sub 3}–In{sub 2}S(Se){sub 3} at 820 K were compared. Along the 50 mol% Ag{sub 2}S(Se), both systems feature continuous solid solutions with the chalcopyrite structure. Along the 17 mol% Ag{sub 2}S(Se), the interactions at the AgIn{sub 5}S(Se){sub 8}–'AgGa{sub 5}S(Se){sub 8}' sections are different. In the Ag{sub 2}S–Ga{sub 2}S{sub 3}–In{sub 2}S{sub 3} system the existence of the layered phase AgGa{sub x}In{sub 5–x}S{sub 8}, 2.25≤x≤2.85, was confirmed (S.G. P6{sub 3}mc). The Ag{sub 2}Se–Ga{sub 2}Se{sub 3}–In{sub 2}Se{sub 3} system features the formation of solid solution (up to 53 mol% Ga{sub 2}Se{sub 3}) based on AgIn{submore » 5}Se{sub 8} (S.G. P-42m). Crystal structure, atomic coordinates were determined by powder diffraction method for samples from the homogeneity region of AgIn{sub 5}Se{sub 8}. Specific conductivities of the crystals Ga{sub 6}In{sub 4}Se{sub 15} (1.33·10{sup −6} Ω{sup −1} m{sup −1}), Ga{sub 5.94}In{sub 3.96}Er{sub 0.1}Se{sub 15} (3.17·10{sup −6} Ω{sup −1} m{sup −1}), Ga{sub 5.5}In{sub 4.5}S{sub 15} (7.94·10{sup −6} Ω{sup −1} m{sup −1}), Ga{sub 5.46}In{sub 4.47}Er{sub 0.07}S{sub 15} (1·10{sup −9} Ω{sup −1} m{sup −1}) were measured at room temperature. Optical absorption and photoconductivity spectra were recorded in the range 400–760 nm. The introduction of erbium leads to an increase in the absorption coefficient and to the appearance of absorption bands at 530, 660, 810, 980, 1530 nm. - Highlights: • Nature of solid solutions in Ag{sub 2}S(Se)–Ga{sub 2}S(Se){sub 3}–In{sub 2}S(Se){sub 3} (820 K) were discussed. • Crystal structures of ternary and quaternary compounds were discussed. • Specific conductivity, optical properties of four single crystals were measured. • Photoconductivity of the Ga{sub 5.5}In{sub 4.5}S{sub 15} in the range 400–760 nm were recorded.« less

Feature selection for wearable smartphone-based human activity recognition with able bodied, elderly, and stroke patients.

PubMed

Capela, Nicole A; Lemaire, Edward D; Baddour, Natalie

2015-01-01

Human activity recognition (HAR), using wearable sensors, is a growing area with the potential to provide valuable information on patient mobility to rehabilitation specialists. Smartphones with accelerometer and gyroscope sensors are a convenient, minimally invasive, and low cost approach for mobility monitoring. HAR systems typically pre-process raw signals, segment the signals, and then extract features to be used in a classifier. Feature selection is a crucial step in the process to reduce potentially large data dimensionality and provide viable parameters to enable activity classification. Most HAR systems are customized to an individual research group, including a unique data set, classes, algorithms, and signal features. These data sets are obtained predominantly from able-bodied participants. In this paper, smartphone accelerometer and gyroscope sensor data were collected from populations that can benefit from human activity recognition: able-bodied, elderly, and stroke patients. Data from a consecutive sequence of 41 mobility tasks (18 different tasks) were collected for a total of 44 participants. Seventy-six signal features were calculated and subsets of these features were selected using three filter-based, classifier-independent, feature selection methods (Relief-F, Correlation-based Feature Selection, Fast Correlation Based Filter). The feature subsets were then evaluated using three generic classifiers (Naïve Bayes, Support Vector Machine, j48 Decision Tree). Common features were identified for all three populations, although the stroke population subset had some differences from both able-bodied and elderly sets. Evaluation with the three classifiers showed that the feature subsets produced similar or better accuracies than classification with the entire feature set. Therefore, since these feature subsets are classifier-independent, they should be useful for developing and improving HAR systems across and within populations.

Feature Selection for Wearable Smartphone-Based Human Activity Recognition with Able bodied, Elderly, and Stroke Patients

PubMed Central

2015-01-01

Human activity recognition (HAR), using wearable sensors, is a growing area with the potential to provide valuable information on patient mobility to rehabilitation specialists. Smartphones with accelerometer and gyroscope sensors are a convenient, minimally invasive, and low cost approach for mobility monitoring. HAR systems typically pre-process raw signals, segment the signals, and then extract features to be used in a classifier. Feature selection is a crucial step in the process to reduce potentially large data dimensionality and provide viable parameters to enable activity classification. Most HAR systems are customized to an individual research group, including a unique data set, classes, algorithms, and signal features. These data sets are obtained predominantly from able-bodied participants. In this paper, smartphone accelerometer and gyroscope sensor data were collected from populations that can benefit from human activity recognition: able-bodied, elderly, and stroke patients. Data from a consecutive sequence of 41 mobility tasks (18 different tasks) were collected for a total of 44 participants. Seventy-six signal features were calculated and subsets of these features were selected using three filter-based, classifier-independent, feature selection methods (Relief-F, Correlation-based Feature Selection, Fast Correlation Based Filter). The feature subsets were then evaluated using three generic classifiers (Naïve Bayes, Support Vector Machine, j48 Decision Tree). Common features were identified for all three populations, although the stroke population subset had some differences from both able-bodied and elderly sets. Evaluation with the three classifiers showed that the feature subsets produced similar or better accuracies than classification with the entire feature set. Therefore, since these feature subsets are classifier-independent, they should be useful for developing and improving HAR systems across and within populations. PMID:25885272

Kinetics of non-catalyzed hydrolysis of tannin in high temperature liquid water*

PubMed Central

Lu, Li-li; Lu, Xiu-yang; Ma, Nan

2008-01-01

High temperature liquid water (HTLW) has drawn increasing attention as an environmentally benign medium for organic chemical reactions, especially acid-/base-catalyzed reactions. Non-catalyzed hydrolyses of gallotannin and tara tannin in HTLW for the simultaneous preparation of gallic acid (GA) and pyrogallol (PY) are under investigation in our laboratory. In this study, the hydrolysis kinetics of gallotannin and tara tannin were determined. The reaction is indicated to be a typical consecutive first-order one in which GA has formed as a main intermediate and PY as the final product. Selective decomposition of tannin in HTLW was proved to be possible by adjusting reaction temperature and time. The present results provide an important basic data and reference for the green preparation of GA and PY. PMID:18500780

Micromirror arrays to assess luminescent nano-objects.

PubMed

Kawakami, Yoichi; Kanai, Akinobu; Kaneta, Akio; Funato, Mitsuru; Kikuchi, Akihiko; Kishino, Katsumi

2011-05-01

We propose an array of submicrometer mirrors to assess luminescent nano-objects. Micromirror arrays (MMAs) are fabricated on Si (001) wafers via selectively doping Ga using the focused ion beam technique to form p-type etch stop regions, subsequent anisotropic chemical etching, and Al deposition. MMAs provide two benefits: reflection of luminescence from nano-objects within MMAs toward the Si (001) surface normal and nano-object labeling. The former increases the probability of optics collecting luminescence and is demonstrated by simulations based on the ray-tracing and finite-difference time-domain methods as well as by experiments. The latter enables different measurements to be repeatedly performed on a single nano-object located at a certain micromirror. For example, a single InGaN∕GaN nanocolumn is assessed by scanning electron microscopy and microphotoluminescence spectroscopy.

Feature Selection Method Based on Neighborhood Relationships: Applications in EEG Signal Identification and Chinese Character Recognition

PubMed Central

Zhao, Yu-Xiang; Chou, Chien-Hsing

2016-01-01

In this study, a new feature selection algorithm, the neighborhood-relationship feature selection (NRFS) algorithm, is proposed for identifying rat electroencephalogram signals and recognizing Chinese characters. In these two applications, dependent relationships exist among the feature vectors and their neighboring feature vectors. Therefore, the proposed NRFS algorithm was designed for solving this problem. By applying the NRFS algorithm, unselected feature vectors have a high priority of being added into the feature subset if the neighboring feature vectors have been selected. In addition, selected feature vectors have a high priority of being eliminated if the neighboring feature vectors are not selected. In the experiments conducted in this study, the NRFS algorithm was compared with two feature algorithms. The experimental results indicated that the NRFS algorithm can extract the crucial frequency bands for identifying rat vigilance states and identifying crucial character regions for recognizing Chinese characters. PMID:27314346

Preparation and in vitro characterization of gallic acid-loaded human serum albumin nanoparticles

NASA Astrophysics Data System (ADS)

Mohammad-Beigi, Hossein; Shojaosadati, Seyed Abbas; Morshedi, Dina; Arpanaei, Ayyoob; Marvian, Amir Tayaranian

2015-04-01

Gallic acid (GA), as an antioxidant and antiparkinson agent, was loaded onto cationic human serum albumin nanoparticles (HSA NPs). Polyethylenimine (PEI)-coated HSA (PEI-HSA) NPs were prepared using three different methods: (I) coating negatively charged HSA NPs with positively charged PEI through attractive electrostatic interactions, (II) coating HSA NPs with PEI via covalent amide bond formation using N-(3-dimethylaminopropyl)- N-ethylcarbodiimide hydrochloride, and (III) coating HSA NPs with PEI via covalent bonding using glutaraldehyde for linking amine groups of PEI and amine groups of albumin NPs. Method II was selected since it resulted in a higher shift in the zeta potential value (mV) and less zeta potential value deviation, and also less size polydispersity. GA was loaded by adsorption onto the surface of PEI-HSA NPs of two different sizes: 117 ± 2.9 nm (PEI-P1) and 180 ± 3.1 nm (PEI-P2) NPs. Both GA-entrapment and GA-loading efficiencies increased slightly with the increasing size of NPs, and were affected intensely by the mass ratio of GA to PEI-HSA NPs. Free radical scavenging of GA was quantified based on the 2,2-diphenyl-1-picrylhydrazyl method. The obtained results showed that GA remains active during the preparation of GA-loaded PEI-HSA NPs. The cytotoxicities of HSA, PEI-HSA, and GA-loaded PEI-HSA NPs on the PC-12 cells, as the neuroendocrine cell line, were measured. Our results indicate that positively charged PEI-HSA NPs are good candidates for efficient and safe delivery of GA to the brain.

Compact cancer biomarkers discovery using a swarm intelligence feature selection algorithm.

PubMed

Martinez, Emmanuel; Alvarez, Mario Moises; Trevino, Victor

2010-08-01

Biomarker discovery is a typical application from functional genomics. Due to the large number of genes studied simultaneously in microarray data, feature selection is a key step. Swarm intelligence has emerged as a solution for the feature selection problem. However, swarm intelligence settings for feature selection fail to select small features subsets. We have proposed a swarm intelligence feature selection algorithm based on the initialization and update of only a subset of particles in the swarm. In this study, we tested our algorithm in 11 microarray datasets for brain, leukemia, lung, prostate, and others. We show that the proposed swarm intelligence algorithm successfully increase the classification accuracy and decrease the number of selected features compared to other swarm intelligence methods. Copyright © 2010 Elsevier Ltd. All rights reserved.

Luminescence emission from nonpolar Al0.3Ga0.7N/GaN core-shell and core-multi-shell nanowires

NASA Astrophysics Data System (ADS)

Namvari, E.; Shojaei, S.; Asgari, A.

2017-12-01

In the present work, we theoretically study the possibility of luminescence emission from two systems of nonpolar Al0.3Ga0.7N/GaN Core-shell and core-multi-shell c-axis oriented nanowires with hexagonal cross section. To obtain energy levels and wave functions through the solution of Schrodinger-Poisson equations, numerical Self-consistent procedure has been employed. N-type doping has been considered to investigate the two-dimensional electron gas formation and its effect on luminescence. The detailed analysis of the results as a function of the various structural parameters has been carried out. The results presents an examination of the band to band luminescence feature and its changes with involved parameters. We found that the size of the system determines the feature of luminescence emission. As main finding, our calculations show that the intensity of luminescence spectrum in facet to facet route of NW cross section is significant than that of corner to corner route. In addition, no shift of the peak position is observed with changing the amount of doping. Our numerical calculations give more insights into the luminescence emission of nonpolar GaN/AlGaN core/shell nanowire and have many implications in experiment.

Glycyrrhetinic Acid-Mediated Polymeric Drug Delivery Targeting the Acidic Microenvironment of Hepatocellular Carcinoma.

PubMed

Zhang, Jinming; Zhang, Min; Ji, Juan; Fang, Xiefan; Pan, Xin; Wang, Yitao; Wu, Chuanbin; Chen, Meiwan

2015-10-01

The major hurdle of current drug carrier against hepatocellular carcinoma (HCC) is the lack of specific and selective drug delivery to HCC. In this study, a novel glycyrrhetinic acid (GA) and poly(L-Histidine) (PHIS) mediated polymeric drug delivery system was developed to target HCC that have GA binding receptors and release its encapsulated anticancer drug in the acidic microenvironment of HCC. Firstly, GA and PHIS were conjugated to form poly (ethylene glycol)-poly(lactic-co-glycolic acid) (GA-PEG-PHIS-PLGA, GA-PPP) micelles by grafting reaction between active terminal groups. Secondly, andrographolide (AGP) was encapsulated to GA-PPP to make AGP/GA-PPP using the solvent evaporation method. The pH-responsive property of AGP/GA-PPP micelles was validated by monitoring its stability and drug release behavior in different pH conditions. Furthermore, selective hepatocellular uptake of GA-PPP micelles in vitro, liver specific drug accumulation in vivo, as well as the enhanced antitumor effects of AGP/GA-PPP micelles confirmed the HCC targeting property of our novel drug delivery system. Average size of AGP/GA-PPP micelles increased significantly and the encapsulated AGP released faster in vitro at pH 5.0, while micelles keeping stable in pH 7.4. AGP/GA-PPP micelles were uptaken more efficiently by human Hep3B liver cells than that by human MDA-MB-231 breast cancer cells. GA-PPP micelles accumulated specifically in the liver and possessed long retention time in vivo. AGP/GA-PPP micelles significantly inhibited tumor growth and provided better therapeutic outcomes compared to free AGP and AGP/PEG-PLGA(AGP/PP) micelles without GA and PHIS decoration. This novel GA-PPP polymeric carrier is promising for targeted treatment of HCC.

Computational Prediction of Protein Epsilon Lysine Acetylation Sites Based on a Feature Selection Method.

PubMed

Gao, JianZhao; Tao, Xue-Wen; Zhao, Jia; Feng, Yuan-Ming; Cai, Yu-Dong; Zhang, Ning

2017-01-01

Lysine acetylation, as one type of post-translational modifications (PTM), plays key roles in cellular regulations and can be involved in a variety of human diseases. However, it is often high-cost and time-consuming to use traditional experimental approaches to identify the lysine acetylation sites. Therefore, effective computational methods should be developed to predict the acetylation sites. In this study, we developed a position-specific method for epsilon lysine acetylation site prediction. Sequences of acetylated proteins were retrieved from the UniProt database. Various kinds of features such as position specific scoring matrix (PSSM), amino acid factors (AAF), and disorders were incorporated. A feature selection method based on mRMR (Maximum Relevance Minimum Redundancy) and IFS (Incremental Feature Selection) was employed. Finally, 319 optimal features were selected from total 541 features. Using the 319 optimal features to encode peptides, a predictor was constructed based on dagging. As a result, an accuracy of 69.56% with MCC of 0.2792 was achieved. We analyzed the optimal features, which suggested some important factors determining the lysine acetylation sites. We developed a position-specific method for epsilon lysine acetylation site prediction. A set of optimal features was selected. Analysis of the optimal features provided insights into the mechanism of lysine acetylation sites, providing guidance of experimental validation. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Features of high-temperature electroluminescence in an LED n-GaSb/n-InGaAsSb/p-AlGaAsSb heterostructure with high potential barriers

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

Danilov, L. V., E-mail: danleon84@mail.ru; Petukhov, A. A.; Mikhailova, M. P.

2016-06-15

The electroluminescent properties of a light-emitting diode n-GaSb/n-InGaAsSb/p-AlGaAsSb heterostructure with high potential barriers are studied in the temperature range of 290–470 K. An atypical temperature increase in the power of the long-wavelength luminescence band with an energy of 0.3 eV is experimentally observed. As the temperature increases to 470 K, the optical radiation power increases by a factor of 1.5–2. To explain the extraordinary temperature dependence of the radiation power, the recombination and carrier transport processes are theoretically analyzed in the heterostructure under study.

Regression-Based Approach For Feature Selection In Classification Issues. Application To Breast Cancer Detection And Recurrence

NASA Astrophysics Data System (ADS)

Belciug, Smaranda; Serbanescu, Mircea-Sebastian

2015-09-01

Feature selection is considered a key factor in classifications/decision problems. It is currently used in designing intelligent decision systems to choose the best features which allow the best performance. This paper proposes a regression-based approach to select the most important predictors to significantly increase the classification performance. Application to breast cancer detection and recurrence using publically available datasets proved the efficiency of this technique.

Minimizing the semantic gap in biomedical content-based image retrieval

NASA Astrophysics Data System (ADS)

Guan, Haiying; Antani, Sameer; Long, L. Rodney; Thoma, George R.

2010-03-01

A major challenge in biomedical Content-Based Image Retrieval (CBIR) is to achieve meaningful mappings that minimize the semantic gap between the high-level biomedical semantic concepts and the low-level visual features in images. This paper presents a comprehensive learning-based scheme toward meeting this challenge and improving retrieval quality. The article presents two algorithms: a learning-based feature selection and fusion algorithm and the Ranking Support Vector Machine (Ranking SVM) algorithm. The feature selection algorithm aims to select 'good' features and fuse them using different similarity measurements to provide a better representation of the high-level concepts with the low-level image features. Ranking SVM is applied to learn the retrieval rank function and associate the selected low-level features with query concepts, given the ground-truth ranking of the training samples. The proposed scheme addresses four major issues in CBIR to improve the retrieval accuracy: image feature extraction, selection and fusion, similarity measurements, the association of the low-level features with high-level concepts, and the generation of the rank function to support high-level semantic image retrieval. It models the relationship between semantic concepts and image features, and enables retrieval at the semantic level. We apply it to the problem of vertebra shape retrieval from a digitized spine x-ray image set collected by the second National Health and Nutrition Examination Survey (NHANES II). The experimental results show an improvement of up to 41.92% in the mean average precision (MAP) over conventional image similarity computation methods.

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.

Feature selection for neural network based defect classification of ceramic components using high frequency ultrasound.

PubMed

Kesharaju, Manasa; Nagarajah, Romesh

2015-09-01

The motivation for this research stems from a need for providing a non-destructive testing method capable of detecting and locating any defects and microstructural variations within armour ceramic components before issuing them to the soldiers who rely on them for their survival. The development of an automated ultrasonic inspection based classification system would make possible the checking of each ceramic component and immediately alert the operator about the presence of defects. Generally, in many classification problems a choice of features or dimensionality reduction is significant and simultaneously very difficult, as a substantial computational effort is required to evaluate possible feature subsets. In this research, a combination of artificial neural networks and genetic algorithms are used to optimize the feature subset used in classification of various defects in reaction-sintered silicon carbide ceramic components. Initially wavelet based feature extraction is implemented from the region of interest. An Artificial Neural Network classifier is employed to evaluate the performance of these features. Genetic Algorithm based feature selection is performed. Principal Component Analysis is a popular technique used for feature selection and is compared with the genetic algorithm based technique in terms of classification accuracy and selection of optimal number of features. The experimental results confirm that features identified by Principal Component Analysis lead to improved performance in terms of classification percentage with 96% than Genetic algorithm with 94%. Copyright © 2015 Elsevier B.V. All rights reserved.

Feature-based and spatial attentional selection in visual working memory.

PubMed

Heuer, Anna; Schubö, Anna

2016-05-01

The contents of visual working memory (VWM) can be modulated by spatial cues presented during the maintenance interval ("retrocues"). Here, we examined whether attentional selection of representations in VWM can also be based on features. In addition, we investigated whether the mechanisms of feature-based and spatial attention in VWM differ with respect to parallel access to noncontiguous locations. In two experiments, we tested the efficacy of valid retrocues relying on different kinds of information. Specifically, participants were presented with a typical spatial retrocue pointing to two locations, a symbolic spatial retrocue (numbers mapping onto two locations), and two feature-based retrocues: a color retrocue (a blob of the same color as two of the items) and a shape retrocue (an outline of the shape of two of the items). The two cued items were presented at either contiguous or noncontiguous locations. Overall retrocueing benefits, as compared to a neutral condition, were observed for all retrocue types. Whereas feature-based retrocues yielded benefits for cued items presented at both contiguous and noncontiguous locations, spatial retrocues were only effective when the cued items had been presented at contiguous locations. These findings demonstrate that attentional selection and updating in VWM can operate on different kinds of information, allowing for a flexible and efficient use of this limited system. The observation that the representations of items presented at noncontiguous locations could only be reliably selected with feature-based retrocues suggests that feature-based and spatial attentional selection in VWM rely on different mechanisms, as has been shown for attentional orienting in the external world.

Automatic migraine classification via feature selection committee and machine learning techniques over imaging and questionnaire data.

PubMed

Garcia-Chimeno, Yolanda; Garcia-Zapirain, Begonya; Gomez-Beldarrain, Marian; Fernandez-Ruanova, Begonya; Garcia-Monco, Juan Carlos

2017-04-13

Feature selection methods are commonly used to identify subsets of relevant features to facilitate the construction of models for classification, yet little is known about how feature selection methods perform in diffusion tensor images (DTIs). In this study, feature selection and machine learning classification methods were tested for the purpose of automating diagnosis of migraines using both DTIs and questionnaire answers related to emotion and cognition - factors that influence of pain perceptions. We select 52 adult subjects for the study divided into three groups: control group (15), subjects with sporadic migraine (19) and subjects with chronic migraine and medication overuse (18). These subjects underwent magnetic resonance with diffusion tensor to see white matter pathway integrity of the regions of interest involved in pain and emotion. The tests also gather data about pathology. The DTI images and test results were then introduced into feature selection algorithms (Gradient Tree Boosting, L1-based, Random Forest and Univariate) to reduce features of the first dataset and classification algorithms (SVM (Support Vector Machine), Boosting (Adaboost) and Naive Bayes) to perform a classification of migraine group. Moreover we implement a committee method to improve the classification accuracy based on feature selection algorithms. When classifying the migraine group, the greatest improvements in accuracy were made using the proposed committee-based feature selection method. Using this approach, the accuracy of classification into three types improved from 67 to 93% when using the Naive Bayes classifier, from 90 to 95% with the support vector machine classifier, 93 to 94% in boosting. The features that were determined to be most useful for classification included are related with the pain, analgesics and left uncinate brain (connected with the pain and emotions). The proposed feature selection committee method improved the performance of migraine diagnosis classifiers compared to individual feature selection methods, producing a robust system that achieved over 90% accuracy in all classifiers. The results suggest that the proposed methods can be used to support specialists in the classification of migraines in patients undergoing magnetic resonance imaging.

Effect of feature-selective attention on neuronal responses in macaque area MT

PubMed Central

Chen, X.; Hoffmann, K.-P.; Albright, T. D.

2012-01-01

Attention influences visual processing in striate and extrastriate cortex, which has been extensively studied for spatial-, object-, and feature-based attention. Most studies exploring neural signatures of feature-based attention have trained animals to attend to an object identified by a certain feature and ignore objects/displays identified by a different feature. Little is known about the effects of feature-selective attention, where subjects attend to one stimulus feature domain (e.g., color) of an object while features from different domains (e.g., direction of motion) of the same object are ignored. To study this type of feature-selective attention in area MT in the middle temporal sulcus, we trained macaque monkeys to either attend to and report the direction of motion of a moving sine wave grating (a feature for which MT neurons display strong selectivity) or attend to and report its color (a feature for which MT neurons have very limited selectivity). We hypothesized that neurons would upregulate their firing rate during attend-direction conditions compared with attend-color conditions. We found that feature-selective attention significantly affected 22% of MT neurons. Contrary to our hypothesis, these neurons did not necessarily increase firing rate when animals attended to direction of motion but fell into one of two classes. In one class, attention to color increased the gain of stimulus-induced responses compared with attend-direction conditions. The other class displayed the opposite effects. Feature-selective activity modulations occurred earlier in neurons modulated by attention to color compared with neurons modulated by attention to motion direction. Thus feature-selective attention influences neuronal processing in macaque area MT but often exhibited a mismatch between the preferred stimulus dimension (direction of motion) and the preferred attention dimension (attention to color). PMID:22170961

Effect of feature-selective attention on neuronal responses in macaque area MT.

PubMed

Chen, X; Hoffmann, K-P; Albright, T D; Thiele, A

2012-03-01

Attention influences visual processing in striate and extrastriate cortex, which has been extensively studied for spatial-, object-, and feature-based attention. Most studies exploring neural signatures of feature-based attention have trained animals to attend to an object identified by a certain feature and ignore objects/displays identified by a different feature. Little is known about the effects of feature-selective attention, where subjects attend to one stimulus feature domain (e.g., color) of an object while features from different domains (e.g., direction of motion) of the same object are ignored. To study this type of feature-selective attention in area MT in the middle temporal sulcus, we trained macaque monkeys to either attend to and report the direction of motion of a moving sine wave grating (a feature for which MT neurons display strong selectivity) or attend to and report its color (a feature for which MT neurons have very limited selectivity). We hypothesized that neurons would upregulate their firing rate during attend-direction conditions compared with attend-color conditions. We found that feature-selective attention significantly affected 22% of MT neurons. Contrary to our hypothesis, these neurons did not necessarily increase firing rate when animals attended to direction of motion but fell into one of two classes. In one class, attention to color increased the gain of stimulus-induced responses compared with attend-direction conditions. The other class displayed the opposite effects. Feature-selective activity modulations occurred earlier in neurons modulated by attention to color compared with neurons modulated by attention to motion direction. Thus feature-selective attention influences neuronal processing in macaque area MT but often exhibited a mismatch between the preferred stimulus dimension (direction of motion) and the preferred attention dimension (attention to color).

Vertebral metastases from neuroendocrine tumours: How to avoid false positives on 68Ga-DOTA-TOC PET using CT pattern analysis?

PubMed

Gauthé, Mathieu; Testart Dardel, Nathalie; Ruiz Santiago, Fernando; Ohnona, Jessica; Nataf, Valérie; Montravers, Françoise; Talbot, Jean-Noël

2018-03-12

To develop criteria to improve discrimination between vertebral metastases from neuroendocrine tumours (NETs) and benign bone lesions on PET combined with CT using DOTA-D-Phe 1 -Tyr 3 -octreotide labelled with gallium-68 ( 68 Ga-DOTA-TOC). In 535 NET patients, 68 Ga-DOTA-TOC PET/CT examinations were reviewed retrospectively for vertebral CT lesions and/or PET foci. For each vertebral PET abnormality, appearance on CT, biological volume (BV), standardized uptake value (SUV max ) and ratios to those of reference organs were determined. All vertebral abnormalities were characterized as a metastasis, a typical vertebral haemangioma (VH) or other benign lesion. In 79 patients (14.8 %), we found 107 metastases, 34 VHs and 31 other benign lesions in the spine. The optimal cut-off values to differentiate metastases from benign lesions were BV ≥0.72 cm 3 , SUVmax ≥2, SUVmax ratio to a reference vertebra ≥2.1, to liver ≥0.28 and to spleen ≥0.14. They corresponded to lesion-based 68 Ga-DOTA-TOC PET/CT sensitivity of 87 %, 98 %, 97 %, 99 % and 94 %, and specificity of 55 %, 100 %, 90 %, 97 %, 100 %, respectively. The high sensitivity of 68 Ga-DOTA-TOC-PET/CT in detecting NET vertebral metastases was confirmed; this study showed that specificity could be improved by combining CT features and quantifying 68 Ga-DOTA-TOC uptake. • Bone metastases in neuroendocrine tumours correlate with prognosis. • Benign bone lesions may mimic metastases on 68 Ga-DOTA-TOC PET/CT imaging. • The specific polka-dot CT pattern may be missing in some vertebral haemangiomas. • Lesion atypical for haemangiomas can be better characterized by quantifying 68 Ga-DOTA-TOC uptake.

An improved wrapper-based feature selection method for machinery fault diagnosis

PubMed Central

2017-01-01

A major issue of machinery fault diagnosis using vibration signals is that it is over-reliant on personnel knowledge and experience in interpreting the signal. Thus, machine learning has been adapted for machinery fault diagnosis. The quantity and quality of the input features, however, influence the fault classification performance. Feature selection plays a vital role in selecting the most representative feature subset for the machine learning algorithm. In contrast, the trade-off relationship between capability when selecting the best feature subset and computational effort is inevitable in the wrapper-based feature selection (WFS) method. This paper proposes an improved WFS technique before integration with a support vector machine (SVM) model classifier as a complete fault diagnosis system for a rolling element bearing case study. The bearing vibration dataset made available by the Case Western Reserve University Bearing Data Centre was executed using the proposed WFS and its performance has been analysed and discussed. The results reveal that the proposed WFS secures the best feature subset with a lower computational effort by eliminating the redundancy of re-evaluation. The proposed WFS has therefore been found to be capable and efficient to carry out feature selection tasks. PMID:29261689

Structural changes during annealing of GaInAsN

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

Kurtz, Sarah; Webb, J.; Gedvilas, L.

2001-02-05

The alloy GaInAsN has great potential as a lower-band-gap material lattice matched to GaAs, but there is little understanding of what causes its poor optoelectronic properties and why these improve with annealing. This study provides information about the structural changes that occur when GaInAsN is annealed. The Fourier transform infrared spectra exhibit two primary features: a triplet at {approx}470 cm-1 (Ga--N stretch) and two or three bands at {approx}3100 cm-1 (N--H stretch). The change in the Ga--N stretch absorption can be explained if the nitrogen environment is converted from NGa{sub 4} to NInGa{sub 3} after annealing. The N--H stretch ismore » also changed after annealing, implying a second, and unrelated, structural change.« less

Resistless lithography - selective etching of silicon with gallium doping regions

NASA Astrophysics Data System (ADS)

Abdullaev, D.; Milovanov, R.; Zubov, D.

2016-12-01

This paper presents the results for used of resistless lithography with a further reactive-ion etching (RIE) in various chemistry after local (Ga+) implantation of silicon with different doping dose and different size doped regions. We describe the different etching regimes for pattern transfer of FIB implanted Ga masks in silicon. The paper studied the influence of the implantation dose on the silicon surface, the masking effect and the mask resistance to erosion at dry etching. Based on these results we conclude about the possibility of using this method to create micro-and nanoscale silicon structures.

Physico-Chemical Properties of MgGa Mixed Oxides and Reconstructed Layered Double Hydroxides and Their Performance in Aldol Condensation of Furfural and Acetone

PubMed Central

Kikhtyanin, Oleg; Čapek, Libor; Tišler, Zdeněk; Velvarská, Romana; Panasewicz, Adriana; Diblíková, Petra; Kubička, David

2018-01-01

MgGa layered double hydroxides (Mg/Ga = 2–4) were synthesized and used for the preparation of MgGa mixed oxides and reconstructed hydrotalcites. The properties of the prepared materials were examined by physico-chemical methods (XRD, TGA, NH3-TPD, CO2-TPD, SEM, and DRIFT) and tested in aldol condensation of furfural and acetone. The as-prepared phase-pure MgGa samples possessed hydrotalcite structure, and their calcination resulted in mixed oxides with MgO structure with a small admixture phase characterized by a reflection at 2θ ≈ 36.0°. The interaction of MgGa mixed oxides with pure water resulted in reconstruction of the HTC structure already after 15 s of the rehydration with maximum crystallinity achieved after 60 s. TGA-MS experiments proved a substantial decrease in carbonates in all rehydrated samples compared with their as-prepared counterparts. This allowed suggesting presence of interlayer hydroxyls in the samples. Acido-basic properties of MgGa mixed oxides determined by TPD technique did not correlate with Mg/Ga ratio which was explained by the specific distribution of Ga atoms on the external surface of the samples. CO2-TPD method was also used to evaluate the basic properties of the reconstructed MgGa samples. In these experiments, an intensive peak at T = 450°C on CO2-TPD curve was attributed to the decomposition of carbonates newly formed by CO2 interaction with interlayer carbonates rather than to CO2 desorption from basic sites. Accordingly, CO2-TPD method quantitatively characterized the interlayer hydroxyls only indirectly. Furfural conversion on reconstructed MgGa materials was much larger compared with MgGa mixed oxides confirming that Brønsted basic sites in MgGa catalysts, like MgAl catalysts, were active in the reaction. Mg/Ga ratio in mixed oxides influenced product selectivity which was explained by the difference in textural properties of the samples. In contrast, Mg/Ga ratio in reconstructed catalysts had practically no effect on the composition of reaction products suggesting that the basic sites in these catalysts acted similarly in aldol condensation of acetone with furfural. It was concluded that the properties of MgGa samples resembled in a great extent those of MgAl hydrotalcite-based materials and demonstrated their potential as catalysts for base-catalyzed reactions. PMID:29881721

Physico-Chemical Properties of MgGa Mixed Oxides and Reconstructed Layered Double Hydroxides and Their Performance in Aldol Condensation of Furfural and Acetone.

PubMed

Kikhtyanin, Oleg; Čapek, Libor; Tišler, Zdeněk; Velvarská, Romana; Panasewicz, Adriana; Diblíková, Petra; Kubička, David

2018-01-01

MgGa layered double hydroxides (Mg/Ga = 2-4) were synthesized and used for the preparation of MgGa mixed oxides and reconstructed hydrotalcites. The properties of the prepared materials were examined by physico-chemical methods (XRD, TGA, NH 3 -TPD, CO 2 -TPD, SEM, and DRIFT) and tested in aldol condensation of furfural and acetone. The as-prepared phase-pure MgGa samples possessed hydrotalcite structure, and their calcination resulted in mixed oxides with MgO structure with a small admixture phase characterized by a reflection at 2θ ≈ 36.0°. The interaction of MgGa mixed oxides with pure water resulted in reconstruction of the HTC structure already after 15 s of the rehydration with maximum crystallinity achieved after 60 s. TGA-MS experiments proved a substantial decrease in carbonates in all rehydrated samples compared with their as-prepared counterparts. This allowed suggesting presence of interlayer hydroxyls in the samples. Acido-basic properties of MgGa mixed oxides determined by TPD technique did not correlate with Mg/Ga ratio which was explained by the specific distribution of Ga atoms on the external surface of the samples. CO 2 -TPD method was also used to evaluate the basic properties of the reconstructed MgGa samples. In these experiments, an intensive peak at T = 450°C on CO 2 -TPD curve was attributed to the decomposition of carbonates newly formed by CO 2 interaction with interlayer carbonates rather than to CO 2 desorption from basic sites. Accordingly, CO 2 -TPD method quantitatively characterized the interlayer hydroxyls only indirectly. Furfural conversion on reconstructed MgGa materials was much larger compared with MgGa mixed oxides confirming that Brønsted basic sites in MgGa catalysts, like MgAl catalysts, were active in the reaction. Mg/Ga ratio in mixed oxides influenced product selectivity which was explained by the difference in textural properties of the samples. In contrast, Mg/Ga ratio in reconstructed catalysts had practically no effect on the composition of reaction products suggesting that the basic sites in these catalysts acted similarly in aldol condensation of acetone with furfural. It was concluded that the properties of MgGa samples resembled in a great extent those of MgAl hydrotalcite-based materials and demonstrated their potential as catalysts for base-catalyzed reactions.

Physico-chemical properties of MgGa mixed oxides and reconstructed layered double hydroxides and their performance in aldol condensation of furfural and acetone

NASA Astrophysics Data System (ADS)

Kikhtyanin, Oleg; Čapek, Libor; Tišler, Zdeněk; Velvarská, Romana; Panasewicz, Adriana; Diblíková, Petra; Kubička, David

2018-05-01

MgGa layered double hydroxides (Mg/Ga=2-4) were synthesized and used for the preparation of MgGa mixed oxides and reconstructed hydrotalcites. The properties of the prepared materials were examined by physico-chemical methods (XRD, TGA, NH3-TPD, CO2-TPD, SEM and DRIFT) and tested in aldol condensation of furfural and acetone. The as-prepared phase-pure MgGa samples possessed hydrotalcite structure, and their calcination resulted in mixed oxides with MgO structure with a small admixture phase characterized by a reflection at 2θ ≈ 36.0°. The interaction of MgGa mixed oxides with pure water resulted in reconstruction of the HTC structure already after 15 s of the rehydration with maximum crystallinity achieved after 60 s. TGA-MS experiments proved a substantial decrease in carbonates in all rehydrated samples compared with their as-prepared counterparts. This allowed suggesting presence of interlayer hydroxyls in the samples. Acido-basic properties of MgGa mixed oxides determined by TPD technique did not correlate with Mg/Ga ratio which was explained by the specific distribution of Ga atoms on the external surface of the samples. CO2-TPD method was also used to evaluate the basic properties of the reconstructed MgGa samples. In these experiments, an intensive peak at T=450 °C on CO2-TPD curve was attributed to the decomposition of carbonates newly formed by CO2 interaction with interlayer carbonates rather than to CO2 desorption from basic sites. Accordingly, CO2-TPD method quantitatively characterized the interlayer hydroxyls only indirectly. Furfural conversion on reconstructed MgGa materials was much larger compared with MgGa mixed oxides confirming that Brønsted basic sites in MgGa catalysts, like MgAl catalysts, were active in the reaction. Mg/Ga ratio in mixed oxides influenced product selectivity which was explained by the difference in textural properties of the samples. In contrast, Mg/Ga ratio in reconstructed catalysts had practically no effect on the composition of reaction products suggesting that the basic sites in these catalysts acted similarly in aldol condensation of acetone with furfural. It was concluded that the properties of MgGa samples resembled in a great extent those of MgAl hydrotalcite-based materials and demonstrated their potential as catalysts for base-catalyzed reactions.

Improved sparse decomposition based on a smoothed L0 norm using a Laplacian kernel to select features from fMRI data.

PubMed

Zhang, Chuncheng; Song, Sutao; Wen, Xiaotong; Yao, Li; Long, Zhiying

2015-04-30

Feature selection plays an important role in improving the classification accuracy of multivariate classification techniques in the context of fMRI-based decoding due to the "few samples and large features" nature of functional magnetic resonance imaging (fMRI) data. Recently, several sparse representation methods have been applied to the voxel selection of fMRI data. Despite the low computational efficiency of the sparse representation methods, they still displayed promise for applications that select features from fMRI data. In this study, we proposed the Laplacian smoothed L0 norm (LSL0) approach for feature selection of fMRI data. Based on the fast sparse decomposition using smoothed L0 norm (SL0) (Mohimani, 2007), the LSL0 method used the Laplacian function to approximate the L0 norm of sources. Results of the simulated and real fMRI data demonstrated the feasibility and robustness of LSL0 for the sparse source estimation and feature selection. Simulated results indicated that LSL0 produced more accurate source estimation than SL0 at high noise levels. The classification accuracy using voxels that were selected by LSL0 was higher than that by SL0 in both simulated and real fMRI experiment. Moreover, both LSL0 and SL0 showed higher classification accuracy and required less time than ICA and t-test for the fMRI decoding. LSL0 outperformed SL0 in sparse source estimation at high noise level and in feature selection. Moreover, LSL0 and SL0 showed better performance than ICA and t-test for feature selection. Copyright © 2015 Elsevier B.V. All rights reserved.

High In-content InGaN nano-pyramids: Tuning crystal homogeneity by optimized nucleation of GaN seeds

NASA Astrophysics Data System (ADS)

Bi, Zhaoxia; Gustafsson, Anders; Lenrick, Filip; Lindgren, David; Hultin, Olof; Wallenberg, L. Reine; Ohlsson, B. Jonas; Monemar, Bo; Samuelson, Lars

2018-01-01

Uniform arrays of submicron hexagonal InGaN pyramids with high morphological and material homogeneity, reaching an indium composition of 20%, are presented in this work. The pyramids were grown by selective area metal-organic vapor phase epitaxy and nucleated from small openings in a SiN mask. The growth selectivity was accurately controlled with diffusion lengths of the gallium and indium species, more than 1 μm on the SiN surface. High material homogeneity of the pyramids was achieved by inserting a precisely formed GaN pyramidal seed prior to InGaN growth, leading to the growth of well-shaped InGaN pyramids delimited by six equivalent {" separators="| 10 1 ¯ 1 } facets. Further analysis reveals a variation in the indium composition to be mediated by competing InGaN growth on two types of crystal planes, {" separators="| 10 1 ¯ 1 } and (0001). Typically, the InGaN growth on {" separators="| 10 1 ¯ 1 } planes is much slower than on the (0001) plane. The formation of the (0001) plane and the growth of InGaN on it were found to be dependent on the morphology of the GaN seeds. We propose growth of InGaN pyramids seeded by {" separators="| 10 1 ¯ 1 }-faceted GaN pyramids as a mean to avoid InGaN material grown on the otherwise formed (0001) plane, leading to a significant reduction of variations in the indium composition in the InGaN pyramids. The InGaN pyramids in this work can be used as a high-quality template for optoelectronic devices having indium-rich active layers, with a potential of reaching green, yellow, and red emissions for LEDs.

On the use of feature selection to improve the detection of sea oil spills in SAR images

NASA Astrophysics Data System (ADS)

Mera, David; Bolon-Canedo, Veronica; Cotos, J. M.; Alonso-Betanzos, Amparo

2017-03-01

Fast and effective oil spill detection systems are crucial to ensure a proper response to environmental emergencies caused by hydrocarbon pollution on the ocean's surface. Typically, these systems uncover not only oil spills, but also a high number of look-alikes. The feature extraction is a critical and computationally intensive phase where each detected dark spot is independently examined. Traditionally, detection systems use an arbitrary set of features to discriminate between oil spills and look-alikes phenomena. However, Feature Selection (FS) methods based on Machine Learning (ML) have proved to be very useful in real domains for enhancing the generalization capabilities of the classifiers, while discarding the existing irrelevant features. In this work, we present a generic and systematic approach, based on FS methods, for choosing a concise and relevant set of features to improve the oil spill detection systems. We have compared five FS methods: Correlation-based feature selection (CFS), Consistency-based filter, Information Gain, ReliefF and Recursive Feature Elimination for Support Vector Machine (SVM-RFE). They were applied on a 141-input vector composed of features from a collection of outstanding studies. Selected features were validated via a Support Vector Machine (SVM) classifier and the results were compared with previous works. Test experiments revealed that the classifier trained with the 6-input feature vector proposed by SVM-RFE achieved the best accuracy and Cohen's kappa coefficient (87.1% and 74.06% respectively). This is a smaller feature combination with similar or even better classification accuracy than previous works. The presented finding allows to speed up the feature extraction phase without reducing the classifier accuracy. Experiments also confirmed the significance of the geometrical features since 75.0% of the different features selected by the applied FS methods as well as 66.67% of the proposed 6-input feature vector belong to this category.

Non-volatile logic gates based on planar Hall effect in magnetic films with two in-plane easy axes.

PubMed

Lee, Sangyeop; Bac, Seul-Ki; Choi, Seonghoon; Lee, Hakjoon; Yoo, Taehee; Lee, Sanghoon; Liu, Xinyu; Dobrowolska, M; Furdyna, Jacek K

2017-04-25

We discuss the use of planar Hall effect (PHE) in a ferromagnetic GaMnAs film with two in-plane easy axes as a means for achieving novel logic functionalities. We show that the switching of magnetization between the easy axes in a GaMnAs film depends strongly on the magnitude of the current flowing through the film due to thermal effects that modify its magnetic anisotropy. Planar Hall resistance in a GaMnAs film with two in-plane easy axes shows well-defined maxima and minima that can serve as two binary logic states. By choosing appropriate magnitudes of the input current for the GaMnAs Hall device, magnetic logic functions can then be achieved. Specifically, non-volatile logic functionalities such as AND, OR, NAND, and NOR gates can be obtained in such a device by selecting appropriate initial conditions. These results, involving a simple PHE device, hold promise for realizing programmable logic elements in magnetic electronics.

A GA based penalty function technique for solving constrained redundancy allocation problem of series system with interval valued reliability of components

NASA Astrophysics Data System (ADS)

Gupta, R. K.; Bhunia, A. K.; Roy, D.

2009-10-01

In this paper, we have considered the problem of constrained redundancy allocation of series system with interval valued reliability of components. For maximizing the overall system reliability under limited resource constraints, the problem is formulated as an unconstrained integer programming problem with interval coefficients by penalty function technique and solved by an advanced GA for integer variables with interval fitness function, tournament selection, uniform crossover, uniform mutation and elitism. As a special case, considering the lower and upper bounds of the interval valued reliabilities of the components to be the same, the corresponding problem has been solved. The model has been illustrated with some numerical examples and the results of the series redundancy allocation problem with fixed value of reliability of the components have been compared with the existing results available in the literature. Finally, sensitivity analyses have been shown graphically to study the stability of our developed GA with respect to the different GA parameters.

Characterization of azimuthal and longitudinal modes in rolled-up InGaAs/GaAs microtubes at telecom wavelengths.

PubMed

Zhong, Qiuhang; Tian, Zhaobing; Dastjerdi, M Hadi Tavakoli; Mi, Zetian; Plant, David V

2013-08-12

We report on theoretical and experimental investigation of azimuthal and longitudinal modes in rolled-up microtubes at telecom wavelengths. These microtubes are fabricated by selectively releasing a coherently strained InGaAs/GaAs bilayer. We apply planar waveguide method and a quasi-potential model to analyze the azimuthal and longitudinal modes in the microtubes near 1550 nm. Then we demonstrate these modes in transmission spectrum by evanescent light coupling. The experimental observations agree well with the calculated results. Surface-scattering-induced mode splitting is also observed in both transmission and reflection spectra at ~1600 nm. The mode splitting is in essence the non-degeneracy of clockwise and counter-clockwise whispering-gallery modes of the microtubes. This study is significant for understanding the physics of modes in microtubes and other microcavities with three-dimensional optical confinement, as well as for potential applications such as microtube-based photonic integrated devices and sensing purposes.

Constraining the Mean Crustal Thickness on Mercury

NASA Technical Reports Server (NTRS)

Nimmo, F.

2001-01-01

The topography of Mercury is poorly known, with only limited radar and stereo coverage available. However, radar profiles reveal topographic contrasts of several kilometers over wavelengths of approximately 1000 km. The bulk of Mercury's geologic activity took place within the first 1 Ga of the planet's history), and it is therefore likely that these topographic features derive from this period. On Earth, long wavelength topographic features are supported either convectively, or through some combination of isostasy and flexure. Photographic images show no evidence for plume-like features, nor for plate tectonics; I therefore assume that neither convective support nor Pratt isostasy are operating. The composition and structure of the crust of Mercury are almost unknown. The reflectance spectrum of the surface of Mercury is similar to that of the lunar highlands, which are predominantly plagioclase. Anderson et al. used the observed center-of-mass center-of-figure offset together with an assumption of Airy isostasy to infer a crustal thickness of 100-300 km. Based on tidal despinning arguments, the early elastic thickness (T(sub e)) of the (unfractured) lithosphere was approximately equal to or less than 100 km. Thrust faults with lengths of up to 500 km and ages of about 4 Ga B.P. are known to exist on Mercury. Assuming a semicircular slip distribution and a typical thrust fault angle of 10 degrees, the likely vertical depth to the base of these faults is about 45 km. More sophisticated modelling gives similar or slightly smaller answers. The depth to the base of faulting and the elastic layer are usually similar on Earth, and both are thought to be thermally controlled. Assuming that the characteristic temperature is about 750 K, the observed fault depth implies that the heat flux at 4 Ga B.P. is unlikely to be less than 20 mW m(exp -2) for a linear temperature gradient. For an elastic thickness of 45 km, topography at 1000 km wavelength is likely to be about 60% compensated. There are thus likely to be considerable lateral variations in crustal thickness. Additional information is contained in the original extended abstract.

Band Structure Engineering and Thermoelectric Properties of Charge-Compensated Filled Skutterudites

PubMed Central

Shi, Xiaoya; Yang, Jiong; Wu, Lijun; Salvador, James R.; Zhang, Cheng; Villaire, William L.; Haddad, Daad; Yang, Jihui; Zhu, Yimei; Li, Qiang

2015-01-01

Thermoelectric properties of semiconductors are intimately related to their electronic band structure, which can be engineered via chemical doping. Dopant Ga in the cage-structured skutterudite Co4Sb12 substitutes Sb sites while occupying the void sites. Combining quantitative scanning transmission electron microscopy and first-principles calculations, we show that Ga dual-site occupancy breaks the symmetry of the Sb-Sb network, splits the deep triply-degenerate conduction bands, and drives them downward to the band edge. The charge-compensating nature of the dual occupancy Ga increases overall filling fraction limit. By imparting this unique band structure feature, and judiciously doping the materials by increasing the Yb content, we promote the Fermi level to a point where carriers are in energetic proximity to these features. Increased participation of these heavier bands in electronic transport leads to increased thermopower and effective mass. Further, the localized distortion from Ga/Sb substitution enhances the phonon scattering to reduce the thermal conductivity effectively. PMID:26456013

Band structure engineering and thermoelectric properties of charge-compensated filled skutterudites

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

Shi, Xiaoya; Yang, Jiong; Wu, Lijun

2015-10-12

Thermoelectric properties of semiconductors are intimately related to their electronic band structure, which can be engineered via chemical doping. Dopant Ga in the cage-structured skutterudite Co 4Sb 12 substitutes Sb sites while occupying the void sites. Combining quantitative scanning transmission electron microscopy and first-principles calculations, we show that Ga dual-site occupancy breaks the symmetry of the Sb-Sb network, splits the deep triply-degenerate conduction bands, and drives them downward to the band edge. The charge-compensating nature of the dual occupancy Ga increases overall filling fraction limit. By imparting this unique band structure feature, and judiciously doping the materials by increasing themore » Yb content, we promote the Fermi level to a point where carriers are in energetic proximity to these features. Increased participation of these heavier bands in electronic transport leads to increased thermopower and effective mass. Further, the localized distortion from Ga/Sb substitution enhances the phonon scattering to reduce the thermal conductivity effectively.« less

Band Structure Engineering and Thermoelectric Properties of Charge-Compensated Filled Skutterudites

NASA Astrophysics Data System (ADS)

Shi, Xiaoya; Yang, Jiong; Wu, Lijun; Salvador, James R.; Zhang, Cheng; Villaire, William L.; Haddad, Daad; Yang, Jihui; Zhu, Yimei; Li, Qiang

2015-10-01

Thermoelectric properties of semiconductors are intimately related to their electronic band structure, which can be engineered via chemical doping. Dopant Ga in the cage-structured skutterudite Co4Sb12 substitutes Sb sites while occupying the void sites. Combining quantitative scanning transmission electron microscopy and first-principles calculations, we show that Ga dual-site occupancy breaks the symmetry of the Sb-Sb network, splits the deep triply-degenerate conduction bands, and drives them downward to the band edge. The charge-compensating nature of the dual occupancy Ga increases overall filling fraction limit. By imparting this unique band structure feature, and judiciously doping the materials by increasing the Yb content, we promote the Fermi level to a point where carriers are in energetic proximity to these features. Increased participation of these heavier bands in electronic transport leads to increased thermopower and effective mass. Further, the localized distortion from Ga/Sb substitution enhances the phonon scattering to reduce the thermal conductivity effectively.

Genetic Screening of Selected Disease-Causing Mutations in Glutaryl-CoA Dehydrogenase Gene among Indian Patients with Glutaric Aciduria Type I.

PubMed

Tp, Kruthika-Vinod; Muntaj, Shaik; Devaraju, K S; Kamate, M; Vedamurthy, A B

2017-09-01

Glutaric aciduria type I (GA-I) is an organic aciduria caused by glutaryl-CoA dehydrogenase (GCDH) deficiency. There are limited studies on GA-I from India. A total of 48 Indian GA-I patients were screened for selected disease-causing mutations such as R402W, A421V, A293T, R227P, and V400M using polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP). Among these patients, 9 (18.8%) had R402W mutation, and none had A421V, A293T, R227P, or V400M mutation. One low excretor mutation (P286S) and several novel mutations (I152M, Q144P, and E414X) were also found in this study. We conclude that among selected mutations, R402W is the most common mutation found among Indian GA-I patients.

Multidisciplinary design optimization using genetic algorithms

NASA Technical Reports Server (NTRS)

Unal, Resit

1994-01-01

Multidisciplinary design optimization (MDO) is an important step in the conceptual design and evaluation of launch vehicles since it can have a significant impact on performance and life cycle cost. The objective is to search the system design space to determine values of design variables that optimize the performance characteristic subject to system constraints. Gradient-based optimization routines have been used extensively for aerospace design optimization. However, one limitation of gradient based optimizers is their need for gradient information. Therefore, design problems which include discrete variables can not be studied. Such problems are common in launch vehicle design. For example, the number of engines and material choices must be integer values or assume only a few discrete values. In this study, genetic algorithms are investigated as an approach to MDO problems involving discrete variables and discontinuous domains. Optimization by genetic algorithms (GA) uses a search procedure which is fundamentally different from those gradient based methods. Genetic algorithms seek to find good solutions in an efficient and timely manner rather than finding the best solution. GA are designed to mimic evolutionary selection. A population of candidate designs is evaluated at each iteration, and each individual's probability of reproduction (existence in the next generation) depends on its fitness value (related to the value of the objective function). Progress toward the optimum is achieved by the crossover and mutation operations. GA is attractive since it uses only objective function values in the search process, so gradient calculations are avoided. Hence, GA are able to deal with discrete variables. Studies report success in the use of GA for aircraft design optimization studies, trajectory analysis, space structure design and control systems design. In these studies reliable convergence was achieved, but the number of function evaluations was large compared with efficient gradient methods. Applicaiton of GA is underway for a cost optimization study for a launch-vehicle fuel-tank and structural design of a wing. The strengths and limitations of GA for launch vehicle design optimization is studied.

Modelling of double air-bridged structured inductor implemented by a GaAs integrated passive device manufacturing process

NASA Astrophysics Data System (ADS)

Li, Yang; Yao, Zhao; Zhang, Chun-Wei; Fu, Xiao-Qian; Li, Zhi-Ming; Li, Nian-Qiang; Wang, Cong

2017-05-01

In order to provide excellent performance and show the development of a complicated structure in a module and system, this paper presents a double air-bridge-structured symmetrical differential inductor based on integrated passive device technology. Corresponding to the proposed complicated structure, a new manufacturing process fabricated on a high-resistivity GaAs substrate is described in detail. Frequency-independent physical models are presented with lump elements and the results of skin effect-based measurements. Finally, some key features of the inductor are compared; good agreement between the measurements and modeled circuit fully verifies the validity of the proposed modeling approach. Meanwhile, we also present a comparison of different coil turns for inductor performance. The proposed work can provide a good solution for the design, fabrication, modeling, and practical application of radio-frequency modules and systems.

Structural and optical characterization of GaAs nano-crystals selectively grown on Si nano-tips by MOVPE.

PubMed

Skibitzki, Oliver; Prieto, Ivan; Kozak, Roksolana; Capellini, Giovanni; Zaumseil, Peter; Arroyo Rojas Dasilva, Yadira; Rossell, Marta D; Erni, Rolf; von Känel, Hans; Schroeder, Thomas

2017-03-01

We present the nanoheteroepitaxial growth of gallium arsenide (GaAs) on nano-patterned silicon (Si) (001) substrates fabricated using a CMOS technology compatible process. The selective growth of GaAs nano-crystals (NCs) was achieved at 570 °C by MOVPE. A detailed structure and defect characterization study of the grown nano-heterostructures was performed using scanning transmission electron microscopy, x-ray diffraction, micro-Raman, and micro-photoluminescence (μ-PL) spectroscopy. The results show single-crystalline, nearly relaxed GaAs NCs on top of slightly, by the SiO 2 -mask compressively strained Si nano-tips (NTs). Given the limited contact area, GaAs/Si nanostructures benefit from limited intermixing in contrast to planar GaAs films on Si. Even though a few growth defects (e.g. stacking faults, micro/nano-twins, etc) especially located at the GaAs/Si interface region were detected, the nanoheterostructures show intensive light emission, as investigated by μ-PL spectroscopy. Achieving well-ordered high quality GaAs NCs on Si NTs may provide opportunities for superior electronic, photonic, or photovoltaic device performances integrated on the silicon technology platform.

Near Field Scanning Optical Microscopy (NSOM) of Nano Devices

DTIC Science & Technology

2008-12-01

FEATURES OF GaN NANOWIRES Gallium Nitride (GaN) nanowires are semiconductor wires of great interest lately for its some of its unique properties. These...via chemical vapour deposition (CVD) [19] or even with gas source molecular beam epitaxy (MBE) [20] The GaN nanowires growth techniques will not be...Denlinger, and Peidong Yang, Crystallographic alignment of high-density gallium nitride nanowire arrays, Nature Materials, Issue 3 Vol 8, pg 524

Multiband tangent space mapping and feature selection for classification of EEG during motor imagery.

PubMed

Islam, Md Rabiul; Tanaka, Toshihisa; Molla, Md Khademul Islam

2018-05-08

When designing multiclass motor imagery-based brain-computer interface (MI-BCI), a so-called tangent space mapping (TSM) method utilizing the geometric structure of covariance matrices is an effective technique. This paper aims to introduce a method using TSM for finding accurate operational frequency bands related brain activities associated with MI tasks. A multichannel electroencephalogram (EEG) signal is decomposed into multiple subbands, and tangent features are then estimated on each subband. A mutual information analysis-based effective algorithm is implemented to select subbands containing features capable of improving motor imagery classification accuracy. Thus obtained features of selected subbands are combined to get feature space. A principal component analysis-based approach is employed to reduce the features dimension and then the classification is accomplished by a support vector machine (SVM). Offline analysis demonstrates the proposed multiband tangent space mapping with subband selection (MTSMS) approach outperforms state-of-the-art methods. It acheives the highest average classification accuracy for all datasets (BCI competition dataset 2a, IIIa, IIIb, and dataset JK-HH1). The increased classification accuracy of MI tasks with the proposed MTSMS approach can yield effective implementation of BCI. The mutual information-based subband selection method is implemented to tune operation frequency bands to represent actual motor imagery tasks.

Vessel Classification in Cosmo-Skymed SAR Data Using Hierarchical Feature Selection

NASA Astrophysics Data System (ADS)

Makedonas, A.; Theoharatos, C.; Tsagaris, V.; Anastasopoulos, V.; Costicoglou, S.

2015-04-01

SAR based ship detection and classification are important elements of maritime monitoring applications. Recently, high-resolution SAR data have opened new possibilities to researchers for achieving improved classification results. In this work, a hierarchical vessel classification procedure is presented based on a robust feature extraction and selection scheme that utilizes scale, shape and texture features in a hierarchical way. Initially, different types of feature extraction algorithms are implemented in order to form the utilized feature pool, able to represent the structure, material, orientation and other vessel type characteristics. A two-stage hierarchical feature selection algorithm is utilized next in order to be able to discriminate effectively civilian vessels into three distinct types, in COSMO-SkyMed SAR images: cargos, small ships and tankers. In our analysis, scale and shape features are utilized in order to discriminate smaller types of vessels present in the available SAR data, or shape specific vessels. Then, the most informative texture and intensity features are incorporated in order to be able to better distinguish the civilian types with high accuracy. A feature selection procedure that utilizes heuristic measures based on features' statistical characteristics, followed by an exhaustive research with feature sets formed by the most qualified features is carried out, in order to discriminate the most appropriate combination of features for the final classification. In our analysis, five COSMO-SkyMed SAR data with 2.2m x 2.2m resolution were used to analyse the detailed characteristics of these types of ships. A total of 111 ships with available AIS data were used in the classification process. The experimental results show that this method has good performance in ship classification, with an overall accuracy reaching 83%. Further investigation of additional features and proper feature selection is currently in progress.

Normally-off Al2O3/GaN MOSFET: Role of border traps on the device transport characteristics

NASA Astrophysics Data System (ADS)

Wang, Hongyue; Wang, Jinyan; Liu, Jingqian; He, Yandong; Wang, Maojun; Yu, Min; Wu, Wengang

2018-03-01

Based on the self-terminating gate recess technique, two different processes featuring gate-recess-first (GF) and ohmic-contact-first (OF) were proposed for E-mode Al2O3/GaN MOSFETs. Increased maximum drain current (Idmax) ∼30% (420 vs 325 mA/mm), field-effect mobility (μFEmax) ∼67% (150 vs 90 cm2/Vs) and reduced on-state resistance (Ron) ∼42% (9.7 vs 16.8 Ω·mm) were observed in the devices fabricated by GF process. Such significant performance difference of GF- and OF-devices resulted from the presence of border traps at Al2O3/GaN interface with a time constant ∼7 × 10-6 s. Experimental results indicated that: (1) the near interface border traps in Al2O3 dielectric significantly affect device channel mobility; (2) a high temperature post-deposition annealing process could effective suppress generation of border traps.

An efficient multi-resolution GA approach to dental image alignment

NASA Astrophysics Data System (ADS)

Nassar, Diaa Eldin; Ogirala, Mythili; Adjeroh, Donald; Ammar, Hany

2006-02-01

Automating the process of postmortem identification of individuals using dental records is receiving an increased attention in forensic science, especially with the large volume of victims encountered in mass disasters. Dental radiograph alignment is a key step required for automating the dental identification process. In this paper, we address the problem of dental radiograph alignment using a Multi-Resolution Genetic Algorithm (MR-GA) approach. We use location and orientation information of edge points as features; we assume that affine transformations suffice to restore geometric discrepancies between two images of a tooth, we efficiently search the 6D space of affine parameters using GA progressively across multi-resolution image versions, and we use a Hausdorff distance measure to compute the similarity between a reference tooth and a query tooth subject to a possible alignment transform. Testing results based on 52 teeth-pair images suggest that our algorithm converges to reasonable solutions in more than 85% of the test cases, with most of the error in the remaining cases due to excessive misalignments.

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.

Noise-enhanced chaos in a weakly coupled GaAs/(Al,Ga)As superlattice.

PubMed

Yin, Zhizhen; Song, Helun; Zhang, Yaohui; Ruiz-García, Miguel; Carretero, Manuel; Bonilla, Luis L; Biermann, Klaus; Grahn, Holger T

2017-01-01

Noise-enhanced chaos in a doped, weakly coupled GaAs/Al_{0.45}Ga_{0.55}As superlattice has been observed at room temperature in experiments as well as in the results of the simulation of nonlinear transport based on a discrete tunneling model. When external noise is added, both the measured and simulated current-versus-time traces contain irregularly spaced spikes for particular applied voltages, which separate a regime of periodic current oscillations from a region of no current oscillations at all. In the voltage region without current oscillations, the electric-field profile consist of a low-field domain near the emitter contact separated by a domain wall consisting of a charge accumulation layer from a high-field regime closer to the collector contact. With increasing noise amplitude, spontaneous chaotic current oscillations appear over a wider bias voltage range. For these bias voltages, the domain boundary between the two electric-field domains becomes unstable and very small current or voltage fluctuations can trigger the domain boundary to move toward the collector and induce chaotic current spikes. The experimentally observed features are qualitatively very well reproduced by the simulations. Increased noise can consequently enhance chaotic current oscillations in semiconductor superlattices.

Noise-enhanced chaos in a weakly coupled GaAs/(Al,Ga)As superlattice

NASA Astrophysics Data System (ADS)

Yin, Zhizhen; Song, Helun; Zhang, Yaohui; Ruiz-García, Miguel; Carretero, Manuel; Bonilla, Luis L.; Biermann, Klaus; Grahn, Holger T.

2017-01-01

Noise-enhanced chaos in a doped, weakly coupled GaAs /Al0.45Ga0.55As superlattice has been observed at room temperature in experiments as well as in the results of the simulation of nonlinear transport based on a discrete tunneling model. When external noise is added, both the measured and simulated current-versus-time traces contain irregularly spaced spikes for particular applied voltages, which separate a regime of periodic current oscillations from a region of no current oscillations at all. In the voltage region without current oscillations, the electric-field profile consist of a low-field domain near the emitter contact separated by a domain wall consisting of a charge accumulation layer from a high-field regime closer to the collector contact. With increasing noise amplitude, spontaneous chaotic current oscillations appear over a wider bias voltage range. For these bias voltages, the domain boundary between the two electric-field domains becomes unstable and very small current or voltage fluctuations can trigger the domain boundary to move toward the collector and induce chaotic current spikes. The experimentally observed features are qualitatively very well reproduced by the simulations. Increased noise can consequently enhance chaotic current oscillations in semiconductor superlattices.

Cold Kit for Prostate-Specific Membrane Antigen (PSMA) PET Imaging: Phase 1 Study of 68Ga-Tris(Hydroxypyridinone)-PSMA PET/CT in Patients with Prostate Cancer.

PubMed

Hofman, Michael S; Eu, Peter; Jackson, Price; Hong, Emily; Binns, David; Iravani, Amir; Murphy, Declan; Mitchell, Catherine; Siva, Shankar; Hicks, Rodney J; Young, Jennifer D; Blower, Philip J; Mullen, Gregory E

2018-04-01

68 Ga-labeled urea-based inhibitors of the prostate-specific membrane antigen (PSMA), such as 68 Ga-labeled N , N '-bis(2-hydroxybenzyl)ethylenediamine- N , N '-diacetic acid (HBED)-PSMA-11, are promising small molecules for targeting prostate cancer. A new radiopharmaceutical, 68 Ga-labeled tris(hydroxypyridinone) (THP)-PSMA, has a simplified design for single-step kit-based radiolabeling. It features the THP ligand, which forms complexes with 68 Ga 3+ rapidly at a low concentration, at room temperature, and over a wide pH range, enabling direct elution from a 68 Ge/ 68 Ga generator into a lyophilized radiopharmaceutical kit in 1 step without manipulation. The aim of this phase 1 study was to assess the safety and biodistribution of 68 Ga-THP-PSMA. Methods: Cohort A comprised 8 patients who had proven prostate cancer and were scheduled to undergo prostatectomy; they had Gleason scores of 7-10 and a mean prostate-specific antigen level of 7.8 μg/L (range, 5.4-10.6 μg/L). They underwent PET/CT after the administration of 68 Ga-THP-PSMA. All patients proceeded to prostatectomy (7 with pelvic nodal dissection). Dosimetry from multi-time-point PET imaging was performed with OLINDA/EXM. Cohort B comprised 6 patients who had positive 68 Ga-HBED-PSMA-11 PET/CT scanning results and underwent comparative 68 Ga-THP-PSMA scanning. All patients were monitored for adverse events. Results: No adverse events occurred. In cohort A, 6 of 8 patients had focal uptake in the prostate (at 2 h: average SUV max , 5.1; range, 2.4-9.2) and correlative 3+ staining of prostatectomy specimens on PSMA immunohistochemistry. The 2 68 Ga-THP-PSMA scans with negative results had only 1+/2+ staining. The mean effective dose was 2.07E-02 mSv/MBq. In cohort B, 68 Ga-THP-PSMA had lower physiologic background uptake than 68 Ga-HBED-PSMA-11 (in the parotid glands, the mean SUV max for 68 Ga-THP-PSMA was 3.6 [compared with 19.2 for 68 Ga-HBED-PSMA-11]; the respective corresponding values in the liver were 2.7 and 6.3, and those in the spleen were 2.7 and 10.5; P < 0.001 for all). In 5 of 6 patients, there was concordance in the number of metastases identified with 68 Ga-HBED-PSMA-11 and 68 Ga-THP-PSMA. Thirteen of 15 nodal abnormalities were subcentimeter. In 22 malignant lesions, the tumor-to-liver contrast with 68 Ga-THP-PSMA was similar to that with 68 Ga-HBED-PSMA (4.7 and 5.4, respectively; P = 0.15), despite a higher SUV max for 68 Ga-HBED-PSMA than for 68 Ga-THP-PSMA (30.3 and 10.7, respectively; P < 0.01). Conclusion: 68 Ga-THP-PSMA is safe and has a favorable biodistribution for clinical imaging. Observed focal uptake in the prostate was localized to PSMA-expressing malignant tissue on histopathology. Metastatic PSMA-avid foci were also visualized with 68 Ga-THP-PSMA PET. Single-step production from a Good Manufacturing Practice cold kit may enable rapid adoption. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.

Comparative investigation of InGaP/GaAs/GaAsBi and InGaP/GaAs heterojunction bipolar transistors

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

Wu, Yi-Chen; Tsai, Jung-Hui, E-mail: jhtsai@nknucc.nknu.edu.tw; Chiang, Te-Kuang

2015-10-15

In this article the characteristics of In{sub 0.49}Ga{sub 0.51}P/GaAs/GaAs{sub 0.975}Bi{sub 0.025} and In{sub 0.49}Ga{sub 0.51}P/GaAs heterojunction bipolar transistor (HBTs) are demonstrated and compared by two-dimensional simulated analysis. As compared to the traditional InGaP/GaAs HBT, the studied InGaP/GaAs/GaAsBi HBT exhibits a higher collector current, a lower base-emitter (B–E) turn-on voltage, and a relatively lower collector-emitter offset voltage of only 7 mV. Because the more electrons stored in the base is further increased in the InGaP/GaAs/GaAsBi HBT, it introduces the collector current to increase and the B–E turn-on voltage to decrease for low input power applications. However, the current gain is slightlymore » smaller than the traditional InGaP/GaAs HBT attributed to the increase of base current for the minority carriers stored in the GaAsBi base.« less

Enhanced thermoelectric transport in modulation-doped GaN/AlGaN core/shell nanowires.

PubMed

Song, Erdong; Li, Qiming; Swartzentruber, Brian; Pan, Wei; Wang, George T; Martinez, Julio A

2016-01-08

The thermoelectric properties of unintentionally n-doped core GaN/AlGaN core/shell N-face nanowires are reported. We found that the temperature dependence of the electrical conductivity is consistent with thermally activated carriers with two distinctive donor energies. The Seebeck coefficient of GaN/AlGaN nanowires is more than twice as large as that for the GaN nanowires alone. However, an outer layer of GaN deposited onto the GaN/AlGaN core/shell nanowires decreases the Seebeck coefficient at room temperature, while the temperature dependence of the electrical conductivity remains the same. We attribute these observations to the formation of an electron gas channel within the heavily-doped GaN core of the GaN/AlGaN nanowires. The room-temperature thermoelectric power factor for the GaN/AlGaN nanowires can be four times higher than the GaN nanowires. Selective doping in bandgap engineered core/shell nanowires is proposed for enhancing the thermoelectric power.

Forage and breed effects on behavior and temperament of pregnant beef heifers

USDA-ARS?s Scientific Manuscript database

Integration of behavioral observations with traditional selection schemes may lead to enhanced animal well-being and more profitable forage-based cattle production systems. Brahman-influenced (BR; n=64) and Gelbvieh x Angus (GA; n=64) heifers consumed either toxic endophyte-infected tall fescue (E+)...

Creating IRT-Based Parallel Test Forms Using the Genetic Algorithm Method

ERIC Educational Resources Information Center

Sun, Koun-Tem; Chen, Yu-Jen; Tsai, Shu-Yen; Cheng, Chien-Fen

2008-01-01

In educational measurement, the construction of parallel test forms is often a combinatorial optimization problem that involves the time-consuming selection of items to construct tests having approximately the same test information functions (TIFs) and constraints. This article proposes a novel method, genetic algorithm (GA), to construct parallel…

[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

PubMed

Zhou, Jinzhi; Tang, Xiaofang

2015-08-01

In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

Neural mechanisms of selective attention in the somatosensory system.

PubMed

Gomez-Ramirez, Manuel; Hysaj, Kristjana; Niebur, Ernst

2016-09-01

Selective attention allows organisms to extract behaviorally relevant information while ignoring distracting stimuli that compete for the limited resources of their central nervous systems. Attention is highly flexible, and it can be harnessed to select information based on sensory modality, within-modality feature(s), spatial location, object identity, and/or temporal properties. In this review, we discuss the body of work devoted to understanding mechanisms of selective attention in the somatosensory system. In particular, we describe the effects of attention on tactile behavior and corresponding neural activity in somatosensory cortex. Our focus is on neural mechanisms that select tactile stimuli based on their location on the body (somatotopic-based attention) or their sensory feature (feature-based attention). We highlight parallels between selection mechanisms in touch and other sensory systems and discuss several putative neural coding schemes employed by cortical populations to signal the behavioral relevance of sensory inputs. Specifically, we contrast the advantages and disadvantages of using a gain vs. spike-spike correlation code for representing attended sensory stimuli. We favor a neural network model of tactile attention that is composed of frontal, parietal, and subcortical areas that controls somatosensory cells encoding the relevant stimulus features to enable preferential processing throughout the somatosensory hierarchy. Our review is based on data from noninvasive electrophysiological and imaging data in humans as well as single-unit recordings in nonhuman primates. Copyright © 2016 the American Physiological Society.

Neural mechanisms of selective attention in the somatosensory system

PubMed Central

Hysaj, Kristjana; Niebur, Ernst

2016-01-01

Selective attention allows organisms to extract behaviorally relevant information while ignoring distracting stimuli that compete for the limited resources of their central nervous systems. Attention is highly flexible, and it can be harnessed to select information based on sensory modality, within-modality feature(s), spatial location, object identity, and/or temporal properties. In this review, we discuss the body of work devoted to understanding mechanisms of selective attention in the somatosensory system. In particular, we describe the effects of attention on tactile behavior and corresponding neural activity in somatosensory cortex. Our focus is on neural mechanisms that select tactile stimuli based on their location on the body (somatotopic-based attention) or their sensory feature (feature-based attention). We highlight parallels between selection mechanisms in touch and other sensory systems and discuss several putative neural coding schemes employed by cortical populations to signal the behavioral relevance of sensory inputs. Specifically, we contrast the advantages and disadvantages of using a gain vs. spike-spike correlation code for representing attended sensory stimuli. We favor a neural network model of tactile attention that is composed of frontal, parietal, and subcortical areas that controls somatosensory cells encoding the relevant stimulus features to enable preferential processing throughout the somatosensory hierarchy. Our review is based on data from noninvasive electrophysiological and imaging data in humans as well as single-unit recordings in nonhuman primates. PMID:27334956

Non-equilibrium Green's function calculation of AlGaAs-well-based and GaSb-based terahertz quantum cascade laser structures

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

Yasuda, H., E-mail: yasuda@nict.go.jp; Hosako, I.

2015-03-16

We investigate the performance of terahertz quantum cascade lasers (THz-QCLs) based on Al{sub x}Ga{sub 1−x}As/Al{sub y}Ga{sub 1−y}As and GaSb/AlGaSb material systems to realize higher-temperature operation. Calculations with the non-equilibrium Green's function method reveal that the AlGaAs-well-based THz-QCLs do not show improved performance, mainly because of alloy scattering in the ternary compound semiconductor. The GaSb-based THz-QCLs offer clear advantages over GaAs-based THz-QCLs. Weaker longitudinal optical phonon–electron interaction in GaSb produces higher peaks in the spectral functions of the lasing levels, which enables more electrons to be accumulated in the upper lasing level.

Re-Os Systematics and HSE Distribution in Tieschitz (H3.6): Two Isochrons for One Meteorite

NASA Technical Reports Server (NTRS)

Smoliar, M. I.; Horan, M. F.; Alexander, C. M. OD.; Walker, R. J.

2004-01-01

Tieschitz is an ordinary chondrite that displays some unique features. So called "white matrix" and "bleached chondrules" are found in only few chondrites, while in Tieschitz they are significant components. These phases have been the object of numerous studies, and are generally considered to be formed by secondary alteration or even redeposition. A Sm-Nd study of selected chondrules from Tieschitz yielded a surprisingly young apparent age of 2.0 Ga, which most likely reflects the time of the alteration process. This makes Tieschitz very interesting with respect to providing a record of a young alteration event.